Concurrent validity of the ages and stages questionnaires with Bayley Scales of Infant Development-III at 2 years – Singapore cohort study
Bibliographic record
Abstract
BACKGROUND: With increasing acceptance of universal developmental screening in primary care, it is essential to evaluate the local validity and psychometric properties of commonly used questionnaires like the parent-completed Ages and Stages Questionnaires, 3rd Edition (ASQ-3) in identifying developmental delays. The aim of this study is to assess the convergent validity of the ASQ-3 with the Bayley Scales of Infant Development-3rd edition (Bayley-III) in identifying developmental delay in a low-risk term cohort in Singapore. METHODS: ASQ-3 and Bayley-III data was collected prospectively with generation of ASQ-3 cut-off scores using three different criteria: 1-standard deviation (SD) (Criterion-I) or 2-SD (Criterion-II) below the mean, and using a Receiver Operator Curve (ROC) (Criterion-III). Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values were calculated. Correlations between the ASQ-3 and Bayley-III domains were evaluated using Pearson coefficients. RESULTS: With all three criteria across different domains ASQ-3 showed high specificity (72-99%) and NPV (69-98%), but lower sensitivity (19-74%) and PPV (11-59%). Criterion-I identified 11-21% of children as "at-risk of developmental delay," and was the most promising criterion measure, with high specificity (82-91%), NPV (69-74%) and overall agreement of 64-71%. Moderate-strong correlations were seen between ASQ-3 Communication and Bayley-III Language scales (r = 0.44-0.59, p < 0.01). The lowest sensitivities were seen in the motor domains. CONCLUSIONS: ASQ-3 is reliable in low-risk settings in identifying typically developing children not at risk of developmental delay, but it has modest sensitivity. Moderate-strong correlations seen in the communication domain are clinically important for early identification of language delay, which is one of the most prevalent areas of early childhood developmental delay.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".