Front Public Health. 2026 Jun 2;14:1822855. doi: 10.3389/fpubh.2026.1822855. eCollection 2026.
ABSTRACT
BACKGROUND: Heart failure (HF) management imposes a substantial multidimensional treatment burden (BoT) on older adults. While digital health interventions offer potential solutions, their success heavily depends on patients' eHealth literacy (eHL). Previous variable-centered research evaluating total scale scores has systematically masked the individual heterogeneity and dimensional interplay between eHL and BoT.
OBJECTIVE: To identify the multidimensional latent profiles of eHealth literacy and treatment burden among older adults with chronic HF, and to explore the independent sociodemographic and clinical predictors of these profiles.
METHODS: A cross-sectional study was conducted involving 425 older adults with HF in China. Data were collected using demographic/clinical abstraction forms, the Chinese eHealth Literacy Scale (C-eHEALS), and the Patient Experience with Treatment and Self-Management (PETS). Latent profile analysis (LPA) was executed using 14 specific continuous dimensional indicators from these scales. Multinomial logistic regression was utilized to identify factors influencing profile membership.
RESULTS: Three distinct latent profiles were identified. As visually supported by the standardized Z-score patterns, the "Vulnerable" profile (28.9%) exhibited a starkly inverse clinical state characterized by profound deficits across all eHL dimensions and overwhelmingly high systemic BoT. The "Capable" profile (22.1%) demonstrated the opposite, optimal pattern (high eHL, minimal BoT). The "Transitional" profile (48.9%) displayed intermediate scores but high dimensional discordance (e.g., adequate information acquisition but poor evaluation, paired with high diet/exercise burdens). Multinomial logistic regression revealed that older age, primary-level education, living alone, and a higher Charlson Comorbidity Index were significant independent predictors of membership in the Vulnerable profile.
CONCLUSION: Older adults with HF do not experience digital health demands and self-care workloads uniformly. Identifying these highly distinct, dimension-specific typologies highlights the potential value of moving away from "one-size-fits-all" digital deployments toward precision-based, stratified care models designed to mitigate specific vulnerabilities.
PMID:42311985 | PMC:PMC13268896 | DOI:10.3389/fpubh.2026.1822855