Skip to main content
NCBI home page
Journal of Studies on Alcohol and Drugs logoLink to Journal of Studies on Alcohol and Drugs
. 2024 Oct 15;85(5):728–736. doi: 10.15288/jsad.23-00043

Order of Cannabis and Alcohol Use on Pregaming and Non-Pregaming Days Among College Students

Eric R Pedersen a,,*, Reagan E Fitzke a, Toni Atieh a, Denise D Tran a, Jordan P Davis b, Rachel L Gunn c,,d, Lauren Micalizzi c,,d, Mark A Prince e
PMCID: PMC11533921  PMID: 38517753

Abstract

Objective:

Pregaming is common among college students and is associated with heavy drinking and negative alcohol-related consequences. The use of cannabis on pregaming days may exacerbate negative alcohol-related consequences, and the ordering of when cannabis is used on these days may buffer against or intensify these consequences. Considering the growing rates of simultaneous use of cannabis and alcohol among college students, it is necessary to examine the role of pregaming behaviors in the context of cannabis use and its effects on alcohol-related consequences.

Method:

In the present study, college students (N = 485) completed a baseline survey and 14 days of daily surveys, reporting on daily alcohol and cannabis use and alcohol-related negative consequences. Multilevel structural equation models were fit to evaluate cannabis outcomes on pregaming versus non-pregaming drinking days and ordering effects on alcohol-related consequences, controlling for number of drinks, age, and sex.

Results:

Across all drinking days, pregaming on that day as well as cannabis use during drinking on that day were associated with a greater risk for alcohol-related consequences. On days that did not involve pregaming, the use of cannabis before drinking was associated with a greater risk for negative alcohol-related consequences, whereas cannabis use after drinking was associated with less risk for consequences. These effects were observed on non-pregaming days only and not on days with pregaming.

Conclusions:

Findings have implications for brief interventions with students, as analyses suggested that both cannabis use and pregaming—independent of number of drinks consumed—are risky behaviors associated with alcohol-related consequences.

Pregaming (i.e., prepartying, predrinking) is the rapid consumption of alcohol in advance of a social event during which more alcohol consumption may take place (Zamboanga & Olthuis, 2016; Zamboanga et al., 2023). Studies consistently show that the majority (55%–90%) of college student drinkers engage in pregaming (Calhoun & Linden-Carmichael, 2022; Pedersen, 2016) and pregaming is associated with risky outcomes, such as heavy alcohol consumption after pregaming events, high levels of intoxication, and negative alcohol-related consequences (Chaney et al., 2019; LaBrie et al., 2016; Miller et al., 2016). Event-level studies indicate that individuals tend to experience more negative consequences on drinking days when they pregame than on drinking days that do not involve pregaming (LaBrie & Pedersen, 2008; Merrill et al., 2013; Radomski et al., 2016). There is mixed evidence in the pregaming literature regarding whether there is a unique association between pregaming and negative consequences (e.g., Calhoun & Linden-Carmichael, 2022; Merrill et al., 2013) or whether this relationship can be explained by the sheer difference in the number of drinks consumed on pregaming days (Labhart et al., 2013; Read et al., 2010). However, because pregaming drinking often occurs in the hours before the larger planned event (where drinking is also typical), the risk in pregaming can come from a longer time spent consuming alcohol but also likely because of the fast-paced drinking that occurs during these often-brief periods, during which high blood alcohol levels can be reached (Pedersen & LaBrie, 2007).

Because pregaming plays an essential role in the study of alcohol-related outcomes among college students, it is important to study other behaviors that may occur on pregaming days. An increasingly pressing consideration is what role, if any, cannabis use may play in college student pregaming behaviors and its potential harms. The prevalence and frequency of cannabis use among college students has been on the rise over the past decade, with past-year prevalence at the highest levels since the early 1980s (Schulenberg et al., 2021). College students who use cannabis can encounter cannabis-related problems and potentially develop a cannabis use disorder (CUD; Caldeira et al., 2008); the more frequently someone uses cannabis, the greater the risk for cannabis-related consequences and CUD symptoms (Gunn et al., 2020). In addition to more acute negative consequences (e.g., cognitive or respiratory impairments), cannabis use may have negative developmental-specific effects with longer-term implications (e.g., lower grade point average, school dropout, delays in graduation; Suerken et al., 2016).

Among students who report past-year cannabis and alcohol use, more than 75% report using both on the same occasion, such that the effects of each overlap (i.e., “simultaneous use”; Bravo et al., 2021; White et al., 2019). Students may use alcohol and cannabis simultaneously because of social pressure and conformity or because of expectancies of positive effects or cross-fading (i.e., experiencing both a “drunk” from drinking and a “high” from using cannabis; Gunn et al., 2022; Lee et al., 2022; Linden-Carmichael & Wardell, 2021; Patrick et al., 2018). Increasing rates of co-use raise concern for the well-being of some students because co-use can lead to increased consumption and problematic use of both substances (Yurasek et al., 2017). For example, relative to only drinking alcohol, simultaneous use of cannabis and alcohol is associated with an increased likelihood of consequences such as blackouts, driving while intoxicated, and physiological and cognitive effects (Cummings et al., 2019; Jackson et al., 2020; Lee et al., 2017). Similarly, young adults are more likely to drink heavily and experience alcohol-related consequences on days they also use cannabis, compared with cannabis non-use days (Lee et al., 2022).

