Prevention Science

, Volume 20, Issue 6, pp 873–883 | Cite as

The Efficacy of an Event-Specific, Text Message, Personalized Drinking Feedback Intervention

  • Jennifer M. CadiganEmail author
  • Matthew P. Martens
  • Emily R. Dworkin
  • Kenneth J. Sher


Tailgating drinking prior to a football game is a type of event-specific drinking associated with increased alcohol use and related problems. Personalized drinking feedback interventions (PFI) are efficacious in reducing alcohol use and problems. The current study aimed to advance understanding of event-specific interventions by examining: (1) the efficacy of an event-specific, text message PFI on tailgating alcohol outcomes, and (2) the extent to which intervention effects generalize to “typical” alcohol outcomes at 1-month follow-up. College students (N = 130; 71% female; 92% white) who reported tailgating within the past 30 days and binge drinking when tailgating in the past year completed assessments on tailgating and typical alcohol use. They were randomly assigned to one of two text message conditions delivered on the morning of a home football game: event-specific PFI (TXT PFI) or a control condition. Multilevel modeling examined the association of treatment condition on tailgating and 1-month alcohol outcomes. When tailgating, participants in TXT PFI reported lower estimated peak blood alcohol concentration (eBAC) and consumed less drinks than the control condition. At the 1-month “typical” drinking follow-up, participants in TXT PFI reported lower peak eBAC and fewer alcohol-related problems than the control condition. Perceived tailgating drinking norms were found to statistically mediate the relationship between condition and alcohol outcome at tailgating and 1-month follow-ups. Findings provide preliminary support for the efficacy of an event-specific, text message PFI in reducing both tailgating and typical drinking alcohol outcomes. Event-specific TXT PFI can be used for prevention/intervention of alcohol misuse.


Event-specific Tailgate Text message Personalized feedback Alcohol 



Data collection and manuscript preparation for this article was supported by National Institute on Alcohol Abuse and Alcoholism Grant F31AA022830 (PI: Cadigan). Manuscript preparation was also supported in part through National Institute of Alcohol Abuse and Alcoholism Grants F32AA025263 (PI: Cadigan), T32AA007455 (PI: Larimer), and K05AA017242 (PI: Sher).

Compliance with Ethical Standards

Conflicts of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.


