Linguistic Predictors of Outcomes in Psychosis

The accurate prediction and tracking of clinical and functional outcomes in young people with schizophrenia-spectrum disorders is critical for delivering appropriate interventions and for understanding the brain mechanisms behind psychosis. Language is an optimal avenue for tracking psychosis processes because language is readily produced and captured, has well-established disruptions in psychosis, and known relationship to brain circuits. Using computers to automate detection of language features has the further advantage of being objective, quantitative, and adaptable into an efficient and cost-effective tool. The investigators propose to use automated linguistic analyses in young people early in the course of schizophrenia spectrum disorders to measure language features including fluency (speech rate), complexity (proportion of unique words), prosody (changes in tone during speech), and semantic coherence (how sequencing of words conform to expected patterns). The investigators will test whether these features meaningfully reflect clinical symptoms, cognition, and functioning, and whether they help predict how psychosis symptoms change over time.