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. Author manuscript; available in PMC: 2012 May 1.
Published in final edited form as: Addict Behav. 2010 Dec 29;36(5):508–511. doi: 10.1016/j.addbeh.2010.12.022

One-Time or Repeat Offenders? An Examination of the Patterns of Alcohol-Related Consequences Experienced by College Students Across the Freshman Year

Kimberly A Mallett a, Miesha Marzell b, Lindsey Varvil-Weld b, Rob Turrisi c, Kelly Guttman a, Caitlin Abar d
PMCID: PMC3063062  NIHMSID: NIHMS270210  PMID: 21276662

Abstract

Recent studies have examined alcohol-related consequences in college students as an independent outcome variable, rather than as a result of heavy drinking. The present study examined the patterns of consequences experienced by first-year college students (n = 169). Specifically, the number of distinct consequences and the frequency of repeated consequences were evaluated as well as the combination of the two. Results revealed that 80% of participants reported experiencing multiple consequences, with over 34% of students reporting 6 or more unique consequences over the course of their freshmen year. In addition, nearly 50% of the sample reported experiencing 3 or more consequences repeatedly. Further, 23% of the sample reported experiencing 5 or more repeated consequences and 6 or more multiple consequences. These individuals experienced 38% of the multiple consequences and 54% of the repeated consequences reported by the entire sample, suggesting individuals who endorsed experiencing multiple consequences repeatedly also experienced a disproportionate number of the total consequences reported by the sample. The findings suggest there are specific high-risk patterns of alcohol-related consequences and demonstrate a need for further examination of additional variables that predict consequences.

Keywords: alcohol, college students, alcohol-related consequences

1. Introduction

College student drinking has been a public health problem for decades (NIAAA, 2002; Strauss & Bacon, 1953). Despite this, a substantial number of students engage in high-risk drinking and experience consequences (Perkins, 2002). As a result, interventions have been developed to reduce student drinking by addressing: 1) education and awareness; 2) cognitive-behavioral skills; and 3) motivational and feedback. Among these, brief motivational interventions (Category 3), particularly those incorporating personalized feedback, have received the most consistent support in the literature for reducing high-risk drinking (Larimer & Cronce, 2002; 2007).

The goal of these interventions is to reduce high-risk drinking with a secondary goal of reducing consequences. The relationship between drinking and consequences is not one-to-one (Larimer, Turner, Mallett & Geisner, 2004; Turner, Larimer & Sarason, 2000), and interventions have had mixed success with reducing consequences. Some have argued this may be due to a variety of issues including short-term follow-up assessments (Carey, Henson, Carey & Maisto, 2007). However, other studies have found reductions in drinking, but not in consequences despite using long-term outcomes (Larimer et al., 2001; Turrisi et al., 2009).

In an attempt to understand the prevalence of alcohol consequences, studies have begun to examine them as outcomes rather than secondary effects of drinking (Mallett, Varvil-Weld, Turrisi & Read, 2010). The literature shows drinking accounts for approximately 30% of the variance in consequences (Larimer et al., 2001; Turner et al., 2000); therefore, identifying other predictors of consequences in addition to drinking is essential. Specifically, research has shown a variety of constructs such as peer and parent approval, negative expectancies, coping motives, attitudes, descriptive norms, and protective behaviors to significantly predict consequences when controlling for drinking (Delva et al., 2004; LaBrie, Hummer, Neighbors & Larimer, 2010; Martens et al., 2004; Neighbors, Lee, Lewis, Fossos & Larimer, 2007; Ray, Turrisi, Abar & Peters, 2009). Studies have also explored individuals’ motivations to avoid consequences (Mallett, Bachrach & Turrisi, 2008), willingness to experience consequences (Mallett, Varvil-Weld et al., 2010), past history of experiencing consequences (Mallett, Marzell, & Turrisi, 2010) positive expectancies and positive consequences (Schulenberg et al., 2001) as predictors of future consequences. Finally, studies have shown that personality disorders and self-regulation predict consequences independent of drinking (Hustad, Carey, Carey & Maisto, 2009; Tragesser, Sher, Trull & Park 2007). Taken together, these findings demonstrate the need to better understand variables that contribute to experiencing consequences and to identify individuals who may be more prone to experience alcohol related problems.

