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Effects of methylphenidate on working memory components: influence of measurement

2007· article· en· W1538570794 on OpenAlexaff
Anne‐Claude Bedard, Umesh Jain, Sheilah Hogg Johnson, Rosemary Tannock

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2007
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsInstitute for Work & HealthCentre for Addiction and Mental HealthHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMethylphenidateWorking memoryAudiologyPsychologyCrossover studyAttention deficit hyperactivity disorderModality (human–computer interaction)PlaceboCognitionMedicineClinical psychologyPsychiatryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: To investigate the effects of methylphenidate (MPH) on components of working memory (WM) in attention-deficit hyperactivity disorder (ADHD) and determine the responsiveness of WM measures to MPH. METHODS: Participants were a clinical sample of 50 children and adolescents with ADHD, aged 6 to 16 years old, who participated in an acute randomized, double-blind, placebo-controlled, crossover trial with single challenges of three MPH doses. Four components of WM were investigated, which varied in processing demands (storage versus manipulation of information) and modality (auditory-verbal; visual-spatial), each of which was indexed by a minimum of two separate measures. RESULTS: MPH improved the ability to store visual-spatial information irrespective of instrument used, but had no effects on the storage of auditory-verbal information. By contrast, MPH enhanced the ability to manipulate both auditory-verbal and visual-spatial information, although effects were instrument specific in both cases. CONCLUSIONS: MPH effects on WM are selective: they vary as a function of WM component and measurement.

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)0.000
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 score0.208
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.028
GPT teacher head0.331
Teacher spread0.303 · 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

Citations81
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of Child Psychology and PsychiatrySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207