Effectiveness of interventions on breastfeeding self‐efficacy and perceived insufficient milk supply: A systematic review and meta‐analysis
Bibliographic record
Abstract
The aim of this systematic review and meta-analysis was to assess the efficacy on an intervention on breastfeeding self-efficacy and perceived insufficient milk supply outcomes. The literature search was conducted among 6 databases (CINAHL, Medline, PsyncInfo, Scopus, Cochrane, and ProQuest) in between January 2000 to June 2016. Two reviewers independently assessed the articles for the following inclusion criteria: experimental or quasi-experimental studies; healthy pregnant women participants intending to breastfeed or healthy breastfeeding women who gave birth to a term singleton and healthy baby; intervention administered could have been educational, support, psycho-social, or breastfeeding self-efficacy based, offered in prenatal or postnatal or both, in person, over the phone, or with the support of e-technologies; breastfeeding self-efficacy or perceived insufficient milk supply as outcomes. Seventeen studies were included in this review; 12 were randomized controlled trials. Most interventions were self-efficacy based provided on 1-to-1 format. Meta-analysis of RCTs revealed that interventions significantly improved breastfeeding self-efficacy during the first 4 to 6 weeks (SMD = 0.40, 95% CI 0.11-0.69, p = 0.006). This further impact exclusive breastfeeding duration. Only 1 study reported data on perceived insufficient milk supply. Women who have made the choice to breastfeed should be offered breastfeeding self-efficacy-based interventions during the perinatal period. Although significant effect of the interventions in improving maternal breastfeeding self-efficacy was revealed by this review, there is still a paucity of evidence on the mode, format, and intensity of interventions. Research on the modalities of breastfeeding self-efficacy should be pursued.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".