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

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

doi:10.3389/fpsyt.2022.833865

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

Front Psychiatry. 2022 Mar 18:13:833865. doi: 10.3389/fpsyt.2022.833865. eCollection 2022.

Authors

Xi Chen¹, Jiyao Chen², Meimei Zhang³, Rebecca Kechen Dong⁴, Jizhen Li⁵, Zhe Dong⁶, Yingying Ye⁷, Lingyao Tong⁸, Ruiying Zhao⁸, Wenrui Cao⁹, Peikai Li⁹, Stephen X Zhang¹⁰

Affiliations

¹ Chinese Open Science Network, Xiamen, China.
² Department of Strategy and Entrepreneurship, College of Business, Oregon State University, Corvallis, OR, United States.
³ Department of Speech-Language-Hearing Sciences, Texas Tech University Health Sciences Center, Lubbock, TX, United States.
⁴ UniSA Business, University of South Australia, Adelaide, SA, Australia.
⁵ Department of Innovation, Entrepreneurship and Strategy, School of Economic and Management, Tsinghua University, Beijing, China.
⁶ Department of Sociology and Interuniversity Center for Social Science Theory and Methodology (ICS), University of Groningen, Groningen, Netherlands.
⁷ Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
⁸ Department of Clinical, Neuro- and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
⁹ Department of Social, Health and Organizational Psychology, Utrecht University, Utrecht, Netherlands.
¹⁰ Entrepreneurship, Innovation and Family Enterprise Discipline, Adelaide Business School, University of Adelaide, Adelaide, SA, Australia.

Abstract

Objective: This 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.

Method: We 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.

Results: The 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).

Conclusion: The 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 registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.

Keywords: COVID-19; frontline healthcare workers; healthcare workers; mental health; meta-analysis; meta-regression; systematic review.

Publication types

Systematic Review