Being well understood and generating interest during verbal interactions: the role of Theory of Mind and clinical symptoms in people with schizophrenia spectrum disorders
Bibliographic record
Abstract
People with schizophrenia spectrum disorders (SSD) present with communication impairments. This study aimed to determine whether individuals with SSD make it less easy or interesting to perform a joint task with them relative to community controls (CO), and to examine the link between clinical symptoms and theory of mind (ToM). Fifty-one outpatients with SSD and 68 CO performed the storytelling in sequence task (STST) with an interaction partner. Four raters subsequently listened to the STST audio recordings and scored how easily they could place the images of the narrated stories in the correct order (Facility ratings), how interesting they found the stories (Interest ratings) and how expressive they found the voice (Expressivity ratings). Symptoms were assessed using the Positive and Negative Syndrome Scale and ToM using the Combined Stories Test. The Facility, Interest and Expressivity ratings were lower in SSD than in CO. In SSD, the Facility ratings were positively associated with ToM and negatively associated with several symptom dimensions. The Interest and Expressivity ratings were strongly linked together and negatively associated with Negative symptoms. ToM deficits in SSD may contribute to difficulties communicating clearly. The strong association between Expressivity and Interesting ratings raises important questions regarding the real-life impacts of reduced expressivity.This article is part of the theme issue 'At the heart of human communication: new views on the complex relationship between pragmatics and Theory of Mind'.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".