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Journal Article

Citation

Papini S, López-Castro T, Swarbrick M, Paul LK, Stanley D, Bauer A, Hien DA. Drug Alcohol Depend. 2023; 248: e109929.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.drugalcdep.2023.109929

PMID

37267744

Abstract

BACKGROUND: Substance use trends during the COVID-19 pandemic have been extensively documented. However, relatively less is known about the associations between pandemic-related experiences and substance use.

METHOD: In July 2020 and January 2021, a broad U.S. community sample (N = 1123) completed online assessments of past month alcohol, cannabis, and nicotine use and the 92-item Epidemic-Pandemic Impacts Inventory, a multidimensional measure of pandemic-related experiences. We examined links between substance use frequency, and pandemic impact on emotional, physical, economic, and other key domains, using Bayesian Gaussian graphical networks in which edges represent significant associations between variables (referred to as nodes). Bayesian network comparison approaches were used to assess the evidence of stability (or change) in associations between the two timepoints.

RESULTS: After controlling for all other nodes in the network, multiple significant edges connecting substance use nodes and pandemic-experience nodes were observed across both time points, including positive- (r range 0.07-0.23) and negative-associations (r range -0.25 to -0.11). Alcohol was positively associated with social and emotional pandemic impacts and negatively associated with economic impacts. Nicotine was positively associated with economic impact and negatively associated with social impact. Cannabis was positively associated with emotional impact. Network comparison suggested these associations were stable across the two timepoints.

CONCLUSION: Alcohol, nicotine, and cannabis use had unique associations to a few specific domains among a broad range of pandemic-related experiences. Given the cross-sectional nature of these analyses with observational data, further investigation is needed to identify potential causal links.


Language: en

Keywords

Alcohol; Cannabis; Substance use; COVID-19 pandemic; Bayesian network analysis; Nicotine

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