Skip to main content

Advertisement

Log in

Pre-college Matriculation Risk Profiles and Alcohol Consumption Patterns During the First Semesters of College

  • Published:
Prevention Science Aims and scope Submit manuscript

Abstract

Excessive alcohol consumption represents a significant concern on U.S. college campuses, and there is a need to identify students who may be at risk for engaging in risky alcohol use. The current study examined how variables measured prior to college matriculation, specifically alcohol-related decision-making variables drawn from the Theory of Reasoned Action (i.e., alcohol expectancies, attitudes, and normative beliefs), were associated with patterns of alcohol use prior to and throughout the first semesters of college. Participants were 392 undergraduate students (56 % female) from a large Northeastern U.S. university. Decision-making variables were assessed prior to college matriculation, and alcohol use was measured with five assessments before and throughout freshman and sophomore semesters. Latent profile analysis was used to identify types of students with distinct patterns of decision-making variables. These decision-making profiles were subsequently linked to distinct patterns of alcohol use using latent transition analysis. Four distinct decision-making profiles were found and were labeled “Anti-Drinking,” “Unfavorable,” “Mixed,” and “Risky.” Five drinking patterns were observed and included participants who reported consistently low, moderate, or high rates of alcohol use. Two patterns described low or non-drinking at the pre-college baseline with drinking escalation during the measurement period. Students’ likelihood of following the various drinking patterns varied according to their decision-making. Findings suggest the early identification of at-risk students may be improved by assessing decision-making variables in addition to alcohol use. The findings also have implications for the design of early identification assessments to identify at-risk college students and for the targeting of alcohol prevention efforts to students based on their alcohol-related attitudes and beliefs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Baer, J. S. (1994). Effects of college residence on perceived norms for alcohol consumption: An examination of the first year in college. Psychology of Addictive Behaviors, 8, 43–50. doi:10.1037/0893-164X.8.1.43.

    Article  Google Scholar 

  • Baer, J. S., Stacy, A., & Larimer, M. L. (1991). Biases in the perception of drinking norms among college students. Journal of Studies on Alcohol, 52, 580–586.

    Article  CAS  PubMed  Google Scholar 

  • Borsari, B., Murphy, J. G., & Barnett, N. P. (2007). Predictors of alcohol use during the first year of college: Implications for prevention. Addictive Behaviors, 32, 2062–2086. doi:10.1016/j.addbeh.2007.01.017.

    Article  PubMed Central  PubMed  Google Scholar 

  • Borsari, B., Neal, J., Collins, S. E., & Carey, K. B. (2001). Differential utility of three indexes of risky drinking for predicting alcohol problems in college students. Psychology of Addictive Behaviors, 15, 321–324. doi:10.1037/0893-164X.15.4.321.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13, 195–212. doi:10.1007/BF01246098.

    Article  Google Scholar 

  • Coffman, D. L., Patrick, M. E., Palen, L. A., Rhoades, B. L., & Ventura, A. K. (2007). Why do high school seniors drink? Implications for a targeted approach to intervention. Prevention Science, 8, 241. doi:10.1007/s11121-007-0078-1.

    Article  PubMed  Google Scholar 

  • Collins, S. E., & Carey, K. B. (2007). The theory of planned behavior as a model of heavy episodic drinking among college students. Psychology of Addictive Behaviors, 21, 498–507. doi:10.1037/0893-164X.21.4.498.

    Article  PubMed Central  PubMed  Google Scholar 

  • Collins, R. L., Parks, G. A., & Marlatt, G. A. (1985). 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, 53, 189–200.

    Article  CAS  PubMed  Google Scholar 

  • Cronce, J. M., & Larimer, M. E. (2011). Individual-level focused approaches to the prevention of college student drinking. Alcohol Research & Health, 34, 210–221. doi: SPS-AR&H-33.

    Google Scholar 

  • DeJong, W., Schneider, S. K., Towvim, L. G., Murphy, M. J., Doerr, E. E., Simonsen, N. R., & Scribner, R. A. (2006). A multisite randomized trial of social norms marketing campaigns to reduce college student drinking. Journal of Studies on Alcohol, 67, 868–879.

    Article  PubMed  Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading: Addison Wesley Publishing Company.

