Individualized Deliberate Practice on a Virtual Reality Simulator Improves Technical Performance of Surgical Novices in the Operating Room
Bibliographic record
Abstract
In Brief Objective: The purpose of this study was to investigate whether individualized deliberate practice on a virtual reality (VR) simulator results in improved technical performance in the operating room. Background: Training on VR simulators has been shown to improve technical performance in the operating room (OR). Currently described VR curricula consist of trainees practicing the same tasks until expert proficiency is reached. It has yet to be investigated whether the individualized deliberate practice, where curricula tasks vary depending on prior levels of technical proficiency, would translate into the OR. Methods: This single-blinded prospective trial randomized 16 novice surgical residents to a deliberate practice (DP) group and a conventional residency training group. Both groups performed a laparoscopic cholecystectomy in the OR that was video-recorded. Technical performance of DP group residents in the OR was assessed using 3 validated assessment tools. A score of less than 60% on any component of the assessment tool resulted in the trainee practicing a specific task on the VR simulator. The DP group practiced on the simulator as per their individualized schedule. Both groups then performed another laparoscopic cholecystectomy. A blinded expert assessed the OR recordings using a validated global rating scale. Results: Although both groups had similar technical abilities preintervention [DP: median score, 13.5 (9.3–15.0); control: median score, 14.5 (9.3–17.8); P = 0.45], the DP residents had a superior technical performance postintervention [DP: median score, 17.0 (15.3–18.5); control: median score, 12.5 (7.5–14.0); P = 0.03]. Of 8 DP residents, 6 practiced 5 basic VR tasks (median 1 trial to pass), and 7 of 8 practiced 2 advanced tasks (median 4 trials to pass). Conclusions: A curriculum of deliberate individualized practice on a VR simulator improves technical performance in the OR. This has implications to greatly improve the feasibility of implementing simulation-based curricula in residency training programs, rather then having them being limited to research protocols. Currently described simulation-based curricula consist of trainees practicing the same tasks until expert proficiency is reached. It has yet to be investigated whether the individualized deliberate practice, where curricula tasks vary depending on prior levels of technical proficiency, would translate into the operating room. This randomized controlled trial effectively demonstrates that deliberate practice on a virtual reality simulator results in an improvement in technical skills in a real clinical situation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".