MHealth and social mediation: Mobile support among stigmatized people living with HIV and substance use disorder. (April 2023)

• Record Type: Journal Article
• Authors: Yang, Fan ("Ellie"); Shah, Dhavan V; Tahk, Alexander; Vjorn, Olivia; Dietz, Sarah; Pe-Romashko, Klaren; Bailey, Erika; Gicquelais, Rachel E; Hwang, Juwon; Gustafson, David H; Westergaard, Ryan
• Is Part Of: New media & society. Volume 25:Number 4(2023)
• Page Start: 702
• Page End: 731
• Publication Date: 2023-04
• Subjects: Digital phenotyping -- expression effects -- mHealth apps -- mobile support -- online communities -- social mediation -- substance use disorders; Mass media -- Social aspects -- Periodicals; Mass media and culture -- Periodicals; Information technology -- Social aspects -- Periodicals; Internet -- Social aspects -- Periodicals; 302.2305
• DOI: 10.1177/14614448231158653
• Languages: English
• ISSNs: 1461-4448

Abstract

The social mediation role of mobile technology is typified by mHealth apps designed to connect individuals to others and support substance use disorder (SUD) recovery. In this study, we examined the use and utility of one such app designed to support people living with HIV (PLWH) and SUD. Drawing on Ling's emphasis on reciprocity and micro-coordination in mobile telephony as a social mediation technology, we gathered digital trace data from app logs to construct two metrics, initiation (i.e. whether a particular feature is engaged on a given day) and intensity (i.e. degree of involvement in the activity when engaged on that day), at three levels of communication—networked (one-to-many), dyadic (one-to-one), and intraindividual (self-to-self). We consider these system features alongside use of information resources, games and relaxation links, a meeting and events calendar, and support tools to address use urges. We found few differences in patterns of use by race, sex, and age, though African Americans were less likely to engage in intraindividual expression, whereas women and older users were more likely to make use of this feature. The initiation and intensity of network and dyadic reception, as well as the intensity of network expression, predicts recovery outcomes as measured on a weekly "check-in" survey, suggesting the utility of mobile log data for digital phenotyping in mHealth. By implementing this app during the COVID-19 pandemic, the study also found the disruption caused by national lockdown was negatively related to the app use.