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

mHealth for Wellness, Behavior Change and Prevention (2922) Mobile Health (mhealth) (2982) Usability of Apps and User Perceptions of mHealth (993)

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

User Preferences for Content, Features, and Style for an App to Reduce Harmful Drinking in Young Adults: Analysis of User Feedback in App Stores and Focus Group Interviews

User Preferences for Content, Features, and Style for an App to Reduce Harmful Drinking in Young Adults: Analysis of User Feedback in App Stores and Focus Group Interviews

User Preferences for Content, Features, and Style for an App to Reduce Harmful Drinking in Young Adults: Analysis of User Feedback in App Stores and Focus Group Interviews

Authors of this article:

Joanna Milward1 Author Orcid Image ;   Zarnie Khadjesari1 Author Orcid Image ;   Stephanie Fincham-Campbell1 Author Orcid Image ;   Paolo Deluca1 Author Orcid Image ;   Rod Watson2 Author Orcid Image ;   Colin Drummond1 Author Orcid Image
Article Authors Cited by (53) Tweetations (29) Metrics

Journals

  1. Milward J, Deluca P, Drummond C, Watson R, Dunne J, Kimergård A. Usability Testing of the BRANCH Smartphone App Designed to Reduce Harmful Drinking in Young Adults. JMIR mHealth and uHealth 2017;5(8):e109 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
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  5. Milward J, Deluca P, Drummond C, Kimergård A. Developing Typologies of User Engagement With the BRANCH Alcohol-Harm Reduction Smartphone App: Qualitative Study. JMIR mHealth and uHealth 2018;6(12):e11692 View
  6. Bhattarai P, Newton-John T, Phillips J. Apps for pain self-management of older people’s arthritic pain, one size doesn’t fit all: A qualitative study. Archives of Gerontology and Geriatrics 2020;89:104062 View
  7. Nicholas J, Fogarty A, Boydell K, Christensen H. The Reviews Are in: A Qualitative Content Analysis of Consumer Perspectives on Apps for Bipolar Disorder. Journal of Medical Internet Research 2017;19(4):e105 View
  8. Davies E, Lonsdale A, Hennelly S, Winstock A, Foxcroft D. Personalized Digital Interventions Showed no Impact on Risky Drinking in Young Adults: A Pilot Randomized Controlled Trial. Alcohol and Alcoholism 2017;52(6):671 View
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  10. Min A, Lee D, Gao G, Jeong S, Shih P. Design and assessment of a personal breathalyzer intervention to support responsible drinking. International Journal of Human-Computer Studies 2020;137:102382 View
  11. Kuntsche E, Kuntsche S, Thrul J, Gmel G. Binge drinking: Health impact, prevalence, correlates and interventions. Psychology & Health 2017;32(8):976 View
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  14. Salgado T, Fedrigon A, Riccio Omichinski D, Meade M, Farris K. Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study. JMIR mHealth and uHealth 2018;6(5):e129 View
  15. Satre D, Ly K, Wamsley M, Curtis A, Satterfield J. A Digital Tool to Promote Alcohol and Drug Use Screening, Brief Intervention, and Referral to Treatment Skill Translation: A Mobile App Development and Randomized Controlled Trial Protocol. JMIR Research Protocols 2017;6(4):e55 View
  16. Crane D, Garnett C, Brown J, West R, Michie S. Factors Influencing Usability of a Smartphone App to Reduce Excessive Alcohol Consumption: Think Aloud and Interview Studies. Frontiers in Public Health 2017;5 View
  17. Deluca P, Coulton S, Alam M, Boniface S, Donoghue K, Gilvarry E, Kaner E, Lynch E, Maconochie I, McArdle P, McGovern R, Newbury-Birch D, Patton R, Pellatt-Higgins T, Phillips C, Phillips T, Pockett R, Russell I, Strang J, Drummond C. Screening and brief interventions for adolescent alcohol use disorders presenting through emergency departments: a research programme including two RCTs. Programme Grants for Applied Research 2020;8(2):1 View
  18. Thornton L, Kay-Lambkin F, Tebbutt B, Hanstock T, Baker A. A Mobile Phone–Based Healthy Lifestyle Monitoring Tool for People With Mental Health Problems (MyHealthPA): Development and Pilot Testing. JMIR Cardio 2018;2(2):e10228 View
  19. Aji M, Gordon C, Peters D, Bartlett D, Calvo R, Naqshbandi K, Glozier N. Exploring User Needs and Preferences for Mobile Apps for Sleep Disturbance: Mixed Methods Study. JMIR Mental Health 2019;6(5):e13895 View
  20. 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
  21. Sharpe J, Zhou Z, Escobar-Viera C, Morano J, Lucero R, Ibañez G, Hart M, Cook C, Cook R. Interest in using Mobile Technology to Help Self-Manage Alcohol use among Persons Living with the Human Immunodeficiency Virus: A Florida Cohort Cross-Sectional Study. Substance Abuse 2018;39(1):77 View
  22. Sallis A, Attwood S, Harper H, Larsen J, Berry D, Vlaev I, Sanders M, Chadborn T. A randomised trial of the effect of appearance versus health-framed messages on engagement with an online brief screening and alcohol reduction intervention. Psychology & Health 2019;34(8):922 View
  23. Hutton A, Prichard I, Whitehead D, Thomas S, Rubin M, Sloand E, Powell T, Frisch K, Newman P, Goodwin Veenema T. mHealth Interventions to Reduce Alcohol Use in Young People: A Systematic Review of the Literature. Comprehensive Child and Adolescent Nursing 2020;43(3):171 View
