Poor air quality is a growing global health concern that impacts millions of people worldwide. Although we are beginning to understand the health impacts of air pollution, it remains a challenge to provide people with the information they need to be able to make health-conscious choices. The CitiSense system gives individuals the realtime tools they need to be able to identify when and where they are exposed to poor air. We present the results of a qualitative study regarding a 4-week "in the wild" deployment of the CitiSense air-quality sensor and system. We focus on how the 16 participants responded to their new-found information about their environment, how they shared information, and what kinds of actions were enabled by having access to real-time air-quality data. Quantitative data gathered through the course of the study frames participant responses by showing what levels of pollution were experienced and what activities heightened exposure. We found that CitiSense's real-time graphical displays and everywhere monitoring provided a critical bridge between data and experience, enabling sophisticated in-the-world sensemaking and sharing with those nearby. This in turn affected behavior and attitudes, leading to shifts in how users reasoned about their world, and how they assessed their personal choices and impact.
Cardiovascular disease remains the leading cause of death and disease worldwide. As demands on an already resource-constrained healthcare system intensify, disease prevention in the future will likely depend on out-of-office monitoring of cardiovascular risk factors. Mobile health tracking devices that can track blood pressure and heart rate, in addition to new cardiac vital signs, such as physical activity level and pulse wave velocity (PWV), offer a promising solution. An initial barrier is the development of accurate and easily-scalable platforms. In this study, we made a customized smartphone app and used mobile health devices to track PWV, blood pressure, heart rate, physical activity, sleep duration, and multiple lifestyle risk factors in ≈250 adults for 17 continual weeks. Eligible participants were identified by a company database and then were consented and enrolled using only a smartphone app, without any special training given. Study participants reported high overall satisfaction, and 73% of participants were able to measure blood pressure and PWV, <1 hour apart, for at least 14 of 17 weeks. The study population's blood pressure, PWV, heart rate, activity levels, sleep duration, and the interrelationships among these measurements were found to closely match either population averages or values obtained from studies performed in a controlled setting. As a proof-of-concept, we demonstrated the accuracy and ease, as well as many challenges, of using mHealth technology to accurately track PWV and new cardiovascular vital signs at home.
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BackgroundThe advent of digital technology has enabled individuals to track meaningful biometric data about themselves. This novel capability has spurred nontraditional health care organizations to develop systems that aid users in managing their health. One of the most prolific systems is Walgreens Balance Rewards for healthy choices (BRhc) program, an incentivized, Web-based self-monitoring program.ObjectiveThis study was performed to evaluate health data self-tracking characteristics of individuals enrolled in the Walgreens’ BRhc program, including the impact of manual versus automatic data entries through a supported device or apps.MethodsWe obtained activity tracking data from a total of 455,341 BRhc users during 2014. Upon identifying users with sufficient follow-up data, we explored temporal trends in user participation.ResultsThirty-four percent of users quit participating after a single entry of an activity. Among users who tracked at least two activities on different dates, the median length of participating was 8 weeks, with an average of 5.8 activities entered per week. Furthermore, users who participated for at least twenty weeks (28.3% of users; 33,078/116,621) consistently entered 8 to 9 activities per week. The majority of users (77%; 243,774/315,744) recorded activities through manual data entry alone. However, individuals who entered activities automatically through supported devices or apps participated roughly four times longer than their manual activity-entering counterparts (average 20 and 5 weeks, respectively; P<.001).ConclusionsThis study provides insights into the utilization patterns of individuals participating in an incentivized, Web-based self-monitoring program. Our results suggest automated health tracking could significantly improve long-term health engagement.
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