Promoting early childhood development in Viet Nam: cost-effectiveness analysis alongside a cluster-randomised trial
Bibliographic record
Abstract
BACKGROUND: Economic evaluations are critical to ensure effective resource use to implement and scale up child development interventions. This study aimed to estimate the cost-effectiveness of a multicomponent early childhood development intervention in rural Viet Nam. METHODS: We did a cost-effectiveness study alongside a cluster-randomised trial with a 30-month time horizon. The study included 669 mothers from 42 communes in the intervention group, and 576 mothers from 42 communes in the control group. Mothers in the intervention group attended Learning Clubs sessions from mid-pregnancy to 12 months after delivery. The primary outcomes were child cognitive, language, motor, and social-emotional development at age 2 years. In this analysis, we estimated the incremental cost-effectiveness ratios (ICERs) of the intervention compared with the usual standard of care from the service provider and household perspectives. We used non-parametric bootstrapping to examine uncertainty, and applied a 3% discount rate. FINDINGS: The total intervention cost was US$169 898 (start-up cost $133 692 and recurrent cost $36 206). The recurrent cost per child was $58 (1 341 741 Vietnamese dong). Considering the recurrent cost alone, the base-case ICER was $14 and mean ICER of 1000 bootstrap samples was $14 (95% CI -0·48 to 30) per cognitive development score gained with a 3% discount rate to costs. The ICER per language and motor development score gained was $22 and $20, respectively, with a 3% discount rate to costs. INTERPRETATION: The intervention was cost-effective: the ICER per child cognitive development score gained was 0·5% of Viet Nam's gross domestic product per capita, alongside other benefits in language and motor development. This finding supports the scaling up of this intervention in similar socioeconomic settings. FUNDING: Australian National Health and Medical Research Council and Grand Challenges Canada. TRANSLATION: For the Vietnamese translation of the abstract see Supplementary Materials section.
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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 | 0.032 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".