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Record W2315479580 · doi:10.1300/j069v25n04_02

Assessment of Cognitive Functioning of Methadone-Maintenance Patients

2006· article· en· W2315479580 on OpenAlexaff
Daniel J. Brooks, Suzanne K. Vosburg, Suzette M. Evans, Frances R. Levin

Bibliographic record

VenueJournal of Addictive Diseases · 2006
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsColumbia College
FundersNational Institute on Drug AbuseU.S. Public Health Service
KeywordsMethadoneCognitionCognitive flexibilityCognitive skillPsychomotor learningWorking memoryPsychologyClinical psychologyAttention deficit hyperactivity disorderMethadone maintenancePsychiatryEffects of sleep deprivation on cognitive performanceMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to determine if methadone-maintained patients (MMP) with cocaine dependence (CD) and/or adult Attention Deficit Hyperactivity Disorder (ADHD) exhibited compounded cognitive dysfunction associated with their poly-substance use and/or co-morbid psychiatric diagnoses. The sample consisted of 79 MMP (59% male, 51% Caucasian), maintained on methadone doses ranging from 40-130 mg/day, who were placed into one of four diagnostic categories: (1) a control group (no ADHD, no CD) (n = 24), (2) CD alone (n = 18), (3)ADHDalone (n = 18), and (4)ADHD+ CD(n = 19). The California Computerized Assessment Package (CalCAP) was administered to assess cognitive functioning requiring focused and sustained attention in a standardized fashion. There were no group differences on Simple Reaction tasks. Compared to the control group, the ADHD+ CD group was slower and less accurate on 33% of the Choice Reaction (CR) tasks. Specifically, individuals in the ADHD + CD group and the ADHD alone group performed significantly worse on tasks measuring attention and psychomotor responding. These tasks are associated with broader cognitive skills in working memory, language discrimination and flexibility of cognitive sets that may have implications for treatment outcome. Diagnostic services capable of identifying cognitive deficits among MMP with ADHD and/or CD are needed to maximize the likelihood of treatment success and to serve as an indicator for the efficacy of therapeutic approaches.

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 score0.009
Threshold uncertainty score0.390

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 head0.014
GPT teacher head0.318
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

Citations17
Published2006
Admission routes1
Has abstractyes

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