Emotional face recognition in male adolescents with autism spectrum disorder or disruptive behavior disorder: an eye‑tracking study

 Emotional face recognition in male adolescents with autism spectrum disorder or disruptive behavior disorder: an eye‑tracking study

Abstract
Autism Spectrum Disorder (ASD), Oppositional Defiant Disorder (ODD), and Conduct Disorder (CD) are often associated with emotion recognition difficulties. This is the first eye-tracking study to examine emotional face recognition (i.e., gazing behavior) in a direct comparison of male adolescents with Autism Spectrum Disorder or Oppositional Defiant Disorder/ Conduct Disorder, and typically developing (TD) individuals. We also investigate the role of psychopathic traits, callous– unemotional (CU) traits, and subtypes of aggressive behavior in emotional face recognition. A total of 122 male adolescents (N = 50 ASD, N = 44 ODD/CD, and N = 28 TD) aged 12–19 years (M = 15.4 years, SD= 1.9) were included in the current study for the eye-tracking experiment. Participants were presented with neutral and emotional faces using a Tobii 1750 eye-tracking monitor to record gaze behavior. Our main dependent eye-tracking variables were: (1) fixation duration to the eyes of a face and (2) time to the first fixation to the eyes. Since distributions of eye-tracking variables were not completely Gaussian, non-parametric tests were chosen to investigate gaze behavior across the diagnostic groups with Autism Spectrum Disorder, Oppositional Defiant Disorder/Conduct Disorder, and Typically Developing individuals. Furthermore, we used Spearman correlations to investigate the links with psychopathy, callous, and unemotional traits and subtypes of aggression as assessed by questionnaires. The relative total fixation duration to the eyes was decreased in both the Autism Spectrum
Disorder group and the Oppositional Defiant Disorder/Conduct Disorder group for several emotional expressions. In both the Autism Spectrum Disorder and the Oppositional Defiant Disorder/Conduct Disorder group, increased time to first fixation on the eyes of fearful faces only was nominally significant. The time to first fixation on the eyes was nominally correlated with psychopathic traits and proactive aggression. The current findings do not support strong claims for differential cross-disorder
eye-gazing deficits and for a role of shared underlying psychopathic traits, callous–unemotional traits, and aggression subtypes. Our data provide valuable and novel insights into gaze timing distributions when looking at the eyes of a fearful face.

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Technology use as a support tool by secondary students with autism

 Technology use as a support tool by secondary students with autism

Abstract
The purpose of this study was to examine how secondary students with autism spectrum disorder use technology in supportive ways. In this self-report survey study, 472 adolescents with autism spectrum disorder enrolled in high school described the forms of technology they use and purposes for which they use it. Students reported the benefits as well as barriers to technology use at school. They reported using technology in school and home settings in a variety of supportive ways such as increasing their independence, reducing their anxiety, and increasing their social opportunities. Findings suggest that practitioners may benefit from learning how to integrate technology as an instructional and support
tool for their students with autism spectrum disorder. Recommendations for future research are provided.

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Automatic emotion and attention analysis of young children at home: a ResearchKit autism feasibility study

 Automatic emotion and attention analysis of young children at home: a ResearchKit autism feasibility study

Current tools for objectively measuring young children’s observed behaviors are expensive, time-consuming, and require extensive training and professional administration. The lack of scalable, reliable, and validated tools impacts access to evidence-based knowledge and limits our capacity to collect population-level data in non-clinical settings. To address this gap, we developed mobile technology to collect videos of young children while they watched movies designed to elicit autism-related behaviors and then used automatic behavioral coding of these videos to quantify children’s emotions and behaviors. We present results from our iPhone study Autism & Beyond, built on ResearchKit’s open-source platform. The entire study—from an e-Consent process to stimuli presentation and data collection—was conducted within an iPhone-based app available in the Apple Store. Over 1 year, 1756 families with children aged 12–72 months old participated in the study, completing 5618 caregiver-reported surveys and uploading 4441 videos recorded in the child’s natural settings. Usable data were collected on 87.6% of the uploaded videos. Automatic coding identified significant differences in emotion and attention by age, sex, and autism risk status. This study demonstrates the acceptability of an app-based tool to caregivers, their willingness to upload videos of their children, the feasibility of caregiver-collected data in the home, and the application of automatic behavioral encoding to quantify emotions and attention variables that are clinically meaningful and may be refined to screen children for autism and developmental disorders outside of

clinical settings. This technology has the potential to transform how we screen and monitor children’s development. CLICK HERE FOR FULL PDF

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