Identifying Factors That Increase the Likelihood for Alcohol-Induced Blackouts in the Prepartying Context

Heads Up! Psychological Science

2011

Identifying Factors That Increase the Likelihood for Alcohol-Identifying Factors That Increase the Likelihood for Alcohol-

Induced Blackouts in the Prepartying Context Induced Blackouts in the Prepartying Context

Joseph W. LaBrie

Loyola Marymount University

, [email protected]

Justin F. Hummer

Loyola Marymount University

, [email protected]

Shannon Kenney

Loyola Marymount University

Andrew Lac

Loyola Marymount University

, andrew[email protected]

Eric Pedersen

University of Washington

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Factors That Increase the Likelihood for Alcohol-Induced Blackouts in the Prepartying Context" (2011).

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Identifying Factors That Increase the Likelihood for Alcohol-

Induced Blackouts in the Prepartying Context

Joseph W. LaBrie

, Justin Hummer

, Shannon Kenney

, Andrew Lac

, and Eric Pedersen

Department of Psychology, Loyola Marymount University, Los Angeles, USA

Department of Psychology, University of Washington, Seattle, USA

Abstract

The present study examined risk factors related to “blacking out” (e.g., temporary periods of

memory loss during drinking) during preparty drinking events (i.e., pregaming, predrinking).

Participants were students from two universities on the West Coast who reported past month

prepartying (N = 2,546) in online surveys administered in the fall of 2008. Among these students,

25% (n = 636) reported blacking out during at least one occasion in which they prepartied in the

past month. A logistic regression model underscored that Greek student affiliation, family history

of alcohol abuse, frequency of prepartying, and both playing drinking games and consuming shots

of liquor while prepartying increased the likelihood of blacking out. Limitations and implications

for future research and collegiate prevention strategies are discussed.

Keywords

alcohol; prepartying; pregaming; alcohol-induced; blackout; college students

INTRODUCTION

College students remain an at-risk population for heavy alcohol use and resulting

consequences including emotional, academic, physical, sexual, and legal problems

(Hingson, Zha, & Weitzman, 2009; Muraven, Collins, Morsheimer, Shiffman, & Paty, 2005;

Wechsler & Nelson, 2006). “Blackout” or “blacking out” refers to a period of time during a

drinking event in which an individual cannot recall all or parts of the event. These alcohol-

induced memory blackouts, also known as anterograde amnesia or acute alcohol-induced

memory dysfunction, may be particularly hazardous. During alcohol-induced blackouts, the

hippocampus, a region of the brain fundamental to memory function, is impaired,

subsequently causing cognitive deficiencies in transferring information from short-term to

long-term memory (Goodwin, 1995; White, 2003). In a blackout situation, individuals suffer

Address correspondence to Dr. Joseph W. LaBriem, Department of Psychology, Loyola Marymount University, 1 LMU Drive, Los

Angeles, 90045; [email protected].

Declaration of Interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.

NIH Public Access

Author Manuscript

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Published in final edited form as:

Subst Use Misuse. 2011 ; 46(8): 992–1002. doi:10.3109/10826084.2010.542229.

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partial (i.e., fragmentary blackout) or complete (i.e., en bloc blackout) memory loss for

drinking events for which they were conscious and active. In addition to potential

neurocognitive impairment, which is especially problematic in younger populations still in

the midst of progressive neurodevelopment (Acheson, Stein, & Swartzwelder, 1998;

DeBellis et al., 2002; Zeigler et al., 2005), alcohol-induced blackouts also amplify proximal

risk (e.g., unsafe sexual behavior, driving while intoxicated, and violence).

Alcohol-Induced Blackouts

In college-based studies, students experiencing alcohol-induced blackouts have been found

to exhibit peak blood alcohol concentrations (BACs) of 0.21 to 0.35 and consume between

8.2 and 11.5 drinks for males and 3.7 and 5.0 drinks for females (Buelow & Koeppel, 2001;

Hartzler & Fromme, 2003; Hunt, 1993). In a study of more than 14,000 students from 119

colleges, 10% of nonbinge drinkers (the authors used the term “binge” to refer to heavy

episodic drinking events—5 or more drinks in a row for men or 4 or more drinks in a row

for women), 27% of occasional binge drinkers (1–2 times in past 2 weeks), and 54% of

frequent binge drinkers (3 or more times in past 2 weeks) reporting having blacked out

during the current school year (Wechsler, Lee, Kuo, & Lee, 2000). Although the link

between “heavy drinking” and blacking out is well known, the direct causes of blacking out

are fast-paced alcohol consumption and rapid elevation of BACs, which when combined are

speculated to overwhelm sensorimotor processes (Goodwin, Othmer, & Halikas, 1970;

Ryback, 1970; White, Jamieson-Drake, & Swartzwelder, 2002; White, Signer, Kraus, &

Swartzwelder, 2004). Whether due to alcohol naivety, underage drinking, the desire to

obtain a “buzz” before going out, or other factors such as playing consumption-focused

games with others, alcohol use in college often takes place away from authority figures

and/or legal drinking environments, which may lend itself to quick-paced drinking practices.

