The role of paternal support in breastfeeding outcomes: a meta-analytic review
Bibliographic record
Abstract
BACKGROUND: The advantages of breastfeeding for maternal and child health have been widely acknowledged on an international scale. However, there is a paucity of research regarding the effectiveness of paternal support in breastfeeding. This study aimed to systematically review the impact of paternal support interventions on breastfeeding and to contribute additional evidence to inform current breastfeeding practices. METHODS: A systematic search was conducted across multiple databases, including China National Knowledge Infrastructure (CNKI), Wanfang Data, the VIP Database, the Chinese Biomedical Literature Service System (SinoMed), PubMed, EMBASE, the Cochrane Library, and Web of Science, for randomized controlled trials (RCTs) related to breastfeeding and paternal support interventions, covering the period from the inception of the databases to June 2024. In accordance with the predefined inclusion and exclusion criteria, two researchers independently screened the literature and performed a meta-analysis via RevMan 5.4.1 software. The choice between fixed or random effects models was determined by the outcomes of the heterogeneity test, and relative risks (RR) along with 95% confidence intervals (CI) were computed. RESULTS: A comprehensive search yielded 3065 studies, of which eight were included in the meta-analysis. These studies involved a total of 2531 participants, with 1306 in the intervention group and 1225 in the control group. The studies conducted across the United Kingdom, Australia, Canada, and China encompassed a variety of interventions, including breastfeeding education, consultations led by specialists, distribution of informational materials, utilization of educational media, facilitation of interactive discussions, provision of online support through phone or WeChat, dissemination of public account messages, training in breastfeeding techniques, postpartum social support, and guidance on maternal and newborn care. The meta-analysis results indicated that the rate of exclusive breastfeeding was significantly higher in the intervention group compared to the control group at various time points: within one week postpartum (RR 1.28; 95% CI 1.16, 1.42); at 30-42 days postpartum (RR 1.12; 95% CI 1.02, 1.23); and at three months postpartum (RR 1.35; 95% CI 1.21, 1.50). These findings suggest that paternal support interventions effectively enhance breastfeeding practices. CONCLUSIONS: The findings suggest that current evidence supports the efficacy of paternal support interventions in both the initiation and maintenance of breastfeeding.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".