August 2011 - Physical Therapy Journal

Transcription

August 2011 Volume 91 Number 8
Research Reports
1153
Age-Related Muscle Fatigue: A Meta-Analysis
1235
1166
Effects of Vestibular Rehabilitation on
Multiple Sclerosis–Related Fatigue and
Upright Postural Control
Frontal-Plane Gait Mechanics in Knee
Osteoarthritis
1244
Physical Performance Tests and Hemodialysis
1253
Fear of Falling Avoidance Behavior
Questionnaire
1184
Cervical Flexor Activity and
Temporomandibular Disorders
1198
Physical Performance and Executive Function
in Older Adults With Mild Cognitive
Impairment
1211
Extended ICF Core Set for Stroke From
Physical Therapists’ Perspective
1223
Association of Body Mass Index With
Measures of Balance and Mobility
Case Report
1266
Internal Carotid Artery Dissection
ProfessionWatch
1275
Outcomes of a Conference to Enhance the
Delivery of Care
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4/4/11 11:57 AM
Physical Therapy
Journal of the American Physical Therapy Association
■ Volume 91
■ Number 8
■ August 2011
Editorial
1150
Establishing Real Global Connections / Rebecca L. Craik
Research Reports
Winslow Homer (American, 1836–1910).
Eagle Head, Manchester, Massachusetts (High
Tide). 1870. Gift of Mrs. William F. Milton,
1923. Photo Credit: Image copyright © The
Metropolitan Museum of Art, New York,
NY / Art Resource, NY.
In a painting that some art critics call
“disquieting,” 3 bathers who have just
emerged from the ocean bend forward to
dry off, remove a shoe, shake out sand.
Thoracic spines, elbows, hips, and knees are
all flexed to varying degrees. Although the
girls are in close physical proximity and—
as a composition—are joined together,
they seem isolated. They face in opposite
directions, with their backs to each other,
and 2 of the faces are obscured. Even the
dog seems wary. One of the bathers wrings
out her wool bathing dress before wringing
out her hair.
1153
Age-Related Differences in Muscle Fatigue Vary by
Contraction Type: A Meta-analysis / Keith G. Avin,
Laura A. Frey Law
1166
Effects of Vestibular Rehabilitation on Multiple Sclerosis–
Related Fatigue and Upright Postural Control:
A Randomized Controlled Trial / Jeffrey R. Hebert, John R. Corboy,
Mark M. Manago, Margaret Schenkman
1184
Electromyographic Activity of the Cervical Flexor Muscles
in Patients With Temporomandibular Disorders While
Performing the Craniocervical Flexion Test: A CrossSectional Study / Susan Armijo-Olivo, Rony Silvestre, Jorge Fuentes,
Bruno R. da Costa, Inae C. Gadotti, Sharon Warren, Paul W. Major,
Norman M.R. Thie, David J. Magee
1198
Associations Between Physical Performance and Executive
Function in Older Adults With Mild Cognitive Impairment:
Gait Speed and the Timed “Up & Go” Test / Ellen L. McGough,
Valerie E. Kelly, Rebecca G. Logsdon, Susan M. McCurry, Barbara B. Cochrane,
Joyce M. Engel, Linda Teri
1208
Invited Commentary / Teresa Y. Liu-Ambrose
1210
Author Response / Ellen L. McGough, Valerie E. Kelly,
Rebecca G. Logsdon, Susan M. McCurry, Barbara B. Cochrane,
Joyce M. Engel, Linda Teri
1211
Content Validity of the Extended ICF Core Set for Stroke:
An International Delphi Survey of Physical Therapists /
Andrea Glässel, Inge Kirchberger, Barbara Kollerits, Edda Amann,
Alarcos Cieza
1146 ■ Physical Therapy Volume 91 Number 8
August 2011
1223
1235
Association of Body Mass Index With Self-Report and
Performance-Based Measures of Balance and Mobility /
Departments
Andrea L. Hergenroeder, David M. Wert, Elizabeth S. Hile,
Stephanie A. Studenski, Jennifer S. Brach
1152
The Bottom Line
1285
Scholarships, Fellowships,
and Grants
Frontal-Plane Gait Mechanics in People With Medial Knee
Osteoarthritis Are Different From Those in People With
Lateral Knee Osteoarthritis / Robert J. Butler, Joaquin A. Barrios,
Todd Royer, Irene S. Davis
1244
Test-Retest Reliability and Minimal Detectable Change
Scores for Sit-to-Stand-to-Sit Tests, the Six-Minute Walk
Test, the One-Leg Heel-Rise Test, and Handgrip Strength
in People Undergoing Hemodialysis / Eva Segura-Ortí,
News from the Foundation for
Physical Therapy
1287
Product Highlights
1288
Ad Index
Francisco José Martínez-Olmos
1253
Development of a Scale to Assess Avoidance Behavior
Due to a Fear of Falling: The Fear of Falling Avoidance
Behavior Questionnaire / Merrill R. Landers, Cortney Durand,
D. Shalom Powell, Leland E. Dibble, Daniel L. Young
Case Report
1266
A Patient With Internal Carotid Artery Dissection /
Gilbert M. Willett, Neal A. Wachholtz
ProfessionWatch
1275
Vitalizing Practice Through Research and Research
Through Practice: The Outcomes of a Conference to
Enhance the Delivery of Care / Marc S. Goldstein,
David A. Scalzitti, Joanell A. Bohmert, Gerard P. Brennan,
Rebecca L. Craik, Anthony Delitto, Edelle C. Field-Fote,
Charles Magistro, Christopher M. Powers, Richard K. Shields
Visit ptjournal.apta.org
To read online Invited
Commentaries and Author
Responses.
View videoclips.
Listen to discussion
podcasts.
August 2011
Volume 91 Number 8 Physical Therapy ■ 1147
Physical Therapy
Journal of the American Physical Therapy Association
Editorial Office
Editor in Chief
Managing Editor /
Associate Director of Publications:
Jan P. Reynolds, [email protected]
Rebecca L. Craik, PT, PhD, FAPTA, Philadelphia, PA
[email protected]
PTJ Online Editor /
Assistant Managing Editor:
Steven Glaros
Deputy Editor in Chief
Associate Editor:
Stephen Brooks, ELS
Editor in Chief Emeritus
Production Manager:
Liz Haberkorn
Manuscripts Coordinator:
Karen Darley
Permissions / Reprint Coordinator:
Michele Tillson
Advertising Manager:
Julie Hilgenberg
Art Director:
Barbara Cross
Director of Publications:
Lois Douthitt
APTA Executive Staff
Vice President for Communications:
Felicity Feather Clancy
Chief Financial Officer:
Rob Batarla
Chief Executive Officer:
John D. Barnes
Advertising Sales
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President / Advertising Account Manager:
Jane Dees Richardson
Board of Directors
Daniel L. Riddle, PT, PhD, FAPTA, Richmond, VA
Jules M. Rothstein, PT, PhD, FAPTA (1947–2005)
Steering Committee
Anthony Delitto, PT, PhD, FAPTA (Chair), Pittsburgh, PA; J. Haxby Abbott, PhD,
MScPT, DipGrad, FNZCP, Dunedin, New Zealand; Joanell Bohmert, PT, MS,
Mahtomedi, MN; Alan M. Jette, PT, PhD, FAPTA, Boston, MA; Charles Magistro,
PT, FAPTA, Claremont, CA; Ruth B. Purtilo, PT, PhD, FAPTA, Boston, MA; Julie
Whitman, PT, DSc, OCS, Westminster, CO
Editorial Board
Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia;
W. Todd Cade, PT, PhD, St Louis, MO; James R. Carey, PT, PhD, Minneapolis, MN;
John Childs, PT, PhD, Schertz, TX; Joshua Cleland, PT, DPT, PhD, OCS, FAAOMPT,
Concord, NH; Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; G. Kelley
Fitzgerald, PT, PhD, FAPTA, Pittsburgh, PA; James C. (Cole) Galloway, PT, PhD,
Newark, DE; Steven Z. George, PT, PhD, Gainesville, FL; Kathleen Gill-Body, PT,
DPT, NCS, Boston, MA; Paul J.M. Helders, PT, PhD, PCS, Utrecht, The Netherlands;
Rana Shane Hinman, PT, PhD, Melbourne, Victoria, Australia; Maura D. Iversen, PT,
DPT, ScD, MPH, Boston, MA; Diane U. Jette, PT, DSc, Burlington, VT; Christopher
Maher, PT, PhD, Lidcombe, NSW, Australia; Chris J. Main, PhD, FBPsS, Keele,
United Kingdom; Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA; Sarah
Westcott McCoy, PT, PhD, Seattle, WA; Patricia J. Ohtake, PT, PhD, Buffalo, NY;
Carolynn Patten, PT, PhD, Gainesville, FL; Linda Resnik, PT, PhD, OCS, Providence,
RI; Kathleen Sluka, PT, PhD, Iowa City, IA; Nicholas Stergiou, PhD, Omaha, NE
Statistical Consultants
Steven E. Hanna, PhD, Hamilton, Ont, Canada; John E. Hewett, PhD, Columbia,
MO; Hang Lee, PhD, Boston, MA; Xiangrong Kong, PhD, Baltimore, MD; Michael
E. Robinson, PhD, Gainesville, FL; Paul Stratford, PT, MSc, Hamilton, Ont, Canada;
David Thompson, PT, PhD, Oklahoma City, OK; Samuel Wu, PhD, Gainesville, FL
President: R. Scott Ward, PT, PhD
Committee on Health Policy and Ethics
Vice President: Paul A. Rockar Jr, PT, DPT, MS
Linda Resnik, PT, PhD, OCS (Chair), Providence, RI; Janet Freburger, PT, PhD,
Chapel Hill, NC; Alan M. Jette, PT, PhD, FAPTA, Boston, MA; Michael Johnson, PT,
PhD, OCS, Philadelphia, PA; Justin Moore, PT, DPT, Alexandria, VA; Ruth B. Purtilo,
PT, PhD, FAPTA, Boston, MA
Secretary:
Laurita M. Hack, PT, DPT, MBA, PhD, FAPTA
Treasurer: Elmer Platz, PT
Speaker of the House:
Shawne E. Soper, PT, DPT, MBA
Vice Speaker of the House:
William F. McGehee, PT, MHS
Directors: Sharon L. Dunn, PT, PhD, OCS; Jennifer
E. Green-Wilson, PT, MBA, EdD; Roger A. Herr,
PT, MPA, COS-C; Dianne V. Jewell, PT, DPT, PhD,
CCS, FAACVPR; Aimee B. Klein, PT, DPT, DSc, OCS;
Kathleen K. Mairella, PT, DPT, MA; Dave Pariser, PT,
PhD; Mary C. Sinnott, PT, DPT, MEd; Nicole L. Stout,
PT, MPT, CLT-LANA
Masthead_8.11.indd 1148
<LEAP> Linking Evidence And Practice
Advisory Group
Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia
(Co-Chair); Diane U. Jette, PT, DSc, Burlington, VT (Co-Chair); W. Todd Cade,
PT, PhD, St Louis, MO; Christopher Maher, PT, PhD, Lidcombe, NSW, Australia;
Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA; David Scalzitti, PT,
PhD, OCS, Alexandria, VA
August 2011
7/8/11 1:19 PM
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7/8/11 1:20 PM
Editorial
Establishing Real Global Connections
W
hen I typed “global connections” as a search term in Google, I got 52,900,000
results (July 6, 2011). Even an inquiry in Google Scholar yielded 1,390,000
results.
It’s rare for undergraduate students not to have some sort of international experience,
and many physical therapist professional education programs in the United States send
students for an international service learning experience. But the larger meaning of
global connections for the physical therapy community and our potential impact on
promoting world health became crystal clear at the 16th International World Confederation for Physical Therapy Congress (WCPT) in Amsterdam, the Netherlands, in June.
At last count, about 5,300 clinicians traveled from 115 countries for this event. I was
struck by the fact that speakers emphasized principles for intervention rather than
clinical context (eg, acute care facility, rehabilitation setting). Two of the focused symposia—one related to recovery from stroke, and another on spinal manipulation—
exemplify this. The symposium titled “Increasing Practice After Stroke to Optimize
Rehabilitation” emphasized using the evidence that supports a relationship between
“dose” of task-specific practice and patient outcome. Rather than focusing solely on
the advances in technology that expedite practice, the speakers highlighted the need
to increase practice time and discussed strategies to overcome barriers such as lack of
access to treadmills and robots that facilitate practice. There were discussions about
increasing the number of therapists, training others in the community, and helping
family members increase the dose. The principle of increased intensity was the message, not the tool.
Similarly, the session titled “Spinal Manipulation—Evidence for Physiotherapist Delivery of Effective Procedures” discussed current evidence related to the effectiveness of
techniques for cervicogenic headache and low back pain. Although the speakers all
agreed that there is a need for additional evidence, they focused on the need to teach
effective screening procedures to enhance safe practice in entry-level programs as well
as to enhance the skills of practicing clinicians worldwide.
I also was impressed with the number of investigators who are conducting research
internationally and how comfortable the presenters were with reporting research outcomes using the International Classification of Functioning, Disability and Health
(ICF).1
To comment,
submit a Rapid
Response to this
editorial posted online
at ptjournal.apta.org.
A number of group networking sessions took place based on requests from physical therapists around the world, with topics including animal physical therapy, cardiorespiratory physical therapy, electrophysical agents, and education. These sessions
provided an informal opportunity to meet and talk with colleagues who share a common interest. WCPT (www.wcpt.org) currently has subgroups for acupuncture, older
people, manual therapy, sports physiotherapy, women’s health, pedatrics, and private
practitioners. In addition, WCPT collaborates with various other physical therapy organizations that are not official subgroups. It’s an incredible experience to sit with clinicians, educators, and researchers from around the world and share experiences. Barriers encountered by physical therapists in one country have sometimes been solved by
clinicians in other countries.
editorial_8.11.indd 1150
August 2011
7/18/11 10:58 AM
Editorial
Several discussion panels addressed issues beyond practice, including:
• Managing the research challenges of the 21st century
• Using physical therapy projects to bring long-term sustainable benefits in conflict
zones and disaster areas
• Working as an international profession to change health policy and service provision
• Addressing factors that affect equitable access to physical therapy in all parts of
the world
In closing, I congratulate Stanley Paris, PT, PhD, FAPTA, who received the Mildred O.
Elson Award, WCPT’s highest honor. In his acceptance speech, he noted, “What I’ve
learned over the years is that the gap between nations in terms of practice standards is
narrowing.” This seems to be the perfect segue to emphasize the need to break down
country “silos” even further.
Physical therapists around the world share a common mission: to improve health and
function through education, research, and practice. Imagine what would happen if we
all worked together in a truly concerted effort to accomplish this goal:
• Could our individual organization-led efforts to develop clinical practice guidelines be
more successful if we partnered with international groups? (See the ProfessionWatch
article by Van der Wees et al.2)
• Is there an international template for clinical competency of the new graduate?
• Could international research on hot topics such as exercise dose protocols and
treatment effectiveness facilitate translation to practice guidelines more efficiently?
Let’s work to grow the exciting global connections that we’ve begun to establish.
Rebecca L. Craik
R.L. Craik, PT, PhD, FAPTA, is Editor in Chief of PTJ and Professor and Chair, Department of Physical Therapy,
Arcadia University, Glenside, Pennsylvania. Dr Craik can be reached at: [email protected].
References
1 International Classification of Functioning, Disability and Health: ICF. Geneva, Switzerland: World Health
Organization; 2001.
2 Van der Wees PJ, Moore AP, Powers CM, et al. Development of clinical guidelines in physical therapy:
perspective for international collaboration [published online ahead of print July 28, 2011]. Phys Ther. doi:
10.2522/ptj.20100305.
[DOI: 10.2522/ptj.2011.91.8.1150]
August 2011
editorial_8.11.indd 1151
7/18/11 10:57 AM
The Bottom Line
The Bottom Line summarizes the key points of articles that report research with a direct impact
on patient care.
Effects of Vestibular Rehabilitation
on Multiple Sclerosis–Related
Fatigue and Upright Postural
Control
People with multiple sclerosis (MS) have
a multitude of symptoms. Fatigue is the
most common complaint, followed by
impaired mobility. Balance training is an
effective treatment for patients with MS
who have impaired upright postural control (ie, balance); however, the evidence for
the effectiveness of interventions for MSrelated fatigue is limited and inconsistent.
Previously, no studies have investigated the
effectiveness of a vestibular rehabilitation
program on both MS-related fatigue and
balance. This study provides early evidence
of the feasibility and effectiveness of a vestibular rehabilitation program on fatigue,
balance, and disability due to dizziness or
disequilibrium for people with MS. Message for patients: If you have MS and have
fatigue and balance problems, participation in a program of vestibular rehabilitation may improve fatigue and balance and
reduce disability related to dizziness or disequilibrium, with no known side effects.
Larger follow-up studies are needed, however, to support these results.
See page 1166.
Cervical Flexor Activity and
Temporomandibular Disorders
Cervical spine dysfunction has been reported to be associated with temporomandibular disorders (TMD). Temporomandibular
disorders also are commonly associated
with other symptoms affecting the head
and neck region such as headache, earrelated symptoms, and altered head and
cervical posture. However, no study has investigated the presence of cervical muscle
impairments using electromyography. The
results of this study may give clinicians insight into the importance of the evaluation
and possible treatment of the deep neck
flexors in patients with TMD. However,
randomized clinical trials are necessary to
determine the effectiveness of an exercise
program targeting the deep neck flexors in
these patients. Message for patients: If you
have a TMD, these findings may help your
physical therapist evaluate your condition.
This evaluation would include an examination of the cervical musculature as well as
the TMD.
See page 1184.
Frontal-Plane Gait Mechanics in Knee
Osteoarthritis
Patients with medial and lateral knee
osteoarthritis exhibit different hip and knee
mechanics during gait. These differences in
mechanics have previously been associated
with elevated disease progression. The findings from this study suggest that patients
with medial and lateral knee osteoarthritis
also have different mechanics at the ankle.
The observed differences in mechanics are
contrary to current clinical beliefs. The difference in presentation may be due to the
chronic effects of the disease process. Message for patients: If you have osteoarthritis on the inside of the knee (medial knee
osteoarthritis), the treatments you receive
may be different from the treatments that
patients with knee osteoarthritis on the outside of the knee (lateral knee osteoarthritis)
may receive.
See page 1235.
Physical Performance and Executive
Function in Older Adults With Mild
Cognitive Impairment
Older adults with mild cognitive impairment (MCI) are at higher risk for dementia
and associated disability. Functional decline often is accelerated in the presence of
both physical and cognitive impairments.
In this study of sedentary older adults with
amnestic MCI (memory loss), slower physical performance on gait and mobility tasks
was associated with lower performance on
executive function tasks, such as those involving planning and judgment. Message
for patients and families: Comprehensive
prevention and rehabilitation strategies
that enhance both cognitive and physical
function are important in reducing functional decline and disability in older adults.
See page 1198.
August 2011
Research Report
Age-Related Differences in Muscle
Fatigue Vary by Contraction Type:
A Meta-analysis
Keith G. Avin, Laura A. Frey Law
Background. During senescence, despite the loss of strength (force-generating
capability) associated with sarcopenia, muscle endurance may improve for isometric
contractions.
Purpose. The purpose of this study was to perform a systematic meta-analysis of
young versus older adults, considering likely moderators (ie, contraction type, joint,
sex, activity level, and task intensity).
Data Sources. A 2-stage systematic review identified potential studies from
PubMed, CINAHL, PEDro, EBSCOhost: ERIC, EBSCOhost: Sportdiscus, and The
Cochrane Library.
Study Selection. Studies reporting fatigue tasks (voluntary activation) performed at a relative intensity in both young (18 – 45 years of age) and old (ⱖ55 years
of age) adults who were healthy were considered.
Data Extraction. Sample size, mean and variance outcome data (ie, fatigue
index or endurance time), joint, contraction type, task intensity (percentage of
maximum), sex, and activity levels were extracted.
Data Synthesis. Effect sizes were (1) computed for all data points; (2) sub-
K.G. Avin, PT, DPT, Graduate Program in Physical Therapy & Rehabilitation Science, The University
of Iowa, Iowa City, Iowa.
L.A. Frey Law, PT, PhD, Graduate
Program in Physical Therapy &
Rehabilitation Science, The University of Iowa, 1-252 Medical
Education Bldg, Iowa City, IA
52242-1190 (USA). Address all
correspondence to Dr Frey Law at:
[email protected].
[Avin KG, Frey Law LA. Age-related
differences in muscle fatigue vary
by contraction type: a metaanalysis. Phys Ther. 2011;91:
1153–1165.]
© 2011 American Physical Therapy
Association
Published Ahead of Print: May 26,
2011
Accepted: March 22, 2011
Submitted: October 7, 2010
grouped by contraction type, sex, joint or muscle group, intensity, or activity level;
and (3) further subgrouped between contraction type and the remaining moderators.
Out of 3,457 potential studies, 46 publications (with 78 distinct effect size data
points) met all inclusion criteria.
Limitations. A lack of available data limited subgroup analyses (ie, sex, intensity,
joint), as did a disproportionate spread of data (most intensities ⱖ50% of maximum
voluntary contraction).
Conclusions. Overall, older adults were able to sustain relative-intensity tasks
significantly longer or with less force decay than younger adults (effect size⫽0.49).
However, this age-related difference was present only for sustained and intermittent
isometric contractions, whereas this age-related advantage was lost for dynamic tasks.
When controlling for contraction type, the additional modifiers played minor roles.
Identifying muscle endurance capabilities in the older adult may provide an avenue
to improve functional capabilities, despite a clearly established decrement in peak
torque.
August 2011
Volume 91
Number 8
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this article at:
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Physical Therapy f
1153
Age-Related Muscle Fatigue: A Meta-analysis
A
lthough it is well recognized
that sarcopenic changes in
aging adults result in diminished muscle mass and subsequent
loss of strength (force-generating
capacity),1,2 it is less clear how aging
affects the properties of muscle
fatigue. A greater understanding of
muscle fatigue capabilities across the
life span may influence clinical decision making and affect therapeutic
exercise prescription.
Although older adults may be commonly perceived as fatiguing more
readily, resistance to muscle fatigue
actually may improve with age.3 Perceptions of fatigue may be reported
as a “feeling of tiredness” or “lack of
energy,”4 which can be distinct from
muscle fatigue, defined as, “any
exercise-induced reduction in the
ability to exert muscle force or
power, regardless of whether or not
the task can be sustained.”5(p691) Several studies have been performed to
assess differences in resistance to
muscle fatigue in young adults versus
old adults. However, to date, these
data have not been systematically
compiled to determine whether older
adults indeed have consistently greater
muscle endurance than young adults
and which factors may influence
these age-related differences.
Muscle fatigue can vary greatly
within and between individuals due
to the complex nature of fatigue.
That is, muscle fatigue capabilities
can vary between contraction types
(isometric versus isokinetic),6 joints
or muscle groups,7 task intensities,8
and position-matching versus forcematching paradigms.9 In addition,
Available With
This Article at
ptjournal.apta.org
• Discussion Podcast with authors
Keith Avin and Laura Frey Law.
Moderated by Carolynn Patten.
1154
f
Physical Therapy
Volume 91
muscle fatigue may differ between
men and women10,11 or with physical activity status.12 These factors
may have the potential to influence
age-related muscle fatigue properties. To date, only small-scale
reviews have provided insights into
subsets of the research available to
ascertain age-related differences in
muscle fatigue properties.3,13
Despite the number of available studies on muscle fatigue, our understanding of age-related changes in
fatigue remains incomplete. Properly
indentifying capabilities in older
adults may affect dose-response relationships and modify therapeutic
exercise interventions. Thus, the
purpose of this study was to characterize differences in muscle fatigue
between young and old adults using
systematic meta-analysis techniques
to compile the available literature.
Effect sizes were used to assess the
degree to which young or old adults
were more fatigable considering all
data, as well as preplanned subgroupings based on contraction
type, sex, joint region, task intensity,
and physical activity levels, when
possible.
Method
Database Review
A 2-stage systematic review of the
literature was used to identify studies on muscle fatigue including both
old and young adults. Stage 1
involved searches of the following
databases: PubMed (1948 to June 28,
2010), the Cumulative Index to Nursing and Allied Health Literature
(CINAHL; 1937 to June 28, 2010),
PEDro (1929 to June 28, 2010),
EBSCOhost: ERIC (1966 to June 28,
2010), EBSCOhost: Sportsdiscus
(1888 to June 28, 2010), and The
Cochrane Library (1993 to June 28,
2010). A total of 11 search terms and
key word combinations were used to
elicit relevant articles, including:
“endurance,” “fatigue,” “aging adult,”
“older adult,” “intermittent fatigue,”
Number 8
“isokinetic fatigue,” and “isometric
fatigue.” For example, a search performed in PubMed (accessed October 5, 2009) using the key words
“aging” and “fatigue” yielded 600
related articles. The inclusion and
exclusion criteria (see below) were
used to include studies providing
young versus old adult muscle
fatigue data. Stage 2 involved reviewing bibliographies of studies meeting
the inclusion criteria of stage 1 to
find additional relevant fatigue studies. All abstracts were first screened
for studies that reported the performance of a relative-intensity fatigue
task, including young and old adult
cohorts. These studies then were
retrieved in full text and reviewed by
both authors to ensure agreement
on inclusion and exclusion criteria,
and all entered data were reviewed
twice against the original articles to
decrease the likelihood of transcription errors.
Inclusion and Exclusion Criteria
The following criteria were used for
study inclusion: human participants
who were healthy; young cohort
mean age between 18 and 45 years
and older cohort mean age ⱖ55
years; sustained isometric, intermittent isometric, isokinetic, or isotonic
tasks using relative intensities based
on maximum voluntary contraction
(% MVC); outcome measures of
either time to task failure (ie, endurance time) or reduction in peak
torque (ie, fatigue index); single-joint
involvement (per fatigue task); and
publication in English. Studies were
excluded if they used electrical stimulation to elicit fatigue, simultaneous
multijoint testing, or functional tasks
that did not assess torque as a percentage of the maximum value or
that used body or limb weight as the
primary resistance (eg, Sorensen
test). In addition, if variance information (eg, standard deviation) was not
reported or was unattainable from
the authors, studies were excluded.
Inclusion and exclusion criteria did
August 2011
not account for athletic training status or level of physical activity, but
when reported, this information was
utilized.
Quality assessment of included studies did not require the traditional
approaches used for meta-analyses to
assess interventions, such as blinded
investigators, placebo-controls, or
random assignment. Rather, the
powerful statistical application of
meta-analysis was used with observational studies to systematically compile the data available to better distinguish fatigue capabilities in the
older versus younger adults, considering several possible moderating
variables.
Outcome Variables
To characterize differences in muscle fatigue between 2 groups, protocols typically utilize relative-intensity
tasks (% MVC) to standardize task
demands between individuals. Muscle fatigue properties are assessed
indirectly, either by the duration a
relative-intensity task can be sustained (ie, endurance time) or the
percentage of baseline peak force
remaining following the performance of a task for a preset duration. Most studies reported only 1 of
these 2 outcome variables, but occasionally those involving intermittent
tasks reported both. When this
occurred, only the percentage of
change in peak force was used in
the meta-analysis, as this was the
preferred outcome variable reported
for intermittent tasks. Greater muscle fatigue is observed as shorter
endurance times or lower percentages of baseline torque values.
Endurance time usually is reported
as the total duration a relativeintensity task can be maintained
until the target muscle torque falls
to 5% to 10% below target levels.
Only acute muscle fatigue was
assessed in this study (ie, immediate
or short-term outcomes, rather than
long-duration decrements in forceAugust 2011
producing capability associated with
low-frequency fatigue). Relevant
endurance or fatigue data reported
only in graphic form were extracted
using pixel analysis (Adobe Photoshop*) to determine the respective
numerical values. Means and standard deviations for young and old
cohorts were recorded for each pair
of data.
Moderating Variables
Additional study information was
recorded for analysis, including sample size, sex, mean age for each
cohort (young, old), standardized
task intensity (from 1% to 100% of
maximum), contraction type (sustained isometric, intermittent isometric, and isokinetic), joint region
tested (eg, ankle, back, elbow), joint
angle, torque direction (eg, flexion,
extension), and physical activity
level (when reported). When outcome measures were not reported
separately by sex and were unavailable following attempts to contact
the corresponding authors, the data
were coded simply as “mixed sex.”
Contractions were classified as 1 of 3
types: 2 static (isometric with [sustained] or without [intermittent] rest
intervals) and 1 dynamic (isokinetic).
Task intensity was categorized as
low (ⱕ33% of maximum), moderate
(34%– 66% of maximum), or high
(ⱖ67% of maximum), regardless of
contraction type. Given the varying
methods for quantifying physical
activity, data were dichotomized to
active or inactive when available.
When necessary, the data for multiple age cohorts (eg, for 20 –29 and
30 –39 years) were combined using
weighted means and pooled standard deviations.14 When multiple
task intensities (eg, 30% and 50% of
maximum) or joint regions (eg, ankle
and elbow) were reported in a single
manuscript, data for each fatigue
* Adobe Systems Inc, 345 Park Ave, San Jose,
CA 95110.
task were included (in separate
rows) rather than combining them
into a single mean or selecting only
one task per study. We chose this
strategy to minimize any potential
self-selection bias or missing potential effects due to joint or intensity
factors. Although this approach
allows for multiple measures that
are not fully independent, particularly for observational studies, it is
challenging to determine whether
independence is ensured across publications (by the same authors). That
is, the same patient population may
be recruited for studies reported in
multiple publications.
Statistical Analyses
Effect size is the standardized mean
difference between 2 populations
(ie, young versus old). Hedges’ g was
chosen as the best effect size estimate due to its correction for slight
overestimations that may occur with
small samples.15 Mean effect sizes
(and associated variances) across
studies were calculated (Comprehensive Meta-Analysis†) using a
mixed-effects model determined a
priori (random and fixed effects). A
random-model approach was chosen
under the guise of generalizing
results among the older population
and inherent inequality of effect
sizes across studies. A fixed subgroup analysis assumes results will
generalize to the specific variables of
interest such as contraction type (eg,
sustained isometric, intermittent isometric, isokinetic), intensity, and so
on. Results are presented such that
positive effect size values indicate
older adults are more resistant to
fatigue, whereas negative effect size
values indicate young adults are
more resistant to fatigue.
Analyses were stratified into 3 levels
(Fig. 1), with preplanned subgrouping categories. A specific subgroup
was included in comparisons only if
†
Volume 91
Biostat, 14 N Dean St, Englewood, NJ 07631.
Number 8
Physical Therapy f
1155
Stage 1:
3,445 related records identified
through database searches
Stage 2:
48 records identified through
citation search of included articles
3,457 records after
duplicates removed
3,457 records screened
3,372 records excluded
39 records excluded:
• 1–Nonvoluntary
• 1–No variance data
• 1–Outcome variables
• 2–Multiple joints
• 12–Old adults only
• 12–Young adults only
• 2–Patient cohort only
• 7–Limited time duration
or no fatigue
• 1–No age specified
85 full-text articles
assessed for eligibility
46 studies included in
quantitative synthesis
(meta-analysis)
(78 data points)
Figure 1.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow
diagram of the literature search.
ogeneity among the data included,
whereas the I2 index is better able
to quantify the magnitude of the
heterogeneity.16 We operationally
defined the magnitude of heterogeneity as low (I2ⱕ33%), moderate
(34%ⱕI2⬍67%), and high (I2ⱖ67%),
based on previous suggestions.17
Heterogeneity estimates were evaluated at each level of analysis.
Results are reported as mean summary effect sizes (with P values) for
each subgroup analysis. A more stringent alpha level than conventionally
used (␣ⱕ.01) was chosen to minimize both type I and II errors.18
Observational studies are less likely
than interventional studies to be
adversely affected by publication
bias, as identifying a fatigue advantage in either direction would be
deemed a valuable scientific contribution. Furthermore, several studies
investigated other aspects of muscle
fatigue, such that the data relevant
to this meta-analysis were not necessarily the primary outcomes (accordingly, lack of age-related fatigue
differences would not influence
likelihood of publication). Therefore, our analyses were not further
extended for publication bias within
or between studies.
Results
it included data from a minimum of
3, separate published studies; thus,
the final set of subgroups was determined by the data available.
The level I analysis determined a single composite effect size for resistance to fatigue for old versus young
groups, including all data points
with no subgroups. Level II analyses
included subgrouping by single individual categories (sex, contraction
type, intensity, joint tested, and
activity level) to the extent sufficient
data were available. Level III analyses
involved further subgrouping the
contraction types from level II, such
as comparing intensity levels, sex,
1156
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Physical Therapy
Volume 91
or joints within each contraction
type (eg, interaction or moderated
effects), when sufficient data were
available. Level III subgroupings
were considered only when sufficient data were available (ie, 3 or
more independent studies).
The goal of a meta-analysis is to
not only compute summary effect
sizes but also determine the extent
of variation present in the true effect
size (ie, heterogeneity), suggesting
whether additional moderating variables are involved. Heterogeneity
was quantified via the I2 index and
the Q test.15 A significant Q statistic
indicates only the presence of heter-
Number 8
Database Review
Initial search strategies (stages 1 and
2) resulted in 3,457 potential studies
(after duplicates were removed),
with 46 studies meeting all inclusion criteria (Fig. 1). Several studies
reported on more than one joint or
muscle group, contraction type, or
task intensity, for a total of 78 young
adult versus old adult fatigue comparisons (ie, individual effect sizes)
to analyze. The numbers of data
points per subgroup comparison are
detailed in the Table.
Level I: Overall Age Effect
The level I analysis, using all 78 individual effect sizes, revealed that
August 2011
Table.
Summary of Heterogeneity Statistics for Each Subgroup Analysis
Analysis Level
na
Q Test
(P Value)b
I2 Index
(%)
78
⬍.001
56.4
Sustained isometric
45
.005
38.9
Intermittent isometric
16
.652
0.0
Subgrouping
Intensity
Level I
Level II, contraction
Isokinetic
16
.001
60.4
Level II, sex
Male
45
⬍.001
58.9
Female
18
.006
51.8
Level II, intensity
Low
15
⬍.001
73.8
Level II, joint
Level II, activity
Level III, contraction/intensity
Level III, contraction/sex
Level III, contraction/joint
Level III, contraction/activity
Moderate
25
.081
29.8
High
38
⬍.001
57.1
Ankle
17
.018
68.7
Elbow
14
.024
47.7
Hand
16
.183
23.9
Knee
22
⬍.001
57.5
Active
44
⬍.001
55.1
Inactive
11
.512
0.0
Low
14
.004
57.4
Moderate
21
.036
38.8
High
10
.692
0.0
3
.554
0.0
Sustained isometric
Moderate
High
13
.582
0.0
Sustained isometric
Male
29
.006
44.6
Female
8
.236
24.2
Male
8
.449
0.0
Female
4
.709
0.0
Isokinetic
Male
7
.001
74.3
Female
6
.336
12.4
Sustained isometric
Ankle
4
.015
71.5
Elbow
12
.030
48.4
Hand
13
.669
0.0
Knee
7
.237
25.2
Ankle
9
.960
0.0
Isokinetic
Ankle
3
.002
83.5
Knee
13
.031
46.9
Active
Sustained isometric
Isokinetic
30
.064
29.8
Inactive
4
.739
0.0
Active
7
.289
18.5
Inactive
6
.750
0.0
Active
8
.004
66.4
a
Number of data points per analysis level.
b
P values are uncorrected for multiple comparisons.
August 2011
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Physical Therapy f
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Article
%
Maximum
Hedges’
g
SE
P
Hand
M
NA
50
0.36
0.35
.309
Bazzucchi et al, 20058
Elbow
M
Active
30
0.27
0.54
.620
Bazzucchi et al, 20058
Elbow
M
Active
50
1.72
0.64
.007
20058
Elbow
M
Active
80
1.26
0.59
.033
Bilodeau et al, 200120
Elbow
MX
Inactive
100
0.70
0.43
.104
200120
Bilodeau et al,
Sex
Activity
Level
Aniansson et al, 197819
Bazzucchi et al,
Joint
Elbow
MX
NA
35
1.53
0.50
.002
Chatterjee and Chowdhuri, 199122
Hand
M
Inactive
40
0.12
0.34
.719
Christie and Kamen, 200923
Ankle
MX
Active
50
⫺0.68
0.49
.163
Griffith et al, 201024
Ankle
MX
Active
30
0.64
0.38
.091
Hara et al, 199825
Hand
MX
Inactive
50
0.56
0.49
.253
Huang et al, 200726
Hand
MX
NA
75
0.89
0.39
.021
200410
Elbow
M
NA
20
1.98
0.49
.000
Hunter et al, 200410
Elbow
F
NA
20
0.32
0.43
.465
200527
Hunter et al,
Elbow
M
NA
20
1.42
0.54
.008
Johnson, 198228
Knee
F
Active
50
0.32
0.36
.365
Lanza et al, 200529
Ankle
M
Inactive
100
0.33
0.48
.492
Larsson and Karlsson, 19781
Knee
M
Active
50
0.42
0.36
.244
Mademli and Arampatzis, 200830
Ankle
M
Active
40
1.40
0.43
.001
Mademli et al, 200831
Knee
M
Active
25
1.15
0.41
.005
Hand
MX
NA
40
0.56
0.49
.254
Hand
M
NA
40
0.03
0.27
.907
Hunter et al,
Momen et al,
200432
Petrofsky et al, 197533
Petrofsky and Lind,
197534
Hand
F
NA
40
0.72
0.28
.010
Petrofsky and Laymon, 200235
Hand
M
NA
40
1.15
0.40
.004
200235
Petrofsky and Laymon,
Knee
M
NA
40
1.43
0.41
.001
Petrofsky et al, 200936
Hand
MX
Active
40
0.45
0.36
.207
Smolander et al, 199837
Hand
M
Active
20
0.18
0.47
.695
Hand
M
Active
40
0.46
0.47
.333
199837
Hand
M
Active
60
0.29
0.47
.542
Knee
M
Active
20
0.30
0.47
.530
199837
Knee
M
Active
40
0.19
0.47
.682
Knee
M
Active
60
0.39
0.47
.408
Smolander et al,
Smolander et al,
Taylor et al,
199138
Hand
M
Active
30
0.28
0.37
.455
Yassierli et al, 200739
Shoulder
M
Active
30
0.60
0.29
.039
Shoulder
M
Active
50
0.40
0.29
.165
Shoulder
M
Active
70
0.21
0.28
.465
200739
Back
M
Active
30
0.44
0.40
.272
Back
M
Active
50
0.28
0.40
.475
200739
Back
M
Active
70
0.12
0.39
.767
Back
F
Active
30
⫺0.12
0.39
.753
Yassierli et al,
Yassierli et al,
(Continued)
Figure 2.
Forest plot of individual effect sizes for sustained isometric contractions only, with their corresponding subgrouping categories for
sex, joint, task intensity, and physical activity level. Positive effect sizes indicate greater fatigue resistance for older adults, whereas
negative effect sizes indicate greater fatigue resistance for younger adults. SE⫽standard error, CI⫽confidence interval, M⫽male,
F⫽female, MX⫽mixed, NA⫽not available.
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August 2011
Article
%
Maximum
Hedges’
g
SE
P
Back
F
Active
50
0.15
0.39
.696
Back
F
Active
70
0.00
0.39
1.000
Yoon et al, 200840
Elbow
M
Active
20
3.17
0.84
.000
200840
Elbow
M
Active
80
0.64
0.55
.247
Yoon et al, 200840
Elbow
F
Active
20
1.52
0.51
.003
Elbow
F
Active
80
Yoon et al,
200840
Isometric Summary
Sex
Activity
Level
Yoon et al,
Joint
(Fixed)
0.44
0.45
.332
0.53
0.06
.000
Figure 2.
Continued
older adults were significantly more
resistant to acute muscle fatigue
(greater muscle endurance) than
young adults, with a moderate mean
effect size of 0.49 (95% confidence
interval⫽0.35– 0.63). Forest plots
showing individual effect sizes by
Article
Joint
contraction type are presented in
Figures 2, 3, and 4. Figure 5 illustrates the effect sizes for each analysis level. One isotonic effect size was
included in the overall analysis, but
was not extended to a separate
Sex
Activity
Level
contraction-type subgroup due to a
lack of comparative studies.
Level II Subgroups
Contraction type. Older adults
demonstrated greater muscle fatigue
resistance (ie, more endurant) for
%
Maximum
Hedges’
g
SE
P
60
0.24
0.54
.656
Allman and Rice, 200341
Elbow
M
Active
Allman and Rice, 200142
Elbow
M
Active
60
0.42
0.51
.409
Callahan et al, 200943
Knee
MX
Inactive
100
1.16
0.38
.002
Hand
MX
Active
100
1.36
0.49
.006
Ankle
M
NA
100
0.97
0.42
.020
200046
Hand
M
Active
100
1.85
0.52
.000
Ditor and Hicks, 200046
Hand
F
Active
100
0.77
0.45
.085
200247
Ankle
M
Inactive
100
0.74
0.43
.082
Kent-Braun et al, 200247
Ankle
F
Inactive
100
1.20
0.47
.010
Lanza et al, 200448
Ankle
M
Active
100
0.54
0.46
.242
Lanza et al, 200749
Ankle
MX
Inactive
100
0.90
0.33
.007
Chan et al,
200044
Chung et al, 200745
Ditor and Hicks,
Kent-Braun et al,
Mademli and Arampatzis,
200850
Ankle
M
NA
Rubinstein and Kamen, 200551
Ankle
F
Active
65
0.94
0.44
.033
100
0.86
0.34
.012
Russ et al, 200852
Ankle
M
Inactive
100
0.48
0.49
.335
Russ et al, 200852
Ankle
F
Inactive
100
0.43
0.47
.361
Stackhouse et al, 200153
Knee
MX
NA
100
Intermittent Isometric Summary
(Fixed)
0.34
0.34
.318
0.82
0.11
.000
Figure 3.
Forest plot of individual effect sizes for intermittent isometric contractions only, with their corresponding subgrouping categories for
sex, joint, task intensity, and physical activity level. Positive effect sizes indicate greater fatigue resistance for older adults, whereas
negative effect sizes indicate greater fatigue resistance for younger adults. SE⫽standard error, CI⫽confidence interval, M⫽male,
F⫽female, MX⫽mixed, NA⫽not available.
August 2011
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Physical Therapy f
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Article
Joint
Sex
Activity
Level
M
NA
Knee
Knee
F
Baudry et al, 200754
Ankle
F
Callahan et al,
200943
%
Maximum
Hedges’
g
SE
P
100
0.25
0.35
.476
NA
100
⫺0.03
0.33
.917
NA
100
⫺0.46
0.35
.188
Knee
MX
Inactive
100
0.09
0.36
.816
Johnson, 198228
Knee
F
Active
100
⫺0.31
0.36
.387
Laforest et al, 199012
Knee
MX
MX
100
⫺0.09
0.22
.686
Lanza et al, 200448
Ankle
M
Active
100
1.72
0.55
.002
Larsson and Karlsson,
19781
Knee
M
Active
100
0.20
0.43
.644
Lindstrom et al, 199755
Knee
M
Active
100
⫺0.47
0.43
.280
Knee
F
Active
100
0.74
0.49
.134
Knee
F
Active
100
0.12
0.47
.809
200656
Knee
M
Active
100
⫺1.13
0.46
.014
Knee
M
Active
50
0.31
0.38
.421
Ankle
MX
NA
100
0.55
0.28
.046
Knee
M
NA
100
0.98
0.35
.005
Knee
F
NA
100
⫺0.40
0.23
.085
0.05
0.09
.564
Lindstrom et al,
Mademli et al, 200831
Muller et al,
200758
Rawson, 200959
Schwendner et al,
199760
Isokinetic Summary
(Fixed)
Figure 4.
Forest plot of individual effect sizes for isokinetic contractions only, with their corresponding subgrouping categories for sex, joint,
task intensity, and physical activity level. Positive effect sizes indicate greater fatigue resistance for older adults, whereas negative
effect sizes indicate greater fatigue resistance for younger adults. SE⫽standard error, CI⫽confidence interval, M⫽male, F⫽female,
MX⫽mixed, NA⫽not available.
both sustained (Fig. 2) and intermittent (Fig. 3) isometric contractions,
but the intermittent tasks showed
the greatest age-related advantage
compared with sustained tasks
(effect size⫽0.82 versus 0.52,
P⫽.009; Fig. 5). However, for
dynamic contractions, no age-related
difference in muscle fatigue was
observed (effect size⫽0.05, Fig. 4).
Sex. Older adults of both sexes
were more fatigue resistant than
younger adults. This age-related
advantage, however, was greater for
men than for women (P⫽.009)
when not accounting for any additional moderating factors (Fig. 5).
Joint. Older adults were significantly more fatigue resistant than
young adults across all joint region
subgroups assessed (ie, ankle,
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elbow, hand, and knee joint regions
had sufficient data available). However, these effect sizes differed
among joints (P⬍.008), with the
exception of the ankle versus the
hand joint regions (P⫽.42). The largest effect size was observed at the
elbow and the smallest effect size
was observed at the knee, when not
accounting for any additional factors
(Fig. 5). However, the elbow joint
tasks comprised solely static contraction protocols, whereas the knee
included both isometric and isokinetic testing (see level III subgrouping below).
Intensity. Older adults were more
resistant to fatigue across all intensity levels (low, moderate, and high)
(Fig. 5). Although effect sizes
decreased with increasing intensity
(ie, the fatigue advantage with
Number 8
advancing age decreased at higher
intensities), none of the differences
achieved significance (P⬎.067)
(Fig. 5).
Physical activity. Older adults
were more resistant to fatigue across
active and inactive cohorts, with the
difference in effect sizes between
subgroups just beyond significance
(P⫽.063).
Level III Analyses
Contraction type ⴛ intensity.
Although task intensity moderated
the age-related fatigue advantage
overall (see level II above), this effect
was lost or reversed when controlling for contraction type (Fig. 5). For
sustained isometric contractions,
older adults remained more fatigue
resistant than young adults across
all intensities (low, moderate, and
August 2011
Level
Hedges’
g
Subgroupings
SE
P
0.49
0.07
⬍.001
Sustained isometric
0.53
0.06
⬍.001
0.82
0.10
⬍.001
Level I, all
Level II, contraction type
Isokinetic
0.05
0.08
.358
Level II, sex
Male
0.49
0.06
⬍.001
Female
0.23
0.09
.005
Level II, intensity
Low
0.51
0.11
⬍.001
Level II, joint
Level II, activity
Level III, contraction/
intensity
Level III, contraction/sex
Moderate
0.50
0.08
⬍.001
High
0.35
0.06
⬍.001
Ankle
0.51
0.10
⬍.001
Elbow
0.97
0.14
⬍.001
Hand
0.55
0.09
⬍.001
Knee
0.20
0.08
.003
Active
0.39
0.06
⬍.001
Inactive
0.60
0.12
⬍.001
Sustained isometric
Low
0.67
0.11
⬍.001
Moderate
0.50
0.08
⬍.001
High
0.41
0.13
.005
Moderate
0.58
0.28
.128
High
0.85
0.11
⬍.001
Sustained isometric
Male
0.55
0.08
⬍.001
Female
0.40
0.14
.003
Male
0.78
0.17
⬍.001
Female
0.82
0.21
⬍.001
Isokinetic
Male
0.26
0.15
.054
⫺0.20
0.14
.268
Sustained isometric
Ankle
0.51
0.22
.020
Elbow
1.08
0.15
⬍.001
Hand
0.44
0.10
⬍.001
Female
joint
activity
Knee
0.61
0.16
⬍.001
Ankle
0.81
0.14
⬍.001
Isokinetic
Ankle
0.37
0.20
.106
Knee
⫺0.02
0.09
.807
Active
0.44
0.08
⬍.001
Inactive
0.38
0.21
.07
Active
0.86
0.18
⬍.001
Inactive
0.85
0.17
⬍.001
Active
0.05
0.15
.344
Sustained isometric
Isokinetic
Figure 5.
Forest plot of summary effect sizes for each subgrouping category (level I–III). Positive effect sizes indicate greater fatigue resistance
for older adults, whereas negative effect sizes indicate greater fatigue resistance for younger adults. SE⫽standard error,
CI⫽confidence interval.
August 2011
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high), with no significant difference
exhibited among intensity subgroups (Pⱖ.07). Conversely, for
intermittent isometric contractions,
no significant age differences
occurred for moderate intensities,
whereas a large effect size was
observed for high intensities (insufficient low-intensity, intermittent task
data available). Although these findings demonstrate opposing influences of intensity on intermittent
tasks than observed with the sustained isometric tasks (or overall in
level II), only 3 of the 16 intermittent
tasks were performed at a moderate
intensity.
Contraction type ⴛ sex. Although
sex was a significant moderator of
the age-related endurance advantage
in the level II analyses, it was not a
significant moderator when considering each contraction type separately. Older adults (both men and
women) remained more fatigue
resistant for sustained and intermittent isometric tasks, but did not differ between sexes (P⬎.17) (Fig. 5).
Furthermore, no age-related advantage was observed in either men or
women (effect sizes not significantly
different than zero) for the isokinetic
contractions.
Contraction type ⴛ joint. Similarly, further subgrouping contraction type by joint region slightly
altered the findings from the previous level II analyses. Within sustained isometric contractions, older
adults were more fatigue resistant
across the joints considered (elbow,
hand, and knee joint regions, with
the ankle just surpassing our stringent critical value). However, only
the elbow continued to result in significantly larger effect sizes than the
remaining joints, with the knee now
exhibiting effect sizes similar to
those of the hand and ankle (Fig. 5).
For intermittent isometric contractions, the ankle (only subgroup possible) demonstrated significant age1162
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Physical Therapy
Volume 91
related advantages in muscle fatigue.
During isokinetic contractions, neither the ankle nor the knee (the only
joints with sufficient data) demonstrated any age-related advantage
(or disadvantage) in fatigue resistance (Pⱖ.06). Overall, joint region
had only mild moderating influences
on the fatigue differences observed
between young versus old adults
when controlling for contraction
type.
Contraction type ⴛ physical activity. Physical activity did not substantially
alter
the
previous
contraction-type subgroups (Fig. 5).
Older adults were significantly more
fatigue resistant across each combination of sustained and intermittent
isometric contraction types and
activity levels except for the inactive, sustained isometric group,
which likely was underpowered
(n⫽4, effect size⫽0.38, P⫽.07). The
age-related fatigue advantage did
not differ significantly between the
active and inactive groups for isometric or intermittent tasks (P⬎.40).
Heterogeneity
Overall, heterogeneity was categorized as low to moderate for all levels
of the meta-analysis (Tab. 1). The
proportion of subgroups categorized
with low heterogeneity increased
from 28.6% for level II analyses to
60.9% for level III analyses. The
increased proportion of low heterogeneity with additional subgroup
analyses suggests that several moderators identified in this analysis (eg,
contraction type, joint, intensity)
contributed to variations in agerelated fatigue resistance. Although
the level III heterogeneity increased
at the ankle for both sustained and
isokinetic contractions, the limited
number of data points (4 and 3,
respectively) demonstrated the difficulty in attaining a consistent summary effect size. Additional data are
needed to fully characterize agerelated fatigue differences.
Number 8
Discussion
This is the first study to systematically compile outcomes data to characterize age-related differences in
muscle fatigue considering several
potential moderating variables: contraction type, intensity, sex, joint
region, and activity level. The primary finding of this meta-analysis is
that muscle fatigue resistance is
enhanced with age for relativeintensity tasks when additional
intrinsic and extrinsic factors are
not considered (level I analysis). This
age-related advantage in fatigue resistance occurred for both sustained
and intermittent isometric contractions, but is lost for isokinetic
contractions.
Improved fatigue resistance with
advancing age is consistent with several reported changes in muscle
properties with aging. A preferential
atrophy of type II fibers1,61 and preferential loss of fast motor units2
have been observed with advancing
age and sarcopenia. These changes
would result in a greater proportion
of type I or slow, oxidative fibers,
which may account for greater
fatigue resistance during relativeintensity tasks (ie, tasks standardized
to maximum strength). However,
this adaptation did not prove beneficial under all conditions (ie, dynamic
tasks).
Level II and III analyses revealed
older adults were more endurant
than young adults for sustained and
intermittent isometric (static) contractions, but not for isokinetic
(dynamic) contractions. This result is
somewhat surprising, as we anticipated the intermittent isometric contractions to behave similarly to isokinetic contractions, as greater muscle
reperfusion, replenishment of oxygenated blood, and removal of metabolic wastes might be facilitated
under both conditions. To the contrary, the intermittent tasks resulted
in the greatest age-related fatigue
August 2011
advantage, whereas isokinetic tasks
showed no age-related differences.
Thus, the inclusion of rest intervals,
and accordingly muscle reperfusion,
does not appear to be the key variable, but rather the contraction type
itself appears to be of importance
in age-related endurance changes.
One explanation may be that the
proportional shift toward type I
fibers and the slowing of both contraction and relaxation times that
occurs with aging may cause a leftward shift in the force-frequency
curve62 and a leftward and downward shift in the force-velocity
curve.63 Thus, although the muscle
fibers are slower and rely on greater
oxidative energy sources, they may
be less able to maintain power
(ie, force ⫻ velocity) over time.
These adaptations may enable the
older adult to be more fatigue resistant for isometric contractions
(slower, oxidative fibers), but not
during dynamic contractions, where
impaired power generation would
be expected to have its greatest
impact.
Anecdotal perceptions of muscle
fatigue increasing with advancing
age are in opposition to the controlled research findings of greater
fatigue resistance with aging. This
finding may be partially explained
by the differences observed between
static and dynamic tasks, as many
functional tasks (eg, sit-to-stand
maneuver, ambulation) require
dynamic rather than static contractions. However, even with dynamic
tasks, older adults are not disadvantaged; thus, this potential discrepancy may be further attributed to differences between absolute- and
relative-intensity conditions. Functional tasks (eg, stair climbing)
require absolute loads that are not
proportional to peak strength. As the
older adult weakens with age,1,2
functional tasks can require a greater
percentage of maximal capacity;
thus, tasks are performed at a higher
August 2011
relative intensity.64 Fatigue occurs
more rapidly with increasing task
intensity; maximum endurance time
decreases nonlinearly with increasing task intensity.7 Thus, although
resistance to fatigue may improve
with age for a relative-intensity (eg,
50% of maximum) task that is standardized among individuals, the
increased relative workload for a
functional task may offset any age
advantage. That is, if a given task
requires 40% of maximum strength
for a young adult, but 60% for an
older adult, the apparent task endurance may be less for the older adult,
even if underlying muscle fatigue
resistance is greater with age.
Interpretation of the remaining
potential moderators (sex, physical
activity, intensity, and joint) associated with age-related differences in
muscle fatigue is somewhat challenging given the incomplete data available for each possible subgrouping.
No significant differences between
men and women were consistently
observed in this meta-analysis, once
contraction type was controlled for,
which is in agreement with conclusions drawn from several individual
studies19,46,47 but in opposition to
others.10 Current comparisons did
not assess whether sex differences in
muscle fatigue occurred, but rather
whether age differences varied by
sex. Lastly, greater physical activity
did not influence the age-related
fatigue advantage. However, these
findings are based on smaller subgroup samples, with heterogeneous
definitions of active versus inactive
individuals, and thus may reflect less
stability in effect size estimates.
