Resources for Educating, Training, and Mentoring Nurses and Unregulated Nursing Care Providers in Palliative Care: A Review and Expert Consultation
Bibliographic record
Abstract
BACKGROUND: Nurses and nursing care providers provide the most direct care to patients at end of life. Yet, evidence indicates that many feel ill-prepared for the complexity of palliative care. OBJECTIVE: To review the resources required to ensure adequate education, training, and mentorship for nurses and nursing care providers who care for Canadians experiencing life-limiting illness and their families. METHODS: This is a systematic search and narrative review in the Canadian context. RESULTS: Six previous reviews and 26 primary studies were identified. Studies focusing on regulated nurses indicated that even amid variability in content, delivery methods, and duration, palliative education improves nurses' knowledge, confidence, attitudes, and communication abilities, and decreases nurses' stress. Results from palliative education in undergraduate curriculum were less definitive. However, studies on palliative simulation in undergraduate education suggest that it improves knowledge and confidence. Studies focusing on educating nursing care providers, either alone or in collaboration with regulated nurses, indicated positive outcomes in knowledge, confidence, communication, identification of clients who are dying, abilities to interact with patients and families, and a better understanding of their own contributions to care. Curricular resources in Canada have been developed. However, there is no dedicated and funded capacity-building strategy. DISCUSSION: Resources exist to support palliative education for nurses and nursing care providers. Furthermore, the evidence suggests good outcomes from this education. However, there is no dedicated strategy for implementing those resources. Furthermore, there is little evidence of the critical role of knowledge translation in preparing nurses and nursing care providers for evidence-informed palliative practice.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".