Exploring non-cancer pain conditions in a community sample:

Transcription

Exploring non-cancer pain conditions in a community sample:
Critiquing a current conceptual model of the acute to chronic pain transition
and examining predictors of chronicity
by
Cathryne Patrice Lang
B.Psych(Hons)
A thesis submitted in fulfilment of the requirements for the degree of
Doctorate of Philosophy
School of Psychology and Counselling
Queensland University of Technology
December 2008
ii
iii
KEYWORDS
Chronic pain, acute to chronic transition, community sample, mixed-methods,
longitudinal
iv
v
ABSTRACT
This program of research examines the experience of chronic pain in a community
sample. While, it is clear that like patient samples, chronic pain in non-patient
samples is also associated with psychological distress and physical disability, the
experience of pain across the total spectrum of pain conditions (including acute and
episodic pain conditions) and during the early course of chronic pain is less clear.
Information about these aspects of the pain experience is important because effective
early intervention for chronic pain relies on identification of people who are likely to
progress to chronicity post-injury. A conceptual model of the transition from acute
to chronic pain was proposed by Gatchel (1991a). In brief, Gatchel’s model
describes three stages that individuals who have a serious pain experience move
through, each with worsening psychological dysfunction and physical disability.
The aims of this program of research were to describe the experience of pain in a
community sample in order to obtain pain-specific data on the problem of pain in
Queensland, and to explore the usefulness of Gatchel’s Model in a non-clinical
sample. Additionally, five risk factors and six protective factors were proposed as
possible extensions to Gatchel’s Model. To address these aims, a prospective
longitudinal mixed-method research design was used. Quantitative data was
collected in Phase 1 via a comprehensive postal questionnaire. Phase 2 consisted of
a follow-up questionnaire 3 months post-baseline. Phase 3 consisted of semistructured interviews with a subset of the original sample 12 months post follow-up,
which used qualitative data to provide a further in-depth examination of the
experience and process of chronic pain from respondents’ point of view. The results
indicate chronic pain is associated with high levels of anxiety and depressive
symptoms. However, the levels of disability reported by this Queensland sample
vi
were generally lower than those reported by clinical samples and consistent with
disability data reported in a New South Wales population-based study. With regard
to the second aim of this program of research, while some elements of the pain
experience of this sample were consistent with that described by Gatchel’s Model,
overall the model was not a good fit with the experience of this non-clinical sample.
The findings indicate that passive coping strategies (minimising activity),
catastrophising, self efficacy, optimism, social support, active strategies (use of
distraction) and the belief that emotions affect pain may be important to consider in
understanding the processes that underlie the transition to and continuation of
chronic pain.
vii
TABLE OF CONTENTS
KEYWORDS ............................................................................................................... iii
ABSTRACT................................................................................................................. V
TABLE OF CONTENTS ........................................................................................... vii
LIST OF TABLES ..................................................................................................... xiii
LIST OF FIGURES ....................................................................................................xvi
LIST OF ABBREVIATIONS................................................................................... xvii
STATEMENT OF ORIGINAL AUTHORSHIP ........................................................xix
ACKNOWLEDGEMENTS ........................................................................................xxi
CHAPTER 1: INTRODUCTION ............................................................................. 1
Brief Overview of the Research .................................................................................... 1
The Experience of Chronic Pain in a Community Sample .......................................... 1
The Transition from Acute to Chronic Pain ................................................................ 2
Aims of the Research ................................................................................................... 3
Research Plan ............................................................................................................... 4
Significance of the Research ......................................................................................... 4
Prevalence of Chronic Pain.......................................................................................... 5
Low Recovery Associated with Chronic Pain ............................................................. 9
High Costs of Chronic Pain ....................................................................................... 10
Disability and Distress Associated with Chronic Pain .............................................. 12
Structure of the Thesis ................................................................................................. 13
Chapter Summary ........................................................................................................ 14
CHAPTER 2: LITERATURE REVIEW ............................................................... 15
Chapter Overview ........................................................................................................ 15
Definitions and Terms ................................................................................................. 15
Preventing Chronic Pain Development and Disability ................................................ 18
The Transition from Acute to Chronic Pain ................................................................ 22
Gatchel’s Conceptual Model of Transition from Acute to Chronic Pain .................. 23
Description of the Model .................................................................................................... 23
A Critique of the Model ..................................................................................................... 28
Predictors of the Development of Disability: Risk Factors ....................................... 32
Risk Factors: Variables from Prevalence Research ............................................................ 35
Risk Factors: Variables from Longitudinal Research......................................................... 36
Protective Factors ...................................................................................................... 41
Protective Factors: Emerging Variables ............................................................................. 44
Coping Strategies. ........................................................................................................... 45
Control Appraisal and Self Efficacy. .............................................................................. 47
Beliefs about Pain............................................................................................................ 49
Positive Affect. ................................................................................................................ 50
Optimism. ........................................................................................................................ 51
viii
Social Support..................................................................................................................53
Examining the Limitations of Previous Research into Protective Factors ..........................54
Aims of the Research .................................................................................................. 56
Aim 1: The Nature of Pain in a Community Sample ................................................ 56
Aim 2: Exploring the Transition between Acute and Chronic Pain ......................... 58
Clinical Model of the Transition from Acute to Chronic Pain ...........................................58
Examine the Predictive Value of Risk Factors and Protective Factors...............................59
Chapter Summary ....................................................................................................... 60
CHAPTER 3: METHODOLOGY OF THE RESEARCH .................................. 63
Chapter Overview ....................................................................................................... 63
The Use of a Mixed-Methods Approach .................................................................... 63
Using a Mixed-Method Approach for the Research ................................................. 64
Choosing the Data Types ....................................................................................................65
Matching a Mixed-Methods Approach to Chronic Pain Research .....................................66
Optimising the Use a Mixed-Methods Approach ..................................................... 67
Description of the Study Methodology ....................................................................... 68
Design ....................................................................................................................... 68
Sample ....................................................................................................................... 69
Procedure .................................................................................................................. 71
Phase1: Baseline Study .......................................................................................................71
Phase 2: Follow-up Study ...................................................................................................71
Phase 3: Interview Study ....................................................................................................72
Ethical Clearance and Occupational Health and Safety Approval .....................................72
Measures ................................................................................................................... 73
Questionnaire: Phase 1 (baseline) .......................................................................................73
Experience of Pain and Disability ...................................................................................75
Graded Chronic Pain Scale ....................................................................................................75
Roland and Morris Disability Questionnaire .........................................................................76
Psychological Distress Variables .....................................................................................77
Center for Epidemiologic Studies Depression scale ..............................................................77
Pain Anxiety Symptoms Scale-20..........................................................................................78
Extensions to Gatchel’s Model: Risk Factor Variables ...................................................80
Fear-Avoidance Beliefs Questionnaire ..................................................................................80
Coping Strategies Questionnaire............................................................................................82
Extensions to Gatchel’s Model: Protective Factors .........................................................83
Chronic Pain Coping Inventory .............................................................................................83
Survey of Pain Attitudes ........................................................................................................84
Pain Self efficacy Questionnaire ............................................................................................85
Positive affect scale of the Affect-Balance Scale ..................................................................86
Life Orientation Test – Revised .............................................................................................87
Multidimensional Scale of Perceived Social Support ............................................................87
Questionnaire: Phase 2 (follow-up) ....................................................................................88
Semi-structured Interview: Phase 3 ....................................................................................88
Statistical Analysis .................................................................................................... 92
Questionnaire: Phase 1 (baseline) & Phase 2 (follow-up) ..................................................92
Semi-structured Interview: Phase 3 ....................................................................................93
Chapter Summary ....................................................................................................... 93
ix
CHAPTER 4: PHASE 1 – BASELINE QUESTIONNAIRES (DESCRIBING
THE COMMUNITY SAMPLE) .............................................................................. 95
Purpose of the Study .................................................................................................... 95
Brief Introduction ........................................................................................................ 95
Method ......................................................................................................................... 96
Sample ....................................................................................................................... 96
Measures .................................................................................................................... 98
Procedure ................................................................................................................... 98
Statistical Analysis ................................................................................................... 100
Internal Consistency ......................................................................................................... 100
Missing Data .................................................................................................................... 100
Results........................................................................................................................ 102
Comparisons across the Pain Samples: Demographic Data .................................... 103
Description of the Experience of Pain ..................................................................... 106
Pain Variables................................................................................................................... 106
Seeking Treatment ............................................................................................................ 110
Influence on Employment ................................................................................................ 111
Psychological Health and Disability ................................................................................ 113
Coping with and Attitudes towards Pain .......................................................................... 115
The Influence of Pain Site on Functioning .............................................................. 118
Discussion .................................................................................................................. 122
Nature of Pain in a Community Sample .................................................................. 122
Who Experiences Pain? ........................................................................................... 123
A Picture of the Pain Experience ............................................................................. 124
Strengths and Limitations of the Baseline Phase ..................................................... 127
Chapter Summary ...................................................................................................... 129
CHAPTER 5: PHASE 1 – BASELINE QUESTIONNAIRES (ASSESSING
GATCHEL’S MODEL) .......................................................................................... 131
Purpose of the Study .................................................................................................. 131
Brief Introduction ...................................................................................................... 131
Method ....................................................................................................................... 132
Sample ..................................................................................................................... 132
Measures .................................................................................................................. 133
Statistical Analysis ................................................................................................... 136
Internal Consistency ......................................................................................................... 136
Missing Data .................................................................................................................... 136
Factor Analysis with the Coping and Attitude Subscales................................................. 137
Results........................................................................................................................ 138
Correlations between Gatchel’s Variables ............................................................... 142
Assessing Differences between the Acute and Chronic Pain subgroups ................. 143
Relationships between Gatchel’s Variables and the Proposed Extension Constructs ...... 143
Predicting De-conditioning: Regression Analyses .................................................. 144
Daily Interference: RMDQ scores .................................................................................... 147
x
Global Disability: GCPS disability estimate.....................................................................149
Depression: CES-D scores ................................................................................................151
Anxiety: PASS scores .......................................................................................................152
Results of the Hierarchical Regressions combined ...........................................................156
Comparing the 3 Stages of Gatchel’s Model .......................................................... 157
Discussion ................................................................................................................. 161
Chapter Summary ..................................................................................................... 165
CHAPTER 6: PHASE 2 – FOLLOW-UP QUESTIONNAIRES ...................... 167
Purpose of the Study ................................................................................................. 167
Brief Introduction...................................................................................................... 167
Method ...................................................................................................................... 170
Sample ..................................................................................................................... 170
Measures ................................................................................................................. 172
Statistical Analysis .................................................................................................. 172
Results ....................................................................................................................... 173
Examining Gatchel’s Model ................................................................................... 173
Correlation Analyses for Gatchel’s Variables ..................................................................174
Correlations between Changes in Physical and Mental De-conditioning .........................176
Changes over Time: Repeated Measures t-Tests ..............................................................177
Predicting the Development of Chronic Pain ......................................................... 179
Predicting Chronic Pain Participants’ Pain Outcome at Follow-up ........................ 182
Resolved vs. Continued Chronic Pain ..............................................................................182
Discussion ................................................................................................................. 188
Examining Gatchel’s Model ................................................................................... 188
Pain Outcome at Follow-Up ................................................................................... 191
Predicting Chronic Pain Development..............................................................................191
Significant Predictors of Continuing Chronic Pain ..........................................................193
Chapter Summary ..................................................................................................... 194
CHAPTER 7: PHASE 3 – SEMI-STRUCTURED INTERVIEWS .................. 197
Purpose of the Study ................................................................................................. 197
Brief Introduction...................................................................................................... 197
Method ...................................................................................................................... 198
Sample ..................................................................................................................... 198
Procedure ................................................................................................................ 203
Data Coding and Analysis....................................................................................... 203
Results ....................................................................................................................... 205
The Experience of Pain ........................................................................................... 205
Descriptions of Pain ..........................................................................................................205
Doing battle. ..................................................................................................................205
New love. .......................................................................................................................206
Lighthouse. ....................................................................................................................206
Co-existence (with the gods). ........................................................................................207
Part of getting older. ......................................................................................................208
xi
Influence of Pain on Self .................................................................................................. 208
Constant pain “Pain doesn’t rule my life” ..................................................................... 208
Episodic pain “You just do what you can handle” ........................................................ 210
Resolved pain “Move along and go onto something else” ............................................ 212
Suffering with the pain “It really drives me insane” ..................................................... 212
The Influence of Pain on Others “You snap at people when you shouldn’t” ................... 213
Coping with Pain .............................................................................................................. 214
Gatchel’s Model ....................................................................................................... 216
The Disability Sequence: Pain, Inactivity, Dysfunction................................................... 216
Mental De-conditioning: Struggling to Cope ................................................................... 218
Influence of Emotion: “Emotions do play a part for me” ............................................. 219
Influence of Personal Characteristics: ‘I’m a pretty resilient person”........................... 220
Attitude: “Woe is me” ................................................................................................... 221
Exhaustion: “It still wears you out a bit” ...................................................................... 222
Evidence of Mental De-conditioning: “Is everything going to be all right” ................. 222
Summary of the Disability Sequence. ........................................................................... 223
Crossover between Mental and Physical De-conditioning: “Exercise gives you a dose of
euphoria as well” .............................................................................................................. 223
Protective Variables ................................................................................................. 223
Coping Strategies ............................................................................................................. 224
Self-talk and distraction: “Using our computer disk”. .................................................. 224
Rest and relaxation: “Pull back, relax, and just let it go for a minute”. ........................ 226
Getting help: “I try to get assistance more than anything” ............................................ 226
Exercising: “I just do my exercises and it goes away”. ................................................. 226
Optimism and Positive Affect: “Mind over matter”......................................................... 227
Self efficacy to Manage Pain: “Pain doesn’t stop me” ..................................................... 229
Beliefs about Pain and Pain Management ........................................................................ 230
“I don’t take pills or anything like that”. ....................................................................... 231
“If it gets bad, I’ll see a doctor”. ................................................................................... 232
Social Support and Solicitude Beliefs .............................................................................. 233
“Whinging and moaning”.............................................................................................. 233
“I have a fantastic partner”. ........................................................................................... 234
“Using a support group”. ............................................................................................... 234
Revisiting and Understanding the Questionnaire Data ............................................ 234
Categorising Respondents’ Pain Experience .................................................................... 234
Survey of Pain Attitude (SOPA) Items ............................................................................ 235
Discussion .................................................................................................................. 237
The Experience of Pain ............................................................................................ 237
Gatchel’s Model ....................................................................................................... 240
Interpretation of Quantitative Data Phases .............................................................. 242
Limitations of the Research ..................................................................................... 243
Chapter Summary ...................................................................................................... 244
CHAPTER 8: DISCUSSION & CONCLUSIONS .............................................. 245
Purpose and Overview of the Research ..................................................................... 245
The Experience of Pain in a Community Sample ...................................................... 246
Characteristics of the Different Pain Subgroups...................................................... 247
Influence on Healthcare Systems ............................................................................. 249
Comparison of Chronic Pain in this Community Sample with Clinical Samples ... 251
xii
An Exploration of Gatchel’s Model.......................................................................... 254
Fit between Gatchel’s Model and the Pain Experience of this Community Sample254
Exploring the Extension Variables (Risk & Protective Factors) ............................ 256
Predicting the Development of Chronic Pain ...................................................................258
Predicting the Continuation of Pain ..................................................................................258
Transposing the Extension Variables onto Gatchel’s Model ............................................259
Contribution to Theory ............................................................................................. 259
Fear-Avoidance Model ........................................................................................... 260
Attachment-Diathesis Model of Chronic Pain ........................................................ 261
Practical Applications ............................................................................................... 262
Strengths and Limitations of this Research .............................................................. 264
Future Directions ...................................................................................................... 270
Conclusion ................................................................................................................ 271
REFERENCES ........................................................................................................ 273
APPENDICES ......................................................................................................... 303
Appendix A: Comparison between Brisbane and rural respondents available for the
Phase 3 (interview) study .......................................................................................... 303
Appendix B: Baseline (Phase 1) Questionnaire ........................................................ 304
Appendix C: Comparison between pain respondents who provided pain duration
and respondents who did not provide pain duration at baseline ............................... 315
Appendix D: Participant Information Sheet ............................................................ 316
Appendix E: Examining Gatchel’s Model with Low Back Pain Respondents ........ 319
xiii
LIST OF TABLES
Table 1
Selected Non-Australian Prevalence Studies of Chronic Pain
Table 2
Examples of Average Pain Duration at Program Entry in Overseas
6
Patient Samples
21
Table 3
Probability of Postcode Selection
70
Table 4
Mapping the Risk and Protective Variables onto the Questionnaire
Measures
74
Table 5
Semi-structured Interview Questions
91
Table 6
Description of the Measures used in Phase 1 to describe the Pain
Experience of Respondents
99
Table 7
Internal Consistency for each of the Scales and Subscales
101
Table 8
Missing Data Imputed
102
Table 9
Demographic Information compared by Pain subgroups
105
Table 10
Comparison of Pain Variables between Acute, Intermittent and
Chronic Pain subgroups
107
Table 11
Treatment-seeking Variables across the Pain subgroups
111
Table 12
Number of Respondents whose Employment was Affected by
their Pain by Pain subgroup
112
Table 13
Frequency of Compensation Seeking for each Pain subgroup
112
Table 14
Average Scores for Psychological Well-being (depression; CES-D
and anxiety; PASS) Measures by Pain subgroup
114
Table 15
Graded Chronic Pain Scale Classifications by Pain subgroup
114
Table 16
The Percentage of Respondent who reported that pain interfered
with these Daily Activities (using the RMDQ)
Table 17
115
Average Endorsement of the Coping Strategies and Attitudes
contained in the CPCI, CSQ and SOPA by Pain subgroup
compared with the Published Means of a Clinical Sample
117
Table 18
Psychological Distress and Disability Data by Primary Pain Site
120
Table 19
Description of the Measures used in Phase 1 (baseline study)
134
Table 20
Internal Consistency for each of the Scales
136
Table 21
137
Table 22
Varimax Rotation of the Six Factor Solution for the CSQ, CPCI
and SOPA items
139
xiv
Table 23
Correlations between Pain Duration and Measures of Gatchel’s
key constructs
Table 24
Comparison of Gatchel’s Variables between Acute and Chronic
Pain subgroups
Table 25
155
The Final Betas for the Predictors of the Physical and Mental Deconditioning Measures
Table 31
154
Hierarchical Regression Analyses to Predict Anxiety Scores
(PASS)
Table 30
150
Hierarchical Regression Analyses to Predict Depression scores
(CES-D)
Table 29
148
Hierarchical Regression Analyses to Predict Disability using the
GCPS disability estimate
Table 28
145
Hierarchical Regression Analyses to Predict Disability using the
RMDQ
Table 27
143
Correlations between Measures of Gatchel’s key constructs and
the Extension Variables
Table 26
142
156
Analysis of Differences between the Stages identified in Gatchel’s
Transitional Model of Pain
159
Table 32
Results of the Classification Scheme
161
Table 33
Demographic Characteristics of the Phase 2 Sample
170
Table 34
Internal Consistency for each of the Scales at Phase 2
171
Table 35
172
Table 36
Demographic Characteristics of the CHRONIC sample
173
Table 37
Correlations between Pain Duration and Measures of Gatchel’s
Variables at Baseline and Follow-Up for Chronic Pain
Respondents
Table 38
Correlation Matrix for Changes Scores on Psychological and
Disability Measures for Chronic Pain Respondents
Table 39
177
Frequencies (%) of GCPS Classification Changes for Chronic
Pain Respondents
Table 41
176
Comparing Gatchel’s Variables between Baseline and Follow-up
data collection for the CHRONIC sample
Table 40
174
177
Details of the Participants who transitioned from Acute to Chronic
Pain
180
xv
Table 42
Comparison of Predictor Variables between the new Chronic Pain
Participants and Resolved Acute Participants
182
Table 43
Univariate tests of Categorical Predictor Variables
184
Table 44
Univariate tests of Continuous Predictor Variables
185
Table 45
Results of the Binary Logistic Regression Predicting Resolved vs.
Table 46
Continued Chronic Pain
186
Profile of Each of the Interviewees
199
xvi
LIST OF FIGURES
Figure 1
Gatchel’s Three-Stage Model: a conceptual model of the
transition from acute to chronic pain
25
Figure 2
Flowchart of the study sample
69
Figure 3
Mapping the measures onto Gatchel’s Model
74
Figure 4
Defining the Phase 1 pain subgroups
98
Figure 5a
Percentage of the acute pain subgroup with pain at each body
site
Figure 5b
Percentage of the intermittent pain subgroup with pain at each
body site
Figure 5c
109
109
Percentage of the chronic pain subgroup with pain at each body
site
110
Figure 6
Boxplot of depression scores by pain site
119
Figure 7
Boxplot of anxiety scores by pain site
121
Figure 8
Scatter plot of the discriminant function scores
160
Figure 9
Flowchart of questionnaires returned
170
Figure 10
Flowchart of the interview sample
197
xvii
LIST OF ABBREVIATIONS
ANOVA
Analysis of Variance
CES-D
Center for Epidemiologic Studies Depression scale
CI
Confidence Interval
CPCI
Chronic Pain Coping Inventory
CSQ
Coping Strategies Questionnaire
FABQ
Fear-Avoidance Beliefs Questionnaire
GCPS
Graded Chronic Pain Scales
IASP
International Association for the Study of Pain
LOT-R
Life Orientation Test - Revised
M
Mean
MSPSS
Multidimensional Scale of Perceived Social Support
NHMRC
National Health and Medical Research Council
NRS
Numerical Rating Scale
PASS
Pain Anxiety Symptoms Scale
PSEQ
Pain Self Efficacy Questionnaire
RMDQ
Roland and Morris Disability Questionnaire
SD
Standard Deviation
SR
Self-reported
SOPA
Survey of Pain Attitudes
xviii
xix
STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted to meet the
requirements for an award at this or any other higher education institution. To the
best of my knowledge and belief, the thesis contains no material previously
published or written by another person except where due reference is made.
Signature
Date
Sections of this research have been presented at the following conferences:
Lang, C.P., Sullivan, K.A., Yates, P.M., & Hansen, J. (2008). Assessing
Fear-Avoidance Beliefs in a community chronic pain sample. Paper presented at the
Australian Pain Society annual conference; Perth, Australia.
Lang, C.P., Sullivan, K.A., & Yates, P.M. (2007). 56% of respondents in a
Queensland sample report significant pain: Examining the nature of significant pain
in a community sample. Refereed Paper presented at the Australian Psychological
Society annual conference; Brisbane, Australia.
Lang, C.P., Sullivan, K.A., & Yates, P.M. (2007). Psychological symptoms
do not worsen over time with chronic pain: An exploration of Gatchel’s (1991)
model. Paper presented at the Australian Psychological Society annual conference;
Brisbane, Australia.
xx
xxi
ACKNOWLEDGEMENTS
I would like to acknowledge and sincerely thank my supervisors, Dr Karen Sullivan
(principal), Prof Patsy Yates and Dr Julie Hansen for the guidance and support that
they provided me during my candidature. I would also like to thank Prof Jenny
Strong and two anonymous examiners for their comments on this document.
This project would not have been completed without the support and encouragement
of my husband, Anthony, to whom I am eternally grateful. Thanks must also go to
all of my colleagues and peers at the School of Psychology & Counselling who have
paved the way for PhD research generally and acted as editors-in-chief for the
various chapters; special thanks to Judy Fleiter, Shari Walsh, (Dr) Ioni Lewis and
(Dr) Erin O’Connor.
This research was supported by a grant from the Institute of Health & Biomedical
Innovation, Queensland University of Technology.
Chapter 1: Introduction
1
CHAPTER 1:
INTRODUCTION
Brief Overview of the Research
This research has a dual focus; it describes the experience of pain in a
community sample and it explores a conceptual model of the transition from acute to
chronic pain (also known as persistent pain).
The Experience of Chronic Pain in a Community Sample
Over the last two decades much large-scale research has been conducted
examining the prevalence of chronic pain using community samples. While the
primary focus of this research has been on prevalence rates, some data on the nature
of chronic pain in non-clinical samples has been gathered. From this research, it is
clear that chronic pain in community samples is associated with psychological
distress (Breivik, Collett, Ventafridda, Cohen, & Gallacher, 2006) and disability
(Blyth et al., 2001), greater use of healthcare services (Blyth, March, Brnabic, &
Cousins, 2004), and lower quality of life (Hoffman, Meier, & Council, 2002).
However, the experience of pain across the total spectrum of pain conditions
(including acute and episodic pain conditions) and during the early course of chronic
pain is less clear. Such data may assist in healthcare planning to reduce associated
psychological distress and physical disability and improve quality of life for those
affected by long-term pain conditions. In addition, such data may increase our
clinical knowledge about the mechanisms underlying the acute to chronic pain
2
transition, which may then also inform the development of early intervention
programs and other community-based healthcare programs.
The Transition from Acute to Chronic Pain
A conceptual model of the transition from acute to chronic pain was
proposed by Gatchel (1991a). In brief, Gatchel’s model describes three stages that
individuals who have a serious pain experience move through, each with worsening
psychological dysfunction and physical disability. Disability status is consolidated
as secondary reinforcers to remaining disabled develop, for example, solicitous
responses from others or decreased domestic responsibilities. Two processes,
mental and physical de-conditioning (described further in Chapter 2), act in tandem
as an individual moves through these stages. Treatment which alleviates physical
and/ or mental de-conditioning is advised to decrease chronic pain disability.
While Gatchel’s Model is one of the few models which attempts to describe
the acute to chronic pain transition, there is little direct empirical support for its
concepts and the relationships it posits. The model was originally developed with
low back pain clinical patients. It has since been extended to other pain conditions,
although its focus on clinical patients remains. However, since chronic pain patients
are a small subset of the total chronic pain population, assessing the value of this
model in a non-clinical sample would seem worthwhile.
In addition, Gatchel’s Model does not account for people who have a
significant pain experience and develop chronic pain but report limited
psychological or physical disability. Nor can this model be used to predict who is at
risk of developing chronic pain disability. Further development of Gatchel’s model
may be informed by other research, which has used large-scale community or
3
primary care samples to identify a number of risk factors for the development of
chronic pain (Gatchel, Polatin, & Mayer, 1995; Linton & Hallden, 1997; Picavet,
Vlaeyen, & Schouten, 2002; Schultz et al., 2004; White, LeFort, Amsel, & Jeans,
1997). These include demographic variables (e.g., gender and age), pain variables
(e.g., pain intensity) and psychosocial variables (e.g., catastrophising, fear-avoidance
beliefs and a weak belief that pain will resolve). Examination of the literature also
reveals that a number of protective factors, for decreased disability later in the
chronic pain trajectory or decreased disability for other health problems, exist.
Although few of these variables have been examined in relation to the acute to
chronic pain transition, these variables may also be protective early in the pain
trajectory (see Chapter 2). Specifically, active coping strategies, specific pain
beliefs, self efficacy, positive affect, optimism and social support may be predictors
of resilience against developing chronic pain disability. This research examines the
value of these proposed risk and protective factors to predict the development of
chronic pain and disability status, and also evaluates the usefulness of incorporating
some or all of these variables into Gatchel’s Model.
Aims of the Research
This research aims to provide a comprehensive description of the nature and
experience of pain (in particular, chronic pain) in a community sample. It will also
examine how people with pain (who have not completed a clinical pain program)
cope with their pain.
This research also aims to assess the fit of Gatchel’s Model with the pain
experience of a non-clinical sample by examining the main premises of the model,
which are that mental and physical de-conditioning will increase over time and that
4
physical and mental de-conditioning processes are linked. In addition, to improve
the utility of Gatchel’s Model, possible risk and protective factors identified through
the literature will be explored as possible extensions to this model.
Research Plan
This thesis presents the results of a large-scale prospective longitudinal
project. Both quantitative and qualitative data collection methods and analysis were
utilised, which allowed the study of multiple aspects of the experience of and
transition to chronic pain (Onwuegbuzie & Johnson, 2006). The first two research
phases used a postal questionnaire sent to randomly selected households across
Queensland to collect baseline and follow-up quantitative data. The third research
phase used semi-structured interviews to obtain an in-depth look at the experience of
chronic pain and the processes that underlie its development with a smaller subset of
the original sample.
Before the methodology and results are presented, first, a closer and more
detailed examination of the significance of research in this area is provided. The
rationale for the project is then presented through a review of the previous literature
about chronic pain and by a considered account of Gatchel’s Model and how this
might be expanded (in Chapter 2).
Significance of the Research
Pain research generally has been identified as a priority funding area through
the 2001-2011 Decade of Pain Control and Research announced by the American
Congress (Turk & Okifuji, 2002). In Australia, pain research and treatment is also a
national priority as was demonstrated at a recent world congress in pain (which was
5
held in Sydney, Australia, by the International Association for the Study of Pain).
Further, pain and pain management are a national health priority recognised for
funding through the National Health and Medical Research Council’s Strategies Plan
2003-2006 (NHMRC, 2003). Some of the reasons that pain and pain management
are a national health priority are clear when examining the prevalence, effects and
long-term outcomes of chronic pain.
Prevalence of Chronic Pain
The prevalence of chronic pain in non-Australian and Australian samples is
considerable. In a review of the prevalence literature published up until 1994,
Verhaak, Kerssens, Dekker, Sorbi and Bensing (1998) report that these chronic pain
prevalence estimates ranged from 2-40% with a median estimate of 15% across 15
non-Australian population and primary healthcare studies. Since this review,
estimates of chronic pain prevalence in 23 samples are available for the United
States of America and Canada, the United Kingdom, China and many countries in
Europe. Most recently a community survey of chronic pain across 15 European
countries and Israel was conducted (Breivik et al., 2006). The prevalence estimates
for each of the countries ranged from 12% to 30% (weighted prevalence across
countries = 19%). As can be seen in Table 1, prior to the Breivik et al. study, a
number of independent prevalence studies had been conducted yielding considerable
variation in their prevalence estimates. This is likely to be related to a number of
factors, shown in Table 1, such as the type of chronic pain each study assessed (e.g.,
musculoskeletal, low back only, non-cancer), the definition of chronic pain used
(e.g., length – 3 months vs. 6 months; frequency – every day, more days than not),
Table 1
Selected Non-Australian Prevalence Studies of Chronic Pain
Reference
Tripp et al.
(2006)
Breivik et al.
(2006)
Rustøen et al.
(2004)
Eriksen et al.
(2004)
Ng et al. (2002)
1
2
Date data
collected
2004
2003
2000
1994
2000
Country
Research methods
Ontario
Canada
Telephone-administered
questionnaire; contacted 2167
households; non-random selection
of person within household
Computer-assisted telephone
interview; conducted 46,394
surveys
15
European
countries &
Israel
Norway
Denmark
Hong Kong
China
Mailed questionnaire to 4000
adults randomly selected from
national register; sent a repeat
questionnaire
6000 people (16+ yrs) randomly
selected from national register;
face-to-face interviews & SF36
questionnaire (written form)
Interviewed 1051 adults randomly
selected from the telephone
directory; adult with DOB closest
to interview date
Response
rate
49%
37%
Characteristics associated with
chronic pain
Female; unmarried; lower
income; poorer SR health; rural
residence 1
19% 2
Varied per country
N=
46,394
Pain > 6 months;
pain in last
month; pain ≥
2/wk; pain ≥ 5 (110 NRS) for last
episode
48.5%
Pain > 3mths
24.4%
Female; older individuals;
divorced or separated; less
education; receiving pension
Pain > 6 months
13.5%
Not reported
Pain > 3 months
10.8%
Female; older than 60 years
N = 1067
54%
Definition of
chronic pain
Pain persisting ≥
90 days in past 6
months
Prevalence
N = 1912
73%
N = 4083
47.7%
N = 1051
After controlling for depression, rural residence was no longer associated with chronic pain (pain grade)
Prevalence rate varied from country to country (range 12-30%)
Reference
Date data
collected
Country
Research methods
Hoffman et al.
(2002)
Not
reported
North
Dakota
USA
750 surveys sent randomly
selected residents – urban and
rural; sent 2 repeat questionnaires
Sweden
3928 mail questionnaires Selected
randomly from population register
(20-74 years); sent 1 repeat
questionnaires followed by a
shorter questionnaire
Bergman et al.
(2001, 2002)
1995
Response
rate
25%
Definition of
chronic pain
Pain ≥ 6 months
Overall 58%
(rural = 66%;
urban = 50%)
Pain > 3mths persistent or
occurs regularly
during last
12mths
31.4%
N = 188
70%
N = 2755
Prevalence
(widespread pain
= left & right side
of body and
below & above
the waist)
Elliott et al.
(1999)
1996
Grampian
Scotland
5036 patients ≥ 25yrs randomly
selected from patient lists of 29
general practices; postal
questionnaire; 2 reminders sent
Note. SR is self-reported. NRS is numerical rating scale.
78%
N = 3928
Pain > 3 months
Characteristics associated with
chronic pain
Not reported
Older age, manual work, current/
former smoker, not having
personal support, family history
of chronic pain (regional pain)
Female, older age, lower SES,
being an immigrant, living in
poor housing area, lower
education, seldom drinking
alcohol, not having personal
support, family history of chronic
pain (widespread pain)
46.5%
Older age; female; council
housing; retired or not working
8
the population studied (e.g., adults, patients) and effort expended to recruit
participants (e.g., the use of reminder letters). Regardless, these studies in
combination demonstrate the size of the problem of chronic pain, which is sizeable
and ranges from approximately 10% (Ng, Tsui, & Chan, 2002) to estimates as high
as 50% or more in some areas (Hoffman et al., 2002).
Australian studies of prevalence are impacted by similar inconsistencies in
the figures reported, which may have resulted from targeting different pain types and
the use of varying definitions of chronic pain. The only Australian population-based
study of chronic pain was conducted in New South Wales, using a population health
survey. Prevalence of chronic pain (daily pain > 3 months in the previous 6-month
period) was 20% for females and 17.1% for males aged above 16 years (Blyth et al.,
2001). There is an estimated 3.2 million people with chronic pain in Australia based
on this New South Wales data (Access Economics, 2007). Blyth et al. (2001)
conclude that chronic pain is a significant problem in both the Australian adult
population and the working-aged population, and further, that chronic pain should be
a research and intervention priority.
Other research conducted in Australia has examined specific pain types or
focused on specific populations. In terms of the most common chronic pain
complaint (Dionne, 1999), low back pain, Walker, Muller and Grant (2004) reported
a prevalence rate of 13.4% for chronic low back pain. Walker et al. used a
population-based survey sent to a random sample of Australian adults selected from
the electoral roll. They suggested that previous surveys designed as more general
health or well-being surveys (not specific to pain) have underestimated the
prevalence of chronic pain conditions through imprecise items and language (see
also Blyth et al., 2001). Given the stricter definition used in this study and its focus
9
on only one type (albeit the most common type) of pain, that is, low back pain, it is
likely that the 20% estimate for all pain conditions provided by the Blyth et al.
(2001) study may understate the problem of chronic pain in Australia.
Two other Australian studies provide some data on pain. Chen, Devine,
Dick, Dhaliwal and Prince (2003) showed that 26% of women aged over 70 years
experience lower extremity pain (i.e., pain located in the lower leg, ankle and foot
region). However, pain duration was not assessed. McClean and Higginbotham
(2002) found that 27.8% of nursing home residents in rural New South Wales able to
communicate (approx 60% of total sample) reported chronic pain. Forty-one percent
of participants with chronic pain reported that the pain was severe.
Due to the small number of Australian studies (n = 4) and frequent focus on a
single pain type, these studies are only indicative of the problem of chronic pain in
Australia. However, it is clear that, like the rest of the western world, chronic pain is
a sizeable health problem in this country. Accordingly, further research examining
the nature of significant pain in Australia is necessary.
Low Recovery Associated with Chronic Pain
While the problem of pain in terms of prevalence is substantial, the
significance of chronic pain research goes beyond prevalence rates. There is
evidence that the prognosis for people with chronic pain is poor. Annual recovery
rate estimates range from 5.4% over a 4-year period (Elliott, Smith, Hannaford,
Smith, & Chambers, 2002) through 8.7% using a 6-year follow-up period (Eriksen,
Ekholm, Sjøgren, & Rasmussen, 2004) to 15% over the longest follow-up period –
12 years (H. I. Andersson, 2004). While it is difficult to discern why estimates of
10
incidence and recovery rates for chronic pain vary from study to study3, it is clear
that recovery from chronic pain conditions is relatively rare even over long time
periods.
Consequently, if chronic pain has a high incidence rate and (in comparison) a
low recovery rate, an increase in prevalence rates can be expected. In combination
with the aging population in many western countries (Elliott et al., 2002; Gatchel,
2004) and increasing prevalence rates with age (H. I. Andersson, Ejlertsson, Leden,
& Rosenberg, 1993; Elliott et al., 2002; Elliott, Smith, Penny, Smith, & Chambers,
1999), the prevalence of chronic pain may rise dramatically. Increases in prevalence
rates are projected to result in 5 million Australians with chronic pain by the year
2050 (Access Economics, 2007).
High Costs of Chronic Pain
In addition to increasing prevalence rates and low recovery rates, chronic
pain is associated with significant costs to the community. Recently, the total annual
cost of chronic pain in Australia was estimated to be over $34 billion (Access
Economics, 2007). This equated to approximately $11,000 per Australian with
chronic pain (Access Economics, 2007).
Studies of chronic pain patients in the United States of America clearly
demonstrate that the costs and level of medical intervention requested by, and
provided to, patients with chronic pain is largely disproportionate to the ratio of
patients with pain who progress to develop chronicity in benign pain conditions (see
e.g. Gatchel, 1991b; Gatchel & Turk, 1996). Similar statistics are found in Europe
and the United Kingdom (see Maetzel & Li, 2002 for a review). In a Chinese
3
Some possible reasons for the discrepancy in the estimates include: samples from diverse countries,
differences in length of follow-up period, and differences in the manner in which the pain populations
were identified (Eriksen et al., 2004).
11
sample, three-quarters of the sample had sought medical attention for their pain, and
one-third of those participants had sought intervention from more than one source
(Ng et al., 2002) (see also Hart, Deyo, & Cherkin, 1995).
Chronic pain is associated with unemployment and a reduction in efficiency
at work (e.g., Ng et al., 2002). In terms of the costs to the Australian community,
the primary costs identified have been to employers through lost productivity and
workers’ compensation litigation. Many overseas studies have focused on absence
from work as an estimate of the cost of chronic pain on employers and the workers
compensation systems generally (e.g., Galizzi & Boden, 2003; Schultz et al., 2004).
However, this type of measure may underestimate the cost of chronic pain to the
work force. Blyth, March, Nicholas, and Cousins (2003) found that days absent
from work only account for one third of the workplace loss, with participants
reporting attending work but being less effective due to pain on three times the
number of (equivalent whole) days they were actually absent from work. These
figures are based on adults who were able to maintain employment – nearly 8% of
the New South Wales sample was not working due to health or pain reasons (Blyth
et al., 2001).
Litigation figures in this New South Wales community sample were also
significant. Nearly 9% of adults with chronic pain were involved with litigation,
primarily through the workers’ compensation system (Blyth, March, Nicholas et al.,
2003). In overseas patient samples, the figures are much higher. For example, 80%
of an American patient sample were seeking or receiving compensation for their
pain (Turk & Okifuji, 1996).
Increases in chronic pain rates (due to low recovery rates and increases in the
aging population of many western countries (Elliott et al., 2002; Gatchel, 2004) and
12
some eastern populations (see Ng et al., 2002)) means that chronic pain is likely to
become more of an economic burden. Postulating from the current cost of chronic
pain (Access Economics, 2007) suggests the annual cost of chronic pain in 2050 will
exceed 55 billion dollars.
Disability and Distress Associated with Chronic Pain
Not only are the community costs high, the experience of chronic pain is
associated with significant disability and distress for the affected individual. The
disabling effects of chronic pain reported vary across samples. Over 50% of a
Chinese chronic pain sample reported some, and 33% reported moderate to severe
interference with their daily life (Ng et al., 2002). In an Australian sample, disability
caused by pain was reported by 13.5% of women and 11% of men (Blyth et al.,
2001). Blyth et al. (2001) also noted the association of chronic pain with
psychological problems. Chronic pain has been associated with depressive
symptoms (Breivik et al., 2006) and lower quality of life (Hoffman et al., 2002).
Finally, chronic pain, particularly widespread chronic pain, may be associated with
increased mortality (H. I. Andersson, 2004).
The reasons that pain research is a national priority in Australia and other
countries are well documented. Of concern to public health professionals is the
economic cost associated with chronic pain. Of concern to health professionals is
the individual’s psychological distress and physical dysfunction. These concerns are
compounded by predictions that chronic pain prevalence rates are rising. This thesis
aims to provide information on the experience of those with chronic pain in the
community and contribute to the theoretical knowledge base used to develop
effective interventions to minimise the symptoms of chronic pain.
13
Structure of the Thesis
This thesis has eight chapters. Chapters 1-3 provide an examination of the
aims of the research, and the factors and variables under consideration. Building on
the thesis overview provided in this chapter, Chapter 2 provides some definitions to
aid in understanding the chronic pain research and provides a detailed literature
review, including what is known about how chronic pain develops and a framework
for understanding the transition from acute to chronic pain. Chapter 3 details the
methodology for the research and presents a rationale for its structure.
Chapters 4-7 present each of the studies conducted as part of this research.
In each of these chapters, the rationale, brief background and method of each study
are detailed. The results and the significance of the findings are also briefly
discussed for each of the studies. Because of the volume of results reported for the
first research phase, Phase 1 is presented in two chapters. Chapter 4 describes the
pain experience in this community sample and Chapter 5 presents an assessment of
Gatchel’s Model. Chapter 6 depicts the second research phase; a quantitative
follow-up of the Phase 1 (baseline) participants. Chapter 7 illustrates the final
research phase of the thesis. This is a qualitative examination of the factors that
people with pain believe are important during the transition to and for the
management of chronic pain.
Chapter 8 highlights the significance of this research and its overall findings;
integrating the results across the studies. This chapter also details the strengths and
limitations of this research, and offers some suggestions for future research.
14
Chapter Summary
In summary, this chapter introduced the topic of this thesis, pain in a
community setting, a contemporary research concern during the Decade for Pain
Control and Research, and highlighted the significance of this research. Prevalence
rates for chronic pain are increasing and expected to further increase in countries
with an aging population, like Australia. With these increases, the economic cost to
healthcare systems and employers is also expected to rise. The impact on
individuals is underscored by the potential for physical and psychological problems
to be associated with chronic pain. Taken together, these studies indicate that
chronic pain is a significant problem for Australian adults as well as for overseas
populations.
As can be seen in this brief overview, the nature of the problem of chronic
pain is not well understood in Australia, and in Queensland, in particular.
Population-specific data may assist in healthcare planning and service provision. In
addition, although estimates of prevalence vary with the type of pain targeted and
the definition of chronic pain used, further research into chronicity in pain
conditions is clearly warranted on the basis of these preliminary prevalence
estimates. The potential benefits gained from the prevention of chronic pain
disability are clear in terms of financial, social and personal benefits.
Chapter 2 begins with an overview of the common terms used in this
research area before discussing the prevention of chronic pain development and
associated disability. In order to prevent chronic pain, the transition from acute to
chronic pain is examined and a framework for understanding this transition, and the
possible risk and protective factors for the development of chronic pain are
reviewed.
Chapter 2: Literature Review
15
CHAPTER 2:
LITERATURE REVIEW
Chapter Overview
This chapter presents a comprehensive literature review that provides the
background for the research. Prior to presenting the literature review, some
definitions are provided. The prevention of the development of chronic pain and
associated disability is then detailed. This is followed by an examination of the
acute pain to chronic pain transition and a model of this transition period, Gatchel’s
Model of Transition from Acute to Chronic Pain. Additional factors – both risk
factors and protective factors – that may extend this model are subsequently
proposed. The research aims are presented at the conclusion of this chapter.
Definitions and Terms
The current definition of pain, provided by the International Association for
the Study of Pain (IASP), is “An unpleasant sensory and emotional experience
associated with actual or potential tissue damage , or described in terms of such
damage” (IASP, 1986, p. s217; Loeser & Treede, 2008; Merskey & Bogduk, 1994).
While the community’s perception is that pain correlates with tissue damage, the
IASP definition clearly gives weight to the affective component of pain. This aspect
is important in chronic pain because while tissue damage may or may not be evident,
the affective experience of pain can be very debilitating and illustrates one
difference between chronic and acute pain conditions.
Many different terms are used with regard to pain types and chronic pain, in
particular. Previously, the definition of chronic pain varied across clinical and
16
research literature, resulting in inconsistencies in literature in terms of the key
features of chronic pain (e.g., prevalence rates, predictors of disability; see Chapter
1). The chronic pain4 definition widely used in research in recent years is that
recommended by the IASP (1986) as pain that persists past three months after onset.
This timeframe is considered to encompass the expected healing times for most
injuries and yet provide a clear research-appropriate definition. Evidently the first
criterion for chronic pain concerns duration.
A second criterion of chronic pain relates to the pervasiveness of pain. A
chronic pain syndrome describes pain that is pervasive and constant in the
individual’s life. Frequent reoccurring pain conditions (like migraine), therefore, do
not meet the criterion of constant pain due to the intermittent nature of such pain;
such conditions will not be considered as chronic in this research. Daily headache
(persistent for greater than three months), however, would meet the criteria for
chronic pain.
Other terms include chronic benign pain, chronic regional pain, chronic
widespread pain and chronic pain syndrome. The term, chronic benign pain,
separates these pain conditions from those associated with malignant diagnoses such
as cancer and acknowledges the link between tissue damage and pain is or has
become, distant; pain cannot be accounted for by physiological injury (Verhaak et
al., 1998). Some research further separates chronic regional pain from chronic
widespread pain (e.g. Bergman, Herrstrom, Jacobsson, & Petersson, 2002). Chronic
regional pain refers to pain that occurs in one or more area of the body. Widespread
pain, on the other hand, refers to pain sites that exist in all four quadrants of the
body, that is, on both sides of the body and both above and below the waistline.
4
More recently, the term persistent pain has been used. This term is believed to reflect that pain has
persisted longer than anticipated but that it may not be a permanent condition.
17
Based on the broadness of these criteria, it can therefore be seen that the
terms, chronic pain or chronic pain syndrome may incorporate “a heterogeneous
group of different pain states with varying degrees of severity, distribution and
functional impact” (H. I. Andersson, 2004, p. 47). Chronic pain has also been
classified into subtypes based on type of injury or site of pain (IASP, 1986), such as
low back pain or rheumatoid arthritis. Often research has focused upon one distinct
pain type, possibly to reduce variability introduced due to pain type, given the range
of pain states.
Chronic pain differs from acute pain in more than these definitional
components (that is, length and pervasiveness). This is more obvious when
considering, as some authors have suggested, that there are three axes of chronic
pain – time, severity and impact (disability) (e.g., Von Korff, Dworkin, & Le
Resche, 1990). In terms of impact or disability, there are differences between acute
and chronic pain on psychological and physical dimensions. First, disability is
greater due to the longer length of pain. Second, chronic pain is associated with
greater levels of psychological distress than acute pain (Gatchel & Oordt, 2003).
Psychological distress is compounded with time. Third, while a comprehensive
discussion of the physiology of pain is beyond the scope of this thesis, it should be
noted that the underlying pathology associated with chronic pain can include
changes to physiological systems including the nervous system (H. I. Andersson,
2004). Central nervous system sensitivity (that is, increased sensitivity to pain-like
stimuli) is thought to develop and play a role in continued pain, after healing at the
original injury site has taken place.
Acute pain is pain that persists up until three months. Some authors refer to
acute (0-4 weeks) and subacute pain (5-12 weeks) (Karjalainen et al., 2001b;
18
Poiraudeau et al., 2006). As acute pain is the first stage in the chronic pain
trajectory, it is also examined in this thesis. It is estimated that 7-20% of acute low
back pain becomes chronic (G. B. J. Andersson, 1999; Klenerman et al., 1995; Reid,
Haugh, Hazard, & Tripathi, 1997). In some ways, acute pain is considered
functional as it leads the individual to desist from harmful activities (e.g., touching a
hot surface) or further damaging injured tissue (e.g., walking on a sprained ankle).
As per chronic benign pain, once pain becomes chronic the link between pain and
tissue damage is believed to become more remote.
Given the variety of terms used in the pain literature, it is easy to see how
different definitions may introduce variance into the results of research in this area.
For the purposes of this study, the term chronic pain will be used generally to refer
to pain lasting greater than 3 months, present on more days than not. Acute pain is
defined as pain that persists up until three months.
Preventing Chronic Pain Development and Disability
As was discussed in Chapter 1, chronic pain is associated with significant
financial and personal costs and has low recovery rates. Prevention of chronic
disability is best achieved by early intervention. Because disability status begins to
consolidate in the first 12 months post-injury and return to work is unlikely after this
time, intervention is required as early as the first few months after an injury (Turner,
Franklin, & Turk, 2000). Studies of early intervention programs in the acute or
subacute phases of low back pain demonstrate that early intervention can increase
the rate of return to work (Elders, van der Beek, & Burdorf, 2000; Hagen, Eriksen,
& Ursin, 2000; Indahl, Haldorsen, Holm, Reikerås, & Ursin, 1998; Indahl, Velund,
& Reikeras, 1995; Karjalainen et al., 2001b; Lindstrom et al., 1992; Patrick Loisel et
19
al., 1997; Schultz et al., 2008; Steenstra et al., 2006). The resultant reduction in
number of sick days is often associated with a cost benefit to employers and
workers’ compensations systems (Hagen, Grasdal, & Eriksen, 2003; Hlobil et al.,
2007; P. Loisel et al., 2002) although this has not always been found to be the case
(Steenstra et al., 2006) and more research is recommended (Tompa, de Oliveira,
Dolinschi, & Irvin, 2008). Most of this research has been conducted with employee
populations and samples accessed via workers’ compensation systems.
Outside of a workers’ compensation scheme, one study has examined the
cost effectiveness of early intervention for low back pain. Gatchel et al. (2003) also
demonstrated early intervention (via a traditional chronic pain program) for people
with acute low back pain who were at high risk of developing chronic pain (see
Gatchel, Polatin, & Mayer, 1995) was effective in preventing the development of
pain disability.
While the results of the above studies demonstrate early intervention can be
effective with low back pain, intensive early intervention for neck and shoulder pain
was not better than usual care (Ekberg, Björkqvist, Malm, Bjerre-Kiely, & Axelson,
1994). Neck and shoulder pain have only been examined in one study; clearly more
research into early intervention for pain at other sites is necessary.
Samples that are more likely to contain patients with heterogeneous pain
conditions are clinical samples. Unfortunately, patients at tertiary pain clinics often
do not present until after they have experienced pain for many years; see Table 2 for
some examples. The differences in average pain duration across samples and the
large standard deviations within samples suggest there is much variability between
these overseas patient samples. Regardless, it is clear that few people present to a
pain clinic in the first 12 months of pain.
20
In Brisbane, Australia, the characteristics of several patient samples
receiving treatment in a tertiary pain clinic have been reported. In two different
samples from the same clinic, the mean pain duration ranged from 8.1 years (SD not
reported; range 1-39 years) for 50 low back pain patients (Strong, Ashton, Cramond,
& Chant, 1990) to 11.1 years (SD = 11.5; range 1-52 years) for 39 chronic pain
patients (McCahon, Strong, Sharry, & Cramond, 2005). Such data suggests that
patients in Brisbane also present to tertiary treatment programs after many years of
suffering pain (although this is not always the case).
The lag time between developing chronic pain and obtaining treatment at a
pain clinic decreases the opportunity to effectively treat chronic pain. Because
clinical patients typically have had chronic pain for many years prior to entry into
the treatment program, they may be difficult to treat as their distress and associated
disability is entrenched (Gatchel et al., 2003). Ultimately this also decreases
treatment clinics’ capacity to decrease chronic pain disability.
In addition, these studies of clinical samples have not shed light on the
mechanisms of the development of chronic pain. Understanding the processes
underlying the transition from acute to chronic may provide researchers and
clinicians with knowledge that can be used to generate effective, early-intervention
for a variety of pain conditions.
Table 2
Examples of Average Pain Duration at Program Entry in Overseas Patient Samples
Study
Country/ region & population
McCracken & Eccleston (2005)
United Kingdom
– chronic pain patients
United States of America
Cleveland
– low back pain patients
Netherlands
– low back pain patients
McCracken & Eccleston (2003)
McCracken (1998)
Heinberg et al. (2004)
Turk et al. (1998)
Vlaeyen et al. (1995)
* median † mean ‡ range Ω standard deviation
Average pain
duration
87.5 months*
Average pain duration
(equivalent in Years)
7.3
Variance
12-528 months‡
32.5 months*
2.7
3-372 months‡
36 months*
3
3-372 months‡
12 years†
12
13.01 yearsΩ
2285.65 days†
6.26
3151.69 daysΩ
9.75 years (men)
10.5 years (women)†
9.75 (men)
10.5 (women)
9.6 (men)
8.7 (women)Ω
22
The Transition from Acute to Chronic Pain
To successfully treat chronic pain with early intervention, understanding the
course and development of pain is vital (H. I. Andersson, 2004; Elliott et al., 2002).
However, to date, the treatment or management of chronic pain once it is established
has been a priority in the literature. As a result, most studies of chronic pain have
focused almost exclusively on patient samples (that is, hospital or specialist pain
clinic patients) who present to such services long after the onset of pain (e.g.,
Cannella, Lobel, Glass, Lokshina, & Graham, 2007; Heinberg et al., 2004; Keeley et
al., 2008; McCracken & Eccleston, 2005, 2006).
In addition, the section of the “course” of chronic pain that has yet to be
extensively charted is that phase during the acute to chronic pain transition, that is,
the first three months of pain. Exploration of the course of chronic pain with nonpatient groups generally occurs after chronic pain has been established – focussing
primarily on changes within the chronic pain experience (e.g., changes in numbers
of sites or location of pain) and spontaneous resolution of pain (e.g., H. I.
Andersson, 2004; Bergman et al., 2002; Elliott et al., 2002). These studies show that
the long term experience of chronic pain varies; the severity of pain can change in
both directions – improvement and deterioration (see Bergman et al., 2002; Forseth,
Førre, & Gran, 1999; Macfarlane et al., 1996). However, these studies lack the
ability to map the week-to-week course of chronic pain, which may provide
information about treatment options for pain patients.
Moreover, clinical patient studies, the most common research type, do not
report correlations between how long their participants have had chronic pain and
other variables of interest that might assist health professionals to capture the typical
course of the transition to chronic pain. While this is not unexpected if this was not
23
a primary aim of the research, it means that the picture of the chronic pain trajectory
has yet to be charted.
To summarise, chronic pain disability may be prevented through early
intervention, although successful treatment has been primarily for low back pain.
Yet, the factors leading to chronic pain are not well understood. Greater
understanding of the transitional aspects in the development of chronic pain may be
able to assist in the development of more effective early intervention programs
(particularly outside of workers’ compensation schemes) and for other pain sites.
Better understanding of how people with pain cope with pain during the acute phase
may inform prevention and treatment (Koleck, Mazaux, Rascle, & BruchonSchweitzer, 2006). Clearly, greater understanding about how people behave and
cope during the acute phase is an important issue.
Gatchel’s Conceptual Model of Transition from Acute to Chronic Pain
Description of the Model
A model that was presented at the World Congress for Pain in 2005 (in
Sydney, Australia) and proposed by Gatchel (1991a; see also Gatchel, 2005)
describes the stages that an individual moves through if they develop chronic pain
disability. Gatchel (1991a, p. 281) originally offered this model as “a conceptual
model … [which] present[s] a number of testable hypotheses and important
treatment implications”. Later, Gatchel (1996) presented data to support the model,
although this research base mostly relied on indirect empirical evidence. Whether
the same mechanisms as proposed by Gatchel occur in the transition from acute to
chronic pain in non-clinical samples is unknown. Regardless, this model provides a
useful framework to examine the psychosocial mechanisms of the transition into
24
chronic pain and related disability. It may be possible to extend this model to be
more useful clinically and to guide theoretical understanding of the development of
chronic pain.
