Mental health of clinical staff working in high-risk epidemic and pandemic health emergencies a rapid review of the evidence and living meta-analysis

  1. Vaughan Bell
  2. Dorothy Wade

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Purpose

The SARS-CoV-2 / COVID-19 pandemic has raised concerns about the potential mental health impact on frontline clinical staff. However, given that poor mental health is common in acute medical staff, we aimed to estimate the additional burden of work involving high exposure to infected patients.

Methods

We report a rapid review, meta-analysis, and living meta-analysis of studies using validated measures from outbreaks of COVID-19, Ebola, H1N1 influenza, Middle East respiratory syndrome (MERS), and severe acute respiratory syndrome (SARS).

Results

A random effects meta-analysis found that high-exposure work is not associated with an increased prevalence of above cut-off scoring (anxiety: RR = 1.30, 95% CI 0.87–1.93, Total N  = 12,473; PTSD symptoms: RR = 1.16, 95% CI 0.75–1.78, Total N  = 6604; depression: RR = 1.50, 95% CI 0.57–3.95, Total N  = 12,224). For continuous scoring, high-exposure work was associated with only a small additional burden of acute mental health problems compared to low-exposure work (anxiety: SMD = 0.16, 95% CI 0.02–0.31, Total N  = 6493; PTSD symptoms: SMD = 0.20, 95% CI 0.01–0.40, Total N  = 5122; depression: SMD = 0.13, 95% CI -0.04–0.31, Total N  = 4022). There was no evidence of publication bias.

Conclusion

Although epidemic and pandemic response work may add only a small additional burden, improving mental health through service management and provision of mental health services should be a priority given that baseline rates of poor mental health are already very high. As new studies emerge, they are being added to a living meta-analysis where all analysis code and data have been made freely available: https://osf.io/zs7ne/ .

Article activity feed

  1. Version published to 10.1007/s00127-020-01990-x
  2. ScreenIT

    SciScore for 10.1101/2020.04.28.20082669: (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 AnalysisWe conducted a power analysis for meta-analysis (Valentine et al., 2010) to determine the minimum number of studies required to detect a statistically significant difference in standardised mean difference between high and low exposure groups.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We searched PubMed, Medline, PsychInfo and Embase for articles including ‘mental health’ or ‘psychosocial’ or ‘emotional’ and ‘staff’ and a number of disease specific key words (epidemic, epidemics, pandemic, flu, SARS, MERS, COVID-19, Ebola, Marburg, H1N1, H7N6) in the title.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    With regard to the published studies, although there are seemingly high rates of staff who score above cut-off on measures of PTSD symptoms, some significant caveats need to be born in mind. As can be seen from Table 3, cut-off values used for defining a positive ‘case’ varied considerably even between studies using the same measure. The most widely used scale in these studies is the Impact of Events Scale-Revised for which a cut-off of 33–34 has been found to be the most predictive of diagnosable PTSD (Creamer et al., 2003; Morina et al., 2013) and yet most studies use a cut-off of considerably less. This suggests that an important proportion of those reported under the prevalence figures are likely to have transitory, sub-syndromal PTSD symptoms, or non-specific distress, that may be a risk for PTSD but are unlikely to reach the level of a diagnosable case. Indeed, the prevalences reported here are comparable to prevalences found in clinical staff more widely. For example, the reported prevalence of >33 scoring on the IES-R is 15% in acute medical staff (Naumann et al., 2017), 16% in surgical trainees (Thompson et al., 2017), and 17% in cancer physicians (McFarland and Roth, 2017). Studies included in this review using similar IES-R cut-offs tended to report lower prevalence rates with only one study (Zhu et al., 2020) reporting higher. Furthermore, studies often did not differentiate between PTSD symptoms arising from pandemic and epidemic response work and those from othe...

    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.

  3. Version published to 10.1101/2020.04.28.20082669v1 on medRxiv