Abstract
Objective:
Co-use of alcohol and marijuana has increased among college students, though comparisons among simultaneous (i.e., use of both substances such that effects overlap), dual (i.e., use of both substances within a similar time period but without overlapping effects), and marijuana-only use are limited. This study aimed to understand differences between simultaneous, dual, and marijuana-only users on marijuana use rates, consequences, and context of use in a multi-university study.
Method:
College students (N=4,764; Mage=19.9 years) who were mainly female (70.6%) and White (67.9%) completed an online survey. The Marijuana Use Grid captured marijuana use quantity/frequency, and the Brief Marijuana Consequences Questionnaire and the Cannabis Use Disorders Identification Test-Revised assessed problem use. Location, method of consumption, and social context of use also were assessed.
Results:
Fifty-five percent of the sample endorsed lifetime use of alcohol and marijuana. Of these students, 36.1% endorsed past-month simultaneous use, 10.8% endorsed past-month dual use, and 6.4% endorsed past-month marijuana-only use. Simultaneous users reported more marijuana use and problems than dual users. Marijuana-only users did not differ from simultaneous users on marijuana use indices, though they reported greater use than dual users as well. Simultaneous users used marijuana in plant form, at parties, and with unknown others a greater percentage of the time than dual users, while dual users used edibles and ingested marijuana a greater percentage of the time.
Conclusions:
Given their greater levels of marijuana use and marijuana-related problems, screening and interventions for simultaneous alcohol-marijuana use is needed in college students.
Keywords: college students, substance use, alcohol, marijuana, simultaneous use
Introduction
While alcohol and marijuana use remain prevalent among college students (Schulenberg et al., 2019), research has begun to examine the effects of two types of co-use of alcohol and marijuana: dual use (i.e., use of both substances within a similar time period [month, year]) and simultaneous use (i.e., use of both substances at the same use time so that effects overlap). A recent review suggests that co-use (which encompasses both dual and simultaneous use) is associated with higher rates of mental health disorders, including alcohol and marijuana use disorders, while also negatively impacting treatment effects for both substances (Yurasek et al., 2017). Nationally representative U.S. data indicate that past year co-use of alcohol and marijuana in college students has increased from 17.1% in 2002 to 24.0% in 2018, for a linearized annual increase of 0.6% (McCabe et al., in press). Thus, further examination of co-use types among college students on use patterns, consequences, and context of use is needed.
In particular, comparative examinations between college students who engage in co-use and those who engage in marijuana-only use are lacking. There is good evidence that co-use conveys greater risk of increased alcohol consumption and negative consequences compared to alcohol-only use (e.g., Cummings et al., 2019; Lee et al., 2020; Linden-Carmichael et al., 2019). Fewer studies have examined comparable metrics against marijuana-only use. Those that include comparisons to marijuana-only days sampled students who report co-use, finding that days in which simultaneous use occurred included greater levels of marijuana use and consequences compared to marijuana-only days (Lee et al., 2017; Linden-Carmichael et al., 2020; Sokolovsky et al., 2010). Few studies have recruited marijuana-only users as a comparison group, and those that have are apt to drop that comparison due to small sample size (e.g., Jackson et al., 2020). Thus, examination of marijuana-related outcomes between students engaging in co-use (both dual and simultaneous use) and those who only use marijuana is warranted.
Further, several contextual factors (e.g., environment, proximal others) may influence students’ decision to engage in simultaneous use. Most research to date on contextual determinants of simultaneous use among college students has focused on alcohol use and social norms, finding that simultaneous use is positively associated with perceived peer and friend norms for both alcohol use and simultaneous use (Linden-Carmichael et al., 2019; White et al., 2019). Additional research with adolescents (Lipperman-Kreda et al., 2017) and young adults (ages 18–30; Lipperman-Kreda et al., 2018) finds that simultaneous use is more likely when parental supervision is low and when many underage drinkers or intoxicated others are present, and less likely to occur at bars and restaurants. This may generalize to college students being more likely to engage in simultaneous use at large social gatherings, such as parties; yet, this is presently unknown. Contextual research on college student marijuana use finds that students most frequently report smoking marijuana, followed by edible use (Wang et al., 2019), and are more likely to use with others than alone (Phillips et al., 2018), though marijuana-only use was not separated from dual use. Moreover, researchers have drawn attention to the heterogeneity in methods of consumption (e.g., blunt, bong, dabbing, with and without tobacco) which has been understudied when examining preference rates among marijuana users (Freeman & Lorenzetti, 2020).
The present study addresses noted gaps in the literature on simultaneous alcohol and marijuana use by comparing marijuana-only users to co-users on several marijuana-use outcomes, and examining relations with several contextual factors (e.g., environment, type and method of use). Specifically, we examined use status (i.e., past 30-day marijuana-only use, dual use, simultaneous use) as a predictor on variables of marijuana use (including type of product and method of consumption), related consequences, consumption location and context, planned use, and best friend’s marijuana use quantity and frequency. In line with prior research, we expected dual and simultaneous users to report greater marijuana use, related problems, and best friend’s use than marijuana-only users. We further expected simultaneous users to be higher on all outcomes than dual users. Analyses comparing use across context were largely exploratory.
