健康素养
医学
逻辑回归
住所
社会支持
心理干预
老年学
比例(比率)
读写能力
多项式logistic回归
评定量表
人口学
心理学
内科学
精神科
医疗保健
发展心理学
社会学
物理
机器学习
经济
心理治疗师
量子力学
经济增长
计算机科学
教育学
作者
Yujiao Shao,Xuejun Xu,Hongyan Guo,Xiaocui Duan,Zeyu Zhang,Shuang Zhao,Xiumu Yang
标识
DOI:10.3389/fpubh.2025.1477314
摘要
Objective To examine the heterogeneity and determinants of digital health literacy among older adult patients with chronic diseases and provide evidence for targeted interventions. Methods A 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. Results The 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 R 2 = 0.590). Conclusion Digital 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.
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