Children with Autism Spectrum Disorder in Manitoba: Population Characteristics and Psychotropic Medication Use
Bibliographic record
Abstract
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disability diagnosed in an increasing number of children. ASD has few effective treatment options. This study describes ASD prevalence and use of psychotropic medications among children and youth in Manitoba. Methodology: Administrative data from the Repository at the Manitoba Centre for Health Policy (MCHP) were used to create a cohort of children born in Manitoba. Diagnoses of ASD were based on medical claim records, hospital abstracts, or special education funding data. Results: Between 2010 and 2014, 3079 Manitoba children aged 0-14 had an ASD diagnosis (1.2% prevalence). Child demographic, health and education, and family environmental characteristics were compared between children with ASD and children in the general population; children with ASD with and without psychotropic medications; and among all children with psychotropic medications. Children with ASD were more likely to have a psychotropic medication than children in the general population. Children with ASD were more likely to receive a psychotropic medication if they were older than age 4, were diagnosed with ASD later than age 4, received special education funding, had participated in behavioural programming, had a co-occurring psychiatric condition, had a sibling diagnosed with ASD or had ever been in the care of child welfare. This study demonstrated that children with ASD received a greater number and intensity of psychotropic medications than children in the general population with similar demographic and psychiatric conditions. Conclusions: In Manitoba, the prevalence of ASD is increasing and differences exist between children with ASD and children in the general population. Future research and treatment planning for children with mental disorders and developmental disabilities should consider the appropriateness of the patterns of medication use and equity of treatment interventions found in this study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".