Differences in Trainee Evaluations of Faculty by Rater and Ratee Gender
Michael J. Cullen, You Zhou, Paul R. Sackett, Taj Mustapha, Jessica Hane, Susan M. Culican
Abstract
PURPOSE: To examine whether gender differences exist in medical trainees' (residents' and fellows') evaluations of faculty at a number of clinical departments. METHOD: The authors conducted a single-institution (University of Minnesota Medical School) retrospective cohort analysis of 5,071 trainee evaluations of 447 faculty (for which trainee and faculty gender information was available) completed between July 1, 2019, and June 30, 2022. The authors developed and employed a 17-item measure of clinical teaching effectiveness, with 4 dimensions: overall teaching effectiveness, role modeling, facilitating knowledge acquisition, and teaching procedures. Using both between- and within-subject samples, they conducted analyses to examine gender differences among the trainees making ratings (rater effects), the faculty receiving ratings (ratee effects), and whether faculty ratings differed by trainee gender (interaction effects). RESULTS: There was a statistically significant rater effect for the overall teaching effectiveness and facilitating knowledge acquisition dimensions (B = -0.28 and -0.14, 95% CI: [-0.35, -0.21] and [-0.20, -0.09], respectively, P < .001, medium corrected effect sizes between -0.34 and -0.54); female trainees rated male and female faculty lower than male trainees on both dimensions. There also was a statistically significant ratee effect for the overall teaching effectiveness and role modeling dimensions (B = -0.09 and -0.08, 95% CI: [-0.16, -0.02] and [-0.13, -0.04], P = .01 and < .001, respectively, small to medium corrected effect sizes between -0.16 and -0.44); female faculty were rated lower than male faculty on both dimensions. There was not a statistically significant interaction effect. CONCLUSIONS: Female trainees rated faculty lower than male trainees and female faculty were rated lower than male faculty on 2 teaching dimensions each. The authors encourage researchers to continue to examine the reasons for the evaluation differences observed and how implicit bias interventions might help to address them.