eHealth literacy in older patients with cardiovascular disease: latent profile analysis and associated factors.

OBJECTIVE: This study aimed to explore the potential latent categories of electronic health (eHealth) literacy among older patients with cardiovascular diseases and analyze the factors associated with eHealth literacy profiles. METHODS: From November 1, 2025 to April 15, 2026, we employed the convenience sampling method to conduct a survey on a total of 459 patients from a tertiary A hospital in China. The demographic information questionnaire and the Electronic Health Literacy Scale were employed to collect the sociodemographic information and eHealth literacy. Latent profile analysis was utilized to identify the latent categories of eHealth literacy among older patients with cardiovascular diseases. Univariate analysis and multivariate logistic regression analysis were conducted to explore factors associated with latent eHealth literacy profiles among these patients. RESULTS: The mean total e-HEALS score was (25.16 ± 5.59), with mean scores of (15.59 ± 3.75), (6.41 ± 1.52), and (3.16 ± 0.96) for application ability, judgment ability, and decision-making ability, respectively. Latent profile analysis identified three distinct categories: low (28.3%), medium (50.3%), and high eHealth literacy (21.4%), demonstrating significant heterogeneity. Multivariate logistic regression showed that higher education level, more frequent Internet use, higher frequency of health information inquiry, regular physical activity, and greater perceived social support were positively associated with medium and high literacy categories, whereas advanced age and higher comorbidity burden were negatively associated. CONCLUSION: Older patients with cardiovascular diseases exhibit heterogeneous and generally moderate-to-low eHealth literacy. Individual behaviors and social support factors were associated with different eHealth literacy profiles, highlighting the need for tailored, multidimensional interventions and the development of disease-specific assessment tools to improve digital health engagement and self-management in this population.