An Ecological Momentary Assessment of Affect, Mental Health Symptoms, and Decisions to Drink Among First-Year College Women: A Pilot Study

  • Danica C. Slavish
  • Nichole M. Scaglione
  • Brittney A. Hultgren
  • Robert Turrisi


College women experience more consequences (e.g., blacking out, unprotected/unwanted sex) on days when they engage in their heaviest drinking. To inform prevention efforts, research is needed to understand decision-making processes that influence women’s drinking behaviors at the event level. The present study used ecological momentary assessment (EMA) methods to examine: (1) associations between positive affect (PA) and negative affect (NA) and decision-making processes on days leading up to, during, and following heavy drinking events; and (2) mental health symptoms as moderators of these associations. Female undergraduate drinkers (N = 57) completed a 14-day EMA protocol on their smartphones, which included three daily assessments of PA, NA, and willingness and intentions to drink. Trait anxiety and depressive symptoms were measured before the EMA protocol and assessed as moderators. Time-varying effect models were used to examine covariation among PA, NA, and willingness and intentions to drink on the days leading up to participants’ heaviest drinking events, the day of the event itself, and the days following the event. Results revealed PA was positively associated with willingness to drink the 2 days before, the day of, and the day after the heaviest drinking event. Similar effects were observed for PA and intentions to drink. Trait anxiety moderated the association between PA and intentions to drink. Findings underscore that positive affect may influence drinking-related decision-making processes surrounding heavy drinking events, particularly in those college women low in anxiety. Results identify potential entry points for real-time intervention efforts targeting college women during times of elevated PA.


College women Willingness and intentions to drink Affect Ecological momentary assessment Time-varying effect models 



The authors would like to thank Drs. Stephanie Lanza and Michael Cleveland for their guidance on implementing TVEM methods and feedback on early versions of this manuscript.


This work was supported by the National Institutes of Health (NIH/NIAAA F31 AA022227) and the National Science Foundation (NSF DGE1255832).

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 participants included in the study.


Any opinions, findings, and conclusions or recommendations are those of the authors and do not necessarily reflect the views of the NIH or NSF.


