Physical Therapy- Journal of the APTA- October 2009, Volume 89, Issue 10

October 2009 Volume 89 Number 10 Research Reports 1016 Stretch Exercises in Patients With Chronic Musculoskeletal Pa...

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October 2009

Volume 89

Number 10

Research Reports 1016

Stretch Exercises in Patients With Chronic Musculoskeletal Pain

1072

Muscle Deficits and Mobility After Knee Replacement

1027

Movement Training in Infants Born Preterm

1080

1039

Information Seeking by Physical Therapists Providing Stroke Management

Aging and Attentional Demands of Stair Ambulation

1089

Physical Fitness in Children With High and Low Motor Competence

1051

Hand Cycle Training in Tetraplegia

1061

Step Test Performance and Measures of Activity and Participation After Stroke

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Get Hooked. For Thousands of Reasons! More than 5,300 extractions of research articles related to the effectiveness of physical therapy intervention are available through Hooked on Evidence. APTA members can search the database on our Web site at www.hookedonevidence.org. Members also can help the database grow and earn CEUs by entering an extraction. Please see the Web site for further information.

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Next month—in PTJ or online at ptjournal.org • CIMT in Children With Cerebral Palsy

• 40th Mary McMillan Lecture ecture

• Intensive, Progressive Exercise Program for Patients After Single-Level Lumbar Microdiskectomy

• 2009 APTA Presidential Address • And much more!

• Physical Therapists’ Management of Patients in the Acute Care Setting • Predicting Performance on the Licensure Examination • A Conceptual Model of Optimal International ServiceLearning • EMG Activity During Step-up Exercises in Older Adults • Supported Treadmill Stepping and Walking Attainment in Preterm and Full-Term Infants

“Just had to RAVE about PTJ Online! I received the email ToC alert, and clicked on the article I wanted. Not only could I cut and paste the references for an upcoming talk, but with a click of the mouse I was transported to the FREE FULL TEXT of these reference articles. Magic! I also listened to 2 podcasts while I was making dinner!“

• Use of the Patient Goal Priority Questionnaire in People With Persistent Musculoskeletal Pain

--Janet Peterson, PT, DPT, MA

Visit ptjournal.org for enhanced features, including articles published ahead of print! Physical Therapy (PTJ)—APTA’s peer-reviewed scholarly journal

0, 19 2. ll 1 f ro fa d# to o n py ac p 5 ls a era f ct to rna th e pa the jou cal wid m i in n ysi ld ) an is tio ph or ing ti h PTJ ilita all ls w nk b g a ra W ha n rn R re amo jou (JC

The Bottom Line The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only. On “Step Test Scores Are Related to Measures of Activity and Participation in the First 6 Months After Stroke” What problems did the researchers set out to study, and why? The Step Test (ST) measures the maximal number of times the foot can be placed onto a 7.5-cm step and returned to the floor in a 15-second interval. In people with stroke and hemiparesis, the ST assesses the ability to use the paretic lower extremity for stepping or for single-limb standing balance. In this study, researchers wanted to determine whether ST scores are related to other well-established measures of activity limitations and participation restrictions in people with stroke and whether these relationships change over the first 6 months following stroke. Gait speed and the Physical Function Index (PFI) of the Medical Outcomes Study 36-Item Short-Form Health Survey were used as function-level measures of activity and participation. Three components of the Stroke Impact Scale (SIS) were used as disability-level measures of activity and participation. Who participated in this study? Thirty-three individuals with stroke were enrolled, out of 78 screened for eligibility. To enroll, participants were required to have an acute unilateral stroke with some lower-extremity motor impairment (score ≤28 on the lower-extremity Fugl-Meyer assessment), be medically stable and without serious cardiovascular or musculoskeletal problems, be able to follow a 3-step command, be able to reach in all directions with the nonparetic hand in unsupported sitting, be able to see and hear adequately to follow testing instructions, be able to read and understand English, and live within 80 km of the testing site. Participants were excluded if they had involvement of the cerebellum or a history of prior stroke or another neurological diagnosis; were unable to ambulate or live independently prior to the stroke; or had a terminal illness, any pain, or reduced motion or weakness in the nonparetic leg. What new information does this study offer? ST scores are related to both function-level and disability-level measures of activity and participation, but the relationships with functional measures appear stronger overall. Specifically, ST scores were positively correlated with both gait speed and PFI scores at all time points, and gait speed was more closely related than PFI scores. ST scores were also positively correlated with the mobility, activities of daily living (ADL)/instrumental activities of daily living (IADL), and participation domains of the SIS. The mobility and ADL/ IADL domains were related at all 3 time points measured; the participation domain was related at 2 time points (baseline and 3 months). What new information does this study offer for patients? Stepping performance measured by ST scores from either the paretic or nonparetic leg is related to performance of important functional skills such as walking. How did the researchers go about the study? Participants were first tested at a hospital facility between initial admission and 1 month post-stroke. Subsequent laboratory testing was done at monthly intervals up to 6 months post-stroke. Outcome

October 2009

For more Bottom Lines on articles in this and other issues, visit www. ptjournal.org.

Volume 89 Number 10 Physical Therapy ■ 1013

The Bottom Line measures were ST scores; gait speed; PFI scores; and SIS mobility, ADL/IADL, and performance scores. ST scores were calculated for paretic leg stepping, nonparetic leg stepping, and the sum of both legs stepping. Gait speed was measured during a 10-m walk. PFI and SIS measures were obtained through personal interview. ST, gait speed, and PFI scores were recorded at each month. SIS scores were recorded at baseline, 3 months, and 6 months only. To determine the relationships among variables, the researchers measured the strength of the linear correlations between each of the variables across all available time points. How might these results be applied to physical therapist practice? The consistent correlation between ST scores and activity and participation measures across multiple time periods of recovery from stroke suggests that the ST may aid physical therapists in clinical decision making. What are the limitations of the study, and what further research is needed? The study used a relatively small sample size, given the large number of statistical comparisons made. Examiners were not blinded with regard to subject characteristics or test performance on previous visits, but avoided access to this information when possible. Future studies should expand this work to include testing of individuals with multiple brain lesions or significant pre-existing conditions, to determine the ability of ST scores to accurately predict outcomes in the chronic state. Susanne M. Morton S.M. Morton, PT, PhD, is Assistant Professor, Graduate Program in Physical Therapy & Rehabilitation Science, Carver College of Medicine, The University of Iowa. This is the Bottom Line for: Stemmons Mercer V, Freburger JK, Chang S, Purser JL. Step Test Scores Are Related to Measures of Activity and Participation in the First 6 Months After Stroke. Phys Ther. 2009;89:1061–1071.

On “Effects of Hand Cycle Training on Physical Capacity in Individuals With Tetraplegia: A Clinical Trial” What problems did the researchers set out to study, and why? Physical activity is important for individuals with tetraplegia, and hand cycling is often used as a form of mobility. Little evidence exists that speaks to the effectiveness of hand cycling as a mode of exercise for this population. The goal of this research was to examine changes in exercise capacity in a group of individuals with tetraplegia who were completing a hand cycling program. Who participated in this study? Twenty-two individuals with tetraplegia (American Spinal Injury Association Impairment Scale classification A–D) for at least 2 years served as participants. They had motor incomplete C5–C8 lesions and had no upper-extremity overuse injuries or secondary health problems. What new information does this study offer? Participants in this study were able to improve their physical capacity while engaged in an interval-based program of hand cycle training, without significant shoulder-arm pain or discomfort.

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October 2009

The Bottom Line What new information does this study offer for patients? This study demonstrates that hand cycling is a feasible form of exercise training for individuals with tetraplegia. This exercise was associated with an increase in exercise capacity and did not produce negative effects in the shoulder and arms during the exercise training. Patients with tetraplegia may want to explore hand cycling as a form of exercise in their pursuit to maximize physical fitness. How did the researchers go about the study? The participants completed a training program over 8 to 12 weeks and about 24 sessions. The training sessions were 35 to 45 minutes in length, were performed at 60% to 80% of heart rate reserve, and were interval-based. The subjects were evaluated before and after the training for peak power output and peak oxygen uptake during a hand cycling test. Secondary outcomes consisted of muscle strength, respiratory function, and shoulder-arm pain. Participants were routinely monitored for signs of autonomic dysreflexia. How might these results be applied to physical therapist practice? The results from this study support the feasibility of using interval-based hand cycle training for individuals with tetraplegia; however, careful attention to the health status of the participants is warranted. What are the limitations of the study, and what further research is needed? This study was limited by a high dropout rate and poor adherence to the exercise program, due in part to a high incidence of urinary tract infections, bowel problems, and pressure sores. Although there were no reports of shoulder-arm pain during training, there was no long-term follow-up. Future research should focus on optimizing hand cycling training protocols and methods to improve adherence to and tolerance of the exercise programs. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Texas State University, San Marcos, Texas. This is the Bottom Line for: Valent LJM, Dallmeijer AJ, Houdijk H, Slootman HJ, Janssen TW, Post MWM, van der Woude LH. Effects of Hand Cycle Training on Physical Capacity in Individuals With Tetraplegia: A Clinical Trial. Phys Ther. 2009;89:1051–1060.

October 2009


Physical Therapy Journal of the American Physical Therapy Association

Editorial Office

Editor in Chief

Managing Editor / Associate Director of Publications: Jan P. Reynolds, [email protected]

Rebecca L. Craik, PT, PhD, FAPTA, Philadelphia, PA [email protected]

PTJ Online Editor / Assistant Managing Editor: Steven Glaros

Deputy Editor in Chief

Associate Editor: Stephen Brooks, ELS Production Manager: Liz Haberkorn Manuscripts Coordinator: Karen Darley Permissions / Reprint Coordinator: Michele Tillson Advertising Manager: Julie Hilgenberg Director of Publications: Lois Douthitt

APTA Executive Staff Senior Vice President for Communications: Felicity Feather Clancy Chief Financial Officer: Rob Batarla Chief Executive Officer: John D. Barnes

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: R. Scott Ward, PT, PhD Vice President: Paul A. Rockar Jr, PT, DPT, MS Secretary: Babette S. Sanders, PT, MS Treasurer: Connie D. Hauser, PT, DPT, ATC Speaker of the House: Shawne E. Soper, PT, DPT, MBA Vice Speaker of the House: Laurita M. Hack, PT, DPT, MBA, PhD, FAPTA Directors: Sharon L. Dunn, PT, PhD, OCS; Kevin L. Hulsey, PT, DPT, MA; Dianne V. Jewell, PT, DPT, PhD, CCS, FAACVPR; Aimee B. Klein, PT, DPT, DSc, OCS; Kathleen K. Mairella, PT, DPT, MA; Stephen C.F. McDavitt, PT, DPT, MS, FAAOMPT; Lisa K. Saladin, PT, PhD; Mary C. Sinnott, PT, DPT, MEd; Nicole L. Stout, PT, MPT, CLT-LANA

Daniel L. Riddle, PT, PhD, FAPTA, Richmond, VA

Editor in Chief Emeritus Jules M. Rothstein, PT, PhD, FAPTA (1947–2005)

Steering Committee Anthony Delitto, PT, PhD, FAPTA (Chair), Pittsburgh, PA; J. Haxby Abbott, PhD, MScPT, DipGrad, FNZCP, Dunedin, New Zealand; Joanell Bohmert, PT, MS, Mahtomedi, MN; Alan M. Jette, PT, PhD, FAPTA, Boston, MA; Charles Magistro, PT, FAPTA, Claremont, CA; Ruth B. Purtilo, PT, PhD, FAPTA, Boston, MA; Julie Whitman, PT, DSc, OCS, Westminster, CO

Editorial Board Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia; W. Todd Cade, PT, PhD, St. Louis, MO; James Carey, PT, PhD, Minneapolis, MN; John Childs, PT, PhD, Schertz, TX; Charles Ciccone, PT, PhD, FAPTA (Continuing Education), Ithaca, NY; Joshua Cleland, PT, DPT, PhD, OCS, FAAOMPT, Concord, NH; Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; G. Kelley Fitzgerald, PT, PhD, OCS, FAPTA, Pittsburgh, PA; James C. (Cole) Galloway, PT, PhD, Newark, DE; Steven Z. George, PT, PhD, Gainesville, FL; Kathleen Gill-Body, PT, DPT, NCS, Boston, MA; Paul J.M. Helders, PT, PhD, PCS, Utrecht, The Netherlands; Maura D. Iversen, PT, ScD, MPH, Boston, MA; Diane U. Jette, PT, DSc, Burlington, VT; Christopher Maher, PT, PhD, Lidcombe, NSW, Australia; Christopher J. Main, PhD, FBPsS, Keele, United Kingdom; Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA; Patricia Ohtake, PT, PhD, Buffalo, NY; Carolynn Patten, PT, PhD, Gainesville, FL; Linda Resnik, PT, PhD, OCS, Providence, RI; Val Robertson, PT, PhD, Copacabana, NSW, Australia; Patty Solomon, PT, PhD, Hamilton, Ont, Canada

Statistical Consultants Steven E. Hanna, PhD, Hamilton, Ont, Canada; John E. Hewett, PhD, Columbia, MO; Hang Lee, PhD, Boston, MA; Xiangrong Kong, PhD, Baltimore, MD; Paul Stratford, PT, MSc, Hamilton, Ont, Canada; Samuel Wu, PhD, Gainesville, FL

The Bottom Line Committee Eric Robertson, PT, DPT, OCS; Joanell Bohmert, PT, MS; Lara Boyd, PT, PhD; James Cavanaugh IV, PT, PhD, NCS; Todd Davenport, PT, DPT, OCS; Ann Dennison, PT, DPT, OCS; William Egan, PT, DPT, OCS; Helen Host, PT, PhD; Evan Johnson, PT, DPT, MS, OCS, MTC; M. Kathleen Kelly, PT, PhD; Catherine Lang, PT, PhD; Tara Jo Manal, PT, MPT, OCS, SCS; Kristin Parlman, PT, DPT, NCS; Susan Perry, PT, DPT, NCS; Maj Nicole H. Raney, PT, DSc, OCS, FAAOMPT; Rick Ritter, PT; Kathleen Rockefeller, PT, MPH, ScD; Michael Ross, PT, DHS, OCS; Katherine Sullivan, PT, PhD; Mary Thigpen, PT, PhD; Jamie Tomlinson, PT, MS; Brian Tovin, DPT, MMSc, SCS, ATC, FAAOMPT; Nancy White, PT, MS, OCS; Julie Whitman, PT, DSc, OCS

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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)— $99; individual (outside USA)—$119 surface mail, $179 air mail. Institutional (inside USA)—$129; institutional (outside USA)—$149 surface mail, $209 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; with the exception of January 2001: $50 USA, $70 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: Membership 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 Membership 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.

Readers are invited to submit manuscripts to PTJ. PTJ’s content—including editorials, commentaries, letters, and book reviews—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.

Full-text articles are available for free at www.ptjournal.org 12 months after the publication date. Full text also is provided through DataStar, Dialog, EBSCOHost Academic Search, Factiva, InfoTrac, ProFound, and ProQuest.

Reprints

PTJ Online at www.ptjournal.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

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 www.ptjournal.org/misc/terms.dtl.

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PTJ is indexed and/or abstracted by Abridged Index Medicus, Abstracts of Health Care Management Studies, AgeLine, AMED (Allied and Complementary Medicine Database), Bibliography of Developmental Medicine and Child Neurology, Current Contents, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE/Exerpta Medica, Exceptional Child Education Resources, Focus on: Sports Science and Medicine, General Science Index (GSI), Health Index, Hospital and Health Administration Index, Index Medicus, Inpharma Weekly, International Nursing Index, ISR, Medical & Surgical Dermatology, MEDLINE, Neuroscience Citation Index, Personal Alert: Automatic Subject Citation Alert (ASCA), Pharmacoeconomics and Outcomes News, Physical Education Index, Reactions Weekly, RECAL Bibliographic Database, Science Citation Index (SCI), Social Sciences Citation Index (SSCI), and SportsS. Article abstracts are available online at www.ptjournal.org (1980 through present) and via DataStar, Dialog, FirstSearch, Information Access, Ovid

October 2009

Technologies. Ingenta provides online document delivery for articles published since September 1988.

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.


Editorial Above Board: Clear Bylaws Support the Research Mission of the Foundation for Physical Therapy Note from the Editor in Chief: The Foundation for Physical Therapy (FPT) has helped to launch the research careers and support the established research activities of many PTJ authors. But there was another reason that I asked Dr Shields to discuss the recent changes in the relationship between FPT and APTA. I believe that this information is relevant to all of our readers—national and international, physical therapist and non–physical therapist, researcher and non-researcher. The experience of FPT and APTA serves as a “case report” to illustrate the importance of knowing the rules, clarifying roles, and preventing conflict of interest when entering into agreements as individuals or as organizations. This case is relevant to those of you who sit on the board of an entity with taxexempt status, to scientists who seek research funding from an upstanding private foundation, and to donors who expect “above board” behavior. —RLC

To comment, submit a Rapid Response to this editorial posted online at www.ptjournal.org.

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I

n 2002, the Sarbanes-Oxley Act (SOX) (Pub.L. 107-204, 116 Stat 745) was passed in direct response to a number of high-profile cases of accounting improprieties in major corporations.1 Governing boards were not being informed of key financial decisions that affected their companies. The goal of SOX was to codify board, governance, management, and auditor responsibilities to assure accountability to the stakeholders of these major corporations. Since 2002, many organizations have adopted SOX guidelines through bylaws that clarify the legal expectations of governing boards. In addition, in 2008, the US Internal Revenue Service (IRS) made significant changes to Form 990, which is required for organizations that receive tax-exempt status.2 IRS officials have repeatedly expressed the belief that the existence of an independent governing board, combined with well-crafted governance bylaws, increases the likelihood that an organization will act in a tax-compliant manner.3 In consideration of both of these imperatives, the APTA Board of Directors and the Foundation for Physical Therapy (FPT) Board of Trustees agreed to proactively clarify the governance of FPT. Both APTA and FPT leadership recognized the fact that the tax-exempt status bestowed on charitable research organizations such as FPT—classified as a 501(c)(3)—comes with the expectation that the organization’s board is accountable and transparent and has direct oversight in governing the organization’s operations. In addition, as a tax-exempt organization, FPT has several restrictions related to advocacy, membership, and services. The services received as a part of membership dues to APTA are quite different from any deliverables from a donation made to a charitable research foundation. For these reasons, a clear distance between political ends of a membership organization and goals of a research foundation is healthy for a profession. The APTA and FPT leadership have an excellent relationship grounded by a mutual respect for each organization’s shared mission, and both organizations embraced the need to develop new bylaws. Representatives from both APTA and FPT met for several months to improve the clarity of the bylaws, to recognize the FPT’s independent nature, and to promote sound and transparent governance for the future. Approved by the APTA Board at the June 2009 annual meeting, the new bylaws clearly communicate the healthy and collaborative but independent nature that supports a philosophical partnership between the 2 organizations. Three clarifications characterize the new bylaws. The FPT Trustees (1) nominate and approve the appointment of their new board members, (2) are granted general powers to manage the organization with oversight of all employees, and (3) initiate any future changes in the Foundation bylaws and Articles of Incorporation. Collectively, the bylaws provide the clarity needed to demonstrate the ongoing oversight that is expected in managing a nonprofit, tax-exempt corporation. The primary goal of FPT is to fund credible scientific research. The methodology to meet this goal is the most important product that FPT offers to the physical therapy community. The FPT is vigilant in educating donors that gifts do not purchase favors regarding the funding process and that the competitive scientific review process is what determines the

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Editorial ultimate recipient of research grants. Donors have the capacity to restrict or endow funds for broad areas of research; however, they cannot “earmark” funds for individuals, section members, or state chapters, as that would conflict with the competitive scientific review process that is the cornerstone of the independent funding of credible research. As a tax-exempt organization, FPT must serve the greater good of the community4—which it accomplishes by funding competitively selected physical therapy research. Membership organizations such as APTA are “not-for-profit” corporations and, at times, need to acquire data independently to best represent the membership regarding national issues related to health care policy. Fortunately, however, our profession also has an operationally distinct Foundation that can issue “calls for proposals” to fund contemporary research of interest to both organizations, via a competitive review process, with transparent procedures in place to determine how the decision is made to fund investigators or groups. The FPT’s scientific review process is critical to minimizing an important source of concern to the public: the independent peer-review process, though never perfect, helps address such issues as “hidden sources of funding” and other forms of bias that may infiltrate any agency.9 Frequent, open rotation of scientific review committee members and transparent oversight of the review process are essential to the integrity of research-funding organizations. We are fortunate to have so many outstanding clinical scientists in our profession willing to volunteer time to assist in this vital process. The FPT and APTA have a true partnership that is “philosophically linked,” but with an acknowledged need to be “organizationally distinct.” Embedded in memoranda from the early 1990s are reflections by Eugene Michels,5 who served on APTA’s staff for 11 years and commented on this exact issue: “The FPT has no political ends.” “Because of its Object and Functions, the APTA rightly has political ends to which it directs its efforts and resources.” “Research believed to be directed by a membership organization may be perceived as biased towards the organization’s purpose.” This concern still resonates today when we consider research carried out by the Tobacco Institute,6 drug studies conducted by the pharmaceutical industry,7 or research sponsored by the orthopedic industry.8 Although privately funded research is necessary and beneficial, bias raises questions about the findings. Interestingly, there is a higher rate of positive findings in studies supported by industry, causing some to speculate on the credibility of those studies.6–8 The FPT is poised to embark on funding high-impact comparative effectiveness research studies. The importance of solid evidence is critical to the future of health care, as treatments shown to be ineffective are abandoned in favor of those that are effective. As our profession embraces evidence-based practice, phasing out ineffective treatments in favor of more effective ones, we make a long-term investment in our own professional credibility, a goal that reflects the common philosophy of both APTA and FPT. As an independent, tax-exempt, charitable research foundation, FPT fosters this goal by supporting physical therapy research without restricting or withholding the dissemination of the outcomes. Industry may choose to withhold research findings because they may jeopardize their product; however, a published scientific report demonstrating that a frequently used treatment is not effective is valuable knowledge and contributes to the greater good of society. The FPT’s new bylaws clarify the responsibilities and commitment of FPT’s Board of Trustees to oversee the mission to advance credible research to the public. Because of our philosophical linkages, APTA and FPT will always work synergistically for the common good in physical therapy. Indeed, APTA and FPT will continue to work in

October 2009


Editorial close proximity to minimize costs and enhance efficiencies. Even to those within the profession, the new bylaws will not be readily apparent as each organization continues to work together to advance research. But there will be a clear separation in governance and management that is necessary to meet reporting requirements for tax-exempt charitable research foundations. The FPT can now proudly share these bylaws with new trustees, students, faculty, public, corporations, the National Institutes of Health (NIH), and the IRS. Our Board of Trustees can clearly articulate and demonstrate, on paper, our longstanding commitment toward managing a credible charitable research organization devoted to the discovery of new knowledge in physical therapy. This is vital as our nation strives to reform health care and as regulatory agencies continue to increase their vigilance in evaluating tax-exempt charitable organizations. APTA showed vision, insight, and long-term commitment to physical therapy research by proactively developing and approving these bylaws. The FPT has grown and continues to grow because of the longstanding support of the physical therapy community, which has embraced the concept that “all boats rise with a rising tide” and, therefore, advancing knowledge in the field—even if it does not always advance an individual’s specific agenda—is of value to the profession. We are fortunate to have some of the most outstanding scientists in the world advancing evidence in our profession, many of whom received their initial support from the Foundation. Imagine the satisfaction of the visionaries who started and sustained FPT when they see the number of physical therapists funded by NIH today or the evidence accumulating in our field at an exponential rate. We owe much gratitude to those leaders who created FPT over 30 years ago; it is as though they knew that evidence would guide the future of our profession in the 21st century. By virtue of these new bylaws, APTA demonstrates its unimpeachable integrity and commitment to a Foundation to support research for many years to come. Richard K. Shields PT, PhD, FAPTA Past President Foundation for Physical Therapy References 1 Bigalke JT, Burrill SJ. Time for a second look at SOX compliance. Healthc Financ Manage. 2007;61(8):56– 62. 2 Peregrine MW. The emphasis on corporate governance: IRS Form 990. Trustee. 2008;June:36. http:// www.trusteemag.com/trusteemag_app/jsp/articledisplay.jsp?dcrpath=TRUSTEEMAG/Article/ data/06JUN2008/0806TRU_AboveBoard_Governance&domain=TRUSTEEMAG. Accessed September 14, 2009. 3 Wolter N. The new IRS Form 990 and Schedule H: what trustees need to know. Trustee. 2008;July:27–28. http://www.trusteemag.com/trusteemag_app/jsp/articledisplay.jsp?dcrpath=TRUSTEEMAG/Article/data/ 07JUL2008/0807TRU_DEPT_CenterVoices&domain=TRUSTEEMAG. Accessed September 14, 2009. 4 Bell J. Telling the story of community benefit. Healthc Financ Manage. 2006;60(1):58–65. 5 Michels E. Personal communication (memo), January 1993. 6 Landman A, Glantz SA. Tobacco industry efforts to undermine policy-relevant research. Am J Public Health. 2009;99:45–58. 7 Peppercorn J, Blood E, Winer E, Partridge A. Association between pharmaceutical involvement and outcomes in breast cancer clinical trials. Cancer. 2007;109:1239–1246. 8 Okike K, Kocher MS, Mehiman CT, Bhandari M. Industry-sponsored research. Injury. 2008;39:666–680. 9 Resnik DB. Perspective: Disclosing hidden sources of funding. Acad Med. 2009;84:1226–1228. [DOI: 10.2522/ptj.2009.89.10.1010]

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Research Report

R.Y.W. Law, BAppSc (Physiotherapy) (Hons), is Musculoskeletal Physiotherapist, Physiotherapy Department, Royal North Shore Hospital, Pacific Highway, St Leonards, Sydney, New South Wales 2065, Australia. Address all correspondence to Ms Law at: [email protected]. L.A. Harvey, BAppSc, GradDipApp Sc(ExSpSc), MAppSc, PhD, is Senior Lecturer, Rehabilitation Studies Unit, Northern Clinical School, Sydney School of Medicine, University of Sydney, Sydney, Australia. M.K. Nicholas, BSc, MSc (Hons), MPsychol, PhD, MAPS, FFPMANZCA (Hons), is Clinical and Research Psychologist, Associate Professor, and Director of the ADAPT Pain Management Program, Pain Management and Research Institute, University of Sydney and Royal North Shore Hospital. L. Tonkin, Dip PT, is Specialist Physiotherapist in Pain Management, Pain Management and Research Institute, University of Sydney and Royal North Shore Hospital. M. De Sousa, GDipPhty, BSc, is Physiotherapist, Pain Management and Research Institute, University of Sydney and Royal North Shore Hospital. D.G. Finniss, MSc Med, BPhty, BExSc, is Physiotherapist and Clinical Lecturer, Pain Management and Research Institute, University of Sydney and Royal North Shore Hospital. [Law RYW, Harvey LA, Nicholas MK, et al. Stretch exercises increase tolerance to stretch in patients with chronic musculoskeletal pain: a randomized controlled trial. Phys Ther. 2009;89: 1016 –1026.]

Stretch Exercises Increase Tolerance to Stretch in Patients With Chronic Musculoskeletal Pain: A Randomized Controlled Trial Roberta Y.W. Law, Lisa A. Harvey, Michael K. Nicholas, Lois Tonkin, Maria De Sousa, Damien G. Finniss

Background. Stretch is commonly prescribed as part of physical rehabilitation in pain management programs, yet little is known about its effectiveness. Objective. A randomized controlled trial was conducted to investigate the effects of a 3-week stretch program on muscle extensibility and stretch tolerance in patients with chronic musculoskeletal pain.

Design. A within-subject design was used, with one leg of each participant randomly allocated to an experimental (stretch) condition and the other leg randomly allocated to a control (no-stretch) condition.

Patients and Setting. Thirty adults with pain of musculoskeletal origin persisting for at least 3 months were recruited from patients enrolled in a multidisciplinary pain management program at a hospital in Sydney, Australia.

Intervention. The hamstring muscles of the experimental leg were stretched daily for 1 minute over 3 weeks; the control leg was not stretched. This intervention was embedded within a pain management program and supervised by physical therapists. Measurements. Primary outcomes were muscle extensibility and stretch tolerance, which were reflected by passive hip flexion angles measured with standardized and nonstandardized torques, respectively. Initial measurements were taken before the first stretch on day 1, and final measurements were taken 1 to 2 days after the last stretch. A blinded assessor was used for testing. Results. Stretch did not increase muscle extensibility (mean between-group difference in hip flexion was 1°, 95% confidence interval⫽⫺2° to 4°), but it did improve stretch tolerance (mean between-group difference in hip flexion was 8°, 95% confidence interval⫽5° to 10°).

Conclusion. Three weeks of stretch increases tolerance to the discomfort associated with stretch but does not change muscle extensibility in patients with chronic musculoskeletal pain.

© 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org 1016

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ood extensibility is important for people with chronic musculoskeletal pain. It enhances their ability to perform normal functional activities, which, in turn, improves fitness, strength (forcegenerating capacity), endurance, and psychological well-being.1–3 Multidisciplinary pain management programs aim to help individuals regain movement and return to normal activity.4 –7 Stretch exercises commonly are prescribed as part of these programs. It is believed that stretch increases muscle extensibility8 and, therefore, improves joint range of motion (ROM), movement, and function.9

Despite the widespread use of stretch in physical rehabilitation, considerable uncertainty remains surrounding its lasting effects. There is little doubt that stretch induces immediate increases in muscle extensibility due to the viscoelastic nature of soft tissues.10 –14 However, these effects are transient and quickly dissipate. The lasting effects of stretch are more controversial but arguably of more importance, particularly for individuals with chronic pain. The controversy arises from the discrepancy between strong anecdotal evidence and evidence from studies of animals15–17 supporting the effectiveness of stretch and high-quality randomized controlled trials indicating otherwise.8,18 –23 Studies of animals showed that soft tissues are adaptable and undergo structural remodeling in response to stretch.10,15,17 On the other hand, results of studies of humans are less consistent. In this article, improvements in extensibility refer to an increase in joint ROM when repeat measurements are taken with the same testing torque (torque is the product of applied force and moment arm or the tendency of a force to cause rotation).24

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Some investigators20,23,25–28 contend that what appear to be lasting changes in extensibility are in fact changes in people’s willingness to tolerate the discomfort associated with stretch over time. For example, following a hamstring muscle stretch program, an individual may touch his or her toes more easily. This patient outcome may not be due to any underlying change in muscle extensibility, but may instead be due to the direct relationship between applied stretch torque and resultant joint ROM. That is, the harder an individual leans forward (ie, the stretch torque), the further he or she can reach down toward the toes (ie, the joint ROM). The ability to reach further is due to altered perceptions and increased willingness to tolerate the discomfort associated with stretch. Extensibility and tolerance are of particular importance for people with chronic musculoskeletal pain. Thus, we were interested in exploring whether stretch affects one, or both, of these factors. The response to stretch in individuals with chronic pain may differ from the response in other people. It is possible that people with chronic pain have a heightened sensitivity to movement due to their hypervigilance and fear of pain and physical activity.29 The aim of this study, therefore, was to determine whether a 3-week stretch program could improve hamstring muscle extensibility and stretch tolerance in people with chronic musculoskeletal pain.

Method Design Overview and Randomization A randomized controlled trial using a within-subject design was undertaken. One leg of each participant was randomly allocated to an experimental condition, and the other leg was randomly allocated to a control condition. In this way, each particiVolume 89

pant acted as his or her own control, reducing variability and increasing statistical power. To ensure concealed allocation, a blocked random allocation schedule with an equal number of right and left legs was generated by computer and placed in a series of consecutively numbered, opaque, sealed envelopes by a person external to the study. The envelopes were kept off-site and opened after each participant’s initial assessment, indicating his or her inclusion into the trial. Setting and Participants Thirty adult participants were recruited from patients enrolled in a multidisciplinary pain management program based at a hospital in Sydney, Australia. To be eligible for inclusion, patients had to have pain of musculoskeletal origin persisting for at least 3 months, be likely to participate in a hamstring muscle stretch regimen as part of the pain management program, and be over 18 years of age. They were excluded if they were unable to tolerate the testing procedure; had excessive hamstring muscle extensibility (able to place palms on the floor in a standard toetouch test)30; required further medical, surgical, or psychiatric investigations or interventions; or had a history of drug or alcohol abuse. A treatment effect of 5 degrees of hip flexion was determined a priori to be clinically important, based on the recommendations of previous re-

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on August 20, 2009, at www.ptjournal.org.

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Stretch Exercises in Patients With Chronic Musculoskeletal Pain maintaining full knee extension (Fig. 1). Participants were instructed to refrain from stretching the hamstring muscles of the control leg during the course of the study. Fourteen of the 18 stretch sessions were performed in the pain management program during weekdays and supervised by physical therapists. The other 4 stretch sessions were unsupervised and performed independently by the participants on weekends. Adherence to the intervention was carefully monitored, and all stretch sessions were recorded on an exercise sheet. This adherence was reviewed at each subsequent supervised stretch session.

Figure 1. The stretch treatment administered to the hamstring muscles. Participants sat on the ground, reaching forward with both hands over the treatment leg while maintaining full knee extension. Image used with permission from www.physiotherapyexercises.com.

searchers.19,20,22,23,31 We estimated that 30 participants would provide a 95% probability of detecting a between-group difference of 5 degrees. This power calculation was based on a predicted standard deviation of 5 degrees,20 a dropout rate of 15%, and an alpha level of .05. Intervention The stretch intervention was supervised by trained physical therapists and embedded within a multidisciplinary pain management program (ADAPT). This program is a wellestablished method of chronic pain management using a multidisciplinary team approach.32 Cognitivebehavioral principles form the basis of the program, incorporating the following components: exercise and stretch, pacing, education, drug reduction, relaxation, sleep manage1018

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ment, relapse prevention, and family involvement.33 The program is conducted over 3 weeks, with at least 3 hours of physical rehabilitation daily aimed at improving muscle extensibility, fitness, strength, and posture. Physical therapists supervise the exercise sessions and use cognitivebehavioral strategies throughout to provide education on behavioral modifications and other issues.34 Stretch Treatment The hamstring muscles of the experimental leg were stretched for 1 minute per day for 3 weeks over 18 consecutive days, and the hamstring muscles of the control leg received no specific stretch treatment during this period. Stretches were selfadministered. Participants sat on the ground, reaching forward with both hands over the treatment leg while

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Outcome Measures The 2 primary outcome measures were hamstring muscle extensibility and stretch tolerance. These measures were assessed on both legs of each participant before and after the 3-week stretch intervention. Measurement Device A device specifically designed to measure passive hip flexion and hip flexor torque was used.35 Its key feature is that it enables the application of known stretch torques after counteracting the torque due to the weight of the leg. The device consists of a wheel connected to the side of a physical therapy bed (Fig. 2). A leg splint was attached to the wheel and both rotated simultaneously. The leg splint ensured full knee extension and restricted any hip abduction or rotation. Adjustable counterweights attached to a long rod were used to counteract the torque produced by the weight of the leg and splint. The long rod was connected to the wheel apparatus and extended proximally from the splint toward the head of the participant. Weights were hung tangentially from the rim of the wheel. The weights generated a hip flexor torque that rotated the October 2009

Stretch Exercises in Patients With Chronic Musculoskeletal Pain leg splint and leg together. The torque was a product of the mass of the weights and the radius of the wheel (28 cm). The device has good reliability (intraclass correlation coefficient⫽.97, 95% confidence interval [CI]⫽.96 to .98).35 Testing Procedure Participants attended a trial session at least 3 days prior to the commencement of the study to allow for familiarization with the testing procedure. Initial measurements were taken on the first day of the 3-week program, prior to the first stretch. Final measurements were taken at least 24 hours and no more than 48 hours after the last stretch to ensure that the results reflected long-lasting changes in extensibility rather than mere transient effects of stretch. This distinction is important, because we were not interested in the immediate effects (due to viscous deformation) known to quickly dissipate upon removal of the stretch.10 –14 By taking measurements more than 24 hours after the last stretch, we could be sure that our results reflected something more than just viscous deformation.8 One blinded assessor was used for all testing, and participants were instructed not to discuss any aspect of the intervention with the assessor. The success of blinding was confirmed by asking the assessor to guess the treatment allocation for each participant. All testing was performed in the same format, with measurements of the right leg taken prior to measurements of the left leg. Participants were positioned supine on a physical therapy bed with the measured leg strapped to a splint. The contralateral leg and pelvis were stabilized with straps. Participants were positioned with their hip joint aligned to the center of the wheel. Passive hip flexion angle was measured with a digital inclinometer aligned on the long axis of October 2009

Figure 2. The testing device. The wheel, leg splint, and rod rotated simultaneously. Image used with permission from www.physiotherapyexercises.com.

the leg splint (Fig. 2). All verbal instructions and explanations were standardized across participants. Assessment of Muscle Extensibility The extensibility of the hamstring muscles was reflected by the angle of passive hip flexion with the application of a standardized torque. This standardized torque was the same for both legs of each participant, but not across participants. This procedure was appropriate because the effects of the stretch intervention were being compared within, rather than between, participants. The standardized torque corresponded to the highest common torque tolerated on both legs at both preintervention and postintervention assessments. Prior to measurement, a stretch torque of 18 N䡠m was applied for 2 Volume 89

minutes. This 2-minute prestretch exhausted most viscous deformation, reducing the effect of “creep” on subsequent measurements and diminishing any reflex muscle activity around the hip and knee joints.11,14,36 –38 Assessment of Stretch Tolerance Stretch tolerance was reflected by the angle of passive hip flexion with the application of a nonstandardized torque, that is, one that corresponded to the highest stretch torque participants were willing to tolerate. This torque varied between legs, testing sessions, and participants. A series of gradually increasing stretch torques, applied at increments of 6.1 N䡠m every 30 seconds, was used to determine stretch tolerance. Hip flexion angle at each increment was measured with a digital inclinometer. Number 10

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Stretch Exercises in Patients With Chronic Musculoskeletal Pain Participants were asked to indicate when the stretch felt “very uncomfortable.” At this point, the torque was slightly reduced. Subsequently, the torque was further increased again but in smaller increments of 1.53 N䡠m at a faster rate. This continued until the participant indicated a second time that the stretch was “very uncomfortable.” At this point, final hip flexion was measured. Pain intensity also was used to reflect stretch tolerance. Participants were asked to rate their pain on an 11point numerical rating scale (with 0 being “no pain” and 10 being the “worst pain you can imagine”). Numerical rating scales are sensitive to changes in pain and have high validity and reliability.39 – 41 Participants were blindfolded throughout testing to minimize the influence of visual feedback on their tolerance to stretch. Data Analysis Changes in hip flexion angles between initial and final measurements with and without a standardized torque were calculated for both the experimental and control legs. Mean between-group differences and their corresponding 95% CIs were then calculated. The t-distribution was used to estimate the 95% CIs for between-group differences in hip angle (posttest score minus pretest score). Paired t tests were used to test for significant differences. A positive change in hip flexion angle with a standardized torque reflected an increase in hamstring muscle extensibility following the stretch intervention. Positive changes in hip flexion angle and pain rating score at the highest-tolerated torque reflected an increase in stretch tolerance. In addition, paired-samples t tests were performed on data collected from 4 pain questionnaires42– 45 routinely used in the ADAPT pain management programs. A P value of ⬍.05

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was considered significant. Data were analyzed by intention-to-treat.46

Results Participant Characteristics All 30 participants completed the study, with no dropouts or withdrawals (Fig. 3). The demographic characteristics of the participants are shown in Table 1. The site of pain was diverse, affecting the neck, back, arm, and leg, with more than half (60%) of the participants reporting pain in 2 or more major sites. Mean initial values on the Depression Anxiety and Stress Scales,42 modified Roland-Morris Disability Questionnaire,43 Multidimensional Pain Inventory,45 and Pain Self-Efficacy Questionnaire44 were consistent with recently developed normative data in people with chronic pain,47 indicating that our participants were representative of this population. Adherence to Protocol The protocol required participants to perform 18 stretch sessions over 18 consecutive days, with 14 sessions supervised and 4 sessions unsupervised. Minor deviations from the protocol occurred, with 12 stretches missed out of a total of 540 (2%) for all participants. Effects of Intervention At the commencement of the trial, there was no difference in the extensibility of the hamstring muscles between the experimental and control legs. The initial mean (SD) hip flexion angles with the application of an 18-N䡠m torque for the experimental and control legs were 47 (12) and 47 (13) degrees, respectively. Similarly, there was no difference in participants’ tolerance to the discomfort associated with stretch between their experimental and control legs. The initial mean (SD) hip flexion angles at the highest-tolerated torque were 69 (18) and 69 (19) degrees, respectively (Tab. 2).

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Primary Analyses Muscle extensibility. The betweengroup mean difference in hip flexion with a standardized torque was 1 degree (95% CI⫽⫺2 to 4; P⫽.39; Tab. 2), indicating that 3 weeks of stretch did not increase hamstring muscle extensibility. The mean (SD) torque applied was 26 (8) N䡠m. Stretch tolerance. The betweengroup mean difference in hip flexion with a nonstandardized torque was 8 degrees (95% CI⫽5 to 10; P⬍.001; Tab. 2). The corresponding betweengroup mean difference in torque tolerated by participants was 8 N䡠m (95% CI⫽4 to 11; P⬍.001; Tab. 2). No difference was found in the amount of pain reported by participants at the highest-tolerated torque before and after intervention or between the experimental and control legs. The between-group mean difference in pain intensity score was 0 points (95% CI⫽⫺1 to 0; P⫽.32; Tab. 2). These results indicate that the stretch intervention was associated with an improvement in participants’ willingness to tolerate more stretch for the same level of pain in the experimental leg.

Discussion Effects of Intervention This trial investigated the effects of stretch on muscle extensibility and stretch tolerance in patients with chronic musculoskeletal pain. The results indicated no real change in hamstring muscle extensibility, despite the apparent increase in hip flexion. This apparent change was due to participants’ improved willingness to tolerate the discomfort associated with stretch, rather than any underlying change in the passive mechanical properties of the hamstring muscles. The participants of this study were all adults aged between 19 and 68 years with chronic musculoskeletal pain originating from a variety of difOctober 2009


Figure 3. Flow of participants through the trial. Primary outcomes measured on the first and final days of the 3-week program.

ferent sources. The most common location of pain was the back (77% of the sample group) followed by the legs (53% of the sample group; Tab. 1). This study examined the effects of stretch to the hamstring muscles regardless of the site of pain. It is possible that participants with leg pain responded differently to hamstring muscle stretches than participants with arm or neck pain. There were insufficient participants to explore this possibility in post hoc subOctober 2009

group analyses, although the narrow 95% CI associated with the betweengroup difference suggests that all participants responded to the stretch intervention in a consistent way. Important design features were used in this study to minimize bias, including randomization and concealed allocation. Although participants were not blinded to the intervention, their legs were carefully screened from view during testVolume 89

ing to block visual cues of leg position. Nevertheless, it is possible that the increased tolerance to stretch reflects the use of unblinded participants, with strong expectations about the therapeutic benefits of stretch. That is, participants anticipated that the stretch intervention would improve muscle extensibility and, therefore, inadvertently tolerated larger torques during the final testing of their experimental legs,

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Stretch Exercises in Patients With Chronic Musculoskeletal Pain Table 1.

tolerance (indicating extensibility).

