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Tracing the Potential Flow of Consumer Data: A Network Analysis of Prominent Health and Fitness Apps.

Quinn GrundyFabian P HeldLisa A Bero
Published in: Journal of medical Internet research (2017)
This cross-sectional analysis highlights the possibilities for user data collection and potential paths that data is able to travel among a sample of prominent health and fitness apps. While individual apps may not collect personally identifiable information, app families and the partners with which they share data may be able to aggregate consumer data, thus achieving a much more comprehensive picture of the individual consumer. The organizations behind the centrally connected app families represent diverse industries, including apparel manufacturers and social media platforms that are not traditionally involved in health or fitness. This analysis highlights the potential for anticipated and voluntary but also possibly unanticipated and involuntary sharing of user data, validating privacy and security concerns in mobile health.
Keyphrases
  • health information
  • social media
  • electronic health record
  • big data
  • healthcare
  • public health
  • body composition
  • mental health
  • network analysis
  • machine learning
  • climate change
  • human immunodeficiency virus