Gender Disparities in Medical Student Research Awards: A 13-Year Study From the Yale School of Medicine

Acad Med. 2018 Jun;93(6):911-919. doi: 10.1097/ACM.0000000000002052.

Abstract

Purpose: The Liaison Committee on Medical Education mandates instruction in research conduct, and many U.S. medical schools require students to complete a research project. All Yale School of Medicine (YSM) graduating students submit a research thesis, and ~5% are awarded highest honors. Gender disparities exist in areas related to physician research productivity, including academic rank, research funding, and publications. The authors asked whether gender disparities exist for medical student research.

Method: The authors conducted a retrospective review of 1,120 theses submitted by graduating medical students from 2003 to 2015 at YSM and collected data on gender, mentoring, research type, sponsoring department, and other characteristics. Multivariate logistic regression modeling examined gender differences in medical student research awards.

Results: Women authored 50.9% of theses, but earned only 30.9% of highest honors awards (OR 0.41; 95% CI: 0.23, 0.74). Among factors associated with increased receipt of highest honors that differed by gender, men were more likely than women to work with a mentor with a history of three or more thesis honorees, take a fifth year of study, secure competitive research funding, undertake an MD-master of health science degree, and conduct laboratory research (all P < .001). After adjustment for these factors, and for underrepresented in medicine status and sponsoring department, women remained less likely to receive highest honors (OR 0.51; 95% CI: 0.27, 0.98).

Conclusions: Women YSM students were less likely to receive highest honors for medical research. Gender disparities in postgraduate biomedical research success may start during undergraduate medical education.

MeSH terms

  • Adult
  • Awards and Prizes*
  • Biomedical Research / statistics & numerical data*
  • Education, Medical, Undergraduate / statistics & numerical data*
  • Female
  • Humans
  • Logistic Models
  • Male
  • Retrospective Studies
  • Schools, Medical
  • Sexism / statistics & numerical data*
  • Students, Medical / statistics & numerical data*
  • United States
  • Young Adult