Relationships between types of father breastfeeding support and breastfeeding outcomes
Bibliographic record
Abstract
Fathers' support can influence mothers' breastfeeding decisions and behavior. Potentially supportive behaviors have been reported in previous studies, but no studies have directly examined which, if any, of those actions are actually more likely to result in desired breastfeeding outcomes. The two studies reported in this paper address this gap by examining relationships between fathers' reported breastfeeding support and mothers' perceptions of received support and breastfeeding intentions, satisfaction, and duration. The Partner Breastfeeding Influence Scale (PBIS) was used in an online survey with 64 women and 41 men (34 couples) and a telephone survey with 80 mothers and 65 fathers (63 couples). Fathers' and mothers' reports of how often fathers engage in the types of support measured by the PBIS were used to predict breastfeeding intentions, satisfaction, and duration. In Study 1, responsiveness predicted breastfeeding success and satisfaction for men and satisfaction for women. However, mothers' intended breastfeeding duration was shorter when fathers both wanted them to breastfeed for a long time and were more appreciative and savvy about breastfeeding. In Study 2, when fathers reported being more appreciative and directly involved in breastfeeding, mothers reported shorter breastfeeding duration. In both studies, mothers' perceptions of their partners' responsiveness and fathers' reports of their own responsiveness predicted longer breastfeeding intentions and duration. These findings suggest that the most effective breastfeeding support is delivered using a sensitive, coordinated teamwork approach that is responsive to the mother's needs.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".