Development and Validation of a Comprehensive Curriculum to Teach an Advanced Minimally Invasive Procedure
Bibliographic record
Abstract
OBJECTIVE: To develop and validate a comprehensive ex vivo training curriculum for laparoscopic colorectal surgery. BACKGROUND: Simulators have been shown to be viable systems for teaching technical skills outside the operating room; however, integration of simulation training into comprehensive curricula remains a major challenge in modern surgical education. Currently, no curricula have been described or validated for advanced laparoscopic procedures. METHODS: This prospective, single-blinded randomized controlled trial allocated 25 surgical residents to receive either conventional residency training or a comprehensive training curriculum for laparoscopic colorectal surgery. The curriculum consisted of proficiency-based psychomotor training on a virtual reality simulator, cognitive training, and participation in a cadaver lab. The primary outcome measure in this study was surgical performance in the operating room. All participants performed a laparoscopic right colectomy, which was video recorded and assessed using 2 previously validated assessment tools. Secondary outcome measures were knowledge relating to the execution of the procedure, assessed with a multiple-choice test, and technical performance on the simulator. RESULTS: Curricular-trained residents demonstrated superior performance in the operating room compared with conventionally trained residents (global score 16.0 [14.5-18.0] versus 8.0 [6.0-14.5], P = 0.030; number of operative steps performed 16.0 [12.5-17.5] versus 8.0 [6.0-14.5], P = 0.021; procedure-specific score 71.1 [54.4-81.6] versus 51.1 [36.7-74.4], P = 0.122). Curricular-trained residents scored higher on the multiple-choice test (10 [9-11] versus 7.5 [5.3-7.5], P = 0.047), and outperformed conventionally trained residents in 7 of 8 tasks on the simulator. CONCLUSIONS: Participation in a comprehensive ex vivo training curriculum for laparoscopic colorectal surgery results in improved technical knowledge and improved performance in the operating room compared with conventional residency training. Reg. ID#NCT 01371136.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".