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

December 2009  Volume 89  Number 12 Research Reports 1275 Motor Control Exercise for Chronic Low Back Pain 1337 A...

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December 2009  Volume 89  Number 12

Research Reports 1275

Motor Control Exercise for Chronic Low Back Pain

1337

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury

1292

Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With Low Back Pain

1354

Center-of-Pressure Movement Variability in Infants

1304

Social and Community Participation of Children and Youth With Cerebral Palsy

1363

Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis

Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause

1371

Primary Care for Osteoarthritis

1315

1327

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O N

PEDIATRICS

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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 “Spinal Manipulative Therapy Has an Immediate Effect on Thermal Pain Sensitivity in People With Low Back Pain: A Randomized Controlled Trial” What problems did the researchers set out to study, and why? Spinal manipulative therapy (SMT) has been demonstrated to improve outcomes in patients with low back pain. However, the mechanisms by which SMT acts to reduce pain remain unclear. Previous research has demonstrated that SMT resulted in decreased pain perception in a group of asymptomatic individuals. It was hypothesized that this effect occurred through a reduction in temporal summation, a behavioral measure of dorsal horn cell central sensitization mediated by C-fiber afferents. The researchers in this study set out to examine the immediate effects of SMT on pain perception in a group of individuals with low back pain, as well as to examine the psychological influences on pain perception and whether the observed effect was local or regional. Who participated in this study? Thirty-six individuals currently experiencing low back pain were included in the study. The subjects were excluded if they demonstrated signs of nerve root compression or had previous back surgery. What new information does this study offer? Reduction in temporal summation was observed only in patients receiving SMT, indicating a modulation of dorsal horn excitability. This effect was observed primarily in the lumbar innervated region and was not related to psychological factors. What new information does this study offer for patients? This study provides preliminary support to a mechanism that explains the effects of SMT. This information may help clinicians decide when best to use SMT as an intervention to prevent individuals with acute low back pain from developing chronic low back pain by affecting the way their central nervous system processes pain. How did the researchers go about the study? Baseline demographic and psychological data were obtained, followed by testing of sensory perception using one protocol to determine Aδ fiber–mediated pain perception and another to determine temporal summation–mediated pain perception. Assessment of pain perception was conducted in both the upper extremity and lower extremity. Subjects were then randomly assigned to groups receiving SMT, riding a stationary bicycle, or performing spinal extension exercises. Follow-up measurements were taken. How might these results be applied to physical therapist practice? This study provides preliminary evidence in support of a centrally mediated mechanism of SMT through an alteration of central sensitization. This evidence has clinical implications as providers make decisions about when to select SMT as an intervention. This evidence supports the use of SMT as an intervention to reduce or prevent central sensitization, a key component to the development and persistence of chronic low back pain.

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

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The Bottom Line What are the limitations of the study, and what further research is needed? Only immediate effects of temporal summation were assessed, and the research design did not allow a correlation of changes in temporal summation to clinical changes in pain or outcomes. Further research is still required to expand upon this preliminary evidence supporting a centrally mediated mechanism of SMT. 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: Bialosky JE, Bishop MD, Robinson ME, Zeppieri Jr G, George SZ. Spinal Manipulative Therapy Has an Immediate Effect on Thermal Pain Sensitivity in People With Low Back Pain: A Randomized Controlled Trial. Phys Ther. 2009;89:1292–1303.

On “Gait Variability Detects Women in Early Postmenopause With Low Bone Mineral Density” What problems did the researchers set out to study, and why? Physical frailty contributes to dependency in daily tasks, prolonged disability after illness, and increased mortality. Women in early postmenopause who have decreased bone mineral density (BMD) may exhibit signs of physical frailty due to sarcopenia and osteopenia. The researchers set out to determine if women with these characteristics exhibit decreased physical performance and differences in gait variability and fall and fracture rates. Who participated in this study? Thirty-one women with low BMD and 23 women with normal BMD who were free from serious illness participated in the study. The participants were between 50 and 65 years of age and were 3 to 10 years after menopause. What new information does this study offer? The women in early postmenopause with low BMD demonstrated increased gait variability in step time and stance time compared with those with normal BMD. Women with low BMD did not demonstrate any differences in balance, strength, or gait speed compared with women with normal BMD. What new information does this study offer for patients? This research suggests that it may be possible for clinicians to identify those women in early postmenopause who have low BMD by observing changes in the variability of their walking pattern. Early detection of low BMD can help reduce the risk that these women will develop physical frailty, allow for early interventions, and improve the overall health status of this group of women. How did the researchers go about the study? The researchers took measurements of dynamic balance (timed backward tandem walk test), strength (handheld dynamometry of isometric quadriceps force production), and free gait speed. The researchers also measured variability in temporal gait characteristics and recorded falls and fractures for 1 year following the initial testing.

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The Bottom Line How might these results be applied to physical therapist practice? The research suggests that observing gait variability through such measures as step time and stance time may be more sensitive for detecting differences in women in early postmenopause with low BMD than traditional physical performance measures. Early detection of these characteristics may help identify those patients at risk for physical frailty. What are the limitations of the study, and what further research is needed? This study may have been underpowered to detect changes in balance and strength. Also, the researchers utilized the most recent scan to determine BMD, which may have been performed up to 2 years preceding the study. A scan performed at the start of the study may have been more accurate. Further research is required across a broader age range of women to better determine the point at which progression to physical frailty occurs, as well as an examination of interventions to determine which treatments may reduce this progression. 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: Palombaro KM, Hack LM, Mangione KK, Barr AE, Newton RA, Magri F, Speziale T. Gait Variability Detects Women in Early Postmenopause With Low Bone Mineral Density. Phys Ther. 2009;89:1315–1326.

On “A Functional Threshold for Long-Term Use of Hand and Arm Function Can Be Determined: Predictions From a Computational Model and Supporting Data From the Extremity Constraint-Induced Therapy Evaluation (EXCITE) Trial” What problems did the researchers set out to study, and why? Low spontaneous use of the upper extremity following stroke is an important predictor of quality of life and function. However, long-term change in arm use following intensive motor learning therapy is variable. Previous research has suggested that this may be related to dose of therapy and the type of motor learning that occurs. The authors of this study set out to determine if a threshold of function exists for patients undergoing rehabilitation for upper-extremity paresis. Above this threshold, spontaneous use would continue beyond therapy; below this threshold, spontaneous use would decrease. Who participated in this study? This study was a secondary analysis of data from 169 subjects who completed the Extremity Constraint-Induced Therapy Evaluation (EXCITE) trial. What new information does this study offer? The computer models presented in this study confirm the existence of a threshold for arm use following therapy. Immediate assessment of spontaneous arm use after therapy is a rough predictor of long-term arm use.

December 2009



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The Bottom Line What new information does this study offer for patients? This study helps clinicians and researchers understand the nonlinear relationship between dose of therapy and arm use after therapy for people with upper-extremity paresis following stroke. An improved understanding of this relationship can help guide interventions to ensure that improvement of arm use continues beyond therapy, specifically related to the dose of the intervention. How did the researchers go about the study? The researchers entered data from the EXCITE trial into new computer simulation models. In the EXCITE trial, participants received constraint-induced movement therapy (CIMT) for 2 weeks and were tested both 1 week and 1 year following therapy. The computer simulation models had the ability to demonstrate that arm use following therapy was dependent on a performance threshold. How might these results be applied to physical therapist practice? This research helps provide information that can enable clinicians to better determine a stopping point for physical therapy. If function at this point is above a threshold, then improvement in arm performance will continue beyond therapy. What are the limitations of the study, and what further research is needed? Future research is needed to determine how clinicians can detect when individuals reach a performance threshold and therapy can be stopped. Limitations of this study included a low predictive value for the computer simulation models and a limited clinical practicality of some of the measured used in the analysis. 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: Schweighofer N, Han CE, Wolf SL, Arbib MA, Winstein CJ. A Functional Threshold for Long-Term Use of Hand and Arm Function Can Be Determined: Predictions From a Computational Model and Supporting Data From the Extremity Constraint- Induced Therapy Evaluation (EXCITE) Trial. Phys Ther. 2009;89:1327–1336.

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Physical Therapy Journal of the American Physical Therapy Association

Editorial Office Managing Editor / Associate Director of Publications: Jan P. Reynolds, [email protected] PTJ Online Editor / Assistant Managing Editor: Steven Glaros Associate Editor: Stephen Brooks, ELS Production Manager: Liz Haberkorn Manuscripts Coordinator: Karen Darley Permissions / Reprint Coordinator: Michele Tillson Advertising Manager: Julie Hilgenberg 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

Editor in Chief

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

Deputy Editor in Chief

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

Committee on Health Policy and Ethics

Linda Resnik, PT, PhD, OCS (Chair), Providence, RI; Janet Freburger, PT, PhD, Chapel Hill, NC; Alan Jette, PT, PhD, FAPTA, Boston, MA; Michael Johnson, PT, PhD, OCS, Philadelphia, PA; Justin Moore, PT, DPT, Alexandria, VA; Ruth Purtilo, PT, PhD, FAPTA, Boston, MA

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

1264 ■ Physical Therapy Volume 89 Number 12

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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)— $90; 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.

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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.

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December 2009

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

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11/10/09 10:49 AM


Invited Commentary The Lower Extremity Assessment Project (LEAP) was a prospective, 8-center observational outcome study of 601 patients with highenergy, limb-threatening lower-leg (below the femur) injuries that evaluated the outcome of amputation versus reconstruction. It was conducted between 1994 and 1997. The investigation by Archer et al1 is a secondary analysis of the data from the reconstruction subgroup data (395 individuals) to determine whether therapists’ and surgeons’ recommendations for the need for physical therapy at 3, 6, and 12 months after injury differed from each other or by center. They used regression analysis to determine factors that may explain similarities and differences. There were wide variations among trauma centers for recommendation for physical therapy at all time periods for both surgeons and physical therapists. In general, the recommendations for physical therapy were similar between surgeons and physical therapists 3 months after injury and higher for physical therapists 6 and 12 months after injury. Knee flexion range of motion (⬍135°, ⱖ135°), unilateral balance (able to perform the task, unable to perform the task), and work self-efficacy were factors in physical therapists’ and surgeons’ decisions. Pain was a factor for physical therapists (moderate to severe, mild, none) and injury severity and weight-bearing status (full, not full) were factors for surgeons. Work status (working, not working) was not a factor for surgeons or physical therapists at any time pe-

December 2009

Lynn Snyder-Mackler

riod. The authors were surprised by this finding. As previously reported by Bosse et al,2 the level of disability in their study was very high (mean Sickness Impact Profile scores of 14.5 at 12 months and 12.0 at 24 months), with more than 42% of the patients scoring greater than 10 on the Sickness Impact Profile at 24 months, indicating severe disability. Only half of the patients in the reconstruction subgroup (49.4%) had returned to work by 24 months.2 The 3-, 6-, and 12-month data were not presented, and I was unable to find the data in any of the other LEAP study group reports. We can assume, however, that almost none of the individuals were working 3 months after injury and that few individuals were working 6 months after injury. Because work status was presumably the same for the entire sample at those periods, there may have been no expectation of a differential effect by work status. But, I must infer, and given the amount of data available, I should not have to. Archer and colleagues’ previous publication on gait symmetry in this group3 included frequency counts for the analyzed factors 24 months after injury. These data gave the reader information to aid in the interpretation of the regression analyses in the previous article. Making inferences about the importance of each factor used and each factor not used in decision making by physical therapists and surgeons is very difficult absent descriptive data. Two years after injury, 25% of the cohort had moderate to severe pain, 64% had impaired unilateral

balance, and 23% had impaired knee flexion.3 Across a number of the LEAP studies, some data can be located, but not the precise information used in this study. I invite the authors to provide these data and discuss the meaningfulness of the identified factors in light of the frequency of occurrence at each follow-up period in their response. Secondary analyses can shed light on many questions that often are only apparent in retrospect or that arise as new information becomes available. It is incumbent on the investigators, however, to ensure that the readers have enough information in each report to fully appreciate the results and judge their applicability to their practices. I look forward to other interesting questions and answers from Archer and colleagues. L. Snyder-Mackler, PT, ScD, FAPTA, is Alumni Distinguished Professor, Department of Physical Therapy, University of Delaware, 301 McKinly Lab, Newark, DE 19716. Address all correspondence to Dr SnyderMackler at: [email protected]. DOI: 10.2522/ptj.20080200.ic2

References 1 Archer KR, MacKenzie EJ, Castillo RC, et al; for the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Phys Ther. 2009;89:1337–1353. 2 Bosse MJ, MacKenzie EJ, Kellam JF, et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N Engl J Med. 2002;347:1924 –1931. 3 Archer KR, Castillo RC, MacKenzie EJ, Bosse MJ. Gait symmetry and walking speed analysis following lower-extremity trauma. Phys Ther. 2006;86:1630 –1640.

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Author Response

Kristin R. Archer, Ellen J MacKenzie, Renan C. Castillo, Michael J. Bosse

We appreciate Snyder-Mackler’s comments regarding the need for descriptive data in her commentary1 on our article2 that examined variability in surgeon and physical therapist assessments of the need for physical therapy in patients with traumatic lower-extremity injuries. We agree that investigators should provide readers with enough information to fully appreciate a study’s findings and judge applicability to clinical practice. Therefore, we have provided readers with descriptive data on the injury, occupational, and clinical variables included in the 3-, 6-, and 12-month follow-up analyses (Table). Snyder-Mackler assumed that no individuals were working at 3

months and few were working at 6 months. However, 7% were working at 3 months, and 19% and 30% were working at 6 and 12 months after hospitalization, respectively. Overall, there was sufficient variability to determine the independent contribution of work status to surgeon and physical therapist clinical decision making. We acknowledge that the nonsignificant association between work status and assessment of need for physical therapy may not be overly surprising at the 3-month follow-up period due to a greater focus on impairments and physical deficits during the immediate recovery period.

Table. Injury, Occupational, and Clinical Characteristics of Study Sample by Follow-up 3-Month Follow-up (nⴝ335) n (%)

Factor

6-Month Follow-up (nⴝ342) n (%)

12-Month Follow-up (nⴝ338) n (%)

Fracture healing Yes (reference) No

However, the nonsignificant work status findings at 6 months and especially at 12 months highlight the need for increased understanding of clinician management of return-towork issues. If surgeons are not referring patients to physical therapists to facilitate return to employment, it appears important to determine to whom they are referring patients, especially as a 2007 survey3 determined that physical medicine and rehabilitation physicians may be underutilized by orthopedic trauma surgeons. Bosse et al4 found that only 49.4% of patients with highenergy, lower-extremity trauma treated by reconstruction had returned to work within 2 years. In light of this finding and our results, we recommend future research to investigate patient need and unmet need for vocational services, to examine specific reasons for unmet need within this patient population, and to determine surgeon referral practices for management of occupational concerns and limitations.

94 (28%)

170 (50%)

265 (78%)

241 (72%)

172 (50%)

73 (22%)

24 (7%)

65 (19%)

102 (30%)

References

311 (93%)

277 (81%)

236 (70%)

1 Snyder-Mackler L. Invited Commentary on “Orthopedic Surgeons and Physical Therapists Differ in Assessment of Need for Physical Therapy After Traumatic LowerExtremity Injury.” Phys Ther. 2009;89: e9. 2 Archer KR, MacKenzie EJ, Castillo RC, et al; for the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Phys Ther. 2009;89:1337–1349. 3 Archer KR, MacKenzie EJ, Bosse MJ, et al. Factors associated with surgeon referral for physical therapy in patients with traumatic lower-extremity injury: results of a national survey of orthopedic trauma surgeons. Phys Ther. 2009;89:893–905. 4 Bosse MJ, MacKenzie EJ, Kellam JF, et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N Engl J Med. 2002;347:1924 –1931.

DOI: 10.2522/ptj.20080200.ar2

Work status Yes (reference) No Pain None (reference)

53 (16%)

63 (18%)

52 (15%)

Mild

181 (54%)

182 (53%)

189 (56%)

Moderate/severe

101 (30%)

97 (29%)

97 (29%)

Weight bearing Full (reference)

64 (19%)

203 (59%)

284 (84%)

271 (81%)

139 (41%)

54 (16%)

0 (0%)

153 (45%)

239 (71%)

335 (100%)

189 (55%)

99 (29%)

ⱖ135° (reference)

160 (48%)

198 (58%)

238 (70%)

⬍135°

175 (52%)

144 (42%)

100 (30%)

Not full a

Balance

Able (reference) Unable Knee flexion range of motion

a

Balance was not included in the 3-month analysis of orthopedic surgeon and physical therapist assessments of need for physical therapy.

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Editorial CARE V Series: Integrating Patient Viewpoints Into Health Care Practice and Research

D

ata now demonstrate that patients and providers view outcomes of care differently.1 Patients tend to view outcomes in a broad and socially relevant context,2–4 whereas providers tend to view outcomes from a biomedical perspective. There is a growing recognition of patients as active members of the health care team and, in some countries, as integral members of clinical research study groups. This recognition has led to a shift in priorities in clinical practice and research.5 In April 2008, the CARE V Conference was held in Oslo, Norway, to foster international collaboration and provide a forum for key stakeholders, patients, and researchers in the field of rheumatology who are interested in advancing nonpharmacologic care. This 3-day conference built on the work of pioneers in arthritis research and care—on the collaborations that began in 2002 at the first CARE conference.6 In 2008, the fifth conference addressed key areas in nonpharmacologic arthritis care and included the identification of patient-oriented core outcomes, measurement challenges, models of care delivery, and effectiveness of interventions for arthritis. In addition, the conference included discussions that focused on ethical issues and strategies to integrate patient perspectives into care. In this issue, PTJ publishes the first in a series of papers that were presented at CARE V. In 2010, the series will explore ethical issues specific to the implementation of qualitative research and international perspectives on patient roles in health care, research, and professional education. During the conference, researchers, patients, and clinicians examined care delivery models across the continuum of care—from pre-diagnosis and factors associated with early help-seeking behaviors to models of care delivery in primary and specialty practice. The presentations integrated the consumer’s perspective, seeking to identify issues that may be associated with access to nonpharmacologic care and the use of this care. “New Models for Primary Care Are Needed for Osteoarthritis”7 addresses the current gaps in care delivery for people with osteoarthritis and discusses how the treatment of these individuals can be enhanced through the development of management pathways. Using data from the United Kingdom, Dziedzic and colleagues postulate that the largest proportion of persons treated in primary care for musculoskeletal complaints are older adults with osteoarthritis. Even though the evidence exists to support the use of simple, easily accessible interventions to manage these patients, in practice patients are not receiving this care.8 The application of the medical model to primary care practice emphasizes the pathophysiology of the condition and leads to recommendations for surgery over nonpharmacologic approaches.

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

Integrated models such as the Chronic Care Model (CCM),9 a generic model for chronic diseases developed by individuals at the MacColl Institute for Healthcare Innovation and later refined by experts at the Robert Wood Johnson Foundation, delineate components of the health care system—such as community resources, self-management support, health care delivery system design, and clinical information system function-


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Editorial ality—that promote excellence in chronic disease management. The CCM emphasizes the role of informed patients who are active participants in their care.10 Building on the concepts established in the CCM, Dziedzic et al7 note that the first approach to improve the primary care of patients with osteoarthritis is the integration of and continued support for self-management strategies. Encouraging use of self-management strategies is particularly important for patients with mild osteoarthritis, as these patients are generally overlooked. Although there is strong evidence that self-management improves health outcomes of people with arthritis,11,12 the use of self-management strategies in primary care is limited. The authors explore the reasons for this lack of implementation and provide suggestions for changing clinical practice. Moe and colleagues13 describe the evidence for nonpharmacologic interventions for hand osteoarthritis, a highly prevalent condition. Although numerous professional societies advocate the use of exercise and nonpharmacologic interventions to manage osteoarthritis, the recommendations lack specificity, particularly for hand osteoarthritis. These authors searched the literature and evaluated the outcomes of 4 systematic reviews of studies examining nonpharmacologic interventions for hand osteoarthritis using the Measurement Tool to Assess Systematic Reviews (AMSTAR).14 They conclude that there is some evidence for topical capsaicin and for splints to relieve pain and that exercise combined with patient education improves function compared with education alone.13 Based on their systematic review of the evidence, they emphasize the need for further research in hand osteoarthritis. This paper raises some important questions. First, how valid are the results of umbrella reviews? To answer this question, we have to recognize the methodological strategies and issues inherent in this type of review—and this is a topic of considerable debate. Some scholars argue that there is a potential for selection bias, basing their argument on the premise that the process used to select randomized controlled trials for the primary reviews might lead to an oversight of seminal papers, which then are lost in the umbrella review. Others contend that the methodologic rigor used in evaluating the quality of the systematic reviews14 counters the selection bias argument. That said, the systematic review by Moe et al challenges us to examine the outcomes of hand splints, a commonly prescribed modality for hand osteoarthritis, in a more comprehensive and vigorous manner. In addition, this paper highlights the paucity of information on the frequency, mode, duration, and intensity of hand exercises. Future research should focus on the most effective dose of exercise for hand osteoarthritis, using a rigorous study to assess dose-response. This information may help to better inform patients and providers about what exercises are effective. In January, Grotle and colleagues15 examine how team care is provided for patients with osteoarthritis following knee and hip arthroplasty and the impact of care delivery on health outcomes. Specifically, 183 Norwegian patients with osteoarthritis were followed prospectively for 6 months to determine the impact of the delivery of care on pain and function. The framework for this study is built on Donabedian’s model of health care delivery, which assesses health care quality based on structures, processes, and outcomes.16 The intent is to provide a rich description of the process and key players in care delivery for these patients. At first glance, the reader might be compelled to argue that care in Norway is inherently different from care in the United States and, therefore, that US physical therapists might not see value in the work. It’s true that processes and inputs in care deliv-

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Editorial ery differ from country to country—but this fact does not negate the relative value of using this approach to examine outcomes of care delivery. As economic and other environmental influences such as workforce shortages continue to impact health care, we will need to look beyond our own practice venues to examine new approaches to care. Other papers in the CARE V series will address new ethical frameworks for nonpharmacologic care, present data regarding education of health care professionals to enhance patient outcomes, and review the current state of evidence for interventions designed to manage arthritis. These issues, particularly the emphasis on integrating patients’ perspectives in arthritis care, will be explored further at the CARE VI Conference in Nancy, France, in April 2010. For further information, or to participate in the conference, contact Dr Francis Guillemin, the Local Organizer of CARE VI, at francis.guillemin@medecine. uhp-nancy.fr, or visit http://www.rheumacare.org. Maura D. Iversen, PT, DPT, SD, MPH Editorial Board Member, PTJ [email protected] References 1 Hewlett SA. Patients and clinicians have different perspectives on outcomes in arthritis. J Rheumatol. 2003;30:877–879. 2 Bauernfiend B, Aringer M, Prodinger B, et al. Identification of relevant concepts of functioning in daily life in people with systemic lupus erythematosus: a patient Delphi exercise. Arthritis Rheum. 2009;61:21–28. 3 Ahlmén M, Nordenskiöld U, Archenholtz B, et al. Rheumatology outcomes: the patient’s perspective. A multicentre focus group interview study of Swedish rheumatoid arthritis patients. Rheumatology (Oxford). 2005;44:105–110. 4 Haywood K. Patient-reported outcome I: measuring what matters in musculoskeletal care. Musculoskeletal Care. 2006;4:187–203. 5 US Department of Health and Human Services, Food and Drug Administration. Guidance for Industry: Patient-Reported Outcomes Measures. Use in Medical Product Development to Support Labeling Claims [draft guidance]. Rockville, MD: US Department of Health and Human Services, Food and Drug Administration; 2007. Available at: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/ Guidances/ucm071975.pdf. Accessed November 9, 2009. 6 Iversen MD. CARE IV Series: state of knowledge, practice, and translation in interdisciplinary arthritis research and care. Phys Ther. 2007;87:1574–1576. 7 Dziedzic KS, Hill JC, Porcheret M, Croft PR. New models for primary care are needed for osteoarthritis. Phys Ther. 2009;89:1371–1378. 8 Porcheret M, Jordan K, Jinks C, Croft P; Primary Care Rheumatology Society. Primary care treatment of knee pain—a survey in older adults. Rheumatology (Oxford). 2007;46:1694–1700. 9 MacColl Institute and The Robert Wood Johnson Foundation. Does the chronic care model work? Available at: http://www.improvingchroniccare.org. Accessed August 25, 2009. 10 Von Korff M, Gruman J Schaefer J, et al. Collaborative management of chronic illness. Ann Intern Med. 1997;127:1097–1102. 11 Mayoux-Benhamou A, Giraudet-Raudet-Le Quintrec JS, Ravaud P et al. Influence of patient education on exercise compliance in rheumatoid arthritis: a prospective 12-month randomized controlled trial. J Rheumatol. 2008;35:216–223. 12 Iversen MD. Arthritis patient education: from the clinical encounter to a public health approach. In: Hochberg MC, Silman AJ, Smolen JS, et al, eds. Rheumatology. 4th ed. Philadelphia, PA: Mosby; 2008:371–379. 13 Moe RH, Kjeken I, Uhlig T, Hagen KB. There is inadequate evidence to determine the effectiveness of nonpharmacological and nonsurgical interventions for hand osteoarthritis: an overview of high-quality systematic reviews. Phys Ther. 2009;89:1363–1370. 14 Shea BJ, Grimshaw JM, Wells GA, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10. 15 Grotle M, Garratt AM, Klokkerud M, et al. Team rehabilitation care is effective after arthroplasty for osteoarthritis: results from a multicenter, longitudinal study assessing structure, process, and outcome. Phys Ther. 2010. In press. 16 Donabedian A. The quality of care: how can it be assessed? JAMA. 1988;260:1743–1748. [DOI: 10.2522/ptj.2009.89.12.1266]


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Research Report Motor Control Exercise for Chronic Low Back Pain: A Randomized Placebo-Controlled Trial Leonardo O.P. Costa, Christopher G. Maher, Jane Latimer, Paul W. Hodges, Robert D. Herbert, Kathryn M. Refshauge, James H. McAuley, Matthew D. Jennings

Background. The evidence that exercise intervention is effective for treatment of chronic low back pain comes from trials that are not placebo-controlled. Objective. The purpose of this study was to investigate the efficacy of motor control exercise for people with chronic low back pain.

Design. This was a randomized, placebo-controlled trial. Setting. The study was conducted in an outpatient physical therapy department in Australia.

Patients. The participants were 154 patients with chronic low back pain of more than 12 weeks’ duration.

Intervention. Twelve sessions of motor control exercise (ie, exercises designed to improve function of specific muscles of the low back region and the control of posture and movement) or placebo (ie, detuned ultrasound therapy and detuned short-wave therapy) were conducted over 8 weeks. Measurements. Primary outcomes were pain intensity, activity (measured by the Patient-Specific Functional Scale), and patient’s global impression of recovery measured at 2 months. Secondary outcomes were pain; activity (measured by the Patient-Specific Functional Scale); patient’s global impression of recovery measured at 6 and 12 months; activity limitation (measured by the Roland-Morris Disability Questionnaire) at 2, 6, and 12 months; and risk of persistent or recurrent pain at 12 months.

Results. The exercise intervention improved activity and patient’s global impression of recovery but did not clearly reduce pain at 2 months. The mean effect of exercise on activity (measured by the Patient-Specific Functional Scale) was 1.1 points (95% confidence interval [CI]⫽0.3 to 1.8), the mean effect on global impression of recovery was 1.5 points (95% CI⫽0.4 to 2.5), and the mean effect on pain was 0.9 points (95% CI⫽⫺0.01 to 1.8), all measured on 11-point scales. Secondary outcomes also favored motor control exercise.

L.O.P. Costa, PT, PhD, is Research Fellow, Musculoskeletal Division, The George Institute for International Health, PO Box M201, Missenden Rd, Sydney, New South Wales 2050, Australia. Address all correspondence to Dr Costa at: lcos3060@ gmail.com. C.G. Maher, PT, PhD, is Director, Musculoskeletal Division, The George Institute for International Health, and Professor, Sydney Medical School, The University of Sydney, Sydney, Australia. J. Latimer, PT, PhD, is Senior Research Fellow, Musculoskeletal Division, The George Institute for International Health, and Associate Professor, Sydney Medical School, The University of Sydney. P.W. Hodges, PhD, Bphty(Hons), is Professor and NHMRC Principal Research Fellow/Professorial Research Fellow, Division of Physiotherapy, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury and Health, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia. R.D. Herbert, PT, PhD, is Senior Research Fellow, Musculoskeletal Division, The George Institute for International Health, and Associate Professor, Sydney Medical School, The University of Sydney. Author information continues on next page.

Limitation. Clinicians could not be blinded to the intervention they provided. Conclusions. Motor control exercise produced short-term improvements in global impression of recovery and activity, but not pain, for people with chronic low back pain. Most of the effects observed in the short term were maintained at the 6- and 12-month follow-ups.

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Post a Rapid Response or find The Bottom Line: www.ptjournal.org Physical Therapy f

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Motor Control Exercise for Chronic Low Back Pain K.M. Refshauge, DipPhty, Grad DipManipTher, MBiomedE, PhD, is Director, Research & Innovation, and Deputy Dean, Faculty of Health Sciences, The University of Sydney, Sydney, Australia. J.H. McAuley, PhD, is Research Manager, Musculoskeletal Division, The George Institute for International Health. M.D. Jennings, PT (Hons), is Deputy Director, Physiotherapy Department, Liverpool Hospital, Sydney South West and Western Sydney Area Health Services, Sydney, Australia. [Costa LOP, Maher CG, Latimer J, et al. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Phys Ther. 2009;89:1275–1286.] © 2009 American Physical Therapy Association

L

ow back pain is a major health and socioeconomic problem and is associated with high costs in care, work absenteeism, and disability worldwide.1–3 A recent inception cohort study demonstrated that 43% of patients with acute low back pain seen in primary care settings developed chronic low back pain and that nearly a third of them did not recover within 1 year.4 Exercise is endorsed as an effective treatment for chronic low back pain in most clinical practice guidelines.1–3 However, at present, there are no placebo-controlled trials of exercise for chronic low back pain.5,6 The positive recommendations in guidelines are derived instead from trials comparing exercise with usual care,7,8 with a waiting list,9 or with no treatment.10 These trials do not control for placebo effects and potentially provide biased estimates of the effect of exercise because they do not control for changes in patient and assessor behavior caused by knowledge of treatment allocation.11,12 Motor control exercise (also known as specific stabilization exercise) was first considered as a treatment for low back pain about 13 years ago, when a group of researchers from The University of Queensland in Australia published the first article on this topic.13 Since then the number of studies on this topic,14 –16 as well as its popularity and use in clinical practice, have increased. The biological rationale for motor control exercise is fundamentally based on the idea that the stability and control of the spine are altered in people with low back pain.13 Physiological studies have demonstrated that patients with low back pain may exhibit a delayed onset of activity of the deep trunk muscles (eg, transversus abdominis, multifidus) when the stability of the spine is

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challenged in dynamic tasks.17,18 Morphologically, a lower crosssectional area19 and a larger percentage of intramuscular fat in the multifidus muscle20 were found in patients with low back pain compared with asymptomatic controls. Moreover, it was found that patients with low back pain tend to increase the spinal stiffness to compensate for the lack of stability from the deep muscles by increasing the activity of the superficial muscles.21 Finally, it was demonstrated that patients who recovered from an episode of acute low back pain are more susceptible to recurrence and chronicity if these changes were not treated with motor control exercise.22 A large number of clinical trials on this topic have been performed, and 3 systematic reviews are now available.14 –16 The most recent systematic review was confined to clinical trials of motor control exercise for patients with chronic low back pain15 and, as an advantage from the 2 previous systematic reviews,14,16 a meta-analysis approach was used. This review identified 13 randomized controlled trials and 1 quasirandomized controlled trial, all of which compared motor control exercise with other treatments (eg, spinal manipulative therapy, other exercise regimens, education, surgery) or with no treatment. Notably, no

Available With This Article at www.ptjournal.org • Data Supplement: Motor Control Training Intervention Manual • Invited Commentary by Julie M. Fritz and the Author Response • Audio Abstracts Podcast This article was published ahead of print on November 5, 2009, at www.ptjournal.org.

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Motor Control Exercise for Chronic Low Back Pain placebo-controlled trials were identified. In order to establish the efficacy of motor control exercise for chronic low back pain, we conducted the first placebo-controlled trial of this intervention.

Method Setting and Participants This randomized, placebo-controlled trial was conducted in an outpatient physical therapy department of a university teaching hospital in Sydney, Australia. Consecutive patients seeking care for chronic low back pain were screened for eligibility. To be eligible for inclusion, participants had to have nonspecific low back pain (defined as pain and discomfort) localized below the costal margin and above the inferior gluteal folds, with or without referred leg pain of at least 3 months’ duration; be currently seeking care for low back pain; be aged between 18 and 80 years; comprehend English; and expect to continue residing in the study region for the study duration. In addition, potential participants underwent a simple trunk muscle test to determine that motor control exercise treatment was indicated.23,24 Exclusion criteria were suspected or confirmed spinal pathology (eg, tumor, infection, fracture, inflammatory disease), pregnancy, nerve root compromise, previous spinal surgery, major surgery scheduled during treatment or follow-up period, and presence of any contraindication to exercise,25 ultrasound, or shortwave therapy. Randomization and Interventions The randomization sequence was computer-generated by one of the investigators who was not involved in recruitment of participants. The sequence was blocked (block sizes of 4, 6, and 8, in random order). Allocation was concealed in sequentially numbered, sealed, opaque envelopes. Eligible patients were alloDecember 2009

cated to treatment groups by the physical therapist who opened the next-numbered envelope. Participants in each group received 12 half-hour treatments over an 8-week period (2 sessions per week in the first month and 1 session per week in the second month). The placebo treatment was designed to be structurally equivalent26 to the active intervention, providing similar contact time with the physical therapist. Both interventions were provided by 3 senior physical therapists who received training from experts in motor control exercise and placebo interventions. This training included a 1-day workshop prior to the commencement of the study and 3 halfday follow-up sessions during the trial period. Random audits and regular meetings provided by the same experts were conducted during the trial to monitor delivery of interventions. No deviations from the treatment protocol were observed during the audits. The motor control exercise program was based on the treatment approach described in previous publications.7,8,27,28 At the first session, participants were comprehensively assessed by the physical therapist, who prescribed exercises that were individualized based on the participant’s presentation. The exercises were designed to improve function of specific muscles of the low back region and control of posture and movement. The motor control exercise program involved 2 stages. Each participant was progressed through the stages according to specific criteria that should be met in each stage.23 The 2 stages and their main objectives were: • Stage 1. Train coordinated activity of the trunk muscles, including independent activation of the deeper

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muscles (including transversus abdominis and multifidus) and reduce overactivity of specific superficial muscles in an individualized manner. • Stage 2. Implement precision of the desired coordination and train these skills in static tasks and incorporate them into dynamic tasks and functional positions.

Stage 1 of the exercise program involved retraining of the multifidus and transversus abdominis muscles. These exercises were supplemented with exercises for the pelvic-floor muscles, breathing control, and control of spinal posture and movement. The specific muscles that were trained depended on the initial assessment. Participants were taught how to contract these muscles independently from the superficial trunk muscles.27,29 Physical therapists used real-time ultrasound biofeedback to enhance learning of the tasks. The exercises were progressed until the patient was able to maintain isolated contractions of the target muscles for 10 repetitions of 10 seconds each while maintaining normal respiration.27 When this level of competence was achieved, patients were considered ready to progress to stage 2. Stage 2 of the exercise program involved increasing the complexity of the exercise by progressing through a range of functional tasks and exercises targeting coordination of trunk and limb movement, maintenance of optimal trunk stability, and improvement of posture and movement patterns. Participants required the ongoing support of a trained physical therapist to ensure correct performance of the exercises. The participants were instructed to perform a daily set of home exercises. These exercises were performed at the same level and in the same position as those demonstrated during the treatment session. Session 12 was a Number 12

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Motor Control Exercise for Chronic Low Back Pain discharge session in which the patient’s progress was reviewed and exercises were prescribed to be continued at home. A more comprehensive description of the motor control intervention is presented online at www.ptjournal.org. The placebo intervention consisted of 20 minutes of detuned shortwave diathermy and 5 minutes of detuned ultrasound for 12 sessions over an 8-week period. This form of placebo was used because the detuned machines do not provide a specific treatment effect, but it has been established in previous trials30 –32 that participants view this intervention as credible. To ensure the perceived credibility of the placebo intervention, physical therapists followed the usual clinical routine for the delivery of the active form of these 2 treatments (ie, by checking for contraindications, monitoring changes in symptoms, adjusting the detuned devices, and appearing to progress the treatment). Each placebo treatment session lasted 30 minutes to match the duration of active treatment sessions. A careful explanation was provided to patients to ensure they remained blinded to treatment allocation. We used the following description for the patients: “In this trial, normal physical therapy treatment and placebo physical therapy treatment will be provided. A placebo treatment is a harmless treatment delivered at less than the effective dose. We will not tell you which type of treatment you will receive, and it is unlikely that you could distinguish them.” The trial staff described the placebo intervention as “pulsed ultrasound and pulsed shortwave” and explained to patients that they probably would not feel any sensation during treatment. The active forms of these treatments delivered in pulsed mode do not produce heat; thus, previous experience with the treat1278

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ments would not unblind participants. The sham machines were identical to active machines (eg, the on and off lights illuminated, the output dial moved), except that they did not provide output. The nature of the interventions precluded blinding of the treatment provider. Outcomes and Follow-up Measurements of outcomes were obtained at baseline and at follow-up appointments 2, 6, and 12 months after randomization. Primary outcomes were nominated in the trial protocol.24 The primary outcomes were pain intensity over the previous week (measured with a 0 –10 numeric rating scale [NRS]),33 activity (measured with the 0 –10 PatientSpecific Functional Scale [PSFS]),34 and global impression of recovery (measured with the ⫺5 to ⫹5 Global Perceived Effect Scale [GPE]) at 2 months.35 Secondary outcomes were pain intensity over the previous week, activity (measured with the PSFS), patient’s global impression of recovery measured at 6 and 12 months, and activity limitation (measured with the 0 –24 Roland-Morris Disability Questionnaire [RMDQ])36 at 2, 6, and 12 months. Table 1 presents the description of each of these outcome measures. Participants reported their outcomes by telephone interview to an investigator who was blinded to the treatment allocation. Patients were asked not to discuss any aspect of their treatment with the assessor. We also measured recovery and recurrence at 12 months. Patients were considered to have recovered if they reported that they had become pain-free and this pain-free period lasted for at least 1 month.37 Recurrences could only occur in patients who had recovered. Recurrence was defined as a new episode of low back pain that persisted for more than 24 hours.37,38

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Baseline data were collected prior to randomization. The baseline data included all outcome measurements and the participant’s characteristics (age, sex, ethnicity, religion, weight, height, level of education, and employment status). In addition, we collected information about depressive symptoms (measured with the Depression Anxiety Stress Scales [DASS21])39,40 to test whether the effect of the exercise intervention on primary outcomes was influenced by the DASS-21 depression score. We chose to investigate depression as a possible effect modifier, first because depression is common in patients with low back pain41 and second because there is evidence from cohort studies that depression is associated with poor outcomes in patients with low back pain.42 Participants rated treatment credibility (measured with the 0 –24 Treatment Credibility Scale)43 after the first treatment session. They were asked about side effects at 2 months using open-ended questions.44 At 12 months, patients were asked about treatment satisfaction, measured with a 4-item scale with questions about the therapist (ie, how helpful, friendly, and understanding the physical therapist was) and about the treatment helpfulness in general. At 12 months, patients were asked “Which treatment did you receive? Real physical therapy treatment? Or a sham or pretend treatment?” to check participant blinding. Data Analysis A sample size of 154 participants was nominated in the trial protocol.24 We allowed for 15% nonadherence to treatment and 15% loss to follow-up, and assumed a correlation of .5 between baseline scores and outcomes. This sample size provides 80% power to detect an effect of exercise of 1 unit on the pain intensity scale (estimated SD⫽2.0), 1 unit on the PSFS (estimated SD⫽1.8), 1 December 2009

Motor Control Exercise for Chronic Low Back Pain Table 1. Outcome Measures Measure

Construct

Description

Activity limitation

The RMDQ is a 24-item questionnaire related to normal activities of daily living. Patients are asked to tick the items that they perceive as difficult to perform due to low back pain. Each answer is scaled either 0 (no difficulty) or 1 (difficulty), thus leaving a range of scores from 0 to 24, with a higher score indicating higher levels of activity limitation. This well-known questionnaire has proven to be reliable,58 valid,59 and responsive35 in patients with low back pain.

Patient-Specific Functional Scale (PSFS)34

Activity

In the PSFS, patients are asked to identify up to 3 important activities that they are having difficulties with or are unable to perform due to their condition (eg, low back pain). In addition, the patients are asked to rate on an 11-point scale (ranging from 0 [“unable to perform activity”] to 10 [“able to perform activity at preinjury level”]) their current level of ability associated with each activity, with a higher score indicating higher functional ability. This scale has levels of reliability, validity, and responsiveness similar to those of to the RMDQ.35,59

Pain numerical rating scale (NRS)60

Pain intensity

The pain NRS involves asking patients to rate their pain intensity levels over the previous week on an 11-point scale (ranging from 0 [“no pain”] to 10 [“pain as bad as could be”]). The number that the patient states represents his or her pain intensity score. This scale has good measurement properties.59

Global Perceived Effect Scale (GPE)61

Overall measure of change

The GPE is an 11-point scale that ranges from ⫺5 (“vastly worse”) to 0 (“no change”) to ⫹5 (“completely recovered”). For all measures of global perceived effect (at baseline and all follow-ups), participants were asked, “Compared to when this episode first started, how would you describe your back these days?” A higher score indicates greater recovery from the condition. This scale has good measurement properties.62

Roland-Morris Disability Questionnaire

(RMDQ)57

unit on the GPE (estimated SD⫽1.7), and 4 units on the RMDQ (estimated SD⫽4.9) when the alpha level is set at .05. Data were double-entered. The statistical analysis was performed on an intention-to-treat basis. The statistician was given coded data and thus was blinded to which group received the exercise intervention. The mean effects of intervention on pain intensity, activity (measured by the PSFS and RDMQ), and global impression of recovery were calculated using linear mixed models (random intercepts and fixed coefficients), which incorporated terms for treatment, time, and the treatment ⫻ time interactions. The effect of time was nonlinear, so time was dummy coded and analyzed as a categorical variable (ie, 3 dummy variables were created for the categories 2, 6, and 12 months). The coefficients of the December 2009

treatment ⫻ time interactions provided estimates of the effects of the exercise intervention. To determine whether baseline depression scores modified the effect of exercise, a secondary analysis was conducted in which a higher-level interaction term (baseline DASS-21 depression score ⫻ group ⫻ time) was added to each of the regression models.45 As very few patients recovered, according to our definition of being pain-free for 30 days during the study period, only a small subset of participants could experience a recurrence. To provide a measure relevant to all participants, we created a new outcome called “persistent or recurrent pain,” which was coded as “no” for participants who recovered and did not have a recurrent episode within 12 months and “yes” for all other participants. This outcome Volume 89

was tested in a post-hoc analysis and, therefore, was considered as secondary. We calculated confidence intervals (CIs) for the risk difference using the method described by Newcombe based on Wilson’s score method, without continuity correction.46 Mixed-models analyses were performed with Stata 9.* Other analyses were performed with SPSS version 16.0 for Windows.† Role of Funding Sources The study was funded by a Research & Development grant from The University of Sydney and the Physiotherapy Research Foundation–Australian Physiotherapy Association. The funding sources had no role in study

* StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845. † SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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Figure 1. Study flow diagram.

design, data collection, data analysis, interpretation of data, or writing of the trial report. The investigators had final responsibility in the decision to submit the report for publication. The study was prospectively registered with the Australian Clinical Trials Registry (ACTRN012605000262606), and the protocol was published.24

Results In total, 220 participants seeking care for low back pain were screened for eligibility between Oc1280

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tober 2005 and December 2007 (Fig. 1). Seventeen patients chose not to participate, and 49 patients were considered ineligible. The reasons for ineligibility were nerve root compromise (n⫽9), previous spinal surgery (n⫽8), serious spinal pathology (n⫽6), non-English speaker (n⫽6), scheduled for major treatment or surgery during the follow-up period (n⫽5), low back pain of less than 12 weeks’ duration (n⫽7), aged older than 80 years (n⫽1), contraindication to exercise (n⫽1), unable to commit to attend the treatment ses-

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sions due to distance (n⫽1), and advice from the trial therapists that the patient was not suitable for motor control exercise treatment due to comorbidities (n⫽5) (for reasons of bilateral knee replacement, substance abuse, recent epilepsy collapse, vascular claudication, or ErdheimChester disease). Results of the simple trunk muscle task indicated that motor control exercise was suitable for all tested individuals, and thus no participants were excluded based upon this criterion. Of the 154 participants who were randomly asDecember 2009

Motor Control Exercise for Chronic Low Back Pain Table 2. Baseline Characteristics Characteristic

Exercise Group (nⴝ77)

Placebo Group (nⴝ77)

Age (y), mean (SD)

54.6 (13.0)

52.8 (12.7)

Female, n (%)

45 (58)

48 (62)

Low back pain duration (wk), mean (SD) Height (m), mean (SD)

334.8 (392.3)

328.2 (395.1)

1.65 (0.09)

1.64 (0.10)

Weight (kg), mean (SD)

74.5 (17.5)

75.9 (15.3)

Smoker, n (%)

21 (27)

19 (25)

Taking analgesics, n (%)

61 (79)

58 (75)

Participating in moderate exercise, n (%)a

41 (53)

51 (66)

6 (8)

13 (17)

Work status, n (%) Working full-time Working part-time

5 (7)

3 (4)

Not working

20 (26)

12 (16)

Not seeking employment

46 (60)

49 (64)

School certificate

19 (25)

17 (22)

High school certificate

19 (25)

18 (23)

Education, n (%)

Trade certificate, diploma, or advanced diploma

9 (11)

15 (20)

Bachelor’s degree or higher

15 (19)

12 (15)

Other (lower than school certificate)

15 (20)

15 (20)

General health status, n (%) Excellent

3 (4)

8 (10)

Very good

18 (23)

12 (16)

Good

38 (49)

44 (57)

Fair

14 (18)

7 (9)

Poor

4 (5)

6 (8)

Depression Anxiety Stress Scales, mean (SD) Depressionb

11.4 (12.9)

11.2 (13.4)

Anxietyc

11.9 (11.1)

11.8 (12.2)

14.1 (11.8)

14.4 (12.5)

Stress

d

Primary outcome scores, mean (SD) Pain intensitye Global impression of recoveryf Activity (Patient-Specific Functional Scale)g

6.8 (2.1)

6.6 (2.0)

⫺1.9 (2.5)

⫺2.1 (2.4)

3.3 (1.7)

3.3 (1.8)

13.1 (5.0)

13.4 (4.9)

Secondary outcome scores, mean (SD) Activity limitation (Roland-Morris Disability Questionnaire)h a

Moderate exercise was any type of exercise of moderate intensity with a duration greater than 30 minutes at least 3 times per week. Scores range from 0 (“no depression”) to 42 (“high depression”). Scores range from 0 (“no anxiety”) to 42 (“high anxiety”). d Scores range from 0 (“no stress”) to 42 (“high stress”). e Scores range from 0 (“no pain”) to 10 (“worst pain possible”). f Scores range from ⫺5 (“vastly worse”) to 5 (“completely recovered), with 0 being “unchanged.” g Scores range from 0 (“cannot perform activity”) to 10 (“can perform activity at preinjury level”). h Scores range from 0 (“no disability”) to 24 (“high disability”). b c

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Motor Control Exercise for Chronic Low Back Pain Table 3. Credibility and Treatment Evaluation Comparisons Characteristic

Exercise Group (nⴝ77)

Placebo Group (nⴝ77)

5 (2)

4 (2)

Median credibility scale (IQRa) How confident do you feel that this treatment can help relieve your pain?b How confident do you feel that this treatment will help you manage your pain?

b

5 (2)

4 (3)

How confident would you be in recommending this treatment to a friend who suffered from similar complaints?b

5 (2)

4 (3)

How logical does this treatment seem to you?c

5 (2)

4 (3)

5 (2)

5 (2)

6 (1)

6 (1)

6 (0)

6 (0)

4 (2)

4 (3)

Median treatment evaluation (IQR) Therapist helpfulnessd Therapist understanding

e

Therapist friendlinessf Treatment helpfulness

d

a

IQR⫽interquartile range. b Scores range from 0 (“not at all confident”) to 6 (“absolutely confident”). c Scores range from 0 (“not at all logical”) to 6 (“very logical”). d Scores range from 0 (“not at all helpful”) to 6 (“extremely helpful”). e Scores range from 0 (“not at all understanding”) to 6 (“extremely understanding”). f Scores range from 0 (“not at all friendly”) to 6 (“extremely friendly”).

signed to groups, 152 attended the 2-month follow-up (98.7%) and 145 attended both 6- and 12-month follow-ups (94.2%). No differences were detected between the participants who were lost to follow-up and the patients who were followed up. The characteristics of the participants in the 2 groups were similar at baseline (Tab. 2). Out of 12 planned treatment sessions, the participants in the exercise group attended a mean of 8.8 sessions (SD⫽3.5) compared with 9.6 sessions (SD⫽3.0) for patients allocated to the placebo group. Most of the participants believed that they were allocated to a “real or active” intervention (85% of patients from the exercise group versus 84% of patients from the placebo group). The ratings of treatment satisfaction were similar in both groups, with the medians ranging from 4 to 6 points (on a 0 – 6 scale) (Tab. 3). Five patients (2 from the placebo group and 3 from the exercise group) reported mild adverse effects of the interventions. All adverse ef1282

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fects were temporary exacerbations of pain. None of the patients withdrew from the trial due to adverse effects. Ten patients from the exercise group and 14 patients from the placebo group reported use of cointerventions during the study period. The exercise intervention improved activity and the patient’s global impressions of recovery (Tab. 4 and Fig. 2). At 2 months, exercise improved activity by a mean of 1.1 points (95% CI⫽1.8 to 0.3) on the PSFS and improved patient’s global impression of recovery by 1.5 points (95% CI⫽2.5 to 0.4). There was not a clear effect of exercise on pain intensity at 2 months (⫺0.9 points, 95% CI⫽⫺1.8 to 0.0, P⫽.053) or 6 months (⫺0.5 points, 95% CI⫽⫺1.4 to 0.5, P⫽.335), but there was a statistically significant effect at 12 months (⫺1.0 point, 95% CI⫽⫺1.9 to ⫺0.1, P⫽.030) in favor of the exercise group. During the study period, few patients had become painfree (recovered): 22% of the patients in the exercise group and 9% in the placebo group recovered. Ten percent of the exercise group and 7% of

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the placebo group recovered but then experienced a recurrence within 12 months. Consequently, 88% of the exercise group and 98% of the placebo group were categorized at 12 months as having persistent or recurrent pain (absolute risk reduction⫽10%, 95% CI⫽1% to 19%, number needed to treat⫽10). Exercise improved activity limitation (measured by the RMDQ) at 2 months (⫺2.7 points, 95% CI⫽⫺4.4 to ⫺0.9) and 6 months (⫺2.2 points, 95% CI⫽⫺4.0 to ⫺0.5), but the differences were smaller and no longer significant at 12 months (difference⫽1.0 point, 95% CI⫽⫺2.8 to 0.8). Finally, there was no evidence that depression was a predictor of response to treatment at 2 months for pain intensity (␤⫽⫺.03, 95% CI⫽⫺0.10 to 0.04), global impression of recovery (␤⫽⫺.05, 95% CI⫽⫺0.23 to 0.13), or activity (␤⫽.10, 95% CI⫽⫺0.07 to 0.27).

Discussion This is the first randomized, placebocontrolled trial of motor control exercise for chronic low back pain. We December 2009

Motor Control Exercise for Chronic Low Back Pain Table 4. Effects of Exercise Versus Placeboa Unadjusted Mean Outcome (SD) Exercise Group

Variable

Placebo Group

Exercise Group Versus Placebo Group Adjusted Treatment Effect (95% CI)

P

⫺0.9 (⫺1.8 to 0.0)

.053

b

Pain

2 mo

4.6 (2.8)

5.6 (2.6)

6 mo

5.0 (2.9)

5.6 (2.5)

⫺0.5 (⫺1.4 to 0.5)

.335

12 mo

5.0 (2.9)

6.3 (2.3)

⫺1.0 (⫺1.9 to ⫺0.1)

.030

2 mo

1.3 (3.2)

0.0 (3.1)

1.5 (0.4 to 2.5)

.005

6 mo

1.5 (2.6)

0.3 (3.0)

1.4 (0.3 to 2.4)

.010

12 mo

1.2 (2.7)

⫺0.3 (2.9)

1.6 (0.6 to 2.6)

.003

2 mo

5.2 (2.4)

4.1 (2.3)

1.1 (0.3 to 1.8)

.004

6 mo

5.3 (2.7)

4.3 (2.6)

1.0 (0.3 to 1.8)

.007

12 mo

5.5 (2.6)

4.0 (2.6)

1.5 (0.7 to 2.2)

⬍.001

9.6 (6.5)

11.9 (5.9)

Global impression of recovery

Activity

c

d

Activity limitatione 2 mo

⫺2.7 (⫺4.4 to ⫺0.9)

.003

6 mo

10.3 (7.0)

12.2 (6.7)

⫺2.2 (⫺4.0 to ⫺0.5)

.014

12 mo

11.4 (7.8)

12.3 (6.4)

⫺1.0 (⫺2.8 to 0.8)

.271

a

Primary outcomes are highlighted. CI⫽confidence interval. Measured with a numerical rating scale, with scores ranging from 0 (“no pain”) to 10 (“worst pain possible”). c Scores ranged from ⫺5 (“vastly worse”) to 5 (“completely recovered”), with 0 being “unchanged.” d Measured with Patient-Specific Functional Scale, with participant selecting 3 activities and rating his or her ability to perform the activity on from 0 (“cannot perform activity”) to 10 (“can perform activity at preinjury level”). Summary score is the mean of the 3 activities. e Measured with Roland-Morris Disability Questionnaire, with scores ranging from 0 (“no disability”) to 24 (“high disability”). b

found evidence of a beneficial, but small, effect of motor control exercise on global impression of recovery, activity, and activity limitation (measured by the PSFS and RDMQ, respectively) at 2 months and on “persistent or recurrent pain” at 12 months, but not pain intensity at 2 and 6 months and activity limitation (measured by the RMDQ) at 12 months. Most of the effects observed at short-term follow-up were maintained 12 months after randomization. We also found that the effect of motor control exercise was not influenced by the level of depressive symptoms. Our interpretation of the trial results is that exercise produces small clinDecember 2009

ical improvements, but complete recovery is unlikely in this nonspecific population. Some patients and clinicians may not consider these effects clinically worthwhile. The effects are smaller than benchmarks for clinically important effects suggested by expert researchers in the low back pain field47,48 and in recent clinical practice guidelines.2 However, we acknowledge that consensus has not been reached on this issue among back pain researchers, and one study of patients with low back pain49 revealed an even wider range of views on how big an improvement in outcomes needs to be before it is considered worthwhile. Given this diversity of views, clinicians may need to spend some time with patients Volume 89

considering motor control exercise treatment, outlining the likely outcomes, and assisting them to decide whether they want to pursue the treatment. The mean effects of exercise treatment were smaller than has been reported in some trials5,11; however, these trials included features associated with exaggerated treatment effects, such as lack of patient blinding and absence of controlling for placebo effects. Our use of a placebocontrolled design provides control of potentially important sources of bias, so the effects of treatment that we observed are less likely to be exaggerated than the effects observed in non–placebo-controlled trials.11 The exact biological basis for the efficacy of motor control exercise in patients with low back pain is still unclear,50 but if subjects can be taught to control their trunk muscles while performing functional activities, then this may explain the improvements seen in activity, activity limitation, and global impression of recovery.19,22 There is some evidence that this training can change trunk muscle behavior during functional tasks.51,52 A range of mechanisms have been proposed to explain the effect of motor control training on pain. These mechanisms include reduced load and improved quality of movement53 as a result of improved coordination of trunk muscles. Such changes in control may be mediated by plastic changes at the motor cortex or elsewhere in the motor system.54 Our study demonstrated that motor control exercise produced a small reduction in the risk for persistent pain at 12 months. This finding is supported by earlier work22 suggesting that patients who have continuing impairment of the deep trunk muscles experience more recurrent low back pain episodes. This earlier Number 12

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Figure 2. Outcomes in the 2 treatment groups. Values shown are unadjusted means (SDs). Measurements were obtained at baseline and at 2, 6, and 12 months, but the data are slightly offset in the figure for clarity. Higher scores represent better outcomes for global impression of recovery and disability, and lower scores represent better outcomes for pain and function. PSFS⫽Patient-Specific Functional Scale, RMDQ⫽Roland-Morris Disability Questionnaire.

work22 provides a rationale for why those in the exercise group, who retrained the deep trunk muscles, experienced less resistant or recurrent pain than those in the placebo group, who had no such training. This study was performed in an outpatient physical therapy department of a public hospital, and the results of this study should be generalizable to groups of patients with similar characteristics (ie, patients with chronic low back pain for a long time, seeking care for their low back pain problems, with moderate levels of depression and not working). In terms of the intervention, we believe that the motor control exercise intervention implemented in our study was well defined (as described in the Data Supplement), and we are confident that physical therapists with ap1284

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propriate training would be able to perform this intervention similarly. Although systematic reviews of the efficacy of exercise for chronic low back pain5 have generally concluded that exercise is effective, most reviews also signal some uncertainty in their conclusions because of methodological concerns in the available trials. Our trial avoided the main methodological problems of previous trials by using a placebo control and blinding patients and assessors. In addition, the trial was prospectively registered and the trial protocol was published.24 Lastly, we took steps to ensure treatment quality by using experienced clinicians who were trained to deliver the treatments according to the protocol, and we monitored treatment delivery.

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The main limitation of our study was that the trial therapists were not blinded to the treatment allocation. We are unaware of a method to blind therapists in trials of exercise. We tried to minimize the effect of unblinding by training the trial therapists to provide a credible placebo treatment and by auditing placebo treatment sessions. We believe that these steps were effective because scores on credibility and treatment satisfaction were similar in both treatment groups. Nevertheless, we cannot exclude the possibility that the lack of therapist blinding introduced some degree of bias into our results. Another potential limitation of this study was that we were not able to monitor adherence to the home exercise program for the patients allocated to the motor control exercise intervention. December 2009

Motor Control Exercise for Chronic Low Back Pain Although it could be argued that our choice of placebo was not perfect, we believe that this choice was the best possible. We do not know of a “placebo exercise” that is both credible and inert. This problem is not unique to the study of exercise, and similar problems with developing an appropriate placebo were found in trials of complex nonpharmaceutical interventions such as spinal manipulative therapy32,55 and acupuncture.56 Our selection of sham electrotherapy as a placebo was primarily based upon the knowledge that these machines do not share the same specific components of the exercise intervention and that they have been used successfully in previous randomized controlled trials.30,32 Our study provides evidence that motor control exercise was better than placebo in patients with chronic low back pain. Most of the effects observed in the short term were maintained at 6- and 12-month follow-ups, but the magnitude of the effects was small in this population, who have aspects associated with poor outcome. Our results suggest that this intervention should be considered for patients with chronic low back pain in order to improve activity and global impression of recovery and to improve pain intensity in the long term but not the short term. Dr Costa, Dr Maher, Dr Latimer, Dr Hodges, Dr Refshauge, and Dr McAuley provided concept/idea/research design. Dr Costa, Dr Maher, Dr Latimer, Dr Hodges, Dr Herbert, and Dr McAuley provided writing. Dr Costa, Dr Maher, and Dr Hodges provided data collection. Dr Costa, Dr Maher, Dr Hodges, and Dr Herbert provided data analysis. Dr Costa, Dr Maher, Dr Latimer, Dr Refshauge, Dr McAuley, and Mr Jennings provided project management. Dr Costa, Dr Maher, Dr Latimer, and Dr Refshauge provided fund procurement. Dr Maher and Mr Jennings provided participants. Dr Maher, Dr Refshauge, Dr McAuley, and Mr Jennings provided facilities/equipment. Dr Maher, Dr McAuley, and Mr Jennings provided institu-

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tional liaisons and clerical support. Dr Maher, Dr Latimer, Dr Herbert, Dr Refshauge, and Mr Jennings provided consultation (including review of manuscript before submission). The study protocol was approved by The University of Sydney Human Research Ethics Committee. This study was funded by a Research & Development grant from The University of Sydney and by the Physiotherapy Research Foundation–Australian Physiotherapy Association. Dr Costa had his PhD supported by CAPES – Ministe´rio da Educaçaõ–Brazil and Pontifıćia Universidade Cato´lica de Minas Gerais–Brazil; Dr Maher, Dr Hodges, and Dr Herbert hold research fellowships funded by the National Health and Medical Research Council of Australia. The study was prospectively registered with the Australian Clinical Trials Registry (ACTRN012605000262606), and the protocol was published.24 This article was received July 2, 2009, and was accepted September 6, 2009. DOI: 10.2522/ptj.20090218

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8 Moseley L. Combined physiotherapy and education is efficacious for chronic low back pain. Aust J Physiother. 2002;48: 297–302. 9 Risch SV, Norvell NK, Pollock ML, et al. Lumbar strengthening in chronic lowback-pain patients: physiological and psychological benefits. Spine. 1993;18: 232–238. 10 Kuukkanen T, Ma¨lkia¨ E, Kautiainen H, et al. Effectiveness of a home exercise programme in low back pain: a randomized five-year follow-up study. Physiother Res Int. 2007;12:213–224. 11 Schulz KF, Chalmers I, Hayes RJ, et al. Empirical-evidence of bias - dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA. 1995;273:408 – 412. 12 Juni P, Altman DG, Egger M. Systematic reviews in health care: assessing the quality of controlled clinical trials. BMJ. 2001; 323:42– 46. 13 Hodges PW, Richardson CA. Inefficient muscular stabilization of the lumbar spine associated with low back pain: a motor control evaluation of transversus abdominis. Spine. 1996;21:2640 –2650, 14 Ferreira PH, Ferreira ML, Maher CG, et al. Specific stabilisation exercise for spinal and pelvic pain: a systematic review. Aust J Physiother. 2006;52:79 – 88. 15 Macedo LG, Maher CG, Latimer J, et al. Motor control exercises for persistent nonspecific low back pain: a systematic review. Phys Ther. 2009;89:9 –25. 16 Rackwitz B, de Bie R, Limm H, et al. Segmental stabilizing exercises and low back pain. What is the evidence? A systematic review of randomized controlled trials. Clin Rehabil. 2006;20:553–567. 17 Hodges PW, Richardson CA. Delayed postural contraction of transversus abdominis in low back pain associated with movement of the lower limb. J Spinal Disord. 1998;11:46 –56. 18 Hodges PW, Richardson CA. Altered trunk muscle recruitment in people with low back pain with upper limb movement at different speeds. Arch Phys Med Rehabil. 1999;80:1005–1012. 19 Hides JA, Stokes MJ, Saide M, et al. Evidence of lumbar multifidus muscle wasting ipsilateral to symptoms in patients with acute/subacute low back pain. Spine. 1994;19:165–172. 20 Alaranta H, Tallroth K, Soukka A, et al. Fatcontent of lumbar extensor muscles and low-back disability: a radiographic and clinical comparison. J Spinal Disord. 1993;6:137–140. 21 van Dieen JH, Selen LP, Cholowicki J. Trunk muscle activation in low back pain patients, an analysis of literature. J Electromyogr Kinesiol. 2003;13:333–351. 22 Hides JA, Jull GA, Richardson CA. Longterm effects of specific stabilizing exercises for first-episode low back pain. Spine. 2001;26:E243–E248.

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Motor Control Exercise for Chronic Low Back Pain 23 Ferreira PH. Effectiveness of Specific Stabilisation Exercises for Chronic Low Back Pain [PhD thesis]. Sydney, New South Wales, Australia: School of Physiotherapy, The University of Sydney; 2004. 24 Maher CG, Latimer J, Hodges PW, et al. The effect of motor control exercises versus placebo in patients with chronic low back pain. BMC Musculoskelet Disord. 2005;6:1– 8. 25 American College of Sports Medicine. ACSM’s Guidelines for Exercise Testing and Prescription. 5th ed. Baltimore, MD: Williams & Wilkins; 1995. 26 Machado LAC, Kamper SJ, Herbert RD, et al. Imperfect placebos are common in low back pain trials: a systematic review of the literature. Eur Spine J. 2008;17: 889 –904. 27 Richardson CA, Jull GA, Hodges PW, Hides J. Therapeutic Exercise for Spinal Segmental Stabilization in Low Back Pain. Edinburgh, United Kingdom: Churchill Livingstone; 1999. 28 Hodges PW, Ferreira PH, Ferreira ML. Lumbar spine: treatment of instability and disorders of movement control. In: Magee DJ, Zachazewski JE, Quillen WS, eds. Scientific Foundations and Principles of Practice in Musculoskeletal Rehabilitation: Pathology and Intervention in Musculoskeletal Rehabilitation. Philadelphia, PA: WB Saunders Co; 2009:398 – 425. 29 Twomey LT, Taylor JR, eds. Physical Therapy of the Low Back. New York, NY: Churchill Livingstone Inc; 1994. Clinics in Physical Therapy, vol 18. 30 Pengel LH, Refshauge KM, Maher CG, et al. Physiotherapist-directed exercise, advice or both for subacute low back pain: a randomized trial. Ann Intern Med. 2007; 146:787–796. 31 Ferreira ML, Ferreira PH, Latimer J, et al. Comparison of general exercise, motor control exercise and spinal manipulative therapy for chronic low back pain: a randomized trial. Pain. 2007;131:31–37. 32 Hancock MJ, Maher CG, Latimer J, et al. Assessment of diclofenac or spinal manipulative therapy, or both, in addition to recommended first-line treatment for acute low back pain: a randomised controlled trial. Lancet. 2007;370:1638 –1643. 33 Scrimshaw SV, Maher CG. Responsiveness of visual analogue and McGill pain scale measures. J Manipulative Physiol Ther. 2001;24:501–504. 34 Stratford PW, Gill C, Westaway M, et al. Assessing disability and change on individual patients: a report of a patient-specific measure. Physiother Can. 1995;47: 258 –263. 35 Pengel LHM, Refshauge KM, Maher CG. Responsiveness of pain, disability and physical impairment outcomes in patients with low back pain. Spine. 2004;29: 879 – 883.

