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. Author manuscript; available in PMC: 2018 Jun 1.
Published in final edited form as: Addict Behav. 2017 Jan 7;69:42–47. doi: 10.1016/j.addbeh.2017.01.006

Individual, Interpersonal, and Contextual Factors Associated with Discrepancies between Intended and Actual Spring Break Drinking

Christine M Lee 1, Megan E Patrick 2, Irene Markman Geisner 1, Nadine R Mastroleo 3, Angela Mittmann 1, Lindsey Zimmerman 1,4
PMCID: PMC5370076  NIHMSID: NIHMS846536  PMID: 28129612

I. Introduction

Event specific drinking has been the focus of recent research and media attention, illustrating there are known times for increased risk for high levels of alcohol use and alcohol-related consequences (Neighbors et al., 2011; Neighbors et al., 2007). Studies have demonstrated that college Spring Break (SB) is one such occasion associated with high-risk alcohol use (Beets, et al., 2009; Del Boca et al., 2004; Goldman et al., 2011; Greenbaum et al., 2005; Lee et al., 2006, 2009; Patrick et al., 2011; Smeaton et al., 1998; Sonmez et al., 2006). Identifying factors that place individuals at greatest risk for negative consequences during SB is an important issue for designing interventions to promote safety during SB. One potentially important issue is whether college students accurately estimate the amount of alcohol they will consume, or whether they end up drinking more than they intended to drink during SB. Underestimating alcohol use, or intending to consume less than is actually consumed, may be critical for understanding alcohol-related consequences during SB. For example, individuals may plan to engage in particular protective behavioral strategies based on their intended number of drinks, and when estimates are inaccurate, individuals might be unprepared for their greater drinking. The purpose of the present paper is to examine individual, interpersonal, and contextual factors that may be related to underestimation of SB drinking and drinking consequences.

1.1 Drinking Intentions and Discrepancies

Several theories of health-risk behaviors link behavioral intentions and perceptions of behavioral consequences to behavior (e.g., Ajzen, 1988, 1991, Ajzen & Fishbein 1980, Becker et al., 1977). Specifically, the theory of planned behavior (TPB; Ajzen, 1988, 1991) suggests behavioral intentions are influenced by the attitude about the likelihood that the behavior will have a specific and expected outcome, while considering the subjective evaluation of the risks and benefits of the expected outcome. This is based on both motivation (intention) and ability (behavioral control), with the key component being the behavioral intent of the students rationale to drink during SB. Intentions for alcohol use during SB indicate how much a student is planning or hoping to drink. However, drinking intentions may not be very accurate. For example, Brister et al. (2010) examined 21st birthday drinking intentions and found that 87% of students were inaccurate in their predictions for how much they would drink during their celebrations, with 68% drinking more than planned. In particular, nearly 1/3 (30%) consumed 5 or more drinks more than anticipated (Brister et al., 2010). The discrepancy between what an individual intends to drink and what he/she actually consumes is important because students who drink more than they planned to drink may be at risk for increased and unintended consequences. To apply the TPB to SB drinking, underestimation of drinking will be examined as an outcome of individual, interpersonal, and contextual factors. In addition, alcohol-related consequences will be examined as an outcome of drinking underestimation.

1.2 Individual Factors

The formation of drinking intentions, and the extent to which intentions underestimate actual drinking behavior, may be associated with individual factors. Men tend to drink more (O’Malley & Johnston, 2002; White et al., 2006), and have also shown greater inaccuracy between drinking intentions and actual drinking (Brister et al., 2010). Fraternity and sorority members also tend to consume more alcohol in general (Capone et al., 2007; Grekin & Sher, 2006; Turrisi et al., 2006) and are more likely than non-members to have pacts or mutual agreements with friends to get drunk during SB (Patrick et al., 2011). The extent to which gender and fraternity/sorority membership predict a discrepancy between intended and actual SB drinking will be examined.

