This paper is in the following e-collection/theme issue:

Text-messaging (SMS, WeChat etc)-Based Interventions (650) Mobile Health (mhealth) (2941) mHealth for Wellness, Behavior Change and Prevention (2872) Alcohol Abuse, Alcoholism Prevention and Recovery (300)

Published on in Vol 4, No 2 (2016): Apr-Jun

Optimizing a Text Message Intervention to Reduce Heavy Drinking in Young Adults: Focus Group Findings

Optimizing a Text Message Intervention to Reduce Heavy Drinking in Young Adults: Focus Group Findings

Optimizing a Text Message Intervention to Reduce Heavy Drinking in Young Adults: Focus Group Findings

Authors of this article:

Brian Suffoletto1 Author Orcid Image ;   Jeffrey Kristan1 Author Orcid Image ;   Laurel Person Mecca2 Author Orcid Image ;   Tammy Chung3 Author Orcid Image ;   Duncan B Clark3 Author Orcid Image
Article Authors Cited by (10) Tweetations (2) Metrics

Journals

  1. Bae S, Ferreira D, Suffoletto B, Puyana J, Kurtz R, Chung T, Dey A. Detecting Drinking Episodes in Young Adults Using Smartphone-based Sensors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2017;1(2):1 View
  2. Choo C, Burton A. Mobile Phone Apps for Behavioral Interventions for At-Risk Drinkers in Australia: Literature Review. JMIR mHealth and uHealth 2018;6(2):e18 View
  3. Attwood S, Parke H, Larsen J, Morton K. Using a mobile health application to reduce alcohol consumption: a mixed-methods evaluation of the drinkaware track & calculate units application. BMC Public Health 2017;17(1) View
  4. Suffoletto B, Goyal A, Puyana J, Chung T. Can an app Help Identify Psychomotor Function Impairments during Drinking Occasions in the Real World? A Mixed-Method Pilot Study. Substance Abuse 2017;38(4):438 View
  5. Chung K, Cho H, Park J. A Chatbot for Perinatal Women’s and Partners’ Obstetric and Mental Health Care: Development and Usability Evaluation Study. JMIR Medical Informatics 2021;9(3):e18607 View
  6. Bae S, Suffoletto B, Zhang T, Chung T, Ozolcer M, Islam M, Dey A. Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study. JMIR Formative Research 2023;7:e39862 View
  7. Staton C, Zadey S, O’Leary P, Phillips A, Minja L, Swahn M, Hirshon J, Boshe J, Sakita F, Vissoci J, Mmbaga B. PRACT: a pragmatic randomized adaptive clinical trial protocol to investigate a culturally adapted brief negotiational intervention for alcohol use in the emergency department in Tanzania. Trials 2022;23(1) View
  8. Suffoletto B, Chung T. Desire to get drunk partially mediates effects of a combined text message-based alcohol intervention for young adults. Drug and Alcohol Dependence 2023;246:109848 View
  9. Palacios-Delgado J, Garduño F. A mobile phone intervention to reduce heavy drinking: a preliminary analysis of anchoring heuristics. BMC Psychology 2023;11(1) View
  10. Wolfe D, Hutton B, Corace K, Chaiyakunapruk N, Ngorsuraches S, Nochaiwong S, Presseau J, Grant A, Dowson M, Palumbo A, Suschinsky K, Skidmore B, Bartram M, Garner G, DiGioacchino L, Pump A, Peters B, Konefal S, Eves A, Thavorn K. Service-level barriers to and facilitators of accessibility to treatment for problematic alcohol use: a scoping review. Frontiers in Public Health 2023;11 View