Complete August Issue - Physical Therapy Journal

Transcription

August 2013 Volume 93 Number 8
<LEAP> Linking Evidence And Practice
1021
Exercise for Managing Osteoporosis in
Women Postmenopause
1073
Home-Based Cardiac Rehabilitation
1084
Active Video Games in Children With
Cerebral Palsy
1092
Facial Pain Associated With Fibromyalgia
1102
Balance Assessment in Stroke
1116
Urinary Incontinence Questionnaire
Research Reports
1026
1037
Effect of Therapeutic Exercise on Pain and
Disability in Chronic Nonspecific Neck Pain
Change in Physical Activity in People With
Relapsing-Remitting Multiple Sclerosis
1049
Effects of Exercise on Osteoarthritic Cartilage
1061
Falls in Ambulatory Individuals With Spinal
Cord Injury
Case Report
1130
Cognitive-Behavioral–Based Physical Therapy
to Improve Surgical Spine Outcomes
Assessing Competence:
A Resource Manual
An Invaluable Tool for Employers and Clinicians
Designed to help both employers and physical therapists, this resource manual
features reviews of 9 of the most common methods for measuring competence:
Order No. E-60
Regular Price: $87.00
APTA Member price: $51.95
To order, call APTA’s Member
Services Department at
800/999-APTA (2782), ext 3395,
Mon-Fri, 8:30 am-6:00 pm, EST
or order online at www.apta.org.
• Case report
• Chart review
• Outcome measurements
• Employee performance appraisal
• Portfolio review
• Key-feature problems/examinations
• Self-assessment
• Competence checklists
• Proficiency testing
Assessing Competence provides samples and updated references and resources.
Employers can use the manual to develop methods for assessing their employees’
performance. Clinicians can use it to evaluate the strengths and weaknesses of
their practices. As a self-assessment tool, it can help guide your professional
development now and in the future.
Physical Therapy
■ Volume 93
■ Number 8
■ August 2013
Health Policy in Perspective
1020
Rothstein Roundtable Podcast—”Medicare Mandate for
Claims-Based Functional Data Collection: An Opportunity
to Advance Care, or a Regulatory Burden?”
<LEAP> Linking Evidence And Practice
Diego Rivera (Mexican, 1886–1957).
Vegetable sellers in market of Santiago
Tlaltelolco, detail on left of the Great
Tenochtitlan. © 2013 Banco de Mexico
Diego Rivera Frida Kahlo Museums Trust,
Mexico, D.F. / Artists Rights Society (ARS),
New York. Photo credit: Gianni Dagli Orti /
The Art Archive at Art Resource, NY.
A controversial figure in both politics
and art, Rivera painted larger-thanlife murals using simple, bold forms
that often echoed ancient Mayan and
Aztec style. The Tlaltelolco market was
one of the largest Aztec markets, with
almost 25,000 buyers and sellers every
day; Rivera captures the interaction
and activity of the marketplace—arms
extended in transaction, babies slung
across mothers’ shoulders, the forwardleaning postures of men bearing loads
from the fields.
1021
Effectiveness of Exercise for Managing Osteoporosis in
Women Postmenopause / Kerstin M. Palombaro, Jill D. Black,
Rachelle Buchbinder, Diane U. Jette
Research Reports
1026
Effect of Therapeutic Exercise on Pain and Disability in
the Management of Chronic Nonspecific Neck Pain:
Systematic Review and Meta-Analysis of Randomized
Trials / Lucia Bertozzi, Ivan Gardenghi, Francesca Turoni,
Jorge Hugo Villafañe, Francesco Capra, Andrew A. Guccione,
Paolo Pillastrini
1037
Longitudinal Change in Physical Activity and Its Correlates
in Relapsing-Remitting Multiple Sclerosis / Robert W. Motl,
Edward McAuley, Brian M. Sandroff
1049
Acute Cartilage Loading Responses After an In Vivo
Squatting Exercise in People With Doubtful to Mild Knee
Osteoarthritis: A Case-Control Study / Ans Van Ginckel,
Erik Witvrouw
1061
Incidence and Factors Associated With Falls in Independent
Ambulatory Individuals With Spinal Cord Injury: A 6-Month
Prospective Study / Sirisuda Phonthee, Jiamjit Saengsuwan,
Wantana Siritaratiwat, Sugalya Amatachaya
Craikcast
Editor in Chief Rebecca Craik gives her unique
insights on the August issue. Available at
http://ptjournal.apta.org/content/93/8/suppl/DC1 and through
iTunes.
1014 ■ Physical Therapy Volume 93 Number 8
TOC_8.13.indd 1014
August 2013
7/15/13 11:41 AM
1073
Departments
Home-Based Versus In-Hospital Cardiac Rehabilitation
After Cardiac Surgery: A Nonrandomized Controlled
Study / Simonetta Scalvini, Emanuela Zanelli, Laura Comini,
Margherita Dalla Tomba, Giovanni Troise, Oreste Febo,
Amerigo Giordano
1084
Facial Pain Associated With Fibromyalgia Can Be Marked
by Abnormal Neuromuscular Control: A Cross-Sectional
Study / Maísa Soares Gui, Cristiane Rodrigues Pedroni,
Scholarships, Fellowships,
and Grants
1147
Product Highlights
1148
Ad Index
Abstracts of Papers to be Presented at
APTA’s Conference and Exposition (added
every May): ptjournal.apta.org/site/misc/
aptaconference.xhtml
Psychometric Properties of the Mini-Balance Evaluation
Systems Test (Mini-BESTest) in Community-Dwelling
Individuals With Chronic Stroke / Charlotte S.L. Tsang,
Lin-Rong Liao, Raymond C.K. Chung, Marco Y.C. Pang
1116
1145
Resources
Luana M. Martins Aquino, Marcele Jardim Pimentel, Marcelo Correa Alves,
Sueli Rossini, Rubens Reimão, Fausto Berzin, Amélia Pasqual Marques,
Célia Marisa Rizzatti-Barbosa
1102
The Bottom Line
News from the Foundation for
Physical Therapy
Exercise Intensity Levels in Children With Cerebral Palsy
While Playing With an Active Video Game Console /
Maxime Robert, Laurent Ballaz, Raphael Hart, Martin Lemay
1092
1018
Psychometric Properties and Practicability of the SelfReport Urinary Incontinence Questionnaire in Patients
With Pelvic-Floor Dysfunction Seeking Outpatient
Rehabilitation / Ying-Chih Wang, Dennis L. Hart, Daniel Deutscher,
PTJ Submission Guidelines:
ptjournal.apta.org/site/misc/ifora.xhtml
APTA Membership Statistics: June issue
PTJ Statement of Ownership: December
issue
Sheng-Che Yen, Jerome E. Mioduski
Case Report
1130
Cognitive-Behavioral–Based Physical Therapy to Improve
Surgical Spine Outcomes: A Case Series / Kristin R. Archer,
Nicole Motzny, Christine M. Abraham, Donna Yaffe, Caryn L. Seebach,
Clinton J. Devin, Dan M. Spengler, Matthew J. McGirt, Oran S. Aaronson,
Joseph S. Cheng, Stephen T. Wegener
Letters
1141
On “Exercise assessment and prescription in patients
with type 2 diabetes...” Hansen D, Peeters S,
Zwaenepoel B, et al. Phys Ther. 2013;93:597–610.
1142
Author Response
Visit ptjournal.apta.org
Listen to audio podcasts.
View videoclips.
Listen to discussion
podcasts.
August 2013
TOC_8.13.indd 1015
Volume 93 Number 8 Physical Therapy ■ 1015
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Physical Therapy
Editor in Chief
Deputy Editor in Chief
Daniel L. Riddle, PT, PhD, FAPTA
Richmond, VA
Rebecca L. Craik, PT, PhD, FAPTA
Philadelphia, PA
[email protected]
Editor in Chief Emeritus
Jules M. Rothstein, PT, PhD, FAPTA
(1947–2005)
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; Leonardo Costa, PT, PhD, São Paulo, Brazil;
Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; Janet K. Freburger, PT, PhD, Durham, NC; Steven Z. George, PT, PhD, Gainesville, FL;
Kathleen Gill-Body, PT, DPT, NCS, Boston, MA; Jan Willem Gorter, PhD, MD, FRCPC, Hamilton, Ont, Canada;
Rana Shane Hinman, PT, PhD, Melbourne, Victoria, Australia; James J. Irrgang, PT, PhD, ATC, FAPTA, Pittsburgh, PA;
Sarah H. Kagan, PhD, FAAN, RN, Philadelphia, PA; Teresa Liu-Ambrose, PT, PhD, Vancouver, BC, Canada;
Christopher Maher, PT, PhD, Sydney, NSW, Australia; Chris J. Main, PhD, FBPsS, Keele, United Kingdom;
Sarah Westcott McCoy, PT, PhD, Seattle, WA; Patricia J. Ohtake, PT, PhD, Buffalo, NY; Carolyn Patten, PT, PhD, Gainesville, FL;
Darcy Schwartz Reisman, PT, PhD, Wilmington, DE; Linda Resnik, PT, PhD, Providence, RI; Kathleen Sluka, PT, PhD, Iowa City, IA;
Nicholas Stergiou, PhD, Omaha, NE; Philip J. Van der Wees, PT, PhD, Nijmegen, the Netherlands;
Chair, Rothstein Roundtable: Anthony Delitto, PT, PhD, FAPTA, Pittsburgh, PA
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
Committee on Health Policy and Ethics
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
<LEAP> Linking Evidence And Practice Advisory Group
Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia (Co-Chair);
Diane U. Jette, PT, DSc, FAPTA, Burlington, VT (Co-Chair); W. Todd Cade, PT, PhD, St Louis, MO;
Christopher Maher, PT, PhD, Sydney, NSW, Australia; Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA;
David Scalzitti, PT, PhD, OCS, Washington, DC
Senior Reviewers
Karen Abraham-Justice, PT, PhD; Peter Altenburger, PT, PhD; Kristin Archer Swygert, DPT, PhD; Paul Beattie, PT, PhD, OCS, FAPTA;
Justin Beebe, PT, PhD; Anjana Bhat, PT, PhD; Sandra Billinger, PT, PhD, FAHA; Mark Bishop, PT, PhD, CSCS; Timothy Brindle, PT, PhD, ATC;
Rhea Cohn, PT, DPT; Chad Cook, PT, PhD, MBA, OCS, FAAOMPT; Janet Copeland, Dip PT, BA, MHealSc; Richard Debigare, PT, PhD;
Susan Deusinger, PT, PhD, FAPTA; Stacey Dusing, PT, PhD; Cheryl Ford-Smith, PT, DPT, MS, NCS; Jorge Fuentes, PT, BSc, MSc, RS, PhD Candidate;
Marc Goldstein, EdD; Karin Gravare Silbernagel, PT, PhD, ATC; David Greathouse, PT, PhD, ECS; Kathy Green, PhD;
Bruce Greenfield, PT, PhD, OCS; Christina Gummesson, PT, PhD; Mijna Hadders-Algra, MD, PhD; Regina Harbourne, PT, PhD, PCS;
Karen Hayes, PT, PhD, FAPTA; Thomas Hornby, PT, PhD; Kenton Kaufman, PhD; Suzanne Kuys, GDPublth, BPhysio(H); Andrew Leaver, PhD;
Amanda Lundvik Gyllensten, PT, PhD; Sunita Mathur, PT; Christine McDonough, PT, PhD; Irene McEwen, PT, PhD, FAPTA; Susanne Morton, PT, PhD;
Kurt Mossberg, PT, PhD; Gina Musolino, PT, MSEd, EdD; Randy Richter, PT, PhD; Mark Damian Rossi, PT, PhD, CSCS; Susan Roush, PhD;
Anita Slade, PhD; Beth Smith, PT, DPT, PhD; Tasha Stanton, PT, PhD; Sandra Stuckey, PT, PhD, MA; Greg Thielman, PT, EdD, ATC;
David Thompson, PT, PhD; Ann Vendrely, PT, DPT, EdD; Ying-Chih Wang, PhD; Kathy Zackowski, PhD, OTR; Joseph Zeni, PhD
Editorial Office
Managing Editor / Director of Evidence-Based Resources: Jan P. Reynolds, [email protected]; PTJ Online Editor / Assistant Managing Editor: Steven Glaros;
Associate Editor: Stephen Brooks, ELS; Production Manager: Liz Haberkorn; Manuscripts Coordinator: Karen Darley;
Permissions / Reprint Coordinator: Michele Tillson; Advertising Manager: Julie Hilgenberg; Publisher: Lois Douthitt
APTA Executive Staff
Vice President for Communications: Felicity Feather Clancy; Chief Financial Officer: Rob Batarla; Interim Chief Executive Officer: Bonnie Polvinale
Advertising Sales
Ad Marketing Group, Inc, 2200 Wilson Blvd, Suite 102-333, Arlington, VA 22201; 703/243-9046, ext 102; President / Advertising Account Manager: Jane Dees Richardson
Board of Directors
President: Paul A. Rockar Jr, PT, DPT, MS; Vice President: Sharon L. Dunn, PT, PhD, OCS; 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: Stuart Platt, PT, MSPT;
Directors: Jennifer E. Green-Wilson, PT, MBA, EdD; Jeanine M. Gunn, PT, DPT; Roger A. Herr, PT, MPA, COS-C; Kathleen K. Mairella, PT, DPT, MA;
Carolyn Oddo, PT, MS, FACHE; Lisa K. Saladin, PT, PhD; Mary C. Sinnott, PT, DPT, MEd; Nicole L. Stout, PT, MPT, CLT-LANA; Sue Whitney, PT, DPT, PhD, NCS, ATC, FAPTA
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Subscriptions
Physical Therapy (PTJ) (ISSN 00319023) is published monthly by the
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Mission Statement
Physical Therapy (PTJ) engages and
inspires an international readership on
topics related to physical therapy. As
the leading international journal for
research in physical therapy and related fields, PTJ publishes innovative and
highly relevant content for both clinicians and scientists and uses a variety
of interactive approaches to communicate that content, with the expressed
purpose of improving patient care. PTJ
is the official scientific journal of the
American Physical Therapy Association
(APTA) and the Royal Dutch Society
for Physical Therapy (KNGF).
Readers are invited to submit manuscripts to PTJ. PTJ’s content—including editorials, commentaries, and letters—represents the opinions of the
authors and should not be attributed
to PTJ or its Editorial Board. Content
does not reflect the official policy of
APTA or KNGF or the institution with
which the author is affiliated, unless
expressly stated.
PTJ Online
at ptjournal.apta.org
PTJ Online is available via RSS
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of print and rapid reader responses to
articles. Articles, letters to the editor, and
editorials are available in full text starting
with Volume 79 (1999) and in searchable PDF format starting with Volume 60
(1980). Entire issues are available online
beginning with Volume 86 (2006) and
include additional data, video clips, and
podcasts.
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Advertising
Advertisements are accepted by PTJ
when they conform to the ethical
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Therapy Association. PTJ does not
verify the accuracy of claims made in
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competencies in clinical specialty areas
does not imply review or endorsement
by the American Board of Physical
Therapy Specialties.
Statement of
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APTA prohibits preferential or adverse
discrimination on the basis of race,
creed, color, gender, age, national or
ethnic origin, sexual orientation, disability, or health status in all areas
including, but not limited to, its qualifications for membership, rights of
members, policies, programs, activities,
and employment practices. APTA is
committed to promoting cultural diversity throughout the profession.
Royal Dutch Society for Physical Therapy
August 2013
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The Bottom Line
The Bottom Line summarizes the key points of articles that report research with a direct impact
on patient care.
Effects of Exercise on
Osteoarthritic Cartilage
Cartilage in joints with osteoarthritis (OA)
shows altered mechanical behavior that
may increase the vulnerability of the cartilage to accelerated degeneration because
of repetitive impact loads. After a 30repetition squatting exercise, tibiofemoral cartilage deformation appeared to be
similar in magnitude and spatial pattern
in participants who were middle-aged
and either had or did not have tibiofemoral OA. Restoration of cartilage volumes
to baseline levels required a 15-minute recovery, especially in participants with OA.
Message for patients: After 30 repetitions
of full weight-bearing squatting, middleaged people should allow at least 15 minutes of rest from exercise to permit knee
cartilage volumes to recover to pre-exercise
levels.
See page 1049.
Home-Based Cardiac
Rehabilitation
Rehabilitation after cardiac surgery often improves quality of life, reduces cardiovascular
disease risk factors, and can increase physical
capacity. A 20% reduction in all-cause mortality and a 27% reduction in cardiac mortality following cardiac rehabilitation also
have been reported in systematic reviews.
This study compared exercise capacity after
a home-based cardiac rehabilitation (HBCR)
program or an in-hospital program in patients with a low to medium risk for early
mortality after cardiac surgery. The study
found that the HBCR program was feasible, safe, and comparable to the conventional in-hospital rehabilitation approach,
indicating that rehabilitation following cardiac surgery in patients at low risk for early
mortality can be implemented effectively
at home when programmed with an integrated telemedicine service. Message for
patients: If you are at low risk for early mortality after cardiac surgery, you may achieve
a better quality of life with a complete, supervised rehabilitation program at home via
telemedicine.
See page 1073.
Active Video Games in Children
With Cerebral Palsy
In the past few years, several studies have
shown that commercially available active
video game consoles (AVGCs) can improve
the fitness of children who are typically developing. Despite the fact that AVGCs such
as the Wii are currently used in several rehabilitation centers, very few studies to date
have evaluated exercise intensity in children
with spastic diplegic cerebral palsy (CP)
during game play. This study showed that
exercise intensity while playing Wii games
was similar between children with and without CP. Message for patients: Active video
game consoles are an affordable, safe, and
playful approach to improve aerobic capacity in children with CP.
Facial Pain Associated With
Fibromyalgia
Myofascial pain associated with temporomandibular disorder (TMD) has been related to fibromyalgia syndrome (FMS), and
fibromyalgia symptoms precede facial pain
in patients with FMS. However, a specific
mechanism explaining these coexisting conditions has not been identified. In this article,
the authors hypothesize that FMS may play
a role in triggering TMD, because patients
with FMS experience facial pain associated
with a different surface electromyographic
response. According to the results of the
study, it appears that the sensorimotor system fails to inhibit muscle contraction with
pain in FMS; however, it remains unclear
whether muscle contraction differences occurred before or after facial pain. Message
for patients: Fibromyalgia syndrome appears to have a series of characteristics that
could constitute predisposing or triggering
factors for facial pain associated with TMD in
patients with FMS.
See page 1092.
See page 1084.
August 2013
Order now at www.APTA.org/Store!
Health Policy in
Perspective
Rothstein Roundtable Podcast— “Medicare
Mandate for Claims-Based Functional Data
Collection: An Opportunity to Advance Care,
or a Regulatory Burden?”
Panelists: Alan Jette, Mary Stilphen, Dan Ciolek. Moderator: Linda Resnik
C
linicians and administrators have begun implementing Medicare’s mandated claims-based functional data
collection. At the 2013 Rothstein Roundtable at APTA Conference in Salt Lake City, Utah, on June 28, 2013,
a panel of administrators and health services and health policy researchers debated the potential benefits—and
the potential pitfalls— of this regulation. The panel discussed how functional status data collection might ultimately
impact the provision of and reimbursement for outpatient therapy services. The Rothstein Roundtable is named in
honor of Physical Therapy (PTJ) Editor-in-Chief Emeritus Jules Rothstein, PT, PhD, FAPTA, who believed passionately in the importance of scholarly dialogue and debate.
The podcast is available at: http://ptjournal.apta.org/content/93/8/1020/suppl/DC1
A. Jette, PT, PhD, FAPTA, Director, Health & Disability Research Institute, and Professor of Health Policy and Management, School of Public
Health, Boston University, Boston, Massachusetts.
M. Stilphen, PT, DPT, Senior Director, Rehabilitation and Sports Therapy, Cleveland Clinic, Cleveland, Ohio.
D. Ciolek, PT, Principal Consultant, MEDPROTECT LLC, an SAIC Company, Baltimore, Maryland.
L. Resnik, PT, PhD, OCS, Research Health Scientist, Providence VA Medical Center; Associate Professor (Research), Department of Health
Services, Policy and Practice, Brown University, Providence, Rhode Island; and a member of the Focus on Therapeutic Outcomes (FOTO)
Research Advisory Board. She is a member of the PTJ Editorial Board.
[DOI: 10.2522/ptj.2013.93.8.1020].
1020
f
Physical Therapy
Volume 93
Number 8
August 2013
⬍LEAP⬎
LINKING EVIDENCE AND PRACTICE
Effectiveness of Exercise for Managing Osteoporosis in
Women Postmenopause
Kerstin M. Palombaro, Jill D. Black, Rachelle Buchbinder, Diane U. Jette
<LEAP> highlights the findings and
application of Cochrane reviews and
other evidence pertinent to the
practice of physical therapy. The
Cochrane Library is a respected
source of reliable evidence related
to health care. Cochrane systematic
reviews explore the evidence for and
against the effectiveness and appropriateness of interventions—medications, surgery, education, nutrition,
exercise—and the evidence for and
against the use of diagnostic tests for
specific conditions. Cochrane reviews
are designed to facilitate the decisions of clinicians, patients, and others in health care by providing a
careful review and interpretation of
research studies published in the scientific literature.1 Each article in this
PTJ series summarizes a Cochrane
review or other scientific evidence
resource on a single topic and will
present clinical scenarios based on
real patients to illustrate how the
results of the review can be used
to directly inform clinical decisions.
This article focuses on exercise for
the management of osteoporosis in
women postmenopause. Which, if
any, approaches to exercise reduce
loss of bone mineral density or
reduce the chance of fractures in
women who are healthy postmenopause?
Find the <LEAP> case archive at
http://ptjournal.apta.org/cgi/
collection/leap.
August 2013
A 2003 report from the Surgeon General of the United States estimated
that 10 million individuals had osteoporosis and almost 34 million had
low bone mass, placing them at
increased risk for osteoporosis.2
Analysis of data from people with 6
to 7 years of Medicare coverage in
the United States in 2005 estimated
the prevalence of osteoporosis to be
approximately 30%.3 The major outcome of concern in osteoporosis is
minimal trauma fracture. This is a
type of fracture resulting from injury
that would be insufficient to fracture
normal bone and are referred to as
low-impact fracture, fragility fracture, and osteoporotic fracture.4 One
study estimated that by 2025, osteoporotic fractures will grow to more
than 3 million, incurring $25.3 billion in costs.5
Primary osteoporosis is the result of
aging or menopause, or both.6 Aging
causes a decrease of osteoblastic
activity, resulting in decreases in
bone formation.6 Menopause causes
an increase of osteoclastic activity,
which results in increases in bone
reabsorption.4 The result is a
decrease in bone mineral density
(BMD), which increases fracture
risk. Bone mineral density is measured by dual-energy x-ray absorptiometry (DXA). According to a World
Health Organization scientific group
report, the risk of fracture at any
biologically relevant site increases
1.5-fold per standard deviation
decrease in BMD from the average
value for young women who are
healthy.7 This measure is termed the
gradient of risk. The highest gradient
of risk is at the femoral neck; the risk
of hip fracture increases by approx-
imately 2.6 for each standard deviation decrease in BMD.
There is a relationship between sarcopenia, which is age-related muscle
loss, and osteopenia, or bone tissue
loss. The prevalence of sarcopenia
increases as BMD decreases.8 Physical performance is affected by sarcopenia, with deficits in gait and
balance noted in people with sarcopenia and osteoporosis.9 Impaired
physical performance increases fall
risk, which, in turn, increases the
risk of fracture for people with
osteoporosis.9 Severe osteoporosis
and sarcopenia are associated with
frailty.10 Decreased physical activity
is one risk factor for both osteoporosis11 and sarcopenia.12 According
to Wolff’s law, bone dynamically
adapts to the stresses placed upon
it.13 Exercise interventions, theoretically, should improve bone density,
both through directly loading bone
and through increasing muscle mass,
which also places further mechanical stress on the skeleton.
The purpose of a systematic review
by Howe et al14 was to determine
the impact of exercise interventions
for postmenopausal women in the
prevention of bone loss and fractures. The primary outcome examined was vertebral and nonvertebral
(hip and wrist) fracture incidence.
The secondary outcomes examined
were changes in BMD, serious
adverse events, and minor adverse
events such as falls.
Take-Home Message
The Cochrane review by Howe et
al14 comprised an electronic database search of the literature through
December 2010. The review included
43 randomized controlled trials with
Volume 93
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Physical Therapy f
1021
<LEAP> Case #16 Exercise for Managing Osteoporosis in Women Postmenopause
Table.
Summary of Key Results of Review by Howe et al14,a
Overview
● 43 RCTs involving a total of 4,320 participants and published up to December 2010
● Studies carried out in North America (19), Europe (12), Australia (4), Japan (4), China (2), and Brazil (2)
● Duration of intervention: 10: ⬍12 months, 26: 12 months, 7: ⬎12 months
● Frequency of intervention: 33: 2–3 times/week, 3: daily, 7: 4–6 times/week
● BMD measured at lumbar spine in 30 studies and at hip in 30 studies
Any Exercise vs Control
Grade of
Evidence
Main Outcome
Results
Fracture risk
High
● 4 studies with 539 participants
● OR⫽0.61 (95% CI⫽0.23 to 1.64)
% BMD change in spineb
High
● 24 studies with 1,441 participants
● MD⫽0.85 (95% CI⫽0.62 to 1.07)
% BMD change in femoral neckc
Low
● 19 studies with 1,338 participants
● MD⫽⫺0.08 (95% CI⫽⫺1.08 to 0.92)
% BMD change in hipd
High
● MD⫽0.41 (95% CI⫽⫺0.64 to 1.45)
% BMD change in trochanter
High
● MD⫽1.03 (95% CI⫽0.56 to 1.49)
Specific Exercise Interventions vs Control
No. of Studies
With Low
Risk of Bias
Exercise Type
Significant Results
Static weight-bearing exercise (eg, single-leg
standing)
0
● 1 study with 31 participants
● % change in hip BMDd: MD⫽2.42 (95% CI⫽0.73 to 4.10)
Dynamic, low-force, weight-bearing exercise
(eg, walking, tai chi)
4
● % change in spine BMDb: MD⫽0.87 (95% CI⫽0.26 to 1.48)
Dynamic, high-force, weight-bearing exercise
(eg, jogging, jumping, running, dancing)
2
● % change in hip BMDd: MD⫽1.55 (95% CI⫽1.41 to 1.69)
Low-force, non–weight-bearing exercise
(eg, low-load, high-repetition strength training)
0
● No significant differences in any outcome measures
High-force, non–weight-bearing exercise
(eg, progressive resistance strength training)
1
1
● % change in femoral neck BMDc: MD⫽1.03 (95% CI⫽0.24 to 1.82)
2
● Risk of fractures: OR⫽0.33 (95% CI⫽0.13 to 0.85)
1
1
● % change in trochanter BMDe: MD⫽1.31 (95% CI⫽0.69 to 1.92)
1
● % change in femoral neck BMDc: MD⫽0.45 (95% CI⫽0.08 to 0.82)
1
● % change in hip BMDd: MD⫽⫺1.07 (95% CI⫽⫺1.58 to ⫺0.56)
Combination exercise (types listed above)
(Continued)
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Table.
Continued
Adverse Events
Event Type
No. of Studies
With Low
Risk of Bias
Results
Total falls
2
● Exercise groups⫽75, control groups⫽55
Others (eg, muscle soreness, joint pain,
headache, itching)
5
● Exercise groups⫽60, control groups⫽5
a
RCT⫽randomized controlled trial, BMD⫽bone mineral density, OR⫽odds ratio, 95% CI⫽95% confidence interval, MD⫽mean difference.
Least significant change in postmenopausal women⫽5.43%.17
d
e
Least significant change unknown.
b
c
a total of 4,320 postmenopausal
women who were healthy and aged
45 to 70 years (Table). Studies were
included in which the intervention
group engaged in an exercise program that could improve aerobic
capacity or aerobic capacity and
muscle strength and a comparison
group engaged in usual activity or
a placebo intervention. The duration of the exercise interventions
reported in the studies ranged
between 6 months and 2 years. Only
8 studies included data obtained
after the completion of the intervention. Pooled data showed that the
odds of incident fracture in groups
engaged in any type of exercise were
not different from the odds of fracture in the control groups (odds ratio
[OR]⫽0.61, 95% confidence interval
[95% CI]⫽0.23 to 1.64). There was,
however, a small, statistically significant effect for any type of exercise
versus a comparison group on mean
BMD loss (pooled data from 24 studies), with 0.85% less bone loss in the
spine (between-group mean difference [MD]⫽0.85, 95% CI⫽0.62 to
1.07) and 1.03% less bone loss in the
trochanter (MD⫽1.03, 95% CI⫽0.56
to 1.49), based on pooled data from
10 studies.
To account for the variability in the
exercise programs reported in the
studies, the authors performed additional subgroup analyses for outAugust 2013
comes with sufficient numbers of
studies to allow meta-analysis. They
found an effect in favor of dynamic,
low-force, weight-bearing exercise
for percentage change in BMD of the
spine (MD⫽0.87, 95% CI⫽0.26 to
1.48); an effect in favor of dynamic,
high-force, weight-bearing exercise
for percentage change in BMD of
the hip (MD⫽1.55, 95% CI⫽1.41 to
1.69); an effect in favor of high-force,
non–weight-bearing exercise for percentage change in BMD of the spine
(MD⫽0.86, 95% CI⫽0.58 to 1.13)
and neck of femur (MD⫽1.03, 95%
CI⫽0.24 to 1.82); and an effect in
favor of combination exercise on
odds of total fractures (OR⫽0.33,
95% CI⫽0.13 to 0.85) and for percentage change in BMD of the spine
(MD⫽3.22, 95% CI⫽1.80 to 4.64),
trochanter (MD⫽1.31, 95% CI⫽0.69
and 1.92), and neck of femur
(MD⫽0.45, 95% CI⫽0.08 to 0.82).
The adverse events that were documented for the exercise intervention
groups included falls, muscle soreness, joint pain, headache, and itching. Although there appeared to be
more falls among those in the exercise groups in comparison with the
control groups (75 versus 55 falls,
respectively, based on 3 studies
with 378 participants), a comparative analysis of the risk of falling
could not be performed, as studies
reported the number of falls rather
than the number of people falling.
Additionally, most trials reporting
adverse events appeared to have paid
more attention to adverse events in
the exercise intervention groups
(known as “performance bias”) and
did not report whether adverse
events were monitored in the same
way in the control groups.
The authors noted several factors
hindering the interpretation of
results of both the main analyses
and subgroup analyses. These factors
included small sample sizes; heterogeneous ethnicity in samples; losses
to follow-up in most studies; the lack
of sufficient reporting of type, intensity, frequency, duration, and mode
of exercise; and heterogeneity of
results across studies. Additionally,
conclusions could not be made
about the impact of exercise in the
initial postmenopausal period versus
the later menopausal period.
Case #16: Applying
Evidence to a Patient
With Osteoporosis
Can exercise training help this
patient?
Mrs Baldwin is a 58-year-old Caucasian woman employed as an administrator in a small private high
school. She was walking across the
school campus when she tripped
and fell. She felt immediate pain in
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her low back and hip. A radiograph
revealed no fractures. Although the
hip pain quickly resolved, the patient
continued to have low back pain
for several days and sought the care
of her physical therapist.
At her outpatient physical therapist
evaluation, Mrs Baldwin reported
that she was 4 years postmenopause,
was a nonsmoker, had no significant
past medical history or predilection
to falling, and was taking no medications; she considered herself very
healthy. There was no known family
history of osteoporosis. Mrs Baldwin
reported that she did 30 minutes of
walking at a moderate pace most
days of the week for exercise and
was an avid gardener. She had had
a DXA scan approximately 1 year
previously indicating the presence
of osteopenia in the lumbar spine
(T-score⫽⫺2.0) and hip (femoral
neck T-score⫽⫺1.8, total hip
T-score⫽⫺1.0). At that time, her
physician had recommended she
take calcium and vitamin D supplements and maintain regular exercise.
Although the physical therapist
focused on evaluation and management of the patient’s acute low back
pain, she wondered whether she
also should provide specific exercise
advice for Mrs Baldwin in view of
her known osteopenia and potential
future fracture risk.
How did the results of the
Cochrane systematic review
apply to Mrs Baldwin?
Using the PICO (Patient, Intervention, Comparison, Outcome) format,
Mrs Baldwin’s physical therapist
asked the question: In a postmenopausal woman with osteopenia who
is generally healthy, will adding a
muscle strengthening component
to a daily walking program of exercise reduce the chance of future fractures and slow the loss of bone mineral density? Based on this question,
a literature search identified the
Cochrane review by Howe et al.14
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Patient relevance. The systematic
review included studies in which the
participants were postmenopausal
women who were healthy, aged 45
to 70 years, and with or without previous fractures. These criteria
matched Mrs Baldwin.
Intervention and comparison relevance. The review included studies with any exercise intervention
that could be assumed to improve
aerobic or muscle strength, and several of the included studies examined the effects of combination exercise regimens. Included studies
compared exercise with usual care
or placebo intervention. Because
Mrs Baldwin had a regular walking
exercise program already, her physical therapist was interested in
whether adding a strength training
component would provide added
benefits. The alternative was to
continue with the walking program
and not add muscle strength training. The therapist, therefore, was
most interested in the results for
combination exercise regimens.
Outcomes relevance. The review
examined the differences between
intervention and comparison groups
in risk of fracture and percent
change in BMD, 2 important considerations for Mrs Baldwin given her
DXA results.
Based on the results of the systematic review and its applicability to
Mrs Baldwin, upper-extremity and
lower-extremity progressive resistive
exercises were gradually implemented as Mrs Baldwin was able to
tolerate them. Additionally, a twiceweekly program consisting of multidirectional jumps and jumping on
and off boxes of various heights
(plyometrics) was initiated. Mrs
Baldwin’s physical therapist recommended that she join a health club
to continue the muscle strength
training and plyometrics program 2
to 3 times per week and that she
Number 8
continue to walk 30 minutes most
days of the week.
How well do the outcomes of the
intervention provided to the
patient match those suggested
by the systematic review?
After Mrs Baldwin had been engaged
in her exercise regimen for 2 years,
her physician requested a repeat
DXA scan.15 The results demonstrated no further bone loss at the
spine or hip. These DXA results,
which might be at least partially
attributed to Mrs Baldwin’s combination exercise regimen, are consistent
with those reported in the systematic review for combination exercise. The systematic review showed
that exercise programs combining
different types of exercise and lasting between 6 and 24 months
resulted in a reduced risk of fracture,
as well as a slightly beneficial effect
on BMD of the spine, trochanter, and
neck of femur.
Can you apply the results of the
systematic review to your own
patients?
The findings of this study may be
applied to postmenopausal women
who are healthy, up to the age of 70
years, and who may or may not have
experienced previous fractures. The
nature of the included studies precluded the review authors from
distinguishing the effects of the
interventions for women in early
phases of menopause compared
with later phases. The first 3 to 5
years postmenopause is a period of
hormonal variability,16 making it
challenging to apply results across all
women postmenopause. The studies
were performed in several countries;
however, the nature of the included
studies did not allow the review
authors to distinguish the effects of
the interventions for women of different racial or ethnic backgrounds.
There was a good deal of variability
in the interventions across studies;
they included exercises such as
August 2013
walking, plyometrics, progressive
resistance strength training, and
combinations of exercise types.
Although the majority of studies provided the exercise intervention 2 or
3 times per week, most studies did
not provide a complete description
of duration, intensity, and frequency.
Most of the types of exercises
reported in the review could be readily accomplished in many settings; all
but one study included only landbased exercises. Some types of exercise, however, are likely to be better
performed in a gym or health club
setting than in the home setting.
With limited follow up after the completion of most study interventions,
the long-term benefits of exercise
interventions on BMD and fracture
rate of women postmenopause
could not be determined. Finally,
the results of the review are based
on studies with variable risk of bias,
with only 13 of 43 (30%) classified as
having a low risk of bias.
What can be advised based on
the results of this systematic
review?
Postmenopausal women who are
healthy, such as Mrs Baldwin, may
benefit from an exercise program at
least 2 to 3 times per week over the
course of at least 6 months, and
physical therapists should consider
helping their clients and patients
to plan and design appropriate
programs. Although engaging in any
type of exercise may be effective in
slightly reducing loss of BMD in the
spine and femoral trochanter, the
most effective type of exercise for
reducing loss of BMD in the neck of
the femur might be high-force, non–
weight-bearing exercise such as
progressive resistance training of
the lower extremity. A combination
exercise regimen seems to be the
most effective for reducing loss of
BMD in the spine and neck of the
August 2013
femur and reducing risk of fracture,
at least in the short term. Combining
results across studies with all types
of exercise, 4 more women out of
100 in the usual care or placebo
group sustained a fracture than in
the exercise group, although this difference was not statistically significant. The long-term impact of these
small differences between women
who engage in exercise interventions and those who perform only
their normal activities is unknown.
5
6
7
8
K.M. Palombaro, PT, PhD, CAPS, Institute for
Physical Therapy Education, Widener University, Chester, Pennsylvania.
9
J.D. Black, PT, DPT, EdD, Institute for Physical
Therapy Education, Widener University.
R. Buchbinder, MBBS(Hons), MSc, PhD,
FRACP, Department of Clinical Epidemiology, Cabrini Hospital, Malvern, Victoria,
Australia.
D.U. Jette, PT, DSc, FAPTA, Department of
Rehabilitation and Movement Science, University of Vermont, Burlington, VT 05405
(USA). Address all correspondence to Dr
Jette at: [email protected].
[Palombaro KM, Black JD, Buchbinder R,
Jette DU. Effectiveness of exercise for managing osteoporosis in women postmenopause. Phys Ther. 2013;93:1021–1025.]
© 2013 American Physical Therapy Association
Published Ahead of Print: May 23, 2013
Accepted: April 2, 2013
Submitted: December 19, 2011
10
11
12
13
14
DOI: 10.2522/ptj.20110476
References
15
1 The Cochrane Library. Available at: http://
www.cochrane.org/cochrane-reviews.
2 Report of the Surgeon General’s Workshop on Osteoporosis and Bone Health:
December 12–13, 2002. The Burden of
Disease: Bone Health, Osteoporosis, and
Related Bone Diseases. 2003. Available
at: http://www.ncbi.nlm.nih.gov/books/
NBK44689/. Accessed February 22, 2013.
3 Cheng H, Gary LC, Curtis JR, et al. Estimated prevalence and patterns of presumed osteoporosis among older Americans based on Medicare data. Osteoporos
Int. 2009;20:1507–1515.
4 World Health Organization. Assessment of
fracture risk and its application to screening for postmenopausal osteoporosis.
16
17
Volume 93
Report of a WHO study group. 1994:1–
129. Available at: http://whqlibdoc.who.
int/trs/WHO_TRS_843.pdf. Accessed January 15, 2013.
Burge R, Dawson-Hughes B, Solomon DH,
et al. Incidence and economic burden
of osteoporosis-related fractures in the
United States, 2005–2025. J Bone Miner
Res. 2007;22:465– 475.
Raisz LG. Pathogenesis of osteoporosis:
concepts, conflicts, and prospects. J Clin
Invest. 2005;115:3318 –3325.
World Health Organization. WHO Scientific Group on the Assessment of Osteoporosis at Primary Health Care Level. 2007.
Available at: http://www.who.int/chp/
topics/Osteoporosis.pdf. Accessed February 2013.
Walsh MC, Hunter GR, Livingstone MB.
Sarcopenia in premenopausal and postmenopausal women with osteopenia,
osteoporosis and normal bone mineral
density. Osteoporos Int. 2006;17:61– 67.
Waters DL, Hale L, Grant AM, et al. Osteoporosis and gait and balance disturbances
in older sarcopenic obese New Zealanders. Osteoporos Int. 2010;21:351–357.
Frisoli A Jr, Chaves PH, Ingham SJ, Fried
LP. Severe osteopenia and osteoporosis,
sarcopenia, and frailty status in communitydwelling older women: results from the
Women’s Health and Aging Study (WHAS)
II. Bone. 2011;48:952–957.
Daly RM, Ahlborg HG, Ringsberg K, et al.
Association between changes in habitual
physical activity and changes in bone density, muscle strength, and functional performance in elderly men and women.
J Am Geriatr Soc. 2008;56:2252–2260.
Baumgartner RN, Waters DL, Gallagher D,
et al. Predictors of skeletal muscle mass
in elderly men and women. Mech Ageing
Dev. 1999;107:123–136.
Barak MM, Lieberman DE, Hublin JJ. A
Wolff in sheep’s clothing: trabecular bone
adaptation in response to changes in joint
loading orientation. Bone. 2011;49:1141–
1151.
Howe TE, Shea B, Dawson LJ, et al. Exercise for preventing and treating osteoporosis in postmenopausal women.
Cochrane Database Syst Rev. 2011;(7):
CD000333.
National Osteoporosis Foundation. Clinician’s Guide to Prevention and Treatment
of Osteoporosis. 2010. Available at: http://
www.nof.org/files/nof/public/content/
file/344/upload/159.pdf. Accessed January 15, 2013.
Qin L, Au SK, Leung PC, et al. Baseline
BMD and bone loss at distal radius measured by peripheral quantitative computed tomography in peri- and postmenopausal Hong Kong Chinese women.
Osteoporos Int. 2002;13:962–970.
Lodder MC, Lems WF, Ader HJ, et al.
Reproducibility of bone mineral density
measurement in daily practice. Ann
Rheum Dis. 2004;63:285–289.
Number 8
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Research Report
L. Bertozzi, PT, School of Physical
Therapy, Alma Mater Studiorum,
University of Bologna, Bologna,
Italy.
I. Gardenghi, PT, Department of
Biomedical and Neuromotor Services, Alma Mater Studiorum, University of Bologna.
F. Turoni, PT, Department of Biomedical and Neuromotor Services, Alma Mater Studiorum, University of Bologna.
J.H. Villafañe, PT, PhD, IRCCS Don
Gnocchi Foundation, Milan, Italy.
F. Capra, PT, Department of Biomedical and Neuromotor Services, Alma Mater Studiorum, University of Bologna.
A.A. Guccione, PT, PhD, DPT,
FAPTA, Department of Rehabilitation Science, College of Health
and Human Services, George
Mason University, Fairfax, Virginia.
P. Pillastrini, PT, Department of
Biomedical and Neuromotor Sciences, Alma Mater Studiorum,
University of Bologna, Via U. Foscolo, 7-40123, Bologna, Italy.
Address all correspondence to
Professor Pillastrini at: paolo.
[email protected].
[Bertozzi L, Gardenghi I, Turoni F,
et al. Effect of therapeutic exercise
on pain and disability in the management of chronic nonspecific
neck pain: systematic review and
meta-analysis of randomized trials. Phys Ther. 2013;93:1026 –
1036.]
© 2013 American Physical Therapy
Association
Published Ahead of Print:
April 4, 2013
Submitted: October 4, 2012
Effect of Therapeutic Exercise on Pain
and Disability in the Management of
Chronic Nonspecific Neck Pain:
Systematic Review and Meta-Analysis
of Randomized Trials
Lucia Bertozzi, Ivan Gardenghi, Francesca Turoni, Jorge Hugo Villafañe,
Francesco Capra, Andrew A. Guccione, Paolo Pillastrini
Background. Given the prevalence of chronic nonspecific neck pain (CNSNP)
internationally, attention has increasingly been paid in recent years to evaluating the
efficacy of therapeutic exercise (TE) in the management of this condition.
Purpose. The purpose of this study was to conduct a current review of randomized controlled trials concerning the effect of TE on pain and disability among people
with CNSNP, perform a meta-analysis, and summarize current understanding.
Data Sources. Data were obtained from MEDLINE, Cumulative Index to Nursing
and Allied Health Literature (CINAHL), EMBASE, Physiotherapy Evidence Database
(PEDro), and Cochrane Central Register of Controlled Trials (CENTRAL) databases
from their inception to August 2012. Reference lists of relevant literature reviews also
were tracked.
Study Selection. All published randomized trials without any restriction regarding time of publication or language were considered for inclusion. Study participants
had to be symptomatic adults with only CNSNP.
Data Extraction. Two reviewers independently selected the studies, conducted
the quality assessment, and extracted the results. Data were pooled in a meta-analysis
using a random-effects model.
Data Synthesis. Seven studies met the inclusion criteria. Therapeutic exercise
proved to have medium and significant short-term and intermediate-term effects on
pain (g⫽⫺0.53, 95% confidence interval [CI]⫽⫺0.86 to ⫺0.20, and g⫽⫺0.45, 95%
CI⫽⫺0.82 to ⫺0.07, respectively) and medium but not significant short-term and
intermediate-term effects on disability (g⫽⫺0.39, 95% CI⫽⫺0.86 to 0.07, and
g⫽⫺0.46, 95% CI⫽⫺1.00 to ⫺0.08, respectively).
Limitations. Only one study investigated the effect of TE on pain and disability at
follow-up longer than 6 months after intervention.
Conclusions. Consistent with other reviews, the results support the use of TE in
the management of CNSNP. In particular, a significant overall effect size was found
supporting TE for its effect on pain in both the short and intermediate terms.
Post a Rapid Response to
this article at:
ptjournal.apta.org
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Effect of Therapeutic Exercise on Pain and Disability in Chronic Nonspecific Neck Pain
N
eck pain is one of the most
common musculoskeletal disorders, second only to low
back pain,1 with an annual prevalence among the general and workforce populations of 30% to 50%.2
Although the natural history of this
condition appears to be favorable,
rates of recurrence3 and chronicity4
appear high. The course of neck pain
often is characterized by exacerbations, and more than one third of
patients with neck pain will develop
chronic symptoms lasting more than
6 months.5 In particular, chronic
nonspecific neck pain (CNSNP) (ie,
chronic neck pain without any specific disease detected as the underlying cause of the complaints6) represents the vast majority of cases,
contributing to substantial health
care costs, work absenteeism, and
loss of productivity at all levels.7,8
In order to decrease this social burden of disability, the use of interventions with demonstrated efficacy for
specific outcomes is clearly essential.9 Increased attention has been
paid in recent years to evaluating the
efficacy of various conservative therapeutic interventions used by physical therapists to manage CNSNP,10
especially
therapeutic
exercise
(TE).11 However, few rehabilitation
studies are designed with the
expressed intention of determining
effectiveness under routine clinical
conditions and with study participants generally representative of a
particular clinical population, rather
than the tightly controlled conditions of a randomized controlled trial
(RCT).
Despite the growing number of studies assessing the efficacy of this intervention, substantial inconsistencies
continue to exist, in part, due to
insufficient evidence regarding optimal dose-response relationships, the
best mode for delivering the service,
and the differential outcomes of different types of exercise on CNSNP,12
August 2013
leaving little clarity for evidencebased clinical practice. For example,
4 recent reviews present conflicting
results regarding the benefit of
strengthening exercises for relieving
neck pain symptoms. Sarig-Bahat11
and Sihawong et al,10 in their
reviews of 2003 and 2010, respectively, found relatively strong evidence supporting the efficacy of
dynamic resisted strengthening exercises of the neck-shoulder musculature. In the intervening years, Kay et
al12 concluded in 2009 that the evidence of efficacy for strengthening
exercises was unclear, and Ylinen,13
in 2007, found moderate evidence
supporting the efficacy of dynamic
and isometric-resisted strengthening
exercises.
One limitation of previous reviews
has been the tendency to aggregate
results pertaining not only to CNSNP
but also to different and heterogeneous conditions (eg, whiplashassociated disorder, myofascial neck
pain, degenerative changes, cervicobrachialgia, back and shoulder pain)
while simply referring to them as
“chronic mechanical neck disorders.” Inconsistencies among the
reviews also are likely due to differences in search dates, characteristics
of interventions, mixing of neck disorder durations, and incompatibility
in the analysis of results obtained
from comparison versus placebocontrolled trials.12,14 In addition,
RCTs published in the past decade
often have lacked sufficient power
to draw clear and definitive conclusions.15 These persistent methodological inconsistencies justified the
need for a study that explicitly targeted its population of interest, characteristics of RCTs, and duration of
follow-up as inclusion criteria in
order to determine a more accurate
estimate of the efficacy of TE and its
impact on pain and disability outcomes in patients with CNSNP, as a
first step in unraveling the tangle of
inconclusive evidence to date.
Method
Data Sources and Searches
Our literature search was aimed at
identifying all available studies that
evaluated the effect of TE in relieving
pain and improving function and disability outcomes in people with
CNSNP. Records were identified by
searching multiple literature databases, including MEDLINE, Cumulative Index to Nursing and Allied
Health
Literature
(CINAHL),
EMBASE, Physiotherapy Evidence
Database (PEDro), and Cochrane
Central Register of Controlled Trials
(CENTRAL), from their inception to
August 2012. The key word “neck
pain” was used at the first level of
inquiry to ensure that our search
began as broadly as possible. Queries
were limited to RCTs as type of publications and to those involving
human adult participants (18 years
or older). Additional records were
searched through other sources to
complement the database findings;
manual research of reference lists
of relevant literature reviews and
indexes of peer-reviewed journals
were used.
Study Selection
Types of studies. Several criteria
were used to select eligible studies.
We included published RCTs without any restrictions on publication
date or language. Quasi-RCT and
nonrandomized controlled trials
were excluded. Among RCTs, only
trials with a control or comparison
group were considered for inclusion
in the study. These comparison trials
included: (1) intervention versus placebo or sham intervention, (2) intervention versus no-exercise intervention or comparator (eg, self-care,
advice, continuing with ordinary or
recreational activities), and (3) intervention versus standard practice (eg,
wait list, usual care). Our criterion
for designating a study as a “comparison” trial required that the investigators compare TE plus another
intervention versus this same inter-
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1027
vention (eg, exercise and electrotherapy versus electrotherapy only)
in a comparably matched group. Furthermore, the study intervention had
to be performed with identical treatment parameters in all study arms.
Types of participants. The participants had to be symptomatic adults
aged 18 years or older, with a diagnosis of CNSNP or chronic neck muscle pain, also called trapezius myalgia. Because our initial review used
“neck pain” as the key phrase to
ensure the broadest sweep of the
literature, we implemented additional criteria in our further review.
Neck pain was considered chronic
when it emerged from the text that
participants reported neck pain of
more than 3 months’ duration16 or,
in the absence of this explicit
description, when the authors themselves designated the pain as
“chronic.” Trapezius myalgia generally accounts for a vast proportion of
nonspecific neck pain17; therefore,
studies using this term to describe
participants were included.
Trials were excluded if any of the
participants received a specific diagnosis such as radiculopathy, myelopathy, fracture, infection, dystonia,
tumor, inflammatory disease, or
osteoporosis.15 Similarly, trials were
excluded if some or all of the participants had whiplash-associated disorder, myofascial neck pain, neck pain
associated with trauma, degenerative changes, fibromyalgia, or cervicobrachialgia. The trials investigating mixed populations such as
people with neck and back pain,
neck and arm pain, neck pain and
headache, and neck and upper-limb
pain were all excluded, with the
exception of those investigating
neck and shoulder pain, provided
that neck pain could be considered a
primary complaint.
Types of interventions. Among
all types of conservative interven1028
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tions used by physical therapists for
the management of chronic neck
pain, only TE was considered in our
study. Any other interventions such
as education, manual therapy, traction, physical agents and modalities,
cognitive-behavioral therapy, and
multidisciplinary rehabilitation were
excluded. Also, exercise used in
combination with other passive
interventions was excluded. Finally,
trials were excluded if the prevention of neck pain was the main clinical purpose of the study intervention.
Types of outcome measures. To
be eligible for inclusion, a study had
to assess pain by a visual analog
scale, a numerical pain rating scale,
or patient self-report as a primary
outcome measure. Disability was
assessed as a primary outcome measure if the chosen instrument measured the impact of chronic neck
pain on everyday life, beyond work
or leisure-time activities. If more
than one measure of an outcome of
interest was reported within the
same study, only one was considered. We chose the measure that
would most likely provide the most
conservative estimate of the effect of
TE on the outcome due to the magnitude of the pain or disability. For
example, in the case of pain, we
selected the measure that most
nearly corresponded to the question
“What is your worst pain?” to be
used in our analysis. Trials investigating the effect of TE on pressure pain
threshold or pressure pain tolerance,
electromyographic signals, range of
motion, or strength or endurance of
cervical muscles were excluded.
Similarly, health-related quality of
life, patient satisfaction, global perceived effect, work-related measures, depression, and other psychosocial measures were not considered
in our analyses. When possible, we
extracted study findings at baseline
(before intervention), after intervention, and at every reported follow-up
within 12 months.
Number 8
Adopting the categorization proposed by Chow and colleagues18 in
their systematic review and metaanalysis on the efficacy of low-level
laser therapy in the management of
neck pain, duration of follow-up was
defined as short term (0 –1 month),
intermediate term (1– 6 months),
and long term (⬎6 months).
Data Extraction and Quality
Assessment
Two review authors (I.G., F.T.) independently conducted study selection
and data extraction. A third author
(P.P.) was consulted in the case of
persisting disagreement. Reviewers
were not blinded to information
regarding the authors, journal of origin, or outcomes for each reviewed
article. Using a standardized form,
data extraction addressed participants, types of intervention,
follow-up times, clinical outcome
measures, and findings that were
reported. These data are detailed in
Table 1. Methodological quality of
studies was assessed using the PEDro
scale, which has been shown to be
reliable19 and valid20 for rating the
quality of RCTs. Two independent
assessors (I.G., F.T.) obtained or
extracted from the PEDro database
the score for each trial when available. Trials were not excluded on the
basis of quality.
Data Synthesis and Analysis
Data were synthesized using a metaanalytic method based on a randomeffects model due to the significant
heterogeneity and because this
method accounts for both withinstudy and between-study variance;
this approach weights studies by the
inverse of the variance and incorporates heterogeneity into the model.21
All effect sizes were pooled using the
Hedges g statistic because it incorporates a small sample bias correction.22 Comprehensive Meta-Analysis
V.2.2 software (Biostat, Englewood
Cliffs, New Jersey)23 was used for the
statistical analyses. Standardized
August 2013
August 2013
5/10
Beer et al,30 2012, Australia
20 patients with persistent neck
pain
Mean age: 29 y (SD⫽11)
Exp, n⫽10e
Ctrl, n⫽10e
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Number 8
Andersen et al,32 2008,
Denmark
48 patients with trapezius
myalgia
Exp1, n⫽18e
Exp2, n⫽16e
Ctrl, n⫽14, 8e
4/10
4/10
7/10
Häkkinen et al,29 2008,
Finlandd
101 patients with chronic
nonspecific neck pain
Exp, n⫽49, 48e
Ctrl, n⫽52, 51e
Ma et al,31 2011, China
60 patients with chronic neck
pain
Exp, n⫽15, 9e
Ctrl, n⫽15, 10e
5/10
d
PEDro
Score
Dellve et
2011, Sweden
pain
Mean age: 49 y
Exp, n⫽27, 20e
Ctrl, n⫽21, 20e
al,28
Study and Participantsb
Characteristics of Included Studiesa
Table 1.
Exp1: 20-min progressive, high-intensity strength training locally for the
neck and shoulder muscles with 5 different dumbbell exercises (1-arm
row, shoulder abduction, shoulder elevation, reverse flies, and upright
row) performed using consecutive concentric and eccentric muscle
contractions
Exp2: 20-min progressive, high-intensity general fitness training with
the legs only on a bicycle ergometer
Ctrl: no exercise therapy; 1-hr health counseling on a group level and
an individual level
Duration: Exp1–2: 3 times a week for 10 wk; Ctrl: once a week for
10 wk
Exp: 20-min standardized exercise program consisting of strengthening
and stretching exercises using Thera-Band tubing (Hygenic Corporation,
Akron, Ohio), focusing on the neck and shoulder muscles
Ctrl: no exercise therapy; standard education booklet about office
ergonomics
Exp: program with exercises to be practiced at home
Duration: 4 times a day for 7 d/wk for 6 wk
Exp: postural exercise performed in sitting position starting with neutral
lumbopelvic region; patients were taught to gently “lift the base of the
skull from the top of the neck” as if to lengthen the cervical spine ⫹ a
neutral scapular position was taught if the scapulae were judged to be
in a position of downward rotation or protraction
Ctrl: no intervention; any medications as usual
Exp: training was received until patients could perform the postural
exercise properly, holding the position for 10 s, ideally every 15–20 min
throughout their waking day
Duration: every day for 2 wk
Exp: strength training and stretching: progressive isometric neck
strength exercises in flexion, extension, and rotation performed in
sitting position ⫹ dynamic exercises for shoulders and upper extremities
by doing dumbbell shrugs, presses, curls, bent-over rows, flies, and
pullovers ⫹ dynamic abdominal exercises, back exercises, and squats ⫹
stretching of neck, shoulders, and upper-extremity muscles
Ctrl: stretching: as for Exp (instructed in a single session)
Exp-Ctrl: program with exercises to be practiced at home, verbal
instructions and written material on self-treatment, good posture, and
ergonomics
Duration: 3 times a week for 52 wk
Exp: intensive muscular strength training: 5- to 10-min program
starting with 2 warm-up movements, followed by 4 exercises for
strengthening and coordinating the upper extremities; the last 2
exercises included breathing and slow-down movements
Ctrl: no intervention
Duration: twice a day for 6 d/wk for 4 wk
Interventionb
Physical Therapy f
● Pain was significantly decreased in
Exp1 after the intervention
● No significant change over time in
Exp2 and Ctrl
● Pain remained significantly lower in
Exp1 vs Exp2 and Ctrl at follow-up
(1) Pain–VAS (0–100)–worstf/general
pain
—Follow-up at 0 and 2.5 mo
(Continued)
● Pain and disability were
significantly decreased in Exp after
the intervention
significantly decreased in Exp vs
Ctrl after the intervention and at
follow-up
● No significant differences in pain
and disability between groups after
the intervention and from before to
after intervention
● Pain was clinically significantly
decreased, and disability was
statistically significantly decreased
in both groups after the
intervention
and disability between groups
● Pain was decreased in Exp vs Ctrl
over time (mainly at follow-up)
Reported Results
(1) Pain–VAS (0–10)
(2) Disability–Neck Disability Index
(0–100)
—Follow-up at 0 and 6 mo
(1) Pain–VAS (0–10)
(0–100)
—Follow-up at 0 mo
(1) Pain–VAS (0–100)
(0–100)
(1) Pain–Numeric Pain Scale (0–10)
—Follow-up at 0 and 2 mo
Outcome Measures and
Follow-upc
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4/10
Lundblad et al,36 1999, Sweden
pain
Exp1, n⫽32, 15e
Exp2, n⫽33, 20e
Ctrl, n⫽32, 23e
Exp1: 50-min strength, endurance, coordination, stretching, rhythm,
ergonomic, and postural exercises
Exp2: Feldenkrais intervention: 50 min of coordination, postural, and
body awareness exercises
Ctrl: no intervention
Exp1 and Exp2: program with exercises to be practiced at home
Duration: twice a week for 16 wk for Exp1; once a week for 16 wk for
Exp2
Exp1: strength training: concentric resisted exercises, including
latissimus pull-down, triceps press, shoulder flexion, and scapular
retraction
Exp2: endurance training: arm cycling alternating with rubber
expanders, abdominal and back exercises
Exp3: coordination training: body awareness training classes
Ctrl: no intervention; study and discussion of stress management
Duration: Exp1/Exp2/Exp3: 3 times a week for 10 wk; 1-hr session (15min warm-up ⫹ 40-min specific exercises ⫹ 5-min stretching for Exp1
and Exp2, 5-min verbal summary for Exp3); Ctrl: once a week for 10
wk; 2-hr session
Exp: 30-min dynamic muscle training with dumbbells to activate large
muscle groups in the neck and shoulder region ⫹ stretching exercises
Ctrl: no intervention; not changing ordinary physical activity
Duration: 3 times a week for 12 wk, followed by 1 wk of
reinforcement training 6 months after randomization for Exp
Exp: 25-min dynamic strengthening resisted-exercises in flexion and
extension with a neck exercise machine ⫹ 10-min activation of deep
neck muscles through neck strengthening isometric flexor exercises in
supine position with an air-filled pressure sensor
Ctrl: no exercise therapy
Exp-Ctrl: infrared irradiation for 20 min and advice on neck care
Duration: twice a week for 6 wk
Interventionb
c
b
Ctrl⫽control group, Exp⫽experimental group, VAS⫽visual analog scale.
