Presented By: Danielle Dickey, Texas A&M University School of Medicine
Co-Authors: Gerilyn Boyle, Texas A&M University School of Medicine
Darby Dwyer, Texas A&M University School of Medicine
Jody Ping, Texas A&M University School of Medicine
Uma Reddy, Texas A&M University School of Medicine
Halil Sari, Texas A&M University School of Medicine
Purpose
Clerkship Narratives are written to include in student's final MSPEs. More emphasis is being put on MSPEs as program directors look for ways to identify candidate fit. Gender bias narratives could influence a students ability to match. In the first part of our study presented via poster at IAMSE 2023, we identified that the gender bias calculator used for recommendation letters did not accurately identify gender bias for MSPEs at our institution. We hope to identify words that are used in gender bias ways in MSPEs in order to create an effective way to identify and correct for gender bias in our clerkship narratives.
Methods
We reviewed 1 years' worth of student narratives for the core clerkship rotations which include Family Medicine, Internal Medicine, Surgery, Psychiatry, Pediatrics and Obstetrics and Gynecology. Narratives were deidentified and run through online word counters. This process has identified a full list of words in each narrative. The number of words overall and the number of each word will be used to identify words that are commonly used to identify male versus female. This data will be used to build a gender bias calculator specifically for medical education.
Results
Results are pending completion of the study but total number of words have been totaled for each narrative and overall length of narratives may show bias. Number and type of words are still be analyzed.
Conclusion
This study will help identify specific places and language where bias appears in our narratives so they can be revised to better describe students without gender bias. This data may also be used for tailored faculty development and narrative templates to be created.