Latent profile and determinants of digital health literacy among older adult patients with chronic diseases: a cross-sectional study

ObjectiveTo examine the heterogeneity and determinants of digital health literacy among older adult patients with chronic diseases and provide evidence for targeted interventions.MethodsA convenience sample of 536 older adult patients with chronic diseases was recruited from three tertiary hospitals...

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Main Authors: Yujiao Shao, Xuejun Xu, Hongyan Guo, Xiaocui Duan, Zeyu Zhang, Shuang Zhao, Xiumu Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Public Health
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Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1477314/full
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Summary:ObjectiveTo examine the heterogeneity and determinants of digital health literacy among older adult patients with chronic diseases and provide evidence for targeted interventions.MethodsA convenience sample of 536 older adult patients with chronic diseases was recruited from three tertiary hospitals in Anhui Province between October 2023 and May 2024. Data were collected using structured questionnaires, including the Digital Health Literacy Assessment Scale, Social Support Rating Scale, General Self-Efficacy Scale, Brief Symptom Rating Scale, Brief Illness Perception Questionnaire, and the age-adjusted Charlson Comorbidity Index. Latent profile analysis (LPA) was conducted in Mplus 8.3. Univariate and multivariate logistic regression analyses were performed using SPSS 26.0 to identify literacy profiles and their associated factors.ResultsThe mean digital health literacy score was 41.36 (SD = 12.8), with an average item score of 2.76 (SD = 0.85). LPA identified three profiles: C1—Low Literacy, Passive Interaction (n = 142, 26.5%); C2—Moderate Literacy, Limited Interaction (n = 276, 51.5%); and C3—High Literacy, Active Interaction (n = 118, 22.0%). Multinomial logistic regression analysis showed that residence, participation in chronic disease health education, daily internet use, perceived ease of use and usefulness of digital health information, general self-efficacy, and social support were significant independent predictors of profile membership (p < 0.05). The model explained approximately 59.0% of the variance in profile classification (Nagelkerke R2 = 0.590).ConclusionDigital health literacy among older adult patients with chronic diseases was generally low, particularly in interactive skills, with significant heterogeneity across subgroups. Tailored strategies that address the unique needs of each profile are essential to improve digital health literacy in this population.
ISSN:2296-2565