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Record W2118725511 · doi:10.1177/0734282906297627

The Relationship Between Working Memory, Inhibition, and Performance on the Wisconsin Card Sorting Test in Children With and Without ADHD

2007· article· en· W2118725511 on OpenAlexaff
Jennifer C. Mullane, Penny Corkum

Bibliographic record

VenueJournal of Psychoeducational Assessment · 2007
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWisconsin Card Sorting TestPsychologyWorking memoryAttention deficit hyperactivity disorderExecutive functionsIntelligence quotientDevelopmental psychologyClinical psychologyTest (biology)CorrelationPsychiatryCognitionNeuropsychology

Abstract

fetched live from OpenAlex

The Wisconsin Card Sorting Test (WCST) has frequently been used to assess executive functions in children with attention deficit hyperactivity disorder (ADHD). We first compared the performance of 15 children with ADHD to 15 children of a control group (age range 6 to 11) on the WCST and then examined the relationship among working memory, inhibition, age, IQ, and scores from this test. When age and IQ were included as covariates, children with and without ADHD did not differ on the perseverative errors (PE) score, but the ADHD group made significantly more failure to maintain set errors (FTMS). Partial correlations revealed that working memory was significantly correlated with PE but was fully mediated by age and IQ. Age and IQ had no effect on the significant correlation between inhibition and FTMS. Clinicians are encouraged to interpret the results of this test with caution when including it in an assessment for 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.387
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations46
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of Psychoeducational AssessmentSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207