  1. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  2. Alati, R., Kinner, S., Najman, J. M., Fowler, G., Watt, K., & Green, D. (2004). Gender differences in the relationships between alcohol, tobacco and mental health in patients attending an emergency department. Alcohol and Alcoholism, 39, 463–469.CrossRefGoogle Scholar
  3. Anderson, N. D., Lau, M. A., Segal, Z. V., & Bishop, S. R. (2007). Mindfulness-based stress reduction and attentional control. Clinical Psychology and Psychotherapy, 14, 449.CrossRefGoogle Scholar
  4. Chaiken, S., & Trope, Y. (1999). Dual-process theories in social psychology. New York, NY: Guilford Press.Google Scholar
  5. Cludius, B., Stevens, S., Bantin, T., Gerlach, A. L., & Hermann, C. (2013). The motive to drink due to social anxiety and its relation to hazardous alcohol use. Psychology of Addictive Behaviors, 27, 806–813.CrossRefGoogle Scholar
  6. Colder, C. R., Shyhalla, K., Frndak, S., Read, J. P., Lengua, L. J., Hawk, L. W., & Wieczorek, W. F. (2017). The prospective association between internalizing symptoms and adolescent alcohol involvement and the moderating role of age and externalizing symptoms. Alcoholism: Clinical & Experimental Research, 41, 2185–2196.CrossRefGoogle Scholar
  7. Colder, C. R., Frndak, S., Lengua, L. J., Read, J. P., Hawk, L. W., & Wieczorek, W. F. (2018). Internalizing and externalizing problem behavior: A test of a latent variable interaction predicting a two-part growth model of adolescent substance use. Journal of Abnormal Child Psychology, 46, 319–330.CrossRefGoogle Scholar
  8. Conger, J. J. (1956). Reinforcement theory and the dynamics of alcoholism. Quarterly Journal of Studies on Alcohol, 17, 296–305.PubMedGoogle Scholar
  9. Cooper, M. L., Frone, M. R., Russell, M., & Mudar, P. (1995). Drinking to regulate positive and negative emotions: A motivational model of alcohol use. Journal of Personality and Social Psychology, 69, 990–1005.CrossRefGoogle Scholar
  10. Dimeff, L. A. (1999). Brief alcohol screening and intervention for college students (BASICS): A harm reduction approach. New York, NY: Guilford Press.Google Scholar
  11. Eisenberg, D., Gollust, S. E., Golberstein, E., & Hefner, J. L. (2007). Prevalence and correlates of depression, anxiety, and suicidality among university students. American Journal of Orthopsychiatry, 77, 534–542.CrossRefGoogle Scholar
  12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.Google Scholar
  13. Gerrard, M., Gibbons, F. X., Houlihan, A. E., Stock, M. L., & Pomery, E. A. (2008). A dual-process approach to health risk decision making: The prototype willingness model. Developmental Review, 28, 29–61.CrossRefGoogle Scholar
  14. Glanz, K., Rimer, B. K., & Viswanath, K. (Eds.). (2015). Health behavior: Theory, research, and practice (5th ed.). Hoboken: NJ: Jossey-Bass.Google Scholar
  15. Gottfredson, N. C., & Hussong, A. M. (2013). Drinking to dampen affect variability: Findings from a college student sample. Journal of Studies on Alcohol and Drugs, 74, 576–583.CrossRefGoogle Scholar
  16. Grant, V. V., Stewart, S. H., & Mohr, C. D. (2009). Coping-anxiety and coping-depression motives predict different daily mood-drinking relationships. Psychology of Addictive Behaviors, 23, 226–237.CrossRefGoogle Scholar
  17. Hann, D., Winter, K., & Jacobsen, P. (1999). Measurement of depressive symptoms in cancer patients: Evaluation of the Center for Epidemiological Studies Depression Scale (CES-D). Journal of Psychosomatic Research, 46, 437-443CrossRefGoogle Scholar
  18. Hultgren, B. A., Scaglione, N. M., Cleveland, M. J., & Turrisi, R. (2015). Examination of a dual-process model predicting riding with drinking drivers. Alcoholism: Clinical and Experimental Research, 39, 1075–1082.CrossRefGoogle Scholar
  19. Hussong, A. M., Hicks, R. E., Levy, S. A., & Curran, P. J. (2001). Specifying the relations between affect and heavy alcohol use among young adults. Journal of Abnormal Psychology, 110, 449–461.CrossRefGoogle Scholar
  20. Kenney, S., Abar, C. C., O’Brien, K., Clark, G., & LaBrie, J. W. (2016). Trajectories of alcohol use and consequences in college women with and without depressed mood. Addictive Behaviors, 53, 19–22.CrossRefGoogle Scholar
  21. Kuntsche, E., & Gmel, G. (2013). Alcohol consumption in late adolescence and early adulthood—Where is the problem? Swiss Medical Weekly, 143, w13826.PubMedGoogle Scholar
  22. Kuntsche, E., Nic Gabhainn, S., Roberts, C., Windlin, B., Vieno, A., Bendtsen, P., Hublet, A., Tynjälä, J., Välimaa, R., Dankulincová, Z., Aasvee, K., Demetrovics, Z., Farkas, J., van der Sluijs, W., Gaspar de Matos, M., Mazur, J., & Wicki, M. (2014). Drinking motives and links to alcohol use in 13 European countries. Journal of Studies on Alcohol and Drugs, 75, 428–437.CrossRefGoogle Scholar
  23. Larson, R. W., Moneta, G., Richards, M. H., & Wilson, S. (2002). Continuity, stability, and change in daily emotional experience across adolescence. Child Development, 73, 1151–1165.CrossRefGoogle Scholar
  24. Lewis, M., King, K., Litt, D., Swanson, A., & Lee, C. (2016). Examining daily variability in willingness to drink in relation to underage young adult alcohol use. Addictive Behaviors, 61, 62–67.CrossRefGoogle Scholar
  25. Li, R., Tan, X., Huang, L., Wagner, A. T., & Yang, J. (2012). TVEM (time-varying effect model) SAS macro suite users’ guide. University Park, PA: The Methodology Center.Google Scholar
