Student nurses’ views on an E-Learning module on comfort, safety, and mobility with older adults: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Nursing students often receive insufficient training in older adults' care. PURPOSE: Examine nursing students' perceptions of an e-learning module developed to enhance their knowledge about the comfort, safety, and mobility of older adults. METHODS: A cross-sectional survey was administered to third-year baccalaureate nursing students at a Canadian university after they had completed the comfort, safety, and mobility module. The survey assessed students' perceptions of the e-learning module using four 5-pointLikert-type items. The survey also contained demographic questions and one open-ended question that invited participants to make any comments they wished. Descriptive statistics were used to summarize participants'demographic characteristics. Responses to the open-ended quesiton were summative content analyzed. RESULTS: The survey was completed by 119 participants, who reported that the module increased their confidence, perceptions and knowledge in working with older adults. Participants also found the method of instruction to be convenient, interactive, and enjoyable. CONCLUSIONS: Results suggest that the learning module has the potential to facilitate student nurses' learning about comfort, safety, and mobility.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".