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Generalizability vs. representativeness: Considerations for internet-based research on substance use


NOVEMBER 18, 2023

Jacob Borodovsky, PhD
Research Scientist, Center for Technology and Behavioral Health and the Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth

About the Presentation: Dr. Borodovsky will present on a recently published “philosophy of science” paper exploring the role of internet-based samples in substance use research. Using existing literature, empirical data, and simulations, the presentation will examine distinctions between the concepts of scientific generalizability and statistical representativeness and then use these two concepts to outline the strengths and weaknesses of internet-based sampling for substance use research.

About the Presenter: Jacob Borodovsky is a Research Scientist and Epidemiologist at CTBH and the Department of Biomedical Data Science in the Dartmouth Geisel School of Medicine. He received his PhD from the Dartmouth Institute for Health Policy and Clinical Practice under the mentorship of Drs. Lisa Marsch, Alan Budney, and Emily Scherer. He completed his postdoctoral training at the Washington University School of Medicine in St. Louis under the mentorship of Drs. Richard Gruzca and Laura Bierut and was awarded an NRSA F32 fellowship by the National Institute on Alcohol Abuse and Alcoholism during this time. Broadly speaking, Jake’s research interests lie at the intersection of addiction, epidemiology, statistical methods, and policy. He enjoys thinking about and trying to answer questions such as, “Why do humans use drugs?” “What is the best way to measure drug use?” and “What happens to drug use behaviors when we try to modify them with population-level regulations and individual-level interventions?” To answer these kinds of questions, Jake utilizes a range of traditional and non-traditional data collection and analysis methods and studies topics such as (1) cannabis legalization and novel methods of cannabis administration, (2) medication and technology-based treatments for opioid use disorder, (3) national patterns of co-use of alcohol and prescription central nervous system depressant medications (e.g., prescription benzodiazepines), (4) and risk behavior propensity among adolescents.