1.3 Interpersonal Factors

Interpersonal factors impact drinking intentions and, likely, the discrepancy between intentions and actual behavior. The theories of reasoned action and planned behavior posit that behavioral intentions that predict behavior are strongly shaped by social norms (Azjen & Fishbein, 1980; Ajzen, 1988, 1991). For most college students, SB is a very social time, which may amplify the interpersonal influences on alcohol use. Interpersonal factors include pacts with friends about drinking, being with friends that encourage heavy alcohol use, and perceived norms of friends’ drinking. Previous work has shown that having pacts with friends to get drunk was associated with heavier alcohol use and more negative alcohol-related consequences during SB (Patrick et al., 2011), while celebrating with influential peers was associated with drinking more than anticipated during 21st birthdays (Brister et al., 2010). In addition, perceived social norms, or expectations of how much one’s friends will drink (Borsari & Carey, 2003), may be another predictor of both the discrepancy between intentions and actual drinking and the resulting number of negative consequences experienced during SB.

1.4 Contextual Factors

Contextual factors that may impact drinking intentions and behaviors during SB include events, such as going on SB trips with friends, and environmental influences, such as bar specials. Going on SB trips with friends is associated with higher levels of alcohol use and related consequences (Grekin et al., 2007; Lee et al., 2006; Patrick & Lee, 2012). However, less is known about how different characteristics of SB may be associated with alcohol use and alcohol consequences (e.g., whether SB was spent at home, with friends, on leisure trip). Theories of health-risk behaviors describe the importance of intentions as immediate antecedents of behavior, and specify norms as predictors of those intentions, but situational or event-based contexts are not typically incorporated. That said, it is likely that intentions for alcohol use and the discrepancy between intended and actual drinking vary depending on the characteristics of SB. Additional contextual factors include characteristics of the SB environment. Research has consistently shown that environmental factors such as bar specials and drinking games influence alcohol use (Clapp et al., 2007, 2008; Hennessy & Saltz, 1993; Clapp & Shillington, 2001). For example, Trim et al. (2011) examined intentions and actual alcohol consumption over a weekend and found that 23.5% drank more than they intended and 9% drank less than intended. The environmental aspects of the weekend, including being surrounded by a greater number of intoxicated people, more drinking games, and the availability of drugs, mediated the relationship between intentions and heavy episodic drinking. The importance of contextual factors as predictors of SB drinking has not been empirically examined to date. Improved understanding of SB context will provide an important extension of health-risk models to SB drinking risks, as contextual factors may contribute to underestimation of drinking and alcohol-related consequences.

1.5 Present Study

Our overall aims are to: 1) examine the accuracy of SB drinking intentions and potential discrepancies (e.g., underestimation) of actual SB drinking; 2) describe which factors influence underestimating the amount of alcohol consumed on SB, with a focus on individual, interpersonal, and contextual factors; and 3) examine how underestimation of SB drinking is related to SB alcohol-related consequences. We hypothesized that students would greatly underestimate their actual SB drinking when reported prior to SB and that individual, interpersonal and contextual factors would be associated with these underestimations. Finally, we hypothesized that greater underestimations of SB drinking would be associated with greater reports of consequences.

2. Methods

2.1 Participants and Procedures

Participants for the present manuscript included 603 undergraduate college students from a large public university in the Pacific Northwest and were part of a larger study evaluating in-person and web-based SB interventions (for details see Lee et al., 2014). The present sample included 57.2% women with a mean age 20.5 years (SD = 1.33, range 18–25); 68.5% self-reported as White, 18.8% Asian or Pacific Islander, 1.8% Black/African American, .7% Native Hawaiian or Pacific Islander, .5% Native American/American Indian or Alaska Native, 7.4% Multi-ethnic, 2.3% indicating Other.