Gatchel’s (1991, see also Block, Gatchel, Deardorff, & Guyer, 2003;
Gatchel, 1996; Gatchel & Dersh, 2002) conceptual model arose from sports
medicine principles, which guide the rehabilitation of athletes (Mayer & Gatchel,
1988). Gatchel proposed that lengthy periods of inactivity increase the likelihood of
developing dysfunctional behaviour patterns, both physical and psychological.
Gatchel’s Conceptual Model of Transition from Acute to Chronic Pain
(hence referred to as Gatchel’s Model) identifies three stages that follow the onset of
pain or injury (see Figure 1 for a diagram). Patients move sequentially through these
stages. Stage 1 describes the initial acute pain stage and the emotional response to
the injury or pain onset (Gatchel, 1991a, 1996; Gatchel & Dersh, 2002; Gatchel &
Kishino, 2006). During this stage, individuals may experience anxiety and fear of
causing re-injury or increased pain, as well as the associated consequences of the
injury or pain itself on their daily lives. This stage is portrayed as an adaptive
response to minimise further harm (Gatchel, 1996).
Stage 2 occurs when pain does not resolve. This stage usually emerges after
2-4 months, the reasonable rehabilitation time for an acute injury (Gatchel, 1996;
Gatchel & Dersh, 2002; Gatchel & Kishino, 2006). Further psychological distress
develops as a result of the continued pain (Gatchel, 1991a, 1996; Gatchel & Dersh,
2002). According to Gatchel’s Model, psychological distress at this stage is
sufficient to interfere with recovery and impede intervention outcomes. Some of the
behavioural and psychological reactions that may be seen at this stage are depression
and learned helplessness, and anxiety disorders, amongst others. Gatchel (1991a)
25
This figure is not available online.
Please consult the hardcopy thesis
available from the QUT Library
Figure 1. Gatchel’s Three-Stage Model: a conceptual model of the transition from acute to
chronic pain. From Gatchel (1991a).
notes that the type of psychopathology will be influenced by current environmental
and socioeconomic factors in addition to individual premorbid psychological
characteristics. For example,
for an individual with a premorbid depressive personality who is
seriously affected economically by loss of a job due to the pain and
disability, depressive symptoms are greatly exacerbated during this
stage. Similarly, an individual who had premorbid hypochrondriacal
characteristics and who receives a great deal of secondary gain
remaining disabled, will most likely display a great deal of
somatization and symptom magnification (Gatchel, 1991a, p. 283).
Stage 3 is the final stage in the progression of chronic pain (Gatchel, 1991a;
Gatchel & Dersh, 2002) produced by unresolved or increasing psychosocial
dysfunction (Gatchel, 1996). This stage is characterised by adoption of a “sick role”
(i.e., acceptance of a life of diminished activity and social responsibilities). Often
there is reduced interest in all activities outside of those necessitated by the pain
26
condition, such as doctor’s appointments (Gatchel, 1996). Disability status is
consolidated during this stage as other reinforcers to remaining “disabled” develop,
for example, increased interaction with family members or decreased caretaker
responsibilities. While Gatchel and colleagues do not place a time period on the
development of this stage, signs of chronic disability begin to become evident
between 6-18 months after pain onset (Krause & Ragland, 1994) and, as mentioned
previously, return-to-work is unlikely after 12 months post-injury (Turner et al.,
2000).
Other authors have also described clusters of pain patients that resemble
Stage 3 patients of Gatchel’s Model. For example, Stage 3 may be likened to the
dysfunctional classification described by Turk and Rudy (1988), which was
characterised by a profile of more severe pain, greater interference in daily life,
reduced activities, greater affective distress and lower perceived ability to control
one’s life. This profile accounted for approximately 43% of their sample of 122
adults attending an outpatient pain clinic. The characteristics of Stage 3 patients are
also similar to people described as having a chronic pain syndrome (Grabois, 2002;
Von Korff et al., 1990). Symptoms associated with this syndrome include:
vegetative signs of depression; psychological distress and
demoralization; preoccupation with the pain experience; impairment of
interpersonal relationships; excessive use of healthcare and pain
medications; significant activity limitations in work, family and social
life; and adoption of a chronic sick role (Von Korff et al., 1990, p.
280).
According to Gatchel’s Model, in addition to these three stages, a cycle of
mental de-conditioning and physical de-conditioning exists. These two deconditioning syndromes are overlaid on the model’s stages. Gatchel (1991a)
27
describes mental de-conditioning as
the development of a “layer” of behavioral and psychological problems
that occur in response to the chronic pain and the patients’ attempts to
cope with it. These problems prevent the individual from maintaining
a productive lifestyle. They prompt cessation or disuse of normal
functioning, with all psychological resources being expended in an
attempt to deal with the prolonged pain and disability (Gatchel, 1991a,
p. 280).
A similar process has also been described by Price, Riley and Wade (2001).
Mental de-conditioning may be considered any psychosocial barrier to returning to
or maintaining a productive lifestyle, which occurs in response to pain. This is
consistent with the biopsychosocial approach to pain, which identifies the increasing
importance of psychosocial factors with the illness progression to remaining
disabled (Gatchel, 1991a, 1996; Gatchel & Dersh, 2002; Guzman et al., 2002;
Karjalainen et al., 2001a; Karjalainen et al., 2001b; Linton, 2000; Turk & Okifuji,
2002).
According to Gatchel’s Model, people with chronic pain develop
psychological distress as a result of exhausting their (mental) resources in failed
attempts to alleviate their pain (Gatchel, 1991a, 1996). However, it is not clear if
mental de-conditioning occurs as a result of or is the process that moves individuals
through these stages. It seems that the persistence of de-conditioning symptoms
does initiate the move from Stage 2 to Stage 3 (Gatchel, 1991a).
The physical de-conditioning cycle is when the individual, in an attempt to
prevent or alleviate pain, protects the painful area by minimising movement. This
guarding results in decreases in muscle strength, endurance and flexibility, which in
turn increase pain and effort required to complete physical tasks (Gatchel, 1996). As
28
pain increases, the individual further minimises movement and the spiral continues
(Gatchel, 1991a).
Mental and physical de-conditioning are separate processes. However, each
of these de-conditioning processes influence and interact with the other. While
physical de-conditioning is likely to occur initially, it may result in mental deconditioning (Block et al., 2003). For example, declines in mental health and self
esteem occur as patients are less able to complete physical tasks (Gatchel, 1991a).
Likewise, psychological distress may influence physical functioning (Gatchel,
1996). For example, motivation to get involved in work or recreational activities is
likely to decrease with psychological distress, and reduce the physical involvement
in these activities. Decreases in physical activities then further increases physical
de-conditioning (Gatchel, 1996). Both these types of de-conditioning may feed back
into the experience of pain intensity (Block et al., 2003; Gatchel, 1996). Much
literature supports the link between psychological distress and greater pain severity
(Crombez, Vlaeyen, Heuts, & Lysens, 1999; Turk & Okifuji, 2002). While both
physical and mental de-conditioning may be important in the transition to chronic
pain (Gatchel, 1996), the relative contribution of these factors to the development of
chronic pain has not been established.
A Critique of the Model
Intuitively Gatchel’s Model provides a clear framework for how the
components of chronic pain develop and influence each other, that is, physical and
psychosocial components, which is consistent with the biopsychosocial model of
pain. There is much support for the involvement of psychological variables in the
transition between acute and chronic pain (see Linton, 2000 for a review).
29
Many chronic pain conditions are associated with higher rates of depression,
anxiety, and substance use and personality disorders compared with both the general
population and acute pain patient groups (see Gatchel & Dersh, 2002 for a review)
(Benjamin, Morris, McBeth, Macfarlane, & Silman, 2000). There is evidence both
that chronic pain precedes depressive symptoms for some individuals (Magni,
Moreschi, Rigatti-Luchini, & Merskey, 1994) and that depressive symptoms precede
chronic pain conditions for other individuals.
Further, symptoms of psychopathology (that is, indicators of mental deconditioning) diminish with the successful treatment of chronic pain that results in a
reduction in disability (Gatchel & Dersh, 2002). Gatchel (1996) described studies of
low back patients that provide evidence for the development of psychological
problems that parallel the development of chronicity of pain. However, to the
author’s knowledge, the model itself has not been specifically evaluated with a pain
population.
Gatchel’s Model was originally developed to specifically illustrate the
transition from acute to chronic back pain (Gatchel, 1991a). However, as other
authors have commented on the similarity of concomitant psychological conditions
found across pain conditions (e.g., Turk et al., 1998), this model may be able to
describe the transition from an acute to chronic condition for a wide range of noncancer pain complaints. Further, Gatchel draws on research from other pain
conditions (e.g., temporomandibular disorders, headache) to provide support for his
model (Gatchel, 1996). Using research from other pain conditions implies that the
model is generalisable beyond the pain condition it was initially developed to
describe.
30
As the focus of Gatchel’s Model is those people who progress from acute to
chronic pain, this model does not describe the patients who experience pain but do
not progress to Stages 2 and 3. The importance of identifying the people who will
progress through de-conditioning processes and why only some people progress
through de-conditioning processes was highlighted by Gatchel himself (1991a). A
number of studies have drawn attention to the presence of pain patients who
continue to experience pain that they describe as severe, who do not have the
accompanying disability indicators such as inability to return to work, reduced
involvement in activities or significant psychological distress (Turk & Okifuji,
2002). Using Gatchel’s Model as a framework suggests that these patients (the ones
who recover) do not decondition at the rate or to the level of their more disabled
counterparts. Regardless, the model does not specify the process by which this
happens nor the types of protective factors that may be important in minimising the
risk of or level of mental de-conditioning that occurs. Nor does this model specify
variables (other than the passage of time) that may be predictive of the transition
from Stage 1 to the other stages. Conversely, the expectation, with this model, is
that when (if) the pain resolves, so too should any comorbid psychological problems
(Gatchel, 1996). In this sense, the model could be considered as describing a
passive process. However, as chronicity develops active strategies are required to
reduce pain and comorbid symptoms.
While protective factors that prevent movement through the stages are not
identified, some processes for reversing each of the de-conditioning syndromes are
provided. Gatchel proposes that physical exercises are able to restore physical
conditioning (see Block et al., 2003; Gatchel, 1991a for a fuller explanation of
physical de-conditioning and pacing physical programs). Physical reconditioning is
31
also expected to ultimately decrease pain (Block et al., 2003). To counteract the
effects of mental de-conditioning, Gatchel (1991a) suggests a return to productivity,
for example, return to work or other daily activities. While this suggestion is not
unreasonable conceptually, it has not been tested empirically nor have the
mechanisms for how a return to productivity reduce mental de-conditioning been
identified.
As mentioned earlier, the process that moves individuals through the three
stages is not clear. Gatchel (1991a, p. 283) states “if the pain persists past a
reasonable acute period, this leads to the progression into Stage 2”. Persistence of
de-conditioning leads to Stage 3. The model appears to have a reliance on time
passing to move individuals through the stages. Further, it may be difficult to
discriminate between the stages. While a time period (2-4 months) was suggested as
a marker of the transition between Stages 1 and 2 (Gatchel, 1991a), no time marker
was given for the transition between Stages 2 and 3. Although the descriptions of
each stage provide a picture of an individual at each stage, these descriptions may
not be as useful in assessing a specific pain patient to identify the stage in which
they fall and to tailor treatment accordingly. For example, a patient in Stage 3 may
require a more intensive program for them to return to meaningful activity compared
to a patient in Stage 2 of the model. Notwithstanding these difficulties, being able to
accurately identify patients in each stage may allow efficient and cost-effective
allocation of resources to obtain the best outcome for each patient.
In summary, the model proposed by Gatchel is a descriptive model of the
transition from acute pain to a problematic chronic pain experience. It does not
identify those pain patients who, despite the experience of chronic pain, do not
develop severe disability. In its current conceptualisation, it does not identify factors
32
that facilitate the transition through the stages. To extend Gatchel’s Model for
greater clinical utility, there is value in examining this model, with particular focus
on the mechanisms that both predict and may prevent or reverse the transition from
acute to chronic pain. Previous research has examined some predictors of the
development of chronic pain, once an acute injury or pain episode has occurred.
Inspection of this literature may provide insight into factors that could extend
Gatchel’s Model.
Predictors of the Development of Disability: Risk Factors
Research examining the acute to chronic pain transition has focused on
identifying predictors of the development of future disability; that is, predictors to
discriminate between individuals who are likely to continue to experience pain (and
disability) and individuals whose pain will resolve. Often the factors identified are
known as risk factors, that is, factors that put the individual at increased risk of
developing chronic pain. These types of predictors may complement Gatchel’s
Model.
Understanding these risk factors may be valuable in identifying those adults
who will develop chronic pain. This is important because of the high economic cost
of chronic pain disability as well as the burden it places on individuals (see Chapter
1). Interventions that reduce the number of people who develop chronic pain have
the potential to be very cost effective. However, since large numbers of adults
experience acute pain in a given year (Australian Bureau of Statistics, 2004) and
most will have their pain resolve without, or regardless of, the intervention provided
(Greene & Laskin, 1974), the expense of intervention for all pain cases nullifies the
potential financial benefit of early treatment. Therefore identifying adults who are
33
likely to develop chronic pain prior to its development and intervening with this
group only, would seem to be a cost-effective method of managing chronic pain.
Selectively targeting pain interventions in this way also has the potential to reduce
patient suffering and distress by preventing chronicity without burdening those
patients at low risk of chronic pain with lengthy or involved treatment.
Cost-effective intervention at the acute stage relies on identification of
individuals who are likely to develop chronic pain (Gatchel, Polatin, & Mayer, 1995;
Linton & Hallden, 1997; Turk & Okifuji, 2002; White et al., 1997). However,
identifying useful predictors of the development of chronic pain has been difficult.
Large prospective studies, either population-based or using acute pain patients, are
required to make statements regarding causal factors (e.g., White et al., 1997)5 6. In
addition, reliable data about the initial course of pain and individuals’ psychological
status prior to the current pain experience is difficult for people with long term pain
to provide (see Koleck et al., 2006).
Considering the volume of literature that has examined predictors of
chronicity, relatively few prospective longitudinal studies have been conducted
(Turk & Okifuji, 2002), perhaps due the relative difficulty and expense of this type
of research (Asghari & Nicholas, 2006). The results of the longitudinal research that
has been conducted are inconsistent. Similar to pain prevalence studies, the
evidence for most predictors varies with sample characteristics, e.g., type of pain
diagnoses such as back pain or headache, and the variety of measures (often of the
same construct) that have been used. Measures of depression are an often cited
example, where researchers have used a single item, questionnaires (newly
5
A brief examination of the evidence for psychological factors involved in the acute to chronic pain
transition provided by retrospective and/ or cross-sectional studies is provided by Koleck et al.
(2006).
6
A review of the predictors of occupational disability was provided by Crook, Milner, Schultz, &
Stringer (2002).
34
developed and standardised) or clinical interviews to measure a variety of constructs
from depressed mood to a clinical mood disorder diagnosis (Banks & Kerns, 1996;
Gatchel, 1996; Gatchel & Dersh, 2002; Sullivan, 2001). Rarely have the same
predictors been re-evaluated in subsequent studies, which would allow for the
replication of findings. As a consequence, while much research has been conducted,
relatively little of it is longitudinal, and a reliable comprehensive set of risk factors
has yet to be identified.
In addition, the outcome measure used will influence the relationships
reported. Initially, researchers used pain reduction as their outcome measure (e.g.,
Linton, Bradley, Jensen, Spangfort, & Sundell, 1989; Linton & Hallden, 1997;
Richardson & Richardson, 1999; White et al., 1997). As pain is a subjective
experience, influenced by culture, personality traits, and past experience (Osterweis,
Kleinman, & Mechanic, 1987; Turk & Okifuji, 2002), pain report may not be an
appropriately sensitive outcome measure. The second wave of research focused on
function (e.g., Crombez et al., 1999; Schultz et al., 2004), which may be a better
outcome measure as it is able to be objectively assessed and more closely reflects
what interventions aim to achieve, decreased disability (traditionally via decreased
pain). However, even function as an outcome criterion is affected by the chosen unit
of measurement. For example, impairment in activities of daily living could be
considered a gauge of more debilitating disability than non-return to work. The use
of multiple measurements of an individual’s function, for example, both impairment
in activities of daily living and impairment in social/ recreational activities provides
a more robust measure of change and allows the significance of the impairment to be
evaluated more fully than either measure alone; this is the measurement approach
that was used in this research.
35
Risk factors have been examined in two types of studies. Prevalence studies
have sometimes provided some information about the demographic factors that are
associated with increased prevalence of pain. As described earlier, longitudinal
studies of people with acute pain who develop chronic pain have been used
specifically to assess a range of demographic, pain and psychological variables
associated with the development of chronic pain.
Risk Factors: Variables from Prevalence Research
A number of demographic variables have been frequently associated with the
prevalence of chronic pain in community samples (see Table 1 in Chapter 1, page 6).
Primarily the demographic characteristics associated with greater prevalence of
chronic pain are female gender (e.g., Elliott et al., 1999; Rustøen et al., 2004; Tripp,
VanDenKerkhof, & McAlister, 2006) and older age (Elliott et al., 1999; Ng et al.,
2002; Rustøen et al., 2004) although older age is not consistently reported (e.g.,
Tripp et al., 2006). In addition, chronic pain is sometimes associated with indicators
of poverty such as living in council housing (Elliott et al., 1999) or a poor housing
area (Bergman et al., 2001), low income (Tripp et al., 2006) or receiving a pension
(Rustøen et al., 2004). Finally chronic pain prevalence has been linked to lower
education (Bergman et al., 2001; Rustøen et al., 2004) and family history of chronic
pain (Bergman et al., 2001).
Similar results are reported in Australian samples; chronic pain in the
community is associated with female gender (Blyth et al., 2001; McClean &
Higginbotham, 2002; B. F. Walker et al., 2004), older age (Blyth et al., 2001), and
lower education (Blyth et al., 2001). Chronic pain is also associated with indicators
of poverty such as an absence of private health insurance and receipt of welfare
36
payments (Blyth et al., 2001). The data reported here has largely come from one
New South Wales sample (Blyth et al., 2001). While this data are consistent with
that from overseas samples, these results need to be replicated in another Australian
sample.
Risk Factors: Variables from Longitudinal Research
While there is some clear evidence for demographic risk factors,
psychological factors have generally been found to have greater impact on the
transition from acute to chronic pain disability (Linton, 2000). This is reflected in
the results of the studies described below, which highlight some of the risk factors
that have emerged from the literature that has focused on the acute to chronic
transition. More research has been conducted examining the transition to chronic
low back pain than other pain aetiologies and a number of reviews of these
longitudinal studies are available (Pincus, Burton, Vogel, & Field, 2002; Pincus,
Vogel, Burton, Santos, & Field, 2006). Recently, a review of whiplash pain was
undertaken (Kamper, Rebbeck, Maher, McAuley, & Sterling, 2008). These results
of these reviews will be discussed here. In addition, because few longitudinal
studies have been conducted examining other pain aetiologies and little replication
has occurred, each of the studies using heterogeneous pain samples are described in
detail.
The first review of longitudinal studies examining the development of
chronic low back pain included 18 cohorts recruited via primary care clinics,
secondary care clinics (including hospital out-patients) and workplaces. Pincus et al.
(2002) conclude that the evidence for depressive symptoms being related to worse
outcome was the most consistently supported finding. This finding is consistent
37
with Gatchel’s Model, although this review does not provide support for additional
complementary risk factors.
The second review of longitudinal studies examining the development of
chronic low back pain specifically examined fear-avoidance beliefs (Pincus et al.,
2006). The authors concluded from their review of nine studies that there was little
overall evidence for the link between fear-avoidance beliefs and pain outcome in the
short or long-term, especially if considering studies that recruited participants within
3 weeks of their back pain episode. It may be that fear-avoidance beliefs have
greater influence later in the pain trajectory (Pincus et al., 2006). One study that was
not included in this review was conducted by Klenerman et al. (1995). They found
that fear-avoidance beliefs were the best predictor of whether low back pain patients
continued to have pain and disability (a combined measure) at 12 months, over and
above demographic variables and history of low back pain. Other authors have also
recognised the importance of fear-avoidance beliefs in the development of chronic
pain (Crombez et al., 1999; Fritz, George, & Delitto, 2001). The conclusions that
can be drawn about the value of fear-avoidance beliefs as a risk factor for chronic
pain are not clear.
A risk factor related to fear-avoidance beliefs is catastrophising.
Catastrophising is a cognitive variable that has been examined extensively with pain
patients with regard to treatment. It was recently identified as one of the most
important factors associated with increased pain and poor adjustment to pain (Keefe,
Rumble, Scipio, Giordano, & Perri, 2004). Catastrophising has also been examined
in a longitudinal context in relation to the development of chronic pain in a Dutch
community sample (Picavet et al., 2002). The authors of this study reported that
pain catastrophising and also kinesophobia (fear of movement/ (re)injury), in
38
separate analyses, predicted low back pain at 6-month follow-up both for
respondents with current low back pain and no back pain. In addition, in an
examination of osteopath patients consulting for acute low back pain,
catastrophising was the strongest predictor of self reported disability at 12 months,
explaining 47% of the variance (Burton, Tillotson, Main, & Hollis, 1995).
The third review of longitudinal studies focused on the development of
whiplash (Kamper et al., 2008). Again, general psychological distress (mainly
depressive symptoms) was consistently associated with poorer outcome. In addition,
acute pain intensity was consistently associated with poorer recovery.
Similar to the findings of the whiplash review, studies that have examined
predictors of chronicity using other pain samples also have found that measures of
pain intensity appear to be a consistently replicated psychosocial predictor (Sieben et
al., 2005; White et al., 1997). The other replicated risk factor in heterogeneous pain
samples is a weak belief that pain would resolve. For example, greater pain
intensity, a weaker belief that the pain would resolve and constant temporal pattern
of pain over the initial 3 weeks of pain were the significant psychosocial predictors
of continued pain at 3 months, compared to those whose pain resolved, for 371 acute
pain patients hospitalised for heterogeneous medical complaints (White et al., 1997).
Older age, trauma diagnosis, longer periods of hospitalisation, and absence of
surgery were the significant demographic and medical variables predictive of the
continued pain at 3 months. These factors together accounted for 21% of the
variance in predicting pain chronicity. However, gender was not a significant
predictor in this sample. A study by Sieben et al. (2005), of general practice patients
presenting with low back pain of less than 3 weeks duration, also found that older
39
age, greater baseline pain, greater number of previous episodes, and a lower level of
education were significant predictors of chronicity.
Linton and Halldén (1997), using less than 4 months absent from work in the
previous year as the cut-off for an acute pain complaint, targeted 142 consecutive
primary healthcare patients. For their sample, the significant psychosocial predictors
of continued pain at 6 months included higher average pain in the past 3 months,
more frequent pain episodes, greater number of pain sites, greater stress and
depression experienced, greater belief that pain would become persistent, belief that
they had a lower perceived chance of working in 6 months, and greater belief that
pain increases with physical activity than those patients who did not have continued
pain. Similarly, when examining self-reported function, all of the previous
predictors for continued pain, plus longer duration of the pain problem and female
gender were the significant predictors of impaired ability to complete activities of
daily living.
Schultz et al. (2004) examined 159 workers who had sustained a low back
injury, recruited through a workers’ compensation board. They found that low
expectations of recovery and low scores on the SF-36 Health Transition scale
(perception of a change in health status) were the main predictors of non-return to
work at 3 months post-initial examination. Low Skill Discretion scores (from The
Job Content Questionnaire; Karasek et al., 1998) also predicted non-return to work,
although this relationship was weaker than the psychosocial predictors.
Demographic predictors were not reported. While this study is a more recent
longitudinal study that has highlighted some possible risk factors, the
representativeness of the sample is uncertain due to the low response rate (28% of
those workers eligible for participation).
40
Outcomes measured at different time periods may also affect the usefulness
of predictors. For example, Gatchel, Polatin and Kinney (1995) demonstrated that in
a sample of acute lumbar pain patients (N = 324) presenting at a pain clinic, 11%
were not working due to back injury at 6 months. Greater pain severity and higher
scores on the Hysteria scale of the Minnesota Multiphasic Personality Inventory
(MMPI) predicted disability. At 12-month follow-up, Gatchel, Polatin and Mayer
(1995) reported that for the original sample plus additional participants (N = 421),
pain severity, gender, presence of an insurance case (i.e., workers’ compensation,
personal injury) and the Hysteria scale scores of the MMPI predicted non-return to
work for the 7% of this sample who were not working.
In summary, the published longitudinal research into the chronic pain
transition indicates that there are inconsistencies in the variables studied (both
predictor and outcome) and the way that these variables have been operationalised.
Not surprisingly, there are inconsistencies in the results of the research, with little
replicated support obtained for any particular variable, with the exception of
depression/ psychological distress, acute pain intensity, beliefs about the likelihood
of recovery from pain, and catastrophising. There is some evidence for fearavoidance beliefs. The evidence for gender is mixed; although there is more
evidence for the predictive value of gender for function at longer term follow-up,
with greater proportions of females developing disability (Gatchel, Polatin, &
Mayer, 1995). Older age as a risk factor was supported in some of the studies (e.g.,
Sieben et al., 2005). Clearly further research is needed to clarify the role of acute
pain severity, beliefs about the likelihood of recovery from pain, catastrophising,
fear-avoidance beliefs, gender and age as predictors of chronic pain.
41
The results from the longitudinal studies described above have all come from
overseas studies – from Canada, the USA and Sweden. Longitudinal research into
risk factors for chronic pain in Australia has not been reported. In addition, while
many of the studies detailed above utilised acceptable sample sizes, the nature of the
recruitment of samples has resulted in studies with limited generalisability that are
based on subgroups of pain sufferers; an approach that has potentially minimised
important predictors. The use of a broader sample to improve the generalisability of
research findings is required. A longitudinal population-based study will minimise
the problem of subgroups and allow for the study of pain that is induced by a range
of aetiologies.
Finally, these studies have examined only risk factors. There has been
inadequate attention devoted to the assessment of possible protective factors. Such
factors might also contribute to an expansion or refinement of Gatchel’s Model by
explaining why some people progress through the model as predicted and others do
not. An examination of this literature, drawn predominantly from the broader
context of health psychology, would seem important. Possible protective factors
will be examined next.
Protective Factors
Consistent with the illness focus of early mainstream psychology and
medicine, the traditional approach in chronic pain research has been to examine and
explore risk factors (reviewed in the previous section). An alternative approach,
more recently adopted in developmental and health psychology, is to examine
protective factors (for e.g., see Bonanno, 2004). In the context of chronic pain
development, protective factors are those factors that discriminate people with acute
42
pain whose pain is more likely to resolve or who have greater likelihood of not
developing psychological distress symptoms. To think of it another way, what are
the variables that predict psychological wellness despite pain?
The examination of protective factors is an approach that is common in the
areas of child trauma and bereavement (e.g., Bonanno, 2004; Bonanno, Papa, &
O'Neill, 2001), sometimes referred to as resilience. Protective factors are more than
simply inverted risk factors. The action of protective variables may vary and have
effect in multiple and non-additive ways. For example, in the areas of bereavement
and trauma exposure, positive emotion and laughter are associated with resilience
via two means. The expression of positive emotion and laughter may both reduce
the amount of expressed negative emotion as well as counteracting the effects of
distress associated with negative emotion (Bonanno, 2004).
When examining the development of chronic pain, there may be several
advantages to concentrating on protective factors and resilience7. Most importantly,
the study of protective factors may increase our understanding of the process by
which people develop chronic pain and guide the refinement of Gatchel’s Model.
As stated by Bonanno (2004),
… dysfunction cannot be fully understood without a deeper
understanding of health and resilience. By viewing resilient functioning
through the same empirical lens as chronic forms of dysfunction and
more time-limited recovery patterns, researchers will be able to
examine and contrast each of these patterns (p. 26-27).
Additionally, protective factors may provide a classification system with
greater specificity than risk factors by identifying which people with pain are not at
7
The central components of resilience are displaying psychological wellness in the face of and after
significant adversity (Cowan, Cowan, & Schultz, 1996; Rutter, 1999) and demonstrating flexibility to
adapt to stressors (Lepore & Revenson, 2006), which may be applicable to chronic pain (see also
Strand et al., 2006).
43
risk of chronic pain. Alternately, rather than replacing the role of risk factors in
identification for early intervention, protective factors may complement identified
risk factors to provide a more accurate combined method for classifying people at
risk of chronic pain. Moreover, if key variables in preventing the development of
chronic pain disability can be identified, these factors may also be important in
treating disability or managing relapse for those already with chronic pain.
Protective mechanisms are likely to provide an emphasis on personal resources that
will fit with current treatment programs that encourage self-management.
Consequently, protective variables may be able to be manipulated or targeted in such
interventions. To more fully understand the protective factors involved with the
recovery from pain is, therefore, one of the aims of the current study.
Despite acknowledgement of the value of protective factors in other areas of
psychology and the advantages of identifying and treating people with chronic pain,
a resilience approach has not been trialled with adults who may develop chronic pain
or as a method to further understand the process of the development of chronic pain.
In contrast, what has been examined more fully by pain researchers is the prediction
of adjustment to chronic pain after it is an established phenomenon. The term,
adjustment, has generally been used to describe an individual who is coping with or
managing the chronic pain experience better than their counterparts (Jensen, Turner,
Romano, & Karoly, 1991; McCracken & Eccleston, 2003; Morley, Davies, &
Barton, 2005). Two common outcomes through which an individual could
demonstrate adjustment include psychological well-being (e.g., measures of
depressive symptoms, anxiety or fear-avoidance beliefs) and physical functioning or
disability (e.g., activity levels, objective measures of physical capacity such as
lifting or grip strength) (Jensen & Karoly, 1991). Some authors (McCracken, 1998;
44
Turner, Jensen, Warms, & Cardenas, 2002) have used indices of pain (e.g., intensity,
severity or duration) as another index of adjustment. Therefore the adjusted chronic
pain patient is one that reports at least one of the following indices – less
psychological distress, greater functioning despite pain, or less pain – than their
counterparts. Adjustment may be the end result of resilience that is displayed by a
person experiencing chronic pain.
More recently, there has been a shift in the focus of pain research to
investigate the concept of resilience with people with an established pain condition.
To date, this focus shift has mainly been in the area of widespread pain conditions
like rheumatoid arthritis (for example, see Strand et al., 2007; Strand et al., 2006) so
the inclusion of protective variables in a study of musculoskeletal pain is likely to be
an important advance.
Protective Factors: Emerging Variables
The variables selected for this research were chosen from the chronic pain
adjustment or health psychology literature because they may also have a protective
role during the development of chronic pain. The variables chosen for this study
were also assessed as having the potential to prevent the development of physical
and/or mental de-conditioning as described in Gatchel’s Model. Some variables are
likely to act against both physical and mental de-conditioning, e.g., active coping
strategies, self efficacy and social support. Others (e.g., positive affect and
optimism) would be expected to influence mental de-conditioning to a greater
degree. The protective factors selected for inclusion in this research were coping
strategies, control appraisal and self efficacy, pain beliefs, positive affect, optimism,
45
and social support. The empirical evidence from which these variables were drawn
is reviewed next.
Coping Strategies.
Recently, coping strategies have been used to predict disability and
continued pain in acute patients (e.g., Koleck et al., 2006). However, the use of
coping strategies has been more often examined in an attempt to predict adjustment
to chronic pain (for a review, see Jensen et al., 1991). Generally findings support
the use of active coping strategies (i.e., those that require the patient to be active in
managing pain) as related to better adjustment. Conversely, passive strategies (e.g.,
hoping, praying, resting) are associated with worse adjustment. For example, lower
depressive symptoms and greater life satisfaction is predicted by the use of coping
strategies of ignoring pain, using coping self-talk, and increasing activities (Jensen
& Karoly, 1991). In another sample, lower depression and lower anxiety were
associated with lower avoidant coping (a similar construct to passive coping; e.g.,
resting) (McCracken, Eccleston, & Bell, 2005). In a Spanish sample of chronic pain
patients, active coping strategies (but not passive strategies) influenced functional
disability whereas passive coping strategies (but not active coping strategies) were
related to pain intensity and depressed mood (Lopez-Martinez, Esteve-Zarazaga, &
Ramirez-Maestre, 2008).
Some research has found that pain severity may effect how coping strategies
influence disability. For example, Jensen and Karoly (1991) found that higher
physical functioning (measured as difficulty in completing activities of daily living
and the frequency in which one engaged in activities within and outside the home)
46
was predicted by ignoring pain, diverting attention from pain and using coping selftalk for patients with low or medium pain severity only.
In contrast, in a 6-month longitudinal study, Revenson and Felton (1989)
found that coping efforts (including information seeking, considering the positive
aspects of the illness experience, emotional expression, wish-fulfilling fantasy, threat
minimization and self-blame) at baseline were unrelated to an increase, decrease or
no change in physical limitations for 45 rheumatoid arthritis patients. The small
number of participants and the short study period in addition to the heterogeneous
nature of the sample (see below) may have resulted in a lack of power to be able to
distinguish differences. An alternate explanation is that since the patients varied
considerably on time since rheumatoid arthritis diagnosis (M = 6 years; SD = 8;
almost one third had been diagnosed only in the previous 12 months), the differences
within the sample’s placement on a disease time line may have masked differences
in coping. This possibility highlights the need to examine these variables at a
specified time period. Gatchel’s Model, which divides the continuum of pain into
stages, will be a useful framework with which to examine the interaction of time
with coping on chronic pain disability. A third possible explanation is that, while
the use of coping strategies is related to current functioning, it is not predictive of
future functioning. The present study will enable these explanations to be tested.
The previous studies of pain coping and adjustment did not assess the factors
that discriminate people who are protected from the development of chronic pain.
One published study has examined coping ability in the transitional process from
acute to chronic pain. Koleck et al. (2006) followed 90 general practice patients
who presented with acute low back pain for 12 months. Using the Coping Strategies
Questionnaire, the praying and distraction scales (in combination with an irrational
47
beliefs scale) were related to low function (a factor score based on measures of
functional limitations and involvement with medical care). The other scales of the
Coping Strategies Questionnaire – catastrophising, reinterpreting, and ignoring –
when combined with other measures were not related to the development of
functional or emotional non-coping. This study offers some support for praying and
distraction subscales, in particular, although further exploration of the influence of
specific coping strategies on clearly defined outcome measures during the
development of chronic pain is necessary. The current research will provide this
data.
Control Appraisal and Self Efficacy.
As has been alluded to, cognition (or cognitive strategies) is an important
factor in adjustment to chronic pain. Self efficacy is an individual’s belief that they
are able to act and their expectation of how easy or difficult action will be (Bandura,
1977). These expectations of success affect whether the person attempts continued
activity (e.g., paid employment) or to actively manage pain (e.g., through relaxation
techniques), as well as the level and duration of effort exerted towards achieving
these goals (Ajzen, 1991; Bandura, 1977, 1982). Self efficacy has been likened to
control appraisal, which are the “beliefs that one has the ability and resources to
manage pain” (Jensen & Karoly, 1991, p. 431). Like coping strategies, a number of
researchers have examined the commonly positive relationship between self efficacy
and psychological functioning (Jensen & Karoly, 1991; see also Jensen et al., 1991).
Self efficacy has been found to be predictive of depression, pain severity,
daily interference and general activity in outpatients with chronic pain (Anderson,
Dowds, Pelletz, Thomas, & Peeters-Asdourian, 1995). In a community sample of
48
adults with osteoarthritis, along with other factors, self efficacy was predictive of
objective measures of physical functioning at 3 years (Sharma et al., 2003).
In Jensen and Karoly’s (1991) study of multidisciplinary pain program
inpatients, the relationship between the control appraisal and functioning was more
complex. There was a significant interaction between control appraisal and pain
severity, where those respondents who had high control appraisal and low or
medium levels of pain had higher activity levels than the other groups (i.e., low
control appraisals or high pain severity) (see also Jensen et al., 1991). Similarly, self
efficacy was a significant partial mediator of the relationship between pain intensity
and disability in a cross-sectional study of pain clinic patients (Arnstein, Caudill,
Mandle, Norris, & Beasley, 1999). In Arnstein et al.’s study, self efficacy also
partially mediated the relationship between pain intensity and depression.
As can be seen, self efficacy and control appraisal beliefs have been
examined previously in both longitudinal and cross-sectional research, and found to
be significantly related with physical and psychological functioning. However, most
cross-sectional research has relied on clinical pain samples (e.g., Arnstein et al.,
1999), while the longitudinal research presented was specific to one type of pain
(e.g., Sharma et al., 2003). The contribution of self efficacy across types of pain
conditions and the influence of self efficacy during the acute to chronic transition
have not been explored. Given the broad influence that self efficacy has
demonstrated on both physical and psychological variables (e.g., Anderson et al.,
1995), it may have a protective role in slowing or halting the progression to chronic
pain as per Gatchel’s Model. Further, as Gatchel (1996) suggests, motivation
(which may include an element of self efficacy) may mediate the relationship
between mental and physical de-conditioning, this variable is important to examine.
49
Beliefs about Pain.
Personal beliefs about health have been documented as having an important
effect on an individual’s health behaviour and engagement with healthcare systems
(Janz & Becker, 1984; Rosenstock, 1974). For chronic pain patients, some specific
beliefs have been identified as risk factors (e.g., fear-avoidance beliefs). There is
also some evidence that certain beliefs may be protective.
Pain beliefs have been associated with psychological functioning, activity
levels and use of medical resources (also described by Jensen & Karoly, 1991;
Jensen & Karoly, 1992). In terms of psychological function, patients who endorsed
that they did not believe themselves to be disabled had lower depressive symptoms
and greater life satisfaction. For patients who reported low pain severity only, low
solicitude beliefs8 were also related to better psychological functioning. Low
disability beliefs9 were correlated with high activity levels, only for patients with
low or medium pain severity. None of the other beliefs (appropriateness of
medication, medical cure, solicitude, or links between emotion and discomfort) were
significant predictors of activity levels (Jensen & Karoly, 1992). Jensen and
Karoly’s study provides preliminary support for the positive contribution of the
following beliefs: strong belief that one is not disabled, weak belief that significant
others should provide care, and strong belief that there is a medical cure for one’s
pain, in a sample of patients of a multidisciplinary pain program. The influence of
these beliefs for non-clinical samples or during the development of chronic pain has
not been explored. The proposed study will explore the above beliefs using the
same measure as Jensen and Karoly (1992) in a community pain sample to assess
their predictive value.
8
9
Belief that significant others should provide care and comfort
Belief that one is disabled by pain
50
Positive Affect.
Positive affect is another variable of recent interest in health psychology (see
Pressman & Cohen, 2005 for a review). It is proposed to be related to coping
generally and to the use of specific coping strategies. Positive affect is a positive
emotion believed to promote an attitude of readiness or willingness to try new
activities (see Strand et al., 2007) and is an important “factor in the process of
resilience following adverse events” (Strand et al., 2006, p. 478). High positive
affect in a person with significant pain may encourage them to try new coping
strategies to manage their pain. There is some evidence that positive affect also
increases physical health via an immune response (Pressman & Cohen, 2005;
Salovey, Detweiler, Steward, & Rothman, 2000), lower levels of stress hormones
(Pressman & Cohen, 2005) as well as decreased perception of pain through gateway
type mechanisms (Strand et al., 2007).
Positive affect has been investigated with several samples of people with
widespread pain (Strand et al., 2007; Strand et al., 2006; Zautra, Johnson, & Davis,
2005). Zautra et al.’s (2005) study showed that for women with osteoarthritis or
fibromyalgia syndrome, higher average positive affect (over 12 weeks) was related
to less pain increases from week to week. Greater average positive affect was also
associated with fewer increases in negative affect during weeks of more severe pain
or greater stress. The results of Zautra et al.’s study suggested that it is presence of
positive affect, rather than simply the absence of negative affect that promotes a less
severe pain experience and combats the influence of negative affect. Similar results
have also been reported with samples of rheumatoid arthritis patients (Strand et al.,
2007; Strand et al., 2006). Positive affect reduced pain intensity over eight weeks
51
(Strand et al., 2006). In addition, high positive affect disrupted the relationship
between pain and negative emotion.
Further, while Revenson and Felton (1989), mentioned previously, reported
positive affect was not directly related to disability, positive affect was related to
pain coping efforts. This may provide another or an alternate method by which
positive affect has a positive affect on managing pain.
Positive affect appears to be related to pain severity and pain coping and may
be valuable to explore as individuals move from acute to chronic pain, and in
relation to Gatchel’s mental de-conditioning concept. Of particular interest is
whether positive affect is predictive of functioning also, and remains predictive of
pain severity over periods of greater than one week.
Optimism.
Optimism is another protective factor from the health psychology literature
(Scheier & Carver, 1992). While there is some controversy about the nature of this
concept and the factors that discriminate it from other psychological concepts, such
as self efficacy, there is robust research that links optimism with physical health and
psychological outcomes (Scheier & Carver, 1992). However, less research has been
conducted with people with chronic pain specifically, including clinical groups.
Optimism can be broadly defined as the emotional response that overlays the
expectation of a socially desirable or advantageous future (Peterson, 2000; Peterson
& Seligman, 2004). Optimism incorporates what is often referred to as hope (the
belief that goals can be achieved and that pathways to achieve these goals exist or
are viable), dispositional optimism (a general view that good things will happen) and
optimism as an explanatory style (i.e., the attributions that individuals give to both
52
positive and negative events) (Peterson, 2000). Optimism has also been related to
individuals’ ability to plan and focus on the future and active problem-solving skills
(Peterson & Seligman, 2004).
Optimism has been linked to greater engagement with preventative health
behaviour (such as smoking cessation, seeking early intervention for medical
conditions), less overt illness behaviour (e.g., days of bed rest), and fewer
occurrences of acute and chronic illnesses (Seeman & Seeman, 1983). Optimism
has also been related to better psychological outcomes (Scheier & Carver, 1992), for
example, greater levels of optimism are negatively associated with postnatal
depression, are positively associated with quality of life post heart surgery
(Fitzgerald, Tennen, Affleck, & Pransky, 1993), and are negatively associated with
distress among women with early stage breast cancer (Wimberly, Carver, & Antoni,
2008).
Some authors have suggested that the strength of optimism has been
underestimated through the practice of controlling for optimism with other
demographic or contextual variables when examining coping (Novy, Nelson, Hetzel,
Squitieri, & Kennington, 1998). Novy et al. (1998) found that optimism interacts
with coping style or strategies to explain a greater proportion of the variance in
individuals’ ability to manage pain. This suggests that optimism may have at least a
partial mediating influence on the use of coping strategies in how well pain is
managed.
While the evidence for the influence of optimism on the development of
chronic pain is not available, optimism has been related to the use of coping
strategies in one clinical sample. Further, evidence for the influence of optimism in
recovery from other health problems and for the prevention of acute and chronic
53
health problems exists. The method by which optimism has its effect, possibly
through individuals’ ability to plan and focus on the future and use of active
problem-solving skills, may prevent mental de-conditioning through a future focus
and distraction from current challenges, and this possibility is explored in this
research.
Social Support.
The availability of social support has been examined in relation to
adjustment in people with pain – both in clinical and non-clinical samples. The
perception of greater social support has been found to be protective against
developing more severe pain (defined as a greater number of pain sites on the body)
three years later (Bergman et al., 2002). In terms of adjustment to chronic pain,
perceived social support makes an independent contribution to explaining the
variance in depressed mood and pain intensity (Lopez-Martinez et al., 2008). In this
study of chronic pain patients, higher social support was associated with lower pain
intensity, which in turn was related to less disability. Although there was no direct
relationship between perceived social support and functional disability, social
support may indirectly decrease disability.
Social support perceptions may also have a protective role during the
development of chronic pain. For recently-diagnosed rheumatoid arthritis patients a
larger social network was related to greater mobility one year later (Evers,
Kraaimaat, Geenen, & Bijlsma, 1998). In the same sample, higher levels of
perceived support at baseline predicted lower functional disability (two self-report
measures and grip strength test) and lower pain severity at three- and five-year
follow-up (Evers, Kraaimaat, Geenen, Jacobs, & Bijlsma, 2003). This study showed
54
that how well people manage their pain in the early stages of disease (participants
were recruited within one year of diagnosis) is associated with their pain and
functioning up to five years later.
In another sample, higher levels of social support at baseline was an
identified protective factor for self-reported physical functioning at three years for
individuals diagnosed with osteoarthritis of the knee (Sharma et al., 2003). The
evidence for perceived social support seems to be strongest and consistent across
different pain groups (community pain sample, knee osteoarthritis and rheumatoid
arthritis sufferers) compared to the other possible protective variables presented
here, for which the evidence is mixed or limited. Further, in the ageing literature,
social support is linked to increased activity levels also (Duke, Leventhal, Brownlee,
& Leventhal, 2002), which prevent or slow physical dysfunction. This suggests that
social support may be a valuable contribution to an extension of Gatchel’s Model
and may act to mediate the speed of physical de-conditioning as described by his
model.
Examining the Limitations of Previous Research into Protective Factors
The studies of protective variables that have been reviewed are limited by a
number of aspects. Most use cross-sectional designs (e.g., Jensen & Karoly, 1991;
McCracken et al., 2005; Strong et al., 1990). Conclusions about the relationships
between predictors and adjustment are therefore difficult to make, because the
direction of the relationship cannot be established and the influence of other factors
(e.g., a third variable) cannot be ruled out. Separating out the relationship between
pain, disability and psychological well-being has become a “chicken-and-egg”
dilemma. These variables are described as influencing each other; however, the
55
logic of the direction of influence is circular, and changes with the focus of the
research reported. Longitudinal rather than cross-sectional research designs are
needed to explore directional and possible causal relations between protective
factors and pain.
Additionally, the use of clinical samples, who are presumably not coping
with chronic pain adequately since they are seeking treatment, to examine
relationships between coping-like variables and adjustment may limit
generalisability. The narrow focus on clinical samples has resulted in overall little
evidence that the results of treatment-seeking patient will generalize to untreated
pain sufferers (Jensen & Karoly, 1992). This, coupled with the long average pain
duration reported by such samples (e.g., 9.5 years in the Morley et al. (2005) study)
makes it unlikely that clinical samples can inform knowledge and understanding of
all people with pain, particularly those early in the course of chronic pain or those
who have chronic pain but are not seeking treatment.
The difficulty of discerning the results of the research reviewed into
protective factors is further complicated by the diversity amongst pain patient
samples. Many studies seem to have recruited heterogeneous samples in terms of
their duration of pain (e.g., Revenson & Felton, 1989) or type of pain (e.g., Bergman
et al., 2002). Such variability in samples may account for the difficulty in
replicating the findings from one study to another. A larger study of significant pain
in the community may address these issues of representativeness and restriction of
range. Respondents may be able to be categorised according to variables such as
pain duration or type of pain, and have the contribution of these factors explored.
Nonetheless, given these preliminary findings, it would seem that variables such as
56
coping, pain beliefs and appraisal, positive affect, optimism and social support may
be protective against developing chronic pain disability.
Aims of the Research
The research has two main aims. The first aim is to examine the nature of
pain in a community sample. The second aim of this research is to explore the
transition from acute to chronic pain with particular emphasis on Gatchel’s Model.
This research will focus on non-cancer pain. Non-cancer pain was chosen to
overcome some of the limitations of previous research that have been restricted to a
site of pain as non-cancer pain is considered a broader category of pain than pain
types differentiated by site (e.g., headache, low back pain). However, excluding
cancer conditions will reduce variance introduced by clinical indicators (e.g., disease
variables, malignancy) (Jay, Elliot, & Varni, 1986; cf Turk et al., 1998). As
Gatchel’s Model was originally developed for low back pain and it has since been
deemed appropriate for other musculoskeletal pain conditions (e.g.,
temporomandibular disorders), examining this model and the proposed extensions to
it with a broader pain population may increase its usefulness.
Aim 1: The Nature of Pain in a Community Sample
In Chapter 1, the review of the literature showed that constant pain that
persists after three months is associated with higher levels of psychological distress
than acute pain conditions. The disability costs to society and the individual are
equally bleak. Studies of overseas populations in addition to a general health survey
conducted in New South Wales indicate that chronic pain is likely to be a significant
problem for Australian adults. Although increases in prevalence rates (and
57
associated economic costs) are predicted, the nature of the problem of chronic pain
is not well understood in Australia, nor in Queensland in particular. In addition,
although estimates of prevalence vary with the type of pain targeted and the
definition of chronic pain used, further research into chronicity in pain conditions is
clearly warranted on the basis of these preliminary estimates.
Data will be collected in one of Australia’s seven states and territories,
Queensland. Queensland has the second fastest rate of population growth in
Australia (Australian Bureau of Statistics, 2008); geographically, Queensland is the
second largest state in Australia; and, by 2041 it is projected to be the second most
populous Australian state (Australian Bureau of Statistics, 2005). Collecting data on
the nature of pain in a community sample in Queensland serves two purposes. First,
it provides Queensland population data, which has not been collected previously.
While a full scale prevalence study was beyond the scope of this research,
population data on chronic pain will be collected in order to comment generally on
the healthcare planning and service provision requirements in rural and urban
Queensland. Recently, community based treatment was identified as “appropriate
for most people with chronic non-disabling pain” (Access Economics, 2007, p. vii).
Second, this research will allow a more comprehensive description of
chronic pain in a community sample than has been undertaken previously. Most of
the knowledge about chronic pain including its presentation and associated disability
are obtained from patient samples, who are long term sufferers and whom arguably
represent the people with chronic pain who are not managing their pain experience.
Many of the patients who present to tertiary pain services could be described as
being at Stage 3 of Gatchel’s Model; also depicted by Turk and Rudy (1988) as
dysfunctional. Yet, a community study conducted in New South Wales
58
demonstrated that over one third of adults with pain did not report that pain
interfered with their daily life (Blyth et al., 2001). Clearly, this portion of the pain
population may be missed by research using patient samples. Therefore, description
of a community sample for comparative purposes for Australian patient studies will
be valuable.
In addition, exploring the nature of pain in a community sample allows for a
broader spectrum of pain conditions to be assessed. Due to a focus on chronic pain,
missing from the pain research is knowledge of the broader experience of pain, for
example, people with longstanding intermittent pain.
Specifically, data about the following areas will be sought: the type of acute
and chronic pain, the sites of pain, perceived causes of pain, involvement with
insurance systems, where people first seek treatment, and the amount of disability
associated with these pain conditions.
Aim 2: Exploring the Transition between Acute and Chronic Pain
Recently, further research into the acute to chronic pain progression was
identified as a priority research area in Australia (Access Economics, 2007).
Currently, the pathways between acute and chronic pain are not well understood.
Nor are the factors that predict continued disability or recovery from pain well
delineated. These factors give rise to two research questions that fall under this
broad aim.
Clinical Model of the Transition from Acute to Chronic Pain
The model proposed by Gatchel (1991a), which has indirect research
evidence, may provide a framework for understanding individuals’ transition from
59
acute pain to chronic pain disability. Whilst this model was first proposed in 1991,
it remains current in the literature (Gatchel, 2005). Therefore, a primary aim of this
research is to explore Gatchel’s Model of the transition from acute to chronic pain
disability. Specifically, this research will 1) explore the development of
psychological distress as acute pain persists and meets the criteria for chronic pain,
with particular focus on some of the psychological symptoms that have been
associated with Gatchel’s concept of mental de-conditioning – depressed mood and
pain-related anxiety – using a longitudinal study design, and 2) compare the
development of physical de-conditioning in this sample with that which is predicted
by Gatchel’s Model.
Examine the Predictive Value of Risk Factors and Protective Factors
Much of the literature presented earlier shows that there are inconsistencies
in the results of research that examines risk factors for the development of chronic
pain. One of the limitations of previous research is that subgroups of people with
pain have been targeted which has resulted in studies with limited generalisability
and may have minimised potentially important predictors. In addition, longitudinal
research into risk factors of chronic pain in Australia has not been conducted.
Similarly, many of the protective factors have not been examined in a community
sample or with people early in the course of chronic pain.
Therefore, this research will use a broader pain sample with the aim to
improve the generalisability of the research findings, with the aim of replicating the
results of previous overseas research regarding the predictive value of risk factors
(acute pain severity, expectations of recovery, catastrophising, fear-avoidance
beliefs, age and gender) in an Australian community sample. In addition, this
60
research will explore the predictive value of possible protective factors (i.e., coping,
self efficacy, pain beliefs, positive affect, optimism and social support). Both risk
and protective factors will be assessed with a view to incorporating these variables
into an extension of Gatchel’s Model. The predictive value of protective factors will
be compared with the predictive value of risk factors for chronic pain.
Chapter Summary
The chapter began with an overview of the common terms used in chronic
pain research. The expression, chronic pain, includes a heterogeneous group of pain
conditions that persist past 3 months and are often associated with affective distress
and physical disability.
It has been demonstrated that the prevention of chronic pain and its
associated disability relies on clear understanding of the transition from acute to
chronic pain. A model that provides a framework for understanding the transition
process was proposed by Gatchel (1991a). One of the strengths of Gatchel’s model
is that treatment recommendations are provided based on the proposed underlying
de-conditioning processes that occur as chronic pain and disability develops.
However, this model has focused solely on clinical samples, who are a small
proportion of people with pain, and has little direct empirical support. In addition,
the mechanisms behind some of the processes described are not clear.
The description of Gatchel’s Model was followed by an examination of risk
and protective factors that may provide a useful extension to this Model. Several
possible risk factors were identified, although little research has examined these
factors in Australian samples. Protective factors were examined also, although there
is less evidence for their influence during the acute to chronic transition.
61
The chapter concluded with the two primary aims of this research. Chapter 3
presents the methodology used in the research to achieve these research aims.
Chapter 3: Methodology of the Research
63
CHAPTER 3:
METHODOLOGY OF THE RESEARCH
Chapter Overview
As was discussed in Chapter 2, the two primary aims of this research were to
explore the experience of pain in a community sample and to examine the transition
process from acute pain to chronic pain disability using Gatchel’s Model. To
address these aims, a prospective longitudinal mixed-method design was utilised.
This chapter describes the rationale for using a mixed-method approach, outlines the
methodology for the research and provides a description of each of the study phases,
the results of which are presented in subsequent chapters.
The Use of a Mixed-Methods Approach
Using a combination of quantitative and qualitative research methods is
known as a mixed-method approach. Mixed-method approaches have been used for
many years; however, these approaches have gained increasing attention as a
specific methodology in the last 20 years (see also Axinn & Pearce, 2006; see
Sandelowski, Voils, & Barroso, 2006). Particularly, mixed-method approaches have
been used in health research in an effort to capture the complexity of the numerous
factors that influence wellbeing (Morgan, 1998b).
A mixed-method approach may offer a number of advantages over a single
type of methodology. Axinn and Pearce (2006) state that “when a research problem
calls for the combination of high levels of structure to test hypotheses and low levels
of structure to discover new hypotheses, mixed-methods are particularly
64
appropriate” (p.24). Mixed-method research is also believed to provide richer
information about the concept under investigation (for a discussion see
Onwuegbuzie & Johnson, 2006). Onwuegbuzie and Johnson (2006) suggests that an
additional value of mixed-method research is that it enables the study of multiple
aspects or multiple research questions in a single piece of research; while
compensating for the weaknesses of each techniques (Axinn & Pearce, 2006). A
mixed methodology was selected for this research for these reasons.
Using a Mixed-Method Approach for the Research
There are a number of ways that the various methods can be combined. In
the most part, these methods are differentiated by the order in which data are
collected and analysed. For example, classifications of these different approaches
have been provided by Morgan (1998b) and Onwuegbuzie and Johnson (2006). The
approach used in this research can be classified as a sequential mixed-method design
(Axinn & Pearce, 2006). This means that the different types of data were collected
one after another; data was collected through quantitative methods and then using
qualitative methods. This particular approach is regarded as well suited to
longitudinal research (Axinn & Pearce, 2006). Using this approach, the data from
one phase are used to inform the following phases. This research used
questionnaires (Phases 1 and 2; quantitative data) followed by semi-structured
interviews (Phase 3; qualitative data). A qualitative approach was used in the later
stages of the research to facilitate the interpretation of quantitative data, known as a
contextual overlaying strategy (Onwuegbuzie & Johnson, 2006). Additionally,
analysis of the large scale data set can guide the collection of the smaller less
structured data set. For example, this information can guide the selection of
65
participants (such as, those most likely to be informative etc.) to be targeted for these
more time-intensive research phases (Axinn & Pearce, 2006).
