AUTHOR=Yang Lan , Yang Jinghua , Zhang Hong , Wu Ning , Han Xuejiao , Li Na 

TITLE=Latent profile analysis of electronic health literacy and its impact on health promoting lifestyles among maintenance hemodialysis patients

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1630350

DOI=10.3389/fpubh.2025.1630350

ISSN=2296-2565

ABSTRACT=BackgroundDespite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. However, there remains a significant gap in studies specifically addressing the eHL needs of patients with maintenance hemodialysis (MHD).ObjectiveThis study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL).MethodsA survey was conducted using a convenience sampling method involving 500 MHD patients from three tertiary hospitals in Baoding. Data were analyzed using latent profile analysis (LPA) and a mixed regression model.ResultsThis study showed that MHD patients could be classified into low (23.17%), middle (49.78%), and high (27.05%) eHL groups, with the three-class model showing optimal fit (AIC = 2321.213, BIC = 2271.168, entropy = 0.967). MHD Patients in the high literacy group scored significantly higher in all dimensions of e-HL and overall HPL (119.58 ± 13.86) compared to those in the low literacy group (91.82 ± 11.73) (all p < 0.001). Multivariate analysis identified high educational level (OR = 1.512), higher average monthly household income (OR = 1.511), longer dialysis duration (OR = 1.314), and self-management abilities (OR = 1.243) as independent predictors of eHL.ConclusionThe findings suggest a heterogeneous stratification of eHL among MHD patients, closely linked to HPL. Stratified intervention strategies should be developed for different patient groups to potentially improve their health behaviors. The study provides evidence-based support for personalized health management.