Examining Predictors of Compassion Fatigue in Intensive Care Nurses
Bibliographic record
Abstract
Background: Registered nurses (RN) working in intensive care units (ICU) care for some of the sickest patients with the highest acuity within hospital settings. Due to the nature of their work and proximity to patient trauma they are at risk for developing compassion fatigue. Compassion fatigue is defined as a secondary traumatic stress reaction which results from a deep involvement with a primarily traumatized person and is described as a work-related stress response in healthcare providers. Compassion fatigue negatively impacts nurses, patients, and organizations with significant implications for the nursing profession. Research focusing on the predictors of nurses’ compassion fatigue in ICUs is limited. Purpose: To test a theoretical model examining selected predictors (exposure to patient suffering, nurses’ age, nurses’ years of experience in ICU, managerial support) of compassion fatigue in RNs working in ICU. Methods: A descriptive cross-sectional survey design was conducted with a sample of 81 RNs working in an ICU in Southeastern Ontario. Participants were asked to complete an online questionnaire including demographic characteristics, Satisfaction with my Manager Scale, and Secondary Traumatic Stress Scale. Results: Participants reported a moderate level of compassion fatigue with 48% reporting mild levels and 39% reporting high or severe levels. Testing of the theoretical model found 18% of the variance in participants’ compassion fatigue was explained by three predictors (exposure to patient suffering, nurses’ years of experience in ICU, managerial support). However, only managerial support was a significant predictor in the final model. Conclusion: The major contribution of this study is the broadening of our understanding of nurses’ compassion fatigue in ICU. The study findings suggest that nurses working in ICU value managerial support to help minimize compassion fatigue. This includes managers being visible, consulting with staff, providing praise and recognition, and where able, being flexible with work schedules. Improving managerial support in ICU environments may help nurses remain empathetic and provide compassionate care.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".