Complete August Issue - Physical Therapy Journal

Transcription

August 2015 Volume 95 Number 8
ProfessionWatch
1087
1142
Ambulatory Activity Decline in
Parkinson Disease
1151
Adaptive Riding in Children With
Cerebral Palsy
Interpreting Effectiveness Evidence in Pain
Research Reports
1095
What Works to Prevent Falls?
1163
Trunk Support and Upper Extremity Function
1111
Skin Intrinsic Fluorescence in
Diabetes Mellitus
1172
Group- and Individual-Level
Responsiveness of 3 Measures
Stratified Primary Care Model for Outpatient
Low Back Pain Management
Perspective
Physical Activity in Parkinson Disease
1184
1120
1135
Nobel Prize for Physical Therapy?
Physical Therapy
f
Volume 95
f
Number 8
f
August 2015
Editorials
1082
Appointment of the Editor in Chief, 2016 –2020 /
Sharon L. Dunn
1084
In Tribute: David L. Sackett / Paul
Stratford
ProfessionWatch
Gustave Caillebotte (French, 1848 –
1894). Boating Party. 1877. Photo credit:
Scala/White Images / Art Resource, NY.
1087
Interpreting Effectiveness Evidence in Pain: Short Tour
of Contemporary Issues / Neil E. O’Connell, G. Lorimer Moseley,
James H. McAuley, Benedict M. Wand, Robert D. Herbert
Known for his use of unusual perspectives, Caillebotte has seated the viewer in
the boat, opposite the rower. The rower’s
head turns to the left, his center of gravity
shifts right, and the boat tilts. The rower’s
hands grip the oars fiercely, out of character with the vague, glassy calm of the
river beyond.
Research Reports
1095
What Works to Prevent Falls in Community-Dwelling
Older Adults? Umbrella Review of Meta-analyses of
Randomized Controlled Trials / Brendon Stubbs, Simone Brefka,
Michael D. Denkinger
1111
Relationship Between Skin Intrinsic Fluorescence—an
Indicator of Advanced Glycation End Products—and
Upper Extremity Impairments in Individuals With
Diabetes Mellitus / Kshamata M. Shah, B. Ruth Clark, Janet B. McGill,
Catherine E. Lang, John Maynard, Michael J. Mueller
1120
Pragmatic Implementation of a Stratified Primary Care
Model for Low Back Pain Management in Outpatient
Physical Therapy Settings: Two-Phase, Sequential
Preliminary Study / Jason M. Beneciuk, Steven Z. George
1135
Levels and Patterns of Physical Activity and Sedentary
Behavior in Elderly People With Mild to Moderate
Parkinson Disease / Martin Benka Wallén, Erika Franzén, Håkan Nero,
Maria Hagströmer
1142
Toward Understanding Ambulatory Activity Decline
in Parkinson Disease / James T. Cavanaugh, Terry D. Ellis,
Gammon M. Earhart, Matthew P. Ford, K. Bo Foreman, Leland E. Dibble
Craikcast
Editor in Chief Rebecca Craik gives her unique
insights on the August issue. Available at
http://ptjournal.apta.org/content/95/8/suppl/DC1 and through
iTunes.
1078
f
Physical Therapy
Volume 95
Number 8
August 2015
1151
1163
Therapist-Designed Adaptive Riding in Children
With Cerebral Palsy: Results of a Feasibility Study /
Departments
Mattana Angsupaisal, Baudina Visser, Anne Alkema, Marja Meinsma-van der Tuin,
Carel G.B. Maathuis, Heleen Reinders-Messelink, Mijna Hadders-Algra
1197
News from the Foundation for
Physical Therapy
Effect of Trunk Support on Upper Extremity
Function in People With Chronic Stroke and
People Who Are Healthy / Seng Kwee Wee, Ann-Marie Hughes,
Martin B. Warner, Simon Brown, Andy Cranny, Evangelos B. Mazomenos,
Jane H. Burridge
1172
Yi-Jing Huang, Kuan-Lin Chen, Yeh-Tai Chou, I-Ping Hsueh, Chieh-Yi Hou,
Ching-Lin Hsieh
1184
Nobel Prize for Physical Therapy? Rise, Fall, and
Revival of Medico-Mechanical Institutes / Nils Hansson,
Anders Ottosson
August 2015
1199
Product Highlights
1200
Ad Index
Resources
Comparison of the Responsiveness of the Long-Form
and Simplified Stroke Rehabilitation Assessment of
Movement: Group- and Individual-Level Analysis /
Perspective
Scholarships, Fellowships,
and Grants
Abstracts of Papers to be Presented at
APTA’s NEXT Conference (added every
May): aptaapps.apta.org/abstracts
PTJ Submission Guidelines:
ptjournal.apta.org/site/misc/ifora.xhtml
iOS App: ptjournal.apta.org/site/misc/
ptj_app.xhtml
APTA Membership Statistics: June issue
PTJ Statement of Ownership:
December issue
Volume 95
Number 8
Physical Therapy f
1079
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, MBA, 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; Mary Gannotti, PT, PhD, Hartford, CT;
Steven Z. George, PT, PhD, Gainesville, FL; Arlene Greenspan, PT, DrPH, Atlanta, GA; Kathleen Gill-Body, PT, DPT, NCS, Boston, MA;
Jill C. Heathcock, PT, PhD, Columbus, OH; Rana Shane Hinman, PT, PhD, Melbourne, Victoria, Australia;
Diane U. Jette, PT DSc, FAPTA, Boston, MA; 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, FAPTA, Seattle, WA;
Patricia J. Ohtake, PT, PhD, Buffalo, NY; Elizabeth K. Rasch, PT, PhD, Bethesda, MD;
Darcy Schwartz Reisman, PT, PhD, Wilmington, DE; Linda Resnik, PT, PhD, Providence, RI;
Samuel R. Ward, PT, PhD, La Jolla, CA; Philip J. van der Wees, PT, PhD, Nijmegen, the Netherlands;
Advisor, Clinical Practice Guidelines: James J. Irrgang, PT, PhD, ATC, FAPTA, Pittsburgh, PA;
Chair, Rothstein Roundtable: Anthony Delitto, PT, PhD, FAPTA, Pittsburgh, PA
Statistical Consultants
Hang Lee, PhD, Boston, MA; Xiangrong Kong, PhD, Baltimore, MD; Gregory F. Petroski, PhD, Columbia, MO;
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
Senior Reviewers
Karen Abraham-Justice, PT, PhD; Peter Altenburger, PT, PhD; Paul Beattie, PT, PhD, OCS, FAPTA; Leanne Bisset, PhD;
Timothy Brindle, PT, PhD, ATC; Donna Cech, PT; Daniel Cipriani, PT, PhD; Barbara H. Connolly, PT, DPT, EdD, FAPTA;
Chad Cook, PT, PhD, MBA, OCS, FAAOMPT; Gammon Earhart, PT, PhD; Christian Evans, PT, PhD; Manuela Ferreira, PT, PhD;
Cheryl Ford-Smith, PT, DPT, MS, NCS; Jorge Fuentes, PT, BSc, MSc, RS, PhD Candidate; Meryl Gersh, PT, PhD; Adam Goode, PT, DPT, PhD;
Kathy Green, PhD; Bruce Greenfield, PT, PhD, OCS; Mijna Hadders-Algra, MD, PhD; Lisa (Elizabeth) Hannold, PhD;
Regina Harbourne, PT, PhD, PCS; Karen Hayes, PT, PhD, FAPTA; Jessie Huisinga, PhD; Kenton Kaufman, PhD;
Suzanne Kuys, GDPublth, BPhysio(H); Merrill Landers, PT, DPT, OCS; Sandra Levi, PT, PhD; Kathleen Mangione, PT, PhD, GCS;
Sunita Mathur, PT; Karen McCulloch, PT, PhD, NCS; Christine McDonough, PT, PhD; Irene McEwen, PT, PhD, FAPTA; Michael Mueller, PT, PhD;
Susan Muir, PT; Gina Musolino, PT, MSEd, EdD; Jacqueline Nuysink, PT, MSc, PCS; Stéphane Poitras, PhD; Emilio Puentedura, PhD;
Kathleen Rockefeller, PT, MPH, ScD; Mark Damian Rossi, PT, PhD, CSCS; Susan Roush, PhD; Lisa Selby-Silverstein, PT, PhD, NCS;
Mary Shall, PT, PhD; Elizabeth Skinner, PhD; Beth Smith, PT, DPT, PhD; Jane Sullivan, PT, PhD, NCS; Greg Thielman, PT, EdD, ATC;
David Thompson, PT, PhD; Carole Tucker, PT, PhD, PCS; Ann Vendrely, PT, DPT, EdD; Susan Wainwright, PT, PhD; Joseph Zeni, PhD
PTJ Editorial Office
Managing Editor: Jan P. Reynolds, [email protected]; PTJ Online Editor / Assistant Managing Editor: Steven Glaros;
Associate Editor: Stephen Brooks, ELS; Editorial Assistant: Natacha Leonard; Editorial Tracking Manager: Karen Darley
Association Staff
Chief Executive Officer: J. Michael Bowers; Vice President of Research: Robyn Watson Ellerbe, PhD;
Director of Publishing / Member Communications: Lois Douthitt
Advertising Manager: Julie Hilgenberg; Permissions / Reprint Coordinator: Michele Tillson
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: Sharon L. Dunn, PT, PhD, OCS; Vice President: Lisa K. Saladin, PT, PhD, FASAHP; Secretary: Laurita M. Hack, PT, DPT, MBA, PhD, FAPTA;
Treasurer: Elmer Platz, PT; Speaker of the House: Susan R. Griffin, PT, DPT, MS, GCS; Vice Speaker of the House: Stuart Platt, PT, MSPT;
Directors: Susan A. Appling, PT, DPT, PhD, OCS; Jeanine M. Gunn, PT, DPT; Roger A. Herr, PT, MPA, COS-C; Matthew R. Hyland, PT, PhD, MPA;
Kathleen K. Mairella, PT, DPT, MA; Sheila K. Nicholson, PT, DPT, JD, MBA, MA; Carolyn Oddo, PT, MS, FACHE;
Robert H. Rowe, PT, DPT, DMT, MHS, FAAOMPT; Sue Whitney, PT, DPT, PhD, NCS, ATC, FAPTA
1080
f
Physical Therapy
Volume 95
Number 8
August 2015
Subscriptions
Physical Therapy (PTJ) (ISSN 00319023) is published monthly by the
American Physical Therapy Association
(APTA), 1111 North Fairfax Street,
Alexandria, VA 22314-1488, at an
annual subscription rate of $12 for
members, included in dues. Nonmember rates are as follows: Individual
(inside USA)—$129; individual (outside
USA)—$149 surface mail, $209 air mail.
Institutional (inside USA)—$169; institutional (outside USA)—$189 surface
mail, $249 air mail. Periodical postage
is paid at Alexandria, VA, and at additional mailing offices. Postmaster:
Send address changes to Physical Therapy, 1111 North Fairfax Street, Alexandria, VA 22314-1488. Single copies: $15
USA, $15 outside USA. All orders payable in US currency. No replacements
for nonreceipt after a 3-month period
has elapsed. Canada Post International
Publications Mail Product Sales Agreement No. 0055832.
Members and Subscribers
Send changes of address to: APTA, Attn:
Member Services Dept, 1111 North
Fairfax St, Alexandria, VA 22314-1488.
Subscription inquiries: 703/684-2782,
ext 3124. PTJ is available in a special
format for readers who are visually
impaired. For information, contact
APTA’s Member Services Department
at 703/684-2782, ext 3124.
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).
August 2015
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
the institution with which the author is
affiliated, unless expressly stated.
PTJ Online
at ptjournal.apta.org
PTJ Online is available via RSS
feeds. PTJ posts articles ahead
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.
Indexing and
Document Delivery
PTJ is indexed by MEDLINE, PubMed,
Cumulative Index to Nursing & Allied
Health (CINAHL), EMBASE/Exerpta
Medica, AgeLine, Allied and Complementary Medicine Database (AMED),
Index Medicus, and Science Citation
Index (SCI), among others. A complete
list is available from ptjournal.apta.org/
site/misc/about.xhtml.
Article abstracts are available online
at ptjournal.apta.org (1980 through
present) and via MEDLINE, PubMed,
Allied and Complementary Medicine
Database (AMED), Cumulative Index
to Nursing & Allied Health (CINAHL),
Dialog, and OCLC FirstSearch, among
others.
Full-text articles are available for free at
ptjournal.apta.org 12 months after the
publication date (1980 to present). Full
text is also provided through Dialog,
EBSCOhost, InfoTrac, ProQuest, and
Westlaw.
Reprints
Readers should direct requests for
reprints to the corresponding author of
the article. Students and other academic
customers may receive permission to
reprint copyrighted material from this
publication by contacting the Copyright
Clearance Center Inc, 222 Rosewood Dr,
Danvers, MA 01923. Authors who want
reprints should contact June Billman,
Cadmus Communications, at 800/4875625, or [email protected]. Nonacademic institutions needing reprint
permission information should go to
ptjournal.apta.org/site/misc/terms.xhtml.
Advertising
Advertisements are accepted by PTJ
when they conform to the ethical standards of the American Physical Therapy
Association. PTJ does not verify the
accuracy of claims made in advertisements, and acceptance does not imply
endorsement by PTJ or the Association. Acceptance of advertisements for
professional development courses
addressing advanced-level competencies in clinical specialty areas does not
imply review or endorsement by the
American Board of Physical Therapy
Specialties.
Statement of
Nondiscrimination
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.
Volume 95
Number 8
Physical Therapy f
1081
Editorial
Appointment of the Editor in Chief,
2016 –2020
O
n behalf of APTA’s Board of Directors, I am pleased to announce the appointment
of Alan M. Jette, PT, PhD, FAPTA, as editor in chief* of Physical Therapy (PTJ),
effective January 1, 2016. Dr. Jette will succeed Rebecca Craik, PT, PhD, FAPTA,
who has led the journal to new heights since 2006 and whose second and final term ends
December 31, 2015. Over the next few months, she will prepare the Journal for its next
phase, working with Alan to achieve a smooth transition.
Alan is no stranger to PTJ; through the years he has been an author (known particularly
for outcomes research), a reviewer, an Editorial Board member, a special issue editor, and
a deputy editor. Most significantly, 10 years ago, he served as interim editor during Editor
in Chief Jules Rothstein’s medical leave. This was a time when the Journal was undergoing major change, due not only to Dr. Rothstein’s illness and death but to rapid
developments in both physical therapy research and the publication of science. Alan
recognized that “electronic publishing is accelerating the expectations of all participants
in scholarly publication and that the Journal was at a critical juncture,”1 and he helped
set the Journal on the right path.
To his role as editor in chief, Alan will bring his experience on the “researcher side” of
publication, having received more than $50 million in grants from the National Institutes
of Health, the National Institute on Disability and Rehabilitation Research, the Centers for
Disease Control and Prevention, the Centers for Medicare and Medicaid Services, the
Social Security Administration, and others. He also will bring his experience in health
policy related to disability, perhaps epitomized by his 2013 election to the National
Academies of Science’s Institute of Medicine (IOM), where he co-chaired the IOM Forum
on Aging, Disability, and Independence. This rich experience, combined with his history
of prestigious academic appointments, uniquely qualifies Alan to take the helm of
PTJ—what he calls a natural extension of his interest in fostering the research of others.2
Alan’s greatest asset may be his enthusiasm for the Journal and its role in supporting the
profession. In 2012, as the 43rd Mary McMillan Lecturer, Alan described a physical
therapy culture that “has matured sufficiently to strive toward a future that is outward in
its orientation,”3(p1224) referring to what Purtilo called a “Period of Societal Identity”
where the challenge “will be to establish the moral foundations for a true professional
partnering with the larger community of citizens and institutions . . . to become full
partners with society.”4(pp1114,1117) Alan asked our profession, “Are we ready to embrace
the emerging season of physical therapy’s Period of Societal Identity with confidence
and renewed energy?”3(p1228) The Board of Directors believes that Alan will vigorously
embrace the emerging season of PTJ’s Period of Societal Identity, which has great
synergy with APTA’s outward-facing vision of “Transforming society by optimizing
movement to improve the human experience.”
On behalf of the Board of Directors, and also as former vice president who served as chair
of the editor-in-chief search committee, I would like to take this opportunity to thank the
To comment,
submit a Rapid
Response to this
editorial posted online
at: ptjournal.apta.org.
1082
f
Physical Therapy
* The editor in chief is appointed by APTA’s Board of Directors for a 5-year term, with possible reappointment
for another 5-year term, as per Board of Director policy “Journal Editor-in-Chief” (BOD Y05-14-02-02
[Amended BOD Y03-04-15-38; BOD 03-03-26-72; BOD 03-94-13-30; BOD 03-88-36-124]). No editor in chief
shall serve more than 2 consecutive 5-year terms.
Volume 95
Number 8
August 2015
Editorial
search committee members—Susan M. Chalcraft, PT, MS; Kathleen Gill-Body, PT, DPT,
NCS, FAPTA; Daniel L. Riddle, PT, PhD, FAPTA; and Philip J. van der Wees, PT, PhD—for
their hard work and their thoughtful deliberation regarding our excellent candidates.
The Board of Directors and I look forward to PTJ’s next evolutionary phase, which will
build on the strong accomplishments of Dr. Craik and her editorial board.
Sharon L. Dunn
S.L. Dunn, PT, PhD, OCS, is President, APTA.
References
1 Reynolds J. Extraordinary people. Phys Ther. 2006;86:6.
2 Alan M. Jette, PT, PhD, FAPTA, Named PTJ Editor-in-Chief. News release. Available at: http://www.apta.
org/Media/Releases/Association/2015/6/1. Accessed June 17, 2015.
3 Jette AM. Forty-Third Mary McMillan Lecture: Face into the storm. Phys Ther. 2012;92:1221–1229.
4 Purtilo RB. Thirty-First Mary McMillan Lecture: A time to harvest, a time to sow: ethics for a shifting
landscape. Phys Ther. 2000;80:1112–1119.
[DOI:10.2522/ptj.2015.95.8.1082]
August 2015
Volume 95
Number 8
Physical Therapy f
1083
Editorial
In Tribute: David L. Sackett
T
he health care community has lost a remarkable human being who had a profound
impact on research methodology and the way clinical practice has evolved over the
past 5 decades.
Dr. David Sackett (Figure), recognized as the father of evidence-based medicine (practice) (EBM), died on May 13, 2015. Evidence-based medicine (practice) is defined as “the
integration of best research evidence with clinical expertise and patient values”1,2 and
was ranked by BMJ as one of the top 10 medical breakthroughs since 1840.3
Sackett was born in Chicago and received a medical degree from the University of Illinois
and a master’s degree in epidemiology from Harvard University. His original medical
training was in internal medicine and nephrology; however, at the time of the Cuban
Missile Crisis, he was drafted and assigned to the US Public Health Service (USPHS). It was
during his experience with the USPHS that he began to conceive how epidemiological
principles could be applied to clinical practice. “Big-E” epidemiology examines the
distribution and determinants of disease and injury in populations, whereas clinical
epidemiology is concerned with the determinants and effects of clinical decisions.
The following is a brief account of Sackett’s career in his own words and edited by Dr.
Brian Haynes. It appeared in an interview-style document that he wrote in response to
questions about his career:
After training in internal medicine, nephrology and epidemiology, David Sackett re-coined the
term “clinical epidemiology” and began his 1st career (age 32) as the founding Chair of Clinical
Epidemiology & Biostatistics at McMaster University’s new medical school. In his 2nd career he
began to design, execute, interpret, nominate, write and teach about randomized clinical trials,
an activity that continues to the present, some 200 trials later. His 3rd career was dedicated to
developing and disseminating “critical appraisal” strategies for busy clinicians and ended when
he decided he was out of date clinically and returned (at age 49), in his 4th career, to a 2-year
“retreading” residency in Hospitalist Internal Medicine. His 5th and 6th careers were largely
clinical, as Physician-in-Chief at Chedoke-McMaster Hospitals, and as Head of the Division of
General Internal Medicine for the Hamilton region. In 1994 a chair was created for him at the
University of Oxford, where he took up his 7th career as Foundation Director of the National
Health Service at the John Radcliffe Hospital, Foundation Chair of the Cochrane Collaboration
Steering Group, and Foundation Co-Editor of Evidence-Based Medicine. Retired from clinical
practice in 1999, he began his 8th career by returning to Canada and setting up the Trout
Research & Education Centre, where he reads, researches, writes and teaches about randomized
clinical trials. Along the way, he has published 12 books, chapters for about 60 others, and over
300 papers in medical and scientific journals.4(p7)
To comment,
submit a Rapid
Response to this
editorial posted online
at: ptjournal.apta.org.
1084
f
Physical Therapy
Sackett’s lifelong commitment was to improve patient outcomes through the application
of the best available evidence. Quite simply, his raison d’ être was to “train the masses”
to transform research findings into clinical actions that best served individual patients.
Although many of his efforts focused on the design, conduct, reporting, and interpretation of randomized clinical trials, he made equally important contributions to many other
areas of clinical practice and education. For example, in a series of 27 monographs
published in the journal Clinical Trials, he and his coauthors addressed a spectrum of
topics including time management, mentoring, sabbaticals, fabrication of data, and
modernization of graduate education courses.
Regardless of his topic, the hallmark of his teaching was to use the clinical vignette as a
way to grab the attention of his readers. One example concerning prognosis: “Suppose,
for example, you detect 10 to 15 degrees of scoliosis in an otherwise healthy 12-year-old
Volume 95
Number 8
August 2015
Editorial
student who has come for her preschool examination.
Do you tell her and her parents (and, if so, what do you
say?), refer her to an ‘orthopod’ or what?”2 These seemingly simple vignettes not only served as a “hook” to
catch the interest of learners but provided the starting
point for a process of inquiry and learning. The “Sackett
process” typically involved the following steps: (1) structure a researchable question, (2) select the most likely
resource, (3) design an effective search strategy,
(4) summarize and critique the evidence, (5) apply the
evidence to the patient of interest, and (6) evaluate the
process and outcome.
Although Sackett’s name will forever be synonymous
with EBM and clinical practice, he last wrote and spoke
about it more than 15 years ago. His reasoning provides
further insight into his character and values:
Figure.
David L. Sackett, OC, FRSC, MD,
MSc(Epidemiology), ScD, FRCP
(Canada, London, Edinburgh).
Professor Emeritus, McMaster
University, Hamilton, Ontario,
Canada.
I had long held the view that ‘experts’ inevitably became
detrimental to the fields of their expertise, for 2 reasons.
First, their opinions and pronouncements about their field
carried a far greater persuasive power than they deserved on the basis of evidence alone.
Second, subconsciously (if not consciously), experts’ acceptance or rejection of new ideas
about their field (presented in the grants and manuscripts they were asked to referee) were
influenced by the extent to which these new ideas challenged their prior expert pronouncements. For these reasons, I had ‘resigned’ from the field of compliance research back in the
early 80’s. Matters were even worse for me as the EBM expert: I was considered a nice guy,
and colleagues who disagreed with my views were worried about hurting my feelings. Shortly
after our return to Canada [circa late 1990’s] I published my resignation from EBM in the BMJ,
and with the exception of these interviews, I haven’t refereed, written, or lectured about EBM
since.4(p57)
Over the decades, David Sackett received numerous awards, including induction into
the Canadian Medical Hall of Fame, the Gairdner Wightman Award, and Officer of the
Order of Canada. Although these recognitions and scholarly achievements are exceptional, the man himself was even more remarkable. He genuinely cared about his
patients, colleagues, and students, and he never sought to upstage those around him.
Although his name will forever be synonymous with evidence-based practice, his legacy
is the countless number of clinicians and researchers he influenced and their “ripple
effect” on others. He will be missed.
Paul Stratford
P. Stratford, PT, School of Rehabilitation Science, McMaster University, Hamilton, Ontario, Canada.
Comment From Editor in Chief Rebecca Craik and
Deputy Editor Daniel Riddle
I (R.C.) was chair of the Strategic Planning Committee for the APTA Section on Research
from 1992 to 1996. Consistent with planning that occurred in many sections at that
time, the mission and vision statements addressed diverse and sometimes divergent
member needs. For the Section on Research, long-term objectives and action items had
to meet the needs of members interested in becoming informed consumers of research,
whereas other objectives had to address the needs of members interested in improving
August 2015
Volume 95
Number 8
Physical Therapy f
1085
Editorial
research design, methodology, and analysis. We struggled. I still remember Lynn SnyderMackler, PT, PhD, FAPTA (APTA’s most recent Mary McMillan Lecturer), bursting into the
room at one of our meetings, carrying a tome. She was so excited to share the Users’
Guides to the Medical Literature I-IX that had been published in JAMA in the early 1990s
(the first aptly called “How to Get Started”5). The Evidence-Based Medicine Working
Group, which had developed those guides, included David Sackett. Lynn advocated for
these articles to serve as a framework for continuing education courses in physical
therapy and for section research efforts.
It is amazing how quickly the term “evidence-based practice” (EBP)—though not necessarily evidence-based actions— became part of our lexicon. Sackett and his colleagues
have inspired so many activities and provided a foundation for essentially all EBP
curricula in physical therapy. Sackett’s impact on physical therapy is profound; here we
list only a few contributions:
• The evaluative criteria6 used by the Commission on Accreditation in Physical Therapy
Education (CAPTE) require that the curriculum prepare students for EBP.
• The Centre for Evidence-Based Physiotherapy,7 established in 1999, strives to maximize the
effectiveness of services by facilitating the application of the best available evidence.
• PEDro,8 the physiotherapy evidence database, contains about 30,000 randomized controlled
trials, systematic reviews, and clinical practice guidelines and can be accessed online for free.
• Stroke Engine9 is a free site designed by the Canadian Partnership for Stroke Recovery to
bridge the gap in knowledge translation between research findings and current clinical
practice.
• PTNow,10 APTA’s clinician website, is designed to help physical therapist and physical
therapist assistant members use evidence in patient care.
To this Sackett-inspired list, we add that PTJ developed the feature “Linking Evidence
And Practice (LEAP)” to demonstrate how to apply evidence to practice.
We thank Paul Stafford, one of PTJ’s statistical consultants and one of Sackett’s fellow
Canadians, for speaking to Sackett’s accomplishments and honoring his memory.
References
1 Sackett DL, Straus SE, Richardson WS, et al. Evidence-based Medicine: How to Practice and Teach EBM. 2nd
ed. Toronto, Ontario, Canada: Churchill Livingstone; 2000.
2 Sackett DL, Haynes RB, Tugwell P. Clinical Epidemiology: A Basic Science for Clinical Medicine. Boston,
MA: Little, Brown and Company; 1985.
3 BMJ Poll Results: Medical Milestones. Available at: http://www.bmj.com/content/suppl/2007/01/18/334.
suppl_1.DC3. Accessed June 19, 2015.
4 Sackett DL. Interview in 2014 and 2015: pp7, 57. Reprinted with permission. Available at: http://fhs.
mcmaster.ca/ceb/docs/David_L_Sackett_Interview_in_2014_2015.pdf. Accessed June 19, 2015.
5 Oxman AD, Sackett DL, Guyatt GH. Users’ guides to the medical literature. I. How to get started. Evidencebased Medicine Working Group. JAMA. 1993;270:2093–2095.
6 Commission on Accreditation in Physical Therapy Education (CAPTA). Evaluative Criteria for Accreditation of Education Programs for the Preparation of Physical Therapists. Available at: http://www.
capteonline.org/uploadedFiles/CAPTEorg/About_CAPTE/Resources/Accreditation_Handbook/
EvaluativeCriteria_PT.pdf. Accessed June 19, 2015.
7 Centre of Evidence-Based Physiotherapy. Available at: http://www.cebp.nl. Accessed June 19, 2015.
8 Physiotherapy Evidence Database (PEDro). Available at: http://www.pedro.org.au. Accessed June 19, 2015.
9 Canadian Partnership for Stroke Recovery. Stroke Engine. Available at: http://www.strokengine.ca.
Accessed June 19, 2015.
10 PTNow. Available at: http://www.ptnow.org. Accessed June 19, 2015.
[DOI:10.2522/ptj.2015.95.8.1084]
1086
f
Physical Therapy
Volume 95
Number 8
August 2015
ProfessionWatch
Interpreting Effectiveness Evidence in Pain:
Short Tour of Contemporary Issues
Neil E. O’Connell, G. Lorimer Moseley, James H. McAuley, Benedict M. Wand, Robert D. Herbert
P
eople with pain and the clinicians who help them are faced
with a maze of treatment
options, each backed by enthusiastic
and highly motivated advocates, all
of whom lay claim to “evidence.”
Negotiating the treatment maze has
never been more difficult. How can
patients make an informed choice
about their own care and how can
clinicians best inform that choice?
Clinical trials remain the best tool for
reducing uncertainty about the
effects of treatment. The recent
growth in the number of clinical trials and systematic reviews, of both
high and low quality, makes it vital
that clinicians, researchers, patients,
and policy makers have the skills and
knowledge to critically interpret the
available evidence. Here, we discuss
some contemporary issues regarding
evidence of effectiveness from clinical trials and systematic reviews in
pain—issues that we think are critical to understanding the field.
Clinical trials can be designed to test
efficacy (whether an intervention
delivers an effect in ideal conditions)
or effectiveness (whether an intervention delivers an effect in the real
world). In reality, many trials test
something that falls somewhere on a
continuum between the two.1 We
focus on evidence of effectiveness of
treatments for pain, particularly
chronic pain. We also examine evidence from the world of pharmacological interventions for pain to consider what lessons there may be
for interpreting nonpharmacological
evidence. Many of these issues also
are relevant to evidence of efficacy
of treatments for pain and are trans-
August 2015
ferable across the spectrum of
evidence-based practice.
Beyond “P”: The Search
for Importance
In effectiveness research, the P value
has long been a critical determinant
of whether a treatment is thought to
work. We contend that the P value
has been a significant barrier to
efforts to establish which treatments
are truly effective and, therefore,
worthwhile. There has been an
implicit acceptance among researchers, and users of evidence, that statistical significance represents clinical effectiveness. Unfortunately, this
position suffers from substantial conceptual flaws.2,3 It is possible for a
treatment effect to be statistically significant and clinically meaningless.
Conversely, although perhaps less
commonly in the field of pain
research, a treatment might provide
important benefits to patients but be
unjustly ignored because it does not
cross this arbitrary statistical
threshold.
Recently, overreliance on the P value
to determine treatment effectiveness
has come under further scrutiny.4
Although it is commonly held that a
P value of ⬍.05 suggests a type I
error rate of less than 5%, the actual
false discovery rate is dependent on
the prior probability of a treatment
having an effect.4 For example, if we
assume that just 10% of the various
interventions that we test might provide a real treatment effect, an alpha
level of ⬍.05 would actually translate to a false discovery rate of 36%
rather than the nominal 5% (for a
review of this concept, see
Colquhoun4). This finding is particu-
larly pertinent for chronic pain trials
where we recruit participants who
have proven refractory to interventions, and hence the prior probability of intervention success is likely to
be low. Aside from this problem,
inappropriate, or perhaps innovative, statistical analyses can yield
supportive-looking P values.5
When assessing the effectiveness of
a treatment, the size, precision, and
subsequent clinical importance of
the treatment’s effects are of greater
importance than whether the apparent effect could have occurred by
chance. Most patients with chronic
pain want a cure for their pain,6 and
treatments are routinely promoted
and marketed as delivering large benefits quickly. Unfortunately, the
prospect of such an outcome
remains very unlikely. So the question shifts to one of how much
improvement would be needed to be
meaningful to a patient. This minimal clinically important difference
(MCID)7 or smallest worthwhile
effect (SWE)8 should represent the
minimum treatment effect with
which patients would be satisfied.
Recognizing this metric is a step forward, it allows us to classify a treatment as imparting enough of an
effect to be of value in the real
world.
What exactly constitutes an MCID,
or an SWE, on any given outcome measure remains contentious,
although various methodological
approaches are being applied to the
problem (for a review with regard
to back pain, see Ferreira et al8).
Remarkably, it seems that many of
these approaches do not actively
Volume 95
Number 8
Physical Therapy f
1087
ProfessionWatch: Interpreting Evidence in Pain
consider the patient’s perspective.8
It is likely that what a patient would
be satisfied with might differ
substantially between individuals,
patient groups, interventions,9 the
point in the care pathway at which
the patient arrives, and a range of
other possible factors. In addition,
people almost certainly have variable
thresholds of what level of risk,
inconvenience, or cost associated
with the intervention they would
consider to be prohibitive—an issue
that, to our knowledge, has received
very little attention. This variability—and the requirement that any
potential benefit of an intervention
must be weighed against its potential
harms (including cost and inconvenience)—suggests that the construct
of a generic MCID for chronic pain
interventions is problematic.
Initiative on Methods,
Measurement, and Pain
Assessment in Clinical Trials
The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) has offered
some provisional benchmarks for
important change in chronic pain.
These benchmarks are based on
studies that compared pain scores
with global impression of change in
patients with neuropathic pain,10
arthropathies,11 and pain following
spinal cord injury or amputation.12
According to the IMMPACT, a 30%
reduction in pain in an individual
patient represents the lower threshold for considering an effect to be
moderately clinically important,
and a 50% reduction represents a
substantially clinically important
change.13 There are obvious problems with applying cutoffs arbitrarily
and across-the-board. For example, it
does not seem reasonable to assume
that we might require the same
degree of change when agreeing to
receive a short educational booklet
as we might when agreeing to
undergo an invasive surgical proce-
1088
f
Physical Therapy
Volume 95
dure. These cutoffs also are sensitive
to baseline levels of symptoms. A
30% improvement in a severe intractable pain is probably quite a different proposition from a 30% change
in a mildly bothersome ache or
twinge.
Rather than focusing on the SWE,
a number of studies have used the
Patient-Centered Outcomes Questionnaire (PCOS) to investigate the
threshold of symptom improvement
required for people with chronic
pain to consider treatment successful.14 –16 These studies suggest that
around 54% to 58% improvement in
pain intensity and 63% to 68%
improvement in pain interference
are required for treatment success.
However, as with the SWE, we might
expect judgments of success to be
specific to the intervention and
other contextual factors. Zeppieri
et al16 investigated participants
about to start physical therapy,
whereas Robinson et al14 and
O’Brien et al15 sampled patients from
pain clinics and a rheumatology
department, respectively, with no
intervention specifically identified.
Thus, although estimates suggest
that large changes may be necessary,
it is not appropriate to assume that
these estimates should apply across
all interventions.
The Elusive “Average”
Patient and the
Elusive “Responder”
The IMMPACT benchmarks and the
thresholds derived from them reflect
within-patient change from baseline.
This is an appealing concept because
it has a real-world resonance, being
the amount of change experienced
by an individual undergoing the
intervention of interest. Unfortunately, within-patient change from
baseline provides a poor measure of
the effects of the intervention
because it includes the influences of
natural recovery, statistical regres-
Number 8
sion, and the nonspecific effects
associated with clinical contact,
including but not limited to “placebo
effects”17 (see Moseley,18 however,
for an alternative understanding of
placebo). Within-patient change in
outcome might tell us how much an
individual’s condition improved, but
it does not tell us how much of
this improvement was due to treatment. In most common randomized
trial designs, the only value that can
help us estimate the actual effect of
the intervention is the average
between-group difference after treatment.19 It is only recently that this
important principle has been applied
to MCID or SWE research.
Ferreira et al9 used the benefitharm trade-off method to try and
determine the SWE for physical therapy in people with chronic low back
pain based on intervention-control
between-group comparison, attempting to capture change due to treatment, not simply change over time.
Participants were informed that their
pain and disability are likely to
improve 30% without intervention
and were asked to estimate how
much
additional
improvement
would be needed to make the intervention worthwhile. The results of
this study suggest that, on average,
people with chronic low back pain
would need to experience an additional 20% improvement in pain and
disability compared with no treatment to perceive that the effect of
physical therapy was worthwhile,
that is, an overall 50% change.
There are limitations inherent in
interpreting the average effects of
interventions in clinical trials. The
question arises of who, if anyone,
experiences the average treatment
effect. It has been argued that, in the
world of pharmaceutical trials for
chronic pain, the response pattern is
often bimodally distributed.20 –22 Simply put, some patients do very well
August 2015
with the intervention, some have
minimal to no effects, and very few
experience intermediate (moderate)
effects. In this instance, the average
effect might be the effect that the
fewest participants actually demonstrate.20 The commonly proposed
solution to this problem is to conduct a “responder analysis,” which
compares the proportion achieving a
clinically important improvement
from baseline in the treatment
and control groups. It has been proposed that this type of analysis better
quantifies individual participant
responses to treatment20 and that it
enables the calculation of easily
interpreted measures such as the
number needed to treat (NNT). The
NNT is the number of people we
would need to treat with the intervention instead of the control condition for one more participant to
achieve the outcome of interest
(often a predefined MCID).
This approach also has important
limitations. The term “responder
analysis” is a misnomer and is frequently misunderstood.23 In this
type of analysis, “responders” are
identified by within-person change
from baseline. For many participants
in each group, we are not really measuring treatment “response,” we are
measuring “good outcome,” which,
as mentioned above, might be due to
natural recovery, nonspecific treatment effects, and regression to the
mean, as well as (or instead of) the
effects of the intervention. Also, it is
possible that some individuals who
responded strongly to the intervention might not be counted as
responders. If the natural history of
individuals during the treatment
period would have been significant
worsening, yet with treatment their
condition remains stable, they
will be counted as nonresponders
despite receiving significant benefit
from the intervention. So, even
though the between-group differ-
August 2015
ence in the proportion of participants who experience a good outcome reflects the net increase in
the proportion of patients who
responded during the treatment
period, it does not get any closer to
telling us about the effects of intervention on individual people.
Methods for distinguishing true
responders
from
those
who
improved regardless of the treatment
have their own substantial difficulties.24 Responder analysis for a subjective outcome measured on a continuous scale (eg, pain severity) may
be sensitive to the cutoffs used to
define clinical importance, and these
cutoffs are often arbitrary. Moreover,
because the outcome is measured
imperfectly and responders may be
frequently misclassified, responder
analyses might underestimate true
effects.25 This approach also potentially introduces the problem of only
detecting positive change, not negative change. That is, all “nonresponders” are considered equal. In
reality, the response within this
group might vary from mild improvement to severe deterioration. Finally,
the dichotomization of outcomes in
responder analyses greatly reduces
the precision of estimates of effect.
Although the use of responder analysis is growing, currently such data
remain scarce, particularly for nonpharmacological interventions.26 A
good case for responder analyses in
rehabilitation trials has not been
clearly established. The observation
that patterns of outcome may be
bimodal for some specific interventions is not evidence that they are
necessarily bimodal for others. More
importantly, evidence of bimodal
outcomes is not evidence of bimodal
treatment effects. The belief that
responder analysis will demonstrate
treatment effects on individuals that
are not apparent in other analyses
may be unfounded. Data from drug
trials in chronic pain, where such
analyses are more common, rarely
show NNTs below 6.20
Do Clinical Trials
Underestimate
Effectiveness?
It is commonly argued that clinical
trials are not fit for the purpose
of evaluating physical interventions
because they fail to capture the true
effects of physical therapy treatments. Such arguments seem common at physical therapy conferences, particularly from therapists
who find the disappointing results
from clinical trials to be at odds with
their clinical experience. The most
common criticisms are that treatments are inadequately targeted in
clinical trials because they are shoehorned into a one-size-fits-all
approach; therapies in clinical trials
differ from real-world therapy,
which is complex, tailored, and
often multimodal, and the effects of
treatment are diluted by the application of single interventions to a complex, heterogeneous group with
diverse treatment needs. These criticisms are certainly justified in some,
but not all, trials. In the field of
chronic pain, additional difficulties
are presented in establishing meaningful diagnoses. Existing diagnostic
labels (eg, chronic nonspecific low
back pain, complex regional pain
syndrome, fibromyalgia) often identify heterogeneous cohorts of people
who share similar symptom profiles
but not necessarily similar disease
mechanisms.
The one-size-fits-all criticism is arguably an unfair characterization of
many modern therapy trials. Indeed,
in recent years, many, if not most,
trials allowed therapists some discretion to tailor their approach to the
individual, usually within a specific
theoretical framework and often in a
way that closely modeled existing
clinical practices. For example, in
Volume 95
Number 8
Physical Therapy f
1089
the manipulation arm of the UK
back pain exercise and manipulation
trial,27 therapists were free to deliver
a range of soft tissue, joint, and neural manual therapy techniques. In
addition, therapists could prescribe
various exercises for the spine and
hip, provide education on activity
and return to work, and address simple psychological issues.28 In the
recent PROMISE trial of exercise for
chronic whiplash,29 therapists were
able to tailor multimodal exercise,
manual therapy, and cognitivebehavioral techniques to the individual patient. Furthermore, in the
SWIFT trial, participants randomized
to the physical therapy arm received
a combination of individualized education or advice, exercise therapy,
and manipulative therapy at the discretion of the treating physical therapist based on usual practice.30
Currently, there are no firmly established robust and widely accepted
models for subgrouping patients
with chronic pain to facilitate better
targeting of treatment. Efforts at subgrouping have largely returned
mixed outcomes.31 Much of this
work has focused on the management of low back pain, both acute
and chronic, for which numerous
approaches to subgrouping have
been developed and tested. The picture that emerges is one in which
positive trials32,33 tend to demonstrate small, positive effects on primary outcomes, although these trials
often fail to be replicated34 –37 or are
currently awaiting independent replication.38 Subgrouping algorithms
are frequently based on retrospective analysis of trial data rather than
on prospective tests of predictions
based on theoretical frameworks or
biological mechanisms. Moreover,
some subgroup analyses have been
shown to be dependent on the cutoff points used to determine MCID,39
and many subgroup analyses conducted within trials have been
1090
f
Physical Therapy
Volume 95
severely underpowered and poorly
reported.40 Better tailoring or subgrouping of cohorts to treatments
may still improve outcomes, but so
far the promise of subgrouping
remains largely unfulfilled.
A further assertion is that the true
effects of an intervention are lost in
the cacophony of competing realworld variables, including social and
psychological factors, competing
therapies, adherence, and participation. This assertion maintains that
the signal of effective treatment cannot always be detected in the presence of noise. Again, there may be
some truth in this assertion, but the
best way around it is to conduct
large trials that can provide precise
estimates of average treatment
effects. Therein lies the challenge
facing all health interventions: to
demonstrate clear benefit in the
chaos of the real world. The “noise”
may be particularly loud in chronic
pain, but we should recognize that,
in both clinical practice and
research, interventions cannot be
provided in the clinical equivalent of
a soundproofed room.
Recently, specifically in the case of
cognitive-behavioral therapy interventions, Morley41 argued for greater
integration of “practice-based evidence,” in which data generated
from routine clinical practice is
afforded greater importance. In this
approach, clinical outcome data are
compared to “benchmark” effect
sizes generated from the treatment
and control arms of clinical trials.
This comparison allows a degree of
control over the effects of natural
history and nonspecific effects of
treatment, although it does not offer
the high level of control offered by
randomization. One possible risk
associated with this approach is that
where effect sizes are sufficiently
low, it may encourage the celebration of possibly dubious successes.
Number 8
As such, it seems best suited to demonstrating “proof of concept” of new
hypotheses regarding treatment
innovation for subsequent testing in
RCTs.
Exaggeration,
Misreporting, and Spin
It also is worth considering the alternative possibility that clinical trials
might generate exaggerated estimates of effectiveness. In the context of clinical trials for physical
interventions, treatments are often
provided by more experienced clinicians, patients are given more time,
and greater steps are taken to ensure
treatment adherence than would be
the case in routine clinical practice,
potentially offering a more effective
package of care than might be realized in routine clinical practice.
More importantly, the observed
effectiveness of a treatment is represented by the true effect of treatment plus the effect of biases that
also can positively influence outcome. These biases are often suboptimally controlled in clinical trials
so the observed effect represents
both the effectiveness of the intervention and bias. Many readers will
be familiar with the conventional
risk of bias criteria by which trials
are assessed in systematic reviews.
Meta-epidemiological
evidence
shows that these criteria are associated with treatment effect sizes, particularly for subjective outcome measures such as pain.42,43 Blinding of
patients and care providers is often
not achieved in trials of physical or
psychological treatments,44 and it is
notable that trials of physical interventions commonly fall short on a
number of other criteria. Although
quality is improving,45 it is likely that
the effect sizes reported in most clinical trials represent more than just
the effects of treatment on patient
outcomes.
August 2015
In clinical trials, size matters; small
studies increase the risk of false negatives by virtue of their low statistical
power, but in clinical trials, they
tend to also result in false positives
and inflated effect sizes.46 – 48 There
are a number of possible reasons for
this phenomenon: small studies may
include more homogeneous clinical
groups for which effects are more
consistent,49 and it is easier to
deliver high-quality interventions in
smaller trials.49 Small trials also are
often more loosely controlled and of
lower methodological quality. Negative small studies have a tendency
not to be published, rendering the
available sample of published small
trials unrepresentatively positive.
Large and significant effects arising
from small, underpowered studies
are at higher risk of being false positives than if they arose from large,
well-powered studies.50 The benefits
of meta-analysis do little to correct
this problem— even where a pooled
estimate includes a large number of
participants, it may be prone to small
study bias if it is dominated by small
studies.
Managing loss to follow-up of participants and protocol violation during
trials is difficult. Traditionally, we
look for an intention-to-treat analysis,
in which all participants are analyzed
by the treatment to which they were
allocated, regardless of what follows
that allocation. Currently, the application and reporting of intention-totreat analyses in analgesic trials are
inconsistent,51 reflecting a common
risk of bias in this field. Common
methods for dealing with missing
data themselves introduce bias. Evidence from drug trials in chronic
pain suggests that the commonly
used “last observation carried forward” approach to imputing data
inflates effect sizes.52 This is often an
issue with adverse event withdrawal,
where the last observation precedes
the adverse event, but also might
August 2015
hold true for other reasons for withdrawal—withdrawal may be associated with worsening symptoms or a
realization that the treatment is not
really helping, both of which may
occur after the last formal observation. New methods for analyzing
clinical trials, particularly multiple
imputation, may improve estimates
of effect in the presence of substantial loss to follow-up,53 although further data are needed to formally evaluate this perspective.
Beyond these threats related to
methodology are challenges to the
balanced conduct and communication of trials. Selective outcome
reporting is considered as a risk of
bias in many assessment tools and
involves the selective presentation of
results that are more positive or statistically significant, as well as the
withholding on negative or nonsignificant results.54 This selective
reporting can be achieved through
poor practices such as deviating
from the trial protocol by switching
the primary outcomes in light of the
trial results. A recent review of analgesic trials55 compared records in
international trials registers with the
final published study reports and
showed discrepancies between the
primary outcomes in 79% of the
available data, with 30% of trials containing what were defined as “unambiguous” discrepancies, where a registered primary outcome was either
not reported in the published trials
or was demoted to a secondary outcome. A similar review of acupuncture trials56 showed inconsistency in
the primary outcomes in 45% of
available trials, of which 71% had a
discrepancy that favored a statistically significant “positive” result on
the primary outcome.
There is also evidence of a strong
positivity bias in the interpretation
and presentation of results from clinical trials. Boutron et al57 found evi-
dence of “spin”—presenting an
experimental treatment as beneficial—in 40% of statistically negative
trials. In rheumatology trials,
Mathieu et al58 found that 23% of the
trials had conclusions that were misleading and that the only predictor of
misleading conclusions was a statistically negative result. This pattern
also is apparent in the analgesic trial
literature. Worryingly, some type of
positive spin was identified in at least
one part of the abstract of 61% of
analgesic trials with statistically nonsignificant results in their primary
analysis, most commonly the placing
of undue emphasis on statistically
significant results from secondary
analyses.59 It seems that beyond the
difficulty of getting negative results
published, researchers do not like to
accept negative results in the first
place. Perhaps this attitude is partially motivated by the “publish or
perish” culture of modern research.
Notwithstanding that, it clearly represents a failure of the scientific process in which there is a bias toward
one possible answer to the research
question. For consumers of research
articles, the message is that simply
looking to the abstract or conclusions of a trial for the truth carries
risk—an issue we have touched on
previously.60
Pursue Success,
Expect Failure?
Looking across the Cochrane Library
at reviews of common interventions
for chronic pain, and being somewhat selective by avoiding interventions where the evidence suggests
no effect at all, reveals that most
“effective” therapies appear to provide only very small, short-term
effects on pain or other important
patient-centered outcomes such as
function, distress, and quality of life.
We must bear in mind that, particularly for complex interventions, the
meta-analyses that produce these
estimates contain multiple sources
Volume 95
Number 8
Physical Therapy f
1091
of clinical heterogeneity that have
the potential to influence effect size;
they combine interventions that are
often quite different in terms of content and dose61; the quality of the
intervention is often hard to determine, although of great potential
importance49; the theories underpinning the interventions often vary significantly among studies or are not
clearly established62; the contextual
equivalence of the control group
interventions is variable63; and
adherence levels vary, and patients
are drawn from diverse sources. But
accepting these limitations, we suggest that, when we do not currently
have robust means of identifying a
priori those patients who might
respond to treatment, it is the average between-group effects that represent our best estimate of the
intervention-specific benefit for any
individual.
our field) and rigorous evidence of
effectiveness.64
Reviewing this evidence can leave
one with a somewhat negative
impression. We acknowledge that
there is a danger here—that such
focused attention on rigor and bias
can appear hypercritical and unduly
negative and take away whatever
desire clinicians and patients may
have had to negotiate the evidence
maze. That, however, is our challenge: to be dispassionate, recognize
bias, and make balanced appraisals
of the strength and direction of the
evidence, and that must in the end
be a positive step. In the words of
the physicist Richard Feynman, “For
a successful technology, reality must
take precedence over public relations, for Nature cannot be fooled.”65
For drug therapies, treatment
response, when it comes, is usually
rapid. Moore and colleagues20 recommend that when we introduce a
new therapy, we should expect failure, be alert to a lack of treatment
response, and switch quickly to
another agent if outcomes are
poor. Such an approach might maximize the chance of finding an effective option as quickly as possible
while minimizing the risks of adverse
events from drugs that confer no
individual benefit, although it makes
the potentially tenuous assumption
that, without intervention, the
patient’s symptoms would not have
changed substantially.
These issues are not unique to the
field of chronic pain research—many
of them apply across the range of
clinical disciplines. This applicability
is important because there are
examples from other clinical fields of
the development and validation of
clearly successful interventions,
investigated by high-quality clinical
trials and systematic reviews. Such
compelling evidence of effectiveness
from other, comparably complex
fields, offers genuine hope for our
own field. For example, we can
now be confident that stress urinary
incontinence can be prevented and
treated with pelvic-floor muscle
training66 and the risk of falling in
the elderly population can be
decreased with exercise programs.67
Could this approach be applied to
nonpharmacological interventions?
We think so, but to avoid pushing
patients through a mill of ineffective
therapies, we also think that we
should limit the potential options to
interventions that possess at least
biological plausibility (a foundation
stone that can be difficult to find in
We should reflect that, in chronic
pain treatment and research, we all
have some sort of vested interest.68 If
we offer assessments of the evidence
for our treatments without due diligence regarding bias and limitations,
we will not serve our patients well.
Our patients may be given a choice
but not the choice they need. By its
1092
f
Physical Therapy
Volume 95
Number 8
very nature, clinical research should
threaten current practice. Acknowledging what does not work, as well
as what does (and by how much), is
of great value and will force us to
innovate. In fair tests,69 if our treatments achieve their goals meaningfully and consistently, the effect sizes
will reflect that truth. An appreciation of how to interpret evidence of
effectiveness is a critical skill not
only for those engaged with research
but also for those who want to use it
in clinical practice.
Altering the natural course of any
clinical condition is a difficult and
complex challenge. In the words of
epidemiologist Archie Cochrane,
after whom the Cochrane Collaboration is named: “[O]ne should. . .be
delightfully surprised when any
treatment at all is effective, and
always assume that a treatment is
ineffective unless there is evidence
to the contrary.”70 This statement
has genuine resonance in chronic
pain, in which we set ourselves the
substantial challenge of changing
symptoms in a group defined by the
fact that those symptoms have so far
proven unchangeable. We suggest
that we should always have that perspective in mind, while remaining
ready to be delightfully surprised.
N.E. O’Connell, PhD, Health Economics
Research Group, Institute for the Environment Health and Societies, Department of
Clinical Sciences, Brunel University London,
Kingston Lane, Uxbridge, UB8 3PH United
Kingdom. Address all correspondence to
Dr O’Connell at: neil.oconnell@brunel.
ac.uk.
G.L. Moseley, PhD, Sansom Institute for
Health Research, University of South Australia, Adelaide, Australia, and Neuroscience
Research Australia, Randwick, Australia.
J.H. McAuley, PhD, Neuroscience Research
Australia.
B.M. Wand, PhD, School of Physiotherapy,
The University of Notre Dame Australia,
Fremantle, Australia.
August 2015
R.D. Herbert, PhD, Neuroscience Research
Australia.
[O’Connell NE, Moseley GL, McAuley JH,
et al. Interpreting effectiveness evidence in
pain: short tour of contemporary issues. Phys
Ther. 2015;95:1087–1094.]
© 2015 American Physical Therapy Association
Published Ahead of Print:
April 30, 2015
Accepted: April 19, 2015
Submitted: October 24, 2014
Dr O’Connell, Dr Moseley, Dr McAuley, and
Dr Wand provided concept/idea/project
design. All authors provided writing.
Dr Moseley and Dr Herbert are supported by
the National Health and Medical Research
Council of Australia.
DOI: 10.2522/ptj.20140480
References
1 Gartlehner G, Hansen RA, Nissman D,
et al. Criteria for Distinguishing Effectiveness From Efficacy Trials in Systematic Reviews. Rockville, MD: Agency for
Healthcare Research and Quality; 2006.
Technical Reviews 12, Report 06-0046.
2 Gardner MJ, Altman DG. Confidence intervals rather than P values: estimation rather
than hypothesis testing. Br Med J (Clin
Res Ed). 1986;292:746 –750.
3 Kline RB. Beyond Significance Testing:
Reforming Data Analysis Methods in
Behavioral Research. Washington, DC:
American Psychological Association;
2004.
4 Colquhoun D. An investigation of the false
discovery rate and the misinterpretation of
P values. Royal Soc Open Sci. 2014;1:
140216.
5 Simonsohn U, Nelson LD, Simmons JP.
P-curve: a key to the file-drawer. J Exp
Psychol Gen. 2014;143:534 –547.
6 Hush JM, Refshauge K, Sullivan G, et al.
Recovery: what does this mean to patients
with low back pain? Arthritis Rheum.
2009;61:124 –131.
7 Jaeschke R, Singer J, Guyatt GH. Measurement of health status: ascertaining the
minimal clinically important difference.
Control Clin Trials. 1989;10:407– 415.
8 Ferreira ML, Herbert RD, Ferreira PH, et al.
A critical review of methods used to determine the smallest worthwhile effect of
interventions for low back pain. J Clin Epidemiol. 2012;65:253–261.
9 Ferreira ML, Herbert RD, Ferreira PH, et al.
The smallest worthwhile effect of nonsteroidal anti-inflammatory drugs and
physiotherapy for chronic low back pain:
a benefit-harm trade-off study. J Clin Epidemiol. 2013;66:1397–1404.
August 2015
10 Farrar JT, Young JP Jr, LaMoreaux L, et al.
Clinical importance of changes in chronic
pain intensity measured on an 11-point
numerical pain rating scale. Pain. 2001;
94:149 –158.
26 Henschke N, Van Enst A, Froud R, Ostelo
R. Responder analyses in randomised controlled trials for chronic low back pain: an
overview of currently used methods. Eur
Spine J. 2014;23:772–778.
11 Salaffi F, Stancati A, Silvestri CA, et al. Minimal clinically important changes in
chronic musculoskeletal pain intensity
measured on a numerical rating scale. Eur
J Pain. 2004;283–291.
27 UK BEAM Trial Team. United Kingdom
back pain exercise and manipulation (UK
BEAM) randomised trial: effectiveness of
physical treatments for back pain in primary care. BMJ. 2004;329:1377.
12 Hanley MA, Jensen MP, Ehde DM, et al.
Clinically significant change in pain intensity ratings in persons with spinal cord
injury or amputation. Clin J Pain. 2006;
22:25–31.
28 Harvey E, Burton AK, Moffett JK, et al. Spinal manipulation for low-back pain: a treatment package agreed to by the UK chiropractic, osteopathy and physiotherapy
professional associations. Man Ther. 2003;
8:46 –51.
13 Dworkin RH, Turk DC, Wyrwich KW,
et al. Interpreting the clinical importance
of treatment outcomes in chronic pain
clinical trials: IMMPACT recommendations. J Pain. 2008;9:105–121.
14 Robinson ME, Brown JL, George SZ, et al.
Multidimensional success criteria and
expectations for treatment of chronic
pain: the patient perspective. Pain Med.
2005;6:336 –345.
15 O’Brien EM, Staud RM, Hassinger AD, et al.
Patient-centered perspective on treatment
outcomes in chronic pain. Pain Med.
2010;11:6 –15.
16 Zeppieri G Jr, Lentz TA, Atchison JW, et al.
Preliminary results of patient-defined success criteria for individuals with musculoskeletal pain in outpatient physical therapy settings. Arch Phys Med Rehabil.
2012;93:434 – 440.
17 Herbert RD, Jamtvedt G, Mead J, Hagen
KB. Outcome measures measure outcomes, not effects of intervention. Aust J
Physiother. 2005;51:3– 4.
18 Moseley GL. Placebo effect: reconceptualising placebo. BMJ. 2008;336:1086.
19 Rubin DB Estimating causal effects of treatments in randomized and nonrandomized
studies. J Educ Psychol. 1974;66:688 –701.
20 Moore A, Derry S, Eccleston C, Kalso E.
Expect analgesic failure; pursue analgesic
success. BMJ. 2013;346:f2690.
21 Moore RA, Derry S, Simon LS, Emery P.
Nonsteroidal anti-inflammatory drugs, gastroprotection, and benefit-risk. Pain
Pract. 2014;14:378 –395.
22 Moore RA, Cai N, Skljarevski V, Tölle TR.
Duloxetine use in chronic painful conditions: individual patient data responder
analysis. Eur J Pain. 2014;18:67–75.
23 Senn S. Individual therapy: new dawn or
false dawn. Drug Inf J. 2001;35:1479 –
1494.
24 Jafari N, Hearne J, Churilov L Why caution
is recommended with post-hoc individual
patient matching for estimation of treatment effect in parallel-group randomized
controlled trials: the case of acute stroke
trials. Stat Med. 2013;32:4467– 4481.
25 Marschner IC, Emberson J, Irwig L, Walter
SD. The number needed to treat (NNT)
can be adjusted for bias when the outcome is measured with error. J Clin Epidemiol. 2004;57:1244 –1252.
29 Michaleff ZA, Maher CG, Lin CW, et al.
Comprehensive physiotherapy exercise
programme or advice for chronic whiplash (PROMISE): a pragmatic randomised
controlled trial. Lancet. 2014;384:133–
141.
30 Hurley DA, Tully MA, Lonsdale C, et al.
Supervised walking in comparison with fitness training for chronic back pain in
physiotherapy: results of the SWIFT singleblinded randomized controlled trial
(ISRCTN17592092). Pain. 2015;156:131–
147.
31 Kamper SJ, Maher CG, Hancock MJ, et al.
Treatment-based subgroups of low back
pain: a guide to appraisal of research studies and a summary of current evidence.
Best Pract Res Clin Rheumatol. 2010;24:
181–191.
32 Hill JC, Whitehurst DG, Lewis M, et al.
