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. Author manuscript; available in PMC: 2026 Jan 23.
Published in final edited form as: J Dual Diagn. 2020 Aug 7;16(4):409–419. doi: 10.1080/15504263.2020.1786616

Obsessive-Compulsive Symptoms and Cannabis Misuse: The Explanatory Role of Cannabis Use Motives

Jafar Bakhshaie 1, Eric A Storch 2, Nhan Tran 3, Michael J Zvolensky 4
PMCID: PMC12826621  NIHMSID: NIHMS2132943  PMID: 32767907

Abstract

Objective:

The purpose of the present investigation was to examine the unique explanatory role of cannabis use motives above the effects of each other, for the relationship between obsessive-compulsive symptomatology and different aspects of cannabis misuse among young adults. The transitional years of young adulthood are characterized by new opportunities for experimentation as well as novel external stressors. Collectively, this makes this developmental epoch a sensitive time for manifestations of cannabis misuse.

Methods:

Bivariate correlations were conducted to examine the association between obsessive-compulsive symptomatology and risky cannabis use, cannabis use problems, and the average quantity of cannabis used per occasion among a young ethno-racially diverse sample of college students with the past year history of cannabis use (N=177, 68.95% female, Mage=21.51, SD=4.24). Next, multiple mediation analyses were conducted to examine the unique explanatory role of cannabis use motives (e.g., enhancement, conformity, coping, social, and expansion) for the association between the obsessive-compulsive symptoms and cannabis misuse variables which showed significant correlation with these symptoms at the bivariate level.

Results:

Obsessive-compulsive symptoms were significantly correlated with risky cannabis use (r=.19; p=.02), but not cannabis use problems or the average quantity of cannabis used per occasion. Conducting the multiple mediation for the relationship with the significant bivariate correlation, coping motives significantly explained the relationship between obsessive-compulsive symptoms and risky cannabis use (b = .04, SE = .02, 95% Bootstrapped CI [.003, .10], Completely Standardized Indirect Effects= .07), after controlling for the variance accounted for by problematic alcohol use and smoking status. This indirect effect was not significant after adding anxiety and depressive symptoms as covariates to the model.

Conclusions:

These findings are discussed in terms of the development of specialized treatments to specifically target cannabis use coping motives among individuals with comorbid obsessive-compulsive disorder and cannabis misuse.

Keywords: Cannabis, Obsessive-compulsive disorder, Cannabis misuse, Cannabis use motives, Coping motives

Introduction

The rates of cannabis use are at an all-time high in the United States, with the prevalence rates more than doubled from the past decade (Hasin et al., 2015; Johnston, O’Malley, Bachman, & Schulenberg, 2013; McCarthy, 2016; Spradlin, 2017). This trend could be due to factors such increased availability and societal acceptance and decreased perceived health consequences of the cannabis use (Hasin et al., 2017; Hasin, 2018; Merz, 2018; Parnes, Smith, & Conner, 2018). The transitional age young adults have opportunities for experimentation in the context of their new independence and are also exposed to novel external stressors related to study/job demands making this cohort more vulnerable to the misuse of cannabis (Arnett, 2000; Dawson, Grant, Stinson, & Chou, 2005). This issue is more concerning given a consistent increase in the psychoactive properties and potency of cannabis strains in the United States over the past few decades, which is associated with a higher risk of misuse, especially among younger age groups (Fedorova et al., 2019). Indeed, the rates of problematic cannabis use and cannabis use disorders are rapidly growing, with nearly 3 of 10 cannabis users eventually developing cannabis use disorders (Hasin et al., 2016; Hasin et al., 2015; Parnes et al., 2018). Such change in cannabis misuse trends is a matter of public health concern since heavier cannabis use and cannabis use disorders are related to adverse health-related consequences such as respiratory illnesses or cognitive dysfunction (Solowij et al., 2002; Volkow, Baler, Compton, & Weiss, 2014), as well as mental health problems (Lev-Ran, Le Foll, McKenzie, George, & Rehm, 2013). Considering the public health relevance of cannabis misuse, understanding the modifiable factors involved in the development and maintenance of risky cannabis use are of clinical significance.

