The influence of cannabis motives on alcohol, cannabis, and tobacco use among treatment-seeking cigarette smokers
Introduction
Alcohol, cannabis, and tobacco are the most widely used substances and they frequently co-occur and interplay with one another in clinically significant ways (Kessler et al., 1997, Redonnet et al., 2012, Roxburgh et al., 2013). For example, cigarette smoking is a key precursor to cannabis relapse (Haney et al., 2013). Further, strong associations between tobacco and alcohol consumption have been documented (Palfai et al., 2000). Relative to abstainers, drinkers are 75% more likely to use tobacco, and 85% of smokers also drink (Harrison et al., 2009, Howell et al., 2010, Krukowski et al., 2005, Reed et al., 2007). Moreover, cannabis is related to a myriad of negative outcomes, including psychological symptoms and disorders (Patton et al., 2002, Zvolensky et al., 2006), and tobacco smokers are more likely to use cannabis (Ford et al., 2002). Coupled with tobacco and alcohol use, cannabis use has adverse effects on fetal growth and development (Cornelius et al., 2002, Richardson et al., 1995), increases risk for harder drugs (Golub and Johnson, 2001), and negatively impacts educational achievements (Centers for Disease, 1991, Martin et al., 1992). Interventions for co-occuring substance use have demonstrated favorable effects (Chariot et al., 2013; Gmel et al., 2013, Laporte et al., 2014). However, recent work has shown differential effects on health risk behavior when comparing the influence of cognitive processes related to one substance versus a different substance. Specifically, alcohol-related cognitive processes have been shown to impact smoking outcomes more strongly than smoking processes impact alcohol consumption (Piasecki et al., 2011). Additionally, cognitive factors important in the process of quitting substance use may not have a straightforward relationship with reducing poly substance use (, 2014). Foster et al. (in press) found that although co-use of tobacco and alcohol decreased among individuals with more cognitive processes related to quitting smoking, a subset of individuals were at greater risk for heavier alcohol use, despite also having greater smoking quit processes. These findings suggest that among multiple substance users, cognitive factors that may facilitate quitting or protect against problem use of substance (e.g., tobacco) might pose difficulties to quitting other substances (e.g., alcohol or cannabis).
One avenue of research that has facilitated development of effective interventions relates to motivational bases of cannabis use. Extensions of its utility to better understanding tobacco and alcohol use have provided important and clinically-relevant insights into patterns related to multiple substance use (Cooper, 1994, Piper et al., 2004). There are five established motives for cannabis use; social, coping, enhancement, conformity, and expansion (Bonn-Miller et al., 2007, Chabrol et al., 2005, Zvolensky et al., 2007a, Zvolensky et al., 2007b). Endorsement of specific motives has been linked with cannabis use frequency in varying populations (Chabrol et al., 2005, Simons et al., 2000) and cannabis motives are shown to be incrementally and uniquely associated with cannabis use over and above the variance explained by alcohol and cigarette use (Bonn-Miller et al., 2007, Zvolensky et al., 2007a, Zvolensky et al., 2007b). Recent work has demonstrated associations between cannabis motives related to coping and gender (Bujarski et al., 2012), conformity, coping, and expansion motives and personality risk factors (Hecimovic et al., 2014), coping motives and social anxiety (Buckner et al., 2014), and enhancement, social, and coping motives and the experience of cannabis-related problems (Buckner, 2013).
Although previous work has evaluated cannabis motives and other substance use (Norberg et al., 2014, Zvolensky et al., 2007a, Zvolensky et al., 2007b), comparatively little is known about the influence of cannabis motives on concurrent substance use (i.e., tobacco, alcohol, and cannabis). Cross-substance motives literature has evaluated why tobacco users may use cannabis (Agrawal et al., 2012), and has also examined associations between alcohol and cannabis motives and alcohol-cannabis co-use (Simons et al., 2005). However, research exploring links between cannabis use motives and multi-substance use is scarce, and as a result, relatively little is known about whether specific motives uniquely contribute to the prediction of co-use and other clinically relevant phenomena over and above theoretically related variables (e.g., gender). Thus, it is necessary to better understand potential antecedents to concurrent use in order to further elucidate critical junctures for altering substance use behavior.
The present study was designed to address this gap in knowledge by examining relationships among cannabis motives and the use of alcohol, tobacco, and cannabis in a sample of daily cigarette smokers who consume alcohol and cannabis using structural equation modeling (SEM) to account for measurement errors of the observed variables by modeling them as latent constructs (Kline, 2011a). This effort will facilitate further advances in understanding how motives for one substance (i.e., cannabis) can relate to co-occurrence of alcohol, tobacco, and cannabis in a treatment seeking population. We examined the incremental validity of cannabis motives in regard to drinking frequency, drinking level, cannabis use, cannabis problems, nicotine dependence, and the number of cigarettes smoked per day. Additionally, we evaluated the unique effects above and beyond theoretically relevant covariates including gender, education, and race (Goncy and Mrug, 2013, Westmaas and Langsam, 2005). Based on previous work indicating positive associations between motives and use (Chabrol et al., 2005), we expected that cannabis motives would be significantly linked with increases in alcohol consumption, tobacco use, and cannabis use. Further, we expected that any observed effects would be unique from shared variance with covariates. These expectations are based on theoretically relevant motivational models and empirical evidence, which suggests that among multiple substance users, factors including motives or reasons for use are linked with substance use.
Section snippets
Participants
The present sample consisted of 167 treatment-seeking daily smokers (41.92% female; Mage = 28.74; SD = 11.88). The racial and ethnic distribution of this sample was as follows: 83.23% identified as White/Caucasian; 7.78% identified as Black/Non-Hispanic; 0.60% identified as Black/Hispanic; 3.59% identified as Hispanic; 1.20% identified as Asian; and 3.59% identified as ‘Other.’ 21.56% of participants completed high school as their highest form of education, 48.50% completed some college, 11.98%
Descriptive data and correlations among variables
Means, standard deviations, and bivariate correlations for all of the study variables are presented in Table 1. Drinking frequency and alcohol problems were positively correlated (r = 0.42, p < 0.001). Cannabis problems were positively correlated with alcohol problems (r = 0.39, p < 0.001) and with cannabis use (r = 0.30, p < 0.001). The number of cigarettes smoked per day was negatively correlated with cannabis use (r = −0.16, p < 0.05) and positively correlated with nicotine dependence (r = 0.64, p < 0.001). All
Discussion
The present study evaluated the unique effects of cannabis motives on multi-substance use in an effort to examine the incremental validity of cannabis motives with respect to substance use outcomes. Findings generally indicated that alcohol, tobacco, and cannabis use correlate with cannabis motives (Zvolensky et al., 2007a, Zvolensky et al., 2007b). Results also largely supported expectations that the observed effects due to cannabis motives were unique from shared variance with theoretically
Author disclosures
Role of funding sources
This project was supported by National Institute of Mental Health grant R01 MH076629-01 (Drs. Zvolensky and Schmidt). Additionally, preparation of this manuscript was supported in part by National Institute on Drug Abuse grant K12-DA-000167 (Dr. Foster). NIMH and NIDA had no direct role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. The contents of this manuscript do not
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