Non‐technical skills curriculum incorporating simulation‐based training improves performance in colonoscopy among novice endoscopists: Randomized controlled trial
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND AIMS: Non-technical skills (NTS), involving cognitive, social and interpersonal skills that complement technical skills, are important for the completion of safe and efficient procedures. We investigated the impact of a simulation-based curriculum with dedicated NTS training on novice endoscopists' performance of clinical colonoscopies. METHODS: A single-blinded randomized controlled trial was conducted at a single center. Novice endoscopists were randomized to a control curriculum or a NTS curriculum. The control curriculum involved a didactic session, virtual reality (VR) simulator colonoscopy training, and integrated scenario practice using a VR simulator, a standardized patient, and endoscopy nurse. Feedback and training were provided by experienced endoscopists. The NTS curriculum group received similar training that included a small-group session on NTS, feedback targeting NTS, and access to a self-reflective NTS checklist. The primary outcome was performance during two clinical colonoscopies, assessed using the Joint Advisory Group Direct Observation of Procedural Skills (JAG DOPS) tool. RESULTS: Thirty-nine participants completed the study. The NTS group (n = 21) had superior clinical performance during their first (P < 0.001) and second clinical colonoscopies (P < .0.001), compared to the control group (n = 18). The NTS group performed significantly better on the VR simulator (P < 0.05) and in the integrated scenario (P < 0.05). CONCLUSION: Our findings demonstrate that dedicated NTS training led to improved performance of clinical colonoscopies among novices.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 it