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Record W2604208477 · doi:10.1017/s1366728915000887

Interaction of bilingualism and Attention-Deficit/Hyperactivity Disorder in young adults

2016· article· en· W2604208477 on OpenAlexaff
Ellen Bialystok, Kornelia Hawrylewicz, Melody Wiseheart, Maggie E. Toplak

Bibliographic record

VenueBilingualism Language and Cognition · 2016
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsYork University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsNeuroscience of multilingualismPsychologyExecutive functionsAttention deficit hyperactivity disorderDevelopmental psychologyVocabularyTask (project management)CognitionAudiologyClinical psychologyPsychiatryMedicineLinguistics

Abstract

fetched live from OpenAlex

One hundred and sixty-eight young adult participants were classified as monolingual or bilingual and as having a previously reported clinical diagnosis of ADHD or not to create four groups. All participants completed tests of language proficiency, ADHD ratings, and executive control. Both bilingualism and ADHD are generally associated with poorer vocabulary knowledge, but bilingualism and ADHD are associated with opposite effects on executive control. Consistent with this literature, bilinguals performed more poorly than monolinguals on the vocabulary test but contrary to predictions, the ADHD group performed somewhat better on language ability than the non-ADHD group, attesting to their high functioning status. For the flanker task, both bilinguals and non-ADHD participants showed less cost in performing in the conflict condition than in the baseline condition. For the stop-signal task, ADHD status interfered more with performance by bilinguals than monolinguals, suggesting a greater burden of ADHD on executive function for this group.

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)0.001
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 score0.274
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.305
Teacher spread0.289 · 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

Citations38
Published2016
Admission routes1
Has abstractyes

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