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

开发社区响应型移动医疗和人工智能/机器学习：了解华盛顿州西班牙裔社区成员的观点

• 批准号: 10598360
• 负责人: Mary L. Disis
• 金额: $ 30.42万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10598360
• 关键词: Artificial Intelligence; Attention; Chronic; Clinical; Clinical and Translational Science Awards; Communities; Community Developments; Coupled; Development; Discrimination; Education; Ensure; Ethics; Event; Face; Feedback; Focus Groups; Fostering; Future; Geography; Goals; Health; Health Personnel; Health Technology; Healthcare; Hispanic; Individual; Informatics; Infrastructure; Institutes; Institutional Racism; Internet; Language; Life; Machine Learning; Methods; Mobile Health Application; Participant; Patients; Persons; Population; Positioning Attribute; Predictive Analytics; Preventive; Process; Registries; Research; Research Personnel; Resources; Risk; Rural; Symptoms; Technology; Time; Translational Research; Universities; Visual Aid; Washington; Work; barrier to care; base; community center; community engaged research; community engagement; community setting; cost; digital health; evidence base; experience; handheld mobile device; health application; health care availability; health care delivery; health care model; health communication; health disparity; health equity; health inequalities; hispanic community; improved; mHealth; marginalized community; member; mortality; multidisciplinary; patient population; prototype; recruit; rural area; sensor; social culture; technology development; tool; translational health science; translational scientist; urban area; wearable sensor technology

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.

移动健康应用程序（mHealth）和数字健康传感器与人工智能和机器相结合