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Record W2331108130 · doi:10.1080/21622965.2015.1021957

Validating the Behavior Rating Inventory of Executive Functioning for Children With ADHD and Their Typically Developing Peers

2015· article· en· W2331108130 on OpenAlexaff
Fiona Davidson, Kathlyn M. Cherry, Penny Corkum

Bibliographic record

VenueApplied Neuropsychology Child · 2015
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyAttention deficit hyperactivity disorderTypically developingWorking memoryExecutive functionsClinical psychologySet (abstract data type)Rating scaleDevelopmental psychologyPsychiatryCognitionAutism

Abstract

fetched live from OpenAlex

The Behavior Rating Inventory of Executive Functioning (BRIEF) has been widely used both clinically and in research for measuring executive functioning (EF) in children with attention-deficit hyperactivity disorder (ADHD). This study examined the concurrent validity of the BRIEF (both parent and teacher ratings) compared to performance-based measures of EF in children with ADHD compared to typically developing (TD) children. The authors assessed 20 children with ADHD and 20 TD controls on 4 EF domains-working memory, planning, inhibition, and set shifting-using the BRIEF and performance-based measures of EF. Children (aged 8-12 years old) with ADHD demonstrated more EF impairment than their TD peers on both questionnaire- and performance-based measures. Ratings on questionnaire- and performance-based measures did not uniquely correlate with each other. Questionnaire-based measures were better at discriminating between children with ADHD and TD children, specifically BRIEF parent ratings, and discrimination depended mostly on the Working Memory, Plan/Organize, and Inhibit subscales. The BRIEF has clinical utility for discriminating between children with ADHD and their TD peers; however, some limitations exist for interpretation of the BRIEF, and it should be used with caution in the assessment and diagnosis of ADHD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.317
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations37
Published2015
Admission routes1
Has abstractyes

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