Demographic Characteristics of Participants (N⫽30) Variable

Value

Sex, n (%) Male

15 (50)

Female

15 (50)

Age (y), mean (SD)

43 (12)

Duration of pain (y), mean (SD)

6 (4)

Height (cm), mean (SD)

173 (10)

Weight (kg), mean (SD)

79 (18)

Toe-touch distance (cm), mean (SD)

23 (16)

Physical activity (h/wk), n (%) 0–5

19 (63)

6–10

6 (20)

ⱖ11

5 (17)

Stretch exercises (h/wk), n (%) None

13 (43)

1–2

13 (43)

ⱖ3

4 (13)

Pain site, n (%) Neck

7 (23)

Back

23 (77)

Arms

12 (40)

Legs

16 (53)

Neck and arms

6 (20)

Back and legs

13 (43)

Multiple (2 or more major pain sites)

18 (60)

Pain questionnaires,a mean (SD) Depression (DASS) (0–42)

16 (12)

Physical disability (RMDQ) (0–24)

12 (5)

Pain intensity (MPI) (0–6)

4 (1)

Pain self-efficacy (PSEQ) (0–60)

24 (12)

a

DASS⫽Depression Anxiety and Stress Scales, RMDQ⫽Roland-Morris Disability Questionnaire, MPI⫽Multidimensional Pain Inventory, PSEQ⫽Pain Self-Efficacy Questionnaire.

leading to an apparent increase in ROM. There is consistent evidence from studies of animals to indicate that sustained stretch changes the passive mechanical properties of muscles, leading to an increase in real extensibility.16,17,48 –50 This increased extensibility is attributed to the highly adaptable nature of soft tissues. Evidence from studies of hu1022

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mans is less consistent,8,51 due in part to the poor definition of extensibility26 and the failure of some investigators to measure joint ROM with a standardized torque.28,52–54 Without accompanying measures of torque, it is impossible to distinguish between increases in ROM from changes in the passive mechanical properties of soft tissues (indicating real extensibility) and increases in ROM from changes in stretch

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apparent

Numerous stretch techniques have been developed, applied, and used by physical therapists, coaches, and trainers.55 These stretch techniques include isometric, ballistic, and dynamic ROM techniques; proprioceptive neuromuscular facilitation; and passive and static stretches.56 A static stretch is a slow, sustained muscle lengthening that can easily be selfadministered and is commonly used across clinical and community settings. Static stretches are usually held for durations of 15 to 60 seconds. We chose a 1-minute static stretch for our intervention protocol, as this duration and type of stretch are typical and representative of current clinical practice in pain management programs. Muscle Extensibility Our results demonstrated that stretch does not increase hamstring muscle extensibility. This finding contradicts anecdotal evidence and the results of some clinical trials indicating the effectiveness of stretch for increasing extensibility in individuals without disabilities.36,52,54,56 –59 Our findings, however, are consistent with those of 2 similar studies of our own in individuals without disabilities.20,23 They also are comparable to the findings of multiple clinical trials involving people with neurological disabilities.19,60,61 Interestingly, these trials examined stretch interventions that were administered for much longer than a few minutes a day, yet still failed to demonstrate any real changes in muscle extensibility, despite good statistical power. It is possible that the muscles of people with neurological disabilities respond differently to stretch than the muscles of individuals without neurological disabilities. Nevertheless, these trials increasingly support the view that stretch, as typically administered in October 2009

Stretch Exercises in Patients With Chronic Musculoskeletal Pain Table 2. Mean (SD) Hamstring Muscle Extensibility and Stretch Tolerance Before and After 3 Weeks of Stretch

Preintervention

Postintervention

Change

Between-Group Mean Difference (95% Confidence Interval)

2 (7)

58 (19)

61 (16)

3 (8)

1 (⫺2 to 4)

72 (16)

2b (10)

69 (18)

79 (15)

10 (11)

8a (5 to 10)

36 (14)

37 (13)

1 (6)

36 (12)

44 (16)

8 (9)

8a,b (4 to 11)

7 (2)

7 (1)

1b (2)

7 (2)

7 (2)

0 (2)

0b (⫺1 to 0)

Control Condition Preintervention

Postintervention

58 (17)

60 (16)

Hip flexion (°)

69 (19)

Highest-tolerated torque (N䡠m)

Variable

Experimental Condition Change

Hamstring muscle extensibility (standardized torque) Hip flexion (°) Stretch tolerance (highesttolerated torque)

Pain intensity (0–10) a b

P⬍.05 Apparent error due to effects of rounding.

the clinical setting, does not induce lasting changes in extensibility. No other study to date has investigated the role of stretch in people with chronic pain. A possible explanation for the failure to increase real muscle extensibility is that 1 minute of stretch per day is subtherapeutic. Perhaps if each stretch had been administered for a longer duration (that is, more than 1 minute a day), the results may have been different. Similarly, it is possible that 3 weeks of stretch is insufficient and if the intervention had been performed over a longer period (that is, more than 3 weeks), different outcomes may have been attained. Nonetheless, the dosage of stretch used in this trial is similar to that typically applied in clinical practice.9 It is unlikely that patients with chronic pain would tolerate moreintensive stretch regimens administered for longer than a few minutes per muscle. In addition, recent evidence in individuals without disabilities indicate no added benefit from stretch administered for up to 20 to 30 minutes a day.20,23 It is possible that the stretch intervention might have increased extenOctober 2009

sibility if only participants with limited hamstring muscle extensibility had been included. However, it is difficult to define limited hamstring muscle extensibility, because joint ROM is a direct function of applied torque. If the applied torque were ignored, most clinicians would argue that a mean maximum of 69 degrees hip flexion, as attained by our participants on entry to the trial, is indicative of limited hamstring muscle extensibility. However, our participants tolerated lower levels of torque than normal. For example, on average, our participants tolerated 36 N䡠m of stretch torque at the commencement of the trial, whereas individuals without disabilities tolerate considerably more (ie, 55 N䡠m).20 It is difficult, therefore, to make direct comparisons. We were aware of the problems associated with defining limited extensibility when designing the research protocol and decided to adopt a pragmatic approach to overcome the problems. That is, we mimicked clinical practice and included all participants who would have received hamstring muscle stretches as part of their pain management program unless they had excessive extensibility Volume 89

(ie, could place the palm of their hands on the floor). The results of this trial do not rule out the possibility that the response to stretch may be a function of initial extensibility. The failure to detect a treatment effect on muscle extensibility was not due to an insufficient sample size. This finding is evidenced by the relationship between the 95% CIs and the predetermined minimally worthwhile treatment effect. Stretch Tolerance This study demonstrated that a stretch program can increase a person’s tolerance to stretch. Similarly, Halbertsma and Goeken25 and Magnusson et al26 also reported altered stretch tolerance following stretch interventions. Both groups of authors investigated the hamstring muscles with relatively intensive regimens of 10 minutes of stretch twice a day for 4 weeks25 and 225 seconds of stretch twice a day for 20 days.26 Bjorklund et al27 similarly showed sensory adaptations in the rectus femoris muscle after a 2-week stretch protocol. Interestingly, although Bjorklund et al27 used a relatively mild stretch regimen (80 seconds of stretch, 4 times a week for 2 weeks) Number 10

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Stretch Exercises in Patients With Chronic Musculoskeletal Pain compared with the 2 previous studies,25,26 the intervention was still sufficient to alter stretch tolerance. Recent evidence from studies by Folpp et al20 and Ben and Harvey23 add further support for this proposition. These investigators reported increases in stretch tolerance but not extensibility following fairly intensive stretch protocols (20 minutes a day, 5 days a week for 4 weeks,20 and 30 minutes a day, 5 days a week for 6 weeks23). Our study suggests that even a shorter and less-intensive regimen (1 minute daily over 3 weeks) can increase stretch tolerance and improve apparent muscle extensibility. These findings have important implications for clinical practice if the aim of stretch is to achieve a greater joint ROM regardless of the underlying mechanism. The explanation for changes in stretch tolerance is not known. Stretch tolerance may be influenced by nociceptive nerve endings, mechanoreceptors, or proprioceptors.26,62 Alternatively, stretch may change some other aspect of the sensory neural pathways.26,63 For example, afferent input from muscles and joints during a stretch maneuver may interfere with signals from nociceptive fibers (stretch discomfort), subsequently inhibiting an individual’s perception of pain. This explanation is consistent with the gate control theory of pain.64 Alternatively, changes in stretch tolerance may be psychologically mediated. It is possible that participants anticipated the positive effects of stretch and, therefore, their perception of the stretch discomfort was dampened. According to the gate control theory,64 sensations of pain and discomfort are affected by descending modulatory influences from higher centers. Prior experiences of stretch, motivation to stretch (possibly from supervision), and elevated mood and confidence from positive 1024

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expectations of stretch benefits are all potential psychological contributors explaining the participants’ altered perception of the discomfort and willingness to tolerate greater stretch over time. It is interesting to note that although the participants tolerated a larger testing torque on their experimental leg following 3 weeks of stretch, there were no changes in their preintervention and postintervention pain intensity scores at the highesttolerated torque. Similarly, there were no changes in preintervention and postintervention pain scores on the Multidimensional Pain Inventory,45 with a mean (SD) change of 0 (1; P⫽.16). These results suggest that it was not the pain itself that changed but rather the participants’ willingness to tolerate it. Perhaps repeated exposure to stretch produced a desensitizing effect, accustoming the individual to the sensation. The participants progressively tolerated larger stretch torques for the same level of experienced pain. This finding is consistent with the concepts of pain acceptance65 and self-efficacy,44 both commonly referred to when discussing coping strategies in the management of chronic pain. Interestingly, there was a significant improvement in mean (SD) Pain Self-Efficacy Questionnaire44 ratings during the ADAPT program from 24 (12) to 40 (10) points (P⬍.001). As participants’ acceptance of the stretch discomfort progressively improved over the 3 weeks, they began to feel more confident in their ability to perform the stretch. Participants’ increased willingness to tolerate the discomfort associated with stretch was found to be specific to the experimental leg, and there was no crossover to the control leg. That is, administering stretch on one leg did not produce any corresponding effect on the opposite leg.

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This was an interesting finding and merits further investigation. Furthermore, the effects of stretch on the experimental leg occurred on top of general improvements in the participants’ overall depression, anxiety, and physical disability. For example, the mean (SD) changes between the initial and final scores on the Depression and Anxiety Stress Scales42 and the modified RolandMorris Disability Questionnaire43 were 5 (6) (P⫽.002) and 3 (4) points (P⫽.002), respectively. The overall improvements in mood and physical disability presumably were influenced by other components of the ADAPT program. These findings together suggest that the stretch intervention itself did not provide a generalized benefit. Rather, the effects were specific to the leg that was stretched. This finding is consistent with reports on fear-avoidance interventions in patients with chronic pain, showing that exposure to one particular movement produced specific improvements in that movement only and did not generalize toward a different movement.66 Clinical Implications This study provides support for the ongoing incorporation of stretch into pain management programs, provided the aim of stretch is to improve joint ROM via increased tolerance to the discomfort associated with stretch, rather than via changing the passive mechanical properties of tissue. Stretch, therefore, may be conceptualized as a graded exposure to movement, increasing tolerance to stretch and ROM. Stretch exercises are particularly relevant in the rehabilitation of patients with chronic musculoskeletal pain, who may have physical deconditioning due to fear of movement or reinjury. Directions for Future Research Further research is needed to investigate the mechanisms underlying changes in tolerance and perception October 2009

Stretch Exercises in Patients With Chronic Musculoskeletal Pain of discomfort associated with stretch. This study raised questions about the possible contributions of neurophysiological and psychological factors accounting for the observed increase in stretch tolerance, and further investigations are needed to address this issue more closely. Future studies also should be directed at ascertaining the relative merits of targeting stretch to specific muscle groups and joints in patients with pain originating from different parts of the body. It is possible that patients with shoulder pain will respond better to specific shoulder stretches, as opposed to a generic hamstring muscle stretch. Similarly, patients with low back pain may respond significantly better to hamstring muscle stretches than patients complaining of neck pain. It is important, therefore, to prescribe specific stretches to target specific muscles and joints. The effectiveness of specific stretch interventions to target specific areas needs to be established by further research.

Conclusion This study showed that 3 weeks of stretch increases tolerance to the stretch sensation but has no effect on the passive mechanical properties of the muscle. The consequence is an increase in ROM but no real underlying change in extensibility. Stretch exercises, therefore, provide a graded exposure to movement, with a resultant increase in ROM, and should continue to be incorporated into multidisciplinary pain management programs. All authors provided concept/idea/research design and project management. Ms Law, Dr Harvey, Dr Nicholas, and Mr Finniss provided writing. Ms Law, Dr Harvey, Ms Tonkin, Ms Sousa, and Mr Finniss provided data collection. Ms Law, Dr Harvey, and Mr Finniss provided data analysis. Dr Nicholas, Ms Tonkin, Ms Sousa, and Mr Finniss provided participants and facilities/equipment. Dr Harvey, Ms Tonkin, Ms Sousa, and Mr

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Finniss provided institutional liaisons. Dr Harvey provided clerical support. Dr Harvey, Dr Nicholas, Ms Tonkin, Ms Sousa, and Mr Finniss provided consultation (including review of manuscript before submission). Trial registered with the Australian Clinical Trials Registry ACTRN012607000299404. The study protocol was approved by the Human Research Ethics Committees of the Northern Sydney Central Coast Area Health Service and the University of Sydney. This article was received February 20, 2009, and was accepted July 2, 2009. DOI: 10.2522/ptj.20090056

References 1 Musacchia XJ. Disuse atrophy of skeletal muscle animal models. Exerc Sport Sci Rev. 1988;16:61– 87. 2 Greenleaf JE. Intensive exercise training during bed rest attenuates deconditioning. Med Sci Sports Exerc. 1997;29:207–215. 3 Smeets RJ, Wittink H, Hidding A, Knottnerus JA. Do patients with chronic low back pain have a lower level of aerobic fitness than healthy controls? Are pain, disability, fear of injury, working status, or level of leisure time activity associated with the difference in aerobic fitness level? Spine. 2006;31:90 –97. 4 Nicholas MK, Wilson PH, Goyen J. Comparison of cognitive-behavioural group treatment and an alterative nonpsychological treatment for chronic lowback pain. Pain. 1992;48:339 –347. 5 Becker N, Sjogren P, Bech P, et al. Treatment outcome of chronic non-malignant pain patients managed in a Danish multidisciplinary pain centre compared to general practice: a randomised controlled trial. Pain. 2000;84:203–211. 6 Jensen IB, Bergstrom G, Ljungquist T, Bodin L. A 3-year follow-up of a multidisciplinary rehabilitation programme for back and neck pain. Pain. 2005;115: 273–283. 7 Skouen JS, Grasdal A, Haldorsen EMH. Return to work after comparing outpatient multidisciplinary treatment programs versus treatment in general practice for patients with chronic widespread pain. Eur J Pain. 2006;10:145–152. 8 Harvey L, Herbert R, Crosbie J. Does stretching induce lasting increases in joint ROM? A systematic review. Physiother Res Int. 2002;7:1–13. 9 Stretching and exercising. In: Nicholas M, Molloy A, Tonkin L, Beeston L. Manage Your Pain. Sydney, New South Wales, Australia: ABC Books; 2000:98 –127. 10 Herbert RD, Balnave RJ. The effect of positioning of immobilisation on resting length, resting stiffness, and weight of the soleus muscle of the rabbit. J Orthop Res. 1993;11:358 –366.

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11 Magnusson SP, Simonsen EB, Aagaard P, Kjaer M. Biomechanical responses to repeated stretches in human hamstring muscle in vivo. Am J Sports Med. 1996;24: 622– 628. 12 Magnusson SP. Passive properties of human skeletal muscle during stretch maneuvers: a review. Scand J Med Sci Sports. 1998;8:65–77. 13 Magnusson SP, Aagaard P, Simonsen E, Bojsen-Moller F. Passive tensile stress and energy of the human hamstring muscle in vivo. Scand J Med Sci Sports. 2000;10: 351–359. 14 Duong B, Low M, Moseley AM, et al. Time course of stress relaxation and recovery in human ankles. Clin Biomech. 2001;16: 601– 607. 15 Goldspink DF. The influence of immobilization and stretch on protein turnover of rat skeletal muscle. J Physiol. 1977;264: 267–282. 16 Goldspink G, Tarbary C, Tarbary JC, et al. Effect of denervation on the adaptation of sarcomere number and muscle extensibility to the functional length of the muscle. J Physiol. 1974;236:733–742. 17 Williams PE, Goldspink G. Changes in sarcomere length and physiological properties in immobilized muscle. J Anat. 1978; 127:459 – 468. 18 Halbertsma JPK, Van Bolhuis AI, Goeken LNH. Sport stretching: effect on passive muscle stiffness of short hamstrings. Arch Phys Med Rehabil. 1996;77:688 – 692. 19 Harvey LA, Byak AJ, Ostrovskaya M, et al. Randomised trial of the effects of four weeks of daily stretch on extensibility of hamstring muscles in people with spinal cord injuries. Aust J Physiother. 2003;49: 176 –181. 20 Folpp H, Deall S, Harvey LA, Gwinn T. Can apparent increases in muscle extensibility with regular stretch be explained by changes in tolerance to stretch? Aust J Physiother. 2006;52:45–50. 21 Harvey AL, De Jong I, Goehl G, Mardwedel S. Twelve weeks of nightly stretch does not reduce thumb web-space contractures in people with a neurological condition: a randomised controlled trial. Aust J Physiother. 2006;52:251–258. 22 Lannin NA, Cusick A, McCluskey A, Herbert RD. Effects of splinting on wrist contracture following stroke: a randomized controlled trial. Stroke. 2007;38:111–116. 23 Ben M, Harvey LA. Regular stretch does not increase muscle extensibility: a randomized controlled trial. Scand J Med Sci Sports. 2009 May 28 [Epub ahead of print]. 24 Serway RA, Jewett JW. Physics for Scientists and Engineers. 6th ed. Belmont, CA: Brooks Cole; 2004. 25 Halbertsma JPK, Goeken LNH. Stretching exercises: effect on passive extensibility and stiffness in short hamstrings of healthy subjects. Arch Phys Med Rehabil. 1994; 75:976 –981. 26 Magnusson SP, Simonsen EB, Aagaard P, et al. A mechanism for altered flexibility in human skeletal muscle. J Appl Physiol. 1996;497:291–298.

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Stretch Exercises in Patients With Chronic Musculoskeletal Pain 27 Bjorklund M, Hamberg J, Crenshaw AG. Sensory adaptation after a 2-week stretching regimen of the rectus femoris muscle. Arch Phys Med Rehabil. 2001;82: 1245–1250. 28 Chan SP, Hong Y, Robinson PD. Flexibility and passive resistance of the hamstrings of young adults using two different static stretching protocols. Scand J Med Sci Sports. 2001;11:81– 86. 29 Leeuw M, Goossens MEJB, Linton SJ, et al. The fear-avoidance model of musculoskeletal pain: current state of scientific evidence. J Behav Med. 2007;30:77–94. 30 Gauvin MG, Riddle DL, Rothstein JM. Reliability of clinical measurements of forward bending using the modified fingertipto-floor method. Phys Ther. 1990;70: 443– 447. 31 Moseley AM, Herbert RD, Nightingale EJ, et al. Passive stretching does not enhance outcomes in patients with plantarflexion contracture after cast immobilization for ankle fracture: a randomized controlled trial. Arch Phys Med Rehabil. 2005; 86:1118 –1126. 32 Nicholas M, Molloy A, Tonkin L, Beeston L. Manage Your Pain. Sydney, New South Wales, Australia: ABC Books; 2000. 33 Williams A, Richardson PH, Nicholas MK, et al. Inpatient vs outpatient pain management: results of a randomised controlled trial. Pain. 1996;66:13–22. 34 Finniss DG, Murphy PM, Brooker C, et al. Complex regional pain syndrome in children and adolescents. Eur J Pain. 2006; 10:767–770. 35 Harvey LA, McQuade L, Hawthorne S, Byak A. Quantifying the magnitude of torque physiotherapists apply when stretching the hamstring muscles of people with a spinal cord injury. Arch Phys Med Rehabil. 2003;84:1072–1075. 36 Bandy WD, Irion JM, Briggler M. The effect of time and frequency of static stretching on flexibility of the hamstring muscles. Phys Ther. 1997;77:1090 –1096. 37 Bohannon RW. Effect of repeated eightminute muscle loading on the angle of straight-leg raising. Phys Ther. 1984;64: 491– 497. 38 Magnusson SP, Simonsen EB, Aagaard P, et al. Viscoelastic response to repeated static stretching in the human hamstring muscle. Scand J Med Sci Sports. 1995;5: 342–347. 39 Jensen MP, Karoly P, Braver S. The measurement of clinical pain intensity: a comparison of six methods. Pain. 1986;27: 117–126.

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40 Jensen MP, Karoly P, O’Riordan EF, et al. The subjective experience of acute pain: an assessment of the utility of 10 indices. Clin J Pain. 1989;5:153–159. 41 Lundeberg T, Lund I, Dahlin L, et al. Reliability and responsiveness of three different pain assessments. J Rehabil Med. 2001;33:279 –283. 42 Lovibond PF. Long-term stability of depression, anxiety, and stress syndromes. J Abnorm Psychol. 1998;107:520 –526. 43 Asghari A, Nicholas MK. Pain self-efficacy beliefs and pain behaviour: a prospective study. Pain. 2001;94:85–100. 44 Nicholas MK. The pain self-efficacy questionnaire: taking pain into account. Eur J Pain. 2007;11:153–163. 45 Kerns RD, Turk DC, Rudy TE. The West Haven-Yale Multidimensional Pain Inventory (WHYMPI). Pain. 1985;23:345–356. 46 Pocock SJ. Clinical Trials: A Practical Approach. Chichester, United Kingdom: Wiley; 1983. 47 Nicholas MK, Asghari A, Blyth FM. What do the numbers mean? Normative data in chronic pain measures. Pain. 2008;134: 158 –173. 48 Williams PE. Use of intermittent stretch in the prevention of serial sarcomere loss in immobilised muscle. Ann Rheum Dis. 1990;49:316 –317. 49 Tabary JC, Tabary C, Tardieu C, et al. Physiological and structural changes in the cat’s soleus muscle due to immobilization at different lengths by plaster casts. J Physiol. 1972;224:231–244. 50 Williams PE, Goldspink G. The effect of immobilization on the longitudinal growth of striated muscle fibres. J Anat. 1973;116: 45–55. 51 Decoster LC, Cleland J, Altieri C, Russell P. The effects of hamstring stretching on range of motion: a systematic literature review. J Orthop Sports Phys Ther. 2005; 35:37–387. 52 Reid DA, McNair PJ. Passive force, angle, and stiffness changes after stretching of hamstring muscles. Med Sci Sports Exerc. 2004;36:1944 –1948. 53 Gajdosik RL, Allred JD, Gabbert HL, Sonsteng BA. A stretching program increases the dynamic passive length of and passive resistive properties of the calf muscletendon unit of unconditioned younger women. Eur J Appl Physiol. 2007;99:449 – 454. 54 Gajdosik RL, Linden DWV, McNair PJ, et al. Effects of an eight-week stretching program on the passive-elastic properties and function of the calf muscles of the older women. Clin Biomech. 2005;20: 973–983.

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55 Halbertsma JPK, Mulder I, Goeken LNH, Eisma WH. Repeated passive stretching: acute effects on the passive muscle moment and extensibility of short hamstrings. Arch Phys Med Rehabil. 1999;80: 407– 414. 56 Bandy WD, Irion JM, Briggler M. The effect of static stretch and dynamic range of motion training on flexibility of the hamstring muscles. J Orthop Sports Phys Ther. 1998; 27:295–300. 57 Bonnar BP, Deivert RG, Gould TE. The relationship between isometric contraction durations during hold-relax stretching and improvement of hamstring flexibility. J Sports Med Phys Fitness. 2004;44: 258 –261. 58 Davis DS, Ashby PE, McCale KL, et al. The effectiveness of 3 stretching techniques on hamstring flexibility using consistent stretching parameters. J Strength Cond Res. 2005;19:27–32. 59 Youdas JW, Krause DA, Egan KS. The effect of static stretching of the calf muscletendon unit on active ankle dorsiflexion range of motion. J Orthop Sports Phys Ther. 2003;33:408 – 417. 60 Harvey L, Baillie R, Ritchie B, et al. Does three months of nightly splinting reduce the extensibility of the flexor pollicis longus muscle in people with tetraplegia? Physiother Res Int. 2007;12:5–13. 61 Ben M, Harvey L, Denis S, et al. Does 12 weeks of regular standing prevent loss of ankle mobility and bone mineral density in people with recent spinal cord injuries? Aust J Physiother. 2005;51:251–256. 62 Proske U, Morgan DL, Gregory JE. Thixotropy in skeletal muscle and in muscle spindles: a review. Prog Neurobiol. 1993;41: 705–721. 63 Laessoe U, Voigt M. Modification of stretch tolerance in a stooping position. Scand J Med Sci Sports. 2003;14:239 –244. 64 Melzack R, Wall PD. Pain mechanisms: a new theory. Science. 1965;150:171–179. 65 McCracken LM, Vowles KE, GauntlettGilbert J. A prospective investigation of acceptance and control-oriented coping with chronic pain. J Behav Med. 2007;30: 339 –349. 66 Vlaeyen JWS, de Jong J, Geilen M, et al. The treatment of fear of movement/(re)injury in chronic low back pain: further evidence on the effectiveness of exposure in vivo. Clin J Pain. 2002;18:251–261.

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Research Report

Exploring Objects With Feet Advances Movement in Infants Born Preterm: A Randomized Controlled Trial Jill C. Heathcock, James C. (Cole) Galloway

Background. Previous work has shown that full-term infants who were healthy contacted a toy with their feet several weeks before they did so with their hands and that movement training advanced feet reaching. Certain populations of preterm infants are delayed in hand reaching; however, feet reaching has not been investigated in any preterm population. Objective. The primary purpose of this study was to determine whether preterm infants born at less than 33 weeks of gestational age contacted a toy with their feet at 2 months of corrected age, before doing so with their hands, and whether movement training advanced feet reaching.

Design. This study was a randomized controlled trial. Methods. Twenty-six infants born preterm were randomly assigned to receive daily movement training or daily social training. During the 8-week training period, the infants were videotaped in a testing session every other week from 2 to 4 months of age.

J.C. Heathcock, PT, PhD, is Assistant Professor, Division of Physical Therapy, Ohio State University, 453 W 10th Ave, Columbus, Ohio 43210 (USA). Address all correspondence to Dr Heathcock at: [email protected]. J.C. Galloway, PT, PhD, is Associate Professor, Department of Physical Therapy, University of Delaware, Newark, Delaware. [Heathcock JC, Galloway JC. Exploring objects with feet advances movement in infants born preterm: a randomized controlled trial. Phys Ther. 2009;89:1027– 1038.] © 2009 American Physical Therapy Association

Results. Both groups contacted the toy with their feet at 2 months of age during the first testing session prior to training, at an age when no infants consistently contacted the toy with their hands. After 8 weeks of training, the movement training group displayed a greater number and longer duration of foot-toy contacts compared with the social training group.

Conclusions. These results suggest that movement experiences advance feet reaching as they do for hand reaching. For clinicians, feet-oriented play may provide an early intervention strategy to encourage object interaction for movement impairments within the first months of postnatal life. Future studies can build on these results to test the long-term benefit of encouraging early purposeful leg movements.

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ull-term infants who are healthy first reach with their hands when they are 3 to 6 months of age.1–3 Certain populations of preterm infants, such as those born at less than 33 weeks of gestational age or weighing less than 2,500 g, show differences in reaching even when age-corrected for preterm birth.4 – 6 Contrary to an obligatory cephalocaudal progression, full-term infants display adequate control of their legs to repeatedly reach out and contact a stationary toy with their feet, several weeks before they do so with their hands.2 In addition, full-term infants improve this ability after several weeks of training.7 The purposes of the present study were: (1) to quantify, for the first time, feet reaching in a preterm population and (2) to quantify the effect of 8 weeks of movement training on their feet reaching. The presence of feet reaching and a positive training effect would suggest a novel and easily implemented intervention strategy to encourage early object interaction in infants with special needs. The lack of feet reaching or a training effect would suggest another early difference from full-term infants and a potential coordination impairment requiring further clinical and research focus.

Purposeful Control of the Legs Full-term infants who are healthy begin to gain purposeful control of their legs within the first months of postnatal life.2,8,9 The 2 most com-

Available With This Article at www.ptjournal.org • Discussion Podcast: Participants to be determined. • Audio Abstracts Podcast This article was published ahead of print on August 27, 2009, at www.ptjournal.org. 1028

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monly studied early leg behaviors are spontaneous kicking,10 –15 where infants kick without significant external stimuli or feedback, and instrumented kicking, where infants adapt their spontaneous kicks to interact with external stimuli, resulting in various types of feedback.9,16 –21 In an extensive series of studies of instrumented kicking, Rovee-Collier and colleagues22,23 used the “mobile paradigm” to study how infants, as young as 3 months of age, learn and remember a simple cause-and-effect relationship. In the traditional paradigm, infants have one leg tethered to an overhead mobile such that kicking results in mobile movement. Full-term infants quickly learn the cause-and-effect relationship during their first session, as evidenced by increasing their kicking frequency compared with periods where their kicks did not result in mobile movement. In addition to controlling the frequency of their kicks, young fullterm infants also can modify the form of their kicks as required to move the mobile. For example, 3-month-olds altered their kicking pattern to include a specific range of knee flexion to move the mobile16 and even produced patterns of hip and knee movement to touch a panel to cause mobile movement,24 which are behaviors not typically observed in spontaneous leg movements of infants of this age.25 Previous studies from our laboratory and other studies suggest that preterm infants differ from full-term infants in how they control their legs in the mobile paradigm. Preterm infants born at less than 36 weeks of gestational age required 1 additional day to learn this paradigm.26 Moreover, preterm infants born at less than 33 weeks of gestational age did not learn this association— even with 12 sessions over 6 weeks.17 Pre-

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term infants also kicked at an equal rate with the tethered and nontethered legs, whereas full-term infants preferentially increased the tethered leg kicking rate, suggesting an additional level of leg control in fullterm infants.18 Thus, in the traditional mobile paradigm, preterm infants have more difficulty than fullterm infants in controlling the frequency of their kicking, but it is unknown whether preterm infants display other levels of leg control such as “feet reaching.”

Early Object Exploration With the Feet From a supported sitting position, full-term infants appear to have greater leg control than arm control for contacting midline objects, resulting in feet reaching being displayed before hand reaching. Galloway and Thelen2 investigated the emergence of feet reaching in 2 experiments. In the first experiment, full-term infants were longitudinally tested from 8 to 15 weeks of age. They contacted toys in a midline position an average of 4 weeks earlier, and more frequently, with their feet than with their hands. In the second experiment, infants contacted a toy in a lateral position with their feet more frequently than with their hands.2 In a separate study, fullterm infants as young as 2 months of age contacted a midline toy with their feet.7 It is unknown whether any population of preterm infant display feet-reaching behaviors. Therefore, the first purpose of this study was to determine whether preterm infants are able to contact a midline toy with their feet during the first experimental session when they are 2 months of corrected age.

Effects of Training Even very young full-term infants alter their steps, kicks, and reaches when provided with additional movement experiences or “training.” For example, 2-month-olds provided with October 2009

Movement Training in Infants Born Preterm additional opportunities to step continued to show stepping for more weeks than nontrained infants.27 Three-month-olds increased the number and pattern of their steps after treadmill training.28 Three- to fourmonth-olds modified their kicking frequency and interlimb kicking patterns after 15 minutes of training with a mobile.8,29 Moreover, there was a dose response to training, with more training resulting in longerlasting changes in kicking.30,31 In addition to kicking, our work and other studies suggest that training advances the onset and quality of both hand and feet reaching in full-term infants.7,32 Infants who received several weeks of daily movement training increased the number and duration of toy contacts and moved closer to the toy.7,33 In addition, when prereaching infants were trained to hold toys with their hands while wearing Velcro* mittens, they also increased the number and durations of hand-toy contacts and looked at toys more.33 After training, infants with developmental disability have demonstrated the ability to change their movements in the form of steps and reaches. For example, infants with Down syndrome walked more than 3 months earlier after daily treadmill training compared with nontrained infants.34 Infants born at less than 33 weeks of gestational age who were delayed in hand reaching contacted toys earlier after movement training compared with nontrained infants.4 It is unknown whether movement training improves feet reaching of preterm infants at risk for developmental disability. Given the positive effects with full-term infants, we hypothesized that infants born * Velcro USA Inc, PO Box 5218, 406 Brown Ave, Manchester, NH 03103.

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Table 1. Participant Characteristics Movement Training Group (nⴝ13)

Variable Sex (male/female) Gestational age (wk), X⫾SD

Social Training Group (nⴝ13)

Pa

5/8

6/7

31⫾2

31⫾2

.799

Birth weight (g), X⫾SD

1,651⫾471

1,635⫾450

.930

Birth length (cm), X⫾SD

42⫾4

42⫾4

.927

Head circumference (cm), X⫾SD

28⫾2.5

Apgar score (1 min), X⫾SD

28⫾3.5

.903

5.5⫾3b

.117

8⫾1

8⫾2

.296

26⫾17

37⫾28

7⫾1

Apgar score (5 min), X⫾SD Time in Special Care Nursery (d), X⫾SD Time on oxygen (d), X⫾SD

7⫾15

Maternal age (y), X⫾SD

49⫾80

28⫾6

30⫾6

Caucasian

8

10

African American

2

3

Hispanic

1

0

Asian

2

0

.276 c

.108 .601

Race/ethnicity

a

Assessed with Student t test. Two infants in the social training group had Apgar scores (1 minute) equal to 1, deflating the mean and increasing the standard deviation in this category. The Apgar scores of these infants were comparable to those of other infants in both groups at 5 minutes. c One infant in the social training group was on oxygen for an extended amount of time (200 days) and inflated the mean and standard deviation in this category. b

preterm who receive movement training would show more foot-toy contacts and longer toy contacts. Therefore, the second purpose of this study was to determine whether preterm infants change their feetreaching behaviors with daily movement training similar to full-term infants.

Method Participants Twenty-seven infants born preterm completed this project. The infants were recruited from the Special Care Nursery (SCN) at Christiana Hospital, Newark, Delaware, and through word of mouth. Infants were recruited from March 2004 to December 2005. Infants were eligible for participation if they were born at less than 33 weeks of gestational age and weighed less than 2,500 g at birth. Infants were excluded for prenatal Volume 89

drug exposure, congenital orthopedic or genetic anomalies, and significant visual or hearing deficits. Infant characteristics shown in Table 1 suggest that groups were comparable on these variables. Table 2 shows available imaging summaries from head ultrasounds. An additional 5 infants were recruited from the SCN and started the project, but voluntarily withdrew due to family time constraints. Guardians of each preterm infant signed an informed consent form approved by the University of Delaware Human Subjects Review Committee or Christina Care Institutional Review Board. Infants who participated in the current project were part of a much larger project on motor behaviors and training in preterm infants. Families of participants were given an honorarium for their participation and were reimbursed for parking costs. Number 10

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Movement Training in Infants Born Preterm Table 2. Available Imaging Summary for Individual Infants in Each Groupa Participant No.

Head Ultrasound 1

Head Ultrasound 2

Movement training group 1

N/A

2

N/A

3

WNL

4

Grade 1 IVH

5

WNL

6

Patchy area of echogenicity in right parietal lobe

7

WNL

8

N/A

9

N/A

‘

10

Mostly WNL

11

WNL

12

Megacisterna magna

13

WNL

Social training group 1

Grade 3 IVH

Mild ventriculomegaly, no evidence of IVH

2

Suspicious for left choroid plexus bleed

3

WNL

4

Grade 2 IVH, mild ventriculomegaly

5

WNL

6

Small right choroid plexus cyst

7

N/A

8

N/A

9

PVL

10

WNL

11

WNL

12

N/A

13

WNL

Reduction 90% of cysts

a

WNL⫽within normal limits, PVL⫽periventricular leukomalacia, IVH⫽intraventricular hemorrhage, N/A⫽not available or no imaging done.

Training Infants were randomly assigned to 1 of 2 groups: a movement training group and a social training group. Training started when infants were 8 to 10 weeks of corrected age (X⫾SD⫽8.9⫾2 weeks for the movement training group and 8⫾2 weeks for the social training group).

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Families of both groups were asked to provide 10 minutes of training with their infants at home, 5 days a week for 8 weeks. Both groups received a training booklet with stepby-step instructions for the training activities and a journal to record how much time was spent on each activity. The primary caregiver was

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trained by the same physical therapist on how to perform training activities. Follow-up questions on how to perform these activities were addressed over the telephone and during the testing sessions over the 8-week training period. Each group completed an average of ⱖ75% of the training per week. Movement training. Thirteen infants were randomly assigned to receive daily movement training at home over 8 weeks. Caregivers were instructed that the movement training activities were designed to improve their infant’s awareness and ability to reach for and interact with toys with their feet. Movement training activities were divided into 3 categories of feet games: general movements,7 midline movements, and distinct movements (Fig. 1). Specific activities were chosen because there are 2 important factors that influence the typical emergence of independent hand reaching: midline behaviors of the hands and physical interaction with toys.2,35,36 Our movement training program incorporates midline movements of the foot and earlier foot-toy interactions. In addition, there are 2 main factors that describe atypical leg movements seen in infants born preterm: a decreased ability to disassociate the joints of the legs and a high frequency of kicking.12,15,37,38 Our movement training program incorporates activities that promote dissociation of the joints by using distinct leg movements to interact with toys. Social training. To control for the increased social interaction that accompanies movement training, caregivers of infants in the social training group were instructed to position their infant supine on the floor and sit near the infant’s feet. Caregivers were given a 10-minute CD of children’s music. They were instructed to interact with their infant visually October 2009

Movement Training in Infants Born Preterm and verbally along with the music, but not to touch or present objects to their infant. Infants were allowed to move throughout these interactions. Thus, the infants in the social training group experienced a similar amount of one-on-one time with the caregiver in the same position as in the movement training group, but they did not physically interact with objects or their caregiver (Fig. 2). Testing Sessions Infants and families were seen in the Infant Motor Behavior Laboratory, University of Delaware, every other week for 8 weeks, for a total of 5 sessions. The protocol followed that of previous feet-reaching studies.2,7 Infants were seated in a custommade chair with a strap placed around their chest (Fig. 3). The chair allowed free movement of the arms and legs. The experimenter stood directly in front of the infant and presented a toy in the infant’s midline at hip height for six 30-second trials. After each trial, the toy was moved out of the infant’s view and repositioned in midline for the next trial. Two synchronized Sony 8mm CCD-TRV608 video cameras† were placed approximately 1.2 m (4 ft) to the front and right of the infant and approximately 1.2 m to the front and left of the infant to record a clear view of all leg movements for behavioral coding.

Figure 1. Three categories of movement training activities: (A) general movements— caregiver encouraging earlier foot-toy interaction by making the bells on infant’s socks ring with Velcro attachment, (B) midline movements— caregiver holding a stationary toy in midline and encouraging a midline reach with the foot to contact the toy, and (C) distinct movements— caregiver holding an infant’s hip at 90 degrees and encouraging primarily knee motion to contact the toy with the foot.

Figure 2. Social training.

Coding Synchronized videotapes were recorded on a computer using Broadway Pro version 4.5 software,‡ and behaviors were coded from the computer image using a custom-made program. Each session was coded twice: once for toy contacts and a second time for duration of the toy contacts. Two research assistants †

Sony Corporation of America, 550 Madison Ave, 33rd Floor, New York, NY 10022-3211. ‡ Data Translation Inc, 100 Locke Dr, Ste 1, Marlborough, MA 01752-7235.

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Figure 3. Infant during the feet trials of a testing session. For hand trials during session 1, the toy was placed in midline at shoulder height.

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Movement Training in Infants Born Preterm who were blinded to each infant’s group coded all videotapes. Interrater reliability assessed with 20% of all trials (reflected by the amount of agreement minus amount of disagreement divided by the total) for contact number (ⱖ95%) and contact duration (ⱖ91%) was high. Dependent Variables Number of foot-toy contacts. The number of times the infant contacted the toy with any part of either foot or toes was recorded for sessions 1 through 5. Number of hand-toy contacts. The number of times the infant contacted the toy with any part of either hand or fingers was recorded for session 1. Hand-toy contacts were used during session 1 to determine whether infants born preterm touched the toy with their feet before touching the toy with their hands. Foot-toy contact duration (seconds). The average amount of time infants spent touching the toy per foot-toy contact was recorded for sessions 1 through 5. Data Analysis Feet reaching during session 1. Descriptive statistics were used to evaluate whether preterm infants contacted the toy with their feet and their hands during session 1. A paired t test was used to test significance. The alpha level was set at ⱕ.05 for a significant difference and at ⱕ.10 for a statistical trend. Given the individual variability typical of infant behavior, the number of infants who contacted the toy more than 1, 5, and 10 times was compared between groups. Feet reaching over sessions 1 through 5. Foot-toy contact number was analyzed with a 2 (group) ⫻ 5 (session) 2-way analysis of variance (ANOVA) for repeated measures on 1032

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one variable (session). Planned comparisons using independent t tests were used for between-group comparisons during each testing session. Foot-toy contact durations required nonparametric statistics because each group had a different total number of foot-toy contacts. Consequently, contact durations are shown graphically as box plots. Nonparametric Friedman tests were used to assess change over sessions, and the MannWhitney U test was used to assess between-group differences. The alpha level was set at ⱕ.05 for a significant difference and at ⱕ.10 for a statistical trend. Role of the Funding Source This work was partly funded by Foundation for Physical Therapy PODS II awards to Dr Heathcock and was a part of her dissertation in the Biomechanics and Movement Science Program in the Department of Physical Therapy at the University of Delaware.

Results Session 1, Prior to Training A paired t test indicated the number of foot-toy contacts of both groups combined was greater than hand-toy contacts during session 1 (t⫽⫺4.3, P⫽.000). Descriptive statistics also suggested that during session 1, when infants were 2 months of corrected age, foot-toy contacts were common, whereas hand-toy contacts were rare. Specifically, 80% (21/26) of the infants contacted the toy with their feet at least once during session 1, for a total of 191 contacts and an average (⫾SD) number of contacts per infant of 7.35⫾7.89 (range⫽0– 31). In addition, 54% (14/26) of the infants contacted the toy more than 5 times, and 42% (11/26) of the infants contacted the toy more than 10 times (Fig. 4). In contrast, 27% (7/26) of infants contacted the toy with their hands at least once, for a total of 23 contacts and an average (⫾SD) number of contacts per infant

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of 0.88⫾2.1 (range⫽0 –9). Only one infant contacted the toy 5 times, and no infant contacted the toy more than 10 times. These results suggest that at 2 months of corrected age, preterm infants elevated their feet to hip height to contact a toy with their feet more often than with their hands. Sessions 1 Through 5 Foot-toy contact frequencies over time and between groups for the 5 sessions are shown in Figure 5. During session 1, there were no differences in the number of foot-toy contacts between groups. At each session during the training period (after session 1), infants in the movement training group contacted the toy more frequently than infants in the social training group (Fig. 5). A group (2) ⫻ session (5) repeatedmeasures ANOVA indicated significant main effects for group (F1,24⫽ 43.3, P⫽.000) and session (F4,96⫽ 3.2, P⫽.016). The movement training group had a higher mean number of foot-toy contacts during sessions 2 through 5 (Fig. 5). A planned comparison indicated a significant difference (X⫾SD) between the movement training group (32.7⫾22.9) and the social training group (15.4⫾ 16.6) during session 5 (t⫽4.86, P⫽.037). During session 5, after 8 weeks of training, infants in the movement training group touched the toy 425 times, whereas infants in the social training group touched the toy 200 times. The effect size for session 5 using the Cohen d statistic was large at .83. On an individual level, 92% (12/13) of infants in the movement training group touched the toy with their feet more than 10 times, whereas 62% (8/13) of infants in the social training group touched the toy with their feet more then 10 times in session 5 (Fig. 4). In summary, infants in both groups showed an equal number of foot-toy October 2009

Movement Training in Infants Born Preterm contacts during session 1, before the training program. In addition, both groups showed an increase in the number to foot-toy contacts over each session. Infants in the movement training group out-performed infants in the social training group over time and during session 5, suggesting that movement training may have improved the infants’ ability to contact a toy with their feet. During our analysis, we noticed that 2 infants in the social training group had the most significant brain injuries (see participants 1 and 9 in Tab. 2). To ensure the difference between the 2 interventions was not attributed to the presence of the most serious brain lesions in the social training group, we ran the above statistical analysis without these 2 infants. A group (2) ⫻ session (5) repeated-measures ANOVA indicated significant main effects for group (F1,22⫽36.7, P⫽.000) and session (F4,88⫽2.5, P⫽.047). The movement training group had a higher mean number of foot-toy contacts during sessions 2 through 5. A planned comparison indicated a significant difference (X⫾SD) between the movement training group (32.7⫾22.9) and the social training group (14.3⫾17.7) during session 5 (t⫽4.7, P⫽.041). In summary, there were no changes in our results. All variables that were significant remained significant. For all variables, these 2 infants performed around the mean of the social training group or better. In addition, both infants touched the toy more than 10 times on visit 5, indicating they were consistent reachers. Therefore, we continued with the statistical analysis including the entire sample. Foot-Toy Contact Duration The results for foot-toy contact duration are shown in Figure 6. Because infants in the movement training group contacted the toy more times than infants in the social training October 2009

Figure 4. Total number of foot-toy contacts for individual infants in the movement training group (top graph) and the social training group (bottom graph).

group, the average duration per contact was entered into nonparametric statistical analyses. Figure 6 suggests that the movement training group contacted toys for a longer duration than the social training group. A nonparametric Friedman test indicated no significant change in foot-toy contact duration over time. A nonparametric Mann-Whitney U test indicated significant differences between groups for session 5 (Z⫽ ⫺2.00, P⫽.045), suggesting that for each foot-toy contact the movement training group touched the toy for longer periods of time. Volume 89

Discussion Early Feet-Reaching Behaviors in Preterm Infants The first purpose of this study was to evaluate whether preterm infants at 2 months of corrected age can use their feet to interact with a stationary midline toy. Preterm infants were able to contact a stationary toy with their feet before being able to contact the toy with their hands, similar to behaviors seen in full-term infants. Specifically, preterm infants demonstrated a much higher number of foot-toy contacts than handtoy contacts during session 1. Furthermore, a majority of preterm Number 10

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Movement Training in Infants Born Preterm infants contacted toys with their feet multiple times during session 1, when no infants were able to contact the toy consistently with their hands. Our findings are similar to the findings of other studies of full-term infants2,7 and suggested that when they are interested in a toy placed within reach of their feet, both fullterm and preterm infants born at less than 33 weeks of gestational age can control their legs to contact the toy multiple times. Figure 5. Mean and standard error of the average number of foot-toy contacts per session for the movement training group (red bars) and the social training group (blue bars). The graph shows that there were more total contacts during each session over time and that the movement training group had more contacts than the social training group during session 5. Sessions were separated by 2 weeks. Asterisk indicates significant difference between groups at P⬍.05.

Figure 6. Box plots for the average foot-toy contact duration in seconds; the median for each group is represented by the dashed line. The error bars represent the maximum and minimum values and the top and bottom quartiles of data distribution. The boxes represent the distribution of data from the 2 middle quartiles. The graph shows that there were no changes in foot-toy contact durations over time and that the movement training group had longer durations than the social training group during session 5. Asterisk indicates significant difference between groups at P⬍.05.

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Effects of Movement Training on Feet Reaching The second purpose of this study was to evaluate the effects of daily movement training on the feetreaching behaviors of preterm infants. Preterm infants in both groups showed an increase in feet reaching over time, with an advantage appearing for the movement training group after 8 weeks of training, when the infants were 4 months of corrected age. Galloway and Thelen2 found that over a 1-month period the duration of foot-toy contacts increased, suggesting that nontrained full-term infants increased their leg control for contacting toys with their feet. The duration of foot-toy contacts for preterm infants born at less than 33 weeks of gestational age did not change over the 8-week testing period for either group. This finding may represent an important difference in early leg control between full-term and preterm infants. It is important to note that the duration of foot-toy contacts was 2 seconds less that typically seen for hand-toy contacts.4 The hand can easily be used to hold a toy. Indeed, young infants who are not yet reaching will hold on to a toy when it is placed in their hand.39 – 41 Equipping socks and toys with Velcro during training could increase infants’ drive to explore and maintain contact with toys with their feet, similar to how “sticky mittens” have been used to train

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Movement Training in Infants Born Preterm young infants to explore toys longer with their hands.33 Our movement training, which focused on midline movements of the feet, earlier experience with foot-toy interactions, and dissociation of the joints of the leg, had a positive effect on the number of foot-toy contacts and duration of foot-toy contacts. All dependent measures began to improve for the movement training group over the social training group during session 5. It is unknown how changes in foot-toy contacts affect other motor skills and how these foot-toy contact behaviors would continue to evolve in preterm infants with and without movement training. In combination, these results suggest that preterm infants may need more movement experience, such as via early intervention, than full-term infants in order to improve or learn a motor skill. Full-term infants show immediate changes in behavior with training in the mobile paradigm and significant changes in hand and feet reaching after 2 to 3 weeks of training.7,33,42 The movement training group in this project showed improvements only after 8 weeks of training. If there is a difference in training effect between full-term and preterm infants, then it is particularly concerning for 3 reasons. First, the length and amount of training provided to preterm infants were more than have typically been reported in training studies on full-term infants.7,27,28,33,43 Thus, full-term infants showed much earlier skill acquisition, even when preterm infants were provided with daily training over many weeks or months. Second, our preterm cohort was not a high-risk population and would be expected to have a training effect more similar to that of full-term infants than that of preterm infants at higher risk. Thus, the effect of training on the early control of the head, October 2009

arms, legs, and trunk needs additional clinical research focus. Third, certain populations of preterm infants display learning differences from full-term infants, both as younger infants17,26 and at older ages.44 – 47 Thus, the difference in training effect could reflect, in part, differences in motor learning. Early Motor Control in Preterm Infants Various populations of preterm infants show marked differences from fullterm infants in terms of postural control,48,49 reaching with the hands,6 spontaneous kicking,12,38,50 and kicking in the mobile paradigm.17,18,26 More importantly, these differences often are predictive of future delays in functional skills such as walking or object exploration.37,49,51 Thus, why is it that preterm infants appear to be relatively good at feet reaching, while struggling with other motor skills during young infancy? Galloway and Thelen2 proposed that feet reaching was easier than hand reaching due, in part, to the interaction of 2 soft constraints: anatomical differences between the arms and legs and differences in early movement experiences of the arms and legs. Similarly, we hypothesize that the anatomical constraints of a stable base, experience moving the legs in the midline, and the task constraints of the current project make feet reaching less difficult for preterm infants than reaching with the hands. First, leg movements may benefit from greater mechanical stability. Reaching out to touch a toy with the hand requires hand-eye coordination, head control, trunk control, and the ability to move the arm against gravity to a midline position.52–56 Providing assistance in these areas, such as postural or head support, increases the number of hand reaches in fullterm infants.57 Similarly, the pelvis Volume 89

offers a more anatomically stable support surface for feet reaching than the scapula offers for hand reaching and potentially fewer degrees of freedom, requiring active control at the hip versus the shoulder. In addition, when moving the arms, a certain degree of head and postural control is required secondary to the mechanical effects resulting from the interaction of arm, head, and trunk motion, as well as the effect of gravity.6,58,59 This effect is less likely, especially in terms of the head, when the legs are moving. This is especially true in our infant chair, which stabilizes the lower trunk and hip more than the upper trunk, shoulder, and head. Preterm infants may take advantage of this constraint and use it to more easily control their legs when contacting a toy. Second, infants have more experience moving their legs in the workspace required for feet reaching. Spontaneous kicking is one of the most common behaviors seen from the last prenatal trimester through the first 3 postnatal months. Both preterm and full-term infants kick their legs several hundred, if not a few thousand, times per day.25 As they move, infants are learning about the properties of their limbs and how to eventually control their bodies.9,60,61 Compared with early arm movements,62– 64 kicking in young infants is relatively stereotypical within a parasagittal plane, with reliable timing between the legs and among the joints of one leg.14 In contrast, spontaneous arm movements are much more variable, as the arms move in multiple planes and rarely in the midline until a few weeks before reaching onset.62– 64 Thus, infants have much greater experience moving their feet near midline and have less distance to control their legs in order to contact a midline toy, as compared with the hands. Number 10

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Movement Training in Infants Born Preterm Lastly, kicking and reaching are different behaviors. The development of leg control in preterm infants over the first few months differs from that of full-term infants. Preterm infants are not able to control the frequency of their leg kicking or the proportion of leg kicking to make a mobile move.17,18,38 The results of this study, however, suggest that preterm and full-term infants may have similar abilities in the development of endpoint control. Kicking behaviors may be too stable and afford less adaptation in kicking tasks such as the mobile paradigm, which positively reinforces any style, speed, or direction of leg movements. In contrast, feet reaching demands a nonkicking movement in which the movement direction and endpoint control are rewarded.

rolling, sitting, crawling, and reaching with the hands.

