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Journal Article

Citation

Wilkinson ML, Linden-Carmichael AN. Addict. Behav. 2023; 145: e107780.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.addbeh.2023.107780

PMID

37354848

Abstract

Simultaneous alcohol and cannabis use (i.e., simultaneous use) is prevalent among young adults and often associated with negative consequences. Understanding reasons for not drinking (RND) may provide insight into a key intervention target for reducing negative consequences associated with simultaneous use. RND may vary on a day-to-day level, and multiple RND may be endorsed on a given day. Latent class analysis (LCA) of daily diary data is a nuanced approach that can identify complex patterns of daily RND as well as its day- and person-level covariates. The current study was a secondary data analysis of daily diary data from young adults who engaged in heavy drinking and recent simultaneous use (n = 154). We aimed to: (1) characterize daily RND, (2) use LCA to classify day-level patterns of RND, and (3) compare latent classes on same-day variables (i.e., positive and negative affect, day of the week), previous-day variables (i.e., substance use, intoxication level, consequences), and person-level characteristics (i.e., age, sex, baseline substance use frequency, simultaneous use motives). Participants completed up to 14 consecutive diaries. Multilevel LCA identified four classes of heterogeneous daily RND profiles. Daily RND classes significantly differed in terms of day of the week, previous day quantity of cannabis use, and several baseline variables (age, typical substance use, simultaneous use motives). Study findings offer preliminary support for heterogeneous RND classes among young adults engaging in simultaneous use and suggest multiple avenues for future research.


Language: en

Keywords

Alcohol; Cannabis; Avoidance motives; Concurrent use; Daily diary data

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