From a prevention standpoint, certain questions regarding consequences remain unanswered. One important issue for prevention is the pattern in which students experience consequences. For example, students could experience the same consequences repeatedly, or they might experience a variety of consequences only once, or they might experience a combination of the two (several consequences repeatedly). For instance, if students tend to experience consequences repeatedly it would be appropriate to target efforts toward reducing those specific consequences. On the other hand, if a variety of different consequences are experienced, targeting risky drinking may be more appropriate since the pattern of consequences is less predictable. If multiple consequences are experienced repeatedly, targeting both a reduction in consumption and specific consequences may be warranted. A second issue for prevention is the prevalence of students in each category. Identifying the percentage of students who fall into these categories will guide intervention efforts to target the specific consequence patterns. These percentages can serve as a benchmark by which to measure the success of environmental and individual-based interventions.

The current study aimed to identify the patterns of consequences of students during their first year of college. Specifically we examined: 1) The number of unique consequences experienced by students over their freshman year, and 2) the frequency of consequences that were experienced repeatedly. In addition, the study examined the association between the two patterns as well as the association with alcohol consumption. We hypothesized that individuals endorsing greater numbers of consequences and higher numbers of repeated consequences consumed more alcohol. However, we hypothesized that these correlations would be moderate based on previous work (Larimer et al., 2004; Mallett, Varvil-Weld et al., 2010). Further, we hypothesized that individuals who experienced multiple consequences on multiple occasions experienced a proportionately greater number of consequences than the rest of the sample.

2. Method

2.1 Participants

The sample consisted of 169 college students at a large, public, northeastern university who consumed at least one alcoholic drink per week. Participants completed the survey during the fall of their second year of college. Respondents were 54.7% (n = 93) female and “traditional” college students with an average age of 19.18 (SD = 0.49). With respect to race, the sample was 91.8% (n = 156) white, 1.7% (n = 3) Asian, 1.2% (n = 2) African American, 2.4% (n = 4) multi-racial, and 2.4% (n = 4) other.

2.2 Procedure

Participants were randomly selected from the university registrar’s database. Invitation letters explaining the procedures and containing a URL and Personal Identification Number (PIN) for accessing the survey were both mailed and emailed to all participants. A 66% response rate was observed, which is consistent with others web-based studies (Larimer et al., 2007; McCabe, Hughes, Bostwick & Boyd, 2005; Thombs, Ray-Tomasek, Osborn & Olds, 2005). Participants received $35 for completing the survey.

2.3 Measures

2.3.1 Alcohol-related consequences

The Young Adult Alcohol Problems Screening Test (YAAPST, Hurlbut & Sher, 1992) measured consequences. Respondents indicated the frequency of occurrence for each consequence listed on the YAAPST (blacking out, receiving a lower grade on an exam, etc.) in the past year. Response options ranged from “never” to “40 or more.”

2.3.2 Alcohol use

As a measure of peak drinking, participants reported the number of drinks they consumed during the occasion on which they drank the most during the past 30 days (Marlatt et al., 1998).

2.3.3 Typical weekly drinking

was measured as the sum of drinks participants indicated they consumed on each day of a typical week within the past 30 days using the Daily Drinking Questionnaire (DDQ; Collins, Parks, & Marlatt, 1985). A standard drink definition was included (i.e., 12 oz. beer, 10 oz. wine cooler, 4 oz. wine, 1 oz. 100 proof {1 ¼ oz. 80 proof} liquor).

2.3.4 Demographics

Participants were asked to provide their age, gender, year in school, and ethnicity.

3. Results

3.1 Descriptives

Respondents reported an average of 13.24 (SD = 9.47) drinks during a typical week and 7.74 (SD = 4.42) drinks during their peak drinking occasion. Only those consequences experienced by at least 5% of the sample were included in the analyses. There were 17 such consequences: hangover (81.1%), vomited (71.6%), blacked out (55.6%), became rude or obnoxious (41.4%), arrived late for work or school (32.5%), skipped an evening meal (30.8%), had regretted sex (29.0%), felt guilty about drinking (25.4%), had sex with someone with whom wouldn’t ordinarily (16.0%), received a lower grade on a test (13.6%), drove after drinking (12.4%), had sex when didn’t want to (11.8%), damaged property (10.1%), got into a physical fight (8.3%), got into trouble at work (8.9%), forgot to use birth control (5.9%), and had the “shakes” after stopping drinking (5.3%).