Clinical Implications At 8 weeks of age, common assessments of infant development are the observations of passive and elicited movements. Foot-to-toy contacts may give clinicians more information about higher-level skills at a younger age. Infants who repeatedly touch a toy with their foot must coordinate the endpoint and joints of their legs and have the strength to move their legs against gravity, sufficient range of motion of the hip, and the motivation to touch the toy. This type of assessment could be used in conjunction with standard assessment tools for preterm infants, such as the Test of Infant Motor Performance (TIMP),65 where observations of spontaneous coordination could be paired with those of skilled movements such as feet reaching. Interestingly, at 8 weeks of corrected age, leg control is one of the most discriminating items on the TIMP.66 These early measures of range of motion, strength, control, flexibility, and interest in objects may be early precursors to similar variables that contribute to the development of

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As an intervention, clinicians may take advantage of this ability to improve coordination and strength of the legs, the learning of cause-andeffect relationships, and object exploration. At 8 weeks of age, most infants are not able to contact a toy independently with their hands, yet they can do so with their feet. This ability highlights that when given the opportunity, infants are able to explore with whatever means they have available. In addition, infants born preterm demonstrate positive changes in their motor skills during a specific early intervention program, such as the ability to improve how they interact with objects with their hands and feet.

Given that this is the first quantification of feet reaching and the effect of movement training on feet reaching in any preterm population, there are several limitations that need to be addressed in future studies. First, our cohort was born at risk for motor impairments, but not at the highest risk. The early identification of impairments and their response to movement training are even more critical for infants at highest risk, such as those with extremely low birth weight and those who are extremely preterm. It is important to study these populations directly and not simply extrapolate findings from studies of lower-risk populations. Second, although we noted a training effect, we would suggest expanding other components in the protocol such as the role of “sticky socks” to maximize infants’ interaction with objects during training. This may be especially helpful if preterm infants have motor learning issues. Lastly, we suggest that our preterm infants displayed adequate leg control to re-

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peatedly place their feet on a midline toy. Further study is needed to directly quantify the degree of coordination using methods such as principal component analysis67 and the uncontrolled manifold technique.68,69 Given the potential developmental connection between spontaneous leg movements and feet reaching, additional work is needed to further test the similarities and differences between these behaviors. Despite these limitations, our results suggest that preterm infants display a new and potentially important ability to contact objects with their feet before their hands. This finding, coupled with a positive effect of training, provides researchers with a foundation for more-specific hypotheses about the role of experience in early purposeful movements and provides clinicians with a new intervention strategy for encouraging object interaction within the first months of life in infants at risk for long-term motor impairments. Both authors provided concept/idea/research design, writing, data analysis, project management, and consultation (including review of manuscript before submission). Dr Heathcock provided data collection. Dr Galloway provided facilities/equipment, institutional liaisons, and clerical support. This study was approved by the University of Delaware Human Subjects Review Committee and the Christiana Care Institutional Review Board. A poster presentation of this research was given at the Combined Section Meeting of the American Physical Therapy Association; February 9 –12, 2009; Las Vegas, Nevada. This work was partly funded by Foundation for Physical Therapy PODS II awards to Dr Heathcock and was a part of her dissertation in the Biomechanics and Movement Science Program in the Department of Physical Therapy at the University of Delaware.

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Movement Training in Infants Born Preterm This article was received September 8, 2008, and was accepted June 29, 2009. DOI: 10.2522/ptj.20080278

References 1 Gesell A, Ames L. The development of handedness. J Gen Psychol. 1947;70: 155–175. 2 Galloway JC, Thelen E. Feet first: object exploration in young infants. Inf Behav Dev. 2004;27:107–112. 3 Thelen E, Corbetta D, Kamm K, et al. The transition to reaching: mapping intention and intrinsic dynamics. Child Dev. 1993; 64:1058 –1098. 4 Heathcock JC, Lobo MA, Galloway JC. Movement training advances the emergence of reaching in infants born less than 33 weeks of gestational age: a randomized clinical trial. Phys Ther. 2008;88:310 –322. 5 Fallang B, Saugstad OD, Grøgaard J, Hadders-Algra M. Kinematic quality of reaching movements in preterm infants. Pediatr Res. 2003;53:836 – 842. 6 Fallang B, Saugstad OD, Hadders-Algra M. Postural adjustments in preterm infants at 4 and 6 months post-term during voluntary reaching in supine position. Pediatr Res. 2003;54:826 – 833. 7 Lobo MA, Galloway JC, Savelsbergh GJ. General and task-related experiences affect early object interaction. Child Dev. 2004;75:1268 –1281. 8 Rovee CK, Rovee DT. Conjugate reinforcement of infant exploratory behavior. J Exp Child Pyschol. 1969;8:33–39. 9 Thelen E, Fisher D. From spontaneous to instrumental behavior: kinematic analysis of movement changes during very early learning. Child Dev. 1983;54:129 –140. 10 Droit S, Boldrini A, Cioni G. Rhythmical leg movements in low-risk and braindamaged preterm infants. Early Hum Dev. 1996;44:201–213. 11 Hayes MJ, Plante LS, Fielding BA, et al. Functional analysis of spontaneous movements in preterm infants. Dev Psychobiol. 1994;27:271–287. 12 Jeng SF, Chen LC, Yau KI. Kinematic analysis of kicking movements in preterm infants with very low birth weight and fullterm infants. Phys Ther. 2002;82:148 –159. 13 Piek JP. Is a quantitative approach useful in the comparison of spontaneous movements in full-term and preterm infants? Hum Mov Sci. 2001;20:717–736. 14 Thelen E, Fisher D. The organization of spontaneous leg movements in newborn infants. J Mot Behav. 1983;15:353–377. 15 van der Heide J, Paolicelli PB, Boldrini A, Cioni G. Kinematic and qualitative analysis of lower-extremity movements in preterm infants with brain lesions. Phys Ther. 1999;79:546 –557. 16 Angulo-Kinzler RM, Ulrich B, Thelen E. Three-month-old infants can select specific leg motor solutions. Motor Control. 2002;6:52– 68.

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17 Heathcock JC, Bhat AN, Lobo MA, Galloway JC. The performance of infants born preterm and full-term in the mobile paradigm: learning and memory. Phys Ther. 2004;84:808 – 821. 18 Heathcock JC, Bhat AN, Lobo MA, Galloway JC. The relative kicking frequency of infants born full-term and preterm during learning and short-term and long-term memory periods of the mobile paradigm. Phys Ther. 2005;85:8 –18. 19 Rovee-Collier CK, Adler SA, Borza MA. Substituting new details for old? Effects of delaying postevent information on infant memory. Mem Cognit. 1994;22:644 – 656. 20 Vaal J, van Soest AJ, Hopkins B. Spontaneous kicking behavior in infants: age-related effects of unilateral weighting. Dev Psychobiol. 2000;36:111–122. 21 Vaal J, van Soest AJ, Hopkins B, Sie LT. Spontaneous leg movements in infants with and without periventricular leukomalacia: effects of unilateral weighting. Behav Brain Res. 2002;129:83–92. 22 Rovee-Collier CK. Information pick-up by infants: what is it, and how can we tell? J Exp Child Psychol. 2001;78:35– 49; discussion 98 –106. 23 Rovee-Collier CH, Hayne H, Colombo M. The Development of Implicit and Explicit Memory. Amsterdam, the Netherlands: John Benjamins; 2001. 24 Chen YP. Making the mobile move: constraining task and environment. Infant Behav Dev. 2002;146:1–26. 25 Thelen E. Developmental origins of motor coordination: leg movements in human infants. Dev Psychobiol. 1984;18:1–22. 26 Gekoski MJ. Early Learning and memory in the preterm infant. Infant Behav Dev. 1984;7:267–276. 27 Zelazo PR, Zelazo NA, Kolb S. “Walking” in the newborn. Science. 1972;176:314 –315. 28 Vereijken B, Thelen E. Training infant treadmill stepping: the role of individual pattern stability. Dev Psychobiol. 1997;30: 89 –102. 29 Thelen E. Three-month-old infants can learn task-specific patterns of interlimb coordination. Psychol Sci. 1994;5:280 –284. 30 Hitchcock DF, Rovee-Collier CK. The effect of repeated reactivations on memory specificity in infancy. J Exp Child Psychol. 1996;62:378 – 400. 31 Rovee-Collier CK, Sullivan MW, Enright M, et al. Reactivation of infant memory. Science. 1980;208(4448):1159 –1161. 32 Heathcock JC, Ulrich B. Enhanced sensory input during partial body weight supported treadmill training changes stepping quality and quantity in infants born at term and ⬍32 weeks of gestational age. Presented at: Combined Sections Meeting of the American Physical Therapy Association; February 6 –9, 2008; Nashville, Tennessee. 33 Needham A. A pick-me-up for infants’ exploratory skills: early simulated experiences reaching for objects using “sticky mittens” enhances young infants’ object exploration skills. Infant Behav Dev. 2002;25:279 –295.

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34 Ulrich DA, Ulrich BD, Angulo-Kinzler RM, Yun J. Treadmill training of infants with Down syndrome: evidence-based developmental outcomes. Pediatrics. 2001;108: E84. 35 van Hof R, van der Kamp J, Savelsbergh GJ. The relation of unimanual and bimanual reaching to crossing the midline. Child Dev. 2002;73:1353–1362. 36 Newland LA, Roggman LA, Boyce LK. The development of social toy play and language in infancy. Infant Behav Dev. 2001; 24:1–25. 37 Jeng SF, Chen LC, Tsou KI, et al. Relationship between spontaneous kicking and age of walking attainment in preterm infants with very low birth weight and fullterm infants. Phys Ther. 2004;84:159 –172. 38 Geerdink JJ, Hopkins B, Beek WJ, Heriza CB. The organization of leg movements in preterm and full-term infants after term age. Dev Psychobiol. 1996;29:335–351. 39 Wallace PS, Whishaw IQ. Independent digit movements and precision grip patterns in 1- to 5-month-old human infants: hand-babbling, including vacuous then self-directed hand and digit movements, precedes targeted reaching. Neuropsychologia. 2003;41:1912–1918. 40 Lew AR, Butterworth G. The development of hand-mouth coordination in 2- to 5month-old infants: similarities with reaching and grasping. Infant Behav Dev. 1997;20: 59 – 69. 41 Striano T. Haptic perception of material properties by 3-month-old infants. Infant Behav Dev. 2005;28:266 –289. 42 Lobo MA, Galloway JC. Experience matters: the relationship between experience, exploration and the emergence of meansend performance. Child Dev. In press. 43 Ohr PS, Fagen JW, Rovee-Collier CK, et al. Amount of training and retention by infants. Dev Psychobiol. 1989;22:69 – 80. 44 Aylward GP. Cognitive and neuropsychological outcomes: more than IQ scores. Ment Retard Dev Disabil Res Rev. 2002; 8:234 –240. 45 Walther FJ, den Ouden AL, VerlooveVanhorick SP. Looking back in time: outcome of a national cohort of very preterm infants born in The Netherlands in 1983. Early Hum Dev. 2000;59:175–191. 46 Cherkes-Julkowski M. Learning disability, attention-deficit disorder, and language impairment as outcomes of prematurity: a longitudinal descriptive study. J Learn Disabil. 1998;31:294 –306. 47 Litt R, Joseph A, Gale R. Six year neurodevelopmental follow-up of very low birthweight children. Isr J Med Sci. 1995;31: 303–308. 48 Samsom JF, de Groot L. The influence of postural control on motility and hand function in a group of “high risk” preterm infants at 1 year of age. Early Hum Dev. 2000;60:101–113. 49 de Vries AM, de Groot L. Transient dystonias revisited: a comparative study of preterm and term children at 21⁄2 years of age. Dev Med Child Neurol. 2002;44:415– 421.

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Movement Training in Infants Born Preterm 50 Piek JP. Spontaneous kicking in full-term and preterm infants: Are there leg asymmetries? Hum Mov Sci. 1999;18:377–395. 51 Fallang B, Øien I, Hellem E, et al. Quality of reaching and postural control in young preterm infants is related to neuromotor outcome at 6 years. Pediatr Res. 2005;58: 347–353. 52 Bertenthal B, Von Hofsten C. Eye, head and trunk control: the foundation for manual development. Neurosci Biobehav Rev. 1998;22:515–520. 53 Provine RR, Westerman JA. Crossing the midline: limits of early eye-hand behavior. Child Dev. 1979;50:437– 441. 54 Rochat P. Self-sitting and reaching in 5- to 8-month-old infants: the impact of posture and its development on early eye-hand coordination. J Mot Behav. 1992; 24:210 –220. 55 Thelen E, Spencer J. Postural control during reaching in young infants: a dynamic systems approach. Neurosci Biobehav Rev. 1998;22:507–514. 56 Savelsbergh GJ, van der Kamp J. The effect of body orientation to gravity on early infant reaching. J Exp Child Psychol. 1994; 58:510 –528. 57 Hopkins B, Ronnqvist L. Facilitating postural control: effects on the reaching behavior of 6-month-old infants. Dev Psychobiol. 2002;40:168 –182.

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58 Von Hofsten C. Structuring of early reaching movements: a longitudinal study. J Mot Behav. 1991;23:280 –292. 59 van der Fits IB, Klip AW, van Eykern LA, Hadders-Algra M. Postural adjustments during spontaneous and goal-directed arm movements in the first half year of life. Behav Brain Res. 1999;106:75–90. 60 d’Avella A, Saltiel P, Bizzi E. Combinations of muscle synergies in the construction of a natural motor behavior. Nat Neurosci. 2003;6:300 –308. 61 Konczak J, Borutta M, Dichgans J. The development of goal-directed reaching in infants, II: learning to produce task-adequate patterns of joint torque. Exp Brain Res. 1997;113:465– 474. 62 Bhat AN, Heathcock JC, Galloway JC. Toyoriented changes in hand and joint kinematics during the emergence of purposeful reaching. Infant Behav Dev. 2005;28: 445– 465. 63 Bhat AN, Galloway JC. Toy-oriented changes during early arm movements: hand kinematics. Infant Behav Dev. 2006;29:358 –372. 64 Bhat AN, Lee HM, Galloway JC. Toyoriented changes in early arm movements, II: joint kinematics. Infant Behav Dev. 2007;30:307–324.

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65 Campbell SK, Kolobe THA, Osten ET, et al. Construct validity of the Test of Infant Motor Performance. Phys Ther. 1995;75: 585–596. 66 Maziero Barbosa V, Campbell SK, Berbaum M. Discriminating Infants from different developmental outcome groups using the Test of Infant Motor Performance (TIMP) item responses. Pediatr Phys Ther. 2007; 19:28 –39. 67 Lee HM, Bhat AN, Scholz JP, Galloway JC. Toy-oriented changes during early arm movements, IV: shoulder-elbow coordination. Infant Behav Dev. 2008;31:447– 469. 68 Scholz JP, Schoner G. The uncontrolled manifold concept: identifying control variables for a functional task. Exp Brain Res. 1999;126:289 –306. 69 Yang JF, Scholz JP, Latash ML. The role of kinematic redundancy in adaptation of reaching. Exp Brain Res. 2007;176:54 – 69.

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Research Report

Factors Influencing Information Seeking by Physical Therapists Providing Stroke Management Nancy M. Salbach, Sara J.T. Guilcher, Susan B. Jaglal, David A. Davis

Background. Searching and reading the research literature are essential activities for enhancing the use of research and optimizing the quality of physical therapist practice. Objectives. The objectives of this study were to identify practitioner, organization, and research characteristics that are associated with searching or reading the research literature among physical therapists involved in stroke management.

Design. A cross-sectional study design was used. Methods. A survey questionnaire was mailed to 1,155 physical therapists in neurological practice in Ontario, Canada. Therapists who treated people with stroke were eligible to participate.

Results. Of the 334 eligible respondents, 270 (80.8%) completed a questionnaire. Among participants with complete data, 37.7% of 265 participants conducted online literature searches and 73.3% of 266 participants read the research literature 2 or more times in a typical month. The following factors were associated with conducting online literature searches 2 or more times in a typical month: participation in research, self-efficacy for implementing evidence-based practice (EBP), being male, perceived facility support of research use, and Internet access to bibliographic databases at work. The following factors were associated with reading the literature 2 or more times in a typical month: participation in research, EBP self-efficacy, membership in a professional organization, perceived facility support of research use, and positive perceptions about the usefulness of the research literature and the relevance of walking interventions evaluated in the stroke rehabilitation research literature. A positive association between searching and reading was observed (odds ratio⫽16.5, 95% confidence interval⫽5.8 – 47.1).

N.M. Salbach, PhD, MSc, BScPT, BSc (Physiology), is Assistant Professor, Department of Physical Therapy, University of Toronto, 160-500 University Ave, Toronto, Ontario, Canada M5G 1V7. Address all correspondence to Dr Salbach at: nancy.salbach@utoronto. ca. S.J.T. Guilcher, MSc, MScPT, BSc, is a PhD candidate, Department of Health, Policy, Management, and Evaluation, University of Toronto. S.B. Jaglal, PhD, MSc, BSc, is Associate Professor, Department of Physical Therapy, University of Toronto. D.A. Davis, MD, FCFP, CCFP, FRCPC (hon), is Senior Director, Continuing Education & Performance Improvement, Association of American Medical Colleges, Washington, DC. [Salbach NM, Guilcher SJT, Jaglal SB, Davis DA. Factors influencing information seeking by physical therapists providing stroke management. Phys Ther. 2009;89: 1039 –1050.] © 2009 American Physical Therapy Association

Limitations. The cross-sectional design limited inferences of causality. Conclusion. Despite a low frequency of searching, the majority of the participating therapists acquired and read the research literature on a monthly basis. Online searching and reading are closely linked behaviors. Modifiable practitioner characteristics, including self-efficacy for implementing EBP and participation in research, appear to be key determinants of EBP. Post a Rapid Response or find The Bottom Line: www.ptjournal.org October 2009

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vidence-based practice (EBP) is a relatively new concept that Sackett et al defined in 1996 as “integrating individual clinical expertise with the best available external clinical evidence from systematic research.”1(p71) Academic physical therapy programs2–5 have embraced EBP and strive to prepare students with the knowledge and skills needed to undertake the steps of EBP. These steps include expressing questions that arise from clinical practice in a searchable format; effectively finding the best evidence to address the question, a step that may require an online literature search; and critically appraising the evidence for validity, impact, and applicability to the clinical question.6,7 After considering the research evidence, clinical expertise, and the patient’s needs and preferences, the practitioner decides on a course of action. Continual evaluation of the effect of clinical practice is considered the final step in the EBP process.1,6 –9 Although physical therapists have indicated that the application of EBP is necessary and improves the quality of patient care,10,11 many do not identify research evidence as a primary source of information to guide clinical practice.11–16 Underuse of research evidence may be attributable to challenges in undertaking the steps of EBP that precede the use of research, including searching and appraising the research literature.7 Effectively searching the research literature is an EBP

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on August 6, 2009, at www.ptjournal.org.

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activity that requires considerable knowledge and skills given the extensive Web-based resources currently available to inform physical therapist practice.17–22 Recent reports indicated that physical therapists who graduated a minimum of 15 years ago are less likely to have learned the foundations of EBP in their academic programs and are more likely to report lower levels of confidence in performing EBP activities, such as searching and appraising the research literature, than therapists who graduated recently.10,11 Furthermore, health care professionals identify lack of time as the most important barrier to updating clinical practice with new knowledge.10,11,15,23–25 It is important to know whether therapists are finding time to read the professional literature, given that reading is a prerequisite to appraisal and to appropriate application of research findings to clinical practice. For the nursing literature, time spent using the Internet and time spent reading research articles have been identified as correlates of the use of research,26,27 highlighting the value of determining what motivates physical therapists to engage in these activities. Few studies have investigated the extent to which physical therapists are searching and reviewing the research literature. A 2002 survey11 of 488 American physical therapists showed that the majority of the respondents rarely conducted online literature searches. As many as 65% of the respondents reported searching the literature with MEDLINE or other bibliographic databases only one time or not at all in a typical month.11 Compared with the rate of searching, the rate of reading the professional literature was higher; 66% of American physical therapists reported reading the professional literature 2 to 5 times in a typical month.11 In comparison, a survey of 206 Canadian physical therapists

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working in neurological practice showed that 54% reported reading the professional literature on a monthly basis and that 21% reported reading on a weekly basis.13 The samples in both studies included members of national professional associations that provided peerreviewed physical therapy journals as part of their memberships. This benefit may have led to a rate of reading higher than that in the general population of physical therapists. The factors influencing physical therapists to search and review the research literature are largely unknown. Evaluations to date have targeted a limited number of variables, including practice and work setting characteristics (eg, number of patients seen, hours worked per day, number of physical therapists, and access to sources of evidence11) and practitioner characteristics (eg, time since graduation13). None of these variables has been related to conducting literature searches, whereas Internet access to bibliographic databases at home has been associated with reading the research literature more than one time in a typical month.11 After a systematic review of individual determinants of the use of research among nurses, Estabrooks et al28 recommended that future studies focus not only on practitioner characteristics but also on influential attributes of the research and of the organization. Given that physical therapists’ engagement in EBP may be influenced by a complex set of variables, a conceptual framework is needed to guide the selection of variables for study and the interpretation of study findings in this field of investigation. Several researchers have attempted to classify factors that influence the rate of adoption of an innovation with the goal of understanding the level at which intervention is needOctober 2009

Information Seeking by Physical Therapists Providing Stroke Management ed.29 –31 Berwick29 provided a clear and broad classification of factors as characteristics of the adopter (ie, the practitioner), the organization (ie, the practice setting), or the innovation (ie, the research literature). In addition, leading knowledge translation researchers advocated the use of theoretical frameworks of behavioral change to guide investigations of processes, such as EBP, that require health care professionals to acquire knowledge and potentially modify clinical practice.28,32–35 Self-efficacy theory36 is an internationally recognized theory that has been used to study the determinants of human behavior and to guide interventions aimed at changing behavior.37 Selfefficacy beliefs, defined as judgments of one’s ability to organize and execute given types of performances,38 are considered to have a primary influence on decisions to engage in or avoid particular activities or settings. For example, a clinician who wants to answer a clinical question by using research evidence is unlikely to undertake an online literature search if he or she believes his or her ability to conduct a search is poor. Although self-efficacy for implementing EBP may be an important predictor of engagement in EBP activities, this notion has not been examined to date. An examination of physical therapists’ engagement in the initial steps of EBP, such as searching online bibliographic databases and reading the research literature, is a prerequisite to understanding the use of research. However, little research has been conducted to investigate physical therapists’ engagement in EBP activities. Studies to date have failed to evaluate a comprehensive set of variables, including characteristics of the physical therapist, the organization, and the research literature, or to use theories of behavioral change to guide the selection of variables and the interpretation of findings. A baseOctober 2009

line is needed to understand the extent to which physical therapists are performing steps of EBP that are a prerequisite to research use. Identifying the factors that influence engagement in searching and reading the research literature will enhance understanding of the demographics and practice environments of therapists who undertake these activities and what actions can be taken to enhance the performance of these activities in the clinical setting. We recently conducted a mail survey and applied Berwick’s framework29 to identifying barriers to EBP at the practitioner, organization, and research levels and to measuring the performance of EBP activities among physical therapists who deliver services to people with stroke.10 The survey questionnaire included a new scale developed to measure selfefficacy for implementing EBP, defined as the judgment of one’s ability to organize and execute the steps of EBP.10 Stroke rehabilitation is an ideal practice domain in which to study EBP, given existing evidence that the implementation of findings from high-quality research in postacute rehabilitation after stroke has been associated with both functional recovery and patient satisfaction.39,40 Data from the mail survey were used in the present study to identify practitioner, organization, and research characteristics that are associated with searching and reading the research literature among physical therapists involved in stroke management. A secondary objective was to explore the relationship between searching and reading the research literature.

Method Study Design Data were available from a crosssectional mail survey that we conducted to investigate barriers to implementing EBP; findings related to practitioner and organization barriVolume 89

ers have been published.10 For the survey, we used a modified Dillman41 3-step approach to mailing to maximize the response rate. We mailed the survey questionnaire in May 2005 and sent a thank-you/ reminder postcard 3 weeks later. The questionnaire was mailed a second time to nonrespondents at the end of June 2005. For the present study, we analyzed data collected from questionnaire items measuring characteristics of the practitioner and the organization, physical therapists’ perceptions of the stroke rehabilitation research literature, and frequencies of conducting online literature searches and reading the research literature. Participants and Sampling Physical therapists who were in clinical practice and who provided physical therapy services to adults with stroke were considered eligible to participate. We sampled potential participants from a mailing list obtained from the College of Physiotherapists of Ontario (the provincial regulatory body); we searched for registrants who were in clinical practice and who had specified neurology as an area of practice at their primary or secondary workplace. We excluded registered therapists who had indicated pediatrics as a practice area. We mailed the questionnaires and asked the therapists to indicate in the first item of the questionnaire whether they provided services to people with stroke. Those who did not were considered ineligible and were asked to leave the rest of the questionnaire blank and to return it in a prestamped envelope provided with the questionnaire. Therapists who were eligible but who did not wish to participate also were asked to return the questionnaire with the remaining items unanswered to indicate that they chose not to participate.

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Information Seeking by Physical Therapists Providing Stroke Management Questionnaire We developed a questionnaire to identify barriers to implementing EBP at the practitioner, organization, and research levels and to measure the performance of EBP activities. We present the questionnaire items and corresponding response options, conceptually grouped into blocks, in the Appendix to make the analysis transparent and to enable replication in future research. Practitioner blocks used in the analysis included education about EBP (3 items), attitudes toward and beliefs about EBP (7 items), interest (2 items) and perceived role (3 items) in engaging in EBP, sociodemographic characteristics (age, sex, highest degree earned, and years in clinical practice), and professional activities (4 items). An additional practitioner characteristic was selfefficacy for performing EBP activities, which was evaluated with a new 12-item scale that we described previously.10 Each item in the scale presents an activity considered integral to the process of EBP; the items include searching, appraising, and applying the research literature with a patient’s needs and treatment preferences in mind.1,7–9 Participants were asked to rate their level of confidence in their ability to perform each activity by using an 11-point scale ranging from 0% (cannot do at all) to 100% (certain can do). Itemlevel ratings were averaged to determine the total score (range⫽0%– 100%), which was analyzed in the present study. The internal consistency estimated with the Cronbach alpha test for data collected in the present study (n⫽261) was .90; this value met the level required for the use of the scale at the individual level.42 Organization blocks included perceived organization and peer support for EBP (2 items), organization resources to promote EBP (6 items), and practice and work setting characteristics (7 items).10

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We evaluated perceptions of the stroke rehabilitation research literature by using 4 items that asked participants about their perceptions of the relevance and clarity of existing research literature in guiding the treatment of walking limitations. We specified research related to walking rehabilitation because walking is an essential activity that is commonly limited after stroke43 and because there is a substantial body of literature devoted to walking rehabilitation. Physical therapists’ judgments about the relevance of this specific literature rather than the entire body of literature about stroke were expected to provide useful feedback to the research community. To gauge the performance of searching and reading the research literature, we asked the participants to indicate how often in a typical month they searched online bibliographic databases, such as MEDLINE, and how often they read or reviewed research literature related to their clinical practice by using the following response options: up to 1 time, 2 to 5 times, 6 to 10 times, 11 to 15 times, and 16 or more times.11 The majority of the items were statements with which the respondents indicated their level of agreement by using a 5-point Likert scale with the following response options: “strongly disagree,” “disagree,” “neutral,” “agree,” and “strongly agree.” Response options for items relating to the availability of organization resources were “yes,” “no,” and “do not know.” We pilot tested the questionnaire with 3 physical therapists delivering health care services to people with stroke in acute care or rehabilitation hospital settings; these therapists verified the readability and relevance of the questionnaire. We made minor revisions, such as shortening the questionnaire and rewording se-

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lected items to enhance clarity, on the basis of their feedback. Statistical Methods We used descriptive statistics, including frequencies and percentages for categorical variables and means, standard deviations, and ranges for variables rated on a continuous scale, to summarize participants’ responses to questionnaire items. Logistic regression then was used to examine relationships between practitioner, organization, and research characteristics (ie, independent variables) and each of the 2 dependent variables (ie, frequency of searching online bibliographic databases and frequency of reading the research literature). Considering the large number of independent variables, we first modeled each subgroup or block of independent variables (outlined in the Appendix) separately with each dependent variable.44 Each independent variable that was significantly associated with the dependent variable within each block (ie, 95% confidence interval [CI] excluded 1) was carried forward to the final multivariable model.44 Before conducting logistic regression, we recategorized the independent variables rated with a Likert scale to obtain binary variables.11 For positively worded statements, we collapsed the “strongly agree” and the “agree” categories to form an “agree” category and combined the “neutral,” “disagree,” and “strongly disagree” categories to form a “disagree” category. For negatively worded items, we collapsed the “strongly disagree” and “disagree” categories to form a “disagree” category and combined the “neutral,” “agree,” and “strongly agree” categories to form an “agree” category. For items with response categories of “yes,” “no,” and “do not know,” we pooled the “no” and “do not know” categories on the basis of the assumption that the effect of not October 2009

Information Seeking by Physical Therapists Providing Stroke Management knowing about the availability of a resource, for example, would be similar to the effect of not having the resource.

ine the relationship between the frequency of searching and the frequency of reading the research literature in a typical month.

Categories of demographic variables with low cell counts also were collapsed before we conducted logistic regression to obtain stable estimates of associations.44 Participation in research, initially expressed as the percentage of work time spent on research activities, was transformed into a binary variable (0%⫽no, 1%– 100%⫽yes) because the responses were skewed toward lower percentages.

Consent was considered implied for physical therapists who returned a completed questionnaire. Data were analyzed with SAS version 9.1.*

Before examining the relationship between the frequency of searching and the frequency of reading the research literature and in preparation for logistic regression, we collapsed the response categories for these variables to form a dichotomous scale of up to 1 time and 2 or more times in a typical month because of the low rate of endorsement of the higher-frequency categories. We reported odds ratios (ORs) and associated 95% CIs from logistic regression for significant associations observed within each block of items and for all variables in the final multivariable model. We verified the assumption of a linear relationship between EBP self-efficacy and the logit of each dependent variable and ruled out multicollinearity by examining the variance inflation factor.44 For each regression model, we reported the Hosmer-Lemeshow statistic to indicate the goodness of fit (a nonsignificant test result indicates good fit) and the C statistic to indicate the discriminative power of the model.44 For the C statistic, a value between .5 and 1.0 is desired, and a higher value reflects a better ability of the model to discriminate participants who search or read the research literature at different frequencies.44 Finally, logistic regression was used to examOctober 2009

Results The questionnaire was mailed to 1,155 physical therapists. A total of 702 therapists returned a questionnaire, and of these respondents, 334 (47.6%) were eligible to participate in the study. Of the eligible respondents, 64 (19.2%) chose not to participate and 270 (80.8%) completed a questionnaire. Analyses were conducted with data from this sample of 270 physical therapists. Table 1 shows the characteristics of the respondents and their practice settings. The respondents were between 23 and 68 years old (X⫽40 years, SD⫽10 years). The percentages of respondents who were women, who held a bachelor’s degree as the highest degree obtained, and who had more than 15 years of practice experience were 88.8%, 76.9%, and 45.4%, respectively. The percentages of participants who spent 0% and 1% to 5% of their work time on research activities were 67.9% and 23.9%, respectively. The most frequently cited workplaces were a teaching hospital (67.3%),10 an urban setting (60.9%),10 and an acute care hospital (39.6%). Table 2 shows the frequencies at which the respondents reported searching or reading the research literature in a typical month. The percentages of physical therapists who reported searching bibliographic databases up to 1 time and 2 to 5 times per month were 62.3% and 32.8%, * SAS Institute Inc, PO Box 8000, Cary, NC 27511.

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respectively. The percentages of respondents who reported reading the literature up to 1 time and 2 to 5 times per month were 26.7% and 56.0%, respectively. Factors that were associated with searching online bibliographic databases 2 or more times in a typical month in block regression modeling included being male, participation in research, self-efficacy for implementing EBP, perceived facility support of the use of research, and Internet access to bibliographic databases at work. Table 3 shows the block ORs and final model ORs for these factors. In the multivariable model, EBP self-efficacy had the largest OR; we found that physical therapists with high ratings of EBP self-efficacy were 4 times more likely than peers who rated their self-efficacy 30% lower to search the research literature 2 or more times in a typical month (OR⫽4.0, 95% CI⫽2.0 –7.9) after adjustment for the effects of sex, research participation, perceived facility support of research use, and Internet access to databases at work. Factors that were independently associated with reading the research literature 2 or more times in a typical month in block regression modeling included membership in a professional physical therapy organization, research participation, EBP selfefficacy, perceived facility support of research use, and perceptions that literature findings are useful in daily practice and that walking interventions evaluated in the research literature are relevant to clinical practice. Table 4 shows the block ORs and final model ORs for these factors. Membership in a professional organization had the largest OR; we found that physical therapists with such a membership were 3.5 times more likely than nonmembers to read the research literature 2 or more times in a typical month (OR⫽3.5, 95% CI⫽1.7–7.3) after adjustment for the Number 10

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Information Seeking by Physical Therapists Providing Stroke Management Table 1.

effects of the other variables in the model.

Participant and Practice Characteristics Characteristic

n

%

20–29

40

14.9

30–39

93

34.7

40–49

75

28.0

ⱖ50

60

22.4

Age (y)

Sex Male

30

11.2

239

88.8

30

11.4

203

76.9

8

3.0

23

8.7

⬍5

40

14.9

5–10

59

21.9

Female Highest degree earned Certificate or diploma Bachelor’s degree Professional master’s degree Applied or research master’s degree Years in practice

11–15

48

17.8

122

45.4

Yes

196

73.4

No

71

26.6

⬎15 Member of professional organization

Percentage of time spent on research activities 0

182

67.9

1–5

64

23.9

6–10

16

6.0

6

2.3

28

10.4

11–100 Hours worked per week ⬍20 20–30

51

19.0

31–40

154

57.5

35

13.1

⬎40 Type of facility Acute care hospital Rehabilitation hospital

16.0

13

4.9

Complex continuing care

10

3.7

3

1.1

Community care access center

14

5.2

Home visiting agency

17

6.3

Private practice or clinic

28

10.5

University or educational institution Other

f

39.6

43

Long-term care

Community health center

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1

0.4

33

12.3

In Tables 3 and 4, the ORs associated with EBP self-efficacy relate to the odds of conducting either online searching or reading for participants who differed in EBP self-efficacy scores by, on average, 10%, 20%, or 30%. The final multivariable models demonstrated good fit, as indicated by nonsignificant Hosmer-Lemeshow test results and discriminative ability reflected by C statistic values above .75. The assumption of linearity for self-efficacy, the only continuous variable modeled in logistic regression, was verified. Table 5 shows the descriptive crosstabulation of the frequency of searching and the frequency of reading the research literature in a typical month. The logistic regression analysis revealed a significant and positive association between these 2 variables; we found that physical therapists who searched online bibliographic databases 2 or more times in a typical month were 16.5 times more likely than those who searched up to 1 time in a typical month to read the research literature 2 or more times in a typical month (OR⫽16.5, 95% CI⫽5.8 – 47.1).

Discussion The present study provides baseline rates of searching and reading the research literature and highlights factors that are associated with these important EBP activities among Canadian physical therapists in stroke rehabilitation practice. The results indicated that the majority of the therapists rarely searched the research literature by using MEDLINE or other bibliographic databases on a monthly basis. However, the reported frequency of reading the research literature was higher; more than half of the respondents (56.0%) October 2009

Information Seeking by Physical Therapists Providing Stroke Management Table 2. Frequencies of Searching and Reading Research Literature No. (%) Responding n

16 Times

as the stroke rehabilitation research literature (ie, relevance of investigated walking interventions to clinical practice) may influence the steps leading to research use among physical therapists. These findings directly support Berwick’s classification of factors influencing the dissemination of innovations.29 In addition to Berwick’s framework,29 the conceptual framework of self-efficacy theory38 was effective in guiding the selection of variables influencing practitioner behavior in the context of EBP. Self-efficacy for implementing EBP was associated with self-reported performance of both online searching and reading the research literature to inform physical therapist practice after

The block modeling phase of the present study showed that characteristics not only of the practitioner (ie, sex, self-efficacy, research participation, membership in a professional organization, and general attitude toward research) but also of the organization (ie, Internet access and facility support of research use) as well

Table 3. Factors Associated With Searching the Research Literature 2 or More Times in a Typical Month Odds Ratioa (95% Confidence Interval) Factor

Level

Block

Final Modelb

Male sex

Female Male

3.9 (1.7–9.0)

Participation in research

No

Reference

Yes

3.1 (1.8–5.4)

2.7 (1.5–4.9)

Evidence-based practice self-efficacy

10% difference

1.7 (1.4–2.1)

1.6 (1.3–2.0)

20% difference

2.9 (1.9–4.3)

2.5 (1.6–4.0)

30% difference

4.9 (2.6–9.0)

4.0 (2.0–7.9)

No

Reference

Yes

2.3 (1.2–4.4)

No

Reference

Yes

3.3 (1.4–7.9)

Perceived facility support of use of research

Internet access to bibliographic databases at work

Reference 3.3 (1.4–8.0)

1.3 (0.6–2.8)

2.0 (0.8–4.8)

Ratio of the odds of searching ⱖ2 times compared with searching ⱕ1 time in a typical month after adjustment for the effects of the other variables in the model. b Hosmer-Lemeshow test, P⫽.65; C statistic⫽.77. a

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Information Seeking by Physical Therapists Providing Stroke Management Table 4. Factors Associated With Reading the Research Literature 2 or More Times in a Typical Month Odds Ratioa (95% Confidence Interval) Factor

Level

Block

Final Modelb

Membership in professional organization

No Yes

3.0 (1.6–5.5)

Participation in research

No

Reference

Yes

3.4 (1.6–7.1)

2.4 (1.1–5.5)

Evidence-based practice self-efficacy

10% difference

1.6 (1.3–2.0)

1.5 (1.2–1.9)

20% difference

2.7 (1.8–4.2)

2.2 (1.3–3.6)

30% difference

4.4 (2.3–8.5)

3.2 (1.5–6.7)

No

Reference

Yes

2.7 (1.5–4.9)

Literature findings perceived as being useful in daily practice

No

Reference

Yes

2.8 (1.3–5.7)

Walking interventions evaluated in research perceived as being relevant to practice

No

Reference

Yes

3.0 (1.4–6.4)

Perceived facility support of use of research

Reference 3.5 (1.7–7.3)

2.0 (1.0–4.1)

2.0 (0.9–4.3)

2.9 (1.3–6.6)

Ratio of the odds of reading ⱖ2 times compared with reading ⱕ1 time in a typical month after adjustment for the effects of the other variables in the model. b Hosmer-Lemeshow test, P⫽.29; C statistic⫽.81. a

stroke. The strength of the relationship between self-efficacy and each dependent variable was comparable, as reflected by the similar magnitudes of the unadjusted ORs in the models (Tabs. 3 and 4). For example, therapists with a higher level of EBP self-efficacy were 4.9 times more likely (95% CI⫽2.6 –9.0) to search online and 4.4 times more likely (95% CI⫽2.3– 8.5) to read the research literature 2 or more times in a typical month than peers with selfefficacy ratings that were 30% lower. These findings support the primary tenet of self-efficacy theory: that an individual’s judgment of his or her ability to perform a specific task in-

fluences his or her decision to engage in that task.36 The causality of the relationships between EBP self-efficacy and searching and reading the research literature in the present study cannot be inferred because the data were collected at one point in time; however, the results provide direction for future prospective investigations of these variables. These findings are particularly relevant to the field of knowledge translation and, specifically, EBP because self-efficacy is a modifiable variable. Researchers have described how strategies for increasing self-efficacy beliefs, includ-

ing social modeling (observing others), verbal persuasion (receiving positive feedback on ability), emotional arousal (positive physiological states), and mastery experiences,36 can be incorporated into a continuing education event; researchers also have used measures of self-efficacy to capture the effects of the event among physicians.45,46 This work45,46 has direct application to the translation of knowledge and EBP in physical therapy. The percentage of respondents searching up to 1 time in a typical month in the present study (62.3%) was similar to that documented

Table 5. 2 ⫻ 2 Table Showing the Relationship Between the Frequency of Searching Online Bibliographic Databases and the Frequency of Reading the Research Literature in a Typical Month (n⫽262) No. (% of Total) Reading the Research Literature

Searching Online Bibliographic Databases

2 Times/mo

Total

ⱕ1 time/mo

66 (25.2)

96 (36.6)

162

ⱖ2 times/mo

4 (1.5)

96 (36.6)

100

Total

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262

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Information Seeking by Physical Therapists Providing Stroke Management among American physical therapists (65%) with the same question and response scale.11 The findings show that this low frequency of searching may be attributable, in part, to the availability of Internet access to online bibliographic databases at work that was lacking for 20.0% of the survey respondents. It was not related in the current study, however, to physical therapists’ perceptions of their role in performing this activity, even though 50.6% of the respondents reported they were neutral or disagreed that physical therapists should be responsible for conducting their own literature reviews to answer their clinical questions.10 Although 62.3% of the therapists rarely conducted online literature searches, the majority of them read the research literature 2 to 5 times in a typical month; these data raise the question of how these therapists were accessing the research literature. The findings of a qualitative study that we conducted subsequent to this survey help to answer this question. During semistructured interviews with 23 survey respondents, therapists described how they delegated the task of searching the research literature to hospital librarians, research therapists, younger colleagues, or physical therapist students.47 Some therapists delegated this task because of a lack of searching skills, and others delegated this task to save time. Delegating tasks may explain why therapists reported reviewing the research literature at a higher frequency than searching. A related finding is that male therapists reported conducting online searches more frequently than female therapists, although the rates of reading the research literature were comparable for men and women. This finding may be explained by previous research showing that, in general, men seek information from the Internet more often than women48 and report finding information October 2009

online with less effort than women.49 Studies investigating physicians’ use of personal digital assistants in clinical practice have found that men are more likely than women to use these electronic tools.50,51 Interestingly, the percentage of respondents who reported reading the research literature 2 or more times in a typical month (73.3%) in the present study was lower than that of American physical therapists (82%) responding to the same questionnaire item.11 Our finding that membership in a professional organization was linked to a higher frequency of reading the research literature helps to explain this discrepancy. Therapists in the American study may have reported reading more frequently than those in the present study because they were all members of the national professional association that provides members with the peer-reviewed scientific journal Physical Therapy, which is published monthly. Only 73.4% of the participants in the present study were members of a professional association at the national or provincial level. Members of the national professional association are provided with the peer-reviewed scientific journal Physiotherapy Canada, which is published 4 times per year—less frequently than its American counterpart. Thus, membership in a professional association may have played a role in facilitating the review of published peer-reviewed research, although it does not guarantee that the articles read were relevant to stroke rehabilitation practice. Another notable finding was the emergence of involvement in research activities as a correlate of searching and reading the research literature. Almost 70% of the participants reported spending none of their work time on research activiVolume 89

ties; approximately a third of the respondents reported spending a small proportion (1%–10%) of their work time on some kind of research activity. This research activity was coupled with a greater likelihood of conducting online searches and reading the research literature. Previous examinations of research participation among nurses showed that this factor is a predictor of research use in some studies but not in others.28,52 The survey questionnaire used in the present study was not designed to identify the type of research activity performed; thus, we are unable to shed light on which work-related research activities may promote EBP activities among physical therapists. Further investigation of the influence of this factor in the context of EBP is needed. Although factors that were associated with searching and reading and that emerged from the block modeling phase of the present study represented characteristics of the practitioner, the organization, and the research literature, variables that remained significantly related to these behaviors in the final multivariable model were largely modifiable individual characteristics, including membership in a professional organization, research participation, and self-efficacy. Findings related to membership in a professional organization may indicate that the benefits of membership, such as access to a journal subscription, promote reading the research literature; alternatively, membership may simply represent a behavior that is commonly coupled with a higher rate of participation in EBP activities. The crosssectional nature of the design of the present study prevents clear interpretation of this finding and suggests an area for future research. With respect to research participation, a better understanding of which research activities facilitate searching and reading the research literature is necNumber 10

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Information Seeking by Physical Therapists Providing Stroke Management essary to inform recommendations for action. The findings of the present study also indicate that educational interventions designed to build capacity to implement EBP may be effective in increasing the frequencies of searching and reading the research literature if they incorporate mechanisms for improving self-efficacy. Finally, the results of the present study suggest that physical therapists’ perceptions of the relevance of the specific research literature that informs their clinical practice influence whether they read or review that literature. Limitations Some limitations of the study design should be considered in the interpretation of the results presented here. This investigation was a crosssectional study; thus, causality of the associations observed cannot be assumed. Moreover, respondents likely had a greater interest in and were more engaged in EBP than nonrespondents. Coupled with the fact that participants may have wished to provide socially desirable responses, we may have overestimated the frequencies of searching and reading the research literature for the population of practitioners studied. The results also apply primarily to the Canadian context and would require replication in other countries because of differences in health care systems and professional physical therapy programs. In addition, measurement of practitioner behavior in the context of EBP is challenging. In the present study, we measured the frequencies of searching and reading the research literature in a typical month. Whether the rating scale that we used is reflective of best practice in EBP is uncertain. A therapist with efficient search skills may not need to search at a high frequency in a typical month and may initiate a search only when a knowledge gap 1048

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that can be addressed with the research literature arises. Despite these limitations, time spent using the Internet and time spent reading research articles have been identified as correlates of the use of research among nurses26,27; these data support the important roles of these EBP activities because similar relationships are likely to exist for physical therapists. The strengths of our research are the use of conceptual and behavioral change frameworks to identify potentially influential variables related to engagement in EBP activities. Participants were sampled from a provincial registry of physical therapists; this fact supports the generalizability of the results for Canadian physical therapists in stroke rehabilitation practice.

