mHealth Intervention to Prevent College Students Hazardous Drinking for College Students: A Randomized Trial

Background: Heavy alcohol use is a major public health concern, costing the United States 249 billion dollars in 2010, causing over 88,000 deaths annually, and contributing to both short- and long-term health risks such as injuries and cancer (Centers for Disease Control and Prevention [CDC], 2018). The consequences of risky alcohol use for young adults is especially pertinent as alcohol consumption and alcohol-related risks peak between the ages of 18 to 25 (Berman et al., 2016). Individuals aged 18 to 25 engage in higher rates of binge drinking (i.e., five or more drinks per drinking occasion for men, four or more for women) and heavy alcohol use (i.e., binge drinking on five or more days in one month) than other age groups (Substance Abuse and Mental Health Services Administration [SAMHSA], 2017) Most of the students who reported on the amount of alcohol consumed the last time they partied reported drinking four or fewer drinks (63.3%); however, 11.5%, 9.0%, and 28.2% report drinking five, six, or seven or more drinks during that drinking occasion, respectively. Mandated college students are at even higher risk since they are individuals who have received a disciplinary sanction from the university due to their misuse of alcohol (i.e., underage drinking). Mandated college students have been found to differ from a voluntary group of college students, in that they often report heavier drinking and more drinking consequences (Carey et al., 2016; Logan et al., 2015; Terlecki et al., 2015). To address drinking on college campuses, a range of interventions has been used to target those engaged in risky drinking (Carey et al., 2016). Although traditional interventions targeting alcohol use are in-person, the benefits of mobile-based interventions are generating preliminary support. The applicability of mobile phone applications could be even more salient in young adults as they are prevalent consumers of technology (Oosterveen et al., 2017). Tebb and colleagues (2016) note that interventions that incorporate theoretical support are associated with a greater proportion of positive effects for alcohol reduction. mHealth applications have been shown to be successful in the delivery of health information and interventions. Thus, we decided to develop a smartphone application to reach college students in an attempt to reduce risky alcohol use. Features are easy to use and have interactive components including text messages which incorporate both Motivational Interviewing (MI; Miller & Rollnick, 2013) and Ecological Momentary Interventions (EMI; Heron & Smyth, 2010). We conducted a Randomized Controlled Trial (RCT) to test the efficacy of the smartphone intervention with college students.

Objectives: The aim of the present study was to examine the efficacy of an app based intervention designed to reduce risky drinking behaviors in college students. To accomplish this aim we conducted preliminary testing of an innovative smartphone (SP) application (or “app”) intervention with voluntary and mandated college students. In both mandated and voluntary groups, the participants used the app for 6 weeks with the mandated group being randomized to compare delivery of pBMI+SP with a BMI delivered in person. For the mandated students we hypothesized that the app based intervention would be at least as effective as BMI delivered in-person. The voluntary groups compared the pBMI+SP with a control assessment only group. For this voluntary group we hypothesized that the app based group would have a greater reduction in drinking related outcomes relative to the control assessment only group. We used data from two independent trials to evaluate the efficacy of an app-based brief motivational intervention with mandated and voluntary college students for prevention of risky drinking. More specifically, we compared the app-based intervention with the efficacious BMI with participants comprised of mandated (Study 1) and voluntary (Study 2) college students. Finally we compared the mandated and voluntary groups to determine if there were any significant differences in alcohol-use and related consequences at baseline and post intervention. To test the efficacy of an app-based intervention (using motivational interviewing and ecological momentary interventions) compared with an in-person brief motivational intervention (BMI) targeting risky alcohol use in college students.

Methods: We conducted two independent studies (Study 1 & 2) simultaneously (N = 379). Study 1 included a randomized controlled trial with mandated students, randomized to either an in-person BMI (n = 70, 42 men) or an app-based intervention (n = 71, 42 men). Study 2 included voluntary students who participated in the control group (n = 157, 42 men) or the app-based intervention (n = 81, 32 men). We collected data at a large, public university in the Southeastern U.S. from 9/1/2016 – 6/30/2018. We collected demographics and drinking-related outcomes using the Alcohol Use Disorders Identification Test (AUDIT); the Protective Behaviors Strategies Scale (PBSS); the Young Adult Alcohol Consequences Questionnaire (YAACQ); the Readiness to Change Questionnaire (RCQ); and the Daily Drinking Questionnaire (DDQ). We used Wilcoxon rank sum test (baseline data; pre-post alcohol-related changes) and Pearson’s Chi-squared test (baseline categorical data) for analysis.

Results: At baseline the mandated groups were very similar in their drinking levels at the risky or hazardous range (AUDIT). Although at baseline the pBMI+SP mandated group had more drinking related consequences, both groups had no significant changes in the number of consequences experienced over time. As expected, both mandated groups were employing strategies to control when drinking (PBSS). The mandated groups AUDIT, PBSS and YACCQ score did not change significantly between baseline and 6 weeks (Table 2). However while the peak BAC increased slightly for the in-person mandated group it decreased significantly in the pBMI+SP group (p-value=0.002). As we hypothesized there was no significant difference in alcohol use and alcohol-related consequences shown between the mandated groups between baseline and 6 weeks (AUDIT, YACCQ). This hypothesis was supported suggesting that the pBMI+SP app intervention was at least as effective as BMI delivered in-person. Participants differed on first drinking age (Study 1 & 2) and gender (Study 2). Study 1 participants differed on alcohol-related consequences at baseline and on peak BAC (baseline to 6-weeks: no change [in-person], reduction [app-based]). In Study 2, the control group had no changes from baseline to 6-weeks, whereas the app-based group had significant reductions in their AUDIT, PBSS, and YAACQ scores.

Conclusions/Importance: Widespread implementation of in-person, evidence-based interventions in the substance abuse field has been slow. This is due, in part, to feasibility issues in training staff, providing in-person services, and funding such interventions. Therefore, we created the pBMI+SP app to take advantage of students’ smartphones as a platform for delivering a real-time alcohol intervention for college students with high-risk drinking behaviors. This study increases our knowledge of the efficacy of a mHealth intervention. Our findings are promising with support that the mHealth pBMI+SP is effective with mandated students. Also testing with the voluntary groups was promising with the app-based group decreasing drinking and alcohol-related consequences relative to the control group. Particularly of interest to nurse practitioners and school health nurses since mHealth interventions have the potential to be effective interventions to address risky drinking among students. Adoption, implementation, and sustainability of alcohol interventions on college campuses have significant implications for the future. Future testing with this mHealth smartphone approach is needed to further assess reach, adoptability, portability and sustainability than current in-person approaches.