Only data of considered sample groups and their respective interventions were reported.
Follow-up time is intended from postintervention onward.
d
Studies whose data were not included in the meta-analysis.
e
Participants whose data were analyzed.
f
Only pain at worst was considered for data pooling.
a
3/10
8/10
6/10
PEDro
Score
Ahlgren et al,35 2001, Sweden
126 patients with trapezius
myalgia
Exp1, n⫽34, 29e
Exp2, n⫽34, 28e
Exp3, n⫽31, 25e
Ctrl, n⫽27, 20e
Viljanen et al,34 2003, Finland
393 patients with chronic
nonspecific neck pain
Exp, n⫽135e
Ctrl, n⫽130e
Chiu et
2005, Hong Kong
pain
Exp, n⫽67e
Ctrl, n⫽78e
al,33
Study and Participantsb
Continued
Table 1.
significantly decreased in both
groups after the intervention and
significantly maintained at followups
and disability between groups
all exercise groups
(Exp1/Exp2/Exp3) after the
intervention
● Only VAS–worst was significantly
decreased in Exp1 vs Ctrl after the
intervention
● Usual pain intensity (VAS–usually)
decreased significantly in both
Exp2 and Ctrl, with better decrease
in Exp2; no significant changes
occurred in VAS–worst
● No significant differences between
groups
(1) Pain–VAS (0–100)–worstf/
general/present pain
(1) Pain–VAS (0–100)–worstf/usually
pain
—Follow-up at 1.5 mo (on average)
Exp (and disability was significantly
decreased in both groups) after the
intervention and significantly
maintained at follow-up
● Significant differences between
groups in pain and disability after
the intervention but only in pain at
follow-up
Reported Results
(1) Pain–Neck Pain Index (0–10)
(2) Disability–Disability Index (0–80)
—Follow-up at 0, 3, and 9 mo
(1) Pain–verbal numeric pain scale
(0–10)
(2) Disability–Northwick Park Neck
Pain Questionnaire
—Follow-up at 0 and 4.5 mo
Outcome Measures and
Follow-upc
August 2013
Identification
Records identified through
database searching (N=2,574)
•
•
•
•
•
Additional records identified through
other sources (n=0)
MEDLINE (n=434)
CINAHL (n=65)
EMBASE (n=526)
PEDro (n=841)
Cochrane Register of Clinical Trials (n=708)
• Reference list of reviews, systematic
reviews, and meta-analyses (n=0)
Eligibility
Screening
Records after duplicates removed
(n=1,268)
Records excluded
(n=1,213)
Records screened
(n=1,268)
Full-text articles assessed
for eligibility
(n=55)
Included
Studies included in
qualitative synthesis
(n=9)
•
•
•
•
•
•
Full-text articles excluded
(n=46)
Unsuitable diagnostic criterion (n=4)
Acute or subacute neck pain (n=6)
Lack of time-based classification (n=5)
Noneligible comparison trials (n=20)
Other interventions or more than exercise
therapy (n=6)
Results from the same study population of
other included studies (n=5)
Studies included in
quantitative synthesis
(meta-analysis)
(n=7)
Figure 1.
Flowchart of the selection of the studies for the present meta-analysis.
mean differences (SMDs) with 95%
confidence intervals (95% CIs) were
calculated for continuous data. Standardized mean differences were
used because different measures
were adopted by each study to
address the same clinical outcome.
To interpret effect size calculated
with SMD, we used the method
described by Cohen24 as a guide to
identify small (0.20), medium (0.50),
or large (0.80) effects. Calculation of
effect size was based only on the
best possible data (ie, final means,
August 2013
standard deviations, and sample sizes
of intervention and control groups).
Selected studies for which these crucial parameters were not directly
reported, or obtainable by contacting authors, were not included in the
meta-analysis. In cases where different articles covered results from the
same study population, data from
only one article were pooled. When
a trial was designed to compare
more than 2 treatments (ie, comparison trial), we broke up the control
group into several parts so that the
total numbers would add up to the
original size of the group in order
not to count the control group
patients twice.25
The Q and I-square statistics were
used to assess heterogeneity among
studies. The Q statistic has low
power as a comprehensive test of
heterogeneity,26 especially when the
number of studies is small (ie, most
meta-analyses). Conversely, the Q
statistic has too much power as a test
of heterogeneity if the number of
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Physical Therapy f
1031
Table 2.
Pooled Effect Sizes of Outcomes for People With Chronic Nonspecific Neck Pain
Pooled Effect Size,
Hedges g (95%
Confidence Interval)
and P Value
Q and P
Values for
Heterogeneity
No. of
Participants
Short term
6 (9)
664
⫺0.53 (⫺0.86 to ⫺0.20)
P⫽.002
18
P⫽.022
55.44
⫺1.91
P⫽.016
Intermediate term
5 (7)
631
⫺0.45 (⫺0.82 to ⫺0.07)
P⫽.01
16.13
P⫽.013
62.79
⫺2.00
P⫽.063
1
265
⫺0.04 (⫺0.28 to 0.20)
P⫽.7
Not applicable
Not applicable
Not applicable
Short term
4
460
⫺0.39 (⫺0.86 to 0.07)
P⫽.10
11.13
P⫽.011
73
⫺2.73
P⫽.173
Intermediate term
3
440
⫺0.46 (⫺1.00 to 0.08)
P⫽.09
10.30
P⫽.006
80.58
⫺4.17
P⫽.069
Long term
1
265
⫺0.14 (⫺0.38 to 0.11)
P⫽.27
Not applicable
Not applicable
Not applicable
Follow-up
I-Square
Value
Egger t Test and
P Values for
Publication Bias
N
(K)a
Pain
Long term
Disability
a
N⫽number of studies, K⫽number of comparison trials.
studies is large.27 A significant Q
value indicates a lack of homogeneity of findings of studies. Following
the approach of Higgins and Thompson,27 heterogeneity was qualified as
low (25%–50%), moderate (50%–
75%), or high (ⱖ75%). Potential publication bias was assessed using the
Egger t test.
considering only the 7 pooled studies, the number of patients who
were enrolled and completed baseline assessments ranged from 20 to
265, with a mean sample size of 92
participants. The mean age of the
study participants was approximately 39 years (range⫽29 – 45). The
majority of the participants were
female (90%).
Results
We identified 2,574 studies through
database searching. No additional eligible studies were identified through
other sources. After removing duplicates and screening titles and
abstracts of all remaining unique articles, 55 full-text articles needed to be
assessed to verify their eligibility for
the inclusion in the present study.
Ultimately, 46 of them were
excluded for various reasons (Fig. 1),
resulting in 9 studies28 –36 included in
the qualitative synthesis, 7 of which
were eligible for quantitative synthesis by pooling their data for metaanalysis. Overall, the 9 included studies, conducted in Europe, Australia,
and Asia, were published from 1999
to 2012, with 7 of them being published in the last decade. Specifically
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Quality Assessment
Trial quality was generally medium,
with 5 out of 9 trials scoring at least
5 on the PEDro scale28 –30,33,34
(Tab. 1). The quality criteria related
to blinding were never met. However, it should be noted that blinding
patients or therapists is not feasible
in trials involving exercise as the
intervention. Another quality criterion that was commonly unmet (only
2 out of 9 studies) was the requirement that at least one key outcome
was obtained from more than 85% of
the participants initially allocated to
groups.29,34
Outcomes of Treatment
Table 2 presents the follow-up study
findings for pain and disability with
Number 8
respect to the pooled effect size for
intervention outcomes, 95% CI values, assessment of heterogeneity
across studies (Q and I-square statistics), and Egger t test for potential
publication bias. Forest plots for
each outcome are shown in Figures
2 and 3. Forest plots depict the effect
size calculated for each study by outcome as well as the overall effect size
obtained for the outcome across
studies at each time interval. Forest
plots also indicate whether the
effects obtained in each study across
studies favor the control group or
the intervention group. When more
than one form of TE was explicitly
analyzed in the same study, one letter in alphabetical order was
assigned to each of them.
Pain. Nearly all studies (n⫽6/7)
assessed this outcome in the short
term, 5 studies had intermediateterm follow-up, and only 1 study had
long-term follow-up. Because 2 studies had more than one experimental
arm, these RCTs had 9 intervention
protocols to analyze for short-term
effect. There were 7 treatment arms
in the 5 studies that reported
August 2013
Figure 2.
Standardized difference in means and 95% confidence intervals (95% CI) for effect of the therapeutic exercise on pain at short-term
and intermediate-term follow-ups compared with control. Superscript letters a, b, and c represent the different arms of a single study
following the order as reported in Table 1.
intermediate-term follow-up. Only 1
study met our operational definition
of long-term follow-up of pain.
Among the 6 studies30 –35 that
assessed pain during the first month
after the intervention, the overall
effect size of TE was medium and
significant (g⫽⫺0.53), with a range
from ⫺0.86 to ⫺0.20. In the 5 studies31–34,36 that assessed pain between
1 and 6 months after the intervention, the overall effect size of TE was
medium and significant (g⫽⫺0.45),
with a range from ⫺0.82 to ⫺0.07.
Only 1 study34 assessed pain
between 6 and 12 months after the
intervention, and the overall effect
size was very small and not significant (g⫽⫺0.04). A moderate heterogeneity of findings appeared for 2
outcomes: short-term pain30 –35 and
intermediate-term
pain31–34,36
(P⬍.05). A significant and positive
Egger t test appeared for one outAugust 2013
come (ie,
(P⬍.05).
short-term
pain)30 –35
Disability. The majority of studies
(n⫽4/7) assessed this outcome in
the short term, 3 studies had
intermediate-term follow-up, and
only 1 study had long-term followup. For the 4 studies30,31,33,34 that
assessed disability during the first
month after the intervention, the
overall effect size of TE was medium
but not significant (g⫽⫺0.39). In the
3 studies31,33,34 that assessed disability between 1 and 6 months after the
intervention, the overall effect size
was medium but not significant
(g⫽⫺0.46). Only 1 study34 assessed
disability between 6 and 12 months
after the intervention, and the overall effect size was very small and not
significant (g⫽⫺0.14). A high heterogeneity of findings appeared for
2 outcomes: short-term disabil-
ity30,31,33,34 and intermediate-term
disability.31,33,34 No significant and
positive Egger t test was found for
any of the 3 outcomes.30,31,33,34
Discussion
This updated systematic review and
meta-analysis aimed to determine a
more accurate estimate of the effect
of TE on pain and disability outcomes in people with CNSNP. We
found 9 studies28 –36 investigating the
efficacy of TE that met our inclusion
criteria, of which 7 were deemed
appropriate for a meta-analysis. The
most important finding we obtained
by pooling these 7 studies was a
medium and significant overall effect
size for TE in reducing pain in the
short term (⬍1 month) and intermediate term (1– 6 months) and a
medium but not significant overall
effect size in reducing disability in
the short term and intermediate
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1033
Figure 3.
Standardized difference in means and 95% confidence intervals (95% CI) for effect of the therapeutic exercise on disability at
short-term and intermediate-term follow-ups compared with control.
term. It was not possible to calculate
an overall effect size for TE at longterm follow-up (6 –12 months) due
to the lack of studies examining this
endpoint.
From a qualitative point of view, our
results are in line with those presented by most of the literature in
recent years10 –14,37 that has supported the benefit of TE in the management of chronic neck pain. One
of the earliest complete systematic
overviews and meta-analyses on conservative management of mechanical
neck pain, published by Aker et al in
1996,38 only cautiously recommended manual treatments in combination with other treatments,
among which TE would be included.
More recently, Hurwitz and colleagues from the US Bone and Joint
Initiative39 have suggested that therapies involving exercise are more
effective than alternate strategies for
management of neck pain. Our analysis specifically contributes to highlighting the efficacy of TE alone for
the management of CNSNP, particularly given that we found a significant overall effect size supporting
this kind of intervention for reducing
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Volume 93
pain in the short term and intermediate term, which does not appear to
have been reported in the literature.
From a quantitative point of view,
these findings are different from
those obtained by 2 other recent systematic reviews and meta-analyses
on this topic.14,37 Gross et al,37 in
2007, concluded that exercise alone
demonstrated intermediate-term and
long-term benefits in reducing both
pain and disability, whereas Leaver
et al,14 in 2010, found specific exercises able to produce only a significant short-term effect on pain reduction. The discordance between these
2 conclusions was one of the reasons
for undertaking the present study.
Our intent was to extrapolate a more
accurate estimate of the overall
potential efficacy of TE in the management of CNSNP by addressing
some methodological issues that had
not previously been taken into
account (ie, isolating studies dealing
specifically with adults with CNSNP
of at least 3 months’ duration as the
population of interest and specifically TE as the intervention).
Number 8
Study Limitations
The most important limitation of the
present work is the limited number
of available studies that prevented us
from making additional analyses and
resolving other methodological
issues. As a consequence, we were
not able to explain our data heterogeneity by conducting subgroup
analyses or to detect the presence of
some potential mediating factors (eg,
type, duration, intensity, and frequency of training regimens or particular population characteristics).
Another limitation is the quality of
the included studies, which was generally medium to low. The requirements for at least one key outcome
to be obtained from more than 85%
of the participants initially allocated
to groups and for an analysis by
“intention to treat” were typically
never met. The blinding criteria of
the PEDro scale lower the methodological quality of exercise-related
trials even when blinding all patients
and therapists may not be feasible.10,11 Publication bias is another
potential limitation of our review. A
strong publication bias, however, is
unlikely because studies in all lanAugust 2013
guages and for any year of publication were included and authors of
included studies were contacted for
any unpublished date. Furthermore,
although the Egger t test turned out
to be significant for one outcome, it
is known that the meaningfulness of
such a test suffers from the small
number of studies and small samples
and from the heterogeneity and different quality of the studies. Using
only clinical trials may have influenced the potential publication bias,
but also allowed us to derive our
conclusions from higher-quality
studies.
Clinical Implications
Combining data, the results of our
meta-analysis sustain a conclusion in
favor of TE in the management of
pain associated with CNSNP. In particular, based on the overall effect
size of TE as derived from pooled
studies, we found that the use of
exercise programs for reducing pain
in the short term (⬍1 month) and
intermediate term (1– 6 months)
could be supported. It was not possible to evaluate the efficacy of TE at
long-term follow-up (6 –12 months)
due to the lack of studies examining
this endpoint.
Future Research
Future studies are needed to clarify
the efficacy of different forms of TE
and specifically on different subgroups of people with CNSNP who
may have different etiologies or
prognoses that help to explain outcomes.40 The possibility of spontaneous relief of chronic symptoms, as
reported in control groups of several
RCTs,33,34,36 as well as the baseline
presence of negative prognostic factors could greatly change final
results, independently from the real
efficacy of the experimented TE. It
will be imperative, therefore, to
grow the body of evidence in favor
of TE by conducting well-designed
RCTs with higher-quality scores and
to describe more precisely the popAugust 2013
ulation studied and the exercise regimen used. Future studies also
should account for the time required
for tissue adaptations as a result of
TE when determining an appropriate
time frame for follow-up.10,13 Then,
we can begin to understand the
effectiveness of TE for this condition
in routine clinical practice.
Dr Bertozzi, Dr Gardenghi, Dr Villafañe, Dr
Capra, Dr Guccione, and Dr Pillastrini provided concept/idea/research design. Dr Bertozzi, Dr Gardenghi, Dr Turoni, Dr Capra, Dr
Guccione, and Dr Pillastrini provided writing. Dr Gardenghi, Dr Turoni, and Dr Capra
provided data collection. Dr Bertozzi, Dr
Capra, and Dr Guccione provided data analysis. Dr Capra provided project management. Dr Villafañe and Dr Pillastrini provided
consultation (including review of manuscript
before submission).
DOI: 10.2522/ptj.20120412
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provide short-term relief for non-specific
neck pain: a systematic review. J Physiother. 2010;56:73– 85.
15 Philadelphia Panel Evidence-Based Clinical
Practice Guidelines on Selected Rehabilitation Interventions for Neck Pain. Phys
Ther. 2001;81:1701–1717.
16 Merskey H, Bogduk N. Classification of
Chronic Pain: Descriptions of Chronic
Pain Syndromes and Definitions of Pain
Terms. 2nd ed. Seattle, WA: IASP Press;
1994.
17 Juul-Kristensen B, Kadefors R, Hansen K,
et al. Clinical signs and physical function
in neck and upper extremities among
elderly female computer users: the NEW
study. Eur J Appl Physiol. 2006;96:136 –
145.
18 Chow RT, Johnson MI, Lopes-Martins RA,
Bjordal JM. Efficacy of low-level laser therapy in the management of neck pain: a
systematic review and meta-analysis of randomised placebo or active-treatment controlled trials [erratum in: Lancet. 2010;
375:894]. Lancet. 2009;374:1897–1908.
19 Maher CG, Sherrington C, Herbert RD,
et al. Reliability of the PEDro scale for rating quality of randomized controlled trials.
Phys Ther. 2003;83:713–721.
20 de Morton NA. The PEDro scale is a valid
measure of the methodological quality of
clinical trials: a demographic study. Aust J
Physiother. 2009;55:129 –133.
21 DerSimonian R, Laird N. Meta-analysis in
clinical trials. Control Clin Trials. 1986;7:
177–188.
22 Hedges LV, Olkin I. Statistical Methods for
Meta-Analysis. San Diego, CA: Academic
Press; 1985.
23 Comprehensive Meta-Analysis [computer
software]. Version 2. Englewood, NJ: Biostat; 2005.
24 Cohen J. Statistical Power Analysis for
the Behavioral Sciences. 2nd ed. Hillsdale,
NJ: Lawrence Erlbaum Associates; 1988.
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25 Alderson P, Green S. Cochrane Collaboration’s Open Learning Material for
Reviewers: Version 1.1. Oxford, United
Kingdom: The Cochrane Library; 2002.
26 Gavaghan DJ, Moore AR, McQuay HJ. An
evaluation of homogeneity tests in metaanalyses in pain using simulations of individual patient data. Pain. 2000;85:415–
424.
27 Higgins JP, Thompson SG. Quantifying
heterogeneity in a meta-analysis. Stat Med.
2002;21:1539 –1558.
28 Dellve L, Ahlstrom L, Jonsson A, et al.
Myofeedback training and intensive muscular strength training to decrease pain
and improve work ability among female
workers on long-term sick leave with neck
pain: a randomized controlled trial. Int
Arch Occup Environ Health. 2011;84:
335–346.
29 Häkkinen A, Kautiainen H, Hannonen P,
Ylinen J. Strength training and stretching
versus stretching only in the treatment of
patients with chronic neck pain: a randomized one-year follow-up study. Clin
Rehabil. 2008;22:592– 600.
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30 Beer A, Treleaven J, Jull G. Can a functional postural exercise improve performance in the cranio-cervical flexion test: a
preliminary study. Man Ther. 2012;17:
219 –224.
31 Ma C, Szeto GP, Yan T, et al. Comparing
biofeedback with active exercise and passive treatment for the management of
work-related neck and shoulder pain: a
randomized controlled trial. Arch Phys
Med Rehabil. 2011;92:849 – 858.
32 Andersen LL, Kjaer M, Søgaard K, et al.
Effect of two contrasting types of physical
exercise on chronic neck muscle pain.
Arthritis Rheum. 2008;59:84 –91.
33 Chiu TT, Lam TH, Hedley AJ. A randomized controlled trial on the efficacy of
exercise for patients with chronic neck
pain. Spine (Phila Pa 1976). 2005;30:E1–
E7.
34 Viljanen M, Malmivaara A, Uitti J, et al.
Effectiveness of dynamic muscle training,
relaxation training, or ordinary activity for
chronic neck pain: randomised controlled
trial. BMJ. 2003;327:475.
35 Ahlgren C, Waling K, Kadi F, et al. Effects
on physical performance and pain from
three dynamic training programs for
women with work-related trapezius myalgia. J Rehabil Med. 2001;33:162–169.
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36 Lundblad I, Elert J, Gerdle B. Randomized
controlled trial of physiotherapy and
Feldenkrais interventions in female workers with neck-shoulder complaints. J
Occup Rehabil. 1999;9:179 –194.
37 Gross AR, Goldsmith C, Hoving JL, et al.
Conservative management of mechanical
neck disorders: a systematic review.
J Rheumatol. 2007;34:1083–1102.
38 Aker PD, Gross AR, Goldsmith CH, Peloso
P. Conservative management of mechanical neck pain: systematic overview and
meta-analysis. BMJ. 1996;313:1291–1296.
39 Hurwitz EL, Carragee EJ, van der Velde G,
et al. Treatment of neck pain—noninvasive interventions: results of the Bone and
Joint Decade 2000 –2010 task force on
neck pain and its associated disorders.
Spine (Phila Pa 1976). 2008;33(4 suppl):
S123–S152.
40 Fritz JM, Brennan GP. Preliminary examination of a proposed treatment-based classification system for patients receiving
physical therapy interventions for neck
pain. Phys Ther. 2007;87:513–524.
August 2013
Research Report
Longitudinal Change in Physical
Activity and Its Correlates in
Relapsing-Remitting Multiple Sclerosis
Robert W. Motl, Edward McAuley, Brian M. Sandroff
Background. Physical activity is beneficial for people with multiple sclerosis
(MS), but this population is largely inactive. There is minimal information on change
in physical activity and its correlates for informing the development of behavioral
interventions.
Objective. This study examined change in physical activity and its symptomatic,
social-cognitive, and ambulatory or disability correlates over a 2.5-year period of time
in people with relapsing-remitting multiple sclerosis.
Methods. On 6 occasions, each separated by 6 months, people (N⫽269) with
relapsing-remitting multiple sclerosis completed assessments of symptoms, selfefficacy, walking impairment, disability, and physical activity. The participants wore
an accelerometer for 7 days. The change in study variables over 6 time points was
examined with unconditional latent growth curve modeling. The association among
changes in study variables over time was examined using conditional latent growth
curve modeling, and the associations were expressed as standardized path coefficients (␤).
Results. There were significant linear changes in self-reported and objectively
measured physical activity, self-efficacy, walking impairment, and disability over the
2.5-year period; there were no changes in fatigue, depression, and pain. The changes
in self-reported and objective physical activity were associated with change in
self-efficacy (␤⫽.49 and ␤⫽.61, respectively), after controlling for other variables and
confounders.
R.W. Motl, PhD, Department of
Kinesiology
and
Community
Health, University of Illinois at
Urbana-Champaign, 233 Freer
Hall, Urbana, IL 61801 (USA).
Address all correspondence to Dr
Motl at: [email protected].
E. McAuley, PhD, Department of
Kinesiology
and
Community
Urbana-Champaign.
B.M. Sandroff, MS, Department of
Kinesiology
and
Community
Urbana-Champaign.
[Motl RW, McAuley E, Sandroff
BM. Longitudinal change in physical activity and its correlates in
relapsing-remitting multiple sclerosis. Phys Ther. 2013;93:1037–
1048.]
Association
April 18, 2013
Submitted: November 29, 2012
Limitations. The primary limitations of the study were the generalizability of
results among those with progressive multiple sclerosis and inclusion of a single
variable from social-cognitive theory.
Conclusions. Researchers should consider designing interventions that target selfefficacy for the promotion and maintenance of physical activity in this population.
this article at:
ptjournal.apta.org
August 2013
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Change in Physical Activity in People With Relapsing-Remitting Multiple Sclerosis
M
ultiple sclerosis (MS) is a
common, nontraumatic, and
chronic disabling disease of
the central nervous system (CNS).1
This disease is typically characterized by intermittent and recurrent
periods of inflammatory demyelination and transection of axons in the
CNS.2,3 Such a presentation is consistent with the relapsing-remitting
clinical course of MS (RRMS) that is
initially diagnosed in the majority of
cases and described by episodes of
symptom worsening followed by
varying degrees of recovery and stability.4 The axonal damage results in
conduction delay and conduction
block of action potentials along CNS
pathways and manifests as symptoms (eg, fatigue, depression, pain),
mobility impairment, and disability.5
Such manifestations present significant barriers for physical activity6
and appear to be associated with
prevalent inactivity in this population.7,8 Importantly, there is increasing evidence for the importance of
physical activity in MS,9 but beneficial outcomes are contingent on participating in this behavior.
The design and success of programs
for increasing physical activity in
people with MS depend, in part, on
the identification of correlates of
physical activity that can become targets of behavioral and selfmanagement interventions. Such
correlates ideally should be variables
that are modifiable, on the basis of
theory, and consistently associated
with physical activity. Researchers
often have focused on identifying
symptoms as correlates of physical
Available With
This Article at
ptjournal.apta.org
• Discussion Podcast with Anne
Jacobson and author Robert
Motl. Moderated by Kathleen
Gill-Body.
1038
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Volume 93
activity among people with MS. This
focus is because symptoms are a hallmark manifestation of MS5 that can
have a profound influence on performance and behavioral outcomes,
including physical activity, on the
basis of reality and the Theory of
Unpleasant Symptoms.10 Symptoms
can further provide a barrier for
physical activity by influencing
social-cognitive variables such as
self-efficacy.11 To date, research has
indicated that the symptoms of
fatigue, depression, and pain are
associated with physical activity in
people with MS.12 Research has further indicated that such associations
might
operate
through
selfefficacy13,14 and walking impairment15 and are independent of a person’s disability status.16
The primary limitation of that previous research has been the reliance
on a cross-sectional research design.
Such a design only permits an inference regarding associations among
changes in focal variables over
time.17 To date, there is limited
research on longitudinal changes in
physical activity and associated correlates in MS, yet adopting a longitudinal design is important for several
reasons and represents the novel
focus of the current research. First,
longitudinal designs are necessary
for conclusions about relationships
involving actual changes in correlates and physical activity over
time.18 Second, correlates in crosssectional data often are more
strongly related to physical activity
than in longitudinal designs, and frequently cross-sectional correlations
do not replicate in longitudinal applications.19 Third, longitudinal designs
allow for developing better informed
and targeted interventions for changing physical activity.20 Accordingly,
studies that examine changes in
physical activity and associations
with changes in correlates over time
are warranted in people with MS.
Number 8
The current research project
adopted a longitudinal research
design and examined changes in
symptoms, self-efficacy, walking
impairment, disability status, and
physical activity over a 2.5-year
period of time in people with RRMS.
We initially examined the trajectory
of change in each of the variables,
particularly self-reported and objectively measured physical activity,
and then examined associations
among the changes in correlates and
physical activity, controlling for possible confounding variables. We
expected a linear reduction in physical activity over time and that worsening of symptomatic fatigue,
depression, pain, self-efficacy, or
walking impairment would predict
the reduction of physical activity
over time. We further controlled for
possible changes in disability status
over time as well as other confounding variables of age, sex, and disease
duration. If successful, this research
would inform the subsequent development of an intervention that targets the identified correlates for possibly promoting change in physical
activity among people with RRMS.
Method
Sample
The data are the primary outcome
variables from a recently completed,
longitudinal investigation of symptoms and physical activity over 2.5
years in people with RRMS. The sample was recruited through a research
advertisement posted on the
National MS Society (NMSS) website
and distributed through 12 midwestern chapters of the NMSS. Those
who were interested in the study
contacted the research team by
either e-mail or a toll-free telephone
call. This contact was followed by a
scripted conversation with the project coordinator, who described the
study procedures and undertook
screening for inclusion criteria. The
inclusion criteria were: (1) diagnosis
of RRMS confirmed by a physician,
August 2013
(2) relapse-free in the previous 30
days, (3) ambulatory with or without
assistance (ie, walk independently or
walk with a cane or crutch or walker
or rollator), and (4) willingness to
complete the study materials every 6
months over 2.5 years. Those who
did not satisfy the inclusion criteria
were excluded from participation.
We successfully contacted 375 of the
463 people who expressed interest
in the study, and 6 were uninterested
in participation after the description
of the study procedures. The remaining 369 people underwent screening, 44 did not satisfy the inclusion
criteria, and 5 declined voluntary
participation. We sent an informed
consent document (completed by
the participant) and RRMS verification form (completed by the participant’s treating physician) to the
remaining 320 people, and 41 did
not return the documents despite 3
attempts for follow-up contact. We
sent study materials to the remaining
279 people, and 10 subsequently
declined further participation; this
distribution of materials occurred in
12 waves of about 25 participants
per wave beginning in March of
2008 (wave 1) and ending in February of 2009 (wave 12). There were
269 people with RRMS who provided baseline data. Of the initial 269
people, there were 258, 253, 245,
244, and 238 who provided
follow-up data 6, 12, 18, 24, and 30
months later (ie, 88%–96% of the initial sample). This attrition involved
either a change in the participant’s
residential address or loss of materials through the US Postal Service.
The baseline sample consisted of 223
women and 46 men. The participants were mostly Caucasian (91%),
well educated (83% had some college education or were college graduates), and reported a median household income that exceeded $40,000/
year (68%). The mean age was 45.9
years (standard deviation [SD]⫽9.6),
and the mean MS disease duration
August 2013
was 8.8 years (SD⫽7.0). The median
Patient Determined Disease Steps
(PDDS) Scale score was 2 (interquartile range⫽3.0), and the mean
12-item Multiple Sclerosis Walking
Scale (MSWS-12) score was 36.0
(SD⫽28.2). Those scores indicated
that the sample, on average, had minimal walking impairment.21,22 There
were 223 people who reported
being treated with a diseasemodifying therapy; interferon ␤-1a
(50%), glatiramer acetate (31%), and
interferon ␤-1b (13%) represented
the most common types of therapy.
All 269 participants had a diagnosis
of RRMS.
Power Analyses
The target sample size of 250 was
based on a series of power analyses
undertaken with the use of the
Monte Carlo study feature in
Mplus.23 We specified a latent
growth curve model (LGM) with 6
time points, set the reliability of the
6 indicators to 0.90, used values
from pilot data for the mean and
standard deviation of the initial status factor, specified the correlation
between the growth factors to be
0.1, and selected the standard deviation of the slope factor such that 95%
of the units would change within
⫾20% of average initial status (ie, 2
standard deviations). The mean
parameter of the slope factor was set
to 5% of the standard deviation of the
indicator of the first time point,
which represents an average 5% of a
standard deviation change within 1
time interval. We used sample sizes
of 100, 150, 200, and 250 individuals
with 500 replications, and the percentage of replications was recorded
where the mean parameter of the
slope factor was statistically significant. The power for detecting a
small, linear decline in physical activity over time was 62.2%, 83.0%,
92.4%, and 95.6% for sample sizes of
100, 150, 200, and 250, respectively.
We then conducted a power analysis
for detecting a small, linear increase
in symptoms across time, and the
power for the mean parameter of the
slope factor was 53.0%, 72.8%,
We finally conducted a third power
study for a model with 2 parallel
growth processes23 representing the
relationship between changes in
symptoms and physical activity over
time. This model had 2 initial status
factors (1 for symptoms and 1 for
physical activity), 2 slope factors (1
for symptoms and 1 for physical
activity), and 2 path coefficients (1
between initial status factors and 1
between change factors). The path
coefficients explained the correlations among initial status and growth
factors. The parameters for each
growth process were established
identically as in the first 2 power
studies, and the values for the 2 standardized path coefficients were 0.3.
The minimal power for the path
coefficients was 61.4%, 78.0%,
Measures
Physical activity. Physical activity
was measured using ActiGraph
model 7164 accelerometers (ActiGraph, Pensacola, Florida), and the
short form of the International Physical Activity Questionnaire (IPAQ).24
Researchers have provided evidence
for the validity of scores from these
measures in people with MS,8,25 and
the inclusion of 2 different measures
allowed for examining the possible
differential correlates of change in
self-reported and objectively measured physical activity. The ActiGraph model 7164 accelerometers
were worn on an elastic belt around
the waist above the nondominant
hip during the waking hours, except
while showering, bathing, and swimming, for a 7-day period. Waking
hours was defined as the moment on
getting out of bed in the morning
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through the moment of getting into
bed in the evening. The participants
recorded the time that the accelerometer was worn on a log, and this
time was verified by inspection of
the minute-by-minute accelerometer
data. Regarding data processing, we
checked the validity of each day’s
data (10 or more hours of wear time
without periods of 60 minutes of
continuous zeros) and then summed
the minute-by-minute movement
counts across each of the valid days
and averaged the total daily movement counts across the valid days.
This process yielded accelerometer
data in total movement counts per
day, with higher scores representing
more physical activity. The lower
bound of scores was 0, and the
upper bound of scores was undefined.
Importantly,
movement
counts are different from step
counts. Step counts reflect a binary
event recorded for each footstep or
occurrence of a foot strike during
ambulation, whereas movement
counts reflect the magnitude or
intensity of the binary event
recorded for each footstep (ie, the
amount of acceleration of the body’s
center of mass per foot strike during
ambulatory physical activity). By
extension, movement counts as
recorded and expressed in this study
reflect the amount of ambulatory
physical activity accumulated over
the course of the day.
The short-form of the IPAQ was
designed for population surveillance
of physical activity among adults and
has 6 items that measure the frequency and duration of vigorousintensity
activities,
moderateintensity activities, and walking
during a 7-day period. We did not
include the duration component in
this study on the basis of previous
research that identified problems
with accurate recall of activity duration in people with MS.25 The
respective frequency values for vig-
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orous, moderate, and walking activities were multiplied by 8, 4, and 3.3
metabolic equivalents and then
summed to form a continuous measure of physical activity. The scores
ranged between 0 and 107.
Symptoms. Fatigue was measured
with the Fatigue Severity Scale
(FSS).26 The FSS has 9 items that
were rated on a 7-point scale that
ranged between 1 (strongly disagree) and 7 (strongly agree). The
item scores were averaged to form
an overall measure of a participant’s
severity of fatigue symptoms during
the past 4 weeks, and FSS scores
ranged between 1 and 7. Higher
scores reflect more severe symptoms
of fatigue. The FSS has good evidence of internal consistency, testretest reliability, and score validity.26
Pain was measured with the shortform McGill Pain Questionnaire
(SF-MPQ).27 This scale has a 15-item
adjective checklist that captures sensory and affective dimensions of pain
experienced during the past 4
weeks. The items were rated on a
4-point scale that ranged between 0
(none) and 3 (severe). The items
were summed to form a composite
that ranged between 0 and 45.
Higher scores reflect more severe
pain. The SF-MPQ is internally consistent, reliable across time, and has
evidence of score validity.27
Depressive symptoms were measured by the Hospital Anxiety and
Depression Scale (HADS).28 The
HADS has 14 items: 7 items measure
anxiety and 7 items measure depression. The items were rated on a
4-point scale that ranged between 0
(most of the time) and 3 (not at all).
We did not include the 7 items for
anxiety because we were only focusing on depressive symptoms as a specific correlate of physical activity.
The negatively worded items were
reverse-scored, and scores from the
7 items were summed for a compos-
Number 8
ite score of the frequency of depressive symptoms during the previous 4
weeks. The scores ranged between 0
and 21, and higher scores reflect a
greater frequency of depressive
symptoms. This scale has good evidence of score reliability and
validity.28
Self-efficacy. Self-efficacy
was
assessed by the Exercise Self-Efficacy
Scale (EXSE).29 The EXSE scale has 6
items that assess a person’s beliefs
relative to engaging in 20⫹ minutes
of moderate physical activity 3 times
per week, in 1-month increments,
across the next 6 months. The items
were rated on a scale from 0 (not at
all confident) to 100 (completely
confident) and averaged into a composite score that ranges between 0
and 100. Higher scores reflect
greater confidence in a person’s ability to engage in regular physical
activity over time. This scale is internally consistent and has evidence of
score validity,29 and it has been
included in previous research on
physical activity in MS.30
Walking
impairment. The
MSWS-12 is a 12-item patient-rated
measure of the impact of MS on
walking.21 The items are rated on a
5-point scale from 1 (not at all) to 5
(extremely), and the items represent
limitations of walking during the previous 2 weeks. The MSWS-12 is
scored by summing the 12 item
scores, subtracting 12, dividing the
difference by 48, and then multiplying by 100. This method of scoring
scales the MSWS-12 score between 0
and 100. The MSWS-12 has good evidence for its internal consistency,
test-retest reliability, and validity of
scores as a measure of walking
impairment in MS.21
Disability status. Disability status
was measured with the use of the
PDDS Scale.22 The PDDS Scale is a
self-report questionnaire for measuring neurological impairment with
August 2013
the use of an ordinal scale of 0 (normal) through 8 (bedridden). This
scale was developed as an inexpensive surrogate for the Expanded Disability Status Scale (EDSS), and
scores from the PDDS Scale have
been reported to be linearly and
strongly related to physicianadministered EDSS scores (r⫽.93).22
This scale was included rather than
the EDSS because the data were collected entirely through the US Postal
Service.
Procedure
After initial telephone contact,
screening for inclusion, and return of
informed consent and MS verification documentation, participants
were sent an accelerometer and battery of questionnaires through the
US Postal Service. We further provided prestamped and preaddressed
envelopes for return postal service.
The project coordinator called to
make sure the participants received
the materials and understood the
instructions. The participants then
completed the battery of questionnaires that included measures of
symptoms, self-efficacy, walking
impairment, disability status, and
physical activity and wore the accelerometer for 7 days. After completing the measures and wearing the
accelerometer, participants returned
the study materials through the US
Postal Service. We contacted participants by telephone and e-mail up to
3 times as a reminder to return the
study materials. We further collected
any missing questionnaire data on
the basis of follow-up telephone
calls. This same procedure was completed every 6 months over a 2.5year period of time. All participants
received $120 remuneration, which
was prorated to be $20 per completion and return of the study
materials.
Data Analysis
The data were analyzed with LGM
with the use of the full-information
August 2013
maximum likelihood (FIML) estimator and the Mplus software package.23 The LGM is a powerful
approach for studying the pattern,
predictors, and consequences of longitudinal change processes.18 This
approach has a number of advantages over other more commonly
adopted approaches used to study
change among continuous variables
(eg, analysis of variance, multivariate
analysis of variance, lagged regression, use of change scores), including the ability to: (1) model change
at the individual as well as the grouplevel of analysis, (2) model individual
differences in change trajectories
(initial status and slope factors), (3)
model change in several focal variables concomitantly, and (4) directly
model important predictors and outcomes of longitudinal change.18
Good model-data fit in the LGM analyses was established on the basis of a
comparative fit index (CFI) of ⱖ.95
and standardized root mean residual
(SRMR) of ⱕ.08.31
with parallel growth processes
included the standard linear LGM
(eg, establishing the pattern or trajectory of change in symptoms and
physical activity over time) and the
addition of path coefficients
between initial status and rate of
change. The path coefficients are
interpreted, for example, as a crosssectional
relationship
between
symptoms and physical activity (initial status) as well as a longitudinal
relationship between changes in
symptoms and physical activity over
time (rate of change). One final set of
LGM analyses involved examining
the association between changes in
variables after accounting for possible confounding variables of disability status and age, sex, and disease
duration. We interpreted the magnitude of the path coefficients as standardized estimates (ie, standardized
on a scale of ⫾1.0) through the use
of the guidelines of .1, .3, and .5 for
small, moderate, and large coefficients, respectively.32
We initially examined linear changes
in the study variables, particularly a
reduction in physical activity,
through the use of standard linear
LGM. This examination involved testing a fixed, linear time series (0, 1, 2,
3, 4, 5, 6) for establishing initial status and rate of change in all variables
measured over the 30-month time
period. When the rate of change was
statistically significant, we estimated
the magnitude of change over the
entire 30-month period on the basis
of Cohen d (absolute difference in 0and 30-month mean scores divided
by baseline standard deviation) and
guidelines of 0.2, 0.5, and 0.8 for
small, moderate, and large effects,
respectively.32
Role of the Funding Source
This investigation was supported by
a grant from the National Multiple
Sclerosis Society (RG 3926A2/1).
We then examined associations
among changes in symptoms, selfefficacy, and walking impairment
with changes in physical activity
through the use of LGM with parallel
growth processes.18,23 The LGM
Results
Standard Latent Growth Curve
Modeling: Establishing Changes
in Variables
The model-data fit indexes and
parameter estimates from the standard linear LGM analyses on all 8
variables are provided in Table 1.
The mean scores and standard errors
for all of the variables are provided in
Table 2, and, importantly, the mean
value for accelerometer counts is
consistent with previous samples of
MS.16,30,33 The 64 ⫻ 64 matrix of
correlations among scores from the
8 variables over 6 time points can be
obtained by contacting the corresponding author.
Physical
activity. The
linear
model had a good fit for the acceler-
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Physical Therapy f
1041
Table 1.
Model Fit Indexes and Parameter Estimates From the Latent Growth Curve Modeling Analysis of Linear Change in the Study
Variables Across 6 Time Points in 269 People With Multiple Sclerosisa
Model Fit Indexes
␹2
Variable
df
P
Model Parameters
CFI
SRMR
Mi
Ms
Vi
⫺3,508
b
b
Vs
r
b
⫺.34b
345.43b
10.16b
⫺.40b
b
b
⫺.16
Accelerometer
63.35
16
.001
.96
.07
208,269
IPAQ
14.93
16
.53
1.00
.03
34.02b
b
0.01
⫺0.13
56.98b
0.43b
⫺.04
b
b
⫺.13
FSS
31.86
16
.10
.99
.05
4.77
SF-MPQ
38.00
16
.001
.99
.06
9.75b
b
⫺0.64b
84,299
b
2.24
1,074
0.04
HADS
28.82
16
.03
.99
.04
7.03
0.01
6.29
EXSE
22.87
16
.12
.99
.03
72.01b
⫺0.76b
82.48b
0.14b
b
b
b
b
.06
0.03b
⫺.11
MSWS-12
27.49
16
.04
.99
.03
PDDS
28.19
16
.03
.99
.03
35.98
0.45
1.99b
0.05b
712.14
2.19b
0.11
8.69
⫺.27b
a
IPAQ⫽International Physical Activity Questionnaire; FSS⫽Fatigue Severity Scale; SF-MPQ⫽Short-Form McGill Pain Questionnaire; HADS⫽Hospital Anxiety
and Depression Scale, depression subscale; EXSE⫽Exercise Self-efficacy Scale; MSWS-12⫽12-item Multiple Sclerosis Walking Scale; PDDS⫽PatientDetermined Disease Steps scale; CFI⫽Confirmatory Fit Index; SRMR⫽standardized root mean residual; Mi⫽mean intercept; Ms⫽mean slope, Vi⫽variance of
initial status; Vs⫽variance of slope; r⫽correlation between initial status and slope factors.
b
Statistically significant parameter estimate.
ometer data. Initial status was significantly
different
from
zero
(P⬍.0001), and there was a significant, linear decrease in accelerometer counts over time (P⬍.001). The
effect size for the 30-month change
(d⫽0.17) was small in magnitude.
There was significant variance
around initial status (P⬍.0001) and
group mean change (P⬍.001). This
finding indicates the presence of
variability in the trajectory of change
in accelerometer counts over time
that can be explained by other vari-
ables. The slope and intercept were
significantly (P⫽.005) and negatively
correlated. This finding indicates
that people with higher initial accelerometer counts had less of a reduction in accelerometer counts over
the 30-month period.
The linear model similarly had a
good fit for the IPAQ data. Initial
status was significantly different
from zero (P⬍.0001), and there was
a significant, linear decrease in IPAQ
scores over time (P⬍.05). The effect
size for the 30-month change
(d⫽0.16) was small in magnitude.
There was significant variance
around initial status (P⬍.0001) and
group mean change (P⬍.001). This
finding indicates that there was variability in the trajectory of change in
IPAQ scores over time that can be
explained by other variables. The
slope and intercept were significantly (P⫽.001) and negatively correlated. This finding indicates that
people with higher initial IPAQ
scores had less of a reduction in
Table 2.
Descriptive Statistics for Each Variable Included in the Latent Growth Curve Modeling Analysis Across 6 Time Points in 269
People With Multiple Sclerosisa
Time (mo)
Variable
0
6
12
18
24
30
Accelerometer (0–infinity)b
210,607 (595.7)
202,299 (620.9)
202,116 (648.1)
196,895 (575.5)
193,843 (580.9)
194,401 (615.2)
34.6 (1.43)
33.1 (1.34)
32.0 (1.39)
32.0 (1.36)
31.8 (1.43)
30.9 (1.37)
IPAQ (0–117)b
FSS (1–7)
4.77 (0.10)
4.78 (0.10)
4.74 (0.10)
4.84 (0.10)
4.77 (0.10)
4.80 (0.11)
SF-MPQ (0–45)
9.88 (0.51)
9.54 (0.52)
9.56 (0.52)
9.37 (0.55)
8.88 (0.48)
9.27 (0.54)
HADS (0–21)
7.00 (0.17)
7.08 (0.18)
7.10 (0.19)
7.11 (0.19)
6.86 (0.18)
7.19 (0.20)
EXSE (0–100)
b
MSWS-12 (0–100)b
PDDS (0–8)b
72.6 (2.00)
68.9 (2.03)
71.4 (2.02)
71.5 (2.04)
69.2 (2.00)
67.5 (2.10)
36.03 (1.72)
35.91 (1.74)
36.87 (1.83)
38.00 (1.82)
37.54 (1.93)
38.23 (1.95)
1.95 (0.10)
2.06 (0.10)
2.09 (0.11)
2.18 (0.10)
2.20 (0.11)
2.21 (0.11)
a
Values are mean score (standard error of the mean). IPAQ⫽International Physical Activity Questionnaire; FSS⫽Fatigue Severity Scale; SF-MPQ⫽Short-Form
McGill Pain Questionnaire; HADS⫽Hospital Anxiety and Depression Scale, depression subscale; EXSE⫽Exercise Self-efficacy Scale; MSWS-12⫽12-item
Multiple Sclerosis Walking Scale; PDDS⫽Patient-Determined Disease Steps scale.
b
Statistically significant linear change over time on the basis of latent growth curve modeling.
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Table 3.
Model Fit Indexes and Parameter Estimates From the Parallel Process Latent Growth Curve Modeling Analysis Examining
Correlates of Change in Objectively Measured Physical Activity Among 269 People With Multiple Sclerosisa
Model
Parameters
Model Fit Indexes
␹2
df
P
CFI
SRMR
␤i
␤s
EXSE
125.51
66
.0001
.98
.05
.37b
.50b
MSWS-12
141.68
66
.0001
.98
.05
⫺.48b
⫺.19
PDDS
127.81
66
.0001
.98
.05
⫺.48b
⫺.22
Correlate
a
EXSE⫽Exercise Self-efficacy Scale; MSWS-12⫽12-item Multiple Sclerosis Walking Scale; PDDS⫽Patient-Determined Disease Steps scale; CFI⫽Confirmatory
Fit Index; SRMR⫽standardized root mean residual; ␤i⫽standardized path coefficient between initial status factors; ␤s⫽standardized path coefficient between
linear change factors.
b
IPAQ scores over the 30-month
period.
Symptoms. The linear model had
a good fit for the FSS data. Initial
status was significantly different
from zero (P⬍.0001), but there was
not a significant, linear change over
time (P⫽.70). There was significant
variance around initial status
(P⬍.0001) and group mean change
(P⬍.001). The slope and intercept
were not significantly correlated
(P⫽.10).
The linear model had a good fit for
the SF-MPQ data. Initial status was
significantly different from zero
(P⬍.0001), but there was not a significant, linear change over time
(P⫽.06). There was significant variance around initial status (P⬍.0001)
and group mean change (P⬍.001).
The slope and intercept were not
significantly correlated (P⫽.76).
the HADS data. Initial status was significantly different from zero
(P⬍.0001), but there was not a significant, linear change over time
(P⫽.80). There was again significant
variance around initial status
(P⫽.27).
August 2013
Other variables. The linear model
had a good fit for the EXSE data.
Initial status was significantly different from zero (P⬍.0001), and there
was a significant, linear decrease
over time (P⬍.05). The effect size
for the 30-month change (d⫽0.16)
was small in magnitude. There was
significant variance around initial status (P⬍.0001) and group mean
change (P⬍.001). The slope and
intercept were significantly (P⬍.01)
and negatively correlated, indicating
that people with higher initial EXSE
scores had less of a reduction in
EXSE scores over the 30-month
period.
the MSWS-12 data. Initial status was
significantly different from zero
(P⬍.0001), and there was a significant, linear increase over time
(P⬍.05). The effect size for the
30-month change (d⫽0.08) was very
small in magnitude. There was significant variance around initial status
(P⫽.49).
the PDDS data. Initial status was significantly different from zero
(P⬍.0001), and there was a significant, linear increase over time
(P⬍.001). The effect size for the
30-month change (d⫽0.15) was
small in magnitude. There was significant variance around initial status
(P⫽.25).
Summary. There were linear
changes in physical activity (accelerometer and IPAQ), self-efficacy
(EXSE), walking impairment (MSWS12), and disability (PDDS Scale) over
time. There were not significant linear changes in symptoms (FSS,
SF-MPQ, or HADS) over time. The
next set of analyses, therefore, examined changes in self-efficacy, walking
impairment, and disability (EXSE,
MSWS-12, and PDDS Scale) as correlates of change in physical activity
(accelerometer and IPAQ) over time;
these variables demonstrated change
and became the focus for understanding the reduction in physical
activity.
Parallel Process Latent Growth
Curve Modeling: Correlates of
Change in Physical Activity
Accelerometer outcome. We initially conducted analyses of associations between changes in EXSE,
MSWS-12, PDDS Scale, and accelerometer data. The model-data fit
indexes and parameter estimates
from the parallel process LGM analyses for examining correlates of
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1043
Table 4.
Model Fit Indexes and Parameter Estimates From the Parallel Process Latent Growth Curve Modeling Analysis Examining
Correlates of Change in Self-Reported Physical Activity Among 269 People With Multiple Sclerosisa
Model
Parameters
Model Fit Indexes
␹2
df
P
CFI
SRMR
␤i
␤s
EXSE
110.86
66
.0001
.98
.04
.36b
.60b
MSWS-12
139.04
66
.0001
.98
.04
⫺.39b
⫺.29b
.04
⫺.36
⫺.28b
Correlate
PDDS
114.84
66
.0001
.98
b
a
EXSE⫽Exercise Self-efficacy Scale; MSWS-12⫽12-item Multiple Sclerosis Walking Scale; PDDS⫽Patient-Determined Disease Steps scale; CFI⫽Confirmatory
Fit Index; SRMR⫽standardized root mean residual; ␤i⫽standardized path coefficient between initial status factors; ␤s⫽standardized path coefficient between
linear change factors.
b
change in accelerometer data are
provided in Table 3. The first model
examined the association between
changes in EXSE scores and accelerometer data over time and had a
good fit to the data. There were significant associations between initial
status for EXSE and accelerometer
data (P⬍.0001) and between the linear changes in EXSE and accelerometer data over time (P⬍.0001). The
latter association indicated that a
1-standard deviation unit change in
EXSE scores was associated with a
0.50-standard deviation unit change
in accelerometer counts over time.
The change in EXSE scores
explained 25% of variance in accelerometer changes over time. The
second model examined the association between changes in MSWS-12
scores and accelerometer data over
time. This model had a good fit to the
data. There was a significant association between initial status for
MSWS-12 and accelerometer data
(P⬍.0001) but not between the linear changes in MSWS-12 and accelerometer data (P⫽.10). The third
model examined the association
between changes in PDDS Scale
scores and accelerometer data over
time and had a good fit to the data.
There was a significant association
between initial status for PDDS Scale
and accelerometer data (P⬍.0001)
but not between the linear changes
in PDDS Scale and accelerometer
data (P⫽.07). The last model exam1044
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ined the association between
changes in EXSE scores and accelerometer data over time controlling
for age, sex, disease duration,
and baseline PDDS Scale and
MSWS-12 scores. The model had a
good fit to the data: ␹2 (df⫽107,
N⫽269)⫽196.31, P⬍.0001, CFI⫽.97,
SRMR⫽.04. The association between
the linear changes in EXSE and accelerometer data over time was statistically significant, nearly large in magnitude, and unchanged after
accounting for those additional variables (standardized path coefficient⫽.49, P⬍.005).
IPAQ. Finally, we conducted analyses of associations between
changes in EXSE, MSWS-12, PDDS
Scale, and IPAQ scores. The modeldata fit indexes and parameter estimates from the parallel process LGM
analyses for examining correlates of
change in IPAQ data are provided in
Table 4. The first model examined
EXSE and IPAQ scores over time and
had a good fit to the data. There
were
significant
associations
between initial status for EXSE and
IPAQ scores (P⬍.0001) and between
the linear changes in EXSE and IPAQ
scores over time (P⬍.0001). The
later association indicated that a
1-standard deviation unit change in
EXSE scores was associated with a
in IPAQ scores over time. The
Number 8
change in EXSE scores explained
36% of variance in IPAQ scores over
time. The second model examined
MSWS-12 and IPAQ scores over time
and had a good fit to the data. There
were
significant
associations
between initial status for MSWS-12
and IPAQ scores (P⬍.0001) and
between the linear changes in
MSWS-12 and IPAQ scores (P⬍.005).
The latter association indicated that
a 1-standard deviation unit change in
MSWS-12 scores was associated with
a 0.29-standard deviation unit
change in IPAQ scores over time.
The change in MSWS-12 scores
explained 8% of variance in IPAQ
scores over time. The third model
examined the association between
changes in PDDS and IPAQ scores
over time. This model had a good fit
to the data. There was a significant
association between initial status for
PDDS and IPAQ scores (P⬍.0001).
There was a significant association
between the linear changes in PDDS
and IPAQ scores over time (P⬍.01).
The latter association indicated that
a 1-standard deviation unit change in
PDDS scores was associated with a
in IPAQ scores over time. The
change in PDDS scores explained 8%
of variance in IPAQ scores over time.
The last 3 models examined the association between changes in EXSE
and IPAQ scores controlling for
August 2013
changes in MSWS-12 scores, PDDS
Scale scores, and then age, sex, disease duration, and baseline PDDS
Scale and MSWS-12 scores. The
model controlling for changes in
MSWS-12 scores had a good fit to the
data: ␹2 (df⫽148, N⫽269)⫽292.57,
P⬍.0001, CFI⫽.97, SRMR⫽.04.
There still was a significant association between the linear changes in
EXSE and IPAQ scores (standardized
path coefficient⫽.53, P⬍.005);
there was not a significant association between the linear changes in
MSWS-12 and IPAQ scores (standardized path coefficient⫽⫺.07, P⫽.61)
in this model. The model controlling
for changes in PDDS scores had a
good fit to the data: ␹2 (df⫽148,
N⫽269)⫽247.72, P⬍.0001, CFI⫽.98,
SRMR⫽.04. There still was a significant association between the linear
changes in EXSE and IPAQ scores
over time (standardized path coefficient⫽.52, P⬍.005); there was not a
significant association between the
linear changes in PDDS and IPAQ
scores (standardized path coefficient⫽⫺.13, P⫽.31) in this model.
The final model controlling for confounders had a good fit to the data,
␹2
(df⫽148,
N⫽269)⫽156.65,
P⬍.001, CFI⫽.98, SRMR⫽.04. There
still was a statistically significant and
strong association between the linear changes in EXSE and IPAQ scores
(standardized path coefficient⫽.61,
P⬍.005).
Summary. The linear change in
accelerometer counts was associated
with change in self-efficacy (EXSE)
but not changes in disability (PDDS
Scale) and walking impairment
(MSWS-12), and this was unchanged
when controlling for confounders.
The linear change in IPAQ scores
was associated with changes in selfefficacy (EXSE), disability (PDDS
Scale), and walking impairment
(MSWS-12), but the association
between changes in IPAQ and selfefficacy was not accounted for by
changes in disability (PDDS Scale) or
August 2013
walking impairment (MSWS-12) or
when controlling for confounders.
Discussion
This study documented a significant
linear reduction of physical activity
over a 2.5-year period of time in people with MS. To our knowledge, this
is the first study that documents such
a change, as 3 previous studies of
people with MS demonstrated no significant change in physical activity
over time.34 –36 For example, one
study administered the exercise/
physical activity subscale of the
Health Promoting Lifestyle Profile II
(HPLP-II) annually over a 5-year
period in a sample of 611 people
with MS and reported no mean
change in physical activity.36
Another study included the Physical
Activity Scale for Individuals With
Physical Disabilities (PASIPD) and a
sample that consisted primarily of
people with MS and spinal cord injuries but did not document a statistically significant mean change in
physical activity over a 12-month
period of time.34 The primary difference between the present study and
previous research is that we
included objective and self-report
measures of physical activity with
established evidence for the validity
of scores in people with MS.8,25 The
validity of the physical activity measures included in previous research
has not been systematically tested in
MS.6 The HPLP-II and PASIDP might
not be valid or sensitive for capturing naturally occurring changes in
physical activity over time among
those with the RRMS. Accordingly,
there does appear to be a reduction
of physical activity over time in people with RRMS that is captured by
validated, objective, and self-report
measures. This observation further
underscores the importance of identifying correlates of physical activity,
when considering that people with
MS are typically physically inactive6 – 8 and probably becoming more
physically inactive over time. When
combined, such behavioral patterns
probably increase the risk of secondary health conditions such as cardiovascular disease33 and negate the
benefits of physical activity for people with MS.9
This study documented significant
changes in self-efficacy for exercise,
walking impairment, and disability
status over a 2.5-year period of time
in people with MS; there were not
statistically significant changes in
symptoms of fatigue, depression,
and pain. We further documented
that change in self-efficacy for exercise correlated with changes in both
objective and self-report measures of
physical activity, even when controlling for walking impairment, disability status, and other confounding
variables. These findings suggest that
self-efficacy is an important correlate
of physical activity in people with
MS, and such an observation extends
existing research.13,14,30,37 For example, cross-sectional research has
demonstrated that self-efficacy correlated with physical activity even after
controlling for symptoms and disability in people with MS.13,14 One prospective study demonstrated that
baseline
self-efficacy
predicted
change in physical activity over a
3-month period of time in a sample
of 16 people with MS.37
One unique aspect of this study,
which has not previously been
reported in the published literature,
is the demonstrated change in selfefficacy being associated with
change in physical activity over 2.5
years in a large sample of people
with MS. Collectively, self-efficacy is
emerging as a cross-sectional, prospective, and longitudinal correlate
of physical activity in people with
MS. We do not specify that selfefficacy is causing physical activity
levels as the existing evidence is
more consistent with the concept of
reciprocal determinism.11 Reciprocal determinism suggests bidirec-
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1045
tional associations between personal
factors such as self-efficacy and
behaviors such as physical activity.