Conclusion The findings of the present study suggest that although the majority of physical therapists in stroke rehabilitation practice rarely search online bibliographic databases for research, they access research articles in other ways because they report reviewing the research literature at a higher frequency. Therapists who search online bibliographic databases are highly likely to read the research literature as well. The findings emphasize the importance of organizations providing environments not only to facilitate access to research both online and through memberships in professional organizations but also to promote involvement in research activities as part of physical therapists’ duties. Continuing education targeting EBP may play a vital role in boosting EBP self-efficacy. Finally, strategies that optimize the relevance to clinical practice of the interventions developed and evaluated in research have the potential to enhance the use of these interventions by clinicians.

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All authors provided concept/idea/research design. Dr Salbach, Ms Guilcher, and Dr Jaglal provided writing, data analysis, and consultation (including review of manuscript before submission). Dr Salbach provided data collection and project management. Dr Jaglal provided facilities/equipment and fund procurement for the original study. The Office of Research Ethics at the University of Toronto approved the study protocol. This article was received March 9, 2009, and was accepted May 28, 2009. DOI: 10.2522/ptj.20090081

References 1 Sackett DL, Rosenberg WM, Gray JA, et al. Evidence based medicine: what it is and what it isn’t. BMJ. 1996;312:71–72. 2 University of Toronto Physical Therapy Program. Available at: http://www. physicaltherapy.utoronto.ca/. Accessed April 30, 2009. 3 McMaster University Physical Therapy Program. Available at: http://www. mcmaster.ca/graduate/2003–2004/pt.html. Accessed May 8, 2009. 4 Duke University Doctor of Physical Therapy Program. Available at: http://dpt.duhs. duke.edu/modules/cfmdpt_home/. Accessed May 8, 2009. 5 University of Florida Doctor of Physical Therapy Program. Available at: http://pt. phhp.ufl.edu/dpt.html. Accessed May 8, 2009. 6 Straus SE, Richardson WS, Glasziou P, Haynes RB. Evidence-Based Medicine: How To Practice and Teach EBM. Edinburgh, United Kingdom: Elsevier Churchill Livingstone; 2005. 7 Guyatt GH, Haynes RB, Jaeschke RZ, et al. Users’ guides to the medical literature, XXV: evidence-based medicine—principles for applying the users’ guides to patient care. JAMA. 2000;284:1290 –1296. 8 Rappolt S. The role of professional expertise in evidence-based occupational therapy. Am J Occup Ther. 2003;57:589 –593. 9 Davidoff F, Haynes B, Sackett D, Smith R. Evidence based medicine. BMJ. 1995;310: 1085–1086. 10 Salbach NM, Jaglal SB, Korner-Bitensky N, et al. Practitioner and organizational barriers to evidence-based practice of physical therapists for people with stroke. Phys Ther. 2007;87:1284 –1303. 11 Jette DU, Bacon K, Batty C, et al. Evidencebased practice: beliefs, attitudes, knowledge, and behaviors of physical therapists. Phys Ther. 2003;83:786 – 805. 12 Jette DU, Grover L, Keck CP. A qualitative study of clinical decision making in recommending discharge placement from the acute care setting. Phys Ther. 2003;83: 224 –236.

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Information Seeking by Physical Therapists Providing Stroke Management 13 Stevenson TJ, Barclay-Goddard R, Ripat J. Influences on treatment choices in stroke rehabilitation: survey of Canadian physical therapists. Physiother Can. 2005; 57:135–144. 14 Huijbregts MPJ, Myers AM, Kay TM, Gavin TS. Systematic outcome measurement in clinical practice: challenges experienced by physiotherapists. Physiother Can. 2002;54:25–31, 36. 15 Rappolt S, Tassone M. How rehabilitation therapists gather, evaluate, and implement new knowledge. J Contin Educ Health Prof. 2002;22:170 –180. 16 Turner P, Whitfield TW. Physiotherapists’ use of evidence based practice: a crossnational study. Physiother Res Int. 1997; 2:17–29. 17 Maher CG, Moseley AM, Sherrington C, et al. A description of the trials, reviews, and practice guidelines indexed in the PEDro database. Phys Ther. 2008;88: 1068 –1077. 18 Maher CG, Sherrington C, Elkins M, et al. Challenges for evidence-based physical therapy: accessing and interpreting highquality evidence on therapy. Phys Ther. 2004;84:644 – 654. 19 Li L, Irvin E, Guzman J, Bombardier C. Surfing for back pain patients: the nature and quality of back pain information on the Internet. Spine. 2001;26:545–557. 20 Korner-Bitensky N, Roy MA, Teasell R, et al. Creation and pilot testing of StrokEngine: a stroke rehabilitation intervention Web site for clinicians and families. J Rehabil Med. 2008;40:329 –333. 21 Teasell R. Evidence-based review of stroke rehabilitation (EBRSR), edition 9. Available at: www.ebrsr.com. Accessed July 10, 2008. 22 American Physical Therapy Association. Hooked on evidence. Available at: http:// www.hookedonevidence.com/. Accessed June 18, 2009. 23 McColl A, Smith H, White P, Field J. General practitioner’s perceptions of the route to evidence based medicine: a questionnaire survey. BMJ. 1998;316:361–365. 24 Pollock AS, Legg L, Langhorne P, Sellars C. Barriers to achieving evidence-based stroke rehabilitation. Clin Rehabil. 2000; 14:611– 617. 25 Closs SJ, Lewin BJP. Perceived barriers to research utilization: a survey of four therapies. British Journal of Therapy and Rehabilitation. 1998;5:151–155.

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26 Estabrooks CA, Midodzi WK, Cummings GG, Wallin L. Predicting research use in nursing organizations: a multilevel analysis. Nurs Res. 2007;56:S7–S23. 27 Milner M, Estabrooks CA, Myrick F. Research utilization and clinical nurse educators: a systematic review. J Eval Clin Pract. 2006;12:639 – 655. 28 Estabrooks CA, Floyd JA, Scott-Findlay S, et al. Individual determinants of research utilization: a systematic review. J Adv Nurs. 2003;43:506 –520. 29 Berwick DM. Disseminating innovations in health care. JAMA. 2003;289:1969 –1975. 30 Grol R, Wensing M. What drives change? Barriers to and incentives for achieving evidence-based practice. Med J Aust. 2004;180:S57–S60. 31 Cabana MD, Rand CS, Powe NR, et al. Why don’t physicians follow clinical practice guidelines? A framework for improvement. JAMA. 1999;282:1458 –1465. 32 Ceccato NE, Ferris LE, Manuel D, Grimshaw JM. Adopting health behavior change theory throughout the clinical practice guideline process. J Contin Educ Health Prof. 2007;27:201–207. 33 Grimshaw JM, Thomas RE, MacLennan G, et al. Effectiveness and efficiency of guideline dissemination and implementation strategies. Health Technol Assess. 2004; 8(6). 34 Grimshaw JM, Eccles MP, Tetroe J. Implementing clinical guidelines: current evidence and future implications. J Contin Educ Health Prof. 2004;24(suppl 1):S31– S37. 35 Eccles M, Grimshaw J, Walker A, et al. Changing the behavior of healthcare professionals: the use of theory in promoting the uptake of research findings. J Clin Epidemiol. 2005;58:107–112. 36 Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191–215. 37 Judge TA, Jackson CL, Shaw JC, et al. Selfefficacy and work-related performance: the integral role of individual differences. J Appl Psychol. 2007;92:107–127. 38 Bandura A. Self-Efficacy: The Exercise of Control. New York, NY: W.H. Freeman; 1997. 39 Duncan PW, Horner RD, Reker DM, et al. Adherence to postacute rehabilitation guidelines is associated with functional recovery in stroke. Stroke. 2002;33: 167–177.

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40 Reker DM, Duncan PW, Horner RD, et al. Postacute stroke guideline compliance is associated with greater patient satisfaction. Arch Phys Med Rehabil. 2002; 83:750 –756. 41 Dillman DA. Mail and Internet Surveys: The Tailored Design Method. New York, NY: John Wiley & Sons Inc; 2000. 42 Nunnally JC, Bernstein IH. Psychometric Theory. New York, NY: McGraw-Hill; 1994. 43 Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995;76: 27–32. 44 Tabachnick BG, Fidell LS. Using Multivariate Statistics. Boston, MA: Allyn and Bacon; 2001. 45 Peterson ED. Measures of perceived selfefficacy as a method of evaluating educational outcomes: an introduction. CE Measure. 2006;1:35–39. 46 Peterson ED, Lulejian A, Laussucq S. Using perceived self-efficacy to measure outcomes: evaluation of a two-day course. J Outcome Meas. 2007;1:59 – 64. 47 Salbach NM, Veinot P, Rappolt S, et al. Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. Phys Ther. 2009;89:556 –568. 48 Jackson LA, Ervin KS, Gardner PD, Schmitt N. Gender and the Internet: women communicating and men searching. Sex Roles. 2001;44:363–380. 49 Ybarra M, Suman M. Reasons, assessments and actions taken: sex and age differences in uses of Internet health information. Health Educ Res. 2008;23:512–521. 50 Menachemi N, Perkins RM, van Durme DJ, Brooks RG. Examining the adoption of electronic health records and personal digital assistants by family physicians in Florida. Inform Prim Care. 2006;14:1–9. 51 Carroll AE, Christakis DA. Pediatricians’ use of and attitudes about personal digital assistants. Pediatrics. 2004;113:238 –242. 52 Tsai SL. Nurses’ participation and utilization of research in the Republic of China. Int J Nurs Stud. 2000;37:435– 444.

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Information Seeking by Physical Therapists Providing Stroke Management Appendix. Blocks of Questionnaire Items Modeled Using Logistic Regression Itemsa (Scoring for Regression Modelingb)

Block Practitioner Education in evidence-based practice (EBP) (3 items)

I learned EBP as part of academic preparation I received formal training to do literature searches I received formal training in critical appraisal of literature as part of academic preparation

Attitude toward EBP (7 items)

EBP is necessary to physical therapist practice Literature or research findings are useful in daily practice EBP improves quality of care EBP helps me make decisions about patient care EBP places an unreasonable demand on physical therapists EBP does not account for patients’ preferences There is a definite divide between research and practice

Interest in EBP (2 items)

I need to increase use of evidence in my daily practice

Perceived role in EBP (3 items)

Physical therapists should be responsible for conducting their own literature reviews

I am interested in improving my EBP skills Physical therapists should be responsible for critical appraisal Physical therapists should be responsible for interpreting whether research applies to their patients Age (20–29, 30–39, 40–49, or ⱖ50 y)

Sociodemographic characteristics

Sex Highest degree earned (diploma or certificate, bachelor’s degree, or graduate degree) Years in clinical practice (⬍5, 5–10, 11–15, or ⬎15) Professional activities

Membership in professional organization (“no” or “yes”) Spend work time participating in research (“no” or “yes”) Percentage of work time spent on patient care (0%–75% or ⬎75%) I am a clinical instructor (“no” or “yes”)

Self-efficacy for implementing EBP (12-item scale)

Self-efficacy for implementing EBP (0%–100%)

Organization Organization and peer support for EBP (2 items)

Facility supports use of current research in practice

Organization resources (6 items)

Access to a resource person (“no or do not know” or “yes”)

Colleagues are skeptical of new EBP Facility provides money for continuing education (“no or do not know” or “yes”) Access to Internet and databases at facility (“no or do not know” or “yes”) Access to printed journals at facility (“no or do not know” or “yes”) Facility mandates use of research in practice (“no or do not know” or “yes”) Facility provides protected time to search literature (“no or do not know” or “yes”) Practice and work setting characteristics (7 items)

I work in a multidisciplinary team (“no” or “yes”) I work at a teaching institution (“no” or “yes”) Hours worked per week (⬍20, 20–30, 31–40, or ⬎40) Patients seen per day (1–10, 11–15, or ⬎15) Location of practice setting (urban, suburban, or rural) Type of facility or setting (acute care, rehabilitation or complex continuing care, or community) Full-time physical therapists in facility (⬍5, 5–10, 11–20, or ⬎20)

Perceptions about research (4 items)

Randomized controlled trial evidence is lacking to support most of the interventions I use to enhance walking ability Research evaluating walking interventions can be easily applied to individual patients Walking interventions evaluated in research are relevant to my clinical practice Research is clear about which therapies will enhance walking capacity in each phase of recovery after stroke

a

See Salbach et al10 for original item wording. EBP⫽evidence-based practice. Unless otherwise indicated, all items were rated with a Likert scale of agreement and were recategorized for regression as described in the ⬙Statistical Methods⬙ section of the text. b

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Research Report L.J.M. Valent, PhD, is Occupational Therapist and Senior Researcher, Department of Research and Development/Occupational Therapy, Heliomare Rehabilitation Centre, Relweg 51, 1949 EC, Wijk aan Zee, the Netherlands. Address all correspondence to Dr Valent at: [email protected].

Effects of Hand Cycle Training on Physical Capacity in Individuals With Tetraplegia: A Clinical Trial Linda J.M. Valent, Annet J. Dallmeijer, Han Houdijk, Hans J. Slootman, Thomas W. Janssen, Marcel W.M. Post, Lucas H. van der Woude

Background. Regular physical activity is important for people with tetraplegia to maintain fitness but may not always be easily integrated into daily life. In many countries, hand cycling has become a serious option for daily mobility in people with tetraplegia. However, little information exists regarding the suitability of this exercise mode for this population. Objective. The purpose of this study was to evaluate the effects of a structured hand cycle training program in individuals with chronic tetraplegia.

Design. Pretraining and posttraining outcome measurements of physical capacity were compared.

Setting. Structured hand cycle interval training was conducted at home or in a rehabilitation center in the Netherlands.

Participants. Twenty-two patients with tetraplegia (American Spinal Injury Association Impairment Scale classification A-D) at least 2 years since injury participated. Intervention. The intervention was an 8- to 12-week hand cycle interval training program.

Measures. Primary outcomes of physical capacity were: peak power output ˙ O2peak), as determined in hand cycle peak (POpeak) and peak oxygen uptake (V exercise tests on a motor-driven treadmill. Secondary outcome measures were: peak muscle strength (force-generating capacity) of the upper extremities (as assessed by handheld dynamometry), respiratory function (forced vital capacity and peak expiratory flow) and participant-reported shoulder pain.

Results. Significant improvements following a mean of 19 (SD⫽3) sessions of hand cycle training were found in POpeak (from 42.5 W [SD⫽21.9] to 50.8 W [SD⫽25.4]), ˙ O2peak (from 1.32 L䡠min⫺1 [SD⫽0.40] to 1.43 L䡠min⫺1 [SD⫽0.43]), and mechanical V efficiency, as reflected by a decrease in submaximal oxygen uptake. Except for shoulder abduction strength, no significant effects were found on the secondary outcomes. Limitations. Common health complications, such as urinary tract infections, bowel problems, and pressure sores, led to dropout and nonadherence.

Conclusion. Patients with tetraplegia were able to improve their physical capacity through regular hand cycle interval training, without participant-reported shoulder-arm pain or discomfort. October 2009

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A.J. Dallmeijer, PhD, is Assistant Professor, Department of Rehabilitation Medicine, VU University Medical Center, Amsterdam, the Netherlands. H. Houdijk, PhD, is a staff member in the Department of Research and Development, Heliomare Rehabilitation Centre, and Assistant Professor, Research Institute MOVE, Institute for Fundamental and Clinical Human Movement Sciences, Faculty of Human Movement Sciences, VU University, Amsterdam, the Netherlands. H.J. Slootman, MD, is a medical doctor in the Spinal Cord Unit, Heliomare Rehabilitation Centre. T.W. Janssen, PhD, is Professor, Research Institute MOVE, Institute for Fundamental and Clinical Human Movement Sciences, Faculty of Human Movement Sciences, VU University, and Rehabilitation Center Amsterdam, Amsterdam, the Netherlands. M.W.M. Post, PhD, is Senior Researcher, De Hoogstraat Rehabilitation Centre and Rudolf Magnus Institute for Neuroscience, University Medical Hospital Utrecht, Utrecht, the Netherlands. L.H. van der Woude, PhD, is Professor, Research Institute MOVE, Institute for Fundamental and Clinical Human Movement Sciences, Faculty of Human Movement Sciences, VU University, and Rehabilitation Center Amsterdam. [Valent LJM, Dallmeijer AJ, Houdijk H, et al. Effects of hand cycle training on physical capacity in individuals with tetraplegia: a clinical trial. Phys Ther. 2009;89:1051–1060.] © 2009 American Physical Therapy Association

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T

he physical capacity of most people with a cervical spinal cord injury (SCI) is low.1 In addition to complete or incomplete paralysis, many other factors may contribute to the low physical capacity of this group. People with tetraplegia often have a disturbed sympathetic nervous system that might lead to bradycardia, orthostatic hypotension, autonomic dysreflexia, temperature dysregulation, and sweating disturbances.2 Depending on the location and severity of the lesion, cardiovascular responses to exercise (eg, increased blood flow to active muscles and vasoconstriction in relatively inactive tissues) may be disturbed.1,2 Secondary complications such as urinary tract infections, spasms, pressure sores, and overuse injuries in the upper extremity also may lead to inactivity and deconditioning. Other barriers to physical activity may be intrinsic (eg, lack of energy or motivation) or extrinsic (eg, costs, not knowing where to exercise, accessibility of facilities, knowledgeable instructors).3 Deconditioning eventually may lead to additional health problems such as obesity, diabetes, and cardiovascular problems.4 Therefore, it is suggested that a certain level of physical activity and fitness is important for people with tetraplegia in order to maintain (or even improve) functioning, participation, health, and quality of life.5

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on July 30, 2009, at www.ptjournal.org.

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In contrast to arm-crank exercise, hand-rim wheelchair propulsion and hand cycling are functional modes of regular daily mobility that are assumed to help people with tetraplegia to maintain a physically active lifestyle. Hand-rim wheelchair propulsion, however, is highly inefficient6 and mechanically straining, often leading to upper-extremity overuse problems.7 For people with tetraplegia, it may even be difficult to apply a well-directed force during every push.8 For them, hand cycling may be easier to perform than handrim wheelchair propulsion. The hands are fixed in pedals with special grips, and forces can be applied continuously over the full 360degree cycle in both push and pull phases. In contrast, during hand-rim wheelchair propulsion, force can be applied in only 20% to 40% of the cycle.6 Furthermore, Dallmeijer et al9 found a higher mechanical efficiency and peak power output (POpeak) in hand cycling compared with hand-rim wheelchair propulsion. According to clinical experience, people for whom hand-rim wheelchair propulsion is too strenuous appear to be able to hand cycle a few hundred meters after only a few practice sessions. Only a few intervention studies are available on the effects of upperbody training in people with tetraplegia.10 These studies were performed with different modes of arm exercise: arm cranking,11,12 wheelchair propulsion,13 circuit resistance training,14 or quad rugby.15 The ergonomics of arm cranking in these studies11,12 differed substantially from the ergonomics of hand cycling in the current study (ie, asynchronous arm cranking versus synchronous hand cycling). A high position of the crank axis (midpoint of the sternum11 or at shoulder level12) is used in arm cranking versus the low position (just below the sternum) used in hand cycling.

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Training studies on the effects of hand cycling in people with SCI are even scarcer, with only one study in people with paraplegia16 and no studies in people with tetraplegia. In a recent observational study on the influence of hand cycling during and 1 year after clinical rehabilitation, we found clinically relevant improvements in physical capacity in patients with paraplegia during rehabilitation, but not in patients with tetraplegia, probably due to the small and heterogeneous groups.17 The aim of this study was to evaluate the effects of a structured hand cycle interval training intervention on physical capacity in people with tetraplegia at least 2 years postinjury. We hypothesized that a structured hand cycle training intervention significantly improves physical work capacity.

Method Participants People with cervical SCI who had been rehabilitated in 1 of 3 Dutch rehabilitation centers were approached to participate. Participants were included if they: (1) had been discharged from clinical rehabilitation more than 1 year previously and had a time since injury (TSI) of at least 2 years, (2) had a motor incomplete C5–C8 lesion (American Spinal Injury Association Impairment Scale [AIS] classification A–D),18 (3) used a manual or powered wheelchair for mobility, (4) were physically active in training and outdoor mobility less than 2 hours a week over the past 3 months, (5) were between 18 and 65 years of age, and (6) had sufficient knowledge of the Dutch language. A physician medically screened all participants. Exclusion criteria were: severe overuse injuries of the upper extremities screened with a questionnaire,19 other secondary health problems (ie, pressure sores, bladder infections, cardiovascular diseases, or contraindications for exercise acOctober 2009

Hand Cycle Training in Tetraplegia cording to American College of Sports Medicine guidelines20), or other medical conditions that did not allow performance of physical activities. All participants signed an informed consent form. Design The pretraining-posttraining design involved a pretraining test (t1), performed 1 week before the start of the 8- to 12-week training period, and a posttraining test (t2), performed 1 week after the end of the training period. A subgroup performed an extra test (t0) prior to t1, and the second baseline measurements (t1) were taken for analysis to rule out the effects of practicing.

Figure. Add-on hand cycle system.

Peak power output and peak oxygen ˙ O2peak) during the hand uptake (V cycle peak exercise test were the primary outcome measures of physical capacity. Muscle strength (forcegenerating capacity) and pulmonary function were evaluated as secondary outcome measures. Intervention: Hand Cycling The add-on hand cycle. The participants used an add-on hand cycle system* (equipped with bullhornshaped cranks and a front wheel) that was coupled to the front of the regular everyday hand-rim wheelchair. The crank pedals move synchronously with alternating flexion and extension of the arms during the 360-degree cycle (Figure). In contrast to conventional straight cranks, the wide bullhorn cranks allow positioning of the crank axis as low as possible, slightly above the upper legs, and, consequently, allow the pedals to move alongside the upper legs (in the lowest position). The hand cycle is equipped with gears that can be changed manually or by moving the chin forward or backward along the switches. * Double Performance, Antwerpseweg 13–1, Gouda, the Netherlands.

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Training protocol. Because not all participants in the study were acquainted with hand cycling, 1 practice session a week was conducted in the 3 weeks before the test. For all participants, we aimed at a total of 24 training sessions within a continuous period of 8 to 12 weeks. Those participants who were using a handrim wheelchair as their primary mode of mobility were assumed to be able to maintain a frequency of 3 training sessions a week for 8 weeks. Those who used an electrical wheelchair were advised to train twice a week for 12 weeks. At least 1 day of rest was scheduled between training days. All participants were asked to continue their regular physical activities and to make up for any missed training session. Depending on their personal situation, participants had the opportunity to train in the rehabilitation center or at home and both indoors and outdoors. To ensure training in case of bad weather conditions, participants received indoor bicycle roller trainers† that were adjusted for hand cycling. The duration of one training session was between † Minoura Magturbo, 1197–1 Godo, Anpachi, Gifu, 503-2305, Japan.

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35 and 45 minutes (Appendix). During training, participants wore heart rate (HR) monitors and were expected to train at 60% to 80% of heart rate reserve (HRR) (peak heart rate [HRpeak] ⫺ resting heart rate [HRrest] [bpm]).21 Rating of perceived exertion (RPE) was monitored using the Borg 10-point scale and was intended to range from 4 to 7, starting at the lower level in the first training sessions.22 Participants were asked to keep a training diary and to score upper-extremity pain following a standardized protocol.19 Data from the HR monitors during the training period were saved for further analysis. If serious complaints of upper-extremity pain or illness occurred, the participants were asked to contact the trainer/researcher before continuation of the training. Outcome Measures Physical capacity. Prior to testing, participants were asked to empty their bladder to help prevent possible bouts of autonomic dysreflexia. Resting heart rate and resting oxygen ˙ O2rest) were monitored uptake (V during 5 minutes of quiet sitting. Subsequently, participants were fa-

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Hand Cycle Training in Tetraplegia miliarized with the hand cycle on the treadmill,‡ and the experimental velocity was adjusted to the ability of the participant, but within the range of 1.11 to 1.94 m䡠s⫺1 and a gear setting resulting in a cadence of approximately 60 rpm. Mean submaximal ˙ O2submax) and oxygen uptake (V submaximal heart rate (HRsubmax) were measured at a constant load in the last 30 seconds of a 3-minute submaximal hand cycle bout. Because velocity and gear setting were kept the same during all measurement occasions, submaximal power output (POsubmax) was comparable between measurements, and a lower ˙ O2submax would indicate inV creased mechanical efficiency. After 3 minutes of rest, POpeak (W), ˙ O2peak (mL䡠min⫺1), and HRpeak V (bpm) were determined in a discontinuous graded peak exercise test performed in the hand cycle on a motor-driven treadmill. Exercise bouts of 2 minutes were interspaced with a rest period of 30 seconds. After each exercise step, the workload was increased by adding resistance (Fadd).9 Increments of 2.00 to 5.25 W were imposed until exhaustion. The test protocol was previously described by Valent et al.21 Rolling resistance (Frol) of the individual hand cycle-user combination on the treadmill was determined in a drag test on the treadmill.23 The power output (PO) was calculated from the separately measured individual drag force (Frol [N]), Fadd (N), and treadmill belt velocity (v [m䡠s⫺1]): PO共W兲 ⫽ 共F rol ⫹ F add 兲 ⫻ v ˙ O2) During the test, oxygen uptake (V was measured continuously with an Oxycon Delta spirometer.§ The high‡ Bonte Techniek BV, Amperestraat 25A 8013 PT, Zwolle, the Netherlands. § Viasys-HC, De Molen 8/10, 3994 DB, Houten, the Netherlands.

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est average 30-second values of PO ˙ O2 during the test were defined and V ˙ O2peak. Heart rate as POpeak and V was continuously monitored with an HR monitor,㛳 and HRpeak was defined as the highest HR value recorded in a 5-second interval. Cardiovascular efficiency, reflected by the oxygen pulse (O2P [mL䡠beat⫺1]), ˙ O2peak and was calculated from V ˙ O2peak HRpeak (O2P [mL䡠beat⫺1] ⫽ V [mL䡠min⫺1]/HRpeak [bpm]).24

on a 5-point scale (1⫽not serious, 5⫽very serious).19 We scored shoulders, elbows, and wrists separately, but the scores for left and right sides were summed.

Muscle strength. Arm muscle groups (elbow flexors and extensors, shoulder exorotators and endorotators, and abductors) that scored ⱖ3 on manual muscle testing were tested with handheld dynamometry (Microfet#), according to a standardized protocol.25 A break test was performed in which the participants built up a peak force against a dynamometer, after which the examiner applied a sufficiently higher resistance to break through it.26 The peak forces of the left- and right-side muscle groups were summed. Only data of participants with a strength score for both left and right sides for a certain muscle group were included in the strength analysis.

Results

Pulmonary function. To assess training effects on pulmonary function, we measured and analyzed simple spirometric values with the Oxycon Delta spirometer. Forced vital capacity (mL䡠min⫺1) and peak expiratory flow (mL䡠min⫺1) were recorded relative to age-, sex-, and body weight-corrected normative data. Adverse Effects Pain in the upper extremities (ie, the musculoskeletal system) was scored before and after the training period with a self-designed questionnaire 㛳

Polar Electro Nederland BV, Postbus 1044, 1300 BA Almere, the Netherlands. # Biometrics Europe BV, Kabelstraat 11, 1322 AD Almere, the Netherlands.

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Data Analysis The change between the pretraining and posttraining outcome measurements was examined using SPSS version 15** with a paired, 2-tailed Student t test (P⬍.05).

Twenty-two participants were included in this training study (Tab. 1). Five participants were moderately active (1.5 hours a week), and all other participants were minimally physically active or were not physically active. Fifteen participants completed the training period (t1– t2) and performed a pretest and a posttest. A subgroup (participants 1–7) of these 15 participants also performed an extra test (t0). Seven participants dropped out during the training period due to various reasons: problems with transportation to the training facility (participant 18), a chronic urinary tract infection (participant 19), persistent bowel problems combined with spasms (participant 20), pressure ulcers as a consequence of a fall out of the wheelchair at home (participant 21), a work-related overuse injury of the elbow (participant 22), serious pain as a consequence of bowel problems (participant 17), and illness (the flu) after 3 weeks of training (participant 8). No significant differences were found in personal and lesion characteristics among the 7 participants who dropped out (Tab. 1) and those who completed the training (n⫽15): age (X⫽43 years, SD⫽13 versus X⫽38 years, SD⫽11); TSI (X⫽9 ** SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606

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M

14

Volume 89

Number 10

12

17

81

110

60

77

64

84

100

63

70

71

84

80

113

77

81

117

70

88

65

58

85

86

83

Weight (kg)

C6/T1

C5/C6

C7/C7

C8/T1

C6/C6

C5/C6

C5/C5

C5/C7

C8/C8

C8/C8

C7/C8

C5/C5

C7/C7

C7/C7

C6/C6

C6/C6

C7/C7

C6/C6

C6/C7

C6/C6

C6/C7

C6/C6

Lesion Level (Right/Left)

A

A

B

B

B

B

A

B

D

B

A

A

B

B

A

B

B

D

C

B

B

B

AIS Classification

Hr

El

Hr

Hr

El

Hr

El

Both

Hr

Hr

Hr

El

Hr

Hr

El

Hr

El

El

Hr

Hr

Hr

El

Daily Wheelchair

1

0

0

1

1

2

0

2

0

0

0

2

1

0

3

0

1

3

3

0

0

0

ISPS (0–3)

0

0.5

1

0

0

0.5

0.5

1

0

1

1

1.5

1.5

1.5

0

1

0

0

1

1.5

1.5

0

Phys Act (hr/wk) No

Yes

Yes

Yes

No

No

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

1

8

1

10

3

4

5

0

8

12

7

8

7

6

8

8

3

8

10

8

8

8

8

10

3

19

do

do

do

do

do

do

20

24

17

19

18

13

19

24

do

24

20

20

23

23

24

17

Training Period Sessions (wk) Completed

21.9

42.5

17.8

16

36

28

23.7

32.0

14.0

20.6

47.1

60.6

66.6

16.0

66.8

69.6

32.0

41.9

24

14

41.8

74.3

51.8

28.8

Pre

25.4

50.9

22.0

21.0

57.6

71.7

86.0

16.0

82.7

74.2

52.4

28

16

53.8

78.5

65.0

38.8

Post

POpeak (W)

0.40

1.32

0.90

0.61

1.32

0.80

0.94

1.12

0.75

1.08

1.69

1.40

1.73

0.91

1.50

2.20

0.82

1.10

0.91

0.95

1.21

1.60

1.60

1.12

Pre

0.43

1.43

0.81

1.12

1.39

1.66

1.87

1.04

1.72

2.00

1.15

0.84

0.95

1.57

2.02

1.93

1.38

Post

˙ O2peak V (L䡠minⴚ1)

a M⫽male, F⫽female, TSI⫽time since injury, AIS⫽American Spinal Injury Association Impairment Scale,18 Hr⫽hand-rim wheelchair, El⫽electric wheelchair, ISPS⫽initial shoulder pain score (1⫽minimal pain, 2⫽slightly moderate pain, 3⫽moderate pain), Phys Act⫽physical activity (sports or outdoor manual wheelchair propulsion), do⫽dropout, pre⫽pretraining, post⫽posttraining.

7

10

39

SD

6

X

21

3

2

20

12

3

6

2

6

12

8

6

28

3

7

3

20

17

15

2

15

TSI (y)

16

M

34

45

58

48

25

48

44

28

32

43

32

54

42

29

64

37

31

37

22

41

Age (y)

51

22

M

M

13

21

M

12

M

M

11

M

M

10

20

M

9

19

M

8

F

M

7

M

M

6

18

F

5

17

F

4

M

M

3

F

M

2

16

M

1

15

Sex

Subject No.

Hand Cycle Experience

Participant Characteristics, Training Adherence, and Peak Power Output (POpeak) and Peak Oxygen Uptake (V˙O2peak) Measurementsa

Table 1.


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Hand Cycle Training in Tetraplegia years, SD⫽7 versus X⫽10 years, SD⫽8), body mass (X⫽87.4 kg, SD⫽22.2 versus X⫽78.2 kg, SD⫽13.3), lesion level (C5 [n⫽2], C6 [n⫽3], C7 [n⫽1], and C8 [n⫽1] versus C5 [n⫽3], C6 [n⫽6], C7 [n⫽4], and C8 [n⫽2]), and AIS classification18 (A [n⫽3], B [n⫽4], C [n⫽0], and D [n⫽0]) versus A [n⫽3], B [n⫽9], C [n⫽1], and D [n⫽1]), respectively. However, the dropouts had significantly lower baseline levels of the primary outcome measures of physical capacity than those who completed the study: POpeak (X⫽26.5 W, SD⫽7.2 versus X⫽42.5 W, SD⫽21.9) ˙ O2peak (X⫽0.93 (P⫽.099) and V L䡠min⫺1, SD⫽0.25 versus X⫽1.32 L䡠min⫺1, SD⫽0.40) (P⫽.04), respectively. Five dropouts had light to moderate shoulder pain at baseline. Six participants who completed the training period initially had light to moderate shoulder pain, and 4 of these participants appeared to have a low baseline physical capacity and only slight absolute improvements after training (Tab. 1). Training Protocol. It turned out to be difficult for the participants to complete 24 training sessions within the designated period (Tab. 1). Five participants missed 5 to 7 sessions, which was more than 20% of all sessions. The main reasons reported were: not feeling well because of an illness (urinary tract infection, flu), transportation problems, too busy (with work), too tired, and no people available to help start up training. Overuse injuries were not mentioned. The distances covered during the hand cycle training sessions increased over time and varied from 2 to 7 km. All participants who completed the training managed to train at, on average, 60% to 80% of HRR, with the 1- to 2-minute rest intervals 1056

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included. During the 3- to 4-minute hand cycle intervals, the HR was between 70% and 80% of HRR. A mean intensity of 6 (SD⫽1) on the 10-point Borg scale was reported after the training sessions, compared with 7 (SD⫽2) after completing the peak exercise test. Particularly those participants with a very limited active muscle mass and a high body mass, who already were exerting at a nearmaximal level when moving the hand cycle forward, initially had to hand cycle in a roller trainer (at a lower power level). After 4 to 6 weeks of training, all participants who completed the training were able to train outdoors at the suggested intensity. Adverse effects. The training was never stopped because of complaints of pain in the arms or shoulders, although 3 participants were advised on one occasion to postpone the next training day or to train at a lower intensity (or gear setting). Comparing pretraining and posttraining pain scores, no increase in pain scores for the wrists or elbows was found following hand cycle training. Three participants (participants 3, 6, and 11) reported a slightly higher shoulder pain score after training compared with before training. All 3 participants mentioned that this higher pain score was due to muscle soreness as a consequence of training too hard (with a gear setting that was too high), which disappeared within 1 day after training. Outcome Measures Hand cycle capacity. Table 2 presents the results of the pretestposttest design (n⫽15). Mean peak respiratory exchange ratio was 1.10 in both the pretest and the posttest, ˙ O2peak suggesting that, in general, V was reached. The VO2peak significantly improved, on average, 114 mL䡠min⫺1 (SD⫽204) after training, which was an increase of 8.7% (SD⫽13.9%). In addition, a signifi-

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cant improvement in POpeak of 8.3 W (SD⫽5.8) was found after training, which was an increase of 20.2% (SD⫽15.0%). No significant improvement in O2P (mean difference⫽1.3 mL䡠beat⫺1, SD⫽0.2) (P⫽.06) was seen in the pretraining-posttraining comparison (n⫽14; Tab. 2). As expected, HRpeak (n⫽14) did not change between pretraining (X⫽128 b䡠min⫺1, SD⫽24) and posttraining (127 b䡠min⫺1, SD⫽27). A significant de˙ O2submax during hand cycrease in V cling of 73 mL䡠min⫺1 (SD⫽122) (X⫽8.8%, SD⫽14.6%) (P⫽.04) was found (n⫽14; Tab. 2) at a constant power output, indicating improved gross mechanical efficiency during hand cycling. Secondary outcomes. Only shoulder abduction strength significantly improved (X⫽5.6%, SD⫽11%); Tab. 2). No effects of hand cycle training were found on pulmonary function outcome measures.

Discussion Structured hand cycle interval training showed significant positive effects on the primary outcomes of physical capacity (POpeak and ˙ O2peak) but not on the secondary V outcomes (muscle strength and pulmonary function). Training A relatively high dropout rate of approximately 30% was encountered in the training period. The relatively low baseline physical capacity in the dropouts compared with participants who completed the training period may have been a result of a long history of health problems that prevented them from maintaining their fitness level. In general, initial shoulder pain was more prevalent in the study dropouts. Furthermore, people with a relatively low physical capacity may be in a vulnerable health condition and thus more October 2009

Hand Cycle Training in Tetraplegia Table 2. Results of Hand Cycle Training: Paired t-Test Analysis of Outcome Measures Pretraining (t1) and Posttraining (t2) (n⫽15)a

Physical Capacity

n

Difference (t2 ⴚ t1)

t1

t2

X (SD)

X (SD)

P

⬍.001

X (95% CI)

Hand cycle capacity POpeak (W)

15

42.5 (21.9)

50.8 (25.4)

V˙O2peak (mL䡠min⫺1)

15

1,317 (399)

1,431 (427)

.05

8.3 (5.2 to 11.5) 114 (0 to 227)

V˙O2peak (mL䡠kg⫺1䡠min⫺1)

14

17.3 (5.2)

19.1 (5.7)

.03

1.8 (0.2 to 3.4)

O2Ppeak (mL䡠beat⫺1)

14

10.7 (2.8)

12.0 (4.0)

.06

1.3 (0.1 to 2.5)

VEpeak (L䡠min⫺1)

15

52.0 (17.3)

54.9 (19.2)

.15

2.9 (⫺1.9 to 7.0)

RERpeak

15

1.10 (0.16)

1.10 (0.14)

.93

0.01 (⫺0.03 to 0.07)

V˙O2submax (mL䡠min⫺1)

14

834 (116)

761 (58)

.04

⫺73 (⫺144 to ⫺3)

HRsubmax (bpm)

14

92 (17)

88 (18)

.40

⫺4 (⫺13 to 5)

8

331 (99)

321 (96)

.47

⫺10 (⫺42 to 21)

Muscle strength (HHD) Extension (L⫹R) (N) Flexion (L⫹R) (N)

15

571 (176)

578 (177)

.49

7 (⫺14 to 27)

Endorotation (L⫹R) (N)

12

358 (130)

360 (118)

.83

2 (⫺9 to 19)

Exorotation (L⫹R) (N)

12

294 (101)

304 (98)

.10

10 (⫺2 to 22)

Abduction (L⫹R) (N)

15

336 (86)

355 (80)

.05

19 (0 to 38)

FVC (L䡠min⫺1)

15

3.80 (1.24)

3.82 (1.21)

.80

FVC (%)

15

75.5 (15.4)

76.8 (17)

.45

1.2 (⫺2.1 to 4.7)

PEF (L䡠min⫺1)

15

6.52 (2.23)

6.14 (2.00)

.07

⫺0.37 (⫺0.78 to 0.04)

PEF (%)

15

70.0 (21.3)

66,3 (18.9)

.27

⫺3.7 (⫺8.2 to 0.8)

Pulmonary function ⫺0.02 (⫺0.21 to 0.16)

CI⫽confidence interval, POpeak⫽peak power output, V˙O2peak⫽peak oxygen uptake, O2P⫽peak oxygen pulse, V˙O2submax⫽submaximal oxygen uptake, HRsubmax⫽submaximal heart rate, HRrest⫽resting heart rate, V˙O2rest⫽resting oxygen uptake, RER⫽respiratory exchange ratio, VEpeak⫽peak ventilation, HHD⫽handheld dynamometry, L⫽left, R⫽right, FVC⫽force vital capacity, PEF⫽peak expiratory flow. For some outcome measures of hand cycle capacity, data were missing in one (but not the same) participant due to measurement errors. Muscle strength was not available for all muscle groups (as the participants scored less than 3 on manual muscle testing or manual muscle testing was not feasible due to pain). a

prone to developing health problems. On the other hand, health problems, although less severe, also were responsible for the high nonadherence rate found in the participants in the training program. It should be noted that health problems in both dropouts and participants who completed training were not related to the training. It can be concluded that untrained people with tetraplegia are in a vulnerable health condition27 and that health problems are likely to interfere with their life and thus with their ability to perform training programs. Protocol. From a preceding unpublished pilot project in untrained subjects with tetraplegia, interval October 2009

training appeared to be more suitable than continuous aerobic training. Most of the participants in our pilot project were not able to hand cycle continuously for longer than approximately 5 to 7 minutes, whereas several hand cycle blocks of 3 minutes, with rest intervals between blocks, were easily sustainable and without extreme muscle fatigue. Therefore, a hand cycle interval training (and discontinuous test) protocol was designed. The exercise intensity was within the range of 50% to 90% HRR, HRpeak, and POpeak, which was imposed in previous upper-body training studies in people with tetraplegia.10 The broad range in RPE scores (4 –7) as well as HRR values (60%– 80%) accounted Volume 89

for the variation in intensity common during interval training.28 It should be noted from a previous study21 that HRR and RPE scores have limitations for monitoring exercise intensity in people with tetraplegia. The study participants tended to score local arm muscle fatigue instead of overall perceived exertion, which is intended by the Borg scale.21 In addition, HR may not always reflect exercise intensity adequately, probably due to a disturbed sympathetic innervation (ie, of the heart, resulting in a low HRpeak29) or other factors related to the low physical capacity and muscle mass involved.21

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Hand Cycle Training in Tetraplegia Despite these limitations, however, RPE together with HRR appeared reasonably useful in training people with tetraplegia. The 2 methods combined helped participants to know their body responses to exercise and understand that HR may not always reflect exercise intensity. For example, study participants reported higher-than-normal HR values (and better performance) during training in the days before a bladder infection or illness was diagnosed. This finding suggests that symptoms of autonomic dysreflexia were present. Adverse effects. In about 40% of the participants, light to moderate pain to the upper extremities was already present before they were included in the present study. With a prevalence between 40% and 70%,7,19 pain in the upper extremities, especially in the shoulder, is common in people with tetraplegia. They are at higher risk for developing musculoskeletal pain as a consequence of partial paralysis of thoracohumeral muscles and imbalance in shoulder muscles.7 We noticed that 2 out of 3 participants with temporal shoulder complaints ( participants 2 and 3) were the only individuals who were using conventional straight cranks (with a high-positioned crank axis). They were forced to move their arms further against gravity and even above shoulder level, which may be disadvantageous for the shoulder musculature. Despite instructions, participants tended to cycle with higher resistance instead of higher pedal frequencies. Cycling at a high resistance potentially can overload the musculoskeletal system, but is not reflected by exercise intensity (HRR). Therefore, especially in the first weeks of training, supervision of the training regimen is recommended. Moreover, for those indi1058

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viduals with initial shoulder pain, it is advised to incorporate an additional muscle (rotator cuff) strengthening program into the training protocol.30 Outcome Measures Hand cycle capacity. The primary outcome measures in the study, ˙ O2peak, showed signifPOpeak and V icant improvements over the training period. Table 1 shows the large interindividual differences in our main outcomes, and clearly an improvement of 8 W after training is more substantial for someone with a baseline value of 16 W than for someone with a baseline value of 60 W. Moreover, it is difficult to compare absolute gains in POpeak and ˙ O2peak with the literature when V different test devices and protocols have been used and with subjects with different training statuses.10 Nevertheless, the relative gains of 20.2% in POpeak and 8.7% in ˙ O2peak in the present study were in V agreement with the study by McLean and Skinner,11 who found gains of 13.7% and 8.3%, respectively, after arm crank exercise. In another study on arm crank exercise in young people with tetraplegia, gains of 23.8% ˙ O2peak were in POpeak and 99% in V found.12 Dallmeijer et al15 did not find any significant improvements in ˙ O2peak after quad rugby POpeak or V training (once a week). During clinical rehabilitation, Hjeltnes and Wallberg-Henriksson31 found significant gains in POpeak but no im˙ O2peak. provements in V The question remains: How much improvement is clinically relevant? According to Brehm et al,32 10% is considered to be a meaningful change. Applying this arbitrary cutoff in the current study, an improvement in POpeak is designated clinically relevant and the change in ˙ O2peak is nearly clinically relevant. V

Number 10

The gains in work capacity indicate the ability to improve fitness in people with tetraplegia. The effects of hand cycle training probably will be primarily local and not necessarily central, given the extremely low muscle mass that is actively involved in the exercise in this population.1 The greater relative increase in POpeak (20.2%) compared with ˙ O2peak (8.7%) and the decrease in V ˙ O2submax indicate an improveV ment in gross mechanical efficiency33 (ie, effects in reduced cocontraction as part of muscle coordination of the arms and shoulders, as well as in external force production). Another possible explanation may be an improved exercise tolerance in the muscles. Muscle strength. No clinically relevant improvements in muscle strength were found after hand cycling. In general, however, the participants reported feeling stronger. A possible explanation may be improved exercise tolerance in the muscles. This improved exercise tolerance likely results from changes in muscle metabolism (eg, increase in mitochondria, improved glycogen storage and synthesis) or a higher density of capillaries, during which less lactic acid is accumulated and diminished muscle fatigue is experienced.34 In the current study, however, we measured isometric peak strength and not muscle endurance. Pulmonary function. No improvements in functional vital capacity or peak expiratory flow were found. In the literature, however, it appears that the effects of upperbody training on pulmonary function in people with high levels of paraplegia or tetraplegia are not uniform.10,35,36 Study Limitations The optimal study design (ie, a randomized controlled trial) was not feasible due to the small number of October 2009

Hand Cycle Training in Tetraplegia available participants. Another limitation was the variability in baseline physical capacity among the participants. However, coalescing subgroups to reduce variability was hampered by the small sample size. The number of dropouts and the nonadherence rate were considerable, but not uncommon in training studies in people with tetraplegia.10 Due to dropouts, the group serving as their own controls (n⫽7) was too small to perform statistical analysis of a double baseline group. With 19 training sessions (instead of 24), our participants trained less than planned. Nevertheless, a positive effect was found on physical capacity.

Conclusions and Recommendations A successful integration of aerobic exercise training into the daily life of people with tetraplegia may be more likely if aerobic exercise is safe, easily adjustable to a person’s low physical capacity, fun to do, motivating, low key, and useful in daily mobility, as well as encouraging social participation. Hand cycling may meet these requirements. Important are an adequate ergonomic interface and an optimal range of gear ratios (or initial use of roller trainers) to impose an adequate power output. Hand cycling around wherever you like and over meaningful distances may be fun to do. After a training period, it may be motivating to see improvements in fitness level and distances covered. Hand cycling (with an attachable unit) may be low key, as no transfers have to be made, and certainly if someone can start from home. The hand cycle may be useful for daily mobility in an ergonomically suitable environment. Hand cycling with peers or together with family members and friends during activities such as walking, jogging, or skating may encourage social participation.