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36 Roland M, Morris R. A study of natural history of back pain, part 1: development of a reliable and sensitive measure of disability in low back pain. Spine. 1983;8: 145–150. 37 de Vet HCW, Heymans MW, Dunn KM, et al. Episodes of low back pain: a proposal for uniform definitions to be used in research. Spine. 2002;27:2409 –2416. 38 Stanton TR, Henschke N, Maher CG, et al. After an episode of acute low back pain, recurrence is unpredictable and not as common as previously thought. Spine. 2008;33:2923–2928. 39 Henry JD, Crawford JR. The short-form version of the Depression Anxiety Stress Scales (DASS-21): construct validity and normative data in a large non-clinical sample. Br J Clin Psychol. 2005;44:227–239. 40 Haggman S, Maher CG, Refshauge KM. Screening for symptoms of depression by physical therapists managing low back pain. Phys Ther. 2004;84:1157–1166. 41 Urquhart DM, Hoving JL, Assendelft WJJ, et al. Antidepressants for non-specific low back pain. Cochrane Database Syst Rev. 2009;1:CD001703. 42 Pincus T, Burton AK, Vogel S, et al. A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain. Spine. 2002;27:E109 –E120. 43 Borkovec TD, Nau S. Credibility of analogue therapy rationales. J Behav Ther Exp Psych. 1972;3:257–260. 44 Bent S, Padula A, Avins AL. Better ways to question patients about adverse medical events: a randomized, controlled trial. Ann Intern Med. 2006;144:257–261. 45 Pocock SJ, Assmann SE, Enos LE, et al. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Stat Med. 2002;21:2917–2930. 46 Newcombe RG. Interval estimation for the difference between independent proportions: comparison of eleven methods. Stat Med. 1998;17:873– 890. 47 van Tulder M, Malmivaara A, Hayden JA, et al. Statistical significance versus clinical importance: trials on exercise therapy for chronic low back pain as example. Spine. 2007;32:1785–1790. 48 Ostelo R, Deyo RA, Stratford PW, et al. Interpreting change scores for pain and functional status in low back pain: towards international consensus regarding minimal important change. Spine. 2008; 33:90 –94. 49 Farrar JT, Portenoy RK, Berlin JA, et al. Defining the clinically important difference in pain outcome measures. Pain. 2000;88:287–294.

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50 Hodges PW. Transversus abdominis: a different view of the elephant. Br J Sports Med. 2008;42:941–944. 51 Tsao H, Hodges PW. Specific abdominal retraining alters motor coordination in people with persistent low back pain. Presented at: 11th World Congress on Pain of the International Association for the Study of Pain; August 21–26, 2005; Sydney, New South Wales, Australia. 52 Tsao H, Hodges PW. Immediate changes in feedforward postural adjustments following voluntary motor training. Exp Brain Res. 2007;181:537–546. 53 Hodges PW, Moseley GL. Pain and motor control of the lumbopelvic region: effect and possible mechanisms. J Electromyogr Kinesiol. 2003;13:361–370. 54 Tsao H, Galea M, Hodges PW. Skilled motor training induces reorganisation of the motor cortex and is associated with improved postural control in chronic low back pain. Presented at: 12th World Congress on Pain of the International Association for the Study of Pain; August 17–22, 2008; Glasgow, United Kingdom. 55 Hancock MJ, Maher CG, Latimer J, McAuley JH. Selecting an appropriate placebo trial of spinal manipulative therapy. Aust J Physiother. 2006;52:135–138. 56 Paterson C, Dieppe P. Characteristic and incidental (placebo) effects in complex interventions such as acupuncture. BMJ. 2005;330:1202–1205. 57 Roland M, Morris R. A study of natural history of back pain, part 1: development of a reliable and sensitive measure of disability in low back pain. Spine 1983;8:145–150. 58 Brouwer S, Kuijer W, Dijkstra PU, et al. Reliability and stability of the RolandMorris Disability Questionnaire: intraclass correlation and limits of agreement. Disabil Rehabil. 2004;26:162–165. 59 Costa LO, Maher CG, Latimer J, et al. Clinimetric testing of three self-report outcome measures for low back pain patients in Brazil. Which one is the best? Spine. 2008; 33:2459 –2463. 60 Turk DC, Melzack R. Handbook of Pain Assessment. New York, NY: The Guilford Press; 1992. 61 Feinstein AR. Clinimetrics. New Haven, CT: Yale University Press; 1987:91–103. 62 Kamper SJ, Maher CG, Mackay G. Global rating of change scales: a review of strengths and weaknesses and considerations for design. J Manipulative Physiol Ther. 2009;17:163–170.

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Invited Commentary Motor control exercise has become an increasingly popular approach for physical therapists in the management of low back pain (LBP). The study by Costa and colleagues1 is the latest of several clinical trials examining motor control exercise published since initial descriptions of the treatment approach approximately 15 years ago. As Costa and colleagues observe, their study is the first to compare motor control exercise with a placebo intervention. The selection of a comparison group in a randomized clinical trial examining a new treatment, such as motor control exercise, is critical to the interpretation of the study results. Previous studies that examined motor control exercise used comparison groups of subjects who received alternative treatments (eg, spinal manipulation), surgery, or other forms of exercise, or no treatment (or minimal intervention) controls.2 Costa and colleagues propose that their use of a placebo-control comparison may offer unique insights into the efficacy of motor control exercise that these previous study designs could not. It is useful to consider the verity of this assertion in light of the methods of this study. There are advantages to the use of a placebo treatment relative to other active treatment comparisons or a no-treatment control group. The primary rationale for using a placebo comparison, and the one offered by Costa and colleagues, is to facilitate blinding and to permit an examination of the efficacy, or the specific mechanism of effect, of a treatment.3 This perspective presupposes that any treatment has both specific and nonspecific effects and that these effects are distinct. Nonspecific effects include factors such as patients’ expectations and the effect of attention

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from clinicians, which are felt to confound the ability to examine treatment efficacy.4 The use of a placebo is understood to control for the nonspecific effects of a treatment by blinding both clinicians and research subjects to the knowledge of whether or not the “real” treatment is being received, thus allowing a quantification of the specific effects of the treatment being investigated.5 Despite the pervasiveness of terminology such as “placebo” and “placebo effect” in the lexicon of researchers, these terms are surprisingly problematic to define, and their applicability to research examining complex interventions such as exercise interventions is not without controversy. A typical definition of a placebo used to inform pharmacological research is “an inactive agent given to a patient as a substitute for an active agent, and where the patient is not informed whether he or she is receiving the active or inactive agent.”6 Key elements of a placebo treatment encompassed by this and other definitions indicate that a placebo should mimic the active treatment and be equally credible to research subjects, yet be inert (ie, not contain the active agent).7 Designing a placebo treatment with each of these characteristics for pharmacological treatments is facilitated by a relatively clear distinction between exactly what is, or is not, the active agent. The classic “sugar pill” can be made to wholly mimic the “real” drug and appear identical to both subjects and clinicians, yet not contain the active pharmaceutical element. Accomplishing these characteristics for treatments that involve complex interactions between subject and clinician such as exercise, manual therapy, psychotherapy, acupuncture, and so on, is much more

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complicated, leading some authors to question whether placebocontrolled trial designs are appropriate, or even possible, in the evaluation of these treatments.7–9 A particular aspect of this complexity results from the difficulty in clearly distinguishing the specific and nonspecific aspects of complex, nonpharmacological interventions. In the context of a pharmaceutical treatment, the therapeutic benefit of interaction between clinician and patient is viewed as nonspecific in the sense that it would be expected to be roughly equivalent regardless of the pharmaceutical under study and, therefore, entirely separate from the specific effects of the drug.10 For a treatment such as motor control exercise, however, the patient-clinician interaction is not entirely generic, or nonspecific; instead, aspects of this interaction are specifically related to and part of the intervention and its underlying theory. Communication with the patient, provision of feedback, reassessment of symptoms, progression of exercises, and so on, are essential elements of a motor control exercise approach11 and are recognized as central to developing an effective therapeutic environment. The procedures used by Costa and colleagues in their placebo group also sought to create a therapeutic environment by monitoring symptoms, assessing for contraindications, adjusting the detuned devices, and appearing to progress treatment. In this sense, the intervention deemed a placebo likely included elements that also could be considered specific to a motor control exercise approach. The inherent difficulty in isolating the specific and nonspecific effects of an intervention such as motor control exercise is the essence of

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Motor Control Exercise for Chronic Low Back Pain the concern about attempts to perform placebo-controlled trials for these interventions. The inclusion of elements of the active treatment in the placebo group may underestimate the actual treatment effect of the intervention, possibly leading to a false-negative result.7,8 The results of the study by Costa and colleagues were significant in favor of the motor control exercise; however, the effect sizes may underestimate the actual effect of a motor control approach relative to a truly inert placebo. Another reason cited for using placebo treatments is the assumption that this will facilitate blinding in the study design. This is clearly the case in pharmaceutical studies; however, in studies involving an intervention such as exercise, it remains impossible to blind clinicians to a subject’s treatment group allocation.3 In reality, there is little to be gained with respect to blinding by use of a placebo treatment instead of an active treatment comparison for an intervention such as exercise. Studies comparing active treatments are able to blind subjects in a manner similar to that used the study by Costa and colleagues, by assuring that subjects find all treatment options credible and are not aware of the theoretical superiority of one treatment versus another. The use of a placebo treatment or an active comparison has advantages in this regard over no treatment or minimal intervention controls that may not be viewed as equally credible by subjects. Unlike pharmaceutical studies, research involving complex, interactive interventions such as exercise cannot blind clinicians, even if the study presumes to involve a placebo control. The potential for bias related to a lack of clinician blinding results from a clinician’s differential attitudes toward, or communication with, subjects based on their group allocation.5 In a study using a pla1288

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cebo, an unblinded clinician may be even more biased against the placebo group than he or she would be if the comparison were another active treatment the clinician viewed as credible. The bias created by differential attitudes of clinicians toward treatment can be substantial.12 Unfortunately, the use of placebo treatments cannot overcome this concern for most physical therapy interventions and may even exacerbate the situation. This may be of particular concern when the same clinicians deliver both treatment arms, as was done in the study by Costa and colleagues. The appeal of a placebo control is the potential to gain insights into the efficacy of a treatment. The efficacy of motor control exercise certainly has been a topic of debate. Advocates of this exercise approach emphasize the centrality of accomplishing independent contractions of deep trunk muscles prior to performing more dynamic, functional tasks.11,13 Other authors have disputed the need to focus on the deep trunk muscles.14 The question of the efficacy of focusing rehabilitation on retraining the deep trunk muscles remains a topic of debate in need of more research evidence. Costa and colleagues state that the purpose of their study was to establish the efficacy of motor control exercise; however, they correctly acknowledge in their discussion that their study design cannot actually address the question of efficacy, even though they endeavored to perform a placebo-controlled study. The reason is primarily related to the inability to disentangle the specific from the nonspecific effects of a complex treatment such as motor control exercise and develop a placebo that can both mimic motor control exercise, yet be truly inert. The efficacy of the theory underlying motor control exercise may be more informed by randomized trials that have com-

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pared motor control exercise interventions with other exercise approaches. These studies generally have not found approaches that emphasize specifically retraining the deep trunk muscles to be superior to other exercise treatments.15–17 Despite the inability to address the question of efficacy of motor control exercise, the study by Costa and colleagues provides a high-quality randomized trial demonstrating the superiority of motor control exercise compared with an attention control intervention for patients with chronic LBP. The benefits of the motor control exercise were most evident for the outcomes of the patients’ global impression of recovery and self-reported functional limitations. These results are an important addition to the body of literature examining the effectiveness of motor control exercise. Prior studies have supported the benefit of motor control exercise compared with minimal intervention groups, but not when compared with alternative exercise or manual therapy groups.2 Viewed collectively, these studies suggest that the effectiveness of motor control exercise may be due to the fact that it is an active, exercise-based approach, as opposed to any explicit efficacy resulting from the theory of specific muscle retraining that informs the approach. More research is needed to examine the effectiveness and explore the efficacy of motor control exercise. A placebocontrolled study design may not be optimal, or perhaps even actually feasible, for addressing the efficacy question for this and most other physical therapy interventions. J.M. Fritz, PT, PhD, ATC, is Associate Professor, Department of Physical Therapy, University of Utah, Salt Lake City, Utah, and Clinical Outcomes Research Scientist, Intermountain Healthcare, Salt Lake City, Utah. Address all

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Motor Control Exercise for Chronic Low Back Pain correspondence to Dr Fritz at: julie.fritz@ hsc.utah.edu. DOI: 10.2522/ptj.20090218.ic

References 1 Costa LOP, Maher CG, Latimer J, et al. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Phys Ther. 2009;89:1275–1286. 2 Macedo LG, Maher CG, Latimer J, McAuley JH. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Phys Ther 2009;89:9 –25. 3 Vickers AJ, de Craen AJM. Why use placebos in clinical trials? A narrative review of the methodological literature. J Clin Epidemiol 2000;53:157–161. 4 Klerman GL. Scientific and ethical considerations in the use of placebo controls in clinical trials of psychopharmacology. Psychopharmaco Bull. 1986;22:25–29. 5 Schulz KF, Grimes DA. Blinding in randomised trials: hiding who got what. Lancet. 2002;359:696 –701.

Author Response We welcome the opportunity to comment on Fritz’s1 opinions and interpretations of our article2 evaluating the efficacy of motor control exercises and to respond to some of the issues she has raised. In her commentary, Fritz has made the assumption that we used the placebo design in order to examine the mechanism of effect of motor control exercise; however, this was not the aim of our study. There seems to be confusion around use of the word “efficacy,” with Fritz using the terms “efficacy” and “mechanism of effect” interchangeably. We believe that the terms have quite distinct and different meanings. We established the efficacy of motor control exercises by comparing outcomes in patients who received the exercises and those who received a placebo, which is the usual definition of treatment efficacy from an epidemiological point of view.3 The objectives of December 2009

6 Meinert CL. Clinical Trials: Design, Conduct and Analysis. Oxford, United Kingdom: Oxford University Press; 1986:298. 7 Birch S. A review and analysis of placebo treatments, placebo effects, and placebo controls in trials of medical procedures when sham is not inert. J Alt Comp Med. 2006;12:303–310. 8 Paterson C, Dieppe P. Characteristic and incidental (placebo) effects in complex interventions such as acupuncture. BMJ. 2005;330:1202–1205. 9 Boutron I, Moher D, Altman DG, et al. Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: explanation and elaboration. Ann Intern Med. 2008;148:295–309. 10 Hro ´ bjartsson A. What are the main methodological problems in the estimation of the placebo effect? J Clin Epidemiol. 2002;55:430 – 435. 11 Richardson CA, Jull G, Hodges P, Hides J. Therapeutic Exercise for Spinal Stabilization in Low Back Pain. Edinburgh, Scotland: Churchill Livingstone; 1999. 12 Di Blazi Z, Harkness E, Ernst E, et al. Influence of context effects on health outcomes: a systematic review. Lancet. 2001;357:757–762.

13 Richardson CA, Jull GA. Muscle controlpain control: What exercises would you prescribe? Man Ther. 1995;1:2–10. 14 Greiner SG, McGill SM. Quantification of lumbar stability by using 2 different abdominal activation strategies. Arch Phys Med Rehabil. 2007;88:54 – 62. 15 Critchley DJ, Radcliffe J, Noonan S, et al. Effectiveness and cost-effectiveness of three types of physiotherapy used to reduce chronic low back pain disability: a pragmatic randomized trial with economic evaluation. Spine. 2007;32: 1474 –1481. 16 Ferreira ML, Ferreira PH, Latimer J, et al. Comparison of general exercise, motor control exercise and spinal manipulative therapy for chronic low back pain: a randomized trial. Pain. 2007;131:31–37. 17 Koumantakis GA, Watson PJ, Oldham JA. Trunk muscle stabilization training plus general exercise versus general exercise only: randomized controlled trial of patients with recurrent low back pain. Phys Ther. 2005;85:209 –225.

Leonardo O.P. Costa, Christopher G. Maher, Jane Latimer, Paul W. Hodges, Robert D. Herbert, Kathryn M. Refshauge, James H. McAuley, Matthew D. Jennings

our study were nominated a priori in our published protocol,4 as well as in our trial registration (http://www. anzctr.org.au/trial_view.aspx?ID⫽ 293), so it seems mistaken to criticize our study for not pursuing other aims. We do not support Fritz’s argument that placebos can be dispensed with, given that they are difficult to incorporate into physical therapy trials. We agree that they are difficult to incorporate, but so are many aspects of trials, such as randomization, concealed allocation, blinding, and good follow-up. The key point is that it is feasible to incorporate these features into physical therapy trials, and there is evidence that trials that do not include these features provide biased estimates of treatment effects.5 We acknowledge that the design of the placebo for complex interventions such as motor control exercise Volume 89

is difficult; however, we do not agree with Fritz that placebo-controlled trials of complex interventions are inappropriate. There are many examples in the literature of successful placebos for complex interventions—such as manual therapy,6,7 acunpuncture,8 and exercise9—that cannot be ignored. This is reinforced by the fact that most of these randomized placebo-controlled trials were published in the top peerreviewed medical journals. There are some key elements to determine an ideal placebo. Ideal placebos should be indistinguishable, inert, structurally equivalent, and credible compared with the active intervention.10 Although we are unaware of any indistinguishable “exercise placebos,” we are confident that the participants allocated to the placebo arm in our trial received an inert, structurally equivalent, and credible placebo. We measured the Number 12

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Motor Control Exercise for Chronic Low Back Pain correspondence to Dr Fritz at: julie.fritz@ hsc.utah.edu. DOI: 10.2522/ptj.20090218.ic

References 1 Costa LOP, Maher CG, Latimer J, et al. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Phys Ther. 2009;89:1275–1286. 2 Macedo LG, Maher CG, Latimer J, McAuley JH. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Phys Ther 2009;89:9 –25. 3 Vickers AJ, de Craen AJM. Why use placebos in clinical trials? A narrative review of the methodological literature. J Clin Epidemiol 2000;53:157–161. 4 Klerman GL. Scientific and ethical considerations in the use of placebo controls in clinical trials of psychopharmacology. Psychopharmaco Bull. 1986;22:25–29. 5 Schulz KF, Grimes DA. Blinding in randomised trials: hiding who got what. Lancet. 2002;359:696 –701.

Author Response We welcome the opportunity to comment on Fritz’s1 opinions and interpretations of our article2 evaluating the efficacy of motor control exercises and to respond to some of the issues she has raised. In her commentary, Fritz has made the assumption that we used the placebo design in order to examine the mechanism of effect of motor control exercise; however, this was not the aim of our study. There seems to be confusion around use of the word “efficacy,” with Fritz using the terms “efficacy” and “mechanism of effect” interchangeably. We believe that the terms have quite distinct and different meanings. We established the efficacy of motor control exercises by comparing outcomes in patients who received the exercises and those who received a placebo, which is the usual definition of treatment efficacy from an epidemiological point of view.3 The objectives of December 2009

6 Meinert CL. Clinical Trials: Design, Conduct and Analysis. Oxford, United Kingdom: Oxford University Press; 1986:298. 7 Birch S. A review and analysis of placebo treatments, placebo effects, and placebo controls in trials of medical procedures when sham is not inert. J Alt Comp Med. 2006;12:303–310. 8 Paterson C, Dieppe P. Characteristic and incidental (placebo) effects in complex interventions such as acupuncture. BMJ. 2005;330:1202–1205. 9 Boutron I, Moher D, Altman DG, et al. Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: explanation and elaboration. Ann Intern Med. 2008;148:295–309. 10 Hro ´ bjartsson A. What are the main methodological problems in the estimation of the placebo effect? J Clin Epidemiol. 2002;55:430 – 435. 11 Richardson CA, Jull G, Hodges P, Hides J. Therapeutic Exercise for Spinal Stabilization in Low Back Pain. Edinburgh, Scotland: Churchill Livingstone; 1999. 12 Di Blazi Z, Harkness E, Ernst E, et al. Influence of context effects on health outcomes: a systematic review. Lancet. 2001;357:757–762.

13 Richardson CA, Jull GA. Muscle controlpain control: What exercises would you prescribe? Man Ther. 1995;1:2–10. 14 Greiner SG, McGill SM. Quantification of lumbar stability by using 2 different abdominal activation strategies. Arch Phys Med Rehabil. 2007;88:54 – 62. 15 Critchley DJ, Radcliffe J, Noonan S, et al. Effectiveness and cost-effectiveness of three types of physiotherapy used to reduce chronic low back pain disability: a pragmatic randomized trial with economic evaluation. Spine. 2007;32: 1474 –1481. 16 Ferreira ML, Ferreira PH, Latimer J, et al. Comparison of general exercise, motor control exercise and spinal manipulative therapy for chronic low back pain: a randomized trial. Pain. 2007;131:31–37. 17 Koumantakis GA, Watson PJ, Oldham JA. Trunk muscle stabilization training plus general exercise versus general exercise only: randomized controlled trial of patients with recurrent low back pain. Phys Ther. 2005;85:209 –225.

Leonardo O.P. Costa, Christopher G. Maher, Jane Latimer, Paul W. Hodges, Robert D. Herbert, Kathryn M. Refshauge, James H. McAuley, Matthew D. Jennings

our study were nominated a priori in our published protocol,4 as well as in our trial registration (http://www. anzctr.org.au/trial_view.aspx?ID⫽ 293), so it seems mistaken to criticize our study for not pursuing other aims. We do not support Fritz’s argument that placebos can be dispensed with, given that they are difficult to incorporate into physical therapy trials. We agree that they are difficult to incorporate, but so are many aspects of trials, such as randomization, concealed allocation, blinding, and good follow-up. The key point is that it is feasible to incorporate these features into physical therapy trials, and there is evidence that trials that do not include these features provide biased estimates of treatment effects.5 We acknowledge that the design of the placebo for complex interventions such as motor control exercise Volume 89

is difficult; however, we do not agree with Fritz that placebo-controlled trials of complex interventions are inappropriate. There are many examples in the literature of successful placebos for complex interventions—such as manual therapy,6,7 acunpuncture,8 and exercise9—that cannot be ignored. This is reinforced by the fact that most of these randomized placebo-controlled trials were published in the top peerreviewed medical journals. There are some key elements to determine an ideal placebo. Ideal placebos should be indistinguishable, inert, structurally equivalent, and credible compared with the active intervention.10 Although we are unaware of any indistinguishable “exercise placebos,” we are confident that the participants allocated to the placebo arm in our trial received an inert, structurally equivalent, and credible placebo. We measured the Number 12

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Motor Control Exercise for Chronic Low Back Pain credibility and blinding of patients after the first treatment session and at 12 months after randomization and observed no between-group differences for these 2 outcomes. We would like to clarify the principal reason we used a placebo in this trial. It is not, as Fritz suggests, so that we can account for any placebo effects because they are trivially small in clinical trials. When these effects have been quantified in a meta-regression of randomized, placebo-controlled trials, this component has been found to be quite small (pooled effect⫽3.2 points on a 100-point scale, 95% confidence interval⫽1.6 – 4.7).11 The main reason for the use of a placebo is to achieve participant blinding, which allows better control of bias and can have substantial effects in a trial. We also would defend our choice of placebo. The placebo was viewed as credible by patients and as inert by therapists involved in the trial.

for addressing the efficacy question for this and most other physical therapy interventions” ignores the available evidence from well-accepted principles of trial design. Our research group has shown that placebo-controlled designs are feasible when evaluating physical therapy interventions.2,7,9 This type of study design involves more work but has the benefit of providing less biased estimates of treatment effects. We are confident that this research design is the best for controlling multiple sources of bias, and, as a consequence, we believe that our estimates of effect are accurate. Our study is the first trial of motor control exercise to be prospectively registered, to have the trial protocol published, and to provide a data supplement in which the trial treatment is described in detail, enabling exact replication of the treatment. In addition, it was a randomized, large study with concealed allocation and excellent follow-up. For all of these reasons, we believe our study makes an important contribution to the question of whether motor control exercise is useful for patients with low back pain.

Although Fritz presents a rationale for why the ritual of applying inoperative shortwave and inoperative ultrasound could be considered real treatments, we find this section of the commentary unconvincing. Our understanding of the motor control literature is that none of the proponents of this treatment have proposed that the active ingredient is the ritual of the treatment. Fritz criticizes our trial for underestimating the effect of motor control exercise, but this interpretation is counter to the prevailing view in clinical epidemiology. We believe that it is more likely that earlier trials incorporated bias by a failure to use blinding, concealed allocation, or adequate follow up and so have provided exaggerated effects of exercise interventions.

Fritz also has made the assumption, like many others, that the initial phase of training is solely focused on augmented activity of deep muscles. On the basis of evidence of increased activity of more superficial trunk muscles12,13 and evidence of increased trunk stiffness—rather than “instability”—in many individuals with low back pain,14 this phase is just as much about reducing overactivity as it is about increasing activity of deep muscles.15 Ongoing and future work should aim to identify the active component of the motor control changes.

Finally, the statement “A placebocontrolled study design may not be optimal, or perhaps even feasible,

As a final note, there are several issues to consider when evaluating the treatment effect size and the compar-

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ison with other interventions. First, it is important to acknowledge that the group of patients included in this trial is known to have a poor prognosis.16 They came from a low socioeconomic region, the majority did not speak English at home, and they had long-term symptoms. Yet, despite these issues, the trial favored motor control training. Second, the trial did not involve subgrouping. Like all other large trials comparing motor control interventions with other exercise approaches, this study investigated motor control training in a generic chronic low back pain group. Patients were not selected based on presumed suitability to this approach, although they were excluded if considered to be inappropriate due to comorbidity and so forth. The jury is still out as to whether this intervention can achieve larger effect sizes for specific subgroups of patients with low back pain. This is a major focus of the current research agenda internationally. DOI: 10.2522/ptj.20090218.ar

References 1 Fritz JM. Invited commentary on “Motor Control Exercise for Chronic Low Back Pain: a Randomized Placebo-Controlled Trial.” Phys Ther. 2009;89:1287–1289. 2 Costa LOP, Maher CG, Latimer J, et al. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Phys Ther. 2009;89:1275–1286. 3 Grobbee DE, Hoes AW. Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research. Sudbury, MA: Jones and Bartlett Publishers; 2009. 4 Maher CG, Latimer J, Hodges PW, et al. The effect of motor control exercises versus placebo in patients with chronic low back pain. BMC Musculoskelet Disord. 2005;6:1– 8. 5 Schulz KF, Chalmers I, Hayes RJ, et al. Empirical-evidence of bias - dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA. 1995;273:408 – 412. 6 Hancock MJ, Maher CG, Latimer J, et al. Selecting an appropriate placebo trial of spinal manipulative therapy. Aust J Physiother. 2006;52:135–138.

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Motor Control Exercise for Chronic Low Back Pain 7 Hancock MJ, Maher CG, Latimer J, et al. Assessment of diclofenac or spinal manipulative therapy, or both, in addition to recommended first-line treatment for acute low back pain: a randomised controlled trial. Lancet. 2007;370:1638 –1643. 8 Paterson C, Dieppe P. Characteristic and incidental (placebo) effects in complex interventions such as acupuncture. BMJ. 2005;330:1202–1205. 9 Pengel LHM, Refshauge KM, Maher CG, et al. Physiotherapist-directed exercise, advice or both for subacute low back pain: a randomized trial. Ann Intern Med. 2007; 146:787–796. 10 Machado LAC, Kamper SJ, Herbert RD, et al. Imperfect placebos are common in low back pain trials: a systematic review of the literature. Eur Spine J. 2008;17: 889 –904.

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11 Kamper SJ, Machado LAC, Herbert RD, et al. Trial methodology and patient characteristics did not influence the size of placebo effects on pain. J Clin Epidemiol. 2008;61:256 –260. 12 Hodges PW, Moseley GL, Gabrielsson A, et al. Experimental muscle pain changes feedforward postural responses of the trunk muscles. Exp Brain Res. 2003;151: 262–271. 13 van Dieen JH, Selen LPJ, Cholewicki J. Trunk muscle activation in low-back pain patients, an analysis of the literature. J Electromyogr Kinesiol. 2003;13:333–351. 14 Hodges PW, van den Hoorn W, Dawson A, et al. Changes in the mechanical properties of the trunk in low back pain may be associated with recurrence. J Biomech. 2009;42:61– 66.

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15 Hodges PW, Ferreira PH, Ferreira ML. Lumbar spine: treatment of instability and disorders of movement control. In: Magee DJ, Zachazewski JE, Quillen WS, eds. Scientific Foundations and Principles of Practice in Musculoskeletal Rehabilitation: Pathology and Intervention in Musculoskeletal Rehabilitation. Philadelphia, PA: WB Saunders & Co; 2007:398 – 425. 16 Costa LCM, Maher CG, McAuley JH, et al. Prognosis for patients with chronic low back pain: inception cohort study. BMJ. 2009;339:b3829.

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Research Report Spinal Manipulative Therapy Has an Immediate Effect on Thermal Pain Sensitivity in People With Low Back Pain: A Randomized Controlled Trial Joel E. Bialosky, Mark D. Bishop, Michael E. Robinson, Giorgio Zeppieri Jr, Steven Z. George J.E. Bialosky, PT, PhD, is Clinical Assistant Professor, Department of Physical Therapy, University of Florida, PO Box 100154, Gainesville, FL 32610-0154 (USA). Address all correspondence to Dr Bialosky at: [email protected]. M.D. Bishop, PT, PhD, is Assistant Professor, Department of Physical Therapy, University of Florida. M.E. Robinson, PhD, is Professor, Department of Clinical and Health Psychology, Center for Pain Research and Behavioral Health and Brooks Center for Rehabilitation Studies, University of Florida. G. Zeppieri Jr, PT, MS, is Staff Physical Therapist, Department of Physical Therapy, Shands Rehabilitation, Gainesville, Florida. S.Z. George, PT, PhD, is Associate Professor, Department of Clinical and Health Psychology, Center for Pain Research and Behavioral Health and Brooks Center for Rehabilitation Studies, University of Florida. [Bialosky JE, Bishop MD, Robinson ME, et al. Spinal manipulative therapy has an immediate effect on thermal pain sensitivity in people with low back pain: a randomized controlled trial. Phys Ther. 2009;89:1292–1303.] © 2009 American Physical Therapy Association

Background. Current evidence suggests that spinal manipulative therapy (SMT) is effective in the treatment of people with low back pain (LBP); however, the corresponding mechanisms are unknown. Hypoalgesia is associated with SMT and is suggestive of specific mechanisms. Objective. The primary purpose of this study was to assess the immediate effects of SMT on thermal pain perception in people with LBP. A secondary purpose was to determine whether the resulting hypoalgesia was a local effect and whether psychological influences were associated with changes in pain perception.

Design. This study was a randomized controlled trial. Setting. A sample of convenience was recruited from community and outpatient clinics.

Participants. Thirty-six people (10 men, 26 women) currently experiencing LBP participated in the study. The average age of the participants was 32.39 (SD⫽12.63) years, and the average duration of LBP was 221.79 (SD⫽365.37) weeks. Intervention and Measurements. Baseline demographic and psychological measurements were obtained, followed by quantitative sensory testing to assess temporal summation and A␦ fiber–mediated pain perception. Next, participants were randomly assigned to ride a stationary bicycle, perform low back extension exercises, or receive SMT. Finally, the same quantitative sensory testing protocol was reassessed to determine the immediate effects of each intervention on thermal pain sensitivity. Results. Hypoalgesia to A␦ fiber–mediated pain perception was not observed. Group-dependent hypoalgesia of temporal summation specific to the lumbar innervated region was observed. Pair-wise comparisons indicated significant hypoalgesia in participants who received SMT, but not in those who rode a stationary bicycle or performed low back extension exercises. Psychological factors did not significantly correlate with changes in temporal summation in participants who received SMT.

Limitations. Only immediate effects of SMT were measured, so the authors are unable to comment on whether the inhibition of temporal summation is a lasting effect. Furthermore, the authors are unable to comment on the relationship between their findings and changes in clinical pain. Conclusions. Inhibition of A␦ fiber–mediated pain perception was similar for all

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groups. However, inhibition of temporal summation was observed only in participants receiving SMT, suggesting a modulation of dorsal horn excitability that was observed primarily in the lumbar innervated area.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP

I

njury will increase the neuronal excitability within the spinal cord, leading to the activation of pain fibers with less provocation and a heightened pain response.1 This occurrence, known as central sensitization, is characterized by allodynia (pain perception to a previously nonpainful stimulus) and hyperalgesia (increased magnitude of pain intensity in response to a previously painful stimulus) and is implicated in the progression of acute pain to chronic pain and in the maintenance of chronic pain.1–3 Subsequently, acute pain resulting from peripheral input may provoke neuroplastic changes within the nervous system and a subsequent shift toward a centrally maintained mechanism of pain.1,2 Evidence for a centrally maintained mechanism of pain is observed in a number of musculoskeletal conditions such as fibromyalgia,4,5 temporomandibular joint disorder,6,7 and whiplash-associated disorder.8,9 For example, compared with people who are healthy, individuals with whiplash-associated disorder and temporomandibular joint disorder may have lower pain thresholds at sites distal from the region of injury.7,9 The corresponding general hypersensitivity to pain is indicative of a central pain mechanism and suggests neuroplastic changes in pain perception. Mounting evidence also suggests chronic low back pain (LBP) is characterized by central sensitization.10 –12 For example, individuals experiencing chronic LBP may report greater pain intensity in response to a standard pressure pain stimulus applied to the thumbnail compared with individuals who are pain-free.12 Consequently, the pain associated with chronic LBP is potentially maintained by centrally mediated mechanisms, and interventions effective in the management of LBP either may prevent the progression of acute pain from a peripheral December 2009

to a centrally mediated mechanism or directly affect a central mechanism of pain. Consequently, interventions that favorably alter central sensitization may be desirable in the treatment of individuals experiencing LBP. Current evidence suggests spinal manipulative therapy (SMT) is effective in the treatment of people with LBP.13–17 Despite SMT’s clinical effectiveness, its corresponding mechanisms are undetermined. Boal and Gillette18 suggested that SMT may provide a novel counter-irritant, resulting in inhibition of neuroplastic changes associated with central sensitization at the dorsal horn of the spinal cord. Prior studies have shown immediate hypoalgesia (decreased magnitude of pain intensity in response to a standard stimulus) associated with SMT19 –23 and support such a mechanism. For example, Fernańdez-Carnero et al19 observed increased pain pressure threshold and pain-free grip in response to SMT applied to the cervical spine. Temporal summation is a specific behavioral measure of dorsal horn cell central sensitization mediated by the C fiber afferents in which a painful stimulus of unchanging magnitude provided at an interpulse interval frequency of less than 3 seconds is perceived as increasingly painful.4,24 We have previously observed inhibition of temporal summation following SMT in people who were pain-free, which was not observed following other interventions for LBP.25 Conversely, hypoalgesia to A␦ fiber–mediated pain perception was not unique to SMT.25 Collectively, these studies support a mechanism of SMT related to the alteration of neuroplastic changes associated with pain that may be specific to inhibition of temporal summation. Although these effects Volume 89

have been observed following SMT in people who were healthy, they have not been replicated in a sample of people experiencing LBP. The purpose of this study was threefold and parallel to a previous study of individuals who were healthy.25 First, we compared immediate changes in A␦ and C fiber (temporal summation)–mediated pain perception across 3 interventions (SMT, low back extension exercises, and use of a stationary bicycle) for individuals experiencing LBP. Similar to the prior study,25 we hypothesized hypoalgesia to A␦ fiber–mediated pain over time regardless of group assignment, with temporal summation inhibition greater in participants receiving SMT. Second, we wanted to determine whether hypoalgesia following SMT was a local effect (occurring in the lumbar innervated region) or a general effect (also occurring in the cervical innervated region). We hypothesized that, similar to our prior study,25 hypoalgesia to thermal stimuli would be localized to the lumbar innervated region. Third, we investigated the association between psychological factors related to pain and hypoalgesia to thermal stimuli. Psychological factors have an association with clinical LBP26 –29 and with thermal pain perception in individuals with LBP.30 We hypothesized a similar relationship would be evident in changes in thermal pain perception following

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 October 1, 2009, at www.ptjournal.org.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP SMT in participants experiencing LBP.

Method Participants A sample of convenience was recruited from the University of Florida Health Science Center community and affiliated outpatient clinics by flyer and word of mouth. Potential participants were introduced to the study method and screened for eligibility by a study representative. Individuals wanting to participate then signed an informed consent form. Inclusion criteria were being 18 to 60 years of age and currently experiencing LBP. Individuals with concomitant lower-extremity complaints were eligible for study participation. Exclusion criteria were being non– English speaking, systemic medical conditions (eg, diabetes, hypertension), current use of psychiatric medications, pregnancy, signs and symptoms indicative of nerve root compression (reflex change, myotomal weakness, or sensation change), and a history of surgery to the low back. Procedure Demographic information, psychological questionnaires, and measurements of baseline thermal pain sensitivity were collected prior to random assignment of participants to treatment groups. The interventions were each applied for 5 minutes to standardize measurement time of experimental pain testing from baseline to immediately after intervention. The examiner was not blinded to group assignment. Measures Numeric rating scales. Numeric rating scales (NRSs) were used to measure pain perception. Participants were asked to quantify the pain experienced during experimental pain testing using a numeric rating scale with anchors of 0 (“no pain at all”) and 100 (“worst pain imagin1294

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able”). The NRS is frequently used as a measure of both clinical and experimental pain and has demonstrated sound psychometric properties in previous studies.31–34

(trait) and situational (state) anxiety symptoms.46 We reported the state portion of the STAI, as this construct better matched the purposes of this study.

Psychological questionnaires. Psychological measures known to influence experimental pain35–38 and LBP26 –29 were chosen and are described below.

The Anxiety Sensitivity Index (ASI) uses a 16-item, 4-point rating scale to assess anxiety sensitivity or the perception of harm from experiencing symptoms of anxiety. The ASI is commonly used in pain studies and has demonstrated sound psychometric properties.47,48

The Fear of Pain Questionnaire–III (FPQ-III)39 is 30-item questionnaire, with individual items scored from 1 to 5 to measure fear of normally painful situations. Higher scores indicate greater pain-related fear. The FPQ has demonstrated sound psychometric properties in both experimental and clinical pain studies.37,40 The Tampa Scale of Kinesiophobia (TSK) is an 11-item questionnaire, with individual items scored from 1 to 4. The questionnaire was developed to quantify the fear of movement and of injury or reinjury for individuals currently experiencing pain. Higher TSK scores indicate greater fear of movement and of injury or reinjury due to pain. The TSK has demonstrated acceptable psychometric properties.41 The Coping Strategies Questionnaire (CSQ-R), commonly used in the assessment of pain, uses a 27-item, 7-point rating scale to measure the frequency of use for common pain coping strategies.42 Consistent with the previous study involving participants who were healthy,25 we included only the catastrophizing subscale using the currently recommended scoring system (CSQ-R).43 The validity of the catastrophizing subscale of the CSQ-R has been supported in prior studies.42– 45 The State-Trait Anxiety Inventory (STAI) is commonly used to assess anxiety. It uses a 40-item, 4-point rating scale to assess dispositional

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Assessment of thermal pain sensitivity. The same quantitative sensory testing (QST) protocol from our previous study25 also was used in this study. The QST was performed using the Medoc Neurosensory Analyzer (TSA 2001*) with handheld peltier element-based stimulator. Participants first underwent a practice session in order to familiarize themselves with the pain testing protocol. Briefly, the practice session included a continuous heat pulse delivered to the volar part of the dominant forearm starting at 35°C and increased at a rate of 0.5°C/s. Participants were instructed to indicate when the stimulus first changed from warmth to pain and the heat pulse was terminated at this point. This procedure was performed twice, with the mean of the 2 temperatures at which the participant reported pain serving as a measure of pain threshold. Participants then underwent separate protocols to measure A␦ fiber–mediated pain sensitivity and temporal summation4,24 in both the upper and lower extremities. These sites were chosen to observe the treatment response in a dermatome specific to the application site of the SMT (lower extremity) and a dermatome separate from the application site of the SMT (upper extremity). Participants were * Medoc Ltd, Ha’dekel St, Ramat Yishai, Israel 30095.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP blinded to the temperature of the thermal stimuli, as well as to whether the A␦ fiber–mediated pain sensitivity or temporal summation protocol was being applied. A␦ fiber–mediated pain sensitivity was assessed on the volar part of the nondominant forearm and the nondominant calf of each participant through the application of heat stimuli of 3 seconds’ duration. The thermode was applied with a baseline temperature of 35°C, which rose rapidly (10°C/s) to a peak of 45°, 47°, 49°, or 50°C. The sequence of testing the extremity (ie, calf and forearm) and the sequence of application of the finishing temperatures were determined randomly to prevent an order effect. Participants were asked to rate their “first” pain intensity using a 0 to 100 NRS. These ratings are believed to be mediated primarily by the A␦ fibers.4,24 The protocol was performed 2 times at each temperature at each extremity, with the average rating of each temperature analyzed. The thermode was moved slightly, and the researcher waited 60 seconds between trials in order to prevent habituation. Temporal summation was assessed on the plantar surface of the nondominant foot and the palmar surface of the nondominant hand using a train of 10 consecutive heat pulses of less than 1 second duration at an inter-stimulus frequency of 0.33 Hz. The baseline temperature of each pulse was 35°C, and temperature peaked at 51°C. Participants were asked to rate their delayed (second) pain for each of the 10 pulses using an NRS. The sequence of testing was counterbalanced to prevent an order effect. Interventions Participants were instructed, as part of the informed consent process, that they would be randomly assigned to receive 1 of 3 interventions December 2009

commonly used in the management of LBP.49 Randomization was computer generated, with group assignments maintained in sealed, opaque, sequentially numbered envelopes. The envelopes were opened in sequential order based on entry in the study and after all baseline measures were completed for the participant. We elected to not incorporate a true control group in this study because we wanted all participants to have some form of intervention for their LBP. Furthermore, changes in temporal summation did not seem biologically plausible in a true control group, but was biologically plausible from performing other activity. All interventions were performed under the supervision of research staff to ensure adherence to the described parameters. Stationary bicycle. Hypoalgesia has been reported in response to general exercise.50,51 Participants rode a stationary bicycle and served as the nonspecific activity comparison group. The treatment dosage was 5 minutes at 60 to 70 rpm and 1 KPa. Lumbar extension exercise. Participants performed a prone low back extension exercise and served as a specific activity comparison group. The exercise has been described previously in the literature for treatment of people with LBP,52,53 and several studies have demonstrated favorable outcomes in participants with LBP after performing this exercise.54 –58 Although not specific to this exercise, hypoalgesia has been reported in response to specific exercise in the cervical spine.59 The treatment dosage was 3 sets of 15 repetitions within a 5-minute period. Spinal manipulative therapy. This technique has been well described in the literature15,17 and was used in our prior studies of Volume 89

the immediate effects of SMT.25,60 Spinal manipulative therapy has been shown to be effective in the management of LBP in participants meeting a clinical prediction rule.15,17 The treatment dosage was performance of the SMT 2 times on each side of the pelvis, for a total of 4 manipulations in the 5-minute period, regardless of whether cavitation was experienced. Immediately following the assigned intervention, the previously described QST protocol was repeated. Sample Size Estimates This study, to our knowledge, was the first to use thermal pain sensitivity as an outcome measure for SMT for participants with LBP. Therefore, limited data were available for a priori sample size calculation. We set a minimum recruitment threshold of 30 participants based on observed effect sizes from the previous study of participants who were healthy.25 Data Analysis All statistical analysis was performed using SPSS for Windows version 16.0.† Significance was set at Pⱕ.05 for all analyses because we were attempting to confirm an observation made in prior studies.25,60 Descriptive statistics were generated for continuous and categorical measures. Univariate analysis of variance (ANOVA) was used to assess postrandomization differences in continuous variables of demographic, psychological, and baseline thermal testing measures. Chi-square analysis was used to assess for postrandomization differences in categorical demographic variables. Our primary outcome of interest was change in thermal pain sensitivity over time (prior to and immediately following the assigned intervention). † SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP We used separate repeated-measures ANOVAs with group assignment as the between-subject factor and preintervention and postintervention measures of A␦ fiber–mediated pain sensitivity and temporal summation as the within-subject factor to assess for group differences in pain sensitivity. We included the ratings from only the 47°C and 49°C temperatures from the A␦ fiber–mediated pain to match the parameters of our previous study. Furthermore, 45°C is not a suprathreshold stimulus for all participants, and 50°C tends to be at tolerance, causing concerns for floor and ceiling effects, respectively. We performed this analysis in both the upper and lower extremities in order to observe for local and general effects of SMT. We used pair-wise comparisons, as indicated by the repeated-measures ANOVA results, to explore specific group changes.

Results

Next, we wanted to observe for significant associations between psychological factors and changes in pain perception. Pearson correlation coefficients were calculated to observe for significant associations among psychological factors, measures of clinical pain, and changes in temporal summation.

Pain Response in Lumbar Innervated Region (Local Response) A␦ fiber–mediated pain sensitivity. The intervention groups did not differ in A␦ fiber–mediated pain sensitivity in the lower extremity to heat pulses of 47°C (P⫽.73) and 49°C (P⫽.96). Additionally, a main effect for time was not observed at 47°C (P⫽.31) or 49°C (P⫽.94), suggesting no change in A␦ fiber–mediated pain sensitivity occurred over time.

Role of the Funding Source The project was supported by grant AT002796 from the National Institutes of Health, National Center for Complementary and Alternative Medicine, awarded to Dr Bishop, Dr Robinson, and Dr George (principal investigator). Dr Bialosky also received support from grant AT002796 and from the National Institutes of Health T-32 Neural Plasticity Research Training Fellowship (T32HD043730). This work also was supported with resources from the Brain Rehabilitation Research Center, a VA Rehabilitation Research and Development Center of Excellence at the Malcom Randall VA Medical Center in Gainesville, Florida. 1296

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Thirty-six individuals met the criteria for the study and agreed to participate, and all individuals completed the study (Fig. 1). Number of excluded individuals and reasons for study exclusion were not tracked as part of this study. Group comparisons of baseline questionnaire and demographic information are presented in Table 1. Significant group differences were observed for sex and fear in baseline measures. Further exploration for covariate consideration indicated fear and sex were not significantly correlated with change in A␦ fiber–mediated pain sensitivity or temporal summation in either the upper or lower extremity (P⬎.05). Subsequently, we elected to exclude fear and sex as covariates in the subsequent analyses, as neither variable met the assumptions for covariance analysis.

Temporal summation. A significant group (randomization) ⫻ time (preintervention to postintervention) interaction was observed for pain sensitivity to the temporal summation protocol in the lower extremity (F2,33⫽3.41, P⫽.05, partial ␩2⫽0.17), suggesting changes in temporal summation differed by group assignment (Tab. 2, Fig. 2). Pair-wise comparisons indicated a significant hypoalgesic effect of temporal summation in the lower extremity of participants who received

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the SMT (mean decrease in pain perception⫽⫺8.5, SD⫽11.8; P⫽.03, Cohen d⫽0.37). Inhibition of temporal summation was not observed in those riding a stationary bicycle (mean increase in pain perception⫽3.7, SD⫽9.2; P⫽.19, Cohen d⫽0.16) or performing lumbar extension exercises (mean decrease in pain perception⫽⫺2.5, SD⫽13.1; P⫽.52, Cohen d⫽0.08). Pain Response in Cervical Innervated Region (General Response) A␦ fiber–mediated pain sensitivity. The intervention groups did not differ in A␦ fiber–mediated pain sensitivity in the upper extremity to heat pulses of 47°C (P⫽.37) and 49°C (P⫽.53). Additionally, a main treatment effect for time was not observed at 47°C (P⫽.26) or 49°C (P⫽.49), suggesting no change in A␦ fiber–mediated pain sensitivity occurred over time. Temporal summation. A significant group (randomization) ⫻ time (preintervention to postintervention) interaction (P⫽.40) was not observed in the upper extremity, indicating the lack of a group-dependent change in temporal summation. Instead, a main treatment effect for time (F1,31⫽6.78, P⫽.01, partial ␩2⫽0.18) was observed for temporal summation in the upper extremity (mean decrease in pain perception⫽ ⫺6.1, SD⫽13.5; Cohen d⫽0.22), suggesting all participants had a decrease in temporal summation. Association Between Psychological Factors and Changes in Thermal Pain Sensitivity Both pain catastrophizing (r⫽⫺.67, P⫽.02) and state anxiety (r⫽⫺.62, P⫽.04) were significantly associated with changes in A␦ fiber–mediated pain sensitivity in the lower extremity in participants who received SMT (Tab. 3). Psychological variables December 2009

Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP

Figure 1. Summary of recruitment, enrollment, randomization, allocation, follow-up, and analysis for the study.

were not correlated with the change in temporal summation in the lower extremity observed in participants who received the SMT (P⬎.05). The largest association was a small to medium association with pain catastrophizing (r⫽.32).

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Discussion Spinal manipulative therapy is hypothesized to inhibit pain at the dorsal horn of the spinal cord through the alterations of neuroplastic changes consistent with central sensitization.18 We have previously observed inhibition of temporal summation following SMT in participants

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who were healthy.25,60 We investigated the same phenomenon in the current study in participants experiencing LBP to determine the relevance of this observation in clinical populations. Similar to our prior study in participants who were healthy,25 we observed inhibition of temporal summation in participants

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP Table 1. Baseline Measures of Demographic Variables and Clinical Pain, Pain Sensitivity, and Psychological Variablesa SB

LEE

SMT

Total Sample

P

Demographic variables Sex, n Male

6

0

4

10

Female

6

12

8

26

Age (y)

34.33 (13.96)

33.25 (13.27)

29.58 (11.07)

.02

32.39 (12.63)

.64

Race, n Caucasian African American Hispanic

11

9

7

27

1

3

3

7

.20

0

0

2

2

15.17 (2.17)

13.92 (2.07)

16.18 (3.19)

16.14 (1.35)

.11

Duration of LBP (wk)

180.55 (411.92)

256.60 (358.20)

230.58 (355.30)

221.79 (365.37)

.89

Intensity of LBP (NRS)

43.0 (21.1)

48.1 (29.7)

30.1 (20.7)

40.4 (24.7)

.22

45.00 (4.02)

43.61 (1.61)

44.17 (2.58)

44.22 (2.81)

.53

31.3 (24.3)

30.1 (22.3)

14.9 (8.1)

25.7 (20.5)

.13

FPQ

73.1 (21.8)

93.9 (15.3)

85.5 (16.3)

84.9 (19.1)

.05

TSK

28.9 (10.2)

26.3 (7.4)

22.1 (5.6)

25.9 (8.3)

.14

CSQ-R

11.5 (7.1)

12.1 (6.0)

7.5 (4.5)

10.4 (6.2)

.15

STAI

32.9 (12.1)

35.1 (12.7)

31.5 (9.8)

33.2 (11.4)

.48

ASI

18.8 (10.7)

20.7 (7.7)

16.8 (8.8)

18.8 (9.0)

.76

Education (y)

Pain sensitivity Pain threshold (°C) Pain threshold rating (NRS) Psychological questionnaires

a

All findings are presented as means (standard deviation) unless otherwise indicated. SB⫽stationary bicycle; LEE⫽lumbar extension exercises; SMT⫽spinal manipulative therapy; LBP⫽low back pain; NRS⫽numeric rating scale, with anchors of 0 (“no pain at all”) and 100 (“worst pain imaginable”); FPQ⫽Fear of Pain Questionnaire; CSQ-R⫽Coping Strategies Questionnaire; TSK⫽Tampa Scale for Kinesiophobia; STAI⫽State-Trait Anxiety Inventory; ASI⫽Anxiety Sensitivity Index.

Table 2. Summary of Comparisons of Within-Group and Between-Group Changes in Temporal Summationa Pre-intervention

Post-intervention

29.6 (20.1)

33.3 (25.6)

Mean Differenceb

95% CI

Effect Size (Cohen d)

⫺10.5 to 3.0

⫺0.40

⫺4.2 to 9.3

0.19

Within-group comparisons SB

⫺3.7 (9.2)

LEE

42.9 (31.7)

40.3 (30.9)

2.5 (13.1)

SMT

28.5 (24.8)

19.9 (21.6)

8.5 (11.8)c

1.8 to 15.3

0.72

12.3 (10.5)c

0.4 to 24.1

1.20

Between-group comparisons (change scores) SMT vs SB SMT vs LEE

6.0 (12.5) ⫺6.3 (11.15)

SB vs LEE

⫺5.8 to 17.8 ⫺18.1 to 5.6

0.48 0.57

a All findings are presented as mean (standard deviation). CI⫽confidence interval, SB⫽stationary bicycle, LEE⫽lumbar extension exercises, SMT⫽spinal manipulative therapy. b Mean differences were not adjusted for covariates. c Significant at P⬍.05.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP with LBP associated with SMT that was greater than the changes observed in response to riding a stationary bicycle or performing lumbar extension exercises. Inhibition of temporal summation appeared to be a local effect, as it was observed primarily in lumbar innervated areas (lower extremity) and was not strongly correlated with psychological variables. Furthermore, this effect did not appear to be a general blunted response to the QST protocol because it was not observed in the A␦ fiber–mediated pain perception. This is the first study, to our knowledge, to observe SMT-associated alterations in temporal summation in a clinical sample. Recent rehabilitation interventions for individuals experiencing neurological impairments, such as those observed following a stroke or spinal cord injury, have attempted to influence neuroplasticity of the central nervous system to regain motor function.61– 64 For example, rather than prioritizing dysfunctions such as specific strength (force-generating capacity) and rangeof-motion deficits, some rehabilitation protocols now attempt to promote neuroplastic changes in motor control through repetitive or forced

Figure 2. Change in temporal summation in the lumbar innervated region following randomly assigned intervention. A significant group (intervention) ⫻ time (preintervention to postintervention) interaction was present for hypoalgesia to temporal summation in the lumbar innervated region (F2,33⫽3.41, P⫽.05, partial ␩2⫽0.17). Pair-wise comparison indicated significant hypoalgesia in the participants who received spinal manipulative therapy (SMT), which was not observed in the participants who rode a stationary bicycle or performed lumbar extension exercises. Positive numbers along the Y axis indicate hypoalgesia. Error bars represent one standard error of the mean. Asterisk indicates significant at Pⱕ.05. NRS⫽numeric rating scale, with anchors of 0 (“no pain at all”) and 100 (“worst pain imaginable”).

use of an involved extremity.62,64,65 Similarly, the observed inhibition of temporal summation suggests SMT may work through a neurophysiological mechanism specific to the alteration of neuroplastic changes associated with pain. Clinically, SMT frequently is applied in response to a

biomechanical dysfunction such as decreased range of motion or a hypomobile joint. For example, an evaluative process is used to localize a dysfunctional vertebral segment followed by the application of a specific SMT technique to correct the noted problem. Despite this focus,

Table 3. Associations (Pearson r) Between Change in Lumbar Innervated Thermal Pain Sensitivity and Baseline Measures of Psychological Variables, Low Back Pain Duration, and Thermal Pain Sensitivity in Participants Who Received Spinal Manipulative Therapy a Outcome Measure Fear of pain (FPQ) Pain catastrophizing (CSQ-R)

A␦ Fiber (47°C) ⫺.34 (P⫽.32) –.67 (P⫽.02)b

A␦ Fiber (49°C)

Temporal Summation

.07 (P⫽.84)

.12 (P⫽.73)

–.21 (P⫽.54)

.32 (P⫽.34)

Kinesiophobia (TSK)

–.39 (P⫽.24)

–.40 (P⫽.22)

.08 (P⫽.83)

Anxiety (STAI)

–.33 (P⫽.33)

–.62 (P⫽.04)b

.06 (P⫽.87)

Anxiety sensitivity (ASI)

–.03 (P⫽.93)

–.35 (P⫽.30)

.05 (P⫽.88)

.37 (P⫽.24)

–.43 (P⫽.16)

–.22 (P⫽.50)

Low back pain duration (wk) Pain threshold (°C)

.38 (P⫽.28)

.09 (P⫽.81)

–.13 (P⫽.72)

Pain threshold rating (NRS)

.32 (P⫽.37)

–.10 (P⫽.79)

.21 (P⫽.56)

a

FPQ⫽Fear of Pain Questionnaire; CSQ-R⫽Coping Strategies Questionnaire; TSK⫽Tampa Scale for Kinesiophobia; STAI⫽State-Trait Anxiety Inventory; ASI⫽Anxiety Sensitivity Index; NRS⫽numeric rating scale, with anchors of 0 (“no pain at all”) and 100 (“worst pain imaginable”). b Significant association at P⬍.05.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP the evaluative process for SMT generally is unreliable,66,67 and prior studies have documented a poor relationship between physical factors such as strength and range of motion and LBP-related outcomes.68 –70 Subsequently, clinical application of SMT may be better guided by the goal of decreasing pain than by the correction of a biomechanical lesion. Our findings of temporal summation inhibition specific to SMT (in comparison with riding a stationary bicycle and performing press-up exercises) suggest SMT may provide a novel stimulus effective in altering the neuroplastic changes associated with central sensitization and support current hypotheses about the counter-irritant properties of SMT.18 Consequently, our findings provide preliminary support for the clinical use of SMT as a means to inhibit neuroplastic changes (eg, central sensitization) associated with LBP. The potential specificity of SMT’s effect is corroborated by a lack of inhibition for A␦ fiber–mediated pain perception for participants with LBP. Our findings of a local effect of SMT further suggest a focused neurophysiological response. Similar to our prior study,25 we observed a localized hypoalgesic effect for SMT in participants experiencing LBP in which inhibition of temporal summation occurred in the dermatomes related to the area of SMT (leg) and not to an unrelated dermatome (upper extremity). Similarly, Dishman et al71 observed changes in lumbar motoneuron pool excitability following SMT to the low back but not the cervical spine. Collectively, these studies suggest a local effect of SMT specific to the region of application. The current findings in a clinical sample and prior observations in participants who were healthy25 suggest the neurophysiological responses associated with SMT to the low back

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are specific to the lumbar innervated regions. Our findings of hypoalgesia to C fiber–mediated pain through the assessment of temporal summation suggest a spinal cord–mediated effect of SMT. Psychological factors are known to influence both outcomes associated with LBP26 –29 and response to experimental pain.30,37,38 Subsequently, we wanted to observe the association of these factors to our outcome measure. Significant correlations between psychological factors and inhibition of temporal summation could suggest a descending, supraspinal mechanism of SMT related to fear, catastrophizing, or negative cognitions. Psychological associations with A␦ fiber–mediated pain perception were expected and parallel a previous study of thermal pain and LBP.30 However, changes in temporal summation did not significantly correlate to any of the psychological measures, and all associations were relatively small, the largest being pain catastrophizing (r⫽.32). We have not observed a significant correlation between psychological factors and SMT-related changes in temporal summation in participants who were healthy25 and now participants experiencing LBP. Collectively, these findings suggest the immediate inhibition of temporal summation related to SMT is independent of descending inhibition related to psychological factors or only minimally influenced by these factors. Limitations The current study represented our first investigation into the effects of SMT on temporal summation in a clinical sample and has several limitations. First, we made no attempt to blind the examiner to the intervention received by the individual participant. As a result, we cannot be certain that examiner bias did not play a role in our findings.

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As this study was exploratory, we incorporated a sample of convenience and obtained a sample of participants with chronic LBP with lower pain intensity ratings than those typically enrolled in clinical trials. As a result, our findings may not be applicable to individuals with acute LBP or to those with a higher intensity of LBP. We used temporal summation as an indirect measure of central sensitization. Animal studies have directly observed activity at the dorsal horn of the spinal cord with similar methods to induce temporal summation.72–74 However, we currently are unable to directly visualize the spinal cord in human participants. Consequently, we cannot be certain that the associated findings of the current study were due to a direct effect mediated by the dorsal horn of the spinal cord. Additionally, pain is a multifaceted sensation relying on the peripheral nervous system in combination with the spinal cord and supraspinal centers, and the effect of SMT on pain likely results from an interaction of sites across the nervous system.75 Spinal manipulative therapy has been suggested to influence pain through mechanisms related to the peripheral nervous system76,77 and the supraspinal centers.78 – 80 Although our findings of diminished temporal summation suggest a spinal cord–mediated effect, other than assessing commonly reported psychological factors, we did not account for potential peripheral and supraspinal influences on our findings. Our primary outcome in the current study was inhibition of temporal summation, and we did not assess clinical pain ratings following treatment. The study was intended to investigate a specific mechanism of SMT, and the benefit of studying an experimental pain model was the ability to control the magnitude of the painful stimulus. The study was December 2009

Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP not intended to measure immediate changes in clinical pain intensity because we did not plan to track outcomes past immediate follow-up. Our protocol provided an indirect measure of a particular pain pathway believed to be important in the development of chronic pain conditions, but we are unable to comment upon the relationship between our findings and changes in clinical pain, as we did not include clinical pain ratings as an outcome measure. Future Studies The current study focused on a potential spinal cord–mediated mechanism of SMT. The mechanisms through which SMT influence musculoskeletal pain are likely related to multiple interactions throughout the nervous system.75 Subsequently, future studies should attempt to replicate the current findings while controlling for or manipulating additional potential factors such as those related to peripheral mechanisms and descending inhibition from supraspinal levels. Researchers in future studies also may want to include multiple sessions in order to assess dose response to SMT and to observe for longitudinal relationships between changes in temporal summation and clinical pain. Prior reviews13,14 suggest SMT is effective in the treatment of people with LBP; however, the evidence is stronger when homogeneous samples are included based on signs and symptoms suggesting a positive response.15–17 In future studies, researchers may want to include a sample of participants meeting a clinical prediction rule suggesting the likelihood of a positive clinical response.

Conclusions There were no differences in inhibition of A␦ fiber–mediated pain sensitivity for SMT in comparison with lumbar exercise and riding a stationary bicycle. The current study is the first to report that SMT specifically December 2009

inhibits temporal summation in individuals with LBP. Additionally, this inhibition appears to be local, as it was observed only in the lower extremity and psychological factors were not strongly associated with resultant inhibition of temporal summation. These findings suggest that inhibition of temporal summation is a potential mechanism for pain relief following SMT for individuals with LBP. Dr Bialosky, Dr Bishop, Dr Robinson, and Dr George provided concept/idea/research design and writing. Dr Bialosky and Mr Zeppieri provided data collection. Dr Bialosky provided data analysis. Dr George provided fund procurement. All authors provided consultation (including review of manuscript before submission). This study was approved by the Institutional Review Board of the University of Florida. A platform presentation of this research was given at the Combined Sections Meeting of the American Physical Therapy Association; February 6 –9, 2008; Nashville, Tennessee. The project was supported by grant AT002796 from the National Institutes of Health, National Center for Complementary and Alternative Medicine, awarded to Dr Bishop, Dr Robinson, and Dr George (principal investigator). Dr Bialosky also received support from grant AT002796 and from the National Institutes of Health T-32 Neural Plasticity Research Training Fellowship (T32HD043730). This work also was supported with resources from the Brain Rehabilitation Research Center, a VA Rehabilitation Research and Development Center of Excellence at the Malcom Randall VA Medical Center in Gainesville, Florida. This study was registered at www. clinicaltrials.gov under the identifier of NCT00922220. This article was received February 20, 2009, and was accepted July 30, 2009. DOI: 10.2522/ptj.20090058

References 1 Winkelstein BA. Mechanisms of central sensitization, neuroimmunology, and injury biomechanics in persistent pain: implications for musculoskeletal disorders. J Electromyogr Kinesiol. 2004;14:87–93.

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2 Rygh LJ, Svendsen F, Fiska A, et al. Longterm potentiation in spinal nociceptive systems: how acute pain may become chronic. Psychoneuroendocrinology. 2005; 30:959 –964. 3 Staud R, Domingo M. Evidence for abnormal pain processing in fibromyalgia syndrome. Pain Med. 2001;2:208 –215. 4 Staud R, Vierck CJ, Cannon RL, et al. Abnormal sensitization and temporal summation of second pain (wind-up) in patients with fibromyalgia syndrome. Pain. 2001; 91:165–175. 5 Staud R, Robinson ME, Price DD. Temporal summation of second pain and its maintenance are useful for characterizing widespread central sensitization of fibromyalgia patients. J Pain. 2007;8:893– 901. 6 Ayesh EE, Jensen TS, Svensson P. Hypersensitivity to mechanical and intraarticular electrical stimuli in persons with painful temporomandibular joints. J Dent Res. 2007;86:1187–1192. 7 Mohn C, Vassend O, Knardahl S. Experimental pain sensitivity in women with temporomandibular disorders and painfree controls: the relationship to orofacial muscular contraction and cardiovascular responses. Clin J Pain. 2008;24:343–352. 8 Sterling M, Jull G, Vicenzino B, Kenardy J. Characterization of acute whiplashassociated disorders. Spine. 2004;29:182– 188. 9 Curatolo M, Petersen-Felix S, ArendtNielsen L, et al. Central hypersensitivity in chronic pain after whiplash injury. Clin J Pain. 2001;17:306 –315. 10 Diers M, Koeppe C, Diesch E, et al. Central processing of acute muscle pain in chronic low back pain patients: an EEG mapping study. J Clin Neurophysiol. 2007;24:76 – 83. 11 O’Neill S, Manniche C, Graven-Nielsen T, Arendt-Nielsen L. Generalized deep-tissue hyperalgesia in patients with chronic lowback pain. Eur J Pain. 2007;11:415– 420. 12 Giesecke T, Gracely RH, Grant MA, et al. Evidence of augmented central pain processing in idiopathic chronic low back pain. Arthritis Rheum. 2004;50:613– 623. 13 Bronfort G, Haas M, Evans RL, Bouter LM. Efficacy of spinal manipulation and mobilization for low back pain and neck pain: a systematic review and best evidence synthesis. Spine J. 2004;4:335–356. 14 Koes BW, Assendelft WJ, van der Heijden GJ, Bouter LM. Spinal manipulation for low back pain: an updated systematic review of randomized clinical trials. Spine. 1996;21:2860 –2871. 15 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. 16 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.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP 17 Flynn T, Fritz JM, Whitman JM, 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. 18 Boal RW, Gillette RG. Central neuronal plasticity, low back pain and spinal manipulative therapy. J Manipulative Physiol Ther. 2004;27:314 –326. 19 Fernańdez-Carnero J, Fernańdez-de-LasPen ˜ as C, Cleland JA. Immediate hypoalgesic and motor effects after a single cervical spine manipulation in subjects with lateral epicondylalgia. J Manipulative Physiol Ther. 2008;31:675– 681. 20 Fernańdez-de-Las-Pen ˜ as C, Alonso-Blanco C, Cleland JA, et al. Changes in pressure pain thresholds over C5-C6 zygapophyseal joint after a cervicothoracic junction manipulation in healthy subjects. J Manipulative Physiol Ther. 2008;31:332–337. 21 Mohammadian P, Gonsalves A, Tsai C, et al. Areas of capsaicin-induced secondary hyperalgesia and allodynia are reduced by a single chiropractic adjustment: a preliminary study. J Manipulative Physiol Ther. 2004;27:381–387. 22 Vernon HT. Qualitative review of studies of manipulation-induced hypoalgesia. J Manipulative Physiol Ther. 2000;23:134 –138. 23 Vernon HT, Aker P, Burns S, et al. Pressure pain threshold evaluation of the effect of spinal manipulation in the treatment of chronic neck pain: a pilot study. J Manipulative Physiol Ther. 1990;13:13–16. 24 Price DD, Staud R, Robinson ME, et al. Enhanced temporal summation of second pain and its central modulation in fibromyalgia patients. Pain. 2002;99:49 –59. 25 George SZ, Bishop MD, Bialosky JE, et al. Immediate effects of spinal manipulation on thermal pain sensitivity: an experimental study. BMC Musculoskelet Disord. 2006;7:68. 26 Hill JC, Dunn KM, Lewis M, et al. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum. 2008;59:632– 641. 27 Fritz JM, George SZ, Delitto A. The role of fear-avoidance beliefs in acute low back pain: relationships with current and future disability and work status. Pain. 2001;94: 7–15. 28 Smeets RJ, Vlaeyen JW, Kester AD, Knottnerus JA. Reduction of pain catastrophizing mediates the outcome of both physical and cognitive-behavioral treatment in chronic low back pain. J Pain. 2006;7: 261–271. 29 Spinhoven P, Ter KM, Kole-Snijders AM, et al. Catastrophizing and internal pain control as mediators of outcome in the multidisciplinary treatment of chronic low back pain. Eur J Pain. 2004;8:211–219. 30 George SZ, Wittmer VT, Fillingim RB, Robinson ME. Sex and pain-related psychological variables are associated with thermal pain sensitivity for patients with chronic low back pain. J Pain. 2007;8:2–10.

