The Montreal augmentation mammoplasty operation (MAMO) simulator: A novel method of training and assessing competence in plastic surgery
Bibliographic record
Abstract
Augmentation mammoplasty procedure remains the most commonly performed aesthetic procedure in plastic surgery. Residents’ training and technical skills assessment in this domain can prove to be challenging due to the limited access to private clinics where such procedures take place. An advanced simulation training environment can provide an alternative tool to train and assess residents’ performance, especially in the era of Competency-Based Education. The purpose of this project was to develop a simulator capable of replicating the essential steps of an augmentation mammoplasty procedure and achieve its face, content and construct validations.After identifying the essential surgical steps of the procedure using the modified Delphi methodology, a pilot project was undertaken to develop an early prototype part-task trainer in the aim of evaluating the silicone materials used. Following satisfactory realism scores achieved by the part-task trainer, the Montreal Augmentation Mammoplasty Operation (MAMO) simulator was developed using molding and casting techniques. All anatomical structures were replicated using adequate silicone material and alterations to the benchtop simulator were made to attain maximum reusability. This study design was a prospective blinded observational study. Plastic surgeons, both staff and residents, were recruited to perform a mammoplasty procedure on the simulator. Following an instructional video, participants completed the essential steps of the procedure and their performance was filmed. The expert surgeon participants evaluated the simulator’s various parameters and their overall experience. Video recordings of all participants’ performances were blindly reviewed and assessed using the Objective Structured Assessment of Technical Skills (OSATS) system: Global Rating Scale (GRS) score, Mammoplasty Objective Assessment Tool (MOAT) score and a Checklist score. Data was recorded as mean (SD).Twenty-one participants were enrolled in this study (14 residents and 7 experts). Mean values of residents and experts were 23.4 (2.5) vs 36.9 (3.1) (p<0.0001) for GRS score, 30.4 (2.2) vs 40 (3.2) (p<0.0001) for MOAT scores and 9.7 (1.5) vs 12 (1) (p<0.001) for Checklist scores respectively. Construct validation was achieved by the demonstrating significantly higher performance by experts with all the objective metric tools used. Face and content validations results showed excellent results among parameters evaluated, with an overall mean score of 4.8 (0.3) on 5. Cronbach’s alpha was 0.96 and 0.83 for GRS and MOAT scores respectively. Intraclass Correlation Coefficients for interrater reliability were excellent at 0.93, 0.92 and 0.89 for the total GRS, MOAT and Checklist scores respectively.This project demonstrated the validation of face, content and construct of the MAMO simulator. It also established the MAMO simulator system as the first Plastic Surgery-specific tool capable of consistently measuring residents’ performance and attributing competence in subpectoral mammoplasty procedures
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".