The Influence of Areas of Worklife and Compassion Satisfaction on Burnout of Mental Health Nurses
Bibliographic record
Abstract
The prevalence of burnout among nurses is linked to sub-optimal wellbeing and is reflected in higher than average rates of illness and absenteeism (Canadian Institute for Health Information, [CIHI], 2007). Additionally, there are consequences for clients including increased staff related errors and poor patient satisfaction. An improved person-job match in the six areas of worklife and higher compassion satisfaction may result in a workforce that is more engaged and able to achieve positive client outcomes. This study explores the relationship between person-job match and both compassion satisfaction and the emotional exhaustion component of burnout of mental health nurses through a secondary analysis of data previously collected as part of a larger study of compassion satisfaction, compassion fatigue and burnout among mental health staff. Findings indicated that compassion satisfaction partially mediates the relationship between person-job match and the emotional exhaustion component of burnout. Further, overall person-job match and compassion satisfaction explained 43% of the variance in emotional exhaustion (F(2, 65) = 25.092, p = 0.005, R2 = 0.430). Findings suggest that improved person-job match and compassion satisfaction would be beneficial in reducing burnout among mental health nurses.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".