Across two years (2010 and 2011), approximately 11,462 students were randomly selected from the university registrar list to participate in a brief 15-minute online screening survey about SB activities to determine eligibility for the longitudinal study evaluating brief SB interventions. Students were emailed information about the study which included a link to additional information and to complete the online survey. Recruitment for the initial pre-SB survey was conducted between six and eight weeks prior to SB. From those invited, 36.3% (n=4,164) completed the initial eligibility survey within a two-week open period. While the response rates may appear low, we should note that we had greater than expected number of participants meet eligibility criteria and recruitment closed when 411 (Year 1) and 413 (Year 2) participants were recruited during each of the two years. Eligibility criteria for the longitudinal study were as follows: 1) intentions to go on a vacation or leisure trip with friends on at least one day during Spring Break, 2) intentions to consume 4 (for women) or 5 (for men) or more drinks on at least one day of Spring Break, and 3) listing and providing contact information for at least one friend who would be going on a SB trip with them or with whom they would be visiting. Upon completion of the screening survey, participants who met eligibility criteria were automatically randomized to one of six conditions (five intervention conditions and one control). In brief, the intervention trial was designed to test an in-person and web-based SB-specific intervention adapted from Brief Alcohol Screening and Intervention for College Students (BASICS, Dimeff et al., 1998) compared to general preventative efforts (i.e., those not focused on a specific event, e.g., General BASICS, Dimeff et al., 1998) and to an assessment-only control group in reducing SB drinking and negative consequences. Furthermore, this study examined the impact of incorporating friends in event specific prevention for reducing SB drinking behavior, thus the design included was a 2 (SB BASICS In-person or Web-based) × 2 (Friend [FI] or No Friend) + 1 (General BASICS) + 1 (Control) design. Please see Lee et al., 2014 for detailed information about the intervention content and outcome results.

Students who consented and met eligibility criteria in the initial (screening) survey were then invited to complete a 40-minute pre-SB survey approximately one to two weeks after the screening. Those randomized to receive their respective intervention did so up to two days prior to spring break. Finally, all students completed one 30-minute post-SB survey 1 week after SB.

Of the 4,164 students who completed the screening survey, 19.8% (n=824) met eligibility criteria and were invited for further participation. Of these 824 students, 95% (n=783) completed the 40-minute pre-SB baseline assessment and 93.1% (n=729) completed the post-SB survey. All students were paid a total of $40 for completion of the screening and pre-SB surveys and $30 for the post-SB survey. For the present manuscript, complete data for analyses were available from n=603. There were no drinking differences at baseline between those who did and did not complete the follow up. All procedures were approved by the institutional IRB and a federal certificate of confidentiality was obtained.

2.2 Measures

SB questions spanned the course of ten days, from Friday (the last day of the Winter quarter) to Sunday (the day before the start of Spring quarter). Unless otherwise noted, all questions refer to the ten days of SB.

Demographics

Students reported whether they were 0=male or 1=female. To control for possible intervention effects, intervention condition was coded as 0=control or 1=intervention. Participants randomized to the five interventions were collapsed into one category.

Previous Alcohol-Related Consequences

The Rutgers Alcohol Problem Index (RAPI, White & Labouvie, 1989) was used to assess drinking consequences The RAPI is 23 items reflecting alcohol’s impact on social and health functioning. Sample items include “how many times have you not been able to do your homework or study for a test because of your alcohol use” and “how many times have you had a fight or argument or bad feelings with a friend because of your alcohol use”. Responses range from 1 to 5 (1 = Never, 2 = 1 to 2 times, 3 = 3 to 5 times, 4 = 6 to 10 times, 5 = more than 10 times). The RAPI has internal consistency of .92 (White & Labouvie, 1989).

SB Trip

In the post-SB survey, students were asked to report where they actually spent each day of SB: 1=Home (where you live during the quarter), 2=Hometown (where you grew up or where your parents currently reside), 3=Vacation/Leisure destination, 4=On a Day Trip, 5=Other type of travel (e.g., for business or family obligation not in home town). SB Trip was recoded to be 0=no SB-trip and 1=SB Trip (i.e., vacation/leisure destination on any of the ten days).

SB Alcohol Use

In the pre-SB survey, students were asked “What is the most you will drink on a single day during SB?” In the post-SB survey, students were asked to report the actual number of drinks consumed on their highest drinking day of SB.

