Alcohol is the most prevalent psychoactive substance used by students in post-secondary education and is associated with a variety of short- and long-term negative consequences. Although many students experience negative consequences, some continue to drink at problematic levels. The present proposal extends a program of research focused on understanding daily process models of alcohol expectancies, alcohol use, and related consequences by developing a mobile phone intervention for community college and 4-year college students. Our prior work (R01AA016979, PI Lee) examined how expectancies influence drinking and consequences later that day; how learning might take place when examining the influence of consequences on future expectations of alcohol's effects; and for whom these relationships exist. We collected data three times a day for 2 weeks in each of four quarters across 1 year. We found important links between daily alcohol expectancies and next-day high-risk alcohol use and between daily consequences and next-day expectancies. Overall, findings have important implications for timing of intervention delivery to target daily expectancies. The present study tests an intervention based on these findings, with real-time feedback using individuals' daily expectancies, use, and consequences, and builds on two NIAAA-endorsed strategies for addressing high-risk college student drinking: challenging alcohol-related expectancies, traditionally done through in-vivo experimental designs, and electronic personalized feedback. Limitations of in-vivo alcohol expectancy challenge (AEC) interventions include low utilization due to lack of feasibility for widespread implementation. Therefore, the present competing renewal application will design a mobile phone application (app) for data collection and intervention. This electronic, mobile AEC (mAEC) intervention is designed to challenge daily- level alcohol expectancies and reduce high-risk drinking and negative consequences. We will incorporate methods and results from our prior R01 to develop mAEC, which will be implemented daily across 14 days with follow-ups through 12 months. The mAEC will provide personalized, daily feedback based on students' drinking intentions, alcohol expectancies, and consequences. A sample of 450 high-risk college drinkers from both community and 4-year colleges will be recruited and randomized to one of two conditions to compare the efficacy of the mAEC and an assessment-only control (AOC) condition.
Specific aims are to examine (1) the efficacy of the mAEC intervention relative to AOC, (2) global expectancies as mediators of intervention efficacy, and (3) whether the intervention weakens the daily link between positive expectancies and consequences and strengthens the daily link between negative expectancies and consequences. The mAEC intervention has the potential to have a major impact on the field because it will be scalable and easily disseminated. The development of an empirically-supported intervention that targets individuals' daily alcohol expectancies and drinking intentions may prove particularly efficacious.

Public Health Relevance

Prior research has documented that alcohol expectancies are powerful predictors of alcohol use and related consequences. The proposed study will develop and test a new personalized mobile phone application (app) intervention to provide real-time feedback about expected and actual consequences of drinking. If efficacious, the app would be the first intervention to target alcohol expectancies that would lend itself to widespread dissemination.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Research Project (R01)
Project #
5R01AA016979-08
Application #
9994144
Study Section
Interventions to Prevent and Treat Addictions Study Section (IPTA)
Program Officer
Ruffin, Beverly
Project Start
2010-04-01
Project End
2022-08-31
Budget Start
2020-09-01
Budget End
2021-08-31
Support Year
8
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Washington
Department
Psychiatry
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Luk, Jeremy W; Fairlie, Anne M; Lee, Christine M (2018) Daily-level Associations between Negative Mood, Perceived Stress, and College Drinking: Do Associations Differ by Sex and Fraternity/Sorority Affiliation? Subst Use Misuse 53:989-997
Lee, Christine M; Rhew, Isaac C; Patrick, Megan E et al. (2018) Learning From Experience? The Influence of Positive and Negative Alcohol-Related Consequences on Next-Day Alcohol Expectancies and Use Among College Drinkers. J Stud Alcohol Drugs 79:465-473
Lee, Christine M; Cronce, Jessica M; Baldwin, Scott A et al. (2017) Psychometric analysis and validity of the daily alcohol-related consequences and evaluations measure for young adults. Psychol Assess 29:253-263
Fairlie, Anne M; Ramirez, Jason J; Patrick, Megan E et al. (2016) When do college students have less favorable views of drinking? Evaluations of alcohol experiences and positive and negative consequences. Psychol Addict Behav 30:555-565
Patrick, Megan E; Cronce, Jessica M; Fairlie, Anne M et al. (2016) Day-to-day variations in high-intensity drinking, expectancies, and positive and negative alcohol-related consequences. Addict Behav 58:110-6
Tanana, Michael; Hallgren, Kevin A; Imel, Zac E et al. (2016) A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing. J Subst Abuse Treat 65:43-50
Lee, Christine M; Atkins, David C; Cronce, Jessica M et al. (2015) A daily measure of positive and negative alcohol expectancies and evaluations: documenting a two-factor structure and within- and between-person variability. J Stud Alcohol Drugs 76:326-35
Lord, Sarah Peregrine; Can, Do?an; Yi, Michael et al. (2015) Advancing methods for reliably assessing motivational interviewing fidelity using the motivational interviewing skills code. J Subst Abuse Treat 49:50-7
Cronce, Jessica M; Bittinger, Joyce N; Liu, Junny et al. (2014) Electronic Feedback in College Student Drinking Prevention and Intervention. Alcohol Res 36:47-62
Atkins, David C; Steyvers, Mark; Imel, Zac E et al. (2014) Scaling up the evaluation of psychotherapy: evaluating motivational interviewing fidelity via statistical text classification. Implement Sci 9:49

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