Prior research underscores the importance of continuing to characterize the co-use of cannabis and alcohol and its related outcomes among college students. Despite emerging research attention to alcohol and cannabis co-use, little is known about the order of when cannabis is used on days of simultaneous use. Recently, researchers examined the order of alcohol and cannabis use among college students using two periods of 28 days of diary data collection, finding that although using cannabis first on simultaneous use days was associated with greater overall cannabis consumption on that day, cannabis use first was also associated with lower levels of drinking during the day (Gunn et al., 2021). Drinking was a predictor of alcohol-related consequences—not cannabis use or any order of alcohol and cannabis. Unexamined in the literature are the ordering effects of alcohol and cannabis use on days that involve pregaming. Given the high prevalence of pregaming and the growing rates of simultaneous co-use with alcohol in the college environment, examining pregaming behaviors in the context of cannabis use is needed to fill an important knowledge gap, which this exploratory study begins to do.

Although the limited prior work precludes us from making clear hypotheses about how the order of cannabis use on pregaming and non-pregaming days attenuates or exacerbates the risk for alcohol-related negative consequences, three research aims guided our analyses. First, we aimed to better understand college student cannabis use on pregaming days versus non-pregaming days; namely, we were interested to know if cannabis use was more prevalent or less prevalent on drinking days that involved pregaming or on drinking days that did not involve pregaming. Second, we aimed to learn more about when students used cannabis during pregaming and non-pregaming drinking days on which cannabis was used: before drinking, during drinking, and after drinking. Third, we were interested to learn, on the days cannabis was used, whether the order of when cannabis was used was associated with alcohol-related consequences and whether those effects varied between pregaming drinking days and non-pregaming drinking days.

Method

Participants and procedure

Participants were college students who were part of a larger randomized controlled trial of a brief mobile intervention to target heavy drinking during pregaming (Pedersen et al., 2022, 2023). The intervention was based on the Brief Alcohol Screening and Intervention for College Students (BASICS; Dimeff et al., 1999) and contained personalized feedback about the student's pregaming behavior, attitudes, and associated risks in a 30-minute interactive video and text mobile phone format. A detailed description of the intervention and the full study design (Pedersen et al., 2022) and the main outcome effects from the brief follow-up period after intervention (Pedersen et al., 2023) are featured elsewhere. Before randomization to the intervention or a psychoeducation control condition, participants completed a screening survey to determine eligibility; if eligible, they completed a baseline survey and 14 days of daily diary surveys. Data analyzed for this study come from the baseline and daily diary surveys conducted before randomization and before any intervention condition was received.

This study was conducted in fall 2021. Students were attending classes in person and living on campus after COVID-19 restrictions had been lifted. Participants were (a) full-time undergraduate students at the university where the study was being conducted, (b) between ages 18 and 24, and (c) pregaming at least once per week or at least four times in the past 30 days. There were no eligibility criteria related to cannabis use. A random sample of 11,482 undergraduate (about 50% of the undergraduate population at the university) emails were obtained from the university's registrar. A study description was emailed to these addresses and 2,498 students completed a screening survey, of which 727 met eligibility criteria (29.1% of those completing the screening survey). Eligible participants were emailed the baseline survey, of which 485 completed it (66.7% of those eligible and invited). Those who completed the baseline survey were given a $20 gift card redeemable online at a choice of retailers. Participants who completed the baseline survey were then invited to complete 14 days of daily diary surveys assessing their drinking and cannabis use behaviors. For each diary they completed, participants received $2 toward a gift card, for a total of $28. Diary completion rates ranged from 71% to 93%, with a mean of 83% of participants completing each diary survey.

Measures

Baseline survey. The baseline survey contained items to assess the following demographics of the sample: age, sex, gender identity, class year, living situation (on campus, off campus, fraternity or sorority housing), race, and ethnicity. Participants were asked how many days they drank any alcohol in the past 30 days as well as how many days they pregamed in the past 30 days. Pregaming was defined as drinking alcohol before attending an event or activity (e.g., drinking before going to a party, bar, or concert; events that had many people or very few people) at which more alcohol may or may not be consumed. Participants were also asked how many days they used cannabis in the past 30 days. The survey defined standard drinks for participants per National Institute on Alcohol Abuse and Alcoholism recommendations. Cannabis use was defined for participants as any marijuana or cannabis product (pot, weed, hash) containing tetrahydrocannabinol (THC) in any form (like smoking a joint or blunt; eating or drinking edibles; or using a bong, vaping, dabs, or concentrates). Participants were asked not to consider the use of cannabidiol products with no THC.

Daily diary surveys. After defining standard drinks for participants, each daily survey asked participants whether they drank the day before (no/yes), and if yes, how many drinks they consumed. Next, participants were asked if they pregamed on this drinking day (yes/no), and if yes, how many drinks they consumed while pregaming. For each drinking day, regardless of pregaming occurrence, participants were asked whether they experienced each of the 24 alcohol-related consequences (yes/no) from the Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ; Kahler et al., 2005, 2008), which included items such as passing out from drinking, taking foolish risks, missing class, or neglecting responsibilities. Rather than ask whether each of these consequences was experienced in the past 30 days as on the original measure, participants were asked whether they experienced each of the consequences on each day they reported drinking. A dichotomous variable for the experience of any alcohol consequences was created for each drinking day (0 = no consequences experienced, 1 = any of the 24 consequences experienced). A sum of alcohol consequences was also calculated for each day, ranging from 0 to 24.