Although the current meta-analysis
was able to identify differences in
muscle fatigue properties across contraction types between young and
old adults, there are several limitations that should be acknowledged.
Several subgrouping comparisons in
levels II and III for joint, intensity,
and contraction type were not performed due to a lack of available
data. The majority of intermittent isometric and isokinetic protocols were
performed at intensities of 50% MVC
or higher (most at 100%), limiting
the interpretation intensity has upon
fatigue differences with aging for
these contraction types. Intermittent
tasks were further limited by the disproportionate number of comparisons including men (8 men versus 4
women) and limited joint regions
that have been tested (ankle⫽9, all
others combined⫽7). Physical activity data were classified simply as
active versus sedentary, which may
miss subtle influences of varying levels of physical activity. Lastly, we
included studies with cohorts aged
ⱖ55 years, thus a relatively “young”
older adult minimum age criterion.
Secondary analyses demonstrated no
significant difference in effect size
estimates if we had used only studies
with adults over 60 years as our age
minimum criterion.
These findings suggest the need for
future studies to explicitly report
fatigue data by sex and provide physical activity information for both
young and old adult cohorts when
possible. Additional fatigue studies
involving isokinetic and intermittent
tasks using the upper extremities
and lower intensities would help
to minimize the potential bias and
interactions present among muscle
group, intensity, and contraction
type, as observed here. In particular,
it is not clear why this age-related
advantage is lost during dynamic
contractions, which would benefit
from research considering potential influences such as: task complexity, passive tissue contributions,
and muscle power. Finally, although
these findings provide greater
insight into age-related changes in
muscle fatigue properties, additional
research is needed to clarify the magnitude and impact of this potential
Volume 91
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Physical Therapy f
1163
benefit and whether it can be further
altered by therapeutic interventions.
Despite the abundance of acute muscle fatigue research, few studies
have attempted to compile all of the
available data on age-related differences in fatigue resistance. This
meta-analysis supports that aging
results in a general muscle fatigue
resistance advantage, but this advantage is particularly dependent on contraction type. Dynamic tasks, specifically isokinetic tasks, were not
found to exhibit any advantage (or
disadvantage) in muscle fatigue for
old versus young adults. The underlying mechanisms for these findings
remain somewhat unclear, but may
be due to a greater loss of muscle
power with aging. Ultimately, these
age-related fatigue differences may
help offset the deleterious effects
of sarcopenia and loss of muscle
strength. In light of a reduction in
strength, therapeutic interventions
may target muscle fatigue resistance
to affect functional capabilities in the
older adult.
Both authors provided concept/idea/project
design, writing, data collection and analysis,
and project management.
A poster presentation of this research was
given at the Combined Sections Meeting
of the American Physical Therapy Association; February 17–20, 2010; San Diego,
California.
The authors were funded, in part, by
National Institute of Arthritis and Musculoskeletal and Skin Diseases/National Institutes
of Health grant K01AR056134, National
Research Service Award 1 F31 AR056175,
and the Foundation for Physical Therapy.
DOI: 10.2522/ptj.20100333
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Research Report
Effects of Vestibular Rehabilitation on
Multiple Sclerosis–Related Fatigue and
Upright Postural Control:
A Randomized Controlled Trial
Jeffrey R. Hebert, John R. Corboy, Mark M. Manago, Margaret Schenkman
J.R. Hebert, PT, PhD, School of
Medicine–Physical Therapy Program, Department of Physical
Medicine and Rehabilitation, and
Department of Neurology, University of Colorado, Anschutz
Medical Campus, Mailstop C-244,
13121 E 17th Ave, ED II South,
Room L28 –3133, Aurora, CO
80045 (USA). Address all correspondence to Dr Hebert at:
[email protected].
J.R. Corboy, MD, Department of
Neurology, University of Colorado, Anschutz Medical Campus.
M.M. Manago, PT, DPT, NCS,
Physical Therapy, Department of
Rehabilitation, University of Colorado Hospital, Aurora, Colorado.
M. Schenkman, PT, PhD, FAPTA,
School of Medicine–Physical Therapy Program and Department of
Physical Medicine and Rehabilitation, University of Colorado,
Anschutz Medical Campus.
[Hebert JR, Corboy JR, Manago
MM, Schenkman M. Effects of
vestibular rehabilitation on multiple sclerosis–related fatigue and
upright postural control: a randomized controlled trial. Phys
Ther. 2011;91:1166 –1183.]
Association
Published Ahead of Print: June 16,
2011
Submitted: November 18, 2010
Background. Fatigue and impaired upright postural control (balance) are the 2
most common findings in people with multiple sclerosis (MS), with treatment
approaches varying greatly in effectiveness.
Objectives. The aim of this study was to investigate the benefits of implementing
a vestibular rehabilitation program for the purpose of decreasing fatigue and improving balance in patients with MS.
Design. The study was a 14-week, single-blinded, stratified blocked randomized
controlled trial.
Setting. Measurements were conducted in an outpatient clinical setting, and
interventions were performed in a human performance laboratory.
Patients. Thirty-eight patients with MS were randomly assigned to an experimental group, an exercise control group, or a wait-listed control group.
Intervention. The experimental group underwent vestibular rehabilitation, the
exercise control group underwent bicycle endurance and stretching exercises, and
the wait-listed control group received usual medical care.
Measurements. Primary measures were a measure of fatigue (Modified Fatigue
Impact Scale), a measure of balance (posturography), and a measure of walking
(Six-Minute Walk Test). Secondary measures were a measure of disability due to
dizziness or disequilibrium (Dizziness Handicap Inventory) and a measure of depression (Beck Depression Inventory–II).
Results. Following intervention, the experimental group had greater improvements in fatigue, balance, and disability due to dizziness or disequilibrium compared
with the exercise control group and the wait-listed control group. These results
changed minimally at the 4-week follow-up.
Limitations. The study was limited by the small sample size. Further investigations are needed to determine the underlying mechanisms associated with the
changes in the outcome measures due to the vestibular rehabilitation program.
Conclusion. A 6-week vestibular rehabilitation program demonstrated both sta-
this article at:
ptjournal.apta.org
1166
f
Physical Therapy
tistically significant and clinically relevant change in fatigue, impaired balance, and
disability due to dizziness or disequilibrium in patients with MS.
Volume 91
Number 8
August 2011
Effects of Vestibular Rehabilitation on Multiple Sclerosis–Related Fatigue and Upright Postural Control
F
atigue and limited mobility are
among the most common symptoms in people with multiple
sclerosis (MS),1 with reports of
fatigue ranging from 50% to 85%.2,3
The definition of MS-related fatigue is
commonly understood as the selfreported perception of decreased
physical or mental energy, often
leading to limitations in daily activities or routines.4,5 Multiple sclerosis–
related fatigue is strongly linked to
impaired physical activity and quality of life.6,7
The cause of fatigue in people with
MS most likely is multifactorial,8
including both primary and secondary causes. Primary fatigue is
directly related to the disease process involving the neuromuscular
system in the form of demyelination
or axonal degeneration. Secondary
fatigue refers to fatigue indirectly
caused by factors such as depression, physical inactivity, or sleep
disorder.5
with resulting dizziness or vertigo.
Impaired upright postural control
has been linked to poor central sensory integration,30 –33 as well as
fatigue,34,35 in patients with MS.
The high prevalence of MS-related
lesions in the brain stem and cerebellum, ranging from 34.7% to
50.9%,36,37 supports the possibility of
impairments of central sensory processing, because the brain stem and
cerebellum are vital to this process.29,38 – 40 Rates of peripheral deficit vestibulopathy as high as 85% also
have been reported in patients with
MS,41 further illustrating the importance of the vestibular system for
central sensory integration in these
patients. Balance training for
patients with MS has been reported
to improve upright postural control,42,43 although the impact on
fatigue has not been tested.
Therefore, we postulated that vestibular rehabilitation would be an effective approach to the improvement of
both fatigue and upright postural
control in patients with MS. The purpose of this investigation was to
examine the effects of such a rehabilitation program on fatigue and
upright postural control in people
with MS. Specifically, we hypothesized that individuals who participate in the vestibular rehabilitation
intervention would have significantly reduced self-reported fatigue
and significantly improved upright
postural control compared with participants in a general exercise program (endurance and stretching program) and participants in a waitlisted control group (usual medical
care).
The Bottom Line
Effective treatment of MS-related
fatigue is limited. Drug therapies
have been tested, with conflicting
reports of efficacy.9,10 Studies of
energy conservation education have
had conflicting results.11,12 Exercise
studies have demonstrated benefits
in fitness level,13–15 quality of
life,13,15–17 balance,14 and walking
capacity13,14,16,18,19 in people with
MS; however, no consistent effect on
fatigue has been reported. Some
multifaceted rehabilitation studies
have shown improvements in
fatigue,17,20 –23 but others have
shown no effect.16
What do we already know about this topic?
One possible cause of fatigue worthy
of investigation is impairments of
central sensory integration. Central
sensory integration of the visual,
somatosensory, and vestibular systems is the basis for effective upright
postural control.24 –29 Impaired central sensory integration can lead to
reduced upright postural control,
If you’re a patient or caregiver, what might these
findings mean for you?
August 2011
People with multiple sclerosis (MS) have a multitude of symptoms.
Fatigue is the most common complaint, followed by impaired mobility.
Balance training is an effective treatment for patients with MS who have
impaired upright postural control (ie, balance); however, the evidence
for the effectiveness of interventions for MS-related fatigue is limited and
inconsistent. Previously, no studies have investigated the effectiveness
of a vestibular rehabilitation program on both MS-related fatigue and
balance.
What new information does this study offer?
This study provides early evidence of the feasibility and effectiveness of a
vestibular rehabilitation program on fatigue, balance, and disability due to
dizziness or disequilibrium for people with MS.
If you have MS and have fatigue and balance problems, participation in a
program of vestibular rehabilitation may improve fatigue and balance and
reduce disability related to dizziness or disequilibrium, with no known
side effects. Larger follow-up studies are needed, however, to support
these results.
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Week 1:
MFIS, DHI, BDI-II, SOT, 6MWT
Baseline Phase
(4 wk)
Week 2:
MFIS,* DHI,* BDI-II*
Week 4:
Stratified, Blocked
Randomized Allocation
Exercise Control Group
(60-min sessions, twice weekly)
Intervention: bicycle ergometry,
stretching, fatigue management
Week 6:
Week 6:
Week 6:
Week 8:
Week 8:
Week 8:
Week 10:
Week 10:
Week 10:
Week 12:
Week 12:
Week 12:
Week 14:
Week 14:
Week 14:
Follow-up Phase
(4 wk)
Intervention Phase
(6 wk)
Experimental Group
(60-min sessions, twice weekly)
Intervention: vestibular
rehabilitation, fatigue management
Wait-Listed
Control Group
(no intervention)
Figure 1.
Study design schematic. MFIS⫽Modified Fatigue Impact Scale, DHI⫽Dizziness Handicap Inventory, BDI-II⫽Beck Depression Inventory–II, SOT⫽Sensory Organization Test (posturography), 6MWT⫽Six-Minute Walk Test. Asterisk indicates measure administered via
telephone.
Method
Design Overview
The study was a 3-arm, 14-week,
single-blinded, stratified blocked randomized controlled trial. The study
consisted of 3 phases (Fig. 1). All
participants underwent 3 outcome
measurement sessions during a
4-week, nonintervention baseline
phase. They then were randomly
assigned to 1 of 3 study arms. There
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were 2 exercise arms (experimental
and exercise control) and a waitlisted control arm. Participants in
both exercise groups were treated
twice weekly for 6 weeks (intervention phase). All participants then
began a 4-week follow-up phase. Participants in the wait-listed control
group received treatment consistent
with the protocols of this study
within the clinical setting upon com-
Number 8
pletion of their participation in the
study (if they chose to receive the
treatment).
Setting and Participants
Most participants were recruited
through clinics at the Rocky Mountain MS Center (RMMSC) at the University of Colorado, Anschutz Medical Campus, Aurora, Colorado. In
addition, the RMMSC and the ColoAugust 2011
123 volunteers were
assessed for eligibility
85 volunteers were excluded
–25 were out of state
–5 were out of the metropolitan area
–47 did not meet inclusion criteria
–8 failed to follow-up for screening
38 participants underwent
randomized allocation
12 were assigned to the
experimental group
exercise control
group
wait-listed
control group
No loss to follow-up
No loss to follow-up
1 loss to follow-up
– Reason: immediately
following assignment
to wait-listed control
group, refused to
continue
12 were included in
intention-to-treat
analysis
13 were included in
intention-to-treat
analysis
13 were included in
intention-to-treat
analysis
Figure 2.
Prospective participant and study participant flow diagram.
rado Chapter of the National Multiple Sclerosis Society disseminated
information about the study. Over a
33-month period, 123 volunteers
were screened for study eligibility
(Fig. 2). Inclusion criteria were: 18 to
65 years of age; clinically definite MS;
able to walk 100 m with or without
August 2011
a single-sided device; a score of ⱖ45
out of 84 on the Modified Fatigue
Impact Scale questionnaire10; and a
composite score of ⬍72 on the computerized Sensory Organization Test
(SOT), demonstrating limited standing balance. Exclusion criteria were:
unable to walk; use of pharmacolog-
ical agents to control fatigue or that
caused fatigue; change in MS-specific
disease modification medication
within 3 months prior to the study;
documented MS-related relapse
within 6 months prior to the study;
other conditions that may cause
fatigue (including depressive and
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Physical Therapy f
1169
sleep disorders); impaired upright
postural control or limited participation in an exercise program; and participation in a vestibular or endurance exercise program within 8
weeks prior to the study.
experimental group and the exercise
control group were performed in the
same human performance laboratory, with each participant having
the same amount of supervision and
interaction with the investigator.
An SOT composite score of 7.0 as a
clinically meaningful difference
resulted in a sample size estimate of
30 to achieve 0.80 power at a significance level of .05. The 7.0-point
effect size was derived from a
previous investigation reporting a
6.7-point effect size indicated a tendency toward statistical significance.44 Oversampling was performed to account for possible
dropouts, resulting in 38 as the final
study size.
Individuals in the experimental
group participated in a standardized
vestibular rehabilitation program
consisting of upright postural control and eye movement exercises
(Appendix 1) based on clinical experience and published literature.45,46
Each item was performed for 1 to 2
minutes, for a total of 55 minutes.
Specific items were selected for a
daily independent home exercise
program (HEP), which was assigned
throughout the intervention and
follow-up phases (Appendix 1).
A physical therapist with 5 years of
experience evaluating patients with
neurological disorders, including
MS, performed all outcome measurements in an outpatient clinical setting and was blinded from group
assignments. An investigator with 12
years of experience as a physical
therapist treating patients with MS
implemented all exercise protocols
in a human performance laboratory
and was blinded from all outcome
measurements. All participants gave
written informed consent.
Randomization and
Interventions
Following the baseline phase, 2
strata were formed based on the
most recent magnetic resonance
imaging report: participants with
and without brain-stem or cerebellar
neurological involvement. Block
sizes of 3 were randomly selected for
each strata. A clinician not involved
in the study concealed the block
sequences and provided the random
group assignments. Participants then
were randomly allocated to 1 of 3
arms: an experimental group, an
exercise control group, or a waitlisted control group. All supervised
intervention sessions in both the
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The exercise control group participated in endurance and stretching
exercises. To account for a possible
abnormally low heart rate response
to exercise (blunted heart rate
response) frequently observed in
patients with MS, participants in the
exercise control group first performed a submaximal modified
YMCA cycle ergometry graded exercise test (GET) (Appendix 2).47 Peak
heart rate (HRpeak), which was the
highest value of heart rate at the time
of symptom-limiting GET termination, served as the value for endurance exercise intensity prescription.
The endurance exercise consisted of
stationary bicycling: 5-minute warmup, two 15-minute sessions; and 2- to
5-minute cool-down. The training
intensity during the 15-minute sessions was 65% to 75% of HRpeak; 11
to 14 (moderate intensity of exertion) on the Borg Rating of Perceived
Exertion (RPE) Scale, ranging from 6
(“no exertion at all”) to 20 (“maximal
exertion”); and constant pedal rate
of 50 rpm. The level of intensity and
duration of cycling were based on
the typical capacity of individuals
with MS and recommendations in
Number 8
the literature.47 The stretching exercises included stretches of the following muscles: gastrocnemiussoleus, quadriceps, hamstrings,
gluteus maximus, and iliopsoas and
rectus femoris. Stretches were held
for 30 seconds. A daily independent
HEP was assigned throughout the
intervention and follow-up phases.
The HEP included the stretching
exercises and stationary bicycling or
an alternative activity (eg, walking)
at levels consistent with the supervised training sessions.
Both exercise groups received the
same 5-minute fatigue management
education. Included were discussions of: daily rest intervals, selfmonitoring of exertion levels, work
station ergonomics, and heat intolerance education. A daily log was
issued to each individual in the exercise groups to record adherence to
the HEP and fatigue management
components.
Outcomes and Follow-up
Primary outcome measures. Selfreported fatigue was measured using
the 21-item Modified Fatigue Impact
Scale (MFIS). The MFIS is reported to
be a reliable and valid measure for
patients with MS.4 Responses are
scored from 0 to 4, with total scores
ranging from 0 to 84 and with higher
scores indicating a larger impact of
fatigue.
Static upright postural control was
measured using a posturography test
(ie, Sensory Organization Test
[SOT]), which has been used in prior
studies to illustrate balance disorders
in people with MS.30,31,42 The Smart
Balance Master System* was used for
this test. This test assesses upright
postural control during 6 different
conditions of sensory feedback. Postural sway is recorded and converted
* NeuroCom International Inc, 9570 SE Lawnfield Rd, Clackamas, OR 97015.
August 2011
to a percentage of equilibrium (composite score).
Walking capacity was measured
using the Six-Minute Walk Test
(6MWT), which has been used measure functional exercise capacity in
this population.48 Standard instructions and testing guidelines were
implemented.49 Distance (in feet)†
was recorded.
Secondary outcome measures.
Self-reported disability due to dizziness or disequilibrium was measured
using the 25-item Dizziness Handicap Inventory (DHI). Each item has 3
responses: “yes,” “sometimes,” and
“no.” Total scores range from 0 to
100, with higher scores indicating
greater disability due to dizziness or
disequilibrium. The DHI has high
reliability and discriminates “fallers”
from “nonfallers” in the MS
population.50
Self-reported depression was measured using the 21-item Beck Depression Inventory–II (BDI-II).51 Each
item has 4 responses, with the total
score ranging from 0 (“no depression”) to 63 (“greatest depression”).
The MFIS, DHI, and BDI-II were
administered 8 times throughout the
study, and the SOT and 6MWT were
administered 4 times (Fig. 1).
Data from the baseline phase were
averaged to provide a point estimate
for the 4 weeks prior to the intervention phase. Outcome measure analyses occurred at the end of the intervention phase (baseline to 10-week
follow-up) and at the end of the
follow-up phase (10-week follow-up
to 14-week follow-up).
Data Analysis
All outcome measures were analyzed
as continuous data. One-way analysis
of variance was used for multigroup
comparisons of preintervention and
†
1 ft⫽0.3048 m.
August 2011
postintervention data and of postintervention to end of follow-up data
for each outcome variable and for
multigroup comparisons of time
duration in the study. Prior to performing post hoc, pair-wise comparisons, a robust test of equality of
means (ie, the Welch statistic) was
performed to verify the valid application of a Bonferroni correction
method. Outcome measures that
underwent multigroup Bonferroni
correction met the statistical significance of equality of means (P⬍.05).
For within-group comparisons of
preintervention and postintervention data and of postintervention to
end of follow-up data, the paired t
test was used. For experimental
group and exercise control group
comparisons of adherence to the
HEP and fatigue management, the
independent t test was used. The
Fisher exact test was used for baseline analysis of nominal data.52 Correlational analyses were performed
to test the relationship between
mean changes in MFIS total score,
SOT composite score, and DHI total
score for the combined study sample
from baseline to the end of the intervention phase and from baseline to
the end of the follow-up phase. The
Pearson product moment correlation coefficient test was used for the
analysis of associations. All tests
were 2-tailed, using .05 as the level
of statistical significance. Standard
deviations and 95% confidence intervals (CIs) also were calculated. The
numeric difference in change of outcome measure between groups is
presented as effect size. Standardized difference of the mean (SDM)
was calculated based on Cohen d
standard effect size index: small
(SDM: ⱕ0.2), medium (SDM: ⬎0.2
but ⱕ0.7), and large (SDM: ⱖ0.8 to
2.0).53–55 Event rates for each group
and the subsequent number needed
to treat are presented for the primary
outcome measures of fatigue (MFIS
total score) and upright postural con-
trol (SOT composite score). A
change in the MFIS total score of
ⱖ15.010 and a change in the SOT
composite score of ⱖ7.044 were
used as the meaningful changes and
cutoff scores for event rate
calculations.
Intention-to-treat analysis was implemented to address any loss to followup. The average of the group change
for each outcome measure at each
analysis period served as the value
applied to data missing from loss to
follow-up. Unless otherwise stated,
statistical analyses were performed
using SPSS for Windows, version
17.0.‡
Role of the Funding Source
This study was partially supported
by the National Multiple Sclerosis
Society (NMSS) (Pilot Project no.
PP1501), which approved the design
of the study, but did not control the
conduct of the research team,
including recruitment, patient participation, data analyses, and manuscript preparation.
Results
Characteristics of the sample, including demographic data and baseline
data for the outcome measures, are
presented in Table 1. No differences
were found among the 3 groups.
Primary and Secondary
Outcomes (Baseline to 10 Weeks)
We first examined differences in the
primary and secondary outcomes following the 6-week intervention
phase (baseline to 10 weeks). These
data are depicted in Table 2.
Fatigue. As hypothesized, the
experimental group demonstrated
significant improvement in MFIS
total score (Tab. 2). Groups were
significantly different on MFIS total
score (P⫽.004), with the experimen‡
SPSS Inc, 233 S Wacker Dr, Chicago, IL
60606.
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Table 1.
Baseline Demographics and Characteristicsa
Experimental
Group
(nⴝ12)
Variable
Age (y)
46.8 (10.5)
Sex, female/male
9/3
MS diagnosis duration (y)
6.5 (5.6)
Exercise
Control Group
(nⴝ13)
42.6 (10.4)
11/2
5.1 (3.2)
Wait-Listed
Control Group
(nⴝ13)
P
50.2 (9.2)
.175b
11/2
.767c
9.1 (7.3)
.206b
1.00c
MS diagnosis subtype
Relapsing-remitting
Secondary progressive
11
11
12
1
2
1
1.00c
MS-related lesion location
Non-brain stem/cerebellar
4
4
4
Brain stem/cerebellar
8
9
9
51.0 (6.8)
51.0 (8.6)
55.9 (11.6)
1,335.6 (320.3)
1,066.1 (335.9)
MFIS total score
6MWT (ft)
1,049.2 (328.9)
.312b
.066b
SOT composite score (%)
60.2 (14.0)
50.3 (16.3)
59.5 (12.1)
.164b
BDI-II total score
16.5 (9.1)
17.3 (8.6)
18.5 (6.4)
.817b
DHI total score
48.0 (10.7)
47.0 (12.1)
56.4 (14.6)
.132b
a
Values expressed as means (SD), except for sex, MS diagnosis subtype, and MS-related lesion location, which are expressed as nominal counts.
MS⫽multiple sclerosis, MFIS⫽Modified Fatigue Impact Scale, 6MWT⫽Six-Minute Walk Test, SOT⫽Sensory Organization Test, BDI-II⫽Beck Depression
Inventory–II, DHI⫽Dizziness Handicap Inventory.
b
P values assessed by one-way analysis of variance.
c
P values assessed by Fisher exact test.
tal group’s improvement significantly greater than that of the exercise control group (P⫽.024) and the
wait-listed control group (P⫽.005).
No difference was found between
the exercise control group and the
wait-listed control group (P⫽1.00).
Large MFIS total score SDMs were
found for the experimental group
compared with the exercise control
group (d⫽1.06) and the wait-listed
control group (d⫽1.33), and the difference in MFIS total score SDMs
between the exercise control group
and the wait-listed control group was
minimal (d⫽0.24). Based on 67% of
the experimental group, 23% of the
exercise control group, and 15% of
the wait-listed control group improving on the MFIS by ⱖ15.0, the number needed to treat was 2.3 when
comparing the experimental group
with the exercise control group and
1.9 when comparing the experimental group with the control group.
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Upright postural control. As
hypothesized, the experimental
group improved significantly in the
SOT composite score (Tab. 2). There
was a significant difference among
the groups (P⬍.001). The experimental group showed significant
improvement compared with the
exercise control group (P⫽.001)
and the wait-listed control group
(P⫽.003). No difference was found
between the exercise control group
(P⫽1.00). Large SOT composite
score SDMs were found for the
experimental group compared with
the exercise control group (d⫽1.37)
(d⫽1.28), and the difference in SOT
composite score SDMs between the
exercise control group and the waitlisted control group was minimal
(d⫽0.21). Based on 92% of the
experimental group and 38% of both
the exercise control group and the
waited-listed control group improv-
Number 8
ing on the SOT by ⱖ7.0, the number
needed to treat was 1.9.
Self-reported disability due to
dizziness or disequilibrium. The
experimental group improved significantly in DHI total score, whereas
the other groups failed to improve
(Tab. 2). Groups were significantly
different (P⫽.005) at the end of the
intervention phase; the experimental group’s improvement was significant compared with that of the exercise control group (P⫽.018) and the
wait-listed control group (P⫽.009).
No difference was found between
the exercise control and wait-listed
control groups (P⫽1.00). Large DHI
total score SDMs were found for the
experimental group compared with
the exercise control group (d⫽1.03)
(d⫽1.12), and the difference in DHI
total score SDMs between the exercise control group and the wait-listed
August 2011
August 2011
P
Volume 91
P
Number 8
1,066.1 (335.9)
P
.092
.345
46.0 (168.7)
⫺56.0 to 148.0
85.1 (159.5)
⫺16.3 to 186.4
95% CI
1,112.1 (391.3)
Change in 6MWT
1,335.6 (320.3)
1,420.7 (283.6)
End of intervention phase
.415
Baseline
6MWT
.010
⫺2.2 (9.5)
⫺8.0 to 3.5
⫺31.9 to ⫺5.5
⫺18.7 (20.7)
95% CI
Change in DHI
44.8 (11.6)
48.0 (10.7)
29.3 (18.6)
47.0 (12.1)
.011
⬍.001
Baseline
DHI
5.2 (6.2)
1.4 to 8.9
18.5 (12.3)
Change in SOT
55.5 (14.9)
50.3 (16.3)
10.7 to 26.3
78.7 (6.0)
95% CI
60.2 (14.0)
.085
⬍.001
⫺6.7 (12.9)
⫺14.5 to 1.1
⫺21.5 (15.0)
⫺31.1 to ⫺11.9
Baseline
SOT
P
95% CI
Change in MFIS
44.3 (16.4)
51.0 (6.8)
29.5 (15.8)
51.0 (8.6)
Exercise Control
Group (nⴝ13)b
Baseline
MFIS
Outcome Measure
Experimental
Group
(nⴝ12)b
.378
⫺30.9 to 75.6
22.4 (88.1)
1,071.6 (375.0)
1,049.2 (328.9)
.821
⫺6.4 to 5.2
⫺0.6 (9.6)
55.8 (20.9)
56.4 (14.6)
.001
3.2 to 9.5
6.4 (5.2)
65.9 (14.5)
59.5 (12.1)
.255
⫺10.6 to 3.1
⫺3.8 (11.4)
52.1 (17.1)
55.9 (11.6)
Wait-Listed
Control
Group
(nⴝ13)b
1.00
⫺104.8 to 182.9
39.1
.018
2.3 to 30.6
16.5
.001
4.9 to 21.8
13.3
.024
1.6 to 28.0
14.8
Effect Sizec
0.24
1.03
1.37
1.06
Effect
Size
Index
(d)
Experimental Group
Compared With Exercise
Control Group
.842
⫺81.1 to 206.5
62.7
.009
3.9 to 32.2
18.1
.003
3.7 to 20.5
12.1
.005
4.5 to 30.9
17.7
Effect Sizec
0.49
1.12
1.28
1.33
Effect
Size
Index
(d)
Experimental Group
Compared With WaitListed Control Group
1.00
⫺117.3 to 164.5
23.6
1.00
⫺12.3 to 15.5
1.6
1.00
⫺7.0 to 9.5
⫺1.2
1.00
⫺10.0 to 15.9
2.9
Effect Sizec
(Continued)
0.18
0.17
⫺0.21
0.24
Effect
Size
Index
(d)
Fatigue, Upright Postural Control, Disability Due to Dizziness or Disequilibrium, Walking Capacity, and Depression: Baseline to End of Intervention Phase (10 Weeks)a
Table 2.
Physical Therapy f
1173
.431
.101
.003
.001
P
a
Baseline, end of intervention phase, and change in outcome measure values expressed as mean (SD), 95% CI⫽95% confidence interval. Effect size⫽numeric difference in change of outcome measure
among groups. Effect size index (d)⫽Cohen d standard effect size index. MFIS⫽Modified Fatigue Impact Scale total score; SOT⫽Sensory Organization Test, composite score (percentage); DHI⫽Dizziness
Handicap Inventory total score; 6MWT⫽Six-Minute Walk Test score (feet); BDI-II⫽Beck Depression Inventory–II total score.
b
Within-group comparison of change in outcome measure (paired t test).
c
Between-group comparison of change in outcome measure (post hoc pair-wise comparisons following one-way analysis of variance).
1.00
.307
0.6
⫺6.8 to 7.8
0.60
5.0
0.70
⫺3.0 to 11.9
4.4
⫺4.5 (9.2)
⫺10.1 to 1.1
⫺5.1 (4.9)
⫺8.0 to ⫺2.1
⫺9.5 (7.4)
⫺14.2 to ⫺4.8
14.0 (9.0)
12.2 (6.5)
Change in BDI-II
18.5 (6.4)
17.3 (8.6)
16.5 (9.1)
7.0 (7.3)
Baseline
BDI-II
95% CI
Effect Sizec
Exercise Control
Group (nⴝ13)b
Physical Therapy
Outcome Measure
Experimental
Group
(nⴝ12)b
f
Continued
Table 2.
1174
⫺2.5 to 12.4
Effect Sizec
Effect Sizec
0.08
Effect
Size
Index
(d)
Effect
Size
Index
(d)
Effect
Size
Index
(d)
Wait-Listed
Control
Group
(nⴝ13)b
Experimental Group
Control Group
Experimental Group
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Number 8
control group
(d⫽0.17).
was
negligible
Depression. Table 2 illustrates
that depression, based on the BDI-II
scores, improved significantly in the
experimental group and the exercise
control group, but not in the waitlisted control group. However,
changes were not considerably different among the groups (P⫽.202).
Walking capacity. Walking capacity, as measured by the 6MWT,
improved in all groups (Tab. 2); however, within-group changes were neither significant nor different among
the groups (P⫽.549).
Primary and Secondary
Outcomes (10 Weeks to
14 Weeks)
We next examined the results of the
4-week follow-up phase. Table 3
presents group changes for the MFIS,
SOT, DHI, and 6MWT for the
follow-up period between week 10
and week 14. Within-group changes
were insignificant, with the exception of the BDI-II. The wait-listed
control group increased in depression (X⫽2.6, SD⫽3.2; P⫽.011);
however, changes in BDI-II scores
were not significantly different
among the groups (P⫽.309).
Ancillary Analyses
Relationship of the changes in
outcome measures. We next
tested for relationships between
changes in the primary outcome
measures of fatigue and upright postural control and the main secondary
outcome measure of disability due to
dizziness or disequilibrium. A correlational analysis was performed on
the total study sample (N⫽38) to
compare the changes from baseline
to the end of the intervention phase
and from baseline to the follow-up
phase.
The MFIS total score mean change
had a significant inverse relationship
August 2011
August 2011
.880
.867
.280
⫺0.4 (3.9)
⫺2.8 to 2.1
.770
Change in SOT
95% CI
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Number 8
.509
⫺24.6 (112.1)
⫺95.8 to 46.7
Change in 6MWT
95% CI
.463
⫺58.2 (308.5)
⫺244.7 to 128.2
1,396.1 (330.5)
P
1,053.9 (448.7)
1,420.7 (283.6)
End of follow-up phase
1,112.1 (391.3)
.590
.507
.348
⫺47.8 to 125.7
38.9 (143.6)
1,110.5 (284.0)
1,071.6 (375.0)
.144
⫺0.7 to 4.1
1.7 (3.9)
⫺1.3 (8.0)
⫺6.1 to 3.6
3.5 (17.7)
6MWT
P
95% CI
57.5 (19.9)
55.8 (20.9)
.524
⫺2.3 to 4.3
1.0 (5.5)
66.9 (14.3)
65.9 (14.5)
.819
⫺3.8 to 4.8
0.5 (7.1)
52.6 (17.4)
52.1 (17.1)
43.5 (14.5)
⫺7.7 to 14.7
32.8 (24.5)
Change in DHI
29.3 (18.6)
DHI
44.8 (11.6)
2.3 (7.4)
⫺2.1 to 6.8
78.3 (4.9)
P
57.8 (16.5)
78.7 (6.0)
55.5 (14.9)
0.4 (9.0)
⫺5.0 to 5.8
0.8 (15.1)
SOT
P
95% CI
44.7 (16.3)
44.3 (16.4)
Exercise
Control Group
(nⴝ13)b
⫺8.9 to 10.4
30.3 (20.8)
Change in MFIS
29.5 (15.8)
MFIS
Outcome Measure
Experimental
Group
(nⴝ12)b
Wait-Listed
Control
Group
(nⴝ13)b
1.00
⫺176.7 to 244.0
33.6
.895
⫺16.0 to 6.5
⫺4.8
.787
⫺8.5 to 3.2
⫺2.7
1.00
⫺11.3 to 10.5
⫺0.4
Effect Sizec
0.14
⫺0.35
⫺0.46
⫺0.03
Effect Size
Index (d)
Experimental Group
Control Group
1.00
⫺273.8 to 146.8
⫺63.5
1.00
⫺13.1 to 9.5
⫺1.8
1.00
⫺7.2 to 4.5
⫺1.4
1.00
⫺11.3 to 10.5
⫺0.3
Effect Sizec
⫺0.49
⫺0.14
⫺0.29
⫺0.03
Effect Size
Index (d)
Experimental Group
Compared With Wait-Listed
Control Group
.731
⫺303.2 to 108.9
⫺97.1
1.00
⫺8.1 to 14.0
3.0
1.00
⫺4.4 to 7.0
1.3
1.00
⫺10.6 to 10.7
0.1
Effect Sizec
(Continued)
⫺0.40
0.48
0.20
0.01
Effect Size
Index (d)
Control Group
Fatigue, Upright Postural Control, Disability Due to Dizziness or Disequilibrium, Walking Capacity, and Depression: End of Intervention Phase (10 Weeks) to End of
Follow-up Phase (14 Weeks)a
Table 3.
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⫺0.27
⫺2.0
Physical Therapy
⫺4.2 to 8.1
1.00
1.00
⫺10.2 to 2.4
.385
.011
.477
.141
0.7 to 4.5
⫺1.4 to 2.8
⫺1.8 to 11.0
a
95% CI
P
16.6 (9.6)
⫺3.9
0.7 (3.4)
12.9 (8.0)
11.6 (12.3)
4.6 (10.0)
Change in BDI-II
14.0 (9.0)
12.2 (6.5)
7.0 (7.3)
Outcome Measure
BDI-II
Experimental
Group
(nⴝ12)b
2.6 (3.2)
⫺0.52
⫺8.3 to 4.3
1.9
Effect Sizec
Effect Size
Index (d)
Effect Sizec
Wait-Listed
Control
Group
(nⴝ13)b
Exercise
Control Group
(nⴝ13)b
f
Continued
Table 3.
1176
End of intervention phase, end of follow-up phase, and change in outcome measure values expressed as mean (SD), 95% CI⫽95% confidence interval. Effect size⫽numeric difference in change of
outcome measure between groups. Effect size index (d)⫽Cohen d standard effect size index. MFIS⫽Modified Fatigue Impact Scale total score; SOT⫽Sensory Organization Test, composite score
(percentage); DHI⫽Dizziness Handicap Inventory total score; 6MWT⫽Six-Minute Walk Test score (feet); BDI-II⫽Beck Depression Inventory–II total score.
b
Within-group comparison of change in outcome measure (paired t test).
c
Between-group comparison of change in outcome measure (post hoc pair-wise comparisons following one-way analysis of variance).
Effect Size
Index (d)
Effect Size
Index (d)
Effect Sizec
0.58
Control Group
Experimental Group
Control Group
Experimental Group
Control Group
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to SOT composite score mean
change at the end of the intervention
phase (r⫽⫺.41, P⫽.011) and the
end of the follow-up phase (r⫽⫺.56,
P⬍.001). Additionally, the MFIS total
score mean change had a significant
direct relationship to DHI total score
mean change at the end of the intervention phase (r⫽.67, P⬍.001) and
at the end of the follow-up phase
(r⫽.76, P⬍.001). Lastly, the DHI
total score mean change had a significant inverse correlation to SOT composite score mean change at the end
of the intervention phase (r⫽⫺.51,
P⫽.001) and at the end of the
follow-up phase (r⫽⫺.38, P⫽.020).
Group equality following randomized allocation. We also
examined the length of time in the
study for each group and adherence
to the HEP and fatigue management
by the experimental and exercise
control groups. The experimental
group’s duration in the study (ie,
16.3 weeks) was not significantly different from that of the other groups;
however, the exercise control
group’s duration in the study (ie,
17.5 weeks) was different from that
of the wisting-list control group (ie,
15.3 weeks) (95% CI⫽0.2 to 4.2,
P⫽.025).
Each of the exercise groups had 4
participants who did not return their
daily log. Of the remaining participants, those in the experimental
group had greater adherence to their
HEP compared with those in the
exercise control group (average of
60.5 and 42.7 days, respectively)
(95% CI⫽4.5 to 31.2, P⫽.012). The
difference in adherence to fatigue
management was negligible: 34.3
days in the experimental group and
25.9 days in the exercise control
group (95% CI⫽⫺8.9 to 25.6,
P⫽.319).
Adverse Events
One participant in the exercise control group incurred a minor ankle
August 2011
sprain during a session. This incident
did not require medical care and did
not limit continued participation.
After being randomly allocated to
the wait-listed control group, one
individual dropped out of the study
due to unhappiness with group
assignment.
Discussion
Findings from this study demonstrate the feasibility of a vestibular
rehabilitation program and its effectiveness on fatigue (MFIS total
score), upright postural control
(SOT composite score), and disability due to dizziness or disequilibrium
(DHI total score). The improvements
found were significantly greater for
participants in the experimental
group (who underwent a vestibular
rehabilitation program) than for participants in either the exercise control
group (who underwent an endurance
and stretching program) or the waitlisted control group.
The main variable of interest was
fatigue, with the results showing that
the experimental group was the only
group to improve. The improvement
of ⫺21.5 points (P⬍.001) in MFIS
total score was significant and
exceeded previous reports from multifaceted
rehabilitation
studies:
12-week program (⫺13.0 points,
P⫽.02),21 4-week program (⫺15.5
points, P⫽.001),22 and 8-week program (⫺4.0 points, P⫽.64).14 In contrast, the changes in MFIS total
scores for both the exercise control
group and the wait-listed control
group were minimal and statistically
similar. The large effect sizes found
for the experimental group met the
clinically relevant difference of 15.0
points.10 The limited improvement
in fatigue found for the exercise control group is comparable to previous
findings of several studies that investigated the possible effect of aerobic
training on fatigue.13–15,56
August 2011
The second variable of interest was
upright postural control. Changes in
SOT composite scores for the exercise control group and the wait-listed
control group were minimal and statistically similar. These changes are
consistent with known learning
effect found in a population of
healthy individuals; an improvement
of 8.0 indicates a true treatment
effect.57 In the current study, 2 baseline measurements were conducted
to account for learning effect. The
experimental group demonstrated a
significant improvement in SOT
composite score of 18.5 (P⬍.001),
which is greater than the score of
14.8 (P⫽.001) reported by Badke
et al,58 who investigated the implementation of a vestibular and
balance-related rehabilitation program involving a “mixed and central
vestibular dysfunction” group. More
importantly,
the
experimental
group’s improvement was significantly greater compared with that of
the exercise control and waiting-list
control groups.
The third major finding of this study
was that the experimental group was
the only group to improve significantly in disability due to dizziness
or disequilibrium, with large effect
sizes. The improvement in DHI total
score of ⫺18.7 points (P⫽.010) is
greater than the improvement of
⫺14.3 points (P⫽.02) reported by
Badke et al.58
This study was not designed to test
the underlying reasons for the
improvements in fatigue, upright
postural control, and disability due
to dizziness or disequilibrium. However, the conceptual framework that
led to our investigation may provide
insight into the theoretical reasoning. The balance training portion of
the vestibular rehabilitation program
can be seen as an attempt to condition the central nervous system to
provide efficient upright postural
control while performing tasks in
standing and walking.
Moderate to strong associations
were found among the changes in
fatigue, upright postural control, and
disability due to dizziness or disequilibrium. Because both postural control and dizziness reflect central
processing, these correlations lend
further support to the proposition
that impairments of central sensory
processing contribute to fatigue in
people with MS. Furthermore, these
findings suggest that changes in one
of these variables could potentially
have a coupled reaction in one or
both of the other variables.
Demyelination and axonal degeneration found in patients with MS often
result in impaired motor control,59
with evidence of partial spontaneous
neural repair, including axonal and
dendritic collateral sprouting.60,61
This neural plasticity has been
shown to be enhanced in patients
with MS following task-specific rehabilitation training.62– 65 With this
knowledge, it can be theorized that
vestibular rehabilitation provides the
necessary task-specific stimuli for
neural reorganization, fostering central sensory integration and resulting
in improved upright postural
control.
Ocular motor training, in the form of
eye movement exercises, plays a key
role in neuromuscular reorganization.66 Abnormal eye movements are
strongly associated with advanced
disability in patients with MS.67– 69
Because visual feedback plays a key
role in coordinated limb movement,70 it is possible the eye movement exercises included in the vestibular
rehabilitation
program
contributed to the improved postural control found in the experimental group.
Peripheral physiological changes
also may be involved, including
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1177
improved muscle endurance due to
repetitive
balance
training.
Improved muscular function may
assist in lessening the negative
effects of motor fatigue on anticipatory postural adjustments.71
Because of impaired central sensory
processing mechanisms, people
with MS may require increased conscious or mental attention while performing daily upright tasks. This
increase in attention could be an
important reason for elevated perception of fatigue in these individuals. This concept is supported by Filippi et al,72 who found that patients
with MS who reported greater levels
of fatigue had elevated brain activity
in the areas devoted to attentional
tasks and lower activity in the motor
planning and execution regions.
Taken together, findings from this
investigation support the theory that
fatigue in patients with MS is linked
to impairments of central sensory
integration. Specifically, an intervention program, based on principles of
rehabilitation for individuals with
vestibular dysfunction and impaired
sensorimotor integration, improved
upright postural control and fatigue.
We also measured depression and
walking capacity, both of which
changed marginally. Depression in
patients with MS has been found to
be associated with fatigue,73 with a
recent investigation showing a
weaker relationship.74 We found
that both exercise groups improved
in self-reported depression; however, the change was not significantly different between the groups.
The lack of significant change in
depression following exercise performance is comparable to previous
reports.75 Additionally, it should be
noted that severe depression was an
exclusion criterion, potentially attenuating our findings.
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At baseline, the experimental group
appeared to have had a greater walking capacity, based on the 6MWT
scores, compared with the exercise
control and wait-listed control
groups; however, these differences
were not significant and were comparable to the range reported previously in people with MS (670 –1,978
ft).76 –78 The 85.1-foot improvement
on the 6MWT by the experimental
group is greater than that reported
by Rampello and colleagues14 (32.8
ft, P⫽.17) following an 8-week “neurological rehabilitation” program;
however, this improvement also was
found to be insignificant (P⫽.092).
Considering this information and
the significant findings for fatigue,
upright postural control, and disability due to dizziness or disequilibrium
in our study, the 6MWT may not be
appropriate for detecting dynamic
upright postural control changes in
this population and more specifically
for this exercise-based investigation.
Changes between the 10-week and
14-week periods (Tab. 3) suggest
that the outcome measure scores
remained stable for 4 weeks following the intervention phase; however,
a larger-scale study with a longer
follow-up is needed to improve the
validity of concluding long-term benefit retention.
Lastly, it should be noted that the 2
training groups were different with
respect to duration of time in the
study and adherence to HEP and
fatigue management. However, the
differences were not statistically significant, nor were they sufficiently
large to be confounding from a clinical perspective.
Limitations should be acknowledged. The sample size was too small
to permit comparisons between
patients with and without brain-stem
and cerebellar lesions. Additionally,
smaller samples have large variance,
although in our study the clinical dif-
Number 8
ferences were sufficient that the variances were not a problem for the
major outcomes.
We chose to include the same
fatigue management education in
the exercise groups in order to avoid
unequal attention to discussions of
the typical approach to management
of MS-related fatigue. The fact that
the exercise control group’s change
in all outcome measures was statistically similar compared with the waitlisted control group and that
reported adherence to fatigue management was similar between the
experimental and exercise control
groups illustrates that the education
approach in this study was not effective; providing further support for
the isolated effects of vestibular rehabilitation found in the experimental
group.
Based on the findings from this investigation, several issues should be
examined in future studies. Specifically, these findings should be replicated in a larger sample with comparisons between individuals who
have brain-stem and cerebellar lesions
and those without these lesions. Furthermore, analyses should examine
other factors that predict which
other patients are most likely to
respond to such an intervention.
Finally, more-specific measures of
vestibular and eye movement functions, such as video-oculography,79
should be included in order to investigate underlying mechanisms.
Conclusion
Findings from this study provide
strong evidence supporting the
effectiveness of vestibular rehabilitation for the treatment of people with
MS who have deficits of fatigue and
upright postural control. The large
treatment effects occurred after a
relatively short intervention period,
and changes after 4 weeks of supervised intervention were small, suggesting that vestibular rehabilitation
August 2011
is a viable treatment option for
patients with MS who experience
fatigue and impaired upright postural control.
Dr Hebert, Dr Corboy, and Dr Schenkman
provided concept/idea/research design,
project management, and fund procurement. All authors provided writing. Dr
Hebert and Dr Manago provided data collection and data analysis. Dr Corboy provided participants. Dr Schenkman provided
facilities/equipment. Dr Corboy and Dr
Schenkman provided institutional liaisons.
Dr Manago provided clerical support. Dr
Corboy and Dr Manago provided consultation (including review of manuscript before
submission). The authors thank the Rocky
Mountain MS Center, Anschutz Medical
Campus, Aurora, Colorado, and the Colorado Chapter of the National Multiple Sclerosis Society for assistance in recruitment for
this study.
A Colorado Multiple Institutional Review
Board approved this study.
This study was partially supported by the
National Multiple Sclerosis Society, Pilot
Project no. PP1501.
Trial registration: ClinicalTrials.gov Identifier:
NCT01216137.
DOI: 10.2522/ptj.20100399
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Work Res. 2007;31:243–248. Available at:
http://findarticles.com/p/articles/mi_
hb6481/is_4_31/ai_n29405442/?tag⫽
content;col1. Accessed April 2009.
55 University of Colorado at Colorado
Springs, Psychology Department. Effect
size calculators. Available at: http://www.
uccs.edu/⬃faculty/lbecker/.
Accessed
June 11, 2010.
56 Schulz KH, Gold SM, Witte J, et al. Impact
of aerobic training on immune-endocrine
parameters, neurotrophic factors, quality
of life and coordinative function in multiple sclerosis. J Neurol Sci. 2004;225:11–
18.
57 Wrisley DM, Stephens MJ, Mosley S, et al.
Learning effects of repetitive administrations of the sensory organization test in
healthy young adults. Arch Phys Med
Rehabil. 2007;88:1049 –1054.
58 Badke MB, Miedaner JA, Shea TA, et al.
Effects of vestibular and balance rehabilitation on sensory organization and dizziness handicap. Ann Otol Rhinol Laryngol.
2005;114(1 pt 1):48 –54.
59 Dobkin BH. Neurobiology of rehabilitation. Ann N Y Acad Sci. 2004;1038:148 –
170.
60 De Stefano N, Matthews PM, Narayanan S,
et al. Axonal dysfunction and disability in a
relapse of multiple sclerosis: longitudinal
study of a patient. Neurology. 1997;49:
1138 –1141.
61 De Stefano N, Matthews PM, Fu L, et al.
Axonal damage correlates with disability
in patients with relapsing-remitting multiple sclerosis: results of a longitudinal magnetic resonance spectroscopy study.
Brain. 1998;121(pt 8):1469 –1477.
62 Mark VW, Taub E, Bashir K, et al.
Constraint-induced movement therapy
can improve hemiparetic progressive multiple sclerosis: preliminary findings. Mult
Scler. 2008;14:992–994.
63 Morgen K, Kadom N, Sawaki L, et al.
Training-dependent plasticity in patients
with multiple sclerosis. Brain. 2004;
127(pt 11):2506 –2517.
64 Saini S, De Stefano N, Smith S, et al.
Altered cerebellar functional connectivity
mediates potential adaptive plasticity in
patients with multiple sclerosis. J Neurol
Neurosurg Psychiatry. 2004;75:840 – 846.
65 Wegner C, Filippi M, Korteweg T, et al.
Relating functional changes during hand
movement to clinical parameters in
patients with multiple sclerosis in a multicentre fMRI study. Eur J Neurol. 2008;15:
113–122.
66 Schor CM. Neuromuscular plasticity and
rehabilitation of the ocular near response.
Optom Vis Sci. 2009;86:E788 –E802.
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67 Niestroy A, Rucker JC, Leigh RJ. Neuroophthalmologic aspects of multiple sclerosis: using eye movements as a clinical and
experimental tool. Clin Ophthalmol.
2007;1:267–272.
68 Downey DL, Stahl JS, Bhidayasiri R, et al.
Saccadic and vestibular abnormalities in
multiple sclerosis: sensitive clinical signs
of brainstem and cerebellar involvement.
Ann N Y Acad Sci. 2002;956:438 – 440.
69 Derwenskus J, Rucker JC, Serra A, et al.
Abnormal eye movements predict disability in MS: two-year follow-up. Ann N Y
Acad Sci. 2005;1039:521–523.
70 Lawrence GP, Khan MA, Buckolz E, Oldham AR. The contribution of peripheral
and central vision in the control of movement amplitude. Hum Mov Sci. 2006;25:
326 –338.
71 Mello RG, Oliveira LF, Nadal J. Anticipation mechanism in body sway control and
effect of muscle fatigue. J Electromyogr
Kinesiol. 2007;17:739 –746.
72 Filippi M, Rocca MA, Colombo B, et al.
Functional magnetic resonance imaging
correlates of fatigue in multiple sclerosis.
Neuroimage. 2002;15:559 –567.
73 Penner IK, Bechtel N, Raselli C, et al.
Fatigue in multiple sclerosis: relation to
depression, physical impairment, personality and action control. Mult Scler. 2007;
13:1161–1167.
74 Mills RJ, Young CA. The relationship
between fatigue and other clinical features
of multiple sclerosis. Mult Scler. 2010
December 6 [Epub ahead of print].
75 Sabapathy NM, Minahan CL, Turner GT,
Broadley SA. Comparing endurance-and
resistive-exercise training in people with
multiple sclerosis. Clin Rehabil. 2011;25:
14 –24.
76 Kileff J, Ashburn A. A pilot study of the
effect of aerobic exercise on people with
moderate disability multiple sclerosis. Clin
Rehabil. 2005;19:165–169.
77 Savci S, Inal-Ince D, Arikan H, et al. Sixminute walk distance as a measure of functional exercise capacity in multiple sclerosis. Disabil Rehabil. 2005;27:1365–1371.
78 Goldman MD, Marrie RA, Cohen JA. Evaluation of the six-minute walk test in multiple sclerosis subjects and healthy controls. Mult Scler. 2008;14:383–390.
79 Wuyts FL, Furman J, Vanspauwen R, Van
de Heyning P. Vestibular function testing.
Curr Opin Neurol. 2007;20:19 –24.
August 2011
Appendix 1.
Vestibular Rehabilitation Protocol: Tasks Performed in Sequential Order 1 to 26a
Upright Postural Control
A. Static Body Position: Standing
Eyes Open
1. BOS: firm surface— heels and toes together*
2. BOS: firm surface—partial heel to toes*
3. BOS: firm surface—full heel to toes (tandem)*
Perform 1–3 with:
— Ball catching and tossing (from and to investigator)
— Head movement: rotate side to side*
— Head movement: head up (neck extension) and down (neck flexion)*
Eyes Closed
4. BOS: firm surface—shoulder width apart*
5. BOS: firm surface— heels and toes together*
6. BOS: firm surface—partial heel to toes*
7. BOS: firm surface—full heel to toes (tandem)*
Eyes Open
8. BOS: foam cushion— heels and toes together*
9. BOS: foam cushion—partial heel to toes*
10. BOS: foam cushion—full heel to toes (tandem)*
Perform 8 –10 with:
— Ball catching and tossing (from and to investigator)
— Head movement: rotate side to side*
— Head movement: head up (neck extension) and down (neck flexion)*
Eyes Closed
11. BOS: foam cushion—shoulder width apart*
12. BOS: foam cushion— heels and toes together*
13. BOS: foam cushion—partial heel to toes*
14. BOS: foam cushion—full heel to toes (tandem)*
Eyes Open
15. BOS: tiltboard
Perform 15 with:
— Side-to-side
Frontal plane of motion, rock tiltboard in plane of motion and stabilize tiltboard in neutral plane of motion
position
— Head rotated side to side
Right rotation when tiltboard rocked to right, left rotation when tiltboard rocked to left
— Forward and backward
Sagittal plane of motion, rock tiltboard in plane of motion and stabilize tiltboard in neutral plane of motion
position
— Head movement: head up (neck extension) and down (neck flexion)
Neck extension when tiltboard rocked backward, head flexion when rocked forward
B. Static Body Position: Half-Kneeling
Eyes Open
16. BOS: half-kneeling
Perform 16 with:
— Bilateral arm flexion (both arms lifted above head at same time)*
— Alternate arm flexion/extension (one arm lifted above head, other arm moved backward), with trunk rotation*
(Continued)
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Appendix 1.
Continued
C. Static Body Position: Standing
Eyes Open
17. BOS: trampoline—shoulder width apart
Perform 17 with:
— Head movement: rotate side to side
— Marching in place combined with turning body 360° right and left
18. BOS: trampoline— heels and toes together
19. BOS: trampoline—partial heel to toes
20. BOS: trampoline—full heel to toes (tandem)
Perform 18 –20 with:
— Head movement: rotate side to side
Eyes Closed
21. BOS: trampoline—shoulder width apart
22. BOS: trampoline— heels and toes together
Perform 22 with:
— Short squats: 5 repetitions
23. BOS: trampoline—partial heel to toes
24. BOS: trampoline—full heel to toes (tandem)
D. Dynamic Body Motion: Walking
25. Walking
— Heel-toe walking forward and back with and without head movements*
— Walking tossing ball side to side and up and down while visually tracking ball
— On-command walking with 180° change in direction, stop-start, and transition into and out of standing on
one leg
Eye Movement Training
26. Eye movements
— Saccades
Perform with: quick eye movement between 2 stationary objects in horizontal, vertical, and 2-direction
diagonals*
— Smooth pursuit
Perform with: visually tracking a moving object in horizontal, vertical, and 2-direction diagonals*
— Vestibular ocular reflex
Perform with: visually fixating on immovable object while turning head side to side and up and down*
a
BOS⫽base of support. Asterisk indicates item included in home exercise program.