One important group of such modifiable risk factors of cannabis misuse are comorbid emotional disorders such as major depression, social anxiety disorder, and PTSD (Agosti, Nunes, & Levin, 2002). Individuals with emotional disorders have been reported to be at higher risk for problematic cannabis use, cannabis use disorder, and its related problems (Buckner et al., 2008), and are more likely to relapse following an attempt to quit cannabis (Flórez-Salamanca et al., 2013). Among emotional disorders, anxiety and depression are among the most investigated risk factors for the development and maintenance of cannabis misuse (Hayatbakhsh et al., 2007). Studies have shown that anxiety and depressive problems are related to cannabis misuse through mechanisms such as using cannabis as a method to cope with emotional distress, attempts to conform and fit in with a social group to avoid scrutiny, and to improve the experience of social gatherings and bond with peers (Buckner, Bonn-Miller, Zvolensky, & Schmidt, 2007; Buckner, Zvolensky, & Schmidt, 2012; Buckner & Zvolensky, 2014; Bujarski, Norberg, & Copeland, 2012; Comeau, Stewart, & Loba, 2001; Johnson, Barrault, Nadeau, & Swendsen, 2009; Metrik et al., 2016).

Despite the wealth of knowledge regarding the role of anxiety and depression disorders on risky cannabis use and related problems, there is a paucity of evidence regarding the association of obsessive-compulsive disorder (OCD) and cannabis misuse. The few existing empirical studies suggest an association between obsessive-compulsive symptoms and cannabis misuse like what is observed in other emotional disorders. For example, one study has shown a positive correlation between obsessive-compulsive symptoms and cannabis use-related problems among cannabis-using young adults (Buckner et al., 2007). Further, in the only existing work primarily focused on the association between obsessive-compulsive symptoms and cannabis misuse, Spradlin and colleagues found that obsessive-compulsive symptoms predict cannabis misuse symptoms and related problems among young adult life-time cannabis users above and beyond the effects of anxiety and depressive symptoms (Spradlin, Mauzay, & Cuttler, 2017). Given the potential risk of cannabis misuse for individuals experiencing obsessive-compulsive symptoms, the evaluation of the underlying explanatory mechanisms involved in the association of OCD and risky/problematic cannabis use is needed.

Cannabis use motives are among the potential explanatory constructs that may be mechanistically involved in the relation between obsessive-compulsive symptoms and cannabis misuse. Indeed, Spradlin et al. (2017) found that the relationship between obsessive-compulsive symptoms and problematic cannabis use as well as symptoms of cannabis use disorder were mediated by coping motives, reflecting the motivation to use cannabis to alleviate stress and negative affect. In other words, an individual’s experiences of obsessive-compulsive symptoms could be associated with a considerable amount of psychological distress. As an affective vulnerability, obsessive-compulsive symptomatology could predispose these individuals to develop motives to use cannabis in an attempt to manage their perceived psychological distress, which in turn, could lead to risky cannabis use and its related consequences (Metrik et al., 2016). This observation is in line with the distress avoidance model of cannabis misuse (Bonn-Miller, Vujanovic, Twohig, Medina, & Huggins, 2010) as well as self-medication hypothesis, which conceptualizes the misuse of cannabis among individuals with emotional disorders as an effort to alleviate the psychiatric symptoms (Arendt et al., 2007; Hong et al., 2019; Pedersen et al., 2015).

Despite this knowledge, research regarding the underlying mechanisms of OCD-cannabis association is limited in several ways. First, similar to the other emotional disorders, it is possible that cannabis use motives other than coping are involved in the development of cannabis misuse in the context of obsessive-compulsive symptoms. For example, conformity motives have shown relevance to other emotional disorders as well as cannabis misuse (Buckner et al., 2012). Thus, research needs to examine the explanatory role of cannabis use motives in a holistic fashion and above the effects of alternative motives for use. Second, past work has not controlled for the frequency and/or heaviness of alcohol and smoking status which are the other two commonly misused substances among young adults that are associated with cannabis misuse (Lee, Brook, & Kim, 2018). Finally, previous research has focused on life-time cannabis users. However, given the potentially different mechanisms involved in the use for the long term versus the more recent cannabis users (Metrik et al., 2016), it is crucial to examine these processes among populations limited to more recent cannabis users.

