Evidence map›Paper›PMID 42291770›Full record

ArticleDigital health

Latent profile analysis of digital health literacy among community-dwelling older adults and its influencing factors.

Bailiang Wu, Chunyan Jin, Jin Zheng

Abstract read
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Article in Digital health. 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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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

3 authors.

Bailiang WuInstitute of Social work and Community governance, Chengdu University of Information Technology Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0002-9786-9855
Chunyan JinCollege of education sciences, Leshan Normal University, Leshan, Sichuan, China.ORCID https://orcid.org/0000-0001-8756-8552
Jin ZhengInstitute of Traditional Chinese Medicine, Sichuan Academy of Chinese Medicine Sciences Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0009-4502-4229

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital health advances universal health coverage, yet insufficient digital health literacy exacerbates the digital divide and health inequalities among older adults. Existing studies lack in-depth exploration of within-group digital health literacy heterogeneity among Chinese community-dwelling older adults. This study aimed to identify digital health literacy latent profiles and associated factors to inform targeted interventions. Methods: A cross-sectional survey was conducted among 535 community-dwelling older adults (aged ≥60 years) from urban and suburban communities in China. Latent profile analysis was used to identify digital health literacy subgroups based on three core subdomains: Self-Perception (SP), Information Acquisition (IA), and Interactive Judgment (IJ). Multinomial logistic regression was applied to examine factors associated with profile membership. Results: Three distinct digital health literacy profiles were identified: Low SP-IA-IJ (38.88%), Medium SP-IA & Low IJ (47.85%), and High SP-IA & Medium IJ (13.27%). Notably, Interactive Judgment (IJ) was a universal weak dimension across all groups. Older age, cognitive decline, depressive symptoms, and loneliness were significant risk factors; higher education, better economic status, favorable self-rated health, and stronger social interaction were protective factors, with differential associations across profiles. Conclusions: Overall digital health literacy among Chinese community-dwelling older adults is generally low with significant within-group heterogeneity. Targeted stratified interventions, universal Interactive Judgment (IJ) capacity building, and age-friendly digital environment optimization can help narrow the digital divide and promote equitable access to digital health services for older adults. This study is limited by its cross-sectional design and regional urban/suburban sample, restricting causal inference and generalizability to rural or other regions.

Indexed as

Chinadigital dividedigital health literacylatent profile analysisolder adults

Identifiers

PMID42291770
PMCPMC13263505

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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.