RESUMO
BACKGROUND: A wide array of existing instruments are commonly used to assess childhood behavior and development for the evaluation of social, emotional and behavioral disorders such as Autism Spectrum Disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and anxiety. Many of these instruments either focus on one diagnostic category or encompass a broad set of childhood behaviors. We analyze a wide range of standardized behavioral instruments and identify a comprehensive, structured semantic hierarchical grouping of child behavioral observational features. We use the hierarchy to create Rosetta: a new set of behavioral assessment questions, designed to be minimal yet comprehensive in its coverage of clinically relevant behaviors. We maintain a full mapping from every functional feature in every covered instrument to a corresponding question in Rosetta. RESULTS: In all, 209 Rosetta questions are shown to cover all the behavioral concepts targeted in the eight existing standardized instruments. CONCLUSION: The resulting hierarchy can be used to create more concise instruments across various ages and conditions, as well as create more robust overlapping datasets for both clinical and research use.
Assuntos
Transtorno do Deficit de Atenção com Hiperatividade , Transtorno do Espectro Autista , Criança , Emoções , HumanosRESUMO
Early identification and intervention of speech and language delays in children contribute to better communication and literacy skills for school readiness and are protective against behavioral and mental health problems. Through collaboration between the data science and clinical teams at Cognoa, we designed Storytime, an interactive storytelling experience on a mobile device using a virtual avatar to mediate speech and language screening for children ages 4 to 6 years old. Our proof-of-concept study collects Storytime session footage from 71 pairs of parents and children including 57 typically developing children and 14 children with a current or prior history of communication impairments. Initial findings suggest that participating children verbally engaged with the video avatar without significant differences in performance across age, gender, and experimental location, leading to promising implications for using Storytime as a future tracking tool with automated feature analyses to detect speech and language delays.