Canadian healthcare workers’ mental health and health behaviours during the COVID-19 pandemic: results from nine representative samples between April 2020 and February 2022
Bibliographic record
Abstract
OBJECTIVE: In the context of COVID-19, Canadian healthcare workers (HCWs) worked long hours, both to respond to the pandemic and to compensate for colleagues who were not able to work due to infection and burnout. This may have had detrimental effects on HCWs' mental health, as well as engagement in health-promoting behaviours. This study aimed to identify changes in mental health outcomes and health behaviours experienced by Canadian HCWs throughout the COVID-19 pandemic. METHODS: = 1615 HCWs) completed the iCARE survey using an online polling firm between April 2020 (Time 1) and February 2022 (Time 9). Participants were asked about the psychological effects of COVID-19 (e.g., feeling anxious) and about changes in their health behaviours (e.g., alcohol use, physical activity). RESULTS: A majority of the HCWs identified as female (65%), were younger than 44 years old (66%), and had a university degree (55%). Female HCWs were more likely than male HCWs to report feeling anxious (OR = 2.68 [1.75, 4.12]), depressed (OR = 1.63 [1.02, 2.59]), and irritable (OR = 1.61 [1.08, 2.40]) throughout the first two years of the pandemic. Female HCWs were more likely than their male counterparts to report eating more unhealthy diets (OR = 1.54 [1.02, 2.31]). Significant differences were also revealed by age, education level, income, parental status, health status, and over time. CONCLUSION: Results demonstrate that the impacts of COVID-19 on HCWs' mental health and health behaviours were significant, and varied by sociodemographic characteristics (e.g., sex, age, income).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".