Therefore, it is not entirely surprising that blackouts are prevalent in college populations.

Other studies report that half of college student drinkers have experienced at least one

alcohol blackout in their lifetimes, 40% have blacked out in the past year, and 9.4% of those

who drank in the past 2 weeks have reported blacking out during the same period (Buelow,

1990; Hartzler & Fromme, 2003; White et al., 2002). Because individuals suffering

blackouts most often rely on others to cue or recount such events, assessing blackout-

associated risk is challenging. Nevertheless, adverse behavioral consequences include

vandalism, unsafe sex, drug use, driving under the influence, and fighting, as well as

stressful psychological consequences such as intrusive thoughts or sleep difficulties (Buelow

& Koeppel, 2001; White et al., 2002, 2004). In a sample of 50 undergraduate students who

reported a blackout and only later became aware of consequences, 50% of males and 38% of

females realized they had engaged in sexual activity with individuals they did not know,

38% of males and females had an argument or fight, 25% of males had vandalized property,

and 12.5% of males had driven a motor vehicle (White et al., 2004).

Prepartying Behavior in the College Context

Because blackouts most often result from quickly rising blood alcohol levels resulting from

fast-paced drinking, it is important to examine the type of drinking behaviors that can lead to

these dangerous states. Prepartying is a high-risk drinking behavior common among college

students that is receiving growing attention in the research literature. Also referred to as

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“pregaming,” “preloading,” “front-loading,” “predrinking,” or “prefunking” (drinking before

a function), depending on the region or local group vernacular, prepartying involves “the

consumption of alcohol prior to attending an event or activity (e.g., party, bar, concert) at

which more alcohol may or may not be consumed” (Pedersen & LaBrie, 2007, p. 238).

Prepartying typically involves fast-paced drinking within brief periods of time, as an

inherent purpose is to create a “buzz” or level of inebriation that will heighten enjoyment of

the event and possibly endure through the event or until more alcohol can be obtained. This

style of drinking makes self-regulation appreciably more difficult and negative

consequences more likely. Prepartying has been found to predict numerous consequences

among college students such as academic neglect, hangovers, passing out, and fighting

(Pedersen & LaBrie, 2007; Pedersen, LaBrie, & Kilmer, 2009).

In three separate studies, researchers estimated that participants reached blood alcohol levels

near or above the legal intoxication limit (0.08) during actual prepartying drinking events

(LaBrie & Pedersen, 2008; Pedersen & LaBrie, 2007; Pedersen et al., 2009). For the

majority of participants, this blood alcohol level was achieved prior to going out and

consuming even more alcohol. In event-level studies, 80% of preparty drinking events

involved further drinking (Pedersen & LaBrie, 2007), and when including drinks consumed

during and after prepartying, students achieved mean blood alcohol levels of 0.15 on

prepartying days (LaBrie & Pedersen, 2008). This elevated level of intoxication is

immensely risk enhancing, significantly impairing motor control, vision, and decision-

making. Thus, prepartying may be especially linked to blackouts. Understanding the link

between prepartying and blacking out among college students will prove helpful both to

researchers who seek to understand college student drinking and practitioners seeking to

design and implement interventions that reduce the risk associated with both of these events.

Study Aims and Hypotheses

The present study examined a large representative sample of students reporting prepartying

behavior to determine how common blacking out was during prepartying events and

whether differences emerged between those who experienced preparty-related blackouts and

those who did not. For this purpose, the primary analysis entailed a binary logistic

regression model of demographic characteristics (age, gender, race, Greek status, family

history of alcohol abuse), prepartying frequency, method of prepartying (alone, with friends/

roommates, while playing drinking games), and type of alcoholic beverage consumed during

prepartying (shots, wine, and mixed drinks) as potential predictors that increased the

likelihood of a blackout. Specifically, it was anticipated that blacking out would be fairly

common among prepartying college students and that risk factors such as prepartying

frequency, playing drinking games while prepartying, and drinking shots of liquor would

greatly contribute to blacking out.

