Effect of a parenting and nutrition education programme on development and growth of children using a social safety-net platform in urban Bangladesh: a cluster randomized controlled trial
Bibliographic record
Abstract
Background: Although sustainable development goals mandate for quality early childhood development (ECD) interventions for children <8 years, little occurs for children <3 years, especially in urban settings in low-and-middle-income countries (LMICs). Our primary objective was to measure the effect of an ECD-focused parenting and nutrition education on children's development through home visits using a social safety net platform of urban Bangladesh. Methods: A cluster randomized controlled trial was conducted with mothers of children aged 6-16 months in 20 clusters across the Rangpur city, Bangladesh. The intervention group received fortnightly ECD-focused parenting and nutrition education at homes by local Community Health Workers (CHWs) for one year. Bayley-III was used to measure children's cognitive, language and motor development. Data were analyzed using intention to treat. ClinicalTrials.gov Identifier: NCT03753646. Findings: 25 years old. After one year, the intervened children had higher cognitive [Effect size Cohen's d; 0.42 SD (95% CI: 0.58-0.25)], language (0.38 SD, 95% CI: 0.55-0.22) and motor (0.17 SD, 95% CI: 0.01-0.34) development. In the intervention group, mothers experienced less violence [Odds ratio; 0.6 (95% CI: 0.4-1.0)] and fathers engaged more (0.23 SD, CI: 0.39-0.06) in ECD activities with their children compared to the comparison group. Total home stimulation and mothers' knowledge on child care were also improved in the intervention. But the children's growth was not improved. Interpretation: This ECD programme improves the development of children of young mothers in urban settings using a social safety-net platform. The evidence may help in increasing ECD coverage in urban areas in LMICs. Funding: Grand Challenges Canada, Saving Brains Programme Grant Number: SB-1810-20176.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".