Regardless of whether the participants drank, they were asked if they used cannabis the day before (yes/no). If so, they were asked two questions to assess the within-day frequency of cannabis use and the duration of intoxication from the cannabis they used: (a) how many times they used on that day and (b) how many hours they felt high from the effects of cannabis on that day. Last, for the days participants had already indicated that they also consumed alcohol, they were asked when they used cannabis relative to when they drank alcohol (i.e., ordering of use: before drinking started, during drinking, after drinking ended). Participants could endorse more than one response to this item on the timing of use (e.g., they used cannabis during and after drinking).

Analytic plan

Descriptive analyses were used to examine cannabis outcomes on pregaming drinking days versus non-pregaming drinking days. Next, we used a series of three multilevel structural equation models (MSEM; cf. Mehta & Neale, 2005) to examine within-day-order effects of alcohol and cannabis use on alcohol-related consequences, as well as the effects of pregaming. In all models, sex and grand mean centered age were included as between-level (i.e., person-level) covariates, daily drinks were included as a within-level (i.e., day-level) covariate, and six binary day-of-the-week variables were included as within-level covariates, with Sunday as the referent group. Drinks per day were person-mean centered. The three binary order variables (i.e., cannabis before drinking, cannabis during drinking, and cannabis after drinking) were person-mean centered (Yaremych et al., 2021). In the first model, pregaming was included as a daily-level predictor. In the second model, we selected for only pregaming days and looked at the effects of alcohol and cannabis use order on consequences. In the third model, we selected for drinking days without pregaming and looked at the effects of alcohol and cannabis use order on consequences.

In all models, the alcohol-related consequences variable was modeled using a negative binomial distribution to account for the highly skewed count distribution of consequences, given that the dispersion parameter was significantly different from zero (Neal & Simons, 2007). With negative binomial regression paths, the unstandardized estimates can be exponentiated to rate ratios (RRs), which provide the predicted percent change in the outcome for a unit change in the predictor (Hilbe, 2011). The interpretation of the predicted percent change in the outcome aligns with clinical observations that those with high levels of the outcome (e.g., alcohol-related consequences) are expected to change more than those with low levels of the outcome. For example, if the RR-predicted percent change is 25% for a unit increase in the predictor, then a person with 8 consequences would be predicted to increase to 10 consequences and a person with 4 consequences would be predicted to increase to 5 consequences. Readers can apply this procedure to all effects to translate RRs to natural units across the domain of the predictor and outcome variables. Models were estimated in Mplus Version 8.7 (Muthén & Muthén, 2017). We interpreted 95% confidence intervals (CIs) around the RRs. CIs that did not include 1 were considered statistically significant. CIs provide more information than p values because, in addition to providing information about whether an effect is statistically significant, they also provide information about the precision of the point estimate (cf. Cumming, 2014).

Results

Sample description

Sample demographics are reported in Table 1. All participants reported drinking in the past 30 days, with all also reporting pregaming. Three hundred and fourteen participants (63.9%) reported past-30-day cannabis use. Among the 485 participants and 6,790 possible days (14 days each among 485 participants), there were 5,990 reported days with data. Of these 5,990 days, 31.1% (1,863 days) included any drinking, with a sample mean of 4.66 (SD = 3.41) drinks per drinking day. Pregaming occurred on 39.7% (738 days) of drinking days, with a sample mean of 3.39 (SD = 2.2) drinks during pregaming.

Table 1.

Sample demographics

graphic file with name jsad.23-00043tbl1.jpg

Variable M (SD) or n (%)
Age, in years, M (SD) 19.98 (1.25)
Sex
 Male 159 (32.8%)
 Female 326 (67.2%)
Gender identity
 Man 159 (32.8%)
 Woman 318 (65.6%)
 Nonbinary or gender nonconforming 8 (1.6%)
College class status
 First-year student/freshman 73 (15.1%)
 Sophomore 119 (24.5%)
 Junior 125 (25.8%)
 Senior 168 (34.6%)
Living situation
 Off campus 318 (65.6%)
 On campus 127 (26.2%)
 Fraternity/sorority housing 40 (8.2%)
Race/ethnicity
 White 232 (47.8%)
 Asian 98 (20.2%)
 Hispanic/Latinx 90 (18.6%)
 Multiracial 48 (9.9%)
 African American/Black 13 (2.7%)
 Other race/ethnicity 4 (0.8%)
Past-30-day substance use at baseline
 Drinking days 10.14 (4.07)
 Pregaming drinking days 7.18 (3.42)
 Days used cannabisa 5.88 (8.49)
Open in a new tab
a

Mean is among the full sample; 171 (36.1%) participants did not use cannabis in the past 30 days. Among the past-30-day cannabis users, mean days of use was 9.19 (9.08).

One fifth (20.8%, 1,243 days) of all reported days included cannabis use. On the days participants reported using cannabis, they reported using a mean of 1.84 (SD = 1.50) times during that day and reported feeling high for a mean of 3.13 (SD = 2.20) hours. Cannabis use was reported on 27.2% of all drinking days (507 of 1,863 drinking days) and 17.8% of nondrinking days (736 of 4,127 nondrinking days). On cannabis-using days, the number of times participants reported using cannabis on drinking days (M = 1.92 times, SD = 1.53) and nondrinking days (M = 1.78 times, SD = 1.47) was similar (i.e., about two times per day). However, participants reported feeling high for about a half hour less on drinking days (M = 2.87 hours, SD = 2.20) versus non-drinking days (M = 3.31 hours, SD = 2.17). Cannabis use was reported on 27.6% of all pregaming days (204 of 738 pregaming days) and 27.1% of non-pregaming drinking days (303 of 1,119 non-pregaming drinking days). On cannabis use days, participants reported using more times on drinking days when they pregamed (M = 2.15 times, SD = 1.89) than on drinking days when they did not pregame (M = 1.76 times, SD = 1.21). Participants' reported length of time feeling high on pregaming drinking days (M = 2.99 hours, SD = 2.49) versus non-pregaming drinking days (M = 2.79 hours, SD = 2.00) was about a half hour longer.