METHOD

Participants

Recruitment and data collection occurred at two West Coast campuses, one a large public

university and the other a private mid-sized university, in 2008. The study was approved by

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the Human Subjects Review Boards at both participating universities. Data were collected as

part of a larger longitudinal intervention study, and all data used in analyses were derived

from the screening survey that was completed before administration of any intervention. Of

the 11,069 students invited to participate in the study, 4,984 (45.0%) completed the initial

survey. Only those 2,546 (51.1%) participants who answered with a value of at least 1 to the

open-ended question, “In the last 30 days, how many days did you engage in prepartying?”

received further preparty questions and were therefore included in the final analyses.

Demographic characteristics of this prepartying sample revealed that they were primarily

female (58.6%) and Caucasian (57.1%). Other ethnic and racial representations were as

follows: 20.2% Asian American, 11.0% Hispanic, 2.1% African American, and 9.6% other/

multiracial. Review of demographic information from the registrar’s office at both

universities revealed that the percentages of women and Caucasians represented in the

sample were comparable with the overall compositions of the general student populations.

Minor discrepancies in the representativeness of ethnic minorities were present for each

institution.

Design and Procedure

At the end of the first month of the fall term, students were randomly selected from registrar

rosters for recruitment. Students received both an email and a postal delivered invitation to

participate in a study regarding alcohol use. If the student chose to participate, he/she

clicked on a link to the online survey, entered a unique Personal Identification Number

(PIN) and was prompted to electronically consent to the study before being directed to the

20-minute screening survey itself. Each student received a nominal stipend of $15 to

complete the survey. The survey assessed demographic variables, as well as several

variables related to alcohol use. Prior to questions assessing drinking behavior, one standard

drink was defined for students as one-half ounce (oz) of ethyl alcohol, one 12 oz beer, one 4

oz glass of wine, or one 1.25 oz. shot. Pictures of standard drinks accompanied these

descriptions.

Measures

Demographics—Background characteristics measured included age, gender, and race.

Also assessed were Greek status (“Are you a member of a fraternity or sorority?”) and

family history of alcohol abuse

(“To your knowledge, do you have any biological relatives

that have a significant drinking problem—one that should or did lead to treatment?”).

Prepartying Behavior—Prior to questions assessing prepartying, the behavior was

defined as “the consumption of alcohol prior to attending an event or activity [e.g., party,

bar, concert] at which more alcohol may or may not be consumed” (Pedersen & LaBrie,

2007, p. 238). Participants first responded to the following open-ended question: “In the last

30 days, how many days did you engage in prepartying?” When participants indicated at

least one prepartying day, they were then asked, “On average, how many drinks did you

consume while prepartying (not including drinks consumed after arriving to your planned

The journal’s style utilizes the category substance abuse as a diagnostic category. Substances are used or misused; living organisms

are and can be abused. Editor’s note.

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destination)?” This was followed by the question, “How did you typically preparty?”

Respondents were asked to check all that apply: (1) “Alone, while getting ready to go out”

(prepartying alone); (2) “With friends/roommates, while getting ready to go out”

(prepartying with friends/roommates); and (3) “Playing drinking games” (prepartying while

playing drinking games). The next question assessed type of alcoholic beverage consumed

while prepartying: “What did you typically drink while prepartying?” Again, respondents

were asked to check all that apply: (1) “beer”; (2) “shots”; (3) “wine”; and (4) “mixed

drinks. ” Finally, participants reported on the following question representing the dependent

variable of interest: “How many times in the past month (30 days) did you blackout on a

night when you prepartied? If this never happened to you, please leave the question blank or

type ‘0’.” This item was on an open-ended response scale and indicated the number of times

the participant experienced a blackout during or after a prepartying event.

Typical Alcohol Use Behavior—Quantity of alcohol consumption was assessed using

the Daily Drinking Questionnaire (DDQ; Collins, Parks, & Marlatt, 1985). Participants were

asked, “Consider a typical week in the last month. How much alcohol, on average (measured

in number of drinks), did you drink on each day of a typical week?” Participants responded

by reporting the typical number of drinks consumed on each day of the week. Weekly

drinking was calculated by summing participants’ responses for each day of the week. The

DDQ has been used in previous studies of college student drinking and has demonstrated

good validity (

Larimer et al., 2001; Marlatt et al., 1998).

RESULTS

Data Analysis

The dependent variable assessed the number of times in the past 30 days participants

blacked out on a night when they engaged in prepartying. Owing to some respondents

reporting extremely high values, this open-ended response variable displayed highly non-

normal distributional properties (skewness = 8.00, p < .001; kurtosis = 137.80, p < .001).

