Breastfeeding self‐efficacy predicts breastmilk feeding in preterm infants at discharge from the neonatal intensive care unit
Bibliographic record
Abstract
AIM: To examine the association between breastfeeding self-efficacy (BSE) and breastmilk feeding at discharge from the neonatal intensive care unit among mothers of preterm infants. DESIGN: Secondary analysis of the Family Integrated Care (FICare) cluster randomized controlled trial. METHODS: Data from 221 mothers of preterm infants who participated in the standard care group of the trial were analysed. BSE at admission was assessed using the modified Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF). Breastmilk feeding was assessed using 24 hr maternal recall at discharge. RESULTS: Mothers who were exclusively breastmilk feeing their infants at discharge had statistically significantly higher mean BSES-SF scores at admission (68.4, SD = 13.7) than those providing a combination of breastmilk and formula or only formula (59.6, SD = 14.7; p < .001). Multivariable logistic regression showed that higher BSE at admission, maternal birth in Canada, and absence of diabetes were statistically significant predictors of exclusive breastmilk feeding at discharge.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".