The highest rates of tobacco, alcohol, and marijuana use are found in young adults aged 18-25 years, a time of life that, for many, includes the college years (SAMHSA, 2002). While the amount each student smokes may vary, even those students who report low levels of smoking are at risk for developing nicotine dependence (Dierker et al., 2007). Since smoking continues to be the leading preventable cause of death in the U.S. (USDHHS, 2006), it is extremely important both to prevent the onset of smoking and help current smokers quit before a long-term habit forms. To be successful, such prevention and treatment efforts must be informed by a thorough understanding of college-age tobacco use and nicotine dependence. However, college-age tobacco use and nicotine dependence are complex, time-varying phenomena that are correlated with other high-risk behaviors, particularly alcohol and marijuana use (Dierker et al., 2006;Reed et al., 2007;Rigotti, Lee, &Wechsler, 2000;Weitzman &Chen, 2005), and with demographic characteristics such as gender (Dierker, et al., 2007;Reed, et al., 2007;Weitzman &Chen , 2005). The strength and even direction of the relations between dynamic variables such as tobacco, alcohol, and marijuana use may, in fact, vary over time as well. The overall purpose of the proposed research is to build on available functional data analysis (FDA) methods (Ramsay, Hooker, &Graves, 2009;Fan, Huang, &Li, 2007), a sophisticated statistical approach, to model the complex time-varying phenomena of tobacco use and nicotine dependence.
The specific aims are to (1) model the dynamics of tobacco use and nicotine dependence in a rich longitudinal data set on daily substance use among college freshman, the UpTERN data (Tiffany, et al., 2004), (2) identify and test hypotheses about the possibly time-varying effects of alcohol use and marijuana use on tobacco use/nicotine dependence and (3) answer new research questions regarding the dynamics of freshman year substance use. The UpTERN data consist of 245 daily assessments of students'tobacco, alcohol, and marijuana use during their freshman year of college, as well as weekly nicotine dependence assessments for current smokers. FDA is an innovative method for analyzing intensive longitudinal behavioral data, and the results from this study will uniquely contribute to research on college-age co-occurring substance use and nicotine dependence. A better understanding of how the relations between tobacco use, marijuana and alcohol use, and nicotine dependence change over the freshman academic year will contribute to the design of effective prevention programs geared towards college students. The proposed research will also improve the FDA approach to enhance its usefulness in addressing substance use research questions. This two-year interdisciplinary pre-doctoral training program has a strong focus both on the statistical methodology developed and on the application of new statistical analysis methods to contribute to drug use and nicotine dependence literature.

Public Health Relevance

Results from the proposed study will provide researchers with a thorough understanding of how the relations between college-age tobacco use, marijuana and alcohol use, and nicotine dependence change over the freshman academic year. These findings will significantly contribute to the design of effective drug prevention programs geared towards first-year college students.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Predoctoral Individual National Research Service Award (F31)
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Special Emphasis Panel (ZRG1-F16-B (20))
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Lambert, Elizabeth
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Pennsylvania State University
Biostatistics & Other Math Sci
Schools of Arts and Sciences
University Park
United States
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Trail, Jessica B; Collins, Linda M; Rivera, Daniel E et al. (2014) Functional data analysis for dynamical system identification of behavioral processes. Psychol Methods 19:175-87