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Appendix 2.
Submaximal Graded Exercise Test (GET) Protocola
Equipment/Instruments:
— Bicycle ergometer
— Borg Rating of Perceived Exertion (RPE) Scale (6 –20)
— Heart rate monitor
— Stethoscope and blood pressure cuff
Pretest measurements:
— Heart rate
— Borg RPE Scale rating
— Blood pressure
Stages:
Initial stage
— 2- to 3-minute warm-up
— Pedal rate of 50 rpm
— Workload of approximately 25 W (1 lb [0.5 kg])
— Heart rate continuously monitored
— Blood pressure at end of stage
Incremental stages (2 minutes each)
— Pedal rate maintained at 50 rpm
— Incremental workload increases of approximately 12.5 W (0.5 lb
[0.25 kg]) per stage
— Heart rate continuously monitored
— Blood pressure recorded at the end of each stage
— Borg RPE Scale rating at the end of the last minute of each stage
Test termination:
— Patient reports unable to continue due to exertion or fatigue symptoms,
serving as the symptom-limiting endpoint for the submaximal GET
— Record: Borg RPE Scale rating and peak heart rate
a
Protocol derived from: White LJ, Dressendorfer RH. Exercise and multiple sclerosis. Sports
Med. 2004;34:1077–1100.
August 2011
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Research Report
Electromyographic Activity of the
Cervical Flexor Muscles in Patients
With Temporomandibular Disorders
While Performing the Craniocervical
Flexion Test: A Cross-Sectional Study
Susan Armijo-Olivo, Rony Silvestre, Jorge Fuentes, Bruno R. da Costa,
Inae C. Gadotti, Sharon Warren, Paul W. Major, Norman M.R. Thie,
David J. Magee
S. Armijo-Olivo, BScPT, MSc, PhD,
Department of Physical Therapy,
Faculty of Rehabilitation Medicine,
and Alberta Research Centre for
Health Evidence, Faculty of Medicine and Dentistry, University of
Alberta, Edmonton, Alberta, Canada. Mailing address: Department
of Physical Therapy, Rehabilitation
Research Centre, Faculty of Rehabilitation Medicine, University of
Alberta, 3–50 Corbett Hall, Edmonton, Alberta, Canada T6G 2G4.
Address all correspondence to Dr
Armijo-Olivo at: [email protected] or
[email protected].
R. Silvestre, BScPT, MSc, Research
Center of Human Movement,
Mayor University, Santiago, Chile.
J. Fuentes, BSc, MScRS, Rehabilitation Research Centre, Faculty of
Rehabilitation Medicine, University of Alberta, and Department of
Physical Therapy, Catholic University of Maule, Talca, Chile.
B.R. da Costa, BScPT, MSc, Institute
of Social & Preventive Medicine,
University of Bern, Bern, Switzerland.
I.C. Gadotti, BScPT, MScPT, PhD,
College of Nursing and Health Sciences, Florida International University, Miami, Florida.
S. Warren, PhD, Faculty of Rehabilitation Medicine, University of
Alberta.
Author information continues on
next page.
Background. Most patients with temporomandibular disorders (TMD) have been
shown to have cervical spine dysfunction. However, this cervical dysfunction has
been evaluated only qualitatively through a general clinical examination of the
cervical spine.
Purpose. The purpose of this study was to determine whether patients with TMD
had increased activity of the superficial cervical muscles when performing the
craniocervical flexion test (CCFT) compared with a control group of individuals who
were healthy.
Design. A cross-sectional study was conducted.
Methods. One hundred fifty individuals participated in this study: 47 were
healthy, 54 had myogenous TMD, and 49 had mixed TMD. All participants performed
the CCFT. Data for electromyographic activity of the sternocleidomastoid (SCM) and
anterior scalene (AS) muscles were collected during the CCFT for all participants. A
3-way mixed-design analysis of variance for repeated measures was used to evaluate
the differences in EMG activity for selected muscles while performing the CCFT
under 5 incremental levels. Effect size values were calculated to evaluate the clinical
relevance of the results.
Results. Although there were no statistically significant differences in electromyographic activity in the SCM or AS muscles during the CCFT in patients with mixed and
myogenous TMD compared with the control group, those with TMD tended to have
increased activity of the superficial cervical muscles.
Limitations. The results obtained in this research are applicable for the group of
individuals who participated in this study under the protocols used. They could
potentially be applied to people with TMD having characteristics similar to those of
the participants of this study.
Conclusion. This information may give clinicians insight into the importance of
evaluation and possible treatment of the deep neck flexors in patients with TMD.
However, future research should test the effectiveness of this type of program
through a randomized controlled trial in people with TMD in order to determine the
real value of treating this type of impairment in this population.
this article at:
ptjournal.apta.org
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August 2011
Cervical Flexor Activity and Temporomandibular Disorders
P.W. Major, DDS, MSc, FRCD(c), School of
Dentistry, University of Alberta.
N.M.R. Thie, BSc, MSc, DDS, TMD/Orofacial
Pain Graduate Program, School of Dentistry,
University of Alberta.
D.J. Magee, PhD, Department of Physical
Therapy, Faculty of Rehabilitation Medicine,
University of Alberta.
[Armijo-Olivo S, Silvestre R, Fuentes J, et al.
Electromyographic activity of the cervical
flexor muscles in patients with temporomandibular disorders while performing the
craniocervical flexion test: a cross-sectional
study. Phys Ther. 2011;91:1184 –1197.]
© 2011 American Physical Therapy Association
Published Ahead of Print: June 9, 2011
Accepted: April 8, 2011
Submitted: July 14, 2010
T
emporomandibular disorders
(TMD) are the most prevalent
category of nondental chronic
pain conditions in the orofacial
region. These disorders are characterized by pain affecting the masticatory muscles, the temporomandibular joint (TMJ), and related
structures.1 Temporomandibular disorders interfere with daily activities
and can significantly affect quality of
life, diminishing patients’ capacity
for work and ability to interact with
their social environment.2 It has
been calculated that approximately
$2 billion has been spent in the
United States due to TMD direct
care.3 Patients with TMD have
shown high levels of unemployment
and decreased work effectiveness.4
In a large, population-based, crosssectional study, it was shown that
TMD chronic pain had an individual
impact and burden similar to that of
back pain, severe headache, and
chest and abdominal pain.5
In a recent study,6 women comprised more than 70% of the patients
having TMD, and the ratio between
women and men was 2.4:1 for
arthralgia, 2.5:1 for osteoarthritis,
3.4:1 for myofascial pain, and 5.1:1
for TMJ disk displacement.6 The literature supports the fact that
women are more sensitive to pain
conditions, reporting more severe
pain, more frequent pain, and pain
of longer duration than men.7–14 In
addition, women are more prompt
in seeking help than men. Therefore,
it seems that women more commonly have TMD and may seek care
for TMD pain more often than men.3
Temporomandibular disorders have
commonly been associated with
symptoms affecting the head and
neck region, such as headache,
cervical spine dysfunction,15,16 and
altered head and cervical posture.17–21 It has been reported that
pain in the cervical musculoskeletal
tissues may be referred to cranial
August 2011
structures, including the jaw muscles22,23; thus, a connection between
cervical muscle dysfunction and jaw
symptoms could exist.24 –27 Additionally, animal studies have revealed
considerable convergence of craniofacial and cervical afferents in the
trigeminocervical nucleus and upper
cervical nociceptive neurons.28 –31
All of this evidence has been the theoretical foundation of pain localization and referral and of neuromuscular adaptations in the cervical and
orofacial regions.32–34 However, to
date, no research has demonstrated a
cause-and-effect relationship.
As stated above, TMD are categorized as musculoskeletal disorders
that commonly involve the cervical
region. Other musculoskeletal disorders associated with the cervical
region, such as neck pain, cervicogenic headache, and whiplashassociated disorders, are characterized by abnormal function of the
cervical muscles.35–37 However, it is
unknown whether people with TMD
have these muscular alterations.
Given the close connection between
the cervical spine and the orofacial
region, knowledge about impairments
in the cervical spine in people with
TMD could help clinicians focus their
efforts on properly evaluating and
treating these impairments.
Previous work has shown that gross
changes in strength (force-generating
capacity) and endurance have been
observed in cervical-related disorders. However, according to Jull et
al36 and Falla and Farina,38 finer
changes in cervical muscular activity
of the cervical spine are present.
Reduced activation of deep cervical
muscles, augmented superficial activity of the sternocleidomastoid (SCM)
and anterior scalene (AS) muscles,
changes in feedforward activation,
reduced capacity to relax the cervical muscles, and prolonged muscle
activity following voluntary contraction could lead to a compromise in
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the control of the cervical spine and
consequently lead to pain and dysfunction.36 Study of these muscular
alterations has gained attention in
the last few years, as exercises
addressing these motor control alterations have had good results in
patients with cervical involvement.39 – 41 Therefore, the assessment and treatment of muscular
impairments is considered a key element in the management of cervicalassociated disorders. Because TMD
have been considered part of the
cervical-associated disorders, it may
be plausible that similar features
could be seen in this patient group.
Knowledge about these features
would be useful for clinicians treating patients with TMD. However,
studies of muscular impairments in
patients with TMD are lacking.
Cervical dysfunction in patients with
TMDs has been evaluated only qualitatively through a general clinical
examination of the cervical spine.
Most of the studies have looked at
cervical spine signs and symptoms in
people with TMD, but they have not
investigated any motor alterations
in a quantitative way. For example,
de Wijer and colleagues27,42
concluded that symptoms of the
stomatognathic system overlap in
patients with TMD and cervical
spine disorders and that symptoms
of the cervical spine overlap in the
same group of patients. Visscher et
al25 found that patients with chronic
TMD more often had cervical spine
pain than those without this disorder. Stiesch-Scholz et al43 found that
asymptomatic functional disorders
of the cervical spine occurred more
frequently in patients with internal
derangement of the TMJ than in a
control group. The presence of tender points in the cervical spine and
shoulder girdle in patients with the
same diagnosis was more common,
especially in upper segments of the
The Bottom Line
Cervical spine dysfunction has been reported to be associated with temporomandibular disorders (TMD). Temporomandibular disorders also are
commonly associated with other symptoms affecting the head and neck
region such as headache, ear-related symptoms, and altered head and
cervical posture. However, no study has investigated the presence of
cervical muscle impairments using electromyography.
The results of this study may give clinicians insight into the importance of
the evaluation and possible treatment of the deep neck flexors in patients
with TMD. However, randomized clinical trials are necessary to determine
the effectiveness of an exercise program targeting the deep neck flexors
in these patients.
If you’re a patient, what might these findings mean
for you?
If you have a TMD, these findings may help your physical therapist
evaluate your condition. This evaluation would include an examination of
the cervical musculature as well as the TMD.
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cervical spine, compared with a control group of individuals who were
healthy. Furthermore, a recent systematic review44 showed that exercises for the neck that also were used
to improve neck and head posture
decreased symptoms in patients
with TMD. However, the systematic
review found that details of the exercises and exercise programs (ie, type
of exercise, dosage, and frequency)
were lacking, as well as a clear
underlying mechanism of why these
exercises, directed toward to the
neck, improved TMD symptoms.
Based on the above information, it
was evident that a more quantitative
evaluation of the motor activity of
the cervical muscles through electromyographic (EMG) assessment, looking at performance patterns of
the cervical musculature activity in
patients with TMD, could assist in
clarifying the role of the cervical
muscles’ involvement in the symptoms of these patients. Additionally,
this evaluation could open an area
of study aimed at treating these alterations through improvement of
motor control of the cervical muscles in patients with TMD.
The main objective of this study was
to determine, through EMG evaluation, whether patients with myogenous TMD and mixed TMD had
altered muscle activity (ie, higher
EMG activity) of the superficial cervical muscles (SCM and AS) when
performing the CCFT compared
with a control group of individuals
who were healthy. The secondary
objectives of this study were: (1) to
determine whether there was an
association between the performance of the cervical flexor muscles
during the 5 stages of the CCFT and
neck disability and jaw disability and
(2) to determine whether there was
an association between level of
chronic disability in patients with
TMD based on the Research Diagnostic Criteria for Temporomandibular
August 2011
Disorders45 (RDC/TMD) (Chronic
Pain Grade Disability Questionnaire
for TMD), pain intensity, duration of
complaint, and performance of the
cervical flexor muscles during the 5
stages of the CCFT.
Table 1.
Descriptive Statistics of Height, Weight, and Age and Clinical Characteristics of
Participants by Groupa
Variable
Height (cm)
Method
Design
A
cross-sectional
conducted.
Weight (kg)
study
was
Age (y)
Participants
A convenience sample of patients
who attended the TMD/Orofacial
Pain Clinic at the School of Dentistry,
Faculty of Medicine and Dentistry,
University of Alberta, and students
and staff at the University of Alberta
who were healthy was recruited for
this study. The sample size for this
study was calculated based on a
repeated-measures analysis of variance (ANOVA) following the guidelines established by Stevens (with
␣⫽.05, ␤⫽0.20, power⫽80%, and
effect size⫽0.57).46 A minimum of 40
participants per group was needed.
The inclusion and exclusion criteria
for the individuals who were healthy
and the patients with TMD have
been described elsewhere.47,48 In
brief, people who were healthy were
included if they were women
between the ages of 18 and 50
years16 and they did not have a history of musculoskeletal pain, TMD
symptoms, neurological disease, systemic disease, or mental illness that
could interfere with the outcomes.
Patients with TMD were included if
they were women between 18 and
50 years of age, had pain in the masticatory muscles or TMJ of at least 3
months’ duration, and had a moderate or severe baseline pain score
(ⱖ30 mm) on a 100-mm visual analog scale (VAS).49 Patients were classified as having myogenous TMD
based on the classification Ia and Ib
of Dworkin and LeResche.45 In addition, they had to have pain upon
palpation in at least 3 of the 12 musAugust 2011
Duration of complaint (y)
Pain intensity (0–100 mm)
Group
Jaw Function Scale
(10–50 points)
a
b
c
SD
165.1
5.1
Healthy (n⫽47)
165.0
6.8
Mixed TMD (n⫽49)
166.3
5.9
Myogenous TMD
64.1
b
9.9
Healthy
64.3b
12.7
Mixed TMD
72.1c
15.9
Myogenous TMD
31.4
9.0
Healthy
28.3
7.5
Mixed TMD
31.3
8.3
Myogenous TMD
6.5c
6.4
Healthy
0.0
0.0
Mixed TMD
8.3c
6.4
45.3c
17.3
Myogenous TMD
Healthy
Neck Disability Index
(0–50 points)
X
Myogenous TMD (n⫽54)
0.0
0.0
Mixed TMD
49.0c
16.1
Myogenous TMD
10.5c
5.5
1.6
1.6
Mixed TMD
12.6c
6.8
Myogenous TMD
18.6b,c
6.6
Healthy
10.1
0.4
Mixed TMD
22.7c
7.1
Healthy
TMD⫽temporomandibular disorders.
Significantly different compared with participants with mixed TMD at ␣⫽.05.
Significantly different compared with participants who were healthy at ␣⫽.05.
cular points proposed by Fricton and
Schiffman.50 –52 Patients were diagnosed as having mixed TMD if they
complained of muscular symptoms
in addition to TMJ symptoms such
as painful clicking, crepitation, or
pain in the TMJ at rest or during
function53 and during a compression
test.54
A total 168 individuals were assessed
for inclusion in this study. A total of
18 individuals were excluded. The
main reasons for exclusion were: not
totally healthy (n⫽9), older than 50
years of age (n⫽2), having a neurological disease (n⫽1), having cancer
(n⫽1), and having a pain score lower
than 30 mm on the VAS (n⫽5). One
hundred fifty participants provided
data for this study: 47 were healthy,
54 had myogenous TMD, and 49 had
mixed TMD.
The general demographics for each
group and the clinical characteristics
of the participants are displayed in
Table 1. There were no significant
differences in age and height in the
sample (P⬎.05). However, weight
was significantly different between
participants with mixed TMD and
those with myogenous TMD (mean
difference⫽8.0 kg, 95% confidence
interval [CI]⫽1.9 to 14.2; P⫽.006)
and between participants with
mixed TMD and those who were
healthy (mean difference⫽7.8 kg,
95% CI⫽1.4 to 14.2; P⫽.01).
Participants with mixed TMD were
similar to those with myogenous
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TMD in most of the general characteristics such as duration of complaint and pain intensity (P⬎.05).
Both groups had a moderate intensity of pain in the jaw and a long
history of pain. Both groups also had
a mild level of disability in the neck
and a moderate level of disability in
the jaw (Tab. 1). The Limitations of
Daily Functions in TMD Questionnaire/Jaw Function Scale (JFS) disability score was significantly higher
for participants with mixed TMD
compared with those with myogenous TMD (mean difference⫽4.1
points, 95% CI⫽1.4 to 6.9; P⫽.001).
The prevalence of neck pain in the
sample of participants with TMD was
high. Approximately 88% (87.5%) of
the participants with myogenous
TMD and 87.8% of those with mixed
TMD had self-reported neck pain.
Clinical Examination
The participants underwent a clinical examination by a physical therapist with experience in musculoskeletal rehabilitation to determine
eligibility for this study and to determine their diagnosis. The clinical
examination followed the guidelines
of the RDC/TMD.45 All participants
read an informational letter and
signed an informed consent statement in accordance with the University of Alberta’s policies on research
using human subjects.
Procedure
Demographic data were collected
on all participants who satisfied the
inclusion criteria. In addition, all
included participants were asked
to report specific characteristics
regarding their jaw problem (eg,
onset, duration of symptoms, treatments received) and their intensity
of pain in the jaw (VAS score)49,55–58
and to complete the Neck Disability
Index (NDI),59,60 the JFS,61 and a
questionnaire for history of jaw pain
used by the RDC/TMD.45 In addition,
participants were asked to complete
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the Chronic Pain Grade Disability
Questionnaire for TMD used by the
RDC/TMD to evaluate the level of
chronic disability due to TMDs.45
The reliability and validity of these
tools have been reported elsewhere.45,59 – 61 After the participants
were evaluated clinically and had
completed the questionnaires, they
performed the CCFT. This testing
was performed in one session.
Electromyographic Evaluation of
the Cervical Flexor Muscles
Electrode placement. Surface electrodes were located on the sternal
head of the SCM muscle and on the
AS muscle as described in the protocol used by Falla and colleagues.62,63
A reference electrode was placed on
the wrist.
Normalization procedure for EMG
data. For normalization purposes,
EMG data were collected for 5 seconds during a maximal voluntary
contraction (MVC). The EMG activity
of the SCM and AS muscles was
recorded during this maximal contraction and saved in the computer.
This procedure was repeated a second time. Submaximal contractions
obtained during the CCFT were normalized using these 2 MVC values.
Submaximal contractions were
expressed as a percentage of the
3-second root mean square (RMS)
value obtained during the MVC. The
average between the normalized contractions using the 2 MVC measurements was used for statistical analysis.
EMG data processing. Data on
EMG activity of the SCM and AS
muscles were obtained using the
Bagnoli-8 EMG system* in a bipolar
configuration with DE-2.1 electrodes.* This system is designed to
make the acquisition of EMG signals
easy and reliable (common-mode
rejection ratio⫽92 dB, system
* Delsys Inc, PO Box 15734, Boston, MA
02215.
Number 8
noise⬍1.2 ␮V [RMS]). The EMG
activity was recorded (analog raw
signal) with a data acquisition program, written in Labview 7.1,† which
collected data at 1,024 Hz using a
PCMCIA card† filtered between 20
and 450/Hz ⫾10% and amplified
using a gain of 1,000 according to
the established standards for EMG
acquisition and reporting.64,65 To
obtain a measure of EMG amplitude,
maximum root mean square (RMS)
was calculated for 4 seconds during
the 10-second submaximal contractions for each muscle while performing the CCFT using IGOR
Pro5.1‡ and was expressed a percentage of the 3-second EMG activity
obtained during the MVC normalization procedure.
Instrumentation for Registering
the Pressure Exerted While
Performing the CCFT
An air-filled pressure sensor (pressure biofeedback unit) was placed
in the suboccipital region of each
patient’s neck and inflated to a pressure of 20 mm Hg. The cuff was
connected to a pressure transducer
(miniature pressure cell) designed
to register increases in pressure with
the movement of nodding action for
the CCFT. Electrical signals from the
pressure transducer were amplified
to a visual feedback device and projected onto a computer screen so
that the participants were able to see
the targeted pressure level. Graphs
with the performance of each participant during the CCFT were stored
using Igor Pro5.1. These data were
analyzed offline by a blinded assessor.
Craniocervical Flexion Test:
Description and Procedures
Before testing began, participants
were asked to perform a warm-up,
which consisted of 2 movements of
the neck and head in all directions
†
National Instruments Corporation, 11500 N
Mopac Expwy, Austin, TX 78759-3504.
‡
WaveMetrics Inc, PO Box 2088, Lake
Oswego, OR 97035.
August 2011
(flexion [forward neck movement],
extension, side flexion [lateral movement of the neck], and rotation). The
participants were placed in a relaxed
supine position with the knees
flexed and the head and neck maintained in a mid-position (ie, neutral
position, no flexion or extension)
following a protocol established previously.66 The head and chin were
parallel to the plinth (Fig. 1).
The CCFT is a low-load test that is
the most common method used to
evaluate the performance of the
deep cervical muscles (ie, longus
colli and rectus capitis). The CCFT
consists of a craniocervical flexion
(nodding) movement, which combines the action of flexion at the
craniocervical junction, performed
by the longus capitis muscles, along
with the flattening of the cervical
lordosis, an action of the longus colli
muscles. Electromyographic activity
of the superficial cervical flexor muscles such as the SCM and AS may be
registered during the CCFT. Elevated
EMG activity may be a compensation
for reduced or impaired activity of
the deep cervical flexor muscles in
individuals with cervical-associated
pain compared with those who are
healthy.67
The CCFT required each participant
to perform the craniocervical flexion
movement in 5 progressive stages of
increasing pressure (22, 24, 26, 28,
and 30 mm Hg) with the aid of a
visual feedback device. Participants
were instructed to perform this gentle nodding movement (craniocervical flexion) and at practiced progressive targeted pressure levels. The
order of the targeted pressure level
was randomized by an independent
assessor. Participants had to maintain a steady pressure at each targeted level for a duration of 10 seconds (Fig. 1). They repeated each
targeted level 2 times, with a rest
period of 1 minute between repetitions to avoid the effects of fatigue.68
August 2011
Figure 1.
Craniocervical flexion test.
Data Analysis
The normalized data of the EMG
activity of all muscles were analyzed
descriptively (ie, mean, standard
deviation). Variables were tested for
normality, homogeneity of variance,
and linearity. All EMG variables were
reasonably normally distributed. Histograms and box plots show that
most of the variables were slightly
skewed to the right. However,
ANOVA analysis is robust to these
mild deviations from normality and
can provide accurate estimates of
the analyzed variables.69
A 3-way mixed-design ANOVA for
repeated measures (3 independent
variables: muscles [SCM and AS], test
[5 levels], and groups [myogenous
TMD, mixed TMD, and control]) was
used to evaluate the differences in
EMG activity for selected muscles
(dependent variable) while performing the CCFT at 5 levels of pressure.
Pair-wise comparisons using the
Bonferroni procedure were administered to evaluate the differences
between variables and groups (ie,
control and TMD groups) in all of
the different conditions (objective
1). The Spearman rho test was used
to evaluate the relationship among
NDI, JFS, and clinical variables with
EMG variables (correlational matrix)
(objectives 2 and 3). The correlation
was considered important when the
correlation coefficient value was
higher than .70. The reference values to make this decision were based
on values reported by Munro.70
To clearly show the impact of the
results for clinical practice, clinical
relevance of the results was assessed
using a distribution-based method.71
The effect size (Cohen d) values
were calculated to determine clinical
relevance of the differences in the
EMG measurements across different
Volume 91
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1189
Myogenous TMD
Healthy
Mixed TMD
Normalized EMG Activity (%MVC)
60
50
40
30
20
10
AvASL_30mmHg
AvASR_30mmHg
AvSCML_30mmHg
AvSCMR_30mmHg
AvASL_28mmHg
AvASR_28mmHg
AvSCML_28mmHg
AvSCMR_28mmHg
AvASL_26mmHg
AvASR_26mmHg
AvSCML_26mmHg
AvSCMR_26mmHg
AvASL_24mmHg
AvASR_24mmHg
AvSCML_24mmHg
AvSCMR_24mmHg
AvASL_22mmHg
AvASR_22mmHg
AvSCML_22mmHg
AvSCMR_22mmHg
AvASL_30mmHg
AvASR_30mmHg
AvSCML_30mmHg
AvSCMR_30mmHg
AvASL_28mmHg
AvASR_28mmHg
AvSCML_28mmHg
AvSCMR_28mmHg
AvASL_26mmHg
AvASR_26mmHg
AvSCML_26mmHg
AvSCMR_26mmHg
AvASL_24mmHg
AvASR_24mmHg
AvSCML_24mmHg
AvSCMR_24mmHg
AvASL_22mmHg
AvASR_22mmHg
AvSCML_22mmHg
AvSCMR_22mmHg
AvASL_30mmHg
AvASR_30mmHg
AvSCML_30mmHg
AvSCMR_30mmHg
AvASL_28mmHg
AvASR_28mmHg
AvSCML_28mmHg
AvSCMR_28mmHg
AvASL_26mmHg
AvASR_26mmHg
AvSCML_26mmHg
AvSCMR_26mmHg
AvASL_24mmHg
AvASR_24mmHg
AvSCML_24mmHg
AvSCMR_24mmHg
AvASL_22mmHg
AvASR_22mmHg
AvSCML_22mmHg
AvSCMR_22mmHg
0
Figure 2.
Normalized electromyographic (EMG) activity of sternocleidomastoid (SCM) and anterior scalene (AS) muscles in participants with
myogenous temporomandibular disorders (TMD), those with mixed TMD, and those who were healthy while performing the
craniocervical flexion test. Error bars⫽95% confidence interval. %MVC⫽percentage of maximum voluntary contraction,
AvSCMR_22mmHg⫽average right SCM muscle EMG activity at 22 mm Hg, AvSCML_22mmHg⫽average left SCM muscle EMG
activity at 22 mm Hg, AvASR_22mmHG⫽average right AS muscle EMG activity at 22 mm Hg, AvASL_22mmHg⫽average left
AS muscle EMG activity at 22 mm Hg, AvSCMR_24mmHg⫽average right SCM muscle EMG activity at 24 mm Hg,
AvSCML_24mmHg⫽average left SCM muscle EMG activity at 24 mm Hg, AvASR_24mmHg⫽average right AS muscle EMG activity
at 24 mm Hg, AvASL_24mmHg⫽average left AS muscle EMG activity at 24 mm Hg, AvSCMR_26mmHg⫽average right SCM muscle
EMG activity at 26 mm Hg, AvSCML_26mmHg⫽average left SCM muscle EMG activity at 26 mm Hg, AvASR_26mmHg⫽average
right AS muscle EMG activity at 26 mm Hg, AvASL_26mmHg⫽average left AS muscle EMG activity at 26 mm Hg,
AvSCMR_28mmHg⫽average right SCM muscle EMG activity at 28 mm Hg, AvSCML_28mmHg⫽average left SCM muscle EMG
activity at 28 mm Hg, AvASR_28mmHg⫽average right AS muscle EMG activity at 28 mm Hg, AvASL_28mmHg⫽average left AS
muscle EMG activity at 28 mm Hg, AvSCMR_30mmHg⫽average right SCM muscle EMG activity at 30 mm Hg,
AvSCML_30mmHg⫽average left SCM muscle EMG activity at 30 mm Hg, AvASR_30mmHg⫽average right AS muscle EMG activity
at 30 mm Hg, AvASL_30mmHg⫽average left AS muscle EMG activity at 30 mm Hg.
levels of pressure and groups.72
Effect sizes of 0.4 or higher were
considered clinically relevant.73 A
subgroup analysis also was conducted to determine differences
between participants with pure
TMD (ie, without neck pain) and
those who were healthy.
The level of significance was set at
␣⫽.05. The SPSS version 17§ and
STATA version 10㛳 statistical programs were used to perform the statistical analysis. The analysis was performed blinded to group condition.
§
60606.
StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845.
㛳
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Results
EMG Activity of the Cervical
Flexors Muscles While
Performing the CCFT
Large variability of the normalized
EMG activity across conditions and
groups was observed (Fig. 2). Using
a 3-way mixed-design ANOVA for
repeated measures, we found
that the main effects of muscles
(F⫽18.5, P⫽.0001) and pressure levels (F⫽27.3, P⫽.0001) were statistically significant. This finding means
that there was a statistically significant difference in EMG activity
among muscles and among pressure
levels. The interaction between muscles and pressure also was statistically significant (F⫽2.9, P⫽.001).
Number 8
However, there was no significant
difference in EMG activity of the analyzed muscles among groups (ie,
mixed TMD, myogenous TMD, and
control) across conditions (F⫽2.6,
P⫽.07). Weight was not significantly
associated with EMG activity (P⫽.49),
so it was not included in the model.
Subgroup Analysis: EMG Activity
in Patients With Pure TMD
(Without Neck Pain) Compared
With Participants Who Were
Healthy
When analyzing a subgroup of participants with TMD but without
neck pain (n⫽13) compared with
the control group (n⫽47), statistically significant differences in EMG
August 2011
Table 2.
Subgroup Analysis Between Participants With Pure Temporomandibular Disorders and Participants Who Were Healthy:
Electromyographic Activity of the Analyzed Muscles While Performing the Craniocervical Flexion Testa
Muscle
Pressure
(mm Hg)
Group
SCMR
22
Myogenous TMD
Healthy
24
Myogenous TMD
SCML
95% Confidence
Interval for
Difference
Mean
Difference
Between Groups
(%MVC)
Lower
Bound
Upper
Bound
Standard
Error
Pb
9.51c
3.315
.017
1.35
17.68
Healthy
11.06c
3.719
.013
1.90
20.22
c
Group
28
Myogenous TMD
Healthy
11.92
4.580
.035
0.637
23.20
30
Myogenous TMD
Healthy
12.17c
5.149
.050
0.051
24.86
Myogenous TMD
⫺6.80
c
2.715
.045
⫺13.48
⫺0.11
Mixed TMD
⫺9.54c
3.380
.019
⫺17.87
⫺1.22
Myogenous TMD
⫺7.32
c
2.922
.045
⫺14.52
⫺0.124
Mixed TMD
⫺12.64c
3.637
.003
⫺21.59
⫺3.68
⫺10.68
4.393
.050
⫺21.50
9.74
3.981
.050
0.062
6.631
.033
⫺33.759
22
24
Healthy
Healthy
26
Healthy
Mixed TMD
ASR
22
Myogenous TMD
Healthy
ASL
24
Healthy
Mixed TMD
⫺17.43c
0.014
19.55
⫺1.093
a
Values based on estimated marginal means. TMD⫽temporomandibular disorders, SCMR⫽right sternocleidomastoid, SCML⫽left sternocleidomastoid,
ASR⫽right anterior scalene, and ASL⫽left anterior scalene.
b
Bonferroni adjustment for multiple comparisons.
c
The mean difference is significant at the .05 level.
activity were found between groups
(F⫽4.831, P⫽.01). Post hoc analysis
using a Bonferroni test indicated
there were many statistically significant differences between groups in
the analyzed muscles and conditions
(Tab. 2).
Association Between EMG
Variables and Clinical Variables
While Performing the CCFT
Very weak (although statistically significant) correlations were found,
mainly between the EMG activity of
the SCM muscles during the 5 stages
of the CCFT and clinical variables
such as pain intensity, duration of
complaint, neck disability, jaw disability, and level of chronic disability
of TMD based on the RDC/TMD
(Chronic Pain Grade Disability Questionnaire for TMDs) (Tab. 3).
Table 3.
Correlations Between Electromyographic Activity and Neck Disability (as Measured by Neck Disability Index), Chronic Pain Grade
Classification, Jaw Disability (as Measured by Jaw Function Scale), Pain Intensity, and Duration of Complainta
Electromyographic
Activity
Neck
Disability
Chronic Pain
Grade Classification
Jaw
Disability
Pain
Intensity
Duration of
Complaint (y)
Average SCM at 22 mm Hg
.23b
.26b
.26b
.32b
.15
b
.05
Average AS at 22 mm Hg
.13
.15
.15
.21
.23b
.26b
.30b
.32b
.19c
.14
.16
.17c
.21c
.08
b
.29b
.09
b
.04
.18
c
.19
c
.24
.13
.12
.15
.21
.18c
.17
.23b
.27b
.13
c
b
.03
.13
.10
.17
.24b
.21c
.28b
.22
.33b
.16c
.20c
.18c
.22b
.28b
.11
a
SCM⫽sternocleidomastoid muscle, AS⫽anterior scalene muscle.
b
Correlation is significant at the .05 level.
c
Correlation is significant at the .01 level.
August 2011
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Table 4.
Moderate Effect Sizes for Comparisons Among Groups at Different Levels of Pressure While Performing the Craniocervical Flexion
Testa
Raw Differences
Standardized Effect Size
Mean
Difference
(%MVC)
Lower
Bound
Upper
Bound
Effect
Size
Lower
Bound
Upper
Bound
Effect Size
Based on
Healthy Group
Standard
Deviation
Average SCMR at 22 mm Hg,
mixed TMD vs healthy
5.36
1.65
9.07
0.59
0.17
0.99
0.73
5.88
1.83
9.93
0.59
0.18
0.99
0.72
5.94
0.77
11.11
0.47
0.06
0.87
0.54
6.31
0.67
11.95
0.45
0.04
0.85
0.48
Average SCML at 22 mm Hg,
myogenous TMD vs healthy
5.10
0.66
9.54
0.45
0.06
0.85
0.72
5.79
2.06
9.52
0.63
0.21
1.03
0.82
4.87
0.79
8.95
0.47
0.07
0.87
0.66
6.53
2.49
10.57
0.66
0.24
1.06
0.89
4.63
0.25
9.01
0.43
0.02
0.83
0.50
5.19
0.06
10.32
0.41
0.00
0.81
0.42
Average ASR at 22 mm Hg,
6.39
0.49
12.29
0.43
0.03
0.82
0.60
12.07
1.02
23.12
0.43
0.03
0.82
0.72
8.24
0.17
16.31
0.41
0.01
0.81
0.49
Confidence Interval
for Difference
Outcome Measure:
Electromyographic Activity
Confidence Interval
for Effect Size
a
TMD⫽temporomandibular disorders, SCMR⫽right sternocleidomastoid muscle, SCML⫽left sternocleidomastoid muscle, ASR⫽right anterior scalene muscle,
%MVC⫽percentage of maximum voluntary contraction.
Clinical Relevance
Effect sizes of comparisons between
mixed TMD and myogenous TMD
groups compared with the control
group while performing the CCFT
are displayed in Table 4 and Figures
3 and 4.
Discussion
The main finding of this study was
that, although statistically significant
differences in EMG activity of the
SCM and AS muscles in patients with
TMD compared with participants
who were healthy while performing
the CCFT were not attained (P⫽.07),
there was a trend for patients with
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TMD to have consistently higher
EMG activity in all of the analyzed
muscles. This increased activity of
the superficial muscles of the cervical spine might be associated with
the neck disturbances seen in
patients with TMD. This information
may give clinicians insight into the
importance of evaluation and possible treatment of the deep neck flexors in patients with TMD. However,
at this point, more research on these
issues is necessary to provide definite conclusions.
The results of this study cannot be
directly compared with those of
Number 8
other studies of cervical flexor muscle performance in patients with
TMD because no studies investigating this issue in this population were
found. However, the CCFT has
widely been used by physical therapists to determine alterations in the
motor control of the craniocervical
flexor muscles in people with cervical disorders such as neck pain,
whiplash-associated disorders, and
cervicogenic headache because
impairment of the deep flexor muscles appears to be generic to neck
disorders.37 All of the studies analyzing craniocervical performance using
the CCFT36,63,74,75 converge in that
August 2011
Study or
Subgroup
Mixed TMD
Healthy
Mean Difference
IV, Fixed, 95% CI
IV, Fixed, 95% CI
X
SD
X
SD
ASR at 30 mm Hg
38.09
22.55
49
29.85
16.7
SCML at 22 mm Hg
22.83
10.83
49
17.04
SCML at 24 mm Hg
24.85
11.93
49
18.32
SCML at 26 mm Hg
26.61
12.07
49
21.98
SCML at 28 mm Hg
28.82
12.5
49
24.2
10.4
SCML at 30 mm Hg
30.49
12.93
49
25.3
12.35
47
7.7%
5.19 (0.13, 10.25)
SCMR at 22 mm Hg
21.01
10.59
49
15.65
7.34
47
15.0%
5.36 (1.73, 8.99)
SCMR at 24 mm Hg
23.19
11.48
49
17.31
8.15
47
12.5%
5.88 (1.91, 9.85)
SCMR at 28 mm Hg
28.57
14.25
49
22.63
10.98
47
7.7%
5.94 (0.86, 11.02)
SCMR at 30 mm Hg
30.58
14.5
49
24.2
13.27
Total (95% CI)
Total
Total
Weight
Mean Difference
47
3.2%
8.24 (0.32, 16.16)
7.09
47
14.8%
5.79 (2.14, 9.44)
7.36
47
12.7%
6.53 (2.58, 10.48)
9.29
47
10.7%
4.63 (0.33, 8.93)
47
9.4%
4.62 (0.03, 9.21)
490
47
6.4%
6.38 (0.82, 11.94)
470
100.0%
5.68 (4.27, 7.08)
Heterogeneity: ␹2⫽1.16, df⫽9 (P⫽1.00), I2⫽0%
Test for overall effect: Z⫽7.92 (P⬍.00001)
Figure 3.
Moderate effect sizes found for comparisons between participants with mixed temporomandibular disorders (TMD) and those who
were healthy at different levels of pressure while performing the craniocervical flexion test. IV⫽inverse variance, 95% CI⫽95%
confidence interval, ASR⫽right anterior scalene muscle, SCML⫽left sternocleidomastoid muscle, SCMR⫽right sternocleidomastoid
muscle.
patients with cervical involvement
have an impaired performance of the
deep and superficial flexor cervical
muscles. The increased activity in
the superficial muscles could be seen
as a strategy to compensate for the
dysfunction of the deep flexor muscles. Sterling et al76 suggested that
the presence of pain could lead to
inhibition or delayed activation of
Study or
Subgroup
specific muscles or group of muscles
in the spine. This inhibition generally occurs in deep muscles such as
the longus colli and longus capitis,
which control joint stability.76
The results of this study are not in
total agreement with those of
the majority of the above-mentioned
studies. In our study, we found no
Myogenous TMD
X
SD
Total
Healthy
X
SD
Total
Weight
statistically significant differences in
superficial cervical flexor muscular
activity among groups while performing the CCFT, as evaluated
though EMG analysis. One possible
explanation for these results could
be the level of dysfunction presented
by the participants with TMD. We
found that the level of dysfunction,
not only at the level of the neck but
Mean Difference
Mean Difference
IV, Fixed, 95% CI
IV, Fixed, 95% CI
ASR at 22 mm Hg
26.05
17.83
54
19.66
10.59
47
19.3%
6.39 (0.75, 12.03)
ASR at 30 mm Hg
41.92
34.82
54
29.85
16.73
47
5.6%
12.07 (1.62, 22.52)
SCML at 22 mm Hg
22.14
13.83
54
17.04
7.09
47
34.7%
5.10 (0.89, 9.31)
SCML at 24 mm Hg
23.19
12.3
54
18.32
7.36
47
40.4%
4.87 (0.97, 8.77)
188
100.0%
Total (95% CI)
216
5.65 (3.17, 8.13)
Heterogeneity: ␹2⫽1.74, df⫽3 (P⫽.63), I2⫽0%
Test for overall effect: Z⫽4.47 (P⬍.00001)
Figure 4.
Moderate effect sizes found for comparisons between participants with myogenous temporomandibular disorders (TMD) and those
who were healthy at different levels of pressure while performing the craniocervical flexion test. IV⫽inverse variance, 95% CI⫽95%
confidence interval, ASR⫽right anterior scalene muscle, SCML⫽left sternocleidomastoid muscle.
August 2011
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1193
also at the level of the jaw, was
considered mild for our participants
with TMD. We might speculate that
because the disability was mild, it did
not have an impact on function or
physical impairment, which generally is found in people with more
disabling pain. Our results are in
agreement with the results obtained
by Falla et al63 in individuals with a
level of disability similar to that of
the participants in this present study
(mean NDI score⫽12.4 points,
SD⫽9.563). Falla et al63 found that
even though the normalized EMG
amplitude of the deep cervical flexor
muscles was significantly lower in
patients with neck pain compared
with individuals who were healthy
(P⬍.05), the increase in EMG activity
of the superficial muscles did not
reach
statistical
significance,
although there was a trend of
increased EMG activity for the superficial muscles in patients with neck
pain. The main explanation of this
finding was the large variability in
the EMG activity found across
groups and conditions. These results
agree with our findings, which also
showed a large amount of variability
in EMG activity among muscles and
conditions (as evidenced by the
wide CIs). When interpreting CIs,
lower and upper boundaries need to
be taken into account to make conclusions.77 Based on this interpretation, we can say that 95% of the time
the estimated difference between
groups could fall between these
lower and upper boundaries. If we
look at the upper boundaries of the
CIs for the raw mean differences
(Tab. 4), we can see that the difference between groups can be as high
as 8.95% to 23.12% of MVC. However, if we look at the lower boundaries, the difference between groups
can be as low as 0.06% to 2.49% of
MVC. Therefore, based on this large
variability, we could have a situation
where a clinically significant difference between groups as well as a
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Volume 91
nonclinically significant difference
between groups could occur.
Although there was great variability
in EMG activity, the mean EMG activity of the superficial muscles was
always higher for participants with
TMD pain compared with the control group across all conditions and
muscles (Fig. 2). However, the large
variability of the normalized EMG
activity across participants and
groups did not lead to a finding of
statistical significance.
The large variability seen in the
EMG activity of the cervical flexor
muscles also has been observed in
other regions such as the low back.78
Hodges et al78 found that people
responded differently to experimental pain in the low back muscles.
They reported that no 2 individuals
showed identical patterns of
increased activity of the low back
muscles when they underwent
experimental pain. If this phenomenon were extrapolated to the cervical spine, it could be speculated that
each individual has a different muscle activation strategy to adapt to
pain. The motor response in the cervical spine, especially in people with
pain, would be an increase of the
activity of the SCM and AS muscles;
however other strategies, using different muscles not investigated in
this research, also could be present.
Further research investigating possible cervical motor strategies in people with TMD under different conditions would help further clarify the
role of the cervical muscles in TMD.
Our study did not measure directly
the activity of the deep cervical
flexor muscles because the technique for measuring the activity of
the deep cervical muscles is invasive
and adherence to the testing protocol would have been impaired. We
measured the superficial cervical
muscles such as the SCM and AS only
as an indirect measure of impairment
Number 8
of the activity of the deep cervical
flexor muscles. Thus, it is still uncertain whether deep cervical muscle
activity was impaired in these
patients. In addition, because the
cervical spine is a very complex system characterized by a high degree
of redundancy in the muscular system,36,79 it is not surprising that
other motor strategies and muscles
not analyzed in this study (other than
SCM and AS muscles) could be used
by people with pain to stabilize the
cervical spine.
The CCFT has become a gold standard for isolating the activation of
the deep flexor muscles and identifying possible co-contraction patterns of superficial muscles in the
cervical spine.63,75,80 Its construct
validity66,81 as well as its reliability67
have been established; however,
other psychometric properties such
as concurrent validity with clinical
variables such as neck disability and
pain intensity of this test need to be
ascertained. Thus, this study investigated the associations between the
muscular activity of the analyzed
muscles through the 5 stages of the
CCFT and clinical variables such as
the level of chronic pain grade classification of TMD based on the
RDC/TMD, pain intensity, time of
complaint, jaw disability, and neck
disability. Most of the associations
were positive but weak, indicating
that the performance of the CCFT is
not strongly related to other clinical
variables such as pain intensity, neck
disability, or jaw disability. These
results are in agreement with those
of Falla et al,82 who reported that
reduction in pain in patients with
neck pain after a training program
was not accompanied by an
improvement in performance of the
cervical flexor muscles. It appears
that pain and physical performance
of the craniocervical muscles represent different aspects of disability in
people with cervical involvement.83
Thus, a more focused evaluation
August 2011
regarding disability and its related
factors in future research is needed
to understand the intricacies among
physical impairments, pain, and
disability.
Because of the variability of EMG
activity among groups and conditions found in this study, an analysis
of the clinical relevance of the
results through the calculation of
effect sizes was conducted to evaluate the relevance of these findings.
To our knowledge, this is the first
time that a study has evaluated the
clinical relevance of EMG activity.
According to Musselman,71 effect
size calculation is one of the most
common ways to evaluate clinical
relevance after the fact.71,84 The
larger this effect size index, the
larger the difference between
groups and the larger the clinical relevance of the results.71 It is recognized that effect sizes of 0.2, 0.5, and
0.8 correspond to small, moderate,
and large effects.73 Although there is
no known research that establishes a
cutoff of EMG activity (percentage of
MVC) to be considered clinically relevant when comparing the EMG
activity of different groups, it has
been shown that EMG activity as low
as 2% to 5% of MVC can be related to
pain in neck-shoulder areas.85– 87 In
addition, a minimally important difference for EMG activity has been
found to be 2.9% of MVC.88
Although a large variability in the
estimates of effect sizes was present
in this data set (which had wide CIs),
based on the calculated mean effect
sizes (ie, standardized mean differences ranging between 0.41 and
0.66) and the raw mean differences
obtained from the comparisons
(ranging from 4.63% to 12.07% of
MVC), differences in EMG activity
were found in some of the comparisons between patients with TMD
and the control group (Tab. 3). Thus,
standardized effect sizes and minimally important difference could
August 2011
serve as an index to guide clinicians
in the relevance of the findings. It
could be said that in the absence of
knowledge and guidelines to determine the clinical relevance of certain
outcomes, calculation of the clinical
relevance, based on the distribution
methods, could be an option. These
results could be of importance for
clinicians who work in this field
because this analysis might indicate
that patients with TMD tended to
have increased activity of the superficial cervical muscles compared
with the control group. In addition,
the results of the subgroup analysis
considering only patients with pure
TMD provide more support for these
findings. Furthermore, preliminary
evidence has shown that exercises
addressing these types of impairments (ie, training of neck flexor
muscles) as part of cervical spine
treatment in people with TMD
reduced pain and improved function
(ie, increased pain-free mouth opening) in patients with TMD, which
potentially supports the fact that
patients with TMD could benefit
from treatment of impaired cervical
flexor muscles.89 Therefore, these
results might be considered when
evaluating and treating patients with
TMD.
Nevertheless, it is necessary to
implement a randomized controlled
trial that addresses these cervical
impairments through cervical flexor
exercises in patients with TMD
and test whether these exercises
decrease pain and improve function
and quality of life in patients with
TMD. In this way, research could
advance clinical practice in this area.
Limitations
The results obtained in this research
are applicable for the group of individuals who participated in this
study under the protocols used.
They potentially could be applied to
people with TMD having characteristics similar to those of the partici-
pants in this study. This limitation
should be taking into consideration
when attempting to extrapolate
these results. In addition, it must be
acknowledged that because this
project was cross-sectional, a causeand-effect relationship between cervical muscular impairment and TMD
cannot be established.
Conclusions
There were no statistically significant differences (P⫽.07) in EMG
activity in the SCM or the AS muscles
in patients with mixed and myogenous TMD compared with individuals who were healthy when performing the CCFT. However, the patients
with TMD tended to have increased
activity of the superficial cervical
muscles compared with the control
group. This increased activity of the
superficial muscles of the cervical
spine might be associated with the
neck disturbances seen in patients
with TMD. This information may
give clinicians insight into the importance of evaluation and possible
treatment of the deep neck flexors
in patients with TMD. However,
future research should test the effectiveness of this type of program
through a randomized controlled
trial in individuals with TMD to
determine the real value of treating
this type of impairment in this
population.
Dr Armijo-Olivo, Dr Warren, Dr Major, and
Dr Magee provided concept/idea/research
design. Dr Armijo-Olivo, Mr da Costa, Dr
Gadotti, Dr Major, Dr Thie, and Dr Magee
provided writing. Dr Armijo-Olivo, Mr Fuentes, Mr da Costa, and Dr Gadotti provided
data collection. Dr Armijo-Olivo and Dr Warren provided data analysis. Dr Armijo-Olivo
and Dr Magee provided project management. Dr Armijo-Olivo provided fund procurement. Dr Magee provided facilities/
equipment and institutional liaisons. Dr
Armijo-Olivo, Mr Fuentes, Mr da Costa, Dr
Gadotti, Dr Warren, Dr Major, Dr Thie, and
Dr Magee provided consultation (including
review of manuscript before submission).
The authors thank all of the participants in
this study and Darrel Goertzen, Luis Cam-
Volume 91
Number 8
Physical Therapy f
1195
pos, and Rodrigo Guzman for their technical
assistance.
The study was approved by the Ethics Committee of the University of Alberta, Edmonton, Alberta, Canada.
This research was presented at the XVIII
International Conference of the International
Society of Electrophysiology and Kinesiology, June 16 –19, 2010, Aalborg, Denmark;
the 5th International Conference on Orofacial Pain and Temporomandibular Disorders,
August 26 –30, 2009, Praia do Forte, Bahia,
Brazil; and the 13th World Conference on
Pain, August 29 –September 2, 2010, Montreal, Quebec, Canada.
Dr Armijo-Olivo was supported by the Canadian Institutes of Health Research (CIHR), the
Alberta Provincial CIHR Training Program in
Bone and Joint Health, an Izaak Walton Killam Scholarship from the University of
Alberta, and the Physiotherapy Foundation
of Canada through an Ann Collins Whitmore
Memorial Award. Mr Fuentes is supported by
the government of Chile (BECAS Chile Scholarship Program) and Catholic University of
Maule, Chile.
DOI: 10.2522/ptj.20100233
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Volume 91
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Research Report
Associations Between Physical
Performance and Executive Function
in Older Adults With Mild Cognitive
Impairment: Gait Speed and the
Timed “Up & Go” Test
Ellen L. McGough, Valerie E. Kelly, Rebecca G. Logsdon, Susan M. McCurry,
Barbara B. Cochrane, Joyce M. Engel, Linda Teri
E.L. McGough, PT, PhD, Department of Rehabilitation Medicine,
University of Washington, 1959
NE Pacific St, Box 356490, Seattle,
WA 98195 (USA). Address all correspondence to Dr McGough at:
[email protected].
V.E. Kelly, PT, PhD, Department
of Rehabilitation Medicine, University of Washington.
R.G. Logsdon, PhD, School of
Nursing, University of Washington.
S.M. McCurry, PhD, School of
Nursing, University of Washington.
B.B. Cochrane, PhD, RN, FAAN,
School of Nursing, University of
Washington.
J.M. Engel, OT, PhD, FAOTA,
Department of Occupational Sciences & Technology, University
of Wisconsin–Milwaukee, Milwaukee, Wisconsin.
L. Teri, PhD, School of Nursing,
University of Washington.
[McGough EL, Kelly VE, Logsdon
RG, et al. Associations between
physical performance and executive function in older adults
with mild cognitive impairment:
gait speed and the Timed “Up &
Go” Test. Phys Ther. 2011;91:
1198 –1207.]
Association
Published Ahead of Print: May 26,
2011
Submitted: November 5, 2010
Background. Older adults with amnestic mild cognitive impairment (aMCI) are
at higher risk for developing Alzheimer disease. Physical performance decline on gait
and mobility tasks in conjunction with executive dysfunction has implications for
accelerated functional decline, disability, and institutionalization in sedentary older
adults with aMCI.
Objectives. The purpose of this study was to examine whether performance on
2 tests commonly used by physical therapists (usual gait speed and Timed “Up & Go”
Test [TUG]) are associated with performance on 2 neuropsychological tests of
executive function (Trail Making Test, part B [TMT-B], and Stroop-Interference,
calculated from the Stroop Word Color Test) in sedentary older adults with aMCI.
Design. The study was a cross-sectional analysis of 201 sedentary older adults with
memory impairment participating in a longitudinal intervention study of cognitive
function, aging, exercise, and health promotion.
Methods. Physical performance speed on gait and mobility tasks was measured
via usual gait speed and the TUG (at fast pace). Executive function was measured with
the TMT-B and Stroop-Interference measures.
Results. Applying multiple linear regression, usual gait speed was associated with
executive function on both the TMT-B (␤⫽⫺0.215, P⫽.003) and Stroop-Interference
(␤ ⫽⫺0.195, P⫽.01) measures, indicating that slower usual gait speed was associated
with lower executive function performance. Timed “Up & Go” Test scores (in
logarithmic transformation) also were associated with executive function on both the
TMT-B (␤⫽0.256, P⬍.001) and Stroop-Interference (␤⫽0.228, P⫽.002) measures,
indicating that a longer time on the TUG was associated with lower executive
function performance. All associations remained statistically significant after adjusting
for age, sex, depressive symptoms, medical comorbidity, and body mass index.
Limitations. The cross-sectional nature of this study does not allow for inferences
of causation.
Conclusions. Physical performance speed was associated with executive function after adjusting for age, sex, and age-related factors in sedentary older adults with
aMCI. Further research is needed to determine mechanisms and early intervention
strategies to slow functional decline.
this article at:
ptjournal.apta.org
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August 2011
Physical Performance and Executive Function in Older Adults With Mild Cognitive Impairment
M
ild cognitive impairment
(MCI) is considered a transitional state that is less severe
than dementia, but beyond that
of typical age-related cognitive
changes.1 Mild cognitive impairment is defined as impairment
(adjusted for age and education) in
one or more domains of cognition,
with relative sparing of global cognitive functions.2– 4 Although MCI is
associated with only mild decline in
cognition, the onset of dementia is
characterized by overt difficulties in
multiple domains of cognitive function as well as performance of daily
activities.2 Even in the presence of
MCI, reduced function has been
identified in executive function
tasks,5,6 instrumental activities of
daily living7,8 and physical performance tasks.9,10 There are 2 major
subclassifications of MCI—amnestic
MCI (aMCI) and nonamnestic MCI
(naMCI)—the more common of
which is aMCI.4,11 Older adults with
aMCI, involving early memory loss,
are at higher risk for Alzheimer disease (AD),4,11 and reduced executive
function may be associated with
early physical decline in people with
aMCI. Identifying whether physical
performance decline is associated
with reduced executive function is
important for developing physical
therapy management strategies
aimed at slowing the progression of
functional decline and associated disability in older adults with aMCI.