Ordering of alcohol and cannabis use

We examined the ordering of cannabis use on drinking days that involved cannabis (i.e., co-use days) separated by pregaming days and non-pregaming drinking days. Of the 303 non-pregaming co-use days, 26.7% involved cannabis use before drinking, with a mean of 2.66 (SD = 1.59) times used and a mean of 4.33 (SD = 2.69) hours high. More than a third (36.3%) involved cannabis use during drinking, with a mean of 2.06 (SD = 1.25) times used and a mean of 2.95 (SD = 1.89) hours high. Last, 54.5% of the non-pregaming drinking days involved cannabis use after drinking had concluded, with a mean of 1.64 (SD = 1.18) times used and a mean of 2.58 (SD = 1.90) hours high.

Of the 204 co-use days that included pregaming, 25.0% of these days involved cannabis use before drinking, with a mean of 3.39 (SD = 2.51) times used and a mean of 4.43 (SD = 2.58) hours high. Nearly half of the pregaming drinking days (45.1%) involved cannabis use during drinking, with a mean of 2.66 (SD = 2.29) times used and a mean of 3.48 (SD = 3.19) hours high. Last, 53.4% of pregaming days involved cannabis use after drinking had concluded, with a mean of 1.98 (SD = 1.56) times used and a mean of 2.91 (SD = 2.03) hours high.

When participants used cannabis on both non-pregaming drinking days and pregaming drinking days, they typically reported use during just one of the ordering periods (i.e., before, during, or after). Only 12% of non-pregaming drinking days contained cannabis use across periods (most typical was across all three: before, during, and after drinking) and 19% of pregaming drinking days contained cannabis use across periods (most typical was during and after drinking).

Predicting alcohol-related negative consequences from cannabis and pregaming

Table 2 contains results from the three MSEMs. In the model that included pregaming as a within-level predictor of consequences, after controlling for day of the week, number of drinks consumed, age, and sex, significant day-level effects were observed for using cannabis before drinking, using cannabis during drinking, and whether pregaming occurred on that day. Interpretation of the RRs indicated that participants reported 24% more alcohol-related consequences when they used cannabis during the drinking episode compared with days they did not use cannabis. Using cannabis before drinking, controlling for pregaming and other covariates, was associated with 29% more consequences compared with not using cannabis before drinking. In addition, this model showed that participants reported 24% more consequences on pregaming days and 18% more consequences per additional drink on a given day. Participants reported 56% more consequences on Tuesday than on Sunday and 38% more consequences on Wednesday than on Sunday. The other days of the week were not statistically different from Sunday.

Table 2.

Multilevel structural equation models predicting alcohol related consequences from alcohol and cannabis use order controlling for day of the week, sex, age, and drinks on a given day

graphic file with name jsad.23-00043tbl2.jpg

Level Outcome Predictor RR [95% CI]
Pregaming in the model
 Within Consequences Cannabis before drinking 1.29 [1.13, 1.46]
Cannabis during drinking 1.24 [1.14, 1.35]
Cannabis after drinking 0.92 [0.83, 1.00]
Drinks 1.18 [1.17, 1.19]
Pregaming 1.24 [1.18, 1.31]
 Between Consequences Sex 1.05 [0.95, 1.16]
Age 0.96 [0.92, 1.00]
Intercept 0.86 [0.72, 1.00]
Pregaming days
 Within Consequences Cannabis before drinking 0.82 [0.58, 1.05]
Cannabis during drinking 0.89 [0.77, 1.02]
Cannabis after drinking 1.07 [0.93, 1.20]
Drinks 1.16 [1.14, 1.18]
 Between Consequences Sex 1.07 [0.95, 1.19]
Age 1.04 [0.99, 1.08]
Intercept 2.10 [1.86, 2.34]
Drinking days without pregaming
 Within Consequences Cannabis before drinking 1.88 [1.67, 2.10]
Cannabis during drinking 1.14 [0.97, 1.31]
Cannabis after drinking 0.81 [0.70, 0.92]
Drinks 1.22 [1.20, 1.24]
 Between Consequences Sex 0.91 [0.78, 1.04]
Age 0.88 [0.84, 0.93]
Intercept 0.61 [0.45, 0.78]
Open in a new tab

Notes: The alcohol-related consequences outcome variable was specified with a negative binomial count distribution: M = 1.62, SD = 2.25, range: 0–17, Mdn = 1.0, intraclass correlation coefficient = 0.38. Drinks represents the total drinks consumed in a day: M = 4.67, SD = 3.41, range: 1–27, Mdn = 4. Bold indicates that the 95% confidence interval (CI) does not contain 1.0. RR = rate ratio. Within = daily-level effects; between = person-level effects. All within-level predictors presented were person-mean centered. Day of the week was included as six dummy-coded variables, with Sunday as the referent group. Day-of-the-week effects were omitted from the table for clarity.

