Concurrent Validity of Ages and Stages Questionnaires in Preterm Infants
Bibliographic record
Abstract
BACKGROUND: Although preterm infants born at 29 to 36 gestational weeks (GW) are at risk for developmental delay, they do not always benefit from systematic follow-up. Primary care physicians are then responsible for their developmental surveillance and need effective screening tests. This study aimed to determine whether the Ages and Stages Questionnaires (ASQ) at 12 and 24 months' corrected age (CA) identify developmental delay in preterm infants. METHODS: With a cross-sectional design involving 2 observations at 12 and 24 months' CA, 124 and 112 preterm infants were assessed. Infants were born between May 2004 and April 2006 at 29 to 36 GW. The ASQ and the Bayley Scales of Infant Development were used. Concurrent validity was calculated by using κ coefficient, sensitivity, and specificity. RESULTS: At 12 months' CA, the ASQ did not perform well in identifying infants with mental delay (κ = 0.08-0.19; sensitivity = 0.20-0.60; specificity = 0.68-0.88). Agreement (κ = 0.28-0.44) and specificity (0.90-0.97) were better for the psychomotor scale, but the sensitivity remained insufficient (0.25-0.52). At 24 months, the ASQ had good sensitivity (0.75-0.92) and specificity (0.55-0.78) for detecting mental delays (κ = 0.45). Results remained unsatisfactory for detecting motor delays (sensitivity = 0.31-0.50; specificity = 0.73-0.92). CONCLUSIONS: Preterm infants with developmental delays at 12 months' CA are not adequately identified with the ASQ. At 24 months' CA, the ASQ identifies mental delays but not psychomotor delays. Additional measures should be used to increase yield of detecting at-risk preterm infants.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".