October 2009

Especially vulnerable individuals with a low physical capacity can benefit from initial supervision by skilled professionals who can help them overcome personal and practical barriers in daily life. Future research should focus on the optimization of hand cycle training protocols (eg, training at a certain percentage of the POpeak, in watts, which was derived from the exercise test21,37) specifically designed for people with tetraplegia. Dr Valent, Dr Dallmeijer, Dr Slootman, Dr Janssen, and Dr van der Woude provided concept/idea/research design. Dr Valent, Dr Dallmeijer, Dr Houdijk, Dr Slootman, Dr Janssen, and Dr van der Woude provided writing. Dr Valent provided data collection. Dr Valent, Dr Dallmeijer, Dr Houdijk, Dr Slootman, and Dr van der Woude provided data analysis. Dr Dallmeijer and Dr van der Woude provided project management. Dr Dallmeijer provided fund procurement. Dr Houdijk and Dr van der Woude provided facilities/equipment. Dr Houdijk provided institutional liaisons. Dr Dallmeijer, Dr Houdijk, Dr Slootman, Dr Janssen, Dr Post, and Dr van der Woude provided consultation (including review of manuscript before submission). Approval for the study was obtained from the local medical ethics committee. This research, in part, was presented at the 47th Annual Scientific Meeting of the International Spinal Cord Society; September 1, 2008; Durban, South Africa. This article was received October 26, 2008, and was accepted June 1, 2009. DOI: 10.2522/ptj.20080340

References 1 Glaser RM. Arm exercise training for wheelchair users. Med Sci Sports Exerc. 1989;21(5 suppl):S149 –S157. 2 Krassioukov AV, Karlsson AK, Wecht JM, et al. Assessment of autonomic dysfunction following spinal cord injury: rationale for additions to International Standards for Neurological Assessment. J Rehabil Res Dev. 2007;44:103–112. 3 Scelza WM, Kalpakjian CZ, Zemper ED, Tate DG. Perceived barriers to exercise in people with spinal cord injury. Am J Phys Med Rehabil. 2005;84:576 –583. 4 Myers J, Lee M, Kiratli J. Cardiovascular disease in spinal cord injury: an overview of prevalence, risk, evaluation, and management. Am J Phys Med Rehabil. 2007; 86:142–152.

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5 Noreau L, Shephard RJ. Spinal cord injury, exercise and quality of life. Sports Med). 1995;20:226 –250. 6 Van der Woude LH, Veeger HE, Dallmeijer AJ, et al. Biomechanics and physiology in active manual wheelchair propulsion. Med Eng Phys. 2001;23:713–733. 7 Curtis KA, Drysdale GA, Lanza RD, et al. Shoulder pain in wheelchair users with tetraplegia and paraplegia. Arch Phys Med Rehabil. 1999;80:453– 457. 8 Dallmeijer AJ, Van der Woude LH, Veeger HE, Hollander AP. Effectiveness of force application in manual wheelchair propulsion in persons with spinal cord injuries. Am J Phys Med Rehabil. 1998;77: 213–221. 9 Dallmeijer AJ, Zentgraaff ID, Zijp NI, Van der Woude LH. Submaximal physical strain and peak performance in hand cycling versus hand-rim wheelchair propulsion. Spinal Cord. 2004;42:91–98. 10 Valent L, Dallmeijer AJ, Houdijk H, et al. The effects of upper body exercise on the physical capacity of people with a spinal cord injury: a systematic review. Clin Rehabil. 2007;21:315–330. 11 McLean KP, Skinner JS. Effect of body training position on outcomes of an aerobic training study on individuals with quadriplegia. Am J Phys Med Rehabil. 1995;76:139 –150. 12 DiCarlo SE. Effect of arm ergometry training on wheelchair propulsion endurance of individuals with quadriplegia. Phys Ther. 1988;68:40 – 44. 13 Whiting RB, Dresinger TE, Dalton RB, Londeree BR. Improved physical fitness and work capacity in quadriplegics by wheelchair exercise. J Cardiac Rehabil. 1983;3: 251–255. 14 Cooney MM, Walker JB. Hydraulic resistance exercise benefits cardiovascular fitness of spinal cord injured. Med Sci Sports Exercise. 1986;18:522–525. 15 Dallmeijer AJ, Hopman MT, Angenot EL, Van der Woude LH. Effect of training on physical capacity and physical strain in persons with tetraplegia. Scand J Rehabil Med. 1997;29:181–186. 16 Mukherjee G, Bhowmik P, Samanta A. Physical fitness training for wheelchair ambulation by the arm crank propulsion technique. Clin R. 2001;15:125–132. 17 Valent L, Dallmeijer AJ, Houdijk H, et al. Influence of hand cycling on physical capacity in the rehabilitation of persons with a spinal cord injury: a longitudinal cohort study. Am J Phys Med Rehabil. 2008;89: 1016 –1022. 18 Marino RJ, Barros T, Biering-Sorensen F, et al. International standards for neurological classification of spinal cord injury. J Spinal Cord Med. 2003;26(suppl 1):S50 – S56. 19 Van Drongelen S, De Groot S, Veeger HE, et al. Upper extremity musculoskeletal pain during and after rehabilitation in wheelchair-using persons with a spinal cord injury. Spinal Cord. 2006;44: 152–159.

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Hand Cycle Training in Tetraplegia 20 Franklin BA, Whaley MH, Howley ET, Balady GJ; American College of Sports Medicine. ACSM’s Guidelines for Exercise Testing and Prescription. 6th ed. Baltimore, MD: Lippincott Williams & Wilkins; 2000. 21 Valent L, Dallmeijer AJ, Houdijk H, et al. The individual relationship between heart rate and oxygen uptake in people with a tetraplegia during exercise. Spinal Cord. 2007;45:104 –111. 22 Noble BJ, Borg GA, Jacobs I, et al. A category-ratio perceived exertion scale: relationship to blood and muscle lactates and heart rate. Med Sci Sports Exercise. 1983;15:523–528. 23 Van der Woude LH, De Groot G, Hollander AP, et al. Wheelchair ergonomics and physiological testing of prototypes. Ergonomics. 1986;29:1561–1573. 24 Wasserman K, Hansen JE, Sue DY, et al. Principles of Exercise Testing and Interpretation. 3rd ed. Philadelphia, PA: Lippincott, Williams & Wilkins; 1999.

25 Andrews AW, Thomas MW, Bohannon RW. Normative values for isometric muscle force measurements obtained with hand-held dynamometers. Phys Ther. 1996;76:248 –259. 26 Phillips BA, Lo SK, Mastaglia FL. Muscle force measured using “break” testing with a hand-held myometer in normal subjects aged 20 to 69 years. Am J Phys Med Rehabil. 2000;81:653– 661. 27 Ginis KA, Hicks AL. Exercise research issues in the spinal cord injured population. Exerc Sport Sci Rev. 2005;33:49 –53. 28 Butcher SJ, Jones RL. The impact of exercise training intensity on change in physiological function in patients with chronic obstructive pulmonary disease. Sports Med. 2006;36:307–325. 29 Figoni SF. Exercise responses and quadriplegia. Med Sci Sports Exerc. 1993;25: 433– 441. 30 Bonninger M, Waters R, Chase T, et al. Preservation of upper limb function following spinal cord injury: a clinical practice guideline for health-care professionals. J Spinal Cord Med. 2005;28:434 – 470.

31 Hjeltnes N, Wallberg-Henriksson H. Improved work capacity but unchanged peak oxygen uptake during primary rehabilitation in tetraplegic patients. Spinal Cord. 1998;36:691– 698. 32 Brehm MA, Harlaar J, Groepenhof H. Validation of the portable VmaxST system for oxygen-uptake measurement. Gait Posture. 2004;20:67–73. 33 De Groot S, Veeger DH, Hollander AP, Van der Woude LH. Wheelchair propulsion technique and mechanical efficiency after 3 wk of practice. Med Sci Sports Exercise. 2002;34:756 –766. 34 Harvey L. Management of Spinal Cord Injury. Philadelphia, PA: Churchill Livingstone Elsevier; 2008. 35 Gass GC, Watson J, Camp EM, et al. The effects of physical training on high level spinal lesion patients. Scand J Rehabil Med. 1980;12:61– 65. 36 Crane L, Klerk K, Ruhl A, et al. The effect of exercise training on pulmonary function in persons with quadriplegia. Paraplegia. 1994;32:435– 441. 37 McLean KP, Jones PP, Skinner JS. Exercise prescription for sitting and supine exercise in subjects with quadriplegia. Med Sci Sports Exercise. 1995;27:15–21.

Appendix. Training Protocol (12 Weeks) Week 1

a

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

3 min hc

3 min hc

Week 8

Week 9

Week 10 Week 11 Week 12

3 min hca 3 min hc

3 min hc

2 min rest 2 min rest

1.5 min rest 1.5 min rest 1.5 min rest 1 min rest 1 min rest 1.5 min rest 1.5 min rest 1 min rest 1 min rest 1 min rest

6⫻

7⫻

7⫻

3 min hc

8⫻

3 min hc

8⫻

8⫻

8⫻

4 min hc

7⫻

4 min hc

7⫻

4 min hc

7⫻

4 min hc

7⫻

4 min hc

8⫻

hc⫽hand cycling.

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Research Report

Step Test Scores Are Related to Measures of Activity and Participation in the First 6 Months After Stroke Vicki Stemmons Mercer, Janet Kues Freburger, Shuo-Hsiu Chang, Jama L. Purser

Background. The Step Test (ST) is a measure of dynamic standing balance and paretic–lower-extremity motor control in patients with stroke. Little is known about the extent to which impairments assessed by the ST relate to activity and participation during stroke recovery. Objective. The purpose of this study was to determine relationships between ST scores and measures of activity and participation during the first 6 months after stroke.

Design. This was a prospective cohort study. Methods. Thirty-three individuals (18 men, 15 women) with a diagnosis of a single, unilateral stroke participated in the study. Participants were tested one time per month from 1 to 6 months poststroke. The ST was considered an impairmentlevel measure. Self-selected gait speed and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) Physical Function Index (PFI) were used to assess physical function. Three domains (mobility, basic and instrumental activities of daily living, participation) of the Stroke Impact Scale were used to assess self-reported disability. Regression analyses were conducted to examine the bivariate associations between ST scores and each physical function and disability measure at each time point (1– 6 months).

Results. The ST scores were positively associated with both physical function

measures. The associations were stronger for self-selected gait speeds (R2⫽.60 –.79) than for the PFI scores (R2⫽.32–.60). During the first 6 months after stroke, each additional step with the paretic lower extremity on the ST corresponded to a 0.07-m/s to 0.09-m/s increase in gait speed, and each additional step with the nonparetic lower extremity was associated with a 0.07-m/s to 0.08-m/s gait speed increase. The impairment-disability associations were weaker than the impairmentphysical function associations.

V.S. Mercer, PT, PhD, is Associate Professor, Division of Physical Therapy, Department of Allied Health Sciences, University of North Carolina at Chapel Hill, CB#7135, Bondurant Hall, Ste 3022, Chapel Hill, NC 275997135 (USA). Address all correspondence to Dr Mercer at: [email protected]. J.K. Freburger, PT, PhD, is Research Associate and Fellow, Cecil G. Sheps Center for Health Services Research, and Research Scientist, Institute on Aging, University of North Carolina at Chapel Hill. S.-H. Chang, PT, PhD, is Postdoctoral Research Scholar, Graduate Program in Physical Therapy and Rehabilitation Science, The University of Iowa, Iowa City, Iowa. J.L. Purser, PT, PhD, is Assistant Professor, Division of Geriatrics, Department of Medicine, and Division of Physical Therapy, Department of Community and Family Medicine, and Senior Fellow, Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, North Carolina.

lack of examiner blinding with regard to participant characteristics.

[Mercer VS, Freburger JK, Chang S-H, Purser JL. Step Test scores are related to measures of activity and participation in the first 6 months after stroke. Phys Ther. 2009;89: 1061–1071.]

Conclusions. Impairments in balance and paretic–lower-extremity motor con-

© 2009 American Physical Therapy Association

Limitations. Limitations of the study include a relatively small sample size and

trol, as measured by the ST, relate to physical function and disability during the first 6 months following stroke. Post a Rapid Response or find The Bottom Line: www.ptjournal.org October 2009

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bout 780,000 people in the United States experience a stroke each year.1 Although some survivors of a stroke achieve a full recovery in physical function, approximately one half have long-term motor deficits, and between 25% and 50% require assistance with activities of daily living (ADL).2,3 The economic burden is enormous, with indirect and direct costs of ischemic stroke from 2005 through 2050 expected to exceed $2.2 trillion.4 Loss of earnings and informal caregiving are the 2 largest contributors to overall costs.4

The World Health Organization’s International Classification of Functioning, Disability and Health (ICF)5 provides a useful framework for understanding how stroke may affect health states from biological, personal, and social perspectives.6 The ICF model organizes the effects of health conditions such as stroke into the domains of “body structure and function” and “activity and participation.”5 Common effects of stroke on body structure and function include motor impairments such as hemiparesis and dyscoordination. Problems in the domain of activity and participation include reduced ability to perform daily tasks (also known as “activity limitations”) and difficulties with involvement in life situations or roles (also known as “participation restrictions”). Although activity and participation


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sometimes are viewed as 2 distinct concepts, recent analyses call into question the wisdom of trying to distinguish between them.7 “Disability” is a general term used to describe a decrement in the activity and participation domain.6 Previous researchers8 –12 have found statistically significant relationships between measures of motor impairment and measures of activity and participation following stroke. These relationships can be quite complex. Correlations tend to be modest in size because of the multitude of factors, in addition to severity of motor impairment, that can affect activity and participation after stroke.9,10,13–15 For example, an individual with severe hemiparesis may use compensatory mechanisms to achieve relatively fast walking speeds.13,16 On the other hand, an individual who regains adequate motor function may lack the social support he or she needs to achieve independence in self-care activities or participation.17 Better understanding of how impairments in body structure or function relate to activity limitations and participation restrictions is critical for clinical decision making and health policy.18 Such understanding will aid clinicians in identifying impairments that may contribute to problems in activity and participation after stroke and in tailoring their interventions to address these impairments. In previous studies of individuals poststroke, the motor abilities having the strongest associations with measures of activity or participation were balance, lower-extremity motor coordination or control, and muscle strength (force-generating capacity).9,10,12,14,16,19,20 A consistent finding from these studies was a stronger association of lower-extremity than upper extremity motor abilities with the occurrence of activity limitations and participation restrictions.9,10,19

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Adequate balance and lowerextremity motor abilities are prerequisites for independence in walking, which, in turn, may facilitate full participation in community, social, and civic life.10,19 Several tools exist for measuring impairments in balance and lowerextremity motor abilities in individuals with stroke. The Berg Balance Scale (BBS)21,22 and the balance subscale of the Fugl-Meyer Assessment (FMA)23 commonly are used to assess balance in people poststroke, and the lower-extremity motor function subscale of the FMA is considered the gold standard for assessing paretic–lower-extremity motor abilities. Although both the BBS24,25 and the FMA26 have been shown to be psychometrically sound for use with individuals poststroke, a major drawback is the length of time required for administration. The BBS requires approximately 20 minutes to complete,27 and a mean (SD) time of 58 (16.6) minutes has been reported for administration of the balance, motor, and sensation subscales of the FMA.28 The length and relative complexity of these measures may place a considerable burden on clinicians and patients, especially patients in the early stages of stroke recovery.26,29 A tool that combines measurement of balance and lowerextremity motor control and can be administered quickly and easily is more amenable to clinical use. In our view, the Step Test (ST)30 is such a tool. Originally developed as a test of dynamic standing balance after stroke, the ST requires the individual to repeatedly place one foot on and off a step as quickly as possible.30 The ST, in addition to requiring balance during lower-extremity movement in standing, reflects lower-extremity motor control and coordination. When the individual steps with the paretic foot, the paretic lower extremity must move October 2009

Step Test Performance and Measures of Activity and Participation After Stroke quickly in flexion and reverse movement direction. When the individual steps with the nonparetic foot, the paretic lower extremity must be stable in extension, supporting full body weight. The ST has evidence of test-retest reliability,30 can be completed in less than 5 minutes, correlates with other measures of balance and mobility after stroke,30 and is responsive to change during stroke recovery.31 The overall purpose of this study was to further our understanding of relationships between balance and lower-extremity motor control, as measured by the ST, and measures of activity and participation in survivors of stroke. We sought to address some of the limitations of previous studies by choosing a wide range of suitable measures of activity and participation and by testing at multiple time points after stroke onset. Many previous researchers8,22,32–34 have used gross measures of ADL, such as the Barthel Index or the Functional Independence Measure, which lack sensitivity and may demonstrate ceiling effects in individuals with mild stroke.25 Duncan and colleagues18,35 have emphasized the importance of including measures of higher levels of activity and participation, such as instrumental activities of daily living (IADL), as benchmarks of recovery in patients with mild to moderate stroke. With these issues in mind, we chose self-selected gait speed36,37 and the Medical Outcomes Study 36Item Short-Form Health Survey (SF36) Physical Function Index (PFI)38 to assess key aspects of physical function (activity domain of the ICF model). Three domains (mobility, ADL/IADL, and participation) of the Stroke Impact Scale (SIS)39,40 were used to assess self-reported disability (activity and participation domains of the ICF model). The specific aim of the study was to determine cross-sectional relationOctober 2009

ships between ST scores and measures of physical function and selfreported disability during the first 6 months of recovery from mild to moderate stroke. We expected that ST scores for both the paretic and nonparetic lower extremities would be positively associated with physical function and self-reported disability. Because of the multiple social and environmental factors affecting self-reported disability, we expected that ST scores would have weaker associations with SIS scores than with measures of physical function.

Method Study Design This was a prospective cohort study. Individuals were identified during an acute hospitalization for stroke and were assessed at monthly intervals for 6 months. Participants Adults who had sustained a unilateral noncerebellar stroke were enrolled as part of a larger study of paretic– lower-extremity loading after stroke. Power analysis was based on the ability to detect a linear association, or correlation, in the data. We determined that a sample size of 30 participants was needed to enable us to identify correlations of size .40 or better at an 80% level of power and .05 level of significance. Participants were recruited by posted flyers and by nursing and therapist contacts at University of North Carolina (UNC) Hospitals in Chapel Hill, North Carolina, and WakeMed Rehab, a rehabilitation hospital in Raleigh, North Carolina. All participants had lowerextremity motor impairment, as indicated by a score of ⱕ28 of the 34 points possible on the lowerextremity motor scale of the FMA.23 Other inclusion criteria were: (1) being medically stable and free of major cardiovascular or musculoskeletal problems, as indicated by physician’s approval for participation in the study; (2) being able to Volume 89

understand and read English; (3) being able to follow 3-step commands; (4) being able to reach in all directions to touch a target with the nonparetic hand while sitting without support; (5) having adequate vision and hearing for completing the study protocol, as indicated by the ability to follow written and oral instructions during screening; and (6) residing within an 80-km (50-mile) radius, with willingness to return to UNC for testing every month from 1 to 6 months poststroke. Exclusion criteria were: (1) a history of previous strokes or other neurologic diseases or disorders; (2) inability to ambulate or live independently in the community prior to the stroke; (3) terminal illness; and (4) pain, limited motion, or weakness in the nonparetic lower extremity that affected performance of daily activities (by self-report). Informed consent was obtained from all participants prior to testing. Procedure Baseline testing was performed at the facility in which the participant was hospitalized and was completed during the time period from hospital admission to 1 month poststroke. At baseline, we examined motor function of the paretic lower extremity using the FMA lower-extremity motor scale. From 1 to 6 months poststroke, participants were tested at monthly intervals at the Center for Human Movement Science at the University of North Carolina at Chapel Hill. Impairments in body structure and function were tested by use of a single measure, the ST. Several measures were used to assess activity and participation, including 2 physical function measures, gait speed and the PFI, and a measure of self-reported disability, the SIS. All tests were administered monthly by the same examiner, with the exception of the SIS, which was administered at 1, 3, and 6 months only. The Number 10

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Step Test Performance and Measures of Activity and Participation After Stroke examiner used new data forms at each session and avoided access to the participant’s previous test scores until after data collection was completed. Step Test. The ST assesses an individual’s ability to place one foot onto a 7.5-cm-high step and then back down to the floor repeatedly as fast as possible for 15 seconds.30 The score is the number of steps completed in the 15-second period for each lower extremity. Participants were permitted to wear any customary orthoses but, in accordance with published procedures for standardized administration,30 were not permitted to use an assistive device during testing. Both sides were tested, with participants completing the test first with the nonparetic foot and then with the paretic foot. Scores for each lower extremity were recorded separately, as well as the sum of these 2 scores. Participants who were unable to stand unsupported were given a score of 0 for both lower extremities. Test-retest reliability of the ST is high, with intraclass correlation coefficients (ICCs) greater than .88 in people undergoing inpatient rehabilitation after stroke.30 The ST has evidence of validity, in that ST scores correlate with other clinical tests of balance and mobility,30 and scores for ST performance with the nonparetic limb as the stepping limb correlate with force platform measures of paretic– lower-extremity loading.41 The ST also has evidence of responsiveness. Following a 4-week period of stroke rehabilitation, the standardized response means (SRMs)42,43 of the ST for the nonparetic and paretic lower extremities were 0.92 and 0.95, respectively.31 Gait speed. Self-selected gait speed was determined from a 10-m walk, which was administered according to standardized procedures.44 A digital stopwatch was used to measure to the 1064

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nearest hundredth of a second the time required for each participant to walk a 10-m distance at his or her “usual, comfortable pace” using any customary assistive devices and orthoses. An additional 5 m was measured and marked at the beginning and end of the 10-m distance to allow the participant enough distance to accelerate and decelerate. The average speed for 2 test trials was recorded. Test-retest reliability of walking speed is high, even in people with stroke or other neurological disorders.36,45 Self-selected walking speed correlates with a number of other measures of walking ability in people with hemiparesis after stroke and has been recommended as an outcome measure for stroke rehabilitation.46 SF-36 Physical Functioning Index. The PFI is a self-report instrument consisting of 10 questions about limitations in higher-level physical activities (eg, vigorous and moderate activities such as pushing a vacuum cleaner, carrying groceries, climbing stairs).38 The score ranges from 0 to 100, with 100 indicating full independence. The PFI was administered by personal interview. Brazier et al47 reported a test-retest reliability coefficient of .81 for the PFI, as well as high internal consistency (Cronbach alpha⫽.93). The SF-36 has been validated for patients with stroke.48 Stroke Impact Scale. The SIS, version 3.0, is a stroke-specific, comprehensive measure of health status.39 For each item, the respondent indicates on a scale of 1 (unable) to 5 (no difficulty at all) the degree of difficulty he or she has had with the item during the past week. Aggregate scores ranging from 0 to 100 are generated for each of the 8 SIS domains. Three domains—mobility, ADL/ IADL, and participation—were selected for use in this study as measures at the level of activity and participation. The SIS was administered during face-to-face interviews

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with the participant or a proxy. A proxy was used for participants with aphasia who were unable to respond in interview or written formats. The same family member acted as a proxy at each administration. The SIS has high test-retest reliability, concurrent validity, and responsiveness to change.39,49 Rasch analysis has revealed that the 3 domains used in the present study are among those having the most robust psychometric characteristics.50 Data Analysis All analyses were conducted using Stata version 9.2.* Descriptive statistics were generated for the baseline characteristics of the sample and for the measurements collected at each session. We conducted t tests and chi-square tests of differences in means or proportions to compare the characteristics of participants who completed all 6 test sessions with those of participants who did not complete all test sessions. Bivariate ordinary least squares (OLS) regression analyses were conducted to examine the relationships between the ST measures and physical function and disability. Separate regression analyses were conducted for each session. In addition, for each relationship we examined, a regression analysis was conducted with the data from all sessions combined. The data for each session and for the sessions combined were plotted to visually examine the relationships between the measures and to verify that linear models were appropriate. Statistical tests were conducted to confirm that the assumptions for OLS analysis were not violated.51 The standard errors for the parameter estimates (ie, slopes of regression

* StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845.

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Step Test Performance and Measures of Activity and Participation After Stroke equations) were corrected if heteroscedasticity was present.52 For the analyses with the data from all sessions combined, the standard errors were corrected to account for the nonindependence of measures within individuals.52 When dealing with data that consist of repeated measures within subjects, one must account for the correlation of measures within subjects when estimating regression parameters. If this nonindependence is unaccounted for, the standard errors of the parameter estimates (eg, the measure of slope in linear regression) may be underestimated, thereby increasing the likelihood of statistically significant findings. One approach to account for the nonindependence of measures within subjects is to use OLS regression and correct the standard errors using the Huber/White/ sandwich estimator of variance.53 This is an acceptable approach when the data are balanced (ie, no missing data) and the variables are normally distributed,54 as was the case with our data. Another advantage of using OLS is that the regression parameters enable prediction of the effect of changing one or more components of X (ie, independent variables) on a given individual (ie, dependent variable for a given individual). Another acceptable approach to deal with the correlation of data within subjects is to use generalized estimating equations (GEEs).54,55 Generalized estimating equations were developed as an extension of the general linear model (eg, OLS regression analysis) to analyze longitudinal and other correlated data, especially when the dependent variable is not normally distributed.54,55 Unlike OLS regression parameters that enable prediction on a given individual, GEEs estimate the average response over the population.43,56 For the GEE models, we specified an identity link function and a normal distribution for the dependent variable because October 2009

Potential participants contacted=112

Declined participation=34

Screened =78

Eligible =45

Ineligible =33 Too high functioning=10 Previous stroke(s)=7 Too low functioning=5 Lived too far away=6 No confirmation of stroke by imaging=4 Cerebellar stroke=1

Declined participation=8 Lost contact=2 Deteriorating cognitive status=2 Enrolled and tested=33

Completed 3 Completed 4 Completed 5 Completed 6 test sessions test sessions test sessions test sessions =3 =25 =1 =4

Figure. Schematic illustrating the recruitment process for the study.

our data were continuous and normally distributed.54 For the analyses examining the relationships between the ST and the functional measures (ie, PFI and gait speed) at the 6 different time points, we specified an autoregressive correlation structure, which is appropriate for withinsubject data that are repeated over time.54 For the analyses examining the relationships between the ST and the disability measures (ie, SIS mobility, ADL/IADL, participation) that had only 3 different time points, we specified an unstructured correlation structure.54 Role of the Funding Sources This study was supported by the National Institutes of Health/National Institute of Child Health and Human Development grant R03HD43907. Partial support was provided by National Institutes of Health/National Volume 89

Institute of Child Health and Human Development grant 5K01HD049593 and National Institutes of Health/National Institute on Aging grant 5P30AG028716 to Dr Purser.

Results During a recruitment period lasting 2 years 4 months, 112 individuals were contacted regarding possible participation in the study (Figure). Approximately 215 adults with a primary diagnosis of cerebral artery occlusion were discharged from our facility each year during this time frame. Thirty-three participants were enrolled in the study and tested. Their baseline characteristics are presented in Table 1. Two individuals with aphasia required proxy administration of the SIS. All participants received usual medical care and rehabilitation during their participation in the study. Fourteen particiNumber 10

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Step Test Performance and Measures of Activity and Participation After Stroke Table 1.

speed, and SIS scores at the first test session.

Baseline Participant Characteristics (n⫽33) Mean (SD) [Range] or N (Percentage)

Variable Age (y)

Descriptive data for the ST, PFI, gait speed, and SIS are presented in Table 2. Eight participants received the lowest possible score on the ST (score of 0) for both lower extremities at all time points. As suggested by Hill et al,30 participants were classified into 3 groups based on whether they had “considerably greater difficulty stepping” with one lower extremity compared with the other lower extremity. “Considerably greater difficulty stepping” was defined as ⱖ3 steps difference between lower-extremity scores at ⱖ2 time points. Twenty-one participants had similar performance with both lower extremities, 10 had greater difficulty stepping with the paretic lower extremity, and 2 had greater difficulty stepping with the nonparetic lower extremity.

58.73 (17.27) [24–97]

Sex Female

15 (45%)

Male

18 (55%)

Race/ethnicity White

18 (55%)

African American

14 (42%)

Hispanic

1 (3%)

Paretic side Right

10 (30%)

Left

23 (70%)

Baseline Fugl-Meyer Assessmenta score a

17.82 (6.22) [7–28]

Lower-extremity motor scale only.

pants were undergoing inpatient rehabilitation when tested at 1 month poststroke. The number receiving physical therapy decreased from 25 at 1 month poststroke to 11 at 6 months poststroke. Study attrition was relatively low, with 3 individuals (9%) dropping out, all after their third test session (Figure). Four participants missed one test session,

and one individual missed 2 test sessions. The 25 participants who completed all 6 test sessions (“completers”) were similar to noncompleters in regard to all baseline characteristics (P⬎.05) except sex, with a greater proportion of female participants not completing all sessions. Completers and noncompleters also were similar in regard to ST, PFI, gait

The results of regression analyses are presented in Tables 3 and 4. At all time points, ST scores were positively associated with both physical function measures. The relationships

Table 2. Descriptive Statistics of Body Structure and Function and Activity and Participation Variablesa Session

Variable

1 (nⴝ33)

2 (nⴝ31)

3 (nⴝ31)

4 (nⴝ30)

5 (nⴝ29)

6 (nⴝ29)

Mean (SD)

Mean (SD)

Mean (SD)

Mean (SD)

Mean (SD)

Mean (SD)

Body structure and function Step Test, paretic limb

3.03 (3.25)

4.90 (3.95)

5.19 (4.42)

5.17 (4.60)

5.86 (5.01)

6.41 (4.63)

Step Test, nonparetic limb

3.48 (3.97)

5.84 (4.57)

5.81 (4.78)

6.27 (5.13)

6.93 (5.44)

7.48 (5.01)

Step Test sum

6.51 (7.08)

10.74 (8.31)

11.00 (8.98)

11.43 (9.48)

12.79 (10.30)

13.90 (9.48)

25.30 (23.11)

38.06 (25.91)

40.16 (26.19)

40.50 (26.98)

38.10 (25.19)

46.38 (23.90)

0.40 (0.36)b

0.56 (0.42)

0.60 (0.44)

0.67 (0.44)

0.71 (0.43)

0.76 (0.42)

Activity and participation, physical function Physical Function Index Gait speed (m/s) Activity and participation, disability SIS, mobility

a b

47.56 (22.65)

61.30 (26.10)

66.86 (22.30)

SIS, ADL/IADL

51.29 (23.75)

59.11 (25.32)

67.33 (21.76)

SIS, participation

31.84 (16.88)

46.48 (22.28)

55.73 (22.71)

SIS⫽Stroke Impact Scale, ADL⫽activities of daily living, IADL⫽instrumental activities of daily living. n⫽32.

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Step Test Performance and Measures of Activity and Participation After Stroke Table 3. Relationships Between Step Test Scores and Physical Function Measuresa Physical Function Index Variable Step Test, paretic limb


Step Test, sum

a

Gait Speed

Session

R

␤

95% CI

R

␤

95% CI

1

.38

4.39

2.35, 6.44

.64

0.09

0.06, 0.11

2

.44

4.35

2.49, 6.21

.74

0.09

0.07, 0.11

3

.38

3.67

1.91, 5.44

.78

0.09

0.07, 0.11

4

.53

4.27

2.71, 5.83

.63

0.08

0.05, 0.10

5

.60

3.89

2.64, 5.15

.73

0.07

0.06, 0.09

2

2

6

.47

3.52

2.04, 5.01

.74

0.08

0.06, 0.10

All

.49

4.08

3.62, 4.53

.72

0.08

0.07, 0.09

GEE

N/A

4.13

3.26, 4.99

N/A

0.05

0.04, 0.06

1

.35

3.46

1.75, 5.18

.60

0.07

0.05, 0.09

2

.45

3.81

2.21, 5.40

.73

0.08

0.06, 0.10

3

.34

3.19

1.50, 4.88

.73

0.08

0.06, 0.10

4

.60

4.07

2.79, 5.36

.66

0.07

0.05, 0.09

5

.53

3.37

2.12, 4.63

.71

0.07

0.05, 0.08

6

.32

2.70

1.14, 4.25

.68

0.07

0.05, 0.09

All

.45

3.52

3.02, 4.02

.70

0.07

0.07, 0.08

GEE

N/A

3.34

2.58, 4.41

N/A

0.03

0.02, 0.04

1

.38

2.01

1.07, 2.95

.64

0.04

0.02, 0.05

2

.47

2.13

1.27, 3.00

.78

0.04

0.04, 0.05

3

.37

1.79

0.92, 2.67

.79

0.04

0.03, 0.05

4

.60

2.20

1.50, 2.90

.68

0.04

0.03, 0.05

5

.58

1.86

1.23, 2.49

.74

0.04

0.03, 0.04

6

.40

1.60

0.83, 2.37

.73

0.04

0.03, 0.05

All

.49

1.97

1.72, 2.22

.73

0.04

0.03, 0.04

GEE

N/A

1.98

1.57, 2.39

N/A

0.02

0.02, 0.03

CI⫽confidence interval, GEE⫽generalized estimating equation, N/A⫽not applicable.

between ST scores and measurements of gait speed were stronger than those between ST and PFI scores, with R2 values ranging from .60 to .79 for the former relationship and from .32 to .60 for the latter relationship (Tab. 3). The strengths of the relationships were similar regardless of whether ST performance was assessed using scores for the paretic or nonparetic lower extremity or the sum of the scores for both extremities. When examining the results of the OLS regression analyses, each additional step with the paretic lower extremity on the ST corresponded to October 2009

a 3.5- to 4.4-point increase in the PFI score (P⬍.001 at all time points) and a 0.07- to 0.09-m/s increase in gait speed (P⬍.001 at all time points). Each additional step with the nonparetic lower extremity was associated with a 2.7- to 4.1-point increase in the PFI score (P⬍.001 at all time points) and a 0.07- to 0.08-m/s increase in gait speed (P⬍.001 at all time points). The results of the GEE models examining the relationship between the ST and the PFI were similar to OLS models examining all of the data. The 95% confidence intervals for the parameter estimates tended to be Volume 89

slightly wider for the GEE models versus the OLS models. The parameter estimates of the GEE models examining the relationship between the ST and gait speed were slightly smaller relative to the OLS models, but still indicated a significant increase in gait speed with each additional step on the ST measures. Step Test scores also were positively associated with the mobility and ADL/IADL domain scores of the SIS at 1, 3, and 6 months poststroke and with the SIS participation scores at the 1- and 3-month time points (Tab. 4). At 6 months, the 95% confidence interval for the beta coeffiNumber 10

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Step Test Performance and Measures of Activity and Participation After Stroke Table 4. Relationships Between Step Test Scores and Self-Reported Disability Measuresa SIS, Mobility Variable Step Test, paretic limb


Step Test, sum

a

SIS, ADL/IADL

SIS, Participation

Session

R

␤

95% CI

R

␤

95% CI

R

␤

1

.34

4.05

1.98, 6.12

.21

3.31

0.92, 5.69

.14

1.91

3

.52

4.28

2.73, 5.83

.37

3.47

1.73, 5.20

.15

1.94

0.18, 3.71

6

.49

3.36

1.99, 4.72

.39

2.94

1.49, 4.38

.13

1.75

⫺0.06, 3.56

2

2

2

95% CI 0.14, 3.67

All

.50

4.07

2.81, 5.33

.36

3.37

2.91, 3.83

.21

2.41

1.18, 3.65

GEE

N/A

3.80

2.84, 4.77

N/A

2.97

2.03, 3.92

N/A

3.24

2.10, 4.38

1

.41

3.67

2.07, 5.27

.22

2.81

0.87, 4.74

.26

2.16

0.82, 3.50

3

.44

3.61

2.05, 5.16

.32

3.00

1.34, 4.66

.13

1.66

0.01, 3.32

6

.49

3.12

1.87, 4.37

.29

2.34

0.89, 3.78

.05

0.98

⫺0.77, 2.72

All

.49

3.62

2.74, 4.50

.32

2.85

2.24, 3.46

.19

2.06

0.26, 3.86

GEE

N/A

2.81

1.99, 3.62

N/A

2.16

1.32, 3.00

N/A

2.79

1.96, 3.62

1

.40

2.01

1.09, 2.92

.22

1.58

0.50, 2.66

.21

1.08

0.30, 1.86

3

.50

2.06

1.28, 2.84

.36

1.69

0.83, 2.55

.14

0.94

0.07, 1.81

6

.51

1.68

1.02, 2.33

.35

1.35

0.62, 2.09

.08

0.69

⫺0.22, 1.60

All

.51

1.99

1.43, 2.54

.35

1.60

1.30, 1.90

.21

1.15

0.38, 1.92

GEE

N/A

1.72

1.27, 2.17

N/A

1.37

0.91, 1.83

N/A

1.72

1.22, 2.22

SIS⫽Stroke Impact Scale, CI⫽confidence interval, GEE⫽generalized estimating equation, N/A⫽not applicable.

cients (ie, slope) for the ST and SIS participation relationship crossed 0 (eg, ST paretic limb and SIS participation at months), indicating no linear association between the 2 variables. The results of the GEE models examining the relationship between the ST and the SIS measures were similar to OLS models examining all of the data. Although the parameter estimates were slightly different with the 2 models, the 95% confidence intervals overlapped. For example, the OLS parameter estimate for the ST (performed with the paretic leg as the stepping leg) and SIS mobility relationship was 4.07 (2.81–5.33), and the GEE parameter estimate was 3.80 (2.84 – 4.77). The strongest relationships between the ST scores and the self-reported disability measures were between the paretic–lower-extremity ST scores and the SIS mobility domain scores. This relationship also tended 1068

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to become a little stronger at the 3and 6-month time points (R2 values of .52 and .49) relative to the 1-month time point (R2 value of .34). The weakest relationships were between the ST scores and SIS participation scores, with a majority of the R2 values below .20.

Discussion Results of this study provide support for relationships between impairments measured by the ST and measures of activity and participation during the first 6 months after stroke. The magnitude of the relationships between ST scores and measurements of gait speed speaks to the importance of dynamic balance or paretic–lower-extremity motor control or the combination of both abilities for walking. In addition, strong relationships between ST scores and SIS mobility domain scores suggest that these abilities may play a role in broader aspects of home and community mobility.

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Adequate balance is a prerequisite for achieving a non-zero score on the ST. Although use of an assistive device can compensate to some extent for balance impairments during walking, previous researchers have reported that balance (measured using the BBS) is a predictor of walking speed and 6-minute walk distance in individuals with chronic stroke14,57 and is the strongest predictor of these outcomes in people with moderate to severe stroke.14 To the extent that the ST is viewed as a measure of balance, our results can be considered to extend these findings to the post–acute phase of stroke recovery. The developers of the ST reported strong correlations between ST scores assessed an average of 54 days poststroke and walking speed in individuals undergoing inpatient rehabilitation.30 These findings are consistent with our results, with ST scores accounting for up to 79% of the variance in walking speed in our participants.

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Step Test Performance and Measures of Activity and Participation After Stroke The effects of balance and strength on walking function often are difficult to separate.14 Perhaps the pattern of ST results for individual patients can help clinicians identify key impairments and design appropriate interventions.30 The 8 participants in our study who scored 0 for both lower extremities on the ST at all time points may have lacked the ability to maintain standing balance or may have had severe deficits in paretic–lower-extremity motor control, or both. Further assessment using the BBS and the FMA lowerextremity motor scale, for example, would be needed to identify specific impairments in these individuals. The 12 participants who had considerably greater difficulty stepping with one lower extremity compared with the other lower extremity apparently had at least minimal balance abilities, but may have had difficulty supporting weight through or performing coordinated movement of the paretic lower extremity. As expected, relationships between ST scores and self-reported disability, as measured by the SIS, were generally lower than those between ST scores and the physical function measures of gait speed and the PFI. Of the 3 SIS domains examined in this study, ST scores explained the largest amount of variance in the mobility domain, presumably reflecting the importance of walking for home and community mobility. Positive associations between ST scores and the ADL/IADL domain of the SIS are consistent with previous reports of correlations in post–acute stroke between measures of balance and lower-extremity motor control and measures such as the Barthel Index or the Functional Independence Measure.19,22,24,32 The magnitudes of the correlations in our study generally were somewhat lower than in previous work, possibly because of the inclusion of items reflecting

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higher-level IADL performance on the SIS. Weak associations between ST scores and the SIS participation domain are indicative of the influence of multiple environmental and personal factors, beyond the individual’s physical function, in determining social roles and quality of life after stroke. The balance and motor control abilities measured by the ST may have figured more prominently in participation in the first few months of stroke rehabilitation, when a majority of the participants were receiving physical therapy and many were in inpatient rehabilitation. By 6 months poststroke, participants had been reintegrated into long-term living environments, and family and other social supports most likely increased in importance. In a study by Desrosiers et al,58 a discharge measure of lower-extremity motor coordination (LEMOCOT) requiring subjects to move the paretic foot alternately between 2 targets was a significant predictor of participation at 6 months and 2 to 4 years poststroke. These associations were similar in strength to our ST-SIS participation relationships, despite the fact that the LEMOCOT is performed in a sitting position and, therefore, lacks a standing balance component. The importance of balance relative to upper- or lower-extremity motor control in determining level of participation may decrease in more chronic stages of recovery after stroke.15 An important strength of this study was collection of data from the same participants at multiple time points, beginning less than 1 month after stroke and continuing at 6 subsequent time points. One limitation of the study was the relatively small sample size. In addition, the examiner was not blinded with regard to participant characteristics, thereby introducing the possibility of bias in Volume 89

testing. We attempted to minimize bias by adhering to standard testing protocols and by avoiding examiner access to previous test scores.

Conclusion Impairments in balance and lowerextremity motor abilities, as measured by the ST, were associated with measures of activity and participation from 1 to 6 months poststroke. The strongest associations were between ST scores and measures of physical function and mobility, such as gait speed. Associations between ST scores and scores on the participation domain of the SIS were weakest and tended to decrease over time. The ST is a simple and quick assessment that can provide important information for clinical decision making. Dr Mercer, Dr Freburger, and Dr Purser provided concept/idea/research design and writing. Dr Mercer and Dr Chang provided data collection and project management. Dr Mercer and Dr Freburger provided data analysis and fund procurement. Dr Mercer provided participants and facilities/equipment. Dr Freburger, Dr Chang, and Dr Purser provided consultation (including review of manuscript before submission). The study was approved by the Biomedical Institutional Review Board at the University of North Carolina at Chapel Hill and by the WakeMed Rehab Institutional Review Board. A platform presentation of this research was given at the Combined Sections Meeting of the American Physical Therapy Association; February 14 –18, 2007; Boston, Massachusetts, and a poster presentation and thematic poster session presentation were given at the Combined Sections Meeting of the American Physical Therapy Association; February 1–5, 2006; San Diego, California. This study was supported by the National Institutes of Health/National Institute of Child Health and Human Development grant R03HD43907. Partial support was provided by National Institutes of Health/National Institute of Child Health and Human Development grant 5K01HD049593 and National Institutes of Health/National Institute on Aging grant 5P30AG028716 to Dr Purser.

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Step Test Performance and Measures of Activity and Participation After Stroke This article was received November 20, 2008, and was accepted June 21, 2009. DOI: 10.2522/ptj.20080368

References 1 Rosamond W, Flegal K, Furie K, et al. Heart disease and stroke statistics—2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2008;117:e25– e146. 2 Bonita R, Solomon N, Broad JB. Prevalence of stroke and stroke-related disability: estimates from the Auckland stroke studies. Stroke. 1997;28:1898 –1902. 3 Gordon NF, Gulanick M, Costa F, et al. Physical activity and exercise recommendations for stroke survivors: an American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical Activity, and Metabolism; and the Stroke Council. Circulation. 2004;109:2031–2041. 4 Brown DL, Boden-Albala B, Langa KM, et al. Projected costs of ischemic stroke in the United States. Neurology. 2006;67: 1390 –1395. 5 International Classification of Functioning, Disability and Health: ICF. Geneva, Switzerland: World Health Organization; 2001. 6 Jette AM. Toward a common language for function, disability, and health. Phys Ther. 2006;86:726 –734. 7 Jette AM, Tao W, Haley SM. Blending activity and participation subdomains of the ICF. Disabil Rehabil. 2007;29:1742– 1750. 8 Roth EJ, Heinemann AW, Lovell LL, et al. Impairment and disability: their relation during stroke rehabilitation. Arch Phys Med Rehabil. 1998;79:329 –335. 9 Desrosiers J, Noreau L, Rochette A, et al. Predictors of handicap situations following post-stroke rehabilitation. Disabil Rehabil. 2002;24:774 –785. 10 Desrosiers J, Malouin F, Bourbonnais D, et al. Arm and leg impairments and disabilities after stroke rehabilitation: relation to handicap. Clin Rehabil. 2003;17: 666 – 673. 11 Andrews AW, Bohannon RW. Discharge function and length of stay for patients with stroke are predicted by lower extremity muscle force on admission to rehabilitation. Neurorehabil Neural Repair. 2001;15:93–97. 12 Bohannon RW, Walsh S. Nature, reliability, and predictive value of muscle performance measures in patients with hemiparesis following stroke. Arch Phys Med Rehabil. 1992;73:721–725. 13 Balasubramanian CK, Bowden MG, Neptune RR, Kautz SA. Relationship between step length asymmetry and walking performance in subjects with chronic hemiparesis. Arch Phys Med Rehabil. 2007;88: 43– 49.

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14 Patterson SL, Forrester LW, Rodgers MM, et al. Determinants of walking function after stroke: differences by deficit severity. Arch Phys Med Rehabil. 2007;88: 115–119. 15 Desrosiers J, Noreau L, Rochette A, et al. Predictors of long-term participation after stroke. Disabil Rehabil. 2006;28: 221–230. 16 Shelton FD, Volpe BT, Reding M. Motor impairment as a predictor of functional recovery and guide to rehabilitation treatment after stroke. Neurorehabil Neural Repair. 2001;15:229 –237. 17 Glass TA, Matchar DB, Belyea M, Feussner JR. Impact of social support on outcome in first stroke. Stroke. 1993;24:64 –70. 18 Barak S, Duncan PW. Issues in selecting outcome measures to assess functional recovery after stroke. NeuroRx. 2006;3: 505–524. 19 Fong KN, Chan CC, Au DK. Relationship of motor and cognitive abilities to functional performance in stroke rehabilitation. Brain Inj. 2001;15:443– 453. 20 Bohannon RW. Strength deficits also predict gait performance in patients with stroke. Percept Mot Skills. 1991;73:146. 21 Berg KO, Wood-Dauphineé SL, Williams JI, Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can. 1989;41: 304 –311. 22 Berg KO, Wood-Dauphineé SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992;83(suppl 2):S7–S11. 23 Fugl-Meyer AR, Jaasko L, Leyman I, et al. The post-stroke hemiplegic patient, 1: a method for evaluation of physical performance. Scand J Rehabil Med. 1975;7: 13–31. 24 Blum L, Korner-Bitensky N. Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Phys Ther. 2008;88:559 –566. 25 Salter K, Jutai JW, Teasell R, et al. Issues for selection of outcome measures in stroke rehabilitation: ICF activity. Disabil Rehabil. 2005;27:315–340. 26 Salter K, Jutai JW, Teasell R, et al. Issues for selection of outcome measures in stroke rehabilitation: ICF body functions. Disabil Rehabil. 2005;27:191–207. 27 Stevenson TJ. Detecting change in patients with stroke using the Berg Balance Scale. Aust J Physiother. 2001;47:29 –38. 28 Malouin F, Pichard L, Bonneau C, et al. Evaluating motor recovery early after stroke: comparison of the Fugl-Meyer Assessment and the Motor Assessment Scale. Arch Phys Med Rehabil. 1994;75: 1206 –1212. 29 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. 30 Hill KD, Bernhardt J, McGann AM, et al. A new test of dynamic standing balance for stroke patients: reliability, validity and comparison with healthy elderly. Physiother Can. 1996;48:257–262.