When examining pregaming days only, none of the cannabis order effects were significant, and the number of drinks in a given day was the only significant within-level predictor of alcohol-related consequences, such that participants reported 16% more consequences per drink on pregaming days. Participants reported 45% fewer consequences on Thursday than on Sunday and 36% fewer consequences on Friday than on Sunday. The other days of the week were not statistically different from Sunday. Sex also predicted consequences at the between level, with male students reporting more consequences. In contrast, on drinking days without pregaming, there were significant within-level effects for using cannabis either before or after drinking as well as drinks per day. The within-level effects indicated that on days when participants reported using cannabis before drinking, they reported 88% more alcohol-related consequences compared with days when they did not use cannabis. On days they reported using cannabis after drinking, they reported 19% fewer alcohol-related consequences compared with non–cannabis-using days. Consistent with previous models, each additional drink was associated with 22% more consequences on drinking days without pregaming. Similar to the model that included pregaming as a predictor, participants reported 99% more consequences on Tuesday than on Sunday and 43% more consequences on Wednesday than on Sunday. The other days of the week were not statistically different from Sunday. Finally, age was a significant between-level predictor, with older participants reporting 12% fewer consequences per additional year of age.

Discussion

This exploratory study was designed to examine how the order of when cannabis was used on pregaming and non-pregaming drinking days was associated with negative alcohol consequences. First, consistent with prior work on general drinking days, descriptive analyses suggested that cannabis use was more likely on drinking days than on nondrinking days (Lee et al., 2022; Metrik et al., 2018). Moreover, participants were likely to report more consequences on weekdays compared with weekends, which is possibly because of responsibilities of daily weekday life (e.g., attending classes, preparing for exams, being present for certain work hours) compared with responsibilities on more flexible weekends (e.g., more free time, ability to sleep in on a Sunday morning). A unique contribution of this study was that we found that cannabis use was no more likely on pregaming drinking days compared with non-pregaming drinking days. However, participants reported using cannabis more times on drinking days when they pregamed than on drinking days when they did not pregame. These findings suggest, then, that although pregaming may not confer additional risk in terms of decisions about whether to use cannabis on drinking days, it may be a risk factor for heavier use after a student starts using cannabis on a drinking day. Interestingly, more frequent cannabis use on pregaming days did not appear to correspond with greater reports of subjective cannabis intoxication (i.e., hours felt high) compared with non-pregaming co-use days.

Overall, regardless of whether the drinking day involved pregaming, cannabis use was most likely to occur after drinking. On the days when college students engaged in couse, cannabis use occurred after drinking for approximately 54% of those events, compared with cannabis use before drinking, which occurred on about one quarter of the co-use days. It is important to note that using cannabis before drinking did confer risk for experiences more consequences. Regarding cannabis use during drinking, almost half of co-use days that involved pregaming included cannabis use while drinking, compared with a little more than one third of non-pregaming co-use days. Consequences were differentially predicted by the ordering of cannabis use. Overall, for all drinking days, there was a high likelihood of experiencing alcohol-related consequences on days with cannabis use before or during drinking, regardless of whether the participant pregamed on those days. Pregaming on co-use days also predicted alcohol consequences experienced on that day, regardless of when cannabis was used, and after controlling for total drinks consumed on that day. This suggests a unique and independent impact of pregaming on alcohol-related consequences, even when cannabis use and overall level of drinking are considered, and fits with the multitude of literature highlighting the unique risks of pregaming among college students (Zamboanga & Olthuis, 2016; Zamboanga et al., 2023).

When we examined pregaming days and non-pregaming drinking separately, we found that the ordering of when cannabis was used was only associated with alcohol-related consequences on non-pregaming days. Using cannabis before drinking on a non-pregaming drinking day predicted a greater number of consequences on that drinking day, whereas cannabis use after drinking predicted fewer consequences. That is, although cannabis use before drinking on non-pregaming drinking days was associated with a greater risk for any consequences, cannabis use after drinking was associated with less risk of experiencing negative consequences. It is possible that using cannabis after drinking replaces what could have been continued heavy drinking (Gunn et al., 2022). Yet, this attenuating effect was not present for pregaming days, with no significant effect of cannabis use, regardless of when it was used, on consequences. Together, these analyses suggest that both cannabis use before drinking (but not pregaming drinking) and pregaming (independent of cannabis use) are predictive of alcohol-related consequences. This idea of “cannabis pregaming” warrants further examination to better understand how using cannabis, including type (e.g., joints vs. edibles that take longer to feel the effects from) and potency (e.g., THC concentration), before going out for the evening can affect the experience of both alcohol- and cannabis-related consequences.

A limitation of this study is that we did not have specific timing of use to determine if the intoxicating effects of cannabis use before drinking were still present once the student began drinking on that day, as well as whether the intoxicating effects of alcohol were still present once drinking ended for the day and cannabis use began (indicating overlapping intoxication effects). We can assume that the use of cannabis endorsed during drinking indicated overlapping intoxication effects, potentially explaining the increased likelihood of consequences on days when cannabis use overlapped with drinking on non-pregaming days. Although using cannabis while also drinking can lead to higher subjective intoxication levels and estimated blood alcohol levels on that day (Metrik et al., 2018), feeling the effects of cannabis and alcohol during pregaming (i.e., before going out for the night) has risky implications for students beyond the risk already linked to pregaming days. Yet, pregaming had a strong effect on alcohol consequences in this study and others (Barnett et al., 2013; Merrill et al., 2013); therefore, although cannabis use during pregaming could be risky, simply the act of pregaming accounts for much of the risk. This continues to support the need for pregaming-specific brief interventions for college students (Cadigan et al., 2019; Pedersen, 2016; Pedersen et al., 2023) to help prevent negative consequences attributed to this risky practice.

