Effectiveness and cost-effectiveness of Assets-based feeding help Before and After birth (ABA-feed) for improving breastfeeding initiation and continuation: protocol for a multicentre randomised controlled trial (Version 3.0)
Bibliographic record
Abstract
INTRODUCTION: Breastfeeding has health benefits for infants and mothers, yet the UK has low rates with marked social inequalities. The Assets-based feeding help Before and After birth (ABA) feasibility study demonstrated the acceptability of a proactive, assets-based, woman-centred peer support intervention, inclusive of all feeding types, to mothers, peer supporters and maternity services. The ABA-feed study aims to assess the clinical and cost-effectiveness of the ABA-feed intervention compared with usual care in first-time mothers in a full trial. METHODS AND ANALYSIS: A multicentre randomised controlled trial with economic evaluation to explore clinical and cost-effectiveness, and embedded process evaluation to explore differences in implementation between sites. We aim to recruit 2730 primiparous women, regardless of feeding intention. Women will be recruited at 17 sites from antenatal clinics and various remote methods including social media and invitations from midwives and health visitors. Women will be randomised at a ratio of 1.43:1 to receive either ABA-feed intervention or usual care. A train the trainer model will be used to train local Infant Feeding Coordinators to train existing peer supporters to become 'infant feeding helpers' in the ABA-feed intervention. Infant feeding outcomes will be collected at 3 days, and 8, 16 and 24 weeks postbirth. The primary outcome will be any breastfeeding at 8 weeks postbirth. Secondary outcomes will include breastfeeding initiation, any and exclusive breastfeeding, formula feeding practices, anxiety, social support and healthcare utilisation. All analyses will be based on the intention-to-treat principle. ETHICS AND DISSEMINATION: The study protocol has been approved by the East of Scotland Research Ethics Committee. Trial results will be available through open-access publication in a peer-reviewed journal and presented at relevant meetings and conferences. TRIAL REGISTRATION NUMBER: ISRCTN17395671.
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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 | 0.044 | 0.048 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.089 | 0.010 |
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".