Formal Thought Disorders and Neurocognition in Treatment-Resistant Schizophrenia: Trouble du cours de la pensée et neurocognition dans la schizophrénie réfractaire
Bibliographic record
Abstract
OBJECTIVE: Formal thought disorders (FTDs), a core feature of schizophrenia, have been subdivided into positive and negative types, and are clinically assessed by examining speech (objective) or patient introspection (subjective). Despite being associated with poorer treatment response and worse outcomes, FTDs have been understudied in patients with schizophrenia, in particular treatment-resistant schizophrenia (TRS) or schizoaffective disorder. We aimed to explore the relationship between the severity of positive and negative FTDs and neurocognition as well as social/occupational functioning in this clinical subgroup. METHOD: This was a retrospective chart review conducted at the Clozapine Clinic at the Centre for Addiction and Mental Health, Toronto, Canada. We reviewed charted standardized assessment of FTDs using the Thought and Language Disorder (TALD) scale, neurocognition using the Brief Cognitive Assessment Tool for Schizophrenia (B-CATS), and functioning using the Social and Occupational Functioning Assessment Scale (SOFAS) between October 2022 and June 2023. Following the original factor structure of the TALD, we computed 4- factor scores that combined positive or negative and objective or subjective FTDs. We then explored the correlation between the scores from each TALD factor and the neurocognition and functioning scores. RESULTS: < 0.001. CONCLUSIONS: Our results demonstrate the strong relationship between FTDs, neurocognition, and social/occupational functioning in a sample of TRS outpatients. Within the cognitive domains assessed, verbal working memory impairment had the strongest correlation with positive FTDs, such as derailment or tangentiality. These findings highlight the value of employing standardized psychopathological scales for FTDs in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".