Category: Addictive Behaviors

Symposium

Symposium 15 - Applying Structural Equation Modeling to Understand and Disseminate Substance Use Data in Diverse Contexts

Friday, November 17
10:15 AM - 11:45 AM
Location: Aqua Salon E & F, Level 3, Aqua Level

Keywords: Substance Abuse | Psychometrics | Research Methods
Presentation Type: Symposium

Substance use research often requires multivariate statistical approaches to model substance use behavior, mechanisms for changing substance use, and the conditions treatments are most effective. Multivariate modeling techniques that address these questions, including SEM, can pose numerous data analytic challenges. First, the majority of SEM models are visualized using path diagrams, which restricts the dissemination of research findings to important stakeholders (e.g., consumers of clinical research without a strong statistical background). In order to overcome this barrier to the dissemination of research, we need new consumer-centered data visualization approaches that can help researchers think more visually (visual perception, visual communication, user-centered design) and make their research more approachable to those who are invested in research outside of academia. Second, substance use data often reflect diverse, not homogeneous populations of individuals. For more than a decade the field has recognized that latent subgroups exist among substance users both cross-sectionally and longitudinally. New methods that further allow researchers to identify non-homogeneous relations among substance use variables can further help researchers identify unique mechanisms of change for diverse subgroups of individuals. Third, substance use is dynamic and idiosyncratic, which requires event-level assessments to capture. Multilevel SEM allows for flexible examinations of intensive repeated assessments. Multilevel modeling allows for multivariate analysis of dynamic changes both across groups and within individuals over repeated assessments. Finally, there are relations among constructs in addictive behaviors that we are just beginning to explore. For research questions that require us to stretch into new territory we need rigorous exploratory methods that allow for comparison of a range of related models examining the relations among constructs. Fortunately, SEM is highly flexible and variations in its application allow us to overcome each of these challenges – ultimately, bringing us closer to modeling the complexity and diversity of real-life experiences. As our methods better map onto clinical experience and are easier to understand, clinicians can more easily utilize current research findings in their practice. These modeling and visualization advances can foster development of new treatments for substance use disorders that utilize the richness of the data to provide clinically meaningful insights and intervention targets at the population, group, subgroup, and individual levels. In addition, these methods can help to identify and analyze critical therapeutic processes elements including active ingredients and mechanisms of behavior change. 

Learning Objectives:

Mark A. A. Prince

Assistant Professor
Colorado State University

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Kevin M. King

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    Mark A. A. Prince

    Assistant Professor
    Colorado State University

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    Kevin A. Hallgren

    Behavioral Research in Technology and Engineering Center, University of Washington

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    Abby L. Braitman

    Old Dominion University

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    Bradley T. Conner

    Associate Professor
    Colorado State University

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