The impact of COVID-19 workload on psychological distress amongst Canadian intensive care unit healthcare workers during the 1st wave of the COVID-19 pandemic: A longitudinal cohort study
Bibliographic record
Abstract
Intensive care unit healthcare workers (ICU HCW) are at risk of mental health disorders during emerging disease outbreaks. Numerous cross-sectional studies have reported psychological distress, anxiety, and depression amongst ICU HCW during the COVID-19 pandemic. However, few studies have followed HCW longitudinally, and none of these have examined the association between COVID-19 workload and mental health. We conducted a longitudinal cohort study of 309 Canadian ICU HCW from April 2020 to August 2020, during the 1st wave of the COVID-19 pandemic. Psychological distress was assessed using the General Health Questionnaire 12-item scale (GHQ-12) at 3 timepoints: during the acceleration phase of the 1st wave (T1), the deceleration phase of the 1st wave (T2), and after the 1st wave had passed (T3). Clinically relevant psychological distress, defined as a GHQ-12 score ≥ 3, was identified in 64.7% of participants at T1, 41.0% at T2, and 34.6% at T3. Psychological distress was not associated with COVID-19 workload at T1. At T2, psychological distress was associated with the number of COVID-19 patients in the ICU (odds ratio [OR]: 1.06, 95% confidence interval [CI]: 1.00, 1.13) while at T3, when COVID-19 patient numbers were low, it was associated with the number of weekly hospital shifts with COVID-19 exposure (OR: 1.33, 95% CI: 1.09, 1.64). When analyzed longitudinally in a mixed effects model, pandemic timepoint was a stronger predictor of psychological distress (OR: 0.24, 95% CI: 0.15, 0.40 for T2 and OR: 0.16, 95% CI: 0.09, 0.27 for T3) than COVID-19 workload. Participants who showed persistent psychological distress at T3 were compared with those who showed recovery at T3. Persistent psychological distress was associated with a higher number of weekly shifts with COVID-19 exposure (OR: 1.97, 95% CI:1.33, 3.09) but not with a higher number of COVID-19 patients in the ICU (OR: 0.86, 95% CI: 0.76, 0.95). In summary, clinically relevant psychological distress was observed in a majority of ICU HCW during the acceleration phase of the 1st wave of the COVID-19 pandemic but decreased rapidly as the 1st wave progressed. Persistent psychological distress was associated with working more weekly shifts with COVID-19 exposure but not with higher numbers of COVID-19 patients in the ICU. In future emerging disease outbreaks, minimizing shifts with direct disease exposure may help alleviate symptoms for individuals with persistent psychological distress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".