Testing the Use of a Social Networking App for American Indians Recovering from Addiction

Nicholas Guenzel, Dennis McChargue, Hongying Dai

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Objectives: American Indians (AIs) have higher rates of addiction than most other groups. Social networking mobile apps are growing in popularity but their use has not been studied among AIs specifically. Methods: This paper describes a pilot program in which 27 AIs recovering from addiction were given access to a mobile app to support addiction recovery (Sober Grid) for up to six months. They completed a technology acceptability survey, monthly surveys of cravings, social connectedness, and quality of life, and a follow-up survey. Their use of the app was also tracked. Findings: We found that individuals in the sample often lacked initial technology access but were widely accepting and trusting of technology use in their recovery. No significant changes were noted in cravings, social connectedness, or quality of life but this was likely due to low initial cravings ratings and the small sample size. We found that the participants varied widely in the features of the app they used most (i.e. adding friends, making posts, commenting on the posts of others, etc.). Conclusions: This pilot indicates that mobile apps to support addiction recovery may be well-accepted by AI individuals. App usage data indicate that apps will be most successful in recovery support if they provide a variety of ways users can interact with others. Larger studies conducted over a longer period of time would be needed to determine how mobile apps can support addiction recovery and help prevent relapses.

Original languageEnglish (US)
Pages (from-to)492-497
Number of pages6
JournalJournal of Technology in Behavioral Science
Issue number3
StatePublished - Sep 2021


  • Addiction
  • American Indian
  • Recovery
  • mHealth

ASJC Scopus subject areas

  • Applied Psychology
  • Health(social science)
  • Human-Computer Interaction
  • Computer Science Applications


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