Social dysfunction is among the most disabling aspects of schizophrenia. Because laboratory assessments are limited, social dysfunction is often measured in daily life. Two common approaches are ecological momentary assessment (EMA; subjective appraisals of one's environment) and mobile sensing methods (MSM; track real- world activity and proximity to speech). Although EMA and MSM increase ecological validity, neither obtains objective accounts of a core facet of social dysfunction: social interactions. The inability to objectively monitor real-world interactions is a critical barrier to accurately identifying and measuring social dysfunction in schizophrenia. The Electronically Activated Recorder (EAR), a computer application for widely used smartphone devices, passively captures real-world social interactions via audio recordings. This proposal's scientific premise is that the EAR will account for limitations of current methods by offering a novel tool to identify social dysfunction in real-world interactions.
The specific aims are to determine the EAR's feasibility, replicability, construct validity, and incremental validity for measuring social dysfunction in schizophrenia. A secondary aim is to improve the EAR's efficiency for research and clinical use by reducing rating time. To test aims, objective ratings of social dysfunction will be made using EAR recordings at baseline and one-month time points in: 1) Healthy control (n = 50) and 2) Schizophrenia groups (n = 50). To show incremental validity, EAR, EMA, and MSM will be conducted simultaneously to test if the EAR accounts for variance beyond EMA/MSM in social dysfunction or its common covariates. In line with NIMH's mission, this proposal will transform understanding of a core mental illness component (i.e., social dysfunction) by offering a window into schizophrenia. Specifically, it addresses Strategic Objective 2.2 by applying a method to identify clinically useful behavioral indicators of social dysfunction. Further, this proposal's use of novel technology to collect real-time data on complex behaviors in schizophrenia is compatible with a recent NIMH High-Priority Area notice (NOT-MH-18-031). Following this study, an R01 trial will integrate the EAR with other naturalistic assessments to measure social dysfunction across illness stages. After the R01, future work will focus on fully automating the EAR and translating it to clinical practice; the long-term goal is to create an evidence-based, objective real-world assessment that evaluates social dysfunction efficiently and is sensitive to different stages of illness and recovery in schizophrenia. However, larger trials are not possible without this essential R03 phase, which serves as a necessary initial test of whether the EAR is feasible and yields added value beyond other real-world approaches.
Schizophrenia accounts for an annual disease burden of over $150 billion in the United States alone; social dysfunction is a primary criterion of this disorder and has been cited by clients as their most disabling symptom. This proposal determines the feasibility, replicability, and validity of a novel tool that accounts for critical limitations of current methodologies by objectively identifying social dysfunction in real-world interactions. By establishing validity and increasing efficiency of this novel tool, findings from this study will directly impact researchers and clinicians in the schizophrenia field by improving identification and measurement of social dysfunction.