Method
Participants and Procedures
College students (N=4,764) were recruited to participate in an online survey from Psychology Department Participant Pools at seven universities across six U.S. states (standardized across sites; Colorado, New Mexico, New York, Virginia [2 sites], Texas, and Wyoming) between Fall 2019 and Spring 2020. Demographic information for the total sample and across sites is reported in Table 1. To minimize burden (i.e., keep survey completion time to an hour), we utilized a planned missing data design (i.e., matrix sampling; Graham et al., 2006; Schafer, 1997), used in other large multi-site college student studies (e.g., Bravo et al., 2018). Participants completed a battery of core measures on substance use and mental health, plus a random sample of 10 measures from a larger pool (22 total measures) that assessed personality, cognitions, and other health behaviors. Participants received research credit upon completion. This study was approved by the University of Wyoming IRB using a single-site IRB model.
Table 1.
General Demographics.
| Total | UWy | W&M | CSU | SUNY-Albany | UNM | Texas State | ODU | |
|---|---|---|---|---|---|---|---|---|
| Total Sample Size | 4764 | 629 | 662 | 577 | 609 | 499 | 919 | 869 |
| Age (Mean, SD) | 19.90 (3.39) | 19.91 (3.23) | 19.10 (1.18) | 19.61 (2.14) | 19.28 (1.51) | 20.22 (4.76) | 19.53 (2.01) | 21.31 (5.44) |
| Sex at Birth | ||||||||
| Male | 29.1% | 32.9% | 34.0% | 30.0% | 34.5% | 29.1% | 24.7% | 22.8% |
| Female | 70.6% | 66.9% | 65.7% | 69.7% | 65.2% | 70.7% | 75.1% | 76.6% |
| Did Not Wish to Answer | 0.3% | 0.2% | 0.3% | 0.3% | 0.3% | 0.2% | 0.2% | 0.6% |
| Race/Ethnicity | ||||||||
| American Indian/Alaska Native | 2.6% | 1.3% | 0.9% | 2.4% | 1.8% | 4.2% | 4.4% | 2.5% |
| Asian | 10.1% | 3.8% | 22.8% | 9.9% | 13.6% | 9.8% | 5.0% | 8.2% |
| Black/African American | 17.7% | 3.5% | 10.6% | 4.9% | 25.1% | 5.2% | 17.6% | 44.2% |
| Native Hawaiian/Pacific Islander | 0.9% | 1.1% | 0.5% | 0.7% | 0.8% | 1.0% | 0.4% | 1.8% |
| White | 67.9% | 93.8% | 69.2% | 81.8% | 53.2% | 67.9% | 69.5% | 47.3% |
| Middle Eastern/North African | 1.5% | 0.0% | 2.7% | 2.8% | 2.0% | 1.6% | 0.5% | 1.4% |
| Other | 6.8% | 1.7% | 3.3% | 4.3% | 10.0% | 15.2% | 8.8% | 5.8% |
| Ethnicity – Hispanic/Latino | ||||||||
| No, Not Hispanic/Latino | 76.1% | 87.9% | 89.3% | 82.8% | 80.6% | 43.5% | 56.4% | 89.5% |
| Yes, Mexican | 15.3% | 8.6% | 2.0% | 12.3% | 2.6% | 40.7% | 37.0% | 3.6% |
| Yes, Puerto Rican | 2.3% | 0.5% | 1.4% | 1.0% | 6.7% | 1.2% | 1.7% | 3.3% |
| Yes, Cuban | 0.6% | 0.5% | 0.9% | 0.5% | 1.0% | 0.2% | 0.5% | 0.6% |
| Yes, Other | 6.5% | 2.7% | 6.5% | 3.8% | 11.8% | 16.2% | 4.6% | 3.6% |
| Education | ||||||||
| Freshman | 48.2% | 46.1% | 54.4% | 50.4% | 46.3% | 52.3% | 50.4% | 40.0% |
| Sophomore | 25.1% | 23.7% | 28.2% | 27.4% | 29.1% | 19.6% | 26.9% | 20.8% |
| Junior | 16.2% | 17.5% | 11.8% | 14.0% | 15.3% | 15.2% | 15.8% | 21.6% |
| Senior | 10.3% | 12.4% | 5.4% | 8.0% | 9.2% | 12.8% | 6.7% | 17.3% |
| Missing | 0.2% | 0.3% | 0.2% | 0.2% | 0.2% | 0.0% | 0.2% | 0.2% |
| Survey Completion Date | ||||||||
| Pre COVID-19 Announcement | 62.1% | 80.1% | 64.2% | 70.7% | 42.7% | 85.2% | 43.2% | 61.9% |
| Post COVID-19 Announcement | 37.9% | 19.9% | 35.8% | 29.3% | 57.3% | 14.8% | 56.8% | 38.1% |
Note. Race/ethnicity were assessed with separate checkbox items (i.e., could select multiple options). COVID-19 Announcement = when schools emailed students indicating that they will not return back to campus and classes are moved to online. UWy = University of Wyoming; W&M = William & Mary; CSU = Colorado State University; SUNY-Albany = State University of New York at Albany; UNM = University of New Mexico; Texas State = Texas State University; ODU = Old Dominion University.