Nevertheless, self-efficacy is presumably a modifiable variable, and there
are established influences on selfefficacy (eg, mastery, social modeling) that can be targeted on the basis
of
social-cognitive
theory.11
Researchers should consider designing interventions that target selfefficacy for the promotion and longterm maintenance of physical
activity behavior in people with MS.
This research might not only change
physical activity but further inform
our understanding of the causal association between self-efficacy and
physical activity.
Regarding changes in symptoms and
associations with physical activity,
the results of the present study were
not consistent with our expectations
on the basis of previous crosssectional research.12–16 Indeed,
cross-sectional research has indicated that symptoms of fatigue,
depression, and pain were correlated with physical activity in people
with MS.12 This body of research
implies that changing such symptoms might be an avenue for changing physical activity in people with
MS. Such an inference required verification in a longitudinal analysis
and resulted in the current focus on
changes in symptoms as correlates of
changes in physical activity. To that
end, we did not observe statistically
significant changes in the measures
of fatigue, pain, and depression over
the 2.5-year period of time. The lack
of changes undermined our capacity
for examining changes in symptoms
as correlates of changes in physical
activity and would not support these
variables as targets of an intervention
for changing physical activity in MS.
The discrepancy between crosssectional and longitudinal results further highlights the importance of
verifying correlates in longitudinal
research, as cross-sectional corre1046
f
Physical Therapy
Volume 93
lates often do not replicate in prospective designs.
There were similarities and differences in the variables that correlated
with changes in objective versus selfreported physical activity in this
study of people with MS. The change
in self-efficacy was associated with
changes in both objective and selfreported physical activity. By comparison, changes in walking impairment and disability status were only
associated with changes in selfreported physical activity, but such
associations were no longer significant when accounting for the
change in self-efficacy. This finding
might indicate that walking impairment and disability are factors that
inform a person’s self-efficacy beliefs
consistent with previous crosssectional research.13 The inconsistency in association between walking impairment and disability status
with the objective and self-report
measures of physical activity might
reflect a self-report bias (ie, scores
from self-report measures might be
correlated simply based on overlapping variance associated with the
method of collecting data).
This research might have implications for the future development and
testing of approaches for increasing
physical activity in people with MS.
Such a focus is important because
physical activity has many benefits in
people with MS,9 but this population
has prevalent inactivity6 – 8 that seemingly becomes more prominent over
time, on the basis of the current
study. To that end, we believe that
our results point toward the adoption of social-cognitive theory as a
backdrop for informing the development and testing of interventions for
increasing physical activity in MS;
such a recommendation has been
made previously.6,7 This recommendation is because self-efficacy is considered an active agent and proximal
determinant of behavior change,11
Number 8
including physical activity,38 and the
magnitude of association between
changes in self-efficacy and physical
activity was quite strong in the present study. There further are factors
for targeting a change in self-efficacy
levels.11 Such factors include mastery or performance accomplishment, verbal persuasion or social
support, vicarious experience or
social learning, and interpretation of
physiological and affective cues.
Importantly, there are several smallscale studies of people with MS that
have targeted the enhancement of
self-efficacy on the basis of a socialcognitive perspective and reported
beneficial changes in exercise adherence39 and physical activity levels40
over short, 12-week periods of time.
To date, we are unaware of largescale studies that have documented
the effect of such an approach for
changing physical activity over long
periods of time (6 or 12 months)
with additional beneficial changes in
fitness, walking, disability, and
quality-of-life outcomes in MS. The
current research sets the stage for
designing interventions that can
result in long-term changes in physical activity and have potential
effects on other outcomes in the MS
population.
There are several limitations of the
current study. We focused only on
people with RRMS because this is
the most common clinical course.
Our results are not generalizable
among those with clinically isolated
syndrome or progressive disease
courses. We further focused on only
one
social-cognitive
variable,
namely, self-efficacy. This approach
was based on previous research
involving symptoms and physical
activity41 and practical issues of balancing the length of the survey battery with patient burden and adherence. Consequently, we do not have
information regarding changes in
outcome expectations, facilitators or
impediments, and behavioral proAugust 2013
cesses as correlates of changes in
physical activity. We only measured
symptoms twice annually with a single scale per symptom because of
the number of measures and duration of the research study. The limited sampling of symptoms might
not have captured important
changes in symptoms that occurred
over shorter time intervals when
considering correlates of changes in
physical activity. There is a lack of
published information on the clinical
meaningfulness of changes in scores
on the scales included in this study.
We were unable to characterize if
the observed small changes in physical activity, self-efficacy, walking,
and disability are clinically meaningful. There is limited published information on the sensitivity of all the
measures, and perhaps the symptomatic outcomes were not sensitive
for capturing actual changes in
fatigue, depression, and pain over
time.
Overall, the current research documented linear changes in physical
activity, self-efficacy, walking impairment, and disability status over a 2.5year period of time in people with
RRMS. There were not significant linear changes in the symptom scores
over time. We identified change in
self-efficacy as a correlate of change
in physical activity variables over
time, even after controlling for walking impairment, disability status, and
other confounding variables. Such
results support the consideration of
developing, delivering, and testing a
behavior intervention based on
social-cognitive theory for increasing
physical activity over a long period
of time in a large sample of people
with MS. This endeavor will further
our efforts in understanding the
importance of physical activity in the
lives of people with MS.42
Professors Motl and McAuley provided concept/idea/research design and fund procure-
August 2013
ment. All authors provided writing. Professor
Motl and Mr Sandroff provided data collection. Professor Motl provided data analysis,
study participants, and facilities/equipment.
Mr Sandroff provided project management.
This investigation was supported by a grant
from the National Multiple Sclerosis Society
(RG 3926A2/1).
DOI: 10.2522/ptj.20120479
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21 Hobart JC, Riazi A, Lamping DL, et al. Measuring the impact of MS on walking ability:
the 12-item MS Walking Scale (MSWS-12).
Neurology. 2003;60:31–36.
22 Hadjimichael O, Kerns RB, Rizzo MA, et al.
Persistent pain and uncomfortable sensations in persons with multiple sclerosis.
Pain. 2007;127:35– 41.
23 Muthén LK, Muthén BO. Mplus. Los Angeles, CA: Muthén & Muthén; 1998 –2004.
24 Craig CL, Marchall AL, Sjostrom M, et al.
International physical activity questionnaire: 12-country reliability and validity.
Med Sci Sports Exerc. 2003;35:1381–1395.
25 Gosney JL, Scott JA, Snook EM, Motl RW.
Physical activity and multiple sclerosis:
validity of self-report and objective measures.
Fam
Community
Health.
2007;3:144 –150.
26 Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The Fatigue Severity Scale: application to patients with multiple sclerosis
and systemic lupus erythematosus. Arch
Neurol. 1989;46:1121–1123.
27 Melzack R. The short-form McGill Pain
Questionnaire. Pain. 1987;30:191–197.
28 Zigmoid AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiat
Scand. 1983;67:361–370.
29 McAuley E. Self-efficacy and the maintenance of exercise participation in older
adults. J Behav Med. 1993;16:103–113.
30 Motl RW, Snook EM, McAuley E, et al. Correlates of physical activity among individuals with multiple sclerosis. Ann Behav
Med. 2006;32:154 –161.
31 Hu L, Bentler PM. Cutoff criteria for fit
indices in covariance structure analysis:
conventional versus new alternatives.
Struct Equat Model. 1999;6:1–55.
32 Cohen J. Statistical Power Analysis for
the Behavioral Sciences. 2nd ed. Hillsdale,
NJ: Lawrence Erlbaum Associates; 1988.
33 Motl RW, Fernhall B, McAuley E, Cutter G.
Physical activity and self-reported cardiovascular comorbidities in persons with
multiple sclerosis: evidence from a crosssectional analysis. Neuroepidemiology.
2011;36:183–191.
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34 Kosma M, Ellis R, Bauer JJ. Longitudinal
changes in psychosocial constructs and
physical activity among adults with physical disabilities. Disabil Health J.
2012;5:1– 8.
35 Stuifbergen AK, Becker H. Health promotion practices of women with multiple
sclerosis. Phys Med Rehabil Clin N Am.
2001;12:9 –22.
36 Stuifbergen AK, Blozis SA, Harrison TC,
Becker HA. Exercise, functional limitations, and quality of life: a longitudinal
study of persons with multiple sclerosis.
Arch Phys Med Rehabil. 2006;87:
935–943.
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37 Motl RW, McAuley E, Doerksen S, et al.
Preliminary evidence that self-efficacy predicts physical activity in multiple sclerosis.
Int J Rehabil Res. 2009;32:260 –263.
38 McAuley E, Blissmer B. Self-efficacy determinants and consequences of physical
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39 McAuley E, Motl RW, Morris KS, et al.
Enhancing physical activity adherence and
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40 Motl RW, Dlugonski D, Wójcicki TR, et al.
Internet intervention for increasing physical activity in persons with multiple sclerosis. Mult Scler. 2011;17:116 –128.
41 Bandura A. Health promotion by social
cognitive means. Health Educ Behav.
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42 Benito-León J. Physical activity in multiple
sclerosis: the missing prescription. Neuroepidemiology. 2011;36:192–193.
August 2013
Research Report
Acute Cartilage Loading Responses
After an In Vivo Squatting Exercise in
People With Doubtful to Mild Knee
Osteoarthritis: A Case-Control Study
Ans Van Ginckel, Erik Witvrouw
Background. The effects of exercise on osteoarthritic cartilage remain elusive.
Objective. The objective of this study was to investigate the effect of dynamic in
vivo squatting exercise on the magnitude and spatial pattern of acute cartilage
responses in people with tibiofemoral osteoarthritis (ie, Kellgren-Lawrence grades 1
and 2).
Design. This investigation was a case-control study.
Methods. Eighteen people with radiographic signs of doubtful to mild medial
tibiofemoral osteoarthritis were compared with 18 people who were middle-aged
and healthy (controls). Three-dimensional magnetic resonance imaging was used to
monitor deformation and recovery on the basis of 3-dimensional cartilage volume
calculations (ie, total volume and volumes in anterior, central, and posterior subregions) before and after a 30-repetition squatting exercise. Three-dimensional volumes
were estimated after semiautomatic segmentation and were calculated at 4 time
points (1 before and 3 after scans). Scans obtained after the exercise were separated
by 15-minute intervals.
Results. In both groups, significant deformation was noted in the medial compart-
ment (⫺3.4% for the femur and ⫺3.2% for the tibia in people with osteoarthritis
versus ⫺2.8% for the femur and ⫺3.8% for the tibia in people in the control group).
People with osteoarthritis had significant deformation in the lateral femur (⫺3.9%)
and a tendency toward significant deformation in the lateral tibia (⫺3.1%). From 15
minutes after exercise cessation onward, volume changes were no longer significantly different from the baseline. At all time points, no significant between-group
differences were revealed for volume changes. People with osteoarthritis showed a
tendency toward slower recovery preceded by larger deformations in entire cartilage
plates and subregions. Spatial subregional deformation patterns were similar between
groups.
A. Van Ginckel, PT, MSc, FWO
Aspirant
(PhD
Fellowship
Research Foundation–Flanders),
Brussels, Belgium, and Department of Rehabilitation Sciences
and Physiotherapy, Ghent University, Hospital Campus, 3B3,
De Pintelaan 185, BE-9000 Ghent,
Belgium. Address all correspondence to Ms Van Ginckel at:
[email protected].
E. Witvrouw, PT, PhD, Ghent University and Aspetar, Doha, Qatar.
[Van Ginckel A, Witvrouw E.
Acute cartilage loading responses
after an in vivo squatting exercise
in people with doubtful to mild
knee osteoarthritis: a case-control
study. Phys Ther. 2013;93:1049 –
1060.]
Association
April 11, 2013
Submitted: December 7, 2012
Limitations. Generalizability is limited to people with doubtful to mild osteoarthritis and low levels of pain.
Conclusions. Tibiofemoral cartilage deformation appeared similar in magnitude
and spatial pattern in people who were middle-aged and either had or did not have
tibiofemoral osteoarthritis (ie, Kellgren-Lawrence grades 1 and 2). Restoration of
volumes required a 15-minute recovery, especially in the presence of osteoarthritic
cartilage degeneration.
this article at:
ptjournal.apta.org
August 2013
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C
linical guidelines for osteoarthritis (OA) management
indicate that exercise is an
important component of first-line
treatment strategies because of its
potential to diminish pain and
improve physical function.1– 6 However, a weak correlation exists
between clinical presentation and
structural joint health, especially in
the early stages of the OA disease
process (ie, Kellgren-Lawrence [K/L]
grades 1 and 2).7,8 Because most trials have focused on symptom-related
outcomes, the effects of exercise on
structural outcomes in joints with
OA remain subject to disparity.
Although exercise appears to beneficially affect cartilage integrity in
young adults who are healthy, the
protective effects of light to moderate (therapeutic) exercise may persist with increasing age in people
without radiographic signs of OA
or people at risk for progressive
radiographic OA (eg, K/L grade 1,
previous knee injury or surgery,
and occasional knee symptoms).9 –17
In people with established radiographic OA (ie, K/L grades 2– 4),
single-event and long-term intervention trials (alone or combined with
diet or glucosamine supplementation) showed beneficial changes or
stability in cartilaginous biomarkers
for ultrastructural compounds or
anti-inflammatory responses.18 –22 In
contrast, Woollard et al23 reported
small cartilage volume changes (up
to a loss of 3.8%) in the central
medial femur after treatment that
included aerobic, strengthening, and
flexibility exercises alone or with
agility and perturbation. Although
the disparity in treatment effects
may be attributable to grouping of
patients with various radiographic
disease stages, characteristics of
patients (such as body mass index
[BMI] and lower-limb alignment),
and differences in cartilage measures
or exercise modes,2,23 a concern is
that weight-bearing exercise may
lead to acceleration of cartilage degradation instead of deceleration.19
The Bottom Line
What do we already know about this topic?
Cartilage in joints with osteoarthritis (OA) shows altered mechanical
behavior that may increase the vulnerability of the cartilage to accelerated
degeneration because of repetitive impact loads.
What new information does this study offer?
After a 30-repetition squatting exercise, tibiofemoral cartilage deformation appeared to be similar in magnitude and spatial pattern in participants who were middle-aged and either had or did not have tibiofemoral
OA. Restoration of cartilage volumes to baseline levels required a
15-minute recovery, especially in participants with OA.
If you’re a patient, what might these findings mean
for you?
After 30 repetitions of full weight-bearing squatting, middle-aged people
should allow at least 15 minutes of rest from exercise to permit knee
cartilage volumes to recover to pre-exercise levels.
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Degraded cartilage shows proteoglycan loss and disruption of the
collagen fiber network.24 –26 These
ultrastructural changes affect the
mechanical behavior of cartilage.
Fibrillation of the collagen network
induces a loss of tensile strength and
causes decreased cartilage compressive stiffness and increased tissue
permeability.25–27 In people at risk
for the development of radiographic
OA displaying ultrastructural cartilage degeneration (ie, collagen disruption and water accumulation),
cartilage showed delayed recovery
of volumes after an in vivo running
event.28 Maintained deformation and
dehydration of cartilage tissue after
loading were suggested to increase
the vulnerability of cartilage to accelerated degeneration in the presence
of repetitive (high)-impact loads.28,29
Although moderate therapeutic
exercise that included weightbearing neuromuscular control and
strength exercises, such as a squatting exercise, was shown to beneficially affect physical function and
cartilage integrity in people with the
early stages of OA development (ie,
K/L grades 1 and 2),10,30 these people, in turn, also had an increased
risk of accelerated OA progression.31
Therefore, insight into the recovery
times required after in vivo weightbearing exercise in these people
may be a first step toward the appropriate design of treatment programs
to positively affect cartilage structural integrity and retard disease
progression.
Therefore, the purpose of this
study was to investigate the effect of
a dynamic in vivo weight-bearing
squatting exercise on acute cartilage
responses in people with K/L grades
1 and 2. To this end, we evaluated
in vivo cartilage deformation (ie,
magnitude and spatial pattern) and
time to recovery in both people with
radiographic signs of doubtful to
mild OA (ie, K/L grades 1 and 2)
August 2013
and people who were middle-aged
and healthy (controls). Although
we expected the spatial patterns to
be similar between the groups,27
we hypothesized that knee cartilage in people with radiographic
signs of doubtful to mild OA would
exhibit increased deformation27,32
followed by a slower recovery after
the exercise.28,29
Method
Study Design Overview
In this case-control study, in vivo
cartilage deformation and recovery
after a squatting exercise in people
with radiographic signs of OA (ie,
K/L grades 1 and 2 and with cartilage defects on magnetic resonance
imaging [MRI]) were compared with
those in people who were middleaged and healthy (controls) (ie,
K/L grade 0 and without cartilage
defects).
Participants
Participants with OA were 18 people
(12 men and 6 women) recruited
from the Department of Physical
Medicine and Orthopedic Surgery,
Ghent University, Hospital Campus.
Eligibility to participate was based
on clinical assessments, medical
imaging, and standard questionnaires. Inclusion criteria were clinical and radiographic signs of doubtful to mild medial tibiofemoral OA
(ie, K/L grades 1 and 2)33,34 and
medial tibiofemoral cartilage defects
on MRI (ie, whole-organ MRI score
of ⱖ2).35 All participants had degenerative meniscal tears on MRI. Additionally, participants had to be able
to perform the exercise correctly at
the time of the study, without substantial discomfort (ie, visual analog
scale [VAS] score of ⬍5 cm for pain
during the exercise and active knee
flexion range of motion of ⱖ90°).
Exclusion criteria were history of
knee surgery, including meniscal
procedures, arthroplasty, or both;
corticosteroid or hyaluronan injections within the 3 months preceding
August 2013
the study; MRI contraindications;
and other known joint or bone
pathologies. For participants with
unilateral disease, the affected knee
was investigated. For participants
with bilateral radiographic disease,
the more affected knee (within K/L
grades 1 and 2) was included; when
both knees were affected to similar
extents, the dominant leg was investigated. Leg dominance was defined
as the limb the participant would
choose to kick a ball.36 –38
Control participants were 18 people
who were middle-aged and recruited
from the community or university
campus. Eligibility was verified with
medical imaging and standard questionnaires. Inclusion criteria were no
radiographic signs of OA and no cartilage defects on MRI. Additionally,
control participants were selected
on the basis of similar physical activity levels (ie, scores on the Baecke
questionnaire28,37–39) and in similar
proportions with regard to sex and
limb dominance. Exclusion criteria
were a history of knee pain, knee
injury, or both, including a previous
diagnosis of cartilage defects; previous knee surgery; BMI of greater
than 30 kg/m2; and age younger
than 40 years and older than 60
years. In this way, the risk of cartilage abnormalities on MRI with
increasing age (even in the presence of normal radiographic appearances)40 was reduced. Additional
exclusion criteria were known bone
pathologies, joint pathologies, or
both (eg, presence of bone marrow
lesions or displaced meniscal tears or
complete degeneration on MRI41)
and MRI contraindications.
Informed consent was obtained from
all participants. Participant characteristics are shown in Table 1.
Setting and
Experimental Procedures
All experimental procedures were
performed during one test appoint-
ment.
All
participants
were
instructed to not practice sports on
the day before testing or the day of
testing and to avoid running, lifting heavy weights, and taking stairs
for 4 hours preceding the actual
experimental procedures.28,36 –38,42
The procedures were performed on
the hospital campus at the same
time of day for all participants.28,36,38
The protocol comprised MRI evaluation for in vivo deformation and
recovery, evaluation of lower limb
function and knee alignment, and
questionnaires.
MRI evaluation of cartilage. Cartilage deformation and recovery
were registered by monitoring cartilage quantitative morphology (ie,
3-dimensional [3D] volumes) before
and after an in vivo weight-bearing
exercise.28,36,38
High-resolution
images of cartilage morphology were
acquired by means of a sagittal 3D
double-echo steady-state sequence
with water excitation (3D DESS WE).
Additionally, to determine eligibility
for inclusion, a fat-saturated turbo–
spin-echo (TSE) sequence with intermediate weighting was included
next to the 3D DESS WE sequence at
the baseline, allowing for grading of
cartilage with the whole-organ MRI
score.35 Finally, a T2 map (MapIt,
Siemens Medical Solutions, Erlangen,
Germany) was included. T2 relaxation times depict ultrastructural
changes in the collagen and water
contents of the cartilage matrix.
Higher T2 values are associated with
early degeneration even before macroscopic changes are present and
were investigated to estimate the
presence of insidious cartilage disease in conjunction with the macromorphological appearance of the
cartilage surface.43
T2 maps were centered on the tibiofemoral compartments and were
reconstructed online with a pixelwise, monoexponential, nonnegative least squares fit analysis (MapIt),
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Table 1.
Participant Characteristicsa
Characteristic
Participants With
Osteoarthritis (nⴝ18)
Control Participants
(nⴝ18)
P
27.1 (3.7)
24.0 (3.5)
.02c,d
54.5 (49.8, 64.3, 14.3)
43.0 (40.0, 45.0, 5.0)
⬍.001d,e
⫺2.6 (27.1)
6.4 (19.6)
.26c
8.4 (1.5)
8.3 (1.4)
.93c
49.6 (18.3)
38.8 (19.8)
.10c
Demographics
Body mass index, kg/m2 b
Age, y
Knee alignment, absolute intercondylar
distance, mmb,f
Symptoms and function
Baecke physical activity level scoreb
FORRS scoreb
FTSTS Test best time, s
7.8 (6.8, 9.0, 2.2)
7.1 (6.1, 7.7, 1.6)
.06e
FTSTS Test mean time, s
8.1 (6.9, 9.8, 2.9)
7.3 (6.9, 8.1, 1.2)
.12e
RAND-36 physical function score
55.0 (32.5, 82.5, 50.0)
100.0 (90.0, 100.0, 10.0)
⬍.001d,e
RAND-36 social function score
87.5 (62.5, 100, 37.5)
100.0 (100.0, 100.0, 0.0)
.001d,e
RAND-36 role limitations physical
health score
100.0 (50.0, 100.0, 50.0)
100.0 (100.0, 100.0, 0.0)
.03d,e
RAND-36 role limitations emotional
health score
100.0 (100.0, 100.0, 0.0)
100.0 (100.0, 100.0, 0.0)
.32e
RAND-36 emotional well-being score
78.0 (72.0, 88.0, 16.0)
88.0 (80.0, 93.0, 13.0)
.03d,e
RAND-36 energy/fatigue score
70.0 (65.0, 76.3, 11.3)
80.0 (73.8, 86.3, 7.5)
.01d,e
RAND-36 pain score
67.4 (53.0, 79.6, 26.6)
100.0 (79.6, 100.0, 20.4)
.002d,e
RAND-36 general health score
72.5 (65.0, 85.0, 30.0)
82.5 (70.0, 90.0, 20.0)
.22e
RAND-36 health change score
50.0 (50.0, 50.0, 0.0)
50.0 (50.0, 50.0, 0.0)
.44e
WOMAC standardized total score, out
of 100
80.2 (62.8, 95.8, 33.0)
100 (100, 100, 0)
⬍.001d,e
0.0 (0.0, 0.0, 0.0)
.001d,e
VAS score for pain during preceding
week, out of 10
2.8 (0.0, 5.0, 5.0)
a
Data are presented as median (25th percentile, 75th percentile, interquartile range) unless otherwise indicated. FORSS⫽Factor Occupational Rating System
Scale, FTSTS⫽Five-Times-Sit-to-Stand, RAND-36⫽RAND 36-Item Health Survey, WOMAC⫽Western Ontario and McMaster Universities Arthritis Index,
VAS⫽visual analog scale. For the WOMAC, standardized total scores were calculated with the following formula: [(96 ⫺ total score) ⫻ 100]/96, where 96
was the maximum score; the higher the score, the smaller the disease impact.
b
Data are presented as mean (standard deviation).
c
P values were determined with the t test for independent samples.
d
Significant difference between groups at an ␣ of less than .05.
e
P values were determined with the Mann-Whitney U test.
f
Positive values represent tendencies toward varus alignment; negative values represent tendencies toward valgus alignment.
enabling instant T2 quantification
after image acquisition. All images
were obtained with a dedicated
8-channel knee coil and a 3-T Trio
Tim magnet (Siemens Medical Solutions). Knee joints were scanned in
extension, and neutral rotation was
ensured by placement of rigid foam
around the lower leg. Supine positioning of participants was standardized on the basis of the position of
the knee joint according to the reference points on the knee coil.37 The
sequence parameters for 3D DESS
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WE, the TSE sequence with intermediate weighting, and the T2 map
were previously described.28
To reduce interference from residual
deformation preceding the experiment, the MRI protocol started with
a 1-hour physical rest period with
the participants in a supine position.28,36,38,44 After the rest period,
baseline scans (tpre: baseline sagittal
3D DESS WE, T2 map, and TSE
sequence with intermediate weighting) were obtained, and then the
Number 8
weight-bearing exercise under study
was performed. Sagittal 3D DESS
WE scans were obtained within 90
seconds after exercise cessation
(tpostt0),36,38 at 15 minutes after
tpostt0 (tpostt15), and at 30 minutes
after tpostt0 (tpostt30). Deformation was expressed as the 3D volume change measured at tpostt0 relative to the baseline: [(3D volume at
tpostt0 ⫺ 3D volume at tpre)/3D volume at tpre] ⫻ 100. The morphological changes measured at tpostt15
and tpostt30 relative to the baseline
August 2013
were considered to represent recovery.28,38 The sequence of events is
displayed in Figure 1.
The exercise consisted of 30 bilateral knee bends until the upper leg
was lowered to a horizontal position
(referenced to the seat of a chair)
in 1 minute. To ensure correct
and standardized performance, the
exercise was carried out under a
researcher’s supervision and performed barefoot next to the scanner
magnet.36,38,44 The exercise speed
was set to the pace of a metronome
(60 bpm). Visual analog scale scores
were collected for the extent of
knee pain experienced during the
exercise (on a 10-cm scale, with
0 cm representing “no pain at all”
and 10 cm representing “extremely
painful”). The effect of 30 knee
bends on cartilage in adults was previously evaluated with MRI.44 – 46
Evaluation of lower limb function
and knee alignment. Functional
lower limb performance was evaluated with the Five-Times-Sit-to-Stand
(FTSTS) Test.47 The FTSTS Test was
performed twice, and both the mean
time and the best time were used for
analysis.
Knee alignment (genu varum or
genu valgum) was determined by
measuring the intercondylar (IC)
or intermalleolar (IM) distance with
an inside caliper as previously
described.48 The IM distance was
subtracted from the IC distance, and
the resulting value was considered to
be the absolute IC distance. Quantification of the absolute IC or IM distance attained high intertester and
intratester reliability values (intraclass correlation coefficients of .95
and .96, respectively)48 and was
shown to be valid when compared
with full limb radiographs (BlandAltman plot: R2⫽.98, P⬍.001; no
correlation between BMI and absolute IC distance [r⫽⫺.03, P⫽.85]).
August 2013
Figure 1.
Schematic overview of the sequence of events during the magnetic resonance imaging
experimental protocol. 1–3⫽postexercise scans obtained within 90 seconds after exercise cessation (tpostt0), at 15 minutes after tpostt0, and at 30 minutes after tpostt0,
respectively; bpm⫽beats per minute; 3D DESS WE⫽3-dimensional double-echo steadystate sequence with water excitation; TSE⫽turbo–spin-echo (sequence). Adapted with
permission from Van Ginckel et al.28,38
Questionnaires. All participants
completed the Baecke questionnaire
to quantify general physical activity
level on the basis of a work, sports,
and leisure index39; the Factor Occupational Rating System Scale to rate
knee joint load during work situations in particular49; a Likert-scale
version of the Western Ontario
and McMaster Universities Arthritis
Index (WOMAC) to quantify pain,
stiffness, and physical function
(activities of daily living)50; and the
RAND 36-Item Health Survey (RAND36) to measure quality of life.51
Visual analog scale scores (out of 10)
were used to describe the amount of
pain experienced during the preceding week, and self-reported duration
of knee complaints (in months) was
recorded.
Data Analysis
Image analysis: 3D volume calculation. Three-dimensional reconstruction, volume calculation, and
model registration were performed
with a commercial modeling software package (Mimics, version
14.0, Materialise NV, Leuven,
Belgium).28,36,38
Three-dimensional
double-echo
steady-state sequence image stacks
were segmented to generate a 3D
reconstruction of lateral femur,
medial femur, lateral tibia, and
medial tibia cartilage. A semiautomated segmentation procedure was
implemented with a 3D LiveWire
algorithm52 and slice-by-slice manual
correction to digitize cartilage plates
by masking. A region-growing algorithm to dispose of abundant voxels
was applied before manual correction. Three-dimensional cartilage
plates were reconstructed, and absolute 3D volumes (in mm3) were calculated for baseline and postexercise
scans.28,36,38 In addition to the calculation of total volumes at all time
points, subregional tibiofemoral volumes were determined to investigate
spatial deformation patterns (eg, at
tpostt0).27 As defined in the cartilage
whole-organ MRI score system,35
femoral and tibial cartilage plates
were divided into anterior, central,
and posterior subregions (anteromedial femur, centromedial femur,
posteromedial femur, anterolateral
femur, centrolateral femur, posterolateral femur, anteromedial tibia,
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Figure 2.
Illustration of the subregions used in this study, as defined in the whole-organ MRI score
system.35 The femoral and tibial surfaces were divided into anterior (A), central (C), and
posterior (P) regions. Region A of the femur corresponds to the patellofemoral articulation, region C corresponds to the weight-bearing surface, and region P corresponds
to the posterior convexity that articulates only in deeper flexion. Region C of the tibial
surface corresponds to the uncovered portion between the anterior and posterior horns
of the meniscus centrally and the portion covered by the body of the meniscus
peripherally.35 Images of the 3-dimensional reconstructions are screen shots taken from
the Mimics software interface.
centromedial tibia, posteromedial
tibia, anterolateral tibia, centrolateral
tibia, and posterolateral tibia). An
illustration of the division into subregions is shown in Figure 2.
All image analyses were performed
by a single researcher who had 4
years of experience at the time of
analysis and who was unaware of the
time sequence of scanning.28,36,38,53
On the basis of 3 repetitions for all
cartilage plates, the intratester reliability values (intraclass correlation
coefficients) for the 3D volumetric
measurements were .96 to .99 in 3
control participants and .92 to .99 in
3 participants with OA, and the precision errors (root-mean-square coefficients of variation) were .02 to .03
in both groups of participants.
Power analysis. For participants
with various K/L grades and ultrastructural cartilage degeneration,
the mean (standard deviation) morphological changes after an in vivo
load ranged from ⫺1.8% (3.0%) to
⫺7.9% (11.0%).27,28,32 Attaining the
smallest difference with a statistical
significance (␣) of less than .05
and standard power required the
inclusion of at least 24 participants
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in the entire group. However, the
between-group differences were
expected to range from 0.1% to
approximately 4.5%.27,28,32 In view
of our precision errors (which
were consistent with precision
errors reported in the relevant literature27,54), the between-group differences needed to reach approximately 3% to be relevant in the
present study. Detecting this difference required the inclusion of at
least 16 participants in each group.
The power analysis was performed
with Gpower (version 3.1.5, Universität Kiel, Kiel, Germany).
Statistical analysis. The ShapiroWilk test revealed a parametric distribution (P⬎.05) for all included
variables except age, WOMAC total
scores, all RAND-36 items, VAS
scores for pain during the preceding week and pain during the study
exercise, and FTSTS Test best and
mean times. Parametric and nonparametric statistics were executed,
and data are presented as means
(standard deviations) and medians
(25th percentile, 75th percentile,
and interquartile range), respectively. To investigate baseline differences in group characteristics, we
Number 8
applied the t test for independent
samples or the Mann-Whitney
U test. To test the hypothesis that
the morphology of all cartilage
plates changed significantly over
time within and between groups, we
applied a general linear model for
repeated measures with time and
cartilage plate as the within-subject
factors and participant group allocation (participants with OA and control participants) as the betweensubject factor. The model corrected
for the main confounding factors
BMI and age as covariates. Bonferroni corrections were used to adjust
P values for multiple comparisons of
main effects. The level of significance (␣) was set at less than .05,
and SPSS (version 21, IBM Statistics,
Armonk, New York) was used for all
analyses.
This study was funded by the
Research Foundation of Flanders
(FWO Vlaanderen).
Results
Group Characteristics:
Demographics, Symptoms,
and Function
The group characteristics are
shown in Table 1. No significant
between-group differences were
found for the Baecke physical activity level (P⫽.93), the Factor Occupational Rating System Scale (P⫽.10),
the FTSTS Test mean time (P⫽.12)
and best time (P⫽.06), and knee
alignment (P⫽.26). The WOMAC
standardized total scores were significantly lower in participants with
OA than in control participants
(P⬍.001), as were scores for all
RAND-36 items except for role limitations emotional health (P⫽.32),
general health (P⫽.21), and health
change (P⫽.44). Control participants were younger and had a lower
BMI than participants with OA
(P⬍.001 and P⫽.02, respectively).
For participants with OA, VAS scores
for pain during the preceding week
August 2013
Table 2.
In Vivo Cartilage Deformation and Recovery Revealed by Three-Dimensional Volume Changes After Exercisea
Three-Dimensional Volume Changes, X (SD), in:
Cartilage
Medial femur
Lateral femur
Medial tibia
Lateral tibia
All
Participants
(Nⴝ36)
Participants With
Osteoarthritis
(nⴝ18)
Control
Participants
(nⴝ18)
Change 1 (at tpostt0)
⫺3.1 (4.0)b
⫺3.4 (3.2)b
⫺2.8 (4.6)b
1.00
⫺0.3 (3.7)
⫺0.7 (3.6)
0.2 (3.8)
1.00
Change in
Morphology at
Indicated Time
P Value
Between
Groups
0.4 (3.5)
0.5 (3.4)
0.3 (3.7)
1.00
⫺3.3 (3.6)b
⫺3.9 (3.5)b
⫺2.8 (3.7)
1.00
⫺1.4 (3.2)
⫺2.6 (3.0)
⫺0.3 (3.0)
.12
⫺0.6 (3.7)
⫺1.6 (3.7)
0.3 (3.5)
.42
⫺3.5 (3.6)b
⫺3.2 (3.9)b
⫺3.8 (3.3)b
1.00
0.0 (4.8)
0.8 (4.2)
⫺0.7 (5.5)
1.00
1.5 (4.0)
⫺0.5 (5.5)
.76
⫺3.1 (4.6)
⫺1.4 (4.4)
.92
0.5 (4.9)
⫺2.2 (4.5)b
⫺1.0 (3.8)
⫺1.5 (2.3)
⫺0.5 (4.8)
1.00
⫺0.6 (3.0)
⫺1.1 (2.5)
⫺0.1 (3.4)
.94
a
tpostt0, tpostt15, and tpostt30⫽within 90 seconds after exercise cessation, at 15 minutes after tpostt0, and at 30 minutes after tpostt0, respectively.
Covariates appearing in the model were evaluated at an age of 50.0 years and a body mass index of 25.6.
Significant difference relative to baseline within groups at an ␣ of less than .05. P values were adjusted for multiple comparisons of main effects and
confounding by age and body mass index.
b
revealed mild to moderate discomfort; the median (25th percentile,
75th percentile, interquartile range)
score was 2.8 (0.0, 5.0, 5.0) cm. The
mean (standard deviation) duration
of self-reported knee complaints was
40.36 (31.8) months.
In Vivo Cartilage Deformation
and Recovery: Percent 3D
Volume Changes After Exercise
For the entire sample (N⫽36), the
squatting exercise effected significant deformation relative to the baseline; the mean (standard deviation)
reductions in 3D volumes at tpostt0
were ⫺3.3% (3.6%) for the lateral
femur (P⬍.001), ⫺3.1% (4.0%) for
the medial femur (P⬍.001), ⫺2.2%
(4.5%) for the lateral tibia (P⫽.02),
and ⫺3.5% (3.6%) for the medial
tibia (P⬍.001). None of the plates
showed significant volume decreases
at the recovery time points (tpostt15
and tpostt30).
For the control participants (n⫽18),
relative to the baseline, none of the
morphological changes at all postexAugust 2013
ercise time points differed significantly in the lateral femur (P⫽.10,
P⫽1.00, and P⫽1.00 for tpostt0,
tpostt15, and tpostt30, respectively)
or the lateral tibia (P⫽.73, P⫽1.00,
and P⫽1.00, respectively). In the
medial femur and the medial tibia,
only changes measured at tpostt0
(ie, deformation) were significantly
different from the baseline; the mean
(standard deviation) changes were
⫺2.8% (4.6%) (P⫽.04) and ⫺3.2%
(3.9%) (P⫽.01), respectively.
For the participants with OA
(n⫽18), changes measured at
tpostt0 differed significantly from
the baseline for all plates, except for
the lateral tibia; the mean (standard
deviation) changes were ⫺3.9%
(3.5%) (P⫽.001), ⫺3.4% (3.2%)
(P⫽.02), and ⫺3.8% (3.3%) (P⫽.01)
for the lateral femur, medial femur,
and medial tibia, respectively. There
was a tendency toward significance
for the lateral tibia; the change was
⫺3.1% (4.6%) (P⫽.05). After completion of the squatting exercise, the
participants with OA reported no to
mild knee pain; the median (25th
percentile, 75th percentile, interquartile range) VAS score was 1.0
(0.4, 3.3, 2.9) cm.
No significant between-group differences were revealed. For all plates
and all time points, percent changes
and confounding factor–adjusted
P values are shown in Table 2.
In Vivo Cartilage Spatial
Deformation Patterns:
Subregional Analysis of
Percent 3D Changes at tpostt0
In both groups of participants, 3D
volumes were significantly smaller in
all subregions at tpostt0 than at the
baseline, with the largest deformation being noted in the posterior
femoral condyles and anterior tibial
plateaus. On the basis of the magnitude of the mean subregional volume decreases, similar spatial deformation patterns were observed in
both groups (posteromedial femur ⬎
anteromedial femur ⫽ centromedial
femur, posterolateral femur ⬎ centrolateral femur ⬎ anterolateral
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Table 3.
In Vivo Cartilage Deformation Patterns Revealed by Subregional Analysis of Three-Dimensional Volume Changesa
Change, X (SD), at
tpostt0 in Control
Participants (nⴝ18)
P Value Within
Control Group
Change, X (SD),
at tpostt0 in
Participants With
Osteoarthritis
(nⴝ18)
FMA
⫺7.1 (3.6)
⬍.001b
⫺7.1 (3.0)
⬍.001b
FMC
⫺7.0 (3.0)
⬍.001b
⫺7.1 (3.6)
⬍.001b
FMP
⫺10.6 (8.6)
.001
b
FLA
⫺2.7 (3.4)
.028b
FLC
Subregion
P Value Within
Osteoarthritis
Group
⫺13.8 (11.6)
.014b
⫺3.0 (3.4)
.001b
⫺5.1 (3.4)
⬍.001
b
⫺5.4 (3.4)
⬍.001b
FLP
⫺5.0 (3.6)
⬍.001b
⫺5.7 (3.4)
⬍.001b
TMA
⫺20.2 (2.7)
⬍.001
b
⫺20.5 (2.4)
⬍.001b
TMC
⫺5.5 (3.6)
⬍.001b
⫺5.8 (3.2)
⬍.001b
TMP
⫺12.0 (3.4)
⬍.001
b
⫺12.3 (3.0)
⬍.001b
TLA
⫺11.5 (1.8)
⬍.001b
⫺12.5 (1.9)
⬍.001b
TLC
⫺3.5 (2.0)
⬍.001
b
⫺4.6 (1.2)
⬍.001b
TLP
⫺6.2 (2.4)
.003b
⫺7.9 (2.2)
.004b
a
FMA⫽anteromedial femur, FMC⫽centromedial femur, FMP⫽posteromedial femur, FLA⫽anterolateral femur, FLC⫽centrolateral femur, FLP⫽posterolateral
femur, TMA⫽anteromedial tibia, TMC⫽centromedial tibia, TMP⫽posteromedial tibia, TLA⫽anterolateral tibia, TLC⫽centrolateral tibia, TLP⫽posterolateral
tibia, tpostt0⫽within 90 seconds after exercise cessation. Covariates appearing in the model were evaluated at an age of 50.0 years and a body mass index
of 25.6.
b
Significant difference relative to baseline at an ␣ of less than .05. P values were adjusted for multiple comparisons of main effects and confounding by age
and body mass index.
femur, anteromedial tibia ⬎ posteromedial tibia ⬎ centromedial tibia,
and anterolateral tibia ⬎ posterolateral tibia ⬎ centrolateral tibia in
participants with OA and posteromedial femur ⬎ anteromedial
femur ⫽ centromedial femur, posterolateral femur ⫽ centrolateral
femur ⬎ anterolateral femur, anteromedial tibia ⬎ posteromedial tibia ⬎
centromedial tibia, and anterolateral
tibia ⬎ posterolateral tibia ⬎ centrolateral tibia in control participants).
For all plates, subregional percent
changes and confounding factor–
adjusted P values are shown in
Table 3.
Discussion
The main purpose of the present
study was to investigate tibiofemoral
cartilage deformation and recovery
after a 30-repetition squatting exercise in participants with osteoarthritic cartilage degeneration (ie, up
to radiographic signs of mild OA; K/L
grades 1 and 2) and participants who
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were middle-aged and healthy (ie, no
radiographic signs of OA and no cartilage defects on MRI). The principal
finding was that, despite a tendency
toward more deformation in the participants with OA, no significant differences between the groups in volume decreases immediately after the
exercise were revealed. Additionally,
similar spatial deformation patterns
were observed in both groups. Interestingly, recovery tended to occur
more slowly in participants with OA,
requiring at least 15 minutes after
exercise cessation for all cartilage
plates to return to baseline volumes.
In the present study, mean cartilage
deformation in the tibiofemoral compartments in participants with OA
ranged from ⫺3.1% to ⫺3.9%. To the
best of our knowledge, this is the
first report on the effects of an in
vivo weight-bearing dynamic exercise on the deformation behavior of
human osteoarthritic cartilage. Two
previous studies of patient popula-
Number 8
tions with K/L grades 2 to 427 and
K/L grades 2 and 332 examined
tibiofemoral morphological changes
after a static load was applied to a
knee flexed 20 degrees. Relative
changes ranged from ⫹1.92% to
⫺7.85%. Static loading has been
described as conveying more deformation than dynamic loading; this
factor may explain the broader
range of outcomes observed in the
static loading experiments. Gradually applied static loads allow cartilage deformation responses to adapt
more easily to the imposed load,
leading to larger deformations of tissue without a considerable pressure
surge within its matrix.36,44,45,55,56
In vitro experiments with healthy
and osteoarthritic cartilage revealed
that dynamic intermittent loading
protocols may upregulate matrix
synthesis; in contrast, static and injurious impacts tend to decrease the
production of matrix compounds
and to stimulate protease activity,
exerting a deleterious effect on carAugust 2013
tilage quality.56 –58 Therefore, in view
of clinical practice, we preferred to
investigate dynamic exercise in the
present study.
In the control participants, mean
3D volume decreases of ⫺1.4% to
⫺3.2% were observed. In young
adults, a similar exercise yielded
mean 3D volume changes of ⫹0.1%
to ⫺3.9% in the tibiofemoral compartments.44 – 46 Interestingly, the
deformation outcomes for both control participants and participants
with OA were within the ranges
established in young adults. In the
present study, the mean difference
between the groups at deformation
was 1.7%, which did not meet the
required difference of approximately
3%. However, we noted a tendency
toward more deformation in the participants with OA, especially in the
lateral femur and the lateral tibia.
Although not involved on radiography, baseline biochemical T2 maps
showed higher T2 values in the lateral femur and the lateral tibia: 37.4
(SD⫽4.0) milliseconds in the lateral
femur and 27.4 (SD⫽4.8) milliseconds in the lateral tibia in control
participants versus 40.1 (SD⫽5.9)
milliseconds in the lateral femur and
32.3 (SD⫽6.2) milliseconds in the
lateral tibia in participants with OA.
Higher T2 values are associated with
early degeneration even before macroscopic changes are present.43 An
ex vivo study of unicompartmental
OA confirmed that cartilage in unaffected compartments was mechanically inferior to normal cartilage
despite sound clinical, radiographic,
and morphological appearances.59
Hence, the tendency toward ultrastructural deterioration in these lateral compartments may have brought
about the larger volume decreases
immediately after the exercise.
Interestingly, although the present
study included people with radiographic signs of medial compartAugust 2013
ment OA, it did not reveal betweengroup differences for the medial
cartilage plates. In contrast, in previous in vivo static loading experiments, the medial compartments in
people with OA were driving the
larger thickness decreases.27,32 However, the fact that those particular
studies included people with K/L
grades of at least 2, as opposed to the
maximum K/L grade of 2 in the present study, and therefore with more
advanced disease, may have enabled
more evident differences to be established between groups.
In agreement with Cotofana et al,27
we found similar subregional spatial
deformation patterns in healthy and
diseased knees27; the largest deformation was observed in the posterior femoral condyles and anterior
tibial plateaus. Kinematic analyses
showed that during increasing knee
flexion, tibiofemoral contact areas
shifted to the posterior femur.60,61
Although this observation may
explain the femoral spatial deformation patterns in the present study,
the anteriorly directed deformation
patterns on the tibial plateaus may
have resulted from altered tibial rotation during knee flexion in the presence of increasing age and OA.62
In participants who are healthy,
next to femoral roll-and-glide motion
and tibial valgus, coupled tibial internal rotation accounts for increased
anterior and posterior loads on
the medial tibial cartilage and lateral
tibial cartilage, respectively. In older
participants with OA, decreased
axial rotation with more apparent
diminished rollback of the lateral
femur over the tibial plateau has
been observed.62 Therefore, tibiofemoral contact may have occurred
more anteriorly during flexion movements, increasing the load on the
anterior regions of both tibial cartilage plates.
Early recovery encompasses the
most important and critical changes
after pressure release.38,63 Recovery
appeared to be similar in both
groups (ie, the mean betweengroup differences of 0.2%–2.3% did
not reach or exceed the required
difference of ⬃3%). However, the
course of volume changes presented
in Table 2 suggested a tendency
toward slower recovery in participants with OA than in control participants. Recovery required at least
15 minutes for all tibiofemoral cartilage plates, including the lateral knee
compartment, to return to baseline
morphological status. Delayed recovery may induce a state of maintained
deformation and dehydration, which
may have deleterious effects on
chondrocyte metabolism.28,29 Therefore, hasty load repetitions may
induce a negative cycle toward progressive degeneration.
The results of the present study
should be interpreted in view of the
relatively limited sample size and limited generalizability of the findings.
The recruited participants had radiographic signs of doubtful to mild OA,
with low levels of pain, and the
majority were men.
For the present study, we intentionally did not recruit participants with
moderate to severe OA (ie, K/L
grades 3 and 4). Because of heterogeneous symptomatic and structural
OA presentations, the effects of
exercise should be investigated in
subgroups rather than in the aggregate group of people with OA.64
Although shifting the focus of OA
management to include people at
increased risk for OA development
or progression as well as people with
established disease has been suggested,65 rat models of experimentally induced OA showed that exercise initially led to the suppression
of inflammation and the promotion
of matrix synthesis. When OA progressed over time, exercise appeared
to have effects similar to those in
nonexercised joints or appeared to
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1057
aggravate catabolic responses, promoting joint deterioration.66,67
As indicated by subregional analysis,
the squatting exercise in the present study induced general dynamic
joint loading, which may have facilitated matrix synthesis.56 –58 Although
from a clinical point of view this
exercise is usually not included in
exercise programs for people with
advanced and severe OA, unstable
knees, malaligned knees, patellofemoral arthritis, or a combination of
these conditions because of pain
aggravation, it is commonly incorporated in therapeutic programs to
rehabilitate neuromuscular control
and functional strength in people
with meniscal degeneration (eg, the
SCOPEX trial, including people with
K/L grades 1 and 2)—like those
recruited in the present study— or
after partial meniscectomy.10,30,68,69
Although in these particular populations of people with doubtful to mild
OA, weight-bearing exercises, such
as squatting, were shown to improve
physical function and potentially cartilage integrity,10,30,69,70 these people, in turn, had an increased risk of
accelerated OA progression.31
At the time of the present study,
however, participants did not
exhibit considerable levels of pain.
In view of the clinical presentation
of people seeking treatment, the relevance of the investigated population may be questioned. The perception of disease does not correlate
well with joint health status,7,8 and
symptoms are known to fluctuate
over time and to display large interindividual variations.71,72 The constructs for pain intensity (ie, VAS
and WOMAC) in the present study
were based on a 1-week history,
at the most, and the data were collected at the time of the study.
Hence, the pain intensity measures
did not cover the participants’
entire history of symptomatic knee
OA. Although the participants were
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f
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Volume 93
recruited from an outpatient setting at our university hospital—and,
therefore, were seeking treatment
for their condition—and the mean
duration of self-reported knee symptoms was 40 months, the clinical relevance of the population in the present study is supported.
The clinical relevance of the present
study is that when weight-bearing
exercises, such as squatting, are considered to be clinically feasible and
are applied in people who are
middle-aged and have doubtful to
mild OA, clinicians must be aware
of the discordance between symptomatic responses and potentially
disproportionate cartilage deformation behavior, which may incite a
downward spiral toward accelerated cartilage degeneration. Hence,
the results of the present study
may have implications for the design
of exercise therapy programs for
these particular groups of people.
Ideally, after a full-weight-bearing
30-repetition squat, people who are
middle-aged should allow approximately 15 minutes for tibiofemoral
cartilage volumes to recover, especially if they have radiographic
signs of doubtful to mild OA. In
this way, cartilage recovery can sufficiently protect against progressive deterioration.28,29 Translation of
these findings to clinical practice
may entail shorter exercise sessions
at a higher frequency over the
course of the day, alternating
between weight-bearing and non–
weight-bearing exercises, and alternating use of assisted weight-bearing
exercises (such as seated leg presses,
assisted weight-bearing squatting
under a vertical pulley apparatus,
and aquatic exercises). Nonetheless, future research should continue to investigate the long-term
effects of structured therapeutic
exercise regimens on cartilage structural integrity.
Number 8
Finally, the sex distribution in the
present study did not concur with
the typical presentation of OA in
the community, in which higher
prevalences are recorded in women
than in men.73 In people who are
younger (⬍63 years old)—as in the
present study (ie, 42– 65 years old)—
epidemiological reports have conversely described higher prevalences, higher incidences, or both in
men, supporting the validity of the
population included in the present
study in this developmental OA
stage.73–75 Nonetheless, the analyses
in the present study took sex distribution into account, and the direction of the main results was in agreement with that in studies in which
the participants with OA were all
women.27
Conclusion
After a 30-repetition squatting exercise, tibiofemoral cartilage deformation appeared to be similar in magnitude (within the measurement
error) and spatial pattern in participants who were middle-aged and
either had or did not have radiographic signs of doubtful to mild tibiofemoral OA (ie, K/L grades 1 and
2). Restoration of volumes required
a 15-minute recovery after the exercise, especially in participants with
osteoarthritic cartilage degeneration.
In terms of prevention of accelerated
OA progression, these results may
have implications for dosing and
grading of exercise therapy in people who have doubtful to mild OA
and for whom weight-bearing exercise is considered clinically feasible.
Both authors provided concept/idea/
research design, project management, and
before submission). Ms Van Ginckel provided writing, data collection and analysis,
study participants, and facilities/equipment.
Dr Witvrouw provided fund procurement
and institutional liaisons. The authors gratefully acknowledge Greta Vandemaele, PhD,
for implementation of parameters for the
August 2013
magnetic resonance imaging sequences
used in this study.
This study was approved by the Ethical Committee of Ghent University Hospital.
This study was funded by the Research Foundation of Flanders (FWO Vlaanderen).
DOI: 10.2522/ptj.20120491
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34 Kellgren JH, Lawrence JS. Radiological
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36 Van Ginckel A, Almqvist F, Verstraete K,
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37 Van Ginckel A, Baelde N, Almqvist KF,
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38 Van Ginckel A, Roosen P, Almqvist KF,
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40 Guermazi A, Niu J, Hayashi D, et al. Prevalence of abnormalities in knees detected
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42 Bingham JT, Papannagari R, Van de Velde
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43 Apprich S, Mamisch TC, Welsch GH, et al.
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44 Eckstein F, Lemberger B, Gratzke C, et al.
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45 Eckstein F, Lemberger B, Stammberger T,
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46 Hudelmaier M, Glaser C, Hohe J, et al.
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47 Sled EA, Khoja L, Deluzio KJ, et al. Effect
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48 Witvrouw E, Danneels L, Thijs Y, et al.
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49 Neeb TB, Aufdemkampe G, Wagener JH,
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50 Roorda LD, Jones CA, Waltz M, et al. Satisfactory cross cultural equivalence of the
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52 Bowers ME, Trinh N, Tung GA, et al.
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54 Wirth W, Eckstein F. A technique for
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55 Herberhold C, Faber S, Stammberger T,
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56 Suh JK, Li Z, Woo SL. Dynamic behavior of
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58 Jeon JE, Schrobback K, Hutmacher D,
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59 Obeid EM, Adams MA, Newman JH.
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60 von Eisenhart-Rothe R, Siebert M, Bringmann C, et al. A new in vivo technique
for determination of 3D kinematics and
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tibio-femoral joint. J Biomech. 2004;37:
927–934.
61 Patel VV, Hall K, Ries M, et al. A threedimensional MRI analysis of knee kinematics. J Orthop Res. 2004;22:283–292.
62 Scarvell JM, Smith PN, Refshauge KM, Galloway HR. Magnetic resonance imaging
analysis of kinematics in osteoarthritic
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63 Rubenstein JD, Kim JK, Henkelman RM.
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bovine articular cartilage: appearance on
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64 Minor MA. Physical activity and knee
osteoarthritis: answers and questions.
Arthritis Rheum. 2007;57:1–2.
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65 Hunter DJ. Lower extremity osteoarthritis
management needs a paradigm shift. Br J
Sports Med. 2011;45:283–288.
66 Nam J, Perera P, Liu J, et al. Effects of
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67 Perera P, Nam J, Friezner S, Agarwal S.
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68 Hall M, Hinman RS, Wrigley TV, et al. The
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69 Thorstensson CA, Henriksson M, von Porat
A, et al. The effect of eight weeks of exercise
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The relationship of joint symptoms with
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71 Paradowski PT, Englund M, Roos EM,
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72 Paradowski PT, Englund M, Lohmander
LS, Roos EM. The effect of patient characteristics on variability in pain and function
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73 Felson DT, Zhang YQ. An update on the
epidemiology of knee and hip osteoarthritis with a view to prevention. Arthritis
Rheum. 1998;41:1343–1355.
74 Felson DT. The epidemiology of knee
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Rheum. 1990;20:42–50.
75 Bijlsma JW, Knahr K. Strategies for the
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Res Clin Rheumatol. 2007;21:59 –76.
August 2013
Research Report
Incidence and Factors Associated With
Falls in Independent Ambulatory
Individuals With Spinal Cord Injury:
A 6-Month Prospective Study
Sirisuda Phonthee, Jiamjit Saengsuwan, Wantana Siritaratiwat,
Sugalya Amatachaya
Background. Sensorimotor impairments following spinal cord injury (SCI) affect
mobility and subsequently increase the risk of falls to patients. However, most of the
fall data for these patients were retrospectively gathered.
Objectives. This study prospectively assessed falls and intrinsic factors associated
S. Phonthee, PT, MSc, School of
Physical Therapy, Faculty of Associated Medical Sciences, and
Improvement of Physical Performance and Quality of Life (IPQ)
Research Group, Khon Kaen University, Khon Kaen, Thailand.
with falls in 89 independent ambulatory individuals with SCI over the course of 6
months. In addition, functional ability between participants who did and did not fall
was compared.
J. Saengsuwan, NU, PhD, IPQ
Research Group and Faculty of
Public
Health,
Khon
Kaen
University.
Methods. Participants were interviewed and assessed for their baseline data and
W. Siritaratiwat, PT, PhD, School
of Physical Therapy, Faculty of
Associated Medical Sciences; IPQ
Research Group; and Back, Neck
and Other Joint Pain (BNOJP)
Research Group, Khon Kaen
University.
functional ability using the Timed “Up & Go” Test and the Six-Minute Walk Test. Then
they were interviewed by telephone to complete a self-report questionnaire once per
week to gather fall data for 6 months. A stepwise multiple logistic regression was
utilized to determine the effects of demographics and SCI characteristics on occurrence of falls. The functional data between participants who fell and those who did
not fall were compared using the Mann-Whitney U test.
Results. Thirty-five participants (39%) experienced at least 1 fall during 6 months
(range⫽1–11). Two participants required medical attention due to patellar and
sternum fractures after falling. Participants with an educational level of high school
graduate or greater, an American Spinal Injury Association Impairment Scale C (AIS-C)
classification, and a fear of falling (FOF) significantly increased their risk of falls
approximately 4 times more than those who graduated primary education, had an
AIS-D classification, and did not have FOF. Moreover, the functional abilities of
participants who fell were significantly poorer than those who did not fall.
Limitations. The sample size was calculated based on the primary objective
(incidence of falls), which may not be sufficient to clearly indicate factors associated
with falls for the participants.
Conclusions. More than one third of the independent ambulatory participants
with SCI experienced at least 1 fall during the 6-month period of the study. The
findings suggest the importance of functional improvement on the reduction of fall
risk in these individuals.
S. Amatachaya, PT, PhD, School of
Physical Therapy, Faculty of Associated Medical Sciences, and IPQ
Research Group, Khon Kaen University, Khon Kaen, 40002 Thailand. Address all correspondence
to Dr Amatachaya at: samata@
kku.ac.th.
[Phonthee S, Saengsuwan J,
Siritaratiwat W, Amatachaya S.
Incidence and factors associated
with falls in independent ambulatory individuals with spinal
cord injury: a 6-month prospective study. Phys Ther. 2013;93:
1061–1072.]
Association
April 18, 2013
this article at:
ptjournal.apta.org
August 2013
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Physical Therapy f
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Falls in Ambulatory Individuals With Spinal Cord Injury
M
ore than half of patients
with spinal cord injury (SCI)
have an incomplete lesion.
