Is the behavior rating inventory of executive function more strongly associated with measures of impairment or executive function?
Bibliographic record
Abstract
The Behavior Rating Inventory of Executive Function (BRIEF) is commonly used in the assessment of children and adolescents presenting with a wide range of concerns. It is unclear, however, whether the questionnaire is more closely related to general measures of behavioral disruption and impairment or to specific measures of executive function. In the present study, associations between the Behavioral Regulation Index and Metacognition Index of the BRIEF and cognitive, behavioral, and academic measures were examined in a sample of clinic-referred youth (n = 60) and healthy youth (n = 37) 6-15 years of age. Measures included ratings of inattentive and hyperactive-impulsive symptoms in youth, ratings of how well youth functioned in their everyday environments, youth's scores on measures of reading and math, and youth's scores on measures of inhibition, performance monitoring, and working memory. Although both BRIEF indices were strongly related to parent and teacher ratings of behavioral disruption and impairment, neither was associated with youth's scores on the performance-based tasks of executive function. These findings support the use of the BRIEF as a clinical tool for assessing a broad range of concerns, but raise questions about the relation of the BRIEF to performance-based tasks that are commonly used to assess executive function.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".