Psychology of Addictive Behaviors 2015, Vol. 29, No. 3, 683– 689
© 2015 American Psychological Association 0893-164X/15/$12.00 http://dx.doi.org/10.1037/adb0000065
BRIEF REPORT
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Predrinking, Alcohol Use, and Breath Alcohol Concentration: A Study of Young Adult Bargoers Samantha Wells
Tara M. Dumas
Centre for Addiction and Mental Health, London, Ontario, Canada, and University of Toronto
University of Illinois at Urbana-Champaign
Sharon Bernards
Emmanuel Kuntsche
Centre for Addiction and Mental Health, London, Ontario, Canada
Addiction Switzerland Research Institute, Lausanne, Switzerland, and Radboud University
Florian Labhart
Kathryn Graham
Addiction Switzerland Research Institute, Lausanne, Switzerland
Centre for Addiction and Mental Health, London, Ontario, Canada, and University of Toronto
Predrinking (preloading, pregaming) has been found to be related to alcohol use and intoxication. However, most research relies on estimates of blood alcohol concentration and does not control for usual drinking pattern. We assessed whether predrinking was associated with subsequent alcohol consumption and breath alcohol concentration (BrAC) among 287 young adult bargoers (173 men [60.3%], Mage ⫽ 21.86 years, SD ⫽ 2.55 years) who were recruited in groups in an entertainment district of a midsized city in Ontario, Canada. We also examined whether predrinking by other group members interacted with individual predrinking in relation to amount consumed/BrAC. Adjusting for nesting of individuals within groups in hierarchical linear models, predrinkers were found to consume more drinks in the bar district and over the entire night compared to nonpredrinkers and had higher BrACs at the end of the night controlling for drinking pattern. A group- by individual-level interaction revealed that individual predrinking predicted higher BrACs for members of groups in which at least half of the group had been predrinking but not for members of groups in which less than half had been predrinking. This study confirms a direct link of predrinking with greater alcohol consumption and higher intoxication levels. Group- by individual-level effects suggest that group dynamics may have an important impact on individual drinking. Given that predrinking is associated with heavier consumption rather than reduced consumption at the bar, initiatives to address predrinking should include more effective policies to prevent intoxicated people from entering bars and being served once admitted. Keywords: predrinking, alcohol, breath alcohol concentration (BrAC), event level, bar goers
This article was published Online First May 18, 2015. Samantha Wells, Social and Epidemiological Research Department, Centre for Addiction and Mental Health, London, Ontario, Canada, and Clinical Public Health, Dalla Lana School of Public Health, University of Toronto; Tara M. Dumas, School of Social Work, University of Illinois at Urbana-Champaign; Sharon Bernards, Social and Epidemiological Research Department, Centre for Addiction and Mental Health; Emmanuel Kuntsche, Addiction Switzerland Research Institute, Lausanne, Switzerland and Behavioural Science Institute, Radboud University; Florian Labhart, Addiction Switzerland Research Institute; Kathryn Graham, Social and Epidemiological Research Department, Centre for Addiction and Mental Health, and Clinical Public Health, Dalla Lana School of Public Health, University of Toronto. Emmanual Kuntsche is also now the secretary of the Swiss Foundation for Alcohol Research. Research for this article was supported by a Canadian Institutes of Health Research (CIHR) Emerging Team Grant: Co-Morbidity of Brain
Disorders and Other Health Problems (CBG–101926, Samantha Wells). CIHR had no role in data collection or manuscript preparation. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the CIHR. The project also received support from the Canada Foundation for Innovation (20289) and the Ontario Ministry of Research and Innovation. We are grateful to Andrea Flynn for coordinating the research and to Roseanne Pulford for assisting with data collection. We thank the bargoer study field staff, Jocelyn Nikita, Fadia Ibrahim, Amanda Burton, Megan Bryant, Jesse Gall, John Ibrahim, Monika Niemasik, Jason Sereda, and Kyle Williamson. We also thank our community advisory committee for helpful advice regarding the project and the Windsor Police Service for assistance in safety planning. Finally, we thank Sue Steinback and Melissa MacLeod for editorial assistance. Correspondence concerning this article should be addressed to Samantha Wells, Centre for Addiction and Mental Health, 200-100 Collip Circle, London, Ontario, Canada N6G 4X8. E-mail: [email protected] 683
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A large proportion of young people engage in a practice known as “predrinking” (also called “preloading” or “pregaming”), involving the consumption of alcohol in a private setting before going to a social event, such as a bar or club. Although predrinking has been found to be positively associated with higher levels of alcohol use (LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read, Merrill, & Bytschkow, 2010), it is unclear whether this relation primarily reflects a tendency for heavier drinkers to engage in predrinking or whether the activity of predrinking itself is associated with greater consumption. A few theories can be proposed to explain the relation of predrinking with consumption. Earlier studies on predrinking simply compared predrinkers with nonpredrinkers, and thus one theory is that those who predrink are simply heavier drinkers compared to those who do not predrink, and this activity is just part of a drinking pattern among heavier drinkers. Consistent with this, predrinking has been shown to be positively related to drinking pattern (Kenney, Hummer, & LaBrie, 2010; Read et al., 2010). Based on justifications provided by young people that they predrink to save money (DeJong, DeRicco, & Schneider, 2010; Forsyth, 2010; Pedersen, LaBrie, & Kilmer, 2009; Wells, Graham, & Purcell, 2009), a related theory is that young people substitute on-premise alcohol use (i.e., higher priced drinks) with off-premise use (i.e., lower priced drinks), with total consumption unaffected. However, event-level evidence showing similar consumption at the bar by predrinkers and nonpredrinkers (Labhart, Graham, Wells, & Kuntsche, 2013) suggests that predrinking is not solely about substitution. Although predrinkers may tend to drink more than nonpredrinkers, an alternative theory is that the activity of predrinking itself increases consumption over the night. Predrinking typically involves the