Evaluation of a social network intervention on child feeding practices and caregiver knowledge
Bibliographic record
Abstract
Food insecurity and poor infant and young child feeding (IYCF) practices contribute to undernutrition. The Kanyakla Nutrition Program was developed in rural Kenya to provide knowledge alongside social support for recommended IYCF practices. Utilizing a social network approach, the Kanyakla Nutrition Program trained community health workers (CHWs) to engage mothers, fathers, and grandparents in nutrition education and discussions about strategies to provide instrumental, emotional, and information support within their community. The 12-week programme included six sessions and was implemented on Mfangano Island, Kenya, in 2014-2015. We analysed intervention effects on (a) nutrition knowledge among community members or CHWs and (2) IYCF practices among children 1-3 years. Nutrition knowledge was assessed using a postintervention comparison among intervention (community, n = 43; CHW, n = 22) and comparison groups (community, n = 149; CHW, n = 64). We used a quasi-experimental design and difference-in-difference to assess IYCF indicators using dietary recall data from an ongoing cohort study among intervention participants (n = 48) with individuals living on Mfangano Island where the intervention was not implemented (n = 178) before the intervention, within 1 month postintervention, and 6 months postintervention. Findings showed no effect of the intervention on IYCF indicators (e.g., dietary diversity and meal frequency), and less than 15% of children met minimum acceptable diet criteria at any time point. However, knowledge and confidence among community members and CHWs were significantly higher 2 years postintervention. Thus, a social network approach had an enduring effect on nutrition knowledge, but no effects on improved IYCF practices.
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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".