Effect of Maternal Confidence on Breastfeeding Duration: An Application of Breastfeeding Self‐Efficacy Theory
Bibliographic record
Abstract
BACKGROUND: Although much research has focused on identifying factors that influence breastfeeding initiation and duration, many high-risk factors are nonmodifiable demographic variables. Predisposing factors for low breastfeeding duration rates that are amenable to supportive interventions should be identified. The purpose of this study was to assess the effect of maternal confidence (breastfeeding self-efficacy) on breastfeeding duration. METHOD: A prospective survey was conducted with 300 women in the last trimester of pregnancy recruited from the antenatal clinic of a large metropolitan hospital in Brisbane, Australia. Telephone interviews were conducted at 1 week and 4 months postpartum to assess infant feeding methods and breastfeeding confidence using the Breastfeeding Self-Efficacy Scale. RESULTS: Although 92 percent of participants initiated breastfeeding, by 4 months postpartum almost 40 percent discontinued and only 28.6 percent were breastfeeding exclusively; the most common reason for discontinuation was insufficient milk supply. Antenatal and 1-week Breastfeeding Self-Efficacy Scale scores were significantly related to breastfeeding outcomes at 1 week and 4 months. Mothers with high breastfeeding self-efficacy were significantly more likely to be breastfeeding, and doing so exclusively, at 1 week and 4 months postpartum than mothers with low breastfeeding self-efficacy. CONCLUSIONS: Maternal breastfeeding self-efficacy is a significant predictor of breastfeeding duration and level. Integrating self-efficacy enhancing strategies may improve the quality of healthcare that healthcare professionals deliver and may increase a new mother's confidence in her ability to breastfeed, and to persevere if she does encounter difficulties.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".