Gender bias in resident evaluations: Natural language processing and competency evaluation. Issue 12 (30th July 2021) - Andrews, Jane; Chartash, David; Hay, Seonaid
Abstract: Background: Research shows that female trainees experience evaluation penalties for gender non‐conforming behaviour during medical training. Studies of medical education evaluations and performance scores do reflect a gender bias, though studies are of varying methodology and results have not been consistent. Objective: We sought to examine the differences in word use, competency themes and length within written evaluations of internal medicine residents at scale, considering the impact of both faculty and resident gender. We hypothesised that female internal medicine residents receive more negative feedback, and different thematic feedback than male residents. Methods: This study utilised a corpus of 3864 individual responses to positive and negative questions over the course of six years (2012‐2018) within Yale University School of Medicine's internal medicine residency. Researchers developed a sentiment model to assess the valence of evaluation responses. We then used natural language processing (NLP) to evaluate whether female versus male residents received more positive or negative feedback and if that feedback focussed on different Accreditation Council for Graduate Medical Education (ACGME) core competencies based on their gender. Evaluator‐evaluatee gender dyad was analysed to see how it impacted quantity and quality of feedback. Results: We found that female and male residents did not have substantively different numbers of positive or negative comments. While certain competencies were discussed more than others, gender did not seem to influence which competencies were discussed. Neither gender trainee received more written feedback, though female evaluators tended to write longer evaluations. Conclusions: We conclude that when examined at scale, quantitative gender differences are not as prevalent as has been seen in qualitative work. We suggest that further investigation of linguistic phenomena (such as context) is warranted to reconcile this finding with prior work. Abstract : Gender bias was explored in resident evaluations from attendings by analyzing thousands of written evaluations over six years; none was found #NLP #MedEd #medtwitter