Measures
Marijuana Use Indicators
Marijuana use was broken down into several indicators: past 30-day use frequency, typical frequency of use, and typical quantity of use. Participants were presented with visual guides showing different amounts of marijuana in grams. Typical marijuana use frequency and quantity were assessed using a grid measure in which each day of the week was broken down into six 4-hour blocks of time (12a-4a, 4a-8a, 8a-12p, etc.) and participants were asked to report at which times they used marijuana during a “typical week” in the past 30 days, as well as the quantity of grams consumed during that time block (Pearson & Marijuana Outcomes Study Team, 2020). We calculated typical frequency of marijuana use by summing the total number of time blocks for which they reported using during the typical week (ranges: 0–42). We calculated typical quantity of marijuana use by summing the total number of grams consumed across time blocks during the typical week (quantity estimates >3SDs above the mean were Winsorized). We also assessed age of first use, best friend frequency of use (response options: 0 = never to 6 = daily or almost daily), and best friend typical quantity of use (based on grams per week).
Marijuana Use Context
Marijuana use context was broken down into several indicators: type of product used (plant, edibles, concentrates, others), ways of consumption (smoked in joint/blunt without tobacco, smoked in joint/blunt with tobacco, smoked in bong/water pipe without tobacco, smoked in bong/water pipe with tobacco, eaten/cooked, used in a vaporizer), consumption location (at their home, at a friend’s home, at a stranger’s home, outside, in a car, at a party, other), consumption context (alone, with friends, with family, with strangers, and other), and planned use (percentage of time they had made a plan to use marijuana before using). For all of these indicators, we used a constant sum approach in which students had to calculate the percentage of the time they used marijuana in the various ways assessed (total had to equal 100%) during the past month. Scores on these variables represent an average percent of the time each method is used across all participants rather than number of participants endorsing each category.
Marijuana-Related Problems and Misuse
Past 30-day marijuana-related problems were assessed using the 21-item Brief Marijuana Consequences Questionnaire (B-MACQ; Simons et al., 2012). We summed all items to create a composite consequences score (M = 4.26; SD = 4.61; α = .89). Marijuana misuse was assessed using the 8-item Cannabis Use Disorders Identification Test-Revised (CUDIT-R; Adamson et al., 2010). We summed items to create a composite misuse score (M = 6.29; SD = 6.40; α = .86).
Dual and Simultaneous Use
Participants indicated whether they had ever used alcohol and marijuana, and if so, if they engaged in past-month use. To assess simultaneous use, students reported how many days in the last month their alcohol and marijuana use occurred during the same use session.
Statistical Analyses
To test study aims, we compared marijuana outcomes on distinct past 30-day college student use statuses: marijuana-only use vs. dual-use, simultaneous use vs. marijuana-only use, and dual use vs. simultaneous use. All marijuana outcomes were most appropriately treated as count variables because either, they were counts by design (e.g., number of using days), counts of items endorsed (e.g., number of consequences), or were highly skewed and overdispersed (e.g., percentages derived from a constant sum). A recent simulation study comparing a number of commonly used statistical approaches to analyzing count data in the addiction field found that Quasi-Poisson (QP) regression models outperformed all other models in the ability to appropriately model count data across a range of distributional properties (Baggio et al., 2018). Thus, QP regressions were run in the statistical software R (R Core Team, 2020), using the MASS package (Venables & Ripley, 2002). The QP regression models also included the following covariates: age, sex at birth, year in school, and COVID-19 school announcement (i.e., whether data collection occurred before or after classes were moved online due to COVID-19). For CUDIT-R and B-MACQ total scores, typical marijuana quantity consumption was also added as a covariate. Because QP regression models are a more general version of generalized linear regression model that still use a log link function, unstandardized regression coefficients can be exponentiated to calculate odds ratios, which are interpreted as the predicted percent change in the count of the outcome for a unit change in the predictor. Given our large sample size (i.e., statistical power) and the number of models tested, significant results for all analyses were determined by 99% confidence intervals for the odds ratio estimates that did not contain one.
Results
Within the total sample, 88% (n = 4197) of students reported consuming alcohol, 56.3% (n = 2,682) reported using marijuana, and 55% (n = 2,631) reported using alcohol and marijuana at least once in their lifetime. Regarding past-month use among co-users (n = 2,631), 11.7% (n = 307) reported no alcohol or marijuana use, 34.1% (n = 897) reported only alcohol use, 6.4% (n = 169) reported only marijuana use, and 47.8% (n = 1,258) reported both alcohol and marijuana use. Among those reporting past 30-day use of alcohol and marijuana (n = 1,258), 23.1% (n = 285) denied using alcohol and marijuana simultaneously (labeled as dual users) and 76.9% (n = 950) reported simultaneous use (labeled as simultaneous users) at least once in the past 30 days (Mean number of days = 7.27, SD = 8.10). Of note, 27.2% of marijuana-only users, 15.4% of dual users, and 28.1% of simultaneous users exceeded the cutoff for hazardous marijuana use (CUDIT-R score > 12; Adamson et al., 2010).
