Simulation-Based Comprehensive Cleft Care Workshops: A Reproducible Model for Sustainable Education
Bibliographic record
Abstract
Objective: Evaluate simulation-based comprehensive cleft care workshops as a reproducible model for education with sustained impact. Design: Cross-sectional survey-based evaluation. Setting: Simulation-based comprehensive cleft care workshop. Participants: Total of 180 participants. Interventions: Three-day simulation-based comprehensive cleft care workshop. Main Outcome Measures: Number of workshop participants stratified by specialty, satisfaction with the workshop, satisfaction with simulation-based workshops as educational tools, impact on cleft surgery procedural confidence, short-term impact on clinical practice, medium-term impact on clinical practice. Results: The workshop included 180 participants from 5 continents. The response rate was 54.5%, with participants reporting high satisfaction with all aspects of the workshop and with simulation-based workshops as educational tools. Participants reported a significant improvement in cleft lip (33.3 ± 5.7 vs 25.7 ± 7.6; P < .001) and palate (32.4 ± 7.1 vs 23.7 ± 6.6; P < .001) surgery procedural confidence following the simulation sessions. Participants also reported a positive short-term and medium-term impact on their clinical practices. Conclusion: Simulation-based comprehensive cleft care workshops are well received by participants, lead to improved cleft surgery procedural confidence, and have a sustained positive impact on participants’ clinical practices. Future efforts should focus on evaluating and quantifying this perceived positive impact, as well reproducing these efforts in other areas of need.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".