Evidence map›Paper›PMID 40063939›Full record

SynthesisJournal of medical Internet research2025

Factors Influencing eHealth Literacy Worldwide: Systematic Review and Meta-Analysis.

Zhong Hua, Song Yuqing, Liu Qianwen, Chen Hong

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis 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 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
–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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

32 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
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.

Zhong Hua *Department of Nursing, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-7929-304X
Song Yuqing *Department of Gynecological Nursing, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-2530-6308
Liu QianwenDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China.ORCID 0009-0005-0926-6408
Chen HongDepartment of Nursing, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-1867-1107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundeHealth literacy has increasingly emerged as a critical determinant of health, highlighting the importance of identifying its influencing factors; however, these factors remain unclear. Numerous studies have explored this concept across various populations, presenting an opportunity for a systematic review and synthesis of the existing evidence to better understand eHealth literacy and its key determinants.

objectiveThis study aimed to provide a systematic review of factors influencing eHealth literacy and to examine their impact across different populations.

methodsWe conducted a comprehensive search of papers from PubMed, CNKI, Embase, Web of Science, Cochrane Library, CINAHL, and MEDLINE databases from inception to April 11, 2023. We included all those studies that reported the eHealth literacy status measured with the eHealth Literacy Scale (eHEALS). Methodological validity was assessed with the standardized Joanna Briggs Institute (JBI) critical appraisal tool prepared for cross-sectional studies. Meta-analytic techniques were used to calculate the pooled standardized β coefficient with 95% CIs, while heterogeneity was assessed using I2, the Q test, and τ2. Meta-regressions were used to explore the effect of potential moderators, including participants' characteristics, internet use measured by time or frequency, and country development status. Predictors of eHealth literacy were integrated according to the Literacy and Health Conceptual Framework and the Technology Acceptance Model (TAM).

resultsIn total, 17 studies met the inclusion criteria for the meta-analysis. Key factors influencing higher eHealth literacy were identified and classified into 3 themes: (1) actions (internet usage: β=0.14, 95% CI 0.102-0.182, I2=80.4%), (2) determinants (age: β=-0.042, 95% CI -0.071 to -0.020, I2=80.3%; ethnicity: β=-2.613, 95% CI -4.114 to -1.112, I2=80.2%; income: β=0.206, 95% CI 0.059-0.354, I2=64.6%; employment status: β=-1.629, 95% CI -2.323 to -0.953, I2=99.7%; education: β=0.154, 95% CI 0.101-0.208, I2=58.2%; perceived usefulness: β=0.832, 95% CI 0.131-1.522, I2=68.3%; and self-efficacy: β=0.239, 95% CI 0.129-0.349, I2=0.0%), and (3) health status factor (disease: β=-0.177, 95% CI -0.298 to -0.055, I2=26.9%).

conclusionsThis systematic review, guided by the Literacy and Health Conceptual Framework model, identified key factors influencing eHealth literacy across 3 dimensions: actions (internet usage), determinants (age, ethnicity, income, employment status, education, perceived usefulness, and self-efficacy), and health status (disease). These findings provide valuable guidance for designing interventions to enhance eHealth literacy.

trial registrationPROSPERO CRD42022383384; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022383384.

Indexed as

Health LiteracyTelemedicineFemaleHumansconsumerdigital healtheHealtheHealth literacyLiteracy and Health Conceptual Frameworkmeta-analysissocial determinants of healthTechnology Acceptance Model

Identifiers

PMID40063939
PMCPMC11933766

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.