Novel Performance Rating Instruments for Gynecological Procedures in Primary Care: A Pilot Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Improving training and confirming the acquisition of gynecological procedure skills for family physicians (FPs) is crucial for safe health care delivery. The objectives of this study were to (a) develop performance rating instruments for four gynecological procedures, and (b) pilot them to provide preliminary validity evidence using modern validity theory. METHODS: Sixteen academic FPs and gynecologists participated in a modified Delphi technique to develop procedure-specific checklists (PSCs) for four procedures: intrauterine device insertion, endometrial biopsy, punch biopsy of the vulva, and routine pessary care. We modified a previously validated global rating scale (GRS) for ambulatory settings. Using prerecorded videos, 19 academic FPs piloted instruments to rate one first-year and one second-year family medicine resident's performance. They were blinded to the level of training. We compared the mean scores for PSCs and GRS for each procedure using paired samples t tests and Cohen's d to estimate effect sizes. RESULTS: Consensus on items for the final PSCs was reached after two Delphi rounds. PSC and GRS scores were numerically higher for the second-year resident than the first-year resident for every procedure, with statistically significant differences for six of eight comparisons (P<.05). All comparisons demonstrated large effect sizes (Cohen's d>0.8). Both instruments received high scores for ease of use by raters. CONCLUSIONS: We developed novel performance rating instruments for four gynecological procedures and provided preliminary validity evidence for their use for formative feedback in a simulation setting. This pilot study suggests that these instruments may facilitate the training and documentation of family medicine trainees' skills in gynecological procedures.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".