Anxiety-related psychopathology and chronic pain comorbidity among public safety personnel
Bibliographic record
Abstract
Canadian Public Safety Personnel (PSP; e.g., correctional service officers, dispatchers, firefighters, paramedics, police officers) regularly experience potentially traumatic, painful, and injurious events. Such exposures increase risk for developing mental disorders and chronic pain, which both involve substantial personal and social costs. The interrelationship between mental disorders and chronic pain is well-established, and both can be mutually maintaining; accordingly, understanding the relationship between mental health and chronic pain among PSP is important for improving health care. Unfortunately, the available research on such comorbidity for PSP is sparse. The current study was designed to provide initial estimates of comorbidities between mental disorders and chronic pain across diverse PSP. Participants included 5093 PSP (32% women) in six categories (i.e., Call Center Operators/Dispatchers, Correctional Workers, Firefighters, Municipal/Provincial Police, Paramedics, Royal Canadian Mounted Police) who participated in a large PSP mental health survey. The survey included established self-report measures for mental disorders and chronic pain. In the total sample, 23.1% of respondents self-reported clinically significant comorbid concerns with both mental disorders and chronic pain. The results indicated PSP who reported chronic pain were significantly more likely to screen positive for posttraumatic stress disorder (PTSD), major depressive disorder, generalized anxiety disorder, social anxiety disorder, and alcohol use disorder. There were differences between PSP categories; but, the most consistent indications of comorbidity were for chronic pain, PTSD, and major depressive disorder. Comorbidity between chronic pain and mental disorders among PSP is prevalent. Health care providers should regularly assess PSP for both symptom domains.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".