Comparison of stratified primary care
management for low back pain with current best practice (STarT Back): a randomised controlled trial. Lancet. 2011;
378:1560 –1571.
33 Fritz JM, Delitto A, Erhard RE. Comparison
of classification-based physical therapy
with therapy based on clinical practice
guidelines for patients with acute low
back pain: a randomized clinical trial.
Spine (Phila Pa 1976). 2003;28:1363–
1367.
34 Hancock MJ, Maher CG, Latimer J, et al.
Independent evaluation of a clinical prediction rule for spinal manipulative therapy: a randomised controlled trial. Eur
Spine J. 2008;17:936 –943.
35 Apeldoorn AT, Ostelo RW, van Helvoirt H,
et al. A randomized controlled trial on the
effectiveness of a classification-based system for subacute and chronic low back
pain. Spine (Phila Pa 1976). 2012;37:
1347–1356.
36 Henry SM, Van Dillen LR, OuelletteMorton RH, et al. Outcomes are not different for patient-matched versus nonmatched treatment in subjects with
chronic recurrent low back pain: a randomized clinical trial. Spine J. 2014;14:
2799 –2810.
37 Dougherty PE, Karuza J, Savino D, Katz P.
Evaluation of a modified clinical prediction rule for use with spinal manipulative
therapy in patients with chronic low back
pain: a randomized clinical trial. Chiropr
Man Therap. 2014;22:41.
Volume 95
Number 8
Physical Therapy f
1093
38 Vibe Fersum K, O’Sullivan P, Skouen JS,
et al. Efficacy of classification-based cognitive functional therapy in patients with
non-specific chronic low back pain: a randomized controlled trial. Eur J Pain. 2013;
17:916 –928.
39 Schwind J, Learman K, O’Halloran B, et al.
Different minimally important clinical difference (MCID) scores lead to different
clinical prediction rules for the Oswestry
Disability Index for the same sample of
patients. J Man Manip Ther. 2013;21:71–
78.
40 Mistry D, Patel S, Hee SW, et al. Evaluating
the quality of subgroup analyses in randomized controlled trials of therapistdelivered interventions for nonspecific
low back pain: a systematic review. Spine
(Phila Pa 1976). 2014;39:618 – 629.
41 Morley S. Efficacy and effectiveness of cognitive behaviour therapy for chronic pain:
progress and some challenges. Pain. 2011;
152(3 suppl):S99 –S106.
42 Wood L, Egger M, Gluud LL, et al. Empirical evidence of bias in treatment
effect estimates in controlled trials with
different interventions and outcomes:
meta-epidemiological study. BMJ. 2008;
336:601– 605.
43 Savović J, Jones H, Altman D, et al. Influence of reported study design characteristics on intervention effect estimates from
randomised controlled trials: combined
analysis of meta-epidemiological studies.
Health Technol Assess. 2012;16:1– 82.
44 Mathieu E, Herbert RD, McGeechan K,
et al. A theoretical analysis showed that
blinding cannot eliminate potential for
bias associated with beliefs about allocation in randomised clinical trials. J Clin
Epidemiol. 2014;67:667– 671.
45 Moseley AM, Elkins MR, Janer-Duncan L,
Hush JM. The quality of reports of randomized controlled trials varies between subdisciplines of physiotherapy. Physiother
Can. 2014;66:36 – 43.
46 Moore RA, Gavaghan D, Trame MR, et al.
Size is everything: large amounts of information are needed to overcome random
effects in estimating direction and magnitude of treatment effects. Pain. 1998;78:
209 –216.
47 Nuesch E, Trelle S, Reichenbach S, et al.
Small study effects in meta-analyses of
osteoarthritis trials: meta-epidemiological
study. BMJ. 2010;341:c3515– c3515.
48 Dechartres A, Trinquart L, Boutron I,
Ravaud P. Influence of trial sample size on
treatment
effect
estimates:
metaepidemiological study. BMJ. 2013;346:
f2304.
49 Herbert RD, Bø K. Analysis of quality of
interventions in systematic reviews. BMJ.
2005;331:507–509.
1094
f
Physical Therapy
Volume 95
50 Button KS, Ioannidis JP, Mokrysz C, et al.
Power failure: why small sample size
undermines the reliability of neuroscience
[erratum in: Nat Rev Neurosci. 2013;14:
451]. Nat Rev Neurosci. 2013;14:365–
376.
51 Gewandter JS, McDermott MP, McKeown
A, et al. Reporting of intention-to-treat
analyses in recent analgesic clinical trials:
ACTTION systematic review and recommendations. Pain. 2014;155:2714 –2719.
52 Moore RA, Straube S, Eccleston C, et al.
Estimate at your peril: imputation methods
for patient withdrawal can bias efficacy
outcomes in chronic pain trials using
responder analyses. Pain. 2012;153:265–
268.
53 Sterne JA, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential
and pitfalls. BMJ. 2009;338:b2393.
54 Higgins JP, Altman DG, Sterne JA, eds.
Assessing risk of bias in included studies.
In: Higgins JP, Green S, eds. Cochrane
Handbook for Systematic Reviews of
Interventions. Version 5.1.0. Updated
March 2011. Available at: http://www.
cochrane-handbook.org. Accessed March
29, 2015.
55 Smith SM, Wang AT, Pereira A, et al. Discrepancies between registered and published primary outcome specifications in
analgesic trials: ACTTION systematic
review and recommendations. Pain.
2013;154:2769 –2774.
56 Su CX, Han M, Ren J, et al. Empirical evidence for outcome reporting bias in randomized clinical trials of acupuncture:
comparison of registered records and subsequent publications. Trials. 2015;16:28.
57 Boutron I, Dutton S, Ravaud P, Altman DG.
Reporting and interpretation of randomized controlled trials with statistically nonsignificant results for primary outcomes.
JAMA. 2010;303:2058 –2064.
58 Mathieu S, Giraudeau B, Soubrier M,
Ravaud P. Misleading abstract conclusions
in randomized controlled trials in rheumatology: comparison of the abstract conclusions and the results section. Joint Bone
Spine. 2012;79:262–267.
59 Gewandter JS, McKeown A, McDermott
MP, et al. Data interpretation in analgesic
clinical trials with statistically nonsignificant primary analyses: an ACTTION systematic review. J Pain. 2015;16:3–10.
60 Harvie D, O’Connell N, Moseley L. Dry
needling for myofascial pain: does the evidence make the grade? 2014. Available at:
http://www.bodyinmind.org/dry-needlingmyofascial. Accessed March 29, 2015.
Number 8
61 Waterschoot FP, Dijkstra PU, Hollak N,
et al. Dose or content; effectiveness of
pain rehabilitation programs for patients
with chronic low back pain: a systematic
review. Pain. 2014;155:179 –189.
62 Williams AC, Eccleston C, Morley S. Psychological therapies for the management
of chronic pain (excluding headache) in
adults. Cochrane Database Syst Rev.
2012;11:CD007407.
63 Bishop FL, Fenge-Davies AL, Kirby S, Geraghty AW. Context effects and behaviour
change techniques in randomised trials: a
systematic review using the example of
trials to increase adherence to physical
activity in musculoskeletal pain. Psychol
Health. 2015;30:104 –121.
64 Bø K, Herbert R. When and how should
new therapies become routine clinical
practice? Physiotherapy. 2009;95:51–57.
65 Feynman R. Appendix F: personal observations on the reliability of the Shuttle.
Kennedy Space Center, FL: NASA; 1986.
Available
at:
http://science.ksc.nasa.
gov/shuttle/missions/51-l/docs/rogerscommission/Appendix-F.txt. Accessed
May 13, 2015.
66 Dumoulin C, Hay-Smith EJ, Mac HabéeSéguin G. Pelvic floor muscle training versus no treatment, or inactive control treatments, for urinary incontinence in
women. Cochrane Database Syst Rev.
2014;5:CD005654.
67 Gillespie LD, Robertson MC, Gillespie WJ,
et al. Interventions for preventing falls in
older people living in the community.
Cochrane Database Syst Rev. 2012;9:
CD007146.
68 Moseley L. Finding the love between
scientists and clinicians: a response
to Dr Butler on noijam. Published February 4, 2013. Available at: http://
www.bodyinmind.org/finding-the-lovebetween-scientists-and-clinicians-aresponse-to-dr-butler-on-noijam/. Accessed March 29, 2015.
69 Evans I, Thornton H, Chalmers I, Glasziou
P. Testing Treatments: Better Research for
Better Healthcare. 2nd ed. London,
United Kingdom: Pinter and Martin; 2011.
Available at: http://www.testingtreatments.
org/wp-content/uploads/2012/09/TT_
2ndEd_English_17oct2011.pdf. Accessed
March 29, 2015.
70 Cochrane AL. Effectiveness and efficiency:
random reflections on health services.
Published June 1, 1972. Reprinted 1999.
Available at: http://www.nuffieldtrust.org.
uk/publications/effectiveness-and-efficiencyrandom-reflections-health-services. Accessed March 29, 2015.
August 2015
Research Report
What Works to Prevent Falls in
Community-Dwelling Older Adults?
Umbrella Review of Meta-analyses of
Randomized Controlled Trials
Brendon Stubbs, Simone Brefka, Michael D. Denkinger
Background. Preventing falls is an international priority. There is a need to
synthesize the highest-quality falls prevention evidence in one place for clinicians.
Purpose. The aim of this study was to conduct an umbrella review of metaanalyses of randomized controlled trials (RCTs) of falls prevention interventions in
community-dwelling older adults.
Data Sources. The MEDLINE, EMBASE, CINAHL, AMED, BNI, PsycINFO,
Cochrane Library, PubMed, and PEDro databases were searched.
Study Selection. Meta-analyses with one pooled analysis containing ⱖ3 RCTs
that investigated any intervention to prevent falls in community-dwelling older adults
aged ⱖ60 years were eligible. Sixteen meta-analyses, representing 47 pooled analyses,
were included.
Data Extraction. Two authors independently extracted data.
Data Synthesis. Data were narratively synthesized. The methodological quality
of the meta-analyses was moderate. Three meta-analyses defined a fall, and 3 reported
adverse events (although minor). There is consistent evidence that exercise reduces
falls (including the rate, risk, and odds of falling), with 13/14 pooled analyses (93%)
from 7 meta-analyses demonstrating a significant reduction. The methodological
quality of meta-analyses investigating exercise were medium/high, and effect sizes
ranged from 0.87 (relative risk 95% confidence interval⫽0.81, 0.94; number of
studies⫽18; number of participants⫽3,568) to 0.39 (rate ratio 95% confidence
interval⫽0.23, 0.66; number of meta-analyses⫽6). There is consistent evidence that
multifactorial interventions reduce falls (5/6, 83% reported significant reduction).
There is conflicting evidence regarding the influence of vitamin D supplementation
(7/12, 58.3% reported significant reduction).
B. Stubbs, PT, MSc, MCSP, Faculty
of Education and Health, University of Greenwich, Southwood
Site, Avery Hill Road, Eltham, London, United Kingdom SE9 2UG.
Address all correspondence to Mr
Stubbs
at:
brendonstubbs@
hotmail.com.
S. Brefka, MD, AGAPLESION
Bethesda Clinic, Department of
Geriatrics, Ulm University, Ulm,
Germany.
M.D. Denkinger, MD, Competence Centre of Geriatrics and
Aging Research Ulm/Alb-Donau,
Ulm, Germany.
[Stubbs B, Brefka S, Denkinger
MD. What works to prevent falls in
community-dwelling older adults?
Umbrella review of meta-analyses
of randomized controlled trials.
Phys Ther. 2015;95:1095–1110.]
© 2015 American Physical Therapy
Association
February 5, 2015
Accepted: January 26, 2015
Limitations. Meta-analyses often used different methods of analysis, and reporting of key characteristics (eg, participants, heterogeneity, publication bias) was often
lacking. There may be some overlap among included meta-analyses.
Conclusions. There is consistent evidence that exercise and individually tailored
multifactorial interventions are effective in reducing falls in community-dwelling
older adults.
Post a Rapid Response to
this article at:
ptjournal.apta.org
August 2015
Volume 95
Number 8
Physical Therapy f
1095
F
alls represent a substantial threat
to the aging global population’s
quality of life and remain a
leading cause of morbidity and mortality.1–3 Falls are common and affect
around 30% of those aged over 65
years of age living in the community,
and the risk increases with age.2,4,5
The financial costs of falls also are
profound. For instance, after
accounting for inflation, the direct
cost of health care provision following a fall in the United States was
estimated at $30 billion in 2010.6 Not
surprisingly, numerous national and
international guidelines have been
developed that seek to prevent
falls.1,7,8
A diverse range of interventions have
been developed and tested through
robust randomized controlled trials
(RCTs) and subsequently summarized in systematic reviews and
meta-analyses. Conclusions based on
systematic reviews of RCTs are considered the top of the hierarchy of
evidence.9 Although there are some
criticisms of systematic reviews as an
entity (eg, prone to bias in original
studies, publication bias, and may
miss landmark well-powered primary studies10), a well-conducted
systematic review does have the ability to make robust, generalizable
conclusions over and above those
from a single study. In addition,
meta-analyses have the potential to
provide the closest effect size of
an intervention.11 Although metaanalyses based on systematic reviews
are considered the “gold standard,”
there is increasing recognition that
even a perfect meta-analysis with
perfect data can provide only a partial overview of the interventions
available to clinicians.12 This finding
is particularly true in complex
interventions such as falls prevention, where many different options
are available to clinicians. With
this realization, the popularity of
umbrella reviews, or systematic
reviews of systematic reviews, has
1096
f
Physical Therapy
Volume 95
increased to provide clinicians, policy makers, and researchers with
the highest-quality information in
one place regarding any particular
intervention.
Concerning the prevention of falls, a
range of interventions has been considered with systematic reviews and
meta-analyses, including single interventions such as exercise13 and vitamin D supplementation14 or more
complex multifactorial interventions.4 Physical therapists have an
integral role in the prevention of
falls, and it is essential they have
knowledge of the highest-quality evidence of interventions that reduce
falls. Because of this proliferation
in high-quality falls prevention
research, we sought to conduct a
comprehensive umbrella review of
all systematic reviews containing
meta-analyses of RCTs on the prevention of falls in community-dwelling
older adults.
Method
This umbrella review followed a
predetermined published protocol
(PROSPERO
registration:
CRD42014010715).
Eligibility Criteria
Meta-analyses of RCTs that investigated any intervention that sought to
reduce falls in community-dwelling
older adults were included. More
specifically, meta-analyses had to
meet the following criteria:
Population. The study population
comprised
community-dwelling
older adults (ie, living in the community and not in a long-term care facility, with a mean age of ⱖ60 years).
We did not include studies conducted in hospitals or long-term care
facilities. We excluded reviews in
specialist populations (eg, stroke,
Parkinson disease).
Number 8
Interventions. Any intervention
that sought to prevent falls was
included.
Outcome measures. Our primary
outcome measure was the effect of
interventions on the rate of falls or
the number of fallers. In this study, a
fall was defined as “an unexpected
event in which the participants
come to rest on the ground, floor, or
lower level.”15(p1619) We considered
any type of falls, including recurrent
(2 or more falls over the study
period) and injurious falls.
We did not place any language
restriction upon our searches. If we
encountered manuscripts published
in languages other than English, German, French, or Spanish, we planned
to contact the authors to acquire the
data of interest. Meta-analyses not
informed by a systematic review
were excluded. Meta-analyses must
contain at least one pooled analysis
with ⱖ3 RCTs. Because some metaanalyses conducted multiple subgroup and sensitivity analyses, we
report the primary analysis (effect
size) for each intervention they
investigated. If we encountered
meta-analyses that were updates
from previous reviews (eg, updated
Cochrane review), we included only
the most recent meta-analysis. If we
encountered reviews on similar topics with different methods of analysis, inclusion criteria, and results, we
included both reviews (decided by 3
authors). Meta-analyses including
some controlled trials were included
if ⱖ80% of the included studies
within the pooled analysis were
RCTs.
Available With
This Article at
ptjournal.apta.org
• eAppendix: Articles Excluded
From Community-Dwelling
Umbrella Review: Reasons for
Exclusion
August 2015
Search Procedure
Two independent authors (B.S., S.B.)
conducted a systematic search of the
MEDLINE, EMBASE, CINAHL, AMED,
BNI, PsycINFO, Cochrane Library,
PubMed, and PEDro databases from
inception to August 2014. A third
author (M.D.D.) was available as a
mediator. The key words used in the
searches were “falls” or “fall*” or
“recurrent falls” or “injurious fall” or
“fall prevention” AND “randomised
control trial” or “RCT” or “systematic
review” or “meta-analysis” AND
“older adult” or “elderly” or
“age” AND “intervention” AND
“exercise” AND “vitamin D supplementation” and “multifactorial.” The
reference lists of all potentially eligible articles were reviewed.
Data Extraction and Synthesis
Two authors (B.S., S.B.) independently extracted data, and a third
reviewer (M.D.D.) was available.
Data extracted included: first author,
year of publication, country, setting,
aim, search strategy, eligibility criteria, type of fall investigating, falls definition used, details of falls intervention, number of studies and number
of participants, participant demographics, main results (effect size
with 95% confidence intervals [95%
CIs]), adverse events, heterogeneity,
publication bias, and conclusions. In
the literature, a range of statistical
methods has been used to assess the
effect of interventions on falls,
including rate ratios (RaR⫽rate of
falls), risk ratios/relative risk (RR⫽
number of people who have fallen/
risk of falls), and odds ratios
(OR⫽odds of having a fall during the
trial). The RaR provides a summary
of the rate of falls between the intervention and control groups.4 The
RR, on the other hand, compares the
number of people who have fallen
between the intervention and control groups,4 and the OR is the ratio
of the odds of a fall happening in
each group.16 Collectively, we refer
to the effect of the interventions on
August 2015
falls. However, when we refer to
individual meta-analyses, we refer to
the actual measurement used in each
study. Where possible, we extracted
data on heterogeneity from each
pooled analysis and, in accordance
with the Cochrane collaboration,
report the I2 statistic, which refers to
the percentage of total variation
across studies that is due to heterogeneity rather than chance.16,17 Low,
moderate, and high I2 values of 25%,
50%, and 75%, respectively, are
commonly accepted.17 Due to the
heterogeneity in the populations,
interventions, and other key characteristics, the results are presented in
a narrative synthesis.12
Methodological Quality
Assessment
Two authors (B.S., S.B.) independently completed the Assessment of
Multiple
Systematic
Reviews
(AMSTAR).18 A third reviewer
(M.D.D.) was available. The AMSTAR
is a reliable and valid way to assess
the methodological quality of systematic reviews and meta-analyses.19
The AMSTAR tool consists of 11
items that are rated as “met,”
“unclear,” or “unmet,” and scores
are given ranging from 0 (low quality) to 11 (highest quality).18,19 The
AMSTAR scores are graded as high
(8 –11), medium (4 –7), or low (0 –3)
quality.18 –20
Results
Description of Search Results
Using the search strategy, 112 full
texts were considered, and 96 articles were excluded (see eAppendix,
available at ptjournal.apta.org, for
list of excluded articles). Within the
final sample, 16 separate metaanalyses reporting 47 pooled analyses were represented.4,14,21–34 Full
details of the search results are presented in the Figure.
Description of Included
Meta-analyses
Details of the included meta-analyses
are summarized in Table 1. In brief,
the meta-analyses included between
3 and 2223 individual RCTs and
between 34823 (education and exercise analysis, number of studies⫽3)
and 27,52221 participants across the
pooled analyses. Only 3 metaanalyses provided a definition for a
fall.4,24,26 Three meta-analyses provided details of adverse events
of the RCT interventions,4,24,29
which were all minor. Overall, the
quality of the meta-analyses was
medium to high. Specifically, 8 metaanalyses were graded as high
quality,4,14,22,24 –26,29,32 7 were graded
as medium quality,21,23,27,28,30,31,33
and 1 was considered as low quality34 (see Tab. 1 for AMSTAR scores).
Single Interventions
Exercise. Seven meta-analyses investigated a range of exercise interventions,4,23,24,27,29,30,34 and from
these meta-analyses, 13 out of 14
pooled analyses demonstrated that
exercise significantly reduced falls
(including the rate and risk of falling). Exercise was responsible for
reductions in falls, ranging from a
13% reduced risk29 (RR⫽0.87; 95%
CI⫽0.81, 0.94); number of trials⫽18;
number
of
participants⫽3,568) and a 61% reduction
in the rate of falls24 (RaR⫽0.39; 95%
CI⫽0.23, 0.66; number of trials⫽6)
and rate of falls causing fracture
(number of trials⫽6). Only one
study34 demonstrated a nonsignificant reduction in falls, although it
was rated as low quality. Overall, the
methodological quality of exercise
MAs was moderate to high.
Guo et al23 pooled 22 studies (number of participants⫽4,912) investigating a range of exercise interventions and found that exercise
significantly reduced the odds of falling (OR⫽0.78; 95% CI⫽0.65, 0.93).
El-Khoury et al24 found that exercise
Volume 95
Number 8
Physical Therapy f
1097
Figure.
Flow diagram of search strategy. RCT⫽randomized controlled trial.
significantly reduced the rate of injurious falls (RaR⫽0.63; 95% CI⫽0.51,
0.77; number of trials⫽10; I2⫽50%),
the rate of falls resulting in medical
care (RaR⫽0.70; 95% CI⫽0.54, 0.92;
number of trials⫽8; I2⫽20%), the
rate of falls causing serious injury
(RaR⫽0.57; 95% CI⫽0.36, 0.90;
number of trials⫽7; I2⫽46%), and
the rate of falls causing a fracture
(RaR⫽0.39; 95% CI⫽0.23, 0.66;
number of trials⫽6; I2⫽0%). Petridou et al27 reported that exercise significantly reduced risk of falls
(RR⫽0.67; 95% CI⫽0.52, 0.85). Gillespie et al4 demonstrated that exercise reduced the rate of falls regardless of whether it was conducted in a
group setting (RaR⫽0.71; 95%
CI⫽0.63, 0.82; number of trials⫽16;
number of participants⫽3,622;
I2⫽48%) or at home (RaR⫽0.68; 95%
number
of
participants⫽951;
1098
f
Physical Therapy
Volume 95
I2⫽0%). They also established that
exercise focused on gait, balance, or
functional training reduces the rate
of falls (RaR⫽0.72; 95% CI⫽0.55,
0.94; number of trials⫽4; number of
participants⫽519; I2⫽0), whereas
tai chi, although significant, was borderline and heterogeneous (RaR⫽
0.72; 95% CI⫽0.52, 1.00; number
of trials⫽5; number of participants⫽1,563; I2⫽72%). Michael et
al29 reported that physical therapy–
based exercises resulted in a reduction in risk of falls (RR⫽0.87; 95%
I2⫽4%). Thomas et al30 reported the
Otago exercise program significantly
reduced the rate of falls across
6 studies involving 1,466 people
(RaR⫽0.68; 95% CI⫽0.56, 0.79;
I2⫽0%).
Number 8
In conclusion, there is consistent evidence (93% or 13/14 pooled analyses) to support the effectiveness of
exercise as a single intervention to
prevent falls (including the risk,
odds, and rate of falls). This finding is
primarily based on medium-high
quality evidence.
Vitamin D supplementation. Seven meta-analyses investigated the
influence of vitamin D supplementation on falls,4,14,21,23,26,29,33 and from
12 pooled analyses, 7 established
that vitamin D supplementation significantly reduced falls. The effect
size ranged from a 22% reduced odds
of falling when vitamin D supplementation was combined with calcium23 (OR⫽0.78; 95% CI⫽0.63,
participants⫽4,326) to a 12%
reduced risk of falls without calcium26 (RR⫽0.88; 95% CI⫽0.81,
August 2015
0.96; number of trials⫽10; number
of participants⫽12,701).
Guo et al23 pooled 11 RCTs (6 with
vitamin D supplementation and calcium and 5 with vitamin D supplementation alone) and found there
was no significant effect on the odds
of falling. In a subgroup analysis, the
authors established that vitamin D
supplementation when combined
with calcium reduced the odds of
falling (OR⫽0.78; 95% CI⫽0.63,
0.98) but vitamin D supplementation
alone did not (OR⫽1.02; 95%
CI⫽0.82, 1.28). Kalyani et al26
pooled 10 studies and reported that
vitamin D supplementation significantly reduced the risk of falls
(RR⫽0.88; 95% CI⫽0.81, 0.96;
I2⫽34%). Gillespie et al4 pooled the
data from 7 RCTs (number of participants⫽9,324) and reported that
vitamin D supplementation had no
significant effect on falls rate
(RaR⫽1.00; 95% CI⫽0.90, 1.11;
I2⫽69%). Murad et al14 and Michael
et al29 pooled the data on RCTs of
vitamin D supplementation with and
without calcium and found that the
risk and odds of falls were respectively reduced (Michael et al29:
RR⫽0.83; 95% CI⫽0.77, 0.89; number of trials⫽9; number of participants⫽5,809; I2⫽3%; Murad et al14:
OR⫽0.80; 95% CI⫽0.69, 0.93;
number of trials⫽16; number of
participants⫽unclear). Bolland et
al21 reported that vitamin D supplementation had no significant effect
on the risk of falls (RR⫽0.96; 95%
number of participants⫽27,522);
this finding remained true in subgroup analyses for vitamin D supplementation alone (RR⫽0.96; 95%
number of participants⫽20,861)
and when combined with calcium
(RR⫽0.93; 95% CI⫽0.85, 1.02; number of trials⫽5; number of
participants⫽9,336).
August 2015
In summary, there is conflicting evidence (58.3% or 7/12 pooled analyses) regarding the effectiveness
of vitamin D supplementation to
reduce falls (including the rate, odds,
and risk), although the influence of
vitamin D supplementation appears
more effective when combined with
calcium.
Environmental interventions. In
total, 3 meta-analyses considered
environmental interventions to reduce falls, and 7 different pooled
analyses were available.4,23,31 All 3
meta-analyses reported one analysis
that demonstrated environmental
interventions reduced falls; overall, 4
out of the 7 pooled analyses demonstrated a statistically significant
reduction in falls.
Guo et al23 reported in the pooled
environmental and assistive technology analysis that the odds of falling
were not significantly reduced
(OR⫽0.83; 95% CI⫽0.68, 1.01; number of trials⫽13; number of participants⫽6,353). However, when they
conducted a subgroup analysis of
these results, they demonstrated that
home visit and modification did significantly reduce the odds of falling
(OR⫽0.75; 95% CI⫽0.56, 0.99; number of trials⫽7; number of participants⫽3,531), whereas assessment
and modification alone did not
(OR⫽1.11; 95% CI⫽0.83, 1.48; number of trials⫽3; number of participants⫽1,956). In their Cochrane
review, Gillespie et al4 demonstrated
that home safety and modification
reduces the rate of falls (RaR⫽
0.81; 95% CI⫽0.68, 0.97; number of
trials⫽6;
number
of
participants⫽4,208; I2⫽64%). They then
demonstrated that home safety interventions were significantly effective
when delivered by an occupational
therapist (RaR⫽0.69; 95% CI⫽0.55,
participants⫽1,443) but not when
delivered by a non-occupational
therapist (RaR⫽0.91; 95% CI⫽0.75,
of participants⫽3,075; I2⫽42%).
Finally, Clemson et al31 conducted a
review focusing solely on environmental interventions and found that
interventions that adapted and modified the environment resulted in a
reduction in the risk of falls
(RR⫽0.79; 95% CI⫽0.65, 0.97; number of trials⫽6; number of participants⫽3,298; I2⫽69%).
Overall, there is conflicting evidence
(57%, 4/7 pooled analysis) to suggest
that environmental interventions
may reduce falls in communitydwelling older adults. This finding
was based on moderate-quality
meta-analyses.
Surgery. Two
meta-analyses4,23
reported a pooled analysis investigating the influence of surgery on falls.
Gillespie et al4 pooled data from 3
RCTs investigating cardiac pacing
surgery and found that it significantly
reduced the rate of falls in older
adults with carotid sinus hypersensitivity, a condition that causes sudden
changes in heart rate and blood
pressure (RaR⫽0.73; 95% CI⫽0.57,
0.93; number of participants⫽349;
I2⫽51%). Guo et al23 pooled 2 studies investigating cardiac pacing and 1
study investigating cataract surgery
and found there was a nonsignificant
reduction in the odds of falling
(OR⫽0.87; 95% CI⫽0.45, 1.66; number of participants⫽704). Overall,
there is limited evidence to suggest
that surgical interventions can
reduce falls.
Other Single Interventions
Guo et al23 reported that education
did not significantly reduce the odds
of falling (OR⫽0.75; 95% CI⫽0.51,
of participants⫽810). Campbell and
Robertson28 pooled a range of single
interventions and reported a statistical reduction in the rate of falls
(RaR⫽0.77; 95% CI⫽0.67, 0.89;
Volume 95
Number 8
Physical Therapy f
1099
number of trials⫽10; number of
participants⫽unclear).
Multifactorial Interventions
Six meta-analyses investigated the
efficacy of individually tailored multifactorial interventions.4,25,27–29,34
Of these meta-analyses, 5 reported
that
falls
were
significantly
reduced,4,25,27,28,34 and 1 showed a
nonsignificant trend toward reducing falls.29 Multifactorial falls preventions reduced falls by between
10%25,27 and 35%,34 although the
study by Weatherall et al34 scored
low (2) on the AMSTAR tool.
Choi and Hector25 pooled 12 RCTs
(number of participants⫽unclear)
and found that multifactorial interventions reduced the risk of falls
(RR⫽0.90; 95% CI⫽0.85, 0.96;
Q⫽1.757; P⫽.185), which is comparable to the effect found in the
meta-analysis by Petridou et al27
(RR⫽0.90; 95% CI⫽0.82, 1.00; number of trials⫽5; number of participants⫽1,952; Q⫽6.9; P⫽.1). Gillespie et al4 pooled data from 19
RCTs investigating multifactorial
interventions and found that the rate
of falls was significantly reduced
(RaR⫽0.76; 95% CI⫽0.67, 0.86;
I2⫽85%). Campbell and Robertson28
pooled data from 6 RCTs and established that the rate of falls was
reduced (RaR⫽0.78; 95% CI⫽0.68,
0.89; number of participants⫽
unclear; I2⫽38%).
component” interventions, where
the interventions were not individually tailored. They found that multicomponent interventions significantly reduced the risk of falls
(RR⫽0.86; 95% CI⫽0.80, 0.92; number of participants⫽unclear; I2⫽0%).
Another meta-analysis32 pooled data
from 4 nurse-led RCTs and found
that the intervention had no significant effect on the odds of falling
(OR⫽0.51; 95% CI⫽0.19, 1.36; number of participants⫽1,392; I2⫽89%).
Overall, there is limited evidence
from one meta-analysis that multicomponent interventions reduce
falls, and there is no evidence that
nurse-led interventions reduce falls.
Summaries of the interventions are
presented in Table 2.
Discussion
Overall, there is consistent evidence
(83%, 5/6 pooled analyses) that
multifactorial interventions reduce
falls (including the rate and risk
of falling) in community-dwelling
older adults. This finding was
based on moderate- to high-quality
meta-analyses.
Within this umbrella review, we
have demonstrated that there is consistent moderate- to high-quality evidence (13/14 pooled analyses or 6/7
meta-analyses) that exercise can significantly reduce falls (including the
rate, risk, and odds of falling). There
is conflicting evidence that environmental and vitamin D supplementation interventions can reduce falls.
There is evidence from moderateand high-quality meta-analyses that
multifactorial interventions can
reduce falls among older adults (5/6
pooled analyses reported significant
reduction). Surprisingly, there is a
dearth of information on the harms
from fall prevention interventions
reported in the meta-analyses included in our umbrella review. However, in those meta-analyses that did
report such information, the
reported harms were all relatively
minor, and this dearth of information
may be a reflection of the lack of
reporting in the original studies.
Other Combined and
Multicomponent Interventions
Goodwin et al22 pooled the data
from 15 RCTs investigating “multi-
The results of this review support
the notion that exercise should be
provided to community-dwelling
older adults to prevent falls. Our
1100
f
Physical Therapy
Volume 95
Number 8
findings echo those of individual
meta-analyses13 showing strong evidence that exercise is effective in
preventing falls (albeit pooled analyses across mixed settings). The exact
type (eg, balance, strengthening, tai
chi), duration, frequency, and setting
of such interventions do show some
variations in the effect of the results,
but describing these variations in
greater detail is beyond the scope of
this review. Still, with regard to the
optimal nature of exercise, a balanced program including endurance,
balance, and strength exercises
could be recommended.35 Perhaps
the most robust included metaanalysis investigating exercise was
the Cochrane review by Gillespie
et al.4 All 4 pooled analyses that we
included demonstrated a similar significant reduction in falls, regardless
of whether it was in a group
(RaR⫽0.71), was at home (RaR⫽
0.68), involved balance training
(RaR⫽0.72), or was tai chi-based
(RaR⫽0.72). In an innovative
review, El-Khoury et al24 found that
exercise had profound effects on
reducing a range of different types of
injurious falls (including fractures);
thus, exercise has an integral role in
the management of falls in the community. Overall, about half of the
pooled analyses investigating exercise (5/11 pooled analyses) had low
to moderate heterogeneity (I2⬍50%
or nonsignificant Cochran Q). Therefore, together with the moderateand high-quality nature of these
meta-analyses, we can be confident
that exercise helps to prevent falls.
Ultimately, outside evidence on the
frequency, intensity, and type (FIT)
principles, the patients’ preference
also should be considered, as it can
influence adherence to exercise programs. In addition, some older adults
may have specific physical comorbidities (eg, musculoskeletal pain3),
meaning that they may need a physical therapist to provide an assessment and deliver appropriate adapAugust 2015
tive interventions. Specifically, the
effectiveness of physical therapy–
based exercise interventions was
established in the US Preventive Services Task Force meta-analysis.29 The
results of the current umbrella
review affirm the central role of
physical therapists in the prevention
of falls in community-dwelling older
adults. When one considers that
exercise has a range of wider health
benefits, such as comparable effects
of medication interventions on preventing mortality,36 the standout
benefits of exercise on falls prevention are encouraging. We recommend, therefore, that all older people at risk for falling or known to fall
should be encouraged to exercise,
and for those who are particularly
high risk and have a range of limitations, physical therapists should
oversee this process.
in a recent review by the same
group, the authors concluded that
any benefit of calcium supplements
on preventing fracture is outweighed by increased cardiovascular
events.41 So far, weighing current
evidence and balancing risks (few)
and benefits (fair) beyond the outcome falls (in the preceding sentences, we discuss the wider implications of vitamin D; here, we are
saying vitamin D may have other
benefits outside of falls prevention),
we support current recommendations of most guidelines: sufficient
vitamin D supplementation of at
least 1,000 IE daily or serum
25-hydroxy-vitamin D supplementation concentrations of 30 ng/mL (75
nmol/L) and higher, especially with
respect to frail older adults and those
with very low vitamin D supplementation levels.42
The evidence regarding vitamin D
supplementation is conflicting, although this intervention does appear
more promising when combined
with calcium supplementation. In
their recent sequential meta-analysis,
Bolland et al21 demonstrated that
vitamin D supplementation did not
reduce falls or alter the relative risk
by 15% or more. They recently compared the results of their metaanalysis21 and an earlier one,14 which
arrived at opposite conclusions,
and stated that the different conclusions were due to methodological
differences and different statistical
approaches.37 Other groups have
criticized these findings because of
the inclusion of low-quality RCTs
and the importance of appropriate
doses.38,39 Although even small
effects of vitamin D supplementation
could still result in public health recommendations because of overall
low serum levels in older adults, little adverse effects, and low price,
calcium has to be considered separately. Calcium supplementation has
been associated with an increased
risk of cardiovascular events,40 and
Regarding environmental falls prevention strategies, the interventions
were generally not well defined and
appear heterogeneous, although
they may be effective in reducing
falls, particularly when conducted
by an occupational therapist.4 Multifactorial interventions, in which particular risk factors are identified and
then interventions are individually
tailored, have become popular in the
medical literature and clinical practice. The results from our umbrella
review support the use of this
approach, although delivering multifactorial interventions and identifying individual risk factors can be
time-consuming. Therefore, the finding from the recent meta-analysis
that multicomponent interventions
(in which the intervention is not specifically tailored to the individual)
also can reduce falls is of great interest.22 This finding again seems to
account particularly for programs
where exercise is part of the intervention. However, effect sizes do
not differ very much from those that
build on exercise alone.
August 2015
Limitations and Strengths
Our umbrella review has a number
of strengths. We conducted a comprehensive search, including only
the highest-quality evidence (metaanalyses of RCTs), and condensed
this evidence in one place to make it
readily accessible for physical therapists and other clinicians. The overall methodological quality of the
included meta-analyses was moderate. Although this is the first
umbrella review, a number of limitations should be acknowledged,
which are largely reflected by limitations in the original studies. First, not
all of the studies assessed heterogeneity, and as shown in Table 1, only
studies of 10 meta-analyses reported
a heterogeneity statistic. Often, the
studies analyzed the effect of the
intervention using different summary measures (eg, RaR, RR, OR),
making it more challenging for the
reader to interpret. Second, the
meta-analyses often did not publish
specific details regarding the
included studies. Thus, it was not
always possible to determine clinical
homogeneity. Third, several metaanalyses may have included similar
studies in their analyses. Also, it is
unclear if the lack of adverse events
reported in the included metaanalyses is due to the absence of
these in the original studies. In addition, relying upon systematic
reviews may mean that landmark primary studies are not highlighted.
Finally, we could not include several
reviews that investigated falls prevention interventions with metaanalysis in mixed settings that did
not provide subgroup analysis for
community-dwelling older adults.
Nevertheless, allowing for these
caveats, our umbrella review is the
first such review and provides key
evidence to position physical therapists to be well equipped to manage
falls in community-dwelling older
adults. In essence, the available evidence suggests that exercise inter-
Volume 95
Number 8
Physical Therapy f
1101
ventions are the most consistently
effective and robust interventions to
tackle falls in older adults, and it
could be hypothesized that exercise
also largely accounts for the effect
seen in multifactorial/multicomponent programs. However, future
research should investigate the frequency, intensity, and type of intervention and setting and test their
effectiveness in clinical practice.
Very few meta-analyses reported on
the harms associated with falls prevention interventions—an important
outcome that was likely limited by
the primary studies. Regardless, policies are often made based on systematic reviews of interventions.
Therefore, it is important that
authors of studies of interventions
adequately report any harmful side
effects and clearly define their outcome measures in advance.
In conclusion, we found consistent
evidence to suggest that exercise
is associated with a reduction in the
rate, risk, and odds of falling (including falls resulting in injury), thus
affirming physical therapists’ central
position to lead in international
efforts to prevent falls. There also is
consistent evidence regarding the
effectiveness
of
multifactorial
interventions.
All authors designed the study, which was
prospectively registered, and helped acquire
the data. Mr Stubbs and Dr Denkinger wrote
the manuscript. Dr Brefka provided input. All
authors approved the final version.
PROSPERO registration: http://www.crd.
york.ac.uk/PROSPERO/display_record.asp?
ID⫽CRD42014010715.
References
1 Panel on Prevention of Falls in Older Persons, American Geriatrics Society and British Geriatrics Society. Summary of the
updated American Geriatrics Society/British Geriatrics Society clinical practice
guideline for prevention of falls in older
persons. J Am Geriatr Soc. 2011;59:148 –
157.
f
Physical Therapy
3 Stubbs B, Binnekade T, Eggermont L, et al.
Pain and the risk for falls in communitydwelling older adults: systematic review
and meta-analysis. Arch Phys Med Rehabil. 2014;95:175–187.e79.
4 Gillespie LD, Robertson MC, Gillespie WJ,
older people living in the community.
Cochrane Database Syst Rev. 2012;9:
CD007146.
Volume 95
16 Higgins JPT, Green S, eds. Cochrane
Handbook for Systematic Reviews of
Interventions Version 5.1.0. Updated
March 2011. The Cochrane Collaboration.
Available at: http://handbook.cochrane.
org. Accessed October 1, 2014.
17 Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in metaanalyses. BMJ. 2003;327:557–560.
18 Shea BJ, Grimshaw JM, Wells GA, et al.
Development of AMSTAR: a measurement
tool to assess the methodological quality
of systematic reviews. BMC Med Res Methodol. 2007;7:10 –17.
5 Rubenstein LZ. Falls in older people: epidemiology, risk factors and strategies for
prevention. Age Ageing. 2006;35:ii37–
ii41.
19 Shea BJ, Hamel C, Wells GA, et al. AMSTAR
is a reliable and valid measurement tool to
assess the methodological quality of systematic reviews. J Clin Epidemiol. 2009;
62:1013–1020.
6 Centers for Disease Control and Prevention. Cost of falls among older adults.
2014. Available at: http://www.cdc.gov/
homeandrecreationalsafety/falls/fallcost.
html. Accessed October 1, 2014.
20 Sharif MO, Janjua-Sharif FN, Ali H,
Ahmed F. Systematic reviews explained:
AMSTAR— how to tell the good from the
bad and the ugly. Oral Health Dent
Manag. 2013;12:9 –16.
7 National Institute for Health and Care
Excellence (NICE). Falls: assessment and
prevention of falls in older people. NICE
guidelines [CG161]. June 2013. Available
at:
https://www.nice.org.uk/guidance/
cg161. Accessed October 1, 2014.
21 Bolland MJ, Grey A, Gamble GD, Reid IR.
Vitamin D supplementation and falls: a
trial sequential meta-analysis. Lancet Diabetes Endocrinol. 2014;2:573–580.
8 WHO Global Report on Falls Prevention
in Older Age. Geneva, Switzerland: World
Health Organization; 2007.
9 Moe RH, Haavardsholm EA, Christie A,
et al. Effectiveness of nonpharmacological
and nonsurgical interventions for hip
osteoarthritis: an umbrella review of highquality systematic reviews. Phys Ther.
2007;87:1716 –1727.
10 Matheson SL, Shepherd AM, Carr VJ. How
much do we know about schizophrenia
and how well do we know it? Evidence
from the Schizophrenia Library. Psychol
Med. 2014,44:3387–3405.
11 Button KS, Ioannidis JPA, Mokrysz C, et al.
Power failure: why small sample size
undermines the reliability of neuroscience. Nat Rev Neurosci. 2013;14:365–
376.
12 Ioannidis JP. Integration of evidence from
multiple meta-analyses: a primer on
umbrella reviews, treatment networks and
multiple treatments meta-analyses. CMAJ.
2009;181:488 – 493.
13 Sherrington C, Whitney JC, Lord SR, et al.
Effective exercise for the prevention of
falls: a systematic review and meta-analysis. J Am Geriatr Soc. 2008;56:2234 –
2243.
14 Murad MH, Elamin KB, Abu Elnour NO,
et al. Clinical review—the effect of vitamin D on falls: a systematic review and
meta-analysis. J Clin Endocrinol Metab.
2011;96:2997–3006.
DOI: 10.2522/ptj.20140461
1102
2 Deandrea S, Lucenteforte E, Bravi F, et al.
Risk factors for falls in communitydwelling older people: a systematic review
and meta-analysis. Epidemiology. 2010;
21:658 – 668.
15 Lamb SE, Jørstad-Stein EC, Hauer K,
Becker C; for the Prevention of Falls Network Europe and Outcomes Consensus
Group. Development of a common outcome data set for fall injury prevention
trials: the Prevention of Falls Network
Europe consensus. J Am Geriatr Soc 2005;
53:1618 –1622.
Number 8
22 Goodwin VA, Abbott RA, Whear R, et al.
Multiple component interventions for preventing falls and fall-related injuries among
older people: systematic review and metaanalysis. BMC Geriatr. 2014;14:15.
23 Guo JL, Tsai YY, Liao JY, et al. Interventions to reduce the number of falls
among older adults with/without cognitive impairment: an exploratory meta-analysis. Int J Geriatr Psychiatry. 2014;29:
661– 669.
24 El-Khoury F, Cassou B, Charles MA,
Dargent-Molina P. The effect of fall prevention exercise programmes on fall
induced injuries in community dwelling
older adults: systematic review and metaanalysis of randomised controlled trials.
BMJ. 2013;347:f6234.
25 Choi M, Hector M. Effectiveness of intervention programs in preventing falls: a systematic review of recent 10 years and
meta-analysis. J Am Med Dir Assoc. 2012;
13:188.e113– e121.
26 Kalyani RR, Stein B, Valiyil R, et al. Vitamin
D treatment for the prevention of falls in
older adults: systematic review and metaanalysis. J Am Geriatr Soc. 2010;58:1299 –
1310.
27 Petridou ET, Manti EG, Ntinapogias AG,
et al. What works better for communitydwelling older people at risk to fall? J
Aging Health. 2009;21:713–729.
28 Campbell AJ, Robertson MC. Rethinking
individual and community fall prevention
strategies: a meta-regression comparing
single and multifactorial interventions.
Age Ageing. 2007;36:656 – 662.
29 Michael YL, Whitlock EP, Lin JS, et al. Primary care-relevant interventions to prevent falling in older adults: a systematic
evidence review for the U.S. Preventive
Services Task Force. Ann Intern Med.
2010;153:815– 825.
August 2015
August 2015
United
Kingdom
Goodwin
et al,22
2014
Taiwan
New
Zealand
Bolland
et al,21
2014
Gou
et al,23
2014
Country
Study
5 (n⫽9,336)
Vitamin D with calcium
Volume 95
Number 8
Nutritional supplement:
Non tai chi exercise
Exercise vs control:
11 (n⫽9,750)
20 (n⫽4,150)
22 (n⫽4,912)
15 (n⫽?, 5,034 in
total)
11 (n⫽20,861)
Vitamin D without
calcium
Multicomponent
interventions (2 or
more interventions
not individually
tailored)
14 (n⫽27,522)
RCTs Included
(nⴝNumber of
Participants)
Vitamin D with or
without calcium
Intervention
Summary and Results of Included Studiesa
Table 1.
Older adults
without
cognitive
impairment
Mean age⫽
64.5–89.0 y
Mean age⫽
69–86.4 y,
38%–100%
female
Mean
age⫽67–81
y in RCTs,
24%–100%
female
participants
in RCTs
Participants’
Details
No
No
No
Define
a Fall?
OR⫽0.89 (0.75, 1.04)
ORⴝ0.78 (0.64, 0.95)
ORⴝ0.78 (0.65, 0.93)
RaRⴝ0.78 (0.71, 0.85)
RRⴝ0.86 (0.80, 0.92)
RR⫽0.93 (0.85, 1.02)
RR⫽0.96 (0.88, 1.04)
RR⫽0.96 (0.90, 1.02)
Main Results
(95% CI)
NR
I2⫽20%
I2⫽0%
NR
NR
NR
Heterogeneity
NR
NR
NR
Adverse
Events
AMSTAR
4
9
5
Conclusion
(Continued)
Vitamin D
supplementation
with calcium
reduces falls,
but vitamin D
alone does not
Exercise reduces
falls in older
adults
Multicomponent
interventions
not specifically
tailored to an
individual’s risk
factors reduce
the number of
fallers and rate
of falls
Vitamin D
supplementation
with or without
calcium does
not reduce the
risk of falling in
communitydwelling older
adults
Physical Therapy f
1103
1104
f
Physical Therapy
El-Khoury
et al,24
2013
Study
Continued
Table 1.
France
Country
Volume 95
Number 8
3 (n⫽704)
Surgery (2⫻ cataract
and 1⫻ cardiac
pacing)
17 (n⫽4,305)
3 (n⫽348)
Education and exercise
Exercise
4 (n⫽810)
7 (n⫽3,531)
Home visit and
modification
Education intervention:
13 (n⫽6,353)
Environment/assistive
technology:
3 (n⫽1,956)
6 (n⫽4,326)
Vitamin D ⫹ calcium
Assess and modification
5 (n⫽5,424)
Vitamin D alone
Intervention
RCTs Included
(nⴝNumber of
Participants)
Mean
age⫽76.7
y, 77%
female
Participants’
Details
Yes
Define
a Fall?
Injurious falls
I2⫽50%
Falls requiring
medical care
I2⫽20%
Serious injury
I2⫽46%
RaR for falls requiring
medical careⴝ0.70
(0.54, 0.92, number
of trialsⴝ8)
RaR for serious
injuryⴝ0.57
(0.36, 0.90, number
of trialsⴝ7)
Heterogeneity
RaR for injurious
fallsⴝ0.63
(0.51, 0.77, number
of trialsⴝ10)
OR⫽0.87 (0.45, 1.66)
OR⫽1.16 (0.40, 3.32)
OR⫽0.75 (0.51, 1.10)
OR⫽1.11 (0.83, 1.48)
ORⴝ0.75 (0.56, 0.99)
OR⫽0.83 (0.68, 1.01)
ORⴝ0.78 (0.63, 0.98)
OR⫽1.02 (0.82, 1.28)
Main Results
(95% CI)
AMSTAR
9
Yes, 6 RCTs
reported, a
total of 8
participants
had minor
injuries
No major
adverse
events
Adverse
Events
(Continued)
Exercise
significantly
reduces all types
of injurious falls,
including falls
requiring
medical care or
resulting in
severe injury or
fractures
Surgery does not
reduce falls
Education alone or
when combined
with exercise
has no effect on
falls
Home visits and
modification
reduce falls
Conclusion
August 2015
August 2015
Greece
United
States
Kalyani
et al,26
2010
Petridou
et al,27
2009
United
States
Country
Choi and
Hector,25
2012
Study
Continued
Table 1.
Volume 95
Number 8
Multifactorial
interventions only
Exercise only
Exercise and
multifactorial
interventions:
Vitamin D
supplementation
Multifactorial
interventions (n⫽15)
or single
interventions (n⫽2)
Intervention
5 (n⫽1,952)
5 (n⫽597)
10 (n⫽2,549)
5 (n⫽1,504)
10 (n⫽12,701)
12/17 community
dwelling (n⫽?,
total⫽5,501)
RCTs Included
(nⴝNumber of
Participants)
All ⱖ65 years
of age
Age range⫽
71–92 y
NR
Participants’
Details
No
Yes
No
Define
a Fall?
Falls causing
fracture
I2⫽0%
Heterogeneity
RRⴝ0.90 (0.82, 1.00)
RRⴝ0.45 (0.29, 0.71)
RRⴝ0.67 (0.52, 0.85)
RRⴝ0.79 (0.69, 0.92)
for participants ⬍80
years of age who
defined a fall
RRⴝ0.88 (0.81, 0.96)
Q⫽6.9 (P⫽.14)
Q⫽18.5
(P⬍.001)
Q⫽51.4
(P⬍.001)
I2⫽29%
I2⫽34%
Q⫽1.757,
Multifactorial
P⫽.185
interventions,
community only
RRⴝ0.90 (0.85, 0.96,
Nⴝ12)
RaR for falls causing
fractureⴝ0.39
(0.23, 0.66, number
of trialsⴝ6)
Main Results
(95% CI)
NR
NR
NR
Adverse
Events
5
9
8
AMSTAR
(Continued)
Exercise and
multifactorial
interventions
both reduce falls
Vitamin D therapy
reduces falls in
adults younger
than 80 y
regardless if a
fall was defined
or not
Multifactorial
interventions
reduce falls
Conclusion
Physical Therapy f
1105
1106
f
Gillespie
et al,4
2012
Study
Continued
Table 1.
Intervention
Physical Therapy
Volume 95
Number 8
RaR⫽1.00 (0.90, 1.11)
RaRⴝ0.72 (0.55, 0.94)
RaRⴝ0.72 (0.52, 1.00)
Home safety by OT
4 (n⫽1,443)
RaRⴝ0.69 (0.55, 0.86)
RaRⴝ0.81 (0.68, 0.97)
3 (n⫽349)
Surgery: cardiac pacing
6 (n⫽4,208)
7 (n⫽9,324)
Vitamin D:
I2⫽48%
Heterogeneity
AMSTAR
I2⫽58%
(Continued)
Home safety and
modification are
effective in
reducing falls
I2⫽64%
Fitting cardiac
pacing device
reduces falls
Vitamin D does
not reduce falls
Tai chi has
marginal effect
on falls
Exercise as a single
intervention
reduces falls
(including
multiple
components
and balance)
Conclusion
Environmental
interventions
and
modifications
reduce falls
when delivered
by an OT to
individuals at
high risk of
falling
Minor adverse
events
Vitamin D
10
Yes
Resistance, 2
trials reported
musculoskeletal
injuries
Adverse Events
I2⫽51%
I2⫽69%
I2⫽0%
I2⫽72%
RaRⴝ0.68, (0.58, 0.80) I2⫽0%
RaRⴝ0.71 (0.63, 0.82)
Main Results
(95% CI)
Home safety and
modification
4 (n⫽519)
Gait, balance, or
functional training
Yes
Define
a Fall?
RaRⴝ0.73 (0.57, 0.93)
5 (n⫽1,563)
Tai chi
70% female
All ⱖ60 years
of age
Participants’
Details
Environment:
7 (n⫽951)
16 (n⫽3,622)
Home-based exercises
containing multiple
components vs
control
Group exercise:
multiple categories
vs control
United
Exercise single
Kingdom
interventions:
Country
RCTs Included
(nⴝNumber of
Participants)
August 2015
August 2015
Country
New
Zealand
United
States
Study
Campbell and
Robertson,28
2007
Michael
et al,29 2010
Continued
Table 1.
Volume 95
Vitamin D (with or
without calcium)
Exercise/
physical therapy
Multifactorial
interventions
Single intervention
9 (n⫽5,809)
18 (n⫽3,568)
19 (n⫽7,099)
14 (n⫽5,968)
19 (n⫽9,503)
Multifactorial
interventions
Multifactorial
interventions
4 (n⫽3,075)
Home safety not by OT
Intervention
RCTs Included
(nⴝNumber of
Participants)
All studies
included
people ⬎65
years of age
67% female
All ⬎65 years
of age
Participants’
Details
No
No
Define
a Fall?
RRⴝ0.83 (0.77, 0.89)
RRⴝ0.87 (0.81, 0.94)
RR⫽0.94 (0.87, 1.02)
RaRⴝ0.77 (0.67, 0.89,
number of
trialsⴝ10)
RaRⴝ0.78 (0.68,0.89,
number of
trialsⴝ6)
RaRⴝ0.76 (0.67, 0.86)
RaR⫽0.91 (0.75, 1.11)
Main Results
(95% CI)
I2⫽3%
I2⫽4%
I2⫽73%
I2⫽54%
I2⫽38%
Heterogeneity
Number 8
No evidence
vitamin D
increases
falls, no
reported
harms
No evidence
of
increased
falls in
physical
therapy
studies
5/19
reported
harms, all
minor
NR
Adverse
Events
8
7
AMSTAR
(Continued)
Physical therapy/
exercise and
vitamin D
significantly
reduces falls,
but it is unclear
if multifactorial
assessment and
interventions
reduce falls
Both multifactorial
and single
interventions
reduce falls and
are equally
effective
Multifactorial
interventions
reduce falls
Conclusion
Physical Therapy f
1107
1108
f
Physical Therapy
Volume 95
Number 8
United
Kingdom
United
Kingdom
New
Zealand
Tappenden
et al,32
2012
Jackson
et al,33
2007
Weatherall,34
2004
5 (n⫽860)
11 (n⫽3,350)
Multifactorial
interventions
3 (n⫽784)
4 (n⫽1,392)
6 (n⫽3,298)
16 (n⫽?, overall
sample)
6 (n⫽1,466), 1
study was CCT
Exercise
Vitamin D
Nurse-based health
promotion
interventions
Environmental
interventions
(adaptations and
modifications to
environment)
Vitamin D
Otago exercise
program
Intervention
RCTs Included
(nⴝNumber of
Participants)
No
No
⬎60 years of
age
NR
No
No
No
No
Define
a Fall?
Age range⫽
71.9–83 y
Mean
age⫽79.6 y
Mean age⫽76
y, 78%
female
Mean
age⫽81.6 y
Participants’
Details
ORⴝ0.65 (0.52, 0.81)
OR⫽0.79 (0.58, 1.08)
RR⫽0.92 (0.75, 1.12)
OR⫽0.51 (0.19, 1.36)
RRⴝ0.79 (0.65, 0.97)
ORⴝ0.80 (0.69, 0.93)
RaRⴝ0.68 (0.56, 0.79)
Main Results
(95% CI)
NR
I2⫽44%
NR
NR
I2⫽89%
NR
NR
NR
4 studies
reported
minor
adverse
events
Adverse
Events
I2⫽69%
NR
I2⫽0%
Heterogeneity
AMSTAR
2
6
8
7
8
7
Conclusion
Note: very lowquality metaanalysis
Exercise does not
significantly
reduce falls, but
multifactorial
interventions do
Vitamin D does
not reduce falls
Nurse-based health
promotion
interventions do
not appear to
significantly
reduce falls
Focused home
assessment
interventions
reduce falls,
particularly in
high risk groups
Vitamin D
combined with
calcium reduces
falls and
number of
fallers among
adults
The Otago
exercise
program
significantly
reduces falls
a
NR⫽not reported, OR⫽odds ratio, CI⫽confidence interval, AMSTAR⫽Assessment of Multiple Systematic Reviews, RR⫽risk ratio (number of people who fall) or relative risk, RaR⫽rate ratio (fall rate),
?⫽unclear how many participants were included in the analysis, OT⫽occupational therapist, CCT⫽controlled clinical trial. Bolded results are statistically significant.
Australia
United
States
Australia
Country
Clemson
et al,31
2008
Murad
et al,14
2011
Thomas
et al,30
2010
Study
Continued
Table 1.
August 2015
August 2015
a
Intervention
7
3
2
1
1
Vitamin D
Environmental
Surgery
Education
Single interventions combined
1
1
2
7
12
14
Volume 95
Number 8
Physical Therapy f
1
1
Education and exercise
combined
Multicomponent
interventions (not
individually tailored)
2
1
1
6
0
0
1 (2)22
0
0
0
5 (5)4,25,27,28,34
Limited
No evidence
1 (1)23
0
No evidence
⫹83% (5/6)
Limited
1 (1)32
1 (1)29
0
No evidence
1 (1)23
There is conflicting evidence that
environmental interventions can reduce
falls. Home assessment and modification
are effective, particularly when delivered
by an occupational therapist.
⫹57% (4/7)
One MA established that multicomponent
interventions not tailored to the
individual reduce falls
Education and exercise had no significant
effect on falls
One MA found that nurse-led combined
interventions do not reduce falls
5 out of 6 MAs demonstrated that
multifactorial interventions reduce falls,
whereas 1 MA showed a trend toward
reduction of falls. One MA
demonstrating positive results had low
methodological quality.
1 MA pooled various single interventions
and did not differentiate the type of
intervention but found it reduced falls
1 MA demonstrated that education does
not reduce falls
There is limited and inconsistent evidence
that surgery reduces falls, although one
MA suggests that cardiac pacing surgery
does reduce falls.
There is conflicting evidence that vitamin D
supplementation prevents falls. Best
evidence exists for combination with
calcium.
⫹58.3% (7/12)
Limited
There is consistent evidence that exercise
significantly reduces falls (rate, risk, and
odds), including those that cause injury.
Only one MA of low methodological
quality demonstrated a nonsignificant
reduction in falls.
Comment
⫹93% (13/14)
% of Overall
Effect
(Pooled)a
1 (1)23
2 (3)4,23
3 (5)4,23,33
1 (1)34
Nonsignificant
Effect
Overall effect⫽number of supporting associations versus overall number (pooled), limited⫽only 1 MA investigating an intervention.
1
6
Nurse-led falls prevention
Individually tailored
multifactorial interventions
0
0
0
1 (1)4
1 (1)28
0
3 (4)4,23,31
0
0
5 (7)14,21,23,26,29
0
0
Reduces Falls
Increases
Falls
Number of MAs (Number of Pooled Analyses)
6 (13)4,23,24,27,29,30
Multifactorial, combined, and multicomponent interventions
7
Exercise
Single interventions
Number
of MAs
Number of
Pooled
Analyses
Overview of Findings of the Meta-Analyses (MAs) Included in the Umbrella Review
Table 2.
1109
30 Thomas S, Mackintosh S, Halbert J. Does
the “Otago exercise programme” reduce
mortality and falls in older adults? A systematic review and meta-analysis. Age Ageing. 2010;39:681– 687.
31 Clemson L, Mackenzie L, Ballinger C, et al.
Environmental interventions to prevent
falls in community-dwelling older people:
a meta-analysis of randomized trials. J
Aging Health. 2008;20:954 –971.
32 Tappenden P, Campbell F, Rawdin A, et al.
The clinical effectiveness and costeffectiveness of home-based, nurse-led
health promotion for older people: a systematic review. Health Technol Assess.
2012;16:1–72.
33 Jackson C, Gaugris S, Sen SS, Hosking D.
The effect of cholecalciferol (vitamin D3)
on the risk of fall and fracture: a metaanalysis. QJM. 2007;100:185–192.
1110
f
Physical Therapy
Volume 95
34 Weatherall M. Prevention of falls and fallrelated fractures in community-dwelling
older adults: a meta-analysis of estimates of
effectiveness based on recent guidelines.
Intern Med J. 2004;34:102–108.
35 Landi F, Marzetti E, Martone AM, et al.
Exercise as a remedy for sarcopenia. Curr
Opin Clin Nutr Metab Care. 2014;17:25–
31.
36 Naci H, Ioannidis JPA. Comparative effectiveness of exercise and drug interventions on mortality outcomes: metaepidemiological study. BMJ. 2013;347:f5577.
37 Bolland MJ, Grey A, Reid IR. Differences in
overlapping meta-analyses of vitamin D
supplements and falls. J Clin Endocrinol
Metab. 2014;99:4265– 4272.
38 Bischoff-Ferrari HA, Orav EJ, Willett WC,
Dawson-Hughes B. The effect of vitamin D
supplementation on skeletal, vascular, or
cancer outcomes. Lancet Diabetes Endocrinol. 2014;2:363–364.
Number 8
39 Bischoff-Ferrari HA, Dawson-Hughes B,
Staehelin HB, et al. Fall prevention with
supplemental and active forms of vitamin
D: a meta-analysis of randomised controlled trials. BMJ. 2009;339:b3692.
40 Bolland MJ, Avenell A, Baron JA, et al.
Effect of calcium supplements on risk of
myocardial infarction and cardiovascular
events: meta-analysis. BMJ. 2010;341:
c3691.
41 Bolland MJ, Grey A, Reid IR. Calcium supplements and cardiovascular risk: 5 years
on. Ther Adv Drug Saf. 2013;4:199 –210.
42 American Geriatrics Society Workgroup
on Vitamin D Supplementation in Older
Adults. Recommendations Abstracted
from the American Geriatrics Society Consensus Statement on Vitamin D for Prevention of Falls and Their Consequences.
J Am Geriatr Soc. 2014;62:147–152.
August 2015
eAppendix.
Articles Excluded From Community-Dwelling Umbrella Review: Reasons for Exclusion
No meta-analysis in the
systematic review
1 Karlsson MK, Vonschewelov T, Karlsson
C, et al. Prevention of falls in the elderly: a
review. Scand J Public Health. 2013;41:
442– 454.
2 Karlsson MK, Magnusson H, von Schewelov T, Rosengren BE. Prevention of falls in
the elderly: a review. Osteoporos Int.
2013;24:747–762.
3 Martin JT, Wolf A, Moore JL, et al. The
effectiveness of physical therapist–administered group-based exercise on fall prevention: a systematic review of randomized controlled trials. J Geriatr Phys Ther.
2013;36:182–193.
4 Simek EM, McPhate L, Haines TP. Adherence to and efficacy of home exercise programs to prevent falls: a systematic review
and meta-analysis of the impact of exercise
program characteristics. Prev Med. 2012;
55:262–275.
5 Neyens JC, van Haastregt JC, Dijcks BP,
et al. Effectiveness and implementation
aspects of interventions for preventing
falls in elderly people in long-term care
facilities: a systematic review of RCTs.
J Am Med Dir Assoc. 2011;12:410 – 425.
6 Latham NK, Anderson CS, Reid IR. Effects
of vitamin D supplementation on strength,
physical performance, and falls in older
persons: a systematic review. J Am Geriatr
Soc. 2003;51:1219 –1226.
7 Stern C, Jayasekara R. Interventions to reduce the incidence of falls in older adult
patients in acute-care hospitals: a systematic review. Int J Evid Based Healthc.
2009;7:243–249
8 Cadore EL, Rodrı́guez-Mañas L, Sinclair A,
Izquierdo M. Effects of different exercise
interventions on risk of falls, gait ability,
and balance in physically frail older adults:
a systematic review. Rejuvenation Res.
2013;16:105–114.
9 Lam FM, Lau RW, Chung RC, Pang MY.
The effect of whole body vibration on balance, mobility and falls in older adults: a
systematic review and meta-analysis.
Maturitas. 2012;72:206 –213.
10 Carter ND, Kannus P, Khan KM. Exercise
in the prevention of falls in older people:
a systematic literature review examining
the rationale and the evidence. Sports
Med. 2001;31:427– 438.
11 Bunn F, Dickinson A, Simpson C, et al.
Preventing falls among older people with
mental health problems: a systematic
review. BMC Nurs. 2014;13:4.
12 Batchelor FA, Dow B, Low MA. Do continence management strategies reduce falls?
A systematic review. Australas J Ageing.
2013;32:211–216.
13 Miake-Lye IM, Hempel S, Ganz DA, Shekelle PG. Inpatient fall prevention programs
as a patient safety strategy: a systematic
review. Ann Intern Med. 2013;158(5 pt
2):390 –396.
August 2015 (eAppendix, Stubbs et al)
14 Winter H, Watt K, Peel NM. Falls prevention interventions for community-dwelling
older persons with cognitive impairment:
a systematic review. Int Psychogeriatr.
2013;25:215–227.
15 Chase CA, Mann K, Wasek S, Arbesman M.
Systematic review of the effect of home
modification and fall prevention programs
on falls and the performance of
community-dwelling older adults. Am J
Occup Ther. 2012;66:284 –291.
16 de Kam D, Smulders E, Weerdesteyn V,
Smits-Engelsman BC. Exercise interventions to reduce fall-related fractures and
their risk factors in individuals with low
bone density: a systematic review of randomized controlled trials. Osteoporos Int.
2009;20:2111–2125.
17 Healey F, Oliver D, Milne A, Connelly JB.
The effect of bedrails on falls and injury: a
systematic review of clinical studies. Age
Ageing. 2008;37:368 –378.
18 Hauer K, Becker C, Lindemann U, Beyer N.
Effectiveness of physical training on motor
performance and fall prevention in cognitively impaired older persons: a systematic
review. Am J Phys Med Rehabil. 2006;85:
847– 857.
19 Kannus P, Sievänen H, Palvanen M, et al.
Prevention of falls and consequent injuries
in elderly people. Lancet. 2005;366:1885–
1893.
20 Sherrington C, Lord SR, Finch CF. Physical
activity interventions to prevent falls
among older people: update of the evidence. J Sci Med Sport. 2004;7(1 suppl):
43–51.
21 Cumming RG. Intervention strategies and
risk-factor modification for falls prevention: a review of recent intervention studies. Clin Geriatr Med. 2002;18:175–189.
22 Wu G. Evaluation of the effectiveness of
Tai Chi for improving balance and preventing falls in the older population: a
review. J Am Geriatr Soc. 2002;50:746 –
754.
23 Gardner MM, Robertson MC, Campbell AJ.
Exercise in preventing falls and fall-related
injuries in older people: a review of randomised controlled trials. Br J Sports Med.
2000;34:7–17.
24 Wooton AC. An integrative review of Tai
Chi research: an alternative form of physical activity to improve balance and prevent falls in older adults. Orthop Nurs.
2010;29:108 –116.
25 Jahnke R, Larkey L, Rogers C, et al. A comprehensive review of health benefits of
Qigong and Tai Chi. Am J Health Promot.
2010;24:e1– e25.
26 Balzer K, Bremer M, Schramm S, et al. Falls
prevention for the elderly. GMS Health
Technol Assess. 201212;8:Doc01.
