Evidence map›Paper›PMID 40735546›Full record

ArticleDigital health

Research on the impact mechanism of health information quality in the social media environment: An analysis based on meta-ethnography and DEMATEL-ISM.

Xing Zhai, Qinxiang Wang, Yaqing Nie, Aiqing Han, Ruifeng Li

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. 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

5 authors.

Xing ZhaiSchool of Management, Beijing University of Chinese Medicine, Beijing, China.
Qinxiang WangXi'an Children's Hospital, Xi'an, China.ORCID https://orcid.org/0000-0002-2916-3829
Yaqing NieSchool of Management, Beijing University of Chinese Medicine, Beijing, China.ORCID https://orcid.org/0009-0004-4637-120X
Aiqing HanSchool of Management, Beijing University of Chinese Medicine, Beijing, China.ORCID https://orcid.org/0000-0002-1087-0873
Ruifeng LiSchool of Management, Beijing University of Chinese Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To systematically investigate the key determinants influencing health information quality in social media environments and elucidate their hierarchical relationships, thereby providing evidence-based guidance for quality improvement. Methods: This study employed an innovative integration of meta-ethnography and Decision-Making Trial and Evaluation Laboratory-Interpretive Structural Modeling (DEMATEL-ISM) methodologies. Through systematic extraction and multi-dimensional analysis of influencing factors-including centrality metrics, causal relationships, and hierarchical structures-we developed a comprehensive mechanism model clarifying factor interactions and their cumulative impacts on health information quality enhancement. Results: Our analysis identified 18 critical factors affecting health information quality, which were categorized into six distinct hierarchical levels through rigorous computational modeling. The results revealed complex cross-level interactions and mutual influences among these determinants. Nine core factors emerged as pivotal: information accuracy, authority orientation, platform reputation, creator expertise, information utility, health information literacy, content originality, source authority, and health concepts. Conclusion: The findings establish a hierarchical quality improvement framework, suggesting that targeted interventions focusing on the nine core factors can significantly enhance health information quality in social media ecosystems. This study provides both theoretical foundations and practical insights for multi-stakeholder collaborative governance in digital health communication.

Indexed as

DEMATEL-ISMhealth information qualityinfluence mechanismmeta-ethnographySocial media

Identifiers

PMID40735546
PMCPMC12304623

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Registered trials

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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.