Abstract
BACKGROUND AND HYPOTHESIS: Negative symptoms are important and common concerns in individuals at clinical high risk for psychosis (CHR-P) but are not systematically utilized to predict or improve outcomes. We explored the ability of various negative symptom models to predict the onset of psychosis while controlling for potential secondary sources of these symptoms. STUDY DESIGN: A total of 581 participants from the North American Prodrome Longitudinal Study (NAPLS3) were assessed at baseline, 2-, 4-, and 6-month follow-up. This included 70 high-risk individuals who transitioned to psychosis (CHR-T) and 415 who did not transition to psychosis (CHR-NT), as well as 96 healthy controls (HCs). Attenuated positive and negative symptoms were rated on the Scale of Prodromal Symptoms. Three negative symptom models were evaluated: (1) total negative symptoms; (2) experiential and expressive negative symptoms; and (3) separate analyses for each negative symptom. Depressive symptoms were determined via the Calgary Depression Scale for Schizophrenia. STUDY RESULTS: Total negative symptoms differed significantly between all 3 groups across time, such that CHR-T > CHR-NT > HC (P < .001). This pattern remained after adjusting for positive and depressive symptoms (P < .001). Baseline negative symptom severity predicted psychosis (P = .007), even with positive and depressive symptoms included in the model. Similar results were observed for experiential (P = .016) and expressive (P = .027) negative symptoms as well as social anhedonia (P = .011) and ideational richness (P = .002). CONCLUSIONS: Our findings reinforce the importance of negative symptoms in predicting psychosis in CHR-P youth. The data support consideration of negative symptoms in predictive algorithms for enhancing early recognition and treatment strategies.