consumption of large amounts of alcohol (LaBrie, Hummer, Kenney, Lac, & Pedersen, 2011) in a short period of time (Pedersen & LaBrie, 2007). Such drinking behavior may have a priming effect on subsequent drinking. Consistent with this, one study found that the number of drinks consumed while predrinking was positively associated with more drinking later in the evening (LaBrie & Pedersen, 2008). Most research on predrinking has used assessments of alcohol use that are subject to recall bias due to memory deficits (Ekholm, 2004; Kuntsche & Labhart, 2012), such as retrospective reports of recent or typical predrinking occasions (e.g., Hughes, Anderson, Morleo, & Bellis, 2008; LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read et al., 2010), as well as estimates of blood alcohol concentrations (BACs) based on self-reported number of drinks consumed and duration of the drinking occasion (e.g., Borsari et al., 2007; Hummer, Napper, Ehret, & LaBrie, 2013; LaBrie & Pedersen, 2008; Read et al., 2010). Although some studies found a relationship between predrinking and higher breath alcohol concentration (BrAC) levels using breathalyzer data (Barry, Stellefson, Piazza-Gardner, Chaney, & Dodd, 2013; Clapp et al., 2009; Glindemann, Ehrhart, Maynard, & Geller, 2006), only one of these (Clapp et al., 2009) controlled for prior drinking, which was measured as recent heavy episodic drinking (five or more drinks in the prior 2 weeks) and thus may not reflect a longer term drinking pattern. Furthermore, very little is known about the role of peer groups in predrinking. Because young people typically attend bars in groups (Miller, Holder, & Voas, 2009) and peer groups
can influence the behaviors of individual members (Rubin, Bukowski, & Parker, 2006), peer groups may be an important factor in young people’s drinking through social modeling (Borsari & Carey, 2001) and conformity to perceived group norms (Rimal & Real, 2005). Although the collective behaviors of drinking groups (e.g., group drinking levels) have been shown to influence individual levels of consumption (Kuendig & Kuntsche, 2012; O’Grady & Skinner, 2007; van Schoor, Bot, & Engels, 2008), no studies to date have examined the role of group predrinking. Group predrinking may create a context where excessive drinking by group members is perceived as normative and/or encouraged and thus may result in higher individual drinking and intoxication. Teasing apart the factors linking predrinking with heavier consumption and intoxication has implications for identifying appropriate evidence-based prevention, such as whether interventions should target particular types of drinkers (i.e., heavy drinkers), address factors that promote predrinking (e.g., increase offpremise pricing to match on-premise pricing, address the role of the drinking group), or make young people’s predrinking occasions safer (e.g., improve bar staff behavior in admitting and serving people who have been drinking). Using alcohol use and breathalyzer data collected from young adult groups of bargoers on their way to and from bars and clubs as well as follow-up online survey data on usual drinking patterns, we hypothesized that, compared to nonpredrinkers, predrinkers would (a) be more likely to report a pattern of heavy drinking, (b) consume at least as many drinks while at bars, and (c) consume a larger number of drinks in total (over the entire night) and have higher BrACs at the end of the night. We also hypothesized that predrinkers would consume more alcohol if they were in groups where most others had also been predrinking.
Methods Design and Procedure Same-sex groups of three to five young adults (aged 19 –29 years) were recruited in a downtown bar district of a midsized city in Ontario, Canada. Recruitment was restricted to same-sex groups because a key focus of the study was peer status (analyzed in other studies; e.g., Dumas, Graham, Bernards, & Wells, 2014), which could be assessed only in single-sex groups. Recruitment occurred on Thursday, Friday, and Saturday evenings over an 11-week period (May to July 2012). Between 10 p.m. and 12:30 a.m., teams of two to three researchers randomly selected eligible groups for recruitment based on the “fixed line method” (Voas et al., 2006). Participation in the study involved three components. First, upon recruitment, participants were asked to complete the “entry” survey, which included a brief interview and a breathalyzer sample at a mobile research station. During the entry survey, participants were asked to return for a brief “exit” survey and to participate in an online survey at a later time. They were given a business card with study information and a website address for the online survey. Those willing (78%) were also sent a text message about the online survey and a reminder to return for the exit survey. Second, before leaving the bar district, participants returned to the data collection site for a brief interview (exit survey) with questions on how much
PREDRINKING, ALCOHOL USE, AND INTOXICATION
they had been drinking since the entry survey and a breathalyzer test. Third, participants completed an online survey at a later time, covering usual drinking patterns and other topics. Participants received gift cards for each study component. The Research Ethics Board at the Centre for Addiction and Mental Health approved all study protocols.
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Participants A total of 357 bargoers (218 men and 139 women) participated in the entry survey. Of these, 287 (173 men and 114 women) returned for the exit survey (80.4%), and 293 (174 men and 119 women) completed the online survey (82.1%). The present analyses use data from participants who completed both the entry and exit surveys (n ⫽ 287, 60.3% male; 68.3% students; Mage ⫽ 21.86 years, SD ⫽ 2.55 years). Analyses controlling for general drinking pattern were restricted to 252 participants who had completed all three surveys (151 men and 101 women). Those who participated in the exit survey were compared with those who did not return at exit on the main variables (age, student status, time of entry and exit, day of week, and predrinking status). Only day of the week was significant, with participants on Thursday evenings more likely to complete the exit survey (89.7%) than those who participated on Fridays (76.6%) or Saturdays (77.3%) (p ⫽ .013). We also assessed whether number of drinks and BrAC at entry were associated with participation in the exit survey. Higher BrAC and number of drinks were found among individuals who did not return at exit compared to those who completed the exit survey (MBrAC ⫽ .058 vs. .037, p ⫽ .001; Mno. drinks ⫽ 4.80 vs. 3.50, p ⫽ .005).
