Driving indicators in teens with attention deficit hyperactivity and/or autism spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Motor vehicle crashes are leading causes of death among teens. Those teens with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), or a dual diagnosis of ADHD/ASD have defining characteristics placing them at a greater risk for crashes. PURPOSE: This study examined the between-group demographic, clinical, and simulated driving differences in teens, representing three diagnostic groups, compared to healthy controls (HCs). METHOD: In this prospective observational study, we used a convenience sample of teens recruited from a variety of community settings. FINDINGS: Compared to the 22 HCs (mean age = 14.32, SD = +/-.72), teen drivers representing the diagnostic groups (ADHD/ASD, n = 6, mean age = 15.00, SD = +/-.63; ADHD, n = 9, mean age = 15.00, SD = +/- 1.00; ASD, n = 7, mean age = 15.14, SD = +/-. 1.22) performed poorer on visual function, visual-motor integration, cognition, and motor performance and made more errors on the driving simulator. IMPLICATIONS: Teens from diagnostic groups have more deficits driving on a driving simulator and may require a comprehensive driving evaluation.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".