Understanding Compassion Satisfaction, Compassion Fatigue and Burnout: A survey of the hospice palliative care workforce
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Despite the increasingly crucial role of the healthcare workforce and volunteers working in hospice and palliative care (HPC), very little is known about factors that promote or limit the positive outcomes associated with practicing compassion. AIM: The purpose of this study was to: 1) understand the complex relationships among Compassion Satisfaction, Compassion Fatigue and Burnout within the hospice and palliative care workforce and 2) explore how key practice characteristics - practice status, professional affiliation, and principal institution - interact with the measured constructs of Compassion Satisfaction, Compassion Fatigue and Burnout. DESIGN: Self-reported measures of Compassion Satisfaction, Compassion Fatigue and Burnout, using validated scales, as well as questions to describe socio-demographic profiles and key practice characteristics were obtained. SETTING/PARTICIPANTS: A national survey of HPC workers, comprising clinical, administrative, allied health workers and volunteers, was completed. Respondents from hospital, community-based and care homes informed the results of our study (n = 630). RESULTS: Our results indicate a significant negative correlation between Compassion Satisfaction and Burnout (r = -0.531, p < 0.001) and between Compassion Satisfaction and Compassion Fatigue (r = -0.208, p < 0.001), and a significant positive correlation between Burnout and Compassion Fatigue (r = 0.532, p < 0.001). Variations in self-reported levels of the above constructs were noted by key practice characteristics. Levels of all three constructs are significantly, but differentially, affected by type of service provided, principal institution, practice status and professional affiliation. Results indicate that health care systems could increase the prevalence of Compassion Satisfaction through both policy and institutional level programs to support HPC professionals in their jurisdictions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it