Prevalence and Correlates of Autism Spectrum Disorders in Quebec
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To estimate the prevalence, comorbidities, and service use of people with autism spectrum disorders (ASDs) based on data from Quebec Integrated Chronic Diseases Surveillance System (QICDSS).We included all residents up to age 24 eligible for health plan coverage who were in Quebec for at least 1 day from January 1, 1996, to March 31, 2015. To be considered as having an ASD, an individual had to have had at least 1 physician claim or hospital discharge abstract from 2000 to 2015 indicating one of the following ASD diagnosis codes: ICD-9 codes 299.0 to 299.9 or their ICD-10 equivalents.The QICDSS shows that the prevalence of ASD has risen steadily over the past decade to approximately 1.2% ( n = 16,940) of children and youths aged 1 to 17 years in 2014 to 2015. The same prevalence was obtained using Ministry of Education data. Common medical comorbidities included congenital abnormalities of the nervous system, particularly in the first year of life. Psychiatric comorbidity was much more highly prevalent, especially common mental disorders like anxiety and attention-deficit/hyperactivity disorder. Children and youths with ASDs made on average 2.3 medical visits per year compared with 0.2 in the general population. Between 18 and 24 years old, the mental health needs of individuals with ASDs were met less by medical specialists and more by general practitioners.Information derived from this database could support and monitor development of better medical services coordination and shared care to meet the continuous and changing needs of patients and families over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it