The worsening of executive function
in older adults with aMCI is associated with the conversion to AD.5 The
degenerative processes in aMCI
involve medial temporal lobe structures, as observed in early stages of
AD, but also may include the frontal
lobe, the part of the brain involved in
executive function.4,5 Executive
function involves higher-order cognitive processes necessary for implementation of goal-directed behaviors,12 and reliance on executive
function is elevated with increasing
August 2011
difficulty of motor tasks,13,14 especially in novel or demanding situations.15 Medication adherence, cooking, housekeeping, and motor tasks
performed in a complex environment are examples of goal-directed
activities that are vulnerable to
decline in executive function.12
Executive function is thought to rely
strongly on the prefrontal cortex and
includes multiple cognitive processes such as planning, tracking,
judgment,
initiation,
scanning,
sequencing, problem solving, and
cognitive flexibility.12,16 The notion
that executive function is multifaceted in nature is supported by evidence from functional magnetic resonance studies indicating that
different aspects of executive function rely on different parts of the
prefrontal cortex.17
Declining physical performance in
conjunction with cognitive decline
has been associated with increased
risk for dementia and disability in
population-based studies of older
adults.18,19 In a prospective, longitudinal study of older adults who were
healthy, slower self-selected gait
speed was associated with cognitive
impairment at the 6-year follow-up.20
In the Sydney Older Persons Study of
people who did not have dementia
at baseline, the presence of slowed
gait speed in combination with
cognitive deficits was associated
with increased odds of progression
to dementia.19 The combination of
impaired physical performance and
executive dysfunction may be more
predictive of dementia risk; therefore, it has implications for accelerated functional decline, disability,
and institutionalization in older
adults with aMCI.
Studies of physical performance in
individuals with MCI support the
notion that physical performance
impairment is present prior to the
onset of dementia,21,22 especially in
older adults who demonstrate executive dysfunction.9,23 Executive dysfunction is predictive of functional
decline and increased risk for
dementia in community-dwelling
older adults.24,25 Early pathology,
consistent with AD, may contribute
The Bottom Line
Older adults with mild cognitive impairment (MCI) are at higher risk for
dementia and associated disability. Functional decline often is accelerated
in the presence of both physical and cognitive impairments.
In this study of sedentary older adults with amnestic MCI (memory loss),
slower physical performance on gait and mobility tasks was associated
with lower performance on executive function tasks, such as those
involving planning and judgment.
If you’re a patient or caregiver, what might these
findings mean for you?
Comprehensive prevention and rehabilitation strategies that enhance
both cognitive and physical function are important in reducing functional
decline and disability in older adults.
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28 presentations at independent retirement residences
890 telephone screening calls
Not eligible (n=343):
Too active=117
Health problem=93
Too young=27
No intervention group=60
Unavailable=46
Eligible for in-person
screening
(n=547)
Completed in-person
screening
(n=359)
Eligible, not
interested (n=188)
Not eligible after in-person
screening (n=97):
High cognition=37
Possible dementia=50
Health problem=10
Eligible for
study
(n=262)
Completed baseline assessment
(n=201)
Figure.
Flow chart of participant recruitment and screening.
to physical performance impairment
through alterations in memory,
attention, and executive function
networks.26,27 Alternatively, age and
age-related comorbid conditions may
be responsible for declining physical
performance and executive dysfunction in older adults with memory
impairment. It is unclear whether an
association between physical performance and executive function
remains after adjusting for age and
age-related factors that are known to
affect both physical performance
and executive function in older
adults with aMCI.
Because older adults with both physical and cognitive impairment are at
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Physical Therapy
Volume 91
higher risk for dementia and disability,28 identifying whether physical
performance decline is associated
with executive dysfunction is important for developing physical therapy
early intervention strategies for older
adults with aMCI. The purpose of
this study was to determine whether
performance on 2 tests that are commonly used by physical therapists
(usual gait speed and the Timed “Up
& Go” Test [TUG]) are associated
with performance on 2 neuropsychological tests of executive function (the Trail Making Test, part B
[TMT-B], and Stroop-Interference,
calculated from the Stroop Word
Color Test) in sedentary older adults
with aMCI after adjusting for age,
Number 8
sex, depressive symptoms, medical
comorbidity, and body mass index
(BMI). We hypothesized that slower
physical performance speed would
be associated with lower executive function after adjusting for factors that are known to affect both
physical performance and executive
function.
Method
Participants
This study involved analysis of baseline data from the Resources and
Activities for Life-Long Independence (RALLI) Study, a longitudinal
intervention study of cognitive function, aging, exercise, and health promotion in sedentary older adults
with aMCI. Participants were volunteers living in independent retirement residences who reported mild
memory problems. Study flyers were
distributed, and a presentation was
given to residents of 28 independent
retirement living centers in the
Seattle, Washington, metropolitan
region. Residents who were interested in volunteering for the RALLI
Study contacted the study coordinator (Figure). The sample size was
determined based on a power analysis conducted for the randomized
controlled trial.
Participants enrolled in the study
were aged 70 years and older, were
sedentary, and were classified as
having aMCI based on screening
interviews and a consensus meeting.
Study recruitment and screening
consisted of: (1) a telephone screening interview, (2) an in-home screening evaluation that consisted of a
semistructured interview and neuropsychological screening tests, and
(3) an expert consensus panel to
review screening data. Petersen criteria1,4 were applied using a combination of cognitive test scores,
screening interview data, and consensus case review to identify people with memory problems that
would be consistent with a clinical
August 2011
subtype of aMCI (single or multiple
domain). Petersen criteria included:
(1) memory complaint, (2) impaired
memory for age and education, (3)
preserved general cognitive function,
(4) essentially preserved activities of
daily living, and (5) not already diagnosed with dementia. Participants
were enrolled in the study from July
2007 through December 2009.
Cognitive function tests and clinical
criteria used to determine whether
participants met the aMCI classification criteria included: (1) the MiniMental State Examination (MMSE)
for global cognition,29 (2) the
Wechsler Memory Scale–Revised
(WMS-R) Logical Memory I and II
subtests for immediate and delayed
recall,30 and (3) the Clinical Dementia Rating Scale for severity rating
of cognitive impairment.31 Memory
impairment was determined by a
Clinical Dementia Rating Scale score
of 0.5 (consistent with MCI), a score
on the WMS-R Logical Memory subtests that was 1 standard deviation
below age- and education-adjusted
norms,32 problems on the memory
recall items of the MMSE, or
observed difficulty with everyday
recall during the assessment interview. Because the classification of
aMCI involves a synthesis of information obtained through neuropsychological assessment, observations of
daily activities, and clinical judgment,2,3 each participant was
reviewed through a consensus process to determine eligibility for the
study. The above neuropsychological test scores, performance on specific memory tasks, and evidence
indicating intact ability to perform
activities of daily living were examined by 2 clinical psychologists at a
consensus meeting. Because aMCI
is a clinical classification for which
there is no single, definitive diagnostic test, a series of neuropsychological tests as well as an expert clinician’s observations and judgment are
critical in identifying people at risk
August 2011
for dementia.3 Sedentary lifestyle
was defined as performance of less
than 150 minutes of moderateintensity exercise per week (over
the previous month), as recommended by the American College
of Sports Medicine and the American Heart Association.33
Potential participants were excluded
from the study if they: (1) did not
meet aMCI criteria; (2) were unable
to walk independently with an assistive device; (3) were expecting to
move away from the area; (4) had a
known terminal illness; (5) were
actively suicidal, hallucinating, or
delusional; (6) had been hospitalized
within the previous 12 months; (7)
had an uncontrolled chronic medical
condition; (8) were blind or deaf; or
(9) had a known central nervous
system condition associated with
dementia. Upon enrollment in the
study, participants completed 2
in-home baseline evaluations administered by trained research assistants.
During these evaluations, testing was
completed for demographic and
health-related information, physical
performance measures, and executive function measures as described
below. Each participant gave consent prior to the screening process.
Demographic and HealthRelated Information
Demographic and health-related information was collected via self-report
responses. Medical comorbidity,
assessed with the Self-Administered
Comorbidity Questionnaire,34 was
defined as having any of the following
conditions: heart disease, hypertension, diabetes, pulmonary disease,
kidney disease, peripheral vascular
disease, osteoarthritis, rheumatoid
arthritis, or back pain. Symptoms of
depression were assessed using the
Geriatric Depression Scale (range of
scores⫽0 –15).35 Body mass index
(kg/m2) was calculated using height
and weight measured at baseline.
Physical Performance Measures
Usual gait speed was calculated from
an 8-foot (approximately 2.4 m) walk
test in which participants walked at
their comfortable pace. The 8-foot
walk test was completed inside the
participant’s apartment or in a
nearby hallway on a level surface
with low-pile or indoor/outdoor carpet. The time to walk 8 feet was
averaged over 2 trials and converted
to gait speed (meters per second).
Comfortable walking speed measurements have been reported to be
highly reliable (r⫽.903) in individuals who were healthy and ranging in
age from 20 to 79 years.36 Usual gait
speed is comparable to the entire
Short Physical Performance Battery
in predicting disability in older
adults.37
The TUG38 was performed at a fast
pace to measure mobility speed.39
Participants were asked to move as
quickly but as safely as possible to
rise from an armchair (45.72-cm [18in] seat height), walk 3 m, turn
around a cone, walk back to the
chair, and sit down. Time to complete the TUG was averaged over 2
trials. When performed at a comfortable pace, TUG scores have good
interrater and intrarater reliability as
well as a high correlation with the
Berg Balance Scale scores (r⫽⫺.81),
gait speed (r⫽⫺.61) and Barthel
Index of Activities of Daily Living
scores (r⫽⫺.78), and normative values have been reported.36,40 When
performed as quickly and as safely as
possible, the TUG has demonstrated
high sensitivity and specificity in
identifying older adults who are
prone to falling.39
Executive Function Measures
The TMT-B was used to evaluate the
components of executive function
that represent complex visual scanning, speed, attention, and ability to
shift sets.41,42 To complete this test,
participants used a pencil to connect
25 encircled numbers and letters in
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numerical and alphabetical order,
alternating between numbers and
letters.43 The maximum amount of
time allowed to complete the TMT-B
is 300 seconds; longer times indicate
worse performance in executive
function. The TMT-B has been
widely used in studies of older
adults, and normative data have been
reported.44,45 The TMT-B was used in
this study because it is considered to
be specific to executive function
processes due to its requirements for
switching sets and mental tracking
throughout the task.46
The Stroop Word Color Test was
used to assess components of executive function representing a person’s ability to deal with conflicting
stimuli.47 This test involves pairs of
conflicting stimuli that are presented
simultaneously, that is, the name of
one color printed in another color.
There are 3 portions to the Stroop
Word Color Test: word naming (W),
color naming (C), and color interference (CW). Although there are variations in test length and scoring
methods,48,49 the version selected
for this study involved recording the
number of correct responses in 45
seconds for each portion of the
test.50 A difference in the number of
words printed in black ink compared
with colors named correctly for
words printed in a different color (ie,
blue ink for the word “red”) is interpreted as interference of color stimuli. An overall Stroop-Interference
score, as introduced by Golden,51
was calculated for this study using
the formula: [CW ⫺ (W ⫻ C)/(W ⫹
C)]. In a previous study comparing
older adults with aMCI with older
adults with noncognitive impairments and mild AD, those with aMCI
performed less well than those who
were noncognitively impaired and
better than the AD group on the
color interference condition.52 Normative values for the raw scores from
the 3 portions of the Stroop Word
Color Test have been reported.44,53
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Volume 91
Data Analysis
We used SPSS statistical software,
version 16.0,* for descriptive statistics and data analysis. To examine
the association between physical
performance and components of
executive function, linear regression
was applied and model fit was evaluated. A curvilinear relationship was
present between the TUG and executive function (both TMT-B and
Stroop-Interference measures). With
the understanding that the model is
not intended for prediction, but
rather to determine whether a relationship exists, we made the decision to log transform TUG scores.
Upon transformation, we found that
a linear relationship was present
between log(TUG) and each executive function variable.
To assess whether executive function, as measured by the TMT-B and
Stroop-Interference, was associated
with usual gait speed after adjusting
for age, sex, depressive symptoms,
medical comorbidity, and BMI, we
created 2 multiple linear regression
models. Covariates known to influence both walking speed and cognitive functions, including age, sex,
depressive symptoms, medical comorbidity, and BMI, were entered into
each model. The covariate variables
were added first to each usual gait
speed model, followed by the executive function variable. Although performance on the TMT-B and the
Stroop Word Color Test have been
associated with age and years of education in older adults,45,53 education
was not included as a covariate in the
multiple regression analysis because
the majority of our sample had 12
years of more of education (97% had
⬎12 years of education, and 79.6%
had ⬎13 years of education).
To assess whether executive function, as measured by the TMT-B and
* SPSS Inc, 233 S Wacker Dr, Chicago, IL
60606.
Number 8
Stroop-Interference, was associated
with the TUG after adjusting for
covariates, 2 models were created
using log(TUG) as the outcome. The
same covariates as above were
entered into each model because
they are known to influence both
mobility speed and cognitive functions. The covariate variables were
added first to each TUG model, followed by the executive function
variable.
A dichotomous variable was created
for comorbidity (none versus one or
more medical conditions). Sex was
coded 0 (male) or 1 (female). Correlations and the variance inflation factor for multicollinearity were used to
identify whether covariates were
strongly correlated. The contribution of the executive function variable in each model was assessed by
the change in R2 values from the
model with the covariates only to
the model with the covariates and
the executive function variable.
Residual analysis for each multiple
linear regression model included
normal probability plots and scatter
plots of standardized residuals.
Dr McGough received support
through a National Institutes of
Health Rehabilitation Sciences predoctoral fellowship (grant 2T32-HD00742416A1), a National Institute of
Nursing Research/National Institutes
of Health post-doctoral fellowship
(grant T32 NR007106), and the de
Tornyay Healthy Aging Doctoral
Scholarship (School of Nursing, University of Washington). This work
was supported by the National Institute on Aging/National Institutes
of Health (grant 2RO1 AG1477706A2).
Results
Data for demographic and healthrelated variables are summarized in
Table 1. Participants had a mean age
of 84.6 years (SD⫽5.7), were 80.1%
August 2011
female, and were 91% Caucasian.
The initial sample was composed of
201 participants; however, 19 participants did not complete the TMT-B
(16 due to vision problems and 3 due
to missing data), and 25 participants
did not complete the Stroop Word
Color Test (22 due to vision problems or color blindness and 3 due to
missing data). There also were missing data on the GDS (n⫽2), TUG
(n⫽5), usual gait speed (n⫽2),
MMSE (n⫽1), and logical memory
(n⫽1). After accounting for all data
entered into the multiple linear
regression models, 179 cases were
analyzed for associations between
physical performance and the
TMT-B, and 173 cases were analyzed
for associations between physical
performance and the StroopInterference measure. Sixteen participants (8.0% of the entire sample
and 10.8% of those in the final analysis) reached the maximum time
(300 seconds) on the TMT-B.
Usual gait speed was statistically significantly associated with executive
function in both the unadjusted analysis (Tab. 2) and after adjusting for
covariates (Tab. 3). In the unadjusted
analysis, usual gait speed was associated with the TMT-B (␤⫽⫺.267,
P⬍.001) and Stroop-Interference
(␤⫽⫺.214, P⫽.004) measures. The
change in R2 values attributed to
executive function was .07 for the
TMT-B and .05 for the StroopInterference measure. After adjusting for covariates, the TMT-B
(␤⫽⫺.215, P⫽.003) and StroopInterference (␤⫽⫺.195, P⫽.01)
findings were statistically significant,
indicating that slower usual gait
speed was associated with lower
executive function performance on
both measures. The change in R2 values attributed to the addition of the
TMT-B (the difference between the
full model and the model with covariates only) was .044. The overall
change in R2 values was .084; therefore, the full model explained 54.5%
August 2011
Table 1.
Descriptive Statisticsa
n
Mean (SD) or
Percentage
Minimum
Age (y)
201
84.6 (5.7)
69.7
Sex, % female
201
80.1
Ethnicity, % Caucasian
201
91.0
% living alone
201
68.7
% high school education
201
97.5
Characteristic
Maximum
Demographic
104.3
Physical performance and
executive function
Gait speed (m/s)
199
0.61 (0.18)
0.24
1.08
TUG (s)
196
11.96 (5.54)
5.20
35.70
TUG (log)
196
1.041 (0.17)
Trail Making Test, part B
182
148.04 (70.35)
0.716
Stroop-Interference
176
⫺81.09 (20.78)
Geriatric Depression Scale
199
2.48 (2.37)
0
12
WMS-R Logical Memory I
200
19.9 (7.5)
5.0
42.0
WMS-R Logical Memory II
200
14.1 (7.6)
0
35.0
MMSE
200
26.47 (2.56)
% CDR 0.5
200
100.0
% BMI ⱖ25 kg/m2
201
59.9
% medical comorbidity
201
77.6
47.0
⫺139.00
1.553
300.0b
⫺23.00
Clinical
18.00
30.00
a
TUG⫽Timed “Up & Go” Test; TMT-B⫽Trail Making Test, part B; WMS-R⫽Wechsler Memory Scale–
Revised; MMSE⫽Mini-Mental State Examination; CDR⫽Clinical Dementia Rating Scale; BMI⫽body
mass index.
b
10.8% of participants (n⫽16) reached the maximum TMT-B time of 300 seconds.
more variance than the unadjusted
model. The change in R2 attributed
to the addition of the StroopInterference measure to the model
was .034. The overall change in R2
values was .102; therefore, the full
model explained 67.1% more of the
variance than the unadjusted model.
In the full model for usual gait speed,
age and depressive symptoms were
statistically significant when the
TMT-B and Stroop-Interference measures were in the models, with
slower usual gait speed associated
with older age and depressive
symptoms.
Log(TUG) was statistically significantly associated with executive
function in both the unadjusted anal-
Table 2.
Linear Regression for Usual Gait Speed and Timed “Up & Go” Test (TUG) (Log
Transformed)
Executive Function
Physical
Performance
Trail Making Test,
Part B (nⴝ180)
Stroop-Interference
Measure (nⴝ174)
Usual gait speed (m/s)
␤⫽⫺.267, P⬍.001 (R2⫽.07)
␤⫽⫺.214, P⫽.004 (R2⫽.05)
Log(TUG)
␤⫽.290, P⬍.001 (R ⫽.08)
␤⫽.251, P⫽.001 (R2⫽.06)
2
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Table 3.
Linear Regression for Gait Speed (m/s)
Standardized
Coefficient
(␤)
P
Age
⫺.199
.007
Sex
⫺.08
.27
Depressive symptoms
⫺.182
.01
.057
.42
Explanatory Variable
and Covariates
Model 1 (n⫽179)
Medical comorbidity
Model 2 (n⫽173)
Body mass index
⫺.09
.22
.110
⫺.215
.003
.154b
Age
⫺.173
.03
Sex
⫺.124
.09
Depressive symptoms
⫺.232
.002
Medical comorbidity
a
R 2a
.081
.26
Body mass index
⫺.071
.35
.118
Stroop-Interference
⫺.195
.01
.152b
F
5.25 (P⬍.001)
5.00 (P⬍.001)
2
The R value for the model not including the executive function variable.
Change in R2 value was statistically significant at the .05 level when adding the executive function
variable to the model.
b
ysis (Tab. 2) and after adjusting for
covariates (Tab. 4). In the unadjusted
analysis, log(TUG) was associated
with the TMT-B (␤⫽.290, P⫽⬍ .001)
and Stroop-Interference (␤⫽.251,
P⫽.001) measures. The change in R2
values attributed to the executive
function variable was .08 for the
TMT-B and .06 for the StroopInterference measure. Log(TUG) was
associated with both executive function measures after adjusting for
covariates. The TMT-B (␤⫽.256,
P⬍.001) and Stroop-Interference
Table 4.
Linear Regression for Timed “Up & Go” Test (Log Transformed)
Explanatory Variable
and Covariates
Model 1 (n⫽178)
Age
.173
P
.051
.45
Depressive symptoms
.217
.002
⫺.009
R 2a
F
.02
Sex
Medical comorbidity
Model 2 (n⫽173)
Standardized
Coefficient
(␤)
.90
Body mass index
.264
⬍.001
.148
.256
⬍.001
.211b
Age
.156
.05
7.66 (P⬍.001)
Examination of multicollinearity
among the explanatory variables
using the variance inflation factor
resulted in values close to 1, indicating no collinearity. Analysis of residuals for each model using normal
q-plots and scatter plots of residuals
by the estimated values showed that
the model fit the data appropriately.
.097
.18
Discussion
Depressive symptoms
.245
.001
In this study of sedentary older
adults with aMCI, an association
between physical performance
speed and executive function on the
TMT-B and Stroop-Interference measures was demonstrated after adjusting for age, sex, depressive symp-
⫺.036
.61
Body mass index
.198
.008
.104
Stroop-Interference
.228
.002
.147b
a
5.96 (P⬍.001)
The R2 value for the model not including the executive function variable.
b
Change in R2 value was statistically significant at the .05 level when adding the executive function
variable to the model.
f
The results indicate that a longer
time to complete the TUG was associated with lower executive function, that is, a longer time to perform
the TMT-B and higher StroopInterference scores. The change in
R2 values attributed to the addition
of the TMT-B to the model was .063
(the difference between the full
model and the model with covariates
only). The overall change in R2 values was .13; therefore, the full model
explained 61.6% more variance than
the unadjusted model. The change in
R2 values attributed to the addition
of the Stroop-Interference measure
to the model was .043. The overall
change in R2 values was .087; therefore, the full model explained 59.2%
more of the variance than the unadjusted model. In the full models
for log(TUG), age, depressive symptoms, and BMI were statistically significant covariates, with higher values of log(TUG) (and, therefore,
slower performance on the TUG)
associated with higher values of BMI
and depressive symptoms.
Sex
Medical comorbidity
1204
(␤⫽.228, P⫽.002) findings were statistically significant after adjusting
for the other variables, indicating
that slower TUG times were associated with lower executive function
performance on both measures.
Physical Therapy
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Number 8
August 2011
toms, and BMI. Slower usual walking
speed was associated with lower
performance on a test of mental flexibility (TMT-B) and with reduced
ability to manage conflicting stimuli
(Stroop-Interference). Similarly, performance on a functional mobility
task (TUG at fast pace) was associated with both measures of executive function. The results of this
study demonstrate a consistent relationship between 2 commonly used
physical therapy assessment tools
and 2 measures of executive function. This finding is clinically relevant in older adults with memory
impairment because impairments in
physical and cognitive domains
increase the risk for accelerated
functional decline and disability,
especially in the presence of executive dysfunction.24
The prevalence of slowed gait speed
is evident when working memory is
challenged in older adults with
MCI,54 thus supporting the notion
that gait is not entirely automatic,
but instead requires attentional
resources.13,55 Physical performance
is particularly challenged when older
adults are asked to concurrently perform a cognitive task, suggesting that
allocation of attention is necessary
in older adults with and without
cognitive impairment.56 Associations
between physical performance and
cognitive function have been
reported in previous studies in the
areas of gait speed, balance, and fall
risk in older adults with MCI,9,57 and
they are especially robust in the presence of executive dysfunction.23
Declining executive function may be
an early indicator of overall functional decline in older adults. For
example, in a prospective study of
older women with intact cognition
at baseline, executive function decline
occurred 3 years prior to memory
decline over a 9-year follow-up period,
and executive function decline
occurred more often than any other
cognitive impairment.58 Sedentary
August 2011
older adults with aMCI may be particularly vulnerable to executive function
and mobility impairment and, therefore, at higher risk for subsequent
functional decline and falls.
Slowed physical performance may
be a compensatory strategy to maintain accuracy in older adults with
aMCI.59 People with MCI performed
daily activities at slower speeds, but
maintained accuracy on a series of
daily activities.60 Older adults with
probable AD who were asked to perform a cognitive task (repeating random digits) while walking demonstrated slower walking and greater
variability in their walking pattern,
possibly due to reduced ability to
divide or prioritize attention.55 A
similar phenomenon may be occurring in older adults with aMCI, with
a slowing of task speed in an effort to
maintain accuracy even under conditions of relatively low cognitive or
environmental challenge, as implemented in our study. Therefore,
older adults with aMCI may be particularly vulnerable to physical performance decline and fall risk on
tasks that require attention and learning, such as attending to a new walking route or other nonroutine activities. Although age and age-related
comorbid conditions may contribute
to declining physical performance
and executive dysfunction in older
adults with memory impairment, the
statistically significant associations
that remain after adjusting for these
factors in our study suggest that
other mechanisms, such as brain
pathology, may be contributing to
this relationship.
Medial temporal lobe structures,
which are responsible for memory
and learning, are the first brain
regions affected by AD pathology,
followed by other cortical and subcortical regions with disease progression.61,62 Pathology consistent with
AD has been reported in the brains
of older adults with aMCI63 and may
contribute to physical performance
impairment through alterations in
memory, attention, and executive
function networks.26,27 Alternatively,
in older adults with aMCI, pathological mechanisms associated with
declining physical performance may
result from pathology not typically
associated with AD, but instead
with other dementia syndromes
(eg, Parkinson disease, vascular disease) that interfere with frontalsubcortical circuits.27,64 Therefore,
further research is needed to identify neuropathological mechanisms
involved in the association between
physical performance speed and
executive dysfunction in older adults
with aMCI.
This study had a defined sample of
sedentary older adults with aMCI and
valid and reliable measures of physical performance and executive function. There were, however, several
limitations. A ceiling effect on the
TMT-B occurred with 8.0% of participants (final analysis) reaching the
300-second maximum, so we lack an
estimate of the slowest performance
possible on the TMT-B. The crosssectional nature of this study does
not allow for inferences of causation.
Nevertheless, consistent associations
were demonstrated, suggesting that
combining physical performance
and executive function assessments
may be clinically useful in detecting
early functional decline in older
adults with MCI. Although efforts
were made to minimize bias through
the selection of valid tests, consideration of potential confounders, and
recruitment practices,65 a potential
source of bias remains because this
sample of older adults was recruited
from independent retirement living
centers. Future longitudinal studies
to assess the predictive value of
executive function measures on
physical performance in people with
aMCI are needed.
Volume 91
Number 8
Physical Therapy f
1205
Conclusions
Slower physical performance was
associated with lower executive
function in our sample of sedentary
older adults with aMCI, and associations remained statistically significant after adjusting for age, sex,
depressive symptoms, medical comorbidity, and BMI. Slower gait and mobility associated with reduced executive
function in sedentary older adults
with aMCI have implications for
accelerated functional decline, disability, and institutionalization. Further research is needed to determine
mechanisms for this association and
whether early intervention strategies
are effective in slowing functional
decline and disability in sedentary
older adults with aMCI. Early intervention strategies that focus on
enhancing executive function as
well as physical performance (eg,
exercise) should be studied in sedentary older adults with aMCI.
Dr McGough, Dr Kelly, Dr Logsdon, Dr
McCurry, and Dr Teri provided concept/
idea/research design. All authors provided
writing. Dr McGough, Dr Logsdon, Dr
McCurry, and Dr Teri provided data collection. Dr McGough, Dr McCurry, and Dr Teri
provided data analysis. Dr Logsdon, Dr
McCurry, and Dr Teri provided project
management, fund procurement, participants, and facilities/equipment. Dr Teri
provided institutional liaisons. Dr Kelly,
Dr Logsdon, Dr McCurry, Dr Cochrane,
Dr Engel, and Dr Teri provided consultation (including review of manuscript
before submission). The authors thank the
Northwest Research Group on Aging, Ken
Pike, PhD, for statistical support, and June
van Leynseele, MA, for study coordination.
The University of Washington Institutional
Review Board approved the study
procedures.
A poster presentation of this research was
given at the Combined Sections Meeting
of the American Physical Therapy Association; February 17–20, 2010; San Diego,
California.
Dr McGough received support through a
National Institutes of Health Rehabilitation
Sciences predoctoral fellowship (grant 2T32HD-00742416A1), a National Institute of
Nursing Research/National Institutes of
1206
f
Physical Therapy
Volume 91
Health post-doctoral fellowship (grant T32
NR007106), and the de Tornyay Healthy
Aging Doctoral Scholarship (School of Nursing, University of Washington). This work
was supported by the National Institute on
Aging/National Institutes of Health (grant
2RO1 AG14777-06A2).
DOI: 10.2522/ptj.20100372
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Invited Commentary
Teresa Y. Liu-Ambrose
In their study,1 McGough and colleagues demonstrated that both
usual gait speed and Timed “Up &
Go” Test performance was significantly associated with executive
functions, after accounting for age,
sex, depressive symptoms, medical
comorbidity, and body mass index,
in a group of sedentary older adults
with memory-based mild cognitive
impairment (MCI). Their study highlights the co-occurrence of cognitive
and physical decline in the clinical
condition of MCI and reminds all of
us of the complexity of geriatric
rehabilitation.
Mild cognitive impairment is a wellrecognized risk factor for both
dementia2 and functional dependence.3,4 It is distinct from dementia
and is conceptually defined as a clinical entity that is characterized by
cognitive decline greater than that
expected for an individual’s age and
education level but that does not
notably interfere with activities of
daily living.2,5 It should be noted that
MCI exists across a cognitive continuum with borders that are difficult
to define precisely.2 Furthermore,
there is considerable etiological and
clinical heterogeneity within MCI.
However, given the consequences of
MCI, it is an important clinical entity
that requires timely recognition and
intervention.
Of particular relevance to the practice of physical therapy, McGough
and colleagues showed that older
adults with MCI have increased risk
for functional decline. Functional
decline is associated with progressive loss of independence, reduced
quality of life, greater risk for institutionalization, and increased mortality.6 –9 Older adults with MCI are at a
higher risk for functional decline in
part due to their increased risk for
1208
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Volume 91
falls. Previous studies have demonstrated that older adults with MCI
have impaired balance and gait10 –13
as well as impaired executive functions14 –16; each of these impairments
is associated with falls.17 For example, Anstey and colleagues18 found
that among older adults without cognitive impairment and dementia,
baseline cognitive performance in
the domain of executive functions
was inversely associated with rate of
falls over an 8-year period.
McGough and colleagues extend
these findings by highlighting the
independent association among gait
speed, mobility, and executive functions in this population of older
adults who are at significant risk for
dementia. In the last 5 years or so,
there has been a growing recognition that physical function and cognitive function are interrelated. Evidence from neuroimaging studies
provides insight into possible underlying mechanisms for this association. Specifically, cerebral white
matter lesions (or leukoaraiosis) are
associated with both reduced executive functions19 and gait and balance abnormalities.20 –23 Cerebral
white matter lesions may interrupt
frontal lobe circuits responsible for
normal gait and balance or they may
interfere with long loop reflexes
mediated by deep white matter sensory and motor tracts.22 In addition,
the periventricular and subcortical
distribution of white matter lesions
could interrupt the descending motor
fibers arising from medial cortical
areas, which are important for lowerextremity motor control.23 It is
important to note that many of the
pathological changes in the brain
(eg, white matter lesions, reduced
frontal-subcortical volume) associated with reduced executive functioning are clinically silent, but nev-
Number 8
ertheless prevalent in the senior
population.19 Thus, clinicians should
be aware that reduced executive
functioning is prevalent even among
community-dwelling older adults
without a formal diagnosis of cognitive impairment.24,25
Executive functions are higher-order
cognitive processes that control,
integrate, organize, and maintain
other cognitive abilities.26 These
cognitive processes are essential to a
person’s ability to carry out healthpromoting behaviors,27 such as
medication management, dietary and
lifestyle changes, self-monitoring of
responses, and follow-up with health
care professionals. Maintaining executive functions is strongly associated
with the ability to perform instrumental activities of daily living28 –33
and to live independently without
assistance.34,35
Thus, to optimally prevent functional decline, McGough and colleagues’ work emphasizes the need
for physical therapists to consider
cognitive function—in particular,
executive functions—in their management of older adults with
impaired gait and mobility. Currently, balance and resistance training exercises are commonly prescribed by physical therapists to
improve balance and mobility in
older adults. However, given the
associations among gait speed,
mobility, and executive functions, it
is time for physical therapists to
prescribe exercise to optimize executive functions. Current evidence
suggests that targeted aerobic exercise training36 or progressive resistance training37 has specific benefits
for executive functions. Importantly,
a recent study demonstrated that targeted aerobic exercise training can
significantly improve executive func-
August 2011
tions in older adults with amnestic
MCI.38 Other potential strategies
for enhancing executive functions
include cognitive training.39
Finally, to ensure optimal rehabilitation uptake and adherence, physical
therapists must work with older
adults to overcome the barriers
imposed by reduced executive functions. For example, they should
include family members or close
friends to facilitate uptake, use fridge
magnets to remind the older adult
the frequency and duration of prescribed exercises, provide easy-toread manuals that clearly illustrate
specific exercises, and provide calendars to track exercise adherence
and progression.
In summary, the work of McGough
and colleagues reinforces the notion
that for rehabilitation strategies to
effectively promote functional independence, they must be comprehensive in approach and not focus solely
on physical function.
T.Y. Liu-Ambrose, PT, PhD, Centre for Hip
Health, Vancouver Coastal Health Research
Institute, and Department of Physical Therapy, University of British Columbia, 3572647 Willow St, Vancouver, British Columbia,
Canada V5Z 3P1. Address all correspondence
to Dr Liu-Ambrose at: [email protected].
DOI: 10.2522/ptj.20100372.ic
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et al. Cardiovascular fitness, cortical plasticity, and aging. Proc Natl Acad Sci U S A.
2004;101:3316 –3321.
We thank Liu-Ambrose for her commentary1 on our work related to
physical performance and executive
function in older adults with mild
cognitive impairment.2 The associations between cognition and physical function in older adults with and
without clinically defined cognitive
impairment have important implications for physical therapy management strategies. Given the associations between executive function
and instrumental activities of daily
living,3,4 observations of everyday
activities provide clinically relevant
information for physical therapists
and may serve as early signs of functional decline.5 In addition, impairments in other cognitive domains,
such as memory, require involvement of caregivers and use of memory aids to achieve ongoing exercise
participation at an optimal dose.
Physical therapy strategies that
address physical, cognitive, environmental, and social barriers are necessary for achieving an optimal
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Volume 91
39 Willis SL, Tennstedt SL, Marsiske M, et al.
Long-term effects of cognitive training on
everyday functional outcomes in older
adults. JAMA. 2006;296:2805–2814.
Ellen L. McGough, Valerie E. Kelly, Rebecca G. Logsdon,
Susan M. McCurry, Barbara B. Cochrane, Joyce M. Engel, Linda Teri
Author Response
1210
37 Liu-Ambrose T, Nagamatsu LS, Graf P,
et al. Resistance training and executive
functions: a 12-month randomized controlled trial. Arch Intern Med. 2010;170:
170 –178.
38 Baker LD, Frank LL, Foster-Schubert K,
et al. Effects of aerobic exercise on mild
cognitive impairment: a controlled trial.
Arch Neurol. 2010;67:71–79.
response to exercise interventions in
older adults with and without clinically defined cognitive impairment.
As noted in our study and in the
commentary by Liu-Ambrose, cognitive and physical functioning are
associated in older adults, including
those with mild cognitive impairment, and these impairments
respond to physical therapy interventions. Early intervention strategies aimed at enhancing executive
function through aerobic and
strengthening interventions are warranted for improving gait function
and reducing fall risk.1,6 Indeed, our
own intervention research7 indicates
functional gains even among those
older adults with dementia. The
potential for physical therapy to
improve the lives of older adults is
clear. We look forward to continued
progress in this area and continued
dialogue.
DOI: 10.2522/ptj.20100372.ar
Number 8
References
1 Liu-Ambrose TY. Invited commentary on
“Associations between physical performance and executive function in older
adults with mild cognitive impairment: gait
speed and the Timed ‘Up & Go’ Test.” Phys
Ther. 2011;91:1208 –1210.
2 McGough EL, Kelly VE, Logsdon RG, et al.
Associations between physical performance and executive function in older
adults with mild cognitive impairment: gait
speed and the Timed “Up & Go” Test. Phys
Ther. 2011;91:1198 –1207.
3 Farias ST, Mungas D, Reed BR, et al. MCI is
associated with deficits in everyday functioning. Alzheimer Dis Assoc Disord. 2006;
20:217–223.
4 Johnson JK, Lui LY, Yaffe K. Executive function, more than global cognition, predicts
functional decline and mortality in elderly
women. J Gerontol A Biol Sci Med Sci.
2007;62:1134 –1141.
5 Wadley VG, Okonkwo O, Crowe M, RossMeadows LA. Mild cognitive impairment
and everyday function: evidence of reduced
speed in performing instrumental activities
of daily living. Am J Geriatr Psychiatry.
2008;16:416 – 424.
6 Liu-Ambrose T, Davis JC, Nagamatsu LS,
et al. Changes in executive functions and
self-efficacy are independently associated
with improved usual gait speed in older
women. BMC Geriatr. 2010;10:25.
7 Teri L, Gibbons LE, McCurry SM, et al. Exercise plus behavioral management in patients
with Alzheimer disease: a randomized controlled trial. JAMA. 2003;290:2015–2022.
August 2011
Research Report
A. Glässel, PT, BSc, MSc, MPH,
Swiss Paraplegic Research, Nottwil,
Switzerland, and ICF Research
Branch in cooperation with the
WHO Collaborating Centre for the
Family of International Classifications in Germany (DIMDI).
Content Validity of the Extended ICF
Core Set for Stroke: An International
Delphi Survey of Physical Therapists
Andrea Glässel, Inge Kirchberger, Barbara Kollerits, Edda Amann, Alarcos Cieza
Background. The “Extended ICF Core Set for stroke” is an application of the
International Classification of Functioning, Disability and Health (ICF) and represents the typical spectrum of problems in functioning of people with stroke.
I. Kirchberger, PhD, MPH, Institute for Health and Rehabilitation Sciences (IHRS), LudwigMaximilian University, Munich,
Germany, and ICF Research
WHO Collaborating Centre for
the Family of International Classifications in Germany (DIMDI).
Design and Methods. Physical therapists experienced in stroke intervention
B. Kollerits, PhD, MPH, Institute
for Health and Rehabilitation Sciences (IHRS), Ludwig-Maximilian
University, and ICF Research
were asked about their patients’ problems and resources and about aspects of the
environment that physical therapists treat in people with stroke in a 3-round
electronic-mail survey using the Delphi technique. The responses were linked to the
ICF. The degree of agreement was calculated using the kappa statistic.
E. Amann, PhD, MPH, Institute
for Health and Rehabilitation Sciences (IHRS), Ludwig-Maximilian
University.
Objective. The objective of this study was to validate this ICF Core Set from the
perspective of physical therapists.
Results. One hundred twenty-five physical therapists from 24 countries named
4,793 problems treated by physical therapists in people with stroke. They identified
10 second-level ICF categories that currently are not represented in the Extended ICF
Core Set for stroke. Twelve responses of the participants were linked to the ICF
component personal factors, and 15 responses were not covered by the current
version of the classification. The kappa coefficient for the linking agreement was 0.39
(95% bootstrapped confidence interval⫽0.34 – 0.41).
Limitations. Two World Health Organization regions were not represented in the
sample of physical therapists.
Conclusions. According to the physical therapists, the current version of the
Extended ICF Core Set for stroke largely covers the types of problems that their
interventions address. However, some aspects of functioning emerged that are not
yet covered and may need further investigation.
A. Cieza, PhD, MPH, Institute for
Health and Rehabilitation Sciences (IHRS), Ludwig-Maximilian
University, Marchioninistrasse 17,
81377 Munich, Germany; Swiss
Paraplegic Research, Nottwil,
Switzerland; and ICF Research
Address all correspondence to Dr
Cieza at: [email protected].
[Glässel A, Kirchberger I, Kollerits
B, et al. Content validity of the
Extended ICF Core Set for stroke:
an international Delphi survey of
physical therapists. Phys Ther.
2011;91:1211–1222.]
Association
2011
Submitted: August 12, 2010
this article at:
ptjournal.apta.org
August 2011
Volume 91
Number 8
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Extended ICF Core Set for Stroke From Physical Therapists’ Perspective
A
nnually about 15 million people worldwide experience a
stroke.1 Although stroke is
one of the leading causes of mortality, 40% to 77% of those affected
are still alive 1 year after the event.2
One third of the survivors face
long-term disability. Disability after
stroke appears in the form of neurological dysfunctions (eg, motor, sensory, visual), limited ability to perform activities of daily living (ADL),
and neuropsychological deficits
(memory, attention, language).3 Taking the diversity and complexity of
consequences of a stroke into
account,
an
interdisciplinary
approach is most appropriate. Rehabilitation after stroke requires an
interprofessional team including
physicians, psychologists, occupational therapists, nurses, social workers, and physical therapists.4,5
Physical therapists are described as
one of the key components of the
interdisciplinary team in stroke rehabilitation.6 – 8 Particularly, physical
therapy aims at restoring motor control in locomotion, improving upperlimb function, enhancing the ability
of people with stroke to cope with
existing deficits in ADL, and achieving the best possible participation in
the community. In order to reach
these rehabilitation goals, physical
therapists use different neurological
intervention approaches and instruct
and advise people with stroke and
their families regarding prevention
of complications, such as falls and
shoulder pain.9,10
To optimize interventions aimed at
improving function and minimizing
disability, a proper understanding
of an individual’s functioning and
health status is needed.4 The World
Health Organization’s International
Classification of Functioning, Disability and Health (ICF)11 is based
on an integrative model of health
that provides a holistic, multidimensional, and interdisciplinary under1212
f
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Volume 91
standing of health and health-related
conditions. According to the ICF, the
problems associated with a disease
may concern body functions and
body structures and the performance of activities and participation in life situations. Health states
and the development of disability are
modified by contextual factors, including environmental factors and personal factors.11 The ICF comprises
1,454 categories from the components body functions, body structures, activities and participation,
and environmental factors, which are
organized in a hierarchical structure
(Fig. 1). Categories are divided into
chapters, which constitute the first
level of specification. Higher-levels
categories (eg, second, third, or
fourth level) are more detailed.
Both the content and the structure of
the ICF point out the potential value
for rehabilitation professions, especially physical therapy.5 The ICF is
increasingly applied in physical therapy and rehabilitation, especially in
the field of neurorehabilitation, to
facilitate interdisciplinary team communication, to structure the rehabilitation process, for goal setting and
assessment, and for documentation
and reporting.12,13 Recently, ICFbased documentation tools have
been developed for use in interdisciplinary rehabilitation management.14
However, the ICF as a whole is not
feasible for use in routine clinical
application. To facilitate the implementation of the ICF into clinical
practice, “ICF Core Sets” have been
developed.15,16 The ICF Core Sets
include a selection of ICF categories
relevant for people with a specific
health condition or a specific intervention phase (eg, acute or postacute care).15 The development of
the ICF Core Set followed a standard
approach that included a formal
decision-making and consensus process integrating evidence gathered
from preparatory studies by expert
Number 8
neurologic health care professionals.
Preparatory studies included a
worldwide Delphi study with 36
experts, including 7 physical therapists; a systematic review of outcome measures used in 160 stroke
clinical trials; and an empiric data
collection on 93 German patients
with stroke.17–19 Based on the results
of these studies, a panel of 36 stroke
experts (25 physicians, 7 physical
therapists, 2 psychologists, 1 social
worker, and 1 sociologist) from 12
different countries decided on the
composition of the “Comprehensive
ICF Core Set for stroke” in a formal
consensus process. The Comprehensive ICF Core Set for stroke includes
a set of 130 ICF categories that cover
the typical spectrum of problems in
functioning in people with chronic
stroke.20 It was extended by 36 ICF
categories from the ICF Core Sets for
people with neurological conditions
in the acute and early postacute
phases to enable its use it in all clinical situations.20,21
Based on this Extended ICF Core
Set for stroke, physical therapists
can comprehensively describe the
impairments, limitations in activities,
restriction in participation, and influential environmental factors of a
determined person with stroke and
can create a functioning profile. The
Extended ICF Core Set for stroke can
facilitate assessment and offers the
opportunity to clarify responsibilities among the team members by distributing the information gathered
from specific ICF categories to the
appropriate team members.13,22
The Extended ICF Core Set for stroke
is now undergoing worldwide testing using a number of approaches,
including international multicenter
field studies, reliability studies,23 and
content validation from the health
care professional perspective. Content validity from the health care
professional perspective means that
at least those problems in functionAugust 2011
ICF
Fuctioning and Disability
Body Functions
and Structures
Activities and
Participation
Classification
Contextual factors
Parts
Personal
Factors
Not classified
Environmental
Factors
Components
Categories
b1-b8
s1-s8
d1-d9
e1-e5
Chapter/
1st level
b110b899
s110s899
d110d999
e110e599
2nd level
b1100b7809
s1100s8309
d1550d9309
e1100e5959
3rd level
b11420b54509
s11000s76009
4th level
Figure 1.
Structure of the World Health Organization’s International Classification of Functioning, Disability and Health (ICF). Reprinted with
permission of the World Health Organization. All rights are reserved by the World Health Organization.
ing that are substantial targets of the
specific interventions applied by
health care professionals are represented in the ICF Core Set for stroke.
This is a prerequisite for the implementation of the ICF Core Set for
stroke in clinical practice. For example, if joint mobility is a main intervention target of physical therapists,
it is essential that physical therapists
document the extent and the change
of joint mobility problems in a determined patient during the treatment
course using the ICF Core Set for
stroke. Consequently, if the corresponding ICF category for joint
mobility is not included in the current version of the Core Set for
stroke, the Core Set is lacking content validity from the perspective of
physical therapists.
The purpose of this study was to
examine the content validity of the
Extended ICF Core Set for stroke
from the perspective of physical
therapists. The aims of this study
August 2011
were: (1) to identify the patient’s
problems, resources, and aspects of
environment treated by physical
therapists and (2) to analyze whether
these issues are represented by the
current version of the Extended ICF
Core Set for stroke.
Method
A 3-round electronic-mail survey of
physical therapists using the Delphi
technique was conducted.24 –27 The
purpose of the Delphi technique is
to gain consensus from a panel of
individuals who have knowledge of a
topic being investigated.28 These
informed people are commonly
called experts.29 The Delphi method
is a multistage process, with each
stage building on the results of the
previous one, and a series of rounds
are used to both gather and provide
information about a particular subject. The technique is characterized
by its anonymity to avoid the dominance of single individuals in a
group; by iteration, which allows
panel members to change their opinions in subsequent rounds; and by
controlled feedback, which shows
the distribution of the group’s
responses as well as each individual’s previous responses.30
Recruitment of Participants
In the preparatory phase of the
study, international associations of
physical therapists, such as the World
Confederation for Physical Therapy
(WCPT) and members of the European Region of WCPT, as well as universities with health care professional
programs and members of the Association of Higher Education of Physical
Therapy (ENPHE) were contacted.
Associations with a focus on neurorehabilitation and certified physical
therapists in neurological intervention from United States received an
invitation to participate. A literature
search and personal recommendations were used to identify experts.
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First Round
Activities of study group
The participants received an e-mail with general
information and instructions as well as a
questionnaire with the following open-ended
question:
“What are the patients’ problems, patients’ resources,
and aspects of the environment treated by physical
therapists in patients with stroke?”
Activities of experts
Creating a list of patients’ problems,
patients’ resources, and aspects
of the environment treated by
physical therapists in patients
with stroke
• Linking of responses to ICF categories
Second Round
The participants received an e-mail with instructions
and the questionnaire for the second round with
the following question:
“Do you agree that these ICF categories represent
patients’ problems, patients’ resources, or aspects of
the environment treated by physical therapists
in patients with stroke?”
Judgment (yes/no), whether the
listed ICF categories reflect the
treatment by physical therapists in
patients with stroke
• Calculation of frequencies (%)
• Feedback of individual judgment
• Feedback of group answer
Third Round
The participants received an e-mail with instructions
and the questionnaire for the third round with
the following question:
“Taking into account the answers of the group and your
individual answer in the second round, do you agree
that these ICF categories represent
patients’ problems, patients’ resources, or aspects of
the environment treated by physical therapists
in patients with stroke?”
Judgment (yes/no), whether the
listed ICF categories reflect the
treatment by physical therapists in
patients with stroke
• Calculation of frequencies (%)
Figure 2.
Description of the Delphi exercise.
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August 2011
The sample was selected using a purposive sampling approach, which is
commonly applied in Delphi studies.25,31,32 Purposive sampling is
based on the assumption that a
researcher’s knowledge about the
population can be used to handpick
the cases to be included in the sample.33 In contrast to random sampling, purposive sampling does not
ensure representativeness. Because
no database of the target population
of physical therapists worldwide
who are experienced in the treatment of patients with stroke was
available, random sampling was not
possible in our study.
To ensure that the participants were
experienced in the management of
people poststroke, the initial letter
specified that participants should be
“physical therapy experts in the
treatment of poststroke individuals.”
The first contact included an invitation to participate and a detailed
description of the project’s targets,
the Delphi process, and the time
line. The study was conducted from
January to August 2005.
Delphi Process
The process and verbatim questions
of the electronic-mail survey using
the Delphi technique are displayed
in Figure 2. The participants had 3
weeks to mail their responses for
each round. Reminders were sent 1
week and 2 days before the deadline
and 1 week after the deadline. The
study was conducted in the English
language.
In the first round of the Delphi procedure, an information letter including instructions and an Excel* file
containing an open-ended questionnaire was sent to all participants. The
participants were requested to list all
of the “patients’ problems, patients’
resources, and aspects of environ* Microsoft Corporation, One Microsoft Way,
Redmond, WA 98052-6399.
August 2011
Figure 3.
Scree test results for second Delphi round. Selection of International Classification of
Functioning, Disability and Health (ICF) categories without clear consensus using the
modified Scree test. The ICF categories of the second Delphi round were ordered by
percentage of expert agreement and plotted. The Scree line was placed onto the slope,
along the points to see where they approximately form a straight line. Points close to
the Scree line indicate an inadequate endorsement. Cutpoints were defined as the points
where the slope markedly deviated from the Scree line. The ICF categories with an
agreement of ⬎25.2% and ⬍90.7% were included in the third Delphi round.
ment treated by physical therapists
in patients with stroke.” The phrasing of this question aimed at encouraging the participants to consider
not only problems but also resources
and environmental factors that are
covered by the ICF model. The
responses were collected and linked
to the ICF. Additionally, the participants were asked to complete questions on demographic characteristics
and professional experience.
In the second Delphi round, the participants received a list of the ICF
categories linked to the responses of
the first round. The participants
were requested to agree or disagree
that the respective ICF category represents patients’ problems, patients’
resources, or aspects of the environment treated by physical therapists
in patients with stroke. Again, the
number of participants considering
the listed ICF categories as relevant
was calculated.
In order to maintain the participants’
motivation and increase the response
rates, the participants of the third Delphi round received only a selection of
ICF categories included in the second
round. The Scree test was used to
identify the categories that did not
reach an adequate consensus.34,35
The Scree test includes an examination of a graph of the percentage of
agreement among the participants
plotted along the vertical axis against
the ICF categories plotted along the
horizontal axis. A straightedge is
placed along the points to see where
they form an approximately straight
line, the Scree line. Points close to the
Scree line indicated an insufficient
endorsement (Fig. 3). The participants
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received a list of the selected ICF categories, including the proportion and
the identification numbers of the participants who had agreed that the
categories represent patients’ problems, patients’ resources, or aspects of
the environment treated by physical
therapists in individuals after stroke.
The participants were requested to
answer the same question taking into
account the answers of the group, as
well as their previous response.
Linking
An ICF category is coded by the component letter and a suffix of 1 to 5
digits. The letters b, s, d, and e refer
to the components body functions
(b), body structures (s), activities
and participation (d) and environmental factors (e) (Fig. 1). This letter is followed by a 1-digit number
indicating the chapter, the code for
the second level (2 digits), and the
codes for the third and fourth levels
(1 digit each). The component letter
with the suffixes of 1, 3, 4, or 5 digits
corresponds to the code of the ICF
categories. Within each component,
the categories are arranged in a
stem/branch/leaf
scheme.
This
scheme indicates that a moredetailed, higher-level category covers all the aspects applicable for the
lower-level category, of which it is a
member, but not vice versa.
Each response from the first Delphi
round was linked to the most precise ICF category based on 10 linking rules established in a previous
study.36 If an answer contained more
than one concept, several ICF categories could be linked. Answers
related to personal factors were
assigned the code “pf.” If the content
of an answer was not included in the
ICF classification, this answer was
coded “not covered.”
The linking was performed by a
physical therapist (A.G.) who specialized in stroke intervention. In
addition, responses from 46 partici1216
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pants (36.8%) out of the 125 participants were linked independently by
a psychologist (E.A., B.K.). The people involved in the linking process
had some years of experience
regarding the ICF. Because the linking process is extremely timeconsuming and the linking of a sample of the 4,793 responses was
expected to provide a good estimation of the true agreement, we
refrained from linking all responses.
Consensus between the physical
therapist and the psychologist was
used to decide which ICF category
should be linked to each response.
In cases of disagreement between
the health care professionals, the
suggested categories were discussed
by a team consisting of psychologists
(E.A., B.K., I.K.) and a physical therapist (A.G.) aimed at a joint decision.
Statistical Methods
Statistical analysis was performed
using SAS for Windows, version 6.†
Descriptive statistics were used to
characterize the sample and frequencies of responses. The agreement
between the individuals who performed the linking was described
using the percentage of agreement
and kappa statistics with bootstrapped confidence intervals.37,38
The values of the kappa coefficient
generally range from 0 to 1, where 1
indicates perfect agreement and 0
indicates no additional agreement
beyond what is expected by chance
only.
The percentage of participants who
agreed with the question of the second and third Delphi rounds was calculated. Only ICF categories that
reached consensus among the participants in the third round were
considered for comparison with the
Extended ICF Core Set for stroke.
Lacking a universally accepted definition of consensus,31 an agreement
of at least 75% among the participants was considered sufficiently
high, based on experiences in previous studies.16,31
Results
Recruitment and Participants
Seventy-eight national physical therapy associations and 54 European
associations named 23 participants.
Three participants were named by
the European Federation of NeuroRehabilitation (EGNR). Seventeen
certified experts in neurology from
the United States agreed to participate. Nine universities with specialization in neurology named 11 participants, and 6 Bobath instructors
agreed to participate. Two participants were identified by literature
searches. Thirty-two international
and 8 national partners from the ICF
Network for stroke were contacted.
Five of them agreed to participate.
The remaining 80 physical therapists
who participated in this study were
contacted on the basis of personal
recommendations of other participants (“snowball sampling”). In
total, 146 physical therapists from 24
countries agreed to participate.
One hundred twenty-five (85.6%)
out of 146 physical therapists who
agreed to participate in the study
completed the first-round questionnaire. The demographic and professional characteristics of these participants are shown in Table 1.
Delphi Process
In the first Delphi round, 4,793
patients’
problems,
patients’
resources, or aspects of the environment treated by physical therapists
in patients with stroke were named.
One hundred eleven out of 125 participants (88.8%) filled in the second
round questionnaire. One hundred
one (90.9%) out of 111 physical therapists completed the third-round
questionnaire.
†
SAS Institute Inc, 100 SAS Campus Dr, Cary,
NC 27513-2414.
Number 8
August 2011
Table 1.
