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Background Negative symptoms (avolition, anhedonia, asociality) are a prevalent symptom in those across the psychosis-spectrum and also occur at subclinical levels in the general population. Recent work has begun to examine how environmental contexts (e.g. locations) influence negative symptoms. However, limited work has evaluated how environments may contribute to negative symptoms among youth at clinical high risk for psychosis (CHR). The current study uses Ecological Momentary Assessment to assess how four environmental contexts (locations, activities, social interactions, social interaction method) impact state fluctuations in negative symptoms in CHR and healthy control (CN) participants. Methods CHR youth (n = 116) and CN (n = 61) completed 8 daily surveys for 6 days assessing negative symptoms and contexts. Results Mixed-effects modeling demonstrated that negative symptoms largely varied across contexts in both groups. CHR participants had higher negative symptoms than CN participants in most contexts, but groups had similar symptom reductions during recreational activities and phone call interactions. Among CHR participants, negative symptoms were elevated in several contexts, including studying/working, commuting, eating, running errands, and being at home. Conclusions Results demonstrate that negative symptoms dynamically change across some contexts in CHR participants. Negative symptoms were more intact in some contexts, while other contexts, notably some used to promote functional recovery, may exacerbate negative symptoms in CHR. Findings suggest that environmental factors should be considered when understanding state fluctuations in negative symptoms among those at CHR participants.

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Although the COVID-19 pandemic has had detrimental effects on mental health in the general population, the impact on those with schizophrenia-spectrum disorders has received relatively little attention. Assessing pandemic-related changes in positive symptoms is particularly critical to inform treatment protocols and determine whether fluctuations in hallucinations and delusions are related to telehealth utilization and treatment adherence. In the current longitudinal study, we evaluated changes in the frequency of hallucinations and delusions and distress resulting from them across three-time points. Participants included: (1) outpatients with chronic schizophrenia (SZ: n = 32) and healthy controls (CN: n = 31); (2) individuals at clinically high risk for psychosis (CHR: n = 25) and CN ( n = 30). A series of questionnaires were administered to assess hallucination and delusion severity, medication adherence, telehealth utilization, and protective factors during the pandemic. While there were no significant increases in the frequency of hallucinations and delusions in SZ and CHR, distress increased from pre-pandemic to early pandemic in both groups and then decreased at the third time point. Additionally, changes in positive symptom severity in SZ were related to psychiatric medication adherence. Findings suggest that positive symptoms are a critical treatment target during the pandemic and that ongoing medication services will be beneficial. Supplementary Information The online version contains supplementary material available at 10.1007/s00406-023-01551-8.

Background: Negative symptoms are prominent in individuals with schizophrenia (SZ) and youth at clinical high-risk for psychosis (CHR). In SZ, negative symptoms are linked to reinforcement learning (RL) dysfunction; however, previous research suggests implicit RL remains intact. It is unknown whether implicit RL is preserved in the CHR phase where negative symptom mechanisms are unclear, knowledge of which may assist in developing early identification and prevention methods. Methods: Participants from two studies completed an implicit RL task: Study 1 included 53 SZ individuals and 54 healthy controls (HC); Study 2 included 26 CHR youth and 23 HCs. Bias trajectories reflecting implicit RL were compared between groups and correlations with negative symptoms were examined. Cluster analysis investigated RL profiles across the combined samples. Results: Implicit RL was comparable between HC and their corresponding SZ and CHR groups. However, cluster analysis was able to parse performance heterogeneity across diagnostic boundaries into two distinct RL profiles: a Positive/Early Learning cluster (65% of participants) with positive bias scores increasing from the first to second task block, and a Negative/Late Learning cluster (35% of participants) with negative bias scores increasing from the second to third block. Clusters did not differ in the proportion of CHR vs. SZ cases; however, the Negative/Late Learning cluster had more severe negative symptoms. Conclusions: Although implicit RL is intact in CHR similar to SZ, distinct implicit RL phenotypic profiles with elevated negative symptoms were identified transphasically, suggesting distinct reward-processing mechanisms can contribute to negative symptoms independent of phases of illness.