National Institute on Drug Abuse – Center for Technology and Behavioral Health P30 Pilot Core
2016 – 2017
Sunny Jung Kim, PhD
Other Project Staff
Lisa A. Marsch, PhD; Alan J. Budney, PhD; Amarendra Das, MD, PhD; Alistair J. O’Malley, PhD; Andrea L. Meier, MS, LADC, LCMHC; David MacKinnon, PhD
Addiction recovery support is a prevalent social media phenomenon exponentially spreading through networks of social media users with substance use problems. Communication features afforded on social media (e.g., share, like, comment) can provide considerable social support for recovery and promote health motivation for people with substance use disorders (SUDs). User-generated social media content and network ties among people with SUDs offer unprecedented opportunities for observing the dynamics in recovery processes at scale in a naturalistic manner, and examining the effects of those communications on psychological and behavioral changes in recovery processes (e.g., relapses and withdrawal symptoms).
Throughout two phases of multidisciplinary studies, the team will examine four primary dimensions: 1) the characteristics of users engaged in recovery support communications, 2) the characteristics of recovery support communications, 3) the social-psychological predictors/mechanisms of recovery support communications, and 4) the recovery outcomes of social media-based recovery support. A systematic review (Phase I) as well as a social media Big Data and survey-based typology (Phase II) with these four core dimensions will provide a novel, scientific foundation for harnessing social media as an observational tool for recovery processes and/or as a platform to offer recovery support for SUDs.
Prior to Phase II, the team will also conduct a series of surveys and experiments to address ethical dilemmas and challenges in Big Data-driven social media research. The proposed research activities and the findings from this study will provide theoretical and empirical evidence in generating evidence-based research protocols, consent forms, and guidelines applicable to social media-based big data research in a sensitive domain such as drug addiction.