Considering equity and cost-effectiveness in assessing a parenting intervention to promote early childhood development in rural Vietnam
Bibliographic record
Abstract
Considering equity in early childhood development (ECD) is important to ensure healthy development for every child. Equity-informative cost-effectiveness analysis can further guide decision makers to maximize outcomes with limited resources while promoting equity. This cost-effectiveness study aimed to examine the equity impacts of a multicomponent ECD intervention in rural Vietnam. We estimated the cost-effectiveness of the intervention with a 30-month time horizon from the service provider and household perspectives with equity considerations. Data were from a cluster-randomized controlled trial comparing the intervention with the local standard of care. The incremental cost-effectiveness ratios (ICERs) per child cognitive development score gained were estimated by household wealth quintile and maternal education level, adjusted for cluster effects and baseline characteristics such as maternal parity and age. A 3% discount rate was applied to costs, and non-parametric cluster bootstrapping was used to examine uncertainty around ICERs. Children in the intervention had higher cognitive development scores than those in the control arm across all subgroups. Based on intervention recurrent cost, the ICER per cognitive development score gained was lower in children from the poorest quintile (-US$6) compared to those from the richest quintile (US$16). Similarly, the ICER per cognitive development score gained was lower in children whose mothers had the lowest education level (-US$0.02) than those with mothers who had the highest education level (US$7). Even though our findings should be interpreted with caution due to the insufficient study power, the findings suggest that the intervention could promote equity while improving child cognitive development with greater cost-effectiveness in disadvantaged groups.
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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 | 0.001 | 0.001 |
| 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".