Improving Medical Student Comfort and Competence in Performing Gynecological Exams: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Performing a gynecological exam is an essential skill for physicians. While interventions have been implemented to optimize how this skill is taught in medical school, it remains an area of concern and anxiety for many medical students. To date, a comprehensive assessment of these interventions has not been done. The authors conducted a systematic review of the literature on interventions that aim to improve medical student education on gynecological exams. METHOD: The authors searched 6 databases (Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL Plus, Scopus, Web of Science Core Collection, and ERIC [Proquest]) from inception to August 4, 2020. Studies were included if they met the following criteria: focus on medical students, intervention with the purpose of teaching students to better perform gynecological exams, and reported outcomes/evaluation. Extracted data included study location, study design, sample size, details of the intervention and evaluation, and context of the pelvic exam. All outcomes were summarized descriptively; key outcomes were coded as subjective or objective assessments. RESULTS: The search identified 5,792 studies; 50 met the inclusion criteria. The interventions described were diverse, with many controlled studies evaluating multiple methods of instruction. Gynecological teaching associates (GTAs), or professional patients, were the most common method of education. GTA-led teaching resulted in improvements in student confidence, competence, and communication skills. Physical adjuncts, or anatomic models and simulators, were the second most common category of intervention. Less resource-intensive interventions, such as self-directed learning packages, online training modules, and video clips, also demonstrated positive results in student comfort and competence. All studies highlighted the need for improved education on gynecological exams. CONCLUSIONS: The literature included evaluations of numerous interventions for improving medical student comfort and competence in performing gynecological exams. GTA-led teaching may be the most impactful educational tool described, though less resource-intensive interventions can also be effective.
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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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".