This study has additional sample and methodology limitations. The sample was restricted to a single university and although students exhibited class year and racial/ethnic diversity, students were primarily female and were enrolled based on a heavy drinking indicator. Because male college students have traditionally been heavier drinkers than female students (Schulenberg et al., 2021), more research is needed to understand sex/gender effects and co-use on pregaming and non-pregaming days among male students and lighter, less frequent drinkers. Measures were all self-reported and subjective—in particular the number of hours spent high on a day—which along with the number of times used on a cannabis use day, served as proxies for more detailed measures of quantity (Calhoun et al., 2022). Quantity of use is often inaccurately estimated by young adults (Borodovsky et al., 2024; Prince et al., 2018), and our survey was designed to monitor pregaming, general alcohol use, and general cannabis use in more global terms (e.g., did it occur or not) rather than on specific quantities. As such, some of the findings may be attributed to the amount of alcohol and amount of cannabis consumed on assessment days. Researchers are encouraged to continue conducting daily diary and ecological momentary assessment studies with more detailed measures of assessment to better understand the impact of cannabis ordering effects on consequences.

In addition, a unique contribution of this study is the collection of data on the order of cannabis use on co-use pregaming and non-pregaming days; to our knowledge, ordering effects of cannabis and drinking have only been looked at with college students in one other study that did not consider the unique effects of pregaming (Gunn et al., 2021). However, we have no data on the contexts of cannabis use before, during, and after drinking and pregaming. Future studies are needed to understand the contexts in which students use cannabis before, during, and after drinking (e.g., with friends or alone, at home or at a party/bar) as well as more detail on the products students use (e.g., joints, edibles, vapes). Although other daily-level assessment studies have used the BYAACQ to indicate the experience of consequences the previous day (e.g., Friedberg et al., 2019), the measure was designed to capture between-person variability in consequences rather than within-person variability in consequences as we assessed here. Thus, the BYAACQ needs to be further validated as a valid measure at the daily level. Last, although we were primarily interested in the consequences experienced related to alcohol on drinking days, we did not assess cannabis-related consequences. Although cannabis use may have precluded students from further drinking and helped limit their time out to experience consequences related to drinking, students may have used cannabis heavily and experienced cannabis-related problems on that day or the day after. Although much of the work on alcohol and cannabis co-use has focused on the additive effects of the substance, research also points to a substitution effect among those who use both substances, such that on a night when they do not drink, they may use cannabis (and vice versa) to get a buzz/high from at least one substance that night (Gunn et al., 2022). Among college students who use alcohol to cope (e.g., with stress or negative emotions), this effect may be even more apparent, as they achieve the desired level of intoxication with one of the substances without needing the other to alleviate stress or negative affect (O'Hara et al., 2016). More work is needed with college students to determine if consequences unique to each substance are emerging on co-use days when substitution occurs.

Conclusions

Pregaming is common among college students and is associated with a heightened risk for negative alcohol-related consequences. Although cannabis use, and more specifically its use when also drinking, confers risk for negative alcohol-related consequences, results from this exploratory study indicate that pregaming itself, regardless of when cannabis is used, is a primary driver of consequences. Prevention and intervention programs aimed at reducing both pregaming drinking and co-use of cannabis on drinking days may help reduce corresponding harm.

Footnotes

This work was funded by a grant from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) (R34AA025968—“Mobile Application Intervention Targeting the High-Risk Drinking Practice of Prepartying”) awarded to Eric R. Pedersen. Manuscript preparation was also supported by NIAAA Grants K08AA027551 awarded to Rachel Gunn and K01DA048135 to Lauren Micalizzi.

