Social and Behavioral Sciences Branch
Social and behavioral factors contribute to disparities in health outcomes in population, community, and clinical settings. A critical understanding of these factors could help develop effective interventions to reduce disparities and improve health outcomes in populations experiencing health disparities. Social and behavioral science research is a multidisciplinary field consisting of health services, psychology, engineering, epidemiology, data, behavioral, and decision sciences.
The Social and Behavioral Sciences branch:
- Examines disparities in individual, clinical, behavioral, and contextual factors that affect health outcomes in populations experiencing health disparities.
- Understands the mechanisms through which psychological, social, institutional, structural, and environmental processes lead to disparities in health promotion and health risk behaviors, clinical decision-making, and related health outcomes.
- Develops novel interventions to promote equitable access to health information, patient engagement, and shared decision-making to improve health outcomes in populations experiencing health disparities.
Kelvin Choi, Ph.D., M.P.H.
Tobacco Related Disparities and Control Lab
Social determinants of health, commercial determinants of health, commercial tobacco use disparities, public health policy
Research and Programmatic Interests
Commercial tobacco use remains the number one cause of preventable death in the United States. While the prevalence of cigarette smoking has declined in the past few decades, such decline is not equal across social determinants of health; the prevalence of cigarette smoking varies greatly by race and ethnicity, sex/gender identity, socioeconomic status, geographical region, and other social determinants of health. Additionally, the tobacco industry continues to leverage commercial determinants of health (e.g., product development, marketing, distribution) to target populations who are socially disadvantaged.
We aim to examine the interrelationship between social determinants of health and commercial tobacco use using a life course perspective, the influence of commercial determinants on the disparities in commercial tobacco use, and the impact of public health policies on these disparities.
Applying an Intersectional Perspective to Understand Tobacco Product Use Disparities
Intersectionality theory asserts that social identities and circumstances, such as race, ethnicity, nativity, gender and socioeconomic position, are interconnected and create overlapping and interdependent systems of power dynamics resulting in persistent advantages and disadvantages in the society.
We apply this perspective to understand and identify the combinations of social identities and circumstances that result in high prevalence of tobacco product use, through the application of advanced statistical models and machine learning.
Using Population-Based Studies to Examine the Interplay Between Tobacco Product Marketing and Use Behaviors
The tobacco industry leverages commercial determinants of health to target individuals who are socially and economically disadvantaged to promote tobacco product use, resulting in disproportionate burden of tobacco-related diseases in them.
Using population-based cross-sectional and longitudinal studies, we examine how exposure to commercial determinants of health (e.g., tobacco product price discounting) differ by social identity and circumstances. We also assess how such disparities in exposure are related to disparities in tobacco product use behaviors.
Investigating the Psychosocial Mechanisms Underlying the Relationships Between Social Determinants of Health, Commercial Determinants of Health, and Tobacco Product Use
Documenting the complex relationship between social and commercial determinants of health with tobacco product use is important. Understanding the mechanisms underlying these relationships provides a stronger scientific foundation to support public health actions and policies.
We use online and laboratory-based experiments (e.g., eye tracking, emotional coding, electroencephalography) to understand how tobacco marketing strategies influence perceptions and beliefs of—and intention to engage with—commercial tobacco use.
Forecasting and Evaluating Tobacco Control Interventions and Policies
Tobacco control interventions and policies at the local, state, and federal levels are effective tools to reduce tobacco product use. However, it is difficult to conduct field experiments to test the potential impact of these interventions and policies before implementing them.
We use computational simulation models to forecast the effect of tobacco control interventions and policies on tobacco product use behaviors and related disparities. Sometimes, these interventions and policies are adopted by different localities, states, and countries. This presents natural experiments that we leverage to understand how these interventions and policies may reduce commercial tobacco use disparities.
Kristen Hamilton-Moseley, Ph.D.
Research and Programmatic Interests
Dr. Hamilton-Moseley investigates mechanisms by which psychological, biological, and environmental factors influence alcohol and tobacco use and how these contribute to health disparities.
In addition to investigating the psychobiological mechanisms by which social determinants influence alcohol and tobacco-related health disparities, Dr. Hamilton-Moseley examines psychological harms associated with exposure to racial and ethnic discrimination.
Jinani Jayasekera, Ph.D., M.S.
Health Equity and Decision Sciences (HEADS) Lab
Health equity, health services research, decision sciences, biostatistics, econometrics, mathematical/simulation modeling, economic analysis, engineering, operations research, behavioral research, systematic reviews, meta-analysis
Research and Programmatic Interests
Decision sciences include a range of quantitative and qualitative methods to inform decision-making at individual, interpersonal, community, and societal levels. The focus on “decision” as the unit of analysis provides a unique framework to develop interventions and policies that could help reduce disparities in health care. Decision sciences utilize a variety of tools, such as biostatistics, econometrics, mathematical modeling, economic analysis, operations research, behavioral research, systematic reviews, and meta-analysis.
Clinical Decision Tools to Support Equitable Cancer Care
Personalized cancer prevention and control decisions are best informed by a combination of multiple data sources that could quantify the variation of effects by patient, clinical, and genomic characteristics of individuals seen in clinical practice.
Mathematical modeling provides a powerful computational tool to combine information from various high-quality data sources to depict complex relationships between patient (e.g., age), clinical (e.g., comorbidities, tumor size), genomic (e.g., BRCA 1/2, 21-gene score), and contextual (e.g., socioeconomic status) characteristics to generate robust estimates that could support personalized clinical care for diverse individuals.
These tools could facilitate optimal communication with health care providers, patients, and their involved family members considering clinical, interpersonal, and societal factors. Dr. Jayasekera's research program focuses on the development, validation, and testing of clinical decision tools to support the delivery of equitable cancer care.
"Virtual" Clinical Trials to Advance Health Equity
Randomized clinical trials are the gold standard for understanding intervention effects and developing clinical guidelines. However, clinical trials consume enormous time and resources. The HEADS research lab uses a range of tools to synthesize existing data and simulate trials to predict trial outcomes; identify key design issues prior to the implementation of a clinical trial; and most importantly, evaluate the implications of trial designs and results on health disparities.
Informing Policies to Reduce Health Disparities in Cancer Outcomes
Improving the quality and equity of health care is an important goal for cancer prevention and control research. New advances in screening and treatment have led to overall declines in U.S. cancer mortality. However, this progress has not been realized equally across the United States. For example, Black women have persistently higher breast cancer mortality rates than White women.
Reasons for these epidemiological trends are likely multifactorial, including availability, access to and quality of health care services, socioeconomic inequalities, completeness, and effectiveness of cancer treatments. The HEADS research lab generates novel data to inform the development of population health policies, guidelines, and interventions that could reduce social inequalities in cancer care.
Page updated Jan. 26, 2024