Unmasking bias and perception of lead surgeons in the operating room: A simulation based study

Am J Surg. 2022 Jan;223(1):58-63. doi: 10.1016/j.amjsurg.2021.07.015. Epub 2021 Jul 23.

Abstract

Background: Perception of a surgeon based on physical attributes in the operating room (OR) environment has not been assessed, which was our primary goal.

Methods: A common OR scenario was simulated using 8 different actors as a lead surgeon with combinations of age (<40 vs. >55), race (white vs. black), and gender (male vs. female). One video scenario with a survey was electronically distributed to surgeons, residents, and OR nurses/staff. The overall rating, assessment, and perception of the lead surgeon were assessed.

Results: Of 974 respondents, 64.5% were females. There were significant differences in the rating and assessment based upon surgeon's age (p = .01) favoring older surgeons. There were significant differences in the assessments of surgeons by the study group (p = .03). The positive assessments as well as perceptions trended highest towards male, older, and white surgeons, especially in the stressful situation.

Conclusion: While perception of gender bias may be widespread, age and race biases may also play a role in the OR. Inter-professional education training for OR teams could be developed to help alleviate such biases.

Keywords: Bias in operating room; Biases in surgery; Operating room culture; Perception of surgeon in operating room.

MeSH terms

  • Adult
  • Ageism / psychology*
  • Ageism / statistics & numerical data
  • Computer Simulation
  • Female
  • Humans
  • Leadership
  • Male
  • Middle Aged
  • Operating Rooms / organization & administration*
  • Operating Rooms / statistics & numerical data
  • Perception
  • Racism / psychology*
  • Racism / statistics & numerical data
  • Sexism / psychology*
  • Sexism / statistics & numerical data
  • Surgeons / organization & administration
  • Surgeons / psychology*
  • Surgeons / statistics & numerical data
  • Surveys and Questionnaires / statistics & numerical data