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31 Bernhardt J, Ellis P, Denisenko S, Hill K. Changes in balance and locomotion measures during rehabilitation following stroke. Physiother Res Int. 1998;3: 109 –122. 32 Chae J, Johnston M, Kim H, Zorowitz R. Admission motor impairment as a predictor of physical disability after stroke rehabilitation. Am J Phys Med Rehabil. 1995; 74:218 –223. 33 Jørgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995; 76:27–32. 34 Patel AT, Duncan PW, Lai SM, Studenski S. The relation between impairments and functional outcomes poststroke. Arch Phys Med Rehabil. 2000;81:1357–1363. 35 Duncan PW, Goldstein LB, Matchar D, et al. Measurement of motor recovery after stroke. outcome assessment and sample size requirements. Stroke. 1992; 23:1084 –1089. 36 Collen FM, Wade DT, Bradshaw CM. Mobility after stroke: reliability of measures of impairment and disability. Int Disabil Stud. 1990;12:6 –9. 37 Green J, Forster A, Young J. Reliability of gait speed measured by a timed walking test in patients one year after stroke. Clin Rehabil. 2002;16:306 –314. 38 Ware JE Jr, Sherbourne CD. The MOS 36item short-form health survey (SF-36), I: conceptual framework and item selection. Med Care. 1992;30:473– 483. 39 Duncan PW, Wallace D, Lai SM, et al. The Stroke Impact Scale version 2.0. evaluation of reliability, validity, and sensitivity to change. Stroke. 1999;30:2131–2140. 40 Lai SM, Studenski S, Duncan PW, Perera S. Persisting consequences of stroke measured by the Stroke Impact Scale. Stroke. 2002;33:1840 –1844. 41 Mercer VS, Freburger JK, Chang SH, Purser JL. Measurement of paretic–lowerextremity loading and weight transfer after stroke. Phys Ther. 2009;89:653– 664. 42 Katz JN, Larson MG, Phillips CB, et al. Comparative measurement sensitivity of short and longer health status instruments. Med Care. 1992;30:917–925. 43 Liang MH, Fossel AH, Larson MG. Comparisons of five health status instruments for orthopedic evaluation. Med Care. 1990; 28:632– 642. 44 Taylor D, Stretton CM, Mudge S, Garrett N. Does clinic-measured gait speed differ from gait speed measured in the community in people with stroke? Clin Rehabil. 2006;20:438 – 444. 45 Holden MK, Gill KM, Magliozzi MR, et al. Clinical gait assessment in the neurologically impaired: reliability and meaningfulness. Phys Ther. 1984;64:35– 40. 46 Witte US, Carlsson JY. Self-selected walking speed in patients with hemiparesis after stroke. Scand J Rehabil Med. 1997;29: 161–165.

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Step Test Performance and Measures of Activity and Participation After Stroke 47 Brazier JE, Harper R, Jones NM, et al. Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ. 1992;305:160 –164. 48 Anderson C, Laubscher S, Burns R. Validation of the Short Form 36 (SF-36) health survey questionnaire among stroke patients. Stroke. 1996;27:1812–1816. 49 Salter K, Jutai JW, Teasell R, et al. Issues for selection of outcome measures in stroke rehabilitation: ICF participation. Disabil Rehabil. 2005;27:507–528. 50 Duncan PW, Bode RK, Min Lai S, Perera S; Glycine Antagonist in Neuroprotection Americans Investigators. Rasch analysis of a new stroke-specific outcome scale: the Stroke Impact Scale. Arch Phys Med Rehabil. 2003;84:950 –963.

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51 Berry WD. Understanding Regression Assumptions. Thousand Oaks, CA: Sage Publications; 1993. 52 StataCorp Inc. Stata Base Reference Manual. Vol 3, R-Z, release 9. College Station, TX: Stata Press; 2005. 53 Estimation and post-estimation commands. In: Stata 9 User’s Guide. College Station, TX: Stata Press; 2005: chap 20. 54 Ballinger GA. Using generalized estimating equations for longitudinal data analysis. Organizational Research Methods. 2004; 7:127–150. 55 Hanley JA, Negassa A, Edwardes MD, Forrester JE. Statistical analysis of correlated data using generalized estimating equations: An orientation. Am J Epidemiol. 2003;157:364 –375.

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56 Zeger SL, Liang K. Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986;42:121–130. 57 Pang MY, Eng JJ, Dawson AS. Relationship between ambulatory capacity and cardiorespiratory fitness in chronic stroke: Influence of stroke-specific impairments. Chest. 2005;127:495–501. 58 Desrosiers J, Rochette A, Noreau L, et al. Long-term changes in participation after stroke. Top Stroke Rehabil. 2006;13: 86 –96.

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Research Report

Muscle Deficits Persist After Unilateral Knee Replacement and Have Implications for Rehabilitation Anu Valtonen, Tapani Poÿho¨nen, Ari Heinonen, Sarianna Sipila¨ A. Valtonen, PT, MSc, is Researcher, Rehabilitation and Pain Unit, Kymenlaakso Central Hospital, Kotkantie 41, FIN-48210 Kotka, Finland, and Department of Health Sciences, University of Jyva¨skyla¨, Jyva¨skyla¨, Finland. Address all correspondence to Ms Valtonen at: anu.m.valtonen@ jyu.fi. T. Poÿho¨nen, PT, PhD, is Exercise Physiologist, Rehabilitation and Pain Unit, Kymenlaakso Central Hospital. A. Heinonen, PT, PhD, is Professor, Department of Health Sciences, University of Jyva¨skyla¨. S. Sipila¨, PT, PhD, is Research Director, Finnish Centre for Interdisciplinary Gerontology, Department of Health Sciences, University of Jyva¨skyla¨. [Valtonen A, Poÿho¨nen T, Heinonen A, Sipila¨ S. Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. Phys Ther. 2009; 89:1072–1079.] © 2009 American Physical Therapy Association

Background. Knee joint arthritis causes pain, decreased range of motion, and mobility limitation. Knee replacement reduces pain effectively. However, people with knee replacement have decreases in muscle strength (“force-generating capacity”) of the involved leg and difficulties with walking and other physical activities. Objective and Design. The aim of this cross-sectional study was to determine the extent of deficits in knee extensor and flexor muscle torque and power (ability to perform work over time) and in the extensor muscle cross-sectional area (CSA) after knee joint replacement. In addition, the association of lower-leg muscle deficits with mobility limitations was investigated. Methods. Participants were 29 women and 19 men who were 55 to 75 years old and had undergone unilateral knee replacement surgery an average of 10 months earlier. The maximal torque and power of the knee extensor and flexor muscles were measured with an isokinetic dynamometer. The knee extensor muscle CSA was measured with computed tomography. The symmetry deficit between the knee that underwent replacement surgery (“operated knee”) and the knee that did not undergo replacement surgery (“nonoperated knee”) was calculated. Maximal walking speed and stair-ascending and stair-descending times were assessed.

Results. The mean deficits in knee extensor and flexor muscle torque and power were between 13% and 27%, and the mean deficit in the extensor muscle CSA was 14%. A larger deficit in knee extension power predicted slower stair-ascending and stair-descending times. This relationship remained unchanged when the power of the nonoperated side and the potential confounding factors were taken into account.

Limitations. The study sample consisted of people who were relatively healthy and mobile. Some participants had osteoarthritis in the nonoperated knee. Conclusions. Deficits in muscle torque and power and in the extensor muscle CSA were present 10 months after knee replacement, potentially causing limitations in negotiating stairs. To prevent mobility limitations and disability, deficits in lowerlimb power should be considered during rehabilitation after knee replacement.

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Muscle Deficits and Mobility After Knee Replacement

W

ith an aging population, the prevalence of degenerative joint diseases, such as knee joint arthritis, increases and thus adds to the burden of health care systems in Western societies. Knee joint arthritis causes pain, decreased range of motion, and mobility limitations. Knee joint replacement is a common surgical procedure that effectively reduces pain.1– 4 However, several studies2,5–12 have shown that people with knee replacement surgery have difficulties with walking and other physical activities. Mobility undergoes an expected decline during the first month after knee replacement.7 Mizner et al7 reported that performance in stair-climbing and “stand-up-and-go” tests returned to the preoperative level at 2 months after surgery. Therefore, although functional ability may improve to the preoperative level, which already is severely impaired because of pain and long-term disuse, it rarely reaches the level in age-matched control subjects.5,12,13 For example, Walsh et al5 and Yoshida et al12 reported that people with knee replacement had a lower maximal walking speed5,12 and negotiated stairs more slowly5 than control subjects even beyond 1 year after surgery. Mobility limitations are known to be associated with decreases in muscle strength (force-generating capacity) and power (ability to perform work over time). These impairments continue to persist for several months after surgery.5,7,8,10,14 –16 Several investigators7,11,14,17–19 have reported declines of 21% to 42% in knee extensor torque and power for the knee that underwent replacement surgery (“operated knee”) compared with the knee that did not undergo replacement surgery (“nonoperated knee”) at 3 to 6 months after surgery. Furthermore, even at 1 to 2 years after knee replacement surgery, a difference of 12% to 29% between the knee extensor muscles has been re-

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ported.5,9,17 Similar deficits have been reported for knee flexor muscle strength.5,14 Knee extensor muscle strength has been reported to remain 19% to 35% lower in people with knee replacement than in agematched people, even at 13 years after surgery.5,11,20 –22 Previous studies11,18,23,24 indicated that there is a decline in the knee extensor muscle cross-sectional area (CSA) of the operated leg during the early recovery phase—1 to 3 months after surgery— compared with the preoperative CSA. To our knowledge, no studies comparing muscle CSA between the legs or reporting spontaneous long-term recovery of muscle CSA after knee replacement surgery have been done. Mobility limitations may be related to lower-limb muscle deficits, that is, side-to-side differences between the operated leg and the nonoperated leg. Previous studies showed that in people who are healthy25,26 and in some clinical populations,27–29 lower-limb power deficits have detrimental effects on mobility. Portegijs et al25 reported that in people who were healthy, knee extensor power asymmetry was associated with a lower walking speed. Additionally, they found that in women recovering from hip fractures, a larger power deficit was associated with limitations in stair-climbing ability.29 To date, little is known about muscle deficits and their persistent effects on mobility limitations in people with knee replacement. Therefore, the purpose of this study was to determine the extent of muscle deficits in knee extensor and flexor muscle torque and power and in the extensor muscle CSA and composition in a group of people who had undergone unilateral knee replacement an average of 10 months earlier. In addition, the association of lower-limb muscle

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deficits with mobility limitations was investigated.

Methods Setting and Participants A total of 201 people who, according to the physical therapy records of Kymenlaakso Central Hospital, had undergone unilateral knee replacement 4 to 18 months before the study were informed about the study. Eighty-six people contacted the research personnel. People with bilateral knee arthroplasty, revision arthroplasty, hemiarthroplasty, severe cardiovascular diseases, dementia, rheumatoid arthritis, or major surgery on either of the knees were excluded from the study. Thus, 48 eligible volunteers (29 women and 19 men; age range⫽55–75 years) participated in the study. The physical characteristics of the participants are shown in Table 1. All of the participants had undergone knee replacement surgery with cement fixation. Eight of the 48 participants had osteoarthritis diagnosed in the nonoperated knee. The data used in this cross-sectional study were collected in 2 phases. Because of the small number of eligible subjects in spring 2005, the data collection was repeated in autumn 2005 with the same recruitment protocol, infrastructure, and staff. Before the laboratory examinations, the participants were informed about the study and gave written informed consent. Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on August 27, 2009, at www.ptjournal.org.

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Muscle Deficits and Mobility After Knee Replacement Table 1. Physical Characteristics of Participants Women (nⴝ29) Characteristic

X

SD

Range

X

SD

Range

67.7

5.5

57–75

65.2

6.2

55–75

Body weight (kg)

79.4

13.6

56.0–115.2

89.1

15.9

70.1–122.0

Body height (cm)

163.3

5.4

152–172

175.4

7.2

161–189

Body mass index

29.7

4.6

21.9–42.2

28.8

3.7

23.2–34.5

9.2

4.5

5–18

9.8

4.2

4–18

Age (y)

Time after surgery (mo) Walking speed (m/s)

1.7

0.3

0.9–2.3

2.1

0.6

0.9–3.8

Stair-ascending time (s)

5.9

2.5

3.6–13.2

3.9

1.8

2.3–10.3

Stair-descending time (s)

6.7

4.2

3.1–21.8

4.1

2.2

2.3–11.2

Measurements The clinical history of the participants, including their medications and diseases, were confirmed by a physician before the laboratory examinations. Body height and body weight were measured by use of standard procedures. The day-to-day intrarater reproducibility of the measurements (muscle torque, power, walking speed, stair ascending, and stair descending) was measured in our laboratory with a pilot sample. The measurements were performed twice by use of identical procedures, with an interval of 1 week between the measurement occasions. In a pilot study (unpublished), 17 volunteers (12 women and 5 men; mean age⫽77 years, range⫽55–75) with unilateral knee replacement an average of 8 months (range⫽4 –12) after surgery participated in the measurements. The intraclass correlation coefficient (ICC) was calculated by use of a 1-way random model. The participants in the pilot sample were not included in the sample in the current study. The reliability (ICC) of each measurement is presented in context with the measurement. Muscle torque and power. The maximal isokinetic torque (N䡠m) of the knee extensor and flexor muscles was measured by use of an iso-

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kinetic dynamometer* with a sampling frequency of 100 Hz and a measurement error of 1% through the entire range of motion. The dynamometer was calibrated before each measurement session according to the standard procedure recommended by the manufacturer. Before the measurement session, the participants were carefully familiarized with the testing procedure. For each leg, the axis of rotation of the dynamometer was aligned with the condylus lateralis femoris. The lever arm of the dynamometer was attached around the ankle 2.5 cm above the midpoint of the malleolus lateralis. The hip and thigh were stabilized with straps. The full knee range of motion was measured. The nonoperated leg was measured first. After a few submaximal flexionextension movements, 3 maximal continuous flexion-extension trials were performed at an angular velocity of 60°/s, and 5 trials were performed at a velocity of 180°/s, with 2 to 3 minutes of rest between trials. The participants were verbally encouraged to make a maximal effort throughout the whole range of motion. The highest peak torque (N䡠m) at an angular velocity of 60°/s was analyzed. Peak power was analyzed * Biodex Medical Systems Inc, 20 Ramsey Rd, Shirley, NY 11967-4704.

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in extension and flexion at an angular velocity of 180°/s. The ICC of the isokinetic parameters for the operated knee in the people with knee replacement varied between .90 and .97. Muscle CSA and attenuation. Computed tomography (CT) scans were obtained from both midthighs by use of a Siemens Somatom DR Scanner† with the subject in a supine position. The midthigh was defined as the midpoint between the greater trochanter and the lower edge of the patella. The scans were analyzed by use of software developed for crosssectional CT image analysis (Geanie 2.1‡), which separates fat and lean tissues on the basis of radiological density (measured as attenuation in Hounsfield units) limits. The quadriceps femoris muscle was determined manually by drawing a line along the fascial plane. A lower mean attenuation value reflects greater fat infiltration within the muscle. The Figure shows an example of the CT analysis. The CT measurements and analyses were conducted in a masked fashion. In our previous study,30 the coefficients of variation between 2 consecutive repeated measurements were calculated and shown to be less than 1% for lean tissue Hounsfield units and 1% to 2% for the CSA. † ‡

Siemens AG, Erlangen, Germany. Commit Ltd, Espoo, Finland.

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Muscle Deficits and Mobility After Knee Replacement Mobility Assessment Walking speed. Maximal walking speed over 10 m was measured in the hospital corridor. Walking time was recorded by use of photocells.§ Participants were instructed to walk as fast as possible without compromising their safety. All participants wore thin aquatic shoes and were allowed 3 m for acceleration. Each participant performed 2 trials, separated by a 1-minute rest period, and the fastest time was accepted as the best result. The ICC for maximal walking speed in people with knee replacement was .86. Negotiating stairs. Times to ascend and descend a 10-step staircase were measured in the hospital corridor. The stair height was 17 cm, and the depth was 29.5 cm. The participants were instructed to step alternately on each stair and walk as fast as possible without compromising their safety. The use of a handrail or taking a step on each stair with both feet was allowed only when necessary. Three participants stepped on each stair with both feet in the stairascending task, and 7 did so in the stair-descending task. Ascending and descending times were recorded by use of photocells.§ Each participant performed 2 ascending trials, followed by a 1-minute rest period, and then performed 2 descending trials. The fastest times were accepted as the best results. The ICCs were .90 for stair ascending and .73 for stair descending in the participants with knee replacement. Data Analysis The differences in muscle characteristics (torque, power, CSA, and attenuation) between the operated leg and the nonoperated leg were analyzed with a paired 2-tailed Student t test. The muscle symmetry deficit (relative difference) was calculated according to the following equation:

Figure. Cross-sectional computed tomography scans obtained from the midthighs of a 70year-old woman who had undergone total unilateral knee replacement 9 months earlier. (A) Thigh on side opposite surgery; total muscle cross-sectional area was 79 cm2, mean attenuation of the muscle tissue was 39.1 Hounsfield units, and total fat crosssectional area was 60.8 cm2. (B) Thigh on side of surgery; total muscle cross-sectional area was 68 cm2, mean attenuation of the muscle tissue was 35.8 Hounsfield units, and total fat cross-sectional area was 68.1 cm2. Muscles: Add⫽adductor, H⫽hamstring, RF⫽rectus femoris, VL⫽vastus lateralis, VM⫽vastus medialis.

symmetry deficit (%) ⫽ [(value for nonoperated leg ⫺ value for operated leg)/value for nonoperated leg] ⫻ 100. Stepwise multiple linear regression models were used to examine the most relevant muscle deficit (muscle torque, power, CSA, and attenuation) and muscle power variable associated with mobility limitations. Variables with nonsignificant independent associations with mobility were removed from the final model. Thus, the final model contained only the explanatory variables that had significant independent associations with mobility limitations and that had the highest possible proportion of the variance explained by coefficients of determination (adjusted R2). The models were further adjusted for age, sex, and time after surgery. For the regression analysis, the results obtained for men and women were pooled because there were no sex differences in age, time after surgery, or any of the muscle deficit variables. Significance was set

Results Knee Extensor Muscles For the entire group, the mean knee extensor torque, power, CSA, and attenuation values for the operated side were significantly (P⬍.001) lower than those for the nonoperated side. For the knee extensor muscles, more than 97% of the participants had lower or equal values in the operated leg than in the nonoperated leg. The mean knee extension torque deficit was 27% (95% confidence interval [CI]⫽22%–32%), and the mean knee extension power deficit was 23% (95% CI⫽17%–29%). The mean knee extensor muscle CSA deficit was 14% (95% CI⫽11%–18%), and the mean knee extensor attenuation deficit was 9% (95% CI⫽6%– 11%). The results for the knee extensor muscles are shown in Table 2.

㛳

§

Newtest Oy, Koulukatu 31 B 11, FIN-90100, Oulu, Finland.

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at P⬍.05. Statistical analyses were run with SPSS (version 13.0) software.㛳

SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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Muscle Deficits and Mobility After Knee Replacement Table 2. Knee Extensor Torque, Power, Cross-Sectional Area, and Attenuation in Operated and Nonoperated Kneesa Operated Knee Group Women

X

SD

X

SD

Pb

Symmetry Deficit, %c (95% CI)

Torque, N䡠m

64.7

17.2

89.9

20.5

⬍.001

26 (18–34)

Power, W

95.4

35.1

127.9

31.8

⬍.001

26 (18–34)

CSA, cm2

36.6

8.5

42.4

8.2

⬍.001

14 (8–19)

Measure

36.8

5.0

40.3

3.8

⬍.001

9 (5–13)

Torque, N䡠m

100.0

27.0

141.5

35.5

⬍.001

29 (22–36)

Power, W

148.5

44.9

190.1

60.9

.001

CSA, cm2

52.7

12.0

62.5

10.9

⬍.001

Attenuation, HU

39.2

6.4

42.8

5.2

⬍.001

9 (5–13)

Torque, N䡠m

79.6

27.9

111.7

37.7

⬍.001

27 (22–32)

Attenuation, HU Men

All

a b c

Nonoperated Knee

19 (9–28) 16 (11–21)

Power, W

117.3

47.1

153.6

55.0

⬍.001

23 (17–29)

CSA, cm2

42.9

12.7

50.3

13.6

⬍.001

14 (11–18)

Attenuation, HU

37.7

5.6

41.3

4.5

⬍.001

9 (6–11)

CI⫽confidence interval, CSA⫽cross-sectional area, HU⫽Hounsfield units. Determined with the equality of means test for the operated knee versus the nonoperated knee. Symmetry deficit (%)⫽[(value for nonoperated leg ⫺ value for operated leg)/value for nonoperated leg] ⫻ 100.

Knee Flexor Muscles For the entire group, the mean knee flexor torque and power values for the operated side were significantly (P⬍.001) lower than those for the nonoperated side. For the knee flexor muscles, over 87% of the participants had lower or equal values in the operated leg than in the nonoperated leg. The mean knee flexion torque deficit was 13% (95% CI⫽7%– 19%), and the mean knee flexion power deficit was 19% (95%

CI⫽11%–27%). The results for the knee flexor muscles are shown in Table 3. Mobility For the entire group, the mean (SD) maximal 10-m walking speed, stairascending time, and stair-descending time were 1.9 (0.5) m/s, 5.1 (2.4) seconds, and 5.6 (3.7) seconds, respectively. The results for mobility are shown separately for women and men in Table 1.

Multivariate regression analysis was performed to examine the association among muscle deficit, muscle power production, and negotiating stairs (Tabs. 4 and 5). A larger knee extension power deficit, together with low knee flexion power on the nonoperated side, predicted slower stair-ascending time (Tab. 4). Adjustments for age, sex, and time after surgery did not materially change the association. In addition, a larger knee extension power deficit, together

Table 3. Knee Flexor Torque and Power in Operated and Nonoperated Kneesa Operated Knee Measure

Women

Torque, N䡠m

40.9

12.1

48.9

11.2

.001

Power, W

85.1

32.5

109.8

31.3

⬍.001

Torque, N䡠m Power, W

All

Torque, N䡠m Power, W

a b c

SD

X

SD

Pb

Group

Men

X

Nonoperated Knee

Symmetry Deficit, %c (95% CI) 16 (7–24) 22 (13–32)

71.4

17.9

80.4

21.2

.016

10 (1–18)

133.4

43.5

168.1

54.3

.012

14 (0–28)

53.8

21.2

62.2

22.4

⬍.001

13 (7–19)

105.0

44.1

133.9

50.9

⬍.001

19 (11–27)

CI⫽confidence interval. Determined with the equality of means test for the operated knee versus the nonoperated knee. Symmetry deficit (%)⫽[(value for nonoperated leg ⫺ value for operated leg)/value for nonoperated leg] ⫻ 100.

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Muscle Deficits and Mobility After Knee Replacement Table 4. Factors Explaining Variability in Stair-Ascending Time in People With Unilateral Knee Replacement Crudea Factor Extension power deficit Flexion power of the nonoperated knee, W

Adjustedb

␤

P

0.042 (0.013)

.404

.002

0.039 (0.014)

.379

⫺0.020 (0.005)

⫺.481

⬍.001

⫺0.017 (0.007)

⫺.423

.021

0.007 (0.052)

.021

.888

B (SEE)

Age, y

a b

␤

B (SEE)

P .006

Sex

⫺0.333 (0.663)

⫺.080

.618

Time after surgery, mo

⫺0.021 (0.060)

⫺.044

.732

R2⫽.372 for the crude model. B⫽unstandardized regression coefficient, SEE⫽standard error of the estimate. R2⫽.378 for the adjusted model.

with low knee flexion power on the nonoperated side, predicted slower stair-descending time (Tab. 5). Adjustments for potential confounding factors did not materially change the association.

Discussion The results of this study showed that at an average of 10 months after knee replacement surgery, the operated leg was significantly weaker than the nonoperated leg, and the extensor muscle CSA in the operated leg was smaller than that in the nonoperated leg. A larger knee extension power deficit predicted slower stair-ascending and stair-descending times. This relationship remained unchanged when the power of the nonoperated side and potential confounding factors were taken into account. Lower-limb muscle power, especially the difference between the legs, seemed to be critical for

mobility limitations; therefore, it should be considered during evaluations of mobility in both people who are healthy and people who have disabilities. In the majority of the participants, the operated leg was weaker than the nonoperated leg, and the muscle CSA of the operated leg was smaller than that of the nonoperated leg. The results of the present study are in line with those of previous studies that investigated muscle force 6 to 12 months after unilateral knee replacement.5,7,14,17 A comparison of the results of the present study and those previously reported is difficult because we calculated the muscle strength deficit for each participant individually, whereas in earlier studies, side-to-side differences were estimated from group mean values. Overall, the deficit in the knee extensor muscles after knee replacement

surgery is considerable and can also be prolonged; the leg with the knee replacement has been shown to be significantly weaker than the legs of healthy control subjects for as long as 13 years after the surgery.5,20 –22 Previous studies7,14,17 showed a difference of 15% to 29% in knee extension torque between the operated leg and the nonoperated leg, which is in line with the 27% difference found in the present study. Rossi and Hasson,16 however, reported a marked, 38% difference in the findings for a single leg press between the operated leg and the nonoperated leg at 16 months after knee replacement. This large side-to-side difference may have been attributable to the multiple muscle groups involved in the leg press. We also found a marked knee flexor torque deficit (ie, 13%) after an average of 10 months from knee replace-

Table 5. Factors Explaining Variability in Stair-Descending Time in People With Unilateral Knee Replacement Crudea Factor Extension power deficit Flexion power of the nonoperated knee, W

B (SEE)

Adjustedb

␤

P

B (SEE)

.001

0.061 (0.019)

.425

⫺0.026 (0.007)

⫺.455

.001

⫺0.021 (0.010)

⫺.369

.043

0.063 (0.071)

.129

.383

⫺0.218 (0.917)

⫺.038

.813

0.021 (0.083)

.032

.800

Sex Time after surgery, mo b

P

.421

Age, y

a

␤

0.060 (0.018)

.003

R2⫽.362 for the crude model. B⫽unstandardized regression coefficient, SEE⫽standard error of the estimate. R2⫽.376 for the adjusted model.

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Muscle Deficits and Mobility After Knee Replacement ment. This finding supports the results of 2 earlier studies reporting a side-to-side difference of 16% to 23% in knee flexor muscles at 6 to 12 months after surgery.5,14 Therefore, this muscle group should receive attention during assessment and rehabilitation of degenerative knee joint problems. We also found 19% to 23% deficits in knee extensor and flexor muscle power; these values were somewhat higher than the value reported by Lamb and Frost,6 who found a difference of 18% in leg extension power at 6 months after knee replacement. This substantial deficit should be taken into consideration in rehabilitation programs because in daily activities it is important to have the muscle power needed to produce effective force quickly to generate desirable or prevent undesirable movements. In particular, the ability to recover from a stumble is highly dependent on the power and coordination of the leg muscles.31–33 In addition, Portegijs et al26 found that, even in people who were healthy, a knee extension power deficit was associated with falls. Although we did not evaluate falls after knee replacement in the present study, we would argue in accordance with the literature26,28 that a power deficit should be taken seriously as a risk factor for falls and therefore should be considered in knee replacement rehabilitation. The extensor muscle CSA deficit was marked (14%) in the present study. To our knowledge, a long-term muscle CSA deficit has not been studied. Previous studies11,18,23,24 showed declines of 5% to 20% (relative to preoperative values) in knee extensor muscle CSA in the operated leg at 1 to 3 months after knee replacement. In the present study, the most likely reason for the large side-to-side difference, in addition to long-term pain and disuse because of osteoar1078

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thritis, was the surgery itself, which resulted in a long wound, considerable surgical trauma, and a long recovery time. In people with hip osteoarthritis after prolonged unilateral disuse, the preoperative side-to-side difference in quadriceps muscle CSA between the affected leg and the nonaffected leg has been reported to be smaller (8%–10%).34 Loss of muscle CSA (atrophy) is an important mechanism underlying muscle weakness, although the amount of muscle CSA lost is often smaller than the amount of muscle force lost.35 A muscle CSA deficit of 14% may present a challenge for rehabilitation because even in older subjects who were healthy, a progressive strength training regimen lasting 3 to 4 months was shown to have an effect of less than 10% on muscle CSA.30,36 Decreased lower-limb muscle power is one of the factors underlying mobility limitations in older adults.37–39 Mizner et al7 and Mizner and SnyderMackler8 reported that weakness of the knee extensor muscles in people with a total knee replacement was closely associated with mobility limitations, especially in stair-climbing tasks and the Timed “Up & Go” Test. According to Lamb and Frost,6 leg extension power is an important determinant of walking speed and stairascending time after knee replacement. Portegijs et al25 reported that extension power asymmetry was also associated with a lower walking speed in older women who were healthy. In the present study, large power and torque deficits were associated with slow stair-ascending and stair-descending times but not with maximal walking speed. This result is in line with the results of Portegijs et al,29 who found that in women recovering from hip fracture, a large power deficit was associated with limitations in stair climbing but not with walking speed. It would appear that because walking is a common

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functional task, the nonoperated leg may be able to compensate for problems with the operated leg. However, to perform more-demanding functional tasks, such as stair ascending and stair descending, a person needs more power and force production in the knee extensor muscles.7,8 The present study had some limitations. The study was a crosssectional analysis without follow-up; therefore, we cannot speculate on the causal relationships or the associations over time. The study population consisted of people who were relatively healthy and mobile and had undergone successful unilateral knee replacement procedures. It is impossible to know whether people with more-extensive mobility problems might have dropped out; such a situation might have reduced the variance in muscle deficits and in mobility problems. In addition, some of the participants had osteoarthritis in the nonoperated knee, and this condition may have influenced the muscle deficits in the lower legs. The clear strength of the present study is the large number of measurements of deficits in muscle torque, power, and CSA. The results of this crosssectional study need to be confirmed in future prospective and experimental studies.

Conclusion Deficits in muscle power or torque are clinically important during evaluations of mobility limitations up to nearly 1 year after surgery. Because the major goals in the rehabilitation of musculoskeletal problems are to restore a person’s mobility and functional capacity and to prevent mobility disability, increasing muscle power, especially in the operated leg, may be one of the central issues to address during the rehabilitation process. The findings of this study are potentially useful for planning preventive and rehabilitative strategies; however, further work is needed. October 2009

Muscle Deficits and Mobility After Knee Replacement All authors provided concept/idea/research design, writing, and data collection and analysis. Dr Poÿho¨nen and Dr Heinonen provided project management. Ms Valtonen, Dr Poÿho¨nen, and Dr Heinonen provided fund procurement. Ms Valtonen and Dr Poÿho¨nen provided participants. Dr Poÿho¨nen provided facilities/equipment. Dr Heinonen provided consultation (including review of manuscript before submission). The study was approved by the ethics committee of Kymenlaakso Central Hospital. An abstract and oral presentation of this research were given at the 18th Nordic Congress of Gerontology; May 28 –31, 2006; Jyva¨skyla¨, Finland; and at the 8th Scandinavian Congress of Medicine and Science in Sports; November 9 –12, 2006; Vieruma¨ki, Finland. This article was received October 3, 2007, and was accepted June 19, 2009. DOI: 10.2522/ptj.20070295

References 1 Martin SD, Scott RD, Thornhill TS. Current concepts of total knee arthroplasty. J Orthop Sports Phys Ther. 1998;28:252–261. 2 Orbell S, Espley A, Johnston M, Rowley D. Health benefits of joint replacement surgery for patients with osteoarthritis: prospective evaluation using independent assessments in Scotland. J Epidemiol Community Health. 1998;52:564 –570. 3 NIH Consensus Panel. NIH Consensus Statement on total knee replacement December 8 –10, 2003. J Bone Joint Surg Am. 2004;86:1328 –1335. 4 Jones DL, Westby MD, Greidanus N, et al. Update on hip and knee arthroplasty: current state of evidence. Arthritis Rheum. 2005;53:772–780. 5 Walsh M, Woodhouse LJ, Thomas SG, Finch E. Physical impairments and functional limitations: a comparison of individuals 1 year after total knee arthroplasty with control subjects. Phys Ther. 1998;78: 248 –258. 6 Lamb SE, Frost H. Recovery of mobility after knee arthroplasty: expected rates and influencing factors. J Arthroplasty. 2003;18:575–582. 7 Mizner RL, Petterson SC, Snyder-Mackler L. Quadriceps strength and the time course of functional recovery after total knee arthroplasty. J Orthop Sports Phys Ther. 2005;35:424 – 436. 8 Mizner RL, Snyder-Mackler L. Altered loading during walking and sit-to-stand is affected by quadriceps weakness after total knee arthroplasty. J Orthop Res. 2005;23: 1083–1090. 9 Rossi MD, Brown LE, Whitehurst M. Knee extensor and flexor torque characteristics before and after unilateral total knee arthroplasty. Am J Phys Med Rehabil. 2006; 85:737–746.

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10 Minns Lowe CJ, Barker KL, Dewey M, Sackley CM. Effectiveness of physiotherapy exercise after knee arthroplasty for osteoarthritis: systematic review and metaanalysis of randomised controlled trials. BMJ. 2007;335:812. 11 Meier W, Mizner RL, Marcus RL, et al. Total knee arthroplasty: muscle impairments, functional limitations, and recommended rehabilitation approaches. J Orthop Sports Phys Ther. 2008;38:246 –256. 12 Yoshida Y, Mizner RL, Ramsey DK, SnyderMackler L. Examining outcomes from total knee arthroplasty and the relationship between quadriceps strength and knee function over time. Clin Biomech (Bristol, Avon). 2008;23:320 –328. 13 Finch E, Walsh M, Thomas SG, Woodhouse LJ. Functional ability perceived by individuals following total knee arthroplasty compared to age-matched individuals without knee disability. J Orthop Sports Phys Ther. 1998;27:255–263. 14 Lorentzen JS, Petersen MM, Brot C, Madsen OR. Early changes in muscle strength after total knee arthroplasty: a 6-month follow-up of 30 knees. Acta Orthop Scand. 1999;70:176 –179. 15 Ouellet D, Moffet H. Locomotor deficits before and two months after knee arthroplasty. Arthritis Rheum. 2002;47:484 – 493. 16 Rossi MD, Hasson S. Lower-limb force production in individuals after unilateral total knee arthroplasty. Arch Phys Med Rehabil. 2004;85:1279 –1284. 17 Berman AT, Bosacco SJ, Israelite C. Evaluation of total knee arthroplasty using isokinetic testing. Clin Orthop Relat Res. 1991;(271):106 –113. 18 Rodgers JA, Garvin KL, Walker CW, et al. Preoperative physical therapy in primary total knee arthroplasty. J Arthroplasty. 1998;13:414 – 421. 19 Gapeyeva H, Buht N, Peterson K, et al. Quadriceps femoris muscle voluntary isometric force production and relaxation characteristics before and 6 months after unilateral total knee arthroplasty in women. Knee Surg Sports Traumatol Arthrosc. 2007;15:202–211. 20 Huang CH, Cheng CK, Lee YT, Lee KS. Muscle strength after successful total knee replacement: a 6- to 13-year follow-up. Clin Orthop Relat Res. 1996;(328): 147–154. 21 Berth A, Urbach D, Awiszus F. Improvement of voluntary quadriceps muscle activation after total knee arthroplasty. Arch Phys Med Rehabil. 2002;83:1432–1436. 22 Silva M, Shepherd EF, Jackson WO, et al. Knee strength after total knee arthroplasty. J Arthroplasty. 2003;18:605– 611. 23 Perhonen M, Komi P, Ha¨kkinen K, et al. Strength training and neuromuscular function in elderly people with total knee endoprosthesis. Scand J Med Sci Sports. 1992;2:234 –243. 24 Mizner RL, Petterson SC, Stevens JE, et al. Early quadriceps strength loss after total knee arthroplasty: the contributions of muscle atrophy and failure of voluntary muscle activation. J Bone Joint Surg Am. 2005;87:1047–1053.

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25 Portegijs E, Sipila¨ S, Alen M, et al. Leg extension power asymmetry and mobility limitation in healthy older women. Arch Phys Med Rehabil. 2005;86:1838 –1842. 26 Portegijs E, Sipila¨ S, Pajala S, et al. Asymmetrical lower extremity power deficit as a risk factor for injurious falls in healthy older women. J Am Geriatr Soc. 2006;54: 551–553. 27 Lamb SE, Morse RE, Evans JG. Mobility after proximal femoral fracture: the relevance of leg extensor power, postural sway and other factors. Age Ageing. 1995; 24:308 –314. 28 Skelton DA, Kennedy J, Rutherford OM. Explosive power and asymmetry in leg muscle function in frequent fallers and non-fallers aged over 65. Age Ageing. 2002;31:119 –125. 29 Portegijs E, Sipila¨ S, Rantanen T, Lamb SE. Leg extension power deficit and mobility limitation in women recovering from hip fracture. Am J Phys Med Rehabil. 2008; 87:363–370. 30 Sipila¨ S, Suominen H. Effects of strength and endurance training on thigh and leg muscle mass and composition in elderly women. J Appl Physiol. 1995;78:334 –340. 31 Thelen DG, Schultz AB, Alexander NB, Ashton-Miller JA. Effects of age on rapid ankle torque development. J Gerontol A Biol Sci Med Sci. 1996;51:M226 –M232. 32 Thelen DG, Muriuki M, James J, et al. Muscle activities used by young and old adults when stepping to regain balance during a forward fall. J Electromyogr Kinesiol. 2000;10:93–101. 33 Robinovitch SN, Hsiao ET, Sandler R, et al. Prevention of falls and fall-related fractures through biomechanics. Exerc Sport Sci Rev. 2000;28:74 –79. 34 Suetta C, Aagaard P, Magnusson SP, et al. Muscle size, neuromuscular activation, and rapid force characteristics in elderly men and women: effects of unilateral longterm disuse due to hip-osteoarthritis. J Appl Physiol. 2007;102:942–948. 35 Frontera WR, Hughes VA, Fielding RA, et al. Aging of skeletal muscle: a 12-yr longitudinal study. J Appl Physiol. 2000;88: 1321–1326. 36 Frontera WR, Meredith CN, O’Reilly KP, et al. Strength conditioning in older men: skeletal muscle hypertrophy and improved function. J Appl Physiol. 1988;64: 1038 –1044. 37 Rantanen T, Avela J. Leg extension power and walking speed in very old people living independently. J Gerontol A Biol Sci Med Sci. 1997;52:M225–M231. 38 Bean JF, Kiely DK, Herman S, et al. The relationship between leg power and physical performance in mobility-limited older people. J Am Geriatr Soc. 2002;50: 461– 467. 39 Herman S, Kiely DK, Leveille S, et al. Upper and lower limb muscle power relationships in mobility-limited older adults. J Gerontol A Biol Sci Med Sci. 2005;60: 476 – 480.

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Age Affects the Attentional Demands of Stair Ambulation: Evidence From a Dual-Task Approach Heidi A. Ojha, Rebecca W. Kern, Chien-Ho Janice Lin, Carolee J. Winstein H.A. Ojha, PT, DPT, OCS, is Clinical Assistant Professor, Department of Physical Therapy, College of Health Professions, Jones Hall, Room 619, 3307 N Broad St, Temple University, Philadelphia, PA 19140 (USA). Address all correspondence to Dr Ojha at: [email protected]. R.W. Kern, PT, DPT, OCS, is Owner and Director, Kern and Associates Physical Therapy, Santa Monica, California. C.-H.J. Lin, PT, PhD, is Postdoctoral Research Associate, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, California. C.J. Winstein, PT, PhD, FAPTA, is Professor and Director of Research, Division of Biokinesiology and Physical Therapy at the School of Dentistry, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California. [Ojha HA, Kern RW, Lin C-HJ, Winstein CJ. Age affects the attentional demands of stair ambulation: evidence from a dual-task approach. Phys Ther. 2009;89: 1080 –1088.] © 2009 American Physical Therapy Association

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Background. Approximately 75% of all injury-producing falls on steps for people of all ages occur in people 65 years of age and older. Diminished attentional capacity contributes to fall risk in older adults, particularly when task demands are high. Objective. The purpose of this study was to compare the attentional demands of ascending and descending a set of stairs (stair ambulation) in older adults and younger adults.

Design. This was a nonblinded, prospective, single-site, observational cohort study.

Methods. Ten older (⬎65 years of age) and 10 younger (21–33 years of age) adults without disabilities were recruited. A dual-task approach was used for 2 task conditions: the first task was standing and responding verbally to an unanticipated auditory tone as quickly as possible (probe task), and the second task was ascending or descending a set of stairs with the same probe task. A 2-factor (group ⫻ task) analysis of variance with repeated measures on task (standing and stair ambulation) was performed for voice response time (VRT). Significance for the analysis was set at P⬍.05. Results. The group ⫻ task interaction was significant for VRT. Post hoc analyses indicated that during stair ambulation, the VRT for older adults was significantly longer than that for younger adults. For the standing task, the VRTs (X⫾SD) were similar for younger (322⫾65 milliseconds) and older (306⫾22 milliseconds) participants. For stair ascent and descent, the average VRTs were more than 100 milliseconds longer for older participants (493⫾113 and 470⫾127 milliseconds, respectively) than for younger participants (365⫾56 and 356⫾67 milliseconds, respectively). Limitations. Because of the small sample size and generally fit older group, generalization of findings to older people at risk for falls is not recommended until further research is done. Conclusions. The results demonstrated that although both older and younger adults required similar attentional resources for the standing task, older adults required significantly more resources during stair ambulation. The findings suggested that the dual-task method used here provided a clinically useful measure for detecting important changes in attentional demands in older adults who are healthy.

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I

n the United States, 1 of every 3 people 65 years of age and older has experienced a fall each year, making falls the leading cause of injuries and hospitalizations for trauma.1 Fall-related injuries in the United States lead to serious morbidity in this population, and costs for these injuries exceed $20 billion each year.2 Mortality rates have been steadily rising, with the number of fall-related deaths in people 65 years of age and older increasing 36% from 1999 to 2003; in comparison, for people younger than 65 years of age, there has been only a 15% increase.3 Of all specified falls (falls reported doing a certain activity, as opposed to falls reported without specification of the activity associated with the fall) recorded by the National Safety Council4 in 2003, the 2 most common types in people 65 years of age and older are falls on the same level, such as while standing and walking (48%), and falls on steps or stairs (18%). Of falls on steps for people of all ages, 75% occur in people 65 years of age and older. Older adults are more likely to have greater resulting injuries and need for hospitalizations with these falls.5

Fall Risk in Older Adults Prior research provided evidence for several factors that can contribute to the rising fall risk with age, including changes in physiology6 –9 and declines in muscle strength (forcegenerating capacity),10 –12 coordination,13 and cognition.14 Recently, considerable evidence has emerged regarding a more specific area of cognition—attentional resources— and its association with fall risk. It is known that older adults who are healthy show longer response times than younger adults for certain imperative motor tasks, such as turning and stopping during ambulation.15 This finding may be attributable to differences in attentional capacity that emerge with age. Several studies October 2009

conducted with older adults without disabilities showed that the ability to ambulate and maintain postural control required greater attentional demands in those adults than in younger adults performing the same motor tasks.16 –19 Furthermore, when a population of older adults was classified by fall history into those with falls and those without falls, studies revealed greater decrements in postural stability and gait parameters in the group with falls, especially when the latter were required to simultaneously perform other cognitive tasks.20 –23 Together, these studies suggested that an inability to maintain the performance of a primary locomotor task as the attentional demands of a secondary task increase could be used to predict which older people are at greater risk for falling in a natural environment.19 –24

Thus, the primary aim of this pilot study was to compare the attentional demands of ascending and descending a set of stairs (stair ambulation) in younger and older adults by using a well-controlled dual-task paradigm administered in a typical clinical setting. Our primary hypothesis was that the attentional demands of a stair-climbing task would be greater for older than for younger adults without disabilities. Our secondary hypothesis posited that descent would demand more attention than ascent; we reasoned that the perceived penalty from an error committed during descent could be greater than that from an error committed during ascent. Therefore, a difference in the perceived penalty might be expected to influence attentional demands differently for ascent and descent.

Dual-Task Paradigm

Method

In the past 10 years, clinical researchers in the field of physical therapy have incorporated the dualtask paradigm, well known in cognitive psychology, as a method to assess the attentional demands inherent in the performance of specific motor tasks.25,26 Provided that the performance of a primary motor task is not disrupted and there is no evidence of a trade-off between the primary motor task and a secondary probe task, the time to respond to the secondary probe task can be considered a reliable reflection of the attentional demands of the primary task.27,28 Dual-task approaches have been used extensively for manipulating attention and its effect on motor performance in younger and older adults for many different functional tasks, including sitting, standing, and walking.19,29 –32 That said, we are unaware of any research that has systematically and directly examined the attentional demands inherent in negotiating stairs while ambulating.

Setting and Participants Participants were recruited from a convenience sample of people affiliated with Kern and Associates Physical Therapy or the Division of Biokinesiology and Physical Therapy at the University of Southern California. All individuals in the study participated on a voluntary basis. Inclusion criteria were an age of greater than or equal to 65 years or between 20 and 35 years, a self-assessed ability to successfully ascend and descend stairs, self-reported good health, and at least 20/70 vision with

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Aging and Attentional Demands of Stair Ambulation corrective lenses as needed. Exclusion criteria were physical therapy treatment within the previous 3 months, the presence of any major heart conditions diagnosed within the preceding year, a history of falls within the preceding year, decreased sensation in either or both of the lower extremities, and performance below the age-matched normative range for the sit-to-stand and marching items of the American College of Sports Medicine fitness tests.33,34 Instrumentation and Apparatus For the dual-task conditions, a tone generator–silent impulse counter (Lafayette model 58024C)* was used to generate a 1,500-Hz tone. This tone output was amplified through an 8-channel 900-MHz wireless receiver (RadioShack model 32-1250)† and transmitted to an earphone headset (RadioShack model 331253)† worn by the subject. The triggered tone started a voice response time (VRT) counter (Lafayette model 63040A).* The response time counter was stopped by vocal output (the participant saying “bah”). This output was transmitted to the VRT counter through a wireless microphone headset (RadioShack model 33-3012)†, a wireless audiolink transmitter (RadioShack model 32-1252)† secured to the participant’s gait belt, and the wireless receiver. The VRT was displayed on the counter until it was manually reset by the experimenter. A Polar Heart Rate Monitor (Nike model SM0017-001)‡ provided a continuous reading of the participant’s heart rate.

* Lafayette Instruments, PO Box 5729, Lafayette, IN 47903. † RadioShack Corp, Riverfront Campus, Mail Stop CF3–311, 300 RadioShack Cir, Fort Worth, TX 76102. ‡ Nike USA Inc, Consumer Services, PO Box 4027, Beaverton, OR 97076.

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Screening and Baseline Assessment Potential participants were contacted by telephone and prescreened for participation on the basis of reported answers to selection criteria (history of falls, heart condition, physical therapy treatment, age, and stair-climbing ability). After the prescreening step, individuals who volunteered to participate gave consent by using an approved informed consent form. After consent was given, a formal assessment was performed at an outpatient clinic (Kern and Associates Physical Therapy). Each participant provided a history and underwent a physical examination. The baseline assessment comprised the inclusion criteria and other tests that were used to characterize physical functioning.

ical and mental status of the 2 groups (older adults and younger adults) once they were qualified for inclusion. Each participant rated his or her highest level of self-perceived activity by using scores of 1 to 5 (1⫽able to walk 5 blocks, 2⫽able to walk 1.6 km [1 mile] in 20 minutes or more, 3⫽able to walk 1.6 km in less than 20 minutes, 4⫽able to run 1.6 km, and 5⫽able to run 4.8 km [3 miles]). Further physical examination included 3 standardized tests for cognition, balance, and balance confidence: the Mini-Mental State Examination; the Tinetti Balance Examination35; and the Activities-specific Balance Confidence Scale questionnaire,36 on which each participant rated his or her perceived level of confidence (from 0% to 100%) in performing 16 functional activities.

