Azure Grant: Lessons from Blood Testers, a Participant-Led Research Project

Azure Grant, associate editor at Quantified Self and leader of the Blood Testers project, presenting at the Quantified Self Symposium 2018.

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.

Azure Grant, associate editor at Quantified Self, describes the Blood Testers project.

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

Katherine Kim: What Counts as Clinical Data? Incorporating Self-Collected Observations into CVD Research

Jeffrey Olgin: Data Aggregation for N-of-1 to “N-of-Many-Ones”

Dana Lewis: Social Infrastructure for Participant-Led Research

Boomer Anderson, Marcel van der Kuil: Participant Perspectives on Regulation of 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

Benjamin Smarr: Changing the Definition of Baseline

Maggie Delano: The Case for Open Instrumentation



The Quantified Self Symposia brings together self-trackers, toolmakers, activists, clinicians, scholars, scientists, and all those interested in using personal data for personal and public health benefit.

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