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Treatment Effect Modifiers for Return-to-Work in Patients With Musculoskeletal Disorders
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DOI：10.1016/j.jpain.2024.104556.png)
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Abstract
En 中文
Investigating how individual characteristics modify treatment effects can improve understanding, interpretation, and translation of trial findings. The purpose of this secondary analysis was to identify treatment effect modifiers of the MI-NAV trial, a 3 arm, parallel randomized controlled trial which compared motivational interviewing and stratified vocational advice intervention in addition to usual case management (UC), to UC alone. This study included (n = 514) participants with musculoskeletal disorders on sick leave for at least 50% of their contracted work hours for at least 7 consecutive weeks with the Norwegian Labour and Welfare Administration. Sickness absence days was the primary outcome, measured from baseline assessment date until the 6-month follow-up. Potential treatment effect modifiers, identified a priori and informed by expert consultation and literature, were evaluated using linear regression models and statistical interaction tests. For motivational interviewing versus UC, age (mean difference [MD] -.7, 95% confidence interval [CI] -1.5 to .2; P = .13) and self-perceived health status (MD -.3, 95% CI -.7 to .1; P = .19) were identified as potential effect modifiers (P <= .2). For stratified vocational advice intervention versus UC, analgesic medication use (MD -26.2, 95% CI -45.7 to -6.7; P = .009) was identified as a treatment effect modifier (P <= .05). These findings may assist in more targeted treatment adaptation and translation as well as the planning of future clinical trials. Perspective: This secondary analysis of the MI-NAV trial found that analgesic medication use, age, and self-perceived health may modify the effect of 2 vocational interventions on reducing sickness absence in people with musculoskeletal disorders. (c) 2024 (c) Published by Elsevier Inc. on behalf of United States Association for the Study of Pain, Inc All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords:
Treatment effect modifiers
vocational interventions
musculoskeletal disorders
chronic pain
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