Measures Predrinking. We defined predrinking as any drinking offpremise (e.g., at home, someone else’s home, outdoors) prior to going to a licensed premise. During the entry survey, participants were asked whether they had been drinking any alcohol that night and, if so, where they had started drinking. Those who had been to multiple locations were asked to list them in chronological order. All participants who reported drinking off-premise prior to the entry survey were coded as predrinkers, and all others were coded as nonpredrinkers. Group-level predrinking. We created a dichotomous variable indicating whether at least half of group members had been predrinking (i.e., coded as 1; otherwise coded as 0). Individual characteristics. During the entry survey, participants were asked to report their age and student status (college, university, other student, or not a student), which was coded as student versus nonstudent. Day and time of entry and exit survey. The day of the week and start time of the entry and exit surveys were recorded. From these, the number of minutes between completion of entry and exit surveys was computed. Number of drinks. During the entry survey, participants were shown a picture displaying typical Canadian standard drink sizes (i.e., 341 ml [12 oz] of beer, 142 ml [5 oz] of wine, 43 ml [1.5 oz] of spirits such as vodka, or 341 ml [12 oz] of a premixed drink or “cooler”) and asked how many standard drinks they had consumed prior to recruitment. During the exit survey, participants were
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asked how many drinks they had consumed since the entry survey. Total number of drinks consumed over the evening was calculated by summing the number of drinks prior to and after entry. BrAC. During the exit survey, participants were asked to provide a breath sample using a handheld breathalyzer unit (Intoxlyzer-CMI, CMI, Inc., Owensboro, KY). BrAC readings were not visible to participants or to research assistants. Usual drinking behavior. As part of the online survey, using the same definition of standard drink sizes described above, participants were asked to report the largest number of drinks consumed on any occasion in the past 12 months and their usual past year frequency of drinking on a 7-point Likert scale (1 ⫽ never, 2 ⫽ less than once a month, 3 ⫽ one to three times a month, 4 ⫽ once a week, 5 ⫽ two to three times a week, 6 ⫽ four to six times a week, 7 ⫽ every day). To assess heavy episodic drinking (HED), we asked how many times in the previous month they had consumed 5–7 drinks, 8 –11 drinks, or 12 or more drinks on a single occasion, which were summed to reflect the number of times participants had consumed 5 or more drinks.
Analyses Chi-square and t tests were used to compare predrinkers with nonpredrinkers in terms of individual characteristics (age and student status), night characteristics (time of entry and exit, minutes from entry to exit, and day of the week), night alcohol use (total number of drinks and exit BrAC), and general drinking pattern. Intraclass correlations (ICCs) were computed to assess the extent of clustering at the group level for the three outcome variables (total number of drinks, number of drinks consumed between entry and exit, and exit BrAC). Hierarchical linear modeling (HLM) was used to account for nesting of individuals within groups using the software program HLM 6.0 (Bryk & Raudenbush, 1992). HLM models tested associations of predrinking with the three drinking outcomes (analyzed separately), controlling for gender, age, usual drinking behavior, and significant covariates related to predrinking (p ⬍ .10) (see Table 1). Explanatory variables were entered in four steps: (a) unadjusted association of predrinking (vs. nonpredrinking), (b) adjustment for covariates at Level 1 (i.e., age, time between entry and exit [in minutes], and night [Saturday vs. other]) and Level 2 (i.e., gender of the drinking group), (c) adjustment for usual drinking behavior (i.e., maximum number of drinks), and (d) cross-level interactions of group predrinking by individual predrinking, with simple slope tests as outlined by Preacher, Curran, and Bauer (2006). Explanatory variables were grandmean centered for ease of interpretation.
Results As shown in Table 1, predrinkers consumed significantly more drinks in total and between the entry and exit surveys (i.e., while in the bar district). They also had significantly higher BrAC levels compared to nonpredrinkers. In terms of usual drinking behavior, both frequency of HED and maximum drinks were significantly higher for predrinkers than for nonpredrinkers, whereas drinking frequency was nonsignificant. All alcohol measures had significant group ICCs (total number of drinks ICC ⫽ .49, 2 ⫽ 368.44, p ⬍ .001; number of
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Table 1 Comparison of Predrinkers and Nonpredrinkers in Terms of Individual Characteristics, Night Characteristics, Night Alcohol Use, and Usual Drinking Pattern No predrinkinga (n ⫽ 146)
Predrinking (n ⫽ 141)
t value or 2
79 (54.1) 21.99 (2.43) 97 (66.4)
35 (24.8) 21.74 (2.68) 99 (70.2)
25.70ⴱⴱⴱ 0.80 0.49
11:37 (0:42) 1:32 (0:43) 1:55 (0:39)
11:42 (0:46) 1:51 (0:38) 2:09 (0:40)
0.98 3.99ⴱⴱⴱ 3.01ⴱⴱ 5.15†
44 (50.6) 58 (59.2) 44 (43.1)
43 (49.4) 40 (40.8) 58 (56.9)
2.86 (3.21) 5.10 (4.53) .04 (.05) n ⫽ 129 5.01 (6.74) 11.53 (6.67) 2.88 (1.13)
4.48 (3.69) 9.28 (5.11) .08 (.05) n ⫽ 123 7.57 (9.80) 14.87 (7.23) 3.06 (1.18)
Individual characteristics Female (ref ⫽ male), n (%) Age, M (SD) Student (ref ⫽ nonstudent), n (%) Night characteristics, M (SD) Time of entry (p.m.) Time of exit (a.m.) Hours from entry to exit Day of week, n (%) Thursday Friday Saturday Night alcohol use/intoxication, M (SD) No. of drinks between entry and exit Total no. of drinks BrAC at exit Usual drinking pattern, M (SD) Frequency of HED Max no. of drinks Frequency of drinking
3.97ⴱⴱⴱ 7.32ⴱⴱⴱ 6.41ⴱⴱⴱ 2.17ⴱ 3.77ⴱⴱⴱ 1.19
Note. BrAC ⫽ breath alcohol concentration; HED ⫽ heavy episodic drinking. Separate analyses by gender are available upon request from the authors. a The group of nonpredrinkers includes people who had not been drinking prior to the entry survey as well as people who had already been drinking at a bar. † p ⬍ .10. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
drinks between entry and exit ICC ⫽ .44, 2 ⫽ 431.46, p ⬍ .001; exit BrAC ICC ⫽ .51, 2 ⫽ 361.04, p ⬍ .001), indicating a need to control for nesting of individuals in groups. Table 2 presents the results from the HLM analyses. Step 1 revealed positive associations of predrinking with total drinks, number of drinks consumed between entry and exit, and exit BrAC, adjusting for nesting in groups. Effects remained significant controlling for age, time between entry and exit, day of the week, and gender (Step 2) and for maximum number of drinks (Step 3). Models were also computed controlling for HED, with similar results obtained. We also included student status as a control variable; it was not significantly related to any outcomes and did not change the results when included in the models. Step 4 identified a significant cross-level interaction between individual and group predrinking in explaining exit BrAC. Simple slopes analysis revealed that individuals who predrank were significantly more likely to have higher BrACs at the end of the night but only when at least half of group members also predrank (b ⫽ .04, t ⫽ 2.04, p ⫽ .04) and not when less than half of their group members predrank (b ⫽ .01, t ⫽ 0.65, p ⫽ .51).
