Exposures to Potentially Psychologically Traumatic Events Among Nurses in Canada
Bibliographic record
Abstract
BACKGROUND: Nurses are regularly exposed to diverse potentially psychologically traumatic events (PPTEs) as a function of their work. Cumulative exposure to PPTEs can lead to clinically significant symptoms of mental disorders. PURPOSE: We designed the current study to investigate the prevalence of different PPTEs among Canadian nurses and estimate the associations between diverse exposures and several mental disorders. METHODS: Canadian nurses (i.e., registered nurses, registered psychiatric nurses, licensed practical nurses, nurse practitioners) completed an online, self-reported survey. In total, 4067 participants (94.8% women) completed all relevant survey measures. RESULTS: <.05) associations between diverse traumatic events and all mental disorders (i.e., Posttraumatic Stress Disorder, Major Depressive Disorder, Generalized Anxiety Disorder, Panic Disorder) except Alcohol Use Disorder. CONCLUSIONS: The current findings suggest that Canadian nurses are substantially exposed to traumatic events, which vary by several sociodemographic categories. PPTE exposures were significantly associated with mental disorders; that is, if PPTEs were eliminated among Canadian nurses in the sample, symptoms would be reduced between 42.0% and 58.0%.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".