  1. Baer, J. S., Stacy, A., & Larimer, M. (1991). Biases in the perception of drinking norms among college students. Journal of Studies on Alcohol, 52, 580–586.CrossRefPubMedGoogle Scholar
  2. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014). Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:1406.5823.Google Scholar
  3. Borsari, B., & Carey, K. B. (2001). Peer influences on college drinking: A review of the research. Journal of Substance Abuse, 13, 391–424.CrossRefGoogle Scholar
  4. Caetano, R., Clark, C. L., & Tam, T. (1998). Alcohol consumption among racial/ethnic minorities: theory and research. Alcohol Research and Health, 22, 233–241.Google Scholar
  5. Carey, K. B., Scott-Sheldon, L. J., Elliott, J. C., Garey, L., & Carey, M. P. (2012). Face-to-face versus computer-delivered alcohol interventions for college drinkers: A meta-analytic review, 1998 to 2010. Clinical Psychology Review, 32, 690–703.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 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.Google Scholar
  7. Coons, C. J., Howard-Hamilton, M., & Waryold, D. (1995). College sports and fan aggression: Implications for residence hall discipline. Journal of College Student Development, 36, 587–593.Google Scholar
  8. Cunningham, J. A., Kypri, K., & McCambridge, J. (2011). The use of emerging technologies in alcohol treatment. Alcohol Research and Health, 33, 320–326.PubMedGoogle Scholar
  9. Del Boca, F. K., & Darkes, J. (2003). The validity of self-reports of alcohol consumption: State of the science and challenges for research. Addiction, 98, 1–12.CrossRefGoogle Scholar
  10. Doumas, D. M., McKinley, L. L., & Book, P. (2009). Evaluation of two web-based alcohol interventions for mandated college students. Journal of Substance Abuse Treatment, 36, 65–74.CrossRefPubMedGoogle Scholar
  11. Fournier, D. A., Skaug, H. J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M. N., … & Sibert, J. (2012). AD model builder: Using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization Methods and Software, 27, 233–249.Google Scholar
  12. Glassman, T., Werch, C. E., Jobli, E., & Bian, H. (2007). Alcohol-related fan behavior on college football game day. Journal of American College Health, 56, 255–260.CrossRefPubMedGoogle Scholar
  13. Hustad, J. T., Mastroleo, N. R., Urwin, R., Zeman, S., LaSalle, L., & Borsari, B. (2014). Tailgating and pregaming by college students with alcohol offenses: Patterns of alcohol use and beliefs. Substance Use & Misuse, 49, 1928–1933.CrossRefGoogle Scholar
  14. Kahler, C. W., Strong, D. R., & Read, J. P. (2005). Toward efficient and comprehensive measurement of the alcohol problems continuum in college students: The brief young adult alcohol consequences questionnaire. Alcoholism: Clinical and Experimental Research, 29, 1180–1189.CrossRefGoogle Scholar
  15. Kahler, C. W., Hustad, J., Barnett, N. P., Strong, D. R., & Borsari, B. (2008). Validation of the 30-day version of the Brief Young Adult Alcohol Consequences Questionnaire for use in longitudinal studies. Journal of Studies on Alcohol and Drugs, 69, 611–615.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Larimer, M. E., Lee, C. M., Kilmer, J. R., Fabiano, P. M., Stark, C. B., Geisner, I. M., & … Neighbors, C. (2007). Personalized mailed feedback for college drinking prevention: A randomized clinical trial. Journal of Consulting and Clinical Psychology, 75, 285–293.Google Scholar
  17. Larimer, M. E., Neighbors, C., LaBrie, J. W., Atkins, D. C., Lewis, M. A., Lee, C. M., … & Hodge, K. (2011). Descriptive drinking norms: For whom does reference group matter? Journal of Studies on Alcohol and Drugs, 72, 833–843.Google Scholar
  18. Lee, C. M., Neighbors, C., Lewis, M. A., Kaysen, D., Mittmann, A., Geisner, I. M., & … Larimer, M. E. (2014). Randomized controlled trial of a Spring Break intervention to reduce high-risk drinking. Journal of Consulting and Clinical Psychology, 82, 189–201.Google Scholar
  19. Leffingwell, T. R., Cooney, N. J., Murphy, J. G., Luczak, S., Rosen, G., Dougherty, D. M., & Barnett, N. P. (2013). Continuous objective monitoring of alcohol use: 21st century measurement using transdermal sensors. Alcoholism, Clinical and Experimental Research, 37, 16–22. Scholar
  20. Lewis, M. A., & Neighbors, C. (2007). Optimizing personalized normative feedback: the use of gender-specific referents. Journal of Studies on Alcohol and Drugs, 68, 228–237.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Martens, M. P., Kilmer, J. R., Beck, N. C., & Zamboanga, B. L. (2010). The efficacy of a targeted personalized feedback intervention among intercollegiate athletes: A randomized controlled trial. Psychology of Addictive Behaviors, 24, 660–669.CrossRefPubMedGoogle Scholar
  22. Matthews, D. B., & Miller, W. R. (1979). Estimating blood alcohol concentration: Two computer programs and their applications in therapy and research. Addictive Behaviors, 4, 55–60.CrossRefPubMedGoogle Scholar
  23. Moser, K., Pearson, M. R., Hustad, J. T., & Borsari, B. (2014). Drinking games, tailgating, and pregaming: Precollege predictors of risky college drinking. The American Journal of Drug and Alcohol Abuse, 40, 367–373.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Muench, F. (2014). The promises and pitfalls of digital technology in its application to alcohol treatment. Alcohol Research: Current Reviews, 36, 131–142.Google Scholar
