Research

Interests

My research program sits at the intersection of statistical methodology and applied public-health research. Three overlapping strands:

Cancer disparities & early-onset colorectal cancer. A line of work I’ve been building since my EVMS days, extending through several intramural and extramural grants. I look at how neighborhood characteristics, environmental exposures, and structural barriers shape stage-at-diagnosis and treatment patterns — with particular attention to young-onset cases in underserved populations.

Machine learning in health outcomes. Over the past several years I’ve been applying machine-learning approaches to problems where classical regression struggles: high-dimensional predictors, complex interactions, and data quality issues typical of registry-based and population-based studies. Recent work applies these methods to colorectal cancer outcomes, breast cancer recurrence, and cancer risk prediction across socioeconomic gradients.

Methods for confounding & propensity scores. My doctoral work on propensity-score methods when association is measured by AUC remains active — in subsequent publications I’ve shown that naive propensity-score adjustment can bias the conditional AUC, a subtle but consequential finding for diagnostic-accuracy studies in observational data.

By the numbers: 20 peer-reviewed journal articles, 19 published abstracts, 54 conference presentations, 8 invited talks. PI on 9 awarded grants (~$114K) and Co-Investigator on 6 totaling $3.85M — roughly $3.97M in cumulative funded work.

Selected publications

APA format. Newest first. For the complete list, see the CV.

Galadima, H., Anson-Dwamena, R., Johnson, A., Bello, G., Adunlin, G., & Blando, J. (2024). Machine learning as a tool for early detection: A focus on late-stage colorectal cancer across socioeconomic spectrums. Cancers, 16(3), 540. doi:10.3390/cancers16030540
Galadima, H., Dumadag, A., & Tonn, C. (2024). Navigating new normals: Student perceptions, experiences, and mental health service utilization in post-pandemic academia. Education Sciences, 14(2), 125. doi:10.3390/educsci14020125
Berumen-Flucker, B., Galadima, H., Shangani, S., Kekeh, M., & Akpinar-Elci, M. (2023). Experiences with COVID-19 stress among Hispanic/Latino farmworkers. Journal of Agricultural Safety and Health, 29(3), 159–172. doi:10.13031/jash.15459
Carter, M., Galadima, H., & Akpinar-Elci, M. (2023). Pregnancy intention and breastfeeding behaviors in Virginia: A secondary analysis of PRAMS data. Clinical Lactation, 14(2), 63–71. doi:10.1891/CL-2022-0024
Lucero, L., Diaz-Kope, L., & Galadima, H. (2022). Politics, preparedness, or resources: Examining state responsiveness to the COVID-19 pandemic. Politics and the Life Sciences, 1–13. doi:10.1017/pls.2022.10
Al-Taiar, A., Al-Sabah, R., Shaban, L., Sharaf Alddin, R., Durgampudi, P. K., & Galadima, H. (2022). Is age of menarche directly related to vitamin D levels? American Journal of Human Biology, e23731. doi:10.1002/ajhb.23731
Galadima, H.I., Adunlin, G., Hughes, M.S., Cropp, C.D., Lucero, L., & Akpinar-Elci, M. (2021). Racial disparities and treatment trends among young-onset colorectal cancer patients: An analysis of a hospital cancer registry. Cancer Epidemiology, 72, 101911. doi:10.1016/j.canep.2021.101911
Enos, C. W., Galadima, H., Saini, A. D., Bell, S., Siegel, M., & Van Voorhees, A. S. (2020). Predictors of biologic use and satisfaction among patients with psoriasis. Journal of Psoriasis and Psoriatic Arthritis, 5(3), 100–108. doi:10.1177/2475530320925553
Galadima, H. I., & McClish, D. K. (2019). Controlling for confounding via propensity score methods can result in biased estimation of the conditional AUC: A simulation study. Pharmaceutical Statistics, 18(5), 568–582. doi:10.1002/pst.1948
Kimmel, A. D., Masiano, S. P., Bono, R. S., Martin, E. G., Belgrave, F. Z., Adimora, A. A., Galadima, H., & Sabik, L. M. (2018). Structural barriers to comprehensive, coordinated HIV care: Geographic accessibility in the US South. AIDS Care, 30(11), 1459–1468. doi:10.1080/09540121.2018.1476656

Selected grants

As Principal Investigator:

Knowledge, Attitude, and Perceived Barriers towards Breast Cancer Screening among Female African Immigrants — Johns Hopkins University, $15,000 (2025–2026). (Faculty Mentor with PhD candidate Rexford Anson-Dwamena.)
Predicting Health Outcomes Among Cancer Patients in Virginia: A Population-Based Machine Learning Approach — ODU School of Public Health Initiatives Intramural Grant, $24,309 (2023–2024).
Assessing Occupational Stress Among Lactation Consultants — ODU SPH Intramural Grant, $18,505 (2023–2024).
Assessing the Impacts of the COVID-19 Pandemic on U.S. Hispanic/Latino Farmworkers — Johns Hopkins University, $9,500 (2021–2023).

As Co-Investigator:

Targeting Brain Macrophage Reservoirs of SIV during HAART — NIH/NIMH (PI: Kim), $3,137,369 (2015–2018).
Social and Spatial Determinants of Melanoma in Hispanics — NIH/NIMHD (PI: Harvey), $250,000 (2015–2017).
The Hampton Roads Academic Health Collaboration — Chesapeake Health Department (PI: Kekeh), $10,000 (2024–2025).

Current projects

Breast cancer recurrence prediction (ongoing): machine-learning approaches to population-based surveillance strategies. Presented at APHA 2025.
Racial and ethnic disparities in breast cancer recurrence (ongoing): population-based cohort analysis, Virginia. Presented at APHA 2025.
Cervical cancer screening uptake — All of Us Research Program analysis (Co-PI; submitted 2025).

Dissertation committee chair

Chairing dissertation committees in the PhD in Health Services Research program at ODU:

Rexford Anson-Dwamena (2023–present)
Mya Achike — Occupational Stress and Coping During a Public Health Emergency (defended 2024)
Anne Dumadag — Mental Health Among the Asian American Population (2022–2024)
Brenda Berumen-Flucker — Acculturative Stressors and Cultural Factors in Health and Safety of Hispanic/Latino Farmworkers (defended 2022)

Looking for the calculator? The open tools I built for teaching live at ztchi.hgaladima.com — free, no signup, no tracking, work shown.