Multiple Mini Interviews vs Traditional Interviews: Investigating Racial and Socioeconomic Differences in Interview Processes.

Abstract

Aim: The study aims to compare traditional interviews with Multiple Mini Interviews (MMIs) to assess their reliability in evaluating applicants across racial and socioeconomic backgrounds.

Background: In the 2019-2020 admissions cycle, The University of Texas Medical Branch John Sealy School of Medicine (JSSOM) admissions committee observed inconsistencies in interview scoring, topics discussed during interviews, and interviewer comments using an unstructured interview format. Additionally, the recent Supreme Court decisions in Students for Fair Admissions, Inc. (SFFA) v. the University of North Carolina and SFFA v. President & Fellows of Harvard College, which ended race-conscious admissions, or affirmative action, and upheld holistic admissions practices, encouraged medical school admissions committee to reevaluate their approach to admissions.

Methods: Data from six admissions cycles (2018-2022), totaling 5799 interviewees, were analyzed to assess potential biases and the effectiveness of the admissions process. Spearman correlation examined relationships between Casper scores and both traditional interview and MMI outcomes. T-tests and Cohen's d explored demographic differences across URM, African American, Hispanic, and disadvantaged applicants in interview and academic metrics to evaluate fairness.

Results: When comparing MMIs and traditional interviews, both appear equal in reducing group differences (Underrepresented in Medicine(URM) versus non-URM, African American to non-URM, Hispanic to non-URM, and disadvantaged to non-disadvantaged). MMIs decreased demographic differences compared with traditional interviews for African-American candidates and slightly increased for URM, Hispanic, and disadvantaged candidates, but the effect size was small.

Conclusion: Future work includes conducting rigorous data analysis to better assess the MMI's utility, exploring the correlations between MMI scores, clinical evaluations, and objective structured clinical examination (OSCE) results. This multifaceted approach will provide a comprehensive view of how MMI performance aligns with real-world clinical assessments and standardized evaluation metrics, offering valuable insights into its effectiveness as a predictor of future medical proficiency.