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Can a Novel Telemedicine Tool Reduce Disparities Related to the Identification of Preschool Children With Autism?

Vanderbilt University Medical Center · 2022
ClinicalTrials.gov · Datasets · License: Public Domain · 2022
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autismautism-spectrum-disordernapreschooltelehealth
Families seeking evaluation for autism spectrum disorder (ASD) often face barriers such as low availability of specialists, lengthy waitlists, and long distances to tertiary care diagnostic centers. This is especially true for children from traditionally underserved groups and communities. Without innovative approaches for enhanced identification of ASD, families and clinicians will continue to struggle with accessing and providing care. Telemedicine offers tremendous potential for addressing this need, but there are few psychometrically sound, validated tools that can be administered remotely, via telehealth platforms. This team of investigators developed and conducted a preliminary evaluation of a novel parent-administered, clinician-guided tele-diagnostic tool, the TAP (TELE-ASD-PEDS), designed specifically for direct-to-home and community clinic use with toddlers. Remote administration of the TAP yielded a very high level of agreement with blinded comprehensive evaluation regarding ASD risk classification. Subsequently, the unanticipated broad dissemination of the TAP during COVID-19 demonstrated its value for traditionally underserved groups, spanning broad geographies. Although promising, this work was limited by its specific focus on toddlers with ASD concerns. A telemedicine tool designed for the unique context and population of preschool-aged children referred for diagnostic assessment could have tremendous value in terms of both accurate identification as well as family engagement with service. In the current work, the investigators will now evaluate the performance, usability, and utility of the TAP-Preschool, a new telemedicine tool for ASD risk assessment in preschoolers, through a clinical trial. The TAP-Preschool was developed through a computationally informed co-production in which the targeted population were recruited as active partners in designing the tool. The investigators will gather critical data not only regarding its structure and accuracy
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