Diagnostic accuracy of developmental screening in primary care at the 18-month health supervision visit: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Communication delays are often the first presenting problem in infants with a range of developmental disabilities. Our objective was to assess the validity of the 18-month Nipissing District Developmental Screen compared with the Infant Toddler Checklist, a validated tool for detecting expressive language and other communication delays. METHODS: A cross-sectional design was used. Children aged 18-20 months were recruited during scheduled health supervision visits. Parents completed both the 18-month Nipissing District Developmental Screen and the Infant Toddler Checklist. We assessed criterion validity (diagnostic test properties, overall agreement) for 1 or more "no" responses (1+NDDS flag) and 2 or more "no" responses (2+NDDS flag) using the Infant Toddler Checklist as a criterion measure. RESULTS: The study included 348 children (mean age 18.6 ± 0.7 mo). The 1+NDDS flag had good sensitivity (94%, 95% confidence interval [CI] 70%-100%, and 86%, 95% CI 64%-96%), poor specificity (63%, 95% CI 58%-68%, and 63%, 95% CI 58%-69%), and fair agreement (0.26) to identify expressive speech and other communication delays, respectively. The 2+NDDS flag had low to fair sensitivity (50%, 95% CI 26%-74%, and 73%, 95% CI 50%-88%), good specificity (86%, 95% CI 82%-90%, and 88%, 95% CI 84%-92%) and moderate agreement (0.45) to identify expressive speech and other communication delays, respectively. INTERPRETATION: The low specificity of the 1+NDDS flag may lead to overdiagnosis, and the low sensitivity of the 2+NDDS flag may lead to underdiagnosis, suggesting that infants who could benefit from early intervention may not be identified. The Nipissing District Developmental Screen does not have adequate characteristics to accurately identify children with a range of communication delays.
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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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".