Atomoxetine and Neuropsychological Function in Children With Attention-Deficit/Hyperactivity Disorder: Results of a Pilot Study
Bibliographic record
Abstract
This pilot longitudinal study using measures from parents and teachers evaluated the effects of flexible doses of atomoxetine (ATX) on neuropsychological and functional outcomes in 21 children with attention-deficit/hyperactivity disorder (ADHD) (mean age, 8.0 +/- 1.3 years; inattentive subtype, 71.4%; combined subtype, 28.6%). Among 16 children completing 6 months of ATX treatment, neuropsychological function measured by the NEPSY instrument found significant improvement from baseline in the memory and learning domain (p = 0.01); this change was also seen in an age- and sex-matched healthy control group (p = 0.011). The patient group showed significant improvement on the Test of Everyday Attention (TEA-Ch) and parent and teacher versions of the Behavior Rating Inventory of Executive Function (BRIEF), which assess attentional and executive processes, respectively. Functional improvement was also observed on the Weiss Functional Impairment Rating Scale-Parent Report (WFIRS-P) and parent and teacher versions of the ADHD Rating Scale (ADHDRS-IV), and the investigator-rated Clinical Global Impressions-Severity (CGI-S) scale evidenced reductions in ADHD symptoms. These findings suggest that potential benefits of ATX treatment may extend beyond reduction of core ADHD symptoms to amelioration of some neuropsychological and functional 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".