Non-inclusive language in human subjects questionnaires: addressing racial, ethnic, heteronormative, and gender bias

Adverse health outcomes disproportionately affect marginalized populations. Utilizing culturally and socially conscious research materials that are inclusive of various identities and experiences is necessary to help remediate these disparities. Our review finds compelling evidence of bias in many widely used data collection instruments. Recommendations for conducting more inclusive science are discussed.

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Publication Details

Journal
BMC Public Health
Published
2025-10-31
DOI
https://doi.org/10.1186/s12889-025-25038-4
Primary Topic
Sex and Gender in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-inclusive language in human subjects questionnaires: addressing racial, ethnic, heteronormative, and gender bias

Christian Douglas, Ixel Hernandez‐Castro, Emily A. Knapp, Velia Nuñez et al.
BMC Public Health
Sex and Gender in Healthcare
article

Non-inclusive language in human subjects questionnaires: addressing racial, ethnic, heteronormative, and gender bias

Christian Douglas, Ixel Hernandez‐Castro, Emily A. Knapp, Velia Nuñez, Vincent Breton, Judy L. Aschner, Kate E. Keenan, Luis E. Maldonado, A. J. Parsons, Lorena Reynaga, Dale R. Sumner, Lisa Croen, Garrett Fuselier, Mark A. Elliott, Max T. Aung, Helen A. Weiss, Jody M. Ganiban, Theresa M. Bastain, Rachel A. Morello-Frosch, Elissa Z. Faro, Isabella Hernandez, Kath Wright, Johnnye Lewis, Anne Lang Dunlop, Stanford, Karina Corona, O’Connor, Natalia Duarte, Kennedy Stewart, Carmen Vélez Vega, O’Shea, Du, Kannan, Fennell, Teitelbaum, Alshawabkeh, Camargo, Dabelea, Deoni, Dunlop, Ferrara, Gern, Hertz-Picciotto, Hipwell, Karagas, Karr, Lester, Leve, MacKenzie, McEvoy, Lyall, Oken, Kerver, Herbstman, Schantz, Trasande
article en

Abstract

Adverse health outcomes disproportionately affect marginalized populations. Utilizing culturally and socially conscious research materials that are inclusive of various identities and experiences is necessary to help remediate these disparities. Our review finds compelling evidence of bias in many widely used data collection instruments. Recommendations for conducting more inclusive science are discussed.

BMC Public HealthVol. 25(1)
University of Southern California (US), University of Iowa (US), Kaiser Permanente (US), Johns Hopkins University (US), Emory University (US), California State University, Northridge (US), University of New Mexico (US), RTI International (US), George Washington University (US), University of Puerto Rico System (PR), University of Illinois Chicago (US), University of Chicago (US), University of California, Berkeley (US)
Northwestern University, Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Duke Clinical Research Institute
Openalex Percentile: Top 58%
Sex and Gender in Healthcare
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