Student peer teaching in paediatric simulation training is a feasible low‐cost alternative for education
Bibliographic record
Abstract
AIM: The World Health Organization recommends regular simulation training to prevent adverse healthcare events. We used specially trained medical students to provide paediatric simulation training to their peers and assessed feasibility, cost and confidence of students who attended the courses. METHODS: Students at the Medical University of Vienna, Austria were eligible to participate. Students attended two high-fidelity simulation training sessions, delivered by peers, which were videorecorded for evaluation. The attendees then completed questionnaires before and after the training. Associated costs and potential benefits were analysed. RESULTS: From May 2013 to June 2015, 152 students attended the sessions and 57 (37.5%) completed both questionnaires. Satisfaction was high, with 95% stating their peer tutor was competent and 90% saying that peer tutors were well prepared. The attendees' confidence in treating critically ill children significantly improved after training (p < 0.001). The average costs for a peer tutor were six Euros per working hour, compared to 35 Euros for a physician. CONCLUSION: Using peer tutors for paediatric simulation training was a feasible and low-cost option that increased the number of medical students who could be trained and increased the self-confidence of the attendees. Satisfaction with the peer tutors was high.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".