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Syntactic network analysis in first-episode psychosis: toward generalizability.
Silvia Ciampelli1, Janna Niña de Boer2, Alban Elias Voppel3
1Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. s.ciampelli@umcg.nl.
Schizophrenia (Heidelberg, Germany)
|December 3, 2025
Summary
Automated syntactic markers accurately identified early psychosis in Brazilian Portuguese speakers. This finding supports using these language-based measures for psychosis detection across different languages and patient groups.
Area of Science:
- Computational linguistics
- Psychiatry
- Neuroscience
Background:
- Early psychosis detection is crucial for effective treatment.
- Automated linguistic analysis offers a novel approach to identifying psychiatric conditions.
- Previous studies showed promise in Dutch-speaking populations.
Purpose of the Study:
- To investigate the efficacy of automated syntactic markers in distinguishing first-episode psychosis (FEP) from healthy controls.
- To assess the generalizability of these markers in a Brazilian Portuguese-speaking sample.
Main Methods:
- Utilized automated syntactic analysis of speech.
- Compared linguistic features between patients with FEP and healthy controls.
- Employed cross-validation techniques for accuracy assessment.
Main Results:
- Automated syntactic markers achieved 81% cross-validated accuracy (AUC = 0.86) in distinguishing FEP.
- Findings replicated previous results observed in Dutch-speaking individuals.
- Effectiveness demonstrated across different languages and speech elicitation tasks.
Conclusions:
- Automated syntactic measures show significant potential for identifying early psychosis.
- These language-based markers are robust and generalizable across linguistic contexts.
- This approach could enhance early detection and intervention strategies for psychosis.
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