The overall objective of the proposed research is to reduce the incidence of sexually transmitted infections (STIs) among college students. We propose to accomplish this by using the innovative, engineering-inspired multiphase optimization strategy (MOST) to develop a highly effective, appealing, economical, and readily scalable internet-delivered behavioral intervention targeting the intersection of alcohol use and sexual risk behavior. The rate of STIs on college campuses is alarming: one in four college students is diagnosed with an STI at least once during their college experience. Sexual activity when drinking alcohol is highly prevalent among college students. Alcohol use is known to contribute to the sexual risk behaviors that are most responsible for the transmission of STIs, namely unprotected sex, contact with numerous partners, and hook- ups (casual sexual encounters). Few interventions have been developed that explicitly target the intersection of alcohol use and sexual risk behaviors, and none have been optimized. In order to reduce the incidence of STI transmission among this and other high-risk groups, a new approach is needed. MOST is a comprehensive methodological framework that brings the power of engineering principles to bear on optimization of behavioral interventions. MOST enables researchers to experimentally test the individual components in an intervention to determine their effectiveness, indicating which components need to be revised and re-tested. Given the high rates of alcohol use and sex among college students, the college setting provides an ideal opportunity for intervening on alcohol use and sexual risk behaviors. The proposed study will include a diverse population of college students (? 50% African American) on 4 campuses: 2 Historically Black Colleges and Universities, 1 large public university, and 1 junior college. This will increase the generalizability of our findings.
Our specific aims are to (1) develop and pilot test an initial set of online intervention components targeting the link between alcohol use and sexual risk behaviors, (2) use the MOST approach to build an optimized preventive intervention, and (3) evaluate the effectiveness of the newly optimized preventive intervention using a fully powered RCT. This work will result in a new, more potent behavioral intervention that will reduce the incidence of STIs among college students in the US, and will lay the groundwork for a new generation of highly effective STI prevention interventions aimed at other subpopulations at risk.

Public Health Relevance

Using an innovative engineering-inspired framework, this project will develop a highly effective and efficient internet-delivered behavioral intervention fo prevention of sexually transmitted infections in college students. It will target the intersection f alcohol use and sexual risk behaviors. Ultimately this will lead to a new generation of more effective, efficient, and cost-effective STI behavioral interventions, and pave the way for both highly tailored interventions to prevent STIs and new approaches to behavioral prevention of HIV.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Research Project (R01)
Project #
1R01AA022931-01A1
Application #
8885133
Study Section
Special Emphasis Panel (ZRG1-RPIA-N (09))
Program Officer
Freeman, Robert
Project Start
2015-07-06
Project End
2020-06-30
Budget Start
2015-07-06
Budget End
2016-06-30
Support Year
1
Fiscal Year
2015
Total Cost
$516,967
Indirect Cost
$76,699
Name
Pennsylvania State University
Department
Miscellaneous
Type
Schools of Allied Health Profes
DUNS #
003403953
City
University Park
State
PA
Country
United States
Zip Code
16802
Nahum-Shani, Inbal; Smith, Shawna N; Spring, Bonnie J et al. (2018) Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Ann Behav Med 52:446-462
Nahum-Shani, Inbal; Dziak, John J; Collins, Linda M (2018) Multilevel factorial designs with experiment-induced clustering. Psychol Methods 23:458-479
Piper, Megan E; Cook, Jessica W; Schlam, Tanya R et al. (2018) A Randomized Controlled Trial of an Optimized Smoking Treatment Delivered in Primary Care. Ann Behav Med 52:854-864
Baker, Timothy B; Smith, Stevens S; Bolt, Daniel M et al. (2017) Implementing Clinical Research Using Factorial Designs: A Primer. Behav Ther 48:567-580
Piper, Megan E; Cook, Jessica W; Schlam, Tanya R et al. (2017) Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action. Drug Alcohol Depend 171:50-58
Piper, Megan E; Schlam, Tanya R; Cook, Jessica W et al. (2017) Toward precision smoking cessation treatment I: Moderator results from a factorial experiment. Drug Alcohol Depend 171:59-65
Hekler, Eric B; Michie, Susan; Pavel, Misha et al. (2016) Advancing Models and Theories for Digital Behavior Change Interventions. Am J Prev Med 51:825-832
Watkins, Edward; Newbold, Alexandra; Tester-Jones, Michelle et al. (2016) Implementing multifactorial psychotherapy research in online virtual environments (IMPROVE-2): study protocol for a phase III trial of the MOST randomized component selection method for internet cognitive-behavioural therapy for depression. BMC Psychiatry 16:345