Discussion Our findings support our first hypothesis and corroborate previous evidence that predrinking is associated with heavier alcohol use (LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read et al., 2010): predrinkers were more likely than nonpredrinkers to engage in HED and consumed a larger maximum number of drinks per occasion. This supports the notion
of predrinking being part of a pattern of heavy episodic drinking (Kenney et al., 2010; Read et al., 2010) and planned intoxication (Engineer, Phillips, Thompson, & Nicholls, 2003; Measham & Brain, 2005) but is not necessarily related to how often the young person drinks. Consistent with our second hypothesis, predrinkers consumed significantly more alcohol while in the bar district than did nonpredrinkers. Thus, although young people may predrink with the intention of saving money by drinking less while on-premise (DeJong et al., 2010; Forsyth, 2010; Pedersen et al., 2009; Wells et al., 2009), our results suggest predrinking is not followed by less drinking and may actually promote further drinking. As per our third hypothesis, compared with nonpredrinkers, predrinkers consumed a significantly larger number of drinks in total (over the entire night) and, consistent with previous research (Barry et al., 2013; Borsari et al., 2007; Clapp et al., 2009; Glindemann et al., 2006; Hummer et al., 2013; LaBrie & Pedersen, 2008), had higher intoxication levels, as measured with breathalyzer data rather than estimates of BAC. These effects remained significant controlling for drinking pattern, suggesting that the association of predrinking with increased drinking and higher BrAC are not fully explained by the usual pattern of drinking and that the act of predrinking itself may be associated with heavier consumption. Consistent with the last hypothesis, our results indicate that individuals who predrank were significantly more likely to have higher BrACs at the end of the night but only when the majority of their group members also predrank. This finding suggests that
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Table 2 Hierarchical Linear Models Comparing Predrinkers With Nonpredrinkers on Alcohol Use and BrAC, Controlling for Maximum Number of Drinks and Other Potential Confounders No. drinks between entry and exit
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b Step 1 Predrinking vs. not Step 2 Predrinking vs. not Gender of the group (Level 2) Age Hours from entry to exit Saturday vs. other Step 3 Predrinking vs. not Gender of the group (Level 2) Age Minutes from entry to exit Saturday vs. other Max no. of drinksa Step 4 Predrinking vs. not
3.790ⴱⴱⴱ 1.526ⴱⴱ ⫺0.835 0.060 0.005 0.971 1.210ⴱ 0.110 0.038 0.004 0.605 0.178ⴱⴱⴱ
Total no. of drinks
SE
b
SE
0.318
7.321ⴱⴱⴱ
0.461
0.487 0.563 0.108 0.004 0.717
3.144ⴱⴱⴱ ⫺1.147 0.010 0.005 1.540†
0.701 0.855 0.132 0.004 0.856
0.601 0.498 0.089 0.003 0.601 0.044
2.684ⴱⴱⴱ 0.486 0.045 0.003 1.215† 0.309ⴱⴱⴱ
0.709 0.606 0.111 0.003 0.685 0.054
No significant interactions
No significant interactions
Gender of the group (Level 2) Age Minutes from entry to exit Saturday vs. other Max no. of drinksa Group predrinking (Level 2) Individual predrinking (Level 1) by group predrinking (Level 2)b
Exit BrAC b 0.061ⴱⴱⴱ 0.026ⴱⴱ ⫺0.003 0.001 0.000 0.000
SE 0.005 0.007 0.009 0.001 0.000 0.008
0.027ⴱⴱⴱ 0.004 0.000 0.000 0.001 0.001
0.008 0.009 0.001 0.000 0.009 0.001
0.010
0.009
0.007 0.000 0.000 ⫺0.002 0.001 0.029ⴱ 0.059ⴱⴱ
0.008 0.001 0.000 0.009 0.001 0.012 0.019
Note. BrAC ⫽ breath alcohol concentration. a Models are presented controlling for maximum number of drinks, because it was most strongly related to predrinking. Models were also computed controlling for heavy episodic drinking, and similar results were obtained. b Interaction effects for gender of the group by individual predrinking were also tested but were nonsignificant. † p ⬍ .10. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
group members become more intoxicated when all or most members of a social group engage in predrinking. Thus, as suggested in previous research, what happens at the group level has an important impact on behavior (Miller, Byrnes, Branner, Johnson, & Voas, 2013). Further research is needed to assess how the group influences individual-level drinking over the course of the night, such as through contagion of group norms, effects of group leaders (Dumas, Wells, Flynn, Lange, & Graham, 2014), round buying, or possibly drinking games that occur while predrinking (Hummer et al., 2013). A limitation of the present study is that findings may not be generalizable to mixed-gender groups and larger groups (i.e., greater than five). Thus, effects of gender composition and size of the drinking group as they relate to predrinking should be examined in future research. Also, gender-specific analyses were not possible due to small sample sizes and thus should be conducted in future studies with larger samples. A further limitation is loss to follow-up, with exit survey participants more likely to have been recruited on Thursday evenings and to have lower alcohol use and intoxication levels at entry compared to those who did not return at exit. However, given that participation at exit was not associated with predrinking status, it is unlikely that the association between predrinking and BrAC is confounded by loss to follow-up.
Conclusion The present study advances the field by demonstrating that predrinking remains significantly associated with greater consumption and intoxication, even after adjusting for drinking pattern. An implication of this study is that programs and policies are needed to reduce predrinking, such as addressing large discrepancies between on- and off-premise alcohol pricing. Such price discrepancies likely motivate predrinking (Wells, Mihic, Tremblay, Graham, & Demers, 2008), even if predrinking does not have the intended effect of consuming less at the bar. Bar staff training and enhanced enforcement are needed to ensure that staff recognize and deter intoxicated patrons when they arrive at the bar and better monitor how much they are drinking while at the bar (see Graham et al., 2014). Initiatives may be needed that address group dynamics, such as social modeling, peer influence, and conformity to dominant group norms. Policy and programming aimed at changing drinking norms and practices, such as rapid consumption, should be considered as well as programs promoting safer choices (e.g., having a sober friend present) when engaging in predrinking. Finally, counseling programs, especially for heavy-drinking young adults, may need to consider predrinking and its role in heavy alcohol use.
