Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study

By L. Dennison, Leanne G. Morrison, G. Conway, Lucy Yardley. Journal of Medical Internet Research, 2013

917 citations recorded by the source corpus.

Background There is increasing interest from academics and clinicians in harnessing smartphone applications (apps) as a means of delivering behavioral interventions for health. Despite the growing availability of a range of health-related apps on the market, academic research on the development and evaluation of such apps is in the relatively early stages. A few existing studies have explored the views of various populations on using mobile phones for health-related issues and some studies are beginning to report user feedback on specific apps. However, there remains little in depth research on users’ (and potential users’) experiences and views on a wide range of features and technologies that apps are, or will soon be, capable of. In particular, research on young adults is lacking, which is an unfortunate omission considering that this group comprises of a good number of mobile technology adoptors. Objective The current study sought to explore young adults’ perspectives on apps related to health behavior change. It sought their experiences and views of features that might support health behavior change and issues that contribute to interest in and willingness to use such apps. Methods Four focus groups were conducted with 19 students and staff at a University in the United Kingdom. Participants included 13 females and 6 males with a mean age of 23.79 (SD 7.89). The focus group discussions centred on participants’ experiences of using smartphone apps to support a healthy lifestyle, and their interest in and feelings about features and capabilities of such apps. The focus groups were recorded, transcribed, and analyzed using inductive thematic analysis. Results Study findings suggested that young, currently healthy adults have some interest in apps that attempt to support health-related behavior change. Accuracy and legitimacy, security, effort required, and immediate effects on mood emerged as important influences on app usage. The ability to record and track behavior and goals and the ability to acquire advice and information “on the go” were valued. Context-sensing capabilities and social media features tended to be considered unnecessary and off-putting. Conclusions This study provided insight into the opportunities and challenges involved in delivering health-related behavioral interventions through smartphone apps. The findings suggested a number of valued features and characteristics that app developers may wish to consider when creating health behavior apps. Findings also highlighted several major challenges that appeared to need further consideration and research to ensure the development of effective and well-accepted behavior change apps.

Subfields: Applied Psychology, General Health Professions

View Paper: https://www.semanticscholar.org/paper/25beecb98860be1af4e3cfcb95b32e0265465864

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Citations in the corpus

Gamification: What It Is and Why It Matters to Digital Health Behavior Change Developers (2013, neutral): “Mobile Phone Technology and Health Behavior Change Mobile phone technology has recently become an area of focus for disseminating health behavior change interventions [1-3].”
A qualitative study of user perceptions of mobile health apps (2016, background): “Many of the themes we identified were consistent with Dennison et al. ’ s findings [16], including smartphones as valuable information sources, tracking progress and raising awareness, aversion of sharing information, privacy and security concerns, skepticism over context sensing, necessity for…”
Health promotion in the digital era: a critical commentary. (2015, background): “The discourse referring to 'behavioural interventions' using smartphones, wearable technologies or social media (Dennison et al., 2013) in a range of sites, including professional health promotion, persuasive computing, health insurance and corporate wellness programs tends to conform to…”
Smartphones and Health Promotion: A Review of the Evidence (2013, background): “Finally, Dennison et al. organized a focus group in order to explore young adults ’ perspectives on apps related to health behavior change, finding among young and healthy subjects a very high level of interest in apps supporting health-related behavior change [43].”
Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review (2016, neutral): “[60, 75] that young people value health behaviour”
The technostress trifecta ‐ techno eustress, techno distress and design: Theoretical directions and an agenda for research (2019, background): “It is important to keep in mind however that such persuasion itself should not happen in an obtrusive, undesired, and consequently stressful manner (Dennison et al. 2013; Kuonanoja et al. 2015).”
Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature (2015, background): “…regarding health apps has focused on preventing and managing chronic disease [6,7], monitoring health behaviors and vitals [8], content analyses of health and fitness apps [9-11], app acceptability and utility [12-15], and qualitative studies of user experience and desired functions [4,16,17].”
The SAMS: Smartphone Addiction Management System and Verification (2013, methodology): “Two specific applications, ‘ A-CHESS ’ and ‘ Netaddiction ’ [16], need to be mentioned here because we used them as references for designing the SAMS.”
New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research (2016, background): “There is also a lack of long-term adherence data, with most studies ending after 6 weeks, and consequently little known on how patients learn to use or accept new apps in studies with longer follow-up times [54].”
Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions (2014, neutral): “The loss of patient and data confidentiality, and privacy remains a concern for smartphone applications [20] and the broader field of telepsychiatry itself [21].”
IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior (2016, background): “Qualitative investigations have also shown that users may be more interested in technologies that frame behaviors as actions to increase as opposed to decrease (eg, increasing the number of days per week free of sugar-sweetened beverages vs cutting back on sugar-sweetened beverages) [51].”
Young people’s uses of wearable healthy lifestyle technologies; surveillance, self-surveillance and resistance (2019, background): “Despite opportunities, potential negative impacts, and possibilities that self-tracking will be imposed, there is a lack of in-depth empirical evidence on young people’s experiences and uses of healthy lifestyle technologies (Dennison et al., 2013; Rich & Miah, 2017).”
Just a Fad? Gamification in Health and Fitness Apps (2014, background): “Mobile Phone Technology and Health Behavior Change Mobile phone technology has recently become an area of focus for disseminating health behavior change interventions [1-3].”
The Person-Based Approach to Intervention Development: Application to Digital Health-Related Behavior Change Interventions (2015, background): “In focus groups we ran with young adults to explore their experiences and views of health apps, we discovered that users can be extremely annoyed by email prompts or push notifications and may actually feel harassed by them [15].”
Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies (2018, methodology): “Qualitative methodologies are commonly employed in the digital health setting to inform the development of interventions (ie, usability testing) and as an evaluation measure (eg, [25-29]).”
Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue using a Fitness App: A Structural Equation Modeling Approach (2018, background): “Indeed, as Eysenbach (2013) posits, mobile apps ’ appeal and usefulness depend on users ’ intentions and motivation, thereby implying that users ’ estimation of a fitness app ’ s usefulness is anchored on the reasons people have for using an app and the ways they use it.”