Improving parenting practices and development for young children in Rwanda: Results from a randomized control trial
Bibliographic record
Abstract
It is well known that the first 1,000 days of life have long-lasting impact on a child’s cognitive, language, socio-emotional, and physical development, but there is little evidence from Rwanda about how to maximize parent–child interactions during these critical early years. Save the Children piloted the First Steps “Intera za Mbere” early childhood parenting education program in one district of Rwanda to promote healthy development through holistic parenting education. Using a cluster randomized control trial, we assessed outcomes of a 17-week parenting education on parenting skills and child development for families with children aged 6–36 months. Families were randomly allocated into three study groups: light touch ( n = 482), full intervention ( n = 482), and control ( n = 483) groups. We used a Kinyarwanda-adaptation of the validated Ages & Stages Questionnaires (ASQ), a Home Observation Measurement of the Environment-Short Form. Multivariate linear and logistic regression analyses were used for both the intention-to-treat analyses and more robust models controlling for ASQ form received, child gender, maternal education, number of children in the home, and baseline ASQ scores. Findings indicate that children in the light touch and full intervention groups were significantly more likely to meet the ASQ benchmarks than the control group in all developmental domains. The strong positive results from the light touch group are especially relevant to efforts to bring beneficial early childhood stimulation programs to scale in low-income contexts.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.005 | 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".