  25. Mulia, N., Karriker-Jaffe, K. J., Witbrodt, J., Bond, J., Williams, E., & Zemore, S. E. (2017). Racial/ethnic differences in 30-year trajectories of heavy drinking in a nationally representative US sample. Drug and Alcohol Dependence, 170, 133–141.CrossRefPubMedGoogle Scholar
  26. Neal, D. J., & Fromme, K. (2007). Event level covariation of alcohol intoxication and behavioral risks during the first year of college. Journal of Consulting and Clinical Psychology, 75, 294–306.CrossRefPubMedGoogle Scholar
  27. Neighbors, C., Oster-Aaland, L., Bergstrom, R. L., & Lewis, M. A. (2006a). Event- and context- specific normative misperceptions and high risk drinking: 21st birthday celebrations and football tailgating. Journal of Studies on Alcohol, 67, 282–289.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Neighbors, C., Dillard, A. J., Lewis, M. A., Bergstrom, R. L., & Neil, T. A. (2006b). Normative misperceptions and temporal precedence of perceived norms and drinking. Journal of Studies on Alcohol, 67, 290–299.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Neighbors, C., Walters, S. T., Lee, C. M., Vader, A. M., Vehige, T., Szigethy, T., & DeJong, W. (2007). Event-specific prevention: Addressing college student drinking during known windows of risk. Addictive Behaviors, 32, 2667–2680.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Neighbors, C., Atkins, D. C., Lewis, M. A., Lee, C. M., Kaysen, D., Mittmann, A., & … Rodriguez, L. M. (2011). Event-specific drinking among college students. Psychology of Addictive Behaviors, 25, 702–707.
  31. Neighbors, C., Foster, D., Fossos, N., & Lewis, M. A. (2012a). Windows of risk: Event and contexts associated with extreme drinking. In C. Correia, J. Murphy, & N. Barnett (Eds.), College student alcohol abuse: A guide to assessment, intervention and prevention. Hoboken: John Wiley & Sons, Inc.Google Scholar
  32. Neighbors, C., Lee, C. M., Atkins, D. C., Lewis, M. A., Kaysen, D., Mittmann, A., Fossos, N., Geisner, I. M., Zheng, C., & Larimer, M. E. (2012b). A randomized controlled trial of event specific prevention strategies for reducing problematic drinking associated with 21st birthday celebrations. Journal of Consulting and Clinical Psychology, 80, 850–862.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Patrick, K., Griswold, W. G., Raab, F., & Intille, S. S. (2008). Health and the mobile phone. American Journal of Preventive Medicine, 35, 177–181.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Patrick, M. E., Lee, C. M., & Neighbors, C. (2014). Web-based intervention to change perceived norms of college student alcohol use and sexual behavior on spring break. Addictive Behaviors, 39, 600–606. Scholar
  35. R Development Core Team. (2008). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing ISBN 3-900051-07-0.Google Scholar
  36. Read, J. P., Wardell, J. D., & Bachrach, R. L. (2013). Drinking consequence types in the first college semester differentially predict drinking the following year. Addictive Behaviors, 38, 1464–1471. Scholar
  37. Rees, D. I., & Schnepel, K. T. (2009). College football games and crime. Journal of Sports Economics, 10, 68–87.CrossRefGoogle Scholar
  38. Rutledge, P. C., Park, A., & Sher, K. J. (2008). 21st birthday drinking: Extremely extreme. Journal of Consulting and Clinical Psychology, 76, 511–516.Google Scholar
  39. Skaug, H., Fournier, D., Nielsen, A., Magnusson, A., & Bolker, B. (2013). Generalized linear mixed models using AD model builder. R package version 0.7, 7.Google Scholar
  40. Suffoletto, B., Kristan, J., Chung, T., Jeong, K., Fabio, A., Monti, P., & Clark, D. B. (2015). An interactive text message intervention to reduce binge drinking in young adults: A randomized controlled trial with 9-month outcomes. PloS One, 10.Google Scholar
  41. Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston: Pearson.Google Scholar
  42. Tingley, D., Yamamoto, T., Hirose, K., Keele, L., & Imai, K. (2014). Mediation: R package for causal mediation analysis. Journal of Statistical Software, 59, 1–38.CrossRefGoogle Scholar
  43. Vicary, J. R., & Karshin, C. M. (2002). College alcohol use: A review of the problems, issues, and prevention approaches. The Journal of Primary Prevention, 22, 299–331.CrossRefGoogle Scholar
  44. 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.CrossRefPubMedGoogle Scholar
  45. Whittaker, R., Borland, R., Bullen, C., Lin, R. B., McRobbie, H., & Rodgers, A. (2009). Mobile phone-based interventions for smoking cessation. Cochrane Database System.Google Scholar
  46. Witkiewitz, K., Desai, S. A., Bowen, S., Leigh, B. C., Kirouac, M., & Larimer, M. E. (2014). Development and evaluation of a mobile intervention for heavy drinking and smoking among college students. Psychology of Addictive Behaviors, 28, 639–650.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Zapolski, T. C., Pedersen, S. L., McCarthy, D. M., & Smith, G. T. (2014). Less drinking, yet more problems: Understanding African American drinking and related problems. Psychological Bulletin, 140, 188–233.CrossRefPubMedGoogle Scholar

Copyright information

© Society for Prevention Research 2018

Authors and Affiliations

  1. 1.Department of Psychiatry and Behavioral SciencesUniversity of WashingtonSeattleUSA
  2. 2.Department of Educational, School, and Counseling PsychologyUniversity of MissouriColumbiaUSA
  3. 3.Department of Psychological SciencesUniversity of MissouriColumbiaUSA

Personalised recommendations