Evidence map›Paper›PMID 41769106›Full record

ArticleFrontiers in public health2026

The impact of digital literacy on health behaviors among middle-aged and older adults: the mediating roles of proactive health awareness and social capital.

Xue Tang, Huiyan Peng, Jie Li, Mingshu Si

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xue TangSchool of Public Administration and Sociology, Jiangsu Normal University, Xuzhou, China.
Huiyan PengSchool of Public Administration and Sociology, Jiangsu Normal University, Xuzhou, China.
Jie LiDepartment of Social Medicine and Health Management, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Mingshu SiSchool of Health Management, Fujian Medical University, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid acceleration of population aging in China, promoting healthy behaviors among middle-aged and older adults has become an urgent public health priority. Digital literacy, as a key skill in the digital era, may influence health behaviors directly or indirectly through psychological and social pathways. This study analyzes the impact of digital literacy on health behaviors among middle-aged and older adults, focusing on the mediating roles of proactive health awareness and social capital. Methods: Using data from the 2021 Chinese General Social Survey (CGSS), this study constructed a composite digital literacy index based on the entropy weight method. A total of 1,458 respondents aged 45 and above were included. Health behaviors were measured by dietary and exercise indicators, while proactive health awareness and social capital were modeled as mediators. Ordinary least squares regression, ordinal logistic regression, and ordered probit regression were applied to analyse the direct and indirect effects of digital literacy on health behaviors. Results: Digital literacy had no significant direct effect on health behaviors ( Conclusion: Among middle-aged and older Chinese adults, digital literacy appears to influence health behaviors mainly by enhancing health awareness and expanding social support. These findings imply that interventions to promote healthy aging should combine digital skills training with health education and community support networks. The observed age differences suggest that such strategies may need to be tailored to different age groups.

Indexed as

Health BehaviorHealth Knowledge, Attitudes, PracticeHealth LiteracySocial CapitalAgedChinaDigital HealthFemaleHumansMaleMiddle Ageddigital literacyhealth behaviormiddle-aged and older adultsproactive health awarenesssocial capital

Identifiers

PMID41769106
PMCPMC12935962

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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.