Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers

ObjectiveThis paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis.MethodWe systematically searched PubMed, Embase, Web of Science, and Me...

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Bibliographic Details
Main Authors: Xi Chen, Jiyao Chen, Meimei Zhang, Rebecca Kechen Dong, Jizhen Li, Zhe Dong, Yingying Ye, Lingyao Tong, Ruiying Zhao, Wenrui Cao, Peikai Li, Stephen X. Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Psychiatry
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Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2022.833865/full
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Summary:ObjectiveThis paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis.MethodWe systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity.ResultsThe meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04).ConclusionThe meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.
ISSN:1664-0640