Assessing Bias Toward a Black or White Simulated Patient with Obesity in a Virtual Reality-Based Genomics Encounter

Abstract

Interpersonal bias based on weight and race is widespread in the clinical setting; it is crucial to investigate how emerging genomics technologies will interact with and influence such biases in the future. The current study uses a virtual reality (VR) simulation to investigate the influence of apparent patient race and provision of genomic information on medical students’ implicit and explicit bias toward a virtual patient with obesity. Eighty-four third- and fourth-year medical students (64% female, 42% White) were randomized to interact with a simulated virtual patient who appeared as Black versus White, and to receive genomic risk information for the patient versus a control report. We assessed biased behavior during the simulated encounter and self-reported attitudes toward the virtual patient. Medical student participants tended to express more negative attitudes toward the White virtual patient than the Black virtual patient (both of whom had obesity) when genomic information was absent from the encounter. When genomic risk information was provided, this more often mitigated bias for the White virtual patient, whereas negative attitudes and bias against the Black virtual patient either remained consistent or increased. These patterns underscore the complexity of intersectional identities in clinical settings. Provision of genomic risk information was enough of a contextual shift to alter attitudes and behavior. This research leverages VR simulation to provide an early look at how emerging genomic technologies may differentially influence bias and stereotyping in clinical encounters.