https://canadianoncologynursingjournal.com/index.php/conj/article/view/982
Bibliographic record
Abstract
Effective patient education can influence cost savings and improve patient outcomes (CCO, 2006). Nursing staff provide education to patients and families through the assessment of learning needs, incorporating the teach-back method to assess comprehension, and documenting the care provided. For this pilot study, an educational intervention was developed incorporating a mnemonic memory aid to support a consistent, standardized approach in delivering effective patient teaching. Forty-five hematology nurses from Hamilton Health Sciences participated in the study, of which 36 completed the follow-up assessments. The mnemonic aid "CARE", developed for this study, helped nurses to recall the steps involved in patient education. The improved knowledge and the use of the mnemonic aid in patient education was sustained over the three- to six-weeks follow-up period. While there was an increase in documentation of the patient education after the intervention, the changes did not reach the statistically significant level. Further research on the use of mnemonics in nursing education would complement this pilot study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.675 | 0.215 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".