Thus, it was necessary to binary code the outcome into whether a respondent experienced a

blacked out at least once (1) or never (0). For the purpose of interpretation in a logistic

regression model, the predictor variables of respondent age and prepartying days in the past

30 days each were recoded and analyzed as discrete categorical variables (see Table 1 for

categories), enabling the comparison levels of a variable to be contrasted to its respective

reference level (Norusis, 2003).

Initial data analyses examined information with regard to number of prepartying days,

prepartying drinks, typical alcohol use behavior, whether participants blacked out, and

gender differences. Next, chi-square tests determined significant bivariate relationships

between each of the 13 categorical variables (see Table 1 for variables) and whether

respondents had experienced a blackout on a prepartying night in the past 30 days. Finally, a

more comprehensive analysis collectively incorporated all variables into a binary logistic

regression model predicting the experience of having a blackout on a prepartying night.

Results from this analysis would yield valuable insight into the most important risk factors

contributing to whether respondents experienced a black out, after statistically controlling

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for, and therefore ruling out, all other covariates in the model. The binary logistic regression

model was specified and estimated according to established procedures (Tabachnick &

Fidell, 2007). The parameter of interest assessing the contribution of each predictor in this

statistical technique is the odds ratio (OR). A null hypothesis OR of 1.0 represents no

difference in ratio of proportion of blacking out (vs. not blacking out) between a specific

comparison level (e.g., Asian, Hispanic, African American, and other/multiracial) and its

corresponding reference level (e.g., Caucasian). The OR also serves as an indicator of effect

size (Lipsey & Wilson, 2001).

Initial Analyses

Participants reported the following number of days they prepartied in the past 30 days: 1

(19.2%), 2–5 (52.1%), 6–9 (17.9%), and 10+(10.8%). Among male participants, the number

of prepartying days reported were 1 (16.4%), 2–5 (50.0%), 6–9 (20.2%), and 10+ (13.4%).

Among female participants, the number of prepartying days reported were 1 (21.1%), 2–5

(53.6%), 6–9 (16.2%), and 10+ (9.0%). A 2 (gender) × 4 (prepartying days categories)

analysis of variance (ANOVA) was performed on the dependent variable of average number

of drinks consumed during a typical preparty occasion. Results revealed a main effect for

both gender, F (1, 2,538) = 186.74, p < .001, and prepartying days categories, F (3, 2,538) =

136.45, p < .001, in addition to their interaction effect, F (3, 2,538) = 8.39, p < .001.

Representation of the interaction effect in Figure 1 shows that males averaged more

beverages during a typical prepartying occasion than females, and that this gender

discrepancy became especially pronounced as the number of prepartying days increased.

Descriptive data also indicated that 25.0% (n = 636) of this prepartying sample of

respondents experienced a blackout in the past 30 days on a night when they prepartied, with

14.2% (n = 361) blacking out once, 5.7% (n = 145) blacking out twice, and 5.1% (n = 130)

blacking out three or more times. In terms of total drinks per week from the DDQ, males

who experienced a blackout consumed 23.14 (standard deviation [SD] = 13.03) drinks per

week compared with 11.85 (SD = .95) drinks per week among males not reporting a

blackout, t (1,052) = 15.41, p < .001. Females reporting a blackout consumed an average of

12.77 (SD = 7.76) total drinks per week in contrast to 6.91 (SD = 5.88) drinks among

females not reporting a blackout, t (1,492) = 14.99, p < .001.

Furthermore, we examined the average number of prepartying drinks consumed during a

typical prepartying event (not including drinks consumed after prepartying). Among the

overall sample, 34.9% of males and 29.4% of females reported engaging in heavy episodic

drinking during a typical prepartying event (consuming 4+ drinks for women and 5+ drinks

for men in a row; O’Malley & Johnston, 2002; Wechsler & Nelson, 2008). Specifically,

among those who reported blacking out, 56.0% of males and 49.7% of females engaged in

heavy episodic drinking during a typical prepartying event. However, among those not

reporting a blackout, only 26.6% of males and 23.2% of females engaged in heavy episodic

drinking during a typical prepartying event. In addition, males who reported blacking out

consumed an average of 4.96 (SD = 2.02) drinks during a typical prepartying event,

compared with 3.67 (SD = 2.02) drinks for males who did not report blacking out, t (1,056)

= 9.29, p < .001. Females who experienced a blackout averaged 3.66 (SD = 1.42) drinks

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during a typical prepartying event, in comparison with 2.70 (SD=1.48) drinks for females

not experiencing a blackout, t (1,493) = 10.76, p < .001.

