Disentangling the Relationships Between the Clinical Symptoms of Schizophrenia Spectrum Disorders and Theory of Mind: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Previous studies have suggested links between clinical symptoms and theory of mind (ToM) impairments in schizophrenia spectrum disorders (SSD), but it remains unclear whether some symptoms are more strongly linked to ToM than others. STUDY DESIGN: A meta-analysis (Prospero; CRD42021259723) was conducted to quantify and compare the strength of the associations between ToM and the clinical symptoms of SSD (Positive, Negative, Cognitive/Disorganization, Depression/Anxiety, Excitability/Hostility). Studies (N = 130, 137 samples) including people with SSD and reporting a correlation between clinical symptoms and ToM were retrieved from Pubmed, PsycNet, Embase, Cochrane Library, Science Direct, Proquest, WorldCat, and Open Gray. Correlations for each dimension and each symptom were entered into a random-effect model using a Fisher's r-to-z transformation and were compared using focused-tests. Publication bias was assessed with the Rosenthal failsafe and by inspecting the funnel plot and the standardized residual histogram. STUDY RESULTS: The Cognitive/Disorganization (Zr = 0.28) and Negative (Zr = 0.24) dimensions revealed a small to moderate association with ToM, which was significantly stronger than the other dimensions. Within the Cognitive/Disorganization dimension, Difficulty in abstract thinking (Zr = 0.36) and Conceptual disorganization (Zr = 0.39) showed the strongest associations with ToM. The association with the Positive dimension (Zr = 0.16) was small and significantly stronger than the relationship with Depression/Anxiety (Zr = 0.09). Stronger associations were observed between ToM and clinical symptoms in younger patients, those with an earlier age at onset of illness and for tasks assessing a combination of different mental states. CONCLUSIONS: The relationships between Cognitive/Disorganization, Negative symptoms, and ToM should be considered in treating individuals with SSD.
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How this classification was reachedexpand
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".