Canadian Nurses’ Psychological Health Assessment and Its Determinants During the Uncertain Context of the Early COVID-19 Pandemic: A Cross-Sectional Study
Bibliographic record
Abstract
Quebec's (Canada) nurses experienced a major reorganization of care during the first wave of the COVID-19 pandemic. This study aimed at investigating nurses’ psychological health and its determinants during this highly uncertain time, with a particular focus on posttraumatic stress disorder (PTSD), anxiety, and depression. In 2020, a web-based cross-sectional survey was completed by a large sample of Quebec nurses ( n = 1,773). High prevalence of PTSD (14.3%), anxiety (39.4%), and depression (46.7%) was observed. Overcommitment at work was associated with higher prevalence of PTSD, anxiety, and depression. More years since licensure, feeling safe with protective measures and increased social support were associated with lower prevalence of PTSD, anxiety, and/or depression. Our study identified modifiable personal and workplace factors that could be targeted by healthcare organizations and policymakers to promote nurses’ well-being and enhance the resilience of healthcare systems to resist future global health crises or pandemics. Future research is needed to better understand the potential long-term consequences of the COVID-19 pandemic on nurses’ psychological health.
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 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 | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".