Search for: All records

IntroductionIn spite of rapid advances in evidence-based treatments for attention deficit hyperactivity disorder (ADHD), community access to rigorous gold-standard diagnostic assessments has lagged far behind due to barriers such as the costs and limited availability of comprehensive diagnostic evaluations. Digital assessment of attention and behavior has the potential to lead to scalable approaches that could be used to screen large numbers of children and/or increase access to high-quality, scalable diagnostic evaluations, especially if designed using user-centered participatory and ability-based frameworks. Current research on assessment has begun to take a user-centered approach by actively involving participants to ensure the development of assessments that meet the needs of users (e.g., clinicians, teachers, patients). MethodsThe objective of this mapping review was to identify and categorize digital mental health assessments designed to aid in the initial diagnosis of ADHD as well as ongoing monitoring of symptoms following diagnosis. ResultsResults suggested that the assessment tools currently described in the literature target both cognition and motor behaviors. These assessments were conducted using a variety of technological platforms, including telemedicine, wearables/sensors, the web, virtual reality, serious games, robots, and computer applications/software. DiscussionAlthough it is evident that there is growing interest in the design of digital assessment tools, research involving tools with the potential for widespread deployment is still in the early stages of development. As these and other tools are developed and evaluated, it is critical that researchers engage patients and key stakeholders early in the design process. 

Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects data on these interactions. We conducted a deployment study with 83 Mexican children who played Feel and Touch to capture their interactions with the game. Our analysis, comparing touch interactions between children with ASD and neurotypical (NT) peers, uncovered three digital markers based on phone tilt and touch patterns that distinguish the two groups. Additionally, we demonstrated the ability of a machine learning model to accurately classify these interactions between ASD and NT children. Our findings discuss the implications in terms of accessibility and ubiquity, as well as the possibilities for the development of digital markers and their application in pervasive computing for healthcare. 

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition that needs an assessment of inattention, hyperactivity, and impulsiveness symptoms. Particularly in young children, hyperactivity-impulsivity stands out as a primary concern. However, those behaviors may or may not be evidenced when a child is in a small room, one-on-one with a single adult. Therefore, Ambient intelligence technology that supports data collection in a natural setting paired with expert human decision-making can potentially improve the quality of assessments. In this paper, we conduct a literature review and analysis to align ADHD assessment criteria with potential sensor technologies to collect behavior data, followed by design sessions proposing personas and scenarios to envision potential solutions.