The First Hybrid International Educational Comprehensive Cleft Care Workshop
Bibliographic record
Abstract
Objective Describe the first hybrid global simulation-based comprehensive cleft care workshop, evaluate impact on participants, and compare experiences based on in-person versus virtual attendance. Design Cross-sectional survey-based evaluation. Setting International comprehensive cleft care workshop. Participants Total of 489 participants. Interventions Three-day simulation-based hybrid comprehensive cleft care workshop. Main Outcome Measures Participant demographic data, perceived barriers and interventions needed for global comprehensive cleft care delivery, participant workshop satisfaction, and perceived short-term impact on practice stratified by in-person versus virtual attendance. Results The workshop included 489 participants from 5 continents. The response rate was 39.9%. Participants perceived financial factors (30.3%) the most significant barrier and improvement in training (39.8%) as the most important intervention to overcome barriers facing cleft care delivery in low to middle-income countries. All participants reported a high level of satisfaction with the workshop and a strong positive perceived short-term impact on their practice. Importantly, while this was true for both in-person and virtual attendees, in-person attendees reported a significantly higher satisfaction with the workshop (28.63 ± 3.08 vs 27.63 ± 3.93; P = .04) and perceived impact on their clinical practice (22.37 ± 3.42 vs 21.02 ± 3.45 P = .01). Conclusion Hybrid simulation-based educational comprehensive cleft care workshops are overall well received by participants and have a positive perceived impact on their clinical practices. In-person attendance is associated with significantly higher satisfaction and perceived impact on practice. Considering that financial and health constraints may limit live meeting attendance, future efforts will focus on making in-person and virtual attendance more comparable.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".