Making Decisions With Trees: Examining Marijuana Outcomes Among College Students Using Recursive Partitioning

Adam D. Wilson, Kevin S. Montes, Adrian J. Bravo, Bradley T. Conner, Matthew R. Pearson, Amber M. Anthenien, Bradley T. Conner, Christopher J. Correia, Robert D. Dvorak, Gregory A. Egerton, John T.P. Hustad, Tatyana Kholodkov, Kevin M. King, Bruce S. Liese, Bryan G. Messina, James G. Murphy, Clayton Neighbors, Xuan Thanh Nguyen, Jamie E. Parnes, Matthew R. PearsonEric R. Pedersen, Mark A. Prince, Sharon A. Radomski, Lara A. Ray, Jennifer P. Read

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Exploratory analyses were used to identify a unique constellation of variables that are associated with marijuana use outcomes among college students. We used recursive partitioning to examine more than 100 putative antecedents of lifetime marijuana user status, past-month marijuana user status, and negative marijuana-related consequences. Participants (N = 8,141) completed measures online across 11 sites in the United States. Norms (descriptive, injunctive, and internalized norms) and marijuana identity best distinguished marijuana users from nonusers (i.e., lifetime/past month), whereas marijuana use frequency, use of protective behavioral strategies, and positive/negative urgency best distinguished the degree to which users reported negative consequences. Our results demonstrate that tree-based modeling is a useful methodological tool in the selection of targets for future clinical research. Additional research is needed to determine if these factors are causal antecedents, rather than consequences or epiphenomena. We hope this large sample study provides the impetus to develop intervention strategies targeting these factors.

Original languageEnglish (US)
Pages (from-to)744-754
Number of pages11
JournalClinical Psychological Science
Volume6
Issue number5
DOIs
StatePublished - Sep 1 2018

All Science Journal Classification (ASJC) codes

  • Clinical Psychology

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