S19. ANALYZING NEGATIVE SYMPTOMS AND LANGUAGE IN YOUTHS AT RISK FOR PSYCHOSIS USING AUTOMATED LANGUAGE ANALYSIS

摘要

Schizophrenia is characterized by disturbances in thought and language, often resulting in reduced production and complexity of speech, and abnormal pauses; these language disturbances have been associated with negative symptoms (Cohen et al., 2016). Using clinical ratings, we and others have shown that both language disturbances and negative symptoms are evident prior to psychosis onset in youths at clinical high risk (CHR). Automated natural language processing (NLP) analyses of transcribed speech show that both reductions in semantic coherence and syntactic complexity predict psychosis onset in CHR individuals (Bedi et al., 2015). In the current study, we assessed whether NLP syntactic complexity features and aberrant pauses may be associated with negative symptoms in CHR youths.