Distribution of the Participants About 3 Delphi Rounds and Demographic and Professional Experience of the Participants From
Round 1a
Professional
Experience (y),
Median
(Range)
Practical
Experience
With Patients
With Stroke
(y), Median
(Range)
Self-rating
Stroke
Treatment
Expertisec
(y), Median
(Range)
Round 1
(n)
Round 2
(n)
Round 3
(n)
%
Female
Age (y),
Median
(Range)
Regions of the
Americas
28
25
23
85.10
39.0 (31.0–51.0)
15.0 (6.0–30.0)
13.0 (5.0–28.0)
4.0 (3.0–5.0)
European region
91
81
73
80.20
42.0 (22.0–67.0)
16.0 (1.0–40.0)
13.0 (1.0–35.0)
4.0 (3.0–5.0)
4
3
3
100.00
43.5 (28.0–47.0)
21.5 (6.0–25.0)
16.5 (3.0–25.0)
4.0 (3.0–4.0)
4.25 (4.0–4.5)
WHO Regionb
Western Pacific
region
African region
Total
2
2
2
50.00
51.5 (35.0–68.0)
26.5 (11.0–42.0)
26.5 (13.0–40.0)
125 (87.4%)
111 (88.8%)
101 (90.9%)
77.9%
40.0 (22–68)
16.0 (1–42)
13.0 (1–40)
4.0 (3–5)
a
WHO⫽World Health Organization.
Region of Americas: Brazil, Canada, Jamaica, and United States; European region: Austria, Belgium, Czech Republic, Finland, Germany, Hungary, Israel,
Italy, Netherlands, Norway, Spain, Sweden, Switzerland, Turkey, and United Kingdom; Western Pacific region: Australia, Japan, and New Zealand; African
region: Nigeria and South Africa; Eastern Mediterranean region: not represented; South East Asia region: not represented.
c
1⫽low, 5⫽excellent.
b
Linking of the Responses
to the ICF
All components of the ICF were represented by 376 identified ICF categories. Seven fourth-level categories,
80 third-level categories, and 59
second-level categories were linked
to the component body functions.
Two fourth-level categories, 12 thirdlevel categories, and 10 second-level
categories were linked to the component body structures. Sixty-seven
third-level categories and 53 secondlevel categories were linked to the
component activities and participation. Twenty-seven third-level categories and 37 second-level categories
were linked to the component environmental factors. Fifteen aspects
were named that could be attributed
to the not-yet-developed ICF component personal factors. Fifteen
responses were not covered by the
current version of the ICF. Agreement between the 2 people who performed the linking was reached in
42% of the responses. The kappa
value for the linking was 0.39, with a
95% bootstrapped confidence interval of 0.34 to 0.41.
August 2011
Representation of the Physical
Therapists’ Responses in the ICF
Core Set for Stroke
In total, from the 376 ICF categories
linked to the participants’ responses,
185 reached an agreement of at least
75% in the final round and were considered for comparison with the
Of the 83 ICF categories linked to
body functions, 26 are included on
the same level of classification and
48 are more-detailed third- and
fourth-level categories, which are
represented by the corresponding
second-level categories (eg, “b1300
Energy level,” which is represented
in the Extended ICF Core Set for
stroke by the second-level category
“b130 Energy and drive functions”)
(Tab. 2). Ten ICF categories that correspond to the 4 second-level ICF
categories “b445 Respiratory muscle
function,” “b720 Mobility of joint
functions,” “b765 Involuntary movement functions,” and “b780 Sensations related to muscles and movement functions” are not represented
stroke (Tab. 2).
Of the component body structures,
23 ICF categories reached an agreement of ⱖ75%. Among these, 6 categories are included in the Extended
ICF Core Set for stroke at the same
level of classification, whereas 9 categories were represented at a different level of the classification. Three
second-level ICF categories and 5
corresponding third-level categories
are not represented in the Extended
ICF Core Set for stroke (Tab. 2).
Of the 67 ICF categories from the
ICF component activities and participation that reached an agreement of ⱖ75%, 23 are included at the
same level of the classification and
42 more-detailed, third-level categories are represented in the Extended
ICF Core Set for stroke by their corresponding second-level categories.
Two ICF categories, namely “d435
Moving objects with lower extremities” and “d6504 Maintaining assistive devices,” are not represented in
the Extended ICF Core Set for stroke
(Tab. 2).
Of the component environmental
factors, 9 categories reached an
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Table 2.
International Classification of Functioning, Disability and Health (ICF) Categories That
Are Not Represented in the Current Version of the ICF Core Set for Stroke:
Percentage of Participants Who Considered the Respective ICF Category as Relevant
in the Final Round (Round 3)a
ICF
Code
Level 2
ICF
Code
Level 3
Title of ICF Category
Final Round
(nⴝ101), %
Body functions
b445
Respiratory muscle functions
b720
Mobility of bone functions
98.2
b765
Involuntary movement functions
93.6
b7650
Involuntary contractions of muscles
86.8
b7651
Tremor
92.9
Sensations related to muscles and movement
functions
99.1
b7800
Sensation of muscle stiffness
98.1
b7801
Sensation of muscle spasm
95.5
Structure of pelvic region
90.7
b780
100.0
Body structures
s740
Muscles of pelvic region
96.3
s760
s7402
Structure of trunk
92.5
s770
Additional musculoskeletal structures related to
movement
94.0
s7700
Bones
89.5
s7701
Joints
96.3
s7702
Muscles
96.2
s7703
Extra-articular ligaments, fasciae, extramuscular
aponeuroses, retinacula, septa, bursae,
unspecified
90.7
Moving objects with lower extremities
98.2
Maintaining assistive devices
83.0
Assistive products and technology for culture,
recreation, and sport
77.7
Activities and participation
d435
d6504
Environmental factors
e1401
a
Only categories with agreement of ⱖ75% are shown.
agreement of ⱖ75%. Of these, 5
categories are included at the same
level of classification in the Extended
ICF Core Set for stroke, whereas 3
categories were represented at a different level of the classification. The
ICF category “e1401 Assistive products and technology for culture, recreation and sport” is not represented
stroke (Tab. 2).
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Twelve responses were assigned to
the not-yet-developed ICF component personal factors and reached
an agreement surpassing 75%. Most
of them addressed attitudes supporting the independence of a person
with stroke in managing his or her
disease (eg, self-management, compliance, autonomy/independence).
Autonomy, compliance, self-concept
and self-management, illness knowl-
Number 8
edge, and coping were considered to
comprise personal factors according
to the ICF language. In addition,
“brain plasticity” and “recovery”
were identified as personal factors
representing relevant aspects of
stroke intervention by physical therapists (Tab. 3). Fifteen responses of
the participants were not covered by
any ICF component or specific ICF
category out of the classification
(Tab. 3).
Discussion
This study examined the content
validity of the Extended ICF Core Set
for stroke from the perspective of
physical therapists. In this study,
content validity refers to the extent
to which the patients’ problems,
patients’ resources, and environmental factors identified by physical therapists as relevant to their management of people with stroke are
represented in the Extended ICF
Core Set for stroke. An agreement of
at least 75% among the participants
in the final Delphi round was
regarded as sufficient consensus.
Consequently, ICF categories with
an agreement of at least 75% that are
not represented in the Extended ICF
Core Set for stroke may indicate
missing content validity and will be
the main focus of the following
discussion.
A 100% agreement among the participants was found regarding the
category “b445 Respiratory muscle
function.” However, this ICF category is not included in the Extended
ICF Core Set for stroke. Several studies have demonstrated that problems
associated with strength (forcegenerating capacity) and endurance
of respiratory muscles, as well as
with muscles of the trunk and the
position of the diaphragm, are
important risk factors for secondary
complications after stroke such as
pneumonia.39 In order to minimize
these risks, physical therapists use
respiratory exercises, including
August 2011
training of respiration and specific
intervention techniques, to activate
or relax respiratory muscles.40
The participants addressed nearly all
of the different categories from the
ICF chapter “Neuro-musculosceletal
and Movement-Related Functions,”
which covers functions of joints,
bones, reflexes, and muscles.11
These aspects clearly represent one
main focus of the physical therapists’
work in stroke rehabilitation. However, although the ICF category
“b720 Mobility of bone functions”
reached an agreement of 98.2%
among the participants, it is not
included in the ICF Core Set for
stroke. Bone mobility is a prerequisite for activities such as grasping a
glass. Bone mobility is treated by
physical therapists using different
manual techniques (eg, mobilization
of the scapulae in people with shoulder pain after stroke).41
Furthermore, more than 90% of the
participants agreed that the ICF category “b765 Involuntary movement
functions” is a problem treated by
physical therapists, which is not
included in the ICF Core Set for
stroke. This finding is clearly supported by literature, which reports a
close relationship between stroke
and spasticity (hypertonicity) and
the incidence of clonus or
tremor.42,43 In addition, validation
studies have identified this ICF category as being relevant for occupational therapists44 and physicians.45
Regarding the ICF category “b780
Sensations related to muscles and
movement functions,” which is not
represented in the ICF Core Set for
stroke, again a high consensus
among the participants was found. It
is quite obvious that people with
stroke experience stiffness and tightness of muscles. Muscle spasms and
heaviness of muscles are commonly
treated by physical therapists.40
August 2011
Table 3.
Responses That Were Linked to the International Classification of Functioning, Disability
and Health (ICF) Component Personal Factors and “Not Classified” Terms:
Percentage of Participants Who Considered the Respective Concepts As Relevant in
the Final Round (Round 3)a
Final Round
(nⴝ101), %
Personal Factors
Autonomy, independence
97.3
Brain plasticity/recovery
97.2
Self-concept, self-perception
95.9
Endurance/discipline, hardiness
93.8
Coping
92.8
Optimistic/positive attitude
92.8
Compliance
92.7
Self-management
91.8
Illness knowledge
91.8
Problems/worries/uncertainty about future
88.6
Sense of mastery
88.5
Life values, life goals, lifestyle
87.6
Final Round
(nⴝ101), %
Not Classified
a
Posture/postural alignment
99.1
Adaptation to bodily changes/compensation strategies
98.1
Secondary complications
98.1
Multiprofessional and interdisciplinary treatment
97.2
Therapeutic positioning
97.2
Assessment of the patient and evaluation
96.3
Impairment of body symmetry
96.3
Positive model for living with a handicap
95.8
Education of self and family about stroke
95.4
Physical therapy intervention
95.2
Perspective of life (living at home, profession)
92.7
Learning experience in dealing with limitations
92.7
Conveying problem to others and their understanding
91.8
Competence in self-relaxation
91.8
Self-observation
91.8
Only concepts with agreement of ⱖ75% are shown.
With regard to the ICF component
body structures, 3 ICF categories
were found not to be included in the
current version of the ICF Core Set
for stroke. Spasticity and muscle
imbalance in lower limbs, which are
major problems after stroke, are
associated with walking problems.
Improvement of multijoint coordination and improvement of muscle
activity in the lower limbs, including
the pelvis, are relevant intervention
goals for physical therapists. However, the ICF category “s740 Structure of pelvic region” is currently not
included.
The ICF category “s760 Structure of
trunk,” including bones, muscles,
and ligaments of the trunk, repre-
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1219
sents a main intervention area of
physical therapy after stroke because
hemiplegia not merely results in
diverse problems in the upper and
lower extremities but also affects the
trunk and its corresponding structures.46,47 Finally, the ICF category
“s770 Additional musculoskeletal
structures related to movement”
addresses structures that still are not
sufficiently mapped in the ICF. For
instance, muscles of the neck frequently are affected in neglect.48
Regarding the ICF component activities and participation, the ICF category “d435 Moving objects with
lower extremities” was regarded as
relevant by the participants, but this
category is not included in the ICF
Core Set for stroke. Indeed, people
with stroke have impairments in
structure and functioning of the feet,
such as decreased muscle power or
problems with spasticity or flaccid
muscles, that can lead to difficulties
with pushing pedals on a bicycle or
pressing the gas pedal of a car.49,50
On the other hand, problems with
riding a bicycle or driving a car are
covered by the ICF category “d475
Driving,” which is already part of the
The high level of agreement among
the participants regarding the ICF
categories related to assistive devices
such as “e115 Products and technology for personal use in daily living”
highlights the relevance of a restoratory and compensatory rehabilitation strategy. Education and training
on the use and maintenance of assistive devices are an inherent part of
physical therapy. However, the ICF
categories “e1401 Assistive products
and technology for culture, recreation, and sport” and “d6504 Maintaining assistive devices” are not yet
included in the Extended ICF Core
Set for stroke.
Twelve aspects were linked to the
not-yet-developed ICF component
1220
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Physical Therapy
Volume 91
personal factors. Patients’ selfmanagement, illness knowledge, and
ability to cope with the disease are
relevant for patient education provided by physical therapists.51 Various studies and systematic reviews
support the positive effects of
patient education regarding selfmanagement51 and coping with disease.52 These results indicate that
personal factors also are considered
by physical therapists. Therefore, it
could be most helpful for physical
therapists if the ICF would provide a
classification of the personal factors
in the future. This classification will
enable health care professionals to
identify systematically all personal
factors influencing the functioning
of a certain person.
Posture/postural alignment was
regarded as a relevant aspect by
almost all of the participants; however, this aspect is not covered by
the ICF. Although the ICF category
“d415 Maintaining a body position”
covers the static aspects of posture,
the dynamic aspects of posture are
missing. Thus, it could be useful to
develop an ICF category addressing
posture/postural alignment more
specifically. However, when increasing the specificity of such an ICF
category, it should be kept in mind
that the ICF should be used by all
health care professions and, therefore, physical therapy–specific terminology should be avoided.
In general, the participants named a
large number of detailed aspects,
represented by third- and fourthlevel ICF categories, which are relevant for stroke intervention. This
detailed information is necessary for
assessment, therapy planning, and
intervention in physical therapy. As
the ICF Core Set includes only lessspecific, second-level categories, this
detailed information might be unfavorable for physical therapist practice on the one hand. On the other
hand, the current version of the
Number 8
already includes 166 second-level
ICF categories, and any further
extension could compromise its feasibility in clinical practice.
The Delphi technique proved to be
an appropriate method for this
study objective. With response rates
exceeding 87% in the present study,
previously reported response rates
of approximately 50%30,33,53 were
clearly surpassed. However, there
are some limitations regarding the
reliability and external validity of this
study.
The agreement between the people
who performed the linking was
lower than in other studies that used
comparable methods.54 –56 This finding may be related to the fact that the
answers of the participants were longer and, therefore, the extraction of
the meaningful concepts was more
difficult than in similar studies
regarding other health conditions.
Consequently, the instructions for
the first round were revised for their
use in future studies. Furthermore,
as we have only linked a sample of
the responses, we cannot exclude
that the agreement would have
been different in another sample of
responses.
Although we were successful in
recruiting physical therapists from
24 countries, the African and Eastern
Mediterranean world regions are not
represented in the sample. Health
care systems in these world regions
may differ from those of other world
regions, and it cannot be excluded
that this difference also affects the
intervention targets of physical therapists in stroke treatment. Thus, the
sample is not representative of all
physical therapists experienced in
the intervention of people with
stroke worldwide. Language barriers
could have influenced the participation in some world regions because
August 2011
the Delphi survey was conducted in
English language only.
Although some restrictions of the
current version of the Extended ICF
Core Set for stroke were detected in
this study, we found the categories
of the current version of the
largely represent what the physical
therapists in our study agreed upon
to take care of in their interventions.
The results of finalized or ongoing
studies involving both health care
professionals44,45 and patients will
further elucidate the validity of the
from the different perspectives. A
number of ICF categories identified
as missing in the current version of
the Extended ICF Core Set for stroke
by occupational therapists44 also
were mentioned by the participants
in our study. These ICF categories
included “b720 Mobility of bone
functions” and “b765 Involuntary
movement functions” from the component body functions, “s760 Structure of trunk” and “s770 Additional
musculoskeletal structures related to
movement” from the component
body structures, “d435 Moving
objects with lower extremities” and
“d650 Caring for household objects”
from the component activities and
participation, and “e140 Products
and technology for culture, recreation, and sport” from the component environmental factors. In contrast to physical therapists and
occupational therapists, physicians
have found only 4 ICF categories that
are relevant for their treatment but
not yet part of the current version of
the Extended ICF Core Set for
stroke.45 Of interest, the ICF category “b765 Involuntary movement
functions” was mentioned as relevant by all 3 health care professions.
Thus, this category would be a good
candidate for inclusion in the
August 2011
The validation from the perspective
of 3 different health care professions has shown that it might be
useful to add relevant ICF categories
to the Extended ICF Core Set for
stroke.44,45 On the other hand, studies that have applied the Extended
ICF Core Set for stroke in a sample of
people with stroke have identified
ICF categories that are less relevant
and might be excluded.57,58
However, the validation from the
patient perspective is not yet completed. It seems reasonable that a
final decision on the content of a
revised version of the Extended ICF
Core Set for stroke should be postponed until the results from the
patient perspective are available and
can be included in the discussion.
All authors provided concept/idea/project
design. Ms Glässel, Dr Kirchberger, and Dr
Cieza provided writing. Ms Glässel provided
data collection. Ms Glässel, Dr Kirchberger,
Dr Kollerits, and Dr Amann provided data
analysis. Ms Glässel and Dr Kirchberger provided project management. Dr Kirchberger
and Dr Cieza provided consultation (including review of manuscript before submission).
The authors thank the participants of the
Delphi exercise for their valuable contribution and their time in responding to the
questionnaires.
This study forms part of Ms Glässel’s doctoral
thesis at the Faculty of Medicine, LudwigMaximilian University, Munich, Germany.
This research, in part, was presented at the
16th International Congress of the World
Confederation for Physical Therapy; June
20 –33, 2011; Amsterdam, the Netherlands.
The responsibility for the content of this publication lies within the ICF Research Branch.
DOI: 10.2522/ptj.20100262
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August 2011
Research Report
Association of Body Mass Index With
Self-Report and Performance-Based
Measures of Balance and Mobility
Andrea L. Hergenroeder, David M. Wert, Elizabeth S. Hile, Stephanie A. Studenski,
Jennifer S. Brach
Background. The incidence of obesity is increasing in older adults, with associated worsening in the burden of disability. Little is known about the impact of body
mass index (BMI) on self-report and performance-based balance and mobility measures in older adults.
Objective. The purposes of this study were (1) to examine the association of BMI
with measures of balance and mobility and (2) to explore potential explanatory
factors.
Design. This was a cross-sectional, observational study.
Methods. Older adults (mean age⫽77.6 years) who participated in an ongoing
observational study (N⫽120) were classified as normal weight (BMI⫽18.5–24.9
kg/m2), overweight (BMI⫽25.0 –29.9 kg/m2), moderately obese (BMI⫽30.0 –34.9
kg/m2), or severely obese (BMIⱖ35 kg/m2). Body mass index data were missing for
one individual; thus, data for 119 participants were included in the analysis. Mobility
and balance were assessed using self-report and performance-based measures and
were compared among weight groups using analysis of variance and chi-square
analysis for categorical data. Multiple linear regression analysis was used to examine
the association among BMI, mobility, and balance after controlling for potential
confounding variables.
Results. Compared with participants who were of normal weight or overweight,
those with moderate or severe obesity were less likely to report their mobility as very
good or excellent (52%, 55%, 39%, and 6%, respectively); however, there was no
difference in self-report of balance among weight groups. Participants with severe
obesity (n⫽17) had the lowest levels of mobility on the performance-based measures,
followed by those who were moderately obese (n⫽31), overweight (n⫽42), and of
normal weight (n⫽29). There were no differences on performance-based balance
measures among weight groups. After controlling for age, sex, minority status,
physical activity level, education level, and comorbid conditions, BMI still significantly contributed to mobility (␤⫽⫺.02, adjusted R2⫽.41).
Conclusions. Although older adults with severe obesity were most impaired,
those with less severe obesity also demonstrated significant decrements in mobility.
A.L. Hergenroeder, PT, PhD, CCS,
School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA 15260 (USA). Address
all correspondence to Dr Hergenroeder at: [email protected].
D.M. Wert, PT, MPT, Department
of Physical Therapy, School of
Health and Rehabilitation Sciences, University of Pittsburgh.
E.S. Hile, PT, PhD, NCS, Department of Physical Therapy, School
of Health and Rehabilitation Sciences, University of Pittsburgh.
S.A. Studenski, MD, MPH, Division
of Geriatric Medicine, Department
of Medicine, University of Pittsburgh, and VA Pittsburgh Geriatric
Research Education and Clinical
Center.
J.S. Brach, PT, PhD, Department of
Physical Therapy, School of Health
and Rehabilitation Sciences, University of Pittsburgh.
[Hergenroeder AL, Wert DM, Hile
ES, et al. Association of body mass
index with self-report and
performance-based measures of
balance and mobility. Phys Ther.
2011;91:1223–1234.]
Association
2011
Submitted: June 25, 2010
this article at:
ptjournal.apta.org
August 2011
Volume 91
Number 8
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Association of Body Mass Index With Measures of Balance and Mobility
O
besity is a major public health
problem in the United States
and around the world. There
has been a substantial increase in the
prevalence of obesity globally, even
in developing countries.1 In the
United States, it is estimated that
more than 65% of adults are overweight, defined as having a body
mass index (BMI) of 25.0 kg/m2 or
higher, with more than 30% considered obese (BMIⱖ30 kg/m2).
Despite increased attention to this
epidemic, the prevalence of obesity
continues to rise.2,3 This increasing
prevalence is of great concern
because the health and economic
burdens of obesity are vast. Numerous chronic diseases, including
hypertension, cardiovascular disease, type 2 diabetes, osteoarthritis,
and certain forms of cancer, are
strongly associated with excess body
weight.4,5 Obesity is estimated to
account for nearly 10% of all medical
spending in the United States.6,7 For
these reasons, it is imperative that
health care professionals be able to
effectively evaluate and treat people
with conditions related to overweight and obesity.
The prevalence of obesity is increasing in older adults, with an estimated
31% of those aged 60 years or older
reported to be obese in 2003–
2004.3,8 The increased prevalence of
obesity in older adults is especially
concerning given the association
between obesity and impaired physical function.9 –16 Physical function
refers to a person’s ability to perform
basic and instrumental activities of
daily living and mobility tasks.
Impairments in physical function,
such as the components of mobility
and balance, have been linked to the
development of disability.17,18 Analysis of recent trends has shown that
obesity-related disability is on the
rise,19 reinforcing the need for a better understanding of the impact of
obesity on mobility and balance.
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The BMI is the most common
method to quantify weight across
a range of body sizes in adults.20
The BMI is calculated by dividing
an individual’s weight (in kilograms)
by his or her height (in meters
squared). Using the BMI, individuals
can be classified as underweight
(⬍18.5 kg/m2), of normal weight
(18.5–24.9 kg/m2), overweight (25–
29.9 kg/m2), class I obese (30 –
34.9 kg/m2), class II obese (35–39.9
kg/m2), or class III obese (ⱖ40
kg/m2). These categories of BMI
were developed by the World Health
Organization based on associated
health risks.21 Guidelines from the
National Institutes of Health suggest
this anthropometric index should be
utilized in the initial assessment of
overweight and obesity.22
The BMI is an inexpensive and easyto-use clinical measure that can be
administered with minimal training.22 Health care professionals, such
as physical therapists, may utilize
this simple measure to screen
patients and determine risks for diseases associated with obesity.
Although BMI is an important indicator of body size for use in the primary care and public health domain,
it is an indirect surrogate measure of
adiposity and thus has several limitations. The BMI may overestimate
body fat in individuals with larger
muscle mass, such as athletes, and
may underestimate body fat in those
who have lost muscle mass (eg, older
adults).23 Furthermore, the BMI
guidelines were established independent of race, age, and sex. Studies
have shown these factors influence
the relationship between BMI and
percentage of body fat, suggesting
the need for population-specific BMI
classifications.24,25 For these reasons,
it has been suggested that the BMI be
used as an initial step in the determination of health risks and that this
measure be used in conjunction with
waist circumference and assessment
Number 8
for the presence of concomitant risk
factors.26
The determination of an individual’s
BMI may assist the clinician in the
identification of risk status and consequently result in an intervention to
reduce weight or disease risk. In
addition to dietary restriction and
behavioral therapy, exercise is a primary treatment for obesity. The public health recommendation for physical activity for adults (men and
women who are healthy and 18 – 65
years of age) and older adults (men
and women ⱖ65 years of age) is a
minimum of 30 minutes of moderateintensity activity on 5 days of the
week (150 min/wk).27,28 However,
there is evidence that higher levels
of exercise are needed for achieving
weight loss (150 –250 min/wk) and
for maintaining weight loss (⬎250
min/wk).29,30 In older adults with
obesity, the benefits of moderate
weight loss achieved through diet
and exercise include improvements
in self-report and performance-based
mobility and balance measures.31 In
addition, studies have shown that
exercise, even in the absence of
weight loss, leads to improvement in
adverse health consequences associated with obesity.32–34
In view of the widespread prevalence of obesity and the critical role
of exercise and physical activity in
weight loss and health risk reduction, physical therapists are well
positioned to have a substantial
impact on this significant public
health problem. In a recent study of
physical therapists’ knowledge of
obesity, the majority believed that
identifying obesity was within their
scope of practice.35 Furthermore,
most therapists recognized that exercise and diet are key components of
a weight loss program. Despite these
findings, the researchers concluded
that physical therapists lacked the
knowledge about the use of the BMI
as an indicator for identifying obesity
August 2011
and estimating associated health
risks.35 To effectively manage individuals who are overweight, physical
therapists must be able to utilize and
interpret obesity measures.
Despite evidence relating obesity to
impaired physical function, there are
several limitations in the current
body of research. Studies investigating the relationship between BMI
and mobility have focused on individuals with severe obesity,36,37 and
few studies have examined the relationship between BMI and balance.38
Thus, little is known about the
impact of BMI on balance and mobility across the broader continuum of
weight ranges. This information
would enable health care professionals to better estimate the functional
consequences of excess weight. Furthermore, it is not known how commonly used clinical measures of
mobility and balance are affected by
BMI. This knowledge would assist
physical therapists in determining
whether it is necessary to alter tests
and measures for patients who are
obese. The purposes of this study
were: (1) to assess differences in
mobility and balance on self-report
and performance-based measures
across the spectrum of weight categories, (2) to describe how mobility
and balance measures are affected by
BMI, and (3) to examine other factors that might explain the association between BMI and mobility and
balance.
Method
Participants
This cross-sectional study examined
older adults who participated in the
baseline data collection of an ongoing observational study at the Claude
D. Pepper Older Americans Independence Center, Pittsburgh, Pennsylvania (N⫽120). Individuals were
recruited from a research registry of
older adults who previously consented to be contacted for studies of
balance and mobility. Participants
August 2011
were included in the study if they
were 65 years of age or older and had
the ability to walk a minimum of a
household distance with or without
an assistive device and without the
assistance of another person. Participants were excluded if they
had any of the following conditions
that might affect their safety during testing: neuromuscular disorders
that impair movement, cancer with
active treatment, hospitalization for
a life-threatening illness or major
surgery in the previous 6 months,
severe pulmonary disease, chest pain
with activity, or a cardiac event such
as a heart attack in the previous 6
months. Body mass index data were
missing on one individual; thus, 119
participants were included in the
data analysis.
Body Mass Index
Height and weight were measured
using a Tanita BWB-800 scale and
HR-200 wall-mounted height rod.*
Participants were measured while
wearing indoor clothing and socks
without shoes. Assistance was given
to obtain the position for both height
and weight measurements, including
cues to stand up straight with heels
against the wall for assessment of
height, but measurements then were
recorded in unsupported stance.
Weight was recorded to the nearest
tenth of a kilogram, and height was
measured to the nearest tenth of a
centimeter with the height rod at the
top of the participant’s head in midline. Height and weight measurements were used to determine BMI.
The BMI classifications used in this
study were based on the World
Health Organization’s definitions of
normal weight (BMI 18.5 to ⬍25
kg/m2), overweight (BMIⱖ25 to
⬍30 kg/m2), class I obesity (BMIⱖ30
to ⬍35 kg/m2), class II obesity
(BMIⱖ35 to ⬍40 kg/m2), and class
* Tanita Corporation of America Inc, 2625
S Clearbrook Dr, Arlington Heights, IL 60005.
III obesity (BMIⱖ40 kg/m2). Because
of the limited number of participants
with class III obesity (n⫽3), participants in the obese categories were
classified based on obesity severity
into moderately obese (BMIⱖ30 to
⬍35 kg/m2) and severely obese
(BMIⱖ35 kg/m2) weight groups.39,40
Self-Report Measures of Mobility
and Balance
A 5-point Likert scale was used to
obtain a global rating of mobility and
balance for each participant. Participants were asked to rate their current level of mobility and balance as
excellent, very good, good, fair, or
poor. Self-report measurements of
balance and mobility were collected
prior to the performance-based measures so that the participants’ performance on the tests would not influence their self-report.
Performance-Based Measures of
Mobility
Figure-of-8
Walk
Test. The
Figure-of-8 Walk Test (F8W) has
been shown to be a valid measure of
walking skill in older adults based on
correlations with gait speed, measures of physical function (Late Life
Function and Disability Instrument),
and activities of daily living (Physical
Performance Test).41 In a study of
older adults, the interrater reliability
of this measure was determined to
be high (intraclass correlation coefficient [ICC]⫽.85–.92).42 Participants
were asked to walk in a figure-of-8
pattern around 2 cones placed 1.524
m (5 ft) apart on the floor. The number of steps taken to complete the
course and the total elapsed time in
seconds were measured.
Gait speed. Gait speed is a valid
measure to predict health-related
outcomes in older adults, including
falls and disability.43,44 Studies of
older adults who were healthy and
those with disease have shown
the test-retest reliability of this
measure to be high (ICC⬎.90).43– 45
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The GaitMat II system† was used to
measure gait speed.46 The GaitMat II
consists of an approximately 4-mlong, pressure-sensitive walkway
controlled by a computer system
that processes the data to generate
both spatial and temporal variables
of walking. On either end of the 4-mlong active walkway, nearly 2 m of
inactive surface was available so that
acceleration and deceleration were
not captured in the timed walk. Gait
speed was determined by dividing
the distance traversed by the time
between the first and last steps (eg,
switch closure) and was recorded in
meters per second. After 2 practice
passes, each participant completed 4
passes at his or her self-selected
walking speed for data collection.
The mean of the 4 passes was used as
the measure of gait speed.
Timed “Up & Go” Test. The
Timed “Up & Go” Test has been used
as a test of basic mobility in older
adults and has been shown to have
high intrarater and interrater reliability (ICC⬎.90).47,48 For this test, the
time required for each participant to
stand up from a chair, walk 3 m,
turn, walk back, and sit down was
measured and recorded.
Six-Minute Walk Test. The 6Minute Walk Test has been used as a
measure of mobility and aerobic
endurance in older adults with and
without disease and has shown to be
a reliable measure (ICC⬎.90).49 Each
participant was asked to walk as far
as possible in 6 minutes, taking
standing rest periods as needed. A
straight path of 15.24 m (50 ft) was
used. The total distance walked back
and forth in 6 minutes was recorded.
Each participant’s heart rate, blood
pressure, rating of perceived exertion, and signs and symptoms were
monitored before and after testing.
†
E.Q. Inc, PO Box 16, Chalfont, PA 189140016.
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Timed chair stands. Chair stands
have been utilized as a performancebased measure of lower body function and have been shown to have
good reliability in older adults
(ICC⬎.80).50 Participants were
seated in a rigid chair, asked to fold
their arms across their chest, and
stand up straight as quickly as possible 5 times. The time to complete 5
repeated stands from the chair was
recorded.
Performance-Based Measures of
Balance
Timed balance measures. Participants were asked to maintain
their balance for up to 30 seconds
under each of the following conditions: standing with eyes closed
while the feet were positioned as
close together as possible, tandem
stance in which the heel of one foot
was directly in front of and touching
the toes of the other foot, and singleleg stance where the participants
were asked to lift one foot off the
ground and maintain their balance
on the remaining leg. The first 2 tests
are a modification of standard balance tests used in the Established
Populations for Epidemiologic Studies of the Elderly (EPESE) project.51
In the current study, times for each
trial were extended from 10 to 30
seconds, and no support was provided to attain the test position.
Interrater reliability (ICC⬎.9) and
test-retest reliability (ICC⫽.7) have
been demonstrated for the EPESE
battery of tests.52 In a previous study
of older adults who were high functioning, change of the reliability
coefficient of single-leg stance was
shown to be .69.50
Postural responses. The postural
stress test was used to test postural
responses to a destabilizing force
applied manually by an examiner in
3 different directions (posteriorly,
right, and left). Previous research has
shown that older adults classified as
“fallers” score lower on postural
Number 8
response tests compared with older
“nonfallers” and young adults.53 The
ability of the participants to remain
upright and their response when
nudged at the pelvis in various directions were graded. The response
was graded using the following
scale: 0⫽responds (single step); 1⫽
responds (multiple steps); 2⫽
responds but requires support to stabilize; and 3⫽no obvious response,
individual must be supported. The
responses to 6 perturbations, 2 in
each of the 3 directions, were
totaled, with higher scores indicating greater impairment.
Narrow walk test. As previously
described by Bandinelli et al,54 participants were asked to walk a distance of 4 m at their usual walking
pace within a 15-cm-wide path
marked on the floor with tape. The
time taken to complete the task was
recorded. The number of deviations
from the 15-cm-wide path was also
recorded. Individuals who could not
complete the test independently, or
who stepped outside the walkway
more than 10 times, were classified
as “unable.” The test-retest reliability
of this measure (ICC⫽.76) has been
demonstrated in a sample of older
adults.54 Concurrent validity of the
narrow walk test has been established based on moderate to strong
correlations with other measures of
physical performance, such as gait
speed and the 400-m corridor walk,
in a sample of older adults.55
Obstacle walk test. As previously
described by Bandinelli et al,54 participants were asked to walk a 7-m
course at their usual walking pace
and step over 2 obstacles of different
heights. One obstacle was 6 cm tall
and positioned 2 m from the starting
line, and the other obstacle was 30
cm tall and positioned 4 m from the
starting line. The time taken to complete this task was recorded. The
obstacle walk test has shown to be a
August 2011
Table 1.
Participant Demographics Stratified by Weight Groupa
Normal Weight
(BMIⴝ18.5–24.9 kg/m2)
(nⴝ28)
Overweight
(BMIⴝ25–29.9 kg/m2)
(nⴝ43)
Moderate Obesity
(BMIⴝ30–34.9 kg/m2)
(nⴝ31)
Severe Obesity
(BMI>35 kg/m2)
(nⴝ17)
P
BMI (kg/m2), X (SD)
22.9 (1.5)
27.6 (1.6)
31.8 (1.6)
38.2 (2.1)
⬍.001
Age (y), X (SD)
77.0 (6.3)
78.1 (5.5)
78.0 (6.4)
76.0 (5.8)
.58
Variable
Demographic characteristics
Sex , % female
75%
64%
71%
88%
.31
100%
90%
81%
76%
.05
82%
64%
68%
59%
.06
76%
62%
58%
31%
.03
Reported fear of falling
36%
42%
45%
56%
.60
Reported fall in previous year
32%
41%
41%
38%
.86
White
College educated
Activity level
Walk for exercise
Fall characteristics
Comorbid conditions, X (SD)
4.3 (1.9)
4.0 (2.0)
4.9 (2.1)
4.9 (1.9)
.19
Angina
11%
10%
13%
12%
.98
Heart attack
11%
5%
10%
12%
.73
0%
2%
12%
6%
.11
Lung disorders
19%
14%
48%
18%
.005
Arthritis
70%
69%
81%
88%
.35
Osteoporosis
48%
29%
23%
24%
.15
7%
10%
29%
12%
.06
Congestive heart failure
Diabetes
Chronic pain
a
0%
2%
10%
6%
.27
Sleep problems
11%
19%
13%
29%
.39
Cancer
33%
26%
29%
41%
.70
Stroke
4%
5%
10%
18%
.30
BMI⫽body mass index.
reliable measure (ICC⫽.89) in older
adults.54
Three licensed physical therapists
and one research assistant with
extensive experience in geriatric
research were responsible for data
collection, including measurement
of height and weight, as well as
administration of the battery of balance and mobility tests. All testers
received training in conducting the
measurements and were blinded to
the purposes of the study but not to
study outcomes. Participants’ BMIs
were calculated after data collection
was completed.
August 2011
Additional Information
Demographics. Data were collected on the following demographic
factors: age, sex, ethnicity, and education level.
Comorbidities Index. This measure is a self-report of common
physician-diagnosed medical conditions, including cardiovascular disease (angina, congestive heart failure, or heart attack), neurologic
conditions (stroke or Parkinson
disease), lung disease, musculoskeletal conditions (arthritis, osteoporosis, fracture, or joint replacement),
general conditions (depression,
sleep problems, or chronic pain syn-
drome), cancer, diabetes, or visual
conditions (glaucoma or cataracts).56
For each medical condition, participants were asked whether they
had ever been told by a physician
that they had the condition. The
number of affirmative responses was
summed to yield a total score.
Fall history questionnaire. Participants were asked to respond to
the following questions: (1) Are you
afraid of falling? and (2) Have you
had a fall in the previous year?
Responses to the questions were
recorded as “yes” or “no.”
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Figure.
Global rating of mobility and balance as excellent or very good, stratified by weight
group. Asterisk indicates P⫽.005.
Physical activity habits. During
administration of the Survey of Activities and Fear of Falling in the
Elderly,57 participants were asked
whether they currently walk for
exercise. Because walking is the
most common form of exercise for
older adults,58 those who responded
affirmatively to the question were
considered to be more physically
active than those who responded
negatively.
Data Analysis
Individuals were classified as being
of normal weight, overweight, moderately obese, or severely obese
based on their BMI. For continuous
data, descriptive statistics are presented as means and standard deviations, and categorical data are presented as frequencies (percentages).
Mobility and balance were compared
among weight groups using analysis
of variance (ANOVA). Post hoc pairwise comparisons were conducted
for continuous data. Chi-square analyses were conducted for categorical
data. One-tailed tests were used
because there was a directional
hypothesis that mobility and balance
would be poorer as BMI increased.
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Multiple linear regression analysis
was used to examine the association
between BMI and mobility and balance during standing and walking
while controlling for age, sex, minority status, education level, physical
activity level, and number of comorbid conditions.
The level of significance was set at
.05. Data analyses were performed
with the SAS statistical package (version 9.2).‡
This research was funded by The
University of Pittsburgh Older Americans Independence Center (grant
P30 AG024827). Dr Brach was supported by a Paul B. Beeson Career
Development
Award
(K23
AG026766). Dr Studenski was supported by the National Institute on
Aging (grant K07 AG023641).
Results
Table 1 provides a summary of the
demographic variables, behavioral
risk factors, fall characteristics, and
‡
SAS Institute Inc, 100 SAS Campus Dr, Cary,
NC 27513-2414.
Number 8
prevalent chronic conditions for all
participants stratified by weight
group. Of the 119 participants, 28
(24%) were of normal weight
(BMI⫽18.5–24.9 kg/m2), 43 (36%)
were overweight (BMI⫽25–29.9
kg/m2), 31 (26%) were moderately
obese (BMI⫽30 –34.9 kg/m2), and 17
(14%) were severely obese (BMIⱖ35
kg/m2). The mean age of the participants was 77.6 years (SD⫽5.9).
There were more women (72%) in
our sample than men, and most participants classified their race as
white (87%). Several characteristics
of the participants were associated
with higher BMI levels. Individuals
with higher BMI levels were more
likely to be black or Hispanic and
less likely to report walking for exercise compared with the normal
weight group (Pⱕ.05). There were
no differences among weight groups
in the total number of comorbid
health conditions reported. However, compared with the other
weight groups, those who were
moderately obese were more likely
to report having lung disorders
(P⫽.005). There were no differences
in the number of falls or fear of falling among weight groups.
The Figure illustrates self-reported
global mobility and balance ratings
stratified by weight group. Compared with participants who were of
normal weight and those who were
overweight, those with moderate
and severe obesity were less likely to
report their mobility as very good or
excellent (52%, 55%, 39%, and 6%,
respectively; P⫽.005). There were
no differences in self-reported ratings of balance among weight
groups.
Table 2 provides a description of
performance-based mobility and balance measures stratified by weight
group. Participants with severe obesity (n⫽17) had the lowest levels of
mobility on the performance-based
measures, followed by those who
August 2011
Table 2.
Description of Performance-Based Mobility and Balance Measures Stratified by Weight Group
Normal Weight
(nⴝ29)
X (SD)
Measure
Overweight
(nⴝ42)
X (SD)
Moderate Obesity
(nⴝ31)
X (SD)
Severe Obesity
(nⴝ17)
X (SD)
P
Mobility
Figure-of-8 walk test (s)
Gait speed (m/s)
9.1 (2.8)
9.3 (2.6)
11.2 (4.5)
11.4 (4.5)
.02
1.20 (0.2)
1.11 (0.2)
1.0 (0.3)
0.86 (0.2)
⬍.001a
9.1 (3.2)
9.9 (2.6)
11.7 (4.5)
12.9 (4.9)
.002b
Timed “Up & Go” Test (s)
1,278.3 (276.2)
1,184.9 (266.7)
954.1 (282.5)
836.9 (389.9)
⬍.001d
12.2 (2.7)
13.8 (4.0)
15.3 (5.4)
15.9 (6.3)
.03
Eyes closed, narrow stance (s)
29.2 (2.8)
29.3 (4.2)
26.2 (8.4)
28.4 (6.6)
.12
Tandem stance test (s) (n⫽89)
22.4 (11.4)
21.3 (11.0)
21.7 (11.3)
19.4 (12.9)
.89
Unilateral stance test (s) (n⫽97)
10.6 (9.7)
10.1 (8.8)
6.2 (7.0)
6.4 (7.9)
.17
3.4 (2.9)
3.5 (4.1)
3.2 (2.3)
3.6 (3.3)
.96
Narrow walk test (s) (n⫽101)
4.9 (1.6)
5.3 (2.4)
5.8 (1.9)
5.7 (1.5)
.32
Narrow walk test (no. of deviations)
1.3 (2.5)
2.5 (3.8)
2.5 (2.9)
3.8 (2.9)
.14
Obstacle walk test (s)
8.0 (4.5)
8.2 (3.5)
10.7 (7.8)
10.8 (4.5)
.10
Six-Minute Walk Test (ft)c (n⫽107)
Timed chair stands (s) (n⫽105)
Balance with standing
Postural responses (total no.)
Balance with walking
a
Difference between normal weight and moderate obesity⫽0.21 s, 95% confidence interval (CI)⫽0.03– 0.38, P⬍.05; difference between normal weight and
severe obesity⫽0.34 s, 95% CI⫽0.13– 0.54, P⬍.05.
b
Difference between normal weight and severe obesity⫽3.82 s, 95% CI⫽0.65–7.0, P⬍.05; difference between overweight and severe obesity⫽3.02 s, 95%
CI⫽0.03– 6.01, P⬍.05.
c
1 ft⫽0.3048 m.
d
Difference between normal weight and moderate obesity⫽324 ft, 95% CI⫽96 –553, P⬍.05; difference between normal weight and severe obesity⫽441 ft,
95% CI⫽174 –709, P⬍.05; difference between overweight and moderate obesity⫽231 ft, 95% CI⫽20 – 441, P⬍.05; difference between overweight and
severe obesity⫽348 ft, 95% CI⫽95– 601, P⬍.05.
were moderately obese (n⫽31),
overweight (n⫽42), and of normal
weight (n⫽29). Higher BMI category
was not associated with differences
in balance. For the mobility measures, post hoc pair-wise comparisons revealed that individuals who
were of normal weight and those
who were overweight were similar
in performance; however, individuals with obesity performed more
poorly compared with the other
weight groups.
Table 3 provides the results for the
percentage of participants who were
able to complete the performancebased measures of balance. Compared with those who were overweight and those who were of
normal weight, a trend was observed
with a greater percentage of partici-
Table 3.
Percentage of Completion for Performance-Based Measures of Balance by Weight
Group
Normal
Weight
Overweight
Moderate
Obesity
Severe
Obesity
P
Tandem stance test
79%
79%
65%
76%
.42
Unilateral stance test
90%
86%
77%
64%
.10
Narrow walk test
83%
93%
81%
76%
.48
Obstacle walk test
90%
95%
90%
82%
.60
Measure
August 2011
pants with moderate and severe obesity unable to complete the unilateral
stance test (P⫽.10).
Table 4 provides the results for the
series of linear regressions examining the association between BMI and
mobility and between BMI and balance during standing and walking.
In unadjusted analyses (model 1),
BMI was most strongly related to
mobility (gait speed, adjusted R2⫽
.14, P⬍.0001) and to a lesser extent
related to balance during standing
(unilateral stance test, adjusted R2⫽
.04. P⬍.03) and balance during walking (obstacle walk test, adjusted
R2⫽.03, P⬍.04). After adjusting for
age, sex, minority status, physical
activity level, and total number of
comorbid conditions (model 2), BMI
remained significantly related to
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Physical Therapy f
1229
Table 4.
Relationship Between Body Mass Index (BMI) and Mobility and Between BMI and Balance During Standing and Walking
Gait Speed
Measure
BMI, ␤ (SE)c
Adjusted R2
Model P value
a
Unilateral Stance Test
b
Model 1
Model 2
⫺0.02 (0.004)d
⫺0.015 (0.004)d
.14
.41
⬍.0001
⬍.0001
Obstacle Walk Test
Model 1
Model 2
Model 1
Model 2
⫺0.39 (0.173)e
⫺0.33 (0.189)
0.20 (0.099)e
0.18 (0.093)
.04
⬍.03
.13
⬍.004
.03
⬍.04
.20
⬍.0001
a
Unadjusted linear regression.
Linear regressions adjusted for age, sex, minority status, education level, physical activity level, and total number of comorbid conditions.
SE⫽standard error.
d
P⬍.001.
e
P⬍.05.
b
c
mobility (␤⫽⫺.015, standard error
[SE]⫽.004, P⬍.0001). Body mass
index approached having a significant association with balance during
standing (␤⫽⫺.331, SE⫽.189, P⬍.08)
and balance during walking (␤⫽.181,
SE⫽.093, P⬍ .06).
Discussion
When examining balance and mobility across weight groups in
community-dwelling older adults,
there were more differences in
mobility than in balance. Individuals
who were classified as being of normal weight and those classified as
overweight were similar in mobility,
but individuals with moderate obesity and those with severe obesity
demonstrated consistently lower
performance than the other groups.
The observed relationship between
BMI and poor mobility suggests that
mobility in older adults is impaired at
all levels of obesity.
In our study, self-report of mobility,
but not balance, was different for
participants with obesity. Individuals
who were of normal weight and
those who were overweight had a
similar perception of mobility.
Although self-reported mobility
declined for participants who were
moderately obese, those with more
severe obesity were much less likely
to report mobility as very good or
excellent. The finding of more frequent self-reported mobility limita1230
f
Physical Therapy
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tion in individuals with obesity is
consistent with the findings of previous studies in older adults.10,14,59 In
a study of 6,981 older men and
women, LaCroix et al14 found that
there was a strong association
between loss of mobility and high
BMI levels. Launer et al10 examined
the association between BMI and
self-reported mobility disability in
the NHANES I Epidemiological
Follow-up Study and found that BMI
was related to mobility disability in
community-dwelling older women;
specifically, individuals in the high
tertile for BMI had greater risk of
impairment compared with those in
the low tertile for BMI.
Higher BMI levels were associated
with poorer mobility on performancebased measures. Thus, our participants’ self-reports of poor mobility
were consistent with the findings on
the performance-based measures.
We found that mobility worsened
with increased BMI level; however,
post hoc pair-wise comparisons
revealed the groups with moderate
and severe obesity differed from the
other weight groups on most of the
measures.
In our sample, only the normal
weight group achieved a desirable
gait speed (ⱖ1.2 m/s) based on a
previous study in older adults.60 For
participants who were overweight
and those who were obese, the
Number 8
mean gait speed was ⬍1.2 m/s,
which may have implications for
these individuals to function successfully in the community. For example,
in order to safely negotiate through a
traffic intersection, an individual
must be able to walk at a speed of 1.2
m/s.61 Furthermore, the gait speeds
found in the participants classified as
moderately or severely obese (1.0
and 0.86 m/s) are not just indicative
of impaired functioning, but also
have been found to be associated
with higher risk for adverse health
events, including nursing home
admission, falls, and disability.60,62
These findings underscore the detrimental impact that excess weight
has on mobility in older adults, even
in those with less severe obesity.
Higher BMI levels were not associated with poorer performance on
measures of balance during standing,
which is consistent with participants’ self-reported balance. This
finding was not surprising given that
there were no differences in fall history among the weight groups; however, our findings differ from those
of previous studies that demonstrated more postural instability38
and greater risk of falls in individuals
with obesity.63 Although increased
BMI in older adults may influence
balance, other factors associated
with aging also may contribute to
postural instability. These factors
include sarcopenia, defined as the
August 2011
age-related loss of skeletal muscle
mass and strength (force-generating
capacity)64; changes in body fat distribution, specifically an increase in
visceral abdominal fat and a decrease
in subcutaneous fat65; and a decline
in the quality of skeletal muscle.66 It
is plausible that changes in skeletal
muscle and body fat distribution may
be related more to postural instability than to BMI alone, which may
explain the lack of a stronger relationship between balance and BMI in
the current study.
Although not statistically significant,
differences in static balance among
weight groups may be clinical meaningful. For example, individuals who
who were overweight had similar
performance on the unilateral stance
test (10.6 and 10.1 seconds, respectively) compared with individuals
with moderate obesity and those
with severe obesity, who had poorer
performance on the unilateral stance
test (6.2 and 6.4 seconds, respectively). A previous study of falls in
older adults who were obese
showed no difference in performance on standing balance tests in
individuals with obesity compared
with those of normal weight; however, in contrast to our study, individuals with obesity reported a
higher prevalence of falls.63 Interestingly, all measures of balance were
static, and no measures of balance
during walking were included. Further investigation of the impact of
obesity on balance in older adults is
warranted and should take into
account skeletal muscle mass,
strength, and body fat distribution.
A greater number of individuals with
moderate obesity and severe obesity
were unable to complete the
performance-based measures of balance compared with those who
who were overweight. Lack of completion of balance measures in parAugust 2011
ticipants with higher BMI was
related to inability to assume the test
positions (eg, tandem stance) and
difficulty performing certain movements (eg, narrow walk test). Thus,
had all participants with obesity
been able to complete the balance
measures, our results may have differed. These findings reinforce the
need for the identification of balance
measures most appropriate for use in
individuals with higher BMIs, specifically those that incorporate balance
during dynamic activities and those
that allow individuals with differing
body sizes to assume the position
required for the test.
Obesity is associated with increased
burden of chronic disease and
decreased physical activity level,
both of which have been shown to
negatively affect mobility.14,67,68 In
the current study, individuals with
obesity were more likely to have
lung disorders and were less likely to
engage in physical activity compared
with those who were overweight
and those of normal weight. The
association between BMI and mobility was partially explained by these
factors; however, the data suggest
that even after adjusting for many
potential confounding factors, BMI
still was independently related to
mobility.
The recommendation for weight loss
in older adults is controversial
because there is a risk of accelerating
the age-related decline in lean mass
and bone density, thereby leading to
poorer physical function.69,70 However, interventions that facilitate
weight loss through diet and exercise have been shown to improve
mobility, balance, and health-related
quality of life in older adults.31,71–73
Villareal et al8 suggested that weight
loss programs for older adults
include strategies to minimize muscle and bone loss and should include
the adoption of resistance exercise
and regular physical activity. This
recommendation should be taken
into account by physical therapists
who are frequently involved in exercise prescription for older adults
with obesity.
There are several limitations to the
current study. First, the results of the
study may not apply to the general
community-dwelling older population because our sample was a volunteer sample of predominantly
white women. Furthermore, there
were unequal numbers of participants in each weight group, and not
all participants were able to complete the physical performance tests.
Individuals in the moderately and
severely obese categories had the
lowest completion rates compared
with those in the normal weight or
overweight categories. Our results
might have differed had there been
equal numbers of participants in the
weight groups and had completion
rates been higher across the weight
groups. Several testers were responsible for data collection in this study,
which could have influenced the differences among the weight groups.
However, we believe this potential
limitation is unlikely in that participant assignment to testers was completely random and all testers evaluated participants from each of the
BMI groupings. In addition, although
not established in our study, the
interrater reliability of many of the
measures that we used has been
established in other studies and is
quite good.
An additional limitation of the current study was the use of the BMI as
an indicator of body size. Older individuals typically have less lean mass
and more fat mass than younger
adults, and as a result, the BMI may
underestimate body fat in these
individuals.74 Furthermore, there is
debate about whether the fat redistribution and relative loss of fat-free
mass that occur with aging may
exert more influence than the BMI in
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Physical Therapy f
1231
determining health risks associated
with obesity in older adults.75 More
sophisticated measures of total body
fat are available, including dualenergy x-ray absorptiometry (DXA)
and electron beam computed tomography (EBT). Even so, prior research
has shown a strong relationship
between BMI and total body fat
determined by EBT in older women
(r⫽.89, P⬍.0001), suggesting that
BMI may be an acceptable initial
screening tool in the clinical setting.76 In addition, DXA and EBT may
not be practical measures of total
body fat in the clinical setting
because these tests are more timeconsuming, require more complex
training, and are expensive to use.
We recognize the limitations of the
BMI; however, in the absence of a
more suitable measure, the use of
the BMI may provide an opportunity
for physical therapists to incorporate
health promotion into clinical practice. When utilizing the BMI, care
should be taken to interpret results
along with assessment of regional fat
distribution as well as visual inspection of fat and muscle mass to
decrease risk of misclassification of
body size.
Conclusion
This study used a comprehensive
battery
of
self-report
and
performance-based measures to
characterize mobility and balance in
older adults who were of normal
weight, overweight, moderately
obese, and severely obese. Higher
BMI levels were associated with
poorer mobility but not balance. Furthermore, individuals classified as
being of normal weight and those
classified as overweight were similar
in mobility, whereas individuals with
obesity had greater impairments in
mobility. Although those participants with severe obesity (BMIⱖ35
kg/m2) were most impaired, older
adults with less severe obesity
(BMI⫽30 –34.9 kg/m2) also demonstrated significant decrements in
1232
f
Physical Therapy
Volume 91
mobility. Body mass index should be
considered when selecting measures
of mobility and balance because
older adults with obesity may be
unable to achieve the position for
some tests. When treating older
adults with obesity, physical therapists are in a unique position to prescribe exercise to address associated
medical complications as well as the
functional consequences of obesity.
Dr Hergenroeder and Dr Brach provided
concept/idea/research design and data analysis. All authors provided writing. Mr Wert,
Dr Hile, and Dr Brach provided project management. Dr Studenski and Dr Brach provided fund procurement and facilities/equipment. Dr Brach provided participants. Mr
Wert and Dr Studenski provided consultation (including review of manuscript before
submission).
This study was approved by the Institutional
Review Board of the University of Pittsburgh.
This work was presented on at Physical Therapy 2009: APTA’s Annual Conference &
Exposition; June 12, 2009; Baltimore,
Maryland.
This research was funded by The University
of Pittsburgh Older Americans Independence Center (grant P30 AG024827). Dr
Brach was supported by a Paul B. Beeson
Career
Development
Award
(K23
AG026766). Dr Studenski was supported by
the National Institute on Aging (grant K07
AG023641).
DOI: 10.2522/ptj.20100214
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August 2011
Research Report
Frontal-Plane Gait Mechanics in
People With Medial Knee
Osteoarthritis Are Different From
Those in People With Lateral Knee
Osteoarthritis
Robert J. Butler, Joaquin A. Barrios, Todd Royer, Irene S. Davis
Background. The majority of research on gait mechanics in knee osteoarthritis
has focused on people with medial compartment involvement. As a result, little is
known about the gait mechanics of people with the less common, lateral compartment disease.