References

  1. Barnett N. P., Orchowski L. M., Read J. P., Kahler C. W. Predictors and consequences of pregaming using day- and week-level measurements. Psychology of Addictive Behaviors. 2013;27(4):921–933. doi: 10.1037/a0031402. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Borodovsky J. T., Hasin D. S., Shmulewitz D., Walsh C., Livne O., Aharonovich E., Struble C. A., Habib M. I., Budney A. J. Typical hits, grams, or joints: Evaluating cannabis survey measurement strategies for quantifying consumption. Cannabis and Cannabinoid Research. 2024;9(2):646–658. doi: 10.1089/can.2022.0237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bravo A. J., Prince M. A., Pilatti A., Mezquita L., Keough M. T., Hogarth L. Young adult concurrent use and simultaneous use of alcohol and marijuana: A cross-national examination among college students in seven countries. Addictive Behaviors Reports. 2021;14:100373. doi: 10.1016/j.abrep.2021.100373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Cadigan J. M., Martens M. P., Dworkin E. R., Sher K. J. The efficacy of an event-specific, text message, personalized drinking feedback intervention. Prevention Science. 2019;20(6):873–883. doi: 10.1007/s11121-018-0939-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Caldeira K. M., Arria A. M., O'Grady K. E., Vincent K. B., Wish E. D. The occurrence of cannabis use disorders and other cannabis-related problems among first-year college students. Addictive Behaviors. 2008;33(3):397–411. doi: 10.1016/j.addbeh.2007.10.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Calhoun B. H., Linden-Carmichael A. N. Pregame drinking among young adults and its association with positive and negative alcohol consequences. Addictive Behaviors. 2022;124:107120. doi: 10.1016/j.addbeh.2021.107120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Calhoun B. H., Patrick M. E., Fairlie A. M., Graupensperger S., Walukevich-Dienst K., Lee C. M. Hours high as a proxy for marijuana use quantity in intensive longitudinal designs. Drug and Alcohol Dependence. 2022;240:109628. doi: 10.1016/j.drugalcdep.2022.109628. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chaney B. H., Martin R. J., Barry A. E., Lee J. G. L., Cremeens-Matthews J., Stellefson M. L. Pregaming: A field-based investigation of alcohol quantities consumed prior to visiting a bar and restaurant district. Substance Use & Misuse. 2019;54(6):1017–1023. doi: 10.1080/10826084.2018.1558252. [DOI] [PubMed] [Google Scholar]
  9. Cumming G. The new statistics: Why and how. Psychological Science. 2014;25(1):7–29. doi: 10.1177/0956797613504966. [DOI] [PubMed] [Google Scholar]
  10. Cummings C., Beard C., Habarth J. M., Weaver C., Haas A. Is the sum greater than its parts? Variations in substance-related consequences by conjoint alcohol-marijuana use patterns. Journal of Psychoactive Drugs. 2019;51(4):351–359. doi: 10.1080/02791072.2019.1599473. [DOI] [PubMed] [Google Scholar]
  11. Fridberg D. J., Faria J., Cao D., King A. C. Real-time mobile monitoring of drinking episodes in young adult heavy drinkers: Development and comparative survey study. JMIR mHealth and uHealth. 2019;7(11):e13765. doi: 10.2196/13765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Gunn R. Patterns of cannabis and alcohol co-use: Substitution versus complementary effects. Alcohol Research: Current Reviews. 2122;40(2) doi: 10.35946/arcr.v42.1.04. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gunn R. L., Aston E. R., Sokolovsky A. W., White H. R., Jackson K. M. Complex cannabis use patterns: Associations with cannabis consequences and cannabis use disorder symptomatology. Addictive Behaviors. 2020;105:106329. doi: 10.1016/j.addbeh.2020.106329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gunn R. L., Sokolovsky A., Stevens A. K., Metrik J., White H., Jackson K. Ordering in alcohol and cannabis co-use: Impact on daily consumption and consequences. Drug and Alcohol Dependence. 2021;218:108339. doi: 10.1016/j.drugalcdep.2020.108339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hilbe J. M. Negative binomial regression. 2011 doi: 10.1017/cbo9780511973420. [DOI] [Google Scholar]
  16. Jackson K. M., Sokolovsky A. W., Gunn R. L., White H. R. Consequences of alcohol and marijuana use among college students: Prevalence rates and attributions to substance-specific versus simultaneous use. Psychology of Addictive Behaviors. 2020;34(2):370–381. doi: 10.1037/adb0000545. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kahler C. W., Hustad J., Barnett N. P., Strong D. R., Borsari B. Validation of the 30-day version of the Brief Young Adult Alcohol Consequences Questionnaire for use in longitudinal studies. Journal of Studies on Alcohol and Drugs. 2008;69(4):611–615. doi: 10.15288/jsad.2008.69.611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kahler C. W., Strong D. R., Read J. P. Toward efficient and comprehensive measurement of the alcohol problems continuum in college students: The Brief Young Adult Alcohol Consequences Questionnaire. Alcoholism: Clinical and Experimental Research. 2005;29(7):1180–1189. doi: 10.1097/01.alc.0000171940.95813.a5. [DOI] [PubMed] [Google Scholar]
  19. Labhart F., Graham K., Wells S., Kuntsche E. Drinking before going to licensed premises: An event-level analysis of predrinking, alcohol consumption, and adverse outcomes. Alcoholism: Clinical and Experimental Research. 2013;37(2):284–291. doi: 10.1111/j.1530-0277.2012.01872.x. [DOI] [PubMed] [Google Scholar]
  20. LaBrie J. W., Earle A. M., Hummer J. F., Boyle S. C. Is prepartying a cause of heavy drinking and consequences rather than just a correlate? A longitudinal look at the relationship between prepartying, alcohol approval, and subsequent drinking and consequences. Substance Use & Misuse. 2016;51(8):1013–1023. doi: 10.3109/10826084.2016.1152493. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. LaBrie J. W., Pedersen E. R. Prepartying promotes heightened risk in the college environment: An event-level report. Addictive Behaviors. 2008;33(7):955–959. doi: 10.1016/j.addbeh.2008.02.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lee C. M., Cadigan J. M., Patrick M. E. Differences in reporting of perceived acute effects of alcohol use, marijuana use, and simultaneous alcohol and marijuana use. Drug and Alcohol Dependence. 2017;180:391–394. doi: 10.1016/j.drugalcdep.2017.08.029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lee C. M., Calhoun B. H., Abdallah D. A., Blayney J. A., Schultz N. R., Brunner M., Patrick M. E. Simultaneous alcohol and marijuana use among young adults: A scoping review of prevalence, patterns, psychosocial correlates, and consequences. Alcohol Research: Current Reviews. 2022;42(1) doi: 10.35946/arcr.v42.1.08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Linden-Carmichael A. N., Wardell J. D. Combined use of alcohol and cannabis: Introduction to the special issue. Psychology of Addictive Behaviors. 2021;35(6):621–627. doi: 10.1037/adb0000772. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Merrill J. E., Vermont L. N., Bachrach R. L., Read J. P. Is the pregame to blame? Event-level associations between pregaming and alcohol-related consequences. Journal of Studies on Alcohol and Drugs. 2013;74(5):757–764. doi: 10.15288/jsad.2013.74.757. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Mehta P. D., Neale M. C. People are variables too: Multilevel structural equations modeling. Psychological Methods. 2005;10(3):259–284. doi: 10.1037/1082-989x.10.3.259. [DOI] [PubMed] [Google Scholar]
