The ABA intervention for improving breastfeeding initiation and continuation: Feasibility study results
Bibliographic record
Abstract
The UK has low breastfeeding rates, with socioeconomic disparities. The Assets-based feeding help Before and After birth (ABA) intervention was designed to be inclusive and improve infant feeding behaviours. ABA is underpinned by the behaviour change wheel and offers an assets-based approach focusing on positive capabilities of individuals and communities, including use of a Genogram. This study aimed to investigate feasibility of intervention delivery within a randomised controlled trial (RCT). Nulliparous women ≥16 years, (n = 103) from two English sites were recruited and randomised to either intervention or usual care. The intervention - delivered through face-to-face, telephone and text message by trained Infant Feeding Helpers (IFHs) - ran from 30-weeks' gestation until 5-months postnatal. Outcomes included recruitment rates and follow-up at 3-days, 8-weeks and 6-months postnatal, with collection of future full trial outcomes via questionnaires. A mixed-methods process evaluation included qualitative interviews with 30 women, 13 IFHs and 17 maternity providers; IFH contact logs; and fidelity checking of antenatal contact recordings. This study successfully recruited women, including teenagers, from socioeconomically disadvantaged areas; postnatal follow-up rates were 68.0%, 85.4% and 80.6% at 3-days, 8-weeks and 6-months respectively. Breastfeeding at 8-weeks was obtained for 95.1% using routine data for non-responders. It was possible to recruit and train peer supporters to deliver the intervention with adequate fidelity. The ABA intervention was acceptable to women, IFHs and maternity services. There was minimal contamination and no evidence of intervention-related harm. In conclusion, the intervention is feasible to deliver within an RCT, and a definitive trial required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".