Evaluating an Initiative to Promote Entry-Level Competence in Palliative and End-of-Life Care for Registered Nurses in Canada
Bibliographic record
Abstract
Numerous competency statements have been developed for the purpose of guiding nurse educators and clinicians. Rarely, though, are there evaluations of the use of these competency statements in practice. In this cross-sectional descriptive study, nurse educators were surveyed to determine how the Canadian Association of Schools of Nursing (CASN) Palliative and End-of-Life Care Entry-to-Practice Competencies and Indicators are used in schools of nursing in Canada. Twenty-four respondents consented to participating in this study. Findings supported that some version of palliative and end-of-life care (PEOLC) education was offered at each school of nursing in Canada, and it was most commonly threaded throughout existing undergraduate courses. Data also suggested that if nurse educators were interested in PEOLC and had existing knowledge or expertise in PEOLC, the CASN Palliative and End-of-Life Care competency document was used to integrate content into curricula. This study provides some initial insights into the use of the CASN Palliative and End-of-Life Care competency document in Canadian schools of nursing. Implications for additional research, policy, education, and practice are discussed.
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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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".