    Google Scholar 

  • Gerrard, M., Gibbons, F. X., Reis-Bergan, M., Trudeau, L., Vande Lune, L. S., & Buunk, B. (2002). Inhibitory effects of drinker and nondrinker prototypes on adolescent alcohol consumption. Health Psychology, 21(6), 601–609. doi:10.1037//0278-6133.21.6.601.

    Article  PubMed  Google Scholar 

  • Graham, J. W., Cumsille, P. E., & Elek-Fisk, E. (2003). Methods for handling missing data. In J. A. Schinka & W. F. Velicer (Eds.), Research methods in psychology (pp. 87–114). New York: John Wiley & Sons.

    Google Scholar 

  • Greenbaum, P. E., Del Boca, F. K., Darkes, J., Wang, C., & Goldman, M. S. (2005). Variation in the drinking trajectories of freshmen college students. Journal of Consulting and Clinical Psychology, 73, 229. doi:10.1037/0022-006X.73.2.229.

    Article  PubMed  Google Scholar 

  • Hingson, R. W., Zha, W., & Weitzman, E. R. (2009). Magnitude of and trends in alcohol-related mortality and morbidity among U.S. college students ages 18–24, 1998–2005. Journal of Studies on Alcohol and Drugs, Supplement No. 16, 12–20.

  • Jaccard, J., Turrisi, R., & Wan, C. K. (1990). Implications of behavioral decision theory and social marketing for designing social action programs. In J. Edwards et al. (Eds.), Social influence processes and prevention (pp. 103–142). New York: Springer Publishing.

    Chapter  Google Scholar 

  • King, A. C., Ahn, D. F., Atienza, A. A., & Kraemer, H. C. (2008). Exploring refinements in targeted behavioral medicine intervention to advance public health. Annals of Behavioral Medicine, 35, 251–260. doi:10.1007/s12160-008-9032-0.

    Article  PubMed  Google Scholar 

  • Knight, J. R., Wechsler, H., Kuo, M., Siebring, M., Weitzman, E. R., & Schuckit, M. A. (2002). Alcohol abuse and dependence among U.S. college students. Journal of Studies on Alcohol, 63, 263–270.

    Article  PubMed  Google Scholar 

  • Kypri, K., Hallett, J., Howat, P., McManus, A., Maycock, B., Bowe, S., & Horton, N. J. (2009). Randomized controlled trial of proactive web-based alcohol screening and brief intervention for university students. Archives of Internal Medicine, 169, 1508–1514. doi:10.1001/archinternmed.2009.249.

    Article  PubMed  Google Scholar 

  • Lanza, S. T., & Collins, L. M. (2006). A mixture model of discontinuous development in heavy drinking from ages 18 to 30: The role of college enrollment. Journal of Studies on Alcohol, 67, 552.

    Article  PubMed  Google Scholar 

  • Larimer, M. E., Lee, C. M., Kilmer, J. R., Fabiano, P., Stark, C., Geisner, I. M., & Neighbors, C. (2007). Personalized mailed feedback for drinking prevention: One year outcomes from a randomized clinical trial. Journal of Consulting and Clinical Psychology, 75, 285–293. doi:10.1037/0022-006X.75.2.285.

    Article  PubMed Central  PubMed  Google Scholar 

  • Larimer, M. E., & Cronce, J. M. (2002). Identification, prevention, and treatment: A review of individual-focused strategies to reduce problematic alcohol consumption by college students. Journal of Studies on Alcohol, Supplement No. 14, 148–163.

  • Larimer, M. E., Turner, A. P., Mallett, K. A., & Geisner, I. M. (2004). Predicting drinking behavior and alcohol-related problems among fraternity and sorority members: Examining the role of descriptive and injunctive norms. Psychology of Addictive Behaviors, 18, 203–212. doi:10.1016/j.addbeh.2007.05.006.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778. doi:10.1093/biomet/88.3.767.

    Article  Google Scholar 

  • Musher-Eizenman, D. R., & Kulick, A. D. (2003). An alcohol expectancy-challenge prevention program for at-risk college women. Psychology of Addictive Behaviors, 17, 163–166.

    Article  PubMed  Google Scholar 

  • Muthén, B. O. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage Publications.

    Google Scholar 

  • Muthén, B. O., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism, Clinical and Experimental Research, 24, 882–891. doi:10.1111/j.1530-0277.2000.tb02070.x.