Objective. The objective of this study was to compare walking mechanics—
R.J. Butler, PT, DPT, PhD, Doctor
of Physical Therapy Division,
Department
of
Community
Health and Family Medicine, Duke
University, DUMC 104002, Durham, NC 27705 (USA). Address all
correspondence to Dr Butler at:
[email protected].
specifically, differences in frontal-plane lower-extremity kinematics and kinetics—in
people with medial knee osteoarthritis, people with lateral knee osteoarthritis, and
people who were healthy.
J.A. Barrios, PT, DPT, PhD, Doctor
of Physical Therapy Program, University of Dayton, Dayton, Ohio.
Design. A cross-sectional design was used.
T. Royer, PhD, Department of
Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware.
Methods. Fifteen people with medial knee osteoarthritis, 15 people with lateral
knee osteoarthritis, and 15 people who were healthy (control group) were recruited
for the study. All participants underwent a gait analysis at an intentional walking
speed. The variables of interest for the study were peak frontal-plane moments and
angles and angular excursions of the lower extremity during the stance phase of gait.
Data were statistically analyzed with a one-way analysis of variance.
Results. Participants with lateral knee osteoarthritis exhibited significantly less
knee adduction excursion, lower peak knee abduction moment, and lower peak
rear-foot eversion compared with the control group and the medial knee osteoarthritis group.
Limitations. Participants in the control group were approximately 10 years
younger than participants with knee osteoarthritis. Despite this difference, neither
body mass index nor gait speed, each of which is a factor with a stronger influence
on gait mechanics, differed among the groups.
Conclusions. Participants with lateral knee osteoarthritis exhibited frontal-plane
gait mechanics at the knee and rear foot that were different from those of participants
with medial knee osteoarthritis. The results of this study may guide the development
of interventions specific to treating people with lateral knee osteoarthritis.
I.S. Davis, PT, PhD, Department of
Physical Therapy, University of
Delaware, and Drayer Physical
Therapy Institute, Hummelstown,
Pennsylvania.
[Butler RJ, Barrios JA, Royer T,
Davis IS. Frontal-plane gait
mechanics in people with medial
knee osteoarthritis are different
from those in people with lateral
knee osteoarthritis. Phys Ther.
2011;91:1235–1243.]
Association
2011
Submitted: September 27, 2010
this article at:
ptjournal.apta.org
August 2011
Volume 91
Number 8
Physical Therapy f
1235
Frontal-Plane Gait Mechanics in Knee Osteoarthritis
K
nee osteoarthritis (OA) is a
degenerative joint disease characterized by pain and stiffness.1
These symptoms are related to disruption of the articular surfaces and
are associated with significant
impairment in functional ability.2
The disease prevalence increases
with age, and currently 12% to 16%
of people older than 65 years of age
in the United States have been diagnosed with knee OA.3,4 It has been
estimated that almost 45% of all people in the United States will develop
knee OA during their lifetime.5 With
the growing prevalence of the disease, a concomitant growth in the
cost of treating the disease also has
been observed. The cost for endstage treatment of the disease has
been estimated to be $38,000.6 Projections show that the cost will continue to rise as the baby boomer generation enters the age range for
typical
symptomatic
disease
presentation.
Tibiofemoral knee OA can develop
in either the medial or lateral compartment.7 However, it is 9 times
more common in the medial compartment.7 Static lower-extremity
alignment has been shown to influence which compartment is
involved, with genu valgus being
associated with lateral OA and genu
varus being associated with medial
OA.8 –11 Genu valgus alignment often
is associated with hip adduction
proximally and rear-foot eversion
distally.12 Genu varus alignment,
however,
is
associated
with
decreased hip adduction proximally
and increased rear-foot inversion
distally.
To date, only one study has compared the gait mechanics of people
who have medial knee OA with
those of people who have lateral
knee OA.13 These researchers
reported that, relative to people in a
control group, people with medial
knee OA exhibited more knee
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Volume 91
adduction but less hip adduction
during gait than people with lateral
knee OA.13 Alterations in hip and
knee alignment are likely to lead to
differences in respective joint loading. Weidow et al13 noted that people with medial knee OA had 52%
higher internal knee abduction
moments than people who were
healthy (control group). People with
lateral knee OA had 63% lower internal knee abduction moments than
the control group.13 Surprisingly,
lower internal peak hip abduction
moments were reported in both people with medial knee OA and people
with lateral knee OA than in the control group. Mundermann et al14
observed similar reductions in hip
abduction moments in people with
severe medial knee OA and in the
control group. However, they found
no difference between people with
less severe medial knee OA and the
control group. Alterations at the hip
and knee are likely to influence
mechanics distally and thus can significantly alter gait mechanics.
Unfortunately, previous research
studies did not include an evaluation
of the differences in these distal
mechanics, such as peak rear-foot
eversion, eversion excursion, and
the peak inversion moment.
In summary, knee OA is clearly associated with some malalignment of
the lower extremity. The direction
of knee malalignment (varus or valgus) influences which knee compartment becomes involved and likely
influences gait mechanics. However,
only one study has compared the gait
mechanics of people who have been
diagnosed with medial knee OA and
those of people who have been diagnosed with lateral knee OA. In addition, no studies have examined the
effect of these differences on rearfoot mechanics during gait. Therefore, the purpose of this study was to
compare frontal-plane gait mechanics at the hip, knee, and rear foot in
people with medial knee OA, people
with lateral knee OA, and people
who were healthy (control group).
The Bottom Line
Patients with medial and lateral knee osteoarthritis exhibit different hip
and knee mechanics during gait. These differences in mechanics have
previously been associated with elevated disease progression.
The findings from this study suggest that patients with medial and lateral
knee osteoarthritis also have different mechanics at the ankle. The
observed differences in mechanics are contrary to current clinical beliefs.
The difference in presentation may be due to the chronic effects of the
disease process.
If you’re a patient, what might these findings mean
for you?
If you have osteoarthritis on the inside of the knee (medial knee osteoarthritis), the treatments you receive may be different from the treatments
that patients with knee osteoarthritis on the outside of the knee (lateral
knee osteoarthritis) may receive.
Number 8
August 2011
We hypothesized that, compared
with people with lateral knee OA or
the control group, people with
medial knee OA would walk with
increased peak knee adduction,
increased knee adduction excursion,
and an increased peak internal knee
abduction moment. We also hypothesized that, compared with people
with lateral knee OA or the control
group, people with medial knee OA
would exhibit decreased hip adduction, decreased hip adduction excursion, and a decreased peak hip
abduction moment. Finally, we
expected that people with lateral
knee OA would exhibit increased
rear-foot eversion, increased eversion excursion, and an increased
peak inversion moment and that, for
all variables of interest, values in the
control group would fall between
values in people with medial knee
OA and values in people with lateral
knee OA.
Method
We conducted an a priori power
assessment for a one-way analysis of
variance (ANOVA) design for the
variables peak knee adduction and
peak knee abduction moment. Using
a ␤ value of .20, an ␣ value of .05, a
difference between groups of 10%,
and the variability from previously
published work, we determined that
14 people per group were needed to
adequately power the study.15,16
Therefore, 15 people per group
were recruited through local
advertisements.
Participants
All participants were 40 to 75 years
of age. The participants in the control group were asymptomatic and
had no history of knee problems.
The participants with OA were diagnosed with unilateral medial or lateral compartment tibiofemoral OA
on the basis of a flexed-knee radiograph that was graded by a single
rheumatologist.
People
were
excluded if they had any other
August 2011
lower-extremity arthritis. A KellgrenLawrence (K-L) grade was assigned
to each radiograph to classify disease
severity.17 A K-L grade of 2 or higher
was required for inclusion in the
study. In addition, all participants
with OA had to report knee pain of
at least 3 of 10 on a verbal analog
scale during walking activities to be
included in the study. Exclusion criteria included any other pathological
condition that could affect ambulation. People with evidence of symptomatic, patellofemoral compartment involvement were excluded.
Finally, all participants had to be able
to ambulate without an assistive
device.
Study Design
People who met the inclusion criteria were invited to a motion analysis
laboratory for an instrumented gait
analysis. Participants first provided
written informed consent. Next, anatomical markers were placed over
the following landmarks on the limb
that was diagnosed with knee OA:
the greater trochanters, the medial
and lateral femoral condyles, the
medial and lateral malleoli, the heads
of the first and fifth metatarsals, and
the distal aspect of the laboratory
shoe (Nike Air Pegasus*). Tracking
markers were placed on the skin
over the L5–S1 interspinous space,
the ipsilateral anterior superior iliac
spine, and the ipsilateral iliac crest.
Additionally, clusters of 4 tracking
markers were placed on the distal
posterior thigh and the posterior lateral shank. A cluster of 3 individual
rear-foot markers were placed
directly over the calcaneus and projected through holes in the heel
counters of the laboratory shoe.15
Marker placement and testing were
completed by 2 trained laboratory
researchers using a marker set that
has been shown to be reliable within
and between days.18
* Nike Inc, One Bowerman Dr, Beaverton, OR
97005.
The gait analysis was then performed. After a standing calibration,
the anatomical markers were
removed, leaving the tracking markers for the walking trials. Each participant’s intentional walking speed
was determined with photocells as
the participant traversed a 25-m
walkway.
Intentional
walking
speed was defined as the speed that
the participants would use to walk to
and from a mailbox. Once determined, the speed was maintained
within ⫾5% for all trials on the basis
of feedback from the photocells.
Data from a minimum of 5 usable
trials were collected. A 6-camera
motion analysis system† sampling at
120 Hz was used to capture the individual marker. Kinetic data were
captured with a force platform‡ sampling at 1,080 Hz. The force platform
was located at approximately the
midpoint of the participant’s gait
path during the trials. Kinematic data
were filtered with a low-pass filter at
8 Hz and a fourth-order, zero-lag Butterworth filter. Kinetic data were filtered with a low-pass filter at 50 Hz
and a fourth-order, zero-lag Butterworth filter. All inverse dynamic and
joint kinematic calculations (Euler
sequence X-Y-Z)19 were performed
with Visual 3D software.§
Outcome Measures
The kinematic variables of interest
were the peak angle, angular excursion, and the peak moment in the
frontal plane for the rear foot, knee,
and hip. Peak angle was defined as
the maximum value during the
stance phase of gait. Angular excursion was defined as the peak angle
during the stance phase subtracted
from the initial angle at heel-strike.
The kinetic variables of interest were
the peak knee abduction moment,
†
Vicon-UK, 14 Minns Business Park, West
Way, Oxford OX2 0JB, United Kingdom.
‡
Bertec Corp, 6171 Huntley Rd, Suite J,
Columbus, OH 43229.
§
C-Motion Inc, 20030 Century Blvd, Suite
104A, Germantown, MD 20874.
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Table 1.
Descriptive Statistics for the Study Participants
Variable
Age, y, X (SD)
2
Body mass index, kg/m , X (SD)
Medial Knee
Osteoarthitis
Group
Control
Group
Lateral Knee
Osteoarthritis
Group
66.2 (7.8)a
56.3 (10.7)b
65.7 (6.4)a
32.2 (7.9)
27.8 (5.7)
30.4 (7.5)
1.4 (0.2)
1.5 (0.1)
1.4 (0.3)
Walking speed, m/s, X (SD)
Kellgren-Lawrence grade, n (%)
a
b
2
5 (33)
Not applicable
3 (20)
3
4 (27)
Not applicable
5 (33)
4
6 (40)
Not applicable
7 (47)
Value was significantly different from that for participants in the control group.
Value was significantly different from that for participants with lateral knee osteoarthritis.
the peak inversion moment, and the
peak hip abduction moment.
Moment data were expressed as
internal moments and were normalized to body weight (in kilograms)
and height (in meters). Data for the
variables of interest were extracted
from 5 individual trials and then
averaged.
Data Analysis
A one-way ANOVA was used to analyze group differences for the vari-
ables of interest. In the case of statistical significance, post hoc tests
(Tukey honestly significant difference) were used to further analyze
the data (SPSS version 14㛳). The
ANOVAs were performed with and
without age as a covariate. Because
age was not a significant covariate,
only the results of the ANOVA without age as a covariate are presented
㛳
60606.
to improve clarity. Corrections for
multiple tests were made by use of
post hoc testing with standard Bonferroni corrections for multiple comparisons. Chi-square analysis was
used to examine the equality of the
distribution of K-L grades between
the medial knee OA and lateral knee
OA groups. Statistical significance
was set at a P value of ⬍.02. To
correlate our results with those of
prior studies, we made an a priori
plan to compare the peak hip abduction moment for participants who
had medial knee OA and a K-L grade
of greater than or equal to 3 with
that for participants in the control
group.14 Only statistical differences
that were beyond the error of the
measurement are reported in this
article.18
This work was made possible by
grant
number
NIH-RR16548
(Thomas Buchanan, primary investigator) from the National Center for
Research Resources (NCRR), a component of the National Institutes of
Health (NIH). The sole role of the
Table 2.
Variables of Interest
Control
Groupa
Lateral Knee
Osteoarthritis
Groupa
⫺0.062 (0.031)
⫺0.065 (0.032)
Medial Knee
Osteoarthritis
Groupa
Variable
Pb
Ankle
Peak inversion moment (N䡠m/kg䡠m)
⫺0.050 (0.045)
6.2 (5.0)c
Peak eversion (°)
Eversion excursion (°)
10.6 (5.6)
.38
3.5 (2.7)
1.8 (3.1)
.01
10.2 (3.7)
10.0 (2.6)
.96
⫺0.326 (0.078)
⫺0.193 (0.111)d
⬍.01
⬍.01
Knee
Peak abduction moment (N䡠m/kg䡠m)
Peak adduction (°)
Adduction excursion (°)
⫺0.420 (0.083)c,d
5.6 (4.0)
c,d
1.1 (5.1)
⫺5.2 (5.9)d
6.9 (2.3)
c,d
5.6 (3.1)
3.8 (1.9)
.01
Hip
Peak abduction moment (N䡠m/kg䡠m)
⫺0.631 (0.132)
⫺0.631 (0.120)
⫺0.659 (0.107)
.90
Peak adduction (°)
5.6 (2.5)
7.1 (3.3)
8.5 (3.4)
.04
Adduction excursion (°)
7.4 (3.3)
7.8 (3.3)
7.0 (3.2)
.11
a
Reported as mean (standard deviation).
b
Reported for the one-way analysis of variance.
c
Value was significantly different from that for participants with lateral knee osteoarthritis.
d
Value was significantly different from that for participants in the control group.
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August 2011
funding source was monetary support for the completion of the study.
The funding source had no role in
data analysis or dissemination of the
results of the study.
Results
There was no difference in body
mass index among the groups. However, participants in the control
group were approximately 10 years
younger than those in the 2 OA
groups (Tab. 1). There was no difference in the proportion of disease
severity between participants with
medial knee OA and those with lateral knee OA (Tab. 1).
The knee abduction moments for all
groups demonstrated a bimodal
shape with a larger peak during the
first half of the stance phase than
during the second half of the stance
phase. The peak abduction moment
was significantly lower in participants with lateral knee OA than in
participants in the control group and
significantly lower in participants in
the control group than in participants with medial knee OA (Tab. 2,
Fig. 1). Similar results were observed
for the peak knee adduction angle.
The peak knee adduction angle
occurred at approximately 25% of
the stance phase for all groups
(Tab. 2, Fig. 1). Knee adduction
excursion in participants with lateral
knee OA was significantly lower than
that in participants with medial knee
OA but was not significantly different from that in participants in the
control group (Tab. 2, Fig. 1). In general, there were greater differences
in knee joint kinetics and kinematics
between the lateral knee OA and
control groups than between the
medial knee OA and control groups.
The hip kinematic patterns appeared
to differ among the groups upon
visual inspection (Fig. 2). Despite an
offset between participants with
medial knee OA and participants in
the control group, their 2 patterns
August 2011
Figure 1.
Knee frontal-plane angle and moment during the stance phase in participants with
medial and lateral knee osteoarthritis (OA) and participants in the control group. Means
are plotted for all groups; ⫾1 standard error of the mean bars are plotted for the control
group only.
were quite similar; participants in
the control group exhibited more
hip adduction than participants with
medial knee OA throughout the
stance phase. However, participants
with lateral knee OA demonstrated a
more defined and larger peak value
during the early stance phase
(Tab. 2, Fig. 2). Compared with participants with lateral knee OA, participants with medial knee OA exhibited a reduction in peak hip
adduction of 2.9 degrees, although
this reduction was not statistically
significant (Tab. 2, Fig. 2). No differ-
ences were observed in hip kinetics.
All groups exhibited similar bimodal
curves with no differences in peak
hip abduction moments. To make
comparisons with previous work
examining hip abduction moments
in people with more severe knee OA
(K-L grade of ⱖ3), we performed a
subset analysis. Similar to the findings for the entire group, no differences in hip abduction moments
were observed among the groups
when participants with more severe
knee OA solely were considered.
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Discussion
The purpose of the present study
was to compare the gait mechanics
of people who have medial knee OA
and lateral knee OA with those of
people in a control group (Fig. 4).
The results suggest that people with
medial knee OA exhibit gait mechanics at the knee, hip, and ankle that
are different from those of people
with lateral knee OA. The peak knee
abduction moment, peak knee
adduction, knee adduction excursion, and peak rear-foot eversion
were all higher in participants with
medial knee OA than in participants
with lateral knee OA. Participants in
the control group typically exhibited
mechanics that fell between those of
participants with lateral knee OA
and those of participants with medial
knee OA.
Figure 2.
Hip frontal-plane angle and moment during the stance phase in participants with
group only.
At the ankle, rear-foot eversion patterns were similar among the
groups. However, there was an offset in the patterns for all groups. The
joint excursions were similar; however, there were significant differences in peak eversion. Participants
with lateral knee OA exhibited less
peak eversion than those in the control group. Participants in the control group exhibited less peak eversion than those with medial knee OA
(Tab. 2, Fig. 3). In terms of frontal1240
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plane kinetics, participants with
medial knee OA and participants in
the control group exhibited similar
patterns during the first 25% of the
stance phase, whereas participants
with lateral knee OA and those in the
control group exhibited similar patterns during the final 75% of the
stance phase. However, the peak
rear-foot inversion moments during
the first half of the stance phase
were not statistically different
among the groups (Tab. 2, Fig. 3).
Number 8
The higher peak knee adduction
exhibited by participants with
medial knee OA than by participants
with lateral knee OA was expected
(Figs. 1 and 4). We believe that this
result is related to the increased knee
adduction associated with the genu
varus alignment that is typical of
medial knee OA. The difference in
peak knee adduction between lateral
knee OA and medial knee OA was
observed previously.13 Weidow et
al13 reported even larger differences
(18°) in knee adduction between
these groups than we reported in the
present study (10.8°). However,
these researchers presented the
median value for each group, which
may yield a larger difference than the
mean value reported in the present
study.13
The difference in knee adduction
excursion between the groups was
similar to the difference in peak knee
adduction; participants with medial
knee OA exhibited more excursion
than participants with lateral knee
OA. Our findings regarding the knee
kinetics were consistent with those
of others; the highest knee abducAugust 2011
tion moments were seen in participants with medial knee OA, and the
lowest were seen in participants
with lateral knee OA.13,14 Previous
research suggested that the peak
knee abduction moment is correlated with load in the medial compartment of the knee joint.20 Combined with our findings, this notion
suggests that people with medial
knee OA exhibit elevated loads in
the medial compartment compared
with people without the disease. In
contrast, people with lateral knee
OA likely exhibit reduced loads in
the medial compartment; thus, more
of the load may be distributed in the
lateral compartment in these people.
Differences in rear-foot mechanics
between people with medial knee
OA and people with lateral knee OA
have yet to be reported in the literature. However, alterations in knee
mechanics are likely to lead to
changes at the foot (Fig. 3). Typically, genu valgus is associated with
rear-foot eversion and genu varus is
associated with rear-foot inversion.12
However, we found that participants
with medial knee OA exhibited more
peak eversion than those with lateral
knee OA. Because the overall excursions were similar in these groups,
the differences in peak values were
attributed to differences at the time
of heel-strike. These differences
remained fairly constant throughout
the stance phase. The values for participants in the control group fell
between those for participants in the
other 2 groups (Fig. 3).
Although the findings were in contrast to our hypothesis, we believe
that they indicate a compensatory
mechanism of the foot to remain
plantigrade. For example, because
genu varus is typically associated
with medial knee OA, the foot is
likely positioned in increased inversion before heel-strike. Therefore,
increased eversion is needed to
obtain a plantigrade position. The
August 2011
Figure 3.
Rear-foot frontal-plane angle and moment during the stance phase in participants with
group only.
opposite is true for genu valgus,
which is associated with lateral knee
OA. This conceptual model recently
was supported by researchers who
observed increased rear-foot eversion in people with genu varum.21 It
is interesting that the offsets seen in
rear-foot kinematics were not mirrored in the kinetics (Fig. 3). For
example, given the increased rearfoot eversion seen in people with
medial knee OA, increased inversion
moments would be expected. However, people with medial knee OA,
on average, exhibited the lowest
inversion moments throughout most
of the stance phase.
The results of the present study provide valuable information regarding
conservative treatments for both
medial knee OA and lateral knee OA.
The differences in lower-extremity
mechanics between people with
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Number 8
Physical Therapy f
1241
participants in either OA group by
approximately 10 years. However,
there is currently no evidence to suggest that this age difference would
significantly influence our variables
of interest. Additionally, our statistical analysis revealed that age was not
a significant covariate in the present
study. Two variables, body mass
index and walking speed, which
were controlled in our study, have
been established as affecting gait
mechanics.28,29 Both of these variables were similar in participants in
the control group and those in the
OA groups.
Figure 4.
Diagram of the posterior view of the left lower extremity in participants with lateral (left)
and medial (right) knee osteoarthritis (OA). Increased rear-foot inversion is needed for
the foot to be plantigrade in the participant with lateral knee osteoarthritis (left), and
increased rear-foot eversion is needed in the participant with medial knee osteoarthritis
(right).
medial knee OA and those with lateral knee OA support current interventions for knee OA. Treatment of
knee OA can be accomplished
directly with knee braces or indirectly with wedged foot orthoses.22,23 Our findings for the rear foot
suggest that caution is needed in the
application of medial and lateral
wedging. For example, a lateral
wedge is used to indirectly reduce
knee adduction associated with
medial knee OA.15,24,25 This reduced
knee adduction is accomplished by
increasing eversion of the foot. Our
results suggest that people with
medial knee OA already exhibit
increased foot eversion as a compensatory measure for knee varus. Further eversion induced by a lateral
wedge may increase the risk of foot
pathologies that are associated with
this motion, such as plantar fasciitis
or posterior tibialis tendinitis. People
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with these preexisting conditions or
excessive rear-foot compensation
might be better served by other
approaches, such as gait retraining
or hip strengthening, to address
abnormal frontal-plane gait mechanics at the knee.26,27 The typical goal
of these types of interventions is to
provide a more proximal mechanism
to alter loading at the knee. Such
interventions would not so aggressively alter plantar loading and thus
might be more successful in improving function in people with knee OA
and a history of foot-related pathology. Regardless of the intervention,
the results of the present study suggest that monitoring changes at the
foot should be an important component of any intervention used to alter
loading at the knee.
We recognize that participants in the
control group were younger than
Number 8
The findings of the present study
should dovetail into current knee OA
research and practice in accounting
for the entire kinetic chain of the
lower extremity during evaluation or
treatment of a patient with medial or
lateral knee OA. Because of the
nature of the study, extrapolation
can be made only with respect to the
frontal plane. Few studies have
examined sagittal-plane changes, and
fewer studies have assessed the
transverse plane in patients with differential compartment involvement
in knee OA.13 Thus, future studies
examining changes in these planes
and in different compartments
involved in primary knee OA would
be beneficial to the rehabilitation
literature. Differences between compartments are typically not of concern for surgery, with the exceptions of extreme cases, because the
hardware tends to correct malalignments. However, these differences
are meaningful to health care providers who aim to improve function in
patients with knee OA using a conservative approach. Initial research
has suggested that patients with
medial knee OA and those with lateral knee OA respond differently to
similar interventions aimed at offloading the compartment in which
the disease is progressing.15,24,25,30
The specificity of the response suggests that the development of cliniAugust 2011
cal prediction rules may help guide
best practices in the conservative
treatment of the disease.
In summary, people with medial
knee OA and those with lateral knee
OA have significantly different
frontal-plane gait mechanics at the
knee, hip, and ankle. These differences should be taken into account
in the development of interventions
designed to treat degenerative joint
diseases. As health care costs and
knee injury rates continue to rise,
the focus on conservative treatments
for knee OA will continue to
increase. We hope that the results of
the present study will provide foundational evidence for effective interventions to mitigate the progression
of knee OA and lead to healthier and
more active lifestyles for patients
with knee OA.
All authors provided concept/idea/research
design and project management. Dr Butler,
Dr Barrios, and Dr Davis provided writing,
data collection, and data analysis. Dr Royer
and Dr Davis provided fund procurement.
The authors thank Nike Inc for donating the
footwear used for the laboratory experiment
and New Balance Inc for donating the footwear used during the accommodation
period of the study.
The protocol for this study was reviewed and
approved by the Institutional Review Board
of the University of Delaware.
A poster presentation of this work was given
at the annual meeting of the American Society of Biomechanics; August 2004; Portland,
Oregon.
This work was made possible by grant number NIH-RR16548 (Thomas Buchanan, primary investigator) from the National Center
for Research Resources (NCRR), a component of the National Institutes of Health
(NIH).
The contents of this article are solely the
responsibility of the authors and do not necessarily represent the official views of the
NCRR or the NIH.
DOI: 10.2522/ptj.20100324
August 2011
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Does knee malalignment increase the risk
of development and progression of knee
osteoarthritis? A systematic review. Arthritis Rheum. 2009;61:459 – 467.
9 Brouwer GM, van Tol AW, Bergink AP,
et al. Association between valgus and
varus alignment and the development and
progression of radiographic osteoarthritis
of the knee. Arthritis Rheum. 2007;56:
1204 –1211.
10 Cerejo R, Dunlop DD, Cahue S, et al. The
influence of alignment on risk of knee
osteoarthritis progression according to
baseline stage of disease. Arthritis Rheum.
2002;46:2632–2636.
11 Sharma L, Song J, Felson DT, et al. The role
of knee alignment in disease progression
and functional decline in knee osteoarthritis. JAMA. 2001;286:188 –195.
12 Gross MT. Lower quarter screening for
skeletal malalignment: suggestions for
orthotics and shoewear. J Orthop Sports
Phys Ther. 1995;21:389 – 405.
13 Weidow J, Tranberg R, Saari T, Karrholm J.
Hip and knee joint rotations differ
between patients with medial and lateral
knee osteoarthritis: gait analysis of 30
patients and 15 controls. J Orthop Res.
2006;24:1890 –1899.
14 Mundermann A, Dyrby CO, Andriacchi TP.
Secondary gait changes in patients with
medial compartment knee osteoarthritis:
increased load at the ankle, knee, and hip
during walking. Arthritis Rheum. 2005;
52:2835–2844.
15 Butler RJ, Marchesi S, Royer T, Davis IS.
The effect of a subject-specific amount of
lateral wedge on knee mechanics in
patients with medial knee osteoarthritis.
J Orthop Res. 2007;25:1121–1127.
NJ: Lawrence Erlbaum Associates; 1988.
17 Kellgren JH, Lawrence JS. Radiological
assessment of osteo-arthrosis. Ann Rheum
Dis. 1957;16:494 –502.
18 Ferber R, McClay Davis I, Williams DS III,
Laughton C. A comparison of within- and
between-day reliability of discrete 3D
lower extremity variables in runners.
J Orthop Res. 2002;20:1139 –1145.
19 Grood ES, Suntay WJ. A joint coordinate
system for the clinical description of threedimensional motions: application to the
knee. J Biomech Eng. 1983;105:136 –144.
20 Andriacchi TP. Dynamics of knee malalignment. Orthop Clin North Am. 1994;25:
395– 403.
21 Barrios JA, Davis IS, Higginson JS, Royer
TD. Lower extremity walking mechanics
of young individuals with asymptomatic
varus knee alignment. J Orthop Res. 2009;
27:1414 –1419.
22 Raja K, Dewan N. Efficacy of knee braces
and foot orthoses in conservative management of knee osteoarthritis: a systematic
review. Am J Phys Med Rehabil. 2011;90:
247–262.
23 Pollo FE, Otis JC, Backus SI, et al. Reduction of medial compartment loads with
valgus bracing of the osteoarthritic knee.
Am J Sports Med. 2002;30:414 – 421.
24 Kakihana W, Akai M, Yamasaki N, et al.
Changes of joint moments in the gait of
normal subjects wearing laterally wedged
insoles. Am J Phys Med Rehabil. 2004;83:
273–278.
25 Hinman RS, Payne C, Metcalf BR, et al. Lateral wedges in knee osteoarthritis: what
are their immediate clinical and biomechanical effects and can these predict a
three-month clinical outcome? Arthritis
Rheum. 2008;59:408 – 415.
26 Barrios JA, Crossley KM, Davis IS. Gait
retraining to reduce the knee adduction
moment through real-time visual feedback
of dynamic knee alignment. J Biomech.
2010;43:2208 –2213.
27 Thorp LE, Wimmer MA, Foucher KC, et al.
The biomechanical effects of focused muscle training on medial knee loads in OA of
the knee: a pilot, proof of concept study.
J Musculoskelet Neuronal Interact. 2010;
10:166 –173.
28 Lai P, Leung A, Li A, Zhang M. Threedimensional gait analysis of obese adults.
Clin Biomech. 2008;23:S2–S6.
29 Landry SC, McKean KA, Hubley-Kozey CL,
et al. Knee biomechanics of moderate OA
patients measured during gait at a selfselected and fast walking speed. J Biomech. 2007;40:1754 –1761.
30 Rodrigues PT, Ferreira AF, Pereira RM,
et al. Effectiveness of medial-wedge insole
treatment for valgus knee osteoarthritis.
Arthritis Rheum. 2008;59:603– 608.
Volume 91
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Physical Therapy f
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Research Report
Test-Retest Reliability and Minimal
Detectable Change Scores for Sit-toStand-to-Sit Tests, the Six-Minute
Walk Test, the One-Leg Heel-Rise Test,
and Handgrip Strength in People
Undergoing Hemodialysis
Eva Segura-Ortı́, Francisco José Martı́nez-Olmos
E. Segura-Ortı́, PT, MSc, PhD,
Department of Physiotherapy, Universidad CEU Cardenal Herrera,
Avda Seminario s/n, 46113 Moncada (Valencia), Spain. Address all
correspondence to Ms SeguraOrtı́ at: [email protected].
F.J. Martı́nez-Olmos, PT, MSc,
Department of Physiotherapy, Universidad CEU Cardenal Herrera.
[Segura-Ortı́ E, Martı́nez-Olmos
FJ. Test-retest reliability and minimal detectable change scores for
sit-to-stand-to-sit tests, the SixMinute Walk Test, the one-leg
heel-rise test, and handgrip
strength in people undergoing
hemodialysis. Phys Ther. 2011;91:
1244 –1252.]
Association
2011
Submitted: April 21, 2010
Background. Determining the relative and absolute reliability of outcomes of
physical performance tests for people undergoing hemodialysis is necessary to
discriminate between the true effects of exercise interventions and the inherent
variability of this cohort.
Objective. The aims of this study were to assess the relative reliability of sit-tostand-to-sit tests (the STS-10, which measures the time [in seconds] required to
complete 10 full stands from a sitting position, and the STS-60, which measures the
number of repetitions achieved in 60 seconds), the Six-Minute Walk Test (6MWT),
the one-leg heel-rise test, and the handgrip strength test and to calculate minimal
detectable change (MDC) scores in people undergoing hemodialysis.
Design. This study was a prospective, nonexperimental investigation.
Methods. Thirty-nine people undergoing hemodialysis at 2 clinics in Spain were
contacted. Study participants performed the STS-10 (n⫽37), the STS-60 (n⫽37), and
the 6MWT (n⫽36). At one of the settings, the participants also performed the one-leg
heel-rise test (n⫽21) and the handgrip strength test (n⫽12) on both the right and the
left sides. Participants attended 2 testing sessions 1 to 2 weeks apart.
Results. High intraclass correlation coefficients (ⱖ.88) were found for all tests,
suggesting good relative reliability. The MDC scores at 90% confidence intervals were
as follows: 8.4 seconds for the STS-10, 4 repetitions for the STS-60, 66.3 m for the
6MWT, 3.4 kg for handgrip strength (force-generating capacity), 3.7 repetitions for
the one-leg heel-rise test with the right leg, and 5.2 repetitions for the one-leg
heel-rise test with the left leg.
Limitations. A limited sample of patients was used in this study.
Conclusions. The STS-16, STS-60, 6MWT, one-leg heel rise test, and handgrip
strength test are reliable outcome measures. The MDC scores at 90% confidence
intervals for these tests will help to determine whether a change is due to error or to
an intervention.
this article at:
ptjournal.apta.org
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Number 8
August 2011
E
nd-stage renal disease was first
considered a rare disease, but
the yearly increase in prevalence in the United States outdated
this definition 20 years ago.1 This
increase in end-stage renal disease
also has been found in Europe,2,3
where the prevalence per million
people was 779 by December 2006
and increased to 881 by December
2008. During this period of time, the
prevalence in Spain2,3 increased
from 983 to 994. The most common
renal replacement therapy is hemodialysis; less common treatments are
renal transplantation and peritoneal
dialysis. Old age and cardiovascular
comorbidities are commonly found
in patients with end-stage renal
disease.1,2
Physical therapists are among the
health care providers who supervise
exercise interventions for patients
receiving hemodialysis. Given the
need to measure outcomes to assess
changes in physical function, specific
clinical tools for assessing treatment
effects should be tested for reliability
with patients receiving hemodialysis.
Exercise interventions have been
implemented in patients undergoing
hemodialysis for almost 30 years.
Outcome measures in most published studies include laboratory
measures, such as the peak oxygen
consumption in a graded exercise
test.4 –7 This test may be difficult for
older patients and patients with low
levels of function to perform. In addition, despite research applicability,
this test is not easy to perform in
clinical settings. The identification of
reliable physical performance tests
for patients undergoing hemodialysis
would enhance the ability to assess
physical function levels and the
effectiveness of interventions for
both clinical and research purposes.
A recent meta-analysis of exercise in
patients undergoing hemodialysis8
concluded that aerobic, resistance,
August 2011
or combined exercise programs
resulted in an increase in peak oxygen consumption4 –7,9 –11 and in physical function measured with the
Medical Outcomes Study 36-Item
Short-Form Health Survey questionnaire.12,13 However, the effects of
exercise on physical performance
tests could not be reported because
of the lack of uniformity of the tests
used in published studies.8,14
Several physical performance tests
were analyzed in the present study.
The Six-Minute Walk Test (6MWT) is
a physical function test that is frequently used to assess the impact of
renal rehabilitation.12,15–22
The STS-10 (a sit-to-stand-to-sit [STS]
test that measures the time [in seconds] required to complete 10 full
stands from a sitting position) has
been recommended to quantify
lower-extremity muscle strength
(force-generating capacity) in patients
with lower-extremity weakness.23 The
STS-60 (an STS test that measures the
number of repetitions achieved in 60
seconds) has been used as a surrogate
index of muscle endurance.20,24
The one-leg heel-rise test consists of
repeated eccentric and concentric
muscle actions and reflects endurance rather than strength in the
plantar-flexor muscles.25 This test
has shown that calf muscles are
weak as early as the predialysis
stage23; this weakness could contribute to an altered gait pattern.26
The maximal voluntary handgrip
strength test is a quantitative and easily performed test that allow comparisons of people who are healthy and
various clinical groups.27,28 Handgrip
strength is necessary for optimal performance of activities of daily living,
such as getting dressed and handling
pans.29 Greater handgrip strength
increases the probability of survival
of patients undergoing dialysis.30
Studies assessing the reliability of
these tests for people undergoing
hemodialysis are uncommon.24,31
The reliability of a test should be
expressed as both relative reliability
and absolute reliability.32 Relative
reliability may be measured with the
intraclass correlation coefficient
(ICC), which is used for test-retest
reliability. Individual performance
and measurement error are measured with absolute reliability,
which provides information for differentiating a true change in performance from a change due to individual variation and measurement error.
The aims of this study were to calculate the test-retest reliability of commonly used physical performance
tests in people undergoing hemodialysis (6MWT, STS-10, STS-60, oneleg heel-rise test, and handgrip
strength test) and to calculate absolute reliability with the standard error
of measurement (SEM) and minimal
detectable change (MDC) scores at
90% confidence intervals (MDC90).
Method
Design
This study was a prospective, nonexperimental, descriptive methodological investigation.
Setting and Participants
Study participants were recruited
from 2 hemodialysis clinics in Valencia, Spain, from 2006 to 2008. Inclusion criteria were evaluated by the participant’s nephrologist, who gave
authorization before solicitation of
interest. The inclusion criteria were
receipt of recurring hemodialysis for 3
months or more with adequate dialysis delivery (Kt/Vⱖ1.2)* and the
absence of acute or chronic medical
conditions that would preclude the
collection of outcome measure data.
* The most common method to calculate the
amount of hemodialysis per patient is by the
calculation of Kt/V around 1.2, where K is urea
clearance, t is the length of the hemodialysis
session, and V is the patient’s water volume.33
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Physical Therapy f
1245
Exclusion criteria were recent myocardial infarction (within 6 weeks),
malignant
arrhythmias,
unstable
angina, and any disorder that was
exacerbated by activity. Demographic
and clinical data were collected from
the medical history and included age,
sex, body mass index, time on hemodialysis, hemoglobin level, cause of
kidney disease, and comorbidities. All
participants
provided
written
informed consent.
Procedure
Participants performed each of the
tests twice, with a 1- to 2-week interval
between the testing sessions, always
on a dialysis day, and immediately
before the second or third hemodialysis session of the week. Every effort
was made to keep all factors associated with the testing sessions consistent: day of the week, time of day, staff
member administering the test, and
area in which the test was performed.
Participants performed the STS tests,
the 6MWT, the one-leg heel-rise test,
and the handgrip strength test.
STS-10 and STS-60. Both STS tests
were performed immediately before
the second hemodialysis session of
the week. The STS-10 was performed
first, and the STS-60 was performed
10 minutes later, when the heart rate
and blood pressure had decreased to
baseline levels. The STS-10 measured
the time (in seconds) required to
perform 10 consecutive repetitions
of sitting down on and getting up
from a chair. Participants were
instructed to perform the task “as
fast as possible,” starting and finishing at the sitting position. Participants were allowed a practice trial
before the beginning of the test.
They began the test by crossing their
arms on their chest and sitting with
their back against the chair.34
For the STS tests and for the 6MWT,
heart rate (Polar S610i†) and blood
pressure (Omron HEM-711AC‡) were
measured immediately before and
after the tests to monitor the physiological and clinical status of the participants during the tests and to obtain
additional information about the
repeat assessment conditions.
The time taken to perform the
STS-10 and the degree of difficulty,
determined as the rate of perceived
exertion (RPE, measured with a Borg
scale from 6 to 20), were recorded at
the end of the test.
Csuka and McCarty35 first described
the use of the STS test as a measure
of lower-extremity strength (forcegenerating capacity of muscle). The
test was performed with a chair that
had no armrests, measured about
44.5 cm high and 38 cm deep, and
was backed up against a wall to minimize the risk of falling.36 Although
this test is nonspecific, it is simple,
inexpensive, rapid, and reproducible35 and is included in the battery
of tests used for people with renal
disease.17,18,20,37
The STS-60 measured the number of
repetitions of sitting down on and
getting up from a chair achieved in
60 seconds. Heart rate and blood
pressure were measured immediately before and after the test. The
number of repetitions achieved and
the degree of difficulty (measured as
RPE⫽6 –20) were recorded at the
end of the test. Each repetition
started and finished at the sitting
position, and if a participant was
standing when the time was over, it
was considered half a repetition. Participants were allowed to stop if rest
was needed and to continue performing the task until the 60 seconds
†
Polar Electro Oy, HQ Professorintie 5, FIN90440 Kempele, Finland.
‡
Omron Europe BV, Wegalaan 67-69, 2132 JD
Hoofddorp, the Netherlands.
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f
Physical Therapy
Volume 91
Number 8
were over. The STS-60 has been
found to be a valid measure of lowerbody strength.38
6MWT. The 6MWT was undertaken immediately before the third
hemodialysis session of the week
because by the end of the week, the
extra fluid retained by the participants was at its lowest level, minimizing its influence on the test
results. The 6MWT was performed in
a 20-m corridor located in the hemodialysis unit; tape was placed every
2 m. Participants were asked to walk
the longest distance possible in 6
minutes by walking continuously the
20 m indicated on the floor, turning
around at the final mark without
stopping, and covering as much
ground as possible.39 The standardized order given to the participants
was, “Walk as far as possible for 6
minutes, but don’t run or jog.”40 Participants were allowed to use any
ambulation aid that they used normally in daily life. They could stop if
needed and restart later. Heart rate
and blood pressure were measured
immediately before and after the
test. The distance covered (in
meters) and the degree of difficulty
(determined as the RPE) were
recorded at the end of the test.
The 6MWT is considered to be a better indicator of the ability to perform
activities that resemble those of daily
living, such as walking, than physiological exercise capacity testing.16
The latter usually requires people to
perform at maximal or nearly maximal levels and in laboratory-based
environments and involves techniques and tasks with which people
are not always familiar.
One-leg heel-rise test. The oneleg heel-rise test was undertaken
immediately before the second
hemodialysis session of the week.
This test was used to measure the
functional strength of the triceps
surae muscle in each leg and was
August 2011
performed only with socks (no footwear). The rhythm, one lift every
other second, was paced with a metronome. Before the test, participants
were asked to maintain balance
while standing on one leg41 by
touching the wall with the fingertips, arms away from the body, and
to avoid pushing their arms against
the wall and thereby shifting their
weight. The contralateral foot was
held just above the floor. After one
trial with the left foot to allow the
participants to become familiar with
the testing procedure, the test was
performed with the right foot. Participants were instructed to lift the
heel as high as possible at the metronome frequency until no further
heel rises could be performed due to
exhaustion. The test was terminated
if a participant’s knee flexed or if a
participant leaned or pushed against
the wall, according to the examiner’s
observation. The test was performed
to a maximum of 25 repetitions
because this is the average number
of repetitions performed by people
who are healthy.25,42 After the test,
the number of repetitions per leg
and the degree of difficulty (determined as the RPE) were recorded.
Handgrip strength dynamometry.
The handgrip strength test was performed immediately before the third
hemodialysis session of the week. A
handgrip dynamometer (Takei Physical Fitness Test TKK 5401 Grip
Dynamometer§) was used to measure the amount of strength developed by each hand in this functional
task. Participants were positioned
standing with the elbow extended at
the moment of the test, according to
the manufacturer’s instructions.
Three consecutive repetitions of 3
seconds, with 15 seconds of rest
between the repetitions, were performed with both arms, starting with
the dominant arm. Verbal encouragement was given during the task.
The highest peak force per arm was
recorded.
Data Analysis
The SPSS package version 15.0 for
Windows㛳 was used for data management and analysis. The level of significance was predetermined to be
Pⱕ.05 for all statistical analyses. Data
are reported as mean (standard deviation), if normally distributed, or as
median (range). The KolmogorovSmirnov test, skewness, and kurtosis
were used to assess whether the data
were normally distributed. Paired
comparisons to assess for systematic
bias between trial weeks were performed with the paired t test or the
Wilcoxon signed rank test. The testretest reliability of data for all
repeated tests was assessed with the
ICC (model alpha), 2-way randomeffects model, which is appropriate
for the present study design. The
test-retest reliability of data for the
physical performance tests (6MWT,
STS-10, STS-60, one-leg heel-rise test,
and handgrip strength test) was
assessed with the ICC (2,1) because
there was only one test score from
each session. The results for intraobserver reliability are presented
because the same physical therapist
administered all of the tests. An ICC
above .75 was considered to demonstrate good reliability, although for
clinical measures it has been suggested that the ICC should exceed
.90.43 The ICC indicates similar patterns of scores in several sets of data;
thus, it checks for consistency rather
than absolute agreement in measurements. Thus, if relative reliability is
high, regardless of whether the precise scores given by 2 evaluators differ, then in both cases good performance receives higher scores than
average performance and average
August 2011
The SEM and the MDC90 were calculated with the following formulas44:
SEM ⫽ SD ⫻ 冑共1 ⫺ r),
where r⫽ICC for the participant
group, and
MDC 90 ⫽ SEM ⫻ 1.65 ⫻ 冑2.
The SEM measures absolute reliability and represents the extent to
which a variable can vary in the measurement process.45 Because some
error may be present in a measurement, a range of values is often
reported. A measurement of ⫾1 SEM
represents a 68% confidence interval. Both 90% and 95% confidence
intervals have been used to describe
the MDC.32,46,47 To be 90% confident
about the range for a measurement,
the calculation 1.68 ⫻ SEM should
be used. Minimal detectable change
is defined as the amount of change
in a measurement necessary to
conclude that the difference is not
attributable to error; it is the smallest
change that falls outside the
expected range of error.45,46 Any
change exceeding the MDC90 is considered true change.
The delta (change) scores within
each trial (scores after the test minus
scores before the test) for heart rate
and blood pressure in the STS tests
and the 6MWT and data on the RPE
were reported, and pairwise comparisons between trials were done
with the paired t test or the Wilcoxon signed rank test.
This study was supported by a grant
from Universidad CEU Cardenal Herrera (PRUCH 06/08).
Results
§
Takei Scientific Instruments Co Ltd, No. 619,
Yashiroda, Akiha-Ku, Niigata City, Niigata Prefecture, 956-0113 Japan.
performance receives higher scores
than poor performance.
㛳
60606.
Data were collected from 39 participants (7 women and 32 men). Some
Volume 91
Number 8
Physical Therapy f
1247
Participants undergoing
hemodialysis in 2 settings
(N=39)
1 participant
could not
perform the
second test due
to worsened
health; 1
participant was
unwilling to
attend the
second test
1 participant
could not
perform the
second test due
to worsened
health; 1
participant was
unwilling to
attend the
second test
1 participant could
not perform the
second test due to a
complicated ulcer
on the foot; 2
participants were
unwilling to attend
the second test
One setting was not
conducive to the 1leg heel-rise test (12
participants did not
perform the test at
that setting), and 6
participants from
the other setting
were unwilling to
attend the test
One setting was not
conducive to the
handgrip test (12
participants did not
perform the test at
that setting), and 15
participants from
the other setting
were unwilling to
attend the test
STS-10 data
from 37
participants
STS-60 data
from 37
participants
6MWT data
from 36
participants
One-leg heel-rise
test data from 21
participants
Handgrip strength
test data from 12
participants
Figure.
Flow chart for study participants. STS-10⫽a sit-to-stand-to-sit (STS) test that measures the time (in seconds) required to complete
10 full stands from a sitting position, STS-60⫽an STS test that measures the number of repetitions achieved in 60 seconds,
6MWT⫽Six-Minute Walk Test.
demographic data were not available
(eg, no height for one participant).
One setting was not conducive to
the performance of the handgrip and
one-leg heel-rise tests, so these tests
were not performed with participants in that setting. The flow chart
(Figure) shows the number of participants who performed each test.
No adverse events occurred during
testing.
Descriptive statistics for the 39 participants are shown in Table 1. In 3
participants, the fistula was located
in the dominant arm. The results of
repeated tests are shown in Table 2.
The distance walked during the
6MWT was significantly greater in
trial 2. The ICCs for test-retest reli1248
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Physical Therapy
Volume 91
ability were high for all of the outcome measures (STS-10, STS-60,
6MWT, and one-leg heel-rise test on
the right and left sides). Data for the
handgrip test with the dominant and
nondominant arms were calculated
for 12 participants. There were no
significant differences between trial
1 and trial 2. For the dominant arm,
the means (standard deviations) in
trial 1 and trial 2 were 26.9 (7.3) kg
and 25.9 (7.1) kg, respectively
(P⫽.083); for the nondominant arm,
the means (standard deviations) in
trial 1 and trial 2 were 23.8 (6.6) kg
and 23.4 (7.1) kg, respectively
(P⫽.594). The ICCs for the dominant and nondominant arms were
.96 (95% confidence interval⫽.88 –
.99) and .95 (95% confidence inter-
Number 8
val⫽.83–.98), respectively. The
repeated-measures SEM and MDC90
are shown in Table 3.
Delta scores within trial 1 and trial 2
for heart rate and blood pressure in
the STS tests and the 6MWT are
shown in Table 4. For the 3 physical
function tests, the delta score for
heart rate was significantly higher in
trial 1. There were no differences
between trials in the delta score for
blood pressure or the RPE.
Discussion
Our findings demonstrated that the
test-retest reliability (relative reliability) of the clinical tests was excellent. All measures were found to
have high test-retest reliability, with
August 2011
Table 1.
been reported. The high test-retest
reliability found for the one-leg heelrise test in the present study is similar to values found in patients with
chronic heart failure (ICC⫽.94).51
The ICC of the handgrip strength
test was high, despite the small sample, in agreement with data from
patients with cervical radiculopathy
(ICC⫽.85–.98).52 Our findings consistently showed high test-retest reliability in all of the physical performance tests. Factors that may
explain the high ICCs in all of the
physical performance tests are consistent timing of the tests (same day
of the week, before the hemodialysis
session) and standardization of the
evaluator’s instructions.
Demographic and Clinical Data for Study Participants (N⫽39)
Characteristic
Value
Age, y, X (SD)
60.3 (15.8)
Sex, no. of women:men
7:32
Handedness, no. who were right handed:left handed
a
10:2
Body mass index, kg/m2, X (SD)b
22.0 (3.3)
Time on hemodialysis, mo, median (range)
25 (6–152)
Hemoglobin level, X (SD)
11.3 (1.4)
Cause of kidney disease (no. of participants)
Diabetes mellitus
8
Glomerulonephritis
9
Nephroangiosclerosis
8
Lupus
1
Interstitial nephropathy
1
Other
12
No. of comorbidities, median (range)
a
b
3 (1–5)
n⫽12.
n⫽38.
only the STS-10 having values slightly
below the threshold of .90 for minimal acceptable reliability for a clinical test.43
In the present study, we calculated
an ICC of .94 for the test-retest reliability of the 6MWT. No previous
determinations of the ICC of this test
in people undergoing hemodialysis
exist, although reported values in
other populations32,46,48,49 are consistent (ICC⫽.94 –.98) with our
results.
The STS tests have not been widely
used in people undergoing hemodialysis; however, the ICCs of these
tests in people who are candidates
for a renal transplant (.84),31 adult
populations (.80),38 and people with
chronic low back pain (.91)50 have
The results of the present study demonstrated that although the testretest reliability was excellent, there
was still a substantial degree of variability in performance for individual
participants from 1 test session to
the next, as shown by the SEM and
MDC90 values (Tab. 3). Because the
SEM is based on the assumption of a
normal distribution, the probabilities
of a normal curve can be applied,
and the values from Table 3 can be
translated to clinical practice use.
Thus, there is a 68% probability that
Table 2.
Reliability Results for Physical Performance Tests in People Undergoing Hemodialysisa
X (SD)
Median
(Range)
ICC for
Trial 1
vs
Trial 2
95%
CI for
ICC
P for
Significance of
Difference
Between Trial 1
and Trial 2
24.0 (10.9)
21.6 (9.5–54.1)
.88
.78–.94
.059b
25.5 (9.4)
24 (11–39)
.97
.94–.98
.966b
.94
.89–.97
.002c
Trial 1
No. of
Participants
X (SD)
STS-10 (s)
37
25.1 (10.4)
STS-60 (repetitions)
37
25.6 (9.8)
6MWT (m)
36
425.2 (116.0)
One-leg heel-rise, right
(repetitions)
21
10.8 (9.2)
7 (0–25)
11.6 (9.2)
9 (0–25)
.97
.92–.99
.138b
One-leg heel-rise, left
(repetitions)
21
10.6 (9.1)
8 (0–25)
10.7 (9.0)
7 (0–25)
.94
.85–.97
.505b
Test
Median
(Range)
Trial 2
22 (10.6–53.9)
24.5 (10–56)
445.9 (106.3)
a
ICC⫽intraclass correlation coefficient, CI⫽confidence interval, STS-10⫽a sit-to-stand-to-sit (STS) test that measures the time (in seconds) required to
complete 10 full stands from a sitting position, STS-60⫽an STS test that measures the number of repetitions achieved in 60 seconds, 6MWT⫽Six-Minute
Walk Test.
b
As determined with the Wilcoxon signed rank test of paired samples.
c
As determined with the paired-samples t test (t⫽⫺3.323).
August 2011
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Physical Therapy f
1249
Table 3.
Standard Error of Measurement (SEM) for Repeated Measures and Minimal
Detectable Change Scores at 90% Confidence Intervals (MDC90) for Various Testsa
Test
SEM
MDC90
3.6
8.4
STS-10 (s)
STS-60 (repetitions)
1.7
4.0
28.4
66.3
Handgrip strength, dominant arm (kg)
1.5
3.4
Handgrip strength, nondominant arm (kg)
1.5
3.4
One-leg heel-rise, right (repetitions)
1.6
3.7
One-leg heel-rise, left (repetitions)
2.2
5.2
6MWT (m)
a
STS-10⫽a sit-to-stand-to-sit (STS) test that measures the time (in seconds) required to complete 10
full stands from a sitting position), STS-60⫽an STS test that measures the number of repetitions
achieved in 60 seconds, 6MWT⫽6-minute walk test.
a repeated measure of a test will be
within 1 SEM of the original score,
and there is a 96% probability that a
repeated measure will be within 2
SEMs. This information could be useful for discriminating between true
change and variability of performance, according to the SEM, in an
examination of the repeat performance of people undergoing
hemodialysis.
The 6MWT was the only outcome
measure that was previously
assessed for absolute reliability, in
Alzheimer disease32 and Parkinson
disease46; high individual variability
was reported in both studies. Ries et
al32 reported an ICC of .98, a SEM of
20 m, and an MDC90 of 37 m, and
Steffen and Seney46 reported an ICC
of .96 and an MDC95 of 82 m. Our
results also revealed high variability,
with an MDC90 of 66 m. Even though
measurement
conditions
were
strictly replicated, variations in the
physiological and clinical status of
the participants undergoing hemodialysis could have accounted for some
of the heterogeneity in the results.
The delta scores for the heart rate in
the 6MWT, STS-10, and STS-60 were
significantly higher in the first trial
than in the second trial (Tab. 4),
although medications were kept
constant and the perceived exertion
did not change. This lack of homogeneity also was found in the results
reported for the 6MWT in the literature; for example, distances of 347 to
522 m were found.15,17,18,21,53 Age
was not found to affect the high variability observed in the present study
(results not shown). The significant
difference
in
meters
walked
between trial 1 and trial 2 can be
explained by the practice effect of
the test,16 which could be prevented
by adding a practice trial. The results
reported in the literature for the STS
Table 4.