The following evaluations were performed to determine eligibility. A relevant history was obtained through interview to confirm that all of the subjective selection criteria were met. Additionally, because the stairclimbing task is considered to be physically demanding, physical tests used as selection criteria were designed to evaluate safety and ensure an acceptable minimal level of fitness for participation. These tests included a physical examination to assess lower-extremity light-touch sensation; assessment of corrected vision with both eyes open and a standard eye chart; and performance on the American College of Sports Medicine fitness tests,33,34 which measure the maximum number of repetitions of rising from a standard chair to a full standing position in 30 seconds and marching in place for 2 minutes. The criterion for acceptable performance in the 2 fitness tests was that the scores fell within the range of published age-matched normative values.

Dual-Task Paradigm Three primary tasks were probed with the auditory tone: (1) standing at the bottom of a single flight of stairs, (2) ascending the stairs, and (3) descending the same stairs. The secondary probe task required a verbal response to an auditory tone stimulus that was presented unpredictably and through headphones during the performance of the primary tasks.

The remaining baseline tests were performed to characterize the phys-

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Controlling for Methodological Confounds Several methodological issues are important for enabling the effectiveness of the dual-task paradigm and for maximizing the validity of the response time data. The measured reaction time can be considered a valid reflection of the attentional demand of the primary task only when: anticipation of the secondary probe task is minimized; there is no evidence of a trade-off effect or compromised performance of the primary task when the secondary probe task is presented; and there is no evidence of structural interference, such as some competition between October 2009

Aging and Attentional Demands of Stair Ambulation the primary task and the secondary task for a common physical or neural effector. To minimize anticipation, we reduced the frequency of occurrence of the probe during the stair trials and included quasi-randomly spaced “catch” trials at a frequency of 33% during the dual-task conditions. A catch trial is one in which the participant performs the primary task (ascent and descent) but no auditory probe is introduced.25 Thus, the frequency of probe trials was 67% of all stair trials. We minimized the trade-off effect by establishing and maintaining a consistent but selfchosen cadence for all probe trials. Finally, structural interference was minimized through implementation of a vocal response to the probe stimulus. Setup and safety. A research assistant helped each participant don the wireless earphone and microphone headsets, the heart rate monitor, and the gait belt. Throughout all of the trials, the experimenter (H.A.O.) operated the VRT counter from a position directly above the set of stairs used by the participant. The wireless audio-link transmitter and the wireless receiver also were set up next to the experimenter. The volume for the tone generator was adjusted to ensure that the volunteer could hear the tone reliably throughout testing. A trained assistant spotted each participant throughout all of the experimental procedures. The assistant or experimenter obtained and recorded baseline blood pressure and heart rate. During the dual-task conditions, the participant momentarily rested while the heart rate was recorded after each ascent and descent. If the heart rate exceeded 20 bpm over the baseline heart rate at any point during the study, the blood pressure recording was repeated. Participants were informed that both sets of hand rails could be used as needed and October 2009

that they could rest as much as desired between trials and conditions, as well as after any ascent or descent. Two or 3 practice trials with the tone generator and voice response were conducted to ensure that each participant understood the procedures and could hear the tone reliably. The sensitivity of the wireless receiver was adjusted to reduce extraneous noise and prevent false arrest of the timer. Preparatory training. In preparation for the dual-task conditions, it was important to obtain a reliable and repeatable cadence. This was established to ensure that performance of the primary task was not compromised by the secondary probe task. To establish a consistent cadence, participants were asked to ascend and descend the flight of 10 stairs at a pace that was most comfortable for them so that they would be able to reproduce the same cadence across trials. A metronome set to a participant’s chosen pace was used throughout the preparatory practice. This procedure was repeated 5 times for stair ascent and descent or until the volunteer was able to achieve consistency across trials. It was important for participants to be sufficiently familiar with their chosen cadence that consistency could be maintained in the dual-task conditions without the use of the metronome. There were 2 experimental task conditions. The first consisted of a simple response time control task in which a participant stood at the foot of the stairs and responded to the auditory tone by saying “bah” as quickly as possible. The second experimental task condition was the dual-task condition with similar criteria but with the participant ascending (task 2a) and descending (task 2b) the set of stairs.

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Experimental condition 1: simple response time task. The participant stood on the landing at the base of the stairs and responded by saying “bah” whenever the auditory tone was heard. The experimenter instructed the volunteer to respond to the auditory tone as fast as possible and as soon as the volunteer heard the tone. The experimenter copied the response time from the impulse counter display after each trial and then reset the counter. For each trial, the experimenter gave the participant a warning with a verbal “ready,” which was followed by a variable fore period of 0 to 10 seconds during which the tone was manually triggered. For all trials, the manual trigger was activated away from the participant’s line of sight. Between 10 and 20 practice trials were performed until the experimenter concluded that the participant was responding to the tone as quickly as possible and that the responses were consistent. The results of 10 trials of the simple response time task were acquired and recorded from the display. The intertrial interval was between 2 and 5 seconds. Experimental condition 2: dual task. The same probe task was implemented and recorded as in condition 1, except that in condition 2, the participant climbed up and down a set of stairs. The same instructions were given to the participants, apart from informing them that they would hear the tone only during some of the trials. Two sets of 15 trials were performed at the previously established self-chosen cadence. Before the 2 sets of trials and at any point during the trials, if the stair-climbing time varied by more than 1 second from the first trial time, the data collection was put on hold and the metronome was played for 5 to 10 seconds at the previously established cadence. This was done to trigger a memory for the motor set and to ensure consistency during the Number 10

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Aging and Attentional Demands of Stair Ambulation Table 1. Group Characteristicsa Younger Group (nⴝ10)b Characteristic Age (y)

X

SD

27

Range

4.0

Older Group (nⴝ10)c X 74.2

SD

Range

P

M

95% CI

6.32

Tinetti (score)

19.70

⫺5.31

13–28

15.20

⫺3.29

12–22

NS

0.5

0.47 to 0.53

MMSE (score)

29.70

⫺0.48

29–30

28.30

⫺1.71

25–30

.03

1.4

1.18 to 1.62

ABC Scale questionnaire (score), %

99

⫺1

98–100

95

⫺3

90–100

0

4

2 to 6

a M⫽difference between the means, CI⫽confidence interval, Tinetti⫽Tinetti Balance Examination, NS⫽not significant, MMSE⫽Mini-Mental State Examination, ABC⫽Activities-specific Balance Confidence. b Four men and 6 women. Highest level of self-perceived activity: 20% could walk 1.6 km in less than 20 minutes, 40% could run 1.6 km, and 40% could run 4.8 km. c Six men and 4 women. Highest level of self-perceived activity: 20% could walk 1.6 km in 20 minutes or more, and 80% could walk 1.6 km in less than 20 minutes.

dual-task conditions. To avoid any confusion with the probe tone, the metronome was not used during the dual-task phase when VRT data were collected. The tone was presented to the participant during 10 of the 15 ascents and descents (66%) for each set of trials. Thus, 5 ascents and descents interspersed throughout the 15 trials were catch trials (33%), in which the tone was not presented. The experimenter activated the tone at some point when the participant was between the second and ninth steps so that starting and stopping ambulation would not interfere with the participant’s attentional resources. The experimenter recorded the response time as in condition 1. Data Analysis Descriptive statistics revealed that the data were normally distributed and appropriate for parametric analysis methods. The Levene test for equality of variance and independent t tests for equality of means were used to compare the baseline characteristics of the 2 groups of participants. Paired t tests were used to compare cadences during catch and probe trials in the stair-climbing condition to rule out a trade-off effect. A 3 (task conditions) ⫻ 2 (practice groups) analysis of variance was conducted to assess the main effects of group and condition and the interac1084

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tion between group and condition. Both group mean and median VRTs were used in these analyses. Significance was set at Pⱕ.05 for all primary analyses. A post hoc Tukey test was performed to determine the locus of any interaction effect. SPSS version 13.0§ was used for all analyses. Role of the Funding Source Equipment and facilities were provided by Kern and Associates Physical Therapy. No other funding was obtained to complete the study.

Results Study Groups Table 1 summarizes the group demographics for the screening and baseline assessment. Forty-three people were contacted, and of these, 21 individuals who met the inclusion and exclusion criteria were enrolled. Three volunteers declined to participate before fully completing the screening because of concerns about aggravating pain in 1 or more lowerextremity joints. One participant in the older group met the inclusion criteria but was unable to complete the study because of fatigue and joint pain, leaving 20 participants available for data analysis. These 20 par§ SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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ticipants met all of the inclusion criteria. Only 2 participants (1 in the younger group and 1 in the older group) needed repeated blood pressure readings during the trials because of a rise in heart rate of greater than 20 bpm compared with the baseline rate. In general, participants in both groups maintained a consistent cadence, and only 3 participants needed 1 or 2 cadence reminders with the metronome. Group ⴛ Task Analyses Although each participant was offered the opportunity to complete the dual-task conditions on a second day, all participants chose to complete the testing in 1 day. Cadence naturally varied among participants, but all 20 participants needed a maximum rest break of 15 minutes between the assessment and condition 1 (standing) and between preparation for condition 2a (ascending) and preparation for condition 2b (descending). Descriptive statistics revealed similar results for the mean and median VRTs. Therefore, we chose the mean VRT as the primary dependent measure for all subsequent analyses. The 2 (practice groups) ⫻ 3 (task conditions) repeated-measures analysis of October 2009

Aging and Attentional Demands of Stair Ambulation Table 2. Voice Response Time (VRT) for Each Group and Task Conditiona VRT (ms) Task Condition

Younger Group (nⴝ10)

Older Group (nⴝ10)

X

SD

Range

X

SD

Range

P

Standing

322

65

240–460

Ascending

365

56

280–450

Descending

356

67

240–460

95% CI

306

22

270–340

.459

⫺.02924 to .06211

493

113

390–690

.005

⫺.21135 to ⫺.04346

470

127

350–720

.022

⫺.21135 to ⫺.04346

Group ⫻ condition interaction (F2,17⫽7.119, P⫽.006); post hoc comparison of group means (young vs old) for standing (F1⫽0.571, P⫽.459), ascending (F1⫽10.167, P⫽.005), and descending (F1⫽6.247, P⫽.022). CI⫽confidence interval. a

variance for VRT revealed a significant group ⫻ task interaction. The VRT data are provided in Table 2, and the group ⫻ task condition VRT data are illustrated in the Figure. Post hoc analyses revealed no group differences in mean VRTs for the standing condition. In contrast, VRTs were significantly longer for the older participants during both ascent and descent than for the younger participants. Finally, in contrast to our secondary hypothesis, the mean VRT for stair descent was not different from that for stair ascent in either group of participants. Trade-off Effect and Anticipation The within-group comparison of cadence (steps per second) between the catch trials (older adults: younger adults: X⫽2.38⫾0.57; X⫽2.93⫾0.30) and the probe trials (older adults: X⫽2.39⫾0.56; younger adults: X⫽2.95⫾0.29) did not reach significance. This finding was confirmed by plotting individual participant data and comparing cadence in the probe trial with that in the catch trial (data not shown). Generally, and as expected, the younger participants had a faster cadence than the older participants. Furthermore, and of particular importance here, although there was considerable variability in cadence among participants, there was no significant difference between the cadence in the probe trial and that in the catch trial for any participant. Collectively, these findings provide October 2009

strong evidence that participants did not trade off performance of the primary stair ambulation task for the secondary VRT task. These results were evident in the older adults for ascent (P⫽.126) and descent (P⫽.980) and in the younger adults for ascent (P⫽.134) and descent

(P⫽.121). Finally, all responses to the tone were acceptable (none ⬍100 milliseconds) and, therefore, did not suggest that the probe tone was anticipated.

Figure. Voice response times for the task conditions and participant groups. The graph shows the group ⫻ task interaction. There was no difference between groups for standing (task 1), but there were significant differences between groups for both ascent (task 2a) and descent (task 2b) (asterisks indicate post hoc comparisons between groups for the stair condition, P⬍.05). Error bars indicate standard deviations.

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Discussion Our primary aim was to compare the attentional demands of stair ambulation in younger and older adults by using a well-controlled dual-task paradigm in a clinical setting. We demonstrated that under the specifications of a protocol approved by the University of Southern California Health Sciences Institutional Review Board and with carefully controlled methods, we could reliably determine the attentional demands of a relatively demanding functional task in a group of older adults who were physically fit. The results supported our primary hypothesis: both groups had similar VRTs during the control task (standing), but the older adults had significantly longer VRTs during the more demanding task (stair ambulation). The critical point, however, is not simply the group difference in the VRT but that, in the context of the methodological constraints (eg, minimized trade-off and anticipation effects), the VRT can be considered a reliable and valid reflection of the “attentional cost” of a task. Our study demonstrated that although both groups required similar attentional resources during static standing, the older adults required significantly more attentional resources during the stair ambulation task. That is, as task difficulty increased, older adults required greater attentional resources than younger adults; greater attentional cost was specific to the older adults in the stair ambulation task. The magnitude of the difference in attentional cost, as measured by the VRT, between the groups only during stair ambulation (combined ascent and descent) was 121 milliseconds (SD⫽105.9)—a difference that is considered large in cognitive psychology, in which chronometric approaches are commonly used to study mental processes.37 Earlier rel1086

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evant work gives us further confidence in the relevance and validity of our findings. Using a similar dualtask approach, Wright and Kemp25 found that a 117-millisecond difference was a significant and meaningful difference in the attentional demands of walking with a standard walker versus walking with a rolling walker in 10 young adults who were healthy. Wellmon et al38 performed a follow-up study with 105 older adults and found that a difference in the VRT of 78 to 158 milliseconds indicated increased attentional demands for 2 dual-task walking conditions versus a simple standing task. Other studies have consistently shown higher attentional demands associated with standing,16,19,39 gait,39,40 and obstacle clearance18,41 in older adults than in younger adults. Although these researchers have shown that postural control tasks demand more attention with increasing age, our pilot study is the first systematic investigation to provide direct evidence for a similar phenomenon associated with stair ambulation. We know from earlier literature that increases in task demands correspond to greater attentional resource requirements,25,38,39 which in turn may leave less reserve to allocate toward a second cognitive or distraction task.40 It is not yet clear how older adults prioritize motor and cognitive tasks42; however, a subgroup of older adults may prioritize a cognitive distraction task over a motor task, a method that would effectively shrink the reserve for the motor task and could precipitate a fall. This theory is supported by research in retrospective21,40 and prospective23,43,44 studies, in which difficulty performing dual tasks was associated with or predictive of falls in older adults. A recent editorial review45 in a Journal of Gerontology special issue on cortical function, postural control, and gait concluded that future research needs to focus

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on more-challenging motor tasks. Our results showed a significant difference in dual-task performance between older adults who were healthy and younger adults in the relatively demanding motor task of stair ambulation. Given that 75% of injury-producing falls on steps for people of all ages occur in older adults,4 increased attentional demands during stair climbing could contribute to fall risk. Furthermore, considering that the older adults in the present study were fit, our dual-task approach proved to be sufficiently sensitive to detect a clinically meaningful difference (⬃25% of the mean VRT for older adults) between age groups in the attentional demands of a functional and demanding motor task. These findings raise at least one speculative but important question: specifically, do increases in attentional requirements for demanding motor tasks anticipate other, impending deficits (such as deficits in physiology, strength, sensory perception, and balance) that are typically seen and reported with aging? The “stops walking when talking” test43 has been shown to prospectively identify people at risk of falling from among a group of older adults with impairments but not from among a group of older adults with a higher level of functioning. Presumably, the higher the attentional cost of a motor task, the more sensitive the measure for fall prediction. More research is needed to determine whether the higher attentional costs of morechallenging motor tasks, such as stair ambulation, could be used as screening measures for fall risk, particularly in older adults who are fit. Additionally, the ability of our methodology to detect overt differences in older adults with a high level of functioning could be used to quantify the pretest-posttest effectiveness of a task-specific training program in longitudinal design intervention trials. October 2009

Aging and Attentional Demands of Stair Ambulation Contrary to our secondary hypothesis, we found no difference in the VRT between stair ascent and stair descent for the older adults. This finding suggests that the attentional demands during these variations of stair ambulation are not different for older adults. This finding could be explained partly by the fact that the older adults had a high level of functioning, with various baseline tests showing no significant differences between older adults and younger adults. Furthermore, the older adults were highly confident and reported a low fear of falling on the Activitiesspecific Balance Confidence Scale questionnaire. On average, they were 95% confident that they could perform various activities without falling. Perhaps older adults with a lower level of functioning would have greater fear avoidance and consequently would require more attentional resources for stair descent than for stair ascent, as we hypothesized. Our pilot study included homogeneous samples of older adults who were healthy and fit and younger adults; accordingly, generalization of the conclusions is limited to these populations. Although significant differences in VRTs were detected between the groups, the small sample size limited the impact of the results. Finally, the present study was predicated on a model of attention that presumes fixed resources, so that if a primary task demands a specific amount of the total attentional resources, then the time to respond to a secondary probe task can be measured and considered to be an indirect measure of the attentional requirements of the primary task.46 The inclusion in the present study of only adults who were not disabled, who were fit, and who had no history of falls precludes an evidencebased extrapolation of the results to a prospective method for fall risk identification, treatment, or both. October 2009

However, the results represent a logical argument that this connection could and should be explored with more research.

This article was received June 18, 2008, and was accepted May 28, 2009. DOI: 10.2522/ptj.20080187

References

Conclusion This pilot study was designed to compare the attentional demands of stair ambulation in younger and older adults by use of a dual-task paradigm. To our knowledge, the results represent the first evidence showing that the attentional demands associated with stair ambulation are greater for older adults who are healthy than for younger adults. The dual-task method proved to be sound, sensitive, and valid for use in future clinical research with older adults who have a high level of functioning. Dr Kern and Dr Winstein provided concept/ idea/research design. Dr Ojha, Dr Kern, and Dr Winstein provided writing. Dr Ojha provided data collection and project management. Dr Lin and Dr Winstein provided data analysis. Dr Ojha and Dr Kern provided participants. Dr Kern provided facilities/equipment and clerical support. Dr Winstein provided institutional liaisons. Dr Lin provided consultation (including review of manuscript before submission). The authors thank Kern and Associates Physical Therapy for providing both the clinic facility and the volunteers for study recruitment. Dr Ojha completed this study in partial fulfillment of the requirements of the Residency in Orthopedic Physical Therapy with the Division of Biokinesiology and Physical Therapy at the School of Dentistry, University of Southern California. This study was approved by the University of Southern California Health Sciences Institutional Review Board. Equipment and facilities were provided by Kern and Associates Physical Therapy. No other funding was obtained to complete the study. This work was presented at the North American Society for the Psychology of Sport and Physical Activity Annual Conference; June 7–9, 2007; San Diego, California; and at the Combined Sections Meeting of the American Physical Therapy Association; February 6 –9, 2008; Nashville, Tennessee.

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1 Gerberding J, Arias I, Wallace D, Ballesteros M. Preventing Falls: How to Develop Community-based Fall Prevention Programs for Older Adults. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2008. 2 Centers for Disease Control and Prevention and Merck Institute of Aging and Health. The State of Aging and Health in America. Washington, DC: Merck Institute of Aging and Health; 2004. 3 Hoskin A. Injury Facts. Itasca, IL: National Safety Council; 2007. 4 Hoskin A. Injury Facts. Itasca, IL: National Safety Council; 2005. 5 Hemenway D, Solnick SJ, Koeck C, Kytir J. The incidence of stairway injuries in Austria. Accid Anal Prev. 1994;26:675– 679. 6 Menz HB, Morris ME, Lord SR. Foot and ankle risk factors for falls in older people: a prospective study. J Gerontol A Biol Sci Med Sci. 2006;61:866 – 870. 7 Carpenter MG, Adkin AL, Brawley LR, Frank JS. Postural, physiological and psychological reactions to challenging balance: does age make a difference? Age Ageing. 2006;35:298 –303. 8 Laughton CA, Slavin M, Katdare K, et al. Aging, muscle activity, and balance control: physiologic changes associated with balance impairment. Gait Posture. 2003; 18:101–108. 9 Brauer SG, Burns YR, Galley P. A prospective study of laboratory and clinical measures of postural stability to predict community-dwelling fallers. J Gerontol A Biol Sci Med Sci. 2000;55:M469 –M476. 10 Moreland JD, Richardson JA, Goldsmith CH, Clase CM. Muscle weakness and falls in older adults: a systematic review and meta-analysis. J Am Geriatr Soc. 2004;52: 1121–1129. 11 Nguyen ND, Pongchaiyakul C, Center JR, et al. Identification of high-risk individuals for hip fracture: a 14-year prospective study. J Bone Miner Res. 2005;20:1921– 1928. 12 Pluijm SM, Smit JH, Tromp EA, et al. A risk profile for identifying communitydwelling elderly with a high risk of recurrent falling: results of a 3-year prospective study. Osteoporos Int. 2006;17:417– 425. 13 Singh AS, Chin APMJ, Bosscher RJ, van Mechelen W. Cross-sectional relationship between physical fitness components and functional performance in older persons living in long-term care facilities. BMC Geriatr. 2006;6:4. 14 Anstey KJ, von Sanden C, Luszcz MA. An 8-year prospective study of the relationship between cognitive performance and falling in very old adults. J Am Geriatr Soc. 2006;54:1169 –1176.

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Aging and Attentional Demands of Stair Ambulation 15 Cao C, Schultz AB, Ashton-Miller JA, Alexander NB. Sudden turns and stops while walking: kinematic sources of age and gender differences. Gait Posture. 1998;7: 45–52. 16 Marsh AP, Geel SE. The effect of age on the attentional demands of postural control. Gait Posture. 2000;12:105–113. 17 Hausdorff JM, Yogev G, Springer S, et al. Walking is more like catching than tapping: gait in the elderly as a complex cognitive task. Exp Brain Res. 2005;164:541– 548. 18 Chen HC, Schultz AB, Ashton-Miller JA, et al. Stepping over obstacles: dividing attention impairs performance of old more than young adults. J Gerontol A Biol Sci Med Sci. 1996;51:M116 –M122. 19 Shumway-Cook A, Woollacott M. Attentional demands and postural control: the effect of sensory context. J Gerontol A Biol Sci Med Sci. 2000;55:M10 –M16. 20 Condron JE, Hill KD. Reliability and validity of a dual-task force platform assessment of balance performance: effect of age, balance impairment, and cognitive task. J Am Geriatr Soc. 2002;50:157–162. 21 Toulotte C, Thevenon A, Watelain E, Fabre C. Identification of healthy elderly fallers and non-fallers by gait analysis under dualtask conditions. Clin Rehabil. 2006;20: 269 –276. 22 Shumway-Cook A, Woollacott M, Kerns KA, Baldwin M. The effects of two types of cognitive tasks on postural stability in older adults with and without a history of falls. J Gerontol A Biol Sci Med Sci. 1997; 52:M232–M240. 23 Verghese J, Buschke H, Viola L, et al. Validity of divided attention tasks in predicting falls in older individuals: a preliminary study. J Am Geriatr Soc. 2002;50: 1572–1576. 24 Beauchet O, Dubost V, Allali G, et al. ‘Faster counting while walking’ as a predictor of falls in older adults. Age Ageing. 2007;36:418 – 423.

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25 Wright DL, Kemp TL. The dual-task methodology and assessing the attentional demands of ambulation with walking devices. Phys Ther. 1992;72:306 –312; discussion 313–315. 26 Lajoie Y, Teasdale N, Bard C, Fleury M. Attentional demands for static and dynamic equilibrium. Exp Brain Res. 1993; 97:139 –144. 27 Abernethy B. Dual-task methodology and motor skills research: some applications and methodological constraints. Journal of Human Movement Studies. 1988;14: 101–132. 28 Salmoni A, Sullivan S, Starkes J. The attention demands of movements: a critique of the probe technique J Mot Behav. 1976; 8:161–169. 29 Dubost V, Kressig RW, Gonthier R, et al. Relationships between dual-task related changes in stride velocity and stride time variability in healthy older adults. Hum Mov Sci. 2006;25:372–382. 30 van Iersel MB, Ribbers H, Munneke M, et al. The effect of cognitive dual tasks on balance during walking in physically fit elderly people. Arch Phys Med Rehabil. 2007;88:187–191. 31 Swan L, Otani H, Loubert PV. Reducing postural sway by manipulating the difficulty levels of a cognitive task and a balance task. Gait Posture. 2007;26:470 – 474. 32 Harley C, Boyd JE, Cockburn J, et al. Disruption of sitting balance after stroke: influence of spoken output. J Neurol Neurosurg Psychiatry. 2006;77:674 – 676. 33 Jones CJ, Rikli RE, Beam WC. A 30-s chairstand test as a measure of lower body strength in community-residing older adults. Res Q Exerc Sport. 1999;70:113– 119. 34 Rikli RE, Jones CJ. Development and validation of a functional fitness test for community-residing older adults. J Aging Phys Act. 1999;7:129 –161. 35 Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc. 1986;34: 119 –126.

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36 Powell LE, Myers AM. The Activitiesspecific Balance Confidence (ABC) Scale. J Gerontol A Biol Sci Med Sci. 1995;50: M28 –M34. 37 Posner M. Chronometric Explorations of Mind. Hillsdale, NJ: Lawrence Erlbaum Associates; 1978. 38 Wellmon R, Pezzillo K, Eichhorn G, et al. Changes in dual-task voice reaction time among elders who use assistive devices. J Geriatr Phys Ther. 2006;29:74 – 80. 39 Lajoie Y, Teasdale N, Bard C, Fleury M. Upright standing and gait: are there changes in attentional requirements related to normal aging? Exp Aging Res. 1996;22:185–198. 40 Springer S, Giladi N, Peretz C, et al. Dualtasking effects on gait variability: the role of aging, falls, and executive function. Mov Disord. 2006;21:950 –957. 41 Kim HD, Brunt D. The effect of a dual-task on obstacle crossing in healthy elderly and young adults. Arch Phys Med Rehabil. 2007;88:1309 –1313. 42 Verghese J, Kuslansky G, Holtzer R, et al. Walking while talking: effect of task prioritization in the elderly. Arch Phys Med Rehabil. 2007;88:50 –53. 43 Lundin-Olsson L, Nyberg L, Gustafson Y. “Stops walking when talking” as a predictor of falls in elderly people. Lancet. 1997; 349:617. 44 Lundin-Olsson L, Nyberg L, Gustafson Y. Attention, frailty, and falls: the effect of a manual task on basic mobility. J Am Geriatr Soc. 1998;46:758 –761. 45 Alexander NB, Hausdorff JM. Guest editorial: linking thinking, walking, and falling. J Gerontol A Biol Sci Med Sci. 2008;63: 1325–1328. 46 Schmidt RA, Lee TD. Motor Control and Learning: A Behavioral Emphasis. 4th ed. Champaign, IL: Human Kinetics; 2005: 92–94, 101–102.

October 2009

Research Report Physical Fitness in Children With High Motor Competence Is Different From That in Children With Low Motor Competence Monika Haga

Background. Physical therapists often treat children with low motor competence. Earlier studies have demonstrated poor physical fitness outcomes and a reduced level of physical activity for these children compared with their peers with normal motor skills. Objective. The aim of this study was to examine how physical fitness developed over time in 2 groups of children: those with a low level of competence in motor skills (low motor competence [LMC]), and those with a high level of competence in motor skills (high motor competence [HMC]).

Design and Methods. From an initial sample of 67 children, a group of 18 was identified as having HMC or LMC on the Movement Assessment Battery for Children and was selected for the present study. Eight children (3 girls and 5 boys) comprised the LMC group, and 10 children (4 girls and 6 boys) made up the HMC group. A longitudinal design was implemented, and physical fitness in the 2 groups was evaluated by measuring different fitness components over a period of 32 months.

M. Haga, PT, MSc, is Assistant Professor, Department of Physiotherapy, Faculty of Health Education and Social Work, Sør-Trøndelag University College, Ranheimsveien 10, Trondheim, 7004 Norway. Address all correspondence to Ms Haga at: [email protected]. [Haga M. Physical fitness in children with high motor competence is different from that in children with low motor competence. Phys Ther. 2009;89:1089 –1097.] © 2009 American Physical Therapy Association

Results. A mixed-effects analysis of variance revealed significant main effects for

group and for time but no group ⫻ time interaction effect. The LMC group performed less well on all physical fitness measures than the HMC group, and both groups scored significantly higher on the physical fitness test after a period of 32 months. The lack of a significant interaction effect indicated that the relative differences in physical fitness outcomes between the groups were relatively constant over time.

Limitations. This study was limited by the small sample size and lack of assessment of anthropometric variables and children’s perceived self-efficacy.

Conclusions. Children with LMC are likely to have poor physical fitness compared with children with HMC. The differences in physical fitness outcomes between the groups were relatively constant over time. Given that various physical fitness components are linked to different health outcomes, these consequences are matters of concern for both current health status and later health status in children with LMC.

Post a Rapid Response or find The Bottom Line: www.ptjournal.org October 2009

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Physical Fitness in Children With High and Low Motor Competence

M

otor competence can be conceptualized as a person’s ability to execute different motor acts, including coordination of both fine (eg, manual dexterity) and gross (eg, static and dynamic balance) motor skills.1 Some children experience considerable difficulties coordinating and controlling their body movements and are often described as having developmental coordination disorder (DCD).2 This disorder is characterized by a marked impairment in the performance of motor skills that has adverse effects on activities of daily living, leisure activities, sports, and academic achievement.3,4 The prevalence of this condition in children is estimated to be 6% to 10%.2 Children with motor problems are not likely to grow out of their coordination difficulties; if left untreated, the symptoms tend to persist into adulthood, although there may be some improvement with development.5–7 Some children may continue to have motor problems because of the moderate to high level of influence of genetics on motor performance.8 In addition to impaired motor coordination, low motor competence (LMC) can have significant long-term effects on other aspects of development,9,10 including risks for a variety of emotional, social, and behavioral difficulties.10 –12 Evidence also is accumulating that LMC can cause decreased participation in physical activity13,14 and below-average performance on


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different components of physical fitness.15–19 There is no universal consensus on how to define physical fitness and its components,20,21 but physical fitness often is defined as the capacity to perform physical activity.22 Of particular interest are aspects of healthrelated fitness, namely, the physical and physiological components that more directly affect health status.23 Important determinants of healthrelated fitness include cardiorespiratory fitness, muscular fitness, and speed or agility.22 Some of the existing tests for motor competence (such as the Movement Assessment Battery for Children [MABC]) typically focus on balance, speed, and accuracy of movement coordination, with little concern for the health-related components included in the term “physical fitness.” Generally, the items in motor competence tests demand little muscular strength (force-generating capacity) or endurance, flexibility, and aerobic performance. The interaction among healthrelated fitness, performance-related fitness, and motor abilities is obvious. During movement activities, various degrees of these components are required.21 It is difficult, if not impossible, to obtain a pure measure of the basic components of physical fitness. Even in test and laboratory settings, only an indirect indication of the different basic components is possible.21 However, it can be argued that measuring physical fitness is different from measuring motor competence because physical fitness includes the socalled health-related components.18,24 Recent findings suggest that children with LMC demonstrate significantly poorer performance on important components of physical fitness, such as aerobic and anaerobic endurance16,17,25 and muscular strength, than their peers who are developing typically.17 Hands and Larkin15 found

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that children who were 5 to 8 years old and had motor learning difficulties had significantly poorer performance on various fitness components, such as sit and reach, sit-ups, standing broad jump, 50-m run, and shuttle run, than children in a control group. The children with motor learning difficulties also had a significantly higher body mass index. These results revealed that a negative interaction between motor competence and fitness begins at a very young age. These findings are consistent with the results of research on older children showing significant differences for all tasks in a physical fitness test between a group with movement difficulties and a comparison group.18 The findings of Cantell et al19 also suggested that people with LMC in different age groups have compromised health-related fitness. The results for children (8 –9 years of age) with LMC indicated reduced muscular endurance. Related findings, such as compromised musculoskeletal fitness and back fitness, were found in adolescents (17–18 years of age) and adults (20 – 60 years of age) with LMC.18 Motor competence has been considered to be a possible determinant of children’s physical activity,26,27 particularly as it pertains to an individual’s ability to master different fundamental movement skills used in physical activity. Children with high motor competence (HMC) may find it easier to participate in physical activity, whereas children with LMC may choose a more sedentary lifestyle because of their motor problems.26,27 Another possible influence on the level of physical fitness in the latter children is their perceived adequacy in physical tasks. If they believe themselves to be inferior in such tasks, they may not make as much of an effort and may even abandon the effort earlier than children without motor deficits.28,29

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Physical Fitness in Children With High and Low Motor Competence Bouffard et al30 presented the activity deficit hypothesis to explain the interaction between LMC and a low level of physical activity and how this relationship influences fitness outcomes. Poor coordination and accompanying feelings of inadequacy in motor activities lead to decreased motivation to participate in physical activity. The lack of success may become frustrating, and the child may voluntarily withdraw from physical activity. Participation also may be influenced by the context or environment; negative responses from parents, teachers, and peers may further restrict the child’s engagement in physical activity. The result may be a continuous negative interaction between LMC and a low level of physical activity, placing further skill development, health, and physical fitness at risk.30 It has been proposed that if the activity deficit between children with LMC and children without LMC widens with age, children with motor difficulties may continue to be more physically inactive than their peers as they age. Furthermore, differences in fitness between children with motor problems and children without motor problems may increase with age.14,17,31,32 Wall31 argued that the skill-learning gap between children with movement difficulties and their peers will increase because the latter group generally will achieve a higher level of motor competence and begin to participate in even more-demanding physical activity tasks. Additionally, physical activity habits established in childhood tend to track moderately into adolescence.33 Consequently, activity patterns in childhood could track into adolescence and then into adulthood and thus be indirectly related to later health outcomes.

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Physical fitness and physical activity have been identified as important markers of health in children and adolescents.22,34,35 Evidence dealing with the effects and health outcomes of physical fitness has indicated a link to cardiovascular disease risk factors, overweight or obesity, and skeletal and mental health.22,36 –38 Given that various fitness components are associated with different health outcomes, these consequences may be of concern for both the current and the future health status of children with LMC. The aim of this study was to examine how physical fitness developed over time in 2 groups of children: those with LMC and those with HMC.

Method Participants Sixty-seven school children aged between 9 and 10 years completed the MABC1 as well as the Test of Physical Fitness (TPF).24 The entire sample was obtained from a mainstream primary school. The mean chronological age for the entire group was 9.7 (SD⫽0.3) years; the overall range was 9.3 to 10.2 years. The group consisted of 31 girls and 36 boys. The mean ages were 9.7 (SD⫽0.3) years for the girls and 9.6 (SD⫽0.3) years for the boys. The correlation between the TPF total score and the MABC total score for the entire sample was ⫺.586 (n⫽67). From the sample of 67 pupils, the children were divided into 2 groups on the basis of their MABC percentile scores. The 12 children with the highest scores (a high score indicates motor problems) were allocated to the LMC group; all of these children had MABC scores of greater than 13.5, placing them at or below the 5th percentile. The 12 children with the lowest scores were allocated to the HMC group; these children had MABC scores of 0 to 3.5, placing them between the 60th and 95th percentiles. The mean chroVolume 89

nological ages were 9.5 (SD⫽0.3) years for the LMC group and 9.9 (SD⫽0.1) years for the HMC group (range⫽9.3–10.1 years). The LMC group consisted of 8 boys and 4 girls, and the HMC group consisted of 6 boys and 6 girls. The mean MABC scores for the LMC and HMC groups were 19.5 (SD⫽4.3) and 2.3 (SD⫽1.1), respectively. The MABC and the TPF were repeated for the entire sample after 32 months. The correlation between the TPF total score and the MABC total score for the entire sample was ⫺.511 (n⫽58). From the initial 2 groups, data from 6 children were missing. Some of the participants were absent from school on the day when the data were gathered; other children had moved. Thus, 18 pupils were included in the analysis. The LMC group consisted of 8 children (3 girls and 5 boys), and the HMC group comprised 10 children (4 girls and 6 boys). The mean chronological ages were 12.1 (SD⫽0.2) years for the LMC group and 12.6 (SD⫽0.1) years for the HMC group (range⫽11.9 – 12.8 years). The MABC mean scores for the LMC and HMC groups were 12.3 (SD⫽6.8) and 5.8 (SD⫽3.5), respectively. The difference in the MABC total scores between the groups was significant (P⫽.007, Mann-Whitney U test, 2-tailed). Both groups had changes in the MABC total scores between the 2 measurement points (March 2004 and November 2006), the LMC group from 20.2 (SD⫽4.3) to 12.3 (SD⫽6.8) and the HMC group from 2.4 (SD⫽1.1) to 5.8 (SD⫽3.5). MABC The MABC1 is an extended version of the Test of Motor Impairment,39 providing a global test of motor competence with assessments of both fine and gross motor coordination.40 The test yields both quantitative and qualitative evaluations of a child’s motor competence in daily life and conNumber 10

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Physical Fitness in Children With High and Low Motor Competence tains 8 subtests, which are divided into 3 categories: manual dexterity (3 subtests), ball skills (2 subtests), and static and dynamic balance (3 subtests). The test battery uses different tasks for children of different ages. For each age band, a given child’s performance is referenced to a standardization sample of children of the same age. A child is deemed to have normal motor performance (compared with 85% of children of the same age), to have borderline performance (compared with 85%– 95% of children of the same age), or to be among the 5% of children with a definite motor problem (relative to 95%–100% of children of the same age).

(P⬍.0001).24 The construct validity values of the test are .93 for girls and .89 for boys (P⬍.0001 for both, Spearman correlation).24

The MABC has a minimum test-retest reliability at any age of .75 and an interrater reliability of .70.1,41 The MABC also has been validated against other measures of motor performance.42,43 Specific standardization of the test in Scandinavia has not yet been carried out; however, several studies have shown that the norms provided in the MABC manual are valid for Scandinavian children.44 – 46

Jumping a distance of 7 m on both feet as quickly as possible. The test item score (the better of 2 attempts) is the time (in seconds) needed to cross the distance.

TPF The TPF is a measure that aims to provide a reliable quantification of a child’s physical fitness.18,24 It consists of activities that are included in most children’s everyday play activities, such as jumping, throwing, running, and climbing. The TPF consists of 9 test items: 3 items based on jumping, 2 based on throwing, 1 based on climbing, and 3 based on running. Most test items also appear in other batteries, such as the European Test of Physical Fitness (EUROFIT),47 the Allgemeiner Sportsmotorischer Test (AST 6 –11),48 the FBH Provet,49 and the Prudential Fitnessgram.50 The test item “climbing wall bars” was designed specifically for the TPF. The test-retest correlation of the TPF total score is high, at .90 1092

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The 9 test items are described below. Standing broad jump. The child starts with the feet parallel and a shoulder width apart behind a starting line. At a signal, the child swings his or her arms backward and forward and jumps with both feet simultaneously as far forward as possible. The test item score (the better of 2 attempts) is the distance (in centimeters) between the starting line and the landing position.

Jumping a distance of 7 m on 1 foot as quickly as possible. The child is free to choose which foot. The test item score (the better of 2 attempts) is the time (in seconds) needed to cross the distance. Throwing a tennis ball with 1 hand as far as possible. The child chooses which hand. The child stands with the contralateral foot in front of the ipsilateral foot. The test item score (the better of 2 attempts) is the distance thrown (in centimeters). Putting a medicine ball (1 kg) with both hands simultaneously as far as possible. The starting position is with the feet parallel and a shoulder width apart and the ball held against the chest. The test item score (the better of 2 attempts) is the distance achieved (in centimeters). Climbing wall bars, crossing over 2 columns to the right, and going down the fourth column as

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quickly as possible. Each column of wall bars is 255 cm high and 75 cm wide. The test item score (the better of 2 attempts) is the time (in seconds) needed to complete the maneuver. Shuttle sprint. The test item score is the time (in seconds) needed to run 5 m 10 times. If the child makes a procedural error, then performance is interrupted and the test item is repeated. Running 20 m as quickly as possible. The child starts in a standing position. If the child makes a procedural error, performance is interrupted and the test item is repeated. The test item score is the time (in seconds) needed to run the distance. Reduced Cooper test. The child runs or walks around a marked rectangle measuring 9 ⫻ 18 m (the size of a volleyball field) for 6 minutes. Both running and walking are allowed. The test item score is the distance covered (in meters) in 6 minutes. The following materials are needed for administering the test items: masking tape, ruler, stopwatch, tennis ball, medicine ball (1 kg), wall bars at least 4 columns wide, and gymnasium mats. Procedure The study was carried out in accordance with the Declaration of Helsinki. Before data were gathered, participants and parents were given written information about the nature of the study. Written consent was obtained from participants and parents or guardians before involvement in the study. Identification numbers were used to maintain data confidentiality. No child had any reported history of learning difficulties or any behavioral, neurological, or orthopedic problems that would

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Physical Fitness in Children With High and Low Motor Competence Table. Means, Standard Deviations, and 95% Confidence Intervals (CIs) for the 9 Items of the Test of Physical Fitness for Children With Low Motor Competence (LMC) (n⫽8) and Children With High Motor Competence (HMC) March 2004 Test Item Standing broad jump (cm)

Jumping on 2 feet (s)

Jumping on 1 foot (s)

Throwing tennis ball (cm)

Putting medicine ball (cm)

Climbing wall bars (s)

Shuttle sprint (s)

Running 20 m (s)

Reduced Cooper test (m)

a

Group

X

November 2006

SD

95% CI

X

SD

95% CI

P

LMC

1.18

0.20

1.0–1.4

1.30

0.34

1.0–1.6

NSa

HMC

1.50

0.21

1.4–1.7

1.69

0.15

1.6–1.8

.001

LMC

4.40

0.81

3.7–5.1

3.84

1.03

3.0–4.7

NS

HMC

3.33

0.65

2.9–3.8

2.98

0.24

2.8–3.7

NS

LMC

3.36

0.77

2.7–4.0

3.07

0.48

2.7–3.7

NS

HMC

2.83

0.44

2.5–3.1

2.49

0.17

2.4–2.6

.034

LMC

11.54

3.35

8.7–14.3

13.59

2.70

11.3–15.9

NS

HMC

15.09

2.19

13.5–16.7

16.15

1.92

14.8–17.5

NS

LMC

3.94

0.57

3.5–4.4

5.26

0.60

4.8–5.8

⬍.001

HMC

5.00

0.37

4.7–5.3

6.60

0.42

6.3–6.9

⬍.001

LMC

7.77

2.76

5.5–10.1

4.41

1.11

3.5–5.3

.049

HMC

5.46

0.70

5.0–6.0

3.20

0.57

2.8–3.6

.004

LMC

25.54

2.99

23.0–28.0

24.07

3.07

21.5–26.6

NS

HMC

21.86

1.58

20.7–23.0

19.80

1.09

19.0–20.6

.003

LMC

4.54

0.38

4.2–4.9

4.46

0.41

4.1–4.8

NS

HMC

4.19

0.18

4.1–4.3

3.92

0.24

3.7–4.1

.012

LMC

924.44

107.21

834.8–1,014.1

1,116.38

106.44

1,027.4–1,205.4

⬍.001

HMC

1,033.95

129.65

941.2–1,126.7

1,281.11

111.10

1,195.7–1,366.5

⬍.001

NS⫽not significant.

qualify as exclusionary criteria for this study. All of the children were tested on the MABC and then on the TPF approximately 1 week later. The assessment of motor competence took place in a quiet room during normal school hours and was conducted in accordance with the MABC manual. The assessment of physical fitness took place in the school sports hall during school hours. Children were tested individually by assistants who had been trained in the test protocols. Each test item was explained and demonstrated before the child started. Each test item was performed twice, except for the 3 tests of running. Participants were given verbal encouragement and support throughout the testing procedure. If the child made a procedural error, instructions and demonstrations October 2009

were repeated and the child made a new attempt. The children wore clothing suitable for physical activity and trainers during both tests. The procedure was repeated 32 months later. Data Reduction and Analysis SPSS (version 16.0)* was used for statistical analysis. Differences in physical fitness between the 2 groups of children (those with HMC and those with LMC) over time were assessed by use of a 2 ⫻ 2 analysis of variance for the scores of the 9 different measurements of physical fitness. Group (LMC versus HMC) was used as the between-subjects factor, and time of testing was used as the repeatedmeasures factor. For measurement of the degree of association between an * SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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effect (eg, main effect of time or group, interaction effect of time ⫻ group) and a dependent variable (each of the items in the TPF), the partial ␩2 was used. The partial ␩2 can be interpreted as the proportion of variance in the dependent variable that is attributable to each effect. Statistical significance was set at P⬍.05. Role of the Funding Source This study was funded by a PhD grant from Sør-Trøndelag University College.

Results The means and standard deviations of the 9 different physical fitness measures for each group over time are shown in the Table. There were significant differences between the LMC group and the HMC group across all measures at the age of 9 years and at the age of 12 years. The Number 10

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Physical Fitness in Children With High and Low Motor Competence LMC group showed significant improvement over time on 3 of the 9 test items: putting the medicine ball, climbing wall bars, and the reduced Cooper test. The HMC group showed significant improvement over the same time on 7 of the 9 test items; no significant differences were observed in jumping on 2 feet or throwing the tennis ball. A 2 ⫻ 2 (time ⫻ group) mixed-model analysis of variance revealed that the main effect of group was significant (F9,7⫽10.157, P⬍.05), with a large effect size (partial ␩2⫽.929). Thus, there was an overall difference in physical fitness measures between the LMC group and the HMC group. A significant main effect was obtained for time (F9,7⫽28.750, P⬍.0001), with a very large effect size (partial ␩2⫽.974). Both groups scored significantly higher on the physical fitness measures after a period of 32 months. However, there was no significant time ⫻ group interaction (F9,7⫽0.742, P⬎.05; partial ␩2⫽.488). These data mean that the changes in physical fitness over time were similar for both the LMC group and the HMC group. The detailed results of the analysis of variance are reported below for each test item. Standing Broad Jump A significant main effect was obtained for time (F1,15⫽7.707, P⬍.05), with a moderate effect size (partial ␩2⫽.339). A significant main effect also was obtained for group (F1,15⫽12.700, P⬍.05), with a moderate effect size (partial ␩2⫽.458). There was no significant interaction effect (F1,15⫽0.135, P⬎.05; partial ␩2⫽.009). Jumping on Both Feet The main effect of time was not significant (F1,15⫽3.542, P⬎.05; partial ␩2⫽.191). The main effect of group was significant (F1,15⫽ 13.432, P⬍.05), and the effect size was moderate (partial ␩2⫽.472). 1094

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There was no significant interaction effect (F1,15⫽0.182, P⬎.05; partial ␩2⫽.012). Jumping on 1 Foot There was a significant main effect of time (F1,15⫽6.623, P⬍.05), with a moderate effect size (partial ␩2⫽.306). The main effect of group was significant (F1,15⫽6.952, P⬍.05), with a moderate effect size (partial ␩2⫽.317). There was no significant interaction effect (F1,15⫽ 0.002, P⬎.05; partial ␩2⫽.000). Throwing a Tennis Ball There was a significant main effect of time (F1,15⫽8.212, P⬍.05; partial ␩2⫽.354). The main effect of group was significant (F1,15⫽11.196, P⬍ .05; partial ␩2⫽.427). There was no significant interaction effect (F1,15⫽ 0.234, P⬎.05; partial ␩2⫽.015). Putting a Medicine Ball There was a significant main effect of time (F1,15⫽104.623, P⬍.05; partial ␩2⫽.306). The main effect of group was significant (F1,15⫽36.860, P⬍ .05; partial ␩2⫽.711). There was no significant interaction effect (F1,15⫽ 1.030, P⬎.05; partial ␩2⫽.064). Climbing Wall Bars There was a significant main effect of time (F1,15⫽38.637, P⬍.05), with a large effect size (partial ␩2⫽.720). The main effect of group was significant (F1,15⫽10.060, P⬍.05), with a moderate effect size (partial ␩2⫽.401). There was no significant interaction effect (F1,15⫽2.094, P⬎.05; partial ␩2⫽.122). Shuttle Sprint There was a significant main effect of time (F1,15⫽13.343, P⬍.05), with a moderate effect size (partial ␩2⫽.471). The main effect of group was significant (F1,15⫽15.707, P⬍.05), with a moderate effect size (partial ␩2⫽.512). There was no significant interaction effect (F1,15⫽ 0.265, P⬎.05; partial ␩2⫽.017).