Variables Bivariately Associated With Blacking Out

Results of the chi-square tests of independence between each variable and blacking out are

displayed in Table 1. Ten of the 13 variables were evidenced to be bivariately associated

with blacking out. Respondents who blacked out, in comparison to those who did not,

tended to be male, Caucasian, Greek-affiliated, and possessed a family history of alcohol

misuse. In addition to these demographic factors, the cohort experiencing the blackout

tended to engage in more days of prepartying, preparty while playing drinking games, as

well as be more likely to consume beer, shots, wine, or mixed drinks during prepartying

events. Age, prepartying alone, and prepartying with friends/roommates did not emerge as

factors associated with blacking out.

Predictive Model

Results from the binary logistic regression model predicting blacking out are presented in

Table 2 and interpreted after statistically controlling for the variance explicated by all other

predictors entered into the model. The overall logistic regression model, with all predictors

entered, emerged as highly significant, Nagelkerke R

= 23.7%, χ

(18) = 442.83, p < .001.

Specifically, Asian (OR = 0.73, p < .05) and African American (OR = 0.43, p < .05) students

tended to be less likely to blackout than their Caucasian peers. Greek status (OR = 1.37, p

< .01) and family history of alcohol misuse (1.24, p < .05) also served as significant

predictors of blacking out. In contrast to respondents engaging in only 1 day of prepartying

in the past 30 days, respondents prepartying 2–5 days (OR = 6.36, p < .001), 6–9 days (OR

= 14.73, p < .001), and 10 or more days (OR = 27.01, p < .001) experienced elevated, and

extremely high, rates of suffering a blackout. Increased risk of experiencing a blackout was

also predicted by prepartying while playing drinking games (OR = 1.26, p < .05) and

prepartying while consuming shots (OR = 1.60, p < .001).

DISCUSSION

The current study assessed the prevalence of past month prepartying behavior and

particularly the concomitant risk of blacking out during a prepartying event in a large

sample of college students. The study further evaluated potential characteristics associated

with those who did or did not experience a blackout on a prepartying night in the past month

and the factors that contributed to the likelihood of a prepartying event resulting in a

blackout. Findings indicated that both prepartying and blacking out when prepartying were

common, with over half of the participants reporting prepartying during the past month and,

among these, one fourth reporting blacking out during a prepartying event. Those who

blacked out drank at higher levels during prepartying than those who did not blackout.

Although typical hours spent consuming beverages was not assessed, previous research

looking at multiple prepartying events revealed that approximately 50% of students’

prepartying events lasted less than 1 hour, with approximately 90% lasting less than 2 hours

(

Pedersen & LaBrie, 2007). This is consistent with research documenting the relationship

between blackouts and a rapid rate of alcohol consumption (White et al., 2002). Descriptive

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data on the current sample revealed that compared with prepartiers who did not report

blacking out during the past month, male and female students who did report a blackout

drank approximately twice as much during a typical week and consumed more drinks during

a typical prepartying occasion. Further, approximately 56% of males and 50% of females

who had experienced a blackout while prepartying engaged in heavy episodic drinking

during a typical prepartying event compared with only 27% of males and 23% of females

who did not experience a blackout. Although the actual duration of drinking events and

subsequent timing of the ensuing blackout was not directly assessed in this study, fast-paced

drinking during prepartying (Pedersen&LaBrie, 2007) is likely associated with reductions in

judgment and minimization of potential consequences (Fromme, Katz, & D’Amico, 1997),

whereby leading to heavier drinking following the prepartying event later in the night.

Indeed, the amount of alcohol consumed during prepartying directly predicts the amount

consumed afterwards (Pedersen & LaBrie, 2007). These links further categorize prepartying

as a risky behavior with the potential for quickly elevated BACs leading to blacking out and

potentially dangerous negative consequences associated with blacking out.

Chi-square tests revealed bivariate relationships between blacking out and the following

factors: being male, being Caucasian, Greek status, family history of alcohol abuse,

prepartying more frequently, prepartying while playing drinking games, and, not

surprisingly, consuming larger amounts of alcohol during prepartying, whether it be beer,

wine, shots, or mixed drinks. Of notable interest is that age did not play a role in

discriminating among students who reported blacking out while prepartying. Although the

genesis of prepartying is not known, one possible speculation is that it emerged from

underage drinkers (those under the legal drinking age of 21 in the United States) not having

access to alcohol once they go out for the evening. For example, underage students may

consume alcohol prior to attending a club that requires students be 18 years of age to enter

but 21 or older to consume alcohol. In addition, concert venues, sporting arenas and

stadiums, or school-sponsored events often are either alcohol free or require that students be

of legal drinking age in order to consume alcoholic beverages. This may be why in one

study that specifically focused on reasons for prepartying among a young college-aged

population, males and females reported arriving to a social event already under the influence

as their most highly endorsed reason for prepartying (Pedersen et al., 2009). Yet while

prepartying is popular among underage drinkers seeking intoxication whether it be before a

school-related function, party, social, or sporting event, it also remains popular among

students of legal drinking age. Previous studies have found no differences between underage

and of-age participants on the number of drinks consumed while prepartying or the

frequency of prepartying in the past month (e.g., Glindemann, Ehrhart, Maynard, & Geller,

