G492 Who 0–3 developmental indicators – a systematic analysis of developmental trajectories of items from seven assessment tools in ten countries
Bibliographic record
Abstract
Aims Over 200 million children under 5 are not reaching their developmental potential. At present, no tools exist that can measure indicators of children’s development in meaningful, valid and culturally comparable ways within or across populations. This study aimed to identify items within validated tools utilised in low and middle income (LAMI) settings that have similarly and adequately functioning developmental trajectories across countries and across tools. Methods We located 14 datasets from 10 countries across Africa, Asia and Latin America that used one or more of 7 developmental tools commonly used in LAMI settings with good psychometrics. Datasets included 22 053 children aged 0–3 years from nationally representative samples or those enrolled in large randomised trials. All excluded children with serious neurodevelopmental problems and most included measurement of socioeconomic status and child anthropometry. A matrix mapping through expert consensus identified individual items that measured related developmental indicators from tools. We performed logistic regression analysis on all sets of items and with this data held a consensus process on which items were most developmentally meaningful for their 1) capacity to discriminate by age, and to do so similarly across tools and countries, and 2) their representativeness of developmental constructs identified by previous systematic review. A set of items was agreed on, and domain and age-gaps identified. A second mapping procedure then looked for further items less closely linked across tools or countries which might have utility in completing the developmental spectrum. Results A total of 1460 developmental items were analysed in 545 groupings of items over two phases. A 119 item prototype was created through consensus covering items which showed good cross cultural validity in fine motor, gross motor, receptive and expressive language, and socio-emotional domains was drafted which is now being pilot tested on three continents prior to a larger field trial in multiple countries. Conclusion Many items in developmental tools used in low income settings do show similar developmental trajectories across tools and across settings. These items may work in creating a valid tool to provide indicators of child development for children from 0–3 across countries worldwide.
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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 | 0.042 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.021 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".