Choosing the Data Types
Each type of data included in this research was chosen deliberately. Phase 1
and 2 of the project used postal questionnaires, which have the advantage of being
able to easily assess a large number of respondents simultaneously (Axinn & Pearce,
2006). Questionnaires also allow the use of standardised measures which can
facilitate the comparison of data between studies. Since one of the aims of this study
is to provide Australian data on concepts that may be comparable to other
populations, it is vital to use approaches that are consistent with those used in
previous research. In addition, as this is the first time that Gatchel’s Model has been
examined with a community sample of people with pain, standardised questionnaires
provide a precedent against which to compare these data.
However, questionnaires and standardised instruments are limited in their
ability to provide in-depth information about new concepts and processes because
the research questions and the measures that are used to assess these questions are
set a priori (Axinn & Pearce, 2006). Due to the structure of questionnaires,
participants’ responses are constrained to factors predetermined by the researcher –
who cannot predict the total experience of their participants. While quantitative
research reduces the variability in a phenomenon to highlight patterns across that
phenomenon, as a result of the reductionist nature of this type of research, some of
the fullness of the experience may be lost, for example, when using standardised
items (Axinn & Pearce, 2006).
66
To overcome some of the limitations of questionnaires, semi-structured
interviews were utilised. The interviews were designed to allow new themes to
emerge as well as exploring the processes underlying the experience of pain. This
type of qualitative data collection has the potential to provide greater opportunities
for insight into the lives of the target population, and opportunities for new
discoveries. Given that this research aimed to extend Gatchel’s Model to include
concepts (e.g., protective factors) not frequently studied in previous pain research,
this approach was considered particularly important.
The limitations of semi-structured interviews also need acknowledgement.
This method is time and labour intensive for the researcher and participant. As well,
this type of data collection may be more confronting for participants who are
disclosing their personal experiences face-to-face with the interviewer. In addition,
similar to questionnaire methods, bias may be introduced through the wording or
order of items as well as through the interaction between the interviewee and
interviewer (Axinn & Pearce, 2006). In order to minimise bias in this research,
consistent wording was used for the primary interview questions and some optional
prompts. Questions were also administered in the same order by one interviewer. In
addition, by emphasising at the beginning of each interview the importance of each
participant’s beliefs, opinions and experiences, the interviewer tried to create a
similar context for all participants, one in which their individual experiences were
valued and welcomed.
Matching a Mixed-Methods Approach to Chronic Pain Research
In addition to selecting the type of data collection that would be undertaken
at each research phase, there were several topic-specific reasons for choosing to use
67
a mixed-method design. Mail questionnaires were used to obtain a snapshot of the
experience of pain in a large community sample, and to allow comparison with
previous literature. In this research postal questionnaires allowed a random sample
of Queensland residents to be targeted in order to be able to generalise the findings
to a broad groups of people with pain. The value of including qualitative methods is
that it allowed the experience of pain, a subjective experience, to be explored in an
experiential way. As relatively little research has examined the perceptions of those
with pain in this way (for exceptions see Campbell & Guy, 2007; Corbett, Foster, &
Ong, 2007; J. C. Richardson, Ong, & Sim, 2006) and more often with women only
(e.g., Johansson, Hamberg, Westman, & Lindgren, 1999; Werner, Isaksen, &
Malterud, 2004) or clinical patients only (e.g., Johansson et al., 1999; J. Walker,
Holloway, & Sofaer, 1999), key information may be missing from our understanding
of pain. In addition, one of the strengths of qualitative research is its ability to
explore processes such as those involved Gatchel’s Model, which the questionnaire
data may be less able to address.
Optimising the Use a Mixed-Methods Approach
There are a number of strategies that have been identified which may
optimise the use of a mixed-method approach. Axinn and Pearce (2006) highlight
the importance of using complementary methods to offset each methods’
weaknesses, for example, choosing a mix of highly- and less-structured techniques
or methods which involve direct and indirect participant contact.
Additionally, five aspects for consideration when designing well integrated
mixed-method studies were emphasised by Yin (2006), and these factors were
considered in the design of this research. First, the research question and studies are
68
integrated; each study should contribute to all research questions. In the current
research, Phases 1 and 3 will examine the first aim and Phases 1, 2 and 3 will target
the second aim. Second, the studies use the same unit of analysis. In this research,
each of the research phases employed participants from one community sample (that
is, a single unit of analysis). Third, in addition to using the same unit of analysis, it
may be desirable to use nested samples. A nested sample is when a sample for one
data collection is a sub-sample of another data collection. In the current research, a
large sample is used for the questionnaire phases and a smaller subset of the original
sample is used in the interview phase. Fourth, overlapping or complementary
instrumentation and data collection methods may allow each of the different
approaches to confirm the findings of the other. In this study, some items were used
in all data phases to better understand how participants interpreted these example
items. A related issue in longitudinal research is the issue of repeated measurement
(Axinn & Pearce, 2006). It is vital to use the same measures to allow changes in
these constructs to be assessed and reduce bias associated with changes to
measurement technique. Finally, the purpose of the different analyses should be
matched across the different types of data. Therefore the findings of each study in
this research will be additive and contribute to the overall research aims.
Description of the Study Methodology
Design
Data were collected using a prospective mixed-methods design. In the first
data collection phase, quantitative data was collected using questionnaires (hence
referred to as the baseline study). The second research phase again used
questionnaires and quantitative data (hence known as the follow-up study). The third
69
data collection phase employed semi-structured interviews to obtain qualitative data
(hence called the interview study). See Figure 2 for an illustration of the samples
and study design.
Phase 1
Questionnaires posted
No response received
Returned questionnaires
Pain-free
participants
Acute pain participants
Intermittent pain participants
Follow-up questionnaire posted
Chronic pain participants
Follow-up questionnaire posted
Lost to follow-up
Lost to follow-up
Phase 2
Returned follow-up
questionnaires
Returned follow-up
questionnaires
Invitation for interviews made
Invitation for interviews made
Lost to follow-up
Lost to follow-up
Phase 3
Interviews conducted
Interviews conducted
Figure 2. Flowchart of the study sample
Sample
Across Queensland, Australia, a community sample of people with pain was
targeted. Using the same methodology, demographic variables were also collected
from participants with no pain. Ten postcode areas were randomly selected; one
from each of the six shires or cities from the greater Brisbane area (the most densely
populated metropolitan area in Queensland (Department of Local Government
Planning Sport and Recreation, 2005)) and one each of the other four remoteness
70
classifications, defined using the Accessibility/ Remoteness Index of Australia
(Australian Department of Health and Aged Care, 1999)10. Postcodes were drawn
out of a hat containing all the postcodes of the region or remoteness classification.
Table 3 displays the probability for the selection of each of the targeted postcodes.
Within each of the 10 randomly selected postcode areas, 800 residential addresses
were further randomly selected to receive the mailed questionnaire11.
Table 3
Probability of Postcode Selection
Selected postcode
4053
4020
4129
4507
4164
4105
4717
4725
4741
4869
Region
Pine Rivers shire
Redcliffe city
Logan city
Caboolture shire
Redland shire
Brisbane city
Blackwater town
Barcaldine town
Mackay region
Cairns city
Probability of selection
1 in 12
1 in 4
1 in 16
1 in 12
1 in 10
1 in 163
1 in 42
1 in 48
1 in 53
1 in 58
Note. A postcode list was not available for Brisbane City. Instead, a Statistical Local Area (SLA: a
category used by the Australian Bureau of Statistics) was randomly chosen from the 163 SLAs in the
Brisbane City. The corresponding postcode for this SLA is 4105.
Survey recipients experiencing pain were asked to provide their postal
address and contact telephone number if they consented to participate in the followup components of this study. Participants with pain, who consented to be recontacted, were then invited to participate in the follow-up study. Participants of the
follow-up study could nominate to be contacted for the interview study.
10
This index classifies geographical locations based on accessibility to services.
One district had only 696 postal addresses; therefore less than 800 residential addresses were
targeted.
11
71
Procedure
Phase1: Baseline Study
The questionnaire packs (N = 7896) were mailed through the Unaddressed
Mail Service12 of Australia Post to residents of the selected Queensland postcodes.
The information sheet and questionnaire instructions requested any adult (18+ years)
experiencing significant pain in the household to complete the questionnaire.
Participants were requested not to respond if their pain related to a diagnosis of, or
treatment for, cancer13. Significant pain was defined as pain that had lasted more
than a 24-hour period in the previous fortnight14. To obtain comparative
demographic information for those without pain, if no one was experiencing
significant pain, one adult member of the household was requested to complete the
demographics section only and return the questionnaire. The use of identification
numbers assigned to returned questionnaires enabled the respondent data to be
matched across the data collection points. A record of returned questionnaires’
identification numbers plus contact details was made (in order for a corresponding
identification number to be pre-printed on the follow-up questionnaire).
Phase 2: Follow-up Study
Baseline respondents who experienced acute or chronic pain were sent the
same questionnaire for a second time (N = 302). The follow-up questionnaires were
sent 12 weeks after the distribution of the baseline questionnaires, the length of time
12
The unaddressed mail service delivers unaddressed mail to all or a random selection of residential
addresses in a chosen postcode delivery area.
13
Unlike other musculoskeletal pain, cancer pain can be a result of the disease or treatment (Jay et al.,
1986) and is associated with different pain cognitions compared with those with non-cancer pain (de
Wit, van Dam, Litjens, & Huijer Abu-Saad, 2001).
14
Fourteen days was chosen as the window for experiencing pain as this was considered a reasonable
length of time to be able to recall a serious pain event and also to increase the number of eligible
participants for the study. This criterion has previously been used and found to be acceptable in
population based studies (e.g., Benjamin et al., 2000). Data are collected on the number of days the
participant has experienced pain.
72
that differentiates between acute and chronic pain (see IASP, 1986 for the
definition).
Phase 3: Interview Study
Follow-up respondents, who indicated interest in being involved in the final
stage of this research, were invited to participate in semi-structured interviews (N =
41). Due to logistical reasons, only respondents living in the greater Brisbane area
were contacted for interviews because these were conducted face-to-face. (When
compared, the urban and rural participants who were available for the interview
study did not differ on depression, anxiety, pain intensity or disability scores; see
Appendix A for these analyses). Interviews were held approximately 12 months
(between 10-14 months) after the follow-up study. This was because some evidence
suggests that back pain in particular fluctuates over time (Burton et al., 1995).
Twelve months was considered a sufficient time to capture some of these
fluctuations.
Ethical Clearance and Occupational Health and Safety Approval
The study was approved by the University Human Research Ethics
Committee (approval number: 0600000252). For the questionnaire phases (baseline
and follow-up) written consent was assumed if participants returned a completed
questionnaire. Consent was given to use the data in the thesis in an aggregate form
to preserve anonymity. For the interview phase, written consent was obtained prior
to commencing the interviews. Consent was obtained to audiotape and transcribe
the interview, and to use the information provided in the thesis anonymously.
73
Occupational health and safety approval was obtained to conduct this project
through the School of Psychology and Counselling.
Measures
Questionnaire: Phase 1 (baseline)
After consideration of the key concepts of Gatchel’s Model and the noted
risk and protective factors, an extensive test battery was compiled. This test battery
included 12 established self-report instruments chosen to reflect the four keys areas
of study within this research, the first two of which are components of Gatchel’s
Model: pain severity and disability (physical de-conditioning), psychological
distress (mental de-conditioning), risk factors and protective factors. Figure 3
illustrates the instruments used to operationalise Gatchel’s de-conditioning concepts
and Table 4 matches the risk and protective factors under investigation with the
standardised instruments used to assess those concepts. Demographic information
was collected at baseline only. Items that assessed pain variables were included so
that a description of this sample’s pain experience could be provided (see Appendix
B for a copy of the questionnaire).
A small pilot study was conducted to assess the readability and ease of
comprehension of the questionnaire. Four adults with pain completed the
questionnaire. The entire measure took approximately 30 minutes to complete.
Several minor aesthetic changes were made to the layout of the items as a result of
feedback from these participants.
74
PHYSICAL DECONDITIONING
Roland & Morris Disability Questionnaire
MENTAL DECONDITIONING
Center for Epidemiologic Studies-Depression
Pain-related Anxiety Symptoms Scale
PAIN
(Hurt = Harm)
STAGE 1
Initial psychological
distress (fear,
anxiety, worry etc)
STAGE 2
Development or
exacerbation of
psychological
problems
STAGE 3
Acceptance of “sick
role”; consolidation of
abnormal illness
behaviour
Figure 3. Mapping the measures onto Gatchel’s Model
Table 4
Mapping the Risk and Protective Variables onto the Questionnaire Measures
Variable Under Investigation
Measure
Risk factors
Acute pain severity
Pain intensity subscale of Graded Chronic Pain Scales
Belief: likelihood of recovery from pain
Single item from the Fear-Avoidance Beliefs
Questionnaire
Catastrophising
Subscale from Coping Strategies Questionnaire
Fear-avoidance beliefs
Gender
Single demographic item
Age
Single demographic item
Protective factors
Coping strategies
Subscales from Coping Strategies Questionnaire
Subscales from Chronic Pain Coping Inventory
Self efficacy
Pain Self Efficacy Questionnaire
Beliefs about pain
Positive affect
Positive Affect scale of the Affect Balance Scale
Optimism
Life Orientation Test - Revised
Social support
75
The following sections describe each of the established instruments included
in the questionnaire. The rationale for their inclusion in this research is also
provided.
Experience of Pain and Disability
Pain and disability variables were examined using the Graded Chronic Pain
Scales (GCPS) and the Roland and Morris Disability Questionnaire (RMDQ). These
measures provided a proxy measure of disability and therefore physical deconditioning.
Graded Chronic Pain Scale
In addition to physical de-conditioning, the Graded Chronic Pain Scale
(GCPS) also provided a measure of pain intensity, a factor that needed to be
controlled, and also allowed the pain experience of a community sample to be
charted. Thus, the GCPS was used because it provides a comprehensive measure of
the severity of chronic pain that accounts for level of pain and the associated
disability. The GCPS contains seven items which form a pain intensity estimate and
a disability estimate appropriate for epidemiology studies (Von Korff et al., 1990;
Von Korff, Ormel, Keefe, & Dworkin, 1992). The combination of the pain intensity
and disability estimates are used to categorise individuals with pain into four
severity grades – I low disability-low intensity; II low disability-high intensity; III
high disability-moderately limiting; IV high disability-severely limiting. The grade
is given based on the level of pain intensity and a disability score (see Von Korff et
al., 1992). However, pain intensity and disability scores provide an alternate
continuous variable for analyses where categorical variables are inappropriate. This
76
measure was designed to be able to be used with people with pain at all anatomical
sites resulting from a variety of causes (Von Korff et al., 1992).
GCPS scoring is calculated in several phases. The pain intensity estimate is
the average of the scores for current, worst and average pain and transformed into a
score from 0 to 100. The disability estimate is scored as the average of interference
with daily activities, social activities and work activities, measured from 0 to 100.
Then a disability days score is assigned (from 0-3) based on the activity limitation
days item. As participants were asked about the previous 3 months, their activity
limitation days response was multiplied by 2 before calculating the disability days
score (Von Korff, 2001)15.
The GCPS was normed on general population and primary care samples. It
has good internal consistency seen across a range of pain and general practice
populations, for example, ranging from .62 to .80 for temporomandibular disorder
pain to .73 to .79 for headache (Underwood, Barnett, & Vickers, 1999; see also Von
Korff, 2001 for a review; Von Korff et al., 1990; Von Korff et al., 1992). Good testretest reliability (≥.82) has been reported in community samples (Underwood et al.,
1999).
Roland and Morris Disability Questionnaire
To improve the concurrent validity of this study, the Roland and Morris
Disability Questionnaire (RMDQ) was chosen as a second measure of disability
because self report instruments are only proxy measures of physical de-conditioning.
The RMDQ is an established and widely used measure of disability. It is a quick 24item measure designed to be completed without assistance from medical personnel
15
Using a 3-month period may result in higher ratios of grade III & IV classifications (Von Korff,
2001).
77
in approximately 5 minutes (Roland & Morris, 1983a, 1983b). The RMDQ was
originally developed to measure disability associated with back pain. However,
consistent with other researchers (Jensen, Keefe, Lefebvre, Romano, & Turner,
2003), the questionnaire was modified to be appropriate for all musculoskeletal pain
conditions by replacing the word ‘back’ with the word ‘pain’.
Responses are scored as 0 (did not apply) or 1 (true). The total score
indicates the level of disability severity with higher scores reflecting greater pain
disability (range 0-24).
The RMDQ has good test-retest reliability (Roland & Morris, 1983a).
Internal consistency was excellent (α = .96) in a community pain sample
(Underwood et al., 1999).
Psychological Distress Variables
Two instruments that examine two common psychological distress factors
were used to examine depressive symptoms (Center for Epidemiologic Studies
Depression scale; CES-D) and pain-related anxiety (Pain Anxiety Symptoms Scale;
PASS). These were used to operationalise mental de-conditioning syndromes.
Center for Epidemiologic Studies Depression scale
Depression is commonly seen in pain patients and was recognised by Gatchel
as a common expression of mental de-conditioning; therefore a measure of
depressive symptoms was used in this research. The Center for Epidemiologic
Studies Depression scale (CES-D Scale) is a 20-item measure of self-reported
depressive symptoms (Radloff, 1977). It was developed for use with the general
population. Respondents mark the frequency of their feelings or behaviour on a 4-
78
point likert scale ranging from rarely or none of the time to most or all of the time.
Each point on the likert scale is anchored to a verbal descriptor. Of all the
depression measures available, the CES-D was selected because it has often been
used in pain research, particularly with non-clinical samples (e.g., Fritz et al., 2001),
and also because it was developed for use with the general population in
epidemiology-type studies (similar to the current study).
CES-D scores are summed; higher total scores reflect more frequent
depressive symptoms with a range from 0 to 60. In the general population cut-off
scores have been developed to differentiate people with significant depressive
symptoms. Due to the overlap between depressive symptoms and symptoms of pain
(such as sleep disturbance), a higher cut-off score is required to detect people with
pain who have significant depressive symptoms (Geisser, Roth, & Robinson, 1997).
The optimal cut-off score is 27, which is used a proxy measure of depression.
The CES-D is a popular measure of depressive symptoms (Santor, Zuroff,
Ramsay, & Cervantes, 1995). It has good internal consistency, between .85 and .90
(Radloff, 1977). The CES-D has moderate test-retest reliability, which is not
unexpected given the changing or cyclic nature of some depressive symptoms
(Radloff, 1977).
Pain Anxiety Symptoms Scale-20
Another common form of mental de-conditioning is pain-related anxiety.
The Pain Anxiety Symptoms Scale (PASS) is a measure that targets four areas of
pain anxiety: somatic anxiety, cognitive anxiety, fear, and escape/ avoidance
responses (McCracken, Zayfert, & Gross, 1992). A 20-item version is available
(McCracken & Dhingra, 2002), which was used in the current study. The PASS was
79
chosen as the measure of anxiety for this study primarily because it is a measure that
is specific to pain; Gatchel’s Model suggests that the anxiety experienced by people
as they develop chronic pain is pain-related. In addition, compared to general
measures of anxiety, pain-related measures have been found to explain more
variance in pain and pain-related disability (McCracken, Gross, Aikens, & Carnrike,
1996). The PASS is a measure that has been previously used with community pain
samples also (Abrams, Carleton, & Asmundson, 2007; Coons, Hadjistavropoulos, &
Asmundson, 2004).
In the 20-item version of the PASS (PASS-20), each subscale is represented
by five items. Respondents are instructed to rate the frequency of the behaviour
detailed in each of the items; response options range from 0 (never) to 5 (always).
Responses are summed to calculate a total score (range 0-100) (McCracken &
Dhingra, 2002). As in previous research (Crombez et al., 1999; McCracken et al.,
1996), the total score was used in this study. A cut-off score of 30 is suggested to
identify individuals with high pain-related anxiety (Abrams et al., 2007).
The PASS-20 correlates strongly with the full-length PASS (McCracken &
Dhingra, 2002). In addition, the psychometric properties of the PASS-20 have been
specifically examined in a number of studies (Abrams et al., 2007; Coons et al.,
2004; McCracken & Dhingra, 2002). Factor analysis of the items consistently
demonstrates a 4-factor solution consistent with the development of the scale.
Internal consistency ranges from .70 to .87 for the subscales and .83 to .91 for the
total scale. The PASS-20 is regarded as having good construct and predictive
validity (Abrams et al., 2007; Coons et al., 2004; McCracken & Dhingra, 2002).
80
Extensions to Gatchel’s Model: Risk Factor Variables
As this research aimed to examine possible extensions of Gatchel’s Model,
concepts identified as risk factors for either developing a pain condition or for worse
pain-related disability outcomes were assessed (see Chapter 2 for more information).
Fear-avoidance beliefs were examined as a possible risk factor for increasing
disability and de-conditioning using the Fear-Avoidance Beliefs Questionnaire
(FABQ). The Coping Strategies Questionnaire (CSQ) was used primarily to
examine the influence of catastrophising as a risk factor and as a possible valuable
addition to Gatchel’s Model.
The Fear-Avoidance Beliefs Questionnaire (FABQ) is a 16-item
questionnaire originally designed to measure fear-avoidance beliefs about work (11
items) and physical activity (5 items) for back pain (Waddell, Newton, Henderson,
Somerville, & Main, 1993). It is frequently used in pain research (e.g., Ciccone &
Just, 2001; Crombez et al., 1999; Fritz et al., 2001). The FABQ was selected for this
research because it measures fear-avoidance beliefs specific to two areas (that is,
physical activity and work) that are noteworthy in terms of the impact on one’s daily
life (Nagi, 1976) and are most affected by fear-avoidance type beliefs (Waddell et
al., 1993). Again, compared to general measures of fear, pain-specific fear measures
have stronger relationships with pain and pain-related disability (McCracken et al.,
1996). Each item is responded to on a 7-point likert scale, anchored at each end with
strongly agree and strongly disagree. Higher scores reflect stronger fear-avoidance
beliefs.
81
Factor analysis reveals two factors, on which only 11 items robustly load – 7
items on beliefs about work and 4 items on beliefs about physical activity. Only the
11 items that load on these factors are scored and summed. For this study, one
additional item was included from the FABQ that reflects the belief that they will
return to work. This additional item was included in the questionnaire because
patients’ beliefs that they will recover are predictive of the development of chronic
pain (Linton & Hallden, 1997; Schultz et al., 2004; White et al., 1997).
The instructions for the FABQ were modified slightly in this research to
reflect that research participants are not patients. Adults whose primary occupation
is homemaker were instructed to consider these duties their ‘work’ as suggested by
Waddell et al. (1993). Like the Roland and Morris Disability Questionnaire, the
items were modified to reflect the variety of pain complaints that respondents had by
removing the word ‘back’ from the instructions, and items 3 and 11.
The FABQ has good test-retest reliability (Waddell et al., 1993). The
internal consistency for the FABQ work subscale is good, ranging from α = .82 to
.92 in chronic pain patient samples (e.g., Ciccone & Just, 2001; Crombez et al.,
1999; Waddell et al., 1993) and .74 in acute pain patient samples (Ciccone & Just,
2001). However, the internal consistency of the FABQ physical activity subscale is
poorer, ranging from .52 to .77 (Crombez et al., 1999; Waddell et al., 1993). While
the scales were derived using factor analysis with an orthogonal rotation (Waddell et
al., 1993), the scales have since been reported to correlate positively (r = .47-.55)
(see Crombez et al., 1999; Fritz et al., 2001).
82
Coping Strategies Questionnaire
The Coping Strategies Questionnaire was originally developed by Rosenstiel
and Keefe (1983) with low back pain patients. It consists of seven theoretical
subscales; diverting attention, reinterpreting pain sensations, catastrophising,
ignoring sensations, praying/ hoping, coping self-statements, and increased
activities. With the exception of the increased activities subscale, the CSQ examines
cognitive coping strategies. Each of the seven scales consists of six items. There
are an additional two items that examine the effectiveness of the coping strategies to
1) control, and 2) reduce pain. The robustness of the structure of the CSQ has been
debated (Swartzman, Gwadry, Shapiro, & Teasell, 1994) and some subscales (i.e.,
ignoring sensations and increased activities) have weak reliability. This measure
was chosen specifically for the catastrophizing subscale, as catastrophizing is a
variable that is associated with poorer outcomes for chronic pain patients (see
Hadjistavropoulos, MacLeod, & Asmundson, 1999; Keefe et al., 2004).
Catastrophising may be a useful extension to Gatchel’s Model as a risk factor.
CSQ responses scored on 7-point likert scale from 0 (never) to 6 (always).
Item scores are averaged to calculate subscale scores. Internal reliability scores
range from .71 to .85 (Rosenstiel & Keefe, 1983). Test-retest reliability of the
original scale ranged from .68 to .93 in a sample of low back pain patients. The
catastrophizing subscale has the overall strongest statistical properties (Main &
Waddell, 1991; Swartzman et al., 1994).
Jensen et al. (2003) developed a shorter scale with two items per each of the
seven subscales. Correlations for each short subscale with the parent scale averaged
.87. Similarly, relationships between the short subscale and measures of depression,
disability and pain rating replicated the relationships between the parent scale and
83
these measures 86% of the time. Tan, Nguyen, Cardin, and Jensen (2006) replicated
the results of Jensen et al. in terms of the level of association with the parent scale
(ranged from .81 to .86) and construct validity. Due to the already lengthy nature of
the questionnaire and the excellent statistical proprieties reported by Jensen et al.
and Tan et al., the short CSQ version was used in this research.
Extensions to Gatchel’s Model: Protective Factors
Chronic Pain Coping Inventory
Protective factors that may reduce or slow the onset of disability and deconditioning were of particular interest in this research (see Chapter 2). One
inventory that examines multiple coping strategies is the Chronic Pain Coping
Inventory (CPCI). The CPCI is a 65-item measure developed by Jensen, Turner,
Romano and Strom (1995). There are eight subscales – guarding, resting, asking for
assistance, relaxation, task persistence, exercise/ stretch, seeking social support and
coping self-statements. The CPCI allows a number of specific strategies to be
examined rather than more generic active vs. passive strategies. The subscales
evaluate strategies that are likely to be addressed in a specialist pain clinic program.
Four of the subscales target strategies that would be encouraged in a specialist pain
clinic program - relaxation, task persistence, exercise/ stretch, and coping selfstatements. Three of the subscales target strategies that would be discouraged guarding, resting, asking for assistance. Seeking social support is considered a
neutral subscale (see Hadjistavropoulos et al., 1999). In contrast to the Coping
Strategies Questionnaire, the CPCI is a measure of primarily behavioural coping
strategies.
84
CPCI items are measured on an 8-point likert scale by asking respondents to
nominate how many days in the previous week each item (strategy) was used.
Scores are averaged to provide scale scores. Internal consistency estimates for the
scales range from .70 to .93 (Jensen et al., 1995). Test-retest reliabilities, over a
fortnight, range from .66 to .90 (Jensen et al., 1995).
A shortened version of the CPCI was developed; containing only 42 items
(Romano, Jensen, & Turner, 2003). A further shortened version of this measure
using only two items for each of the subscales was subsequently developed (Jensen
et al., 2003). Each of the subscales for the 16-item version correlates strongly with
each of the parent subscales (Jensen et al., 2003). The test statistics for the
shortened version are good to excellent and have been replicated in other
populations (Tan et al., 2006). Tan and colleagues reported the association with the
parent scale .75 to .91 for each of the subscales. The 16-item CPCI version was
used in this study.
Like the Chronic Pain Coping Inventory, the Survey of Pain Attitudes
(SOPA) is an established measure of a range of attitudes that are thought to be
important for people with chronic pain. Pain beliefs are considered as an extension
to Gatchel’s Model. Since an early version of this measure was used by Jensen and
Karoly (1991) in their work on beliefs and chronic pain, the SOPA has undergone a
number of revisions (see Jensen, Karoly, & Huger, 1987; Jensen, Turner, Romano,
& Lawler, 1994; Strong, Ashton, & Chant, 1992). The most-well known and
utilised version has 57 items. The SOPA measures seven beliefs about pain –
personal control over pain, appropriateness of solicitous responses from family,
85
appropriateness of medications for chronic pain, inability to function, relationship
between pain and emotion, medical cure exists for pain problem, and pain signifies
harm (Jensen et al., 1994). Responses are given on a 5-point likert scale. Each point
on the scale is anchored with a verbal description, for example, a score of 3 = This is
somewhat true for me (Jensen et al., 1994). After calculating reverse-scored items,
the average of each subscale is derived.
Each of the belief scales has adequate statistical properties. Cronbach’s
alpha ranges from .71 to .81 (Jensen et al., 1994). Test-retest reliability estimates
range from .63 to .68 for each of the scales (Jensen et al., 1994).
Like the Chronic Pain Coping Inventory, a 14-item version of the SOPA
(with each scale represented by two items) has been developed. This shorter version
was used in this study. Each of the subscales for the shortened SOPA correlates
strongly with the corresponding parent subscale (Jensen et al., 2003; Tan et al.,
2006).
Pain Self efficacy Questionnaire
Self efficacy has been identified as an important factor in managing chronic
pain and is associated with pain-related disability; it may be protective during the
acute to chronic pain transition. The Pain Self efficacy Questionnaire (PSEQ) is a
10-item measure of self efficacy (Nicholas, 2007). It was chosen for this research
because it was originally developed for, and has been subsequently used in,
Australian samples (Gibson & Strong, 1996; Nicholas, Wilson, & Goyen, 1992).
Also, the PSEQ focuses on the respondent’s confidence that they can engage in
certain activities despite pain.
86
PSEQ items are scored on a 7-point likert scale, from 0 (not at all confident)
to 6 (completely confident). Item scores are summed to provide a total score (range
0-60); higher scores reflect higher self efficacy to function despite pain. In terms of
norms, the mean score in a rehabilitation setting was 36 (Gibson & Strong, 1996).
The mean scores for chronic pain patient samples were: pre-treatment range 23-28
and post-treatment range 31-32 (Frost, Lamb, & Shackleton, 2000; Nicholas, 2007;
Nicholas et al., 1992; Strong, Westbury, Smith, McKenzie, & Ryan, 2002).
The PSEQ has been used by many researchers, who report good reliability
and validity estimates for the questionnaire (Nicholas, 2007). In previous Australian
research, internal consistency ranges from .92 (Asghari & Nicholas, 2006; Strong et
al., 2002) to .94 (Gibson & Strong, 1996). Test-retest reliability is reported to be .73
over 3 months (Nicholas, 2007). The PSEQ has been used as an outcome measure
in the treatment of chronic pain patients (Nicholas et al., 1992) as well as a
predictive measure of other treatment outcomes (Strong et al., 2002).
Positive affect scale of the Affect-Balance Scale
As discussed in Chapter 2, positive affect is a further possible protective
factor. The Affect-Balance Scale is a 10-item established measure of positive and
negative affect (Bradburn, 1969), which has been used with people with rheumatoid
arthritis (Revenson & Felton, 1989). It was chosen for this reason.
Five items reflect positive affect. Items are answered yes or no. Affirmative
responses are scored 1. The scores of each item are summed for total score. Scores
range from 0 to 5; higher scores reflect greater positive affect. Internal consistency
at two time points ranged from .71 to .72 (Revenson & Felton, 1989).
87
Life Orientation Test – Revised
Optimism was identified as a possible protective factor in Chapter 2. The
Life Orientation Test – Revised (LOT-R) is a 10-item measure of optimism that
focuses explicitly on expectancies for the future (Carver & Scheier, 2003; Scheier,
Carver, & Bridges, 1994). The LOT-R was included in this research because it is a
well-used measure of optimism in health research and has been used with chronic
pain patient samples previously (Cannella et al., 2007).
The LOT-R uses 3 negatively worded and 3 positively worded items that
contribute to the scale as well as four filler items. Participants indicate on a 5-point
likert scale their level of agreement with each item; from strongly disagree to
strongly agree. All points of the likert scale are anchored with a description, for
example, a score of 1 corresponds with disagree. Negatively worded items are
reversed scored prior to summing the scores to produce a total score (range 0-24).
Internal consistency statistics for the LOT-R are acceptable at .78 (Scheier et al.,
1994).
Perceived social support, a potential protective factor, was assessed using the
Multidimensional Scale of Perceived Social Support (MSPSS). The MSPSS was
included in this research to overcome the limitations of single item measures of
social support that have been often used in pain research. The MSPSS has 12 items,
measured on a 7-point likert scale with anchors at each end from very strongly
disagree to very strongly agree (Zimet, Dahlem, Zimet, & Farley, 1988). Items are
averaged to provide a total score, which ranges from 1 to 7. Internal reliability of
the scale is good; cronbach’s α ranges from .88 (Zimet et al., 1988) to .93 (Osborne,
88
Jensen, Ehde, Hanley, & Kraft, 2007). Test-retest reliability over 2-3 months is also
good (r = 0.85) (Zimet et al., 1988).
Questionnaire: Phase 2 (follow-up)
The questionnaire used during Phase 2 incorporated some of the previously
described standardised measures. These included the Graded Chronic Pain Scales,
Roland and Morris Disability Questionnaire, Center for Epidemiologic Studies –
Depression scale and the Pain Anxiety Symptoms Scale.
Semi-structured Interview: Phase 3
Semi-structured interviews were conducted between 10-14 months after
Phase 2 (follow-up study) data collection. Twenty participants, recruited from the
greater Brisbane area and who had consented follow-up contact, attended the
interviews. Interviews were scheduled at the interviewees’ convenience.
In the main, interviews were held in either small function rooms at public
libraries located in the general vicinity of participants’ homes or in a university
meeting room if the university campus was closer to the participant’s home than the
local library. The choice of interview location used in this study was intended to
facilitate participation since ensuring that research involvement is easy for
interviewees can increase the willingness of potential interviewees to be involved
(Axinn & Pearce, 2006). One interview was conducted in the participant’s home
(sitting room) because he was unable to access either of these public venues due to
limited availability of public transport. In all cases, only the researcher and
interviewee were present. Private rooms were chosen to offer participants
confidentiality during the interview, to minimise distractions, and reduce extraneous
89
noise to improve the audio recording. In addition, the use of a neutral zone to
conduct interviews may make it easier for participants to discuss sensitive topics
(Axinn & Pearce, 2006); as noted above this occurred in all but one case.
In preparation for the interview, the interviewees’ questionnaires were reexamined by the researcher. Reviewing this data was intended to assist in rapport
development between the interviewer and interviewee, to allow the interviewer to
provide prompts if necessary and in order for the interviewer to be sensitive to the
site of pain, the severity of pain and any psychological distress that the respondents
had reported previously (see Axinn & Pearce, 2006). Consideration of this data was
found to be particularly helpful during the interviews with participants whose pain
had resolved.
Prior to beginning the interview, participants were provided with an
information sheet detailing the expectations and requirements for the study. It was
emphasised to participants that there were no right or wrong answers, and that the
aim of the interviews was to obtain their opinions and thoughts (whatever they may
be).
Questions for the semi-structured interviews were generated from Gatchel’s
Model and the Phase 2 questionnaire data. The interview questions were designed to
be open-ended. Additional prompts were used to elicit greater description of, or to
clarify, information provided by interviewees.
To begin the interview, participants were asked to describe their pain
experience. This question acted as a warm-up item and also encouraged participants
to provide the salient points of their pain experience from their point of view.
Subsequent questions targeted interviewees’ experiences of aspects of Gatchel’s
Model (e.g., how did the pain affect you emotionally?), reasons for the development
90
of chronic pain (e.g., some people’s pain does get better and some people’s pain
doesn’t get better; why do you think that is?), and strategies to manage or prevent
chronic pain disability (e.g., what do you think is the best way to deal with pain?).
At the conclusion of the interview, participants were given the opportunity to
comment on or re-emphasise any aspect of pain that they thought was important
(which the researcher should know). The questions used in the semi-structured
interviews can be found in Table 5.
Prior to beginning the interviews, the first four participants were considered a
pilot group, with which to trial the questions with members of the target group.
(This number was arbitrarily chosen, based upon the timing of the scheduled
interviews). By chance, these participants had all been classified as having
continuing chronic pain in Phase 2. At the conclusion of each of these interviews,
the researcher explored each question in terms of three aspects; clarity (i.e., whether
the participant easily understood the question), openness of the response (i.e.,
whether the question elicited detailed responses/ data), and appropriateness and
sensitivity of the terms used (i.e., whether the terms used fit well with the
participant’s experience and were non-offensive). On the basis of these four pilot
interviews and the subsequent reflection, one item was changed to improve the
clarity of this question (see Table 5). An additional prompt was written for another
question to reduce any offensiveness and to convey acceptance of participants’
experience (see Table 5).
Interviews lasted between 25-95 minutes. Respondents whose pain had
resolved generally had shorter interviews (range 25-69 minutes). Reflective
listening techniques were used during the interviews to encourage continued
narrative and to check for understanding.
91
Table 5
Semi-structured Interview Questions
Interview Items
As a reminder to me, can you tell me about the pain you have/ had, how it started … that kind of
thing?
Why do you think you still have pain? / Why do you think you improved?
How did/ do you cope with your pain?
Is there anything that you think (thought) that helps/ ed you cope?
Some people say that the way they feel can help them cope. What about your feelings –
like your emotions – was there anything about them that helped you cope?
What do you think is the best way to deal with pain?
If you think back about when you first had pain … can remember when you first thought to
yourself this isn’t going to get better?
What was happening at that time?
When on the time line?
Was there something about your thinking that changed?
How does pain get better or worse over time? a
How did or does the pain affect you emotionally?
For example, a couple of people that I have spoken with have said that they can get a bit
grumpy when they’re in pain b
Over time, did that get better or worse?
How did or does the pain affect you physically?
Over time, did that get better or worse?
I have some statements that are from the questionnaire. The answers from all the people who
completed the questionnaire were very different. I wondered if you could let me know what you
think about them?
1. There is little that I can do to ease my pain
2. There is a connection between my emotions and my pain level
3. Exercise can decrease the amount of pain I experience
Apart from your pain, have other things changed for you because of your pain?
Has anything become better?
Has anything become worse?
Do you think that the type of person you are has changed because of your pain?
What were you like before this pain started?
Some people’s pain does get better, and some people’s pain doesn’t … why do you think this is?
If you were asked to give some advice to someone who had the same kind of pain as you had,
what would you tell them??
Note. Dot points denote additional prompts that may have been used.
a
Original item: How does pain change over time? How do you think pain is related to the
passage of time?
b
This prompt was written as a result of the pilot interviews.
Interviews were audio taped and subsequently transcribed verbatim, as soon
as practicable, after the interview was conducted. Most interviews were transcribed
by the interviewer; seven were transcribed by a transcription service. The seven
92
transcripts (sent out for external transcription) were checked against the audiorecording for accuracy by the researcher.
Analysis was considered as commencing with the first interview and
continued in an ongoing fashion with subsequent interviews. As a result, after the
first 20 interviews were conducted, because consistent issues emerged, it was judged
that the breadth of the pain experience been had obtained (Morgan, 1998a). During
the first 16 interviews, interviewees described new concepts. However, after this, no
new information was forthcoming from the interviews. As no new information was
probable in additional interviews, no further participants were contacted.
Regardless, the final four interviews were completed and included in the data
analysis as they had been already arranged with interviewees.
Statistical Analysis
Questionnaire: Phase 1 (baseline) & Phase 2 (follow-up)
The questionnaire data was entered into a Statistical Package for the Social
Sciences data file. Analyses were conducted using Statistical Package for the Social
Sciences version 15.0. Unless stated, an alpha level of .05 was used. In most cases,
imputation of missing quantitative data was performed (see Chapters 4-6 for further
details). Data were screened for breaches of the assumptions of the statistical
analyses undertaken and for univariate and multivariate outliers. Where breaches of
assumptions occurred, these are detailed in the Results sections of Chapters 4-6.
93
Semi-structured Interview: Phase 3
Interviews were transcribed verbatim. Interview transcripts were uploaded
into NVivo version 7 for thematic analysis16.
Chapter Summary
A mixed-method approach was chosen for this research to utilise the
strengths of each of the research types – questionnaires to examine Gatchel’s
variables and the risk and protective variables using measures that allow comparison
between the current data and previous studies; and semi-structured interviews to
examine the experience of pain and transition to chronic pain from an individuals’
perspective using a method that allows greater opportunities for insight into the lives
of target population.
The procedure and results of the data analysis for Phase 1 are presented in
Chapters 4 and 5, along with the purpose of this study and in this context, and a brief
discussion of the results. Phases 2 and 3 are reported in Chapters 6 and 7,
respectively.
16
Because the quantitative data informed the interview items and interpretation of the qualitative
data, a grounded theory approach or phenomenological approach was not suitable for data analysis.
Chapter 4: Phase 1 – Baseline Questionnaires (community sample description)
95
CHAPTER 4:
PHASE 1 – BASELINE QUESTIONNAIRES
(Describing the community sample)
Purpose of the Study
The purpose of the baseline phase was to address both primary research
aims. As discussed, the first aim was to obtain information on the nature of
significant pain in a Queensland community sample as no large community painspecific studies have been conducted in Queensland previously. Given prevalence
data internationally, and from New South Wales, it is likely that chronic pain will be
a serious health problem in Queensland, and one that is associated with significant
psychological distress, physical disability and healthcare costs. This study provided
the opportunity to examine a broad range of pain conditions – heterogeneous in type
and body site, as well as pain conditions that do not meet the criteria for chronic pain
(e.g., episodic pain conditions). The data addressing the second aim, exploring
Gatchel’s Model, is presented in Chapter 5.
Brief Introduction
Studies of community samples have found that chronic pain is not
uncommon. For example, approximately 1 in 5 people in New South Wales report
chronic pain (Blyth et al., 2001). Further, chronic pain in community samples
interferes with activities of daily living (Blyth et al., 2001), results in greater use of
healthcare services (Blyth et al., 2004), is associated with depressive symptoms
(Breivik et al., 2006) and lower quality of life (Hoffman et al., 2002), and substantial
work-related costs (increased absenteeism and workers’ compensation litigation, and
96
decreased productivity) (Blyth, March, Nicholas et al., 2003). These studies
highlight the cost of chronic pain, even for people who do not present to a tertiary
clinic setting.
Missing from the research in this area is knowledge of the broader
experience of pain, for example, the experience of chronic pain by groups not
currently defined as “patients”, or people with longstanding intermittent pain. An
examination of the total pain experience in the community (including acute pain) is
necessary to map the pain trajectory across the whole spectrum of pain conditions;
knowledge of which is important to inform treatment programs and the development
of transitional models of acute to chronic pain such as those proposed by Gatchel
(1991a).
The study details the experience of pain in this community sample, including
the influence of pain site, and the coping strategies used by a community sample.
This chapter will focus on those people who meet the criteria for chronic pain, those
who have intermittent pain, and those who describe an acute pain experience, as an
important preliminary step to understanding the range of pain experienced in the
Australian community and to inform transitionary process models of chronic pain.
Method
Sample
As described in Chapter 3, 7896 questionnaires were sent out. Eight hundred
and twenty-one questionnaires were returned. Of these, 20 were excluded from
further analysis: six questionnaires were returned uncompleted, four questionnaires
were completed by respondents under 18 years of age, one respondent nominated a
New South Wales permanent address, and nine questionnaires had more than 50%
97
missing data. Removal of these cases resulted in 801 useable questionnaires; a
response rate of 10.14%. The 801 respondents were classified into pain groups,
corresponding to the pain definitions presented earlier (see Chapter 2). The process
of defining pain groups is illustrated in Figure 4. Figure 4 shows that 348
participants were pain-free; these respondents will be known as the “pain-free
sample”. Pain-free respondents provided demographic information only so that
comparisons between their background characteristics and the other pain participants
could be made.
Four hundred and fifty-three respondents had significant pain. Of these, 55
participants reported more pain-free than pain-affected days; they will be referred to
as the “intermittent subgroup”. There were 395 people who reported that they
experienced this pain on more days than not. Three participants did not respond to
this item, and were therefore excluded from subsequent analyses.
Of the 395 respondents with pain on most days, 47 had acute pain (pain ≤ 3
months; hereafter called the acute subgroup) and 320 had chronic pain17 (pain > 3
months; hereafter called the chronic subgroup). There were also 28 respondents
whose pain status could not be inferred because they did not report how long they
had experienced their pain.
Because 28 respondents did not report how long they had experienced their
pain and could not be clearly assigned to either the chronic or acute pain groups,
they were excluded from subsequent analyses. To determine if the exclusion of this
group might have introduced sample bias, the demographic characteristics of this
group was compared with the rest of the pain respondents; there were no differences
17
This represented 19.6% of the adults residing in the respondent households.
98
801 completed
questionnaires
348 pain-free
55 intermittent pain
(more pain free days)
395 pain on most
days
320 chronic pain
47 acute pain
(pain most days
>3mths)
(pain most days
≤3mths)
Figure 4. Defining the Phase 1 pain subgroups
on gender, marital status, education level completed, age or number of adults in the
household (the details of these analyses can be found in Appendix C). Therefore,
there was no evidence that this excluded group differed from the rest of the sample.
Measures
Participants received a questionnaire that explored their experience of pain
using the 12 measures described in Chapter 3, as well as demographic variables
(age, gender, marital status, residential postcode, number of adults in household).
Only the standardised measures that were used to describe respondents’ experience
of pain are detailed here; the properties of which are presented in Table 6.
Procedure
One questionnaire pack was sent to approximately 800 randomly selected
residential addresses in each of the 10 chosen postcode areas. Adults residing at
targeted households were invited to participate through an information letter, which
provided details of the study and ethical considerations (see Appendix D for a copy
of the information sheet). A reply-paid envelope was provided in which to return
Table 6
Description of the Measures used in Phase 1 to describe the Pain Experience of Respondents
Instrument
(GCPS)
Author
Von Korff et al.,
1990, 1992
Concept measured
Pain Intensity
Disability
# items
7
Roland and Morris
Disability Questionnaire
(RMDQ)
Roland & Morris,
1983a, 1983b
Pain-related disability; daily interference
24
Center for Epidemiologic
Studies Depression scale
(CES-D)
Radloff, 1977
Depressive symptoms
20
0-60; higher scores = greater depressive symptoms
Cut-off score of 27 for depression in people with pain
(Geisser et al., 1997)
Pain Anxiety Symptoms
Scale-20 (PASS-20)
McCracken et al.,
1992
Pain-related anxiety
20
0-100; higher scores reflect greater anxiety
Cut-off score of 30 for high pain-related anxiety (Abrams
et al., 2007)
Coping Strategies
Questionnaire (CSQ) short version
Rosenstiel &
Keefe, 1983
Jensen et al., 2003
14
0-6 for each subscale score
Chronic Pain Coping
Inventory (CPCI) - short
version
Jensen et al., 1995,
2003
Cognitive coping strategies:
Reinterpreting pain sensations; Diverting attention;
Ignoring sensations; Praying/ hoping; Coping selfstatements; Increased activities; Catastrophising
Behavioural coping strategies:
Guarding; Resting; Asking for assistance;
Relaxation; Task persistence; Exercise/ stretch;
Seeking social support; Coping self-statements
16
(SOPA) - short version
Jensen et al., 1994,
2003
14
Attitudes associated with coping:
Personal control over pain; Appropriateness of
solicitous responses ; Appropriateness of pain
medications; Inability to function; Relationship
between pain & emotion; Medical cure exists for
pain problem; Pain signifies harm
Score range
Pain intensity 0-100
Disability estimate 0-100
Four classification levels: I low disability-low intensity;
II low disability-high intensity; III high disabilitymoderately limiting; IV high disability-severely limiting
0-24; higher score reflect greater disability
100
the completed questionnaire. Participants were offered an opportunity to be entered
into a holiday draw on returning a completed questionnaire.
Reliability analyses were conducted before missing data was imputed. These
analyses were conducted in this order so that imputed values did not artificially
increase the cronbach’s alpha18.
Internal Consistency
For the coping and attitude measures (i.e., CSQ, CPCI, SOPA), internal
consistency was calculated for each subscale. As can be seen in Table 7, the internal
consistency of each of the disability and psychological distress scales ranged from
good to excellent. However, the internal consistency for subscales of the CSQ,
CPCI, and SOPA was lower. This is likely to be because each of these subscales
contained only two items. Due to the number of and the low reliability estimates for
these subscales, only those subscales with an alpha ≥ .55 were used in the following
analyses.
Missing Data
The data was examined for missing values. Scale items were examined for
patterns of missing data. No patterns were identified. Missing data was minimal
and random. If 70% of the items for a scale were available, missing data was
replaced using an Estimated Maximisation technique for all baseline scale items,
calculated scale by scale for pain respondents. (Pain-free respondents were not
18
Reliability analysis was re-run after missing values were imputed; the same alpha values were
obtained.
Table 7
Internal Consistency for each of the Scales and Subscales (N = 453)
Scale/ Subscale
α
Pain intensity
.78
Disability Estimate
.92
Center for Epidemiologic Studies - Depression
.91
.94
Subscales of the Coping Strategies Questionnaire:
Diverting attention
.75
Reinterpreting pain sensations
.53
Catastrophising
.68
Ignoring sensations
.51
Praying/ hoping
.42
Coping self-statements
.54
Increased activities
.42
Subscales of the Chronic Pain Coping Inventory:
Guarding
.62
Resting
.63
Asking for assistance
.80
Relaxation
.57
Task persistence
.76
Exercise/ stretch
.59
Seeking social support
.71
Coping self-statements
.51
Subscales of the Survey of Pain Attitudes:
Personal control over pain
.25
Appropriateness of solicitous responses from family
.67
Appropriateness of pain medications
.46
Inability to function when in pain
.67
Relationship between pain & emotion
.71
Medical cure exists for pain problem
.48
Pain signifies harm
.11
101
102
required to complete these measures). Table 8 displays the number of items and
minimum number of items required in each scale for missing data to be replaced. As
can be seen in Table 8, less than 3% of the data were imputed on any given scale.
Table 8
Missing Data Imputed (n = 453)
7
Minimum #
items required
for imputation
5
# item
replacements
made
9
CES-D
20
14
67
0.74
Anxiety
PASS
20
14
64
0.71
Coping strategies
CPCI
16
11
97
1.34
Coping strategies
CSQ
14
10
46
0.73
SOPA
14
10
59
0.93
Construct
Scale
#
items
Pain and disability
GCPS
Depression
Pain attitudes
% possible
replacementsa
2.84
Note. GCPS: Graded Chronic Pain Scales, CES-D: Center for Epidemiologic Studies – Depression,
PASS: Pain Anxiety Symptoms Scale, CPCI: Chronic Pain Coping Inventory, CSQ: Coping
Strategies Questionnaire and SOPA: Survey of Pain Attitudes
a
% of possible replacements = (# replacements /N x # items in scale) x 100
Results
The description of pain in this sample is presented in a number of sections.
First, the demographic information for each of the pain subgroups is presented, with
reference to the comparative demographic data provided by the pain-free sample.
This is followed by a description of the experience of pain (pain severity, length, site
etc) and its influence on activities of daily living (e.g. movement, employment,
compensation seeking) for acute, chronic and intermittent pain subgroups separately,
and a comparison of these variables made between the subgroups. Last, the
influence of pain site on disability and psychological functioning is examined across
all respondents with pain.
103
Comparisons across the Pain Samples: Demographic Data
Demographic data are presented to describe each of the samples: pain-free,
acute, intermittent and chronic pain (see Table 9). Each of the groups is compared
on these demographic data. These comparisons were undertaken to examine
whether the acute, intermittent and chronic pain subgroups differed from each other,
and also whether they each differed from a pain-free sample recruited using the
same methods. Chi-square analyses were used for categorical variables (gender,
marital status, and education). Independent group ANOVAs were conducted for the
continuous variables (age and adults per household).
There were significant differences between the samples on four of the five
demographic variables (see Table 9). There were more women in each of the
groups, and a greater proportion of female respondents in the pain-free and
intermittent samples compared to the acute or chronic samples. The higher
proportion of women in the pain-free sample suggests that women are more likely to
respond to unsolicited mail questionnaires. Given this likelihood, it is more difficult
to determine whether there are more women overall in the community who
experience pain. (This will be addressed further in the Discussion). However, it
seems likely that intermittent pain is experienced by comparatively more women
than men when compared to acute or chronic pain.
The relationship status of the pain subgroups varied. Primarily, the
intermittent pain sample was more likely to be partnered (and less likely to be
divorced) than the other groups. Also, the pain-free sample was less likely to be
partnered and a higher proportion of this sample was widowed. The older pain
subgroups (intermittent and chronic pain) were the only groups who contained
widowed respondents.
104
The pain subgroups differed on highest level of education completed. In
simplest terms, there was a difference between the proportion of each pain group
who had completed tertiary education; approximately one-third each of the pain-free
and intermittent samples, one-half of the acute sample, and one-fifth of the chronic
sample. In contrast, more respondents from the chronic sample had completed Year
10 education only, in comparison with the other groups. The difference in the
educational levels may have been related to the difference in the ages between the
groups; the two older samples had fewer respondents who had completed tertiary
education. This is consistent with Australian census data that indicates older groups
are less likely to have completed tertiary education (Australian Bureau of Statistics,
2007). Post-hoc analyses examining age across the three groups indicated that the
chronic pain group was older than the acute pain and intermittent pain subgroups.
The pain-free sample was also older than the intermittent pain sample.
In summary, the overall sample contained more women and was older than
expected. While the overall sample contained a higher proportion of female
respondents than would be expected based on census estimates (67.1%, cf census
estimate of 51% female), the ratio of females reporting chronic pain was consistent
with Australian prevalence data for chronic pain (Blyth et al., 2001). Similarly, the
median age for the sample was 52.00 years (SD = 16.18), also higher than the
projected median age of 44 years for the Queensland adult population (projection for
2006; based on 2001 census data). However, the mean age for female respondents
was consistent with previous estimates (Blyth et al., 2001) (M = 51.09, CI = 49.0153.17), although the average age of male participants was higher (M = 58.28, CI =
55.79-60.77). Examination of the pain subgroups revealed there were a number of
differences between the acute, intermittent and chronic pain respondents and the
Table 9
Demographic Information compared by Pain subgroups
Demographic variable
Female (%)
Statistical comparison ∞
Pain-free
N = 348
73.5 a b
Acute pain
N = 47
59.6 a f
Intermittent pain
N = 55
79.6 e f
Chronic pain
N = 320
60.1 b e
χ² (3, n = 766) = 18.65, p < .001
66.1 d
76.1
83.3 d e
70.8 e
χ² (9, n = 766) = 24.76, p = .003
Relationship status (%)
Partnered
f
ef
e
Divorced
9.8
15.2
Widowed
11.2 a d
0.0 a
0.0 d
6.0
12.9
8.7
14.8
10.7
6.7
0.0
3.7
9.6
Year 10
23.5 d
19.6 c f
9.3 d e f
33.0 c e
Year 12
16.0
15.2
14.8
10.3
Single
1.9
12.6
Highest level of education completed (%)
Primary school
d
15.2
cf
33.3
df
χ² (12, n = 756) = 54.20, p<.001
27.6 c
TAFE or equivalent
19.2
Tertiary undergraduate / postgraduate
34.6 b
50.0 c
38.9 e
19.6 b c e
51.15 (17.24) d
47.13 (15.04) c
43.85 (13.72) d e
53.98 (14.95) c e
F(3, 759) = 7.83, p <.001
2.03 (.82)
2.32 (1.00)
2.20 (.76)
2.15 (.85)
F(3, 749) = 2.48, p = .060
Age in years: Mean (SD)
# adults in the household: Mean (SD)
∞ Some N<770 due to missing data on that item
a
difference between pain-free and acute pain groups b difference between pain-free and chronic pain groups c difference between acute and chronic pain groups
d
difference between pain-free and intermittent pain e difference between intermittent pain and chronic pain f difference between acute pain and intermittent
106
pain-free respondents. Principally, the chronic pain group were older and less likely
to have completed tertiary education. The intermittent pain group, which was the
youngest group, were more likely to be partnered than the other groups.
Description of the Experience of Pain
To characterise the nature of pain experienced by the community sample,
descriptive analyses were performed for pain characteristics (including severity,
onset, previous episodes, and location), treatment seeking behaviour, and the
influence of pain on employment, psychological well-being and daily living. These
analyses were conducted for the acute, intermittent and chronic pain subgroups
separately, and then the subgroups were compared.
