Azure Grant: Lessons from Blood Testers, a Participant-Led Research Project
“Small group research with participants who are very curious to learn about themselves, in combination with high-temporal resolution baseline data, is a powerful tool for learning about human physiology in the real world.” — Azure Grant
Azure introduces the QS Blood Testers project, showing data that suggests a single point measure may be inadequate for understanding cardiovascular risk. In the Blood Testers group, every participant crossed a CVD risk category by time of day in at least one lipid output. And 80% of participants crossed a risk category based on time of day when only fasting measurements were considered. Blood Testers data also showed that this lipid variability isn’t random, but is structured on the timescales of hours, days, and across the ovulatory cycle. These insights were gained using data from very high frequency measurement — sometimes as often as once per hour — and none of this could have happened without dedicated participants asking questions they cared about, with access to their own data.
Highlights from the QS Symposium 2018
Introduction to the Quantified Self Symposium 2018
Reza Mirza: The History and Future of Single-Subject Science
Hugo Campos: 10 Years With An Implantable Cardiac Device, Still No Data Access
Jana Beck: Carb Intake and 60 Lipid Measurements
Azure Grant: Lessons from Blood Testers, a Participant-Led Project
Dorothy D. Sears: Circadian Rhythms and Cardiometabolic Health
Carsten Skarke: Characterizing the Chronobiome with “Supertrackers”
Whitney E. Boesel: Cholesterol Variability Across Postpartum Menstrual Cycles
Xiao Li: Finding the Signal in Rich Self-Collected Data
Jeffrey Olgin: Data Aggregation for N-of-1 to “N-of-Many-Ones”
Dana Lewis: Social Infrastructure for Participant-Led Research
Camille Nebeker: Informed Consent, Self-Consent
Steven Steinhubl: Where “All of Us” Meets All of Us
Sunita Vohra: What N-of-1 Can Do
