Compassion Fatigue, Burnout, and Compassion Satisfaction Among Oncology Nurses in the United States and Canada
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To examine the experiences of compassion fatigue, burnout, and compassion satisfaction among oncology nurses in the United States and Canada. . DESIGN: Quantitative, descriptive, nonexperimental. . SETTING: Online survey with members from the Canadian Association of Nursing Oncology and the Oncology Nursing Society. . SAMPLE: 486 American and 63 Canadian practicing oncology nurses. . METHODS: The Professional Quality of Life (ProQOL) scale, version 5, and modified Abendroth Demographic Questionnaire were administered through FluidSurveys™, an online data collection instrument. Chi-square tests of independence were used to investigate associations between demographic characteristics, health, personal stressors, and work-related characteristics to experiences of compassion fatigue, burnout, and compassion satisfaction. Compassion fatigue was measured using the subscales of secondary traumatic stress and burnout. . MAIN RESEARCH VARIABLES: Compassion fatigue, burnout, and compassion satisfaction. . FINDINGS: Demographic characteristics were similar in American and Canadian participants, and both cohorts reported comparable levels of compassion fatigue, burnout, and compassion satisfaction. Perception of team cohesiveness within the workplace environment was found to be significant for both groups, as indicated by significant relationships in all three subscales of secondary traumatic stress, burnout, and compassion satisfaction in the ProQOL. . CONCLUSIONS: Healthy and supportive work environments are imperative to nurses' health, well-being, and satisfaction. Improvements in the workplace can help prevent negative sequelae, as well as improve health outcomes for patients and nurses, decrease nurse turnover, and reduce healthcare expenditures. . IMPLICATIONS FOR NURSING: Findings can be used to implement institutional changes, such as creating policies and guidelines for the development of preventive interventions and psychosocial support for nurses.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".