Evidence map›Paper›PMID 40531981›Full record

ArticlePloS one2025

Identifying determinants for promoting public engagement via Chinese E-government TikTok in public health emergencies.

Jingjing Guo, Julia Wirza Mohd Zawawi, Syafila Kamarudin

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Jingjing GuoFaculty of Modern Languages and Communication, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.ORCID 0009-0008-5396-0394
Julia Wirza Mohd ZawawiFaculty of Modern Languages and Communication, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Syafila KamarudinInstitute for Social Science Studies, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media have become vital tools for governments during public health crises, enabling the timely dissemination of critical information, health guidance, and public engagement. In China, public engagement through social media, particularly TikTok, presents unique challenges during crises. This study investigates the factors that predict public engagement via the Chinese government's TikTok during a public health emergency, focusing on the roles of information quality, source credibility, multiple cues, immediate feedback, and trust as a mediating variable.

methodsThe study is grounded in the Elaboration Likelihood Model (ELM) and Media Richness Theory (MRT) to frame the relationships between these variables. Data were collected through an online questionnaire survey employing convenience sampling, involving 614 respondents aged 18-40 from Hebei Province, China. Descriptive statistical analysis was performed using SPSS, and Structural Equation Modeling (SEM) was employed to test the hypotheses.

resultsThe findings indicate that information quality and immediate feedback are significantly positively associated with public engagement via the Chinese government's TikTok. However, source credibility and multiple cues did not have a positive impact on public engagement. Additionally, the study reveals that trust mediates the relationships between information quality, source credibility, and immediate feedback with public engagement.

conclusionThese results underscore the importance of trust in fostering public engagement and highlight the potential for enhancing government communication strategies on social media during crises. The study suggests that improving the quality of information and providing timely feedback can significantly increase public engagement through social media platforms like TikTok, particularly in the context of public health emergencies.

Indexed as

Community ParticipationEmergenciesPublic HealthSocial MediaAdolescentAdultChinaFemaleGovernmentHumansInformation DisseminationMaleSurveys and QuestionnairesTrustYoung Adult

Identifiers

PMID40531981
PMCPMC12176294

What OpenQuestion holds

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LicenceCC BY
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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.