MétaCan
Menu
Back to cohort
Record W4376611899 · doi:10.1177/10870547231174036

The Relationship Between Cortical Thickness and Executive Function Measures in Children With and Without ADHD

2023· article· en· W4376611899 on OpenAlexaff
Elana Sarabin, Kelsey Harkness, Kara Murias

Bibliographic record

VenueJournal of Attention Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsHotchkiss Brain InstituteOntario Brain InstituteAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsImpulsivityPsychologyWorking memoryAttention deficit hyperactivity disorderExecutive functionsCognitionCBCLDevelopmental psychologyResponse inhibitionClinical psychologyAudiologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Attention Deficit Hyperactivity Disorder (ADHD) is characterized by inattention, hyperactivity, and impulsivity; however, other executive function dysregulation is common, including inhibition and working memory. This study aims to identify CT differences based on executive function performance in individuals with and without ADHD. METHODS: Data for this study was acquired from the Adolescent Brain and Cognitive Development (ABCD) database (61 ADHD, and 61 age and sex matched controls). General linear models were used to assess relationships between measures, CT, and diagnosis. RESULTS: We found a significant relation between CT and working memory scores in the right precentral area. Additionally, we found significant interactions between CT, diagnosis, and measure outcome in the Flanker assessment (in the left fusiform area) and the attention score of the CBCL (in the right precentral region). CONCLUSION: This suggests that there may be different relationships that exist between CT and executive function in children with 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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.052
GPT teacher head0.325
Teacher spread0.273 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Attention DisordersSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207