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Received October 7, 2014 Revision received January 19, 2015 Accepted January 21, 2015 䡲
© 2015 American Psychological Association 0893-164X/15/$12.00 http://dx.doi.org/10.1037/adb0000065
BRIEF REPORT
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Predrinking, Alcohol Use, and Breath Alcohol Concentration: A Study of Young Adult Bargoers Samantha Wells
Tara M. Dumas
Centre for Addiction and Mental Health, London, Ontario, Canada, and University of Toronto
University of Illinois at Urbana-Champaign
Sharon Bernards
Emmanuel Kuntsche
Centre for Addiction and Mental Health, London, Ontario, Canada
Addiction Switzerland Research Institute, Lausanne, Switzerland, and Radboud University
Florian Labhart
Kathryn Graham
Addiction Switzerland Research Institute, Lausanne, Switzerland
Centre for Addiction and Mental Health, London, Ontario, Canada, and University of Toronto
Predrinking (preloading, pregaming) has been found to be related to alcohol use and intoxication. However, most research relies on estimates of blood alcohol concentration and does not control for usual drinking pattern. We assessed whether predrinking was associated with subsequent alcohol consumption and breath alcohol concentration (BrAC) among 287 young adult bargoers (173 men [60.3%], Mage ⫽ 21.86 years, SD ⫽ 2.55 years) who were recruited in groups in an entertainment district of a midsized city in Ontario, Canada. We also examined whether predrinking by other group members interacted with individual predrinking in relation to amount consumed/BrAC. Adjusting for nesting of individuals within groups in hierarchical linear models, predrinkers were found to consume more drinks in the bar district and over the entire night compared to nonpredrinkers and had higher BrACs at the end of the night controlling for drinking pattern. A group- by individual-level interaction revealed that individual predrinking predicted higher BrACs for members of groups in which at least half of the group had been predrinking but not for members of groups in which less than half had been predrinking. This study confirms a direct link of predrinking with greater alcohol consumption and higher intoxication levels. Group- by individual-level effects suggest that group dynamics may have an important impact on individual drinking. Given that predrinking is associated with heavier consumption rather than reduced consumption at the bar, initiatives to address predrinking should include more effective policies to prevent intoxicated people from entering bars and being served once admitted. Keywords: predrinking, alcohol, breath alcohol concentration (BrAC), event level, bar goers
This article was published Online First May 18, 2015. Samantha Wells, Social and Epidemiological Research Department, Centre for Addiction and Mental Health, London, Ontario, Canada, and Clinical Public Health, Dalla Lana School of Public Health, University of Toronto; Tara M. Dumas, School of Social Work, University of Illinois at Urbana-Champaign; Sharon Bernards, Social and Epidemiological Research Department, Centre for Addiction and Mental Health; Emmanuel Kuntsche, Addiction Switzerland Research Institute, Lausanne, Switzerland and Behavioural Science Institute, Radboud University; Florian Labhart, Addiction Switzerland Research Institute; Kathryn Graham, Social and Epidemiological Research Department, Centre for Addiction and Mental Health, and Clinical Public Health, Dalla Lana School of Public Health, University of Toronto. Emmanual Kuntsche is also now the secretary of the Swiss Foundation for Alcohol Research. Research for this article was supported by a Canadian Institutes of Health Research (CIHR) Emerging Team Grant: Co-Morbidity of Brain
Disorders and Other Health Problems (CBG–101926, Samantha Wells). CIHR had no role in data collection or manuscript preparation. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the CIHR. The project also received support from the Canada Foundation for Innovation (20289) and the Ontario Ministry of Research and Innovation. We are grateful to Andrea Flynn for coordinating the research and to Roseanne Pulford for assisting with data collection. We thank the bargoer study field staff, Jocelyn Nikita, Fadia Ibrahim, Amanda Burton, Megan Bryant, Jesse Gall, John Ibrahim, Monika Niemasik, Jason Sereda, and Kyle Williamson. We also thank our community advisory committee for helpful advice regarding the project and the Windsor Police Service for assistance in safety planning. Finally, we thank Sue Steinback and Melissa MacLeod for editorial assistance. Correspondence concerning this article should be addressed to Samantha Wells, Centre for Addiction and Mental Health, 200-100 Collip Circle, London, Ontario, Canada N6G 4X8. E-mail: [email protected] 683
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A large proportion of young people engage in a practice known as “predrinking” (also called “preloading” or “pregaming”), involving the consumption of alcohol in a private setting before going to a social event, such as a bar or club. Although predrinking has been found to be positively associated with higher levels of alcohol use (LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read, Merrill, & Bytschkow, 2010), it is unclear whether this relation primarily reflects a tendency for heavier drinkers to engage in predrinking or whether the activity of predrinking itself is associated with greater consumption. A few theories can be proposed to explain the relation of predrinking with consumption. Earlier studies on predrinking simply compared predrinkers with nonpredrinkers, and thus one theory is that those who predrink are simply heavier drinkers compared to those who do not predrink, and this activity is just part of a drinking pattern among heavier drinkers. Consistent with this, predrinking has been shown to be positively related to drinking pattern (Kenney, Hummer, & LaBrie, 2010; Read et al., 2010). Based on justifications provided by young people that they predrink to save money (DeJong, DeRicco, & Schneider, 2010; Forsyth, 2010; Pedersen, LaBrie, & Kilmer, 2009; Wells, Graham, & Purcell, 2009), a related theory is that young people substitute on-premise alcohol use (i.e., higher priced drinks) with off-premise use (i.e., lower priced drinks), with total consumption unaffected. However, event-level evidence showing similar consumption at the bar by predrinkers and nonpredrinkers (Labhart, Graham, Wells, & Kuntsche, 2013) suggests that predrinking is not solely about substitution. Although predrinkers may tend to drink more than nonpredrinkers, an alternative theory is that the activity of predrinking itself increases consumption over the