2006; Pedersen et al., 2009). Coupled with the current results, it appears that risky drinking

behaviors, such as prepartying, may need to be demythologized as a primarily first-year

student or underage drinking phenomenon.

Previous research has identified factors such as being Caucasian (Office of Applied Studies,

2008; O’Malley & Johnston, 2002), Greek status (Larimer, Anderson, Baer, & Marlatt,

2000; Park, Sher, & Krull, 2008), possessing a family history of alcohol misuse (Warner,

White, & Johnson, 2007), drinking frequently (Borsari, Neal, Collins, & Carey, 2001), and

playing drinking games (Borsari et al., 2007) to be associated with risky or problematic

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drinking. Thus, for a more comprehensive examination, we incorporated all potential factors

into a logistic regression model to determine which factors uniquely accounted for blacking

out while prepartying when controlling for the other factors. Similar to previous findings,

the likelihood of having had a blackout was uniquely predicted by being in a fraternity or

sorority, possessing a family history of alcohol abuse, engaging in prepartying more

frequently, playing drinking games while prepartying, and consuming shots of liquor while

prepartying.

Identifying prepartying factors that provide unique risk for preparty-related blackouts

provides information that can be incorporated into targeted prevention efforts. Prevention

and intervention messaging could discuss the dangers of combining drinking games with

prepartying, as well as the heightened risk associated with drinking shots of liquor in the

context of prepartying. White et al. (2004) also found that students were more likely to

blackout on nights in which they were drinking liquor. This is likely due to the quickened

drinking and absorption factors typically associated with liquor as opposed to other types of

alcoholic beverages such as beer or wine. Furthermore, drinking games have been linked to

numerous consequences in college students (e.g., hangovers, campus violations, reliance on

alcohol, risky sexual behaviors, and car accidents; Borsari et al., 2007; Pedersen & LaBrie,

2006). Problems may be especially compounded in the context of prepartying, however,

given the short duration and the possibility that some students may be unfamiliar with the

acute effects of alcohol. Thus, when consuming several shots or engaging in drinking games

within the short period of the “preparty,” students may not realize the intoxication levels that

will be reached following time-delayed absorption, which may account for the dangerously

high prevalence of blacking out.

Further, previous research has found that female students are more likely to consume shots

of liquor when prepartying than male students, who typically drink beer when prepartying

(Pedersen & LaBrie, 2007). Also, women experienced more alcohol-related consequences

on a prepartying day than on a non-prepartying day (LaBrie & Pedersen, 2008). Thus, the

current findings showing that drinking shots of liquor when prepartying increases the

likelihood of blacking out hold particular relevance for women’s health and well-being.

Women absorb alcohol more quickly than men, reaching higher BACs more rapidly and,

when blacked out or at risky BACs, are at risk for serious consequences, particularly

sexually-related negative consequences. Focusing on prepartying behaviors among women,

while providing information on the physiological differences between men and women in

processing alcohol, may be particularly effective at reducing risk among female students.

Finally, blacking out has traditionally been linked to dosages commonly referred to as

“acute excessive alcohol consumption,” “fast-paced drinking,” “high blood alcohol levels,”

or “heavy episodic drinking.” Such descriptions may not resonate with students when

promoting prevention or intervention messages. Prepartying (and its regional variations),

however, is identifiable as a behavior well established in collegiate nomenclature and that

can be quantifiably researched. As a result, prepartying may hold more potential as a target

for efficacious experimental manipulation than other, more abstract, concepts of “heavy

drinking.”

