A Systematic Review of the Correlation Between Marital Relationship and Breastfeeding Self-Efficacy, and Duration of Breastfeeding
Bibliographic record
Abstract
Background:Breastfeeding as an important key to sustainable development strategies is the best nutrition for ensuring healthy growth and development in the first 1,000 days of life. Objective:The current systematic review and meta-analysis were conducted to evaluate the correlation between marital relationship satisfaction and breastfeeding self-efficacy and duration of breastfeeding. Method:A systematical search was carried out in main electronic databases (PubMed, Scopus, Embase, ProQuest, and Web of Science) and gray literature until June 2022. The study's risk of bias was assessed using the Newcastle-Ottawa risk-of-bias tool. Publication bias was evaluated using a funnel plot, and Begg's and Egger's tests. The degree of heterogeneity was assessed using the I2 test. To estimate common effect size r coefficient (r) and confidence intervals (95% CIs), random-effect models were fitted, and the results were presented using forest plots. Results:In total, 13 studies with 5,843 subjects were included in the meta-analysis. Overall, the pool estimates show a positive correlation between marital relationship satisfaction, and breastfeeding self-efficacy (r = 0.27, 95% CI (0.09–0.50), p = 0.024), but this relationship was not found in the term of breastfeeding duration (r = 0.11, 95% CI [−0.01 to 0.23], p = 0.079). The heterogeneity of studies was high (I2 = 95.2%) Conclusion:Our finding confirms a positive and moderate level of correlation between marital relationship satisfaction and breastfeeding self-efficacy. It is suggested to conduct more studies to reach appropriate conclusions regarding marital relationship satisfaction and breastfeeding duration.
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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 | 0.015 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".