Racial/Gender Biases in Student Clinical Decision-Making: a Mixed-Method Study of Medical School Attributes Associated with Lower Incidence of Biases. Academic Article uri icon

abstract

  • Accumulating evidence suggests that clinician racial/gender decision-making biases in some instances contribute to health disparities. Previous work has produced evidence of such biases in medical students.To identify contextual attributes in medical schools associated on average with low levels of racial/gender clinical decision-making biases.A mixed-method design using comparison case studies of 15 medical schools selected based on results of a previous survey of student decision-making bias: 7 schools whose students collectively had, and 8 schools whose students had not shown evidence of such biases.Purposively sampled faculty, staff, underrepresented minority medical students, and clinical-level medical students at each school.Quantitative descriptive data and qualitative interview and focus group data assessing 32 school attributes theorized in the literature to be associated with formation of decision-making and biases. We used a mixed-method analytic design with standard qualitative analysis and fuzzy set qualitative comparative analysis.Across the 15 schools, a total of 104 faculty, administrators and staff and 21 students participated in individual interviews, and 196 students participated in 29 focus groups. While no single attribute or group of attributes distinguished the two clusters of schools, analysis showed some contextual attributes were seen more commonly in schools whose students had not demonstrated biases: longitudinal reflective small group sessions; non-accusatory approach to training in diversity; longitudinal, integrated diversity curriculum; admissions priorities and action steps toward a diverse student body; and school service orientation to the community.We identified several potentially modifiable elements of the training environment that are more common in schools whose students do not show evidence of racial and gender biases.

publication date

  • December 2018