Peer Counseling Promotes Appropriate Infant Feeding Practices and Improves Infant Growth and Development in an Urban Slum in Bangladesh: A Community-Based Cluster Randomized Controlled Trial
Bibliographic record
Abstract
Undernutrition and poor cognitive development affect many children in developing countries. Good nutrition and health care are essential for optimal child development and growth. We assessed the impact of peer counseling combined with psychosocial stimulation on feeding practices and child growth and development in slums in Bangladesh. We performed a community-based cluster randomized controlled trial in selected slums; 350 mother–infant pairs were allocated to receive peer counseling on feeding practices plus psychosocial stimulation (PC + PCS; n = 175) or usual health messages (control; n = 175) using restricted randomization. Data were collected at enrollment and 1, 3, 5, 7, 9, and 12 mo after delivery. We collected data on infant and young child feeding practices and anthropometric measurements from birth until 12 mo to assess the main outcomes, including feeding practices and growth. We used the Bayley Scale III at 12 mo to assess child development. The effects of the PC + PCS intervention were assessed by using regression models. More mothers in the PC + PCS group than in the control group reported early initiation of breastfeeding (in the first hour: 89% compared with 78%, respectively; P < 0.05) and exclusive breastfeeding at 5 mo (73% compared with 27%, respectively; P < 0.001). Peer counseling had positively impacted infant length gain at 12 mo (P < 0.005). Children in the PC + PCS group were found to be more socially and emotionally active compared with controls at 12 mo (standardized score: 0.165 compared with −0.219, respectively; P < 0.05). Combining peer counseling with psychosocial stimulation had positive effects on infant feeding practices and growth at 12 mo and on the social–emotional development of young children. This trial was registered at clinicaltrial.gov as NCT03040375.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".