doi:10.1155/2011/907172 Research Article An Examination of Palliative or End-of-Life Care Education in Introductory Nursing Programs across Canada
Bibliographic record
Abstract
Copyright © 2011 Donna M. Wilson et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. An investigation was done to assess for and describe the end-of-life education provided in Canadian nursing programs to prepare students for practice. All 35 university nursing schools/faculties were surveyed in 2004; 29 (82.9%) responded. At that time, all but one routinely provided this education, with that school developing a course (implemented the next year). As compared to past surveys, this survey revealed more class time, practicum hours, and topics covered, with this content and experiences deliberately planned and placed in curriculums. A check in 2010 revealed that all of these schools were providing death education similar to that described in 2004. These findings indicate that nurse educators recognize the need for all nurses to be prepared to care for dying persons and their families. Regardless, more needs to be done to ensure novice nurses feel capable of providing end-of-life care. Death education developments will be needed as deaths increase with population aging. 1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.680 | 0.410 |
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".