Factors Associated With Burnout, Post-traumatic Stress and Anxio-Depressive Symptoms in Healthcare Workers 3 Months Into the COVID-19 Pandemic: An Observational Study
Bibliographic record
Abstract
Objective: This study examined how best to identify modifiable protective and risk factors for burnout in healthcare workers in the face of the COVID-19 pandemic. Individual, occupational, organizational and social factors were investigated. The study also assessed the impact of these factors on post-traumatic stress disorder (PTSD), anxiety, and depression. Methods: Healthcare workers in the Quebec (Canada) healthcare system were recruited between May 21 to June 5, 2020. Participants answered an electronic survey 3 months after the COVID-19 epidemic outbreak began in Canada. Using the Maslach Burnout Inventory, PTSD Checklist for DSM-5, and Hospital Anxiety and Depression Scale, we studied the prevalence of burnout, PTSD, anxiety and depression in this cohort. Multivariable logistic or linear regression models including resilience, social and organizational support, workload and access to mental health help, simulation techniques and protective personal equipment (PPE) as well as perception of PPE security were conducted for each outcome. Results: In mid-June 2020, 467 participants completed the survey. We found that half (51.8%) of the respondents experienced burnout characterized by emotional exhaustion and/or depersonalization at least once a week. In total, 158 healthcare workers (35.6%) displayed severe symptoms of at least one of the mental health disorders (24.3% PTSD, 23.3% anxiety, 10.6% depression). Resilience (OR = 0.69, 95% CI: [0.55–0.87]; p = 0.002) and perceived organizational support (OR = 0.75, 95% CI: [0.61–0.93]; p = 0.009) were significantly associated with burnout and other outcomes. Social support satisfaction, perception of PPE security, work type and environment, mental health antecedents and reassignment were associated with PTSD and/or anxiety and/or depression, but not burnout. Conclusion: Future studies should address primarily resilience and perceived organizational support to promote mental health and prevent burnout, PTSD, anxiety and depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".