Reliable and valid assessment of ultrasound operator competence in obstetrics and gynecology
Bibliographic record
Abstract
OBJECTIVES: To explore the reliability and validity of a recently developed instrument for assessment of ultrasound operator competence, the Objective Structured Assessment of Ultrasound Skills (OSAUS). METHODS: Three groups of 10 doctors with different levels of ultrasound experience in obstetrics and gynecology were included. The novices had less than 1 month of experience, the intermediate group had 12-60 months of experience and the senior participants were all consultants. Fifteen participants performed transabdominal fetal biometry and the other 15 participants performed systematic transvaginal gynecological ultrasound scans. All scans were video-recorded and assessed by two blinded consultants using the OSAUS scale. The OSAUS scores were compared between the groups using the Kruskal-Wallis test, and pass/fail scores were determined using the contrasting-groups method of standard setting. RESULTS: For the transabdominal fetal biometry examinations, the mean ± SD OSAUS scores of the novices, intermediates and senior participants were 1.5 ± 0.4, 3.3 ± 0.6 and 4.4 ± 0.4, respectively (P = 0.003). For the systematic transvaginal scans, the mean ± SD OSAUS scores of the novices, intermediates and senior participants were 1.8 ± 0.2, 3.1 ± 0.1 and 3.9 ± 0.5, respectively (P = 0.003). Post-hoc comparisons showed significant differences between each of the groups for both types of scans. The pass/fail score was 2.5 for the transvaginal scan and 3.0 for the transabdominal biometry examinations. The inter-rater reliability was 0.89. CONCLUSIONS: Ultrasound competence can be assessed in a reliable and valid way using the OSAUS scale. The pass/fail scores may be used to help determine when trainees are qualified for independent practice.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".