Although 80% of these patients can
regain ambulatory ability after rehabilitation, sensorimotor dysfunctions
following SCI affect the quality and
degree of ambulation and increase
risk of falls in these individuals.1,2
Krause3 reported that individuals
with SCI had a high rate of subsequent injuries due to a variety of
causes, including falls. That study,
however, considered injuries due to
a variety of causes and did not investigate falls exclusively. Brotherton
et al4 retrospectively surveyed falls
in 119 independent ambulatory individuals with SCI and found that 75%
(n⫽89) sustained at least 1 fall in a
year. After falls, 18% of these individuals experienced fractures, and 45%
had restricted ability to function
independently in the community and
engage in productive activities.4 The
researchers also found that exercise
frequency and walker use significantly reduced the risk of falls.5
However, the data were retrospectively gathered using a mail survey
and subjectively reported by the participants, with a large number of
nonresponders (46%). Later, Amatachaya et al6 reported that 74% of
independent ambulatory individuals
with incomplete SCI experienced at
least 1 fall in 6 months (range⫽1–
24), and 1 individual had a metatarsal
fracture that required limited weight
bearing for 2 weeks. However, the
study recruited only 23 independent
ambulatory individuals with incomplete SCI and reported incidence of
falls as a factor relevant to functional
alteration after discharge.6 Recently,
Phonthee et al7 also retrospectively
gathered data on falls and found that
34% of independent ambulatory individuals with SCI experienced falls
during 6 months before participation
in the study (range⫽1– 6) and that
individuals who experienced a fall
had better functional ability than
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those who did not fall. The researchers suggested that better functional
ability may increase the integration
of walking while performing daily
activities that expose people to a
high risk of falls.7
Until now, most studies relating to
falls in independent ambulatory
people with SCI retrospectively
reported the data3,4,7 or recruited a
small number of participants.6 Moreover, participants in these studies3,4,6,7 indicated impairments of
balance and walking ability as major
causes of falls. However, the data
were subjectively reported by the
participants, which might have
reduced the strength of the findings.
Therefore, a further study using prospective fall data collection with the
incorporation of objective assessments relating to falls would ensure
the validity of the findings and direct
the application of proper rehabilitation strategies to improve safety
issues for the patients.
The impairments of balance and
walking ability can be quantitatively
measured using the Timed “Up &
Go” Test (TUG) and the Six-Minute
Walk Test (6MWT). The TUG incorporates many complex tasks that
reflect ability of dynamic balance
control. The 6MWT is one of the
most thorough measures, and the
results correlate with many walking
ability tests, such as the Walking
Index for Spinal Cord Injury II
(WISCI-II) and the 10-Meter Walk
Test (10MWT).8 –10 This study prospectively assessed the incidences,
circumstances, consequences, and
intrinsic factors associated with falls
in independent ambulatory people
with SCI over 6 months and compared the functional ability between
participants who fell and those who
did not fall using the TUG and
6MWT.
Number 8
Method
Participants
This study prospectively monitored
data on falls over 6 months in a
cohort of independent ambulatory
individuals with SCI from several
communities in Thailand. The participants had an SCI either from traumatic causes or nonprogressive diseases at a subacute or chronic stage
of injury. In addition, they needed to
be at least 18 years of age and have
the ability of independent walking
over at least 17 m with or without a
walking device (Functional Independence Measure [FIM] locomotor subscale score of 5–7).8 Exclusion criteria included the inability to read Thai
and having an SCI from a progressive
disease or other medical conditions
that might affect ambulatory ability,
such as visual deficits, pain in the
musculoskeletal system with a pain
scale more than 5 out of 10 on a
visual analog scale, leg length discrepancy, or deformities in the joints
of the lower extremities. Eligible participants provided written informed
consent prior to taking part in the
study.
Ninety-one independent ambulatory
patients with SCI agreed to participate in this study. However, 2
individuals were lost during the
follow-up period because they had
changed their telephone numbers;
therefore, 89 participants completed
the study (Fig. 1). Most of the participants were men, had a chronic or
mild severity of SCI (American Spinal
Injury Association Impairment Scale
D [AIS-D]) from a nontraumatic
cause, and required a walking
device. Table 1 presents baseline
demographics and characteristics of
SCI of the participants.
Protocols of the Study
Participants were interviewed and
assessed for baseline demographics,
SCI characteristics, and self-perceived
health status using a self-report
questionnaire (Appendix) that was
August 2013
TUG. Participants were instructed
to stand up from a chair with armrests; walk around a traffic cone,
which was located 3 m away from
the chair; and return to the sitting
position in the chair, at a maximum
and safe speed, with or without a
walking device.11,12 The amount of
time from the command “go” until
the participant’s back was against
the backrest was recorded.
91 independent ambulatory
patients with spinal cord injury
agreed to participate in the study
2 participants were lost
to follow-up in the
second month
89 participants completed the study
6MWT. Participants were required
to walk along a rectangular walkway
for as long as possible in 6 minutes.
During the test, participants were
allowed to rest as needed, without
stopping the timer, and continued
walking as soon as they could. Every
1 minute during the test, participants
were informed about the time left
and offered encouragement. The distance covered in 6 minutes was
recorded.8,9
35 participants experienced at least
1 fall (39%, range=1–11 times)
54 participants did
not fall (61%)
Figure 1.
Flowchart of study participants.
developed from data of previous
studies.4,6,7 Then, the content validity of the questionnaire was judged
subjectively through the method of
expert panel discussion using 4 rehabilitation experts (2 physical therapists, a nurse, and a physician) who
had extensive clinical experience in
treating patients with neurological
conditions. Subsequently, the ques-
tionnaire was preliminarily tested in
10 independent ambulatory patients
with SCI. Thereafter, some items
were deleted, modified, or rearranged to improve the clarity and
completeness of the questionnaire.
Then participants were assessed for
their functional ability using the TUG
and 6MWT. Details of the tests are
below.
Following the test, participants
received a fall diary (see part 3.1 in
the Appendix) to daily record data
relating to falls at home, and the
researcher (S.P.) telephoned them
weekly to interview and summarize
the data for the week. Data on the
occurrence of falls, including date,
time, place, circumstances, and con-
Table 1.
Baseline Demographics and Spinal Cord Injury Characteristics of the Participants
Total
(nⴝ89)
Nonfallers
(nⴝ54)
Fallers
(nⴝ35)
P
Age (y)a
53.0 (43.0–60.0)
54.0 (43.0–63.0)
50.0 (40.0–58.0)
.129
Postinjury time (m)a
42.0 (15.5–72.0)
36.0 (13.5–72.0)
48.0 (24.0–72.0)
.559
60 (67)
33 (61)
27 (77)
.115
34 (38)
20 (37)
14 (40)
.779
76 (85)
46 (85)
30 (86)
.945
28 (31)
16 (57)
12 (43)
.644
29 (33)
14 (48)
15 (52)
.096
36 (40)
22 (61)
14 (39)
.945
Variable
Sex: male (n [%])b
Cause: traumatic (n [%])
b
Stage of injury: chronic (n [%])b
Level of injury: tetraplegia (n [%])
b
AIS class: AIS-C (n [%])b,c
Using a walking device: no (n [%])
b
a
The data are presented using median (interquartile range: Q1–Q3), the data between fallers and nonfallers were compared using the Mann-Whitney U
test.
b
The variables are categorized as follows: sex: male/female; cause: traumatic/nontraumatic; stage of injury: subacute/chronic; level of injury:
tetraplegia/paraplegia; AIS class: AIS-C/AIS-D; use of a walking device: yes/no. The data between participants who did and did not fall were compared using
the chi-square test.
c
AIS⫽American Spinal Injury Association (ASIA) Impairment Scale.
August 2013
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Physical Therapy f
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Table 2.
Fall Data: Time, Place, Circumstances, and Factors Inducing Falls as Perceived by the
Participants
No. of Fallsa
(n [%])
Fall Data
Period of falls
Morning
46 (47)
Afternoon
23 (24)
Evening
17 (17)
Night
12 (12)
Location of falls
Within the house
42 (43)
Immediate surroundings of the house
37 (38)
Community
13 (13)
Workplace
6 (6)
Activities during falls
Changing posture
23 (23)
Standing
1 (1)
Walking
74 (76)
Factors inducing falls as perceived by the participants
Loss of balance
21 (21)
Lower limb muscle weakness
32 (33)
Environmental hazard
42 (43)
Less attention during movement
a
3 (3)
The total number of falls was 98.
sequences, were gathered during
the telephone interviews. To ensure
information accuracy, the findings
were confirmed by caregivers or relatives. If there was any conflicting
information between the participant
and caregiver, the researcher relied
on the data that were consistent
with those in the fall diary. For the
purposes of this study, a fall was
defined as an unplanned, unexpected, or unintentional event that
occurred during standing, walking,
or changing posture and resulted in
a person coming to rest on the
ground or other lower or supporting
surface.5,6
Data Analysis
Descriptive statistics were applied
to explain baseline demographics,
SCI characteristics, and findings of
the study. The data between participants who fell and those who did not
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Volume 93
fall were compared using the MannWhitney U test for continuous variables and the chi-square test for categorical data. The stepwise multiple
logistic regression analysis was utilized to determine effects of independent variables (including age,
sex, living arrangements, having a
caregiver, level of education, cause
of SCI, level of SCI, severity of SCI,
the requirement of a walking device,
current perceived health when
compared with a previous year, and
fear of falling [FOF]) on the occurrence of falls. The results were
reported as an adjusted odds ratio
(aOR) with corresponding 95% confidence intervals (95% CI) and Beta
(␤) coefficients with the standard
error around the Beta coefficient.
The aOR provides information about
the increase or decrease in the possibility of falls given that the independent variable has occurred when
Number 8
controlling for other independent
variables in the model. An aOR of
less than 1 indicates a decrease in the
chance that the fall will occur given
that the independent variable occurs
(a protective factor). On the contrary, an aOR of greater than 1 indicates an increase in the chance that
the fall will occur given that the independent variable occurs (a risk factor). The Beta coefficients represent
the log of the aOR or the influence of
independent variables on the occurrence of falls.13 The level of significance was set at P⬍.05.
This study was supported by funding
from the Faculty of Associated Medical Sciences, the Improvement of
Physical Performance and Quality of
Life (IPQ) research groups, and the
Graduate School, Khon Kaen University, Khon Kaen, Thailand.
Results
Incidence, Circumstances, and
Consequences of Falls
Thirty-five participants experienced
at least 1 fall in 6 months (range⫽1–
11) (Fig. 1), and the total number of
falls was 98. Table 2 presents circumstances of falls in which most of the
falls occurred while walking within
the house and its immediate surroundings (n⫽74) (areas of falls
within the house included the bedroom [n⫽11], bathroom [n⫽15],
walkway in the house [n⫽14], and
kitchen [n⫽2]), during the morning
to afternoon time (5:00 am– 4:59
pm). Participants indicated lowerlimb muscle weakness and environmental hazards (ie, uneven surface
[n⫽10], slippery floor [n⫽18], and
obstacle on the floor [n⫽14]) as
major causes of falls (Tab. 2). Most
participants reported no serious consequences after falling. Two participants, however, had fractures: one
participant had a patellar fracture
that needed rehospitalization for 14
days with limited weight bearing,
and another participant had a sterAugust 2013
Figure 2.
Physical, functional, and psychological consequences of falls.
num fracture that required readmission for 5 days (Fig. 2).
Factors Associated With Falls
Data of stepwise logistic regression
analysis indicated that living arrangements, having a caregiver, level of
education, level of SCI, severity of
SCI, the requirement of a walking
device, current perceived health
when compared with a previous
year, and FOF were the best predictors for the occurrence of a fall
(Tab. 3). Among these variables, at
least high school graduation, having
an AIS-C classification, and having
FOF significantly increased risk of
falls by approximately 4 times compared with those who graduated primary education, had an AIS-D classification, and did not have FOF
(P⬍.05) (Tab. 3).
Table 3.
Data on Factors Associated With Falls in Independent Ambulatory Participants With Spinal Cord Injurya
Variableb
Marital status: did not have a couple
Total
(nⴝ89)
Nonfallers
(nⴝ54)
n (%)
Fallers
(nⴝ35)
n (%)
33
16 (48)
17 (52)
␤
Coefficient
0.78
SE
0.52
aOR (95% CI)
P
2.18 (0.78–6.07)
.134
Having a caregiver: yes
57
34 (60)
23 (40)
0.92
0.60
2.51 (0.77–8.11)
.121
Level of education: ⱖhigh school
31
13 (42)
18 (58)
1.49
0.56
4.43 (1.48–13.24)c
.008
Level of injury: tetraplegia
28
16 (57)
12 (43)
⫺0.66
0.63
0.52 (0.15–1.77)
.293
AIS class: AIS-C
29
14 (48)
15 (52)
1.49
0.69
4.45 (1.16–17.11)c
.030
Using a walking device: no
36
22 (61)
14 (39)
0.95
0.66
2.58 (0.71–9.46)
.152
Health status compared to a previous year: worse
13
5 (38)
8 (62)
1.00
0.76
2.72 (0.62–11.98)
.186
Fear of falling: yes
60
41 (68)
29 (48)
1.42
0.72
4.16 (1.02–16.90)c
.047
a
SE⫽standard error, aOR⫽adjusted odds ratio, 95% CI⫽95% confidence interval, AIS⫽American Spinal Injury Association (ASIA) Impairment Scale.
b
The variables are categorized as follows: marital status: did not have a couple (reference group)/have a couple; having a caregiver: no (reference group)/
yes; educational level: primary school (reference group)/at least high school; injury level: paraplegia (reference group)/tetraplegia; AIS class: AIS-D (reference
group)/AIS-C; using a walking device: yes (reference group)/no; health status compared with a previous year: same-better (reference group)/worse; fear of
falling: no (reference group)/yes.
c
aOR is significantly different from the reference group for which the value was set at 1.0 (P⬍.05).
August 2013
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Physical Therapy f
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Discussion
This study prospectively investigated
falls and associated factors in 89
independent ambulatory individuals
with SCI. The findings showed that
39% of the participants experienced
at least 1 fall during 6 months
(range⫽1–11/participant). The falls
mostly occurred while participants
were walking, during morning to
afternoon hours, and within the
house and its immediate surroundings (Tab. 2). After falls, 2 participants had fractures that needed medical attention. Participants with an
educational level of at least high
school graduation with an AIS-C
classification and FOF significantly
increased their risk of falling by
approximately 4 times compared
with those who graduated primary
school, had an AIS-D classification,
and did not have FOF (P⬍.05)
(Tab. 3). The TUG and 6MWT data
indicated that participants who fell
had significantly poorer functional
ability than those who did not fall
(P⬍.05) (Fig. 3).
Figure 3.
Data of functional tests in fallers and nonfallers for the (A) Timed “Up & Go” Test and
the (B) Six-Minute Walk Test with P values from the Mann-Whitney U test.
Functional Ability in Participants
Who Fell and Those Who Did
Not Fall
TUG. The TUG data of 6 participants were considered outliers (the
data that were more than 1.5 times
of the interquartile range: Q1–Q3);14
thus, the data were analyzed in 83
participants. The findings indicated
that individuals who fell required a
significantly longer time to complete
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Volume 93
the TUG compared with those who
did not fall (P⬍.05) (Fig. 3A).
6MWT. The 6MWT data of 2 participants were considered outliers;
thus, the data were analyzed in 87
participants. The findings suggest
that individuals who did not fall
could walk a significantly longer distance, within a 6-minute period, than
those who fell (P⬍.05) (Fig. 3B).
Number 8
The incidence of falls found in this
study was less than that reported
previously.4,6 The differences may
relate to study design, follow-up
period, and sample size. The present
study used prospective fall data collection every week for 6 months. A
prospective design allows data gathering, from exposure to outcome,
that can establish a temporal relationship of the observed events.15
However, frequent follow-up of the
fall data may lead to the “Hawthorne
effect,” which commonly occurs
when individuals know that they are
being observed and temporarily
change their behavior.15 This may
be a reason that the incidence of falls
found in this study (39%) was less
than that of previous reports (74%–
75%).4,6 However, the findings were
similar to those recently reported
(34%) in a study using retrospective
face-to-face interviews to gather fall
data during a 6-month period.7
August 2013
The sensorimotor deterioration following SCI and inappropriate environmental conditions may have limited the ability of the individuals to
participate in the community. Therefore, the falls frequently occurred at
home (within the house and its
immediate surroundings). In addition, the time of falls was associated
with the duration of the performed
exercises and physical activities
(subjective data from the self-report
questionnaire). After falling, 2 participants experienced fractures that
needed medical attention. The finding was in agreement with those of
previous studies that also reported
that individuals had experienced
fractures after falls.4,6,7 The findings
emphasize the serious consequences
after falls and the need for a proper
rehabilitation strategy or management to improve safety issues, particularly while walking in actual environments, of these individuals.
The findings indicate that participants who achieved at least high
school graduation and had an AIS-C
classification and FOF significantly
increased their risk of falling by
approximately 4 times compared
with those who completed primary
school education and had an AIS-D
classification and FOF (P⬍.05)
(Tab. 3). Regidor et al16 reported that
educational level is associated with
attention to health status. Individuals
with a high educational level may
increase attention to their health status and thus move more frequently
in order to improve their functional
ability. However, sensorimotor dysfunctions following SCI may distort
their ability to move safely; hence,
they may increase their exposure to
fall opportunities. This assumption
was associated with the subjective
data that the participants indicated
the impairments of balance control
and lower-limb muscle strength and
environmental hazards as major
causes of falls (Tab. 2). Similarly,
Brotherton et al5 also found that a
August 2013
high educational level (at least a
bachelor’s degree) significantly
increased unadjusted odds ratios for
the fall risk of independent ambulatory individuals with SCI.
Having an AIS-C classification and
FOF also significantly increased the
risk of falls (P⬍.05) (Tab. 3). A level
of severity is associated with a
degree of sensorimotor impairments
and a level of functioning. Harkema
et al17 reported that individuals with
an AIS-C classification had significantly poorer balance and functional
ability than those with an AIS-D classification as determined using the
Berg Balance Scale, 10MWT, and
6MWT. A lower level of functioning
also may increase the level of FOF
and decrease a person’s confidence
in his or her ability to engage in a
daily activity. In other words, fear of
falling frequently occurs in individuals with low levels of functioning
that subsequently reduces their selfconfidence in movement control.18,19 Low levels of functioning
also have been recognized as a risk
factor for falls in elderly people and
individuals with stroke and SCI.5,20,21
Brotherton et al5 found that exercise
frequency significantly reduced risk
of falls in independent ambulatory
individuals with SCI. The researchers
suggested that the implementation
of an exercise program may help to
improve health status, reduce the
number of medical conditions, and
increase confidence in the ability to
engage in community activities, and
thus the individuals have decreased
risk of falls.5
The findings of the TUG and 6MWT
also emphasize the importance of
good functional ability on the reduction of fall risk in these individuals
(Fig. 3). The TUG incorporates many
complex tasks (ie, standing up, walking, turning, and sitting down) that
may reflect daily activities and balance control while walking more
accurately than the 10MWT.9 The
longer time required to complete the
TUG (Fig. 3A) indicates that the participants who fell had poorer balance control than those who did not
fall.11,12 A long-distance walking test,
such as the 6MWT, is a thorough
investigation for functional endurance and a good predictor of habitual walking9,22,23
Guimaraes and Isaacs24 found that
during a short-distance walking test,
such as the Six-Meter Walk Test, individuals who fell showed a trend
toward increased step length variability (ie, unsteadiness or inconsistency and arrhythmicity of stepping).
On the contrary, while performing
the 6MWT, participants who fell
demonstrated significantly greater
gait variability than those who did
not fall in which the gait unsteadiness, or variability, had been indicated as an important predictor for
the increased risk of falls.25 Van
Hedel et al10 also found that the
results of the TUG and 6MWT had
good to excellent correlation with
other walking tests such as the
10MWT (r⫽.89 for the TUG and
␳⫽⫺.95 for the 6MWT) and the
WISCI II (␳⫽⫺.76 for the TUG and
␳⫽.60 for the 6MWT). However, the
findings in this study were different
from those reported by Phonthee et
al,7 who found that the TUG and
6MWT data of the individuals who
fell were significantly better than
those of the individuals who did not
fall. The different findings may relate
to the study designs in which the
measurements of functional ability
were executed before (for a prospective study) and after (for a retrospective study) falls. Therefore, a further
investigation to indicate functional
alteration of individuals who did and
did not fall with SCI may help to
support the findings.
Currently, there is a trend toward
considerably decreasing the rehabilitation period of these patients (from
115 days in 1974 to 36 days in
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2005).26,27 Therefore, it is likely that
patients cannot reach an optimal
level of ability at the time of discharge27 and have increased risk of
falling and subsequent injury. Thus,
the present findings emphasize the
importance of the exploration for
rehabilitation strategies or management to improve ability of movement control and safety for these
patients. However, the data contain
several noteworthy limitations. The
study used frequent prospective
follow-up fall data with confirmation
from caregivers or relatives in order
to improve data accuracy. However,
frequent follow-up periods may
affect a natural lifestyle (eg, frequent
follow-up could increase conscious
awareness of movements that influences the incidence of falls). Also,
the sample size was calculated based
on the primary objective (to investigate incidence of falls), which may
not be sufficient to clearly indicate
factors associated with falls for the
participants. Furthermore, the data
of the functional tests (TUG and
6MWT) indicate functional impairments, not the impairments of the
body systems, affecting falls. Thus, a
further study using unscheduled
follow-up of the fall data in a greater
number of participants with the
assessments of system impairments
influencing falls (ie, muscle strength,
sensation, and spasticity) may
strengthen the findings.
All authors provided concept/idea/research
design and data analysis. Ms Phonthee and
Dr Amatachaya provided writing. Ms
Phonthee provided data collection. Dr Amatachaya provided fund procurement and
facilities/equipment. Dr Saengsuwan provided consultation (including review of manuscript before submission). The authors
thank Mr Ian Thomas for his help in preparing the manuscript.
This study was approved by the Khon Kaen
University Ethics Committee for Human
Research.
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This study was supported by funding from
the Faculty of Associated Medical Sciences,
the Improvement of Physical Performance
and Quality of Life (IPQ) research groups,
and Graduate School, Khon Kaen University,
Khon Kaen, Thailand.
DOI: 10.2522/ptj.20120467
References
1 Wyndaele M, Wyndaele JJ. Incidence,
prevalence and epidemiology of spinal
cord injury: what learns a worldwide literature survey? Spinal Cord. 2006;44:523–
529.
2 Field-Fote EC. Spinal cord control of movement: implications for locomotor rehabilitation following spinal cord injury. Phys
Ther. 2000;80:477– 484.
3 Krause JS. Factors associated with risk for
subsequent injuries after traumatic spinal
cord injury. Arch Phys Med Rehabil. 2004;
85:1503–1508.
4 Brotherton SS, Krause JS, Nietert PJ. Falls
in individuals with incomplete spinal cord
injury. Spinal Cord. 2007;45:37– 40.
5 Brotherton SS, Krause JS, Nietert PJ. A
pilot study of factors associated with falls
in individuals with incomplete spinal cord
injury. J Spinal Cord Med. 2007;30:243–
250.
6 Amatachaya S, Wannapakhe J, Arrayawichanon P, Siritarathiwat W, et al. Functional abilities, incidences of complications and falls of patients with spinal cord
injury 6 months after discharge. Spinal
Cord. 2011;49:520 –524.
7 Phonthee S, Saengsuwan J, Amatachaya S.
Falls in independent ambulatory patients
with spinal cord injury: incidence, associated factors and levels of ability. Spinal
Cord. 2013;51:365–368.
8 Jackson AB, Carnel CT, Ditunno JF, et al.
Outcome measures for gait and ambulation in the spinal cord injury population.
J Spinal Cord Med. 2008;31:487– 499.
9 van Hedel HJ, Wirz M, Dietz V. Standardized assessment of walking capacity after
spinal cord injury: the European network
approach. Neurol Res. 2008;30:61–73.
10 van Hedel HJ, Wirz M, Dietz V. Assessing
walking ability in subjects with spinal cord
injury: validity and reliability of 3 walking
tests. Arch Phys Med Rehabil. 2005;86:
190 –196.
11 Bischoff HA, Stähelin HB, Monsch AU,
et al. Identifying a cut-off point for normal
mobility: a comparison of the timed ’’up
and go’ test in community-dwelling and
institutionalised elderly women. Age Ageing. 2003;32:315–320.
12 Shumway-Cook A, Brauer S, Woollacott M.
Predicting the probability for falls in
community-dwelling older adults using
the Timed Up & Go Test. Phys Ther. 2000;
80:896 –903.
Number 8
13 Plichta SB, Garzon LS. Statistics for Nursing and Allied Health. Philadelphia, PA:
Lippincott Williams & Wilkins; 2009.
14 Jones J. Stats: measures of position. Available at: http://people.richland.edu/james/
lecture/m170/ch03-pos.html.
Accessed
September 27, 2012.
15 Grimes DA, Schulz KF. Cohort studies:
marching towards outcomes. Lancet.
2002;359:341–345.
16 Regidor E, Dominguez V, Navarro P, Rodriguez C. The magnitude of differences in
perceived general health associated with
educational level in the regions of Spain.
J Epidemiol Community Health. 1999;53:
288 –293.
17 Harkema SJ, Schmidt-Read M, Lorenz DJ,
et al. Balance and ambulation improvements in individuals with chronic incomplete spinal cord injury using locomotor
training-based rehabilitation. Arch Phys
Med Rehabil. 2012;93:1508 –1517.
18 Legters K. Fear of falling. Phys Ther. 2002;
82:264 –272.
19 Cumming RG, Salkeld G, Thomas M,
Szonyi G. Prospective study of the impact
of fear of falling on activities of daily living,
SF-36 scores, and nursing home admission.
J Gerontol A Biol Sci Med Sci. 2000;55:
M299 –M305.
20 Maki BE, Holliday PJ, Topper AK. Fear of
falling and postural performance in the
elderly. J Gerontol.1991;46:M123–M131.
21 Belgen B, Beninato M, Sullivan PE, Narielwalla K. The association of balance capacity and falls self-efficacy with history of
falling in community dwelling people with
chronic stroke. Arch Phys Med Rehabil.
2006;87:554 –561.
22 Gijbels D, Alders G, Van Hoof E, et al. Predicting habitual walking performance in
multiple sclerosis: relevance of capacity
and self-report measures. Mult Scler. 2010;
16:618 – 626.
23 Troosters T, Gosselink R, Decramer M. Six
minute walking distance in healthy elderly
subjects. Eur Respir J. 1999;14:270 –274.
24 Guimaraes RM, Isaacs B. Characteristics of
the gait in old people who fall. Int Rehabil
Med. 1980;2:177–180.
25 Hausdorff JM, Edelberg HK, Mitchell SL,
et al. Increased gait unsteadiness in
community-dwelling elderly fallers. Arch
Phys Med Rehabil 1997;78:278 –283.
26 National Spinal Cord Injury Statistical Center. Facts and Figures at a Glance 2008.
Available at: https://www.nscisc.uab.edu/
PublicDocuments/reports/pdf/Facts08.pdf.
Accessed February 9, 2011.
27 Hall K, Cohen M, Wright J, et al. Characteristics of the Functional Independence
Measure in traumatic spinal cord injury.
Arch Phys Med Rehabil. 1999;80:1471–
1476.
August 2013
Appendix.
Questionnaire for Fall Data Collection of Independent Ambulatory Individuals With Spinal Cord Injurya
ID No
▫▫▫▫▫
Date...../...../.....
General Information: This questionnaire is used to interview and record baseline data and fall information of
independent ambulatory individuals with spinal cord injury (SCI). It is divided into 3 parts.
Part 1: Baseline demographics
Part 2: SCI characteristics, health status, and level of ability
Part 3: Fall information
Part 1: Baseline Demographics
1. Sex
( ) Male
( ) Female
2. Age. . . . . . ..years
3. Marital status
( ) Single
( ) Married
( ) Widowed/separated/divorced
4. Highest level of education obtained
( ) Primary school
( ) High school
( ) ⬎High school
5. Career or work after SCI
( ) Does not work
( ) Works
6. Having a caregiver
( ) No
( ) Yes
7. Exercise (an activity performed for at least 10 minutes continuously)
( ) No
( ) Yes
If yes, please specify type. . . . . . . . . . frequency (times/day). . . . . . . . . . . times
Frequency (times/week). . . . . . . . . . . . times
Time of day and duration: ( ) morning
( ) afternoon
( ) evening for total of. . . . . . . . . . minutes
Part 2: SCI Characteristics, Health Status, and Level of Ability
8. Cause of injury
( ) Traumatic, please indicate. . . . . . . . . . . . . . . . . . . . .
( ) Nontraumatic, please indicate. . . . . . . . . . . . . . . . . .
9. Levels of injury
( ) Incomplete tetraplegia at C. . . . . . . . . . . . . . . . . .
( ) Incomplete paraplegia at T. . . . . . . . . . . . or L. . . . . . . . . . . .
10. Severity of injury (according to the American Spinal Injury Association Impairment Scale [AIS] classification)
( ) AIS-C
( ) AIS-D
(Continued)
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Appendix.
Continued
11. Stage of injury
( ) Subacute stage (ⱕ12 months)
( ) Chronic stage (⬎12 months)
Please indicate length of time since injury. . . . . . . . . . . . . . . months
12. Functional Independence Measure-Locomotion (FIM-L) scores
( ) FIM-L score of 5 (walking with or without a walking device between 17 and 50 m)
( ) With a device, indicate type. . . . . . . . . . . . . . .
( ) Without a device
( ) FIM-L score of 6 (walking with a walking device at least 50 m)
Please indicate type of device. . . . . . . . . . . . . . . . . . .
( ) FIM-L score of 7 (walking without a device at least 50 m)
The longest distance walked (continuously). . . . . . . . . . . . . . . . . . meters (if able to walk longer than 6 minutes,
measure the distance walked in 6 minutes)
13. Average time to complete the Timed “Up & Go” Test (TUG). . . . . . . . . . . . .seconds
14. Perceived current health status
( ) Poor to fair
( ) Good
15. Perceived health status when compared with a previous year
( ) Worse
( ) Same
( ) Better
16. Fear of falling
( ) Not at all
( ) Mild to moderate
( ) Very to most
Part 3: Fall Information
Instructions: The information in this part is divided into 2 subparts: part 3.1, for individuals with SCI to daily record
fall data at home, and part 3.2, for an assessor to gather fall data every week through interview.
Part 3.1: Fall Information Self-Report Form for an Individual With SCI
Instructions: Please record the fall data every day by writing ⻫ for the day with fall, and ⫻ for the day without fall.
If there is any fall, please also record time, place, and consequences of each fall below the table.
Month. . . . . . . . . . . . . . . (March, for example)
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
(Continued)
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Appendix.
Continued
Date
Time
Activity
During Fall
Places
Factor
Inducing Fall*
Physical
Consequences*
Functional
Consequences*
Psychological
Consequences*
* Choose the appropriate number from the information below (can be applied to more than 1 item)
Factor inducing fall
Physical consequences
Subsequent injury
1. Bruise
2. Abrasion
3. Pain
4. Sprain/strain
5. Joint dislocation
6. Fracture
7. Other, indicate . . . .
1. Loss of balance
2. Weakness of the lower extremity muscles
3. Spasticity
4. Impaired sensation
5. Fatigue
6. Less attention during movement
7. Moving too fast
8. Improper footwear
9. Dizziness
10. Alcohol/drug consumption
11. Visual impairments
12. Poor lighting
13. Environmental hazards
14. Bad luck
15. Other, indicate . . . . . . .
Functional consequences
Psychological consequences
1. Decreased self-care ability
2. Limited ability to participate in
a community
3. Limited time out of bed
4. Limited ability to engage in a
productive activity
5. Limited interaction with others
6. Limited ability to earn money
1. Increased level of fear of
falling
2. Decreased confidence in
movements
Treatments
8. Rest
9. Medication
10. Admission for . . . days
Part 3.2: Weekly Fall Data Gathered by Interview
Number of falls: (
(
(
(
(
(
(
)1
)2
)3
)4
)5
)6
)7
Details of falls
Date . . . . . . .
Time of fall
( ) Morning
Indicate time
( ) Afternoon
Indicate time
( ) Evening
Indicate time
( ) Night
Indicate time
.......
.......
(
(
(
(
(
(
(
)8
)9
) 10
) 11
) 12
) 13
) 14
(
(
(
(
(
(
) 15
) 16
) 17
) 18
) 19
) 20 (add more, if needed)
Locations of falls
( ) The house
Indicate where in the
house . . . . . . .
( ) Immediate surroundings of
the house
( ) Community
( ) Workplace
Activities
during falls
Self-perceived factors inducing
falls*
( ) Changing posture
( ) Standing
( ) Walking
( ) Loss of balance
( ) Weakness of the lower extremity
muscles
( ) Spasticity
( ) Impaired sensation
( ) Fatigue
( ) Less attention during movement
( ) Moving too fast
( ) Improper footwear
( ) Dizziness
( ) Alcohol/drug consumption
( ) Visual impairments
( ) Poor lighting
( ) Environmental hazards
( ) Bad luck
( ) Other, indicate . . . . . . .
.......
.......
* More than one item can be applied.
(Continued)
August 2013
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Physical Therapy f
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Appendix.
Continued
Part 3.3: Consequences of each fall
Number of falls: (
(
(
(
(
(
(
)1
)2
)3
)4
)5
)6
)7
(
(
(
(
(
(
(
)8
)9
) 10
) 11
) 12
) 13
) 14
(
(
(
(
(
(
) 15
) 16
) 17
) 18
) 19
) 20 (add more, if needed)
Physical consequences (times)
Subsequent injuries
Medical attention
Functional consequences
( ) No
( ) Yes*
( ) Bruise
( ) Abrasion
( ) Pain
( ) Sprain/strain
( ) Joint dislocation
( ) Fracture
( ) Other, indicate . . . . . . .
( ) No
( ) Yes*
( ) Rest
( ) Medication
( ) Admission for . . . . . . . days
( ) No
( ) Yes*
( ) Decreased self-care ability
( ) Limited ability to participate in a
community
( ) Limited time out of bed
( ) Limited ability to engage in a
productive activity
( ) Limited interaction with others
( ) Limited ability to earn money
Psychological consequences
( ) No
( ) Yes*
( ) Increased level of fear of
falling
( ) Decreased confidence in
movements
* More than 1 item can be applied.
a
The questionnaire may not be used or reproduced without written permission from the authors.
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Research Report
Home-Based Versus In-Hospital
Cardiac Rehabilitation After
Cardiac Surgery: A Nonrandomized
Controlled Study
Simonetta Scalvini, Emanuela Zanelli, Laura Comini, Margherita Dalla Tomba,
Giovanni Troise, Oreste Febo, Amerigo Giordano
Background. Exercise rehabilitation after cardiac surgery has beneficial effects,
especially on a long-term basis. Rehabilitative programs with telemedicine plus
appropriate technology might satisfy the needs of performing rehabilitation at home.
Objective. The purpose of this study was to compare exercise capacity after
home-based cardiac rehabilitation (HBCR) or in-hospital rehabilitation in patients at
low to medium risk for early mortality (EuroSCORE 0 –5) following cardiac surgery.
Design. A quasi-experimental study was conducted.
Methods. At hospital discharge, patients were given the option to decide
whether to enroll in the HBCR program. Clinical examinations (electrocardiography,
cardiac echo color Doppler, chest radiography, blood samples) of patients in the
HBCR group were collected during 4 weeks of rehabilitation, and exercise capacity
(assessed using the Six-Minute Walk Test [6MWT]) was assessed before and after
rehabilitation. A group of patients admitted to the in-hospital rehabilitation program
was used as a comparison group. Patients in the HBCR group were supervised at
home by a medical doctor and telemonitored daily by a nurse and physical therapist
by video conference. Periodic home visits by health staff also were performed.
Results. One hundred patients were recruited into the HBCR group. An equal
number of patients was selected for the comparison group. At the end of the 4-week
study, the 2 groups showed improvement from their respective baseline values only
in the 6MWT. No difference was found in time ⫻ group interaction.
Limitations. Because patients self-selected to enroll in the HBCR program and
because they were enrolled from a single clinical center, the results of the study
cannot be generalized.
Conclusions. In patients who self-selected HBCR, the program was found to be
effective and comparable to the standard in-hospital rehabilitative approach, indicating that rehabilitation following cardiac surgery can be implemented effectively at
home when coadministered with an integrated telemedicine service.
S. Scalvini, MD, Telemedicine
Service, Fondazione Salvatore
Maugeri, Institute for Care and
Scientific Research (IRCCS), Via
Giuseppe Mazzini, 129-25065
Lumezzane, Brescia, Italy. Address
all correspondence to Dr Scalvini
at: [email protected].
E. Zanelli, MD, Cardiology Rehabilitative Division, Fondazione Salvatore Maugeri, IRCCS, Lumezzane, Brescia, Italy.
L. Comini, PhD, Health Directorate, Fondazione Salvatore Maugeri, IRCCS, Lumezzane, Brescia,
Italy.
M. Dalla Tomba, MD, Cardiac Surgery, Fondazione Poliambulanza
Istituto Ospedaliero, Brescia, Italy.
G. Troise, MD, Cardiac Surgery,
Fondazione Poliambulanza Istituto
Ospedaliero, Brescia, Italy.
O. Febo, MD, Cardiology Rehabilitative Division, Fondazione Salvatore Maugeri, IRCCS, Montescano, Pavia, Italy.
A. Giordano, MD, Cardiology
Rehabilitative Division, Fondazione Salvatore Maugeri, IRCCS,
Lumezzane, Brescia, Italy.
[Scalvini S, Zanelli E, Comini L, et
al. Home-based versus in-hospital
cardiac rehabilitation after cardiac
surgery: a nonrandomized controlled study. Phys Ther. 2013;
93:1073–1083.]
Association
April 18, 2013
Submitted: May 28, 2012
this article at:
ptjournal.apta.org
August 2013
Volume 93
Number 8
Physical Therapy f
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R
ehabilitation after cardiac surgery often improves selfassessment and clinical parameters,1 reduces risk factors, and can
increase physical capacity. A 20%
reduction in all-cause mortality and a
27% reduction in cardiac mortality
have been reported in systematic
reviews.2,3 However, despite international guidelines that recommend
cardiac rehabilitation,1 the proportion of patients admitted to a rehabilitative program remains small.4 –7
Mostly, patients are discharged to the
home without any rehabilitation.8
For this reason, home-based cardiac rehabilitation (HBCR) programs
have been introduced in the United
States and some European countries in attempts to increase patient
participation, in particular for older
or socially deprived people, ethnic
minorities, and those from rural
areas who encounter difficulties in
attending center-based facilities.
Home-based cardiac rehabilitation
programs could yield clinical outcomes similar to those of rehabilitation programs, with a possible positive impact on some areas of health
care utilization.9,10
In Italy, formal cardiac rehabilitation is offered within a rehabilitative
hospital.11 However, the inclusion
of patients in rehabilitation programs following surgery differs
among Italian regions. The ISYDE
study,11 designed to provide
a detailed snapshot of cardiac rehabilitation in Italy for patients after a
surgical procedure, shows that inhospital rehabilitation service was
The Bottom Line
Rehabilitation after cardiac surgery often improves quality of life, reduces
cardiovascular disease risk factors, and can increase physical capacity. A
20% reduction in all-cause mortality and a 27% reduction in cardiac
mortality following cardiac rehabilitation also have been reported in
systematic reviews.
This study compared exercise capacity after a home-based cardiac rehabilitation (HBCR) program or an in-hospital program in patients with a low
to medium risk for early mortality after cardiac surgery. The study found
that the HBCR program was feasible, safe, and comparable to the conventional in-hospital rehabilitation approach, indicating that rehabilitation
following cardiac surgery in patients at low risk for early mortality can be
implemented effectively at home when programmed with an integrated
telemedicine service.
for you?
If you are at low risk for early mortality after cardiac surgery, you may
achieve a better quality of life with a complete, supervised rehabilitation
program at home via telemedicine.
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provided by 62.4% of the centers,
whereas outpatient care is provided
on a day-hospital basis by 10.9%
of facilities, with 20% of the centers referring patients to ambulatory
structures.11 Indeed, differences
from region to region are present. In
the Lombardy region, all patients
who have undergone cardiac surgery are admitted for in-hospital
rehabilitation. Moreover, patients
who have undergone cardiac surgery
without complications are allowed
to participate in pilot programs at
home using telemedicine as an alternative to an in-hospital rehabilitation
program. In particular, all patients
discharged 5 to 10 days after cardiac
surgery stayed at a rehabilitative center for a mean period of 18 days.12
Up to 2006, in the Lombardy region,
all patients after cardiac surgery
followed an in-hospital rehabilitation program. From 2006 onward,
a regional project (CRITERIA) proposed, at an experimental level, an
HBCR program with telemedicine to
follow up patients at low to medium
risk for early mortality after cardiac
surgery at home.
Telemedicine and application of
information and communication
technology in the health system have
been shown to support and manage
home care programs quite efficiently.13 However, few studies have
examined the application of HBCR
with telemedicine in patients after
cardiac surgery, myocardial infarction, and percutaneous transluminal
coronary angioplasty14,15; to our
knowledge, we have performed the
only investigation in Italy to test
the feasibility of this approach in
patients following cardiac surgery.16
The current study was aimed at
reproducing at home the in-hospital
cardiac rehabilitation protocol procedures in patients at low to medium
risk after cardiac surgery. The primary objectives of the study were:
August 2013
Table 1.
Rehabilitative Intervention in the 2 Different Settingsa
Measure
Patient selection
What
Home-Based
Rehabilitation
(nⴝ100)
When and How
Age, sex, LFEV, EuroSCORE,
type of intervention
In-Hospital
Rehabilitation
(nⴝ100)
Yes
Yes
4 wk
4 wk
Yes
Yes
Yes
No
Exercise monitoring
Video conference
Face to face
Exercise intervention
(how)
DVD
Face to face
Time for rehabilitation
Education intervention
Exercise intervention
(what and when)
At discharge
At home
Calisthenic (upper and lower
limbs, trunk, neck,
shoulders, education, and
bronchial clearing)
50 min/session
Once a day
Morning
Morning
Stretching/relaxation
(5 min ⫻ 2)
10 min/session
Once a day
Morning
Morning
Interval training on cycle
ergometer
40 min/session
Twice a day
Morning and afternoon
Morning and afternoon
At the end of the program
(25 W increased every
3 min)
Yes
Coming on-site
Start at 25 W for 5 min
Increase to 50 W for
35 min
Bicycle graded
symptom-limited
exercise test
Internal staff
a
Nurse tutor
Every 2 wk
Usual care
Physical therapist
First day after discharge
and every week
Usual care
Specialists
On demand
Usual care
LFEV⫽left ventricular ejection fraction.
(1) to evaluate the feasibility of
implementing an in-hospital rehabilitation protocol in a home setting
with an up-to-date telemedicine platform and (2) to compare key efficacy
indicators such as exercise capacity
(assessed using the Six-Minute Walk
Test [6MWT]). Length of the rehabilitative period, number of days from
the surgical intervention to rehabilitation, and mean total duration of the
rehabilitative sessions were secondary outcome measures.
Method
Design
The study was designed as quasiexperimental.
August 2013
Participants
The study participants were divided
into 2 groups: (1) an HBCR group
and (2) an in-hospital group, which
served as a comparison group.
HBCR group. The HBCR group
(n⫽100) included all patients allocated in our institute (Fondazione
Salvatore Maugeri) who underwent
cardiac surgery procedures between
January 2006 and June 2010 at a
single cardiac surgery center (Fondazione
Poliambulanza
Istituto
Ospedaliero, Brescia, Italy). All participants gave their written informed
consent.
Inclusion criteria were: over 18 years
of age, EuroSCORE between 0 and
5 (European System for Cardiac
Operative Risk Evaluation: 0 –2⫽
low-risk group, 3–5⫽medium-risk
group, ⱖ6⫽high-risk group),17 no
major complications after surgery,
and hemoglobin value ⬎8.5 g/dL. All
enrolled patients were required to
have the availability of a caregiver at
home and to live within 30 km from
the hospital. The main exclusion criteria were insulin-dependent diabetes and overt chronic respiratory
insufficiency. Allocation to the HBCR
group was made based on the
patients’ preference. Among 387
patients who were admitted to the
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Table 2.
Core Elements of Home-Based Cardiac Rehabilitation and Ways of Delivering
Through the Care Platforma
Elements
a
Tools
1. Assessment review and follow-up
1. Face-to-face assessment appointment with a nurse
2. Participants receive training on using the service,
mobile telephone and its applications
3. Personnel health record
4. Scheduled telephone support by nurse
5. Video conference
2. Physical activity and exercise training
6.
7.
8.
9.
Videoconference
Education by a physical therapist (DVD)
Telemonitoring: 1-lead ECG and BP measurement
Home intervention by a physical therapist
3. Behavioral modification strategies
and risk-factor management
10. Scheduled telephone support by a nurse
11. Wellness diary to record weight, food intake,
sleep, alcohol, smoking, exercise, BP
12. Educational sessions by a nurse
4. Nutritional counseling
13. Dietitian interview at discharge
5. Psychological and psychosocial
management
14. Video conference applications
15. Weekly teleconference
BP⫽blood pressure, ECG⫽electrocardiogram.
bilitative program in both settings is
summarized in Table 1.
During the in-hospital rehabilitation, a standardized training program
for cardiovascular rehabilitation following Italian recommended guidelines11 was applied (Tab. 1). Clinical
examinations included electrocardiographic (ECG) testing, cardiac
echo color Doppler, chest radiography, and routine blood tests. Exercise capacity was assessed with
the 6MWT before and after the rehabilitation period. The training program included callisthenic exercises,
cycle training, and education on
healthy lifestyles. The program was
individualized, with exercises provided ad hoc for particular problems
of each patient and adapted daily as
needed by the physical therapist.
Details on the HBCR program are
described in Table 2. At time of discharge from the Cardiac Surgery
Department, a nurse and cardiologists provided an educational session
to introduce the program to each
patient.
Figure 1.
The platform of video conference used during the home cardiac telerehabilitation.
hospital after cardiac surgery, 100
were enrolled as the HBCR group.
In-hospital group. The in-hospital
group (n⫽100) was retrospectively identified from the database
of the Cardiovascular Rehabilitation
Department (Fondazione Salvatore
Maugeri) of patients consecutively
admitted between January 2006 and
June 2010. All patients who had
been hospitalized in our hospitals a
priori gave signed informed consent
for the use of their data for research,
and none had to be contacted for
this reason.
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A matching program18 was used to
select participants based on age,
sex, left ventricular ejection fraction
(LVEF), EuroSCORE, and type of
intervention. Among 600 patients
who were admitted to the hospital
after cardiac surgery during the
period of the current study, 100
were identified as the comparison
group.
Procedure
The HBCR program16 was set up in
an identical fashion to the in-hospital
rehabilitation program.11 Physical
activity performed during the reha-
Number 8
During the HBCR program, participants underwent testing similar to
that of the in-hospital setting (eg, cardiology visits and blood tests, cardiac
echo color Doppler, chest radiography, and 6MWT) before and after
rehabilitation. Electrocardiographic
testing was performed either in the
hospital during visits (12-lead ECG
recording), or measurements were
collected at home during bicycle
training through transtelephonic
1-lead ECG recording (Card-Guard
2206, Card Guard Scientific Survival
Ltd, Rehovot, Israel) or during home
visits the by nurse through 12-lead
ECG recording (Card-Guard 7100,
Scientific Survival Ltd).
All participants in the HBCR group
were supervised by a medical doctor and teleassisted at home daily
by a nurse and a physical theraAugust 2013
pist by video conference. The participants were given instructions on
their medications and directions
to the respective emergency department in case of an emergency.
All drugs for routine therapy and
an emergency kit (antibiotics, antiinflammatory
drugs,
sedatives,
diuretics, beta-blockers, and general medicaments) were supplied
to each participant. A DVD illustrating the correct way to perform callisthenic exercises also was provided. Furthermore, a 1-lead ECG
recorder and a computer notebook
with mobile broadband capabilities
(which allowed point-multipoint
video and audio transmissions simultaneously) were provided to each
participant. An electronic health
record was prepared for each
patient, and the patient’s general
practitioner was informed.
Table 3.
Clinical and Functional Characteristics of the Participants at Baselinea
Characteristic
Age (y), X (SD)
In-Hospital
Rehabilitation
(nⴝ100)
Home-Based
Rehabilitation
(nⴝ100)
63 (11)
63 (12)
P
ns
Male (n)
89
86
ns
CABG (n)
61
57
ns
Valve (n)
26
36
ns
6
5
ns
7
2
ns
3.78 (1.7)
3.95 (2.5)
ns
CABG⫹valve (n)
Plastic surgery on valve (n)
EuroSCORE, X (SD)
COPD (n)
4
2
ns
Renal insufficiency (n)
2
2
ns
Diabetes (n)
10
16
ns
62 (5)
64 (8)
ns
LVEF (%), X (SD)
56.2 (7.3)
55.7 (7.7)
ns
6MWT score (m), X (SD)
354 (102)
334 (90)
ns
.001
Body weight (kg), X (SD)
11 (1.7)
10.2 (1.3)
Cholesterol (mg/dL), X (SD)
Hemoglobin (mg/dL), X (SD)
145.9 (37)
155.7 (33)
ns
Triglycerides (mg/dL), X (SD)
123.3 (43.3)
116.6 (39)
ns
a
Video conference rehabilitation sessions directed by a nurse or a therapist were provided every morning
and afternoon (Fig. 1). We are currently using a multiple platform
video conference that can follow
multiple patients simultaneously,
mimicking the in-hospital program.
We can follow up to 8 patients
at each rehabilitation session. The
operator of telemedicine rehabilitation views on the monitor a
mosaic composed of a video of each
patient participating in the session,
but the interaction is one to one.
Conversely, the patient views only
the operator. It is possible to allow
direct communication with the individual patient during the rehabilitation session and shift from one to
another. The platform allows the
management of video signal in full
screen mode (ie, turning off the
microphone and displaying a full
screen video).
CABG⫽coronary artery bypass graft, COPD⫽chronic obstructive pulmonary disease, LVEF⫽left
ventricular ejection fraction, 6MWT⫽Six-Minute Walk Test, ns⫽not significant. EuroSCORE value
represents a score for the prediction of early mortality in patients after cardiac surgery in Europe on
the basis of 17 objective risk factors: 9 patient-related factors, 4 derived from the patient’s preoperative
cardiac status, and 4 dependent on the timing and nature of the operation performed. The system is
additive and identifies 3 different categories of patients: low risk⫽0 –2, medium risk⫽3–5, and high
riskⱖ6. Baseline differences between the 2 groups were analyzed by chi-square test for discrete
variables, by the Student t test for normally distributed continuous variable, and by the Mann-Whitney
test for non–normally distributed continuous variables.
All training exercise sessions (Tab. 1)
were supervised at the participant’s
home by the physical therapist the
day after discharge and once a
During the HBCR program, participants visited the hospital to
undergo routine blood tests and
clinical examinations (ie, cardiac
August 2013
week. The nurse tutor provided services every 2 weeks at home. During
this visit, the nurse performed a
12-lead ECG recording. Rehabilitation sessions (Monday–Friday) lasted
approximately 100 minutes at the
morning session and 40 minutes
at the afternoon session. Saturday
sessions consisted of the morning
session only. The maximum period
of the rehabilitation program was
24 working days (4 weeks). The
training included 60 minutes of arm
and leg isotonic calisthenic exercises
as well as exercises for posture and
respiration and techniques for muscle relaxation. These exercises had
to be performed once a day in the
morning with the help of the DVD.
The cycle ergometer exercise was
performed twice a day (40 minutes/
session) with the help of cardiac
telemonitoring through 1-lead ECG
recordings. Daily, the nurse tutor
contacted the participant by telephone for the collection of his clinical data, confirmation or variation of
the therapy, and resolution of possible needs (ie, to dress the surgical
wound and adaptation of the daily
physical performance). In case of
mild complications, the participant
was supported by teleassistance or
unscheduled home visits performed
by either a nurse or physical therapist. In cases of severe complications, the participant had access to a
cardiologist or to the emergency
department.
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Table 4.
Clinical Outcomes and Process Measures Evaluated at the End of the Programa
In-Hospital
Rehabilitation
(nⴝ100)
Home-Based
Rehabilitation
(nⴝ100)
P
LVEF (%), X (95% CI)
56.3 (46.8–65.8)
56.9 (47.2–63.6)
ns
6MWT score (m), X (95% CI)
442 (345–539)
449 (346–552)
ns
11.4 (1.2)
12.4 (1.2)
.001
Measure
Hemoglobin (mg/dL), X (95% CI)
Time from surgical intervention to rehabilitation (d),
X (95% CI)
Rehabilitative period (d), X (95% CI)
9.8 (7.8–11.8)
23 (22–24)
Total duration of rehabilitative sessions (min),
X (95% CI)
7.9 (5.8–9.0)
22 (21–23)
.01
ns
891 (800–982)
984 (914–1,054)
ns
Patients with antiplatelet/anticoagulant at discharge (%)
98
100
ns
Patients with statins at discharge (%)
70
98
.01
12-lead ECG/patient (n), X (95% CI)
5.2 (4.7–5.7)
4.1 (3.8–4.5)
.02
Echocardiograms/patient (n), X (95% CI)
1.6 (1.4–1.8)
3.2 (3.0–3.4)
.001
Chest radiographs/patient (n), X (95% CI)
1.3 (1.2–1.4)
1.2 (1.1–1.3)
.05
Blood withdrawings/patient (n), X (95% CI)
7.1 (6.6–7.7)
5.6 (5.2–6.1)
.001
a
CABG⫽coronary artery bypass graft, COPD⫽chronic obstructive pulmonary disease, LVEF⫽left ventricular ejection fraction, 6MWT⫽Six-Minute Walk Test,
95% CI⫽95% confidence interval, ECG⫽electrocardiogram, ns⫽not significant. Data are reported as mean (95% CI) or percentage.
The differences between the 2
groups were analyzed by the chisquare test for discrete variables, by
the Student t test for normally distributed continuous variable, and
by the Mann-Whitney test for non–
normally distributed continuous variables using Prism GraphPad version
4 software (GraphPad Software Inc,
La Jolla, California).
Figure 2.
Participants in the home-based cardiac rehabilitation (HBCR) and in-hospital rehabilitation groups each made significant gains in Six-Minute Walk Test (6MWT) distance following their respective rehabilitation intervention; pre⫽before intervention,
post⫽after intervention. No evidence of time ⫻ group interaction was found. Asterisk
indicates P⬍.001.
echo-color Doppler and 6MWT).
The final visit to the hospital also
included the evaluation of maximal exercise capacity by a bicycle
graded symptom-limited exercise
test (25 W increased every 3 minutes). At the end of the HBCR program, participants filled in a general
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questionnaire (Appendix) indicating
their satisfaction with the program.16
Data Analysis
Data are expressed as number, percentage or mean (standard deviation), and mean (95% confidence
interval [95% CI]) where indicated.
Number 8
The SAS/STAT Logistic program (SAS
Institute Inc, Cary, North Carolina)
was used to evaluate the analysis of
variance (ANOVA) for repeated measures. The ANOVA model was constructed to analyze the effect of time,
group, and time ⫻ group interaction
for the 6MWT, LVEF, and hemoglobin measurements obtained at entry
and at the end of the rehabilitation
program. Post hoc tests were used to
compare means when a significant F
ratio of the main effects was found in
ANOVA model. The P value was considered significant if ⬍.05.
Results
Data from all participants in the
HBCR and in-hospital groups were
August 2013
subjected to statistical analysis. Table
3 shows the clinical and functional
participants’ characteristics at time
of enrollment in the 2 groups. No
significant baseline differences in the
participants’ characteristics were
found except for hemoglobin level,
which was higher in the in-hospital
group (P⬍.001).
During the program, a total of 3,042
calls were made. Ninety-nine percent of the calls were scheduled by
the nurse tutor. Only 1% of calls
were requested by the participant.
The mean (standard deviation) numbers of home care visits made by
nurse, physical therapist, and cardiologists were 1.6⫾1.0, 2.5⫾1.0, and
0.2⫾0.4 visits/patient, respectively.
The outcomes and clinical measures
of the 2 groups are described in
Table 4. Length of rehabilitative
period was similar in the 2 groups
(Tab. 4). However, the number of
days from the surgical intervention
to rehabilitation were significantly
higher in the in-hospital rehabilitative setting (P⬍.01, Tab. 4).
Comparing data at entry and discharge from the program in the 2
groups, we found that both groups
increased LVEF without significant
differences within groups (F⫽3.73,
P⫽nonsignificant). On the contrary,
a significant increase in hemoglobin
concentration, which was more evident in the HBCR group, was found
at the end of the program (F⫽59.36,
P⬍.001). Participants in the HBCR
group performed the exercise programs for a mean (SD) total time of
983.9 (358.1) minutes compared
with 891.0 (464.4) minutes for the
in-hospital group (P⫽nonsignificant)
(Tab. 4). In particular, participants
at home spent more time on a cycloergometer (645.6 [278.1] minutes,
16.9 [6.9] sessions/participant) with
respect to rehabilitative sessions
(338.6 [137.6] minutes, 21.5 [9.3]
sessions/participant).
August 2013
Both groups increased their 6MWT
scores (F⫽159.34, P⬍.001, Tab. 4,
Fig. 2). The HBCR group improved
by ⫹109.3 m (95% CI⫽85.6 –133.0),
and the in-hospital group improved
by ⫹89.1 m (95% CI⫽69.1–109.1).
These increases were statistically
nonsignificant, and no within-group
differences were found (F⫽0.024,
P⫽nonsignificant). At the end of
the program, the graded symptomlimited exercise test accounting for
maximal exercise capacity in the
HBCR group was similar to that of
the in-hospital group (107.4 [3.7] W
versus 100.8 [4] W, respectively).
The mean numbers of 12-lead ECGs
per participant, chest radiographs
per participant, and blood withdrawings per participant were significantly fewer in the HBCR group
(P⬍.02, P⬍.001, and P⬍.05, respectively) than in the in-hospital group
(Tab. 4). On the contrary, a higher
mean number of echocardiographs
per participant was performed in the
HBCR group (P⬍.001).
The percentage of participants
with coronary artery disease under
antiplatelet or anticoagulant therapy
at discharge was 100% in the HBCR
group and 98% in the in-hospital
group (Tab. 3); participants using
statins at discharge, an obligatory
therapy for patients with coronary
artery disease, was 94% in the HBCR
group and 70% in the in-hospital
group (P⬍.01) (Tab. 4).
