O-279 ASSESSING BURNOUT AND OCCUPATIONAL STRESS AMONG REHABILITATION PROFESSIONALS OF INDIGENOUS, BLACK, AND RACIALIZED BACKGROUNDS IN TORONTO, ONTARIO, CANADA
Bibliographic record
Abstract
Abstract Background Burnout and occupational stress can significantly impact home care rehabilitation professions (hcRPs) participation and engagement at work. The hcRPs provide services to clients who need help at home or long-term care facilities around the clock. This study aimed to understand burnout and job stress among hcRPs for racial/ethnic disparities related to burnout and occupational stress, and future policy implications. Methods We conducted in-depth interviews among the hcRPs with indigenous, marginalized, or racialized backgrounds. Participants from the equity-deserving groups were encouraged to describe their strategies to support their work-life balance and workplace mental health. The recorded data was transcribed, and thematic analysis was done using NVivo version 14. Results All the participants were female (n=10), from South Asian or of mixed-race backgrounds. Most participants were occupational therapists (6) or physiotherapists (3) and one speech therapist. All of them (100%) have experienced stress and burnout during the COVID-19 pandemic. The stressors and barriers included travel issues, increased client load, language barriers, discrimination, and work-life imbalance. Discussion hcRPs have experienced occupational stress due to fear of COVID-19 infection, concerns about transmitting the virus to loved ones, rapid changes in clinical practice, increased workload demands, and professional isolation. Participants also emphasized the support they received from their peers and employer during these challenging times. Conclusion This study is the first to explore burnout and occupational stress among RPs from racialized/ minority groups in Toronto, Ontario, Canada. Community-based organizations play a key role in fostering a safe, and inclusive work environment to improve the quality of home healthcare services.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".