Estimating Implicit and Explicit Gender Bias Among Health Care Professionals and Surgeons

Abstract

Importance: The Implicit Association Test (IAT) is a validated tool used to measure implicit biases, which are mental associations shaped by one's environment that influence interactions with others. Direct evidence of implicit gender biases about women in medicine has yet not been reported, but existing evidence is suggestive of subtle or hidden biases that affect women in medicine.

Objectives: To use data from IATs to assess (1) how health care professionals associate men and women with career and family and (2) how surgeons associate men and women with surgery and family medicine.

Design, setting, and participants: This data review and cross-sectional study collected data from January 1, 2006, through December 31, 2017, from self-identified health care professionals taking the Gender-Career IAT hosted by Project Implicit to explore bias among self-identified health care professionals. A novel Gender-Specialty IAT was also tested at a national surgical meeting in October 2017. All health care professionals who completed the Gender-Career IAT were eligible for the first analysis. Surgeons of any age, gender, title, and country of origin at the meeting were eligible to participate in the second analysis. Data were analyzed from January 1, 2018, through March 31, 2019.

Main outcomes and measures: Measure of implicit bias derived from reaction times on the IATs and a measure of explicit bias asked directly to participants.

Results: Almost 1 million IAT records from Project Implicit were reviewed, and 131 surgeons (64.9% men; mean [SD] age, 42.3 [11.5] years) were recruited to complete the Gender-Specialty IAT. Healthcare professionals (n = 42 991; 82.0% women; mean [SD] age, 32.7 [11.8] years) held implicit (mean [SD] D score, 0.41 [0.36]; Cohen d = 1.14) and explicit (mean [SD], 1.43 [1.85]; Cohen d = 0.77) biases associating men with career and women with family. Similarly, surgeons implicitly (mean [SD] D score, 0.28 [0.37]; Cohen d = 0.76) and explicitly (men: mean [SD], 1.27 [0.39]; Cohen d = 0.93; women: mean [SD], 0.73 [0.35]; Cohen d = 0.53) associated men with surgery and women with family medicine. There was broad evidence of consensus across social groups in implicit and explicit biases with one exception. Women in healthcare (mean [SD], 1.43 [1.86]; Cohen d = 0.77) and surgery (mean [SD], 0.73 [0.35]; Cohen d = 0.53) were less likely than men to explicitly associate men with career (B coefficient, -0.10; 95% CI, -0.15 to -0.04; P < .001) and surgery (B coefficient, -0.67; 95% CI, -1.21 to -0.13; P = .001) and women with family and family medicine.

Conclusions and relevance: The main contribution of this work is an estimate of the extent of implicit gender bias within surgery. On both the Gender-Career IAT and the novel Gender-Specialty IAT, respondents had a tendency to associate men with career and surgery and women with family and family medicine. Awareness of the existence of implicit biases is an important first step toward minimizing their potential effect.

Figure 1.. Implicit Association Test (IAT) Standardized D Scores by Participant Gender

For the Gender-Career IAT, implicit measures include 34 662 women and 7624 men; explicit measures, 34 835 women and 7675 men. For the Gender-Specialty IAT, implicit and explicit measures included 45 women and 85 men. Error bars represent SE. Standard errors for the Gender-Career IAT data are so small that they are not visible on the graph.

Figure 2.. Explicit Bias Scores by Participant Gender

Explicit bias scores are calculated as the difference between the responses to 2 self-reported items about participants’ associations of gender with career and family (Gender-Career Implicit Association Test [IAT]) or with surgery and family medicine (Gender-Specialty IAT).