night. Predrinking typically involves the consumption of large amounts of alcohol (LaBrie, Hummer, Kenney, Lac, & Pedersen, 2011) in a short period of time (Pedersen & LaBrie, 2007). Such drinking behavior may have a priming effect on subsequent drinking. Consistent with this, one study found that the number of drinks consumed while predrinking was positively associated with more drinking later in the evening (LaBrie & Pedersen, 2008). Most research on predrinking has used assessments of alcohol use that are subject to recall bias due to memory deficits (Ekholm, 2004; Kuntsche & Labhart, 2012), such as retrospective reports of recent or typical predrinking occasions (e.g., Hughes, Anderson, Morleo, & Bellis, 2008; LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read et al., 2010), as well as estimates of blood alcohol concentrations (BACs) based on self-reported number of drinks consumed and duration of the drinking occasion (e.g., Borsari et al., 2007; Hummer, Napper, Ehret, & LaBrie, 2013; LaBrie & Pedersen, 2008; Read et al., 2010). Although some studies found a relationship between predrinking and higher breath alcohol concentration (BrAC) levels using breathalyzer data (Barry, Stellefson, Piazza-Gardner, Chaney, & Dodd, 2013; Clapp et al., 2009; Glindemann, Ehrhart, Maynard, & Geller, 2006), only one of these (Clapp et al., 2009) controlled for prior drinking, which was measured as recent heavy episodic drinking (five or more drinks in the prior 2 weeks) and thus may not reflect a longer term drinking pattern. Furthermore, very little is known about the role of peer groups in predrinking. Because young people typically attend bars in groups (Miller, Holder, & Voas, 2009) and peer groups
can influence the behaviors of individual members (Rubin, Bukowski, & Parker, 2006), peer groups may be an important factor in young people’s drinking through social modeling (Borsari & Carey, 2001) and conformity to perceived group norms (Rimal & Real, 2005). Although the collective behaviors of drinking groups (e.g., group drinking levels) have been shown to influence individual levels of consumption (Kuendig & Kuntsche, 2012; O’Grady & Skinner, 2007; van Schoor, Bot, & Engels, 2008), no studies to date have examined the role of group predrinking. Group predrinking may create a context where excessive drinking by group members is perceived as normative and/or encouraged and thus may result in higher individual drinking and intoxication. Teasing apart the factors linking predrinking with heavier consumption and intoxication has implications for identifying appropriate evidence-based prevention, such as whether interventions should target particular types of drinkers (i.e., heavy drinkers), address factors that promote predrinking (e.g., increase offpremise pricing to match on-premise pricing, address the role of the drinking group), or make young people’s predrinking occasions safer (e.g., improve bar staff behavior in admitting and serving people who have been drinking). Using alcohol use and breathalyzer data collected from young adult groups of bargoers on their way to and from bars and clubs as well as follow-up online survey data on usual drinking patterns, we hypothesized that, compared to nonpredrinkers, predrinkers would (a) be more likely to report a pattern of heavy drinking, (b) consume at least as many drinks while at bars, and (c) consume a larger number of drinks in total (over the entire night) and have higher BrACs at the end of the night. We also hypothesized that predrinkers would consume more alcohol if they were in groups where most others had also been predrinking.
Methods Design and Procedure Same-sex groups of three to five young adults (aged 19 –29 years) were recruited in a downtown bar district of a midsized city in Ontario, Canada. Recruitment was restricted to same-sex groups because a key focus of the study was peer status (analyzed in other studies; e.g., Dumas, Graham, Bernards, & Wells, 2014), which could be assessed only in single-sex groups. Recruitment occurred on Thursday, Friday, and Saturday evenings over an 11-week period (May to July 2012). Between 10 p.m. and 12:30 a.m., teams of two to three researchers randomly selected eligible groups for recruitment based on the “fixed line method” (Voas et al., 2006). Participation in the study involved three components. First, upon recruitment, participants were asked to complete the “entry” survey, which included a brief interview and a breathalyzer sample at a mobile research station. During the entry survey, participants were asked to return for a brief “exit” survey and to participate in an online survey at a later time. They were given a business card with study information and a website address for the online survey. Those willing (78%) were also sent a text message about the online survey and a reminder to return for the exit survey. Second, before leaving the bar district, participants returned to the data collection site for a brief interview (exit survey) with questions on how much
PREDRINKING, ALCOHOL USE, AND INTOXICATION
they had been drinking since the entry survey and a breathalyzer test. Third, participants completed an online survey at a later time, covering usual drinking patterns and other topics. Participants received gift cards for each study component. The Research Ethics Board at the Centre for Addiction and Mental Health approved all study protocols.
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Participants A total of 357 bargoers (218 men and 139 women) participated in the entry survey. Of these, 287 (173 men and 114 women) returned for the exit survey (80.4%), and 293 (174 men and 119 women) completed the online survey (82.1%). The present analyses use data from participants who completed both the entry and exit surveys (n ⫽ 287, 60.3% male; 68.3% students; Mage ⫽ 21.86 years, SD ⫽ 2.55 years). Analyses controlling for general drinking pattern were restricted to 252 participants who had completed all three surveys (151 men and 101 women). Those who participated in the exit survey were compared with those who did not return at exit on the main variables (age, student status, time of entry and exit, day of week, and predrinking status). Only day of the week was significant, with participants on Thursday evenings more likely to complete the exit survey (89.7%) than those who participated on Fridays (76.6%) or Saturdays (77.3%) (p ⫽ .013). We also assessed whether number of drinks and BrAC at entry were associated with participation in the exit survey. Higher BrAC and number of drinks were found among individuals who did not return at exit compared to those who completed the exit survey (MBrAC ⫽ .058 vs. .037, p ⫽ .001; Mno. drinks ⫽ 4.80 vs. 3.50, p ⫽ .005).
