• Deborah Lupton


  1. Ablon, L., Libicki, M., & Golay, A. (2015). Markets for cybercrime tools and stolen data. Santa Monica, CA: RAND Corporation. [Google Scholar]
  2. Ebeling, M. (2016). Healthcare and big data: Digital specters and phantom objects. Houndmills: Palgrave Macmillan. [Crossref][Google Scholar]
  3. Fox, S., & Duggan, M. (2013). Tracking for health. Retrieved from [Google Scholar]
  4. Gajanayake, R., Lane, B., Iannella, R., & Sahama, T. (2013). Accountable-ehealth systems: The next step forward for privacy. Electronic Journal of Health Informatics8(2), 11. Retrieved from [Google Scholar]
  5. IMS Institute for Healthcare Informatics. (2015). Patient adoption of mHealth: Use, evidence and remaining barriers to mainstream acceptance. Parsipanny, NJ: IMS Institute for Healthcare Informatics. [Google Scholar]
  6. Lupton, D. (2013). Understanding the human machine. IEEE Technology & Society Magazine32(4), 25–30. doi: 10.1109/MTS.2013.2286431 [Crossref][Web of Science ®][Google Scholar]
  7. Lupton, D. (2015). Fabricated data bodies: Reflections on 3D printed digital body objects in medical and health domains. Social Theory & Health13(2), 99–115. doi: 10.1057/sth.2015.3 [Crossref][Web of Science ®][Google Scholar]
  8. Lupton, D. (2016a). The quantified self: A sociology of self-tracking. Cambridge: Polity Press. [Google Scholar]
  9. Lupton, D. (2016b). Critical research on self-tracking: A reading list. This Sociological Life. Retrieved from [Google Scholar]
  10. Lupton, D. (2016c). Interesting HCI research on self-tracking: A reading list. This Sociological Life. Retrieved from [Google Scholar]
  11. Lupton, D. (2016d). Living digital data research program. This Sociological Life. Retrieved from [Google Scholar]
  12. Nafus, D. (2014). Stuck data, dead data, and disloyal data: The stops and starts in making numbers into social practices. Distinktion: Scandinavian Journal of Social Theory15(2), 208–222. doi: 10.1080/1600910X.2014.920266 [Taylor & Francis Online][Google Scholar]
  13. Nafus, D. (Ed.). (2016). Quantified: Biosensing technologies in everyday life. Cambridge, MA: MIT Press. [Crossref][Google Scholar]
  14. Neff, G., & Nafus, D. (2016). Self-tracking. Cambridge, MA: MIT Press. [Crossref][Google Scholar]
  15. Pasquale, F. (2014). The dark market for personal data. The New York Times. Retrieved from [Google Scholar]
  16. Selke, S. (Ed.). (2016). Lifelogging: Digital self-tracking and lifelogging – between disruptive technology and cultural transformation. Wiesbaden: Springer VS. [Crossref][Google Scholar]
  17. Swan, M. (2012). Health 2050: The realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen. Journal of Personalized Medicine2(3), 93–118. doi: 10.3390/jpm2030093 [Crossref][PubMed][Google Scholar]
  18. Thilakanathan, D., Chen, S., Nepal, S., Calvo, R., & Alem, L. (2014). A platform for secure monitoring and sharing of generic health data in the cloud. Future Generation Computer Systems35, 102–113. doi: 10.1016/j.future.2013.09.011 [Crossref][Web of Science ®][Google Scholar]
  19. Topol, E. (2015). The patient will see you now: The future of medicine is in your hands. New York: Basic Books. [Google Scholar]
  20. Wicks, P., & Chiauzzi, E. (2015). ‘Trust but verify’ – five approaches to ensure safe medical apps. BMC Medicine13(205). Retrieved from [Crossref][Google Scholar]
The SELF Institute