SB Alcohol-related Consequences

A total of 12 questions were used to assess alcohol-related consequences in the post-SB survey. Eleven items were taken or adopted from the Young Adult Alcohol Problems Screening Test (YAAPST; Hurlbut & Sher, 1992) or the Young Adult Alcohol Consequences Questionnaire (YAACQ; Read et al., 2006) based on review by investigators for consequences relevant to SB drinking versus chronic or academic consequences which were less relevant to SB drinking. An additional item was added to assess injuring oneself during SB. These items were chosen due to their relevancy to SB drinking. Participants were asked to report which items they had experienced during each day of SB (range 0–12 items per day). For each of the 10 days, number of consequences was scored as the number of problems participants reported having occurred on that day.

SB Friends’ Drinking Norms

Similar to the SB drinking questions, students were asked, “How many DRINKS you think YOUR FRIENDS will drink during their PEAK Spring Break drinking occasion?”

SB Trip with Friends

Students were asked how many days of their SB were spent with friends. Responses ranged from 0 to 10 days.

SB Pacts with Friends

Students were asked whether they had a pact to drink more than normal or get drunk with their friends during SB (0=no, 1=yes) and whether they were encouraged to get drunk on SB (0=no, 1=yes).

SB Environmental Context

Students were asked several questions one-week post SB to determine the contextual variables which may have led to underestimating their actual drinking. Questions included were: “Did anyone purchase drinks for you during Spring Break?” (0=no, 1=yes) “Did you receive any Spring Break bar specials during Spring Break?” (0=no, 1=yes) “Were drinking games played during your Spring Break?” (0=no, 1=yes)

3. Results

Descriptive statistics are shown in Table 1. The mean number of actual peak drinks on a single day of SB was 7.84 (SD=4.84, range=0–25). Addressing Aim 1, 29% of participants underestimated their alcohol use during SB, that is, they estimated that they would consume fewer drinks than they actually did (mean intended drinks = 5.44 (SD = 4.8).

Table 1.

Descriptive Statistics

Variable M/% SD Range
Predictor variables
Male gender 40%
Fraternity/Sorority status 18%
Intervention condition 84%
Previous alcohol-related consequences 9.65 9.97 0 – 74
Own intended peak number of SB drinks 5.44 4.80 0 – 25
Prediction of friends’ peak number of SB drinks 6.12 4.65 0 – 25
Drinking pacts with friends 61%
Friends encouraged getting drunk 3.32 1.74 0 – 6
Number of days spent with friends during SB 6.77 3.13 0 – 10
Spent day(s) of SB at home, where currently live 13%
Spent day(s) of SB in hometown 8%
Spent day(s) of SB on leisure trip 11%
Received bar specials during SB 30%
Received drinks purchased by others during SB 73%
Played drinking games during SB 68%
Outcome variables
Underestimation of actual number of peak SB drinks (actual number drinks > intended) 29%
Total SB alcohol-related consequences 4.86 6.68 0 – 61
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Note. Gender was contrast coded (Men = 1, Women = 0); SB = 10 days of Spring Break; Peak = highest number of drinks consumed in a single sitting; Underestimated of peak SB drinking was a dichotomous Yes/No variable derived from the discrepancy between intended peak number of drinks reported at Screening and the number of drinks actually consumed on the peak Spring Break drinking occasion as reported at 1 week follow-up.

