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Published on: November 8, 2013
Development of a Multivariable Predictive Model for Adherence to Remotely Monitored Home-Based Pulmonary
Sheng Ye1, Zi Chen2, Dandan Zhang3
1Department of Respiratory and Critical Care Medicine, Nanjing BenQ Medical Center, The Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
Purpose:
This study aimed to explore factors affecting adherence to remote home-based pulmonary rehabilitation (PR) in patients with stable chronic obstructive pulmonary disease (COPD) and to develop a predictive model.
Patients And Methods:
This multicenter, cross-sectional survey study included 86 patients who underwent 12 weeks of health education-integrated, home-based PR with remote monitoring. Patients were stratified into high-completion (HC, ≥ 70%) and low-completion (LC, < 70%) groups. Demographic data, clinical features, and psychological parameters were analyzed. Receiver operating characteristic curve and area under the curve (AUC) analyses evaluated the predictive performance of key indicators. Binary logistic regression identified four predictors: Pulmonary Rehabilitation Adapted Index of Self-Efficacy (PRAISE), Outcome Expectations for Exercise Scale (OEE), Montreal Cognitive Assessment (MoCA), and Visual Analog Scale (VAS). These components formed an optimized predictive model with corresponding formula and cutoff values.
Results:
A cross-sectional survey of 71 patients, 44 in the HC group and 27 in the LC group, revealed significantly higher scores in the HC group in the following domains of the 36-Item Short Form Health Survey (SF-36), including physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, mental health, and social functioning, as well as in the MoCA scores (all p-values < 0.05). Significant intergroup differences were also observed in PRAISE, OEE and VAS scores (all p < 0.001). PRAISE (AUC = 0.810), OEE (AUC = 0.784), MoCA (AUC = 0.719), and VAS (AUC = 0.801) demonstrated discriminatory power in assessing PR adherence. The combined predictive model achieved an AUC of 0.895 (95% confidence interval: 0.812-0.977, p < 0.05), with 77.8% sensitivity and 93.2% specificity.
Conclusion:
Social cognitive theory (SCT) originated from social learning theory. It explains human behavior through a triadic, dynamic, and reciprocal model. This model posits continuous interaction among an individual's behavior, cognitive factors, and environmental context. The four-variable predictive model, based on SCT, effectively evaluates adherence to home-based PR under remote monitoring in patients with COPD. Among the indicators in the four-variable model, PRAISE shows potential as a target for intervention to enhance PR completion rates.
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