  24. Molina-Recio G, Molina-Luque R, Jiménez-García A, Ventura-Puertos P, Hernández-Reyes A, Romero-Saldaña M. Proposal for the User-Centered Design Approach for Health Apps Based on Successful Experiences: Integrative Review. JMIR mHealth and uHealth 2020;8(4):e14376 View
  25. Short C, DeSmet A, Woods C, Williams S, Maher C, Middelweerd A, Müller A, Wark P, Vandelanotte C, Poppe L, Hingle M, Crutzen R. Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies. Journal of Medical Internet Research 2018;20(11):e292 View
  26. Garnett C, Crane D, West R, Michie S, Brown J, Winstock A. User characteristics of a smartphone app to reduce alcohol consumption. Translational Behavioral Medicine 2017;7(4):845 View
  27. Kazemi D, Borsari B, Levine M, Li S, Shehab M, Fang F, Norona J. Effectiveness of a Theory-Based mHealth Intervention for High-Risk Drinking in College Students. Substance Use & Misuse 2020;55(10):1667 View
  28. Perski O, Baretta D, Blandford A, West R, Michie S. Engagement features judged by excessive drinkers as most important to include in smartphone applications for alcohol reduction: A mixed-methods study. DIGITAL HEALTH 2018;4 View
  29. Hoeppner B, Schick M, Kelly L, Hoeppner S, Bergman B, Kelly J. There is an app for that – Or is there? A content analysis of publicly available smartphone apps for managing alcohol use. Journal of Substance Abuse Treatment 2017;82:67 View
  30. Milward J, Drummond C, Fincham-Campbell S, Deluca P. What makes online substance-use interventions engaging? A systematic review and narrative synthesis. DIGITAL HEALTH 2018;4 View
  31. Garnett C, Crane D, West R, Brown J, Michie S. The development of Drink Less: an alcohol reduction smartphone app for excessive drinkers. Translational Behavioral Medicine 2019;9(2):296 View
  32. File D, Bőthe B, Kapitány‐Fövény M, Demetrovics Z. Efficacy of a complex smartphone application for reducing hazardous alcohol consumption: Study protocol for a randomized controlled trial with analysis of in‐app user behavior in relation to outcome. International Journal of Methods in Psychiatric Research 2020;29(4):1 View
  33. Deluca P, Coulton S, Alam M, Boniface S, Cohen D, Donoghue K, Gilvarry E, Kaner E, Maconochie I, McArdle P, McGovern R, Newbury-Birch D, Patton R, Pellatt-Higgins T, Phillips C, Phillips T, Pockett R, Russell I, Strang J, Drummond C. Brief interventions to prevent excessive alcohol use in adolescents at low-risk presenting to Emergency Departments: Three-arm, randomised trial of effectiveness and cost-effectiveness. International Journal of Drug Policy 2021;93:103113 View
  34. Meegahapola L, Gatica-Perez D. Smartphone Sensing for the Well-Being of Young Adults: A Review. IEEE Access 2021;9:3374 View
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  36. Kong M, Lee M, Kang H, Hong T. Development of a framework for evaluating the contents and usability of the building life cycle assessment tool. Renewable and Sustainable Energy Reviews 2021;150:111475 View
  37. Colonna R, Tucker P, Holmes J, Wilson J, Alvarez L. Mobile-based brief interventions targeting cannabis-impaired driving among youth: A Delphi study. Journal of Substance Abuse Treatment 2022;141:108802 View
  38. Ahmed A, Aziz S, Khalifa M, Shah U, Hassan A, Abd-Alrazaq A, Househ M. Thematic Analysis on User Reviews for Depression and Anxiety Chatbot Apps: Machine Learning Approach. JMIR Formative Research 2022;6(3):e27654 View
  39. Alhur M, Alshamari S, Oláh J, Aldreabi H. Unsupervised Machine Learning to Identify Positive and Negative Themes in Jordanian mHealth Apps. International Journal of E-Services and Mobile Applications 2022;14(1):1 View
  40. Williamson C, White K, Rona R, Simms A, Fear N, Goodwin L, Murphy D, Leightley D. Smartphone-Based Alcohol Interventions: A Systematic Review on the Role of Notifications in Changing Behaviors toward Alcohol. Substance Abuse 2022;43(1):1231 View
  41. Biviji R, Williams K, Vest J, Dixon B, Cullen T, Harle C. Consumer Perspectives on Maternal and Infant Health Apps: Qualitative Content Analysis. Journal of Medical Internet Research 2021;23(9):e27403 View
  42. Colonna R, Alvarez L. Characteristics of mobile-based brief interventions targeting substance use among youth: a rapid review. Journal of Substance Use 2023;28(3):293 View
  43. Wang S, Lee H, Choi W. A feature-oriented analysis of developers’ descriptions and user reviews of top mHealth applications for diabetes and hypertension. International Journal of Medical Informatics 2021;156:104598 View
  44. Mehra R, Pulman A, Dogan H, Murphy J, Bitters F. A Tailored mHealth App to Improve Health and Well-being Behavioral Transformation in the Police: Usability Testing via a Mixed-Methods Study Among UK Police Workers (Preprint). JMIR Human Factors 2022 View
  45. White K, Carr E, Leightley D, Matcham F, Conde P, Ranjan Y, Simblett S, Dawe-Lane E, Williams L, Henderson C, Hotopf M. Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial. JMIR mHealth and uHealth 2024;12:e44214 View
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Books/Policy Documents

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