Race and Gender Bias in Internal Medicine Program Director Letters of Recommendation

Author:

Zhang Neil1,Blissett Sarah2,Anderson David3,O'Sullivan Patricia4,Qasim Atif5

Affiliation:

1. Neil Zhang, MD, MS, is Clinical Instructor, Department of Medicine, University of California, San Francisco

2. Sarah Blissett, MD, MHPE, is Assistant Professor, Division of Cardiology, Department of Medicine, and Centre for Education Research and Innovation, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

3. David Anderson, MD, is a Cardiology Fellow, Division of Cardiology, Department of Medicine, University of California, San Francisco

4. Patricia O'Sullivan, EdD, is Professor, School of Medicine, University of California, San Francisco

5. Atif Qasim, MD, MSCE, is Cardiology Fellowship Program Director and Associate Professor, Division of Cardiology, Department of Medicine, University of California, San Francisco

Abstract

ABSTRACT Background While program director (PD) letters of recommendation (LOR) are subject to bias, especially against those underrepresented in medicine, these letters are one of the most important factors in fellowship selection. Bias manifests in LOR in a number of ways, including biased use of agentic and communal terms, doubt raising language, and description of career trajectory. To reduce bias, specialty organizations have recommended standardized PD LOR. Objective This study examined PD LOR for applicants to a cardiology fellowship program to determine the mechanism of how bias is expressed and whether the 2017 Alliance for Academic Internal Medicine (AAIM) guidelines reduce bias. Methods Fifty-six LOR from applicants selected to interview at a cardiology fellowship during the 2019 and 2020 application cycles were selected using convenience sampling. LOR for underrepresented (Black, Latinx, women) and non-underrepresented applicants were analyzed using directed qualitative content analysis. Two coders used an iteratively refined codebook to code the transcripts. Data were analyzed using outputs from these codes, analytical memos were maintained, and themes summarized. Results With AAIM guidelines, there appeared to be reduced use of communal language for underrepresented applicants, which may represent less bias. However, in both LOR adherent and not adherent to the guidelines, underrepresented applicants were still more likely to be described using communal language, doubt raising language, and career trajectory bias. Conclusions PDs used language in a biased way to describe underrepresented applicants in LOR. The AAIM guidelines reduced but did not eliminate this bias. We provide recommendations to PDs and the AAIM on how to continue to work to reduce this bias.

Publisher

Journal of Graduate Medical Education

Subject

General Medicine

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