Together, the present investigation sought to examine the unique explanatory role of cannabis use motives above the effects of each other (in a simultaneous analytic model) for the relationship between obsessive-compulsive symptomatology and cannabis misuse among a young ethno-racially diverse sample of college students with the past year history of cannabis use. College students have a significantly higher likelihood of initiation of cannabis use compared to young adults not enrolled in college with potential risk for development of cannabis use disorder (Miech, Patrick, O’malley, & Johnston, 2017). The dependent variables included risky cannabis use, cannabis-related problems, and the average quantity of cannabis use per occasion. Based upon previous work in emotional disorders, it was hypothesized that coping, conformity, and social motives would uniquely explain the relationship between obsessive-compulsive symptoms and the dependent measures over and above the effects of one another and other cannabis use motives. Additionally, it was expected that observed effects would be evident above and beyond the variance accounted for by problematic alcohol use, smoking status, and depressive and anxiety symptoms.

Methods

Participants

The present sample is a subset of participants from a larger study of mental health among students at a large, southwestern university. Participants were 177 undergraduate college students (68.95% female, Mage=21.51, SD=4.24; Range= 18-35) who reported past-year use of cannabis. As part of the larger study, participants received extra credit toward their psychology course as compensation and were recruited via flyers and posting on the extra credit website. Exclusion criteria for the larger study included being younger than age 18 years and non-proficiency in English (to ensure comprehension of study questions). The sample was diverse: 39.51% Hispanic (n=70), 18.12 % Asian/Pacific Islander (n=32), 25.41% non-Hispanic White (non-Hispanic; n=45), 10.35% Black (non-Hispanic; n=18), and 5.13% other (n=9). Among the participants, 47.67% reported using cannabis at least once a month, and 28.83% reported using cannabis at least once a week. Participants reported using cannabis 4.35 days in the past month on average (see Figure 1 for a detailed description). A total of 28.23% of the sample presented with the scores above the clinical cut-score of 21 on the measure of OCD (Foa et al., 2002).

Figure 1.

Figure 1.

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Number of days used cannabis in the past month among the study sample per MSHQ.

Procedures

This study was approved by the institutional review board (IRB) at the university in which the study was conducted, and all study procedures complied with the IRB approved protocol. After a complete discussion of the study objectives and procedures with potential participants, written informed consent was obtained. Specifically, each participant completed online informed consent before proceeding to an Internet-based self-report survey. All study measures were completed online. No identifying information was collected linking participants to survey responses.

Measures

Obsessive Compulsive Inventory-Revised (OCI-R)(Foa et al., 2002).

The OCI-R is an 18-item self-report measure of obsessive-compulsive symptoms. In addition to a total score, the measure yields six subscale scores, including hoarding, checking, neutralizing, obsessing, ordering, and washing. Previous research has demonstrated that the OCI-R has good internal consistency, test-retest reliability, and convergent validity within both clinical and non-clinical samples (Foa et al., 2002). In the current study, the total score of the OCI-R was used, which demonstrated good internal consistency (α = .94).

The Alcohol, Smoking, and Substance Involvement Screening Test--Version 3.0 Modified (ASSIST V3.0r) (Newcombe, Tanielu-Stowers, McDermott, Stephen, & Nosa, 2016).