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31 Bolton JE, Wilkinson RC. Responsiveness of pain scales: a comparison of three pain intensity measures in chiropractic patients. J Manipulative Physiol Ther. 1998; 21:1–7. 32 DeLoach LJ, Higgins MS, Caplan AB, Stiff JL. The visual analog scale in the immediate postoperative period: intrasubject variability and correlation with a numeric scale. Anesth Analg. 1998;86:102–106. 33 Hartrick CT, Kovan JP, Shapiro S. The numeric rating scale for clinical pain measurement: a ratio measure? Pain Pract. 2003;3:310 –316. 34 Jensen MP, Karoly P, Braver S. The measurement of clinical pain intensity: a comparison of six methods. Pain. 1986;27: 117–126. 35 George SZ, Dannecker EA, Robinson ME. Fear of pain, not pain catastrophizing, predicts acute pain intensity, but neither factor predicts tolerance or blood pressure reactivity: an experimental investigation in pain-free individuals. Eur J Pain. 2006; 10:457– 465. 36 Osman A, Barrios FX, Gutierrez PM, et al. The Pain Catastrophizing Scale: further psychometric evaluation with adult samples. J Behav Med. 2000;23:351–365. 37 Osman A, Breitenstein JL, Barrios FX, et al. The Fear of Pain Questionnaire–III: further reliability and validity with nonclinical samples. J Behav Med. 2002;25:155–173. 38 Schmidt NB, Cook JH. Effects of anxiety sensitivity on anxiety and pain during a cold pressor challenge in patients with panic disorder. Behav Res Ther. 1999;37: 313–323. 39 McNeil DW, Rainwater AJ III. Development of the Fear of Pain Questionnaire–III. J Behav Med. 1998;21:389 – 410. 40 Roelofs J, Peters ML, Deutz J, et al. The Fear of Pain Questionnaire (FPQ): further psychometric examination in a nonclinical sample. Pain. 2005;116:339 –346. 41 Woby SR, Roach NK, Urmston M, Watson PJ. Psychometric properties of the TSK-11: a shortened version of the Tampa Scale for Kinesiophobia. Pain. 2005;117:137–144. 42 Rosenstiel AK, Keefe FJ. The use of coping strategies in chronic low back pain patients: relationship to patient characteristics and current adjustment. Pain. 1983; 17:33– 44. 43 Robinson ME, Riley JL III, Myers CD, et al. The Coping Strategies Questionnaire: a large-sample, item-level factor analysis. Clin J Pain. 1997;13:43– 49. 44 Keefe FJ, Brown GK, Wallston KA, Caldwell DS. Coping with rheumatoid arthritis pain: catastrophizing as a maladaptive strategy. Pain. 1989;37:51–56. 45 Stewart MW, Harvey ST, Evans IM. Coping and catastrophizing in chronic pain: a psychometric analysis and comparison of two measures. J Clin Psychol. 2001;57: 131–138. 46 Spielberger CD, Gorsuch RL, Lushene RE, et al. Manual for the State and Trait Anxiety Inventory (Form Y). Palo Alto, CA: Consulting Psychologists Press; 1983.

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47 Schmidt NB, Joiner TE. Structure of the Anxiety Sensitivity Index psychometrics and factor structure in a community sample. J Anxiety Disord. 2002;16:33– 49. 48 Dehon C, Weems CF, Stickle TR, et al. A cross-sectional evaluation of the factorial invariance of anxiety sensitivity in adolescents and young adults. Behav Res Ther. 2005;43:799 – 810. 49 Jette AM, Delitto A. Physical therapy treatment choices for musculoskeletal impairments. Phys Ther. 1997;77:145–154. 50 Kemppainen P, Pertovaara A, Huopaniemi T, et al. Modification of dental pain and cutaneous thermal sensitivity by physical exercise in man. Brain Res. 1985;360:33– 40. 51 Droste C, Greenlee MW, Schreck M, Roskamm H. Experimental pain thresholds and plasma beta-endorphin levels during exercise. Med Sci Sports Exerc. 1991; 23:334 –342. 52 Delitto A, Erhard RE, Bowling RW. A treatment-based classification approach to low back syndrome: identifying and staging patients for conservative treatment. Phys Ther. 1995;75:470 – 485. 53 McKenzie RA. The Lumbar Spine: Mechanical Diagnosis and Treatment. Waikanaie, New Zealand: Spinal Publications Ltd; 1989. 54 Donelson R, Grant W, Kamps C, Medcalf R. Pain response to sagittal end-range spinal motion: a prospective, randomized, multicentered trial. Spine. 1991;16(6 suppl):S206 –S212. 55 Donelson R, Silva G, Murphy K. Centralization phenomenon: its usefulness in evaluating and treating referred pain. Spine. 1990;15:211–213. 56 Werneke M, Hart DL. Centralization phenomenon as a prognostic factor for chronic low back pain and disability. Spine. 2001;26:758 –764. 57 Werneke M, Hart DL, Cook D. A descriptive study of the centralization phenomenon: a prospective analysis. Spine. 1999; 24:676 – 683. 58 Werneke MW, Hart DL. Categorizing patients with occupational low back pain by use of the Quebec Task Force Classification System versus pain pattern classification procedures: discriminant and predictive validity. Phys Ther. 2004;84:243–254. 59 O’Leary S, Falla D, Hodges PW, et al. Specific therapeutic exercise of the neck induces immediate local hypoalgesia. J Pain. 2007;8:832– 839. 60 Bialosky JE, Bishop MD, Robinson ME, et al. The influence of expectation on spinal manipulation induced hypoalgesia: an experimental study in normal subjects. BMC Musculoskelet Disord. 2008;9:19. 61 Barriere G, Leblond H, Provencher J, Rossignol S. Prominent role of the spinal central pattern generator in the recovery of locomotion after partial spinal cord injuries. J Neurosci. 2008;28:3976 –3987. 62 Behrman AL, Bowden MG, Nair PM. Neuroplasticity after spinal cord injury and training: an emerging paradigm shift in rehabilitation and walking recovery. Phys Ther. 2006;86:1406 –1425.

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Effects of Spinal Manipulative Therapy on Thermal Pain Sensitivity in People With LBP 63 Mark VW, Taub E, Morris DM. Neuroplasticity and constraint-induced movement therapy. Eura Medicophys. 2006;42:269 – 284. 64 Gauthier LV, Taub E, Perkins C, et al. Remodeling the brain: plastic structural brain changes produced by different motor therapies after stroke. Stroke. 2008;39:1520 – 1525. 65 Behrman AL, Harkema SJ. Physical rehabilitation as an agent for recovery after spinal cord injury. Phys Med Rehabil Clin N Am. 2007;18:183–202. 66 Seffinger MA, Najm WI, Mishra SI, et al. Reliability of spinal palpation for diagnosis of back and neck pain: a systematic review of the literature. Spine. 2004;29:E413– E425. 67 Troyanovich SJ, Harrison DD, Harrison DE. Motion palpation: it’s time to accept the evidence. J Manipulative Physiol Ther. 1998;21:568 –571. 68 Poitras S, Loisel P, Prince F, Lemaire J. Disability measurement in persons with back pain: a validity study of spinal range of motion and velocity. Arch Phys Med Rehabil. 2000;81:1394 –1400. 69 Nattrass CL, Nitschke JE, Disler PB, et al. Lumbar spine range of motion as a measure of physical and functional impairment: an investigation of validity. Clin Rehabil. 1999;13:211–218.

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70 Gross DP, Battie´ MC. The prognostic value of functional capacity evaluation in patients with chronic low back pain, part 2: sustained recovery. Spine. 2004;29:920 – 924. 71 Dishman JD, Cunningham BM, Burke J. Comparison of tibial nerve H-reflex excitability after cervical and lumbar spine manipulation. J Manipulative Physiol Ther. 2002 ;25:318 –325. 72 Craig AD, Andrew D. Responses of spinothalamic lamina I neurons to repeated brief contact heat stimulation in the cat. J Neurophysiol. 2002;87:1902–1914. 73 Duggan AW, Hope PJ, Jarrott B, et al. Release, spread and persistence of immunoreactive neurokinin A in the dorsal horn of the cat following noxious cutaneous stimulation: studies with antibody microprobes. Neuroscience. 1990;35:195–202. 74 Jeftinija S, Urban L. Repetitive stimulation induced potentiation of excitatory transmission in the rat dorsal horn: an in vitro study. J Neurophysiol. 1994;71:216 –228. 75 Bialosky JE, Bishop MD, Price DD, et al. The mechanisms of manual therapy in the treatment of musculoskeletal pain: a comprehensive model. Man Ther. 2009;14: 531–538.

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76 Degenhardt BF, Darmani NA, Johnson JC, et al. Role of osteopathic manipulative treatment in altering pain biomarkers: a pilot study. J Am Osteopath Assoc. 2007; 107:387– 400. 77 McPartland JM, Giuffrida A, King J, et al. Cannabimimetic effects of osteopathic manipulative treatment. J Am Osteopath Assoc. 2005;105:283–291. 78 Wright A. Hypoalgesia post-manipulative therapy: a review of a potential neurophysiological mechanism. Man Ther. 1995;1:11–16. 79 Sterling M, Jull G, Wright A. Cervical mobilisation: concurrent effects on pain, sympathetic nervous system activity and motor activity. Man Ther. 2001;6:72– 81. 80 Vicenzino B, Collins D, Benson H, Wright A. An investigation of the interrelationship between manipulative therapyinduced hypoalgesia and sympathoexcitation. J Manipulative Physiol Ther. 1998;21:448 – 453.

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Research Report

R.J. Palisano, PT, ScD, is Professor, Department of Physical Therapy and Rehabilitation Sciences, Drexel University, Mail Stop 502, 245 N 15th St, Philadelphia, PA 19102-1192 (USA) and a member of the scientific staff of Shriners Hospitals for Children, Philadelphia, Pennsylvania. Address all correspondence to Dr. Palisano at: [email protected].

Social and Community Participation of Children and Youth With Cerebral Palsy Is Associated With Age and Gross Motor Function Classification Robert J. Palisano, Lin-Ju Kang, Lisa A. Chiarello, Margo Orlin, Donna Oeffinger, Jill Maggs

Background. Through social and community participation, children and youth with cerebral palsy (CP) form friendships, gain knowledge, learn skills, express creativity, and determine meaning and purpose in life. Objective. The purposes of this study were: (1) to determine whether social and

L.-J. Kang, PT, MS, is a doctoral candidate in the Department of Physical Therapy and Rehabilitation Sciences, Drexel University.

community participation of children and youth with CP differ based on age, sex, and gross motor function, and (2) to identify the types of activities in which social and community participation are highest.

L.A. Chiarello, PT, PhD, PCS, is Associate Professor, Department of Physical Therapy and Rehabilitation Sciences, Drexel University, and a member of the scientific staff of Shriners Hospitals for Children, Philadelphia.

Design and Methods. A prospective cross-sectional analytic design was used. The participants were a sample of convenience of 291 children (6 –12 years of age) and 209 youth (13–21 years of age) with CP (55.4% males, 44.6% females) receiving services from 7 children’s hospitals. Participants completed the Children’s Assessment of Participation and Enjoyment (CAPE) by structured interview. Gross Motor Function Classification System (GMFCS) level was determined by the researchers.

M. Orlin, PT, PhD, is Associate Professor, Department of Physical Therapy and Rehabilitation Sciences, Drexel University, and a member of the scientific staff of Shriners Hospitals for Children, Philadelphia. D. Oeffinger, PhD, is Director of Research Development, Shriners Hospitals for Children, Lexington, Kentucky. J. Maggs, DocEd, MCSP, is Assistant Professor, Department of Physical Therapy and Rehabilitation Sciences, Drexel University. [Palisano RJ, Kang L-J, Chiarello LA, et al. Social and community participation of children and youth with cerebral palsy is associated with age and gross motor function classification. Phys Ther. 2009;89:1304 – 1314.]

Results. Youth did a higher percentage of activities with friends and others and outside the home than children. Children and youth in level I did a higher percentage of activities with friends and others compared with children and youth in levels II and III and in levels IV and V. Children and youth in level I and in levels IV and V did a higher percentage of activities outside the home than children and youth in levels II and III. Differences were not found between females and males. The percentage of activities done with friends and others and outside the home was highest for physical and skill-based activities.

Limitations. Findings cannot be attributed only to GMFCS level. Conclusions. The ability to walk without restrictions is desirable for social and community participation. For children and youth with CP who have limitations in mobility, physical therapists have roles as consultants for accessibility, activity accommodations, and assistive technology and as advocates for inclusive environments.

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Social and Community Participation of Children and Youth With Cerebral Palsy

C

erebral palsy (CP) describes a group of disorders of posture and movement that occur as a result of a nonprogressive disturbance in the developing fetal or infant brain.1 United Cerebral Palsy2 estimates that in the United States 9,000 infants and children younger than school age are diagnosed with CP each year and the number of children and adults with CP is 764,000. Children with CP frequently receive physical therapy.3 Physical therapy interventions for individuals with CP focus on impairments in motor control, muscle performance, and musculoskeletal alignment that are thought to contribute to activity limitations in sitting, standing, transfers, and mobility.4,5 Contemporary models for understanding health and disability, such as the International Classification of Functioning, Disability and Health (ICF)6 and the Social Model of Disability,7 suggest that an important outcome of rehabilitation services is to optimize children’s participation in home, school, and community life. The ICF is a biopsychosocial model based on the premise that disability involves an interaction between features of the person and features of the environment. Components of functioning and disability (body functions and structures, activity, participation) are viewed as outcomes of interactions among health conditions and contextual factors (environmental and personal). The Social Model of Disability states that disability results when features of the physical, social, or attitudinal environment restrict participation in activities that an individual needs or wants to do.8,9 Chen and Cohn10 proposed that, for children, social participation involves interactions with others within the contexts of home, school, and community and is influenced by the extent that environments are acDecember 2009

cessible and interactions are positive. Through social participation, children form friendships, gain knowledge, learn skills, express creativity, and determine meaning and purpose in life.11,12 People with childhood onset disabilities have reported that opportunities to form social networks and develop social competencies have positive benefits for mental and physical health.13,14 Belonging to social networks outside the family is a particular desire for adolescents with physical disabilities.15 Social self-efficacy (a person’s belief in his or her ability to succeed in a particular situation) is associated with independence and persistence in adolescents with physical disabilities.16 Adolescents with CP identified being believed in, believing in yourself, and being accepted by others as important for success in life.17 Differences in participation have been reported between children and youth with and without physical disabilities and between females and males. Children and youth with physical disabilities participate in fewer social activities, are less socially active, and are less skilled when interacting with others compared with children and youth without disabilities.18 –20 Brown and Gordon20 reported that children with physical disabilities spent more time in dependent activities, quiet recreation, and self-care and less time in social engagements, active recreation, household tasks, and community activities compared with children without physical disabilities. Children with disabilities who desire more social participation but have limited opportunities for participation may feel socially isolated and demonstrate more passive activity compared with children without disabilities.9,18 –21 Differences in participation between females and males have been reported for children with and without disabilities. In general, females participate more in arts Volume 89

and social activities, whereas males participate more in group activities involving physical activity and sports.22–25 Among individuals with disabilities, adolescents and youth have been reported to have less social participation than children.18 –20,26 In a sample of 60 individuals with CP, aged 12 to 22 years, more than 50% indicated that their best friends had disabilities and their participation with friends was mostly passive (eg, watching television) or sedentary recreation (eg, playing chess).21 Adolescents with CP were reported to be less physically active27 and to walk less than adolescents without CP.28 Lack of information, limited disability awareness, program costs, and transportation were identified as barriers to participation in recreation for youth with disabilities.29 Inadequate activity accommodations and difficulties in planning and coordinating services are other potential barriers to participation.30 The aims of this study were: (1) to determine whether social and community participation of children and youth with CP differ based on age, sex, and gross motor function level; and (2) to identify the types of activities in which social and community participation are highest. Social participation was operationally defined as doing an activity with friends or other non–family members (instructors, coaches, and other individuals). Community participation was operationally defined as doing an activity

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on October 8, 2009, at www.ptjournal.org.

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Social and Community Participation of Children and Youth With Cerebral Palsy Table 1. Characteristics of the Children and Youth With Cerebral Palsy and Family Incomea Children (6–12 y) (nⴝ291)

Characteristics Age (y), mean, SD

9.7

2.0

Youth (13–21 y) (nⴝ209) 16.2

2.3

Gross motor function level I–Walks without restrictions

74

25.4%

54

25.8%

II–Walks with limitations

69

23.7%

57

27.3%

III–Walks with assistive device

61

21.0%

33

15.8%

IV–Limited self-mobility

45

15.5%

26

12.4%

V–Severe limitations in posture and self-mobility

42

14.4%

39

18.7%

Sex Male

169

58.1%

108

51.7%

Female

122

41.9%

101

48.3%

Ethnicity Caucasian

231

79.4%

142

67.9%

African American

19

6.5%

21

10.0%

Hispanic/Latino

21

7.2%

21

10.0%

Other

20

6.9%

25

12.0%

Intellectual disability

45

16.0%

32

16.4%

Learning disability

98

34.8%

80

41.0%

Attention deficit disorder

27

9.6%

27

13.8%

134

47.5%

118

60.5%

Associated diagnosis

b

Associated conditions

b

Visual impairments Hearing impairments

15

5.3%

13

6.7%

Communication impairments

83

29.4%

50

25.6%

Speech impairments

105

37.2%

69

35.4%

Behavioral/emotional problems

86

30.5%

48

24.6%

Seizure disorder

61

21.6%

46

23.6%

Heart conditions

12

4.3%

5

2.6%

Respiratory conditions

56

19.9%

27

13.8%

Orthopedic conditions

98

34.8%

99

50.8%

Less than $15,000

29

11.3%

21

11.9%

$15,000–$29,999

33

12.8%

29

16.5%

$30,000–$44,999

59

23.0%

34

19.3%

$45,000–$59,999

38

14.8%

18

10.2%

$60,000–$74,999

36

14.0%

29

16.5%

$75,000–$99,999

35

13.6%

17

9.7%

$100,000 and over

27

10.5%

28

15.9%

Family income

a b c

c

Reported values are numbers and percentages of participants, unless otherwise indicated. Number of participants: children⫽282, youth⫽195. Number of participants: children⫽257, youth⫽176.

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outside the home or a relative’s home. “Outside the home” includes in the neighborhood, at school (but not during classes), in the community, and outside the community. The results will increase knowledge of social and community participation of children and youth with CP and have implications for physical therapy interventions to optimize social and community participation.

Method Participants The participants were 500 children and youth with CP, (mean age⫽12.4 years, SD⫽3.8, range⫽6 –21) who were receiving services from 6 Shriners Hospitals for Children (Chicago, Illinois; Erie, Pennsylvania; Lexington, Kentucky; Sacramento, California; Philadelphia, Pennsylvania; and Springfield, Massachusetts) and Kluge Children’s Rehabilitation Center, Charlottesville, Virginia. Children and youth with CP were excluded only if they had a second diagnosis such as autism or a mental health disorder that might influence social participation. The study was approved by the institutional review board of each hospital. Informed consent was provided by parents or guardians and youth under the age of 18 years. Informed assent was provided by children and adolescents 7 to 17 years of age. Participant characteristics are presented in Table 1. The sample comprised 291 children (6 –12 years of age) and 209 youth (13–21 years of age) with CP; 277 (55.4%) of the participants were males and 223 (44.6%) were females. The number of participants in each of the 5 levels of the Gross Motor Function Classification System (GMFCS)31 varied from 71 to 128. Parents reported that 16% of the participants had a secondary diagnosis of intellectual disability, 37% had a diagnosed learning disability, and 11% had a diagnosis of attention deficit disorder. The perDecember 2009

Social and Community Participation of Children and Youth With Cerebral Palsy Table 2. Examples of Items for Each Activity Type of the Children’s Assessment of Participation and Enjoyment (CAPE)32 Recreational

Physical

Social

Playing computer or video games

Bicycling, in-line skating, or skateboarding

Talking on the telephone

Swimming

Getting extra help for schoolwork from a tutor

Watching television or a rented movie

Doing team sports

Hanging out

Horseback riding

Reading

Playing on equipment

Doing individual physical activities

Going to a party

Participating in community organizations

Doing homework

centage of children with health conditions and impairments in body functions and structures associated with CP varied from 4% (heart condition) to 53% (visual impairment). The diagnoses and conditions reported are consistent with the definition of CP.1 Family income was fairly evenly distributed and varied from less than $15,000 to more than $100,000 per year. Measures Children’s Assessment of Participation and Enjoyment. The Children’s Assessment of Participation and Enjoyment (CAPE)32 is a 55-item measure of participation in leisure and recreational activities designed for completion by children and youth of 6 to 21 years of age. The CAPE is completed by a questionnaire or structured interview and parent assistance is permitted. Five dimensions of participation are rated for each item: whether the activity was done during the past 4 months and, for each activity done, how of-

Skill-Based

ten, with whom, where, and level of enjoyment. Each item is categorized by activity domain (formal or informal) and activity type (recreational, physical, social, skill-based, or selfimprovement). Formal activities refer to activities structured by adults that involve rules or goals (eg, organized sports, art lessons), and informal activities refer to activities involving little or no planning that often are initiated by the child (eg, playing non-team sports, reading). Examples of items for each activity type are provided in Table 2. A score can be calculated for each of the 5 dimensions of participation. The diversity score is the number of activities performed in the past 4 months. The intensity score is the total ratings for how often each activity was performed divided by the total number of items. The “With Whom,” “Where,” and enjoyment scores are the total ratings for each dimension divided by the diversity score. The response options for the 3 dimen-

Self-Improvement

sions analyzed in this study are presented in Table 3. Evidence of reliability and validity of the CAPE have been reported previously.25,32 Test-retest stability was examined in 48 children. The intraclass correlation coefficients (ICCs) were .75 for the overall diversity score, .72 for the overall intensity score, and .65 for the overall enjoyment score. Construct validity was examined using correlation analysis. Intensity and enjoyment scores correlated significantly with environmental, family, and child variables, in expected ways. Predictions also were supported with respect to differences in mean scores for boys and girls and younger and older children. Agreement between scores when the CAPE was completed by questionnaire versus structured interview was high for intensity (ICC⫽.82–.99) and moderate for enjoyment (ICC⫽.47–.78). The reader is referred to an appraisal of the CAPE for more information.33

Table 3. Response Options for Diversity (Number of Activities Performed) and “With Whom” and “Where” Dimensions of the Children’s Assessment of Participation and Enjoyment (CAPE)32 Activity Performed?

With Whom?

Where?

0 No

1 Alone

1 At home

1 Yes

2 With family (parents, brothers, sisters)

2 At a relative’s home

3 With other relatives (grandparents, aunts, uncles, cousins)

3 In your neighborhood

4 With friends

4 At school (but not during classes)

5 With others (instructors, other individuals, or multiple types of people)

5 In your community 6 Beyond your community

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Social and Community Participation of Children and Youth With Cerebral Palsy Gross Motor Function Classification System. The GMFCS34 is a 5-level system for children with CP ages 12 years or younger. A classification is made based on current performance of gross motor function in daily activities with emphasis on mobility and sitting. The preliminary version of the 12- through 18-yearold age band of the expanded and revised GMFCS31 was used to classify participants over the age of 12 years. The GMFCS has evidence of content, construct, and discriminative validity and interrater reliability.31,34

ture card for each of the 55 activities on a laptop computer and to record responses electronically. Guidelines were developed for parent assistance in recall of the number of times an activity was done in the past 4 months and where and with whom the activity was done. The researcher provided assistance to children or parents who had difficulty with reading or entering responses. If a child or youth was unable to communicate whether or not each activity was done, the CAPE was completed by parent proxy.

Procedure A prospective cross-sectional analytic design was used. At each hospital, data were collected by 1 to 3 research assistants. The research assistants were primarily health care professionals experienced in providing services to children with CP. They included physical therapists, occupational therapists, a nurse, a psychologist, and a social worker. Research assistants who were not health care professionals were selected to collect data based on their positive interpersonal and communication skills.

The CAPE was completed independently by 32% of the children and 56% of the youth. The CAPE was completed by a parent for 34% of the children and 22% of the youth. Sixtythree percent of the children and youth in level I, 49% of the children and youth in levels II and III, and 13.2% of the children and youth in levels IV and V completed the CAPE independently. The CAPE was completed by a parent for 59.2% of the children and youth in levels IV and V.

Prior to data collection, the research assistants received a procedural manual and attended a 2-day workshop to learn the procedures. Following instruction in the GMFCS, interrater reliability was examined using a criterion videotape. Each research assistant classified a minimum of 11 children and achieved agreement of ⬎80% with the criterion rating. To ensure data fidelity, teleconferences were scheduled at 3-month intervals, and a second workshop was held at the midpoint of data collection. The CAPE was completed by interview using either a custom-designed display on a computer monitor or the standard picture cards and scoring form. Permission was obtained from the publisher to display the pic1308

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Data Analysis Participants were grouped by age (ages 6 –12 years and 13–21 years), sex, and GMFCS level (I, II and III, and IV and V). The 2 age bands were selected to permit comparisons between children and youth. The decision to combine GMFCS levels II and III and levels IV and V was based on previous research.35,36 In a study of performance of physical activity of children and youth with CP (ages 11–17 years), the mean score on the Activity Scales for Kids35 was highest for participants in level I, and scores of participants in levels II and III and participants in levels IV and V were similar to each other.36 Orlin et al37 found a similar relationship between GMFCS level and CAPE scores for diversity and intensity of participation in their study.

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The overall percentage of activities done with friends or other nonfamily members (friends and others) and the percentage of activities done with friends and others for each of the 5 activity types were calculated for each participant as follows. First, the diversity score was determined by summing the number of activities done in the past 4 months (Tab. 3). Second, the number of activities done in which the “With Whom” dimension score was 4 or 5 was summed (Tab. 3). Third, the sum of scores of 4 and 5 for the “With Whom” dimension was divided by the diversity score, and the ratio was multiplied by 100. For example, 1 child reported having done 20 of the 55 activities in the past 4 months. Five activities were done with friends, 3 activities were done with others (non-family members), and 12 activities were done alone, with family members, or with other relatives. The overall percentage of activities done with friends and others was (5 ⫹ 3)/20 ⫻ 100⫽40%. The overall percentage of activities done outside the home and the percentage done outside the home for each of the 5 activity types were calculated as follows. The number of activities done in which the “Where” dimension score was 3 through 6 (Tab. 3) was summed, divided by the diversity score, and multiplied by 100. In the previous example, the child did 3 activities at school (extracurricular), 2 activities in his neighborhood, and 5 activities in the community, and 10 activities were done either at home or at a relative’s home. The overall percentage of activities done outside the home was (3 ⫹ 2 ⫹ 5)/20 ⫻ 100⫽50%. The use of percentages instead of absolute numbers of activities enabled comparisons across participants with different diversity scores for overall activities and among 5 activity types with different numbers of items. December 2009

Social and Community Participation of Children and Youth With Cerebral Palsy Statistical analysis was performed using SPSS for Windows, version 16.0.* Among the 500 participants, 50 (10%) did not do any activities with friends and others. Logistic regression was performed to determine if the adjusted odds of not participating in an activity with friends and others differed by age, sex, or gross motor function level. Three-way analyses of variance (ANOVAs) were computed to analyze the effect of age, sex, and gross motor function level on the overall percentage of activities done: (1) with friends and others and (2) outside the home. Post hoc analysis of significant effects was performed using Bonferroni corrections for pairwise comparisons. The significance level for all analyses was P⫽.05. The data for the 450 participants who did at least 1 activity with friends and others and the 497 participants who did at least 1 activity outside the home were used for the ANOVAs. The distribution of “With Whom” scores was positively skewed; therefore, natural logarithmic transformation was performed prior to statistical analysis. The “Where” scores of the 497 participants who did at least 1 activity outside the home had a normal distribution. Friedman 2-way ANOVA by ranks was used to analyze whether the percentage of activities done with friends and others and the percentage of activities done outside the home differed among the 5 activity types. The distributions of scores for activity types were positively skewed. The high number of 0 scores precluded transformation of data; therefore, nonparametric statistics were used. Post hoc analyses were performed using the Wilcoxon signed-rank test. The significance level for the Friedman test was * SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

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Table 4. Analysis of Whether the Odds That Children and Youth Who Did Not Do Any Activities With a Friend or Other Non-Family Member (n⫽50) Differed Based on Age, Sex, and Gross Motor Function Levela Variable

OR

95% CI

P

0.5–1.7

.73

0.7–2.3

.47

Age (y) 6–12

1.0

13–21

0.9

Sex Male

1.0

Female

1.2

GMFCS level I

1.0

II/III

4.6

1.4–15.8

.02

IV/V

8.2

2.4–27.7

.001

a OR⫽adjusted odds ratio, CI⫽confidence interval, GMFCS⫽Gross Motor Function Classification System.

P⫽.05 and for the post hoc Wilcoxon test was P⫽.01. Role of the Funding Source Funding support for this study was provided by Shriners Hospitals for Children (COS #9197).

Results The results of the logistic regression are presented in Table 4. Among the 50 children and youth who did not do any activities with friends and others, 3 were in level I, 22 were in levels II and III, and 25 were in levels IV and V. The numbers represent 2%, 10%, and 16% of the participants in each group, respectively. The adjusted odds of children and youth not doing any activities with friends and others in the past 4 months differed for gross motor function level but not age or sex. Compared with children and youth in level I, children and youth in levels IV and V were 8.2 times (P⫽.001) more likely to not do any activities with friends and others and children and youth in levels II and III were 4.6 times (P⫽.02) more likely to not do any activities with friends and others.

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Effect of Age, Sex, and Gross Motor Function Level Descriptive statistics for the CAPE are presented in Table 5. The mean number of activities done by the entire sample was 23.7; on average, children and youth did 43% of the 55 activities on the CAPE. The mean number of activities done varied from a low of 18.5 (34%) for youth in levels IV and V to a high of 27.9 (51%) for children in level I. The results of the ANOVAs are presented in Table 6. The mean percentage of activities done with friends and others differed based on age and gross motor function level. The effect of sex and the interaction effects were not significant. Youth did a higher percentage of activities with friends and others (30.3%) than children (20.2%, P⬍.001). Children and youth in level I did a higher percentage of activities with friends and others (29.8%) compared with children and youth in levels II and III (22.9%, P⬍.001) and in levels IV and V (21.5%, P⬍.001). The mean percentage of activities done outside the home differed by

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Social and Community Participation of Children and Youth With Cerebral Palsy Table 5. Mean Number of Activities Done (Diversity Score) and the Mean Percentage of Activities Done With Friends and Others and Outside the Home for Children and Youth With Cerebral Palsy Grouped by Age and Gross Motor Function Level (Gross Motor Function Classification System [GMFCS]) 6–12 y

GMFCS Level No. of activities done (n⫽500)

% activities done with friends and others (n⫽450)

% activities done outside the home (n⫽497)

13–21 y

n

Mean

SD

n

Mean

SD

n

Mean

SD

74

27.9

6.2

54

24.5

7.3

128

26.5

6.9

II/III

130

25.0

6.2

90

23.2

6.4

220

24.3

6.4

IV/V

87

21.8

7.5

65

18.5

6.9

152

20.4

7.4

Total

291

24.8

I

7.0

209

7.2

500

23.7

71

25.2%

12.5%

54

35.8%

19.7%

125

29.8%

16.8%

II/III

118

19.1%

11.5%

80

28.5%

17.2%

198

22.9%

14.8%

IV/V

72

17.0%

10.5%

55

27.3%

15.2%

127

21.5%

13.7%

Total

261

20.2%

11.9%

189

30.3%

17.7%

450

24.4%

15.4%

74

40.3%

10.9%

54

45.5%

14.5%

128

42.5%

12.8%

II/III

130

34.2%

11.9%

89

36.8%

13.5%

219

35.2%

12.6%

IV/V

86

35.6%

11.2%

64

44.8%

16.9%

150

39.5%

14.6%

Total

290

36.1%

11.7%

207

41.5%

15.4%

497

38.4%

13.6%

I

I

age and gross motor function. The effect of sex and the interaction effects were not significant. Youth did a higher percentage of activities outside the home (41.5%) than children (36.1%, P⬍.001). Children and youth in level I (42.5%) and in levels IV and V (39.5%) did a higher percentage of activities outside the

22.1

home compared with children and youth in levels II and III (35.2%, P⬍.001). The difference in the percentage of activities done outside the home between children and youth in level I and in levels IV and V was not significant (P⬎.01).

Table 6. Three-Way Analyses of Variance: Effect of Age, Sex, and Gross Motor Function Level (Gross Motor Function Classification System [GMFCS]) on the Mean Percentage of Activities Done With Friends and Others and Outside the Home by Children and Youth With Cerebral Palsy % Activities Performed With Friends and Others (nⴝ450) Main Effects/Interactions Age

% Activities Performed Outside the Home (nⴝ497)

Fa

Paired Comparisons

Fb

Paired Comparisons

35.65c

6–12 y ⬍ 13–21 yc

22.80c

6–12 y ⬍ 13–21 yc

I ⬎ II/IIIc I ⬎ IV/Vc

12.84c

Sex

0.02

GMFCS level

9.05c

Age ⫻ sex

0.00

1.84

Age ⫻ GMFCS level

0.74

2.84

0.79

Sex ⫻ GMFCS level

0.64

2.35

Age ⫻ sex ⫻ GMFCS level

0.58

0.60

a

df⫽1,438 for age; df⫽2,438 for GMFCS level. df⫽1,485 for age; df⫽2,485 for GMFCS level. P⬍.001. d P⬍.01. b c

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I ⬎ II/IIIc IV/V ⬎ II/IIId

7.2

Effect of Activity Type The mean number of activities that were done and percentages of activities done with friends and others and outside the home for each activity type are presented in Table 7. On average, children and youth participated in 67.7% of social activities, 63.3% of recreational activities, and 46.9% of self-improvement activities. There was only 21% of physical and 19% of skill-based participation by children and youth for related activities. The percentage of activities done with friends and others differed by activity type (␹2⫽190.4, df⫽4, P⬍.001). Post hoc analysis indicated that the percentage of activities done with friends and others was highest for physical (37.1%) and skill-based (34.9%) activities, followed by social activities (23.5%), and was lowest for self-improvement (16.0%) and recreational (14.8%) activities (P⬍.01). The percentage of activities done outside the home differed by activity type (␹2⫽319.8, df⫽4, P⬍.001). The mean percentage of activities done outside the home was highest for

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Social and Community Participation of Children and Youth With Cerebral Palsy Table 7. Mean Number of Activities Done (Diversity Score) and Mean Percentage of Activities Done With Friends and Others and Outside the Home by Children and Youth With Cerebral Palsy for Each Activity Type Recreational (12 Items)

Physical (13 Items)

Social (10 Items)

SelfImprovement (10 Items)

Skill-Based (10 Items)

Mean

SD

Mean

SD

Mean

SD

Mean

SD

Mean

SD

7.6

2.6

2.7

2.1

6.8

1.9

1.9

1.4

4.7

2.0

% activities done (n⫽500)

63.3%

21.3%

20.7%

16.2%

67.7%

19.2%

19.2%

14.4%

46.9%

19.9%

% activities done with friends and others (n⫽450)

14.8%

17.6%

37.1%

36.9%

28.3%

23.5%

34.9%

37.9%

16.0%

19.0%

% activities done outside the home (n⫽497)

20.0%

16.1%

48.3%

39.5%

40.1%

19.4%

45.4%

40.4%

47.8%

21.9%

No. of activities done (n⫽500)

physical (48.3%), self-improvement (47.8%), and skill-based (45.4%) activities, followed by social activities (40.1%), and was lowest for recreational activities (20.0%) (P⬍.01).

only to gross motor function level. Although the sample was large and there was a wide geographical distribution, we do not know the extent that the participants are representative of children and youth with CP.

Discussion Children and youth with CP differed in social and community participation based on gross motor function level and age, but not sex. For the entire sample, social and community participation were highest for physical and skill-based activities and lowest for recreational activities. Several limitations should be considered when interpreting the results. The operational definitions reflect the content and construct of the CAPE and, consequently, do not encompass all aspects of social and community participation. In particular, we did not address social engagement, the nature of relationships, and involvement with friends and other non-family members while doing an activity.38 The activities analyzed were limited to the 55 items on the CAPE. The CAPE was completed by parent proxy for 59.2% of the children and youth in levels IV and V, indicating that they were more likely to have problems in communication, cognition, or both. Consequently, differences in social and community participation cannot be attributed December 2009

Children and youth with CP who walk without restrictions (level I) did the highest percentage of activities with friends and other nonfamily members. Children and youth in level I have the ability to run and jump, which may enable social participation in physical activities and sports. Conversely, children and youth who do not walk (levels IV and V) were more likely not to have done any activities with friends and others in the past 4 months. A relationship between mobility and social participation has been documented for children and youth with CP; however, mediating factors are not well understood.39 Reduced speed, endurance, and efficiency of walking may limit the ability of children and youth in levels II and III to keep up with peers, especially outdoors and in the community. The finding that children and youth in levels IV and V did a percentage of activities outside the home similar to that of children and youth in level I is encouraging and may reflect a conVolume 89

certed effort by family members. Previously, Palisano et al40 reported that parents of children and youth in levels IV and V were more likely to express a need for help in locating camps and sports, recreational, social, and leisure activities than parents of children and youth in level I and levels II and III. In a qualitative study of 15 families, parents were characterized as making extraordinary efforts to promote a social life for their adolescent with a disability. Almost all parents enrolled their adolescent in recreational activities, often those especially for young people with disabilities.41 Transportation to accommodate a wheelchair, attending the activity to assist their child, instruction of others on accommodations, and activity modifications are resources family members may need to enable their children’s participation when they require physical assistance for mobility and self-care. The mean percentage of activities done outside the house by the child and youth in our study varied from 35.2% to 42.5%. Mactavish et al42 analyzed family recreation patterns of 65 families who have a child with a disability. Sixty percent of parents reported that family recreation occurred with equal frequency at home Number 12

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Social and Community Participation of Children and Youth With Cerebral Palsy and in the community, 29% reported that most family recreation took place at home, and 11% reported that most family recreation occurred in the community. In comparison, Orthner and Mancini43 reported that among families of children without disabilities, family recreation occurred most often at home and less frequently in the neighborhood and community. The findings that youth did a higher percentage of activities with friends and others and outside the home than children are consistent with life span development. Forming new and more mature relationships with peers of both sexes is an accomplishment that characterizes adolescence.44 At first glance, the results appear to contradict studies in which participation was lower in youth than in children.18 –20,26 We previously reported that among the participants in the present study, children had a higher diversity and intensity of participation than youth.37 The aim of the present study, however, was not to quantify age-related differences in how many and how often activities were done. Rather, we were interested in the percentage of activities that were done with friends and others and outside the home. Time did not permit asking participants to complete the Preferences for Activities of Children (PAC),32 a companion measure to the CAPE. Consequently, the extent that the activities done in the past 4 months reflect what the children and youth would have preferred to do is not known. Females and males did not differ in social and community participation. Our results do not corroborate differences reported between females and males with and without disabilities.22–25 Similar to the results for age, the discrepancy may reflect the aims of our study. Our primary interest was to quantify whether females 1312

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and males differed in the percentage of activities done with friends and others and outside the home rather than differences in the types of activities done by females and males. Comparison of scores for domains, activity types, and items on the CAPE would provide a more in-depth analysis of differences between males and females.

and sports that they are interested in performing. Most children with CP, however, do not walk without restrictions.45 For children and youth who are capable of walking with limitations (levels II and III), an issue is whether physical therapy interventions to improve walking and gross motor function generalize to social and community participation.

Although not an aim of the study or analyzed statistically, descriptive data for activity types suggest that for children and youth with CP, the number of activities done is not an indicator of social and community participation. Children and youth did the highest percentage of physical and skill-based activities with friends and others and outside the home, activity types where they did only 20.7% and 19.2% of the activities. Conversely, although the participants did 63.3% of recreational activities and 67.7% of social activities, they were more likely to do these activities by themselves, with members of their family, and at home. Many recreational activities on the CAPE, such as playing computer or video games, are well suited to do alone. Social activities such as going to a party or movie may be done with family members and relatives. Given the descriptive data, we caution against assumptions about activity types where social and community participation should be encouraged.

Powered mobility is an option for self-sufficient mobility for children and youth with CP who are unable to walk or when walking is not effective for social and community participation. Parents of children with disabilities, however, identified environmental barriers that restrict use of powered mobility, including the size of rooms, availability of transportation to accommodate a wheelchair, and durability of the wheelchair when used outdoors.46 Mobility also includes transporting oneself via riding a bicycle, driving a car, or using transportation to move around as a passenger in a bus.6 Youth with physical disabilities have consistently indicated that the lack of accessible and reliable transportation is an obstacle to participation.30,39,46 Notable from the perspective of youth who use wheelchair-accessible public transportation is the inability to go places and do things in a spontaneous manner that is typical of socialization among youth.47 Collectively, the findings support a team approach to selection of assistive technology and the importance of problem solving to minimize barriers to powered mobility and other means of transportation.

Implications for Physical Therapy Self-sufficient mobility, or getting from place to place without relying on other people, is desirable for social and community participation. Children and youth with CP who walk without restrictions and perform gross motor tasks such as running and jumping did more activities with friends and others. Children and youth who are able to run and jump may benefit from instruction and practice of physical activities

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Physical therapists are encouraged to provide services to children and youth with CP in a manner that promotes social self-efficacy. This approach includes involving children and youth in identifying priorities for social and community participation, making choices, and participating in real-world experiences. We adDecember 2009

Social and Community Participation of Children and Youth With Cerebral Palsy vocate for strength-based ecological and experiential approaches to learning that build on the abilities and interests of children and youth. Ecological and experiential approaches are based on the principle that real-world experiences optimize the development of life skills such as self-knowledge, communication, interpersonal relationships, problem solving, and daily living and work skills.48,49

state policymakers. Whiteneck et al54 proposed that accessibility, accommodation, resource availability, social support, and equality are characteristics of environments that foster social participation of people with disabilities. Their perspective is supported by parents of young children with physical disabilities who encouraged service providers to change the environment, not the child.55

Physical therapists have an important role as consultants in supporting social and community participation of children and youth with CP. Strategies include linking children, youth, and families to community supports, enhancing knowledge of community opportunities, and creating individualized opportunities and experiences. Information about community programs is a common need expressed by families.40,50 –52 Limited knowledge of community programs has been associated with fewer opportunities for participation.53 Therapists are encouraged to share information about leisure, recreational, and social activities, sports programs, and camps with children, youth, and families. Direct consultation with educators, instructors, and coaches is recommended to address issues related to accessibility, activity accommodations, and assistive technology. Social and community participation involves interaction of the person and environment. Observation of a child or youth during a community activity enables the therapist to evaluate physical, social, and attitudinal features that facilitate or restrict participation.

Further research is recommended to understand personal and environmental factors that are determinants of social and community participation of children and youth with CP. Participation is a multidimensional construct involving personal experiences.56,57 Mixed-methods designs58 involving quantitative and qualitative methods are well suited for this area of inquiry. We perceive successful social participation as physical, social, and psychological engagement in an activity that is enjoyable and that promotes self-efficacy. Research is needed to identify factors that facilitate social and community participation desired by children and youth with CP.

Physical therapists have a role as advocates for environments that enable social participation of children and youth with CP. Advocacy might involve providing educational materials to the community, serving on an advisory board of an agency or organization, and meeting with local and December 2009

Dr Palisano, Ms Kang, Dr Chiarello, Dr Orlin, and Dr Oeffinger provided concept/idea/research design. Dr Palisano, Ms Kang, and Dr Orlin provided writing. Dr Orlin, Dr Oeffinger, and Dr Maggs provided data collection. Dr Palisano, Ms Kang, Dr Orlin, and Dr Oeffinger provided data analysis. Dr Palisano, Dr Oeffinger, and Dr Maggs provided project management. Dr Oeffinger and Dr Maggs provided fund procurement. Dr Oeffinger provided participants and facilities/equipment. Dr Palisano and Dr Oeffinger provided institutional liaisons. Ms Kang, Dr Chiarello, Dr Oeffinger, and Dr Maggs provided consultation (including review of manuscript before submission). The authors thank Marcy Polansky, ScD, MSW, School of Public Health, Drexel University, Philadelphia, Pennsylvania; Lawrence Vogel, MD, Shriners Hospitals for Children, Chicago, Illinois; Chester Tylkowski, MD, Shriners Hospitals for Children, Lexington, Kentucky; Anita Bagley, PhD, Shriners Hos-

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pitals for Children, Sacramento, California; George Gorton, BS, Shriners Hospitals for Children, Springfield, Massachusetts; and Mark Abel, MD, and Richard Stevenson, MD, University of Virginia School of Medicine, for their contributions. The authors give special thanks to the research coordinators and the parents, children, and youth who participated in the study. The primary institutional review board approval for this study was granted by Temple University and Drexel University. Institutional review board approval also was obtained from all participating hospitals. A platform presentation related to this study was given at the annual meeting of the American Academy of Cerebral Palsy and Developmental Medicine; September 23–26, 2009; Scottsdale, Arizona. Funding support for this study was provided by Shriners Hospitals for Children (COS #9197). This article was received May 15, 2009, and was accepted August 3, 2009. DOI: 10.2522/ptj.20090162

References 1 Rosenbaum P, Paneth N, Leviton A, et al. A report: the definition and classification of cerebral palsy April 2006. Dev Med Child Neurol Suppl. 2007;109:8 –14. 2 United Cerebral Palsy Web site. Available at: http://www.ucp.org/ucp_generaldoc. cfm/1/9/37/37–37/447#howmany. Accessed December 20, 2008. 3 Hayes MS, McEwen IR, Lovett D, et al. Next step: survey of pediatric physical therapists’ educational needs and perceptions of motor control, motor development and motor learning as they relate to services for children with developmental disabilities. Pediatr Phys Ther. 1999;11:4 – 164. 4 Chiarello LA, O’Neil M, Dichter CG, et al. Exploring physical therapy clinical decision making for children with spastic diplegia: Survey of pediatric practice. Pediatr Phys Ther. 2005;17:46 –54. 5 Palisano RJ. A collaborative model of service delivery for children with movement disorders: a framework for evidence-based decision making. Phys Ther. 2006;86: 1295–1305. 6 International Classification of Functioning, Disability and Health (ICF). Geneva, Switzerland: World Health Organization; 2001. 7 Oliver M. The Politics of Disablement. London, United Kingdom: MacMillan; 1990. 8 Colver A. A shared framework and language for childhood disability. Dev Med Child Neurol. 2005;47:780 –784.

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Social and Community Participation of Children and Youth With Cerebral Palsy 9 Law M, Dunn W. Perspectives on understanding and changing the environments of children with disabilities. Phys Occup Ther Pediatr. 1993;13:1–17. 10 Chen HF, Cohn ES. Social participation for children with developmental coordination disorder: conceptual, evaluation and intervention considerations. Phys Occup Ther Pediatr. 2003;23:61–78. 11 Dijkers MP, Whiteneck G, El-Jaroudi R. Measures of social outcomes in disability research. Arch Phys Med Rehabil. 2000; 81:S63–S80. 12 Lyons RF. Meaningful activity and disability: capitalizing upon the potential of outreach recreation networks in Canada. Can J Rehabil. 1993;6:256 –265. 13 Specht J, King G, Brown E, Foris C. The importance of leisure in the lives of persons with congenital physical disabilities. Am J Occup Ther. 2002;56:436 – 445. 14 Barletta A, Loy DP. The experience of participation in challenger little league through the eyes of a child with physical disability. Am J Recreation Ther. 2006;5:6 –12. 15 McGavin H. Planning rehabilitation: a comparison of issues for parents and adolescents. Phys Occup Ther Pediatr. 1998; 18:69 – 82. 16 King GA, Shultz IZ, Steel K, et al. Selfevaluation and self-concept of adolescents with physical disabilities. Am J Occup Ther. 1993;47:132–140. 17 King GA, Cathers T, Polgar JM, et al. Success in life for older adolescents with cerebral palsy. Qual Health Res. 2000;10: 734 –749. 18 Poulsen AA, Ziviani JM, Cuskelly M, Smith R. Boys with developmental coordination disorder: loneliness and team sports participation. Am J Occup Ther. 2007;61: 451– 462. 19 Stevenson CJ, Pharoah PO, Stevenson R. Cerebral palsy: the transition from youth to adulthood. Dev Med Child Neurol. 1997;39:336 –342. 20 Brown M, Gordon WA. Impact of impairment on activity patterns of children. Arch Phys Med Rehabil. 1987;68:828 – 832. 21 Blum RW, Resnick MD, Nelson R, St Germaine A. Family and peer issues among adolescents with spina bifida and cerebral palsy. Pediatrics. 1991;88:280 –285. 22 McMeeking D, Purkayastha B. “I can’t have my mom running me everywhere”: adolescents, leisure, and accessibility. J Leisure Res. 1995;27:360 –378. 23 Allison KR, Dwyer JJ, Goldenberg E, et al. Male adolescents’ reasons for participating in physical activity, barriers to participation, and suggestions for increasing participation. Adolescence. 2005;40:155–170. 24 Law M, King G, King S, et al. Patterns of participation in recreational and leisure activities among children with complex physical disabilities. Dev Med Child Neurol. 2006;48:337–342. 25 King GA, Law M, King S, et al. Measuring children’s participation in recreation and leisure activities: construct validation of the CAPE and PAC. Child Care Health Dev. 2007;33:28 –39.

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26 Pollock N, Stewart D. A survey of activity patterns and vocational readiness of young adults with physical disabilities. Can J Rehabil. 1990;4:17–26. 27 Maher CA, Williams MT, Olds T, Lane AE. Physical and sedentary activity in adolescents with cerebral palsy. Dev Med Child Neurol. 2007;49:450 – 457. 28 Bjornson KF, Belza B, Kartin D, et al. The relationship of physical activity to health status and quality of life in cerebral palsy. Pediatr Phys Ther. 2008;20:247–253. 29 Magill-Evans J, Darrah J, Adkins R. Youths with cerebral palsy and their satisfaction with recreational services: implications for inclusion. Leisure. 2003/2004;28:71– 86. 30 Mactavish JB, Schleien SJ. Re-injecting spontaneity and balance in family life: parents’ perspectives on recreation in families that include children with developmental disability. J Intellect Disabil Res. 2004;48:123–141. 31 Palisano RJ, Rosenbaum P, Bartlett D, Livingston MH. Content validity of the expanded and revised Gross Motor Function Classification System. Dev Med Child Neurol. 2008;50:744 –750. 32 King GA, Law M, King S, et al. Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC). San Antonio, TX: Harcourt Assessment Inc; 2004. 33 Imms C. Review of the Children’s Assessment of Participation and Enjoyment and the Preferences for Activity of Children. Phys Occup Ther Pediatr. 2008;28:389 – 404. 34 Palisano RJ, Rosenbaum P, Walter S, et al. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997;39:214 –223. 35 Young NL. The Activities Scale for Kids Manual. Toronto, Ontario, Canada: The Hospital for Sick Children; 1994. 36 Palisano RJ, Copeland WP, Galuppi BE. Performance of physical activities by adolescents with cerebral palsy. Phys Ther. 2007;87:77– 87. 37 Orlin M, Palisano RJ, Chiarello LA, et al. Participation in home, extracurricular, and community children and youth with cerebral palsy. Dev Med Child Neurol. In press. 38 Bandura A. Self-Efficacy: The Exercise of Control. New York, NY: WH Freeman; 1997. 39 Lepage C, Noreau L, Bernard PM. Association between characteristics of locomotion and accomplishment of life habits in children with cerebral palsy. Phys Ther. 1998;78:458 – 469. 40 Palisano RJ, Almasri N, Chiarello L, et al. Family needs of parents of children and youth with cerebral palsy. Child Care Health Dev. In press. 41 Antle BJ, Mills W, Steele C, et al. An exploratory study of parents’ approaches to health promotion in families of adolescents with physical disabilities. Child Care Health Dev. 2007;34:185–193.

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42 Mactavish J, Schlieren S, Tabourne C. Patterns of family recreation in families that include children with a developmental disability. J Leisure Res. 1997;29:21– 46. 43 Orthner DK, Mancini JA. Leisure impacts on family interaction and cohesion. J Leisure Res. 1990;22:125–137. 44 Havisghurst R. Developmental Tasks and Education. 3rd ed. New York, NY: D. McKay Co; 1972. 45 Hanna SE, Rosenbaum PL, Bartlett DJ, et al. Stability and decline in gross motor function among children and youth with cerebral palsy ages 2 to 21 years. Dev Med Child Neurol. 2009;51:295–302. 46 Berry ET, McLaurin SE, Sparling JW. Parent/caregiver perspectives on the use of power wheelchairs. Pediatr Phys Ther. 1996;8:146 –150. 47 Palisano RJ, Shimmell LJ, Stewart D, et al. Mobility experiences of adolescents with cerebral palsy. Phys Occup Ther Pediatr. 2009;29:135–155. 48 Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall; 1986. 49 Brollier C, Shepherd J, Markley KF. Transition from school to community living. Am J Occup Ther. 1994;48:346 –353. 50 Sloper P, Turner S. Service needs of families of children with severe physical disability. Child Care Health Dev. 1992;18: 259 –282. 51 Ellis JT, Luiselli JK, Amirault D, et al. Families of children with developmental disabilities: assessment and comparison of self-reported needs in relation to situational variables. J Dev Phys Disabil. 2002; 14:191–202. 52 Nitta O, Taneda A, Nakajima K, Surya J. The relationship between the disabilities of school-aged children with cerebral palsy and their family needs. J Phys Ther Sci. 2005;17:103–107. 53 Mihaylov SI, Jarvis SN, Colver AF, Beresford B. Identification and description of environmental factors that influence participation of children with cerebral palsy. Dev Med Child Neurol. 2004;46:299 –304. 54 Whiteneck GG, Fougeyrollas P, Gerhart KA. Elaborating the model of disablement. In: Fuhrer M, ed. Assessing Medical Rehabilitation Practices: The Promise of Outcomes Research. Paul H Brookes Publishing Co; 1997. 55 Pollock N, Stewart D. Occupational performance needs of school-aged children with physical disabilities in the community. Phys Occup Ther Pediatr. 1998;18: 55– 68. 56 Eriksson L, Granlund M. Conceptions of participation in students with disabilities and persons in their close environment. J Dev Phys Disabil. 2004;16:229 –245. 57 Law M. Participation in the occupations of everyday life. Am J Occup Ther. 2002;56: 640 – 649. 58 Rauscher L, Greenfield BH. Advancements in contemporary physical therapy research: use of mixed methods designs. Phys Ther. 2009;89:91–100.

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Research Report

Gait Variability Detects Women in Early Postmenopause With Low Bone Mineral Density Kerstin M. Palombaro, Laurita M. Hack, Kathleen Kline Mangione, Ann E. Barr, Roberta A. Newton, Francesca Magri, Theresa Speziale

Background. Women in early postmenopause and with low bone mineral density (BMD) may exhibit early markers for physical frailty as a result of sarcopenia and osteopenia. Objective. The purpose of this study was to determine whether women in early postmenopause and with low BMD exhibit decreased physical performance and differences in gait variability and fall and fracture rates.

Design. This study was an observational cohort design with participants assigned to groups on the basis of BMD status.

Methods. Fifty-four women, 31 with low BMD and 23 with normal BMD, participated. This study was conducted in a university research facility. Physical performance was measured by assessment of dynamic balance (timed backward tandem walk test), strength (handheld dynamometry of isometric quadriceps muscle force production), and free gait speed. Gait variability was assessed on the basis of the coefficient of variation for temporal-spatial gait characteristics. Falls and fractures were assessed for the year after initial testing.

Results. Significant between-group differences were found for step time and stance time variability.

Limitations. The limitations of this study included group assignment on the basis of the results of the most recent bone density scan within the preceding 2 years.

Conclusions. Women in early postmenopause and with low BMD exhibited increased gait variability in step time and stance time but did not exhibit differences in balance, strength, or gait speed. Gait variability may be more sensitive for detecting differences in women in early postmenopause and with or without low BMD than more typical measures of physical performance.

K.M. Palombaro, PT, PhD, is Community Engagement Coordinator, Institute for Physical Therapy Education, Widener University, One University Pl, Chester, PA 19013 (USA). Address all correspondence to Dr Palombaro at: kpalombaro@ mail.widener.edu. L.M. Hack, PT, DPT, PhD, MBA, FAPTA, is Professor, Department of Physical Therapy, Temple University, Philadelphia, Pennsylvania. K.K. Mangione, PT, PhD, GCS, is Professor, Department of Physical Therapy, Arcadia University, Glenside, Pennsylvania. A.E. Barr, PT, DPT, PhD, is Chair and Professor, Department of Physical Therapy, Thomas Jefferson University, Philadelphia, Pennsylvania. R.A. Newton, PT, PhD, FGSA, is Professor, Department of Physical Therapy, Temple University. F. Magri, PT, DPT, is an orthopedic physical therapy resident at Drayer Physical Therapy Institute, Harrisburg, Pennsylvania. T. Speziale, PT, DPT, is Physical Therapist, Drayer Physical Therapy Institute, Camp Hill, Pennsylvania. [Palombaro KM, Hack LM, Mangione KK, et al. Gait variability detects women in early postmenopause with low bone mineral density. Phys Ther. 2009;89: 1315–1326.] © 2009 American Physical Therapy Association

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

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P

hysical frailty describes a process in which multiple organ systems deteriorate. This deterioration both results from and causes physical inactivity.1 Markers for frailty include osteopenia, which is the loss of bone tissue, and sarcopenia, which is the loss of muscle tissue.2 As women age, their risk for frailty increases.3 Physical frailty contributes to dependency in daily tasks,4 longer periods of disability after illness,4 and increased mortality.5,6

More than 44 million Americans 50 years of age or older have osteoporosis or osteopenia, with women representing 30 million of those cases.7 People are diagnosed with osteopenia when their bone mineral density (BMD), determined by dual x-ray absorptiometry (DXA) scanning, falls between 1.1 and 2.5 standard deviations below the mean for adults who are healthy; people are diagnosed with osteoporosis when their BMD falls more than 2.5 standard deviations below the mean for adults who are healthy.7 Osteoporosis is a systemic skeletal disease that is marked by decreased bone mineral mass and compromises in bone architecture.8 Women with primary osteoporosis, that is, bone demineralization attributable to aging and menopause, are at increased risk for frailty9 because they experience greater loss of muscle and bone tissue than their peers who are healthy.10

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 October 15, 2009, at www.ptjournal.org.

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One definition of frailty is a syndrome in which 3 or more of the following criteria are present: unintentional weight loss of greater than 4.5 kg (10 lb) in a year and selfreported exhaustion, weakness, decreased physical activity, and slow walking speed.5 Free gait speed is predicted by knee extensor muscle strength (force-generating capacity)11 and is correlated with BMD at various skeletal sites.12 Variability in temporal-spatial gait characteristics, such as step width and step length, has been investigated in other studies in relation to both falls13–15 and the transition to frailty.16 Because older women with osteoporosis tend to be more frail than their peers who are healthy,17 women in early postmenopause and with low BMD may exhibit early markers for physical frailty, including changes in balance and gait. Sarcopenia associated with aging and frailty is related to poorer physical performance,18 –23 which in turn could result in falls.3 Approximately half of women who are postmenopausal will sustain an osteoporosisrelated fracture in their lifetime, and 15% will sustain a hip fracture. If women in early postmenopause are at risk for frailty, their risk of fracture from an injurious fall may be elevated because of low BMD8 as well as weakness and impaired balance.24 To date, no studies have examined these variables in women in early postmenopause and with low BMD. If deficits in balance, strength, and gait were identified in this population, then physical performance measures could provide an earlier indication of risk for frailty. The primary aim of this study was to determine whether women in early postmenopause and with low BMD exhibit poorer performance in dynamic balance, quadriceps femoris muscle strength, and free gait speed than women without low BMD. The

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secondary aims were to determine whether women in early postmenopause and with or without low BMD exhibit differences in variability in temporal-spatial gait characteristics and to determine whether there are differences in fall and fracture rates in the year after initial testing.

Method Study Design This study was an observational cohort study. Participants were assigned to groups on the basis of BMD status. Participants were assigned to the low BMD group if their BMD was ⱖ2.0 standard deviations below the mean for adults who are healthy at one or more skeletal sites in accordance with the DXA scan results.8 The results of each DXA scan were confirmed by the radiologist’s written DXA scan report. Participants were assigned to the normal BMD group if their BMD was within 1.0 standard deviation of the mean for adults who are healthy. Participants were excluded from the latter group when any skeletal site had a bone density of 1.1 to 1.9 standard deviations below the mean for adults who are healthy. This exclusion criterion recognizes that although severe osteopenia is defined as 2.0 standard deviations below the mean for adults who are healthy,25 the range of 1.1 to 1.9 is still classified as osteopenia. All testing occurred at Arcadia University. Pilot testing was conducted to estimate sample size. Eight women, 4 with low BMD and 4 with normal BMD, completed the pilot testing. These women had a mean (SD) age of 59.1 (3.1) years; had been postmenopausal for, on average, 6.3 (SD⫽2.2) years; had a mean (SD) body mass index (BMI) of 24.3 (1.5) kg/m2; and had a mean (SD) physical activity level of 2,214.1 (189.8) kcal/d, as determined with the Stanford 7-Day Physical Activity Recall Questionnaire. Results from the pilot study indicated that women December 2009

Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause in early postmenopause and with low BMD exhibited differences in backward tandem walk time and quadriceps femoris muscle strength compared with their peers who were healthy. Effect sizes were large (r⫽⫺.75) for backward tandem walk time and medium for the strength of both quadriceps femoris muscles (r⫽.43). The study was powered with a medium effect size because it represented the lowest effect size for the specific aims. Given a power of at least 0.80, a medium effect size of r⫽.43, and an alpha level of .05, a target sample of 28 women per group, for a total of 56 participants, was assumed.26 Data collection for the main study took place from August 2006 to April 2007. Performance data were collected in one session, which lasted approximately 1 hour. Participants were contacted by telephone 1 year after performance testing. Participants Participants were recruited through informational flyers placed in Arcadia University–area community buildings for people aged 55 years and older, churches, gymnasiums, synagogues, physical therapy clinics, and libraries and advertisements placed in church bulletins and local newspapers. A total of 82 women responded to recruitment flyers and advertisements. After potential participants made contact with the principal investigator (K.M.P.), they were telephoned and screened with inclusion and exclusion criteria. To be considered for inclusion in the study, participants had to be community-dwelling women who were 50 to 65 years of age and 3 to 10 years after menopause, who had DXA test results from within the preceding 2 years, and who were able to ambulate independently. Years after menopause was assessed by reading the definition of menopause, which is “cessation of the menstrual period for a December 2009

Figure 1. Flow diagram of study recruitment. BMD⫽bone mineral density, BMI⫽body mass index.

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause Table 1. Demographic Characteristics of Participants Values for Participants With the Following Bone Mineral Density: Low (nⴝ31) Characteristic Age, y Years after menopause Body mass index (kg/m2) Physical activity level

a

Normal (nⴝ23)

X (SD)

Range

X (SD)

Range

P

59.19 (3.30)

52.00–65.00

58.13 (3.33)

51.00–65.00

.125

6.19 (2.56)

3.00–10.00

5.89 (2.33)

3.00–10.00

.329

23.52 (3.09)

18.30–29.20

26.33 (3.60)

19.30–32.30

.002a

2,290.61 (376.32)

1,517.82–3,161.13

2,683.79 (573.05)

1,568.29–3,719.57

.003a

No. of medications

2.77 (1.89)

0.00–7.00

2.39 (2.31)

0.00–8.00

.253

No. of comorbidities

1.84 (1.79)

0.00–7.00

1.83 (1.67)

0.00–6.00

.490

Habitual gait speed (m/s)

1.35 (0.17)

1.03–1.69

1.38 (0.20)

0.96–1.73

.260

Fast gait speed (m/s)

1.96 (0.18)

1.53–2.44

2.03 (0.23)

1.56–2.24

.105

Statistically significant.

span of time of at least 12 months,”27 and then asking, “At what age did your period cease?” Participants were excluded if they were organ transplant recipients, had active, severe liver or kidney disease, were undergoing chemotherapy or renal dialysis, had chemical menopause or menopause because of oophorectomy, had chronic, severe cardiac or pulmonary disease, had a history of bone cancer or bone metastases, used corticosteroids for a long period of time, or had medical issues that affected the lower extremities and that, in turn, could affect ambulation. Examples of such medical issues were joint replacement; joint inflammation causing swelling, tenderness, or both; lowerextremity surgery within the preceding 6 months; or neurological diseases that could affect ambulation, such as Parkinson disease, multiple sclerosis, or residual weakness from a cerebrovascular accident. Twentyfour women did not meet all of the inclusion criteria (age, n⫽1; years after menopause, n⫽12; DXA scan test date, n⫽2; chronic lung disease or use of asthma inhalers, n⫽2; menopause because of oophorectomy, n⫽4; lower-extremity joint replacement, n⫽2; and neurological 1318

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disease affecting the lower extremities, n⫽1), and 1 woman declined to participate without financial compensation. Potential participants who met the inclusion criteria were scheduled for assessment. Participants were informed of the study objectives and provided written informed consent before data collection. Fifty-seven women, 33 with low BMD and 24 with normal BMD, participated in the testing for this study. Two participants were excluded from the low BMD group because their physical activity levels were greater than 2 standard deviations above the participant mean (4,130.23 and 4,166.20 kcal/d, respectively), and 1 participant was excluded from the normal BMD group because both her physical activity level and BMI were greater than 2 standard deviations above the group mean (3,953.73 kcal/d and 42.2, respectively) (Fig. 1). Four participants (3 in the normal BMD group and 1 in the low BMD group) were lost to follow-up for the 1-year evaluation of falls and fractures despite numerous attempts to contact them.

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Demographic Variables The participants completed a demographic and health status questionnaire that included questions about age, number of years after menopause, date and results of the last DXA scan, medical history, current medications, and use of calcium and vitamin D supplements. With the exception of the DXA scan results, these variables are associated with BMD,28 –31 physical performance,32–34 or both. Participants’ height (in meters) and weight (in kilograms) were measured on a calibrated physician scale,* and BMI (kg/ m2) was calculated from these values. The BMI was calculated because it is associated with sarcopenia35 and BMD.28 Next, the participants were administered the Stanford 7-Day Physical Activity Recall Questionnaire.36 Physical activity level was measured as a potential covariate because activity level could affect both physical performance37–39 and BMD.40 The Stanford 7-Day Physical Activity Recall Questionnaire was selected because it has been used with both older women41 and women who are post* Health O Meter Inc, 11800 S Austin Ave, #B, Alsip, IL 60803.

