Linguistic determinants of formal thought disorder in first episode psychosis
Why this work is in the frame
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Bibliographic record
Abstract
AIM: Thought disorder is a core feature of schizophrenia but assessment of disordered thinking is challenging, which may contribute to the paucity of mechanistic understanding of disorganization in early psychosis. We studied the use of linguistic connectives in relation to clinically quantified dimensions of thought disorder using automated speech analysis in untreated, first episode psychosis (FEPs) and healthy controls (HCs). METHODS: 39 treatment-naïve, actively psychotic FEPs and 23 group matched HCs were recruited. Three one-minute speech samples were induced in response to photographs from the Thematic Apperception Test and speech was analysed using COH-METRIX software. Five connectives variables from the Coh-Metrix software were reduced using principle component analysis, resulting in two linguistic connectives factors. Thought disorder was assessed using the Thought Language Index (TLI) and the PANSS-8. RESULTS: Connective factors predicted disorganization, but not impoverishment suggesting aberrant use of connectives is specific to positive thought disorder. An independent t test comparing low and high disorganization FEPs showed higher load of acausal temporal connectives in high disorganization FEPs compared to low disorganization FEPs (mean [SD] in high vs low disorganization FEPs = 0.64 (1.1) vs -0.37 (1.02); t = 2.91, P = .006). Acausal-temporal connectives were not correlated with severity of symptoms or cognition suggesting connective use is a specific index of disorganized thinking rather than overall illness status. CONCLUSIONS: Clinical assessment of disorganization in psychosis is likely linked to the aberrant use of connectives resulting in an intuitive sense of incoherence. In early psychosis, thought disorder may be reliably quantifiable using automated syntax analysis.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it