Clinical Events
No statistically significant differences in clinical events, evaluated
by chi-square test for discrete variables, were observed between the 2
groups. During the HBCR period,
complications were documented in
19 participants due to the following
issues: pericardial effusion (n⫽4);
atrial tachyarrhythmia (n⫽9), stroke
(n⫽1), thrombosis (n⫽1), wound
infection (n⫽1), congestive heart
failure decompensation (n⫽1),
atrial fibrillation (n⫽1), and psychiatric cause (n⫽1). Four participants
were sent to the emergency department. No deaths occurred. Only 1
participant dropped out of the study
for personal reasons. The global satisfaction of the HBCR group was
reported as “very much high” by
80% of the participants, “high” by
12% of the participants, “medium”
by 4% of the participants, and “low”
by 4% of the participants.
In the in-hospital group, clinical
events were reported in 18 participants who required hospitalization due to atrial tachyarrhythmia
(n⫽11), infection complications
(n⫽3), pericardial effusion (n⫽2), or
dehiscence of the wound (n⫽2).
Seven participants prematurely interrupted the program, and 3 participants dropped out for personal reasons. No deaths occurred in this
group as well.
Discussion
At the international level, guidelines
state that all patients who undergo
cardiac surgery should participate in
a cardiac rehabilitation program.
However, because of organization
and cost problems, in-hospital rehabilitation is reserved for patients
who are very ill. Although many
patients at low to medium risk could
be rehabilitated at home, HBCR
remains a very small service compared with the number of patients
who can take advantage of it. This
study represents the first experience
of a home-based rehabilitation program monitored by telemedicine in a
homogeneous group of patients at
low to medium (noncomplicated)
risk who underwent cardiac surgery
and comparing exercise capacity
with a conventional in-hospital rehabilitation program. In our previous
study,16 a feasibility study of 47
patients, we gave a detailed description of the service and of the first
release of the telemedicine platform
in these patients, and the results of
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the program were not validated.
The present study was a quasiexperimental study performed on
100 patients at home with respect to
a comparative in-hospital group; a
different technology (video conference during rehabilitation sessions)
was provided to help physical therapists to follow up on patients at
home in real time or later (store and
forward system), and results on validation of the program are presented.
In contrast to the present study,
Dalleck et al6 included in their rehabilitation program patients with different types of cardiac conditions
(postcardiac surgery, acute myocardial infarction, and percutaneous
transluminal coronary angioplasty)
and with a different incidence of
events in the first period after surgery. They compared changes in
risk factors for cardiovascular disease in a conventional rehabilitation
outpatient program toward rehabilitation performed in a telemedicine
center, located 240 km far from
the conventional cardiac rehabilitation center. The 2 studies are similar
in the technology used but completely different regarding the
modality used to deliver the service:
in the telemedicine rural center,6
there was a junior exercise physiologist, whereas in the current study, a
physical therapist and a nurse were
present in hospital as pivotal people
for telesupport and telemonitoring
of the program and for assisting
patients at their home.
In the study by Ades et al,9 patients
were recruited not only after coronary artery bypass graft but also
after acute myocardial infarction and
percutaneous transluminal coronary
angioplasty. That study compared
home rehabilitation and outpatient
service of cardiac rehabilitation,
whereas our study compared home
rehabilitation and in-hospital rehabilitation. An important difference in
technology support also was found
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between the 2 studies in that Ades
and colleagues used direct voice contact but did not use a video
conference.
Our study showed that HBCR is feasible and yields similar outcomes for
the majority of patients. The application of information and communication technology facilitated implementation of the HBCR program,
and the use of telemedicine allowed
a safer approach to the program.
There was a selection bias because
patients could decide whether to
enter the study (ie, to undergo HBCR
or usual in-hospital rehabilitation)
and intervention could not be randomized to individual patients.
Although the percentage of patients
who had chosen the home-based
model is relatively low, the data are
in agreement with the findings of a
previous study.19 This low rate of
enrollment was mainly related to
patients’ fear of clinical complications to be managed at home by
relatives during convalescence.
This observation highlights the role
that structured assessments and sharing of patient information in the
in-hospital setting have in promoting
favorable patient outcomes after
discharge.20
Because the patients came only from
one cardiac surgery center, it is difficult to transfer our results to the
general population. The participation of a greater number of patients,
facilitated by telemedicine, obviously could lead to events reduction
(eg, secondary prevention).
We have found that the number
of days from the surgical intervention to rehabilitation was significantly higher in the in-hospital rehabilitative setting. The most plausible
explanation for the different times
to rehabilitation between the 2
groups could be that hospital admission requires hospital patient turnover, such as bed availability. How-
Number 8
ever, it also could reflect a different
medical or functional recovery of
the patients. The home-based program was effective and comparable
to the conventional inpatient rehabilitative approach, providing similar
improvement in exercise capacity
and quality of life as that found in the
study by Ades and colleagues.9
Supervision and education of HBCR
by the physical therapist provided an
important validation of the HBCR
concept. Indeed, the physical therapist has unique skills compared with
a nurse or exercise physiologist in
this setting and, with the cardiologists’ supervision, is fundamental in
providing valuable guidance both in
the inpatient setting and in a home
care setting (as shown by HBCR).
The physical therapist can promote
favorable patient outcomes after discharge by structured assessments
and sharing of patient information
during the in-hospital or home setting. The physical therapist, embracing the role of advocate for the
cardiac rehabilitation, can educate
patients on the value of participating in this important lifestyle intervention and ensuring that the
patients’ adherence to recommendations may lower the risk of readmission. Moreover, supervision by
health staff using telemedicine
allows the performance of HBCR
patients at low to medium risk without compromising the high medical
safety that exists in the in-hospital
environment. Similar results were
reported by other authors.21,22 In
particular, the use of supervised
ECG and video conference capabilities allowed objective parameters to
be monitored during the HBCR. This
approach also provided accurate
data on exercise time and bypassed
reliance on self-reported exercise
time, which may lead to an overestimation or underestimation of
exercise.23
August 2013
A therapeutic approach was followed in this study in agreement
with the coronary prevention guidelines.24 In particular, the use of antiplatelet or anticoagulant therapy for
reducing cardiovascular events has
been shown to be equally dispensed
in both settings.
The number of clinical events was
not significantly different between
the 2 programs: acute intervention
was necessary only in a few cases
at home, whereas events arising during in-hospital rehabilitation were
directly managed in the hospital.
The study was not designed for
cost evaluation, but we can consider
that the HBCR program, with equivalent efficacy, might result in a costbenefit to the health care system
(Lombardy region) because the
mean (standard deviation) fee per
patient in the program is €2,972⫾
€1,000.8 (US $3,945⫾$1,328) in
HBCR compared with €7,079.6⫾
€2,228.7 (US $9,396⫾$2,958) in
in-hospital rehabilitation.
A well-designed and surveyed program, both for medical treatment
and exercise training, could become
an attractive method to restore functional capacity in selected patients
after cardiac surgery. The good
results of this study are corroborated
by the good results of a satisfaction
questionnaire.
Limitations
Although patients self-selected into
the groups are representative of a
particular subgroup of patients who
underwent cardiac surgery (with
EuroSCORE less than 5, without any
complication after surgery, and
meeting all of the inclusion criteria),
the results could be applied to a
broader population with the same
inclusion criteria. This study did not
specifically take into consideration
(eg, asking the patients via a questionnaire) whether there were intrinsic factors to the patients who chose
August 2013
HBCR that contributed to their outcomes, but we believe that many
patients, with those inclusion criteria, could benefit from a HBCR program, particularly if other possibilities for cardiac rehabilitation do not
exist in their location. Further studies should analyze whether it is possible to reach similar outcomes.
Because of its observational and
retrospective nature, this quasiexperimental study could not apply
an intention-to-treat analysis. During
the exercise sessions, a greater proportion on the cycle performed by
the HBCR group could have influenced the results. The inpatient satisfaction was not measured by the
same questionnaire used for HBCR.
Conclusions
The HBCR program was feasible,
safe, and comparable to the conventional in-hospital rehabilitation
approach, indicating that rehabilitation following cardiac surgery can
be implemented effectively at home
when programmed with an integrated telemedicine service. In the
Lombardy region, a great number of
patients who have undergone cardiac surgery without complications
could participate in HBCR programs
using telemedicine as an alternative
to in-hospital rehabilitation.
The choice of participating in HBCR
is expected to provide more options
for patients at low to medium risk.
In an era of cost-containment in
health care, the challenge to cardiac rehabilitation specialists will be
to encourage home cardiac rehabilitation using a new integrated care
model with the help of information
communication technologies, appropriately identifying who could be
safely allocated. Indeed, although
patients with severe conditions
require a more conventional
in-hospital cardiac rehabilitation setting, patients at low to medium risk
appear to be more likely triaged to
supervised home programs.
The possibility to adopt the same
program in different settings justifies future randomized controlled
studies to explore the real effectiveness of telemedicine-based cardiac
rehabilitation programs. Mixed models could take into consideration the
management of patients with postsurgery complications, with half of
the conventional period of rehabilitation (ie, first 10 days) in the hospital and continuing at home for a similar period of time.
Dr Scalvini and Dr Giordano provided concept/idea/research design. Dr Scalvini and
Dr Comini provided writing. Dr Zanelli,
Dr Troise, and Dr Febo provided data collection. Dr Comini and Dr Dalla Tomba provided data analysis. Dr Scalvini provided
project management and fund procurement. Dr Scalvini, Dr Zanelli, Dr Dalla
Tomba, Dr Troise, Dr Febo, and Dr Giordano
provided study participants. Dr Comini
provided institutional liaisons. Dr Scalvini,
Dr Zanelli, Dr Comini, Dr Dalla Tomba,
Dr Troise, and Dr Giordano provided consultation (including review of manuscript
before submission). The authors thank
Mrs Doriana Baratti and Mr Giuliano Assoni
for their excellent professional assistance and
Dr Margherita Penna for providing pharmacy assistance. The authors are indebted to
Dr Alessandro Bettini, medical writer, for the
English revision of the manuscript.
The study was approved by deliberation VIII/
002471 (May 11, 2006) and by the Scientific
and Technical Committee (CTS June 15,
2006) of Fondazione Salvatore Maugeri and
followed the principles stated in the Declaration of Helsinki.
The current program is the result of the
authors’ participation in the CRITERIA Project, a joint project of 2 structures: Fondazione Salvatore Maugeri IRCCS and Centro
Cardiologico della Fondazione Monzino
IRCCS. This project, under the scientific
responsibility of Dr Maurizio Marzegalli
(Cardiological Department, San Carlo Hospital, Milan, Italy), was financed by the Italian Health Ministry (Programma Di Ricerca
ex art.12, lett.b, D.Lgs. #502/92) and by the
Lombardy Region Decree of the General
Director (Health General Directorate
#15882, September 29, 2003) and coordinated by the Lombardy Region Health and
Family General Directorates.
DOI: 10.2522/ptj.20120212
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References
1 Graham I, Atar D, Borch-Johnsen K, et al;
for European Society of Cardiology (ESC)
Committee on Practice Guidelines (CPG).
European guidelines on cardiovascular disease prevention in clinical practice: executive summary: Fourth Joint Task Force of
the European Society of Cardiology and
Other Societies on Cardiovascular Disease
Prevention in Clinical Practice (constituted by representatives of nine societies
and by invited experts). Eur Heart J. 2007;
28:2375–2414.
2 Jolliffe JA, Rees K, Taylor RS, et al.
Exercise-based rehabilitation for coronary
heart disease. Cochrane Database Syst
Rev. 2001;1:CD001800.
3 Heran BS, Chen JM, Ebrahim S, et al.
Exercise-based cardiac rehabilitation for
coronary heart disease. Cochrane Database Syst Rev. 2011;7:CD001800.
4 Thompson DR, Clark AM. Cardiac rehabilitation: into the future. Heart. 2009;95:
1897–1900.
5 Kmill C, Sherrington L, Third G. Increasing
access to cardiac rehabilitation through
telemedicine technology. Can Nurse.
2007;103:8 –9.
6 Dalleck LC, Schmidt LK, Lueker R. Cardiac rehabilitation outcomes in a conventional versus telemedicine-based programme. J Telemed Telecare. 2011;17:
217–221.
7 NHS Information Centre and British Society for Heart Failure. National Heart Failure Audit Annual Report 2010/2011. Available at: http://www.ucl.ac.uk/nicor/
audits/heartfailure/additionalfiles/pdfs/
annualreports/annual11.pdf.
Accessed
May 9, 2013.
8 Hannan EL, Zhong Y, Lahey SJ, et al.
30-day readmissions after coronary artery
bypass graft surgery in New York State.
JACC Cardiovasc Interv. 2011;4:569 –576.
9 Ades PA, Pashkow FJ, Fletcher G, et al. A
controlled trial of cardiac rehabilitation in
the home setting using electrocardiographic and voice transtelephonic monitoring. Am Heart J. 2000;139:543–548.
10 Shaw DK, Sparks KE, Jennings HS III,
Vantrease JC. Cardiac rehabilitation using
simultaneous voice and electrocardiographic transtelephonic monitoring. Am J
Cardiol. 1995;76:1069 –1071.
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11 Tramarin R, Ambrosetti M, De Feo S, et al;
ISYDE-208 Investigators of the Italian
Association for Cardiovascular Prevention,
Rehabilitation and Prevention. The Italian
survey on cardiac rehabilitation–2008
(ISYDE-2008), part 3: national availability
and organization of cardiac rehabilitation
facilities. Official report of the Italian Association for Cardiovascular Prevention,
Rehabilitation and Epidemiology (IACPRGICR). Monaldi Arch Chest Dis. 2008;70:
175–205.
12 De Feo S, Tramarin R, Faggiano P, et al.
The inability to perform a 6 minute walking test after cardio-thoracic surgery is a
marker of clinical severity and poor outcome: data from the ISYDE-2008 Italian
survey. Int J Cardiol. 2011;151:115–116.
13 Inglis SC, Clark RA, McAlister FA, et al.
Which components of heart failure programmes are effective? A systematic
review and meta-analysis of the outcomes
of structured telephone support or telemonitoring as the primary component of
chronic heart failure management in 8323
patients: abridged Cochrane Review. Eur
J Heart Fail. 2011;13:1028 –1040.
14 Blair J, Corrigall H, Angus NJ, et al. Home
versus hospital based cardiac rehabilitation: a systematic review. Rural Remote
Health. 2011;11:1532.
15 Sparks KE, Shaw DK, Eddy D, et al. Alternatives for cardiac rehabilitation patients
unable to return to a hospital-based program. Heart Lung. 1993;22:298 –303.
16 Scalvini S, Zanelli E, Comini L, et al. Homebased exercise rehabilitation with telemedicine following cardiac surgery.
J Telemed Telecare. 2009;15:297–301.
17 Nashef SA, Roques F, Michel P, et al. European system for cardiac operative risk
evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999;16:9 –13.
18 Parsons LS. Reducing bias in a propensity
score matched-pair sample using greedy
matching techniques (paper 214 –26). In:
Proceedings of the 26th Annual SAS Users
Group International Conference; April 22–
25, 2001; Long Beach, California. Cary,
NC: SAS Institute Inc, 2001. Available at:
http://www2.sas.com/proceedings/sugi26/
p214-26.pdf. Accessed May 9, 2013.
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19 Brual J, Gravely S, Suskin N, et al. The role
of clinical and geographic factors in the
use of hospital versus home-based cardiac
rehabilitation. Int J Rehabil Res. 2012;35:
220 –226.
20 Arena R, Williams M, Forman DE, et al;
for American Heart Association Exercise,
Cardiac Rehabilitation and Prevention
Committee of the Council on Clinical
Cardiology, Council on Epidemiology and
Prevention, and Council on Nutrition,
Physical Activity and Metabolism. Increasing referral and participation rates to outpatient cardiac rehabilitation: the valuable
role of healthcare professionals in the
inpatient and home health settings: a science advisory from the American Heart
Association. Circulation. 2012;125:1321–
1329.
21 Smith KM, Arthur HM, McKelvie RS, Kodis
J. Differences in sustainability of exercise
and health-related quality of life outcomes
following home or hospital-based cardiac
rehabilitation. Eur J Cardiovasc Prev
Rehabil. 2004;11:313–319.
22 Varnfield M, Karunanithi MK, Särelä A,
et al. Uptake of a technology-assisted
home-care cardiac rehabilitation program.
Med J Aust. 2011;194:S15–S19.
23 Blanchard C. Understanding exercise behaviour during home-based cardiac rehabilitation: a theory of planned behaviour perspective. Can J Physiol Pharmacol. 2008;
86:8 –15.
24 EUROASPIRE I and II Group: European
Action on Secondary Prevention by Intervention to Reduce Events. Clinical reality
of coronary prevention guidelines: a comparison of EUROASPIRE I and II in nine
countries. Lancet. 2001;357:995–1001.
August 2013
Appendix.
Questionnaire of Satisfaction for the Home-Based Cardiac Rehabilitation Program
Question 1: How do you judge the system overall?
Very Satisfying
Quite Satisfying
Fairly Satisfying
Poorly Satisfying
Not Satisfying At All
Question 2: Was it easy to use the telecardiography/pulse oximeter system?
Very Complicated Quite Complicated Complicated Quite Easy Very Easy
Question 3: Did you experience difficulties in contacting the service?
Very Frequently Frequently Sometimes Rarely Never
Question 4: How was the relationship with your nurse tutor?
Optimal Good Satisfying Discontinuous No Relationship
Question 5: Were the indications of the nurse tutor clear?
Very Clear Quite Clear Fairly Clear Poorly Clear Not At All
Question 6: Are you satisfied with the support of the system in dealing with acute crises?
Completely Satisfied Quite Satisfied Neither Satisfied nor Unsatisfied Quite Unsatisfied Totally Unsatisfied
Question 7: Do you feel more secure since having access to the service?
Very Secure Much Secure Quite Secure Poorly Secure Not At All
Question 8: How frequently do you contact your family doctor since you have had access to the service?
Much More Frequently More Frequently As Before Less Frequently Much Less Frequently
Question 9: Do you believe the access to the system improved your life?
Very Much Much Fairly Poorly Not At All
Question 10: Did the access to the service help your family or the people you live with?
Very Much Much Fairly Poorly Not At All
August 2013
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Research Report
M. Robert, MSc, Centre de Réadaptation Marie Enfant, CHU
Sainte-Justine, Montréal, Québec,
Canada; Université du Québec à
Montréal, Montréal, Québec,
Canada;
and
Groupe
de
Recherche en Activité Physique
Adaptée (GRAPA), Montréal, Québec, Canada.
L. Ballaz, PhD, Centre de Réadaptation Marie Enfant, CHU
Sainte-Justine; Université du Québec à Montréal; and Groupe de
Adaptée (GRAPA).
R. Hart, MSc, Centre de Réadaptation Marie Enfant, CHU
Adaptée (GRAPA).
M. Lemay, PhD, Centre de Réadaptation Marie Enfant, CHU
Adaptée
(GRAPA).
Mailing
address: Centre de Réadaptation
Marie Enfant, 5200 Bélanger Est,
Montréal, Québec, Canada H1T
1C9. Address all correspondence
to Dr Lemay at: lemay.martin@
uqam.ca.
[Robert M, Ballaz L, Hart R, Lemay
M. Exercise intensity levels in children with cerebral palsy while
playing with an active video game
console. Phys Ther. 2013;93:
1084 –1091.]
Association
April 11, 2013
Submitted: May 14, 2012
Exercise Intensity Levels in Children
With Cerebral Palsy While Playing
With an Active Video Game Console
Maxime Robert, Laurent Ballaz, Raphael Hart, Martin Lemay
Background. Children with cerebral palsy (CP) are prone to secondary complications related to physical inactivity and poor cardiorespiratory capacity. This problem could be greatly attenuated through the use of video games that incorporate
physical activity for 2 reasons: Video games already represent an important component of leisure time in younger people, and such games can lead to a high level of
exercise intensity in people who are healthy.
Objective. The study objective was to evaluate exercise intensity in children with
spastic diplegic CP and children who were typically developing while playing with
an active video game console.
Design. This was a cross-sectional study.
Methods. Ten children (7–12 years old) with spastic diplegic CP (Gross Motor
Function Classification System level I or II) and 10 children who were age matched
and typically developing were evaluated in a movement analysis laboratory. Four
games were played with the active video game console (jogging, bicycling, snowboarding, and skiing) for 40 minutes. Heart rate was recorded during the entire
playing period with a heart rate belt monitor. Exercise intensity was defined as the
percentage of heart rate reserve (HRR). In addition, lower extremity motion analysis
was carried out during the final minute of the playing period for the jogging and
bicycling games.
Results. No difference between groups was observed for any variables. A main
effect of games was observed for the amount of time spent at an intensity greater than
40% of HRR. Specifically, more than 50% of the playing time for the jogging game and
more than 30% of the playing time for the bicycling game were spent at an intensity
greater than 40% of HRR. In addition, the jogging game produced a larger range of
motion than the bicycling game.
Limitations. A limitation of this study was the relatively small and heterogeneous
sample.
Conclusions. For all 4 games, similar exercise intensity levels were observed for
children who were typically developing and children with CP, suggesting that
children with CP could obtain exercise-related benefits similar to those obtained by
children without CP while playing with an active video game console.
this article at:
ptjournal.apta.org
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Active Video Games in Children With Cerebral Palsy
I
n children with cerebral palsy
(CP), reduced levels of physical
activity increase the occurrence of
secondary conditions (eg, poor bone
density, fatigue, and chronic pain) as
they age and can affect functional
mobility and gait.1 In this population, the intensity of daily activities
is usually too low to significantly
improve physical fitness.2 The American Physical Therapy Association
has emphasized the importance of
identifying and promoting accessible physical exercise for children
with CP with the goals of reversing deconditioning secondary to
impaired mobility and optimizing
motor functions. However, various
financial and societal barriers, such
as a lack of equipment, a lack of
availability of exercise instructors,
and a lack of access to adapted transportation, greatly limit accessible
physical activity for children with
disabilities.3 In this context, physical
activity performed at home and
independently by children with CP
may be a suitable and pragmatic
approach.
Video games represent an important
part of leisure time in younger people.4 In the last decade, new types of
consoles, namely, active video game
consoles (AVGCs), have provided an
opportunity to transform what has
traditionally been sedentary screen
time into a period of physical activity. Active video game consoles are
based on virtual reality concepts and
involve interactive physical activity.5
One commercially available AVGC,
the Nintendo Wii (Nintendo, Redmond, Washington), allows people
to interact with a virtual environment and play a variety of sports
games through the use of a handheld
motion sensor (remote control) or
an instrumented platform (Wii Fit).
The player approximately reproduces movements similar to those
performed in real life. For example,
the player can control the direction
of a virtual skier by changing the
August 2013
distribution of weight between his
feet. The Wii can provide many task
repetitions, real-time feedback, a
safe environment, and a high level of
motivation, which are among the
key factors for successful rehabilitation.6 This inexpensive and commercially available technology has generated tremendous interest among
physical therapists worldwide.
The intensity of exercise while playing with an AVGC is a key factor in
determining its relevance in the context of a physical training or rehabilitation program. Exercise intensity
corresponds to the degree of difficulty or effort associated with an
exercise and can be classified as
mild, moderate, or vigorous.7 The
intensity and duration of a given
exercise influence the activitybased energy expenditure, that is,
the energetic cost required to perform the exercise. According to the
American College of Sports Medicine
(ACSM), exercise at moderate intensity (between 40% and 70% of heart
rate reserve [HRR]) is needed to
ensure the maintenance or improve-
ment of cardiorespiratory fitness in
people with chronic disease and disabilities,8 whereas an exercise intensity greater than 50% of HRR is
needed in people who are healthy.7
Several studies have shown that
using AVGCs can lead to positive
changes in the aerobic capacities of
various asymptomatic and symptomatic populations,9 –12 including
adults with CP.13 Some studies have
shown that in children who are typically developing, playing with
AVGCs results in an intensity exceeding the minimal exercise requirement for improving aerobic capacity
in this population.10,12 Other studies
have shown that exercise intensity is
insufficient to meet the recommended requirement.14,15 The types
of games chosen could explain some
of the discrepancies among these
studies. Miyachi et al16 evaluated
exercise intensity levels in 12 adults
who were healthy while playing 68
games and reported intensity levels
equivalent to or greater than those
of moderate exercise for 22 of the
68 games. Most of those 22 games
The Bottom Line
In the past few years, several studies have shown that commercially
available active video game consoles (AVGCs) can improve the fitness of
children who are typically developing. Despite the fact that AVGCs such
as the Wii are currently used in several rehabilitation centers, very few
studies to date have evaluated exercise intensity in children with spastic
diplegic cerebral palsy (CP) during game play.
This study showed that exercise intensity while playing Wii games was
similar between children with and without CP.
for you?
Active video game consoles are an affordable, safe, and playful approach
to improve aerobic capacity in children with CP.
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(17/22) involved lower limb or full
body movements.16 In a recent
review, Biddiss and Irwin17 proposed that games involving lower
body or full body movements lead to
higher energy expenditure than
games soliciting mostly upper limb
movements.
The fact that movements in lower
limbs are affected in children with
spastic diplegic CP18 could limit the
benefits obtained by using the Wii to
improve their physical fitness. One
recent study of children with hemiplegic CP showed that a moderate
level of exercise intensity could be
achieved with Wii games soliciting
mostly upper limb movements.19
However, to our knowledge, exercise intensity levels in children with
spastic diplegic CP while playing
with the Wii have never been evaluated. The primary goal of this study
was to compare exercise intensity
levels in children with spastic diplegic CP and children who were typically developing while playing Wii
games mainly soliciting lower limb
movements. The secondary goal
was to explore whether motor limitations associated with spastic diplegic CP (spasticity, limited range of
motion, and lower strength) influenced exercise intensity levels.
Method
Participants
Ten children who were 7 to 12 years
old (4 boys, 6 girls; mean age⫽
9.1 years, SD⫽2.02) and had spastic diplegic CP (Gross Motor Function Classification System [GMFCS]
level I or II) were compared with 10
children who were age matched
(7–12 years old; 5 boys, 5 girls;
mean age⫽9.4 years, SD⫽1.78) and
typically developing (without CP).
Inclusion criteria for children with
CP were the ability to follow simple
verbal instructions, the ability to
maintain a standing position without support for at least 10 minutes,
and normal or corrected-to-normal
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vision. Exclusion criteria were the
inability to provide parental consent
or participant assent, surgical procedures or botulinum toxin type A
(Botox, Allergan Inc, Irvine, California) injection in the preceding 3
months, and other known neurological problems (eg, epilepsy). All parents and participants provided written informed consent or assent.
Measurements
Before the experiment, several measurements were collected, in the following order: resting heart rate,
range of motion, spasticity, and maximal strength. The participants were
then asked to complete various Wii
tests that provide information to
players on how to use the Wii Fit and
the remote control. For calibration
of the Wii Fit according to the
weight of the participants, the participants were asked to perform a
balance test. Finally, the participants
played 4 games (skiing, jogging,
snowboarding, and bicycling) for
10 minutes each in a random order
with a 5-minute rest period between
games. Each game was played for
10 minutes to obtain a valid measure
of the heart rate response and to
avoid excessive fatigue (for a similar
procedure, see Worley et al20 and
Lannigham-Foster et al21). The jogging game had to be restarted a maximum of 4 times (eg, at the end of a
level), but restarting could be done
very quickly (⬍5 seconds). The
games were chosen because they
involve mostly lower limbs movements. Preliminary testing (unpublished data) had shown that the jogging and bicycling games led to
moderate to vigorous levels of exercise intensity in participants who
were healthy.
For the jogging game, a player followed a virtual guide by stepping
in place with the remote control in
his or her pocket. During the bicycling game, a player controlled the
direction and speed of the bicycle by
Number 8
tilting the remote control and by
stepping in place on the Wii Fit
platform. The jogging and bicycling games were performed at a
self-selected speed with a relatively
steady effort and therefore did not
require short, intense bursts of
effort. Games requiring lower exercise intensity (skiing and snowboarding) were chosen to maintain
participants’ motivation by allowing them to alternate between
demanding games and less demanding games. These games required a
player to produce an anteroposterior
(snowboarding game) or mediolateral (skiing game) weight transfer
to control the displacement of an
onscreen avatar.
The selected games were chosen
because they were easy to understand, appeared to be appropriate
for children with CP, and were associated with a high level of motivation. The order of presentation of the
games was stratified and randomized
so that games expected to generate a
high exercise intensity (bicycling
and jogging) were alternated with
games expected to produce a low
exercise intensity (skiing and snowboarding). Before each game, the
participants received standardized
instructions on how to play, and the
experimenter made sure that the
task was well understood.
Exercise intensity level was the primary outcome measure and was
defined as the percentage of HRR
(HRR ⫽ maximum heart rate ⫺ resting heart rate). The HRR has been
used in other studies of children
with CP, notably to monitor exercise
intensity during an intervention.22,23
Resting heart rate was evaluated
after 10 minutes in a lying position
with a heart rate belt monitor (Polar
RS400; Polar, Kempele, Finland) and
was defined as the minimum value
recorded by the monitor. This monitor samples the heart rate every 5
seconds through a chest belt and
August 2013
transmits the data to a watch. Maximum heart rate was first calculated
with the following formula: 208 ⫺
(years of age ⫻ 0.7).24,25 This formula has been shown to be valid for
children and adolescents.25 Maximal heart rate also was estimated in
children with CP using the value of
194 in accordance with the recommendation of Verschuren et al.26
However, no significant difference
between the formulas was observed.
Therefore, the formula 208 ⫺ (years
of age ⫻ 0.7) was used for both
groups.
Heart rate was recorded during the
entire playing period for all games.
Heart rate measures have been used
to determine the intensity of exercise in children and adults playing
AVGCs.10,12,15 Heart rate monitor
devices do not restrict movements,27
are less intimidating for children
than indirect calorimetry, provide
precise values, are field-based measures that are more readily available
and easier for clinicians to use in the
context of a rehabilitation program,
and have been extensively validated
in other studies (for a review, see
Achten and Jeukendrup28).
For each 10-minute game period,
the percentage of time spent at an
intensity greater than 40% of HRR
(ie, moderate to vigorous intensity
or greater than 3 metabolic equivalents [1 MET⫽3.5 mL O2䡠kg⫺1䡠min⫺1])
was determined (for a similar procedure, see Koopman et al29). This
threshold was chosen in accordance
with ACSM’s suggestion that physical activity needs to be performed
at an intensity greater than 40% of
HRR to provide significant benefits to the cardiorespiratory system in
people with motor limitations or
disabilities.8,29,30
Secondary measures were collected
to control for the possible influence
of motor limitations on exercise
intensity levels. Quadriceps muscle
August 2013
spasticity was evaluated with the
Modified Ashworth Scale at the knee
articulation (flexion and extension).31,32 The Modified Ashworth
Scale is a 6-point scale (0, 1, 1⫹, 2, 3,
and 4); lower values are associated
with a lower level of spasticity. Spasticity can affect exercise intensity
levels by restraining movement,
causing compensatory movements,
or both.33 The passive flexion and
extension range of motion of the
hip, knee, and ankle articulations
was measured with a goniometer.
Limitations in joint range of motion
can lead to smaller movements and,
therefore, reduce exercise intensity
levels.34
The maximal flexion and extension
isometric strength of the flexor and
extensor muscles at the hip, knee,
and ankle joints was measured with
a handheld dynamometer (Lafayette
Instrument Co, Lafayette, Indiana).35
A reduction in strength is associated
with an increase in intensity for various exercises, such as walking.36
Handheld dynamometers have been
validated for measuring maximal
isometric strength in children with
CP.37 In the present study, the
examiner held the device rigidly in
place while the participant was
encouraged (with standardized verbal encouragement) to push “as
hard as possible” for 4 seconds.
Once familiar with the task, each
participant performed 3 maximal
exertions for each muscle with at
least a 30-second rest period
between exertions. Peak force was
recorded with the dynamometer,
and the 2 highest values were
retained. The values then were averaged and normalized with respect to
body weight and lower limb length
(N䡠m/kg).38 Values obtained from
the right and left sides were combined into 1 measure for each
participant.
recording at 60 Hz (Vicon 512,
Oxford Metrics, Oxford, United
Kingdom) also was performed during the jogging and bicycling games.
These 2 games were expected to
be associated with higher exercise
intensity levels than the skiing and
snowboarding games. They also
required lifting the feet from the
ground. The analysis was performed
to evaluate whether larger ranges
of motion would be associated
with higher exercise intensity levels.
Sixteen reflective markers were
placed on the lower limbs at the
following anatomic landmarks: anterior superior iliac spines, posterior
superior iliac spines, lateral aspect
of the knee joints, lateral malleoli,
heels, second metatarsals, and lateral aspects of the thigh and calf
segments. The last 30 seconds of
each game were recorded (for a
similar procedure, see Berry et al39).
Because of their potential impact on
exercise intensity levels,34 the following parameters were measured:
hip flexion, hip extension, knee flexion, knee extension, ankle dorsiflexion, and ankle plantar flexion.
Finally, after each game, participants
completed the Borg Scale to quantify
the perceived exertion on a scale
from 6 (no exertion) to 20 (maximal
exertion).10 For facilitating the interpretation of each level of the Borg
Scale, standardized pictograms representing each level of perceived
effort were shown. The Borg Scale
has been shown to have good validity and reliability for children who
are healthy,40 and the measure was
used in a previous study with the
Wii.10 The Borg Scale also was used
to evaluate perceived exertion in
children with CP.41,42 The participants also reported their degree of
interest in each game on a numeric
scale from 1 (not motivated) to 10
(very motivated).
A kinematic analysis with an
8-camera motion capture system
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Table 1.
ported by CIHR-MENTOR postdoctoral training fellowship.
Characteristics of Participantsa
Participants
With CP
(nⴝ10)b
Participants
Without CP
(nⴝ10)b
Statistical
Test
Results
Weight, kg
34.47 (13.08)
32.45 (9.12)
t18⫽0.160, P⫽.69
Height, cm
135 (15)
134 (13)
t18⫽0.027, P⫽.87
4:6
5:5
18.19 (3.62)
17.81 (3.73)
t18⫽0.055, P⫽.82
6:4
N/A
N/A
Knee flexion
2.27 (0.83)
2.29 (0.43)
t18⫽0.006, P⫽.94
Knee extension
4.58 (0.99)
5.14 (0.73)
t18⫽2.081, P⫽.17
Hip flexion
1.04 (0.34)
1.34 (0.30)
t18⫽3.761, P⫽.06
Hip extension
2.88 (1.07)
3.16 (0.56)
t18⫽0.326, P⫽.58
Ankle dorsiflexion
2.26 (0.93)
3.45 (1.44)
t17⫽4.431, P⫽.05
Ankle plantar flexion
4.62 (1.13)
6.06 (1.52)
t17⫽5.342, P⫽.03c
Characteristic
Sex, no. of boys:girls
Body mass index, kg/m
2
GMFCS level I:level II, no. of children
␹2⫽0.20, P⫽.99
Strength, N䡠m/kg
Passive range of motion (°)
Hip flexion
139 (9)
N/A
N/A
Hip extension
⫺9 (8)
N/A
N/A
Knee flexion
151 (6)
N/A
N/A
0 (5)
N/A
N/A
Ankle flexion
48 (22)
N/A
N/A
Ankle extension
10 (7)
N/A
N/A
0.73 (0.72)
N/A
N/A
Knee extension
Spasticity
a
b
c
CP⫽cerebral palsy, GMFCS⫽Gross Motor Function Classification System, N/A⫽not applicable.
Data are reported as mean (standard deviation) unless indicated otherwise.
Significant difference between the groups.
Data Analysis
The normality of the distributions was determined with the
Kolmogorov-Smirnov test. To examine differences between groups and
games, we submitted the main outcome measure to a 2 (groups) ⫻ 4
(games) analysis of variance with
repeated measurements on the last
factor. Secondary measures were
submitted independently to a 2
(groups) ⫻ 2 (games: jogging and
bicycling) analysis of variance with
repeated measurements on the last
factor. Effect size was calculated by
dividing the difference of the means
for the outcome variables by the
pooled standard deviations and was
interpreted in accordance with
Cohen guidelines: 0.20 as small, 0.50
as moderate, and 0.80 as large.43 To
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determine the variables predicting
exercise intensity, we implemented
a linear regression model with a forward stepwise model selection procedure. This supplementary analysis
was used to predict exercise intensity with the secondary measures as
independent variables. The variables
were entered into the model if the F
probability was inferior to .05 and
were removed from the model if the
F probability was superior to .1. All
statistical analyses were performed
with SPSS (version 17.0, SPSS Inc,
Chicago, Illinois).
Mr Robert was supported by a
Fonds de Recherche du QuébecSanté (FRQS) master’s training
award, and Dr Ballaz was sup-
Number 8
Results
The characteristics of the participants are shown in Table 1. There
was no significant difference
between groups for age, height,
weight, sex, or body mass index
(P⬎.05). Dorsiflexion strength and
plantar-flexion strength were lower
in children with CP than in children
without CP (Pⱕ.05).
Resting heart rate in children with
CP was between 58 and 93 bpm,
with an average of 74 bpm (SD⫽10).
Resting heart rate in children without CP was between 53 and 81 bpm,
with an average of 68 bpm (SD⫽7).
Working heart rate in children with
CP was between 133 and 199 bpm,
with an average of 168 bpm
(SD⫽23). Working heart rate in children without CP was between 119
and 197 bpm, with an average of 158
bpm (SD⫽30). No significant difference was observed between groups
for resting heart rate and working
heart rate (P⬎.05).
No significant difference was
observed between groups for the
percentage of time spent at an intensity greater than 40% of HRR (P⬎.05)
(Figure). However, a main effect of
games was observed for the percentage of time spent at an intensity greater than 40% of HRR
(F⫽16.538; df⫽1,18; P⫽.001; effect
size⫽0.970). Participants spent
more time at an intensity greater
than 40% of the HRR in the jogging
game than in any of the other games.
In addition, the bicycling game was
significantly more demanding than
the snowboarding game (Figure).
The analysis of variance revealed
no significant difference between
groups (P⬎.05) for the secondary
measures obtained during game
play. The range of motion for lower
limb articulation was larger in the
August 2013
Figure.
Comparison of the relative time (%) (left axis) and actual time (minutes) (right axis) spent at an intensity greater than 40% of heart
rate reserve for groups and games. Effect sizes (d) are shown for each game. CP⫽cerebral palsy. Asterisk indicates P⬍.05.
Table 2.
Measures During Game Playa
Participants With CP
(nⴝ10)b
Measure
Participants Without CP
(nⴝ10)b
Groups
Groups ⴛ
Games
Games
Jogging
Bicycling
Jogging
Bicycling
F
P
d
F
8.88 (3.14)
5.93 (4.93)
6.72 (2.71)
4.19 (2.01)
2.228
.153
0.293
13.394
P
d
F
P
Active range of
motion (°)
Ankle
a
b
c
.002c
0.933
0.078
.783
c
0.989
0.305
.587
.009c
0.788
2.243
.152
⬍.001
Knee
20.81 (7.24)
15.27 (4.8)
19.63 (4)
15.30 (5.41)
0.069
.796
0.057
20.115
Hip
15.01 (6.24)
11.02 (4.92)
13.01 (4.25)
11.81 (4.58)
0.073
.789
0.058
8.514
Borg Scale score
11.8 (4.71)
10.3 (2.95)
11.89 (2.26)
9.6 (2.95)
0.028
.868
0.053
4.144
.058
0.484
0.119
.735
Motivation score
7.9 (2.88)
7.38 (2.72)
7.89 (1.90)
0.018
.894
0.052
0.031
.862
0.053
0.315
.583
7.64 (2.84)
CP⫽cerebral palsy, F⫽F statistic, d⫽effect size.
Data are reported as mean (standard deviation).
Values were significantly different (P⬍.05).
jogging game than in the bicycling
game (P⬍0.05) (Tab. 2). The children’s degree of interest in the different games did not vary (P⬎.05);
however, the perceived exertion, as
measured with the Borg Scale,
tended to differ among the games
(P⫽.058) (Tab. 2). Concerning the
linear regression analysis, no variable
was entered in the model because
the conditions were not met. Therefore, exercise intensity could not be
predicted by any of the secondary
measures.
August 2013
Discussion
Previous studies showed that exercise intensity levels while playing
the Wii can be sufficiently high in
children who are typically developing to benefit the cardiorespiratory system, especially if the lower
limbs are involved.44 However, it
was not known whether children
with CP could similarly benefit
from this system. The present study
showed similar exercise intensity
levels in children with CP and children without CP for all tested games.
This finding suggests that AVGC systems such as the Wii could be used
as an adjunct therapeutic tool to
increase the amount of physical
activity in children with CP, at least
for children who are ambulatory
without devices.
The present study also showed that
children with CP played in a fashion
similar to that of their counterparts who were healthy, as shown
by their similar ranges of motion for
lower limb articulation. All other
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Physical Therapy f
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secondary measures were similar
between the groups, with the exception of the level of strength at the
ankle, which was lower in children
with CP. Mockford and Caulton45
also showed that children with CP
had a lower level of ankle strength.
This reduction in strength, however, did not affect exercise intensity
levels. It should be noted that only
children who scored at level I or II
on the GMFCS participated in the
present study. These children had
minor motor dysfunctions that did
not seem to interfere with exercise
intensity.
The total relative amounts of time
spent above a moderate level of exercise intensity (above 40% of HRR)
differed greatly between the 2 games
expected to produce a high level of
exercise intensity (jogging and bicycling). Accordingly, the perception
of exertion, as measured with the
Borg Scale, was significantly higher
for jogging than for bicycling. This
difference could be explained by
the observation of a greater range of
motion in lower limb articulation
for the jogging game than for the
bicycling game, confirming previous observations that larger movements elicit greater exercise intensities.46 Another explanation could be
related to the different levels of complexity of the games. The bicycling
game involved dual tasks (moving
the legs while operating the remote
control). According to Baranowski
et al,47 a more complex game could
reduce exercise intensity levels in
children.
The ACSM recommends that children who are healthy should participate in a minimum of 60 minutes of
moderate to intense physical activity
daily. To meet that recommendation,
children would have to play the
equivalent of 95 minutes of the jogging game or 210 minutes of the
bicycling game. It is clearly unrealistic to expect children to achieve the
recommendations of the ACSM
solely by using the Wii. It should be
noted, however, that boys and girls
already spend averages of 59 and 23
minutes, respectively, playing passive video games each day (for a
review, see Marshall et al4). This sedentary playing time could be converted to active playing time and
complemented with other physical
activities. Because children with CP
often have poor cardiorespiratory
capacities, a smaller amount of physical activity is required to observe a
positive adaptation in their cardiorespiratory systems.51
A limitation of the present study was
the relatively small and heterogeneous sample; the results must be
confirmed with a larger sample.
However, the results confirmed the
findings of previous studies showing
that playing the Wii can result in
adequate exercise intensity in children without CP.10,12 More importantly, the results clearly showed
that playing the Wii Fit jogging and
bicycling games increased exercise
intensity as much as moderate to vigorous exercises in children with CP
(at GMFCS level I or II).
Conclusion
Despite the fact that the jogging
game was much more demanding
than the bicycling game, the levels of
interest in the games were similar.
This finding demonstrates that a
game can be both strenuous and
motivating at the same time; these
factors are important in successful
rehabilitation48 and for participation
in physical activity.12,49,50
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The regular use of the Wii bicycling
and jogging games could increase
the amounts of physical activity in
children with CP. This system can be
considered a low-cost, safe, readily
available, and efficient tool that can
be used at home to improve the
health of children with motor limitations such as CP. With proper supervision, this tool also could comple-
Number 8
ment the effort of clinicians to
increase daily physical activity levels
in their patients. Further studies
should examine the effects of longterm AVGC training in children with
CP. It also would be interesting to
evaluate the benefits of using the Wii
for children with CP at GMFCS level
III or higher.
Mr Robert, Dr Ballaz, and Dr Lemay provided
concept/idea/research design. All authors
provided writing and data collection and
analysis. Dr Lemay provided project management and fund procurement. Dr Ballaz
and Mr Hart provided consultation (including review of manuscript before submission).
The authors thank the children who participated in this study, their parents, and the
Programme des Déficits Moteurs Cérébraux
du Centre de Réadaptation Marie Enfant
for their collaboration. The authors report
no conflict of interest, and they alone are
responsible for the content and writing of
the article.
The study was approved by the Ethics Committee of the Sainte-Justine University Hospital Research Center.
Mr Robert was supported by a Fonds de
Recherche du Québec-Santé (FRQS) master’s training award, and Dr Ballaz was supported by CIHR-MENTOR postdoctoral training fellowship.
DOI: 10.2522/ptj.20120204
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Volume 93
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Research Report
Facial Pain Associated With
Fibromyalgia Can Be Marked by
Abnormal Neuromuscular Control:
A Cross-Sectional Study
Maı́sa Soares Gui, Cristiane Rodrigues Pedroni, Luana M. Martins Aquino,
Marcele Jardim Pimentel, Marcelo Correa Alves, Sueli Rossini, Rubens Reimão,
Fausto Berzin, Amélia Pasqual Marques, Célia Marisa Rizzatti-Barbosa
M.S. Gui, PT, MSc, Department of
Anatomy,
Piracicaba
Dental
School, State University of Campinas, Piracicaba, PO Box 52,
Limeira Avenue, 901, São Paulo,
Brazil 13414-903. Address all correspondence to Professor Gui at:
[email protected].
C.R. Pedroni, PT, MSc, PhD, Faculty of Philosophy and Science,
Universidade Estadual Paulista,
Marilia, São Paulo, Brazil.
L.M.M. Aquino, DDS, MSc, PhD,
Piracicaba Dental School, State
University of Campinas.
M.J. Pimentel, DDS, MSc, Department of Periodontology and
Prosthodontics, Piracicaba Dental
School, State University of
Campinas.
M.C. Alves, PhD, Piracicaba Dental School, State University of
Campinas.
S. Rossini, PhD, Division of Clinical
Neurology,
Sleep
Medicine
Advanced Research Group, Clinicas Hospital of the University of
São Paulo, University of São Paulo
School of Medicine, São Paulo,
Brazil.
R. Reimão, MD, MSc, PhD, Division of Clinical Neurology, Sleep
Medicine Advanced Research
Group, Clinicas Hospital of the
University of São Paulo, University
of São Paulo School of Medicine.
Background. Temporomandibular disorder (TMD) development in fibromyalgia
syndrome (FMS) is not yet fully understood, but altered neuromuscular control in FMS
may play a role in triggering TMD.
Objective. The purpose of this study was to verify the association between
neuromuscular control and chronic facial pain in groups of patients with FMS and
TMD.
Design. A cross-sectional study was conducted.
Methods. This study involved an analysis of facial pain and electromyographic
activity of the masticatory muscles in patients with FMS (n⫽27) and TMD (n⫽28). All
participants were evaluated according to Research Diagnostic Criteria for Temporomandibular Disorders and surface electromyography (SEMG). Myoelectric signal
calculations were performed using the root mean square and median frequency of
signals.
Results. The data revealed premature interruption of masticatory muscle contraction in both patient groups, but a significant correlation also was found between
higher median frequency values and increased facial pain. This correlation probably
was related to FMS because it was not found in patients with TMD only. Facial pain
and increased SEMG activity during mandibular rest also were positively correlated.
Limitations. Temporal conclusions cannot be drawn from the study. Also, the
study lacked a comparison group of patients with FMS without TMD as well as a
control group of individuals who were healthy.
Conclusions. Altered neuromuscular control in masticatory muscles may be
correlated with perceived facial pain in patients with FMS.
Author information continues on
next page.
this article at:
ptjournal.apta.org
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Number 8
August 2013
F. Berzin, DDS, MSc, PhD, Piracicaba Dental
School, State University of Campinas.
A.P. Marques, PT, MSc, PhD, Department of
Physical Therapy, Communication Science
and Disorders, Occupational Therapy, Medical College of the University of São Paulo.
C.M. Rizzatti-Barbosa, DDS, MSc, PhD,
Department of Prosthesis and Periodontology, Piracicaba Dental School, State University of Campinas.
[Gui MS, Pedroni CR, Aquino LMM, et al.
Facial pain associated with fibromyalgia can
be marked by abnormal neuromuscular control: a cross-sectional study. Phys Ther.
2013;93:1092–1101.]
Published Ahead of Print: April 18, 2013
Submitted: August 28, 2012
F
ibromyalgia syndrome (FMS) is
characterized by widespread
chronic musculoskeletal pain
and specific anatomical sites painful
to palpation (tender points).1,2 The
syndrome appears to be linked to
central neural mediation that alters
sensory processing and pain perception.3–5 Other symptoms frequently
associated with FMS include sleep
disturbance, fatigue, morning stiffness, anxiety, and depression.6
The coexistence of fibromyalgia and
myofascial pain associated with temporomandibular disorder (TMD) also
has been reported in the literature,7–11 and involvement of the masticatory muscles apparently aggravates the symptoms of FMS.7,8,12 In
addition, the literature on the prevalence of TMD symptoms in people
with FMS reports rates ranging from
59.3% to 80.6%.8,13–15
However, we believe these are not
merely coexisting conditions but
that fibromyalgia may play a role in
triggering TMD, given that electromyographic studies in FMS have indicated that sensitization of muscle
nociceptors is revealed by abnormal
patterns of reflex motor neuron
activation.16
Available With
This Article at
ptjournal.apta.org
• eFigure: Minimum, Maximum,
and Median Values of the Pain
Rating Index in Participants With
Fibromyalgia Syndrome
August 2013
In addition, analysis of the biceps
femoris muscle in people with fibromyalgia showed spinal cord hyperexcitability,17 and analysis of the
biceps brachialis muscle in people
with fibromyalgia showed significantly higher muscle fiber conduction velocity,18 whereas analysis of
the trapezius muscle in people with
FMS showed the median frequency
of the signal was reached in less time
than in individuals who were
healthy19 (ie, a higher number of
motor units were active at the beginning of the contraction). Therefore,
our hypothesis is that if these
changes also occur in the masticatory muscles, this finding could represent a relevant factor contributing
to the development of TMD in people with FMS.
It appears that diffuse pain originating from FMS, associated with sleep
disorders, may affect the performance of the masticatory muscles,
leading to an imbalance in muscle
function and impaired functioning of
the stomatognathic system, resulting
in facial pain.20,21 These centrally
generated pain conditions play a role
in the onset and persistence of clinically significant TMD; however, a
specific mechanism to explain this
relationship has not yet been
identified.10,12
Electromyography is a valuable tool
for investigating neuromuscular control.22 Electromyography signal
amplitude and frequency spectrum
can be used to characterize muscle
fatigue. Premature discontinuation
of muscle contraction can be determined by examining the behavior of
the median frequency over time during isometric contraction.23 In addition, median frequency values represent motor unit discharge rates, and
studying the pattern of recruitment
of motor units in the presence of
pain may help characterize muscle
response. This approach may allow
us to differentiate myofascial pain
from fibromyalgia or could suggest
hypotheses that explain TMD in people with FMS.
Therefore, the main objective of our
study was to verify the association
between neuromuscular control and
chronic facial pain in patients with
fibromyalgia and patients with TMD.
The secondary objective was to characterize facial pain in patients with
fibromyalgia.
Method
Study Design
A cross-sectional study was conducted in patients who were receiving treatment at the Clinicas Hospital
of the University of São Paulo and at
Volume 93
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Physical Therapy f
1093
the teaching clinic of the Piracicaba
Dental School from September 2009
to August 2010.
Participants
Female patients with FMS, clinically
diagnosed according to the American College of Rheumatology (ACR)
criteria of 19901,2 for the classification of FMS, were recruited from the
Clinicas Hospital of the University of
São Paulo. After screening using
inclusion and exclusion criteria,
these patients were examined and
diagnosed using the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD)24 by a
trained and qualified investigator.
The inclusion criteria for selection of
the FMS group were sex (female)
and the presence of TMD (myofascial pain). Exclusion criteria were
the presence of systemic diseases,
polyarthritis, exposure to macrofacial trauma, dislocated joints, use of
orthodontic braces, dental pain, and
the presence of sinusitis, ear infections, cancer, hormonal disorders, or
morbid obesity (body mass index
⬎40 kg/m2); the latter criterion was
included because an increase in
facial adipose tissue could attenuate
the SEMG signal.
Additionally, a TMD group of female
patients with facial pain only was
recruited and investigated. The
inclusion criteria for selection were
sex (female) and the presence of
TMD (myofascial pain). Exclusion
criteria were the same as those
applied for the FMS group plus the
presence of FMS diagnosis.
Sample Size
The sample size for this study was
calculated using the “Power Procedure” of the SAS System (release
9.2–TS Level 2M0, SAS Institute Inc,
Cary, North Carolina), assuming a
null correlation of .20, a theoretical
The Bottom Line
Myofascial pain associated with temporomandibular disorder (TMD) has
been related to fibromyalgia syndrome (FMS), and fibromyalgia symptoms
precede facial pain in patients with FMS. However, a specific mechanism
explaining these coexisting conditions has not been identified.
In this article, the authors hypothesize that FMS may play a role in
triggering TMD, because patients with FMS experience facial pain associated with a different surface electromyographic response. According to
the results of the study, it appears that the sensorimotor system fails to
inhibit muscle contraction with pain in FMS; however, it remains unclear
whether muscle contraction differences occurred before or after facial
pain.
If you’re a patient/caregiver, what might these
findings mean for you?
Fibromyalgia syndrome appears to have a series of characteristics that
could constitute predisposing or triggering factors for facial pain associated with TMD in patients with FMS.
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Pearson correlation of .65, 80%
power, and a .05 level of significance. After a pilot study,25 a sample
size of 27 participants per group was
estimated. After receiving a verbal
presentation of the project, the volunteers signed an informed consent
form prior to participating in the
study.
Procedure
Intensity of facial pain was assessed
by the visual analog scale (VAS), and
pain was analyzed qualitatively based
on the McGill Pain Questionnaire26,27 using the Pain Rating Index
(PRI). The PRI was calculated based
on the weighted means of the dimensions, as each category has a number
of different subcategories and
descriptors.
To further characterize the patients
with FMS, an evaluation was performed to determine quality of life
using the Fibromyalgia Impact Questionnaire (FIQ), validated for the Brazilian population.28 This questionnaire investigates the quality of life of
patients with fibromyalgia, where
the higher the score, the greater the
impact of FMS on quality of life.
Briefly, the questionnaire is scored
based on the mean value of M1,
which is the average of 7 items
(questions 4 –10) that have continuous measures (from 0 to 10) encompassing domains such as professional
difficulties, well-being, pain, fatigue,
morning stiffness, sleep disorders,
anxiety, and depression. To assess
quality of sleep, we used the Pittsburgh Sleep Quality Index (PSQI),29
validated for the Brazilian population.30 The PSQI provides a score of
severity and nature of sleep disorders during the preceding months.
The highest score is 21 points, and
scores above 5 indicate that sleep
quality has been compromised. The
reliability and validity of these tools
have been reported elsewhere.31–33
August 2013
Patients with FMS
Assessed for eligibility (n=41)
Patients with orofacial pain
Assessed for eligibility (n=33)
Enrollment
Allocated evaluation (n=27)
(questionnaires and
RDC/TMD)
Not meeting inclusion criteria
(n=8)
Without diagnosis of TMD
(n=4)
Declined to participate (n=2)
Allocated evaluation
(n=28)
(diagnosed by
RDC/TMD)
Not meeting inclusion
criteria (n=4)
Declined to participate
(n=1)
Allocation
Group IA: myofascial pain (n=22)
Group IB: myofascial pain with limited
opening (n=5)
Group IA: myofascial pain (n=23)
Group IB: myofascial pain with limited
opening (n=5)
Group II: disk disorders (n=4)
Group II: disk disorders (n=7)
Group III: joint disorders (n=5)
Analysis
Group III: joint disorders (n=18)
Electromyography examination (n=55)
Figure 1.
Flow diagram of participants’ enrollment in the study. FMS⫽fibromyalgia syndrome, TMD⫽temporomandibular disorder, RDC/
TMD⫽Research Diagnostic Criteria for Temporomandibular Disorders.
For TMD diagnosis, the RDC/TMD24
was used. Briefly, the RDC/TMD is
divided into 2 axes. Axis I assesses
joint movement, 20 sites of muscle
palpation and the lateral pole of the
temporomandibular joints (TMJs),
and the posterior region of these
joints, totaling 24 points of palpation. The RDC/TMD is proposed to
classify subtypes of temporomandibular disorder into 3 groups: (1) muscle disorders-myofascial pain (group
I), (2) disk displacement (group II),
and (3) joint disorders (group III).
Axis II measures the degree of mandibular disability, depression, nonspecific physical symptoms, the
presence of parafunctional habits,
and the degree of interference in
daily individual problems that fit into
psychological and social behaviors.34
To assess oral parafunctional behavAugust 2013
ior and bruxism on RDC/TMD axis II,
2 aspects were considered: clenching and grinding.34
SEMG
The SEMG signal was recorded
simultaneously by 4 electrodes
attached to the skin placed in the
region of the right and left temporalis and masseter muscles, following
the recommendations of the International Society of Electrophysiology
and Kinesiology.35 Briefly, simple
active differential surface electrodes
were used, composed of 2 parallel
bars of pure silver, 1 mm thick and
10 mm long, with a distance of 10
mm between electrodes, a 20-fold
increase (gain), an input impedance
of 10 ⍀,15 and a common-mode
rejection ratio of 92 dB. The electrodes were connected to a
MyosystemBr1-P84 (portable model)
signal acquisition module (DataHominis Tecnologia Ltda, Uberlândia, Minas Gerais, Brazil). The SEMG
signals were amplified 100-fold at a
frequency of 2 kHz and band-pass
filtered (20 –1,000 Hz, Butterworth
filter). The reference electrode was
placed at the ulnar styloid process
region and greased with gel, and the
active differential electrodes were
placed on the muscle bellies. Prior to
attaching the electrodes, the skin
was cleaned with 70% alcohol.
During the collection of the signals,
the participant remained in a sitting
position resting against the chair
back on a Frankfurt plane parallel
with the floor, eyes open, feet placed
flat on the floor, and arms resting on
the thighs. Three 5-second recordings of SEMG signals were collected
with the mandible at rest, and three
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Table 1.
Mean (SD) Values of Body Mass Index (BMI) of Patients With Fibromyalgia
Syndrome (n⫽27) and Scores Obtained on the Fibromyalgia Impact Questionnaire
(FIQ), Pittsburgh Sleep Quality Index (PSQI), Visual Analog Scale (VAS), and Total
Pain Rating Index (PRI) and Number of Words Chosen on the McGill Pain
Questionnaire (MPQ)
Variable
Measure
2
Anthropometric
BMI (kg/m )
Quality of life
FIQ (M1)a (0–10)
Sleep quality
PSQI (global score)
Widespread painb
VAS (cm) (0–10)
Facial pain
c
X (SD)
28.19 (5.23)
6.86 (1.41)
13.18 (4.37)
7.7 (2.45)
VAS (cm) (0–10)
4.47 (2.52)
MPQ, total PRI (0–78)
37.78 (12.21)
MPQ, number of words chosen (0–20)
15.15 (3.47)
a
M1⫽average of 7 items (questions 4 –10).
