Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study

Obesity (Silver Spring). 2014 Apr;22(4):1201-8. doi: 10.1002/oby.20687. Epub 2014 Jan 9.

Abstract

Objective: To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students.

Methods: A web-based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti-fat attitudes test.

Results: A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice.

Conclusions: Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Age Factors
  • Attitude of Health Personnel*
  • Bias
  • Body Weight*
  • Continental Population Groups
  • Data Collection
  • Female
  • Health Knowledge, Attitudes, Practice
  • Homosexuality, Female / psychology
  • Homosexuality, Male / psychology
  • Humans
  • Longitudinal Studies
  • Male
  • Minority Groups / psychology
  • Obesity / psychology*
  • Overweight / psychology*
  • Poverty / psychology
  • Regression Analysis
  • Sex Factors
  • Students, Medical / psychology*