Marijuana-Only vs Dual Use
The QP regression analyses comparing those who report marijuana-only use (n = 169) to those who report dual use (n = 285) showed a number of significant differences (see Table 2). Specifically, past 30-day use frequency was significantly higher for marijuana-only users compared to dual users. Similar patterns were seen on the following outcomes: typical quantity, typical frequency, and best friend typical frequency. Additionally, those who reported marijuana-only use reported smoking marijuana in a joint or a blunt mixed with tobacco a greater percentage of the time than those who reported dual use. In contrast, those who reported dual use endorsed ingesting marijuana a greater percentage of the time than those who used only marijuana. In terms of use contexts, those who reported dual use endorsed using with friends on a higher percentage of occasions relative to those who reported only using marijuana. Conversely, those who reported marijuana-only use reported using with people they do not know a greater percentage of the time than those who reported dual use. Finally, those who reported only using marijuana reported significantly higher CUDIT-R scores than those who reported dual use.
Table 2.
Quasi-Poisson regression models of marijuana use patterns among those reporting 30-day marijuana-only use vs. alcohol and marijuana dual use.
| Descriptive Statistics | Model Results (0 = marijuana only; 1 = dual use) | |||||||
|---|---|---|---|---|---|---|---|---|
| Marijuana only (n = 169) | Dual use (n = 285) | CIs | ||||||
| M | SD | M | SD | Estimate | OR | 0.5% | 99.5% | |
| Marijuana Use Indicators | ||||||||
| Age of First Use | 16.40 | 2.03 | 16.78 | 5.43 | 0.02 | 1.02 | 0.96 | 1.10 |
| Use Frequency Last 30 Days | 12.70 | 11.41 | 6.94 | 8.59 | −0.59 | 0.56 | 0.43 | 0.72 |
| Typical Quantity (grams) | 7.52 | 11.51 | 3.31 | 6.39 | −0.89 | 0.41 | 0.26 | 0.64 |
| Typical Frequency | 7.93 | 8.84 | 3.69 | 4.92 | −0.81 | 0.45 | 0.32 | 0.61 |
| Best Friend Typical Frequency | 4.72 | 2.23 | 4.07 | 2.18 | −0.15 | 0.86 | 0.76 | 0.97 |
| Best Friend Typical Quantity (grams) | 3.97 | 5.38 | 2.68 | 4.74 | −0.41 | 0.67 | 0.44 | 1.02 |
| Type of Product | ||||||||
| Plant | 68.45 | 39.72 | 55.99 | 43.32 | −0.21 | 0.81 | 0.68 | 0.96 |
| Edibles | 10.92 | 25.00 | 20.19 | 34.54 | 0.62 | 1.86 | 1.11 | 3.25 |
| Concentrates | 15.18 | 29.76 | 17.07 | 32.03 | 0.12 | 1.13 | 0.70 | 1.87 |
| Other | 5.45 | 21.83 | 6.75 | 24.45 | 0.30 | 1.36 | 0.50 | 4.22 |
| Methods of Consumptions | ||||||||
| Smoked in joint/blunt without tobacco | 26.54 | 35.50 | 28.94 | 38.29 | 0.09 | 1.09 | 0.78 | 1.54 |
| Smoked in joint/blunt with tobacco | 12.32 | 27.53 | 5.86 | 19.83 | −0.72 | 0.49 | 0.25 | 0.96 |
| Smoked in bong/water pipe without tobacco | 29.74 | 38.82 | 25.27 | 36.65 | −0.19 | 0.83 | 0.58 | 1.18 |
| Smoked in bong/water pipe with tobacco | 4.94 | 18.82 | 3.09 | 14.59 | −0.45 | 0.64 | 0.21 | 1.94 |
| Eaten/cooked | 9.04 | 24.03 | 17.72 | 33.19 | 0.75 | 2.11 | 1.18 | 4.05 |
| Used in a vaporizer | 17.42 | 33.21 | 19.12 | 34.17 | 0.08 | 1.08 | 0.68 | 1.75 |
| Consumption Location | ||||||||
| At my home | 47.98 | 42.42 | 43.15 | 43.84 | −0.10 | 0.90 | 0.71 | 1.16 |
| At a friend’s home | 25.23 | 36.09 | 34.06 | 41.47 | 0.26 | 1.30 | 0.93 | 1.84 |
| At a stranger’s home | 1.19 | 8.73 | 0.51 | 3.82 | −0.99 | 0.37 | 0.08 | 1.62 |
| Outside | 10.46 | 24.46 | 9.10 | 24.52 | −0.10 | 0.90 | 0.48 | 1.74 |
| In a car | 10.73 | 23.23 | 7.22 | 20.37 | −0.46 | 0.63 | 0.35 | 1.17 |
| At a party | 2.15 | 7.58 | 2.95 | 11.48 | 0.43 | 1.55 | 0.64 | 4.15 |
| Other | 2.26 | 13.89 | 3.35 | 17.11 | 0.50 | 1.65 | 0.43 | 8.56 |
| Consumption Context | ||||||||
| Alone | 31.89 | 38.42 | 20.62 | 34.71 | −0.36 | 0.70 | 0.49 | 1.00 |
| With friends | 56.08 | 41.95 | 71.98 | 39.45 | 0.21 | 1.23 | 1.05 | 1.45 |