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause menopausal and have low BMD.42– 45 This questionnaire asks people to recall the number of hours slept each night as well as the number of hours spent in moderate, hard, and very hard activities during the preceding 7 days. Examples of moderate, hard, and very hard physical, social, and occupational activities are provided to each individual. A description of exertion levels also is provided. Energy expenditure is calculated from the numbers of hours spent in sleep and in activity and is reported as kilocalories per day. The reliability36 and validity46 of Stanford 7-Day Physical Activity Recall Questionnaire scores have been reported. Of the 57 women who participated in the testing for this study, 55 were white and 2 were African American. On average, the women were 58.8 (SD⫽3.3) years of age and had been postmenopausal for 6.1 (SD⫽2.5) years. Analysis of the results indicated significant between-group differences for BMI and level of physical activity. Participants with low BMD had a mean BMI that fell within the healthy category, and those with normal BMD had a mean BMI that fell in the overweight category. Participants with low BMD had a mean (SD) physical activity level of 2,290.61 (376.32) kcal/d, or 13 h/wk, and those with normal BMD had a mean (SD) physical activity level of 2,683.79 (573.05) kcal/d, or 15 h/wk. All participants walked at speeds that exceeded reported thresholds for successful community ambulation, such as crossing the street within the timing of a traffic light (1.0 –1.2 m/s).47 The most common types of medications included over-the-counter supplements, daily aspirin, statins, and osteoporosis medications for participants in the low BMD group. The most common comorbidities were high cholesterol levels and hypothyroidism (Tab. 1). December 2009

Physical Performance Variables Physical performance measures included assessment of dynamic balance, quadriceps femoris muscle strength, and gait. The order of testing was the same for all participants. Dynamic balance was assessed with a timed, backward tandem walk test.48,49 Participants were instructed to walk backward as quickly as possible in a heel-to-toe fashion on a 2.44-m line. This test is timed with a stopwatch.37 Participants were allowed 1 practice trial to become accustomed to the testing procedure. They then performed 2 trials of the test. The time for the 2 trials was recorded in seconds, and the mean time for the 2 trials was calculated. This test was selected to minimize the ceiling effect that can occur when subjects under age 65 are tested; other balance measures that use ordinal scales, such as the Berg Balance Scale, have a documented ceiling effect for such subjects.50 The backward tandem walk test has been used for older adults49 and people with osteoporosis.48 The validity of the backward tandem walk test for isokinetic knee extension strength has been reported.49 Isometric quadriceps femoris muscle force production for each leg was measured with a MicroFET 2 handheld dynamometer.† Participants sat upright on a plinth of sufficient height to prevent the feet from touching the floor. The upper thighs were strapped to the plinth to prevent compensatory movements, and the knees were flexed to 90 degrees.51 The dynamometer was placed on the anterior tibia just proximal to the malleolus.51 Participants were asked to push as hard as possible for 5 seconds while the investigator matched the resistance (make test). The left lower extremity was tested first. Participants performed 2 † Hogan Health Industries, 8020 South 1300 West, West Jordan, UT 84084.

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practice trials and then a minimum of 2 maximal-effort trials with a 1-minute rest period between the trials. The peak force for each trial was recorded, and the mean for the 2 trials was calculated.52 In the event that the 2 trials were not within 10% of each other (⬃50% of the participants), additional trials were performed. The quadriceps femoris muscle complex was chosen because quadriceps femoris muscle strength has been found to predict gait speed11 and is associated with static and dynamic balance in women with osteoporosis.42 Handheld dynamometry has been reported to have reliability42 and validity.53 Handheld dynamometry52 and similar testing procedures42– 44 have been used to assess lowerextremity strength in women with osteoporosis. Free gait speed data were collected with the GaitMat II‡ to determine temporal and spatial gait characteristics. The GaitMat II is a 3.87-m walkway containing pressure-sensitive switches54 (Fig. 2). Free gait speed was chosen as a variable because walking speed is one of the criteria included in the definition of frailty.5 The participants completed 2 trials of free speed with the instruction to “walk across the mat at your normal speed.” Individually determined rest periods were given between the trials. Gait variability was calculated from the walking trials as the coefficient of variation of free speed step length, stride length, step width, step time, and stance time as described by Brach et al13 (Fig. 1). The coefficient of variation, calculated as (standard deviation/mean) ⫻ 100,13 represents the variability within a distribution of numbers. The reliability and validity of data obtained with the GaitMat II have been reported.54

‡ E.Q. Inc, PO Box 16, Chalfont, PA 189140016.

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Figure 2. (A) GaitMAT II System. (B) Step length, defined as the distance between contacts of the contralateral extremities. Step length is defined with respect to the advancing limb.77 (C) Step width, defined as the lateral distance between contralateral footfalls. Thus, right step width is defined with respect to the left trailing limb and left step width is defined with respect to the right trailing limb.77 (D) Stride length, defined as the distance from the contact of one foot to the subsequent contact of the same foot. Initial contact typically is used as the measurement reference. One stride represents the completion of one cycle of gait.77 (E) Step time, defined as the time necessary to complete a right or left step length.77 (F) Stance time, defined as the time a limb is in contact with the ground.77 Photographs used with permission of E.Q. Inc. 1320

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause Table 2. Results of Data Analysis of Primary Variables Results of Analysis of Variance for Groups

X (SD) for Participants With the Following Bone Mineral Density: Low (nⴝ31)

Variable Backward tandem walk time (s)

10.04 (3.65)

Normal (nⴝ23)

F 1.54

.221

Right quadriceps femoris muscle force output (N)

155.8 (30.57)

166.4 (35.6)

1.39

.244

Left quadriceps femoris muscle force output (N)

151.2 (28.20)

154.7 (36.2)

0.274

.603

0.447

.507

Free gait speed (m/s)

1.35 (0.17)

8.76 (3.89)

P

1.39 (0.20)

Table 3. Results of Analysis of Variance (ANOVA) for Gait Variabilitya X (SD) CV for Participants With the Following Bone Mineral Density: Low

Normal

F

P

Step length

0.03 (0.016)

0.03 (0.012)

0.386

.537

Step width

0.17 (0.224)

0.12 (0.084)

1.130

.293

Stride length

0.02 (0.013)

0.02 (0.013)

2.071

.156

Step time

0.09 (0.13)

0.03 (0.02)

4.323

.043b

Stance time

0.07 (0.09)

0.03 (0.02)

4.064

.049b

Variable

a b

Results of ANOVA for Groups

CV⫽coefficient of variation. Statistically significant.

Data on Falls and Fractures Data on falls and fractures were collected for the year after initial testing. Participants were contacted 1 year from their initial test date and were provided with the definition of a fall: “A fall is defined as unintentionally coming to rest on the ground, floor, or other lower level.”55(p1619) Participants then were asked whether they had fallen in the preceding year and, if so, how many falls they had sustained. Participants also were asked whether they had sustained any fractures or broken bones in the preceding year and, if so, which bones they had broken. They were not questioned about the circumstances of the fall or whether a hospitalization resulted from the fall. Data Analysis All data were analyzed with SPSS software, version 14.0.§ Descriptive §

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

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statistics were determined for all demographic and health-related variables. Data were excluded from the analyses when a participant’s physical activity level or BMI exceeded 2 standard deviations of the group mean to prevent outliers from skewing the results. Independent sample t tests were performed to assess between-group differences for all demographic variables and to assess potential between-group differences between the pilot sample and the full-study sample for both the low BMD group and the normal BMD group. Analyses of variance were performed to test differences in physical performance variables (primary aim) and differences in gait variability (secondary aim). Chi-square analyses were performed to test differences in rates of falls and fractures (secondary aim). We treated falls and fractures as dichotomous variables instead of using the numbers of falls

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and fractures as metrics. Statistical significance was set at P⬍.05. Role of the Funding Source This study was funded, in part, by grants from the Pennsylvania Physical Therapy Association and the Section on Women’s Health of the American Physical Therapy Association. The funding received for this study allowed for office supply costs, such as postage and purchases of paper and statistical software; photocopying costs; advertising costs for recruitment purposes; and partial salary support for the principal investigator (K.M.P.). The principal investigator was required to submit a poster presentation of preliminary results to the Pennsylvania Physical Therapy Association and one article related to her dissertation to the Journal of Women’s Health Physical Therapy as part of the funding stipulations. This study was conducted in partial fulfillment of Dr Palombaro’s doctoral degree.

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Results There were no significant betweengroup differences in backward tandem walk time, free gait speed, or isometric quadriceps femoris muscle force. However, women with low BMD had poorer balance (slower times on the backward tandem walk test), slower walking speeds, and less strength (isometric quadriceps femoris muscle force) than women with normal BMD (Tab. 2). Significant between-group differences were found for step time and stance time variability. Additionally, a tendency toward increased variability in step width was found for the low BMD group (Tab. 3). Nine women with low BMD (30%) and 5 women with normal BMD (25%) sustained at least 1 fall in the year after physical performance testing. Two women with low BMD sustained a total of 3 fractures. These differences were not statistically significant.

Discussion The primary aim of the present study was to address potential physical performance differences in women in early postmenopause and with or without low BMD. Although there was a tendency for women in early postmenopause and with low BMD to demonstrate poorer performance in the physical performance measures than their peers with normal BMD, no statistically significant differences were found. The tendency toward poorer performance did not translate to clinically meaningful between-group differences for balance (1.28 seconds) and strength (4.58 –10.63 N). Although other studies12,42,44 have demonstrated that women in late postmenopause and with low BMD exhibit significantly poorer physical performance in measures of balance, quadriceps femoris muscle strength, and gait speed, the differences in samples as well as the types of tools 1322

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used to measure physical performance may partially explain the conflicting results. In the present study, on average, women were 59 years of age and had been postmenopausal for 6 years, had a mean BMI of 25 kg/m2, and had a mean physical activity level of 2,457.65 kcal/d (14 hours of activity per week). In earlier research, subjects had an age range of 68.3 to 69.4 years, a BMI range of 24.7 to 25.9 kg/m2, and total physical activity times ranging from 6 to 21 h/wk.12,42,44 Two studies included women who had been postmenopausal for at least 5 years,42,44 and 1 study did not have minimum or maximum cutoffs for years after menopause.12 Thus, the subjects in earlier research were, on average, older, more sedentary, and likely to be in late postmenopause because of age and menopause inclusion criteria. The between-group differences in these studies12,42,44 may have been larger because of the effects of aging and physical activity on bone density and physical performance. Finally, the tests and measures used in the present study to assess physical performance and activity levels may not be sensitive enough to detect changes at the level of functional limitations in women in early postmenopause. Earlier research focusing on women in late postmenopause revealed a relationship between physical performance and BMD.12,42,44 Our results for dynamic balance and isometric force output testing contrasted with those in the studies of Carter et al,42 and Liu-Ambrose et al,44 who found associations of quadriceps femoris muscle strength and dynamic balance (as measured with the Figureof-8 Test) with BMD in older women (mean age of ⬎65 years) who were postmenopausal. Our free gait speed results also differed from the findings of Lindsey et al,12 who reported an association between free gait speed and BMD.

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A secondary aim of the present study was to explore more-sensitive measures of gait variability to determine whether subtle changes were occurring in gait at the level of impairment. Our study revealed statistically significant differences in step time and stance time; women with low BMD exhibited increased variability in both of these variables. Women with low BMD also demonstrated a tendency toward increased step width variability. As in our study, Hausdorff et al15 found increased stance time variability in older adults who had fallen. Maki14 found increased step time variability and a tendency toward step width variability in older adults who had fallen. Brach et al13 found an association between increased step width variability and falls in older adults walking at normal speeds. Kressig et al16 found that stride length variability increased in older adults who were transitioning to frailty, a finding that supports the hypothesis that spatial gait characteristics may change before changes in strength and balance are detectable. Because step width variability may be a more-sensitive measure for differentiating people who have fallen from those who have not fallen, step time and stance time may be more-sensitive measures for detecting progression to frailty in women in early postmenopause. In earlier research on gait variability,13–16 older adults with mean ages ranging from 79 to 82 years were examined. The participants in our sample, with a mean age of 59 years, represent an earlier point on the age continuum of gait variability. However, the percentage differences in variability between the group with low BMD and the group with normal BMD in the variables of step time (9% versus 7%) and step width (17% versus 12%) mirror the findings of Brach et al.13 Our findings may indicate that women with low BMD are beginning to experience some balance December 2009

Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause instability. This notion is supported by our finding of a tendency toward increased time on the backward tandem walk test in women with low BMD. Another aim of the present study was to determine whether there were differences in fall and fracture rates between women who were in early postmenopause and had low BMD and women who were in early postmenopause and did not have low BMD. Although no significant between-group differences were found, 9 women with low BMD (30%) fell, and 2 women with low BMD sustained a total of 3 fractures. The percentage of falls in our sample of women with osteoporosis mirrors the reported rate of falls of 32%,56 whereas the percentage of fractures in women in the low-BMD group who fell (10%) exceeds the reported rate of fractures of 2.8% in the age group of 50 to 64 years.57 The detection of differences in gait variability and at the level of functional limitations in balance, strength, and gait speed was explored as a possible method for detecting and thus preventing58 early frailty. Poorer performance on tasks related to functional limitations may be subtle in a younger cohort of women. Fried et al59 defined preclinical disability as an increase in the time needed to complete a task, modification of a task, or a decrease in the frequency of task performance. In community-dwelling people, compensatory strategies may mask early changes that indicate the potential to progress to frailty.60 Compensatory strategies may have accounted for the tendency toward poorer performance in all physical performance tasks and the significant differences in gait variability observed in the present study. Physical activity level and resultant BMI may have been important mediDecember 2009

ators in the present study. Participants in the low-BMD group had a significantly lower BMI and lower activity levels than those in the group with normal BMD. Changes in total daily physical activity are associated with 3-year changes in mobility performance, as measured by deficits in the time needed to rise from a chair and timed walking.61 Physical activity and mobility limitations were found to be mediated by knee extension strength in a sample of 3,075 adults who were 70 to 79 years of age.62 Increasing physical activity levels from the onset of middle age results in a slower progression of functional limitations and prevention of disability.61,63,64 Although women with low BMD in the present study exhibited significantly lower physical activity levels than women with normal BMD, there were no observable deficits in balance, strength, and gait speed. Addressing physical activity in women in early postmenopause and with low BMD (similar to the women in our sample) might serve as a preventative intervention to limit progression to frailty. Clinical Relevance Early detection of functional limitations and disability is vital to preventing frailty.58 A recently published consensus report recommended focusing on domains such as mobility, muscle strength, balance, endurance, fatigue, and physical activity in older adults who are likely at risk for frailty because these areas are strong, independent predictors of frailty.65 That report also emphasized that interventions to prevent frailty should target people most likely to benefit. Those who would likely benefit the most might be similar to the women in the present study who, although not exhibiting changes in physical performance measures, were beginning to demonstrate changes in the more-sensitive measure of gait variability.

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As part of their role in health and wellness promotion, clinicians should ask women who are in early postmenopause (women in their mid-40s to mid-50s) and are being seen by physical therapists for examination or screening whether they have had a DXA scan and what the DXA scan results were. Although most clinicians do not have access to instrumented gait analysis systems, they nevertheless should be aware that women in early postmenopause and with low BMD might have subtle changes in gait variability that are not detected by more-typical measures of physical performance, such as balance, strength, and gait speed. Knowledge that potential subclinical changes could be occurring would allow physical therapists to provide their patients in early menopause with education about the benefits of regular physical activity that includes weight-bearing and resistance exercises66 to preserve physical function3,18,21,63 and to reduce the risk of injurious falls.37,43 Clinicians could use the results of a physical activity questionnaire as a starting point for patient education because patient education programs about selfmanagement of osteoporosis have been reported to be successful.67 Physical activity could be assessed with standardized tools, such as the one used in the present study (Stanford 7-Day Physical Activity Recall Questionnaire), or tools that might be less time-consuming, such as the Rapid Assessment of Physical Activity68 and the International Physical Activity Questionnaire.69 These tools might be more useful in a clinical setting. Such programs would address prevention of the transition to frailty in women in late postmenopause and with low BMD while simultaneously addressing factors that lead to injurious falls in adults. A dose-response effect of exercise on fracture risk has been reported in the literature, with higher activity levels Number 12

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause being related to lower fracture risk.70,71 This finding has particular bearing in younger people with low BMD, who may be at risk for distal radius fractures. Distal radius fractures often are the initial symptom of low BMD.72 People who are 50 years of age and sustain a distal radius fracture have a 17% lifetime risk of hip fracture; the risk in the general population is 11%.73 These findings support physical therapist interventions that target frailty-related musculoskeletal changes with the aim of reducing injurious falls in women with low BMD. Additionally, there is a lack of published literature about physical performance variables in women in early postmenopause. Although no between-group differences in measures of balance, strength, and gait speed were found in the present study, the physical performance data from this study can provide clinicians with initial values with which to compare measures from their own patients in early postmenopause. Limitations There were several limitations of the present study. The pilot study results indicated significant between-group differences in balance and strength. The study was powered with a medium effect size. Power was reanalyzed at the completion of data collection. Effect size was small for all variables and indicated that 175 women would have to be recruited to detect between-group differences. Data analysis showed that the pilot sample was different from the full-study sample for all variables for the low-BMD group and for mean quadriceps femoris muscle force output for the group with normal BMD. These differences might have resulted in underpowering of the present study. Replicating the study with a larger sample might demonstrate between-group differences in measures of physical performance. 1324

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Additionally, a larger sample might have introduced greater variability in demographic variables, such as the number of years after menopause or age, which are mediators of bone density. The lack of variability in these variables inhibited the consideration of their impact on BMD and physical performance. Another limitation was that leg length was not measured; therefore, step length was not adjusted for leg length. No significant betweengroup differences were found for height, but without adjustment for leg length. It is unknown whether the between-group differences for gait speed were larger or smaller than those in the unadjusted data. A final limitation was the reliance on the results of the most recent DXA scan to categorize BMD status. Current guidelines for DXA scanning suggest testing every 2 years for people with osteopenia or osteoporosis and every 5 years for people with normal BMD.74 –76 In an attempt to be more stringent, we required all participants to have had a DXA scan within the preceding 2 years. It would have been most accurate to test participants’ BMD just before group assignment because some women with normal BMD, as determined from their most recent DXA scan, might have been categorized in the low-BMD group or excluded when their BMD fell into the range of 1.1 to 1.9 standard deviations below the mean. However, the physical performance of the 2 groups was similar, so this limitation in methods might not have affected the final results of the present study.

Conclusion The results of the present study demonstrated a tendency toward poorer physical performance and a tendency toward increased rates of falls and fractures in women in early postmenopause and with low BMD but

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no significant between-group differences. Significantly increased step time and stance time variability and a tendency toward increased step width variability were found. Gait variability might be more sensitive than more typical measures of physical performance for detecting differences in women in early postmenopause and with or without low BMD. The subtle changes in gait variability observed in the present study indicated a need for preventive physical therapist interventions to maintain and improve current physical functioning in women in early postmenopause and with low BMD, thus addressing the potential for the transition to frailty in this population. Research examining physical performance in a wider age range of women in postmenopause and with or without low BMD might help to identify the point at which the progression to frailty occurs and would provide a more complete description of the transition to frailty in women in early postmenopause and with low BMD. Dr Palombaro, Dr Hack, Dr Mangione, Dr Barr, and Dr Newton provided concept/ idea/research design and writing. Dr Palomaro provided data collection, project management, fund procurement, and participants. Dr Palombaro, Dr Hack, Dr Magri, and Dr Speziale provided data analysis. Dr Hack provided facilities/equipment. Dr Hack and Dr Newton provided institutional liaisons. Dr Hack, Dr Mangione, Dr Barr, and Dr Newton provided consultation (including review of manuscript before submission). This study was conducted in partial fulfillment of Dr Palombaro’s doctoral degree. The institutional review boards for the protection of human subjects of Arcadia University, Widener University, and Temple University approved the examination procedures before data collection. This study was funded, in part, by grants from the Pennsylvania Physical Therapy Association and the Section on Women’s Health of the American Physical Therapy Association.

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause A poster containing the physical performance data was presented at the Pennsylvania Physical Therapy Association Annual Conference; October 26 –28, 2007; Pittsburgh, Pennsylvania. This article was received December 16, 2008, and was accepted August 3, 2009. DOI: 10.2522/ptj.20080401

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14 Maki BE. Gait changes in older adults: predictors of falls or indicators of fear. J Am Geriatr Soc. 1997;45:313–320. 15 Hausdorff JM, Rios DA, Edelberg HK. Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil. 2001;82:1050 – 1056. 16 Kressig RW, Gregor RJ, Oliver A, et al. Temporal and spatial features of gait in older adults transitioning to frailty. Gait Posture. 2004;20:30 –35. 17 Lane JM, Russell L, Khan SN. Osteoporosis. Clin Orthop Relat Res. 2000:139 –150. 18 Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc. 2002;50:889 – 896. 19 Riggs BL, Melton LJ III. The prevention and treatment of osteoporosis. N Engl J Med. 1992;327:620 – 627. 20 Judge JO, Underwood M, Gennosa T. Exercise to improve gait velocity in older persons. Arch Phys Med Rehabil. 1993;74: 400 – 406. 21 Rantanen T, Guralnik JM, Sakari-Rantala R, et al. Disability, physical activity, and muscle strength in older women: the Women’s Health and Aging Study. Arch Phys Med Rehabil. 1999;80:130 –135. 22 Vetta F, Ronzoni S, Taglieri G, Bollea MR. The impact of malnutrition on the quality of life in the elderly. Clin Nutr. 1999;18: 259 –267. 23 Dutta C. Significance of sarcopenia in the elderly. J Nutr. 1997;127:992S–993S. 24 Stone KL, Seeley DG, Lui LY, et al. BMD at multiple sites and risk of fracture of multiple types: long-term results from the study of osteoporotic fractures. J Bone Miner Res. 2003;18:1947–1954. 25 Siris ES, Chen YT, Abbott TA, et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med. 2004;164:1108 –1112. 26 Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Erlbaum Associates; 1988. 27 Greendale GA, Lee NP, Arriola ER. The menopause. Lancet. 1999;353:571–580. 28 Johnell O. Advances in osteoporosis: better identification of risk factors can reduce morbidity and mortality. J Intern Med. 1996;239:299 –304. 29 Heaney RP. Bone mass, nutrition, and other lifestyle factors. Am J Med. 1993;95: 29S–33S. 30 Dhesi JK, Moniz C, Close JC, et al. A rationale for vitamin D prescribing in a falls clinic population. Age Ageing. 2002;31: 267–271. 31 Bischoff-Ferrari HA, Borchers M, Gudat F, et al. Vitamin D receptor expression in human muscle tissue decreases with age. J Bone Miner Res. 2004;19:265–269. 32 Montero-Odasso M, Duque G. Vitamin D in the aging musculoskeletal system: an authentic strength preserving hormone. Mol Aspects Med. 2005;26:203–219.

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33 Chapuy MC, Arlot ME, Duboeuf F, et al. Vitamin D3 and calcium to prevent hip fractures in the elderly women. N Engl J Med. 1992;327:1637–1642. 34 Dawson-Hughes B, Harris SS, Krall EA, Dallal GE. Effect of calcium and vitamin D supplementation on bone density in men and women 65 years of age or older. N Engl J Med. 1997;337:670 – 676. 35 Aloia JF, McGowan DM, Vaswani AN, et al. Relationship of menopause to skeletal and muscle mass. Am J Clin Nutr. 1991;53: 1378 –1383. 36 Sallis JF, Haskell WL, Wood PD, et al. Physical activity assessment methodology in the Five-City Project. Am J Epidemiol. 1985;121:91–106. 37 Nelson ME, Fiatarone MA, Morganti CM, et al. Effects of high-intensity strength training on multiple risk factors for osteoporotic fractures: a randomized controlled trial. JAMA. 1994;272:1909 –1914. 38 Kaneko M, Morimoto Y, Kimura M, et al. A kinematic analysis of walking and physical fitness testing in elderly women. Can J Sport Sci. 1991;16:223–228. 39 Malmberg JJ, Miilunpalo SI, Vuori IM, et al. A health-related fitness and functional performance test battery for middle-aged and older adults: feasibility and health-related content validity. Arch Phys Med Rehabil. 2002;83:666 – 677. 40 Kemmler W, Weineck J, Kalender WA, Engelke K. The effect of habitual physical activity, non-athletic exercise, muscle strength, and VO2max on bone mineral density is rather low in early postmenopausal osteopenic women. J Musculoskelet Neuronal Interact. 2004;4:325–334. 41 Nichols JF, Omizo DK, Peterson KK, Nelson KP. Efficacy of heavy-resistance training for active women over sixty: muscular strength, body composition, and program adherence. J Am Geriatr Soc. 1993;41: 205–210. 42 Carter ND, Khan KM, Mallinson A, et al. Knee extension strength is a significant determinant of static and dynamic balance as well as quality of life in older community-dwelling women with osteoporosis. Gerontology. 2002;48:360 –368. 43 Carter ND, Khan KM, McKay HA, et al. Community-based exercise program reduces risk factors for falls in 65- to 75-yearold women with osteoporosis: randomized controlled trial. CMAJ. 2002;167:997– 1004. 44 Liu-Ambrose T, Eng JJ, Khan KM, et al. Older women with osteoporosis have increased postural sway and weaker quadriceps strength than counterparts with normal bone mass: overlooked determinants of fracture risk? J Gerontol A Biol Sci Med Sci. 2003;58:862– 866. 45 Liu-Ambrose T, Eng JJ, Khan KM, et al. The influence of back pain on balance and functional mobility in 65- to 75-year-old women with osteoporosis. Osteoporos Int. 2002;13:868 – 873. 46 Richardson MT, Ainsworth BE, Jacobs DR, Leon AS. Validation of the Stanford 7-day recall to assess habitual physical activity. Ann Epidemiol. 2001;11:145–153.

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Physical Performance, Gait Variability, Falls, and Fractures in Early Postmenopause 47 Robinett CS, Vondran MA. Functional ambulation velocity and distance requirements in rural and urban communities: a clinical report. Phys Ther. 1988;68:1371– 1373. 48 Arnold CM, Busch AJ, Schachter CL, et al. The relationship of intrinsic fall risk factors to a recent history of falling in older women with osteoporosis. J Orthop Sports Phys Ther. 2005;35:452– 460. 49 Topp R, Mikesky A, Wigglesworth J, et al. The effect of a 12-week dynamic resistance strength training program on gait velocity and balance of older adults. Gerontologist. 1993;33:501–506. 50 Steffen TM, Hacker TA, Mollinger L. Ageand gender-related test performance in community-dwelling elderly people: SixMinute Walk Test, Berg Balance Scale, Timed “Up & Go” Test, and gait speeds. Phys Ther. 2002;82:128 –137. 51 Bohannon RW. Reference values for extremity muscle strength obtained by handheld dynamometry from adults aged 20 to 79 years. Arch Phys Med Rehabil. 1997; 78:26 –32. 52 Mangione KK, Palombaro KM. Exercise prescription for a patient 3 months after hip fracture. Phys Ther. 2005;85:676 – 687. 53 Wadsworth CT, Krishnan R, Sear M, et al. Intrarater reliability of manual muscle testing and hand-held dynametric muscle testing. Phys Ther. 1987;67:1342–1347. 54 Barker S, Craik R, Freedman W, et al. Accuracy, reliability, and validity of a spatiotemporal gait analysis system. Med Eng Phys. 2006;28:460 – 467. 55 Lamb SE, Jorstad-Stein EC, Hauer K, et al. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc. 2005;53:1618 –1622. 56 Tinetti ME, Speechley M, Ginter SF. Risk factors for falls among elderly persons living in the community. N Engl J Med. 1988; 319:1701–1707. 57 Cranney A, Jamal SA, Tsang JF, et al. Low bone mineral density and fracture burden in postmenopausal women. CMAJ. 2007; 177:575–580.

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58 Wolinsky FD, Miller DK, Andresen EM, et al. Further evidence for the importance of subclinical functional limitation and subclinical disability assessment in gerontology and geriatrics. J Gerontol B Psychol Sci Soc Sci. 2005;60:S146 –S151. 59 Fried LP, Bandeen-Roche K, Chaves PH, Johnson BA. Preclinical mobility disability predicts incident mobility disability in older women. J Gerontol A Biol Sci Med Sci. 2000;55:43–52. 60 Carriere I, Colvez A, Favier F, et al. Hierarchical components of physical frailty predicted incidence of dependency in a cohort of elderly women. J Clin Epidemiol. 2005;58:1180 –1187. 61 Visser M, Pluijm SM, Stel VS, et al. Physical activity as a determinant of change in mobility performance: the Longitudinal Aging Study Amsterdam. J Am Geriatr Soc. 2002; 50:1774 –1781. 62 Visser M, Kritchevsky SB, Goodpaster BH, et al. Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79: the Health, Aging and Body Composition Study. J Am Geriatr Soc. 2002;50: 897–904. 63 Binder EF, Schechtman KB, Ehsani AA, et al. Effects of exercise training on frailty in community-dwelling older adults: results of a randomized, controlled trial. J Am Geriatr Soc. 2002;50:1921–1928. 64 Frontera WR, Hughes VA, Lutz KJ, Evans WJ. A cross-sectional study of muscle strength and mass in 45- to 78-yr-old men and women. J Appl Physiol. 1991;71:644 – 650. 65 Ferrucci L, Guralnik JM, Studenski S, et al. Designing randomized, controlled trials aimed at preventing or delaying functional decline and disability in frail, older persons: a consensus report. J Am Geriatr Soc. 2004;52:625– 634. 66 Kemmler W, Engelke K, Lauber D, et al. Exercise effects on fitness and bone mineral density in early postmenopausal women: 1-year EFOPS results. Med Sci Sports Exerc. 2002;34:2115–2123. 67 Kanat AA, Yurtkuran M. Efficacy of a selfmanagement program for osteoporotic subjects. Am J Phys Med Rehabil. 2007; 86:633– 640.

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68 Topolski TD, LoGerfo J, Patrick DL, et al. The Rapid Assessment of Physical Activity (RAPA) among older adults. Prev Chronic Dis. 2006;3:A118. 69 Craig CL, Marshall AL, Sjo ¨ stro ¨ m M, et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395. 70 Gregg EW, Cauley JA, Seeley DG, et al. Physical activity and osteoporotic fracture risk in older women. Ann Intern Med. 1998;129:81– 88. 71 Paganini-Hill A, Chao A, Ross RK, Henderson BE. Exercise and other factors in the prevention of hip fracture: the Leisure World study. Epidemiology. 1991;2: 16 –25. 72 Hegeman JH, Oskam J, van der Palen J, et al. The distal radial fracture in elderly women and the bone mineral density of the lumbar spine and hip. J Hand Surg Br. 2004;29:473– 476. 73 Lauritzen JB, Schwarz P, McNair P, et al. Radial and humeral fractures as predictors of subsequent hip, radial or humeral fractures in women, and their seasonal variation. Osteoporos Int. 1993;3:133–137. 74 Heinemann DF. Osteoporosis: an overview of the National Osteoporosis Foundation clinical practice guide. Geriatrics. 2000;55:31–36. 75 Nelson HD, Helfand M, Woolf SH, Allan JD. Screening for postmenopausal osteoporosis: a review of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002;137:529 –541. 76 Brown JP, Josse RG, et al. 2002 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada. CMAJ. 2002;167(10 suppl):S1–S34. 77 Craik RL, Dutterer L. Spatial and temporal characteristics of foot fall patterns. In: Craik RL, Oatis CA, eds. Gait Analysis: Theory and Application. St Louis, MO: Mosby; 1995:143–158.

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Research Report A Functional Threshold for Long-Term Use of Hand and Arm Function Can Be Determined: Predictions From a Computational Model and Supporting Data From the Extremity ConstraintInduced Therapy Evaluation (EXCITE) Trial Nicolas Schweighofer, Cheol E. Han, Steven L. Wolf, Michael A. Arbib, Carolee J. Winstein

Background. Although spontaneous use of the more-affected arm and hand after stroke is an important determinant of participation and quality of life, a number of patients exhibit decreases in use following rehabilitative therapy. A previous neurocomputational model predicted that if the dose of therapy is sufficient to bring performance above a certain threshold, training can be stopped. Objective. The aim of this study was to test the hypothesis that there exists a threshold for function of the paretic arm and hand after therapy. If function is above this threshold, spontaneous use will increase in the months following therapy. In contrast, if function is below this threshold, spontaneous use will decrease.

Methods. New computer simulations are presented showing that changes in arm use following therapy depend on a performance threshold. This prediction was tested by reanalyzing the data from the Extremity Constraint-Induced Therapy Evaluation (EXCITE) trial, a phase III randomized controlled trial in which participants received constraint-induced movement therapy for 2 weeks and were tested both 1 week and 1 year after therapy.

Results. The results demonstrate that arm and hand function measured immediately after therapy predicts, on average, the long-term change of arm use. Above a functional threshold, use improves. Below this threshold, use decreases.

Limitations. The reanalysis of the EXCITE trial data provides a “group” threshold above which a majority of patients, but not all, improve spontaneously. A goal of future research is to provide the means to assess when patients reach their individual threshold.

Conclusion. Understanding of the causal and nonlinear relationship between limb function and daily use is important for the future development of cost-effective interventions and prevention of “rehabilitation in vain.”

N. Schweighofer, PhD, is Assistant Professor, Division of Biokinesiology and Physical Therapy at the School of Dentistry, and Department of Computer Science, University of Southern California, 1540 E Alcazar, CHP 155, Los Angeles, CA 90089 (USA). Address all correspondence to Dr Schweighofer at: [email protected]. C.E. Han, MS, is a PhD student, Department of Computer Science, University of Southern California. S.L. Wolf, PT, PhD, FAPTA, FAHA, is Professor, Departments of Rehabilitation Medicine and Medicine, and Associate Professor, Department of Cell Biology, Emory University School of Medicine, Center for Rehabilitation Medicine; Professor, Health and Elder Care, Nell Hodgson Woodruff School of Nursing at Emory University; and Senior Research Scientist, VA Rehabilitation R&D Center, Atlanta, Georgia. M.A. Arbib, PhD, is Professor, Department of Computer Science, University of Southern California. C.J. Winstein, PT, PhD, FAPTA, is Professor and Director of Research, Division of Biokinesiology and Physical Therapy at the School of Dentistry, and Associate Professor, Department of Neurology, Keck School of Medicine, University of Southern California. [Schweighofer N, Han CE, Wolf SL, et al. A functional threshold for long-term use of hand and arm function can be determined: predictions from a computational model and supporting data from the Extremity Constraint-Induced Therapy Evaluation (EXCITE) trial. Phys Ther. 2009;89:1327–1336.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org

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troke is the leading cause of disability in the United States, and about 65% of survivors of stroke experience long-term upperextremity functional limitations. In more than half of patients with severe paresis after stroke, recovery of upper-extremity function is achieved solely by use of the less-affected limb.1 Improving use of the moreaffected arm is important, however, because difficulty in using this arm in daily tasks has been associated with both reduced participation and quality of life.2,3 There now is evidence that intensive, task-specific practice, in which patients actively engage in repeated attempts to produce motor behaviors beyond their present capabilities, is effective for improving upperextremity function and use after stroke.4 –9 Constraint-induced movement therapy (CIMT) in particular, which involves intense, functionally oriented task practice of the moreaffected upper limb along with restraint of the less-impaired limb for 90% of waking hours, was shown in the Extremity Constraint-Induced Therapy Evaluation (EXCITE) phase III randomized controlled trial to largely improve limb function and arm use compared with usual and customary care.7,9 Several weeks of challenging rehabilitative training with the upper limb contralateral to Available With This Article at www.ptjournal.org • Discussion Podcast: Participants to be determined. • The Bottom Line clinical summary

the lesion reverses, at least partially, the loss of cortical representation due to stroke through recruitment of adjacent brain areas.10 –12 Such reorganization may last several years after the initial injury13 and has been linked to change in performance.14 Long-term change in arm and hand use in the months following therapy, however, is variable among patients. In some patients, use continues to improve in the months following therapy.9,15,16 Earlier, we proposed that the repeated attempts to use the affected arm in daily activities can promote motor learning that improves performance and function15; this improvement in function, in theory, could further increase arm use. However, for other patients, improvements can be short-lasting. For a number of patients in the EXCITE trial, for instance (see Results section), and presumably for a larger number of patients who receive usual and customary care, a decrease in use of the affected arm appears in the year following therapy. If this decrease is large, rehabilitation is in vain. Accordingly, understanding the conditions that lead to sustained gains in arm use following an intense bolus of therapy is important. To achieve a unimanual task, such as drinking from a glass, a patient recovering from stroke can be conceptualized as a decision maker who chooses to use either the more-affected limb or less-affected limb (the decisions here need not be made consciously). The choice of limb use will presumably depend on many factors, including lesion characteristics, impairment and functional levels, motor training, previously rewarding or punishing experience after stroke, and motivation.

• The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on October 1, 2009, at www.ptjournal.org.

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In a recent computational model,17 we modeled bilateral reaching movements in patients recovering from stroke to explore the interactions between the adaptive decision process Number 12

of limb use and limb performance. Here, “arm performance” is defined as the directional error of the movement toward the selected target and is the equivalent of “arm and hand function” in patients. Therapy is a simulation of CIMT: the simulated patient is forced to use the affected arm. When no therapy is given, the patient is free to choose 1 of the 2 arms to reach a target appearing on a circle centered on (overlapping) initial hand locations. Our neural model contains 2 independent motor cortices, each controlling the contralateral arm, with one being affected by stroke.* Before each movement, one motor cortex is selected by an adaptive decision-making system, tentatively located in cortico-striatal networks. In our model, neural reorganization in the motor cortex was modeled with a neural learning rule that aims to achieve 2 goals concurrently. The first goal is to reorganize the neural code to increase arm performance via error-based learning (also called “supervised learning”). The second goal is to maximize neural resources for particular desired movement directions to minimize movement variability via Hebbian learning (a model of long-term potentiation, which also is called “unsupervised learning” because there is no teacher). Furthermore, in the model, the decision to use one limb or the other is made by comparing the “action value” of each limb in the adaptive decision-making system. The values for each arm are updated based on reward prediction errors (this type of learning also is called “reinforcement learning”). If performancebased rewards are greater than expected, the arm will be chosen more often for this particular movement. If * Note that our model does not account for the approximately 20% of uncrossed fibers from the corticospinal tract.

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Understanding the Functional Threshold for Paretic Hand and Arm Use After Therapy not, the arm will be chosen less often.

threshold with a reanalysis of clinical data from the EXCITE clinical trial.7

Simulation results showed that after small doses of therapy, the model exhibited a simple form of learned non-use, as use increased with therapy but decreased again to low levels after therapy (for a more complete account of learned non-use, see Wolf18). With large doses of therapy, use increased after therapy. With a specific intermediate dose of therapy, there is no change in use after therapy. That is, there is a threshold for rehabilitation. This threshold is an emergent property of the learning dynamics and exists only when the 3 types of learning— error-driven, Hebbian-like, and reward-based—are implemented.17 The model further showed that, similar to experimental observations, sufficient CIMT in the model reversed the cortical representation loss, principally because of the synergistic effect of supervised learning and unsupervised learning, which was “adaptive.” No rehabilitation, or too little rehabilitation, increased this loss, principally because of reorganization due to unsupervised learning, which was “maladaptive” (see Han et al17 for further details and results).

Method

The present article directly tests the hypothesis that there is a threshold level for function of the paretic arm and hand after therapy. If function is above this threshold, spontaneous use will increase in the months following therapy. In contrast, if function is below this threshold, spontaneous use will decrease or deteriorate in the months following therapy, and compensatory use of the nonparetic hand will further develop. We first present new computer simulations of the model to directly show the emergence of the hypothesized performance threshold that determines average longterm limb use in simulated patients. We then tested our prediction of a December 2009

Computer Simulation Methods The objective of these computer simulations is to test the hypothesis that there is a threshold level for function of the paretic arm and hand after therapy in simulations that mimic the conditions of the EXCITE trial. Our model, although necessarily highly simplified, contains key ingredients that make it applicable to the participants in the EXCITE trial. First, as described above, our model is a model of stroke recovery that contains up-to-date knowledge about plastic processes underlying stroke recovery. Second, therapy in the model has been modeled loosely after CIMT. That is, during therapy, the simulated patient is constrained to use the affected arm. Third, in the model, lesion sizes can easily be varied to capture the diversity of patients with stroke in the EXCITE trial. Finally, the model makes predictions of long-term changes in arm use as a function of performance just after therapy, and the EXCITE data precisely capture such variables in these time frames. In our previous work,17 “identical” simulated patients (same lesion size and location) received various doses of therapy. In the present study, in contrast, we simulated patients with various lesion locations and sizes, and all simulated patients received the same dose of therapy. Specifically, we simulated 125 patients with locations of the lesion center randomly chosen within the affected motor cortex. The lesion sizes were empirically determined within a range of 16% to 43% of the affected motor cortex sizes, because such lesion sizes lead to effects that are neither too mild (to need therapy) nor too severe (to benefit from therapy). All patients received the same dose of 400 forced-use trials of Volume 89

therapy (corresponding to the 2 weeks of CIMT that was the standard dose in EXCITE). Then, for each simulated patient, we measured use of the affected arm just after therapy (corresponding to the 1-week posttest in the EXCITE trial) and in a delayed follow-up test, given after 3,000 free-choice trials following therapy (corresponding to the 1-year posttest in the EXCITE trial). All other simulation parameters are shown in Han et al.17 We developed sigmoid models of spontaneous arm use as a function of the error both immediately after therapy and 3,000 trials after therapy. For this purpose, we fitted the equivalent linear models to the data: Y⫽a ERROR ⫹ b, where Y⫽log (USE/(100%⫺USE)), USE is the average spontaneous arm use either just after therapy or 3,000 trials after therapy, and ERROR is the average of directional error (in degrees) just after therapy. USE and ERROR are computed from the average of 100 trials over the affected range. The parameter a is the sigmoid slope, the parameter b is a free parameter, and log is the natural logarithm. We report the P value obtained from these linear regression models with transformed Y values. We compared linear fits and sigmoid fits with root mean square error (RMSE) in spontaneous arm use. Reanalysis of Clinical Data From the EXCITE Trial The objective of this reanalysis of the data from the EXCITE clinical trial7 was to test the prediction, derived from our simulations, of a performance threshold, on average, in patients poststroke. We performed a retrospective analysis of data from the 169 patients enrolled in the EXCITE trial who did not withdraw from the trial.7 Briefly, in the EXCITE trial, subjects were randomly assigned to either an imNumber 12

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Understanding the Functional Threshold for Paretic Hand and Arm Use After Therapy mediate CIMT group or a delayed CIMT group. The immediate CIMT group received 2 weeks of therapy after inclusion in the study (Pre1); the delayed CIMT group received no immediate therapy but did receive 2 weeks of therapy after a 1-year delay (Pre2). Subjects were tested with the Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL) at Pre1, at 1 week after the immediate CIMT group received therapy (Post1), at Pre2, and at 1 week after the delayed CIMT group received therapy (Post2). All subjects were tested again at 24 months after inclusion in the study (MT24).7,19 In the current analysis, we compared arm use 1 week after therapy with arm use a year later, so time of therapy was not a factor in this analysis. We thus combined all data in the EXCITE trial at these points and studied arm function and use in the posttest just following therapy (Post1 for the immediate CIMT group and Post2 for the delayed CIMT group) and arm function and use in the delayed 1-year posttest (Pre2 for the immediate CIMT group and MT24 for the delayed CIMT group). Briefly, the WMFT measures performance time (up to 120 seconds) needed for patients with stroke to perform 15 laboratory-based arm function tasks requiring use of the more-affected upper extremity.20 –22 The WMFT also contains a shoulder strength (force-generating capacity) task and a grip strength task. Additionally, the quality of motor function during the timed tasks is assessed by independent raters using the 6-point Functional Activity Scale (FAS). The WMFT has good reliability and validity and has been shown not to suffer from a learning effect.22 In our analyses, as in Wolf et al,21 the natural logarithm of the WMFT time score was used to normalize the distribution. In the MAL, patients (or their caregivers) rate how well (on the Quality of Movement [QOM] 1330

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scale) and how much (on the Amount of Use [AOU] scale) the paretic arm is used spontaneously to accomplish 30 activities of daily living outside of the laboratory.23,24 Each item on the MAL has an 11point scale, with scores ranging from 0 (no use) to 5 (normal) in increments of 0.5. Validity and reliability of the MAL scores have been established.24 In our analyses, we present average MAL AOU scale scores. Our neural computational model predicts that if performance is above threshold after therapy, use will increase between 1 week after and 1 year after therapy (positive change). If performance is below threshold, use will decrease (negative change). The model thus predicts a positive correlation between performance and change in use after therapy. To test this prediction, we performed 2 correlation analyses. The first correlation analysis was performed to determine the relationship between the difference in average MAL AOU scale scores from 1 week posttherapy to 1 year posttherapy and the logarithm of the WMFT time score. The second correlation analysis was performed to determine the relationship between the difference in average MAL AOU scale scores from 1 week posttherapy to 1 year posttherapy and the WMFT FAS scores. We then verified this theoretically driven prediction with a datadriven (hypothesis-free) analysis using a stepwise linear regression (see Appendix for details). In this analysis, a large number of variable predictors initially were entered in the linear model that predicts long-term changes in MAL AOU scale scores. If a measure of function 1 week after therapy is a significant predictor of long-term changes in use, this stepwise linear regression would give further support to the threshold hypothesis.

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In view of the predictions of our simulations on the sigmoidal shapes of the relationship between performance 1 week after therapy and use both 1 week after therapy and after a delay of 1 year and because the MAL AOU scale is bounded between 0 and 5, we developed sigmoid models of the average MAL AOU scale scores as a function of the WMFT FAS scores both immediately (1 week) after therapy and 1 year after therapy. For this purpose, we fitted the equivalent linear models to the data: Y⫽a FAS ⫹ b, where Y⫽⫺log (5/ MAL ⫺ 1), MAL is the MAL AOU scale score taken either in the 1-week posttest or the 1-year posttest, FAS is the WMFT FAS score, the parameter a is the sigmoid slope, the parameter b is a free parameter, and log is the natural logarithm. We report the P value obtained from these linear regression models with transformed Y values. We compared linear fits and sigmoid fits with the RMSE in MAL scores, where a smaller RMSE indicates a better fit. In this analysis with sigmoidal models, we included only patients with WMFT and MAL data available at both time points (although all subjects included in our analysis completed the trial, a number of data points were missing at either the 1-week posttest or the 1-year posttest). Furthermore, to obtain convergence of the sigmoidal fit, we removed 2 subjects with perfect MAL AOU scores (scores of 5 at 1 week after therapy; no participants had scores of 5 at 1 year following therapy). We thus analyzed data from 132 subjects. We also compared sigmoidal models and linear models after removal of outliers, defined as individuals with residuals (observedpredicted values) greater than 2 standard deviations of the residuals. We compared the sigmoid models at 1 week posttherapy and at 1 year posttherapy by computing and comDecember 2009

Understanding the Functional Threshold for Paretic Hand and Arm Use After Therapy paring the confidence intervals (CIs) at 95% and 90% of the slope parameter of the sigmoid regression models. We predicted that for those subjects whose performance was above threshold after therapy, use would increase from 1 week posttherapy to 1 year posttherapy. Contrarily, we predicted that for those subjects whose performance was below threshold, use would decrease. Assuming that sigmoid models are a good fit to the use data at 1 week posttherapy and at 1 year posttherapy, this prediction can be tested by the change in slope of the sigmoids from 1 week posttherapy to 1 year posttherapy. The slope should be greater at 1 year posttherapy than at 1 week posttherapy. Finally, the performance threshold was obtained at the crossing of the sigmoids at 1 week posttherapy and at 1 year posttherapy. The prediction is that the 2 curves will cross because the slope is greater at 1 year posttherapy than at 1 week posttherapy. Above this crossing point, use will be greater at 1 year posttherapy than at 1 week posttherapy, on average. Below this crossing point, use will be smaller at 1 year posttherapy than at 1 week posttherapy, on average. Thus, this crossing represents an average threshold. We set the significance level at P⫽.05.

Results Computer Simulation To test the hypothesis that spontaneous use will increase in the months following therapy if arm performance after therapy is above a threshold, we first investigated arm use at 0 trials and at 3,000 trials following therapy as a function of performance just after therapy. For simulated patients above threshold, spontaneous arm use should increase, on average, from 0 to 3,000 trials. For patients below threshold, the spontaneous arm use should decrease, on average, from 0 to 3,000 trials. December 2009

In the model, performance is measured as angular error between the target direction and the actual arm movement direction. Spontaneous arm use is measured as percentage of use of the affected arm to the targets in the range of movement directions most affected by the lesion (in the model, the lesions affect some ranges more than others; see Han et al17 for details). Figure 1A shows that for most simulated patients with high performance after therapy, spontaneous arm use was high and saturated to maximum use (100% in the model). Conversely, for simulated patients with low performance, use saturated near zero. Because of these ceiling and floor effects, arm use after therapy was fit better by a sigmoidal function of performance (RMSE⫽17.08, P⬍.0001) than by a linear function of performance (RMSE⫽18.74, P⬍.0001). Figure 1B shows that arm use in the follow-up test at 3,000 trials after therapy also was fit better by a sigmoidal function (RMSE⫽18.98, P⬍.0001) than by a linear function (RMSE⫽19.36, P⬍.0001). Finally, the slope of the sigmoid model in the long-term follow-up test was steeper than that just after therapy (slope just after therapy⫽0.31; slope 1 year after therapy⫽0.52). The intersection of the 2 curves gives an average (or “group”) threshold in arm performance, corresponding to a reaching error of 22.8 degrees. Above this threshold, the arm use of most simulated patients (89.1%) improved spontaneously following therapy; below this threshold, the arm use of most simulated patients (87.1%) worsened following therapy. These simulation results make 3 testable predictions. First, the relationship between use after therapy and function after therapy is sigmoidal, and this is true if spontaneous use is measured just after therapy or in a Volume 89

delayed follow-up test. Second, the sigmoid is steeper in the follow-up test than just after therapy. Third, the intersection of the sigmoid for use just after therapy with the sigmoid for use in the long-term followup test (Fig. 1C) gives an average threshold in performance above which use improves spontaneously following therapy and below which use worsens. We next tested these predictions with a reanalysis of clinical data from the EXCITE trial. Clinical Data Analysis The correlation analysis between the difference in average MAL AOU scores from just after therapy to 1 year posttherapy and the logarithm of the WMFT time score shows that function (WMFT score) was positively correlated with change in use (MAL AOU scale score) (Pearson correlation r⫽⫺.172, P⫽.046, n⫽135). A similar correlation analysis shows that the WMFT FAS score correlated better with long-term changes in use (r⫽.22, P⬍.010, n⫽134). Among a large number of variables included as potential predictors of change in MAL AOU scores after therapy in the stepwise regression analysis, only 2 variables were included in the final model (P⬍.0005, R2⫽.123, n⫽133): the WMFT FAS score posttherapy (P⬍.0001, standardized coefficient⫽0.42) and the “weight to box” task with the moreaffected arm (a strength task part of the WMFT) measured upon enrollment (P⬍.005, standardized coefficient⫽⫺0.34) (see the Appendix for details). The sigmoid models of the average MAL AOU scale scores as a function of the WMFT FAS scores showed a good fit to the data both immediately (1 week) after therapy (RMSE⫽0.83, P⬍.0001) and 1 year after therapy (RMSE⫽0.86, P⬍.0001). The mean slope of the sigmoid model was larger at 1 year after therapy (mean Number 12

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Figure 1. Simulated data of use of the affected arm (A) just after therapy and (B) 3,000 trials after therapy as a function of performance (reach directional error in the model) just after therapy for 125 simulated subjects with different lesion sizes and locations. (C) Comparison of the sigmoidal fit of use just after therapy and 3,000 trials after therapy. The intersection of the 2 curves gives the threshold in arm performance above which use increases and below which use decreases. The upward arrow indicates that 89.1% of the simulated subjects above threshold showed increased arm use after therapy. The downward arrow indicates that 87.1% of the simulated subjects below threshold showed decreased arm use after therapy. Note that we reversed the x axis, to compare with the data of Figure 2.

slope⫽1.71, standard error [SE] of slope⫽0.14, 95% CI⫽1.43–1.99, and 90% CI⫽1.47–1.94) than at 1 week after therapy (mean slope⫽1.31, SE⫽0.13, 95% CI⫽1.05–1.58, and 90% CI⫽1.09 –1.53). The corresponding linear models fit the data with similar RMSE values (RMSE⫽ 0.83, P⬍.0001 and RMSE⫽0.87, P⬍.0001) for the 1-week and 1-year models, respectively. The strength of the relationships between MAL AOU scale scores and WMFT FAS scores at 1 week and 1 1332

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year after therapy increased after removal of outliers. Based on our criterion for outlier removal, 4 subjects were removed in the 1-week model, 5 subjects were removed in the 1-year model, and 3 subjects were outliers for both the 1-week and 1-year models; thus, n⫽128 for the 1-week model and n⫽127 for the 1-year model). Compared with the sigmoid models without outlier removal, these models with outlier removal (Figs. 2A and B) showed improved fit to the data (1 week after therapy: RMSE⫽0.76, P⬍.0001; 1

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year after therapy: RMSE⫽0.79, P⬍.0001) and smaller CIs of the slopes both 1 week after and 1 year after therapy (1 week after therapy: mean slope⫽1.44, SE of slope⫽0.13, 95% CI⫽1.19 –1.68, 90% CI⫽1.23– 1.64; 1 year after therapy: mean slope⫽1.91, SE⫽0.14, 95% CI⫽ 1.63–2.18, 90% CI⫽1.67–2.14). Finally, the sigmoid models with outlier removal fit the 1-week and 1-year data better than the linear models with outlier removal (1 week after therapy: n⫽130, RMSE⫽0.78,

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Figure 2. Use of the more-affected arm, as recorded by the Motor Activity Log Amount of Use (MAL AOU) subscale: (A) 1 week after therapy and (B) 1 year after therapy as a function of arm and hand function (Functional Ability Scale [FAS]) 1 week after therapy for subjects of the EXCITE trial. (C) Comparison of the sigmoidal fit of use 1 week after therapy and 1 year after therapy. The intersection of the 2 curves gives the functional threshold (FAS score⫽3.44) above which uses increases and below which use decreases. The upward arrow indicates that 68.2% of subjects above threshold showed increased arm use after therapy. The downward arrow indicates that 63.5% of subjects below threshold showed decreased arm use after therapy.

P⬍.0001; 1 year after therapy: n⫽129, RMSE⫽0.83, P⬍.0001). Thus, the slope of the sigmoidal model 1 year after therapy was greater than the slope of the sigmoidal at 1 week after therapy, although there was a very small overlap of the 95% CIs (by 0.05) but no overlap of the 90% CIs. The results were qualitatively similar without outlier removal, but the 95% CIs for the sigmoid slopes overlapped somewhat (by 0.15); however, there was less overlap of the 90% CIs (by 0.06). The December 2009

steeper slope of the sigmoid at 1 year posttherapy compared to 1 week posttherapy is well illustrated in Figure 2C, in which we plotted the 2 sigmoids (models without outliers). The intersection of the 2 sigmoids with mean slopes gives the average threshold in function, given by WMFT FAS score⫽3.44. Among 22 subjects with function above this threshold, 15 (68.2%) showed an increase in use in the year following therapy (model without outliers). Conversely, among 104 subjects Volume 89

with function below this threshold, only 38 (36.5%) showed an increase in use in the year following therapy (Fig. 2C). Thus, as predicted by the computational model, when function 1 week after therapy was above this average threshold, subjects on average showed improvements in use in the year following therapy, and when function 1 week after therapy was below this average threshold, subjects on average experienced a worsening of use in the year following therapy.

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Discussion To better understand the interactions between arm function and use after therapy, we have presented new simulations with conditions that mimic those of the EXCITE trial. These simulations made 3 new predictions, all of which were confirmed in a reanalysis of arm use and function data from the EXCITE trial. First, the relationship between use after therapy and performance is better fit by a sigmoidal model than a linear regression model, and this sigmoidal relationship is true whether use is measured 1 week after therapy or in a follow-up test. The differences, however, between the linear fits and sigmoidal fits are not very large (as shown by the relatively small differences in RMSE between linear and sigmoidal models at 1 week after therapy and at 1 year after therapy in the outlier removal conditions). Thus, this sigmoidal relationship needs to be verified with other clinical databases. A sigmoidal relationship can result for 2 possible, nonexclusive reasons. The first possible reason is simply that the MAL AOU scale does not adequately measure arm use when use is high or low. The second possible reason is an actual nonlinear relationship between function and use in patients, at least on average. A floor effect would suggest that when function is low, the arm is not used at all. A ceiling effect would suggest that when function is high but less than maximal, the arm is used as if the patient did not have a stroke. Second, the sigmoid is steeper in the 1-year follow-up test than 1 week after therapy. This indicates that, for the average patient in EXCITE trial, if function is high 1 week after therapy, use improves. Conversely, and again on average, if function is low 1 week after therapy, use worsens. Third, the intersection of the sigmoid for use 1 week after therapy with the sigmoid for use in the 1-year 1334

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follow-up test gives an average (or group) threshold in function of WMFT FAS score⫽3.44. An FAS score of 3 is given if the affected arm performance does not require assistance from the other arm but is limited by synergistic movements, or is performed slowly or with effort. An FAS score of 4 is given if the affected arm performance is close to normal (ascertained by performance of the less-affected limb and with premorbid dominance considered) but slightly slower and may lack precision, fine coordination, or fluidity. If function is above the threshold 1 week after therapy, use of the moreaffected arm in the year following therapy improves, on average. On the contrary, if function is below this threshold, use is not sustained, on average. Thus, functional abilities just after therapy predict change in use in the long-term following therapy, and, on average, a functional threshold can be determined. In the stepwise regression analysis of the EXCITE trial data, only a measure of arm and hand function (the WMFT FAS) and shoulder strength 1 week after therapy predicted change in use. Furthermore, shoulder strength was negatively correlated with a future change in use, although this correlation was only moderate (⫺.34). How can this result be interpreted? One possibility is that patients with greater shoulder strength may be better able to compensate with the proximal arm for the lowerfunctioning distal upper extremity. Because of these compensatory movements, use of the hand is not reinforced and decreases. Another, nonexclusive possibility is that increase in arm strength correlates with a shrinkage of neural areas encoding the distal representation and an increase in neural areas encoding the proximal representation; this would explain the negative correlation. In any case, because stepwise regression is an exploratory tool,

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these results and predictions warrant further investigation by studies that combine brain imaging or neural recording and behavioral data analysis. Furthermore, we note that we have defined shoulder strength as performance of the “weight to box” task of the WMFT. This task does not directly measure shoulder strength, and thus the correlation might be different if strength is tested with the actual shoulder strength test. Limitations and Future Work A practical clinical implication of the present work is the determination of a stopping criterion to determine the dose of therapy for each patient. The intersection of the sigmoid curves in our reanalysis of the EXCITE trial data gives a “group” threshold, above which most patients improve spontaneously. A goal of our future research, therefore, is to provide the means to assess when an individual reaches his or her personal threshold so that therapy may be stopped without adverse effect. More research is needed, however, before we are able to provide robust threshold values for individual patients and before such a stopping rule can be implemented in the clinic, for the following reason. Notably, the predictive capability of our simple sigmoidal models is rather low: only 68.2% of subjects above the threshold showed improvement in use; conversely, 36.5% of subjects below the threshold showed improvement in use. Such low predictive values arise because our sigmoidal models are simple averaged models that do not consider individual lesion size, location, or any other patient characteristics, such as motivation, handedness, and so on, besides function 1 week after therapy. To be able to determine functional thresholds for individual patients, we are currently extending this work in 2 aspects. First, we are developing individualized predictive December 2009

Understanding the Functional Threshold for Paretic Hand and Arm Use After Therapy models that can be used for individualized determination of threshold and dose. We previously argued from a theoretical viewpoint,17 and confirmed to some extent here with clinical data, that stroke recovery is a time-varying process (arm use changes in the year following therapy) that is nonlinear (arm use can increase or decrease in the year following therapy, depending on arm function after therapy). We currently are developing time-varying and nonlinear models of recovery that will use neurological data such as stroke lesion location and volume as regressors. Second, both the WMFT FAS and the MAL AOU scale are lengthy tests that are impractical to use in the clinic. To address this, we are developing a novel, easy-toadminister, reliable, and valid measure of arm use that is based on actual arm choices in a bilateral arm reaching task.25 Based on predictions from these novel models and tools, we expect to determine the functional threshold with high confidence for individual patients and, as a result, to determine the patient-specific dose of therapy that will bring function above this threshold. Such an understanding of nonlinear relationships between limb function and use is important for the future development of cost-effective interventions and the prevention of “rehabilitation in vain.” Dr Schweighofer, C.E. Han, Dr Wolf, and Dr Winstein provided concept/idea/research design and data analysis. Dr Schweighofer, Dr Wolf, Dr Arbib, and Dr Winstein provided writing. C.E. Han, Dr Wolf, and Dr Winstein provided data collection. Dr Winstein provided project management. Dr Wolf provided fund procurement, participants, and facilities/equipment. Dr Wolf and Dr Winstein provided institutional liaisons. Dr Wolf, Dr Arbib, and Dr Winstein provided consultation (including review of manuscript before submission). The authors thank Dr Jean Zhang, Dr Paul Thompson, and Dr Phill Miller for providing

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the EXCITE trial data and Dr James Gordon for helpful discussions. The model was presented at the 37th Annual Meeting of the Society for Neuroscience Annual; November 3–7, 2007; San Diego, California. This work was funded, in part, by National Institutes of Health/National Institute of Neurological Disorders and Stroke grant P20 RR020700-01 and R01 HD 37606. This article was received December 16, 2008, and was accepted August 5, 2009. DOI: 10.2522/ptj.20080402

References 1 Nakayama H, Jorgensen HS, Raaschou HO, Olsen TS. Compensation in recovery of upper extremity function after stroke: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1994;75:852– 857. 2 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. 3 Mayo NE, Wood-Dauphineé S, Cote R, et al. Activity, participation, and quality of life 6 months poststroke. Arch Phys Med Rehabil. 2002;83:1035–1042. 4 Butefisch C, Hummelsheim, H, Denzler, P, Mauritz, KH. Repetitive training of isolated movements improves the outcome of motor rehabilitation of the centrally paretic hand. J Neurol Sci. 1995;130:59 – 68. 5 Kwakkel G, Wagenaar RC, Twisk JW, et al. Intensity of leg and arm training after primary middle-cerebral artery stroke: a randomized trial. Lancet. 1999;354:191–196. 6 Wolf SL, Blanton S, Baer H, et al. Repetitive Task practice: a critical review of constraint induced therapy in stroke. Neurologist. 2002;8:325–338. 7 Wolf SL, Winstein CJ, Miller JP, et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296: 2095–2104. 8 Winstein CJ, Wolf SL. Task-oriented training to promote upper extremity recovery. In: Stein J, Macko R, Winstein CJ, Zorowitz R, eds. Stroke Recovery and Rehabilitation. New York, NY: Demos Medical; 2008:267–290. 9 Wolf SL, Winstein CJ, Miller JP, et al. Retention of upper limb function in stroke survivors who have received constraintinduced movement therapy: the EXCITE randomised trial. Lancet Neurol. 2008;7: 33– 40. 10 Nudo RJ, Wise BM, SiFuentes F, Milliken GW. Neural substrates for the effects of rehabilitative training on motor recovery after ischemic infarct. Science. 1996;272: 1791–1794. 11 Kleim JA, Barbay S, Nudo RJ. Functional reorganization of the rat motor cortex following motor skill learning. J Neurophysiol. 2998;80:3321–3325.

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12 Liepert J, Bauder H, Wolfgang HR, et al. Treatment-induced cortical reorganization after stroke in humans. Stroke. 2000;31: 1210 –1216. 13 Taub E, Uswatte G, Morris DM. Improved motor recovery after stroke and massive cortical reorganization following constraintinduced movement therapy. Phys Med Rehabil Clin N Am. 2003;14:S77–S91, ix. 14 Conner JM, Culberson A, Packowski C, et al. Lesions of the basal forebrain cholinergic system impair task acquisition and abolish cortical plasticity associated with motor skill learning. Neuron. 2003;38: 819 – 829. 15 Winstein CJ, Rose DK, Tan SM, et al. A randomized controlled comparison of upper-extremity rehabilitation strategies in acute stroke: a pilot study of immediate and long-term outcomes. Arch Phys Med Rehabil. 2004;85:620 – 628. 16 Fujiwara T, Kasashima Y, Osada M, et al. Motor improvement and corticospinal modulation induced by hybrid assistive neuromuscular dynamic stimulation (HANDS) therapy in patients with chronic stroke. Clin Neurophysiol. 2008;119:e82– e82. 17 Han CE, Arbib MA, Schweighofer N. Stroke rehabilitation reaches a threshold. PLoS Computat Biol. 2008;4:e1000133. 18 Wolf SL. Revisiting constraint-induced movement therapy: are we too smitten with the mitten? Is all nonuse “learned”? and other quandaries. Phys Ther. 2007;87: 1212–1223. 19 Winstein CJ, Miller JP, Blanton S, et al. Methods for a multisite randomized trial to investigate the effect of constraintinduced movement therapy in improving upper extremity function among adults recovering from a cerebrovascular stroke. Neurorehabil Neural Repair. 2003;17: 137–152. 20 Wolf SL, Lecraw DE, Barton LA, Jann BB. Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Exp Neurol. 1989;104:104 –132. 21 Wolf SL, Catlin PA, Ellis M, et al. Assessing the Wolf Motor Function Test as an outcome measure for research in patients after stroke. Stroke. 2001;32:1635–1639. 22 Wolf SL, Thompson PA, Morris DM, et al. The EXCITE trial: attributes of the Wolf Motor Function Test in patients with subacute stroke. Neurorehabil Neural Repair. 2005;19:194 –205. 23 Uswatte G, Taub E, Morris D, et al. Reliability and validity of the upper-extremity Motor Activity Log-14 for measuring real-world arm use. Stroke. 2005;36:2493– 2496. 24 Uswatte G, Taub E, Morris D, et al. The Motor Activity Log-28: assessing daily use of the hemiparetic arm after stroke. Neurology. 2006;67:1189 –1194. 25 Chen SY, Han CE, Parikh N, et al. BART: a novel laboratory-based instrument to quantify preferred limb use in patients after stroke. Presented at: 38th Annual Meeting of the Society for Neuroscience; November 15–19, 2008; Washington, DC.

