Evidence map›Paper›PMID 40138681›Full record

ArticleJournal of medical Internet research2025

Decomposition and Comparative Analysis of Urban-Rural Disparities in eHealth Literacy Among Chinese University Students: Cross-Sectional Study.

Yao Yu, Zhenning Liang, Qingping Zhou, Yusupujiang Tuersun, Siyuan Liu, Chenxi Wang, Yuying Xie, Xinyu Wang, Zhuotong Wu, Yi Qian

Abstract readComparative Study
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
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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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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Yao Yu *School of Health Management, Southern Medical University, Guangzhou, China.ORCID 0009-0005-0456-6831
Zhenning Liang *School of Health Management, Southern Medical University, Guangzhou, China.ORCID 0009-0006-9498-7847
Qingping Zhou *School of Health Management, Southern Medical University, Guangzhou, China.ORCID 0009-0003-0831-766X
Yusupujiang TuersunSchool of Health Management, Southern Medical University, Guangzhou, China.ORCID 0000-0003-4865-8306
Siyuan LiuSchool of Public Health, Southern Medical University, Guangzhou, China.ORCID 0000-0003-4740-0581
Chenxi WangSchool of Health Management, Southern Medical University, Guangzhou, China.ORCID 0009-0007-9644-5627
Yuying XieShenzhen Longhua Maternity and Child Health Hospital, Shenzhen, China.ORCID 0009-0008-1827-054X
Xinyu WangSchool of Public Health, Southern Medical University, Guangzhou, China.ORCID 0009-0001-4640-3441
Zhuotong WuSchool of Public Health, Southern Medical University, Guangzhou, China.ORCID 0009-0001-0683-9064
Yi QianSchool of Health Management, Southern Medical University, Guangzhou, China.ORCID 0000-0002-3873-8014

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health care is rapidly expanding in China, making the enhancement of eHealth literacy a crucial strategy for improving public health. However, the persistent urban-rural divide may contribute to disparities in eHealth literacy between urban and rural university students, potentially affecting their health-related behaviors and outcomes.

objectiveThis study aims to examine disparities in eHealth literacy between university students in urban and rural China, identifying key influencing factors and their contributions. The findings will help bridge these gaps, promote social equity, enhance overall health and well-being, and inform future advancements in the digital health era.

methodsThe eHealth Literacy Scale (eHEALS) was used to assess eHealth literacy levels among 7230 university students from diverse schools and majors across 10 regions, including Guangdong Province, Shanghai Municipality, and Jiangsu Province. Descriptive statistics summarized demographic, sociological, and lifestyle characteristics. Chi-square tests examined the distribution of eHealth literacy between urban and rural students. A binary logistic regression model identified key influencing factors, while a Fairlie decomposition model quantified their contributions to the observed disparities.

resultsThe average eHealth literacy score among Chinese university students was 29.22 (SD 6.68), with 4135 out of 7230 (57.19%) scoring below the passing mark. Rural students had a significantly higher proportion of inadequate eHealth literacy (2837/4510, 62.90%) compared with urban students (1298/2720, 47.72%; P<.001). The Fairlie decomposition analysis showed that 71.4% of the disparity in eHealth literacy was attributable to urban-rural factors and unobserved variables, while 28.6% resulted from observed factors. The primary contributors were monthly per capita household income (13.4%), exercise habits (11.7%), and 9-item Patient Health Questionnaire (PHQ-9) scores (2.1%).

conclusionsRural university students exhibit lower eHealth literacy levels than their urban counterparts, a disparity influenced by differences in socioeconomic status, individual lifestyles, and personal health status. These findings highlight the need for targeted intervention strategies, including (1) improving access to eHealth resources in rural and underserved areas; (2) fostering an environment that encourages physical activity to promote healthy behaviors; (3) expanding school-based mental health services to enhance health information processing capacity; and (4) implementing systematic eHealth literacy training with ongoing evaluation. These strategies will support equitable access to and utilization of eHealth resources for all students, regardless of their geographic location.

Indexed as

Health LiteracyRural PopulationStudentsTelemedicineUrban PopulationAdolescentAdultChinaCross-Sectional StudiesFemaleHumansMaleUniversitiesYoung AdulteHealth literacyFairlie decomposition modelhealth equityuniversity studentsurban-rural disparities

Identifiers

PMID40138681
PMCPMC11982776

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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.