To address Aim 2, logistic regression was used to predict whether students underestimated their Spring Break total number of drinks (compared to overestimating), based on individual (Step 1), interpersonal (Step 2), and contextual (Step 3) characteristics (Table 2). To address Aim 3, linear regression was used to estimate the total number of negative alcohol-related consequences experienced during SB, based on the same variables described for Aim 2 plus the addition of underestimating total number of drinks (Step 4) as a predictor (Table 2). Of the individual variables, men were more likely to underestimate peak drinks than women, and there were no gender differences for consequences. Fraternity/sorority members had nearly twice the odds of underestimating their peak drinks, but did not report any greater likelihood of experiencing more total consequences than non-members. There were no intervention differences on underestimation or number of reported alcohol consequences. Students who reported experiencing greater number of alcohol-related consequences in the prior 3 months reported greater likelihood of underestimating their peak SB drinking and, not surprisingly, also reported experiencing more total number of negative SB consequences. Students who intended to consume more peak drinks were less likely to underestimate their peak drinks and experienced more consequences. Interpersonal characteristics were also significant as a set, although predictions of friends’ peak drinking did not predict underestimation or consequences. Students who had drinking pacts with friends and whose friends encouraged them to drink experienced more consequences. Further, students whose friends encouraged getting drunk were also more likely to underestimate their peak drinks.

Table 2.

Logistic and linear multiple regressions predicting underestimation of peak drinks consumed and total alcohol-related consequences during Spring Break (SB)

Variable Underestimation of number of drinks to be consumed on peak SB occasion Total SB alcoholrelated consequences experienced
B (SE) Odds ratio CI B (SE) β
Step 1-Individual
Male gender .71 (.21) * 2.03* [1.34, 3.08] −0.06 (.52) −.00
Fraternity/Sorority Status .64 (.20) 1.89 ** [1.27, 2.81] 0.79 (.51) .05
Intervention condition .17 (.25) 1.19 [0.73, 1.92] −0.95 (.60) −.05
Previous alcohol-related consequences .03 (.01) 1.03 ** [1.01, 1.05] 0.34 (0.3) .47***
Own intended peak number of SB drinks −.17 (.03) 0.85 *** [0.80, 0.90] 0.32 (.07) .19***
Step χ2 Step R2 Δ = .33***
Step 2-Interpersonal
Prediction of friends’ peak number of SB drinks .02 (.04) 1.02 [0.95, 1.10] 0.15 (.08) .09
Drinking pacts with friends .42 (.22) 1.52 [0.99, 2.35] 1.52 (.50) .11**
Friends encouraged getting drunk .32 (.07) 1.38 *** [1.21, 1.57] 0.84 (.14) .21***
Step χ2 =42.78*** Step R2 Δ = .07***
Step 3-Contextual
Number of days spent with friends during SB .07 (.04) 1.07t [1.00, 1.15] 0.10 (.07) .04
Spent day(s) of SB at home, where currently live .25 (.28) 1.28 [0.75, 2.20] −0.95 (.59) −.05
Spent day(s) of SB in hometown .02 (.21) 1.02 [0.67, 1.53] −0.44 (.45) −.03
Spent day(s) of SB on leisure trip .54 (.24) 1.71 * [1.08, 2.72] 0.15 (.49) .01
Received bar specials during SB .19 (.23) 1.21 [0.77, 1.89] 1.88 (.52) .12***
Received drinks purchased by others during SB .58 (.25) 1.78* [1.09, 2.92] 0.98 (.51) .07
Played drinking games during SB .43 (.25) 1.54 [0.95, 2.49] 0.67 (.52) .05
Step χ2 =25.15** Step R2 Δ = .03***
Step 4 -Underestimation of Peak SB drinking
Underestimation of actual number of peak SB drinks (actual number of drinks > intended) 2.64 (.50) .18***
Step R2 Δ = .03***
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Note.

*

p < 0.05,

**

p < 0.01,

***

p < 0.001; Gender was contrast coded (Men = 1, Women = 2); SB = 10 days of Spring Break; Peak = highest number of drinks consumed in a single sitting; Underestimated of peak SB drinking was a dichotomous Yes/No variable derived from the discrepancy between intended peak number of drinks reported at Screening and the number of drinks actually consumed on the peak SB drinking occasion as reported at 1 week follow-up.

Contextual factors significantly predicted both outcomes, although the patterns were different. Number of days spent with friends during SB, spending more days at home (where they currently live), spending time in one’s hometown, and playing drinking games were not associated with either outcome. Spending more days on a leisure trip was associated with a greater likelihood of underestimating peak drinks, but not consequences. Students who received bar specials had no difference on underestimation of peak drinks but experienced more consequences. Those who received drinks purchased by others were more likely to underestimate their peak drinks but did not experience more consequences. Finally, underestimating peak drinking was associated with experiencing more consequences.

