Presentation Type

Oral Presentation

Start Date

4-5-2022 1:30 PM

End Date

4-5-2022 3:00 PM

Subjects

gender identity, disability, disadvantaged background, workforce, health inequities

Other

I'm not sure if this is supposed to be the department in which I am enrolled, or the department that is relevant to this research. I chose the latter.

Advisor

Lisa Marriott

Student Level

Masters

Abstract

Federal strategic plans call for increased diversity within the biomedical workforce. The National Institutes of Health (NIH) defined underrepresented populations in biomedical science (NOT-OD-20-031), though operationalization remains a challenge for training programs. Implementing inclusive demographic measures may help to identify key demographic groups facing barriers to participation and retention in STEM programs and the biomedical workforce. Approaches for measuring demographic variables were sourced from scientific literature and research stakeholders. Gender, race/ethnicity, disability, and disadvantaged background were prioritized for comparison given their focus by NIH, with opportunities for stakeholders to identify additional demographic variables important in their work. Gender minorities, sex minorities, and sexual minorities were largely absent from programs’ demographic practices and warrant greater inclusion. Oregon Health Authority’s Race, Ethnicity, Language, and Disability (REALD) offers a vetted tool for expanding granularity of racial/ethnic data, which can be merged with NIH categories for reporting. Disability can be measured as functional limitations through REALD. Disadvantaged background included several variables that were underreported when verified, including first-generation college student status and rural eligibility. Summaries for operationalizing demographic variables in biomedical research training efforts are described. Inclusive demographics permit the identification of individuals who are being excluded, marginalized, or improperly aggregated, increasing our capacity to address inequities in biomedical research training. As trainees do not enter training programs with equal access, accommodations, or preparation, inclusive demographic measures can help inform a nuanced set of program outcomes, facilitating research on intersectionality, and ultimately supporting the retention of underrepresented students in biomedical research.

Please provide feedback:

https://docs.google.com/forms/d/e/1FAIpQLScNnF9Jm2e-7YA8v57vbECv0H5RwZrYgXjlvkdlaAs0izXymg/viewform?usp=sf_link

Persistent Identifier

https://archives.pdx.edu/ds/psu/37494

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May 4th, 1:30 PM May 4th, 3:00 PM

Inclusive Approaches for Measuring Demographics of Underrepresented Populations in STEM and Biomedical Research Training Programs

Federal strategic plans call for increased diversity within the biomedical workforce. The National Institutes of Health (NIH) defined underrepresented populations in biomedical science (NOT-OD-20-031), though operationalization remains a challenge for training programs. Implementing inclusive demographic measures may help to identify key demographic groups facing barriers to participation and retention in STEM programs and the biomedical workforce. Approaches for measuring demographic variables were sourced from scientific literature and research stakeholders. Gender, race/ethnicity, disability, and disadvantaged background were prioritized for comparison given their focus by NIH, with opportunities for stakeholders to identify additional demographic variables important in their work. Gender minorities, sex minorities, and sexual minorities were largely absent from programs’ demographic practices and warrant greater inclusion. Oregon Health Authority’s Race, Ethnicity, Language, and Disability (REALD) offers a vetted tool for expanding granularity of racial/ethnic data, which can be merged with NIH categories for reporting. Disability can be measured as functional limitations through REALD. Disadvantaged background included several variables that were underreported when verified, including first-generation college student status and rural eligibility. Summaries for operationalizing demographic variables in biomedical research training efforts are described. Inclusive demographics permit the identification of individuals who are being excluded, marginalized, or improperly aggregated, increasing our capacity to address inequities in biomedical research training. As trainees do not enter training programs with equal access, accommodations, or preparation, inclusive demographic measures can help inform a nuanced set of program outcomes, facilitating research on intersectionality, and ultimately supporting the retention of underrepresented students in biomedical research.

Please provide feedback:

https://docs.google.com/forms/d/e/1FAIpQLScNnF9Jm2e-7YA8v57vbECv0H5RwZrYgXjlvkdlaAs0izXymg/viewform?usp=sf_link