Breastfeeding Knowledge, Confidence, Beliefs, and Attitudes of Canadian Physicians
Bibliographic record
Abstract
BACKGROUND: Physicians' attitudes and recommendations directly affect breastfeeding duration. Yet, studies in many nations have shown that physicians lack the skills to offer proper guidance to breastfeeding mothers. OBJECTIVE: This study aims to assess breastfeeding knowledge, confidence, beliefs, and attitudes of Canadian physicians. METHODS: A breastfeeding questionnaire was developed and piloted prior to study enrollment. These questionnaires were sent to 1429 pediatricians (PED), 1329 family physicians (FP), and final-year pediatric and final-year family medicine residents (PR and FMR). RESULTS: The analysis included 397 PED, 322 FP, 17 PR, and 44 FMR who completed the questionnaire. Mean overall correct knowledge score was 67.8% for PED, 64.3% for FP, 72.7% for PR, and 66.8% for FMR. Two hundred eighty-five PED (74.2%), 228 FP (73.1%), 7 PR (41.2%), and 21 FMR (53.8%) felt confident with their breastfeeding counseling skills. Less than half (49.6% of PED and 45.4% of FP) believed that evaluating breastfeeding was a primary care physician's responsibility, and few PED or FP (5.1% and 11.3%) routinely observed breastfeeding in mother-infant pairs. CONCLUSION: Several areas of potential deficits were identified in Canadian physicians' breastfeeding knowledge. Physicians would benefit from greater education and support, to optimize care of infants and their mothers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".