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

Isabella Hernandez; Velia Nuñez; Lorena Reynaga; Kennedy Stewart; Ixel Hernandez-Castro; Luis E Maldonado; Karina Corona; Max Aung; Emily A Knapp; Garrett Fuselier; Christian Douglas; Carmen Velez Vega; Elissa Faro; Rachel Morello Frosch; Johnnye Lewis; Lisa A Croen; Anne Lang Dunlop; Jody Ganiban; Kate Keenan; Theresa Bastain; Environmental influences on Child Health Outcomes

doi:10.1186/s12889-025-25038-4

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

Journal article

Open access

Peer reviewed

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

Isabella Hernandez, Velia Nuñez, Lorena Reynaga, Kennedy Stewart, Ixel Hernandez-Castro, Luis E Maldonado, Karina Corona, Max Aung, Emily A Knapp, Garrett Fuselier, …

BMC public health, Vol.25(1), 3708

10/31/2025

DOI: 10.1186/s12889-025-25038-4

PMCID: PMC12577174

PMID: 41174740

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Abstract

Background Questionnaires for research that involve diverse populations require inclusive language. There are few guidelines to assist researchers in minimizing social and cultural biases in data collection materials; such biases can result in harm and negatively impact data integrity. Methods We describe an approach to evaluating language in data collection forms reflecting racial, ethnic, heteronormative, and gender bias using the Environmental influences on Child Health Outcomes (ECHO)-wide Cohort Study (EWC) as a case study. The 245 data collection forms were used by 69 cohorts in the first seven years of the (ECHO)-wide Cohort Study (EWC). A diverse panel of reviewers (n = 5) rated all forms; each form also was rated by a second student. Items identified as reflecting bias were coded as to the specificity of the bias using nine categories (e.g., racial bias, heteronormative assumptions) following whole panel discussion. We provide recommendations for conducting inclusive research to the scientific community. Results Thirty-six percent (n = 88) of the data collection forms were identified as containing biased language. In total, 137 instances of bias were recorded, eight instances of racial or ethnic bias, 56 instances of bias related to sex, gender identity and sexual orientation and 73 instances of bias related to universal assumptions. Seventy-three percent (n = 64) of forms with biased language are validated measures. The review culminated in recommended revisions to forms used by ECHO and the general scientific community. Conclusion 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.

Cohort Studies

Ethnicity - statistics & numerical data

Female

Humans

Language

Male

Racial Groups

Racism

Sexism

Surveys and Questionnaires - standards

Details

Title: Subtitle: Non-inclusive language in human subjects questionnaires: addressing racial, ethnic, heteronormative, and gender bias
Creators: Isabella Hernandez - University of Southern California
Velia Nuñez - California State University, Northridge
Lorena Reynaga - California State University, Northridge
Kennedy Stewart - California State University, Northridge
Ixel Hernandez-Castro - University of Southern California
Luis E Maldonado - University of Southern California
Karina Corona - University of Southern California
Max Aung - University of Southern California
Emily A Knapp - Johns Hopkins University
Garrett Fuselier - Johns Hopkins University
Christian Douglas - RTI International
Carmen Velez Vega - University of Puerto Rico System
Elissa Faro - University of Iowa
Rachel Morello Frosch - University of California, Berkeley
Johnnye Lewis - University of New Mexico
Lisa A Croen - Kaiser Permanente
Anne Lang Dunlop - Emory University
Jody Ganiban - George Washington University
Kate Keenan - University of Chicago
Theresa Bastain - University of Southern California
Environmental influences on Child Health Outcomes
Resource Type: Journal article
Publication Details: BMC public health, Vol.25(1), 3708
DOI: 10.1186/s12889-025-25038-4
PMID: 41174740
PMCID: PMC12577174
NLM abbreviation: BMC Public Health
ISSN: 1471-2458
eISSN: 1471-2458
Publisher: BioMed Central
Grant note: UH3OD023344 / NIH Office of the Director UH3OD023251 / NIH Office of the Director UH3OD023389 / NIH Office of the Director UH3OD023287 / NIH Office of the Director U24OD023382 / NIH Office of the Director UH3OD023289 / NIH Office of the Director UH3OD023244 / NIH Office of the Director UH3OD023318 / NIH Office of the Director UH3OD023320 / NIH Office of the Director UH3OD023272 / NIH Office of the Director
Language: English
Date published: 10/31/2025
Academic Unit: General Internal Medicine; Internal Medicine
Record Identifier: 9985024257102771

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