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已发表论文
慢性阻塞性肺疾病患者远程监测家庭肺康复依从性的多变量预测模型的开发
Authors Ye S, Chen Z, Zhang D , Xia T, Wang C, Xu B, Li Q, Wang C, Zhang Y, Yin Z, Wang J
Received 15 April 2025
Accepted for publication 10 September 2025
Published 7 October 2025 Volume 2025:20 Pages 3361—3375
DOI https://doi.org/10.2147/COPD.S534600
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Vanesa Bellou
Sheng Ye,1,* Zi Chen,2,* Dandan Zhang,3,* Tingting Xia,2,* Caihua Wang,2,4,* Biyun Xu,5 Qin Li,6 Cheng Wang,1 Ye Zhang,1 Zhifei Yin,7 Jinfan Wang8
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; 2Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 3Department of Respiratory, Geriatric hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Intensive Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 5Medical Statistics and Analysis Center, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China; 6Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA; 7Rehabilitation Medicine Center, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 8The NMU Research Center for Doctor-Patient Communication, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Jinfan Wang, The NMU Research Center for Doctor-Patient Communication, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu, 211166, People’s Republic of China, Tel +86-13912996067, Email yhgt2013@njmu.edu.cn Zhifei Yin, Rehabilitation Medicine Center, The First Affiliated Hospital, Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, People’s Republic of China, Tel +86-13813958128, Email feifei44881@sina.com
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.
Keywords: pulmonary rehabilitation, remote monitoring, social cognitive theory, predictive model, chronic obstructive pulmonary disease, patient compliance
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; 2Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 3Department of Respiratory, Geriatric hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Intensive Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 5Medical Statistics and Analysis Center, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China; 6Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA; 7Rehabilitation Medicine Center, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 8The NMU Research Center for Doctor-Patient Communication, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Jinfan Wang, The NMU Research Center for Doctor-Patient Communication, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu, 211166, People’s Republic of China, Tel +86-13912996067, Email yhgt2013@njmu.edu.cn Zhifei Yin, Rehabilitation Medicine Center, The First Affiliated Hospital, Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, People’s Republic of China, Tel +86-13813958128, Email feifei44881@sina.com
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.
Keywords: pulmonary rehabilitation, remote monitoring, social cognitive theory, predictive model, chronic obstructive pulmonary disease, patient compliance