Work Characteristics, Workplace Support, and Mental Ill-Health in a Canadian Cohort of Healthcare Workers During the COVID-19 Pandemic
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to identify determinants of mental health in healthcare workers (HCW) during the COVID-19 pandemic. METHODS: A cohort of Canadian HCW completed four questionnaires giving details of work with patients, ratings of workplace supports, a mental health questionnaire, and substance use. Principal components were extracted from 23 rating scales. Risk factors were examined by Poisson regression. RESULTS: A total of 4854 (97.8%) of 4964 participants completed ratings and mental health questionnaires. Healthcare workers working with patients with COVID-19 had high anxiety and depression scores. One of three extracted components, 'poor support,' was related to work with infected patients and to anxiety, depression, and substance use. Availability of online support was associated with feelings of better support and less mental ill-health. CONCLUSIONS: Work with infected patients and perceived poor workplace support were related to anxiety and depression during the pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".