The ASSIST was initially developed by the WHO Assist Working Group (2002) to screen for the past three months risky use of tobacco, alcohol, cannabis, cocaine, amphetamine-type stimulants, sedatives, hallucinogens, inhalants, opiates, and other drugs in primary care settings. The resulting instrument consists of eight items that applies to all listed substances (e.g., Have you ever tried and failed to control, cut down or stop using: tobacco, alcohol, cannabis, cocaine, amphetamine-type stimulants, sedatives, hallucinogens, inhalants, opiates, and other drugs ?) One item uses a dichotomous ‘Yes’/‘No’ response format. The remaining items use five- or three-point rating scales. ASSIST V3.0r exhibits satisfactory concurrent and construct validity (Newcombe et al., 2016). In this study, the ASSIST score on the risky use of cannabis was used; it is calculated as the sum of items two to seven for cannabis, with the scores ranging from 0 to 39 (α = 0.77).

Marijuana Problems Scale (MPS) (Stephens, Roffman, & Curtin, 2000).

The MPS is a 19-item list of negative social, occupational, physical, and personal consequences associated with cannabis use in the past 90 days. Respondents are asked to rate the level of problems (e.g., “problems between you and your partner,” “legal problems”) associated with their cannabis use on a scale from 0 (no problem) to 2 (serious problem). As in past work (Buckner & Schmidt, 2008), internal consistency was good in the current sample (α = 0.88).

Marijuana Smoking History Questionnaire (MHSQ) (Bonn-Miller & Zvolensky, 2009).

The MSHQ is a self-report questionnaire measure of respondents’ cannabis use history. For this study, the answer to the following question was used as an index of average quantity of cannabis use per occasion: “On average, how much marijuana do you smoke per occasion.” Responses were based upon an eight-point visually depicted illustration of the quantity of cannabis smoked (i.e., possible joint sizes; range = 1 to 8).

Marijuana motives measure (MMM) (Simons, Correia, Carey, & Borsari, 1998).

The MMM consists of 25 items that measures possible reasons a respondent has used cannabis (example items: To forget my worries, To be social) (Simons et al., 1998). Items are answered on a 5-point scale ranging from Almost Never/Never to Almost Always/Always. The measure includes five subscales: enhancement, social, conformity, expansion, and coping (Simons et al., 1998). The MMM subscales have demonstrated strong internal consistency in past work (range of α coefficients: 0.861 to 0.934) and have been successfully used to assess motivation for using cannabis (Chabrol, Ducongé, Casas, Roura, & Carey, 2005). Internal consistency was good for all subscales in the current study (enhancement: α = 0.87; social: α = 0.88; conformity: α = 0.88; expansion: α = 0.91; coping: α = 0.89).

The Core Alcohol and Drug Survey (CADS) (Presley, Meilman, & Lyerla, 1994).

The CADS is a self-report measure designed to assess the substance use attitudes, patterns, and demographic information in a college setting. The past-month frequency of use of cannabis was measured through responding to the question: “During the past 30 days on how many days did you have used cannabis?” Response choices included: 0= 0 days, 1= 1-2 days, 2= 3-5 days, 3= 6-9 days, 4= 10-19 days, 5= 20-29 days, 6= All 30 days. Further, as a part of this questionnaire, participants responded to the question “within the last year about how often have you used tobacco?” Response choices included: 0= Did not use, 1= Once/year, 2= 6 times/year, 3= Once/month, 4= Twice/month, 5= Once/week, 6= 3 times/week, 7= 5 times/week, 8= Every day. A dichotomous variable was created for smoking status due to the low base rate of smoking in the current sample (use = 1 or no use = 0).1

The Alcohol Use Disorders Identification Test (AUDIT) (Saunders, Aasland, Babor, De la Fuente, & Grant, 1993).

AUDIT is a 10-item self-report measure designed to assess for problematic alcohol use. Questions (e.g., “How often do you have a drink containing alcohol”) are rated on various scales from 0 (“never”) to 4 (“4 or more times a week”). The items are summed to a total score as well as the three subscales (e.g., consumption). The AUDIT has strong psychometric properties, including reliability and validity (Babor, de la Fuente, Saunders, & Grant, 2001; Saunders et al., 1993). The AUDIT-consumption total score was used as a measure of problematic alcohol use (α = 0.82).