| With family | 8.65 | 23.24 | 5.53 | 20.98 | −0.47 | 0.63 | 0.28 | 1.42 |
| With people I don’t know | 0.98 | 7.87 | 0.16 | 1.22 | −1.72 | 0.18 | 0.02 | 0.87 |
| Other | 2.40 | 15.11 | 2.42 | 15.29 | 0.13 | 1.14 | 0.23 | 7.26 |
| Planned vs. Unplanned Use | ||||||||
| Planned Use | 64.54 | 41.40 | 67.58 | 41.50 | 0.05 | 1.05 | 0.89 | 1.23 |
| Consequences | ||||||||
| B-MACQ – Total Score (Range = 0 – 21) | 4.27 | 4.30 | 2.75 | 3.73 | −0.27 | 0.77 | 0.56 | 1.06 |
| CUDIT-R – Total Score (Range = 0 – 40) | 9.85 | 7.48 | 6.52 | 5.38 | −0.27 | 0.76 | 0.62 | 0.94 |
Note: Significant results are bolded and were determined via 99% CIs for the Odds Ratios that did not contain 1. Regression models controlled for age, sex at birth (0 = male, 1 = female), year in school, and COVID-19 school announcement (0 = survey taken prior to school in-person teaching closure; 1 = survey taken after school in-person teaching closure). For CUDIT-R and B-MACQ, typical marijuana quantity consumption was also added as a covariate. We calculated typical frequency of marijuana use by summing the total number of time blocks for which they reported using during the typical week (ranges: 0–42). Best friend frequency of use was assessed using a 7-point response scale (response options: 0 = never to 6 = daily or almost daily). For type of product used, ways of consumption, consumption location, consumption context, and planned use, we used a constant sum approach in which students had to calculate the percentage of the time they used marijuana in the various ways assessed (total had to equal 100%) during the past month. Scores on these variables represent an average percent of the time each method is used across all participants rather than number of participants endorsing each category.
Marijuana-Only vs Simultaneous Use
When comparing those who reported marijuana-only use to those who reported simultaneous use (n = 950), there were few differences (see Table 3). The differences were seen in consumption location and contexts. Specifically, individuals who reported marijuana-only use reported using in a car a greater percentage of the time than those who reported simultaneous use, whereas simultaneous users reported using at a party on a higher percentage of occasions than marijuana-only users. Finally, those who reported simultaneous use reported using with friends a greater percentage of the time than those who only use marijuana.
Table 3.
Quasi-Poisson regression models of marijuana use patterns among those reporting 30-day marijuana-only use vs. alcohol and marijuana simultaneous use.
| Descriptive Statistics | Model Results (0 = marijuana only; 1 = simultaneous use) | |||||||
|---|---|---|---|---|---|---|---|---|
| Marijuana only (n = 169) | Simultaneous use (n = 950) | CIs | ||||||
| M | SD | M | SD | Estimate | OR | 0.5% | 99.5% | |
| Marijuana Use Indicators | ||||||||
| Age of First Use | 16.40 | 2.03 | 16.11 | 2.00 | −0.02 | 0.98 | 0.95 | 1.00 |
| Use Frequency Last 30 Days | 12.70 | 11.41 | 12.93 | 10.86 | 0.03 | 1.03 | 0.86 | 1.24 |
| Typical Quantity (grams) | 7.52 | 11.51 | 7.60 | 10.78 | 0.03 | 1.03 | 0.74 | 1.46 |
| Typical Frequency | 7.93 | 8.84 | 7.53 | 7.96 | −0.05 | 0.95 | 0.75 | 1.22 |
| Best Friend Typical Frequency | 4.72 | 2.23 | 4.73 | 2.15 | 0.00 | 1.00 | 0.91 | 1.10 |
| Best Friend Typical Quantity (grams) | 3.97 | 5.38 | 3.45 | 4.65 | −0.15 | 0.86 | 0.65 | 1.17 |
| Type of Product | ||||||||
| Plant | 68.45 | 39.72 | 67.96 | 36.08 | −0.01 | 0.99 | 0.88 | 1.11 |
| Edibles | 10.92 | 25.00 | 10.71 | 22.21 | −0.01 | 0.99 | 0.64 | 1.60 |
| Concentrates | 15.18 | 29.76 | 17.89 | 29.83 | 0.16 | 1.18 | 0.81 | 1.77 |
| Other | 5.45 | 21.83 | 3.43 | 16.67 | −0.41 | 0.66 | 0.29 | 1.75 |
| Methods of Consumptions | ||||||||
| Smoked in joint/blunt without tobacco | 26.54 | 35.50 | 33.46 | 35.63 | 0.23 | 1.26 | 0.98 | 1.65 |
