Occupational Therapy and Public Safety Personnel: Return to Work Practices and Experiences
Bibliographic record
Abstract
Background. Public safety personnel (PSP) are frequently exposed to psychological trauma through their work. Evidence shows that worker's compensation claims for work-related psychological injuries are on the rise for PSP. Occupational therapists increasingly provide return to work (RTW) services for this population. Purpose. To explore the therapeutic practices and personal experiences of occupational therapists working with PSP who have work-related psychological injuries. Method. This mixed methods descriptive study included a chart review of available occupational therapy client records from 2016 to 2020 for PSP with work-related psychological injuries from two Ontario companies. Additionally, a web-based self-report survey for Ontario occupational therapists providing RTW services to this same population was available from November 1, 2021 to June 1, 2022. Findings. The chart review included 31 client records and the online survey was completed by 49 Ontario occupational therapists. Therapists commonly provided services in clients’ homes, workplaces, and communities, and focused on functional activities. The evidence base drawn on by therapists was not always occupation-based. Barriers to RTW included challenges with interprofessional collaboration, stigma, and the COVID-19 pandemic. Implications. Occupational therapists are commonly working with PSP with work-related psychological injuries and have the opportunity to contribute to the evidence base for occupational approaches to RTW.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".