4. Discussion

The present study was designed to examine the accuracy of college students’ intentions to drink alcohol during SB and to explore individual, interpersonal, and contextual factors that might predict whether an individual drinks more than he/she anticipated prior to SB. Our study applies the Theory of Planned Behavior to SB drinking to account for links between behavioral intentions, behavior, and behavioral consequences, during the high-risk SB context. Findings confirm that many students, almost 1/3 (29%), underestimate how much they will actually drink during SB, and underestimation is associated with experiencing a greater number of negative alcohol-related consequences. Results indicated that being male, being a member of a fraternity or sorority, previously experiencing more negative consequences, and intending to drink less during SB predicted underestimating peak drinks consumed during SB. In general, interpersonal and contextual factors appear to be risk factors for underestimating how much one will drink on peak drinking days during SB and for experiencing more negative consequences during SB. Interpersonal factors, such as having pacts with friends and having friends’ encourage getting drunk was associated total number of consequences. Further, having friends’ who encouraged getting drunk was associated with greater underestimation of SB drinking. Contextual factors depended on the outcome with going on a SB trip: having people buy drinks associated with greater underestimation, whereas receiving bar specials was associated with more negative consequences. Underestimating the peak number of drinks to be consumed on SB was associated with experiencing a greater number of alcohol-related consequences.

These findings are consistent with TPB: students’ pre-SB underestimation of their actual SB drinking indicates a misperception of likely SB alcohol use and, thereby, misperception of risk for SB alcohol-related consequences. Significant findings from the study suggest that students with lower drinking intentions prior to an event are not necessarily at lower risk for SB alcohol use. In fact, findings from the individual factors suggest that students who have higher intentions had lower likelihood of underestimating their peak drinking, framed another way this suggests that students who had lower intentions were at greater risk of underestimating how much they actually drink. The fact that students may have lower pre-SB intentions certainly does not preclude getting into situations that strongly encourage drinking during SB (i.e., partying with friends at SB vacation destinations). When “in the moment,” individuals may ultimately make the decision to drink at unexpectedly high levels and place themselves at even more risk than individuals who are better able to anticipate their drinking. This extra risk may arise because those with lower intentions to drink may not plan adequate protective strategies in advance (i.e., more money for taxi, designated driver, etc.) compared to those who intend to drink more. Other research has shown that students who are typically lighter drinkers during the academic year but who drink at greater rates during events such as 21st birthdays and SB are at higher risk for experiencing negative consequences (Lee et al., 2009; Lewis et al., 2009). Consistent with this research, intervention programs should not only target those who anticipate drinking at high rates during SB, but also those who intend to drink lower amounts but have other risk factors, such as going on a trip for multiple days, having pacts with friends to drink, having friends who encourage getting drunk, or being in situations where people may buy them alcohol.

To some extent our findings are consistent with the theory planned behavior, as social/interpersonal factors also significantly influenced drinking and drinking risks. However, while interpersonal factors, particularly perceived drinking norms, have been shown to be important predictors of general college student alcohol use (Baer et al., 1991; Wood et al., 2001), the present study did not find support for perceived friend norms when other individual and interpersonal factors were controlled. Both the theory of reasoned action and the theory of planned behavior posit that perceived social norms influence intentions and behavior more strongly when social influences are considered important. Not surprisingly, the students who actively made pacts with their friends to engage in high-risk alcohol use underestimated how much they were going to actually drink during SB and experienced more consequences, which is consistent with prior research (Patrick et al., 2011). Therefore, this may be another example where the SB context must be taken into account as these relationships may be more relevant during SB. Future research could further explore the dynamic and mutual influences friends have on SB drinking, particularly in the contextual/environmental factors found important in this study, such as buying each other drinks.

