LAUSR

For more than a century, clinicians have used clinical observation to describe complex psychiatric disorders, such as autism spectrum disorder (ASD). From these observations, screening tools and diagnostic methods, such as the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition), have been developed to predict and define overlapping and heterogeneous conditions that affect neurodevelopment. The current standard of care for screening for ASD involves asking caregivers to complete a questionnaire about their toddlers’ behavior during a pediatric well-child visit. If the caregivers indicate a certain number of symptoms, the toddlers are referred for diagnostic assessment by a trained clinician who observes the children’s behavior using semistandardized behavioral tasks. The clinician then decides whether symptoms are present and their severity. Because of the difficulty in establishing reliable clinical ratings based on subjective observations of behavior, diagnostic training requires extensive background knowledge about child development and several months of training by a criterion standard clinical expert. This rigorous training has influenced the field of autism research over the past several decades, allowing for replication and comparability among studies that was previously impossible. Although standardized methods for clinical observation have been essential in accurately detecting and defining psychiatric disorders, several features of the current process pose challenges. These include using subjective rather than objective measurements, the lack of precision in measurement, a need for highly trained professionals causing long waiting periods for families seeking diagnostic assessments, difficulty in exporting these methods to natural environments, such as homes or communities lacking access to trained professionals, and the infeasibility of gathering large data sets to clarify the heterogeneity of ASD and its overlap with other comorbid disorders. Digital behavioral measurements have the potential to address each of these challenges and transform clinicians’ ability to detect, characterize, diagnose, and monitor symptoms for ASD and other neurodevelopmental disorders. Currently, the use of digital measurement tools is an active area of research in the autism field and has already achieved some success in other areas of psychiatry.1