Neuropsychological Performance in DSM-IV ADHD Subtypes: An Exploratory Study with Untreated Adolescents
Bibliographic record
Abstract
OBJECTIVE: To explore neuropsychological performance in untreated Brazilian adolescents suffering from attention-deficit hyperactivity disorder (ADHD). METHOD: We assessed 30 untreated adolescents with ADHD and 60 healthy control subjects, aged 12 to 16 years, using a neuropsychological battery including the Wisconsin Card-Sorting Test (WCST), the Stroop Test (ST), the Digit Span, and the Word Span. RESULTS: We found neuropsychological differences among the DSM-IV ADHD subtypes. Adolescents with the predominantly inattentive subtype (ADHD-I) performed more poorly than did control subjects on both the Digit Span and the ST. On both the Digit Span and the WCST, adolescents with the combined subtype (ADHD-C) presented significantly more impairments than did control subjects. Adolescents with the predominantly hyperactive-impulsive type (ADHD-HI) did not differ significantly from the control subjects in any measure assessed, but had a better performance than did those with ADHD-C on both the Digit Span and the WCST. In addition, adolescents with ADHD-HI performed better on the ST than did adolescents with ADHD-I. CONCLUSIONS: These findings suggest cognitive differences among ADHD subtypes, supporting the diagnostic distinction among them. Adolescents with ADHD-HI do not seem to have significant cognitive deficits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".