Pain Variables
Participants were asked a number of questions designed to elicit a description
of their pain. Items targeted the frequency, site, and severity of their pain
experience. Table 10 presents this data.
As would be expected because of the way the pain groups were defined, most
acute and chronic pain respondents reported daily pain and had pain on the day they
completed the questionnaire, whereas only half of the intermittent pain sample
experienced pain on the day they completed the questionnaire. Respondents with
intermittent or chronic pain were more likely to report that their pain had begun
gradually whereas acute pain respondents were more likely to have pain with a
sudden onset. The acute and chronic pain respondents were more likely to report
that this was their first episode of this type of pain compared to the intermittent
sample. Both intermittent and chronic pain participants (approximately one-quarter
of each group) were more likely to nominate that they had experienced 21 or more
Table 10
Comparison of Pain Variables between Acute, Intermittent and Chronic Pain subgroups
Pain variables
Pain present today (%)
Acute pain (N = 47)
Intermittent pain (N = 55)
Chronic pain (N = 320)
91.3
52.7
94.3
Site of most severe pain*
10.6
18.2
_
Neck (%)
_
23.6
8.4
Upper back (%)
_
_
8.4
Lower back (%)
_
25.5
26.6
Shoulder/s (%)
17.0
_
_
Hand/s and wrist/s (%)
10.6
_
_
Leg/s (including knee) (%)
21.3
_
14.4
1.93 (1.45)
1.96 (1.07)
2.81 (1.68)
76.6
NA
65.0
1 month (2-90 days)
4 yrs (2 days-47 yrs)
5 yrs (15 weeks-40 yrs)
36.2
58.2
69.0
# painful sites – Mean (SD)
Pain every day
Pain duration
Median ^ (Range)
Gradual onset of pain (%)
Previous episodes of pain (%)
χ² (2, n = 417) = 79.90, p <.001
χ² (24, n = 360) = 71.77, p <.001
Head (%)
a
Statistical comparison
∆
F(2, 417) = 11.23, p <.001
χ² (1, n = 367) = 2.47, p = .116∞
_
χ² (2, n = 418) = 19.99, p < .001
χ² (6, n = 307) = 38.34, p <.001
First episode
65.9
25.0
61.4
1-5 previous episodes
25.0
30.0
9.9
6-20 previous episodes
4.5
17.5
4.5
21+ previous episodes
4.5
27.5
24.2
*Three most endorsed sites of most severe pain ∞As intermittent pain by definition did not include daily pain, this subgroup was not included in the chi-square analysis. aAs
this was the criterion on which each sample was based this comparison was not conducted ^Data on this variable was positively skewed; therefore median is reported as the
measure of central tendency ∆95 chronic pain respondents did not answer this item
108
pain episodes when compared to acute pain participants (4.5%). In this sense, the
chronic pain participants were divided, with the majority endorsing either that this
was their first episode (61%) or that they had experienced 21 or more previous
episodes (24%).
When examining the location of respondents’ primary pain site,
approximately one-quarter of the respondents in the chronic and intermittent samples
reported lower back pain. This was different to the acute sample; only 8.5%
reported low back pain as their primary pain site. Respondents in the acute sample
were more likely to report the leg region as their primary pain site. Chronic pain
respondents reported a greater number of pain sites also compared to the acute and
intermittent pain subgroups.
In terms all sites of significant pain, Figures 5a-c show that more chronic
pain participants reported pain in the lower back and legs. A greater number of acute
pain participants reported pain in the shoulder, leg, and neck regions. The
intermittent pain sample experienced more pain in the neck and shoulder region.
Using an arbitrary cut-off of 25%, it can be seen that despite some differences in the
most prevalent sites of pain for each pain group, the common sites of pain are the
legs, lower back, shoulder, neck and head.
Body site
feet & ankle/s
leg/s
hips & pelvis
stomach
chest
lower back
upper back
hand/s & wrist/s
arm/s
shoulder/s
neck
face
head
8.5
29.8
8.5
4.3
2.1
19.1
10.6
17
10.6
31.9
25.5
4.3
12.8
0
5
10
15
20
25
30
35
Endorsement frequency (%) of acute pain sample
Body site
Figure 5a. Percentage of the acute pain subgroup with pain at each body site
3.6
feet & ankle/s
leg/s
hips & pelvis
stomach
chest
lower back
upper back
hand/s & wrist/s
arm/s
shoulder/s
neck
face
head
12.7
1.8
5.5
3.6
32.7
14.5
1.8
7.3
25.5
32.7
5.5
25.5
0
5
10
15
20
25
30
35
Endorsement frequency (%) of intermittent pain sample
Figure 5b. Percentage of the intermittent pain subgroup with pain at each body site
109
Body site
110
9.1
feet & ankle/s
leg/s
hips & pelvis
stomach
chest
lower back
upper back
hand/s & wrist/s
arm/s
shoulder/s
neck
face
head
32.5
7.2
4.1
4.1
45.3
22.2
8.1
9.1
27.5
26.3
4.1
10.9
0
10
20
30
40
50
Endorsement frequency (%) of chronic pain sample
Figure 5c. Percentage of the chronic pain subgroup with pain at each body site
Seeking Treatment
Over 80% of all the pain subgroups had sought treatment from a health
professional for their pain (see Table 11). For all groups, most commonly a general
practitioner19 was consulted initially. Physiotherapists and chiropractors were the
next most common health professional initially consulted by participants.
Respondents with acute pain initially attended a physiotherapist whereas
respondents with intermittent or chronic pain were equally likely to see either type
of health professional. These figures need to be interpreted cautiously as 25% of
chronic pain respondents listed multiple responses, which could not be coded.
Two-thirds of those who had sought treatment were still receiving treatment
for their pain. Over 70% of the participants had received a diagnosis for their pain;
chronic pain respondents were more likely to have received a diagnosis (83.5%), χ²
(2, n = 418) = 7.18, p = .028.
19
Another term for general practitioner is primary care physician.
111
Table 11
Treatment-seeking Variables across the Pain subgroups
Pain variables
Sought treatment (%)
Acute pain
(N = 47)
Intermittent pain
(N = 55)
Chronic pain
(N = 320)
83.0
86.8
95.0
Practitioner from who treatment was initially sought^
General Practitioner (%)
38.2
53.1
69.2
Physiotherapist (%)
23.5
12.5
7.6
Chiropractor (%)
8.8
15.6
8.5
^ 79 chronic pain respondents listed multiple responses that were unable to be coded
Seventy-eight (24.4%) of the chronic pain sample reported that their pain
was due to an arthritis-type condition. Only one respondent from the acute sample
and two respondents from the intermittent sample had been diagnosed with arthritis.
This difference was statistically significant, χ² (2, n = 417) = 23.10, p <.001.
Influence on Employment
There were differences between the pain subgroups in terms of the effect that
their pain had on their employment. Almost 10% of the chronic pain participants
indicated that they were unemployed due to their pain condition whereas only 2% of
the acute pain respondents and none of the intermittent pain sample were
unemployed as a result of their pain condition.
However, 25% of the acute pain participants indicated that their pain had led
them to access paid leave, reduced hours or changed duties at work. In contrast,
pain had resulted in these kinds of job modifications for a smaller proportion of
intermittent (5.45%) and chronic pain participants (8.13%; see Table 12). Of those
employed, most reported not missing any work due to pain; 76.2% (n = 21) of the
112
acute pain subgroup, 67.7% (n = 34) of the intermittent pain subgroup and 63.7% (n
= 124) of the chronic pain subgroup.
Table 12
Number of Respondents whose Employment was Affected by their Pain by Pain subgroup
Employment status
Acute pain
Intermittent
Chronic pain
(N = 47)
pain (N = 55)
(N = 320)
Sick/ workers compensation leave
6
1
4
Reduced hours
2
1
11
Changed duties
1
1
11
Employment affected by pain (Total)
9
3
26
Few respondents intended to seek or were receiving compensation (see Table
13 for frequency data). There were no differences in the ratios of respondents from
each subgroup who had sought or intended to seek workers’ compensation payment,
χ² (4, n = 251) = 4.42, p = .352, or those who had sought or intended to seek
personal injury insurance, χ² (4, n = 414) = 1.28, p = .865.
Table 13
Frequency of Compensation Seeking for each Pain subgroup
Compensation status
Acute pain
Intermittent
Chronic pain
(N = 47)
pain (N = 55)
(N = 320)
Received workers’ compensation
3
1
7
Intend to seek workers’ compensation
1
0
1
Received personal injury insurance
2
2
9
Intend to seek personal injury
0
0
3
insurance
113
Psychological Health and Disability
Depression and pain-related anxiety scores provided a measure of the
psychological health of the pain subgroups. The average depression (CES-D) scores
for each of the pain subgroups is provided in Table 14; there were no differences
between the three groups, F(2, 404) = 2.92, p = .055. To determine whether the
depressive symptoms described by the pain subgroups were meaningful beyond their
pain experience20, a cut-off score of 27 was used to identify cases of depression
(Geisser et al., 1997). Use of this cut-off score indicated that 17.0% (n = 8) of the
acute, 14.5% (n = 8) of the intermittent, and 21.9% (n = 70) of the chronic pain
subgroups met the screening test criteria for significant depression.
The average pain-related anxiety (PASS) score for the chronic pain subgroup
(mean = 33.71; scale range 0-100) was similar to that reported in clinical pain
samples (McCracken & Dhingra, 2002). Similar average scores were reported by
the acute and intermittent pain subgroups, F(2, 408) = 1.21, p = .301; see Table 14
for this data. A cut-off score of 30 has been previously recommended to indicate
high levels of anxiety (Abrams et al., 2007). Re-examining the data in this way
revealed that 42.2% (n = 19) of the acute, 49.1% (n = 27) of the intermittent, and
53.1% (n = 165) of the chronic pain subgroups experienced high levels of anxiety.
Disability was assessed in two ways. The GCPS provided a classification
score taking into account pain intensity and disability, and the RMDQ assessed a
number of specific activities of daily living which respondents had difficulty
performing due to pain (daily interference). Using the GCPS classifications (see
Table 15), approximately one-third each of the acute pain and chronic pain
20
Some of the difficulties in assessing depressive symptoms in pain populations were detailed earlier
in the thesis. Recall that depression measures that include somatic symptoms, which could be caused
by pain rather than depression, may inflate estimates of depression rates.
114
Table 14
Average Scores for Psychological Well-being (depression; CES-D and anxiety; PASS)
Measures by Pain subgroup
Psychological well-being
Pain sample
Depression (CES-D)
Anxiety (PASS)
Median
IR
Median
IR
Acute pain (n = 47)
13.00
13.00
27.00
26.00
Intermittent pain (n = 55)
11.50
12.00
28.50
29.00
Chronic pain (n = 320)
15.00
17.00
32.00
34.00
Note. Median and IR (interquartile range) is reported because these data were skewed.
participants were classified as grade II (low disability – high intensity). In contrast
over half of the intermittent group were classified as grade I (low disability – low
intensity). Additionally, although respondents from each of the pain subgroups were
spread over the four classifications, the chronic pain sample contained a greater
proportion of respondents classified as Grade IV (high disability – severely
limiting), χ² (6, n = 411) = 32.82, p <.001.
Table 15
Graded Chronic Pain Scale Classifications by Pain subgroup
Acute pain
Intermittent
Chronic pain
(N = 47)
pain (N = 55)
(N = 320)
Grade
Description
N
%
N
%^
N
%†
I
low disability-low intensity
13
27.7
30
54.5
66
20.6
II
low disability-high intensity
15
31.9
14
25.5
117
36.6
III
high disability-moderately limiting
12
25.5
7
12.7
54
16.9
IV
high disability-severely limiting
7
14.9
3
5.5
73
22.8
^ Classifications could not be calculated for 1 respondent
† Classifications could not be calculated for 10 respondents
In terms of interference with daily living, the RMDQ showed that on
average, people with chronic pain reported the highest number of limitations on their
115
activities due to their pain (median = 7; IR = 8), followed by the acute pain (median
= 5; IR = 8) and then the intermittent pain subgroups (median = 3; IR = 5), F(2, 419)
= 373.09, p <.001. The intermittent pain sample reported significantly less activity
limitations than either the acute or chronic pain subgroups. The chronic and acute
pain subgroups had greater variance in scores compared to the intermittent group
also.
Table 16 presents the most commonly endorsed activities that pain interfered
with for all the pain subgroups. In addition, over one-third of the acute and chronic
samples (38.3% and 34.1%, respectively) and one-quarter of the intermittent pain
sample reported that they were more irritable due to their pain.
Table 16
The Percentage of Respondents who reported that Pain Interfered with these Daily
Activities (using the RMDQ)
Acute pain
Intermittent pain
Chronic pain
N = 47 (%)
N = 55 (%)
N = 320 (%)
Sleeping
66.0
50.9
57.8
Sitting in one position
55.3
45.5
70.9
Turning over in bed
44.7
32.7
39.4
Dressing
42.6
18.2
4.7
Undertaking heavy jobs around the house
42.6
41.8
50.6
Walking at their usual pace
38.3
27.3
50.6
Using stairs
38.3
10.9
39.7
Putting socks/ stockings on
29.8
12.7
38.4
Bending or kneeling
27.7
27.3
46.6
Activities
Coping with and Attitudes towards Pain
Strategies for coping with pain have been identified in clinical samples.
Standardised measures are available to assess the strategies that are both taught or
116
discouraged in treatment programs. It is not clear whether these same coping
strategies are used by community samples. As the reliability of the subscales of the
coping and attitude measures were low, only subscales with a cronbach’s alpha ≥ .55
were used in the following analyses.
Independent group ANOVAs were conducted comparing the acute pain,
intermittent pain and chronic pain subgroups on their endorsement of use of coping
strategies or strength of attitude (see Table 17). As can be seen, strategies to seek
support from others or ask for assistance were used infrequently. The average use of
these types of strategies across all pain subgroups was less than 3 days per week.
Similarly, participants from all pain subgroups used guarding or resting infrequently
to manage their pain, although chronic pain respondents used these two strategies
more often than the intermittent pain participants. Relaxation was also used
infrequently to manage pain by participants from all pain subgroups. Exercise and/
or stretching were used about half the time. Respondents more frequently persisted
with tasks despite pain on approximately 4 days per week. Compared to a clinical
sample (Jensen, Turner, & Romano, 2001), the current sample were less likely to
seek social support, ask for assistance, guard the painful area, or rest to cope with
their pain. Similar levels of endorsement for the task persistence items and higher
levels of endorsement particularly by the chronic pain subgroup were seen for
relaxation and exercise and/ or stretching subscales compared to the clinical sample.
Participants infrequently diverted their attention away from pain by using
thinking about pleasant experiences, and were less likely than the clinical sample to
use this coping technique (Jensen et al., 2001). Chronic pain respondents were more
like to engage in catastrophising than either the acute or intermittent pain
respondents; however, catastrophising was still endorsed on average as less than 3
Table 17
Average Endorsement of the Coping Strategies and Attitudes contained in the CPCI, CSQ and SOPA by Pain subgroup compared with the Published Means
of a Clinical Sample
Subscale
Acute pain (N = 47)
Intermittent pain (N = 55)
F
p
Clinical
sample
mean *
CPCI seeking social support^
Mean
2.02
SD
2.29
Mean
1.13
SD
1.59
Mean
1.46
SD
1.94
2.68
.070
3.05
CPCI asked for assistance^
2.52
2.32
1.66
1.78
2.23
2.24
2.13
.120
3.24
CPCI task persistence^
3.90
2.61
3.84
2.32
4.32
2.39
1.31
.270
4.21
CPCI guarded the area^
2.32
2.32
1.29 b
1.62
2.68 b
2.26
9.10
.000
4.43
b
1.71
3.03
b
2.34
8.63
.000
4.32
CPCI rested^
2.70
2.46
1.62
CPCI relaxation^
2.49
1.93
2.27
2.06
2.77
2.24
1.35
.262
2.40
CPCI exercise/ stretching^
3.74
2.74
2.85
2.29
3.64
2.33
2.79
.062
3.31
CSQ diverting attention°
1.72
1.88
2.07
1.66
2.34
1.75
2.65
.072
2.79
1.78
12.79
.000
2.47
CSQ catastrophising°
1.62
SOPA expect solicitous responses ˜
a
b
1.37
2.42
ab
1.75
1.28
1.35
1.06
1.86
1.28
1.50
1.28
2.45
.088
1.31
SOPA disabled by pain˜
1.76
1.42
1.20 b
1.05
1.69 b
1.21
3.96
.020
2.48
SOPA link between emotion and pain˜
1.49
1.24
1.93
1.42
1.91
1.38
1.94
.146
1.96
Note. Higher scores indicate greater use of strategy or stronger beliefs.
^ Maximum range = 0-7 days; halfway point = 3.5 ° Maximum range = 0-6; halfway point = 3.0 ˜ Maximum range = 0-4; halfway point = 2.0
a
Difference between the acute and chronic pain subgroups; b Difference between the intermittent and chronic subgroups
* Jensen et al. (2001)
118
on a 0-6 point scale. This finding was similar to the clinical sample mean (Jensen et
al., 2001).
On average, respondents across all pain subgroups disagreed with the
following beliefs: that their family should act in a solicitous manner towards them,
that they were disabled by pain and that there was a link between their emotions and
their pain experience. However, compared to intermittent pain participants chronic
pain respondents were more likely to agree that they were disabled by pain.
Compared to previously published subscale means in a clinical sample (Jensen et al.,
2001), this community sample was overall less likely to endorse that they were
disabled by pain. Only the acute pain subgroup was less likely to agree that there
was a link between their emotions and their pain experience compared to the clinical
sample. The mean level of endorsement for the belief that their family should act in
a solicitous manner towards them appeared higher in the current intermittent pain
and chronic pain participants when compared with a clinical sample mean.
The Influence of Pain Site on Functioning
As few pain studies use samples with heterogeneous pain sites, the
psychological well-being and disability experience of pain respondents was
examined grouped by pain site. Table 18 provides the number of respondents with
their most severe (primary) pain at each body site as well as functioning data by pain
site. As Figure 6 illustrates stomach pain was associated with greater depressive
symptoms and neck and shoulder pain fewer depressive symptoms. Pain at other
body sites appears to be associated with comparable levels of depressive symptoms.
Only the mean depression score for the participants with stomach pain is above the
depression cut-off score of 27 (Geisser et al., 1997) indicated in red on Figure 6.
60.00
Depression (CES-D)
50.00
40.00
30.00
20.00
10.00
0.00
Head
Face
Neck
Shoulder
Arm
Upper
back
Lower
back
Chest
Stomach
Leg
Site of most severe pain
Figure 6. Boxplot of depression scores by pain site
Hips/
pelvis
Hands/
Feet/
wrists
ankles
including including
fingers
toes
119
Table 18
Psychological Distress and Disability Data by Primary Pain Site
Upper
Lower
back
back
4
32
10
21.5
32
19
5
5
31.6
22.2
GCPS Grade II (%)
36.8
GCPS Grade III (%)
GCPS Grade IV (%)
Functioning
Hip/
Hand/
Feet/
pelvis
wrist
ankles
58
12
17
16
37
9.5
17
11
13.5
25
50
19
32
25
20
5
3
10.5
7.5
3
4
6
30.0
28.6
57.1
0.0
30.0
36.4
40.0
12.5
25.0
36.7
35.2
14.3
40.0
38.0
45.5
26.7
56.3
11.1
75.0
16.7
22.0
14.3
20.0
12.0
9.1
33.3
18.8
22.2
0.0
16.7
14.3
14.3
40.0
20.0
9.1
0.0
12.5
Head
Face
Neck
Shoulder
Arm
Chest
Stomach
Leg
N
22
9
42
32
103
7
6
Depression (median)
20
22
13
20
13
13
Anxiety (median)
44
34
13
24
33
Interference (median)
2
4
4.5
6
GCPS Grade I (%)
30.0
33.3
0.0
33.3
42.5
33.3
10.5
33.3
10.0
21.1
11.1
17.5
Note. Depression: Center for Epidemiologic Studies – Depression, Anxiety: Pain Anxiety Symptoms Scale, Interference: Roland Morris Disability Questionnaire, GCPS:
121
Similarly, stomach pain was associated with higher anxiety scores. This can
be seen in Figure 7. A red line has been added to the boxplot to indicate where the
cut-off score (see Abrams et al., 2007) to designate high levels of anxiety lies. In
addition to respondents with stomach pain, respondents with head, face, neck, lower
back or pelvis pain are likely to experience high levels of pain-related anxiety. (The
average anxiety score for respondents with each of these sites of pain was above the
cut-off score).
100.0
Anxiety (PASS)
80.0
60.0
40.0
20.0
0.0
Head
Face
Neck
Shoulder
Arm
Upper
back
Lower
back
Chest
Stomach
Leg
Hips/
pelvis
Hands/
Feet/
wrists
ankles
including including
fingers
toes
Site of most severe pain
Figure 7. Boxplot of anxiety scores by pain site
Table 18 also provides the median disability score on the RMDQ
(interference) for respondents at each pain site, and the percentage of each pain
group classified according into the four grades of the GCPS. The two disability
measures provide a consistent account of the association between disability and pain
122
site, with stomach pain associated with a higher median RMDQ score and high
proportion of respondents at Grade IV. For most of the other pain site groups, the
highest proportion of participants was classified as Grade II.
Discussion
This research provides preliminary data on the nature of pain experienced by
a community sample. Due to the sampling technique used, designed to achieve a
random sample of pain respondents, these results provide an important perspective
on pain in the general community that addresses a need for research that extends
beyond investigations of chronic pain patients alone. Such a perspective is
important to develop and refine transitional process models of pain, and inform
treatment and rehabilitation services.
Nature of Pain in a Community Sample
Chronic pain was reported by 19.6% of participants in this community
sample21. Although this estimate must be considered with caution, due to the low
response rate in the current study, this estimate is consistent with previous
prevalence estimates of chronic pain provided by Blyth et al. (2001; Blyth, March, &
Cousins, 2003), who reported a prevalence rate of approximately 20% in a New
South Wales sample. The consistency in the chronic pain rate found in this study
and the study by Blyth et al. is notable given the methodological differences between
the two. In this study, participation was directed primarily towards those
experiencing pain; questionnaire items focused on pain. In contrast, the New South
Wales study, while focusing on general health only, used a sampling strategy that
21
This estimate accounts for the pain status of all adults who resided in the respondent households.
123
allowed all householders an equal chance of participating (therefore providing a true
test of prevalence). The similarity of these chronic pain frequency estimates
provides an independent but confirmatory indication of the prevalence of this
condition. Further, whilst the failure to limit selection bias in the current study
might be a limitation in measuring prevalence, it also highlights a major strength of
the study – this is the first major and detailed survey of the pain experience of a
community sample in Queensland. Overall, the findings indicate that chronic pain is
a significant health problem in Queensland.
Who Experiences Pain?
Three subgroups of people with pain were identified – acute pain,
intermittent pain and chronic pain – in addition to a pain-free subgroup. The
demographic characteristics differed between each of the subgroups. In brief, the
chronic pain respondents were mostly female and older than the acute and pain-free
respondents. As there were a high percentage of female respondents in the pain-free
sample as well as the pain groups, some of the variance in gender may be due to
respondent bias; within each household, female members were more likely to
respond to the questionnaire. However, the finding of greater proportions of female
pain sufferers is consistent with other research (e.g., Blyth et al., 2001; Elliott et al.,
1999; Rustøen et al., 2004; Tripp et al., 2006). Similarly, older age has been
previously associated with chronic pain (Blyth et al., 2001; Elliott et al., 1999; Ng et
al., 2002; Rustøen et al., 2004). Prevalence of chronic pain has also been linked to
lower education (Bergman et al., 2001; Rustøen et al., 2004). Consistent with
previous research, in this sample, respondents with chronic pain were the least likely
to have completed tertiary education.
124
While it is supposition, one possible explanation for the relative youth of the
acute subgroup may be that younger adults engage in activities which are more
likely to result in acute injuries such as sporting matches and heavy trades.
Consistent with this idea, acute pain respondents were also more likely to report that
their pain had a sudden onset.
Interestingly, respondents with an intermittent pain condition were more
likely to be partnered, compared with the pain-free participants. Some research
suggests that a spouse may prolong chronic pain behaviour through secondary
reward processes (Jensen et al., 1994), however, this is yet to be demonstrated for
other pain conditions like intermittent pain.
A Picture of the Pain Experience
For those experiencing chronic pain, the lower back was the most common
site of pain. Similarly, other literature has reported that the lower back is a frequent
site of benign pain (Dionne, 1999; B. F. Walker et al., 2004). Other common painful
areas in this sample were the legs, shoulders and neck. These correspond to
common sites reported in community samples in Sweden (Bergman et al., 2001;
Brattberg, Thorslund, & Wikman, 1989) and North America (Hoffman et al., 2002).
While the most common primary pain site for the acute (i.e., shoulder) and
intermittent (i.e., neck) pain subgroups differed, there were five common pain sites
across all types of pain – legs, lower back, shoulders, neck and head.
Chronic pain respondents endorsed a greater number of pain sites on the
body compared to acute pain and intermittent pain respondents. This may be due to
the pain sensitisation process that is hypothesised to occur once pain becomes
chronic (Bement, Skyba, Radhakrishnan, & Sluka, 2003). The pain-free periods that
125
the intermittent respondents have may negate this effect, even for those with
ongoing pain conditions.
In this study, between 15-22% of the respondents with pain were classified
as having a depressive illness according to the cut-off scores provided by Geisser et
al. (1997). This figure is higher than prevalence estimates for the general Australian
population, which range from 4.2-7.4% (Australian Bureau of Statistics, 1997), and
highlights the seriousness of the problem of depression for people with pain. In
addition, some pain sites appeared to be associated with higher depressive
symptoms, particularly stomach pain. However, this figure should be interpreted
cautiously as this represented only a small number of participants.
For pain-related anxiety symptoms, the average score and distribution in the
chronic pain sample was similar to that reported in a university pain clinic sample
(M = 38.62, SD = 20.38) (McCracken & Dhingra, 2002). These results indicate that
community samples of people with chronic pain, outside a clinical setting, may
experience pain-related anxiety symptoms similar to clinical samples and this painrelated anxiety is related to their ability to function22. In addition, the acute pain
sample was similarly affected by pain-related anxiety. Two out of five people with
pain in the sample would be classified as having high levels of anxiety (Abrams et
al., 2007), and head and stomach pain seemed associated with higher levels of
anxiety.
Disability was related to the level of frequency and duration of pain, with
intermittent pain participants reporting the least impairment of daily activities due to
pain, and chronic pain respondents, the highest. The acute pain respondents fell
between these two groups. Common basic daily activities that were difficult to
22
Bivariate correlations between anxiety (PASS) scores and disability measures (RMDQ and GCPS)
revealed significant positive associations.
126
complete due to pain, included activities such as sitting in one position, sleeping,
undertaking heavy jobs around the house, walking at a usual pace, and bending or
kneeling. Again, this highlights the disruptive influence that pain has on the lives of
adults. Further, 35% of those with chronic pain were classified as high disability
(grade III and IV). These figures are higher than those reported in Canada (Tripp et
al., 2006), where only 17% reported high disability, and may be partially explained
by the use of a 3-month period to assess activity limitations which can result in a
greater portion of respondents being classified at Grades III and IV (Von Korff,
2001). However, a large-scale New South Wales study reported that 27% of their
sample was classified as Grades III and IV (Blyth, March, & Cousins, 2003; Blyth,
March, Nicholas, & Cousins, 2005). Further examination of disability in an
Australian sample is required. As would be expected, the GCPS classifications were
much lower for the intermittent pain respondents, and somewhat lower for people
with acute pain, compared to the chronic pain respondents.
Even though this sample was not recruited from a clinical population,
respondents reported their chronic pain had a significant influence on their daily life.
Pain was daily for two-thirds of the sample. The pain had led almost all to seek
treatment from a healthcare professional, and two-thirds were still receiving
treatment for their pain. General practitioners were the most commonly attended
healthcare professional as a first source of treatment, highlighting the importance of
training for managing long-term pain for general practitioners, especially in light of
other research indicating that general practitioners’ fear-avoidance beliefs about
remaining active may have a negative influence on chronic pain patients’ recovery
(Coudeyre et al., 2006).
127
Examination of the types of coping strategies used indicated that, compared
to clinical samples, these types of coping strategies were used infrequently.
Exploration of the attitudes towards pain that may underlie the use of these strategies
showed that respondents did not believe that their family should act in a solicitous
manner towards them nor did they believe that they were disabled by pain. This
may explain why participants in this study infrequently sought social support or
asked for assistance. In addition, if they did not believe they were disabled, this may
explain why resting was infrequently used as a coping strategy.
It was important to examine the relationships between pain site and
psychological distress and physical disability in this research because most research
has focused on low back pain only or clinical samples of patients with
heterogeneous pain conditions where the influence of pain site has not been
examined. As mentioned above, stomach pain was associated with greater
depressive symptoms, pain-related anxiety and disability. In addition, higher
average pain-related anxiety scores were reported by participants with pain in two
general areas of the body; head, face and neck pain, and low back, hip and pelvis
pain. In contrast, it appeared that limb pain was less anxiety producing. This may
be explained by respondents interpreting pain at the core of the body as more
threatening than pain at the extremities. While these results are preliminary, they
may indicate that some pain sites should flag clinical attention for the development
or expression of pain-related anxiety.
Strengths and Limitations of the Baseline Phase
The findings reported here need to be interpreted cautiously. The response
rate for this study was disappointing. Follow-up of non-respondents was not
128
possible because of the recruitment strategy used, which aimed to achieve a random
sample of households. Apart from the absence of participation reminders, another
reason for the low response rate may be that non-addressed mail was used. While an
effort to discriminate the questionnaire from other non-addressed mail was used
(e.g., by using official university stationery with the university logo), perhaps the
absence of a name and address on the envelope lead to the questionnaire being
discarded before it was opened. In addition, since the mail was unaddressed,
respondents may have expected that reminders would not be sent and that they could
discard the initial questionnaire without recrimination. Other research designed to
maximise response rate is encouraged with this population. Compared to census
data, it seems likely that there was a respondent bias overall towards older, female
respondents, suggesting that these results may not generalise as well to the broader
community and are probably most useful to understand the pain experience of
women. Whilst future research is needed to replicate our results and test their
generalisability, it is important to remember that other research has also reported
higher pain prevalence rates for females and older respondents. Other studies also
report better response rates from women and older adults (Elliott et al., 1999).
Regardless, the strength of this research is that it expands our knowledge of
pain in community settings and provides an initial indication of the nature of acute,
intermittent and chronic pain in Queensland. In comparison to other Australian
community studies (cf Blyth et al., 2005; e.g., Chen et al., 2003; B. F. Walker et al.,
2004), this study also targeted wellness behaviour of those with pain including an
assessment of the coping strategies that are used. This information can be used in
general practice or early intervention programs to target unhelpful beliefs (e.g., that
129
pain is separate to emotional states, which was endorsed by 46.6% of this sample).
As stated previously, this study is the first of its kind conducted in Queensland.
Chapter Summary
This study phase provided information about the demographic and pain
characteristics of people who experience acute, intermittent, and chronic pain
conditions; data that encompasses the whole spectrum of pain conditions.
Longitudinal research to explore further the spectrum of pain conditions is the next
step and the follow up data from this group is reported in Chapter 6. Further,
through consideration of the characteristics of this non-clinical chronic pain sample,
this study may inform and improve the design and delivery of chronic pain
assessment and treatment services for people who are yet to present to tertiary
referral treatment centres. Given that, as was previously argued, the most costefficient treatment is likely to be delivered to those who will make the transition
from acute to chronic pain; the next chapter explores this data using Gatchel’s
Model.
Chapter 5: Phase 1 – Baseline Questionnaires (Gatchel’s Model)
131
CHAPTER 5:
PHASE 1 – BASELINE QUESTIONNAIRES (assessing Gatchel’s Model)
Recall that the purpose of the baseline phase was twofold. The previous
chapter (Chapter 4) reported on the first aim, which was to describe the pain
experience of this community sample. This chapter presents the examination of the
Phase 1 data in order to meet the second aim for the baseline phase. This aim was to
examine Gatchel’s Model using a cross-sectional design. This is an important
introductory step as Gatchel’s Model has been exclusively examined using patient
samples. This study also provided the baseline measurement of variables believed to
be important in the development of chronic pain disability as the first stage of the
longitudinal design of this research (see Chapter 6 for the follow-up phase).
Brief Introduction
Gatchel (1991a) describes a model of the transition from acute pain to
chronic pain disability, which was developed in his work with patient samples.
However, since chronic pain patients consist of only a small proportion of people
with chronic pain, it is valuable to assess the usefulness of Gatchel’s Model in a nonclinical sample. There have been few direct tests of Gatchel’s Model; this study will
provide one of the first empirical examinations of the model.
This study provides an examination of the key concepts of Gatchel’s Model –
physical and mental de-conditioning – using a cross-sectional research design as a
preliminary test of this model. The relationships that the proposed risk factors
(catastrophising, fear-avoidance beliefs, and the belief that one will not return to
132
work) and protective factors (optimism, positive affect, perceived social support, self
efficacy, coping and pain beliefs) have with mental and physical de-conditioning
will also be examined based on the relationships suggested by Gatchel’s model.
Specifically, it was hypothesised that measures of psychological distress (a
proxy measure of mental de-conditioning) and self-reported disability (a proxy
measure of physical de-conditioning) would be positively correlated. Second, it was
hypothesised that pain duration would be positively correlated with psychological
distress and self-reported disability, and that respondents with acute pain would
report lower psychological distress and disability compared to chronic pain
respondents. Third, it was predicted that the risk factor measures would be
positively correlated and the protective factor measures would be negatively
correlated with the measures of psychological distress and self-reported disability.
Fourth, it was hypothesised that the risk and protective factors would account for
variance in disability above that accounted for by Gatchel’s variables. Finally,
whether pain and psychosocial variables can discriminate the three stages of
Gatchel’s Model was assessed.
Method
Sample
The acute pain and chronic pain subgroups only were selected from the
sample described in Chapter 4 to examine the elements of Gatchel’s Model. As was
reported in Chapter 4, 47 participants had acute pain (pain ≤ 3 months) and 320
participants had chronic pain (pain > 3 months). These two pain subgroups were
selected because both experienced constant pain (i.e., pain on more days than not).
133
Given that Gatchel’s Model is based upon patient data, this constancy criterion was
applied to simulate the severity of pain that might be seen in a clinical sample.
Measures
The questionnaire included the 12 measures described in Chapter 3 as well as
demographic and pain variables. The properties of each standardised measure are
presented in Table 19. Recall that these measures were selected to assess the four
key areas of study: two aspects were related to Gatchel’s Model (physical and
mental de-conditioning) and two represented the possible extensions to the model
(risk and protective factors).
Pain and disability variables were examined using the Graded Chronic Pain
Scales (GCPS) and the Roland and Morris Disability Questionnaire (RMDQ).
Mental de-conditioning was examined using the Center for Epidemiologic Studies
Depression scale (CES-D) and the Pain Anxiety Symptoms Scale (PASS). Risk and
protective factors were assessed using the Fear-Avoidance Beliefs Questionnaire
(FABQ), Coping Strategies Questionnaire (CSQ), Chronic Pain Coping Inventory
(CPCI), Survey of Pain Attitudes (SOPA), Pain Self efficacy Questionnaire (PSEQ),
the positive affect scale of the Affect-Balance Scale, Life Orientation Test – Revised
(LOT-R), and the Multidimensional Scale of Perceived Social Support (MSPSS).
Table 19
Description of the Measures used in Phase 1 (baseline study)
Instrument
Graded Chronic Pain
Scales (GCPS)
Author
Von Korff et al.,
1990, 1992
Concept measured
Roland and Morris
Disability Questionnaire
(RMDQ)
Roland & Morris,
1983a, 1983b
Pain-related disability; daily interference
(Physical de-conditioning)
24
0-24; higher score reflect greater disability
Center for Epidemiologic
Studies Depression scale
(CES-D)
Radloff, 1977
Depressive symptoms
(Mental de-conditioning)
20
0-60; higher scores = greater depressive symptoms
Cut-off score of 27 for depression in people with
pain (Geisser et al., 1997)
Pain Anxiety Symptoms
Scale-20 (PASS-20)
McCracken et al.,
1992
Pain-related anxiety
(Mental de-conditioning)
20
0-100; higher scores reflect greater anxiety
Cut-off score of 30 for high pain-related anxiety
(Abrams et al., 2007)
Fear-Avoidance Beliefs
Questionnaire (FABQ)
Waddell et al.,
1993
Fear-avoidance beliefs about work & physical
activity
16^
Work 0-42; higher scores = stronger fear-avoidance
beliefs
Physical activity 0-24; higher scores = stronger
fear-avoidance beliefs
Belief one will not return to work 0-6
10
0-60; higher scores = greater self efficacy
Pain Intensity
Disability
(Physical de-conditioning)
# items
7
Item: Belief that they will not return to work
Pain Self efficacy
Questionnaire (PSEQ)
Nicholas, 1989,
2007
Pain-related self efficacy
Score range
Pain intensity 0-100
Disability estimate 0-100
Four classification levels: I low disability-low
intensity; II low disability-high intensity; III high
disability-moderately limiting; IV high disabilityseverely limiting
Instrument
Life Orientation Test –
Revised (LOT-R)
Affect-Balance Scale –
positive affect
Author
Scheier et al.,
1994; Carver &
Scheier, 2003
Bradburn, 1969
Concept measured
Optimism
# items
10
Score range
0-24; higher scores = stronger optimism
Positive affect
5
0-5; higher scores = greater positive affect
Multidimensional Scale
of Perceived Social
Support (MSPSS)
Zimet et al., 1988
Perceived social support
12
1-7; higher scores = greater perceived social support
Coping Strategies
Questionnaire (CSQ) short version
Rosenstiel &
Keefe, 1983
Jensen et al.,
2003
Cognitive strategies:
Reinterpreting pain sensations; Diverting
attention; Ignoring sensations; Praying/ hoping;
Coping self-statements; Increased activities;
Catastrophising
14
Chronic Pain Coping
Inventory (CPCI) - short
version
Jensen et al.,
1995, 2003
16
(SOPA) - short version
Jensen et al.,
1994, 2003
Behavioural strategies:
Guarding; Resting; Asking for assistance;
Relaxation; Task persistence; Exercise/ stretch;
Seeking social support; Coping self-statements
Attitudes:
Personal control over pain; Appropriateness of
solicitous responses ; Appropriateness of pain
medications; Inability to function; Relationship
between pain & emotion; Medical cure exists
for pain problem; Pain signifies harm
14
^ Only 11 items are scored
136
As was reported in Chapter 4, both internal consistency and missing data
analyses were conducted with this data. These results are provided below.
Internal Consistency
Recall that the internal consistency of the GCPS, CES-D, and PASS ranged
from .78 (GCPS pain intensity) to .94 (PASS). The internal consistency for the
FABQ, PSEQ, MSPSS, LOT-R, and Positive Affect scale are reported in Table 20.
Table 20
Internal Consistency for each of the Scales (N = 367)
Scale
α
Fear-Avoidance Beliefs Questionnaire (FABQ)
.88
Pain Self efficacy Questionnaire (PSEQ)
.93
Life Orientation Test – Revised (LOT-R)
.80
Multidimensional Scale of Perceived Social Support (MSPSS)
.94
Positive Affect scale of Affect-Balance Scale (AB)
.75
As stated in Chapter 4, the internal consistency for subscales of the coping
strategy measures (i.e., CSQ, CPCI, and SOPA) were low. Due to the number of
and the low reliability estimates for these subscales, a principal components analysis
was conducted in order to derive contextually meaningful and reliable measures of
underlying coping factors (reported below), which were then used in the analyses in
place of the subscales of each of these measures.
Missing Data
Missing data analysis was reported in Chapter 4. Recall that missing data
was replaced using an Estimated Maximisation technique if 70% of the items for a
137
scale were available. Missing data replacements were calculated scale by scale.
Table 21 displays the number of items and minimum number of items required in
each scale for missing data to be replaced. As can be seen in Table 21, less than 3%
of the data were imputed on any given scale. This method of missing value
replacement was chosen because it prevented relationships between scales being
artificially inflated by using data from other scales to estimate missing data.
Table 21
Construct
Scale
#
items
# item
replacements
made
9
% possible
replacements a
7
Minimum #
items required
for imputation
5
Disability
GCPS
Depression
CES-D
20
14
67
0.74
Anxiety
PASS
20
14
64
0.71
FABQ
12
8
44
0.81
Self efficacy
PSEQ
10
7
17
0.38
Optimism
LOT-R
6^
4
11
0.26
Pain attitudes
SOPA
14
10
59
0.93
Coping strategies
CPCI
16
11
97
1.34
Coping strategies
CSQ
14
10
46
0.73
MSPSS
12
8
17
0.31
Social support
2.84
Note. GCPS: Graded Chronic Pain Scales, CES-D: Center for Epidemiologic Studies-Depression,
PASS: Pain Anxiety Symptoms Scale, FABQ: Fear-Avoidance Beliefs Questionnaire, PSEQ: Pain
Self Efficacy Questionnaire, LOT-R: Life Orientation Test-Revised, SOPA: Survey of Pain Attitudes
CPCI: Chronic Pain Coping Inventory, CSQ: Coping Strategies Questionnaire, MSPSS:
Missing data was calculated on the total data file (N = 453)
a
^ While the LOT-R contains 10 items, only 6 items are used to calculate the total score. Filler items
were not replaced.
Factor Analysis with the Coping and Attitude Subscales
As noted earlier, the subscales on the three coping questionnaires (CSQ,
CPCI, and SOPA) each consisted of very few items, with low internal consistency.
In order to derive reliable measures of the coping strategies captured by these
138
questionnaires, the 14 items of the CSQ, 16 items of the CPCI and 14 items of the
SOPA were subjected to a principal components analysis. Initial analyses indicated
that the items were factorable, KMO = .84. Parallel analysis (O'Connor, 2000) was
performed which showed that six factors had an eigenvalue above the 95%
confidence interval for eigenvalues, which would have been predicted by chance. A
six-factor principal components analysis with varimax rotation yielded a
theoretically meaningful and interpretable factor structure, accounting for 44% of
the variance in the questionnaire items. These six coping components can be seen in
Table 22. After examination of the items that loaded most strongly on each
component, the components were labelled Limiting Activities, Use of Distraction,
Influence of Emotion, Task Persistence, Catastrophising, and No Expectation for a
Cure. Factor scores were derived using the regression method.
Results
A key aim of the baseline study and the purpose of this chapter was to
examine the key concepts of Gatchel’s Model and their predicted relationships.
While cross-sectional analyses are limited in their ability to examine processes over
time, these analyses provide an important preliminary step as Gatchel’s Model has
been exclusively applied to clinical samples.
Table 22
Varimax Rotation of the Six Factor Solution for the CSQ, CPCI and SOPA items
Scale
Item
CPCI
Limited my standing time
Factor 1:
Activity
limitations
.70
Factor 2:
Use of
distraction
CPCI
Asked for help with chore
.70
CPCI
Asked for help carrying, lifting, pushing …
.68
CPCI
Lay down on a bed
.67
CPCI
Avoided activity
.66
CPCI
Talked to friend/ family for support
.62
CPCI
Rested in chair/ recliner
.59
CPCI
Got support from friend
.58
SOPA
Pain does not stop me leading a physically active life
-.55
SOPA
Pain does not need to interfere with my activity level
-.43
CSQ
See pain as a challenge & don’t let it bother me
.65
CSQ
Do something active
.62
CSQ
Think of things I enjoy doing
.60
CSQ
Replay pleasant experiences in my mind
.59
CSQ
Pretend it is not a part of me
.59
CSQ
Do something I enjoy
.54
CSQ
Ignore it
.52
CSQ
Tell myself that I can’t let pain stand in the way
.51
CSQ
Think of it as some other sensation
.48
SOPA
I have learned to control pain
.45
CSQ
Don’t pay any attention to it
.41
Factor 3:
Influence of
emotion
Factor 4:
Task
persistence
Factor 5:
Catastrophising
Factor 6: No
cure
expectation
Scale
Item
SOPA
Stress increases the pain
SOPA
Connection between emotion & pain level
Factor 1:
Activity
limitations
Factor 2:
Use of
distraction
Factor 3:
Influence of
emotion
.72
Factor 4:
Task
persistence
Factor 5:
Catastrophising
Factor 6: No
cure
expectation
.67
SOPA
When I hurt I want my family to treat me better
.55
SOPA
When I hurt I deserve to be treated with care & concern
.54
CSQ
I pray for the pain to stop
.42
CPCI
Don’t let pain interfere with activities
.66
CPCI
Don’t let pain affect what I do
.62
CPCI
Exercised to improve physical condition
.60
CPCI
Told myself that my pain will get better
.59
CPCI
Stretched the muscles where I hurt
.53
CPCI
Reminded myself that there are people worse off than I am
.49
CPCI
Focused on relaxing my muscles
.48
SOPA
There is little I can do to ease my pain
.70
CSQ
It’s terrible & never going to get any better
.65
CSQ
I can’t stand it any more
.56
SOPA
Pain is a sign that damage is being done
.54
SOPA
Do not expect a medical cure
.61
CSQ
Try to think years ahead when I have gotten rid of pain
-.55
SOPA
Trust that doctors can cure my pain
-.53
% of variance explained
Cronbach’s alpha^
14.95
11.61
5.13
4.60
4.24
3.59
.84
.78
.65
.71
.67
.41
Note. Only loading above .4 are displayed. Four items did not load ≥.4 on any component.
^ Cronbach’s alphas was calculated for each factor using the original items that loaded above .4 on that factor.
141
The key elements of Gatchel’s Model – pain duration, physical deconditioning and mental de-conditioning (hence referred to as Gatchel’s variables) –
were initially examined using correlation analysis to explore the level of relationship
between these variables. In addition, the acute pain participants and chronic pain
participants were compared on these variables. The inter-correlations between the
proposed extension variables and their correlation with Gatchel’s variables were also
assessed. This was followed with hierarchal regression analyses, which allowed the
unique contribution of each of the independent variables in the prediction of
disability to be assessed, and allowed the contribution of the extension variables to
be calculated after accounting for Gatchel’s variables. Finally, whether individuals
at each of the three stages of Gatchel’s Model could be discriminated using the pain
and psychosocial predictors was examined.
Prior to the analyses being undertaken, the data were screened for breaches
of the assumptions of these statistical analyses. Some breaches of normality were
evident. Pain duration was positively skewed (skewness = 1.71, kurtosis = 2.62).
The distribution of pain duration was made more normal by applying a square root
transformation (skewness = 0.64, kurtosis = -0.34). Analyses were conducted using
the original variable and the transformed variable. There was no difference in the
results obtained. Therefore, for ease of interpretation, the original variable is
reported. Self efficacy (PSEQ) and social support (MSPSS) were also mildly
negatively skewed. A square root transformation was applied to these variables.
However, this transformation resulted in a positive skew of a similar strength.
Therefore, these variables were used unchanged.
142
Correlations between Gatchel’s Variables
Gatchel’s variables were first examined in relation to each other. To this
end, correlation analyses were conducted with the main variables from the model –
including pain duration, level of disability, depressive symptoms, and pain-related
anxiety (see Table 23). These analyses revealed that pain duration, which is
arguably the key factor in the movement between stages of Gatchel’s Model, was
not significantly related to any other variable. As can also be seen in Table 23,
depression and anxiety scores were highly intercorrelated, and there were moderate
positive correlations among the other variables.
Table 23
Correlations between Pain Duration and Measures of Gatchel’s key constructs (n = 367)^
Pain
duration
Pain duration
Depression
Anxiety
Daily interference
Pain intensity
Global disability
1
Daily
Pain
Global
interfere.
intensity
disability
.040
.018
.074
.054
.707**
.488**
.454**
.565**
1
.521**
.480**
.579**
1
.467**
.598**
1
.587**
Depression
Anxiety
-.001
1
1
Note. Depression: Center for Epidemiologic Studies – Depression, Anxiety: Pain Anxiety Symptoms
Scale, Daily interference: Roland Morris Disability Questionnaire, Pain intensity: GCPS Graded
Chronic Pain Scales – Intensity estimate, Global disability: GCPS Graded Chronic Pain ScalesDisability estimate
^ The value of n varies due to missing data
** p<.01
143
Assessing Differences between the Acute and Chronic Pain subgroups
Independent group t-tests were conducted to examine the differences on the
mental and physical de-conditioning variables between respondents early in their
pain trajectory (Stage 1: acute pain) with those who had an established pain
condition (Stages 2 and 3: chronic pain). These comparisons were conducted to
specifically test for differences in pain experience between respondents with acute
and chronic pain. Table 24 present the results of these analyses. There were no
differences between the acute pain participants and the chronic pain participants on
each measure of physical de-conditioning. Neither were there any differences on
either measure of mental de-conditioning.
Table 24
Comparison of Gatchel’s Variables between Acute and Chronic Pain subgroups
Acute pain (N = 47)
Measure
Mean
SD
Mean
SD
Test of significance
Mental de-conditioning
Depression (CES-D)
16.33
12.31
17.82
12.23
t (350) = -.77, p =.440
Anxiety (PASS)
29.37
18.47
33.73
22.22
t (65.9) = -1.45, p =.151
Daily interference (RMDQ)
6.91
5.65
8.20
5.85
t (365) = -1.29, p =.158
Global disability (GCPS
disability estimate)
42.62
26.45
44.14
27.52
t (362) = -1.52, p =.723
Physical de-conditioning
Relationships between Gatchel’s Variables and the Proposed Extension Constructs
Correlations were conducted between Gatchel’s variables and the proposed
extension constructs – fear-avoidance beliefs, belief that one will not return to work,
self efficacy, optimism, social support, positive affect and the coping factors
(Limiting Activities, Use of Distraction, Influence of Emotion, Task Persistence,
Catastrophising, and No Expectation for a Cure) (see Table 25). Due to the large
number of analyses conducted, results were interpreted at an alpha level of .01.
144
These analyses showed that pain duration was not correlated with the risk
and protective factors (r ≤ |.075|), with the exception of weak positive correlations
with the belief that one would not return to work (r = .201), Use of Distraction
coping factor (r = .149) and the No Expectation for a Cure coping factor (r = .379).
All other significant correlations were in the expected direction; the de-conditioning
variables were negatively correlated with the protective factors and positively
correlated with the risk factors. Primarily, the strongest correlations were between
self efficacy and Gatchel’s de-conditioning variables. Self efficacy was negatively
correlated with depression, anxiety, daily interference, and global disability (r ≥ .643). Self efficacy was also negatively correlated with the Limiting Activities
coping factor (r = -.617). In addition, the Limiting Activities coping factor was
strongly positively correlated with one of the physical de-conditioning measures,
daily interference (RMDQ); r = .655.
Predicting De-conditioning: Regression Analyses
Hierarchical regression analyses were conducted to examine the relative
contribution of each of the predictor variables from Gatchel’s Model, and the risk
and protective factors on each measure of de-conditioning. Assumption testing
revealed that there were no assumption breaches. Parallel analyses were conducted
for the two disability measures (daily interference; RMDQ, and global disability;
GCPS disability estimate) and two mental de-conditioning measures (depressive
symptoms; CES-D, and anxiety; PASS). Gatchel’s variables were entered into the
regression as the first step. As the second step, the risk and protective factors were
grouped in the following way: personality characteristics (i.e., optimism and positive
affect) were entered together, social support was entered alone, pain beliefs (i.e., self
Table 25
Correlations between Measures of Gatchel’s key constructs and the Extension Variables (n = 367)^
Catastrophising
Will not return
Fear-avoidance
.379**
1
.707**
.488**
.454**
.565**
-.643**
-.512**
-.352**
-.411**
.398**
.354**
.381**
-.114
.471**
-.194**
.328**
.035
1
.521**
.480**
.579**
-.680**
-.433**
-.173*
-.304**
.562**
.432**
.449**
-.208**
.462**
-.075
.417**
-.035
1
.467**
.598**
-.667**
-.248**
-.074
-.213**
.534**
.527**
.655**
-.057
.135
-.079
.242**
.054
1
.587**
-.481**
-.304**
-.005
-.191**
.361**
.333**
.370**
-.051
.155*
-.062
.360**
.016
1
-.669**
-.253**
-.032
-.219**
.525**
.462**
.572**
-.115
.184*
-.113
.235**
.032
1
.372**
.106
.386**
-.543**
-.567**
-.617**
.251**
-.262**
-.210**
-.313**
-.087
1
.336**
.490**
-.283**
-.160*
-.123
.147*
-.231**
.221**
-.384**
-.096
1
.380**
-.081
.009
.130
.086
-.163*
.158*
-.117
-.118
1
-.166*
-.111
-.099
.288**
-.090
.220**
-.261**
-.073
1
.583**
.533**
-.081
.129
-.074
.297**
.096
1
.537**
.039
.162*
-.094
.188*
.246**
1
-.016
.035
-.056
-.044
.004
1
.044
.049
-.064
.018
Use of
No Cure
.042
Expectation
.046
Task
.060
persistence
.149*
Influence of
.057
Emotion
.201**
Distraction
.045
Limiting
-.017
Activity
.056
to work
Use of Distraction
-.075
beliefs
Limiting Activities
Positive affect
Will not return to work
Social support
Optimism
Positive affect
Self efficacy
Social support
-.050
Global
Optimism
.054
disability
Self efficacy
.074
Pain
Global disability
.018
intensity
Pain intensity
.040
Daily
Daily interference
-.001
interference
Anxiety
Anxiety
Depression
Depression
Pain duration
.008
.016
1
-.006
-.014
1
.020
Note. Depression: Center for Epidemiologic Studies – Depression, Anxiety: Pain Anxiety Symptoms Scale, Daily interference: Roland Morris Disability Questionnaire, Pain
intensity: GCPS Graded Chronic Pain Scales – Intensity estimate, Global disability: GCPS Graded Chronic Pain Scales – Disability estimate, Self efficacy: Pain Self
Efficacy Questionnaire, Optimism: Life Orientation Test – Revised, Social support: Multidimensional Scale of Perceived Social Support, positive affect: Affect-Balance
Coping factors: Limiting Activities, Use of Distraction, Influence of Emotion, Task persistence, Catastrophising, No Expectation for a Cure
^ The value of n varies due to missing data
* p<.01 ** p<.001
No Cure
-.013
Catastrophising
Scale, Fear-avoidance beliefs: Fear-Avoidance Beliefs Questionnaire, Not return to work: single item
Expectation
Catastrophising
Task
persistence
1
Influence of
Emotion
Task persistence
Use of
Distraction
Limiting
Activity
Will not return
to work
Fear-avoidance
beliefs
Positive affect
Social support
Optimism
Self efficacy
Global
disability
Pain
intensity
Daily
interference
Anxiety
Depression
Influence of Emotion
147
efficacy and the fear-avoidance beliefs) were entered together, and the coping
factors were entered together. Separate hierarchical regression analyses were
conducted for each group of risk and protective factors; these series of separate
second regression steps are referred to as steps 2A, 2B, 2C and 2D. The third step
contained all of the predictor variables. Due to the high intercorrelations amongst
the predictor variables, the predictor variables were entered in this way to separate
out the influence of each predictor type on disability.
Daily Interference: RMDQ scores
As can be seen in Table 26, mental de-conditioning variables explained
approximately 30% of the variance in the RMDQ scores, F(3, 306) = 44.26, p <.001.
Both depression and anxiety scores were significant predictors of RMDQ scores,
uniquely explaining approximately 3% and 7% of the variance in the RMDQ scores,
respectively. Pain duration was not a significant predictor of daily interference.
