Evidence map›Paper›PMID 35058679›Full record

ArticleChina economic review2022

"The better you feel, the harder you fall": Health perception biases and mental health among Chinese adults during the COVID-19 pandemic.

Peng Nie, Lu Wang, Davide Dragone, Haiyang Lu, Alfonso Sousa-Poza, Nicolas R Ziebarth

Open access · greenAbstract read
In one paragraph

Article in China economic review, 2022. 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
1.5field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 14 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

6 authors at 5 institutions in 4 countries.

Peng NieSchool of Economics and Finance, Xi'an Jiaotong University, 710061 Xi'an, China.
Lu WangSchool of Economics and Finance, Xi'an Jiaotong University, 710061 Xi'an, China.
Davide DragoneDepartment of Economics, University of Bologna, Italy.
Haiyang LuThe West Center for Economics Research, Southwestern University of Finance and Economics, Chengdu, China.
Alfonso Sousa-PozaSchool of Economics and Finance, Xi'an Jiaotong University, 710061 Xi'an, China.
Nicolas R ZiebarthDepartment of Economics and Jeb E. Brooks School of Public Policy, Cornell University, USA.
IZA - Institute of Labor Economics · DECornell University · USSouthwestern University of Finance and Economics · CNUniversity of Bologna · ITXi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The health risks of the current COVID-19 pandemic, together with the drastic mitigation measures taken in many affected nations, pose an obvious threat to public mental health. To assess predictors of poor mental health in the context of the COVID-19 pandemic, this study first implements survey-based measures of health perception biases among Chinese adults during the pandemic. Then, it analyzes their relation to three mental health outcomes: life satisfaction, happiness, and depression (as measured by the CES-D). We show that the health overconfidence displayed by approximately 30% of the survey respondents is a clear risk factor for mental health problems; it is a statistically significant predictor of depression and low levels of happiness and life satisfaction. We also document that these effects are stronger in regions that experienced higher numbers of confirmed COVID-19 cases and deaths. Our results offer clear guidelines for the implementation of effective interventions to temper health overconfidence, particularly in uncontrollable situations like the COVID-19 pandemic.

Indexed as

ChinaHealth perception biasMental healthOverconfidenceUnderconfidence

Identifiers

PMID35058679
PMCPMC8570802
OpenAlexW3211394495

What OpenQuestion holds

Textmetadata
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.