Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

Hoffman, Kelly M.; Trawalter, Sophie; Axt, Jordan R.; Oliver, M. Norman

doi:10.1073/pnas.1516047113

Cited by 2,486Race, Genetics, and SocietySocial and Intergroup PsychologyRacial and Ethnic Identity Research

Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

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Hoffman, Kelly M., Trawalter, Sophie, Axt, Jordan R., Oliver, M. Norman·2016·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.1516047113PMC PMC4843483

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Abstract

Significance: The present work examines beliefs associated with racial bias in pain management, a critical health care domain with well-documented racial disparities. Specifically, this work reveals that a substantial number of white laypeople and medical students and residents hold false beliefs about biological differences between blacks and whites and demonstrates that these beliefs predict racial bias in pain perception and treatment recommendation accuracy. It also provides the first evidence that racial bias in pain perception is associated with racial bias in pain treatment recommendations. Taken together, this work provides evidence that false beliefs about biological differences between blacks and whites continue to shape the way we perceive and treat black people—they are associated with racial disparities in pain assessment and treatment recommendations.

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A substantial minority of medical students and residents report false beliefs about biological differences between racial groups.
“a substantial minority of medical students and residents report false beliefs about biological differences between racial groups—such as Black people having thicker skin than White people.23”
From Challenging Race-Based Medicine Through Historical Education About the Social Construction of Race (2023) · cites this paper as [23]
Study 2 reports that about 50% of its medical-student and resident participants considered at least one false belief possibly, probably, or definitely true. The paper describes this as a sample of white medical students and residents, so the citing sentence omits a population qualifier. The paper also gives the thicker-skin belief as an example. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Without accounting for existing health disparities, generative AI systems could erroneously recommend treatments for different patients.
“Without this consideration, generative AI systems could erroneously recommend treatments for different patients99.”
From Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare (2023) · cites this paper as [99]

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Authors: Hoffman, K. M., Trawalter, S., Axt, J. R., & Oliver, M. N.
Affiliations: University of Virginia (US)
Corresponding author: Hoffman, Kelly M.
ORCID: Hoffman, Kelly M.
Trawalter, Sophie
Axt, Jordan R.
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2016-04-04
Volume: 113
Issue: 16
Pages: 4296-4301
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.1516047113
PMC: PMC4843483
OpenAlex: W2318723339
Cited by: 2,486
References: 44
Citations by year: 2026: 201 · 2025: 286 · 2024: 365 · 2023: 456 · 2022: 363 · 2021: 357 · 2020: 211 · 2019: 104 · 2018: 74 · 2017: 46 · 2016: 19 · 2015: 1 · 2014: 1
FWCI: 64.78
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Proceedings of the National Academy of Sciences (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
Keywords: racial bias, pain assessment, undertreatment of pain, racial disparities in health care, false belief, medical students, medical residents, treatment guidelines, African Americans
MeSH terms: Adult, Black or African American, Culture, Female, Humans, Male, Pain, Pain Measurement, White People, Pain Management, Racism

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Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

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