Care Aides Compassion Fatigue, Burnout, and Compassion Satisfaction Related to Long-Term Care (LTC) Working Environment
Bibliographic record
Abstract
Severe staff shortages, sustained stress, low compassion satisfaction, high compassion fatigue, and serious levels of burnout among healthcare workers were frequently reported during COVID-19. In this cross-sectional study with 760 care aides working in 28 LTC homes in Alberta, Canada, we used a two-level multilevel regression model to examine how working environments were associated with compassion fatigue, burnout, and compassion satisfaction measured with the Professional Quality of Life (ProQOL-9) scale. Our findings showed that higher compassion satisfaction and lower burnout were observed when care aides perceived a more supportive working culture. Care aides reported higher compassion fatigue when there was a lack of structural or staffing resources. We also found that perceptions of not having enough staff or enough time to complete tasks were significantly associated with higher levels of burnout. These findings suggest which elements of the working environment may be promising targets for improvement efforts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".