The Impact of COVID-19 on the Mental Health of Healthcare Workers
Bibliographic record
Abstract
This poster presentation summarizes publicly available data collected by the World Health Organization, the Government of Canada, the College of Nurses of Ontario, the Registered Nurses’ Association of Ontario, and the University of Windsor’s scholarly database to examine the impact of the COVID-19 Pandemic on the mental health and well-being of healthcare workers. We reviewed online databases to find peer-reviewed articles and journals. We also reviewed government and organizational websites, as well as broadcasting platforms. We analyzed secondary data systematically vetting for credibility, reliability, and relevance to our topic. We found a positive correlation between the impact of the COVID-19 pandemic and the mental health of healthcare workers. Further research is required to understand the full impact on mental health of health care workers at all levels and regions, with particular interest for studies affecting individuals living in great adversity, as well as those living in lower-to-middle income countries.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".