Recent Trends in Continuing Medical Education Among Obstetrician–Gynecologists
Bibliographic record
Abstract
OBJECTIVE: To estimate current trends in continuing medical education among obstetrician-gynecologists in relation to the Maintenance of Certification program. METHODS: A validated questionnaire was mailed to 1,030 randomly selected physicians of the American College of Obstetricians and Gynecologists in the United States, Puerto Rico, and Canada. Participants were asked about current practices and opinions regarding continuing medical education activities. Responses were compared between members mandated for Maintenance of Certification (board certification 1986 or later; time-limited certificate) or not (board certification before 1986; nontime-limited certificate). RESULTS: Five hundred twenty (50.4%) surveys were completed. Respondents were more often male (57.1%), generalists (87.3%), in community-based (73.8%) group practices (77.2%) with mean (±standard deviation) age 52.4±9.9 years. College physicians mandated to participate in the Maintenance of Certification program were more likely to rely on Annual Board Certification articles as a major source of continuing medical education credits compared with those not requiring Maintenance of Certification (79.9% compared with 44.6%, P<.001). This finding remained significant after multivariable adjustment for age, gender, years in practice, and practice type (odds ratio [OR] 9.09, 95% confidence interval [CI] 4.03-20.5). Conversely, Maintenance of Certification requirement led to decreased use of the national or international meetings (OR 0.31, 95% CI 0.14-0.67) and self-selected continuing medical education materials (OR 0.29, 95% CI 0.14-0.60) as sources of continuing medical education credits. Despite these differences, physicians in both groups equally valued the relevance of Annual Board Certification articles (92.6% compared with 96.4%, P=.23), the importance of content at academic meetings (98.3% compared with 99.3%, P=.33), the usefulness of simulation drills (97.8% compared with 94.3%, P=.35), and the general ability of continuing medical education activities to improve skills as a physician (90.9% compared with 86.4%, P=.20). CONCLUSION: Requirement of the Maintenance of Certification program has led to significant changes in continuing medical education choices by obstetrician-gynecologists. The changes in continuing medical education appear related to mandated obligations rather than personal preference.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".