Nursing student patient safety errors in the practice domain: a scoping review protocol of the quantitative and qualitative evidence
Bibliographic record
Abstract
REVIEW QUESTION/OBJECTIVE: The objective of this scoping review is to identify the range of patient safety events that includes patient safety errors, harms or near misses that student nurses make while nursing in their clinical placements. The question that will guide this review is: what types of hazards, healthcare-associated harms, patient safety incidents, reportable circumstances, near misses, harmful incidents, no harm incidents and injuries to patients are being made and reported by nursing students during their practice in healthcare facilities?
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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 | 0.113 | 0.158 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.014 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".