Developing Community-Responsive mHealth and AI/ML: Understanding Perspectives of Hispanic Community Members in Washington State

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Mobile health applications (mHealth) and digital health sensors coupled with artificial intelligence and machine learning (AI/ML) have the potential to become breakthrough technologies and support a holistic, preventive model of healthcare. These technologies allow individuals to integrate their daily life activities with healthcare delivery and are especially promising for patients living with 1 or more chronic conditions. mHealth technologies are key to reaching populations who rely on mobile devices for internet access. They also have the potential to reduce health inequities for those who face barriers to healthcare access because of cost, geography, language, or systemic racism. However, if these technologies are developed without appropriately incorporating the values of those intended to benefit from them, they risk exacerbating rather than alleviating health disparities by amplifying existing structural assumptions in healthcare, resulting in technologies that are unusable, unresponsive, or otherwise not appropriate for the sociocultural context in which people live. Researchers developing mHealth and AI/ML technologies need a robust evidence base about community values to inform technology development, including which health conditions are highest priority and tools to support embedding community values throughout research. This project will build on longstanding relationships that the University of Washington Institute of Translational Health Sciences (ITHS) has developed with Hispanic communities across Washington State. We will examine ethical questions about the potential benefits and burdens of mHealth and AI/ML from the perspective of Hispanic-identifying community members and produce a prototype translational resource for mHealth and AI/ML research and application development. This supplement brings together 2 key goals for ITHS: (1) integrating community stakeholders at all stages of translational research, and (2) developing accessible methods, tools, and education for informatics and machine learning. To advance these goals, we aim to: (1) develop community-facing materials conveying key features of potential mHealth applications; (2) describe perspectives of Hispanic-identifying community members in Washington State about the use of mHealth and AI/ML; and (3) produce a prototype translational resource to guide mHealth and AI/ML researchers in development of community-responsive technologies. This resource can be refined by future research teams, both within the Clinical and Translational Science Award (CTSA) consortium and beyond, and can be used to guide future work across patient populations and clinical scenarios.