27 Verhagen AP, Immink M, van der Meulen
A, Bierma-Zeinstra S. The efficacy of Tai
Chi Chuan in older adults: a systematic
review Fam Pract. 2004;21:107–113.
28 Karinkanta S, Piirtola M, Sievänen H, et al.
Physical therapy approaches to reduce fall
and fracture risk among older adults Nat
Rev Endocrinol. 2010;6:396 – 407.
29 Sawka AM, Ismaila N, Cranney A, et al. A
scoping review of strategies for the prevention of hip fracture in elderly nursing
home residents. PLoS One. 2010;5:e9515.
30 Harling A, Simpson JP. A systematic review to determine the effectiveness of Tai
Chi in reducing falls and fear of falling in
older adults. Phys Ther Rev. 2008;13:237–
248.
31 Drukker M, de Bie RA, van Rossum E. The
effects of exercise training in institutionalized elderly people: a systematic review.
Phys Ther Rev. 2001;6:273–285.
32 Holt KR, Haavik H, Elley CR. The effects of
manual therapy on balance and falls: a systematic review [with consumer summary]. J Manipulative Physiol Ther. 2012;35:
227–234.
33 Nuffield Institute for Health, University of
Leeds, NHS Centre for Reviews and Dissemination University of York. Preventing
falls and subsequent injury in older people. Eff Health Care. 1996;2:1–16. Available at: https://www.york.ac.uk/inst/crd/
EHC/ehc24.pdf.
34 Rogers CE, Larkey LK, Keller C. A review
of clinical trials of Tai Chi and Qigong in
older adults. West J Nurs Res. 2009;31:
245–279.
35 Komagata S, Newton R. The effectiveness
of Tai Chi on improving balance in older
adults: an evidence-based review. J Geriatr Phys Ther. 2003;26:9 –16.
36 Anderson O, Boshier P, Hanna G. Interventions designed to prevent healthcare bedrelated injuries in patients [with consumer
summary]. Cochrane Database Syst Rev.
2011;11:CD008931.
37 Evans D, Hodgkinson B, Lambert L, et al.
Falls in acute hospitals: a systematic
review. The Joanna Briggs Institute for Evidence Based Nursing and Midwifery, Adelaide, South Australia, Australia. Number 1.
1998. Available at: http://citeseerx.
ist.psu.edu/viewdoc/download?doi⫽10.
1.1.170.9008&rep⫽rep1&type⫽pdf.
38 Steultjens EM, Dekker J, Bouter LM, et al.
Occupational therapy for community
dwelling elderly people: a systematic
review. Age Ageing. 2004;33:453– 460.
39 Ishigaki EY, Ramos LG, Carvalho ES, Lunardi AC. Effectiveness of muscle strengthening and description of protocols for preventing falls in the elderly: a systematic
review. Braz J Phys Ther. 2014;18:111–
118.
40 Tofthagen C, Visovsky C, Berry DL.
Strength and balance training for adults
with peripheral neuropathy and high risk
of fall: current evidence and implications
for future research. Oncol Nurs Forum.
2012;39:E416 –E424.
Volume 95
(Continued)
Number 8
Physical Therapy f
1
eAppendix.
Continued
41 Liu H, Frank A. Tai chi as a balance
improvement exercise for older adults: a
systematic review. J Geriatr Phys Ther.
2010;33:103–109.
Could not separate randomized
controlled trial (RCT) pooled
results from non-RCT
42 Sirkin AJ, Rosner NG. Hypertensive management in the elderly patient at risk for
falls. J Am Acad Nurse Pract. 2009;21:
402– 408.
55 Hempel S, Newberry S, Wang Z, et al. Hospital fall prevention: a systematic review
of implementation, components, adherence, and effectiveness. J Am Geriatr Soc.
2013;61:483– 494.
43 Marks R, Allegrante JP. Falls-prevention
programs for older ambulatory community dwellers: from public health research
to health promotion policy. Soz Praventivmed. 2004;49:171–178.
44 van Haastregt JC, Diederiks JP, van Rossum E, et al. Effects of preventive home
visits to elderly people living in the community: systematic review. BMJ. 2000;
320:754 –758.
45 Kosse NM, Brands K, Bauer JM, et al. Sensor technologies aiming at fall prevention
in institutionalized old adults: a synthesis
of current knowledge. Int J Med Inform.
2013;82:743–752.
46 Health Quality Ontario. Prevention of falls
and fall-related injuries in communitydwelling seniors: an evidence-based analysis. Ont Health Technol Assess Ser. 2008;
8:1–78.
47 Sohng KY, Choi JH, Song HH, Moon JS. A
meta-analysis of exercise programmes or
preventing falls in older people. Asian
Journal of Nursing Studies. 2005;8:3–15.
48 Cadore EL, Rodrı́guez-Mañas L, Sinclair A,
Izquierdo M. Effects of different exercise
interventions on risk of falls, gait ability,
and balance in physically frail older adults:
a systematic review. Rejuvenation Res.
2013;16:105–114.
Relied on meta-analysis with <3
studies on falls outcome measure
49 Logghe IH, Verhagen AP, Rademaker AC,
et al. The effects of Tai Chi on fall prevention, fear of falling and balance in older
people: a meta-analysis. Prev Med. 2010;
51:222–227.
50 Oliver D, Hopper A, Seed P. Do hospital
fall prevention programs work? A systematic review. J Am Geriatr Soc. 2000;48:
1679 –1689.
51 DiBardino D, Cohen ER, Didwania A. Metaanalysis: multidisciplinary fall prevention
strategies in the acute care inpatient population. J Hosp Med. 2012;7:497–503.
52 Leung DP, Chan CK, Tsang HW, et al. Tai
chi as an intervention to improve balance
and reduce falls in older adults: a systematic and meta-analytical review. Altern
Ther Health Med. 2011;17:40 – 48.
53 Desapriya E, Subzwari S, Scime-Beltrano G,
et al. Vision improvement and reduction
in falls after expedited cataract surgery:
systematic review and meta-analysis. J Cataract Refract Surg. 2010;36:13–19.
54 Fox MT, Persaud M, Maimets I, et al. Effectiveness of acute geriatric unit care using
acute care for elders components: a systematic review and meta-analysis. J Am
Geriatr Soc. 2012;60:2237–2245.
2
f
Physical Therapy
Volume 95
56 Hill-Westmoreland EE, Soeken K, Spellbring AM. A meta-analysis of fall prevention programs for the elderly: how effective are they? Nurs Res. 2002;51:1– 8.
Not looking at RCTs for fall
prevention
57 Pritchard E, Brown T, Lalor A, Haines T.
The impact of falls prevention on participation in daily occupations of older adults
following discharge: a systematic review
and meta-analysis. Disabil Rehabil. 2014;
36:787–796.
58 Fairhall N, Sherrington C, Clemson L, Cameron ID. Do exercise interventions
designed to prevent falls affect participation in life roles? A systematic review and
meta-analysis. Age Ageing. 2011;40:666 –
674.
59 Sawka AM, Boulos P, Beattie K, et al. Do
hip protectors decrease the risk of hip
fracture in institutional and communitydwelling elderly? A systematic review and
meta-analysis of randomized controlled trials. Osteoporos Int. 2005;16:1461–1474.
60 McClure R, Turner C, Peel N, et al.
Population-based interventions for the
prevention of fall-related injuries in older
people. Cochrane Database Syst Rev.
2005;1:CD004441.
61 Kemmler W, Häberle L, von Stengel S.
Effects of exercise on fracture reduction in
older adults: a systematic review and metaanalysis. Osteoporos Int. 2013;24:1937–
1950.
62 Nyman SR, Victor CR. Older people’s participation in and engagement with falls
prevention interventions in community
settings: an augment to the Cochrane systematic review. Age Ageing. 2012;41:16 –
23.
63 Davis JC, Robertson MC, Ashe MC, et al.
Does a home-based strength and balance
programme in people aged ⬎ or ⫽80
years provide the best value for money to
prevent falls? A systematic review of economic evaluations of falls prevention interventions. Br J Sports Med. 2010;44:80 – 89.
66 Bergman GJ, Fan T, McFetridge JT, Sen SS.
Efficacy of vitamin D3 supplementation in
preventing fractures in elderly women: a
meta-analysis. Curr Med Res Opin. 2010;
26:1193–1201.
67 Granacher U, Gollhofer A, Hortobágyi T,
et al. The importance of trunk muscle
strength for balance, functional performance, and fall prevention in seniors: a
systematic review. Sports Med. 2013;43:
627– 641.
68 Schwenk M, Jordan ED, Honarvararaghi B,
et al. Effectiveness of foot and ankle exercise programs on reducing the risk of falling in older adults: a systematic review and
meta-analysis of randomized controlled trials. J Am Podiatr Med Assoc. 2013;103:
534 –547.
69 McMahon S, Fleury J. External validity of
physical
activity
interventions
for
community-dwelling older adults with fall
risk: a quantitative systematic literature
review. J Adv Nurs. 2012;68:2140 –2154.
Specialist population
70 Batchelor F, Hill K, Mackintosh S, Said C.
What works in falls prevention after
stroke? A systematic review and meta-analysis. Stroke. 2010;41:1715–1722.
71 Verheyden GS, Weerdesteyn V, Pickering
RM, et al. Interventions for preventing
falls in people after stroke. Cochrane
Database Syst Rev. 2013;5:CD008728.
72 Tomlinson CL, Patel S, Meek C, et al. Physiotherapy intervention in Parkinson’s disease: systematic review and meta-analysis
[with consumer summary]. BMJ. 2012;
345:e5004.
73 Allen NE, Sherrington C, Paul SS, Canning
CG. Balance and falls in Parkinson’s disease: a meta-analysis of the effect of exercise and motor training. Mov Disord.
2011;26:1605–1615.
74 Allen J, Koziak A, Buddingh S, et al. Rehabilitation in patients with dementia following hip fracture: a systematic review [with
consumer summary]. Physiother Can.
2012;64:190 –201.
75 Jensen LE, Padilla R. Effectiveness of interventions to prevent falls in people with
Alzheimer’s disease and related dementias.
Am J Occup Ther. 2011;65:532–540.
76 Iwamoto J, Takeda T, Matsumoto H. Sunlight exposure is important for preventing
hip fractures in patients with Alzheimer’s
disease, Parkinson’s disease, or stroke.
Acta
Neurol
Scand.
2012;125:
279 –284.
(Continued)
64 Donaldson MG, Sobolev B, Cook WL, et al.
Analysis of recurrent events: a systematic
review of randomised controlled trials of
interventions to prevent falls. Age Ageing.
2009;38:151–155.
65 Bischoff-Ferrari HA, Willett WC, Wong JB,
et al. Fracture prevention with vitamin D
supplementation: a meta-analysis of randomized controlled trials. JAMA. 2005;
293:2257–2264.
Number 8
eAppendix.
Continued
Not informed by a systematic
review
77 Province MA, Hadley EC, Hornbrook MC,
et al. The effects of exercise on falls in
elderly patients: a preplanned metaanalysis of the FICSIT trials. Frailty and
Injuries: Cooperative Studies of Intervention Techniques. JAMA. 1995;273:1341–
1347.
78 Robertson MC, Campbell AJ, Gardner MM,
Devlin N. Preventing injuries in older people by preventing falls: a meta-analysis of
individual-level data. J Am Geriatr Soc.
2002;50:905–911.
Language difficulties
79 Park M, Song R. Effects of Tai Chi on fall
risk factors: a meta-analysis [in Korean]. J
Korean Acad Nurs. 2013;43:341–351.
Overlap of already included
review
80 Lucke JE. Fall-prevention programs for the
elderly: a Bayesian secondary meta-analysis. Can J Nurs Res. 2004;36:48 – 64.
81 Gillespie WJ, Gillespie LD, Parker MJ. Hip
protectors for preventing hip fractures in
older people. Cochrane Database Syst
Rev. 2010;10:CD001255. Update in:
Cochrane
Database
Syst
Rev.
2014;3:CD001255.
Not relevant/different outcomes
82 Jung D, Lee J, Lee SM. A meta-analysis of
fear of falling treatment programs for the
elderly. West J Nurs Res. 2009;31:6 –16.
83 Beswick AD, Rees K, Dieppe P, et al. Complex interventions to improve physical
function and maintain independent living
in elderly people: a systematic review and
meta-analysis. Lancet. 2008;371:725–735.
84 Tricco AC, Cogo E, Holroyd-Leduc J, et al.
Efficacy of falls prevention interventions:
protocol for a systematic review and network meta-analysis. Syst Rev. 2013;2:38.
85 McPhate L, Simek EM, Haines TP. Programrelated factors are associated with adherence to group exercise interventions for
the prevention of falls: a systematic review
[with consumer summary]. J Physiother.
2013;59:81–92.
Not community dwelling
86 Cameron ID, Gillespie LD, Robertson MC,
older people in care facilities and hospitals. Cochrane Database Syst Rev. 2012;
12:CD005465.
87 Silva RB, Eslick GD, Duque G. Exercise for
falls and fracture prevention in long-term
care facilities: a systematic review and
meta-analysis. J Am Med Dir Assoc.
2013;14:685– 689.e2.
Did not separately pool
community-dwelling
adults/contain sufficient number
of RCTs in community-dwelling
adults for separate analysis
Staehelin HB, et al. Fall prevention with
supplemental and active forms of vitamin
D: a meta-analysis of randomised controlled trials. BMJ. 2009;339:b3692.
89 Sherrington C, Whitney JC, Lord SR, et al.
Effective exercise for the prevention of
falls: a systematic review and meta-analysis. J Am Geriatr Soc. 2008;56:2234 –
2243.
90 Gates S, Fisher JD, Cooke MW, et al. Multifactorial assessment and targeted intervention for preventing falls and injuries
among older people in community and
emergency care settings: systematic
review and meta-analysis. BMJ. 2008;336:
130 –133.
91 Coussement J, De Paepe L, Schwendimann
R, et al. Interventions for preventing falls
in acute- and chronic-care hospitals: a systematic review and meta-analysis. J Am
Geriatr Soc. 2008;56:29 –36.
92 Oliver D, Connelly JB, Victor CR, et al.
Strategies to prevent falls and fractures in
hospitals and care homes and effect of
cognitive impairment: systematic review
and meta-analyses. BMJ. 2007;334:82.
Willett WC, et al. Effect of Vitamin D on
falls: a meta-analysis. JAMA. 2004;291:
1999 –2006.
94 Chang JT, Morton SC, Rubenstein LZ, et al.
Interventions for the prevention of falls in
older adults: systematic review and metaanalysis of randomised clinical trials. BMJ.
2004;328:680.
95 Sherrington C, Tiedemann A, Fairhall N,
et al. Exercise to prevent falls in older
adults: an updated meta-analysis and best
practice recommendations. N S W Public
Health Bull. 2011;22:78 – 83.
96 Santesso N, Carrasco-Labra A, BrignardelloPetersen R. Hip protectors for preventing
hip fractures in older people. Cochrane
Database Syst Rev. 2014;3:CD001255.
Volume 95
Number 8
Physical Therapy f
3
Research Report
Relationship Between Skin Intrinsic
Fluorescence—an Indicator of
Advanced Glycation End Products—
and Upper Extremity Impairments in
Individuals With Diabetes Mellitus
K.M. Shah, PT, PhD, Department
of Physical Therapy, Arcadia University, Glenside, Pennsylvania. At
the time of the study, Dr Shah was
affiliated with the Program in
Physical Therapy, Washington
University School of Medicine, St
Louis, Missouri.
Kshamata M. Shah, B. Ruth Clark, Janet B. McGill, Catherine E. Lang,
John Maynard, Michael J. Mueller
Background. Accumulation of advanced glycation end products (AGEs) is
thought to contribute to limited joint mobility in people with diabetes mellitus (DM),
but the relationships among AGEs, shoulder structural changes, movement, and
disability are not understood.
Objective. The purpose of this study was to determine the differences and
relationships among skin intrinsic fluorescence (SIF), a proxy measure of AGEs,
biceps and supraspinatus tendon thickness, upper extremity movement, and disability in groups with and without DM.
Design. This was a cross-sectional, case-control study.
Methods. Fifty-two individuals participated: 26 with type 2 DM and 26 controls
matched for sex, age, and body mass index. The main outcome measures were: SIF;
biceps and supraspinatus tendon thickness; 3-dimensional peak shoulder motion; and
Disability of the Arm, Shoulder and Hand (DASH) questionnaire scores.
Results. Mean SIF measurements were 19% higher in the DM group compared
with the control group (P⬍.05). Biceps tendons (mean and 95% confidence interval
[CI]) (4.7 mm [4.4, 5.0] versus 3.2 mm [2.9, 3.5]) and supraspinatus tendons (6.4 mm
[5.9, 6.8] versus 4.9 mm [4.4, 5.3]) were thicker and peak humerothoracic elevation
(139° [135°, 146°] versus 150° [146°, 155°]) and glenohumeral external rotation (35°
[26°, 46°] versus 51° [41°, 58°]) were reduced in the DM group compared with the
control group (P⬍.05). In the DM group, SIF was correlated to biceps tendon
thickness, DASH score, and shoulder motion (r⫽.44 –.51, P⬍.05). The SIF score and
shoulder strength explained 64% of the DASH scores (P⬍.01).
Limitations. Because this was a cross-sectional study design, a cause-effect relationship could not be established.
Conclusions. Accumulation of AGEs in the connective tissues of individuals with
DM appears to be associated with increased tendon thickness and decreased shoulder
joint mobility and upper extremity function. Physical therapists should be aware of
these possible metabolic effects on structure, movement, and disability when treating
people with diabetes.
B.R. Clark, PT, PhD, Program in
Physical Therapy, Washington
University School of Medicine.
J.B. McGill, MD, Division of Endocrinology, Metabolism and Lipid
Research, Department of Medicine,
Washington
University
School of Medicine.
C.E. Lang, PT, PhD, Program in
Physical Therapy, Program in
Occupational Therapy, Department of Neurology, Washington
University School of Medicine.
J. Maynard, MS, MDDC, Albuquerque, New Mexico.
M.J. Mueller, PT, PhD, FAPTA, Program in Physical Therapy and
Department of Radiology, Washington University School of Medicine, Campus Box 8502, 4444
Forest Park Ave, Ste 1101, St
Louis, MO 63108-2212 (USA).
Address all correspondence to Dr
Mueller at: [email protected].
[Shah KM, Clark BR, McGill JB,
et al. Relationship between skin
intrinsic fluorescence—an indicator of advanced glycation end
products—and upper extremity
impairments in individuals with
diabetes mellitus. Phys Ther.
2015;95:1111–1119.]
Association
April 9, 2015
Submitted: August 1, 2014
this article at:
ptjournal.apta.org
August 2015
Volume 95
Number 8
Physical Therapy f
1111
Skin Intrinsic Fluorescence in Individuals With Diabetes Mellitus
U
pper extremity musculoskeletal complications occur more
frequently in people with diabetes mellitus (DM) compared with
those without DM.1– 4 Larkin et al,5 in
a recent prospective study, reported
that 66% of their 1,217 participants
with type 1 diabetes had cheiroarthropathy, defined as the presence of any one of the following:
adhesive capsulitis, carpal tunnel
syndrome, flexor tenosynovitis,
Dupuytren contracture, or a positive
prayer sign. Prevalence of shoulder
impairments is reported to be about
11% to 50% in people with DM compared with 2% to 20% in those without DM.6 –9 Limited joint mobility
(LJM) is a systemic problem documented in the hands, shoulders,
ankles, and feet of people with
DM.4,10 –15 In its beginning stage, LJM
at the shoulders and hands can be
painless and go unnoticed but may
be a precursor to the severe upper
extremity impairments associated
with pain and disability.13–15
The excessive accumulation of
advanced glycation end products
(AGEs) in the connective tissues is
thought to contribute to LJM and the
high incidence of musculoskeletal
problems seen in DM.14 Advanced
glycation end products accumulate
in all people and are formed by oxidative stress and the nonenzymatic
condensation of glucose and proteins.16 –18 This process is greatly
accelerated, however, in the presence of high levels of glucose, as
seen in people with DM. Excessive
levels of AGEs lead to pathological
collagen cross-linking and structural
changes in the tissues. Of particular
interest is the excessive cross-linking
in the collagen-rich musculoskeletal
tissues such as tendons, ligaments,
skin, and muscle.18 –20 Structural
changes that occur in the shoulders
of individuals with diabetes as a
result of excessive levels of AGEs
include increased thickness in the
biceps and supraspinatus tendons.14,21,22 Additionally, fibrous
contractures and dense collagen
matrix have been observed in the
shoulder joint capsule, with adherence to the head of the humerus,
rotator interval area, and coracohumeral ligament.23,24 We hypothesize
that these excessive AGEs and structural changes lead to upper extremity movement impairments, pain,
and disability (Fig. 1).
The accumulation of AGEs can be
estimated noninvasively, in vivo
using skin intrinsic fluorescence
(SIF). This method uses nearultraviolet and blue light to excite
and measure the fluorescence produced by AGEs.25–27 Estimating AGEs
levels in the skin is particularly beneficial because AGEs that accumulate
in the skin have an estimated half-life
of 15 to 20 years and, therefore, are
a good indicator of long-term glycemic exposure of collagen-rich tissues.28,29 Previous research has
shown that this SIF measure is correlated to the severity of complications related to tissue-specific diabetes such as peripheral neuropathy
(seen mainly in the distal lower
extremities), increased arterial stiffness, and nephropathy.25,30,31 A 2014
study by Larkin et al5 showed differences in skin fluorescence, glycated
hemoglobin, and functional disabil-
ity between groups with and without upper extremity impairments in
a sample of people with type 1 DM.
However, the complete set of relationships outlined in Figure 1 among
AGEs, shoulder structural changes,
3-dimensional joint motion, and
upper extremity pain and disability
needs to be evaluated, especially in
people with type 2 DM. Such investigation should provide insight into
the mechanism and management (ie,
prevention or rehabilitation) of these
upper extremity impairments in individuals with DM.
The purpose of this study was to
determine group differences (DM
versus control) and relationships
among SIF (an indicator of AGEs
accumulation in the skin), structural
changes, and upper extremity movement impairments and disability in
the group with DM (Fig. 1). We
hypothesized that: (1) the SIF measure would be higher, the biceps and
supraspinatus tendons would be
thicker, and upper extremity movement would be reduced in the group
with DM compared with the control
group; (2) the SIF measure would be
positively correlated to the tendon
thickness and upper extremity disability and negatively correlated to
shoulder movement; and (3) a significant amount of the variance of the
upper extremity disability would be
explained by SIF, biceps tendon
thickness, movement impairments,
and shoulder strength.
Method
Participants
We recruited a total of 52 participants: 26 participants with type 2
Figure 1.
Theoretical framework for upper extremity (UE) impairments.
1112
f
Physical Therapy
Volume 95
Number 8
August 2015
Table 1.
a
Demographic Information
Variable
Age (y)
Sex (male/female)
Height (m)
Weight (kg)
2
BMI (kg/m )
HbA1c (%)
DM Group
Control Group
Pb
64.5 (61.5, 66.8)
64.2 (61.9, 66.4)
.80
13/13
13/13
1.7 (1.66, 1.74)
1.00
86.2 (71.9, 101.1)
1.7 (1.6, 1.8)
86.6 (81.7, 91.6)
.80
30.1 (23.7, 36.4)
30.0 (28.3, 31.4)
.90
6.9 (6.4, 7.3)
Diabetes duration (y)
13.0 (5.4, 20.4)
Dominance (right/left)
22/4
Prayer sign (positive/negative)
15/11
22/4
9/17
.14c
a
All data presented as mean (95% confidence interval) or number of participants. DM
group⫽participants with diabetes mellitus, control group⫽participants without diabetes mellitus,
BMI⫽body mass index, HbA1c⫽glycated hemoglobin.
b
Significance determined using independent-sample Student t tests.
c
Significance determined using chi-square analysis.
diabetes and 26 controls matched for
age, body mass index (BMI), and sex
who did not have diabetes (selfreported) or shoulder pain. The participants’ demographic information
is shown in Table 1. Both groups
were recruited from the outpatient
diabetes center of a large medical
hospital and the Volunteers for
Health at Washington University
School of Medicine, St Louis, Missouri. All participants signed an
institution-approved consent form
prior to the clinical examination.
The intent of recruitment to meet
the aims of this study was to include
individuals without acute or severe
shoulder problems who were attending an outpatient diabetes clinic and
at high risk for developing shoulder
LJM and subsequent shoulder impairments and compare them with a control group without DM or shoulder
pain. Characteristics associated with
systemic LJM include duration of diabetes5– 8,32 and a positive prayer sign
(ie, an inability to fully extend the
interphalangeal joints of the hands
when pressed together).32 Therefore, inclusion criteria for the group
with DM were: duration of diagnosed diabetes of more than 10 years
or a positive prayer sign and age
August 2015
between 40 and 70 years. We
wanted to include the insidious
development of shoulder impairments; therefore, we did not exclude
individuals in the group with DM
based solely on their pain levels. To
eliminate other potential confounders, participants in the control group
were matched for age, BMI, and sex.
We also matched groups for side of
hand dominance, as it may affect
range of motion (ROM), strength,
and possibly tendon size and would
allow us to make appropriate comparisons between the DM and control groups.
In both groups, individuals were
excluded if they had acute or severe
shoulder problems, including a history of or current adhesive capsulitis,
rotator cuff tears, recent upper
extremity injury or fractures, or surgery in the upper extremity or thorax; neck pain; stroke with residual
upper extremity involvement; rheumatic conditions; hypothyroid malfunctions; angina or other symptoms
of myocardial ischemia; severe skin
allergies in the area to be tested;
known or at risk for photosensitivity
reactions; or known connective tissue diseases. In addition, participants with a BMI greater than 35
kg/m2 were excluded, as the kinematic measurement errors are
known to be large in people with
high BMI.33 Control participants
were screened by phone for shoulder pain because we wanted the
group with DM to be compared with
a control group without any shoulder impairments. All measurements
were made by a single, trained physical therapist during a single session
on the right arm using the following
standardized methods for all
participants.
Measurements
Skin intrinsic fluorescence. Skin
intrinsic fluorescence was measured
as an indicator of AGEs (Fig. 1).
Duplicate measurements of SIF were
obtained from the skin on the underside of the left forearm using a
SCOUT skin fluorescence spectrometer (VeraLight, Albuquerque, New
Mexico). The SIF was excited with a
light-emitting diode (LED) centered
at 435 nm and was detected over the
emission range of 470 to 655 nm.
Skin reflectance was assessed with a
white LED over the 435- to 655-nm
spectral region. The measured skin
reflectance was used to compensate
for absorbance due to melanin and
hemoglobin as well as individualspecific light scattering using the
intrinsic fluorescence correction5
formula expressed in the equation:
f xm ⫽
F xm
k
Rm
R xk x
m
where the measured fluorescence
(Fxm) is divided by reflectance values
from the excitation and white LEDs
(Rx and Rm, respectively). The reflectance values are adjusted by the
dimensionless exponents, kx and km.
For these analyses, the 435-nm
excited fluorescence was utilized
with kx set to 0.4 and km set to 0.9.
The resulting intrinsic fluorescence
(fxm) was integrated over the 470- to
655-nm spectral region and multiplied by 1,000 to represent SIF,
Volume 95
Number 8
Physical Therapy f
1113
reported in arbitrary units. The intraindividual skin variation in SIF
assessed by the SCOUT has previously been documented in 1,185 participants with type 1 diabetes and
was 4.2%.27
Tendon thickness. Tendon thickness was measured as an indicator of
structural changes occurring in the
shoulder secondary to the accumulation of AGEs (Fig. 1). Ultrasound
examination (Acuson XP 128/10, Siemens Medical Solutions Inc, Mountain View, California) for tendon
thickness of the long head of the
biceps and supraspinatus tendons
was performed using a highresolution, multifrequency (7–10
MHz) linear transducer by a single
examiner. Images of the transverse
view and longitudinal view were
obtained for the biceps and supraspinatus tendons, respectively, as
described previously.21,22 The tendon thickness was measured using
the ImageJ (version 1.45s, National
Institutes of Health, Bethesda, Maryland) computerized image analysis
program. The maximum thickness of
the biceps tendon in the transverse
view was measured within the bicipital groove of the humerus. In the
longitudinal view, the maximum
supraspinatus tendon thickness was
measured just in front of the lateral
part of the humeral head, close to its
insertion (anatomical neck) on the
lesser tubercle. We took an additional measurement at the midpoint
of the anatomical footprint (greater
tubercle of the humerus) of the
supraspinatus tendon to account for
differences in the anatomy of the
tendon among individuals. The longitudinal thickness was an average of
these 2 measurements. The average
of 3 thickness measurements for
each tendon was used for data
analyses.
Upper extremity movement.
Three-dimensional humerothoracic
(humerus relative to thorax) and
1114
f
Physical Therapy
Volume 95
glenohumeral (humerus relative to
scapula) joint motion was measured
using the Flock of Birds electromagnetic tracking device (Ascension
Technology Inc, Burlington, Vermont) and Motion Monitor software
(The Motion Monitor, Innovative
Sports Training Inc, Chicago, Illinois). The humerus sensor was
attached to a thermoplastic cuff to
reduce rotation errors and attached
to the humerus using tapes. Standard
methods were used to build the anatomic segments and define the
motion.34,35 Measurements for 3 trials were collected during full, painfree active ROM during scapularplane elevation, defined as elevation
in a plane 40 degrees anterior to the
frontal plane. Using the same methods, the difference between the surface marker and a bone pin marker
for humerus motion was 0 to 4
degrees for elevation angle and 1.7
to 2.3 degrees for axial rotation
movements.33 The angles extracted
for this study were the peak humerothoracic elevation and peak glenohumeral external rotation.
Shoulder flexor muscle strength.
The isometric strength of the shoulder flexor muscles was measured
using a handheld, digital strain-gauge
dynamometer (Microfet, Hoggan
Health Industries Inc, West Jordan,
Utah). Each participant was in the
supine position, and standard stabilization and test positions were
used.36 An average of 2 trials was
used for the data analysis.
Measure of upper extremity
disability. We measured upper
extremity disability using the Disability of the Arm, Shoulder and Hand
(DASH) self-report questionnaire,37
which has been used previously in
the diabetes population and has
excellent reliability.4,7 The DASH has
30 questions, including questions on
disability as well as pain. The scores
were calculated for a range between
Number 8
0% and 100%, where a higher number indicates more impairments.
Statistical Analyses
Study size was based on our preliminary studies of goniometric shoulder ROM differences (effect sizes⫽1.21–1.22)38 and previously
published supraspinatus and biceps
tendon
thickness
differences
between groups with and without
DM (effect size⫽1.8 and 1.31,
respectively).21 We conservatively
estimated that 26 participants per
group would be required to see differences in primary variables
between groups and allow multiple
regression analysis in the group with
DM (statistical power level⫽0.8,
alpha⫽.05).
Statistical analyses of the data were
performed using IBM SPSS Statistics
for Windows version 22.0 (IBM
Corp, Armonk, New York). Means,
standard deviations, and percent
changes were used to describe the
variables. Differences in the demographic variables were analyzed
using independent-sample Student t
tests (continuous variables) and chisquare analysis (categorical variable:
hand LJM, as examined by a positive
prayer sign). The mean peak
humerothoracic elevation and peak
glenohumeral external rotation
angles were converted to positive
values for ease of understanding. All
variables were tested for their distribution, and appropriate statistics
were used. For all variables included
in the a priori hypotheses,
independent-sample 1-tailed Student
t tests were used to examine the differences between the 2 groups.
Mean and 95% confidence interval
(CI) were calculated and reported.
Pearson product moment correlation coefficients was used to examine relationships between SIF and
tendon thickness, peak humerothoracic elevation and glenohumeral
external rotation, and upper extrem-
August 2015
Table 2.
Differences in Metabolic, Structural, and Upper Extremity Movement and Function in
Between Groupsa
Variable
Pb
DM Group
Control Group
SIF (AU)
3.1 (2.5, 3.8)
2.6 (2.4, 2.8)
.047
BT thickness (mm)
4.7 (4.4, 5.0)
3.2 (2.9, 3.5)
⬍.001
SST thickness (mm)
6.4 (5.9, 6.8)
4.9 (4.4, 5.3)
⬍.001
Peak humerothoracic elevation (°)
139 (135, 146)
150 (146, 155)
.002
35 (26, 46)
51 (41, 58)
.008
Peak glenohumeral external rotation (°)
Flexor strength (kg)
13.0 (11.2, 14.7)
16.6 (14.8, 18.4)
DASH score (%)
19.4 (9.8, 30.0)
2.6 (0.6, 4.9)
.004
⬍.001
a
All data presented as mean (95% confidence interval). DM group⫽participants with diabetes
mellitus, control group⫽participants without diabetes mellitus, SIF⫽skin intrinsic fluorescence,
AU⫽arbitrary units, BT⫽biceps tendon, SST⫽supraspinatus tendon, DASH⫽Disability of the Arm,
Shoulder and Hand questionnaire.
b
Significance determined using independent-sample Student t test (one tailed) to examine group
differences (P⬍.05).
ity pain and disability in the group
with DM.
We further conducted a hierarchical
multiple regression analysis to
explain the variance of the DASH
scores in the group with DM (n⫽26).
The variables of interest were SIF
scores, biceps tendon thickness,
peak glenohumeral external rotation, and shoulder flexor muscle
strength. These variables were
selected a priori from the sequence
of events described in Figure 1.
Shoulder flexor muscle strength was
added to the model because a combination of shoulder mobility and
strength is necessary for adequate
upper extremity function. A hierarchical multiple regression analysis
was run by adding one variable at a
time. The independent variable was
left in the overall equation if: (1) the
overall P value (for the F value) was
less than .05, (2) the individual P
value (based on the t-test value) was
less than .10, and (3) the variable
added at least 5% unique variance
beyond the preceding variables. If all
of these criteria were not met, the
variable was removed from the equation, and the next variable was
entered. Statistical significance was
set at P⬍.05.
August 2015
Role of the Funding Source
This study was supported by a grant
from the Research Division of the
Program in Physical Therapy, Washington University School of Medicine, St Louis, Missouri; by grant 1
R21 DK100793-01 from the National
Institute of Diabetes and Digestive
and Kidney Diseases, National Institutes of Health (Dr Mueller); and by
Diabetes Research and Training Center (Grant No. P30 DK020579).
Results
Differences Between Groups
The differences between groups are
shown in Table 2. The mean SIF measure was higher in the DM group
compared with the control group
(3.1 arbitrary units [95% CI⫽2.5,
3.8] versus 2.6 arbitrary units [95%
CI⫽2.4, 2.8], respectively; P⫽.047).
The biceps tendon and supraspinatus tendon were 47% and 31%
thicker (P⬍.001), respectively, in
the DM group compared with the
control group. Peak humerothoracic
elevation was decreased by 11
degrees (139° [95% CI⫽135°, 146°]
in the DM group versus 150° [95%
CI⫽146°, 155°] in the control group;
P⫽.002), and peak glenohumeral
external rotation was decreased by
16 degrees (35° [95% CI⫽26°, 46°]
in the DM group versus 51° [95%
CI⫽41°, 58°] in the control group;
P⫽.008). Shoulder flexor strength
was reduced by 27% (P⫽.004) in the
DM group compared with the control group. The mean DASH score
was 19.4% (95% CI⫽9.8, 30.0) in the
DM group, indicating that these individuals had some complaints of
upper extremity disability and pain.
Four control participants reported
very low levels of pain and disability
during their laboratory visit (mean
DASH score⫽2.6 [95% CI⫽0.6, 4.9];
P⬍.01; Tab. 2).
Relationships Between SIF and
Tendon Thickness, Upper
Extremity Movement, and Pain
and Disability in the DM Group
The SIF measure was correlated to
biceps tendon thickness (r⫽.44,
P⫽.023; Fig. 2A) but not correlated
to supraspinatus tendon thickness
(r⫽.28, P⫽.2). The SIF measure was
negatively correlated to humerothoracic elevation (r⫽⫺.44, P⫽.024;
Fig. 2B) but not correlated to glenohumeral external rotation (r⫽⫺.32,
P⫽.13). The SIF measure was not
related to shoulder flexor muscle
strength (r⫽.07, P⫽.7). The SIF measure was correlated to the DASH
scores, a measure of upper extremity
disability (r⫽.51, P⫽.009; Fig. 2C).
Figure 2 shows the relationship
between the SIF and biceps tendon
thickness, humerothoracic elevation, and DASH scores in the DM
group. The control group data are
shown for comparison only, and
these values were not included in
the correlation analyses.
The SIF (R2⫽.24, P⫽.013) and shoulder flexor muscle strength (R2
change⫽.40, P⬍.001) explained
64% of the variance of the DASH
scores in the DM group. The biceps
tendon thickness and peak glenohumeral external rotation were not
included in the final model because
the individual contributions of these
predictors were not significant,
Volume 95
Number 8
Physical Therapy f
1115
tively correlated to the peak humerothoracic elevation. This study
uniquely examined and provides
insights about the relationships
among a proxy measure of AGEs,
structural changes, and upper
extremity LJM and disability in people with type 2 DM. The results are
consistent with our a priori hypotheses and the suspected deleterious
effect of excessive AGEs on structure, joint movement, and pain and
disability as outlined in Figure 1.
Figure 2.
Correlations between skin intrinsic fluorescence and (A) biceps tendon thickness, measured in the bicipital groove (DM group: r⫽.44, P⫽.02); (B) peak humerothoracic
elevation (DM group: r⫽⫺.44, P⫽.02); and (C) Disability of the Arm, Shoulder and
Hand (DASH) questionnaire scores (DM group: r⫽.51, P⫽.009). Data points for the
control group are included for comparison of distribution. Data analyzed for DM group
using Pearson product moment correlation coefficients. DM⫽diabetes mellitus,
AU⫽arbitrary units.
beyond the variables already entered
(Tab. 3).
Discussion
The results of this study demonstrated that the biceps and supraspinatus tendons were thicker and
shoulder movements, especially
1116
f
Physical Therapy
Volume 95
humeral external rotation and muscle strength, were substantially
reduced in the group with DM compared with the age-matched group
without DM. The SIF, an indicator of
AGEs accumulation, was related to
the biceps tendon thickness and
upper extremity disability and nega-
Number 8
The SIF measure was approximately
19% higher in individuals with DM
compared with controls in this study
(Tab. 2), which is in a similar range
as previous reports placing the SIF
values about 17% to 33% higher in
patients with DM compared with the
The
control
population.25,30,31
recent study by Larkin et al5 indicated higher SIF values in people
with type 1 DM and upper extremity
musculoskeletal problems compared
with those with DM who did not
have musculoskeletal problems.
Previous studies have used SIF to
understand the relationship between
accumulation of AGEs and diabetesrelated complications such as coronary artery disease30,31 and polyneuropathy25 in individuals with type 1
and type 2 DM. Furthermore, the
noninvasive dermal SIF may be a better marker for understanding the
musculoskeletal complications in
individuals with DM than blood or
serum markers because the turnover
of collagen is so much longer than
that of red blood cells (18 years versus 3– 4 months).28,29 For example,
SIF has been reported to be more
strongly associated with the presence of peripheral neuropathy than
the mean 18-year average of the glycated hemoglobin (HbA1c).25 In our
study, the SIF measures were related
to biceps tendon thickness, upper
extremity movement, and pain and
disability but not to supraspinatus
tendon thickness.
August 2015
Table 3.
Hierarchical Regression Analysis to Predict Variance in Disability of the Arm, Shoulder and Hand (DASH) Questionnaire Scores in
Participants With Diabetes (n⫽26)
Predictor Variablesa
Constant
Skin intrinsic fluorescence
Unstandardized
Coefficients (B)
Standard
Error
39.0
11.4
8.8
2.1
Standardized
Coefficients (B)
t
3.4
0.54
R2
P
4.2
.002
⬍.01
.24
Biceps tendon thickness
⫺2.57
4.6
⫺0.09
⫺0.6
.58
.24
Peak external rotation
⫺0.44
0.2
⫺0.04
⫺0.3
.77
.25
Shoulder flexor muscle strength
⫺1.6
0.3
⫺0.64
⫺4.9
⬍.01
.64
a
Variables are listed in the order that they were entered in the model; bold variables indicate significant unique variance after previous variables had been
entered.
The biceps and supraspinatus tendons were considerably thicker in
the group with DM compared with
the age-, BMI-, and sex-matched
control group (Tab. 2). Previous
work in this area has shown similar
results, with biceps and supraspinatus tendons thicker in groups with
DM compared with control groups
(4.0 mm versus 3.0 –3.2 mm and 6.2–
6.6 mm versus 4.9 –5.2 mm,
respectively).21,22
A unique contribution of our study is
that the SIF measure was related to
biceps tendon thickness, indicating
that as the skin accumulation of
AGEs increases, the tendon tends to
be thicker. However, the SIF measure was not correlated to supraspinatus tendon thickness. Possible reasons for this discrepancy include: (1)
SIF is an indirect measure of AGEs
and, the study was underpowered to
identify a relationship between the
SIF measure and supraspinatus tendon thickness (a post hoc power
analysis indicated 77 participants
would be needed); (2) there is
slightly greater measurement variability in the thickness of the
supraspinatus tendon compared
with the biceps tendon; and (3)
other factors besides AGEs levels
may uniquely affect tendon thickness in people with diabetes. Besides
thickness, however, AGEs levels
have been shown to be correlated to
the intrinsic tendon properties of
August 2015
cross-link formation, distortion of
the physiologic pattern of the tendon fibers, and tendon fiber sliding,
all of which would affect tendon
stiffness properties.39,40 Other structural changes thought to be associated with AGEs levels include fibrous
contractures in the capsule and
coracohumeral ligament in the
shoulders of individuals with
DM.23,24 In general, we hypothesize
that changes in tendon thickness and
other structures (ie, shoulder capsule) are primarily a result of the
accumulation of AGEs that leads to
LJM and movement impairments in
the upper extremity (Fig. 1). Future
studies need to examine in vivo
extrinsic and intrinsic properties of
the tendons, capsules, and connective tissues to understand better the
influence of increased accumulation
of AGEs on these structures.
There was substantial loss of peak
glenohumeral external rotation
(humerus relative to scapula) and
humerothoracic (humerus relative to
thorax) elevation in the DM group
compared with the control group.
Decreased elevation motion (about
20°) has been reported in people
with DM using traditional goniometric methods of assessing ROM.13,14 A
recent study in our laboratory demonstrated similar decreases of about
22 degrees and 10 degrees in the
humerothoracic elevation and external rotation movement.38 We also
observed decreased flexor muscle
strength (10.9 kg versus 14.7 kg,
respectively) in the cohort with DM
and the age- and BMI-matched control group.38 High levels of AGEs
accumulation in older adults have
been associated with low grip
strength values.41,42 Higher concentrations of AGEs in the intramuscular
connective tissue may contribute to
decreases in muscle function and
increased disability. The SIF measure
was negatively related to the peak
humerothoracic elevation, indicating that as the skin AGEs accumulation increases, the movement
decreases. We hypothesized that a
significant portion of the upper
extremity disability would be
explained by SIF, biceps tendon
thickness, peak glenohumeral external rotation movement, and flexor
muscle strength. Sixty-four percent
of the variance in the DASH scores
was explained by SIF and shoulder
flexor muscle strength (Tab. 3).
Therefore, accumulation of AGEs
and a decrease in shoulder flexor
muscle strength are important correlates of adverse outcomes of upper
extremity disability. Further exploration of these relationships, especially
the relationship between selfreported pain and disability and
AGEs, is warranted in future prospective studies.
The effect of joint movement and
exercise on the development or pre-
Volume 95
Number 8
Physical Therapy f
1117
vention of LJM in DM is not known.
Shoulder LJM may not be related to
complaints of pain at the early stage.
We postulate that the insidious loss
of ROM and strength may hit a
“threshold” and manifest as severe
symptoms of pain and disability. The
appropriate type and dosage of exercise prescribed may be useful in
reducing LJM, strength deficits, and
pain and disability. Additional
research is needed to investigate the
interaction of movement and metabolic complications on musculoskeletal problems in people with DM. If
impairments related to functional
limitations are detected early, rehabilitation and pharmaceutical (glucose lowering, AGEs inhibiting, and
cross-link breaking agents) therapies
may be developed to help prevent
additional detrimental changes. In
addition, close control of glucose
level is thought to be important in
minimizing the deleterious effects of
diabetes on the musculoskeletal
system.5
Limitations for this study are
acknowledged and discussed to facilitate interpretation of the results. We
assessed tendon thickness but not
the intrinsic tendon qualities such as
histology, stiffness, and strength.
Although we evaluated tendon thickness in individuals with DM to see
how it relates to movement impairments, there are other factors (eg,
bone spurs, muscle stiffness, capsule
stiffness) that may influence shoulder LJM. The full 3-dimensional kinematic descriptions of the humerus
and scapula during reaching was
beyond the scope of this article but
are reported elsewhere.43 Results
should not be generalized beyond
the characteristics of these study
groups. The DM group had relatively
good control of their diabetes (mean
HbA1c⫽6.9 [95% CI⫽6.4, 7.3]). Furthermore, individuals with a BMI
greater than 35 kg/m2 were
excluded due to documented problems obtaining their kinematic mea1118
f
Physical Therapy
Volume 95
surements.33 Therefore, this sample
does not fully represent the entire
population with diabetes, especially
those with poor control of their diabetes or severe obesity. Additionally,
control participants self-reported
their diabetes status and may have
had impaired glucose levels, especially those who had high BMI.
Therefore, the effect sizes observed
in this study may be different but
likely even greater in individuals
with worse glucose control or obesity compared with a control group
with documented exclusion of DM.
However, control participants were
screened by phone to exclude those
with shoulder pain to allow comparison of the group with DM to a fully
nonimpaired control group. Such an
exclusion criterion for the control
group may have overestimated the
deficits of the group with DM, but
we aimed to highlight this unique
group of people with DM at high risk
for LJM and subsequent shoulder
problems by comparing them with
an impairment-free control group.
As this was a cross-sectional study
design, we were not able to establish
a cause-effect relationship. Also, we
do not have information about the
temporal relationship of the risk of
diabetes and development of shoulder problems. Longitudinal studies
are needed to clarify the causal relationship of these variables. A single
therapist who was not blinded to
group status allows the potential for
measurement bias. This bias was
minimized by using highly standardized measures and methods. The
sample size was relatively small but,
due to large effect sizes, was conservatively powered to determine differences between individuals with
DM and those without DM. The sample size of participants with DM was
small for regression analysis in the
DM group. Additional prospective
studies with larger sample sizes are
necessary to confirm these findings
Number 8
and further clarify the relationships
outlined in Figure 1.
In summary, accumulation of AGEs
in the connective tissues of individuals with DM appears to be associated with increased tendon thickness and decreased shoulder joint
mobility and upper extremity function. Physical therapists should be
aware of these possible metabolic
effects on structure, movement, and
disability when treating people with
diabetes. These insights can help
focus future rehabilitation and pharmaceutical interventions on the
mechanisms of upper extremity
musculoskeletal problems in people
with DM and develop targeted strategies to treat them.
Dr Shah, Dr Clark, Dr McGill, Dr Lang, and
Dr Mueller provided concept/idea/research
design. All authors provided writing. Dr Shah
and Dr McGill provided data collection. Dr
Shah, Dr Clark, Dr Lang, and Dr Mueller
provided data analysis. Dr Shah and Dr
Mueller provided project management.
Dr Mueller provided fund procurement. Dr
McGill provided participants. Mr Maynard
and Dr Mueller provided facilities/equipment. Dr McGill and Dr Mueller provided
institutional liaisons. Dr McGill, Mr Maynard,
and Dr Mueller provided consultation
(including review of manuscript before submission). The authors thank Victor Cheuy,
Emily Martin, Lisa Simone, and Molly Burns
for helping with data collection and analysis.
Parts of this study were presented in abstract
form (podium) at the Combined Sections
Meeting of the American Physical Therapy
Association; January 4 – 6, 2014; Las Vegas,
Nevada.
This study was a part of Dr Shah’s doctoral
thesis presented to the Graduate School of
Arts and Sciences at the Washington University School of Medicine.
This study was supported by a grant from
the Research Division of the Program in
Physical Therapy, Washington University
School of Medicine, St Louis, Missouri; by
grant 1 R21 DK100793-01 from the National
Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health
(Dr Mueller); and by Diabetes Research and
Training Center (Grant No. P30 DK020579).
DOI: 10.2522/ptj.20140340
August 2015
References
1 Ramchurn N, Mashamba C, Leitch E, et al.
Upper limb musculoskeletal abnormalities
and poor metabolic control in diabetes.
Eur J Intern Med. 2009;20:718 –721.
2 Arkkila PE, Gautier JF. Musculoskeletal disorders in diabetes mellitus: an update. Best
Pract Res Clin Rheumatol. 2003;17:945–
970.
3 Arkkila PE. Hand and shoulder abnormalities in diabetic patients: association with
diabetes-related complications and diabetes [academic thesis]. Annales Universitatis Turkuensis 1996;244:1–136.
4 Laslett LL, Burnet SP, Redmond CL, McNeil
JD. Predictors of shoulder pain and shoulder disability after one year in diabetic outpatients. Rheumatology (Oxford). 2008;
47:1583–1586.
5 Larkin ME, Barnie A, Braffett BH, et al; and
the DCCT/EDIC Research Group. Musculoskeletal complications in type 1 diabetes. Diabetes Care. 2014;37:1863–1869.
6 Thomas SJ, McDougall C, Brown I, et al.
Prevalence of symptoms and signs of
shoulder problems in people with diabetes mellitus. J Shoulder Elbow Surg. 2007;
16:748 –751.
7 Tighe CB, Oakley WS Jr. The prevalence of
a diabetic condition and adhesive capsulitis of the shoulder. South Med J. 2008;101:
591–595.
8 Cole A, Gill TK, Shanahan EM, et al. Is diabetes associated with shoulder pain or
stiffness? Results from a population-based
study. J Rheumatol. 2009;36:371–377.
9 Pal B, Anderson J, Dick WC, Griffiths ID.
Limitation of joint mobility and shoulder
capsulitis in insulin and non-insulin dependent diabetes mellitus. Br J Rheumatol
1986;25:147–151.
10 Molsted S, Tribler J, Snorgaard O. Musculoskeletal pain in patients with type 2 diabetes. Diabetes Res Clin Pract. 2012;96:
135–140.
11 Mueller MJ, Diamond JE, Delitto A, Sinacore DR. Insensitivity, limited joint mobility, and plantar ulcers in patients with
diabetes mellitus. Phys Ther. 1989;69:
453– 459.
12 Silverstein JH, Gordon G, Pollock BH,
Rosenbloom AL. Long-term glycemic control influences the onset of limited joint
mobility in type 1 diabetes. J Pediatr.
1998;132:944 –947.
13 Schulte L, Roberts MS, Zimmerman C,
et al. A quantitative assessment of limited
joint mobility in patients with diabetes:
goniometric analysis of upper extremity
passive range of motion. Arthritis Rheum.
1993;36:1429 –1443.
14 Abate M, Schiavone C, Pelotti P, Salini V.
Limited joint mobility (LJM) in elderly subjects with type II diabetes mellitus. Arch
Gerontol Geriatr. 2011;53:135– 410.
15 Balci N, Balci MK, Tüzüner S. Shoulder
adhesive capsulitis and shoulder range of
motion in type II diabetes mellitus: association with diabetic complications. J Diabetes Complications. 1999;13:135–140.
August 2015
16 Brownlee M. Glycation products and the
pathogenesis of diabetic complications.
Diabetes Care. 1992;15:1835–1843.
17 Brik R, Berant M, Vardit P. The
scleroderma-like syndrome of insulindependent diabetes mellitus. Diabetes
Metab Rev. 1991;7:121–128.
18 Bai PM, Phua K, Hardt T, et al. Glycation
alters collagen fibril organization. Connect
Tissue Res. 1992;28:1–12.
19 Reddy GK. Cross-linking in collagen by
nonenzymatic glycation increases the
matrix stiffness in rabbit Achilles tendon.
Exp Diabesity Res. 2004;5:143–153.
20 Haus JM, Carrithers JA, Trappe SW,
Trappe TA. Collagen, cross-linking, and
advanced glycation end products in aging
human skeletal muscle. J Appl Physiol
(1985). 2007;103:2068 –2076.
21 Akturk M, Karaahmetoglu S, Kacar M, Muftuoglu O. Thickness of the supraspinatus
and biceps tendons in diabetic patients.
Diabetes Care. 2002;25:408.
22 Abate M, Schiavone C, Salini V. Sonographic evaluation of the shoulder in
asymptomatic elderly subjects with diabetes. BMC Musculoskelet Disord. 2010;7;
11:278.
23 Bunker TD, Anthony PP. The pathology of
frozen shoulder: a Dupuytren-like disease.
J Bone Joint Surg Br. 1995;77:677– 683.
24 Homsi C, Bordalo-Rodrigues M, Da Silva JJ,
Stump XM. Ultrasound in adhesive capsulitis of the shoulder: is assessment of the
coracohumeral ligament a valuable diagnostic tool? Skeletal Radiol. 2006;35:673–
678.
25 Conway BN, Aroda VR, Maynard JD, et al.
Skin intrinsic fluorescence correlates with
autonomic and distal symmetrical polyneuropathy in individuals with type 1 diabetes. Diabetes Care. 2011;34:1000 –
1005.
26 Maynard JD, Rohrscheib M, Way JF, et al.
Noninvasive type 2 diabetes screening:
superior sensitivity to fasting plasma glucose and A1C. Diabetes Care. 2007;30:
1120 –1124.
27 Cleary PA, Braffett BH, Orchard T, et al.
Clinical and technical factors associated
with skin intrinsic fluorescence in subjects
with type 1 diabetes from the Diabetes
Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study. Diabetes Technol Ther.
2013;15:466 – 474.
28 Verzijl N, DeGroot J, Thorpe SR, et al.
Effect of collagen turnover on the accumulation of advanced glycation end products.
J Biol Chem. 2000;275:39027–39031.
29 Aroda VR, Conway BN, Fernandez SJ, et al.
Cross-sectional evaluation of noninvasively detected skin intrinsic fluorescence
and mean hemoglobin A1C in type 1 diabetes. Diabetes Technol Ther. 2013;15:
117–123.
30 Conway BN, Aroda VR, Maynard JD, et al.
Skin intrinsic fluorescence is associated
with coronary artery disease in individuals with long duration of type 1 diabetes. Diabetes Care. 2012;35:2331–2336.
31 Conway BN, Edmundowicz D, Matter N,
et al. Skin fluorescence correlates strongly
with coronary artery calcification severity
in type 1 diabetes. Diabetes Technol Ther.
2010;12:339 –345.
32 Rosenbloom AL, Silverstein JH, Lezotte
DC, et al. Limited joint mobility in childhood diabetes indicates increased risk for
microvascular disease. N Engl J Med.
1981;305:191–194.
33 Hamming D, Braman JP, Phadke V, et al.
The accuracy of measuring glenohumeral
motion with a surface humeral cuff. J Biomech. 2012;45:1161–1168.
34 Wu G, Van der Helm FC, Veeger HE, et al;
International Society of Biomechanics. ISB
recommendation on definitions of joint
coordinate systems of various joints for
the reporting of human joint motion? Part
II: shoulder, elbow, wrist and hand. J Biomech. 2005;38:981–992.
35 Ludewig PM, Phadke V, Braman JP, et al.
Motion of the shoulder complex during
multiplanar humeral elevation. J Bone
Joint Surg Am. 2009;91:378 –389.
36 Bohannon RW. Reference values for
extremity muscle strength obtained by
hand-held dynamometry from adults aged
20 to 79 years. Arch Phys Med Rehabil.
1997;78:26 –32.
37 Hudak PL, Amadio PC, Bombardier C.
Development of an upper extremity outcome measure: the DASH (Disabilities of
the Shoulder, Arm and Hand). Am J Ind
Med. 1996;29:602– 608.
38 Shah KM, Clark BR, McGill JB, Mueller MJ.
Upper extremity impairments, pain and
disability in patients with diabetes mellitus. Physiotherapy. 2015;101:147–154.
39 Li Y, Fessel G, Georgiadis M, Snedeker JG.
Advanced glycation end-products diminish tendon collagen fiber sliding. Matrix
Biol. 2013;32:169 –177.
40 Kragstrup TW, Kjaer M, Mackey AL. Structural, biochemical, cellular, and functional
changes in skeletal muscle extracellular
matrix with aging. Scand J Med Sci Sports.
2011;21:749 –757.
41 Dalal M, Ferrucci L, Sun K, et al. Elevated
serum advanced glycation end products
and poor grip strength in older
community-dwelling women. J Gerontol A
Biol Sci Med Sci. 2009;64:132–137.
42 Momma H, Niu K, Kobayashi Y, et al. Skin
advanced glycation end product accumulation and muscle strength among adult
men. Eur J Appl Physiol. 2011;111:1545–
1552.
43 Shah KM, Clark BR, McGill JB, et al. Shoulder limited joint mobility in people with
diabetes mellitus. Clin Biomech (Bristol
Avon). 2015;30:308 –313.
Volume 95
Number 8
Physical Therapy f
1119
Research Report
Pragmatic Implementation of a
Stratified Primary Care Model for Low
Back Pain Management in Outpatient
Physical Therapy Settings: Two-Phase,
Sequential Preliminary Study
Jason M. Beneciuk, Steven Z. George
J.M. Beneciuk, PT, PhD, MPH,
Department of Physical Therapy,
University of Florida, PO Box
100154, Gainesville, FL 32610
(USA), and Brooks Rehabilitation–
College of Public Health and
Health
Professions
Research
Collaboration, Jacksonville, Florida. Address all correspondence
to
Dr
Beneciuk
at:
[email protected].
S.Z. George, PT, PhD, Department
of Physical Therapy, University of
Florida, and Brooks Rehabilitation–College of Public Health and
Health
Professions
Research
Collaboration.
[Beneciuk JM, George SZ. Pragmatic implementation of a stratified primary care model for low
back pain management in
outpatient physical therapy settings: two-phase, sequential preliminary
study.
Phys
Ther.
2015;95:1120 –1134.]
Association
April 9, 2015
Submitted: September 25, 2014
Background. The effectiveness of risk stratification for low back pain (LBP)
management has not been demonstrated in outpatient physical therapy settings.
Objective. The purposes of this study were: (1) to assess implementation of a
stratified care approach for LBP management by evaluating short-term treatment
effects and (2) to determine feasibility of conducting a larger-scale study.
Design. This was a 2-phase, preliminary study.
Methods. In phase 1, clinicians were randomly assigned to receive standard
(n⫽6) or stratified care (n⫽6) training. Stratified care training included 8 hours of
content focusing on psychologically informed practice. Changes in LBP attitudes and
beliefs were assessed using the Pain Attitudes and Beliefs Scale for Physiotherapists
(PABS-PT) and the Health Care Providers Pain and Impairment Relationship Scale
(HC-PAIRS). In phase 2, clinicians receiving the stratified care training were
instructed to incorporate those strategies in their practice and 4-week patient outcomes were collected using a numerical pain rating scale (NPRS), and the Oswestry
Disability Index (ODI). Study feasibility was assessed to identify potential barriers for
completion of a larger-scale study.
Results. In phase 1, minimal changes were observed for PABS-PT and HC-PAIRS
scores for standard care clinicians (Cohen d⫽0.00 – 0.28). Decreased biomedical
(⫺4.5⫾2.5 points, d⫽1.08) and increased biopsychosocial (⫹5.5⫾2.0 points,
d⫽2.86) treatment orientations were observed for stratified care clinicians, with
these changes sustained 6 months later on the PABS-PT. In phase 2, patients receiving
stratified care (n⫽67) had greater between-group improvements in NPRS (0.8 points;
95% confidence interval⫽0.1, 1.5; d⫽0.40) and ODI (8.9% points; 95% confidence
interval⫽4.1, 13.6; d⫽0.76) scores compared with patients receiving standard physical therapy care (n⫽33).
Limitations. In phase 2, treatment was not randomly assigned, and therapist
adherence to treatment recommendations was not monitored. This study was not
adequately powered to conduct subgroup analyses.
Conclusions. In physical therapy settings, biomedical orientation can be modified, and risk-stratified care for LBP can be effectively implemented. Findings from
this study can be used for planning of larger studies.
this article at:
ptjournal.apta.org
1120
f
Physical Therapy
Volume 95
Number 8
August 2015
Stratified Primary Care Model for Outpatient LBP Management
S
tratified care approaches for
low back pain (LBP) management are appealing because
they involve targeting treatment to
subgroups of patients based on key
characteristics (eg, psychological
factors).1 Recently, Hill and colleagues2 reported that a riskstratified primary care model (ie,
STarT Back approach) resulted in
greater improvements in clinical outcomes and cost savings when compared to current best practice for
patients with LBP. The effectiveness
of prognostic risk stratification for
LBP management has not been evaluated when initiated outside of primary care. Therefore, preliminary
studies are warranted to determine
feasibility of stratified care in secondary care settings and to provide estimates of effect sizes for a larger clinical trial.
Considering that not all patients will
enter the health care system through
primary care, there is a need to have
physical therapists who are adept in
implementing risk stratification
approaches for LBP management.
Psychologically informed physical
therapist practice is a secondary prevention approach for chronic LBP
that merges impairment-focused
physical therapy with cognitivebehavioral principles.3 The primary
goal of psychologically informed
physical therapist practice is prevention of future LBP-associated disability by emphasizing: (1) identification
of individuals who are at high risk for
developing chronic LBP based on the
presence of psychological distress
and (2) targeted treatment aimed at
psychological factors in conjunction
with traditional, impairment-based
physical therapy.3 Biomedical or
impairment-based perspectives are
predominantly emphasized during
the education and clinical practice of
many physical therapists, with little,
if any, content being provided from a
biopsychosocial
perspective.3– 8
Therefore, sustained clinician attiAugust 2015
tudes and beliefs toward biomedical
treatment orientations may serve
as a barrier for clinical practice
approaches that rely heavily on psychologically informed principles.4,9
Consequently, there is a need to evaluate whether implementation strategies for shifting clinicians’ attitudes
and beliefs to a biopsychosocial
treatment orientation9 are effective
for alignment with current conceptualization of pain experiences.10
Attempts at changing physical therapists’ attitudes and beliefs toward a
more biopsychosocial treatment orientation have provided mixed
results,11–16 with few studies
evaluating patient outcomes.12,14
Embedding psychological elements
into physical therapist management
strategies for LBP is associated with
several challenges, including uncertainty about education, implementation, and clinician culture.4 Prior to
embracing a stratified care approach
that consists of psychologically
informed practice principles, there
is a need to further investigate implementation strategies in physical therapy settings. First, there is a need to
evaluate training and education strategies geared toward increasing a biopsychosocial treatment orientation
for physical therapists. Second, there
is a need to evaluate if improved clinical outcomes are associated with
therapists who received stratified
care training following the training
for a biopsychosocial treatment
orientation.
and education strategies, and (3) estimates of training and education
effect on clinicians’ attitudes and
beliefs. For the second phase of this
study, our feasibility objectives were
to assess: (1) patient recruitment,
sampling methods, and follow-up
rates and (2) sample size estimations
that would allow for future subgroup
analyses. Providing estimates of stratified care treatment effect on shortterm clinical outcomes also was an
objective for the second phase of the
study. For exploratory purposes, we
compared stratified care and standard care groups by risk categorization for 4-week clinical outcomes to
provide preliminary subgroup estimates. The results of this study will
be used for planning of future studies that will determine if primary
care– based risk stratification strategies can be successfully translated to
secondary care settings.
Method
Design Overview
This was a 2-phase, sequential study
that evaluated feasibility and generated preliminary treatment effects
for 4-week clinical outcomes (Fig. 1).
The first phase consisted of clinician
training and education (February
2013–April 2013). The second phase
consisted of patient outcome collection from the previously trained clinicians (May 2013–February 2014).