Widespread pain in patients with fibromyalgia syndrome.
c
Facial pain related to temporomandibular disorder in patients with fibromyalgia syndrome.
b
Figure 2.
Positive Spearman correlation between the pain reported by visual analog scale (VAS)
and root mean square (RMS) at mandibular rest of the anterior temporalis muscles
(R⫽.43806, P⫽.0223) and masseter muscles (R⫽.3414, P⫽.08) using for analysis the
next higher value of RMS in participants with fibromyalgia syndrome (n⫽27). *P⬍.05.
15-second recordings were collected
at maximum intercuspation (isometry), while clenching Parafilm M
(Bemis Company Inc, Neenah, Wisconsin) between the premolars and
molars to ensure the reliability and
effectiveness of the recording.36
Data acquisition was controlled by a
software program with 16-bit resolution (MyosystemBr1 software application) based on the root mean
square (RMS) and the median frequency of the myoelectric signal calculations. To observe the behavior of
the median frequency and RMS over
time during isometric contraction,
SEMG signal windows were defined
using a specific software program,
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disregarding the first and last window of the signal, while analyzing
the second, fifth, and ninth
windows.
On the SEMG analysis under maximum isometric contraction, physiological muscle fatigue was evident,
occurring when the median frequency shifted toward lower frequencies, which may be accompanied by an increase in the amplitude
of the SEMG signal.23
The electromyographic signal was
not normalized in this study because
the SEMG was carried out on a single
day, electrodes placed only once,
Number 8
and the pain reported by the participant compared with the participant’s SEMG signal.37,38
Data Analysis
Calculations were performed using
the SAS System, and the level of significance was set at .05. For analysis
of RMS at mandibular rest, the data
were subjected to an analysis of variance (ANOVA) and to Spearman correlation (R⬎.70⫽strong correlation,
.70⬎R⬎.40⫽moderate correlation,
and .40⬎R⬎.20⫽weak correlation).
For analysis of MNF during isometric
contraction at maximal clenching,
the data were subjected to an
ANOVA, followed by the Tukey post
hoc test. To complement the
ANOVA and test the effect of windows and covariables on median frequencies, the Tukey-Kramer multiple comparison test of means was
applied, maintaining a .05 level of
significance. Means of the slope coefficient of the linear regression line of
the electromyography signal spectrogram of the masticatory muscles
were compared by applying the
unpaired Student t test or MannWhitney U test at a .05 level of
significance.
Financial support for the study was
provided by Conselho Nacional de
Desenvolvimento Cientı́fico e Tecnológico (CNPq) (Ed. #70/2009) and
Coordenação de Aperfeiçoamento
de Pessoal de Nı́vel Superior (CAPES)
for the 2-year postgraduate sponsorship (#2009 –2010).
Results
Of the initial 82 patients, clinically
diagnosed with fibromyalgia according to the ACR criteria, 41 female
patients (mean age⫽53.2 years,
SD⫽5.61) agreed to participate.
After screening of these patients
using inclusion and exclusion criteria, 31 were recruited and subsequently assessed using the RDC/
August 2013
Table 2.
Mean (SD) Values of Median Frequency and Slope of the Linear Regression Line of the Electromyographic Signal of the Left
Masseter (ML), Right Masseter (MR), Left Anterior Temporalis (TL), and Right Anterior Temporalis (TR) Muscles in Isometric
Contraction (at Maximum Intercuspation) in the 3 Windows of the Surface Electomyography Signal of the Fibromyalgia
Syndrome (FMS) Group (n⫽27) and the Temporomandibular Disorder (TMD) Group (n⫽28)a
Median Frequency (Hz)
Muscle
ML
MR
TL
TR
a
Group
2nd Window
A
5th Window
B
Slope
9th Window
Median
C
⫺1.97 (2.5)
FMS
168.88 (47.08)
TMD
160.11 (52.60)A
152.83 (53.91)B
148.32 (54.48)B
⫺1.65 (2.4)
FMS
160.86 (51.34)A
155.03 (52.92)B
143.87 (50.20)C
⫺2.44 (2.7)
TMD
143.12 (33.85)A
134.51 (34.30)B
129.18 (36.51)B
⫺1.95 (2.4)
FMS
157.32 (46.71)A
152.37 (46.55)A
150.37 (46.71)A
⫺0.9 (3.46)
TMD
145.28 (27.67)A
138.56 (24.02)B
132.43 (24.22)C
⫺1.81 (2.4)
FMS
183.34 (59.05)A
172.73 (62.54)AB
166.89 (58.36)B
⫺2.3 (4.7)
TMD
150.04 (46.69)A
142.05 (43.81)B
139.33 (40.34)B
⫺1.48 (2.01)
164.37 (47.02)
155.16 (46.68)
P
.63
.48
.29
.23
Means (SD) of windowed signal followed by distinct letters differ based on the Tukey test (␣⫽.05).
TMD.24 Twenty-seven (87.1%) of
these patients (FMS group) received
at least one diagnosis of TMD and
participated in our study (Fig. 1).
Additionally, 33 female patients with
facial pain were investigated, but
only 28 (mean age⫽45 years,
SD⫽9.53) received TMD diagnoses
(Fig. 1) and agreed to participate
(TMD group).
In the FMS group, participants had
been diagnosed with FMS for a mean
of 8.51 years (SD⫽6.19) and with
facial pain for a mean of 4.23 years
(SD⫽5.01). Facial pain was less
intense than pain perceived in the
rest of the body (Tab. 1). In this
group, 62.9% of the volunteers were
overweight or obese, and 96.3% had
poor sleep patterns (PSQI⬎5), in
addition to reporting a high impact
of fibromyalgia on quality of life
(Tab. 1). There was no association
between poor sleep quality and
facial pain. Oral parafunctional
behavior such as clenching or grinding was reported by 74.1% of the
participants with FMS (axis II of the
RDC/TMD).
The descriptors from the McGill Pain
Questionnaire that best explained
the facial pain of these patients were
August 2013
“throbbing,” “tiring,” and “sickening,” which accounted for 59.2% of
the descriptions, followed by “nagging” and “pricking” (51.8%) (ie, a
predominance of descriptors from
the affective category). When asked
to indicate the painful region of the
face, participants with both TMD
and fibromyalgia cited the temporalis muscle (85.2%). For the PRI of the
McGill Pain Questionnaire, the categories that best described facial pain
were “affective” and “evaluative”
(eFigure, available at ptjournal.
apta.org). In the TMD group, oral
parafunctional
behavior
was
reported by all participants (axis II of
the RDC/TMD), and facial pain measured by the VAS was a mean of 3.27
(SD⫽3.03).
There were no significant differences in facial pain, age, and weight
in the sample (P⬎.05). However,
participants with TMD showed a
higher number of joint disorders
than participants with FMS (Fig. 1).
Electromyographic Analysis
Mandibular rest. In the FMS
group, for the anterior temporalis
muscles, a moderate positive correlation was found between heightened electromyographic activity
(measured by the RMS parameter)
and pain, whereas a weak correlation was found between the RMS at
rest and pain for the masseter muscles (Fig. 2). In other words, the
higher the activity of the anterior
temporalis muscles at mandibular
rest, the greater the facial pain. In
the TMD group, a weak and not statistically significant correlation was
found between the RMS and pain for
the masseter muscles (R⫽.4088,
P⫽.1654) and the anterior temporalis muscles (R⫽.3867, P⫽.1967).
Isometric contraction at maximal
clenching. We found a significant
decrease in the median frequency
values over time during isometric
contraction of masticatory muscles
in both study groups, but the coefficient of decrease (measured by
slope) did not differ between the
groups (Tab. 2). No significant variation was found among SEMG signal
amplitudes (measured by the RMS
parameter) in any of the muscles
studied here during the 15-second
isometric contraction. Therefore, we
tested only the effects of the VAS
covariable (facial pain) on the
median frequency, with results
showing that the higher the median
frequency value for the left masseter
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and right anterior temporalis muscles, the higher the value reported
on the VAS in the FMS group (Fig. 3).
Furthermore, equations with a positive slope for median frequency and
pain were found in the FMS group,
whereas the opposite occurred in
the TMD group (ie, a negative slope
for median frequency and pain)
(Fig. 4).
Discussion
Figure 3.
Equations from the analysis of variance with repeated measures to test the effects of
visual analog scale (VAS) covariable (facial pain) at maximal clenching on the median
frequency of the isometric contraction of the left masseter muscle (y⫽7.1898x⫹b) and
right anterior temporalis muscle (y⫽8.2928x⫹b) and the right masseter muscle
(y⫽4.3372x⫹b) and left anterior temporalis muscle (y⫽5.2546x⫹b) in the electromyographic signal windowing in patients with fibromyalgia syndrome (n⫽27). *P⬍.05.
Figure 4.
Equations from the analysis of variance with repeated measures to test the effects of the
visual analog scale (VAS) covariable (facial pain) at maximal clenching on the median
frequency of the isometric contraction of the left masseter muscle (y⫽⫺0.014x⫹b) and
right masseter muscle (y⫽⫺0.824x⫹b) and the right anterior temporalis muscle
(y⫽⫺25.41x⫹b) and left anterior temporalis muscle (y⫽⫺24.14x⫹b) in the electromyographic signal windowing in patients with temporomandibular disorder (n⫽28)
(P⬎.05).
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The main finding of our study was
that masticatory muscle fatigue
occurred in both groups, reflecting
the inability of both patients with
TMD and patients with FMS to perform efficient muscle contractions
with facial pain. However, a different
pattern of muscle activation was
observed in the FMS group compared with the TMD group, where
electromyographic findings were
correlated with facial pain.
The limitations of this study were the
small number of participants and the
lack of a comparison group of
patients with fibromyalgia without
TMD as well as a control group of
individuals who were healthy, precluding comparisons with normal
conditions. In addition, it remains
unclear whether muscle contraction
differences occurred before or after
facial pain because this crosssectional study prevented temporal
conclusions from being drawn.
However, our SEMG studies showed
differences in muscle recruitment
among participants evaluated in the
presence of facial pain, as there was
a significant correlation between
increase in motor unit discharge
rates (higher values of median frequency) of the masticatory muscles
and facial pain in the FMS group.
Therefore, we suggest these are not
merely coexisting comorbid conditions but that FMS may play a role in
the onset of facial pain.
August 2013
Because these muscles impaired by
FMS could already present a condition of premature interruption of
muscle contraction, contraction may
have occurred, discharging the
motor units at higher frequencies
(tetanic contraction) in order to activate the required contraction, which
is even more fatiguing, generating a
cycle of muscle fatigue and pain.
The integrated pain adaptation
model of Murray and Peck39 proposes that changes in muscle activity
limit movement and thereby protect
the sensorimotor system from further injury. With pain, a new, optimized motor unit recruitment strategy arises, leading to pain
minimization in order to maintain
homeostasis. In the TMD group, this
strategy appeared to occur (ie, these
patients’ need for homeostasis is met
by minimizing the generation of further pain at rest or during subsequent movement). On the other
hand, in the FMS group, these patterns of recruitment were not
adopted by the sensorimotor system.
Perhaps there is an abnormal nociceptive response that fails to produce a protective decrease in muscle
activation, even in the presence of
pain. This model also proposes that
under certain circumstances, if some
motor units are recruited in ways
they are not used to, more pain may
be generated, and the pathological
situation appears to occur in FMS.
Furthermore, sensitization of muscle
nociceptors is revealed by abnormal
patterns of reflex motor neuron activation in patients with FMS,16 and
the strength and endurance of these
muscle nociceptors are limited differently by nociceptive afferent feedback from exertion. Consequently,
fatigue and pain occur at a lower
workload in patients with FMS than
in individuals who are pain-free.16,40
Muscle fatigue associated with FMS
appears to be present in different
muscle groups,19,22,41 including the
August 2013
masticatory muscles, as observed in
this study, which may explain the
high prevalence of TMD in people
with FMS. In other words, it is possible that muscle fatigue is a predisposing factor for TMD in this patient
group.
The clinical relevance of our study is
the finding that a different pattern of
muscle activation occurred in people with FMS, where these results
may lead to new pathophysiological
insights into TMD in this group of
patients. We also observed that facial
pain in patients with FMS was most
frequently described by the affective
dimension of pain perception, indicating fear of pain and activity, anxiety, and depression.31,42,43
Fibromyalgia syndrome appears to
have a series of characteristics (parafunction34; muscle fatigue22; functional overload, anxiety, and stress43;
sleep disorders44; allodynia and
hyperalgesia4,45; and increased joint
friction10) that constitute predisposing and triggering factors for TMD.
Acting concomitantly, these factors
could easily exceed the limit of functional adaptation to stress in the TMJ,
leading to its dysfunction.
Moreover, because these factors are
inherent to FMS, they also act as perpetuating factors and may increase
the progression and chronicity of the
dysfunction. According to Cairns,46
the physiopathology of TMD
involves the association of these
mechanical factors, which, when
exceeding adaptive capacity, generate hypoxia, leading rapidly to the
production of proinflammatory cytokines and hence to degradation of
the articular cartilage. Clearly, more
research is needed to unravel the
relationship among muscle activation, central motor control failure,
and central sensitization to pain in
the clinical picture of FMS.
In conclusion, the current study
demonstrated that the intensity of
facial pain in people with FMS is
moderate and best characterized by
the affective dimension of the McGill
Pain Questionnaire. The masticatory
muscles present muscular fatigue in
patients with TMD and FMS; however, different patterns of muscle
activation are associated with pain in
people with FMS. In the present
study, we put forward the hypothesis that FMS can play a role in triggering TMD. It appears that the sensorimotor system fails to inhibit
muscle contraction with pain in people with FMS.
Professor Gui, Professor Pedroni, Dr Aquino,
Dr Pimentel, Dr Reimão, Professor Berzin,
and Professor Rizzatti-Barbosa provided concept/idea/research design. Professor Gui,
Professor Pedroni, and Professor RizzattiBarbosa provided writing. Professor Gui, Dr
Aquino, and Dr Pimentel provided data collection. Professor Gui, Professor Pedroni, Dr
Aquino, Dr Pimentel, Dr Alves, Dr Reimão,
Professor Berzin, Dr Marques, and Professor
Rizzatti-Barbosa provided data analysis. Dr
Rossini, Professor Berzin, and Professor
Rizzatti-Barbosa provided project management. Dr Pimentel, Dr Reimão, Professor Berzin, and Professor Rizzatti-Barbosa provided
study participants. Professor Berzin and Professor Rizzatti-Barbosa provided facilities/
equipment. Professor Berzin and Dr Marques
provided institutional liaisons. Professor Gui,
Professor Pedroni, Dr Aquino, Dr Pimentel,
Dr Rossini, Dr Reimão, and Professor RizzattiBarbosa provided consultation (including
review of manuscript before submission).
This study was approved by the Ethics Committee on Research Involving Human Subjects of the Piracicaba School of Dentistry,
State University of Campinas–UNICAMP,
Brazil, under protocol number 103/2009.
The study is registered in the International
Clinical Trial Registry under identification
number ACTRN12610000517077, according to the criteria established by the World
Health Organization and the International
Committee of Medical Journal Editors.
An abstract of the manuscript was presented
at ESB2010: 17th Congress of the European
Society of Biomechanics; July 4 – 8, 2010;
Edinburgh, United Kingdom.
Financial support for the study was provided
by Conselho Nacional de Desenvolvimento
Volume 93
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Cientı́fico e Tecnológico (CNPq) (Ed. #70/
2009) and Coordenação de Aperfeiçoamento de Pessoal de Nı́vel Superior (CAPES)
for the 2-year postgraduate sponsorship
(#2009 –2010).
DOI: 10.2522/ptj.20120338
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21 Solberg Nes L, Carlson CR, Crofford LJ,
et al. Self-regulatory deficits in fibromyalgia and temporomandibular disorders.
Pain. 2010;151:37– 44.
22 Maquet D, Croisier JL, Duponta C, et al.
Fibromyalgia and related conditions: electromyogram profile during isometric muscle contraction. Joint Bone Spine. 2010;
77:264 –267.
23 Basmajian JV, Deluca CJ. Muscle Alive:
Their Function as Revealed by Electromyography. Baltimore, MD: Williams &
Wilkins; 1985.
24 Dworkin S, LeResche L. Research diagnostic criteria for temporomandibular disorders: review, criteria, examinations, and
specifications, critique. J Cranio Mandib
Dis Fac Oral Pain. 1992;6:301–355.
25 Gui MS, Pedroni CR, Berni KS, et al. Electromyography activity and pain assessment of masticatory muscles in patients
with fibromyalgia and temporomandibular
disorder: a pilot study. Presented at: Proceedings of the 17th Congress of the European Society of Biomechanics; July 4 – 8,
2010; Edinburgh, United Kingdom.
26 Melzack R. The McGill Pain Questionnaire:
major properties and scoring methods.
Pain. 1975;1:277–299.
Number 8
27 Pimenta CAM, Teixeira MJ. Proposta de
adaptação do questionário de dor McGill
para a lı́ngua portuguesa. Rev Esc Enf USP.
1996;70:473– 483.
28 Marques AP, Santos AMB, Matsutani LA,
et al. Validation of the Brazilian version of
the Fibromyalgia Impact Questionnaire
(FIQ). Rev Bras Reumatol. 2006;46:24 –
31.
29 Buysse DJ, Reynolds CF, Monk TH, et al.
The Pittsburgh Sleep Quality Index: a new
instrument for psychiatric practice and
research. Psychiatry Res. 1989;28:193–
213.
30 Bertolazi NA, Fagondes SC, Hoff L, et al.
Validation of the Brazilian-Portuguese version of the Pittsburgh Sleep Quality Index.
Sleep Med. 2011;12:70 –75.
31 Pedroni CR, de Oliveira AS, Bérzin F. Pain
characteristics of temporomandibular disorder: a pilot study in patients with cervical spine dysfunction. J Appl Oral Sci.
2006;14:388 –392.
32 Smith MT, Wickwire EM, Grace EG, et al.
Sleep disorders and their association with
laboratory pain sensitivity in temporomandibular joint disorder. Sleep. 2009;32:779 –
790.
33 Turk DC, Robinson JP, Burwinkle T. The
prevalence of fear of pain and activity in
patients with fibromyalgia syndrome. J
Pain. 2004;5:483– 490.
34 Van der Meulen MJ, Ohrbach R, Aartman
IH, et al. Temporomandibular disorder
patients’ illness beliefs and self-efficacy
related to bruxism. J Orofac Pain. 2010;
24:367–372.
35 Merletti R. Standards for reporting EMG
data. J Electromyogr Kinesiol. 1999;9:III–
IV.
36 Biazotto-Gonzalez DA, Andrade DV, Gonzalez TO, et al. Correlation between temporomandibular dysfunction, cervical posture and quality of life. Rev Bras Cresc e
Desenv Hum. 2008;18:79 – 86.
37 Albertus-Kajee Y, Tucker R, Derman W,
Lambert M. Alternative methods of normalising EMG during cycling. J Electromyogr Kinesiol. 2010;20:1036 –1043.
38 Burden A. How should we normalize electromyograms obtained from healthy participants? What we have learned from over
25 years of research. J Electromyogr Kinesiol. 2010;20:1023–1035.
39 Murray GM, Peck CC. Orofacial pain and
jaw muscle activity: a new model. J Orofac
Pain. 2007;21:263–278.
40 Bengtsson A. The muscle in fibromyalgia.
Rheumatology (Oxford). 2002;41:721–
724.
41 Bazzichi L, Dini M, Rossi A, et al. Muscle
modifications in fibromyalgia patients
revealed by surface electromyography
(SEMG) analysis. BMC Musculoskelet Disord. 2009;10:36.
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42 De Peuter S, Van Diest I, Vansteenwegen
D. Understanding fear of pain in chronic
pain: interoceptive fear conditioning as a
novel approach. Eur J Pain. 2011;15:889 –
894.
43 Gormsen L, Rosenberg R, Bach FW, Jensen
TS. Depression, anxiety, health-related
quality of life and pain in patients with
chronic fibromyalgia and neuropathic
pain. Eur J Pain. 2010;14:127.e1–127.e8.
August 2013
44 Schütz TCB, Andersen ML, Tufik S. The
influence of orofacial pain on sleep pattern: a review of theory, animal models
and future directions. Sleep Med. 2009;10:
822– 828.
45 Woolf CJ. Central sensitization: implications for the diagnosis and treatment of
pain. Pain. 2010;152:S2–S15.
46 Cairns BE. Pathophysiology of TMD pain:
basic mechanisms and their implications
for pharmacotherapy. J Oral Rehab. 2010;
37:391– 410.
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1.0
27
Pondered Mean
0.8
0.6
0.4
0.2
0.0
Sensory
Affective
Evaluative
Mixed
Dimensions of McGill Pain Questionnaire
eFigure.
Minimum, maximum, and median values of the Pain Rating Index (weighted means of the values attached to each word in each
category of the McGill Pain Questionnaire) in participants with fibromyalgia syndrome (n⫽27).
August 2013 (eAppendix, Gui et al)
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1
Research Report
Psychometric Properties of the MiniBalance Evaluation Systems Test
(Mini-BESTest) in CommunityDwelling Individuals With
Chronic Stroke
Charlotte S.L. Tsang, Lin-Rong Liao, Raymond C.K. Chung, Marco Y.C. Pang
C.S.L. Tsang, MSc, Department of
Rehabilitation Sciences, Hong
Kong Polytechnic University,
Hung Hom, Hong Kong.
L-R. Liao, MPT, Department of
Kong Polytechnic University, and
Department of Physiotherapy,
Guangdong
Provincial
Work
Injury Rehabilitation Hospital,
Guangzhou, China.
R.C.K. Chung, PhD, Department
of Rehabilitation Sciences, Hong
Kong Polytechnic University.
M.Y.C. Pang, PhD, Department of
Kong Polytechnic University,
Hung Hom, Hong Kong. Address
all correspondence to Dr Pang at:
[email protected].
[Tsang CSL, Liao L-R, Chung RCK,
Pang MYC. Psychometric properties of the Mini-Balance Evaluation
Systems Test (Mini-BESTest) in
community-dwelling individuals
with chronic stroke. Phys Ther.
2013;93:1102–1115.]
Association
April 4, 2013
Background. The Mini-Balance Evaluation Systems Test (Mini-BESTest) is a new
balance assessment, but its psychometric properties have not been specifically tested
in individuals with stroke.
Objectives. The purpose of this study was to examine the reliability and validity
of the Mini-BESTest and its accuracy in categorizing people with stroke based on fall
history.
Design. An observational measurement study with a test-retest design was
conducted.
Methods. One hundred six people with chronic stroke were recruited. Intrarater
reliability was evaluated by repeating the Mini-BESTest within 10 days by the same
rater. The Mini-BESTest was administered by 2 independent raters to establish interrater reliability. Validity was assessed by correlating Mini-BESTest scores with scores
of other balance measures (Berg Balance Scale, one-leg-standing, Functional Reach
Test, and Timed “Up & Go” Test) in the stroke group and by comparing Mini-BESTest
scores between the stroke group and 48 control participants, and between fallers (ⱖ1
falls in the previous 12 months, n⫽25) and nonfallers (n⫽81) in the stroke group.
Results. The Mini-BESTest had excellent internal consistency (Cronbach
alpha⫽.89 –.94), intrarater reliability (intraclass correlation coefficient [3,1]⫽.97),
and interrater reliability (intraclass correlation coefficient [2,1]⫽.96). The minimal
detectable change at 95% confidence interval was 3.0 points. The Mini-BESTest was
strongly correlated with other balance measures. Significant differences in MiniBESTest total scores were found between the stroke and control groups and between
fallers and nonfallers in the stroke group. In terms of floor and ceiling effects, the
Mini-BESTest was significantly less skewed than other balance measures, except for
one-leg-standing on the nonparetic side. The Berg Balance Scale showed significantly
better ability to identify fallers (positive likelihood ratio⫽2.6) than the Mini-BESTest
(positive likelihood ratio⫽1.8).
Limitations. The results are generalizable only to people with mild to moderate
chronic stroke.
Conclusions. The Mini-BESTest is a reliable and valid tool for evaluating balance
in people with chronic stroke.
this article at:
ptjournal.apta.org
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S
troke is a major cause of disability and global disease burden.1
Dysfunction in balance control
is one of the most common physical impairments observed after
stroke.2,3 Compromised balance ability has been associated with reduced
ambulatory function,4 poorer performance in activities of daily living
(ADL),5 and restricted societal participation.6 Impaired balance also is a
significant predictor of falls7 and
long-term institutionalization.8
Much effort has been directed
toward enhancing balance function
in people with stroke.9 –11 Balance
control is complex and involves various aspects such as ability to maintain a body position, postural
responses to external perturbations,
anticipatory postural adjustments,
and sensory integration.12 To obtain
a clearer understanding of balance
dysfunctions after a stroke and to
better assess the effect of intervention programs, a standardized assessment of balance function is essential.
Many clinical tools are available to
assess balance in individuals with
stroke.13,14 Some of the most commonly used balance assessment tools
in stroke rehabilitation are the Berg
Balance Scale (BBS),15 Functional
Reach Test (FRT),16 Timed “Up &
Go” Test (TUG),17 and one-leg standing (OLS).18,19 However, they are not
without their limitations. For example, important aspects of dynamic
balance control that reflect balance
challenges during ADL are missing in
the BBS.20 Leroux et al21 found that
among ambulatory patients with
chronic stroke, improvement in postural stability observed after exercise
intervention was poorly correlated
with change in the BBS score. On the
other hand, OLS, FRT, and TUG,
being single-task assessments, are
unable to provide information on
which postural control subsystem is
dysfunctional and have a limited role
in directing treatment.13 Significant
floor or ceiling effects also have been
August 2013
identified in the BBS, OLS, and
FRT.22–24 Furthermore, the BBS25,26
and TUG27 have been criticized for
their limited ability to predict falls in
people with stroke. Certain balance
assessment tools that are specifically
designed for people with stroke also
have similar limitations. For example, the balance subscale of the FuglMeyer test28 has been shown to have
significant floor effects.22
The Balance Evaluation Systems Test
(BESTest) is a relatively new multitask balance assessment developed
to identify specific postural control
problems (ie, biomechanical constraints, stability limits, postural
responses, anticipatory postural
adjustments, sensory orientation,
dynamic balance during gait, and
cognitive effects).20,29 However, this
36-item assessment takes 30 to 35
minutes to complete and may not be
feasible in real clinical settings,
where time constraint is often a
major concern. A shorter version of
the test, the 14-item Mini-BESTest,
has recently been developed.20 It
takes only 10 minutes to complete,
and good intrarater and interrater
reliability have been reported in a
sample of people with mixed conditions.30 Recent studies further
showed that the Mini-BESTest has
good interrater and intrarater reliability and concurrent validity31,32
and is useful in predicting falls33,34 in
patients with Parkinson disease
(PD). However, the psychometric
properties of the Mini-BESTest have
not been specifically evaluated in the
stroke population. Additionally, no
study has evaluated the ability of the
Mini-BESTest in distinguishing fallers
from nonfallers among individuals
with stroke. The current study was
undertaken to (1) examine the reliability and validity of the MiniBESTest and (2) compare the MiniBESTest with 4 other balance
measures based on the floor and ceiling effects and on sensitivity and
specificity
for
distinguishing
between individuals with and without a history of falls in a group of
community-dwelling people with
chronic stroke.
Method
Study Overview
This was an observational measurement study. Floor and ceiling effects,
reliability (internal consistency,
intrarater and interrater), and validity
(concurrent, convergent, discriminant, known-groups) of the MiniBESTest were assessed in a sample of
people with stroke. To establish
known-groups validity, a control
group was included to enable us to
assess the differences in MiniBESTest scores between the stroke
group and control group. The ability
of the Mini-BESTest to distinguish
between people with stroke with
and without a history of falls also was
examined and compared with that of
4 other balance measures (ie, BBS,
TUG, OLS, and FRT). All of the raters
involved in the study were physical
therapists who had more than 10
years of relevant experience and
were well trained to administer all of
the balance assessment tools used in
this study.
Participants and Sample Size
Calculations
Participants were recruited during
the period June 2009 and December
2010. Individuals with stroke were
recruited from a local rehabilitation
center and community self-help
groups on a volunteer basis (ie, convenience sampling). Each participant was interviewed during the first
assessment session. Ability to understand verbal instructions was one of
the inclusion criteria. An individual
was considered to have fulfilled this
criterion if he or she managed to
carry out a normal conservation with
the assessor. Other inclusion criteria
for the stroke group were: a diagnosis of stroke for more than 6 months,
community-dwelling, and aged 18
years or older. The exclusion criteria
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were: pain during performance of
daily activities, neurological conditions in addition to stroke, other conditions that affect balance (eg,
Ménière disease), and any other serious illnesses that precluded participation. Control individuals were
recruited from the community for
comparison. The eligibility criteria
were the same as those used in the
stroke group, except that the control
participants did not have a history of
stroke. All participants provided
written informed consent before
enrollment in the study. All procedures were conducted in accordance
with the Declaration of Helsinki.
All sample size calculations were
done prior to enrollment of participants and were based on an alpha
level of .05 (2-tailed) and a power of
0.8 (NCSS and PASS 2005, NCSS LLS
Co, Kaysville, Utah). For reliability
analysis, a coefficient of .75 or
greater was generally considered to
be acceptable.35 Leddy et al32 found
that the Mini-BESTest had excellent
intrarater and interrater reliability in
people with PD, with intraclass correlation coefficient (ICC) values of
.92 and .91, respectively. A similar
reliability coefficient was expected
in this study. Thus, the acceptable
reliability and expected reliability
was set at ICC⫽.75 and ICC⫽.90,
respectively.32 For establishing interrater reliability between 2 raters, a
sample of 26 patients with stroke
was required. As establishing intrarater reliability required 2 assessment sessions, a 10% attrition rate
was estimated, yielding a minimum
sample of 30 participants.
A study by King et al31 showed a
strong correlation between the MiniBESTest and the BBS in patients with
PD (r⫽.79; large effect size). Therefore, for analysis of concurrent and
convergent validity, a large effect
size was expected when the MiniBESTest was correlated with other
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viduals with stroke. Using the conventional value of a large effect size
(r⫽.5) in the sample size calculation,35 the minimum number of participants required for the analysis of
concurrent validity would be 26.
The Mini-BESTest scores obtained
from the stroke group were compared with those from the control
group to establish known-groups
validity. Horak et al29 compared the
BESTest total score between patients
with different balance problems
(X⫽74.5, SD⫽9.0) and controls
without
disabilities
(X⫽90.6,
SD⫽4.8), and the effect size was
large (Cohen d⫽1.8). We expected
the Mini-BESTest to also have good
ability to discriminate between the 2
groups. Using the conventional value
of a large effect size (Cohen d⫽0.8)
for calculation,35 a minimum of 26
participants per group would be
required for this analysis.
We also were interested in determining whether the Mini-BESTest scores
and other balance tests could differentiate people with stroke with and
without a history of falls. Receiver
operating characteristic (ROC) curve
plots were used for this analysis.35
An area under the curve (AUC) value
of 0.7 to 0.8 was generally considered to be acceptable.36 Duncan et
al34 showed that the Mini-BESTest
had good ability to identify fallers
among patients with PD, with an
AUC value of 0.86. The acceptable
and expected AUC values thus were
set at 0.7 and 0.9, respectively.36 Previous studies in community-dwelling
individuals with stroke demonstrated a fall rate of 23% to 73%.7,37–39
Assuming that the proportion of
fallers was 30% in our stroke group,
a minimum of 60 individuals with
stroke (fallers: n⫽18; nonfallers:
n⫽42) would be required for ROC
curve plots. In summary, a minimum
of 60 and 26 individuals would be
recruited from the stroke and control groups, respectively.
Number 8
Procedure
Stroke group. In the initial assessment (session 1), relevant demographic data (eg, age, medical history) and fall history were obtained
from interviewing the participants.
To calculate body mass index (BMI,
in kg/m2), height (in meters) and
weight (in kilograms) were measured with a stadiometer (Health O
Meter, Alsip, Illinois). Each participant was evaluated with the MiniBESTest, 4 additional balance assessments (BBS, FRT, OLS, and TUG) and
other measures (Chedoke-McMaster
Stroke Assessment, Modified Ashworth Scale [MAS], Activitiesspecific Balance Confidence [ABC]
Scale, Abbreviated Mental Test
[AMT], Geriatric Depression Scale–
short form [GDS], and Oxfordshire
Community Stroke Project Classification). Either rater 1 or rater 2 conducted the assessments in session 1.
The first 30 participants assessed by
rater 2 in session 1 also were evaluated with the Mini-BESTest a second
time by another independent rater
(rater 3) in the same session.
Whether rater 2 or rater 3 administered the Mini-BESTest first was
determined randomly by drawing
lots. Intermittent rest periods were
given throughout the session. The
typical duration of session 1 was 2.5
hours, including the rest periods.
Interrater reliability of the MiniBESTest was determined by comparing the scores given by raters 2 and 3
in session 1.
The 30 participants with stroke who
were evaluated for interrater reliability also participated in the intrarater
reliability experiments. A second
assessment session (session 2) was
held within 10 days after session 1.
The participants did not receive any
physical therapy intervention during
the period between sessions 1 and 2.
In session 2, each of the 30 participants was evaluated with the MiniBESTest once by rater 2. Session 2
August 2013
was typically 20 minutes in duration.
Intrarater reliability was established
by comparing the Mini-BESTest
scores given by rater 2 in sessions 1
and 2.
Control group. The participants
in the control group underwent one
assessment session conducted by
rater 1. Demographic data (eg, age,
medical history), height, and weight
were obtained using the same methods as in the stroke group described
above. The Mini-BESTest was administered once. Comparing the MiniBESTest scores of the control group
with those of the stroke group
would be useful in determining the
known-groups validity. No other
measures were administered to the
control group.
Measures
Fall history. Information on fall
history was obtained through interview of participants. Those who had
experienced one or more falls in the
previous 12 months were considered to have a positive fall history.
Mini-BESTest. The Mini-BESTest
is a 14-item performance-based measure of balance disorders. The tasks
involved varied in difficulty and covered different balance subsystems,
including responses to external perturbations, anticipatory postural
adjustments, stability in gait, and sensory orientation. Each task was rated
from an ordinal scale of 0 to 2. Items
3 (stand on one leg) and 6 (compensatory stepping correction in lateral
direction) assessed both sides, and
only the side with a lower score was
used for calculating the total score.20
When reporting the item scores,
however, the results of both the
paretic and nonparetic sides were
shown for these 2 items. The total
score ranged from 0 to 28, with
higher scores denoting better balance ability.
Other balance measures. The
BBS is a 14-item assessment of functional balance. Each task was rated
from 0 to 4, yielding a possible maximum total score of 56. Higher
scores are indicative of better balance.15 The BBS has shown good
interrater and intrarater reliability
(ICC⬎.90) and concurrent validity
(correlation with Postural Assessment Scale for Stroke Patients:
r⫽.92–.95) in individuals with
stroke.15,22,40
The FRT measures balance by assessing the limit of stability.16 The maximum distance (in centimeters) an
individual could reach forward
beyond arm’s length on a fixed base
of support was measured. Its interrater reliability (ICC⫽.99) and validity
(correlation with the BBS: r⫽.619) in
people with stroke are well established.40 A score of 0 cm was given
for participants who were unable to
maintain the standing position without external support.
The OLS test measures the time (in
seconds) an individual can stand on
one leg (either side).18 Participants
were asked to stand on one leg with
eyes open and hands placed on the
hips. Using a stopwatch, timing commenced when the foot left the
ground and stopped when the same
foot touched the ground, when the
individual’s hand swung away from
the hips, or when OLS was maintained for a period of 1 minute. Oneleg standing was tested on both sides
in the current study. One-leg standing has shown good intrarater reliability (nonparetic side: ICC⫽.88,
paretic side: ICC⫽.92) and significant correlation with the BBS
(r⫽.65) in people with stroke.18 A
score of 0 second was given for participants who were unable to maintain the standing position without
external support.
The TUG measures the time (in seconds) an individual required to get
August 2013
up from an armed chair, walk 3 m
with normal walking pace, turn
around, walk back, and sit down
again.17 Use of a walking aid was
allowed if necessary. The TUG has
shown good test-retest reliability
(ICC⫽.96) and concurrent validity
(correlation with Community Balance and Mobility Scale: rho⫽⫺.75)
in individuals with stroke.41,42
Measures of other related functions. The Impairment Inventory
of the Chedoke-McMaster Stroke
Assessment was used to assess the
motor recovery of arm, hand, leg,
and foot in the stroke group.43 Each
of the 4 body parts was rated on a
7-point scale, with a higher score
indicating better motor recovery.
Good intrarater (ICC⫽.98) and interrater reliability (ICC⫽.97) have been
reported in people with stroke.43
The MAS, a 6-point ordinal scale, was
used for assessing muscle tone
around the ankle joint of the affected
leg (0⫽no increase in muscle tone,
4⫽part rigid in flexion and extension).44 The intrarater and interrater
reliability of the MAS in people with
stroke
are
well
established
(kappa⬎.8).44
The ABC Scale was used for measuring balance confidence.45 Participants were asked to rate their confidence in their balance associated
with performing 16 listed daily tasks
from 0% (absolutely no confidence)
to 100% (fully confident). The average score of the 16 items was calculated. The ABC Scale has shown high
test-retest reliability (ICC⫽.87) and
concurrent validity (correlation with
the BBS: ␳⫽.36 and with gait speed:
␳⫽.48) among individuals with
chronic stroke.46,47
Other measures. The Oxfordshire Community Stroke Project
Classification was used to identify
the clinical stroke subtypes.48 The
intrarater agreement and interrater
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agreement for the classification was
moderate to good, with kappa values
of .48 to .83 and .54 to .64,
respectively.49,50
The AMT was used to assess cognitive function.51 The AMT has shown
good internal consistency (Cronbach
␣⫽.81), interrater reliability (ICC⫽
.99), and concurrent validity (correlation with Mini-Mental State Examination: r⫽.86) among older adults.52
It also is able to differentiate
between individuals with and without cognitive impairments (Pⱕ
.001).52
The 15-item GDS was used to indicate the severity of depressive symptoms (0 – 4⫽no depression, 5–10⫽
mild depression, and ⱖ11⫽severe
depression).53,54 The GDS has shown
good test-retest reliability (ICC⫽.75)
in people with stroke.54
Data Analysis
All statistical analyses were performed using SPSS 18.0 software
(SPSS Inc, Chicago, Illinois), unless
otherwise indicated. The significance level was set a priori at ⱕ.05.
Floor and ceiling effects. The
skewness (␥1) of the distribution of
scores was first assessed for each balance measure. Positive skewness
reflects a floor effect and negative
skewness indicates a ceiling effect
for the Mini-BESTest, BBS, OLS, and
FRT, whereas the opposite is true for
the TUG.31 R Statistical Software
with Bootstrapping methods (version 2.15.2, Bell Laboratories, Murray Hill, New Jersey) was used to
compare the degree of skewness in
distribution of scores between the
Mini-BESTest and other balance measures.31 To further explore the floor
and ceiling effects, the proportion of
participants with the lowest and
highest possible scores was examined.23 Floor or ceiling effects
greater than 20% were considered to
be significant.23
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Reliability. Using
the
data
obtained from the stroke group, the
internal consistency of the MiniBESTest was assessed by Cronbach
alpha. Intraclass correlation coefficients were used to determine the
intrarater (ICC [3,1]) and interrater
(ICC [2,1]) reliability of the MiniBESTest total score. An ICC ⬎.75 is
indicative of good reliability, and an
ICC of .5 to .75 is indicative of
moderate reliability.55 The kappa
statistic was used to examine the
intrarater and interrater reliability
of each individual test item (kappa:
.81⫽almost perfect agreement, .61–
.8⫽substantial agreement, .41–.6⫽
adequate agreement, .21–.4⫽fair
agreement, and 0 –.2⫽slight agreement).35 Using the intrarater reliability results, the minimal detectable
change at the 95% confidence interval (MDC95) was computed using the
following formula35:
MDC95 ⫽ 1.96 ⫻ SEM ⫻ 公2
The standard error of measurement
(SEM) value of the Mini-BESTest total
score was derived from the following formula35:
SEM ⫽ Sx公(1 ⫺ rxx),
where Sx is the standard deviation of
the Mini-BESTest total score and rxx
is the reliability coefficient.
Validity. For the stroke group
data, the Spearman rho was used to
examine the degree of association of
the Mini-BESTest total scores (measured in the first session) with the
following: (1) other established balance measures (ie, BBS, FRT, TUG,
and OLS) (ie, concurrent validity),
(2) instruments measuring attributes that supposedly are related
to balance function (ie, ChedokeMcMaster Stroke Assessment leg and
foot impairment score and ABC
Scale) (ie, convergent validity), and
(3) measures that assess unrelated
Number 8
characteristics (ie, GDS and AMT)
(ie, discriminant validity).
In addition to assessing convergence
and discrimination, another way to
examine the construct validity of the
Mini-BESTest was to evaluate the
known-groups validity. A test with
good known-groups validity should
be able to distinguish individuals
with good balance ability from those
with poor balance ability. Comparisons of Mini-BESTest total and item
scores were made between the
stroke and control groups, and
between participants with and without a history of falls in the stroke
group, using the Mann-Whitney U
test, as the total scores were not
normally distributed (checked by
Kolmogorov-Smirnov test) and the
item scores were ordinal in nature.
In Mann-Whitney U test, the
between-group comparison was
based on rank ordering of the raw
scores.35 Considering the data of the
2 groups together, the scores were
ranked from the smallest to largest.
For example, the lowest score was
assigned the rank of 1, and the next
smallest value was assigned the rank
of 2. When 2 or more scores were
tied, they were each given the same
rank, which was the average of the
ranks they occupied. For example, if
there were 3 scores with the smallest
value, they occupied ranks 1, 2, and
3. Thus, they were each given the
rank of 2 (the average of 1⫹2⫹3).35
The rank scores of each group then
were summed and divided by the
number of participants in the group
to yield the mean rank score. A
higher mean rank reflected an overall better balance ability as a group.
To further compare the Mini-BESTest
with other balance measures in differentiating between people with
stroke with and without a history of
falls, ROC curves were constructed.
The AUC derived from the MiniBESTest data then was compared
with that of other balance measures,
August 2013
using the chi-square test for comparing the areas under 2 or more correlated ROC curves (SigmaPlot version
12.3, Systat Software Inc, San Jose,
California).56 For each ROC curve,
the score that yielded the largest
Youden index (sensitivity ⫹ [1 ⫺
specificity]) was chosen as the cutoff
score. The positive and negative likelihood ratios (LR⫹ and LR⫺) and
their 95% confidence intervals (95%
CI) were computed using an online
CI calculator.57 As 4 participants
were unable to ambulate without
manual assistance and thus did not
complete the TUG, their data were
not included for the comparison of
skewness and AUC between the
Mini-BESTest and the TUG.
Table 1.
Characteristics of Participantsa
Descriptor
A total of 106 individuals with stroke
(73 men, 33 women) and 48 controls
(28 men, 20 women) participated in
the study. The participant characteristics are shown in Table 1. Seventy
participants (66.0%) in the stroke
group did not require any walking
aid for ambulation. Twenty-five individuals (23.6%) in the stroke group
had a history of falls, 7 (6.6%) of
whom were recurrent fallers (ie, 2 or
more falls during the previous 12
months).
Four participants required physical
assistance to ambulate and thus were
unable to complete the TUG. Three
individuals were unable to maintain
the standing position without external support and were given a score
of 0 for the OLS and FRT. There were
no significant differences in any of
the demographic variables (eg, age,
proportion of men and women, BMI)
between the stroke and control
groups.
Score Distribution and
Ceiling and Floor Effects
The score distribution of the MiniBESTest within the stroke group is
shown in Figure 1A, and those of the
BBS, FRT, TUG, and OLS are shown
August 2013
Control Group
(nⴝ48)
P
57.1 (11.0)
60.2 (9.3)
.09
73/33
28/20
.20
24.9 (3.8)
23.9 (3.1)
.11
Demographics
Age, y
Sex (male/female), n
Body mass index, kg/m
2
Poststroke duration, y, median (IQR)
2.9 (1.2–5.5)
Hemiplegic side (left/right), n
46/60
Chedoke McMaster Stroke Assessment, median
(IQR)
Leg (1–7)
4.0 (4.0–5.0)
Foot (1–7)
3.0 (2.8–4.0)
Arm (1–7)
3.0 (2.8–5.0)
Hand (1–7)
3.0 (2.0–5.0)
Type of stroke
TACI/PACI/PCI/LCI/hemorrhage/unknown, n
Results
Stroke Group
(nⴝ106)
0/15/9/32/46/4
Modified Ashworth Scale (0–4), median (IQR)
1.5 (1.0–2.0)
Walking aid for indoor walking
None/cane/quadripod/wheelchair/others, n
70/11/14/4/7
Geriatric Depression Scale (0–15), median
(IQR)
0/0/0/0/0
5.0 (3.0–9.0)
Abbreviated Mental Test (0–10), median (IQR)
10.0 (9.0–10.0)
Activities-specific Balance Confidence (ABC)
Scale (0–100)
71.3 (31.4)
Balance performance, median (IQR)
Mini-BESTest (0–28)
19.0 (14.0–22.0)
Berg Balance Scale (0–56)
54.0 (50.0–56.0)
Functional Reach Test, cm
25.4 (22.9–30.5)
One-leg standing: paretic side, s
27.0 (26.0–27.0)
1.3 (0.8–4.4)
One-leg standing: nonparetic side, s
12.7 (4.4–36.0)
Timed “Up & Go” Test, s
16.6 (12.1–35.2)
a
Values are mean⫾SD unless otherwise indicated. IQR⫽interquartile range, LCI⫽lacunar circulation
infarct, Mini-BESTest⫽Mini-Balance Evaluation Systems Test, PACI⫽partial anterior circulation infarct,
PCI⫽posterior circulation infarct, TACI⫽total anterior circulation infarct.
in Figure 1B–F. We found that the
Mini-BESTest had significantly less
skewness than other balance measures (Pⱕ.001), except OLS on the
nonparetic side (P⫽.965) (Tab. 2).
The proportion of participants with
the lowest and highest possible MiniBESTest scores was 0% and 0.9%,
respectively. The BBS had the most
severe ceiling effect, with 32% of the
individuals achieving the highest
possible score.
Reliability Analysis
Thirty individuals with stroke participated in the reliability assessment.
The Mini-BESTest demonstrated
good internal consistency, with
Cronbach alpha values of .89, .93,
and .94 for raters 1, 2, and 3, respectively. Intrarater reliability of the
Mini-BESTest total score was excellent (ICC [3,1]⫽.97, Pⱕ.001), yielding an MDC95 value of 3.0 points.
The Mini-BESTest total score also
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1107
Figure.
Score distribution of the balance tests. Frequency distributions of scores on the (A) Mini-Balance Evaluation Systems Test (MiniBESTest), (B) Berg Balance Scale (BBS), (C) Functional Reach Test (FRT), (D) Timed “Up & Go” Test (TUG), (E) one-leg standing (OLS)
(paretic side), and (F) OLS (nonparetic side) are shown. The data of 106 individuals with stroke are shown, except for the TUG, which
was based on 102 participants with stroke only, as 4 participants were unable to walk without manual assistance.
1108
f
Physical Therapy
Volume 93
Number 8
August 2013
showed excellent interrater reliability (ICC [2,1]⫽.96, Pⱕ.001). When
the test items were analyzed separately, adequate to excellent intrarater and interrater reliability were
found for all items (Tab. 3), except
for item 5 (compensatory stepping
correction in backward direction),
item 6 (compensatory stepping correction in lateral direction), and item
8 (stand on foam surface with eyes
closed), which showed fair reliability
(kappa⫽.30 –.40).
Table 2.
Comparison of Mini-BESTest With Other Balance Measures: Floor and Ceiling Effectsa
Balance Measure
Skewness
(␥1)
Floor Effect
(% Participants
With Lowest
Possible Score)
Ceiling Effect
(% Participants
With Highest
Possible Score)
⫺0.81
0
0.9
Berg Balance Scale (0–56)
⫺2.69b
0
32.1
Functional Reach Test, cm
⫺1.15b
2.8
NA
One-leg standing: paretic side, s
4.06b
13.2
0.9
One-leg standing: nonparetic side, s
0.80
7.5
14.2
Timed “Up & Go” Test, s
1.69b,c
NA
NA
a
Mini-BESTest⫽Mini-Balance Evaluation Systems Test, NA⫽not applicable.
Significant difference in skewness compared with the Mini-BESTest (Pⱕ.001).
The analysis of skewness was based on 106 participants with stroke, except for the Timed “Up & Go”
Test data, which were based on 102 people with stroke only.
b
Validity Analysis
Concurrent validity. In the stroke
group, significant relationships were
found between the Mini-BESTest
total score and the BBS (rho⫽.83,
Pⱕ.001), FRT (rho⫽.55, Pⱕ.001),
OLS on the paretic side (rho⫽.83,
Pⱕ.001), OLS on the nonparetic side
(rho⫽.54, Pⱕ.001), and TUG
(rho⫽⫺.82, Pⱕ.001).
Convergent and discriminant
validity. In the stroke group, the
Mini-BESTest total score was significantly correlated with the ChedokeMcMaster Stroke Assessment leg
score (rho⫽.53, Pⱕ.001) and foot
score (rho⫽.64, Pⱕ.001), MAS
(rho⫽⫺.22, P⫽.02), and ABC Scale
(rho⫽.50, Pⱕ.001), but not with the
GDS (rho⫽⫺.17, P⫽.08) and AMT
(rho⫽.08, P⫽.42), thus demonstrating good convergent and discriminant validity.
Known-groups validity. Significant differences in the Mini-BESTest
total score and most individual item
scores were found between the
stroke and control groups and
between fallers and nonfallers in the
stroke group (Tab. 4).
ROC curve analysis. Receiver
operating characteristic curves were
constructed to assess the ability of
the various balance measures to distinguish people with stroke with and
without a history of falls (Tab. 5).
The cutoff score for the Mini-BESTest
August 2013
c
was 17.5, and the ROC curve yielded
an AUC of 0.64 (95% CI⫽0.51– 0.77),
a sensitivity of 64.0% (95% CI⫽44.5–
79.7), and a specificity of 64.2% (95%
CI⫽53.3–73.7). The associated LR⫹
and LR⫺ values were 1.8 (95%
CI⫽1.2–2.7) and 0.6 (95% CI⫽0.3–
1.0), respectively. The AUC value of
the Mini-BESTest then was compared with that of the BBS, TUG,
OLS, and FRT. We found that the
AUC of the Mini-BESTest was significantly smaller than that of the
BBS (␹2⫽7.36, P⫽.01). The AUC of
the Mini-BESTest was not significantly different from that of the
TUG (␹2⫽0.05, P⫽.82), OLS on the
paretic side (␹2⫽0.80, P⫽.37), OLS
on the nonparetic side (␹2⫽0.01,
P⫽.90), and FRT (␹2⫽0.48, P⫽.49).
Discussion
In this study, the psychometric properties of the Mini-BESTest for people
with chronic stroke were examined. The ceiling and floor effects
and ability of the Mini-BESTest to
identify fallers among individuals
with chronic stroke also were systematically compared with those of
4 other balance measures for the
first time. The study showed that the
Mini-BESTest is a reliable and valid
measure of balance performance
for community-dwelling individuals
with chronic stroke, with no signifi-
cant floor or ceiling effects. The association between the Mini-BESTest
and fall history, however, is limited.
Score Distribution and
Ceiling and Floor Effects
Our results showed that among the
various balance measures, the MiniBESTest has the least floor or ceiling
effects, as indicated by both the
degree of skewness and the proportion of participants with minimum
and maximum possible scores. In
contrast, a significant ceiling effect
was found for the BBS (32.5%). Mao
et al22 found a similar ceiling effect of
the BBS among patients with chronic
stroke (at 180 days after discharge)
(28.8%). A study comparing the MiniBESTest with the BBS in patients
with PD also showed that the score
distribution for the BESTest was significantly less skewed than that for
the BBS.31 Our data revealed that the
score distribution for the TUG demonstrated
substantial
skewness
(Tab. 2), with almost half of our participants with stroke being able to
complete the task within 15 seconds
(ie, ceiling effect) (Fig. 1D). The BBS
consists of a good number of relatively less demanding tasks such as
sitting unsupported, standing unsupported, and moving from sitting to
standing, whereas the TUG is a
single-item assessment involving
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Table 3.
Intrarater and Interrater Reliability of the Mini-BESTesta
Intrarater Reliability (nⴝ30)
b
0
1
2
0
1
2
Kappa
P
0
1
2
0
1
2
Kappa
P
1
4
25
1
4
25
1.00
ⱕ.001c
1
4
25
1
4
25
1.00
ⱕ.001c
2. Rise to toes
13
11
6
13
12
5
.58
ⱕ.001c
13
11
6
14
11
5
.68
ⱕ.001c
c
6
22
2
14
3
3
.49
ⱕ.001c
3a. Paretic side, stand on one leg
6
22
2
7
20
3
.64
ⱕ.001
3b. Nonparetic side, stand on one leg
4
20
6
6
15
9
.60
ⱕ.001c
4
20
6
3
19
8
.67
ⱕ.001c
9
0
21
9
0
21
.84
ⱕ.001c
4. Compensatory stepping correction in
forward direction
9
0
21
9
0
21
.84
ⱕ.001
backward direction
14
4
12
18
2
10
.37
.01c
14
4
12
14
6
10
.57
ⱕ.001c
6a. Displacement toward the paretic side
(stroke group) or left side (control
group): compensatory stepping
correction in lateral direction
20
2
8
22
3
5
.64
ⱕ.001c
20
2
8
22
4
4
.36
.01c
6b. Displacement toward the nonparetic
side (stroke group) or right side
(control group): compensatory
stepping correction in lateral
direction
16
0
14
18
0
12
.73
ⱕ.001c
16
0
14
12
4
14
.36
.02c
7. Stance, eyes open on firm and flat
surface
2
2
26
2
2
26
1.00
ⱕ.001c
2
2
26
2
2
26
1.00
ⱕ.001c
8. Stance, eyes closed on foam surface
5
22
3
6
20
4
.43
.01c
5
2
3
12
16
2
.38
.01c
9. Stance, eyes closed on firm and
inclined surface
3
1
26
3
1
26
1.00
ⱕ.001c
3
1
26
3
1
26
1.00
ⱕ.001c
4
2
24
4
2
24
.80
ⱕ.001c
4
2
24
5
5
20
.46
ⱕ.001c
c
5
16
9
5
6
19
.41
ⱕ.001c
10. Change in gait speed
c
11. Walk with horizontal head turns
5
16
9
5
17
8
.61
ⱕ.001
12. Walk with pivot turns
5
24
1
5
25
0
.89
ⱕ.001c
5
24
1
5
21
4
.76
ⱕ.001c
c
19
8
3
15
8
7
.43
ⱕ.001c
5
19
6
5
18
7
.70
ⱕ.001c
13. Step over obstacle
14. TUG and TUG with dual task
(cognitive)
MiniBESTest
total score
c
Countb
(Rater 3)
1. Sit to stand
Mini-BESTest item score
b
Countb
(Rater 2)
Count
(Time 2)
Count
(Time 1)
a
Interrater Reliability (nⴝ30)
b
19
8
3
19
10
1
.54
ⱕ.001
5
19
6
5
22
3
.76
ⱕ.001c
Time 1
Median (IQR)
Time 2
Median (IQR)
ICC
(3,1)
P
Rater 2
Median (IQR)
Rater 3
Median (IQR)
ICC
(2,1)
P
18.0 (12.0–21.0)
16.5 (13.8–21.0)
.97
ⱕ.001c
18.0 (12.0–21.0)
18.0 (11.0–22.0)
.96
ⱕ.001c
Mini-BESTest⫽Mini-Balance Evaluation Systems Test, TUG⫽Timed “Up & Go” Test, IQR⫽interquartile range, ICC⫽intraclass correlation coefficient.
Count: the number of participants who received a score of 0, 1, or 2 for each item is shown.
Statistically significant at Pⱕ.05 (kappa for item scores or ICC for total scores).
only moving from sitting to standing,
walking, and turning. The majority
of our participants, however, have
regained their ambulatory function,
thus leading to a ceiling effect. In
contrast, the inclusion of more challenging tasks such as postural
responses to external perturbations
(items 4 – 6) and walking balance
tasks (items 11–14) in the MiniBESTest may have improved the discrimination between participants.
1110
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Physical Therapy
Volume 93
The OLS (paretic side) showed considerable positive skewness, indicating a possible floor effect. It reveals
that maintaining balance while
standing on the paretic leg remains a
very difficult task for many individuals with stroke, despite all of our
participants
being
communitydwelling. Eighty-three (78%) of our
participants with stroke had an OLS
time of less than 5 seconds, and 14
(13%) of these individuals were even
Number 8
unable to perform the task (ie, score
of 0 second) (Fig. 1E).
Reliability
The Mini-BESTest had high internal
consistency (Cronbach alpha⫽.89 –
.94), indicating all of the items measure the same underlying attribute.
The intrarater and interrater reliability of the Mini-BESTest also were
excellent when administered to people with stroke, comparable to those
August 2013
Table 4.
