The Biomedical Engineering and Social Science Training (BEST) Program at UC Irvine.
The Biomedical Engineering and Social Science Training (BEST) program seeks to train researchers to solve problems at the intersection of cardiovascular health, identity (e.g., race, ethnicity, sex, gender, LGBTQ+ status), and technology. We use a team science-based approach to interdisciplinary graduate education to accelerate advances in cardiovascular health equity.
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Our vision is to create a professional technical workforce able to address cardiovascular health inequities in an entirely new way. Whether beginning from a biomedical engineering, behavioral sciences, or psychological sciences background, BEST trainees will receive convergent education and training in card iovascular health and health care, systemic racism and discrimination, social determinants of health, the social ecology ecosystem, and principles of design thinking. This training will incorporate best practices in team science, culturally aware research mentoring, and mentor-mentee relationships, as well as in-depthoral and written communication skills training and practice. In this way, BEST will provide a systems perspective on cardiovascular health, identity, and technology. BEST research questions at the heart of the program will focus on (Theme 1) the psycho-physio-biological root causes of cardiovascular health inequities; (Theme 2) accurate, unbiased, and accessible health technology design and innovation; and (Theme 3) social, behavioral, and economic influences on technology for cardiovascular health care.
To interrogate the root causes of cardiovascular health inequities, this Theme brings biomedical engineering and social sciences perspectives to bear on the (1) the analysis of pre-existing large clinical datasets using data mining and artificial intelligence, (2) the design and implementation of prospective clinical studies, and (3) the development of biophysical models.
In this Theme, BEST fellows will be trained to develop accurate, unbiased, and accessible technologies through convergent biomedical engineering and social sciences research and engagement with communities of color in one of the following ways: (1) Using novel technologies to replace systems with known inaccuracy or bias; (2) Using artificial intelligence to correct systems with known inaccuracy or bias; or (3) improving the likelihood of future adoption and implementation of novel devices technologies.
Theme 3 will use this systems perspective to advance understanding of the constellation of factors that encourage or discourage (1) adoption of new devices and technologies by industry, health care systems, and providers; and (2) individuals’ use of new devices and technologies.