  27. Metrik J., Gunn R. L., Jackson K. M., Sokolovsky A. W., Borsari B. Daily patterns of marijuana and alcohol co-use among individuals with alcohol and cannabis use disorders. Alcoholism: Clinical and Experimental Research. 2018;42(6):1096–1104. doi: 10.1111/acer.13639. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Miller M. B., Borsari B., Fernandez A. C., Yurasek A. M., Hustad J. T. P. Drinking location and pregaming as predictors of alcohol intoxication among mandated college students. Substance Use & Misuse. 2016;51(8):983–992. doi: 10.3109/10826084.2016.1152496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Muthén L. K., Muthén B. O. Los Angeles, CA: Authors; 2017. Mplus user's guide, v. 8.6. [Google Scholar]
  30. Neal D. J., Simons J. S. Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Psychology of Addictive Behaviors. 2007;21(4):441–452. doi: 10.1037/0893-164x.21.4.441. [DOI] [PubMed] [Google Scholar]
  31. O'Hara R. E., Armeli S., Tennen H. Alcohol and cannabis use among college students: Substitutes or complements? Addictive Behaviors. 2016;58:1–6. doi: 10.1016/j.addbeh.2016.02.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Patrick M. E., Kloska D. D., Terry-McElrath Y. M., Lee C. M., O'Malley P. M., Johnston L. D. Patterns of simultaneous and concurrent alcohol and marijuana use among adolescents. American Journal of Drug and Alcohol Abuse. 2018;44(4):441–451. doi: 10.1080/00952990.2017.1402335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Pedersen E. R. Using the solid research base on pregaming to begin intervention development: An epilogue to the special issue on pregaming. Substance Use & Misuse. 2016;51(8):1067–1073. doi: 10.1080/10826084.2016.1187533. [DOI] [PubMed] [Google Scholar]
  34. Pedersen E. R., Hummer J. F., Davis J. P., Fitzke R. E., Christie N. C., Witkiewitz K., Clapp J. D. A mobile-based pregaming drinking prevention intervention for college students: Study protocol for a randomized controlled trial. Addiction Science & Clinical Practice. 2022;17(1) doi: 10.1186/s13722-022-00314-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Pedersen E. R., Hummer J. F., Davis J. P., Fitzke R. E., Tran D. D., Witkiewitz K., Clapp J. D. A mobile-based pregaming drinking prevention intervention for college students: A pilot randomized controlled trial. Psychology of Addictive Behaviors. 2023;37(7):841–852. doi: 10.1037/adb0000925. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Pedersen E. R., LaBrie J. Partying before the party: Examining prepartying behavior among college students. Journal of American College Health. 2007;56(3):237–245. doi: 10.3200/jach.56.3.237-246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Prince M. A., Conner B. T., Pearson M. R. Quantifying cannabis: A field study of marijuana quantity estimation. Psychology of Addictive Behaviors. 2018;32(4):426–433. doi: 10.1037/adb0000370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Prince M. A., Pearson M. R., Bravo A. J., Montes K. S. A quantification of the alcohol use-consequences association in college student and clinical populations: A large, multi-sample study. American Journal on Addictions. 2018;27(2):116–123. doi: 10.1111/ajad.12686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Radomski S., Blayney J. A., Prince M. A., Read J. P. PTSD and pregaming in college students: A risky practice for an at-risk group. Substance Use & Misuse. 2016;51(8):1034–1046. doi: 10.3109/10826084.2016.1152497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Read J. P., Merrill J. E., Bytschkow K. Before the party starts: Risk factors and reasons for “pregaming” in college students. Journal of American College Health. 2010;58(5):461–472. doi: 10.1080/07448480903540523. [DOI] [PubMed] [Google Scholar]
  41. Schulenberg J. E., Patrick M. E., Johnston L. D., O'Malley P. M., Bachman J. G., Miech R. A. Ann Arbor, MI: Institute for Social Research, The University of Michigan; 2021. Monitoring the Future national survey results on drug use, 1975-2020: Volume II, College students and adults ages 19-60. [Google Scholar]
  42. Suerken C. K., Reboussin B. A., Egan K. L., Sutfin E. L., Wagoner K. G., Spangler J., Wolfson M. Marijuana use trajectories and academic outcomes among college students. Drug and Alcohol Dependence. 2016;162:137–145. doi: 10.1016/j.drugalcdep.2016.02.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. White H. R., Kilmer J. R., Fossos-Wong N., Hayes K., Sokolovsky A. W., Jackson K. M. Simultaneous alcohol and marijuana use among college students: Patterns, correlates, norms, and consequences. Alcoholism: Clinical and Experimental Research. 2019;43(7):1545–1555. doi: 10.1111/acer.14072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Yurasek A. M., Aston E. R., Metrik J. Co-use of alcohol and cannabis: A review. Current Addiction Reports. 2017;4(2):184–193. doi: 10.1007/s40429-017-0149-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zamboanga B. L., Olthuis J. V. What is pregaming and how prevalent is it among U.S. college students? An introduction to the special issue on pregaming. Substance Use & Misuse. 2016;51(8):953–960. doi: 10.1080/10826084.2016.1187524. [DOI] [PubMed] [Google Scholar]
  46. Zamboanga B. L., Van Hedger K., George A. M. Prologue to the special issue on predrinking and drinking game behaviors among adolescents and young adults in the United States and across the globe: Definitions and overview of prevalence rates. Addictive Behaviors. 2023;144:107731. doi: 10.1016/j.addbeh.2023.107731. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Studies on Alcohol and Drugs are provided here courtesy of Rutgers University. Center of Alcohol Studies

RESOURCES