Known-Groups Validity of the Mini-BESTesta
Stroke Group
(nⴝ106)
Countb
1
2
1. Sit to stand
1
8
97
75.5
0
0
48
2. Rise to toes
27
43
36
62.0
0
1
47
0
1
2
Mean
Rank
Nonfallers (nⴝ81)
Countb
P
0
1
2
Mean
Rank
0
1
2
Mean
Rank
82.0
.04c
1
4
20
47.3
0
4
77
55.4
.01c
P
111.7
ⱕ.001c
11
9
5
41.5
16
34
31
57.2
.01c
c
12
86
8
58.9
0
8
40
118.7
ⱕ.001
6
19
0
43.7
6
67
8
56.5
.01c
7
56
43
66.5
0
7
41
101.8
ⱕ.001c
4
15
6
42.3
3
41
37
56.9
.02c
forward direction
24
20
62
67.9
0
1
47
98.7
ⱕ.001c
10
1
14
48.6
14
19
48
55.0
.30
backward direction
34
29
43
63.6
0
1
47
108.3
ⱕ.001c
15
2
8
41.6
19
27
35
57.2
.01c
6a. Displacement toward the paretic side
(stroke group) or left side (control
group): compensatory stepping
correction in lateral direction
66
11
29
60.6
0
3
45
114.8
ⱕ.001c
17
3
5
49.8
49
8
24
54.6
.43
6b. Displacement toward the nonparetic
side (stroke group) or right side
(control group): compensatory
stepping correction in lateral
direction
41
3
62
68.8
0
4
44
96.8
ⱕ.001c
14
0
11
45.0
27
3
51
56.1
.07
7. Stance, eyes open on firm and flat
surface
3
3
100
76.1
0
0
48
80.5
.09
1
3
21
48.1
2
0
79
55.1
.01c
16
69
21
59.5
0
3
45
117.2
ⱕ.001c
7
13
5
48.1
9
56
16
55.1
.23
3
3
100
76.1
0
0
48
80.5
.09
2
1
22
50.0
1
2
78
54.5
.11
5
15
86
73.0
0
0
48
87.5
ⱕ.001c
2
5
18
48.5
3
10
68
55.0
.17
94.0
ⱕ.001
5
9
11
43.5
4
25
52
56.5
.03c
c
3b. Nonparetic side (stroke group) or
right side (control group), stand on
one leg
8. Stance, eyes closed on foam surface
9. Stance, eyes closed on firm and
inclined surface
10. Change in gait speed
11. Walk with horizontal head turns
9
34
63
70.0
0
5
43
c
12. Walk with pivot turns
16
66
24
61.1
0
5
43
113.8
ⱕ.001
6
17
2
43.2
10
49
22
56.6
.02c
13. Step over obstacle
57
28
21
59.2
0
4
44
118.0
ⱕ.001c
17
5
3
45.5
40
23
18
55.9
.12c
14. TUG and TUG with dual task
(cognitive)
21
68
17
75.4
0 45
3
82.2
.13
7
14
4
49.8
14
54
13
54.6
.42
Mini-BESTest
total score
c
Countb
0
3a. Paretic side (stroke group) or left side
(control group), stand on one leg
b
Fallers (nⴝ25)
Countb
Mean
Rank
Mini-BESTest item score
a
Control Group
(nⴝ48)
Stroke Group
Median (IQR)
19.0 (14.0–22.0)
Control Group
Median (IQR)
P
27.0 (26.0–27.0)
ⱕ.001
c
Fallers
Median (IQR)
Nonfallers
Median (IQR)
P
16.0 (10.5–21.0)
19.0 (15.5–22.0)
.03c
Mini-BESTest⫽Mini-Balance Evaluation Systems Test, TUG⫽Timed “Up & Go” Test, IQR⫽interquartile range.
Count: the number of participants who received a score of 0, 1, or 2 for each item is shown.
Statistically significant difference at Pⱕ.05 (Mann-Whitney U test).
of the BBS (intrarater⫽.92–.98, interrater⫽.93–.99),15,22,30,40 TUG (intrarater⫽.96),40 OLS (intrarater⫽.88 –
.92),18 and FRT (interrater⫽.99)40
previously reported in people with
stroke. Our results are thus in line
with those of Godi et al,30 who found
that the Mini-BESTest had excellent
intrarater reliability (ICC⫽.96) and
interrater reliability (ICC⫽.98) in a
August 2013
sample of people with different balance disorders. Leddy et al32 also
evaluated both the intrarater and
interrater reliability of the MiniBESTest, and their results obtained
from patients with PD are similar to
ours (intrarater⫽.88 –.91, interrater⫽.91–.96). The MDC95 obtained
in our study was 3.0 points, which
represents the minimum difference
that would reflect a real change in
the mini-BESTest total score. Godi et
al30 found a very similar MDC95 value
(3.5 points) in their sample of participants with mixed conditions. The
minimal detectable change established here would be useful for
future stroke clinical trials in determining whether the experimental
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1111
intervention has caused any real
change in balance ability.
as indicated by the significant difference in scores between the stroke
and control groups and between
people with stroke with and without
a history of falls. Our results concord
with the findings of King et al,31 who
showed that the Mini-BESTest can
effectively distinguish between individuals with and without postural
response deficits as defined by the
Hoehn and Yahr scale.
It is noted that item 5 (compensatory
stepping correction in a backward
direction), item 6 (compensatory
stepping correction in a lateral direction), and item 8 (standing on a foam
surface with eyes closed) showed
fair reliability only. The discrepancies in scoring between the 2 testing
sessions or between the 2 raters may
have been partly due to the actual
change in patients’ performance.
These 3 items represent the more
challenging tasks, with the majority
of participants attaining a score of
only 0 or 1 at initial assessment
(Tab. 4). A patient’s performance of
these tasks thus might be more variable with repeated testing. For the
compensatory stepping reaction
tests (items 5 and 6), the lower
agreement in scores also might be
related to the consistency of the
therapist in applying the displacement. A slight increase or decrease
in magnitude of the displacing force
applied by the therapist might elicit
a very different balance response
from the patient.
When comparing the ROC curves,
however, the results show that the
Mini-BESTest (AUC⫽0.64, 95% CI⫽
0.51– 0.77), similar to the TUG
(AUC⫽0.66, 95% CI⫽0.53– 0.80),
OLS on the paretic side (AUC⫽0.67,
95% CI⫽0.54 – 0.80), OLS on the
nonparetic side (AUC⫽0.64, 95%
CI⫽0.52– 0.77), and FRT (AUC⫽
0.67, 95% CI⫽0.55– 0.79), has a limited association with fall history
(AUC ⬍0.7). Only the BBS showed a
reasonable AUC value of 0.72 (95%
CI⫽0.61– 0.83), which was significantly greater than that of the MiniBESTest. Whether this statistically
significant difference in AUC was
clinically meaningful will need further study.
Validity
We found that the Mini-BESTest total
score was significantly associated
with other established balance measures (BBS, OLS, FRT, and TUG) and
other measures evaluating related
concepts (lower-limb motor recovery, ABC Scale), but not with measures assessing different attributes
(eg, GDS, AMT), thus demonstrating
good concurrent, convergent, and
discriminant validity, respectively.
Our results are in agreement with
King et al,31 who found a strong association of the Mini-BESTest with the
BBS (r⫽.79) and Unified Parkinson’s
Disease Rating Scale motor score
(r⫽⫺.51) among patients with PD.
The results showed that the MiniBESTest total score was able to separate people with different balance
abilities (ie, known-groups validity),
The limited association of the MiniBESTest with fall history in people
with stroke may be explained by several reasons. First, it is well known
that the causes of falls are multifactorial. Many factors other than
balance ability, both intrinsic and
extrinsic, may contribute to falls
after stroke.58 For example, Harris
et al27 found that ambulatory individuals with stroke who attained a
low BBS score and used a wheelchair or walker for longer distances
had lower risk for falls compared
with those who had a higher BBS
score and only used a cane for ambulation. Apparently, the relationship
between balance and falls is not linear and involves the interplay of
many other factors. This possible
explanation may partly explain why
balance assessment tools, when used
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alone, may not be effective in predicting falls in people with stroke.
Indeed, a number of previous studies
have shown that various balance
assessment tools commonly used in
stroke rehabilitation, such as the BBS
and TUG, have limited ability to predict falls after chronic stroke.25–27,59
Second, the fall data were collected
retrospectively, which is more susceptible to recall problems and bias
than when a prospective design is
used for fall data collection. For
example, a fall that occurred earlier
in the period (eg, 10 months previously) may not be reported compared with a fall that occurred more
recently (eg, 2 weeks previously).
One may not recall a fall that was
relatively inconsequential compared
with a fall that necessitated medical
attention. Further study should
assess the utility of the Mini-BESTest
for predicting future falls in patients
with stroke.
Our results are in contrast to the
findings of Duncan et al,34 who
examined the relationship between
the Mini-BESTest and recurrent falls
during the previous 6 months (retrospective) and future 12 months (prospective) in a sample of 80 patients
with PD. Their results showed a
strong association of the MiniBESTest with recurrent falls, both
retrospectively and prospectively.
The AUC values reported were 0.77
to 0.86, with a sensitivity of 0.62 to
0.88, a specificity of 0.74 to 0.78, an
LR⫹ of 2.4 to 4.0, and an LR⫺ of
0.15 to 0.52. The discordance in
results between their study and ours
may be explained by the different
study population and research methods. Patients with PD were used in
their study, whereas our sample consisted of only people with chronic
stroke. In their study, the MiniBESTest was used to predict recurrent fallers (those who experienced
2 or more falls), whereas the faller
group included both single and
recurrent fallers in our study. The fall
August 2013
August 2013
Mini-BESTest⫽Mini-Balance Evaluation Systems Test, IQR⫽interquartile range, 95% CI⫽95% confidence interval, LR⫹⫽positive likelihood ratio, LR⫺⫽negative likelihood ratio, AUC⫽area under the curve,
BBS⫽Berg Balance Scale, FRT⫽Functional Reach Test, OLS⫽one-leg standing, TUG⫽Timed “Up & Go” Test.
b
Significant difference between fallers and nonfallers at Pⱕ.001 (Mann-Whitney U test).
c
The analysis of TUG data was based on 102 participants (23 fallers, 79 nonfallers).
0.64 (0.52–0.77)
0.67 (0.54–0.80)
0.66 (0.53–0.80)
0.6 (0.3–1.0)
1.8 (1.2–2.9)
67.1% (56.2–76.4)
60.9% (40.8–77.8)
19.0
14.8 (11.6–21.1)
23.4 (13.3–50.6)
a
TUG, s
c
0.7 (0.5–1.0)
0.6 (0.4–0.9)
2.5 (1.5–4.3)
2.5 (1.2–5.0)
84.0% (74.4–90.4)
77.8% (67.6–85.5)
56.0% (37.0–73.3)
40.0% (23.4–59.3)
3.6
0.9
1.5 (1.0–5.0)
16.0 (5.1–40.0)b
0.9 (0.0–2.3)
7.5 (1.0–20.1)
FRT, cm
OLS: paretic side, s
22.8 (19.0–27.9)
BBS (0–56)
OLS: nonparetic side, s
0.67 (0.55–0.79)
0.72 (0.61–0.83)
50.0 (43.0–54.0)
b
0.6 (0.4–1.0)
0.6 (0.4–0.9)
2.6 (1.5–4.5)
2.0 (1.2–3.4)
74.0% (63.6–82.4)
80.2% (70.3–87.4)
24.1
52.0% (33.5–70.0)
50.5
26.6 (22.8–30.4)b
16.5 (7.5–21.0)
Balance Measure
54.0 (51.0–56.0)
b
52.0% (33.5–70.0)
0.6 (0.3–1.0)
1.8 (1.2–2.7)
64.2% (53.3–73.7)
17.5
19.0 (15.0–22.0)b
64.0% (44.5–79.7)
LRⴚ
(95% CI)
LRⴙ
(95% CI)
Specificity
(95% CI)
Cutoff
Score
Sensitivity
(95% CI)
Distinguishing Fallers From Nonfallers
Nonfallers
(nⴝ81)
Median (IQR)
Fallers
(nⴝ25)
Median (IQR)
Comparison of Mini-BESTest With Other Balance Measures: Differentiating Between Fallers and Nonfallers in the Stroke Groupa
Table 5.
Limitations and Future
Research Directions
This study has several limitations.
First, because the participants in the
stroke group were communitydwelling and most were ambulatory,
the results are generalizable only to
people with similar characteristics.
Further research is needed to validate the Mini-BESTest in people who
are in acute or subacute stages of
stroke recovery, severely impaired,
or institutionalized. Second, the ability to carry on a normal conversation
was used as an eligibility criterion,
but it may not be equivalent to being
able to follow directions. Perhaps a
cutoff score of a standardized assessment of cognition should have been
used to determine eligibility. Third,
the actual number of enrolled participants was higher than that derived
from the sample size calculation
described in the “Method” section.
We received an overwhelming
response, and a large number of people volunteered to participate in our
study. As there were no substantial
budgetary concerns, we decided to
measure all volunteers who were eli-
AUC
(95% CI)
rate reported also was higher in their
study. The proportion of fallers in
our study was 23.6%, and only 6.6%
were recurrent fallers, whereas
27.5% and 32.5% of their study participants reported recurrent falls in
the previous 6 months and the
12-month follow-up period, respectively. The lower fall rate may be due
to several factors. First, our sample
was
relatively
young
(mean
age⫽57.1 years). The time since the
onset of stroke was more than 6
months for all of our participants
(median⫽2.9 years). Thus, they
likely had developed compensatory
strategies in their adaptation to a
chronic and presumably more stable
condition. In contrast, the patients
with PD in the study by Duncan et
al34 were older (mean age⫽68.2
years) and were coping with a disease that was progressive in nature.
0.64 (0.51–0.77)
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Physical Therapy f
1113
gible. Although the power analysis
a priori helped us to determine the
minimum sample size required to
detect significant findings, a larger
sample size presumably would have
further increased the statistical
power of the study. Indeed, with the
current sample size of 106 people
with stroke, the power was
increased to 0.95, if the alpha level
(.05) and acceptable and expected
AUC (0.7 and 0.9, respectively)
remained the same as originally
planned.
We also acknowledge that other clinical balance scales are available for
patients with stroke, including the
Postural Assessment Scale for Stroke
Patients, Trunk Control Test, and
many others,14,28,60 – 62 but were not
used for comparison with MiniBESTest in this study. We selected
only the most commonly used balance assessment tools in stroke rehabilitation and research for comparison. In addition, feasibility of the
study and patient fatigue would be
concerns if more balance tests were
added to the assessment battery.
Another interesting research question has to do with the responsiveness of the Mini-BESTest. Godi et al30
found that the Mini-BESTest is more
responsive to change in balance ability than the BBS in a sample consisting of patients with different balance
disorders. Is the Mini-BESTest more
responsive than other balance measures in detecting treatment effects
among individuals with stroke at different stages of recovery? Further
study is needed to address this interesting and important question.
Overall, although the association of
fall history with the Mini-BESTest is
limited, the Mini-BESTest remains a
better option than other balance
measures used in this study to assess
balance function in communitydwelling people with chronic stroke
who have mild to moderate neurological impairments, as it has excel1114
f
Physical Therapy
Volume 93
lent reliability and validity, with no
significant floor and ceiling effects.
Additionally, compared with singleitem measures such as the TUG and
OLS, the Mini-BESTest is useful in
identifying specific postural control
problems and directing treatment.
Ms Tsang and Dr Pang provided concept/
idea/research design and project management. Ms Tsang, Mr Liao, and Dr Pang provided writing. Ms Tsang and Mr Liao
provided data collection. All authors provided data analysis. Dr Pang provided fund
procurement and facilities/equipment. Ms
Tsang provided institutional liaisons. Ms
Tsang, Dr Chung, and Dr Pang provided
before submission).
Ethics approval for the study was granted
by the Ethics Review Committee of the Hong
The preliminary data were presented in
abstract format at the 21st European
Stroke Conference; May 22–25, 2012; Lisbon, Portugal.
Mr Liao was supported by a full-time
research studentship granted by the Hong
DOI: 10.2522/ptj.20120454
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1115
Research Report
Psychometric Properties and
Practicability of the Self-Report
Urinary Incontinence Questionnaire in
Patients With Pelvic-Floor Dysfunction
Seeking Outpatient Rehabilitation
Ying-Chih Wang, Dennis L. Hart,† Daniel Deutscher, Sheng-Che Yen,
Jerome E. Mioduski
Y-C. Wang, OTR/L, PhD, Department of Occupational Science &
Technology, University of Wisconsin–Milwaukee, PO Box 413,
Enderis Hall 971, Milwaukee, WI
53201-0413 (USA), and Focus On
Therapeutic Outcomes, Inc, Knoxville, Tennessee. Address all correspondence to Dr Wang at:
[email protected].
D.L. Hart, PT, PhD, Focus On Therapeutic Outcomes, Inc, Knoxville,
Tennessee.
Background. Pelvic-floor dysfunction (PFD) affects a substantial proportion of
individuals, mostly women. In responding to the demands in measuring PFD outcomes in outpatient rehabilitation, the Urinary Incontinence Questionnaire (UIQ)
was developed by FOTO in collaboration with an experienced physical therapist who
has a specialty in treating patients with PFD.
Objective. The purpose of this study was to evaluate psychometric properties and
practicability of the 21-item UIQ in patients seeking outpatient physical therapy
services due to PFD.
Design. This was a retrospective analysis of cross-sectional data from 1,628
D. Deutscher, PT, PhD, Physical
Therapy Service, Maccabi Healthcare Services, Tel Aviv, Israel.
patients (mean age⫽53 years, SD⫽16, range⫽18 –91) being treated for their PFD in
91 outpatient physical therapy clinics in 24 states (United States).
S-C. Yen, PT, PhD, Department of
Physical Therapy, Northeastern
University, Boston, Massachusetts.
Methods. Using a 2-parameter logistic item response theory (IRT) procedure and
J.E. Mioduski, MS, Focus On Therapeutic Outcomes, Inc, Knoxville,
Tennessee.
†
Dr Hart died April 11, 2012.
[Wang Y-C, Hart DL, Deutscher D,
et al. Psychometric properties and
practicability of the self-report Urinary Incontinence Questionnaire
in patients with pelvic-floor dysfunction seeking outpatient rehabilitation. Phys Ther. 2013;93:
1116 –1129.]
Association
April 11, 2013
Submitted: March 27, 2012
the graded response model, the UIQ was assessed for unidimensionality and local
independence, differential item functioning (DIF), discriminating ability, item hierarchical structure, and test precision.
Results. Four items were dropped to improve unidimensionality and discriminating ability. Remaining UIQ items met IRT assumptions of unidimensionality and local
independence. One item was adjusted for DIF by age group. Item difficulties were
suitable for patients with PFD with no ceiling or floor effect. Item difficulty parameters ranged from ⫺2.20 to 0.39 logits. Endorsed items representing highest difficulty
levels were related to control urine flow, impact of leaking urine on life, and
confidence to control the urine leakage problem. Item discrimination parameters
ranged from 0.48 to 1.18. Items with higher discriminating abilities were those
related to impact on life of leaking urine, confidence to control the urine leakage
problem, and the number of protective garments for urine leakage.
Limitations. Because this study was a secondary analysis of prospectively collected data, missing data might have influenced our results.
Conclusions. Preliminary analyses supported sound psychometric properties of
the UIQ items and their initial use for patients with PFD in outpatient physical therapy
services.
this article at:
ptjournal.apta.org
1116
f
Physical Therapy
Volume 93
Number 8
August 2013
P
elvic-floor dysfunction (PFD)
affects a substantial proportion
of individuals, mostly women.1–3 It is estimated that up to one
third of adults experience one or
more PFD conditions during their
lifetime.2,3 To improve functional
outcomes and reduce PFD symptoms, many patients seek outpatient
pelvic-floor physical therapy.4 In a
previous longitudinal cohort of
2,452 patients with PFD receiving
outpatient physical therapy services,5 most patients (92%) were
female, and for most of them the PFD
had been present for more than 90
days (74%). A majority (55%) had urinary leakage, and combinations of
urinary, bowel, and pelvic-floor pain
disorders were common (37%).
To assist in clinical care planning and
outcomes assessment in patients
with PFD, there is an increasing
demand for patient-reported outcomes (PROs) to be applied in this
patient population during routine
clinical practice and research.6,7
There are several reasons that stimulate this demand. First, individuals
with PFD are commonly managed in
outpatient physical therapy services.8 –10 Second, to assess the PFD outcomes, many health indicators by
nature rely on subjective patient
reports. For example, PFD symptoms commonly include urinary
urgency, urinary frequency, bowel
constipation, pelvic pain, and sexual
dysfunction. Functional outcomes of
PFD frequently involve whether
patients have reduced urgency and
frequency, less restriction doing
daily activities, or more ability to participate in social events. These
assessments strongly rely on
patients’ perspectives, instead of laboratory tests or physical examination. Third, because PRO measures
provide information related to
patients’ perception of their health
status without interpretation from
clinicians or a third party, several
institutes such as the National InstiAugust 2013
tutes of Health,11 Food and Drug
Administration,12 and World Health
Organization6 are encouraging the
medical research community to use
PROs to support intervention effectiveness13–15 and monitor patient
management.16
and collect pilot data for the initial
item bank. The additional validated
surveys included the PFDI, PFIQ, Pelvic Floor Prolapse/Urinary Incontinence Sexual Function Questionnaire (PISQ), and Pain Disability
Index (PDI).
In 1998, the first International Consultation on Incontinence (ICI) was
held,6 and the ICI Scientific Committee recognized the need to develop a
universally applicable questionnaire
for wide application across international populations in clinical practice and research to assess urinary
incontinence. Since then, many
questionnaires measuring urinary
incontinence have been developed,
such as the ICIQ-UI Short Form,17
Incontinence Impact Questionnaire
(IIQ),18 Pelvic Floor Distress Inventory (PFDI),19,20 Pelvic Floor Impact
Questionnaire (PFIQ),19,20 and Urogenital Distress Inventory (UDI).21 In
responding to the demands in measuring PFD outcomes in outpatient
rehabilitation, the FOTO Pelvic Floor
Dysfunction
Assessment
was
designed by Focus On Therapeutic
Outcomes, Inc (FOTO) in collaboration with an experienced physical
therapist who has a specialty in treating patients with PFD. Questions
were designed that would be sensitive to change in the issues of greatest concern to patients with PFD
seeking outpatient rehabilitation
therapy and to develop an item
response theory (IRT)-based item
bank suitable for computerized adaptive testing (CAT) application for this
patient population. One part of the
development involved an assessment
of face validity by collecting feedback on the initial item bank (item
description and rating categories)
from a small group of physical therapist clinical experts. In 2008, FOTO
added various patient history–
related questions, along with 4 additional validated surveys for patients
with PFD to facilitate research at the
Rehabilitation Institute of Chicago
The psychometric properties of the
initial FOTO PFD item bank have not
been studied. The purpose of the
current study was to evaluate psychometric properties and practicability of the self-report Urinary
Incontinence Questionnaire (UIQ),
as part of the FOTO Pelvic Floor
Dysfunction Assessment, in patients
with PFD seeking outpatient physical therapy services.
Method
Data Collection
The platform used for outcomes data
collection has been described.5
Briefly, patients with PFD were managed in outpatient rehabilitation clinics participating with FOTO, an
international medical rehabilitation
outcomes database management
company.22,23 Prior to initial evaluation and therapy (intake), patients
entered demographic data and completed self-report surveys using
Patient Inquiry, a computer program
developed by FOTO (Knoxville, Tennessee).22,23 Demographic variables
of interest were age, sex, symptom
acuity, surgical history, number of
comorbid conditions, exercise history, and payer source. Data on age
were collected with age as a continuous variable and categorized as 18
to 44, 45 to 64, and 65 years and
older. The participants’ sex was categorized as female and male. Symptom acuity, which we operationally
defined as the number of calendar
days from the date of onset of the
condition being treated to the date
of initial therapy evaluation, was categorized as acute (⬍22 days), subacute (22–90 days), and chronic
(⬎90 days). Surgical history was categorized as none, 1, 2, 3, or 4 or
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more surgeries related to the condition being treated. Number of
comorbid conditions was assessed
using a list of 29 conditions common
to patients entering an outpatient
rehabilitation clinic (eg, arthritis,
asthma, diabetes, heart attack, AIDS,
sleep disturbance, cancer).24,25 Exercise history prior to receiving therapy was categorized as exercising 3
times a week or more, exercising 1
to 2 times a week, or exercising seldom or never. Last, more than 15
payer sources (eg, preferred provider organization, Medicare) were
listed for patient to select from.
When clinic staff recorded patient
data into the software and the staff
selected “Pelvic Floor” as the broad
heading for the reason for treatment,
PFD-related questions were administered to the patients. Because data
were collected in routine, busy outpatient clinics, we used a branching
system to administer questions to
collect data efficiently and reduce
administrative burden (ie, reduced
the number of items administered).
When PFD surveys were administered, patients were instructed to
select disorders that might apply to
them (ie, urinary, bowel, and pelvic
pain). For any selected disorder, subsequent subtypes pertinent to a specific disorder were given. For example, if patients selected “urinary,”
they were instructed to select a more
detailed subtype (ie, leakage, frequency, or retention). At any time,
patients could choose one, more
than one, or no subtype. Patients
could skip any question and proceed
to the next question without explanation. Based on the subtype
reported by the patient, only items
relevant to that subtype were given,
which led to 7 possible branching
routines that produced groups of
patients with different numbers of
items asked. Patients received the
full 21 UIQ items only if they
selected all 3 subtypes (leakage, frequency, and retention).
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UIQ
The UIQ was designed to evaluate
urinary function in patients with PFD
seeking outpatient physical therapy
services. The UIQ consists of 21
items: 17 related to urinary leakage
problems, 2 related to frequency
problems, and 2 related to retention
problems. Each item has its own Likert rating scale structure and operational definition (Appendix).
Data were selected from the database if patients: (1) were 18 years of
age or older, (2) were managed for
their PFD problems, (3) received
outpatient physical therapy services,
and (4) responded to FOTO Patient
Inquiry computer-based UIQ items at
admission to therapy between May
2007 and January 2011.
Analytical Procedure
We assessed the UIQ for its unidimensionality and local independence, differential item functioning
(DIF), discriminating ability, item
hierarchical structure, and test precision using the two-parameter logistic Item Response Theory (IRT)
approach.
Data management. Prior to data
analysis, item responses from all
items, except item 17, were
recoded, with higher (more positive)
responses representing higher functioning. As an example, the original
rating categories of item 1 were
reversed (ie, the rating categories of
1 to 6 were replaced with those of 6
to 1) so patients with higher scores
were those patients who never have
urine leakage when they are awake.
Based on our preliminary analysis
using a 1-parameter IRT model, the
category thresholds increased in
order (ie, there were no disorder
thresholds). For item 17, we collapsed 2 of the lowest (1 and 2) and
highest (10 and 11) responses
because of low frequency counts
(11% and 5% for items 1 and 2 and
7% and 2% for items 10 and 11,
Number 8
respectively) for those category
choices and challenges in analyzing
responses with 2-digit width.
Unidimensionality and local independence. To assess IRT assumptions of unidimentionality and local
independence,
we
conducted
exploratory factor analyses (EFAs) of
latent trait variables, followed by
confirmatory factor analyses (CFAs)
utilizing Mplus (Muthén & Muthén,
Los Angeles, California)26 on all
items.
Unidimensionality of a scale means
its items represent only one construct.27 To test for unidimensionality, we analyzed (1) the factor loadings and (2) variances explained by
each factor. As suggested by Nunnally,28 we eliminated items with factor loadings below 0.40.
Local independence means that,
after taking into account patient ability, patient responses to the items
are statistically independent.27 To
test for local independence, we analyzed (1) the residual correlation
matrix, (2) the magnitude of the standardized coefficients, and (3) the
percentage of absolute residual correlations ⬎0.10. Model fit was evaluated using comparative fit index
(CFI), the Tucker-Lewis index (TLI),
and the root-mean-square error of
approximation (RMSEA). The TLI
and CFI range from 0 (poor fit) to 1
(good fit). Values of CFI and TLI
greater than 0.90 are indicative of
good model fit; RMSEA values less
than 0.08 suggest adequate fit.29 To
our knowledge, there is no empirically substantiated standard for the
cutoff of residual correlation. We
eliminated one item in each pair of
items with a residual correlation of
0.20 or more.30 Items that had a
higher number of residual correlation (⬎0.10) with other items were
inspected and removed if necessary
to improve the model fit.
August 2013
Because the minimum covariance
coverage was not fulfilled for all
items using the original data set due
to missing values, for the purposes of
assessing unidimensionality and
local independence of the 21 UIQ
items, we generated a set of data
where imputed values supplanted
missing responses, as described by
Hart et al.31 To generate the imputed
values, the original data set, which
contained actual responses and missing values, was used to generate a
simulated set of values using Masters’
partial credit model (PCM)32 and
WINSTEPS software (Winsteps, Chicago, Illinois).33 Once a complete set
of imputed responses was generated, each missing response in half of
the original data set (ie, 50% of the
patient records) was randomly
selected and replaced with the
imputed value for that patient. The
simulated data set was used only to
assess unidimentionality and local
independence utilizing Mplus.26 The
original data set was used for the
remaining analyses.
DIF. All patients at a given level of
ability should have an equal probability of scoring positively on
each item regardless of their group
membership (eg, sex).34 Items are
flagged “significant DIF” when this
requirement does not hold. Measuring DIF was 1 of 10 recommendations for advancing patientcentered outcomes measurement35
because if items in a health assessment instrument are biased, detection rates can be overestimated or
underestimated.35
For the purposes of DIF detection,
we followed a method developed by
Crane et al36 and described in detail
by Hart et al37 and Nilsagård and
Forsberg.38 Specifically, we calibrated item responses to Samejima’s
2-parameter graded response model
(GRM)39 using Parscale (Scientific
Software International Inc, Lincolnwood, Illinois)40 and difwithpar softAugust 2013
ware (University of Washington,
Seattle, Washington).41 The difwithpar software examines 3 ordinal
logistic regression (OLR) models
for each item and each demographic category selected for analysis: sex (female and male), age
group (18 – 44, 45– 64, and ⱖ65
years), symptom acuity (acute, subacute, and chronic), and number
of PFD comorbid conditions (1⫽
patient reported only one urinary
problem, 2⫽urinary and one other
symptom, 3⫽urinary, bowel, and
pelvic pain symptoms). As described
by Crane et al,36 items were examined for the presence of (1) uniform
DIF by examining the relative difference between beta coefficients in
the regression models (ie, a 10% difference) and (2) nonuniform DIF by
comparing the ⫺2 log likelihoods of
2 of the regression models. Uniform
DIF exists when the probability of
answering the item correctly or
endorsing the same rating category is
greater for one group than the other
uniformly over all levels of ability.
Nonuniform DIF exists when there is
interaction between ability level and
group membership (sex, age group,
symptom acuity), with certain combinations having a higher probability
of answering the item correctly or
endorsing the same rating category.
Discriminating ability. We continued to use Samejima’s 2parameter GRM39 to estimate item
parameters. The GRM was selected
because it is a model for polytomous
ordinal data,39 and it allows items
to have different slopes (ie, discrimination parameters). The slopes
allowed us to assess how well each
item is able to discriminate between
patients with different abilities (ie,
high and low urinary function), as
well as to estimate item information
functions for each item. The slopes
were expressed in logits, with higher
positive values indicating a better
discriminating ability. Items with a
low slope of ⬍0.40 were excluded
from the item pool because of low
discriminating ability.
Item hierarchical structure. Item
difficulty hierarchical order was
inspected via estimated item difficulty parameters. Item difficulty
parameters were expressed in logits
with higher positive values indicating a more challenging task that usually is accomplished or endorsed by
patients with higher functioning.
Test precision. We assessed the
test precision using the test information function (TIF) and standard
error (SE). The TIF27,42 indicates the
level of information or score precision provided by the scale over the
range of the construct’s continuum
and is the sum of the item information functions (IIFs) at each patient
ability level along the construct’s
continuum being measured (ie, urinary function). The amount of information provided by a scale at each
ability level is inversely related to the
error with which functional status is
estimated at that level of ability.42
We plotted the TIF generated using
data from the UIQ items. The shape
of the TIF provides a visual comparison of the level of test precision for
UIQ items. To quantify measure precision at each ability level, we plotted averaged SEs of functional status
estimates from the UIQ item and
superposed with the TIF.
Results
Data from 1,628 patients with PFD
symptoms receiving outpatient rehabilitation in 91 clinics in 24 states
were analyzed (Tab. 1). Patients
were primarily female (93% female),
with 75% of patients being under
65 years of age (mean age⫽53 years,
SD⫽16, range⫽18 –91) and having
chronic PFD. Of 1,628 patients
who reported urinary problem, 58%
had solely urinary problems, 15%
had both urinary problems and pelvic pain, 14% had both urinary
and bowel problems, and 13% had
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Table 1.
Patient Characteristics at Rehabilitation Intake (N⫽1,628)
Characteristica
Percentage
Age (y), X⫾SD, range
53⫾16, 18–91
18 to ⬍45 (%)
31
45 to 65 (%)
44
⬎65 (%)
25
Missing (%)
0
Sex (% female)
93
Missing
0
Acuity of symptoms (%)
Acute (0–21 days)
3
Subacute (22–90 days)
8
Chronic (⬎90 days)
75
Missing
14
Surgical history (%)
None
64
1
14
2
3
3
2
ⱖ4
2
Missing
15
No. of functional comorbiditiesb (%)
None
30
1
14
2 or 3
18
ⱖ4
24
Missing
14
Exercise history (%)
At least 3⫻/wk
37
1–2⫻/wk
18
Seldom or never
31
Missing
14
Payer source (%)
PPO
44
Medicare part B
16
HMO
5
Medicaid
2
Indemnity insurance
2
Medicare part A
2
Other
25
Missing
a
b
4
HMO⫽health maintenance organization, PPO⫽preferred provider organization.
Functional comorbidities are medical conditions shown to affect physical functioning.
urinary and bowel problems as well
as pelvic pain. Most patients had urinary problems affecting leakage
(82%), with fewer reporting problems with urinary frequency (60%)
or retention (27%).
Unidimensionality and Local
Independence
The EFA indicated that the 21 UIQ
items tended to represent one dominant factor, with the first 3 factors explaining 42%, 6%, and 5% of
the total variance. Preliminary analysis showed no item pair had a
residual correlation of 0.20 or
more. The results suggested possible local dependence between 21
item pairs (10%) with absolute correlation residuals higher than desired
(⬎0.10). After inspecting the patterns, we decided to remove items 2
(How much urine usually leaks for
no obvious reason when you are
awake?) and 11 (How much urine
usually leaks when you are physically active or coughing or sneezing?) because of redundancy, but
kept other items based on clinical
reasons to cover different types of
urinary incontinence. In addition,
item 18 (What is the frequency of
your daytime urination?) had a low
loading (0.4) on the first factor. We
felt item 18 was more descriptive
than functional and thus removed it.
The remaining 18-item set was reanalyzed. All remaining items met the
evaluation criteria. The first 3 eigenvalues were 7.81, 1.20, and 1.02,
with the first 3 factors explaining
43%, 7%, and 6% of data variance. Fit
statistics for 1-, 2-, and 3-factor models were CFI values of 0.88, 0.94,
and 0.96, respectively, TLI values of
0.97, 0.98, and 0.99, respectively,
and RMSEA values of 0.07, 0.05,
and 0.04, respectively, supporting
unidimensionality.
DIF
After removing items 2, 11, and 18,
the results of DIF analysis using the
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18 UIQ items with real data values
were suggestive of no DIF by sex,
age group, acuity, and number of
PFD comorbid conditions, except
the presence of nonuniform DIF by
sex for item 12 (What type of protection do you use for your urine
leakage?) (P⬍.0001) and uniform
and nonuniform DIF by age group
for item 15 (To what extent do you
feel your sex life has been affected
by urine leakage?) (P⬍.0001 and
change in estimate ⬎0.1). Detailed
inspection of item 12 showed female
patients tended to use underpants
liners or mini-pads, whereas male
patients did not. Temporarily removing the response category 2 from
item 12 by treating it as a missing
value eliminated the DIF effect. Item
15 was split into 3 new items by age
group: age group 1 (18 – 44 years),
age group 2 (45– 64 years), and age
group 3 (ⱖ65 years) to account for
the DIF effect. However, due to low
frequency counts on response categories of age group 3 after splitting,
the convergence was not achieved.
Because we were unable to obtain
stable parameter estimations on item
15 for age group 3, this item was
removed from the parameter estimation analysis (described below).
Discriminating Ability
Item 19 (How often do you urinate at
night?) had a slope of 0.28 (⬍0.40)
and was excluded from the item
pool because of its low discriminating ability. Table 2 lists the item characteristics of the remaining UIQ
items sorted by the item difficulty
parameter. Item discrimination
parameters ranged from 0.48 to 1.18.
When comparing the item discrimination parameters, item 14 had the
highest item discrimination value,
followed by items 16, 13, 7, 1, and
17, implying these items were able
to discriminate between patients of
different ability within a narrow
effective range around their item difficulty parameter estimates.
August 2013
Item Hierarchical Structure
Item hierarchical structure of the
final UIQ items is presented in Table
2. The numbers of patients who
responded to specific items are listed
in the “Frequency Count” column.
Items are ranked based on the item
difficulty parameter, with more difficult items on the top. Item difficulty
parameters ranged from ⫺2.20 to
0.39 (logits). Items representing
more difficult tasks to be endorsed
by patients with a high level of functioning were related to control of
urine flow (item 21), impact of leaking urine on life (item 14), and confidence in ability to control the urine
leakage problem (items 16 and 17).
Items representing easier tasks
endorsed by patients with a low
level of functioning were related to
the amount of urine leakage under
different situations (items 6, 4, and
8).
The patient ability distribution was
bell-shaped, with no ceiling or floor
effects. The mean of the patient ability estimations was 0.00 (SD⫽0.83).
Patient ability parameters ranged
from ⫺3.61 to 2.87 (logits). Compared with the patient ability distribution, the UIQ items were slightly
easier relative to this sample’s overall
ability level. Figure 1 illustrates the
item-person map of the UIQ items.
Test Precision
Figure 2 illustrates a bell-shaped TIF
curve with one peak located at the
middle ability level. The SE values
were small in the middle range of
patient
ability
measures
but
increased as ability measures (logits)
became extreme. The average SE
value for all patients was 1.84, but
the average SE value for 90% of the
patients with ability measures
between ⫺1.4 and 1.4 was 0.71.
For individual item information (IIF)
curves, item 14 had the highest
peak, followed by items 13, 17, 7,
16, and 1. These items could be
potential items for single-item
screening purposes. However, the
TIF curve shifted slightly toward the
left (lower ability measures), which
implied more difficult items were
needed to increase test information
and thus reduce the measurement
error at the high-functioning level.
Discussion
The purpose of this study was to
evaluate psychometric properties
and practicability of the UIQ in
patients seeking outpatient physical
therapy services due to PFD. Overall,
the results showed that the final UIQ
scale produced reliable and precise
measures of urinary function for
patients at different levels of urinary
function. The results indicated that
the final revised UIQ items met IRT
assumptions of unidimensionality
and local independence and were
free from DIF for the variables
assessed. Measures of urinary function were free from floor and ceiling
effects and covered the functional
continuum well with good measurement precision. Item difficulties
were suitable for patients with PFD
with different levels of urinary function. More challenging and discriminating items are recommended to
expand the existing item bank. The
data fit the GRM measurement model
well. Findings from this study will be
used to develop an initial pelvicfloor, body part–specific CAT application to be used in the outpatient
physical therapy services.
To our knowledge, this is the first
study designed to develop an IRTbased item bank suitable for CAT
application for patients with PFD
seeking outpatient rehabilitation
therapy. Our results suggest the UIQ
scale represents an adequate first
step in the development of multiple
CATs for this population, particularly
because we analyzed data from a relatively large sample (N⫽1,628). Two
previous studies used IRT methods
to examine the psychometric prop-
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Table 2.
Item Characteristics of the Urinary Incontinence Questionnaire (UIQ) Itemsa
Category Parameter
Diff SE
Slope
Slope SE
1
2
3
21. Control urine flow
after starting to urinate
Item Description
440
0.39
0.09
0.61
0.04
1.57
⫺0.38
⫺1.18
17. Control urine leak
(0–10 points)
996
0.19
0.04
0.92
0.03
1.71
1.17
0.74
0.34
14. Leaking urine
interferes with your
life
996
0.15
0.03
1.18
0.04
1.49
0.44
⫺0.31
⫺1.61
1,004
0.09
0.07
0.48
0.02
2.22
0.84
0.38
⫺0.89
⫺2.55
996
0.07
0.04
1.00
0.03
1.61
0.09
⫺1.70
1,326
⫺0.09
0.03
0.95
0.03
2.53
0.19
⫺0.24
⫺0.86
⫺1.62
439
⫺0.24
0.08
0.65
0.03
2.05
1.11
⫺0.08
⫺0.85
⫺2.23
9. Urine leak when you
are physically active
16. Level of confidence
(4 levels)
1. Urine leak while
awake
20. Delay urination after
feeling the urge
Freq Count
Diff
4
5
6
7
8
⫺0.36
⫺0.69
⫺1.12
⫺1.79
993
⫺0.55
0.05
0.79
0.03
1.18
0.36
⫺1.54
7. Urine leak before you
can get to the toilet
1,006
⫺0.57
0.04
0.96
0.03
2.13
0.44
0.03
⫺0.79
⫺1.80
5. Leak urine after
finished urinating
1,028
⫺0.78
0.06
0.62
0.02
2.07
0.29
⫺0.12
⫺0.72
⫺1.52
10. Level of activity that
causes urine leakage
865
⫺0.86
0.06
0.76
0.04
0.81
⫺0.09
⫺0.72
15. Sex life affected (age
group 1)
294
⫺0.87
0.11
0.67
0.06
0.83
0.02
⫺0.85
13. No. of protective
garments
724
⫺1.38
0.05
0.97
0.04
1.19
0.51
⫺0.32
15. Sex life affected (age
group 2)
451
⫺1.40
0.11
0.60
0.05
0.93
⫺0.09
⫺0.84
1,024
⫺1.71
0.06
0.82
0.04
1.39
0.38
⫺0.12
8. How much urine
leaks before getting
to the toilet
791
⫺1.93
0.07
0.58
0.03
1.65
0.61
⫺2.26
4. How much urine
leaks while sleeping
349
⫺1.99
0.12
0.53
0.04
1.51
⫺1.51
6. How much urine
leaks after urinating
651
⫺2.20
0.10
0.52
0.03
1.52
⫺1.52
12. Type of protection
3. Urine leak when
asleep
⫺1.37
⫺0.51
⫺1.14
a
Items were ranked based on the item difficulty parameter, with more difficult items on the top. The first column lists the item number as listed in the
Appendix. Freq Count⫽number of patients who have responded to a specific item, Diff⫽item difficulty parameter, SE⫽standard error, slope⫽item
discrimination parameter. Items 2, 11, 18, and 19 were removed from the analysis, and item 15 was split into 3 items by age group: age group 1 (age 18 –
44 years), age group 2 (age 45– 64 years), and age group 3 (age ⱖ65 years). For item 15, age group 3 was dropped due to low frequency count and
unstable parameter estimations.
erties of urinary incontinence questionnaires: Handa and Massof18
(N⫽27 women with stress urinary
incontinence) and Bower et al43
(N⫽156 children with bladder dysfunction). Compared with these 2
studies,18,43 our larger and more
diverse sample should produce more
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stable and precise estimates of item
parameters for patients with PFD in
general. Comparing our results with
the findings of these 2 studies was
difficult because the questionnaires
used were related to the quality of
life in children (eg, body image, family and home, self-esteem)43 or the
Number 8
impact of urinary incontinence on
social life (eg, hobbies, ability to do
household chores, going on vacation),18 whereas the UIQ emphasizes
urinary urgency and frequency, as
well as severity of the urinary
symptoms.
August 2013
Figure 1.
Item-person map of the Urinary Incontinence Questionnaire (UIQ) The item-person map was derived by analyzing the UIQ items
using Samejima’s 2-parameter graded response model and Parscale. The map illustrates the relationship of the person score
distribution (right) with the hierarchical order of UIQ items (left). Both person ability and item difficulty are expressed on a common
metric, which is expressed along the central axis in logits, with higher positive values indicating a more difficult item or a person with
a higher level of functioning.
We were unable to run Mplus26 to
assess unidimentionality and local
independence using our original
data set because the minimum covariance coverage was not fulfilled for
all items (insufficient frequency
counts for all items). As a result, we
generated a data set in which each
missing response in half (50%) of
the original data set was randomly
selected and replaced with an
imputed value. Such replacement
may lead to better results than using
the original data set with real values.
We explored such an effect by generating 2 additional data sets where
25% and 100% of the original data
set were randomly selected and
replaced with imputed values and by
conducting the same analytical procedures. Comparing the CFI, TLI,
and RMSEA values of these 3 data
August 2013
Figure 2.
Test information function (TIF) and standard error (SE), illustrating a bell-shaped TIF
curve with one peak located at the middle ability level. The SE values were small in the
middle range of patient ability measures but increased as ability measures (logits)
became extreme. Overall, the TIF curve shifted slightly toward the left (lower ability
measures), which implied more difficult items were needed to increase test information
and thus reduce the measurement error at the high-functioning level.
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sets (with 25%, 50%, and 100%
records supplemented with imputed
values), all 3 analyses demonstrated
that one factor was sufficient for adequate model fit. For 25%, 50%, and
100% imputed data sets, respectively, there were local dependence
relationships among 35 (15%), 21
(10%), and 3 (1%) item pairs (out of
210 item pairs), with absolute correlation residuals higher than desired
(⬎0.10). Because the data set with
25% imputed data revealed too many
large correlation residuals to examine the pattern, and the data set with
100% imputed data showed unrealistically good results, the data set with
50% imputed values was used.
To make the decision of removing
items using the IRT methods, different criteria existed. To test unidimensionality and local independence, we chose a selection cutoff of
a correlation residual of 0.20,30
although a cutoff of 0.25 has been
used.44 We used a more restrictive
criterion because we expected better results using the imputed data set
than using the original data set with
just real values. To assess the discriminating ability, we decided to
remove items with a low slope of
⬍0.40, although a much higher criterion of 0.70 has been used.44 On
average, the majority of UIQ items
had relatively low discrimination
parameters. Lower estimations of
discrimination parameters may suggest: (1) modifications of wording of
the question or rating scale structure
or (2) challenges in quantifying the
urinary function accurately because
the leakage, frequency, and retention problems may partially depend
on the details of daily events (eg,
beverages a person consumes in a
day, a sudden cough, heavy lifting).
Keeping items with low slope values
in the item pool should not affect
the measurement, although these
items would have a smaller chance
of being selected in the CAT
application.44
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In the process of developing the
questionnaire, we administered the
same questionnaire to both male
and female participants. In the
future, as we continue to collect
more data, we intend to develop sexspecific surveys because urinary and
bowel structures and sex functions
are very different between sexes. To
examine the sex factor, we used a
method developed by Crane et al36
for DIF detection by sex. Results supported clinically relevant findings in
sex differences in using type of protection (item 12) and age differences
in sex life (item 15). In a follow-up
analysis, we inspected data from
item 12 that appeared to be geared
toward female participants. We did
observe that female patients tended
to select “underpants liners or minipads” (14% of female patients who
responded to item 12) and that relatively few male patients (3% of male
patients who responded to item 12)
selected that response based on the
frequency count. However, both
female and male patients responded
to item 12 under the predicted
hypothesis that patients who have
more severe urinary incontinence
symptoms would rely on more protection. Although removing the
response category 2 from item 12 by
treating it as a missing value resulted
in no DIF by sex, the current male
sample size was small (only 48 male
patients responded to item 12).
Therefore, we should be cautious in
generalizing our results to the male
population, and we will continue
monitoring item 12 in the future.
To account for the DIF effect, we
split item 15 into 3 new items by age
group. There seems to be a general
tendency that the impact of urine
leakage on sex life decreases by age,
where the younger group feels sex
life has been affected by urine leakage the most. However, there was no
perceptible impact on urinary function estimates when adjusting for
DIF; the correlation between the
Number 8
unadjusted and fully adjusted ability
estimates was 0.999, similar to the
finding by Crane et al,45 suggesting
no practical DIF.
We used the GRM measurement
model to perform the initial examination of the psychometric properties of the UIQ items because it is a
model for polytomous ordinal data39
and it is a 2-parameter model containing both item difficulty and discrimination parameters. In a
follow-up analysis, we analyzed the
same data set using Masters’ oneparameter partial credit model
(PCM)32 and WINSTEPS software.33
We found that most results were similar. The item hierarchical structure
remained, except item 12 became an
easier item compared with the estimate using the GRM. Similarly, the
distribution of ability estimations
was normally distributed, with no
obvious ceiling or floor effect. Findings suggested that the UIQ data fit
the PCM well, with no items showing misfit (all infit or outfit values
were ⬍1.4 and ⬎0.6). The results of
the TIF analysis also showed a bellshaped TIF with one peak located at
the middle ability level and indicated
that the UIQ was reliable and precise
for measuring most patients at different levels of urinary function. Lastly,
with the person-separation index (G)
equal to 0.95, these UIQ items separated person ability into 1.6 (ie,
[4 ⫻ 0.95 ⫹ 1]/3) statistically distinct strata, indicating the need to
add more challenging or easier items
to distinguish patients into different
levels of urinary function. As a result,
the PCM measurement model
seemed to be a better choice,
although the item discrimination
parameters were varied among UIQ
items (0.48 –1.18).
There were several limitations of this
study. First, because this study was a
secondary analysis of prospectively
collected data via a proprietary database management company (FOTO),
August 2013
we were not in control of the data
collection procedure, and there was
no specific timetable for patients to
be assessed, as no training was given
to therapists prior to the data collection. Additionally, generalizability of
results may be limited because differences between participating clinics
and clinics that do not collect data
using FOTO may exist.
Because data were collected in routine, busy outpatient rehabilitation
clinics, PFD items were selected
from the computer-based administrative branching algorithm to reduce
the respondent burden. By utilizing
this type of data collection
approach, the presence of missing
data due to unanswered items makes
statistical analyses challenging. In
this data set, there were 1,628
patients who took the UIQ at rehabilitation admission. The number of
patients who responded to a specific
item ranged from 294 to 1,028, providing a sufficient sample size even
for items with low response rates.
Additionally, based on the fact that
the UIQ was administered in 91 outpatient physical therapy clinics in 24
states, we believe the impact of
potential patient selection bias was
reduced simply by sampling from a
wide variety of clinics in many
locations.
in analyzing responses with 2-digit
width (ie, item 17 with response
categories of 1–11), we collapsed
2 of the lowest and highest
responses. Although the real impact
is unknown, we did monitor the
potential influence on the item calibration of item 17 by comparing the
results derived from the 2-parameter
GRM using Parscale and the results
derived from the PCM using WINSTEPS. The results were similar, with
item 21 the most challenging item
and item 17 remaining one of the 3
most difficult items.
Last, we did not use medical terminology to classify patients. For
instance, urinary incontinence is
divided into stress urinary incontinence, urge urinary incontinence,
and overflow urinary incontinence.
Because data were collected from
patient self-report surveys, we used
general descriptions with the intention of avoiding self-judgments from
patients. Future studies should
endeavor to reduce the potential for
misclassifying patients by collecting
more complete medical information.
Classifying patients correctly should
assist researchers developing PFD
CATs that can discriminate patients
by stress, urge, overflow, or mixed
urinary incontinence, if appropriate.
Conclusion
To run certain analyses, we used
imputed data to replace missing values. We acknowledge that data sets
with imputed values produce artificially more ideal results. Although
we did not test the impact of using
imputed responses versus complete
original responses on the factor analytic results, preliminary results studied by Hart et al31 showed that the
patient ability estimates were similar and highly correlated across data
sets using original responses with
missing values, original responses
with imputed values for missing
responses, and entirely imputed values. Similarly, due to the challenges
August 2013
The preliminary analyses supported
sound psychometric properties of
the UIQ items and their use in
patients with PFD seeking treatment
in outpatient physical therapy services. Findings from this study will
be used to develop an initial pelvicfloor, body part–specific CAT application to be used in outpatient physical therapy services.
Dr Wang and Dr Hart provided concept/
idea/research design. Dr Wang, Dr Hart, and
Dr Yen provided writing. Mr Mioduski provided data collection, project management,
and study participants. Dr Wang provided
data analysis. Dr Hart, Dr Deutscher, and Dr
Yen provided consultation (including review
of manuscript before submission).
The institutional review boards of Focus On
Therapeutic Outcomes, Inc and the University of Wisconsin–Milwaukee approved the
study procedures.
This research, in part, was presented at the
Combined Sections Meeting of the American Physical Therapy Association; February
8 –12, 2012; Chicago, Illinois.
DOI: 10.2522/ptj.20120134
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14 Resnik L, Liu D, Hart DL, Mor V. Benchmarking physical therapy clinic performance: statistical methods to enhance
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data. Phys Ther. 2008;88:1078 –1087.
15 Resnik L, Hart DL. Using clinical outcomes
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Ther. 2003;83:990 –1002.
16 Guide to Physical Therapist Practice. Phys
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17 Avery K, Donovan J, Peters TJ, et al. ICIQ:
a brief and robust measure for evaluating
the symptoms and impact of urinary
incontinence. Neurourol Urodyn. 2004;2:
322–330.
18 Handa VL, Massof RW. Measuring the
severity of stress urinary incontinence
using the Incontinence Impact Questionnaire. Neurourol Urodyn. 2004;23:27–32.
19 Barber MD, Spino C, Janz NK, et al. The
minimum important differences for the
urinary scales of the Pelvic Floor Distress
Inventory and Pelvic Floor Impact Questionnaire. Am J Obstet Gynecol. 2009;200:
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20 Barber MD, Walters MD, Cundiff GW.
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484.
August 2013
Appendix.
Urinary Incontinence Questionnaire (UIQ)a
Urinary Leakage Items
1 How often does urine leak for no obvious reason when you are awake?
1
Never
2
Once or less per week
3
More than once a week
4
Once a day
5
Several times a day
6
Continuously
2 How
1
2
3
4
much urine usually leaks for no obvious reason when you are awake?
A few drops
Enough to make underpants/pads wet
Enough to wet outer clothes
Urine runs down legs onto floor
3 How
1
2
3
4
5
6
often does urine leak when you are asleep?
Never
Once a day
Several times a day
Continuously
4 How
1
2
3
much urine usually leaks while you are sleeping?
A few drops
Enough to make pajamas/pads wet
Enough to wet all clothes and bedding
5 How
1
2
3
4
5
6
often do you leak urine after you thought you had finished urinating?
Never
Once a day
Several times a day
Every time
6 How
1
2
3
4
much urine usually leaks after you thought you had finished urinating?
A few drops
7 How
1
2
3
4
5
6
often does urine leak before you can get to the toilet?
Never
Once a day
Several times a day
Every time
(Continued)
August 2013
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Appendix.
Continued
8 How
1
2
3
4
much urine usually leaks before you can get to the toilet?
A few drops
9 How
1
2
3
4
5
6
often does urine leak when you are physically active, including coughing or sneezing?
Never
Once a day
Several times a day
Every time
10 Describe the level of activity that causes urine leakage.
1
Vigorous activity, such as running, exercise, coughing, or sneezing
2
Moderate activity, such as household chores or lifting
3
Light activity, such as walking, bending, or rising
4
Leak even without activity
11 How
1
2
3
4
much urine usually leaks when you are physically active or coughing or sneezing?
A few drops
12 What type of protection do you use for your urine leakage?
1
None
2
Underpants liners or mini-pads
3
Maxi-pads
4
Incontinence pads
5
Incontinence briefs
6
Diapers
13 Select the number of protective garments for urine leakage you use per day.
1
1
2
2
3
3
4
4
5
ⱖ5
14 Overall, how much does leaking urine interfere with your life?
1
Does not interfere with my life
2
Minor inconvenience
3
Slight problem
4
Moderate problem
5
Major problem
15 To what extent do you feel your sex life has been affected by urine leakage?
1
Has not affected my sex life
2
A little
3
Somewhat
4
A great deal
(Continued)
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August 2013
Appendix.
Continued
16 Describe your level of confidence in your ability to control your urine leakage problem.
1
Complete confidence
2
Moderate confidence
3
Little confidence
4
No confidence
17 How
1
2
3
4
5
6
7
8
9
10
11
well do you control your urine leakage? (0 being “no control” to 10 being “full control”)
0 (no control)
1
2
3
4
5
6
7
8
9
10 (full control)
Urination Frequency Items
18 What is the frequency of your daytime urination?
1
1– 4 times per day
2
5– 8 times per day
3
9 –12 times per day
4
ⱖ13 times per day
19 How
1
2
3
4
5
often do you urinate at night?
Do not urinate at night
1 time per night
2 times per night
3 times per night
4 or more times per night
Urinary Retention Items
20 How long can you delay urination from the first time you feel the urge?
1
1 or more hours
2
30 minutes
3
15 minutes
4
less than 10 minutes
5
1–2 minutes
6
Cannot delay urination
21 After
1
2
3
4
a
starting to urinate, can you:
Stop urine flow completely
Maintain a change to the urine stream
Partially deflect or change the urine stream
Unable to deflect, change, or slow urine stream
The Urinary Incontinence Questionnaire may not be used or reproduced without written permission from the authors.
August 2013
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1129
Case Report
Cognitive-Behavioral–Based Physical
Therapy to Improve Surgical Spine
Outcomes: A Case Series
Kristin R. Archer, Nicole Motzny, Christine M. Abraham, Donna Yaffe,
Caryn L. Seebach, Clinton J. Devin, Dan M. Spengler, Matthew J. McGirt,
Oran S. Aaronson, Joseph S. Cheng, Stephen T. Wegener
K.R. Archer, PT, DPT, PhD, Department of Orthopaedic Surgery &
Rehabilitation, School of Medicine, Vanderbilt University, Medical Center East–South Tower,
Suite 4200, Nashville, TN 37232
(USA). Address all correspondence
to Dr Archer at: kristin.archer@
vanderbilt.edu.
N. Motzny, PT, DPT, Department
of Orthopaedic Surgery & Rehabilitation, School of Medicine,
Vanderbilt University.
C.M. Abraham, MA, Department
D. Yaffe, PhD, Chase Brexton
Health Services Inc, Baltimore,
Maryland.
C.L. Seebach, PsyD, Department
of Neurology, Washington DC
Veterans Affairs Medical Center,
Washington, DC.
C.J. Devin, MD, Department of
Orthopaedic Surgery & Rehabilitation, School of Medicine, Vanderbilt University.
D.M. Spengler, MD, Department
M.J. McGirt, MD, Department of
Neurological Surgery, School of
Medicine, Vanderbilt University.
Background and Purpose. Fear of movement is a risk factor for poor postoperative outcomes in patients following spine surgery. The purposes of this case
series were: (1) to describe the effects of a cognitive-behavioral– based physical
therapy (CBPT) intervention in patients with high fear of movement following lumbar
spine surgery and (2) to assess the feasibility of physical therapists delivering
cognitive-behavioral techniques over the telephone.
Case Description. Eight patients who underwent surgery for a lumbar degenerative condition completed the 6-session CBPT intervention. The intervention
included empirically supported behavioral self-management, problem solving, and
cognitive restructuring and relaxation strategies and was conducted in person and
then weekly over the phone. Patient-reported outcomes of pain and disability were
assessed at baseline (6 weeks after surgery), postintervention (3 months after surgery), and at follow-up (6 months after surgery). Performance-based outcomes were
tested at baseline and postintervention. The outcome measures were the Brief Pain
Inventory, Oswestry Disability Index, 5-Chair Stand Test, and 10-Meter Walk Test.
Outcomes. Seven of the patients demonstrated a clinically significant reduction
in pain, and all 8 of the patients had a clinically significant reduction in disability at
6-month follow-up. Improvement on the performance-based tests also was noted
postintervention, with 5 patients demonstrating clinically meaningful change on the
10-Meter Walk Test.
Discussion. The findings suggest that physical therapists can feasibly implement
cognitive-behavioral skills over the telephone and may positively affect outcomes
after spine surgery. However, a randomized clinical trial is needed to confirm the
results of this case series and the efficacy of the CBPT intervention. Clinical implications include broadening the availability of well-accepted cognitive-behavioral
strategies by expanding implementation to physical therapists and through a telephone delivery model.
Author information continues on
next page.
this article at:
ptjournal.apta.org
1130
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Number 8
August 2013
Cognitive-Behavioral–Based Physical Therapy to Improve Surgical Spine Outcomes
O.S. Aaronson, MD, Department of Neurological Surgery, School of Medicine, Vanderbilt University.
