Telemedicine Journal and e-Health · 2016 · 68 citations · 21 references
NursingHealth BehaviorHealth InformaticsConsumer Health InformaticsMobile Health InformaticsObesity PreventionMobile Health AnalyticsMobile Health ApplicationsMobile Health Data CollectionPersonalizationWearable Health TechnologiesFitness TrackingMobile Health TrackingPersonal DataPhysical Activity TrackingSelf-report Data CaptureSelf-tracking DataWearable Activity TrackersWearable Devices
INTRODUCTION: Smartphone lifestyle applications (apps) and wearable fitness-tracking devices collect a wealth of data that could provide research insights to support prevention and treatment of obesity and chronic diseases. The aim of this study was to pilot a survey to explore patterns of behavioral tracking using smartphone lifestyle apps and individuals' willingness to share their app-generated data. METHODS: A cross-sectional Web-based survey was conducted within a university setting. The 35-item survey asked participants about their self-tracking patterns; use of lifestyle apps and wearable devices; how their self-tracked health data could be useful to them; and any restrictions they would impose on sharing personal data. Responses were tabulated and analyzed for trends. RESULTS: The survey was completed by 101 participants. On average, 3.1 (standard deviation [SD] ±1.9) health and fitness apps were installed by current app users (n = 85), with MyFitnessPal, MapMyRun, Nike+, and Fitbit being most popular. Most participants were willing to share their personal health data for research (77%). Those who did not normally share their health-tracking data were more likely than sharers to be concerned about privacy (odds ratio [OR] = 5.93; 95% confidence interval [95% CI] = 2.09-16.78), as were those not identifying with the quantified-self movement compared with those who were (OR = 5.04; 95% CI = 1.64-15.50). DISCUSSION: Participants were generally willing to share personal data, thus increasing the potential for these data to inform public health research and for use in targeted personalized program and intervention development. CONCLUSIONS: Opportunities for partnerships between researchers and commercial app developers or industry could improve public health research and practice.
21
A stage-based model of personal informatics systems
Ian Li, Anind Dey, Jodi Forlizzi · 2010 · 1.1K citations
Architecture, Information Systems, Human-computer Interaction +7
Understanding quantified-selfers' practices in collecting and exploring personal data
Eun Kyoung Choe, Nicole B. Lee, Bongshin Lee et al. · 2014 · 770 citations
Michelle C. Carter, V. J. Burley, Camilla Nykjaer et al. · Journal of Medical Internet Research · 2013 · 709 citations · Full text
Jeana Frost, Michael P. Massagli · Journal of Medical Internet Research · 2008 · 550 citations · Full text