ArticleAEM education and training2025
Differences in language used to describe racial groups in emergency medicine standardized letter of evaluation.
Article in AEM education and training, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Language Differences by Race in the Narrative Section of the Emergency Medicine Standardized Letter of Evaluation.The western journal of emergency medicine · 2025Article
- Article
- Differences in language used to describe racial groups in emergency medicine standardized letter of evaluation.AEM education and training · 2025Article
- Intersectional Bias and Coded Language in Emergency-Medicine Evaluations: A Response to Gonzalez et al.AEM education and training · 2025Article
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: According to program directors in emergency medicine (EM), the standardized letter of evaluation (SLOE) is the most important component of the EM residency application. Understanding possible biases in SLOE language is critical for an equitable review process. Past studies have shown differences in the way medical students are described in narrative evaluations by race and gender; however, research on SLOE narratives has been limited to gender. This study seeks to evaluate narrative linguistic differences in applicant SLOEs by race. Methods: This is a narrative analysis of all U.S. MD and DO SLOEs from applicants to the study institution in the 2022 application cycle. We used Linguistic Inquiry and Word Count (LIWC) to complete two analyses. Analysis 1 used frequency of words within 19 categories to evaluate differences between underrepresented minorities in medicine (URiM) and non-URiM applicants and within racial subgroups. Analysis 2 used LIWC to evaluate dichotomous use of 21 key words in these same groups. Linear mixed models were performed for each of the outcomes to evaluate for associations between URiM/non-URiM status or racial subgroup and each outcome. Results: Of the 809 unique applicants, 18.3% identified as URiM, 57.5% identified as White, 17.4% identified as Asian, 10% identified as Latinx, and 6.3% identified as Black. The analysis revealed applicants who are Black contained on average 0.537 (SE 0.154, Bonferroni-adjusted Conclusion: Applicants who were URiM or Black were more likely to be described with communal words than their peers. URiM applicants had twice the amount of empathic words in their SLOEs when compared to their non-URiM peers; however, this finding did not meet statistical significance (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.