J.S. Cheng, MD, Department of Neurological
Surgery, School of Medicine, Vanderbilt
University.
S.T. Wegener, PhD, Department of Physical
Medicine and Rehabilitation, Johns Hopkins
Medicine, Baltimore, Maryland.
[Archer KR, Motzny N, Abraham CM, et al.
Cognitive-behavioral– based physical therapy to improve surgical spine outcomes: a
case series. Phys Ther. 2013;93:1130–1139.]
Published Ahead of Print: April 18, 2013
Submitted: October 15, 2012
T
he United States has the highest rate of lumbar spine surgery in the world, with rates
increasing more than 200% in the
last decade.1 Medicare spends more
than $1 billion annually on lumbar
spine surgery, and fusion procedures
account for almost half of total
spending.1 Despite surgical advances,
individuals after surgery for degenerative lumbar spine disease continue
to have poorer physical and psychosocial functioning compared with
the general US population, and up
to 40% have residual chronic pain
and functional disability.2 Our work
and that of other researchers3,4 has
shown fear of movement to be a
significant predictor of increased
pain and disability after lumbar spine
surgery.
Cognitive-behavioral therapy (CBT)
has strong empirical support, with
randomized controlled trials documenting a positive influence on fear
of movement in chronic pain populations.5 Subsequently, initial studies
have begun to explore incorporating
cognitive and behavioral strategies
into physical therapy for patients
with back and neck pain. Sullivan
et al6 targeted fear of movement
and pain catastrophizing with a
10-week activity-based psychosocial
physical therapy intervention and
found a higher return-to-work rate
at 12-month follow-up. George et al7
found a decrease in self-reported disability at 6-month follow-up with a
6-session behavioral physical therapy
intervention in participants with elevated fear-avoidance beliefs.
Available With
This Article at
ptjournal.apta.org
• Video of Selected Components
From the Cognitive-Behavioral–
Based Physical Therapy Program
August 2013
To date, only 2 studies, to our knowledge, have investigated a cognitivebehavioral approach to physical
therapy in patients following spine
surgery. Randomized controlled trials by Christensen et al8 and Abbott
et al9 showed significantly reduced
leg pain and improved function with
an 8-week group behavioral physical
therapy intervention and decreased
disability with a 3-session psychomotor therapy program, respectively,
at 2 years following lumbar fusion.
Overall, preliminary evidence suggests that physical therapist– delivered cognitive and behavioral interventions targeting psychosocial risk
factors have the potential to yield
significant reductions in pain and
disability.
The primary purpose of this case
series was to describe the effects of
a cognitive-behavioral– based physical therapy (CBPT) intervention in
patients with high fear of movement
following lumbar spine surgery for
degenerative conditions. The CBPT
intervention was designed to address
fear of movement through behavior
self-management and cognitive
restructuring techniques in order
to increase physical activity. Innovative aspects of the CBPT intervention include a risk-factor–targeted
approach for improving outcomes
and a telephone-based delivery
model. Due to the novelty of physical therapists delivering a broad
range of cognitive and behavioral
strategies over the telephone, the
feasibility of the CBPT intervention
was assessed to inform a randomized
controlled trial.
Patient History and
Review of Symptoms
The case series included adult
patients undergoing surgery for a
lumbar
degenerative
condition
between February and April 2011 at
an academic medical center. Degenerative conditions included spinal
stenosis, spondylosis, and spondylolisthesis. Patients had to be at least
21 years of age; English speaking;
undergoing laminectomy with arthrodesis; participating in postoperative physical therapy; have back or
lower extremity pain for greater than
6 months; have no medical history of
schizophrenia or other psychotic disorder; have high fear of movement;
and have a stable address and access
Volume 93
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Physical Therapy f
1131
to a telephone, indicating the ability
to participate in the study. Patients
having microsurgical techniques (eg,
microdiskectomy) as the primary
procedure, surgery for spinal deformity as the primary indication, or
surgery for pseudarthrosis, trauma,
infection, or tumor were excluded.
In addition, patients could not have
surgery covered by a workers’ compensation claim.
Fifteen patients provided informed
consent prior to surgery. The
patients were screened for high fear
of movement using a validated questionnaire (Tampa Scale for Kinesiophobia). Eight patients had scores
greater than 394 and remained eligible for the study intervention. An
intake assessment was completed
that gathered data on demographic
and health characteristics.
Examination
A baseline assessment occurred at a
standard 6-week postoperative clinic
visit before initiation of the CBPT
intervention. The patients were
asked questions with regard to age,
sex, education, marital status, insurance, smoking status, comorbidities,
height and weight, and previous spinal surgery. A battery of self-report
instruments measured fear of movement, pain catastrophizing, depressive symptoms, pain self-efficacy,
pain intensity and interference, and
disability. Patients also completed
3 performance-based tests. After the
CBPT intervention (3 months after
surgery), the patients completed the
same battery of self-report instruments and performance-based tests.
Performance tests were conducted
in the clinic, but patients were given
the questionnaires to complete at
home and send in by mail. A selfreport follow-up assessment administered by mail also was conducted
at 6 months following surgery.
Patients who did not return their
follow-up questionnaires within 1
week of receipt through clinic con1132
f
Physical Therapy
Volume 93
tact or mail were contacted by telephone to complete the assessment.
specific (0.90) for the diagnosis of
major depression.13
Outcome Measures
Pain Self-efficacy
The 10-item Pain Self-Efficacy Questionnaire (PSEQ)14 measures the
strength and generality of a person’s
belief in his or her ability to accomplish a range of activities despite
pain. Respondents rate how confident they are on a 7-point scale from
“not at all confident” to “completely
confident.” Scores range from 0 to
60, with a score greater than 40
indicating high pain self-efficacy.
The PSEQ has been found to have
excellent internal consistency, good
test-retest reliability, and construct
validity through correlations with
depression, anxiety, coping strategies, and pain ratings in patients with
chronic pain.14
Fear of Movement
The 17-item Tampa Scale for Kinesiophobia (TSK) was used to measure
fear of movement.10 A total score can
range from 17 to 68. Respondents
are asked to rate each item, 4 being
negatively worded and reversescored, on a 4-point Likert scale with
scoring alternatives ranging from
“strongly disagree” to “strongly
agree.” A decrease of 4 or more
points on the TSK is considered a
clinically relevant reduction.11 The
TSK has good internal consistency
and test-retest reliability in patients
with chronic pain.10
Pain Catastrophizing
The 13-item Pain Catastrophizing
Scale (PCS)12 assessed catastrophic
thinking associated with pain.
Respondents rate items on a 5-point
scale with the end points “not at all”
and “all the time.” A total score
ranges from 0 to 52, and a score
greater than 24 differentiates
between “catastrophizers” and “noncatastrophizers.”12 Pain Catastrophizing Scale scores have been found
to be associated with pain, selfreported disability, negative affect,
and pain-related fear.12
Depressive Symptoms
The 9-Item Patient Health Questionnaire (PHQ-9)13 assessed depressive
symptoms. Each item has 4 possible
answers to quantify how often a
patient has had a particular depressive symptom: “not at all,” “several
days,” “more than half the days,” and
“nearly every day.” A total score
ranges from 0 to 27. A score of 10
or greater is the most commonly
recommended cutoff point for a
“clinically significant” depressive
symptom. Compared with independent diagnoses made by mental
health professionals, the PHQ-9 has
been found both sensitive (0.75) and
Number 8
Pain Intensity and Interference
The Brief Pain Inventory (BPI)15
measured pain intensity and interference with daily activity. The pain
intensity subscale assesses current,
worst, least, and average pain, and
the interference subscale assesses
general activity, mood, walking ability, normal work, relations with
other people, sleep, and enjoyment
of life. Both subscales use a rating
scale with 0 representing “no pain
or does not interfere” and 10 representing “pain as bad as you can imagine or completely interferes.” Scores
of 5 or greater indicate moderate to
severe pain intensity and interference. The BPI has proved both reliable and valid in both surgical
patients and patients with chronic
low back pain.15 Published values of
minimum clinically important difference (MCID) for pain range from 1.2
to 2.1 after lumbar spine surgery.16
Disability
The 10-item Oswestry Disability
Index (ODI)17 assessed the impact of
lumbar spinal disorders on daily living. Ratings for each item are from
0 (high functioning) to 5 (low funcAugust 2013
tioning). Total scores are divided
by the total possible score and multiplied by 100 to create a percentage
of disability. Scores on the ODI
above 40% classify individuals as having severe disability. The ODI has
demonstrated good test-retest reliability, internal consistency, and
validity, with moderately high correlations with the Medical Outcomes
Study 36-Item Short-Form Health Survey questionnaire (SF-36) and various condition-specific disability measures.17 The MCID for the ODI has
been found to range from 11 to 12.8
in patients undergoing lumbar spine
surgery.16,18
Performance-Based Function
The 5-Chair Stand Test19 was used
to assess lower extremity strength.
Patients were instructed to fold their
arms across their chest and stand up
from and sit down on a standard
chair. If able to perform one time
successfully, patients were asked to
stand up and sit down 5 times as fast
as possible starting in the sitting position and stopping after the fifth rise.
Performance on the 5-Chair Stand
Test was measured in seconds. The
5-Chair Stand Test has demonstrated
good test-retest reliability and validity, with significant correlations with
other measures of physical performance and self-reported disability.19
The 10-Meter Walk Test was used to
assess gait speed.20 Patients were
given a 2-m warm-up distance preceding the 10-m distance and 2 m
beyond the 10 m to continue walking. The time that it took to traverse
the 10 m at a comfortable pace and
a fast pace were recorded. Two trials
were conducted at each pace, with a
brief rest as needed by the patient
between trials. Measurements for
both trials were averaged for each
respective walking speed. Excellent
interrater and intrarater reliability
and good test-retest reliability for
self-paced timed walking speed tests
using a stopwatch have been
August 2013
reported.21 Validity for walking
speed tests has been determined by
significant correlations with measures of function and mortality in
older adults.20,21 The MCID for the
10-Meter Walk Test at a comfortable
pace has been estimated to be 0.16
m/s, and a meaningful change in
older adults has been documented at
0.10 m/s.22
Feasibility
One physical therapist with 4 years
of experience treating patients with
chronic and postsurgical low back
pain and no prior experience delivering cognitive-behavioral strategies
participated in a training program.
Formal training included 2 sessions
with a clinical psychologist. Feasibility of the training was determined
through a written test after the first
2-day session and a skills test after
the second 1-day session (ie, scores
needed to be ⬎85).
Feasibility of the intervention was
monitored through a therapist
checklist that was completed at the
end of each session to determine
whether specific CBPT strategies
were delivered and patient exit interviews that gathered data on satisfaction with the program and specific components. All sessions were
audiotaped and reviewed by a clinical psychologist and research personnel to evaluate adherence to the
CBPT manual and specific CBT competencies. These competencies23
were: (1) setting clear, measurable,
and achievable goals; (2) problem
solving obstacles to goal achievement; (3) leaving responsibility for
recovery with the patient; and (4)
affirming positive behaviors and goal
achievement.
Intervention
The CBPT intervention is a structured, manual-based program that
was designed to complement and
be integrated into postoperative
physical therapy to improve surgical
spine outcomes through decreases
in fear of movement and increases in
physical activity. Patients received
weekly sessions with a study physical therapist for 6 weeks. The first
session was conducted in person
during a clinic visit at 6 weeks following surgery, and the remaining
sessions were delivered over the
telephone. All sessions were 30 minutes in length, except the first session, which was about 1 hour. In
addition to the CBPT intervention,
all patients were referred for outpatient physical therapy close to their
home for 12 sessions. Outpatient
physical therapy included a range of
therapeutic modalities and exercises
as determined by the treating surgeon and therapist. Patient adherence to the physical therapy script
of 12 sessions was documented by
the study physical therapist during
weekly CBPT intervention contact.
The CBPT program focuses on
empirically supported behavioral
self-management, problem solving,
cognitive restructuring, and relaxation training (Appendix).24 –26 The
main components of the program
include a graded activity plan (ie, a
comprehensive list of activities
ordered from least to most difficult
based on fear or pain) and weekly
activity and walking goals (see video,
available at ptjournal.apta.org).
Goals are rated by patients on a scale
from 0 to 10 (completely confident),
and scores of 8 or greater indicate a
realistic goal. A cognitive or behavioral strategy is introduced in each
session, with the therapist helping
patients identify enjoyable activities
(ie, distraction), replace negative
thinking with positive thoughts, find
the right balance between rest and
activity, and manage setbacks by recognizing high-risk situations and negative thoughts.
Outcomes
All 8 patients completed
6-session intervention and
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the
the
1133
Table 1.
Baseline Demographic and Clinical Characteristics of Patients Following Lumbar Spine Surgerya
a
Patient
Age
(y)
1
48
Sex
Education
Married
Insurance
Male
High school
Yes
Public
Comorbid
Conditions
Body Mass Index
(kg/m2)
Revision
Surgery
Former
⬎1
21.3
Yes
Smoker
2
68
Male
High school
Yes
Public
Never
⬎1
26.2
No
3
50
Female
High school
Yes
Private
Never
⬎1
53.1
No
4
56
Male
College
Yes
Private
Never
None
29.5
No
5
44
Female
High school
Yes
Private
Never
None
30.9
Yes
6
23
Female
High school
Yes
Private
Former
7
51
Female
High school
No
Public
Never
8
62
Female
High school
Yes
Private
Current
1
24.2
No
⬎1
27.4
No
1
29.4
No
All patients were white.
3-month (postintervention) and
6-month follow-up assessments. The
demographic and clinical characteristics of the patients are presented in
Table 1.
With regard to feasibility, the therapist passed the written and skills
tests with scores greater than 90.
Therapist checklists demonstrated
that at least 90% of the CBPT components were delivered during each
session. Exit interviews showed
100% of the patients were very satisfied with the program and that they
found the most benefit from the
graded activity plan, goal setting,
positive statements, and pain management plan. Review of audiotapes
also demonstrated that the therapist
covered greater than 90% of the
CBPT techniques and greater than
85% of CBT competencies in each
session, which indicated adequate
knowledge of the CBPT intervention.
All patients decreased their scores
on the TSK, PCS, and PHQ-9 at 3
months (postintervention) and 6
months after lumbar spine surgery
(Tab. 2). Patients 1, 3, 4, 5, 6, and 7
at 3-month follow-up and all patients
at 6-month follow-up demonstrated
a clinically relevant reduction in fear
of movement (Fig. 1A). Patients 1, 5,
6, and 7 were identified as “catastrophizers” at baseline (ie, PCS score
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Physical Therapy
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⬎24) and had the largest decreases
in PCS scores at 6-month follow-up
(Fig. 1B). Clinically relevant depressive symptoms (ie, PHQ-9 score
ⱖ10) were noted at baseline for
patients 1, 3, 5, 6, and 7, and all of
these patients reported none or minimal symptoms by 6-month follow-up
(Fig. 1C). Patient 2 demonstrated
minimal symptoms at 3 months and
6 months, and patient 8 reported
minimal symptoms only at 6-month
follow-up. Patient 4 reported no
depressive symptoms at both 3 and
6 months following surgery. Large
increases in pain self-efficacy were
noted (Fig. 1D), with all patients
reporting high pain self-efficacy at
6-month follow-up (ie, PSEQ score
⬎40).14
Patients 1, 3, 4, and 6 demonstrated
moderate pain intensity at baseline,
with BPI scores greater than 5, and
patients 2, 5, 7, and 8 reported mild
pain intensity at baseline (Tab. 2).
All 8 patients decreased their BPI
pain intensity scores from baseline
to 3-month assessment and from
3-month assessment to 6-month
follow-up. Patients 1, 3, 4, 6, and 7
exceeded the MCID for pain at the
3-month assessment (Fig. 2A).
Patients 3, 7, and 8 reported no pain
at 6 months following lumbar spine
surgery. For pain interference,
patients 1, 5, 6, and 7 reported
Number 8
severe interference, with BPI scores
of 7 or greater, patients 3 and 4
reported moderate interference, and
patients 2 and 8 reported mild interference at baseline (Tab. 2). Six of
the 8 patients exceeded MCID for
pain at the 3-month assessment, with
3 of these patients reporting no pain
interference at 6 months following
surgery (Fig. 2B). All 8 patients had
severe disability at baseline (Tab. 2),
and 7 of the 8 patients decreased
their ODI scores to moderate disability (ie, ODI score⫽21– 40) by 3
months (postintervention). Patient
8 reported minimal disability at
6-month follow-up, and the remaining 7 patients demonstrated moderate disability, with ODI scores
between 22 and 32 (Fig. 2C). All
patients exceeded the MCID for the
ODI at 6 months.
The 8 patients decreased their time
on the 5-Chair Stand Test and
increased their distance on the
10-Meter Walk Test at 3 months following surgery (Tab. 2). Patient 4
had the lowest time on the 5-Chair
Stand Test and maintained the lowest time at the 3-month assessment
(Fig. 3A). Patients 1 and 5 had the
lowest comfortable pace baseline
scores and maintained the lowest
scores at follow-up (Fig. 3B), and
patients 2 and 8 exceeded the MCID
for the 10-Meter Walk Test at a comAugust 2013
Table 2.
Individual Outcomes for Patients at 6 Weeks (Baseline), 3 Months (Postintervention), and 6 Months After Lumbar Spine Surgerya
Patient 1
Patient 2
Baseline
3
Months
6
Months
TSK
46
37
35
PCS
25
9
6
PHQ-9
21
7
4
9
PSEQ
15
28
52
25
7
3.5
1.8
3.5
BPI: interference
8.9
4.3
2.1
ODI
78
32
30
Measure
Patient 3
3
Months
6
Months
40
37
18
15
Patient 4
Baseline
3
Months
6
Months
35
40
36
9
13
9
4
3
11
6
0
9
0
0
42
54
45
56
60
29
48
55
3
2.5
5.3
1
0
5.3
1.8
1
4.9
4
2.4
6.3
1
0
6.9
2.9
2.1
52
32
30
52
30
22
66
32
28
Baseline
Baseline
3
Months
6
Months
31
41
37
32
0
21
8
6
Patient-reported outcomes
BPI: intensity
Performance-based outcomes
5-Chair Stand
Test (s)
27.6
23.2
23.6
17.0
19.4
15.8
15.3
11.2
Comfortable
pace (m/s)
0.71
0.79
0.67
1.0
0.88
0.96
1.0
1.05
Fast pace (m/s)
0.80
0.89
0.71
1.15
1.22
1.35
1.23
1.56
Patient 5
Patient 6
Baseline
3
Months
6
Months
TSK
54
48
PCS
37
13
PHQ-9
22
PSEQ
20
Measure
Patient 7
Baseline
3
Months
6
Months
37
50
37
9
36
9
11
4
18
32
56
7
4
1.8
6.5
Patient 8
Baseline
3
Months
6
Months
Baseline
3
Months
6
Months
35
43
30
28
40
37
28
6
33
9
6
11
9
3
7
4
25
9
0
8
6
4
28
52
37
53
60
40
51
60
3.5
1.8
4.3
1.8
0
3.5
1
0
Patient-reported outcomes
BPI: intensity
4.5
BPI: interference
7
6
2.1
9.1
4.3
2.1
8
0.71
0
4
1.5
0
ODI
60
52
32
60
32
30
48
40
22
48
30
16
Performance-based outcomes
5-Chair Stand
Test (s)
19.4
14.2
28.4
19.6
18.8
13.7
17.0
12.9
Comfortable
pace (m/s)
0.70
0.82
0.88
0.94
1.25
1.29
1.13
1.34
Fast pace (m/s)
0.86
1.28
1.15
1.25
1.44
1.54
1.18
1.67
a
Values expressed as total score. Comfortable pace and fast pace measured during 10-Meter Walk Test. TSK⫽Tampa Scale for Kinesiophobia (scores range
from 17 to 68, with scores ⬎39 indicating high fear of movement), PCS⫽Pain Catastrophizing Scale (scores range from 0 to 52, with scores ⬎24 indicating
high pain catastrophizing), PHQ-9⫽9-item Patient Health Questionnaire (scores range from 0 to 27, with scores ⱖ10 indicating clinically significant
depressive symptoms), PSEQ⫽Pain Self-Efficacy Questionnaire (scores range from 0 to 60, with scores ⬍40 indicating low self-efficacy), BPI⫽Brief Pain
Inventory (scores range from 0 to 10, with scores ⬎5 indicating moderate to severe pain or interference with activity), ODI⫽Oswestry Disability Index
(scores range from 0 to 100, with scores ⬎40 indicating severe disability).
fortable pace. For the fast pace, large
increases in distance were noted for
patients 2, 5, and 8 (Fig. 3C), and
5 patients exceeded a meaningful
change at 3 months.
August 2013
Discussion
Prior studies have demonstrated the
importance of psychosocial risk factors to persistent pain and disability
in patients with low back pain who
undergo spinal surgery.3,4 Subse-
quently, rehabilitation research has
begun to investigate the use and
effectiveness of CBT strategies
delivered by physical therapists.6 –9
The purpose of this case series was
to assess the feasibility and describe
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1135
Figure 1.
Changes over time in outcomes for fear of movement, pain catastrophizing, depression, and pain self-efficacy: (A) Tampa Scale for
Kinesiophobia (TSK), (B) Pain Catastrophizing Scale (PCS), (C) 9-item Patient Health Questionnaire (PHQ-9), and (D) Pain Self-Efficacy
Questionnaire (PSEQ). P1-P8⫽patients 1– 8.
Figure 2.
Changes over time in outcomes for pain and disability: (A) Brief Pain Inventory: pain intensity (BPI: Intensity), (B) Brief Pain Inventory:
pain interference (BPI: Interference), (C) Oswestry Disability Index (ODI). P1–P8⫽patients 1– 8.
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August 2013
Figure 3.
Changes over time in outcomes for performance-based function: (A) 5-Chair Stand Test, (B) 10-Meter Walk Test at comfortable pace,
(C) 10-Meter Walk Test at fast pace. P1–P8⫽patients 1– 8.
the effects of a telephone-delivered
CBPT intervention on fear of
movement, pain, disability, and
performance-based function, as well
as pain catastrophizing, depressive
symptoms, and pain self-efficacy, in
patients following lumbar spine surgery. The feasibility results demonstrated that physical therapists can
learn and successfully implement
cognitive-behavioral techniques over
the telephone following structured
training by a clinical psychologist.
Furthermore, all 8 patients in this
case series demonstrated a decrease
in fear of movement, pain catastrophizing, depressive symptoms, pain,
and disability and an increase in
pain self-efficacy following the CBPT
intervention and at 6-month followup. Decreases in time and increases
in distance during the performancebased tests also were noted from
baseline to 3 months following surgery (treatment completion).
August 2013
The results of this case series appear
consistent with the findings of Sullivan et al6 and George and colleagues7 in suggesting that identifying patients at-risk for poor outcomes
and applying a targeted rehabilitation approach may lead to meaningful reductions in psychosocial risk
factors as well as pain and disability
outcomes. The findings also support
work by Abbott et al,9 who demonstrated that a combined cognitivebehavioral and motor learning rehabilitation intervention significantly
improved functional disability in
patients undergoing lumbar spinal
fusion surgery.
Reductions of pain and disability
appear clinically relevant, with 7 of
the 8 patients exceeding published
values of MCID for pain intensity
(1.2–2.1) and all patients exceeding
MCID for the ODI (11–12.8) at
6-month follow-up.16,18 Decreases
in both pain and disability may have
been due to the CBPT intervention’s
focus on decreasing barriers to functional activity and walking rather
than focusing solely on pain symptoms. All CBPT sessions included
patient-tailored activity and walking
goals and problem solving, which
also may have had a direct result on
improvement for the walking tests,
with 5 patients demonstrating clinically meaningful change (in meters
per second).22 It is important to note
that improvements occurred in all
patients for both patient-reported
and objective outcomes, especially
as low correlations have been
reported between these 2 types of
measures.27
Specific changes in fear of movement and pain catastrophizing for all
patients appear similar to or larger
than TSK and PCS change scores
obtained following behavioral physical therapy interventions in patients
with back pain24 and following lum-
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Physical Therapy f
1137
bar disk surgery.28 Changes for all
patients were consistent with the
physical therapist– delivered Progressive Goal Attainment Program,
an activity-based psychosocial intervention, in patients following whiplash injury.6 In addition, change in
fear of movement scores appear clinically relevant based on prior work
demonstrating that fear of movement is stable following lumbar
spine surgery in the absence of a
psychological intervention.4
Patients had larger-than-expected
gains in pain self-efficacy following
the CBPT intervention. All 8 patients
had PSEQ scores greater than 50 at
the 6-month follow-up and scores
greater than 40 have been found to
be associated with maintenance of
functional gains.15 Turner et al29
demonstrated the importance of
self-efficacy to decreased disability
and improved functioning in chronic
pain populations, and their findings
suggest that increasing a patient’s
self-efficacy may provide additional
benefit beyond decreasing fear of
movement and pain catastrophizing.
Several limitations should be considered when interpreting our findings.
First, we used a case series design,
and statistical testing was not performed; thus, our findings may be
attributed to chance. Second, we
are unable to determine whether
improvement in outcomes was a
direct result of the CBPT intervention or due to other factors such as
the participation in physical therapy,
benefits of surgery, or impact of
greater attention from study personnel. Our next step is to assess the
efficacy of the CBPT intervention in
a randomized clinical trial to compare a CBPT group with an attentioncontrol group. Third, patient assessment occurred at completion of
the CBPT intervention and again 3
months later, and longer follow-up
is needed to assess maintenance of
treatment gains. Finally, all patients
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Physical Therapy
Volume 93
were white, which limits the generalizability of our findings.
Overall, our case series findings suggest that physical therapists can feasibly implement cognitive-behavioral
skills over the telephone and may
positively affect psychosocial factors, pain, and disability after spine
surgery. However, a randomized
clinical trial is needed to confirm the
results of this case series and the
efficacy of the CBPT intervention.
Clinical implications of this study
and future work in this area include
the opportunity to broaden the availability of well-accepted and effective
CBT strategies by expanding implementation from traditional providers
(psychologists) to physical therapists30 and through a telephone
delivery model. Screening for psychosocial risk factors and incorporating cognitive-behavioral techniques
into postoperative rehabilitation may
have the potential to improve outcomes in patients undergoing lumbar spine surgery.
Dr Archer, Dr Devin, Dr McGirt, Dr Aaronson, Dr Cheng, and Dr Wegener provided
concept/idea/project design. Dr Archer, Dr
Devin, Dr McGirt, and Dr Wegener provided
writing. Dr Archer, Ms Abraham, and Dr
Aaronson provided data collection and fund
procurement. Dr Archer provided data analysis. Dr Archer and Ms Abraham provided
project management. Dr Motzny, Dr Devin,
Dr Aaronson, and Dr Cheng provided
patients. Dr Motzny, Dr Yaffe, Dr Seebach,
Dr Devin, Dr Spengler, Dr McGirt, Dr Aaronson, Dr Cheng, and Dr Wegener provided
before submission).
This publication was made possible by a
grant from the American Physical Therapy
Association, Orthopedic Section, and Vanderbilt Clinical and Translational Science
Award grant UL1 RR024975-01 from the
National Center for Research Resources/National Institutes of Health.
DOI: 10.2522/ptj.20120426
Number 8
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measures in older adults. J Am Geriatr
Soc. 2006;54:743–749.
23 van der Windt D, Hay E, Jellema P, Main C.
Psychosocial interventions for low back
pain in primary care: lessons learned from
recent trials. Spine. 2008;33:81– 89.
24 Woods MP, Asmundson G. Evaluating the
efficacy of graded in vivo exposure for the
treatment of fear in patients with chronic
back pain: a randomized controlled clinical trial. Pain. 2008;136:271–280.
25 Williams AC, McCracken LM. Cognitivebehavioral therapy for chronic pain: an
overview with specific reference to fear
and avoidance. In: Asmundson G, Vlaeyen
JWS, Crombez G, eds. Understanding and
Treating Fear of Pain. London, United
Kingdom: Oxford University Press; 2004:
293–312.
26 Turner JA, Mancl L, Aaron LA. Brief
cognitive-behavioral therapy for temporomandibular disorder pain: effects on daily
electronic outcome and process measures.
Pain. 2005;117:377–387.
27 Bean JF, Olveczky DD, Kiely DK, et al.
Performance-based
versus
patientreported function: what are the underlying predictors? Phys Ther. 2011;91:1804 –
1811.
28 Ostelo RW, de Vet HC, Vlaeyen JW, et al.
Behavioral graded activity following firsttime lumbar disc surgery: 1-year results of
a randomized clinical trial. Spine. 2003;28:
1757–1765.
29 Turner JA, Holtzman S, Mancl L. Mediators, moderators, and predictors of therapeutic change in cognitive-behavioral
therapy in chronic pain. Pain. 2007;127:
276 –286.
30 Nicholas MK, George SZ. Psychologically
informed interventions for low back pain:
an update for physical therapists. Phys
Ther. 2011;91:765–776.
Appendix.
Summary of the Cognitive-Behavioral-Based Physical Therapy Intervention by Session
Topics
Major Content and Activities
All sessions include: graded exposure, goal
setting, and problem solving
Each session builds upon the content of the previous session. Format includes: (1) review of
previous session personally tailored activity and walking goals and skills practice, (2) problemsolving barriers to completing goals, (3) introduction of new content through discussion and
worksheets, and (4) patient summary of goals to reinforce commitment to the program.
Goals are specific, measurable, and realistic.
Session 1: Goal Setting
Review purpose of the program; conduct semistructured patient interview to assess current
activity level, expectations of recovery, social support, and the extent to which beliefs
contribute to pain and symptoms; explore gate control theory of pain; complete a graded
activity plan and fear hierarchy; set activity goals based on hierarchy; explore walking history
and set walking goals; and introduce deep breathing as pain management strategy.
Session 2: Your Mind and Recovery
Check graded activity practice and activity goals, set new activity goals, review walking goals
and set new goals, problem-solve barriers to completing goals, review event-thoughtsfeeling-action handouts, and introduce distraction as pain management strategy and
complete worksheet.
Session 3: Balance Your Thinking
Review activity and walking progress and set new goals, problem-solve barriers to completing
goals, identify negative thoughts that affect activity using worksheet, practice replacing
negative thoughts with positive self-talk and complete worksheet, and introduce progressive
muscle relaxation CD.
Session 4: Rest and Activity
goals, review activity types handouts, explore pacing strategies for pain management and
complete worksheet, and identify benefits of program so far and complete worksheet.
Session 5: Managing Setbacks
goals, review relapse cycle handout, and complete relapse prevention worksheet.
Session 6: Staying Healthy
Review activity and walking progress, problem-solve barriers to completing goals, complete
pain management plan worksheet (goals for activity, walking, relaxation, distraction, positive
thinking, pacing, medication use, and exercises received from their physical therapist),
identify benefits of program so far and complete worksheet, and reinforce importance of
regular exercise and follow-up visits with surgeon.
August 2013
Volume 93
Number 8
Physical Therapy f
1139
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Physical Therapy (PTJ)—APTA’s peer-reviewed scholarly journal
78
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of journc jour
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to ab ed
ac 3 rehrthop
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On
of
Letters to the Editor
On “Exercise assessment and
prescription in patients with
type 2 diabetes...” Hansen D,
Peeters S, Zwaenepoel B, et al.
Phys Ther. 2013;93:597–610.
Congratulations to Hansen and
colleagues on a fine article on
physical therapy and diabetes and
to PTJ for publishing the article
in the May 2013 issue.1 The following observations are meant to
supplement the information. They
are not intended to be critical of
the work.
Diabetes and the many other associated chronic diseases need to
further emerge on the radar and
practices of physical therapists
should we continue on our path
as doctors unbound by referral. It
is still common to see statements
such as, “Secondary conditions,
such as diabetes, may be prevalent
in this population, and physical
therapists need to be aware of
this to adjust interventions and
treatment.”2(p1408) Much worse positions often are encountered, such
as, “Physical therapy does not
treat diabetes. We do not prescribe
medication.”
The terms “advanced glycation
end-products (AGEs) or equivalent” and “chronic systemic inflammation (metaflammation) or
equivalent” are absent from the
Hansen et al article. Until physical therapy further translates the
pathophysiology of this and related chronic diseases to our profession, we will remain practitioners following prescriptions and
treating symptoms as opposed to
addressing the origin of the maladies we treat. Exercise—one of
the primary interventions for prevention, treatment, and recovery
(PTR) in diabetes—places physical therapists as one of the most
important practitioners in the PTR
August 2013
Letter 8.13.indd 1141
of diabetes and its many comorbid
conditions. Physical therapists are
positioned to be the lead practitioners in this and related diseases. We offer significant natural
intervention approaches for PTR
beyond the limitations and side
effects of a “pill” or surgery. This
potential will continue to be obfuscated by viewpoints and biases
seen too often in our profession
and certainly other professions we
come into contact with. When 80%
of the population is at direct risk,2
the issue does not remain a casual
footnote to our treatment plans.
With “diabesity”3 as a significant
disease descriptor, it is time for
the physical therapy profession
to take a fresh look at diabetes
and associated diseases in view of
the mounting evidence emerging
from the laboratories around the
world. All are related to AGEs and
metaflammation generated from
our lifestyle that alters the cellular function of every system of
the body. If physical therapy can
shake the shackles of the virtual
absence of evidence-based nutrition in its practice and further
define its role in exercise and lifestyle modification, it can make the
greatest contribution to the PTR of
diabetes of any of the professions
addressing the disease currently.
Unfortunately, diabetes PTR is at
present a very dark corner in the
physical therapy profession.
The profession will benefit by
observing information such as
the meta-analysis by Umpierre et
al4 making the association with
exercise and glycemic control. Additionally, practicing professionals
need to understand and expand
their knowledge of DNA methylation and the resultant metaflammation5 as it relates to cellular dysfunction that begins in utero6 and
progresses over the lifetime.7–9 We
must translate the importance of
myokines10 and adipokines11 from
our musculoskeletal and adipose
tissue endocrine systems into our
practice.
Recent emerging evidence alters
a physical therapist’s focus past
symptom treatment and toward
the pathophysiological origin of
the problem for treatment intervention strategies. Because Kirkness et al2 included no mention
of inflammation or AGEs in their
article, it must be assumed that
their “secondary” designation of
diabetes is related to the other
symptoms we are treating. Under
present knowledge, diabetes appears to be secondary to the AGEs
and resultant or accompanying
metaflammation. It is likely one
of many symptoms of this chronic
long-term build-up that generally
occurs covertly over many years
mainly due to our lifestyle and
nutritional practices. Diabetes becomes one of the comorbidities of
this chronic degeneration and is
not secondary to the other symptoms we treat so frequently. Although diabetes does create great
damage, the most effective treatment strategy for PTR is to address
the underlying pathophysiology of
all of the symptoms. Perhaps the
designation of “secondary” might
have more accurately been termed
“comorbid” or “accompanying”?
Kirkness et al make very important connections and points in
their excellent article; perhaps my
impression is not what the authors
intended. But diabetes itself is not
generally viewed as a disease we
treat directly. How many physical
therapist notes do you read that
address “exercise for glycemic
control” as one of the treatment
goals? Hansen et al effectively
push back against this too common omission. Still, we should be
7/11/13 10:06 AM
viewing this exercise intervention
strategy at the cellular level, which
puts us at DNA methylation,12,13
AGEs,14 and metaflammation.15
7 Lin T, Walker GB, Kurji K, et al. Parainflammation associated with advanced
glycation endproduct stimulation of
RPE in vitro: implications for age-related degenerative diseases of the eye.
Cytokine. 2013;17:00146–00144.
Nonetheless, the articles by Hansen et al1 and Kirkness et al2 are
fine offerings as the profession
struggles to expand its horizons
past symptom treatment toward
addressing the basic pathophysiology of diabetes with all of its
comorbid symptoms. PTJ is to be
commended for recognizing their
importance to the practice of physical therapy and publishing them.
8 Masternak MM, Bartke A. Growth hormone, inflammation and aging. Pathobiol Aging Age Relat Dis. 2012 Apr 4
[Epub ahead of print]. doi: 10.3402/
pba.v2i0.17293.
Joseph B. Gentzel
9 Mosquera J. Role of the receptor for
advanced glycation end products
(RAGE) in inflammation. Invest Clin.
2010;51:257–268.
10 Pedersen B. Muscles and their myokines. J Exp Biol. 2011;214(pt 2):337–
346.
11 Dastani Z, Hivert MF, Timpson N, et
al. Novel loci for adiponectin levels
and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS Genet. 2012;8:29.
J.B. Gentzel, PT, DPT, Institute for Chronic Disease Inc, 131 Galilee Church Rd,
Jefferson, GA 30549 (USA). Address
all correspondence to Dr Gentzel at:
[email protected].
12 Nitert MD, Dayeh T, Volkov P, et al.
Impact of an exercise intervention on
DNA methylation in skeletal muscle
from first-degree relatives of patients with type 2 diabetes. Diabetes.
2012;61:3322–3332.
This letter was posted as a Rapid Response on
June 26, 2013 at ptjournal.apta.org.
13 Barres R, Zierath JR. DNA methylation in metabolic disorders. Am J Clin
Nutr. 2011;93:2.
References
14 Sell DR, Monnier VM. Molecular basis of arterial stiffening: role of glycation: a mini-review. Gerontology.
2012;58:227–237.
1 Hansen D, Peeters S, Zwaenepoel B, et
al. Exercise assessment and prescription in patients with type 2 diabetes
in the private and home care setting:
clinical recommendations from AXXON (Belgian Physical Therapy Association). Phys Ther. 2013;93:597–610.
2 Kirkness CS, Marcus RL, Lastayo PC,
et al. Diabetes and associated risk
factors in patients referred for physical therapy in a national primary care
electronic medical record database.
Phys Ther. 2008;88:1408–1416.
3 Teixeira-Lemos E, Nunes S, Teixeira
F, Reis F. Regular physical exercise
training assists in preventing type 2
diabetes development: focus on its
antiooxidant and anti-inflamatory
properties.
Cardiovasc Diabetol.
2011;10:12.
4 Umpierre D, Ribeiro P, Kramer C,
et al. Physical activity advice only or
structured exercise training and association with HbA1c levels in type
2 diabetes: a systematic review and
meta-analysis. JAMA. 2011;305:1790–
1799.
5 Furuhashi M, Ishimura S, Ota H,
Miura T. Lipid chaperones and metabolic inflammation. Int J Inflam.
2011;642612:30.
6 Houde AA, Hivert MF, Bouchard L.
Fetal epigenetic programming of adipokines. Adipocyte. 2013;2:41–46.
15 Brandt C, Pedersen BK. The role of
exercise-induced myokines in muscle
homeostasis and the defense against
chronic diseases. J Biomed Biotechnol. 2010 Mar 9 [Epub ahead of print].
doi: 10.1155/2010/520258.
[DOI: 10.2522/ptj.2013.93.8.1141]
Author Response
We thank Gentzel for his valuable
comments and suggestions1 on our
recently published clinical recommendations regarding exercise assessment and prescription in type
2 diabetes mellitus (T2DM) for
physical therapists in private and
home care settings.2 We agree with
the comment that physical therapists should focus on the impact of
exercise intervention on molecular
cascades that are related to T2DM.
In this way, exercise interventions
are implemented to cure disease
(affecting the molecular cascades
that are related to insulin resistance
[IR], which is the precursor for the
development of T2DM), instead of
symptomatic control only (lowering blood glucose content). It follows that physical therapy might
be on the verge of a new era:
physical therapists could be able
to cure T2DM by exercise intervention, instead of simply suppressing
symptoms of disease. However, to
achieve such an ambiguous goal,
it is important that: (1) research
be conducted to further understand the development of insulin
resistance (IR) and the impact of
exercise intervention on these
molecular cascades and (2) physical therapists follow the literature
and adjust their exercise therapies
accordingly.
We would like to provide a brief
overview of the pathophysiology
of IR and how we could tackle IR
by exercise intervention. It should
be kept in mind, however, that the
pathophysiology of IR is extremely
complex and not yet fully understood. Moreover, the mechanisms
mentioned below are not complete,
as an in-depth discussion would be
beyond the scope of this response.
However, we believe that obtaining
some knowledge about the etiology of IR and the impact of exercise
intervention on molecular cascades
leading to IR would contribute to
more effective exercise prescription in patients with T2DM.
Type 2 diabetes mellitus results
from sustained IR. It thus follows
that when we aim to cure T2DM,
we should aim to restore insulin
sensitivity. Insulin resistance is
present in skeletal muscle cells
and adipocytes (besides the liver),
which are organs that could be targeted by exercise intervention. The
exact cause of IR, however, remains
a topic of intense debate, although
August 2013
7/11/13 10:08 AM
great progress has been made in
our understanding of the etiology
of IR during the last decade. According to current literature, different mechanisms of IR are being
proposed, although it is highly possible that the combination of these
mechanisms contributes to IR.3
On the one hand, it is argued that
IR results from the accumulation of
intramuscular lipids and lipid metabolites, especially in the presence
of a reduced lipid oxidation capacity.3 Such accumulation would ultimately lead to defects in skeletal
muscle insulin signaling and thus
to impaired muscle glucose transport.3 If this mechanism would
be valid, exercise interventions in
people with T2DM should focus
on the improvement of fat oxidation capacity and the decrease in
intramuscular lipids. However,
simply executing low-intensity
exercise bouts, with the aim to
acutely stimulate fat oxidation, fails
to improve glycemic control with
greater magnitude in patients with
T2DM in the long term, as opposed
to isocaloric high-intensity exercise
bouts.4,5 It thus might be necessary
to more aggressively force the skeletal muscles to oxidize intramuscular triacylglycerols by, for example,
providing pharmacologic support
during exercise (acute lowering in
blood free fatty acid content would
acutely increase intramuscular fat
oxidation)6 or exercise training in
a fasting condition.7 Both treatment
strategies remain to be studied during long-term exercise intervention
in patients with T2DM. We await
the outcomes from these studies
with great interest.
Other researchers, however, propose to prescribe low-volume,
high-intensity interval exercise
bouts in patients with T2DM.8
This training method would lead
to a significantly greater increase
August 2013
in skeletal muscle mitochondrial
density or content, leading the way
to greater skeletal muscle fat oxidation capacity. Although it has been
shown that high-intensity interval
exercise training—as opposed to
continuous
moderate-intensity
exercise training—is more effective in improving skeletal muscle
oxidative capacity and endurance
capacity, its additional impact on
the improvement in insulin sensitivity in the long term in patients
with T2DM remains uncertain.9 It
thus remains speculative whether
physical therapists do have the
opportunity to remediate IR by
applying different exercise training
approaches with the aim to affect
molecular cascades in the skeletal
muscles (related to intramuscular
fat content/oxidation).
It is often reported that IR results
from a state of chronic whole-body
inflammation that originates from
dysfunction of enlarged adipocytes (obesity). Physical therapists
should be aware of the fact that
adipocytes are highly active protein
(adipokines) and cytokine secreting organs. Adipocyte hypertrophy,
as well as adipocyte atrophy, is accompanied by an altered secretion
of these adipokines and cytokines.
It is currently assumed that severe
adipocyte hypertrophy would lead
to cellular stress that, in turn, would
result in oxidative stress and inflammatory responses.10 Moreover,
it has been observed that adipocytes in people who are obese are
infiltrated by mononuclear cells,
further contributing to an inflammatory response.11 This mechanism
would give way to elevated secretion of proinflammatory cytokines
and adipokines. From this mechanism, it would seem logical that
adipose tissue mass loss through
exercise intervention would lead
to an improvement in insulin sen-
sitivity. Indeed, the latter has been
noticed frequently. Moreover, it has
been established that exercise volume is an important determinant of
the improvement in glycemic control in patients with T2DM.5 This
finding could be explained by the
fact that exercise interventions with
greater exercise volumes often lead
to elevated adipose tissue mass
loss (and thus greater adipocyte
atrophy).12 Based on this logic, it
follows that exercise interventions
with large exercise volumes should
be prescribed in patients with
T2DM to remediate IR.
On the other hand, it is now known
that skeletal muscles affect the
whole-body inflammatory status by
secreting a whole array of musclederived cytokines (myokines),11
thereby explaining a reduction in
whole-body inflammation in the
presence of a minimal body weight
loss during exercise intervention.
Interleukin-6 especially seems an
interesting candidate to lower IR by
acute exercise. A profound increase
in skeletal muscle interleukin-6
secretion during acute exercise is
present and seems to suppress IR
significantly.13 However, how exercise should be prescribed to lower
whole-body inflammation (contributing to improved insulin sensitivity) through secretion of myokines
remains speculative, especially in
patients with T2DM. Also here, we
are awaiting results from exercise
studies with great expectations.
From the above, we hope that
physical therapists will become
convinced to redefine the treatment
targets of exercise intervention in
patients with T2DM in the near
future. The etiology of IR will be
further explored in greater detail,
leading us to a greater understanding of this disease, while other
researchers simultaneously explore
the impact of different training mo-
7/11/13 10:08 AM
dalities on these newly discovered
molecular cascades of IR. It is very
likely that physical therapists will
enter a new era in which they have
the opportunity to implement exercise interventions with the aim to
cure, instead of to provide care for,
T2DM. We certainly hope that this
will be the case for other chronic
diseases as well.
Dominique Hansen, Stefaan Peeters,
Michel Schotte
D. Hansen, PT, PhD, Hasselt University,
Faculty of Medicine and Life Sciences, Agoralaan, Building A, 3590, Diepenbeek, Belgium; Heart Centre Hasselt, Jessa Hospital,
Hasselt, Belgium; and Flemish Working
Group from AXXON (Belgian Physical
Therapy Association), Antwerp, Belgium.
Address all correspondence to Dr Hansen
at: [email protected].
S. Peeters, PT, Flemish Working Group from
AXXON.
M. Schotte, PT, Flemish Working Group
from AXXON.
This letter was posted as a Rapid Response on
July 1, 2013 at ptjournal.apta.org.
References
1 Gentzel JB. Letter to the editor: on “Exercise assessment and prescription in
patients with type 2 diabetes in the private and home care setting: clinical recommendations from AXXON (Belgian
Physical Therapy Association). Phys
Ther. 2013;93:1141–1142.
2 Hansen D, Peeters S, Zwaenepoel B,
et al. Exercise assessment and prescription in patients with type 2 diabetes
in the private and home care setting:
clinical recommendations from AXXON
(Belgian Physical Therapy Association).
Phys Ther. 2013;93:597–610.
3 Samuel VT, Petersen KF, Shulman
GI. Lipid-induced insulin resistance:
unraveling the mechanism. Lancet.
2010;375:2267–2277.
4 Hansen D, Dendale P, Jonkers RAM, et
al. Continuous low-to-moderate intensity exercise training is equally effective
as moderate-to-high intensity exercise
training at lowering blood HbA1c content in type 2 diabetes patients. Diabetologia. 2009;52:1789–1797.
5 Umpierre D, Ribeiro PA, Schaan BD, Ribeiro JP. Volume of supervised exercise
training impacts glycaemic control in
patients with type 2 diabetes: a systematic review with meta-regression analysis. Diabetologia. 2013;56:242–251.
6 van Loon LJC, Manders RJF, Koopman R,
et al. Inhibition of adipose tissue lipolysis increases intramuscular lipid use in
type 2 diabetic patients. Diabetologia.
2005;48:2097–2107.
7 Van Proeyen K, Szlufcik K, Nielens H, et
al. Training in the fasted state improves
glucose tolerance during fat-rich diet. J
Physiol. 2010;588:4289–4302.
8 Little JP, Gillen JB, Percival ME, et al.
Low-volume
high-intensity
interval
training reduces hyperglycemia and increases muscle mitochondrial capacity
in patients with type 2 diabetes. J Appl
Physiol. 2011;111:1554–1560.
9 Kessler HS, Sisson SB, Short KR. The potential for high-intensity interval training to reduce cardiometabolic disease
risk. Sports Med. 2012;42:489–509.
10 Kwon H, Pessin JE. Adipokines mediate inflammation and insulin resistance.
Front Endocrinol. 2013;4:71.
11 Teixeira-Lemos E, Nunes S, Teixeira F,
Reis F. Regular physical exercise training assists in preventing type 2 diabetes
development: focus on its antioxidant
and anti-inflammatory properties. Cardiovasc Diabetol. 2011;10:12.
12 Hansen D, Dendale P, van Loon LJC,
Meeusen R. The effects of training modalities on clinical benefits of exercise
intervention in cardiovascular disease
risk patients or type 2 diabetes mellitus.
Sports Med. 2010;40:921–940.
13 Pedersen L, Hojman P. Muscle-to-organ
cross talk medicated by myokines. Adipocyte. 2012;1:164–167.
[DOI: 10.2522/ptj.2013.93.8.1142]
August 2013
7/11/13 10:09 AM
Scholarships,
Fellowships, and Grants
News from the Foundation for Physical Therapy
Foundation Alumni
Publications
“Reviews of Wellness and Physical Activity Web Sites for Persons
With Neurological Disability,” by
Addison O, Whetten B, Hayes H,
and DeJong SL, was published in
the Journal of Neurologic Physical Therapy
(2013;37:91–93).
Odessa Addison, PT, DPT, PhD,
was awarded a Florence P. Kendall Doctoral Scholarship in 2008.
Stacey L. DeJong, PT, PhD, PCS,
was awarded a Florence P. Kendall Doctoral Scholarship in 2007,
a Promotion of Doctoral Studies
(PODS) I scholarship in 2008, a
PODS II scholarship in 2010, and
a New Investigator Fellowship
Training Initiative (NIFTI) in 2012.
“Effectiveness of Exercise for Managing Osteoporosis in Women Postmenopause,” by Palombaro KM,
Black JD, Buchbinder R, and Jette
DU, was published in this issue of
Physical Therapy (2013;93:1021–
1025). Kerstin M. Palombaro, PT,
PhD, CAPS, was awarded a Mary
McMillan Doctoral Scholarship in
2003. Diane U. Jette, PT, DSc, FAPTA, was awarded a Doctoral Training Research Grant in 1991.
“Fatigue Modulates Synchronous
But Not Asynchronous Soleus
Activation During Stimulation
of Paralyzed Muscle,” by Shields
RK and Dudley-Javoroski S, was
published online in Clinical Neurophysiology on May 11, 2013.
Richard K. Shields, PT, PhD,
FAPTA, was awarded Doctoral
Training Research Grants in
1989 and 1990. Shauna DudleyJavoroski, PT, PhD, was awarded
a Mary McMillan Doctoral Scholarship in 2003, PODS I scholarships in 2005 and 2006, and a
PODS II scholarship in 2008.
August 2013
Foundation 8.13.indd 1145
“The Relationship Between Spatiotemporal Gait Asymmetry and Balance in Individuals With Chronic
Stroke,” by Lewek MD, Bradley CE,
Wutzke CJ, and Zinder SM, was
published online in the Journal of
Applied Biomechanics on May 13,
2013. Michael D. Lewek, PT, PhD,
was awarded a PODS II scholarship in 2002 and a Geriatric Research Grant in 2009.
“Treadmill Exercise Elevates Striatal Dopamine D2 Receptor Binding Potential in Patients With Early
Parkinson’s Disease,” by Fisher BE,
Li Q, Nacca A, Salem GJ, Song J,
Yip J, Hui JS, Jakowec MW, and
Petzinger GM, was published online in Neuroreport on April 29,
2013. Beth E. Fisher, PT, PhD, was
awarded a Doctoral Training Research Grant in 1997, a PODS II
scholarship in 1998, and a Magistro Family Foundation Research
Grant in 2008.
Foundation Announces
Winning Schools of the
25th Pittsburgh–Marquette
Challenge
The Foundation announced the
winners of the Pittsburgh–Marquette Challenge at its annual gala
on June 27 in Salt Lake City, Utah.
Physical therapist and physical
therapist assistant students from
80 schools across the country
raised $222,008 to support physical therapy research. In 25 years,
the Challenge has raised more
than $2.5 million to benefit the
Foundation.
Congratulations to the top performing schools of this year’s
Pittsburgh–Marquette Challenge:
•
1st Place: University of Miami
($28,808)
•
2nd Place: University of Pittsburgh ($28,450)
•
3rd Place: New York University
($16,275)
The Foundation would also like to
recognize the Marquette University
students for their financial commitment to the Challenge in donating
$20,000.
Award of Excellence (donating
$10,000 or more): University of
Colorado, Virginia Commonwealth
University.
Award of Merit (donating $6,000
or more): Emory University, MGH
Institute of Health Professions, Rosalind Franklin University of Medicine & Science.
Honorable Mention (donating
$3,000 or more): Arcadia University,
Drexel University, Mayo School of
Health Sciences, Midwestern University (Downers Grove, Illinois),
Northeastern University, Northwestern University, Simmons College, Somerset Community College,
University of Delaware, University
of Illinois at Chicago, University
of Iowa, University of North Carolina at Chapel Hill, University of
Oklahoma Health Sciences Center,
University of Southern California,
Washington University in St Louis.
Special Awards:
•
Most Successful
University
of
Milwaukee
Newcomer:
Wisconsin–
•
Biggest Stretch Schools: University of Miami
•
Most Successful PTA School:
Somerset Community College
•
Most Creative Fundraiser: the
Student Special Interest Group
of the Illinois Physical Therapy
Association.
7/10/13 10:15 AM
Scholarships, Fellowships, and Grants
We would also like to recognize
the following schools who participated: A.T. Still University, Boston University, Clarkson College,
Cleveland State University, Columbia University, Concordia University Wisconsin, Creighton University,
Daemen College, Elon University,
Fox College, George Washington University, Indiana University,
Ithaca College, Louisiana State
University Health Sciences Center–
Shreveport, Lynchburg College,
Marymount University, Maryville
University of St Louis, MCPHS
University, Midwestern University
(Glendale, Arizona), Nassau Community College, Nazareth College, Northern Illinois University,
Oakton Community College, Ohio
State University, Pennsylvania State
University–Shenango, Quinnipiac
University, Richard Stockton College of New Jersey, Rockhurst University, Sacred Heart University,
Saint Louis University, Slippery
Rock University of Pennsylvania,
Southwestern Illinois College, St
Ambrose University, Temple University, Texas Woman’s University–
Houston, Thomas Jefferson University, UMDNJ-SHRP and Rutgers
Camden, University of Evansville,
University of Hartford, University
of Kentucky, University of Mississippi Medical Center, University of
Nebraska Medical Center, University of North Florida, University of
Saint Francis, University of Scranton, University of South Dakota,
University of St Augustine–Florida,
University of Wisconsin–La Crosse,
University of Wisconsin–Madison,
University of Wisconsin–Milwaukee, Walsh University, West Kentucky Community and Technical
College, Western Carolina University, Western University of Health
Sciences, Wichita State University,
Youngstown State University.
The 2013–2014 Miami–Marquette
Challenge kicks off at the National
Student Conclave in Louisville, Kentucky, on October 24, 2013.
Foundation Announces
Fundraising Campaign for
Health Services Initiative
The Foundation recently announced that it will launch the
public phase of a campaign to
establish the nation’s first center
dedicated to expanding the number of physical therapy scientists
in the field of health services and
health policy.
Through this program, called
The Center of Excellence (COE),
physical therapist researchers
will receive the training and
skills necessary to examine the
most effective ways to deliver,
organize, and finance health care
delivery.
As of June, the campaign had already raised $1.7 million toward
the goal of $3 million (which will
fund the initiative for 5 years),
thanks in large part to a generous
lead gift of $1 million from APTA.
Other significant contributors include the Magistro Family Foundation, Tennessee Chapter, Wisconsin Chapter, Section on Geriatrics,
Home Health Section, Neurology
Section, Orthopedic Section, Private Practice Section, Section on
Research, and the Sports Physical
Therapy Section.
The COE will ultimately help shape
the role of the physical therapy
profession in health care delivery
around the country. In the coming months, the Foundation will
be reaching out to every remaining ATPA components, individuals,
and organizations outside the profession to reach its campaign goal
by the end of the year.
Foundation 8.13.indd 1146
Current Funding
Opportunities
The Foundation is now accepting applications for the Kendall
Scholarship and Research Grant
programs. Students beginning
their postprofessional doctoral
programs are encouraged to apply for a $5,000 Kendall Scholarship. Foundation Research
Grants are available for either
1- or 2-year projects for new and
emerging investigators. Be sure
to review all guidelines and instructions carefully before beginning an application. Applications for both opportunities are
due Wednesday, August 14, 2013,
at noon, EDT. For more details,
please visit Foundation4PT.org/
apply-for-funding.
Share Your Research News
and Announcements
To have your information posted in
the Foundation’s section of Physical Therapy, please e-mail Rachael
Crockett
at
RachaelCrockett@
Foundation4PT.org.
Stay Connected in 3 Easy Ways
1. www.facebook.com/foundation
4PT.
2. Check
out
our
Foundation4PT.org.
website:
3. Receive the monthly newsletter
for updates on donors, Foundation alumni, events, and much
more! E-mail RachaelCrockett@
Foundation4PT.org to subscribe.
[DOI: 10.2522/ptj.2013.93.8.1145]
August 2013
7/10/13 10:15 AM
Product
Highlights
It’s a matter of time.
Spend less time hunting and more time healing. Start
your search for evidence at www.hookedonevidence.org.
APTA’s Hooked on Evidence database provides members
with article extracts and patient clinical scenarios of commonly
seen conditions. Each extract provides information about the
participants, treatments, and outcomes that you can apply in your
own practice.
Bookmark our site. Let Hooked on Evidence lead you
to the articles that apply best to your patients.
And benefit from instant access to evidence
of the effectiveness of physical therapy
interventions.
www.hookedonevidence.org
August 2013
Product Highlights
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Ad Index
Aretech ......................................................... Cover 2
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WebPT .............................................................. 1019
APTA Products and Services
Assessing Competence:
A Resource Manual ........................................ 1013
Electrotherapuetic Terminology
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FirstHand Student Kit .................................... Cover 3
Hooked on Evidence ......................................... 1147
Membership ..................................................... 1140
Request FREE Product Information on products advertised in PTJ.
Go to APTA’s online resource at: http://www.apta.org/freeproductinfo
August 2013
FirstHand Student Kit
Buy it for school. Use it for years.
APTA's FirstHand meets the current and future needs of physical therapy students! FirstHand is a prepackaged kit containing the most frequently used instruments, with brand names you trust, that students of
physical therapy need for their clinical education—and beyond. FirstHand includes:
Rappaport-type stethoscope
Thera-Band® Resistive Exerciser
sphygmomanometer
penlight
A Quick Reference to Common Tests &
Measurements in Physical Therapy booklet
Buck hammer
ergonomic ballpoint pen
bandage scissors
skin marker
6" and 8" goniometers
retractable tape measure
These instruments are organized in a professional-looking, durable, water-repellant
black Cordura case. Please note that gait belts are not included in this product.
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This premium 60" vinyl gait belt is US-made and
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Complete August Issue - Physical Therapy Journal

Transcription

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