Evidence map›Paper›PMID 33776873›Full record

ArticleFrontiers in psychology2021

The Public's Risk Information Seeking and Avoidance in China During Early Stages of the COVID-19 Outbreak.

Mei Liu, You Chen, Dan Shi, Tingwu Yan

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Prevalence and predictors of medical information avoidance: a systematic review and meta-analysis.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2025
    Pooled it
  2. Pooled it
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  7. Information avoidance in the age of COVID-19: A meta-analysis.Information processing & management · 2023
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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

4 authors.

Mei LiuDepartment of Business Administration, College of Economics and Management, Huazhong Agricultural University, Wuhan, China.
You ChenDepartment of Business Administration, College of Economics and Management, Huazhong Agricultural University, Wuhan, China.
Dan ShiDepartment of Business Administration, College of Economics and Management, Huazhong Agricultural University, Wuhan, China.
Tingwu YanDepartment of Agricultural Economics and Management, College of Economics and Management, Huazhong Agricultural University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study uses the Planned Risk Information Seeking Model (PRISM) to estimate the public's information seeking and avoidance intentions during the COVID-19 outbreak based on an online sample of 1031 Chinese adults and provides support for the applicability of PRISM framework in the situation of a novel high-level risk. The results indicate that information seeking is primarily directed by informational subjective norms (ISN) and perceived seeking control (PSC), while the main predictors of information avoidance include ISN and attitude toward seeking. Because ISN are the strongest predictor of both information seeking and avoidance, the way the public copes with COVID-19 information may be strongly affected by individuals' social environment. Furthermore, a significant relationship between risk perception and affective risk response is identified. Our results also indicate that people who perceive greater knowledge of COVID-19 are more likely to report greater knowledge insufficiency, which results in less information avoidance.

Indexed as

COVID-19emerging riskinformation avoidanceinformation seekingrisk perception

Identifiers

PMID33776873
PMCPMC7994604

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.