Evidence map›Paper›PMID 35774579›Full record

ArticleFrontiers in public health2022

Does Citizen Engagement With Government Social Media Accounts Differ During the Different Stages of Public Health Crises? An Empirical Examination of the COVID-19 Pandemic.

Wei Zhang, Hui Yuan, Chengyan Zhu, Qiang Chen, Richard Evans

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

5 authors.

Wei ZhangSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.
Hui YuanSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.
Chengyan ZhuSchool of Political Science and Public Administration, Wuhan University, Wuhan, China.
Qiang ChenSchool of Journalism and New Media, Xi'an JiaoTong University, Xi'an, China.
Richard EvansFaculty of Computer Science, Dalhousie University, Halifax, NS, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The COVID-19 pandemic has created one of the greatest challenges to humankind, developing long-lasting socio-economic impacts on our health and wellbeing, employment, and global economy. Citizen engagement with government social media accounts has proven crucial for the effective communication and management of public health crisis. Although much research has explored the societal impact of the pandemic, extant literature has failed to create a systematic and dynamic model that examines the formation mechanism of citizen engagement with government social media accounts at the different stages of the COVID-19 pandemic. This study fills this gap by employing the Heuristic-Systematic Model and investigating the effects of the heuristic clues including social media capital, information richness, language features, dialogic loop, and the systematic clue including content types, on citizen engagement with government social media across three different stages of the pandemic, employing the moderating role of emotional valence. Methods: The proposed model is validated by scraping 16,710 posts from 22 provincial and municipal government micro-blog accounts in the Hubei province, China. Results: Results show that the positive effects of social media capital on citizen engagement were observed at all stages. However, the effects of information richness, language features, dialogic loop, and content types, and the moderating effect of emotional valence, varied across the different pandemic development stages. Conclusions: The findings provide suggestions for the further effective use of government social media, and better cope with crises. Government agencies should pay attention to the content and form of information shared, using technical means to analyze the information needs of citizens at different stages of public health emergencies, understanding the content most concerned by citizens, and formulating the content type of posts.

Indexed as

COVID-19Social MediaGovernmentHumansPandemicsPublic HealthSARS-CoV-2citizen engagementcrisis stagedialogic communicationgovernment social mediainformation richnesslanguage featurespublic health crisissocial media capital

Identifiers

PMID35774579
PMCPMC9237959

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.