Developing Typologies of User Engagement With the BRANCH Alcohol-Harm Reduction Smartphone App: Qualitative Study

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...

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Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis

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Engagement With a Web-Based Intervention to Reduce Harmful Drinking: Secondary Analysis of a Randomized Controlled Trial

“…Thus, we could not capture whether the individual’s usage was distributed over few or many sessions or which modules were completed. The fact that SUD did rarely correlate with any of the outcomes or user characteristics might therefore be due to different patterns of use resulting in the same amount of time spent in the intervention [ 7 , 12 ]. Because the questionnaire that we used to measure SRU has not been evaluated, its validity remains uncertain.…”

“…It has been argued that the overall inconclusive findings might be due to a lack of consensus on how to measure engagement [ 8 ] or different patterns of usage [ 7 ]. The latter claim is supported by Milward et al [ 12 ] who found that some users of a smartphone app aimed at reducing harmful drinking used it to track their alcohol consumption, while others also used its other features. Furthermore, individuals might differ with respect to the extent of intervention usage required for them to engage in behavior change [ 1 ].…”