Ethnic and gender-based prejudice towards medical doctors? The relationship between physicians’ ethnicity, gender, and ratings on a physician rating website

ABSTRACT

We investigated manifestations of ethnic and gender-based prejudice in a rather understudied high-status environment, that is we studied biased ratings of physicians with a migration background and female physicians. In a preregistered, archival study, we analyzed ratings of more than 140,000 physicians on a German rating website for medical professionals. Results indicate that general practitioners (but not dentists or specialists) with non-German names are rated less favorably than general practitioners with German names. This effect did not vary across regional contexts with varying prosperity and diversity. Our analyses also revealed that female physicians are evaluated less positively than male physicians. Contrary to our assumptions, bias against female physicians was especially strong in medical sub-disciplines that are characterized by a high share of female physicians.

KEYWORDS:

• Ethnicity
• gender
• prejudice
• physician ratings
• multi-level analysis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data described in this article are openly available in the Open Science Framework at https://osf.io/ksb6w/ and https://osf.io/hzvxb.

Open scholarship

This article has earned the Center for Open Science badges for Open Data, Open Materials and Preregistered. The data and materials are openly accessible at https://osf.io/ksb6w/ and https://osf.io/hzvxb.

Supplementary Material

Supplemental data for this article can be accessed on the publisher’s website.

Notes

1. The term persons with a migration background refers to individuals who immigrated to Germany, and individuals with at least one parent that immigrated to Germany or who was born as a foreigner in Germany (Statistisches Bundesamt, 2021).

2. Please note, however, that research indicates that women show a higher burnout prevalence (Templeton et al., 2019), perceive more challenges during surgical training (Myers et al., 2019), and receive worse feedback during residencies from attending physicians (Mueller et al., 2017).

3. Please note that in the preregistration we outlined that we will use the full data set for all analyses and that analyses will be re-run with data of physicians with a minimum amount of user-ratings for the sake of robustness checks. At a later stage of the project we then decided to focus on the reduced data set limited to profiles of physicians with at least three ratings. Please also note that in the full data sets no gender-differences were found for all broader medical fields, general practitioners, and specialists.

4. Results for full data set (N = 103,633, k = 32 sub-disciplines; average cluster size = 3239.47) can be found in the supplemental material. Sample sizes were lower because information on sub-disciplines was unavailable for some physicians.

Additional information

Notes on contributors

Mathias Kauff

Mathias Kauff is a professor for social psychology at the Medical School Hamburg, Germany. His research interests include intergroup relations, prejudice and discrimination, attitudes towards diversity, and intergroup contact.

Julian Anslinger

Julian Anslinger is a social psychologist researching at the Interdisciplinary Research Centre for Technology, Work and Culture (IFZ) in Graz, Austria. Dr. Anslinger works on gender in science and technology, responsible artificial intelligence, biases, and sexual harassment.

Oliver Christ

Oliver Christ is a professor for psychological methods and evaluation at the FernUniversität in Hagen, Germany. In his research, he focuses on intergroup relations, especially on the central question on how to bring different groups into contact and thus, how to reduce conflict between groups and to improve intergroup relations.

Moritz Niemann

Moritz Niemann is an educational researcher at the Medical School Hamburg, Germany. His research interests include motivation, self-regulated learning, and process measures of affect during learning.

Michaela Geierhos

Michaela Geierhos is a professor for Data Science at the Universität der Bundeswehr München, Germany. She combines expertise from the fields of computer science, computational linguistics, and economics to address current and future-oriented research questions in the areas of semantic information processing and knowledge & data engineering.

Lars Huster

Lars Huster is a Senior Doctor of Dental Science at the Dental Clinic Marburg, Germany. His research focus includes competence-oriented teaching, Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM), craniomandibular dysfunction and rehabilitation of toothless jaws.