Inventory of Depression and Anxiety Symptoms (IDAS) (Watson et al., 2007).

The IDAS is a 64-item self-report measure used to assess anxiety and depressive symptoms, rated on a 5-point Likert scale from 1 (Not at all) to 5 (Extremely). The scale yields 10 specific symptom scales (Suicidality, Lassitude, Insomnia, Appetite Loss, Appetite Gain, Ill Temper, Well-Being, Panic, Social Anxiety, and Traumatic Intrusions), as well as 2 global factors (General depression and Dysphoria). For the current study, the General Depression (Cronbach’s α= 0.92), Panic (Cronbach’s α= 0.93), and Social Anxiety (Cronbach’s α= 0.91) specific symptom scales were used.

Data analysis

Analyses were conducted using SPSS version 24. After running the bivariate correlations between the obsessive-compulsive symptoms and cannabis outcome variables (risky cannabis use, cannabis use problems, and average quantity of cannabis use per occasion), multiple mediation analyses were conducted for the observed significant correlations using the PROCESS macro (Hayes, 2016). In the first step, multiple mediation models were run with obsessive-compulsive symptoms as the predictor, the five cannabis use motives as mediators, and the cannabis outcome variable as the dependent variable. The multiple mediation model was adjusted for problematic alcohol use and smoking status. At the second step, the same multiple mediation models were repeated with additional covariates, including depressive, panic, and social anxiety symptoms. Both direct and total effects for each model were reported. To detect the significance of the indirect effects, bootstrapping with 10,000 bootstrap re-samplings was conducted. Bootstrapping estimates the sampling distribution of an estimator based on re-sampling with replacement from the data set, which creates an empirically generated sampling distribution (Mooney, & Duval, 1993). A bootstrapped confidence interval that does not include zero indicates a statistically significant indirect effect (MacKinnon, Lockwood, & Williams, 2004). Effect sizes were calculated using completely standardized indirect effects (CSIE) (Preacher & Kelley, 2011). Little’s Missing Completely at Random (MCAR) test revealed a non-significant result, suggesting that the data were missing at random (p = 0.89). Analyses were conducted using pairwise deletion for missing data with 10 to 12% missing across models. Hypothesizing small to medium indirect effects and using Monte Carlo simulation methods (Thoemmes, MacKinnon, & Reiser, 2010), the power of the multiple mediation tests before controlling for anxiety and depressive symptoms was satisfactory (>.8).

Results

Descriptive data

Descriptive statistics and correlations between variables are shown in Table 1. Of note, all cannabis use motive scores were significantly correlated with obsessive-compulsive symptoms (rs ranging from .16 to .31). Obsessive-compulsive symptoms were significantly correlated with risky cannabis use (r=.19), but not cannabis use problems or the average quantity of cannabis used per occasion. Further, most of cannabis use motives were correlated with risky cannabis use, cannabis use problems, and the average quantity of cannabis used per occasion, as well as with each other.

Table 1.

Bivariate correlations and descriptive statistics.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
1. Obsessive-compulsive symptoms 1 .19* .12 .13 .16* .29** .31** .26**. 26** 0.12 0.03 .47** .42** .40**
2. Risky cannabis use 1 .39** .36** .39** 0.05 .43** .39** .39** 0.13 .25** .20* .29** .22**
3. Cannabis use problems 1 .16 0.11 .32** .28** .20* .21* .34** .25** .29** .28** .22**
4. Cannabis quantity 1 .34** 0.04 .22** .33** .25** 0.05 .20* 0.02 0.16 0.13
5. Enhancement 1 .02 .53** .59** .55** 0.06 −0.02 0.14 0.09 .19*
6. Conformity 1 .21** .40** .21** .17* 0.04 .25** .29** .17*
7. Coping 1 .66** .60** 0.01 −0.001 .34** .22** .34**
8. Social 1 .55** 0.15 −0.01 .21* .17* .24**
9. Expansion 1 0.12 0.01 0.09 0.12 .22**
10. Problematic alcohol use 1 .26** .33** .24** .29**
11. Smoking 1 .13 .25** .18*
12. Depression 1 .68** .70**
13. Panic 1 .73**
14. Social Anxiety 1
Mean 15.71 7.56 3.67 2.78 11.41 6.62 7.44 9.16 9.11 7.92 .32 46.59 13.37 10.22
SD 13.25 7.18 4.01 2.01 4.10 2.56 3.29 3.58 4.12 6.02 .47 15.70 6.52 4.99
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Note:

