Evidence map›Paper›PMID 36467202›Full record

ArticleFrontiers in psychology2022

The impact of major public health emergencies on Trust in Government: From SARS to COVID-19.

Kun Zhai, Xuemei Yuan, Guoqing Zhao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

6 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Kun ZhaiBusiness School, Institute of Finance, University of Jinan, Jinan, China.
Xuemei YuanBusiness School, Institute of Finance, University of Jinan, Jinan, China.
Guoqing ZhaoShandong Key Laboratory of Blockchain Finance, Shandong University of Finance and Economics, Jinan, China.
University of Jinan · CNShandong University of Finance and Economics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major public health emergencies always test the credibility of the government. The success of governments' strategies relies on trust in government and broad acceptance of response measures. The profound experience of the epidemic often has a long-term impact on people's cognition. We construct a difference-in-difference estimator by combining the variations of epidemic effects across cohorts and regions, and intend to evaluate the long-term effect of individuals' early SARS experience on trust in government during the COVID-19 pandemic. We also use the instrumental variable method to overcome the endogenous problem caused by two-way causality. The results show that the impact of COVID-19 has significantly reduced trust in government of the groups who had not been exposed to the SARS epidemic (including groups who were in early childhood and the unborn during the SARS outbreak). While it has a positive impact on trust in government of people experienced SARS in adolescence, and only a little negative impact on trust in government of people experienced SARS in adulthood. We also find that the impact of COVID-19 mainly reduced the trust in government among groups socially vulnerable or without SARS experience (e.g., low income, low social status etc.). The results suggest that: (a) the trust created by governments' successful anti-epidemic measures is long-lasting; (b) governments should pay more attention to their trust among socially vulnerable groups.

Indexed as

age groupepidemic experiencelong-term effectpublic health emergenciestrust in government

Identifiers

PMID36467202
PMCPMC9710386
OpenAlexW4309313949

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.