Knowledge of students from a health science university on human error and patient safety
Bibliographic record
Abstract
Objective: This research aimed to identify the knowledge of students from a health science university on human error and patient safety.Methods: This is an observational, cross-sectional research with a quantitative approach. A total of 228 students of the following baccalaureate courses participated: Physical Education, Nursing, Medicine, Nutrition, and Psychology. The study was conducted in the second semester of 2019 through an online questionnaire with 27 closed and 4 open questions. Simple frequencies, central tendency measures, and correlation tests were used to analyze the data. The IRAMUTEQ software was used to analyze the answers to open questions.Results: The study demonstrated that the Nursing students had more contact with the patient safety theme and greater confidence to perform techniques during clinical practice. In general, students pointed out positive responses regarding knowledge about patient safety, such as: recognition of the possibility of errors, the importance of communication, and learning from mistakes.Conclusion: The results may contribute to strengthening teaching about patient safety in universities.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".