Acceptability and Feasibility of a Breast Milk Expression Education and Support Intervention in Mothers of Preterm Infants
Bibliographic record
Abstract
PURPOSE: A pilot study was conducted to assess the acceptability and feasibility of a breast milk expression education and support intervention in mothers of preterm infants and study procedures. SUBJECTS: Forty mothers of preterm infants born at less than 30 weeks of gestation. DESIGN: Pilot randomized controlled trial. METHODS: Mothers of preterm infants were randomly allocated to the breast milk expression education and support intervention or standard care. The experimental intervention encompassed a breast milk expression education session on 7 themes, telephone follow-up, and telephone helpline. MAIN OUTCOME MEASURES: Data related to the acceptability and feasibility of the intervention and study procedures were collected throughout the study. At the end of the study, mothers allocated to the experimental intervention completed a self-report questionnaire assessing the acceptability of each of the intervention components. RESULTS: It was feasible to recruit 70% of eligible mothers and retain 83% of mothers who consented to participate in the study. Mothers reported that all the intervention components were appropriate and effective in supporting their breast milk production. Although the reliability of the data collection method was demonstrated, the fidelity of the telephone follow-up faced some challenges. CONCLUSIONS: Both the intervention and study procedures were acceptable and feasible. Improvements related to the fidelity of the intervention would ensure the feasibility and internal validity of a larger-scale trial.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".