General Versus Technique-Specific Surgical Skills Assessments: Do We Need to Reinvent the Wheel?
Bibliographic record
Abstract
Background: Reliable and valid methods of evaluating operative performance are essential for surgical training programs and education research. Laparoscopic surgery entails a unique skill set, but it is unclear whether it requires a specific assessment form or whether more general assessment tools can be applied. The primary purpose of this study was to assess the concurrent validity of 2 previously validated assessment scales. One of these scales was designed specifically to assess laparoscopic skills and the other to assess more general surgical skills. Construct validity and reliability of both scales were also assessed.Methods: Postgraduate year (PGY) 1–5 general surgery and urology residents (N = 33) performed a live human laparoscopic cholecystectomy. Three attending surgeon raters scored their performance using previously validated objective structured assessment of technical skills (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS) global rating scales.Results: Pearson's correlation coefficient between OSATS and GOALS was 0.975 (P = .01). Evidence of construct validity was demonstrated for both OSATS and GOALS with senior residents (PGY 3–5) demonstrating significantly higher scores than the junior (PGY 1–2) group (P < .001). Both OSATS and GOALS demonstrated reliability with a Cronbach's alpha of 0.959 and 0.957, respectively.Conclusions: Reliability and construct validity were confirmed for both OSATS and GOALS global rating scales. The near total correlation between the 2 scales questions the need for separate laparoscopic assessment tools. This study highlights the real strengths of OSATS, the use of which allows for more consistent nomenclature and standardized skills assessment across surgical platforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".