Impairments in social communication are among the core symptoms of ASD, but at present, there are no validated tools that can be used to evaluate social communication outcomes in clinical trials. Researchers from three sites across the United States will validate two newly developed treatment outcome measures — the Brief Observation of Social Communication Change (BOSCC) and Elicitation of Language Samples for Analysis (ELSA) over the course of an ASD behavioral intervention trial (JASPER).

Eva Loth and Robert Leech plan to combine age-appropriate animated cartoons with cutting-edge artificial intelligence techniques to optimize and validate a set of novel tablet tests assessing key social, emotional, motivational and cognitive processes implicated in core features of autism.

Finding a tool that can quickly and accurately help triage risk of autism is a critical need in the field and can have a large impact on families and clinicians. Stephen Kanne, Antonio Hardan and Micah Mazurek plan to perform a multisite study to evaluate whether a tool called AutismEYES, which assesses an individual’s eye gaze, can provide a quantitative and objective measure to improve ASD identification and track symptom change over time.

Guillermo Sapiro, in collaboration with Geraldine Dawson, seeks to develop and validate automatic, objective and quantitative measurements of social communicative and motor behaviors based on visual attention, affective facial expressions, vocalizations and head movements that can serve as feasible, reliable and sensitive outcome measures in autism clinical trials.

One of the most important objectives of autism spectrum disorder (ASD) interventions is to improve spoken communicative language skills. Across all ages and levels of language, quantitative changes in the amount of intelligible speech, the length of speaker turns and better conversational turn-taking are key measures of advances in spoken language. Changes in these measures not only signify that a treatment is effective in improving language itself, but also leads to improvements in social communication.

Very early interventions for autism spectrum disorders (ASDs) have the potential to improve long-term outcomes by targeting emotion regulation, social learning and social communication. However, treatment studies currently rely upon long-term measures that are often far removed from the underlying targets of treatment and that are rather insensitive to short-term treatment effects. Measuring short-term outcomes would improve treatment research by speeding discovery and validation of early interventions, but such an approach is currently limited by diagnostic tools that are insensitive to small changes in behavior.

Individuals with autism spectrum disorder (ASD) have difficulties engaging in social interactions, including problems making eye contact with other people and sharing attention with others about objects in their environment (joint attention). Many interventions aim to allow individuals to more effectively use gaze during social interactions. Currently, there is a shortage of objective, quick and reliable measurements that can detect changes in social communication behaviors. Without good measures to capture change, it is almost impossible to determine if a treatment is effective or is helping to ameliorate ASD symptoms. In addition, measures that are used to determine change are often time intensive, making them impractical to use in many clinical settings.

Eye-tracking is a well-established research tool that can be used to study social cognition in individuals with autism spectrum disorder (ASD). Previous work at the Yale Child Study Center has shown that eye-tracking techniques are robust measures of atypical social-information processing across the lifespan in individuals with ASD.