Bettina B Hoeppner1, Melissa R Schick2, Lourah M Kelly3, Susanne S Hoeppner4, Brandon Bergman5, John F Kelly5. 1. Recovery Research Institute and Center for Addiction Medicine, Massachusetts General Hospital, Harvard Medical School, United States; Psychiatry Department, Massachusetts General Hospital, Harvard Medical School, United States. Electronic address: bhoeppner@mgh.harvard.edu. 2. Recovery Research Institute and Center for Addiction Medicine, Massachusetts General Hospital, Harvard Medical School, United States. 3. Recovery Research Institute and Center for Addiction Medicine, Massachusetts General Hospital, Harvard Medical School, United States; Suffolk University, Psychology Department, 73 Tremont Street, 8th Floor, MA 02114, United States. 4. Psychiatry Department, Massachusetts General Hospital, Harvard Medical School, United States. 5. Recovery Research Institute and Center for Addiction Medicine, Massachusetts General Hospital, Harvard Medical School, United States; Psychiatry Department, Massachusetts General Hospital, Harvard Medical School, United States.
Abstract
INTRODUCTION: Smartphone apps are emerging as a promising tool to support recovery from and prevention of problematic alcohol use, yet it is unclear what type of apps are currently available in the public domain, and to what degree these apps use interactive tailoring or other dynamic features to meet users' specific needs. METHODS: We conducted a content analysis of Android apps for managing drinking available on Google Play (n=266), downloaded between November 21, 2014 and June 25, 2015. We recorded app popularity (>10,000 downloads) and user-rated quality (number of stars) from Google Play, and coded the apps on three domains (basic descriptors, functionality, use of dynamic features). RESULTS: In total, the reviewed 266 apps were downloaded at least 2,793,567 times altogether. The most common types of app were BAC calculators (37%), information provision apps (37%), tracking calendars (24%), and motivational tools (21%). Most apps were free (65%) or low in cost (mean=$3.76; SD=$5.80). Many apps provided at least some level of tailored feedback (60%), but the extent of tailoring was limited. Use of other dynamic features (i.e., push notifications, passive data collection) was largely absent. Univariate models predicting app popularity (i.e., >10,000 downloads vs. not) and user-rated quality (i.e., star rating) indicated that tailoring was positively related to popularity (OR=2.41 [1.30-4.46]), and the existence of time-based tailoring (e.g., tracking) was related to quality (b=0.48 [0.19-0.77]). CONCLUSIONS: These apps have a wide public health reach with >2.7 million total combined downloads to date. A wide variety of apps exist, allowing persons interested in using apps to help them manage their drinking to choose from numerous types of supports. Tailoring, while related favorably to an app's popularity and user-rated quality, is limited in publicly available apps.
INTRODUCTION: Smartphone apps are emerging as a promising tool to support recovery from and prevention of problematic alcohol use, yet it is unclear what type of apps are currently available in the public domain, and to what degree these apps use interactive tailoring or other dynamic features to meet users' specific needs. METHODS: We conducted a content analysis of Android apps for managing drinking available on Google Play (n=266), downloaded between November 21, 2014 and June 25, 2015. We recorded app popularity (>10,000 downloads) and user-rated quality (number of stars) from Google Play, and coded the apps on three domains (basic descriptors, functionality, use of dynamic features). RESULTS: In total, the reviewed 266 apps were downloaded at least 2,793,567 times altogether. The most common types of app were BAC calculators (37%), information provision apps (37%), tracking calendars (24%), and motivational tools (21%). Most apps were free (65%) or low in cost (mean=$3.76; SD=$5.80). Many apps provided at least some level of tailored feedback (60%), but the extent of tailoring was limited. Use of other dynamic features (i.e., push notifications, passive data collection) was largely absent. Univariate models predicting app popularity (i.e., >10,000 downloads vs. not) and user-rated quality (i.e., star rating) indicated that tailoring was positively related to popularity (OR=2.41 [1.30-4.46]), and the existence of time-based tailoring (e.g., tracking) was related to quality (b=0.48 [0.19-0.77]). CONCLUSIONS: These apps have a wide public health reach with >2.7 million total combined downloads to date. A wide variety of apps exist, allowing persons interested in using apps to help them manage their drinking to choose from numerous types of supports. Tailoring, while related favorably to an app's popularity and user-rated quality, is limited in publicly available apps.
Authors: Garrett I Ash; Ralitza Gueorguieva; Nancy P Barnett; Wuyi Wang; David S Robledo; Kelly S DeMartini; Brian Pittman; Nancy S Redeker; Stephanie S O'Malley; Lisa M Fucito Journal: Alcohol Clin Exp Res Date: 2022-05-14 Impact factor: 3.928
Authors: Paolo Deluca; Simon Coulton; Mohammed Fasihul Alam; Sadie Boniface; David Cohen; Kim Donoghue; Eilish Gilvarry; Eileen Kaner; Ian Maconochie; Paul McArdle; Ruth McGovern; Dorothy Newbury-Birch; Robert Patton; Tracy Pellatt-Higgins; Ceri Phillips; Thomas Phillips; Rhys D Pockett; Ian Russell; John Strang; Colin Drummond Journal: Int J Drug Policy Date: 2021-01-22