Inattention, Hyperactivity, and Impulsivity in Teenagers with Intellectual Disabilities, with and without Autism
Bibliographic record
Abstract
OBJECTIVE: To explore inattentive, hyperactive, and impulsive behaviours in teenagers with intellectual disabilities (ID), with and without autism. METHOD: We identified teenagers with ID, with and without autism, in a single geographic area. Those with autism were matched for age, sex, and nonverbal IQ to those with ID only. We compared inattentive, hyperactive, and impulsive (IHI) behaviours in the 2 groups, along with adaptive functioning and medical circumstances. We further subdivided the autism group into those with IHI behaviours (autism IHI) and those without (autism non-IHI) and explored similarities and differences between autism subgroups. RESULTS: As a group, those with autism and ID had more IHI behaviours than those with ID alone. More in the autism group met criteria for attention-deficit hyperactivity disorder and hyperkinetic syndrome. Lifetime exposure to psychotropic medication was greater in the autism group, with stimulant and antipsychotic medications predominating. However, just under one-half of those in the autism group showed no IHI behaviours. Comparison of autism IHI and autism non-IHI groups showed that those with IHI behaviours were significantly more likely to have past (but not current) exposure to stimulant medication. CONCLUSIONS: One in 2 teenagers with ID and coexisting autism displayed clinically significant inattentive, hyperactive, and (or) impulsive behaviours, compared with 1 in 7 of those with ID alone. Most of the remaining teenagers with autism displayed no IHI behaviours. Our results support the need for further investigation into the prevalence and etiology of these IHI behaviours in individuals with autism.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".