Measures Predrinking. We defined predrinking as any drinking offpremise (e.g., at home, someone else’s home, outdoors) prior to going to a licensed premise. During the entry survey, participants were asked whether they had been drinking any alcohol that night and, if so, where they had started drinking. Those who had been to multiple locations were asked to list them in chronological order. All participants who reported drinking off-premise prior to the entry survey were coded as predrinkers, and all others were coded as nonpredrinkers. Group-level predrinking. We created a dichotomous variable indicating whether at least half of group members had been predrinking (i.e., coded as 1; otherwise coded as 0). Individual characteristics. During the entry survey, participants were asked to report their age and student status (college, university, other student, or not a student), which was coded as student versus nonstudent. Day and time of entry and exit survey. The day of the week and start time of the entry and exit surveys were recorded. From these, the number of minutes between completion of entry and exit surveys was computed. Number of drinks. During the entry survey, participants were shown a picture displaying typical Canadian standard drink sizes (i.e., 341 ml [12 oz] of beer, 142 ml [5 oz] of wine, 43 ml [1.5 oz] of spirits such as vodka, or 341 ml [12 oz] of a premixed drink or “cooler”) and asked how many standard drinks they had consumed prior to recruitment. During the exit survey, participants were
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asked how many drinks they had consumed since the entry survey. Total number of drinks consumed over the evening was calculated by summing the number of drinks prior to and after entry. BrAC. During the exit survey, participants were asked to provide a breath sample using a handheld breathalyzer unit (Intoxlyzer-CMI, CMI, Inc., Owensboro, KY). BrAC readings were not visible to participants or to research assistants. Usual drinking behavior. As part of the online survey, using the same definition of standard drink sizes described above, participants were asked to report the largest number of drinks consumed on any occasion in the past 12 months and their usual past year frequency of drinking on a 7-point Likert scale (1 ⫽ never, 2 ⫽ less than once a month, 3 ⫽ one to three times a month, 4 ⫽ once a week, 5 ⫽ two to three times a week, 6 ⫽ four to six times a week, 7 ⫽ every day). To assess heavy episodic drinking (HED), we asked how many times in the previous month they had consumed 5–7 drinks, 8 –11 drinks, or 12 or more drinks on a single occasion, which were summed to reflect the number of times participants had consumed 5 or more drinks.
Analyses Chi-square and t tests were used to compare predrinkers with nonpredrinkers in terms of individual characteristics (age and student status), night characteristics (time of entry and exit, minutes from entry to exit, and day of the week), night alcohol use (total number of drinks and exit BrAC), and general drinking pattern. Intraclass correlations (ICCs) were computed to assess the extent of clustering at the group level for the three outcome variables (total number of drinks, number of drinks consumed between entry and exit, and exit BrAC). Hierarchical linear modeling (HLM) was used to account for nesting of individuals within groups using the software program HLM 6.0 (Bryk & Raudenbush, 1992). HLM models tested associations of predrinking with the three drinking outcomes (analyzed separately), controlling for gender, age, usual drinking behavior, and significant covariates related to predrinking (p ⬍ .10) (see Table 1). Explanatory variables were entered in four steps: (a) unadjusted association of predrinking (vs. nonpredrinking), (b) adjustment for covariates at Level 1 (i.e., age, time between entry and exit [in minutes], and night [Saturday vs. other]) and Level 2 (i.e., gender of the drinking group), (c) adjustment for usual drinking behavior (i.e., maximum number of drinks), and (d) cross-level interactions of group predrinking by individual predrinking, with simple slope tests as outlined by Preacher, Curran, and Bauer (2006). Explanatory variables were grandmean centered for ease of interpretation.
Results As shown in Table 1, predrinkers consumed significantly more drinks in total and between the entry and exit surveys (i.e., while in the bar district). They also had significantly higher BrAC levels compared to nonpredrinkers. In terms of usual drinking behavior, both frequency of HED and maximum drinks were significantly higher for predrinkers than for nonpredrinkers, whereas drinking frequency was nonsignificant. All alcohol measures had significant group ICCs (total number of drinks ICC ⫽ .49, 2 ⫽ 368.44, p ⬍ .001; number of
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Table 1 Comparison of Predrinkers and Nonpredrinkers in Terms of Individual Characteristics, Night Characteristics, Night Alcohol Use, and Usual Drinking Pattern No predrinkinga (n ⫽ 146)
Predrinking (n ⫽ 141)
t value or 2
79 (54.1) 21.99 (2.43) 97 (66.4)
35 (24.8) 21.74 (2.68) 99 (70.2)
25.70ⴱⴱⴱ 0.80 0.49
11:37 (0:42) 1:32 (0:43) 1:55 (0:39)
11:42 (0:46) 1:51 (0:38) 2:09 (0:40)
0.98 3.99ⴱⴱⴱ 3.01ⴱⴱ 5.15†
44 (50.6) 58 (59.2) 44 (43.1)
43 (49.4) 40 (40.8) 58 (56.9)
2.86 (3.21) 5.10 (4.53) .04 (.05) n ⫽ 129 5.01 (6.74) 11.53 (6.67) 2.88 (1.13)
4.48 (3.69) 9.28 (5.11) .08 (.05) n ⫽ 123 7.57 (9.80) 14.87 (7.23) 3.06 (1.18)
Individual characteristics Female (ref ⫽ male), n (%) Age, M (SD) Student (ref ⫽ nonstudent), n (%) Night characteristics, M (SD) Time of entry (p.m.) Time of exit (a.m.) Hours from entry to exit Day of week, n (%) Thursday Friday Saturday Night alcohol use/intoxication, M (SD) No. of drinks between entry and exit Total no. of drinks BrAC at exit Usual drinking pattern, M (SD) Frequency of HED Max no. of drinks Frequency of drinking
3.97ⴱⴱⴱ 7.32ⴱⴱⴱ 6.41ⴱⴱⴱ 2.17ⴱ 3.77ⴱⴱⴱ 1.19
Note. BrAC ⫽ breath alcohol concentration; HED ⫽ heavy episodic drinking. Separate analyses by gender are available upon request from the authors. a The group of nonpredrinkers includes people who had not been drinking prior to the entry survey as well as people who had already been drinking at a bar. † p ⬍ .10. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
drinks between entry and exit ICC ⫽ .44, 2 ⫽ 431.46, p ⬍ .001; exit BrAC ICC ⫽ .51, 2 ⫽ 361.04, p ⬍ .001), indicating a need to control for nesting of individuals in groups. Table 2 presents the results from the HLM analyses. Step 1 revealed positive associations of predrinking with total drinks, number of drinks consumed between entry and exit, and exit BrAC, adjusting for nesting in groups. Effects remained significant controlling for age, time between entry and exit, day of the week, and gender (Step 2) and for maximum number of drinks (Step 3). Models were also computed controlling for HED, with similar results obtained. We also included student status as a control variable; it was not significantly related to any outcomes and did not change the results when included in the models. Step 4 identified a significant cross-level interaction between individual and group predrinking in explaining exit BrAC. Simple slopes analysis revealed that individuals who predrank were significantly more likely to have higher BrACs at the end of the night but only when at least half of group members also predrank (b ⫽ .04, t ⫽ 2.04, p ⫽ .04) and not when less than half of their group members predrank (b ⫽ .01, t ⫽ 0.65, p ⫽ .51).
