Breastfeeding During Family Medicine Residency
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Canadian residents' breastfeeding experiences have only been reported in studies that broadly explored pregnancy and parenthood. We sought to fully explore Canadian family medicine resident mothers' breastfeeding experiences, and identify strategies to support workplace breastfeeding for future trainees. METHODS: Using an online survey, University of Toronto family medicine residents who gave birth from 2010 through 2016 were queried about their exclusive and overall breastfeeding duration, barriers, and facilitators to workplace breastfeeding, and strategies to improve the breastfeeding experience for future resident mothers. Data were downloaded from Qualtrics software and descriptive statistical analyses were conducted using IBM SPSS Statistics v.24.0. Subjective comments were examined and linked to quantitative findings. RESULTS: Fifty-six of 179 eligible residents completed the survey (31% response rate). More than three-quarters of residents were on maternity leave for 7 to 12 months. All initiated breastfeeding, and 54% breastfed exclusively for 6 months. The median breastfeeding duration was 10 to 12 months. Almost two-thirds of residents were breastfeeding upon return to work, and all experienced barriers to workplace breastfeeding including lack of time, private space, and refrigeration for expressed milk. Lack of a workplace breastfeeding policy and inadequate support from supervisors or program directors were additional barriers. Peer mentorship and more breastfeeding education were identified as strategies to support future residents' breastfeeding goals. CONCLUSIONS: Addressing long-standing barriers to workplace breastfeeding, and providing peer and educational supports were identified as strategies that could inform program policies to support future trainees' breastfeeding goals and experiences.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".