JMIR Research Protocols · 2017 · 13 citations · 5 references
ComputingData ScienceHealth InformaticsConsumer Health InformaticsHealth Data InteroperabilityPhysical ActivityBehavioral Data CollectionMobile SensingPhysical Activity AssessmentSurvey ResearchWearable Health TechnologiesOnline SurveysSelf-administered QuestionnairesSelf-report Data CaptureSensor-based Data CollectionWearable Activity TrackersWearable Activity TrackingWearable Device Data CollectionWearable Technology
BACKGROUND: As technology increasingly becomes an integral part of everyday life, many individuals are choosing to use wearable technology such as activity trackers to monitor their daily physical activity and other health-related goals. Researchers would benefit from learning more about the health of these individuals remotely, without meeting face-to-face with participants and avoiding the high cost of providing consumer wearables to participants for the study duration. OBJECTIVE: The present study seeks to develop the methods to collect data remotely and establish a linkage between self-reported survey responses and consumer wearable device biometric data, ultimately producing a de-identified and linked dataset. Establishing an effective protocol will allow for future studies of large-scale deployment and participant management. METHODS: A total of 30 participants who use a Fitbit will be recruited on Mechanical Turk Prime and asked to complete a short online self-administered questionnaire. They will also be asked to connect their personal Fitbit activity tracker to an online third-party software system, called Fitabase, which will allow access to 1 month's retrospective data and 1 month's prospective data, both from the date of consent. RESULTS: The protocol will be used to create and refine methods to establish linkages between remotely sourced and de-identified survey responses on health status and consumer wearable device data. CONCLUSIONS: The refinement of the protocol will inform collection and linkage of similar datasets at scale, enabling the integration of consumer wearable device data collection in cross-sectional and prospective cohort studies.
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Michael D. Buhrmester, Tracy Kwang, Samuel D. Gosling · Perspectives on Psychological Science · 2011 · 10.1K citations
Lisa Cadmus‐Bertram, Bess H. Marcus, Ruth E. Patterson et al. · JMIR mhealth and uhealth · 2015 · 222 citations · Full text
Ulrich Ebner‐Priemer, Timothy J. Trull · European Psychologist · 2009 · 183 citations
Nursing, Psychiatry, Psychology +17