ArticleJMIR mHealth and uHealth2018
Developing Typologies of User Engagement With the BRANCH Alcohol-Harm Reduction Smartphone App: Qualitative Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review.Journal of medical Internet research · 2020Pooled it
- Brief report: Aging adult utilization of an mHealth intervention for problem drinking.Frontiers in public health · 2024Trial
- How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial.JMIR mHealth and uHealth · 2023Trial
- Engagement With a Web-Based Intervention to Reduce Harmful Drinking: Secondary Analysis of a Randomized Controlled Trial.Journal of medical Internet research · 2020Trial
- Engagement of Users in Digital Health Applications: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Designing mHealth Apps for Substance Use Recovery Through Real-World Co-Design and Deployment: Mixed Methods Study.JMIR mHealth and uHealth · 2026Article
- Theory-based evaluation of user participation in MedPrev, a digital preventive intervention in primary care in France.BMC primary care · 2026Article
- Enhancing care in alcohol-associated liver disease through peer support for alcohol use disorder.Hepatology communications · 2026Review
- The double-edged sword of self-tracking: investigating factors of technostress in performance-oriented cycling and triathlon.Frontiers in sports and active living · 2024Article
- Testing a Digital Health App for Patients With Alcohol-Associated Liver Disease: Mixed Methods Usability Study.JMIR formative research · 2023Article
- U.S. veterans' experiences and factors associated with use of a smartphone application to self-manage unhealthy alcohol use.Psychological services · 2023Article
- Opportunities and challenges to enhance the value and uptake of Chief Nursing Informatics Officer (CNIO) Roles in Canada: A Qualitative Study.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- Using peers to increase veterans' engagement in a smartphone application for unhealthy alcohol use: A pilot study of acceptability and utility.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2021Article
- Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review.Healthcare (Basel, Switzerland) · 2021Review
- 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 · 2020Article
- Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis.JMIR mHealth and uHealth · 2020Observational
- Article
- User types, psycho-social effects and societal trends related to the use of consumer health technologies.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundUnderstanding how users engage with electronic screening and brief intervention (eSBI) is a critical research objective to improve effectiveness of app-based interventions to reduce harmful alcohol consumption. Although quantitative measures of engagement provide a strong indicator of how the user engages with an app at the group level, they do not elucidate finer-grained details of how apps function from an individual, experiential perspective and why, or how, users engage with an intervention in a particular manner.
objectiveThe aim of this study was to (1) understand why and how participants engaged with the BRANCH app, (2) explore facilitators and barriers to engagement with app features, (3) explore how the BRANCH app impacted drinking behavior, (4) use these data to identify typologies of users of the BRANCH app in terms of engagement behaviors, and (5) identify future eSBI app design implications.
methodsIn total, 20 one-to-one semistructured telephone interviews were conducted with participants recruited from a randomized controlled trial, which evaluated the effectiveness of engagement-promoting strategies in the BRANCH app targeting harmful drinking in young adults (aged 18-30 years). The topic guide explored users' current engagement levels with existing health promotion apps, their views toward the effectiveness of such apps, and what they liked and disliked about BRANCH, specifically focusing on how they engaged with the app. Framework analysis was used to develop typologies of user engagement.
resultsThe study identified 3 typologies of engagers. Trackers were defined by their motivations to use health-tracking apps to monitor and understand quantified self-data. They did not have intentions necessarily to cut down and predominantly used only the drinking diary. Cut-downers were motivated to use the app because they wanted to reduce their alcohol consumption Unlike Trackers, they did not use a range of different health apps daily, but saw the BRANCH app as an opportunity to test out a different method of trying to cut down their alcohol use. This typology used more features than Trackers, such as the goal setting function. Noncommitters were characterized as a group of users who were initially enthusiastic about using the app; however, this enthusiasm quickly waned and they gained no benefit from it.
conclusionsThis was the first study to identify typologies of user engagement with eSBI apps. Although in need of replication, it provides a first step in understanding independent categories of eSBI users, who may benefit from apps tailored to a user's typology or motivation. It also provides new evidence to suggest that apps may be used more effectively as a tool to raise awareness of drinking, instead of reducing alcohol use, and be a step in the care pathway, identifying at-risk individuals and signposting them to more intensive treatment.
trial registrationInternational Standard Randomised Controlled Trial Number ISRCTN70980706; http://www.isrctn.com /ISRCTN70980706 (Archived by WebCite at http://www.webcitation.org/73vfDXYEZ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.