Exposures to Potentially Psychologically Traumatic Events among Canadian Coast Guard and Conservation and Protection Officers
Bibliographic record
Abstract
Canadian Public Safety Personnel (PSP) (i.e., municipal/provincial police, firefighters, paramedics, Royal Canadian Mounted Police, correctional workers, dispatchers) report frequent and varied exposures to potentially psychologically traumatic events (PPTEs). Exposure to PPTEs may be one explanation for the symptoms of mental health disorders prevalent among PSP. The objective of the current study was to provide estimates of lifetime PPTE exposures among Canadian Coast Guard (CCG) and Conservation and Protection (C&P) Officers and to assess for associations between PPTEs, mental health disorders, and sociodemographic variables. Participants (n = 412; 55.3% male, 37.4% female) completed an online survey assessing self-reported PPTE exposures and self-reported symptoms of mental health disorders. Participants reported higher frequencies of lifetime exposures to PPTEs than the general population (all ps < 0.001) but lower frequencies than other Canadian PSP (p < 0.5). Several PPTE types were associated with increased odds of positive screens for posttraumatic stress disorder, major depressive disorder, general anxiety disorder, social anxiety disorder, panic disorder, and alcohol use disorder (all ps < 0.05). Experiencing a serious transportation accident (77.4%), a serious accident at work, home, or during recreational activity (69.7%), and physical assault (69.4%) were among the PPTEs most frequently reported by participants. The current results provide the first known information describing PPTE exposures of CCG and C&P members, supporting the growing evidence that PPTEs are more frequent and varied among PSP and can be associated with diverse mental health disorders.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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".