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Understanding the Functional Threshold for Paretic Hand and Arm Use After Therapy Appendix. Stepwise Regression

To confirm our theoretical prediction, we used a stepwise regression to determine, in a purely data-driven way, what variables potentially predicted changes in Motor Activity Log Amount of Use (MAL AOU) scale scores after therapy. We used the combined procedures for inclusion and exclusion of variables in SPSS version 14.a The criteria for variable inclusion and exclusion were: probability of F to enter ⱕ0.050, probability of F to remove ⱖ0.10. We found that among a large number of variables (see below) initially considered to predict changes in MAL AOU subscale scores after therapy, only 2 variables were included in the final regression model (regression model with 2 regressors: P⬍.0005, R2⫽0.123, n⫽133). The first variable to be included was the Wolf Motor Function Test Functional Activity Scale (WMFT FAS) score posttherapy (P⬍.0001, standardized coefficient⫽0.42). The second variable to be included was the “weight to box” task with the more-affected arm (a strength task part of the WMFT) measured upon enrollment in the study (P⬍.005, standardized coefficient⫽⫺0.336). The following variables, measured upon enrollment, just before therapy, and 1 week after therapy, were not included in the final model by the stepwise regression algorithm: Upon enrollment: age, marital status, sex, affected side, concordance (did the stroke affect the dominant hand?), functional level (high or low), hand domain of the Stroke Impact Scale (SIS), Fugl-Meyer (FM) motor score, FM proprioception score, total FM score, MAL AOU and Quality of Movement (QOM) subscale scores, time score of the WMFT, and grip strength of the more-affected arm. Before therapy: hand function domain of the SIS, natural logarithm of time score of the WMFT, FM motor score. 1 week after therapy: natural logarithm of time score of the WMFT, FM motor score (SIS data not available after therapy; see Wolf et al7 and Winstein et al19 for details). a

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

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Research Report

Orthopedic Surgeons and Physical Therapists Differ in Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury Kristin R. Archer, Ellen J. MacKenzie, Renan C. Castillo, Michael J. Bosse; for the LEAP Study Group

K.R. Archer, PT, PhD, DPT, is Assistant Professor, Department of Orthopaedics and Rehabilitation, School of Medicine, Vanderbilt University Medical Center, Medical Center East–South Tower, Suite 4200, Nashville, TN 37232 (USA). Address all correspondence to Dr Archer at: kristin.archer@ vanderbilt.edu.

Background. Lower-extremity injuries constitute the leading cause of trauma hospitalizations among people under the age of 65 years. Rehabilitation has the potential to favorably influence the outcomes associated with traumatic lowerextremity injuries.

E.J. MacKenzie, PhD, is Fred and Julie Soper Professor and Chair, Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.

Objectives. The objectives of this study were to explore variability in surgeon and physical therapist assessments of the need for physical therapy in patients with traumatic lower-extremity injuries and to determine the factors associated with assessments of need.

Design. This study was a retrospective cohort investigation. Methods. Participants were 395 patients treated by reconstruction in the LowerExtremity Assessment Project. They were evaluated at 8 level I trauma centers at 3, 6, and 12 months after hospitalization by an orthopedic surgeon and a physical therapist to determine the need for physical therapy. Analyses included multilevel logistic regression.

Results. Chi-square analyses showed that surgeon and therapist assessments of need differed statistically across trauma centers. Surgeons were more likely to assess a need for therapy at 3 months when participants had low work self-efficacy, impaired knee flexion range of motion (ROM), and weight-bearing limitations and at 6 and 12 months when participants had impaired knee flexion ROM and weightbearing and balance limitations. Therapists were more likely to assess a need for therapy at 3 months when participants had moderate to severe pain and at 6 and 12 months when participants had low work self-efficacy, pain, impaired knee flexion ROM, and balance limitations.

Conclusions. The results revealed variability in assessments of the need for physical therapy at the provider and trauma center levels. Differences in provider assessments highlight the need for communication and further investigation into the outcomes and timing of physical therapy for the treatment of traumatic lowerextremity injuries.

R.C. Castillo, PhD, is Assistant Professor, Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University. M.J. Bosse, MD, is Director of Clinical Research and Orthopaedic Traumatologist, Department of Orthopaedic Surgery, Carolinas Medical Center, Charlotte, North Carolina. The LEAP Study Group is: Ellen J. MacKenzie, PhD; Michael J. Bosse, MD; James F. Kellam, MD; Andrew R. Burgess, MD; Lawrence X. Webb, MD; Marc F. Swiontkowski, MD; Roy Sanders, MD; Alan L. Jones, MD; Mark P. McAndrew, MD; Brendan Patterson, MD; Melissa L. McCarthy, ScD; Thomas G. Travison, PhD; and Renan C. Castillo, PhD. [Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ; for the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Phys Ther. 2009; 89:1337– 1349.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org

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L

ower-extremity injuries constitute the leading cause of trauma hospitalizations among adolescents and adults under the age of 65 years.1–3 Long-term impairments often are significant, with research showing moderate to severe levels of disability, low rates of return to employment, and chronic pain for up to 7 years after injury.4 –7 Rehabilitation has the potential to favorably affect these long-term outcomes, but limited research has suggested low levels of use of physical therapy in patients with traumatic lowerextremity injuries.2,3,8 –13 Physician referral practices may contribute to the low levels of use of rehabilitation services. The literature on referral to physical therapists has indicated wide variability in referral rates.14 –17 Research also has demonstrated variations in physician attitudes toward physical therapy and knowledge of available services.18 –20 Overall, these studies on referral patterns have suggested that variations may result in underreferral or inappropriate referral practices.14 –20 Concerns about the implications of referral variability for access to services and patient outcomes have prompted researchers to examine Available With This Article at www.ptjournal.org • Invited Commentary from Michael P. Johnson and the Author Response • Online Invited Commentary from Lynn Snyder-Mackler and the Author Response • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on October 29, 2009, at www.ptjournal.org.

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the physical therapy referral process. In several studies, the content of physician referral with regard to the provision of specific diagnoses and therapeutic procedures has been examined to provide a better understanding of the professional role of physical therapists.19,21–23 Findings consistently have shown that limited referral information is provided to physical therapists and that physicians perceive therapists as technicians rather than as professional colleagues.21 Research also has explored patient-related factors associated with referral to physical therapists, with evidence supporting associations with the age and sex of patients, injury severity, and insurance status.14 –21 However, patientrelated factors explain only a small proportion of the observed variations in physical therapy referral rates.14,15,24 To our knowledge, in only one study have the clinical factors associated with referral to physical therapists been examined. Freburger et al15 found that scores on the Oswestry Disability Index and on the bodily pain, physical function, and role–physical subscales of the Medical Outcomes Study 36-Item Health Survey Questionnaire were associated with referral for the treatment of spine disorders. These authors also reported significant variations in physical therapy referral rates from center to center. On the basis of the poor long-term outcomes of patients with traumatic lower-extremity injuries and the potential for significant provider and site variations in referral practices, the goals of our study were to use the Lower-Extremity Assessment Project (LEAP) database to explore variability in assessments of the need for physical therapy and to compare the factors associated with orthopedic surgeon and physical therapist assessments of need in patients with traumatic lower-extremity injuries. The LEAP database is unique because

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it allows for comparisons across various centers and of surgeon and therapist clinical decision making. Specifically, we aimed to examine variability in assessments of the need for physical therapy in patients across 8 level I trauma centers and to examine the patient-related, medical, and clinical factors associated with surgeon and physical therapist assessments of the need for physical therapy. After a review of the literature on both physical therapy referral and outcomes after traumatic lowerextremity injuries, we tested the hypotheses that variability in assessments of the need for physical therapy would exist at the trauma center level and that patients who had traumatic lower-extremity injuries, patients who were not working, and patients who experienced more pain would be more likely to be assessed as needing physical therapy.

Method For the present study, we used a retrospective cohort design. Data on 395 patients (16 – 69 years of age) treated by lower-extremity reconstruction were obtained from the LEAP database. The LEAP was a multicenter, prospective cohort study designed to examine differences in functional outcomes after reconstruction or amputation because of traumatic lower-extremity injuries. A total of 601 patients were enrolled between March 1994 and June 1997 at 8 level I trauma centers (Carolinas Medical Center, Cleveland MetroHealth Medical Center, Harborview Medical Center, North Carolina Baptist Hospital, R. Adams Cowley Shock Trauma Center, Tampa General Hospital, University of Texas Southwestern Medical Center, and Vanderbilt University Medical Center).25 Lowerextremity trauma was defined, as described by Gustilo et al,26 as type December 2009

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury IIIB and IIIC fractures, selected type IIIA fractures, dysvascular limbs, major soft tissue injuries, and severe foot or ankle injuries. The most notable exclusion criteria were scores of less than 15 on the Glasgow Coma Scale at admission, spinal cord deficits, prior amputation, third-degree burns, inability to speak English or Spanish, documented psychiatric disorders, and active military duty.4 Participants were evaluated at hospital discharge and at 3, 6, and 12 months after hospitalization. Follow-up assessments included a nurse interview and separate orthopedic surgeon and physical therapist evaluations. Measurement of Variables Outcomes. Outcomes included surgeon and physical therapist assessments of a patient’s need for physical therapy and disagreements about assessments of need. At follow-up visits at 3, 6, and 12 months, surgeons and physical therapists conducted separate evaluations of participants. Each provider independently documented either “yes” or “no” as to whether a participant would need physical therapy between that assessment and the next follow-up assessment. A positive, or “yes,” response was considered to be an assessment of the need for physical therapy, and a negative, or “no,” response was considered to be an assessment of no need for physical therapy. Characteristics of participants. Data on the age, sex, race, education, health insurance coverage, poverty level, health before injury, and smoking status of the participants during the initial hospitalization were collected. Poverty was calculated by relating total household income to household size and was categorized as follows: not poor— incomes higher than 200% of the federal poverty level defined by the December 2009

US Census Bureau, nearly poor—incomes within 125% of the federal poverty level, or poor—incomes lower than 125% of the federal poverty level.25,27 Participants rated their health before injury as excellent, good, fair, or poor and were classified as active if they reported involvement in regular exercise at least once per week. Participants were asked if they had any of the following health conditions before injury: asthma, chronic bronchitis, emphysema, arthritis, hypertension, stroke, diabetes, cancer, tuberculosis, or kidney disease. A positive response for at least one of the conditions led to the classification of an individual as having a prior health condition. Participants also were asked if they had ever required medical attention for joint disease, fracture, dislocation, sprain or strain, burn, or ligament injury that involved either leg. A positive response for any of the injury categories indicated a prior leg condition. At each follow-up assessment, participants reported their use of physical therapy services. Participants were asked at 3 months if they had received physical therapy since hospital discharge and were asked at 6 and 12 months if they had received physical therapy since last speaking with the interviewers. Characteristics of injuries. Lower-extremity injuries were classified at the time of admission as tibia shaft or articular fractures, severe ankle or foot injuries, and major soft tissue or dysvascular injuries. The Hannover Fracture Scale28 was used to indicate the extent of bone loss (⬍2 or ⬎2 cm) and contamination (none, single, multiple, or massive). The Predictive Salvage Index29 was used to categorize bone and muscle injuries as mild, moderate, or severe.

whether these complications resulted in a subsequent hospitalization. Fracture healing, as determined from radiographs, was rated as completed healing, progressive healing, or no healing. Edema was described as no edema, mild edema (1⫹), or moderate to severe edema (2⫹ to 4⫹). Occupational factors. Preinjury work status was recorded during the initial hospitalization as either working or not working, and current work status was assessed at each follow-up visit. Participants who reported returning to work either full time or part time were categorized as working. Work self-efficacy was measured in the hospital by asking participants to rate from 1 to 10 how confident they were in their ability to return to work within 1, 3, 6, and 12 months.5 A score of 1 indicated that they were not at all confident, and a score of 10 indicated that they were completely confident. A work self-efficacy score was calculated by multiplying the mean for the 4 levels of confidence by 10. These 4 levels and the scoring method were adapted from selfefficacy scales that were used by Bandura et al30 and Ewart et al31 and that were found to have moderate test-retest reliability and validity, with Pearson correlation coefficients of greater than .80.30,31 Pain. Participants rated their average daily leg pain from “no pain” to “unbearable pain” by using a visual analog scale (VAS), a horizontal line from 0 to 100 mm. The VAS scores were recorded by measuring the distance from 0 (no pain) to the participant’s mark on the line. The scores were categorized as no pain (0 – 4 mm), mild pain (5– 44 mm), moderate pain (45–74 mm), or severe pain (75–100 mm).32

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury Disability. The Sickness Impact Profile (SIP) was administered to measure self-reported health status, with a score of greater than 20 indicating severe disability.33 The SIP consists of 136 items grouped into 12 categories and 2 dimensions of health (physical and psychosocial). The physical dimension comprises the ambulation, mobility, and body care and movement categories, and the psychosocial dimension includes the communication, alertness, and emotional behavior categories. Scores can range from 0 to 100 for the overall instrument, each category, and the 2 dimensions of health. The SIP has been shown to have high test-retest reliability (r⫽.92) and internal consistency (r⫽.94), a multidimensional perspective on function, and sensitivity to small differences in function.34,35 Weight bearing and balance. The weight-bearing status of the injured leg was documented at each follow-up visit as full weight bearing, partial weight bearing, toe touch weight bearing, or non–weight bearing. Two categories were used: full weight bearing and not full weight bearing (including partial weight bearing and toe touch weight bearing). Balancing on the involved limb was assessed with an unsupported singleleg stance task. Participants were asked to stand on 1 leg with their eyes open and their arms across their chest for 30 seconds. The number of seconds a participant was able to stand before dropping the other leg was recorded. A score of 0 seconds was attributed to participants who were unable to perform the task. Participants were classified as either being able to perform the balance task (standing for ⱖ30 seconds) or being unable to perform the task (standing for ⬍30 seconds). A score of less than 30 seconds in an unsupported

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single-leg stance task has been defined as functionally poor.36,37 Range of motion (ROM). Participants were placed in the supine position and asked to actively move the hip and knee joints through flexion and the ankle joint through dorsiflexion (DF) and plantar flexion (PF). In the prone position, participants were asked to lift the hip into extension. The ROM of the hip and knee joints was measured with a universal goniometer, and the ROM of the ankle was measured with a small, fullcircle goniometer.38 High intrarater reliability of the goniometers for knee ROM and ankle ROM has been reported, with intraclass correlation coefficients ranging from .97 to .99 for the knee and from .82 to .86 for the ankle.39,40 The starting and ending positions of each joint, as recommended by the American Academy of Orthopaedic Surgeons, were used to appropriately record measurements; norms were determined on the basis of the averages published by the American Academy of Orthopaedic Surgeons.41 Strength (force-generating capacity). Hip flexion and extension, knee flexion and extension, and ankle DF and PF strength were measured with a Force Evaluation and Testing System (model FET5000) force gauge* anchored to a table; this instrument previously was found to have acceptable levels of interrater and intrarater reliability.42,43 Participants were placed into antigravity positions and asked to apply maximum force against the forceplates. A force transducer produced an output that represented each participant’s force, and the output was displayed on a digital panel meter. Three measurements of each motion of the involved and uninvolved limbs were recorded. An average strength score * Hoggan Health Industries, PO Box 488, West Jordan, Utah 84084.

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for the involved and uninvolved limbs and the ratio of the maximum effort of the injured limb to that of the uninjured limb were calculated. Data Analysis Descriptive statistics explored the percentages of participants needing physical therapy, as assessed by surgeons and physical therapists at each follow-up visit. Chi-square tests were used to compare surgeon and physical therapist assessments of the need for physical therapy in participants across the 8 level I trauma centers. Two outcomes were of interest: surgeon assessment of a participant’s need for physical therapy and physical therapist assessment of a participant’s need for therapy. Separate multilevel logistic regression analyses (1 for surgeon assessment of need and 1 for physical therapist assessment of need) were performed for the 3-, 6-, and 12-month follow-up visits. Random effects were included in all analyses to account for the clustering of visits at the provider and center levels. Subsequently, 2-level random-intercept models were analyzed with the generalized linear latent and mixed model (GLLAMM) macro in the Stata statistical package, version 9.0.†,44,45 The GLLAMM macro produced estimates of the variance of the random effects for providers (␶2) and centers (␻2) but not for participants (␴2). The fractions of the variance attributable to differences between providers and differences between centers were calculated by dividing the variance of the specific random effect by the total variance (␴2 ⫹ ␶2 ⫹ ␻2) in the model. The variance for ␴2 was considered to be ␲2/3 for calculation purposes.44,45

† Stata Corp, 4905 Lakeway Dr, College Station, TX 77845.

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury Separate multilevel bivariate regression analyses at each of the 3 follow-up visits included the following variables for the participants: age, sex, race, education, insurance status, poverty status, smoking status, prior health status, activity level, and prior health conditions and leg injuries; injury type, bone loss, contamination, complications, subsequent hospitalizations, and bone and muscle damage; work self-efficacy and prior and current work status; and fracture healing, edema level, VAS pain score, SIP score, weightbearing status, single-leg balancing on the involved leg, hip and knee flexion and extension ROM, ankle DF and PF ROM, dynamometric strength measurements of hip and knee flexion and extension and ankle DF and PF, and use of physical therapy services. Independent variables that had P values of less than or equal to .25 (Wald test) or that were considered to be relevant to the assessment decision were identified and entered into multiple-variable mixed-model forward and backward logistic regression models.44 The .25 level was used as a screening criterion to allow for the possibility that several variables, each of which may be weakly associated with the outcome, may become important predictors when placed in a model together.46 Patient-related factors (sex, race, insurance status, and prior physical therapy), occupational factors (work status and self-efficacy), injury-related factors (injury severity, fracture healing, and edema level), and clinical factors (VAS pain score, weight-bearing status, balance, knee flexion and extension ROM and strength, and ankle DF and PF strength) were entered as separate groups. Likelihood ratio tests were conducted to remove the least significant covariates, and models also were compared with goodness-of-fit tests. Multicollinearity was explored December 2009

Table 1. Baseline Demographic Characteristics of Study Population (N⫽395) Characteristic

No.

%

White

281

71.1

Nonwhite

114

28.9

297

75.2

98

24.8

Race

Sex Male Female Age (y) 16–24

84

21.3

25–34

108

27.3

35–44

111

28.1

45–54

59

14.9

55⫹

33

8.4

Tibia fracture

207

52.4

Foot or ankle

116

29.4

72

18.2

304

77.0

9

2.3

Injury

Soft tissue or dysvascular Usual major activity Working Laid off or looking Homemaking

12

3.0

Attending school

20

5.1

Other

50

12.6

Poverty status Poor

136

34.4

84

21.3

175

44.3

Less than high school

114

28.9

High school graduate

281

71.1

154

39.0

Nearly poor Not poor Education

Health insurance None Public

34

8.6

Private

207

52.4

Self-assessed health Fair to poor

39

9.9

Good

130

32.9

Excellent

226

57.2

Regular exercise None

163

41.3

⬍4 times/wk

153

38.7

⬎4 times/wk

79

20.0

Never

140

35.4

Former

109

27.7

Current

146

36.9

Smoking history

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury Table 2. Chi-Square Results for Surgeon and Physical Therapist Assessments of Need for Physical Therapy in Participants Across Level I Trauma Centers % of Surgeons Assessing Need for Therapy at: No. of Surgeons

3 mo (nⴝ335)a

6 mo (nⴝ342)b

12 mo (nⴝ338)a

No. of Therapists

3 mo (nⴝ325)a

6 mo (nⴝ326)b

12 mo (nⴝ329)

20

58.5

36.2

16.7

4

61.9

64.3

44.8

B

19

72.7

41.7

23.8

13

91.3

81.8

59.1

C

11

93.8

59.1

44.4

9

96.8

86.4

54.1

D

10

47.4

50.0

5.9

3

43.8

43.8

13.3

E

35

93.3

74.2

46.9

6

84.6

73.3

46.7

F

27

93.9

57.1

34.1

7

86.3

66.7

40.9

G

12

79.3

47.5

16.4

3

49.1

60.7

47.4

Site A

H Total a b

% of Therapists Assessing Need for Therapy at:

14

75.0

65.5

32.3

4

77.8

75.0

54.5

148

78.8

52.3

28.1

49

74.5

70.3

47.1

P⬍.001. P⬍.01.

after regression with the variance inflation factor. Variables that had P values of less than .05 or that were relevant from a theoretical (participant’s sex, race, insurance status, and prior physical therapy) or clinical (injury severity and work status) perspective were retained. The stability of the final model was tested by adding back in each excluded variable one at a time. Overall, missing data represented less than 5% of the following variables: self-efficacy, edema level, VAS pain score, balance, hip flexion and extension ROM and strength, knee flexion and extension ROM and strength, and ankle DF and PF ROM and strength. Missing data were processed by multiple imputation with regression models that imputed the missing values as a function of the other covariates. More specifically, each regression model was analyzed 5 times, and the results were combined to produce a final estimate for the missing values.47,48 Role of the Funding Source This research was supported with funds from the National Institute of Arthritis and Musculoskeletal and 1342

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Skin Diseases, National Institutes of Health (ROI-AR42659); the Johns Hopkins Education and Research Center for Occupational Safety and Health at the Johns Hopkins Bloomberg School of Public Health, which is sponsored by the National Institute for Occupational Safety and Health (T42OH00842428); and the Johns Hopkins Center for Injury Research and Policy at the Johns Hopkins Bloomberg School of Public Health, which is funded by the National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (CE00019803).

Results Selected demographic characteristics of the study population are shown in Table 1. A complete description of this population can be found elsewhere.4,25 Most participants were white (71%), were men (75%), and were between 25 and 54 years of age (70%). Approximately 50% of injuries occurred through motor vehicle and motorcycle collisions. The distribution of injuries included tibia fractures (52.4%), severe foot or ankle injuries (29.4%), and

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major soft tissue or dysvascular injuries (18.2%). Seventy-nine percent of the participants and 75% of the participants were assessed as needing physical therapy by surgeons and by physical therapists, respectively, at the 3-month follow-up visit. The need for physical therapy, as assessed by surgeons, steadily declined, with 52% of the participants needing therapy at 6 months and 28% of the participants needing therapy at 12 months. In comparison, physical therapists found that 70% and 47% of the participants needed therapy at 6 months and at 12 months, respectively. Chi-square analyses were used to test variability in assessments of the need for physical therapy in participants across the 8 level I trauma centers; these analyses revealed that surgeon assessments of need differed statistically across sites at the 3-, 6-, and 12-month follow-up visits (P⬍.01) (Tab. 2). Surgeon assessments of the need for physical therapy ranged from 94% to 47%, 74% to 36%, and 47% to 6% at the 3-, 6-, and 12-month follow-up visits, respectively. PhysiDecember 2009

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury cal therapist assessments of need differed statistically across sites at the 3- and 6-month follow-up visits (P⬍.01). The ranges of physical therapist assessments were 97% to 44%, 86% to 44%, and 59% to 13% at the 3-, 6-, and 12-month follow-up visits, respectively. The centers had different numbers of surgeons and physical therapists participating in the study; some centers had fewer than 15 surgeons and 3 or 4 therapists, whereas others had more than 20 surgeons and 5 therapists.

Table 3. Factors Associated With Orthopedic Surgeon and Physical Therapist Assessments of Need for Physical Therapy in Participants at 3-Month Follow-up Visita Odds Ratio (95% Confidence Interval) for: Factor

Orthopedic Surgeons (nⴝ335)

Physical Therapists (nⴝ325)

Participant characteristics Sex Female (reference) 0.95 (0.43, 2.1)

0.38 (0.16, 0.91)b

3.1 (1.4, 7.1)c

0.39 (0.18, 0.85)b

1.5 (0.65, 3.4)

0.56 (0.23, 1.4)

0.97 (0.96, 0.99)c

1.0 (0.98, 1.0)

0.61 (0.15, 2.4)

1.3 (0.32, 5.2)

Mild

3.0 (1.0, 7.9)

1.1 (0.41, 2.7)

Moderate or severe

1.6 (0.56, 4.4)

4.3 (1.3, 13.8)b

6.5 (2.8, 15.3)c

2.0 (0.80, 4.9)

3.0 (1.4, 6.4)c

1.4 (0.68, 3.0)

Provider variance, SE

0 (0)

2.97 (1.56)

Trauma center variance, SE

1.6 (0.99)

1.49 (1.44)

Male Injury characteristics Articular injury No (reference) Yes

Factors Associated With Assessments of Need for Physical Therapy at 3 Months Table 3 shows multiple-variable multilevel logistic regression results for both surgeon and physical therapist assessments of the need for physical therapy at the 3-month follow-up visit.

Fracture healing Yes (reference) No Occupational factors Self-efficacy (score⫽0–100) Work status Yes (reference) No

Characteristics of participants. The sex of the participants was statistically associated with therapist assessments of the need for therapy, with men being assessed as needing therapy less often than women (odds ratio [OR]⫽0.38, P⬍.05).

Clinical factors Pain (visual analog scale) None (reference)

Weight bearing Full (reference)

Characteristics of injuries. Surgeons assessed participants with articular injuries (OR⫽3.1, P⬍.01) as needing therapy more often than participants with nonarticular injuries, whereas therapists assessed participants with articular injuries (OR⫽0.39, P⬍.05) as needing therapy less often than participants with nonarticular injuries. Occupational factors. Higher work self-efficacy beliefs were negatively associated with surgeon assessments of the need for physical therapy (OR⫽0.97, P⬍.01).

Not full Knee flexion range of motion ⱖ135° (reference) ⬍135° Random effects

a

Results were obtained from multilevel logistic regression models, which were adjusted for prior physical therapy, race, insurance coverage, and level of edema. b P⬍.05. c P⬍.01.

Clinical factors. No association was found between surgeon assessments of need and participants’ VAS pain scores, but physical therapists December 2009

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury were more likely to assess participants as needing therapy when they had moderate to severe pain (OR⫽4.3, P⬍.05) rather than no pain. However, participants with weight-bearing limitations were more likely to be assessed as needing therapy by surgeons (OR⫽6.5, P⬍.01), whereas no association was found with therapist assessments. Impaired knee flexion ROM was statistically associated with surgeon assessments of the need for physical therapy (OR⫽3.0, P⬍.01).




Injury characteristics Articular injury No (reference) Yes

1.2 (0.69, 2.2)

1.0 (0.52, 2.0)

1.7 (1.1, 3.2)b

1.1 (0.59, 2.4)

0.99 (0.98, 1.0)

0.98 (0.97, 0.99)c

0.75 (0.37, 1.5)

1.4 (0.62, 3.1)

Mild

1.0 (0.49, 2.2)

2.4 (1.1, 5.5)b

Moderate or severe

1.2 (0.53, 2.8)

2.8 (1.1, 7.4)b

3.1 (1.6, 6.3)c

0.80 (0.34, 1.8)

2.5 (1.3, 4.8)c

2.8 (1.3, 6.4)b

2.3 (1.3, 4.1)c

3.6 (1.7, 7.6)c

Provider variance, SE

0.36 (0.39)

1.26 (0.75)

Trauma center variance, SE

0 (0)

0.06 (0.34)

Fracture healing Yes (reference) No Occupational factors

Random effects. The fractions of the variance attributable to nonmeasured provider characteristics were 0% in the surgeon assessment model and 38% in the therapist assessment model. Trauma center characteristics explained 33% and 19% of the variance in the surgeon and therapist models, respectively.

Self-efficacy (score⫽0–100) Work status Yes (reference) No Clinical factors Pain (visual analog scale) None (reference)

Factors Associated With Assessments of Need for Physical Therapy at 6 Months Table 4 shows multiple-variable multilevel logistic regression results for both surgeon and physical therapist assessments of the need for physical therapy at the 6-month follow-up visit.

Weight bearing Full (reference) Not full Balancing on involved leg Able (reference) Unable Knee flexion range of motion ⱖ135° (reference)

Characteristics of injuries. Progressive healing or no fracture healing (OR⫽1.7) was statistically associated with surgeon assessments of the need for physical therapy (P⬍.05).

⬍135° Random effects

a

Occupational factors. Higher work self-efficacy beliefs were negatively associated with therapist assessments of the need for physical therapy (OR⫽0.98, P⬍.01). Clinical factors. No association was found between surgeon assessments of need and participants’ VAS pain scores, but physical therapists were more likely to assess participants as needing therapy when they had mild pain (OR⫽2.4, P⬍.05) or 1344

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Results were obtained from multilevel logistic regression models, which were adjusted for prior physical therapy, sex, race, insurance coverage, and level of edema. b P⬍.05. c P⬍.01.

moderate to severe pain (OR⫽2.8, P⬍.05) rather than no pain. However, participants with weightbearing limitations were more likely to be assessed as needing therapy by surgeons (OR⫽3.1, P⬍.01), whereas no association was found with therapist assessments. Limitations of the involved leg in the single-leg balance

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task and impaired knee flexion ROM were statistically associated with both surgeon and therapist assessments of the need for physical therapy (P⬍.05). Random effects. The fractions of the variance attributable to nonmeasured provider characteristics were December 2009

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury 10% in the surgeon assessment model and 27% in the therapist assessment model. Trauma center characteristics explained 0% and 1% of the variance in the surgeon and therapist models, respectively.


Articular injury No (reference) Yes

0.84 (0.48, 1.5)

2.8 (1.2, 6.9)b

2.1 (0.94, 4.6)

1.0 (0.98, 1.0)

0.99 (0.98, 0.99)c

0.76 (0.37, 1.6)

1.1 (0.60, 1.9)

Mild

0.68 (0.26, 1.8)

1.7 (0.76, 4.0)

Moderate or severe

0.99 (0.33, 3.0)

2.6 (1.0, 6.5)c

8.0 (2.9, 22.0)b

2.7 (1.1, 7.2)

2.7 (1.0, 7.4)c

3.0 (1.5, 6.0)b

5.2 (2.4, 11.0)b

3.2 (1.7, 6.2)b

2.0 (1.2)

0.36 (0.27)

Yes (reference) No Occupational factors Self-efficacy (score⫽0–100) Work status Yes (reference) No Clinical factors Pain (visual analog scale) None (reference)

Occupational factors. Higher work self-efficacy beliefs were negatively associated with therapist assessments of the need for physical therapy (OR⫽0.98, P⬍.05).

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0.90 (0.44, 1.9)

Fracture healing

Characteristics of injuries. Progressive or no fracture healing (OR⫽2.8) was statistically associated with surgeon assessments of the need for physical therapy (P⬍.01).

Random effects. The fractions of the variance attributable to nonmeasured provider characteristics were 36% in the surgeon assessment


Injury characteristics

Factors Associated With Assessment of Need for Physical Therapy at 12 Months Table 5 shows multiple-variable multilevel logistic regression results for both surgeon and physical therapist assessments of the need for physical therapy at the 12-month follow-up visit.

Clinical factors. No association was found between surgeon assessments of need and participants’ VAS pain scores, but physical therapists were more likely to assess participants as needing therapy when they had moderate to severe pain (OR⫽2.6, P⬍.05) rather than no pain. However, participants with weight-bearing limitations were more likely to be assessed as needing therapy by surgeons (OR⫽8.0, P⬍.01), whereas no association was found with therapist assessments. Limitations of the involved leg in the single-leg balance task and impaired knee flexion ROM were statistically associated with both surgeon and therapist assessments of the need for physical therapy (P⬍.05).


Weight bearing Full (reference) Not full Balance for involved leg Able (reference) Unable Knee flexion range of motion ⱖ135° (reference) ⬍135° Random effects Provider variance, SE Trauma center variance, SE

25.0 (0.50)

0 (0)

a

Results were obtained from multilevel logistic regression models, which were adjusted for prior physical therapy, sex, race, insurance coverage, and level of edema. b P⬍.01. c P⬍.05.

model and 10% in the therapist assessment model. Trauma center characteristics explained 5% and 0% of the variance in the surgeon and therapist models, respectively.

Discussion A weight-bearing limitation and impaired knee flexion ROM were conVolume 89

sistently associated with surgeon assessments of the need for physical therapy across a 12-month recovery period in participants with traumatic lower-extremity injuries; for physical therapists, the associated factor was moderate to severe pain. Injury severity was important to both surgeons and physical therapists at the Number 12

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury 3-month follow-up assessment, and balance limitations and impaired knee flexion ROM were important at the 6- and 12-month assessments. Characteristics of injuries associated only with surgeon assessments of need at 6 and 12 months included delayed fracture healing. Although these findings provide insight into similarities and differences in surgeon and therapist assessments of the need for physical therapy, they explain only a small proportion of the observed assessment variability. The variability in assessments across the 8 participating level I trauma centers and between providers and the variance of the random effects indicate that some of the variability can be attributed to trauma center and provider characteristics. As indicated in the literature, provider characteristics may include practice style, clinical uncertainty, outcome expectations, and knowledge of and experience with physical therapy, and trauma center characteristics such as medical culture, colleagues’ expectations, and training protocols may influence the assessment process.49 –56 Characteristics of the participants were not found to significantly influence surgeon assessments of the need for physical therapy. This finding was surprising because studies of physician referral to both physical therapists and medical specialists have reported an association between referral and the age, sex, education, and insurance coverage of the participants.15,50 –57 However, these studies did not control for the extensive clinical and injury factors included in our analyses. In addition, this difference might be attributable to the severity of the injuries in our study population. As expected, participants with more severe injuries, such as articular fractures and delayed fracture healing, 1346

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were more likely to be assessed by surgeons as needing physical therapy. However, fracture healing did not significantly influence therapist assessments of need, and an articular injury was negatively associated with a therapist assessment at 3 months. This difference might have been a result of minimal communication between the surgeon and the therapist about the nature of the injury, the surgical procedure, and postoperative radiographic findings. Further support for a lack of communication between providers was demonstrated by the findings for weightbearing limitations. Surgeons considered weight bearing to be one of the most important factors during assessments of the need for physical therapy at all follow-up time points, but weight bearing was not statistically associated with therapist assessments. This difference might have reflected a desire by therapists to postpone gait rehabilitation until later in the recovery period and to focus instead on pain and on ROM and balance impairments. An important finding was that, although ROM was explored for the hip, knee, and ankle, only the knee appeared to be particularly relevant to assessments of the need for physical therapy. The insignificant hip joint findings might have been related to the distribution of injuries in the present study because relatively few participants had hip impairments (as opposed to knee and ankle impairments). Our hypothesis that pain would be associated with surgeon assessments of the need for physical therapy was not supported by the study results. This finding was unexpected because pain has been found to contribute to long-term disability and poor vocational outcomes10,58,59 and because clinical trials have found physical therapy to favorably affect pain in patients with various musculoskeletal conditions.60 – 63 On the basis of the poor long-term outcomes

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of this patient population, it is important to determine the specific effects of physical therapy on patients’ pain complaints and disseminate this information to both surgeons and physical therapists treating traumatic lower-extremity injuries. In addition, it would be beneficial to examine orthopedic surgeons’ attitudes and beliefs about the management of postoperative pain. The nonsignificant finding for work status was also unexpected because rehabilitation has been shown to improve occupational outcomes3,64,65 and often has been considered an appropriate treatment for patients experiencing workplace limitations.66,67 Instead, patients’ work self-efficacy was significantly related to surgeon assessments of the need for physical therapy at 3 months and therapist assessments at 6 and 12 months, suggesting that patients’ belief in their ability to return to work and not their actual work status influenced assessments. This finding might be explained by the severity of injuries in this patient population. Lower-extremity injuries treated by reconstruction have high rates of complications and often require additional surgery during the first year of recovery, leading to a delayed return to work.68,69 Thus, physical deficits and patients’ work self-efficacy, important predictors of a return to work,10 may be more important during the first 12 months of recovery than employment status per se. Of interest was the finding of differences in assessments between surgeons and physical therapists across the 12-month recovery period. The results suggested that surgeons and therapists tended to assess participants as needing physical therapy at 3 months but that, although there was a steady decline in surgeon assessments of participants as needing therapy at 6 and 12 months, the rates of therapist assessments of the need December 2009

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury for therapy remained relatively high. Seventy percent of the participants at 6 months and almost half of the participants at 12 months were assessed by therapists as needing therapy. The results suggested that participants with traumatic lowerextremity injuries might not be referred by surgeons for physical therapy further into their recovery. The findings support the need for more communication between surgeons and physical therapists about the plan of care for participants at 6- and 12-month follow-up evaluations. The limitations of the present study must be taken into account in interpretations of the results. First, the LEAP study was conducted more than 10 years ago. Studies have documented little change in the physical therapy referral process,19,21,22 with variability in referral rates, the content of referral prescriptions, the limited professional role of physical therapists, and the influence of patient-related factors on referral to physical therapists remaining consistent.14 –24,70 However, both formal and informal roles of physical therapists in the health care system have expanded during the last decade; thus, study results need to be interpreted with caution because of the age of the data set. We attempted to mitigate this limitation of the present study by conducting a prospective, cross-sectional survey of 274 surgeon members of the Orthopaedic Trauma Association (OTA) to verify the findings in the surgeon assessment model.71 Surgeons were asked to make physical therapy referral decisions on the basis of traumatic lower-extremity cases abstracted from the LEAP database. The results supported the association between surgeon referral to physical therapists and weight-bearing status, knee flexion ROM, and injury severity. Furthermore, pain relief and return to work did not appear to be expected outcomes of referral to physDecember 2009

ical therapists for the treatment of traumatic lower-extremity injury. A second limitation is that the outcome measures of assessments of need for physical therapy were not confirmed with documented referral prescriptions, a fact that limited the generalizability of our findings to the broader referral process. Also, the results might not be generalizable beyond providers at level I trauma centers because of their training and expertise. Third, the occupational factors of preinjury work status and current work status were based on patient self-report, a fact that might have resulted in an underestimation of the association between work status and the assessment of need. Fourth, orthopedic surgeons and physical therapists followed different evaluation protocols, a fact that might have contributed to the differences in the assessment models. However, surgeon and physical therapist evaluation procedures are inherently different because of training and experience, and the LEAP study procedures represented current clinical practice at level I trauma centers.

clude identifying the surgeon and level I trauma center characteristics that contribute to variations in referral practices to facilitate the development of an effective strategy for decreasing variability; determining surgeon perceptions and management of postoperative pain and work status in patients to facilitate an understanding of current clinical practice; and exploring the optimal time for referral to physical therapists of patients with traumatic lowerextremity injuries. Furthermore, examining the effects of physical therapy on pain and work outcomes in this patient population and disseminating this information to orthopedic surgeons have the potential to improve the long-term outcomes associated with traumatic lowerextremity injuries. All authors provided concept/idea/research design and data analysis. Dr Archer, Dr MacKenzie, and Dr Castillo provided writing. Dr Castillo and Dr Bosse provided data collection and fund procurement. Dr Castillo provided project management. Dr Bosse provided participants. Dr MacKenzie provided institutional liaisons. Dr Archer and Dr Castillo provided consultation (including review of manuscript before submission).

Despite these study limitations, we found evidence that variability in assessments of the need for physical therapy existed not only at the provider and trauma center levels but also throughout the 12-month recovery period. The findings emphasized the need for communication about the nature of the patient’s injury, the surgical procedure, postoperative healing status, the patient’s pain level, and weight-bearing status. Focusing on these factors has the potential to improve access to and appropriate use of physical therapy for patients with traumatic lowerextremity injuries.

This study was approved by the institutional review boards at the coordinating center (Johns Hopkins School of Public Health, Baltimore, Maryland) and at each study site.

On the basis of the findings of the present study, specific recommendations for future research on traumatic lower-extremity injuries in-

A platform presentation of this research was given at the Annual Conference and Exposition of the American Physical Therapy Asso-

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This research was supported with funds from the National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health (ROI-AR42659); the Johns Hopkins Education and Research Center for Occupational Safety and Health at the Johns Hopkins Bloomberg School of Public Health, which is sponsored by the National Institute for Occupational Safety and Health (T42OH00842428); and the Johns Hopkins Center for Injury Research and Policy at the Johns Hopkins Bloomberg School of Public Health, which is funded by the National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (CE000198-03).

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury ciation; June 11–14, 2008; San Antonio, Texas. This article was received June 25, 2008, and was accepted August 7, 2009. DOI: 10.2522/ptj.20080200

References 1 Rice DP, MacKenzie EJ, Jones AS, et al. Cost of Injury in the United States: A Report to Congress. San Francisco, CA: Institute for Health and Aging at the University of California and Injury Prevention Center at The Johns Hopkins University; 1989. 2 Dillingham TR, Pezzin LE, MacKenzie EJ. Incidence, acute care length of stay, and discharge to rehabilitation of traumatic amputee patients: an epidemiologic study. Arch Phys Med Rehabil. 1998;79: 279 –287. 3 Pezzin LE, Dillingham TR, MacKenzie EJ. Rehabilitation and long-term outcomes of persons with trauma-related amputations. Arch Phys Med Rehabil. 2000;81: 292–300. 4 Bosse MJ, MacKenzie EJ, Kellam JF, et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N Engl J Med. 2002;347:1924 –1931. 5 MacKenzie EJ, Bosse MJ, Pollak AN, et al. Long-term persistence of disability following severe lower-limb trauma. J Bone Joint Surg Am. 2005;87:1801–1809. 6 McCarthy ML, MacKenzie EJ, Edwin D, et al. Psychological distress associated with severe lower-limb injury. J Bone Joint Surg Am. 2003;85:1689 –1697. 7 Castillo RC, MacKenzie EJ, Wegener ST, Bosse MJ. Prevalence of chronic pain seven years following limb threatening lower extremity trauma. Pain. 2006; 124:321–329. 8 MacKenzie EJ, Morris JA, Jurkovich GJ, et al. Return to work following injury: the role of economic, social, and job-related factors. Am J Public Health. 1998;88: 1630 –1637. 9 Schoppen T, Boonstra A, Groothoff JW, et al. Employment status, job characteristics, and work-related health experience of people with a lower limb amputation in the Netherlands. Arch Phys Med Rehabil. 2001;82:239 –245. 10 MacKenzie EJ, Bosse MJ, Kellam JF, et al. Early predictors of long-term work disability following major limb trauma. J Trauma. 2006;61:688 – 694. 11 Jelic M, Eldar R. Rehabilitation following major traumatic amputation of lower limbs: a review. Clin Rev Phys Rehabil Med. 2003;15:235–252. 12 Archer KR, Castillo RC, MacKenzie EJ, Bosse MJ. Gait symmetry and walking speed analysis following lower-extremity trauma. Phys Ther. 2006;86:1630 –1640. 13 Castillo RC, MacKenzie EJ, Webb LX, et al. Use and perceived need of physical therapy following severe lower-extremity trauma. Arch Phys Med Rehabil. 2005;86: 1722–1728.

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14 Freburger JK, Holmes GM, Carey TS. Physician referrals to physical therapy for the treatment of musculoskeletal conditions. Arch Phys Med Rehabil. 2003;84: 1839 –1849. 15 Freburger JK, Carey TS, Holmes GM. Physician referrals to physical therapists for the treatment of spine disorders. Spine J. 2005;5:530 –541. 16 Ward AW, Williams BT, Dixon RA. Physiotherapy: its prescription and implementation for orthopaedic out-patients. Rheumatol Rehabil. 1978;17:14 –22. 17 Pless BI, Satterwhite B, Van Vechten D. Chronic illness in childhood: a regional survey of care. Pediatrics. 1976;52:37– 46. 18 Ritchey FJ, Pinkston D, Goldbaum JE, Heerten ME. Perceptual correlates of physician referral to physical therapists: implications for role expansion. Soc Sci Med. 1989;28:69 – 80. 19 Uili RM, Shepard KF, Savinar E. Physician knowledge and utilization of physical therapy procedures. Phys Ther. 1984;64: 1523–1529. 20 Kerssens JJ, Groenewegen PP. Referrals to physiotherapy: the relation between the number of referrals, the indication for referral, and the inclination to refer. Soc Sci Med. 1990;30:797– 804. 21 Davenport TE, Watts HG, Kulig K, Resnik C. Current status and correlates of physicians’ referral diagnoses for physical therapy. J Orthop Sports Phys Ther. 2005;35: 572–579. 22 Clawson Al, Domholdt E. Content of physician referrals to physical therapists at clinical education sites in Indiana. Phys Ther. 1994;74:356 –360. 23 Wong WP, Galley P, Sheehan M. Changes in medical referrals to an outpatient physiotherapy department. Aust J Physiother. 1994;40:9 –14. 24 Ehrmann-Feldman D, Rossignol M, Abenhaim L, Gobeille D. Physician referral to physical therapy in a cohort of workers compensated for low back pain. Phys Ther. 1996;76:150 –157. 25 MacKenzie EJ, Bosse MJ, Kellam JF, et al. Characterization of patients with highenergy lower extremity trauma. J Orthop Trauma. 2000;14:455– 466. 26 Gustilo RB, Mendoza RM, Williams DN. Problems in the management of type III (severe) open fractures: a new classification of type III open fractures. J Trauma. 1984;24:742–746. 27 Fisher GM. The development and history of the poverty thresholds. Soc Sci Bull. 1992;55:3–14. 28 Suedkamp NP, Barbey N, Veuskens A, et al. The incidence of osteitis in open fractures: an analysis of 948 open fractures (a review of the Hannover experience). J Orthop Trauma. 1993;7:473– 482. 29 Howe HR, Poole GV, Hansen KJ, et al. Salvage of lower extremities following combined orthopedic and vascular trauma: a predictive salvage index. Am Surg. 1987;53:205–208.

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30 Bandura A, O’Leary A, Taylor CB, et al. Perceived self-efficacy and pain control: opioid and nonopioid mechanisms. J Pers Soc Psychol. 1987;53:563–571. 31 Ewart CK, Stewart KJ, Gillian RE, Keleman MH. Self-efficacy mediates strength gains during circuit weight training in men and women with coronary artery disease. Med Sci Sports Exerc. 1986;18:531–540. 32 Jensen MP, Chen C, Brugger AM. Interpretation of visual analog scale ratings and change scores: a reanalysis of two clinical trials of postoperative pain. J Pain. 2003;4:407– 414. 33 Bergner M, Bobbitt RA, Carter WB, Gilson BS. The Sickness Impact Profile: development and final revision of a health status measure. Med Care. 1981;19:787– 805. 34 De Bruin AF, de Witte LP, Stevens F, Diedriks JP. Sickness Impact Profile: the state of the art of a generic functional status measure. Soc Sci Med. 1992;35: 1003–1014. 35 Jurkovich G, Mock C, MacKenzie E, et al. The Sickness Impact Profile as a tool to evaluate functional outcome in trauma patients. J Trauma. 1995;39:625– 631. 36 Schoppen T, Boonstra A, Groothoff JW, et al. Physical, mental, and social predictors of functional outcome in unilateral lower-limb amputees. Arch Phys Med Rehabil. 2003;84:803– 811. 37 Magee DJ. Orthopedic Physical Assessment. Philadelphia, PA: WB Saunders Co; 1997. 38 Norkin CC, White DJ. Measurement of Joint Motion: A Guide to Goniometry. 3rd ed. Philadelphia, PA: FA Davis Co; 2003. 39 Brosseau L, Balmer S, Tousignant M, et al. Intra- and intertester reliability and criterion validity of the parallelogram and universal goniometers for measuring maximum active knee flexion and extension of patients with knee restrictions. Arch Phys Med Rehabil. 2001;82:396 – 402. 40 Youdas JW, Bogard CL, Suman VJ. Reliability of goniometric measurements and visual estimates of ankle joint active range of motion obtained in a clinical setting. Arch Phys Med Rehabil. 1993;74:111–118. 41 American Academy of Orthopaedic Surgeons. Joint Motion: Method of Measuring and Recording. Chicago, IL: American Academy of Orthopaedic Surgeons; 1965. 42 Peindl RD, McCarthy ML, MacKenzie EJ, inventors; The Johns Hopkins University and The Charlotte-Mecklenburg Hospital Authority, assignees. Apparatus for exercising and measuring strength of a patient’s limb and an adjustable pivot clamp. US patent 5,662,591. September 2, 1997. 43 McCarthy ML, McAndrew MP, MacKenzie EJ, et al. Correlation between the measures of impairment, according to the modified system of the American Medical Association, and function. J Bone Joint Surg Am. 1998;80:1034 –1042. 44 Rabe-Hesketh S, Skrondal A. Multilevel and Longitudinal Modeling Using Stata. College Station, TX: Stata Press; 2005.

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury 45 Rabe-Hesketh S, Skrondal A, Pickles A. GLLAMM Manual (October 2004). UC Berkeley Division of Biostatistics Working Paper Series. Working Paper 160. Available at: http://www.bepress.com/ ucbbiostat/paper160. Accessed September 4, 2009. 46 Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley & Sons, Inc; 2000. 47 van Buuren S, Oudshoorn CGM. Multivariate Imputation by Chained Equations: MICE V1.0 User’s Manual. Leiden, the Netherlands: TNO Preventie en Gezondheid; 2000. Report PG/VGZ/00.038. 48 Royston P. Multiple imputation of missing values. Stata Journal. 2004;4:227–241. 49 Jorgensen CK, Olesen F. Predictors for referral to physiotherapy from general practice. Scand J Prim Health Care. 2001;19:48 –53. 50 Bertakis KD, Callahan EJ, Azari R, Robbins JA. Predictors of patient referrals by primary care residents to specialty care clinics. Fam Med. 2001;33:203–209. 51 Shea D, Stuart B, Vasey J, Nag S. Medicare physician referral patterns. Health Serv Res. 1999;34:331–348. 52 Cowen ME, Zodet MW. Methods for analyzing referral patterns. J Gen Intern Med. 1999;14:474 – 480. 53 Franks P, Williams GC, Zwanziger J, et al. Why do physicians vary so widely in their referral rates? J Gen Intern Med. 2000;15:163–168. 54 Chan BT, Austin PC. Patient, physician, and community factors affecting referrals to specialists in Ontario, Canada: a population-based, multi-level modeling approach. Med Care. 2003;41:500 –511.

Invited Commentary My congratulations to Archer and colleagues1 on a well-designed and thoughtful health services research study that examined factors associated with the assessment of need for physical therapy services among patients with traumatic lowerextremity injury. This report is a valuable addition to the literature and helps to uncover issues that ultimately affect a patient’s access to physical therapy services. The study examined the assessment of need for physical therapy services by both orthopedic surgeons and physical therapists. It is somewhat December 2009

55 Bachman KH, Freeborn DK. HMO physicians’ use of referrals. Soc Sci Med. 1999;8:547–557. 56 Forrest CB, Nutting P, Werner JJ, et al. Managed health plan effects on the specialty referral process: results from the Ambulatory Sentinel Practice Network referral study. Med Care. 2003;41:242–253. 57 Franks P, Clancy CM. Referrals of adult patients from primary care: demographic disparities and their relationship to HMO insurance. J Fam Pract. 1997;45:47–53. 58 MacKenzie EJ, Cushing BM, Jurkovich GJ, et al. Physical impairment and functional outcomes six months after severe lower extremity fracture. J Trauma. 1993;34: 528 –539. 59 Mock C, MacKenzie E, Jurkovich G, et al. Determinants of disability after lower extremity fracture. J Trauma. 2000;49: 1002–1011. 60 Hurwitz EL, Aker PD, Adams AH, et al. Manipulation and mobilization of the cervical spine: a systematic review of the literature. Spine. 1996;21:1746 –1759. 61 Bergman GJ, Winters JC, Groenler KH, et al. Manipulative therapy in addition to usual care for patients with shoulder dysfunction and pain. Ann Intern Med. 2004;141:432– 439. 62 Hayden JA, van Tulder MW, Tomlinson G. Systematic review: strategies for using exercise therapy to improve outcomes in chronic low back pain. Ann Intern Med. 2005;142:776 –785. 63 Harris GR, Susman JL. Managing musculoskeletal complaints with rehabilitation therapy: summary of the Philadelphia Panel evidence-based clinical practice guidelines on musculoskeletal rehabilitation interventions. J Fam Pract. 2002; 51:1042–1046.

64 Sheikh K. Return to work following limb injuries. J Soc Occup Med. 1985;35: 114 –117. 65 Schmidt SH, Oort-Marburger D, Meijman TF. Employment after rehabilitation for musculoskeletal impairments: the impact of vocational rehabilitation and working on a trial basis. Arch Phys Med Rehabil. 1995;76:950 –954. 66 Livingston DH, Keenan D, Kim D, et al. Extent of disability following traumatic extremity amputation. J Trauma. 1994;37: 495– 499. 67 Morris JA Jr, Sanchez AA, Bass SM, MacKenzie EJ. Trauma patients return to productivity. J Trauma. 1991;31:827– 834. 68 Fairhurst MJ. The function of below-knee amputees versus the patient with salvaged grade III tibial fracture. Clin Orthop. 1994;301:227–232. 69 Busse JW, Jacobs CL, Swiotkowski MF, et al. Complex limb salvage or early amputation for severe lower-limb injury: a metaanalysis of observational studies. J Orthop Trauma. 2007;21:70 –76. 70 Joyce J, Kuperstein J. Improving physical therapy referrals. Am Fam Phys. 2005; 71:1183–1184. 71 Archer KR, MacKenzie EJ, Bosse MJ, et al. Factors associated with surgeon referral for physical therapy in patients with traumatic lower-extremity injury: results of a national survey of orthopedic trauma surgeons. Phys Ther. 2009;89:893–905.

Michael P. Johnson

surprising that factors such as insurance status (nearly 40% of the study population was uninsured), education, and poverty level did not have any impact on the assessment of need for physical therapy services. A large body of literature exists that supports these variables as key indicators for patients who are likely to receive medical care, including physical therapy.2– 4 The authors indicate that these findings may have been due to the fact that their study included a broad range of clinical and injury-specific variables, which could be better predictors of who needs physical therapy services. This Volume 89

may be true. The broad range of variables included in the multivariate regression analysis models is a clear strength of this study. Few previous articles have included the breadth of variables when designing regression models to examine clinical behavior. The findings from this study also may be attributed to the fact that the surgeons and physical therapists involved were making assessments for who they believed needed physical therapy services. As the authors noted, the article did not include data to describe how many of those patients for whom a physical therapy Number 12

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury 45 Rabe-Hesketh S, Skrondal A, Pickles A. GLLAMM Manual (October 2004). UC Berkeley Division of Biostatistics Working Paper Series. Working Paper 160. Available at: http://www.bepress.com/ ucbbiostat/paper160. Accessed September 4, 2009. 46 Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley & Sons, Inc; 2000. 47 van Buuren S, Oudshoorn CGM. Multivariate Imputation by Chained Equations: MICE V1.0 User’s Manual. Leiden, the Netherlands: TNO Preventie en Gezondheid; 2000. Report PG/VGZ/00.038. 48 Royston P. Multiple imputation of missing values. Stata Journal. 2004;4:227–241. 49 Jorgensen CK, Olesen F. Predictors for referral to physiotherapy from general practice. Scand J Prim Health Care. 2001;19:48 –53. 50 Bertakis KD, Callahan EJ, Azari R, Robbins JA. Predictors of patient referrals by primary care residents to specialty care clinics. Fam Med. 2001;33:203–209. 51 Shea D, Stuart B, Vasey J, Nag S. Medicare physician referral patterns. Health Serv Res. 1999;34:331–348. 52 Cowen ME, Zodet MW. Methods for analyzing referral patterns. J Gen Intern Med. 1999;14:474 – 480. 53 Franks P, Williams GC, Zwanziger J, et al. Why do physicians vary so widely in their referral rates? J Gen Intern Med. 2000;15:163–168. 54 Chan BT, Austin PC. Patient, physician, and community factors affecting referrals to specialists in Ontario, Canada: a population-based, multi-level modeling approach. Med Care. 2003;41:500 –511.

Invited Commentary My congratulations to Archer and colleagues1 on a well-designed and thoughtful health services research study that examined factors associated with the assessment of need for physical therapy services among patients with traumatic lowerextremity injury. This report is a valuable addition to the literature and helps to uncover issues that ultimately affect a patient’s access to physical therapy services. The study examined the assessment of need for physical therapy services by both orthopedic surgeons and physical therapists. It is somewhat December 2009

55 Bachman KH, Freeborn DK. HMO physicians’ use of referrals. Soc Sci Med. 1999;8:547–557. 56 Forrest CB, Nutting P, Werner JJ, et al. Managed health plan effects on the specialty referral process: results from the Ambulatory Sentinel Practice Network referral study. Med Care. 2003;41:242–253. 57 Franks P, Clancy CM. Referrals of adult patients from primary care: demographic disparities and their relationship to HMO insurance. J Fam Pract. 1997;45:47–53. 58 MacKenzie EJ, Cushing BM, Jurkovich GJ, et al. Physical impairment and functional outcomes six months after severe lower extremity fracture. J Trauma. 1993;34: 528 –539. 59 Mock C, MacKenzie E, Jurkovich G, et al. Determinants of disability after lower extremity fracture. J Trauma. 2000;49: 1002–1011. 60 Hurwitz EL, Aker PD, Adams AH, et al. Manipulation and mobilization of the cervical spine: a systematic review of the literature. Spine. 1996;21:1746 –1759. 61 Bergman GJ, Winters JC, Groenler KH, et al. Manipulative therapy in addition to usual care for patients with shoulder dysfunction and pain. Ann Intern Med. 2004;141:432– 439. 62 Hayden JA, van Tulder MW, Tomlinson G. Systematic review: strategies for using exercise therapy to improve outcomes in chronic low back pain. Ann Intern Med. 2005;142:776 –785. 63 Harris GR, Susman JL. Managing musculoskeletal complaints with rehabilitation therapy: summary of the Philadelphia Panel evidence-based clinical practice guidelines on musculoskeletal rehabilitation interventions. J Fam Pract. 2002; 51:1042–1046.

64 Sheikh K. Return to work following limb injuries. J Soc Occup Med. 1985;35: 114 –117. 65 Schmidt SH, Oort-Marburger D, Meijman TF. Employment after rehabilitation for musculoskeletal impairments: the impact of vocational rehabilitation and working on a trial basis. Arch Phys Med Rehabil. 1995;76:950 –954. 66 Livingston DH, Keenan D, Kim D, et al. Extent of disability following traumatic extremity amputation. J Trauma. 1994;37: 495– 499. 67 Morris JA Jr, Sanchez AA, Bass SM, MacKenzie EJ. Trauma patients return to productivity. J Trauma. 1991;31:827– 834. 68 Fairhurst MJ. The function of below-knee amputees versus the patient with salvaged grade III tibial fracture. Clin Orthop. 1994;301:227–232. 69 Busse JW, Jacobs CL, Swiotkowski MF, et al. Complex limb salvage or early amputation for severe lower-limb injury: a metaanalysis of observational studies. J Orthop Trauma. 2007;21:70 –76. 70 Joyce J, Kuperstein J. Improving physical therapy referrals. Am Fam Phys. 2005; 71:1183–1184. 71 Archer KR, MacKenzie EJ, Bosse MJ, et al. Factors associated with surgeon referral for physical therapy in patients with traumatic lower-extremity injury: results of a national survey of orthopedic trauma surgeons. Phys Ther. 2009;89:893–905.

Michael P. Johnson

surprising that factors such as insurance status (nearly 40% of the study population was uninsured), education, and poverty level did not have any impact on the assessment of need for physical therapy services. A large body of literature exists that supports these variables as key indicators for patients who are likely to receive medical care, including physical therapy.2– 4 The authors indicate that these findings may have been due to the fact that their study included a broad range of clinical and injury-specific variables, which could be better predictors of who needs physical therapy services. This Volume 89

may be true. The broad range of variables included in the multivariate regression analysis models is a clear strength of this study. Few previous articles have included the breadth of variables when designing regression models to examine clinical behavior. The findings from this study also may be attributed to the fact that the surgeons and physical therapists involved were making assessments for who they believed needed physical therapy services. As the authors noted, the article did not include data to describe how many of those patients for whom a physical therapy Number 12

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury need was determined actually received a referral for physical therapy. The outcome of the question “Do you believe this patient needs physical therapy services?” may differ from whether the patient actually received a referral for physical therapy services. Additionally, the fact that a patient received a referral for physical therapy services may not assure that he or she was able to see a physical therapist for care. The literature supports that physicians, at least, make referral decisions based on factors other than need.5 These issues are important to consider because the process of assessing need is only the first step in ensuring access to care, followed by referral (step 2) and then receipt of services (step 3). There are many issues that can affect a patient’s access to care at any step in this process; however, this study sheds light on the first step—who needs physical therapy services and how do different clinicians make that determination? The variability in decision making related to who needed physical therapy services, seen within this study, is problematic. The study revealed significant differences across surgeon and physical therapist groups at each of the 3-, 6-, and 12-month intervals. These findings suggest that clinician and facility characteristics play a large role in determining which patients are recommended for physical therapy services. The authors provide some thoughts as to potential factors, such as clinical uncertainty, practice style, experience, and training protocols. The findings among surgeons are validated by previous evidence regarding physician variability in referral patterns.6 Unfortunately, the evidence suggests that physical therapists are not much better than surgeons at making consistent decisions regarding who will benefit from physical therapy services. This finding is perhaps more troubling because it cannot be attrib1350

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uted to a lack of knowledge regarding physical therapy, such as we may see with physician referrals. If physical therapists understand that physical therapy intervention can help patients with traumatic lowerextremity injuries, then it appears we are not sure of when and under what circumstances we should be providing our services. As a result, patient needs are not being met in a consistent, reliable, and predictable manner. This finding, to me, is perhaps the most concerning, as it relates to contemporary physical therapist practice and provides an assessment of need for the profession— consistency and reliability. Work by Fisher et al6 related to Medicare beneficiaries showed that within the medical community there is a great deal of variability in the care received among this patient population. There is every reason to suspect that this is equally true for physical therapy services.7 If so, then patients are not being referred or managed with any acceptable level of predictability. This situation presents physical therapists with a problem when they are looking to become the practitioner of choice for neuromusculoskeletal conditions. If we are not more consistent in what we do and how we do it, consumers and payers alike will see what we do as a set of mildly predictable tasks (eg, exercise, modalities) whose outcomes are not worth the cost. Physical therapy will not be seen as a true professional service, delivered by licensed physical therapists who can be relied upon to provide highquality, meaningful advice (consultation) to patients and other health care professionals as well as provide overall management of patients with neuromusculoskeletal conditions. We will remain, in the eyes of payers, a line item cost that lacks obvious value related to patient care.

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We have 2 clear ways in which to improve the quality of patient care and, consequently, our image as professionals. First, we must look for ways to enhance interdependent, interdisciplinary collaboration among clinicians. The surgeons and physical therapists in this study placed an emphasis on different variables when making decisions about the need for physical therapy services. Physical therapists used pain levels in their decision making at 3, 6, and 12 months, whereas pain did not appear to be a factor for surgeons. Surgeons found fracture healing, articular injury, and weight-bearing status to be key factors in their decision making for recommending physical therapy referral, yet physical therapists did not appear to consider these variables in a similar way when making the same decision. Surgeons appeared to emphasize variables associated with tissue healing, whereas physical therapists focused on variables associated with patient self-report and impairments. The authors suggest that a lack of communication between surgeons and physical therapists may have contributed to the disparity in selection variables. Which factors would have predicted the recommendation for physical therapy services if decision making occurred collaboratively among surgeons and therapists? How would the assessment of need for physical therapy services have been influenced if the patient was included in the decision-making process? Very often in clinical practice, determinations of patient need are made by clinicians in isolation without true collegial discussion and decision making among other providers and the patient. There have been recent recommendations for a focus on patient-centered care and the increased use of interdisciplinary health care “teams,” with evidence of their role in improved quality of care.8,9 This type of interdepenDecember 2009

Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury dence among providers and patients, however, is difficult to create and sustain. Payment structures and differences in power and culture among the health care professions have a significant impact on how health services are delivered in this country and often serve to impede interdisciplinary collaboration.10 Frequently, it is not the patient who is best served. This study appears to confirm the need to promote methods that encourage and reward interdisciplinary collaboration and communication. The 3 variables where surgeons and physical therapists showed some agreement were work self-efficacy, balance, and knee flexion range of motion. The authors described the statistical significance of the work self-efficacy variable; however, given that the likelihood ratios ranged from 0.97 to 0.99 (with 1 indicating no likelihood), it does not provide clinically meaningful data related to decision making for either group. As for balance and knee flexion range of motion, the agreement here was significant and meaningful, especially at the 6- and 12-month follow-up periods. The results for these variables may come from their historic use as indicators for physical therapy services, focusing primarily on impairments, and their ease of consistency in measurement and interpretation. Second, the consistent use of evidence-based decision tools (when available) can help decrease variability and improve the patient experience with physical therapy care. One of the best examples in physical therapy is related to treatment of patients with low back pain using a system of classification.11 Evidence exists that when we adhere to rec-

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ommended care for patients with acute low back pain, including classification, the outcomes are better (less pain and disability) and the utilization of present and future services is less (physical therapy visits, prescription medication, diagnostic imaging studies).12 Improved outcomes with decreased service utilization (lower costs) help support the value of physical therapy services for this population. We need more research supporting the value of what we do as physical therapists, and then, perhaps more importantly, we need to do it— evidence-based consultation, examination, decision making, and intervention—with consistency.13 As this study illustrates, we still have much work to do if we hope to achieve consistency in clinical decision making that can reliably determine which patients actually need and will benefit from our services. Archer and colleagues have provided us with valuable information—insights into how orthopedic surgeons and physical therapists make clinical decisions related to the need for physical therapy services among patients with traumatic lowerextremity injuries. It is through this type of health services research that we can begin to understand how clinicians think and behave in practice, thus providing us with real starting points from which to begin transforming physical therapist practice, and perhaps the entire health system, for the better.

References 1 Archer KR, MacKenzie EJ, Castillo RC, et al; the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Phys Ther. 2009;89:1337–1349. 2 Carter SK, Rizzo JA. Use of outpatient physical therapy services by people with musculoskeletal conditions. Phys Ther. 2007;87:1–16. 3 Fiscella K. Socioeconomic status disparities in healthcare outcomes: selection bias or biased treatment? Med Care. 2004;42: 939 –942. 4 Skinner J, Zhou W, Weinstein J. The influence of income and race on total knee arthroplasty in the United States. J Bone Joint Surg Am. 2006;88:2159 –2166. 5 Mitchell JM, Hadley J, Sulmasy DP, Bloche JG. Measuring the effects of managed care on physicians’ perceptions of their personal financial incentives. Inquiry. 2000;37:134 –145. 6 Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending, part 1: the content, quality, and accessibility of care. Ann Intern Med. 2003;138:273–287. 7 Jette AM, Delitto A. Physical therapy treatment choices for musculoskeletal impairments. Phys Ther. 1997;77:145–154. 8 Cooper RA. Health care workforce for the twenty-first century: the impact of nonphysician clinicians. Annu Rev Med. 2001; 52:51– 61. 9 Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: Institute of Medicine; 2001:1–337. 10 Johnson MP, Abrams SL. Historical perspectives of autonomy within the medical profession: considerations for 21st century physical therapy practice. J Orthop Sports Phys Ther. 2005;35:628 – 636. 11 Delitto A, Erhard RE, Bowling RW. A treatment-based classification approach to low back syndrome: identifying and staging patients for conservative treatment. Phys Ther. 1995;75:470 – 485; discussion 485– 489. 12 Fritz JM, Cleland JA, Speckman M, et al. Physical therapy for acute low back pain: associations with subsequent healthcare costs. Spine. 2008;33:1800 –1805. 13 Delitto A. Thirty-Ninth Mary McMillan Lecture: We are what we do. Phys Ther. 2008; 88:1219 –1227.

