Heavy alcohol use among community college students is a serious problem, leaving students vulnerable to social and health impairment, physical or sexual assault, unintentional injuries, and death. However, there have been limited efforts to research and treat community college students, despite these students comprising nearly 40% of all college students nationwide. Community college students are diverse in ethnicity, age, socioeconomic status, living situation, and employment status. Thus, successful interventions must be sufficiently flexible to apply across a diverse array of individual characteristics and needs. Unfortunately, there is evidence of great unmet need among this group;community college students drive under the influence of alcohol more frequently than students at four-year colleges, and due to lesser time spent on campus, are less available for in-person interventions coordinated at their college. The long-term objective of this research program is to address a gap in the treatment of heavy alcohol use by the community college population. As a first step toward achieving that goal, this R21 application will develop an intervention that is tailored to the needs of community college students and which uses mobile communications platforms that are already used by the vast majority of this population. Taking this approach, the intervention will be mobile, accessible wherever the user is located, and able to be tailored to individual characteristics. We will begin by presenting out initial intervention design to focus groups (4 groups of 8 heavy drinking community college students) and obtaining feedback from key informants (advisory board). We will use feedback from these groups to finalize the design and develop a working prototype. We will then pilot the intervention among heavy drinking community college students (N=10) for six weeks to test the usability and acceptability of the prototype intervention. Participants will be interviewed at the end of the program to provide feedback and evaluate their experience with the system, and content experts will again evaluate the prototype using semi-structured interviews. Finally, we will pilot the modified intervention with heaving drinking community college students (N=40) for six weeks. These participants will be randomly assigned to either the intervention program or a standard intervention (print self-help) with a contact-control. Assessments will be conducted at end-of- treatment, and at 3 and 6 months follow up. These data will be used to guide the planning of a full-scale clinical trial to test the efficacy and cost-effectiveness of the intervenion in reducing hazardous drinking among community college students.
Heavy alcohol use is a significant health problem for community college students, who comprise nearly 40% of all college students nationwide. The proposed intervention will use text messaging to provide mobile, individualized treatment for this diverse population. Effective interventions tailored to the needs of this population could have a major impact on the health of millions of Americans who are at high risk from the consequences of heavy drinking.
Sillice, Marie A; Dunsiger, Shira; Jennings, Ernestine et al. (2018) Differences in mobile phone affinity between demographic groups: implications for mobile phone delivered interventions and programs. Mhealth 4:39 |
Bock, Beth C; Thind, Herpreet; Fava, Joseph L et al. (2016) Development of the Mobile Phone Attachment Scale. Proc Annu Hawaii Int Conf Syst Sci 2016:3401-3407 |
Bock, Beth C; Barnett, Nancy P; Thind, Herpreet et al. (2016) A text message intervention for alcohol risk reduction among community college students: TMAP. Addict Behav 63:107-13 |
Bock, Beth C; Rosen, Rochelle K; Barnett, Nancy P et al. (2015) Translating Behavioral Interventions Onto mHealth Platforms: Developing Text Message Interventions for Smoking and Alcohol. JMIR Mhealth Uhealth 3:e22 |
Bock, Beth; Rosen, Rochelle; Thind, Herpreet et al. (2014) Building an Evidence Base Using Qualitative Data for mHealth Development. Proc Annu Hawaii Int Conf Syst Sci 2014:2655-2664 |
Brigham, Janet; Schooley, Benjamin (2014) Introduction to Minitrack Evidence-Based mHealth Design and Analysis. Proc Annu Hawaii Int Conf Syst Sci 2014:2644 |