Recent research has begun to develop interventions that target specific known, high-risk events such as 21st birthdays and SB (e.g., Lee et al., 2014; Neighbors et al., 2009, 2012, Patrick et al., 2014). Many college campuses recognize SB risks for increased alcohol use among students and some provide programming for SB, often in the form of media campaigns and campus-based educational lecture programming, though most work has not been evaluated for efficacy. Interventions targeting students could focus on discussion of how drinking intentions may be altered depending on situations or events and may not be adhered to in the moment, placing individuals at risk for greater drinking and experiencing negative consequences. Helping students to identify, plan, and utilize protective behavioral strategies for high-risk drinking, even on occasions they do not plan to drink or to drink a lot may buffer the harm that could result from unplanned drinking. Further, targeting high-risk individuals (e.g., those going on trips) or including friends who are planning a trip together may help reduce SB risky drinking and related consequences. Although research has suggested individually-based motivational interventions have the strongest effects regarding reduced drinking and negative alcohol-related consequences when compared to computer-delivered interventions (see Carey et al., 2012), the feasibility of delivering an individual intervention to each student planning a SB trip is unrealistic. Group based interventions have shown recent promise with high-risk, mandated students (Hustad et al., 2014), which offers some support for considering this approach with specific high-risk individuals in an effort to reduce the potential for underestimating SB drinking and, as a result, a potential for more alcohol-related consequences.

The present study should be viewed in light of certain limitations, and can be extended in several future directions. While the present manuscript utilized data from a large public university, results may not generalize to all students. While the initial sample that was drawn for study invitation was representative of the larger university demographics, participants who were eligible and enrolled for the study included only students who met eligibility criteria, including that of heavy drinking intentions during spring break, thus may not represent the demographics of the larger university but may be of those who met eligibility criteria. A majority of these students were White and the sample only included students who had previously planned to go on a SB trip. Further response rate from the initial study was 36.3% which is slight lower than what typically is expected with similar recruitment procedures, however we shortened our recruitment period considerably due to higher than expected rates of students meeting our eligibility criteria. Numerous future research directions are highlighted by the present findings. Although potentially cost prohibitive and burdensome for participants, daily or repeated-measures designs assessing a greater number of interpersonal and contextual factors throughout SB would be quite informative. In addition, understanding what protective behavioral strategies are being planned and actually utilized on days of higher and lower intentions would provide further information for tailoring intervention content to particular situations. Future studies could examine factors related to overestimating (i.e., are there protective factors that lead students to drink less than intended?), and whether the destination of the trip or other variables related to context relate to alcohol use and consequences. Future research could also assess motivational factors for SB trip-taking and how reasons for travel may impact drinking intentions and the underestimation of alcohol to be consumed during SB.

Highlights.

  • Many college students underestimated how much they would drink during Spring Break.

  • Individual factors (e.g., being male) predicted underestimating actual drinking.

  • SB trips & having drinking pacts with friends predicted underestimating actual drinking.

  • Receiving drinks from others predicted alcohol-related negative consequences.

  • Students who underestimated their peak drinks on SB had more negative consequences.

Acknowledgments

Data collection and article preparation were supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) Grants R01AA016099 to C. M. Lee and R03AA018735 to M. E. Patrick.

Role of Funding Sources

The project described and manuscript preparation was supported by Award Number R01AA016099 from the National Institute on Alcohol Abuse and Alcoholism. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Alcohol Abuse and Alcoholism or the National Institutes of Health.

Footnotes

Contributors

The authors have worked in collaboration for this study. Christine Lee was the principal investigator of the larger study and responsible for study design and implementation. Christine Lee and Megan Patrick conceived the ideas for the present manuscript and Megan conducted the statistical analyses and prepared the draft of results. Angela Mittmann, Irene Geisner, Nadine Mastroleo, and Lindsey Zimmerman assisted with preparation of the manuscript including conducting a literature review and drafting the initial draft of introduction and methods and critically revising drafts of the manuscript.

Conflict of Interest

All authors declare they have no conflicts of interest.

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