Heart Rate (HR), Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Rate of Perceived Exertion (RPE) in Response
to Various Testsa
Trial 1
Test
6MWT
STS-10
Parameter
Delta score for HR (bpm)
19.5 (⫺2 to 66)
No. of
Participants
Median
(Range)
in Trial 2
No. of
Participants
38
16 (2 to 63)
36
.038
Delta score for SPB (mm Hg)
15 (⫺37 to 55)
31
11.5 (⫺18 to 65)
30
.829
Delta score for DBP (mm Hg)
3 (⫺24 to 27)
31
1 (⫺17 to 35)
30
.636
36
.369
37
.001
RPE
11 (7 to 16)
38
11 (0 to 49)
38
STS-60
Median
(Range)
in Trial 1
P for
Significance of
Difference
Between Trial 1
and Trial 2
Trial 2
2 (⫺23 to 31)
⫺2 (⫺18 to 9)
11 (7 to 17)
6 (⫺6 to 27)
31
2 (⫺36 to 40)
29
.682
31
0 (⫺19 to 13)
29
.194
RPE
11 (7 to 13)
38
11 (7 to 17)
37
.850
18 (0 to 58)
37
14 (⫺18 to 62)
37
.018
8 (⫺34 to 62)
31
8 (⫺52 to 39)
33
.381
0 (⫺26 to 25)
31
⫺1 (⫺24 to 62)
33
.751
38
13 (11 to 17)
37
.673
RPE
13 (11 to 17)
a
6MWT⫽Six-Minute Walk Test, delta score⫽score after the test minus score before the test within the trial, bpm⫽beats per minute, STS-10⫽a sit-to-standto-sit (STS) test that measures the time (in seconds) required to complete 10 full stands from a sitting position, STS-60⫽an STS test that measures the
number of repetitions achieved in 60 seconds.
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August 2011
tests in patients undergoing hemodialysis also showed some heterogeneity, with results ranging from 21 to
29 seconds on the STS-1011,17,18,21
and 22 repetitions on the STS-60.24
The RPEs for the 6MWT and the STS
tests were lower than expected,
although they were in agreement with
the results of previous research.54 An
underestimation of RPEs has been
observed clinically and practically.16,55
Handgrip strength for the right arm
and the left arm in the present study
were 26.9 and 23.8 kg, respectively;
these values were lower than those
reported in a previous study (41.6 kg
for the right arm and 39.9 kg for the
left arm).18 We found that fistula location had no effect on handgrip
strength (results not shown). Future
studies with a larger number of participants should include results related
to sex and age.56
One-leg heel-rise repetitions in the
present study were below 25, the
value established as normal in 2 studies.25,42 Jan et al57 showed that the
ability to repeat heel rises was
closely related to age and sex in a
study in which adults who were
healthy and older than 60 years of
age achieved only 20 or fewer repetitions. Because people in poor physical condition are not able to perform a single repetition, future
studies are needed to clarify whether
the floor effect of this test allows
discrimination among people with
different physical conditions. Additionally, this test is difficult for only
one observer to control because control of both flexion of the knee and
leaning or pushing against the wall is
required.
The present study indicated that the
6MWT, STS-10, STS-60, one-leg heelrise test, and handgrip strength test
are reliable measures. Clinicians are
encouraged to understand how
changes in scores translate to clinical
practice. On the basis of our results, if
a change exceeding ⫾66 m (MDC90)
August 2011
occurs in the 6MWT, clinicians can be
90% confident that the difference is
not due to measurement error or variability among participants. Clinicians
could arrive at similar conclusions for
all tests being evaluated.
In conclusion, the results of the present study demonstrated excellent
test-retest reliability for the 6MWT,
STS-10, STS-60, one-leg heel-rise test,
and handgrip strength test in people
undergoing hemodialysis. Despite
high ICCs for absolute reliability, there
was important individual variability in
the performance of these measures.
The SEM and MDC90 values for each of
the tests provide clinicians with
thresholds for identifying changes
beyond those expected from measurement error and individual variability.
This information will help in monitoring performance changes over time
and assessing the effectiveness of
exercise interventions in people
undergoing hemodialysis.
Both authors provided concept/idea/research
design, data collection and analysis, participants, facilities/equipment, and consultation
(including review of manuscript before submission). Ms Segura-Ortı́ provided writing
and project management.
The study was approved by the ethical
review boards of the Universidad CEU Cardenal Herrera and the Fundación Hospital General Universitario de Valencia, Valencia,
Spain.
This study was supported by a grant from
Universidad CEU Cardenal Herrera (PRUCH
06/08).
DOI: 10.2522/ptj.20100141
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August 2011
Research Report
Development of a Scale to
Assess Avoidance Behavior
Due to a Fear of Falling:
The Fear of Falling Avoidance
Behavior Questionnaire
Merrill R. Landers, Cortney Durand, D. Shalom Powell, Leland E. Dibble,
Daniel L. Young
Background. A history of falls or imbalance may lead to a fear of falling, which
may lead to self-imposed avoidance of activity; this avoidance may stimulate a vicious
cycle of deconditioning and subsequent falls.
Objective. The purpose of this study was to develop a questionnaire that would
quantify avoidance behavior due to a fear of falling.
Design. This study consisted of 2 parts: questionnaire development and psychometric testing. Questionnaire development involved an expert panel and 39 residents
of an assisted living facility. Sixty-three community-dwelling individuals with various
health conditions participated in psychometric testing.
Method. Questionnaire development included the evaluation of face and content
validity and factor analysis of the initial questionnaire. The final result of questionnaire development was the Fear of Falling Avoidance Behavior Questionnaire
(FFABQ). In order to determine its psychometric properties, reliability and construct
validity were assessed through administration of the FFABQ to participants twice,
1 week apart, and comparison of the FFABQ with other questionnaires related to fear
of falling, functional measures of balance and mobility, and daily activity levels using
an activity monitor.
Results. The FFABQ had good overall test-retest reliability (intraclass correlation
coefficient⫽.812) and was found to differentiate between participants who were
considered “fallers” (ie, at least one fall in the previous year) and those who were
considered “nonfallers.” The FFABQ predicted time spent sitting or lying and
endurance.
Limitations. A relatively small number of people with a fear of falling were
willing to participate.
Conclusion. Results from this study offer evidence for the reliability and validity
of the FFABQ and support the notion that the FFABQ measures avoidance behavior
rather than balance confidence, self-efficacy, or fear.
M.R. Landers, PT, DPT, OCS,
Department of Physical Therapy, School of Allied Health Sciences, Division of Health Sciences,
University of Nevada, Las Vegas,
4505 Maryland Pkwy, Box
453029, Las Vegas, NV 891543029 (USA). Address all correspondence to Dr Landers at:
[email protected].
C. Durand, PT, DPT, Fernley Physical Therapy, Fernley, Nevada,
and Department of Physical Therapy, School of Allied Health Sciences, Division of Health Sciences,
University of Nevada, Las Vegas.
D.S. Powell, PT, DPT, Department
Allied Health Sciences, Division
of Health Sciences, University of
Nevada, Las Vegas.
L.E. Dibble, PT, PhD, ATC, Department of Physical Therapy, University of Utah, Salt Lake City, Utah.
D.L. Young, PT, DPT, Department
Allied Health Sciences, Division
of Health Sciences, University of
Nevada, Las Vegas.
[Landers MR, Durand C, Powell
DS, et al. Development of a scale
to assess avoidance behavior due
to a fear of falling: the Fear of
Falling Avoidance Behavior Questionnaire. Phys Ther. 2011;91:
1253–1265.]
Association
2011
Submitted: September 10, 2010
this article at:
ptjournal.apta.org
August 2011
Volume 91
Number 8
Physical Therapy f
1253
Fear of Falling Avoidance Behavior Questionnaire
I
t has been reported that 28% to
35% of individuals 65 years of age
and older will fall within a year’s
time, exposing them to serious
potential injury.1 Although injuries
as a result of a fall can be significant,2–7 a fear of falling may be a
more serious problem, as it may lead
to restricted activity and mobility in
elderly people.2,3,8 Research indicates 50% of the elderly population
have a fear of falling after experiencing just one fall, and a quarter of
these individuals describe avoiding
some activity due to their fear.6 A
fall, however, is not a prerequisite to
the fear of falling or subsequent
activity restriction.2,9 Howland et al2
reported 20% of individuals who
had not recently experienced a fall
were still somewhat or very afraid of
falling. Therefore, “fallers” and “nonfallers” alike may have a fear of falling that may lead to inactivity and
social isolation, which in turn could
stimulate deconditioning, functional
decline, and decreased quality of
life.2,10 –14
Despite the availability of many balance impairment tools, balance confidence measures, and self-efficacy
measures, there is a need for a practical, clinical tool that can help
quantify the effect of fear of falling on activity and participation,
as defined by the International Classification of Functioning, Disability
and Health (ICF).15 The most commonly used self-perceived balance
confidence and efficacy questionnaires—the Activities-specific Balance Confidence (ABC) Scale16 and
the Falls Efficacy Scale (FES)17—
appear to be adequate at measuring “confidence” and “self-efficacy,”
respectively, with activities of daily
living (ADL); however, both questionnaires fail to capture the downstream consequence (ie, activity
limitation and participation restriction) that a lack of confidence or
decreased self-efficacy has on performing functional tasks. Further1254
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Physical Therapy
Volume 91
more, the ABC Scale and the FES
do not assess whether this confidence translates into avoidance
behavior. Instead, these questionnaires are focused on the ICF-defined
personal factors rather than activity
and participation. Research has indicated these fall-related instruments
often are used beyond the scope of
their original design to measure fear
of falling.18 Although performancebased measures of balance, gait,
and fall risk (ie, Berg Balance Scale
[BBS],19 –22 Dynamic Gait Index
[DGI],7,23–25 Timed “Up & Go” Test
[TUG],7,22 Functional Reach Test
[FRT],26 –28 and dynamic posturography29,30) are good at measuring different aspects of balance and fall
risk, they fail to capture the role and
influence that the fear of falling has
on activity and participation. In addition, the use of fall incidence is not
an adequate measure of avoidance
behavior, as an individual may avoid
activities out of fear without having
had any falls.8
There are few survey instruments
that measure the effect of fear of
falling on activity. The Survey of
Activities and Fear of Falling in the
Elderly (SAFFE) is an interviewbased, 11-item survey instrument
intended to differentiate individuals
who restrict their activity because of
fear of falling from those who do
not restrict their activity but still
have a fear of falling.31 Although no
test-retest reliability was published
for the original SAFFE measure, the
authors did provide evidence for
convergent validity of the SAFFE.31,32
Evidence for reliability and validity of
the SAFFE has been found recently
for individuals with Parkinson disease (PD).33 Deshpande et al34 found
SAFFE scores indicating severe and
moderate activity restriction due to a
fear of falling to be an independent
predictor of increasing independent
ADL disability. On the other hand,
Hotchkiss et al35 found that the
SAFFE was unable to accurately pre-
Number 8
dict frequency of falls, activity limitation, and frequency of leaving
home. The FES was a better predictor of people who exhibited activity restriction compared with the
SAFFE, even though the FES is not
intended to measure activity restriction.34 Although the SAFFE instrument has items consistent with the
ICF levels of activity and participation, it is a 6-page document that
involves qualitative and quantitative
components, making it less userfriendly as well as time-consuming to
complete and score. The SAFFE was
designed to be administered in a
face-to-face interview and has been
described by researchers as “too
long and burdensome” to administer, making it less practical for clinicians and researchers.18,36
A modified version of the SAFFE
(Modified Survey of Activities and
Fear of Falling in the Elderly
[mSAFFE]) is a 17-item scale directed
at activity avoidance.37 It was
designed to be a self-administered
questionnaire, which would be more
efficient and less time-consuming to
administer, complete, and score than
its predecessor. The mSAFFE was
found to have satisfactory test-retest
reliability (rho⫽.75), but no validity
was reported.37 Moore and Ellis18
compared the SAFFE and mSAFFE
and reported that the mSAFFE may
be a more useful measure of fear of
falling and its effects on activity
restriction, but they concluded that
more research is needed to support
the measure prior to its use.
The Geriatric Fear of Falling Measure
(GFFM) was created as a quick and
culturally relevant measure of fear of
falling for community-dwelling older
adults living in Taiwan.38 It comprises 3 subscales (psychosomatic
symptoms, risk prevention, modifying behavior), with a total score of
15 points, that are intended to measure activity restriction.38 The
GFFM has good test-retest reliability
August 2011
(r⫽.88) but poor validity (r⫽.29)
compared with the FES.38 However,
generalizability also is an issue for
the GFFM, as the authors acknowledged the data are limited to Taiwanese older adults and suggested reliability and validity should be
investigated further.18,38 The body of
research on these measures emphasizes the effect of fear-avoidance
behaviors on mobility. However,
given the existing methodological
limitations, there is still a need for a
convenient and reliable clinical tool
that can be used on heterogenous
populations to standardize avoidance behavior at the level of activity
and participation.
To address this need, we are proposing a new, practical self-assessment
measurement tool, the Fear of
Falling Avoidance-Behavior Questionnaire (FFABQ). The FFABQ quantifies avoidance behavior (activity limitation and participation restriction)
related to the fear of falling. It was
based on the fear-avoidance model of
exaggerated pain perception presented by Lethem et al39 and Troup
et al.40 This model is used to understand the psychogenic component
of an individual’s condition that may
cause avoidance of certain activities.41 The model explains that individuals learn through operant conditioning to fear situations or stimuli
that cause harm or stress and, as a
result, to avoid that situation or these
stimuli.41 The premise for the FFABQ
was that individuals with a fear of
falling (secondary to a previous fall
or awareness of the negative consequences of falling) would avoid
activities that put them at a risk for a
fall. Therefore, the FFABQ would
capture the avoidance of activities
that would result from a fear of
falling.
An important goal of this project
was to create a tool that would aid
the researcher and the clinician alike
in quickly, quantitatively, and reliAugust 2011
ably assessing avoidance behavior
(activity limitation and participation
restriction) due to a fear of falling.
The FFABQ was not intended to be
used in isolation but as a complement to other balance assessment
tools in creating a more complete
picture of the effects that balance
impairment and falls have on a
patient’s life. The purposes of this
study were to outline the development of this questionnaire and to
examine its psychometric properties
and validity, so that it may be used in
conjunction with other measurement tools to help create a more
complete picture of the influence
that falls, fall-avoidance behavior,
and balance deficits have on the individual’s life. Our specific hypothesis
was that people with a history of
falling would report more fearavoidance behavior. In addition,
because we believe that the FFABQ
measures a different but tangentially
related construct compared with
other commonly used clinical balance tests, we hypothesized that
there would be moderate correlations with these other tests. Lastly,
we expected the FFABQ to contribute a unique amount of the variation
beyond what is accounted for by
other scales with a similar construct.
Method
The overall design of the study
involved 2 main components:
(1) questionnaire development and
(2) questionnaire psychometrics.
Questionnaire development included
face validity, content validity, and a
pilot study analysis of the initial questionnaire. The goal of this phase was
to improve the syntax and appropriateness of the individual items on
the questionnaire by using an expert
panel of physical therapists and
patients with a history of falling. In
addition, other questions or items
that were not present in the questionnaire would be added if the item
domain was missing or underrepresented. A secondary goal of the
development was to remove items
that were redundant or very similar
to other items. Ultimately, this process would shape the questionnaire
into a final iteration, which then
would undergo psychometric testing. This testing would include analysis of the reliability and construct
validity of the final questionnaire.
The goal of this phase was to establish the psychometric properties of
this questionnaire. All participants
provided written informed consent
prior to the study.
Questionnaire Development:
Face Validity, Content Validity,
and Pilot Study Analysis
Face and content validity of the original 21-item questionnaire, as conceptualized by its developers, were
determined by a panel of 13 experts:
7 physical therapy educators (including 4 who have published research
related to balance or falls), 1 physical
therapist who was a generalist, 3
physical therapists whose specialty
was balance, and 2 patients with a
history of falling. In addition to being physical therapists, several of
the panel members provided additional breadth and depth of expertise through their experiences in
community-based programs for people with PD and with family members who had restricted their activity
due to a fear of falling. They were
asked to assess the overall face and
content validity of the questionnaire
through an assessment of the language and the relevance of each individual item.
Each item was stated as follows:
“Due to my fear of falling, I
avoid . . . (activity or participation),”
with the following anchors: completely disagree, disagree, unsure,
agree, completely agree. Each statement was scored using a Likert-style,
5-point ordinal scale (0⫽completely
disagree to 4⫽completely agree),
resulting in a total possible score of
84 points. A higher score indicates
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Table 1.
International Classification of Functioning, Disability and Health (ICF) Information Matrix Domain Codes for Each of the Fear of
Falling Avoidance Behavior Questionnaire Items
Item No.
Due to My Fear of Falling, I Avoid:
Walking
Walking (d450)
2
Lifting and carrying objects (eg, cup, child)
Lifting and carrying objects (d430)
3
Going up and downstairs
Walking (d450)
Moving around (d455)
Moving around in different locations (d460)
4
Walking on different surfaces (eg, grass, uneven
ground)
Walking (d450)
5
Walking in crowded places
Walking (d450)
6
Walking in dimly lit, unfamiliar places
Walking (d450)
Products and technology for personal use in
daily living (e115)
7
Leaving home
8
Getting in and out of a chair
Changing basic body position (d410)
9
Showering or bathing
Washing oneself (d510)
10
Exercise
Looking after one’s health (d570)
11
Preparing meals (eg, planning, cooking, serving)
Preparing meals (d630)
12
Doing housework (eg, cleaning, washing clothes)
Doing housework (d640)
13
Work or volunteer work
Remunerative employment (d850)
Nonremunerative employment (d855)
14
Recreational and leisure activities (eg, play,
sports, arts and culture, crafts, hobbies,
socializing, traveling)
Recreation and leisure (d920)
greater activity limitation and participation restriction as a result of
the fear of the falling.
The initial version of the questionnaire was pilot tested on 39 residents
of an assisted living facility (mean
age⫽85.03 years, SD⫽5.1; 16 fallers,
23 nonfallers; 11 male, 28 female) to
assess each of the items of the questionnaire with factor analysis. These
individuals were recruited using convenience sampling and consented to
participate in the study with institutional review board approval. Factor
analysis was used to reduce the number of items of the questionnaire
by identifying items that had high
intercorrelations. Results from the
expert panel and the factor analysis
guided several changes to the questionnaire. Items that resulted in high
intercorrelations were combined or
eliminated. Based on the panel recommendations, several items were
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ICF Information Matrix Domain Codes
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Volume 91
reworded to be more consistent
with the domains of the ICF model of
activity limitation and participation
restriction (Tab. 1). Those items that
were not consistent with ICF model
domains were dropped from the
questionnaire. The final version of
the questionnaire (ie, the FFABQ)
consisted of 14 items (Appendix)
ranked using the same Likert-style,
5-point ordinal scale as described
above, resulting in a total possible
score of 56 points. A high score indicates greater activity limitation and
participation restriction as a result of
the fear of the falling.
Questionnaire Psychometrics:
Reliability and Construct Validity
Participants. The goal of participant recruitment for this portion
of the study was to achieve variability in the amount of fear of falling and avoidance behavior. Therefore, a heterogenous sample with rel-
Number 8
atively equivalent populations of
those with and without fear of falling was needed. In order to obtain
this desired sample, individuals who
were healthy (presumably without
balance problems) as well as those
with pathologies known to have a
high prevalence of balance problems (eg, cerebrovascular accident
[CVA], PD) were the target populations for recruitment. Subsequently,
63 individuals (23 men and 40
women) with a mean age of 72.2
years (SD⫽7.2, range⫽60 – 88) were
recruited as a convenience sample
through snowball sampling at local
senior centers, physical therapy balance clinics, and various support
groups (eg, PD support group,
stroke support group) in Las Vegas,
Nevada. The participants were
English-speaking and communitydwelling individuals of 60 years of
age or older. The Mini-Mental State
Examination (MMSE) was used to
August 2011
Table 2.
Primary Fall Categories and Their Respective Health Conditions
Total No. of
Participants (%)
Healthy
Parkinson
Disease
Cerebrovascular
Accident
Diabetes
Cardiovascular
Diagnosis
Faller
25 (39.7%)
8
7
8
1
1
Frequent faller
12 (19.0%)
3
3
5
0
1
Recent faller
11 (17.5%)
2
3
5
0
1
Injured faller
11 (17.5%)
5
3
2
0
1
Fall Category
Table 3.
Self-Perceived Balance Confidence and Self-Efficacy Questionnaires
Standardized Scale
Evidence for
Reliability
Construct
No. of Items
Activities-specific
Balance Confidence
Scale16
Self-administered assessment
of confidence with
balance during various
activities of daily living
16 items, scores ranging from
0% (not confident) to
100% (very confident)
r⫽.9216
Correlated with age, balance
score, gait scores, mobility
scores, and falls in the
previous year63
Falls Efficacy Scale17
Self-administered assessment
of self-efficacy in
completing activities of
daily living without falling
10 items, total scores ranging
from 10 (very confident) to
100 (not confident)
r⫽.7117
Correlated with age, balance
score, gait scores, mobility
scores, and falls in the
previous year63
determine the level of cognition of
the participants. Those with moderate cognitive impairment (⬍21 on
the MMSE) were excluded.42,43 The
participants’ primary health conditions were as follows: 25 were
healthy, 16 had PD, 11 had a history
of CVA, 6 had diabetes, and 5 had a
cardiovascular diagnosis (eg, coronary artery bypass, angina). Nine
individuals had secondary diagnoses
(eg, diabetes), but had a primary
diagnosis that was more pronounced
(eg, CVA).
Participants also were classified
using their recollection of their fall
history. Twenty-five individuals were
classified as a faller, defined as an
individual who had at least one unexplained event where he or she
descended to the floor in the previous year (Tab. 2). Twelve individuals
were classified as frequent fallers,
defined as having had 2 or more falls
in the previous year. Eleven individuals were classified as recent fallers,
defined as having had a fall in the
previous month. An injured faller
was defined as an individual who sustained an injury from a fall that
August 2011
required medical assistance in the
previous year. Eleven individuals
were classified as injured fallers.
These categories of classification
were not mutually exclusive; as a
result, a participant may have been
placed in more than one category
(Tab. 2).
Reliability. In order to determine
test-retest reliability, the FFABQ was
administered to 63 participants
twice, approximately 1 week apart.
The first administration of the
FFABQ was timed to determine the
average length for completion. Two
individuals were not included in the
reliability analysis because they
experienced a fall during the testretest period. Minimal detectable
change (MDC) was calculated based
on the standard error of measurement (SEM) using the test-retest reliability statistic, where rxx⫽test-retest
reliability44 – 46: SEM⫽baseline standard deviation ⫻ 公1 ⫺ rxx . Once
the SEM was determined, the MDC at
a 95% confidence level (MDC95) for
the questionnaire was calculated by
multiplying the SEM by 1.96 (representing 95% of the area under the
Evidence for Validity
curve of a normal distribution) and
1.41 (the square root of 2 to control
for possible error associated with calculating the coefficient from 2 data
sets [ie, test and retest]).44
Construct and convergent validity. Construct validity was assessed
via known-groups analysis and convergent validity. The purpose of
the known-groups analysis was to
compare a known characteristic,
related to the construct of interest,
which would allow logical inferences about the validity of the measurement tool (ie, FFABQ). For this
study, our known-groups characteristic was the dichotomous response
(“yes” or “no”) of the participants
regarding their fall history (ie, faller,
frequent faller, recent faller, or
injured faller) (Tab. 2). Independentsamples t tests were utilized to determine whether there was a difference
between participants with a history
of falling and those without a history of falling based on their FFABQ
scores. It was presumed that those
with a history of falling would have
more avoidance behavior than those
without a fall history.
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Table 4.
Performance-Based Balance Assessment Toolsa
Standardized Scale
a
Construct
No. of Items
Evidence for
Reliability
Berg Balance Scale19
Clinician-rated assessment of
balance tasks
14 tasks, total score 0
(greatest fall risk) to
56 (least fall risk)
ICC⫽.9819,20
Validated for populations that
had a cerebrovascular
accident or Parkinson
disease20,64 and to predict
future falls65
Dynamic Gait Index25
Clinician-rated assessment of
ability to modify gait under
various conditions
Eight tasks, total score
ranging from 0
(greatest fall risk) to
24 (least fall risk)
ICCⱖ.98324,66
Correlated with Berg Balance
Scale, timed walking test,
Timed “Up & Go” Test,
and Activities-specific
Balance Confidence Scale in
chronic stroke (range⫽.68–
.83)67 and to predict fall
risk68
Sensory Organization
Test
Computerized posturography
used to challenge the 3
sensory components of
balance
Composite score of 6
scenarios, ranging
from 0 to 100 based
on age and heightadjusted averages
ICC⫽.6666
Able to predict individuals
with 2 or more falls in the
previous 6 mo with cutoff
score of 3869
Limits of stability
Computerized posturography
used to assess how far
individual can purposefully
displace center of gravity
for 8 seconds
Five scores (reaction
time, movement
velocity, endpoint
excursion, maximum
excursion, and
directional control)
based on age and
height-adjusted
averages
Movement time ICC
(2,1)⫽.825
Path sway ICC
(2,1)⫽.846
Distance error ICC
(2,1)⫽.63270
Anterior displacement was
correlated to the Sensory
Organization Test
composite score for fallers
(r⫽.79, P⫽.006)30
Timed “Up & Go”
Test7,22
A timed test of functional
mobility
Three components
(standing up,
walking, and sitting
down) where longer
than 30 seconds
indicated
dependence in
mobility
Intrarater and
interrater r values
ranging from .93
to .9971
Correlated with Functional
Independence Measure
(⫺.59 at P⬍.001) in older
individuals,72 Tinetti
balance measure scores
r⫽⫺.55, Tinetti gait
measure scores (r⫽⫺.53),
and walking speed (r⫽.66)
where longer performance
times predicted fall
occurrence and decline in
performance of activities of
daily living in communitydwelling older people71
Self-selected gait
speed73
Timed comfortable walking
pace over 10 m
N/A
ICC⫽.9574
Slow walking speed
associated with a fear of
falling75
ICC⫽intraclass correlation coefficient, N/A⫽not applicable.
Convergent validity was evaluated
by comparing the FFABQ with measures of the same or similar constructs as other balance assessments
using correlational statistics (Pearson
product moment correlations) and
multiple regression analysis (stepwise entry). In this study, the FFABQ
was compared with the following 3
categories of assessment tools: selfperceived balance confidence and
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self-efficacy questionnaires (Tab. 3),
performance-based balance assessment tools (Tab. 4), and endurance
and activity level measures (Tab. 5).
Activity levels were measured using
activPAL monitors,* which measured
the number of hours each day a par* PAL Technologies Ltd, 141 St James Rd, Glasgow G4 0LT, United Kingdom.
Number 8
ticipant spent sitting or lying down,
standing upright, and stepping. The
monitors also measured the number
of times the individual transitioned
from sitting to standing or vice versa
(up/down transitions) and metabolic equivalent of tasks (METs)
performed each day. The activPAL
software estimates METs by taking
commonly accepted MET values
for the aforementioned tasks and
August 2011
Table 5.
Endurance and Activity Level Measuresa
Standardized
Scale
a
Construct
No. of Items
Evidence for Reliability
Six-Minute Walk
Test
A functional walking endurance
test where the individual
walks as far as possible in
6 min
N/A
High intraclass correlation between
trials for adults older than 60
years of age: trials 1 and 2
(.88⬍r⬍.94), trials 2 and 3
(.91⬍r⬍.97)76
Correlated with treadmill
scores (r⫽.78) and
functional ability76
Activity monitor61
A device that measures
activity levels for a 1-wk
period
Five components: hours sitting
or lying, hours standing,
hours stepping, up/down
transitions, and metabolic
equivalent of tasks
Interdevice reliability of step
number and cadence: ICC
(2,1)ⱖ.9961
Absolute percentage of error
⬍1% for outdoor
ambulation, ⱕ2% for
walking speeds of
ⱕ0.67 m/s62
ICC⫽intraclass correlation coefficient, N/A⫽not applicable.
applying them to the individual’s
daily activity. These types of activity monitors have been used in the
past as a measure of walking activity in patients with spinal cord
injury and cerebral palsy.47,48 Activity levels, as measured by these monitors, are not a direct measurement
of activities or participation; they
are, however, an indirect indicator
of more movement, which would
occur if someone were active (eg,
walking). In a general sense, this
measurement would allow some
logical inferences about whether
someone was active (ie, low FFABQ
scores) or not (ie, high FFABQ
scores). Someone who has significant activity limitation or participation restriction may not be moving
around very much and would logically register low activity levels on
activity monitors. On the other hand,
someone who is engaged in activities
and participation may register high
activity levels on the activity monitors. Participants were asked to wear
the activity monitors for 7 days; however, only data from days 2 through 6
were included and averaged for use
in analysis because on days 1 and 7
participants did not have the monitor for a full day.
Results
Reliability
Overall test-retest reliability was
.812 (95% confidence interval (CI)⫽
August 2011
Figure.
Confidence interval distribution among varied fall history groups. FFABQ⫽Fear of
Falling Avoidance Behavior Questionnaire.
.706 –.883), with 90.9 seconds as
the average time of completion for
the FFABQ (mean⫽90.9 seconds,
SD⫽49.5). The test-retest reliability
for participants with neurological
involvement (ie, cerebrovascular
accident, PD) was good (intraclass
correlation coefficient [ICC] (3,1)⫽
.751, 95% CI⫽.524 –.878). Likewise,
good reliability was noted for those
reporting no health conditions (ICC
[3,1]⫽.798, 95% CI⫽.593–.905).
Reliability was not analyzed for the
other health conditions, as there
were not enough participants for
each of the diagnostic categories.
The individual MDC95 was 14.69
scale points for the overall sample
(95% CI⫽11.61–17.77).
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Table 6.
Correlation Statistics of the Fear of Falling Avoidance Behavior Questionnaire With
Other Measures of Balance and Activity
r
r2
⫺.678a
.460
.558a
.311
Berg Balance Scale
⫺.498a
.248
Dynamic Gait Index
⫺.585
a
.342
Self-selected gait speed
⫺.475a
.226
Timed “Up & Go” Test
a
.279
⫺.385a
.148
.280b
.078
Measure
Self-perceived balance/fall confidence questionnaires
Activities-specific Balance Confidence Scale
Falls Efficacy Scale
Performance-based balance assessment tools
.528
Sensory Organization Test composite score
Limits of stability
Reaction time
Movement velocity
⫺.295
b
.087
Maximum excursion
⫺.285b
.081
Endpoint excursion
⫺.238
.057
Directional control
⫺.200
.040
Six-Minute Walk Test
⫺.523a
.274
Hours sitting or lying
a
Endurance and activity level measures
a
b
.326
.106
Hours standing
⫺.214
.046
Hours stepping
⫺.420a
.176
Steps per day
⫺.416a
.173
Up/down
⫺.227
.052
Metabolic equivalent of task
⫺.431a
.186
Correlation is significant at Pⱕ.01 (2-tailed).
Correlation is significant at Pⱕ.05 (2-tailed).
Known-Groups Validity Analysis
There was a statistically significant
difference between fallers (mean⫽
17.48, SD⫽15.20, 95% CI⫽11.20 –
23.76) and nonfallers (mean⫽7.97,
SD⫽8.28, 95% CI⫽5.25–10.70) on
FFABQ scores (t[61]⫽2.860, P⫽.007;
homogeneity violation, P⫽.005)
(Figure). The number of falls in the
previous year also correlated significantly with the FFABQ scores
(r⫽.408, r2⫽.166). Likewise, there
was a statistically significant difference between the frequent fallers
(mean⫽23.83, SD⫽17.54, 95% CI⫽
12.69 –34.98) and nonfrequent fallers (mean⫽8.90, SD⫽8.83, 95%
CI⫽6.42–11.38) on the FFABQ
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(t[61]⫽2.864, P⫽.014; homogeneity
violation, P⫽.013) (Figure).
There also was a statistically significant difference between recent fallers (mean⫽24.55, SD⫽17.52, 95%
CI⫽12.78 –36.31) and nonrecent
fallers (mean⫽9.04, SD⫽9.07, 95%
CI⫽6.51–11.56) (t[61]⫽2.856, P⫽
.015; homogeneity violation, P⫽
.008) (Figure). However, there was
not a statistically significant difference between the injured fallers
(mean⫽19.00, SD⫽17.70, 95% CI⫽
7.11–30.89) and the noninjured fallers (mean⫽10.21, SD⫽10.49, 95%
CI⫽7.29 –13.13) (t[61]⫽1.589, P⫽
Number 8
.139; homogeneity violation, P⫽
.001; power⫽10.8%).
Convergent Validity Analysis
Table 6 contains the correlational
statistics for the relationships of
the FFABQ to self-perceived balance and fall confidence questionnaires (ie, ABC Scale and FES),
performance-based balance assessment measures (ie, BBS, DGI, selfselected gait speed, TUG, Sensory
Organization Test [SOT], and limits
of stability [LOS]), and endurance
and activity level measures (ie, SixMinute Walk Test [6MWT] and activity monitor results). The FFABQ
scores correlated moderately with
the ABC Scale, FES, BBS, DGI, TUG,
and 6MWT scores. No significant
correlations were noted between the
FFABQ and the LOS endpoint excursion, LOS directional control, daily
hours standing, and daily up/down
transitions.
Multiple linear regression analyses
were used to compare the predictive
validity of the variables with the
most similar theoretical concepts
(ie, FFABQ, ABC Scale, and FES) on
measures of endurance (ie, 6MWT)
and daily physical activity (ie, sitting
or lying, stepping, up/down transitions, and daily METs). The only
variable that correlated significantly
with sitting or lying was the FFABQ
(b⫽.055, ␤⫽.326, t⫽2.692, P⫽.009).
The FFABQ explained 9.2% of the
variance of time spent sitting or lying
(adjusted r2⫽.092). None of the variables entered into the regression predicted time spent standing. However, the ABC Scale did significantly
predict stepping (b⫽.016, ␤⫽.476,
t⫽4.229, P⬍.0005), explaining 21.4%
of the variance (adjusted r2⫽.214).
Likewise, the ABC Scale was the
only variable that was entered into
the final model for prediction of
up/down transitions (b⫽.262, ␤⫽
.340, t⫽2.828, P⫽.006) and daily
METs (b⫽.030, ␤⫽.435, t⫽3.773, P⬍
.0005), explaining 10.1% (adjusted
August 2011
r2⫽.101) and 17.6% (adjusted
r2⫽.176) of the variance, respectively. Both the ABC Scale (b⫽
2.209, ␤⫽.345, t⫽2.413, P⫽.019)
and the FFABQ (b⫽⫺3.194,
␤⫽⫺.290, t⫽2.030, P⫽.047) were
found to be correlated significantly
with distance on the 6MWT. The full
model explained approximately
31.6% of the variance (adjusted r2⫽
.316), with the ABC Scale explaining
28.1% (adjusted r2⫽.281) and the
FFABQ explaining an additional 3.5%
of the variance over and above the
ABC Scale. Without the ABC Scale
entered into the analysis, the FFABQ
explained 26.2% (adjusted r2⫽.262)
of the variance in the 6MWT scores.
Discussion
The primary purpose of this study
was to develop a questionnaire that
would be a practical, self-assessment
tool with sound psychometric properties for measuring avoidance
behavior due to a fear of falling. Our
results offer preliminary evidence
for the reliability and validity of the
FFABQ for the assessment of activity
limitation and participation restriction due to a fear of falling in
community-ambulating elderly people. In addition, these results suggest
that the FFABQ may have utility as
a complementary assessment tool
with other balance assessment tools
to help create a more complete picture of the influence that balance
impairment and falling have on a
patient’s life.
The FFABQ was reliable for
community-ambulating elderly people with different diagnoses. Therefore, we feel that it can be reasonably
used with all patients who have normal cognition or only mild cognitive deficits and suspected avoidance behavior due to a fear of
falling. Because of its good reliability and ease of use, as evidenced
by the short average time of completion (approximating 1.5 minutes), it offers the clinician a quick,
August 2011
consistent, and standardized assessment tool. In addition, with an
MDC of 15 scale points, the therapist can be confident that a change
in score beyond this value would
be indicative of a significant increase
or decrease in activity and
participation.
The validity of the FFABQ was supported by results from the knowngroups analysis of this study. Participants who were classified as fallers
reported a greater amount of avoidance behavior, as measured by the
FFABQ, compared with nonfallers.
As previous research has indicated,
people who have experienced a fall
may restrict activities or situations
that would put them at risk for
falling.2,6,12 Frequent fallers (2 or
more falls in the previous year)
also reported more avoidance behavior than nonfrequent fallers (one
fall or fewer in the previous year).
This result is consistent with findings by Delbaere et al.49 In addition, the more often a person fell,
the more fear-avoidance behavior
was exhibited. Although the correlation between the number of falls
and the FFABQ scores was in
the low-moderate range (r⫽.408),
these results suggest that there may
be a dose-dependent relationship
between falling and fear-avoidance
behavior. Recent fallers, presumably
because of a fresh memory from the
proximity of the incident, also exhibited more avoidance behavior, as
measured by the FFABQ. In addition,
individuals classified as fallers, frequent fallers, or injured fallers may
have increased anxiety from the fall
or anxiety related to their unsteadiness. This anxiety may contribute
to a vicious cycle involving fear
of falling, activity and participation restriction, and vulnerability to
future falls.50
We had hypothesized that individuals who had sustained an injury due
to a fall would be more likely to
restrict their activity. Despite the
mean difference of 8.79 scale points
on the FFABQ, this hypothesized
outcome was not the case in the
present study. In relation to current
evidence, our findings add little to
the inconsistent data from other
studies on fall injuries and avoidance behavior. One study showed
that individuals who restricted their
activity were more likely to have a
history of an injurious fall in the previous year,51 whereas other studies
showed there was no association
between activity restriction and a fall
causing an injury.52,53 However, we
cannot rule out the possibility of a
type II error because this comparison was clearly underpowered at
10.8%.
Self-perceived balance confidence
and self-efficacy questionnaires (ie,
ABC Scale and FES) were most
strongly correlated with the FFABQ.
These moderate correlations may
have been due to the possible contributing roles of confidence and
self-efficacy on performing activities.54,55 That is, if a person feels
more confident and capable in completing an activity, he or she will
perform that activity more often.
Although the constructs of confidence and self-efficacy differ from
that of fear-avoidance behavior, the
correlations noted in our study suggest these constructs are similar or
closely related. If the FFABQ was
truly measuring the same construct
as either the FES or the ABC Scale,
we would have observed higher
intercorrelations. Therefore, these
results support the notion that the
FFABQ measures avoidance behavior
rather than balance confidence, selfefficacy, or fear.
The FFABQ also was moderately correlated with many performancebased measures of balance, which
supports previous research that
associates activity limitation with
decreased physical capacity.52,56,57
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Physical Therapy f
1261
This association is reasonable
because people with high avoidance
behavior due to a fear of falls would
logically have had some balance dysfunction.58 The performance-based
measures that had a greater dynamic
component (ie, BBS, DGI, selfselected gait speed, and TUG) were
most strongly correlated with FFABQ
scores. The most logical explanation is that participants with more
avoidance behavior (ie, high FFABQ
scores) had poorer dynamic balance
capabilities. This finding also may be
a result of decreased dynamic activity caused by avoidance behavior
that has been shown to cause slower
times on physical performance tests
(eg, walking rapidly for 6.096 m
[20 ft], turning a circle, rising from a
chair 3 times).51
Performance-based measures of balance with a more static component
(ie, SOT and LOS) also were correlated with the FFABQ, but these correlations were considerably lower
than the dynamic measure correlations. Delbaere et al49 found that fear
of falling and avoidance behavior
measured by the mSAFFE were
related to a reduced forward displacement as measured by the LOS.
However, these findings may be
induced by the negative impact that
fear may have on postural performance as opposed to actual deterioration of the postural control systems.59 The smaller correlations
between the FFABQ and more static
performance-based measures suggest the FFABQ may be better able to
capture avoidance of more dynamic
activities.
Perhaps the most important finding
of the present study is the correlation between the FFABQ and daily
physical activity measured by the
activity monitors. Our claim that the
FFABQ quantifies avoidance behavior in terms of activity limitation
and participation restriction should
be reflected by a decrease in daily
1262
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Volume 91
physical activity. In addition, a
decrease in physical activity, logically, can result in the downstream
consequence of physical deconditioning and decreased endurance.
The 6MWT was used in this study
with this in mind. A positive correlation of the FFABQ with hours spent
sitting or lying and negative correlations of the FFABQ with hours stepping, METs, and the 6MWT in the
present study support the notion
that individuals with high FFABQ
scores (ie, high avoidance behavior)
are less physically active (as measured by the activity monitor) and
have decreased physical endurance
(as measured by the 6MWT). This
decrease in physical endurance may
be the result of avoidance of mobility
tasks, such as walking, which has
been found to be more frequently
avoided by elderly people with a fear
of falling.49 However, hours spent
standing, as measured by the activity
monitor, was not correlated with the
FFABQ. Because standing is a static
and somewhat less mobile task, this
would presumably not be considered a “risky” behavior. Therefore,
static standing is not avoided as
much as dynamic movements. This
finding is consistent with the higher
correlations of the FFABQ with
dynamic balance measures compared with static balance measures.
In addition, the transition from sitting to standing was not correlated
with the FFABQ. This finding may be
due to the requirement of this transition in unavoidable ADL tasks (eg,
toileting, dressing, bathing) that
often must be performed on a regular basis despite the presence of a
fear of falling.
Predictive validity was best represented by the FFABQ and ABC Scale.
The FFABQ was the only variable
that predicted hours spent sitting, a
sedentary activity. The ability to predict this sedentary activity further
supports the FFABQ’s capacity to
measure activity limitation, as indi-
Number 8
viduals with a high FFABQ score
could reasonably be expected to
engage in increased hours of sitting
(ie, avoidance behavior). The ABC
Scale was found to be a better predictor of activity levels compared
with the FFABQ and FES. Previous
research has shown the ABC Scale to
be superior to the FES at differentiating between individuals who had
a fear of falling and limited activity
and those who did not.60 The FFABQ
and ABC Scale both predicted endurance as measured by the distance
walked on the 6MWT, indicating
both tests may have the ability to
predict the deconditioning that can
occur after a substantial period of
activity limitation. Although the ABC
Scale predicted more of the variance
of endurance, the FFABQ predicted
an additional unique contribution
over and above the ABC Scale, supporting the notion that the measurement constructs are related but
different.
Recruitment of community-ambulating elderly individuals who exhibited high fear-avoidance behavior
was challenging. Those with high
fear-avoidance behavior were not
likely to participate in a study that
required them to travel and be
physically active, both prerequisites
to participation in our study. Subsequently, a sample of convenience
was used, and because of the difficulty in recruiting individuals with
high fear of falling, we tended to
have participants at the lower end
of the scale. Future research targeting homebound elderly people may
yield a participant pool with a
higher level of fear-avoidance behavior. Another limitation of this study
was the activPAL activity monitors.
They could not be worn while
swimming, and a couple of individuals participated in swimming during
the week they wore the activity
monitor. In addition, the combination of the activity monitor applied
to the mid-thigh with adhesive backAugust 2011
ing resulted in frequent need for
reapplication of the adhesive backing and in a lack of adherence to
use of the activity monitor in a few
cases. It has been reported that activity monitors are not sensitive to people who have a bradykinetic gait (ie,
individuals with PD).61 For this reason, the activity monitor is not recommended for those with a selfselected gait speed below 0.67
m/s.62 However, in our study, the
average gait speed of participants
with PD was 1.23 m/s, making it
unlikely that this was an issue.
Conclusion
The results from this study provide evidence for the reliability
and validity of the FFABQ for different populations, including elderly
people who are healthy and people
with PD and CVA. Furthermore, our
results support the notion that the
FFABQ measures avoidance behavior
rather than balance confidence, selfefficacy, or fear. The results of this
study also illustrate that the FFABQ
has the potential to offer the clinician an efficient way to assess the
effectiveness of balance treatment
on a patient whose fear of falling
has triggered a reduction in his or
her daily activity and participation.
Currently, there are no other assessment tools that measure these
sequelae of balance impairment and
falls in a clinically useful and practical manner.
All authors provided concept/idea/research
design and writing. Dr Landers, Dr Durand,
and Dr Powell provided data collection and
analysis. Dr Landers provided project management, facilities/equipment, and institutional liaisons. Dr Powell provided participants. Dr Durand, Dr Powell, Dr Dibble, and
Dr Young provided consultation (including
This study was approved by the University of
Nevada, Las Vegas, Biomedical Sciences
Institutional Review Board.
This research was presented at the Combined Sections Meeting of the American
August 2011
Physical Therapy Association; February
9 –12, 2011; New Orleans, Louisiana.
DOI: 10.2522/ptj.20100304
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Number 8
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August 2011
Appendix.
Fear of Falling Avoidance-Behavior Questionnairea
Name:
Date:
Please answer the following questions that are related to your balance. For each statement, please check one box
to say how the fear of falling has or has not affected you. If you do not currently do the activities in question, try
and imagine how your fear of falling would affect your participation in these activities. If you normally use a walking
aid to do these activities or hold on to someone, rate how your fear of falling would affect you as if you were not
using these supports. If you have questions about answering any of these statements, please ask the questionnaire
administrator.
Please check one box for each question
Completely
disagree (0)
Disagree
(1)
Unsure
(2)
Agree
(3)
Completely
agree (4)
1. Walking
䡺
䡺
䡺
䡺
䡺
2. Lifting and carrying objects (eg,
cup, child)
䡺
䡺
䡺
䡺
䡺
3. Going up and downstairs
䡺
䡺
䡺
䡺
䡺
4. Walking on different surfaces
(eg, grass, uneven ground)
䡺
䡺
䡺
䡺
䡺
5. Walking in crowded places
䡺
䡺
䡺
䡺
䡺
6. Walking in dimly lit, unfamiliar
places
䡺
䡺
䡺
䡺
䡺
7. Leaving home
䡺
䡺
䡺
䡺
䡺
8. Getting in and out of a chair
䡺
䡺
䡺
䡺
䡺
9. Showering or bathing
Due to my fear of falling, I avoid . . .
䡺
䡺
䡺
䡺
䡺
10. Exercise
䡺
䡺
䡺
䡺
䡺
11. Preparing meals (eg, planning,
cooking, serving)
䡺
䡺
䡺
䡺
䡺
12. Doing housework (eg, cleaning,
washing clothes)
䡺
䡺
䡺
䡺
䡺
13. Work or volunteer work
䡺
䡺
䡺
䡺
䡺
14. Recreational and leisure
activities (eg, play, sports, arts
and culture, crafts, hobbies,
socializing, traveling)
䡺
䡺
䡺
䡺
䡺
Please make sure you have checked one box for each question. Thank you!
Total:
a
/56
The Fear of Falling Avoidance-Behavior Questionnaire may not be used or reproduced without written permission from the authors.
August 2011
Volume 91
Number 8
Physical Therapy f
1265
Case Report
A Patient With Internal Carotid
Artery Dissection
Gilbert M. Willett, Neal A. Wachholtz
G.M. Willett, PT, PhD, OCS, CSCS,
Division of Physical Therapy Education, University of Nebraska
Medical Center, 984420 Nebraska
Medical Center, Omaha, NE
68198-4420 (USA). Address all
correspondence to Dr Willett at:
[email protected].
N.A. Wachholtz, PT, Excel Physical
Therapy, Omaha, Nebraska.
[Willett GM, Wachholtz NA. A
patient with internal carotid artery
dissection. Phys Ther. 2011;91:
1266 –1274.]
Association
2011
Submitted: June 29, 2010
Background and Purpose. The purpose of this case report is to raise physical
therapist awareness of Horner syndrome as a “red flag” for immediate medical
referral.
Case Description. A 45-year-old man sought physical therapy for examination
and treatment of neck pain and headache symptoms 5 days after experiencing a
whiplash-type injury while waterskiing. His complaints were similar to a prior
condition diagnosed as occipital neuralgia that had successfully responded to education, cervical and thoracic joint mobilization, and exercise provided by a physical
therapist. The initial examination findings also were similar to those of the previous
episode. However, signs consistent with Horner syndrome were noted on the second
visit. This finding raised immediate concern on the part of the treating clinician and
resulted in prompt physician referral, medical diagnosis, and intervention.
Outcomes. A magnetic resonance imaging angiogram revealed an internal carotid
artery dissection. A successful outcome was achieved over the course of 6 months
through medical intervention, which consisted of anticoagulant therapy and modification of activity levels.
Discussion. In this case, the patient’s sudden onset of signs of Horner syndrome
was indicative of a medical emergency—internal carotid artery dissection.
this article at:
ptjournal.apta.org
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August 2011
I
ndividuals with neck pain and
headaches commonly seek physical therapy intervention for their
symptoms. Neck pain is second only
to low back pain as a significant
cause of impairment.1 The reported
12-month prevalence of neck pain
varies from 30% to 50%, and lifetime
prevalence is approximately 70%.1
Fifteen percent of visits to hospitalbased physical therapists are neck
pain related.1 Individuals with neck
pain and headaches commonly demonstrate impairments that appear to
be associated with their symptomatic complaints. Forward head posture has been linked to neck pain
and headache symptoms.2,3 Upper
cervical spine joint disorders are
directly associated with cervicogenic
headache.4 – 6 Weakness of the longus colli and longus capitis cervical
spine muscles also have been linked
to neck pain and headaches.7–9 Common problems associated with traumatic, whiplash-type injuries include
neck pain, occipital headaches, and
greater occipital neuralgia.10,11 Individuals with whiplash-type injuries
often demonstrate elements of all of
these impairments upon initial examination. Patients should be continuously monitored for new signs or
symptoms, which would raise “red
flags” relative to appropriateness for
physical therapy intervention.12 A
patient who suddenly develops signs
of Horner syndrome, which include
ptosis (drooping eyelid) and miosis
(pupil constriction) of one eye,
would be one example of a new finding indicative of a need for further
medical evaluation. Physical therapists need to be able to make decisions regarding the need for medical
referral based on patient observation
and examination findings.13
cervical ganglion. Next, it ascends
within the adventitia of the internal
carotid artery. Sympathetic nerve
fibers join the ophthalmic division
of the fifth cranial nerve (trigeminal
nerve) in the cavernous sinus and
travel with it to the orbit. These sympathetic fibers innervate the iris dilator muscle as well as Müller’s muscle, a small smooth muscle in the
eyelids responsible for a minor portion of the upper lid elevation and
lower lid retraction.14 A plethora
of medical conditions can cause
Horner syndrome, a number of
which require immediate medical
examination.15 Some of the most
common causes of Horner syndrome
reported in the literature include
surgical trauma, cervical carotid
artery dissection, and a cavernous
sinus mass.16
Horner syndrome can result from a
lesion occurring along the sympathetic nervous system pathway. The
pathway starts in the hypothalamus
area of the brain and travels along
the sympathetic trunk to the superior
The patient stated that his recurrence of symptoms (similar to his
visit 2 years previously) was precipitated by a “major wipeout” while
waterskiing on a Saturday afternoon
(5 days prior to the examination by
August 2011
The purpose of this case report is
to increase physical therapist
awareness of signs of Horner syndrome that may indicate a potentially catastrophic underlying medical
condition.
the physical therapist). He stated he
caught the edge of his slalom ski
while cutting across the water,
which resulted in a “face plant” into
the water. He estimated the boat
speed at around 50 km/hr. He
reported having a global headache
the same day and taking ibuprofen
to reduce his symptoms. He stated
that the symptoms subsided the following day, and he returned to his
regular work duties as a physical
therapist (with more than 20 years
of practice) with no limitations. He
reported the onset of a primarily
right-sided, severe headache and
neck pain 4 days after the initial
trauma. He sought physical therapy
the day after the onset of this headache. This self-referral was to a
therapist who worked for another
employer but knew the patient well
and had treated him previously.
Verbal questioning to screen for general health and constitutional symptoms revealed no significant findings.17 Specific questions included:
• What medical conditions have you
been diagnosed with?
• What issues have you seen your
physician for in the previous 5 to
10 years?
• What surgeries have you had?
• Have you experienced any constitutional symptoms such as fever,
dizziness, nausea, trouble swallowing, headaches, or numbness and
tingling in the previous 2 weeks?
Case Description: Details of
the Risk Management Topic
The patient was a 45-year-old man
who reported cervical pain (greater
on the right side than on the left
side) and a primarily right-sided
headache extending from the occipital region to just above the eye
(Fig. 1). He had been treated successfully 2 years previously by the same
physical therapist for a similar complaint. His medical diagnosis at the
time had been “occipital neuralgia”
of unknown onset. This diagnosis had
been made by an anesthesiologist/
pain specialist. The patient had been
referred to by his family physician.
The only medical care the patient
had received in the previous 5 years
was for occipital neuralgia, as previously reported. No prior history of
surgery or use of prescribed medications was reported. The patient
noted the constant, stabbing headache and neck pain on his right side
as being significant, while stating
that the mild ache on the left side of
his head and neck felt as though it
may be resultant from the pain on
the right. He also reported that the
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in the clinical setting to measure a
patient’s self-reported function.
Although this scale has not been validated specifically in patients with
headache or neck pain, it has shown
a strong correlation with wellestablished outcome measures for
the shoulder.19
Figure 1.
Pain diagram completed by the patient during the initial examination.
back of his head was tender to touch
on the right side. The body chart
pain diagram completed by the
patient is shown in Figure 1.
The patient was asked to rate his
pain on the right and left sides using
a numeric pain rating scale (NPRS),
an 11-point scale with 0 indicating
“no pain” and 10 indicating “worst
pain imaginable.” Changes in pain
intensity have been shown to be
accurately measured using the
NPRS.18 He rated his right-side worst
pain over the previous 24 hours as
9/10, and as 7/10 at the time of the
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examination. He stated his “best”
pain was 7/10 and his average pain
was 7/10 as well. He rated his leftside worst and best pain over the
previous 24 hours as 2/10, and his
pain level remained at 2/10 at the
time of the examination. The patient
reported not experiencing any night
pain or difficulty sleeping since the
accident. A global function rating of
80% was identified by the patient,
with 0% representing “unable to perform any activity” and 100% representing “able to perform all activities
without limitation.” The global function rating scale is commonly used
Number 8
Clinical Impression
The patient’s primary concern was
right-sided headache. Based on his
medical history, the examining therapist wanted to discern whether the
headache was possibly due to a
re-aggravation of the postural and
upper cervical and thoracic joint
hypomobility issues encountered
previously, or perhaps a non–
musculoskeletal-related condition in
need of additional medical evaluation. The objective of the physical
examination was to assess whether
musculoskeletal impairments that
reproduced his headache symptoms
were present. Upper cervical and
thoracic joint mobility limitations
and myofascial trigger points in the
cervical region are commonly associated with cervicogenic headaches.3,20 The focus of the physical
examination was on these areas.
Additional medical history information that can be useful for differential
screening of individuals with headaches includes: detailed assessment
of neurologic symptoms (eg, seizures, confusion, changes in alertness, clumsiness), eye pain and
simultaneous vision changes, and
family history (migraines or cancer).20 The initial presentation of
this patient suggested a relatively
straightforward reoccurrence of his
previous musculoskeletal dysfunction, based on the absence of any
differential screening red flags. However, the subsequent onset of new
symptoms at the second visit completely changed the course of intervention and prognosis of this case.
August 2011
Physical Examination
Posture
Moderate forward head posture was
noted upon observation of sitting
and standing.