    Article  PubMed  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (2012). Mplus user’s guide (7th ed.). Los Angeles: Muthén and Muthén.

    Google Scholar 

  • National Institute for Alcohol Abuse and Alcoholism (2012). College drinking. Retrieved from: http://www.niaaa.nih.gov/aboutNIAAA/NIAAASponsoredPrograms/underage.htm

  • O'Connor, R. M., & Colder, C. R. (2005). Predicting alcohol patterns in first-year college students through motivational systems and reasons for drinking. Psychology of Addictive Behaviors, 19, 10–20. doi:10.1037/0893-164X.19.1.10.

    Article  PubMed  Google Scholar 

  • Read, J. P., Wood, M. D., Davidoff, O. J., McLacken, J., & Campbell, J. F. (2002). Making the transition from high school to college: The role of alcohol-related social influence factors in students' drinking. Substance Abuse, 23, 53–65. doi:10.1080/08897070209511474.

    PubMed  Google Scholar 

  • Reinert, D. F., & Allen, J. P. (2002). The Alcohol Use Disorders Identification Test (AUDIT): A review of recent research. Alcoholism, Clinical and Experimental Research, 26, 272–279.

    Article  PubMed  Google Scholar 

  • Saitz, R., Palfai, T. P., Freedner, N., Winter, M. R., Macdonald, A., Lu, J., & Dejong, W. (2007). Screening and brief intervention online for college students: The ihealth study. Alcohol and Alcoholism, 42, 28–36. doi:10.1093/alcalc/agl092.

    Article  PubMed  Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics. Boston: Allyn and Bacon. doi: 10.1177/014662168400800412.

    Google Scholar 

  • Turrisi, R. (1999). Cognitive and attitudinal factors in the analysis of alternatives to binge drinking. Journal of Applied Social Psychology, 29, 1510–1533.

    Google Scholar 

  • Turrisi, R., Abar, C., Mallett, K. A., & Jaccard, J. (2010). An examination of the meditational effects of cognitive and attitudinal factors of a parent intervention to reduce college drinking. Journal of Applied Social Psychology, 40, 2500–2526.

    Article  PubMed Central  PubMed  Google Scholar 

  • Turrisi, R., Jaccard, J., Taki, R., Dunnam, H., & Grimes, J. (2001). Examination of the short-term efficacy of a parent intervention to reduce college student drinking tendencies. Psychology of Addictive Behaviors, 15, 366–372. doi:10.1037/0893-164X.15.4.366.

    Article  CAS  PubMed  Google Scholar 

  • Turrisi, R., Larimer, M., Mallett, K., Kilmer, J. R., Ray, A. E., Mastroleo, N. R., & Montoya, I. (2009). A randomized clinical trial evaluating a combined alcohol intervention for high-risk college students. Journal of Studies on Alcohol and Drugs, 70, 555–567.

    Article  PubMed Central  PubMed  Google Scholar 

  • Turrisi, R., Mallett, K. A., Cleveland, M., Varvil-Weld, L., Abar, C., Scaglione, N., & Hultgren, B. (2013). An evaluation of timing and dosage of a parent based intervention to minimize college students’ alcohol consumption. Journal of Studies on Alcohol and Drugs, 74, 30–40.

    Article  PubMed Central  PubMed  Google Scholar 

  • Walters, S. T., Vader, A. M., & Harris, T. R. (2007). A controlled trial of web-based feedback for heavy drinking college students. Prevention Science, 8, 83–88. doi:10.1007/s11121-006-0059-9.

    Article  PubMed  Google Scholar 

Download references

Acknowledgment

This research was supported by National Institute on Alcohol Abuse and Alcoholism (NIAAA) grant F31 AA018592 awarded to Jerod Stapleton, NIAAA grant R01 AA015737 to Rob Turrisi, and The Biometrics Shared Resource of Rutgers Cancer Institute of New Jersey (P30 CA072720).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jerod L. Stapleton.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Stapleton, J.L., Turrisi, R., Cleveland, M.J. et al. Pre-college Matriculation Risk Profiles and Alcohol Consumption Patterns During the First Semesters of College. Prev Sci 15, 705–715 (2014). https://doi.org/10.1007/s11121-013-0426-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11121-013-0426-2

Keywords

Navigation