Distinguishing subpopulations of marijuana users with latent profile analysis

Matthew R. Pearson, Adrian J. Bravo, Bradley T. Conner, Amber M. Anthenien, Adrian J. Bravo, 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. Pearson, Eric R. PedersenMark A. Prince, Sharon A. Radomski, Lara A. Ray, Jennifer P. Read, Amber M. Anthenien, Adrian J. Bravo, 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. Pearson, Eric R. Pedersen, Mark A. Prince, Sharon A. Radomski, Lara A. Ray, Jennifer P. Read

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

Background Although marijuana is the most commonly used illicit drug in the United States, little is known about the effects of typical marijuana use patterns and whether there are distinct subgroups of marijuana users. Methods The present study used latent profile analysis to determine the number of distinct subgroups of marijuana users in a large sample of college students (n = 2129 past month marijuana users across 11 universities). We also examined how these distinct groups differ on several putative risk/protective factors (e.g., personality traits, perceptions of marijuana, and motives for using marijuana). Results Using the Lo-Mendell-Rubin Likelihood Ratio Test, we identified four latent classes with the largest class consisting of infrequent marijuana users, and three other classes demonstrating increasingly frequent use and more negative consequences with the most severe class being the smallest class. We found the largest between-class differences (i.e., distinctions across classes) to be on identification with being a marijuana user and use of protective behavioral strategies (PBS), such that the heavier user classes showed higher identification with marijuana users and lower use of PBS. Conclusions Our findings demonstrate that college student marijuana users are a heterogeneous group with different profiles of risk/protective factors and that those who use marijuana a few times per month are different from those who are near-daily or daily users. Our findings also serve as a call to action for the field to consider examining identification with being a marijuana user and the use of PBS in future marijuana studies.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalDrug and alcohol dependence
Volume172
DOIs
StatePublished - Mar 1 2017

All Science Journal Classification (ASJC) codes

  • Toxicology
  • Pharmacology
  • Psychiatry and Mental health
  • Pharmacology (medical)

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    Pearson, M. R., Bravo, A. J., Conner, B. T., Anthenien, A. M., Bravo, A. J., Conner, B. T., Correia, C. J., Dvorak, R. D., Egerton, G. A., Hustad, J. T. P., Kholodkov, T., King, K. M., Liese, B. S., Messina, B. G., Murphy, J. G., Neighbors, C., Nguyen, X. T., Parnes, J. E., Pearson, M. R., ... Read, J. P. (2017). Distinguishing subpopulations of marijuana users with latent profile analysis. Drug and alcohol dependence, 172, 1-8. https://doi.org/10.1016/j.drugalcdep.2016.10.043