The Current State of Ultrasound Training in Obstetrics and Gynecology Residency Programs
Bibliographic record
Abstract
OBJECTIVES: We evaluated the current state of ultrasound training in obstetrics and gynecology (OB-GYN) residency programs across the United States. METHODS: An electronic survey was sent to OB-GYN residency program directors and OB-GYN residents. Responses were obtained in September 2016. Program directors and residents were asked to reflect on their current ultrasound curriculum. RESULTS: A total of 93 program directors and 437 residents responded. Respondents were mostly from university programs located in tertiary centers. Ultrasound curricula varied: 11% of program directors and 23% of residents did not have any ultrasound-related didactics; of those who did, 27% of program directors and 40% of residents had it yearly or less. Three-quarters had mandatory ultrasound rotations, and few offered ultrasound electives (program directors, 52%; residents, 28%). Most residents were required to perform ultrasound examinations daily or weekly (98%). Most stated that the main focus of the rotation was OB only. Skill was evaluated mainly subjectively by direct observation. Although most program directors stated that residents were satisfactory/excellent in ultrasound, 22% would not treat patients on the basis of ultrasound examinations performed by their senior residents. Similarly, of all postgraduate year 4 respondents (n = 86), 76% stated that they will require additional training to be able to perform or read ultrasound examinations independently, and 43% would not treat a patient on the basis of their own ultrasound examinations without further confirmation. Residents believed that the biggest obstacle in ultrasound training is lack of dedicated faculty time (41%). CONCLUSIONS: Recognizing the lack of clearly defined milestones in ultrasound training in OB-GYN residency, this study confirms the substantial heterogeneity in curricula between programs, highlighting a need for a standardized ultrasound curriculum.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".