Anxiety and depression among medical doctors in Catalonia, Italy, and the UK during the COVID-19 pandemic

  1. Climent Quintana-Domeque
  2. Ines Lee
  3. Anwen Zhang
  4. Eugenio Proto
  5. Michele Battisti
  6. Antonia Ho

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Abstract

Healthcare workers have had the longest and most direct exposure to COVID-19 and consequently may suffer from poor mental health. We conducted one of the first repeated multi-country analysis of the mental wellbeing of medical doctors (n = 5,275) at two timepoints during the COVID-19 pandemic (June 2020 and November/December 2020) to understand the prevalence of anxiety and depression, as well as associated risk factors. Rates of anxiety and depression were highest in Italy (24.6% and 20.1%, June 2020), second highest in Catalonia (15.9% and 17.4%, June 2020), and lowest in the UK (11.7% and 13.7%, June 2020). Across all countries, higher risk of anxiety and depression symptoms were found among women, individuals below 60 years old, those feeling vulnerable/exposed at work, and those reporting normal/below-normal health. We did not find systematic differences in mental health measures between the two rounds of data collection, hence we cannot discard that the mental health repercussions of the pandemic are persistent.

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  1. Version published to 10.1371/journal.pone.0259213
  2. ScreenIT

    SciScore for 10.1101/2021.07.08.21260072: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: We conducted an anonymous survey, The Healthcare Workers Survey, approved by the University of Exeter Business School Research Ethics Committee (eUEBS003024).
    Consent: Informed written consent was provided by all survey participants prior to their participation.
    Sex as a biological variablenot detected.
    RandomizationThis random sampling was chosen to avoid over-burdening members, given other surveys were taking place at the same time.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationAuthentication: It has been validated as an anxiety screening tool and severity measure in different populations [20,22–24].

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The COMB invited 5,062 members in June and November 2020 (19.9%), focusing on those with medical license numbers ending in 1 or 2.
    COMB
    suggested: (ComB, RRID:SCR_010757)
    Stata statistical software version 16.1 (StataCorp) was used for statistical analyses.
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations: This study has several limitations. First, when comparing two cross-sectional surveys for each country, we were not comparing the same individuals. Differences in prevalence of mental health symptoms could be driven by changes in sample composition across waves. Relatedly, the survey did not take place at the same point during an epidemic wave in data collections round 1 and 2. Second, participants in our survey are not necessarily representative of the underlying populations of medical doctors and may be self-selected since they voluntarily take part in the survey. Reporting bias is likely. If individuals with symptoms were more likely to respond (e.g. to express grievances), then our estimates may be higher than the population average. Conversely, if individuals with above-average symptoms are less likely to respond (e.g. due to time constraints), then our estimates may be below the population average. Third, anxiety and depression symptoms may not be comparable across countries due to different reporting norms in the GAD-7 and PHQ-9 questionnaires. Reassuringly, our pooled multivariable logistic regressions produce similar results even when controlling for occupation and institution fixed effects. Finally, our measures of anxiety and depression are not based on an objective diagnosis made by a clinician.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.08.21260072v1 on medRxiv