Evidence map›Paper›PMID 38384350›Full record

ArticleFrontiers in psychology2024

Risk perceptions of COVID-19 in Beijing: a cross-sectional study.

Qing Liu, Yiyang Tan, Zheng Zhu, Jiawei Zhang, Yaqun Fu, Quan Wang, Zhijie Nie, Li Yang, Xiaoguang Li

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In one paragraph

Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Qing LiuGeneral Practice Department, Second Outpatient Section, Peking University Third Hospital, Beijing, China.
Yiyang TanDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Zheng ZhuDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Jiawei ZhangDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Yaqun FuDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Quan WangDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Zhijie NieDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Li YangDepartment of Health Policy and Management, Peking University School of Public Health, Beijing, China.
Xiaoguang LiDepartment of Infectious Diseases, Peking University Third Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Chinese government has ended the "dynamic zero-COVID" policy, and residents are now living together with the SARS-CoV-2 virus. Only a limited number of studies have investigated the specific content and structure of COVID-19-related risk perceptions, as well as their underlying determinants. This study measured the residents' risk perception of COVID-19 and analyzed the predictors of RP. Methods: We conducted a comprehensive questionnaire-based survey among residents mostly in Beijing, using a specially designed scale consisting of 11 items to accurately measure COVID-19 risk perceptions. We then utilized multiple linear regression analysis to investigate the factors associated with risk perceptions. Results: A total of 60,039 residents participated in the survey. Our study reveals that COVID-19-related worries are significantly influenced by other dimensions of RP ( Conclusion: This study evaluates the specific content and structure of COVID-19-related risk perceptions, as well as their determinants. It is essential to understand the risk perceptions and health-protective behaviors of residents with diverse educational levels, incomes, and medical histories.

Indexed as

COVID-19cross-sectional studydeterminantspandemicrisk perception

Identifiers

PMID38384350
PMCPMC10879607

What OpenQuestion holds

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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.