Discussion Our findings support our first hypothesis and corroborate previous evidence that predrinking is associated with heavier alcohol use (LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Read et al., 2010): predrinkers were more likely than nonpredrinkers to engage in HED and consumed a larger maximum number of drinks per occasion. This supports the notion
of predrinking being part of a pattern of heavy episodic drinking (Kenney et al., 2010; Read et al., 2010) and planned intoxication (Engineer, Phillips, Thompson, & Nicholls, 2003; Measham & Brain, 2005) but is not necessarily related to how often the young person drinks. Consistent with our second hypothesis, predrinkers consumed significantly more alcohol while in the bar district than did nonpredrinkers. Thus, although young people may predrink with the intention of saving money by drinking less while on-premise (DeJong et al., 2010; Forsyth, 2010; Pedersen et al., 2009; Wells et al., 2009), our results suggest predrinking is not followed by less drinking and may actually promote further drinking. As per our third hypothesis, compared with nonpredrinkers, predrinkers consumed a significantly larger number of drinks in total (over the entire night) and, consistent with previous research (Barry et al., 2013; Borsari et al., 2007; Clapp et al., 2009; Glindemann et al., 2006; Hummer et al., 2013; LaBrie & Pedersen, 2008), had higher intoxication levels, as measured with breathalyzer data rather than estimates of BAC. These effects remained significant controlling for drinking pattern, suggesting that the association of predrinking with increased drinking and higher BrAC are not fully explained by the usual pattern of drinking and that the act of predrinking itself may be associated with heavier consumption. Consistent with the last hypothesis, our results indicate that individuals who predrank were significantly more likely to have higher BrACs at the end of the night but only when the majority of their group members also predrank. This finding suggests that
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Table 2 Hierarchical Linear Models Comparing Predrinkers With Nonpredrinkers on Alcohol Use and BrAC, Controlling for Maximum Number of Drinks and Other Potential Confounders No. drinks between entry and exit
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b Step 1 Predrinking vs. not Step 2 Predrinking vs. not Gender of the group (Level 2) Age Hours from entry to exit Saturday vs. other Step 3 Predrinking vs. not Gender of the group (Level 2) Age Minutes from entry to exit Saturday vs. other Max no. of drinksa Step 4 Predrinking vs. not
3.790ⴱⴱⴱ 1.526ⴱⴱ ⫺0.835 0.060 0.005 0.971 1.210ⴱ 0.110 0.038 0.004 0.605 0.178ⴱⴱⴱ
Total no. of drinks
SE
b
SE
0.318
7.321ⴱⴱⴱ
0.461
0.487 0.563 0.108 0.004 0.717
3.144ⴱⴱⴱ ⫺1.147 0.010 0.005 1.540†
0.701 0.855 0.132 0.004 0.856
0.601 0.498 0.089 0.003 0.601 0.044
2.684ⴱⴱⴱ 0.486 0.045 0.003 1.215† 0.309ⴱⴱⴱ
0.709 0.606 0.111 0.003 0.685 0.054
No significant interactions
No significant interactions
Gender of the group (Level 2) Age Minutes from entry to exit Saturday vs. other Max no. of drinksa Group predrinking (Level 2) Individual predrinking (Level 1) by group predrinking (Level 2)b
Exit BrAC b 0.061ⴱⴱⴱ 0.026ⴱⴱ ⫺0.003 0.001 0.000 0.000
SE 0.005 0.007 0.009 0.001 0.000 0.008
0.027ⴱⴱⴱ 0.004 0.000 0.000 0.001 0.001
0.008 0.009 0.001 0.000 0.009 0.001
0.010
0.009
0.007 0.000 0.000 ⫺0.002 0.001 0.029ⴱ 0.059ⴱⴱ
0.008 0.001 0.000 0.009 0.001 0.012 0.019
Note. BrAC ⫽ breath alcohol concentration. a Models are presented controlling for maximum number of drinks, because it was most strongly related to predrinking. Models were also computed controlling for heavy episodic drinking, and similar results were obtained. b Interaction effects for gender of the group by individual predrinking were also tested but were nonsignificant. † p ⬍ .10. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
group members become more intoxicated when all or most members of a social group engage in predrinking. Thus, as suggested in previous research, what happens at the group level has an important impact on behavior (Miller, Byrnes, Branner, Johnson, & Voas, 2013). Further research is needed to assess how the group influences individual-level drinking over the course of the night, such as through contagion of group norms, effects of group leaders (Dumas, Wells, Flynn, Lange, & Graham, 2014), round buying, or possibly drinking games that occur while predrinking (Hummer et al., 2013). A limitation of the present study is that findings may not be generalizable to mixed-gender groups and larger groups (i.e., greater than five). Thus, effects of gender composition and size of the drinking group as they relate to predrinking should be examined in future research. Also, gender-specific analyses were not possible due to small sample sizes and thus should be conducted in future studies with larger samples. A further limitation is loss to follow-up, with exit survey participants more likely to have been recruited on Thursday evenings and to have lower alcohol use and intoxication levels at entry compared to those who did not return at exit. However, given that participation at exit was not associated with predrinking status, it is unlikely that the association between predrinking and BrAC is confounded by loss to follow-up.
Conclusion The present study advances the field by demonstrating that predrinking remains significantly associated with greater consumption and intoxication, even after adjusting for drinking pattern. An implication of this study is that programs and policies are needed to reduce predrinking, such as addressing large discrepancies between on- and off-premise alcohol pricing. Such price discrepancies likely motivate predrinking (Wells, Mihic, Tremblay, Graham, & Demers, 2008), even if predrinking does not have the intended effect of consuming less at the bar. Bar staff training and enhanced enforcement are needed to ensure that staff recognize and deter intoxicated patrons when they arrive at the bar and better monitor how much they are drinking while at the bar (see Graham et al., 2014). Initiatives may be needed that address group dynamics, such as social modeling, peer influence, and conformity to dominant group norms. Policy and programming aimed at changing drinking norms and practices, such as rapid consumption, should be considered as well as programs promoting safer choices (e.g., having a sober friend present) when engaging in predrinking. Finally, counseling programs, especially for heavy-drinking young adults, may need to consider predrinking and its role in heavy alcohol use.
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Received October 7, 2014 Revision received January 19, 2015 Accepted January 21, 2015 䡲
