As many as half of school children with autism spectrum disorder (ASD) exhibit\nsymptoms of attention-deficit/hyperactivity disorder (ADHD), resulting in marked negative\nacademic, social, and behavioral outcomes. The focus of the US Food and Drug Administration\n(FDA) on real-world data from novel digital sources, and the emergence of Current Procedural\nTerminology (CPT) codes to reimburse for digital monitoring and neurobehavioral testing suggest\nan increasing acceptance of the role of technology in augmenting clinical care and research.\nEmpowered Brain is an augmented reality and artificial intelligence-based social-emotional\ncommunication aid for students with ASD. In this study, student performance on Empowered Brain\nis correlated to validated clinical measures of ADHD. Seven high school students with a diagnosis\nof ASD were recruited from a public high school. All students were assessed for severity of ADHDrelated\nsymptoms via three clinical gold-standard assessments, namely the Aberrant Behavioral\nChecklist (ABC), Social Responsiveness Scale 2 (SRS-2), and Teacher Report Form (TRF). Students\nused Empowered Brain over a one-week period. We measured the correlation of student in-game\nperformance (as measured by point- and star-based rewards) relative to the hyperactivity subscale\nof the ABC (ABC-H), and the ADHD-subscale of the TRF. All seven students completed the study\nand managed to successfully use Empowered Brain. Students received a culminative total of 32\nsessions, an average of 4.6 sessions per student (range 2-8). Student in-game performance\ndemonstrated highly significant correlation relative to ABC-H (points: p =0.0013; stars: p =0.0013).,\nand significant correlation to TRF ADHD scores (points: p =0.012; stars: p =0.012). No adverse effects\nwere noted among students who used Empowered Brain. New technologies may herald novel ways\nof identifying and characterizing symptoms of ADHD in student populations. This study provides\nevidence that Empowered Brain in-game performance correlates with ADHD symptom severity in\nstudents with ASD. Larger samples are required to validate these findings, with more diverse\nparticipants that can also widen the generalizability of these findings to a broader range of brain\nconditions that manifest with inattention, impulsivity, and hyperactivity. Through further research,\nwe may find that such technologies can help us to identify and longitudinally monitor such\nsymptoms, and potentially aid in severity stratification and digital phenotyping
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