Evidence map›Paper›PMID 42668793›Full record

ArticlePakistan journal of medical sciences2026

Latent Class Analysis of eHealth Literacy in Patients with Acute Coronary Syndrome: Associations with Secondary Prevention Medication Adherence and Care Dependency.

Mengxi He, Ru Ye, Linglong Chen, Aidi Pan

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mengxi HeMengxi He, Department of Emergency, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang, China.
Ru YeRu Ye, Department of Emergency, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang, China.
Linglong ChenLinglong Chen, Department of Emergency, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang, China.
Aidi PanAidi Pan, Department of Emergency, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Acute coronary syndromeCare dependencyeHealth literacyLatent classesSecondary prevention medication adherence

Identifiers

PMID42668793
PMCPMC13525523

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