All clinicians and patients were
selected from 7 outpatient physical
therapy clinics of Brooks Rehabilitation (Jacksonville, Florida).
Therefore, the primary purpose of
this study was to assess the feasibility
of biopsychosocially oriented stratified care in a physical therapy setting
and provide an estimate of the subsequent treatment effect on commonly used clinical outcomes for
LBP. For the first phase of this study,
our feasibility objectives were to
assess: (1) clinician recruitment and
sampling methods, (2) implementation of pragmatic clinician training
Volume 95
Available With
This Article at
ptjournal.apta.org
• eTable: Descriptive
Characteristics of Physical
Therapists
Number 8
Physical Therapy f
1121
Figure 1.
Flow diagram for 2-phase study. PABS-PT⫽Pain Attitudes and Beliefs Scale for Physical Therapists, HC-PAIRS⫽Health Care Providers’
Pain and Impairment Relationship Scale, LBP⫽low back pain.
Phase
1. Physical
therapists
(n⫽63) employed by a large rehabilitation health system who practiced
in an outpatient setting were
recruited by email to participate in
this study. The only criterion for participation was that therapists commonly evaluate and treat patients
with LBP. Twelve clinicians (19%)
1122
f
Physical Therapy
Volume 95
responded and were randomly
assigned to 1 of 2 groups (standard
care or stratified care) using a random number generator (http://
www.randomization.com)
with
blocked design to ensure an equal
number of clinicians in each group.
This randomization process resulted
Number 8
in 6 clinicians in each group (eTable,
available at ptjournal.apta.org).
Standard care group clinicians
attended 3 formal group meetings
over the course of 4 weeks, each
lasting approximately 60 minutes,
where they were provided with a
description of the study and received
August 2015
protocol training (eg, informed consent process, study packet review,
screening and outcome measure
administration). Stratified care group
clinicians received similar study
descriptions and protocol training;
however, they received an additional
8 hours of stratified care education.
Clinicians randomized to receive
stratified care education attended 3
sessions over the course of 4 weeks.
Each session was provided by the
study authors and lasted 2 to 4 hours
in duration. Educational content
(Appendix) focused on psychologically informed physical therapist
practice principles3 and was developed to reflect protocols that have
been used in previous studies,17–19
including both theoretical and clinical application components. The
overall objective of this multifactorial education approach was for clinicians to embrace the biopsychosocial model of pain and disability.20
As a component of stratified care
education, physical therapists were
trained on implementation of the
STarT Back approach for LBP management.2,21 The STarT Back
approach provides an example of
stratification based on prognostic
risk for persistent LBP-related disability that consists of 2 corresponding
components. First, patients are categorized into 1 of 3 subgroups (low,
medium, or high risk) for persistent
LBP-related disability using the
9-item STarT Back Screening Tool
(SBT), which consists of statements
about physical or psychological
prognostic factors that are considered modifiable with treatment.22
Second, suggested targeted treatment pathways are matched to each
SBT subgroup such that patients categorized as being at low risk receive
minimal care, primarily consisting of
reassurance and education. Patients
categorized as being at medium risk
also receive reassurance and education, but their treatment is suppleAugust 2015
mented with physical therapy
focused on restoring function and
targeting physical symptoms. For
patients categorized as being at high
risk, physical therapy is focused on
restoring function using a combination of physical and psychological
approaches. In addition, physical
therapists in the stratified care group
were educated on utilization of
the American Physical Therapy
Association (APTA) Orthopaedic
Section LBP clinical practice guidelines (CPGs),23 specifically for targeting physical symptoms and
impairments.
Validated questionnaires for attitudes and beliefs about LBP were
completed by all participating clinicians and administered before training, upon completion of training,
and 6 months later. Physical therapists’ attitudes and beliefs were measured using the Pain Attitudes and
Beliefs Scale for Physical Therapists
(PABS-PT)24 and the Health Care Providers’ Pain and Impairment Relationship Scale (HC-PAIRS).25
The PABS-PT consists of 19 items
about treatment orientation that are
rated using a 6-point Likert scale
ranging from “totally disagree” to
“totally agree.”24 The PABS-PT biomedical scale (10 items) has a potential score range from 10 to 60, and
the PABS-PT biopsychosocial scale (9
items) has a potential score range
from 9 to 54, with higher scores indicating increased treatment orientation for the respective scale. The
PABS-PT has been reported to have
fair-to-excellent levels of internal
consistency (Cronbach ␣ [biomedical scale: .77–.84, psychosocial
scale: .58 –.68]) and is responsive to
educational interventions.26
The original HC-PAIRS consisted of
15 items and was developed to
assess health care providers’ attitudes and beliefs about the relationship between LBP and physical func-
tion.27 We used a revised 13-item
version based on previous recommendations25 and removed the term
“chronic” from statements describing LBP.28,29 Responses to items are
rated using a 6-point Likert scale
ranging from “completely disagree”
to “completely agree.” This version
of the HC-PAIRS has a potential score
range from 13 to 78, with higher
scores indicating beliefs in a strong
relationship between pain and
impairment and attitudes that LBP
justifies disability and limitation of
activities. The HC-PAIRS has been
reported to have adequate levels of
internal consistency (Cronbach
␣⫽.78 –.84); however, its responsiveness to educational interventions
has not been adequately evaluated.30
Phase 2. The same group of physical therapists (n⫽12) who completed phase 1 of this study provided
treatment for patients with LBP that
was consistent with the type of training and education received.
The participants in this phase of the
study were consecutive patients
across 7 outpatient clinic locations
who were referred by a physician for
physical therapy for LBP and evaluated by a physical therapist and who
had completed phase 1 of the study.
The outpatient clinics were part of a
large rehabilitation system located in
the southeastern region of the
United States where physical therapy
treatment is provided for a wide
spectrum of musculoskeletal conditions. Physical therapists recruited
and screened all patients with LBP
for study eligibility prior to enrollment. Potential study participants
were consecutively recruited to
determine if the following criteria
were met before being enrolled in
the study: (1) between the ages of 18
and 65 years and seeking physical
therapy for LBP (defined as having
symptoms at T12 or lower, including
radiating pain into the buttocks and
lower extremity) and (2) ability to
Volume 95
Number 8
Physical Therapy f
1123
read and speak the English language.
Potential study participants were
ineligible to participate in this study
for any of the following: (1) the presence of systemic involvement
related to metastatic or visceral disease, (2) recent spinal fracture, (3)
osteoporosis, or (4) pregnancy. All
eligible patients were briefed on the
study, and informed consent was
obtained in compliance with the
University of Florida’s Institutional
Review Board.
Study participants were asked to
complete a standardized self-report
questionnaire consisting of questions related to age, sex, race, ethnicity,
education,
household
income, marital status, and employment status. Information involving
LBP clinical characteristics (ie, prior
surgery, symptom duration, symptom onset, symptom location, workrelated LBP) also was obtained.
The STarT Back Tool (SBT) consists
of 9 items related to physical and
psychosocial factors used to categorize patients with LBP in primary
care settings based on their risk for
poor future disability outcomes.22
The SBT overall scores (ranging from
0 to 9) are determined by summing
all positive responses, and SBT
psychosocial subscale scores (ranging from 0 to 5) are determined by
summing items related to bothersomeness, fear, catastrophizing, anxiety, and depression. Based on overall and psychosocial subscale
scoring, patients are categorized as
“high risk” (psychosocial subscale
scores ⱖ4), in which high levels of
psychosocial prognostic factors are
present, with or without physical
factors present; “medium risk” (overall score ⬎3; psychosocial subscale
score ⬍4), in which physical and
psychosocial factors are present but
not a high level of psychosocial factors; or “low risk” (overall score:
0 –3), in which few prognostic factors are present. The SBT has dem1124
f
Physical Therapy
Volume 95
onstrated adequate-to-high levels of
test-retest reliability,22 concurrent
validity,31 and predictive validity.32,33
For the current study, the SBT was
self-administered by all patients at
intake and 4 weeks later; however,
only physical therapists in the stratified care group were educated on
SBT scoring methods. Prior to beginning this study, the SBT was not used
in any of the clinics to assist with
initial treatment decision making.
Patients were not randomized to different treatment groups in this study.
Physical therapists in the standard
care group were instructed to provide treatment for patients with LBP
as they normally would have administered if not participating in this
study. Physical therapists in the stratified care group received an additional 8 hours of training and education consisting of content related to
psychologically informed physical
therapist practice principles3,17 and
APTA Orthopaedic Section LBP
CPGs.23 As a component of these
training experiences, clinicians were
directed to incorporate the knowledge and skills learned into subsequent management strategies for
their patients with LBP. Specifically,
we asked clinicians to utilize SBT categorization to guide initial treatment
decision making. For patients categorized as SBT low risk, we suggested a
minimal physical therapist intervention approach (1–2 sessions per
week) and adherence to the APTA
Orthopaedic Section CPGs. For
patients categorized as SBT medium
risk, we suggested an increased
physical
therapist
intervention
approach (2–3 sessions per week)
with adherence to the APTA Orthopaedic Section CPGs. For patients
categorized as SBT high risk, we suggested an increased physical therapist intervention approach (2–3 sessions per week) with adherence to
the APTA Orthopaedic Section CPGs
and psychologically informed practice principles previously learned as
Number 8
a component of prestudy training
(Appendix).
Self-report outcome measures were
collected at intake and 4 weeks later
and are described in more detail
below.
Pain intensity was rated using a
numerical pain rating scale (NPRS),
ranging from 0 (“no pain”) to 10
(“worst pain imaginable”). Participants were asked to rate their current pain intensity as well as their
best and worst levels of pain intensity over the previous 24 hours.
These 3 pain ratings were averaged
and used as the NPRS variable in this
study.34 The NPRS has been found to
have sound psychometric properties,34 –36 with a minimal clinically
important difference reported to be
2 points.37 A ⱖ30% improvement in
NPRS scores from baseline has been
recommended as a useful threshold
for identifying clinically meaningful
improvement for patients with
LBP.38 Therefore, reporting the proportion of patients achieving this
magnitude has been suggested.39
Low back pain–related disability was
assessed with a modified version of
the ODI, which has 10 items that
assess how LBP affects common
daily activities.40,41 The ODI has a
range of 0% (“no disability due to
LBP”) to 100% (“completely disabled
due to LBP”), with higher scores
indicating higher disability from LBP.
The ODI has been found to have
sound
psychometric
properties,40,42,43 with a reported minimal
clinically important difference of 10
percentage points.38 A ⱖ30%
improvement in ODI scores from
baseline has been recommended as a
useful threshold for identifying clinically meaningful improvement for
patients with LBP.38 Therefore,
reporting the proportion of patients
achieving this magnitude has been
suggested.39
August 2015
We analyzed and reported NPRS and
ODI data on a continuous scale (primary outcome) and on a binary scale
(secondary outcome) to generate
treatment effect estimates for future
study planning.
Data Analysis
All statistical analyses were performed using IBM SPSS version 21.0
(IBM Corp, Armonk, New York).
Descriptive statistics were used to
provide a summary of data. Point
estimates and 95% confidence intervals (95% CIs) were reported for
selected analyses based on previous
recommendations for evaluating
pilot study findings.44 We also incorporated hypothesis testing and
reported associated P values and
effect sizes for selected analyses to
provide preliminary estimates for
treatment effectiveness.45
Phase 1. Differences between clinician groups for demographic characteristics, PABS-PT (biomedical and
biopsychosocial
scale),
and
HC-PAIRS scores before training
were tested using independentsamples t tests (for continuous data)
and chi-square tests (for categorical
data). We used separate 2 ⫻ 3
repeated-measures analysis of variance (ANOVA) models to test for
relationships between training and
attitude and belief scores, with clinician group (standard or stratified
education) as the between-subjects
variable and time (before training,
upon completion of training, and 6
months later) as the within-subject
variable. For this study phase, we
were particularly interested in detection of a 2-way interaction between
time and clinician group to determine if clinicians who received stratified care education were associated
with changes in attitudes and beliefs
favoring a biopsychosocial treatment
approach. We also were interested
in determining if within-group
changes were observed immediately
following education intervention
August 2015
and if those changes were maintained 6 months later. Three separate repeated-measures ANOVA
models were used, with either
PABS-PT (biomedical or biopsychosocial) or HC-PAIRS scores serving as
the dependent variables.
Phase 2.
Differences between
patient groups for demographic and
clinical characteristics were tested
using independent-samples t tests
(for continuous data) and chi-square
tests (for categorical data). We used
separate 2 ⫻ 2 repeated-measures
ANOVA models to test for relationships between treatment approaches
and clinical outcome scores, with clinician group (standard or stratified
care) as the between-subjects variable and time (intake and 4 weeks)
as the within-subject variable. For
this study phase, we were particularly interested in detection of a
2-way interaction between time and
clinician group to determine if
patients who received treatment
from clinicians who received stratified care education were associated
with superior outcomes. Two separate repeated-measures ANOVA
models were used, with either NPRS
or ODI scores serving as the dependent variables. We calculated effect
sizes using the Cohen d coefficient
to provide an estimate of magnitude
between groups using the following
formula: [(stratified care group
change score ⫺ standard care group
change score)/pooled standard deviation], with an effect size of 0.2 considered small, 0.5 moderate, and 0.8
large.46
A proportional responder analysis
was performed to provide an indication of the percentage of patients
achieving clinically meaningful
improvement. A ⱖ30% improvement in NPRS and ODI scores from
baseline has been recommended as a
useful threshold for identifying clinically meaningful improvement for
patients with LBP.38 Therefore,
reporting the proportion of patients
achieving this magnitude has been
suggested.39 We also provided a full
range of cutoff scores to provide data
on the proportion of participants
achieving above and below 30%
improvement.
Percent
change
scores were calculated for both the
NPRS and ODI using the following
formula: [(initial score ⫺ 4-week
score)/initial score ⫻ 100]. Each
patient was then coded as having
“clinically meaningful improvement”
(percent change ⱖ30%) or “nonclinically meaningful improvement” (percent change ⬍30%) for NPRS and
ODI outcomes at 4 weeks. Relative
risk (RR) estimates were calculated
based on previous recommendations47 to compare clinically and
nonclinically meaningful improvement status between stratified and
standard care. A cumulative proportion responder analysis48,49 figure
was generated to describe the proportion of participants who experienced 4-week changes at each NPRS
and ODI threshold level or higher.
For planned exploratory analyses,
we compared stratified care and
standard care groups by SBT risk categorization for visit frequency and
4-week changes in NPRS and ODI
scores using independent-samples t
testing. Our rationale for these analyses was to provide preliminary findings related to: (1) SBT low-risk participant visit frequency based on
previous suggestions that overtreatment for patients categorized as SBT
low risk should be avoided1,2,21 and
(2) SBT high-risk participant outcomes because our stratified education content placed a strong emphasis on psychologically informed
practice.
Results
Phase 1
Physical therapists. A total of 12
physical therapists participated in
this study. There were no differences between clinician groups for
Volume 95
Number 8
Physical Therapy f
1125
Table 1.
PABS-PT and HC-PAIRS Scoresa
Group
Pretraining
(95% CI)
Posttraining
(95% CI)
6 mo (95% CI)
PABS-PT (biomedical)
Stratified care
28.5 (25.2, 31.8)
24.0 (18.7, 29.2)
23.0 (16.7, 29.2)
Standard care
26.7 (20.2, 33.1)
28.7 (20.4, 36.9)
26.7 (19.9, 33.3)
PABS-PT (biopsychosocial)
Stratified care
36.0 (33.6, 38.3)
41.5 (39.8, 43.2)
40.5 (36.3, 44.6)
Standard care
36.0 (31.6, 40.3)
36.7 (33.5, 39.8)
36.1 (31.4, 40.9)
HC-PAIRS
Stratified care
33.3 (27.9, 38.7)
28.0 (18.8, 37.1)
27.6 (18.1, 37.2)
Standard care
28.3 (20.9, 35.7)
28.7 (18.9, 38.3)
28.7 (18.4, 38.9)
Measure
a
All values are reported as mean point estimate (95% confidence interval). PABS-PT⫽Pain Attitudes and Beliefs Scale for Physical Therapists (biomedical
scale, potential range: 10 – 60), (biopsychosocial scale, potential range: 9 –54); HC-PAIRS⫽Health Care Providers’ Pain and Impairment Relationship Scale
(potential range: 13–78).
most demographic characteristics
and PABS-PT and HC-PAIRS scores
before training (eTable). The only
exception was that standard care
group clinicians were associated
with a higher number of years in
practice (X⫽10.1, SD⫽5.3) compared with stratified care group clinicians (X⫽4.4, SD⫽2.9), which
may have been influenced by 2 clinicians who had more than 15 years of
practice.
Physical therapists’ attitudes and
beliefs. Results from the repeatedmeasures ANOVA indicated statistically significant group ⫻ time interactions for PABS-PT biomedical scale
scores (F2,20⫽4.91, P⫽.018) and
PABS-PT
biopsychosocial
scale
scores (F2,20⫽4.95, P⫽.018). Compared with pretraining PABS-PT biomedical and biopsychosocial scores,
minimal changes were observed during posttraining assessment (biomedical: mean change⫽⫹2.0, SD⫽3.0,
Cohen d⫽0.28; biopsychosocial:
mean
change⫽⫹0.7,
SD⫽3.3,
Cohen d⫽0.19), with no changes
observed 6 months later (biomedical: mean change⫽0.0, SD⫽4.5,
Cohen d⫽0.0; biopsychosocial:
mean
change⫽⫹0.1,
SD⫽2.7,
Cohen d⫽0.02) for the clinician
group that did not receive stratified
care training (Tab. 1). For the stratified
care–trained
clinicians,
decreased PABS-PT biomedical scale
1126
f
Physical Therapy
Volume 95
scores
(mean
change⫽⫺4.5,
SD⫽2.5, Cohen d⫽1.08) and
increased biopsychosocial scale
scores
(mean
change⫽⫹5.5,
SD⫽2.0, Cohen d⫽2.86) were
observed during posttraining assessment, with these findings also maintained 6 months later (Tab. 1).
Results from the repeated-measures
ANOVA indicated no statistically significant group ⫻ time interactions
for HC-PAIRS scores (F2,20⫽2.62,
P⫽.097) or main effects (F2,20⫽2.06,
P⫽.154). Compared with pretraining HC-PAIRS scores, minimal
changes were observed during posttraining
assessment
(mean
change⫽⫹0.4, SD⫽4.4, Cohen
d⫽0.05) for the clinician group that
did not receive stratified care training, with these findings also maintained 6 months later (Tab. 1). For
the stratified care clinicians,
decreased HC-PAIRS scores (mean
change⫽⫺5.3, SD⫽6.4, Cohen
d⫽0.74) were observed during posttraining assessment, with these findings also maintained 6 months later
(Tab. 1).
Phase 2
During the study period, a total of
254 consecutive patients were
screened for eligibility to participate
in this study (Fig. 1). Of these
patients, 145 were excluded from
study participation, with the most
Number 8
common reason being that they
were older than 65 years of age
(n⫽91). Two patients were consulting with a lawyer due to workrelated LBP and refused to participate. The remaining 109 patients
provided informed consent and
were enrolled in the study. Of these
patients, 9 were not able to complete the study and provide 4-week
follow-up data due to personal reasons. Therefore, intake data were
obtained from 109 patients, and
4-week
follow-up
data
were
obtained from 100 patients.
Baseline demographic and clinical
data for the entire study sample are
presented in Table 2. Baseline characteristics were similar across treatment groups for all variables, with
the exception of the frequency of
participants reporting work-related
LBP (standard care: n⫽6, 15.3%;
stratified care: n⫽3, 14.3%), with 6
fully
employed,
2
part-time
employed, and 1 unemployed. An
approximately normal distribution
for initial pain intensity (NPRS
scores) and LBP-related disability
(ODI scores) was suggested based on
visual inspection of histograms and
normality plots.
Overall, the 4-week follow-up rate
was 91.7%, with differences
observed between groups (84.6%
standard care, 95.7% stratified care)
August 2015
Table 2.
Descriptive Characteristics of Study Samplea
Variable
Age (y)
Total Sample
(Nⴝ109)
Standard Care Group
(nⴝ39)
Stratified Care Group
(nⴝ70)
P
46.2 (12.2)
46.6 (11.2)
46.0 (12.8)
.821
64 (58.7)
22 (56.4)
42 (60.0)
.133
Sex, female, n (%)
Race
.987
Caucasian
83 (76.1)
30 (76.9)
53 (75.7)
Black or African American
20 (18.3)
7 (17.9)
13 (18.6)
6 (5.5)
2 (5.1)
4 (5.7)
Other
Employment status
.095
Employed
87 (79.8)
29 (74.4)
58 (82.9)
Unemployed
13 (11.9)
8 (20.5)
5 (7.1)
Retired
9 (8.3)
2 (5.1)
7 (10.0)
9 (8.3)
6 (15.3)
3 (4.3)
6 (5.5)
3 (7.7)
3 (4.3)
Subacute (15–90 d)
40 (36.7)
13 (33.3)
27 (38.6)
Chronic (ⱖ91 d)
63 (57.8)
23 (59.0)
40 (57.1)
Low
30 (27.5)
14 (35.9)
16 (22.9)
Medium
47 (43.1)
16 (41.0)
31 (44.2)
High
32 (29.4)
9 (23.1)
23 (32.9)
Work-related LBP (yes)
Symptom duration
.044
.694
Acute (ⱕ14 d)
SBT risk
.297
Outcome measure
NPRS
4.9 (2.0)
4.9 (2.1)
4.8 (1.9)
.676
ODI
33.5 (14.9)
34.7 (15.0)
32.8 (15.0)
.530
a
Estimates are provided as frequency count (%), with the exception of age and outcome measures, which are presented as mean (SD). LBP⫽low back pain,
SBT⫽STarT Back Tool, NPRS⫽numerical pain rating scale (potential range: 0 –10), ODI⫽Oswestry Disability Index (potential range: 0%–100%).
(P⫽.044). For participants who provided follow-up data, the average
number of physical therapy visits at
4 weeks was similar among groups
(X⫽6.3, SD⫽2.3, minimum⫽1, maximum⫽12) (P⫽.174). Four-week
physical therapy status also was similar at 4 weeks, with participants still
currently receiving physical therapy
(73.0%), having completed and were
discharged from physical therapy
(11.0%), or electing to not continue
with physical therapy (16.0%)
(P⫽.559).
Results from the repeated-measures
ANOVA indicated statistically significant group ⫻ time interactions for
4-week NPRS scores (F1,98⫽4.08,
P⫽.046, Cohen d⫽0.40) and ODI
August 2015
scores (F1,98⫽13.6, P⬍.001, Cohen
d⫽0.76) (Figs. 2A and 2B). From a
group perspective, participants who
received stratified care were associated with greater improvements in
NPRS scores (between-group difference⫽0.8 points; 95% CI⫽0.1, 1.5)
and ODI scores (between-group difference⫽9.0 percentage points; 95%
CI⫽4.1, 13.6) compared with those
who received standard care.
Achievement of ⱖ30% improvement
rates for NPRS and ODI scores following 4 weeks of physical therapy
is reported in Table 3. Thirty-nine
percent of the participants achieved
ⱖ30% improvement in NPRS scores,
with a greater proportion observed
for stratified care (47.8%) compared
with
standard
care
(21.2%)
(RR⫽2.25; 95% CI⫽1.11, 4.55). Fiftytwo percent of the participants
achieved ⱖ30% improvement in ODI
scores, with a greater proportion
observed for stratified care (61.2%)
compared with standard care
(33.3%) (RR⫽1.84; 95% CI⫽1.10,
3.08). Interpretation of the cumulative distribution of responders based
on NPRS scores (Fig. 3A) and ODI
scores (Fig. 3B) indicates a similar
trend, with a greater proportion of
participants who received stratified
care compared with those who
received standard care achieving
improvement for a range of threshold change scores.
Volume 95
Number 8
Physical Therapy f
1127
95% CI⫽⫺1.1, 2.2) or ODI scores
(9.8 percentage points; 95%
CI⫽⫺3.8, 23.4); however, changes
in ODI scores alone (16.7 percentage
points; 95% CI⫽10.2, 23.2) favored
stratified care at 4 weeks.
Discussion
Figure 2.
Changes in (A) pain intensity scores and (B) ODI scores. ODI⫽Oswestry Disability Index,
NPRS⫽numerical pain rating scale. Error bars represent 1 standard error of the mean.
For exploratory analyses, we used
independent-samples t tests to compare frequency of visits and changes
in NPRS and ODI scores following 4
weeks of physical therapy between
treatment groups by SBT risk categorization (Tab. 3). For participants categorized as SBT low risk, there were
no differences between groups in
the mean number of treatment sessions (stratified care group: X⫽6.5,
SD⫽1.7; standard care group:
X⫽6.6, SD⫽2.2). There were no
between-group
differences
for
changes in NPRS scores (0.1 points;
95% CI⫽⫺1.3, 1.2) or ODI scores
CI⫽⫺3.0, 11.4); however, changes
in ODI scores alone (10.4 percentage
points; 95% CI⫽5.0, 15.9) favored
1128
f
Physical Therapy
Volume 95
stratified care at 4 weeks. For participants categorized as SBT medium
risk, there were no differences
between groups in the number of
treatment sessions (stratified care
group: X⫽6.3, SD⫽2.5; standard
care group: X⫽5.9, SD⫽2.3).
Between-group
differences
for
95% CI⫽0.2, 2.6) and ODI scores
CI⫽5.1, 17.8) favored stratified care
at 4 weeks. For participants categorized as SBT high risk, those who
received stratified care had more visits (X⫽6.9, SD⫽2.1) compared with
those who received standard care
(X⫽4.6, SD⫽2.2). There were no
between-group
differences
for
Number 8
This study investigated the feasibility
of a risk stratification approach for
LBP management that was initially
implemented outside of primary
care, and the results were favorable
for the translation to physical therapy settings. In addition, we generated estimates of treatment effects
based on 4-week clinical outcomes
that may be helpful for planning of
future studies. Specifically, our findings demonstrated that clinician biomedical treatment orientations can
be modified and that patients who
received stratified physical therapy
care were associated with greater
improvement compared with those
who received standard physical therapy care. Furthermore, there was a
greater cumulative proportion of
positive pain intensity and disability
responders among patients who
received stratified care compared
with those who received standard
care. Collectively, these findings suggest that physical therapists’ attitudes and beliefs can be changed and
maintained toward a biopsychosocially oriented treatment approach
and that those changes may positively influence patient clinical outcomes when combined with a
stratified care approach. To our
knowledge, this is the first study conducted in the United States that has
shown favorable clinical outcomes
using risk-stratified care in combination with guideline recommendations in settings outside of primary
care.
Feasibility Issues–Phase 1
Several feasibility issues may aid in
planning future studies. First, alternative clinician recruitment methods
may be needed to generate a more
August 2015
Table 3.
Changes in NPRS and ODI Scores Following 4 Weeks of Physical Therapya
SBT Risk Categorization
Total Sample
Low Risk
Medium Risk
High Risk
Stratified care
Variable
N⫽67
n⫽15
n⫽31
n⫽21
Standard care
N⫽33
n⫽14
n⫽12
n⫽7
Stratified care
6.5⫾2.2
6.5⫾1.7
6.3⫾2.5
6.9⫾2.1
Standard care
5.9⫾2.3
6.6⫾2.2
5.9⫾2.3
4.6⫾2.2
Number of visits
NPRS
Stratified care
1.4 (1.1, 2.0)
0.8 (0.2, 1.6)
1.7 (1.0, 2.4)
Standard care
0.7 (0.1, 1.3I)
0.9 (⫺0.2, 2.0)
0.2 (⫺0.9, 1.3)
0.9 (⫺0.9, 2.0)
Between-group
difference
0.8 (0.1, 1.5)
0.1 (⫺1.3, 1.2)
1.4 (0.2, 2.6)
0.6 (⫺1.1, 2.2)
0.40
0.06
Effect sizeb
1.5 (0.8, 2.4)
0.86
0.31
ⱖ30% improvement
Stratified care
47.8%
Standard care
21.2%
P⫽.010
26.7%
P⫽.909
28.6%
64.5%
P⫽.005
16.7%
38.1%
P⫽.243
14.3%
ODI
Stratified care
13.2 (10.6, 16.0)
10.4 (5.0, 15.9)
12.3 (9.4, 15.2)
16.7 (10.2, 23.2)
Standard care
4.4 (0.3, 8.7)
6.1 (1.0, 11.3)
0.8 (⫺6.8, 8.4)
6.8 (⫺9.7, 23.0)
Between-group
difference
8.9 (4.1, 13.6)
4.2 (⫺3.0, 11.4)
11.5 (5.1, 17.8)
9.8 (⫺3.8, 23.4)
0.76
0.46
Effect sizeb
1.14
0.61
ⱖ30% improvement
Stratified care
61.2%
Standard care
33.3%
P⫽.009
53.3%
42.9%
P⫽.573
71.0%
P⬍.001
16.7%
52.4%
P⫽.663
42.9%
a
Values are reported as mean (95% confidence interval), unless otherwise indicated. Number of visits are reported as mean⫾SD. NPRS⫽numerical pain
rating scale, ODI⫽Oswestry Disability Index, SBT⫽STarT Back Tool.
Effect sizes (Cohen d) were calculated using the following formula: [(stratified care group change score – standard care group change score)/pooled
standard deviation].
b
diverse pool of physical therapists.
For example, we used email to
recruit potentially interested physical therapists, and a majority of the
physical therapists who participated
were residency or fellowship
trained. In the future, we plan to
provide brief in-service presentations at several clinical sites to
describe potential research opportunities with the intent to improve clinician and researcher engagement
and recruit a more heterogeneous
group of physical therapists. Second,
using the PABS-PT and HC-PAIRS as
measures for educational intervention responsiveness appears to be
appropriate based on the direction
August 2015
of changes observed; however, interpreting the magnitudes of change
still warrants further investigation.
For future study planning, we will
consider analyses that evaluate relationships between magnitude of
changes in PABS-PT and HC-PAIRS
scores and clinical outcome scores.
Finally, in retrospect, our educational intervention for clinicians may
be improved by including more
in-depth
content
related
to
cognitive-behavioral principles that
is provided by a clinical psychologist
and including follow-up mentoring
sessions.9,50
Physical Therapists’
Attitudes and Beliefs
We expected that adaptions toward
less biomedical and more biopsychosocial treatment orientation would
be observed for clinicians who
received 8 hours of training and education focusing on psychologically
informed physical therapist practice
principles. Pretraining PABS-PT biomedical (X⫽28.1, SD⫽4.9) and biopsychosocial (X⫽36.2, SD⫽3.2)
scores observed in this study were
similar to those of previous studies11,15; however, HC-PAIRS scores
(X⫽30.5, SD⫽6.2) were lower
compared with findings of previous
studies that involved physical thera-
Volume 95
Number 8
Physical Therapy f
1129
of the current study. Our findings
indicate that training periods for
belief changing can be shortened
from what was previously reported
in the literature. The clinical meaningfulness of changes in PABS-PT and
HC-PAIRS scores remains unclear
and warrants further investigation.11,26,30 The findings from phase
2 of this study, however, provide a
preliminary indication that these
changes in beliefs and attitudes were
potentially sufficient to affect clinical
outcomes for patients who received
stratified care education.
Figure 3.
(A) Cumulative proportion of responders for 4-week pain intensity outcomes highlighting 47.8% of stratified care group (21.2% of standard care group) achieved at least
30% improvement in numerical pain rating scale (NPRS) (potential range: 0 –10).
Nonpositive responders for NPRS changes (ie, less than 0%) are not indicated in the
figure. (B) Cumulative proportion of responders for 4-week pain disability outcomes
highlighting 61.2% of stratified care group (33.3% of standard care group) achieved at
least 30% improvement in Oswestry Disability Index (ODI) scores (potential range:
0%–100%). Nonpositive responders for ODI changes (ie, less than 0%) are not indicated in the figure.
pists.11,29 Although the responsiveness of the PABS-PT and HC-PAIRS
has not been extensively evaluated,26,30 within-group changes in
PABS-PT biomedical (⫺4.5 points)
and biopsychosocial (⫹5.5 points)
scores and HC-PAIRS scores (⫺5.3
points) observed in this study for
stratified care clinicians are consistent with the findings of previous
1130
f
Physical Therapy
Volume 95
studies that incorporated similar biopsychosocially oriented training programs.11,15 For example, a previous
study11 investigating the effect of an
8-day biopsychosocially oriented
course netted similar improvements
and maintenance of beliefs that were
measured using the PABS-PT and
HC-PAIRS, although the findings varied slightly in magnitude from those
Number 8
Feasibility Issues–Phase 2
The findings of phase 2 of this study
also will inform planning of future
studies. First, to allow for appropriately powered subgroup analyses,
the number of patients categorized
as SBT high risk needs to be considered. For example, 29% of the
patients in this study were initially
categorized as SBT high risk, and previous studies32,33 conducted in similar settings have indicated between
19% and 26%. For future study analyses, we will need to consider determining sample size calculations
based on multiple hypothesis tests
comparing stratified care and standard care by SBT categorization, similar to previous study protocols.21,51
We observed differences in clinical
outcomes between stratified and
standard care that were driven by
SBT medium-risk categorization in
our cohort (Tab. 3), which is not
consistent with previous study findings of higher benefit for patients at
high risk.2,52 One potential strategy
to consider for future studies is to
power differences in clinical outcome scores between medium and
low risk or high and low risk, as the
ability to detect differences between
medium and high risk may be more
difficult.
Second, the influence of treatment
visits on clinical outcomes will need
to be accounted for in future analyAugust 2015
ses, particularly if we are suggesting
a minimal treatment approach for
patients categorized as SBT low risk.
Finally, implementation of our stratified care approach could be
improved on several levels. For
example, we recommended a minimal physical therapist intervention
approach consisting of 1 or 2 treatment visits per week for patients at
low risk who are receiving stratified
care; however, similar rates were
observed for stratified and standard
care groups at 4 weeks. During
future study planning, we will better
structure clinician adherence for
treatment of patients at low risk. We
also will incorporate consistent mentoring sessions between clinicians
and researchers during training and
active study time periods that will
provide opportunities to address
potential barriers to implementation.
Estimates of Treatment Effects
for Clinical Outcomes
Greater improvements in LBP clinical outcomes at 4 weeks were
observed in patients who received
physical therapy following a stratified care management approach.
Further inspection of pain and disability outcomes indicated betweengroup differences favoring stratified
care, with associated small (Cohen
d⫽0.40) and moderate (Cohen
d⫽0.76) effect sizes, respectively.
These results are similar to 4-month
findings of the larger STarT Back
trial2 that compared stratified care
(n⫽568) with current best practice
(n⫽283) in UK primary care settings.
In that study, Hill et al2 reported
between-group differences for NPRS
and Roland-Morris Disability Questionnaire scores favoring stratified
care, with smaller respective (Cohen
d⫽0.24 and 0.29) effect sizes. Specifically related to patients categorized as SBT high risk, we observed a
large effect size (0.61) for improvements in ODI scores favoring stratified care; however, we acknowledge
August 2015
that this study was not powered for
subgroup analyses. Patients at SBT
high risk who received stratified care
had more visits (6.9) compared with
those who received standard care
(4.6), suggesting the beneficial
effects may have been due to
extended treatment and increased
attention as designed by psychologically informed practice. Collectively,
these findings provide continuing
evidence that stratified care with
SBT categorization has the potential
to improve LBP outcomes when
combined with psychologically
informed practice.
We also incorporated a proportional
responder analysis to determine if
different
statistical
approaches
would provide variations in the
appraisal of our clinical outcomes
data. The analysis of treatment
response using previously suggested
thresholds (ie, ⱖ30% improvement)
for clinically important changes in
NPRS and ODI scores provided similar results. A greater percentage of
patients in the stratified care group
achieved the clinically relevant
change threshold for NPRS (47.8%)
and ODI (61.2%) scores compared
with the standard care group (21.2%
and 33.3%, respectively). These differences were not trivial, as patients
who received stratified care were
approximately 2 times more likely to
achieve ⱖ30% improvement on the
pain intensity and disability measures. Furthermore, compared with
the standard care group, there was a
consistent trend for a higher cumulative percentage of patients in the
stratified care group who achieved a
wide range of NPRS (Fig. 3A) and
ODI (Fig. 3B) thresholds for
improvement across the continuum,
potentially providing further validation for the outcomes reported in
this study. The greatest percentage
of positive responders observed in
the current study (71.0%) and the
STarT Back trial (71.0%) were
patients at SBT medium risk who
received stratified care. Several factors need to be considered prior to
interpreting these findings related to
treatment response. For example,
treatment response in this study was
based on 4-week clinical outcomes;
however, 73.0% of the patients were
still receiving physical therapy care
at that time. Therefore, we cannot
speculate on long-term implications.
Strengths and Limitations
One strength of this study is that
there was a planned combination of
internal (phase 1) and external
(phase 2) validity. Clinicians were
randomized to different training and
education groups during phase 1,
and we intentionally incorporated a
pragmatic approach to be consistent
with typical clinical management for
LBP during phase 2. Neither stratified care nor standard care clinicians
were required to follow rigid treatment protocols for patients with
LBP. Rather, clinicians utilized the
knowledge and strategies learned
during training sessions (stratified
care group) or their normal management strategies (standard care
group) for patients with LBP.
Another strength of the study is that,
compared with previous studies,2
the stratified care education content
provided was brief, but similar outcomes were obtained. Previous studies53,54 have indicated that one of the
most significant barriers to attending
postprofessional education courses
is time. Therefore, it was our intent
to provide the necessary education
for this study in reasonable intervals
that also accommodated clinicians’
schedules (ie, 8 hours over multiple
sessions) in order to improve retention rates and be consistent with our
pragmatic approach.
This study also had several limitations that have not already been
mentioned. First, most physical therapists participating in this study
were either orthopedic residency
trained (n⫽11, 91.7%) or manual
Volume 95
Number 8
Physical Therapy f
1131
therapy fellowship trained (n⫽8,
66.7%), or both (n⫽8, 66.7%), which
may limit the generalizability of
these findings. In addition, only 12 of
63 eligible physical therapists (19%)
volunteered to participate in this
study; therefore, the influence of volunteer bias should be considered,
which also may limit the generalizability of these findings. However,
the overall influence of this bias was
likely minimized by randomly assigning therapists to training groups (ie,
stratified or standard care). Second,
patients older than 65 years were not
eligible to participate in this study,
which may limit the generalizability
of our findings, especially considering that 35.8% of the patients were
not eligible based on the age criterion. In addition, 2 patients were
consulting with a lawyer due to
work-related LBP and refused to participate. Future studies are needed to
determine if the risk-stratified care
approach used in this study is generalizable across all age groups and for
individuals receiving work-related
disability. Third, in phase 2, patients
were not randomized to different
treatment groups in this observational study, nor did we assess for
clinician selection bias of patients;
therefore, our outcome findings
should be interpreted with caution.
Planning of future larger-scale studies (eg, comparative effectiveness
research) may not necessarily
require randomization of patients to
treatment groups, particularly if the
intent is for pragmatic implementation in routine clinical practice.55
Finally, 4-week outcomes provide a
short-term perspective on the
impact of patient management. Ideally, longer follow-up data would
have been available.
apy settings. However, estimates of
specific treatment effects for the
clinical outcomes reported in this
article should be interpreted with
caution based on this study design.
Findings from this preliminary study
can be used for planning of future
studies that more definitively determine the impact of stratified care on
patient outcomes.
Clinical Implications
Overall, our results indicated that
implementation of stratified care
based on the STarT Back approach
and APTA Orthopaedic Section CPGs
is feasible in outpatient physical ther-
4 Foster NE, Delitto A. Embedding psychosocial perspectives within clinical management of low back pain: integration of psychosocially
informed
management
principles into physical therapist practice— challenges and opportunities. Phys
Ther. 2011;91:790 – 803.
1132
f
Physical Therapy
Volume 95
Both authors provided concept/idea/research design and writing. Dr Beneciuk provided data collection and analysis, project
management, and fund procurement. Dr
George provided consultation (including
review of manuscript before submission).
The authors acknowledge the following clinicians from Brooks Rehabilitation in Jacksonville, Florida: Trent Harrison, Renata Salvatori, Monika Beneciuk, Raine Osborne,
Brian Hagist, Tasha Mouton, Timothy
Shreve, Jenny Hagist, Sara Cristello, Sara Bertrand, Nate Moore, and Steve Pompilio. The
authors also acknowledge the following
administrative personnel from Brooks Rehabilitation: Douglas Baer, Michael Spigel,
Amanda Osborne, Victor Derienzo, Robert
Rowe, Holly Morris, Flo Singletary, and Mallorey Smith.
This study was funded by the 2012 Brooks
Rehabilitation Collaborative Grant. The manuscript was written while Dr Beneciuk
received support from the National Institutes
of Health Rehabilitation Research Career
Development Program (K12-HD055929).
DOI: 10.2522/ptj.20140418
References
5 Smart K, Doody C. The clinical reasoning
of pain by experienced musculoskeletal
physiotherapists. Man Ther. 2007;12:40 –
49.
6 Daykin AR, Richardson B. Physiotherapists’ pain beliefs and their influence on
the management of patients with chronic
low back pain. Spine (Phila Pa 1976).
2004;29:783–795.
7 Bishop A, Foster NE. Do physical therapists in the United kingdom recognize psychosocial factors in patients with acute
low back pain? Spine (Phila Pa 1976).
2005;30:1316 –1322.
8 Simmonds MJ, Derghazarian T, Vlaeyen
JW. Physiotherapists’ knowledge, attitudes, and intolerance of uncertainty influence decision making in low back pain.
Clin J Pain. 2012;28:467– 474.
9 Sanders T, Foster NE, Bishop A, Ong BN.
Biopsychosocial care and the physiotherapy encounter: physiotherapists’ accounts
of back pain consultations. BMC Musculoskel Disord. 2013;14:65.
10 Institute of Medicine. Relieving Pain in
America: A Blueprint for Transforming
Prevention, Care, Education, and
Research. Washington, DC: The National
Academies Press; 2011.
11 Overmeer T, Boersma K, Main CJ, Linton
SJ. Do physical therapists change their
beliefs, attitudes, knowledge, skills and
behaviour after a biopsychosocially orientated university course? J Eval Clin Pract.
2009;15:724 –732.
12 Overmeer T, Boersma K, Denison E, Linton SJ. Does teaching physical therapists
to deliver a biopsychosocial treatment
program result in better patient outcomes:
a randomized controlled trial. Phys Ther.
2011;91:804 – 819.
13 Demmelmaier I, Denison E, Lindberg P,
Asenlof P. Tailored skills training for practitioners to enhance assessment of prognostic factors for persistent and disabling
back pain: four quasi-experimental singlesubject studies. Physiother Theory Pract.
2012;28:359 –372.
1 Foster NE, Hill JC, O’Sullivan P, Hancock
M. Stratified models of care. Best Pract Res
Clin Rheumatol. 2013;27:649 – 661.
14 Sullivan MJ, Adams H, Rhodenizer T, Stanish WD. A psychosocial risk factor: targeted intervention for the prevention of
chronic pain and disability following
whiplash injury. Phys Ther. 2006;86:8 –18.
2 Hill JC, Whitehurst DG, Lewis M, et al.
Comparison of stratified primary care
management for low back pain with current best practice (STarT Back): a randomised controlled trial. Lancet. 2011;
378:1560 –1571.
15 Vonk F, Pool JJ, Ostelo RW, Verhagen AP.
Physiotherapists’ treatment approach
towards neck pain and the influence of a
behavioural graded activity training: an
exploratory study. Man Ther. 2009;14:
131–137.
3 Main CJ, George SZ. Psychologically
informed practice for management of low
back pain: future directions in practice
and research. Phys Ther. 2011;91:820 –
824.
16 Domenech J, Sanchez-Zuriaga D, SeguraOrti E, et al. Impact of biomedical and biopsychosocial training sessions on the attitudes, beliefs, and recommendations of
health care providers about low back pain:
a randomised clinical trial. Pain. 2011;
152:2557–2563.
Number 8
17 Main CJ, Sowden G, Hill JC, et al. Integrating physical and psychological approaches
to treatment in low back pain: the development and content of the STarT Back
trial’s “high-risk” intervention (StarT Back;
ISRCTN 37113406). Physiotherapy. 2012;
98:110 –116.
August 2015
18 Moseley GL, Nicholas MK, Hodges PW. A
randomized controlled trial of intensive
neurophysiology education in chronic low
back pain. Clin J Pain. 2004;20:324 –330.
19 Louw A, Puentedura EL, Mintken P. Use of
an abbreviated neuroscience education
approach in the treatment of chronic low
back pain: a case report. Physiother Theory Pract. 2012;28:50 – 62.
20 Pincus T, Kent P, Bronfort G, et al.
Twenty-five years with the biopsychosocial model of low back pain—is it time to
celebrate: a report from the Twelfth International Forum for Primary Care Research
on Low Back Pain. Spine (Phila Pa 1976).
2013;38:2118 –2123.
21 Hay EM, Dunn KM, Hill JC, et al. A randomised clinical trial of subgrouping and
targeted treatment for low back pain compared with best current care: the STarT
Back Trial Study Protocol. BMC Musculoskelet Disord. 2008;9:58.
22 Hill JC, Dunn KM, Lewis M, et al. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum. 2008;59:632– 641.
23 Delitto A, George SZ, Van Dillen LR, et al.
Low back pain. J Orthop Sports Phys Ther.
2012;42:A1–A57.
24 Houben RM, Ostelo RW, Vlaeyen JW, et al.
Health care providers’ orientations
towards common low back pain predict
perceived harmfulness of physical activities and recommendations regarding
return to normal activity. Eur J Pain.
2005;9:173–183.
25 Houben RM, Vlaeyen JW, Peters M, et al.
Health care providers’ attitudes and beliefs
towards common low back pain: factor
structure and psychometric properties of
the HC-PAIRS. Clin J Pain. 2004;20:37–
44.
26 Mutsaers JH, Peters R, Pool-Goudzwaard
AL, et al. Psychometric properties of the
pain attitudes and beliefs scale for physiotherapists: a systematic review. Man Ther.
2012;17:213–218.
27 Rainville J, Bagnall D, Phalen L. Health
care providers’ attitudes and beliefs about
functional impairments and chronic back
pain. Clin J Pain. 1995;11:287–295.
28 Evans DW, Foster NE, Underwood M, et al.
Testing the effectiveness of an innovative
information package on practitioner
reported behaviour and beliefs: the UK
Chiropractors, Osteopaths and Musculoskeletal Physiotherapists Low back pain
ManagemENT
(COMPLeMENT)
trial
[ISRCTN77245761]. BMC Musculoskelet
Disord. 2005;6:41.
29 Evans DW, Breen AC, Pincus T, et al. The
effectiveness of a posted information
package on the beliefs and behavior of
musculoskeletal practitioners: the UK Chiropractors, Osteopaths, and Musculoskeletal Physiotherapists Low Back Pain ManagemENT (COMPLeMENT) randomized
trial. Spine (Phila Pa 1976). 2010;35:
858 – 866.
August 2015
30 Bishop A, Thomas E, Foster NE. Health
care practitioners’ attitudes and beliefs
about low back pain: a systematic search
and critical review of available measurement tools. Pain. 2007;132:91–101.
31 Hill JC, Dunn KM, Main CJ, Hay EM. Subgrouping low back pain: a comparison of
the STarT Back Tool with the Örebro Musculoskeletal Pain Screening Questionnaire.
Eur J Pain. 2010;14:83– 89.
32 Fritz JM, Beneciuk JM, George SZ. Relationship between categorization with the
STarT Back Screening Tool and prognosis
for people receiving physical therapy for
low back pain. Phys Ther. 2011;91:722–
732.
33 Beneciuk JM, Bishop MD, Fritz JM, et al.
The STarT Back Screening Tool and individual psychological measures: evaluation
of prognostic capabilities for low back
pain clinical outcomes in outpatient physical therapy settings. Phys Ther. 2013;93:
321–333.
34 Jensen MP, Turner LR, Turner JA, Romano
JM. The use of multiple-item scales for
pain intensity measurement in chronic
pain patients. Pain. 1996;67:35– 40.
35 Jensen MP, Turner JA, Romano JM, Fisher
LD. Comparative reliability and validity of
chronic pain intensity measures. Pain.
1999;83:157–162.
36 Bolton JE. Accuracy of recall of usual pain
intensity in back pain patients. Pain. 1999;
83:533–539.
37 Childs JD, Piva SR, Fritz JM. Responsiveness of the numeric pain rating scale in
patients with low back pain. Spine (Phila
Pa 1976). 2005;30:1331–1334.
38 Ostelo RW, Deyo RA, Stratford PW, et al.
Interpreting change scores for pain and
functional status in low back pain:
towards international consensus regarding
minimal important change. Spine (Phila
Pa 1976). 2008;33:90 –94.
39 Deyo RA, Dworkin SF, Amtmann D, et al.
Report of the NIH Task Force on research
standards for chronic low back pain. J
Pain. 2014;15:569 –585.
40 Fritz JM, Irrgang JJ. A comparison of a
modified Oswestry Low Back Pain Disability Questionnaire and the Quebec Back
Pain Disability Scale [erratum in: Phys
Ther. 2008;88:138 –139]. Phys Ther. 2001;
81:776 –788.
41 Hudson-Cook N, Tomes-Nicholson K,
Breen A. A revised Oswestry disability
questionnaire. In: Roland MO, Jenner JR,
eds. Back Pain: New Approaches to Rehabilitation and Education. New York, NY:
Manchester University Press; 1989:187–
204.
43 Roland M, Fairbank JC. The Roland-Morris
Disability Questionnaire and the Oswestry
Disability Questionnaire [erratum in:
Spine (Phila Pa 1976). 2001;26:847].
Spine (Phila Pa 1976). 2000;25:3115–
3124.
44 Thabane L, Ma J, Chu R, et al. A tutorial on
pilot studies: the what, why and how.
BMC Med Res Methodol. 2010;10:1.
45 Moore CG, Carter RE, Nietert PJ, Stewart
PW. Recommendations for planning pilot
studies in clinical and translational
research. Clin Transl Sci. 2011;4:332–337.
46 Cohen J. A power primer. Psychol Bull.
1992;112:155–159.
47 Portney LG, Watkins MP. Foundations of
Clinical Research: Applications to Practice. 3rd ed. Upper Saddle River, NJ: Prentice Hall; 2009.
48 McLeod LD, Coon CD, Martin SA, et al.
Interpreting patient-reported outcome
results: US FDA guidance and emerging
methods. Expert Rev Pharmacoecon Outcomes Res. 2011;11:163–169.
49 Farrar JT, Dworkin RH, Max MB. Use of
the cumulative proportion of responders
analysis graph to present pain data over a
range of cut-off points: making clinical
trial data more understandable. J Pain
Symptom Manage. 2006;31:369 –377.
50 Nielsen M, Keefe FJ, Bennell K, Jull GA.
Physical therapist-delivered cognitivebehavioral therapy: a qualitative study of
physical therapists’ perceptions and experiences. Phys Ther. 2014;94:197–209.
51 Foster NE, Mullis R, Young J, et al. IMPaCT
Back study protocol; implementation of
subgrouping for targeted treatment systems for low back pain patients in primary
care: a prospective population-based
sequential comparison. BMC Musculoskelet Disord. 2010;11:186.
52 Foster NE, Mullis R, Hill JC, et al. Effect of
stratified care for low back pain in family
practice (IMPaCT Back): a prospective
population-based sequential comparison.
Ann Fam Med. 2014;12:102–111.
53 Chau J, Chadbourn P, Hamel R, et al. Continuing education for advanced manual
and manipulative physiotherapists in Canada: a survey of perceived needs. Physiother Can. 2012;64:20 –30.
54 Sran MM, Murphy S. Postgraduate physiotherapy training: interest and perceived
barriers to participation in a clinical master’s degree programme. Physiother Can.
2009;61:234 –243.
55 Horn SD, Gassaway J. Practice-based evidence study design for comparative effectiveness research. Med Care. 2007;45(10
suppl 2):S50 –S57.
42 Fairbank JC, Pynsent PB. The Oswestry
Disability Index. Spine (Phila Pa 1976).
2000;25:2940 –2952.
Volume 95
Number 8
Physical Therapy f
1133
Appendix.
Stratified Care Education Content
Introduction and Overview of Study
Pain Neuroscience
Variability in Musculoskeletal Pain
Development and Maintenance of Chronic Low Back Pain
Patient Subgrouping
Psychologically Informed Physical Therapist Practice
STarT Back Approach
Identification (Screening)
Management (Targeted Treatment)
Interventions
Communication Skills
Education-Based Intervention
Pain Neuroscience
Activation Philosophy
Activity-Based Intervention
Graded Exercise or Activity
Graded Exposure
Physical Impairment-Based Intervention
American Physical Therapy Association Orthopaedic Section Clinical Practice Guidelines
Outcome Measures
Treatment Monitoring
Case Examples
Adherence
Implementation Challenges
1134
f
Physical Therapy
Volume 95
Number 8
August 2015
Stratified Primary Care Model
eTable.
Descriptive Characteristics of Physical Therapistsa
Total Sample
(Nⴝ12)
Standard Care Group
(nⴝ6)
Stratified Care Group
(nⴝ6)
P
6 (50)
3 (50)
3 (50)
.999
Years of practice
7.3 (5.0)
10.1 (5.3)
4.4 (2.9)
.042
Residency (yes)
11 (91.7)
6 (100)
.296
5 (83.3)
.221
Variable
Sex (female)
Fellowship (yes)
8 (66.7)
PABS-PT (biomedical)b
PABS-PT (biopsychosocial)
HC-PAIRSb
b
5 (83.3)
3 (50.0)
27.6 (4.7)
26.7 (6.1)
28.5 (3.1)
.529
36.0 (3.1)
36.0 (4.1)
36.0 (2.2)
.999
30.8 (6.4)
28.3 (7.0)
33.3 (5.1)
.191
a
Values are reported as mean (SD), with the exception of sex, residency, and fellowship, which are reported as frequency count (%). PABS-PT⫽Pain
Attitudes and Beliefs Scale for Physical Therapists (biomedical scale, potential range: 10 – 60), (biopsychosocial scale, potential range: 9 –54); HCPAIRS⫽Health Care Providers’ Pain and Impairment Relationship Scale (potential range: 13–78).
b
Pretraining and education scores.
August 2015 (eTable, Beneciuk and George)
Volume 95
Number 8
Physical Therapy f
1
Research Report
Levels and Patterns of Physical Activity
and Sedentary Behavior in
Elderly People With Mild to
Moderate Parkinson Disease
Martin Benka Wallén, Erika Franzén, Håkan Nero, Maria Hagströmer
Background. Decreased movement ability, one of the hallmarks of Parkinson
disease (PD), may lead to inadequate physical activity (PA) and excessive time spent
in sedentary behaviors—2 factors associated with an elevated risk for lifestyle-related
diseases, poor management of PD, and premature death. To identify the extent to
which people with PD are physically active, a comprehensive characterization of PA
in this population is needed.
Objective. The study objective was to describe levels and patterns of PA and
sedentary behaviors in elderly people with PD.
Design. This cross-sectional study involved a free-living setting and 53 men and 42
women (mean age⫽73.4 years) with mild to moderate idiopathic PD.
Methods. Time spent in PA and sedentary behaviors was assessed for 1 week with
accelerometers.
Results. Mean daily step counts were 4,765; participants spent 589 minutes in
sedentary behaviors, 141 minutes in low-intensity activities, 30 minutes in moderateintensity lifestyle activities, and 16 minutes in moderate- to vigorous-intensity ambulatory activities. No differences were found between weekdays and weekend days.
Patterns were characterized by a rise in total PA in the morning, peaking between
10 am and 3 pm, and a gradual decline toward the late evening. The proportion
achieving 150 minutes of moderate- to vigorous-intensity PA per week was 27%, and
16% achieved 7,000 or more steps per day.
Limitations. Nonrandomized selection of participants may limit the generalizability of the results.
Conclusions. Physical activity levels were generally low, in terms of both total
volume and intensity, with only minor variations over the course of a day or between
days. These results emphasize the need to develop strategies to increase PA and
reduce time spent in sedentary behaviors in elderly people with mild to moderate PD.
M. Benka Wallén, PhD, RPT,
Department of Neurobiology,
Care Sciences and Society, Division of Physiotherapy, Karolinska
Institutet, Alfred Nobels Alle 23,
141 83 Huddinge, Sweden.
Benka Wallén at: [email protected].
E. Franzén, PhD, RPT, Department
of Neurobiology, Care Sciences
and Society, Division of Physiotherapy, Karolinska Institutet, and
Department of Physical Therapy,
Karolinska University Hospital,
Stockholm, Sweden.
H. Nero, MSc, RPT, Department of
Neurobiology, Care Sciences and
Society, Division of Physiotherapy,
Karolinska Institutet.
M. Hagströmer, PhD, RPT, Department of Neurobiology, Care Sciences and Society, Division of
Physiotherapy, Karolinska Institutet, and Department of Physical
Therapy, Karolinska University
Hospital.
[Benka Wallén M, Franzén E, Nero
H, Hagströmer M. Levels and patterns of physical activity and sedentary behavior in elderly people
with mild to moderate Parkinson
disease. Phys Ther. 2015;95:
1135–1141.]
Association
February 5, 2015
this article at:
ptjournal.apta.org
August 2015
Volume 95
Number 8
Physical Therapy f
1135
P
arkinson disease (PD) is a progressive, neurodegenerative disorder characterized by rigidity,
tremor, impaired postural stability,
decreased walking ability, and an
increased risk of falls.1 These symptoms affect movement abilities
in everyday tasks,1,2 leading to
decreased physical activity (PA) and
increased time spent in sedentary
behaviors. This situation may, in
turn, lead to a cycle of poorer balance, muscle weakness, fear of falling, and a sedentary lifestyle.
Insufficient PA is associated with
many adverse health outcomes, and
several studies have demonstrated
PA to be effective in the treatment
and prevention of a number of
diseases.3– 6 A systematic review
recently highlighted the therapeutic
value of PA,7 which reduces mortality for many common health conditions at rates similar to those of pharmaceutical treatments. In addition,
PA is essential for healthy aging and
has been shown, when in the form
of structured exercise, to have positive effects on PD symptoms and
complaints—such as improved gait
performance, balance control, muscular strength, cardiovascular fitness, and quality of life (for reviews,
see Speelman et al8 and Goodwin
et al9).
Recent research based on selfreport10 or accelerometry11 indicated that people with PD are
approximately 30% less physically
active than people in a control group
matched for age. In addition, the volume of PA diminishes with a higher
level of disease severity, as shown in
both cross-sectional11 and longitudinal12 studies. However, little is
known about any PA occurring in
the lower range of the intensity spectrum. Emerging evidence has suggested that low-intensity PA (LPA)
not only may decrease sedentary
time—which, by itself, is a risk factor
for disease5,6,13— but also may pro1136
f
Physical Therapy
Volume 95
vide significant health benefits on its
own.13 It was recently suggested that
total daily activity counts may be
more strongly associated with
adverse health outcomes than
moderate- to vigorous-intensity PA
(MVPA)14 and, therefore, should be
estimated along with time spent at
different intensity levels in studies of
PA (for a review, see Bassett et al15).
To our knowledge, such data have
not been presented for people with
PD.
Another aspect of PA that is particularly relevant for PD is the diurnal
pattern. Specifically, motor performance in people with PD has been
shown to fluctuate over the course
of a day, characterized primarily by
morning activity levels that are lower
than those of people who are
healthy.16 However, to our knowledge, a more detailed characterization of diurnal variations, in which
different intensity levels are quantified separately, has not been
published.
Thus, the 3 aims of this study were:
(1) to quantify the total volume of
daily and weekly PA in elderly people with mild to moderate PD, (2) to
determine the amount of time spent
daily at different intensity levels, and
(3) to characterize patterns of different intensity levels of PA and sedentary behaviors over the course of a
day, including a comparison of
weekdays with weekend days.
Method
Study Design
The present study was a substudy of
an ongoing randomized controlled
trial examining the effects of a balance training program on outcomes
related to PD (the BETA-PD study;
clinical trial number NCT01417598).
The BETA study procedure has been
described elsewhere.17 Accelerometer data collected at baseline (in
2012 and 2013) were analyzed in the
present study.
Number 8
Participants
People who had mild to moderate
PD and dwelled in the community
were recruited through advertisements in local newspapers, from
Karolinska University Hospital, or
from the Swedish Parkinson Association. Inclusion criteria were an age
of 60 years or older and a clinical
diagnosis of idiopathic PD, according to the Queen Square Brain Bank
Criteria18 and Hoehn and Yahr stages
2 and 3.19 Exclusion criteria were
atypical PD, according to Hughes et
al20; a Mini-Mental State Examination
score of ⱕ2421; and other neuromuscular disorders that influence gait
and balance.
The study included 95 people (42
women) with idiopathic PD, classified as stage 2 (n⫽41) or 3 (n⫽54),
according to Hoehn and Yahr.19 The
means for various characteristics
were as follows: age, 73.4 years
(SD⫽5.7 years); weight, 76.6 kg
(SD⫽14.2 kg); height, 171.4 cm
(SD⫽9.3 cm); body mass index, 25.8
kg/m2 (SD⫽3.7); and disease duration, 5.9 years (SD⫽5.0 years). All
participants
provided
written
informed consent.
Instrumentation
Physical activity was assessed by use
of ActiGraph GT3X⫹ accelerometers (ActiGraph, Pensacola, Florida)
with firmware version 2.5.0. GT3X⫹
accelerometers sample changes in
force at a frequency of 30 Hz before
converting them to digital counts
with a 12-bit analog-to-digital converter.22 To exclude nonhuman
motion, accumulated data can be
processed through 1 of 2 band-pass
filters: either a normal filter (0.25–
2.4 Hz) or a low-frequency extension
option (bandwidth not specified by
manufacturer). ActiGraph suggests
applying the low-frequency extension filter for the assessment of people who exhibit very low acceleration outputs, such as elderly
people.23 However, we have found
August 2015
this option likely to overestimate PA
in people with PD and, therefore,
selected the normal filter setting.24
One-minute epochs were used to
determine the time spent at different
intensity levels (definitions of PA levels are given below).
Data Acquisition
Upon arrival at the laboratory, participants were assessed for height and
weight and evaluated with the motor
part of the Unified Parkinson Disease
Rating Scale.25 Each participant was
then provided with an accelerometer attached to a belt and given verbal and written instructions on its
proper use. The belt was to be worn
around the waist at hip level during
all time awake for 7 consecutive