3.2 Multiple Consequences

First, each YAAPST item was recoded to indicate whether or not the respondent had experienced that consequence in the past year. Scores were then summed to create a “multiple consequence” variable reflecting the total number of unique consequences experienced (see Table 1). The mean for multiple consequences was 4.68 (SD = 3.42). While over 80% of the sample reported experiencing multiple consequences, 34% endorsed experiencing 6 or more consequences. Finally, results indicated reports of multiple consequences were related to higher weekly (r = .49, p < .01) and peak drinking (r = .47, p < .01).

Table 1.

Frequency distribution of consequences.

Number of multiple
consequences		 N (%) Number of repeated
consequences		 N (%)
0–1 30 (17.8%) 0 32 (18.9%)
2–3 44 (26.0%) 1–2 57 (33.7%)
4–5 37 (21.9%) 3–4 41 (24.3%)
6 or more 58 (34.3%) 5 or more 39 (23.1%)
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3.3 Repeated Consequences

For repeated consequences, the original YAAPST items were recoded where a score of 1 reflected consequences that were experienced two or more times in the past year; otherwise, the item was scored ‘0’. Scores were summed to create the “repeated consequence” variable reflecting repeated consequences over the past year. The mean for repeated consequences was 2.80 (SD = 2.55). According to Table 1, 80% of the sample reported repeated consequences; where 23% of the sample reported 5 or more repeated consequences. The most common repeated consequences were hangover (71%), vomit (53.5%), blacking out (37.6%), and being rude (28%). Finally, results indicated reports of repeated consequences were correlated with weekly (r = .56, p < .01) and peak drinking (r = .49, p < .01).

3.4 Multiple and Repeated Consequences

Experiencing multiple consequences was significantly correlated with repeatedly experiencing consequences (Spearman’s r = .861, p < .001). Examination of Table 2 revealed of the 34% of the sample who experienced 6 or more (multiple) consequences, 67% reported 5 or more repeated consequences and 29% reported 3 to 4 repeated consequences. Further, while 86% of the sample reported experiencing either multiple or repeated consequences, 23% were in the highest risk group (5 or more repeated and 6 or more multiple). These individuals accounted for 38% of the multiple consequences and 54% of the repeated consequences reported by the entire sample. Finally, 13% of participants did not experience either multiple or repeated consequences.

Table 2.

Conditional distribution of multiple and repeated consequences.

Repeated consequences
Multiple
consequences		 0 1–2 3–4 5 or more
0–1 23 (13.6%) 7 (4.1%) 0 (0%) 0 (0%)
2–3 7 (4.1%) 33 (19.5%) 4 (2.4%) 0 (0%)
4–5 2 (1.2%) 15 (8.9%) 20 (11.8%) 0 (0%)
6 or more 0 (0%) 2 (1.2%) 17 (10.1%) 39 (23.1%)
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Note. Percentages reflect the total number of participants in the sample

4. Discussion

The study examined patterns of consequences by college students during their first year. The first pattern consisted of multiple consequences. This suggests students are experiencing a variety of unique consequences with varying degrees of risk (e.g., 34% experiencing 6 or more consequences). The second pattern consisted of those individuals that experienced the same consequences repeatedly. Nearly 50% of the sample reported experiencing 3 or more consequences repeatedly. The most commonly repeated consequences were physical in nature.

Based upon our findings recommendations for tailoring interventions can be considered. First, an intervention targeting a reduction in drinking may be most useful for individuals prone to experiencing multiple unique consequences. This is the typical intervention approach used most frequently on college campuses (Turrisi et al., 2009). Second, for individuals who experience the same consequences repeatedly, a novel approach may be to target specific consequences. It may be most useful to keep the focus of the intervention on avoiding consequences. Our findings revealed quantity of drinking was only moderately associated with the repeated consequences, indicating the importance of identifying additional variables, aside from drinking. For example, consequence-specific attitudes, beliefs, and normative perceptions have shown unique relationships with consequences independent of drinking and warrant further examination (Mallett, Varvil-Weld et al., 2010).

Our data also revealed that a small percentage of the sample accounted for a disproportionate number of experienced consequences, both multiple and repeated. First, it is imperative to identify these students as they transition to college to intervene early. Second, research is needed to examine variables that may both provide screening information (e.g. age of drinking onset) and become targeted by interventions (e.g. motivation to avoid consequences).

