Evidence map›Paper›PMID 41013303›Full record

ArticleBMC geriatrics2025

The mediating effect of perceived social support between e-health literacy and self-management ability in elderly stroke patients: a cross-sectional survey.

Taotao He, Jing Huang, Caini Song, Conghui Du, Wenxia Zhang, Qunli Zhu, Hongmei Shi

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Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Taotao HeDepartment of Nursing, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), Changsha, 410006, Hunan, China.
Jing Huang *Department of Scientific Research, Hunan Academy of Traditional Chinese Medicine, Changsha, 410006, Hunan, China.
Caini SongDepartment of Nursing, Changsha Central Hospital, Changsha, 410004, Hunan, China.
Conghui DuDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha, 410006, Hunan, China.
Wenxia ZhangSchool of Nursing, Hunan University Of Chinese Medicine, Changsha, 410006, Hunan, China.
Qunli ZhuDepartment of Nursing, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha, 410006, Hunan, China.
Hongmei Shi *Department of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha, 410006, Hunan, China. 18274940066@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-management significantly affects the physical and mental recovery of elderly stroke patients and can improve their quality of life. This study aims to describe the current status and investigate the correlations of e-health literacy, self-management abilities, and perceived social support among elderly stroke patients. Furthermore, it explores the mediating effect of perceived social support on the relationship between e-health literacy and self-management abilities in elderly stroke patients.

methods337 elderly stroke patients from four tertiary hospitals in Hunan Province were recruited via convenience sampling and completed a demographic questionnaire, the eHealth Literacy Scale, the Perceived Social Support Scale, and the Stroke Self-Management Ability Scale, between March and May 2024. Statistical analyses were conducted using independent samples t-test, one-way analysis of variance, Pearson correlation analysis, and the Bootstrap method.

resultsThe total scores for eHealth literacy, self-management ability, and perceived social support among elderly stroke patients were 17.43 ± 8.11, 87.76 ± 13.39, and 55.33 ± 12.09, respectively. The three variables were positively correlated (P < 0.05), and perceived social support partially mediated the relationship between eHealth literacy and self-management ability in elderly stroke patients, accounting for 49.02% of the total effect.

conclusionsIn elderly stroke patients, e-health literacy is low, self-management ability is medium, and perceived social support serves as a partial mediator between them. It was suggested that medical staff focus on the social support system of elderly stroke patients, increase their use of social support, and then improve their e-health literacy for the purpose to provide a solid foundation for promoting their self-management of the disease and enhancing their quality of life.

Indexed as

Health LiteracySelf-ManagementSocial SupportStrokeAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedQuality of LifeSurveys and QuestionnairesTelemedicineElderlyElectronic health literacyPerceived social supportSelf-management abilityStroke

Identifiers

PMID41013303
PMCPMC12465189

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LicenceCC BY-NC-ND
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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.