Implementing Ethics for a Mobile App Deployment

This paper discusses the ethical dimensions of a research project in which we deployed a personal tracking app on the Apple App Store and collected data from users with whom we had little or no direct contact. We describe the in-app functionality we created for supporting consent and withdrawal, our approach to privacy, our navigation of a formal ethical review, and navigation of the Apple approval process. We highlight two key issues for deployment-based research. Firstly, that it involves addressing multiple, sometimes conflicting ethical principles and guidelines. Secondly, that research ethics are not readily separable from design, but the two are enmeshed. As such, we argue that in-action and situational perspectives on research ethics are relevant to deployment-based research, even where the technology is relatively mundane. We also argue that it is desirable to produce and share relevant design knowledge and embed in-action and situational approaches in design activities

Using degraded music quality to encourage a health improving walking pace : BeatClearWalker

Meeting the target of 8000 steps/day, as recommended by many national governments and health authorities, can provide considerable physical and mental health benefits and is seen as a key target for reducing obesity levels and improving public health. However, to optimize the health benefits, walking should be performed at a “moderate” intensity. While there are numerous mobile fitness applications that monitor distance walked, none directly support walking at this cadence nor has there been any research into live feedback for walking cadence. We present a smartphone fitness application to help users learn how to walk at a moderate cadence and maintain that cadence. We apply real-time audio effects that diminish the audio quality of music when the target walking cadence is not being reached. This provides an immersive and intuitive application that can easily be integrated into everyday life as allows users to walk while listening to their own music and encourages eyes-free interaction. In this paper, we introduce our approach, design, initial lab evaluation and a controlled outdoor study. Results show that using music degradation decreases the number of below-cadence steps, that users felt they worked harder with our player and would use it while exercise walking

Using degraded music quality to encourage a health improving walking pace : BeatClearWalker

Meeting the target of 8000 steps/day, as recommended by many national governments and health authorities, can provide considerable physical and mental health benefits and is seen as a key target for reducing obesity levels and improving public health. However, to optimize the health benefits, walking should be performed at a "moderate" intensity. While there are numerous mobile fitness applications that monitor distance walked, none directly support walking at this cadence nor has there been any research into live feedback for walking cadence. We present a smartphone fitness application to help users learn how to walk at a moderate cadence and maintain that cadence. We apply real-time audio effects that diminish the audio quality of music when the target walking cadence is not being reached. This provides an immersive and intuitive application that can easily be integrated into everyday life as allows users to walk while listening to their own music and encourages eyes-free interaction. In this paper, we introduce our approach, design, initial lab evaluation and a controlled outdoor study. Results show that using music degradation decreases the number of below-cadence steps, that users felt they worked harder with our player and would use it while exercise walking

Children's Health: Evaluating the Impact of Digital Technology. Final Report for Sunderland City Council.

EXECUTIVE SUMMARY The Children’s Health project sponsored by the City of Sunderland Digital Challenge project examined the impact of providing health-focused digital technologies to children aged 11-15 years, in terms of their usage and requirements of such technologies, and their subsequent behavioural changes. The empirical study ran with three groups of six children over a period of seven weeks for each group. A console-based exercise game and an exercise-focused social website were used in the study and the focus was on opportunistic (unstructured/unplanned) exercise. The emergent findings are: • Data collected about physical activity must be more extensive than simple step counts. • Data collection technologies for activities must be ubiquitous but invisible. • Social interaction via technology is expected; positive messages reinforcing attainments of goals are valued; negative feedback is seen as demotivating. • participants were very open to sharing information (privacy was not a concern). • Authority figures have a significant impact on restricting adolescents’ use of technologies. This document reports the how the study was conducted, analyses the findings and draws conclusions from these regarding how to use digital technologies to improve and/or maintain the physical activity levels of children throughout their adolescence and on into adulthood. The appendices provide the detailed (anonymised) data collected during the study and the background literature review

Wellness Routines with Wearable Activity Trackers: A Systematic Review

With the advent of technological advancements, different types of wearables are built and introduced to individuals to better quantify and monitor their lifestyles. This helps in creating awareness among individuals about their health and wellness, motivating them to make healthy changes in their lifestyles. The young-elderly (aged 60–75) age group constitutes an important segment of the society, which is growing worldwide, but with little or no attention of researchers and practitioners. Wearables offer lots of open research avenues; with a proper integration with new and existing mobile applications it will be possible to build systematic and smart life routines for users. Designing wearables for young elderly is an interesting design challenge with its own set of requirements. We have carried out a systematic review of current literature to get an understanding of how wearables can support wellness routines for individuals. The purpose is to study the current state of art in creating wellness routines with wearables as technological interventions. In doing so we present a categorization of existing approaches and a summarization of different design recommendations that serve different design goals. The review also suggests a clear lack of efforts to address the needs of the young-elderly. We suggest an introduction of action design research to encourage users to be part of a co-creation process that would help to lower adoption barriers for the young elderly