4.1 Limitations & Future Directions

Although this study highlights examining patterns of consequences, it should be noted the data were retrospective. Future studies would benefit from prospective, diary approaches to examine the time between experiencing consequences, the immediate impact on drinking, and the perceptions of the consequences. In addition, participants were all freshmen, limiting generalizability. Future research could examine students in upper-class years to provide information regarding maturing out, which may enhance prevention by revealing an optimal intervention time. Overall, the findings suggest a need for prospective studies to elucidate the specific nature of consequences experienced by college students and subsequent drinking behavior. Further, studies that examine specific high-risk drinking behaviors (e.g. combined alcohol and energy drink use) and background characteristics (e.g. parent and peer factors) that may be protective or risky are needed considering they may provide information for prevention targeting high-risk individuals.

4.2 Conclusion

In conclusion, the study identified patterns of consequences experienced by college students and highlighted the need for examining unique predictors of consequences. Results identified a high-risk subgroup of students who may benefit from intervention efforts that focus on reducing drinking and increasing motivation to avoid drinking consequences.

Acknowledgments

This research was supported by grant R01AA015737 from the National Institute on Alcohol Abuse and Alcoholism.

Footnotes

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References

  1. Carey KB, Henson JM, Carey MP, Maisto SA. Which heavy drinking college students benefit from a brief motivational intervention? Journal of Counseling and Clinical Psychology. 2007;75:663–669. doi: 10.1037/0022-006X.75.4.663. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Collins RL, Parks GA, Marlatt GA. Social determinants of alcohol consumption: The effects of social interaction and model status on the self-administration of alcohol. Journal of Consulting and Clinical Psychology. 1985;53:189–200. doi: 10.1037//0022-006x.53.2.189. [DOI] [PubMed] [Google Scholar]
  3. Delva J, Smith MP, Howell RL, Harrison DF, Wilke D, Jackson DL. A study of the relationship between protective behaviors and drinking consequences among undergraduate college students. Journal of American College Health. 2004;53:19–26. doi: 10.3200/JACH.53.1.19-27. [DOI] [PubMed] [Google Scholar]
  4. Hurlbut SC, Sher KJ. Assessing alcohol problems in college students. Journal of American College Health. 1992;41:49–58. doi: 10.1080/07448481.1992.10392818. [DOI] [PubMed] [Google Scholar]
  5. Hustad JT, Carey KB, Carey MP, Maisto SA. Self-regulation, alcohol consumption, and consequences in college student heavy drinkers: a simultaneous latent growth analysis. Journal of Studies on Alcohol and Drugs. 2009;70:373–382. doi: 10.15288/jsad.2009.70.373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. LaBrie JW, Hummer JF, Neighbors C, Larimer ME. Whose opinion matters? The relationship between injunctive norms and alcohol consequences in college students. Addictive Behaviors. 2010;35:343–349. doi: 10.1016/j.addbeh.2009.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Larimer ME, Cronce JM. Identification, prevention, & treatment: A review of individual-focused strategies to reduce problematic alcohol consumption by college students. Journal of Studies on Alcohol Suppl. 2002;14:148–163. doi: 10.15288/jsas.2002.s14.148. [DOI] [PubMed] [Google Scholar]
  8. Larimer ME, Cronce JM. Identification, prevention, and treatment revisited: Individual-focused college drinking prevention strategies 1999–2006. Addictive Behaviors. 2007;32(11):2439–2468. doi: 10.1016/j.addbeh.2007.05.006. [DOI] [PubMed] [Google Scholar]
  9. Larimer ME, Lee CM, Kilmer JR, Fabiano P, Stark C, Geisner IM, Mallett KA, Lostutter TW, Cronce JM, Feeney M, Neighbors C. Personalized mailed feedback for drinking prevention: One year outcomes from a randomized clinical trial. Journal of Consulting and Clinical Psychology. 2007;75:285–293. doi: 10.1037/0022-006X.75.2.285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Larimer ME, Turner AP, Anderson BK, Fader JS, Kilmer JR, Palmer RS, Cronce JM. Evaluating a brief alcohol intervention with fraternities. Journal of Studies on Alcohol. 2001;62:370–380. doi: 10.15288/jsa.2001.62.370. [DOI] [PubMed] [Google Scholar]
