Potential Role of Smartphone Technology in Advancing Work on Neurological Soft Signs with a Focus on Schizophrenia

Abstract

Learning Objective: After participating in this CME activity, the psychiatrist should be better able to • Outline and Identify potential benefits of using neurological soft signs (NSS) as biomarkers of schizophrenia. Abstract Since the late 1960s, NSS have been a focus of study across psychiatric illnesses, including depression, bipolar disorder, and schizophrenia in particular. Utilizing these subtle neurological impairments as biomarkers of illness has numerous benefits; NSS offer a direct connection between clinical presentation and neurological functioning, and assessments are cost-effective. However, incongruent measurement scales, confounding variables, and rating system subjectivity have hindered the advancement and scalability of NSS research and clinical implementation. This article provides a brief overview of the literature on NSS as related to schizophrenia, and proposes utilizing smartphone sensing technology to create standardized NSS assessments with objective scoring. Incorporating digital phenotyping into NSS assessment offers the potential to make measurement more scalable, accessible, and directly comparable across locations, cultures, and demographics. We conducted a narrative search in PubMed and APA PsycInfo using the following keywords: neurological soft signs, schizophrenia spectrum disorders, and psychotic illnesses. No date limitations were used. There is no other direct work on NSS and new smartphone methods like digital phenotyping; though, there is related work in neurology. Harnessing advances in smartphone technology could provide greater insight into and further our understanding of specific aspects of the NSS field. For instance, it could help us distinguish trait vs. state markers and better understand how distinct groups of signs may reflect different aspects of psychiatric illness and neurological impairment. In addition, such technology can help advance research on the capabilities of NSS as an effective diagnostic tool.