MétaCan
Menu
Back to cohort

The International Society for Bipolar Disorders–Battery for Assessment of Neurocognition (ISBD‐BANC)

2010· review· en· W2030740270 on OpenAlexaff
Lakshmi N. Yatham, Ivan J. Torres, Gin S. Malhi, Sophia Frangou, David C. Glahn, Carrie E. Bearden, Katherine E. Burdick, Anabel Martínez‐Arán, Sandra Dittmann, Joseph F. Goldberg, Ayşegül Özerdem, Ömer Aydemır, K. N. Roy Chengappa

Bibliographic record

VenueBipolar Disorders · 2010
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsBC Mental Health & Substance Use ServicesUniversity of British Columbia
Fundersnot available
KeywordsBipolar disorderNeurocognitivePsychologyCognitionSchizophrenia (object-oriented programming)PsychiatryBipolar II disorderClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: Although cognitive impairment is recognized as an important clinical feature of bipolar disorder, there is no standard cognitive battery that has been developed for use in bipolar disorder research. The aims of this paper were to identify the cognitive measures from the literature that show the greatest magnitude of impairment in bipolar disorder, to use this information to determine whether the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB), developed for use in schizophrenia, might be suitable for bipolar disorder research, and to propose a preliminary battery of cognitive tests for use in bipolar disorder research. METHODS: The project was conducted under the auspices of the International Society for Bipolar Disorders and involved a committee that comprised researchers with international expertise in the cognitive aspects of bipolar disorder. In order to identify cognitive tasks that show the largest magnitude of impairment in bipolar disorder, we reviewed the literature on studies assessing cognitive functioning (including social cognition) in bipolar disorder. We further provided a brief review of the cognitive overlap between schizophrenia and bipolar disorder and evaluated the degree to which tasks included in the MCCB (or other identified tasks) might be suitable for use in bipolar disorder. RESULTS: Based on evidence that cognitive deficits in bipolar disorder are similar in pattern but less severe than in schizophrenia, it was judged that most subtests comprising the MCCB appear appropriate for use in bipolar disorder. In addition to MCCB tests, other specific measures of more complex verbal learning (e.g., the California Verbal Learning Test) or executive function (Stroop Test, Trail Making Test-part B, Wisconsin Card Sorting Test) also show substantial impairment in bipolar disorder. CONCLUSIONS: Our analysis reveals that the MCCB represents a good starting point for assessing cognitive deficits in research studies of bipolar disorder, but that other tasks including more complex verbal learning measures and tests of executive function should also be considered in assessing cognitive compromise in bipolar disorder. Several promising cognitive tasks that require further study in bipolar disorder are also presented.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.007

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 head0.040
GPT teacher head0.356
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 designBench or experimental
Domainnot available
GenreMethods

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

Citations262
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueBipolar DisordersSame topicBipolar Disorder and TreatmentFrench-language works237,207