Mental health of health care workers during the COVID-19 pandemic and evidence-based frameworks for mitigation: A rapid review

  1. Ajay Major
  2. Fay J. Hlubocky

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Abstract

Background

The ongoing COVID-19 pandemic has profoundly affected the mental health of health care workers (HCWs), and optimal strategies to provide psychological support for HCWs are not currently established.

Aims

To rapidly review recently-published literature on the mental health of HCWs during the COVID-19 pandemic.

Methods

Query of all quantitative research through the PubMed database on the mental health of HCWs during the COVID-19 pandemic which utilized validated mental health instruments. 723 articles were screened and 87 articles were included.

Results

Nearly all included studies were cross-sectional, survey-based assessments of the prevalence of and risk factors for mental illness. Only one interventional study was identified. Prevalence of mental health outcomes varied widely: 7.0-97.3% anxiety, 10.6-62.1% depression, 2.2-93.8% stress, 3.8-56.6% post traumatic stress, 8.3-88.4% insomnia, and 21.8-46.3% burnout. Risk and protective factors were identified in personal and professional domains, including degree of COVID-19 exposure, adequacy of protective equipment, and perception of organizational support.

Conclusions

The myriad risk factors for poor mental health among HCWs suggests that a comprehensive psychosocial support model with individual- and organization-level interventions is necessary. Further longitudinal research on specific evidence-based interventions to mitigate adverse mental health outcomes among HCWs is urgently needed as the pandemic continues.

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  1. ScreenIT

    SciScore for 10.1101/2021.01.03.21249166: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    In this rapid review of quantitative research studies assessing the mental health of HCWs during the COVID-19 pandemic, we searched for potential eligible articles on the PubMed online database on September 14, 2020 using the following search term: (COVID*) AND (health worker OR healthcare worker OR healthcare professional OR health professional) AND (mental OR psych*).
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Data extraction was performed in Microsoft Excel and relevant information, including country, dates of survey assessment, sample size, types of HCWs workers studied, instruments used, and outcomes were noted.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: Strengths of this rapid review include a broad initial query for all studies on the mental health of HCWs during the COVID-19 pandemic, as well as only including studies that utilized validated mental health instruments. Further, approximately half of the countries represented in this review were outside of China, which enhances the external validity of the review. Limitations include the intrinsic variability and heterogeneity of outcomes and mental health instruments utilized across studies, wide variation in the sample sizes and inclusion of studies with low power, and utilization of only one database. Interventional studies were poorly represented in this review, and future reviews will be required to capture new interventional studies as they are published.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.01.03.21249166v1 on medRxiv