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Neuropsychological functioning in euthymic bipolar disorder: a meta‐analysis

2007· review· en· W2071744520 on OpenAlexaff
Ivan J. Torres, Vanessa G. Boudreau, Lakshmi N. Yatham

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2007
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaRiverview HospitalSimon Fraser UniversityVancouver Coastal Health
Fundersnot available
KeywordsNeuropsychologyBipolar disorderPsychologyCognitionExecutive functionsWorking memoryNeuropsychological assessmentClinical psychologyPsychiatryAudiologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Although cognitive deficits are prominent in symptomatic patients with bipolar disorder, the extent and pattern of cognitive impairment in euthymic patients remain uncertain. METHOD: Neuropsychological studies comparing euthymic bipolar patients and healthy controls were evaluated. Across studies, effect sizes reflecting patient-control differences in task performance were computed for the 15 most frequently studied cognitive measures in the literature. RESULTS: Across the broad cognitive domains of attention/processing speed, episodic memory, and executive functioning, medium-to-large performance effect size differences were consistently observed between patients and controls, favoring the latter. Deficits were not observed on measures of vocabulary and premorbid IQ. CONCLUSION: Meta-analytic findings provide evidence of a trait-related neuropsychological deficit in bipolar disorder involving attention/processing speed, memory, and executive function. Findings are discussed with regard to potential moderators, etiologic considerations, limitations, and future directions in neuropsychological research on bipolar disorder.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.011
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.377
Teacher spread0.295 · 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.

Study designMeta-analysis
DomainMethods
GenreReview

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

Citations616
Published2007
Admission routes1
Has abstractyes

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