Learning needs of family physicians, pediatricians and obstetricians to support breastfeeding and inform physician education
Bibliographic record
Abstract
BACKGROUND: Physicians require breastfeeding education appropriate to their roles. The aim of this survey was to determine physician learning needs and to inform development of breastfeeding education for physicians. METHODS: A cross sectional survey was distributed to family physicians, pediatricians and obstetricians in a tertiary institution. Importance of knowledge to practice and confidence to manage was assessed for 18 learning topics proposed by a multi-specialty physician working group. Descriptive statistics, ANOVA and tests for equality of variances were calculated. Mean values of importance to practice and confidence to manage for each topic suggested learning priorities. RESULTS: The study group included 75 physicians. The most important topics were "informed choice when supporting newborn feeding," "analgesics, antidepressants and other medications while breastfeeding" and "community resources for breastfeeding support." Confidence to manage was lowest for "latch assessment," "what mom can do during pregnancy to promote milk production," and "risk factors for delayed lactogenesis." Preferred learning formats were 15-minute online modules and grand rounds. CONCLUSIONS: Physicians acknowledged the importance of all topics but report lowest confidence to manage latch assessment, prenatal interventions to support lactogenesis and management of delayed lactogenesis. Participants placed relatively low importance on learning about latch assessment despite the central nature of this skill in supporting early breastfeeding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".