*

indicates p < 0.05, and

**

indicated p < 0.01.

Alcohol: Problematic alcohol use per the Alcohol Use Disorders Identification Test ; Smoking: Past year smoking status per the Alcohol, Smoking and Substance Involvement Screening Test; 3. Depression, Panic, Social Anxiety: Depressive, panic, and social anxiety symptoms per the Inventory of Depression and Anxiety Symptoms (IDAS); Enhancement, Conformity, Expansion, Coping, and Social: Cannabis use motives per Marijuana Motives Measure; Risky cannabis use: Risky cannabis use per the Alcohol, Smoking and Substance Involvement Screening Test; Cannabis use problems: Cannabis use problems per Marijuana Problems Scale. Cannabis quantity: Average quantity of cannabis use per occasion.

Mediation analysis

Risky Cannabis Use

In predicting risky cannabis use, there was a significant total effect of obsessive-compulsive symptoms (b = .10, SE = .04, p =.03). Additionally, there was a significant indirect effect of obsessive-compulsive symptoms through coping motives (b = .04, SE = .02, 95% Bootstrapped CI [.003, .10], CSIE = .07) for risky cannabis use after controlling for alcohol use and smoking status. The direct effect of obsessive-compulsive symptoms in relation to risky cannabis use after introducing the mediators to the model was not significant (b = .02, SE = .04, p =.62). After running the models adjusted for depressive, panic, and social anxiety symptoms none of the hypothesized indirect effects of obsessive-compulsive symptoms on risky cannabis use through cannabis motives were significant (See Table 2 for full mediation results and Figure 2 for standardized beta coefficients). 2

Table 2.

Multiple mediation model for Risky Cannabis Use adjusted for problematic alcohol use and smoking status.

Model b SE t p LLCI ULCI
OCD→Enhancement (a1) .05 .03 1.7 .10 −.01 .09
OCD →Conformity (a2) .05 .02 3.12 .002 .02 .08
OCD→ Coping (a3) .08 .02 3.83 .006 .04 .12
OCD → Social (a4) .07 .02 2.81 .01 .02 .11
OCD → Expansion (a5) .08 .03 3.02 .003 .02 .13
Enhancement → Risky Cannabis Use (b1) .18 .17 1.07 .28 −.16 .52
Conformity → Risky Cannabis Use (b2) −.27 .23 −1.16 .24 −.74 .19
Coping → Risky Cannabis Use (b3) .49 .13 2.09 .03 .03 .96
Social → Risky Cannabis Use (b4) .31 .23 1.38 .16 −.14 .77
Expansion → Risky Cannabis Use (b5) .20 .16 1.20 .23 −.13 .53
OCD → Risky Cannabis Use (c) .10 .05 2.15 .03 .01 .18
OCD → Risky Cannabis Use (c’) .02 .04 .49 .62 −.07 .10
OCD → Enhancement → Risky Cannabis Use (a1*b1) .01 .01 - - −.003 .04
OCD → Conformity → Risky Cannabis Use (a2*b2) −.01 .02 - - −.06 .01
OCD → Coping → Risky Cannabis Use (a3*b3) .04 .02 - - .003 .10
OCD → Social → Risky Cannabis Use (a4*b4) .02 .01 - - −.01 .06
OCD → Expansion → Risky Cannabis Use (a5*b5) .02 .02 - - −.004 .08
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Note. a Effects of X on M; b effects of M on Y; c total effect of X on Y; c’ direct effect of X on Yi controlling for M; Path a is consistent in all models; therefore, it presented only in model 1. Obsessive-compulsive symptoms is the predictor; Enhancement, Conformity, Expansion, Coping, and Social are the mediator variables; Risky cannabis use per the Alcohol, Cannabis use problems, and Cannabis Quantity is the outcome variable. LLCI lower bound of a 95% confidence interval; ULCI upper bound; → effects. The indirect effect (a*b) is the product of path a and path b. Bolded values are statistically significant. Problematic alcohol use and smoking status were covariates.

