Usability Enhancement and Functional Extension of a Digital Tool for Rapid Assessment of Risk for Autism Spectrum Disorders in Toddlers Based on Pilot Test and Interview Data

Abstract

Early accurate identification and treatment of young children with Autism Spectrum Disorder (ASD) represents a pressing public health and clinical care challenge. Unfortunately, large numbers of children are still not screened for ASD, waits for specialized diagnostic assessment can be very long, and the average age of diagnosis in the US remains between 4 to 5 years of age. In a step towards meaningfully addressing this issue, we previously developed Autoscreen: a digital tool for accurate and time-efficient screening, diagnostic triage, referral, and treatment engagement of young children with ASD concerns within community pediatric settings. In the current work, we significantly improve upon and expand Autoscreen based on usability data and interview data collected in a pilot investigation of pediatric healthcare providers using Autoscreen. The enhanced version of Autoscreen addresses limitations of the previous tool, such as scalability, and introduces important new features based on rigorous interviews with the target user population. Once validated on a large sample, Autoscreen could become an impactful tool for early ASD screening and targeted referral in primary care settings. The comprehensively-enhanced tool described in the current work will enable the investigative team to achieve this goal.