M.P. Johnson, PT, PhD, OCS, is Director of Clinical Leadership, Bayada Nurses, Skilled Visit Services, Moorestown, NJ 08057. Address all correspondence to Dr Johnson at: [email protected]. DOI: 10.2522/ptj.20080200.ic1

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Author Response

Kristin R. Archer, Ellen J. MacKenzie, Renan C. Castillo, Michael J. Bosse

We appreciate the thoughtful comments from Johnson1 on our article2 that examines variability in surgeon and physical therapist assessments of the need for physical therapy in patients with traumatic lowerextremity injuries. Our database was unique because it allowed for comparison across 8 centers and between surgeons and physical therapists. We were able to contribute to the health services research literature by determining the factors associated with the first step in the referral process—the “assessment of need.” As the physical therapy profession continues to advocate for direct access to therapy services, it becomes increasingly important to explore variability in physical therapist clinical decision-making and practice patterns. Consistent evidence supports wide variability in physician referral rates for physical therapy, and it appears important to ask the question: “Would variability exist if physical therapists were making the referral decision?” Our study showed evidence of variability in assessments of need for both surgeons and physical therapists and at the trauma center level throughout a 12-month recovery period. We hope our work will influence future health services research studies to examine patient access to physical therapy and subsequent use of services. It was surprising to us as well that insurance status and other socioeconomic (SES) variables were not associated with assessment of need for physical therapy, especially as evidence supports an association between education and insurance coverage and physician referral to physical therapists3–7 and, as Johnson points out, an association among race, education, and type of insur-

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ance and use of medical care.8,9 We concur that this finding may be attributed to the difference in our outcome measure. Because we were examining an assessment of need and not a documented referral or receipt of services, variables of SES may play less of a role than clinical or injury characteristics. We thank Johnson for highlighting the need for research into the continuum of access to care based on our findings, more specifically, that it is important to separately examine the process of assessing need (step 1), referral (step 2), and receipt of services (step 3) to improve access to and appropriate use of physical therapy for patients with musculoskeletal injuries. We agree that the variability in physical therapist decision making is problematic, but this finding is not surprising based on the nature of the patients’ injuries. Limited evidence exists on the beneficial effects of physical therapy for high-energy traumatic lower-extremity injuries,10 and evidence-based clinical practice guidelines for rehabilitation referral and intervention have yet to be determined. Thus, physical therapists must rely on their clinical experience and training and their knowledge of these injuries and centerspecific protocols. Although variability in physical therapist assessment of need cannot be attributed to a lack of knowledge of physical therapy services, it can be attributed to a lack of knowledge or understanding of the injuries and the recovery process. High-energy traumatic lower-extremity injuries tend to require extensive surgical procedures, have an extended recovery process due to complications and rehospitalizations, and lead to persistent pain and disability and a reduced capacity to return to

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work.11–14 In addition, psychological distress and psychosocial factors may contribute to difficulties in identifying the patients in need of and who will benefit from physical therapy services.11,15,16 Therefore, it seems important to determine whether variability in physical therapist decision making exists for patient populations for whom evidence-based guidelines exist or who have a more standard course of healing and recovery. Differences were found in assessments between surgeons and physical therapists, and we believe the findings emphasize a need for improved communication about the nature of a patient’s injury, surgical procedures, healing status, and pain level and weight-bearing limitations. Johnson raises important issues regarding interdisciplinary care and the role of the patient in the decision-making process. Numerous studies have supported the use of a multidisciplinary team approach for survivors of traumatic injuries based on the multifactor problems associated with these injuries and the poor long-term functional and mental health outcomes.11,17–20 However, as Johnson emphasizes in his commentary, a team approach is difficult to create and sustain, especially due to payment structures and the culture within level I trauma centers. We would argue that qualitative studies are needed to identify successful inpatient multidisciplinary models and to detect facilitators and barriers to the implementation and maintenance of such models within level I trauma centers. In addition, as noted in our article, the identification of the specific provider and center characteristics contributing to variations in decision-making and practice patterns may facilitate the devel-

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Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury opment of innovative strategies to not only decrease variability but also improve provider collaboration. We support the need for more research to confirm the value of physical therapy and agree with Johnson’s statement that “we need to provide evidence-based decision making and intervention with consistency.” It is essential not only to conduct highquality efficacy and effectiveness studies, but to develop and adhere to clinical practice guidelines. Studies have documented a positive association between the use of guidelines and improved quality of care and lower heath care costs.21 There is consistent evidence, however, of poor implementation and adherence to practice guidelines among various health care professionals.21–23 In particular, the majority of primary care physicians continue to be nonadherent to evidence-based back pain guidelines.24 –26 Gonzalez-Urzelai and colleagues27 found adherence rates for diagnostic procedures in the care of low back pain to range from 27% to 33% and for therapeutic processes from 23% to 77%. Barriers to adherence include knowledge of and attitudes toward guidelines, limited access to guidelines and recommended services, concern over liability, inadequate time to consider guidelines, and patient desires and expectations.21,26 Therefore, the physical therapy community needs to consider the development of evidence-based clinical practice guidelines as only the first step in decreasing variability and improving patient care. In conclusion, we agree that enhancing collaboration across disciplines and developing and adhering to evidence-based clinical practice guidelines will decrease variability in clinical decision making, improve quality of patient care, and expand

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the professional role of physical therapists. There also is a clear need to identify the specific provider and center characteristics contributing to clinical decision making and ultimately access to care. Additional health services research on physical therapists’ evaluation, decision making, and intervention is recommended in order to facilitate an increased understanding of the variability in overall practice patterns. DOI: 10.2522/ptj.20080200.ar1

References 1 Johnson MP. Invited commentary on “Orthopedic Surgeons and Physical Therapists Differ in Assessment of Need for Physical Therapy After Traumatic Lower-Extremity Injury.” Phys Ther. 2009;89:1349 –1351. 2 Archer KR, MacKenzie EJ, Castillo RC, et al; for the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Phys Ther. 2009;89:1337–1349. 3 Freburger JK, Holmes GM, Carey TS. Physician referrals to physical therapy for the treatment of musculoskeletal conditions. Arch Phys Med Rehabil. 2003;84:1839 – 1849. 4 Freburger JK, Carey TS, Holmes GM. Physician referrals to physical therapists for the treatment of spine disorders. Spine J. 2005;5:530 –541. 5 Ward WM, Williams BT, Dixon RA. Physiotherapy: its prescription and implementation for orthopaedic out-patients. Rheumatol Rehabil. 1978;17:14 –22. 6 Ritchey FJ, Inkston D, Goldbaum JE, Heerten ME. Perceptual correlates of physician referral to physical therapy for role expansion. Soc Sci Med. 1989;28:69 – 80. 7 Kerssens JJ, Groenewegen PP. Referrals to physiotherapy: the relation between the number of referrals, the indication for referral, and the inclination to refer. Soc Sci Med. 1990;30:797– 804. 8 Carter SK, Rizzo JA. Use of outpatient physical therapy services by people with musculoskeletal conditions. Phys Ther. 2007; 87:1–16. 9 Skinner J, Zhou W, Weinstein J. The influence of income and race on total knee arthroplasty in the United States. J Bone Joint Surg Am. 2006;88:2159 –2166. 10 Castillo RC, MacKenzie EJ, Archer KR, et al. Evidence of beneficial effect of physical therapy after lower-extremity trauma. Arch Phys Med Rehabil. 2008;89:1873–1879. 11 Bosse MJ, MacKenzie EJ, Kellam JF, et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N Engl J Med. 2002;347:1924 –1931.

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12 Castillo RC, MacKenzie EJ, Wegener ST, Bosse MJ. Prevalence of chronic pain seven years following limb threatening lower extremity trauma. Pain. 2006;124: 321–329. 13 MacKenzie EJ, Bosse MJ, Kellam JF, et al. Characterization of patients with highenergy lower extremity trauma. J Orthop Trauma. 2000;14:455– 466. 14 MacKenzie EJ, Bosse MJ, Pollak AN, et al. Long-term persistence of disability following severe lower-limb trauma. J Bone Joint Surg Am. 2005;87:1801–1809. 15 McCarthy ML, MacKenzie EJ, Edwin D, et al. Psychological distress associated with severe lower-limb injury. J Bone Joint Surg Am. 2003;85:1689 –1697. 16 Zatzick DF, Rivara FP, Nathens AB, et al. A nationwide US study of post-traumatic stress after hospitalization for physical injury. Psych Med. 2007;37:1469 –1480. 17 Urquhart DM, Williamson OD, Gabbe BJ, et al. Outcomes of patients with orthopaedic trauma admitted to level I trauma centres. ANZ J Surg. 2006;76:600 – 606. 18 Holtslag HR, van Beeck EF, Lindeman E, Leenen LP. Determinants of long-term functional consequences after major trauma. J Trauma. 2007;62:919 –927. 19 Zatzick D, Roy-Byrne P, Russo J, et al. A randomized effectiveness trial of stepped collaborative care for acutely injured trauma survivors. Arch Gen Psychiatry. 2004;61:498 –506. 20 Zatzick D, Jurkovich G, Russo J, et al. Posttraumatic distress, alcohol disorders, and recurrent trauma across level I trauma centers. J Trauma. 2004;57:360 –366. 21 Sammer CE, Lykens K, Singh KP. Physician characteristics and the reported effect of evidence-based practice guidelines. Health Serv Res. 2008;43:569 –581. 22 McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348:2635–2645. 23 Saarni SI, Gylling HA. Evidence-based medicine guidelines: a solution to rationing or politics disguised as science? J Med Ethics. 2004;30:171–175. 24 Di Iorio D, Henley E, Doughty A. A survey of primary care physician practice patterns and adherence to acute low back problem guidelines. Arch Fam Med. 2000;9:1015–1021. 25 Webster BS, Courtney TK, Huang Y, et al. Physicians’ initial management of acute low back pain versus evidence-based guidelines. J Gen Intern Med. 2005;20: 1132–1135. 26 Feuerstein M, Hartzell M, Rogers HL, Marcus SC. Evidence-based practice for acute low back pain in primary care: patient outcomes and cost of care. Pain. 2006; 124:140 –149. 27 Gonzalez-Urzelai V, Palacio-Elua L, Lopezde-Munain J. Routine primary care management of acute low back pain: adherence to clinical guidelines. Eur Spine J. 2003;12:589 –594.

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Research Report Infants Born Preterm Exhibit Different Patterns of Center-of-Pressure Movement Than Infants Born at Full Term Stacey C. Dusing, Anastasia Kyvelidou, Vicki S. Mercer, Nick Stergiou S.C. Dusing, PT, PhD, is Assistant Professor, Department of Physical Therapy, Virginia Commonwealth University, PO Box 980224, Richmond, VA 23298 (USA). Address all correspondence to Dr Dusing at: [email protected]. A. Kyvelidou, MS, is Graduate Research Assistant, Nebraska Biomechanics Core Facility, University of Nebraska Medical Center and University of Nebraska at Omaha, Omaha, Nebraska. V.S. Mercer, PT, PhD, is Associate Professor, Division of Physical Therapy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. N. Stergiou, PhD, is Isaacson Professor and Director, Nebraska Biomechanics Core Facility, College of Education and College of Public Health, University of Nebraska Medical Center and University of Nebraska at Omaha. [Dusing SC, Kyvelidou A, Mercer VS, Stergiou N. Infants born preterm exhibit different patterns of center-of-pressure movement than infants born at full term. Phys Ther. 2009;89:1354 –1362.] © 2009 American Physical Therapy Association

Background. Infants born preterm are at risk for developmental impairments related to postural control. Objective. The purpose of this study was to determine whether infants born preterm and infants born at full term differed in postural control at 1 to 3 weeks after term age.

Design. This study included 17 infants born preterm (mean gestational age⫽31.9 weeks, range⫽25.0 –34.6) and 15 infants born at full term (mean gestational age⫽38.9 weeks, range⫽37.3– 40.6). All infants were without diagnosed neurological or genetic conditions. Measurement. Center-of-pressure (COP) data were recorded at 5 Hz while each infant was positioned supine on a pressure-sensitive mat in an alert behavioral state. Root mean square (RMS) displacement and approximate entropy (ApEn) were used to describe the COP movement variability in the time series. Differences between groups were identified using independent t tests. Results. The COP time series were found to be deterministic, suggesting order in the time series. Infants born preterm exhibited significantly larger RMS values in the caudal-cephalic direction than infants born at full term (1.11 and 0.83 cm, respectively; t⫽⫺2.6, df⫽30, P⫽.01). However, infants born at full term had significantly larger ApEn values in the caudal-cephalic direction (1.19 and 1.11, respectively; t⫽2.4, df⫽30, P⫽.02). The 2 groups did not differ in RMS or ApEn values in the medial-lateral direction or the resultant.

Conclusions. Infants born at full term exhibited COP displacements in the caudal-cephalic direction that were smaller in amplitude, but may be considered more complex or less predictable, than those of infants born preterm. One explanation is that infants born preterm exhibited more stereotypic patterns of movement, resulting in large, but repetitive, COP excursions. A combination of linear and nonlinear measures may provide insight into the control of posture of young infants.

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nfants who are born at full term and are developing typically exhibit complex and variable movements, maintain their trunks in a flexed position, kick their legs, and visually explore the environment in the first weeks of life.1–3 In contrast, many infants born preterm have limited antigravity trunk flexion and difficulty maintaining a quiet alert state, and some infants exhibit repetitive movement patterns.4,5 Infants born preterm frequently have atypical trunk and extremity positioning, muscle tone (velocity-dependent resistance to stretch), and muscle power in the first 6 months of life compared with infants born at full term.6,7 Although these findings may be transient in nature, they are associated with deficits in posture, reaching, hand function, sitting balance, coordination, and cognition at 2 to 7 years of age.8 –12 Early assessment of postural control may provide insight into the developmental trajectories of infants and aid in early identification of those at greatest risk for developmental difficulties. Postural control involves controlling the body’s position in space for the dual purpose of: (1) orientation, which is the ability to maintain an

appropriate relationship between body segments and the environment, and (2) stability, which is the ability to control the center of mass in relation to the base of support.13 The center of pressure (COP), or the ground reaction force, at the base of support traditionally has been considered a reflection of the organization of posture and is commonly used in both research and clinical quantification of postural control.13 Center of pressure provides a measure of posture in any position and is influenced by extremity, head, trunk, and pelvic position in standing, sitting, or supine positions.13,14 Because young infants spend a large portion of their nonsupported play time in a supine position,15 this is a functional position for postural control assessment in these infants and has been described previously in 4and 6-month-old infants.8 Adequate postural control in a supine position is critical to enable the infant to maintain a stable base while performing active trunk and extremity movements or to reorient the body by rolling. In this study, we used COP movement variability to characterize the ability to maintain a stable base during spontaneous movements in infants born preterm and in

infants born at full term. In this model of supine postural control, COP is used to describe the location of the ground reaction force while the infant moves. Movements of the trunk (including the pelvis) into antigravity flexion or pushing into extension on the support surface, as well as head and extremity movements, may influence the COP location (Figs. 1 and 2). Although a supine infant maintains much of his or her body in contact with the support surface, the challenges of lifting the extremities against gravity and flexing or extending the trunk require postural control or trunk stability. Movement variability has been a major theme in the motor control literature. The motor program perspective viewed variability as the result of errors in the ability to scale the essential parameters to perform a Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on October 8, 2009, at www.ptjournal.org.

Figure 1. Example of pressure mapping method and pictorial display of pressure distribution: (A) a preterm infant positioned supine on the pressure-sensitive mat while awake and active, (B) a screen shot from the data collection software representing one frame of pressure data (in millimeters of mercury) and the center-of-pressure trace for the preceding 10 seconds.

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Figure 2. A model of supine postural control. The photographs in this figure depict an infant positioned supine on the pressure-sensitive mat while awake and active. The arrow represents the location of the center of pressure (COP) for the infant’s position. As the infant moves from (A) a position of antigravity flexion to (B) a position of extremity and trunk extension, the COP shifts. The continuous evaluation of these shifts in COP provides a summary measure of the infant’s postural control.

movement.16 Schmidt and Lee16 suggested that specificity in practicing a skill would lead to the elimination of errors and thus to the optimization of the movement pattern. In contrast, dynamic systems theory appreciated variability from the perspective that while an individual is in a stable phase, there is little variability. However, an individual developing a new skill moves through an unstable phase in which variability increases. Increasing variability in an individual may predict the development of a new skill or the transition to a new phase of development. Thelen and Smith17 suggested that individuals transition through stable and unstable periods during acquisition of new skills. However, this appreciation of variability does not recognize the rich organization of motor behavior that may be observed in elite athletes and musicians during stable phases of development. Limited recognition of this important aspect of motor behavior may be due to the prevalence of research that addresses only the magnitude of variability. Specifically, variability of postural control can be investigated in terms of both magnitude and organization. Magnitude is evaluated using traditional linear measures of central1356

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ity, such as standard deviations. Organization or structure is evaluated using nonlinear analysis that determines the evolution of behavior over time.18 The absence of utilization of both types of analyses has led to contradictory results regarding the evaluation of the COP. For example, there are conflicting interpretations of linear measures of COP such as the path length, excursion, and path area. Hughes and colleagues19 described subjects with increased COP path area as having greater postural control, whereas Riach and Hayes20 interpreted similar results as representing decreased postural control. In addition, clinical measures of postural control do not correlate well with linear measures of COP movement variability.21 Inconsistent interpretation and lack of clinical correlations led Palmieri et al22 to argue that linear COP measures do not quantify stability of the postural control system and that new measures are needed to examine the COP signal and quantify change. Therefore, nonlinear tools such as approximate entropy (ApEn) are being used increasingly in several medical fields to describe complex conditions for which linear tech-

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niques are inadequate or scientifically confounding.23–25 The use of nonlinear measures to describe COP movement variability provides new insights concerning the complexity and temporal organization of postural control.26 Temporal organization or “structure” is quantified by the degree to which values emerge in an orderly (ie, predictable) manner across a range of time scales.27 Approximate entropy measures the complexity of the COP time series28,29 and can be used to quantify the regularity or predictability of a time series.30 A more predictable and regular time series also is less complex. A change in complexity may be indicative of learning and a reorganization of the available degrees of freedom.29,31 Approximate entropy measures the logarithmic probability that a series of data points a certain distance apart will exhibit similar relative characteristics on the next incremental comparison with the state space.28,30 Time series with a greater likelihood of remaining the same distance apart upon comparison will result in lower ApEn values, whereas data points that exhibit large differences in distances between data points will reDecember 2009

Center-of-Pressure Movement Variability in Infants sult in higher values. Values typically range from 0 to 2. Values closer to 0 are consistent with greater periodicity (less complexity). Conversely, values nearing 2 represent greater irregularity (higher complexity).

Table 1. Participant Demographics Variable

Preterm Infants

Full-Term Infants

17

15

n Sex Male

Nonlinear analysis of COP data can provide a window into infant neurological status, increasing our understanding of the complex strategies infants use to control posture. Previous research has shown that nonlinear analysis is useful in examining small increments of change in postural control before behavioral changes can be identified.18,27 However, this type of analysis has never been used to describe supine postural control of young infants. The purpose of this study was to determine whether infants born at full term and infants born preterm differed in their COP movement variability characteristics, evaluated both linearly and nonlinearly, while positioned supine at 1 to 3 weeks after term age. Based on our previous research32 and that of other researchers,33 we expected differences between groups in both linear and nonlinear postural control measures. We hypothesized that infants born preterm would have larger and more repetitive or predictable COP movement patterns compared with infants born at full term.

Method Participants A sample of convenience comprising 17 infants born preterm and 15 infants born at full term was used in this study. Infants were recruited from the neonatal intensive care unit and newborn nursery of 2 medical centers, and their parents provided informed consent. Medical records were reviewed to ensure the infants met the inclusion and exclusion criteria for the study. All infants were born at weights that were appropriate for their gestational age and had December 2009

10

3

7

12

12 (9 twins, 3 triplets)

4 (4 twins)

31.9

38.9

3.0

1.1

Female Multiple births Gestational age at birth (wk) Mean SD Range

25.0–34.6

37.3–40.6

1,691.6

3,356.5

461.8

565.3

780–2,381

2,381–4,167

Mean

68.9

14.5

SD

22.9

5.1

Birth weight (g) Mean SD Range Age at assessment (d)

Range

45–124

been discharged from the hospital prior to their participation. Infants born preterm were born at a mean (SD) of 31.9 (3.0) weeks of gestation, and infants born at full term were born at a mean (SD) of 38.9 (1.1) weeks of gestation. Infants were excluded from participation if they had periventricular leukomalacia, grade 3 or 4 intraventricular hemorrhage, a history of seizures, congenital abnormalities, a genetic or endocrine system syndrome, or drug or alcohol exposure or if they required supplemental oxygen at the time of the assessment. Infants also were excluded if they did not have a parent or guardian who spoke English. Infants born preterm were assessed at 41 to 43 weeks of post-conceptual age (mean [SD]⫽41.7 [0.7] weeks of post-conceptual age) and infants born full term were assessed 1 to 3 weeks after delivery (mean [SD]⫽41.0 [1.1] weeks of postconceptual age) (Tab. 1).

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Instrumentation and Procedure Center of pressure traditionally is measured using a force platform. However, force platforms are limited in their clinical utility by their size, weight, and lack of portability. Pressure-sensitive mats have been used in clinical and research settings to evaluate the pressure between a patient’s body and a wheelchair seat, chair, or bed.34 Center-of-pressure movements measured in a sitting position using pressure-sensitive mats are both reliable and valid compared with force platforms.35,36 Validation of COP measured using a pressuresensitive mat in a supine position has not been published. The portability, noninvasiveness, reliability, and validity of pressure-sensitive mats make them ideal measurement tools for assessing supine postural control of both infants who are healthy and infants born preterm and at high risk for developmental difficulties in their natural environments. A frequency analysis of representative COP time series indicated that

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Center-of-Pressure Movement Variability in Infants 99.99% of the signal power was below 0.5 Hz. Therefore, pressure data were sampled for a minimum of 5 minutes with a sampling frequency of 5 Hz in order to stay a factor of 10 above the highest frequency contained in the signal. All data were collected in the infant’s home with one or more parents present. The parent placed the infant in a supine position on a pressuresensitive mat (FSA UltraThin Seat Mat*), which was positioned on the same close cell foam mat for all assessments (Figs. 1 and 2). The infant wore a diaper and a thin, one-piece outfit or T-shirt. The locations of the infant’s head and pelvis were recorded in reference to the pressure-sensitive mat’s grid system. During each data collection session, the examiner documented each behavioral state change (deep sleep, light sleep, drowsy, quiet alert, active alert, crying) using the criteria of Brazelton.3 The examiner also documented each time the infant was touched by an adult (for calming or repositioning) or rolled out of the supine position with one side of the pelvis and one shoulder off the support surface. Each state change, adult contact, and roll was documented in the data collection software and synchronized with the pressure data. The infant’s parent was permitted to talk to or look at the infant as needed to keep the infant happy and awake. If the infant began to cry, the parent calmed the infant and then returned the infant to the pressure-sensitive mat. A total of 1,500 data samples were collected in several shorter segments if the infant had difficulty remaining calm and awake in a supine position without swaddling for a full 5 minutes. Data Reduction Center-of-pressure coordinates, behavioral state, adult contact, and roll notations for each data sample were * Vista Medical, 120 Maryland St, Winnipeg, Manitoba, Canada R3G 1L1.

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exported for analysis. Using the notations exported from the data collection software, data segments consisting of 500 sequential data samples (100 continuous seconds of data collection) meeting the following criteria were identified: (1) the infant was in a quiet or active alert behavioral state, (2) no adult was in contact with the infant, and (3) the infant was not rolling. This data length is considered adequate for the type of nonlinear analysis performed in this study.28 Three segments of 500 data samples were identified for 16 infants born preterm and for 12 infants born at full term. Three infants born at full term and 1 infant born preterm had frequent behavioral state changes during data collection and, therefore, had only 2 segments of 500 sequential data samples, which were included in the analysis. The COP movement was analyzed with both linear and nonlinear measures for each continuous block using MATLAB version R2007a.† We used the procedure of surrogation to validate whether postural control in the supine position of the infants born preterm and at full term was deterministic (has order) or stochastic (random) in nature. Surrogate data sets were generated for all original COP time series. This procedure was performed in MATLAB using the algorithms developed by Theiler et al.37 The surrogates were produced from the original COP data, but the deterministic structure from the original data set was removed, generating a random equivalent with the same mean, variance, and power spectra as the original. To compare the original with the surrogate data sets, we also computed ApEn from all the surrogate data sets. Linear measures included root mean square (RMS) of the COP in caudal† The MathWorks Inc, 3 Apple Hill Dr, Natick, MA 01760-2098.

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cephalic and medial-lateral directions and the resultant or total COP movement. Nonlinear measures included the ApEn and surrogation analysis. Both measures were calculated from the COP time series in the caudal-cephalic and medial-lateral directions and resultant. The ApEn was calculated using MATLAB code developed by Kaplan and Staffin,38 implementing the methods of Pincus et al,30 using a lag value of 1, an r value of 0.2 times the standard deviation of the data file, and a vector length m of 2. These r and m values are typically used in the calculation of ApEn for human physiologic time series.28 Data Analysis For the surrogation procedure, the statistical comparisons were made with an infant-to-infant analysis and also across the entire sample by using a dependent t test. If the original value of ApEn for one infant was lower than the corresponding surrogate, then a value of 1 was given. If the original value of ApEn for one infant was greater than the corresponding surrogate, then a value of 0 was given. When all comparisons were made, a percentage between values of 0 and values of 1 was estimated. In order for the data to be deterministic, we would expect to have numerous values of 1. This percentage was estimated for the 2 surrogation algorithms published by Theiler et al.37 For one algorithm, this percentage was 99%, and for the other algorithm, the percentage was 96%, which suggests that the data were deterministic.37 Descriptive statistics were used to describe the samples and dependent variables. Differences between infants born preterm and infants born at full term in linear and nonlinear parameters were calculated using independent t tests for the caudalcephalic and medial-lateral directions and the resultant. All statistical analysis was completed using SPSS December 2009

Center-of-Pressure Movement Variability in Infants Table 2. Group Differences in Center-of-Pressure Variablesa

a b

Dependent Variable

Full-Term Infants Mean (SD), Range

Preterm Infants Mean (SD), Range

Mean Difference (95% CI)

P Values From t Test

RMS caudal-cephalic (cm)

0.83 (0.23), 0.52–1.28

1.11 (0.35), 0.61–2.00

⫺0.11 (⫺0.20 to ⫺0.02)

.01b

RMS medial-lateral (cm)

0.76 (0.26), 0.25–1.16

1.00 (0.72), 0.40–2.84

⫺0.95 (⫺0.25 to 0.06)

.23

RMS resultant (cm)

1.15 (0.31), 0.58–1.69

1.54 (0.72), 0.75–3.32

⫺0.15 (⫺0.32 to 0.01)

.06

ApEn caudal-cephalic

1.19 (0.8), 1.02–1.32

1.11 (0.10), 0.93–1.26

0.08 (0.01 to 0.14)

.02b

ApEn medial-lateral

0.93 (0.18), 0.64–1.19

0.86 (0.20), 0.52–1.09

0.07 (⫺0.07 to 0.22)

.29

ApEn resultant

1.19 (0.10), 0.96–1.34

1.13 (0.13), 0.83–1.31

0.06 (⫺0.03 to 0.14)

.19

CI⫽confidence interval, RMS⫽root mean square, ApEn⫽approximate entropy. P⬍.05.

version 14.0,‡ with the alpha equal to .05. Role of the Funding Source Dr Dusing and Dr Stergiou were each funded by National Institutes of Health/National Institute of Child Health and Human Development career development awards (1K12HD 055931– 01 and K25HD047194, respectively), allowing time for this secondary data analysis and manuscript preparation. Dr Stergiou and Ms Kyvelidou were supported by consecutive National Institute on Disability and Rehabilitation Research grants (H133G040118 and H133G080023) and the McDonald Fellowship and Bukey Fellowship from the University of Nebraska Medical Center. A portion of Dr Mercer’s time in preparation of this manuscript was funded by a Competitive Research Leave from the Office of the Provost, University of North Carolina at Chapel Hill. Initial study design and data collection were funded by a grant to Dr Dusing from the University of North Carolina at Chapel Hill Human Movement Science Student Research Fund. None of the funding sources had any role in the study design or analysis or the reported outcomes.

Results

Discussion

Surrogation analysis revealed that the fluctuations observed in the COP data in all directions were deterministic in nature. This finding was indicated by the significantly larger ApEn values found for the surrogate data sets compared with the original (P⬍.05). The findings from the surrogation analysis revealed that the variability observed in the COP data was deterministic across both preterm and full-term infants. Thus, both preterm and full-term infants have significantly different structure than stochastic noise. These findings provided the basis to continue with the nonlinear analysis.

The COP time series was deterministic in nature, confirming that variability within the COP time series is structured and it is not random noise. This result further emphasizes the importance of investigating COP time series, because invaluable information about postural control may be hidden in the structure of the COP time series. Thus, description of this variability serves to enhance our understanding of the organization of postural control in infants. Infants born preterm were found to exhibit larger COP displacements in the caudal-cephalic direction than infants born at full term, as quantified by linear analysis of the COP movement variability. Infants born preterm also were found to have lesscomplex COP movement in the caudal-cephalic direction compared with infants born at full term, as quantified by nonlinear analysis of COP movement variability. These findings support our hypothesis that infants born preterm differ from infants born at full term with respect to supine postural control at 1 to 3 weeks after term age.

Our group analysis identified that the infants born preterm exhibited larger RMS values in the caudalcephalic direction than infants born at full term (F⫽1.94, df⫽30, P⫽.01; Tab. 2, Fig. 3A). There were no significant differences in RMS values in the ml direction or in the resultant (Tab. 2, Fig. 3A). Infants born preterm had smaller ApEn values in the caudal-cephalic direction than infants born at full term (F⫽2.33, df⫽30, P⫽.02; Tab. 2, Fig. 3B). There were no group differences in the ApEn values in the medial-lateral direction or the resultant (Tab. 2, Fig. 3B).

‡ SPSS Inc, 233 S Wacker St, Chicago, IL 60606.

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The findings from this study complement our previous research with the same cohort.32 In the previous study, we found that infants born at full term, but not infants born preterm, were successful in maintaining anti-

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Figure 3. Group differences in center-of-pressure (COP) movement variability: (A) group differences in root mean square (RMS) of the COP in caudal-cephalic (cc) and medial-lateral (ml) directions and the resultant, (B) group differences in approximate entropy (ApEn) calculated from the COP time series in the caudal-cephalic and medial-lateral directions and the resultant. Asterisks represent statistically significant differences (P⬍.05). Error bars represent the 95% confidence intervals.

gravity trunk flexion or a neutral position more than two thirds of the time. Together, these studies suggest that infants born at full term maintain antigravity trunk flexion or a neutral position and exhibit minimal COP sway with varied organization. In contrast, infants born preterm exhibit large and predictable COP sway in the caudal-cephalic direction. Linear and nonlinear analyses combined provide complementary information about postural control in this group of infants. Although the linear measures (RMS of the COP in the caudal-cephalic direction) identified greater variability in the infants born preterm, the nonlinear measures (ApEn in the caudal-cephalic direction) identified smaller alterations in the organizational structure of the variability in the COP time series for infants born preterm. The purpose of this study was not to describe the specific movement patterns of the infants. However, the COP movement provides us with a summary of how the infants moved their entire 1360

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bodies during spontaneous movement. The results from this study provide preliminary evidence that infants born preterm exhibit a less stable posture and move in a repetitive manner in the caudal-cephalic direction compared with infants born at full term. These findings may be the result of variations in extremity, trunk (including the pelvis), or head movements observed during spontaneous movements. Figure 2 represents 2 postures of an infant who was developing typically demonstrated during an assessment of spontaneous movement. If this infant moved back and forth between only these 2 postures using the same COP trajectory each time, the infant’s ApEn in the caudal-cephalic direction would be low (similar to the infants born preterm). If the infant moved between these 2 postures using different COP trajectories with each change in posture, the infant’s ApEn would be larger (similar to the infants born at full term).

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Previous research has documented the importance of movement variability and complexity in fetuses, infants, and young children during spontaneous movements, sitting, and kicking.1,2,27,39 Robertson1 proposed that the temporal patterns of fetal and neonatal cyclical movements might be altered or abolished by perinatal stress or central nervous system damage. Generalized movement assessment describes extremity movements in neonates based on their complexity, variability, speed, and amplitude.2,40,41 Infants who have repetitive or rigid movements are more likely to have abnormal brain imaging or be diagnosed with cerebral palsy or coordination problems.42,43 The complexity of COP movement in a supine position can be quantified and, with additional research, may be useful in identifying infants with postural control deficits, as well as furthering our understanding of the development of infant postural control. Our results concerning the deterministic nature of COP movement in suDecember 2009

Center-of-Pressure Movement Variability in Infants pine infants are consistent with the results of previous studies of sitting and spontaneous arm movements.27,44 These results support the principle of self-organization, as described in dynamic systems theory and the theory of optimal variability.17,18 Both of these theories support the concept that variability within the system is not random error but a necessary source of solutions that allow the system to selforganize and be flexible to changing conditions. Although further longitudinal research is needed to gain understanding of these self-organizing processes, this cross-sectional study provides some early evidence that infants born preterm and infants born at full term may differ in the nature or timing of self-organization or their movement flexibility. Only with longitudinal studies will we be able to further describe the development of postural control in very young infants. The combination of both linear and nonlinear tools will be more effective at describing the emergence of postural control and its influence on development. This study had several limitations, which must be acknowledged and addressed in future studies. The pressure-sensitive mat used in this study measures only vertical ground reaction forces. Therefore, we were unable to report on the influence of shear forces that may result from movement. The precision of the pressure-sensitive mat used in this study is reported to be 0.25 cm in a sitting position.35,36 Although this is not as precise as a force platform, the minimum RMS observed was 0.52 cm in the caudal-cephalic direction and 0.25 cm in the medial-lateral direction. The lack of measurement precision may have contributed to the lack of significant findings in the mediallateral direction. However, it is unlikely that the lack of precision affected the findings in the caudalcephalic direction, given the RMS December 2009

values. Further research is needed to validate the use of the pressuresensitive mat to evaluate COP in young infants. The type of nonlinear analysis used in this study was limited by the length of the time series. Ideally, longer data collection periods should be included in future studies to allow for the use of additional nonlinear assessment tools. However, we should mention here that the number of input data points for ApEn computations has been as low as 50.28 The fact that such small data sets can be used for the calculation of ApEn is one of the advantages of ApEn in comparison with other nonlinear tools (eg, Lyapunov exponent).28 For noisy and medium-sized data sets, ApEn has been shown to produce stable values.28 Videotape of the infants’ behavior and spontaneous extremity movement was not recorded, limiting our understanding of the correlation between limb movement and postural control in this sample. The frames of data in which an infant rolled or was not in a quiet or active alert state or an adult was touching the infant were eliminated from the analysis. The frames immediately prior to these activities may have included changes in COP movement that were different from those observed during supine spontaneous movements. The infants born preterm in our sample had a mean gestational age of 31.9 weeks, with only 3 infants born at less than 30 weeks of gestation. Future studies should include a stratified sample of infants born preterm to ensure that infants born at a variety of gestational ages are included and described separately. The addition of infants with a history of brain injuries such as periventricular leukomalacia or intraventricular hemorrhage would lead to better insight into the predictive value of this assessment and analysis protocol. Volume 89

Lastly, the cross-sectional nature of this study prohibits us from speculating on the developmental trajectory of the infants who participated. Longitudinal designs with data collection at key time points during development will be needed to elucidate the dynamics of the postural control system in young infants. Although we are only beginning to understand the complexity of infant postural control, our results and those of previous researchers highlight the importance of both the magnitude and the organization of variability in postural control. When observing developing infants, clinicians should consider both types of factors, noting not only the extent and speed of movement but also the variety. Future longitudinal studies are needed to provide insights concerning optimal variability in typical development and critical periods for intervention and to facilitate evaluation of intervention strategies. Dr Dusing, Dr Mercer, and Dr Stergiou provided concept/idea/research design and writing. Dr Dusing provided data collection, project management, fund procurement, and participants. Ms Kyvelidou and Dr Stergiou provided data analysis. Dr Mercer provided facilities/equipment. All authors provided consultation (including review of manuscript before submission). This study was approved by the Committee on the Protection of the Rights of Human Subjects at the University of North Carolina and Wake Medical Center. An abstract of the data was presented at the Combined Sections Meeting of the American Physical Therapy Association; February 9 –12, 2009; Las Vegas, Nevada. Dr Dusing and Dr Stergiou were each funded by National Institutes of Health/National Institute of Child Health and Human Development career development awards (1K12HD055931-01 and K25HD047194, respectively), allowing time for this secondary data analysis and manuscript preparation. Dr Stergiou and Ms Kyvelidou were supported by consecutive National Institute on Disability and Rehabilitation Research grants (H133G040118 and H133G080023) and

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Center-of-Pressure Movement Variability in Infants the McDonald Fellowship and Bukey Fellowship from the University of Nebraska Medical Center. A portion of Dr Mercer’s time in preparation of this manuscript was funded by a Competitive Research Leave from the Office of the Provost, University of North Carolina at Chapel Hill. Initial study design and data collection were funded by a grant to Dr Dusing from the University of North Carolina at Chapel Hill Human Movement Science Student Research Fund. None of the funding sources had any role in the study design or analysis or the reported outcomes. This article was received November 10, 2008, and was accepted August 5, 2009. DOI: 10.2522/ptj.20080361

References 1 Robertson SS. Oscillation and complexity in early infant behavior. Child Dev. 1993; 64:1022–1035. 2 Einspieler C, Prechtl HFR, Bos AF, et al. Prechtl’s Method on the Qualitative Assessment of General Movements in Preterm, Term, and Young Infants. London, United Kingdom: MacKeith Press; 2004:91. Clinics in Developmental Medicine Series, No. 167. 3 Brazelton TB. Neonatal Behavioral Assessment Scale. London, United Kingdom: MacKeith Press; 1995. 4 Ferrari F, Bertoncelli N, Gallo C, et al. Posture and movement of healthy preterm infants in supine position in and out of the nest. Arch Dis Child Fetal Neonatal Ed. 2007;92:F386 –F390. 5 Groen SE, de Blecourt AC, Postema K, Hadders-Algra M. General movements in early infancy predict neuromotor development at 9 to 12 years of age. Dev Med Child Neurol. 2005;47:731–738. 6 Allen MC, Capute AJ. Tone and reflex development before term. Pediatrics. 1990; 85(3 pt 2):393–399. 7 de Groot L, van der Hoek AM, Hopkins B, Touwen BC. Development of muscle power in preterm infants: individual trajectories after term age. Neuropediatrics. 1993;24:68 –73. 8 Fallang B, Oien 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. 9 Allen MC. Neurodevelopmental outcomes of preterm infants. Curr Opin Neurol. 2008;21:123–128. 10 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. 11 Samsom JF, de Groot L, Bezemer PD, et al. Muscle power development during the first year of life predicts neuromotor behaviour at 7 years in preterm born highrisk infants. Early Hum Dev. 2002;68: 103–118.

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12 Wijnroks L, Veldhoven NV. Individual differences in postural control and cognitive development in preterm infants. Inf Behav Dev. 2003;26:14 –26. 13 Prieto TE, Myklebust JB, Hoffmann RG, et al. Measures of postural steadiness: differences between healthy young and elderly adults. IEEE Trans Biomed Eng. 1996;43:956 –966. 14 Fallang B, Saugstad OD, Hadders-Algra M. Goal directed reaching and postural control in supine position in healthy infants. Behav Brain Res. 2000;115:9 –18. 15 Bartlett DJ, Kneale Fanning JE. Relationships of equipment use and play positions to motor development at eight months corrected age of infants born preterm. Pediatr Phys Ther. 2003;15:8 –15. 16 Schmidt R, Lee T. Motor Control and Learning: A Behavioral Emphasis. 4th ed. Champaign, IL: Human Kinetics Publishers; 2005. 17 Thelen E, Smith LB. A Dynamic Systems Approach to the Development of Cognition and Action. Cambridge, MA: MIT Press; 1996. 18 Stergiou NE, Harbourne RT, Cavanaugh JT. Optimal movement variability: a new theoretical perspective for neurologic physical therapy. J Neurol Phys Ther. 2006;30: 120 –129. 19 Hughes MA, Duncan PW, Rose DK, et al. The relationship of postural sway to sensorimotor function, functional performance, and disability in the elderly. Arch Phys Med Rehabil. 1996;77:567–572. 20 Riach CL, Hayes KC. Maturation of postural sway in young children. Dev Med Child Neurol. 1987;29:650 – 658. 21 Duncan G, Wilson JA, MacLennan WJ, Lewis S. Clinical correlates of sway in elderly people living at home. Gerontology. 1992;38:160 –166. 22 Palmieri RM, Ingersoll CD, Stone MB, Krause BA. Center-of-pressure parameters used in the assessment of postural control. J Sport Rehabil. 2002;11:51– 66. 23 Goldberger AL, Rigney DR, Mietus J, et al. Nonlinear dynamics in sudden cardiac death syndrome: heart rate oscillations and bifurcations. Experientia. 1988;44:983–987. 24 Lanza GA, Guido V, Galeazzi MM, et al. Prognostic role of heart rate variability in patients with a recent acute myocardial infarction. Am J Cardiol. 1998;82:1323–1328. 25 Slutzky MW, Cvitanovic P, Mogul DJ. Deterministic chaos and noise in three in vitro hippocampal models of epilepsy. Ann Biomed Eng. 2001;29:607– 618. 26 Harbourne RT, Stergiou NE. Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. Phys Ther. 2009;89:267–282. 27 Harbourne RT, Stergiou NE. Nonlinear analysis of the development of sitting postural control. Dev Psychobiol. 2003;42: 368 –377. 28 Stergiou NE, Buzzi U, Kurz M, Heidel J. Nonlinear tools in human movement. In: Innovative Analyses for Human Movement. Stergiou NE, ed. Stergiou, Editor. Champaign, IL: Human Kinetics Publishers; 2004:63–90.

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29 Vaillancourt DE, Newell KM. The dynamics of resting and postural tremor in Parkinson’s disease. Clin Neurophysiol. 2000; 111:2046 –2056. 30 Pincus SM, Gladstone IM, Ehrenkranz RA. A regularity statistic for medical data analysis. J Clin Monit. 1991;7:335–345. 31 Cavanaugh JT, Guskiewicz KM, Giuliani C, et al. Recovery of postural control after cerebral concussion: new insights using approximate entropy. J Athl Train. 2006; 41:305–313. 32 Dusing SC, Mercer VS, Yu B, et al. Trunk position in supine of infants born preterm and at term: an assessment using a computerized pressure mat. Pediatr Phys Ther. 2005;17:2–10. 33 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. 34 Geyer MJ, Brienza DM, Karg P, et al. A randomized control trial to evaluate pressure-reducing seat cushions for elderly wheelchair users. Adv Skin Wound Care. 2001;14:120 –129; quiz 131–132. 35 Fenety PA, Putnam C, Walker JM. In-chair movement: validity, reliability and implications for measuring sitting discomfort. Appl Ergon. 2000;31:383–393. 36 Lacoste M, Therrien M, Cote JN, et al. Assessment of seated postural control in children: comparison of a force platform versus a pressure mapping system. Arch Phys Med Rehabil. 2006;87:1623–1629. 37 Theiler J, Eubank S, Longtin A, et al. Testing for nonlinearity in time series: the method of surrogate data. Physica D. 1992;58:77–94. 38 Kaplan D, Staffin P. Software for Heart Rate Variability. St Paul, MN: Macalester College; 1996. 39 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 full-term infants. Phys Ther. 2004;84: 159 –172. 40 Bos AF, van Loon AJ, Hadders-Algra M, et al. Spontaneous motility in preterm, small-for-gestational age infants, II: qualitative aspects. Early Hum Dev. 1997;50: 131–147. 41 Cioni G, Bos AF, Einspieler C, et al. Early neurological signs in preterm infants with unilateral intraparenchymal echodensity. Neuropediatrics. 2000;31:240 –251. 42 Bos AF. Differential effects of brain lesions and systemic disease on the quality of general movements: a preliminary report. Early Hum Dev. 1993;34:39 – 45. 43 Cioni G, Ferrari F, Einspieler C, et al. Comparison between observation of spontaneous movements and neurologic examination in preterm infants. J Pediatr. 1997; 130:704 –711. 44 Ohgi S, Morita S, Loo KK, Mizuike C. A dynamical systems analysis of spontaneous movements in newborn infants. J Mot Behav. 2007;39:203–214.

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CARE V Conference Series There Is Inadequate Evidence to Determine the Effectiveness of Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis: An Overview of High-Quality Systematic Reviews Rikke H. Moe, Ingvild Kjeken, Till Uhlig, Kåre Birger Hagen

Background. Patients with hand osteoarthritis are commonly treated by health care professionals (allied to medicine). Practice should be informed by updated evidence from systematic reviews of randomized controlled trials. Purpose. The purpose of this overview is to summarize the evidence from systematic reviews of the effectiveness of nonpharmacological and nonsurgical interventions for patients with hand osteoarthritis.

Data Sources and Study Selection. Systematic reviews published between January 2000 and October 2008 were identified by a comprehensive literature search. Data Extraction and Synthesis. Two reviewers independently selected reviews for inclusion, assessed their methodological quality, and extracted and synthesized data according to predefined criteria. Four systematic reviews finally were included. Based on single randomized controlled trials, there is some evidence of the effect of pain relief from topical capsaicin compared with placebo and for favorable functional outcomes for exercise and education compared with osteoarthritis information alone.

Limitations. In overviews, results are dependent on available systematic reviews. They are important tools to guide choice of interventions and locate areas where more research is needed, but they might not be useful for deciding specifically how interventions should be carried out.

Conclusions. There currently is insufficient high-quality evidence regarding nonpharmacological and nonsurgical interventions for hand osteoarthritis. Considering the limited research evidence and the prevalence and impact of the disease, there is an urgent need for more trials of nonpharmacological and nonsurgical interventions for hand osteoarthritis.

R.H. Moe, PT, MSc, is Research Fellow, National Resource Centre for Rehabilitation in Rheumatology, Diakonhjemmet Hospital, PO Box 23 Vinderen, 0319 Oslo, Norway. Address all correspondence to Ms Moe at: Rikke.Moe@ nrrk.no. I. Kjeken, OT, PhD, is Researcher, National Resource Centre for Rehabilitation in Rheumatology, Diakonhjemmet Hospital. T. Uhlig, MD, PhD, is Leading Consultant, National Resource Centre for Rehabilitation in Rheumatology, Diakonhjemmet Hospital. K.B. Hagen, PT, PhD, is Professor, Institute of Nursing and Health Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway. [Moe RH, Kjeken I, Uhlig T, Hagen KB. There is inadequate evidence to determine the effectiveness of nonpharmacological and nonsurgical interventions for hand osteoarthritis: an overview of highquality systematic reviews. Phys Ther. 2009;89:1363–1370.] © 2009 American Physical Therapy Association


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steoarthritis (OA) is a chronic joint condition characterized by loss of articular cartilage and new bone formation and is associated with pain, functional disability, and impaired quality of life.1 Most people with OA are female, and the condition increases in prevalence with age. Symptomatic OA in at least one hand joint occurs in about 20% of the population, and the majority of people over 55 years of age show radiographic hand OA.2,3 The occurrence of OA may vary depending upon the population studied and the diagnostic methods used.4 In a recent population-based study in Norway, the prevalence of self-reported hand OA in women between 24 and 76 years of age was 5.8%, whereas the corresponding estimate for men was 2.5%.5 Despite its growing burden on society, OA remains a poorly understood disease. At present, no diseasemodifying interventions are available,6 and current treatment of OA, therefore, is aimed mainly at alleviating symptoms and includes pharmacological approaches, physical therapy, exercises, braces and orthoses, weight reduction, and surgery.4 The European League Against Rheumatism (EULAR) endorses recommendations of a combination of pharmacological and nonpharmacological care in treating people with hand OA.7 However, although evidence of the effectiveness of education and exercise for reducing pain and improving physical functioning is convincing regarding knee OA,1 such

Available With This Article at www.ptjournal.org

evidence still is very uncertain for hand OA7 and hip OA.8 Decisions regarding the provision of health care increasingly are based on the available evidence from highquality clinical research. Patients, health care professionals, and researchers need information about the effectiveness of interventions so that they can improve selfmanagement strategies and clinical practice and set research priorities. Decisions regarding health care reimbursement also are increasingly evidence based. Thus, purchasing organizations and policy makers in health care will demand reliable information on the effectiveness of interventions. Conclusions based on a systematic review of randomized controlled trials (RCTs) are considered to provide the highest level of evidence about the effectiveness of an intervention. Based on a review of literature up to 2001, Chard and Dieppe concluded that nonpharmaceutical therapies for OA have not been researched enough for us to understand their potential benefit.9 The aim of this overview is to summarize currently available evidence from systematic reviews on the effectiveness of nonpharmacological and nonsurgical interventions for patients with hand OA.

Method Criteria for Including Reviews We included systematic reviews with the primary aim of investigating the effects of nonpharmacological and nonsurgical interventions for hand OA published in the English, Dutch, or Scandinavian language. More specifically, the following inclusion criteria were used:

• Audio Abstracts Podcast This article was published ahead of print on October 22, 2009, at www.ptjournal.org.

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• People with hand OA: Diagnosis according to the American College of Rheumatology criteria10 or other acceptable criteria. Reviews in-

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cluding people with OA in other joints or various rheumatic diagnoses were accepted only if results for hand OA could be extracted separately. • Interventions: All types of nonpharmacological and nonsurgical interventions. Excluded were interventions such as gene therapy, all types of invasive interventions (eg, injections, arthroscopy), therapeutic apheresis, and interventions related to pharmacological or surgical interventions. • Outcomes: For the purpose of this overview, the primary outcome measures were pain, stiffness, and function. The concept of “function” is based on the International Classification of Functioning, Disability and Health (ICF)11 definition, where “function” is an umbrella term for body functions, body structures, activities, and participation.1,9

We searched the Cochrane Library (Cochrane Database of Systematic Reviews and DARE), MEDLINE, EMBASE, PEDro, PsychINFO, and CINAHL from 2000 up to week 40 of 2008 for “hand osteoarthritis/ arthrosis or OA.” A broad computerized search strategy was developed (Appendix 1). Reference lists from retrieved reviews were examined. Retrieved hits were assessed by 2 of the authors (R.H.M., K.B.H.), who screened the titles and abstracts to identify relevant studies. If doubt occurred, one of the other authors was consulted. The full text of potential relevant articles was read by 2 authors (R.H.M., K.B.H.). Assessment of Methodological Quality Two authors (R.H.M., K.B.H.) independently assessed the methodological quality of the reviews. Disagreement was resolved by discussion. Eleven criteria were rated as “met,” “unclear/partly met,” or “not met” December 2009


Figure. Flowchart.

according to a criteria list from the Measurement Tool to Assess Systematic Reviews (AMSTAR) for assessing quality of evidence for each review. AMSTAR is a reliable and valid measurement tool for assessing systematic reviews based on assessments of quality of primary studies, design of primary studies, consistency, and directness, with overall scores ranging from 0 to 10 (out of a maximum of 11 criteria)12,13 (Appendix 2). Data Extraction and Synthesis Data on effectiveness were extracted from the identified high-quality reviews by 2 of the authors (R.H.M., K.B.H.). The following criteria were applied when data on effects were extracted: • Adequate quantitative pooling of data in reviews was regarded as more valid than a qualitative data synthesis approach. • If no direct comparisons between treatments were undertaken or no quantitative pooling of data was

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performed, the results were reported as “no quantitative pooling,” and the statement by the authors was reported. • When we found that the results were reported inconsistently in different sections of one review or inconsistently between 2 different reviews, the effects were extracted from the referenced primary studies.

Results Selection Procedure The literature search identified 173 reviews on hand OA. One hundred sixty-five articles were clearly not relevant based on information from the title and abstract. The full text of 8 articles was retrieved and assessed, and 3 articles were excluded for various reasons (Figure). Based on the assessment of the methodological quality of the remaining 5 systematic reviews, one review14 was excluded because it met none of the AMSTAR quality criteria for systematic reviews. Thus, 4 systematic reviews7,15–17 were included and served as the baVolume 89

sis of this umbrella review (Tab. 1). One of these reports is not strictly a systematic review, but offers recommendations for treatment.7 As it includes all of the core elements of a systematic review, we decided to include it in the present overview. The characteristics and methodological assessment of the 4 included reviews are presented in Table 1. Effects Generally, few reviews provided results by quantitative pooling. For one of the included reviews, results in terms of effects were not extracted because outcomes for the comparisons (ie, pain or function) were not specified.16 Pain. As shown in Table 2, topical capsaicin, the active principal of hot chili pepper, was more effective than a placebo in reducing pain. Zhang et al7 reported that the number needed to treat to obtain moderate to excellent (more than 50%) pain relief or symptomatic improveNumber 12

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Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis Table 1. Characteristics of Included Reviewsa

Review Towheed,16 2005

Zhang et al,7 2007

Egan and Brousseau,17 2007

Forestier and Francon,15 2008

a

Population Included Hand OA defined by any method or no method

Hand OA (not specified)

OA in thumb CMC joint

Hand OA (not specified)

Intervention and Control (Duration)

No. of Primary Studies (No. of Patients)

Outcomes Reported

Capsaicin cream vs placebo (NR)

2 RCTs (73)

NR

Low-energy neon laser therapy vs placebo (NR)

1 RCT (67)

NR

Yoga vs no therapy (NR)

1 RCT (45)

NR

Pressure gloves vs controls, no glove (NR)

1 RCT (45)

NR

Berthollet spa vs topical ibuprofen (NR)

1 RCT (116)

NR

Splinting (NR)

3 RCTs (69)

NR

Stinging nettle (Urtica dioica)

1 RCT (27)

NR

Exercise and education vs OA information (NR)

1 RCT (40)

NR

Exercise and education vs OA information (12 wk)

1 RCT (40)

Pain, function

Full splint vs half splint (1 wk)

2 RCTs (47)

Pain

Topical capsaicin vs placebo (4 wk)

2 RCTs (318)

Pain, function

Splint vs no treatment (7 mo)

1 RCT (33)

Desire for surgery

Comparison of different types of splints (1–4 wk)

3 RCTs (61)

Pain, function, strength

Thermal vapor at 44°C vs topical ibuprofen (3 weeks)

1 RCT (116)

Pain, function

Berthollet spa, old mud vs new mud (NR)

1 RCT (159)

NR

Methodological Assessment (AMSTAR)10,11 Met⫽4 (criteria 1, 3, 7, and 11) Not met⫽6 (criteria 2, 4, 5, 6, 8, and 10) Cannot answer⫽1 (criterion 9)

Met⫽2 (criteria 1 and 3) Not met⫽6 (criteria 4, 5, 6, 7, 8, and 10) Cannot answer⫽3 (criteria 2, 9, and 11) Met⫽4 (criteria 1, 3, 6, and 7) Not met⫽4 (criteria 2, 4, 5, and 10) Cannot answer⫽3 (criteria 8, 9, and 11) Met⫽3 (criteria 3, 7, and 11) Not met⫽5 (criteria 1, 4, 5, 6, and 10) Cannot answer⫽3 (criteria 2, 8, and 9)

AMSTAR⫽Measurement Tool to Assess Systematic Reviews, OA⫽osteoarthritis, NR⫽not reported, RCT⫽randomized controlled trial, CMC⫽carpometacarpal.

ment was 3 (95% confidence interval⫽2–5). For splinting of the thumb, there were conflicting results between 2 of the reviews on both the quantification of effect sizes and the direction of effect.7,17 Zhang et al presented a quantitative pooling of 2 RCTs18,19 and concluded that there was “more pain relief from the full splint compared to the half splint (ES [effect size]⫽0.64 [0.02–1.26]).”7 1366

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Egan and Brousseau did not provide any quantitative pooling, but reported that “there was fair evidence for the effectiveness of splinting to relieve pain and improve function.”17 However, they acknowledged that “this evidence came exclusively from pretest-posttest types of studies or from the pretest-posttest phase of RCTs.”17 Based on 3 RCTs comparing different kinds of splinting,18 –20 Egan and Brousseau further stated, “There was no clear evidence

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of the superiority of one type of splint over another for pain relief, comfort or function.”17 Egan and Brousseau included one trial (Buurke et al20) that was not included by Zhang et al.7 However, this trial included only 10 women who wore 3 different splints in random order, and it was not possible to calculate effect sizes “due to unreliability in data.”17 Weiss et al19 (N⫽26) compared a custom-made December 2009

Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis Table 2. Results Compiled From 4 Systematic Reviews on Nonpharmacological and Nonsurgical Intervention for Hand Osteoarthritis (OA)a Outcome Pain

Function

Desire for surgery

Intervention and Control Intervention

No. of Studies (No. of Patients)

Effect (95% Confidence Interval)

Thermal vapor at 44°C vs topical ibuprofen

1 RCT (116)

No quantitative pooling presented. Authors’ conclusion: “No significant difference.”

Long splint vs short splint

2 RCTs (47)

ES⫽0.64 (95% CI⫽0.02–1.26) in favor of long splint

OA in thumb CMC joint. Conflicting results in 2 reviews.7,17

Topical capsaicin vs placebo

2 RCTs (318)

NNT⫽3 (95% CI⫽2–5) in favor of topical capsaicin

Conflicting information between 2 reviews7,17 regarding number of included patients (73 vs 31)

Exercise and education vs OA information

1 RCT (40)

NNT⫽2 (95% CI⫽1–6) in favor of exercise and education (patient global function)

Thermal vapor at 44°C vs topical ibuprofen

1 RCT (116)

No quantitative pooling presented. Authors’ conclusion: “Significant vs control.”

Splint vs no treatment

1 RCT (33)

No quantitative pooling. Authors’ conclusion: “Approximately one third of each group desired surgery, indicating that splinting did not have an effect on this outcome.”

Comments

Authors state that “Berthollet was superior over topical ibuprofen at treatment completion.”

a NNT⫽number needed to treat to obtain moderate to excellent (more than 50%) pain relief or symptomatic or functional improvement, ES⫽effect size (mean difference between treatment and control divided by the standard deviation of the difference), RCT⫽randomized controlled trial, CMC⫽carpometacarpal, CI⫽confidence interval.

short opponens splint (which crosses only the carpometacarpal [CMC] joint) with a large opponens splint (which crosses the CMC joint, the wrist, and the metacarpophalangeal joint) and found that both splints reduced CMC joint pain significantly (pretest-posttest), but there was no significant difference between the splints in their effect on thumb pain. Although Egan and Brousseau presented no data for statistical recalculation, they concluded that “our calculations based on their graphs demonstrated the superiority of the short opponens splint.”17 Weiss et al18 (N⫽25) compared a custom-made short opponens thermoplastic splint (which crosses only the CMC joint) with a prefabricated neoprene splint (which crosses both the CMC joint and the metacarpophalangeal joint). They found that December 2009

thumb pain was significantly less (P⫽.019) when wearing the neoprene splint compared with the thermoplastic splint. Considering that these trials had relatively small sample sizes, with unclear and somewhat conflicting effect estimates, it may be reasonable to conclude that there is limited evidence that splints for the CMC joint in people with OA have a pain-reducing effect, but there is not enough evidence to give any recommendations regarding design or material. For the effect of thermal vapor treatment at 44°C versus topical ibuprofen on pain (1 RCT, N⫽116), no quantitative pooling was presented. The authors’ conclusion was presented as: “No significant difference.”15

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Function. For the comparison between exercise and education versus OA information only, the effects based on 1 RCT (N⫽40) was in favor of exercise and education. The number needed to treat to obtain moderate to excellent (more than 50%) improvement in “patient global function” on a visual analog scale was 2 (95% confidence interval⫽1– 6).7 For the effect of thermal vapor treatment at 44°C versus topical ibuprofen on function (1 RCT, N⫽116), no quantitative pooling was presented. The authors’ conclusion was presented as: “Significant vs control.”15 The authors further stated that “Berthollet was superior over topical ibuprofen at treatment completion.”15(p145)

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Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis Other outcomes. On the question of whether patients’ desire for surgery changed after splinting, the comparisons were splinting versus no treatment.17 This review was based on a single RCT (N⫽33), and no quantitative pooling was presented. The authors’ conclusion was: “Approximately one third of each group desired surgery, indicating that splinting did not have an effect on this outcome.”17(p74)

that could alter our findings have been published since then. Other limitations of overviews are that important information from primary studies is not reported and that overviews are too broad to be useful for clinicians. We would argue that overviews are important tools to guide directions in choice of interventions, but they might not be useful for deciding how interventions specifically should be carried out.

Discussion

Furthermore, the results of an umbrella review could be limited by the presence of publication bias at the level of primary studies. Although “publication bias” was assessed, according to AMSTAR, we cannot exclude that publication bias at the level of primary studies might have biased the findings in the present overview. In an umbrella review, it is very important to include all systematic reviews that meet the inclusion criteria. A broad computerized search strategy was performed (Appendix 1) in addition to hand searches, but we still might have missed eligible systematic reviews. We excluded reviews providing anecdotal evidence for clinically relevant (and potentially effective) interventions, but will argue that the main aims of such an overview are to provide clinicians, patients, and policy makers with unbiased information about the effectiveness of nonpharmacological interventions for hand OA and to provide the research community with unbiased information about research gaps on this topic.

Based on an overview of systematic reviews, we found that there is some evidence for the pain-relieving effect of topical capsaicin compared with a placebo and favorable functional outcomes for exercise and education compared with OA information alone. There also is limited evidence that splinting of the thumb CMC joint reduces pain. However, the most striking finding of the present overview was the paucity of available systematic reviews. Thus, there currently is a very limited body of evidence for the effects of nonpharmacological and nonsurgical interventions for hand OA. The present overview may have several limitations. A major limitation applies to summarizing evidence based on systematic reviews, as new, relevant primary studies may have been published but were not captured in the included systematic reviews. The review of Zhang et al7 is the most recent of the included reviews and addresses all nonpharmacological treatments. Zhang et al included studies published up to January 2006 and could identify only a few relevant primary studies (RCTs and controlled clinical trials). For example, they identified only 1 study on education, 2 studies on exercises and yoga, 1 study on transcutaneous electrical nerve stimulation, 1 study on laser treatment, and 3 studies on splints and gloves. It is unlikely that a substantial number of new studies 1368

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One of the reviews identified through the electronic searches was excluded based on the assessment of the methodological quality.14 It was published in a journal supplement and originally presented as a critical review, not a systematic review. The primary studies included were all covered by the other 4 reviews included in the present overview. Thus, including this review would

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not have significantly influenced the results. One of the reviews7 was published as a treatment recommendation, but we included it because it contained a systematic review of available treatments for hand OA. The other components of the article leading to treatment recommendations were not considered in this study. All reviews, regardless of whether they are systematic reviews or umbrella reviews, rely on the availability of high-quality studies of the effects of different interventions. Although the paucity of systematic reviews for the purpose of this study was striking, it also indicates a lack of highquality primary studies for the treatment of people with hand OA— which in itself is an incentive for systematic reviews. Thus, in this overview, in addition to summarizing the evidence on treatment of people with hand OA that does not include drugs or surgery, we identify a demand for primary studies on exercise, education, and splints, which could alleviate the burden of the disease to patients.

Conclusion Based on an overview of available systematic reviews, there currently is insufficient high-quality evidence regarding nonpharmacological and nonsurgical interventions for hand OA. Considering the limited literature in this area and the prevalence and impact of the disease, more primary studies and updated systematic reviews are warranted. Ms Moe, Dr Kjeken, and Dr Hagen provided concept/idea/project design and data analysis. All authors provided writing and project management. Dr Hagen provided data collection. Dr Uhlig provided facilities/ equipment. Dr Kjeken and Dr Uhlig provided consultation (including review of manuscript before submission). The authors thank librarian Hilde Iren Flaaten at Diakonhjemmet Hospital, Oslo, Norway, for performing the literature search.

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Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis This work was inspired and facilitated by the CARE V International Conference. A presentation of this work was given at the European League Against Rheumatism (EULAR) Congress; June 10 –13, 2009; Copenhagen, Denmark. This article was received December 15, 2008, and was accepted May 6, 2009. DOI: 10.2522/ptj.20080398

References 1 Jordan KM, Arden NK, Doherty M, et al. EULAR Recommendations 2003: an evidence based approach to the management of knee osteoarthritis: report of a task force of the Standing Committee for International Clinical Studies Including Therapeutic Trials (ESCISIT). Ann Rheum Dis. 2003;62:1145–1155. 2 Dahaghin S, Bierma-Zeinstra SM, Reijman M, et al. Prevalence and determinants of one month hand pain and hand related disability in the elderly (the Rotterdam study). Ann Rheum Dis. 2005;64: 99 –104. 3 Dahaghin S, Bierma-Zeinstra SM, Ginai AZ, et al Prevalence and pattern of radiographic hand osteoarthritis and association with pain and disability (the Rotterdam study). Ann Rheum Dis. 2005; 64:682– 687. 4 March LM, Bagga H. Epidemiology of osteoarthritis in Australia. Med J Aust. 2004; 180(5 suppl):S6 –S10.

5 Grotle M, Hagen KB, Natvig B, et al. Prevalence and burden of osteoarthritis: results from a population survey in Norway. J Rheumatol. 2008;35:677– 684. 6 Altman RD. Structure-/disease-modifying agents for osteoarthritis. Semin Arthritis Rheum. 2005;34(6 suppl 2):3–5. 7 Zhang W, Doherty M, Leeb BF, et al. EULAR evidence based recommendations for the management of hand osteoarthritis: report of a task force of the EULAR Standing Committee for International Clinical Studies Including Therapeutics (ESCISIT). Ann Rheum Dis. 2007;66: 377–388. 8 Zhang W, Doherty M, Arden N, et al. EULAR evidence based recommendations for the management of hip osteoarthritis: report of a task force of the EULAR Standing Committee for International Clinical Studies Including Therapeutics (ESCISIT). Ann Rheum Dis. 2005;64:669 – 681. 9 Chard J, Dieppe P. The case for nonpharmacologic therapy of osteoarthritis. Curr Rheumatol Rep. 2001;3:251–257. 10 Altman R, Alarcon G, Appelrouth D, et al. The American College of Rheumatology criteria for the classification and reporting of osteoarthritis of the hand. Arthritis Rheum. 1990;33:1601–1610. 11 International Classification of Functioning, Disability and Health: ICF. Geneva, Switzerland: World Health Organization; 2001. 12 Shea BJ, Grimshaw JM, Wells GA, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10.

