Predictors of healthcare worker burnout during the COVID-19 pandemic

  1. Amy V Ferry
  2. Ryan Wereski
  3. Fiona E Strachan
  4. Nicholas L Mills

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Abstract

Objective

We aim to provide a ‘snapshot’ of the levels of burnout, anxiety, depression and distress among healthcare workers during the COVID-19 pandemic.

Design, setting, participants

We distributed an online survey via social media in June 2020 that was open to any UK healthcare worker. The primary outcome measure was symptoms of burnout as measured using the Copenhagen Burnout Inventory (CBI). Secondary outcomes of depression, anxiety and distress as measured using the Patient Health Questionnaire-9, General Anxiety Scale-7, and Impact of Events Scale-Revised were recorded along with subjective measures of stress. Multivariate logistic regression analysis was performed to identify factors associated with burnout, depression, anxiety and distress.

Results

Of 539 persons responding to the survey, 90% were female, and 26% were aged 41-50 years, 53% were nurses. Participants with moderate-to-severe burnout were younger (49% [206/424] versus 33% [38/115] under 40 years, P=0.004), and more likely to have pre-existing comorbidities (21% versus 12%, P=0.031). They were twice as likely to have been redeployed from their usual role (22% versus 11%; adjusted odds ratio [OR] 2.2, 95% confidence interval [CI] 1.5-3.3, P=0.042), or to work in an area dedicated to COVID-19 patients (50% versus 32%, adjusted OR 1.6, 95% CI 1.4-1.8, P<0.001), and were almost 4-times more likely to have previous depression (24% versus 7%; adjusted OR 3.6, 95% CI 2.2-5.9, P=0.012). A supportive workplace team and male sex protected against burnout reducing the odds by 40% (adjusted OR 0.6, 95% CI 0.5-0.7, P<0.001) and 70% (adjusted OR 0.3, 95% CI 0.2-0.5, P=0.003), respectively.

Conclusion

Independent predictors of burnout were younger staff, redeployment to a new working area, working with patients with confirmed COVID-19 infection, and being female or having a previous history of depression. Evaluation of existing psychological support interventions is required with targeted approaches to ensure support is available to those most at risk.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.26.20182378: (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 variableParticipants were recruited through a non-funded social-media campaign initiated by the study investigators (1 male and 2 female) using snowball sampling (sharing of the survey link among networks).

    Table 2: Resources

    No key resources detected.

    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:
    Limitations: This study has several limitations. The majority of respondents were female, which is perhaps not unsurprising given than more than half were from the nursing profession where 89% of the workforce are women (15). We did not collect data on ethnicity of respondents. As it is now known that black and ethnic minority groups are more adversely affected by COVID-19 this may have an impact on mental health outcomes among these staff groups. However, in Scotland 96% of the population identify as white (30) therefore it is unlikely we could have performed analyses stratified by ethnicity in our respondent population. Additionally, it is possible that a mental health social media survey has captured the responses of those that are already engaged with the topic and may therefore overestimate the prevalence burnout, anxiety and depression in the target population.

    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

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  2. Version published to 10.1101/2020.08.26.20182378v1 on medRxiv
  3. Version published to 10.1093/qjmed/hcab065