Ecological momentary assessment of negative symptoms in schizophrenia: Relationships to effort-based decision making and reinforcement learning.

Abstract

Negative symptoms are a core clinical feature of schizophrenia, but conceptual and methodological problems with current instruments can make their assessment challenging. One hypothesis is that current symptom assessments may be influenced by impairments in memory and may not be fully reflective of actual functioning outside of the laboratory. The present study sought to investigate the validity of assessing negative symptoms using ecological momentary assessment (EMA). Participants with schizophrenia (N = 31) completed electronic questionnaires on smartphones 4 times a day for 1 week. Participants also completed effort-based decision making and reinforcement learning (RL) tasks to assess the relationship between EMA and laboratory measures, which tap into negative symptom relevant domains. Hierarchical linear modeling analyses revealed that clinician-rated and self-report measures of negative symptoms were significantly related to negative symptoms assessed via EMA. However, working memory moderated the relationship between EMA and retrospective measures of negative symptoms, such that there was a stronger relationship between EMA and retrospective negative symptom measures among individuals with better working memory. The authors also found that negative symptoms assessed via EMA were related to poor performance on the effort task, whereas clinician-rated symptoms and self-reports were not. Further, they found that negative symptoms were related to poorer performance on learning reward contingencies. The findings suggest that negative symptoms can be assessed through EMA and that working memory impairments frequently seen in schizophrenia may affect recall of symptoms. Moreover, these findings suggest the importance of examining the relationship between laboratory tasks and symptoms assessed during daily life. (PsycINFO Database Record