The exploration of remote simulation strategies for the acquisition of psychomotor skills in medicine: a pilot randomized controlled trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Progress in remote educational strategies was fueled by the advent of the COVID-19 pandemic. This pilot RCT explored the efficacy of a decentralized model of simulation based on principles of observational and peer-to-peer learning for the acquisition of surgical skills. Methods Sixty medical students from the University of Montreal learned the running subcuticular suture in four different conditions: (1) Control group (2) Self-learning (3) Peer-learning (4) Peer-learning with expert feedback. The control group learned with error-free videos, while the others, through videos illustrating strategic sub-optimal performances to be identified and discussed by students. Performance on a simulator at the end of the learning period, was assessed by an expert using a global rating scale (GRS) and checklist (CL). Results Students engaging in peer-to-peer learning strategies outperformed students who learned alone. The presence of an expert, and passive vs active observational learning strategies did not impact performance. Conclusion This study supports the efficacy of a remote learning strategy and demonstrates how collaborative discourse optimizes the students’ acquisition of surgical skills. These remote simulation strategies create the potential for implantation in future medical curriculum design. Trial Registration : NCT04425499 2020-05-06.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it