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Study Limitations and Future Directions

The current study has several limitations. First, this study did not specify or define the type

of blackout that was experienced. It is possible that referring to a generic term of “blacking

out” may have resulted in students thinking about times they woke up with no memories,

also known as en bloc. However, research suggests that fragmentary blackouts are most

common among college students (White et al., 2004), and thus participants may actually

have underreported the frequency of blackout occurrence while prepartying. Similarly, the

wording of the question may have led students to answer as if the blackout referred to the

prepartying event itself; however, this is unlikely given that the text read as “… did you

blackout on a night when you prepartied.” Anecdotal experiences during our work with

students suggested that our phrasing of the question was understood to indicate that the

blackout could have occurred at any point during the night (i.e., during the prepartying event

or after). Second, while the generalizability of the participants within each site was indicated

by the representative percentage of female and Caucasian participants, the slightly

discrepant percentages of African American, Asian American, and Hispanic American

participants may have led to inconclusive findings when comparing Caucasians with these

groups. Studies with ample number of minority participants specifically targeting

differences in ethnicity-specific prepartying behavior are needed. Third, all measures were

self-report and therefore subject to errors in recall. However, this limitation is attenuated by

the fact that participants were repeatedly assured of confidentiality and that blacking out is a

salient event for most students, meaning that they may be more apt to accurately recall

specific characteristics surrounding prepartying events. As length of time typically spent

prepartying was not assessed, we were unable to determine if participants generally reached

blackout BACs (Buelow & Koeppel, 2001; Hartzler & Fromme, 2003; Hunt, 1993) during

prepartying or if prepartying associated with increased risk for further drinking that led to a

blackout.

While this study focused on the blackout as the measure of consequence, it would also be

interesting to garner a sense of the potential consequences that blacking out may have

caused. Future research could include a wider assessment of whether students were able to

find out what transpired while they were blacked out and if any physical, psychological, or

psychosocial consequence occurred as a result. Circulating such data to other students could

aid in creating awareness of psychological stressors that could potentially occur in the

aftermath of a blackout, prompting reconsideration of engaging in future “heavy drinking”

episodes. Finally, recent research has documented a high (45%) prevalence rate of

prepartying during the final months of high school, which was subsequently found to

prospectively increase alcohol-related risk upon the transition into college (Kenney,

Hummer, & LaBrie, 2010). In light of the current findings, research should continue to focus

on high school and noncollege samples to determine whether memory blackouts or other

serious consequences are associated with prepartying in drinking environments other than

college. Novel and tailored intervention approaches for this risky drinking context are

clearly needed and such calls are being increasingly echoed in recent research (e.g., Read,

Merrill, & Bytschkow, 2010).

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Summary

Prepartying is a high-risk drinking context that is common in college students and which

often leads to blacking out. By examining factors that predispose students to hazardous

scenarios, practitioners can potentially make a stronger impact in reducing some of these

risks via intervention and prevention efforts. The present study began to address some

specific indicators involved in the likelihood of blacking out while prepartying, including

drinking shots of liquor, playing drinking games, prepartying frequently, and racial/ethnic

identity. Thus, college student affairs personnel are encouraged to remain cognizant of these

markers and create novel messaging and programming targeting these risk-inducing factors.

Acknowledgments

This research was supported by grant R01 AA 012547–06A2 from the National Institute of Alcohol Abuse and

Alcoholism and grant Q184H070017 from the US Department of Education.

Biographies

Joseph W. LaBrie obtained a Ph.D. in clinical psychology in 2002 from the University of

Southern California, in addition to holding a M.Div. in theology and a M.S. in mathematics.

He is currently the Special Assistant to the President, Associate Professor of psychology,

and Director of the Heads Up research lab at the Loyola Marymount University. His

research interests are focused on prevention and intervention efforts for risky behaviors

among young adults and adolescents. Dr. LaBrie has published over 70 research articles in

this area as well and been the recipient of numerous private and federal grants to study

young adult health behaviors and approaches to prevention and intervention.

Justin F. Hummer is the Assistant Director of the Heads Up research lab at the Loyola

Marymount University. His primary research interests consider how social and motivational

factors relate to the etiology, prevention, and treatment of health-risk behaviors among

college students.

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Shannon R. Kenney graduated from the Brown University in 2006 with a Ph.D. in

sociology. She is currently a postdoctoral fellow in the Heads Up research lab and Visiting

Assistant Research Professor at the Loyola Marymount University. Her research has focused

on youth and adolescent health, including the treatment and prevention of substance misuse

and poorer mental health.

Andrew Lac is earning his Ph.D. in psychology at the Claremont Graduate University, and

serves as a Statistical Consultant at the Loyola Marymount University and the University of

Southern California. With interests encompassing social, developmental, and health

psychology, his published research applies multivariate methods to examine adolescent

delinquency and family dynamics.

Eric R. Pedersen is a doctoral candidate in the clinical psychology program at the

University of Washington. His interests are in young adult substance use. In particular, he is

interested in exploring the contextual factors related to alcohol and marijuana use among

college students.

