Amanda M Hall1, Steven J Kamper2, Marian Hernon3, Katie Hughes4, Gráinne Kelly5, Chris Lonsdale6, Deirdre A Hurley7, Raymond Ostelo8. 1. School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland. Electronic address: amandahall@george.org.au. 2. Musculoskeletal Division, George Institute for Global Health, Sydney, NSW, Australia; EMGO+ Institute, VU University Medical Center, Amsterdam, The Netherlands. 3. School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland. 4. School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland; Faculty of Education and Health Sciences, University of Limerick, Limerick, Ireland. 5. Department of Clinical Therapies, University of Limerick, Limerick, Ireland. 6. Faculty of Health Sciences, Australian Catholic University, Sydney, NSW, Australia. 7. Faculty of Education and Health Sciences, University of Limerick, Limerick, Ireland. 8. EMGO+ Institute, VU University Medical Center, Amsterdam, The Netherlands.
Abstract
OBJECTIVES: To identify measures of adherence to nonpharmacologic self-management treatments for chronic musculoskeletal (MSK) populations; and to report on the measurement properties of identified measures. DATA SOURCES: Five databases were searched for all study types that included a chronic MSK population, unsupervised intervention, and measure of adherence. STUDY SELECTION: Two independent researchers reviewed all titles for inclusion using the following criteria: adult (>18y) participants with a chronic MSK condition; intervention, including an unsupervised self-management component; and measure of adherence to the unsupervised self-management component. DATA EXTRACTION: Descriptive data regarding populations, unsupervised components, and measures of unsupervised adherence (items, response options) were collected from each study by 1 researcher and checked by a second for accuracy. DATA SYNTHESIS: No named or referenced adherence measurement tools were found, but a total of 47 self-invented measures were identified. No measure was used in more than a single study. Methods could be grouped into the following: home diaries (n=31), multi-item questionnaires (n=11), and single-item questionnaires (n=7). All measures varied in type of information requested and scoring method. The lack of established tools precluded quality assessment of the measurement properties using COnsensus-based Standards for the selection of health Measurement INstruments methodology. CONCLUSIONS: Despite the importance of adherence to self-management interventions, measurement appears to be conducted on an ad hoc basis. It is clear that there is no consistency among adherence measurement tools and that the construct is ill-defined. This study alerts the research community to the gap in measuring adherence to self-care in a rigorous and reproducible manner. Therefore, we need to address this gap by using credible methods (eg, COnsensus-based Standards for the selection of health Measurement INstruments guidelines) to develop and evaluate an appropriate measure of adherence for self-management.
OBJECTIVES: To identify measures of adherence to nonpharmacologic self-management treatments for chronic musculoskeletal (MSK) populations; and to report on the measurement properties of identified measures. DATA SOURCES: Five databases were searched for all study types that included a chronic MSK population, unsupervised intervention, and measure of adherence. STUDY SELECTION: Two independent researchers reviewed all titles for inclusion using the following criteria: adult (>18y) participants with a chronic MSK condition; intervention, including an unsupervised self-management component; and measure of adherence to the unsupervised self-management component. DATA EXTRACTION: Descriptive data regarding populations, unsupervised components, and measures of unsupervised adherence (items, response options) were collected from each study by 1 researcher and checked by a second for accuracy. DATA SYNTHESIS: No named or referenced adherence measurement tools were found, but a total of 47 self-invented measures were identified. No measure was used in more than a single study. Methods could be grouped into the following: home diaries (n=31), multi-item questionnaires (n=11), and single-item questionnaires (n=7). All measures varied in type of information requested and scoring method. The lack of established tools precluded quality assessment of the measurement properties using COnsensus-based Standards for the selection of health Measurement INstruments methodology. CONCLUSIONS: Despite the importance of adherence to self-management interventions, measurement appears to be conducted on an ad hoc basis. It is clear that there is no consistency among adherence measurement tools and that the construct is ill-defined. This study alerts the research community to the gap in measuring adherence to self-care in a rigorous and reproducible manner. Therefore, we need to address this gap by using credible methods (eg, COnsensus-based Standards for the selection of health Measurement INstruments guidelines) to develop and evaluate an appropriate measure of adherence for self-management.
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