Burnout and occupational stress of home care rehabilitation professionals transitioning out of the COVID-19 pandemic in Ontario, Canada
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has significantly impacted the home healthcare industry, with increased rates of burnout and stress among homecare rehabilitation professionals (hcRPs). This study aimed to (1) examine the nature of burnout and occupational stress among homecare rehabilitation professionals at a large home care organization in Ontario, Canada, transitioning out of the pandemic, and (2) assess its impact on work participation and engagement. Methods: We conducted a cross-sectional survey using the National Institute for Occupational Safety and Health Generic Job Stress Questionnaire and Copenhagen Burnout Inventory to examine burnout and job stress. Results: One hundred thirty-nine participants identified that work stress and burnout are more likely to occur when one struggles to cope, experiences unexpected circumstances, and feels a lack of control, which can lead to anger and emotional exhaustion. The adjusted odds ratio for emotional exhaustion was 5.46, indicating that the probability of experiencing work stress among homecare rehabilitation professionals increases as emotional exhaustion increases. Significant associations were found between coping with daily tasks and levels of burnout. Conclusion: Work stress and burnout influence coping, unexpected circumstances in homecare rehabilitation professionals work-life. Furthermore, highlighting the need to provide organizational support and policies that specifically address these issues in the home care sector.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".