Developmental functioning and symptom severity influence age of diagnosis in Canadian preschool children with autism
Bibliographic record
Abstract
BACKGROUND: Early diagnosis of autism spectrum disorder (ASD) is essential in most Canadian jurisdictions to access interventions that improve long-term child outcomes. Our main objective was to identify factors associated with timing of ASD diagnosis in five provinces across Canada. METHODS: Factors influencing age of diagnosis were assessed in the analyses of an inception cohort of children diagnosed with ASD between ages 2 and 5 years. We examined bivariate associations and using a series of multiple variable regression models, evaluated the unique contributions of developmental functioning, ASD symptoms and demographic variables. Children with known genetic abnormalities, or severe sensory or motor impairments interfering with assessment were excluded. RESULTS: associated with age of diagnosis. In regression analyses, language and cognitive skills accounted for 6.8% of variance in age of diagnosis and ASD symptoms contributed an additional 5.5%. Provincial site accounted for 4.0% of variance in age of diagnosis, independent of developmental skills and ASD symptoms. INTERPRETATION: Diagnosis of ASD occurred, on average, 19 months after parents' initial concerns. Language and cognitive skills, symptom severity and provincial site accounted for variation in age of ASD diagnosis in this Canadian cohort. Variable presentation across the developmental continuum must be considered in planning assessment services to ensure timely ASD diagnosis so that outcomes can be improved. Policy and practice leadership is also needed to reduce interprovincial variability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".