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Record W2795323660 · doi:10.1093/schbul/sby018.867

S80. NEUROCOGNITIVE FUNCTIONING IN YOUTH AT RISK OF SERIOUS MENTAL ILLNESS

2018· article· en· W2795323660 on OpenAlexaffabout
Sylvia Romanowska, Glenda MacQueen, Benjamin A. Goldstein, JianLi Wang, Sidney H. Kennedy, Signe Bray, Catherine Lebel, Jean Addington

Bibliographic record

VenueSchizophrenia Bulletin · 2018
Typearticle
Languageen
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsUniversity of OttawaUniversity of TorontoUniversity Health NetworkHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsNeurocognitivePsychiatryAnxietyBipolar disorderSchizophrenia (object-oriented programming)PsychologyPsychosisClinical psychologyMoodMental illnessApathyMedicineMental healthCognition

Abstract

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Neurocognitive deficits are associated with many serious mental illnesses (SMI), including schizophrenia, bipolar disorder, and major depressive disorder, and have been found to negatively impact social and occupational outcomes, clinical prognosis, and overall quality of life. These deficits have also been observed in people in earlier phases of schizophrenia, specifically in young people at clinical high risk (CHR) of psychosis. In these youth, neurocognitive deficits present at a level intermediate to healthy controls and those with early psychosis, indicating that mild impairments in neurocognitive functioning may be early markers of illness development. It is possible that neurocognitive deficits may be present in young people at risk of a range of SMI beyond the psychosis-spectrum, including affective and anxiety disorders. The aim of this study was to compare neurocognitive functioning in a sample of youth at risk of SMI across the different clinical stages described by McGorry and colleagues and compare them to healthy controls (HCs). It was hypothesized that participants in the later stages of risk, characterized by the presence of subthreshold psychiatric symptoms or attenuated syndromes, would exhibit impairments in neurocognitive performance compared to HCs and asymptomatic youth at familial high risk. This was an observational, cross-sectional study of 243 male and female individuals between the ages of 12–26. The sample consists of participants in the Canadian Psychiatric Risk and Outcome Study (PROCAN) and included: asymptomatic participants at familial high risk for SMI (Stage 0; n=41); youth with early mood or anxiety symptoms (Stage 1a; n=52); youth with attenuated psychotic or affective syndromes and distress (Stages 1b; n=108); and HCs (n=42). The neurocognitive battery included the WRAT-4 reading task, WASI Vocabulary and WASI Matrix Reasoning tasks, and the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB). All neurocognitive tasks were administered at baseline. Group differences in neurocognitive performance were analyzed using MANCOVA/ANCOVA analyses. Covariates included age and sex. Subjects in Stage 0 and Stage 1a did not significantly differ from any group. Subjects in Stage 1b (attenuated syndromes) had significantly lower neurocognitive scores in the domains of speed of processing, working memory, attention/vigilance and reasoning and problem solving, and on composite scores of neurocognitive performance and full-scale IQ compared to HCs. A secondary analysis demonstrated that subjects in Stage 1b who met CHR status according to Criteria of Psychosis-risk Syndromes (n=83) had lower scores in the domains of working memory, verbal learning, and reasoning and problem solving and on the overall composite score than the other participants in Stage 1b who did not meet CHR criteria. This study provides evidence for a growing literature which suggests that neurocognitive deficits may be markers of susceptibility for SMI development. It also increases what is known about neurocognitive performance associated with different stages of risk for SMI. Identification of such impairments could aid with detection of early mental health problems prior to illness onset.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes2
Has abstractyes

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