Psychological distress, depression symptoms and fatigue among Quebec nursing staff during the COVID‐19 pandemic: A cross‐sectional study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To describe the state of health of Quebec nursing staff during the pandemic according to their exposure to COVID-19, work-related characteristics and sociodemographic factors (gender, generational age group). State of health was captured essentially by assessing psychological distress, depression symptoms and fatigue. DESIGN AND METHODS: A large-scale cross-sectional study was conducted with 1,708 nurses and licenced practical nurses in Quebec (87% women, mean age of 41 ± 11 years). The survey included several questionnaires and validated health-related scales (psychological distress, depression symptoms and fatigue). The STROBE guidelines were followed in reporting the study's findings. RESULTS: Results showed that the prevalence of psychological distress and depression symptoms was moderate to severe. Women, generation Xers and Yers, nurses who cared for COVID-19 patients and those with a colleague who was infected with COVID-19 at work scored higher for fatigue, psychological distress and depression.
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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 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it