Providing direction for change: assessing Canadian nursing students learning needs
Bibliographic record
Abstract
AIM: To examine the current curriculum content and learning needs of graduating nursing students related to end-of-life care (EOLC). DESIGN: A survey method was employed. SAMPLE: A purposive sample of 58 Anglophone and Francophone students completed the Palliative Care Quiz for Nursing (PCQN) and Frommelt's Attitudes Toward Care of the Dying Scale (FATCOD). Students responded to open-ended questions regarding perceptions of preparedness to care for terminally ill patients, and provided suggestions for changes to the curriculum. Key informant educators identified opportunities to include EOLC content in courses and clinical placements. RESULTS: Results indicated that students held positive attitudes towards caring for dying patients, had modest knowledge levels, and that one third did not feel adequately prepared to care for dying patients. Although EOLC education tends to be threaded throughout the program, the emphasis is dependent upon the commitment of individual professors and clinical instructors with experience and/or expertise in this area. CONCLUSION: Students and educators agreed more emphasis on EOLC was needed. Recommendations include development of teaching strategies and experiential learning in EOLC throughout the curriculum.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".