When examining the different combinations of the second step of predictors,
it can be seen that the personality characteristics (optimism and positive affect)23 and
social support24 were not significant predictors; depression and anxiety scores
remained significant predictors in Steps 2A and 2B. When beliefs about pain were
entered as the second step, all beliefs (self efficacy, fear-avoidance beliefs, and the
belief that one will not return to work) were significant predictors. As a group they
explained approximately 21% of additional variance above that explained by the
mental de-conditioning variables, F(3, 292) = 42.90, p <.001. The entry of the
coping factors as the second step revealed that, as a group, the coping variables
explained approximately 24% of additional variance beyond that explained by the
23
24
F(2, 293) = 1.54, p =.216
F(1, 300) = 2.99, p =.085
148
Table 26
Hierarchical Regression Analyses to Predict Disability using the RMDQ
Step
Predictor variable
B
SE
β
sr²
R²
R² change
DV: Daily Interference (RMDQ)
1
Pain duration
.011
.032 .017
_
.303
_
Depression (CES-D)
.114
.033 .233*
.027
Anxiety (PASS)
.099
.018 .360**
.065
2A Pain duration
.020
.033 .030
_
.311
.007
Depression (CES-D)
.128
.036 .262**
.030
Anxiety (PASS)
.104
.019 .379**
.071
Optimism (LOT-R)
.124
.071 .110
_
Positive affect (AB)
-.180
.219 -.047
_
2B Pain duration
.009
.032 .013
_
.307
.004
Depression (CES-D)
.133
.035 .272**
.033
Anxiety (PASS)
.094
.019 .343**
.058
_
Social support (MSPSS)
.363
.210 .089
_
2C Pain duration
-.020
.029 -.029
.514
.211**
_
Depression (CES-D)
.030
.030 .062
_
Anxiety (PASS)
.002
.019 .008
Self efficacy (PSEQ)
-.182
.028 -.430**
.072
Fear-avoidance beliefs (FABQ)
.069
.020 .200**
.021
Belief that one will not return to work
.356
.130 .151*
.013
_
2D Pain duration
-.022
.029 -.032
.547
.244**
_
Depression (CES-D)
.074
.029 .150
_
Anxiety (PASS)
.030
.020 .108
Limiting Activities
3.226
.292 .566**
.190
_
Use of Distraction
.104
.253 .017
_
.015
.321 .002
_
Task persistence
-.046
.242 -.008
Catastrophising
.919
.300 .154*
.015
_
No Expectation for a Cure
-.022
.254 .075
_
3
Pain duration
-.017
.030 -.025
.597
.294**
_
Depression (CES-D)
.042
.033 .087
_
Anxiety (PASS)
.004
.021 .014
_
Optimism (LOT-R)
.086
.060 .075
_
.055
.187 .014
_
-.320
.187 -.079
-.134
.032 -.315**
.027
_
.031
.020 .090
_
.161
.135 .068
Limiting Activities
2.163
.378 .380**
.050
_
Use of Distraction
.222
.269 .037
_
-.154
.319 -.026
_
Task persistence
.251
.245 .043
_
Catastrophising
.488
.321 .083
_
.049
.268 .008
Note. Unique variance (sr²) was calculated only for significant predictors * p<.01 ** p<.001
149
mental de-conditioning variables, F(6, 291) = 25.33, p <.001. However, only the
Limiting Activities and Catastrophising coping factors were significant predictors of
RMDQ scores, uniquely explaining 19% and 1.5% of the variance in RMDQ scores,
respectively. Both depression and anxiety scores were superseded by the entry of
the pain belief variables and the coping factors and were no longer significant
predictors in Steps 2C and 2D.
At Step 3, when all of the predictor variables were entered into the model,
the only two significant predictors were self efficacy and the Limiting Activities
factor, which accounted for approximately 3% and 5% of variance in RMDQ scores,
respectively. At Step 3, approximately 60% of the variance in RMDQ scores was
accounted for; this was an additional 29% beyond mental de-conditioning.
Global Disability: GCPS disability estimate
The same procedure was repeated for the GCPS disability estimate, with the
predictors grouped together and entered into the model separately at the second step.
Therefore Step 1 contained the mental de-conditioning variables and pain duration,
Step 2 contained the risk and protective factors grouped as in the previous analysis
and Step 3 contained all the predictor variables.
Mental de-conditioning variables explained approximately 36%; both
depression and anxiety scores were significant predictors (see Table 27). The
addition of optimism and positive affect did not improve the predictive power of the
model beyond Gatchel’s variables, F(2, 292) = 3.06, p = .049. However, each of the
other second step combinations (social support, pain beliefs, and coping factors)
each explained additional variance above that explained by Gatchel’s variables. In
combination with Gatchel’s variables, social support explained an additional 2%
150
Table 27
Hierarchical Regression Analyses to Predict Disability using the GCPS disability estimate
Step
Predictor variable
B
SE
β
sr²
R²
DV: Global disability (GCPS disability
estimate)
1
Pain duration
.144
.142 .046
_
.366
Depression (CES-D)
.686
.146 .302**
.046
Anxiety (PASS)
.444
.082 .350**
.062
2A
Pain duration
.189
.146 .061
_
.371
Depression (CES-D)
.769
.160 .338**
.050
Anxiety (PASS)
.478
.084 .378**
.070
Optimism
.771
.314 .148
_
Positive affect
-.678
.980 -.038
_
2B
Pain duration
.125
.141 .040
_
.390
Depression (CES-D)
.865
.153 .382**
.066
Anxiety (PASS)
.400
.081 .316**
.049
Social support
3.351
.912 .178**
.028
2C
Pain duration
.066
.132 .021
_
.518
Depression (CES-D)
.333
.137 .149
_
Anxiety (PASS)
.055
.085 .044
_
Self efficacy
-.819
.126 -.421**
.069
.293
.089 .185*
.018
Beliefs that one will not return to work
.566
.594 .052
_
2D
Pain duration
.088
.145 .028
_
.486
Depression (CES-D)
.587
.145 .260**
.029
Anxiety (PASS)
.176
.099 .139
_
Limiting Activities
10.630
1.439 .404**
.097
Use of Distraction
-.527
1.253 -.019
_
-.511
1.579 -.018
_
_
Task persistence
-1.083
1.190 -.040
_
Catastrophising
3.286
1.475 .120
_
.711
1.257 .026
_
3
Pain duration
.177
.143 .056
.558
Depression (CES-D)
.576
.158 .259**
.022
_
Anxiety (PASS)
.040
.099 .032
_
Optimism
.693
.288 .134
_
Positive affect
.322
.893 .018
_
Social support
.863
.891 .047
Self efficacy
-.793
.150 -.410**
.046
_
.245
.096 .154
_
Beliefs that one will not return to work
.002
.645 .000
_
Limiting Activities
3.060
1.801 .118
_
Use of Distraction
.387
1.284 .014
_
-1.739
1.522 -.064
_
Task persistence
-.076
1.166 -.003
_
Catastrophising
1.043
1.532 .039
_
-.880
1.279 -.032
R²
change
_
.005
.024**
.152**
.120**
.192**
151
compared to Gatchel’s variables alone, F(1, 300) = 13.49, p <.001. Self efficacy,
fear-avoidance beliefs and the belief that one would not return to work accounted for
an additional 15% on top of Gatchel’s variables, F(3, 292) = 30.86, p <.001. Self
efficacy and fear-avoidance beliefs were significant predictors, uniquely explaining
approximately 7% and 2% of the variance in the GCPS disability estimate,
respectively. The coping factors explained an additional 12% beyond Gatchel’s
variables, F(6, 290) = 11.66, p <.001. Of the coping factors, Limiting Activities was
the strongest and only significant predictor, explaining approximately 5% of unique
variance in the GCPS disability estimate.
When all predictors were entered into the model, approximately 56% of the
variance in the GCPS disability estimate was accounted for; this was an additional
19% beyond Gatchel’s variables. The strongest unique predictors were depression
(accounting for approximately 2% of the variance) and self efficacy (which
accounted for approximately 5% of the variance).
Depression: CES-D scores
A similar procedure was repeated for depression scores, with the predictors
grouped together and entered into the model separately at the second step. Therefore
Step 1 contained the physical de-conditioning variables and pain duration, Step 2
contained the risk and protective factors grouped as in the previous analysis and Step
3 contained all the predictor variables.
Physical de-conditioning variables explained approximately 34%; both
disability scores were significant predictors (see Table 28). Each of the other second
step combinations (personality characteristics, social support, pain beliefs, and
coping factors) each explained additional variance above that explained by Gatchel’s
variables. The addition of optimism and positive affect improved the predictive
152
power of the model beyond Gatchel’s variables, F(2, 298) = 51.02, p <.001. Both
optimism and positive affect were significant predictors, uniquely explaining
approximately 8% and 2% of the variance in depression scores, respectively. In
combination with Gatchel’s variables, social support explained an additional 9%
compared to Gatchel’s variables alone, F(1, 307) = 59.04, p <.001. Similarly, self
efficacy, fear-avoidance beliefs and the belief that one would not return to work
accounted for an additional 9% on top of Gatchel’s variables, F(3, 293) = 19.42, p
<.001. Self efficacy was a significant predictor, uniquely explaining approximately
10% of the variance in depression scores. The coping factors explained an
additional 20% beyond Gatchel’s variables, F(6, 292) = 23.35, p <.001. Of the
coping factors, Influence of Emotion, Task Persistence and Catastrophising were
significant predictors, explaining approximately 16%, 2% and 5% of unique
variance in depression.
variance in depression was accounted for; this was an additional 32% beyond
Gatchel’s variables. The strongest unique predictors were global disability,
optimism, social support, self efficacy, Influence of Emotion and Catastrophising.
Anxiety: PASS scores
This procedure was repeated with the anxiety scores as the dependent
variable. Therefore, Step 1 contained the physical de-conditioning variables and
pain duration, Step 2 contained the risk and protective factors grouped as in the
previous analysis and Step 3 contained all the predictor variables.
Physical de-conditioning variables explained approximately 38%; both
disability scores were significant predictors (see Table 29), explaining
153
approximately 6% and 10% of the variance, respectively. Each of the other second
step combinations (individual characteristics, social support, pain beliefs, and coping
factors) each explained additional variance above that explained by Gatchel’s
variables. The addition of optimism and positive affect improved the predictive
power of the model beyond Gatchel’s variables, F(2, 297) = 25.74, p <.001.
Optimism was the only significant predictor, uniquely explaining approximately 7%
of the variance in anxiety scores. In combination with Gatchel’s variables, social
support explained an additional 2% compared to Gatchel’s variables alone, F(1, 305)
= 9.56, p =.002. Self efficacy, fear-avoidance beliefs and the belief that one would
not return to work accounted for an additional 16% on top of Gatchel’s variables,
F(3, 297) = 34.40, p <.001. Self efficacy and fear-avoidance beliefs were significant
predictors, uniquely explaining approximately 9% and 4% of the variance in the
anxiety scores, respectively. The coping factors explained an additional 30%
beyond Gatchel’s variables, F(6, 295) = 47.22, p <.001. Of the coping factors,
Limiting Activities, Use of Distraction, Influence of Emotion and Catastrophising
were significant predictors, explaining approximately 4%, 3%, 18% and 12% of
unique variance in anxiety, respectively.
variance in anxiety scores was accounted for; this was an additional 34% beyond
Gatchel’s variables. The strongest unique predictors were self efficacy, fearavoidance beliefs, Limiting Activities, Use of Distraction, Influence of Emotion,
Catastrophising and No Expectation for a Cure.
154
Table 28
Hierarchical Regression Analyses to Predict Depression scores (CES-D)
Step
Predictor variable
B
SE
β
sr²
R²
R² change
DV: Depression (CES-D)
1
Pain duration
-.039
.062 -.028
_
.344
_
.500
.116 .245**
.039
Global disability (GCPS disability)
.180
.025 .407**
.106
2A Pain duration
-.078
.056 -.057
_
.503
.159**
.378
.104 .185**
.022
.145
.023 .329**
.069
Optimism (LOT-R)
-.780
.110 -.340**
.084
-1.102
.370 -.142*
.015
2B Pain duration
-.006
.058 -.005
_
.438
.094**
.446
.108 .218**
.031
.186
.023 .421**
.114
.107
-2.743
.357 -.328**
_
2C Pain duration
-.027
.063 -.019
.436
.092**
_
.082
.129 .040
.016
.081
.028 .182*
-.441
.060 -.508**
.101
.050
.042 .071
_
-.429
.285 -.089
_
_
2D Pain duration
-.076
.059 -.055
.543
.199**
_
.254
.120 .124
.290
.103
.024 .233**
Limiting Activities
1.664
.682 .142
_
_
Use of Distraction
-.949
.493 -.077
.159
5.089
.497 .413**
.015
Task persistence
-1.521
.482 -.125*
Catastrophising
3.029
.525 .249**
.051
_
.321
.511 .027
_
3
Pain duration
-.046
.056 -.032
.666
.322**
_
.111
.114 .054
.018
.088
.023 .196**
.020
Optimism (LOT-R)
-.436
.110 -.188**
_
-.509
.345 -.065
.026
-1.527
.338 -.184**
-.173
.062 -.199*
.010
_
-.035
.037 -.049
_
-.077
.252 -.016
Limiting Activities
1.436
.727 .123
_
_
Use of Distraction
.106
.491 .009
.067
3.608
.500 .293**
_
Task persistence
-.422
.455 -.035
.013
Catastrophising
1.770
.557 .147*
_
-.393
.491 -.032
155
Table 29
Hierarchical Regression Analyses to Predict Anxiety scores (PASS)
Step
1
2A
2B
2C
2D
Predictor variable
DV: Anxiety (PASS)
Pain duration
Pain duration
Optimism (LOT-R)
Pain duration
Pain duration
Pain duration
SE
β
sr²
R²
R² change
_
.056
.098
_
.040
.071
.073
_
_
.051
.100
.019
_
_
_
.376
_
.463
.087**
.391
.015*
.538
.162**
.681
.305**
.717
.341**
.011
1.072
.380
-.053
.923
.265
-1.298
.010
.035
1.026
.312
-2.041
.063
.064
.086
-.750
.359
-.657
.061
.324
.110
.204
.044
.106
.195
.042
.204
.690
.111
.204
.044
.660
.102
.210
.045
.097
.068
.463
.089
.180
.004
.294**
.390**
-.021
.253**
.335**
-.317**
.001
.014
.281**
.394**
-.139*
.025
.018
.108
-.486**
.285**
-.077
.025
.089
.092
.043
_
_
_
.101
.036
.128*
.009
6.513
-3.872
1.024
.739
.314**
-.176**
.044
.030
9.463
.744
.433**
.175
Task persistence
-.759
.721
-.035
Catastrophising
8.150
-1.828
.786
.767
.379**
.129
.050
.042
-.424
.621
-.852
-.320
.201
-.075
4.077
-2.704
.091
.186
.038
.174
.561
.542
.099
.060
.409
1.183
.799
.051
.014
.052
-.103
.045
-.059
-.207*
.158*
-.009
.196*
Limiting Activities
Use of Distraction
3
B
Pain duration
Optimism (LOT-R)
Limiting Activities
Use of Distraction
-.085
-.124*
_
.116
_
_
_
_
_
_
_
.011
.012
_
.012
.012
.087
7.424
.812 .339**
_
Task persistence
.248
.742 .012
.043
Catastrophising
5.850
.904 .274**
.012
-2.708
.792 -.125*
156
Table 30
The Final Betas for the Predictors of the Physical and Mental De-conditioning Measures
Physical de-conditioning
Daily
Global
interference
disability
Mental de-conditioning
Depression
Anxiety
Pain duration
-.025
.056
-.032
.051
.087
.259**
.054
.014
.014
.032
.196**
.052
Optimism (LOT-R)
.075
.134
-.188**
-.103
.014
.018
-.065
.045
-.079
.047
-.184**
-.059
-.315**
-.410**
-.199*
-.207*
.090
.154
-.049
.158*
.068
.000
-.016
-.009
Limiting Activities
.380**
.118
.123
.196*
Use of Distraction
.037
.014
.009
-.124*
-.026
-.064
.293**
.339**
Task persistence
.043
-.003
-.035
.012
Catastrophising
.083
.039
.147*
.274**
.008
-.032
-.032
Note. The β weights presented are those at the last step of the regression analysis.
-.125*
* p<.01 ** p<.001
Results of the Hierarchical Regressions combined
Table 30 presents the final beta weights for the each of the hierarchical
regressions conducted to examine the predictive ability of Gatchel’s variables and
the risk and protective variables to explain the physical and mental de-conditioning
variables. As can be seen in Table 30, self-efficacy is a consistent predictor of deconditioning variance. Also, many more variables accounted for unique variance in
the measures of mental de-conditioning than physical de-conditioning.
157
Comparing the 3 Stages of Gatchel’s Model
A final examination of Gatchel’s Model explored whether the three stages of
Gatchel’s Model could be discriminated on the basis of the psychosocial factors
known to be affected by pain (without reliance on pain duration). This was done by
classifying the respondents into the three stages of Gatchel’s Model on the basis of
disability, examining the univariate relationships between each predictor variable
and Gatchel’s stages and then conducting a discriminant function analysis.
Respondents were classified into the three stages of Gatchel’s Model in the
following way. As stage 3 is the end stage of disability and is associated with a total
focus on the pain experience and lack of outside interests and activities, respondents
with chronic pain who were unemployed because of their pain condition and had
grade III or IV pain severity (according to the GCPS) were categorised as Stage 3 (n
= 21). Stage 2 is the middle stage where pain has had a lesser influence on lifestyle
but pain has been ongoing. Therefore respondents with ongoing pain who did not
meet the criteria for Stage 3 were classified as being in Stage 2 (n = 197). Stage 1 is
the acute phase; acute pain respondents were classified as Stage 1 (n = 47).
Because these analyses were exploratory and because of the large number of
possible predictor variables, independent group ANOVAs were conducted as a
second step. These analyses examined the univariate relationships between each
predictor variable and Gatchel’s stages (see Table 31)25. On the basis of these
results, a direct discriminant function analysis was performed using 12 variables
(which significantly differed at the univariate level) as predictors of membership in
three groups. Predictors were Gatchel’s variables (depression, anxiety and daily
interference), pain variables (number of pain sites) and risk and protective factors
25
Because the GCPS grades were used to classify respondents into Gatchel’s stages, the GCPS pain
intensity estimates and disability estimate were not included as predictor variables.
158
(fear-avoidance beliefs, optimism, self efficacy and the coping factor scores –
Limiting Activities, Use of Distraction, Influence of Emotion, Catastrophising and
No Expectation of Cure). The data met the assumptions required for this
multivariate technique.
Two discriminant functions were calculated, with a significant overall Wilks
Lambda, Λ = .574, χ² (24, n = 237) = 126.79, p<.001, indicating that overall the
predictors could discriminate between the three groups. After removal of the first
function, the residual Wilks Lambda was significant, Λ = .815, χ² (11, n = 237) =
46.74, p<.001, indicating that there was still a strong correlation between groups and
predictors in the second function was not explained by the first function. The first
function accounted for 29.6% and the second function 18.5 % of the variability.
The functions were labelled by examining the structure matrix. The first
function was labelled Catastrophising and the second function, Managing Pain.
The discriminant function scores are plotted against in the two functions can be seen
in Figure 8. Univariate ANOVAs followed by Tukey post-hoc tests conducted with
each function revealed that the first function separated all three stages from each
other. The second function also separated all three stages from each other. The
post-hoc tests revealed and as is demonstrated in Figure 8, Stage 3 respondents
reported greater catastrophising, fewer expectations for a cure and greater number of
pain sites compared to both Stage 1 and 2 respondents. Stage 2 participants also
reported greater catastrophising, fewer expectations for a cure and greater number of
pain sites in comparison to Stage 1 respondents. Compared to Stage 1 and 3
participants, Stage 2 participants reported greater optimism, and less disability,
Table 31
Analysis of Differences between the Stages identified in Gatchel’s Transitional Model of Pain
Measures
Possible
Stage 1 (N = 47)
Stage 2 (N = 197)
Stage 3 (N = 21)
F
p
11.68
14.68
<.001
21.40
15.59
<.001
5.21
18.61
<.001
score range
Mean
SD
Mean
SD
Mean
SD
0-60
16.33 a
12.31
18.54 b
11.93
32.90 a b
18.47
b
21.42
59.70
ab
5.28
15.10
ab
Gatchel’s variables
Depression
Anxiety
0-100
29.37
a
a
34.42
b
5.65
8.10
1.93 a c
1.45
2.92 b c
1.60
4.24 a b
2.45
14.58
<.001
0-66
29.50 a
15.44
32.50 b
15.82
53.55 a b
10.53
18.90
<.001
Optimism (LOT-R)
0-24
16.17
a
5.25
5.03
.007
0-5
3.33
1-7
5.61
Daily interference
0-24
6.91
_
Pain variables
# sites
Risk & Protective factors
Limiting Activities
Use of Distraction
0-60
44.35
_
0.24 a
_
c
_
Task Persistence
_
Catastrophising
No Expectations for Cure
a
a
_
_
-0.41
-0.31
ac
0.11
-0.55
ac
-0.71
ac
5.28
14.87
1.52
3.13
1.28
5.29
14.30
42.35
1.18
1.02
b
b
ab
5.07
11.90
1.56
2.67
1.74
1.29
.278
1.55
4.96
1.68
1.50
.224
12.29
20.54
<.001
ab
12.84
23.45
0.05 b
0.93
1.29 a b
0.71
14.48
<.001
0.15
c
0.95
-0.22
0.73
6.69
.001
0.85
0.02
c
1.02
0.38
a
1.01
3.65
.027
1.14
0.03
0.98
0.21
0.86
0.92
0.27
0.07
c
bc
0.95
0.99
difference between Stage 1 and 3 b difference between Stage 2 and 3 c difference between Stage 1 and 2
0.79
0.37
.691
a
1.09
16.64
<.001
ab
0.86
15.49
<.001
0.56
0.54
160
depression and anxiety. Stage 1 participants also reported greater optimism, and less
disability, depression and anxiety in comparison to Stage 3 participants.
Gatchel's stages
4
Optimism
Stage1
Stage 2
Stage 3
Group Centroid
2
Function 2
Stage 2
Stage1
0
Stage 3
-2
Limited
activities
Daily
interference
Fear-avoid
beliefs
-4
-6
-3
-2
-1
0
1
Function 1
2
3
Catastrophising
No expectation for cure
# pain sites
Figure 8. Scatter plot of the discriminant function scores
The classification scheme, using a sample proportions as prior probabilities,
classified 79.3% of the participants correctly (see Table 32). Respondents in Stage 2
were the most correctly classified (92% correct), followed by Stage 1 (43%). To
assess the accuracy of the group predictions, the kappa coefficient was computed to
assess how well the discriminant function improved prediction above chance level.
This statistic was significant with a moderate value of .411 (p<.001). The stability
of the classification procedure was determined using cross-validation of the
classification functions. Using the leave-one-out technique, 75.5% of the cases were
161
correctly classified. However, the misclassification of the Stage 3 respondents
increased from 64.7% to 88.2%, indicating that the classification scheme was
affected by the small cell sizes and is likely to be sample specific.
Table 32
Results (%) of the Classification Scheme
Original
Cross-validated
Gatchel’s
Stages
Predicted Group Membership
Stage 1
Stage 2
Stage 3
Stage 1
42.9%
54.8%
2.4%
Stage 2
5.1%
92.1%
2.8%
Stage 3
5.9%
58.8%
35.3%
Stage 1
35.7%
61.9%
2.4%
Stage 2
5.6%
91.0%
3.4%
Stage 3
5.9%
82.4%
11.8%
Discussion
This research provides preliminary cross-sectional data on the key concepts
from Gatchel’s Model in a non-clinical sample. A key aim of this study was to
investigate the transitional model of pain proposed by Gatchel (1991a), which
suggests that disability and psychological distress will increase as pain becomes
chronic, and continue to worsen as pain becomes more severe. Contrary to the
predictions based on this model, pain duration was not associated with psychological
distress (a proxy measure of mental de-conditioning) or self-reported disability (a
proxy measure of physical de-conditioning).
Gatchel suggests that mental and physical de-conditioning influence and
interact with each other. While depression and anxiety scores did significantly
correlate with disability measures, in combination they only accounted for about
one-third of the variance in disability.
162
While the relationship between pain duration and de-conditioning was not so
clear cut, it was expected that there would be differences between the acute and
chronic pain subgroups on levels of mental and physical de-conditioning. Also
contrary to this prediction, there were no differences between the pain groups on
depressive symptoms or pain-related anxiety (i.e., mental de-conditioning) or
disability scores (i.e., physical de-conditioning). Further examination of Gatchel’s
Model using longitudinal data and additional research of this type is required to
understand the relationships between psychological distress variables and pain.
These relationships are examined further in subsequent study phases, including
longitudinally, in Chapter 6.
Gatchel’s variables in combination explained approximately one-third of the
variance in each of the disability measures. Contrary to the hypotheses for this
research phase, examination of the predictive power of the risk and protective
factors revealed that optimism and positive affect were not able to account for
variance in disability beyond Gatchel’s variables. This may be partially explained
by a possible overlap between some of the items of the CES-D and positive affect
and optimism (Pressman & Cohen, 2005). Recall that there were moderate negative
correlations between the CES-D and Affect-Balance scale (positive affect; r = .41)
and LOT-R (optimism; r = .51).
Consistent with study predictions, self efficacy, fear-avoidance beliefs, and
the Limiting Activities coping factor were significant predictors of disability. The
evidence for perceived social support, the belief that one will not return to work, and
the Catastrophising coping factor was mixed. When all the predictors were
examined simultaneously, the significant predictor in both models was self efficacy.
The Limiting Activities coping factor was a significant predictor of daily
163
interference (RMDQ scores) and depression scores was a significant predictor of
global disability (GCPS disability estimate). The robustness of these findings is
underscored by the consistency in the results of these analyses, which used two
different measures of disability as proxy measures of physical de-conditioning.
A larger proportion of the variance in the measures of mental deconditioning was explained by the predictor variables, compared to the disability
measures. The risk and protective factors which were significant predictors of
depression included optimism, positive affect, social support, self efficacy, Influence
of Emotion, Task Persistence and Catastrophising. When all predictors were
examined simultaneously, optimism, social support, Influence of Emotion and
Catastrophising remained significant predictors. When examining anxiety, the
following predictors were significant, optimism, social support, self efficacy, fearavoidance beliefs, Limiting Activities, Use of Distraction, Influence of Emotion and
Catastrophising. Of these predictors, self efficacy, fear-avoidance beliefs, Limiting
Activities, Use of Distraction, Influence of Emotion and Catastrophising remained
significant predictors when all predictors were examined together.
Finally, whether a community sample could be classified into the three stages
of Gatchel’s model in a meaningful way was examined. Two discriminant functions
which were able to discriminate between these stages were derived, which provides
some support for Gatchel’s stages. Strong optimism and low activity limitations,
fear-avoidance beliefs, depression, anxiety, catastrophising, low expectations for a
cure and less number of pain sites separated Stage 2 respondents from Stage 3
respondents. However, these results should be interpreted cautiously as the
classification scheme derived was likely to be sample specific and limited by the
small number of Stage 3 respondents in this sample. Regardless, people with
164
chronic pain who would be categorised as being at Stage 3 of Gatchel’s Model may
be over-represented in clinical samples. While the numbers of Stage 3 respondents
were small in this sample and this possibly influenced the classification scheme, this
community sample may reflect the true numbers of people who are severely disabled
by chronic pain in the community.
In conclusion, this research phase provides the first test of Gatchel’s Model
in a community sample. Although only cross-sectional data are presented here, this
data offers a preliminary examination of many of the concepts of Gatchel’s Model
and some possible extensions that could be made to this model. Based on this data,
self efficacy, the Limiting Activities coping factor and the Catastrophising coping
factor may be useful additions to assist in explaining the disability that is caused by
pain. Although, because these factors were derived from this data, it is not clear
how these concepts would be best operationalised in other research. Future research
could assess the value of the original Catastrophising subscale of the Coping
Strategies Questionnaire and 42-item Chronic Pain Coping Inventory in community
samples as the factors derived from these instruments were the most predictive of
pain disability.
In addition, this data are limited by the manner in which mental and physical
de-conditioning were operationalised. While mail questionnaires were used in order
to obtain a large non-clinical sample of people with pain, the use of questionnaires
for data collection prohibited the collection of objective measures of disability and
physical de-conditioning. To partially offset this limitation of the current study, two
standardised instruments of disability were collected in an attempt to increase
robustness of the findings; however, future research may need to explore other ways
of assessing these concepts. Similarly, as the form of mental de-conditioning is
165
reliant on characteristics of the individual as well as environmental factors, the
measures of mental de-conditioning used in this study do not capture all possible
manifestations of mental de-conditioning as described by Gatchel (1991a).
Regardless, this study has focused on the two most common manifestations of
mental de-conditioning, that is, depression and anxiety to try to capture the majority
of mental de-conditioning syndromes.
Chapter Summary
This study provided an initial examination of Gatchel’s Model in a nonclinical sample. Support was found for some but not all of the concepts and
relationships posited by the model. There was no evidence that de-conditioning had
increased with time in this sample. However, measures of mental and physical deconditioning were correlated. Some of the risk and protective factors that were
explored may be useful extensions to Gatchel’s Model, particular pain-related self
efficacy, optimism, social support, and the Influence of Emotion, Catastrophising
and the Limiting Activities coping factors. Further examination of this model is
needed using a longitudinal analysis; this analysis is presented in Chapter 6.
Chapter 6: Phase 2 – Follow-Up Questionnaires
167
CHAPTER 6:
PHASE 2 – FOLLOW-UP QUESTIONNAIRES
The purpose of this research phase was to examine Gatchel’s Model over
time using 3-month follow-up data from respondents who had participated in Phase
1 (see Chapter 5). This phase also enabled the influence and predictive value of
each of the risk and protective factors on the development of chronic pain and
chronic pain disability to be explored further, with the view to proposing possible
extensions to Gatchel’s Model.
Brief Introduction
As identified in Chapter 2, the transition from acute to chronic pain is of
particular interest to clinicians in order to implement effective early intervention for
individuals at risk of chronic pain (H. I. Andersson, 2004; Elliott et al., 2002).
Gatchel’s Model (1991a; see also Gatchel, 2005) provides a framework in which to
examine the transition from acute to chronic pain. In brief, Gatchel’s Model
describes three stages that individuals who have a serious pain experience move
through, each with worsening psychological dysfunction and physical disability.
According to this model, two processes, mental and physical de-conditioning, act in
tandem as an individual moves through the three stages.
As described in Chapter 5, a number of predictions can be made on the basis
of Gatchel’s Model. These include the assumptions that: 1) pain duration should be
positively correlated with the level of physical disability and psychological distress
experienced; 2) depressive symptoms and pain-related anxiety (used to assess mental
168
de-conditioning) and disability (physical de-conditioning) should increase for those
respondents who still have pain from baseline to 3-month follow-up as mental and
physical de-conditioning worsens; and 3) because physical and mental deconditioning processes are linked, changes in mental de-conditioning variables
should be associated with changes in physical de-conditioning variables and vice
versa.
In addition to Gatchel’s Model, other psychosocial factors have been
identified as risk factors for developing chronic pain disability; either continued
report of pain in acute conditions or worsening disability in chronic conditions. As
discussed in Chapter2, these include pain intensity (Linton & Hallden, 1997; Reid et
al., 1997; Sieben et al., 2005; White et al., 1997), the belief that pain will become
persistent (Linton & Hallden, 1997; Schultz et al., 2004; White et al., 1997),
catastrophising (Burton et al., 1995; Keefe et al., 2004; Picavet et al., 2002) and fearavoidance beliefs (Buer & Linton, 2002; Ciccone & Just, 2001; Crombez et al.,
1999; Fritz et al., 2001; Grotle, Vollestad, Veierod, & Brox, 2004; Klenerman et al.,
1995; cf Sieben et al., 2005). In Phase 1 of this research, some evidence was found
for high fear-avoidance beliefs and catastrophising in separating respondents at
Stage 2 (chronic pain) of Gatchel’s Model with respondents from Stage 3 (disabled
by chronic pain).
In terms of physiological factors, there is also evidence that a greater number
of pain sites in the acute stage (Linton & Hallden, 1997) or a greater number of
previous episodes of this type of pain condition (Sieben et al., 2005) is related to
continued pain26. The influence of these variables will be able to be explored with
26
A number of demographic variables have also been linked to increased risk of chronic pain
development (see Chapter 2). However, these are not included here because this sample may be
biased towards female sex and older participants (see Chapter 4).
169
respondents who were classified as having acute pain at Phase 1 and continue to
report pain at Phase 2.
In addition, factors that may act as protective against chronic pain
development have been identified in the context of chronic pain adjustment or
generally better health outcomes. These variables include active coping strategies
(Jensen & Karoly, 1991; Jensen et al., 1991; Koleck et al., 2006; McCracken et al.,
2005; cf Revenson & Felton, 1989), stronger pain-related self efficacy (Arnstein et
al., 1999; Sharma et al., 2003), specific pain beliefs (Jensen & Karoly, 1992),
positive affect (Zautra et al., 2005), optimism (Novy et al., 1998; Scheier & Carver,
1992), and perceived social support (Bergman et al., 2002; Evers et al., 1998; Evers
et al., 2003). The results of Phase 1 support that high optimism and low activity
limitations (a passive coping response) are able to separate respondents with chronic
pain from those who are disabled by chronic pain. Further, self efficacy was a
significant predictor of disability whereas the evidence for perceived social support
was mixed.
While the previous research phase offered a cross-sectional examination of
these variables, a longitudinal design (necessary to examine the predictive validity of
these factors over time) has not been used previously. This is especially important
as these risk and protective factors might also contribute to an expansion or
refinement of Gatchel’s Model by explaining why some people progress through the
model as predicted and others do not. Therefore, the aim of this study was to
examine the three hypotheses made on the basis of Gatchel’s Model using a
longitudinal design. Secondary aims of this study included 1) exploring the
development of chronic pain with respondents who had acute pain during Phase 1
170
and continued to have pain at follow-up, and 2) assessing the predictive value of risk
and protective factors for continuing pain in the chronic pain sample.
Method
Sample
Eighty-two percent (N = 302) of the Phase 1 participants with acute or
chronic pain nominated to be contacted for the follow-up phase of the project.
Follow-up questionnaires were returned by 218 respondents (59.40% of the original
acute or chronic pain respondents; 72.19% of those consenting to follow-up). Most
follow-up questionnaires (n = 184) were received after the initial mail-out; a further
34 participants returned a completed questionnaire after a reminder letter was mailed
(reminders were mailed out to non-responders 4 weeks after the initial mail-out).
Participants were from across all 10 postcode areas.
From the acute pain subgroup, there were 28 participants (59.57%) who
responded at follow-up (10 with continued pain and 18 for whom their pain had
resolved). From the chronic pain subgroup, there were 190 with chronic pain
(59.38%) at baseline who responded at follow-up; 163 continued to report pain at
follow-up and 27 reported that their pain had resolved. Figure 9 presents a flowchart
of how the pain groups were classified and the number of people in each pain group.
As can be seen in Figure 9, participants were divided into four categories – new
chronic pain (N = 10), resolved acute pain (N = 18), continuing chronic pain (N =
163) and resolved chronic pain (N = 27).
The demographical information for each group is presented in Table 33. As
can be seen, respondents in each category were similar to the Phase 1 subgroup from
which they originated: the new chronic and resolved acute pain groups were similar
171
to the Phase 1 acute pain subgroup and the continuing chronic pain and resolved
chronic pain groups were similar to the Phase 1 chronic pain subgroup.
Phase 1 sample
(used to examine
Gatchel’s Model)
BASELINE
47 ACUTE
320 CHRONIC
19 lost at follow-up
FOLLOW-UP
130 lost at follow-up
10 NEW CHRONIC
PAIN
18 RESOLVED
ACUTE PAIN
163 CONTINUED
CHRONIC PAIN
27 RESOLVED
CHRONIC PAIN
Figure 9. Flowchart of questionnaires returned.
Table 33
Demographic Characteristics of the Phase 2 Sample (N = 218)
New chronic
Resolved
Continuing
Resolved
pain
acute pain
chronic pain
chronic pain
(N = 10)
(N = 18)
(N = 163)
(N = 27)
49.8 ± 14.2
55.7 ± 14.3
54.1 ± 17.7
Age in years (mean ± SD)
53.6 ± 8.2
Female (%)
70
50
60.7
59.3
Primary school
0.0
0.0
10.6
3.7
Year 10
40.0
17.6
31.9
22.2
Year 12
10.0
11.8
6.9
18.5
TAFE or equivalent
0.0
23.5
30.0
37.0
University
50.0
47.1
20.6
18.5
Partnered
60.0
88.2
67.5
74.1
No partner
40.0
11.8
32.5
25.9
Education (%)^
Relationship status
^ Does not total to 100% due to missing data
172
Measures
Follow-up questionnaires contained four of the established self-report
instruments used for Phase 1 (i.e., GCPS, RMDQ, CES-D and PASS) in addition to
an item asking whether pain was still present. For greater detail about each of these
measures please refer to Chapter 3. In addition, the measures collected in Phase 1
and the coping factor scores were used as predictors in these analyses (see Chapter
5).
The same preliminary analyses as were used in Phase 1 (see Chapters 4 and
5) were calculated. Cronbach’s alpha was calculated for each scale prior to missing
data analysis. Table 34 shows, similar to the reliability calculations conducted with
the baseline data; the internal consistency of the scales at follow-up was excellent.
Table 34
Internal Consistency for each of the Scales at Phase 2
Phase 2
(n = 218)
α
Scale
Pain intensity
.85
Disability Estimate
.93
Roland & Morris Disability Questionnaire
.90
Center for Epidemiological Studies–Depression scale
.91
.94
The same basic approach to missing data analysis and imputation used in
Chapters 4 and 5 was used in Phase 2. Table 35 displays the minimum number of
173
items required in each scale for missing data to be replaced and the number of
replacements made (<1.5% for any scale).
Table 35
Missing Data Imputed (N = 218)
7
# items - minimum
available data required
(70%)
5
# item
replacements
made
3
CES-D
20
14
30
0.69
PASS
20
14
31
0.71
Scale
# items
GCPS
% possible
replacements a
0.19
Note. GCPS: Graded Chronic Pain Scales, CES-D: Center for Epidemiologic Studies-Depression,
PASS: Pain Anxiety Symptoms Scale
a
Results
As the primary purpose of this study was to examine the key concepts of
Gatchel’s Model using a longitudinal design, these results are presented first. The
psychosocial correlates of the development of chronic pain were then explored, by
focussing on the respondents who had acute pain at Phase 1 which was still present
at follow-up (and therefore considered chronic pain at Phase 2). Next, the predictive
value of the risk and protective factors for continuing pain was determined. Finally,
the course of chronic pain was plotted using measures of depression, anxiety, daily
interference, global disability, and use of coping strategies.
Examining Gatchel’s Model
Because Gatchel’s Model deals primarily with people who continue to have
pain, respondents were selected for the following analyses if they reported that their
pain was still present at follow-up. Use of this criterion resulted in a sample of 173
174
participants – called the “CHRONIC sample” – consisting of the continuing chronic
pain (N = 163) and the new chronic pain (N = 10) participants. Demographic
information is provided in Table 36. The CHRONIC sample was similar to the total
sample described in Phase 1 (see Chapter 4). The sample consisted of more women
and the majority lived with an intimate partner.
Table 36
Demographic Characteristics of the CHRONIC sample (N = 173)
Age (years)
55.7 ± 14.0
Female (%)
61.3
Education (%)^
Primary school
9.8
Year 10
31.8
Year 12
6.9
TAFE or equivalent
27.7
University
22.0
Relationship status
Partnered
67.1
No partner
32.9
^ Does not total to 100% due to missing data
Initially, analyses were undertaken to examine the relationships between
Gatchel’s variables and assess changes over time. The correlation analyses and
repeated measures t-tests are presented next.
Correlation Analyses for Gatchel’s Variables
The key elements of Gatchel’s Model – pain duration, disability, depressive
symptoms and pain-related anxiety – were examined using correlation analyses. As
described in Chapter 5, pain duration was positively skewed. However, correlation
175
analysis using a square root transformation resulted in the same results as correlation
analysis using the original variable. Therefore, the results using the original variable
are reported. Correlations were conducted first using the Phase 1 data and then
using the Phase 2 data to compare whether the correlations between the variables
changed as pain became chronic or more established (see Table 37). Analyses
revealed that pain duration was not related to any of the de-conditioning variables.
As in Phase 1, depression and anxiety scores were highly intercorrelated. At Phase
2, the two disability measures and pain intensity were also highly intercorrelated (r ≥
.55). There were moderate positive correlations among the other variables.
Table 37
Correlations between Pain Duration and Measures of Gatchel’s Variables at Baseline
(shaded) and Follow-Up (unshaded) for Chronic Pain Respondents (N = 173)^
Daily
Pain
Overall
interfer.
intensity
disability
-.027
-.022
.034
-.015
1
.673**
.440**
.444**
.555**
.008
.702**
1
.487**
.508**
.592**
Daily interference
.021
.471**
.572**
1
.444**
.560**
Pain Intensity
.073
.453**
.427**
.550**
1
.585**
Global disability
-.021
.561**
.569**
.697**
.650**
1
Duration
Depression
Anxiety
1
-.057
Depression
-.011
Anxiety
Duration
Chronic Pain Scales – Intensity estimate, Global disability: GCPS Graded Chronic Pain Scales –
Disability estimate
^ The value of N varies due to missing data
** p<.01
176
Correlations between Changes in Physical and Mental De-conditioning
Gatchel’s Model suggests that mental and physical de-conditioning processes
are linked, and influence each other over time. To determine whether changes in
mental and physical de-conditioning were related over the three-month follow-up
period, correlation analyses were conducted between the change scores for each of
the psychological distress variables (depression and anxiety) and the two disability
measures.
First, change scores were calculated. Positive scores indicate that the score
has increased from baseline to follow-up (e.g., depressive symptoms have
increased); that is, a worsening of the pain or psychological distress. Negative scores
indicate that the score has decreased from baseline to follow-up (e.g., depressive
symptoms have decreased). While the value of the mean change on each of the
measures was small27, the change scores were normally distributed with an adequate
range of scores.
Table 38 shows the correlations between the change scores for the four deconditioning variables – depression (CES-D), anxiety (PASS), daily interference
(RMDQ) and global disability (GCPS disability estimate). To control for familywise error rates, results were interpreted at an alpha level of .01. There were
moderate correlations between the changes in depression and anxiety, and changes
in the two disability measures. However, in terms of the relationships between
psychological distress and physical disability, only one of the four correlations was
significant (see the shaded section of Table 38). The correlation between anxiety
and global disability was small but statistically reliable, r = .23.
27
See also the repeated measures t-tests conducted below.
177
Changes over Time: Repeated Measures t-Tests
Gatchel’s Model suggests that both psychological distress (i.e., mental deconditioning) and disability (i.e., physical de-conditioning) will worsen over time.
Repeated measure t-tests were conducted to explore how levels of psychological
distress or disability changed over time, for the four measures of de-conditioning
(depressive symptoms, pain-related anxiety, daily interference and global disability).
Due to the number of analyses, results were interpreted at an alpha level of .01 to
minimise the rate of type I error.
Table 38
Correlation Matrix for Changes Scores on Psychological and Disability Measures for
Chronic Pain Respondents (N = 173)^
CES-D change
PASS change
CES-D
change
PASS
change
RMDQ
change
Disability est.
change
1
.333**
.154
.217
1
.121
.229*
1
.306**
RMDQ change
Disability estimate change
1
Note. CES-D Center for Epidemiologic Studies – Depression, PASS Pain Anxiety Symptoms Scale,
RMDQ Roland Morris Disability Questionnaire, GCPS Graded Chronic Pain Scales & Disability
estimate
* p<.01 ** p<.001
The results indicated that there was a small but statistically significant
decrease in depression scores from baseline to follow-up (see Table 39) but no
change in anxiety scores. In terms of disability, there were no changes in daily
interference over time. However, global disability decreased from baseline to
follow-up by approximately 5 points, on average.
Table 39
Comparing Gatchel’s Variables between Baseline and Follow-up data collection for the CHRONIC sample (N = 173)
Baseline
Dependent variables
3-month Follow-up
Test of Significance
Possible score
range
M
SD
M
SD
Depression (CES-D)
18.19
12.61
16.61
11.53
t (163) = 2.60, p = .010*
0-60
Pain-related anxiety (PASS)
34.25
21.57
32.19
21.33
t (169) = 2.17, p = .032
0-100
8.68
5.83
8.68
5.66
t (172) = 0.02, p = .984
0-24
Global disability (GCPS Disability estimate)
46.88
27.28
41.34
26.21
t (158) = 3.93, p < .001*
0-100
* Statistically significant using Bonferroni adjustment (α = .0125)
Table 40
Frequencies (%) of GCPS Classification Changes for Chronic Pain Respondents
Classification change
N
%
3 grade decrease
2
1.2
2 grade decrease
9
5.2
1 grade decrease
40
23.1
No change
65
37.6
1 grade increase
13
7.5
2 grade increase
1
0.6
Note. % does not sum to 100% because 43 respondents did not have change scores calculated. Grade decreases indicate that respondents had a reduction in the severity of
their pain. Grade increases indicate that respondents’ pain worsened.
179
To further explore the impact that the reduction in disability estimate scores
had, if any, on GCPS classification scores, change scores for the GCPS classification
were calculated and frequency statistics examined. Respondents’ changes in
disability classification ranged from a decrease of three classification levels to an
increase of two classification levels. Table 40 shows the frequency and proportion
of respondents whose GCPS classification changed over time. As can be seen, even
though all of these participants had chronic pain28, approximately 29% had
decreased pain intensity29 and/ or disability which resulted in a less severe
classification at follow-up. Regardless, the classification for the largest number of
respondents did not change (37.6%). Only 8% of the respondents were classified at
a higher level (i.e., more disabled).
Predicting the Development of Chronic Pain
One aim of this research was to examine the predictors of the development of
chronic pain from acute pain. However, thorough statistical analysis was not
possible due to the small numbers of respondents with acute pain (n = 47), and even
smaller numbers of people with acute pain who responded at follow-up (n = 28).
Only 10 respondents with acute pain at baseline reported pain at follow-up. Due to
the small numbers, only descriptive information and preliminary univariate analyses
are reported. This information is presented to offer preliminary data about who
develops chronic pain in a community sample.
The new chronic cases were compared with the acute resolved sample on
demographic data. Chi-square analyses were used for categorical variables (gender,
28
These analyses were also conducted with the continuing chronic pain respondents only to rule out
the influence of the acute to chronic transition period on the GCPS classifications; the results were
consistent with that reported above.
29
Changes in pain intensity were also examined. On average, pain intensity reduced by 7 points on
the 100-point scale from baseline to follow-up, t (171) = 6.10, p <.001.
180
marital status, education and location). Independent group t-tests were conducted
for the continuous variables (age). Because of the small sample sizes, these analyses
should be considered indicative only; an alpha level of .1 was used.
To summarise, new chronic cases (n = 10) were mostly women and were
aged 43 to 66 years. All had completed at least Year 12 education; half had
completed university education. Just over half lived with an intimate partner. Six
participants lived in regional or rural Queensland. In terms of the demographic
characteristics of this group, they were similar to the respondents with resolved
acute pain (n = 18) with regard to gender (χ² (1, n = 28) = 1.05, p =.306), age (t (26)
= .71, p =.485), education (χ² (3, n = 27) = 3.60, p =.309) and relationship status
(χ² (1, n = 27) = 2.90, p =.088); see Table 33 on page 170. However, new chronic
pain participants were more likely to be from a rural area (60.0% vs. 5.6%),
χ² (1, n = 28) = 10.16, p =.001.
Descriptive pain data are presented for the new chronic pain participants.
Table 41 provides a description of each of these participants. Independent group ttests were conducted to compare the people with acute pain who still had pain vs.
those who did not have pain at 3 months; only statistically significant differences are
discussed. The pain conditions of the group varied in terms of site of pain and
number of pain sites. New chronic pain participants had a greater number of pain
sites (3.3 vs. 1.5) than resolved acute participants at baseline, t (26) = 1.80, p =.005.
Over half experienced pain every day. Pain duration at baseline ranged from 1 week
to 3 months. None of these participants indicated having a previous pain episode of
this type. This was different from the acute resolved respondents who had an
average of 1.12 previous episodes of pain, t (16) = -1.12, p =.027, equal variances
not assumed.
Table 41
Details of the Participants who transitioned from Acute to Chronic Pain (N = 10)
ID
Gender
Marital
Education
Age
status
Home
Pain site
Diagnosis
postcode
#
Pain
Pain
# of
Depression
sites
frequency
duration
previous
score
episodes
92
Female
Partnered
Tertiary
43
4020
Shoulder/s
_
3
Everyday
7 days
0
10
267
Male
Divorced
Tertiary
48
4129
Head
Sinus
2
Most days
2 months
_
47*
301
Male
Divorced
Year 10
63
4507
Shoulder/s
_
1
Everyday
3 months
0
3
345
Female
Partnered
Tertiary
60
4507
Leg/s
_
5
Everyday
14 days
0
9
626
Female
Divorced
Year 10
48
4869
_
8
Everyday
1 month
0
55*
644
Female
Partnered
Tertiary
51
4741
Leg/s
4
Most days
2 months
_
42*
664
Female
Partnered
Year 12
47
4869
Head
Viral throat infection
that attacked all joints
Sciatic & work-related
stress
_
3
Everyday
14 days
_
34*
711
Female
Partnered
Year 10
62
4717
Feet
_
1
Everyday
3 months
_
7
750
Male
Partnered
Year 10
66
4869
Neck
3
Most days
10 days
_
11
815
Female
Divorced
Tertiary
48
4741
Head
Disc in spine slips out of
place
Occipital neuropathy &
ear infection
3
Most days
2 months
_
40*
* indicates that CES-D (depression) score was above the cut-off score for a depressive disorder
182
The two groups were compared on baseline measures of pain duration, pain
intensity, disability, pain-related anxiety, fear-avoidance beliefs, the belief that one
would not return to work, pain-related self efficacy, optimism, social support and
positive affect. Means and standard deviations are presented in Table 42. Only on
depressive symptoms were the groups different, t (11.10) = 2.145, p = .055, equal
variances not assumed. On average, there was a 14 point difference on the CES-D;
people who continued to report pain at follow-up (M = 25.8; SD = 19.6) reported
greater baseline depressive symptoms than people whose pain did not continue (M =
11.8; SD = 8.6). As the possible range on the CES-D is 0-60, this would seem to
represent a clinically relevant improvement in depressive symptoms.
Predicting Chronic Pain Participants’ Pain Outcome at Follow-up
The predictive value of the variables from Gatchel’s Model and the risk and
protective factors were investigated with regard to predicting continued chronic pain
at Phase 2. To examine these variables, the continuing chronic pain sample (N =
163) was compared with the resolved chronic pain sample (N = 27).
Resolved vs. Continued Chronic Pain
A binary logistic regression was chosen to determine if substantial
independent contributions to the continued presence of pain could be identified
amongst the proposed risk and protective factors. The outcome variable was
presence of pain at 3-month follow-up. The predictors were socio-demographic
variables (gender, whether partnered or not, education level, and age), pain variables
(number of previous episodes of this type of pain, whether respondents’ employment
had been affected by pain, whether pain was daily or not, and pain duration),
183
Gatchel’s de-conditioning variables (depression, anxiety, and disability), and risk
and protective factors (fear-avoidance beliefs, the belief that one will not return to
work, self efficacy, optimism, perceived social support, positive affect, and the
coping factors); all predictor variables were from Phase 1 data.
Table 42
Comparison of Predictor Variables between the new Chronic Pain Participants (N = 10)
and Resolved Acute Participants (N = 18)
Predictor variables
New Chronic Pain
Resolved Acute
Participants (N = 10)
Participants (N = 18)
Test of Significance
Mean
SD
Mean
SD
Pain duration
.12
.09
.10
.09
t (26) = .528, p = .602
Pain intensity
63.67
21.69
56.48
16.98
t (26) = .972, p = .304
Global disability
38.33
32.63
38.52
23.35
t (26) = -.017, p = .986
Daily interference
7.2
6.39
7.22
5.15
t (26) = -.010, p = .992
Depression
25.80
19.60
11.76
8.64
Anxiety
36.60
24.21
27.41
16.91
t (11.10) = 2.15, p =
.055 ^
t (25) = 1.161, p = .257
29.30
16.99
29.22
15.59
t (26) = .012, p = .990
Belief that one would
not return to work
Self efficacy
.60
1.90
.11
.32
42.70
17.94
46.12
12.38
t (9.29) = .808, p =
.439^
t (26) = -.586, p = .563
Optimism
15.10
6.12
15.72
5.63
t (26) = -.272, p = .788
Social support
5.19
1.60
5.84
1.23
Positive affect
3.22
1.56
3.65
1.41
t (26) = -1.195, p =
.243
t (24) = -.704, p = .488
Note. Pain intensity: GCPS Graded Chronic Pain Scales – Intensity estimate, Global disability:
GCPS Graded Chronic Pain Scales – Disability estimate, Daily interference: Roland Morris Disability
Questionnaire, Depression: Center for Epidemiologic Studies – Depression, Anxiety: Pain Anxiety
Symptoms Scale, Fear-avoidance beliefs: Fear-Avoidance Beliefs Questionnaire, Self efficacy: Pain
Self Efficacy Questionnaire, Optimism: Life Orientation Test – Revised, Social support:
Multidimensional Scale of Perceived Social Support, positive affect: Affect-Balance Scale
^ Equal variances not assumed
Univariate analyses were conducted between each predictor variable and
presence of pain to identify the important predictors for entry into the binary logistic
184
regression whilst ensuring adequate power30. Predictors that were associated with
the presence of pain at an alpha level of .1 were included in the final binary logistic
regression. The results of these analyses, chi-square tests for categorical variables
and t-tests for continuous variables are presented in Tables 43 and 44, respectively.
The final binary logistic regression included a subset of the predictors stated above,
namely pain variables (number of previous episodes of this type of pain, whether
pain was daily or most days and pain duration), key concepts from Gatchel’s Model
(anxiety and disability), and risk and protective factors (fear-avoidance beliefs, the
belief that one will not return to work, self efficacy, social support, Limiting
Activities and Catastrophising). These predictors were entered into the model in
three steps – pain variables, Gatchel’s variables, and the risk/ protective variables in
order to examine the relative variance explained by each group of variables.
Results are expressed as relative odds of presence of pain and associated
95% confidence intervals (CI). Odds ratios of 1.5 or higher for risk factors, or
equivalently, 0.67 or lower for protective factors, are reported as contextually
meaningful effect sizes. Statistical significance using an alpha level of .05 is also
reported. Contribution to variation in presence of pain was described using changes
in the Nagelkerke’s pseudo-R² statistic between the models. See Table 45 for these
results.
Only one of the pain variables and one of the protective factors were
significant predictors of continuing pain when assessed using this multivariate
approach. None of Gatchel’s variables were significant predictors when the full set
of predictors was considered simultaneously. Respondents whose pain was present
everyday at baseline were at increased risk of continuing pain at follow-up (ORadj =
30
There was insufficient power to enter all predictor variables into the binary logistic regression
analysis.
