OHSU Digital Collections (Oregon Health and Science University)

Science, technology, engineering, and math (STEM) training programs share an overarching goal of enhancing education and support for their students. The desire to understand student impact is shared across disciplines and training levels, which underscores the importance of how student access, engagement, and retention in STEM are measured.This presentation invites students, staff, and faculty to engage in conversations around inclusive demographics and share considerations for improving data science training to younger students

Paris, Stephanie E.

Espinosa, Shanthia N.

Link, Aaron R.

Jones, Adri

Braley, Amanda

Wakim, Nicky

Community-engaged research partnerships for building 
capacity and training in inclusive data science
Paris, S.E., Espinosa, S.N., Raz Link, A., Jones, A., Fu, R., Wakim, N., Jones, J., Braley, A., 
and Marriott, L.K; OHSU-PSU School of Public Health; Oregon Health and Science 
University 
Keywords 
Cross-Sectional Studies; Diversity, Equity, Inclusion; Data Science; Intersectional 
Framework; Data Collection; Qualitative Research; Representation, Demographics
Abstract 
Science, technology, engineering, and math (STEM) training programs share an overarching 
goal of enhancing education and support for their students. The desire to understand 
student impact is shared across disciplines and training levels, which underscores the 
importance of how student access, engagement, and retention in STEM are measured. 
Demographics should be representative of the complexity and intersectionality of student 
identities (National Academies of Sciences, Engineering, and Medicine, 2023; Paris et al., 
2024), with Executive Orders calling for expansion of demographic data collection 
practices to incorporate broader categories of race, ethnicity, religion, income, geography, 
gender identity, sexual orientation, and disability (White House, 2021, 2023). Our recent 
collaborative project with equity-focused researchers and STEM partners defined a set of 
expanded demographics that facilitate inclusive measurement of individual identities and 
their intersections between different demographic factors (Paris et al., 2024), which are 
integrated into informatics platforms (Let’s Get Healthy! and STEM Assessment and 
Reporting Tracker; www.startinstem.org) that deliver tailored educational feedback about 
health and STEM development. In August, 2023, OHSU received a new five-year Science 
Education Partnership Award from the National Institutes of Health’s Office of Data 
Science Strategy to expand data science training for middle and high school students. 
Project Aim
The collaborative project aims to 1) identify considerations for inclusive demographic data 
collection and responsible reporting; 2) establish a training collaborative that aligns 
qualitative research with data science outputs to enhance authentic representation of a 
diverse biomedical workforce; and 3) characterize how demographic data are used to make 
decisions and inform practice. This presentation invites students, staff, and faculty to 
engage in conversations around inclusive demographics and share considerations for 
improving data science training to younger students. 
Symposium on Educational 
Excellence 2024
This project is approved by an overarching Institutional Review Board study entitled “Biomedical 
Workforce Development” (OHSU #22889) that enables cross-sectional and longitudinal research 
with students from elementary school through retirement, representing the full spectrum of 
schooling and career. This presentation will apply considerations from Paris and colleagues (2024) to 
engage in dialogue that builds an interprofessional network of undergraduates, graduate students, 
and professional partners interested in supporting youth training and representation of a diversity of 
identities in STEM. Together, we will establish a communication network that facilitates connection 
with our multidisciplinary partners to accelerate educational scholarship, training, and outreach 
related to inclusive data science. As we continue to identify considerations for capacity and training 
in inclusive demographic data collection and responsible reporting across intersectional 
demographics, we enthusiastically invite fellow researchers, scholars, and colleagues to join our 
efforts and share their unique perspectives to promote diversity, equity, inclusion, and accessibility 
within biomedical workforce development.
Learning Objectives 
At the end of the session, the learner will:
• Identify resources to connect with the research team around equitable data science training.
• Consider ways to enhance authentic representation of diverse student identities in STEM 
education and biomedical science.
• Describe the impact of demographic data on decision-making and practices in STEM education 
programs for middle and high school students.
• Identify transferable research skills associated with inclusive data science training for K-12 
students. 
References
1. Gómez, L. E., & Bernet, P. (2019). Diversity improves performance and outcomes. Journal of the 
National Medical Association, 111(4), 383–392. https://doi.org/10.1016/j.jnma.2019.01.006
2. National Academies of Sciences, Engineering, and Medicine. (2023). Advancing Antiracism, 
Diversity, Equity, and Inclusion in STEMM Organizations: Beyond Broadening Participation. 
Washington, DC: The National Academies Press. https://doi.org/10.17226/26803.
3. Paris, S.E., Dinno, A., Marr, M.C., Raz Link, A., Lentz, B.L., Setthavongsack, A., Espinosa, S.N., 
Shusterman, G., Abel, J., Harrison, K., Hook, J., Alvord, T.W, Richardson, D.M., Chase, K., and 
Marriott, L.K. (2024).  Inclusive approaches for measuring demographics of historically 
underrepresented populations in STEM and biomedical research training programs. Journal of 
STEM Outreach, 7(2), 1-22. https://www.jstemoutreach.org/article/92768-inclusive-
approaches-for-measuring-demographics-of-underrepresented-populations-in-stem-and-
biomedical-research-training-programs
4. White House (2021, June 25). Executive Orders on Diversity, Equity, Inclusion and Accessibility 
( #14035). https://www.whitehouse.gov/briefing-room/presidential-actions/2021/06/25/
executive-order-on-diversity-equity-inclusion-and-accessibility-in-the-federal-workforce/
5. White House (2023, February 16). Executive Order on Further Advancing Racial Equity and 
Support for Underserved Communities Through The Federal Government (#14091). https://
www.whitehouse.gov/briefing-room/presidential-actions/2023/02/16/executive-order-on-
further-advancing-racial-equity-and-support-for-underserved-communities-through-the-
federal-government/


English

Community-engaged research partnerships for building capacity and training in inclusive data science

The aim of this research is to utilize MRF techniques to characterize vascularization differences between healthy pancreas tissue and tumorous tissue. To do this, both healthy volunteers and cancer patients eligible for surgery were scanned using contrast generated by iron nanoparticles (Ferumoxytol), and values for T1, T2 and T2* were extracted from a dictionary fitting. A secondary aim of this project was to analyze the differences between breath hold and free breathing techniques in MRF scans, thus scans were completed with both breath holds and free breathing

Barton, Zachary J.

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Licensed Content Title The Essential Physics of Medical Imaging
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Multi-Parametric MRI Fingerprinting Analysis of
Pancreatic Lesions with Ferumoxytol Contrast for
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Multi-parametric MRI fingerprinting analysis of pancreatic lesions with ferumoxytol contrast for correlation with vascular structure

Bartos, James (Brother)

Tanaka, Augustus M. (1923-2015)

The prevalence of venereal infections in this country, as in others, has long been recognized, but that a large percentage of deaths each year may be laid directly, and a far greater percentage, indirectly, to the various manifestations and complications of these diseases, is not so generally appreciated

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Community-engaged research partnerships for building capacity and training in inclusive data science

Multi-parametric MRI fingerprinting analysis of pancreatic lesions with ferumoxytol contrast for correlation with vascular structure

Venereal diseases as causes of death

3,119

38,149