Evidence map›Paper›PMID 35306120›Full record

ArticleJournal of affective disorders2022

Economic crisis and mental health during the COVID-19 pandemic in Japan.

Tetsuya Matsubayashi, Yumi Ishikawa, Michiko Ueda

Abstract read
In one paragraph

Article in Journal of affective disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
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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

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

16 citing papers in PubMed, 3 syntheses or guidelines 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

3 authors.

Tetsuya MatsubayashiOsaka School of International Public Policy, Osaka University, 1-31 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan. Electronic address: matsubayashi@osipp.osaka-u.ac.jp.
Yumi IshikawaKobe University, Japan.
Michiko UedaWaseda University, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe economic crisis induced by the COVID-19 pandemic can have a serious impact on population mental health. This study seeks to understand whether the economic shocks associated with the pandemic have a differential impact by sex because the current pandemic may have disproportionally affected women compared to men.

methodsWe analyzed data from original online monthly surveys of the general population in Japan conducted between April 2020 and February 2021 (N = 9000). We investigated whether individuals who had experienced a major job-related adverse change were more likely to have experienced depressive symptoms (PHQ-9) and anxiety disorders (GAD-7) during the pandemic and also if its effect varied by sex.

resultsThe results of logistic regression suggest that depressive and anxiety symptoms were more prevalent among those who had recently experienced drastic changes in employment and working conditions, as well as among individuals with low income and those without college education. We also found that both female and male respondents who had experienced a major employment-related change exhibited depression and anxiety disorders. LIMITATIONS: We do not have data on the pre-COVID mental health conditions of our respondents, and our findings are descriptive. Some segments of the population may not be represented in our sample because our surveys were conducted online.

conclusionsCOVID-induced economic shocks can have a detrimental effect on mental health among both economically vulnerable female and male workers.

Indexed as

COVID-19PandemicsAnxietyCross-Sectional StudiesDepressionEconomic RecessionFemaleHumansJapanMaleMental HealthSARS-CoV-2AnxietyCOVID-19DepressionJapanMental healthRecession

Identifiers

PMID35306120
PMCPMC8924027

What OpenQuestion holds

Textmetadata
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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.