days, except when showering, swimming, or bathing.
Data Reduction
ActiLife 6 (ActiGraph) was used to
process all accelerometer data: data
cleansing, filtering, and computation
of different PA parameters. In accordance with previous research on
elderly people, episodes ⱖ90 minutes of consecutive zeroes (ie, inactivity) were excluded.26 Wear time
was determined by subtracting nonwear time from total time. Hours
with ⱖ54 minutes of data (90%)
were included.
The following outcome variables
were generated: total volume of PA,
defined as vector magnitude counts
per minute; steps per day; and minutes spent at different intensity levels per day, based on vertical axis
counts. Total daily vector magnitude
counts, representing the sum of averaged triaxial vector counts per minute, have been suggested to provide
a more reliable means of operationalizing PA than estimating time at
different intensity levels15 and, therefore, also were included. Because
the ActiGraph system has not been
calibrated for people with PD and
preliminary analyses demonstrated
August 2015
zero or very few minutes at vigorous
intensity per week—that is, greater
than 6 metabolic equivalents
(METs)— cutoffs that were previously used in epidemiological studies of elderly people27,28 were
applied as follows: for sedentary
behaviors, 1 to 1.5 METs or 0 to 99
cpm; for LPA, 1.5 to 2.9 METs or 100
to 759 cpm; and for moderateintensity PA or higher (MPA⫹), ⱖ3
METs or ⱖ760 cpm. Moderateintensity PA or higher was further
divided into moderate-intensity lifestyle activities (MPALS; 3 METs or
760 –2,019 cpm), for activities such
as sweeping, vacuuming, raking, and
shoveling,27 and moderate- to
vigorous-intensity ambulatory activities (MVPA; ⬎3 METs or ⬎2,019
cpm), corresponding to a walking
speed of 4 km/h or more.28
Data Analysis
Levels. In accordance with previous research,28 –30 days with ⱖ10
hours of valid data were used to summarize the total amount of daily PA
and the time spent at different intensity levels in terms of means and 95%
confidence intervals (CIs). New variables representing average time at
different intensity levels per day
(Monday–Sunday) were determined
from the mean values for a minimum
of 4 and up to 7 days per week,
depending on how many valid days
were available. The requirement for
4 recording days was based on previous research on adults who were
healthy31 and adults who were overweight,32 and the assessment of 4
days of PA was shown to agree
highly with the assessment of a full
week of PA.29,31
To determine the proportion meeting the guideline of 150 minutes of
MVPA weekly or 7,000 or 8,000
steps per day, proportions and 95%
CIs (binomial exact method) were
estimated. Average values for 4 to 7
valid days were multiplied by 7 to
obtain time spent in MVPA per
week. The cutoff for meeting the PA
recommendation was set to ⱖ150
minutes of accumulated time spent
in MVPA per week. Two cutoffs for
meeting the recommendation for
total daily steps were used: 7,000
steps and 8,000 steps.
Patterns. Outcome variables representing weekdays were generated
from the mean values for 3 to 5
weekdays (ie, Monday–Friday), and
outcome variables representing
weekend days were determined
from the mean values for both Saturday and Sunday. That is, a minimum
of 3 weekdays or both weekend
days, respectively, was required for
inclusion in the analyses. Statistical
analyses were performed with
STATA version 11 (StataCorp LP, College Station, Texas). All variables
demonstrated an approximately normal distribution when evaluated on a
histogram, except for MVPA, which
was skewed to the right. Log10 and
natural log transformations did not
improve the distribution; hence,
nontransformed data were used. Differences between weekdays and
weekends with respect to time spent
at different PA intensity levels and
steps per day were estimated with a
one-way repeated-measures analysis
of variance or a Wilcoxon signed
rank test for MVPA. The alpha level
was set at Pⱕ.05.
To describe the patterns of PA and
sedentary behaviors over the course
of a day, we plotted time (minutes
per hour) spent at different intensity
levels over an 18-hour time frame
between 6 am and 11 pm for weekdays and weekend days. Because the
values for MVPA and MPALS were
very low and difficult to evaluate on
a graph, their combined values
(MPA⫹) were used to illustrate the
number of minutes spent in PA of
moderate or higher intensity each
hour. All valid hours within the given
time frame were selected to calculate the average number of minutes
Volume 95
Number 8
Physical Therapy f
1137
Table 1.
Characteristics of Participants From Whom Valid Data Were Obtained for Various Periodsa
Characteristic
Minimum of 4/7 d/wk (nⴝ79)
Age, y
Women, n (%)
Height, cm
Weight, kg
BMI, kg 䡠 m
UPDRS score, mean (range)
Weekend Daysb (nⴝ62)
73.2 (5.7)
73.3 (5.7)
73.5 (5.9)
37 (47)
36 (46)
29 (47)
171.5 (8.8)
171.8 (9.1)
171.9 (8.4)
75.1 (13.9)
2
3–5 Weekdays (nⴝ79)
75.6 (14.4)
75.9 (12.8)
25.4 (3.7)
25.5 (3.7)
25.6 (3.6)
35.3 (14–62)
35.7 (14–62)
34.8 (17–62)
a
Data are presented as means (standard deviations) unless indicated otherwise. BMI⫽body mass index, UPDRS⫽Unified Parkinson Disease Rating Scale
(motor part).
b
Saturday and Sunday.
spent at different intensity levels for
each time point (ie, for each hour).
The study was funded by the Swedish Research Council, StratNeuro
Karolinska Institutet, NorrbackaEugenia Foundation, and the
national doctoral school in health
care sciences at Karolinska Institutet.
Results
Participant characteristics are shown
in Table 1. Valid data were obtained
from 79 participants for a minimum
of 4 of 7 days per week, from 79
participants for 3 to 5 weekdays,
from 62 participants for weekend
days, and from 59 participants for
both weekdays and weekend days.
Levels of PA
Of the 13 hours 6 minutes of wear
time for an average day of the week,
9 hours 49 minutes (75%) was spent
in sedentary behaviors, 2 hours 21
minutes (18%) was spent in LPA, 30
minutes (4%) was spent in MPALS,
and 16 minutes (2%) was spent in
MVPA. The mean total time spent in
MVPA per week was 114.8 minutes
(SD⫽150.4 minutes). Table 2 shows
means and 95% CIs for total time
spent in PA (vector magnitude
counts per day and per minute and
step counts per day) as well as time
spent at different PA intensity levels
and in sedentary behaviors for an
average day of the week, weekday,
and weekend day.
Estimations of binomial proportions
demonstrated that 27% (95% CI⫽18%,
36%) met the guideline of 150 minutes of MVPA per week. The proportion achieving 7,000 or more steps per
day was 16% (95% CI⫽8%, 25%),
whereas 11% (95% CI⫽4%, 19%)
achieved 8,000 or more steps per day.
Patterns of PA
There were nonsignificant trends
toward more time being spent in
sedentary behaviors (mean difference⫽9 minutes) and LPA (mean difference⫽0.9 minute) on weekdays
and more time being spent in higherintensity PA on weekend days (mean
difference in MPALS⫽0.6 minute;
mean difference in MVPA⫽3.2 minutes; mean difference in steps⫽167)
Table 2.
Accelerometer Outcomes Determined for Various Periodsa
Activity
SB, min 䡠 d
Minimum of 4/7 d/wk (nⴝ79)
⫺1
⫺1
LPA, min 䡠 d
MPALS, min 䡠 d⫺1
MVPA, min 䡠 d
⫺1
Steps per day
VM, counts 䡠 d⫺1
VM, counts 䡠 min⫺1
⫺1
Wear time, h 䡠 d
3–5 Weekdays (nⴝ79)
Weekend Daysb (nⴝ62)
588.9 (571.6, 606.1)
593.9 (575.6, 612.3)
584.5 (561.0, 608.0)
140.6 (126.5, 154.6)
143.0 (128.7, 157.2)
142.1 (124.2, 160.0)
30.1 (25.3, 34.9)
30.7 (26.0, 35.4)
31.3 (23.6, 39.0)
16.4 (11.6, 21.2)
15.2 (10.8, 19.7)
18.4 (11.1, 25.7)
4,765 (4,071, 5,461)
4,721 (4,038, 5,403)
4,888 (3,896, 5,881)
293,614 (259,255, 327,972)
291,470 (256,899, 326,041)
305,269 (262,068, 348,469)
374 (77, 1,146)
368 (73, 1,144)
388 (83, 1,229)
13.1 (12.7, 13.4)
13.2 (12.8, 13.6)
13.1 (12.7, 13.6)
Data are presented as means (95% confidence intervals). SB⫽sedentary behaviors, LPA⫽low-intensity physical activities, MPALS⫽moderate-intensity lifestyle
activities, MVPA⫽moderate- to vigorous-intensity physical activity, VM⫽vector magnitude. No statistically significant differences were found between
weekdays and weekend days for any of the outcomes (P⬎.05).
b
Saturday and Sunday.
a
1138
f
Physical Therapy
Volume 95
Number 8
August 2015
(Tab. 2). Similarly, vector magnitude
counts per day (mean difference⫽13,799) and per minute
(mean difference⫽167) were higher
on weekend days than on weekdays;
however, these differences were not
statistically significant (all P values
⬎.5). The differences were even
smaller when wear time (5 minutes
longer on weekdays) was taken into
account; when expressed as a percentage of daily wear time, sedentary
behaviors represented 75% of weekdays and 74% of weekend days, and
LPA, MPALS, and MVPA represented
18%, 4%, and 2%, respectively, of
both weekdays and weekend days
(Tab. 2). Descriptive data for weekdays and weekend days are shown in
Table 2.
The Figure shows PA patterns over
the course of a day, with weekdays
and weekend days being displayed
separately. Physical activity patterns
over the course of a day showed that
LPA increased starting at approximately 7 am, climbed toward a peak
at 10 to 11 am, and then gradually
tapered off toward a low plateau
at approximately 9 pm. A slight
increase was again observed between 10 and 11 pm. Weekdays and
weekend days showed virtually identical patterns at this intensity level.
Time in MPA⫹ followed a similar
pattern, although at a consistently
lower level. Again, similar patterns
were found between weekdays and
weekend days, with 2 exceptions:
the first between 1 and 3 pm and the
second between 10 and 11 pm.
At both of these times, MPA⫹
tended to be higher on weekend days
than on weekdays. This elevation was
paralleled by a decrease in sedentary
behaviors during the same times.
Apart from this difference, patterns
of sedentary behaviors were similar
on weekdays and weekend days.
Discussion
The main finding of the present
study was that approximately 75% of
August 2015
Figure.
Illustration of the average number of minutes spent in sedentary behaviors (prefix S),
low-intensity physical activities (prefix L), and a combination of moderate-intensity
lifestyle activities and moderate- to vigorous-intensity ambulatory activities (prefix M⫹)
on an hour-to-hour basis for weekdays (W; black symbols) and weekend days (WE; gray
symbols).
all time awake was spent in sedentary behaviors, 18% was spent in
LPA, and 6% was spent in a combination of MPALS or MVPA. These
results are in line with previous
research demonstrating that people
with mild to moderate PD are ambulatory at moderate or higher intensity
only 5% of the day.11 They also
largely agree with the previous finding that 76% of all time awake comprises sedentary behaviors.33 When
explicitly studying people who had
PD and led a sedentary lifestyle,
other authors found that 98% of all
time awake comprised a combination of sedentary behaviors and LPA,
whereas less than 2% represented
moderate- to vigorous-intensity PA.34
Despite several methodological differences among these studies, the
results collectively indicate that people with PD lead a lifestyle characterized by excessive sedentary
behaviors and insufficient MPA⫹.
The findings of the present study
have important clinical implications
because both excessive time in sedentary behaviors and insufficient
MVPA predispose people to many
comorbidities, such as coronary
heart disease, stroke, diabetes,
hypertension, cancer, depression,
and premature death.3– 6 In addition,
a sedentary lifestyle may have a
direct negative effect on disease
management
and
progression
because the potentially positive
effects of exercise on symptoms specifically related to PD are lost.8
Recent epidemiological studies suggested that LPA and sedentary behaviors are independently associated
with metabolic syndrome13 and that
total activity counts are more
strongly associated with biomarkers
for cardiovascular disease than boutaccumulated MVPA.14 On the basis
of these findings and others, it has
been proposed that total daily PA, in
terms of activity counts, should be
considered in the evaluation of PA,
rather than time spent in MVPA
alone.15 In the present study, we
found that 18% of the day was spent
in LPA, which together with MPALS
and MVPA adds up to a little more
than 3 hours in any PA daily and total
Volume 95
Number 8
Physical Therapy f
1139
daily activity counts to 293,614. Additional research that relates daily
activity counts to adverse health outcomes is needed to interpret these
results.
In a few studies, PA behavior in people with PD and PA behavior in people in a similarly aged control group
were compared directly. Using questionnaire data, van Nimwegen et al10
found that people with PD were 29%
less physically active than people in
a control group. Similarly, using
accelerometry, Lord et al11 found
that the level of ambulatory PA was
27% lower in people with PD than in
a control group of people who were
healthy. Lord et al11 also found that
the step count was 5,500 steps per
day; this count was similar to the
count of 4,760 steps per day
reported here but in stark contrast to
the daily count of 10,200 steps
reported by Cavanaugh et al.12 This
rather large discrepancy is most
likely due to methodological differences, further emphasizing the need
to standardize PA measurements
across studies.
When we evaluated diurnal PA patterns, only minor fluctuations were
seen over the course of a day, confirming previous research.16 Expanding on what was previously known,
we found patterns of low variability
across all intensity levels. On weekdays, PA levels peaked at about 10 to
11 am before gradually declining,
whereas they remained elevated
until the early afternoon on weekend
days. This finding suggests that
motor symptoms may be less prominent at midday and during the early
afternoon, even though this notion
was not explicitly studied. Although
these findings provide a better
understanding of PA patterns in people with PD on a group level, several
different
mechanisms—including
fatigue, fear of falling, lack of motivation, physical constraints, and
symptoms related to pharmacologi1140
f
Physical Therapy
Volume 95
cal treatment— could underpin PA
on an individual level. Therefore, to
provide each patient with the most
appropriate recommendations, PA
programs may need to be individually tailored on the basis of a thorough anamnesis and accelerometer
assessment of each patient.
In addition to describing the levels
and patterns of PA, we also estimated the extent to which PA
recommendations were met in the
studied population; we found that
73% of the participants failed to
achieve 150 minutes of MVPA per
week. Most studies evaluating PA in
various populations use the guidelines set forth by the American College of Sports Medicine (2008),4
according to which older adults are
advised to perform a total of 150
minutes of MVPA per week, preferably in bouts no shorter than 10 minutes. These guidelines were derived
from self-reported data, which have
been shown to agree rather poorly
with objective methods, generally
returning higher levels of PA than
accelerometry.35 This incongruence
becomes particularly striking when
the rule of 10-minute bouts of accumulated MVPA is applied; whereas
one study based on self-report estimated that more than 46% of the
general adult population achieved
150 minutes of MVPA (in bouts) per
week,36 a study based on accelerometry found that less than 5% reached
the same level.28 Discrepancies
between self-reported PA and accelerometry also have been found in
studies of people with PD specifically.37 Collectively, these studies
demonstrate that PA recommendations derived from self-reports likely
do not apply to accelerometry.
Taken together, our results demonstrate that people with mild to moderate PD spend a large part of their
day in sedentary behaviors and only
a small amount of time in PA. These
findings are important to physical
Number 8
therapists and other health care professionals who may promote and
prescribe PA. Although the benefits
of PA in disease prevention and management are now widely recognized,
the specific methods and procedures
that may be effective for increasing
PA in people with mild to moderate
PD have yet to be determined.
Limitations
One of the main challenges for
assessing PA by means of accelerometry is to define appropriate cutoffs
to represent different types of PA.
Because the ActiGraph system has
not been calibrated for people with
PD, we used cutoffs that have been
developed from the general population. It is possible that these thresholds do not validly reflect intensity
levels in people with PD because,
among other issues, PD generally
presents with an altered gait pattern
that is likely more energy demanding
than “normal” gait.38
The present study was part of an
ongoing project in which participants were recruited locally rather
than being randomly selected from
the whole population of people with
PD. The way in which this method
may have affected the results is not
easily discerned; however, it likely
limits the generalizability of the
study. Moreover, we specifically
included people with mild to moderate PD, and additional studies are
needed to characterize PA and sedentary behaviors in people with
more severe PD.
The present study demonstrated that
elderly people with mild to moderate PD displayed low levels of PA, in
terms of both total volume and intensity. Much of their day was spent in
sedentary behaviors, with small variations in PA over the course of a day
and over different days of the week.
Taken together, the results emphasize the need to develop strategies
that will increase PA levels and
August 2015
reduce time spent in sedentary
behaviors in this population.
Dr Benka Wallén, Dr Franzén, and Dr Hagströmer provided concept/idea/research
design. All authors provided writing. Dr
Benka Wallén, Dr Franzén, and Mr Nero provided data collection. Dr Benka Wallén and
Dr Hagströmer provided data analysis. Dr
Franzén, Mr Nero, and Dr Hagströmer provided project management. Dr Franzén and
Dr Hagströmer provided fund procurement,
participants, and facilities/equipment. Dr
Franzén provided institutional liaisons. Mr
Nero provided administrative support and
consultation (including review of manuscript
before submission). The authors acknowledge PhD students David Conradsson and
Niklas Löfgren for support with data collection.
The Regional Board of Ethics in Stockholm,
Sweden, granted approval for the study.
The study was funded by the Swedish
Research Council, StratNeuro Karolinska
Institutet, Norrbacka-Eugenia Foundation,
and the national doctoral school in health
care sciences at Karolinska Institutet.
DOI: 10.2522/ptj.20140374
References
1 Marsden CD. Parkinson’s disease. J Neurol
Neurosurg Psychiatry. 1994;57:672– 681.
2 Franzén E, Paquette C, Gurfinkel VS, et al.
Reduced performance in balance, walking
and turning tasks is associated with
increased neck tone in Parkinson’s disease. Exp Neurol. 2009;219:430 – 438.
3 Lee IM, Shiroma EJ, Lobelo F, et al. Effect
of physical inactivity on major noncommunicable diseases worldwide: an
analysis of burden of disease and life
expectancy. Lancet. 2012;380:219 –229.
4 Physical Activity Guidelines Advisory
Committee. Physical Activity Guidelines
Advisory Committee Report. Washington,
DC: Department of Health and Human Services; 2008.
5 Healy GN, Matthews CE, Dunstan DW,
et al. Sedentary time and cardio-metabolic
biomarkers in US adults: NHANES 200306. Eur Heart J. 2011;32:590 –597.
6 Wilmot EG, Edwardson CL, Achana FA,
et al. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and
meta-analysis. Diabetologia. 2012;55:
2895–2905.
7 Naci H, Ioannidis JP. Comparative effectiveness of exercise and drug interventions on mortality outcomes: metaepidemiological study. BMJ. 2013;347:f5577.
8 Speelman AD, van de Warrenburg BP, van
Nimwegen M, et al. How might physical
activity benefit patients with Parkinson
disease? Nat Rev Neurol. 2011;7:528 –534.
August 2015
9 Goodwin VA, Richards SH, Taylor RS, et al.
The effectiveness of exercise interventions for people with Parkinson’s disease:
a systematic review and meta-analysis.
Mov Disord. 2008;23:631– 640.
10 van Nimwegen M, Speelman AD, Hofmanvan Rossum EJ, et al. Physical inactivity in
Parkinson’s disease. J Neurol. 2011;258:
2214 –2221.
11 Lord S, Godfrey A, Galna B, et al. Ambulatory activity in incident Parkinson’s: more
than meets the eye? J Neurol. 2013;260:
2964 –2972.
12 Cavanaugh JT, Ellis TD, Earhart GM, et al.
Capturing ambulatory activity decline in
Parkinson’s disease. J Neurol Phys Ther.
2012;36:51–57.
13 Kim J, Tanabe K, Yokoyama N, et al.
Objectively measured light-intensity lifestyle activity and sedentary time are independently associated with metabolic syndrome: a cross-sectional study of Japanese
adults. Int J Behav Nutr Phys Act. 2013;
10:30.
14 Wolff DL, Fitzhugh EC, Bassett DR, Churilla JR. Total activity counts and bouted
minutes of moderate-to-vigorous physical
activity: relationships with cardiometabolic biomarkers using 2003-2006
NHANES. J Phys Act Health. 2014 Aug 7
[Epub ahead of print]. doi: 10.1123/jpah.
2013-0463.
15 Bassett DR, Troiano RP, McClain JJ, Wolff
DL. Accelerometer-based physical activity:
total volume per day and standardized
measures. Med Sci Sports Exerc. 2015;47:
833– 838.
16 van Hilten JJ, Hoogland G, van der Velde
EA, et al. Diurnal effects of motor activity
and fatigue in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1993;56:874 –
877.
17 Conradsson D, Löfgren N, Ståhle A, et al. A
novel conceptual framework for balance
training in Parkinson’s disease: study protocol for a randomised controlled trial.
BMC Neurol. 2012;12:111.
18 Gibb WR, Lees AJ. The significance of the
Lewy body in the diagnosis of idiopathic
Parkinson’s disease. Neuropathol Appl
Neurobiol. 1989;15:27– 44.
19 Hoehn MM, Yahr MD. Parkinsonism:
onset, progression and mortality. Neurology. 1967;17:427– 442.
20 Hughes AJ, Daniel SE, Kilford L, Lees AJ.
Accuracy of clinical diagnosis of idiopathic
Parkinson’s disease: a clinico-pathological
study of 100 cases. J Neurol Neurosurg
Psychiatry. 1992;55:181–184.
21 Folstein MF, Folstein SE, McHugh PR.
“Mini-mental state”: a practical method for
grading the cognitive state of patients for
the clinician. J Psychiatr Res. 1975;12:
189 –198.
22 Chen KY, Bassett DR Jr. The technology of
accelerometry-based activity monitors:
current and future. Med Sci Sports Exerc.
2005;37(11 suppl):S490 –S500.
23 ActiGraph. Low frequency extension
explained. ActiGraph Support Web page.
Available at: https://help.theactigraph.
com/entries/21767838-Low-FrequencyExtension-Explained. Posted July 24,
2012. Accessed February 3, 2015.
24 Wallén MB, Nero H, Franzén E, Hagströmer M. Comparison of two accelerometer filter settings in individuals with Parkinson’s disease. Physiol Meas. 2014;35:
2287–2296.
25 Fahn S, Elton R. Unified Parkinson’s Disease Rating Scale. In: Fahn S, Marsden CD,
Calne DB, Goldstein M, eds. Recent Developments in Parkinson’s Disease. Vol 2.
Florham Park, NJ: Macmillan Health Care
Information; 1987:153–163, 293–304.
26 Choi L, Liu Z, Matthews CE, Buchowski
MS. Validation of accelerometer wear and
nonwear time classification algorithm.
Med Sci Sports Exerc. 2011;43:357–364.
27 Matthew CE. Calibration of accelerometer
output for adults. Med Sci Sports Exerc.
2005;37(11 suppl):S512–S522.
28 Troiano RP, Berrigan D, Dodd KW, et al.
Physical activity in the United States measured by accelerometer. Med Sci Sports
Exerc. 2008;40:181–188.
29 Trost SG, McIver KL, Pate RR. Conducting
accelerometer-based activity assessments
in field-based research. Med Sci Sports
Exerc. 2005;37(11 suppl):S531–S543.
30 Hagströmer M, Troiano RP, Sjöström M,
Berrigan D. Levels and patterns of objectively assessed physical activity: a comparison between Sweden and the United
States. Am J Epidemiol. 2010;171:1055–
1064.
31 Matthews CE, Ainsworth BE, Thompson
RW, Bassett DR Jr. Sources of variance in
daily physical activity levels as measured
by an accelerometer. Med Sci Sports
Exerc. 2002;34:1376 –1381.
32 Jerome GJ, Young DR, Laferriere D, et al.
Reliability of RT3 accelerometers among
overweight and obese adults. Med Sci
Sports Exerc. 2009;41:110 –114.
33 Chastin SF, Baker K, Jones D, et al. The
pattern of habitual sedentary behavior is
different in advanced Parkinson’s disease.
Mov Disord. 2010;25:2114 –2120.
34 Dontje ML, de Greef MH, Speelman AD,
et al. Quantifying daily physical activity
and determinants in sedentary patients
with Parkinson’s disease. Parkinsonism
Relat Disord. 2013;19:878 – 882.
35 Prince SA, Adamo KB, Hamel ME, et al. A
comparison of direct versus self-report
measures for assessing physical activity in
adults: a systematic review. Int J Behav
Nutr Phys Act. 2008;5:56.
36 Centers for Disease Control and Prevention. Adult participation in recommended
levels of physical activity: United States,
2001 and 2003. MMWR Morb Mortal
Wkly Rep. 2005;54:1208 –1212.
37 van Nimwegen M, Speelman AD, Overeem
S, et al. Promotion of physical activity and
fitness in sedentary patients with Parkinson’s disease: randomised controlled trial.
BMJ. 2013;346:f576.
38 Katzel LI, Ivey FM, Sorkin JD, et al.
Impaired economy of gait and decreased
six-minute walk distance in Parkinson’s
disease. Parkinsons Dis. 2012;2012:
241754.
Volume 95
Number 8
Physical Therapy f
1141
Research Report
Toward Understanding Ambulatory
Activity Decline in Parkinson Disease
James T. Cavanaugh, Terry D. Ellis, Gammon M. Earhart, Matthew P. Ford,
K. Bo Foreman, Leland E. Dibble
J.T. Cavanaugh, PT, PhD, Department of Physical Therapy, University of New England, Portland, ME
04103 (USA). Address all correspondence to Dr Cavanaugh at:
[email protected].
T.D. Ellis, PT, PhD, Department of
Physical Therapy and Athletic
Training, Boston University, Boston, Massachusetts.
G.M. Earhart, PT, PhD, Program in
Physical Therapy, School of Medicine, Washington University, St
Louis, Missouri.
M.P. Ford, PT, PhD, Department
of Physical Therapy, Samford University, Birmingham, Alabama.
K.B. Foreman, PT, PhD, Department of Physical Therapy, University of Utah, Salt Lake City, Utah.
L.E. Dibble, PT, PhD, Department
of Physical Therapy, University of
Utah.
[Cavanaugh JT, Ellis TD, Earhart
GM, et al. Toward understanding
ambulatory activity decline in Parkinson
disease.
Phys
Ther.
2015:95:1142–1150.]
Association
April 9, 2015
Submitted: November 4, 2014
Background. Declining ambulatory activity represents an important facet of
disablement in Parkinson disease (PD).
Objective. The primary study aim was to compare the 2-year trajectory of ambulatory activity decline with concurrently evolving facets of disability in a small cohort
of people with PD. The secondary aim was to identify baseline variables associated
with ambulatory activity at 1- and 2-year follow-up assessments.
Design. This was a prospective, longitudinal cohort study.
Methods. Seventeen people with PD (Hoehn and Yahr stages 1–3) were recruited
from 2 outpatient settings. Ambulatory activity data were collected at baseline and at
1- and 2-year annual assessments. Motor, mood, balance, gait, upper extremity
function, quality of life, self-efficacy, and levodopa equivalent daily dose data and data
on activities of daily living also were collected.
Results. Participants displayed significant 1- and 2-year declines in the amount and
intensity of ambulatory activity concurrently with increasing levodopa equivalent
daily dose. Worsening motor symptoms and slowing of gait were apparent only after
2 years. Concurrent changes in the remaining clinical variables were not observed.
Baseline ambulatory activity and physical performance variables had the strongest
relationships with 1- and 2-year mean daily steps.
Limitations. The sample was small and homogeneous.
Conclusions. Future research that combines ambulatory activity monitoring with
a broader and more balanced array of measures would further illuminate the dynamic
interactions among evolving facets of disablement and help determine the extent to
which sustained patterns of recommended daily physical activity might slow the rate
of disablement in PD.
this article at:
ptjournal.apta.org
1142
f
Physical Therapy
Volume 95
Number 8
August 2015
Ambulatory Activity Decline in Parkinson Disease
T
he natural course of idiopathic
Parkinson disease (PD) is one
of ongoing disablement.1,2
Despite pharmacological intervention, disablement in PD commonly
evolves in a multifaceted, cumulative
fashion as impairments in motor and
nonmotor systems, limitations in
functional mobility and activities of
daily living (ADL), and restrictions in
the ability to participate in recreation, travel, exercise, or other physical activities.3–5 Importantly, the
rate of disablement in PD may not be
uniform across its various underlying
components. Motor impairments
with minimal activity limitations or
participation restrictions are generally characteristic of disease onset.6,7
Worsening of motor impairments
and increased difficulty with walking
tend to appear earlier than limitations in some gait-dependent ADL
tasks, including housework, dressing, and traveling in the community.3,6 Postural instability and gait
impairments often mark the transition from early- to middle-stage disease, before the onset of difficulty
with cognitively based ADL (eg, managing medication or money, using
the
telephone)
in
advanced
disease.3,6
Declining ambulatory activity in PD
has recently emerged as a growing
concern8 –11 because of its implications for health12–14 and its potential
association with accelerating disability.7 Whether it precedes clinical
impairments, evolves gradually
throughout the early and middle
stages of disease, or emerges more
dramatically in concert with postural
instability and gait impairment has
not yet been determined. A better
understanding of ambulatory activity
decline in the context of other facets
of disablement could inform clinical
interventions designed to slow the
rate of functional decline in PD.15
In a preliminary investigation,8 we
began the process of examining
August 2015
ambulatory activity decline over a
1-year period in 33 people with
early- to middle-stage PD. Ambulatory activity was measured directly
with a step activity monitor for up to
7 days at baseline and follow-up. In
addition to levodopa dosage, clinical
measures of motor impairments,
walking endurance, and maximal
gait speed were collected at each
time point. After 1 year, the participants displayed significant declines
in the amount and intensity of daily
ambulatory activity; concurrent
changes in clinical measures were
not observed. The results provided
insight into physical activity and
exercise behavior and suggested that
the participants had difficulty meeting recommended physical activity
guidelines.13,16 The findings also
revealed that the amount and intensity of ambulatory activity, which
characterizes many behaviors in the
participation domain of the International Classification of Functioning,
Disability and Health (ICF),2,17,18
may be relatively more useful than at
least some clinical measures for
detecting early disablement in PD.
The purpose of the present study
was to extend our preliminary examination of ambulatory activity
decline in PD by adding a newly collected, second year of step activity
data to the analysis. We also
expanded our comparison of ambulatory activity decline with concurrently evolving facets of disablement
by including a broader array of clinical measurement data from the baseline, 1-year, and 2-year assessments.
The clinical measures collectively
represented the body structure and
function, activity, participation, and
contextual factor domains of the ICF
model (Figure). On the basis of our
preliminary results,8 we hypothesized that measures reflecting the
amount and intensity of daily ambulatory activity would be relatively
more responsive to disablement than
clinical measures. In a secondary
exploratory analysis, we sought to
provide a foundation for future
research by identifying baseline variables that were relatively more likely
to be associated with ambulatory
activity at the 1- and 2-year
assessments.
Method
Study Design and Sample
Participants were selected from the
sample of a previously described
2-year, prospective, longitudinal
cohort study19 on the basis of the
availability of annual ambulatory
monitoring data. Participants were
recruited from outpatient movement
disorder clinics and local support
groups at Boston University and the
University of Utah. Inclusion criteria
were as follows: a diagnosis of idiopathic PD according to the criteria of
the Parkinson’s Disease Society Brain
Bank (London, United Kingdom),20
modified Hoehn and Yahr stages 1
through 4, age ⱖ40 years, living in
the community (not in an institution), and ability to attend assessment sessions and provide consent.
Participants were excluded if they
had a diagnosis of atypical parkinsonism, a classification of Hoehn and
Yahr stage 5, or previous surgical
management of their PD. All participants provided informed consent
after initial screening.
The present study was based on a
subset of people who had PD, whose
baseline and 1-year ambulatory activity data we had analyzed in our preliminary study (n⫽33),8 and for
whom ambulatory activity data from
the 2-year assessment also were available (n⫽17). Reasons for missing
ambulatory activity data at the 2-year
assessment (n⫽16) included the limited supply of monitors, the availability of a monitor on a particular day, a
participant’s willingness to wear a
monitor, and the presence of cognitive or integumentary impairments
that might have interfered with the
wearing protocol. Additional ambu-
Volume 95
Number 8
Physical Therapy f
1143
with lower scores indicating greater
activity limitations. The reliability,
internal consistency, and validity of
the FGA total score were established
in adults who were healthy and
in patients with neurological
disorders.28,29
The 10-Meter Walk Test (10MWT)
was used to assess gait speed during
the discrete task of walking a short
distance over an uncluttered, flat
indoor surface. The time to walk
10 m was recorded at a participant’s
self-selected pace with a standardized protocol.23 Lower values indicate greater activity limitations. Gait
speed is a reliable and valid indicator
of gait function in people with
PD.23,30
Figure.
Study measures categorized according to International Classification of Functioning,
Disability and Health model domains. MDS-UPDRS⫽Movement Disorder Society–
Unified Parkinson’s Disease Rating Scale, PDQ-39⫽39-item Parkinson’s Disease
Questionnaire.
latory activity monitoring details are
given below.
Measures
Body structure and function
domain. Section III of the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale (MDSUPDRS) was used to assess motor
function.21,22 Section scores can
scores indicating greater impairments related to bradykinesia,
tremor, rigidity, freezing, and postural control. The reliability of the
MDS-UPDRS for people with PD was
previously established.23
The Geriatric Depression Scale was
used to assess self-reported depressive symptoms.24 Total scores can
scores indicating greater mood
impairments. The Geriatric Depression Scale was previously validated
for people with PD.25
1144
f
Physical Therapy
Volume 95
Activity domain. Section II of the
MDS-UPDRS was used to assess selfreported limitations in discrete ADL
tasks. Section scores can range from
0 to 52, with higher scores indicating
greater activity limitations.
The Berg Balance Scale (BBS) was
used to assess static and dynamic balance performance during a series of
14 discrete sitting or standing
tasks.26 Total scores can range from
0 to 56, with lower scores indicating
greater activity limitations. The validity and high test-retest reliability of
the BBS total score were demonstrated across a variety of populations, including patients with
PD.23,27
The Functional Gait Assessment
(FGA) was used to assess dynamic
balance performance during a series
of 10 discrete walking tasks, each
conducted over a short distance.
Total scores can range from 0 to 30,
Number 8
The Six-Minute Walk Test (6MWT)
was used to assess sustained walking
performance during the discrete task
of walking a relatively long distance
over an uncluttered, flat indoor surface, according to the protocol outlined by the American Thoracic Society.31 Scores are represented as
distance walked in 6 minutes, with
lower scores indicating greater activity limitations. The test-retest reliability of the 6MWT for people with PD
is high.23
The Nine-Hole Peg Test (9HPT) was
used to assess dominant upper
extremity finger dexterity and movement time during the discrete task of
placing into and removing from
holes in a board 9 pegs as quickly as
possible. Scoring is represented as
the total time to complete the task,
with higher scores indicating greater
activity limitations. The 9HPT has
high interrater reliability and good
test-retest reliability in people with
PD.32
Participation
domain. Natural
ambulatory activity was captured at
each annual assessment with a StepWatch 3 Step Activity Monitor (SAM,
Orthocare Innovations, Mountlake
August 2015
Terrace, Washington). The SAM is
the size of a pager, weighs only 38 g,
and attaches at the ankle with Velcro
(Velcro USA Inc, Manchester, Hew
Hampshire) closures. It was validated previously for use in populations with impaired gait.8,17,33,34 Participants received a SAM at each
annual assessment and were
instructed to wear it during customary activity, including exercise but
excluding bathing, showering, or
swimming, during waking hours for
7 consecutive days. Monitors were
configured to record stride counts in
1-minute intervals. The ability to
detect steps was optimized according to each participant’s height, typical walking speed (slow, normal, or
fast), and leg motion (dynamic/fidgety, normal, or gentle/geriatric). Participants wore the SAM on the ankle
of the leg with the least severe motor
impairment, which was determined
from scores on the lower extremity
items of the MDS-UPDRS motor subsection. Oral and written instructions were provided regarding
proper SAM placement and wearing
schedule. Optimal accuracy was verified during the first minutes of
recording by comparing monitor
step counts, identified by a flashing
indicator light, with visual observation. Participants returned the SAM
to the researchers after 7 days.
Consistent with our preliminary
investigation,8 one investigator
(J.T.C.) used SAM manufacturer software to transform recorded 1-minute
stride counts into step counts (step
count ⫽ stride count ⫻ 2) and to
calculate mean daily values for the
amount and intensity of ambulatory
activity. Steps, defined as the total
number of steps accumulated, were
used as the sole indicator of daily
activity amount. Moderate-intensity
minutes, defined as the mean number of minutes per day in which
greater than 100 steps were
recorded,13 and maximum output,
defined as the mean step rate (steps
August 2015
per minute) during the 30 most
active consecutive minutes of the
day, were used to indicate daily
activity intensity. Daily values were
calculated for 24-hour intervals,
including time spent sleeping or
with the monitor off, from 12:00 am
to 11:59 pm. Lower values for each
parameter indicated greater participation restrictions.
The 39-item Parkinson’s Disease
Questionnaire is a health status
instrument that is used to measure
the degree of healthful, competent,
and satisfying participation in daily
life activities.35,36 Total scores can
scores indicating greater participation restrictions. The reliability,
validity, and sensitivity to change of
the 39-item Parkinson’s Disease
Questionnaire were established in
people who had PD and dwelled in
the community.36
Personal factors. The Self-Efficacy
for Exercise Scale was used to capture participants’ confidence in their
ability to continue exercising despite
barriers to exercise.37 The SelfEfficacy for Exercise Scale score is
represented by an average item
score from 0 (“not confident”) to 10
(“very confident”), with lower values
indicating lower self-efficacy. The
reliability, validity, and internal consistency (Cronbach ␣⫽.92) of the
Self-Efficacy for Exercise Scale have
been established.37
Environmental
factors. Drug
name, dose, and frequency data
were collected as ICF environmental
factors at each assessment.2 The
levodopa equivalent daily dose was
calculated by use of an established
protocol.38
Procedure
All measures were administered at
baseline and at 1- and 2-year annual
assessments.
Participants
were
tested
in
an
on-dopamine-
replacement-medication state that
was scheduled 0.75 to 1.5 hours
after they took their dopamine
replacement medications. To ensure
the consistency of clinical testing
procedures at the sites, we provided
research personnel with a standard
operating procedure manual and an
instructional video that described
the protocol for administering and
scoring each clinical test for people
with PD. Before study participants
were enrolled, each evaluator rated
2 video examples of participants
undergoing testing on 2 occasions
separated by 1 week. We subsequently verified the intrarater and
interrater reliability of the measures,
with intraclass correlation coefficients (1,4) ranging from .64 to .89
across measures.
Data Analysis
All data were analyzed with the IBM
SPSS statistical software program,
version 21.0 (IBM Corp, Armonk,
New York). Point estimators of central tendency and dispersion as well
as interval estimators were calculated for demographic, clinical, and
ambulatory activity parameters to
describe sample characteristics. Differences among baseline, 1-year, and
2-year assessment scores were evaluated by use of a 1-way repeatedmeasures analysis of variance. To
accommodate any violations of the
sphericity assumption, we relied on
the more conservative GreenhouseGeisser F test. Degrees of freedom
used for the corrected F test were
not necessarily whole numbers. Post
hoc pair-wise comparisons between
time points were evaluated by use of
the least significant difference
method. P values of less than .05
were considered statistically significant. The cumulative magnitude of 1and 2-year changes relative to the
baseline was quantified for each measure by use of the Cohen d for withinsubject designs.39 In a secondary analysis, we used Pearson productmoment correlations (r) to explore
Volume 95
Number 8
Physical Therapy f
1145
Table.
Baseline, 1-Year, and 2-Year Values for Study Variables, Organized by ICF Domaina
Domain
Baseline
Assessment
Variable
1-Year
Changeb
29.3 (21.7, 36.9)
⫺0.1 (0.01)
2-Year Assessment
36.8 (28.2, 45.4)c
2-Year
Changeb
BS and BF
MDS-UPDRS
section III
GDS
6.1 (3.6, 8.6)
6.7 (4.4, 9.0)
0.6 (0.13)
7.5 (4.9, 10.0)
1.4 (0.29)
Activity
MDS-UPDRS
section II
9.4 (6.4, 12.3)
9.7 (6.7, 12.7)
0.3 (0.05)
11.1 (7.7, 14.4)
1.7 (0.27)
Berg Balance Scale
51.9 (48.6, 55.3)
50.7 (46.9, 54.5)
FGA (n⫽16)
23.1 (20.3, 26.0)
21.9 (19.3, 24.6)
⫺1.2 (0.18)
10MWT, m/s
(n⫽16)
1.31 (1.16, 1.47)
1.24 (1.09, 1.39)
⫺0.07 (0.21)
1.16 (1.04, 1.29)c
⫺0.15 (0.42)
6MWT, m (n⫽13)
508.9 (445.1, 572.8)
518.1 (439.6, 596.7)
9.2 (0.06)
533.7 (453.9, 613.5)
24.8 (0.20)
9-Hole Peg Test, s
(n⫽16)d
26.3 (23.3, 29.3)
27.6 (23.1, 32.1)
1.3 (0.14)
27.1 (23.2, 31.0)
0.8 (0.11)
Participation
29.4 (23.8, 35.0)
1-Year Assessment
Daily steps
9,328 (7,503, 11,154)
⫺1.2 (0.16)
7,976 (6,678, 9,275)c
c
Moderate-intensity
minutes
18.8 (10.3, 27.3)
11.5 (5.6, 17.5)
Maximum output
62.0 (48.3, 75.7)
55.8 (44.1, 67.6)c
PDQ-39
Environmental
factors
LEDD
Personal factors
SEE Scale
17.2 (11.4, 23.0)
270.6 (155.2, 386.0)
7.0 (6.3, 7.8)
15.5 (9.5, 21.5)
399.4 (229.1, 570.0)c
6.3 (5.4, 7.2)
⫺1,352 (0.38)
⫺7.3 (0.46)
⫺6.2 (0.23)
⫺1.7 (0.15)
128.8 (0.41)
⫺0.7 (0.42)
⫺0.5 (0.06)
51.5 (48.2, 54.8)
⫺1.6 (0.24)
21.5 (18.0, 25.0)
7,383 (5,936, 8,830)c,e
9.9 (3.2, 16.6)
c,e
46.6 (35.5, 57.8)c,e
15.0 (10.2, 19.8)
521.4 (308.3, 735.0)c,e
6.3 (5.5, 7.0)
7.4 (0.41)
⫺1,945 (0.59)
⫺8.9 (0.56)
⫺15.3 (0.58)
⫺2.2 (0.21)
250.9 (0.64)
⫺0.8 (0.48)
a
All values are reported as means (95% confidence intervals) (n⫽17) unless otherwise indicated. Bold type denotes a statistically significant change (P⬍.05).
ICF⫽International Classification of Functioning, Disability and Health; BS and BF⫽body structure and function; MDS-UPDRS⫽Movement Disorder Society–
Unified Parkinson’s Disease Rating Scale (sections II and III); GDS⫽Geriatric Depression Scale; FGA⫽Functional Gait Assessment; 10MWT⫽10-Meter Walk
Test; 6MWT⫽Six-Minute Walk Test; PDQ-39⫽39-item Parkinson’s Disease Questionnaire; LEDD⫽levodopa equivalent daily dose; SEE⫽Self-Efficacy for
Exercise.
b
Values represent cumulative changes relative to the baseline and are reported as the mean change (Cohen d [effect size]) for within-subject designs.
c
Significant change relative to the baseline.
d
Values are for the dominant arm.
e
Significant change relative to the 1-year assessment.
the strength of relationships between
baseline variables and mean daily steps
at 1 year and between baseline variables and mean daily steps at 2 years
(␣⫽.05).
This study was funded primarily by
the Davis Phinney Foundation and
the Parkinson Disease Foundation.
Additional funding was provided by
Boston University Building Interdisciplinary Research Careers in Women’s Health (K12 HD043444), the
National Institutes of Health
(R01NS077959), the Utah Chapter of
the American Parkinson Disease
Association (APDA), the Greater St
Louis Chapter of the APDA, and the
APDA Center for Advanced PD
Research at Washington University.
1146
f
Physical Therapy
Volume 95
Results
The sample comprised 12 men and 5
women with a baseline mean age of
65.6 years (SD⫽9.9) and a mean
duration from diagnosis of 5.1 years
(SD⫽4.6). For 15 participants at
baseline, 14 participants at 1 year,
and 12 participants at 2 years, the
modified Hoehn and Yahr stage was
less than 3. Participants generally
adhered to wearing ambulatory
activity monitors for an entire week
(mean days of wear at baseline, 1
year, and 2 years were 6.8 [SD⫽0.5],
7.0 [SD⫽0.6], and 6.8 [SD⫽0.5],
respectively).
The amount and intensity of ambulatory activity declined significantly
during the 2-year period (for
mean daily steps: F1,81⫽7.3, P⫽.003;
Number 8
for moderate-intensity minutes:
F1,37⫽10.5, P⫽.002; for maximum
output: F1,82⫽16.0, P⬍.001). Post
hoc comparisons revealed significant
declines (P⬍.05) between baseline
and the 1-year assessment, between
baseline and the 2-year assessment,
and between the 1-year and 2-year
assessments (Table). The effect sizes
for changes in ambulatory activity
variables ranged from 0.23 to 0.46 at
1 year and from 0.56 to 0.59 at 2
years (Table). For the statistically significant changes observed, the rates
of change at 1-year and 2-year intervals for mean daily steps, moderateintensity minutes, maximum output,
and levodopa equivalent daily dose
were relatively higher than the rates
of change for 10MWT and MDSUPDRS section III values.
August 2015
Several other significant changes
occurred during the 2-year period
(Table). Like ambulatory activity,
therapeutic levodopa regimens
evolved (F1,38⫽9.4), with significant
increases in levodopa equivalent
daily dose occurring between baseline and the 1-year assessment
(P⫽.03), between baseline and the
2-year assessment (P⫽.004), and
between the 1-year and 2-year assessments (P⫽.009). Motor impairment
worsened (F1,89⫽6.2), but a significant increase in MDS-UPDRS section
III scores relative to those at the
baseline occurred only at the 2-year
assessment (P⫽.003). Similarly, gait
speed declined (F1,97⫽6.0), but a significant change relative to gait speed
at the baseline occurred only after 2
years (P⫽.005). Effect sizes corresponding to statistically significant
changes in clinical measures ranged
from 0.41 to 0.64. None of the
remaining clinical measures changed
significantly at either the 1-year or
the 2-year assessment (P⬎.05).
Baseline values for all ambulatory
activity and physical performance
measures
(mean
daily
steps,
moderate-intensity minutes, maximum output, BBS, FGA, 10MWT,
6MWT, and 9HPT) were significantly
associated with mean daily steps at
the 1- and 2-year assessments
(P⬍.05). For each of these relationships, the mean correlation coefficient was at least .6, with the highest
mean correlation occurring for baseline mean daily steps (r⫽.76). Age
was the only factor unrelated to
physical performance to have a similar mean strength of association
(r⫽.59). The remaining baseline factors all had weaker, nonsignificant
relationships with 1- and 2-year
mean daily steps (mean correlation
coefficients of ⬍.5). Without exception, greater previous impairment,
activity limitation, or participation
restriction was associated with
reduced future ambulatory activity.
August 2015
Discussion
In the present study, we analyzed
ambulatory activity data and related
factors collected annually over 2
years from a sample of people
(n⫽17) whose baseline and 1-year
data had been included in our preliminary work (n⫽33).8 Our 2-year
results revealed a continued pattern
of decline in the amount and intensity of ambulatory activity (Table).
Specifically, the mean number of
accumulated steps per day (ie, steps)
and the mean step rate during the 30
most active consecutive minutes of
the day (ie, maximum output)
declined during the second year at
rates similar to those observed during the first year. In contrast, the rate
of decline in the mean number of
minutes per day in which at least 100
steps were recorded (ie, moderateintensity minutes) was lower during
the second year than during the first
year. Nonetheless, consistent with
the previous study,8 the collective
cumulative 2-year decline in ambulatory activity appeared to outpace the
worsening of all other impairments,
activity limitations, and participation
restrictions under study.
The results suggested that natural
ambulatory behavior may be a particularly robust indicator of decline,
especially during the earliest stages
of PD, when motor impairment
remains relatively mild. However,
whether the rate of the observed
2-year decline in ambulatory activity
would have continued in a relatively
linear fashion with further disease
progression remains unclear. Moreover, given that participants were
enrolled in the study at various,
although relatively early, points in
the disease process, the collective
rate of ambulatory activity decline
(Table) was more likely to have
reflected sample characteristics
rather than population characteristics. These caveats highlight the preliminary nature of the study and lay
an important foundation for future
research.
The study findings may have been
confounded by methodological differences between ambulatory monitoring and clinical assessment
approaches. Ambulatory monitoring
is relatively unobtrusive and allows
people to interact naturally with
their customary environment over
an extended period of time. In contrast, clinical assessments are often
conducted under optimal performance conditions, in which patients
with PD are likely to have taken medications; walking surfaces are uncluttered, flat, and well lit; and few distractions are present. Clinical
assessments may be more subject
than ambulatory monitoring to
patients’ awareness that they are
being scrutinized, which may engender beliefs about researcher or clinician expectations and thereby lead
to alterations in behavior.40 Taken
together, these methodological differences are important considerations when rates of disablement
across the domains of the ICF model
are compared.
Expanded Comparison With
Clinical Measures
The ICF model portrays decrements
in human function and disability as
the product of dynamic interactions
among various health conditions and
contextual factors.1 In the present
study, we sought to expand our preliminary work8 by attempting to
compare the individual trajectories
of representative measures from
each domain of the ICF model (Figure). Consistent with previous investigations,3–5,7 our results supported
the idea that individual trajectories
of worsening motor, mobility, and
ADL function are not parallel; they
appear instead to occur at different
rates and at different points in the
overall disease course.
Volume 95
Number 8
Physical Therapy f
1147
In our sample, the primary driver of
disablement during the study period
appeared to be the dynamic interactions of worsening motor function
(ie, impairment), declining gait
speed (ie, activity limitation), and
diminishing ambulatory activity (ie,
participation restriction). Disablement emerged despite relatively minimal disability at baseline and contextual factors that were likely to
support optimal functioning (ie, sustained self-efficacy for exercise and
increasing levodopa dosage [Table]).
The results were consistent with a
previous report of difficulty with
walking as a relatively early symptom
of impending disability.3
Baseline Variables Associated
With Future Ambulatory Activity
The prospect of progressive inactivity in PD is of great concern because
of its implications for health8,12–17
and its potential association with
accelerating disability.7 In this context, baseline variables that might
predict future ambulatory activity
are of interest to clinicians and
researchers seeking to develop effective exercise and physical activity
interventions. Although many of the
variables that we studied showed
predictive potential, it appeared that
baseline ambulatory activity was
most strongly associated with ambulatory activity at the 1- and 2-year
assessments. This result appeared to
be consistent with the popular
maxim that past behavior often predicts future behavior, especially
when the behavior is well learned
and routinely performed in stable
contexts.41 Moreover, this result was
remarkable for its simplicity, especially given the potential for many
factors to influence exercise and
physical activity behavior in people
with PD.42
Interestingly, self-efficacy, which we
previously reported to be associated
with current exercise behavior in
PD,42 was only weakly associated
1148
f
Physical Therapy
Volume 95
with future ambulatory activity. In
our view, this result did not necessary call into question the important
role of self-efficacy in exercise
behavior; rather, it highlighted the
potential differences between factors affecting current and future
exercise behaviors and between the
more specific construct of exercise
behavior and the broader construct
of ambulatory activity in general.43
Clinical Implications
A “secondary prevention” approach
to health promotion, injury prevention, and rehabilitation intervention
for people with PD is one designed
to delay the onset of and to slow the
rate of disablement.44 Our results
suggested that people in relatively
early disease stages, especially
before the onset of measurable postural instability or overt gait disturbance, may benefit from interventions that specifically target public
health recommendations for daily
physical activity.12–14,16 Whether
social, recreational, occupational, or
related to exercise, recommended
levels of routine physical activity
provide the necessary substrate for
sustaining long-term reductions in
disability risk and optimal levels of
health-related quality of life.45,46
Limitations and Future Directions
The present study and our related,
preliminary work8 were intended to
contribute to a growing body of evidence suggesting that physical activity decline is an important feature of
early disablement in PD.9 –11 However, the study clearly had limitations. First, our small, relatively
homogeneous sample of people in
relatively early disease stages limited
the external validity of our findings.
Second, the participants in the present study (n⫽17) may not have been
fully representative of the original
cohort (n⫽33). Although reasons for
withdrawal were not collected,
health conditions, cognitive impairment, or both may have limited at
Number 8
least some participants’ ability to
successfully wear an activity monitor
at the 2-year assessment. As a result,
the collective decline of the remaining participants during the second
year was likely to have been a conservative estimate. Third, compared
with other ICF domains, the ICF
activity domain was highly represented by our measures. Finally,
although ambulatory activity metrics
have the potential to reveal much
about ongoing and evolving ambulatory behavior, our sample was evaluated at only 2 time points separated
by 1 year; therefore, our study was
limited by low resolution.
Future PD research that combines
ambulatory activity monitoring with
a broader and more balanced array of
measures across ICF domains would
help to further illuminate the
dynamic interactions among evolving facets of disablement, either as
they occur naturally or in response
to intervention. In particular, measures that capture impairments in
body structure or function, participation restrictions, or personal and
environmental factors are needed.
The inclusion of larger, more diverse
samples of people with PD would
help to more fully describe the problem of physical inactivity across disease stages. Ultimately, investigators
should seek to determine the extent
to which—and the physiological
mechanisms for how—sustained patterns of recommended daily physical
activity might slow the rate of disablement in PD.
All authors provided concept/idea/research
design. Dr Cavanaugh, Dr Ellis, and Dr Dibble provided writing. Dr Ellis, Dr Ford, Dr
Foreman, and Dr Dibble provided data analysis. Dr Ellis, Dr Earhart, Dr Foreman, and Dr
Dibble provided project management and
fund procurement. Dr Ellis, Dr Foreman, and
Dr Dibble provided participants and facilities/equipment. Dr Ellis, Dr Earhart, and Dr
Foreman provided consultation (including
The authors acknowledge the participants in
August 2015
this research as well as Tami DeAngelis, PT,
GCS, for her assistance and persistence in
educating participants, programming the
monitors, and ensuring the return of the
monitors.
The institutional review board at each institution approved the study protocol.
This study was funded primarily by the Davis
Phinney Foundation and the Parkinson Disease Foundation. Additional funding was
provided by Boston University Building Interdisciplinary Research Careers in Women’s
Health (K12 HD043444), the National Institutes of Health (R01NS077959), the Utah
Chapter of the American Parkinson Disease
Association (APDA), the Greater St Louis
Chapter of the APDA, and the APDA Center
for Advanced PD Research at Washington
University.
DOI: 10.2522/ptj.20140498
References
1 Jette AM. Toward a common language for
function, disability, and health. Phys Ther.
2006;86:726 –734.
2 International Classification of Functioning, Disability and Health: ICF. Geneva,
Switzerland: World Health Organization;
2001.
3 Shulman LM, Gruber-Baldini AL, Anderson
KE, et al. The evolution of disability in Parkinson disease. Mov Disord. 2008;23:790 –
796.
4 Alves G, Wentzel-Larsen T, Aarsland D,
Larsen JP. Progression of motor impairment and disability in Parkinson disease: a
population-based study. Neurology. 2005;
65:1436 –1441.
5 Jankovic J, Kapadia AS. Functional decline
in Parkinson disease. Arch Neurol. 2001;
58:1611–1615.
6 Poewe W, Mahlknecht P. The clinical progression of Parkinson’s disease. Parkinsonism Relat Disord. 2009;15(suppl
4):S28 –S32.
7 Shulman LM. Understanding disability in
Parkinson’s disease. Mov Disord. 2010;
25(suppl 1):S131–S135.
8 Cavanaugh JT, Ellis TE, Earhart GM, et al.
Capturing ambulatory activity in Parkinson’s disease. J Neurol Phys Ther. 2012;
36:51–57.
9 White DK, Wagenaar RC, Del Olmo M,
Ellis T. Test-retest reliability of 24 hours of
activity monitoring in individuals with Parkinson’s disease in home and community.
Neurorehabil Neural Repair. 2006;21:
327–340.
10 White DK, Wagenaar RC, Ellis T. Monitoring activity in individuals with Parkinson
disease: a validity study. J Neurol Phys
Ther. 2006;30:12–21.
August 2015
11 Skidmore FM, Mackman CA, Pav B, et al.
Daily ambulatory activity levels in idiopathic Parkinson disease. J Rehabil Res
Dev. 2008;45:1343–1348.
26 Berg KO, Wood-Dauphinée SL, Williams JI,
Maki B. Measuring balance in the elderly:
validation of an instrument. Can J Public
Health. 1992;83(suppl 2):S7–S11.
12 Tudor-Locke C, Hatano Y, Pangrazi RP,
Kang M. Revisiting “how many steps are
enough?” Med Sci Sports Exerc. 2008;40(7
suppl):S537–S543.
27 Qutubuddin AA, Pegg PO, Cifu DX, et al.
Validating the Berg Balance Scale for
patients with Parkinson’s disease: a key to
rehabilitation evaluation. Arch Phys Med
Rehabil. 2005;86:789 –792.
13 Tudor-Locke C, Craig CL, Aoyagi Y, et al.
How many steps/day are enough? For
older adults and special populations. Int J
Behav Nutr Phys Act. 2011;8:80.
14 Tudor-Locke C, Washington TL, Hart TL.
Expected values for steps/day in special
populations. Prev Med. 2009;49:3–11.
15 Earhart GM, Falvo MJ. Parkinson disease
and exercise. Compr Physiol. 2013;3:833–
848.
16 Office of Disease Prevention and Health
Promotion. Physical activity guidelines.
Available at: http://www.health.gov/
paguidelines/. Accessed April 10, 2015.
28 Walker ML, Austin AG, Banke GM, et al.
Reference group data for the Functional
Gait Assessment. Phys Ther. 2007;87:
1468 –1477.
29 Wrisley DM, Marchetti GF, Kuharsky DK,
Whitney SL. Reliability, internal consistency, and validity of data obtained with
the Functional Gait Assessment. Phys
Ther. 2004;4:906 –918.
30 Brusse KJ, Zimdars S, Zalewski KR, Steffen
TM. Testing functional performance in
people with Parkinson disease. Phys Ther.
2005;85:134 –141.
17 Cavanaugh JT, Gappmaier VO, Dibble LE,
Gappmaier E. Ambulatory activity in individuals with multiple sclerosis. J Neurol
Phys Ther. 2011;35:26 –33.
31 ATS Committee on Proficiency Standards
for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the sixminute walk test. Am J Respir Crit Care
Med. 2002;166:111–117.
18 Bowden MG, Hannold EM, Nair PM, et al.
Beyond gait speed: a case report of a multidimensional approach to locomotor
rehabilitation outcomes in incomplete spinal cord injury. J Neurol Phys Ther. 2008;
32:129 –138.
32 Earhart GM, Cavanaugh JT, Ellis T, et al.
The 9-hole PEG test of upper extremity
function: average values, test-retest reliability, and performance in people with
Parkinson disease. J Neurol Phys Ther.
2011;35:157–163.
19 Dibble LE, Cavanaugh JT, Earhart GM,
et al. Charting the progression of disability
in Parkinson disease: study protocol for a
prospective longitudinal cohort study.
BMC Neurol. 2010;10:110.
33 Munneke M, de Jong Z, Zwinderman AH,
et al. The value of a continuous ambulatory activity monitor to quantify the
amount and intensity of daily activity in
patients with rheumatoid arthritis. J Rheumatol. 2001;28:745–750.
20 Hughes AJ, Daniel SE, Kilford L, Lees AJ.
Accuracy of clinical diagnosis of idiopathic
Parkinson’s disease: a clinico-pathological
study of 100 cases. J Neurol Neurosurg
Psychiatry. 1992;55:181–184.
34 Manns PJ, Baldwin E. Ambulatory activity
of stroke survivors: measurement options
for dose, intensity, and variability of activity. Stroke. 2009;40:864 – 867.
21 Goetz CG, Poewe W, Dubois B, et al. The
MDS-UPDRS: How to Apply the New
UPDRS in Practice and Research Settings.
Milwaukee, WI: International Parkinson
and Movement Disorder Society; 2006.
35 Den Oudsten BL, Van Heck GL, De Vries J.
The suitability of patient-based measures
in the field of Parkinson’s disease: a systematic review. Mov Disord. 2007;22:
1390 –1401.
22 Goetz CG, Tilley BC, Shaftman SR, et al.
Movement Disorder Society–sponsored
revision of the Unified Parkinson’s Disease
Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov
Disord. 2008;23:2129 –2170.
36 Jenkinson C, Fitzpatrick R, Peto V, et al.
The Parkinson’s Disease Questionnaire
(PDQ-39): development and validation of a
Parkinson’s disease summary index score.
Age Ageing. 1997;26:353–357.
37 Resnick B, Jenkins LS. Testing the reliability and validity of the Self-Efficacy for Exercise Scale. Nurs Res. 2000;49:154 –159.
23 Steffen T, Seney M. Test-retest reliability
and minimal detectable change on balance
and ambulation tests, the 36-item ShortForm Health Survey, and the Unified Parkinson Disease Rating Scale in people with
parkinsonism. Phys Ther. 2008;88:733–
746.
38 Tomlinson CL, Stowe R, Patel S, et al. Systematic review of levodopa dose equivalency reporting in Parkinson’s disease.
Mov Disord. 2010;25:2649 –2653.
24 Yesavage JA, Brink TL, Rose TL, et al.
Development and validation of a geriatric
depression screening scale: a preliminary
report. J Psychiatr Res. 1982;17:37– 49.
39 Lakens D. Calculating and reporting effect
sizes to facilitate cumulative science: a
practical primer for t-tests and ANOVAs.
Front Psychol. 2013;4:863.
25 Mondolo F, Jahanshahi M, Grana A, et al.
The validity of the Hospital Anxiety and
Depression Scale and the Geriatric Depression Scale in Parkinson’s disease. Behav
Neurol. 2006;17:109 –115.
40 McCambridge J, Witton J, Elbourne DR.
Systematic review of the Hawthorne
effect: new concepts are needed to study
research participation effects. J Clin Epidemiol. 2014;67:267–277.
Volume 95
Number 8
Physical Therapy f
1149
41 Ouellette JA, Wood W. Habit and intention
in everyday life: the multiple processes by
which past behavior predicts future
behavior. Psychol Bull. 1998;124:54 –74.
42 Ellis T, Cavanaugh JT, Earhart GM, et al.
