Interphysician weight bias: A cross-sectional observational survey study to guide implicit bias training in the medical workplace.

Abstract

Implicit bias contributes to both health care disparities and professional limitations, and it exists among physicians. Prior literature has described physician weight bias (WB) toward patients, but little research has investigated interphysician WB. This study describes the prevalence of interphysician implicit WB and investigates the relationships between implicit, explicit, and professional biases. The authors hypothesized that the majority of physicians possess interphysician implicit WB and that the degree of implicit bias has a direct relationship with explicit and professional WB. In this cross-sectional study, a survey was used to measure interphysician implicit, explicit, and professional WB. It included adaptations of two previously validated measures (the Implicit Association Test and the Crandall Anti-fat Attitudes Questionnaire) and an investigator developed and tested Professional Weight Bias Scale. The survey was distributed electronically via medical society message boards, email lists, and social media groups. A total of 620 physicians and medical students participated. Fifty-eight percent were female, ages ranged from 22 to 83years (mean= 44years), and body mass index (BMI) ranged from 16 to 59 (mean= 26). Descriptive analyses revealed that 87% had some degree of implicit interphysician antifat bias, with 31% and 34% categorized as moderate and severe, respectively. Correlation and multiple regression analyses revealed that male sex, increased age, and decreased BMI were related to increased implicit bias, controlling for all other factors. Furthermore, implicit, explicit, and professional bias all had significant, direct relationships with each other. Our findings highlight the prevalence of interphysician implicit WB; the strong correlations between implicit, explicit, and professional WB; and the potential disparities faced by physicians with obesity. These results may be used to guide implicit bias training for a more inclusive medical workplace.