241 Using the Ages and Stages Questionnaire to Capture Patterns of Risk for Developmental Delay in Canadian Children Born Late Preterm
Bibliographic record
Abstract
Background and aims Nearly three quarters of preterm infants are 34 to 36 weeks gestational age (GA), or late preterm (LPT). LPT children are at significantly greater risk for neurological, language and communication delays, social and emotional problems, and attention-deficit/hyperactivity disorder than children born full term. Developmental screening and early intervention may mitigate these risks. Little is known about early patterns of risk across developmental domains in the LPT group as this grouping has been consistently defined only recently. The purpose of this study was to describe patterns of development in Canadian children born LPT. Methods Mothers of 61 LPT infants (57% male) completed the Ages and Stages Questionnaire 3rd edition (ASQ-3) when their child was 4, 8 and 18 months corrected age. The 30-item ASQ-3 addresses communication, gross motor, fine motor, problem solving, and personal social functioning. Referral cut-off is < 2 SD below the mean, and monitoring is required between 1 and 2 SD below. Results There was a clear inverse relationship between GA and proportion of children requiring referral or monitoring over time. For 34 weeks GA, 67% to 83% of children demonstrated risk in one or more domains; for 35 weeks, the proportion was 50% to 65%; and still lower for 36 weeks (40% to 54%). Communication and gross motor were the most problematic domains. Conclusion The ASQ-3 may be useful to capture delays in LPT children, particularly in communication and gross motor domains. These results have implications for early childhood developmental assessment and intervention services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".