Psychosocial distress amongst Canadian intensive care unit healthcare workers during the acceleration phase of the COVID-19 pandemic
Bibliographic record
Abstract
Intensive care unit healthcare workers (ICU HCW) are at risk of mental health issues during emerging disease outbreaks. A study of ICU HCW from France revealed symptoms of anxiety and depression in 50.4% and 30.4% of workers at the peak of the first wave of the pandemic. The level of COVID-19 exposure of these ICU HCW was very high. In Canada, ICU HCW experienced variable exposure to COVID-19 during the first wave of the pandemic, with some hospitals seeing large numbers of patients while others saw few or none. In this study we examined the relationship between COVID-19 exposure and mental health in Canadian ICU HCW. We conducted a cross-sectional cohort study of Canadian ICU HCW in April 2020, during the acceleration phase of the first wave of the pandemic. Psychosocial distress was assessed using the 12-item General Health Questionnaire (GHQ-12). Participants were asked about sources of stress as well as about exposure to COVID-19 patients and availability of personal protective equipment (PPE). Factors associated with clinically-relevant psychosocial distress were identified. Responses were received from 310 Canadian ICU HCW affiliated with more than 30 institutions. Of these, 64.5% scored ≥ 3 points on the GHQ-12 questionnaire, indicating clinically-relevant psychosocial distress. The frequency of psychosocial distress was highest amongst registered nurses (75.7%) and lowest amongst physicians (49.4%). It was also higher amongst females (64.9%) than males (47.6%). Although PPE availability was good (> 80% of participants reported adequate availability), there was significant anxiety with respect to PPE availability, with respect to the risk of being infected with COVID-19, and with respect to the risk of transmitting COVID-19 to others. In multivariable regression analysis, Anxiety with respect to being infected with COVID-19 (OR 1.53, CI 1.31-1.81) was the strongest positive predictor of clinically-relevant psychosocial distress while the Number of shifts with COVID-19 exposure (OR 0.86, CI 0.75-0.95) was the strongest negative predictor. In summary, clinically-relevant psychosocial distress was identified amongst a majority of ICU HCW during the acceleration phase of the first wave of the COVID-19 pandemic, including those with minimal or no exposure to COVID-19. Strategies to support mental health amongst ICU HCW are required across the entire healthcare system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".