Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective.

Health behaviors are inextricably linked to health and well-being, yet issues such as physical inactivity and insufficient sleep remain significant global public health problems. Mobile technology-and the unprecedented scope and quantity of data it generates-has a promising but largely untapped potential to promote health behaviors at the individual and population levels. This perspective article provides multidisciplinary recommendations on the design and use of mobile technology, and the concomitant wealth of data, to promote behaviors that support overall health. Using physical activity as anexemplar health behavior, we review emerging strategies for health behavior change interventions. We describe progress on personalizing interventions to an individual and their social, cultural, and built environments, as well as on evaluating relationships between mobile technology data and health to establish evidence-based guidelines. In reviewing these strategies and highlighting directions for future research, we advance the use of theory-based, personalized, and human-centered approaches in promoting health behaviors.

Evaluating In-Car Movements in the Design of Mindful Commute Interventions: Exploratory Study.

BACKGROUND: The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. OBJECTIVE: This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. METHODS: We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breath-based) while engaged in either simple (highway) or complex (city) simulated urban driving tasks using autonomous and manual driving modes. Then, we performed a matching exercise where participants could experience vibrotactile patterns from the back of the car seat and map them to the prior movements. RESULTS: We report a summary of individual perceptions concerning different movements and vibrotactile patterns. Beside describing situations within a drive when it may be more likely to perform movement-based interventions, we also describe movements that may interfere with driving and those that may complement it well. Furthermore, we identify movements that could be conducive to a more relaxing commute and describe vibrotactile patterns that could guide such movements and exercises. We discuss implications for design such as the influence of driving modality on the adoption of movement, need for personal customization, the influence that social perception has on participants, and the potential role of prior awareness of mindful techniques in the adoption of new movement-based interventions. CONCLUSIONS: This exploratory study provides insights into which types of movements could be better suited to design mindful interventions to reduce stress for commuters, when to encourage such movements, and how best to guide them using noninvasive haptic stimuli embedded in the car seat.

Exploring the Relationship Between Attribute Discrepancy and Avatar Embodiment in Immersive Social Virtual Reality.

Social virtual reality (VR) is an emerging set of platforms where users interact while embodying avatars. Given that VR headsets track real physical movements and map them onto one's avatar body, the nature of one's digital representation is an important aspect of social VR. However, little is known about how the visual proximity of an avatar to the self shapes user experience in naturalistic, social VR environments. In this article, we use this context to explore how embodiment is influenced by the perceived differences between the physical attributes of a user and the virtual attributes of their avatar. We selected a number of attributes for this measure that have been shown to be important for customization and representation in VR. Participants created an avatar, spent time in social VR, and reported on their experience in a questionnaire. Our results demonstrate a significant negative association between attribute discrepancy and avatar embodiment, the psychological experience of one's virtual body as their own body. We discuss implications for theories of self-representation and suggest urgency on the part of games and VR designers to improve the methods of creating avatars.

Personal identifiability of user tracking data during observation of 360-degree VR video.

Virtual reality (VR) is a technology that is gaining traction in the consumer market. With it comes an unprecedented ability to track body motions. These body motions are diagnostic of personal identity, medical conditions, and mental states. Previous work has focused on the identifiability of body motions in idealized situations in which some action is chosen by the study designer. In contrast, our work tests the identifiability of users under typical VR viewing circumstances, with no specially designed identifying task. Out of a pool of 511 participants, the system identifies 95% of users correctly when trained on less than 5 min of tracking data per person. We argue these results show nonverbal data should be understood by the public and by researchers as personally identifying data.

Designing Ambient Narrative-Based Interfaces to Reflect and Motivate Physical Activity.

Numerous technologies now exist for promoting more active lifestyles. However, while quantitative data representations (e.g., charts, graphs, and statistical reports) typify most health tools, growing evidence suggests such feedback can not only fail to motivate behavior but may also harm self-integrity and fuel negative mindsets about exercise. Our research seeks to devise alternative, more qualitative schemes for encoding personal information. In particular, this paper explores the design of data-driven narratives, given the intuitive and persuasive power of stories. We present WhoIsZuki, a smartphone application that visualizes physical activities and goals as components of a multi-chapter quest, where the main character's progress is tied to the user's. We report on our design process involving online surveys, in-lab studies, and in-the-wild deployments, aimed at refining the interface and the narrative and gaining a deep understanding of people's experiences with this type of feedback. From these insights, we contribute recommendations to guide future development of narrative-based applications for motivating healthy behavior.

Using mobile & personal sensing technologies to support health behavior change in everyday life: lessons learned.

Lifestyle modification is a key facet of the prevention and management of chronic diseases. Mobile devices that people already carry provide a promising platform for facilitating these lifestyle changes. This paper describes key lessons learned from the development and evaluation of two mobile systems for encouraging physical activity. We argue that by supporting persistent cognitive activation of health goals, encouraging an extensive range of relevant healthy behaviors, focusing on long-term patterns of activity, and facilitating social support as an optional but not primary motivator, systems can be developed that effectively motivate behavior change and provide support when and where people make decisions that affect their health.

The Vocal Joystick: evaluation of voice-based cursor control techniques for assistive technology.

PURPOSE: Mouse control has become a crucial aspect of many modern day computer interactions. This poses a challenge for individuals with motor impairments or those whose use of hands is restricted due to situational constraints. We present a system called the Vocal Joystick which allows the user to continuously control the mouse cursor by varying vocal parameters such as vowel quality, loudness and pitch. METHOD: Evaluations were conducted to characterize expert performance capability of the Vocal Joystick, and to compare novice user performance and preference for the Vocal Joystick and two other existing speech based cursor control methods. RESULTS: Our results show that Fitts' law, a well adopted model of human motor performance for movement tasks, is a good predictor of the speed - accuracy tradeoff for the Vocal Joystick, and suggests that the optimal performance of the Vocal Joystick may be comparable to that of a conventional hand-operated joystick. Novice user evaluations show that the Vocal Joystick can be used by people without extensive training, and that it presents a viable alternative to existing speech-based cursor control methods. CONCLUSIONS: The Vocal Joystick, with its ease of use, minimal setup requirement, and controllability, offers promise for providing an efficient method for cursor control and other forms of continuous input for individuals with motor impairments.