Equitable Imagery in the Preclinical Medical School Curriculum: Findings From One Medical School.


PURPOSE: The unequal representation of women and people of color compared with men and whites in medical school textbooks has been well documented, as have health care inequities, and biases-both overt and implicit-by health care providers and in access to care. The authors investigated whether this bias exists in PowerPoint slides used in didactic material for preclinical students at one medical school. METHOD: The authors analyzed 747 "decks" of slides from 33 preclinical courses in the medical school curriculum at the University of Washington School of Medicine in the years spanning 2009 to 2011. The authors coded the human images into various sex- and race-specific classifications and evaluated the distribution of images into these categories. RESULTS: Of the 4,033 images that could be coded by sex, 39.6% (1,595) were female and 60.5% (2,438) were male. Of the 5,230 images that could be coded by race/ethnicity, 78.4% (4,100) were white and 21.6% (1,130) were persons of color. Thus, images of whites and males predominated. CONCLUSIONS: The proportion of images used in didactic courses at one school of medicine is not representative of the U.S. population in terms of race or sex. The authors discuss the potential sources and impact of this bias, make a case for sex and race diversity in didactic imagery, and propose possible avenues for further research and curricular reform in an era when the population is becoming increasingly racially and ethnically diverse.


Martin, Glenna C; Kirgis, Julianne; Sid, Eric; Sabin, Janice A;


  • Audiovisual Aids/ statistics & numerical data
  • Cultural Diversity
  • Curriculum/ statistics & numerical data
  • Education, Medical, Undergraduate/ methods
  • Education, Medical, Undergraduate/ statistics & numerical data
  • Female
  • Humans
  • Male
  • Observer Variation
  • Racism/ statistics & numerical data
  • Schools, Medical/ statistics & numerical data
  • Sexism/ statistics & numerical data
  • Washington

External Links