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已发表论文
基于健康信念模型的决定因素分析：一项预测中国社区老年人认知障碍的研究
Authors Zhu Q, Xia J, Wang Q, Bai L, Shen C, Yang Y
Received 20 October 2025
Accepted for publication 15 January 2026
Published 22 January 2026 Volume 2026:19 568925
DOI https://doi.org/10.2147/JMDH.S568925
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Veronica Swallow
Qingjiao Zhu,1,2,* Jinjing Xia,3,* Qing Wang,2 Lu Bai,4 Chunxian Shen,5 Ying Yang6
1School of Nursing, Jinzhou Medical University, Jinzhou, 121001, People’s Republic of China; 2Department One of Gynecology, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 3Operating Room, Department of Anesthesiology and Perioperative Medicine, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 4Department of Medical Aesthetics, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 5Department of Infectious Diseases, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 6Department of Rehabilitation Business, The Second Hospital of Huangshi City, Huangshi, 435002, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ying Yang, Department of Rehabilitation Business, The Second Hospital of Huangshi City, No. 102, Qingshanqiao, Huangshigang District, Huangshi, Hubei, 435002, People’s Republic of China, Email hsyangying0706@163.com
Introduction: To investigate the predictive value of psychosocial factors and the Health Belief Model (HBM) for cognitive impairment in community-dwelling older adults, develop a combined prediction model, analyze the mechanistic pathways linking social support, loneliness, and self-efficacy, and evaluate the efficacy of nursing interventions guided by the integrated HBM framework.
Methods: A single-center cross-sectional observational survey enrolled 158 older adults from a community. Participants were categorized into cognitively normal and cognitive impairment groups based on cognitive status. Data collected included demographics, HBM constructs (perceived susceptibility, severity, benefits, barriers, cues to action, and self-efficacy), and psychosocial factors (social support, loneliness). Multivariable logistic regression identified determinants of cognitive impairment. ROC curves assessed the predictive model’s performance, and mediation analysis explored pathways through which psychosocial factors and self-efficacy influence cognitive impairment.
Results: Multivariable analysis identified age, hypertension, perceived barriers, and loneliness as risk factors for cognitive impairment, while educational attainment, exercise ≥ 3 times/week, self-efficacy, and social support as protective factors (P < 0.05). The combined model demonstrated superior predictive accuracy (AUC = 0.951) to single-factor models. Mediation analysis revealed that social support and loneliness primarily exerted direct effects on cognitive impairment, though the mediating role of self-efficacy did not reach statistical significance.
Conclusion: Social support and self-efficacy are significant protective factors against cognitive impairment in community-dwelling older adults, whereas loneliness and perceived barriers are risk factors. A prediction model integrating HBM and psychosocial factors enhances early screening efficacy for community-based cognitive impairment. Nursing interventions leveraging the synergistic HBM framework warrant broader community implementation.
Keywords: cognitive impairment, health belief model, social support, loneliness, SELF-efficacy, combined prediction model
1School of Nursing, Jinzhou Medical University, Jinzhou, 121001, People’s Republic of China; 2Department One of Gynecology, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 3Operating Room, Department of Anesthesiology and Perioperative Medicine, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 4Department of Medical Aesthetics, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 5Department of Infectious Diseases, Suizhou Hospital, Hubei University of Medicine (Suizhou Central Hospital), Suizhou, 441300, People’s Republic of China; 6Department of Rehabilitation Business, The Second Hospital of Huangshi City, Huangshi, 435002, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ying Yang, Department of Rehabilitation Business, The Second Hospital of Huangshi City, No. 102, Qingshanqiao, Huangshigang District, Huangshi, Hubei, 435002, People’s Republic of China, Email hsyangying0706@163.com
Introduction: To investigate the predictive value of psychosocial factors and the Health Belief Model (HBM) for cognitive impairment in community-dwelling older adults, develop a combined prediction model, analyze the mechanistic pathways linking social support, loneliness, and self-efficacy, and evaluate the efficacy of nursing interventions guided by the integrated HBM framework.
Methods: A single-center cross-sectional observational survey enrolled 158 older adults from a community. Participants were categorized into cognitively normal and cognitive impairment groups based on cognitive status. Data collected included demographics, HBM constructs (perceived susceptibility, severity, benefits, barriers, cues to action, and self-efficacy), and psychosocial factors (social support, loneliness). Multivariable logistic regression identified determinants of cognitive impairment. ROC curves assessed the predictive model’s performance, and mediation analysis explored pathways through which psychosocial factors and self-efficacy influence cognitive impairment.
Results: Multivariable analysis identified age, hypertension, perceived barriers, and loneliness as risk factors for cognitive impairment, while educational attainment, exercise ≥ 3 times/week, self-efficacy, and social support as protective factors (P < 0.05). The combined model demonstrated superior predictive accuracy (AUC = 0.951) to single-factor models. Mediation analysis revealed that social support and loneliness primarily exerted direct effects on cognitive impairment, though the mediating role of self-efficacy did not reach statistical significance.
Conclusion: Social support and self-efficacy are significant protective factors against cognitive impairment in community-dwelling older adults, whereas loneliness and perceived barriers are risk factors. A prediction model integrating HBM and psychosocial factors enhances early screening efficacy for community-based cognitive impairment. Nursing interventions leveraging the synergistic HBM framework warrant broader community implementation.
Keywords: cognitive impairment, health belief model, social support, loneliness, SELF-efficacy, combined prediction model