Ann-Christin Pfeifer, Paul Schröder-Pfeifer, Marcus Schiltenwolf, Lutz Vogt, Christian Schneider, Petra Platen, Heidrun Beck, Pia-Maria Wippert, Tilman Engel, Monique Wochatz, Frank Mayer, Daniel Niederer
{"title":"在腰痛的随机对照试验中发现运动坚持的预测因素：使用机器学习技术的个人数据重新分析。","authors":"Ann-Christin Pfeifer, Paul Schröder-Pfeifer, Marcus Schiltenwolf, Lutz Vogt, Christian Schneider, Petra Platen, Heidrun Beck, Pia-Maria Wippert, Tilman Engel, Monique Wochatz, Frank Mayer, Daniel Niederer","doi":"10.1016/j.apmr.2024.12.015","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To identify predictors of adherence in supervised and self-administered exercise interventions for individuals with low back pain.</p><p><strong>Design: </strong>Cohort study.</p><p><strong>Setting: </strong>Rehabilitation.</p><p><strong>Participants: </strong>This preplanned reanalysis within the Medicine in Spine Exercise Network included 1511 participants with low back pain (57% female, mean age 40.9 years, SD ±14 years).</p><p><strong>Interventions: </strong>Participants underwent an initial 3-week supervised phase of sensorimotor exercises, followed by a 9-week self-administered phase.</p><p><strong>Main outcome measures: </strong>Biological, psychological, and social factors potentially impacting training adherence were evaluated. During the supervised phase, adherence was tracked through a standardized training log. During the self-administered phase, adherence was monitored via a diary, with adherence calculated as the percentage of scheduled versus completed sessions. Adherence was analyzed both as an absolute percentage and as a dichotomized variable (adherent vs nonadherent, with a 70% adherence cut-off). Predictors for adherence were identified using Gradient Boosting Machines and Random Forests (R package caret). Seventy percent of the observations were used for training, whereas 30% were retained as a hold-out test-set.</p><p><strong>Results: </strong>The average overall adherence was 64% (±31%), with 81% (±28%) adherence during the supervised phase and 58% (±39%) in the self-administered phase. The root mean square error for the test-set ranged from 36.2 (R<sup>2</sup>=0.18, self-administered phase) to 19.3 (R<sup>2</sup>=0.47, supervised phase); prediction accuracy for dichotomized models was between 64% and 83%. Predictors of low to intermediate adherence included poorer baseline postural control, decline in exercise levels, and fluctuations in pain intensity (both increases and decreases).</p><p><strong>Conclusion: </strong>Identified predictors could aid in recognizing individuals at higher risk for nonadherence in low back pain exercise therapy settings.</p>","PeriodicalId":8313,"journal":{"name":"Archives of physical medicine and rehabilitation","volume":" ","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finding Predictive Factors of Stabilization Exercise Adherence in Randomized Controlled Trials on Low Back Pain: An Individual Data Reanalysis Using Machine Learning Techniques.\",\"authors\":\"Ann-Christin Pfeifer, Paul Schröder-Pfeifer, Marcus Schiltenwolf, Lutz Vogt, Christian Schneider, Petra Platen, Heidrun Beck, Pia-Maria Wippert, Tilman Engel, Monique Wochatz, Frank Mayer, Daniel Niederer\",\"doi\":\"10.1016/j.apmr.2024.12.015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To identify predictors of adherence in supervised and self-administered exercise interventions for individuals with low back pain.</p><p><strong>Design: </strong>Cohort study.</p><p><strong>Setting: </strong>Rehabilitation.</p><p><strong>Participants: </strong>This preplanned reanalysis within the Medicine in Spine Exercise Network included 1511 participants with low back pain (57% female, mean age 40.9 years, SD ±14 years).</p><p><strong>Interventions: </strong>Participants underwent an initial 3-week supervised phase of sensorimotor exercises, followed by a 9-week self-administered phase.</p><p><strong>Main outcome measures: </strong>Biological, psychological, and social factors potentially impacting training adherence were evaluated. 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Finding Predictive Factors of Stabilization Exercise Adherence in Randomized Controlled Trials on Low Back Pain: An Individual Data Reanalysis Using Machine Learning Techniques.
Objective: To identify predictors of adherence in supervised and self-administered exercise interventions for individuals with low back pain.
Design: Cohort study.
Setting: Rehabilitation.
Participants: This preplanned reanalysis within the Medicine in Spine Exercise Network included 1511 participants with low back pain (57% female, mean age 40.9 years, SD ±14 years).
Interventions: Participants underwent an initial 3-week supervised phase of sensorimotor exercises, followed by a 9-week self-administered phase.
Main outcome measures: Biological, psychological, and social factors potentially impacting training adherence were evaluated. During the supervised phase, adherence was tracked through a standardized training log. During the self-administered phase, adherence was monitored via a diary, with adherence calculated as the percentage of scheduled versus completed sessions. Adherence was analyzed both as an absolute percentage and as a dichotomized variable (adherent vs nonadherent, with a 70% adherence cut-off). Predictors for adherence were identified using Gradient Boosting Machines and Random Forests (R package caret). Seventy percent of the observations were used for training, whereas 30% were retained as a hold-out test-set.
Results: The average overall adherence was 64% (±31%), with 81% (±28%) adherence during the supervised phase and 58% (±39%) in the self-administered phase. The root mean square error for the test-set ranged from 36.2 (R2=0.18, self-administered phase) to 19.3 (R2=0.47, supervised phase); prediction accuracy for dichotomized models was between 64% and 83%. Predictors of low to intermediate adherence included poorer baseline postural control, decline in exercise levels, and fluctuations in pain intensity (both increases and decreases).
Conclusion: Identified predictors could aid in recognizing individuals at higher risk for nonadherence in low back pain exercise therapy settings.
期刊介绍：
The Archives of Physical Medicine and Rehabilitation publishes original, peer-reviewed research and clinical reports on important trends and developments in physical medicine and rehabilitation and related fields. This international journal brings researchers and clinicians authoritative information on the therapeutic utilization of physical, behavioral and pharmaceutical agents in providing comprehensive care for individuals with chronic illness and disabilities.
Archives began publication in 1920, publishes monthly, and is the official journal of the American Congress of Rehabilitation Medicine. Its papers are cited more often than any other rehabilitation journal.
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