Research Review
A majority of first-year medical students at a single medical school who were surveyed regarding race and social class preferences had scores consistent with an unconscious preference toward white people and upper social class, although when presented with various clinical scenarios, these biases were not associated with the students' clinical assessments or decision making, according to a study in The Journal of the American Medical Association. Race and socioeconomic status are predictors of worse health outcomes in the United States. "Disparities may be related to where patients seek care, available resources, and the types of training physicians receive. Unconscious or implicit bias among physicians has recently been suggested as another important factor contributing to racial disparities in healthcare," according to background information in the article. "The presence of unconscious race and social class bias and its association with clinical assessments or decision making among medical students is unknown." The authors add that a better understanding of the way biases may be generated or reinforced during medical education and training may enable the design of interventions to address disparities in healthcare. Adil H. Haider, MD, MPH, of the Johns Hopkins School of Medicine in Baltimore, and colleagues conducted a study to estimate the presence or absence of unconscious race and social class bias among first-year medical students and investigated the association of these biases with their clinical assessments. The study included a secure Web-based survey administered to 211 medical students entering classes at Johns Hopkins School of Medicine in August 2009 and August 2010. The survey included the Implicit Association Test (IAT) to assess unconscious preferences, direct questions regarding students' explicit race and social class preferences, and eight clinical assessment vignettes, focused on pain assessment, informed consent, patient reliability and patient trust. Analyses were conducted to determine whether responses to the vignettes were associated with unconscious race or social class preferences. The researchers found that among the 202 students who completed the survey, race IAT responses were consistent with no implicit preference in 34 (17%), a white preference in 140 (69%), and a black preference in 28 (14%) of the students. Social class IAT responses were consistent with an implicit upper class preference in 174 (86%), no preference in 22 (11%), and a lower-class preference in 6 (3%). The authors wrote that for almost all vignettes, participant responses were not associated with the race of the patient they were randomly assigned. "There were no significant associations between explicit preferences and responses on the clinical vignettes on multivariable analysis," the authors wrote. "...Analyses for all vignettes found no significant relationship between implicit biases and clinical assessments. "Our study raises the question of why the decision-making processes of first-year medical students do not correlate with their implicit biases in the same way that may occur among more experienced physicians. Younger students may have been more exposed to educational curricula focused on cultural competency, translating to improved awareness and management of implicit bias. Naive students who have not been exposed to the rigors of medical training might not be influenced by implicit preferences. It has been recommended that medical education curricula focus on integrating cross-cultural education to reduce disparities; however, students have noted the existence of a 'hidden curriculum' in which what is taught about bias in the classroom differs starkly from in-hospital training experiences." The authors conclude that further studies are needed to have a better understanding of whether implicit preferences are associated with clinical assessments and whether experiences during medical training influence social or racial bias in decision making. "If this occurs, medical training could be an effective intervention point to decrease implicit biases and possibly mitigate physician-driven healthcare disparities." — Source: American Medical Association |