Transdisciplinary Perspectives on Precision Medicine

Health Equity. 2021 May 13;5(1):288-298. doi: 10.1089/heq.2020.0131. eCollection 2021.

Abstract

Purpose: The Precision Medicine Health Disparities Collaborative fosters collaboration between researchers with diverse backgrounds in precision medicine and health disparities research, to include training at the interface between genomics and health disparities. Understanding how perceptions about precision medicine differ by background may inform activities to better understand such differences. Methods: We conducted a cross-sectional survey of Center members and beyond. Data were collected on categories of educational background, current activities, and level of agreement with 20 statements related to genomics and health disparities. Respondents categorized their background and activities as social/behavioral, genetics, both, or neither. Fisher's exact test was used to assess levels of agreement in response to each statement. Statistically significant associations were further analyzed using ordinal logistic regression adjusting for age, self-identified race/ethnicity, and gender. Results: Of 130 respondents, 50 (38%) identified educational backgrounds and current activities as social-behavioral or genomic 55 (42%). Respondents differed by educational background on the statement Lifestyle and other life experiences influence how genes impact disease risk (p=0.0009). Respondents also differed by current activities on the statement Reducing disparities in access to health care will make precision medicine more effective (p=0.0008), and on Racism and discrimination make me concerned about how genetic test results will be used (p=0.0011). Conclusions: Respondents who differed on prior education and current activities, whether social behavioral science or human genomics, were associated with different perceptions regarding precision medicine and health disparities. These results identify potential barriers and opportunities to strengthen transdisciplinary collaboration.

Keywords: beliefs; genomics; health disparities; knowledge; social-behavioral.