Breastfeeding self-efficacy and breastmilk feeding for moderate and late preterm infants in the Family Integrated Care trial: a mixed methods protocol
Bibliographic record
Abstract
BACKGROUND: Breastmilk is the ideal nutrition for preterm infants. Yet, breastmilk feeding rates among preterm infants are substantially lower than those of full-term infants. Barriers incurred through hospital care practices as well as the physical environment of the neonatal intensive care unit (NICU) can result in physical and emotional separation of infants from their parents, posing a substantial risk to establishing and maintaining breastfeeding. Additionally, current practitioner-focused care provision in the NICU can result in decreased breastfeeding self-efficacy (BSE), which is predictive of breastfeeding rates in mothers of preterm infants at 6 weeks postpartum. METHODS: Family Integrated Care (FICare) integrates and supports parents to actively participate in the care of their infant while in the NICU. Nested within the broader FICare trial, we will conduct an explanatory sequential mixed methods study to investigate if FICare improves maternal BSE and rates of breastmilk feeding in moderate and late preterm infants at discharge from the NICU. In phase 1, we will calculate the mean difference between admission and discharge BSE scores for the intervention group. Mothers who score in the top and bottom 20th percentile of change scores will be invited to participate in a semi-structured telephone interview exploring maternal experiences with infant feeding in the NICU. We will conduct inductive thematic analysis to identify and describe the facilitators and barriers of FICare on maternal feeding experiences. Once data saturation is achieved and themes have been established, phase 2 will revisit the quantitative data to determine whether FICare was impactful on BSE and breastmilk feeding rates. Findings from the qualitative and quantitative phases will be integrated to determine how infant feeding experiences on FICare units work to improve or detract from maternal BSE and rates of breastmilk feeding. DISCUSSION: FICare may help to improve maternal BSE and rates of breastmilk feeding in moderate and late preterm infants. Improved breastmilk feeding outcomes can have a substantial impact on overall infant health, developmental outcomes, and maternal-infant bonding and will help to improve long-term health outcomes for moderate and late preterm infants. TRIAL REGISTRATION: (NCT02879799). Registered May 27, 2016 protocol version June 9, 2016 Version 2.
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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 | 0.033 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".