Complementary and alternative therapies: supporting the woman with inadquate milk production
Bibliographic record
Abstract
While the benefits of breastfeeding are well established, and high initiation rates indicate that women recognize these benefits and wish to provide their infants with the healthiest beginnings, duration rates indicate that women are having difficulty overcoming challenges in the early weeks of breastfeeding. Studies indicate that early breastfeeding cessation is correlated with perceived or actual inadequate milk supply (Lewallen et al., 2006). While the traditional management of insufficient supply during breastfeeding has involved breastfeeding support with particular attention to effectiveness of maternal and infant position, milk transfer, and frequency of feeds, some women may not see improvement in supply from traditional measures. Breastfeeding websites, parenting books, and review articles by breastfeeding professionals suggest the use of complementary and alternative therapies such as acupuncture, herbal medicines, relaxation therapy, aromatherapy, and homeopathy to increase milk supply, however little clinical evidence exists to support the use of such therapies. This literature review summarizes the available data in research and grey literature regarding the use of acupuncture and herbal medicine in managing insufficient milk supply. The majority of evidence supporting the use of acupuncture and herbal medicine in the breastfeeding woman is qualitative and quasi-experimental, with few randomized controlled trials supporting the safety and efficacy of these treatments for increasing milk production in the lactating woman. The role of the nurse practitioner in supporting patients using complementary and alternative therapies is discussed. --Leaf 2.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".