Evidence map›Paper›PMID 42548714›Full record

ArticleFrontiers in public health2026

Misleading health risk information and public health decision-making on digital platforms: evidence from tech-fearmongering food production short videos.

Qiong Zhao, Haochen Yu, Xiaoyu Chen

Abstract read
In one paragraph

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. Not yet cited in PubMed.

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Qiong ZhaoShanghai Institute of Visual Arts, Shanghai, China.
Haochen YuSocial Research Institute, University College London, London, United Kingdom.
Xiaoyu ChenLaw School, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital platforms have become important channels for public health risk information and everyday health decision-making. Misleading risk information may distort public risk cognition, weaken trust in regulatory systems, and reshape protective behavioral intentions. Methods: Grounded in Protection Motivation Theory, this study examined tech-fearmongering food production short videos as a case of misleading health risk information in platform environments. A scenario-based experimental design was used with 487 valid responses from Chinese internet users. Single-mediator and parallel multiple mediator models were estimated using PROCESS Model 4 with 5,000 bootstrap resamples to test the mediating roles of health threat appraisal, negative emotions, and trust erosion. Results: Cognitive, affective, and social trust pathways all contributed to the mechanism linking misleading risk information to public health decision-making. In the parallel mediation model, health threat appraisal and trust erosion showed unique significant indirect effects on public risk cognition, while health threat appraisal was the dominant unique mediator for protective behavioral intention. Conclusion: Tech-fearmongering food production short videos can influence public health decision-making through health threat appraisal, negative emotions, and trust erosion. Digital health risk information governance should address emotional reactions and trust erosion in addition to cognitive threat appraisal, with implications for platform governance, health risk communication, and public health information quality control.

Indexed as

Decision MakingPublic HealthAdultChinaDigital MediaFemaleHumansInternetMedia ExposureRisk AssessmentTrustVideo Recordingdigital public healthhealth risk informationnegative emotionsplatform governanceprotective behavioral intentionpublic health decision-makingrisk communicationtrust erosion

Identifiers

PMID42548714
PMCPMC13429709

What OpenQuestion holds

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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.