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Record W4361211270 · doi:10.1016/j.scog.2023.100283

Verbal and visual learning ability in patients with treatment-resistant schizophrenia: A 1-year follow-up study

2023· article· en· W4361211270 on OpenAlexaff
Urška Arnautovska, Kathryn Vitangcol, James P. Kesby, Nicola Warren, Susan L. Rossell, Erica Neill, Anthony Harris, Cherrie Galletly, David Castle, Dan Siskind

Bibliographic record

VenueSchizophrenia Research Cognition · 2023
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Health and Medical Research CouncilH. Lundbeck A/S
KeywordsVerbal learningSchizophrenia (object-oriented programming)PsychologyCognitionVerbal memoryAnticholinergicCalifornia Verbal Learning TestEffects of sleep deprivation on cognitive performanceClinical psychologyPsychiatryAudiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Objective: In the general population, repeated cognitive testing produces learning effects with potential for improved test performance. It is currently unclear whether the same effect of repeated cognitive testing on cognition pertains to people living with schizophrenia, a condition often associated with significant cognitive impairments. This study aims to evaluate learning ability in people with schizophrenia and-considering the evidence that antipsychotic medication can additionally impair cognitive performance-explore the potential impact of anticholinergic burden on verbal and visual learning. Method: The study included 86 patients with schizophrenia, treated with clozapine, who had persisting negative symptoms. They were assessed at baseline, weeks 8, 24 and 52 using Positive and Negative Syndrome Scale, Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-R (BVMT-R). Results: There were no significant improvements in verbal or visual learning across all measurements. Neither the clozapine/norclozapine ratio nor anticholinergic cognitive burden significantly predicted participants' total learning. Premorbid IQ was significantly associated with verbal learning on the HVLT-R. Conclusions: These findings advance our understanding of cognitive performance in people with schizophrenia and demonstrate limited learning performance in individuals with treatment-refractory schizophrenia.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
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 head0.037
GPT teacher head0.344
Teacher spread0.307 · 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.

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

Citations7
Published2023
Admission routes1
Has abstractyes

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