Does Dynamic Tailoring of A Narrative-Driven Exergame Result in Higher User Engagement among Adolescents? Results from A Cluster-Randomized Controlled Trial.

Physical activity interventions for youth are direly needed given low adherence to physical activity guidelines, but many interventions suffer from low user engagement. Exergames that require bodily movement while played may provide an engaging form of physical activity intervention but are not perceived as engaging to all. This study aimed to evaluate whether dynamic tailoring in a narrative-driven mobile exergame for adolescents played in leisure settings, can create higher user engagement compared to a non-tailored exergame. A cluster-randomized controlled trial assessed differences in user engagement between a dynamically tailored (based on an accelerometer sensor integrated in a T-shirt) and non-tailored condition. In total, 94 participants (M age = 14.61 ± 1.93; 35% female) participated and were assigned to one of the two conditions. User engagement was measured via a survey and game metric data. User engagement was low in both conditions. Narrative sensation was higher in the dynamically tailored condition, but the non-tailored condition showed longer play-time. User suggestions to create a more appealing game included simple and more colorful graphics, avoiding technical problems, more variety and shorter missions and multiplayer options. Less cumbersome or more attractive sensing options than the smart T-shirt may offer a more engaging solution, to be tested in future research.

Data Mining in the Development of Mobile Health Apps: Assessing In-App Navigation Through Markov Chain Analysis.

BACKGROUND: Mobile apps generate vast amounts of user data. In the mobile health (mHealth) domain, researchers are increasingly discovering the opportunities of log data to assess the usage of their mobile apps. To date, however, the analysis of these data are often limited to descriptive statistics. Using data mining techniques, log data can offer significantly deeper insights. OBJECTIVE: The purpose of this study was to assess how Markov Chain and sequence clustering analysis can be used to find meaningful usage patterns of mHealth apps. METHODS: Using the data of a 25-day field trial (n=22) of the Start2Cycle app, an app developed to encourage recreational cycling in adults, a transition matrix between the different pages of the app was composed. From this matrix, a Markov Chain was constructed, enabling intuitive user behavior analysis. RESULTS: Through visual inspection of the transitions, 3 types of app use could be distinguished (route tracking, gamification, and bug reporting). Markov Chain-based sequence clustering was subsequently used to demonstrate how clusters of session types can otherwise be obtained. CONCLUSIONS: Using Markov Chains to assess in-app navigation presents a sound method to evaluate use of mHealth interventions. The insights can be used to evaluate app use and improve user experience.

Citizen Science to Communicate about Public Health Messages: The Reach of a Playful Online Survey on Sitting Time and Physical Activity.

There is a lack of research on how to communicate public health guidelines. Citizen science (CS) has been an effective way to involve the public in research. This study analyses the reach of a well-established CS experiment, launched during an annual national science event, to understand if it could be used as communication strategy for public health issues. A short playful online survey contained tailored health-related messages associated to an "animal totem" profile, based on the combination of sitting and physical activity levels (koala: high sitting, low activity; gorilla: high sitting, high activity; zebra: low sitting, low activity; bee: low sitting, high activity). Tweets, radio interviews, radio and online advertisements, press articles, and a press conference were used to promote the CS experiment. Google Analytics and Facebook Graph API (application programming interface) (use and spread of experiment) and descriptive statistics (attributes of adults completing the experiment) were used. A total of 6,246 adults completed the experiment, with a peak of views (n = 5,103) and completions (n = 1,209) a couple of days before the event. Completers were mostly female (65.8%), on average 37.5 years old, and had a healthy body mass index (23.8 kg/m2). Nearly half (46.4%) had the most beneficial profile ("bee"), 26.5% had the least healthy profile ("koala"). CS as part of a national science event is a good platform for health communication as 1 in 1,000 Flemish adults were reached. However, those completing the experiment were not representative of the general Flemish adult population and reported to be more physically active. Abbreviations: API: application programming interface; BMI: body mass index; CVD: cardiovascular disease; METs: metabolic equivalents.

Mobile Exergaming in Adolescents' Everyday Life-Contextual Design of Where, When, with Whom, and How: The SmartLife Case.

Exergames, more specifically console-based exergames, are generally enjoyed by adolescents and known to increase physical activity. Nevertheless, they have a reduced usage over time and demonstrate little effectiveness over the long term. In order to increase playing time, mobile exergames may increase potential playing time, but need to be engaging and integrated in everyday life. The goal of the present study was to examine the context of gameplay for mobile exergaming in adolescents’ everyday life to inform game design and the integration of gameplay into everyday life. Eight focus groups were conducted with 49 Flemish adolescents (11 to 17 years of age). The focus groups were audiotaped, transcribed, and analyzed by means of thematic analysis via Nvivo 11 software (QSR International Pty Ltd., Victoria, Australia). The adolescents indicated leisure time and travel time to and from school as suitable timeframes for playing a mobile exergame. Outdoor gameplay should be restricted to the personal living environment of adolescents. Besides outdoor locations, the game should also be adaptable to at-home activities. Activities could vary from running outside to fitness exercises inside. Furthermore, the social context of the game was important, e.g., playing in teams or meeting at (virtual) meeting points. Physical activity tracking via smart clothing was identified as a motivator for gameplay. By means of this study, game developers may be better equipped to develop mobile exergames that embed gameplay in adolescents’ everyday life.

Computer-Mediated Social Support for Physical Activity: A Content Analysis.

PURPOSE: Online fitness communities are a recent phenomenon experiencing growing user bases. They can be considered as online social networks in which recording, monitoring, and sharing of physical activity (PA) are the most prevalent practices. They have added a new dimension to the social experience of PA in which online peers function as virtual PA partners or supporters. However, research into seeking and receiving computer-mediated social support for PA is scarce. Our aim was to study to what extent using online fitness communities and sharing physical activities with online social networks results in receiving various types of online social support. METHOD: Two databases, one containing physical activities logged with Strava and one containing physical activities logged with RunKeeper and shared on Twitter, were investigated for occurrence and type of social support, by means of a deductive content analysis. RESULTS: Results indicate that social support delivered through Twitter is not particularly extensive. On Strava, social support is significantly more prevalent. Especially esteem support, expressed as compliments for the accomplishment of an activity, is provided on both Strava and Twitter. CONCLUSION: The results demonstrate that social media have potential as a platform used for providing social support for PA, but differences among various social network sites can be substantial. Especially esteem support can be expected, in contrast to online health communities, where information support is more common.