Early Breast Milk Pumping Intentions Among Postpartum Women
Bibliographic record
Abstract
INTRODUCTION: Milk expression has become common, but little is known about women's intentions and motivations for pumping. Our objectives were to measure, among newly postpartum women, intentions related to breast milk feeding and pumping, reasons for intending to pump, and timing of pumping initiation. METHODS: We conducted a cross-sectional study at a large university hospital in 2015 using a convenience sample of 100 women before their discharge following delivery, who intended to feed their infant breast milk for at least 6 months. RESULTS: All participants planned to feed their baby at the breast. Ninety-eight percent said that they would use a breast pump to express milk for their baby, with most of this subset (69%) intending to start within weeks of delivery. Over a quarter of participants (29%) had already initiated pumping or intended to initiate within the subsequent few days. Primiparae were more likely to report having already started pumping at the time of the interview. For all women, the most common reason for pumping was to keep up their milk supply. Women who started pumping while in the hospital also noted that they pumped to increase their milk supply and overcome latch difficulties. CONCLUSIONS: The common intention to use a breast pump so early after delivery indicates a need for increased lactation support to reduce concerns about having an insufficient milk supply immediately following delivery. Additionally, clinicians who help facilitate breastfeeding should be aware of how early women intend to use a breast pump.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".