ABSTRACT
COVID-19 has led to a great deal of general suffering and an increased prevalence of psychiatric illness worldwide. Within the area of psychosis-risk syndromes, a highly heterogeneous clinical population, the picture is quite nuanced as the social restrictions resulting from the pandemic have reduced stress for some and increased it for others. Further, a number of pandemic-related societal and cultural changes have obfuscated the diagnostic and treatment landscape in this area as well. In this opinion article, we describe several prototypical cases, representative of presentations seen in our clinical high-risk (CHR) research programs. The cases highlight considerable clinical variability and, in addition, speak to the current complexities faced by diagnosticians and treatment providers. In addition to discussing these issues, this piece introduces potential solutions highlighting the promise of incorporating data-driven strategies to identify more homogenous CHR subtypes and employ precision medicine.
Subject(s)
COVID-19 , Psychotic Disorders , Schizophrenia , Adolescent , Adult , Female , Humans , Male , Prodromal Symptoms , Psychotic Disorders/diagnosis , Psychotic Disorders/physiopathology , Psychotic Disorders/therapy , Risk , Schizophrenia/diagnosis , Schizophrenia/physiopathology , Schizophrenia/therapyABSTRACT
The integration of technology in clinical care is growing rapidly and has become especially relevant during the global COVID-19 pandemic. Smartphone-based digital phenotyping, or the use of integrated sensors to identify patterns in behavior and symptomatology, has shown potential in detecting subtle moment-to-moment changes. These changes, often referred to as anomalies, represent significant deviations from an individual's baseline, may be useful in informing the risk of relapse in serious mental illness. Our investigation of smartphone-based anomaly detection resulted in 89% sensitivity and 75% specificity for predicting relapse in schizophrenia. These results demonstrate the potential of longitudinal collection of real-time behavior and symptomatology via smartphones and the clinical utility of individualized analysis. Future studies are necessary to explore how specificity can be improved, just-in-time adaptive interventions utilized, and clinical integration achieved.