The NIH and the private sector have invested millions of dollars into development of mobile technology- based (mHealth) autism screening tools, with the hope that advanced technologies will improve early identification of Autism Spectrum Disorder [ASD]. However, no research to date has assessed how mobile device-based ASD screening will address the problem of racial, ethnic, language, and income disparities in ASD identification. In addition, no current efforts explicitly assess what key mHealth ASD screener adaptations are needed for mHealth autism screeners to be successfully used by minority and low-income families and the professionals who interact with them. In this proposal, we will examine existing mHealth ASD screeners for overall quality and adaptability to ASD health disparities populations, by comparing them to established mHealth standards. We will then perform user testing of key tools with a sample of racial/ethnic minority and low-income families and health and educational providers. We will interview parents, providers, and mHealth ASD screener developers, to understand the challenges of creating and using mHealth ASD screeners in health disparities populations. Finally, we will use the results of this research, and the guidance of a multi- disciplinary expert panel, to develop a set of guidelines for mHealth autism screener usability in ASD disparities populations. We will disseminate these guidelines throughout the autism research and informatics communities. This research will ensure that the next generation of ASD screening tools effectively reduces disparities in ASD identification.
Mobile health (mHealth) autism screening tools may be an innovative means of improving early access to ASD care; however, low-income and minority families may face special challenges using this technology. In this research proposal, we will examine quality features of existing mHealth autism screening tools; collect qualitative and quantitative user data from low-income/minority parents and community providers to understand barriers to use; and conduct qualitative interviews with screener tool developers to understand challenges in developing tools that meet the needs of the underserved. This research will be used to develop guidelines for mHealth autism screening tools that can effectively reduce autism disparities.