A theory-based behavioural change communication intervention to decrease the provision of water to infants under 6 months of age in the Republic of Guinea
Bibliographic record
Abstract
Abstract Objective: In many countries, the provision of water in the early months of a baby’s life jeopardises exclusive breast-feeding (EBF). Using a behavioural theory, this study assessed the impact of a behaviour change intervention on mothers’ intention to act and, in turn, on the water provision in addition to breast milk to their infants under 6 months of age (IU6M) in two regions of Guinea. Design: A quasi-experimental design. Data on individual and environmental factors of the theoretical framework, sociodemographic and outcomes were collected using validated questionnaires before and after the intervention. The outcomes examined were the intention to provide water to IU6M, the provision of water and EBF. Path analyses were performed to investigate pathways by which psychosocial and environmental factors influenced the water provision in addition to breast milk. Setting: Four health centres were assigned randomly to each study’s arm (one control/CG and one intervention group/IG per region). Participants: The sample included 300 mothers of IU6M: 150 per group. Results: In IG, the proportion of mothers providing water decreased from 61 % to 29 % before and after the intervention (P< 0·001), while no difference was observed in CG (P= 0·097). The EBF rate increased in IG (from 24·0 % to 53·8 %,P< 0·001) as opposed to CG (36·7 % to 45·9 %,P= 0·107). An association (P< 0·001) between the intention and the behaviour was observed in both groups. Conclusions: An intervention developed using a sound framework reduces the provision of water among IU6M and improves EBF.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.003 | 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".