Executive Functions: Performance-Based Measures and the Behavior Rating Inventory of Executive Function (BRIEF) in Adolescents with Attention Deficit/Hyperactivity Disorder (ADHD)
Bibliographic record
Abstract
Performance-based measures and ratings of executive functions were examined in a sample of adolescents with attention deficit/hyperactivity disorder (ADHD) and comparison controls. Performance-based measures of executive function included inhibition, working memory, set shifting, and planning, and ratings of these same executive functions were completed by parents and teachers. Adolescents with ADHD demonstrated lower executive function performance than controls and displayed elevated ratings on the executive function ratings by parents and teachers. Significant associations were obtained between the performance-based measures and the parent and teacher ratings, but each measure was not uniquely associated with its respective scale on the rating scales. When performance-based measures and ratings were examined as predictors of ADHD status, the parent and teacher ratings entered as significant predictors of ADHD status. Further commonality analyses indicated that performance-based measures accounted for little unique variance in predicting ADHD status and also displayed little overlap with the behavioral ratings. These findings highlight the diagnostic utility of behavioral ratings of executive function in predicting ADHD status; however, behavioral ratings should not be assumed to be a proxy for performance on measures of executive function in clinical practice.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".