| Smoked in joint/blunt with tobacco | 12.32 | 27.53 | 8.06 | 21.14 | −0.43 | 0.65 | 0.41 | 1.09 |
| Smoked in bong/water pipe without tobacco | 29.74 | 38.82 | 31.03 | 35.50 | 0.03 | 1.03 | 0.80 | 1.34 |
| Smoked in bong/water pipe with tobacco | 4.94 | 18.82 | 3.62 | 13.79 | −0.30 | 0.74 | 0.36 | 1.67 |
| Eaten/cooked | 9.04 | 24.03 | 8.05 | 20.47 | −0.09 | 0.91 | 0.55 | 1.61 |
| Used in a vaporizer | 17.42 | 33.21 | 15.78 | 29.46 | −0.08 | 0.92 | 0.63 | 1.39 |
| Consumption Location | ||||||||
| At my home | 47.98 | 42.42 | 42.91 | 39.19 | −0.14 | 0.87 | 0.72 | 1.05 |
| At a friend’s home | 25.23 | 36.09 | 31.67 | 35.20 | 0.20 | 1.23 | 0.94 | 1.62 |
| At a stranger’s home | 1.19 | 8.73 | 1.42 | 7.97 | 0.25 | 1.29 | 0.40 | 6.58 |
| Outside | 10.46 | 24.46 | 9.87 | 22.89 | 0.05 | 1.06 | 0.66 | 1.78 |
| In a car | 10.73 | 23.23 | 6.11 | 15.55 | −0.56 | 0.57 | 0.37 | 0.90 |
| At a party | 2.15 | 7.58 | 6.63 | 16.12 | 1.13 | 3.09 | 1.49 | 7.84 |
| Other | 2.26 | 13.89 | 1.39 | 9.24 | −0.50 | 0.61 | 0.20 | 2.40 |
| Consumption Context | ||||||||
| Alone | 31.89 | 38.42 | 24.38 | 31.68 | −0.24 | 0.78 | 0.61 | 1.02 |
| With friends | 56.08 | 41.95 | 68.36 | 34.73 | 0.17 | 1.19 | 1.05 | 1.34 |
| With family | 8.65 | 23.24 | 4.81 | 16.33 | −0.50 | 0.61 | 0.34 | 1.14 |
| With people I don’t know | 0.98 | 7.87 | 1.30 | 6.31 | 0.28 | 1.32 | 0.44 | 5.97 |
| Other | 2.40 | 15.11 | 1.15 | 9.91 | −0.77 | 0.46 | 0.13 | 2.26 |
| Planned vs. Unplanned Use | ||||||||
| Planned Use | 64.54 | 41.40 | 71.00 | 37.28 | 0.09 | 1.10 | 0.97 | 1.24 |
| Consequences | ||||||||
| B-MACQ – Total Score (Range = 0 – 21) | 4.27 | 4.30 | 4.80 | 4.79 | 0.13 | 1.14 | 0.91 | 1.45 |
| CUDIT-R – Total Score (Range = 0 – 40) | 9.85 | 7.48 | 9.59 | 6.87 | −0.02 | 0.98 | 0.84 | 1.15 |
Note: Significant results are bolded and were determined via 99% CIs for the Odds Ratios that did not contain 1. Regression models controlled for age, sex at birth (0 = male, 1 = female), year in school, and COVID-19 school announcement (0 = survey taken prior to school in-person teaching closure; 1 = survey taken after school in-person teaching closure). For CUDIT-R and B-MACQ, typical marijuana quantity consumption was also added as a covariate. We calculated typical frequency of marijuana use by summing the total number of time blocks for which they reported using during the typical week (ranges: 0–42). Best friend frequency of use was assessed using a 7-point response scale (response options: 0 = never to 6 = daily or almost daily). For type of product used, ways of consumption, consumption location, consumption context, and planned use, we used a constant sum approach in which students had to calculate the percentage of the time they used marijuana in the various ways assessed (total had to equal 100%) during the past month. Scores on these variables represent an average percent of the time each method is used across all participants rather than number of participants endorsing each category.
Dual Use vs Simultaneous Use
When comparing dual vs. simultaneous users on marijuana outcomes (see Table 4), those who reported simultaneous use reported a younger first age of marijuana use, higher levels of all marijuana use indicators (exception being best friend’s typical quantity of use), and more marijuana related consequences than those who reported dual use. Furthermore, those reporting dual use used marijuana in plant form, in a party setting, and with people they didn’t know a lower percentage of the time, and used edibles and ingested marijuana a greater percentage of the time compared to those who reported simultaneous use.
Table 4.
Quasi-Poisson regression models of marijuana use patterns among those reporting 30-day alcohol and marijuana dual use vs. alcohol and marijuana simultaneous use.
