Contextual and socioeconomic variation in early motor and language development
Bibliographic record
Abstract
OBJECTIVE: To compare early motor and language development of children <3 years of age growing up in high-income and low-income contexts. DESIGN: Cross-sectional study. SETTING: We analysed differences in motor and language skills across study sites in Cambodia, Chile, Ghana, Guatemala, Lebanon, Pakistan, the Philippines and the USA. MAIN OUTCOME MEASURE: Cognitive and language development assessed with the Caregiver Reported Early Development Instruments (CREDI) tool. RESULTS: 4649 children aged 0-35 months (mean age=18 months) were analysed. On average, children in sites with a low Human Development Index (HDI) had 0.54 SD (95% CI -0.63 to -0.44) lower CREDI motor scores and 0.73 SD (95% CI -0.82 to -0.64) lower language scores than children growing up in high HDI sites. On average, each unit increase in national log income per capita was associated with a 0.77-month (95% CI -0.93 to 0.60) reduction in the age of motor milestone attainment and a reduction in the age of language milestone attainment of 0.55 months (95% CI -0.79 to -0.30). These observed developmental differences were not universal: no developmental differences across sites with highly heterogeneous socioeconomic contexts were found among children growing up in households with highly educated caregivers providing stimulating early environments. CONCLUSION: Developmental gaps in settings with low HDI are substantial on average, but appear to be largely attributable to differences in family-level socioeconomic status and caregiving practices. Programmes targeting the most vulnerable subpopulations will be essential to reduce early life disparities and improve long-run outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".