[Resiliency : evaluation of a teaching initiative with second year nursing students]
Bibliographic record
Abstract
Introduction : resilience is the ability that helps an individual adapt and grow during difficult moments. It is an essential aspect of ensuring the quality of care. Context : nursing schools need to cultivate resilience among their students. Despite the growing popularity of the benefits of being resilient, few studies or teaching strategies exist in the literature in the nursing area. Objective : this article describes the implementation of a new learning initiative with a group of Canadian nursing students enrolled in a care and chronicity course. Method : the four part project sought to increase students’ knowledge about resilience and apply this knowledge during an interview with a person living or having lived a difficult experience. An electronic survey answered by 42 students helps evaluate the project’s objectives. Results : three quarter of the students stated having increased their knowledge about resilience and applied this information during their interview and two thirds stated that the project would influence future interactions with the care receivers. Discussion : several recommendations were brought forth to help enhance the learning initiative and expand it throughout the program and even beyond, by introducing it in other health related programs offered by the Faculty.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".