Houston, we have a problem! A cross-sectional survey of academic family physicians’ provision of gynecologic procedures
Bibliographic record
Abstract
Purpose: Globally, women and individuals with female-assigned reproductive organs experience barriers in accessing office-based gynecologic procedures (OBGPs), an issue compounded by the COVID-19 pandemic. This study aimed to provide a cross-sectional snapshot of the practice patterns of academic family physicians (AFPs) and identify the barriers they encounter when providing OBGPs. Methods: An anonymous survey was circulated to 17 family medicine departments across Canada. Eligible respondents were AFPs devoting >20% of their time to practicing family medicine. The survey included questions on demographics, practice patterns pre-post-pandemic, and barriers to performing OBGPs. Descriptive statistics and bivariate associations were computed. Results: Eighteen of 71 (26.9%) total respondents reported having enhanced skills training with a certificate of added competence (CAC). Most participants (97.2%) performed >1 Pap smear per month, while provision dropped to 5.6-67.7% for all other OBGPs assessed. A higher percentage of CAC holders in women’s health and low-risk obstetrics provided IUD insertions (100% vs. 67.3%) and endometrial biopsies (90.0% vs. 53.1%) than general AFPs. During the COVID-19 pandemic, respondents reported reducing or complete cessation of Pap Smears (44%) and all other OBGPs (20%). Barriers to offering OBGPs included lack of knowledge, procedural skills, and insufficient patient volumes to maintain competence. Conclusions: This study’s findings highlight the urgent need to integrate women’s health and low-risk obstetrics CAC holders into a centralized referral system to improve access to OBGPs. Additional and innovative strategies are required to simultaneously tackle the persistent procedural skills educational gap for trainees, practicing and faculty family physicians.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".