  26. Mallett, K. A., Turrisi, R., Cleveland, M. J., Scaglione, N. M., Reavy, R., Sell, N. M., & Varvil-Weld, L. (2015). A dual-process examination of alcohol-related consequences among first-year college students. Journal of Studies on Alcohol and Drugs, 76, 862–871.CrossRefGoogle Scholar
  27. Merrill, J. E., Kenney, S. R., & Barnett, N. P. (2017). A time-varying effect model of the dynamic association between alcohol use and consequences over the first two years of college. Addictive Behaviors, 73, 57–62.CrossRefGoogle Scholar
  28. Miles Cox, W., & Klinger, E. (1988). A motivational model of alcohol use. Journal of Abnormal Psychology, 97, 168–180.CrossRefGoogle Scholar
  29. Muraven, M., Collins, R. L., Morsheimer, E. T., Shiffman, S., & Paty, J. A. (2005). The morning after: Limit violations and the self-regulation of alcohol consumption. Psychology of Addictive Behaviors, 19, 253–262.CrossRefGoogle Scholar
  30. National Institute on Alcohol Abuse and Alcoholism. (2000). Tenth special report to the U.S. In Congress on alcohol and health. Washington, DC: National Institutes of Health.Google Scholar
  31. Neal, D. J., & Fromme, K. (2007). Event-level covariation of alcohol intoxication and behavioral risk during the first year of college. Journal of Consulting & Clinical Psychology, 75, 294–306.CrossRefGoogle Scholar
  32. Neighbors, C., Lee, C. M., Lewis, M. A., Fossos, N., & Walter, T. (2009). Internet-based personalized feedback to reduce 21st-birthday drinking: A randomized controlled trial of an event-specific prevention intervention. Journal of Consulting and Clinical Psychology, 77, 51–63.CrossRefGoogle Scholar
  33. Piasecki, T. M., Cooper, M. L., Wood, P. K., Sher, K. J., Shiffman, S., & Heath, A. C. (2014). Dispositional drinking motives: Associations with appraised alcohol effects and alcohol consumption in an ecological momentary assessment investigation. Psychological Assessment, 26, 363–369.CrossRefGoogle Scholar
  34. Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.CrossRefGoogle Scholar
  35. Read, J. P., Wood, M. D., Kahler, C. W., Maddock, J. E., & Palfai, T. P. (2003). Examining the role of drinking motives in college student alcohol use and problems. Psychology of Addictive Behaviors, 17, 13–23.CrossRefGoogle Scholar
  36. Read, J. P., Beattie, M., Chamberlain, R., & Merrill, J. E. (2008). Beyond the “binge” threshold: Heavy drinking patterns and their association with alcohol involvement indices in college students. Addictive Behaviors, 33, 225–234.CrossRefGoogle Scholar
  37. Riordan, B. C., Conner, T. S., Flett, J. A., & Scarf, D. (2015). A brief orientation week ecological momentary intervention to reduce university student alcohol consumption. Journal of Studies on Alcohol and Drugs, 76, 525–529.CrossRefGoogle Scholar
  38. Rohsenow, D. J. (1982). Social anxiety, daily moods, and alcohol use over time among heavy social drinking men. Addictive Behaviors, 7, 311–315.CrossRefGoogle Scholar
  39. SAS Institute. (2008). SAS (Version 9.4). Cary, NC: SAS Institute, Inc.Google Scholar
  40. Scaglione, N. M., Turrisi, R., Mallett, K. A., Ray, A. E., Hultgren, B. A., & Cleveland, M. J. (2014). How much does one more drink matter? Examining effects of event-level alcohol use and previous sexual victimization on sex-related consequences. Journal of Studies on Alcohol and Drugs, 75, 241–248.CrossRefGoogle Scholar
  41. Scaglione, N. M., Hultgren, B. A., Reavy, R., Mallett, K. A., Turrisi, R., Cleveland, M. J., & Sell, N. M. (2015). Do students use contextual protective behaviors to reduce alcohol-related sexual risk? Examination of a dual-process decision-making model. Psychology of Addictive Behaviors, 29, 733–743.CrossRefGoogle Scholar
  42. Schwarz, R. M., Burkhart, B. R., & Green, S. B. (1982). Sensation-seeking and anxiety as factors in social drinking by men. Journal of Studies on Alcohol and Drugs, 43, 1108–1114.CrossRefGoogle Scholar
  43. Selya, A. S., Updegrove, N., Rose, J. S., Dierker, L., Tan, X., Hedeker, D., Li, R., & Mermelstein, R. J. (2015). Nicotine-dependence-varying effects of smoking events on momentary mood changes among adolescents. Addictive Behaviors, 41, 65–71.CrossRefGoogle Scholar
  44. Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32.CrossRefGoogle Scholar
  45. Spielberger, C. D., Gorsuch, R. L., Lushene, P. R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory (Form Y). Redwood City, CA: Mind Garden.Google Scholar
  46. Tan, X., Shiyko, M. P., Li, R., Li, Y., & Dierker, L. (2012). A time-varying effect model for intensive longitudinal data. Psychological Methods, 17, 61–77.CrossRefGoogle Scholar
  47. Turrisi, R., Mallett, K. A., Cleveland, M. J., Varvil-Weld, L., Abar, C., Scaglione, N., & Hultgren, B. (2013). 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.CrossRefGoogle Scholar
  48. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.CrossRefGoogle Scholar
  49. Wechsler, H., Dowdall, G. W., Davenport, A., & Rimm, E. B. (1995). A gender-specific measure of binge drinking among college students. American Journal of Public Health, 85, 982–985.CrossRefGoogle Scholar

Copyright information

© Society for Prevention Research 2018

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of North TexasDentonUSA
  2. 2.Center on Social Determinants, Risk Behaviors, and Prevention Science, RTI InternationalWashingtonUSA
  3. 3.Center for the Study of Health & Risk BehaviorsUniversity of WashingtonSeattleUSA
  4. 4.Department of Biobehavioral Health & Edna Bennett Pierce Prevention Research CenterPennsylvania State UniversityUniversity ParkUSA

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