Thought and Language Index: an instrument for assessing thought and language in schizophrenia
Bibliographic record
Abstract
BACKGROUND: Subtle formal thought disorders are difficult to quantify. Their relationship to florid thought disorder is unknown. AIMS: To assess the interrater reliability, sensitivity and factor structure of a new assessment instrument, the Thought and Language Index (TLI), and to determine if minor aberrations detectable in the speech of healthy individuals are related to the more severe formal thought disorders characteristic of schizophrenia. METHOD: Interrater reliability was evaluated by determining the intraclass correlation for the ratings by five assessors. Factor analysis of the TLI scores of 87 patients was performed, and TLI scores in matched patients and controls were compared. RESULTS: The intraclass correlation was good for individual TLI items, and excellent for sub-scale scores. Factor analysis identified three groups of approximately orthogonal disorders. Mild speech aberrations were observed in healthy participants and in patients with schizophrenia. The prevalence of mild aberrations was correlated with the prevalence of definite formal thought disorders. CONCLUSIONS: The TLI is reliable and capable of detecting subtle disorders. Some mild aberrations occurring in the speech of healthy individuals appear to be attenuated forms of the florid disorders characteristic of schizophrenia.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".