Active Range of Motion
Cervical spine active range of motion
(AROM) and associated symptom
responses were measured with the
patient in a sitting position. An
inclinometer was used to measure
cervical flexion and extension, and
cervical rotation was measured
with a standard goniometer. The
details of these measurement procedures have been described elsewhere, and the reliability findings
have been reported as .84 for flexion and extension, .82 for side bending, and .81 for rotation.21–23 Cervical spine motion was as follows:
flexion⫽50 degrees, extension⫽57
degrees, left rotation⫽63 degrees,
right rotation⫽65 degrees, side
bending to the left⫽33 degrees,
and side bending to the right⫽35
degrees. Discomfort was noted at
the end range of left rotation and
left-side bending. Moderate limitations were noted during AROM
assessment of C1/occipital flexion
(3°) and C1–C2 left rotation (25°)
with the patient in a sitting position.
Joint Mobility
Hypomobility was noted with posterior to anterior “spring” testing of
the mid and upper thoracic spine
(␬⫽⫺.2 to .26 depending on level
tested) and with C1/occipital flexion
(␬⫽.29) and C1–C2 left rotation
assessments (␬⫽.20 left, .37 right).
Mild reproduction of the patient’s
symptoms was noted with assessment of the hypomobile regions of
the cervical spine. Mobility assessment of the cervical and thoracic
spine in patients with mechanical
neck pain has been shown to have
fair to poor reliability.23
August 2011
Neurologic Screen
A neurologic screen (upper-limb and
head/face sensation, muscle strength
[force-generating capacity] and deep
tendon reflexes) was performed.
Findings were symmetrical and unremarkable for all areas tested. These
tests have been described elsewhere.24 Numbness has been
reported to have a sensitivity of .79
and a specificity of .25, weakness a
sensitivity of .65 and a specificity of
.39, and deep tendon reflexes a sensitivity ranging from .24 to .03 and a
specificity ranging from .95 to .93.24
Special Tests
Sharp-Purser test. The findings of
this test for cervical instability were
unremarkable. The details of this test
have been described elsewhere and
have been reported to have acceptable sensitivity (.69) and specificity
(.96), a positive likelihood ratio of
17.25, and a negative likelihood ratio
of 0.32.24
Vertebral artery test. No significant findings other than positionrelated discomfort were noted. This
test was performed in the anticipation that the patient might benefit
from grade 5 cervical spine manual
therapy interventions as used in his
previous treatment. The clinical utility of this test alone has been
reported to be limited, and the use
of a qualitative assessment of all vascular risk factors (carotid and vertebral) incorporating a “systems-based
approach” has been recommended
in order to enhance the clinical reasoning process.25
Palpation
Muscle guarding and tightness were
noted in the suboccipital region and
were greater on the right side than
on the left side. Headache symptoms
were aggravated with palpation of
both the suboccipital paraspinal
musculature and occiput of the skull
on the right side.
Physical examination test reliability
and diagnostic utility must be taken
into consideration when selected as
part of the examination procedure
by the clinician. A thorough explanation and discussion of these issues
are available elsewhere.24
The examination was concluded at
this point due to irritability of the
patient’s symptoms. Additional
assessment of functional movements
and cervical muscle strength would
have been included in the examination provided the patient’s symptoms had not been aggravated. The
patient’s increased discomfort from
the examination prompted the therapist to reduce the aggressiveness of
his planned initial manual therapy
intervention strategy. The patient’s
goals for physical therapy were to
eliminate the symptoms and to review
and modify his self-management
home program, if needed.
Clinical Impression
Based on the patient’s uneventful
return to normal activities for several days, the similarity of physical
examination findings to the initial
presentation 2 years previously, and
headache symptoms and palpation
findings being consistent with occipital neuralgia, the physical therapist
hypothesized that the patient had
exacerbated his previous condition.26,27 Occipital neuralgia pain is
characterized as a constant “stabbing” and associated with tenderness
to palpation of the occipital nerve.26
Occipital neuralgia has been cited as
a common cause of cervicogenic
headache.28 Clinical diagnosis is difficult because of the overlying features between primary headaches
(eg, tension-type migraines) and cervicogenic headaches. Interventional
pain physicians have focused on supporting the clinical diagnosis of cervicogenic headaches with confirmatory nerve blocks. There is mounting
evidence that manual therapy interventions aimed at vertebral mobility
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Figure 2.
Photograph of the patient showing right-side ptosis (drooping eyelid) and miosis (pupil
constriction).
impairments can be effective in the
management of occipital neuralgia
when used in conjunction with medical management strategies such as
occipital nerve block injections.20
The overall examination findings
appeared to support the physical
therapist’s initial hypothesis that
the patient had a musculoskeletal
impairment-based dysfunction that
should be responsive to interventions aimed at addressing the impairments of joint hypomobility and
muscle guarding and a potential
need for modification of home exercises (to be assessed in future visits).
The therapist decided that any soft
tissue injuries that the patient may
have incurred from the skiing acci-
Figure 3.
Magnetic resonance imaging angiogram of the patient demonstrating entire view of
the carotid arteries (anterior-posterior view). The white arrow is pointing to the area of
dissection of the right internal carotid artery; note the reduced blood flow (narrow area
of contrast medium).
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dent were most likely in the early
proliferative phase of healing secondary to the traumatic incident and
that initial interventions should not
include aggressive cervical manual
interventions (grade 4 or 5 mobilization) or resistance exercises at that
time. Of note, decision rules for
whether referral for cervical radiographs is appropriate in cases of cervical trauma are well documented
in the literature.29 In this case, the
patient’s uneventful return to work,
lack of upper-limb symptoms, and
cervical AROM measurements led
the therapist to rule out the need for
radiograph referral at the time of the
initial examination.
The initial interventions were based
on the impairments noted in the
examination. These interventions
included review and practice of
appropriate posture and head position in sitting and standing, supine
upper thoracic (third thoracic vertebral level) anterior-posterior joint
(grade 5) mobilization, gentle suboccipital manual traction and occipital
release, and contract-relax mobilization (grades 2 and 3) for left rotation
of C1–C2, followed by application of
an ice pack on the cervical region.
The manual therapy techniques used
in this case are well described in
the literature.20,30,31 The patient
reported mild symptomatic relief at
the end of the intervention and demonstrated symmetrical C1–C2 rotation mobility (⬃40°). The patient
was instructed to perform seated
or standing chin tuck exercises and
cervical rotation AROM exercises
within the pain-free range of motion
throughout the following day. A
return visit was scheduled for 2 days
later.
Upon his second visit for treatment
(Saturday, 7 days after the initial
injury), the patient reported a brief
reduction in his headache (⬃2
hours) after the initial visit (5/10 on
the NPRS), but his pain level had
August 2011
returned to 7/10. Next, the therapist
asked the patient to actively demonstrate his upper cervical (C1–C2)
rotation by flexing his chin to his
chest and rotating side to side.
Observation of this AROM revealed
symmetrical movement (⬃40° bilaterally), with no patient report of
change in symptoms. When the
patient looked up from the AROM
assessment, the therapist noted
pupil asymmetry with miosis on the
right side and ptosis of the right eyelid (Fig. 2). The patient had not
noticed these signs prior to the therapist bringing them to his attention.
The therapist recognized the signs
as being consistent with Horner syndrome. Horner syndrome can result
from a wide range of medical conditions, including tumors, spinal cord
injuries, vascular problems, and specific types of headaches.14 An appropriate medical evaluation and a
timely elucidation of the etiology
may allow for a potentially lifesaving
intervention.14 No further assessment was performed. The therapist
considered these signs as a red flag
and informed the patient he wanted
to contact his physician immediately
to report this change in findings. The
patient chose to contact his physician at the time via personal cell
phone.
If the patient had not chosen to
contact his physician personally,
the therapist would have called the
patient’s family physician to describe
the situation and ask for recommendations. In retrospect, after learning
of the potential high-risk medical
diagnoses associated with the sudden onset of signs of Horner syndrome, providing the patient with
an immediate ride to the closest hospital emergency department would
have been appropriate.11,31,32
Actions Taken to Address
the Risk
The patient’s physician ordered a
head magnetic resonance imaging
August 2011
Figure 4.
Magnetic resonance imaging angiogram of the patient providing a cross-sectional view
of the internal carotid arteries. The white arrow is pointing to the area of dissection of
the right internal carotid artery; note the reduced blood flow (large area of lighter
density of contrast medium and small area of greater density).
(MRI) scan the same day. Negative
findings and accompanying cervical
pain led the physician to consider
carotid artery dissection as a possible
cause.12,14,33 The patient was sent
to the emergency department of a
local hospital for a neurologist consultation and a cervical MRI angiogram (MRA). The MRA images are
shown in Figures 3 and 4. The findings resulted in a diagnosis of internal carotid artery dissection (ICAD).
The patient was hospitalized, and
treatment of vascular risk factors
for stroke prevention with heparin
was initiated. He was subsequently
released from the hospital with
ongoing anticoagulation therapy
(Coumadin*) for 6 months and
advised to limit physical activity to
mild amounts of exertion. The goal
of this standard approach to medical
management of ICAD via pharmaceutical intervention is to reduce the
possibility of a cerebrovascular accident.34 A follow-up MRA at the end
of the treatment period (6 months
later) revealed normal, symmetrical
carotid artery findings (Fig. 5).
The patient returned to full activity
levels with no limitations. His neck
pain and headaches had gradually
receded over the 6-month treatment
period, and he reported no symptoms 1 year later. The patient’s right
pupil miosis and eyelid ptosis also
diminished over the course of the
6 months, but remained observable
to the trained eye.
* Bristol-Myers Squibb Co, PO Box 4500,
Princeton, NJ 08543-4500.
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of Horner syndrome include dorsolateral medullary stroke and carotid
artery dissection.12 In cases where
the cause of Horner syndrome is
unknown, patient signs and symptoms assist with localizing the area
of the lesion and subsequent diagnosis of the causes. For example, acute
neck or face pain indicate a lesion
in the cervical region, arm pain or
weakness indicate a lesion in the
paraspinal region, and sixth cranial
nerve palsy indicates a lesion in the
cavernous sinus area.12
Figure 5.
Follow-up magnetic resonance imaging angiogram of the patient (after 6 months of
anticoagulant therapy) demonstrating entire view of the carotid arteries (anteriorposterior view). The white arrow is pointing to the area where the dissection of the right
internal carotid artery had occurred.
Discussion
Internal carotid artery dissection
occurs as a result of a tear in the
inner lining of the artery. The tear
can be spontaneous or associated
with mild trauma such as sneezing or
more severe trauma such as whiplash injury or aggressive cervical
spine rotation manipulation.15,35– 40
Understanding of the pathophysiology that makes a person susceptible
to ICAD is somewhat limited.41 The
signs and symptoms experienced by
the patient in this case report are
similar to those described in other
examples in medical literature.15,42– 45
occurs in adults at a mean age of 40
years and with a male:female ratio of
1.5.38 Approximately 60% of ICADs
appear to occur spontaneously.44
The clinical presentation of spontaneous dissections of the internal
carotid artery may include cervical
or cranial pain, Horner syndrome,
and cranial nerve palsy; however,
ICAD also may be silent. The favorable natural history of ICAD emphasizes the need for a noninvasive
approach to detection, monitoring,
and follow-up. Follow-up studies
suggest a fairly good overall prognosis in adults.38
Internal carotid artery dissection
accounts for up to one fifth of ischemic strokes occurring in people
under the age of 45 years. It typically
The onset of signs consistent with
Horner syndrome was the reason for
concern on the part of the therapist
in this case report. Common causes
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Common signs and symptoms associated with any ICAD include ipsilateral clinical manifestations: head,
facial, or neck pain; Horner syndrome; pulsatile tinnitus; and cranial
nerve palsy.35 Cluster headache
symptoms also have been associated
with Horner syndrome signs and
underlying ICAD.45– 48 The classic
signs of Horner syndrome include:
miosis, ptosis, and facial anhydrosis,
all on the ipsilateral side of the
head.12 Diagnostic imaging (MRI or
angiography) is strongly recommended in cases where an individual
has Horner syndrome of unknown
etiology, especially when accompanied by head, face, or neck
pain.12,16,49 Approximately 50% of
individuals who have had a carotid
artery dissection also have connective tissue aberrations of their skin.41
The patient in this case report did
not have any medical history or physical findings that indicated he may
have had a connective tissue disorder; however, he did exhibit signs
and symptoms consistent with ICAD
upon his second visit for physical
therapy intervention.
In conclusion, this case report
describes a patient who initially presented a history, signs, and symptoms of what appeared to be a treatable musculoskeletal condition. The
sudden onset of signs consistent
with Horner syndrome in addition
to his continued headache and
August 2011
neck pain complaints prompted the
attending physical therapist to immediately refer the individual to his physician. An ICAD was diagnosed, and
appropriate
medical
treatment
ensued. Identification of signs inconsistent with a musculoskeletal system injury facilitated the medical
referral. In retrospect, the therapist
could have considered more extensive cranial nerve and cervical testing during the initial examination
due to the patient’s initial history,
which included trauma. However, it
is unlikely these examinations would
have revealed additional information
if the onset of his ICAD was spontaneous or if it developed gradually
after the initial trauma. The therapist
also may have put too much stock in
the information and recommendations being provided by the patient
due to his background and experience as a physical therapist. A thorough examination should always be
conducted, regardless of a patient’s
background and experience. The
lesson learned: a sudden onset of
signs atypical for what is expected
(Horner syndrome for a musculoskeletal injury in this case) should be
considered a red flag for medical
referral.
Dr Willett provided concept/idea/project
design. Mr Wachholtz provided data collection. Both authors provided writing and consultation (including review of manuscript
before submission).
DOI: 10.2522/ptj.20100217
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49 Chan CC, Paine M, O’Day J. Carotid dissection: a common cause of Horner’s syndrome. Clin Experiment Ophthalmol.
2001;29:411– 415.
August 2011
ProfessionWatch
Vitalizing Practice Through Research and
Research Through Practice: The Outcomes of a
Conference to Enhance the Delivery of Care
Marc S. Goldstein, David A. Scalzitti, Joanell A. Bohmert, Gerard P. Brennan, Rebecca L. Craik, Anthony Delitto,
Edelle C. Field-Fote, Charles M. Magistro, Christopher M. Powers, Richard K. Shields
T
he American Physical Therapy
Association (APTA) provided
funding for a series of meetings among a small group of leaders
representing the research and clinical communities whose task was to
plan a conference, the outcome of
which would be a “road map” for the
process of generating evidence that
would be implemented by clinicians
so that the provision of services
might be enhanced. Two of these
planning sessions were held and
resulted in a decision to focus a conference on the identification of strategies to lessen perceived “gaps”
between physical therapist clinicians
and researchers and the development of strategies to bridge the
“gaps” between the 2 groups. These
meetings ultimately resulted in the
Vitalizing Practice Through Research
and Research Through Practice Conference hosted by APTA.
A perceived gap between research
and practice has been cited as a
problem by others within and outside the profession as well. In a
recent editorial in the Journal of
Orthopaedic and Sports Physical
Therapy, Bechtel et al stated, “We
have a problem in manual therapy,
and perhaps in the whole profession
of physical therapy. Our problem is
the growing chasm between
researchers on the one hand, and
clinicians on the other.”1(p451) A
recent Institute of Medicine workshop titled “Transforming Clinical
Research in the United States: Challenges and Opportunities” echoed
this theme and identified bridging
August 2011
the divide between research and
practice as one of the most critical
needs facing clinical research.2 Discussion of the perceived gap
between research and practice
extends internationally, as Demers
and Poissant3 lamented that research
would be meaningless if it did not
affect clinical practice. Furthermore,
Demers and Poissant discussed the
value of creating partnerships across
the research process, from conception to dissemination of results.
Translational Research
Translational research, at its most
macroscopic level, essentially refers
to efficient movement of new discoveries into clinical practice. This
research is typically connoted by the
phrase “bench to bedside,” implying
that the majority of translation is
directional, from the basic science
arena to the clinical arena. Authors
define translational research slightly
differently. Although a number of
definitions for translational research
exist,4 –7 we adopted for the conference the definition generated by the
Institute for Translational Health
Sciences (ITHS), a consortium of
38 medical research institutions
supported by the National Institutes
of Health, which defines translational research as moving knowledge
and discovery gained from the basic
sciences to its application in clinical
and community settings.8 The ITHS
model delineates 5 phases of translational research and labels the phases
from T0 to T4 (Fig. 1). The model
recognizes that translational research
can be described via a continuum
that extends from the identification
of opportunities and approaches to
a health problem (basic research),
to the impact of practice on the
health of the population (outcomes
research).8 Furthermore, it should be
recognized that the model is bidirectional and should not be interpreted
as moving only from identification of
opportunities and approaches to a
health problem through the study of
practice to population health impact.
Regardless of the specific definition
or model used to describe translational research, the goal is similar: to
provide a framework that describes
how basic and clinical research will
interact in the future.
Knowledge Translation
Concomitant with an acknowledgment of the importance of the need
for translational types of research is
the recognition that an infrastructure
needs to be developed so that the
evidence created is utilized adequately. Thus, although the focus of
translational research is the creation
of new knowledge, there is a coexisting need to facilitate consistent
application of the findings in practice. This concept of translating evidence into practice has been given
a number of designations, among
them “diffusion theory,”9 “implementation science,”10 and, more
often, “knowledge translation.”11–17
Knowledge translation has been formally defined by the Canadian Institutes of Health Research as a
dynamic and iterative process that
includes the synthesis, dissemina-
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Physical Therapy f
1275
ProfessionWatch: Outcomes of a Conference to Enhance the Delivery of Care
T0
Identify
problems,
opportunities,
and
approaches
T4
Evaluation of health
impact on real-world
populations
Goal:
Human Health
Improvements
T1
Discovery or
foundational research
T2
Health
application
to access
efficacy
T3
Health practice;
science of
dissemination
and
implementation
Figure 1.
The Institute for Translational Health Sciences (ITHS) model of translational research.8
tion, exchange, and ethically sound
application of knowledge to
improve health, provide more effective health services and products,
and strengthen the health care system.13 Regardless of what it is called,
the implementation of knowledge is
as important as the creation of new
knowledge and technologies to
improve health outcomes.18
For a clinical science such as physical therapy, the importance of
embracing the concept of knowledge translation should not be
undervalued. Clearly, the issue of
translating knowledge into practice
is one that transcends physical therapy. It is a concern affecting all
of health care. The lack of consistent
implementation of evidence into
practice is illustrated by McGlynn et
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Physical Therapy
Volume 91
al,19 who evaluated physician performance on 439 evidence-based indicators of quality of care for 30 common acute, chronic, or preventative
conditions. Through telephone interviews and chart reviews across 12 US
cities, the authors determined that
patients received the right care at
the right time less than 55% of the
time. These results appear to represent a lack of timely translation of
research findings into clinical practice and warrant our attention as
physical therapists, as the authors
stated that one solution to this issue
is the routine availability of information on performance of providers.
To provide an example related to
physical therapy, a recent retrospective study demonstrated that adherence to recommendations of clinical
practice guidelines in treatment of
Number 8
people with acute low back pain was
more likely to result in better clinical
outcomes and lower costs.20 The
rate of adherence to the guideline
recommendations was 40.4%, which
suggests that although clinical practice guidelines have been developed
and following the recommendations may result in better care, active
strategies are needed to increase
awareness of the guidelines, implement the evidence in practice, and
improve adherence.
Given that both translational
research and knowledge translation
rely on a dynamic and iterative process, important infrastructure systems need to be in place throughout
academia or other settings whose
purpose is, in part, to create knowledge; throughout care delivery systems; and within funding sources.
With this in mind, the Vitalizing Practice Through Research and Research
Through Practice Conference was
designed to reinforce to the profession the importance of translational
research and to identify the need for
infrastructure and resource development that would augment the existing research capability of physical
therapists nationwide, as well as
ensuring that this evidence is used to
enhance practice. The success of the
conference will be judged by how
well it serves as the impetus for additional translational studies and leads
to the creation of such an infrastructure, one that supports translational
research and enhances knowledge
translation.
The Vitalizing Practice
Through Research and
Research Through Practice
Conference
With the goal of generating evidence
and enhancing practice, as outlined
above, as the incentive, the Vitalizing
Practice Through Research and
Research Through Practice Conference was planned over the course of
August 2011
2 meetings. The meetings were
directed by a planning committee
that had been appointed by the
APTA Board of Directors and convened by APTA staff. Planning meeting discussions were guided by 2
assumptions: (1) the quality of physical therapy is threatened by the
inappropriate variation in the care
delivered, and (2) there is a lack of
consistency or uniformity in tracking
outcomes. The planning group
acknowledged a need for the development of infrastructure to disseminate information to clinicians and to
examine the effectiveness of
evidence-based care delivery by measuring clinical and cost outcomes. In
order to create processes for optimum care to be delivered to
patients, the following were anticipated outcomes of the conference:
• Clinician attendees would depart
the conference with an understanding of what it means to have a
systematic approach to data
collection;
• Development of a model for a
minimum data set necessary to
describe the process of care;
• Creation of strategies to develop
relationships with external stakeholders to enhance patient care
delivery; and
• Creation of new collaborations
among researchers and clinicians to
enhance patient care.
Conference Design and
Format
The conference was designed to provide value to both researchers and
clinicians. The themes discussed by
the planning group attempted to
ensure that conducted research
would be useful to clinicians. Conversely, the relevant evidence generated from the research investigations
would be adopted to enhance the
delivery of care. Thus, the first phase
of the conference recognized the
importance of translational research
August 2011
(ie, the movement of knowledge and
discovery gained from research to its
application in clinical and community settings).8
The second phase of the conference
was designed to address infrastructure development. Topics such as
development of databases, registries,
and clinical research networks were
deemed important, as the planning
committee realized the creation of a
hub from which studies could be
conducted and results disseminated
was vital to knowledge translation.
To publicize the conference, a series
of announcements using various
media were used to disseminate the
purpose of the conference and to
invite nominations of the individual
receiving the announcement or a
colleague. Conference participants
were selected by members of the
planning committee using the following guidelines: (1) ensure adequate representation of clinicians
and researchers, (2) select individuals who would act collegially, and
(3) select participants who adhere
to the principle that collaboration
between clinicians and scientists will
enhance clinical practice outcomes.
Fifty-four participants were selected
from 128 nominations (Appendix 1).
Thirty-four of the participants considered themselves to be research
investigators, and 20 considered
themselves to be primarily clinicians.
The participants ranged from individuals who were relatively new
physical therapists to those with
more than 40 years of experience.
Nearly every setting in which physical therapists work was represented,
although the largest number of participants were members of university faculties. A total of 75 individuals
attended the conference, including
the members of the planning committee and APTA staff members.
The planning committee chose conference speakers who understood
the concepts of translational
research and knowledge translation
as evidenced through publications
and presentations. Each of the conference presentations had a common
theme, which was the importance of
translational research to the clinical
community, payers, and policy
makers.
Speakers represented a mix of clinicians and researchers: 5 were physical therapist clinicians, and 4 were
physical therapist researchers. Two
speakers were from outside the
physical therapy profession: one was
a health services researcher, and one
maintained both research and administrative responsibilities in a large
health care system.
The conference took place on
December 2– 4, 2009, in Philadelphia, Pennsylvania. The majority of
the presentations were recorded
prior to the conference. Participants
reviewed the presentations prior to
attending the conference in preparation for active discussion (Appendix
2). Viewing these presentations
ahead of time facilitated the accomplishment of the first anticipated outcome, which stated that participants
would have an understanding of
what it means to have a systematic
approach to data collection.
The core of the conference focused
on guided discussions among participants. Four small groups, with an
equal representation of clinicians
and researchers, were charged to
develop strategies to encourage
researchers and clinicians to work
more collaboratively. A member of
the planning committee facilitated
each group’s work.
The groups’ discussion was guided
by 2 basic questions—“Does
research inform practice?” and
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Physical Therapy f
1277
●
How well does research now inform practice?
䡩
Are there published results to support practice in key areas of practice?
䡩
Are these results widely disseminated?
䡩
Where there is good evidence, how well are the results implemented?
䡩
䡲
What are the barriers?
䡲
What are the solutions?
What are the infrastructure needs to enhance researchers informing
practice?
●
How well does practice inform research?
䡩
Are practitioners provided an adequate venue to influence research
questions?
䡩
Do researchers adequately value practitioner concerns (eg, reimbursement), enough to drive a research agenda or a specific study?
䡩
How do innovations in practice become elucidated? Is it necessary to take
these findings to “the next level” (eg, corroborating research studies)?
䡩
What are the infrastructure needs to enhance practice informing
researchers?
Figure 2.
Guiding questions for breakout sessions.
“Does practice inform research?”—
and a series of subquestions (Fig. 2).
Answers to the questions were
focused on how well research and
practice currently inform each other
and on identifying barriers to and
solutions for optimal integration. Clinicians were encouraged to articulate how they can influence the
behavior of researchers, and
researchers were asked to describe
ways their research could be made
more useful to clinicians. This portion of the group discussion focused
on issues such as:
• Clinicians having the opportunity
to influence the questions asked by
researchers,
• The value of clinician concerns
when lines of research are
formulated,
• Clinical innovations serving as an
impetus for additional study, and
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• The infrastructure necessary to create communication between clinicians and researchers.
The questions do not necessarily
relate to either the desired outcomes
or foci of the conference. Rather, the
planning group decided during the
course of the meeting that the best
way to generate discussion and
guide the work of the breakout
groups was to assign very generic
questions and permit the discussions
to lead in a direction that would
result in appropriate responses to
the original outcomes and foci. We
are convinced that the strategy was a
sound one, as the conference produced
recommendations
that
exceeded the expectations of the
planning group.
These small-group deliberations
were shared in a plenary session that
Number 8
completed the activities of the second day. Summaries from each of the
groups were very similar. The discussions generally could be categorized
into the following themes:
• Clinicians must determine methods
to gain access to clinical information, including clinical guidelines.
An underlying theme was the
importance of clinical registries or
databases.
• There must be mutual respect and
collaboration between the clinical
and research communities.
• Physical therapists should take
advantage of research generated
external to the profession as well as
studies conducted by physical therapist scientists.
• The appropriate outcomes measures should be specified and outcome instruments selected so that
physical therapists can justify their
interventions among both payers
and policy makers.
A health care economist discussed
the need to develop an infrastructure
to support the concept of valuebased practice. Value-based practice
maintains that a patient’s values are
pervasive and powerful parameters
influencing decisions about health,
clinical practice, and research.21 The
session introduced the idea of valuebased practice, which is complementary to evidence-based practice,
patient-centered care, and ethical
care and provided the perspective
on improving health care effectiveness by a stakeholder outside the
profession.
The conference concluded with participants identifying recommendations they felt were most essential. A
number of themes emerged from
this plenary session. The obvious
central role of the patient in the process of care, as a driving motivation
for research, was acknowledged and
respected in this discussion. The
August 2011
need for patients to assist in driving a
research agenda is not novel.22,23 In
response to recognition of the
important role of the patient, the
group discussed taking advantage of
a variety of media platforms, similar
to an iPhone application, to make
decision support systems available to
individual consumers potentially in
need of physical therapy. Participants stressed that creating a collaborative culture would be costly and
that all mechanisms of external funding should be explored to facilitate
and bridge communication between
the research and clinical communities, if the goals of translational
research were to be accomplished.
Recommendations and
Conclusions
Based on the deliberations of the
small groups and the ensuing presentations during the plenary session,
recommendations were made. These
recommendations were consolidated by the planning committee
into 4 key recommendations. These
recommendations are not addressed
to any one specific group; rather, the
acknowledgment and implementation of the recommendations are the
responsibility of the entire physical
therapy profession.
Recommendation 1
Identify mechanisms to distinguish
conditions amenable to the development of clinical practice guidelines.
The development of such guidelines
will distinguish physical therapist
practice that is supported by evidence from physical therapist practice that is not supported by evidence, as well as assist in the
identification of outcomes.
The recommendation of creation of
guidelines is not a new or unique
idea. As an example, APTA’s Section
on Orthopaedics has already begun
the process. The Canadian Medical
Association, in its series on knowl-
August 2011
edge translation, has strongly advocated for the use of guidelines.24 Furthermore, it has been cited that
interventions to implement guidelines do, in fact, affect the process
and outcomes of care, although the
effect size (10%) is small.25
Simply creating guidelines and making them available to clinicians will
not ensure that they will be widely
used. Evidence of this statement
abounds. In their widely cited article, McGlynn et al19 estimated that
evidence-based health care is delivered to patients approximately 55%
of the time. One strategy to assist in
bridging the gap between evidence
and practice is the expanded use of
electronic databases to accelerate
the diffusion of new evidence into
practice. A goal of electronic databases is to make it easier for those
who provide care by making evidence more readily available at the
point of care.26 In a recent article, a
group of researchers in the Netherlands demonstrated that adherence
to evidence-based guidelines for low
back pain resulted in greater
improvement in patient functioning,
lower utilization of care, and fewer
treatment sessions.27 Although clinical guidelines are being developed
and clinicians are using electronic
databases,28 –32 recommendation 1
urges that these efforts be expanded.
Recommendation 2
Develop clinical registries, minimum
data sets, outcome databases, and
core sets of outcome measures that
cover the patient life span and the
domains of ability and disability for
each area of physical therapist
practice.
The coordination of local or, perhaps, national registries or databases
is a necessity for developing the
infrastructure to its optimum capacity. Patient registries are defined as
an organized system that uses obser-
vational study methods to collect
uniform data (clinical and other) to
evaluate specified outcomes for a
population defined by a particular
disease, condition, or exposure and
that serves one or more predetermined scientific, clinical, or policy
purposes.33 Potential uses of a registry include the determination of
clinical effectiveness and costeffectiveness of physical therapy
intervention.
Recommendation 3
Form a consultant group to investigate the development and implementation incentives for physical
therapists to collect minimum data
sets that are included within a clinical registry from which reports can
be generated to develop optimal
clinical practice guidelines, guide
research, and enhance practice.
The third recommendation is essentially an extension of the second recommendation and calls for the establishment of a consultant group,
perhaps overseen by APTA, to
administer development and implementation of these registries. This
group will be integral to the success
of all of the recommendations
generated.
Recommendation 4
Ensure that the consumer is the center of efforts for the provision of
physical therapy services. There
needs to be a transformation from
the physical therapist as the “driver”
of the provision of care; rather, it
must be recognized that the consumer must be the beneficiary of services that are based on evidence.
A primary theme of the conference
was the recognition that researchers
and clinicians must more effectively
collaborate to benefit the physical
therapy profession and our patients.
These collaborations are to be
devised so that the best care possi-
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ble, at the least expense, can be provided to the patient. The patient
should be at the core of any system
that is developed and implemented.
Throughout most of the history of
health care, the clinician rather than
the consumer has been the focus.26
The role of the patient cannot be
overlooked in the development of
new models that might be created as
a result of the conference. A focus
on the consumer is consistent with
the outcomes of the recent APTA
Physical Therapy and Society Summit (PASS)34 and with the focus of
APTA’s Research Agenda.35
We realize that the recommendations specifically do not mirror the
original anticipated outcomes of the
conference. This slight lack of congruence was a result of the enthusiasm demonstrated by conference
participants and their motivation to
modify the outcomes initially developed by conference planners. We
believe these new recommendations
exceed, in value, the original anticipated outcomes of the conference.
The Vitalizing Practice Through
Research and Research Through
Practice Conference provided a
unique format for physical therapist
researchers and clinicians to interact, plan, and prepare for the future
of the profession. The dialogue provided a clear indication that: (1) the
pursuit of translational research will
have a definite impact on physical
therapist practice, and (2) infrastructure will need to be developed so
that physical therapy’s impact can
be monitored not only at the level
of an individual patient but also at
the systems level. The dialogue also
resulted in 4 recommendations to
provide specific direction for meeting these goals.
Based on anecdotal reports following the conference, the potential
exists for substantive results to
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develop as a function of the efforts
of those in attendance. The conference, however, was only the first
step in “vitalizing practice and
research.” An ongoing evaluation
process will assess the implementation of the recommendations that
were generated. The results of the
evaluation process will truly measure the impact of the conference
and determine its role in the creation
of a larger cadre of clinical scientists
who enhance the manner in which
physical therapy care is currently
delivered.
The evaluation process will be based
on the desire that conference recommendations must be implemented
throughout the profession. These
recommendations stress the idea that
there needs to be more collaboration
between clinicians and researchers
than is currently the case. Conference participants cited examples
where collaborative efforts have succeeded in improving patient care
and reducing the costs of interventions, not only of physical therapy
but of all therapeutic care provided
throughout the episode. It is hoped
that the examples cited at the conference will generalize across the
profession and increase services that
are based on evidence so that
evidence- and value-based practice
becomes the norm throughout the
profession.
The evaluation process cited above
also will affect the entire profession.
The first stage of the process
involves presentations that have
been made and will continue to be
made at local, regional, and national
meetings to describe the conference
and inform audiences of the recommendations developed at the conference. However, this is only the initial
step. Over time, those physical therapists who are practicing either
based on evidence or in collaboration with researchers will be pro-
Number 8
vided opportunities to share their
experiences with groups of physical
therapists as well. Dissemination of
these experiences can lead to more
collaboration, to the development
of additional databases of evidence
that can be contributed to and used
by larger numbers of clinicians,
and, ultimately, to the enhancement
of patient care.
One of the recommendations was
that the client should be at the center of efforts for the provision of services and consumers must be the
beneficiary of services based on evidence. The recognition of evidencebased services for the ultimate benefit of the client is motivating
individual clinicians and networks.
The conference can and will be
judged successful if this mode of
practice is adopted by a substantial
proportion of the profession. Adoption of these recommendations
will only enhance our status as a
profession.
Conference Evaluation
Simply conducting a conference
without assessing its value almost
defeats the purpose of having a conference. Therefore, an extensive
evaluation will be undertaken that
will span into the future. The
extended time frame is warranted, as
it will likely take a substantial
amount of time for the recommendations to be fully implemented. The
evaluation of the effectiveness of the
conference will follow a modified
version of the CIPP (Context-InputProcess-Product) model developed
by Stufflebeam.36,37 This model
accounts for the context in which
decisions have to be made. Thus,
inputs, process, and outputs of a
decision have to be evaluated. In the
evaluation of this particular conference, we will have to account for
behavioral changes of clinicians and
researchers and cite how these
changes affect the context or the
environment in which services are
August 2011
provided. Thus, the evaluation will
proceed over a somewhat lengthy
period of time until the profession
can be confident that its services are
provided in the optimum manner.
M.S. Goldstein, EdD, American Physical
Therapy Association, Alexandria, Virginia.
Address all correspondence to Dr Goldstein
at: [email protected].
The effectiveness evaluation model
will be modified, as not all components are applicable. The portion of
the model that deals with all postconference activities contains the
most useful elements; these are the
elements that will be used to assess
the value of the conference. Thus,
the evaluation will contain the following elements:
J.A. Bohmert, PT, MS, Special Education,
Anoka-Hennepin ISD 11, Anoka, Minnesota.
• Impact evaluation, which assesses a
program’s reach to the target
audience,
• Effectiveness evaluation, which
assesses both the quality and significance of outcomes, and
• Sustainability evaluation, which
assesses the extent to which a program’s contributions are successfully institutionalized and continued over time.24
E.C. Field-Fote, PT, PhD, Department of
Orthopaedics and Rehabilitation, University
of Miami, Coral Gables, Florida.
Given that the evaluation process
will encompass a lengthy period of
time, the expectation is that the conference is only the first step in a
process that, ideally, will change the
behaviors of both researchers and
clinicians. Any discussion of a time
frame would have to be couched in
terms of increments. It is incumbent
on conference planners to assess any
adaptive behaviors over a period of
years.
[Goldstein MS, Scalzitti DA, Bohmert JA,
et al. Vitalizing practice through research
and research through practice: the outcomes of a conference to enhance the delivery of care. Phys Ther. 2011;91:1275–1284.]
Having said that, however, during
the upcoming year, a series of assessments will be made that will allow
conference planners to determine at
least the preliminary effects of the
conference on the profession. At
least 2 presentations involving a
panel of conference participants will
be given during the upcoming year.
August 2011
D.A. Scalzitti, PT, PhD, OCS, American Physical Therapy Association.
G.P. Brennan, PT, PhD, Physical Therapy
Department, IHC Health Center–South Jordan, South Jordan, Utah.
R.L. Craik, PT, PhD, FAPTA, Department of
Physical Therapy, Arcadia University, Glenside, Pennsylvania.
A. Delitto, PT, PhD, FAPTA, Department of
Physical Therapy, University of Pittsburgh,
Pittsburgh, Pennsylvania.
C.M. Magistro, PT, FAPTA, Claremont,
California.
C.M. Powers, PT, PhD, Department of Biokinesiology & Physical Therapy, University of
Southern California, Los Angeles, California.
R.K. Shields, PT, PhD, FAPTA, Physical Therapy and Rehabilitation Sciences, Carver College of Medicine, University of Iowa, Iowa
City, Iowa.
All authors provided concept/idea/project
design, writing, and consultation (including
The authors would like to recognize and
thank the following individuals for contributing to the conference and this article:
Ralph Nitkin, PhD, and Daofen Chen, PT,
PhD, who were instrumental in conference
planning, and Steven Z. George, PT, PhD,
and Gregory Hicks, PT, PhD, who reviewed
and commented on an earlier draft of
the manuscript. Their input is greatly appreciated.
Published Ahead of Print: June 9, 2011
Submitted: October 18, 2010
DOI: 10.2522/ptj.20100339
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17 Wensing M, Bosch M, Grol R. Developing
and selecting interventions for translating
knowledge to action. CMAJ. 2010;182:
E85–E88.
18 Woolf SH, Johnson RE. The break-even
point: when medical advances are less
important than improving the fidelity with
which they are delivered. Ann Fam Med.
2005;3:545–552.
19 McGlynn EA, Asch SM, Adams J, et al. The
quality of health care delivered to adults in
the United States. N Engl J Med. 2003;348:
2635–2645.
20 Fritz JM, Cleland JA, Brennan GP. Does
adherence to the guideline recommendation for active treatments improve the
quality of care for patients with acute low
back pain delivered by physical therapists?
Med Care. 2007;45:973–979.
21 Petrova M, Dale J, Fulford BK. Value-based
practice in primary care: easing the tensions between individual values, ethical
principles and best evidence. Br J Gen
Pract. 2006;56:703–709.
22 Kjeken I, Ziegler C, Skrolsvik J, et al. How
to develop patient-centered research:
some perspectives based on surveys
among people with rheumatic diseases
in Scandinavia. Phys Ther. 2010;90:450 –
460.
23 Tallon D, Chard J, Dieppe P. Relation
between agendas of the research community and the research consumer. Lancet.
2000;355:2037–2040.
24 Harrison M, Légaré F, Graham ID, Fervers
B. Adapting clinical practice guidelines for
local context and assessing barriers to
their use. CMAJ. 2010;182:E78 –E84.
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25 Brouwers M, Stacey D, O’Connor A.
Knowledge creation: synthesis, tools and
products. CMAJ. 2010;182:E68 –E72.
26 Liang L. The gap between evidence and
practice. Health Affairs. 2007;26:w119 –
w121.
27 Rutten GM, Degen S, Hendriks EJ, et al.
Adherence to clinical practice guidelines
for low back pain in physical therapy: do
patients benefit? Phys Ther. 2010;90:
1111–1122.
28 Etheredge LM. A rapid-learning health system. Health Affairs. 2007;26:w107–w118.
29 Granger CV, Markello SJ, Graham JE, et al.
The Uniform Data System for Medical
Rehabilitation: report of patients with
traumatic brain injury discharged from
rehabilitation programs in 2000 –2007.
Am J Phys Med Rehabil. 2010;89:
265–278.
30 Duncan JR, Evens RG. Using information
to optimize medical outcomes. JAMA.
2009;301:2383–2385.
31 Kerse N, Arroll B, Lloyd T, et al. Evidence
databases, the Internet, and general practitioners: the New Zealand story. N Z Med
J. 2001;114:89 –91.
32 Goldstein MS. Creating a culture of collaboration: vitalizing practice through
research and research through practice.
Presented at: Vitalizing Practice Through
Research and Research Through Practice
Conference; American Physical Therapy
Association; December 2– 4, 2009; Philadelphia, Pennsylvania.
Number 8
33 Gliklich RE, Dreyer NA, eds. Registries for
Evaluating Patient Outcomes: A User’s
Guide. 2nd ed. Rockville, MD: Agency for
Healthcare Research and Quality; September 2010. AHRQ Publication No. 10EHC049.
34 Kigin CM, Rodgers MM, Wolf SL; PASS
Steering Committee Members. The Physical Therapy and Society Summit (PASS)
Meeting: observations and opportunities.
Phys Ther. 2010;90:1555–1567.
35 Goldstein MS, Scalzitti DA, Craik RL, et al.
The Revised Research Agenda for Physical
Therapy. Phys Ther. 2011;91:165–174.
36 Guba EG, Lincoln YS. Effective Evaluation: Improving the Usefulness of Evaluation Results Through Responsive and
Naturalistic Approaches. San Francisco,
CA: Jossey-Bass Inc Publishers; 1981.
37 Stufflebeam DL. CIPP Evaluation Model
Checklist: a tool for applying the fifth installment of the CIPP Model to assess long-term
enterprises. Western Michigan University.
June 2002. Available at: http://www.
wmich.edu/evalctr/checklists/. Accessed
September 2010.
August 2011
Appendix 1.
Conference Participants
Stephanie Renee Albin, PT, OCS (Utah)
Stephen C. Allison, PT, PhD (Arizona)
Kristin Archer, PT, DPT, PhD (Tennessee)
Skulpan Asavasopon, PT, MPT, OCS, FAAOMPT (California)
Heather Lisa Atkinson, PT, DPT, NCS (New Jersey)
George Beneck, PT, OCS (California)
Stacey Lynn Brickson, PT, PhD, ATC (Wisconsin)
David Alan Brown, PT, PhD (Illinois)
Amy L. Castillo, PT, MPT, SCS, CSCS (Indiana)
Prisca M. Collins, PT (Illinois)
Chad Edward Cook, PT, PhD, MBA, FAAOMPT (Ohio)
Judith Deutsch, PT, PhD (New Jersey)
Reuben Escorpizo, PT (Florida)
Linda V. Fetters, PT, PhD, FAPTA (California)
Eileen Fowler, PT, PhD (California)
Sara Francois, PT (Iowa)
Julie M. Fritz, PT, PhD, ATC (Utah)
Mary Lou Galantino, PT, PhD, MSCE (Delaware)
Steven Z. George, PT, PhD (Florida)
Laura Sisola Gilchrist, PT, PhD (Minnesota)
Deborah Lynn Givens, PT, PhD, OCS (Ohio)
Allan M. Glanzman, PT, DPT, PCS, ATP (Pennsylvania)
Denise Gobert, PT, PhD (Texas)
Joseph John Godges, PT, DPT, MA, OCS (California)
Andrew Guccione, PT, DPT, PhD, FAPTA (Virginia)
Robbin Ann Hickman, PT, DSc, PCS (Nevada)
Gregory Evan Hicks, PT, PhD (Maryland)
August 2011
Karen Holtgrefe, PT, DHS, OCS (Ohio)
Thomas M. Howell, PT, MPT (Idaho)
Eva Margareta Huey, PT (Ohio)
Gail M. Jensen, PT, PhD, FAPTA (Nebraska)
Diane U. Jette, PT, DSc (Vermont)
Tara Jo Manal, PT, DPT, OCS, SCS (Delaware)
Kathleen Kline Mangione, PT, PhD, GCS (Pennsylvania)
Kimberly Susan Marryott-Lee, PT (Georgia)
Michael Jeffrey Mueller, PT, PhD, FAPTA (Missouri)
Kim A. Nixon-Cave, PT, PhD, PCS (New Jersey)
Barbara J. Norton, PT, PhD, FAPTA (Missouri)
Shreedevi Pandya, PT, MS (New York)
Genevieve Pinto-Zipp, PT, EdD (New Jersey)
Mary Jane K. Rapport, PT, DPT, PhD (Colorado)
Clare E. Safran-Norton, PT, PhD, MS, OCS (Massachusetts)
Karen Lohmann Siegel, PT (Maryland)
Maureen Janet Simmonds, PT, PhD (Canada)
Patricia L. Sinnott, PT, PhD, MPH (California)
Beth Ann Smith, PT, DPT, PhD (Oregon)
Cheryl Lynn Sparks, PT, DPT, OCS (Illinois)
Scott Karl Stackhouse, PT, PhD (Pennsylvania)
Katherine Sullivan, PT, PhD (California)
Anne K. Swisher, PT, PhD, CCS (West Virginia)
Anne Thackeray, PT (Utah)
Leslie Torburn, PT, DPT (California)
Robert S. Wainner, PT, PhD, ECS, OCS (Texas)
Steven L. Wolf, PT, PhD, FAPTA (Georgia)
Volume 91
Number 8
Physical Therapy f
1283
Appendix 2.
Conference Presentationsa
Prerecorded Audiovisual Presentations
The Business Case of Quality
Joseph Baumgaertner, PT, MS
The Essential Components
Larry Benz, PT, DPT, MBA, ECS
Consumer-Driven Approach to Research
Joanell A. Bohmert, PT, MS
Improving Practice Through Clinical Research
Gerard P. Brennan, PT, PhD
Performance Assessment and Cost-Effectiveness Research
Anthony Delitto, PT, PhD, FAPTA, and Pamela B. Peele, PhD
A Systematic Approach to Physical Therapy Documentation
Susan Horn, PhD
Translating Clinical Research Into Improved Patient Outcomes
Stephen Hunter, PT, OCS
The Relevance of Translational Research in Physical Therapy
Alan Jette, PT, PhD, FAPTA
Engaging the Professional Workforce
Mike Johnson, PT, PhD, OCS
Private Practice, A Health System and Academia—It Can Work
Paul Rockar, PT, DPT, MS
Presentations On Site During the Conference
Evolution of the Conference
Marc S. Goldstein, EdD
Vitalizing Practice Through Research and Research Through Practice: A Clinician’s Perspective
Charles M. Magistro, PT, FAPTA
Are You Ready?
Rebecca L. Craik, PT, PhD, FAPTA
Practice to Research to Practice: Cycle of Influence and Implementation
Joseph J. Godges, PT, DPT, MA, OCS
Elements for Change
Pamela B. Peele, PhD
a
Information regarding the conference and the presentations is available at: http://www.apta.org/ResearchConference2009.
1284
f
Physical Therapy
Volume 91
Number 8
August 2011
Scholarships,
Fellowships, and Grants
News from the Foundation for Physical Therapy
Recent Publications by
Foundation-Funded
Researchers
“Appropriate Use of Diagnostic
Imaging in Low Back Pain—A
Reminder That Unnecessary Imaging May Do as Much Harm as
Good,” by Flynn TW, Smith B, and
Chou R, was published online in
the Journal of Orthopaedic and
Sports Physical Therapy on June
3, 2011. Timothy W. Flynn, PT,
PhD, OCS, was awarded a 1996
Doctoral Training Research Grant
and a 2000 Orthopaedic Section
Research Grant.
“Dual-Task Demands of Hand
Movements for Adults With Stroke:
A Pilot Study,” by Pohl PS, Kemper S, Siengsukon CF, Boyd L,
Vidoni ED, and Herman RE, was
published in Topics in Stroke Rehabilitation (2011;18[3]:238–247).
Patricia S. Pohl, PT, PhD, was
awarded Doctoral Training Research Grants in 1993 and 1994.
“Low-Frequency H-Reflex Depression in Trained Human Soleus
After Spinal Cord Injury,” by
Shields RK, Dudley-Javoroski S,
and Oza PD, was published in Neuroscience Letters (2011;499[2]:88–
92). Richard K. Shields, PT, PhD,
FAPTA, was awarded Doctoral
Training Research Grants in 1989
and 1990.
“Lumbopelvic Landing Kinematics and EMG in Women With Contrasting Hip Strength,” by Popovich JM Jr, and Kulig K, was published online in Medicine and
Science in Sports and Exercise on
June 8, 2011. John M. Popovich Jr,
PT, DPT, MS, was awarded Promotion of Doctoral Studies (PODS) I
scholarships in 2005 and 2007 and
a PODS II scholarship in 2008.
August 2011
Foundation 8.11.indd 1285
“Predictors of Web-based Followup Response in the Prevention of
Low Back Pain in the Military Trial
(POLM),” by Childs JD, Teyhen
DS, Van Wyngaarden JJ, Dougherty BF, Ladislas BJ, Helton GL,
Robinson ME, Wu SS, and George
SZ, was published online in BMC
Musculoskeletal Disorders
on
June 13, 2011. John D. Childs, PT,
PhD, MBA, OCS, CSCS, FAAOMPT,
was awarded a PODS I scholarship in 2001 and the Pittsburgh–
Marquette Research Grant in 2004.
Steven Z. George, PT, PhD, MS,
was awarded a PODS I scholarship in 2000 and a PODS II scholarship in 2001.
“A Profile of Glenohumeral Internal and External Rotation
Motion in the Uninjured High
School Baseball Pitcher,” a 2-part
article by Hurd WJ, Kaplan KM,
Eiattrache NS, Jobe FW, Morrey
BF, and Kaufman KR, was published in the Journal of Athletic
Training (2011;46[3]:282–288 and
2011;46[3]:289–295). Wendy J.
Hurd, PT, PhD, MS, was awarded
the Mary McMillan Doctoral scholarship in 2002, a PODS I scholarship in 2003, and a PODS II scholarship in 2004.
“Analysis of Shortened Versions of
the Tampa Scale for Kinesiophobia and Pain Catastrophizing Scale
for Patients After Anterior Cruciate Ligament Reconstruction,” by
George SZ, Lentz TA, Zeppieri G,
Lee D, and Chmielewski TL, was
published online in The Clinical
Journal of Pain on June 14, 2011.
Steven Z. George, PT, PhD, MS,
was awarded a PODS I scholarship in 2000 and a PODS II scholarship in 2001.
“Age-Related Differences in Muscle Fatigue Vary by Contraction
Type: A Meta-analysis,” by Keith
G. Avin, PT, MPT, MS, and Laura
A. Frey Law, PT, PhD, MS, was
published in Physical Therapy
(2011;91[8]:1153–1165]. Avin was
awarded a Florence P. Kendall
scholarship in 2008, a PODS I
scholarship in 2009, and a PODS
II scholarship in 2010. Frey Law
was awarded a McMillan Doctoral scholarship in 2000, a PODS I
scholarship in 2001, and a PODS
II scholarship in 2002.
Foundation Announces
Winning Schools of
Pittsburgh–Marquette
Challenge
The
Foundation
announced
the winners of the Pittsburgh–
Marquette Challenge at its annual
gala on June 9 at National Harbor, Maryland. Physical therapist
and physical therapist assistant
students from 62 schools across
the country raised a record-breaking $264,274 to support physical
therapy research. In 23 years, the
Challenge has raised more than $2
million to benefit the Foundation.
Congratulations to the winning schools of the Pittsburgh–
Marquette Challenge:
•
•
•
1st Place: University of
Pittsburgh ($56,800);
2nd Place: Sacred Heart
University ($31,600);
3rd Place: Emory University
($23,800).
7/8/11 1:22 PM
Scholarships, Fellowships, and Grants
Award of Merit (donating $6,000 or
more): Rosalind Franklin University, Somerset Community College,
University of Delaware, University
of Miami, University of North Carolina–Chapel Hill, and Virginia Commonwealth University.
Honorable Mention (donating
$3,000 or more): Arcadia University, Boston University, Lynchburg
College, Mayo School of Health
Science, MGH Institute of Health
Professions, Midwestern
University, Northeastern University,
Northwestern University, Simmons
College, University of Alabama at
Birmingham, University of Evansville, University of Iowa, University of Oklahoma, University of St
Augustine, and Washington University in St Louis.
Kendall scholarship. Foundation
Research Grants are available for
either 1- or 2-year projects for new
and emerging investigators.
Applications are due August 17,
2011, at 12:00 pm, noon, ET. For
more details or to apply, please
visit Foundation4PT.org/apply-forfunding.
Share Your Research News
and Announcements With
the Foundation
To have your information posted in
the Foundation’s section of Physical Therapy, please e-mail our Program Assistant, Rachael Crockett, at
RachaelCrockett@Foundation4PT.
org.
Stay Connected With the
Foundation in 3 Easy Ways
1. www.facebook.com/foundation
4PT.
2. Check out our Web
Foundation4PT.org.
site:
3. Subscribe to our monthly newsletter for updates on our donors,
researchers, events, and much
more! E-mail AbegailMatienzo@
Foundation4PT.org to sign up
today.
[DOI: 10.2522/ptj.2011.91.8.1285]
Special Awards:
•
•
•
Most Successful Newcomer:
Lynchburg College;
Biggest
Stretch
School:
University of North Carolina–
Chapel Hill;
Most Successful PTA School:
Somerset Community College.
For a complete listing of schools
that participated in the Pittsburgh–Marquette Challenge, visit
the Foundation’s Web site. The
2011–2012 Pittsburgh–Marquette
Challenge kicks off at the National
Student Conclave in Minneapolis,
Minnesota, on October 21, 2011.
Current Funding
Opportunities
The Foundation is now accepting
applications for the Florence P. Kendall Doctoral scholarship, Foundation Research Grant, and Magistro
Family Foundation Research Grant.
Students beginning their postprofessional doctoral programs are
encouraged to apply for a $5,000
Any Amount—Every Month—Leads to ExcePTional Results
Your Participation Matters
Every Gift Counts
The Foundation for Physical Therapy’s excePTional giving program allows the Foundation to direct funds
to areas with the most urgent needs,
and it all starts with you. Monthly or
quarterly gifts provide sustained revenue that let the Foundation plan for
the future. The benefits are endless.
The Foundation for Physical Therapy
equips new researchers to make a
difference in our world. Your support of the excePTional monthly giving program makes this possible by
providing the resources necessary to
fund postprofessional doctoral scholarships, fellowships, and research
grants. Your investment in your colleagues’ talents and energy, and in
all they will accomplish for the world
that awaits them, will have an impact on our profession and health
care for decades to come.
Your gift is automatically charged to
your credit card each month or quarter. You retain full control and can
modify or cancel future gifts at any
time. At the end of the year, you will
receive an itemized receipt for your
gifts. Gifts of $10 per month become
$120 a year; gifts of $84 per month
become more than $1,000 a year!
Foundation 8.11.indd 1286
To make a gift today, please visit
Foundation4PT.org/Get-Involved/
Donate. To learn more about joining the excePTional program, visit
Foundation4pt.kintera.org/become
exceptional.
For more information, contact Rachael
Estep, assistant director of development, 800/875-1378, RachaelEstep
@Foundation4PT.org.
August 2011
7/18/11 10:51 AM
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Index to General Information
Found at: www.apta.org
Physical Therapy (PTJ)
Accredited Education
Programs ............http://www.capteonline.org/Programs/
Awards ..................... http://www.apta.org/HonorsAwards/
Bylaws ................................. http://www.apta.org/Policies/
Call for Nominations .......... http://www.apta.org/Elections/
Code of Ethics .................................... http://www.apta.org/
CoreDocuments/
Abstracts of Papers Accepted for
Presentation at Annual Conference
(added every May) ............................ ptjournal.apta.org/
site/misc/annualcon.xhtml
Submission Guidelines .......................... ptjournal.apta.org/
site/misc/ifora.xhtml
In Memoriam............................................................March
Index (Author/Subject) .......................................December
Mary McMillan Lecture ...................................... November
Membership Statistics ..................................................June
Presidential Address ........................................... November
Statement of Ownership .....................................December
August 2011
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August 2011

August 2011 - Physical Therapy Journal

Transcription

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