  11. Larimer ME, Turner AP, Mallett KA, Geisner IM. Predicting drinking behavior and alcohol-related problems among fraternity and sorority members: Examining the role of descriptive and injunctive norms. Psychology of Addictive Behaviors. 2004;18:203–212. doi: 10.1037/0893-164X.18.3.203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Mallett KA, Bachrach RL, Turrisi R. Are all negative consequences truly negative? Assessing variations among college students’ perceptions of alcohol related consequences. Addictive Behaviors. 2008;33:1375–1381. doi: 10.1016/j.addbeh.2008.06.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Mallett KA, Marzell M, Turrisi R. Is reducing drinking always the answer to reducing consequences in first year college students? 2010 doi: 10.15288/jsad.2011.72.240. Manuscript submitted for publication. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Mallett KA, Varvil-Weld L, Turrisi R, Read A. Examination of behavioral willingness to experience consequences, alcohol consumption and alcohol related consequences in first year college students. 2010 Manuscript submitted for publication. [Google Scholar]
  15. Marlatt GA, Baer JS, Kivlahan DR, Dimeff LA, Lairmer ME, Quigley LA, Somers JM, Williams E. Screening and brief intervention with high-risk college student drinkers: Results from a two-year follow-up assessment. Journal of Consulting and Clinical Psychology. 1998;66:604–615. doi: 10.1037//0022-006x.66.4.604. [DOI] [PubMed] [Google Scholar]
  16. Martens MP, Taylor KK, Damann KM, Page JC, Mowry ES, Cimini MD. Protective behavioral strategies when drinking alcohol and their relationship to negative alcohol-related consequences in college students. Psychology of Addictive Behaviors. 2004;18:390–393. doi: 10.1037/0893-164X.18.4.390. [DOI] [PubMed] [Google Scholar]
  17. McCabe SE, Hughes TL, Bostwick W, Boyd CJ. Assessment of difference in dimensions of sexual orientation: Implications for substance use research in a college-age population. Journal of Studies on Alcohol. 2005;66:620–629. doi: 10.15288/jsa.2005.66.620. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. National Institute on Alcohol Abuse and Alcoholism. Bethesda, MD: US Dept of Health and Human Services; A call to action: Changing the culture of drinking at US colleges. 2002
  19. Neighbors C, Lee CM, Lewis MA, Fossos N, Larimer ME. Are social norms the best predictor of outcomes among heavy drinking college students? Journal of Studies on Alcohol and Drugs. 2007;68:556–565. doi: 10.15288/jsad.2007.68.556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Perkins HW. Surveying the damage: a review of research on consequences of alcohol misuse in college populations. Journal of Studies on Alcohol Suppl. 2002:91–100. doi: 10.15288/jsas.2002.s14.91. [DOI] [PubMed] [Google Scholar]
  21. Ray AE, Turrisi R, Abar B, Peters KE. Social-cognitive correlates of protective drinking behaviors and alcohol-related consequences in college students. Addictive Behaviors. 2009;34(11):911–917. doi: 10.1016/j.addbeh.2009.05.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Schulenberg J, Maggs JL, Long SW, Sher KJ, Gotham HJ, Baer JS, Kivlahan DR, Marlatt GA, Zucker RA. The problem of college drinking: insights from a developmental perspective. Alcoholism, Clinical and Experimental Research. 2001;25:473–477. [PubMed] [Google Scholar]
  23. Straus R, Bacon S. Drinking in College. New Haven, CT: Yale University Press; 1953. [Google Scholar]
  24. Thombs DL, Ray-Tomasek J, Osborn CJ, Olds RS. The role of sex-specific normative beliefs in undergraduate alcohol use. American Journal of Health Behavior. 2005;29:342–351. doi: 10.5993/ajhb.29.4.6. [DOI] [PubMed] [Google Scholar]
  25. Tragesser SL, Sher KJ, Trull TJ, Park A. Personality disorder symptoms, drinking motives and alcohol use and consequences: cross-sectional and prospective mediation. Experimental and Clinical Psychopharmacology. 2007;15:282–292. doi: 10.1037/1064-1297.15.3.282. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Turner AP, Larimer ME, Sarason IG. Family risk factors for alcohol-related consequences and poor adjustment in fraternity and sorority members: Exploring the role of parent-child conflict. Journal of Studies on Alcohol. 2000;61:818–826. doi: 10.15288/jsa.2000.61.818. [DOI] [PubMed] [Google Scholar]
  27. Turrisi R, Larimer M, Mallett KA, Kilmer J, Ray A, Mastroleo N, Giesner I, Grossbard J, Lostutter T, Tollison S, Montoya H. A randomized clinical trial evaluating a combined alcohol intervention for high-risk college students. Journal of Studies on Alcohol and Drugs. 2009;70:555–567. doi: 10.15288/jsad.2009.70.555. [DOI] [PMC free article] [PubMed] [Google Scholar]

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