Figure 2.

Figure 2.

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Multiple mediation model for Risky Cannabis Use adjusted for problematic alcohol use and smoking status: Coping motives as explanatory variable.

*Numbers represent the standardized beta coefficients and related errors for each path. The significant indiret paths are bolded.

Discussion

The empirical evidence regarding the mechanisms underlying the association between obsessive-compulsive symptoms and cannabis misuse is limited. The present investigation sought to address this clinically relevant gap in the extant literature by exploring the simultaneous role of five cannabis use motives in the relation between obsessive-compulsive symptoms and different indices of cannabis misuse among a sample of young adults. Results indicated a positive correlation between obsessive-compulsive symptoms and risky cannabis use. The subsequent multiple mediation analysis demonstrated a significant indirect effect of coping motives in the relationship between obsessive-compulsive symptoms and risky cannabis use over the effects of other cannabis use motives. Moreover, this effect was evident above the variance accounted for by problematic alcohol use and smoking status of the participants. The effect sizes for the explanatory role of coping motives was small to medium size (CSIE=.07). After controlling for the variance in these relationships that is accounted for by anxiety and depressive symptoms, this indirect effect became non-significant. However, given concerns about the relevance of controlling for anxiety and depressive symptoms in models including obsessive-compulsive symptoms in the context of these symptoms being implicated as an essential component of OCD psychopathology (Jefferies, Laws, Fineberg, & Disorders, 2012; Moore, & Howell, 2017), the theoretical and clinical implications of the explanatory role of coping motives in the relationship between obsessive-compulsive symptoms and risky cannabis use before controlling for anxiety and depressive symptoms are still worth consideration. Indeed, this finding is broadly in line with previous work documenting the role of internally and externally focused negative reinforcement processes (versus positive reinforcement processes such as enhancement motives) in the relationship between emotional distress problems and cannabis misuse (Mitchell, Zvolensky, Marshall, Bonn-Miller, & Vujanovic, 2007). Specifically, psychological distress associated with the experience of emotional problems contributes to the development of motives oriented toward reducing the unpleasant experience of such distress (Spradlin, Mauzay, & Cuttler, 2017). From this perspective, the unique explanatory role of negatively reinforcing coping motives for the obsessive-compulsive symptoms-risky cannabis use relationship could be conceptualized in the context of the prominence of efforts to reduce psychological distress associated with the experience of these symptoms, compared to enhancement efforts (Zvolensky, et al, 2007).

The present findings add to the existing evidence regarding the motive-based explanatory factors of OCD-cannabis misuse linkage and extend it to a more comprehensive context with considerations for different types of cannabis use motives. The non-significant explanatory role of coping motives after adjusting for the effects of the anxiety and depressive symptoms were not in line with the only other examination of these mechanistic pathways that has demonstrated that the coping motives explain the relationship between obsessive-compulsive symptoms and cannabis use symptoms/problems even after controlling for anxiety and depression (Spradlin et al., 2017). In addition to the concerns indicated above regarding the clinical value of controlling for anxiety and depressive symptoms in models including obsessive-compulsive symptoms (Jefferies et al., 2012), it should be also mentioned that the current study sample showed lower rates of cannabis misuse (less than 50% of the participants compared to over 80% in the Spradlin et al. study reported past month use of cannabis). Such differential rates of cannabis use across these samples could be due to reasons such as the relatively diverse ethno-racial composition of the current study sample compared to Spradlin et al. (Buckner, Shah, Dean, & Zvolensky, 2016; Wu et al., 2013). Further the indirect effect of obsessive-compulsive symptoms on cannabis outcomes after controlling for the variance accounted for by the anxiety and depressive symptoms may be too small to be evident in the current sample. Future research needs to further evaluate these relations in clinical samples.

