Evidence map›Paper›PMID 41179753›Full record

ArticleFrontiers in public health2025

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

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

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Lan Yang *Department of Nephrology, Baoding No. 1 Central Hospital, Baoding, Hebei, China.
Jinghua Yang *Internal Medicine-Cardiovascular Department, Dongzhimen Hospital of Beijing University of Chinese Medicine, Beijing, China.
Hong ZhangDepartment of Nephrology, Baoding No. 1 Central Hospital, Baoding, Hebei, China.
Ning WuDepartment of Nephrology, Baoding No. 1 Central Hospital, Baoding, Hebei, China.
Xuejiao HanDepartment of Nephrology, Baoding No. 1 Central Hospital, Baoding, Hebei, China.
Na LiDepartment of Nephrology, Baoding No. 1 Central Hospital, Baoding, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite 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). Objective: This study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL). Methods: A 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. Results: This 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 Conclusion: The 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.

Indexed as

Health LiteracyHealth PromotionHealthy LifestyleRenal DialysisAdultAgedChinaFemaleHumansMaleMiddle AgedSurveys and Questionnairese-health literacyhealth-promoting lifestylelatent profile analysismaintenance hemodialysisquality of life

Identifiers

PMID41179753
PMCPMC12575380

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.