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Record W4253434502 · doi:10.1093/schbul/sbaa029.650

T90. QUANTIFYING THE CORE DEFICIT IN CLASSICAL SCHIZOPHRENIA

2020· article· en· W4253434502 on OpenAlexaff
Mohanbabu Rathnaiah, Elizabeth B. Liddle, Lauren E. Gascoyne, Jyothika Kumar, Mohammad Zia Ul Haq Katshu, Catherine Faruqi, Christina Kelly, Malkeet Gill, Siân E. Robson, Mathew Brookes, Lena Palaniyappan, Peter G. Morris, Peter F. Liddle

Bibliographic record

VenueSchizophrenia Bulletin · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyCognitionCognitive deficitPsychopathologyTrail Making TestClinical psychologyNeuropsychologyNeurosciencePsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

Abstract Background For more than 100 years, disorganization and impoverishment of mental activity have been recognised as fundamental symptoms of schizophrenia. These symptoms may reflect a core brain process underlying persisting disability. Predisposition to persisting disability is a clinically important aspect of schizophrenia, yet the psychopathological processes predisposing to persisting disability are poorly understood. The delineation of a putative core deficit associated with persisting disability would be of potentially great value in delineating the underlying pathological processes and eventually in enhancing treatment. Aims To derive scores for mental disorganization and impoverishment from commonly used rating scales, and test the hypothesis that disorganization and impoverishment, along with impaired cognition and role-function reflect a latent variable that is a plausible candidate for the putative core deficit. Methods In a group of 40 patients with schizophrenia, we tested the hypothesis that mental disorganization and impoverishment, along with impaired cognition and role-function reflect a latent variable that is a plausible candidate for the core deficit. We derived disorganization and impoverishment factors from three symptom scales: PANSS, SSPI and CASH. For each of the three scales, we demonstrated significant correlation between these factors and impaired role function assessed using the Social and Occupational Functioning Scale (SOFAS) and cognitive impairment measured using the Digit Symbol Substitution Test (DSST). We then assessed the relationship between this latent “core deficit” variable and Post Movement Beta Rebound (PMBR), measured using magnetoencephalography and associated with persisting brain disorders. Results A single factor model provided excellent fit for the four features of core deficit, requiring no further modifications. Results were consistently similar for measures from all three scales. χ2 value was non-significant (range: 0.30 to 2.13, df = 2, p > 0.35), GFI met the threshold of greater than 0.9 (range = .976 to .996) and RMSEA was lesser than 0.06 (range = 0.000 to 0.040). PMBR was found to be significantly reduced in the schizophrenia group compared to healthy controls (t (28) =44.2 ± 12.1, p = 0.001). PMBR was strongly correlated with disorganization (r (40) = .600, p=0.001). In the hierarchical regression, neither age nor medication dose were significant predictors, but PMBR did predict the severity of the core deficit (F (1, 23) = 12.6, P=0.002, R² = -.592). Discussion Scores for the two latent variables representing impoverishment and disorganization of mental activity in schizophrenia can be derived from each of three symptom rating scales. A composite measure of impoverishment, disorganization, impaired cognition and impaired role function reflects an underlying psychopathological process that might be described as the core deficit of classical 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 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.098
GPT teacher head0.283
Teacher spread0.185 · 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 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".

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Citations3
Published2020
Admission routes1
Has abstractyes

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