Syntactic complexity of spoken language in the diagnosis of schizophrenia: A probabilistic Bayes network model.
Angelica M Silva, Roberto Limongi, Michael Mackinley, Sabrina D Ford, Maria Francisca Alonso-sánchez, Lena Palaniyappan
Schizophrenia research September 1, 2023 Peer reviewed DOI: 10.1016/j.schres.2022.06.011 via PubMed
Summary
Syntactic complexity declines in the six months after a first episode of psychosis among people later diagnosed with schizophrenia. Twenty-six first-episode psychosis patients and 12 healthy controls gave spoken responses to pictures at first assessment and after six months. Automated analysis of clause complexity showed that a decrease in nominal subjects per clause predicted a schizophrenia diagnosis. A 50% decrease in this measure over six months had a 95.4% probability of being explained by first-episode psychosis. Among those with psychosis, a 30% decrease predicted schizophrenia with 95% probability, distinguishing schizophrenia from other psychotic illnesses.
Study at a glance
| Design | observational cohort |
|---|---|
| Sample size | 38 |
| Population | first-episode psychosis patients and healthy controls |
| Key finding | A longitudinal decrease in nominal subjects per clause over six months after first-episode psychosis predicts a diagnosis of schizophrenia. |
Abstract
In the clinical linguistics of schizophrenia, syntactic complexity has received much attention. In this study, we address whether syntactic complexity deteriorates within the six months following the first episode of psychosis in those who develop a diagnosis of schizophrenia. We collected data from a cohort of twenty-six first-episode psychosis and 12 healthy control subjects using the Thought and Language Index interview in response to three pictures from the Thematic Apperception Test at first assessment and after six months (the time of consensus diagnosis). An automated labeling (part-of-speech tagging) for specific syntactic elements calculated large and granular syntactic complexity indices with a focus on clause complexity as a particular case from this spoken language data. Probabilistic reasoning leveraging the conditional independence properties of Bayes networks revealed that consensus diagnosis of schizophrenia predicted a decrease in nominal subjects per clause among individuals with first episode psychosis. From the entire sample, we estimate a 95.4 % probability that a 50 % decrease in mean nominal subjects per clause after six months is explained by the presence of first episode psychosis. Among those with psychosis, a 30 % decrease in this clause-complexity index after six months of experiencing the first episode predicted with 95 % probability a consensus diagnosis of schizophrenia, representing a conditional relationship between a longitudinal decrease in syntactic complexity and a diagnosis of schizophrenia. We conclude that an early drift towards linguistic disorganization/impoverishment of clause complexity-at the granular level of nominal subject per clause-is a distinctive feature of schizophrenia that decreases longitudinally, thus differentiating schizophrenia from other psychotic illnesses with shared phenomenology.