| Descriptive Statistics | Model Results (0 = dual use; 1 = simultaneous use) | |||||||
|---|---|---|---|---|---|---|---|---|
| Dual Use (n = 285) | Simultaneous use (n = 950) | CIs | ||||||
| M | SD | M | SD | Estimate | OR | 0.5% | 99.5% | |
| Marijuana Use Indicators | ||||||||
| Age of First Use | 16.78 | 5.43 | 16.11 | 2.00 | −0.04 | 0.96 | 0.93 | 0.99 |
| Use Frequency Last 30 Days | 6.94 | 8.59 | 12.93 | 10.86 | 0.62 | 1.85 | 1.54 | 2.25 |
| Typical Quantity (grams) | 3.31 | 6.39 | 7.60 | 10.78 | 0.84 | 2.31 | 1.62 | 3.42 |
| Typical Frequency ( | 3.69 | 4.92 | 7.53 | 7.96 | 0.71 | 2.04 | 1.59 | 2.67 |
| Best Friend Typical Frequency | 4.07 | 2.18 | 4.73 | 2.15 | 0.15 | 1.16 | 1.07 | 1.27 |
| Best Friend Typical Quantity (grams) | 2.68 | 4.74 | 3.45 | 4.65 | 0.25 | 1.29 | 0.98 | 1.72 |
| Type of Product | ||||||||
| Plant | 55.99 | 43.32 | 67.96 | 36.08 | 0.19 | 1.21 | 1.09 | 1.35 |
| Edibles | 20.19 | 34.54 | 10.71 | 22.21 | −0.64 | 0.53 | 0.39 | 0.71 |
| Concentrates | 17.07 | 32.03 | 17.89 | 29.83 | 0.07 | 1.07 | 0.80 | 1.46 |
| Other | 6.75 | 24.45 | 3.43 | 16.67 | −0.70 | 0.50 | 0.26 | 1.00 |
| Methods of Consumptions | ||||||||
| Smoked in joint/blunt without tobacco | 28.94 | 38.29 | 33.46 | 35.63 | 0.15 | 1.16 | 0.95 | 1.43 |
| Smoked in joint/blunt with tobacco | 5.86 | 19.83 | 8.06 | 21.14 | 0.31 | 1.36 | 0.83 | 2.38 |
| Smoked in bong/water pipe without tobacco | 25.27 | 36.65 | 31.03 | 35.50 | 0.20 | 1.22 | 0.98 | 1.54 |
| Smoked in bong/water pipe with tobacco | 3.09 | 14.59 | 3.62 | 13.79 | 0.15 | 1.16 | 0.58 | 2.56 |
| Eaten/cooked | 17.72 | 33.19 | 8.05 | 20.47 | −0.80 | 0.45 | 0.32 | 0.64 |
| Used in a vaporizer | 19.12 | 34.17 | 15.78 | 29.46 | −0.17 | 0.84 | 0.62 | 1.15 |
| Consumption Location | ||||||||
| At my home | 43.15 | 43.84 | 42.91 | 39.19 | −0.03 | 0.97 | 0.83 | 1.15 |
| At a friend’s home | 34.06 | 41.47 | 31.67 | 35.20 | −0.07 | 0.93 | 0.77 | 1.14 |
| At a stranger’s home | 0.51 | 3.82 | 1.42 | 7.97 | 1.07 | 2.91 | 0.84 | 18.54 |
| Outside | 9.10 | 24.52 | 9.87 | 22.89 | 0.11 | 1.12 | 0.76 | 1.76 |
| In a car | 7.22 | 20.37 | 6.11 | 15.55 | −0.15 | 0.87 | 0.57 | 1.34 |
| At a party | 2.95 | 11.48 | 6.63 | 16.12 | 0.83 | 2.29 | 1.33 | 4.32 |
| Other | 3.35 | 17.11 | 1.39 | 9.24 | −0.87 | 0.42 | 0.17 | 1.08 |
| Consumption Context | ||||||||
| Alone | 20.62 | 34.71 | 24.38 | 31.68 | 0.15 | 1.16 | 0.91 | 1.49 |
| With friends | 71.98 | 39.45 | 68.36 | 34.73 | −0.05 | 0.96 | 0.88 | 1.04 |
| With family | 5.53 | 20.98 | 4.81 | 16.33 | −0.18 | 0.83 | 0.48 | 1.54 |
| With people I don’t know | 0.16 | 1.22 | 1.30 | 6.31 | 2.11 | 8.24 | 1.83 | 127.67 |
| Other | 2.42 | 15.29 | 1.15 | 9.91 | −0.82 | 0.44 | 0.14 | 1.49 |
| Planned vs. Unplanned Use | ||||||||
| Planned Use | 67.58 | 41.50 | 71.00 | 37.28 | 0.05 | 1.05 | 0.95 | 1.16 |
| Consequences | ||||||||
| B-MACQ – Total Score (Range = 0 – 21) | 2.75 | 3.73 | 4.80 | 4.79 | 0.45 | 1.58 | 1.26 | 1.99 |
| CUDIT-R – Total Score (Range = 0 – 40) | 6.52 | 5.38 | 9.59 | 6.87 | 0.28 | 1.33 | 1.15 | 1.54 |
Note: Significant results are bolded and were determined via 99% CIs for the Odds Ratios that did not contain 1. Regression models controlled for age, sex at birth (0 = male, 1 = female), year in school, and COVID-19 school announcement (0 = survey taken prior to school in-person teaching closure; 1 = survey taken after school in-person teaching closure). For CUDIT-R and B-MACQ, typical marijuana quantity consumption was also added as a covariate. We calculated typical frequency of marijuana use by summing the total number of time blocks for which they reported using during the typical week (ranges: 0–42). Best friend frequency of use was assessed using a 7-point response scale (response options: 0 = never to 6 = daily or almost daily). For type of product used, ways of consumption, consumption location, consumption context, and planned use, we used a constant sum approach in which students had to calculate the percentage of the time they used marijuana in the various ways assessed (total had to equal 100%) during the past month. Scores on these variables represent an average percent of the time each method is used across all participants rather than number of participants endorsing each category.