13 Shea BJ, Bouter LM, Peterson J, et al. External validation of a measurement tool to assess systematic reviews (AMSTAR). PLoS ONE. 2007;2(12):e1350. 14 Mejjad O, Maheu E. Therapeutic trials in hand osteoarthritis: a critical review. Osteoarthritis Cartilage. 2000;8(suppl A): S57–S63. 15 Forestier R, Francon A. Crenobalneotherapy for limb osteoarthritis: systematic literature review and methodological analysis. Joint Bone Spine. 2008;75:138 –148. 16 Towheed TE. Systematic review of therapies for osteoarthritis of the hand. Osteoarthritis Cartilage. 2005;13:455– 462. 17 Egan MY, Brousseau L. Splinting for osteoarthritis of the carpometacarpal joint: a review of the evidence. Am J Occup Ther. 2007;61:70 –78. 18 Weiss S, LaStayo P, Mills A, Bramlet D. Splinting the degenerative basal joint: custom-made or prefabricated neoprene? J Hand Ther. 2004;17:401– 406. 19 Weiss S, LaStayo P, Mills A, Bramlet D. Prospective analysis of splinting the first carpometacarpal joint: an objective, subjective, and radiographic assessment. J Hand Ther. 2000;13:218 –226. 20 Buurke JH, Grady JH, de VJ, Baten CT. Usability of thenar eminence orthoses: report of a comparative study. Clin Rehabil. 1999;13:288 –294.

Appendix 1. Search Strategy

The following searched:

databases

were

MEDLINE 1996 –2008, week 40; CINAHL 1982–2008, week 40; AMED 1985–2008, week 40; EMBASE 1996 –2008, week 40; PsychINFO 1996 –2008, week 40; The Cochrane Library and PEDro 2000 –2008, week 40. The search strategy has been formulated in Ovid (MEDLINE, CINAHL, EMBASE, and AMED). A broad computerized search strategy was built upon the following components to identify: (a) Study type: Systematic reviews Search strategy: 1. controlled.ab. (ab.⫽all searchable words from the

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abstract); 2. design.ab.; 3. evidence.ab.; 4. randomized controlled trials/ [MESH]; 5. meta-analysis.pt. (pt.⫽publication type); 6. review.pt.; 7. sources.ab.; 8. studies.ab.; 9. OR/1– 8, 10. letter.pt.; 11. comment.pt.; 12. editorial.pt.; 13. OR/10 –12, 14. 9 NOT 13 (b) Participants: Hand[MeSH], osteoarthritis[MeSH] OR osteoarthrosis[MeSH] (c) Interventions: Nonpharmacological and nonsurgical exp “behaviour and behaviour mechanisms”/ OR exp “psychological phenomena and processes”/ OR exp “mental disorders”/ OR exp “behavioural disciplines and activities”/

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In addition, the following free-text words were used: hand osteoathritis OR osteoarthrosis AND modalities/ OR heat/ OR cold/ OR cryo/ OR TENS/ OR thermotherapy/ OR acupuncture/ OR copper/ OR bracelet/ OR magnet/ OR exercise/ OR flexibility/ OR strengthening/ OR aerobic/ OR Feldenkrais/ OR aquatic/ OR hydrotherapy/ OR pool exercise/ OR glucosamine/ OR herbal/ OR laser/ OR ultrasound/ OR ultrasonography/ OR nonmedical/ OR nonmedicinal/ OR noninvasive/ OR braces/ OR orthoses/ OR physiotherapy/ OR physical therapy/ OR education/ OR school/ OR management/ OR treatment/ OR recommendations/ OR distraction/ OR traction/ OR conservative/ OR NOT surgery NOT

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Nonpharmacological and Nonsurgical Interventions for Hand Osteoarthritis pharmacological therapy

NOT

pharmaco-

Appendix 2. Criteria for Assessment of the Quality of the Systematic Reviews

The following MESH terms and floating subheadings were excluded from the search result with NOT: exp “Specialties, Surgical”/ OR su.fs [Surgery as floating subheading to a MESH term]/ OR exp “inorganic chemicals”/ OR exp “organic chemicals”/ OR exp “heterocyclic compounds”/ OR exp “polycyclic compounds”/ OR exp macromolecular substances/ OR exp “hormones, hormone substitutes, and hormone antagonists”/ OR exp “enzymes and coenzymes”/ OR exp “carbohydrates”/ OR exp “lipids”/ OR exp “amino acids, peptides, and proteins”/ OR exp “nucleic acids, nucleotides, and nucleosides”/ OR exp “complex mixtures”/ OR exp “biological factors”/ OR exp “biomedical and dental materials”/ OR exp “pharmaceutical preparations”/ OR exp “chemical actions and uses”/

The following criteria were rated as “met,” “unclear/partly met,” or “not met” according to the Measurement Tool to Assess Systematic Reviews (AMSTAR) criteria list12,13:

(d) Language restrictions: English, Dutch, or Scandinavian language

9. Were the methods used to combine the findings of studies appropriate?

1. Was an “a priori” design provided? 2. Was there duplicate study selection and data extraction? 3. Was a comprehensive literature search performed? 4. Was the status of publication (ie, gray literature) used as an inclusion criterion? 5. Was a list of studies (included and excluded) provided? 6. Were the characteristics of the included studies provided? 7. Was the scientific quality of the included studies assessed and documented? 8. Was the scientific quality of the included studies used appropriately in formulating conclusions?

10. Was the likelihood of publication bias assessed? (e) Publication year from to 2000 to 2008, week 40

11. Were potential conflicts of interest included?

Additionally, The Cochrane Library was manually explored title by title for possible relevant reviews.

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CARE V Conference Series

New Models for Primary Care Are Needed for Osteoarthritis Krysia S. Dziedzic, Jonathan C. Hill, Mark Porcheret, Peter R. Croft Musculoskeletal problems are the most common cause of restriction in daily life in most countries. Most health care for musculoskeletal problems is provided in primary care settings, and back pain and joint problems together represent the largest workload of cases of chronic disease seen and managed there. This article reflects on aspects of the occurrence, natural history, prognosis, and management of common joint problems in primary care. Although the biomedical model has contributed to major advances, a model that embraces chronic pain management and its psychological and social components is needed. In particular, primary care is the ideal arena to achieve high-impact secondary prevention of pain and disability in people with osteoarthritis. Physical therapists are in a crucial position in primary care to provide support for self-management of this condition, especially for interventions related to exercise and behavioral change.

K.S. Dziedzic, PhD, is Senior Lecturer in Physiotherapy, Arthritis Research Campaign National Primary Care Centre, Primary Care Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Address all correspondence to Dr Dziedzic at: k.s. [email protected]. J.C. Hill, PhD, is Lecturer in Physiotherapy, Arthritis Research Campaign National Primary Care Centre, Primary Care Sciences, Keele University. M. Porcheret, MBBS, MPhil, is GP Research Fellow, Arthritis Research Campaign National Primary Care Centre, Primary Care Sciences, Keele University. P.R. Croft, MD, is Professor of Primary Care Epidemiology, Arthritis Research Campaign National Primary Care Centre, Primary Care Sciences, Keele University. [Dziedzic KS, Hill JC, Porcheret M, Croft PR. New models for primary care are needed for osteoarthritis. Phys Ther. 2009;89:1371–1378.] © 2009 American Physical Therapy Association


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usculoskeletal problems, including osteoarthritis, are the most common cause of restriction in daily life in most countries.1,2 Primary care, although its structure varies among countries, is the arena in which most health care for musculoskeletal problems is provided. Many individuals who experience these problems do not seek health care,3 but the problems are so common that they still represent the largest workload of cases of chronic disease seen and managed in primary care.

The medical model has achieved substantial advances for people with inflammatory joint disease or advanced osteoarthritis, through drugs and surgery, respectively. However, most people seen in primary care will not have these more severe conditions, and most of the population disability attributable to musculoskeletal disease is generated by the large numbers of older people with less severe osteoarthritic joint pain and of working-age adults with regional musculoskeletal syndromes such as back, neck, and shoulder pain. Although local mechanical factors such as repetitive activity are linked with the corresponding regional musculoskeletal pain syndrome (eg, at the shoulder),4,5 there is consistent evidence across different regional syndromes that psychological factors, such as work satisfaction, and social factors, such as education level, often play crucial roles in determining whether patients with these problems in primary care recover or develop chronic pain and Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on October 22, 2009, at www.ptjournal.org.

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disability.6 This is not to argue against the basic tenets of clinical diagnosis, because knowledge of pathology is clearly important in guiding management of many musculoskeletal conditions. However, there is a need to appreciate that such management embraces broader principles than pathology alone and that an overemphasis on diagnosis and attempts at cure often may do little to address the prevention of persistent and progressive osteoarthritis. The challenge for primary care is to preserve the advantages of the medical model while encouraging a shift of perspective toward a model of care that addresses biopsychosocial factors associated with the development of chronicity. Drugs and operations, which may be highly successful interventions in selected patients with specific conditions, will not alone solve most musculoskeletal problems seen in primary care. As a consequence, questions have been raised about the need for new models of primary care to better address the public health and prevention perspectives required for effective osteoarthritis management. For example, it may be possible to replace the existing “wait and see” model of care with a prognostic approach, based on epidemiological evidence. Patients are stratified and potential complex “cases” identified who are appropriate for fast-tracked, targeted secondary prevention. Models of care within the occupational medicine arena have made large shifts to early, targeted care, but it remains unclear how best to adopt a similar model within the primary care osteoarthritis arena. The purposes of this perspective article are to identify the current gaps in knowledge about management of osteoarthritis and to consider how existing models of care might be shaped into management pathways

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to provide better clinical outcomes in the future.

Frequency Musculoskeletal problems are a very common reason for visits to primary care, as demonstrated by typical data in the United Kingdom (Figs. 1 and 2). These data are taken from national statistics based on continuous recording of morbidity seen in consultations in a sample of family practices in the United Kingdom,7 and similar figures are available from the Netherlands.8 The data confirm that conditions that are serious for the individual, such as rheumatoid arthritis, and that are commonly seen in secondary care specialist rheumatology clinics represent only a minority of musculoskeletal conditions seen in primary care. Here other problems dominate, such as osteoarthritis, back pain, and other regional pain syndromes. The distribution of consultations for these conditions varies little with age and sex except for patients with osteoarthritis. Among older people (75– 84 years of age), osteoarthritis dominates as the main reason for primary care musculoskeletal consultations.

Natural History The classic view of the natural history for these patients with regional musculoskeletal pain was that most of them get better and that the impact of these problems on health care practice and society is borne by the minority of people who have problems that become chronic. However, evidence has emerged over the past 20 years showing this picture is not entirely true. Certainly, patients who consult a primary care professional for back, shoulder, or joint pain tend to improve, but most will not fully recover.9 Even those who are completely better within 3 months of consulting (ie, no pain, no disability) will have, in the case of back pain at least, a recurrence rate

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Primary Care for Osteoarthritis of about 25% follow-up.10

in

2

years

of

This is particularly true for people with osteoarthritis, which affects mainly the knee, hip, hand, and foot, among whom the problem tends to become long-term after they have been seen for health care.11 In fact, the natural history of osteoarthritis in older people looks rather similar to that of back pain. Their pain and disability tends to improve after consultation, but most patients will not recover completely, and a distinct proportion will progress to more severe, persistent problems. The longer the duration of problems at the time of consultation, the longer the problem is likely to last subsequently.12 Comorbidity is commonly seen in older adults with osteoarthritis. In the Netherlands, a review of both community and general practice databases showed that hypertension, heart disease, and osteoarthritis commonly occurred together, with 20% of a community cohort of older adults (55– 85 years of age) having both hypertension and osteoarthritis and 18% having osteoarthritis and heart disease.13

ANNUAL INCIDENCE OF CONSULTATIONS IN PRIMARY CARE Patients consulting per 10,000 population per year 400

Male s

350

Fe male s

300 250 200 150 100 50 0

Rheumatoid

Osteoarthritis

Back

Regional Pain

Arthritis

Figure 1. Musculoskeletal consultations with a general practitioner in a 1-year period for adults 18 years of age and over (based on data from McCormick et al7).

Primary Care Consultations in 75- to 84-Year-Olds 1,400 per 10,000 population 1,200 per year

Males Females

1,000 800

Prognostic Factors The traditional medical view of joint pain in primary care is that the diagnosis will determine the route of subsequent treatment.14 Rheumatoid arthritis and advanced osteoarthritis both represent examples to support this view. However, for most musculoskeletal problems seen in primary care, including osteoarthritic joint pain in older people, prognostic characteristics other than medical diagnosis best predict outcome. The severity of the presenting pain and disability is a crucial factor, as well as psychosocial factors, regardless of the location or cause of the pain. This is the rationale for researchers to establish standardized assessment December 2009

600 400 200 0

In

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at m m a

or

y Po

l

ya ym

lg

is

ia

rit

th

r oa

c Ne

k

Ba

ste

O

ck g Re

io

l na F

c ra

r tu

es

Figure 2. Musculoskeletal consultations with a general practitioner in a 1-year period for older adults 75 to 84 years of age (based on data from McCormick et al7).

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Primary Care for Osteoarthritis Table. National Institute of Health and Clinical Excellence (NICE) Guidelines on the Management of Osteoarthritis: Nonpharmacological Approaches23 Other Nonpharmacological Approaches Recommended as Adjuncts to the Core Treatments:

All Patients With Osteoarthritis Should Have as Core Treatment: Access to information, advice, and education

Transcutaneous electrical nerve stimulation

Weight loss if overweight or obese

Supports and braces

Strengthening exercises and aerobic fitness training

Manual therapy, particularly manipulation and stretching for the hip Local cold/heat therapy Assistive devices, canes, walking sticks

of pain in practice15–18 and to increasingly advocate that patients who are seen with a range of indicators of poor prognosis need effective, early, targeted secondary prevention in primary care.19 –21 The evidence as to how such information may improve practice is yet to come, but this is undoubtedly a powerful area for current research.

Evidence for Treatment Porcheret et al22 have provided an overview of systematic reviews of primary care treatments for osteoarthritis, and more recently the National Institute of Health and Clinical Excellence (NICE) in the United Kingdom has published guidelines for the management of osteoarthritis, including its management in primary care.23 The NICE guidelines have outlined pharmacological and nonpharmacological approaches.23 They advise that all patients with osteoarthritis should have access to information, advice, and education; strengthening exercises and aerobic fitness training; and weight loss if overweight or obese. Other nonpharmacological approaches (Table) recommended by NICE as adjuncts to the core treatments are manual therapy, particularly manipulation and stretching for the hip; transcutaneous electrical nerve stimulation; local cold or heat 1374

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therapy; supports and braces; and assistive devices, canes, and walking sticks. The Osteoarthritis Research Society International has published consensus statements based on a detailed systematic review and meta-analysis of available data.24 The European League Against Rheumatism is publishing a series of evidence-based guidelines for each joint separately (eg, the hand25). Thus, there is much reviewing and consensus work on which primary care practitioners can reflect when choosing the best treatment for their patients. There is substantial agreement among the different publications (although inevitably also some differences on matters of detail).26 For primary care, the first message that emerges from the reviews and guidelines is that there is a range of simple interventions for which there is evidence of efficacy. By contrast, evidence that these same interventions are being systematically and widely put into practice, and evidence about how to do this, is singularly lacking. A patient survey in the United Kingdom27 revealed many people with diagnosed osteoarthritis of the knee had not received, been advised about, or tried the first-line nonpharmacological interventions recommended in the

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guidelines, such as written information about osteoarthritis and joint pain, weight loss, and exercise, in contrast to the majority who had tried pharmacological approaches to analgesia. A French national survey of general practitioners, in contrast, revealed higher reported rates of advice or delivery of many nonpharmacological interventions, but pessimism about the capacity of patients to maintain these approaches in the long term.28 The second message is that there are other things to be tried if the basic core interventions fail to relieve the pain and disability, including referral to specialists. However, once again, the way these interventions are applied in primary care practice and the extent of their use in that setting seem haphazard and insufficient. There are many likely reasons for this, which include the pessimism of physicians and their patients about the likely success of trying such interventions, the low priority given to osteoarthritis by physicians and patients compared with the comorbidities of many older patients with joint pain,29 and the dominance of the medical model, which encourages clinicians to focus on identifying the patients who might benefit from joint replacement or invasive procedures and leaves them unsure what to do about the others apart from prescriptions of anti-inflammatory drugs. Evidence for the effectiveness of drug treatment for osteoarthritis is available only for short-term effects on pain.24 Such effects may be valuable for the patient but are only a small part of the picture in a problem that is long-term and persistent, although variable in the severity of its manifestations. One problem of drug treatment in older patients with osteoarthritis is that the small risk of serious side effects, spread across the many recipients of any drug sold on the basis December 2009

Primary Care for Osteoarthritis of a benefit for this common problem, will end up affecting many people. Adjunctive treatments have been recommended on the basis of relatively small effects. However, the indirect costs of osteoarthritis are large, not only from the disease itself but also from psychological and work-related factors.30 Thus, the beneficial effects of drugs, physical therapy, or self-care, however small, also may have substantial population benefits because of the numbers involved.

The Role of Nonpharmacological Treatments and New Models for Care Information provided in a positive way that helps patients to understand their joint pain and its causes and information about exercise, weight loss, intelligent use of analgesia and some anti-inflammatory medications, aids and appliances, and selected referral for further procedures such as joint replacement appear in guidelines and summaries of evidence about management of clinical osteoarthritis in primary care. In osteoarthritis, the medical model has provided the basis for the success of joint replacement surgery for people with osteoarthritis who have severe functional limitation. However, the relationship between symptoms and osteoarthritic changes in the joint is weak.31 In defining osteoarthritis as “wear and tear” in the joint and as a degenerative disease, the medical model can be unhelpful. Such definitions may not, in themselves, be harmful, but if interpreted by the patient and health care professional as “nothing can be done” and that osteoarthritis is an inevitable part of aging, this hampers good clinical care. For example, there is good evidence for the benefit of exercise in relieving pain and improving function in people with osteoar-

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thritis, yet some people may believe that exercise will “wear out” joints. Erroneous health beliefs can be detrimental to a good clinical outcome. The first obvious shift to a new model of care has been the emphasis placed on the need for positive approaches to self-care, particularly among patients whose prognosis appears relatively good. We do not know the effect of a physician or therapist stating that “the joint is degenerating” or “it is your age” or “there is nothing much to be done— learn to live with it,” but it is unlikely to be helpful. In contrast, positive encouragement from the health care professional for self-management by patients, such as the approach pioneered by Lorig and colleagues in the United States,32 has many attractive features and is reasonable to pursue on humanitarian and common-sense grounds. Evidence, however, is variable about the long-term effects of such approaches on clinical outcome, although they do seem to increase people’s sense of confidence and of being in control of their symptoms and their condition,33 and this might be a crucial component in helping people to live independently and positively with their joint pain, even in the absence of cure and in the presence of persisting disability. Many patients accept the need for and attraction of self-management but say they need help from health care professionals to achieve it. This has contributed to the idea of selfmanagement needing to be strongly supported by health care professional involvement in chronic disease programs, including joint pain. An alternative to the medical approach is the biopsychosocial model of care.34,35 In this model, there is an understanding that addressing physical complaints alone is not enough for some patients and needs to be seen in the context of their psychological and social needs. For examVolume 89

ple, pain medication alone will not address a person’s fear of moving (fear-avoidance beliefs) or a person’s depression from being unable to work. Factors outside the joint need to be considered, and these factors are not necessarily addressed in the biomedical model.35 In the biopsychosocial model, environmental and work-related risk factors are recognized as important. Osteoarthritis can lead to reduced capacity to perform activities of daily living, participate in leisure activities, or remain in work.35 Who should provide care for such patients who score highly on psychosocial indicators? High-quality trials have shown that physical therapists can deliver exercise, selfmanagement, and patient education approaches within the health care settings in the United Kingdom, and these approaches have been shown to be cost-effective.23,36 –38 The problem is widespread implementation. This problem is due partly to the configuration of services and partly to the lack of recognition that although patients want self-management, they want it to be led by the health care practitioner.39 We are left with the question of whether large numbers of primary care practitioners should be trained to extend their traditional scopes and provide treatment beyond their traditional discipline-bound practice or whether optimal care is more appropriately provided by primary care multidisciplinary units. Technological developments, such as Internet-based interventions, may further change the ways in which practitioners address psychosocial issues to provide clinical benefit in the future. Another emerging option that may prove cost-effective is for patients with high scores on psychosocial measures to be better identified in practice so that interventions

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is evidence of efficacy, clinical effectiveness, and cost-effectiveness.45,46

The UK Arthritis and Musculoskeletal Alliance (ARMA) Standards of Care for osteoarthritis41 indicated the need for key workers to coordinate management of osteoarthritis in primary care. With limited resources, however, a health care worker working alongside the general physician could provide the first level of care, trained by physical therapists to give high-quality advice and monitoring and to know when to refer the patient. This model currently is being tested in the United Kingdom for patients with hand or knee osteoarthritis. Other groups are trying different approaches, such as testing the efficacy of nurse-led pain coping skills training for patients with osteoarthritis.42

Although there is no trial of the overall effect of a physical therapist–led primary care service for the management of osteoarthritis, much of the evidence about specific components in the primary care of osteoarthritis suggests that it is a model of care worth investigating. In back pain care, studies such as that of Fritz et al47 are beginning to provide evidence that physical therapists following guidelines supported by their own profession can result in improvements beyond usual care. Occupational therapists have developed interventions that embrace the biopsychosocial model and draw on educational-behavioral techniques, and these interventions have resulted in improvements in clinical outcomes over and above those seen in patients participating in standard occupational therapy programs.48 However, in the UK system at least, one crucial advantage of general practitioners is that they deliver continuing care for all conditions with which their patients may present, whereas therapy services are still designed to deliver discrete episodes of care. This anomaly may need to be tackled in any new model of primary care, because continuity is an important component of care for any chronic disease such as osteoarthritis, and there is evidence for its effectiveness as a component in, for example, the occupational rehabilitation of patients with back pain.49

Occupational therapists have been trained in approaches that consider the multidimensional interactions of a person with osteoarthritis and his or her psychological, social, and environmental needs. It has been estimated, for example, that 70% of people 75 years of age and older have difficulty preparing meals, shopping, doing housework, or performing personal care.35,43 Access to such therapists may be limited. Older people often feel that nothing can be done, and rates of consultation with a general physician are lower than might be expected, and older adults with hand pain rarely see an occupational therapist in any one year.44

Emerging New Roles for Physical Therapists Physical therapists are in a crucial position in primary care to provide greater support for patients with osteoarthritis, especially around selected topics such as exercise and advice on pain management. This is in addition to their capacity to provide specific interventions for which there

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Psychological interventions such as pain coping and cognitive behavioral therapy strategies can influence not only the experience of pain but also the impact of pain on psychological distress and physical functioning. They have been shown to be effective where traditional biomedical approaches have failed.42 Self-efficacy, for example, has been found to be an important predictor of adjustment to

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pain from osteoarthritis.42,50,51 Access to information, education, and self-management approaches are advocated as core treatments in all current guidelines.23–25 Although the benefits in terms of pain relief and functional ability are disappointing, such approaches are known to improve self-efficacy, anxiety, and depression.33 People with severe and limiting chronic pain conditions have been managed in specialist pain centers with highly trained practitioners. Evidence shows, for example, that 100 hours of cognitive behavioral therapy can improve outcomes in people with low back pain.52 However, providing such specialist services for large numbers of people with musculoskeletal pain in primary care is prohibitive. Hay et al53 have shown that in providing physical therapists with training in pain management for people with low back pain, brief interventions can be used successfully in routine clinical practice for the majority of patients with mild to moderate psychological dysfunction.

Achieving Change Achieving change in our models of care means something wide-ranging and radical, as it means taking on board all the evidence in the literature about the importance of the biopsychosocial model in understanding and managing painful musculoskeletal conditions, including osteoarthritis, and being prepared to extend the scope of traditional discipline-bound practice and expertise. There is evidence, for example, that managing the depression associated with osteoarthritis improves the pain and depression outcomes of the joint disease, as well as the emotional problem itself.54 The challenges for research and clinical practice in physical therapy are to identify the best and most costeffective approach to tackling bioDecember 2009

Primary Care for Osteoarthritis psychosocial issues and to determine the extent to which physical therapists should be trained in specific behavioral techniques and in managing the social context of the clinical problem, such as work rehabilitation, in order to achieve optimal outcomes.

sionals.55 However, the providers of such care often are limited in their capacity to tackle these broader issues. New models of care are needed to ensure patients feel confident to commence and maintain preventive activity and self-management programs.

Partnerships between occupational therapists and physical therapists in the management of osteoarthritis would seem to be sensible for complex cases. Core interventions in the management of osteoarthritis also include weight loss and exercise. These are complex interventions where the health care practitioner has to be skilled at guiding patients in self-management. Simply giving someone a leaflet or showing someone quadriceps muscle exercises will not be sufficient. Lifestyle behavioral interventions also can have a positive benefit on physical and social functioning. Physical therapists may need to work with other agencies to consider how they might engage social networks to enhance opportunities for aerobic exercises and healthy eating.

Primary care has to shift to a more positive view while not peddling the idea of a cure. Much is possible, as has been highlighted by a recent review of the range of small benefits that nonpharmacological treatments can bring for back pain.56 Research is currently focused on exploring which clinical pathways best achieve clinical outcomes, not only for improved self-management among patients with a relatively good prognosis but also for solutions to more complex cases such as additional training for physical therapists in behavioral approaches or the provision of care using greater cross-professional partnerships. Primary care is the ideal arena to achieve high-impact secondary prevention of pain and disability in people with osteoarthritis, and physical therapists have a key role to play.

Summary The evidence of the effectiveness of nonpharmacological approaches that educate patients to be more confident to provide self-care and control their own symptoms is growing, but current models of care need to be reconsidered. Patients are asking for more help from health care professionals, such as physical therapists, to assist them in better understanding how to cope with and manage their symptoms, particularly in respect to levels of activity among older patients with osteoarthritis. This is particularly relevant for patients who have unhelpful illness perceptions and misconceptions, which may hinder progress unless adequately addressed and which may be matched by similar unhelpful attitudes among health care profesDecember 2009

Dr Dziedzic and Professor Croft provided concept/idea/project design. All authors provided writing. Dr Hill provided consultation (including review of manuscript before submission). This work was inspired and facilitated by the CARE V Conference; April 23–25, 2008; Oslo, Norway. Dr Croft is grateful to the international and local organizers of the CARE V Conference for giving him the opportunity to attend the conference, for stimulating the genesis of this article, and for being such kindly hosts. Many staff members of the Arthritis Research Campaign National Primary Care Centre at Keele University have provided much of the thinking and the evidence used in this piece, responsibility for which remains, however, our own. This work was supported by research funded by the Arthritis Research Campaign UK and the National Institute of Health Research UK.

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This article was received January 7, 2009, and was accepted August 11, 2009. DOI: 10.2522/ptj.20090003

References 1 Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation: United States, 2003–2005. MMWR Morb Mortal Wkly Rep. 2006;55:1089 – 1092. 2 Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ. 2003;81:646 – 656. 3 Jinks C, Jordan K, Ong BN, Croft PR. A brief screening tool for knee pain in primary care (KNEST), 2: results from a survey in the general population aged 50 and over. Rheumatology. 2004;43:55– 61. 4 van der Windt DA, Thomas E, Pope DP, et al. Occupational risk factors for shoulder pain: a systematic review. Occup Environ Med. 2000;57:433– 442. 5 Miranda H, Punnett L, Viikari-Juntura E, et al. Physical work and chronic shoulder disorder: results of a prospective population-based study. Ann Rheum Dis. 2008;67:218 –223. 6 Macfarlane GJ, Pallewatte N, Paudyal P, et al. Evaluation of work-related psychosocial factors and regional musculoskeletal pain: results from a EULAR Task Force. Ann Rheum Dis. 2009;68:885– 889. 7 McCormick A, Fleming D, Charlton J. Morbidity Statistics From General Practice: Fourth National Study, 1991–1992. London, United Kingdom: HMSO; 1995. 8 van der Waal JM, Bot SD, Terwee CB, et al. The incidences of and consultation rate for lower extremity complaints in general practice. Ann Rheum Dis. 2006;65: 809 – 815. 9 Croft PR, Macfarlane GJ, Papageorgiou AC, et al. Outcome of low back pain in general practice: a prospective study. BMJ. 1998; 316:1356 –1359. 10 Carey TS, Garrett JM, Jackman A, Hadler N. Recurrence and care seeking after acute back pain: results of a long-term follow-up study. North Carolina Back Pain Project. Med Care. 1999;37:157–164. 11 Blagojevic M, Jinks C, Jordan KP. The influence of consulting primary care on knee pain in older people: a prospective cohort study. Ann Rheum Dis. 2008;67: 1702–1709. 12 Thomas E, Dunn KM, Mallen C, Peat G. A prognostic approach to defining chronic pain: application to knee pain in older adults. Pain. 2008;139:389 –397. 13 Schram MT, Frijters D, van de Lisdonk EH, et al. Setting and registry characteristics affect the prevalence and nature of multimorbidity in the elderly. J Clin Epidemiol. 2008;61:1104 –1112. 14 Kent PM, Keating JL, Taylor NF. Primary care clinicians use variable methods to assess acute non-specific low back pain and usually focus on impairments. Man Ther. 2009;14:88 –100.

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Primary Care for Osteoarthritis 15 Von Korff M, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. Pain. 1992;50:133–149. 16 Von Korff M, Miglioretti DL. A prognostic approach to defining chronic pain. Pain. 2005;117:304 –313. 17 Peat G, Thomas E, Croft PR. Staging joint pain and disability: a brief method using persistence and global severity. Arthritis Rheum. 2006;55:411– 419. 18 Huas D, Pouchain D, Gay B, et al; French College of Teachers in General Practice. Assessing chronic pain in general practice: are guidelines relevant? A cluster randomised controlled trial. Eur J Gen Pract. 2006;12:52–57. 19 Boersma K, Linton SJ. Screening to identify patients at risk: profiles of psychological risk factors for early intervention. Clin J Pain. 2005;21:38 – 43. 20 Turk DC. The potential of treatment matching for subgroups of patients with chronic pain: lumping versus splitting. Clin J Pain. 2005;21:44 –55. 21 Hill JC, Dunn KM, Lewis M, et al. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum. 2008;59:632– 641. 22 Porcheret M, Jordan K, Croft PR; Primary Care Rheumatology Society. Treatment of knee pain in older adults in primary care: development of evidence-based model of care. Rheumatology. 2007;46:638 – 648. 23 NICE 2008. Osteoarthritis: the care and management of osteoarthritis in adults. Available at: http://www.nice.org.uk/ CG059. Accessed June 2009. 24 Zhang W, Moskowitz RW, Nuki G, et al. OARSI recommendations for the management of hip and knee osteoarthritis, part II: OARSI evidence-based, expert consensus guidelines. Osteoarthritis Cartilage. 2008;16:137–162. 25 Zhang W, Doherty M, Leeb BF, et al. EULAR evidence-based recommendations for the management of hand osteoarthritis: report of a Task Force of the EULAR Standing Committee for International Clinical Studies Including Therapeutics (ESCISIT). Ann Rheum Dis. 2007;66:377–388. 26 Misso ML, Pitt VJ, Jones KM, et al. Quality and consistency of clinical practice guidelines for diagnosis and management of osteoarthritis of the hip and knee: a descriptive overview of published guidelines. Med J Aust. 2008;189:394 –399. 27 Porcheret M, Jordan K, Jinks C, Croft PR; Primary Care Rheumatology Society. Primary care treatment of knee pain: a survey in older adults. Rheumatology. 2007;46: 1694 –1700. 28 Conrozier T, Marre JP, Payen-Champenois C, Vignon E. National survey on the nonpharmacological modalities prescribed by French general practitioners in the treatment of lower limb (knee and hip) osteoarthritis: adherence to the EULAR recommendations and factors influencing adherence. Clin Exp Rheumatol. 2008;26:793–798. 29 Bedson J, Mottram S, Thomas E, Peat G. Knee pain and osteoarthritis in the general population: what influences patients to consult? Fam Pract. 2007;24:443– 453.

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30 Li X, Gignac MA, Anis AH. The indirect costs of arthritis resulting from unemployment, reduced performance, and occupational changes while at work. Med Care. 2006;44:304 –310. 31 Peat G, McCarney R, Croft PR. Knee pain and osteoarthritis in older adults: a review of community burden and current use of primary health care. Ann Rheum Dis. 2001;60:91–97. 32 Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002;288:2469 –2475. 33 Buszewicz M, Rait G, Griffin M, et al. Self management of arthritis in primary care: randomised controlled trial. BMJ. 2006;333:867– 868. 34 Engel GL. The need for a new medical model: a challenge for biomedicine. Science. 1977;196:129 –136. 35 Hunt MA, Birmingham TB, Skarakis-Doyle E, Vandervoort AA. Towards a biopsychosocial framework of osteoarthritis of the knee. Disabil Rehabil. 2007;30:54 – 61. 36 Nordeman L, Nilsson B, Moller M, Gunnarsson R. Early access to physical therapy treatment for subacute low back pain in primary health care: a prospective randomised clinical trial. Clin J Pain. 2006; 22:505–511. 37 Hay EM, Foster NE, Thomas E, et al. Effectiveness of community physiotherapy and enhanced pharmacy review for knee pain in people aged over 55 presenting to primary care: pragmatic randomised trial. BMJ. 2006;333:995. 38 McCarthy CJ, Mills PM, Pullen R, et al. Supplementation of a home-based exercise programme with a class-based programme for people with osteoarthritis of the knees: a randomised controlled trial and health economic analysis. Health Technol Assess. 2004;8:1– 61. 39 Jinks C, Ong BN, Richardson J. A mixed methods study to investigate needs assessment for knee pain and disability: population and individual perspectives. BMC Musculoskelet Disord.2007;8:59. 40 Hay E, Dunn K, Hill J, et al. A randomised clinical trial of subgrouping and targeted treatment for low back pain compared with best current care: the STarT Back Trial Study Protocol. BMC Musculoskelet Disord. 2008,9:58 41 ARMA 2004 Standards of Care for People With Osteoarthritis. Available at: http:// www.arma.uk.net/pdfs/oa06.pdf. Accessed June 2009. 42 Keefe FJ, Somers TJ, Martire LM. Psychological interventions and lifestyle modifications for arthritis pain management. Rheum Dis North Am. 2008;34:351–368. 43 Arthritis in Canada: An Ongoing Challenge. Ottowa, Ontario, Canada: Health Canada; 2003. 44 Dziedzic KS, Thomas E, Hill S, et al. The impact of musculoskeletal hand problems in older adults: findings from the North Staffordshire Osteoarthritis Project (NorStOP). Rheumatology. 2007;46:963–967.

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45 Hurley MV, Walsh NE, Mitchell HL, et al. Clinical effectiveness of a rehabilitation program integrating exercise, selfmanagement, and active coping strategies for chronic knee pain: a cluster randomized trial. Arthritis Rheum. 2007;57: 1211–1219. 46 Hurley MV, Walsh NE, Mitchell HL, et al. Economic evaluation of a rehabilitation program integrating exercise, selfmanagement, and active coping strategies for chronic knee pain. Arthritis Rheum. 2007;57:1220 –1229. 47 Fritz JM, Cleland JA, Brennan GP. Does adherence to the guideline recommendation for active treatments improve the quality of care for patients with acute low back pain delivered by physical therapists? Med Care. 2007;45;973–980. 48 Hammond A, Freeman K. The long-term outcomes from a randomized controlled trial of an educational-behavioural joint protection programme for people with rheumatoid arthritis. Clin Rehabil. 2004; 18:520 –528. 49 Stephens B, Gross DP. The influence of a continuum of care model on the rehabilitation of compensation claimants with soft tissue disorders. Spine. 2007;32: 2898 –2904. 50 Keefe FJ, Blumenthal J, Baucom D, et al. Effects of spouse-assisted coping skills training and exercise training in patients with osteoarthritis knee pain: a randomised controlled study. Pain. 2004;110: 539 –549. 51 Pells JJ, Shelby RA, Keefe FJ, et al. Arthritis self-efficacy and self-efficacy for resisting eating: relationship to pain, disability and eating behavior in overweight and obese individuals with osteoarthritis knee pain. Pain. 2008;136:340 –347. 52 Guzman J, Esmail R, Karjalainen K, et al. Multidisciplinary bio-psycho-social rehabilitation for chronic low back pain. Cochrane Database Syst Rev. 2006;2: CD000963. 53 Hay EM, Mullis R, Lewis M, et al. Comparison of physical treatments versus a brief pain-management programme for back pain in primary care: a randomised clinical trial in physiotherapy practice. Lancet. 2005;365:2024 –2030. 54 Lin EH, Katon W, Von Korff M, et al; IMPACT investigators. Effect of improving depression care on pain and functional outcomes among older adults with arthritis: a randomised controlled trial. JAMA. 2003;290:2428 –2429. 55 Bishop A, Foster NE, Thomas E, Hay EM. How does self-reported clinical management of patients with low back pain relate to the attitudes and beliefs of health care practitioners? A survey of UK general practitioners and physiotherapists. Pain. 2008; 135:187–195. 56 Keller A, Hayden J, Bombardier C, van Tulder M. Effect sizes of non-surgical treatments of non-specific low-back pain. Eur Spine J. 2007;16:1776 –1788.

December 2009

Scholarships, Fellowships, and Grants News from the Foundation for Physical Therapy Foundation Thanks Outgoing Members of the SRC

FoundationforPhysicalTherapy.org) under Program Information.

The Board of Trustees and staff of the Foundation for Physical Therapy bid a tremendous thankyou to the 3 outgoing members of the Scientific Review Committee (SRC). Carolynn Patten, PT, PhD, University of Florida; Linda Fetters, PT, PhD, FAPTA, University of Southern California; and Steven Wolf, PT, PhD, FAPTA, FAHA, Emory University, all finish their terms of service on the SRC in December. The Board and the Foundation recognize the many years of dedicated effort and time they have donated to the Foundation’s scholarship and grant programs. The Foundation has been able to confidently award hundreds of thousands of dollars to scientifically sound physical therapy research and education during their tenures, thanks to their reviews.

Foundation Thanks SRC and SAC for Service in 2009

A special thank-you is deservedly extended to outgoing SRC Chair Carolynn Patten for serving since January 2005 and for leading the Foundation through the transition from paper applications to the current online application system. Patten assisted Foundation staff in developing the system format and design and was instrumental in the transition to the online review sessions that the SRC currently uses. With the other SRC members, she tirelessly worked to emphasize the SRC standards and guidelines so that funded grants and scholarships would lead to sound, publishable research. The Foundation will be seeking nominations again in 2010 for skilled reviewers to join the SRC. Criteria for membership are posted on the Foundation’s Web site (www.

The Foundation for Physical Therapy extends a sincere thank-you to the members of the SRC and the Scientific Advisory Committee (SAC) for another year of dedicated service through committee membership. This has been a busy year for both committees. The SRC completed 2 review cycles, including one of the largest pools of applicants for Promotion of Doctoral Studies (PODS) scholarships ever. The SAC was instrumental in developing the Foundation’s latest Request for Proposals. The Foundation relies upon the expertise of these volunteers and deeply appreciates the time dedicated to serve on the 2 committees.

Recent Publications by Foundation-Funded Researchers “Neural Correlates of Impaired Functional Independence in Early Alzheimer’s Disease,” by Vidoni ED, Honea RA, and Burns JM, was published online in the Journal of Alzheimer’s Disease on October 8, 2009. Eric Vidoni, MSPT, PhD, is the 2009 recipient of the New Investigator Fellowship Training Initiative (NIFTI). “Infants Born Preterm Exhibit Different Patterns of Center-of-Pressure Movement Than Infants Born at Full Term,” by Dusing SC, Kyvelidou A, Mercer VS, and Stergiou N, was published online ahead of print in Physical Therapy on October 8, 2009. Stacey Dusing, PT, PhD, won a 2002 Kendall Scholarship and a 2005 PODS II.


Foundation 12.09.indd 1380

“Gait Variability Detects Women in Early Postmenopause With Low Bone Mineral Density,” by Palombaro KM, Hack LM, Mangione KK, Barr AE, Newton RA, Magri F, and Speziale T, was published online ahead of print in Physical Therapy on October 15, 2009. Kerstin Palombaro, PT, PhD, received a 2003 Kendall Scholarship. Ann Barr, PT, DPT, PhD, received NIFTI awards in both 1998 and 1999 and currently serves on the SRC for the Foundation. “Observation of Amounts of Movement Practice Provided During Stroke Rehabilitation,” by Lang CE, Macdonald JR, Reisman DS, Boyd L, Jacobson Kimberley T, Schindler-Ivens SM, Hornby TG, Ross SA, and Scheets PL, appeared in the Archives of Physical Medicine and Rehabilitation (2009;90[10]:1692–1698). Catherine Lang, PT, PhD, received a 1999 PODS I, a 2000 PODS II, and a 2008 Magistro Family Research Grant. Darcy Reisman, PT, PhD, received a 1999 Kendall Scholarship. Lara Boyd, PT, PhD, was awarded a 1998 PODS I and a 2000 PODS

Keep Up With Research News From the Foundation PTJ readers are encouraged to subscribe to the Foundation’s monthly e-Newsletter and FPT Research Alerts. Not only will subscribers receive alerts when the Foundation’s online grant application system is open, they also will be “in the know” about key Foundation events and activities and will be able view the latest researcher profiles. Subscribe at www. FoundationforPhysicalTherapy. org, and click on “Join Our Email List.” December 2009

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Scholarships, Fellowships, and Grants II. Teresa Jacobson Kimberley, PT, PhD, was the recipient of a 2000 PODS I. Sheila Schindler-Ivens, PT, PhD, received a PODS I in 1998 and 1999 and a PODS II in 2000.

Applications Still Being Accepted for PODS I and II Scholarships and NIFTI-HSR The Foundation is still accepting applications for the Promotion of Doctoral Studies (PODS) scholarships and the New Investigator Fellowship Training Initiative– Health Services Research (NIFTI– HSR) award. Please visit the Foundation at www.Foundation forPhysicalTherapy.org for more information and guidelines. Applications will be accepted until noon on January 26, 2010.

Foundation Accepting Applications in 2010 for $300,000 Research Grant The Foundation for Physical Therapy will begin accepting proposals in 2010 for a 2-year, $300,000 award that will focus on the topic “Physical Therapy Exercise Interventions to Reduce Activity Limitations and Improve Community Participation in Older Adults with Multiple Chronic Conditions.” This funding opportunity is intended to support innovative research focused on therapeutic exercise interventions to improve activity and participation in older adults with multiple chronic conditions. The target of this funding mechanism is toward those projects that are considered high-impact, highrisk, and high-reward applications. The Foundation encourages multidisciplinary teams to apply for this funding opportunity.

December 2009

Foundation 12.09.indd 1381

CSM 2010 Events Section Events to Benefit Foundation You are invited to attend 2 events hosted by APTA sections during CSM 2010 in San Diego that will benefit the Foundation. Join your friends and colleagues for a fun-filled evening at the Sports Physical Therapy Section (SPTS) Beach Party Redux at the Hilton San Diego Bayfront Hotel. The evening will include music and dancing to the famed “Beach Toys,” a Beach Boys tribute band who rocked the event on our last visit to San Diego. The everpopular SPTS Silent Auction will once again feature sports memorabilia, gifts, clothing, and equipment for your bidding. Tickets are $25 for members ($10 for students). Purchase tickets by calling APTA Member Services at 800/999-2782, ext 3395, or online at the Foundation’s Web site. Catch the Buzz at the Home Health Section Coffee to benefit the Foundation. Start your morning off with Starbucks coffee before you begin your educational programming. Make a quick stop by the Hilton Bayfront and grab a cup to go, or linger and chat with friends

and colleagues. Foundationfunded researchers will be our special guests. Gentiva Health Service, a Foundation Partner in Research, is sponsoring this event. Tickets are $15 ($5 for students) and can be purchased by calling Member Services or on the Foundation’s Web site. Foundation Forum The Foundation for Physical Therapy will once again host a forum on obtaining Foundation funding at Combined Sections Meeting 2010 in San Diego. “Foundation Funding for Post-Professional Study: Options and Guidelines,” will be held on Thursday, February 18, from 10:30 am to 12:15 pm. The program will include 4 roundtable discussion groups on each Foundation funding program. Each discussion group will be led by a member or two of the SRC. This is a great opportunity to discuss the application process and what reviewers look for in potentially successful applications. This program is once again graciously sponsored by the Section on Research.

[DOI: 10.2522/ptj.2009.89.12.1380]


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Index to Volume 89 incomplete spinal cord injury.] 2009;89:612– 615.

Author Index

Beissner K, Henderson CR Jr, Papaleontiou M, et al. Physical therapists’ use of cognitivebehavioral therapy for older adults with chronic pain: a nationwide survey. 2009;89:456 – 469.

A

Adams SB Jr: See Schuh R Aguilera AJ: See Young IA

Beissner K, Reid MC. Author response to invited commentary. [RE: Physical therapists’ use of cognitivebehavioral therapy for older adults with chronic pain: a nationwide survey.] 2009;89:472– 473.

Allison SC. Letter to the editor. [RE: A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions.] 2009;89:1098 –1099. Altman DG: See Moher D Aoki M: See Muraki T Arbib MA: See Schweighofer N Archer KR, MacKenzie EJ, Bosse MJ, et al. Factors associated with surgeon referral for physical therapy in patients with traumatic lowerextremity injury: results of a national survey of orthopedic trauma surgeons. 2009;89:893–905. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. Author responses to invited commentary and invited e-commentary (online only). [RE: Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury.] 2009;89:1352–1353, e10.

Arletti C: See Costi S Åsenlo ¨ f P, Siljeba¨ck K. The Patient Goal Priority Questionnaire is moderately reproducible in people with persistent musculoskeletal pain. 2009;89:1226 –1234.

B

Barr AE: See Palombaro KM Barr JO. Letter to the editor. [RE: Congratulations on the diabetes special issue!] 2009;89:102.

Beneciuk JM: See George SZ Beneck GJ: See Kulig K Beninato M, Portney LG, Sullivan PE. Author response to invited commentary. [RE: Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke.] 2009;89:827– 828. Beninato M, Portney LG, Sullivan PE. Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. 2009;89:816 – 825.

Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ; for the LEAP Study Group. Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. 2009;89:1337–1349.

Azen S: See Kulig K

Beneciuk JM, Bishop MD, George SZ. Clinical prediction rules for physical therapy interventions: a systematic review. 2009;89:114 –124.

Bialosky JE, Bishop MD, Robinson ME, et al. Spinal manipulative therapy has an immediate effect on thermal pain sensitivity in people with low back pain: a randomized controlled trial. 2009;89:1292–1303.

regarding people who are obese.] 2009;89:1100. Brown R: See Jette DU Bundy AC: See Lin C-WC Burks RT: See Gerber JP Burnett D: See Salbach NM Burnfield JM: See Kulig K

C

Cahalin LP: See Chatham K Campo MA, Weiser S, Koenig KL. Job strain in physical therapists. 2009;89:946 –956. Castillo RC: See Archer KR Cauraugh JH, Summers JJ. Invited commentary. [RE: Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Hammer AM, Lindmark B.] 2009;89:539 –541. Causey JB: See Scott WB Chan L: See Shumway-Cook A Chang CL: See Teulier C Chang S-H: See Mercer VS Charles J. Invited commentary. [RE: Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.] 2009;89:542–544. Charles J, Wolf SL. Invited commentary. [RE: Bound for success: a systematic review of constraintinduced movement therapy in children with cerebral palsy supports improved arm and hand use.] 2009;89:1142–1143.

Bishop MD: See Bialosky JE

Chatham K, Gelder CM, Lines TA, Cahalin LP. Suspected statin-induced respiratory muscle myopathy during long-term inspiratory muscle training in a patient with diaphragmatic paralysis. 2009;89:257–266.

Bishop MD: See George SZ

Chen C-H: See Lin J-H

Black K: See Dunning K

Chen CJ: See Peterson LE

Bond C: See Hendrick P

Chen P-S: See Luo H-J

Bosse MJ: See Archer KR

Chen TC: See Kulig K

Bowman A: See Westcott McCoy S

Chen WJ: See Luo H-J

Bilodeau N: See Haley SM Bishop MD: See Beneciuk JM

Boyd LA: See Siengsukon CF

Chiarello LA: See Palisano RJ

Bayley M: See Salbach NM

Brennan GP: See Cleland JA

Choi SW: See Hart DL

Behrman AL. Invited commentary. [RE: Training of walking skills overground and on the treadmill: case series on individuals with

Brooks GS. Letter to the editor. [RE: Physical therapists’ attitudes, knowledge, and practice approaches

Cibulka MT. Letter to the editor. [RE: Ilial anterior rotation hypermobility in a female collegiate tennis player.] 2009;89:508 –509.

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Number 12

December 2009

Index to Volume 89 Cieza A: See Escorpizo R Ciol MA: See Shumway-Cook A Cleland JA, Fritz JM, Brennan GP, Magel J. Does continuing education improve physical therapists’ effectiveness in treating neck pain? A randomized clinical trial. 2009;89:38 – 47.

D

as a framework to examine the association between falls and clinical assessment tools in people with stroke.] 2009;89:825– 827.

Dallmeijer AJ: See Valent LJM D’Amico R: See Costi S Davis DA: See Salbach NM

F

Collette N: See Jette DU

de Bode S, Fritz SL, Weir-Haynes K, Mathern GW. Constraint-induced movement therapy for individuals after cerebral hemispherectomy: a case series. 2009;89:361–369.

Fabrizio P. Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. 2009;89:351–360.

Cook KF: See Hart DL

de Graaff S: See de Groot JF

Fetters L: See Huang H

Corbetta D. Invited commentary. [RE: Movement variability and the use of nonlinear tools: principles to guide physical therapist practice.] 2009;89:282–284.

de Groot JF, Takken T, de Graaff S, et al. Treadmill testing of children who have spina bifida and are ambulatory: does peak oxygen uptake reflect maximum oxygen uptake? 2009;89:679 – 687.

Finniss DG: See Law RYW

De Sousa M: See Law RYW

Fragala-Pinkham MA: See Haley SM

Dhaher YY: See Lewek MD

Fraher E: See Landry MD

Di Bari M: See Costi S

Frank J: See Horak FB

Dibble LE: See Gerber JP

Freburger JK: See Mercer VS

Dudgeon BJ: See Shumway-Cook A

Friant W: See Jette DU

Dumas HM: See Haley SM

Friedrich M, Hahne J, Wepner F. A controlled examination of medical and psychosocial factors associated with low back pain in combination with widespread musculoskeletal pain. 2009;89:786 – 803.

Cleland JA: See Young IA Clini EM: See Costi S

Costa LOP, Maher CG, Latimer J, et al. Author response to invited commentary. [RE: Motor control exercise produces short-term improvement for chronic low back pain: a randomized, placebocontrolled trial.] 2009;89:1289 –1291. Costa LOP, Maher CG, Latimer J, et al. Motor control exercise produces short-term improvement for chronic low back pain: a randomized, placebo-controlled trial. 2009;89: 1275–1286. Costa LOP, Maher CG, Latimer J, Smeets RJEM. Reproducibility of rehabilitative ultrasound imaging for the measurement of abdominal muscle activity: a systematic review. 2009;89:756 –769. Costi S, Di Bari M, Pillastrini P, et al. Short-term efficacy of upperextremity exercise training in patients with chronic airway obstruction: a systematic review. 2009;89:443– 455. Cousins E, Ward AB, Roffe C, et al. Quantitative measurement of poststroke spasticity and response to treatment with botulinum toxin: a 2-patient case report. 2009;89:688 – 697. Craik RL. Editorial: PT 2009 notes, PTJ welcomes and thanks. 2009;89:626 – 627. Craik RL. Editorial: A responsibility to put “Health Policy in Perspective.” 2009;89:1114 –1115. Crisafulli E: See Costi S Croft PR: See Dziedzic KS Cruz TH: See Lewek MD

December 2009

Davenport TE: See Rundell SD

Duncan E: See Hendrick P Dunning K, Black K, Harrison A, et al. Neuroprosthesis peroneal functional electrical stimulation in the acute inpatient rehabilitation setting: a case series. 2009;89:499 –506.

Fabbri LM: See Costi S

Fiore P: See Santamato A Flanagan SP: See Kulig K Fletcher JP: See Taylor JD Fouad K: See Musselman KE

Frisardi V: See Santamato A

Dusing SC, Kyvelidou A, Mercer VS, Stergiou N. Infants born preterm exhibit different patterns of centerof-pressure movement than infants born at full term. 2009;89: 1354 –1362.

Fritz JM. Invited commentary: [RE: Motor control exercise produces short-term improvement for chronic low back pain: a randomized, placebo-controlled trial.] 2009;89: 1287–1289.

Dziedzic KS, Hill JC, Porcheret M, Croft PR. New models for primary care are needed for osteoarthritis. 2009;89:1371–1378.

Fritz JM: See Cleland JA Fritz SL: See de Bode S Fujii M: See Muraki T

G

E

Gagnon Blodgett M: See Ries JD

Echternach JL: See Ries JD

Gajewski B: See Kluding P

Escorpizo R, Cieza A. Letter to the editor. [RE: Physical therapist management of acute and chronic low back pain using the World Health Organization’s International Classification of Functioning, Disability and Health.] 2009;89:308.

Galantino ML: See Gilchrist LS

Escorpizo R, Cieza A, Stucki G. Invited commentary. [RE: Using the International Classification of Functioning, Disability and Health

Volume 89

Galloway JC. Editorial (online only): “Just the facts, ma’am”: if it were only that simple, Joe. 2009;89:e5– e6. Galloway JC: See Heathcock JC Ge TT: See Kulig K Gelder CM: See Chatham K George SZ, Beneciuk JM, Bishop MD. Author response to letter to the

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Index to Volume 89 editor. [RE: Clinical prediction rules for physical therapy interventions: a systematic review.] 2009;89:394 –395.

Halbert J: See Jette DU

Hart DL, Werneke MW, George SZ, et al. Screening for elevated levels of fear-avoidance beliefs regarding work or physical activities in people receiving outpatient therapy. 2009;89:770 –785.

Hale J: See Huang H

Hart DL: See Wang Y-C

Hale L: See Hendrick P

Harting J, Rutten GMJ, Rutten STJ, Kremers SP. A qualitative application of the Diffusion of Innovations Theory to examine determinants of guideline adherence among physical therapists. 2009;89:221–232.

low motor competence. 2009;89: 1089 –1097. Hagen KB: See Moe RH

George SZ, Valencia C, Zeppieri G Jr, Robinson ME. Development of a selfreport measure of fearful activities for patients with low back pain: the Fear of Daily Activities Questionnaire. 2009;89:969 –979.

Hahne J: See Friedrich M

George SZ: See Beneciuk JM

Haley SM, Fragala-Pinkham MA, Dumas HM, et al. Evaluation of an item bank for a computerized adaptive test of activity in children with cerebral palsy. 2009;89:589 – 600.

George SZ: See Bialosky JE George SZ: See Hart DL Gerber JP, Marcus RL, Dibble LE, et al. Effects of early progressive eccentric exercise on muscle size and function after anterior cruciate ligament reconstruction: a 1-year follow-up study of a randomized clinical trial. 2009;89:51–59. Gilchrist LS, Galantino ML, Wampler M, et al. A framework for assessment in oncology rehabilitation. 2009;89:286 –306.

Hambleton RK: See Haley SM Hammer AM, Lindmark B. Author response to letter to the editor. [RE: Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.] 2009;89:995–997. Hammer AM, Lindmark B. Author responses to invited commentaries. [RE: Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.] 2009;89:541–542, 544 –545.

Goodman C: See Peterson LE Gooskens RHJM: See de Groot JF Gonzalez-Rothi EJ: See Patten C Gordon J: See Kulig K Gorton GE: See Haley SM Grant-Beuttler M, Palisano RJ, Miller DP, et al. Author response to invited e-commentary (online only). [RE: “Gastrocnemius-soleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm.”] 2009;89:e2– e4. Grant-Beuttler M, Palisano RJ, Miller DP, et al. Gastrocnemius-soleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm. 2009;89: 136 –148.

Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. 2009;89:526 –539. Han CE: See Schweighofer N Hancock M, Herbert R, Maher CG. Author response to letter to the editor. [RE: A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions.] 2009;89:1099 –1100.

Harvey LA: See Law RYW Heathcock JC, Galloway JC. Exploring objects with feet advances movement in infants born preterm: a randomized controlled trial. 2009;89:1027–1038. Heathcock JC. Invited e-commentary (online only). [RE: “Gastrocnemiussoleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm.”] 2009;89:e1. Heinonen A: See Valtonen A Helders PJM: See de Groot JF Henderson CR Jr: See Beissner K Hendrick P, Bond C, Duncan E, Hale L. Clinical reasoning in musculoskeletal practice: students’ conceptualizations. 2009;89:430 – 442. Herbert R: See Hancock M Herbert RD: See Costa LOP Herbert RD: See Hancock M Heriza CB: See Grant-Beuttler M Hesch J. Letter to the editor. [RE: Ilial anterior rotation hypermobility in a female collegiate tennis player.] 2009;89:509 –511.

Graves L: See Jette DU

Hancock M, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. 2009;89:698 –704.

Greenfield BH: See Rauscher L

Hancock M: See Stanton TR

Hill JC: See Dziedzic KS

Greis PE: See Gerber JP

Harbourne RT, Stergiou N. Author response to invited commentary. [RE: Movement variability and the use of nonlinear tools: principles to guide physical therapist practice.] 2009;89:284 –285.

Hodges PW: See Costa LOP

Gross MT: See Mercer VS Guilcher SJT: See Salbach NM Gummesson C: See Lundkvist Josenby A

Hidaka E: See Muraki T

Hoffman J: See Shumway-Cook A Hofstaetter SG: See Schuh R Horak FB, Wrisley DM, Frank J. The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. 2009;89:484 – 498.

H

Hack LM: See McGinnis PQ

Harbourne RT, Stergiou N. Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. 2009;89:267–282.

Hack LM: See Palombaro KM

Harris SR: See Westcott McCoy S

Hornby TG: See Lewek MD

Haga M. Physical fitness in children with high motor competence is different from that in children with

Harrison A: See Dunning K

Houdijk H: See Valent LJM

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Volume 89

Horak FB: See King LA Hornby TG: See Kahn JH

Hsieh C-L: See Lin J-H

Number 12

December 2009

Index to Volume 89 Hsieh W-S: See Luo H-J Hsu M-J: See Lin J-H

capsulitis: a retrospective cohort study. 2009;89:419 – 429.

Kong X: See Riddle DL Kremers SP: See Harting J

Huang H, Fetters L, Hale J, McBride A. Author response to invited commentary. [RE: Bound for success: a systematic review of constraintinduced movement therapy in children with cerebral palsy supports improved arm and hand use.] 2009;89:1144.

Jewell DV: See Riddle DL

Kristen K-H: See Schuh R

Johnson MP. Invited commentary. [RE: Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lowerextremity injury.] 2009;89: 1349 –1351.

Kubo M: See Teulier C

Huang H, Fetters L, Hale J, McBride A. Bound for success: a systematic review of constraint-induced movement therapy in children with cerebral palsy supports improved arm and hand use. 2009;89: 1126 –1141.

Judd M: See Salbach NM

Huijbregts MPJ, Teare GF, McCullough C, et al. Standardization of the Continuing Care Activity Measure: a multicenter study to assess reliability, validity, and ability to measure change. 2009;89:546 –555.

K

I

Jull G. Invited commentary. [RE: Does continuing education improve physical therapists’ effectiveness in treating neck pain? A randomized clinical trial.] 2009;89:48 –50.

Kahn JH, Hornby TG. Rapid and longterm adaptations in gait symmetry following unilateral step training in people with hemiparesis. 2009;89:474 – 483. Kang L-J: See Palisano RJ

Israel S: See Dunning K

Karnes EK: See Peterson LE

Iversen MD. Editorial: CARE V series: integrating patient viewpoints into health care practice and research. 2009;89:1266 –1268

Kaufman RR. Author response to invited commentary. [RE: Career factors help predict productivity in scholarship among faculty members in physical therapist education programs.] 2009;89:219 –220.

Iverson C: See Jette DU Izumi T: See Muraki T

Kulig K, Beneck GJ, Selkowitz DM, et al; Physical Therapy Clinical Research Network (PTClinResNet). An intensive, progressive exercise program reduces disability and improves functional performance in patients after single-level lumbar microdiskectomy. 2009;89: 1145–1157. Kulig K, Reischl SF, Pomrantz AB, et al. Nonsurgical management of posterior tibial tendon dysfunction with orthoses and resistive exercise: a randomized controlled trial. 2009;89:26 –37. Kyvelidou A: See Dusing SC

L

Landers M: See Wulf G Landry MD, Ricketts TC, Fraher E, Verrier MC. Physical therapy health human resource ratios: a comparative analysis of the United States and Canada. 2009;89:149 –161. LaStayo PC: See Gerber JP Latimer J: See Costa LOP Latimer J: See Macedo LG

J

Jaglal SB: See Salbach NM

Kaufman RR. Career factors help predict productivity in scholarship among faculty members in physical therapist education programs. 2009;89:204 –216.

Jan MH: See Song CY

Kautz SA: See Patten C

Janssen TW: See Valent LJM

Law RYW, Harvey LA, Nicholas MK, et al. Stretch exercises increase tolerance to stretch in patients with chronic musculoskeletal pain: a randomized controlled trial. 2009;89:1016 –1026.

Kay TM: See Huijbregts MPJ

Jarnlo GB: See Lundkvist Josenby A

LEAP Study Group: See Archer KR

Kern RW: See Ojha HA

Jeng S-F: See Luo H-J

Leggin BG: See Santamato A

Khan H: See Sack S

Jennings MD: See Costa LOP

Khoo LT: See Kulig K

Jette DU, Brown R, Collette N, et al. Physical therapists’ management of patients in the acute care setting: an observational study. 2009;89: 1158 –1181.

Kigin C. A systems view of physical therapy care: shifting to a new paradigm for the profession. 2009;89:1117–1119.

Lewek MD, Cruz TH, Moore JL, et al. Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. 2009;89:829 – 839.

Jette DU, Halbert J, Iverson C, et al. Use of standardized outcome measures in physical therapist practice: perceptions and applications. 2009;89:125–135. Jewell DV, Riddle DL, Thacker LR. Interventions associated with an increased or decreased likelihood of pain reduction and improved function in patients with adhesive

December 2009

King LA, Horak FB. Delaying mobility disability in people with Parkinson disease using a sensorimotor ability exercise program. 2009;89:384 –393. Kjeken I: See Moe RH

Lewthwaite R: See Wulf G Liberati A: See Moher D Lin C-HJ: See Ojha HA

Kluding P, Gajewski B. Lowerextremeity strength differences predict activity limitations in people with chronic stroke. 2009;89:73– 81.

Lin C-WC, Moseley AM, Refshauge KM, Bundy AC. The Lower Extremity Functional Scale has good clinimetric properties in people with ankle fracture. 2009;89:580 –588.

Koenig KL: See Campo MA

Lin DH: See Song CY

Volume 89

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Index to Volume 89 Lin J-H, Hsu M-J, Sheu C-F, et al. Psychometric comparisons of 4 measures for assessing upperextremity function in people with stroke. 2009;89:840 – 850.

McAuley JH: See Costa LOP

Moore JL: See Lewek MD

McAuley JH: See Macedo LG

Morris GS: See Gilchrist LS

McBride A: See Huang H.

Lin K-H: See Luo H-J

McCullough C: See Huijbregts MPJ

Lin R-T: See Lin J-H

McEwen SE: See Huijbregts MPJ

Morris ME. Invited commentary. [RE: External focus instructions reduce postural instability in individuals with Parkinson disease.] 2009;89:169 –170.

Lin YF: See Song CY

McGinnis PQ, Hack LM, Nixon-Cave K, Michlovitz SL. Factors that influence the clinical decision making of physical therapists in choosing a balance assessment approach. 2009;89:233–247.

McBride K: See Dunning K

Lindmark B: See Hammer AM Lines TA: See Chatham K Little VL: See Patten C Lu T-W: See Luo H-J

Megens AM: See Westcott McCoy S

Lundkvist Josenby A, Jarnlo GB, Gummesson C, Nordmark E. Longitudinal construct validity of the GMFM-88 total score and goal total score and the GMFM-66 score in a 5-year follow-up study. 2009;89: 342–350.

Mercer VS, Freburger JK, Chang S-H, Purser JL. Measurement of paretic– lower-extremity loading and weight transfer after stroke. 2009;89:653– 664. 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. 2009;89:1061–1071.

Luo H-J, Chen P-S, Hsieh W-S, et al. Associations of supported treadmill stepping with walking attainment in preterm and full-term infants. 2009;89:1215–1225.

Mercer VS, Gross MT, Sharma S, Weeks E. Comparison of gluteus medius muscle electromyographic activity during forward and lateral step-up exercises in older adults. 2009;89:1205–1214.

M

Macedo LG, Maher CG, Latimer J, McAuley JH. Motor control exercise for persistent, nonspecific low back pain: a systematic review. 2009;89:9 –25.

Mercer VS: See Dusing SC Miceli E: See Jette DU

Moseley AM: See Lin C-WC Mueller MJ. Editor response to letter to the editor. [RE: Congratulations on the diabetes special issue!] 2009;89:102. Muraki T, Aoki M, Izumi T, et al. Lengthening of the pectoralis minor muscle during passive shoulder motions and stretching techniques: a cadaveric biomechanical study. 2009;89:333–341. Murazko K: See Teulier C Musselman KE, Fouad K, Misiaszek JE, Yang JF. Author response to invited commentary. [RE: Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury.] 2009;89:615– 616. Musselman KE, Fouad K, Misiaszek JE, Yang JF. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. 2009;89:601– 611.

Michener LA: See Young IA Michlovitz SL: See McGinnis PQ

MacKenzie EJ: See Archer KR

Miller DP: See Grant-Beuttler M

Magel J: See Cleland JA

N

Mioduski JE: See Hart DL

Ness KK: See Gilchrist LS

Mioduski JE: See Wang Y-C

Newton RA: See Palombaro KM

Misiaszek JE: See Musselman KE

Ni P: See Haley SM

Miyamoto S: See Muraki T

Nicholas MK: See Law RYW Nixon-Cave K: See McGinnis PQ

Mairella KK: See Sack S

Moe RH, Kjeken I, Uhlig T, Hagen KB. There is inadequate evidence to determine the effectiveness of nonpharmacological and nonsurgical interventions for hand osteoarthritis: an overview of high-quality systematic reviews. 2009;89:1363–1370.

Mais-Requejo S: See Kulig K

Moerchen V: See Teulier C

Mangione KK: See Palombaro KM

Ojha HA, Kern RW, Lin C-HJ, Winstein CJ. Age affects the attentional demands of stair ambulation: evidence from a dual-task approach. 2009;89:1080 –1088.

Mathern GW: See de Bode S

Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Reprint— Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement. [Reprinted from Ann Intern Med. July 2009.] 2009;89:873– 880.