Contradictions in digital health engagement:An activity tracker’s ambiguous influence on vulnerable young adults’ engagement in own health

Objective Activity trackers are designed to support individuals in monitoring and increasing their physical activity. The use of activity trackers among individuals diagnosed with depression and anxiety has not yet been examined. This pilot study investigates how this target group engages with an activity tracker during a 10-week health intervention aimed to increase their physical activity level and improve their physical and mental health. Methods Two groups of 11 young adults (aged 18–29 years) diagnosed with depression or anxiety participated in the digital health intervention. The study used mixed methods to investigate the research question. Quantitative health data were used to assess the intervention’s influence on the participants’ health and qualitative data provided insights into the participants’ digital health experience. Results The study demonstrated an ambiguous influence from the use of an activity tracker with positive physical and mental health results, but a fading and even negative digital health engagement and counterproductive competition. Conclusions The ambiguous results identify a need for (1) developing strategies for health professionals to provide supervised use of activity trackers and support the target groups’ abilities to convert health information about physical activity into positive health strategies, and (2) designing alternatives for health promoting IT targeted users who face challenges and need motivation beyond self-tracking and competition. </jats:sec

The Role of Fitbits in Corporate Wellness Programs: Does Step Count Matter?

Striving to promote the health and well-being of their workforce and decrease insurance expenditures, many organizations are incorporating wearable fitness trackers into their corporate wellness programs. Research suggests that these devices encourage individuals to make healthier choices; however, little is known about the drivers and impact of fitness trackers on employee health and well-being. We seek to fill this knowledge gap by investigating the following research questions: (1) what is the impact of wearable fitness device use on employee health and well-being? (2) what is the impact of wearable fitness device use on step count? Our results indicate that extended use has a positive impact on employee well-being and step count, which fully mediates the relationship between feature use and health. These findings have implications for research into wearable fitness trackers and, more specifically, for research on the uses of wearable fitness devices in corporate wellness programs

Evaluating the impact of physical activity apps and wearables: interdisciplinary review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

Self-tracking modes: reflexive self-monitoring and data practices

The concept of ‘self-tracking’ (also referred to as life-logging, the quantified self, personal analytics and personal informatics) has recently begun to emerge in discussions of ways in which people can voluntarily monitor and record specific features of their lives, often using digital technologies. There is evidence that the personal data that are derived from individuals engaging in such reflexive self-monitoring are now beginning to be used by actors, agencies and organisations beyond the personal and privatised realm. Self-tracking rationales and sites are proliferating as part of a ‘function creep’ of the technology and ethos of self-tracking. The detail offered by these data on individuals and the growing commodification and commercial value of digital data have led government, managerial and commercial enterprises to explore ways of appropriating self-tracking for their own purposes. In some contexts people are encouraged, ‘nudged’, obliged or coerced into using digital devices to produce personal data which are then used by others. This paper examines these issues, outlining five modes of self-tracking that have emerged: private, communal, pushed, imposed and exploited. The analysis draws upon theoretical perspectives on concepts of selfhood, citizenship, biopolitics and data practices and assemblages in discussing the wider sociocultural implications of the emergence and development of these modes of self-tracking

Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Study Protocol of the Ally Micro-Randomized Trial

Background: Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Using machine learning techniques to infer each user’s context from smartphone sensor data is a promising approach to further enhance tailoring. Objective: The primary objective of this study is to quantify main effects, interactions, and moderators of 3 intervention components of a smartphone-based intervention for physical activity. The secondary objective is the exploration of participants’ states of receptivity, that is, situations in which participants are more likely to react to intervention notifications through collection of smartphone sensor data. Methods: In 2017, we developed the Assistant to Lift your Level of activitY (Ally), a chatbot-based mobile health intervention for increasing physical activity that utilizes incentives, planning, and self-monitoring prompts to help participants meet personalized step goals. We used a microrandomized trial design to meet the study objectives. Insurees of a large Swiss insurance company were invited to use the Ally app over a 12-day baseline and a 6-week intervention period. Upon enrollment, participants were randomly allocated to either a financial incentive, a charity incentive, or a no incentive condition. Over the course of the intervention period, participants were repeatedly randomized on a daily basis to either receive prompts that support self-monitoring or not and on a weekly basis to receive 1 of 2 planning interventions or no planning. Participants completed a Web-based questionnaire at baseline and postintervention follow-up. Results: Data collection was completed in January 2018. In total, 274 insurees (mean age 41.73 years; 57.7% [158/274] female) enrolled in the study and installed the Ally app on their smartphones. Main reasons for declining participation were having an incompatible smartphone (37/191; 19.4%) and collection of sensor data (35/191; 18.3%). Step data are available for 227 (82.8%, 227/274) participants, and smartphone sensor data are available for 247 (90.1%. 247/274) participants