Automating Peer Learning to Reduce Alcohol Use and Related Deviant Behavior in Secondary School
Automating Peer Learning to Reduce Alcohol Use and Related Deviant Behavior in Secondary School
Deviant peer affiliation is one of the most important predictors of alcohol use in adolescence. These affiliations arise when socially marginalized youth self-aggregate and reinforce alcohol use and other deviant activity (i.e., "deviant peer clustering"). Existing efficacious school-based prevention programs generally have small effects and can be difficult to disseminate with fidelity and challenging to sustain due to complex designs and significant time-and-money expenditures required for materials and training. Existing school-based prevention programs have not provided compelling value to schools, which has limited their dissemination. The investigators found significantly lower rates of deviant peer affiliation and alcohol/tobacco use and moderate-to-strong suppressive effects on bullying, victimization, stress, and emotional problems, and strong positive effects on student engagement, achievement, and social-emotional skills in peer-learning intervention schools compared to control schools. However, teachers in intervention schools faced challenges implementing peer learning, including: (1) design fidelity: ensuring that peer learning provided the most positive student experience by including all the essential design elements; and, (2) instructional support: managing the flow and timing of the activities to complete the lesson on time while dealing with unexpected disruptions. Investigators developed an initial version of a mobile software application (PeerLearning.net) that provided easy-to-use organizational templates with workflow support that teachers used to automate the design and delivery of peer learning lessons. In this cluster randomized trial of the app, the investigators will use a sample of middle and high schools and conduct pre/post student assessments of peer relations, alcohol/drug use, antisocial/prosocial behavior, and social-emotional skills. They will also collect information on stress, bullying/victimization and related outcomes, including sleep quality and mental health. Investigators will also collect data on the frequency of lesson delivery with the app by teacher and school to assess dosage, which will be incorporated into our analyses. The investigators hypothesize that use of PeerLearning.net will have significant suppressive effects on alcohol use and related outcomes (i.e., tobacco/marijuana use, antisocial behavior, bullying, emotional problems) and promote increased levels of social-emotional skills and prosocial behavior. The investigators hypothesize that these results will be moderated by dosage (i.e., use of the app), such that greater usage yields larger effects.
Schools (N = 12) will be randomly assigned to intervention or waitlist control conditions, and data will be collected immediately in the fall (i.e., baseline measure) and in the spring, approximately 6 months later (i.e., post-treatment assessment). Overall, the investigators will have two assessment points. Data will be collected from teachers and students via on-line surveys (i.e., Qualtrics) and through observations; see below on the Measures. Intervention schools will receive training and access to the PeerLearning.net app immediately, whereas control schools will receive access in the spring after the second wave of data collection is completed.
The investigators hypothesize that usage of PeerLearning.net will promote increasing levels of prosocial behavior and have a significant suppressive effects on alcohol use and related outcomes (i.e., tobacco/marijuana use, antisocial behavior, bullying/victimization, mental health problems) and salutary effects on social-emotional skills, peer relations, and sleep quality. The investigators hypothesize that there will be effects of dosage (i.e., usage of the app). Finally, the investigators will examine differences in program effects by sex (gender) and ethnicity, which the investigators expect to be small or nonexistent.
Participants will include both teachers and students at 12 middle and high schools, cluster randomized to intervention vs. waitlist control. Teachers will use PeerLearning.net to design and deliver small-group peer learning lessons during the school year. The investigators will not exclude any participant based upon race/ethnicity, gender, or disability. Participating schools, teachers, and students will be rewarded.
Inclusion Criteria:
Exclusion Criteria: