#WeAreNotWaiting by Dana Lewis

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From the Quantified Self Public Health Symposium

“I didn’t want to wait. I don’t want to die in my sleep. We are patients who are not waiting.”

Dana Lewis became a reluctant self-tracker at the age of 14 when she was diagnosed with type 1 diabetes. Dana and her partner Scott Leibrand have been developing a DIY artificial pancreas that is built on top of the data flows from Dana’s continuous glucose monitor. In this talk, she describes the role that access to data plays in the DIY pancreas, with immediate and profoundly positive effects on her life.

Watch Dana’s talk on Medium.

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Bridging the Gap by Aaron Coleman


From the Quantified Self Public Health Symposium

“On the Fitbit, every single minute has a met value attached, every minute has an intensity score— all these different things from these little inexpensive friendly wearables are giving us amazing insights.”

Integrating consumer self-tracking tools into scientific and clinical workflows is harder than it looks. Aaron Coleman has built his entire company, Fitabase, around the needs of researchers to authorize and integrate physical activity data from trackers like the Fitbit. After supporting nearly a hundred different studies, Aaron can talk with unique insight about what it takes to bridge the gap between the companies whose devices are on the wrists and in the pockets of consumers, and the researchers who are looking to make sense of it.

Watch Aaron’s talk on Medium.

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Sharing Self-Collected Data by Andrei Pop


From the Quantified Self Public Health Symposium

“If I am able to take my data out of this place and share it with something that I find useful, I can actually unlock more value from the underlying source.”

Andrei Pop is the co-founder of Human API, whose purpose is to open the world of self-collected data to app developers, so they can build new experiences tied to the health and fitness questions people may have about themselves. Many of these apps built on top of Human API are for health care providers, but there are many other possible uses. In this talk, Andrei argues for “data liquidity” as the key to unlocking value for all stakeholders.

Watch Andrei’s talk on Medium.

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Making Health Data Accessible and Actionable by Drew Schiller


From the Quantified Self Public Health Symposium

How does data flow out of a specific device or app? Can we get a copy? Can we combine it with other data? The difficulty of moving and combining personal data has given rise to an entirely new layer in the health data ecosystem: the QS aggregator. Right now, most of these aggregators are focused on helping healthcare organizations and researchers combine data from various systems, but many questions remain about who controls these data flows and what purposes they can serve. In this short talk Drew Schiller the co-founder and CTO of Validic, a digital health data platform with many enterprise customers, talks about how personal data can be more accessible and useful to the individuals who collect it.

Watch Drew’s talk on Medium.

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A New Type of Evidence by Dawn Lemmane


From the Quantified Self Public Health Symposium

“We are turning the evidence pyramid on its head. We think the single subject trial should be at the top of that pyramid.”

Dawn Lemanne, the founder of Oregon Integrative Oncology, is a pioneering clinician who brings powerful tools of patient involvement and self-assessment to evaluating treatment options. A widely respected researcher, she also organizes the Independent Metabolic Research Group (iMeRG) based in Southern Oregon, a group of over 40 licensed healthcare professionals who meet regularly to discuss their individual single-subject research studies. Here, Dawn describes some of the research her group is conducting, reflecting on what our future concepts of evidence may be when single subject research becomes more commonplace.

Watch Dawn’s talk on Medium.

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Shelly Jang: Can You See That I Was Falling In Love?



When someone comes into your life and takes up a special place in your heart, do they also occupy a similar place in your data? Shelly used GMvault to look through 5 years of Google Chat logs to “hunt for signals that I loved my husband and not somebody else.”

She looked at whom she messages, the time of a day, and the words she uses. She was able to extract meaning from innocuous metrics like “delay in response” to show whether her or her future husband were “playing games” at the beginning of the relationship. She also found that use of the word “love” did not correspond with the object of her affections (case in point: “This cytometer needs love too.”)

If you would like to do a similar analysis of your Google Chat log, contact Shelly to get the scripts she used.