Factors associated with exercise behavior
in people with Parkinson disease. Phys
Ther. 2011;91:1838 –1848.
43 Manns PJ, Dunstan DW, Owen N, Healy
GN. Addressing the nonexercise part of
the activity continuum: a more realistic
and achievable approach to activity programming for adults with mobility disability? Phys Ther. 2012;92:614 – 625.
1150
f
Physical Therapy
Volume 95
44 Ellis T, Motl RW. Physical activity behavior
change in persons with neurologic disorders: overview and examples from Parkinson disease and multiple sclerosis. J Neurol Phys Ther. 2013;37:85–90.
45 Paterson DH, Warburton DE. Physical
activity and functional limitations in older
adults: a systematic review related to Canada’s Physical Activity Guidelines. Int J
Behav Nutr Phys Act. 2010;7:38.
Number 8
46 Spirduso WW, Cronin DL. Exercise doseresponse effects on quality of life and independent living in older adults. Med Sci
Sports Exerc. 2001;33(6 suppl):S598 –
S608.
August 2015
Research Report
Therapist-Designed Adaptive Riding in
Children With Cerebral Palsy:
Results of a Feasibility Study
Mattana Angsupaisal, Baudina Visser, Anne Alkema, Marja Meinsma-van der Tuin,
Carel G.B. Maathuis, Heleen Reinders-Messelink, Mijna Hadders-Algra
Background. It is debatable whether adaptive riding (AR) in children with
cerebral palsy (CP) improves postural control and gross motor development.
Objective. The study aim was to explore the feasibility of an extensive assessment
M. Angsupaisal, PT, MSc, Division
of Developmental Neurology,
Department of Paediatrics, University of Groningen, University
Medical Center Groningen, Groningen, the Netherlands.
B. Visser, PT, MPPT, Division of
Developmental
Neurology,
Medical Center Groningen.
A.
Alkema,
BSc,
Division
of Developmental Neurology,
Medical Center Groningen.
protocol for a randomized controlled trial of therapist-designed adaptive riding
(TDAR) in children with CP, with the goals of assessing the effect on child outcomes
and evaluating working mechanisms of sitting postural control.
M. Meinsma-van der Tuin, MD,
Rehabilitation Center Revalidatie
Friesland, Beetsterzwaag, the
Netherlands.
Design. A pretest-posttest group design with 2 baseline measurements was used.
C.G.B. Maathuis, MD, PhD,
Department of Rehabilitation
Medicine, Center for Rehabilitation, University of Groningen, University Medical Center Groningen.
Methods. Six children (1 girl, 5 boys; age range⫽6 –12 years, median age⫽8 years
9 months) with bilateral spastic CP (Gross Motor Function Classification System level
III) participated. Outcomes were evaluated 3 times (T0, T1, and T2) at 6-week
intervals. T0 and T1 were baseline measurements; between T1 and T2, a TDAR
intervention including an integrated program of postural challenge exercises (2 times
per week for 1 hour) was applied. The complex protocol included the 88-item Gross
Motor Function Measure (GMFM-88) and electromyographic (EMG) recording of
postural muscle activity during reaching while sitting (EMG recording at T1 and T2
only).
Results. The protocol was feasible. Median GMFM-88 scores changed from 64.4 at
T0 to 66.7 at T1 and from 66.7 at T1 to 73.2 at T2. The change scores for all children
exceeded the minimal clinically important difference of the GMFM-88. Five of
6 children showed a decrease in stereotyped top-down recruitment between T1
and T2.
Limitations. Study limitations included the lack of a control group, small sample
size, and potential assessor bias for all but the EMG parameters.
Conclusions. The feasibility of the complex protocol was established. The data
suggested that a 6-week TDAR intervention may improve gross motor function and
may reduce stereotyped postural adjustments in children with CP. The limited results
warrant replication in a well-powered randomized controlled trial.
H. Reinders-Messelink, PhD, Rehabilitation
Center
Revalidatie
Friesland.
M. Hadders-Algra, MD, PhD, Division of Developmental Neurology,
Medical
Center
Groningen,
Y3208, Hanzeplein 1, 9713 GZ
Groningen, the Netherlands.
Address
all
correspondence
to
Dr
Hadders-Algra
at:
[email protected].
[Angsupaisal M, Visser B, Alkema
A, et al. Therapist-designed adaptive riding in children with cerebral palsy: results of a feasibility
study. Phys Ther. 2015;95:
1151–1162.]
Association
April 23, 2015
Submitted: April 4, 2014
this article at:
ptjournal.apta.org
August 2015
Volume 95
Number 8
Physical Therapy f
1151
Adaptive Riding in Children With Cerebral Palsy
E
quine-assisted activities and
therapies are frequently used in
children with cerebral palsy
(CP).1,2 However, it is debatable
whether equine-assisted activities
and therapies are effective in reducing bodily impairments, such as spasticity and impaired posture and balance, and in lessening limitations in
activities and limitations in participation in nonequine contexts.2,3
The limited evidence on effectiveness may be partially explained by
the heterogeneity in the therapies
applied. The heterogeneity is
reflected in past and present terminology. In the past, therapies were
labeled “hippotherapy,” “therapeutic riding,” or “horseback riding therapy.”1,2 However, these terms were
confusing because the services delivered in the different approaches
overlapped partially. The American
Hippotherapy Association1 recently
suggested standard terminology to
describe the 2 basic forms of equineassisted activities and therapies: (1)
hippotherapy, implying that a therapist (physical therapist, occupational
therapist, or speech therapist) uses
the movement or the environment
of the horse (or both) to reach specific therapy goals, and (2) adaptive
riding (AR), implying recreational
horseback riding lessons adapted for
people with disabilities.1 Hippotherapy sessions are one-to-one sessions of a therapist and a patient,
whereas AR is provided to groups.1 A
systematic review and meta-analyses
of the 2 forms of equine-assisted
activities and therapies revealed that
hippotherapy has been better investigated than AR.3 Short-term hippotherapy was found to be associated
with a significant reduction in asymmetrical activity of the hip adductor
muscle.3,4 The meta-analyses3 indicated that neither hippotherapy nor
AR was associated with a statistically
significant improvement in gross
motor function, as measured with
the Gross Motor Function Measure
1152
f
Physical Therapy
Volume 95
(GMFM),5 or with an improvement
in stride length.
Equine-assisted activities and therapies are assumed to improve the postural control of children with CP and
therewith to improve gross motor
function and eventually function in
daily life.1,2,4,6,7 Dysfunctional postural control is a major limitation in
children with CP. The postural dysfunction directly influences daily
activity performance, the extent
depending on the degree of disability.8 In the organization of postural
control, 2 functional levels can be
distinguished. The first level consists
of direction specificity, meaning that
when the body sways forward, such
as during reaching, primarily dorsal
muscles are activated, whereas backward body sway results primarily in
ventral muscle recruitment.9 The
second level of control is involved
with fine-tuning of the directionspecific adjustments in a particular
situation, for instance, by changing
the order of recruitment of the
direction-specific muscles.10 Children with CP generally have
direction-specific
adjustments.8,10
However, children with CP virtually
always show dysfunction at the second level of control. For instance,
during reaching in the sitting position, they show stereotyped topdown recruitment instead of the variable recruitment of peers developing
typically.10 Children developing typically exhibit a mixture of top-down,
bottom-up, and more variable patterns of recruitment order.8,10
Recent literature indicates that therapy based on the principles of motor
learning,11,12 including trial-and-error
learning, is more effective in improving the motor abilities of children
with CP than therapy that involves
handling and assisting the child
(hands-on therapy).13,14 Therefore,
we opted to study the effect of an AR
intervention supervised by a pediatric physical therapist. The therapist-
Number 8
designed AR (TDAR) intervention
involved minimal hands-on guidance
and maximal self-practice of the
child and included an integrated program of varied postural challenge
exercises.
The primary aim of this preliminary
study was to explore the feasibility
of an extensive assessment protocol
for a randomized controlled trial
(RCT) of the effect of TDAR in children with spastic CP, with the goals
of assessing effectiveness across all
levels of the International Classification of Functioning, Disability
and Health: Children and Youth
Version—(ICF-CY)15 and evaluating
working mechanisms underlying a
potentially beneficial effect of TDAR.
A pretest-posttest group design with
2 baseline measurements was used.
The secondary aim of this preliminary study was to assess the effect of
the intervention. The primary outcome parameter was gross motor
function, measured with the 88-item
Gross Motor Function Measure
(GMFM-88),5 with dimension D
(standing) and dimension E (walking, running, and jumping) serving
as goal areas.5 We hypothesized that
6 weeks of TDAR would result in
change scores in dimensions D
and E that would exceed the minimal
clinically important differences
(MCIDs).16 Secondary outcome
parameters were spasticity, function
in daily life, quality of life, and selfesteem. An important tool for assessing one of the working mechanisms
was the evaluation of postural control by means of surface electromyographic (EMG) recording during
reaching while sitting.10,17
Available With
This Article at
ptjournal.apta.org
• eAppendix: Classification of
Activities and Assistance During
Equine Movement
August 2015
Method
Participants
Six participants (5 boys, 1 girl; age
range⫽6 –12 years, median age⫽8
years 9 months) were recruited
through the outpatient clinic at
Rehabilitation Center Revalidatie
Friesland, Beetsterzwaag, in the
northern part of the Netherlands.
The pediatric physiatrist (M.M.) and
pediatric physical therapist (B.V.)
had prescribed TDAR with the aim of
improving the children’s gross
motor function. Children older than
8 years and all parents signed an
informed consent form for participation; this form was approved by the
Medical Ethical Committee of the
University Medical Center Groningen. All participants met the following 4 inclusion criteria: diagnosis
of spastic CP,18 Gross Motor Function Classification System (GMFCS)19
level II or III, age of 6 to 12 years, and
ability to cooperate and follow verbal instructions. Children were
excluded if they had a predominantly dyskinetic movement disorder (because their postural problems might differ from those of children with spastic CP), severe behavioral problems, unstable epilepsy
(ⱖ2 seizures per week), or a known
allergy to or fear of horses or if they
had received treatment with botulinum toxin during the preceding 6
months or orthopedic or neurologic
surgery during the preceding year.
All 6 participants were diagnosed
with bilateral spastic CP (GMFCS
level III). They needed walking aids
and orthoses in daily life. Four children had no AR experience; the 2
oldest children had 6 to 8 months of
AR experience (in the preceding
year). All participants received their
regular therapy at the same frequency throughout the baseline and
intervention periods of the study.
Design of the Study
A pretest-posttest group design with
2 baseline measurements was used.
August 2015
Figure 1.
Schematic presentation of the study design, including the outcome measures.
Moments of evaluation: T0⫽6 weeks before the start of the therapist-designed adaptive
riding (AR) intervention, T1⫽start of the intervention, T2⫽end of the intervention. V1
and V2 represent the moments of video recording of the intervention during the second
and eleventh sessions, respectively. In addition to the measurements shown, the child’s
appreciation of each intervention session was assessed with a 5-point “smiley scale.”
The therapist-designed AR program was delivered with minimal hands-on guidance and
maximal self-practice (1-hour group class, twice weekly). GMFM-88⫽88-item Gross
Motor Function Measure, EMG⫽surface electromyography, PEDI⫽Dutch version of the
Pediatric Evaluation of Disability Inventory.
Outcomes were evaluated with an
extensive assessment protocol 3
times (T0, T1, and T2) at 6-week
intervals (Fig. 1). T0 and T1 were
baseline measurements; between T1
and T2, a TDAR intervention (2 times
per week for 1 hour) was applied.
Two sessions were video recorded
to improve understanding of the
contents of the TDAR program.
TDAR
The TDAR intervention was conducted in the indoor arena of the
Riding Center Onder de Linde,
which collaborates with Rehabilitation Center Revalidatie Friesland. All
children participated in the same
1-hour group class, which met twice
weekly. It started at T1 and lasted
until T2; that is, 12 TDAR sessions
were provided over 6 weeks. Before
the study began, the pediatric physical therapist (B.V.) discussed the
individual goals and challenges of
each child with the certified therapeutic riding instructor, and
together they designed the contents
of the TDAR intervention for each
child and each session. Next, the riding instructor selected 6 trained
horses, all of which fit the riding
needs of each participant. Our TDAR
intervention deliberately opts for
varied experience with horses
because variation in practice and
across contexts is associated with
better skill development.13,20 In addition, the instructor selected for each
child a saddle pad, a helmet, an experienced horse handler, and a trained
side walker (one or none).
The therapeutic riding instructor
directed the class with the 6 pairs of
children and horses. The instructor
herself was coached by the pediatric
physical therapist (B.V.), who
attended each riding class session.
Coaching is one of the novel and
promising strategies used in pediatric physical therapy and pediatric
rehabilitation.21,22 The riding instructor coached and responded to the
group of children as a whole. We
opted for a group approach for 2
reasons. First, our program emphasizes the need for self-practice and
Volume 95
Number 8
Physical Therapy f
1153
minimization of hands-on guidance—also a strategy in line with
novel approaches in pediatric physical therapy.13,20 Second, group practice fosters a child’s social skills and
is, in general, associated with
increased pleasure. The horse handler led the horse according to the
instructor’s directions. The side
walker walked alongside the horse,
coached the child during riding, and
ensured safety on the basis of the
instructions from the riding instructor. To avoid a horse-specific effect
on the children’s performance and
to increase variation in experience,
we rotated horse use: each week,
each child used a different horse, so
that at the end of the intervention,
each child had been riding for 1
week on 1 of the 6 horses.13,20
The TDAR protocol included an integrated program of postural challenge
exercises in various riding situations
(eAppendix, available at ptjournal.
apta.org). The protocol also focused
on riding skills, as mastery of riding
skills is a major motivator for activity
based on equine movement performance. The program became
increasingly difficult during the
course of 12 sessions, challenging
the child’s postural control. Examples of exercises included raising the
arms high up, giving a high five to a
side walker, rewarding the horse by
tapping the horse’s neck (involving
forward leaning), or leaning backward to touch the back of the horse
when the horse stood still. Five types
of saddles were used: sheepskin, 2
different modifications of sheepskin,
and 2 typical saddles (Western and
English saddles) (eAppendix). The
sheepskin modification saddles may
be regarded as the “golden mean”
between the sheepskin and the typical saddles because— on the one
hand—they are less broad and less
firm than a typical saddle and do not
include stirrups, but— on the other
hand—they are more preformed and
more firm than a sheepskin saddle.
1154
f
Physical Therapy
Volume 95
The use of the saddles was varied
across children, horses, and sessions.13,20 Note that backward leaning exercises could be performed
only when a sheepskin saddle or a
sheepskin modification saddle was
used. To adapt the contents of the
TDAR sessions to individual capacities, the therapeutic riding instructor
recorded the children’s riding performances in activity logs. The pediatric physical therapist (B.V.) used
the activity logs in her coaching of
the riding instructor to adjust the
contents of the next riding session
for the children’s needs and
challenges.
which is a new approach for detecting meaningful change in clinical
and research settings.16,26 Recently,
the MCID of the total GMFM-88 was
studied in children who were 2 to 7
years of age.26 In addition, the
MCIDs of goal dimensions D and E
were established in children and
adolescents who were 4 to 18 years
of age.16 For children functioning at
GMFCS level III, the minimum
change scores needed for MCIDs of
medium (0.5) and large (0.8) effect
sizes for dimension D were 1.5 and
2.4, respectively; those for dimension E were 1.8 and 3.0,
respectively.16
Outcome Measures
We used an extensive assessment
protocol. The same assessment
battery was used at each evaluation,
with 1 exception: At T0, no EMG
recordings were obtained. Electromyographic
recordings
and
GMFM-88 and Tardieu Scale assessments for each child were completed within 1 day at Rehabilitation
Center Revalidatie Friesland. All children were tested within 1 week,
with T1 occurring in the week
before the start of the TDAR intervention and T2 occurring in the
week after the last TDAR session.
The parents completed questionnaires within 3 days after the assessment date. The complex assessment
protocol was administered by experienced pediatric physical therapists
(B.V. and M.A.), who were not
masked with regard to assessment
time (T0, T1, or T2).
The spasticity of the hip adductor,
hamstring,
gastrocnemius,
and
biceps brachii muscles was measured with the modified Tardieu
Scale.27 This scale27 takes into
account the velocity dependence of
spasticity for describing the quality
of muscle reaction from grades 0 to 4
and defines the moment of the
“catch,” seen in the passive range of
motion at a particular joint angle at a
fast passive stretch. The difference
between the 2 angles (R2 [passive
range of motion following slow
velocity stretch] ␮R1 [angle of catch
following fast velocity stretch]
range) represents the level of
dynamic restriction in the joint.27
The reliability and validity of the
scale are sufficient.28
The GMFM-88 was the primary outcome measure; dimension D (standing) and dimension E (walking, running, and jumping) were the goal
areas, as the participants were
school-aged children who were able
to walk with walking aids.5 The reliability, validity, and responsiveness
of GMFM scores in children with CP
are highly acceptable.5,23–26 It is
important to understand the MCID,
Number 8
The Dutch version of the Pediatric
Evaluation of Disability Inventory
(PEDI)29 was used to measure function in daily life. The PEDI assesses
function in 3 domains: self-care,
mobility, and social function. The
interrater and intrarater reliabilities
of the PEDI are good (intraclass correlation coefficients⫽.95–.99).30 The
PEDI has been validated as a responsive tool, allowing the detection of
change over a 6-month period in
children with CP.31 In addition,
MCIDs for the PEDI mobility domain
were recently established by Ko.26
August 2015
The range of MCIDs (0.3 SD, 0.5 SD,
and 0.8 SD at baseline) for the PEDI
mobility domain for children functioning at GMFCS level III ranged
from 2.61 to 6.96.26
The parents completed 3 questionnaires: the Behavioral Rating Scale of
Presented Self-Esteem,32 the generic
KIDSCREEN-52,33 and the CP
module of the disease-specific
DISABKIDS.34 We included these
questionnaires on the basis of anecdotal reports of parents stating that
their child’s self-esteem and overall
pleasure in life improved during
TDAR. The Behavioral Rating Scale
of Presented Self-Esteem has 15
items assessing children’s behavioral
manifestations of self-esteem (eg,
self-confidence, independence, and
initiative) and children’s socialemotional expression. Items are
rated on a 4-point Likert scale. The
scale has good validity and internal
consistency.32 The KIDSCREEN-5233
and the DISABKIDS34 are tools for
measuring health-related quality of
life (eg, independence, physical limitations and well-being, self-perception, and peer and social support).
Both tools are suitable for a large age
range and have acceptable test-retest
reliability, internal consistency, and
validity; the tested domains cover a
substantial part of the ICF-CY
domains.33–35 Data on the sensitivity
to change, including MCIDs, of the 3
questionnaires are lacking. The children’s appreciation of TDAR was
evaluated with a 5-point “smiley
scale” after each session.
Assessment of Postural Control
Procedures. At T1 and T2, postural control during sitting while
reaching was measured with surface EMG. The children sat on a table
without back or foot support. The
children reached with their dominant arm to a small toy presented in
the midline at arm-length distance.
Muscle activity was recorded continuously with bipolar surface elecAugust 2015
trodes (interelectrode distance: 14
mm). Electrodes were applied to the
reaching side of the body on 5 postural muscles (sternocleidomastoid,
neck extensor, rectus abdominis,
thoracic extensor, and lumbar extensor) and 4 arm muscles (deltoid, pectoralis major, biceps, and triceps
brachii). The sessions were recorded
in frontal-lateral and lateral views by
2 video cameras. The EMG signal
was recorded at a sampling rate of
500 Hz with the Portilab software
program (Twente Medical Systems
International,
Enschede,
the
Netherlands).17
EMG analysis. Electromyographic
analysis was performed by a medical
master’s degree student (A.A.) who
had not been involved in data collection and who was masked for the
timing of the assessment (before or
after intervention). The analysis was
carried out with the PedEMG program (Division of Developmental
Neurology, Department of Paediatrics, University Medical Center Groningen, Groningen, the Netherlands).17 The author who performed
the EMG analysis was trained to use
PedEMG, which allows for a synchronous analysis of EMG and video
data. In brief, the PedEMG program
integrates video analysis and EMG
analysis to allow for continuous
monitoring of the results. The program uses the dynamic threshold statistical algorithm of Staude and
Wolf36 to determine onsets of phasic
EMG activity. Before onsets were
determined, the signal was filtered
for 50-Hz noise with a fifth-order
Chebyshev stop-band filter. Signal
artifacts and cardiac activity were
identified when appropriate. Clear
signal artifacts were identified manually. Cardiac activity (QRS complexes) was identified by use of a
pattern recognition algorithm based
on a linear derivative approximation
of the signal with a combination of
the repeating pattern and specific
shapes of the QRS complexes.17
The activity of the postural muscles
was considered to be related to the
arm movement if increased muscle
activity was found within a time window consisting of 100 milliseconds
before activation of the “prime
mover,” that is, the arm muscle that
was activated first, and the duration
(the first 1,000 milliseconds) of
the reaching movement. For each
postural evaluation session, 2 parameters were calculated. The first
parameter was the percentage of
direction-specific trials at the neck or
trunk level (or both); direction specificity meant that the “directionspecific” (ie, dorsal) muscle was
recruited before the antagonistic
ventral muscle or without antagonistic activation. The second parameter
was the order of recruitment of the
direction-specific muscles in the
direction-specific trials, resulting in
the percentage of trials with topdown, bottom-up, simultaneous, or
mixed order of recruitment. Recruitment order could be determined
only when at least 2 directionspecific muscles showed significant
phasic activity. We also determined
the preferred recruitment order,
defined as the order that was used
most frequently.17
Video Recording of
TDAR Sessions
The second and eleventh sessions
(V1 and V2, respectively; Fig. 1)
were video recorded by 6 master’s
degree students, each filming one
child-horse pair. The TDAR contents
were analyzed with The Observer
(version XT 9.0, Noldus, Wageningen, the Netherlands), which was
designed for behavioral observation
(see Dirks et al22). The Observer
allows for the quantification of
behavioral data in terms of duration,
frequency, and serial order of
defined actions. Using theory and
practice, we designed a protocol
for evaluating the TDAR sessions
(eAppendix). Next, the observation
protocol was translated into a coding
Volume 95
Number 8
Physical Therapy f
1155
Table 1.
Frequencies of Posture and Balance Challenges During TDAR Sessionsa
V1 Median
(Range)
V2 Median
(Range)
P (Wilcoxon Signed
Rank Test)
Arm challenges
5.5 (3–8)
14 (6–19)
.027
Body sway challenges
3.5 (1–5)
TDAR Component
9 (4–11)
.042
Horse challenges
0 (0–2)
12 (12–13)
.026
Total challenges
9 (4–13)
35 (23–42)
.027
a
The quantitative data were from video analysis of therapist-designed adaptive riding (TDAR) sessions
at the beginning (V1) and at the end (V2) of the program. Data represent the number of challenges
performed; P values represent the differences between V1 and V2 (Wilcoxon signed rank test). In arm
challenges, posture and balance were challenged by exercises such as “raise your arms high up in the
air” and “fly like an airplane”; in body sway challenges, posture and balance were challenged by
exercises such as lying prone or leaning backward on the horse; in horse challenges, posture and
balance were challenged by, for instance, a change from walking to trotting.
scheme for The Observer. In this
step, we focused on the frequency of
specific TDAR components that challenged postural control. The
observer (A.A.) was trained in
the application of The Observer and
the protocol. During video analysis,
she was unaware of the timing of the
video (V1 or V2). The interrater reliability of the assessment of postural
challenges, performed by 2 authors
(A.A. and B.V.), was good (ICC
[2,1]⫽.96, range⫽.86 –.98).
Data Analysis
Data analysis started with a graphic
presentation of the developmental
trajectories of the individual participants. Next, we applied the Wilcoxon signed rank test (IBM SPSS
version 20, IBM Corp, Armonk, New
York) to analyze changes over time
in the group data for GMFM-88 and
all of the other outcome parameters.
Probability values of less than .05
were considered statistically significant. Probability values were not
adjusted for multiple comparisons
because of the preliminary nature of
the study.
The Stichting Beatrixoord NoordNederland and Stichting GroningenAlmelo funded the study.
Results
All participants completed the 12
sessions of TDAR and all assess1156
f
Physical Therapy
Volume 95
ments. No adverse effect of the intervention was reported. Moreover, the
smiley scales revealed that all children rated the TDAR sessions as 5,
that is, as very pleasant. About 70%
of the riding time was spent on riding a walking horse. The time spent
on exercises challenging postural
control increased from 3.3% at V1 to
14.5% at V2 (Wilcoxon signed rank
test, P⫽.046; for details on the number of challenges, see Tab. 1). At V1,
4 children were accompanied by a
side walker, but the 2 oldest children
(11 and 12 years of age), who were
also the 2 children with past AR
experience, were not. At V2, only 2
children (6 and 7 years of age) needed
a side walker. For 5 children, the side
walkers did not touch the children;
for 1 child, the side walker occasionally supported the child at the level
of the hips. The therapeutic riding
instructor, the pediatric physical
therapist (B.V.), and the horse handlers were present at all 12 sessions.
Figure 2 shows the changes in the
total scores and the scores on dimensions D and E of the GMFM-88 for the
group and for the individual participants. During the baseline period
(between T0 and T1), the total
GMFM-88 scores for 2 children (participants 2 and 3) increased considerably, whereas those for the others
did not; during the intervention
(between T1 and T2), the scores for
Number 8
all 6 children increased. A more or
less similar picture was present for
GMFM-88 dimensions D and E: during the baseline period, 3 children
improved, and during TDAR, all 6
obtained better scores. During the
baseline period, the scores of 2 children exceeded in dimension D the
MCID of a large effect size (2.4),
whereas in none of the children did
the changes in dimension E exceed
the threshold of the MCID of a large
effect size (3.0) (Tab. 2). In contrast,
during the intervention, the changes
in dimensions D and E largely
exceeded in all children the MCIDs
of a large effect size in children functioning at GMFCS level III (Tab. 2).
Group analyses indicated that the
total GMFM-88 scores did not change
significantly between T0 and T1,
but they did change significantly
between T1 and T2 (Fig. 2). None of
the secondary outcome measures
showed
statistically
significant
changes over time (Tab. 2).
The EMG analysis revealed that 75%
of reaches during both measurements (median value, range⫽27%–
100%) were accompanied by direction-specific activity in the neck and
trunk muscles. The frequency of topdown recruitment of the directionspecific muscles decreased in 5 of 6
children between T1 and T2 (Figs. 3
and 4). The child (participant 2) who
did not show a decrease in top-down
recruitment was the only child who,
during the EMG assessments, was
characterized as showing inattentive
and fidgeting behavior. Group analyses indicated that top-down recruitment decreased from 41% to 16%
(Wilcoxon signed rank test, P⫽.17).
Discussion
This preliminary study indicated that
it is feasible to conduct a TDAR intervention study with a complex assessment protocol in children with spastic CP. The results suggested that a
TDAR intervention of 6 weeks, with
an intensity of 1 hour, twice per
August 2015
Figure 2.
Development of 88-item Gross Motor Function Measure (GMFM-88) scores. (A) Box plots of total GMFM-88 scores for the group
data 6 weeks before the start of the therapist-designed adaptive riding (AR) intervention (T0), at the start of the intervention (T1),
and at the end of the intervention (T2). Horizontal lines indicate median values, boxes indicate interquartile ranges, and vertical lines
indicate the full range. Wilcoxon signed rank test: P⫽.075 for T1 versus T0 and P⫽.028* for T2 versus T1 (asterisk represents
significant difference). (B–D) Individual developmental trajectories of the percentage scores for the total GMFM-88 (B) and the goal
areas (GMFM-88 dimension D [standing] [C] and GMFM-88 dimension E [walking, running, and jumping] [D]) during the baseline
(T0 to T1) and during the therapist-designed AR intervention (T1 to T2). Participants 4 and 5 had previous AR intervention
experience; the other children did not. For clarity, the GMFM-88 scales (y-axes) in panels C and D differ from those in panels A
and B.
week, was associated with a significant improvement in GMFM-88
scores.
All children were enthusiastic about
TDAR. In addition, the assessment
protocol was feasible, notwithstandAugust 2015
ing its complexity. We hypothesized
that TDAR would affect, in particular, gross motor function, especially
dimensions D and E of the GMFM88 —and that was the case. However, we also wanted to know
whether TDAR would affect the
ICF-CY domain participation (PEDI),
the children’s personal factor selfesteem, the overall measure quality
of life, and the underlying working
mechanisms (postural control and
spasticity). The limited data of the
feasibility study (Tab. 2) suggest that
Volume 95
Number 8
Physical Therapy f
1157
Table 2.
Group Comparisons of Outcome Measures at Each Assessmenta
Median Change Scorec
From
T0 to T1
From
T1 to T2
T0b
T1b
T2b
Total score
64.40 (46.96–75.00)
66.66 (51.10–76.78)
73.18 (65.69–82.65)
1.71
7.06
NA
Dimension D
37.18 (25.64–61.54)
47.44 (25.64–66.67)
55.13 (38.46–76.92)
2.56
10.25
2.4
Dimension E
15.28 (11.11–37.50)
16.67 (11.11–38.89)
21.53 (18.06–45.83)
0.69
6.25
3.0
0
0
NA
Outcome Measure
MCID
GMFM-88d
Level of
the ICF-CY
A
PEDI
A/P
Self-care
Mobility
58 (33–69)
58.5 (33–69)
60 (33–69)
A/P
40 (28–52)
40.5 (28–53)
41.5 (30–53)
0
1
6.96
A
54.5 (36–66)
55 (36–66)
55 (38–66)
0
0
NA
P
50.5 (38–57)
49 (40–57)
51 (39–57)
⫺0.5
1
NA
Pe
DISABKIDS
22.5 (18–26)
23.5 (18–27)
28 (26–32)
0.5
6
NA
QoL
KIDSCREEN-52
45.5 (41–50)
46 (43–48)
41 (37–44)
0.5
⫺5.5
NA
QoL
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Social function
Parent questionnaires
QoL
Self-esteem
e
Modified Tardieu Scale
BS/F
Hip adductor muscle
Spasticity grade
R2⫺R1 (range)
2
18.25 (5–35)
2
19.75 (11–50)
2
20 (8.5–35)
Hamstring muscle
Spasticity grade
2
R2⫺R1 (range)
37 (11–67)
2
40 (7–66)
2
35.5 (19–76)
Gastrocnemius muscle
Spasticity grade
2
2
2
R2⫺R1 (range)
⫺9 (⫺22 to 16)
⫺9 (⫺19 to 0)
⫺2 (⫺24 to 7)
Biceps brachii muscle
Spasticity grade
0 (n⫽2), 1 (n⫽1),
2 (n⫽3)
0 (n⫽2), 1 (n⫽1),
2 (n⫽3)
0 (n⫽3), 1 (n⫽1),
2 (n⫽2)
R2⫺R1 (range)
3 (0–93)
0 (0–91)
6 (0–90)
a
T0⫽6 weeks before the start of the therapist-designed adaptive riding (TDAR) intervention; T1⫽start of the TDAR intervention; T2⫽end of the TDAR
intervention; MCID⫽minimal clinically important difference of a large effect size for Gross Motor Function Classification System level III18; ICFCY⫽International Classification of Functioning, Disability and Health: Children and Youth Version; GMFM-88⫽88-item Gross Motor Function Measure;
A⫽activity; NA⫽not available; PEDI⫽Dutch version of the Pediatric Evaluation of Disability Inventory; A/P⫽activities and participation; P⫽participation;
QoL⫽quality of life; Self-Esteem⫽Behavioral Rating Scale of Presented Self-Esteem; Pe⫽personal factors; DISABKIDS⫽cerebral palsy module of disease-specific
DISABKIDS (higher scores denote a poorer outcome); KIDSCREEN-52⫽generic KIDSCREEN-52; BS/F⫽body structure and function.
b
Values are reported as median (range) (minimum–maximum) for the 6 participants unless otherwise indicated.
c
Bold values exceeded the MCIDs.
d
The goal areas of the GMFM-88 were dimension D (standing) and dimension E (walking, running, and jumping).
e
In the modified Tardieu Scale, a 5-point rating scale (grades) was used to describe the quality of the muscle reaction. A grade of 0 indicated no resistance
throughout the course of the passive movement; a grade of 1 indicated slight resistance throughout the course of the passive movement (no clear “catch”
at a precise angle); a grade of 2 indicated a clear catch at a precise angle, interrupting the passive movement, followed by release; a grade of 3 indicated
fatigable clonus (⬍10 seconds when maintaining the pressure and appearing at a precise angle); and a grade of 4 indicated infatigable clonus (⬎10 seconds
when maintaining the pressure at a precise angle). Spasticity grades were obtained for 6 participants unless otherwise indicated. In addition, 2 angles (R1
and R2) were determined: R1 was the angle of catch after a high-velocity stretch, and R2 was the passive range of motion after a low-velocity stretch. The
difference between the 2 angles (R2⫺R1) represented the level of dynamic contracture in the joint. Negative values indicated plantar flexion at the ankle
joint.
1158
f
Physical Therapy
Volume 95
Number 8
August 2015
Figure 3.
Examples of electromyographic (EMG) recordings of postural muscle activity during
reaching while sitting. (A) Trial for participant 1 before the therapist-designed adaptive
riding (TDAR) intervention. (B) Trial for participant 1 at the end of the TDAR intervention. The vertical dashed lines represent the presence of the reaching movement; the
left line represents the moment at which the video indicated the start of the reaching
movement, and the right line represents the end of the reaching movement, as
observed in a video. The short, bold vertical lines denote the onset of significant EMG
bursts, as defined by the computer algorithm. The biceps brachii muscle was the prime
mover in both trials; that is, it was the arm muscle initiating the reaching movement.
The vertical dotted line indicates the onset of the reaching movement by the prime
mover. Both trials showed direction specificity at the neck and trunk levels. In both trials,
the neck extensor muscle was activated before the neck flexor muscle. At the trunk level,
direction specificity was expressed in 2 different ways: In panel A, thoracic extensor and
lumbar extensor muscles were activated but the rectus abdominis muscle was not
recruited; in panel B, the thoracic and lumbar extensor muscles were recruited before
the rectus abdominis muscle. Panel A illustrates top-down recruitment, during which
the neck extensor muscle was recruited before the thoracic and lumbar extensor
muscles. Panel B illustrates a mixed order of recruitment of the dorsal muscles.
a large RCT study would be needed
to determine if there are any changes
in the participation measures.
The assessment of postural control
seems to be a promising way to
improve insight into the mechanisms
underlying changes in gross motor
function. Ideally, postural control
also should be assessed during an
intervention; future studies may
embark on this endeavor. Muscle
tone is considered to be another
potential mechanism underlying
changes in motor performance in
children with CP.37 The Tardieu
Scale is the best clinical tool available, but it is not a perfect tool.28 To
assess muscle tone more reliably,
future studies should include the
August 2015
evaluation of muscle tone by EMG
recordings, similar to the evaluation
in the study of McGibbon et al,4 who
reported a significant improvement
in hip adductor symmetry after
hippotherapy.
Our secondary aim was to assess the
effect of TDAR. Therapist-designed
AR was associated with improvements in GMFM-88 dimensions D
and E that exceeded the MCIDs. The
latter finding suggested that the
changes were clinically meaningful.16 The data indicated that some
children showed larger changes than
others, both during the baseline and
during the intervention. The children with the largest changes (participants 2 and 3) were relatively
young (6 –7 years of age) and, therefore, had the largest potential to
improve GMFM-88 scores. Our secondary outcome measures assessed
functions at other levels of the ICFCY; the data did not suggest an effect
of TDAR. These data correspond to
the findings of Davis et al,38 who
studied the effect of AR (once per
week) in a relatively large RCT.
Three factors may explain the
absence of an effect of TDAR on our
secondary outcomes: the small
group size, the short duration of the
TDAR intervention, and insufficient
sensitivity of the tools used to evaluate the effect of TDAR (eg, the parent questionnaires on quality of
life).33–35
A significant improvement in
GMFM-88 scores in a small study
group needs to be interpreted with
caution. It may be a chance finding,
as the review of Tseng et al3 indicated that equine-assisted activities
and therapies were not associated
with significant improvements in
GMFM scores. However, the review
did indicate that hippotherapy may
be associated with improved postural control; a similar effect of AR
(without an integrated program of
postural exercises) was less clear.
Interestingly, in studies (2 on hippotherapy7,39 and 2 on AR40,41) in
which the intervention was applied
twice per week—as in the present
study—a significant improvement in
GMFM scores was reported. These
data suggested that the intensity of
therapy may be a significant factor in
determining outcome, similar to
what has been reported for other
types of physical therapy in children
with CP.42 Three other elements that
may have contributed to the
improvement in GMFM-88 scores
were the hands-off approach, favoring self-practice; the variation in
experience resulting from the use of
6 different horses per child; and the
use of an integrated program of varied postural challenge exercises in
Volume 95
Number 8
Physical Therapy f
1159
Figure 4.
Changes in top-down recruitment order from T1 (before the intervention) to T2 (after the intervention). (A) Box plots of the group
data for the various types of recruitment order at T1 (white boxes) and T2 (gray boxes). The horizontal bars indicate the median
values, the boxes indicate the interquartile ranges, the vertical lines indicate the full range, and the circle is an outlier. In group
analyses of the effect of the therapist-designed adaptive riding intervention on top-down recruitment order, the P value was .173
(Wilcoxon signed rank test). (B) Individual data on frequency of top-down recruitment order at T1 (white bars) and T2 (black bars).
The frequency in participant 5 at T2 was 0%.
our TDAR program. The postural
EMG data suggested that the
improvement in GMFM-88 scores
during TDAR may have been associated with an improved fine-tuning of
postural activity because, after the
intervention, the recruitment order
closely resembled the typical pattern
of varied recruitment order. The
video recordings of TDAR showed
that at the end of the intervention,
fewer children were accompanied
by a side walker; this result may suggest that their riding skills improved
and that they were able to perform
more challenging postural exercises.
The latter observation supports the
suggestion that postural control
improved with increasing intervention time.
The limitations of the present study
are related to its design as a feasibility study with a small sample of children who had CP and functioned at
GMFCS level III—a design that did
not allow for generalization to all
children with CP. In addition, the
use of only one postintervention
1160
f
Physical Therapy
Volume 95
assessment precluded conclusions
about long-term effects. Another limitation was that the assessors were
not masked with regard to the intervention; this limitation posed the
risk of detection bias.43 The exception to this rule was the masked
assessor of the EMG data; she did not
know whether the EMG recordings
that she analyzed were obtained
before or after the intervention.
We suggest that future studies of
TDAR use an RCT design to compare
the outcome of an intervention and
the outcome for nonriding controls
with similar assessment tools, such
as a battery evaluating outcome
across the levels of the ICF-CY,15,20
and—if possible—an assessment of
working mechanisms. Relatively
large numbers of participants are
needed because CP is characterized
by heterogeneity.18 We recommend
block randomization for the severity
of CP (GMFCS levels I–III versus
GMFCS levels IV and V). In addition,
we suggest that TDAR last for 3
months (1 hour, 2 times per week)
Number 8
and that evaluation (carried out by
masked assessors) include follow-up
at least 3 months after the intervention. We encourage practitioners to
describe their intervention protocols
and to evaluate the protocols with
video analysis to determine which
aspects of the intervention are beneficial and have an impact on a
child’s life.20
The present study suggests that it is
feasible to perform an RCT of TDAR
with our complex protocol. The data
from this feasibility study suggest
that TDAR may enhance gross motor
function and postural adjustments in
children who have CP and function
at GMFCS level III.
Mrs Angsupaisal, Dr Maathuis, Dr ReindersMesselink, and Dr Hadders-Algra provided
concept/idea/research design. Mrs Angsupaisal, Mrs Visser, Dr Reinders-Messelink,
and Dr Hadders-Algra provided writing and
project management. Mrs Angsupaisal and
Mrs Visser provided data collection. Mrs
Angsupaisal, Mrs Visser, Ms Alkema, and Dr
Hadders-Algra provided data analysis. Dr
Hadders-Algra and Dr Reinders-Messelink
August 2015
provided fund procurement. Dr Meinsmavan der Tuin provided participants and facilities/equipment. Dr Meinsma-van der Tuin
and Dr Hadders-Algra provided institutional
liaisons. Mrs Angsupaisal provided administrative support. Mrs Angsupaisal, Dr
Meinsma-van der Tuin, and Dr Maathuis
provided consultation (including review of
manuscript before submission).
7 Kwon JY, Chang HJ, Lee JY, et al. Effects
of hippotherapy on gait parameters in children with bilateral spastic cerebral palsy.
Arch Phys Med Rehabil. 2011;92:774 –
779.
The authors acknowledge the skillful collaboration of the team at the Riding Center
Onder de Linde; the support of Tineke Dirks,
PT, in the development of the video protocol
for the classification of activities and assistance during equine movement; the assistance of the students who filmed the
therapist-assisted adaptive riding sessions;
and the encouragement and support of
Stichting ZorgPKs, Federatie Paardrijden
Gehandicapten, and the parent organization, BOSK.
9 Forssberg H, Hirschfeld H. Postural adjustments in sitting humans following external perturbations: muscle activity and
kinematics. Exp Brain Res. 1994;97:515–
527.
This study was approved by the Medical Ethical Committee of the University Medical
Center Groningen.
The Stichting Beatrixoord Noord-Nederland
and Stichting Groningen-Almelo funded the
study.
DOI: 10.2522/ptj.20140146
References
1 American Hippotherapy Association Inc.
Hippotherapy vs therapeutic riding. Available
at:
http://windrushfarm.org/
downloads/american.pdf. Accessed April
28, 2015.
2 Sterba J. Does horseback riding therapy or
therapist-directed hippotherapy rehabilitate children with cerebral palsy? Dev Med
Child Neurol. 2007;49:68 –73.
3 Tseng SH, Chen HC, Tam KW. Systematic
review and meta-analysis of the effect of
equine assisted activities and therapies on
gross motor outcome in children with
cerebral palsy. Disabil Rehabil. 2013;35:
89 –99.
4 McGibbon NH, Benda W, Duncan BR,
Silkwood-Sherer D. Immediate and longterm effects of hippotherapy on symmetry
of adductor muscle activity and functional
ability in children with spastic cerebral
palsy. Arch Phys Med Rehabil. 2009;90:
966 –974.
5 Russell DJ, Rosenbaum PL, Avery LM, Lane
M. Gross Motor Function Measure
(GMFM-66 & GMFM-88) User’s Manual.
London, United Kingdom: Mac Keith
Press; 2002. Clinics in Developmental
Medicine No. 159.
6 Shurtleff TL, Standeven JW, Engsberg JR.
Changes in dynamic trunk/head stability
and functional reach after hippotherapy.
Arch Phys Med Rehabil. 2009;90:1185–
1195.
August 2015
8 Hadders-Algra M, Carlberg EB, eds. Postural Control: A Key Issue in Developmental Disorders. London, United Kingdom: Mac Keith Press; 2008. Clinics in
Developmental Medicine No. 179.
22 Dirks T, Blauw-Hospers C, Hulshof L,
Hadders-Algra M. Differences between the
family-centered “COPCA” program and
traditional infant physical therapy based
on neurodevelopmental treatment principles. Phys Ther. 2011;91:1303–1322.
23 Russell DJ, Rosenbaum PL, Cadman DT,
et al. The Gross Motor Function Measure:
a means to evaluate the effects of physical
therapy. Dev Med Child Neurol. 1989;31:
341–352.
24 Bjornson KF, Graubert CS, Buford VL,
McLaughlin J. Validity of the Gross Motor
Function Measure. Pediatr Phys Ther.
1998;10:43– 47.
10 Van Der Heide JC, Begeer C, Fock JM,
et al. Postural control during reaching in
preterm children with cerebral palsy. Dev
Med Child Neurol. 2004;46:253–266.
25 Ko J, Kim MY. Reliability and responsiveness of the Gross Motor Function
Measure-88 in children with cerebral palsy. Phys Ther. 2013;93:393– 400.
11 Schmidt RA, Wrisberg CA. Motor Control
and Learning and Performance: A
Problem-Based Learning Approach. 2nd
ed. Champaign, IL: Human Kinetics Publisher; 2000.
26 Ko J. Sensitivity to functional improvements of GMFM-88, GMFM-66 and PEDI
mobility scores in young children with
cerebral palsy. Percept Mot Skills. 2014;
119:305–319.
12 Larin H. Motor learning: theories and strategies for the practitioners. In: Campbell
SK, Vander Linden DW, Palisano RJ, eds.
Physical Therapy for Children. 2nd ed.
Philadelphia, PA: WB Saunders Co; 2000:
170 –197.
27 Boyd R, Graham H. Objective measurement of clinical findings in the use of botulinum toxin type A in the management of
children with cerebral palsy. Eur J Neurol.
1999;6(suppl 4):S23–S35.
13 Hadders-Algra M. Variation and variability:
key words in human motor development.
Phys Ther. 2010;90:1823–1837.
14 Novak I, McIntyre S, Morgan C, et al. A
systematic review of interventions for children with cerebral palsy: state of the evidence. Dev Med Child Neurol. 2013;55:
885–910.
15 International Classification of Functioning, Disability and Health: Children and
Youth Version—ICF-CY. Geneva, Switzerland: World Health Organization; 2007.
16 Oeffinger D, Bagley A, Rogers S, et al. Outcome tools used for ambulatory children
with cerebral palsy: responsiveness and
minimum clinically important differences.
Dev Med Child Neurol. 2008;50:918 –925.
17 van Balen L, Dijkstra L, Hadders Algra M.
Development of postural adjustments during reaching in typically developing
infants from 4 to 18 months. Exp Brain
Res. 2012;220:109 –119.
18 Surveillance of cerebral palsy in Europe: a
collaboration of cerebral palsy surveys and
registers. Dev Med Child Neurol. 2000;42:
816 – 824.
19 McMaster University. GMFCS: expanded
and revised (2007). CanChild Centre for
Childhood Disability Research website.
Available at: http://www.canchild.ca/en/
measures/gmfcs_expanded_revised.asp.
Accessed April 28, 2015.
20 Law M, Darrah J. Emerging therapy
approaches: an emphasis on function.
J Child Neurol. 2014;29:1101–1107.
21 Palisano RJ, Chiarello LA, King GA, et al.
Participation-based therapy for children
with physical disabilities. Disabil Rehabil.
2012;34:1041–1052.
28 Scholtes VA, Becher JG, Beelen A, Lankhorst GJ. Clinical assessment of spasticity
in children with cerebral palsy: a critical
review of available instruments. Dev Med
Child Neurol. 2006;48:64 –73.
29 Custers J, Wassenberg-Severijnen J, Van
der Net J, et al. Dutch adaptation and content validity of the “Pediatric Evaluation of
Disability Inventory (PEDI-NL).” Disabil
Rehabil. 2002;24:250 –258.
30 Berg M, Jahnsen R, Froslie K, Hussain A.
Reliability of the Pediatric Evaluation of
Disability Inventory (PEDI). Phys Occup
Ther Pediatr. 2004;24:61–77.
31 Wright FV, Boschen KA. The Pediatric
Evaluation of Disability Inventory (PEDI):
validation of a new functional assessment
outcome instrument. Can J Rehabil. 1993;
7:41– 42.
32 Fuchs-Beauchamp KD. Preschoolers’
inferred self-esteem: the Behavioral Rating
Scale of presented self-esteem in young
children. J Genet Psychol. 1996;157:204 –
210.
33 Ravens-Sieberer U, Gosch A, Rajmil L, et al.
The KIDSCREEN-52 quality of life measure
for children and adolescents: psychometric results from a cross-cultural survey in
13 European countries. Value Health.
2008;11:645– 658.
34 Simeoni MC, Schmidt S, Muehlan H, et al.
Field testing of a European quality of life
instrument for children and adolescents
with chronic conditions: the 37-item
DISABKIDS Chronic Generic Module.
Qual Life Res. 2007;16:881– 893.
35 Janssens L, Willem Gorter J, Ketalaar M,
et al. Health-related quality-of-life measures for long-term follow-up in children
after major trauma. Qual Life Res. 2008;
17:701–713.
Volume 95
Number 8
Physical Therapy f
1161
36 Staude G, Wolf W. Objective motor
response onset detection in surface myoelectric signals. Med Eng Phys. 1999;21:
449 – 467.
37 Ostensjø S, Carlberg EB, Vøllestad NK.
Motor impairments in young children with
cerebral palsy: relationship to gross motor
function and everyday activities. Dev Med
Child Neurol. 2004;46:580 –589.
38 Davis E, Davies B, Wolfe R, et al. A randomized controlled trial of the impact of
therapeutic horse riding on the quality of
life, health, and function of children with
cerebral palsy. Dev Med Child Neurol.
2009;51:111–119.
1162
f
Physical Therapy
Volume 95
39 McGibbon NH, Andrade CK, Widener G,
Cintas HL. Effect of an equine-movement
therapy program on gait, energy expenditure, and motor function in children with
spastic cerebral palsy: a pilot study. Dev
Med Child Neurol. 1998;40:754 –762.
40 Bertoti DB. Effect of therapeutic horseback riding on posture in children with
cerebral palsy. Phys Ther. 1988;68:1505–
1512.
41 Cherng RJ, Liao HF, Leung HWC, Huang
AW. The effectivenss of therapeutic horseback riding in children with spastic cerebral palsy. Adapt Phys Activ Quart. 2004;
21:103–121.
Number 8
42 Gordon A. To constrain or not to constrain, and other stories of intensive upper
extremity training for children with unilateral cerebral palsy. Dev Med Child Neurol.
2011;53(suppl 4):56 – 61.
43 Guyatt GH, Oxman AD, Vist G, et al.
GRADE guidelines, 4: rating the quality of
evidence—study limitations (risk of bias).
J Clin Epidemiol. 2011;64:407– 415.
August 2015
eAppendix.
Classification of Activities and Assistance During Equine Movement
The therapist-designed adaptive riding (TDAR) intervention actions are classified into 7 main categories that contain
various subcategories (second level of observation). For each specific action, one or more examples of concrete
TDAR intervention actions are provided (third level of observation).
A. Involvement and educational actions
The extent to which people are involved in the TDAR intervention for the child and the extent of guidance,
interference, coaching, or training by the instructor and volunteers during the TDAR intervention session
A.1 People involved in the guidance of the child
People involved in the TDAR intervention session
1. The child is leading the horse and does not receive assistance from a side walker; the instructor and the horse
handler are present
2. One side walker is coaching the child; the instructor and the horse handler are present
3. Two side walkers are coaching the child; the instructor is present
A.2 Educational actions
A.2.1 The type of interference by the instructor with the child’s activities
1.
2.
3.
4.
The
The
The
The
child receives no instructions
instructor asks the child to stop in order to provide the child with additional instructions, hands-off
instructor asks the child to stop in order to provide the child with additional instructions, hands-on
instructor challenges the child to give verbal commands to the horse (eg, “ho,” “step,” “trot”)
A.2.2 The type of guidance given to the horse handler and side walker(s) by the instructor
1. The instructor demonstrates and explains how global tasks can be monitored; for example, the instructor tells
the horse handler, the side walker(s), or both (or all) to increase the pace of the horse
2. The instructor demonstrates and explains the importance of an erect and symmetrical body posture
3. The instructor demonstrates and explains the principles of variation and challenging motor behavior and
postural abilities
B. Situation
The instructor creates various situations during the TDAR session to challenge the child’s motor and cognitive
abilities
B.1 Type of situation
1.
2.
3.
4.
Mounting
Walking
Trotting
Standing still, that is, halting the horse
(Continued)
August 2015 (eAppendix, Angsupaisal et al)
Volume 95
Number 8
Physical Therapy f
1
eAppendix.
Continued
B.2 Exercise during walking
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Down the center line
Stop at a specific sign (letter, number)
Change from walk to trot
Change from trot to walk
Circle
Turn
Serpentine
Follow arena track
Change rein
Across long diagonal
Figure-of-eight
B.3 Exercise on the horse while standing still or walking
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Sit relaxed with arms hanging down alongside the body
Lift right hand up
Lift left hand up
Reward the horse by tapping the horse
Give someone a high five
Put both hands in the air like an airplane— both hands high up in the air
Cross both arms
Do swimming movements: breaststroke
Do swimming movements: crawl
Do swimming movements: backstroke
Lie prone on the horse
Lean backward on the horse
Commands about the use of reins, for example, “Get your reins”
B.4 Performance of exercise
Indicate for each of the above-mentioned exercises how the exercise is performed
1. Child performs action adequately or performs action with great effort (regardless of result)
2. Child shows moderate performance and shows limited signs of effort
3. Child does not perform the task
C. Postural support
All actions in which the child is given opportunities to explore his or her postural capacities
(Continued)
2
f
Physical Therapy
Volume 95
Number 8
eAppendix.
Continued
C.1 No postural support
The child tries out his or her own postural capacities.
Examples of concrete actions:
• One side walker walks beside the horse for safety reasons (hands-off), and the child leads the horse; the child may hold onto
the handle of the saddle
• The horse handler leads the horse by a rope but does not touch the child (hands-off); the child may hold onto the handle
of the saddle
C.2 Minimal postural support
The instructor or side walker provides as little support as possible in order to challenge the postural behavior of the
child. The challenge is reflected by the presence of swaying movements made by the child to maintain balance.
• The horse handler leads the horse, and the side walker has her or his hands behind the child on the back of the horse
• The side walker or instructor assists (by means of a single action of ⱕ3 seconds) the child to achieve the midline position
on the horse (hands-on)
C.3 Clear postural support
The instructor or side walker provides evident support to parts of the child’s body. The amount of support provided
leaves the child with some but limited postural challenge; that is, it is clear from the video that some postural effort
of the child is required, but not to such an extent that it often results in swaying movements.
• The horse handler leads the horse, and the side walker has her or his hands on the knee or back of the child
• The side walker or instructor assists the child in maintaining a symmetrical, erect midline position on the horse by means
of hands-on actions lasting more than 3 seconds
C.4 Full support
The instructor or side walker provides excessive postural support or assistance, leaving no opportunity for the child
to practice balancing capacities.
D. Communication
All communication between the instructor, horse handler, and side walker and the child
D.1 Type of information exchange
All communication during which information is exchanged during the TDAR session; the instructor, horse handler,
or side walker provides the opportunity for the child to tell about experiences related to daily life activities and
events
1. The instructor, horse handler, or side walker asks the child about the horse riding therapy
2. The instructor provides information about the roles of the instructor, horse handler, and side walker
(Continued)
Volume 95
Number 8
Physical Therapy f
3
eAppendix.
Continued
D.2 Type of instruction
All communication in which the child is given instructions on the TDAR intervention
1. The instructor explicitly explains how to sit on the horse in terms of posture, asymmetry or symmetry, and
hand placement
2. The instructor explicitly explains how to perform a task; for example, the instructor explains how to ride a
figure-of-eight or how to make the horse walk faster or slower
3. The instructor gives hints or provides a suggestion or clue in a very indirect way
D.3 Type of feedback
All communication in which the performance of the child is evaluated
1. The instructor gives positive feedback (what went fine)
2. The instructor gives negative feedback (what went wrong)
3. The instructor asks for and listens to the opinion of the child
E. Not specified
All time during the TDAR session that cannot be classified into the above-defined categories
1. Technical problems interfering with assessment (eg, child, horse, or both out of view, blurred image)
2. Video is acceptable, but actions are not specified
F. Behavioral state
1. Alert and smiling during the TDAR session
2. Alert neutral mood during the TDAR session
3. Alert but withdrawn, fussy, or reluctant
G. Posture of the child on the horse
1. Most of the time in an upright position
2. Most of the time in a collapsed posture
H. Postural support by devices on the horse
H.1 Type of saddle
1.
2.
3.
4.
5.
Sheepskin
“Wendy Molenaar” saddle (modification of sheepskin)
“Ariane de Ranitz” saddle (modification of sheepskin)
English saddle
Western saddle
(Continued)
4
f
Physical Therapy
Volume 95
Number 8
eAppendix.
Continued
H.2 Type of stirrups
1. Ordinary stirrups
2. Adapted stirrups
3. Absent
H.3 Foot protection
1. Yes
2. No
H.4 Type of handles on saddle
1. One midline firm handle
2. Two more laterally placed firm handles
3. One midline relatively flexible saddle belt
H.5 Rider belt
1. Yes
2. No
(Continued)
Volume 95
Number 8
Physical Therapy f
5
Research Report
S.K. Wee, PT, Rehabilitation and
Health Technologies Research
Group, Faculty of Health Sciences,
University of Southampton, Bldg
45, Highfield Campus Southampton, Southampton, United Kingdom SO17 1BJ, and Rehabilitation
Centre, Tan Tock Seng Hospital,
Singapore. Address all correspondence to Mr Wee at: skw1g12@
soton.ac.uk or seng_kwee_wee@
ttsh.com.sg.
Effect of Trunk Support on
Upper Extremity Function in
People With Chronic Stroke and
People Who Are Healthy
Seng Kwee Wee, Ann-Marie Hughes, Martin B. Warner, Simon Brown,
Andy Cranny, Evangelos B. Mazomenos, Jane H. Burridge
Background. Trunk control is thought to contribute to upper extremity (UE)
function. However, this common assumption in neurorehabilitation has not been
validated in clinical trials.
Objective. The study objectives were to investigate the effect of providing external trunk support on trunk control and UE function and to examine the relationship
between trunk control and UE function in people with chronic stroke and people
who were healthy.
Design. A cross-sectional study was conducted.
Methods. Twenty-five people with chronic stroke and 34 people who were
healthy and matched for age and sex were recruited. Trunk control was assessed with
the Trunk Impairment Scale (TIS), and UE impairment and UE function were assessed
with the UE subsection of the Fugl-Meyer Assessment (FMA-UE) and the Streamlined
Wolf Motor Function Test (SWMFT), respectively. The TIS and SWMFT were evaluated, with and without external trunk support; the FMA-UE was evaluated without
trunk support.
Results. With trunk support, people with stroke showed improvement from 18 to
20 points on the TIS, a reduction in SWMFT performance times from 37.20 seconds
to 35.37 seconds for the affected UE, and improvement from 3.3 points to 3.4 points
on the SWMFT Functional Ability Scale for the function of the affected UE. With trunk
support, the SWMFT performance time for people who were healthy was reduced
from 1.61 seconds to 1.48 seconds for the dominant UE and from 1.71 seconds to
1.59 seconds for the nondominant UE. A significant moderate correlation was found
between the TIS and the FMA-UE (r⫽.53) for people with stroke.
Limitations. The limitations included a nonmasked assessor and a standardized
height of the external trunk support.
Conclusions. External trunk support improved trunk control in people with
chronic stroke and had a statistically significant effect on UE function in both people
with chronic stroke and people who were healthy. The findings suggest an association between trunk control and the UE when external trunk support was provided
and support the hypothesis that lower trunk and lumbar stabilization provided by
external support enables an improvement in the ability to use the UE for functional
activities.
August 2015
Volume 95
A-M. Hughes, PhD, Rehabilitation
and Health Technologies Research
University of Southampton.
M.B. Warner, PhD, Rehabilitation
S. Brown, BSc(Hons), Rehabilitation and Health Technologies
Research Group, Faculty of
Health Sciences, University of
Southampton.
A. Cranny, PhD, Electronics and
Computer Science, Faculty of
Physical Sciences and Engineering, University of Southampton.
E.B. Mazomenos, PhD, Electronics
and Computer Science, Faculty of
Physical Sciences and Engineering, University of Southampton.
J.H. Burridge, PhD, Rehabilitation
[Wee SK, Hughes A-M, Warner
MB, et al. Effect of trunk support
on upper extremity function in
people with chronic stroke and
people who are healthy. Phys Ther.
2015;95:1163–1171.]
Association
February 26, 2015
Accepted: February 17, 2015
Number 8
this article at:
ptjournal.apta.org
Physical Therapy f
1163
S
troke affects the control of the
trunk muscles and, therefore,
the ability to remain upright,
adjust to weight shifts, and perform
selective trunk movements to maintain stability during static and
dynamic postural adjustments.1,2
The trunk is thought to play an integral role in postural stabilization by
supporting controlled movement of
the extremities during task performance.2,3 The development of trunk
stability and control is considered to
be a prerequisite to upper extremity
(UE) function and use of the hand.4 It
has been hypothesized that proximal
stability allows for independent use
of the arms and hands in manipulative and purposeful activity.4 However, this common assumption in
