Typology of cannabis use among adults: A latent class approach to risk and protective factors. (May 2019)

• Record Type: Journal Article
• Authors: Manning, Kara; Garey, Lorra; Paulus, Daniel J.; Buckner, Julia D.; Hogan, Julianna B.D.; Schmidt, Norman B.; Zvolensky, Michael J.
• Is Part Of: Addictive behaviors. Volume 92(2019)
• Page Start: 6
• Page End: 13
• Publication Date: 2019-05
• Subjects: Cannabis -- Marijuana -- Smoking -- Groups -- Risk factors; Substance abuse -- Periodicals; Alcoholism -- Periodicals; Drug addiction -- Periodicals; Nicotine addiction -- Periodicals; Smoking -- Periodicals; Gambling -- Psychological aspects -- Periodicals; Electronic journals; 362.29
• DOI: 10.1016/j.addbeh.2018.12.008
• Languages: English
• ISSNs: 0306-4603

Abstract

Abstract: Background: Cannabis is among the most widely used substances worldwide. The United States has seen an increase in the number of adult daily cannabis users and in the number of adults diagnosed with cannabis use disorder. However, little work has examined patterns of use or unique subgroups of adult cannabis users, which may be useful in developing targeted treatment interventions for problematic cannabis users. Therefore, the current study used latent profile analysis to identify whether cannabis users can be categorized across distinct subgroups of adult users. Method: The sample included 374 current cannabis using adults (64.2% Male; M age = 32.6). Cannabis use frequency, quantity, and related problems were used to differentiate subgroups. Further, age, race, emotion dysregulation, affect, anxiety sensitivity, other substance use, and motives for cannabis use were examined as class correlates. Results: Results supported five unique classes of cannabis users, generally ranging from light, infrequent users with few problems to heavy, frequent users with more problems. Additionally, race, negative affectivity, anxiety sensitivity, emotion regulation, cannabis use motives, and alcohol use emerged as unique predictors of class membership. The current findings substantiate past work for heterogeneous latent classes that underlie the larger cannabis using population, however, this study provides novel evidence for subgroups of adult users. Conclusion: The identification of different classes of cannabis users may inform future treatment interventions, and ultimately, lead to the development of personalized treatments for each class based on correlates of group membership. Highlights: Results indicate five classes of cannabis use, ranging from light users with few problems to heavy users with more problems. Several significant constructs emerged as unique predictors of class membership of class membership. This expands of prior work by providing novel evidence for subgroups of adult cannabis users.