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Learning from my N of 1 by Mark Drangsholt


From The Quantified Self Public Health Symposium

Mark Drangsholt is a clinician scientist with a PhD in epidemiology, but the story he tells in this short talk is about deciphering two different serious medical conditions through tracking and thinking about his own personal data.

“My main story today is not about my professional life. A key event happened here in San Diego about 13 years ago. I was at a research conference, and while sitting in the back of an auditorium just like this my heart rhythm went completely haywire. The thing that was most surprising was that instead of waving my arms and asking for help, I just slumped in my chair and greyed out, thinking this was the end. I thought I was dying.”

In the years since, Mark has developed pioneering methods of self-investigation to solve his own health issues, methods that he describes here with an explanation of how they drive more widespread health discovery.

Watch Mark’s talk on Medium.

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Asking Myself 10,000 Questions by Brian Levine


From The Quantified Self Public Health Symposium

How do you study yourself when you’re not looking? Brian Levine is the co-founder of Tap2, the creator of younlocked, a unique self-assessment tool that helps individuals collect self-report data by asking questions during the phone unlocking process. By answering almost 10,000 questions during a six-month period Brian was able to find out: “Why am I so tired, and why can’t I be in a better mood?” By connecting self-assessment to the phone unlocking gesture, which is performed many times a day, Brian created a novel form of self-observation. In this short talk Brian shares some details about his rich self-collected data set that, as well as a method that, if widely adopted, could be the foundation for many new personal and public health discoveries.

Watch Brian’s video on Medium.

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A Public Infrastructure For Data Access

Smarr2 (1)Larry Smarr’s major contributions to scientific progress are well known. A physicist and the founding director of the National Center for Supercomputing Applications (NCSA), he helped bring the power of computing to scientific research at a time when computers will still highly specialized instruments. Today he is the Director of the California Institute for Telecommunications and Information Technology (Calit2), one of the most innovative research institutes in the world. He’s also an avid self-tracker, using his own data to correctly self-diagnose the onset of Crohn’s disease. In preparation for our upcoming Quantified Self Public Health Symposium I asked Larry about his idea for a large scale, non-commercial, broadly accessible infrastructure for improving access to self-collected data for both personal and public benefit.

Gary Wolf: What’s the role of the public health sector and of the academic research community in a world where individuals and consumer-oriented tech companies are taking on increasingly complex questions of personal and population health?

Larry Smarr: The fundamental role is bridging the gap between N=1 and N=a lot. Any time in the last 30 years when I’ve seen a technical innovation that mattered, like a software tool, the first approaches aren’t ready for prime time. They are not developed with professional-level software engineering, version controls, documentation and all that. Similarly, scaling up of biomedical observations made by N=1 quantified individuals is going to require the professional methodologies of the public health sector.

GW: Can this be left to industry?

LS: Not entirely, although startups are doing a fabulous job of getting tracking tools into the hands of tens of millions of individuals. The problem is how to do research on the data produced by that broad population. Too often these days I see  researchers from the university going to tracking companies and asking for access to the company’s raw data feeds, for instance to heart rate or exercise time series, and the company says no. They will give you the weekly or daily average, but you can’t get to the raw data. If you go to them and say, I’ve got this really great innovation that can be used to understand this data, more often than not they decline. They have an installed base and market share to protect, which naturally tends to make them conservative. I think there is a real opening for companies to make this anonymized broad population data available to academic researchers. That’s when a raft of scientific discoveries will be made from the quantified population.

GW: Those are the consumer fitness companies, but what about the healthcare IT world?

LS: Again there is a disconnect between the consumer fitness cloud-based apps for millions of individuals and the electronic health records in your healthcare provider. If you’re a doctor in a medical office, unlike a data science researcher, you don’t want all this data. What you want to know is: did my patient do 1000 steps or 10,000 steps today, did you get aerobic exercise or not, are they getting enough sleep? So it’s not like you need a vast dumping place inside electronic health records.  Again, I think pilot experiments are the way to get started.

GW: You’re arguing that the incentives aren’t there.

