Return-to-Work Outcomes Following Mental Health Treatment Among Public Safety Personnel Disabled by Post-Traumatic Stress Disorder
Bibliographic record
Abstract
OBJECTIVE: To evaluate the influence of a mental health treatment program for public safety personnel (PSP) disabled by post-traumatic stress disorder (PTSD) on return-to-work outcomes. METHODS: A mental health treatment program established exclusively for PSPs disabled by work-related PTSD received 582 referrals over the period November 2021 to June 2023. Return-to-work outcomes were defined as the cessation of workers' compensation wage replacement benefits over an 18-36 month period following referral. Outcomes among the referral cohort were compared to PSPs not referred to treatment who also had an accepted workers' compensation claim for PTSD. Referrals were matched to non-referrals on age, sex, occupation and date of injury. RESULTS: Among the 472 referrals to the treatment program eligible for inclusion in the study, 54.4% initiated treatment. There was no difference in return-to-work outcomes over the follow-up period between the referrals who initiated treatment (29.9%) and the 215 referrals not initiating treatment (32.5%, p = 0.612). In contrast, return-to-work outcomes were more positive among the matched non-referral comparison group (41.9%, p < 0.001, all referrals vs the matched non-referral comparison group). CONCLUSION: In this large cohort of PSPs disabled by PTSD, there was no evidence of a positive treatment effect on return-to-work outcomes. The prognosis for return-to-work among public safety personnel with long durations of recovery from PTSD is poor. The implications of this study point to the importance of the development and testing of novel evidence-based treatments and opportunities to support employers' commitment and capacity to provide suitable accommodation as strategies to improve return-to-work outcomes among public safety personnel disabled by PTSD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".