EVALUATING THE PREDICTIVE VALIDITY OF THE NIPISSING DISTRICT DEVELOPMENTAL SCREEN IN PRIMARY CARE SETTINGS AT THE 18-MONTH HEALTH SUPERVISION VISIT
Bibliographic record
Abstract
Abstract BACKGROUND The Canadian Paediatric Society (CPS) recommends that every Canadian physician caring for young children provide an enhanced 18-month well-baby visit including the use of a developmental screening tool, such as the Nipissing District Developmental Screen (NDDS). The Province of Ontario implemented an enhanced 18-month well-baby visit specifically emphasizing the NDDS, which is now widely used in Ontario primary care. However, the diagnostic accuracy of the NDDS in identifying early developmental delays in real-world clinical settings is unknown. OBJECTIVES To assess the predictive validity of the NDDS in primary care for identifying developmental delay and prompting a specialist referral at the 18-month health supervision visit. DESIGN/METHODS This was a prospective longitudinal cohort study enrolling healthy children from primary care practices. Parents completed the 18-month NDDS during their child’s scheduled health supervision visit between January 2012 and February 2015. Using a standardized data collection form, research personnel abstracted data from the child’s health records regarding the child’s developmental outcomes following the 18-month assessment. Data collected included confirmed diagnoses of a development delay, specialist referrals, family history, and interventions. Research personnel were blind to the results of the NDDS. We assessed the diagnostic test properties of the NDDS with a confirmed diagnosis of developmental delay as the criterion measure. The specificity, sensitivity, positive predictive value, and negative predictive value were calculated, with 95% confidence intervals. RESULTS We included 255 children with a mean age of 18.5 months (range, 17.5–20.6) and 139 (55%) were male. 102 (40%) screened positive (1+ flag result on their NDDS). A total of 48 (19%) children were referred, and 23 (9%) had a confirmed diagnosis of a developmental delay (speech and language: 14; gross motor: 4; autism spectrum disorder: 3; global developmental delay: 1; developmental delay: 1). The sensitivity was 74% (95% CI: 52–90%), specificity was 63% (95% CI: 57–70%), positive predictive value was 17% (95% CI:10–25%), and the negative predictive value was 96% (95% CI: 92–99%). CONCLUSION For developmental screening tools, sensitivity between 70%-80% and specificity of 80% have been suggested. The NDDS has moderate sensitivity and specificity in identifying developmental delay at the 18-month health supervision visit. The 1+NDDS flag cut-point may lead to overdiagnosis with more children with typical development being referred, leading to longer wait times for specialist referrals among children in need. Future work includes investigating the diagnostic accuracy of combining the NDDS with other screening tools.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".