neurorehabilitation has not been validated in clinical trials.
There is strong evidence that trunk
control is an important predictor of
overall functional outcome after
stroke.5–9 The reported variance of
functional recovery after stroke that
is explained by trunk control ranges
from 45%5,8 to 71%.10 Various studies5–10 have clearly illustrated that
trunk control affects many facets of
recovery in people with stroke, such
as activities of daily living, balance,
and gait. However, no research has
built upon these findings to investigate the effect of trunk control on
the recovery of UE function in people with stroke specifically, even
though the UE plays a vital role in the
performance of activities of daily
living.11,12
Several studies on the use of trunk
restraint in people with chronic
stroke13–20 have demonstrated that
stabilizing the trunk to restrict compensatory trunk movements leads to
improved shoulder and elbow movements and thereby results in
improvements in reaching to grasp.
Our recent systematic review and
meta-analysis revealed that trunk
restraint has moderate effects in
1164
f
Physical Therapy
Volume 95
terms of the reduction of UE impairment, increased shoulder flexion,
and the reduction of excessive anterior trunk movement during reaching in people with chronic stroke.21
Taken together, the findings suggest
a possible relationship between
trunk control and UE function. However, in previous studies,13,14,17,18 the
trunk was restrained with a chest
harness, which eliminated the need
for trunk control.
Our aims were to investigate the
effect of external trunk support on
trunk control and UE function and to
examine the relationship between
trunk control and UE function in
people with chronic stroke and people who were healthy. The trunk
support that we used, unlike the
trunk restraints used in other studies,13,14,17,18 provided stability to the
trunk without restricting normal
movement. We hypothesized that a
more stable trunk enables improved
dissociation of the UE from the trunk
for function. Our findings could
advance the understanding of how
trunk control affects UE function in
people with stroke and subsequently
inform the design of targeted rehabilitation programs for the trunk and
UE to optimize functional outcomes
after stroke.
at a 5% significance level, we determined that 25 participants per group
were required.
Participants
For this cross-sectional study, participants were recruited between
November 2013 and March 2014 via
paper and electronic advertisements
and talks at 7 local stroke clubs. Participants were matched for age and
sex. Inclusion criteria for participants with chronic stroke were as
follows: 18 years of age or older,
more than 6 months after stroke,
able to understand the purpose of
the study and follow simple instructions, and able to sit unsupported for
10 seconds. Exclusion criteria for
participants with chronic stroke
were as follows: brain stem or cerebellar stroke, presence of neurological or orthopedic pathology, and
presence of acute low back pain.
Inclusion criteria for people who
were healthy were as follows: 18
years of age or older and able to
understand the purpose of the study
and follow simple instructions.
Exclusion criteria for people who
were healthy were as follows: history of neurological injury or disease,
orthopedic spinal pathology, and
orthopedic UE pathology. All participants provided written informed
consent.
Method
Sample Size Calculation
Sample size was determined with a
power calculation based on the
between-group (people with stroke
versus people who are healthy) difference in performance times on the
Wolf Motor Function Test (WMFT),
the primary UE function outcome
measure. Mean WMFT scores have
been recorded for people who
are healthy (X⫽1.20 seconds,
SD⫽0.20)22 and for people with
chronic stroke (X⫽7.05 seconds,
SD⫽6.85).23 To detect a difference
of 5.85 seconds in WMFT performance times between groups and to
achieve 85% power in a 2-sided test
Number 8
Outcome Measures
The Trunk Impairment Scale (TIS)
was used to evaluate trunk control in
the participants.1 The TIS consists of
3 subscales that assess static sitting
balance, dynamic sitting balance,
and trunk coordination on a scale
ranging from 0 to 23 points. A higher
score indicates better trunk control.
Upper extremity motor impairment
after stroke was measured with the
UE subsection of the Fugl-Meyer
Assessment (FMA-UE).24 Each of the
33 items of the FMA-UE was rated on
a 3-point scale. The maximum score
is 66 points. Upper extremity motor
August 2015
function was measured with the
Streamlined Wolf Motor Function
Test (SWMFT).25 The 6 SWMFT tasks
appropriate for people with chronic
stroke were lifting the hand from a
table to a box, lifting a can to the
mouth, lifting a pencil with a 3-jaw
chuck grasp, folding a towel, turning
a key in a lock, and extending the
elbow against a 0.45-kg (1-lb)
weight.26 The performance time on
the SWMFT tasks was measured with
a stopwatch, and a 6-point Functional Ability Scale (FAS) was used to
rate the quality of movement during
the performance of the tasks.26 Good
psychometric properties and good
clinical utility that are appropriate
for people with subacute and
chronic stroke have been demonstrated for the TIS, FMA-UE, and
SWMFT.27
Procedure
All assessments were conducted in
the research laboratory of the
University of Southampton, Southampton, United Kingdom. The participants sat unsupported on a
height-adjustable plinth with their
thighs fully supported on the plinth,
knees at 90 degrees, and feet flat on
the ground as the starting position.
The assessment of UE impairment
(with the FMA-UE) was conducted
only for people with stroke. Trunk
control was assessed with the TIS,
once with no external trunk support
and once with an adjustable highdensity foam support around the
trunk (Fig. 1). The use of an appropriately sized trunk support, which
fit snugly at the posterior and lateral
aspects of the trunk (up to the level
between the tenth and twelfth thoracic vertebrae), provided trunk support but allowed free forward movement and minimal movement in the
posterior and lateral directions.
After the trunk assessment, the UE
function of the participants was
assessed with and without trunk support (with the SWMFT). People with
August 2015
Figure 1.
Trunk support.
stroke performed the SWMFT tasks
with the unaffected UE and then
with the affected UE. The order of
testing with trunk support and without trunk support was randomized
by use of blocked randomization,28
with a block size of 4, to avoid possible order bias due to practice or
fatigue while ensuring equal numbers in the order protocols. People
who were healthy performed the
SWMFT tasks with the dominant UE
and then with the nondominant UE.
Hand dominance was determined
with the Edinburgh Handedness
Inventory–Short Form.29
Data Analysis
Data analysis was performed with
IBM SPSS Statistics 20 software (IBM
SPSS, Chicago, Illinois). The level of
statistical significance was set at a P
value of less than .05 for all tests. The
Shapiro-Wilk test was used to confirm normal data distribution.
In view of the comparison of 2
groups (people with chronic stroke
and people who were healthy)
under 2 support conditions (with
trunk support and without trunk
support), a split-plot analysis of variance (SPANOVA) was used to ana-
lyze the results for the TIS and
SWMFT performance times because
they were interval variables. The
affected UE of people with stroke
was compared with the nondominant UE of people who were
healthy. This design allowed participants with hemiparesis in the nondominant arm to be at less of a comparative disadvantage.30 The main
effect of group, the main effect of
support, and the interaction effect
(interaction between group and support conditions) were analyzed. The
results for the SWMFT FAS (ordinal
scale) under the 2 support conditions were analyzed with the Wilcoxon signed rank test.
The SPANOVA was used to compare
the difference in SWMFT performance times on the basis of sex,
hand dominance, the order of testing
of trunk support, the type of stroke,
and the side of the affected UE for
people with stroke and people who
were healthy.
The association between the TIS and
SWMFT performance times under
the condition of no trunk support
was determined with the Pearson
correlation coefficient because the
Volume 95
Number 8
Physical Therapy f
1165
Table 1.
Characteristics of Participantsa
People Who Were Healthy
(nⴝ34)
Characteristic
Age (y)
People With Stroke (nⴝ25)
X
SD
Range
X
SD
Range
60.4
12.4
38–82
65.3
12.0
38–84
107.1
12–432
15.3
14–64
Sex (no. of participants)
Men
18
15
Women
16
10
Time since stroke (mo)
N/A
100.4
Ischemic
N/A
18
Hemorrhagic
N/A
7
Type of stroke (no. of participants)
Hand dominance (no. of participants)
Right
Left
30
23
4
2
Affected upper extremity (no. of participants)
Right
N/A
9
Left
N/A
16
N/A
41.4
Fugl-Meyer Assessment (FMA) UE subsection
score
No. of participants with FMA score of:
a
ⱕ20 (severe impairment)
N/A
4
21–50 (moderate impairment)
N/A
12
51–66 (mild impairment)
N/A
Trunk Impairment Scale score
22.62
9
1.00
19–23
18.00
3.80
10–23
N/A⫽not applicable, UE⫽upper extremity.
data were normally distributed. The
Spearman rho (␳) was used to determine the relationship between the
TIS and the SWMFT FAS because the
SWMFT FAS is an ordinal scale.
Because of the normal distribution of
FMA-UE data, the Pearson correlation coefficient was used to determine the relationship between the
TIS and the FMA-UE.
This work was partly supported by
the European Union under the Seventh Framework Programme, grant
agreement #288692, StrokeBack.
The funds were used to cover the
transportation cost for the participants. Tan Tock Seng Hospital, Singapore, provided funding for the first
author’s PhD study at the University
of Southampton, United Kingdom.
1166
f
Physical Therapy
Volume 95
Results
SWMFT performance times, from
37.20 seconds to 35.37 seconds
(P⬍.05), for the affected UE with
trunk support relative to no trunk
support (Tab. 2).
Participants
Twenty-five people with chronic
stroke (mean age⫽65.3 years,
SD⫽12.0) and 34 people who were
healthy and matched for age and sex
(mean age⫽60.4 years, SD⫽12.4)
were recruited (Tab. 1). There was
no significant difference in age
between people with stroke and
people who were healthy. All of the
participants were able to perform
the SWMFT tasks.
With trunk support, the SWMFT performance times of people who were
healthy was reduced significantly,
from 1.61 to 1.48 seconds (P⬍.001)
for the dominant UE and from 1.71
to 1.59 seconds (P⬍.001) for the
nondominant UE (Tab. 2).
Clinical Outcomes
People with stroke demonstrated significant improvement in TIS scores,
from 18 points to 20 points
(P⬍.001), significant improvement
in SWMFT FAS scores, from a median
of 3.3 points to 3.4 points (P⬍.01),
and a significant reduction in
Comparison of Clinical Outcomes
in People With Chronic Stroke
and People Who Were Healthy
The results of the SPANOVA
revealed a statistically significant difference (F1,57⫽44.39, P⬍.001) in
TIS scores between people with
stroke and people who were
Number 8
August 2015
Table 2.
Clinical Outcomes of People Who Were Healthy and People With Strokea
People Who Were Healthy (nⴝ34)
Without
Trunk
Support
Outcome Measure
X
Trunk Impairment Scale score
(maximum score⫽23)
22.62
People With Stroke (nⴝ25)
With Trunk
Support
SD
X
1.02 22.85
b
SWMFT performance time of dominant
UE in people who were
healthy/affected UE in people with
stroke
1.6b
0.38
1.48
SWMFT performance time of
nondominant UE in people who were
healthy/unaffected UE in people with
stroke
1.71b
0.34
1.59b
SWMFT FAS score of dominant UE in
people who were healthy/affected UE
in people with stroke (maximum
score⫽5)
5
5
SWMFT FAS score of nondominant UE
in people who were healthy/
unaffected UE in people with stroke
(maximum score⫽5)
5
5
Without Trunk
Support
With Trunk
Support
SD
95% CI
X
SD
X
SD
95% CI
0.70
⫺0.10, 0.48
18.00b
3.76
20.00b
2.80
1.12, 2.88
0.35
0.08, 0.18
37.20c
49.22
35.37c
47.37
0.15, 3.80
0.30
0.04, 0.19
8.12
9.18
7.31
8.82
⫺0.59, 2.22
3.3 (1.8–4.3)d
3.4 (1.9–4.4)d
5
5
a
CI⫽confidence interval (CI of difference between the 2 means [without trunk support versus with trunk support]), SWMFT⫽Streamlined Wolf Motor
Function Test, UE⫽upper extremity, FAS⫽Functional Ability Scale.
b
P⬍.001.
c
P⬍.05.
d
Reported as median (first quartile through third quartile). P⬍.01.
healthy, regardless of the support
conditions (Tab. 3). The partial etasquared (␩2p), a measure of effect
size, was found to be 0.44 (large
effect size). By convention, ␩2p values
of 0.01, 0.06, and 0.14 represent
small, moderate, and large effect
sizes, respectively.31,32 People with
stroke had significantly lower TIS
scores (X⫽18.00 points) than people who were healthy (X⫽22.62
points). The difference between TIS
scores with trunk support and TIS
scores without trunk support,
regardless of the groups, was significant (F1,57⫽33.06, P⬍.001), and the
effect size was large (␩2p⫽0.37)
(Tab. 3). Further analysis revealed a
large significant interaction effect
(between group and support conditions)
(F1,57⫽20.60,
P⬍.001,
␩2p⫽0.27).
The results of the SPANOVA
revealed a significant difference
(F1,57⫽17.63, P⬍.001) in SWMFT
performance times between people
Table 3.
SPANOVA Results for TIS Scores and SWMFT Performance Time in People Who Were Healthy and People With Strokea
X (SD)
Clinical Outcome
TIS score
SWMFT performance time
Group
Without Support
With Support
People with stroke
18.00 (3.76)
20.00 (2.80)
People who were
healthy
22.62 (1.02)
22.85 (0.70)
People with stroke
37.20 (49.22)
35.37 (47.37)
People who were
healthy
1.71 (0.34)
1.59 (0.30)
F
P
Partial
Eta-Squared
Group
44.39
⬍.001
0.44
Support
33.06
⬍.001
0.37
Support ⫻ group
20.60
⬍.001
0.27
Group
17.63
⬍.001
0.24
Support
5.59
⬍.05
0.09
Support ⫻ group
4.37
⬍.05
0.07
Effect
SPANOVA⫽split-plot analysis of variance, TIS⫽Trunk Impairment Scale, SWMFT⫽Streamlined Wolf Motor Function Test, support ⫻ group⫽interaction
effect.
a
August 2015
Volume 95
Number 8
Physical Therapy f
1167
Discussion
In the present study, we investigated
the effect of providing external
trunk support on trunk control and
UE function and examined the relationship between trunk control and
UE function in people with chronic
stroke and people who were healthy
by using clinical scales.
Figure 2.
Moderate significant interaction effect between group and support conditions (P⬍.05,
partial eta-squared⫽0.07). SWMFT-Time⫽Streamlined Wolf Motor Function Test performance time.
with stroke and people who were
healthy, regardless of the support
conditions (Tab. 3). The effect size
was large (␩2p⫽0.24). The difference
in SWMFT performance times
between the 2 support conditions,
regardless of the groups, was significant (F1,57⫽5.59, P⬍.05), and the
effect size was moderate (␩2p⫽0.09).
There was a moderate significant
interaction effect (between group
and support conditions) (F1,57⫽4.37,
P⬍.05; ␩2p⫽0.07). Although SWMFT
performance times were significantly reduced with trunk support in
both groups, the reduction was significantly larger in people with
stroke (from 37.20 seconds to 35.37
seconds) than in people who were
healthy (from 1.71 seconds to 1.59
seconds) (Fig. 2).
There was no significant difference
in SWMFT performance times
between people with stroke and
people who were healthy on the
basis of sex (F1,57⫽0.08, P⫽.78),
hand
dominance
(F1,57⫽0.52,
P⫽.48), or the order of testing of
trunk support (F1,57⫽2.32, P⫽.14).
For people with stroke, there was no
significant difference in SWMFT per1168
f
Physical Therapy
Volume 95
formance times on the basis of the
type of stroke (F1,23⫽0.95, P⫽.34)
or the side of the affected UE
(F1,23⫽0.07, P⫽.80).
Association Between TIS and
Clinical Variables
There was no significant correlation
between the TIS and SWMFT performance times (Pearson correlation
coefficient r⫽⫺.31, P⬎.05) or
between the TIS and the SWMFT FAS
(Spearman ␳⫽.38, P⬎.05) in people
with stroke and without trunk support. A significant moderate correlation was found between the TIS and
the FMA-UE (r⫽.53, P⬍.01) in people with stroke and without trunk
support.
No association was found between
the TIS and SWMFT performance
times in people who were healthy
and did not receive trunk support
(r⫽⫺.08, P⬎.05). The coefficient of
correlation between the TIS and the
SWMFT FAS in people who were
healthy was not calculated because
all achieved the maximum score of 5
on the SWMFT FAS.
Number 8
With trunk support, there were significant improvements in trunk control (TIS) in people with stroke and
significant improvements in the performance of UE tasks (SWMFT performance times) and UE function
(SWMFT FAS) in both people with
stroke and people who were
healthy. The significant reduction in
the SWMFT performance time of
1.83 seconds with trunk support in
people with chronic stroke was considered a clinically important difference. The minimal clinically important difference for WMFT time was
reported to be 1.5 seconds to 2 seconds for people with chronic
stroke.23 However, it is important to
recognize that the SWMFT did not
distinguish between tasks accomplished by UE movements and those
accomplished by UE movements
assisted by trunk movement because
no kinematic analysis was conducted
in the present study. We plan to conduct a kinematic analysis of the trunk
and UE during performance of the
SWMFT tasks to understand the
mechanisms underlying the changes
in outcome measures in a future
study. A significant interaction effect
(between group and support conditions) was demonstrated for the TIS
and SWMFT performance times. The
findings demonstrated that a higher
TIS score was associated with better
UE function and supported the common assumption that a stable trunk
enables the dissociation of the UE
from the trunk for function.
In the present study, we did not
investigate the mechanisms associated with the improved UE function.
August 2015
However, we propose possible
explanations for the significant
reduction in SWMFT performance
times and the improvement in
SWMFT FAS scores when the trunk
was supported. It is possible that a
stabilized trunk enabled improved
movement of the proximal and distal
segments of the UE to occur against
a background of stabilized core muscles of the body. This notion is supported by a study demonstrating a
significant improvement in the functional reaching ability of the UE in
people with stroke after an intervention consisting of trunk stability
exercise.33 These data suggest that
trunk stability has an effect on the
stability of the shoulders which, in
turn, improves the movement of the
elbow, wrist, and fingers.34 A stable
trunk provides a solid foundation for
the torque generated by the extremities.35 Performing a reaching movement on a stable surface is different
from the challenges faced when
attempting to reach for objects while
balancing on an unstable surface.
Studies have demonstrated that
unstable conditions can lead to
decreased force output and muscle
activation of the extremities.36,37
the upper trunk and the lower
trunk.39 In other words, the motor
system has to manage at least 32
DOFs during a reaching task in an
unsupported seated condition. Our
external trunk support aided in the
stabilization of the trunk, limiting
trunk excursion or reducing the
number of DOFs, especially in the
lower trunk. This scenario could
have led to a decrease in the overall
demand on the motor system to reorganize the DOFs of the UE into a
coordinated pattern of reaching
movement and thus might have led
to improvements in SWMFT performance times and SWMFT FAS scores.
This notion is congruent with the
finding, in a recent systematic
review, that the manipulation of
mechanical DOFs of the trunk via
trunk restraint during reaching
enhances the recovery of UE function after stroke.40
Previous trunk restraint studies13–21
demonstrated that the restriction of
compensatory trunk movements by
a physical restraint can lead to
improved shoulder and elbow movements and thereby result in improvements in reaching to grasp. The
present study demonstrated an
improvement in UE function
(SWMFT performance times and
SWMFT FAS scores) with external
trunk support that was not constraining. Taken together, the results indicate that stabilizing or physically
restricting the trunk improves UE
function. This effect may be
explained by considering the concept of degrees of freedom (DOFs).
The improvements in SWMFT performance times and SWMFT FAS
scores might have been due to the
design (“C-shaped”) of the trunk support and its height (up to approximately the T10 –T12 vertebral levels). The external support might
have assisted the pelvis in tilting
more anteriorly, thus facilitating a
more extended position of the lower
lumbar region. This alteration might
have led to postural improvement
for UE task performance. This postulation is supported by studies demonstrating that trunk posture and
alignment affect UE performance.3,41
A neutral trunk posture and alignment significantly improved UE performance relative to flexed3,41 and
laterally flexed3 trunk postures.
Taken together, the findings of the
present study and previous studies3,41 support the hypothesis that a
stable trunk with good postural
alignment enables the dissociation of
the UE from the trunk for function.
There are a minimum of 26 DOFs for
UE movement38 and 3 DOFs each in
No association was found between
the TIS and SWMFT performance
August 2015
times or between the TIS and
SWMFT FAS scores in people with
stroke; this result may have been due
to the relatively small sample size.
However, the observation of an
improvement in UE function with
trunk support demonstrates a link
between trunk control and UE,
which is supported by a significant
moderate correlation between trunk
control
and
UE
impairment
(FMA-UE).
On the basis of our results, it can be
suggested that incorporating external trunk support may offer an
opportunity for better movement
reeducation and facilitate better
retraining of the UE. However, this
concept must be explored further,
and appropriately designed intervention studies are needed to examine
the effect of providing external
trunk support on UE function during
rehabilitation after stroke.
The results of the present study must
be considered in light of methodological limitations. All of the assessments with the TIS, FMA-UE, and
SWMFT were administered by the
principal investigator. This design
may have introduced an element of
observer bias to the study. Another
potential limitation of the present
study was the standardized height of
the trunk support; the superior part
of the trunk support was at different
contact points on the posterior and
lateral aspects of the trunk for the
participants. However, the height of
the trunk support was designed so
that none of the participants would
experience restrictions as they performed lateral flexion of the trunk
during the TIS assessment. For
addressing this limitation, however,
trunk supports with different height
dimensions could be created. We
acknowledge that the use of external
trunk support would invalidate the
administration of the TIS. The reason
for the inclusion of trunk support in
the experimental procedure was to
Volume 95
Number 8
Physical Therapy f
1169
simulate the presence of someone
with a “better” TIS score (ie, with
better trunk control) in the same session and then to investigate its effect
on UE function.
Another limitation that might have
confounded the observed improvements in the outcome measures was
the Hawthorne effect. To minimize
any presence of the Hawthorne
effect or performance bias, we did
not inform the participants of the
hypothesis of the study. Eliminating
the Hawthorne effect completely in
the present study would have been
challenging because providing a
sham condition would have been difficult, but this goal is an important
consideration for future studies.
Because the present study was crosssectional, a causal relationship cannot be drawn from the results unless
future randomized controlled trials
are conducted to verify the association reported here.42 In the present
study, we measured trunk control
not from a kinematic perspective but
with a clinical scale based on the TIS.
In a future study, we plan to capture
kinematic data to shed light on the
mechanisms associated with the
improvements in UE function with
external trunk support.
The observed improvements in
trunk control and UE function with
trunk support were immediate
effects; carryover was not assessed
because it was not the aim of the
present study. It remains unknown
whether a period of UE training with
external trunk support for people
with stroke will yield sustainable
gains in the observed improvements
in trunk control and UE function. In
the future, we may conduct a randomized controlled trial to investigate the effectiveness of trunk support in improving UE function.
port on trunk control and UE in
patients with trunk ataxia due to
neurological disorders, such as cerebellar stroke or brain stem stroke.
Gaining a deeper understanding of
the mechanisms underlying trunk
stability and trunk control may
provide insights into a new therapeutic approach for the management of trunk ataxia and UE in
neurorehabilitation.
External trunk support improved
trunk control in people with chronic
stroke and had a statistically significant effect on UE function in both
people with chronic stroke and people who were healthy. The findings
suggest an association between
trunk control and UE when external
trunk support was provided and support the hypothesis that lower trunk
and lumbar stabilization provided
by external support enables an
improvement in the ability to use the
UE for functional activities.
Mr Wee, Dr Hughes, Dr Warner, Dr Cranny,
Dr Mazomenos, and Dr Burridge provided
concept/idea/research design. Mr Wee, Dr
Hughes, Dr Warner, and Dr Burridge provided writing. Mr Wee, Dr Warner, Mr
Brown, Dr Cranny, and Dr Mazomenos provided data collection. Mr Wee and Dr Warner provided data analysis. Mr Wee and Dr
Hughes provided project management and
study participants. Mr Wee and Dr Burridge
provided fund procurement. Mr Brown, Dr
Warner, Dr Cranny, and Dr Mazomenos provided facilities/equipment. Mr Wee, Dr
Hughes, Dr Warner, and Dr Burridge provided consultation.
The Institutional Review Board of the University of Southampton, United Kingdom,
approved the study (Ethics Number 7547).
This work was partly supported by the European Union under the Seventh Framework
Programme, grant agreement #288692,
StrokeBack.
Mr Wee acknowledges Tan Tock Seng Hospital, Singapore, for funding his PhD study at
the University of Southampton, United
Kingdom.
DOI: 10.2522/ptj.20140487
Future researchers may consider
investigating the effect of trunk sup1170
f
Physical Therapy
Volume 95
Number 8
References
1 Verheyden G, Nieuwboer A, Mertin J,
et al. The Trunk Impairment Scale: a new
tool to measure motor impairment of the
trunk after stroke. Clin Rehabil. 2004;18:
326 –334.
2 Davies PM. Steps to Follow: The Comprehensive Treatment of Patients With
Hemiplegia. 2nd ed. Berlin, Germany:
Springer; 2000.
3 Gillen G, Boiangiu C, Neuman M, et al.
Trunk posture affects upper extremity
function of adults. Percept Mot Skills.
2007;104:371–380.
4 Rosenblum S, Josman N. The relationship
between postural control and fine manual
dexterity. Phys Occup Ther Pediatr. 2003;
23:47– 60.
5 Hsieh C, Sheu C, Hsueh I, Wang C. Trunk
control as an early predictor of comprehensive activities of daily living function in
stroke patients. Stroke. 2002;33:2626 –
2630.
6 Duarte E, Marco E, Muniesa JM, et al.
Trunk control test as a functional predictor in stroke patients. J Rehabil Med.
2002;34:267–272.
7 Verheyden G, Nieuwboer A, De Wit L,
et al. Trunk performance after stroke: an
eye catching predictor of functional outcome. J Neurol Neurosurg Psychiatry.
2007;78:694 – 698.
8 Di Monaco M, Trucco M, Di Monaco R,
et al. The relationship between initial
trunk control or postural balance and inpatient rehabilitation outcome after stroke: a
prospective comparative study. Clin
Rehabil. 2010;24:543–554.
9 Sebastia E, Duarte E, Boza R, et al. Crossvalidation of a model for predicting functional status and length of stay in patients
with stroke. J Rehabil Med. 2006;38:204 –
206.
10 Franchignoni FP, Tesio L, Ricupero C, Martino MT. Trunk control test as an early
predictor of stroke rehabilitation outcome. Stroke. 1997;28:1382–1385.
11 Clarke P. Well-being after stroke in Canadian seniors: findings from the Canadian
Study of Health and Aging. Stroke. 2002;
33:1016 –1021.
12 Desrosiers J, Malouin F, Richards C, et al.
Comparison of changes in upper and
lower extremity impairments and disabilities after stroke. Int J Rehabil Res. 2003;
26:109 –116.
13 Michaelsen SM, Dannenbaum R, Levin MF.
Task-specific training with trunk restraint
on arm recovery in stroke: randomized
control trial. Stroke. 2006;37:186 –192.
14 Michaelsen SM, Levin MF. Short-term
effects of practice with trunk restraint on
reaching movements in patients with
chronic stroke: a controlled trial. Stroke.
2004;35:1914 –1919.
15 Thielman G. Rehabilitation of reaching
poststroke: a randomized pilot investigation of tactile versus auditory feedback for
trunk control. J Neurol Phys Ther. 2010;
34:138 –144.
August 2015
16 Woodbury ML, Howland DR, McGuirk TE,
et al. Effects of trunk restraint combined
with intensive task practice on poststroke
upper extremity reach and function: a
pilot study. Neurorehabil Neural Repair.
2009;23:78 –91.
17 Wu CY, Chen YA, Lin KC, et al. Constraintinduced therapy with trunk restraint for
improving functional outcomes and trunkarm control after stroke: a randomized
controlled trial. Phys Ther. 2012;92:483–
492.
18 Wu CY, Chen YA, Chen HC, et al. Pilot
trial of distributed constraint-induced therapy with trunk restraint to improve poststroke reach to grasp and trunk kinematics. Neurorehabil Neural Repair. 2012;
26:247–255.
19 de Oliveira R, Cacho EW, Borges G.
Improvements in the upper limb of hemiparetic patients after reaching movements
training. Int J Rehabil Res. 2007;30:67–70.
20 Michaelsen SM, Luta A, Roby-Brami A,
Levin MF. Effect of trunk restraint on the
recovery of reaching movements in hemiparetic patients. Stroke. 2001;32:1875–
1883.
21 Wee SK, Hughes AM, Warner M, Burridge
JH. Trunk restraint to promote upper
extremity recovery in stroke patients: a
systematic review and meta-analysis. Neurorehabil Neural Repair. 2014;28:660 –
677.
22 Wolf SL, McJunkin JP, Swanson ML, Weiss
PS. Pilot normative database for the Wolf
Motor Function Test. Arch Phys Med
Rehabil. 2006;87:443– 445.
23 Lin KC, Hsieh YW, Wu CY, et al. Minimal
detectable change and clinically important
difference of the Wolf Motor Function
Test in stroke patients. Neurorehabil Neural Repair. 2009;23:429 – 434.
August 2015
24 Page SJ, Fulk GD, Boyne P. Clinically
important differences for the upperextremity Fugl-Meyer Scale in people with
minimal to moderate impairment due to
chronic stroke. Phys Ther. 2012;92:791–
798.
25 Bogard K, Wolf S, Zhang Q, et al. Can the
Wolf Motor Function Test be streamlined?
Neurorehabil Neural Repair. 2009;23:
422– 428.
26 Chen HF, Wu CY, Lin KC, et al. Rasch
validation of the Streamlined Wolf Motor
Function Test in people with chronic
stroke and subacute stroke. Phys Ther.
2012;92:1017–1026.
27 Sullivan JE, Crowner BE, Kluding PM, et al.
Outcome measures for individuals with
stroke: recommendations from the American Physical Therapy Association Neurology Section Task Force. Phys Ther. 2013;
93:1383–1396.
28 Efird J. Blocked randomization with randomly selected block sizes. Int J Environ
Res Public Health. 2011;8:15–20.
29 Veale
JF.
Edinburgh
Handedness
Inventory-Short Form: a revised version
based on confirmatory factor analysis. Laterality. 2014;19:164 –177.
30 Alt Murphy M, Willen C, Sunnerhagen KS.
Kinematic variables quantifying upperextremity performance after stroke during
reaching and drinking from a glass. Neurorehabil Neural Repair. 2011;25:71– 80.
31 Cohen J. Statistical Power Analysis for
the Behavioral Sciences. 2nd ed. Hillsdale,
NJ: Lawrence Erlbaum; 1988.
32 Richardson JTE. Eta squared and partial eta
squared as measures of effect size in educational research. Educ Res Rev. 2011;6:
135–147.
33 Kim YH, Kim EJ, Gong WT. The effects of
trunk stability exercise using PNF on the
Functional Reach Test and muscle activities of stroke patients. J Phys Ther Sci.
2011;23:699 –702.
34 Miyake Y, Kobayashi R, Kelepecz D, Nakajima M. Core exercises elevate trunk stability to facilitate skilled motor behavior of
the upper extremities. J Bodyw Mov Ther.
2013;17:259 –265.
35 Behm DG, Drinkwater EJ, Willardson JM,
Cowley PM. The use of instability to train
the core musculature. Appl Physiol Nutr
Metab. 2010;35:91–108.
36 Behm DG, Anderson K, Curnew RS. Muscle force and activation under stable and
unstable conditions. J Strength Cond Res.
2002;16:416 – 422.
37 Anderson KG, Behm DG. Maintenance of
EMG activity and loss of force output with
instability. J Strength Cond Res. 2004;18:
637– 640.
38 Edwards WH. Motor Learning and Control: From Theory to Practice. Belmont,
CA: Wadsworth, Cengage Learning; 2010.
39 Zatsiorsky VM. Kinematics of Human
Motion. Champaign, IL: Human Kinetics;
1998.
40 Hayward KS, Barker RN, Carson RG,
Brauer SG. The effect of altering a single
component of a rehabilitation programme
on the functional recovery of stroke
patients: a systematic review and metaanalysis. Clin Rehabil. 2014;28:107–117.
41 Gandavadi A, Ramsay J. Effect of two seating positions on upper limb function in
normal subjects. Int J Ther Rehabil. 2005;
12:485– 490.
42 Mann CJ. Observational research methods:
research design II— cohort, cross sectional, and case-control studies. Emerg
Med J. 2003;20:54 – 60.
Volume 95
Number 8
Physical Therapy f
1171
Research Report
Y-J. Huang, BS, School of Occupational Therapy, College of Medicine, National Taiwan University,
Taipei, Taiwan.
K-L. Chen, PhD, Department of
Occupational Therapy, College of
Medicine, National Cheng Kung
University, Tainan, Taiwan.
Y-T. Chou, MS, Department of
Psychology, National Chung
Cheng University, Chiayi, Taiwan,
and Research Center for Psychological and Educational Testing,
National Taiwan Normal University, Taipei, Taiwan.
I-P. Hsueh, MA, School of Occupational Therapy, College of Medicine, National Taiwan University,
4F, No. 17, Xuzhou Road, Taipei
100, Taiwan, and Department of
Physical Medicine and Rehabilitation, National Taiwan University
Hospital. Address all correspondence to Ms Hsueh at: iping@
ntu.edu.tw.
C-Y. Hou, MS, Department of
Physical Medicine and Rehabilitation, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan.
C-L. Hsieh, PhD, School of Occupational Therapy, College of Medicine, National Taiwan University,
and Department of Physical Medicine and Rehabilitation, National
Taiwan University Hospital.
[Huang Y-J, Chen K-L, Chou Y-T,
et al. Comparison of the responsiveness of the long-form and simplified
Stroke
Rehabilitation
Assessment of Movement: groupand individual-level analysis. Phys
Ther. 2015;95:1172–1183].
Association
March 5, 2015
Accepted: February 17, 2015
Comparison of the Responsiveness of
the Long-Form and Simplified Stroke
Rehabilitation Assessment of
Movement: Group- and IndividualLevel Analysis
Yi-Jing Huang, Kuan-Lin Chen, Yeh-Tai Chou, I-Ping Hsueh, Chieh-Yi Hou,
Ching-Lin Hsieh
Background. The group-level responsiveness of the original, 30-item Stroke
Rehabilitation Assessment of Movement measure (STREAM-30) is similar to that of the
simplified STREAM (STREAM-15), even though the STREAM-30 has twice as many
items as those of the STREAM-15.
Objective. The purpose of this study was to compare the responsiveness of the
STREAM-30 and STREAM-15 at both group and individual levels in patients with
stroke. For the latter level, the Rasch-calibrated 27-item STREAM (STREAM-27) was
used because the individual-level indexes of the STREAM-30 could not be estimated.
Design. A repeated-measurements design was used. In total, 195 patients were
assessed with the STREAM-30 at both admission and discharge.
Methods. The Rasch scores of the STREAM-27 and STREAM-15 were estimated
from the participants’ responses on the STREAM-30. We calculated the paired t-test
value, effect size, and standardized response mean as the indexes of group-level
responsiveness. The significance of change for each participant was estimated as the
individual-level responsiveness index, and the paired t test and test of marginal
homogeneity were used for individual-level comparisons between the STREAM-27
and STREAM-15.
Results. At the group level, the STREAM-30, STREAM-27, and STREAM-15 showed
sufficient and comparable responsiveness. At the individual level, the STREAM-27
detected significantly more participants with significant improvement and fewer
participants with no change or deterioration compared with the STREAM-15.
Limitations. Few patients with subacute stroke showed deterioration at discharge, so the abilities of the 2 measures to detect deterioration remain inconclusive.
Conclusions. The STREAM-27 detected more participants with significant recovery compared with the STREAM-15, although the group-level responsiveness of the 2
measures was the same. The STREAM-27 is recommended as an outcome measure to
demonstrate the treatment effects of movement and mobility for patients with stroke.
this article at:
ptjournal.apta.org
1172
f
Physical Therapy
Volume 95
Number 8
August 2015
Group- and Individual-Level Responsiveness of 3 Measures
R
esponsiveness can be defined
as the ability of a measure to
detect change when it has
occurred.1–3 Outcome measures
should be responsive in order to
demonstrate treatment effects and
monitor patients’ progress.4 Some
authors have argued that the responsiveness of a measure should be
examined at both the group level
(detection of the average amount of
change in a group) and the individual level (detection of change in an
individual patient).2 To date, most
studies examining the responsiveness of measures have used grouplevel indexes, which show the average treatment effect of a patient
population.2,3 However, group-level
indexes can hardly be applied to
interpret change in individual
patients in clinical or research settings,5 and individual-level indexes
can help interpret individual
patients’ treatment effects that
group-level indexes cannot. Therefore, both the group-level responsiveness and the individual-level
responsiveness of an outcome measure are critical for researchers and
clinicians to identify changes over
time in patients.
Moreover, it has been argued that
group-level comparisons of the
responsiveness of competing measures (eg, long-form and short-form
measures) potentially misrepresent
the responsiveness of measures, possibly leading users to select a rather
unresponsive outcome measure.6 – 8
In the past, short-form measures
were recommended for efficiently
quantifying patients’ progress due to
their briefness, speediness, and ability to detect change (ie, group-level
responsiveness) similar to that of the
long-form measures.9 –12 Nevertheless, in these studies, only grouplevel comparisons were conducted,
casting doubt on the implications of
the findings. Previous studies compared the responsiveness of shortform and long-form measures
August 2015
(eg, the 5-item short-form Postural
Assessment Scale for Stroke Patients
[PASS] versus the 12-item PASS, the
12-item short-form Fugl-Meyer Motor
Scale [FM] versus the 50-item FM)
at both group and individual
levels.6 – 8,13 The short-form measures
were found to have inferior individuallevel responsiveness, although both
short-form and long-form measures
have equivalent group-level responsiveness. Thus, the responsiveness of
outcome measures should be compared at both group and individual
levels to provide comprehensive and
robust evidence for clinicians and
researchers to select from among
competing measures.
Movement and mobility impairments
are very frequent sequelae after
stroke.14 To plan treatment and monitor progress, it is crucial to assess
movement and mobility functions in
patients with stroke. The original,
30-item Stroke Rehabilitation Assessment of Movement (STREAM-30) is
one of the recommended objective
and quantitative outcome measures
for assessing voluntary upper and
lower limb movement (UL and LL)
and basic mobility (MO) difficulties
after stroke.15,16 Its psychometric
properties (reliability, validity, and
group-level responsiveness) have
been well supported by previous
studies based on the classical test
theory.16 –20 The STREAM-30 is recommended and preferred over other
related movement or mobility measures for measuring and monitoring
motor function in patients with
stroke.19,20 However, the STREAM-30
has a weakness in the construct validity revealed by Rasch analysis.21 Furthermore, the STREAM-30 requires 15
to 35 minutes to complete.22 Such a
time-consuming administration limits
the utility of the STREAM-30 in clinical
settings. Accordingly, the 27-item
STREAM (STREAM-27) and its short
form, the 15-item simplified STREAM
(STREAM-15), have been constructed to improve the psychomet-
ric properties and clinical utility of
the STREAM-30.21
The STREAM-15 is brief and quick to
administer, and its psychometric
properties are similar to those of the
STREAM-30, particularly the grouplevel responsiveness.10,21,23 However, as mentioned above, the similarity in group-level responsiveness does
not guarantee similar abilities to detect
change in an individual patient. Due to
the lack of evidence supporting the
individual-level responsiveness, clinicians and researchers cannot select a
more responsive measure that can
detect changes in movement and
mobility in more patients. To ameliorate this situation, this study aimed
to compare the responsiveness of
the STREAM-30, STREAM-27, and
STREAM-15 at both group and individual levels in patients with stroke.
However, the STREAM-30 was not
used in the individual-level comparison because the Rasch scores of the
STREAM-30, used for calculating
individual indexes, could not be estimated. Because the STREAM-27 has
more items and thus provides more
information for assessing movements and mobility, we hypothesized that the STREAM-27 would
have
superior
individual-level
responsiveness.
Method
Participants
The data used in this study were
obtained from a previous longitudinal follow-up study.10 Participants
were recruited from the departments of physical medicine and rehabilitation at 5 hospitals in Taiwan
between April 2004 and October
2005. Patients were eligible for the
study if they met the following criteria: (1) first or recurrent onset of
cerebrovascular accident without
other major diseases (eg, cancer,
amputation, severe rheumatoid
arthritis), (2) subacute stroke with
hemiparesis or hemiplegia, (3) ability to follow instructions to com-
Volume 95
Number 8
Physical Therapy f
1173
plete the measure, and (4) informed
consent given personally or by
proxy. Patients discharged within 1
week of admission for rehabilitation
were excluded.
Procedure
Each participant was assessed with
the STREAM-30 at admission to the
rehabilitation wards and reassessed
at discharge. The assessments were
administered by 1 of 12 therapists (3
physical therapists and 9 occupational therapists) who were experienced in using the STREAM-30. The
interrater reliability of these raters
on the 3 subscales of the STREAM-30
was sound (intraclass correlation
coefficients ⬎.96).10 The data of
both the STREAM-27 and STREAM-15
were obtained from the STREAM-30
data of the same sample.
Measures
The STREAM-30 contains 30 items
equally divided into 3 subscales (ie,
10 items in each of the UL, LL, and
MO subscales).16 The items of the UL
and LL subscales are scored on a
3-point ordinal scale (0 –1–2) for rating the excursion and quality of limb
movement as compared with the less
impaired side. The items of the MO
subscale are scored on a 4-point ordinal scale (0 –1–2–3) for rating the
quality, completion, and assistance
required of the task. A total of 20
points can be obtained from each
limb subscale, and 30 points can be
obtained from the MO subscale.
The STREAM-27 was revised from
the STREAM-30 based on Rasch analysis to improve the psychometric
properties of the STREAM-30.21 The
responses of 3 items in the
STREAM-30 (2 UL susbscale items:
scapular elevation and opposition; 1
LL subscale item: hip abduction) did
not conform to the Rasch model’s
assumptions24 (ie, unidimensionality
and equal item discrimination).
Thus, the misfit items were deleted
to obtain the advantages of Rasch
1174
f
Physical Therapy
Volume 95
analysis, such as the resulting scores
can be viewed as intervals rather
than ordinal scores, and the standard
error (SE) of each score can be estimated for users.21 The STREAM-27
consists of 27 items: 8 UL subscale
items, 9 LL subscale items, and 10
MO subscale items. The scaling of
each subscale is the same as that of
the STREAM-30. All 27 items in their
respective subscales showed good fit
to the Rasch model. The 3 subscales
of STREAM-27 have good-toexcellent Rasch reliability.21
The STREAM-15 was constructed
to improve the administrative efficiency of the STREAM-30. The
STREAM-15 was developed from
the STREAM-27 by retrieving 5 items
in each of the subscales according to
Rasch analysis and item representativeness.21 The scaling of the
STREAM-15 is identical to that of
the STREAM-30. The psychometric
properties of the STREAM-15 are comparable to those of the STREAM-30 and
STREAM-27, including the Rasch reliability, test-retest reliability, unidimensionality, concurrent validity, predictive validity, discriminative validity,
and group-level responsiveness.10,21,23
The Barthel Index (BI) was developed to assess basic activities of daily
living (ADL) function in patients
with neurological or musculoskeletal
problems.25 The total score ranges
from 0 to 20. The BI has satisfactory
psychometric properties in patients
after stroke.26,27 We used the BI as
the external criterion to investigate
the external responsiveness of the 3
STREAM measures.
Data Analysis
In this study, we used the raw scores
of the STREAM-30 and the Rasch
scores of the STREAM-27 and the
STREAM-15 for data analyses. We
estimated the Rasch scores and standard errors of the 3 subscales for
both the STREAM-27 and the
STREAM-15 using the multidimen-
Number 8
sional Rasch rating scale model. The
Rasch score for each subscale was
linearly transformed to a range of 0
to 100 for ease of understanding.
The linear transformation equation
for each subscale was: Rasch score ⫻
100 ⫼ (maximum Rasch score ⫺
minimum Rasch score). All item
parameter estimates (ie, difficulty
logits) were fixed to the values
obtained from the original data in the
study by Hsueh et al.21 This process
was used to ensure that the Rasch
parameters of each item were consistent across assessments at the 2
time points.
Comparison of the group-level
responsiveness. To examine the
group-level responsiveness of the 3
subscales of the STREAM-30,
STREAM-27, and STREAM-15, both
the internal and external responsiveness were inspected. Regarding the
internal responsiveness, we calculated 3 indexes: paired t test, effect
size (ES), and standardized response
mean (SRM). Paired t tests were performed to determine the significance
of the change scores in each subscale from admission to discharge.
Two-sided P⬍.05 was considered
statistically significant. Both the ES
and SRM provided information on
the magnitude of change. Effect size
was calculated by dividing the mean
change scores by the standard deviation of the baseline scores.28 The SRM
was calculated by dividing the mean
change scores by the standard deviation of the change scores.28 Effect size
and SRM values ⱖ0.80 were considered large, values of 0.50 to 0.80 were
considered moderate, and values of
0.20 to 0.50 were considered
small.29,30 To investigate the external
responsiveness, the correlation
between change scores in each subscale of the 3 STREAM measures and
those in the external criterion, the
BI, was calculated using the Pearson correlation coefficient (r). Pearson coefficients ⱖ.60 were consid-
August 2015
2
2
SEdifference ⫽ 冑SEadmission
⫹ SEdischarge
ered high, values of .30 to .60 were
considered moderate, and values
ⱕ.30 were considered poor.31 A
moderate correlation was considered to indicate sufficient external
responsiveness.
(2)
We used the bootstrap approach32 to
compare statistical differences of the
group-level internal and external
responsiveness among the 3 STREAM
measures. We drew 10,000 bootstrap
samples, each equal in size to the number of participants observed. For each
of the 10,000 samples, we calculated
the ES, SRM, and r values for each
subscale and calculated pair-wise differences of the ES, SRM, and r values
among the 3 STREAM measures. We
examined whether zero was
included in the 98.4% bootstrap percentile confidence intervals (CIs)
of differences. The critical alpha
level was adjusted down to .016
(ie, ␣/n comparisons⫽.05/3) applying the Bonferroni correction for
multiple comparisons. If zero was
not included, the group-level internal or external responsiveness of
those 2 measures was considered
significantly different.
With respect to the external responsiveness, we calculated the percentages of the participants who had significant improvement in each
STREAM measure and had improvement above the minimal clinically
important difference (MCID) in the
BI. Significant improvement in the
STREAM measures was determined
as an SC ⱖ1.96 ⫻ linear transformation equation. The MCID of the BI,
the lowest benchmark to determine
whether the changes are important
to patients with stroke, has been estimated to be 1.85.34
Comparison of the individuallevel responsiveness. Both the
internal and external responsiveness
were investigated at the individual
level. To examine the individuallevel internal responsiveness of the
STREAM-27 and STREAM-15, we estimated the significance of change
(SC) for each participant. The SC was
adopted to quantify the size of an
individual
participant’s
Rasch
change score between admission
and discharge, which was expressed
in units of his or her own SE of the
Rasch score.6 The SE for each participant’s score was estimated by Rasch
analysis. The SC was calculated using
the following formulas6,33:
(1)
SC ⫽
Rasch scoredischarge ⫺ Rasch scoreadmission
SEdifference
August 2015
A brief description of the deduction
of the SEdifference formula is provided
in the Appendix.
To compare the individual-level
responsiveness
between
the
STREAM-27 and STREAM-15, we conducted paired t tests, marginal homogeneity tests (G2 statistics), and tests
for difference of proportion (DP) in
the comparisons of internal responsiveness, as well as DP in the comparisons of external responsiveness. In
terms of the internal responsiveness,
paired t tests were adopted to determine the statistical differences of the
mean SCs of both measures. In addition, we used G2 statistics to examine whether the distributions of participants detected to achieve
different levels of SC by the 2 measures were different. We categorized
the SCs according to their sizes and
directions into the following 3
groups: (1) significant improvement:
SC ⱖ1.96 ⫻ linear transformation
equation; (2) nonsignificant improvement: 0 ⬍ SC ⬍ 1.96 ⫻ linear
transformation equation; and (3) no
change or deterioration: SC ⱕ0. A P
value of ⬍.05 in G2 statistics was
considered statistically significant.
The 95% CI for the DP was used to
compare the 2 proportions in each
SC group. Zero in this interval meant
that there was no difference
between the 2 proportions. As for
the comparisons of the external
responsiveness,
we
examined
whether zero was included in the
95% CI for the DP between the 2
STREAM measures in each subscale.
Floor and ceiling effects. The
floor and ceiling effects of the 3 subscales in each STREAM measure
were examined. We calculated the
percentages of the participants who
obtained the lowest and highest possible scores to indicate floor and ceiling effects, respectively. Floor and
ceiling effects ⬎15.0% were considered significant.35
This study was supported by
research grants from the E-Da
Hospital
(EDAHT102015
and
EDAHT103027).
Results
A total of 388 participants were
assessed using the STREAM-30 at
admission, but 193 of these participants were lost at second assessment
either because they were in an unstable condition or were discharged
without prior notification. The
remaining 195 participants (50.3%)
completed the assessments at both
admission and discharge, and their
data were used for further analyses.
The baseline scores of the 3 subscales of the STREAM-30 of the
remaining 195 participants were not
significantly different (P⬎.05) from
those of the 193 participants lost at
second assessment. The scores of
the 195 participants were scattered
across the entire ranges of the 3 subscales’
possible
scores.10
As
expected, deterioration during hospitalization was detected by the
STREAM-30 in a few of the participants (10, 12, and 6 participants for
the UL, LL, and MO subscales,
respectively). The demographic
characteristics of the participants
and the raw scores and Rasch scores
Volume 95
Number 8
Physical Therapy f
1175
Table 1.
Demographic Characteristics and Descriptive Statistics of the STREAM-30, STREAM-27, and STREAM-15 in Participants With
Stroke (n⫽195)a
Characteristic
Value
Sex (n), male/female
130/65
Age (y), X (SD)
63.4 (13.7)
Side of lesion (n), right/left
109/86
Measure
STREAM-30 (raw score)
Subscale
Admission/Discharge
X (SD)
UL
8.7 (8.2)/10.5 (8.3)
LL
8.0 (7.3)/10.4 (7.7)
MO
11.5 (8.5)/15.8 (8.9)
UL
6.9 (6.6)/8.4 (6.8)
LL
STREAM-27 (Rasch score)
STREAM-15 (Rasch score)
7.4 (6.6)/9.5 (6.9)
MO
11.5 (8.5)/15.8 (8.9)
UL
4.4 (4.2)/5.3 (4.3)
LL
4.2 (3.7)/5.3 (3.9)
MO
6.2 (4.1)/8.4 (4.2)
UL
47.6 (27.1)/55.5 (27.4)
LL
47.3 (25.1)/56.3 (25.5)
MO
41.9 (20.9)/52.6 (21.6)
UL
47.4 (28.1)/55.3 (28.4)
LL
46.3 (26.4)/55.8 (27.0)
MO
43.6 (21.6)/54.6 (21.9)
a
STREAM-30⫽the original Stroke Rehabilitation Assessment of Movement, STREAM-27⫽the 27-item STREAM, STREAM-15⫽the 15-item STREAM, UL⫽upper
limb movement, MO⫽basic mobility, LL⫽lower limb movement.
of the STREAM-30, STREAM-27, and
STREAM-15 are shown in Table 1.
Comparison of the Group-Level
Responsiveness
Table 2 presents the scores for grouplevel internal and external responsiveness of the STREAM-30, STREAM-27,
and STREAM-15. Regarding the internal responsiveness, the changes in
score between admission and discharge of each subscale in the 3 measures were all significant (t⫽
7.89 –15.05, all P values ⬍.001). The
ES and SRM values showed the 3
STREAM measures to have similar and
small-to-large group-level internal
responsiveness. As to the external
responsiveness,
the
correlation
between the change scores of each
subscale and those of the BI were similar among the 3 STREAM measures.
The UL and LL subscales demonstrated
1176
f
Physical Therapy
Volume 95
moderate external responsiveness,
and the MO subscale showed high
external responsiveness.
Table 3 shows the results of comparisons of group-level internal and external indexes among the 3 STREAM measures. In terms of the internal indexes
(ES and SRM), zero was included in
most 98.4% CI values of the differences. Particularly, the STREAM-15
had ES and SRM values similar to those
of the STREAM-30 and STREAM-27,
except for the comparisons in UL and
LL subscales between the STREAM-15
and STREAM-30. That is, the ES and
SRM values of the UL subscale and the
SRM values of the LL subscale of the
STREAM-15 were significantly higher
than those of the STREAM-30, but the
magnitudes of difference were small.
Concerning the external indexes (r
values), all of the 98.4% CI values
Number 8
embraced zero, indicating that the
external responsiveness did not differ
significantly among the 3 STREAM
measures.
Comparison of the IndividualLevel Responsiveness
The results for individual-level internal and external responsiveness of
the STREAM-27 and STREAM-15 are
listed in Table 4. For internal responsiveness, the mean SCs of the
STREAM-27 were higher than those
of the STREAM-15, and the differences were significant in all 3 subscales (t⫽3.56 – 6.00, all P values
⬍.001). The G2 statistics show that
the distributions of participants in
the 3 SC groups were significantly
different between the STREAM-27
and STREAM-15 (P⫽.002–.011). In
terms of the proportions in each SC
group, more participants were
August 2015
Table 2.
Group-Level Internal and External Responsiveness of the STREAM-30, STREAM-27, and STREAM-15 (n⫽195)a
Subscale
Measure
UL
LL
MO
1.9 (3.4)
2.3 (3.3)
4.4 (4.4)
STREAM-30 raw score
Mean change score (SD)
Internal responsiveness
7.89 (⬍.001)
9.98 (⬍.001)
14.00 (⬍.001)
ES
t (P)
0.23
0.32
0.52
SRM
0.57
0.72
1.00
External responsiveness
r (P)
.38 (⬍.001)
.40 (⬍.001)
7.9 (10.5)
9.0 (9.9)
.67 (⬍.001)
STREAM-27 Rasch score
10.7 (9.9)
10.45 (⬍.001)
12.71 (⬍.001)
15.05 (⬍.001)
ES
t (P)
0.29
0.36
0.51
SRM
0.75
0.91
1.08
r (P)
.35 (⬍.001)
.40 (⬍.001)
.64 (⬍.001)
7.9 (11.2)
9.5 (10.8)
11.0 (10.6)
9.84 (⬍.001)
12.26 (⬍.001)
14.39 (⬍.001)
ES
t (P)
0.28
0.36
0.51
SRM
0.71
0.88
1.03
r (P)
.38 (⬍.001)
.45 (⬍.001)
.62 (⬍.001)
a
limb movement, MO⫽basic mobility, LL⫽lower limb movement, ES⫽effect size, SRM⫽standardized response mean.
detected to achieve “significant
improvements” of LL and MO function by the STREAM-27 (22.6%–
35.9%) than by the STREAM-15
(18.5%–29.2%). The UL subscales of
both measures exhibited trends similar to those of the LL and MO subscales. On the other hand, a significantly smaller proportion of
participants were categorized as having “no change or deterioration” in
each of the 3 subscales by the
STREAM-27 (12.8%–18.5%) than by
the STREAM-15 (18.5%–24.1%).
Regarding the external responsiveness, significantly more participants
were found to have significant/imAugust 2015
portant improvement by both the
STREAM-27 and BI (20.0%–32.8%)
than by both the STREAM-15 and BI
(17.4%–26.7%) in the MO subscale.
The UL and LL subscales also showed
similar trends.
The Figure shows the distributions of
the SE values (vertical axis) across UL,
LL, and MO subscale functions (horizontal axis) for the STREAM-27 and
STREAM-15 at admission and discharge. The curves of the SE values of
both measures appeared to be parallel.
Particularly, at every time point and
subscale, a majority of the SE values of
the STREAM-15 were larger than those
of the STREAM-27, and the mean SE
values of the STREAM-15 were significantly larger than those of the
STREAM-27 (t⫽22.46 – 46.56, all P values ⬍.001).
Floor and Ceiling Effects
Table 5 shows that the STREAM-30
demonstrated both significant floor
effects (21.0%–31.3%) and ceiling
effects (19.0%–26.2%) in the UL subscale at both time points, a significant
floor effect (20.5%) at admission, and a
significant ceiling effect (19.5%) at discharge in the LL subscale and no significant floor or ceiling effects in the
MO subscale. Neither a floor effect nor
Volume 95
Number 8
Physical Therapy f
1177
Table 3.
Bootstrap Analyses for Comparisons of Group-Level Internal and External Responsiveness Among the STREAM-30 (Raw Score),
STREAM-27 (Rasch Score), and STREAM-15 (Rasch Score) in Participants With Stroke (n⫽195)a
98.4% CI of Differencesb
Measure
UL
LL
MO
ES
STREAM-30 vs STREAM-27
⫺.10, ⫺.02c
⫺.07, .00
⫺.02, .03
⫺.09, ⫺.01c
⫺.08, .00
⫺.04, .06
⫺.01, .03
⫺.03, .03
⫺.03, .04
⫺.30, ⫺.08c
⫺.28, ⫺.12c
⫺.13, ⫺.02c
⫺.26, ⫺.03c
⫺.27, ⫺.06c
⫺.11, .06
⫺.01, .10
⫺.06, .12
⫺.04, .14
⫺.08, .12
⫺.08, .07
⫺.01, .07
⫺.11, .09
⫺.15, .04
⫺.02, .13
⫺.07, .02
⫺.12, .02
⫺.04, .09
SRM
Pearson r
a
STREAM-30⫽the original Stroke Rehabilitation Assessment of Movement, STREAM-27⫽the 27-item STREAM, STREAM-15⫽the 15-item STREAM,
UL⫽upperlimb movement, MO⫽basic mobility, LL⫽lower limb movement, CI⫽confidence interval, ES⫽effect size, SRM⫽standardized response mean.
b
Applying the Bonferroni correction for multiple comparisons, the critical alpha level was adjusted down to .016 (ie, ␣/n comparisons⫽.05/3). Thus, we
used 98.4% CI.
c
ES or SRM values between 2 measures were significantly different.
a ceiling effect was found in the 3
subscales of the STREAM-27 and those
of the STREAM-15.
Discussion
The main purpose of this study was
to investigate whether the ability of
the STREAM-15 to detect patients’
progress is similar to those of the
STREAM-30 and STREAM-27 at both
the group and individual levels. We
found that the STREAM-15 showed
sufficient and similar group-level
responsiveness, both in internal and
external indexes, to the STREAM-30
and STREAM-27; however, the
STREAM-27 had greater individuallevel internal and external responsiveness than the STREAM-15. These
results demonstrate that the STREAM30, STREAM-27, and STREAM-15 are
equally able to identify changes in
movement status and mobility when
used in a group and that the group
changes in the 3 STREAM measures
can comparably reflect the corre1178
f
Physical Therapy
Volume 95
sponding changes of ADL function
assessed with the BI. As for detection
of an individual patient’s movement
and
mobility
recovery,
the
STREAM-27 can detect more patients
with significant movement and
mobility improvement than the
STREAM-15. In addition, the
STREAM-27 revealed a greater number of patients achieving both significant recovery in movement and
mobility and clinically important
improvement in ADL function.
Accordingly, the STREAM-27 is recommended as an outcome measure
to demonstrate treatment effects of
movement and mobility for patients
with stroke in both clinical and
research settings.
The superior ability of the STREAM-27
over that of the STREAM-15 to detect
change in movement and mobility
in individuals was supported by 2
individual-level indexes. First, all of the
SCs of the STREAM-27 were signifi-
Number 8
cantly higher than those of the
STREAM-15. That is, the STREAM-27
could identify greater amounts of
change in movement and mobility for
individual patients compared with the
STREAM-15. Second, the DP showed
that the STREAM-27 detected significantly more patients with significant
movement and mobility recovery and
fewer patients with no change or deterioration of movement and mobility
function compared with the STREAM15. The reason for the better
individual-level responsiveness of the
STREAM-27 could be that the
STREAM-27 yields smaller measurement errors (ie, SE values) of the
scores for individual patients, as
shown in the Figure. With a narrower
distribution (smaller SE values) of estimated scores, the score differences
between admission and discharge of
each patient are more likely to be significant. These observations indicate
that the STREAM-27 is a better
August 2015
2.6 (⫺0.4, 5.6)
18.5 (36)
21.0 (41)
BI improvement
⬎MCID
STREAM-27⫽the 27-item Stroke Rehabilitation Assessment of Movement, STREAM-15⫽the 15-item Stroke Rehabilitation Assessment of Movement, UL⫽upper limb movement, MO⫽basic mobility,
LL⫽lower limb movement, CI⫽confidence interval, BI⫽Barthel Index, DP⫽difference of proportion, SC⫽significance of change, MCID⫽minimal clinically important difference. The STREAM-30 was not
included in individual-level comparisons because its Rasch scores and standard errors could not be estimated using Rasch analysis.
b
DP was significant (P⬍.05).
a
6.2 (1.7, 10.6)b
26.7 (52)
32.8 (64)
2.6 (⫺1.0, 6.2)
17.4 (34)
DP (95% CI)
DP (95% CI)
20.0 (39)
DP (95% CI)
Significant
Improvement
% (n)
Significant
Improvement
% (n)
Significant
Improvement
% (n)
Significant
Improvement
% (n)
External
Responsiveness
Significant
Improvement
% (n)
Significant
Improvement
% (n)
⫺5.6 (⫺10.0, ⫺1.3)b
18.5 (36)
12.8 (25)
⫺5.1 (⫺9.6, ⫺0.7)b
20.0 (39)
⫺5.6 (⫺10.2, ⫺1.1)b
24.1 (47)
18.5 (36)
No change or
deterioration
14.9 (29)
⫺1.0 (⫺7.8, 5.8)
52.3 (102)
51.3 (100)
1.0 (⫺5.0, 7.1)
61.5 (120)
2.1 (⫺3.8, 7.9)
54.9 (107)
56.9 (111)
Nonsignificant
improvement
62.6 (122)
6.7 (1.5, 11.8)b
29.2 (57)
35.9 (70)
4.1 (0.1, 8.1)
18.5 (36)
22.6 (44)
3.6 (0.0, 7.2)
21.0 (41)
24.6 (48)
% (n)
DP (95% CI)
Significant
improvement
% (n)
% (n)
DP (95% CI)
% (n)
% (n)
SC Group
% (n)
1.2 (1.6)
G2 (P)
SC, X (SD)
b
6.00 (⬍.001)
1.4 (1.3)
1.7 (1.5)
3.56 (⬍.001)
9.0 (.011)
1.0 (1.1)
4.23 (⬍.001)
1.1 (1.5)
1.1 (1.2)
9.5 (.009)
t (P)
STREAM-15
STREAM-27
t (P)
STREAM-15
STREAM-27
Internal
Responsiveness
Measure
12.6 (.002)
t (P)
STREAM-15
STREAM-27
MO
LL
UL
Individual-Level Internal and External Responsiveness of the STREAM-27 (Rasch Score) and STREAM-15 (Rasch Score) (n⫽195)a
Table 4.
August 2015
DP (95% CI)
outcome
measure
than
the
STREAM-15 at the individual level.
Floor and ceiling effects limit a measure’s ability to detect changes in
individuals who score the minimum
and maximum scores, respectively,36
thereby decreasing both the grouplevel and the individual-level responsiveness of a measure. Our results
imply that both the STREAM-27
and STREAM-15 can differentiate
among individuals with low or high
levels of movement and mobility
function, but the STREAM-30 cannot. Such an observation results
from the fact that more measurement information from the related
subscales was taken into account
using multidimensional Rasch scaling model in the STREAM-27 and
STREAM-15. That is, a patient’s
Rasch score on one subscale (eg,
UL) was estimated by considering
