Validating neuropsychological subtypes of ADHD: how do children <i>with</i> and <i>without</i> an executive function deficit differ?
Bibliographic record
Abstract
OBJECTIVE: The study investigates behavioural, academic, cognitive, and motivational aspects of functioning in school-age children with attention-deficit/hyperactivity disorder (ADHD) with and without an executive function deficit (EFD). METHOD: Children with ADHD--EFD (n = 22) and children with ADHD + EFD (n = 26) were compared on aspects of ADHD behaviour, school functioning, general cognitive ability, intra-individual response variability, affective decision-making, and delay aversion. RESULTS: Children with ADHD--EFD and children with ADHD + EFD were comparable in terms of ADHD symptomatology and school functioning. However, children with ADHD + EFD had significantly lower IQ and more intra-individual response variability than no EFD counterparts. Children with ADHD alone appeared more delay averse on the C-DT task than children with ADHD + EFD. CONCLUSIONS: Some children with ADHD were primarily characterised by problems with executive functions and variability others by problems with delay aversion supporting multiple pathway models of ADHD. Given the exploratory nature of the study, results are in need of replication.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".