Table 43
Univariate tests of Categorical Predictor Variables (N = 190)
Predictor variable
Gender
Relationship status
Education
# of pain sites
Pain had affected employment
Pain constancy
Disability classification
Category levels
Pain resolved (%)
Pain continued (%)
14.7
13.9
15.4
11.7
5.6
10.5
31.3
17.2
13.2
22.7
14.9
5.9
16.1
8.1
23.1
9.6
34.4
11.8
12.9
4.5
85.3
86.1
84.6
87.3
94.4
89.5
68.8
82.8
86.8
77.3
85.1
94.1
83.9
91.9
76.9
90.4
65.6
88.2
87.1
95.5
Male
Female
Living with partner
No partner
Primary school
Year 10
Year 12
TAFE
Tertiary
1
2-3
4+
No
Yes
Not everyday
Everyday
Grade I
Grade II
Grade III
Grade IV
^Variables were chosen for inclusion in the logistic regression model if p < .1
* indicates the variable was included in the logistic regression model
p^
χ² (1) = 0.02, n = 190
.884
χ² (1) = 0.47, n = 190
.495
χ² (4) = 5.94, n = 187
.204
χ² (2) = 5.53, n = 189
.063*
χ² (1) = 1.59, n = 186
.216
χ² (1) = 6.37, n = 190
.012*
χ² (3) = 14.44, n = 183
.002*
Table 44
Univariate tests of Continuous Predictor Variables (N = 190)
Predictor variable
Possible
Pain resolved (N = 27)
Pain continued (N = 163)
p^
score range
Mean
SD
Mean
SD
Age
_
54.07
17.66
55.84
14.24
t (186) = -5.77
.565
Pain duration
_
5.69
8.25
9.42
9.32
t (36.79) = -2.09
.044*
Depression (CES-D)
0-60
15.46
12.20
17.69
11.95
t (178) = -.879
.381
Anxiety (PASS)
0-100
21.68
15.96
34.36
21.66
t (39.21) = -3.50
.001*
Daily interference
0-24
5.15
2.90
8.77
5.80
t (67.04) = -5.03
.001*
0-60
48.96
10.80
41.30
13.37
t (38.46) = 3.24
.002*
0-66
22.85
15.22
33.73
16.84
t (179) = -3.14
.002*
Belief that will not return to work
0-6
1.04
1.97
2.32
2.68
t (44.49) = -2.95
.005*
Optimism (LOT-R)
0-60
15.96
4.05
15.12
5.43
t (43.38) = .94
.351
Positive affect
0-5
3.35
1.60
3.16
1.54
t (179) = .56
.574
Social support
1-7
4.80
1.74
5.40
1.53
t (186) = -1.84
.068*
Limiting activities
_
-.21
.68
.11
.99
t (40.39) = -.204
.048*
Use of Distraction
_
.31
1.04
.15
.99
t (176) = .76
.450
_
-.21
.92
-.01
1.08
t (176) = -.85
.398
Task persistence
_
-.33
1.31
.12
.98
t (27.19) = -1.61
.118
Catastrophising
_
-.27
.87
.30
1.00
t (176) = -2.65
.009*
No Expectation of a cure
_
-.25
1.03
.09
.93
t (176) = -1.64
.103
^Variables were chosen for inclusion in the logistic regression model if p < .1
* indicates the variable was included in the logistic regression model
Table 45
Results of the Binary Logistic Regression Predicting Resolved (n = 27) vs. Continued Chronic Pain (n = 163)^
Categories
N
% pain
Crude OR
1 site
29
77.3
2-3 sites
67
4 + sites
Not every day
Adjusted
OR
95% CI
1.00
1.00
Referent
85.1
0.81
2.25
0.45-11.30
41
94.1
2.19
8.95
0.89-90.43
48
76.9
1.00
1.00
Referent
Every day
89
90.4
1.86
6.43*
1.30-31.95
_
154
_
0.07
1.08
0.98-1.17
Anxiety
_
186
_
0.03
1.03
0.97-1.10
Daily interference
_
190
_
0.22
1.24
0.95-1.63
Disability classification
Grade I
23
65.6
1.00
1.00
Referent
Grade II
57
88.2
0.34
1.40
0.26-7.70
Grade III
23
87.1
-2.75
0.06
0.00-1.44
Grade IV
34
95.5
-0.61
0.54
0.01-20.63
Pain variables
Number of pain sites
Pain constancy
Pain duration
Gatchel’s Model variables
Protective Factors
Self efficacy
_
188
_
-0.04
0.96
0.85-1.08
Social support
_
188
_
0.57
1.75*
1.12-2.75
_
181
_
0.03
1.03
0.97-1.11
Belief that will not return to work
_
183
_
-0.05
0.96
0.57-1.59
Limiting Activities
_
178
_
-0.89
0.41
0.12-1.37
Catastrophising
_
178
_
0.33
1.39
0.69-2.82
^ There were 53 missing cases *p < .05
188
6.43; CI 1.30-31.95), as were respondents who had greater perceived social support
(ORadj = 1.75; CI 1.12-2.75). When examining each step of the model, pain
variables explained approximately 20% of the variance in the presence of pain at
follow-up, with Gatchel’s variables contributing an additional 17%, and the risk and
protective factors contributing an additional 10%; the total model accounted
approximately 47% of the variance in the presence of pain at follow-up.
Discussion
Examining Gatchel’s Model
The primary aim of this study was to examine the elements of Gatchel’s
Model over time in a non-clinical sample of people with pain. The main premise of
the model is that people with pain will worsen over time in terms of their physical
disability (termed physical de-conditioning) and psychological distress (termed
mental de-conditioning) until they reach a state of chronic pain disability. A number
of predictions can be made on the basis of Gatchel’s Model, which are considered
below.
First, as the stages of the model are temporally defined, pain duration is
expected to be associated with the level of physical disability and psychological
distress experienced. Second, because physical and mental de-conditioning are
predicted to worsen over time, depressive symptoms and pain-related anxiety
(indicators of mental de-conditioning) should increase from baseline to 3-month
follow-up. Concurrently, it was expected that disability would worsen. Finally,
Gatchel’s Model suggests that physical and mental de-conditioning processes are
linked, and consequently it was predicted that changes in these variables would be
associated with changes in the other.
189
The results of this study were, in the main part, inconsistent with the above
predictions. Contrary to the first prediction, pain duration was not related with the
de-conditioning variables at baseline or follow-up, even when examining only
people with chronic pain.
Contrary to the prediction that de-conditioning would worsen over time,
there were no changes on some de-conditioning variables and decreases on other deconditioning variables. Small reductions were seen in depressive symptoms while
there was no change in pain-related anxiety from baseline to 3-month follow-up
(rather than increases on these variables). There was also no change in the daily
interference levels. Overall disability decreased from baseline to follow-up. When
the change in disability classification was examined in more detail, it showed that
for many respondents, their level of disability had not changed. However, for
approximately 29% of these respondents, their disability classification had dropped
at least one level. Very few respondents became more disabled during the 3-month
follow-up period. Finally, correlation analyses between the change scores on
depressive symptoms, pain-related anxiety, daily interference and global disability
showed that while change scores were related in the expected direction (i.e., they
increased over time), the associations were small.
However, the measures of mental and physical de-conditioning were
significantly associated with each other at baseline and follow-up. This offers
partial support for Gatchel’s Model, as mental and physical conditioning are posited
to be linked.
While it appears that Gatchel’s Model does not provide an adequate
framework for the acute to chronic pain transition in this community sample, a
number of alternate explanations for these results should be considered. It is
190
possible that the data suffered from restriction of range; that is, there was not
sufficient variability in the data to detect relationships. This seems unlikely because,
although the majority of these respondents were classified as having chronic pain at
baseline, the chronic sample examined here also contained the 10 new chronic cases.
In addition, pain duration ranged from 13 weeks to 37 years.
A second alternate explanation is that the follow-up period used in this
research (i.e., 3 months) may have been insufficient to capture changes in mental
and physical de-conditioning. This may be likely issue in the current sample
because the majority of the sample has experienced chronic pain for many years (see
Table 10 in Chapter 4). This suggestion may explain the variables that did not
change (pain-related anxiety and daily interference). However, it does not account
for the considerable portions of the sample who experienced decreased overall
disability or fewer depressive symptoms. These decreases in some measures of
mental and physical de-conditioning provide some evidence for three months as a
sufficient follow-up period for change to occur.
While the analyses undertaken to explore Gatchel’s variables were conducted
using a subset of the sample who continued to experience chronic pain at follow-up,
(similar to the groups reported by Gatchel), the nature of this community sample
may have been different to those seen by Gatchel and those described as providing
support for this model. Regardless, as one of the aims of this research was to assess
the value of Gatchel’s Model in a community sample, it would seem that it does not
provide a good fit with the experience of non-clinical samples.
Nonetheless, as Gatchel’s Model was first developed with references to
patients with low back pain, these analyses were re-run with only those respondents
who nominated the low back as their primary pain site. The results of these analyses
191
were mostly consistent with that already presented (so the data are not shown; see
Appendix E for these results). That is, pain duration was not related with the deconditioning variables at baseline or follow-up. Nor were the changes in mental and
physical de-conditioning scores correlated. However, there was one exception; there
was no change in depression, anxiety or disability scores for those with low back
pain. This may indicate that a 3-month follow-up period is insufficient to see the deconditioning effects of low back pain. Alternatively, there may have been
insufficient power to detect an effect as these analyses utilised a smaller sample.
Finally, as discussed in Chapter 5, this data may be limited by the manner in
which mental and physical de-conditioning were operationalised. Objective
measures of disability and physical de-conditioning were not collected and not all of
the possible manifestations of mental de-conditioning were assessed.
In summary, the results are not consistent with Gatchel’s Model as a helpful
way of understanding the acute to chronic pain transition, in particular with pain at
other sites than the lower back, in a community setting. These results also indicate
that there is considerable movement in the pain experience and level of disability of
non-clinical samples, at least in the relative short-term (that is, 3 months).
Pain Outcome at Follow-Up
Predicting Chronic Pain Development
Unfortunately, the predictive value of the proposed risk and protective
factors for the development of chronic pain could not be assessed using multivariate
techniques due to the small sample size of those who reported acute pain at baseline,
and the attrition rate at follow-up. Results indicated that the characteristics of the 10
people, who had acute pain at baseline and continued to report pain at follow-up,
192
were not different from those whose pain resolved except for residential location.
Participants who developed chronic pain were more likely to reside in a rural
location. This finding is consistent with a North American study which found that
rural residents have a higher prevalence of pain (Hoffman et al., 2002); perhaps rural
residents are more likely to develop chronic pain once an injury has occurred. One
explanation for this increased risk relates to limited access to medical care
(compared to urban residents) for rural residents; Australian data shows that rural
areas have been associated with difficulty accessing healthcare (Public Health
Division, 2000). In addition, North American research shows there are few pain
specialists in rural areas (Breuer, Pappagallo, Tai, & Portenoy, 2007), a similar
situation may also be true in Australia.
The pain conditions reported by the new chronic pain respondents were
highly varied, in terms of site of pain, number of pain sites and pain duration. Those
who developed chronic pain reported a greater number of pain sites than the
respondents whose pain resolved, which is consistent with previous research (Linton
& Hallden, 1997). Interestingly, none of the new chronic pain participants indicated
having a previous pain episode of this type. This differed from the acute resolved
sample, where respondents were more likely to report having experienced this type
of pain previously. It is also inconsistent with research that has found that the
presence of a greater number of previous episodes of pain is predictive of chronic
pain development (e.g., Sieben et al., 2005). However, over half of the new chronic
pain cases did not respond to this item, so this finding should be considered
preliminary.
For the psychosocial variables, the only difference between the people with
acute pain who developed chronic pain and those who did not was the presence of a
193
greater number or more severe depressive symptoms at baseline. Examination of the
distribution of depression scores for the people who developed chronic pain revealed
considerable variance; scores ranged from 3-55 (possible range 0-60) with a bimodal distribution. While caution needs to be exercised when interpreting and
generalising these results, they offer preliminary evidence for the influence of
depressive symptoms in the early stages of the acute to chronic pain transition for
some people only.
Significant Predictors of Continuing Chronic Pain
In addition to exploring Gatchel’s Model with this community sample, the
predictive value of the risk and protective factors was examined, as was the
predictive value of demographic and pain variables. While none of the demographic
variables predicted continued presence of pain at follow-up, at a univariate level two
pain variables were associated with the continuation of pain; respondents whose pain
continued were more likely to report their pain was present every day and a longer
duration of pain. In terms of Gatchel’s variables, worse disability on both daily
interference and global disability and higher anxiety were associated with the
continued presence of pain at follow-up. Of the risk and protective factors,
continued presence of pain was related to stronger fear-avoidance beliefs, a stronger
belief that one would not return to work, greater activity limitations, greater
catastrophising and lower self efficacy.
However, when the pain variables, Gatchel’s variables, risk variables and
protective variables were assessed in combination, only greater social support and
pain everyday were the independent predictors of continued presence of pain at
follow-up. Previously, White et al. (1997) also found that a constant temporal
194
pattern of pain over the initial 3 weeks after hospital admission was predictive of the
development of chronic pain in hospitalised patients with acute pain. The current
findings indicate that this relationship is true even once pain becomes chronic.
The findings for social support are surprising. Perceived social support was
included in this research as a protective factor. However, these results suggest that
greater perceived social support is a risk factor for continuing pain. In previous
studies, the perception of greater social support had been found to be protective
against developing more severe pain (H. I. Andersson, 2004; Bergman et al., 2002;
Evers et al., 2003) and greater disability (Evers et al., 2003; Sharma et al., 2003) in
community samples of people with chronic pain. One explanation for this finding is
that because high perceived social support was reported by the majority of the
sample, those with the highest scores had support that actually prolonged chronic
pain behaviour through secondary reward processes (Jensen et al., 1994). At this
stage, these results in the context of our research may be interpreted cautiously as
evidence that very high social support is problematic but moderate to high social
support is helpful. Alternately, it may be that people with worse pain receive more
social support as these data were collected when respondents already had pain. Data
collected prior to the onset of chronic pain is required to test these hypotheses.
Chapter Summary
The results of this study show that similar to the cross-sectional analysis of
Gatchel’s Model (see Chapter 5), little support was found for the concepts and
relationships predicted by Gatchel’s Model in this community sample. The data
provide some evidence for constant pain and higher perceived social support as
predictors of continued pain. Higher depression scores and rural location were
195
indicated as preliminary predictors of chronic pain development. However, these
results are limited by the way in which the de-conditioning syndromes were
operationalised. The processes by which these respondents did develop chronic pain
or have their pain resolve are still unclear. These issues are examined in Chapter 7,
where the results of the Phase 3 are discussed.
Chapter 7: Phase 3 – Semi-structured Interviews
197
CHAPTER 7:
PHASE 3 – SEMI-STRUCTURED INTERVIEWS
The purpose of Phase 3 was to use a qualitative approach to further explore
the two primary aims of the research (i.e., the experience of pain in a community
sample and Gatchel’s Model in a non-clinical sample). A qualitative design was
chosen to both capture the respondents’ point of view about their pain as well as
enable the underlying processes of the acute to chronic pain transition and the
consolidation of pain-related disability to be further explored. Using a qualitative
approach as the final research phase also permitted the results of the previous
questionnaire phases to be extended and re-examined.
Brief Introduction
Previously, the rationale for using a mixed-method approach was discussed
(see Chapter 3) and the quantitative data were presented in Chapters 4, 5 and 6. The
results of Phase 1 support previous research which suggests that 1 in 5 adults
experience chronic pain (Blyth et al., 2001). In this community sample, respondents
with pain reported significant levels of depression, anxiety and disability, which
were comparable to those reported in clinical samples.
In terms of Gatchel’s Model (1991a), the results thus far suggest that while
respondents at each of the three stages of the model may be able to be distinguished,
pain duration is not an important variable for discrimination of these stages. The
data supports that mental and physical de-conditioning are correlated. However,
changes over time in one de-conditioning type did not correspond with changes in
198
the other. Finally, there was evidence that activity limitations and self efficacy are
strongly linked with disability, and perceived social support and constant pain are
predictors of continued pain.
The current research phase provided an opportunity to explore the experience
of pain and Gatchel’s Model from the respondents’ viewpoint. Specifically, this
research phase aimed to examine: 1) the aspects of the pain experience that people
with pain, particularly chronic pain, believed were important and 2) the key elements
of Gatchel’s Model and the presence (or not) of possible risk and protective
mechanisms. A secondary aim of this data collection was to use this data to
facilitate interpretation of the quantitative data collected in the previous research
phases.
Method
Sample
Single semi-structured interviews were conducted with a subset of the
original sample of participants with pain (see Chapter 3 and 4 for the full details of
the original sample). One hundred and eleven participants consented to be contacted
for an interview (50.92 %of 218 participants from Phase 2).
The sample was chosen in order to draw on a range of pain experiences.
Therefore, contact with participants from all of the pain subgroups (defined in Phase
2) was attempted. The Phase 2 pain subgroups were new chronic pain (N = 10),
resolved acute pain (N = 18), original chronic pain (N = 163) and resolved chronic
pain (N = 27). Recall that respondents of the previous phases were able to be
classified in this way through their pain duration at Phase 1 and the continued
presence (or not) of pain at Phase 2. In addition, because the study of anomalous
199
cases can result in an enhanced understanding of a phenomenon (Axinn & Pearce,
2006) and because a major limitation of Gatchel’s Model is that it does not account
for recovery from pain, respondents whose pain had resolved were particularly
targeted (i.e., resolved acute pain and resolved chronic pain).
Of the 41 people31 with whom contact was attempted, approximately 50% (n
= 20) proceeded to interview (see Figure 10). Two letters were returned; marked
sender not at this address. Telephone contact was attempted on three separate
occasions for the remaining 39 participants; contact was made with 26 participants.
Non-contact occurred for the following reasons: disconnected telephone, no answer
on three separate call attempts and no response to a message left on an answering
Participants agreed to
follow up contact; n = 111
Letter of invitation mailed; n
= 41
Incorrect address; n = 2
Telephone contact
attempted; n = 39
Telephone disconnected;
n=3
Did not wish to participate;
n=4
Contact made; n = 26
No answer; n = 2
Did not attend interview;
n=2
Interview conducted;
n = 20
Original chronic pain
n=7
New chronic pain
n=1
Did not return call; n = 8
Resolved acute pain
n=4
Resolved chronic pain
n=8
Figure 10. Flowchart of the interview sample
31
Due to the discrepancy in the group sizes, all participants from the new chronic pain, resolved acute
pain and resolved chronic pain subgroups were contacted initially. From the original chronic pain
subgroup, approximately 20% were randomly chosen. A 20% selection was made in order to contact
a similar number of participants with original chronic pain (compared to the other three pain
subgroups).
200
machine or voicemail service. Of those contacted, four participants did not wish to
participate and two agreed to participate but did not attend an interview.
The interviews were completed by 12 women and 8 men, with an age range
of 42-82 years (median = 54.5 years) (see Table 46 for a detailed demographic and
pain profile of each of the interviewees). Thirteen participants were living in a
marriage or marriage-like relationship. Participants came from each of the greater
Brisbane postcode areas used in the questionnaire phase. Most interviewees (n = 13)
still experienced constant or recurrent pain at the time of the interview. The mean
number of painful sites was 2.2 (SD = 1.11). The most common sites of primary
pain were the leg/s (n = 6), lower back (n = 3) and shoulder/s (n = 3). Pain duration
(at questionnaire baseline) ranged from 1 week to 40 years (median pain duration =
1.38 years).
Comparisons between those who agreed to participate and those who were
invited but did not participate in the interviews, using independent groups t-tests
revealed that there were no differences on age (t (39) =.094, p = .926), number of
pain sites (t (39) = .992, p = .328), and pain duration (t (39) =.300, p = .765). These
comparisons were made using Phase 1 baseline data. There were also no differences
between those who agreed to participate and those who did not on their most recent
measures of depression (t (39) =.027, p = .979), anxiety (t (38) =-.480, p = .634),
global disability (t (38) =-1.43, p = .161) or pain intensity (t (39) =.-1.31, p = .199)
collected in Phase 2. These group comparisons suggest that the respondents who
participated in the interviews were similar to those who did not proceed to interview
when compared on the pain and Gatchel’s variables.
Table 46
Profile of Each of the Interviewees
Phase 1 data
Identifier Gender
Phase 2 data
Primary pain
Pain
site
duration
Pain group
Phase 3 data
Age
(yrs)
Primary pain site
Description
18
female
multiple sites
3 years
resolved chronic
55
multiple sites
Ongoing recurrent pain
24
male
upper back
40 years
resolved chronic
60
back
92
female
shoulder
7 days
new chronic
45
lower back/ hip
Pain resolved through chiropractic treatment and shoe
inserts a
119
female
head
2 months
resolved acute
63
head
Pain resolved
156*
Male
shoulder
20 years
original chronic
59
knee/ shoulder
Ongoing constant pain
215
female
shoulder
6 years
resolved chronic
64
shoulders/ wrist
231
male
leg
2 months
resolved acute
46
leg
Pain resolved
244
female
arm
8 months
resolved chronic
42
arm
Pain resolved.
283
female
wrist
2 months
resolved acute
58
wrist/ shoulder
Broken wrist in fall; resolved originally. Some recurrent
soreness recently.
305*
female
leg
13 years
original chronic
57
knee
346
male
chest
14 years
resolved chronic
77
chest
355
male
leg
20 years
original chronic
81
knee
Phase 1 data
Identifier Gender
Phase 2 data
Primary pain
Pain
site
duration
Pain group
Phase 3 data
Age
(yrs)
Primary pain site
Description
371
female
lower back
2 years
original chronic
49
multiple sites
Ongoing recurrent pain. Diagnosis of osteoarthritis
406*
male
leg
5 months
original chronic
83
leg / lower back
Ongoing constant back pain for 60 years. Some relief
for back and leg pain via anaesthetic injected into spine.
424*
female
hip
9 months
original chronic
50
hip/ shoulder
475
female
leg
6 months
resolved chronic
51
knee
Knee still tender; some recurrent episodes
497
male
neck
2 years
original chronic
54
lower back
557
female
lower back
20 years
resolved chronic
55
lower back
559
female
lower back
21 days
resolved acute
76
lower back
Successful acupuncture treatment
819
male
lower back
6 months
resolved chronic
53
lower back
Successful back surgery
Note. Identifiers are used in the Results section to denote from whom the quotes came.
*Participant formed part of the pilot testing group
a
This participant chose to speak about another chronic pain condition (lower back/ hip) which has resolved, rather than her shoulder pain that had also resolved.
203
Procedure
Letters of invitation were sent to 41 participants, followed by telephone
contact to address any questions regarding participation and to arrange a suitable
interview time. As noted in Chapter 3, most interviews were held in private rooms
at public libraries or a university campus32.
Prior to beginning each interview, it was emphasised to participants that
there were no right or wrong answers, and that the aim of the interviews was to
obtain their opinions and thoughts. Questions for the semi-structured interviews
were generated from Gatchel’s Model and the questionnaire data. In general terms,
the prescribed interview questions explored in greater depth the experience of pain
and strategies to manage the development of psychological distress and physical
disability. Interview questions were designed to be open-ended (see Chapter 3 for a
copy of the interview items). Additional prompts were used to elicit greater
description of or clarify information that interviewees provided. Participants were
also given the opportunity to comment on or re-emphasise any aspect of pain at the
close of the interview. This aspect was included as a strategy to improve the
accuracy and validity of the interpretations made from this data.
Data Coding and Analysis
The focus of the analysis of the interview data was to examine, in more
detail, individuals’ experience of developing chronic pain, in relation to possible risk
and protective mechanisms as well as mental and physical de-conditioning over
time. Specifically, the mechanisms by which risk and protective factors have their
effect and the interaction between mental and physical de-conditioning, predicted by
32
Recall that one participant’s interview took place in his home (see Chapter 3 for more details).
204
Gatchel’s Model, was also explored. The analysis was ongoing and additional
themes evolved during the coding and analysis stages. Data from all 20 interviews
were examined together.
Initially, Gatchel’s Model and the proposed risk and protective factors that
may extend Gatchel’s Model were used as the framework for thematic analysis. A
list of Gatchel’s variables was created and all data that referred to aspects of
Gatchel’s Model was identified. References to the proposed risk and protective
factors - including the variables that were assessed through the questionnaire phase,
for example, optimism, social support, or positive affect - were also identified.
Additionally, during the coding process other themes in the data were noted and
considered as they occurred. As a key aim of the research was to explore aspects or
processes that may be important in the experience of chronic pain, which have not
been captured in previous research; this process provided an extra richness that was
data driven. Analysis of this data was conducted using this deductive framework.
The data were considered in light of the results of Phase 1 and 2, and the results of
the previous phases were re-examined in light of the data from this phase.
Two (10%) of the transcripts were coded by an independent reviewer,
experienced in qualitative data analysis. Through discussion of the coding applied
and the descriptions of the codes, two codes were identified as vague. These codes
were modified accordingly. In addition, this process enabled the interviewer to
reflect on the data from another perspective in order to improve the accuracy of the
interpretation of the data.
205
Results
As per the aims of this research phase, the results are presented in a number
of sections. Initially, the experience of pain as described by interviewees is
provided. Second, references to the elements of Gatchel’s Model are detailed.
Third, an examination of the questionnaire data with consideration of this qualitative
data are presented. Additional (data driven) themes are considered throughout.
While the data are discussed in sections for the purposes of simplicity, the data was
interconnected and overlap is described.
The Experience of Pain
Descriptions of Pain
Some interviewees provided descriptions that were illustrative of various
perspectives on pain. These descriptions are presented below.
Doing battle.
One of the ways that respondents spoke about interacting with pain was
suggestive of doing battle. Like battle, participants prepared for pain episodes when
triggers for a pain flare-up were present or expected. Respondents seemed fearless
of pain if the activity or their goal was worth the pain. Interviewees spoke about the
importance of maintaining control over pain. For example, one participant (#305)
did not want to take medication because it diminished her ability to stay in control.
Similarly, one participant who no longer had pain compared managing pain
episodes to managing a business problem; an analogous concept may be applied to
planning warfare. Accordingly, pain should be examined and analysed, and the
appropriate action steps implemented to remove the problem of pain.
206
I think, like if you’ve got a business problem, I supervise a [large
manufacturing] plant … and if I have a problem, you have to solve it
professionally. And your pain is a similar type of issue. Attack it like a business
problem with bringing in the best advice, taking the right steps, making an
action plan, and following it. You have to take [pain] on like a project. [#231,
male, resolved leg pain]
New love.
In contrast, pain was described by another participant as being like new love.
While, love has positive connotations (unlike battle), it was the attention consuming
aspects of love that aligned with the pain experience. This resemblance is more
obvious if the pain is interpreted as a precursor to death or serious injury as it was by
this participant.
Describing pain, it’s like love. It’s a rather outlandish description. But love is
all overwhelming, all possessing. When you fall in love, you can think of one
thing only – what a wonderful man, what a beautiful woman. Pain is a bit the
same. It overwhelms you. You think of nothing but that pain. It’s uppermost in
your mind. [#346, male, chest pain]
Lighthouse.
The interviewee who described pain like love also described pain as a
lighthouse. In conjunction with the overwhelming nature of pain, pain was seen as a
life-threatening warning. Consequently, such a warning would compel attention. As
above, this point of view was consistent with pain being an antecedent to dying.
It’s hard to know how to describe pain. It’s like a lighthouse that shines light on
the rocks. It’s a warning. [#346, male, chest pain]
207
Co-existence (with the gods).
Finally, a number of interviewees spoke about co-existing with pain. This
entailed compromising with the dictations of pain. It reminded the interviewer of
living alongside the gods in Greek mythology: the reactions or moods of the gods
could be difficult to predict but within that framework, humans do what they can to
appease them or to not upset them in the first place.
One participant (#557) specified that she did not ignore her pain; neither did
she let it totally dictate her life. Through listening to her body and her pain and
recognising when her back was tender, this interviewee was able to adjust her
activities for that day so that she could still attend another future valuable endeavour
in the days to come. A second interviewee described the compromise with pain as
follows.
So provided I can live a life that is not too debilitating I’ve learned to live with
the pain, I suppose, when it happens. And um I’m doing a lot better than a
couple of the specialists … [they] suggested that I would be in a wheelchair by
the time I was 40, 45 max. Well, I’m well beyond 10 years on that and I’m quite
happy to keep out of [a wheelchair] thank you very much. So we’ll see how that
goes as well. [#156, male, knee & shoulder pain]
Consistent with this view, pain was often discussed in a personified form –
pain was able to become upset, to become aggravated and to be vengeful. It seemed
important to “respect” pain in order to ease it.
[Pain] goes if you don’t keep annoying it [#557, female, back pain]
208
Part of getting older.
Participants spoke about some pain and disability as just being part of getting
older. Within that framework of becoming more debilitated, pain and some of its
associated limitations were viewed as “normal” and “expected”.
I just acknowledge that it's now part of arthritis and that obviously I have got
arthritis in other parts of my body, not just in that hip … I just accept that it's
part of getting older, yeah. I don't let it worry me, much. I just accept it's
there. [#559, female, resolved back pain]
Influence of Pain on Self
Even within some of the descriptions provided above, respondents talked
specifically about the influence of their pain on themselves and their lives. The
various types of pain (i.e., constant, episodic and resolved) seemed to be related to
the influence pain had on the individual. Therefore, participants with each type of
pain are grouped together. At the end of this section, two respondents who stood out
as suffering with their pain are described.
Constant pain “Pain doesn’t rule my life”
Respondents, particularly those who experienced constant pain, highlighted
the difference between being cautious or careful and managing pain, and conversely,
letting pain rule their life. Pain and pain flare-ups were often viewed as inevitable.
Interviewees spoke about having to bear their pain and not give up or treating their
pain as a challenge to be risen up against.
[Apart from your pain, do you think other things have changed for you because
you have had these painful experiences?] Yes, only in the way that I can't be as
vigorous as what I would do. Like, the bushwalking, I used to be like a little
mountain goat, where you can jump from rock to rock … whereas if I do that
209
now, my ankle will give in very quickly; that jarring motion of jumping. So it
has, but [pain] doesn't stop me. It doesn't stop me. That's the difference. [#18,
female, multiple sites]
So I didn’t let that stop me. I did know that it was going to be an issue, so I just
planned accordingly. … you look at what’s most important, and you enjoy what
you need to do. So I enjoyed that day and dealt with it afterwards. [Pain]
doesn’t rule my life but it does sometimes slow it down a little. [#497, male,
back pain]
Since pain was accepted as part of everyday life, whether an activity would
cause pain or not was not a determining factor in decision making. Often
interviewees listed activities or roles that they continued to play despite pain. This
was sometimes discussed in a matter-of-fact way; sometimes it seemed to be a
matter of pride. For example, one interviewee spoke about mending a carport roof
despite pain. He believed that completing this task was more important than the
pain it would cause. In addition, many respondents spoke about not prioritising pain
over hobbies or activities that were highly prized (e.g., cake decorating, gardening).
Working to earn a wage to support their family was also often prioritised over
experiencing pain.
But [pain] hasn’t stopped me playing sport. It hasn’t stopped my work. It hasn’t
stopped social interaction or anything like that. [#24, male, back pain]
I love gardening so I just do it anyway whether I have pain or not. [#424,
female, shoulder & hip pain]
Despite claims that pain did not rule the lives of these participants, pain did
have some effects. (For example, see the quote above from respondent #497).
These effects seemed to be far reaching; affecting home life, work life and
relationships. For example, one interviewee (#305) claimed that she had lost trust in
people as a result of her pain experience; that she could not rely on others to treat her
210
well. Interviewees appeared to be engaged in a constant juggle to maintain a
balance between achieving sufficient quality of life and minimising pain.
When I do things that, perhaps I regret having done; [pain] will get
particularly bad; when I just need to manage it with painkillers and resting. Yes
so that’s basically it. There are things I can’t do such as mowing. I’ll get a
mower man in to mow. I can do it. But I would regret it the next day. I would
not be able to do the things that I’d like to do the next day. [#497, male, back
pain]
Some interviewees talked about having constant reminders of the pain – a
feeling, knowing it is there or awareness on another level of consciousness –
whereas others spoke about deliberately ignoring or not focusing on the pain. These
respondents seemed able to ignore pain successfully with often sharp reminders
about their pain once the activity in which they were engaged ceased.
I can be kneeling there gardening. I can be there for half an hour to an hour
and the brain is elsewhere. I know what I’m doing though; it’s not that you’re
not conscious of what you’re doing. I know exactly what I am doing, but I know
much of my brain is somewhere else I guess. I am not even conscious of the
pain until I stand up…. And I think, “I’ve been in pain down there” [#305,
female, knee pain]
Episodic pain “You just do what you can handle”
Some interviewees described that their pain was fluctuating; either pain came
and went, or, although some pain was always present, there were better and worse
periods. Some people took responsibility for that fluctuation (e.g., citing that it was
because they were managing their pain well). Others could not predict the
fluctuations and seemed frustrated by this lack of predictability.
211
It’s just the craziest thing. Sometimes you can do it and other times you can’t
[lift the arm due to pain], and there’s no rhyme or reason as to why [#424,
female, shoulder pain]).
For those who had some pain-free periods, these respondents spoke about
continuing to do activities but changing the way that they did them to avoid pain.
As one respondent put it, “don’t do things that hurt”. However, similar to those
respondents who had constant pain; these interviewees prioritised some activities
over the pain episode which it would trigger (e.g., team sports, gardening).
Vacuuming; I now pay my son to do the vacuuming and wash the floors.
Gardening; I love gardening. I have a big garden and I love it. So I have to do
that in little bits at a time. 10-15 minutes at a time. If I’m doing anything that is
bending then I sit down and have a rest then come back and tackle it again.
[#557, female, back pain]
The previous quote also illustrates that some activities were not sufficiently
important to risk a pain flare-up (e.g., housework) and were delegated to others.
Some activities and chores were disregarded altogether as being unimportant.
Pain was viewed as another consideration in life when making small (e.g.,
attempting to use stairs or using the ramp) and large decisions (e.g., moving to a
lowset house). In this sense, pain was often described as a hassle. Sometimes life
was described as coming to a stop, for example, by spending the weekend in bed.
While many respondents would recommend to other people with pain that
they learn to live within their limitations, some were willing to try new treatments to
manage or cure their pain and were alert to new remedies. Still others were more
purposively looking for “the answer”.
212
Resolved pain “Move along and go onto something else”
Some interviewees actually found it difficult to describe their pain now that it
had resolved. This seemed to be more likely if the pain was not considered a large
part of their life when it was present or if it was one of many health challenges that
may have been superseded by other health concerns. For example, arm pain was
only one of many health challenges experienced by an interviewee with a diagnosis
of multiple sclerosis. Another example was sinus pain that, when compared to an
earlier back pain episode, was insignificant.
But I mean, you get all these aches and pains all your life, and what do you do?
Move along and go onto something else. Well I do. [#119, female, resolved
head pain]
Finally, one respondent explained the fading memory of pain as a self preservation
trick of the mind.
Especially as you get older you do to tend to … forget how painful things
were…. I think that when you think back it is never obviously as bad – but that
is just a self-preservation kind of thing. And there are certain things in my life
that I said I’m going to remember this. I’m going to remember how hard this
was … Even now when I remind myself of that, I keep thinking, “It wasn’t
really that bad”. [#92, female, hip & lower back pain]
Interviewees gave several reasons for their recovery. Most commonly,
exercise and time were cited. Another believed that seasonal changes accounted for
the resolution of her pain.
Suffering with the pain “It really drives me insane”
Two participants described excruciating pain and significant disability and
despair. These two respondents stood out from the other interviewees because of the
despair and distress they described. Strikingly, there were a number of other
213
similarities between the two. Predominantly, these were their beliefs about a
medical cure. They had continued to take prescription medication despite their belief
that it was not helpful. Both were reliant on medical professionals to provide a cure
for their pain. The level of distress and disability they experienced is highlighted in
the following quote.
[Pain] … progressively got worse and worse and I was on quite a few
pain-killers, OxyContin, Endone, all those sort of things. It was pretty [bad]; it
made me sick and all that sort of stuff. There's a time there that I couldn't even
walk from my office to the factory without having to sit down with pain and
when walking back from the factory to the office. It just got really, really too
bad. So when they said, "Your operation is in August," it was like the best thing
ever - you know … [But later] by the time I had to have the operation, I was
convinced I was going to die in the operation [#819, male, back pain]
Even though pain resolved for one interviewee (through surgery), this person still
had significant psychological distress, which continued even though he was painfree. The other interviewee was continuing to search for a cure via a series of
specialists.
I am thinking maybe after 12 months I have found a correct doctor. It’s just
been you know asking around everyone, everyone at work and um “you got
anyone I can go to” and the guy that’s been looking after my shoulders just
lately. My husband was painting his surgery and he got talking to him and he
said “this is what I do. I’m a rehab doctor”. I said “yeah, that’s what I need”.
But I’ve seen him now a coupla months and I’ve been going to the gym under
his guidance and everything. … And um this particular doctor, this rehab
doctor, has had surgery on his shoulder with this specialist. And feeling like,
maybe at long last, I’m going to have some success.
The Influence of Pain on Others “You snap at people when you shouldn’t”
Interviewees gave many examples of how their pain had an influence on
other people, mostly family members and work colleagues. Irritability was the most
214
common cause of negative effects on others. Respondents reported having to be
vigilant to avoid these interactions or being alert to feedback from others. Though,
some participants identified that they may not realise until after the interaction that
they had displayed grumpiness or impatience. Some thought that their behaviour
was reasonable or excusable given their level of pain.
Some examples of social withdrawal were also discussed. For example,
withdrawal from sports competitions because respondents believed that pain
prevented them from performing at their peak level, which would lead them to let
the team down. Also, fears of being touched by others (which exacerbated their
pain), had led to social withdrawal.
Coping with Pain
A strong focus in the interviews was on coping with pain. The following
points are the main thoughts about the best ways or the most influential aspects to
managing pain – either that respondents use themselves or have observed in others.
1.
Positive attitude. Respondents thought that their frame of mind was very
influential in how they coped and viewed their pain. Interviewees believed
that it was important to have a positive attitude and not to dwell on the
hardships or difficulties of having pain. If necessary, it was central to “get on
with it” rather than focusing on the pain. It was a case of mind over matter, if
they wanted to achieve their goals.
Now, look at my little friend up there, up the road, with her [pain] and she's so
positive all the time, all the time. You know, my mother is the same age and two
different people. One wants to be young and get out there, loves to be out of the
house and amongst people and my mother just mopes and mopes and groans
and carries on. So I think the attitude [is important] [#18, female, multiple
pain sites]
215
I think its probably attitude or positiveness. … Some people tend to fall into a
trap where pain becomes part of their lifestyle. So say if you know someone
that’s not been well and people come up and say how you feel. People ask them
how they are feeling all the time and they are not expecting a positive answer
so they sort of give them the negative answer … It seems to become sort of a
career. [#231, male, resolved leg pain]
2.
Getting a good night’s sleep. Another aspect that some respondents spoke
about was the importance of getting restful sleep. Sleep assisted respondents
with the emotional and mental coping.
If I can get at least 5-6 hours sleep at night, I can manage it mentally as well as
physically. I find mentally I can cope. [#371, female, multiple pain sites]
I think pain is worse if you’re tired. If you wake up in the morning, you
probably don’t feel too bad. But if you have a big heavy day or you’ve had a lot
of pain in the day, I think then, by then your tolerance is, sort of, you know.
[#119, female, resolved head pain]
3.
Doing things that you enjoy. Respondents spoke about staying active and
continuing to do activities that they enjoyed doing. It seemed imperative to
have a life outside of pain. Doing enjoyable activities could also push pain
into the background for people.
Well if I’m interested in what I’m doing I guess I tend to ignore the pain barrier
more. But if I’m not interested in what I’m doing then I allow myself to get
grumpy and decide I don’t want to do this.
For instance shopping or
sightseeing with my wife. [#24, male, back pain]
4.
Push through the pain. Sometimes it was considered worthwhile to push
through the pain. As above, pushing through the pain by remaining active
could decrease the focus on pain. Pushing through the pain was also believed
to strengthen the individual’s ability to bear other episodes of intense pain.
From the car park to here, when I get here my calves are burning. They’re
burning. By the time I sit with you here now, they’re cold. Same with the
216
thighs. They burn hot. Pain. But I push through that because I learnt how to
push through the back pain. [#406, male, back & leg pain]
Gatchel’s Model
A main research aim of this phase was to examine the premises of Gatchel’s
Model in relation to participants’ experience of pain. Some of the key premises of
Gatchel’s Model include 1) pain leads to inactivity which leads to dysfunctional
behaviour patterns, 2) the resultant psychopathology is influenced by individual
characteristics and environmental factors, and 3) mental and physical deconditioning processes are interactive. Like all the data presented here, these
premises are addressed separately for the purposes of clarity, although as the
concepts in Gatchel’s Model are interconnected, so too were the ways in which
participants spoke about these themes.
The Disability Sequence: Pain, Inactivity, Dysfunction
The main premise of Gatchel’s Model, upon which many of the other
assertions rest, is that pain leads to inactivity and the greater the duration of
inactivity, the greater the likelihood of developing dysfunctional behaviour patterns
including physical de-conditioning (disability). However, as mentioned previously,
the premise that pain leads to inactivity was inconsistent with the reports of most
interviewees, particularly those with constant pain. Specifically, interviewees spoke
about remaining active despite pain.
Interviewees cited a number of strategies that were important to enable them
to remain active. These strategies included changing how they undertook tasks,
making additional preparations prior to commencing a task, seeking help, going
slower, not measuring themselves against others, being realistic about what they
217
could achieve and doing activities that they enjoyed or were otherwise worthwhile
for them. Determination was often cited as a key ingredient necessary to achieve
and stay active. Some people spoke about giving up certain activities that were
unattainable (e.g., bush walking) but committing to other more attainable and still
enjoyable activities (e.g., walking and cycling). The pain experience seemed to have
changed the behaviour of the majority of participants but the changes were reported
as functional changes that allowed continued activity and quality of life.
Actually that’s a thing [driving] that I have really restricted, even in my own
vehicle because it aggravates me. I think when I first realised it was when I
was driving [buses]. … And that’s when I fortunately I was able to make
careers changes to help me deal with that. … So what I’ve got to now is I’m in
an admin job and I do find the seats better designed and help me a lot. So I’m
not bouncing up and down in vehicle for example. So change of lifestyle.
[#497, male, low back pain]
There were a number of reasons that interviewees spontaneously gave for
staying active. Some people used activity as a distraction tool for pain (e.g., walking
to the local shops when their hand was sore). Others remained active or exercised
for the mental health benefits.
It's interesting because I can get up feeling really horrible on a day that I am
due to go to the gym and I make myself go. The very fact of doing that physical
exercise makes the improvement. So if I can get myself out of bed and get
going, go and do it, I'm fine. I feel better when I walk out, you know, an hour
later, and the improvement continues for the rest of the day. [#215, female,
shoulder pain]
Some interviewees received advice from health professionals, specialists and
physiotherapists that they should remain active and exercise. Although a few
respondents spoke about stopping some activities and responsibilities (e.g.,
gardening), they resumed doing these activities out of necessity.
218
Respondents spoke about a use it or lose it attitude. This was true even if
physical activity caused or increased their pain. Some participants also kept
exercising despite health professionals’ warning that this particular exercise may
increase the damage at the injury site. These risks seemed to be outweighed by other
benefits. Reasons given for continuing these types of exercise included enjoying
that type of exercise, weight maintenance and established family time.
I look at exercise as it’s going to keep me walking. He said no walking, no
push bike riding, no climbing. … I love walking. And I tried the exercise to
decrease the pain. It doesn’t. It increases the pain. … [The specialist] said
that you have to rest it. You cannot walk. The more I use the joint, the more I
split the joint. I give him that. But again it comes back to, he said don’t, but I
have to. So long as I keep moving hey it’s got to be good. [#305, female, knee
pain]
In summary there was little evidence for the premise that inactivity and
disability would result from the experience of even constant pain; the majority of the
interviewees described continuing to be active despite pain. Primarily this seemed
to be because these activities were considered worthwhile by respondents.
However, some activities may have increased participants’ current and future pain.
Underlying some of these decisions appeared to be an absence of fear of pain.
Mental De-conditioning: Struggling to Cope
Gatchel’s Model also posits that there is a positive relationship between pain
duration and mental de-conditioning (similar to that with physical de-conditioning).
As discussed earlier, according to Gatchel’s Model, the development of
psychopathology is dependent on individuals’ characteristics and environmental
factors. It also hypotheses that individuals will become mentally fatigued by failed
attempts to relieve pain.
219
Influence of Emotion: “Emotions do play a part for me”
While pain duration was not raised as an important construct by
interviewees, participants recognised the influence of emotions on their pain.
Respondents identified that, for them, pain could lead to worse emotional states such
as irritability, impatience, and anger (see earlier section on page 213). Some
believed that that the relationship was unidirectional, where pain led to irritability,
for example, but positive mood states did not relieve pain.
See, today it is great; it really is. … I don’t think it’s because I’m happy at the
moment. I just think that I didn’t do anything to annoy [my back]. [#557,
female, low back pain]
Others believed that the relationship between emotional state and pain
experience was bidirectional. Some interviewees spoke about this relationship in a
specific sense, e.g., on a pleasant occasion pain was decreased because one was
enjoying themselves. Others presented this relationship in a more global sense.
… if you get a really nervous uptight person who always got something wrong
with them and dying of something, I think their emotions probably make their
pain appear worse. [#119, female, resolved head pain]
But emotions do play a part for me in … if I am worried and nervous and
stressed about something, I find that I’m in more pain. … And to me that is all a
part.
If you are stressed and worried about something, then you’re not
sleeping, then your body is not rejuvenating. And so when your body is not
rejuvenating, then something has got to give. [#371, female, multiple pain sites]
Interviewees identified a cyclic nature to the relationship between mental
states and pain. Coping with pain was easier on some days compared to others.
I must admit that some days I’ve just sat down and cried because it’s all got too
much. I can’t deal with this any more. … But the next day I was alright. But
most of the time you just get up and keep going. [#371, female, multiple pain
sites]
220
If you are down for the day, if you are feeling down, something has happened
and you are down, I think everything else feels down, too. Everything is flaring
up. Even though it's no worse than yesterday, it flares up in your mind because
you’re down. [#18, female, multiple pain sites]
Influence of Personal Characteristics: ‘I’m a pretty resilient person”
While interviewees did not spontaneously introduce mental illness into the
conversation, personality aspects were considered important in how they managed
their pain experience. Interviewees cited independence, determination and resilience
as being important characteristics which they held and helped them cope with pain.
I am an independent cuss, so I don't want to have people doing things for me or
anything like that unless I really need their help, whereas other people are
more dependent, I think, and they sometimes use that as a way to make contact
with people or … I don't know. [#215, female, shoulder pain]
A related aspect that was discussed by a small number of participants was
their experiences with illness in childhood or young adulthood. These respondents
stated that these previous illness or pain experiences had given them the skills to
cope with their current pain.
Everything I experience now, I compare to that renal colic pain. I have never
experienced anything as bad as that renal colic pain. So it’s like you say to
yourself, “it is not as bad”. [#305, female, knee pain]
I have a very strong threshold to pain. I tell myself that and I always have as a
child. I think because of the operations I had to endure all the time, much time
I was in hospital for the ears and throat. [#18, female, multiple sites]
221
Attitude: “Woe is me”
Some interviewees identified extended family members who were not coping
with their pain. Many respondents put this down to attitude and the way that these
people thought about their experience.
She tells her mind that, "Woe is me, my pain," and nobody else in the world has
any pain except for her and she's a real drama Queen, she really is, … I just
say, "Well, look, maybe if you move it more, it will be better," sort of encourage
her. She is the opposite [to me]. She will have a handful of tablets, "They don't
work; they don't work." And her attitude is very negative, very negative [#18,
female, multiple sites]
I suppose I am a little bit more determined because I have a sister-in-law that is
just [shakes head] …believe me. And I keep thinking, my God, just get up and
get on with your life. Get over it. It’s not that bad. … And I suppose I gauge
myself on that. [Interviewer: Is your sister-in-law getting better?] No. She’s
got herself on a walker at the age of 46, which is, you know [crazy].
[Interviewer: Do you compare her with yourself?] I’m not a malingerer. I tend
not to be and I don’t think I am. But she is a totally different person, … It
doesn’t matter how bad somebody else is, she has got herself into this stage
now, that she is the worst and nobody can make it better. Even though doctors
have said, for God’s sake get on with your life. Stop doing this to yourself. It
depends on the person you are. And I think a lot of it has to do with … her and I
and our situation, our background is a lot of it. She comes from … her family is
a bit that way, o woe is me, close the windows, close the doors, don’t let
anybody in, I’ve got to stay inside - whereas my family has never been like that.
… And the willingness to help yourself; really to me that is a lot of it. Just to
deal with it and try and make yourself better rather than accept that I’m in pain
so I’ll go to bed. I’ve got clients who have done that. They can’t deal with it so
they go to bed and that’s where they stay and that’s where they die. But she is a
lot younger than I am. I get frustrated. [#371, female, multiple pain sites]
222
Exhaustion: “It still wears you out a bit”
Consistent with Gatchel’s Model, interviewees described pain as exhausting.
Specifically, pain was described as capable of wearing down one’s resources and
that this effect could be exacerbated by sleep disturbance as a result of pain. The
below quotes provide some examples.
It makes me a bit tired sometimes. It does wear you out. Pain does wear you
down a bit especially when you’re trying to do things that you need to do. And
you’re trying to ignore it; it still wears you out a bit. [#497, male, back pain]
But it’s when you’re woken up at 2 o’clock in the morning and you can’t go
back because your shoulder is aching. And you think, ohhh, and I lie there
holding it. And I’ll put the heat pack on and I’ll take some tablets and think,
“just stop; just let me get some sleep”. [#371, female, multiple pain sites]
Evidence of Mental De-conditioning: “Is everything going to be all right”
While the above descriptions are representative of the majority of the
interviewees, there were two interviewees whose experience was quite different (see
earlier section of page 212). Recall the experience of one of the men with low back
pain. He had experienced some psychopathology in terms of depression and anxiety
with his low back pain; this is consistent with Gatchel’s Model. After surgery had
corrected his injury relieving his pain, he continued to experience depression. He
also began to have panic attacks, for which he was under the care of a psychologist.
Using Gatchel’s Model as a framework, this individual would not have been
expected to continue to have problematic psychological symptoms or the
development of new symptoms. However, this may be explained by a predisposition
to depressive and anxiety disorders, which may fit with Gatchel’s Model.
223
Summary of the Disability Sequence.
In summary, emotions (i.e., mental de-conditioning) were described as being
related to one’s pain experience by the majority of interviewees. Pain duration did
not factor in this relationship though. Respondents described background factors
that were protective (such as determination) rather than risk factors for poorer
outcomes. Despite the exhausting nature of pain, some people found the strength to
keep going and keep active. Being worn down by pain was a temporary affliction
rather than one which lead to increased disability.
Crossover between Mental and Physical De-conditioning: “Exercise gives you a
dose of euphoria as well”
Gatchel's Model proposed that mental and physical de-conditioning
processes are not independent, but rather, these processes influence each other. In
the interviews, there was evidence of links between mental and physical deconditioning. Participants spoke about exercising even when they did not feel like it
for the mental health benefits (see also quote from #215 on page 217).
For me exercise doesn’t help, um, physically. But mentally yes. It is a huge
buzz mentally. That I can go walking for 4kms, 5kms, um, and it might sound
big-headed but I come home and I feel really proud. [#305, female, knee pain]
Protective Variables
The interviews provided an opportunity to examine the protective variables
(identified through the literature and examined in Phases 1 and 2). These variables
included coping strategies, optimism, self efficacy to manage pain, beliefs about
pain and pain management, social support, and positive affect. These same variables
were examined to the extent that they occurred in the interview data.
224
Coping Strategies
Many of the coping strategies that interviewees spontaneously spoke about
using are those strategies that are assessed in standardised questionnaires. While
these strategies are judged by health professionals to be helpful (or not) for long
term pain management, this data provided an insight into how people with pain
viewed these strategies. Typically, interviewees viewed coping as a personal
phenomenon where different strategies worked for different people.
I think everybody has got their own way of dealing with pain and we have all
got our own cures and remedies [#559, female, resolved back pain]
Self-talk and distraction: “Using our computer disk”.
The importance of attitude and using cognitive skills to cope with pain was
emphasised by interviewees. Participants spoke about using self talk to “call
themselves to task” or motivate oneself to continue a task despite pain. Often
participants acted as the devil’s advocate and used insults to motivate or as
punishment for not taking appropriate preventative action. Self talk was also used to
soothe and comfort oneself.
Apart from being a little bit self-abusive and saying “you stupid *** - you
should have been doing this days ago” – when you first got twinges or
whatever. That’s bout the only thing that is consciously going through. [#156,
male, knee/ shoulder pain]
I actually do talk to myself and go, "Oh, you are just being stupid. You are just
being an idiot. Get up and start moving again," [#18, female, multiple pain
sites]
It might sound funny. But I talk to myself. That’s my coping mechanism. “Just
calm down. It’s not that bad. It’s going to stop in a minute”. [#371, female,
multiple pain sites]
225
Distraction was used to give oneself a break from the pain. Participants used
tasks at work and at home as a distraction from pain (see earlier section on page
210). Cognitive abilities were also used to “switch off” from pain mentally.
Sometimes switching off sounded like an automatic process but other participants
did this more intentionally.
I just take myself into another zone; the body is doing one thing but the mind is
just not there. [#305, female, knee pain]
So generally I manage it, by concentrating on other things for a start. I’ve got
lots of things to do. And I often think “it’s not worth concentrating on that,
let’s concentrate on that. What do I need to do? What’s more important?”
[#497, male, back pain]
For some interviewees, distraction was all they used or all that was required
to cope. For others, it was the only coping mechanism that the situation allowed or
the first step in a line of coping strategies that may be used. Distraction was also
used in combination with other strategies such as medication or rest.
So for example, if I need to do something and I have got bad pain, I will just
deal with it by painkillers and concentrating on what I need to do. Sometimes
… it might make it a bit worse later on but at least I’ve done what I needed to
do or wanted to do. [#497, male, back pain]
Using distraction to cope with pain may have other mental health benefits. Being
able to ignore pain in order to attain a goal was described as very rewarding.
Interviewees spoke with pride about what they had achieved despite pain (see above
quote from #497). Distraction was also used to cope with the emotional
consequences of pain.
I change my thought pattern, sort of thing. So as soon as you feel yourself
getting a bit too depressed, you try and think of something else, sort of thing.
226
Rest and relaxation: “Pull back, relax, and just let it go for a minute”.
Rest was used particularly by interviewees with low back pain. Rest was
mostly described as a short term coping mechanism, which was used as a specific
strategy in relation to a specific incident. Resting was not described as being used to
prevent pain. Periods of rest were followed by resuming normal activities. In
addition, if rest was not possible due to environmental constraints, most typically
being in the workplace, then other coping strategies were used.
So most times I try and concentrate on what I am doing but if it gets really bad,
some bed rest. And bed rest is usually only, take some painkillers, strong
painkillers, and rest for perhaps an hour. Then usually it’s get up and continue
on with what I need to do. [#497, male, back pain]
Getting help: “I try to get assistance more than anything”
Few respondents spoke about asking for assistance with tasks as a coping
mechanism. Although, as mentioned in earlier section on page 211, some tasks were
relegated to others. These were typically household tasks such as carrying groceries,
mowing and house cleaning.
I have found lately – and it’s just been over the last few months – that the kids
come shopping with me now; just getting the groceries into the car and out of
the car and upstairs. [#371, female, multiple pain sites]
Exercising: “I just do my exercises and it goes away”.
There were a range of opinions about completing exercise generally and
exercise in particular to cope with pain. For some participants, exercise in general in
terms of keeping active had benefits for managing their pain. Additionally, it also
had positive effects on their mood, e.g., “exercise gives you a dose of euphoria as
227
well” [#231, male, resolved leg pain]. Some interviewees had specific exercises to
keep pain at bay or to ease pain once a new episode or flare up had begun. Many of
these exercises were recommended by a physiotherapist or chiropractor. Other
participants had a negative opinion of exercise and despite recognising the benefits
of the specific physiotherapy treatment regimes, resented having to adhere to these
regimes. See the below quotes for an illustration of these ideas.
I also have twinges when I’ve just turned [in my seat]. I think it’s probably just
a joint gets locked or something. And that is really painful and I can barely
move. And the way to fix that is to stretch my spine – either hang off a beam, or
lie on the floor and get someone to pull on my legs. And almost immediately,
I’m ok. [#24, male, back pain]
I think I’ve had enough of physiotherapists, you know. And that is probably a
bad thought, because they are good at what they do. They do provide good
exercises. But they also have a different focus on life to me. Their focus in that
you exercise every day. I have never exercised in my life. I’m not that sort of
person.
So doing this was foreign to me, particularly with my arms, the
exercises for my arms. But otherwise I am then down to limited mobility and
pain. I don’t want either. [#283, female, hand & shoulder pain]
Potentially an important part of exercising is also one’s attitude to exercise
and keeping active. Some people did not have an exercise regime per se but
nonetheless they remained active.
I do a lot of walking day-to-day and a lot of exercising. I don’t exercise as in
people walking up and down the street. My doctor says I should but I don’t
because I figure I do enough. [#371, female, multiple pain sites]
Optimism and Positive Affect: “Mind over matter”
As previously mentioned on pages 214, interviewees believed remaining
positive, even during pain flare ups, contributed to their psychological well-being
228
and how well they coped with their pain. Respondents generally believed that they
had always been “positive people”. The possible influence of a positive attitude was
captured by one participant when they spoke about the people that they knew who
had been diagnosed with serious illness (e.g., cancer, multiple sclerosis) and, in her
mind, had given up and therefore died shortly afterwards.
