Early childhood trajectories of domain-specific developmental delay and gestational age at birth: An analysis of the All Our Families cohort
Bibliographic record
Abstract
OBJECTIVE: To describe developmental domain-specific trajectories from ages 1 through 5 years and to estimate the association of trajectory group membership with gestational age for children born between ≥34 and <41 weeks gestation. METHODS: Using data from the All Our Families cohort, trajectories of the domain-specific Ages & Stages Questionnaire scores were identified and described using group-based trajectory modeling for children born ≥34 and <41 weeks of gestation (n = 2664). The trajectory groups association with gestational age was estimated using multinomial logistic regression. RESULTS: Across the five domains, 4-5 trajectory groups were identified, and most children experienced changing levels of risk for delay over time. Decreasing gestational age increases the Relative risk of delays in fine motor (emerging high risk: 1.46, 95% CI: 1.19-1.80; resolving moderate risk: 1.11, 95% CI: 1.03-1.21) and gross motor (resolving high risk: 1.21, 95% CI: 1.04-1.42; and consistent high risk: 1.64, 95% CI: 1.20-2.24) and problem solving (consistent high risk: 1.58 (1.09-2.28) trajectory groups compared to the consistent low risk trajectory groups. CONCLUSION: This study highlights the importance of longitudinal analysis in understanding developmental processes; most children experienced changing levels of risk of domain-specific delay over time instead of having a consistent low risk pattern. Gestational age had differential effects on the individual developmental domains after adjustment for social, demographic and health factors, indicating a potential role of these factors on trajectory group membership.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".