Matheson JW: See Hart DL

Montpetit K: See Haley SM

Maggs J: See Palisano RJ Magri F: See Palombaro KM Maher C. Editorial: PRISMA: helping to deliver information that physical therapists need. 2009;89:870 – 872. Maher CG: See Costa LOP Maher CG: See Hancock M Maher CG: See Macedo LG Maher CG: See Stanton TR

Marchese VG: See Gilchrist LS Marchetti G: See Schreiber J Marcus RL: See Gerber JP Marshall TL: See Scott WB

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Number 12

Nof L: See Ries JD Nordmark E: See Lundkvist Josenby A

O

Oeffinger D: See Palisano RJ

Olkhovskaya Y: See Beissner K Orlin M: See Palisano RJ Osmotherly PG: See Walmsley S Otten I: See Huijbregts MPJ

December 2009

Index to Volume 89

P

Palisano RJ, Kang L-J, Chiarello LA, et al. Social and community participation of children and youth with cerebral palsy is associated with age and gross motor function classification. 2009;89:1304 –1314. Palisano RJ: See Grant-Beuttler M Palombaro KM, Hack LM, Mangione KK, et al. Gait variability detects women in early postmenopause with low bone mineral density. 2009;89:1315–1326. Pandyan AD: See Cousins E Panza F: See Santamato A Papaleontiou M: See Beissner K Patten C, Gonzalez-Rothi EJ, Little VL, Kautz SA. Invited e-commentary (online only). [RE: “Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial”] 2009;89:e7– e8. Pearson S: See Riddle DL Pechak CM, Thompson M. A conceptual model of optimal international service-learning and its application to global health initiatives in rehabilitation. 2009;89:1192–1204. Peterson LE, Goodman C, Karnes EK, et al. Assessment of the quality of cost analysis literature in physical therapy. 2009;89:733–755. Physical Therapy Clinical Research Network (PTClinResNet): See Kulig K

Poulter DC. Letter to the editor. [RE: Ilial anterior rotation hypermobility in a female collegiate tennis player.] 2009;89:507–508. Powers CM: See Kulig K Po ¨ yho ¨ nen T: See Valtonen A The PRISMA Group: See Moher D Provident I: See Schreiber J Purser JL: See Mercer VS

R

Rutten STJ: See Harting J

S

Radler DR: See Sack S Ranieri M: See Santamato A Rappolt S: See Salbach NM Rauscher L, Greenfield BH. Advancements in contemporary physical therapy research: use of mixed methods designs. 2009;89: 91–100. Reddien Wagner B: See Grant-Beuttler M Refshauge KM: See Costa LOP Refshauge KM: See Lin C-WC Reid MC: See Beissner K Reischl SF: See Kulig K Ricketts TC: See Landry MD Riddle DL, Utzman RR, Jewell DV, et al. Academic difficulty and program-level variables predict performance on the National Physical Therapy Examination for licensure: a population-based cohort study. 2009;89:1182–1191. Riddle DL: See Jewell DV

Pomrantz AB: See Kulig K Popovich JM Jr: See Kulig K

Riley LH III: See Archer KR

Poppert EM: See Kulig K

Rimington LD: See Cousins E

Porcheret M: See Dziedzic KS

Rivett DA: See Walmsley S

Portney LG. Invited commentary. [RE: Career factors help predict productivity in scholarship among faculty members in physical therapist education programs.] 2009;89: 216 –219.

Robinson ME: See Bialosky JE

Pillastrini P: See Costi S Pollak AN: See Archer KR

Portney LG: See Beninato M Post MWM: See Valent LJM

December 2009

Rundell SD, Davenport TE, Wagner T. Physical therapist management of acute and chronic low back pain using the World Health Organization’s International Classification of Functioning, Disability and Health. 2009;89:82–90. Rutten GMJ: See Harting J

Ries JD, Echternach JL, Nof L, Gagnon Blodgett M. Test-retest reliability and minimal detectable change scores for the Timed “Up & Go” Test, the SixMinute Walk Test, and gait speed in people with Alzheimer disease. 2009;89:569 –579.

Pichler F: See Schuh R

Health Organization’s International Classification of Functioning, Disability and Health.] 2009;89: 309 –310.

Sack S, Radler DR, Mairella KK, et al. Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese. 2009;89:804 – 815. Sakellariou D: See Sengupta S Salbach NM, Guilcher SJT, Jaglal SB, Davis DA. Factors influencing information seeking by physical therapists providing stroke management. 2009;89:1039 –1050. Salbach NM, Veinot P, Rappolt S, et al. Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. 2009;89:556 –568. Samudrala S: See Kulig K Sanders K: See Westcott McCoy S Santamato A, Solfrizzi V, Panza F, et al. Short-term effects of highintensity laser therapy versus ultrasound therapy in the treatment of people with subacromial impingement syndrome: a randomized clinical trial. 2009;89:643– 652. Scheidt RA: See Stoeckmann TM Scherer MR, Schubert MC. Traumatic brain injury and vestibular pathology as a comorbidity after blast exposure. 2009;89:980 –992. Schreiber J, Stern P, Marchetti G, Provident I. Strategies to promote evidence-based practice in pediatric physical therapy: a formative evaluation pilot project. 2009;89: 918 –933.

Robinson ME: See George SZ Roffe C: See Cousins E Roth HR: See Lewek MD Rundell SD, Davenport TE, Wagner T. Author response to letter to the editor. [RE: Physical therapist management of acute and chronic low back pain using the World

Volume 89

Schubert MC: See Scherer MR Schuh R, Hofstaetter SG, Adams SB Jr, et al. Rehabilitation after hallux valgus surgery: importance of physical therapy to restore weight

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Index to Volume 89 bearing of the first ray during the stance phase. 2009;89:934 –945. Schwartz JA: See Peterson LE Schweighofer N, Han CE, Wolf SL, et al. A functional threshold for long-term use of hand and arm function can be determined: predictions from a computational model and supporting data from the Extremity ConstraintInduced Therapy Evaluation (EXCITE) trial. 2009;89:1327–1336. Scott WB, Causey JB, Marshall TL. Comparison of maximum tolerated muscle torques produced by 2 pulse durations. 2009;89:851– 857.

Shah P: See Jette DU Shamie AN: See Kulig K Sharma S: See Mercer VS Sheu C-F: See Lin J-H Shewokis PA: See Grant-Beuttler M Shields RK. Editorial: Above board: clear bylaws support the research mission of the Foundation for Physical Therapy. 2009;89:1010 –1012. Shumway-Cook A, Ciol MA, Hoffman J, et al. Falls in the Medicare population: incidence, associated factors, and impact on health care. 2009;89:324 –332.

Smith-Blockley J: See Westcott McCoy S

Volume 89

Tonkin L: See Law RYW Touger-Decker R: See Sack S Trnka H-J: See Schuh R

Stern P: See Schreiber J

Tucker CA: See Haley SM

Stoeckmann TM, Sullivan KJ, Scheidt RA. Elastic, viscous, and mass load effects on poststroke muscle recruitment and co-contraction during reaching: a pilot study. 2009;89:665– 678.

Turk DC: See Sluka KA

U

Uhlig T: See Moe RH

Stout NL. Cancer prevention in physical therapist practice. 2009;89:1119 –1122.

Ulrich BD: See Teulier C

Stratford PW: See Wang Y-C

V

Taylor JD, Fletcher JP, Tiarks J. Impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes: a randomized clinical trial. 2009;89:884 – 892.

Smith RW: See Kulig K

Tondi G: See Santamato A

Stergiou N: See Harbourne RT

Takken T: See de Groot JF

Smith BA: See Teulier C

Tiarks J: See Taylor JD

Stergiou N: See Dusing SC

T

Smeets RJEM: See Costa LOP

Physical Therapy

Tomey KM, Sowers MR. Assessment of physical functioning: a conceptual model encompassing environmental factors and individual compensation strategies. 2009;89:705–714.

Summers JJ: See Cauraugh JH

Sluka KA, Turk DC. Invited commentary. [RE: Physical therapists’ use of cognitivebehavioral therapy for older adults with chronic pain: a nationwide survey.] 2009;89:470 – 472.

f

To ¨ llner T: See Wulf G

Speziale T: See Palombaro KM,

Sullivan KJ: See Stoeckmann TM

Slootman HJ: See Valent LJM

1388

Sowers MR: See Tomey KM

Sullivan PE: See Beninato M

Sipila¨ S: See Valtonen A

Snyder-Mackler L. Invited e-commentary (online only).

Thorpe DL. Letter to the editor. [RE: Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial.] 2009;89:1253.

Stucki G: See Escorpizo R

Siljeba¨ck K: See Åsenlo ¨f P

Thompson M: See Pechak CM

Song CY, Lin YF, Wei TC, et al. Surplus value of hip adduction in leg-press exercise in patients with patellofemoral pain syndrome: a randomized controlled trial. 2009;89:409 – 418.

Streiner D: See Huijbregts MPJ

Siengsukon CF, Boyd LA. Does sleep promote motor learning? Implications for physical rehabilitation. 2009;89:370 –383.

Thacker LR: See Jewell DV Thordarson DB: See Kulig K

Stanton TR, Maher CG, Hancock M. Letter to the editor. [RE: Clinical prediction rules for physical therapy interventions: a systematic review.] 2009;89:394.

Sengupta S, Sakellariou D. Letter to the editor. [RE: Sexuality and health care: are we training physical therapy professionals to address their clients’ sexuality needs?] 2009;89:101–102.

on a motorized treadmill. 2009;89:60 –72.

Solfrizzi V: See Santamato A

Spoonamore MJ: See Kulig K

Selkowitz DM: See Kulig K

Snyder AR: See Young IA

[RE: Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lowerextremity injury.] 2009;89:e9.

Teare GF: See Huijbregts MPJ Tetzlaff J: See Moher D Teulier C, Smith BA, Kubo M, et al. Stepping responses of infants with myelomeningocele when supported

Number 12

Utzman RR: See Riddle DL

Valencia C: See George SZ Valent LJM, Dallmeijer AJ, Houdijk H, et al. Effects of hand cycle training on physical capacity in individuals with tetraplegia: a clinical trial. 2009;89:1051–1060. Valtonen A, Po ¨ yho ¨ nen T, Heinonen A, Sipila¨ S. Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. 2009;89:1072–1079. van der Woude LH: See Valent LJM Vanhees L: See de Groot JF VanWye WR. Patient screening by a physical therapist for nonmusculoskeletal hip pain. 2009;89:248 –256. Vaughn HT. Author response to letters to the editor. [RE: Ilial anterior rotation hypermobility in a female collegiate tennis player.] 2009;89:511–512.

December 2009

Index to Volume 89 Veinot P: See Salbach NM

Wolf SL: See Schweighofer N

Verrier MC: See Landry MD

Wong SKC: See Huijbregts MPJ

● Invited e-commentary (online only). Patten C, Gonzalez-Rothi EJ, Little VL, Kautz SA. 2009; 89:e7– e8.

Wrisley DM: See Horak FB

W

Wagner T: See Rundell SD Walmsley S, Rivett DA, Osmotherly PG. Adhesive capsulitis: establishing consensus on clinical identifiers for stage 1 using the Delphi technique. 2009;89:906 –917. Wampler M: See Gilchrist LS Wang JC: See Kulig K Wang Y-C, Hart DL, Stratford PW, Mioduski JE. Clinical interpretation of a Lower-Extremity Functional Scale– derived computerized adaptive test. 2009;89:957–968. Wang Y-C: See Hart DL

Wu T-S: See Lin J-H Wulf G, Landers M, Lewthwaite R, To ¨ llner T. External focus instructions reduce postural instability in individuals with Parkinson disease. 2009;89:162–168. Wulf G, Lewthwaite R, Landers M, To ¨ llner T. Author response to invited commentary. [RE: External focus instructions reduce postural instability in individuals with Parkinson disease.] 2009;89:170 –172.

Y

Yamada KA: See Kulig K Yang JF: See Musselman KE

Ward AR. Electrical stimulation using kiloherz-frequency alternating current. 2009;89:181–190.

Yen TY: See Song CY

Ward RS. 2009 APTA Presidential Address: We must see the possibilities. 2009;89:1250 –1252.

Young IA, Michener LA, Cleland JA, et al. Author response to letter to the editor. [RE: Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial.] 2009;89:1253.

Weeks E: See Mercer VS Wei TC: See Song CY Weir-Haynes K: See de Bode S Weiser S: See Campo MA Wepner F: See Friedrich M Werneke MW: See Hart DL Westcott McCoy S, Bowman A, SmithBlockley J, et al. Harris Infant Neuromotor Test: comparison of US and Canadian normative data and examination of concurrent validity with the Ages and Stages Questionnaire. 2009;89:173–180. Wigglesworth J: See Beissner K Winstein CJ. 40th Mary McMillan Lecture: The best we can be is yet to come. 2009;89:1236 –1249.

Yorkston K: See Shumway-Cook A

Young IA, Michener LA, Cleland JA, et al. Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial. 2009;89:632– 642.

Zeppieri G Jr: See George SZ

Subject Index

Osteoarthritis Editorial: CARE V series: integrating patient viewpoints into health care practice and research. Iversen MD. 2009;89:1266 –1268. New models for primary care are needed for osteoarthritis. Dziedzic KS, Hill JC, Porcheret M, Croft PR. 2009;89:1371–1378. There is inadequate evidence to determine the effectiveness of nonpharmacological and nonsurgical interventions for hand osteoarthritis: an overview of highquality systematic reviews. Moe RH, Kjeken I, Uhlig T, Hagen KB. 2009;89:1363–1370.

External focus instructions reduce postural instability in individuals with Parkinson disease. Wulf G, Landers M, Lewthwaite R, To ¨ llner T. 2009;89:162–168.

Winstein CJ: See Ojha HA

Ambulation Aids

Winstein CJ: See Schweighofer N

General Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. Lewek MD, Cruz TH, Moore JL, et al. 2009;89:829 – 839.

December 2009

2009 APTA Presidential Address: We must see the possibilities. Ward RS. 2009;89:1250 –1252.

Balance The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. Horak FB, Wrisley DM, Frank J. 2009;89:484 – 498.

Zeppieri G Jr: See Bialosky JE

A

Wolf SL: See Charles J

Membership Statistics. 2009;89:618.

B

Z

Winstein CJ: See Kulig K

Wolf SL. Letter to the editor. [RE: Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.] 2009;89:993–995.

40th Mary McMillan Lecture: The best we can be is yet to come. Winstein CJ. 2009;89:1236 –1249.

Arthritis

Ward AB: See Cousins E

Watson K: See Haley SM

American Physical Therapy Association Editorial: Above board: clear bylaws support the research mission of the Foundation for Physical Therapy. Shields RK. 2009;89:1010 –1012.

Volume 89

● Invited commentary. Morris ME. 2009;89:169 –170. ● Author response. Wulf G, Lewthwaite R, Landers M, To ¨ llner T. 2009;89:170 –172. Factors that influence the clinical decision making of physical therapists in choosing a balance assessment approach. McGinnis PQ,

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Index to Volume 89 Hack LM, Nixon-Cave K, Michlovitz SL. 2009;89:233–247.

● Letter to the editor. Wolf SL. 2009;89:993–995.

Gait variability detects women in early postmenopause with low bone mineral density. Palombaro KM, Hack LM, Mangione KK, et al. 2009;89:1315–1326.

● Author response. Hammer AM, Lindmark B. 2009;89:995–997. Elastic, viscous, and mass load effects on poststroke muscle recruitment and co-contraction during reaching: a pilot study. Stoeckmann TM, Sullivan KJ, Scheidt RA. 2009;89:665– 678.

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

Factors influencing information seeking by physical therapists providing stroke management. Salbach NM, Guilcher SJT, Jaglal SB, Davis DA. 2009;89:1039 –1050.

Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Beninato M, Portney LG, Sullivan PE. 2009;89:816 – 825.

Lower-extremity strength differences predict activity limitations in people with chronic stroke. Kluding P, Gajewski B. 2009;89:73– 81. Measurement of paretic–lowerextremity loading and weight transfer after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:653– 664.

● Invited commentary. Escorpizo R, Cieza A, Stucki G. 2009;89: 825– 827. ● Author response. Beninato M, Portney LG, Sullivan PE. 2009; 89:827– 828.

Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. Salbach NM, Veinot P, Rappolt S, et al. 2009;89:556 –568.

C Cardiac General Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. Lewek MD, Cruz TH, Moore JL, et al. 2009;89:829 – 839. ● Invited e-commentary (online only). Patten C, Gonzalez-Rothi EJ, Little VL, Kautz SA. 2009;89: e7– e8. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Hammer AM, Lindmark B. 2009;89:526 –539. ● Invited commentary. Cauraugh JH, Summers JJ. 2009;89:539 –541. ● Author response. Hammer AM, Lindmark B. 2009;89:541–542. ● Invited commentary. Charles J. 2009;89:542–544. ● Author response. Hammer AM, Lindmark B. 2009;89:544 –545.

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Psychometric comparisons of 4 measures for assessing upperextremity function in people with stroke. Lin J-H, Hsu M-J, Sheu C-F, et al. 2009;89:840 – 850. Step Test scores are related to measures of activity and participation in the first 6 months after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:1061–1071. Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Beninato M, Portney LG, Sullivan PE. 2009;89:816 – 825. ● Invited commentary. Escorpizo R, Cieza A, Stucki G. 2009;89: 825– 827. ● Author response. Beninato M, Portney LG, Sullivan PE. 2009;89: 827– 828. Cerebral Palsy Evaluation Evaluation of an item bank for a computerized adaptive test of

Number 12

activity in children with cerebral palsy. Haley SM, Fragala-Pinkham MA, Dumas HM, et al. 2009;89: 589 – 600. Social and community participation of children and youth with cerebral palsy is associated with age and gross motor function classification. Palisano RJ, Kang L-J, Chiarello LA, et al. 2009;89:1304 –1314. Treatment Bound for success: a systematic review of constraint-induced movement therapy in children with cerebral palsy supports improved arm and hand use. Huang H, Fetters L, Hale J, McBride A. 2009;89: 1126 –1141. ● Invited commentary. Charles J, Wolf SL. 2009;89:1142–1143. ● Author response. Huang H, Fetters L, Hale J, McBride A. 2009;89:1144.

D Decision Making Factors that influence the clinical decision making of physical therapists in choosing a balance assessment approach. McGinnis PQ, Hack LM, Nixon-Cave K, Michlovitz SL. 2009;89:233–247. Diabetes [Comparison of combined aerobic and high-force eccentric resistance exercise with aerobic exercise only for people with type 2 diabetes mellitus. Marcus RL, Smith S, Morrell G, et al. 2008;88:1345–1354.] ● Correction. 2009;89:103. [Effect of weight-bearing activity on foot ulcer incidence in people with diabetic peripheral neuropathy: Feet First randomized controlled trial. LeMaster JW, Mueller MJ, Reiber GE, et al. 2008;88:1385–1398.] ● Correction. 2009;89:1103. Impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes: a randomized clinical trial. Taylor JD, Fletcher JP, Tiarks J. 2009;89: 884 – 892.

December 2009

Index to Volume 89 Letter to the editor. [RE: Congratulations on the diabetes special issue!] Barr JO. 2009;89:102. ● Editor response. Mueller MJ. 2009;89:102. Diagnosis Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ; for the LEAP Study Group. 2009;89:1337–1349. ● Invited commentary. Johnson MP. 2009;89:1349 –1351. ● Author response. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:1352–1353. ● Invited e-commentary (online only). Snyder-Mackler L. 2009;89:e9. ● Author response (online only). Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:e10. Patient screening by a physical therapist for nonmusculoskeletal hip pain. VanWye WR. 2009;89: 248 –256.

E Editorials Editorial: Above board: clear bylaws support the research mission of the Foundation for Physical Therapy. Shields RK. 2009;89:1010 –1012. Editorial: CARE V series: integrating patient viewpoints into health care practice and research. Iversen MD. 2009;89:1266 –1268. Editorial: PRISMA: helping to deliver information that physical therapists need. Maher C. 2009;89:870 – 872. Editorial: PT 2009 notes, PTJ welcomes and thanks. Craik RL. 2009;89:626 – 627. Editorial: A responsibility to put “Health Policy in Perspective.” Craik RL. 2009;89:1114 –1115. Editorial (online only): “Just the facts, ma’am”: if it were only that simple, Joe. Galloway JC. 2009;89:e5– e6.

Education: Physical Therapist

Equipment

Clinical Education Clinical reasoning in musculoskeletal practice: students’ conceptualizations. Hendrick P, Bond C, Duncan E, Hale L. 2009;89:430 – 442. Continuing Education Does continuing education improve physical therapists’ effectiveness in treating neck pain? A randomized clinical trial. Cleland JA, Fritz JM, Brennan GP, Magel J. 2009;89: 38 – 47.

General Effects of hand cycle training on physical capacity in individuals with tetraplegia: a clinical trial. Valent LJM, Dallmeijer AJ, Houdijk H, et al. 2009;89:1051–1060.

● Invited commentary. Jull G. 2009; 89:48 –50. Faculty Members Career factors help predict productivity in scholarship among faculty members in physical therapist education programs. Kaufman RR. 2009;89:204 –216.

Evidence-Based Practice Editorial: PRISMA: helping to deliver information that physical therapists need. Maher C. 2009;89:870 – 872.

● Invited commentary. Portney LG. 2009;89:216 –219. ● Author response. Kaufman RR. 2009;89:219 –220. General Academic difficulty and programlevel variables predict performance on the National Physical Therapy Examination for licensure: a population-based cohort study. Riddle DL, Utzman RR, Jewell DV, et al. 2009;89:1182–1191. Electromyography Comparison of gluteus medius muscle electromyographic activity during forward and lateral step-up exercises in older adults. Mercer VS, Gross MT, Sharma S, Weeks E. 2009;89:1205–1214. Electrotherapy Electrical Stimulation Comparison of maximum tolerated muscle torques produced by 2 pulse durations. Scott WB, Causey JB, Marshall TL. 2009;89:851– 857. Electrical stimulation using kiloherzfrequency alternating current. Ward AR. 2009;89:181–190. Neuroprosthesis peroneal functional electrical stimulation in the acute inpatient rehabilitation setting: a case series. Dunning K, Black K, Harrison A, et al. 2009;89:499 –506.

Stepping responses of infants with myelomeningocele when supported on a motorized treadmill. Teulier C, Smith BA, Kubo M, et al. 2009;89:60 –72.

A qualitative application of the Diffusion of Innovations Theory to examine determinants of guideline adherence among physical therapists. Harting J, Rutten GMJ, Rutten STJ, Kremers SP. 2009;89:221–232. Reprint—Preferred Reporting Items for Systematic Reviews and MetaAnalyses: the PRISMA Statement. [Reprinted from Ann Intern Med. July 2009.] Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. 2009;89:873– 880. Strategies to promote evidencebased practice in pediatric physical therapy: a formative evaluation pilot project. Schreiber J, Stern P, Marchetti G, Provident I. 2009;89:918 –933. Exercise General [Comparison of combined aerobic and high-force eccentric resistance exercise with aerobic exercise only for people with type 2 diabetes mellitus. Marcus RL, Smith S, Morrell G, et al. 2008;88:1345–1354.] ● Correction. 2009;89:103. Comparison of gluteus medius muscle electromyographic activity during forward and lateral step-up exercises in older adults. Mercer VS, Gross MT, Sharma S, Weeks E. 2009;89:1205–1214. Delaying mobility disability in people with Parkinson disease using a sensorimotor ability exercise program. King LA, Horak FB. 2009;89:384 –393. Effects of early progressive eccentric exercise on muscle size

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Index to Volume 89 and function after anterior cruciate ligament reconstruction: a 1-year follow-up study of a randomized clinical trial. Gerber JP, Marcus RL, Dibble LE, et al. 2009;89:51–59. Effects of hand cycle training on physical capacity in individuals with tetraplegia: a clinical trial. Valent LJM, Dallmeijer AJ, Houdijk H,et al. 2009;89:1051–1060. An intensive, progressive exercise program reduces disability and improves functional performance in patients after single-level lumbar microdiskectomy. Kulig K, Beneck GJ, Selkowitz DM, et al; Physical Therapy Clinical Research Network (PTClinResNet). 2009;89:1145–1157. Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial. Young IA, Michener LA, Cleland JA, et al. 2009;89:632– 642. ● Letter to the editor. Thorpe DL. 2009;89:1253. ● Author response. Young IA, Michener LA, Cleland JA, et al. 2009;89:1253. ● Correction. 2009;89:1254 –1255. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Costa LOP, Maher CG, Latimer J, et al. 2009; 89:1275–1286.

● Author response. Costa LOP, Maher CG, Latimer J, et al. 2009; 89:1289 –1291. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Macedo LG, Maher CG, Latimer J, McAuley JH. 2009;89:9 –25.

Short-term efficacy of upperextremity exercise training in patients with chronic airway obstruction: a systematic review. Costi S, Di Bari M, Pillastrini P, et al. 2009;89:443– 455.

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Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89: 601– 611. ● Invited commentary. Behrman AL. 2009;89:612– 615. ● Author response. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89:615– 616.

G Geriatrics Age affects the attentional demands of stair ambulation: evidence from a dual-task approach. Ojha HA, Kern RW, Lin C-HJ, Winstein CJ. 2009;89: 1080 –1088.

Foundation for Physical Therapy Editorial: Above board: clear bylaws support the research mission of the Foundation for Physical Therapy. Shields RK. 2009;89:1010 –1012.

Comparison of gluteus medius muscle electromyographic activity during forward and lateral step-up exercises in older adults. Mercer VS, Gross MT, Sharma S, Weeks E. 2009;89:1205–1214.

Scholarships, Fellowships, and Grants. 2009;89:105–106, 191–192, 311, 397–398, 513–514, 617, 715– 716, 859 – 860, 1001–1002, 1104 – 1105, 1256 –1257, 1380 –1381.

Falls in the Medicare population: incidence, associated factors, and impact on health care. ShumwayCook A, Ciol MA, Hoffman J, et al. 2009;89:324 –332.

● Correction. 2009;89:1103.

Nonsurgical management of posterior tibial tendon dysfunction with orthoses and resistive exercise: a randomized controlled trial. Kulig K, Reischl SF, Pomrantz AB, et al. 2009;89:26 –37.

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Surplus value of hip adduction in leg-press exercise in patients with patellofemoral pain syndrome: a randomized controlled trial. Song CY, Lin YF, Wei TC, et al. 2009;89:409 – 418.

Functional Training and Activities [Effect of weight-bearing activity on foot ulcer incidence in people with diabetic peripheral neuropathy: Feet First randomized controlled trial. LeMaster JW, Mueller MJ, Reiber GE, et al. 2008;88:1385–1398.]

● Invited commentary. Fritz JM. 2009;89:1287–1289.

Stretch exercises increase tolerance to stretch in patients with chronic musculoskeletal pain: a randomized

controlled trial. Law RYW, Harvey LA, Nicholas MK, et al. 2009;89: 1016 –1026. Strengthening Impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes: a randomized clinical trial. Taylor JD, Fletcher JP, Tiarks J. 2009;89: 884 – 892.

Interventions associated with an increased or decreased likelihood of pain reduction and improved function in patients with adhesive capsulitis: a retrospective cohort study. Jewell DV, Riddle DL, Thacker LR. 2009;89:419 – 429. Lower-extremity strength differences predict activity limitations in people with chronic stroke. Kluding P, Gajewski B. 2009;89:73– 81. Surplus value of hip adduction in leg-press exercise in patients with patellofemoral pain syndrome: a randomized controlled trial. Song CY, Lin YF, Wei TC, et al. 2009;89:409 – 418.

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Physical therapists’ use of cognitivebehavioral therapy for older adults with chronic pain: a nationwide survey. Beissner K, Henderson CR Jr, Papaleontiou M, et al. 2009;89: 456 – 469. ● Invited commentary. Sluka KA, Turk DC. 2009;89:470 – 472. ● Author response. Beissner K, Reid MC. 2009;89:472– 473. Standardization of the Continuing Care Activity Measure: a multicenter study to assess reliability, validity, and ability to measure change. Huijbregts MPJ, Teare GF, McCullough C, et al. 2009;89: 546 –555.

H Head Injury Traumatic brain injury and vestibular pathology as a comorbidity after blast exposure. Scherer MR, Schubert MC. 2009;89:980 –992.

December 2009

Index to Volume 89 Health Care Cancer prevention in physical therapist practice. Stout NL. 2009; 89:1119 –1122. A conceptual model of optimal international service-learning and its application to global health initiatives in rehabilitation. Pechak CM, Thompson M. 2009;89: 1192–1204. Editorial: CARE V series: integrating patient viewpoints into health care practice and research. Iversen MD. 2009;89:1266 –1268. Editorial: A responsibility to put “Health Policy in Perspective.” Craik RL. 2009;89:1114 –1115. Falls in the Medicare population: incidence, associated factors, and impact on health care. ShumwayCook A, Ciol MA, Hoffman J, et al. 2009;89:324 –332. Letter to the editor. [RE: Sexuality and health care: are we training physical therapy professionals to address their clients’ sexuality needs?] Sengupta S, Sakellariou D. 2009;89:101–102. Physical therapy health human resource ratios: a comparative analysis of the United States and Canada. Landry MD, Ricketts TC, Fraher E, Verrier MC. 2009;89: 149 –161. A systems view of physical therapy care: shifting to a new paradigm for the profession. Kigin C. 2009;89: 1117–1119. Hemiplegia Gait Rapid and long-term adaptations in gait symmetry following unilateral step training in people with hemiparesis. Kahn JH, Hornby TG. 2009;89:474 – 483. General Effects of hand cycle training on physical capacity in individuals with tetraplegia: a clinical trial. Valent LJM, Dallmeijer AJ, Houdijk H, et al. 2009;89:1051–1060. Lower-extremity strength differences predict activity limitations in people with chronic stroke. Kluding P, Gajewski B. 2009;89:73– 81.

December 2009

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Stoeckmann TM, Sullivan KJ, Scheidt RA. 2009;89:665– 678. [Ilial anterior rotation hypermobility in a female collegiate tennis player. Vaughn HT, Nitsch W. 2008;88:1578 –1590.]

Kinesiology/Biomechanics Gait Analysis Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. Lewek MD, Cruz TH, Moore JL, et al. 2009;89:829 – 839.

● Letter to the editor. Poulter DC. 2009;89:507–508. ● Letter to the editor. Cibulka MT. 2009;89:508 –509. ● Letter to the editor. Hesch J. 2009;89:509 –511.

● Invited e-commentary (online only). Patten C, Gonzalez-Rothi EJ, Little VL, Kautz SA. 2009; 89:e7– e8.

● Author response. Vaughn HT. 2009;89:511–512. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89:601– 611.

Associations of supported treadmill stepping with walking attainment in preterm and full-term infants. Luo H-J, Chen P-S, Hsieh W-S, et al. 2009;89:1215–1225.

● Invited commentary. Behrman AL. 2009;89:612– 615.

Gait variability detects women in early postmenopause with low bone mineral density. Palombaro KM, Hack LM, Mangione KK, et al. 2009;89:1315–1326. Rapid and long-term adaptations in gait symmetry following unilateral step training in people with hemiparesis. Kahn JH, Hornby TG. 2009;89:474 – 483. Rehabilitation after hallux valgus surgery: importance of physical therapy to restore weight bearing of the first ray during the stance phase. Schuh R, Hofstaetter SG, Adams SB Jr, et al. 2009;89: 934 –945. Stepping responses of infants with myelomeningocele when supported on a motorized treadmill. Teulier C, Smith BA, Kubo M, et al. 2009;89: 60 –72. Test-retest reliability and minimal detectable change scores for the Timed “Up & Go” Test, the SixMinute Walk Test, and gait speed in people with Alzheimer disease. Ries JD, Echternach JL, Nof L, Gagnon Blodgett M. 2009;89:569 –579. General Age affects the attentional demands of stair ambulation: evidence from a dual-task approach. Ojha HA, Kern RW, Lin C-HJ, Winstein CJ. 2009;89: 1080 –1088. Elastic, viscous, and mass load effects on poststroke muscle recruitment and co-contraction during reaching: a pilot study.

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● Author response. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89:615– 616. Treadmill testing of children who have spina bifida and are ambulatory: does peak oxygen uptake reflect maximum oxygen uptake? de Groot JF, Takken T, de Graaff S, et al. 2009;89:679 – 687. Lower Extremity Measurement of paretic–lowerextremity loading and weight transfer after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:653– 664. Upper Extremity Lengthening of the pectoralis minor muscle during passive shoulder motions and stretching techniques: a cadaveric biomechanical study. Muraki T, Aoki M, Izumi T, et al. 2009;89:333–341.

L Locomotion Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. Lewek MD, Cruz TH, Moore JL, et al. 2009;89:829 – 839. ● Invited e-commentary (online only). Patten C, Gonzalez-Rothi EJ,

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Index to Volume 89 Nonsurgical management of posterior tibial tendon dysfunction with orthoses and resistive exercise: a randomized controlled trial. Kulig K, Reischl SF, Pomrantz AB, et al. 2009;89:26 –37.

Little VL, Kautz SA. 2009; 89:e7– e8. Lower Extremity Ankle and Foot [Effect of weight-bearing activity on foot ulcer incidence in people with diabetic peripheral neuropathy: Feet First randomized controlled trial. LeMaster JW, Mueller MJ, Reiber GE, et al. 2008;88:1385–1398.]

Orthopedic surgeons and physical therapists differ in assessment of need for physical therapy after traumatic lower-extremity injury. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ; for the LEAP Study Group. 2009;89:1337–1349.

● Correction. 2009;89:1103. Effects of early progressive eccentric exercise on muscle size and function after anterior cruciate ligament reconstruction: a 1-year follow-up study of a randomized clinical trial. Gerber JP, Marcus RL, Dibble LE, et al. 2009;89:51–59.

● Invited commentary. Johnson MP. 2009;89:1349 –1351. ● Author response. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:1352–1353. ● Invited e-commentary (online only). Snyder-Mackler L. 2009;89:e9.

Exploring objects with feet advances movement in infants born preterm: a randomized controlled trial. Heathcock JC, Galloway JC. 2009;89:1027–1038.

● Author response (online only). Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:e10.

The Lower Extremity Functional Scale has good clinimetric properties in people with ankle fracture. Lin C-WC, Moseley AM, Refshauge KM, Bundy AC. 2009;89: 580 –588.

Hip Patient screening by a physical therapist for nonmusculoskeletal hip pain. VanWye WR. 2009;89: 248 –256.

Rehabilitation after hallux valgus surgery: importance of physical therapy to restore weight bearing of the first ray during the stance phase. Schuh R, Hofstaetter SG, Adams SB Jr, et al. 2009;89: 934 –945. General Clinical interpretation of a LowerExtremity Functional Scale– derived computerized adaptive test. Wang Y-C, Hart DL, Stratford PW, Mioduski JE. 2009;89:957–968. Factors associated with surgeon referral for physical therapy in patients with traumatic lowerextremity injury: results of a national survey of orthopedic trauma surgeons. Archer KR, MacKenzie EJ, Bosse MJ, et al. 2009;89:893–905. Lower-extremity strength differences predict activity limitations in people with chronic stroke. Kluding P, Gajewski B. 2009;89:73– 81. Measurement of paretic–lowerextremity loading and weight transfer after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:653– 664.

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Surplus value of hip adduction in leg-press exercise in patients with patellofemoral pain syndrome: a randomized controlled trial. Song CY, Lin YF, Wei TC, et al. 2009;89:409 – 418. Knee Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. Valtonen A, Po ¨ yho ¨ nen T, Heinonen A, Sipila¨ S. 2009;89:1072–1079.

M Manual Therapy Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial. Young IA, Michener LA, Cleland JA, et al. 2009;89:632– 642. ● Letter to the editor. Thorpe DL. 2009;89:1253. ● Author response. Young IA, Michener LA, Cleland JA, et al. 2009;89:1253. ● Correction. 2009;89:1254 –1255. Spinal manipulative therapy has an immediate effect on thermal pain

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sensitivity in people with low back pain: a randomized controlled trial. Bialosky JE, Bishop MD, Robinson ME, et al. 2009;89:1292–1303. Medical Conditions Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese. Sack S, Radler DR, Mairella KK, et al. 2009;89:804 – 815. ● Letter to the editor. Brooks GS. 2009;89:1100. Motor Activity Standardization of the Continuing Care Activity Measure: a multicenter study to assess reliability, validity, and ability to measure change. Huijbregts MPJ, Teare GF, McCullough C, et al. 2009;89: 546 –555. Step Test scores are related to measures of activity and participation in the first 6 months after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:1061–1071. Motor Skills Does sleep promote motor learning? Implications for physical rehabilitation. Siengsukon CF, Boyd LA. 2009;89:370 –383. Gastrocnemius-soleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm. Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009;89:136 –148. ● Invited e-commentary (online only). Heathcock JC. 2009;89:e1. ● Author response (online only). Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009;89:e2– e4. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Costa LOP, Maher CG, Latimer J, et al. 2009;89: 1275–1286. ● Invited commentary. Fritz JM. 2009;89:1287–1289. ● Author response. Costa LOP, Maher CG, Latimer J, et al. 2009; 89:1289 –1291. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Macedo LG, Maher CG, Latimer J, McAuley JH. 2009;89:9 –25.

December 2009

Index to Volume 89 Physical fitness in children with high motor competence is different from that in children with low motor competence. Haga M. 2009;89:1089 –1097. Movement Science Bound for success: a systematic review of constraint-induced movement therapy in children with cerebral palsy supports improved arm and hand use. Huang H, Fetters L, Hale J, McBride A. 2009;89: 1126 –1141.

● Author response. Vaughn HT. 2009;89:511–512.

Stoeckmann TM, Sullivan KJ, Scheidt RA. 2009;89:665– 678.

Infants born preterm exhibit different patterns of center-ofpressure movement than infants born at full term. Dusing SC, Kyvelidou A, Mercer VS, Stergiou N. 2009;89:1354 –1362.

Impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes: a randomized clinical trial. Taylor JD, Fletcher JP, Tiarks J. 2009;89: 884 – 892.

Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. Harbourne RT, Stergiou N. 2009;89: 267–282.

● Invited commentary. Charles J, Wolf SL. 2009;89:1142–1143.

● Invited commentary. Corbetta D. 2009;89:282–284.

● Author response. Huang H, Fetters L, Hale J, McBride A. 2009;89:1144.

● Author response. Harbourne RT, Stergiou N. 2009;89:284 –285.

Constraint-induced movement therapy for individuals after cerebral hemispherectomy: a case series. de Bode S, Fritz SL, WeirHaynes K, Mathern GW. 2009;89: 361–369. Delaying mobility disability in people with Parkinson disease using a sensorimotor ability exercise program. King LA, Horak FB. 2009;89:384 –393. Editorial (online only): “Just the facts, ma’am”: if it were only that simple, Joe. Galloway JC. 2009;89: e5– e6. Exploring objects with feet advances movement in infants born preterm: a randomized controlled trial. Heathcock JC, Galloway JC. 2009;89:1027–1038. External focus instructions reduce postural instability in individuals with Parkinson disease. Wulf G, Landers M, Lewthwaite R, To ¨ llner T. 2009;89:162–168. ● Invited commentary. Morris ME. 2009;89:169 –170. ● Author response. Wulf G, Lewthwaite R, Landers M, To ¨ llner T. 2009;89:170 –172. [Ilial anterior rotation hypermobility in a female collegiate tennis player. Vaughn HT, Nitsch W. 2008;88: 1578 –1590.] ● Letter to the editor. Poulter DC. 2009;89:507–508. ● Letter to the editor. Cibulka MT. 2009;89:508 –509. ● Letter to the editor. Hesch J. 2009;89:509 –511.

December 2009

Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. Salbach NM, Veinot P, Rappolt S, et al. 2009;89:556 –568. Muscle Gastrocnemius-soleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm. Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009; 89:136 –148. ● Invited e-commentary (online only). Heathcock JC. 2009;89:e1. ● Author response (online only). Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009;89:e2– e4. Lengthening of the pectoralis minor muscle during passive shoulder motions and stretching techniques: a cadaveric biomechanical study. Muraki T, Aoki M, Izumi T, et al. 2009;89:333–341. Muscle Performance General Comparison of gluteus medius muscle electromyographic activity during forward and lateral step-up exercises in older adults. Mercer VS, Gross MT, Sharma S, Weeks E. 2009;89:1205–1214. Comparison of maximum tolerated muscle torques produced by 2 pulse durations. Scott WB, Causey JB, Marshall TL. 2009;89:851– 857. Elastic, viscous, and mass load effects on poststroke muscle recruitment and co-contraction during reaching: a pilot study.

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Reproducibility of rehabilitative ultrasound imaging for the measurement of abdominal muscle activity: a systematic review. Costa LOP, Maher CG, Latimer J, Smeets RJEM. 2009;89:756 –769. Suspected statin-induced respiratory muscle myopathy during long-term inspiratory muscle training in a patient with diaphragmatic paralysis. Chatham K, Gelder CM, Lines TA, Cahalin LP. 2009;89: 257–266. Lower Extremity Effects of early progressive eccentric exercise on muscle size and function after anterior cruciate ligament reconstruction: a 1-year follow-up study of a randomized clinical trial. Gerber JP, Marcus RL, Dibble LE, et al. 2009;89:51–59. Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. Valtonen A, Po ¨ yho ¨ nen T, Heinonen A, Sipila¨ S. 2009;89:1072–1079. Measurement Quantitative measurement of poststroke spasticity and response to treatment with botulinum toxin: a 2-patient case report. Cousins E, Ward AB, Roffe C, et al. 2009;89: 688 – 697. Musculoskeletal Disorders General Clinical reasoning in musculoskeletal practice: students’ conceptualizations. Hendrick P, Bond C, Duncan E, Hale L. 2009;89:430 – 442. A controlled examination of medical and psychosocial factors associated with low back pain in combination with widespread musculoskeletal pain. Friedrich M, Hahne J, Wepner F. 2009;89: 786 – 803. New models for primary care are needed for osteoarthritis. Dziedzic

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Index to Volume 89 ● Author response. Rundell SD, Davenport TE, Wagner T. 2009; 89:309 –310.

KS, Hill JC, Porcheret M, Croft PR. 2009;89:1371–1378. The Patient Goal Priority Questionnaire is moderately reproducible in people with persistent musculoskeletal pain. Åsenlo ¨ f P, Siljeba¨ck K. 2009;89: 1226 –1234.

● Correction. 2009;89:310. Spinal manipulative therapy has an immediate effect on thermal pain sensitivity in people with low back pain: a randomized controlled trial. Bialosky JE, Bishop MD, Robinson ME, et al. 2009;89:1292–1303. General Does continuing education improve physical therapists’ effectiveness in treating neck pain? A randomized clinical trial. Cleland JA, Fritz JM, Brennan GP, Magel J. 2009;89: 38 – 47.

Stretch exercises increase tolerance to stretch in patients with chronic musculoskeletal pain: a randomized controlled trial. Law RYW, Harvey LA, Nicholas MK, et al. 2009;89: 1016 –1026.

N

● Invited commentary. Jull G. 2009;89:48 –50.

Neck and Trunk

Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. Fabrizio P. 2009;89:351–360.

Back A controlled examination of medical and psychosocial factors associated with low back pain in combination with widespread musculoskeletal pain. Friedrich M, Hahne J, Wepner F. 2009;89: 786 – 803.

Neuromuscular Disorders

Development of a self-report measure of fearful activities for patients with low back pain: the Fear of Daily Activities Questionnaire. George SZ, Valencia C, Zeppieri G Jr, Robinson ME. 2009;89:969 –979. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Costa LOP, Maher CG, Latimer J, et al. 2009;89: 1275–1286. ● Invited commentary. Fritz JM. 2009;89:1287–1289. ● Author response. Costa LOP, Maher CG, Latimer J, et al. 2009; 89:1289 –1291. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Macedo LG, Maher CG, Latimer J, McAuley JH. 2009;89:9 –25. Physical therapist management of acute and chronic low back pain using the World Health Organization’s International Classification of Functioning, Disability and Health. Rundell SD, Davenport TE, Wagner T. 2009;89: 82–90. ● Letter to the editor. Escorpizo R, Cieza A. 2009;89:308.

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General Test-retest reliability and minimal detectable change scores for the Timed “Up & Go” Test, the SixMinute Walk Test, and gait speed in people with Alzheimer disease. Ries JD, Echternach JL, Nof L, Gagnon Blodgett M. 2009;89:569 –579. Parkinson Disease Delaying mobility disability in people with Parkinson disease using a sensorimotor ability exercise program. King LA, Horak FB. 2009;89:384 –393. External focus instructions reduce postural instability in individuals with Parkinson disease. Wulf G, Landers M, Lewthwaite R, To ¨ llner T. 2009;89:162–168. ● Invited commentary. Morris ME. 2009;89:169 –170. ● Author response. Wulf G, Lewthwaite R, Landers M, To ¨ llner T. 2009;89:170 –172.

O Occupational Therapy Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. Fabrizio P. 2009;89:351–360.

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Oncology Cancer prevention in physical therapist practice. Stout NL. 2009; 89:1119 –1122. A framework for assessment in oncology rehabilitation. Gilchrist LS, Galantino ML, Wampler M, et al. 2009;89:286 –306. Orthopedics: Fractures Lower Extremity The Lower Extremity Functional Scale has good clinimetric properties in people with ankle fracture. Lin C-WC, Moseley AM, Refshauge KM, Bundy AC. 2009;89: 580 –588. Orthopedics General Factors associated with surgeon referral for physical therapy in patients with traumatic lowerextremity injury: results of a national survey of orthopedic trauma surgeons. Archer KR, MacKenzie EJ, Bosse MJ, et al. 2009;89:893–905. Gait variability detects women in early postmenopause with low bone mineral density. Palombaro KM, Hack LM, Mangione KK, et al. 2009;89:1315–1326. An intensive, progressive exercise program reduces disability and improves functional performance in patients after single-level lumbar microdiskectomy. Kulig K, Beneck GJ, Selkowitz DM, et al; Physical Therapy Clinical Research Network (PTClinResNet). 2009;89:1145–1157. Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial. Young IA, Michener LA, Cleland JA, et al. 2009;89:632– 642. ● Letter to the editor. Thorpe DL. 2009;89:1253. ● Author response. Young IA, Michener LA, Cleland JA, et al. 2009;89:1253. ● Correction. 2009;89:1254 –1255. Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. Valtonen A, Po ¨ yho ¨ nen T, Heinonen A, Sipila¨ S. 2009;89:1072–1079. Orthopedic surgeons and physical therapists differ in assessment of

December 2009

Index to Volume 89 need for physical therapy after traumatic lower-extremity injury. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ; for the LEAP Study Group. 2009;89:1337–1349. ● Invited commentary. Johnson MP. 2009;89:1349 –1351. ● Author response. Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:1352–1353. ● Invited e-commentary (online only). Snyder-Mackler L. 2009;89:e9. ● Author response (online only). Archer KR, MacKenzie EJ, Castillo RC, Bosse MJ. 2009;89:e10. Orthotics/Splints/Casts Lower Extremity Nonsurgical management of posterior tibial tendon dysfunction with orthoses and resistive exercise: a randomized controlled trial. Kulig K, Reischl SF, Pomrantz AB, et al. 2009;89:26 –37.

P Pain A controlled examination of medical and psychosocial factors associated with low back pain in combination with widespread musculoskeletal pain. Friedrich M, Hahne J, Wepner F. 2009;89: 786 – 803. Development of a self-report measure of fearful activities for patients with low back pain: the Fear of Daily Activities Questionnaire. George SZ, Valencia C, Zeppieri G Jr, Robinson ME. 2009;89:969 –979. Does continuing education improve physical therapists’ effectiveness in treating neck pain? A randomized clinical trial. Cleland JA, Fritz JM, Brennan GP, Magel J. 2009;89: 38 – 47. ● Invited commentary. Jull G. 2009; 89:48 –50. Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. Fabrizio P. 2009;89:351–360. Interventions associated with an increased or decreased likelihood of pain reduction and improved function in patients with adhesive capsulitis: a retrospective cohort

December 2009

study. Jewell DV, Riddle DL, Thacker LR. 2009;89:419 – 429. Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Costa LOP, Maher CG, Latimer J, et al. 2009;89: 1275–1286. ● Invited commentary. Fritz JM. 2009;89:1287–1289. ● Author response. Costa LOP, Maher CG, Latimer J, et al. 2009; 89:1289 –1291. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Macedo LG, Maher CG, Latimer J, McAuley JH. 2009;89:9 –25. The Patient Goal Priority Questionnaire is moderately reproducible in people with persistent musculoskeletal pain. Åsenlo ¨ f P, Siljeba¨ck K. 2009;89: 1226 –1234. Patient screening by a physical therapist for nonmusculoskeletal hip pain. VanWye WR. 2009;89: 248 –256. Physical therapist management of acute and chronic low back pain using the World Health Organization’s International Classification of Functioning, Disability and Health. Rundell SD, Davenport TE, Wagner T. 2009;89: 82–90. ● Letter to the editor. Escorpizo R, Cieza A. 2009;89:308. ● Author response. Rundell SD, Davenport TE, Wagner T. 2009; 89:309 –310. ● Correction. 2009;89:310. Physical therapists’ use of cognitivebehavioral therapy for older adults with chronic pain: a nationwide survey. Beissner K, Henderson CR Jr, Papaleontiou M, et al. 2009;89: 456 – 469. ● Invited commentary. Sluka KA, Turk DC. 2009;89:470 – 472. ● Author response. Beissner K, Reid MC. 2009;89:472– 473. Spinal manipulative therapy has an immediate effect on thermal pain sensitivity in people with low back pain: a randomized controlled trial. Bialosky JE, Bishop MD, Robinson ME, et al. 2009;89:1292–1303.

Volume 89

Stretch exercises increase tolerance to stretch in patients with chronic musculoskeletal pain: a randomized controlled trial. Law RYW, Harvey LA, Nicholas MK, et al. 2009;89: 1016 –1026. Surplus value of hip adduction in leg-press exercise in patients with patellofemoral pain syndrome: a randomized controlled trial. Song CY, Lin YF, Wei TC, et al. 2009;89:409 – 418. Pediatrics Development Associations of supported treadmill stepping with walking attainment in preterm and full-term infants. Luo H-J, Chen P-S, Hsieh W-S, et al. 2009;89:1215–1225. Gastrocnemius-soleus muscle tendon unit changes over the first 12 weeks of adjusted age in infants born preterm. Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009; 89:136 –148. ● Invited e-commentary (online only). Heathcock JC. 2009;89:e1. ● Author response (online only). Grant-Beuttler M, Palisano RJ, Miller DP, et al. 2009;89:e2– e4. Harris Infant Neuromotor Test: comparison of US and Canadian normative data and examination of concurrent validity with the Ages and Stages Questionnaire. Westcott McCoy S, Bowman A, SmithBlockley J, et al. 2009;89:173–180. Stepping responses of infants with myelomeningocele when supported on a motorized treadmill. Teulier C, Smith BA, Kubo M, et al. 2009;89: 60 –72. Evaluation Social and community participation of children and youth with cerebral palsy is associated with age and gross motor function classification. Palisano RJ, Kang L-J, Chiarello LA, et al. 2009;89:1304 –1314. General Evaluation of an item bank for a computerized adaptive test of activity in children with cerebral palsy. Haley SM, Fragala-Pinkham MA, Dumas HM, et al. 2009;89: 589 – 600. Exploring objects with feet advances movement in infants born

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preterm: a randomized controlled trial. Heathcock JC, Galloway JC. 2009;89:1027–1038. Infants born preterm exhibit different patterns of center-ofpressure movement than infants born at full term. Dusing SC, Kyvelidou A, Mercer VS, Stergiou N. 2009;89:1354 –1362. Physical fitness in children with high motor competence is different from that in children with low motor competence. Haga M. 2009;89:1089 –1097. Treatment Bound for success: a systematic review of constraint-induced movement therapy in children with cerebral palsy supports improved arm and hand use. Huang H, Fetters L, Hale J, McBride A. 2009;89: 1126 –1141.

Professional Issues Academic difficulty and programlevel variables predict performance on the National Physical Therapy Examination for licensure: a population-based cohort study. Riddle DL, Utzman RR, Jewell DV, et al. 2009;89:1182–1191. Assessment of the quality of cost analysis literature in physical therapy. Peterson LE, Goodman C, Karnes EK, et al. 2009;89:733–755. Cancer prevention in physical therapist practice. Stout NL. 2009; 89:1119 –1122. Clinical prediction rules for physical therapy interventions: a systematic review. Beneciuk JM, Bishop MD, George SZ. 2009;89:114 –124.

an observational study. Jette DU, Brown R, Collette N, et al. 2009; 89:1158 –1181. Physical therapy health human resource ratios: a comparative analysis of the United States and Canada. Landry MD, Ricketts TC, Fraher E, Verrier MC. 2009;89: 149 –161. A systems view of physical therapy care: shifting to a new paradigm for the profession. Kigin C. 2009;89: 1117–1119. Posture General External focus instructions reduce postural instability in individuals with Parkinson disease. Wulf G, Landers M, Lewthwaite R, To ¨ llner T. 2009;89:162–168.

● Invited commentary. Charles J, Wolf SL. 2009;89:1142–1143.

● Letter to the editor. Stanton TR, Maher CG, Hancock M. 2009;89: 394.

● Author response. Huang H, Fetters L, Hale J, McBride A. 2009;89:1144.

● Author response. George SZ, Beneciuk JM, Bishop MD. 2009;89:394 –395.

● Author response. Wulf G, Lewthwaite R, Landers M, To ¨ llner T. 2009;89:170 –172.

Strategies to promote evidence-based practice in pediatric physical therapy: a formative evaluation pilot project. Schreiber J, Stern P, Marchetti G, Provident I. 2009;89:918 –933.

Editorial: PT 2009 notes, PTJ welcomes and thanks. Craik RL. 2009;89:626 – 627.

Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Beninato M, Portney LG, Sullivan PE. 2009;89:816 – 825.

Editorial: A responsibility to put “Health Policy in Perspective.” Craik RL. 2009;89:1114 –1115.

Peer-Reviewed Publications Editorial (online only): “Just the facts, ma’am”: if it were only that simple, Joe. Galloway JC. 2009;89: e5– e6.

Editorial (online only): “Just the facts, ma’am”: if it were only that simple, Joe. Galloway JC. 2009;89: e5– e6.

Phototherapy

Job strain in physical therapists. Campo MA, Weiser S, Koenig KL. 2009;89:946 –956.

Laser Short-term effects of high-intensity laser therapy versus ultrasound therapy in the treatment of people with subacromial impingement syndrome: a randomized clinical trial. Santamato A, Solfrizzi V, Panza F, et al. 2009;89:643– 652. ● Correction. 2009;89:999. Physical Fitness Physical fitness in children with high motor competence is different from that in children with low motor competence. Haga M. 2009;89: 1089 –1097.

Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. Harbourne RT, Stergiou N. 2009;89: 267–282. ● Invited commentary. Corbetta D. 2009;89:282–284. ● Author response. Harbourne RT, Stergiou N. 2009;89:284 –285. Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese. Sack S, Radler DR, Mairella KK, et al. 2009;89:804 – 815. ● Letter to the editor. Brooks GS. 2009;89:1100. Physical therapists’ management of patients in the acute care setting:

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● Invited commentary. Morris ME. 2009;89:169 –170.

● Invited commentary. Escorpizo R, Cieza A, Stucki G. 2009;89: 825– 827. ● Author response. Beninato M, Portney LG, Sullivan PE. 2009;89:827– 828. Professional-Patient Relations Letter to the editor. [RE: Sexuality and health care: are we training physical therapy professionals to address their clients’ sexuality needs?] Sengupta S, Sakellariou D. 2009;89:101–102. Publications and Audiovisual Materials Editorial: PT 2009 notes, PTJ welcomes and thanks. Craik RL. 2009;89:626 – 627. Pulmonary General Short-term efficacy of upperextremity exercise training in patients with chronic airway obstruction: a

December 2009

Index to Volume 89 systematic review. Costi S, Di Bari M, Pillastrini P, et al. 2009;89:443– 455.

● Letter to the editor. Hesch J. 2009;89:509 –511.

Suspected statin-induced respiratory muscle myopathy during long-term inspiratory muscle training in a patient with diaphragmatic paralysis. Chatham K, Gelder CM, Lines TA, Cahalin LP. 2009;89:257–266.

● Author response. Vaughn HT. 2009;89:511–512.

Editorial: Above board: clear bylaws support the research mission of the Foundation for Physical Therapy. Shields RK. 2009;89:1010 –1012.

Muscle deficits persist after unilateral knee replacement and have implications for rehabilitation. Valtonen A, Po ¨ yho ¨ nen T, Heinonen A, Sipila¨ S. 2009;89:1072–1079.

Factors influencing information seeking by physical therapists providing stroke management. Salbach NM, Guilcher SJT, Jaglal SB, Davis DA. 2009;89:1039 –1050.

Neuroprosthesis peroneal functional electrical stimulation in the acute inpatient rehabilitation setting: a case series. Dunning K, Black K, Harrison A, et al. 2009;89:499 –506.

A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Hancock M, Herbert RD, Maher CG. 2009;89:698 –704.

Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. Salbach NM, Veinot P, Rappolt S, et al. 2009;89:556 –568.

● Author response. Hancock M, Herbert R, Maher CG. 2009;89: 1099 –1100.

Treadmill testing of children who have spina bifida and are ambulatory: does peak oxygen uptake reflect maximum oxygen uptake? de Groot JF, Takken T, de Graaff S, et al. 2009;89:679 – 687.

R Rehabilitation A conceptual model of optimal international service-learning and its application to global health initiatives in rehabilitation. Pechak CM, Thompson M. 2009;89:1192–1204. Does sleep promote motor learning? Implications for physical rehabilitation. Siengsukon CF, Boyd LA. 2009;89:370 –383. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Hammer AM, Lindmark B. 2009;89: 526 –539. ● Invited commentary. Cauraugh JH, Summers JJ. 2009;89:539 –541. ● Author response. Hammer AM, Lindmark B. 2009;89:541–542. ● Invited commentary. Charles J. 2009;89:542–544. ● Author response. Hammer AM, Lindmark B. 2009;89:544 –545. ● Letter to the editor. Wolf SL. 2009;89:993–995. ● Author response. Hammer AM, Lindmark B. 2009;89:995–997. A framework for assessment in oncology rehabilitation. Gilchrist LS, Galantino ML, Wampler M, et al. 2009;89:286 –306. [Ilial anterior rotation hypermobility in a female collegiate tennis player. Vaughn HT, Nitsch W. 2008;88: 1578 –1590.] ● Letter to the editor. Poulter DC. 2009;89:507–508. ● Letter to the editor. Cibulka MT. 2009;89:508 –509.

December 2009

Physical therapy health human resource ratios: a comparative analysis of the United States and Canada. Landry MD, Ricketts TC, Fraher E, Verrier MC. 2009;89: 149 –161. Rehabilitation after hallux valgus surgery: importance of physical therapy to restore weight bearing of the first ray during the stance phase. Schuh R, Hofstaetter SG, Adams SB Jr, et al. 2009;89:934 –945. Reproducibility of rehabilitative ultrasound imaging for the measurement of abdominal muscle activity: a systematic review. Costa LOP, Maher CG, Latimer J, Smeets RJEM. 2009;89:756 –769. Screening for elevated levels of fearavoidance beliefs regarding work or physical activities in people receiving outpatient therapy. Hart DL, Werneke MW, George SZ, et al. 2009;89:770 –785. Research Advancements in contemporary physical therapy research: use of mixed methods designs. Rauscher L, Greenfield BH. 2009;89:91–100. Clinical prediction rules for physical therapy interventions: a systematic review. Beneciuk JM, Bishop MD, George SZ. 2009;89:114 –124. ● Letter to the editor. Stanton TR, Maher CG, Hancock M. 2009;89: 394. ● Author response. George SZ, Beneciuk JM, Bishop MD. 2009;89:394 –395.

Volume 89

● Letter to the editor. Allison SC. 2009;89:1098 –1099.

S Spinal Cord Dysfunction General Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89:601– 611. ● Invited commentary. Behrman AL. 2009;89:612– 615. ● Author response. Musselman KE, Fouad K, Misiaszek JE, Yang JF. 2009;89:615– 616.

T Tests and Measurements Functional Assessment of physical functioning: a conceptual model encompassing environmental factors and individual compensation strategies. Tomey KM, Sowers MR. 2009;89:705–714. Psychometric comparisons of 4 measures for assessing upperextremity function in people with stroke. Lin J-H, Hsu M-J, Sheu C-F, et al. 2009;89:840 – 850. Social and community participation of children and youth with cerebral palsy is associated with age and gross motor function classification. Palisano RJ, Kang L-J, Chiarello LA, et al. 2009;89:1304 –1314.

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Index to Volume 89 Standardization of the Continuing Care Activity Measure: a multicenter study to assess reliability, validity, and ability to measure change. Huijbregts MPJ, Teare GF, McCullough C, et al. 2009;89: 546 –555. Step Test scores are related to measures of activity and participation in the first 6 months after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:1061–1071. General The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. Horak FB, Wrisley DM, Frank J. 2009;89:484 – 498.

Development of a self-report measure of fearful activities for patients with low back pain: the Fear of Daily Activities Questionnaire. George SZ, Valencia C, Zeppieri G Jr, Robinson ME. 2009;89:969 –979.

Harris Infant Neuromotor Test: comparison of US and Canadian normative data and examination of concurrent validity with the Ages and Stages Questionnaire. Westcott McCoy S, Bowman A, SmithBlockley J, et al. 2009;89:173–180. Longitudinal construct validity of the GMFM-88 total score and goal total score and the GMFM-66 score in a 5-year follow-up study. Lundkvist Josenby A, Jarnlo GB, Gummesson C, Nordmark E. 2009;89:342–350. The Lower Extremity Functional Scale has good clinimetric properties in people with ankle fracture. Lin C-WC, Moseley AM, Refshauge KM, Bundy AC. 2009;89:580 –588. Measurement of paretic–lowerextremity loading and weight transfer after stroke. Mercer VS, Freburger JK, Chang S-H, Purser JL. 2009;89:653– 664.

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Reproducibility of rehabilitative ultrasound imaging for the measurement of abdominal muscle activity: a systematic review. Costa LOP, Maher CG, Latimer J, Smeets RJEM. 2009;89:756 –769.

Quantitative measurement of poststroke spasticity and response to treatment with botulinum toxin: a 2-patient case report. Cousins E, Ward AB, Roffe C, et al. 2009;89: 688 – 697.

Short-term effects of high-intensity laser therapy versus ultrasound therapy in the treatment of people with subacromial impingement syndrome: a randomized clinical trial. Santamato A, Solfrizzi V, Panza F, et al. 2009;89:643– 652.

Screening for elevated levels of fearavoidance beliefs regarding work or physical activities in people receiving outpatient therapy. Hart DL, Werneke MW, George SZ, et al. 2009;89:770 –785.

Clinical interpretation of a LowerExtremity Functional Scale– derived computerized adaptive test. Wang Y-C, Hart DL, Stratford PW, Mioduski JE. 2009;89:957–968.

Evaluation of an item bank for a computerized adaptive test of activity in children with cerebral palsy. Haley SM, Fragala-Pinkham MA, Dumas HM, et al. 2009;89:589 – 600.

The Patient Goal Priority Questionnaire is moderately reproducible in people with persistent musculoskeletal pain. Åsenlo ¨ f P, Siljeba¨ck K. 2009;89: 1226 –1234.

Test-retest reliability and minimal detectable change scores for the Timed “Up & Go” Test, the SixMinute Walk Test, and gait speed in people with Alzheimer disease. Ries JD, Echternach JL, Nof L, Gagnon Blodgett M. 2009;89:569 –579. Use of standardized outcome measures in physical therapist practice: perceptions and applications. Jette DU, Halbert J, Iverson C, et al. 2009;89:125–135. Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Beninato M, Portney LG, Sullivan PE. 2009;89:816 – 825. ● Invited commentary. Escorpizo R, Cieza A, Stucki G. 2009;89: 825– 827. ● Author response. Beninato M, Portney LG, Sullivan PE. 2009;89: 827– 828.

● Correction. 2009;89:999. Upper Extremity General Bound for success: a systematic review of constraint-induced movement therapy in children with cerebral palsy supports improved arm and hand use. Huang H, Fetters L, Hale J, McBride A. 2009;89: 1126 –1141. ● Invited commentary. Charles J, Wolf SL. 2009;89:1142–1143. ● Author response. Huang H, Fetters L, Hale J, McBride A. 2009;89:1144. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Hammer AM, Lindmark B. 2009;89: 526 –539. ● Invited commentary. Cauraugh JH, Summers JJ. 2009;89:539 –541. ● Author response. Hammer AM, Lindmark B. 2009;89:541–542. ● Invited commentary. Charles J. 2009;89:542–544. ● Author response. Hammer AM, Lindmark B. 2009;89:544 –545. ● Letter to the editor. Wolf SL. 2009;89:993–995.

U

● Author response. Hammer AM, Lindmark B. 2009;89:995–997.

Ultrasound [Noncontact ultrasound therapy for adjunctive treatment of nonhealing wounds: retrospective analysis. Bell AL, Cavorsi J. 2008;89:1517–1524.

Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. Fabrizio P. 2009;89:351–360.

● Invited commentary. Robertson VJ. 2008;88:1524 –1526. ● Author response. Bell AL, Cavorsi J. 2008;88:1526 –1528.] ● Correction. 2009;89:103.

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A functional threshold for long-term use of hand and arm function can be determined: predictions from a computational model and supporting data from the Extremity ConstraintInduced Therapy Evaluation (EXCITE) trial. Schweighofer N, Han CE, Wolf SL, et al. 2009;89:1327–1336.

December 2009

Index to Volume 89 Psychometric comparisons of 4 measures for assessing upperextremity function in people with stroke. Lin J-H, Hsu M-J, Sheu C-F, et al. 2009;89:840 – 850. Short-term efficacy of upperextremity exercise training in patients with chronic airway obstruction: a systematic review. Costi S, Di Bari M, Pillastrini P, et al. 2009;89:443– 455.

December 2009

Hand and Wrist There is inadequate evidence to determine the effectiveness of nonpharmacological and nonsurgical interventions for hand osteoarthritis: an overview of highquality systematic reviews. Moe RH, Kjeken I, Uhlig T, Hagen KB. 2009;89:1363–1370. Shoulder Adhesive capsulitis: establishing consensus on clinical identifiers for stage 1 using the Delphi technique. Walmsley S, Rivett DA, Osmotherly PG. 2009;89:906 –917.

Volume 89

Lengthening of the pectoralis minor muscle during passive shoulder motions and stretching techniques: a cadaveric biomechanical study. Muraki T, Aoki M, Izumi T, et al. 2009;89:333–341.

V Vestibular System Traumatic brain injury and vestibular pathology as a comorbidity after blast exposure. Scherer MR, Schubert MC. 2009;89: 980 –992.

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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- October 2009, Volume 89, Issue 10

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- 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)

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

sports medicine Volume 39 Issue 12 December 2009

Manual Therapy Journal - Volume 14, Issue 6, Pages 585-716 (December 2009)

Journal of Semantics, Volume 12, Issue 3, 1995

sports medicine Volume 40 Issue 12 December 2010

sports medicine Volume 38 Issue 12 December 2008

Behavioral and Brain Sciences, Volume 32, Issue 6, December 2009

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

Manual Therapy Journal- Volume 13, Issue 6, Pages 475-564 (December 2008)

Radical Philosophy Issue: 89

The Perl Journal (December)

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

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- October 2009, Volume 89, Issue 10

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- 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)

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

sports medicine Volume 39 Issue 12 December 2009

Manual Therapy Journal - Volume 14, Issue 6, Pages 585-716 (December 2009)

Journal of Semantics, Volume 12, Issue 3, 1995

sports medicine Volume 40 Issue 12 December 2010

sports medicine Volume 38 Issue 12 December 2008

Behavioral and Brain Sciences, Volume 32, Issue 6, December 2009

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

Manual Therapy Journal- Volume 13, Issue 6, Pages 475-564 (December 2008)

Radical Philosophy Issue: 89

The Perl Journal (December)

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