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Running 20 Meters There was a significant main effect of time (F1,15⫽5.491, P⬍.05), with a moderate effect size (partial ␩2⫽.268). The main effect of group was significant (F1,15⫽11.535, P⬍.05), with a moderate effect size (partial ␩2⫽.435). There was no significant interaction effect (F1,15⫽ 1.429; df⫽1,15, partial ␩2⫽.087). Reduced Cooper Test There was a significant main effect of time (F1,15⫽80.377, P⬍.05), with a moderate effect size (partial ␩2⫽.306). The main effect of group was significant (F1,15⫽11.005, P⬍.05), with a moderate effect size (partial ␩2⫽.423). There was no significant interaction effect (F1,15⫽ 0.321, P⬎.05; partial ␩2⫽.021).

Discussion The main purpose of this study was to examine how physical fitness developed over time in 2 groups of children: those with LMC and those with HMC. Several physical fitness components were tracked over a period of 32 months. The main effect of group revealed an overall difference in physical fitness measures between the LMC group and the HMC group, favoring the latter on all 9 test items. The LMC group performed more poorly than the HMC group on all 9 test items at both measurement points (Table). This finding is in accordance with studies reporting reduced physical fitness in terms of reduced aerobic and anaerobic endurance,16,17,25 reduced muscular strength and endurance,15,17,19 and reduced speed or agility15,18 in children with LMC compared with their peers. One cannot presume that children with motor problems grow out of their coordination difficulties as they age7; as a consequence, it is likely that other negative implications of the condition will persist into adolesOctober 2009

Physical Fitness in Children With High and Low Motor Competence cence and adulthood. Therefore, a concern is that children with LMC will continue to show decreased participation in physical activity and reduced physical fitness compared with their peers.14 As Bouffard et al30 stated with regard to their activity deficit hypothesis, it is easy to imagine how poor coordination and poor performance in motor activities influence a child’s enjoyment and motivation to participate in physical activity. In discussions about determinants of physical activity behavior in childhood, in terms of activity patterns and levels, children’s selfefficacy in the physical domain51,52 and perceived motivational environment in learning situations53 often are identified as being important. According to Harter’s competence motivation theory,54 children with LMC develop a negative perception of their own physical competence, making them less likely to choose challenging tasks and more likely to reveal a lack of endurance in demanding physical activity tasks. The different test items used to assess physical fitness require coordination and motor planning. As a consequence, many children with motor problems find such tests particularly difficult to perform.55,56 Inefficient movement patterns contribute to poor test outcomes even though children may be making just as much of an effort as their peers without coordination problems.15 Because of those patterns, along with a negative self-perception of competence in the physical domain, children with LMC may be less likely to persist at a task and may abandon the effort sooner, resulting in poorer outcomes on tasks such as aerobic performance tests.29 In the present study, the use of TPF was an attempt to assess children’s fitness in a more “child-friendly” way. The test situation was characterized by a game-style atmosphere, and the tasks were easy to underOctober 2009

stand and meaningful for the children; such characteristics might reduce children’s level of stress and facilitate their motivation to participate and perform as well as possible. It is fair to assume that the use of tasks that are easily understandable and meaningful to children will reduce the cognitive demands of motor planning.24

cents, or adults, suggesting that differences in fitness between children with LMC and children with HMC increase with age.17,19 Motor proficiency in childhood appears to be an important factor in developing a positive self-perception of competence in the physical domain and seems to be connected to increased physical activity and fitness in adolescence.57

A significant main effect of time indicated that both groups scored significantly higher on the TPF after a period of 32 months. However, as indicated in the Table, the LMC group showed no significant improvement over that time period on 6 of the 9 test items, which contained elements of cardiovascular fitness, muscular fitness, and speed or agility. However, performance was significantly better in putting a medicine ball, climbing wall bars, and performing the reduced Cooper test. The HMC group showed significant improvement on 7 of the 9 test items; no significant increase was found for jumping on 2 feet or throwing a tennis ball. There was no significant interaction effect, indicating that the relative differences in physical fitness outcomes between the groups were maintained over time.

Physical fitness is considered to be a powerful marker of health outcomes in children and adolescents.22 Studies of the relationship between physical fitness and overweight or obesity in young people have indicated that there is an inverse relationship between the 2 factors.58,59 A low level of cardiovascular fitness has also been associated with clustering of cardiovascular disease risk factors in children.36,38 Atypical development of physical fitness and a low level of physical activity may also restrict the opportunities for children with LMC to practice and develop movement skills.56,60

The impact of LMC on fitness measures over time has now been confirmed in longitudinal research.32 Changes over time were significantly different between the LMC group and the HMC group for measures such as the multistage fitness test, 50-m run, and balance.32 Results from cross-sectional studies of children, adolescents, and adults with DCD revealed that several indicators of poorer fitness outcomes and negative metabolic indexes were found across all ages for these groups compared with their control groups.17,19 However, sometimes these negative fitness outcomes were found only in the group of oldest children, adolesVolume 89

How to measure and survey children’s physical fitness status has been the subject of much debate in the literature; the discussion has included different methodological challenges.61 Another issue has been whether it is more important to measure participation in physical activity (in terms of activity patterns, habits, and levels) or an individual’s physical fitness.22,36,62 Although physical activity can be viewed as a complex, multidimensional behavior,63 physical fitness can be defined as the capacity to perform physical activity.22 When physical fitness is tested, all body functions involved in the performance of physical activity are evaluated.22 Therefore, physical fitness may be a more precise way to predict health outcomes in children than physical activity.59 It may be intuitively obvious that there is a link between physical activity and motor competence, as conNumber 10

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Physical Fitness in Children With High and Low Motor Competence firmed by the study of Wrotniak et al.27 However, the results of other studies that explored this relationship showed that these variables were not strongly related.64 – 66 These results may have been attributable to the different methodological challenges of assessing children’s physical activity levels. The present study had several limitations that will motivate future work. Anthropometric variables were not measured, and participants were not matched for other physical variables, such as body composition (weight/ height and body mass index). Differences in these variables among participants may affect different aspects of physical fitness. In addition, children’s perceived self-efficacy in athletic competence was not assessed. This factor can influence the desire to participate in physical activity as well as physical fitness, especially in children with LMC. The statistical power of the relatively small sample also must be taken into account. A complete and substantiated approach to intervention for children with coordination difficulties is still needed.67 However, in addition to reducing motor problems in these children, an objective must be to minimize the additional consequences of these difficulties for other aspects of life. It is important, therefore, to assess not only motor competence but also overall physical fitness with suitable assessment tools. Furthermore, intervention settings should focus on improving general fitness, not just motor skills, in children with LMC. It also is important to gain a better understanding of the factors that influence children’s participation and how patterns of physical activity and physical fitness are created. Focusing on the creation of optimal motivational environments in learning situations and the creation of 1096

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positive self-efficacy for physical activity in children with LMC may be beneficial as well. A child’s selfperception of competence in the physical domain can be regarded as an important predictor of physical fitness outcomes in adolescence and is influenced by motor competence in childhood.57 The identification of children at risk of developing a low level of fitness may be relevant, so that preventive strategies or clinical treatments can be applied at an early stage. The results of the present study indicate that motor competence has multifaceted implications for different components of physical fitness in children. Children with LMC performed less well on all fitness measures than children with HMC. Both groups scored significantly higher on the TPF after a period of 32 months, but the relative differences in physical fitness outcomes between the groups were stable over time. More empirical findings and longitudinal studies should provide an improved understanding of the relationship between motor competence and factors related to physical fitness. Ethical approval for this study was granted by the Norwegian Social Science Data Service. This study was funded by a PhD grant from Sør-Trøndelag University College. This article was received February 19, 2009, and was accepted June 29, 2009. DOI: 10.2522/ptj.20090052

References 1 Henderson SE, Sugden D. The Movement Assessment Battery for Children. Kent, United Kingdom: The Psychological Corporation; 1992. 2 Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994. 3 Polatajko H, Cantin N. Developmental coordination disorder (dyspraxia): an overview of the state of the art. Semin Pediatr Neurol. 2006;12:250 –258. 4 Summers J, Larkin D, Dewey D. Activities of daily living in children with developmental coordination disorder: dressing, personal hygiene, and eating skill. Hum Mov Sci. 2008;27:215–229.

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5 Losse A, Henderson SE, Elliman D, et al. Clumsiness in children: do they grow out of it? A 10-year follow-up study. Dev Med Child Neurol. 1991;33:55– 68. 6 Geuze R, Bo ¨ rger H. Children who are clumsy: five years later. Adapt Phys Activ Q. 1993;10:10 –21. 7 Cantell MH, Smyth MM, Ahonen TP. Two distinct pathways for developmental coordination disorder: persistence and resolution. Hum Mov Sci. 2003;22:413– 431. 8 Maes HHM, Beunen GP, Vlietnik RF, et al. Inheritance of physical fitness in 10-yr-old twins and their parents. Med Sci Sports Exerc. 1996;28:1479 –1491. 9 Mandich AD, Polatajko HJ, Rodger S. Rites of passage: understanding participation of children with developmental coordination disorder. Hum Mov Sci. 2003;22:583–595. 10 Piek JP, Baynam GB, Barrett NC. The relationship between fine and gross motor ability, self-perceptions and self-worth in children and adolescents. Hum Mov Sci. 2006;25:65–75. 11 Green D, Baird G, Sugden D. A pilot study of psychopathology in developmental coordination disorder. Child Care Health Dev. 2006;32:741–750. 12 Piek JP, Rigoli D, Pearsall-Jones JG, et al. Depressive symptomatology in child and adolescent twins with attention-deficit hyperactivity disorder and/or developmental coordination disorder. Twin Res Hum Genet. 2007;10:587–596. 13 Smyth MM, Anderson HI. Coping with clumsiness in the school playground: social and physical play in children with coordination impairments. Br J Dev Psychol. 2000;18:389 – 413. 14 Cairney J, Hay JA, Faught BE, et al. Developmental coordination disorder, age, and play: a test of the divergence in activitydeficit with age hypothesis. Adapt Phys Activ Q. 2006;23:261–276. 15 Hands B, Larkin D. Physical fitness differences in children with and without motor learning difficulties. European Journal of Special Needs Education. 2006;21: 447– 456. 16 Cairney J, Hay JA, Faught BE, et al. Developmental coordination disorder and cardiorespiratory fitness in children. Pediatr Exerc Sci. 2007;19:20 –28. 17 Scott N, Alof V, Hultsch D, Meemann D. Physical fitness in children with developmental coordination disorder. Res Q Exerc Sport. 2007;78:438 – 450. 18 Haga M. Physical fitness in children with movement difficulties. Physiotherapy. 2008;94:253–259. 19 Cantell MH, Crawford SG, Doyle-Parker PK. Physical fitness and health indices in children, adolescents and adults with high or low motor competence. Hum Mov Sci. 2008;27:344 –362. 20 Bouchard C. Heredity and health-related fitness. Physical Activity & Fitness Research Digest. 1993;1:1–7. 21 Gallahue DL, Ozmun JC. Understanding Motor Development: Infants, Children, Adolescents, Adults. 6th ed. Boston, MA: McGraw-Hill Book Co; 2006.

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Physical Fitness in Children With High and Low Motor Competence 22 Ortega FB, Ruiz JR, Castillo MJ, Sjo ¨ stro ¨m M. Physical fitness in childhood and adolescence: a powerful marker of health. Int J Obes (Lond). 2008;32:1–11. 23 Powell KE, Casperson C, Koplan JP, Ford ES. Physical activity and chronic disease. Am J Clin Nutr. 1998;49:999 –1006. 24 Fjørtoft I, Pedersen AV, Sigmundsson H, Vereijken B. Testing Children’s Physical Fitness: Developing a New Test for 4 –12 Year Old Children. Oslo, Norway: The Norwegian Social and Health Ministry; 2003. Report IS-1256. 25 Faught BE, Hay JA, Cairney J, Flouris A. Increased risk for coronary vascular disease in children with developmental coordination disorder. J Adolesc Health. 2005; 37:376 –380. 26 Okely AD, Booth ML, Patterson JW. Relationships of physical activity to fundamental movement skills among adolescents. Med Sci Sports Exerc. 2001;33:1899 –1904. 27 Wrotniak BH, Epstein LH, Dorn JM, et al. The relationship between motor proficiency and physical activity in children. Pediatrics. 2006;118:1758 –1765. 28 Cairney J, Hay JA, Faught BE, et al. Developmental coordination disorder, selfefficacy toward physical activity and participation in free play and organized activities: does gender matter? Adapt Phys Activ Q. 2005;22:67– 82. 29 Cairney J, Hay JA, Wade T, et al. Developmental coordination disorder and aerobic fitness: is it all in their heads or is measurement still the problem? Am J Hum Biol. 2006;18:66 –70. 30 Bouffard M, Watkinson EJ, Thompson LP, et al. A test of the activity deficit hypothesis with children with movement difficulties. Adapt Phys Activ Q. 1996;13:61–73. 31 Wall T. The developmental skill-learning gap hypothesis: implications for children with movement difficulties. Adapt Phys Activ Q. 2004;21:197–218. 32 Hands B. Changes in motor skill and fitness measures among children with high and low motor competence: a five-year longitudinal study. J Sci Med Sport. 2008; 11:155–162. 33 Kristensen PL, Møller NC, Korsholm L, et al. Tracking of objectively measured physical activity from childhood to adolescence: the European Youth Heart Study. Scand J Med Sci Sports. 2008;18:171–178. 34 Hallal PC, Victoria CG, Azevedo MR, Wells JCK. Adolescents’ physical activity and health: a systematic review. Sports Med. 2004;36:1019 –1030. 35 Strong WB, Malina RM, Blimkie CJR, et al. Evidence based physical activity for schoolage youth. J Pediatr. 2005;146:732–737. 36 Hurtig-Wennlo ¨ f A, Ruiz JR, Harro M, Sjo ¨stro ¨ m M. Cardiorespiratory fitness relates more strongly than physical activity to cardiovascular disease risk factors in healthy children and adolescents: the European Youth Heart Study. Eur J Cardiovasc Prev Rehab. 2007;14:575–581. 37 Ortega FB, Tresaco B, Ruiz JR, et al. Cardiorespiratory fitness and sedentary activities are associated with adiposity in adolescents. Obesity. 2007;15:1589 –1599.

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38 Anderssen SA, Cooper AR, Riddoch C, et al. Low cardiorespiratory fitness is a strong predictor for clustering of cardiovascular disease risk factors in children independent of country, age and sex. Eur J Cardiovasc Prev Rehab. 2007;14:526 – 531. 39 Stott DH, Moyes FA, Henderson SE. The Test of Motor Impairment. San Antonio, TX: The Psychological Corporation; 1985. 40 Visser J, Geuze RG, Kalverboer AF. The relationship between physical growth, the level of activity and the development of motor skills in adolescence: differences between children with DCD and controls. Hum Mov Sci. 1998;17:573– 608. 41 Tan SK, Parker HE, Larkin D. Concurrent validity of motor test used to identify children with motor impairment. Adapt Phys Activ Q. 2001;18:168 –182. 42 Bruininks RH. Bruininks-Oseretsky Test of Motor Proficiency: Examiner’s Manual. Circle Pines, MN: American Guidance Service; 1978. 43 Crawford SG, Wilson BN, Dewey D. Identifying developmental coordination disorder: consistency between tests. Phys Occup Ther Pediatr. 2001;20:29 –50. 44 Mæland AF. Identification of children with motor coordination problems. Adapt Phys Activ Q. 1992;9:330 –342. 45 Røsblad B, Gard L. The assessment of children with developmental coordination disorders in Sweden: a preliminary investigation of the suitability of the Movement ABC. Hum Mov Sci. 1998;17:711–719. 46 Sigmundsson H, Rostoft MS. Motor development: exploring the motor competence of 4-year-old Norwegian children. Scandinavian Journal of Educational Research. 2003;47:451– 459. 47 Adam C, Klissouras V, Ravazollo M, et al. EUROFIT: European Test of Physical Fitness—Handbook. Rome, Italy: Committee for the Development of Sport, Council of Europe; 1998. 48 Bo ¨ s K, Wohlman R. Allgemeiner Sportsmotorischer Test (AST 6 –11) zur Diagnose der konditionellen und koordinativen Leistungsfa¨higkeit. Lehrilfen fu ¨ r den Sportunterrich. 1987;36:145–160. 49 Bille B, Brieditis K, Ekstro ¨ m B, Esscher E. FBH Provet: Erfarenheter från Folke Ber¨ rebro, Sweden: Monadottehemmet. O torika; 1992. 50 The Prudential Fitnessgram: Test Administration Manual. Dallas, TX: Cooper Institute for Aerobics Research; 2001. 51 Cairney J, Hay JA, Faught BE, et al. Developmental coordination disorder, generalized self-efficacy toward physical activity, and participation in organized and free play activities. J Pediatr. 2005;147:515– 520. 52 Poulsen AA, Ziviani JM, Cuskelly M. General self-concept and life satisfaction for boys with differing levels of physical coordination: the role of goal orientations and leisure participation. Hum Mov Sci. 2006;25:839 – 860.

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53 Causgrove Dunn J, Dunn JGH. Psychosocial determinants of physical education behaviour in children with movement difficulties. Adapt Phys Activ Q. 2006;23:293– 309. 54 Harter S. The determinants and mediational role of global self-worth in children. In: Eisenberg N, ed. Contemporary Topics in Developmental Psychology. New York, NY: Wiley; 1987:219 –242. 55 O’Beirne C, Larkin D, Cable T. Coordination problems and anaerobic performance in children. Adapt Phys Activ Q. 1994;11: 141–149. 56 Hands B, Larkin D. Physical fitness and developmental coordination disorder. In: Cermak SA, Larkin D, eds. Developmental Co-ordination Disorder. Albany, NY: Thomson Learning; 2002:172–184. 57 Barnett LM, Morgan PJ, van Beurden E, Beard JR. Perceived sports competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment. Int J Behav Nutr Phys Act. 2008;5:40. Available at: http://www. ijbnpa.org/content/5/1/40. DOI: 10.1186/ 1479-5868-5-40. 58 Kim J, Must A, Fitzmaurice GM, et al. Relationship of physical fitness to prevalence and incidence of overweight among schoolchildren. Obes Res. 2005;13:1246 –1254. 59 Bovet P, Auguste R, Burdette H. Strong inverse association between physical fitness and overweight in adolescents: a large school-based survey. Int J Behav Nutr Phys Act. 2007;4:24. Available at: http://www.ijbnpa.org/content/4/1/24. DOI: 10.1186/1479-5868-4-24. 60 Marshall JD, Bouffard M. The effects of quality daily physical education on movement competency in obese versus nonobese children. Adapt Phys Activ Q. 1997; 14:222–237. 61 Harris J, Cale L. A review of children’s fitness testing. European Physical Education Review. 2006;12:201–225. 62 Blair SN, Cheng Y, Scott Holder J. Is physical activity or physical fitness more important in defining health benefits? Med Sci Sports Exerc. 2001;33:379 –399. 63 Boreham C, Riddoch C. The physical activity, fitness and health of children. J Sports Sci. 2001;19:915–929. 64 Fisher A, Reilly JJ, Kelly LA, et al. Fundamental movement skills and habitual physical activity in young children. Med Sci Sports Exerc. 2005;37:684 – 688. 65 Okely AD, Booth ML, Patterson JW. Relationships of physical activity to fundamental movement skills among adolescents. Med Sci Sports Exerc. 2001;33:1899 –1904. 66 Reed JA, Metzker A, Phillips DA. Relationships between physical activity and motor skills in middle school children. Percept Mot Skills. 2004;99:483– 494. 67 Sugden D. Current approaches to intervention in children with developmental coordination disorder. Dev Med Child Neurol. 2007;49:467– 471.

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Letters to the Editor On “A guide to interpretation of studies...” Hancock M, et al. Phys Ther. 2009; 89:698–704. I read with interest and some puzzlement the article titled “A Guide to Interpretation of Studies Investigating Subgroups of Responders to Physical Therapy Interventions” by Hancock et al1 in the July 2009 issue of PTJ. In their article, these authors expressed the opinion that treatment-related clinical prediction rules (CPRs) are flawed when derived using single-arm studies. The single-arm research design has been used for virtually all published CPRs in this category, so the implication seems to be that all currently published CPR derivations of this type are inherently flawed. These authors drew distinctions among treatment effect modifiers, prognostic factors, and diagnostic tests. They asserted that although a single-arm research design is appropriate for prognostic and diagnostic studies, this design is inappropriate for determining treatment effect modifiers, which are best determined with randomized controlled trials (RCTs). As an author who has participated in several CPR derivation studies,2–4 I believe it is unnecessarily limiting to rigidly compartmentalize patient attributes quantitatively associated with treatment success or nonsuccess as treatment effect modifiers, prognostic factors, or diagnostic tests. Any patient attribute or combination of attributes measured at an initial assessment with power to predict treatment success or nonsuccess is potentially clinically useful regardless of what label we place on it. Using a CPR to quantitatively predict a probability of treatment success can be viewed as prognosis: “Given your clinical presentation, your prognosis is

a 95% probability of success with this proposed treatment.” Using a CPR as part of a treatment-based classification scheme also can be viewed as diagnosis: “Given your clinical presentation, my diagnosis is that you have the kind of low back pain that will likely respond well to spinal manipulation.” If predictive attributes derived quantitatively are later validated in independent studies, the research design used to first identify those attributes is, by any pragmatic consideration, adequate. Hancock et al stated their opinion that “there is no reason to expect that factors found in single-arm trials to be predictive of outcome will subsequently be found in 2-arm trials to be predictive of response to treatment.”1(p700) This statement unaccountably follows immediately after their description of 2 such related studies that contradict that premise. Flynn et al2 used a single-arm trial to derive a CPR to suggest which patients with low back pain might be the best candidates for spinal manipulation. Childs et al5 later used that derived CPR in an RCT and found that the attributes identified by Flynn et al indeed were predictive of treatment success. The existence of these 2 studies, combined with subsequent reports of successful implementation of this CPR in clinical settings,6,7 seems to undermine the basic premise presented by Hancock et al, yet there was no apparent attempt in their perspective article to reconcile this contradiction. An alternate interpretation of our efforts to develop treatment-related CPRs in physical therapy might be that the single-arm trial design has been our most successful method to date for this purpose: 100% of CPRs derived from single-arm trials subsequently subjected to RCT validation (1 of 1) demonstrated a clinically useful result.


We have only begun to explore methods and results to achieve the highly desirable outcome of clinically useful CPRs for helping to determine which patients are best candidates for specific physical therapy treatments. I believe the categorical dismissal by Hancock et al of the single-arm trial method as a data-driven approach to CPR derivation is unwarranted. As an alternative to data-driven methods used with single-arm trials, Hancock et al suggested instead that researchers rely upon intuitive use of “plausible rationale” to define patient attributes possibly predictive of treatment success that then can be used to define subgroups in RCTs that would show significant interaction effects. Although I respect the need to combine clinical judgment with results of data analysis in order to derive CPRs that are both statistically sound and clinically useful, I am surprised by the suggestion that we revert to notions of biologic plausibility for our initial estimates of treatment effect modifiers to study. Over-reliance on notions of biologic plausibility for treatment decisions is thought to be partly responsible for our current problem of unwarranted variation in patient care offered by physical therapists and others.8,9 I hope that discussion of methods and uses of CPRs intended to help inform clinical treatment decisions will continue. However, I believe it is unhelpful to categorically dismiss an approach using a specific research design that has been shown to successfully identify a cluster of patient attributes later validated to help identify which patients are the best candidates for a specific treatment. As others have noted, it is now time for more research to determine whether derived CPRs can be validated and thereafter October 2009

Letters to the Editor used in the clinic to provide better patient outcomes. Stephen C. Allison S.C. Allison, PT, PhD, is Professor, Rocky Mountain University of Health Professions, and Associate Professor, Baylor University. This letter was posted as a Rapid Response on August 12, 2009, at www.ptjournal.org.

References 1 Hancock M, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009;89:698–704. 2 Flynn T, Fritz J, Whitman J, et al. A clinical prediction rule for classifying patients with low back pain who demonstrate shortterm improvement with spinal manipulation. Spine. 2002;27:2835–2843. 3 Wainner RS, Fritz JM, Irrgang JJ, et al. Reliability and diagnostic accuracy of the clinical examination and patient self-report measures for cervical radiculopathy. Spine. 2003;28:52–62. 4 Wainner RS, Fritz JM, Irrgang JJ, et al. Development of a clinical prediction rule for the diagnosis of carpal tunnel syndrome. Arch Phys Med Rehabil. 2005;86:609–618. 5 Childs JD, Fritz JM, Flynn TW, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928. 6 Childs JD, Fritz JM, Piva SR, Erhard RE. Clinical decision making in the identification of patients likely to benefit from spinal manipulation: a traditional versus an evidence-based approach. J Orthop Sports Phys Ther. 2003;33:259–272. 7 Cleland JA, Fritz JM, Whitman JM, et al. The use of a lumbar spine manipulation technique by physical therapists in patients who satisfy a clinical prediction rule: a case series. J Orthop Sports Phys Ther. 2006;36:209–214. 8 Fritz J, Flynn TW. Autonomy in physical therapy: less is more. J Orthop Sports Phys Ther. 2005;35:696–698. 9 Wennberg JE. Unwarranted variations in healthcare delivery: implications for academic medical centres. BMJ. 2002;325(7370):961–964. [DOI: 10.2522/ptj.2009.89.10.1098]

Author Response Allison1 writes to defend the use of single-arm trials to investigate treatment effect modification. This position, in our view, is not defensible. October 2009

The effect of treatment is the difference between outcomes with and without treatment. A single-arm trial cannot provide information about outcomes without treatment, so it cannot quantify the effect of treatment. Therefore, single-arm trials cannot quantify treatment effect modification. In our opinion, much of the confusion with regard to clinical prediction rules (CPRs) for physical therapy intervention has arisen because investigators have ignored these basic methodological considerations. In contrast to Allison, we believe the distinction between prognostic factors and treatment effect modifiers is important. Allison provides an example in which a patient is told, “Given your clinical presentation, your prognosis is a 95% probability of success with this proposed treatment.” This statement implies that success is due to the treatment. If the trial is a single-arm trial, then it is not possible to determine whether a successful outcome is due in any way to the treatment, so the information provided to the patient is potentially misleading. In the second example, the patient is told he or she “will likely respond well to spinal manipulation”; again, this statement is potentially misleading if it is based on a trial with no control group. In this case, treatment effects cannot be established. It could be that patients with those characteristics may recover equally quickly without any treatment or with an alternative treatment. Patients have the right to know if their outcome is due to treatment (treatment effects) or equally likely without treatment (prognosis). Allison indicates that we categorically dismiss any use of single-arm trials in CPR derivation. This was not our intent, nor do we believe that our article states this. On this point, our article states, “Where research-

ers believe there is a rationale for why a CPR derived in a single-arm study also may predict response to an intervention, the CPR should be investigated in a controlled trial before any suggestion about the role in predicting response to treatment is made.”2(p700) Some prognostic factors may later be shown to be effect modifiers, but many will not. Until tested in a controlled trial, there is no evidence that the predictor can identify people with a favorable response to treatment, and it is misleading to readers of the literature—and to patients—to suggest otherwise. Allison refers to the trials of Flynn et al3 and Childs et al4 as support for the notion that single-arm trials can be used to identify responders to intervention. He does not refer to the far more numerous examples of secondary analyses of clinical trials that clearly demonstrate that certain factors associated with prognosis are not associated with response to a specific treatment. His position also ignores the most fundamental principles of clinical research. The need for controlled trials to identify the effect of specific interventions is universally accepted. Julie Fritz, who was a senior author on the 2 trials referred to by Allison, participated in a recent PTJ podcast on the topic of effect modification (http://www.ptjournal.org/ cgi/content/full/89/7/698/DC1). We encourage readers to listen to the podcast. Fritz’s comments on this issue broadly align with ours. Mark Hancock, Rob Herbert, Christopher G. Maher M. Hancock, PT, PhD, is Lecturer, Back Pain Research Group, The University of Sydney, Sydney, New South Wales, Australia R. Herbert PT, PhD, is Senior Research Fellow, The George Institute for International Health, The University of Sydney.


Letters to the Editor used in the clinic to provide better patient outcomes. Stephen C. Allison S.C. Allison, PT, PhD, is Professor, Rocky Mountain University of Health Professions, and Associate Professor, Baylor University. This letter was posted as a Rapid Response on August 12, 2009, at www.ptjournal.org.

References 1 Hancock M, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009;89:698–704. 2 Flynn T, Fritz J, Whitman J, et al. A clinical prediction rule for classifying patients with low back pain who demonstrate shortterm improvement with spinal manipulation. Spine. 2002;27:2835–2843. 3 Wainner RS, Fritz JM, Irrgang JJ, et al. Reliability and diagnostic accuracy of the clinical examination and patient self-report measures for cervical radiculopathy. Spine. 2003;28:52–62. 4 Wainner RS, Fritz JM, Irrgang JJ, et al. Development of a clinical prediction rule for the diagnosis of carpal tunnel syndrome. Arch Phys Med Rehabil. 2005;86:609–618. 5 Childs JD, Fritz JM, Flynn TW, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928. 6 Childs JD, Fritz JM, Piva SR, Erhard RE. Clinical decision making in the identification of patients likely to benefit from spinal manipulation: a traditional versus an evidence-based approach. J Orthop Sports Phys Ther. 2003;33:259–272. 7 Cleland JA, Fritz JM, Whitman JM, et al. The use of a lumbar spine manipulation technique by physical therapists in patients who satisfy a clinical prediction rule: a case series. J Orthop Sports Phys Ther. 2006;36:209–214. 8 Fritz J, Flynn TW. Autonomy in physical therapy: less is more. J Orthop Sports Phys Ther. 2005;35:696–698. 9 Wennberg JE. Unwarranted variations in healthcare delivery: implications for academic medical centres. BMJ. 2002;325(7370):961–964. [DOI: 10.2522/ptj.2009.89.10.1098]

Author Response Allison1 writes to defend the use of single-arm trials to investigate treatment effect modification. This position, in our view, is not defensible. October 2009

The effect of treatment is the difference between outcomes with and without treatment. A single-arm trial cannot provide information about outcomes without treatment, so it cannot quantify the effect of treatment. Therefore, single-arm trials cannot quantify treatment effect modification. In our opinion, much of the confusion with regard to clinical prediction rules (CPRs) for physical therapy intervention has arisen because investigators have ignored these basic methodological considerations. In contrast to Allison, we believe the distinction between prognostic factors and treatment effect modifiers is important. Allison provides an example in which a patient is told, “Given your clinical presentation, your prognosis is a 95% probability of success with this proposed treatment.” This statement implies that success is due to the treatment. If the trial is a single-arm trial, then it is not possible to determine whether a successful outcome is due in any way to the treatment, so the information provided to the patient is potentially misleading. In the second example, the patient is told he or she “will likely respond well to spinal manipulation”; again, this statement is potentially misleading if it is based on a trial with no control group. In this case, treatment effects cannot be established. It could be that patients with those characteristics may recover equally quickly without any treatment or with an alternative treatment. Patients have the right to know if their outcome is due to treatment (treatment effects) or equally likely without treatment (prognosis). Allison indicates that we categorically dismiss any use of single-arm trials in CPR derivation. This was not our intent, nor do we believe that our article states this. On this point, our article states, “Where research-

ers believe there is a rationale for why a CPR derived in a single-arm study also may predict response to an intervention, the CPR should be investigated in a controlled trial before any suggestion about the role in predicting response to treatment is made.”2(p700) Some prognostic factors may later be shown to be effect modifiers, but many will not. Until tested in a controlled trial, there is no evidence that the predictor can identify people with a favorable response to treatment, and it is misleading to readers of the literature—and to patients—to suggest otherwise. Allison refers to the trials of Flynn et al3 and Childs et al4 as support for the notion that single-arm trials can be used to identify responders to intervention. He does not refer to the far more numerous examples of secondary analyses of clinical trials that clearly demonstrate that certain factors associated with prognosis are not associated with response to a specific treatment. His position also ignores the most fundamental principles of clinical research. The need for controlled trials to identify the effect of specific interventions is universally accepted. Julie Fritz, who was a senior author on the 2 trials referred to by Allison, participated in a recent PTJ podcast on the topic of effect modification (http://www.ptjournal.org/ cgi/content/full/89/7/698/DC1). We encourage readers to listen to the podcast. Fritz’s comments on this issue broadly align with ours. Mark Hancock, Rob Herbert, Christopher G. Maher M. Hancock, PT, PhD, is Lecturer, Back Pain Research Group, The University of Sydney, Sydney, New South Wales, Australia R. Herbert PT, PhD, is Senior Research Fellow, The George Institute for International Health, The University of Sydney.


Letters to the Editor C.G. Maher, PT, PhD, is Director, The George Institute for International Health, The University of Sydney. This letter was posted as a Rapid Response on August 24, 2009, at www.ptjournal.org.

References 1 Allison SC. Letter to the editor on “A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions.” Phys Ther. 2009;89:1098–1099. 2 Hancock MJ, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009;89:698–704. 3 Flynn T, Fritz J, Whitman J, et al. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation. Spine. 2002;27:2835–2843. 4 Childs JD, Fritz JM, Flynn TW, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928. [DOI: 10.2522/ptj.2009.89.10.1099]

On “Physical therapists’ attitudes, knowledge, and practice…” Sack S, et al. Phys Ther. 2009;89:804-815. I commend Sack and colleagues1 for studying physical therapists’ attitudes, knowledge, and practices related to obesity. Given the current concern regarding the obesity epidemic, this research is very timely. I would like to offer a different perspective on their findings and conclusions. The authors measured, among other things, physical therapists’ attitudes toward people with obesity. Respondents rated various characteristics, each of which had a positive as well as a negative anchor. The authors presented means and standard deviations as well as proportions of negative, neutral, and positive responses to summarize ratings for each set of attributes. To their credit, the authors acknowledged that majorities of respondents indicated some nega-

tive attitudes toward people with obesity. However, their conclusion that “overall” physical therapist attitudes are neutral was based on the mean ratings. This conclusion was reflected in the discussion and was emphasized in the abstract. In my opinion, examination of the percentages of respondents with negative attitudes leads to a different interpretation. For example, the authors reported that more than 50% of the respondents tended toward attitudes that people with obesity are “noncompliant” or “weak willed,” and 40% of the respondents tended to indicate that people with obesity are “lazy” or “sloppy.” Assuming that this survey is representative, an alternative conclusion is that large segments of our profession hold negative attitudes toward people with obesity. Negative attitudes toward people with obesity may be fostered unintentionally by the way issues are framed. In surveying physical therapists’ opinions regarding causes of obesity, the authors listed 11 causal factors, all of which measure individual-level characteristics. Some causes are genetic or physiologic in nature, some are behavioral, but none touched upon community- or population-level factors. Emerging epidemiologic evidence strongly suggests that obesity rates are influenced by factors such as lack of availability and high cost of nutritious foods, easy access to and low cost of energy-dense fast food and processed food; and lack of safe and available opportunities for physical activity.2,3 These factors disproportionately affect economically disadvantaged communities where obesity rates often are highest.4 By neglecting to ask about community- and population-level factors, we ignore the social, economic, and political determinants


of obesity. It follows, then, that we tend to place blame on individuals for their obesity. Similarly, the interventions listed in Table 7 all approached the problem on an individual level, overlooking community- and population-level interventions.5 Thus, when our patients and clients are unsuccessful in their efforts to reduce obesity, it is viewed solely as an individual failure—without recognizing society’s failure to provide conditions that encourage healthy living. The causes of and solutions to obesity are multifactorial and include environmental as well as individuallevel components. By including community- and population-level items on surveys pertaining to obesity, we gain a more comprehensive understanding of the problem, and, in so doing, we may broaden physical therapists’ perspectives about obesity. Gary S. Brooks G.S. Brooks, PT, DrPH, CCS, is Academic Physical Therapy Faculty, SUNY Upstate Medical University This letter was posted as a Rapid Response on August 7, 2009, at www.ptjournal.org.

References 1 Sack S, Radler DR, Mairella KK, et al. Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese. Phys Ther. 2009;89:804–815. 2 Hill JO, Peters J. Environmental contributions to the obesity epidemic. Science. 1998;280:1371–1374. 3 Sallis JF, Glanz K. Physical activity and food environments: solutions to the obesity epidemic. Millbank Q. 2009;87:123–154. 4 Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295:1549–1555. 5 Kahn LK, Sobush K, Keener D, et al. Recommended community strategies and measurements to prevent obesity in the United States. MMWR. 2009;58(RR-7):1–29. [DOI: 10.2522/ptj.2009.89.10.1100]

October 2009

Letters to the Editor C.G. Maher, PT, PhD, is Director, The George Institute for International Health, The University of Sydney. This letter was posted as a Rapid Response on August 24, 2009, at www.ptjournal.org.

References 1 Allison SC. Letter to the editor on “A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions.” Phys Ther. 2009;89:1098–1099. 2 Hancock MJ, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009;89:698–704. 3 Flynn T, Fritz J, Whitman J, et al. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation. Spine. 2002;27:2835–2843. 4 Childs JD, Fritz JM, Flynn TW, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928. [DOI: 10.2522/ptj.2009.89.10.1099]

On “Physical therapists’ attitudes, knowledge, and practice…” Sack S, et al. Phys Ther. 2009;89:804-815. I commend Sack and colleagues1 for studying physical therapists’ attitudes, knowledge, and practices related to obesity. Given the current concern regarding the obesity epidemic, this research is very timely. I would like to offer a different perspective on their findings and conclusions. The authors measured, among other things, physical therapists’ attitudes toward people with obesity. Respondents rated various characteristics, each of which had a positive as well as a negative anchor. The authors presented means and standard deviations as well as proportions of negative, neutral, and positive responses to summarize ratings for each set of attributes. To their credit, the authors acknowledged that majorities of respondents indicated some nega-

tive attitudes toward people with obesity. However, their conclusion that “overall” physical therapist attitudes are neutral was based on the mean ratings. This conclusion was reflected in the discussion and was emphasized in the abstract. In my opinion, examination of the percentages of respondents with negative attitudes leads to a different interpretation. For example, the authors reported that more than 50% of the respondents tended toward attitudes that people with obesity are “noncompliant” or “weak willed,” and 40% of the respondents tended to indicate that people with obesity are “lazy” or “sloppy.” Assuming that this survey is representative, an alternative conclusion is that large segments of our profession hold negative attitudes toward people with obesity. Negative attitudes toward people with obesity may be fostered unintentionally by the way issues are framed. In surveying physical therapists’ opinions regarding causes of obesity, the authors listed 11 causal factors, all of which measure individual-level characteristics. Some causes are genetic or physiologic in nature, some are behavioral, but none touched upon community- or population-level factors. Emerging epidemiologic evidence strongly suggests that obesity rates are influenced by factors such as lack of availability and high cost of nutritious foods, easy access to and low cost of energy-dense fast food and processed food; and lack of safe and available opportunities for physical activity.2,3 These factors disproportionately affect economically disadvantaged communities where obesity rates often are highest.4 By neglecting to ask about community- and population-level factors, we ignore the social, economic, and political determinants


of obesity. It follows, then, that we tend to place blame on individuals for their obesity. Similarly, the interventions listed in Table 7 all approached the problem on an individual level, overlooking community- and population-level interventions.5 Thus, when our patients and clients are unsuccessful in their efforts to reduce obesity, it is viewed solely as an individual failure—without recognizing society’s failure to provide conditions that encourage healthy living. The causes of and solutions to obesity are multifactorial and include environmental as well as individuallevel components. By including community- and population-level items on surveys pertaining to obesity, we gain a more comprehensive understanding of the problem, and, in so doing, we may broaden physical therapists’ perspectives about obesity. Gary S. Brooks G.S. Brooks, PT, DrPH, CCS, is Academic Physical Therapy Faculty, SUNY Upstate Medical University This letter was posted as a Rapid Response on August 7, 2009, at www.ptjournal.org.

References 1 Sack S, Radler DR, Mairella KK, et al. Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese. Phys Ther. 2009;89:804–815. 2 Hill JO, Peters J. Environmental contributions to the obesity epidemic. Science. 1998;280:1371–1374. 3 Sallis JF, Glanz K. Physical activity and food environments: solutions to the obesity epidemic. Millbank Q. 2009;87:123–154. 4 Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295:1549–1555. 5 Kahn LK, Sobush K, Keener D, et al. Recommended community strategies and measurements to prevent obesity in the United States. MMWR. 2009;58(RR-7):1–29. [DOI: 10.2522/ptj.2009.89.10.1100]

October 2009

Corrections LeMaster JW, et al. “Effect of weight-bearing activity on foot ulcer incidence...” Phys Ther. 2008;88:1385–1398. The authors have notified the Editor in Chief regarding errors in Table 1 that had occurred during data programming. Instead of all analyses being restricted to baseline observations, they were performed on a lineby-line basis in the analysis program, and sometimes the restriction was omitted. The corrected values appear in bold and blue in the revised Table 1 (below). The article originally stated that there are no differences at baseline in any parameter. There still are no differences at baseline in any parameter. An additional error was found. The original percentages of patients reporting cardiovascular disease were incorrect. The correct values appear in the revised table. No significant differences in the proportion of patients with cardiovascular disease were found between the 2 groups. The authors regret the errors. Table 1 (Revised).

Baseline Characteristics by Groupa Characteristic

Control Group (n=38)

Intervention Group (n=41)

Demographic/behavioral Age (y), mean (SD)

64.8 (9.4)

66.3 (10.6)

Married (%)

61

68

Women (%)

53

49

Nonwhite (%)

8

7

Nonsmokers (%)

87

95

Years of education, mean (SD)

15 (2.9)

14.2 (3.0)

No health insurance (%)

0

3

Health Type 2 diabetes (%)

92

95

Years since diabetes diagnosis, mean (SD)

11.2 (8.5)

10.9 (8.3)

No. of comorbid diseases, mean (SD) Cardiovascular disease (%)

1.8 (1.2) 34

1.8 (1.2) 39

Joint pain in lower limbs (%)

71

73

Cancer (%)

21

20

Respiratory disease (chronic bronchitis or asthma) (%)

25

21

BMI (SD)

37.3 (8)

36.0 (8.2)

CESD depression score (>16 = depressed), mean (SD)

10.2 (9.2)

10.7 (8.7)

1.6 (1.9)

2.0 (2.2)

0.6 (1.5)

0.37 (1.3)

Physical activity (estimated, weighted by no. days data provided) No. of days performing exercise program during last 7 days, mean (SD) Foot-related characteristics No. of foot ulcers in past year, mean (SD) Ankle brachial blood pressure index (1.0= normal) (SD)

1.02 (0.1)

1.05 (0.1)

Adequate shoes worn (%)

50

62

Foot-related disability score (range=0–81), mean (SD)

25.7 (19)

25.3 (20)

No characteristics were significant at P

Physical Therapy- Journal of the APTA- October 2009, Volume 89, Issue 10

Physical Therapy- Journal of the APTA- June 2009, Volume 89, Issue 6

Physical Therapy- Journal of the APTA- July 2009, Volume 89, Issue 7

Physical Therapy- Journal of the APTA- August 2009, Volume 89, Issue 8

Physical Therapy- Journal of the APTA- Feburary 2009, Volume 89, Issue 2

Physical Therapy- Journal of the APTA- March 2009, Volume 89, Issue 3

Physical Therapy- Journal of the APTA- January 2009, Volume 89, Issue 1

Physical Therapy- Journal of the APTA- September 2009, Volume 89, Issue 9

Physical Therapy- Journal of the APTA- November 2009, Volume 89, Issue 11

Physical Therapy- Journal of the APTA- May 2009, Volume 89, Issue 5

Physical Therapy- Journal of the APTA- December 2009, Volume 89, Issue 12

Physical Therapy- Journal of the APTA- April 2009, Volume 89, Issue 4

Physical Therapy- Journal of the APTA, Volume 90, Issue 2 (February 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 3 (March 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 7 (July 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 1 (January 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 6 (June 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 4 (April 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 5 (May 2010)

Manual Therapy Journal - Volume 14, Supplement (October 2009)

sports medicine Volume 39 Issue 10 October 2009

Manual Therapy Journal - Volume 14, Issue 5, Pages 461-584 (October 2009)

Journal of Chiropractic Humanities: Volume 16, Issue 1, (December 2009)

Behavioral and Brain Sciences, Volume 32, Issue 5, October 2009

Journal of Neurologic Physical Therapy (March 2010, Volume 34, Issue 1)

sports medicine Volume 38 Issue 10 October 2008

sports medicine Volume 40 Issue 10 October 2010

sports medicine Volume 41 Issue 10 October 2011

Radical Philosophy Issue: 89

October journal No.10 Autumn (1979)

Physical Therapy- Journal of the APTA- October 2009, Volume 89, Issue 10

Physical Therapy- Journal of the APTA- June 2009, Volume 89, Issue 6

Physical Therapy- Journal of the APTA- July 2009, Volume 89, Issue 7

Physical Therapy- Journal of the APTA- August 2009, Volume 89, Issue 8

Physical Therapy- Journal of the APTA- Feburary 2009, Volume 89, Issue 2

Physical Therapy- Journal of the APTA- March 2009, Volume 89, Issue 3

Physical Therapy- Journal of the APTA- January 2009, Volume 89, Issue 1

Physical Therapy- Journal of the APTA- September 2009, Volume 89, Issue 9

Physical Therapy- Journal of the APTA- November 2009, Volume 89, Issue 11

Physical Therapy- Journal of the APTA- May 2009, Volume 89, Issue 5

Physical Therapy- Journal of the APTA- December 2009, Volume 89, Issue 12

Physical Therapy- Journal of the APTA- April 2009, Volume 89, Issue 4

Physical Therapy- Journal of the APTA, Volume 90, Issue 2 (February 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 3 (March 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 7 (July 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 1 (January 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 6 (June 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 4 (April 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 5 (May 2010)

Manual Therapy Journal - Volume 14, Supplement (October 2009)

sports medicine Volume 39 Issue 10 October 2009

Manual Therapy Journal - Volume 14, Issue 5, Pages 461-584 (October 2009)

Journal of Chiropractic Humanities: Volume 16, Issue 1, (December 2009)

Behavioral and Brain Sciences, Volume 32, Issue 5, October 2009

Journal of Neurologic Physical Therapy (March 2010, Volume 34, Issue 1)

sports medicine Volume 38 Issue 10 October 2008

sports medicine Volume 40 Issue 10 October 2010

sports medicine Volume 41 Issue 10 October 2011

Radical Philosophy Issue: 89

October journal No.10 Autumn (1979)

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