Clinically, the present findings suggest that it may be helpful to address coping motives for cannabis use among college students reporting co-occurring obsessive-compulsive symptoms to reduce risky cannabis use. Specifically, it may be advisable to develop tailored psychosocial interventions that can modulate motives concerning alleviating the emotional distress (i.e., tension-reduction) in young adults who endorse higher levels of obsessive-compulsive symptoms. For example, intervention strategies such as motivational interviewing and cognitive-behavioral techniques have shown promise in reducing negative reinforcement motives of cannabis use ( Blevins, Banes, Stephens, Walker, & Roffman, 2016). Alternatively, mindfulness-based interventions as a standalone treatment modality or in combination with CBT could help to reduce the individual’s level of emotional distress and potentially reduce the coping-oriented motives (i.e., self-mediation) for cannabis use (Buckner, Walukevich, Lemke, & Jeffries, 2018; Hale, Strauss, & Taylor, 2013). The development of specialized treatments to specifically target coping motives in the context of obsessive-compulsive symptoms may be particularly effective in individuals with comorbid OCD and cannabis use disorder.

The current study has several limitations that warrant consideration. First, the data collected were cross-sectional, preventing determination of temporal precedence and causality. Longitudinal investigations should be performed to further elucidate the directionality of the observed relationships. Second, although the sample reported experiencing obsessive-compulsive symptoms, they were not a clinical sample with OCD diagnosis. Future work should replicate these findings in a population with clinical OCD. Additionally, the current study focused on obsessive-compulsive symptomatology among young adults, and it may be useful to examine whether the findings are generalizable to other age ranges. Third, the present sample was largely female, and future work should include samples with relatively more balanced gender distributions. This issue is particularly important in the context of gender differences in both affective and cannabis use disorders, as well as the age of onset of obsessive-compulsive symptoms and substance use comorbidities in OCD (Bruce et al., 2005; Khan et al., 2013; Lochner et al., 2004). Fourth, the current sample did not report high levels of cannabis misuse, which is typical for college samples. Future work needs to examine these relationships among populations with higher rates of cannabis misuse. Fifth, participants’ response on the visually depicted index of the quantity of cannabis smoked in the MHSQ could have been affected by their differential subjective interpretations. Future work should use an objective measure of quantity of use. Finally, future research should examine the possible influence of the method of use (i.e., smoking, eating or vaping) on the observed findings.

Conclusions

Overall, the current study provides novel empirical evidence that coping motives may help to explain the relationship between obsessive-compulsive symptoms and cannabis use problems among a diverse sample of college students after accounting for the role of other cannabis use motives as well as other common misused substances among young adults. Future work is needed to explore the extent to which individuals with obsessive-compulsive symptoms may benefit from targeted psychosocial strategies aimed at decreasing these motives, with the goal of improving obsessive-compulsive symptoms-related cannabis misuse outcome.

Acknowledgments:

The authors wish to thank Angelina Mayorga who helped with data collection.

Footnotes

Disclosure of interest: The authors report no conflict of interest.

Declarations of interest: none

1

We re-run the analyses using the continuous measure of tobacco use. The pattern of the findings stayed the same using this measure. These results can be obtained by contacting Dr. Bakhshaie.

2

We also ran the analyses controlling for “duration of use.” The pattern of the indirect effects remained the same. These results can be obtained by contacting Dr. Bakhshaie.

Contributor Information

Jafar Bakhshaie, Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA

Eric A. Storch, Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA

Nhan Tran, Department of Psychology, University of Houston, Houston, TX, USA

Michael J. Zvolensky, Department of Psychology, University of Houston, Houston, TX, USA; Department of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; HEALTH Institute, University of Houston, Houston, TX, USA

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