GLOSSARY

Alcohol-Induced

Blackout

Period of time in which memory is impaired by alcohol consumption

such that an individual is unable to recall all or parts of a past

drinking event (also known as anterograde amnesia or acute alcohol-

induced memory dysfunction).

En Bloc

Blackout

A blackout in which an individual suffers complete memory loss

related to a drinking event, even when provided details.

Fragmentary

Blackout

A blackout associated with partial memory loss in which an

individual is able to recall some but not all aspects of a drinking

event, and is often able to remember details when prompted.

Prepartying

Also referred to as pregaming, preloading, front-loading, predrinking,

or prefunking, prepartying involves the consumption of alcohol prior

to attending an event or activity (e.g., party, bar, concert) at which

more alcohol may or may not be consumed.

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FIGURE 1.

Gender × prepartying days on average drinks during a typical preparty occasion.

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TABLE 1

Chi-square tests between each variable and blacking out on a prepartying night

Blacked out

No Yes

Predictor Level %

Pearson χ

Age

Under 21 years 62.8 1,200 63.8 406 0.21

21+ 37.2 710 36.2 230

Gender

6.63

Male 39.9 763 45.8 291

Female 60.1 1,147 54.2 345

Race

Caucasian 54.6 1,042 64.6 411

31.65

***

Asian 22.4 427 13.8 88

Hispanic 10.6 203 11.9 76

African American 2.5 47 1.1 7

Other/multiracial 10.0 191 8.5 54

Greek status

82.96

***

No 72.3 1,379 52.8 335

Yes 27.7 528 47.2 300

Family history of alcohol abuse

10.46

***

No 64.4 1,230 57.2 364

Yes 35.6 680 42.8 272

Prepartying days (past 30 days)

364.21

***

1 24.7 472 2.5 16

2–5 55.3 1,056 42.6 271

6–9 13.9 266 29.7 189

10+ 6.1 116 25.2 160

Prepartying alone 1.08

No 95.1 1,816 94.0 598

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Blacked out

No Yes

Predictor Level %

Pearson χ

Yes 4.9 94 6.0 38

Prepartying with friends/roommates 0.91

No 4.7 90 5.7 36

Yes 95.3 1,820 94.3 600

Prepartying while playing drinking games

89.02

***

No 61.7 1,178 40.3 256

Yes 38.3 732 59.7 380

Prepartying with beer

26.64

***

No 42.8 818 31.9 203

Yes 57.2 1,092 68.1 433

Preparty with shots

43.24

***

No 33.1 632 19.3 123

Yes 66.9 1,278 80.7 513

Prepartying with wine

8.96

No 85.1 1,625 80.0 509

Yes 14.9 285 20.0 127

Prepartying with mixed drinks

8.36

No 44.8 855 38.2 243

Yes 55.2 1,055 61.8 393

p < .05,

p < .01,

***

p < .001.

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TABLE 2

Binary logistic regression model predicting blacking out on a prepartying night (1 = yes, 0 = no)

Predictor Level

B SE

Wald

Age

Under 21 years 1.00

21+ 0.06 0.11 0.30 1.06

Gender

Male 1.00

Female −0.07 0.11 0.41 0.93

Race

Caucasian 1.00

Asian −0.32 0.15 4.83

0.73

Hispanic −0.05 0.16 0.10 0.95

African American −0.85 0.44 3.84

0.43

Other/multiracial −0.21 0.18 1.27 0.81

Greek status

No 1.00

Yes 0.32 0.11 8.71

1.37

Family history of alcohol abuse

No 1.00

Yes 0.21 0.10 4.19

1.24

Prepartying days (past 30 days)

1 1.00

2–5 1.85 0.27 48.48

6.36

***

6–9 2.69 0.28 93.26

14.73

***

10+ 3.30 0.29 128.01

27.01

***

Prepartying alone

No 1.00

Yes −0.01 0.22 0.00 0.99

Prepartying with friends/roommates

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Predictor Level

B SE

Wald

No 1.00

Yes −0.24 0.24 1.06 0.79

Prepartying while playing drinking games

No 1.00

Yes 0.23 0.11 4.11

1.26

Prepartying with beer

No 1.00

Yes 0.08 0.12 0.49 1.09

Prepartying with shots

No 1.00

Yes 0.47 0.12 14.61

1.60

***

Prepartying with wine

No 1.00

Yes 0.14 0.14 1.04 1.15

Prepartying with mixed drinks

No 1.00

Yes −0.03 0.11 0.06 0.97

Note. The first level of each predictor variable represents the reference level; SE, standard error.

Adjusted odds ratio, after controlling for all other predictors in the model.

p < .05,

p < .01,

***

p < .001.

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