PROJECT SUMMARY The overall goal of this application is to support and facilitate the necessary training to develop an independent research career focused on examining online and offline social contexts that influence adolescent substance use (SU). In the long-term, the applicant seeks to develop a program of research focused on the use of digital technologies to examine social risk factors that lead to alcohol and drug use among adolescents and to deliver prevention programming. Through the training goals, guided mentorship, and complementary experiences, the proposed project will strategically advance the applicant's knowledge of social media and SU research. The applicant will also be trained in state-of-the-art quantitative methodologies to enhance the design, conduct, and analysis of big data to improve our current understanding of socialization effects on adolescent SU. The prevention of alcohol and drug use among adolescents remains a critical area for research, as experimentation with alcohol and drug use can lead to long-term negative consequences. In fact, 9 out of 10 people that experience SU problems began using before the age of 18 (CASAColumbia, 2011). While initiation of SU typically occurs during the teenage years, adolescents are also spending a substantial amount of time using social media. Adolescents use social media as a way to connect with a social network, as well as view and display SU behaviors. However, research evaluating the impact of social media on adolescent SU has been understudied, and the available research has several methodological limitations. Namely, prior work has primarily focused on college samples, as well as a less popular social media platform among adolescents (i.e., Facebook). Furthermore, prior work has used self-report data or human coding to assess online SU content. The proposed study seeks to advance the knowledge regarding the role of social media, specifically exposure to SU content, and user-generated e-cigarette content, in the escalation of alcohol and drug use among adolescents. The proposed project at the center of this training fellowship includes two aims that propose secondary data analyses, and the collection of original data. Aim 1 of the proposed project (n = 243) will use secondary data analyses to determine whether SU attitudes, subjective norms, and perceived behavioral control mediate the prospective association between exposure to SU-related content posted by peers and influential figures on offline SU behaviors. Aim 2 of the proposed project (n = 200) will prospectively examine the association between online user-generated e-cigarette content on Instagram and offline e-cigarette use using a novel methodological approach. Machine learning algorithms will be developed to detect e-cigarette content on Instagram profiles, and will be compared to self-report data to assess whether the strength of this association varies based on approach. This project will increase knowledge of a...