文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

中风患者的电子健康素养:潜在剖面分析及影响因素

E-health literacy in stroke patients: Latent profile analysis and influencing factors.

作者信息

Xue Menghan, Wang Qian, Wang Jiajia, Ge Song, Zhang Zhenxiang, Mei Yongxia

机构信息

School of Nursing and Health, Zhengzhou University, Zhengzhou, People's Republic of China.

Department of Vaccination Clinic, Zhengzhou Yihe Hospital, Zhengzhou, People's Republic of China.

出版信息

J Adv Nurs. 2025 Mar;81(3):1388-1398. doi: 10.1111/jan.16351. Epub 2024 Jul 26.


DOI:10.1111/jan.16351
PMID:39058032
Abstract

AIMS: This study sought to explore latent categories of electronic health (e-health) literacy among stroke patients and analyse its influencing factors. DESIGN: A cross-sectional, descriptive exploratory design with the STROBE reporting checklist was applied. METHODS: Between July and October 2020, 558 stroke participants from three tertiary care hospitals in Henan Province, China, were recruited using a convenience sampling method. A general information questionnaire and the Electronic Health Literacy Scale were used to collect their socio-demographic information and e-health literacy. Latent profile analysis was used to analyse latent categories of e-health literacy in stroke patients. Multiple logistic regression was used to analyse factors influencing latent categories of e-health literacy in stroke patients. RESULTS: Three latent categories of e-health literacy existed, including the low e-health literacy group, the low application-high decision-making group and the high literacy-low decision-making group. Multiple logistic regression showed that education level, presence of comorbidities, willingness to interact with people with mental illness, health information sources, frequency of Internet access, frequency of health information inquiry and willingness to receive remote care were predictors of the participants' latent categories of e-health literacy. CONCLUSION: Three latent categories of e-health literacy in stroke patients exist, and each latent category's characteristics should be considered while developing health education programmes. It is imperative that healthcare providers understand the requirement of creating tailored and efficient health education programmes for various categories of stroke patients to enhance their e-health literacy. IMPACT: It is imperative to improve Chinese stroke patients' overall e-health literacy. We categorized stroke patients' e-health literacy using advanced LPA. These findings hold implications for healthcare approaches, contributing to the enhancement of stroke patients' e-health literacy, enabling them to apply the acquired e-health information to manage and solve their own health issues. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

摘要

目的:本研究旨在探索中风患者电子健康素养的潜在类别,并分析其影响因素。 设计:采用横断面描述性探索性设计,并遵循STROBE报告清单。 方法:2020年7月至10月期间,采用便利抽样法,从中国河南省的三家三级医院招募了558名中风参与者。使用一般信息问卷和电子健康素养量表收集他们的社会人口学信息和电子健康素养。采用潜在剖面分析来分析中风患者电子健康素养的潜在类别。使用多因素logistic回归分析影响中风患者电子健康素养潜在类别的因素。 结果:存在三种电子健康素养潜在类别,包括低电子健康素养组、低应用-高决策组和高素养-低决策组。多因素logistic回归显示,教育水平、合并症的存在、与精神疾病患者互动的意愿、健康信息来源、上网频率、健康信息查询频率以及接受远程护理的意愿是参与者电子健康素养潜在类别的预测因素。 结论:中风患者存在三种电子健康素养潜在类别,在制定健康教育计划时应考虑每个潜在类别的特征。医疗保健提供者必须了解为各类中风患者制定量身定制且高效的健康教育计划的要求,以提高他们的电子健康素养。 影响:提高中国中风患者的整体电子健康素养势在必行。我们使用先进的潜在剖面分析对中风患者的电子健康素养进行了分类。这些发现对医疗保健方法具有启示意义,有助于提高中风患者的电子健康素养,使他们能够应用所获得的电子健康信息来管理和解决自己的健康问题。 患者或公众贡献:无患者或公众贡献。

相似文献

[1]
E-health literacy in stroke patients: Latent profile analysis and influencing factors.

J Adv Nurs. 2025-3

[2]
Variations in health literacy and influential factors affecting the categories of social support among rural patients with diabetes mellitus.

Front Public Health. 2024

[3]
Trajectory patterns and influencing factors of supportive care needs in stroke patients: A longitudinal study.

J Adv Nurs. 2025-2

[4]
Traditional Chinese medicine health literacy among rural older adults: a cross-sectional study.

Front Public Health. 2024

[5]
Exploring Health Literacy Categories in Patients With Heart Failure: A Latent Class Analysis.

J Cardiovasc Nurs.

[6]
Potential profiling of self-management skills in older co-morbid patients.

BMC Geriatr. 2024-6-25

[7]
The relationships between quality of life with health literacy, social support and resilience in older stroke survivors: A structural equation model.

Nurs Open. 2024-9

[8]
Enhancing training transfer among stroke specialist nurses: Insights from latent profile analysis.

Nurse Educ Pract. 2024-11

[9]
Assessment of public literacy in TB prevention and control in the National 13th Five-Year plan for Tuberculosis Prevention and Control (2016-2020) in China.

BMC Health Serv Res. 2025-1-9

[10]
Latent profile and determinants of self-management behaviors among older adult patients with chronic diseases: a cross-sectional study.

Front Public Health. 2025-2-5

引用本文的文献

[1]
Factors that influence technophobia in Chinese older patients with ischemic stroke: a cross-sectional survey.

BMC Geriatr. 2025-8-19

[2]
Patient-centered integration of the treatment and prevention of cardiovascular diseases in the community: a digital intelligence exploration.

Front Med (Lausanne). 2025-7-8

[3]
Relationship Between Stroke Knowledge, Health Information Literacy, and Health Self- Management Among Patients with Stroke: Multicenter Cross-Sectional Study.

JMIR Med Inform. 2025-6-23

[4]
Factors affecting online health information-seeking behavior in young and middle-aged patients with stroke.

PLoS One. 2025-4-28

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索