Quantified Self and Apple's ResearchKit
Ernesto Ramirez
March 9, 2015
Apple’s announcement of ResearchKit is strong evidence that Quantified Self practices are emerging as a major influence on medical research and other forms of knowledge making.
Apple talked about how their new effort focused on opening up health research is designed to combat five main current issues:
- Limited Participation
- Small sample sizes limit our understanding of diseases
- Reliance on subjective data
- Infrequent data provide only snapshots through time
- One-way communication from researcher to participant (and only at the end of the study, if at all)
Furthermore, the design of ResearchKit allows the participant to decide how data is shared. Apple will not see the data. Participants are allowed to be involved in the data collection in real-time, using the data they’re collecting to understand and inform their own health improvement plans.
In light of today’s announcement we wanted to highlight some of our favorite and most powerful examples of taking the research process into one’s own hands, making their own knowledge through thoughtful data collection and reflection. We invite you watch what’s possible now, and imagine with us what could be accomplished tomorrow.
Mark Drangsholt: Deciphering My Brain Fog
Lindsay Meyer on Tracking Hearing Loss
Thomas Christiansen on Learning from 60,000 Observations
Nan Shellabarger: 26 Years of Weight Tracking
Rob Rothfarb on Tracking My Blood
Last year we gather a fantastic group of researchers, toolmakers, and science leadership at the 2014 Quantified Self Public Health Symposium to discuss how personal data can impact personal and public health. That meeting culminated in a great report that touches on many of the aspects discussed today regarding ResearchKit. We invite you to download, read, and share that report. For a more nuanced look into how ResearchKit may impact the research community, we’re highlighting four great talks from the the meeting.
Susannah Fox shares research from the Pew Internet and Life Project and describes the challenges ahead for promoting self-tracking.
Margaret McKenna explores the issues, challenges, and ideas large scale self-tracking applications have in mind when they consider working with the research community.
Jason Bobe talks about the lessons learned from involving research participants in the data ownership and discovery process.
Doug Kanter describes what he’s learned from tracking and visualizing his diabetes data.
If you’re interested in how ResearchKit will be affecting self-tracking, personal data, and access to information, research and knowledge making, then stay tuned to our Access Channel here on QuantifiedSelf.com and on Medium.
We are sure to have many great talks and sessions that focus on ResearchKit at our QS15 Conference and Actrivate Exposition. We invite you to join us.
We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com and @quantifiedself.