I think attitude has a lot to do with pain and I think your attitude towards pain
means you either have a good experience with it or a bad. So I value life. I
have still got lots of things to do, so whatever happens I will kind of deal with it
as it comes along, hopefully. [#559, female, resolved back pain]
One participant spoke about not moaning or whinging because of the
negative influence it has on your experiences. In the interview, even though she
could list examples of physical limitations that pain imposed, cognitively these were
downplayed. She said that her pain “hadn’t really affected” her activity levels.
Other interviewees also spoke about being active rather than sitting at home and
feeling sorry for themselves or that being miserable was not helpful.
I think you’re better if you’re up and about and going to work than if you’re at
home, thinking “I’m so sick, I’m so miserable, I have to lie down and go to
bed”. [#119, female, resolved head pain]
But for me it is mind over matter, nobody’s going to tell me I can’t do anything.
So the longer I stay active, the longer I can be active. I am 57 and I am not in a
wheelchair. I have no intention of being in wheelchair. … I am not going to
stop. I am not going to be one of these people who is waiting to die. You come
through here once and I intend to live life. [#305, female, knee pain]
Further, despite a significant pain condition, participants actually “counted
their blessings”. Some interviewees did this by comparing themselves to those
worse than themselves.
You need to say, yes I am in pain but I can still do this, I can still do that, I can
still move. You aren’t crippled, lost and unable to do things for yourself. Try
229
and look at it that way. And think about the people that are out there and are a
hundred times worse off than you. I had an aunt whose fingers were so bent
she couldn’t even feed herself. [#371, female, multiple pain sites]
Some people whose pain had resolved through treatment viewed their
(optimistic) attitude that they would find a resolution as a strength that had
encouraged them to keep seeking treatment. Eventually these two participants had
found pain resolution; one through shoe inserts and the other via physiotherapy
treatment. Because their searching lead to successful treatment it is difficult to know
how fruitless searching may have affected their experience. However, both had
remained active despite pain during this period. This may act as a safeguard against
disuse syndromes like those described by Gatchel’s Model.
Self efficacy to Manage Pain: “Pain doesn’t stop me”
Participants spoke about self efficacy in terms of a range of behaviour,
including managing pain, finding ways of easing pain, seeking pain resolution and
finding information. Participants believed self efficacy to manage pain is innate.
Determination was an important component of this.
Participants believed that they had the knowledge or the skills to manage the
pain during a flare up. Many believed that they could predict a flare up and
therefore take preventative action or could actively manage this flare up.
I’m confident that I can predict in advance that this is not going to be nice to
my back. [Back pain] really hasn’t stopped me doing things. And it won’t!
In addition, interviewees mostly disagreed with the item, there is little that I
can do to ease my pain. They seemed to take responsibility for either finding a cure
230
or easing their pain, saying that there was always something, even if it was small,
that they could do.
[Pain is] something that you have and you can either do something about it or
you can sit around and moan. I'm not a ‘sit around and moaner’ type. So I will
do something about it. [#559, female, resolved back pain]
As I said, there's little you can do, but there's always something you can do. …
I just sit there if I am watching telly, I will just gently manipulate [my finger]
like that and just rub it gently and pulling it back, like so. … With my neck and
back problem, I find by using the backpack handbag 100% better than having a
handbag on your shoulder. [#18, female, multiple sites]
One participant agreed with the statement, there is little that I can do to ease my
pain. She stated that she had tried everything to no avail. However, when pressed,
she did receive a few days relief from cortisone injections. She identified herself as
a resilient person; she was unable to get relief but did not let the pain affect her life.
For me that would probably be true. I’ve tried everything. I even tried the
bean bags in the microwave, the heat, thinking that if I make it so boiling hot
the all I could feel is the pain of the heat. Or even … Inflicting pain on some
other part of the body so all you can feel is this pain; you can’t feel that [pain]
any more. Even resorted to doing that. It works. Or getting someone else to do
it. [#424, female, shoulder & hip pain]
Beliefs about Pain and Pain Management
A number of beliefs about pain were expressed explicitly or implicitly by
participants. The topic that interviewees spoke the most about was medication use
and use of other medical services. Other beliefs that were discussed in the
interviews focused on social support and the responses of significant others.
231
“I don’t take pills or anything like that”.
Opinions about the use of medication were wide ranging. While some
interviewees were against the use of pain medication, many respondents talked about
pain medication for severe pain only or as a last resort. If they did not take pain
medication, often they stated that their pain was not severe enough to warrant this
intervention. Other participants used pain medication during flare ups or used a
medication hierarchy where over-the-counter medications were used regularly and
prescription medication was used only during pain flare ups.
I’m not one of these to take anything for pain unless it’s really bad. And yes, if
it’s really bad I will take it. [#119, female, resolved head pain]
Not with medication. I’ve already decided that when it gets to the stage and I
can’t handle it, I will go and try acupuncture, that sort of thing. [#305, female,
knee pain]
When it gets really bad I, it does respond in my case to some anti-inflammatory,
and I take Proxin or whatever for 3 or 4 days just to ease it down and then I
knock it off. [#156, male, knee & shoulder pain]
The notion of a pill popper was a negative image for most interviewees.
Many participants said that they were not that sort of person, implying that
medication use is confined to a certain type of person. In addition, participants said
that they did not like to take medication. Some cited that medication was just a
bandaid-type solution that covered up the problem but did not resolve it.
I would dearly love, I mean if there was something I could swallow to be long
life pain-free, I would pay for it. It wouldn’t worry me. It would be just great.
But you’re just working with pain killers. That’s all you’re doing; they’re not
actually fixing. It’s just a bandaid. [#557, female, back pain]
Finally, interviewees commented on the side effects of medication – commonly
constipation and occasionally the tolerance effects.
232
“If it gets bad, I’ll see a doctor”.
Most respondents had disengaged with the medical system with the
exception of the two interviewees who were struggling to cope (see earlier section
on page 212-213) and one participant who was receiving quarterly spinal injections.
The other interviewees were self managers of their pain. In fact, some specifically
said, they wanted to avoid specialists as long as they could.
I suppose I should go back and get it re-assessed. And just see what they say
now. Spend 100 dollars or so, because I’m in private cover, and just see what
they say. Could be worth it. Must be 20 years since I’ve had it looked at.
[#557, female, back pain]
Several references were made about doctors being incompetent or
misdiagnosing the cause of their pain. One respondent spoke about being put in
plaster from neck to knee to cure back pain. Another spoke about botched surgery at
the hands of an orthopaedic surgeon (confirmed by two other specialists).
There is no one else to go to. I have exhausted the medical profession. And
they don’t know anything, today. They know very little. [#406, male, back &
leg pain]
On the other hand, participant #424, who struggled with pain, had received
many diagnostic procedures and had seen numerous allied health professionals and
medical specialists. Her experience is reminiscent of those described by clinical
patients.
I’m also having an MRI because I’ve had everything. Same with the hip. Every
ultrasound, every x-ray, every drug. Um, physio, acupuncture, chiropractor.
You name it, I’ve had it. But still can’t pinpoint what actually it is. [#424,
female, shoulder & hip pain]
233
Social Support and Solicitude Beliefs
Interviewees had few expectations of support. Correspondingly, less than a
third of the interviewees spoke about the social support they received or did not
receive.
“Whinging and moaning”.
In terms of respondents’ beliefs about solicitude, some participants saw their
pain as a private experience and therefore did not want to “sit around and moan”
about their pain. Others believed that a little bit of whinging was reasonable and that
it was acceptable to indulge in a bit of whinging every now and then.
There's no point saying to somebody … if I say to you, "I've got arthritis in that
finger." You have a look and say to me, "Oh, poor thing, how does that feel?"
You can't feel that pain, so you don't understand what I am saying. So what's
the point? No-one likes to know. [#18, female, multiple sites]
Who wants to go complaining about [pain] all the time when you want to do
other things with people? If you go out doing other things with people, you
don’t always say “ohh, I’ve got bad back pain; don’t know why I’m here” and
that sort of rubbish. [#497, male, back pain]
Oh, I might whinge a bit occasionally. If you have got someone with you and
[the knees] may hurt, and you whinge a bit but that's all right. [#355, male,
knee pain]
However, too much assistance or sympathy as a result of whinging was seen as
negative. Some interviewees believed that too much assistance or sympathy may
encourage a person with pain to do less; many respondents cited examples of people
who used their pain and the associated support received to avoid tasks and gain
attention. Some believed overly supportive behaviour could contribute to the
continuation of pain.
234
“I have a fantastic partner”.
A few of the women talked positively about the support that their husbands
offered them. Just the fact of saying this appeared to have a calming affect in these
participants. This was not the case for all respondents, e.g., one woman said that her
husband would not even know if she was in pain. A few respondents spoke about
raising their pain with their partner as pointless because their partner was not able to
“do anything” about the pain.
“Using a support group”.
One respondent who had experience severe low back pain that was eased
with successful back surgery believed that support-style groups where people with
pain and people who had surgery could offer support to each other. He believed that
this was a service that the medical profession should organise and offer people
waiting for surgery. As discussed in previous sections, this participant’s experience
and viewpoint was not widely held.
Revisiting and Understanding the Questionnaire Data
The collection of qualitative data provided some insight into the results of the
quantitative phases. As noted previously, this is a strength of a mixed-methods
approach and was one of the aims of this phase.
Categorising Respondents’ Pain Experience
Some of the respondents, who had been categorised as having chronic pain at
baseline that had resolved at follow-up, upon closer examination during the
interview still had episodes of pain. Of the eight interviewees who had been
235
classified as resolved chronic pain, four had ongoing pain episodes at their
nominated pain site and one had the potential for additional pain episodes (although
this was minimised through good pain management). The pain of these respondents
appeared to be better understood as episodic pain; by chance they were experiencing
a pain-free episode during the follow-up data collection.
Regardless, it is difficult to categorise people’s experience with pain. This
was evident when considering participant #559. Although, she was classified as
having resolved acute pain, which seemed to be an accurate reflection of her lower
back pain, this participant had extensive experience with continuing arthritis pain (a
chronic pain condition).
Survey of Pain Attitude (SOPA) Items
Three items from the Survey of Pain Attitudes (Jensen et al., 1994) (Jensen et
al., 2003) (refer to Chapter 3: Methodology) were discussed with interviewees.
These items were explored in the interviews for two reasons: to allow aspects of the
pain experience to be raised with participants without the inference that the
interviewer held a particular view, and to enable the thinking behind and reasons for
the responses to these questionnaire items to be explored. Items were chosen as
examples from the subscales with poor internal reliability (see Chapter 4).
Discussion of statement 1, “there is little I can do to ease my pain”, revealed that
participants had interpreted that item a number of ways. Some people talked about a
short-term focus, whether they could ease their pain today, versus a long-term focus,
whether their pain could be cured. For a single individual then, this item may have
been interpreted in two ways as per the quotes below.
236
If you look at it "ease my pain", yeah, if I sit down, I am going to ease my pain,
or if I lie down I am going to ease my pain. But the fact that my pain is going to
be here today and it's going to be there tomorrow and it's going to be there
tomorrow after, in that sort of sense, yeah, my pain is not going to reduce. It's
not going to get any better. [#819, male, back pain]
I’ve got a left hand and a right hand response to that. If I say I’d agreed with
that, I wouldn’t want it to be seen that as losing hope; that I’ve given up … But
on the other hand, if I say there isn’t much I can do to ease my pain because I
live with and I get on with it anyway. I see that as a more positive response,
giving the same answer to that question. [#24, male, back pain]
Given that health professionals would view disagreement with this statement
as a more adaptive response; reliance on this item may be misclassifying people’s
attitudes and resultant behaviour.
The second statement, “there's a connection between my emotions and my
pain level” received little support in the Phase 1 data collection (see Chapter 4 for
the results of the SOPA emotion subscale)33. However, when discussed in the
interviews, most participants agreed with this statement. One explanation for this
discrepancy is that participants had not considered the influence of emotion prior to
reading this statement on the first questionnaire. Once they were exposed to this
idea, they may have noted the influence of emotion on their pain in the following
time period. Alternately, when reading that item on a lengthy questionnaire,
participants may not have considered the item as deeply as they did when asked it in
conversation, such as only thinking about if emotion affects pain rather than
including instances where their pain increased emotion (like irritability), which was
a common response in the interviews.
The inclusion of the third statement, “exercise can decrease the amount of
pain I experience”, highlighted that some respondents may be doing exercise that is
33
Of the 20 interviewees, 14 nominated that this statement was not true or did not apply to them.
237
contraindicated for their type of pain. Nonetheless, most remained active and had a
positive attitude toward exercise.
Discussion
Phase 3 further explored the experience of pain in a more detailed way and
investigated the processes of Gatchel’s Model from the viewpoint of people with
pain. The data collected in this study lead to a re-evaluation of the Phase 1 and 2
data through a better understanding of how participants’ interpreted the
questionnaire items and the episodic nature of some of their pain conditions. As a
result, a richer picture of the nature of pain was obtained.
The Experience of Pain
There were a number of ways that pain was viewed by interviewees from
battling with pain to co-existing with pain. One’s view of pain obviously influenced
each person’s experience of pain and the way that they attempted to cope with their
pain. Regardless, the majority reported coping sufficiently well with their pain. In
addition, most participants would be considered to meet the goals of health
professionals working in the area of pain, that is, participants were functioning
despite pain. Similar to other cognitive processes that are believed to affect
decisions about health, (e.g., health belief model), participants seemed to weigh up
the costs and benefits of continuing to be active despite pain. Moreover, many
interviewees seemed to detail with pride the roles that they continued to have despite
pain. As role loss is associated with poorer psychological adjustment (i.e.,
depression) (Harris, Morley, & Barton, 2003), the fact that participants involved in
238
this research phase reported little change in roles (or conversely, much stability in
their roles) may provide an explanation for why they reported coping so well.
Pain had an overwhelming influence on the lives of the interviewees and
affected all facets of their lives. However, overall the impression that the author had
was that these respondents were characterised by flexibility about how they
managed their pain. The level of importance attached to the functional changes that
they made to cope with pain was consistent with how well respondents coped with
the experience of pain; participants who did not attach much significance to their
pain condition and the changes that it necessitated appeared to cope most well. This
may fit with research that shows that the greater the influence of pain on chronic
pain sufferers’ perceptions of their “self” and their future hopes and dreams, the
worse their current level of coping (Morley et al., 2005; Sutherland & Morley).
Cognitively down playing their own experience of pain may have protected these
respondents’ sense of self, which was not reliant on being pain-free. This mismatch
between the severity of pain and disability with respondents’ report of wellness or
well being has been found in other quantitative research. Söderberg reported that,
“The results produced a complex picture of women with FM [fibromyalgia]. On the
one hand, they reported severe pain of different kinds, concentration difficulties, and
fatigue. On the other hand, they rated themselves as feeling quite well and ‘like
others’.” (Söderberg, Lundman, & Norberg, 1997, p. p501).
Although many participants spoke about accepting their pain as part of their
life and making the necessary changes to remain functionally active, still they spoke
about becoming annoyed and frustrated with their pain or related disability at times.
Participants also spoke about living despite pain, accepting that pain was a part of
their life and making adjustments for pain to continue to have a meaningful or
239
rewarding life. Regardless, the total experience of pain appeared to be
acknowledged by these interviewees (e.g., reporting that they also had “miserable”
periods). Nonetheless, for the majority of the time, these participants prioritised
other activities or events over pain (e.g., seeing the sights whilst overseas for work,
working for a living). Living despite pain with all that entails sounds very much like
pain acceptance (McCracken, 1998; McCracken & Eccleston, 2003, 2005, 2006)
which is a current concept in pain literature but which has proved difficult to capture
quantitatively (McCracken, Vowles, & Eccleston, 2004; Nicholas & Asghari, 2006).
As noted previously, this is like that which health professionals would like to see
pain patients integrate into their lives.
The experience of two participants was not consistent with the majority.
These participants described experiencing extreme distress and disability. Unlike
the other interviewees, these participants had sought (or were still seeking) a cure
through medical specialists and had undergone many diagnostic tests. One
participant continued to experience psychological disorders after he was pain-free.
When considering some of the risk factors for continued pain and high levels
of disability (see Chapter 2), interviewees did not exhibit catastrophising cognitions,
with the exception of the two extremely distressed participants. Respondents
seemed able to disengage from cognitions about pain as a threat, which would be
associated with fear-avoidance beliefs, for example by ignoring pain or using other
distraction techniques. Fear-avoidance beliefs are also associated with withdrawing
from activities that cause pain, which was clearly not the case for most participants.
Consistently, participants reported having a positive attitude, getting rest,
doing enjoyable activities and pushing through pain if necessary were key to coping
well with pain.
240
Gatchel’s Model
Interviewees’ point of view about their pain and their description of their
pain experience offered some support for Gatchel’s Model. The experience of two
participants who described much distress and disability fit with the predictions of the
Model most closely. Although, as noted previously, the psychological distress of
one participant did not resolve with his pain; this was inconsistent with the
predictions of Gatchel’s Model.
For most interviewees, pain had not resulted in inactivity and disability. This
is in clear opposition to that which would be predicted by Gatchel’s Model. While
remaining active required specific strategies in order to be achieved, it was clearly
possible for these respondents. The attitudes of these participants to exercise may
have encouraged them to remain active despite pain and also complete specific
rehabilitative exercises provided by physiotherapists and other allied health
professionals.
Again there seemed little evidence of the development of mental deconditioning. However, the manifestation of mental de-conditioning is dependent on
individual characteristics and environmental factors. Because of the variety of
factors and influences that may affect the presentation of mental de-conditioning,
this is a challenging concept to assess. The influence of emotions on the experience
of pain was reported by many participants, which is partially consistent with the
premises of Gatchel’s Model. The report that irritability was a common emotion
was consistent with the data from Phase 1 where one-third of the sample endorsed
that their pain made them more irritable. Several participants, however, strongly
rejected any notion that their pain had any non-physiological components. Rather
than psychological vulnerabilities, participants cited personal strengths such as
241
determination and resilience which helped them cope (and presumably prevented deconditioning syndromes). When speaking about other people with pain, respondents
cited that dwelling on their pain and having others assist the person with pain to
ruminate on their discomfort were vulnerabilities.
Consistent with Gatchel’s Model, interviewees reported that pain wore down
their resources and could affect their ability to sleep (further wearing down their
resources). This may explain the cyclic nature of their emotional state where coping
on some days was very difficult. However, many interviewees knew how to relieve
or reduce pain, even if just for a short period. Being able to relieve pain at times
may have contributed to the inconsistencies of these interviewees’ experiences
compared to what would have been predicted on the basis of Gatchel’s Model.
True to Gatchel’s Model, interviewees spoke about the interaction between
physical activity and psychological well-being, although this was discussed in a
positive context (i.e., that being active could increase mental well-being).
Spontaneously, interviewees spoke about a number of the protective factors
that are of interest in this research. Of the coping strategies targeted in clinical
samples, respondents in this community sample found distraction and self-talk, and
exercise useful. Asking for assistance and expecting solicitous responses from
others was mentioned less frequently. As these types of beliefs have been associated
with greater psychological dysfunction in clinical samples (Jensen et al., 1994) it is
perhaps not surprising that it was infrequently raised by these respondents who
reported coping well with their pain.
Remaining positive and having a positive outlook was deemed imperative by
these interviewees. This attitude appeared to bolster respondents when coping was
difficult. Some respondents believed that a positive attitude also had health benefits.
242
Tied in with positive attitude was self efficacy to manage pain. Being determined
and having the knowledge and skills (and the expertise borne of long-term pain) to
manage a pain flare-up and pain on a day-to-day basis were key elements in
managing pain. Even for the respondents whose pain had resolved, these
respondents reported that a strong belief that they could find a cure for their pain
was crucial in their search. As this is a retrospective account, it is difficult to assess
whether these respondents would have rated their self efficacy as strong while they
were in pain and still searching for a cure. A key concept in clinical treatment
programs is for the patient to accept that a cure for their pain is unlikely and
therefore, managing pain should be the patient’s focus. It would be interesting to see
how these respondents would be doing now if they had not found a cure for their
pain.
Attitudes towards medication and the use of medical services varied.
Overall, interviewees were self managers of their pain condition. Similarly,
respondents did not rely on others to manage their pain, although many identified
that they did have social support available to them.
Interpretation of Quantitative Data Phases
Using the interviews to evaluate the data from the quantitative phases
revealed that some chronic pain respondents who had been categorised as resolved at
Phase 2, still continued to have episodes of pain. These participants appeared to be
different from the intermittent pain respondents that were discussed in Chapter 4,
where these chronic pain participants experienced long episodes of pain and long
pain-free periods (compared, for example, to people with migraine). Other research
has indicated that back pain symptoms, in particular, can fluctuate (Burton et al.,
243
1995); this may explain the experience of some of these respondents who were
classified as having chronic pain at Phase 1 and resolved pain at Phase 2 as two of
these participants had back pain and one other had multiple sites of pain including
the back. Regardless, these results indicate that to capture the total experience of
pain, more frequent follow-up data collection may be required.
Exploration of three items taken from the Survey of Pain Attitudes (Jensen et
al., 2003; Jensen et al., 1994) revealed that some items may not have been
interpreted the way they were intended by these interviewees. Since the SOPA was
developed with clinical patient sample, this data highlights the importance of this
kind of exploration when using an established measure in a new population (i.e., a
population other than the one it was developed in).
Limitations of the Research
Unfortunately, while an attempt was made to select participants with a range
of pain experiences as identified through the questionnaire phases of this research,
the final sample consisted mostly of people who continued to have constant or
recurrent episodes of pain. While, this provided a comprehensive account of coping
with pain, some of the aspects of the processes underlying resolved pain may not
have been forthcoming. However, there were no differences between nonparticipators and participators on the key variables at baseline or follow-up.
Regardless, the experience described here is that of a sample of people with pain
(primarily) who responded to a request for an interview.
244
Chapter Summary
The results of the semi-structured interviews highlighted that people with
constant and severe pain can continue to live a functional life, that is, engage in
meaningful activities, maintain employment and enjoy family or social recreation.
Respondents of this research phase spoke about a number of keys aspects to coping
with pain, which included staying positive, prioritising a good night’s sleep,
continuing to do activities that you enjoy, and pushing through the pain.
Little support was found for Gatchel’s Model in terms of the way that these
people with pain described pain or their experiences with pain. However, as these
people are clearly coping better than might be predicted by Gatchel’s Model, this is
perhaps not surprising.
Chapter 8: Discussion & Conclusions 245
CHAPTER 8:
DISCUSSION & CONCLUSIONS
Purpose and Overview of the Research
This program of research had a dual focus. First, this research aimed to
provide much needed data on the pain experience of people in the community. This
information is required to expand our knowledge of the broader experience of pain,
including acute and intermittent pain conditions. Knowledge of the total spectrum
of pain is important for two reasons. This knowledge can be used to inform
healthcare planning and to provide the foundation for the development of
transitional models of acute to chronic pain. In addition, treatment and rehabilitation
planning relies on sound understanding of transitional processes to develop
appropriate interventions which can be provided in a community setting, prior to
disability behaviour becoming entrenched.
The community data provided in this thesis also provides population-specific
Queensland data, which has not previously been available. This data may be able to
be used for healthcare planning and service provision requirements in Queensland
particularly, and in combination with previous New South Wales data (Blyth et al.,
2004; Blyth et al., 2001; Blyth, March, & Cousins, 2003), may be applied to other
Australian states. It provides a comprehensive (deep) description of chronic pain in
a community sample, and allows comparisons to be made with patient data, of which
there is much literature available.
The second aim of this research was to explore the key variables of Gatchel’s
Model of the Transition from Acute to Chronic Pain in a non-patient sample of
people with chronic pain. In addition, emerging variables taken from the literature
(risk and protective factors) were explored to examine their value as an extension to
the basic model proposed by Gatchel. A critical examination of transition models,
like that proposed by Gatchel, is vital to aid our understanding of how chronic pain
disability develops in order to target interventions to prevent or manage chronic
pain.
Both of these research aims were met through three research phases using a
mixed-method research approach. Phase 1 used a baseline questionnaire to collect
quantitative data from 801 community-dwelling adults, and allowed the experience
of pain in this community sample to be documented. An initial examination of the
key variables in Gatchel’s Model was undertaken using cross-sectional analyses.
Phase 2 utilised quantitative data collected using a follow-up questionnaire with a
subset of the original sample (N = 218). This phase permitted the key variables from
Gatchel’s Model to be examined over time, and the predictive value of the risk and
protective factors to be assessed. Semi-structured interviews gathered qualitative
data for Phase 3, which permitted the experience of pain in a small subset of the
original sample (N = 20) to be described using this rich data source. In addition,
Phase 3 enabled an in-depth examination into the reasons that evidence for some of
the hypothesised relationships based upon Gatchel’s Model was not found in the
earlier research phases.
The Experience of Pain in a Community Sample
Quantitative data was collected and collated for three pain groups. Overall
this data provides an indication of how an individual’s pain experience is influenced
by their type of pain, how individuals engage with healthcare systems, and whether
community chronic pain samples are comparable to clinical pain samples (including
the use of coping strategies taught in clinical settings).
Characteristics of the Different Pain Subgroups
This research collected data from and categorised pain respondents as having
acute (≤ 3 months on ≥ 4 days/ week), intermittent (≤ 3 days/ week) or chronic (> 3
months on ≥ 4 days/ week) pain. These categories were based on the IASP
definitions of acute and chronic pain (IASP, 1986; Merskey & Bogduk, 1994) and
reflect the severity at which acute and chronic pain conditions exist. However,
whether these categories are useful, when describing the pain experience of a
community sample, is unknown.
In this community sample, aside from the pain characteristics which differed
as a result of the definitional components used to categorise respondents, there were
a number of differences in the way that respondents experienced their pain
condition. Participants with chronic pain were more likely to report more than one
site of pain than respondents with acute or intermittent pain. In addition, chronic
pain respondents reported that their pain interfered with a greater number of daily
activities compared to the acute or intermittent pain respondents. Consistent with
this report, approximately one-quarter of chronic pain respondents were classified as
Grade IV using the Graded Chronic Pain Scales, which is described as high
disability – severely limiting. This was different from the participants with acute or
intermittent pain. On the one hand, interviewees with chronic pain showed great
flexibility in their management of pain (by changing the way they performed or
ordered activities) and pain was a clear influence on their decisions, activities and
employment. On the other hand, interviewees insisted that their pain had not
changed them or their life.
In Phase 3, participants with acute pain provided less description of their
pain experience than chronic pain respondents, and generally had shorter interviews.
They tended to place less emphasis on pain’s influence on their life, seeing it as a
temporary phase. This was consistent with the data in Phase 1 which showed that
few acute respondents reported previous episodes of this type of pain. Also
consistent with this outlook was that acute respondents were the most likely to
consult a physiotherapist in the first instance (24%), which may indicate that these
respondents believed their injury was treatable. Regardless, acute pain participants
also reported a greater number of pain-related limitations on their activities
compared to intermittent pain respondents. Consistent with this finding, a higher
proportion of the acute pain participants were classified at Grades III and IV (on the
Graded Chronic Pain Scales) than the intermittent pain respondents.
Respondents also reported differences in the way in which pain had affected
their employment. While few acute participants were unemployed because of their
pain condition, people with acute pain more commonly accessed sick or workers’
compensation leave than the other pain respondents. None of the intermittent
respondents were unemployed due to their pain and few reported that their pain
influenced their employment in terms of leave or changed work conditions.
Interestingly, despite differences in the amount of disability reported across
the pain subgroups, there were no differences in the rates of depressive symptoms
and anxiety in the pain samples. Across all subgroups high levels of depressive
symptoms were reported by approximately 20%. Approximately 40% of each of the
pain subgroups reported high levels of anxiety.
In summary, it appears that the different types of pain are associated with
different experiences beyond those related to their definitional differences. In
particular, respondents with chronic pain are more disabled in aspects of daily life as
measured via standardised questionnaires and are more likely to be unemployed due
to their pain, although they describe great flexibility in managing their pain. Acute
pain participants in contrast have a short term focus with their pain. However, all
pain types were associated with significant psychological distress.
Influence on Healthcare Systems
Most participants had engaged with the healthcare system about their pain,
with over 80% of the acute and intermittent pain respondents and 95% of the chronic
pain respondents seeking treatment for their pain. As noted previously, the first
source of medical attention was most commonly a general practitioner. While data
on the frequency of healthcare visits was not collected, the large proportion of the
sample that continued to receive treatment may indicate that, as reported in other
research (see Maetzel & Li, 2002 for a review), pain is likely to be an economic
burden on Queensland’s healthcare system.
In another Australian sample from New South Wales, Blyth et al. (2004)
found that chronic pain associated with greater interference (score of ≥4 on a single
item 5-point adjective scale) was related to greater use of healthcare including visits
to general practitioners, emergency departments, and hospital admissions.
Compared to pain-free adults, people with chronic pain also reported a greater
number of visits to general practitioners, emergency departments and hospital
admissions. While no information on pain duration or other pain characteristics was
available for this New South Wales sample, these results compliment the findings of
this research where two-thirds of this sample continued to receive treatment for their
pain. Clearly, chronic pain results in the ongoing use of healthcare services; this is
true for a community sample of people with chronic pain and is an additional
healthcare burden beyond the pain services provided to clinical patients.
Somewhat inconsistent with the results of the questionnaire data was the
general opinion, expressed during Phase 3, that interviewees would prefer not to
seek treatment through traditional primary care or specialist physicians. Most
interviewees also preferred to avoid or minimise the use of and/ or strength of pain
medication consumed. The frequent report that people minimised their use of pain
medication conflicts with data from the New South Wales sample where oral
medications (including vitamin supplements) were taken by 70% of this sample over
the previous 6-month period (Blyth, March, & Cousins, 2003). As no data was
collected on vitamin supplements in this research, this data is difficult to compare
across studies. Anecdotally, many interviewees mentioned the consumption of
supplements. Perhaps the majority of oral medications/ supplements reported by the
New South Wales sample are actually non-prescribed vitamin or herbal remedies.
With regard to treatment and other healthcare services, as many of the
interviewees recognised the benefits of alternate treatments (e.g., acupuncture,
chiropractic or massage) and chose these treatments over surgery or medication,
perhaps many of the current sample who were still receiving treatment for their pain
were accessing this treatment through non-traditional means. These conclusions
need to be interpreted with caution as the interviewees were a small subset of the
total sample and may not represent the views of the total sample or the broader
population of people with pain. Further research to fully investigate treatment
preference and use in terms of traditional and non-traditional health services is
recommended. Such research may assist with service planning and provision.
Comparison of Chronic Pain in this Community Sample with Clinical Samples
As noted in Chapter 2, the majority of the research into chronic pain has been
conducted with clinic patient samples (e.g., Cannella et al., 2007; Heinberg et al.,
2004; Keeley et al., 2008; McCracken & Eccleston, 2005, 2006). However, people
with chronic pain who present to pain clinics are only a small subset of the total
population of chronic pain sufferers. In addition, as clinical patients are actively
seeking medical treatment, they may represent people with chronic pain who are
coping less well with their pain. Greater understanding of the majority of people
with chronic pain relies on research with community samples, and may inform
clinical treatment by detailing the coping strategies and strengths of people with
chronic pain who are self managers of their pain condition.
The experience of chronic pain in this community sample varied
considerably and appeared to be quite different to that reported by clinical samples
of people with chronic pain. However, like clinical samples (Harris et al., 2003;
Strong et al., 1990) (McCahon et al., 2005), there were more women than men in the
current sample. Chronic pain respondents were the least likely of the pain groups to
have completed tertiary education and were older than the other groups. This is
consistent with prevalence studies that have found that lower education (Bergman et
al., 2001; Rustøen et al., 2004) and older age (Elliott et al., 1999; Ng et al., 2002;
Rustøen et al., 2004) are risk factors for chronic pain.
Also like clinical samples (McCahon et al., 2005; Strong et al., 1990), pain
duration for chronic pain ranged widely from 4 months to 40 years. The lower back
area was the most common primary site of pain, consistent with other research
(Dionne, 1999; B. F. Walker et al., 2004). Although these participants met the
definition for chronic pain on the occasion when they completed the baseline
questionnaire (i.e., pain ≥ 4 days per week for > 3 months), approximately 40%
indicated that they had experienced this type of pain on numerous occasions,
suggesting that they had pain-free episodes also. Interview data also supports this
inference; three interviewees experiencing a new episode of pain at Phase 3 were
classified as being pain-free at Phase 2.
As discussed in Chapter 4, pain-related anxiety scores for the chronic
participants were similar to those reported in a clinical sample using the same
instrument (McCracken & Dhingra, 2002). Therefore it seems that community
samples of people with chronic pain, outside a clinical setting, may experience high
levels of pain-related anxiety symptoms. This pain-related anxiety is also related to
their ability to function. In addition, the acute pain sample was similarly affected by
pain-related anxiety. While a comparison of depressive symptoms is difficult due to
the varying measures of depression used, transforming the CES-D scores into
equivalent Beck Depression Inventory scores (Fountoulakis et al., 2007) indicates
that this sample reported less symptoms of depression than would be expected based
on clinical norms (Nicholas, Asghari, & Blyth, 2008).
While pain resulted in interference in activities of daily living and social,
family and recreational activities, based on published norms for clinical samples the
chronic pain respondents in this sample had lower daily interference than clinical
patients (RMDQ; M = 8.20; SD = 5.8 vs M = 12.3; SD = 5.7) (Nicholas et al., 2008).
Although the most common site of pain was the low back region, it is possible that
the pathology associated with the respondents’ pain in the current sample was less
severe than would be seen in a clinical sample. Some caution is warranted in
interpreting the results of this study for people whose source of pain is not
musculoskeletal in nature.
Consistent with the finding of lower daily interference, the chronic pain
respondents in this sample had higher pain-related self efficacy (PSEQ; M = 42.0;
SD = 13.7 vs M = 25.5; SD = 13.8) based on these same published norms (Nicholas
et al., 2008). Chronic pain respondents also reported coping well with their pain
during the interview phase; this was contradictory to Australian normative clinic
data (Nicholas et al., 2008). While chronic pain respondents provided low
endorsement on the standardised measures of coping strategies (i.e., CPCI and
CSQ), during the Phase 3 interviews, respondents reported that a positive attitude
and keeping active were the key aspects to coping. Many of the interviewees
described being able to integrate these aspects into the management of their pain.
Regardless of the differences (or similarities) between this community
sample and published patient data, it cannot be overlooked that it is possible that
some of the participants of this research may have also been patients of a pain clinic.
It was not the intention of the research to target clinical patients. Participation in this
research was not linked with a healthcare service, which allowed a potentially wider
community sample to be obtained. However, the quantitative responses of this
sample indicated that the majority of the people with chronic pain had sought
treatment as some stage for their pain and many continued to receive healthcare for
their pain. It is not clear where they were receiving this current treatment nor did
respondents provide data on all the previous pain-related treatments which they had
received. However, in the interviews, participants expressed a preference not to use
specialist physicians. While the responses of the majority of the interviewees
indicated that they were not clinical patients nor likely to become clinical patients in
the future, regardless, the possibility that participants from the wider sample were
also patients of pain-related healthcare services cannot be ruled out.
An Exploration of Gatchel’s Model
A primary aim was to explore Gatchel’s Model of the acute to chronic pain
transition and examine possible extensions to this model. A diagram of the model is
presented in Chapter 2 on page 25. Using quantitative data, the components of
Gatchel’s Model were examined in two ways; comparing people with acute vs.
chronic pain using a cross-sectional design in Phase 1 and tracking changes in
mental and physical de-conditioning over time for those whose pain persisted at
follow-up (Phase 2). The key components of Gatchel’s model were also discussed
in the semi-structured interviews at Phase 3. The data are discussed with regard to
the fit of Gatchel’s Model with this non-clinical sample and the value of the
additional risk and protective factors in explaining the development of chronic pain
or increasing disability.
Fit between Gatchel’s Model and the Pain Experience of this Community Sample
Overall, the experience described by this community sample did not fit well
with Gatchel’s Model. Regardless, an aspect of Gatchel’s Model that was consistent
with the experience of these respondents was that the two de-conditioning
syndromes (i.e., mental and physical de-conditioning) were related to each other as
proposed by the model. At baseline, moderate positive correlations were reported
between measures of disability, depressive symptoms and anxiety. Further, some
interviewees articulated that there was a link between their emotional state and
activity levels, although this was mostly referred to using a positive framework;
where being active was viewed as improving one’s emotional or mental state. Also
contradictory with the processes described by the model, over a 3-month follow-up
period, changes in disability, depressive symptoms and anxiety were not associated
with each other in a way that suggested that changes in one would produce changes
in the other. In this sense, evidence that one de-conditioning syndrome influenced
the other was absent.
A finding of this research was that the experience of this community sample
was not time dependent in the way that it is described in Gatchel’s Model. When the
measures of de-conditioning (two self-report measures of disability, one measure of
depressive symptoms and one measure of pain-related anxiety) were examined in
relation to time since pain onset (i.e., pain duration), duration was not correlated
with these variables in cross-sectional analyses (see Chapter 5) nor did pain duration
predict future disability (see Chapter 6). Further, over the 3-month follow-up
period, depressive symptoms and global disability actually decreased even though
these chronic pain respondents still had pain.
While, Gatchel’s Model predicts that pain leads to inactivity an examination
of the groups at a cross-sectional level (Phase 1) showed that physical deconditioning was present in chronic pain respondents, many participants of the Phase
3 interviews specifically spoke about remaining active despite pain. Some people
remained active by changing the way they perform tasks, seeking help or going
slower. In addition, there were a number of strategies that interviewees cited as
being important to remain active. These strategies included being prepared, stepping
back rather than rushing in to a commitment or a task, not measuring themselves
against others and doing activities that they enjoyed. For the majority of these
participants, pain did not lead to significant physical inactivity.
Examination of two common types of mental de-conditioning revealed that
pain duration was not correlated with depressive symptoms or pain-related anxiety at
baseline or follow-up (as noted earlier). Regardless, some interviewees spoke about
the influence that their emotional state had on their pain experience. Rumination
and feeling depressed about their situation were seen by interviewees to have a
negative influence on their experience of pain and life in general.
In conclusion, Gatchel’s Model did not fit well with the data from this study.
While the data supported the links between mental and physical de-conditioning, the
course of the de-conditioning processes was not supported. There were a number of
strategies that respondents used, which may have minimised de-conditioning. These
strategies (that is, staying positive and remaining active) are those which health
professionals already encourage with patient samples. While replication of these
results is required, this data suggests that Gatchel’s Model does not capture the
processes involved in the development of continuation of chronic pain in non-patient
samples.
Exploring the Extension Variables (Risk & Protective Factors)
A number of risk factors for the development of chronic pain and factors that
were proposed to be protective against the development of chronic pain were
assessed. These variables were also included in this research to gauge their
usefulness for inclusion in Gatchel’s Model to explain some of the underlying
processes that may exist during the course of chronic pain (not explained by mental
and physical de-conditioning syndromes as they currently stand).
Due to the recruitment strategy used, the overall sample in this research
consisted of a greater proportion of women and was older than would be expected
based upon Australian census data. As a result, two of the proposed risk factors
(that is, gender and age) were not able to be explored with this data. The other risk
factors, fear-avoidance beliefs, catastrophising (which was a factor score derived
from the CSQ, CPCI and SOPA subscales), and the belief that one will not return to
work, were examined. These risk factors were positively associated with the
measures of de-conditioning and pain intensity, and negatively correlated with the
protective factors. These findings demonstrate that, in this community sample, these
three risk factors were correlated in the expected theoretical direction. Likewise, the
associations between the protective factors and de-conditioning measures were in the
predicted direction, with the exception of social support (which was not correlated
with the disability measures).
The predictive ability of each of the risk and protective factors on each of the
de-conditioning measures was assessed in Phase 2 (see Chapter 6). Despite high
inter-correlations between the risk and protective factors (which may have
minimised their opportunity for unique prediction), significant predictors of physical
de-conditioning were self efficacy and Limiting Activities (a derived coping factor).
The significant predictors of each of the mental de-conditioning syndromes differed
somewhat. Depressive symptoms were predicted by optimism, social support,
Influence of Emotion (coping factor: belief that one’s emotional state influences
their pain experience) and Catastrophising (coping factor) whereas anxiety was
predicted by self efficacy, fear-avoidance beliefs, Limiting Activities, Use of
Distraction (active coping factor), Influence of Emotion and Catastrophising. These
findings suggest that self-efficacy may be important for both the physical and
psychosocial components of chronic pain. The other psychosocial variables
typically have the greatest influence on the emotional or psychological components
of chronic pain.
Predicting the Development of Chronic Pain
The prediction of the development of chronic pain was of particular interest
for this research. Gatchel’s Model did not provide a useful framework for this
prediction. As noted in Chapter 6, the conclusions of this research about the
development of chronic pain are limited by the small numbers of participants who
reported acute pain at baseline and continued to have pain at follow-up. Regardless,
two predictors of the development of chronic pain were identified. These were rural
residence and higher depressive symptom score at baseline. Greater depressive
symptoms are consistent with Gatchel’s Model; potentially these participants
displayed signs of early mental de-conditioning. However, since this was true for
half of the new chronic pain respondents only, the predictive utility of this variable
is limited. Future large-scale research which specifically targets people with acute
pain is required to further tease out these relationships.
Predicting the Continuation of Pain
In addition to predicting the development of chronic pain, the factors that
predicted continued disability were explored. These analyses aimed to assess the
value of the variables from Gatchel’s Model and also the additional risk and
protective factors. When predicting those with continued chronic pain compared to
those for whom chronic pain would resolve, two predictors of continued pain were
observed. These included a constant pattern of pain and very high perceived social
support. This finding provided some evidence for one of the proposed protective
factors, although in this case very high perceived social support was a risk factor for
continued pain.
Transposing the Extension Variables onto Gatchel’s Model
One of the objectives of this research was to evaluate the value of the
proposed extension variables with the view that one or more of these may be a
useful addition to Gatchel’s Model. This was a significant objective of the research.
A clear theoretical framework to guide research into the development or prediction
of chronic pain has been lacking in much of the pain literature. It was proposed that
if Gatchel’s Model could provide this basic model on which to base our
understanding of these processes, then hanging the influence of these proposed
extension variables (on chronic pain development) onto Gatchel’s Model would be
useful.
Because the findings of this research program did not support the utility of
Gatchel’s Model in a non-patient sample, the basic model was not well supported.
For this reason, the utility of 'adding on' the significant risk and protective factors
identified in this investigation was not clear. Instead, the pattern of results may be
better understood from other theoretical perspectives and these perspectives are
considered next.
Contribution to Theory
This research found limited support for the constructs and processes
described by Gatchel’s Model. It is therefore important to consider alternate
theories as a basis for understanding the process of the development and
continuation of chronic pain in non-patient groups; the majority of people with
chronic pain. Two other primary theories of chronic pain development are the FearAvoidance Model (Vlaeyen et al., 1995) and more recently, the AttachmentDiathesis Model of Chronic Pain (ADMoCP) (Meredith, Ownsworth, & Strong,
2008).
Fear-Avoidance Model
The Fear-Avoidance Model of Exaggerated Pain Perception, originally
proposed 1983, was based on the premise that a fear of pain may lead to two
opposite outcomes; confrontation or avoidance of the “threat” (Lethem, Slade,
Troup, & Bentley, 1983). Avoidance was proposed to lead to exaggerated pain
perception. The Fear-Avoidance Model was developed later as not only fear of pain
but fear of movement that may cause pain, or fear of (re)injury was identified was an
important factor (Vlaeyen et al., 1995). This fear of (re)injury in addition to pain
catastrophising is believed to underlie fear-avoidance behaviour resulting in
disability, depression and pain-related anxiety.
The Fear-Avoidance Model has much support in the literature. For example,
fear-avoidance beliefs have been found to be superior predictors of both selfreported and objective measures of disability (compared to negative affect, pain
intensity or pain catastrophising) in chronic pain patient samples (e.g., Crombez et
al., 1999). In addition, psychological treatments based on the Fear-Avoidance Model
of chronic pain, which aim to expose individuals to activities previously avoided due
to fear of (re)injury, have been shown to be successful (Woods & Asmundson,
2008).
The results of this research also offer some support for the Fear-Avoidance
Model. For example, fear avoidance beliefs were positively correlated with current
pain, level of disability, pain-related anxiety and depressive symptoms (all r’s ≥ .36;
see Table 25; Chapter 5). In addition, fear-avoidance beliefs were a significant
predictor of disability (see Tables 26 and 27; Chapter 5) and anxiety (see Table 29;
Chapter 5). However, caution should be used when considering these results in light
of the Fear-Avoidance Model because fear of (re)injury was not specifically
assessed. Still, it may be appropriate to conclude that these results can be
understood within this framework and may offer some indirect support for the FearAvoidance Model.
Attachment-Diathesis Model of Chronic Pain
The ADMoCP contains four main sections: attachment diathesis, cognitive
appraisals, responses of the individual (emotions, coping behaviour and strategies)
and impact on adjustment to pain (Meredith et al., 2008). It is proposed by this
model that pain is a stressor that triggers cognitive appraisals (e.g., of pain and
available support) and emotional, cognitive and behavioural responses to this
stressor (e.g., coping strategies) as per the attachment diathesis an individual has.
Any vulnerabilities (due to attachment insecurities), the cognitive appraisals and the
response of the individual all affect how well the individual manages, copes with or
adjusts to pain and their wellness in spite of pain.
Given that the ADMoCP has been published only recently, there is little
research directly examining the variables that this model posit as important. The
results of the current research also do not shed light on the mechanisms proposed by
the ADMoCP. Although, some further evidence for the ADMoCP may be that few
people have insecure attachments (van Ijzendoorn, 1995) and few people access
specialist medical pain treatment in order to manage their pain condition. Greater
research is needed to evaluate the usefulness of the ADMoCP in research and
clinical settings.
As this research found limited support for the constructs and processes
described by Gatchel’s Model, it is recommended that either of these two alternate
models be examined for use with community samples to further our understanding
of the processes of the development of chronic pain. In deciding which model to
pursue in future research, the Fear-Avoidance Model is recommended. There are
two reasons for this recommendation. First, the Fear-Avoidance Model has a longer
research history to substantiate it and therefore may be regarded as more wellestablished. Second, it provides a better fit with data from this research than the
ADMoCP, although it must also be acknowledged that there was more overlap
between the variables assessed in this study and the variables of the Fear-Avoidance
Model than the variables of the ADMoCP.
Practical Applications
The results of this research support at least one of the treatment goals of pain
clinics. Interview respondents talked at length about the importance of maintaining
employment or links with other meaningful activity, which is not related to their
pain experience. As the primary goal for pain clinics is to encourage patients to
become more physically active and engage in meaningful activities despite pain
(McCracken, 1998; McCracken & Eccleston, 2005), it is encouraging that
respondents who have not accessed this type of clinical service have found that
engaging in meaningful activity is possible and useful in the self-management of
their pain. It may also be possible to use the strategies that these research
respondents had found helpful – including making preparations before starting a
task, not measuring themselves against others and doing things that they enjoy – to
encourage people with pain to maintain their activity levels.
The participants in this research most often had first sought healthcare
through general practitioners. It would therefore seem that general practitioners are
best placed to provide information about the basic physiology of pain and managing
pain by staying active. If this is not a service that general practitioners are able to
provide, general practitioners may be best placed to refer to other community-based
pain-specific treatment services. In Australia, as more and more general practice
centres include other allied health consultants (such as clinical nurses, psychologists,
physiotherapists, and pharmacists), it seems practicable and valuable for
community-based pain specialists to be included in these primary care centres. In
this manner, individuals very early in the pain trajectory could access guidelines and
healthcare advice about managing their pain before disability became entrenched.
Effective short-term intervention at this early stage has the potential to be very cost
effective.
While caution is warranted in the interpretation of the data about the
continuation of chronic pain (as noted previously, replication of this result is
required), these results indicate that practitioners should be wary of the effects of
secondary rewards via very strong social support on the experience of chronic pain.
As other authors have noted (Flor, Kerns, & Turk, 1987; Paulsen & Altmaier, 1995),
involvement of the patients’ significant others may be necessary to improve
functioning and meet activity goals.
Finally, the use of a mixed-method approach in this research has
demonstrated that practitioners using standardised pain questionnaires with a
community population should be wary about how respondents interpret some items.
While these questionnaires are standardised and have demonstrated reliability and
validity in clinical samples, most pain questionnaires were developed with clinical
(and often treatment) samples. Clinical patients have therefore been exposed to the
language that is used in clinical environments and often in these questionnaires.
Without further research, practitioners cannot be confident that the underlying
construct that the items are designed to measure is actually been captured in a
population sample. Future research that generates community-based normative data
may be helpful to address this gap in the literature.
Strengths and Limitations of this Research
There are a number of strengths to this program of research. This project is
one of the first pain-specific community survey conducted in Australia (see also
Blyth, March, & Cousins, 2003) and the first longitudinal study of risk factors for
chronic pain in Australia. Previous population-based research into pain in Australia
has focused on specific pain sites groups (e.g., lower extremities (Chen et al., 2003),
low back pain (B. F. Walker et al., 2004)) or population groups (e.g., elderly people
(Chen et al., 2003)). Data on broader population groups or pain sites has been
gained through more general health surveys (Blyth et al., 2001). Therefore, this
research addresses an important gap in knowledge in terms of examining the
influence and experience of pain (including chronic pain) in a community sample.
The overall scope of the research and nature of the data collection was
considerable. The research encompassed data on pain variables, disability and
psychosocial variables using multi-method data collection and included a
comprehensive questionnaire with follow-up and qualitative data. A wide-ranging
methodology was used to obtain both standardised measurement of pain variables
and in-depth exploration of the pain experience from the viewpoint of people with
pain. The value of including the qualitative component into the program of research
was evident when a comparison was made between the questionnaire and interview
data; it is difficult to comprehensively categorise people’s pain experience using a
questionnaire.
Design features, such as longitudinal data collection and multi-method
techniques, were incorporated to explore the experience of pain; the use of these
features adds to the reliability and utility of the overall findings. The combination of
quantitative data and qualitative data allowed specific hypotheses to be tested
(proposed on the basis of Gatchel’s Model), comparative data to be collected for
reference to previous and future pain data sets, as well as the lived experience of
pain to be described. All of which allow clinicians and researchers to gain a fuller
understanding of the processes involved in acute and chronic pain.
The use of a theoretical framework to guide the research, including the
inclusion of risk and protective variables, is another strength of this program of
research. Explaining how and why a variable exerts its influence is equally
important as the finding that a psychological variable is linked with chronic pain
(Linton, 2000; Pincus et al., 2002). One of the criteria applied to the inclusion of
these extension variables was that they would act on one of the two de-conditioning
processes proposed by Gatchel’s Model (that is, mental or physical de-conditioning).
Predominantly, previous pain research has been atheoretical (e.g., Galizzi & Boden,
2003; McCracken & Eccleston, 2005). This is particularly true for research that has
examined the relationships between pain and other variables in community samples
(e.g., Benjamin et al., 2000; Karoly & Ruehlman, 2006). However, the value of
theory or theoretical models to provide a basis for understanding the relationships
between variables cannot be understated.
The results of this research improve our understanding of the utility of a
prominent theoretical framework (Gatchel's model) in the area. To the author’s
knowledge, this is the first empirical examination of some of the key processes that
underlie Gatchel’s Model. This is an important advance for pain research, as
Gatchel’s Model has been presented in the literature for over a decade without direct
empirical review. Even though this model did not provide a good description of the
pain experience of participants, we now know something more about the
generalisability of this framework beyond clinical pain samples.
Regardless, some limitations of the research need to be considered. As
described in Chapters 5 and 6, in terms of the measurement of Gatchel’s concepts,
self-report disability measures provide only a proxy estimate of objective disability.
In order to address this issue and increase the reliability of the results two different
self-report measures of disability were utilized. While the measures were strongly
correlated (r = .6), there was not 100% overlap between the two, indicating that each
instrument tapped into different aspects of disability. This enabled a more
comprehensive examination of disability to be achieved, but the proxy nature of this
measurement needs noting as a potential limitation.
Similarly, a limitation of this research is how mental de-conditioning was
operationalised; this was also described in Chapters 5 and 6. Gatchel (1991a)
describes mental de-conditioning as “the development of a “layer” of behavioral and
psychological problems that occur in response to the chronic pain and the patients’
attempts to cope with it” (Gatchel, 1991a, p. 280). These behavioural or
psychological problems are of sufficient strength to “prevent the individual from
maintaining a productive lifestyle” (Gatchel, 1991a, p. 280) in order to be
considered mental de-conditioning. As can be seen from this description, mental deconditioning encompasses a vast number of behavioural or psychological problems.
Due to the relatively narrow conceptualisation of mental de-conditioning used, this
research was unable to capture all of the possible mental de-conditioning processes
and was not tailored to each participant’s predisposition to particular psychological
problems. Regardless, this research focused on the two most common
manifestations of mental de-conditioning, that is, depression and anxiety, to try to
capture the majority of mental de-conditioning syndromes. Future research would
need to assess personality characteristics prior to individuals’ developing chronic
pain to attempt to address the limitations of this study. Previously, Gatchel has
relied on the MMPI-2 to capture personality data. While the MMPI-2 is the most
commonly used personality measure (Deardorff, 2000), there is some controversy
about it use and the usefulness of the data it provides (Deardorff, 2000). In addition,
its length and the restricted conditions of use prohibit its use with a large community
sample, like the one used in this research. Nevertheless, if future research uses
Gatchel’s Model in a non-clinical sample, this discussion may inform attempts to
operationalise concepts from that model, identify ways of improving on the methods
used here, and contribute to recognition of important methodological considerations.
Another limitation of this study, highlighted previously, is that it is difficult
to assess the representativeness of the sample as the pain-free respondents consisted
of a greater number of women and were older than would have been predicted by
Australian census data. While this does not necessarily preclude the
representativeness of the pain samples, it does indicate that caution should be
applied when interpreting these results in the context of the wider Australian
community. The findings of this research may be more applicable to women and
older adults with pain. However, as previous research has indicated, female sex and
older age are risk factors for chronic pain (Blyth et al., 2001; Elliott et al., 1999;
Rustøen et al., 2004), it is likely that these results may be applied to the majority of
people with pain.
This research aimed to use a broader sample of the general population than
previous studies to broaden the applicability of these results beyond employee (e.g.,
Hagen et al., 2000; Karjalainen et al., 2001b) or patient samples (e.g., McCahon et
al., 2005; McCracken & Eccleston, 2005). This objective was not achieved due to
the low response rate and small number of acute participants who developed chronic
pain. While the recruitment strategy achieved a random sample of households, using
a non-addressed postal package meant that follow-up of non-respondents was not
possible. As discussed in Chapter 4, other research may have achieved higher
response rates through the use of addressed correspondence and multiple nonrespondent reminders. Regardless, the small numbers of people who developed pain
during the course of the research means that some important variables may not have
been captured due to low power.
The sample consisted of adults who voluntarily participated and therefore
could be considered to have self selected into the research. It can be argued that the
effects of self selection, however, were minimised (at least in part) by randomly
targeted households to receive the baseline questionnaire and specifically targeting
people with pain. Nonetheless, it remains possible that this sample reflects those
people with chronic pain who are coping most well with their pain and, therefore,
have the time and energy to participate. Alternatively, the sample may consist of
people with less severe pain or less severe psychological symptoms. This latter
interpretation seems unlikely as the anxiety levels reported by this sample were
similar to those reported by some clinical samples (McCracken & Dhingra, 2002).
Additionally, an attempt was made to minimise some of these possible biases by
offering an incentive to participate by way of a competition to win a holiday
voucher. In addition, to reduce taxing potential participants, people were instructed
that they could complete the questionnaire in multiple sittings and a reply-paid
envelope was provided so that there were no out-of-pocket expenses associated with
participation. Given the length of the baseline questionnaire and the tiring effects of
pain, obtaining a sample of over 400 participants with pain is noteworthy. Recall
also that the rate of chronic pain in the selected households for this research was
consistent with previous Australian prevalence research (Blyth et al., 2001). This
suggests that a good response rate for those with chronic pain was achieved. In
addition, a good response rate at follow-up was achieved which is consistent with
other large-scale community research (e.g., Bergman et al., 2002; Elliott et al.,
2002).
