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ORIGINAL RESEARCH article

Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1506545
This article is part of the Research Topic Health Literacy and Digital Health Literacy among Older Adults: Public Health Interventions View all 14 articles

Latent Profile and Determinants of Self-Management Behaviors Among Elderly Patients with Chronic Diseases ：A Cross-Sectional Study

Provisionally accepted
Yujiao Shao Yujiao Shao 1XiaoCui Duan XiaoCui Duan 1Xuejun Xu Xuejun Xu 1Hongyan Guo Hongyan Guo 2Zeyu Zhang Zeyu Zhang 3Shuang Zhao Shuang Zhao 4Fuzhi Wang Fuzhi Wang 1Yongxia Chen Yongxia Chen 2Qin Chen Qin Chen 5Shiqing Zhang Shiqing Zhang 1Xiumu Yang Xiumu Yang 1,6*
  • 1 Bengbu Medical College, Bengbu, China
  • 2 First Affiliated Hospital, Bengbu Medical College, bengbu, China
  • 3 The 902nd Hospital of Joint Logistic Support Force of PLA, Bengbu, China
  • 4 First People's Hospital Affiliated with Bengbu Medical College, Bengbu, China
  • 5 Suzhou Hospital Affiliated with Anhui Medical University, Suzhou, China
  • 6 University of Science and Technology of China, Hefei, Anhui Province, China

The final, formatted version of the article will be published soon.

    To explore latent profiles of self-management behaviors in elderly patients with chronic diseases and identify the factors that influence different profiles, guiding targeted interventions. Methods: This study used convenience sampling to recruit 536 elderly patients with chronic diseases from three tertiary hospitals in Anhui Province between October 2023 and May 2024. Data were collected using a general information questionnaire, the age-adjusted Charlson Comorbidity Index (aCCI), the Chronic Disease Self-Management Behavior Scale, the Chronic Disease Management Self-Efficacy Scale, the Psychological Status Scale, the Digital Health Literacy Scale, and the Social Support Scale. Latent profile analysis was conducted using Mplus 8.3, and univariate and multivariate logistic regression analyses were performed using SPSS 26.0.Results: Three profiles of self-management behaviors emerged: "Low Self-Management" (50.2%), "High Exercise and Cognitive Management" (8.6%), and "Moderate Management with Enhanced Communication" (41.2%). Multivariate logistic regression revealed that residence, aCCI, number of digital devices used, perceived usefulness of digital health information, digital health literacy, social support, chronic disease management self-efficacy, and psychological status were significant factors affecting self-management profiles (all p < 0.05). Conclusion: Self-management behaviors in elderly patients with chronic diseases were generally low, with substantial heterogeneity across profiles. Healthcare providers should tailor interventions based on the characteristics of each group to enhance self-management in digital health contexts.

    Keywords: Elderly, chronic diseases, self-management, Influencing factors, latent profile analysis

    Received: 05 Oct 2024; Accepted: 13 Jan 2025.

    Copyright: © 2025 Shao, Duan, Xu, Guo, Zhang, Zhao, Wang, Chen, Chen, Zhang and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xiumu Yang, Bengbu Medical College, Bengbu, China

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