Discussion
Extant work on marijuana and alcohol use among college students suggests that students who use these substances simultaneously engage in more problematic drinking than those who engage in dual or alcohol-only use. However, little work has evaluated marijuana use behaviors among those who only use marijuana versus those who use alcohol and marijuana. This is largely due to the few students who report marijuana but not alcohol use (Yurasek et al., 2017). This was also true in the present study, such that among students who reported lifetime use of alcohol and marijuana, only 6.4% reported only using marijuana in the past 30-days. Despite the notable limitation of the small marijuana-only sample, our findings offer important information about the extent of problematic marijuana use across use statuses. As predicted, problematic marijuana use is higher among simultaneous users than dual users; though surprisingly, few differences were seen between simultaneous and marijuana-only users, and marijuana-only users actually reported more marijuana misuse compared to dual users. Given that both marijuana-only and simultaneous users reported using with unknown others a greater percentage of the time than dual users, social context may place these users at higher risk for negative outcomes (as has been found in the alcohol literature, see Storvoll et al., 2016); although future research is needed to replicate these results.
Another major aim of the present study was to investigate whether contextual factors differentially related to use status. Most notably, we found that marijuana-only users are proportionally less likely to use with friends and instead use with unknown others a greater percentage of the time; that dual users use edibles and ingest marijuana a greater proportion of the time; and that simultaneous users use plant material, at parties, and both with friends and unknown others on a high percentage of occasions. This contextual information suggests that simultaneous use may be associated with attempts to enhance positive experiences and to fit in with peers, which is consistent with prior findings that simultaneous use is most likely to occur on days when students report elevated enhancement and conformity motives (Patrick et al., 2019). It may also reflect increased likelihood of use at parties due to the potential for greater availability or access to marijuana. That marijuana was used in plant form on a higher percentage of occasions during simultaneous than dual use also suggests that smoking marijuana may be coupled with drinking alcohol, especially at parties, akin to known relations between drinking and cigarette smoking (Witkiewitz et al., 2012).
Simultaneous use compared to dual use was also associated with greater perceptions of best friend marijuana use. Yet, marijuana-only users also reported higher frequency of best friend’s marijuana use compared to dual users. Interestingly, no differences emerged on planned use of marijuana. Across user statuses, students indicated making a plan to use at least approximately two-thirds of the time. Despite the lack of research on planned use, we would expect more frequent unplanned use by simultaneous users given the association with use at parties and with unknown others. However, to the extent that students are planning their use, attempts to disrupt this planning or to include planned attempts to limit consequences (i.e., protective behavioral strategies; see Pearson, 2013; Prince et al., 2013 for reviews) may be effective in reducing risk.
Our findings should be considered alongside study limitations. First, data were collected from college students at a limited number of four-year institutions, and thus may not represent the entire population of those who co-use alcohol and marijuana (e.g., students at 2-year institutions). Additionally, the data are cross-sectional, which limits conclusions regarding causality and temporal sequencing of effects of each of the substances. Also, while the MUG was developed to more accurately quantify marijuana use, the diverse contexts and methods to use marijuana brought about the following limitations: (a) reported grams were not assessed as a function of the number of individuals with whom marijuana was shared, (b) the potency and ratio of tetrahydrocannabinol (THC) to cannabidiol (CBD) was not assessed, and (c) a visual aid of non-plant material quantity was not provided and thus the accuracy of the amount of non-plant use is unclear. Finally, all reports of substance use were self-report and reflected past 30-day use, which may introduce significant recall biases (Gmel & Daeppon, 2007).
Beyond replication of study findings, additional research should address etiological differences in engagement in alcohol or marijuana use alone compared to co-use. Attention to when, how, and with whom students use marijuana and alcohol is critical to prevent harm and long-term impairment from these substances. While we sought to better conceptualize the patterns of co-use of marijuana and alcohol by college students, growing work has shed light on some important psychosocial (e.g., perceived norms; White et al., 2019) and personality (e.g., sensation seeking; Linden-Carmichael et al., 2019) antecedents to investigate in future work. Additional research is needed to identify prevention and intervention strategies to directly target simultaneous alcohol and marijuana use. Finally, cross-cultural research is needed to examine whether the prevalence and risk associated with simultaneous use is universal or culture-specific.
Public Significance Statement:
Within this study, college students who engaged in either marijuana-only or simultaneous use of alcohol and marijuana (i.e., use of both substances such that their effects overlapped) reported greater past 30-day marijuana use frequency, quantity, and consequences than those who engaged in dual use (i.e., use of both substances within a designated time period, but without effects overlapping). Based on the results of this study, more research is needed to understand etiological and contextual factors related to different use types.
Role of Funding Sources
The author(s) thank the Office of the Provost of W&M University for a faculty summer research grant to Dr. Bravo in support of this work. This project was supported by an Institutional Development Award (IDeA) by the National Institute of General Medical Sciences (#82P20GM103432). This project was supported by a grant (R01DA043691) from the National Institute on Drug Abuse (NIDA). The content is the authors’ responsibility and does not necessarily represent the views of NIDA or NIAAA, and NIDA and NIAAA had no role in the design of the study, the analyses, interpretation of results or the decision to submit the manuscript for publication.
Contributor Information
Alison Looby, Department of Psychology, University of Wyoming.
Mark A. Prince, Department of Psychology, Colorado State University.
Margo C. Villarosa-Hurlocker, Center on Alcoholism, Substance Abuse, and Addictions, University of New Mexico.
Bradley T. Conner, Department of Psychology, Colorado State University.
Ty S. Schepis, Department of Psychology, Texas State University.
Adrian J. Bravo, Department of Psychological Sciences, William & Mary, USA.
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