the same patient’s responses on the
other 2 subscales (ie, LL and MO).
Thus,
the
STREAM-27
and
STREAM-15 were more likely than
the STREAM-30 to reveal the fine
distinctions among patients with
very low or high levels of function,
and the floor and ceiling effects of
the STREAM-27 were the smallest.
These findings may be one of the
reasons why the STREAM-27 and
STREAM-15 had similar but slightly
higher group-level responsiveness
than the STREAM-30 and why the
STREAM-27 had the best individuallevel responsiveness.
Previously, the STREAM-15 was recommended as an efficient and reliable substitute for the STREAM-30
because its group-level psychometric properties were shown to be as
robust as those of the STREAM-30
and STREAM-27.10,21,23 However, we
found that the STREAM-15 is less
able than the STREAM-27 to demonstrate treatment effects for individual
patients in clinical trials or clinical
settings. Our findings were consistent with those of previous studies
Volume 95
Number 8
Physical Therapy f
1179
Figure.
Comparison of standard errors across function location on the upper limb movement (UL), lower limb movement (LL), and basic
mobility (MO) subscales between the 27-item Stroke Rehabilitation Assessment of Movement (STREAM-27) and 15-item STREAM
(STREAM-15) at admission and discharge. The standard error for each participant’s Rasch score was estimated by Rasch analysis. The
standard errors showing U-shaped distribution, as shown in the other Rasch-calibrated measures,37–39 indicate that the measurement
errors of 2 extreme levels of function were larger. The large measurement errors were due to the smaller number of items developed
for both extremely difficult levels of function and led to less precise measurement.
comparing both the group-level and
individual-level responsiveness of
long-form and short-form outcome
measures.6 – 8,13 Long-form measures
are expected to be more responsive
than any of their short-form measures because more items with different difficulty levels would provide
more useful information to estimate
patients’ abilities. Thus, the measurement errors (SE) would decrease,
which would yield better individual1180
f
Physical Therapy
Volume 95
level responsiveness. These results
imply that using only the group-level
responsiveness is insufficient, and
the misguided belief in its sufficiency
might have led clinicians and
researchers to choose a less responsive outcome measure. Furthermore,
the individual-level responsiveness
of outcome measures can provide
individual-level effects (eg, individual patient’s progress, number of
patients with significant improve-
Number 8
ment) that the traditional indexes of
group-level responsiveness cannot
provide. This information can help
researchers to interpret the treatment effects and assist clinicians in
translating the evidence from
research to clinical settings (eg, how
many patients could benefit from the
treatment protocol). Thus, we
strongly suggest that individual-level
responsiveness needs to be included
in the examination of responsiveness
August 2015
Table 5.
Floor and Ceiling Effects of the STREAM-30, STREAM-27, and STREAM-15 at Admission and Discharge (n⫽195)a
Admission, n (%)
Measure
STREAM-30 raw score
Subscale
Discharge, n (%)
Floor Effect
Ceiling Effect
Floor Effect
Ceiling Effect
UL
61 (31.3)
37 (19.0)
41 (21.0)
51 (26.2)
LL
40 (20.5)
23 (11.8)
25 (12.8)
38 (19.5)
MO
8 (4.1)
0 (0.0)
5 (2.6)
3 (1.5)
UL
6 (3.1)
0 (0.0)
4 (2.1)
3 (1.5)
LL
6 (3.1)
0 (0.0)
4 (2.1)
3 (1.5)
MO
6 (3.1)
0 (0.0)
4 (2.1)
3 (1.5)
UL
10 (5.1)
1 (0.5)
4 (2.1)
3 (1.5)
LL
10 (5.1)
1 (0.5)
4 (2.1)
3 (1.5)
MO
10 (5.1)
1 (0.5)
4 (2.1)
3 (1.5)
a
limb movement, MO⫽basic mobility, LL⫽lower limb movement. The extents of the floor and ceiling effects on the 3 subscales of either the STREAM-27 or
the STREAM-15 were all the same because in the multidimensional Rasch model, only the participants who obtained the lowest or highest raw scores of all
3 subscales simultaneously had the lowest or highest Rasch scores, respectively.
of outcome measures in order to
provide comprehensive empirical
evidence.
This study had 3 limitations. First,
only 3% to 6% of the participants, as
expected, deteriorated during hospitalization. Therefore, the abilities of
the STREAM-27 and STREAM-15 to
detect deterioration of movement
and mobility in patients with stroke
remain unknown. Second, the participants were in the subacute stage.
Consequently, the individual-level
responsiveness of the STREAM-27
and STREAM-15 may not be generalized to the patients with acute or
chronic stroke. Last, the high attrition rate (49.7%) might limit the generalizability of our findings. However, the limitation of the
generalizability might be trivial for
the following 2 reasons. First, we
found that the differences in movement and mobility impairments
between the remaining 195 patients
and the 193 participants lost at second assessment were not significant.
In addition, the 195 participants covered a wide range of movement and
mobility deficits.
In summary, our findings demonstrate that the STREAM-27 is better
August 2015
able than the STREAM-15 to detect
movement and mobility improvement for an individual patient,
although the STREAM-15 and the
STREAM-27 are equally able to detect
change in a group. Thus, the
STREAM-27 is recommended as an
outcome measure to demonstrate
treatment effects of movement and
mobility for patients with stroke in
both clinical and research settings.
2 Beaton DE, Bombardier C, Katz JN, Wright
JG. A taxonomy for responsiveness. J Clin
Epidemiol. 2001;54:1204 –1217.
3 Wright JG, Young NL. A comparison of
different indices of responsiveness. J Clin
Epidemiol. 1997;50:239 –246.
4 Guyatt G, Walter S, Norman G. Measuring
change over time: assessing the usefulness
of evaluative instruments. J Chronic Dis.
1987;40:171–178.
5 Redelmeier DA, Tversky A. Discrepancy
between medical decisions for individual
patients and for groups. N Engl J Med.
1990;322:1162–1164.
6 Hobart JC, Cano SJ, Thompson AJ. Effect
sizes can be misleading: is it time to
change the way we measure change?
J Neurol Neurosurg Psychiatry. 2010;81:
1044 –1048.
All authors provided concept/idea/research
design. Ms Huang and Dr Hsieh provided
writing. Dr Hsieh provided data collection,
project management, fund procurement,
and administrative support. Mr Chou provided data analysis. Mr Hou provided study
participants. Dr Chen and Ms Hsueh provided consultation (including review of manuscript before submission).
7 Hsueh IP, Chen KL, Chou YT, et al.
Individual-level responsiveness of the original and short-form Postural Assessment
Scale for Stroke Patients. Phys Ther. 2013;
93:1377–1382.
8 Chen KL, Chen CT, Chou YT, et al. Is the
long form of the Fugl-Meyer motor scale
more responsive than the short form in
patients with stroke? Arch Phys Med
Rehabil. 2014;95:941–949.
This study was approved by the Institutional
Review Board of National Taiwan University
Hospital.
9 Chien CW, Lin JH, Wang CH, et al. Developing a short form of the Postural Assessment Scale for people with stroke. Neurorehabil Neural Repair. 2007;21:81–90.
This study was supported by research grants
from the E-Da Hospital (EDAHT102015 and
EDAHT103027).
10 Hsieh YW, Lin JH, Wang CH, et al. Discriminative, predictive and evaluative
properties of the simplified Stroke Rehabilitation Assessment of Movement Instrument in patients with stroke. J Rehabil
Med. 2007;39:454 – 460.
DOI: 10.2522/ptj.20140331
References
1 de Bruin AF, Diederiks JP, de Witte LP,
et al. Assessing the responsiveness of a
functional status measure: the Sickness
Impact Profile versus the SIP68. J Clin Epidemiol. 1997;50:529 –540.
11 Chou CY, Chien CW, Hsueh IP, et al.
Developing a short form of the Berg Balance Scale for people with stroke. Phys
Ther. 2006;86:195–204.
Volume 95
Number 8
Physical Therapy f
1181
12 Hobart JC, Thompson AJ. The five-item
Barthel index. J Neurol Neurosurg Psychiatry. 2001;71:225–230.
13 Chen KL, Chou YT, Yu WH, et al. A prospective study of the responsiveness of the
original and the short form Berg Balance
Scale in people with stroke. Clin Rehabil.
2015;29:468 – 476.
14 Langhorne P, Coupar F, Pollock A. Motor
recovery after stroke: a systematic review.
Lancet Neurol. 2009;8:741–754.
15 Baker K, Cano SJ, Playford ED. Outcome
Measurement in stroke: a scale selection
strategy. Stroke. 2011;42:1787–1794.
16 Daley K, Mayo N, Danys I, et al. The Stroke
Rehabilitation Assessment of Movement
(STREAM): refining and validating the content. Physiother Can. 1997;49:269 –278.
17 Daley K, Mayo N, Wood-Dauphinée S. Reliability of scores on the Stroke Rehabilitation Assessment of Movement (STREAM)
measure. Phys Ther. 1999;79:8 –19.
18 Wang CH, Hsieh CL, Dai MH, et al. Interrater reliability and validity of the Stroke
Rehabilitation Assessment of Movement
(STREAM) instrument. J Rehabil Med.
2002;34:20 –24.
19 Hsueh IP, Wang CH, Sheu CF, Hsieh CL.
Comparison of psychometric properties of
three mobility measures for patients with
stroke. Stroke. 2003;34:1741–1745.
20 Ahmed S, Mayo NE, Higgins J, et al. The
Stroke Rehabilitation Assessment of Movement (STREAM): a comparison with other
measures used to evaluate effects of stroke
and rehabilitation. Phys Ther. 2003;83:
617– 630.
21 Hsueh IP, Wang WC, Wang CH, et al. A
simplified stroke rehabilitation assessment
of movement instrument. Phys Ther.
2006;86:936 –943.
1182
f
Physical Therapy
Volume 95
22 Sullivan JE. Measurement characteristics
and clinical utility of the Stroke Rehabilitation Assessment of Movement among
stroke patients. Arch Phys Med Rehabil.
2014;95:207–208.
23 Hsueh IP, Hsu MJ, Sheu CF, et al. Psychometric comparisons of 2 versions of the
Fugl-Meyer Motor Scale and 2 versions of
the Stroke Rehabilitation Assessment of
Movement. Neurorehabil Neural Repair.
2008;22:737–744.
24 Embretson SE, Reise SP. Item Response
Theory for Psychologists. Mahwah, NJ:
Lawrence Erlbaum Associates; 2000.
25 Mahoney FI, Barthel DW. Functional evaluation: the Barthel Index. Md State Med J.
1965;14:61– 65.
26 Hsueh IP, Lin JH, Jeng JS, Hsieh CL. Comparison of the psychometric characteristics of the Functional Independence Measure, 5-item Barthel Index, and 10-item
Barthel Index in patients with stroke.
J Neurol Neurosurg Psychiatry. 2002;73:
188 –190.
27 Hsueh IP, Lee MM, Hsieh CL. Psychometric characteristics of the Barthel activities
of daily living index in stroke patients. J
Formos Med Assoc. 2001;100:526 –532.
28 Husted JA, Cook RJ, Farewell VT, Gladman
DD. Methods for assessing responsiveness:
a critical review and recommendations.
J Clin Epidemiol. 2000;53:459 – 468.
29 Cohen J. Statistical Power Analysis for
the Behavioral Sciences. 2nd ed. Mahwah,
NJ: Lawrence Erlbaum Associates; 1988.
30 Crosby RD, Kolotkin RL, Williams GR.
Defining clinically meaningful change in
health-related quality of life. J Clin Epidemiol. 2003;56:395– 407.
Number 8
31 Andresen EM. Criteria for assessing the tools
of disability outcomes research. Arch Phys
Med Rehabil. 2000;81(supple 2):S15–S20.
32 Efron B. Bootstrap methods: another look
at the jackknife. Ann Stat. 1979;7:1–26.
33 Maassen GH. The standard error in the
Jacobson and Truax Reliable Change
Index: the classical approach to the assessment of reliable change. J Int Neuropsychol Soc. 2004;10:888 – 893.
34 Hsieh Y-W, Wang C-H, Wu S-C, et al. Establishing the minimal clinically important
difference of the Barthel Index in stroke
patients. Neurorehabil Neural Repair.
2007;21:233–238.
35 Terwee CB, Bot SD, de Boer MR, et al.
Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60:34 –
42.
36 Fitzpatrick R, Davey C, Buxton MJ, Jones
DR. Evaluating patient-based outcome
measures for use in clinical trials. Health
Technol Assess. 1998;2:i–iv, 1–74.
37 Hsueh IP, Wang WC, Sheu CF, Hsieh CL.
Rasch analysis of combining two indices
to assess comprehensive ADL function in
stroke patients. Stroke. 2004;35:721–726.
38 Hsueh IP, Chen JH, Wang CH, et al. Development of a computerized adaptive test
for assessing activities of daily living in
outpatients with stroke. Phys Ther. 2013;
93:681– 693.
39 Lu YM, Wu YY, Hsieh CL, et al. Measurement precision of the disability for back
pain scale-by applying Rasch analysis.
Health Qual Life Outcomes. 2013;11:119.
August 2015
Appendix.
Deduction of SEdifference Formulaa
In classical test theory, the observed scores comprise true scores and measurement errors. If a patient’s ability (ie,
true score) has not changed between assessments, which is a necessary assumption in the estimation of reliability,
the fluctuation of observed scores between 2 assessments obtained on the same measure by the same patient comes
solely from the measurement errors (formulas 1 and 2). Therefore, the variance of the observed change scores
(measurement error between repeated assessments) is equal to the variance of the difference of the measurement
errors (formula 3). In addition, the measurement errors are random variables and are assumed to be independent
between repeated assessments. Thus, the covariance of the measurement errors between admission and discharge
should be zero and could be ignored for calculation of SEdifference (formula 4). The deduction of SEdifference formula
are presented as follows:
(1)
Rasch scoreadmission ⫽ True score (T) ⫹ Measurement error (E)admission
(2)
Rasch scoredischarge ⫽ True score (T) ⫹ Measurement error (E)discharge
(3)
2
SEdifference
⫽ Variance (Rasch scoredischarge ⫺ Rasch scoreadmission)
⫽ Variance (T ⫹ Edischarge ⫺ T ⫺ Eadmission)
⫽ Variance (Edischarge ⫺ Eadmission)
⫽ Variance (Edischarge) ⫹ Variance (Eadmission) ⫺ 2 Covariance (Edischarge, Eadmission)
2
2
⫹ SEdischarge
⫺0
⫽ SEadmission
2
2
⫽ SEadmission
⫹ SEdischarge
(4)
SEdifference ⫽
2
冑SEadmission
2
⫹ SEdischarge
a
The abbreviation “SE” here means measurement error, not standard error of the mean. The SE represents the measurement error of an individual patient’s
Rasch score, and the SEdifference means the measurement error of an individual patient’s Rasch change score between repeated assessments.
August 2015
Volume 95
Number 8
Physical Therapy f
1183
Perspective
Rise, Fall, and Revival of MedicoMechanical Institutes
Nils Hansson, Anders Ottosson
N. Hansson, PhD, Institute for the
History of Medicine and Medical
Ethics, University of Cologne,
Joseph-Stelzmann-Strasse
20,
50931 Köln/Cologne, Germany.
Hansson at: [email protected].
A. Ottosson, PhD, Department of
Historical Studies, Gothenburg
University, Gothenburg, Sweden.
[Hansson N, Ottosson A. Nobel
Prize for physical therapy? Rise,
fall, and revival of medicomechanical institutes. Phys Ther.
2015;95:1184 –1194.]
This historical vignette explores the considerations of the Nobel Prize Committee for
Physiology or Medicine by vetting the Nobel Prize chances of Dr Gustaf Zander
(1835–1920). His way to stardom started 150 years ago when he began mechanizing
the passive and active movements that physical therapists manually used to treat
diseases. A glance at his machines shows that they parallel surprisingly well what can
be found in modern fitness studios. By combining files from the Nobel Prize Archive
and sources from the first physical therapists, this vignette pieces together why
Zander was considered one of the best candidates for the Nobel Prize in 1916. By
providing this glimpse of history, questions about the origin of physical therapy
concepts and the profession of the physical therapist are raised.
Association
February 5, 2015
Submitted: June 24, 2014
this article at:
ptjournal.apta.org
1184
f
Physical Therapy
Volume 95
Number 8
August 2015
D
id a researcher with physical
therapy interests ever have a
chance to receive the Nobel
Prize for Physiology or Medicine? In
this overview, we will examine the
discussions of the Nobel Prize committee concerning a major contributor to the development of presentday fitness studios—who, as we will
see, was a very strong candidate for
the Nobel Prize in 1916. The aim of
this article is to shed light on overlooked aspects of the history of the
physical therapy profession by relating to a Nobel Prize nomination and
a Nobel committee report as well as
to sources from the first physical
therapists. Although the Nobel Prize
Archive at the Karolinska Institute in
Solna, Sweden, has gained scholarly
attention among historians,1– 8 this
specific area has, to date, been
neglected. First, we will briefly contextualize the rise of the physical
therapy profession and mechanomedical medicine in Sweden and
identify some important historical
figures. Second, we will highlight the
remarkable transfer of their theories
and praxis within Europe and to the
United States. We argue that not only
Zander’s machines but also the US
physical therapy profession could be
better understood if the context and
transfer of knowledge put forward
here were better included in historical analyses. Finally, we reconstruct
and discuss how the Nobel Prize
committee dealt with mechanomedical medicine and in what way
their arguments were tainted by the
First World War.
In his will of 1895, the Swedish innovator Alfred Nobel stipulated that 1
of 5 yearly Nobel Prizes should go to
the person “who [had] made the
most important discovery within the
domain of physiology or medicine.”9
The first Nobel Prize was awarded in
1901. Today, it is seen as the most
prestigious benchmark of excellence
in medicine, and it is used for ranking universities and gauging the sciAugust 2015
Figure 1.
Torso rotator. Source: Tekniska Muséet, Stockholm, Sweden.
entific reputation of whole nations.
It is the job of the Nobel Prize committee at the Karolinska Institute to,
each year, single out 1, 2, or 3 prizeworthy individuals.
In the first 2 decades of the 20th
century, hundreds of scholars were
nominated for the Nobel Prize for
Physiology or Medicine. The majority of all nominees were physiologists, such as Eduard Pflüger (unsuccessfully nominated 40 times!)10;
bacteriologists, such as the 1905
Nobel Prize laureate Robert Koch11;
or surgeons, such as Theodor
Kocher12, the Nobel Prize recipient
of 1909, all praised for their promising lab-oriented research. However,
in the Nobel Prize committee’s shortlist of candidates in 1916, 1 of the 6
possible laureates was atypical: the
Swedish physician Jonas Gustaf Wilhelm Zander (1835–1920). Zander’s
5 competitors were very much on
par with the contemporary scientific
profile and reflected the kind of biomedical cutting-edge research that
was in vogue at the time. Zander was
nominated for his so-called medicomechanical devices, which aimed at
treating and curing many chronic
diseases and orthopedic deformities
(eg, scoliosis). Altogether, he had
designed no fewer than 76
apparatuses13,14(p258) “to twist every
part of the body in every possible
direction”15(p493) (Figs. 1 and 2).
Although not selected by the Nobel
Prize committee, Zander did not
stand out only for his physical therapy interests. He also was one of
Volume 95
Number 8
Physical Therapy f
1185
Figure 2.
“Swedishroom” at Dr Harvey Kellogg’s world-famous sanitarium, Battle Creek, Michigan. The machines are Zander’s but could be
modified. Kellogg was known to alter and mix different practices. Source: Willard Library, Battle Creek, Michigan.
Europe’s leading theosophians (from
the Greek the- ⫹ sophia–wisdom)
and published more than 200 articles
on this matter.16 The theosophians
represented an esoteric and mystic
philosophy in search of the divine
organic truths of life and nature.
It is tempting to view Zander’s odd
but strong candidacy as only an
expression of the nationalistic “zeitgeist” found in Europe at the time
and assume that he was favored
because he was a Swedish physician.
If you overlook the theosophian part
of Zander’s career, it is not hard to
see why this could be the case. Few
Swedish physicians can match his
impact on a global scale. From 1864
(when he opened his first mechanomedical institute in Stockholm, Sweden) onward, Zander’s machines
reached almost every corner of the
world. They were found at universities, sanitariums, and hospitals in
Scandinavia, the United States,
Argentina, Bulgaria, France, Great
Britain, Portugal, Switzerland, Hol1186
f
Physical Therapy
Volume 95
land, Russia, Italy, and Spain. The list
continues with Belgium, Chile,
South Africa, Egypt, and Cuba. In
Germany, the success was particularly pronounced. The first Zander
institute was founded in BadenBaden in 1884, and in 1911 about
120 Zander institutes were in operation.17,18 Moreover, large oceangoing ships, such as the Titanic,
were equipped with Zander’s
machines, allowing passengers to
handle their ailments during the long
trips.
Zander gained worldwide recognition within the scientific community. His devices were shown at
international exhibitions—for example, in Brussels in 1876, in Philadelphia in 1876, and in Paris in 1878 —
and he received the Swedish Medical
Society’s gold medal for his dissertation titled “On the Treatment of
Chronic Scoliosis With Mechanical
Gymnastics/Physical Therapy.”17
Number 8
Mechanical Medicine and
Pehr Henrik Ling
As alluring as it might be to interpret
Zander’s Nobel Prize nomination
merely as a patriotic gesture from his
Swedish countrymen, there are
other historical circumstances that
can help us understand why Zander
caught the eyes of the Nobel
Prize committee. We believe that
these circumstances can be best
understood by relating his invention
to the therapeutic and scientific discourse from which they clearly
evolved. This discourse is forgotten
today but was very prominent during
the 19th century.
Zander’s gym machines reflect the
influence of the work of Pehr Henrik
Ling (1776 –1839), known as the
“father” of Swedish gymnastics.
Ling’s influence on institutionalized
physical education is well appreciated in international literature. His
gymnastic system contained a
branch of physical education (peda-
August 2015
Figure 3.
Patients treated at the Royal Central Institute of Gymnastics (RCIG) polyclinic, 1896. Source: The library of the Swedish School of
Sport and Health Sciences (current name of RCIG).
gogical gymnastics) deemed as prolific as German gymnastics (Turnen),
English sports, and the Sargent system in the United States. Ling was
first mentioned in the United States
in sources dating back to the 1830s,
although it was during the last
decades of the century that his
impact became immense. Many physicians favored Ling’s physical education over sports and other systems
because they believed that Ling’s
model was based on existing rational
and scientific principles.19 –21
No longer well known, however, is
how much physicians also favored a
different branch of Ling’s gymnastic
system, his physical therapy (in
Swedish, “sjukgymnastik,” and in
English, then called “medical gymnastics” or “remedial gymnastics”).
Many approved of his curative movements and manipulations to the
August 2015
extent that it is not an exaggeration
to state that Ling’s impact on 19th
century medicine even trumped
Zander’s—also in the United
States.22 Giants in physical medicine,
such as Dr Harvey Kellogg and Dr
Douglas Graham, have many connections to Ling and his physical therapy, with frequent references to him
in their publications.23,24 It is no
coincidence that Swedish Movements on Medical Gymnastics, written by the most authoritative author
of textbooks on Ling’s physical therapy in the 19th century, the Swedish
Professor T.J. Hartelius, was translated into English and published in
Battle Creek, Michigan, with a foreword by Kellogg himself.25
Ling’s legacy still is very much present. In 1813, he founded the Royal
Central Institute of Gymnastics
(RCIG) in Stockholm, which had a
great impact on the education and
professional identity of physical therapists (Fig. 3). The RCIG provided
the first formal education for physical therapists more than 200 years
ago. To avoid conceptual confusion,
it should be noted that the title
“physical therapist” or “physiotherapist” was not used as a distinct professional designation until a couple
of decades into the 20th century.
Today, most countries have changed
their former vernacular names to
“physiotherapist.” The Germans, for
instance, turned “Krankengymnast”
into “Physiotherapeut” in 1994, and
the Swedes recently did the same
with “sjukgymnast.” However, this
only entails nomenclature. Movements and manual techniques are
still the core of physical therapist
practice and physical therapists’ professional identity.
Volume 95
Number 8
Physical Therapy f
1187
With this in mind, we can readdress
the RCIG and its 19th century curriculum. Apart from anatomy, physiology, and pathology, the training program offered included Ling’s system
of gymnastics, which in addition to
physical therapy and pedagogical
gymnastics (or physical education)
also contained a branch of military
gymnastics (mostly fencing). The
system was viewed as an organism,
meaning that it could not reach its
full capacity unless all branches communicated with each other. An RCIG
examination rendered its alumni a
competence cluster, allowing them
to operate with both sick and
healthy bodies, in the army as well as
in civil society. When training students and soldiers, he was a physical
educator, and when treating sick
people, he was a physical therapist.
In 1887, this competence was given
the official prestigious title of “Director of Gymnastics,” a title referring to
an owner of a clinic where sick people were treated with physical therapy. The physical therapists earned
the right to be licensed by the government the very same year. When
the first women were allowed to
enter the RCIG in 1864, they gained
the same competence as the men,
the military part excluded.
To understand Ling’s (and hence
Zander’s) impact on physical therapy historically, we believe it is
important to note that it was the
physical therapy component of
Ling’s system that made it scientific,
something Ling and his numerous
followers agreed on during the major
part of the 19th century.23,26
Equally important to grasp are the
full intentions Ling had with his
physical therapy. Ling, and the physical therapists walking in his footsteps, wanted to revolutionize orthodox medicine, which they believed
was too occupied with pharmacological cures. Instead, Ling believed
that orthodox medicine should be
1188
f
Physical Therapy
Volume 95
oriented more toward mechanical
modes of treating illness, ergo his
physical therapy movements and
manipulations of the body. These
were seen as potent a remedy as
drugs and surgery. Hence, the medical sciences needed theoretical and
practical knowledge of Ling’s physical therapy, or the physicians’ regimens would remain unbalanced and
even “poisonous.” The RCIG’s main
objective, in fact, was to “cure”
orthodox medicine from its onesidedness.14(pp130 –139) The healing
powers of every undertaken movement and manipulation were declared to have a certain physiological
value, which rigorous scientific
work had proven valid. It also was
believed possible to direct their
effects to certain areas of the body
via blood vessels and nerves. In light
of the current popular trend in prescribing physical activity to patients,
it is interesting to note that 19th
century physical therapists did the
same. After careful examinations in
order to give a correct diagnosis, the
“cure” was administrated via individualized prescriptions containing a
combination of movements and
manipulations.
Although not free from contemporary criticism, Ling’s impact on
orthodox medicine did become
immense and was especially evident
in Sweden. Despite the fact that Ling
was not affiliated with a faculty of
medicine, the government sanctioned the RCIG’s objective to educate “doctors of gymnastics,” a title
referring to a “drug-physician” also
competent in “mechanics,” ergo
trained in the same way as physical
therapists. During several occasions
in the second half of the 19th century, the Karolinska Institute advocated Ling’s physical therapy as a
compulsory part of physicians’ curricula. Orthopedists especially were
enthusiastic, and they even used
Ling to help orthopedics reach scientific and therapeutic status. The
Number 8
scientific status of the RCIG was so
great that physical therapists, without being physicians, could receive
the title “professor of the Swedish
government.” Some physicians even
worked as employees at clinics
owned and headed by physical
therapists.
Worth noting is that Ling was by no
means the only person interested in
systemized mechanical cures. There
were others competing with him,
expressing similar interests and
ambitions, including physicians.27
Yet, it was his system of physical
therapy that reached the greatest scientific and therapeutic recognition.
One rival, for example, was Dr Daniel Gottlieb Moritz Schreber’s German “Kinesiatrik.” But it was not
until the end of the 19th century that
a physician started challenging
Ling’s top-ranking position in
mechanical medicine: the Dutch
physician Johann Metzger, who
received the epithet “inventor of scientific massage.”28
Regardless, the RCIG became an
international node and authoritative
center for physical therapists and
physicians interested in cures using
movements and manipulations. The
main proponents of Ling’s physical
therapy outside of Sweden were his
many disciples, physicians as well as
physical therapists. They were convinced that they were representatives of a new science destined to
convert the one-sided orthodox
medicine taught at the universities.
Consequently, they opened physical
therapy clinics abroad and wrote
books, theses, and pamphlets praising Ling and his mechanical
doctrines.29 –34
Ling’s Links to
Physical Therapy in the
United States
Before focusing on Zander’s Nobel
Prize nomination, it is worth asking
August 2015
ourselves if Ling’s influence needs to
be better accounted for in the analyses of the history of the physical
therapy profession. Ling’s physical
therapy is not touched upon in current research on the US physical
therapy profession. The accepted
premise is that the profession came
into being during World War I. The
experience of the war had made
American physicians see a need for
personnel able to rehabilitate soldiers who were maimed and
wounded. They directed their attention toward female physical education teachers, whose knowledge of
fitness, anatomy, and physiology
made them ideal to be trained as
“reconstruction aides” in so-called
“war emergency courses.”35–37 It is
also briefly mentioned in the literature that the physical therapists-to-be
were already educated in techniques
of manual therapy as well as massage. Little has been done, to date, to
investigate what kind of “manual
therapy” the first physical therapists
knew and where they had acquired
their skills.
Figure 4.
Although this still is a terra incognita, this white spot is easy to map,
at least tentatively, if we look more
closely at what kind of physical education the first physical therapists
mastered. The first 6 schools where
the reconstruction aides were
recruited and where the “war emergency courses” were set up are well
known: Reed College (Portland, Oregon), Normal School of Gymnastics
(Battle Creek, Michigan), New
Haven Normal School of Gymnastics
(New Haven, Connecticut), Boston
Normal School of Gymnastics, American School of Physical Education
(Boston, Massachusetts), and Posse
Normal School of Gymnastics (Boston, Massachusetts; originally Posse
Gymnasium).
When
cross-referencing
these
schools with studies on the history
of North American physical educaAugust 2015
A manual torso rotator. Here, 2 physical therapists fixate the patient’s body, and 2
physical therapists are executing the movement. This is exactly the same movement
mimicked by Zander in Figure 1. A comparison reveals how labor-intensive “manual
machines” could be compared with Zander’s machines. At most, 5 different physical
therapists or assistants were needed to execute a movement or technique. Source:
National Archives, Sweden.
tion, it becomes evident that many of
these schools, if not all, had Ling’s
gymnastic system as a kingpin. At the
closing decade of the 19th century,
Ling’s system became the favorite of
the normal schools training women
to become physical educators. Physical therapy (then called “medical
gymnastics” or “remedial gymnastics”), therefore, was often included
in the curriculum.19(p178),21 The system’s greatest promoter during the
1880s and 1890s, Dr Edward M.
Hartwell, believed the RCIG produced the best physical educators in
the world because its students were
trained to also handle children not fit
enough for the gymnasium.38,39 It
may not be far-fetched to assume
that the reconstruction aides coming
from these Normal Schools did not
need to be taught much of the
basics. To physical educators trained
with Ling’s system, working with
sick bodies was not alien.
Boston Normal School of Gymnastics
and Posse Normal School of Gymnastics carried the very distinctive
marks of the RCIG alumnus Baron
and Lieutenant Nils Posse. He is
sometimes referred to as the “Father
of Swedish Gymnastics” in the
United States,40 although when he
Volume 95
Number 8
Physical Therapy f
1189
physical therapy clinics prior to the
war.43
Gustaf Zander and Ling’s
Physical Therapy
Figure 5.
Bending and stretching the upper arm. Source: National Archives, Sweden.
first arrived in Boston in 1885, it was
as a physical therapist with the intention of propagating Ling’s physical
therapy. The idea of a strong Ling
connection also is reinforced when
highlighting the background of 2 of
the leading figures in early US physical therapy history: Marguerite Sanderson and Mary McMillan. Sanderson
was sent to Walter Reed General
Hospital in Washington, DC, in 1917
to organize units of the Reconstruction Aide Corps. She was a graduate
of the Boston Normal School of Gymnastics. When Sanderson left for
Europe to inspect her trainees, Mary
McMillan took her place. McMillan,
in turn, had “graduate work in physical culture and corrective exercises,
including Swedish gymnastics and
the dynamics of scoliosis.”41 Because
1190
f
Physical Therapy
Volume 95
she advanced and became organizer
of and instructor at the largest of the
“War Emergency Courses” (Reed
College) and founded the American
Physical Therapy Association (originally the American Physiotherapy
Association), we believe it is time to
pay more historical and sociological
attention to what McMillan says in
her most influential publication,
where she states that it is to “Peter
(sic) Henry Ling and Swedish systemized order that we owe much today
. . . in the field of medical gymnastics
or therapeutic exercise.”42 Further
research will try to substantiate the
validity of the questions raised in the
present article, but it is clear that
students from the Boston Normal
School of Gymnastics could open
Number 8
Having put forward the works and
the possible early influence of Ling
on the emerging American physical
therapy profession, we now turn our
attention to Dr Zander and his
accomplishments. Zander considered himself one of Ling’s successors. He wanted to duplicate the
many active and passive movements
(including massage techniques)
found in Ling’s physical therapy. He
believed that machines could execute the movements better than
humans and that machines guaranteed a more accurate way to measure
results, which made them more scientific. In other words, Zander’s
machines did not add anything new
to the actual movements; they had
been practiced systematically for a
long time, but manually.44 Using
weights and levers, Zander came up
with an alternative method that was
less labor-intensive. It did not require
as many physical therapists who
would otherwise be needed for the
treatment. Steam engines were
engaged for many of the so-called
passive movements (Figs. 4, 5, and
6).
Given the many physicians and physical therapists depending on “manual” machines (scientifically and
financially), it took a while before
Zander’s inventions were accepted.
Many feared that their expertise and
work could be replaced with
machines. Within a few years after
the machines had been launched,
critics questioned their effects. Some
physicians were cautious and contended that the treatment had to be
thoroughly evaluated before any reliable assumptions could be made.
Others were much more harsh. The
German physician Georg Hünerfauth
ironically referred to the machines as
“magnificent toys for large chilAugust 2015
dren.”45 Swedish orthopedists even
accused Zander of ruining Ling’s
great science.14(pp261–263),46
In the end, however, the critics
could not prevent Zander from
achieving success, with an epicenter
in Germany. Zander appears frequently as a key figure in German
books on the history of medicine.47–53 The extreme popularity in
Germany can be explained partly by
the mandatory accident insurance
that was imposed on employers in
1884. Through this insurance, rehabilitation and economic concerns
became entangled. The worse the
invalidity caused by a work injury
was, the more costly the insurance
became for the employer. Using
Zander’s machines to treat individuals with chronic or acute musculoskeletal injuries could lower their
economic burden because patient
care did not require a large staff of
physical therapists to provide passive mobilization and 1-on-1 to 5-on-1
care. Zander’s machines could lower
their economic burden. Unlike a
large staff of physical therapists, they
did not need a salary; hence, their
services were more affordable—at
least this seems very likely
(Fig. 7).14(pp258 –262)
It is our belief that Zander’s Nobel
Prize nomination cannot be fully
appreciated if this lively competitive
scientific discourse of mechanical
medicine is not highlighted. This
belief is confirmed with the Nobel
Prize nomination of Zander, written
by Patrik Haglund (1870 –1937),
Sweden’s first professor of orthopedics at the Karolinska Institute and
the main organizer of Sweden’s care
of people with movement disorders
and disabilities. He also was one of
those doctors of gymnastics who
completed a formal examination
from the RCIG, meaning he had the
same mechanical training and competence as a physical therapist.
August 2015
Figure 6.
Bending and stretching the upper arms in Zander’s apparatus. Source: Tekniska Muséet,
Sweden.
Haglund’s support for Zander’s
medico-mechanical machines, as he
wrote in his nomination, was
strongly influenced by the First
World War and the great effect of
restoring the functional abilities of
soldiers who were maimed and
wounded.
Haglund
personally
vouched for this when sharing his
experiences from a trip to Germany
during the summer of 1915. He had
witnessed great qualitative and quantitative progress in the Zander treatment of soldiers with joint, skeletal,
and muscle problems. He stressed
that several surgeons and orthopedists were convinced that no alternative treatment was as effective.54
Haglund also declared that Zander
training would be valuable to a wide
range of patient groups, such as people with overweight, nervousness,
symptoms in the digestive tract, neuralgia, and heart, vascular, and joint
diseases (Fig. 8).
Evaluation of Zander by the
Nobel Prize Committee
The surgeon Jules Åkerman was chosen as reviewer of Zander. Earlier, he
had evaluated primarily surgeons,
such as Victor Horsley in 1911, John
B. Murphy in 1912, and Alexis Carrel
in 1912. In 1912, Åkerman managed
to persuade his peers in the Nobel
Prize committee that Alexis Carrel
should receive the prize because of
his development of a vascular suture.
He had then stressed that the suture
could be of great importance during
wartimes to treat gunshot wounds.
The First World War facilitated the
consideration of various aspects of
how to treat injured soldiers, which
Volume 95
Number 8
Physical Therapy f
1191
Figure 7.
Zander also invented anthropometric devices. Here, we have the “Bålmätningsapparaten” (trunk measuring apparatus) used to monitor the results of scoliosis treatment.
Source: Tekniska Muséet, Sweden.
were brought up in Nobel Prize nominations. Scientists who had developed limb prosthetics were repeatedly nominated, such as the German
surgeon Ferdinand Sauerbruch.6 In
that sense, the Nobel Prize committee’s interest in Zander’s devices was
quite on par and not peculiar.
In his 13-page report, written on
August 19, 1916, Åkerman summarized that Zander would be a worthy
Nobel Prize candidate.55 He put forward several advantages already
highlighted above. Zander’s apparatuses, with their precise calibration
(each machine could be adjusted to
suit each individual’s strength, and
1192
f
Physical Therapy
Volume 95
the machine was targeted at a specific set of muscles), were of paramount significance. They also
reduced the labor force (ie, massage
therapists and physical therapists)
and could handle many patients.
According to Åkerman, the remarkable number of Zander’s machines
was due, to a large extent, to the
German physician Hermann Nebel
(1835–1930). Nebel was one of the
strongest promoters of the machines
in Germany. He was head of Zander
institutes in Hamburg and Frankfurt
and was convinced that the
machines could strengthen muscles
and bring about a better life for each
Number 8
new user. He was also a prolific
writer on the subject.56 –59 The many
German physicians praising Zander
probably gave a silver lining to his
candidacy. Swedish physicians at the
time were strongly influenced by
medical progress in Germany. After
Åkerman had recommended Zander,
the other members of the Nobel
Prize committee requested more
information about him. Patrik
Haglund was called upon to elaborate, and he submitted a more comprehensive background to his nomination. In this written supplement,
Zander’s recognition in Germany
was reinforced. It primarily dealt
with the opinions of German physicians. At the end of the letter (dated
September 21, 1916), Haglund even
gave this a patriotic twist. He stated,
“In contemporary Germany, all manifestations of life breathe Germanism, ‘Deutschtum’ and ‘Deutschland
über alles,’ the Germans have recognized a very important therapeutic
method by a foreigner as superior.
This seems to be the best proof of
what Gustaf Zander has done to benefit mankind.”54 In other words,
there was some chauvinistic flavor to
Zander’s nomination, but not in the
simple form the first impression provided us with.
However, the Nobel Prize candidacy
of Zander had an unexpected turn.
The reason for this sudden turn harbors a good dose of historic irony.
The Nobel Prize became a victim of
World War I. Due to the war, the
Nobel Prize committee chose not to
award the prize to anyone in 1916.
Thereby, Zander’s Nobel Prize case
was closed. As Zander was not nominated in the following years, the
Nobel Prize committee never again
brought him up as a candidate.
By the time Zander died in 1920, the
popularity of his machines had
decreased. The distribution of
Zander’s machines reached its peak
during World War I, but the interest
August 2015
dropped to a minimum a few years
later. The lack of interest in his
machines was probably due to 2
intertwined factors. One factor was
the ongoing advances in medicine
that had opened up new possibilities, such as the scientific progress of
orthopedic surgery, including anesthesia and asepsis/antisepsis procedures. The other was the depression
caused by the war. The high initial
costs of installing a full gym of
machines were no longer affordable
in the bleak economic times. It
would take almost 50 years for the
gym machines to make a comeback,
then in the form of the Nautilus concept, which was invented by Arthur
Jones (1926 –2007). Nowadays, gym
machines can be found in fitness studios everywhere. In terms of their
biomechanical function, they seldom differ from Zander’s machines.
The only thing that strongly separates Zander’s machines from modern gym machines is that they were
primarily intended for people who
were sick and not used for
bodybuilding.
Conclusion
The Nobel Prize was, and still is, not
seen as a reward for a lifetime
achievement. It usually is awarded
for a discovery or an innovation that
has the character of a breakthrough—the establishment of a
new fact or technique that is
intended to open up new ways of
treating patients or understanding
the natural world. It is easy to view
the Nobel Prize as merely an arena
reflecting what we often understand
as hard-core science. But as displayed in this article, excellence in
science and medicine can sometimes
mean something else, especially if
not focusing on the actual laureates.
Thereby, one can better understand
the medical profession and its allied
professions historically: how they
evolved, took different shapes, and
engaged different levels of society.
Gustaf Zander was a candidate
August 2015
Figure 8.
A manual leg curl targeting the hamstring muscles. Source: National Archives, Sweden.
rooted in a tradition “scienticized”
by physical therapists outside the
ranks of physicians. When looking
beyond the realms of the medical
profession
and
contextualizing
Zander’s scientific success historically, a window is opened into a forgotten past of the history of the physical therapy profession.
3 Crawford E, ed. Historical Studies in the
Nobel Archives: The Prizes in Science and
Medicine. Tokyo, Japan; Universal Academy Press; 2002.
4 Norrby E. Nobel Prizes and Nature’s Surprises. Hackensack, NJ: World Scientific
Publishing Co Inc; 2013.
5 Hansson N, Daan S. Politics and physiology: Hermann Rein and the Nobel Prize.
J Physiol. 2014;592:2911–2914.
6 Hansson N, Schagen U. In Stockholm they
apparently had some kind of countermovement: Ferdinand Sauerbruch (18751951) and the Nobel prize. NTM. 2014;22:
133–161.
Both authors provided concept/idea/project
design, writing, and data analysis. Dr Hansson provided data collection, project management, and consultation (including
The authors thank Julia Perry, Göttingen, for
proofreading the manuscript.
7 Hansson N, Packy LM, Halling T, et al.
Vom Nobody zum Nobelpreisträger: Der
Fall Werner Forßmann [article in German]. Urologe A. 2015;54:412– 419.
8 Hansson N, Schlich T. “Highly Qualified
Loser”? Harvey Cushing and the Nobel
Prize. J Neurosurg. 2015 Jan 2 [Epub
ahead of print].
Files on Gustaf Zander in the Nobel Prize
Archive were kindly provided by the Nobel
Prize Committee for Physiology or Medicine,
Medicinska Nobelinstitutet, Nobels Väg 1,
Solna, Sweden.
9 Full text of Alfred Nobel’s will. Available
at:
http://www.nobelprize.org/alfred_
nobel/will/will-full.html. Accessed June
17, 2014.
10 Hansson N, Schlich T. A “life dedicated to
true science”: Eduard Pflüger and the
Nobel Prize for Physiology or Medicine.
Pflugers Arch. 2014;466:2021–2024.
DOI: 10.2522/ptj.20140284
References
1 Liljestrand G. The prize in physiology or
medicine. In: Schück H, et al. Nobel: The
Man and His Prizes. Amsterdam, the
Netherlands: Elsevier; 1962:135–316.
2 Luttenberger F. Excellence and chance:
the Nobel Prize case of E. von Behring and
E. Roux. Hist Philos Life Sci. 1996;18:225–
238.
11 Berger S. Bakterien in Krieg und Frieden:
Eine Geschichte der Medizinischen Bakteriologie in Deutschland 1890-1933.
Göttingen, Germany: Wallstein; 2009.
12 Tröhler U. Theodor Kocher’s Nobelpreis:
Voraussetzungen, Bedingungen, Folgen,
Ein Blick hinter die Kulissen. In: Steinke H,
Wolff E, Schmid RA, eds. Schnitten, Knoten und Netze. 100 Jahre Schweizerische
Gesellschaft für Chirurgie, Zurich, Switzerland: Chronos Verlag; 2013:87–110.
Volume 95
Number 8
Physical Therapy f
1193
13 Levertin A. Dr. G Zander’s Medicomechanische Gymnastik: Ihre Methode,
Bedeutung und Anwendung, Nebst Auszügen aus der Einschlägigen. Stockholm,
Sweden; Literatur; 1882.
14 Ottosson A. Sjukgymnasten–Vart tog han
Vägen? En Undersökning av Sjukgymnastyrkets
Maskulinisering
och
Avmaskulinisering 1813-1934 [doctoral
thesis]. Göteborg, Sweden: University of
Gothenburg; 2005.
15 Bakewell S. Illustrations from the Wellcome Institute Library: medical gymnastics and the Cyriax collection. Med Hist.
1997;41:487– 495.
16 Ahlback T. Theosophy and socialism in
Finland: an unsuccessful coup d’etat at the
beginning of the century. Temenos. 1985;
21:39 –54.
17 Zander E. Doktor Gustaf Zander: Samlade Medicinska Skrifter och Lefnadsteckning. Stockholm, Sweden: MedikoMekanista Institut; 1915.
18 Ottosson A. Gymnastik som Medicin:
Berättelsen om en Svensk Exportsuccé.
Stockholm, Sweden: Bokförlaget Atlantis;
2013.
19 Verbrugge MH. Able-Bodied Womanhood: Personal Health and Social Change
in Nineteenth-Century Boston. New
York, NY: Oxford University Press; 1988.
20 Roberta J, Park J. Biological thought, athletics and the formation of a “man-character”: 1830-1900. IJHS. 2007;24:1543–
1569.
21 Remley RM. An ever-widening circle: the
expansion of Swedish gymnastics through
teacher training. In: 8th International
Congress for the History of Sport and
Physical Education; Uppsala, Sweden;
1979. 1979:220 –227.
22 Ottosson A. The manipulated history of
manipulations of spines and joints?
Rethinking orthopaedic medicine through
the 19th century discourse of European
mechanical medicine. Med Stud. 2011;3:
83–116.
23 Kellogg JH. The Art of Massage: Its Physiological and Therapeutic Applications.
Battle Creek, MI: Modern Medicine Publishing Co; 1895.
24 Graham D. A Treatise on Massage, Theoretical and Practical: Its History, Mode of
Application and Effects, Indications and
Contra Indication. New York, NY: JH Vail
& Co; 1890.
25 Hartelius TJ. Swedish Movements or Medical Gymnastics. Battle Creek, MI: Modern
Medicine Publishing Co; 1896.
26 Lindroth J. Ling—Från Storhet till Upplösning: Studier i Svenk Gymnastikhistoria.
Stockholm, Sweden: Symposion; 2005:
52–55.
27 Thomas T. Roots of physical medicine,
physical therapy, and mechanotherapy in
the Netherlands in the 19th century: a disputed area within the healthcare domain.
J Man Manip Ther. 2007;15:23– 41.
1194
f
Physical Therapy
Volume 95
28 Metzger J. De Behandeling van Distorsio
Pedis met Frictes. Amsterdam, the Netherlands: 1868:28.
29 Schreber DG. Moritz, Kinesiatrik oder die
Gymnastische Heilmethode: Für Ärzte
und Gebildete Nichtärtze nach Eigenen
Erfahrungen
Dargestellt.
Leipzig,
Germany: Friedrich Fleischer; 1852.
30 Calvert RN. The History of Massage: An
Illustrated Survey From Around the
World. Rochester, VT: Healing Arts Press;
2002:80 –147.
31 de Betou IGI. Therapeutic Manipulation:
Or a Successful Treatment of Various Disorders of the Human Body by Mechanical Applications. London, United Kingdom: Simpkin, Marshall & Co; 1842.
32 Erenhoff CC. Medicina Gymnastics or
Therapeutic Manipulation: A Short Treatise on This Science as Practiced at the
Royal Institution at Stockholm. London,
United Kingdom: J. Masters; 1845.
33 Georgii A. Kinésiethérapie ou Traitements des Maladies par le Mouvement,
Selon la Méthod de Ling, Suivi d’un
Abrégé des Applications de la Théorie de
Ling à l’Éducation Physique. Paris,
France: Germer Baillière; 1847.
34 Neumann JA. Die Heil-Gymnastik oder
die Kunst der Leibesübungen, Angewandt zur Heilung von Krankheiten
nach dem Systeme des Schweden Ling
und Seiner Schüler Branting, Georgii, de
Ron, Sowie nach Eigenen Ansichten und
Erfahrungen. Berlin, Germany: Jeanrenaud; 1852.
35 Linker B. Strength and science: gender,
physiotherapy, and medicine in earlytwentieth-century America. J Womens
Hist. 2005;17:107–109.
36 Linker B. War’s Waste: Rehabilitation in
World War I America. Chicago, IL: University of Chicago Press; 2011:61–72.
37 Heap R. Training women for a new women’s profession: physiotherapy education
at the University of Toronto, 1917-40. Hist
Educ Quart. 1995;35:135–158.
38 Barrows CI. Physical Training: A Full
Report of the Papers and Discussions of
the Conference Held in Boston in November 1889. Boston, MA: Press of George H.
Ellis; 1890:61.
39 Park RJ. Edward M. Hartwell and physical
training at the Johns Hopkins University,
1879-1890. J Sport Hist. 1987;14:108 –119.
40 Howell RA. Baron Nils Posse: the “father”
of Swedish gymnastics in the United
States. In: 8th International Congress for
the History of Sport and Physical Education; Uppsala, Sweden; 1979. 1979:209 –
219.
41 Swisher LL, Page CG. Professionalism in
Physical Therapy: History, Practice &
Development. St Louis, MO: Saunders;
2005:32.
42 McMillan M. Massage and Therapeutic
Exercise. Philadelphia, PA: WB Saunders
Co: 1921:209.
Number 8
43 Gritzer G, Arluke A. The Making of Rehabilitation: A Political Economy of Medical Specialization, 1890-1980. Berkeley,
CA: University of California Press; 1985.
44 Kreck HC. Die Medico-Mechanische
Therapie Gustaf Zanders in Deutschland:
Ein Beitrag zur Geschichte der Krankengymnastik [dissertation]. Frankfurt,
Germany: Orthopadische Universitatsklinik Friedrichsheim, Johann Wolfgang
Goethe-Universitat Frankfurt am Main;
1987:74.
45 Hünerfauth G. Handbuch der Massage:
Für Studierende und Aertze. Leipzig, Germany: Vogel; 1887.
46 Zander G. Några ord till Belysning af Frågan om de Tvänne Olika Behandlingsmetoderna, den Manuella och den
Mekaniska. Stockholm, Sweden: Nya
Dagligt Allehanda Tryckeri; 1872.
47 Neuburger M, Pagel J. Handbuch der
Geschichte der Medizin: Band III. Jena,
Germany: Gustav Fischer Verlag; 1905:
124, 339, 351–353.
48 Sudhoff K. Geschichte der Medizin. Berlin, Germany: Verlag von S. Karger; 1922:
434.
49 Diepgen P. Geschichte der Medizin. Berlin/Leipzig, Germany: Springer; 1928:75.
50 Fischer I, ed. Biographisches Lexikon der
Hervorragenden Ärzte der Letzten Fünfzig Jahre. München/Berlin, Germany:
Urban & Schwarzenberger; 1932:1717.
51 Mayrhofer B. Wörterbuch zur Geschichte
der Medizin. Jena, Germany: Verlag von
Gustav Fischer; 1937:223.
52 Ackerknecht EH. Geschichte der Medizin:
Kurze Geschichte der Medizin. Stuttgart,
Germany: Ferdinand Enke Verlag; 1959:
160.
53 Ackerknecht EH. Geschichte der Medizin,
3: Überbearbeitete Auflage von Kurze
Geschichte der Medizin. Stuttgart,
Germany: Ferdinand Enke Verlag; 1977:
172.
54 Nobel Prize Archive for Physiology or
Medicine, P. Haglund 1916 (nomination
Zander).
55 Nobel Prize Archive for Physiology or
Medicine, J. Åkerman 1916 (evaluation
Zander).
56 Nebel H. Über Heilgymnastik und Massage. Wiesbaden, Germany: J.F. Bergmann; 1886.
57 Nebel H. Beiträge zur Mechanischen
Behandlung: Mit Besonderer Berücksichtigung der Schwedischen Heilgymnastik Speciell der Mechanischen Gymnastik
des Dr. Gust. Zander. Wiesbaden,
Germany: J.F. Bergmann; 1888.
58 Nebel H. Bewegungskuren Mittelst
Schwedischer Heilgymnastik und Massage: Mit Besonderer Berücksichtigung
der Mechanischen Behandlung des Dr. G.
Zander. Wiesbaden, Germany: J.F. Bergmann; 1889.
59 Nebel H. Die Behandlung Mittelst Bewegungen und Massage: Ihre Bedeutung,
Handhabung und Indikationen. Wiesbaden, Germany: J.F. Bergmann; 1891.
August 2015
Who said you can’t take PTJ with you?
PTJ Mobile @ m.ptjournal.apta.org
PTJ Mobile, a streamlined version of PTJ Online,
is compatible with most smartphones and tablet
devices. The mobile site includes all the essential
features you have come to expect from PTJ Online,
such as:
•
Access to full-text and PDF articles from
January 1999 to the present
•
Access to PTJ’s archive from January 1980
through December 1998 in PDF
•
Accepted manuscripts published ahead of
print at Online First
•
Figure/table-only views
•
Keyword, title, and author search capabilities
•
Fully linked reference lists
•
PTJ’s podcasts
•
Ability to manage your alert settings to receive
the monthly e-Table of Contents, citation
alerts, and notiﬁcations when Online First
articles are posted
Scholarships,
Fellowships, and Grants
News from the Foundation for Physical Therapy
Recent Publications by
Foundation Alumni
“Bone Is Not Alone: The Effects of
Skeletal Muscle Dysfunction in
Chronic Kidney Disease,” by Avin
KG and Moorthi RN, was published
in Current Osteoporosis Reports
(2015;13:173–179). Keith G. Avin,
PT, PhD, was awarded a Florence
P. Kendall Doctoral Scholarship in
2008, a Promotion of Doctoral Studies (PODS) I scholarship in 2009, and
a PODS II scholarship in 2010.
“In-Field Gait Retraining and Mobile
Monitoring to Address Running Biomechanics Associated With Tibial
Stress Fracture,” by Willy RW,
Buchenic L, Rogacki K, Ackerman J,
Schmidt A, and Willson JD, was published online in the Scandinavian
Journal of Medicine & Science in
Sports on February 4, 2015. Richard
W. Willy, PT, PhD, OCS, was
awarded PODS I scholarships in
2008 and 2009 and a PODS II scholarship in 2010. John D. Willson, PT,
PhD, was awarded PODS I scholarships in 2004 and 2005 and a PODS
II scholarship in 2006.
“What Is the Relationship Between
Depressive Symptoms and Pain During Functional Tasks in Persons
Undergoing TKA? A 6-Year Perioperative Cohort Study,” by Riddle
DL, Perera RA, Nay WT, and
Dumenci L, was published online in
Clinical Orthopaedics and Related
Research on February 21, 2015.
Daniel L. Riddle, PT, PhD, FAPTA,
was awarded a Doctoral Training
Research Grant in 1990.
Congratulations to PODS and
NIFTI Recipients
As part of its postprofessional Doctoral Opportunities for Clinicians
and Scholarships (DOCS) program to
fund the most highly qualified doc-
August 2015
toral and postdoctoral students preparing for research careers, the
Foundation awards PODS I scholarships of $7,500 each year to physical
therapists or physical therapist assistants who have completed at least 2
full semesters or 3 full quarters of
their coursework toward a postprofessional doctoral degree. PODS II
scholarships of up to $15,000 each
are awarded to physical therapists or
physical therapist assistants who
have been formally admitted to
postprofessional doctoral candidacy.
These scholarships are funded by the
American Physical Therapy Association (APTA) Fund, the Neurology
Endowment Fund, and the Center of
Excellence/Health Services Research
(COE/HSR) Fund.
Congratulations to the 2015 PODS
I scholarship recipients: Amelia
Arundale, PT, DPT, University of Delaware; Daniel Bittel, PT, DPT, Washington University in St Louis; Jason
Falvey, PT, DPT, GCS, CEEAA, University of Colorado, Denver; Timothy Faw, PT, DPT, NCS, The Ohio
State University; Abbigail Fietzer, PT,
DPT, University of Southern California; Allison Kosir, PT, DPT, University of Colorado, Denver; and Trevor
Lentz, PT, University of Florida.
Timothy Faw, PT, DPT, NCS, The
Ohio State University, is the recipient of the 2015 Patricia Leahy Award
for his outstanding application in
postprofessional studies within neurology. This award is given in memory of Patricia Leahy, PT, MS, NCS,
an APTA Section on Neurology member, an accomplished physical therapist, and a Foundation Doctoral
Training Research Grant recipient.
Leahy was a professor at the University of the Sciences in Philadelphia
and was one of the first physical therapists ever to receive the Neurologic
Certified Specialist certification. This
scholarship is generously supported
by members of the Neurology Section through the Foundation’s Neurology Endowment Fund.
Trevor Lentz, PT, DPT, University of
Florida, has been named as the
recipient of the Miami-Marquette
Challenge Award for exceptional
achievement within a PODS application. This award was made possible
by the 2014 –2015 Miami-Marquette
Challenge. The Challenge is the signature annual fundraising initiative
of the Foundation, raising more
funds each year than any other Foundation activity. The Challenge is
coordinated and carried out by physical therapist and physical therapist
assistant students across the country.
Students organize grassroots fundraisers on their campuses and in
their local communities that raise
awareness for and benefit the Foundation for Physical Therapy. Since its
inception, the Challenge has raised
more than $3 million and has specifically funded more than 20 research
grants and scholarships.
The 2015 PODS II Scholarship recipients are: Allyn Bove, PT, DPT, University of Pittsburgh; Kendra CherryAllen,
PT,
DPT,
Washington
University in St Louis; Andrew Kittelson, PT, DPT, University of Colorado, Denver; Rebekah Lawrence,
PT, DPT, OCS, University of Minnesota; Philip Malloy, PT, MS, Marquette University; Jacqueline Palmer,
PT, DPT, University of Delaware; and
Andrew Smith, PT, DPT, Northwestern University.
Andrew Smith, PT, DPT, Northwestern University, is the recipient of the
2014 Mary Lou Barnes Award for his
outstanding PODS II application in
postprofessional studies within neurology. This award is given in honor
of Mary Lou Barnes, PT, FAPTA, an
Volume 95
Number 8
Physical Therapy f
1197
Scholarships, Fellowships, and Grants
APTA Section on Neurology member
and an accomplished physical therapist. Barnes was the founding director of the West Virginia University
physical therapy program and served
as chair of Georgia State University’s
program. During her terms, both
programs achieved national recognition. Members of the Neurology Section provided generous support for
this award through the Foundation’s
Neurology Endowment Fund.
Kendra Cherry-Allen, PT, DPT, Washington University in St Louis, has
been named the Viva J. Erickson
Award recipient for exceptional academic and leadership achievement
within a PODS II application. The
award is given in honor of Viva J.
Erickson, PT, an accomplished physical therapist and leader in APTA.
The $78,000 New Investigator Fellowship Training Initiative (NIFTI)
was awarded to Amee Seitz, MS, PT,
DPT, PhD, OCS, of Northwestern
University. Her fellowship will
include a research training experience entitled “Mechanisms of Painful
Rotator Cuff Tears: Establishing
Scientifically-Based Treatment.” She
will be mentored by Jules Dewald,
PT, PhD, Director of the Neuroimaging and Motor Control Laboratory in
the Department of Physical Therapy
and Human Movement Science at
the Northwestern University Feinberg School of Medicine, and by Ana
Maria Acosta, PhD, an Associate Professor in the Department of Physical
Therapy and Human Movement Sciences at Northwestern University.
This award is supported through the
APTA Supporting the Profession
Fund and the APTA Fund.
1198
f
Physical Therapy
Volume 95
The NIFTI supports postprofessional, doctorally prepared physical
therapists as they begin their
research careers. It is designed to
accommodate both traditional postdoctoral and new faculty applicants
for a closely mentored research
experience.
Alumni Shout-Outs
Foundation alumnus Timothy Faw,
PT, DPT, NCS (2013 Kendall Scholarship, 2014 PODS I), was recently
elected to serve on the APTA Neurology Section’s Spinal Cord Injury
Special Interest Group (SIG) Nominating Committee, and alumna Alexandra Borstad, PT, PhD, NCS (2009
PODS I), was elected to the section’s
Stroke SIG Nominating Committee.
Foundation alumna Bernadette Gillick, PT, MSPT, PhD (2009, 2010
PODS II, 2014 Magistro Grant), was
recently interviewed on PBS NewsHour for a segment on noninvasive
brain stimulation. Watch the full
video at https://www.youtube.com/
watch?v⫽yoEu2mEdLjw.
Foundation alumna Amy Bastian, PT,
PhD (1995, 1994 Doctoral Training
Research Grant), was recently
named as the first Chief Science Officer of the Kennedy Krieger Institute.
Sarah Gilliland, PT, DPT, PhD, CSCS
(2011, 2012 PODS I, 2014 PODS II)
successfully defended her dissertation and graduated from University
of California, Irvine in July. She will
begin a tenure-track position at
Chapman University this summer.
defended her dissertation and graduated from Northwestern University.
She began a postdoctoral fellowship
with fellow Foundation alumna Amy
Bastian, PT, PhD, at Johns Hopkins
University.
Share Your News and
Announcements with the
Foundation
To have your information posted in
the Foundation’s section of Physical
Therapy, please email Rachael
Crockett
at
RachaelCrockett@
foundation4pt.org.
Stay Connected with the
Foundation in Four Easy
Ways:
1. www.facebook.com/
foundation4PT
2. Visit our Web site:
Foundation4PT.org
3. Follow us on Twitter:
twitter.com/Foundation4pt
4. Receive the monthly newsletter for updates on donors,
Foundation Alumni, events,
and much more! Email
RachaelCrockett@foundation
4pt.org to subscribe.
[DOI: 10.2522/ptj.2015.95.8.1197]
Kristan Leech, PT, DPT, PhD (2010
Kendall Scholarship, 2012 PODS I,
2013, 2014 PODS II), successfully
Number 8
August 2015
Product
Highlights
August 2015
Volume 95
Number 8
Physical Therapy f
1199
Product Highlights
Ad Index
MedChex.......................................................Cover 2
Parker Laboratories ........................................Cover 4
Raintree Systems ................................................1077
ReDoc ............................................................Cover 3
APTA Products and Services
Electrotherapeutic Terminology in Physical
Therapy ...........................................................1077
First Hand Student Kits.......................................1196
PTJ Mobile .........................................................1195
Request FREE Product Information on products advertised in PTJ.
Go to APTA’s online resource at: http://www.apta.org/freeproductinfo
1200
f
Physical Therapy
Volume 95
Number 8
August 2015

Complete August Issue - Physical Therapy Journal

Transcription

Similar documents

A Randomized Controlled Trial on Rehabilitaºon through Caregiver

Wholesale Nurseries Australia

Grand Rapids Children`s Museum When

What is Stroke Handout - American Stroke Association

Brochure AP-810-AH-T

Eastern NC Stroke Network Meeting

Worship Leader Robert Smtih # 993 What A Mighty God We Serve

W-12 view

02 - Descriptive Statistics

Sound Pads