JAYLA (Junior Agent to typifY Levels of Autism): A Virtual Training Platform to Teach Severity Levels of Autism

Abstract

This initial exploratory study’s primary focus is to investigate the effectiveness of a virtual patient training platform to present a health condition with a range of symptoms and severity levels. The secondary goal is to examine visualization’s role in better demonstrating variances of symptoms and severity levels to improve learning outcomes. We designed and developed a training platform with a four-year-old pediatric virtual patient named JAYLA to teach medical learners the spectrum of symptoms and severity levels of Autism Spectrum Disorder in young children. JAYLA presents three sets of verbal and nonverbal behaviors associated with age-appropriate, mild autism, and severe autism. To better distinguish the severity levels, we designed an innovative interface called the spectrum-view, displaying all three simulated severity levels side-by-side and within the eye span. We compared its effectiveness with a traditional single-view interface, displaying only one severity level at a time. We performed a user study with thirty-four pediatric trainees to evaluate JAYLA’s effectiveness. Results suggest that training with JAYLA improved the trainees’ performance in careful observation and accurate classification of real children’s behaviors in video vignettes. However, we did not find any significant difference between the two interface conditions. The findings demonstrate the applicability of the JAYLA platform to enhance professional training for early detection of autism in young children, which is essential to improve the quality of life for affected individuals, their families, and society.