How Mental Health Nurses Report Their Compassion Fatigue and Compassion Satisfaction: A Cross-Sectional Study and the Implications for Healthcare Leaders
Bibliographic record
Abstract
Compassion fatigue is the cost of caring for others in emotional pain where the helping professional absorbs the trauma of those they help and cannot detach emotionally at the end of the day. Stressful and perceived unsupportive work environments may leave the caregiver at a heightened risk for compassion fatigue. To study the level of compassion fatigue and compassion satisfaction experienced by mental health nurses. A descriptive, cross-sectional, electronic survey design was utilized. The Professional Quality of Life Scale-5 was used. The study was conducted at a large, urban hospital that exclusively treats patients with mental health and addiction issues located in Ontario, Canada. The sample included all nurses who were listed on the hospital's Email list. All nurses who are displayed on this list are mental health nurses. Analyses were conducted to assess for differences between the characteristics and the subscales of professional quality of life. One hundred and forty-eight mental health nurses completed a questionnaire. The response rate was 21%. Seventy-six percent reported moderate levels of burnout, 59% reported moderate levels of secondary traumatic stress, and 21% reported high levels of compassion satisfaction. Predictors were seen for the characteristics of gender, ethnicity, marital status, area, exposure to violence and support felt. Compassion fatigue has clear implications. Organizations willing to invest in reducing it, have the potential to improve patient outcomes and the well-being of nurses. The majority of mental health nurses reported moderate levels for each of the subscales.
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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 | 0.003 | 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 | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".