LS: These are currently major structural barriers. Who is going to work on the bridging we are discussing? There aren’t incentives for the commercial tracking companies to work on it. Neither are there incentives for the electronic medical record companies to work on it. NIH isn’t going to support bridging between commercial companies.  It falls between the stools. You need to have the research community, and health care IT experts, the commercial tracking companies, and the individual self-trackers all come together and collaborate.

GW: You envision some kind of technical system so that individuals and health care providers and researchers could all benefit from access to data. What does your experience tell you about how long this would take to have a working prototype that would be practically useful?

LS: It’s a three-to-five year project. I think if a major funder did a call for proposals requiring a health care provider, university research community and the self-tracking community to come together a prototype a solution, I think they would get some very interesting proposals.

GW: In a talk you gave in 2011, you said “science is not enough.” You pointed out that we’ve known the link between smoking and cancer for over half a century, and yet global cigarette consumption has tripled during this time. So we have all this possibility for new discoveries with self-tracking data, but how is that going to help make people healthier?

LS: Yes, just knowledge of what causes negative impacts on health is not enough. My former UC San Diego colleague Naomi Oreskes documents how economic interests slowed down the logical social reaction to smoking health threats and climate change in her Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming (2010). We are seeing similar delaying and disinformation tactics in the obesity/diabetes epidemic, which has been building for four decades. It is sobering to me to see someone as politically skilled as New York City mayor Bloomberg defeated in his efforts to ban jumbo sugary drinks. My best guess is that we face a multi-decadal battle, just as we have had with tobacco and climate change, to get our society to move to healthy eating and drinking. The bright spots are subcultures of healthy living, often empowered by tracking and social media, that are developing across the country.  My hope is that these will spread and scale over the next decade.

GW: It seems you are also pointing toward activism, since that’s been so important with smoking.

LS: Activism is essential given the enormous power of the entrenched economic interests. Activism can lead to regulatory reform, which over time can make huge social changes.  For example, when I grew up in the 1950s and early 60s my father didn’t smoke, but he was embarrassed that you had to have ashtrays in your house, because he said you couldn’t tell people not to smoke in your own home. Socially, you just couldn’t. About that time the Surgeon General’s report on smoking was published. Fifty years later, huge chunks of society are smoke-free, such as all the University of California campuses, restaurants, and large social gatherings. Just think of what an enormous shift that has been! We are beginning to see similar activism in getting pension fund investors to boycott carbon fuel companies in order to slow down climate change. So can we imagine a boycott against sweetened beverages and high glycemic prepared foods? I believe that there is a huge role for health-related individual and organized activism in the near future.

GW: At the last Quantified Self Public Health meeting, you suggested that this emerging field needs a new kind of journal where individuals can report their discoveries. In light of the big challenges you’ve been describing, challenges that can’t be solved by academic and research publication alone, what kind of contribution could a new journal make?

LS: Let’s go back to the issue of scaling we discussed. Imagine the journal articles are fairly short, describing how the data was generated, but the back end is a publicly available cloud of data so that you could begin growing a large dataset of N=1 projects. Then the research community could pick up on the ideas coming out of the Quantified Self community, explore the data, and take it further. That’s how things grow.

GW: You want to be on the editorial board?

LS: No, I want to submit a paper!

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Solving the Right Problem by Susannah Fox and Don Norman

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From the Quantified Self Public Health Symposium

The cognitive scientist Don Norman is one of the world’s most influential design theorists. His best-selling book, The Design of Everyday Things, has been in print for twenty-five years and is widely recognized as a classic. He is currently the director of The Design Lab at University of California, San Diego.

Here he talks with Susannah Fox, who was at the time of their conversation an entrepreneur-in-residence at the Robert Wood Johnson Foundation. (Today Susannah is the CTO at the US Department of Health And Human Services.) Susannah begins by asking Don about his idea that the first job of design is the solve the right problem. How do you know the problem you’ve chosen is the right one?

“In Human-Centered Design,” Don answers, “when we’re asked to solve the problem the rule is no, don’t solve the problem. Ask, why is that the problem? Why do you need this? What is this problem about?”

Watch Susannah and Don’s talk on Medium.

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