Research

 

Behavioral Health Research: Populations, Workforce, and Scientific Integrity

The Institute's primary mission is research. Its scholarly work informs continuing education, professional development workshops, and community learning initiatives designed to disseminate evidence-based practices and strengthen the behavioral health workforce.

 

 

Integrated Behavioral Health in Primary Care

Approaches to embedding behavioral health services within primary care settings to address mental health, substance use, and related psychosocial needs alongside physical health conditions in a unified, team-based approach. 

Populations & Patient-Centered Care

Investigating psychosocial, behavioral, and structural mechanisms linking mental health conditions with chronic medical illnesses to develop data-informed strategies to improve prevention, treatment engagement, and health outcomes across the lifespan. 

Behavioral Health Workforce & Training 

BxH Workforce
Studying people, systems, and policies that shape access to and quality of mental health and substance use disorder services.
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Featured Research

The All of Us Research Program at CHS

Western University of Health Sciences has a data use and registration agreement in place with the National Institutes of Health (NIH) All of Us Research Program to ensure data security and integrity. WesternU faculty, students, researchers, and postdoctoral fellows can leverage this one-of-a-kind dataset to improve understanding of health and disease, identify opportunities to reduce disparities, and enable more precise approaches to care. For questions, email Dr. Josh Matacotta in the College of Health Sciences at jmatacotta@westernu.edu. 

Learn about our research

Publications

  • Matacotta, J. J., Tran, D., & Yoon, S. (2024). The prevalence of major depressive disorder in people with HIV: Results from the All of Us Research Program. HIV Medicine. https://doi.org/https://doi.org/10.1111/hiv.13653
    Publisher's Version
    HIV Medicine Journal

    Objectives

    The All of Us (AoU) Research Program is a national-scale effort to build a dataset to help transform the future of health research by equipping researchers with comprehensive health data from diverse populations, especially those underrepresented in biomedical research. Our objectives were to evaluate the burden of HIV and major depressive disorder (MDD) in underrepresented groups and the frequency of the HIV/MDD comorbidity.

    Methods

    We conducted a cross-sectional analysis combining collected survey and electronic health record (EHR) data. We ascertained HIV and MDD cases using Observational Medical Outcomes Partnership codes. We used multivariable logistic regression to obtain the odds ratio of HIV in AoU participants and MDD in AoU participants with HIV.

    Results

    The latest AoU data release includes 412 211 participants: 254 700 have at least one medical condition concept in their EHR, of whom 5193 (1.3%) had HIV, and 2238 (43%) of those with HIV had a diagnosis of MDD. Black AoU participants had approximately 4.58 times the odds of having an HIV diagnosis compared with the combined odds of all other racial groups. AoU participants with HIV were more likely to have MDD (p = 0.001) than were participants without HIV.

    Conclusion

    Among AoU participants, Black individuals have a disproportionately high burden of HIV, pointing to underlying factors such as social determinants of health, limited access to healthcare or prevention resources, and potential systemic biases that contribute to these differences. In addition, HIV is a risk factor for mental health issues like MDD. Further data collection from people with HIV will elucidate contributing factors and the need for interventions.

  • Hicks, C. M., & Lee, C. S. (2024). Developer Thriving: Four sociocognitive factors that create resilient productivity on software teams. IEEE Software, 41(4), 68-77. (Original work published 2024)
    Publisher's Version
    Publisher's Version

    We present a research-based framework for measuring successful environments on software teams for long-term and sustainable sociocognitive problem-solving. Across 1,282 full-time developers in 12+ industries, we tested the factors of our framework and found it predictive of developers’ self-reported productivity.

    See also: Behavioral Health
  • Novak, B., Panbechi, K., & Matacotta, J. J. (2021). Knowledge and risk perception about hepatitis C: Preliminary evidence from a cross-sectional study of adults living in Louisiana. 2021 Western Medical Research Conference, 69(1), 103-296.
    Publisher's Version
    J Investig Med.

    Overview of Key Findings

    Low Screening Rates: Only about 35–36% of respondents reported ever being tested for HCV, while more than 60% had never been screened. The most common reasons for not testing were believing they were not at risk and never receiving a provider recommendation

    Knowledge Gaps: Although nearly all participants (≈98%) had heard of HCV, 65–67% had never heard of direct-acting antivirals (DAAs) and did not know HCV was curable

    Generational Risk Awareness: About one-quarter of untested participants were from the Baby Boomer generation, a population at increased risk according to CDC guidelines

    Perceived Stigma: Roughly 75% of HCV-positive participants and two-thirds of HCV-negative/unknown participants believed people with HCV would be treated differently if they disclosed their status, and nearly 70% believed shame keeps people from seeking treatment

    Health Perception: A majority (≈80–83%) reported their health as excellent, very good, or good, and this correlated with lower perceived risk of infection

  • Collaboration, C. for O. S. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). (Original work published 2015)

    Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.