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Latent Class Analysis of eHealth Literacy in Patients with Acute Coronary Syndrome: Associations with Secondary
Mengxi He1, Ru Ye2, Linglong Chen3
1Mengxi He, Department of Emergency, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang, China.
Objective:
To investigate the latent classes of eHealth literacy in patients with acute coronary syndrome(ACS) and their associations with secondary prevention medication adherence and care dependency.
Methodology:
This was a retrospective study. A cross-sectional survey was conducted on 142 ACS patients admitted to the Emergency Department of Wenzhou People's Hospital from January 2024 to November 2025, via convenience sampling method. Data were retrospectively extracted from the hospital's electronic medical record(EMR) system. Latent class analysis (LCA), univariate analysis, and multivariate logistic regression analysis were applied to identify the latent classes of eHealth literacy and examine their associations with secondary prevention medication adherence and care dependency.
Results:
Three eHealth literacy subgroups were identified: low (23.24%), moderate (50.00%), and high (26.76%). Age, education, stress, insurance, medication adherence, and care dependency were significant influencing factors(P< 0.05).
Conclusion:
Acute coronary syndrome(ACS) patients showed heterogeneity in eHealth literacy latent classes. eHealth literacy was positively correlated with medication adherence and negatively correlated with care dependency, which were influenced by age, education, stress, insurance type, medication adherence and care dependency.
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