Objective assessment of surgical competence in gynaecological laparoscopy: development and validation of a procedure‐specific rating scale
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to develop a global- and a procedure-specific rating scale based on a well-validated generic model (objective structured assessment of technical skills) for assessment of technical skills in laparoscopic gynaecology. Furthermore, we aimed to investigate the construct validity and the interrater agreement (IRA) of the rating scale. We investigated both the gamma coefficient (Kendall's rank correlation), which is a measure of the strength of dependence between observations, and the kappa value for each of the ten individual items included in the rating scale. DESIGN: Prospective cohort, observer-blinded study. SETTING: Departments of Obstetrics and Gynaecology in Zealand, Denmark. POPULATION: Twenty one gynaecologists or gynaecological trainees. MATERIAL AND METHODS: Twenty-one video recordings of right side laparoscopic salpingectomies were collected prospectively, eight from novices (defined as <10 procedures), seven from intermediate experienced (20-50 procedures) and six from experts (> 200 procedures). All operations were performed by the same operative principles and using a standardised technique. The recordings were analysed by two independent, blinded observers. MAIN OUTCOME MEASURES: Construct validity of the rating scale based on operative performance (median of total score) and interrater reliability. RESULTS: There were significant differences between the three groups: median score of novices 24.00 versus intermediate 29.50 versus expert 39.50, P < 0.003) The IRA was 0.83 overall. The gamma correlation coefficient was 0.91. The kappa values varied from 0.510-0.933 for each of the individual items of the rating scale. CONCLUSIONS: The procedure-specific rating scale for laparoscopic salpingectomy is a valid and reliable tool for assessment of technical skills in gynaecological laparoscopy.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".