Evidence map›Paper›PMID 40269916›Full record

ArticleBMC public health2025

Promote citizen engagement with warnings - an empirical examination of government social media accounts during public health crises.

Yanan Guo, Jida Liu, Chenxi Lian

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Cute Communication: Can Cute Discourse Be Used in Risk Communication?Behavioral sciences (Basel, Switzerland) · 2025
    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

3 authors.

Yanan GuoSchool of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China. b2341245@ustb.edu.cn.
Jida LiuSchool of Economics and Management, Harbin Institute of Technology, Harbin, 150010, China.
Chenxi LianSchool of Public Finance and Management, Yunnan University of Finance and Economics, Kunming, 650000, China.

Funding

National Natural Science Foundation of China No.72404024the China postdoctoral Science Foundation No. 2024M750190the Program of the Postdoctoral Fellowship Program of CPSF No.GZB20240059
6 · The paper itself

Abstract

backgroundEffective warnings are important for preventing the spread of disease during the early stages of outbreaks. Social media serves as a valuable platform for disseminating warning messages. The success of warnings issued through government social media accounts (GSMAs) depends on citizen engagement. However, an incomplete understanding of the relationship between warning messages and audience responses has hindered the design of crisis communication strategies.

methodsWe investigated the factors affecting citizen engagement with warnings on GSMAs during public health crises. Drawing on the Elaboration Likelihood Model (ELM) and the Crisis and Emergency Risk Communication (CERC) framework, model was developed to analyze the effects of central routes (content features) and peripheral routes (microstructural and source features) on citizen engagement, as well as the moderating effect of disease type. Data were collected from 38 Sina Weibo accounts of government agencies in China during two public health crises: COVID-19 and H1N1. Logit regression analysis was conducted to test the hypothesized relationships.

resultsThe results indicate that (1) positive emotional tendencies and more warning elements are associated with citizen engagement; (2) the relationship between message length and citizen engagement follows an inverted U-shape; (3) media richness and information style variety significantly enhance citizen engagement; and (4) disease type (emerging vs. reemerging infectious diseases) moderates the relationships between media richness, information style variety, source influence, and citizen engagement.

conclusionsGiven that issuing warnings is critical to emergency management, our findings provide significant theoretical and practical insights, particularly for improving early government-public communication through social media platforms.

trial registrationNot applicable.

Indexed as

Community ParticipationCOVID-19Health CommunicationPublic HealthSocial MediaChinaHumansCitizen engagementGovernment social media accountPublic health crisesRisk communicationWarning messages

Identifiers

PMID40269916
PMCPMC12016071

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LicenceCC BY-NC-ND
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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.