While self-report measures are a typical and accepted methodology in this
area (Blyth et al., 2001; Linton, 2005; McCracken & Eccleston, 2006), the reliance
on self-report measures for the variables assessed in Phases 1 and 2 may be viewed
as a limitation of the research. However, some of the key variables assessed in this
research (e.g., depressive symptoms and beliefs) are only able to be captured by self
report (Asghari & Nicholas, 2001). In addition, the use of well-validated and
specific assessment tools allowed for the comparison of the findings of this research
with previous studies. Regardless, using self-reported disability in this research may
have resulted in artificially inflated relationships between disability and other (self
reported) psychosocial variables due to measurement error and was complicated by
the fact that some measures were developed for clinical samples as noted previously.
The design of future research and interpretation of the current findings should be
cognisant of these theoretical and practical limitations.
Future Directions
This program of research has highlighted a number of areas for future
research, which have been mentioned previously. These include research which
specifically targets community-dwelling adults who are coping less well with their
pain perhaps through community-based health services such as general practitioners
or other allied health services. Such research would compliment the current research
to provide a further opportunity to inform community early interventions for those
who require such treatments. Equally, research that targets men and younger adults
(i.e., 18-35 years) would add to our knowledge of the pain experience over the
spectrum of the lifespan and for men (who were under-represented in the current
sample). Likewise, an examination of the use of medication and other treatments in
the management of chronic pain in a community setting would provide a clearer
picture of the current cost of chronic pain in non-patient populations.
While Gatchel’s Model does not appear to generalise well outside a patient
population and was not a useful framework for understanding the experience of pain
of this community sample, this research did not provide a true test of this model.
Replication of this research that addresses the measurement limitations, described
earlier, may help determine whether Gatchel’s Model provides a useful framework
to understand the pain experience in a community samples. Use of objective
measures of disability and assessment of personality prior to the development of
chronic pain would strengthen the assessment of this model. However, given the
discussion of other theoretical frameworks to understand the experience of pain in
this sample, further research which utilises the Fear-Avoidance Model is also
warranted. Similarly, examination of the risk and protective factors that were
identified in the current research as important either in the development or
continuation of pain is necessary.
In summary, research of the nature described is required to better understand
how people with chronic pain mange their pain and further examine some the
important factors in the transition to chronic pain. Research of this kind may assist
to reduce the burden of chronic pain.
Conclusion
The current program of research examined the experience of chronic pain in
a community sample, assessed the utility of a conceptual model of acute to chronic
pain transition proposed by Gatchel (1991a) in a non-clinical sample, and evaluated
a number of risk and protective factors that may be useful extensions to this model.
Overall the findings highlight a number of issues. First, chronic pain in a
community sample is associated with significant disability and psychological
distress. It would appear that the pain experience of people with acute, intermittent
and chronic pain is different across a number of variables including disability levels
and influence on employment. This sample reported similar levels of pain-related
anxiety but lower levels of depressive symptoms and physical disability when
compared to clinical samples. Second, in its current conceptualisation Gatchel’s
Model of the acute to chronic pain transition did not match the experience of this
non-clinical sample. In particular, the development of psychological distress and
disability are not time dependent as is described by the model. Third, the findings
highlight some factors for further research. These include self efficacy, optimism,
social support, fear-avoidance beliefs, catastrophising and some specific coping
strategies, which seem to play a role in the acute pain to chronic pain disability
transition, at least in non-clinical samples. The results of this study provide a more
comprehensive picture of the experience of people with chronic pain who are not
clinical pain patients and highlight some variables that may be important to consider
in the design of community-based treatment.
References 273
REFERENCES
Abrams, M. P., Carleton, R. N., & Asmundson, G. J. G. (2007). An exploration of
the psychometric properties of the PASS-20 with a nonclinical sample. The
Journal of Pain, 8(11), 879-886.
Access Economics. (2007). The high price of pain: The economic impact of
persistent pain in Australia. Sydney: MBF Foundation and University of
Sydney Pain Management Research Institute.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and
Human Decision Processes, 50, 179-211.
Anderson, K. O., Dowds, B. N., Pelletz, R. E., Thomas, E. W., & Peeters-Asdourian,
C. (1995). Development and initial validation of a scale to measure selfefficacy beliefs in patients with chronic pain. Pain, 63(1), 77-83.
Andersson, G. B. J. (1999). Epidemiological features of chronic low-back pain.
Lancet, 354, 581-585.
Andersson, H. I. (2004). The course of non-malignant chronic pain: A 12-year
follow-up of a cohort from the general population. European Journal of
Pain, 8(1), 47-53.
Andersson, H. I., Ejlertsson, G., Leden, I., & Rosenberg, C. (1993). Chronic pain in
a geographically defined general population: Studies of differences in age,
gender, social class, and pain localization. Clinical Journal of Pain, 9, 174182.
Arnstein, P., Caudill, M., Mandle, C. L., Norris, A., & Beasley, R. (1999). Self
efficacy as a mediator of the relationship between pain intensity, disability
and depression in chronic pain patients. Pain, 80, 483-491.
References 274
Asghari, A., & Nicholas, M. K. (2001). Pain self-efficacy beliefs and pain
behaviour. A prospective study. Pain, 94(1), 85-100.
Asghari, A., & Nicholas, M. K. (2006). Personality and pain-related beliefs/ coping
strategies: A prospective study. Clinical Journal of Pain, 22(1), 10-18.
Australian Bureau of Statistics. (1997). Mental health and wellbeing: Profile of
adults (No. 4326.0). Canberra: Australian Bureau of Statistics.
Australian Bureau of Statistics. (2004). Injury in Australia: A snapshot (No.
4825.0.55.001). Canberra: Australian Bureau of Statistics.
Australian Bureau of Statistics. (2005). Population Projections, Australia, 2004 to
2101 (No. 3222.0). Canberra: Australian Bureau of Statistics.
Australian Bureau of Statistics. (2007). Australian Social Trends 2007:
Qualification profile of Australians. Retrieved 24 May 2008. from
http://www.abs.gov.au/AUSSTATS/[email protected]/Latestproducts/FFEDA0779C
20049DCA25732C00207383?opendocument.
Australian Bureau of Statistics. (2008). Regional Population Growth, Australia,
2006-07 (No. 3218.0). Canberra: Australian Bureau of Statistics.
Australian Department of Health and Aged Care. (1999). Measuring remoteness:
Accessibility/remoteness index of Australia (ARIA). Canberra: Australian
Department of Health and Aged Care.
Axinn, W. G., & Pearce, L. D. (2006). Mixed method data collection. New York:
Cambridge University Press.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84(2), 191-215.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American
Psychologist, 37(2), 122-147.
References 275
Banks, S. M., & Kerns, R. D. (1996). Explaining high rates of depression in chronic
pain: A diathesis-stress framework. Psychological Bulletin, 119(1), 95-110.
Bement, M. K. H., Skyba, D. A., Radhakrishnan, R., & Sluka, K. A. (2003). Review:
Central sensitization and musculoskeletal pain. Seminars in Pain Medicine,
1(3), 139-149.
Benjamin, S., Morris, S., McBeth, J., Macfarlane, G. J., & Silman, A. J. (2000). The
association between chronic widespread pain and mental disorder: A
population-based study. Arthritis & Rheumatism, 43(3), 561-567.
Bergman, S., Herrstrom, P., Hogstrom, K., Petersson, I. F., Svensson, B., &
Jacobsson, L. T. H. (2001). Chronic musculoskeletal pain, prevalence rates,
and sociodemographic association in a Swedish population study. Journal of
Rheumatology, 28(6), 1369-1377.
Bergman, S., Herrstrom, P., Jacobsson, L. T. H., & Petersson, I. F. (2002). Chronic
widespread pain: A three year followup of pain distribution and risk factors.
Journal of Rheumatology, 29(4), 818-825.
Block, A. R., Gatchel, R. J., Deardorff, W. W., & Guyer, R. D. (2003). Postsurgical
deconditioning and reconditioning. In A. R. Block & R. J. Gatchel (Eds.),
Psychology of spine surgery (pp. 193-206). Washington D.C.: American
Psychological Association.
Blyth, F. M., March, L. M., Brnabic, A. J. M., & Cousins, M. J. (2004). Chronic
pain and frequent use of health care. Pain, 111(1), 51-58.
Blyth, F. M., March, L. M., Brnabic, A. J. M., Jorm, L. R., Williamson, M., &
Cousins, M. J. (2001). Chronic pain in Australia: A prevalence study. Pain,
89(2-3), 127-134.
References 276
Blyth, F. M., March, L. M., & Cousins, M. J. (2003). Chronic pain-related disability
and use of analgesia and health services in a Sydney community. Medical
Journal of Australia, 179(2), 84-87.
Blyth, F. M., March, L. M., Nicholas, M. K., & Cousins, M. J. (2003). Chronic pain,
work performance and litigation. Pain, 103(1), 41-47.
Blyth, F. M., March, L. M., Nicholas, M. K., & Cousins, M. J. (2005). Selfmanagement of chronic pain: A population-based study. Pain, 113(3), 285292.
Bonanno, G. A. (2004). Loss, trauma, and human resilience: Have we
underestimated the human capacity to thrive after extremely aversive events?
American Psychologist, 59(1), 20-28.
Bonanno, G. A., Papa, A., & O'Neill, K. (2001). Loss and human resilience. Applied
& Preventive Psychology, 10(3), 193-206.
Bradburn, N. M. (1969). The structure of psychological well-being. Chicago: Aldine
Publishing Company.
Brattberg, G., Thorslund, M., & Wikman, A. (1989). The prevalence of pain in a
general population. The results of a postal survey in a county of Sweden.
Pain, 37, 215-222.
Breivik, H., Collett, B., Ventafridda, V., Cohen, R., & Gallacher, D. (2006). Survey
of chronic pain in Europe: Prevalence, impact on daily life, and treatment.
European Journal of Pain, 10(4), 287-333.
Breuer, B., Pappagallo, M., Tai, J. Y., & Portenoy, R. K. (2007). U.S. boardcertified pain physician practices: Uniformity and census data of their
locations. The Journal of Pain, 8(3), 244-250.
References 277
Buer, N., & Linton, S. J. (2002). Fear-avoidance beliefs and catastrophizing:
Occurrence and risk factor in back pain and ADL in the general population.
Pain, 99(3), 485-491.
Burton, A. K., Tillotson, K. M., Main, C. J., & Hollis, S. (1995). Psychosocial
predictors of outcome in acute and subchronic low back trouble. Spine,
20(6), 722-728.
Campbell, C., & Guy, A. (2007). 'Why can't they do anything for a simple back
problem?' A qualitative examination of expectations for low back pain
treatment and outcome. Journal of Health Psychology, 12(4), 641-652.
Cannella, D. T. L., Lobel, M., Glass, P., Lokshina, I., & Graham, J. E. (2007).
Factors associated with depressed mood in chronic pain patients: The role of
intrapersonal coping resources. The Journal of Pain, 8(3), 256-262.
Carver, C. S., & Scheier, M. F. (2003). Optimism. In S. J. Lopez & C. R. Snyder
(Eds.), Positive psychological assessment: A handbook of models and
measures (pp. 75-89). Washington, D.C.: American Psychological
Association.
Chen, J., Devine, A., Dick, I. M., Dhaliwal, S. S., & Prince, R. L. (2003). Prevalence
of lower extremity pain and its association with functionality and quality of
life in elderly women in Australia. The Journal of Rheumatology, 30(12),
2689-2693.
Ciccone, D. S., & Just, N. (2001). Pain expectancy and work disability in patients
with acute and chronic pain: A test of the fear avoidance hypothesis. The
Coons, M. J., Hadjistavropoulos, H. D., & Asmundson, G. J. G. (2004). Factor
structure and psychometric properties of the Pain Anxiety Symptoms Scale-
References 278
20 in a community physiotherapy clinic sample. European Journal of Pain,
8(6), 511-516.
Corbett, M., Foster, N. E., & Ong, B. N. (2007). Living with low back pain - stories
of hope and despair. Social Science & Medicine, 65(8), 1584-1594.
Coudeyre, E., Rannou, F., Tubach, F., Baron, G., Coriat, F., Brin, S., Revel, M., &
Poiraudeau, S. (2006). General practitioners' fear-avoidance beliefs influence
their management of patients with low back pain. Pain, 124(3), 330-337.
Cowan, P. A., Cowan, C. P., & Schultz, M. S. (1996). Thinking about risk and
resilience in families. In E. M. Hetherington & E. A. Blechman (Eds.),
Stress, coping, and resiliency in children and families (pp. 1-38). New
Jersey: Lawrence Erlbaum Associates, Inc.
Crombez, G., Vlaeyen, J. W. S., Heuts, P. H. T. G., & Lysens, R. (1999). Painrelated fear is more disabling than pain itself: Evidence on the role of painrelated fear in chronic back pain disability. Pain, 80, 329-339.
Crook, J., Milner, R., Schultz, I. Z., & Stringer, B. (2002). Determinants of
occupational disability following a low back injury: A critical review of the
literature. Journal of Occupational Rehabilitation, 12(4), 277-295.
de Wit, R., van Dam, F., Litjens, M.-J., & Huijer Abu-Saad, H. (2001). Assessment
of pain cognitions in cancer patients with chronic pain. Journal of Pain &
Symptom Management, 22(5), 911-924.
Deardorff, W. W. (2000). The MMPI-2 and chronic pain. In R. J. Gatchel & J. N.
Weisberg (Eds.), Personality characteristics of patients with pain. (pp. 109125): American Psychological Association.
References 279
Department of Local Government Planning Sport and Recreation. (2005).
Population growth - highlights and trends. Queensland. Canberra:
Department of Local Government Planning Sport and Recreation.
Dionne, C. E. (1999). Low back pain. In I. K. Crombie, P. R. Croft, S. J. Linton, L.
Le Resche & M. Von Korff (Eds.), Epidemiology of pain: A report of the
task force on epidemiology of the International Association for the Study of
Pain (pp. 283-297). Seattle, Washington: IASP Press.
Duke, J., Leventhal, H., Brownlee, S., & Leventhal, E. A. (2002). Giving up and
replacing activities in response to illness. Journals of Gerontology: Series B:
Psychological Sciences & Social Sciences, 57B(4), 367-376.
Ekberg, K., Björkqvist, B., Malm, P., Bjerre-Kiely, B., & Axelson, O. (1994).
Controlled two year follow up of rehabilitation for disorders in the neck and
shoulders. Occupational and Environmental Medicine, 51(12), 833-838.
Elders, L. A. M., van der Beek, A. J., & Burdorf, A. (2000). Return to work after
sickness absence due to back disorders – A systematic review on intervention
strategies. International Archives of Occupational and Environmental
Health, 73(5), 339-348.
Elliott, A. M., Smith, B. H., Hannaford, P. C., Smith, W. C., & Chambers, W. A.
(2002). The course of chronic pain in the community: Results of a 4-year
follow-up study. Pain, 99(1-2), 299-307.
Elliott, A. M., Smith, B. H., Penny, K. I., Smith, W. C., & Chambers, W. A. (1999).
The epidemiology of chronic pain in the community. Lancet, 354(9), 12481252.
References 280
Eriksen, J., Ekholm, O., Sjøgren, P., & Rasmussen, N. K. (2004). Development of
and recovery from long-term pain. A 6-year follow-up study of a crosssection of the adult Danish population. Pain, 108(1-2), 154-162.
Evers, A. W. M., Kraaimaat, F. W., Geenen, R., & Bijlsma, J. W. J. (1998).
Psychosocial predictors of functional change in recently diagnosed
rheumatoid arthritis patients. Behaviour Research and Therapy, 36(2), 179193.
Evers, A. W. M., Kraaimaat, F. W., Geenen, R., Jacobs, J. W. G., & Bijlsma, J. W. J.
(2003). Pain coping and social support as predictors of long-term functional
disability and pain in early rheumatoid arthritis. Behaviour Research and
Therapy, 41(11), 1295-1310.
Fitzgerald, T. E., Tennen, H., Affleck, G., & Pransky, G. S. (1993). The relative
importance of dispositional optimism and control appraisals in quality of life
after coronary artery bypass surgery. Journal of Behavioral Medicine, 16(1),
25-42.
Flor, H., Kerns, R. D., & Turk, D. C. (1987). The role of spouse reinforcement,
perceived pain, and activity levels of chronic pain patients. Journal of
Psychosomatic Research, 31(2), 251-259.
Forseth, K. Ø., Førre, Ø., & Gran, J. T. (1999). A 5.5 year prospective study of selfreported musculoskeletal pain and of Fibromyalgia in a female population:
Significance and natural history. Clinical Rheumatology, 18, 114-121.
Fountoulakis, K. N., Bech, P., Panagiotidis, P., Siamouli, M., Kantartzis, S.,
Papadopoulou, A., Papadopoulou, M., Kaprinis, S., Kourila, E., Iacovides,
A., & St. Kaprinis, G. (2007). Comparison of depressive indices: Reliability,
References 281
validity, relationship to anxiety and personality and the role of age and life
events. Journal of Affective Disorders, 97(1-3), 187-195.
Fritz, J. M., George, S. Z., & Delitto, A. (2001). The role of fear-avoidance beliefs in
acute low back pain: Relationships with current and future disability and
work status. Pain, 94(1), 7-15.
Frost, H., Lamb, S. E., & Shackleton, C. H. (2000). A functional restoration
programme for chronic low back pain: A prospective outcome study.
Physiotherapy, 86(6), 285-293.
Galizzi, M., & Boden, L. I. (2003). The return to work of injured workers: Evidence
from matched unemployment insurance and workers' compensation data.
Labour Economics, 10(3), 311-337.
Gatchel, R. J. (1991a). Early development of physical and mental deconditioning in
painful spinal disorders. In T. G. Mayer, V. Mooney & R. J. Gatchel (Eds.),
Contemporary conservative care for painful spinal disorders (pp. 278-289).
Pennyslvania: Lea & Febiger.
Gatchel, R. J. (1991b). Psychosocial assessment and disability in the rehabilitation
of painful spinal disorders. In T. G. Mayer, V. Mooney & R. J. Gatchel
(Eds.), Contemporary conservative care for painful spinal disorders (pp.
441-454). Pennsylvania: Lea & Febiger.
Gatchel, R. J. (1996). Psychological disorders and chronic pain. Cause-and-effect
relationships. In R. J. Gatchel & D. C. Turk (Eds.), Psychological
approaches to pain management: A practitioner's handbook (pp. 33-52).
New York: The Guilford Press.
Gatchel, R. J. (2004). Comorbidity of chronic pain and mental health disorders: The
biopsychosocial perspective. American Psychologist, 59(8), 795-805.
References 282
Gatchel, R. J. (2005). Premorbid and comorbid personality traits associated with
chronic pain disability. Paper presented at the 11th World Congress on Pain,
21-26 August, Sydney, Australia.
Gatchel, R. J., & Dersh, J. (2002). Psychological disorders and chronic pain: Are
there cause-and-effect relationships? In D. C. Turk & R. J. Gatchel (Eds.),
Psychological approaches to pain management: A practitioner's handbook
(2nd ed., pp. 30-51). New York: The Guilford Press.
Gatchel, R. J., & Kishino, N. (2006). Influence of personality characteristics of pain
patients: Implications for causality in pain. In G. Young, K. Nicholson & A.
W. Kane (Eds.), Psychological knowledge in court: PTSD, pain and TBI (pp.
149-162). New York: Springer Science.
Gatchel, R. J., & Oordt, M. S. (2003). Clinical health psychology and primary care:
Practical advice and clinical guidance for successful collaboration.
Washington D.C.: American Psychological Association.
Gatchel, R. J., Polatin, P. B., & Kinney, R., K. (1995). Predicting outcome of
chronic back pain using clinical predictors of psychopathology: A
prospective analysis. Health Psychology, 14(5), 415-420.
Gatchel, R. J., Polatin, P. B., & Mayer, T. G. (1995). The dominant role of
psychosocial risk factors in the development of chronic low back pain
disability. Spine, 20(24), 2702-2709.
Gatchel, R. J., Polatin, P. B., Noe, C., Gardea, M., Pulliam, C., & Thompson, J.
(2003). Treatment- and cost-effectiveness of early intervention for acute lowback pain patients: A one-year prospective study. Journal of Occupational
Rehabilitation, 13(1), 1-9.
References 283
Gatchel, R. J., & Turk, D. C. (1996). Psychological approaches to pain
management: A practitioner's handbook. New York: The Guilford Press.
Geisser, M. E., Roth, R. S., & Robinson, M. E. (1997). Assessing depression among
persons with chronic pain using the Center for Epidemiological StudiesDepression scale and the Beck Depression Inventory: A comparative
analysis. Clinical Journal of Pain, 13, 163-170.
Gibson, L., & Strong, J. (1996). The reliability and validity of a measure of
perceived functional capacity for work in chronic back pain. Journal of
Occupational Rehabilitation, 6(3), 159-175.
Grabois, M. (2002). Conceptual model of pain and its management. In T. N. Monga
& M. Grabois (Eds.), Pain management in rehabilitation (pp. 1-21). New
York: Demos Medical Publishing.
Greene, C. S., & Laskin, D. M. (1974). Long-term evaluation of conservative
treatment for myofascial pain-dysfunction syndrome. Journal of American
Dental Association, 89, 1365-1368.
Grotle, M., Vollestad, N. K., Veierod, M. B., & Brox, J. I. (2004). Fear-avoidance
beliefs and distress in relation to disability in acute and chronic low back
pain. Pain, 112(3), 343-352.
Guzman, J., Esmail, R., Karjalainen, K., Malmivaara, A., Irvin, E., & Bombardier,
C. (2002). Multidisciplinary bio-psycho-social rehabilitation for chronic lowback pain (review). The Cochrane Database of Systematic Reviews 2002, 1.
Hadjistavropoulos, H. D., MacLeod, F. K., & Asmundson, G. J. G. (1999).
Validation of the Chronic Pain Coping Inventory. Pain, 80(3), 471-481.
References 284
Hagen, E. M., Eriksen, H. R., & Ursin, H. (2000). Does early intervention with a
light mobilization program reduce long-term sick leave for low back pain?
Spine, 25(15), 1973-1976.
Hagen, E. M., Grasdal, A., & Eriksen, H. R. (2003). Does early intervention with a
light mobilization program reduce long-term sick leave for low back pain: A
3-year follow-up study. Spine, 28(20), 2309-2315.
Harris, S., Morley, S., & Barton, S. B. (2003). Role loss and emotional adjustment in
chronic pain. Pain, 105(1-2), 363-370.
Hart, L. G., Deyo, R. A., & Cherkin, D. C. (1995). Physician office visits for low
back pain: Frequency, clinical evaluation, and treatment patterns from a U.S.
national survey. Spine, 20(1), 11-19.
Heinberg, L. J., Fisher, B. J., Wesselmann, U., Reed, J., & Haythornthwaite, J. A.
(2004). Psychological factors in pelvic/urogenital pain: The influence of site
of pain versus sex. Pain, 108(1-2), 88-94.
Hlobil, H., Uegaki, K., Staal, J. B., de Bruyne, M. C., Smid, T., & van Mechelen, W.
(2007). Substantial sick-leave costs savings due to a graded activity
intervention for workers with non-specific sub-acute low back pain.
European Spine Journal, 16(7), 919-924.
Hoffman, P. K., Meier, B. P., & Council, J. R. (2002). A comparison of chronic pain
between an urban and rural population. Journal of Community Health
Nursing, 19(4), 213-224.
International Association for the Study of Pain. (1986). Classification of chronic
pain. Definitions of chronic pain syndromes and definition of pain terms.
Pain, 24(Supplement).
References 285
Indahl, A., Haldorsen, E. H., Holm, S., Reikerås, O., & Ursin, H. (1998). Five-year
follow-up study of a controlled clinical trial using light mobilization and an
informative approach to low back pain. Spine, 23(23), 2625-2630.
Indahl, A., Velund, L., & Reikeras, O. (1995). Good prognosis for low back pain
when left untampered: A randomized clinical trial. Spine, 20(4), 473-477.
Janz, N. K., & Becker, M. H. (1984). The Health Belief Model: A decade later.
Health Education Quarterly, 11, 1-47.
Jay, S. M., Elliot, C., & Varni, J. W. (1986). Acute and chronic pain in adults and
children with cancer. Journal of Consulting and Clinical Psychology, 54,
601-607.
Jensen, M. P., & Karoly, P. (1991). Control beliefs, coping efforts, and adjustment to
chronic pain. Journal of Consulting and Clinical Psychology, 59(3), 431438.
Jensen, M. P., & Karoly, P. (1992). Pain-specific beliefs, perceived symptom
severity, and adjustment to chronic pain. Clinical Journal of Pain, 8, 123130.
Jensen, M. P., Karoly, P., & Huger, R. (1987). The development and preliminary
validation of an instrument to assess patients' attitudes toward pain. Journal
of Psychosomatic Research, 31(3), 393-400.
Jensen, M. P., Keefe, F. J., Lefebvre, J. C., Romano, J. M., & Turner, J. A. (2003).
One- and two-item measures of pain beliefs and coping strategies. Pain,
104(3), 453-469.
Jensen, M. P., Turner, J. A., & Romano, J. M. (2001). Changes in beliefs,
catastrophizing, and coping are associated with improvement in
References 286
multidisciplinary pain treatment. Journal of Consulting and Clinical
Psychology, 69(4), 655-662.
Jensen, M. P., Turner, J. A., Romano, J. M., & Karoly, P. (1991). Coping with
chronic pain: A critical review of the literature. Pain, 47(3), 249-283.
Jensen, M. P., Turner, J. A., Romano, J. M., & Lawler, B. K. (1994). Relationship of
pain-specific beliefs to chronic pain adjustment. Pain, 57(3), 301-309.
Jensen, M. P., Turner, J. A., Romano, J. M., & Strom, S. E. (1995). The Chronic
Pain Coping Inventory: Development and preliminary validation. Pain,
60(2), 203-216.
Johansson, E. E., Hamberg, K., Westman, G., & Lindgren, G. (1999). The meanings
of pain: An exploration of women's descriptions of symptoms. Social Science
& Medicine, 48, 1791-1802.
Kamper, S. J., Rebbeck, T. J., Maher, C. G., McAuley, J. H., & Sterling, M. (2008).
Course and prognostic factors of whiplash: A systematic review and metaanalysis. Pain, 138(3), 617-629.
Karjalainen, K., Malmivaara, A., van Tulder, M., Roine, R., Jauhiainen, M., Hurri,
H., & Koes, B. (2001a). Multidisciplinary biopsychsocial rehabilitation for
neck and shoulder pain among working age adults (review). The Cochrane
Database of Systematic Reviews 2001, 3.
Karjalainen, K., Malmivaara, A., van Tulder, M., Roine, R., Jauhiainen, M., Hurri,
H., & Koes, B. (2001b). Multidisciplinary biopsychsocial rehabilitation for
subacute low-back pain among working age adults (review). The Cochrane
Database of Systematic Reviews 2001, 3.
References 287
Karoly, P., & Ruehlman, L. S. (2006). Psychological "resilience" and its correlates
in chronic pain: Findings from a national community sample. Pain, 123(1-2),
90-97.
Keefe, F. J., Rumble, M. E., Scipio, C. D., Giordano, L. A., & Perri, L. M. (2004).
Psychological aspects of persistent pain: Current state of the science. The
Keeley, P., Creed, F., Tomenson, B., Todd, C., Borglin, G., & Dickens, C. (2008).
Psychosocial predictors of health-related quality of life and health service
utilisation in people with chronic low back pain. Pain, 135(1-2), 142-150.
Klenerman, L., Slade, P. D., Stanley, M., Pennie, B., Reilly, J. P., Atchison, L. E.,
Troup, J. D. G., & Rose, M. J. (1995). The prediction of chronicity in
patients with an acute attack of low back pain in a general practice setting.
Spine, 20(4), 478-484.
Koleck, M., Mazaux, J.-M., Rascle, N., & Bruchon-Schweitzer, M. (2006). Psychosocial factors and coping strategies as predictors of chronic evolution and
quality of life in patients with low back pain: A prospective study. European
Krause, N., & Ragland, D. R. (1994). Occupational disability due to low back pain:
A new interdisciplinary classification based on a phase model of disability.
Spine, 19(9), 1011-1020.
Lepore, S., & Revenson, T. A. (2006). Relationships between posttraumatic growth
and resilience: Recovery, resistance, and reconfiguration. In L. G. Calhoun &
R. Tedeschi, G. (Eds.), Handbook of posttraumatic growth. Research and
practice. (pp. 24-46). New Jersey: Lawrence Erlbaum Associates, Inc.
References 288
Lethem, J., Slade, P. D., Troup, J. D. G., & Bentley, G. (1983). Outline of a fearavoidance model of exaggerated pain perception--I. Behaviour Research and
Therapy, 21(4), 401-408.
Lindstrom, I., Ohlund, C., Eek, C., Wallin, L., Peterson, L.-E., Fordyce, W. E.,
Nachemson, A. L., & Nelson, R. M. (1992). The effect of graded activity on
patients with subacute low back pain: A randomized prospective clinical
study with an operant-conditioning behavioral approach. Physical Therapy,
72(4), 279-293.
Linton, S. J. (2000). A review of psychological risk factors in back and neck pain.
Spine, 25(9), 1148-1156.
Linton, S. J. (2005). Do psychological factors increase the risk for back pain in the
general population in both a cross-sectional and prospective analysis?
Linton, S. J., Bradley, L. A., Jensen, I., Spangfort, E., & Sundell, L. (1989). The
secondary prevention of low back pain: A controlled study with follow-up.
Pain, 36(2), 197-207.
Linton, S. J., & Hallden, K. (1997). Risk factors and the natural course of acute and
recurrent musculoskeletal pain: Developing a screening instrument. In T. S.
Jensen, J. A. Turner & Z. Wiesenfeld-Hallin (Eds.), Proceedings of the 8th
World Congress on Pain (Vol. 8, pp. 527-536). Seattle: IASP Press.
Loeser, J. D., & Treede, R.-D. (2008). The Kyoto protocol of IASP basic pain
terminology. Pain, 137(3), 473-477.
Loisel, P., Abenhaim, L., Durand, P., Esdaile, J. M., Suissa, S., Gosselin, L., Simard,
R., Turcotte, J., & Lemaire, J. (1997). A population-based, randomized
clinical trial on back pain management. Spine, 22(24), 2911-2918.
References 289
Loisel, P., Lemaire, J., Poitras, S., Durand, M., Champagne, F., Stock, S., Diallo, B.,
& Tremblay, C. (2002). Cost-benefit and cost-effectiveness analysis of a
disability prevention model for back pain management: A six-year follow up
study. Journal of Occupational and Environmental Medicine, 59(12), 807815.
Lopez-Martinez, A. E., Esteve-Zarazaga, R., & Ramirez-Maestre, C. (2008).
Perceived social support and coping responses are independent variables
explaining pain adjustment among chronic pain patients. The Journal of
Pain, 9(4), 373-379.
Macfarlane, G. J., Thomas, E., Papageorgiou, A. C., Schollum, J., Croft, P. R., &
Silman, A. J. (1996). The natural history of chronic pain in the community:
A better prognosis than in the clinic? Journal of Rheumatology, 23, 16171620.
Maetzel, A., & Li, L. (2002). The economic burden of low back pain: A review of
studies published between 1996 and 2001. Best Practice and Research
Clinical Rheumatology, 16(1), 23-30.
Magni, G., Moreschi, C., Rigatti-Luchini, S., & Merskey, H. (1994). Prospective
study on the relationship between depressive symptoms and chronic
musculoskeletal pain. Pain, 56(3), 289-297.
Main, C. J., & Waddell, G. (1991). A comparison of cognitive measures in low back
pain: Statistical structure and clinical validity at initial assessment. Pain,
46(3), 287-298.
Mayer, T. G., & Gatchel, R. J. (1988). Functional restoration of spinal disorders:
The sports medicine approach. Philadelphia: Lea & Febiger.
References 290
McCahon, S., Strong, J., Sharry, R., & Cramond, T. (2005). Self-report and pain
behavior among patients with chronic pain. Clinical Journal of Pain, 21(3),
223-231.
McClean, W. J., & Higginbotham, N. H. (2002). Prevalence of pain among nursing
home residents in rural New South Wales. The Medical Journal of Australia,
177(1), 17-20.
McCracken, L. M. (1998). Learning to live with the pain: Acceptance of pain
predicts adjustment in persons with chronic pain. Pain, 74(1), 21-27.
McCracken, L. M., & Dhingra, L. (2002). A short version of the Pain Anxiety
Symptoms Scale (PASS-20): Preliminary development and validity. Pain
Research Management, 7, 45-50.
McCracken, L. M., & Eccleston, C. (2003). Coping or acceptance: What to do about
chronic pain? Pain, 105(1-2), 197-204.
McCracken, L. M., & Eccleston, C. (2005). A prospective study of the acceptance of
pain and patient functioning with chronic pain. Pain, 118, 164-169.
McCracken, L. M., & Eccleston, C. (2006). A comparison of the relative utility of
coping and acceptance-based measures in a sample of chronic pain sufferers.
McCracken, L. M., Eccleston, C., & Bell, L. (2005). Clinical assessment of
behavioral coping responses: Preliminary results from a brief inventory.
McCracken, L. M., Gross, R. T., Aikens, J., & Carnrike, C. L. M. (1996). The
assessment of anxiety and fear in persons with chronic pain: A comparison of
instruments. Behaviour Research and Therapy, 34(11-12), 927-933.
References 291
McCracken, L. M., Vowles, K. E., & Eccleston, C. (2004). Acceptance of chronic
pain: Component analysis and a revised assessment method. Pain, 107(1-2),
159-166.
McCracken, L. M., Zayfert, C., & Gross, R. T. (1992). The Pain Anxiety Symptoms
Scale: Development and validation of a scale to measure fear of pain. Pain,
50, 67-73.
Meredith, P., Ownsworth, T., & Strong, J. (2008). A review of the evidence linking
adult attachment theory and chronic pain: Presenting a conceptual model.
Clinical Psychology Review, 28, 407-429.
Merskey, H., & Bogduk, N. (1994). Classification of chronic pain. In H. Merskey &
B. N (Eds.), Part III: Pain terms, a current list with definitions and notes on
usage. IASP task force on taxonomy (2nd ed., pp. 209-214). Seattle: IASP
Press.
Morgan, D. L. (1998a). Planning focus groups (Vol. 2). Thousand Oaks, CA: SAGE
Publications, Inc.
Morgan, D. L. (1998b). Practical strategies for combining qualitative and
quantitative methods: Applications to health research. Qualitative Health
Research, 8(3), 362-376.
Morley, S., Davies, C., & Barton, S. (2005). Possible selves in chronic pain: Selfpain enmeshment, adjustment and acceptance. Pain, 115(1-2), 84-94.
Nagi, S. Z. (1976). An epidemiology of disability among adults in the United States.
MMFQ Health and Society, 54, 439-467.
Ng, K. F. J., Tsui, S. L., & Chan, W. S. (2002). Prevalence of common chronic pain
in Hong Kong adults. Clinical Journal of Pain, 18, 275-281.
References 292
National Health and Medical Research Council. (2003). Strategic Plan for 20032006. Retrieved 06 May 2008. from
http://www.nhmrc.gov.au/publications/synopses/nh46syn.htm.
Nicholas, M. K. (2007). The pain self-efficacy questionnaire: Taking pain into
account. European Journal of Pain, 11, 153-163.
Nicholas, M. K., & Asghari, A. (2006). Investigating acceptance in adjustment to
chronic pain: Is acceptance broader than we thought? Pain, 124(3), 269-279.
Nicholas, M. K., Asghari, A., & Blyth, F. M. (2008). What do the numbers mean?
Normative data in chronic pain measures. Pain, 134(1-2), 158-173.
Nicholas, M. K., Wilson, P. H., & Goyen, J. (1992). Comparison of cognitivebehavioral group treatment and an alternative non-psychological treatment
for chronic low back pain. Pain, 48(3), 339-347.
Novy, D. M., Nelson, D. V., Hetzel, R. D., Squitieri, P., & Kennington, M. (1998).
Coping with chronic pain: Sources of intrinsic and contextual variability.
Journal of Behavioral Medicine, 21(1), 19-34.
O'Connor, B. P. (2000). SPSS and SAS programs for determining the number of
components using parallel analysis and Velicer's MAP test. . Behavior
Research Methods, Instrumentation, and Computers, 32, 396-402.
Onwuegbuzie, A. J., & Johnson, R. B. (2006). The validity issue in mixed research.
Research in the Schools, 13(1), 48-63.
Osborne, T. L., Jensen, M. P., Ehde, D. M., Hanley, M. A., & Kraft, G. (2007).
Psychosocial factors associated with pain intensity, pain-related interference,
and psychological functioning in persons with multiple sclerosis and pain.
Pain, 127(1-2), 52-62.
References 293
Osterweis, M., Kleinman, A., & Mechanic, D. (1987). Pain and disability: Clinical,
behavioral and public policy perspectives. Washington, D.C.: National
Academy Press.
Paulsen, J. S., & Altmaier, E. M. (1995). The effects of perceived versus enacted
social support on the discriminative cue function of spouses for pain
behaviors. Pain, 60(1), 103-110.
Peterson, C. (2000). The future of optimism. American Psychologist, 55(1), 44-55.
Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A
handbook and classification. New York: Oxford University Press.
Picavet, H. S. J., Vlaeyen, J. W. S., & Schouten, J. S. A. G. (2002). Pain
catastrophizing and kinesiophobia: Predictors of chronic low back pain.
American Journal of Epidemiology, 156(11), 1028-1034.
Pincus, T., Burton, A. K., Vogel, S. D., & Field, A. P. (2002). A systematic review
of psychological factors as predictors of chronicity/ disability in prospective
cohorts of low back pain. Spine, 27(5), E109-E120.
Pincus, T., Vlaeyen, J. W. S., Kendall, N. A. S., Von Korff, M. R., Kalauokalani, D.
A., & Reis, S. (2002). Cognitive-Behavioral Therapy and psychosocial
factors in low back pain: Directions for the future. Spine, 27(5), E133-E138.
Pincus, T., Vogel, S., Burton, A. K., Santos, R., & Field, A. P. (2006). Fear
avoidance and prognosis in back pain: A systematic review and synthesis of
current evidence. Arthritis & Rheumatism, 54(12), 3999-4010.
Poiraudeau, S., Rannou, F., Baron, G., Henanff, A. L., Coudeyre, E., Rozenberg, S.,
Huas, D., Martineau, C., Jolivet-Landreau, I., & Garcia-Mace, J. (2006).
Fear-avoidance beliefs about back pain in patients with subacute low back
pain. Pain, 124(3), 305-311.
References 294
Pressman, S. D., & Cohen, S. (2005). Does positive affect influence health?
Psychological Bulletin, 131(6), 925-971.
Price, D. D., Riley, J. L. I., & Wade, J. B. (2001). Psychophysical approaches to
measurement of the dimensions and stages of pain. In D. C. Turk & R.
Melzack (Eds.), Handbook of Pain Assessment (2nd ed., pp. 35-52). New
York: The Guilford Press.
Public Health Division. (2000). Report on the 1997 and 1998 NSW Health Surveys.
Sydney: NSW Health Department.
Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research
in the general population. Applied Psychological Measurement, 1(3), 385401.
Reid, S., Haugh, L. D., Hazard, R. G., & Tripathi, M. (1997). Occupational low back
pain: Recovery curves and factors associated with disability. Journal of
Revenson, T. A., & Felton, B. J. (1989). Disability and coping as predictors of
psychological adjustment to Rheumatoid Arthritis. Journal of Consulting and
Clinical Psychology, 57(3), 344-348.
Richardson, I. H., & Richardson, P. H. (1999). Does cognitive change predict the
outcome of cognitive-behavioural pain management? Psychology, Health &
Medicine, 4(1), 27-44.
Richardson, J. C., Ong, B. N., & Sim, J. (2006). Is chronic widesprerad pain
biographically disruptive? Social Science & Medicine, 63, 1573-1585.
Roland, M., & Morris, R. (1983a). A study of the natural history of back pain. Part I:
Development of a reliable and sensitive measure of disability in low-back
pain. Spine, 8(2), 141-144.
References 295
Roland, M., & Morris, R. (1983b). A study of the natural history of low-back pain.
Part II: Development of guidelines for trials of treatment in primary care.
Spine, 8(2), 145-150.
Romano, J. M., Jensen, M. P., & Turner, J. A. (2003). The chronic pain coping
inventory-42: Reliability and validity. Pain, 104, 65-73.
Rosenstiel, A. K., & Keefe, F. J. (1983). The use of coping strategies in chronic low
back pain patients: Relationship to patient characteristics and current
adjustment. Pain, 17(1), 33-44.
Rosenstock, I. M. (1974). Historical origins of the Health Belief Model. Health
Education Monographs, 2(4), 328-335.
Rustøen, T., Wahl, A. K., Hanestad, B. R., Lerdal, A., Paul, S., & Miaskowski, C.
(2004). Prevalence and characteristics of chronic pain in the general
Norwegian population. European Journal of Pain, 8(6), 555-565.
Rutter, M. (1999). Resilience concepts and findings: Implications for family therapy.
Journal of Family Therapy, 21, 119-144.
Salovey, P., Detweiler, J. B., Steward, W. T., & Rothman, A. J. (2000). Emotional
states and physical health. American Psychologist, 55(1), 110-121.
Sandelowski, M., Voils, C. I., & Barroso, J. (2006). Defining and designing mixed
research synthesis studies. Research in the Schools, 13(1), 29-40.
Santor, D. A., Zuroff, D. C., Ramsay, J. O., & Cervantes, P. (1995). Examining scale
discriminability in the BDI and CES-D as a function of depressive severity.
Psychological Assessment, 7(2), 131-139.
Scheier, M. F., & Carver, C. S. (1992). Effects of optimism on psychological and
physical well-being: Theoretical overview and empirical update. Cognitive
Therapy and Research, 16(2), 201-228.
References 296
Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguishing optimism
from neuroticism (and trait anxiety, self-mastery, and self-esteem): A
reevaluation of the Life Orientation Test. Journal of Personality and Social
Psychology, 67(6), 1063-1078.
Schultz, I. Z., Crook, J., Berkowitz, J., Milner, R., Meloche, G., & Lewis, M. (2008).
A prospective study of the effectiveness of early intervention with high-risk
back-injured workers - A pilot study. Journal of Occupational
Schultz, I. Z., Crook, J., Meloche, G. R., Berkowitz, J., Milner, R., Zuberbier, O. A.,
& Meloche, W. (2004). Psychosocial factors predictive of occupational low
back disability: Towards development of a return-to-work model. Pain, 107,
77-85.
Seeman, M., & Seeman, T. E. (1983). Health behavior and personal autonomy: A
longitudinal study of the sense of control in illness. Journal of Health and
Social Behavior, 24, 144-160.
Sharma, L., Cahue, S., Song, J., Hayes, K., Pai, Y.-C., & Dunlop, D. (2003).
Physical functioning over three years in knee osteoarthritis: Role of
psychosocial, local mechanical, and neuromuscular factors. Arthritis and
Rheumatism, 48(12), 3359-3370.
Sieben, J. M., Vlaeyen, J. W. S., Portegijs, P. J. M., Verbunt, J. A., van Riet-Rutgers,
S., Kester, A. D. M., Von Korff, M., Arntz, A., & Knottnerus, J. A. (2005). A
longitudinal study on the predictive validity of the fear-avoidance model in
low back pain. Pain, 117(1-2), 162-170.
References 297
Söderberg, S., Lundman, B., & Norberg, A. (1997). Living with fibromyalgia: Sense
of coherence, perception of well-being, and stress in daily life. Research in
Nursing and Health, 20, 495-503.
Steenstra, I., Anema, J., van Tulder, M., Bongers, P., de Vet, H., & van Mechelen,
W. (2006). Economic evaluation of a multi-stage return to work program for
workers on sick-leave due to low back pain. Journal of Occupational
Strand, E. B., Kerns, R. D., Christie, A., Haavik-Nilsen, K., Klokkerud, M., &
Finset, A. (2007). Higher levels of pain readiness to change and more
positive affect reduce pain reports - A weekly assessment study on arthritis
patients. Pain, 127(3), 204-213.
Strand, E. B., Zautra, A. J., Thoresen, M., Ødegård, S., Uhlig, T., & Finset, A.
(2006). Positive affect as a factor of resilience in the pain-negative affect
relationship in patients with rheumatoid arthritis. Journal of Psychosomatic
Research, 60(5), 477-484.
Strong, J., Ashton, R., & Chant, D. (1992). The measurement of attitudes towards
and beliefs about pain. Pain, 48(2), 227-236.
Strong, J., Ashton, R., Cramond, T., & Chant, D. (1990). Pain intensity, attitude and
function in back pain patients. The Australian Occupational Therapy
Journal, 37(4), 179-183.
Strong, J., Westbury, K., Smith, G., McKenzie, I., & Ryan, W. (2002). Treatment
outcome in individuals with chronic pain: Is the Pain Stages of Change
Questionnaire (PSOCQ) a useful tool? Pain, 97(1-2), 65-73.
References 298
Sullivan, M. D. (2001). Assessment of psychiatric disorders. In D. C. Turk & R.
Melzack (Eds.), Handbook of pain assessment (2nd ed., pp. 275-291). New
York: The Guilford Press.
Sutherland, R., & Morley, S. (2008). Self-pain enmeshment: Future possible selves,
sociotropy, autonomy and adjustment to chronic pain. Pain, 137(2), 366-377.
Swartzman, L. C., Gwadry, F. G., Shapiro, A. P., & Teasell, R. W. (1994). The
factor structure of the Coping Strategies Questionnaire. Pain, 57(3), 311-316.
Tan, G., Nguyen, Q., Cardin, S. A., & Jensen, M. P. (2006). Validating the use of
two-item measures of pain beliefs and coping strategies for a veteran
population. The Journal of Pain, 7(4), 252-260.
Tompa, E., de Oliveira, C., Dolinschi, R., & Irvin, E. (2008). A systematic review of
disability management interventions with economic evaluations. Journal of
Tripp, D. A., VanDenKerkhof, E. G., & McAlister, M. (2006). Prevalence and
determinants of pain and pain-related disability in urban and rural settings in
southeastern Ontario. Pain Research & Management: The Journal Of The
Canadian Pain Society, 11(4), 225-233.
Turk, D. C., & Okifuji, A. (1996). Perception of traumatic onset, compensation
status, and physical findings: Impact on pain severity, emotional distress, and
disability in chronic pain patients. Journal of Behavioral Medicine, 19(5),
435-453.
Turk, D. C., & Okifuji, A. (2002). Psychological factors in chronic pain: Evolution
and revolution. Journal of Consulting and Clinical Psychology, 70(3), 678690.
References 299
Turk, D. C., & Rudy, T. E. (1988). Toward an empirically derived taxonomy of
chronic pain patients: Integration of psychological assessment data. Journal
of Consulting and Clinical Psychology, 56(2), 233-238.
Turk, D. C., Sist, T. C., Okifuji, A., Miner, M. F., Florio, G., Harrison, P., Massey,
J., Lema, M. L., & Zevon, M. A. (1998). Adaptation to metastatic cancer
pain, regional/local cancer pain and non-cancer pain: Role of psychological
and behavioral factors. Pain, 74(2-3), 247-256.
Turner, J. A., Franklin, G., & Turk, D. C. (2000). Predictors of chronic disability in
injured workers: A systematic literature synthesis. American Journal of
Industrial Medicine, 38, 707-722.
Turner, J. A., Jensen, M. P., Warms, C. A., & Cardenas, D. D. (2002).
Catastrophizing is associated with pain intensity, psychological distress, and
pain-related disability among individuals with chronic pain after spinal cord
injury. Pain, 98(1-2), 127-134.
Underwood, M. R., Barnett, A. G., & Vickers, M. R. (1999). Evaluation of two timespecific back outcome measures. Spine, 24(11), 1104-1112.
van Ijzendoorn, M. (1995). Adult attachment representations, parental
responsiveness, and infant attachment: A meta-analysis on the predictive
validity of the Adult Attachment Interview. Psychological Bulletin, 117(3),
387-403.
Verhaak, P. F. M., Kerssens, J. J., Dekker, J., Sorbi, M. J., & Bensing, J. M. (1998).
Prevalence of chronic benign pain disorder among adults: A review of the
literature. Pain, 77(3), 231-239.
References 300
Vlaeyen, J. W. S., Kole-Snijders, A. M. J., Boeren, R. G. B., & van Eek, H. (1995).
Fear of movement/(re)injury in chronic low back pain and its relation to
behavioral performance. Pain, 62(3), 363-372.
Von Korff, M. (2001). Epidemiological and survey methods: Assessment of chronic
pain. In D. C. Turk & R. Melzack (Eds.), Handbook of pain assessment (pp.
603-618). New York: The Guilford Press.
Von Korff, M., Dworkin, S. F., & Le Resche, L. (1990). Graded chronic pain status:
An epidemiologic evaluation. Pain, 40(3), 279-291.
Von Korff, M., Ormel, J., Keefe, F. J., & Dworkin, S. F. (1992). Grading the
severity of chronic pain. Pain, 50(2), 133-149.
Waddell, G., Newton, M., Henderson, I., Somerville, D., & Main, C. J. (1993). A
Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fearavoidance beliefs in chronic low back pain and disability. Pain, 52(2), 157168.
Walker, B. F., Muller, R., & Grant, W. D. (2004). Low back pain in Australian
adults. Prevalence and associated disability. Journal of Manipulative and
Physiological Therapeutics, 27(4), 238-244.
Walker, J., Holloway, I., & Sofaer, B. (1999). In the system: The lived experience of
chronic back pain from the perspectives of those seeking help from pain
clinics. Pain, 80(3), 621-628.
Werner, A., Isaksen, L. W., & Malterud, K. (2004). 'I am not the kind of women
who complains of everything': Illness stories on self and shame in women
with chronic pain. Social Science & Medicine, 59, 1035-1045.
White, C. L., LeFort, S. M., Amsel, R., & Jeans, M.-E. (1997). Predictors of the
development of chronic pain. Research in Nursing and Health, 20, 309-318.
References 301
Wimberly, S. R., Carver, C. S., & Antoni, M. H. (2008). Effects of optimism,
interpersonal relationships, and distress on psychosexual well-being among
women with early stage breast cancer. Psychology & Health, 23(1), 57-72.
Woods, M. P., & Asmundson, G. J. G. (2008). Evaluating the efficacy of graded in
vivo exposure for the treatment of fear in patients with chronic back pain: A
randomized controlled clinical trial. Pain, 136(3), 271-280.
Yin, R. K. (2006). Mixed methods research: Are the methods genuinely integrated or
merely parallel? Research in the Schools, 13(1), 41-47.
Zautra, A. J., Johnson, L. M., & Davis, M. C. (2005). Positive affect as a source of
resilience for women in chronic pain. Journal of Consulting and Clinical
Psychology, 73(2), 212-220.
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The
Multidimensional Scale of Perceived Social Support. Journal of Personality
Assessment, 52(1), 30-41.
Appendices 303
APPENDICES
Appendix A: Comparison between Brisbane and rural respondents available for the
Phase 3 (interview) study
Table A1
Demographic Variables for Participants willing to be contacted for Interview by Location
Variable
Female (%)
Urban
respondents
(N = 127)
57.5
Rural
respondents
(N = 36)
77.8
χ² (1, n = 163) = 4.90, p = .027*
65.1
80.6
χ² (1, n = 162) = 3.11, p = .078
Partnered (%)
Highest level of education (%)
χ² (4, n = 159) = 12.96, p = .011*
Primary school
8.1
2.8
Year 10
23.6
52.8
Year 12
6.5
8.3
TAFE or equivalent
35.0
25.0
University
26.8
11.1
56.73 (13.18)
52.11 (13.26)
t (159) = 1.85, p = .066
# adults in the household:
2.02 (.82)
2.19 (.82)
t (157) = -1.09, p = .278
Mean (SD)
Table A2
Pain Variables for Participants willing to be contacted for Interview by Location
Variable
Urban respondents
(N = 127)
Rural respondents
(N = 36)
Mean
SD
Mean
SD
Depression (CES-D)
15.31
11.63
17.26
11.55
t (161) = -0.89, p = .374
Anxiety (PASS)
28.90
20.00
31.92
21.90
t (159) = -0.78, p = .436
7.60
5.92
7.64
5.54
t (161) = -0.37, p = .971
Global disability (GCPS)
36.75
27.72
37.31
25.16
t (157) = -.11, p = .912
Pain intensity (GCPS)
51.35
21.20
51.20
16.76
t (160) = 0.04, p = .970
Appendices 304
Appendix B: Baseline (Phase 1) Questionnaire
Appendices 315
Appendix C: Comparison between pain respondents who provided pain duration
and respondents who did not provide pain duration at baseline
Table C1
Demographic Variables for Baseline Pain Participants by Whether Pain Duration data was
provided
Female (%)
62.5
Respondents
who did not
provide pain
duration
(N = 28)
44.4
Partnered (%)
73.0
74.1
Variable
Respondents
who provided
pain duration
(N = 450)
Highest level of education (%)
χ² (1, n = 446) = 3.50, p = .061
χ² (1, n = 445) = 0.02, p = .900
χ² (4, n = 440) = 9.22, p = .056
Primary school
7.8
10.7
Year 10
28.4
17.9
Year 12
11.4
28.6
TAFE or equivalent
26.9
14.3
University
25.5
28.6
51.92 (15.25)
54.46 (17.49)
t (442) = 0.84, p = .397
2.18 (.86)
2.44 (1.05)
t (435) = 1.55, p = .121
# adults in the household:
Mean (SD)
Appendices 316
Appendix D: Participant Information Sheet
Appendices 319
Appendix E: Examining Gatchel’s Model with Low Back Pain Respondents
Table E1
Correlations between Pain Duration and Measures of Gatchel’s Variables at Baseline
(shaded) and Follow-Up (unshaded) for Low Back Pain Respondents (N = 47)^
Daily
Pain
Overall
interfer.
intensity
disability
-.039
-.094
-.132
-.094
1
.623**
.457**
.499**
.607**
-.077
.721**
1
.757**
.617**
.760**
Daily interference
-.158
.512**
.667**
1
.554**
.740**
Pain Intensity
.018
.590**
.416**
.470**
1
.599**
Global disability
-.152
.623**
.760**
.780**
.593**
1
Duration
Depression
Anxiety
1
.145
Depression
.034
Anxiety
Duration
Chronic Pain Scales – Intensity estimate, Global disability: GCPS Graded Chronic Pain Scales –
Disability estimate
** p<.01
Table E2
Correlation Matrix for Changes Scores on Psychological and Disability Measures for Low
Back Pain Respondents (N = 47)^
CES-D change
PASS change
RMDQ change
Disability estimate change
CES-D
change
PASS
change
RMDQ
change
Disability est.
change
1
.154
-.123
.195
1
.174
.146
1
.452**
1
Note. CES-D Center for Epidemiologic Studies – Depression, PASS Pain Anxiety Symptoms Scale,
RMDQ Roland Morris Disability Questionnaire, GCPS Graded Chronic Pain Scales & Disability
estimate
* p<.01 ** p<.001
Appendices 320
Table E3
Comparing Gatchel’s Variables between Baseline and Follow-up data collection for Low
Back Pain respondents (N = 47)
Dependent variables
Baseline
3-month Follow-up
t-tests
M
SD
M
SD
Depression (CES-D)
17.84
13.13
16.74
11.35
t (43) = 1.00, p = .325
Pain-related anxiety (PASS)
36.22
22.65
35.28
23.67
t (45) = 0.52, p = .606
8.91
5.96
9.06
6.09
t (46) = -0.26, p = .795
Global disability (GCPS)
40.36
26.79
36.81
26.29
t (45) = 1.34, p = .188
Table E4
Frequencies (%) of GCPS Classification Changes for Low Back Pain Respondents
Classification change
N
%
2 grade decrease (better)
3
6.4
1 grade decrease (better)
12
25.5
No change
16
34.0
1 grade increase (worse)
4
8.5
Note. % does not sum to 100% because 12 respondents did not have change scores calculated. Grade
decreases indicate that respondents had a reduction in the severity of their pain. Grade increases
indicate that respondents’ pain worsened.

Exploring non-cancer pain conditions in a community sample:

Transcription

Similar documents

HealthTrax Brochure

PAIN MANAGEMENT SERVICES

How to include people with chronic disease in community activities guide

The Prevention and Public Health Fund: A Priority for Cancer Health

Changing Your Mind, Changing Your Pain. Presenter

Chronic Pain or Illness: Relationships and Communication

I

December 2015 - Romoland School District

Document 6428074