Association between Breastfeeding Self-Efficacy and Human Milk Feeding in Mothers of Moderate and Late Preterm Infants in a Level II NICU
Bibliographic record
Abstract
Introduction: There is a positive association between breastfeeding self-efficacy (BSE) and breastmilk feeding duration in mothers of healthy, full-term infants. BSE refers to a mother’s perceived ability to successfully breastfeed her infant and is associated with four main factors: (a) performance accomplishments, (b) vicarious experience, (c) verbal persuasion, and (d) physiological and affective states. Limited research explores the relationship between BSE and breastmilk feeding duration for mothers of pre-term infants. Aim: The aim of this research was to explore the association between BSE and human milk feeding at discharge in mothers of moderate and late pre-term infants in a level II NICU. Methods: This study was part of a larger study known as the Family Integrated Care (FICare) study, a cluster randomized controlled trial conducted in 10 level II neonatal intensive care units (NICUs) in Alberta. BSE and breastmilk feeding rates were secondary outcomes. I conducted an observational study that involved secondary data analysis. Participants in this study included 221 maternal-infant dyads from the five control sites. BSE was collected using the modified breastfeeding self-efficacy scale – short form and human milk feeding outcomes were collected using categories recommended by Labbok and Krasovec. I aimed to look at predictors of human milk feeding at discharge and how previous breastfeeding experience may affect feeding outcomes. Results: The primary hypothesis for this study was supported and with all models (multivariable, crude, and stratified by parity analyses), BSE at admission was significantly associated with human milk feeding at discharge (p < 0.05). The secondary hypothesis was not supported since there was no important difference in the association between higher modified BSES-SF scores at admission and providing human milk at discharge when stratified by parity (p > 0.05). Conclusion: using the modified BSES-SF at admission in level II NICUs has potential as a clinical tool to support healthcare providers in identifying mothers of moderate and late pre-term infants at risk of early discontinuation of human milk feeding at discharge. Further research is needed to support the association between higher modified BSES-SF scores at admission and type of feeding at discharge with this maternal-infant dyad.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".