Beta Test Results of a New System Assessing Competence in Laparoscopic Surgery
Bibliographic record
Abstract
BACKGROUND: There is currently a need for objective measures of surgical competence. Such measures should assess knowledge, judgment, and manual skills. The Fundamentals of Laparoscopic Surgery (FLS) program was developed by the Society of American Gastrointestinal and Endoscopic Surgeons to meet these criteria. The FLS assessment includes a multiple-choice cognitive test and a manual skills test. We present the results of validation studies of this novel assessment tool. STUDY DESIGN: Beta testing of the FLS examination was undertaken at 7 sites by 70 surgeons representing 4 levels of experience and training. Surgeons provided information about their prior experience and indicated a self-assessment of their laparoscopic competence. Results were assessed by ANOVA followed by orthogonal contrasts. RESULTS: Cognitive performance by training level: There was no difference between fellows and staff in percentage of questions answered correctly, but there was a discrepancy between junior and senior residents and between residents and senior surgeons (p < 0.01). Cognitive performance by laparoscopic experience quartiles: There were notable contrasts between the first and second quartiles of experience (p < 0.02) and between the third and fourth quartiles (p < 0.01). No marked difference was found between the second and third quartiles. Cognitive performance compared with self-assessment: Test results were substantially different (p < 0.01) between test-takers who assessed themselves as "better than average" and those who assessed themselves as "average" or "below average." Manual skills performance by training level: The major difference was found between junior residents versus senior residents, fellows or staff (p < 0.01). Manual skills performance by laparoscopic experience level: Differences were primarily seen between the first two quartiles and the last two quartiles of laparoscopic experience (p < 0.001). Manual skills performance compared with self-assessment: Those who assessed themselves as "above average" in laparoscopic skill performed markedly better than those indicating they had "average" or "below average" skill (p < 0.01). CONCLUSIONS: Beta test results for the FLS examination demonstrate satisfactory reliability, appropriate psychometric properties, and substantial initial validity. The FLS project is one of the first validated surgical education efforts to assess the competence of surgeons in a specific field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".