Chris Roth — cofounder DoubleBlinded — on taking a scientific aproach to life
Chris is a software engineer turned data scientist with a specialization in health, biotech, and science. He is interested in quality of life improvement both at the individual level through lifestyle design and at the macro level through urban planning and public policy. In addition to software and tech, he studies, health, biology, and nutrition.
He is a cofounder of DoubleBlinded, an experimental new platform for personal experimentation and crowdsourced science.
Could you refresh everyone’s mind and tell us what the Quantified Self movement is all about?
I’ll give you the “official” definition as Wikipedia defines it, for starters:
The Quantified Self (QS) is a movement to incorporate technology into data acquisition on aspects of a person’s daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical).
It’s hard to beat that definition, so I’ll elaborate on what parts of that I think are the most profound…
To me, QS is about taking a scientific approach to your life. Instead of just assuming that your intuitions are correct, QS is about taking your intuitions and validating them with numbers so that you can track pieces of your life with scientific certainty. This gives you the tools to fine-tune your life and detect progress or regressions that might otherwise slip under your radar.
Here’s an example: as you age, your hormones change. Generally a man’s testosterone levels slowly decrease after age 30 by about 1% each year. This happens gradually… most men don’t notice. If you are able to quantify your blood hormones, then you can notice the slow decline and intervene. Perhaps this is a natural, healthy trend, but some of the negative effects like low energy, low libido, and brain fog can be ameliorated with interventions such as TRT, supplementation, and weight lifting. Once you’ve intervened, you’ll want to see if your intervention is actually working… with another hormone test. This gives you the tools to definitively know if what you are doing is working.
The way that media portrays the QS movement, you’d think it was a super esoteric movement full of health nerds. I believe it is part of a much larger movement about quantifying the world in general. As technology advances and we have better tools for measuring our bodies, we make use of those tools and react to the measurements that we gain. This is nothing new… hormone tests, for example, have been around long before the term “Quantified Self” existed. The movement is simply a new term describing the recent popularization of self-measurement which has emerged as a result of cheaper, more accurate measurement tools.
Logging data, by itself, doesn’t really tell you a lot. It makes for a really cool time-lapse-video (and they are often cool), but if one has the goal to improve for example his/her health than you have to do more than logging, right? What are your ideas on that?
You touch on an interesting distinction. The QS community is made up of people from a lot of different backgrounds, each having very different motivations, but I think the community can generally be divided into two camps: those who are intrinsically motivated as hobbyists and those who are trying to solve health problems.
For the intrinsically motivated crowd, logging is much like journaling: it’s self-satisfying and doesn’t need to solve any particular problem. It’s simply for fun and enjoyment. In that respect, I find that a lot of QS projects are actually artwork, and I think this is one of the most beautiful things about the movement. We’re seeing a merging of artwork, technology, and mathematics in a way that wasn’t possible before. I can certainly say that I enjoy this aspect of QS myself. I would self-log regardless of the outcome, even if it were just for fun.
Then there are the health-motivated folks. The diabetes community, for example, is very present in the QS world because of the nature of their condition. The diabetes community is an interesting area of study for grassroots innovation in general. I was recently at a conference hosted by Dr. Harold DeMonaco and Eric von Hippel of MIT who study patient-led innovation. A lot of the people in this community self-track not just for fun, but to manage their diabetes.
And another health area that is ripe for this kind of quantification-based improvement is mental health. Bipolar, for example, is a disease that really needs to be tracked: manic episodes and depressive episodes need to be monitored in order to identify triggers. And the same goes with migraines, too… there are an increasing number of mobile apps out there that use self-logging as a tool to try to identify potential triggers such as citrus fruit or brightly-lit screens.
Do you like what you have read so far? Get a quarterly update of what I am busy with.
If you didn’t pitch your company yet… Let’s have it.
DoubleBlinded is a platform for personal experimentation and crowdsourced research. We send you a clinical trial in a box: you test a nutritional supplement of your choosing over four weeks. You get four pill bottles. Two of them are the expected supplement, two are placebos. You don’t know which are which until you’ve completed the month-long experiment. We show you how you respond to the active ingredient vs placebo as measured by as series of cognitive assessments.
For our first trial, we partnered with Quantified-Mind.com to conduct part of the assessments and measure the effects of L-Theanine on executive function. (L-Theanine is an amino acid associated with relaxation and calmness that is naturally-occurring in Tea leaves).
And this is just our proof-of-concept project. We set out to validate that crowdsourced science experiments of this nature, where the participant pays, are viable. We were successful.
We are looking to expand into a few areas as well, such as crowdfunding of clinical trials, ways to make clinical trials cheaper, and doing non-manipulative experiments where we let users input observational data to find correlations without actually having to order kits or ingest supplements.
Why did you actually start your company?
DoubleBlinded is a social experiment moreso than it is a company. We aim to harness the billions of data points that could (and we believe, SHOULD) be collected by everyone who is self-experimenting with their lifestyles and health. With all of the new research coming out on diet, supplementation, nootropics, and meditation, there are a lot of people experimenting at home.
But do these behavior changes really have the intended benefits? And how do they interact with hereditary factors, health conditions, and life circumstances? These are all questions worth answering, and we believe that if we can tap into the millions of people who are self-experimenting, we can find interesting answers that move science forward.
You talk a lot about quality of life. If I want to impress people I’ll tell them about the Meaning of Life (sciency) symposium I organized in 2008.
And that became a theme again when we tried to predict individual (life) satisfaction at Booking.com. I’m all about quality of life. My friend Ruut Veenhoven who is an emeritus Professor of social conditions for human happiness, would boil it down to:
- enjoying what you do
- and keep yourself busy.
Tracking activities, like in experience sampling or the day reconstruction method, seems a really interesting approach.
Now the question comes: on a scale of (1) — — — (10) how cool do you think I am?
I’ll give you an 11 😉 And I would be curious to hear you discuss these approaches, I think they could be interesting.
So, in measuring happiness (life satisfaction) there are some ways of doing it. One is the standard survey with the question “Everything considered how satisfied with your life are you right now?” That question is the basis of all the “Denmark is the happiest country in the World” studies and the enthusiastic news coverage it gets.
Experience Sampling (by Mihali Csikszentmihalyi) takes another approach. It can be used with a reminder device or app on your phone and will ask at random time how happy someone is at that specific time.
The Day Reconstruction Method (Dan Kahneman) would ask people to tell what they did the day before and how the activities made them feel.
When working at Booking.com as its first Travel Scientist it was the goal of my team to try to predict in which place and accomodation people would feel the happiest. Would they like to go to Paris, or rather Bratislava? And would they feel good in a Bed And Breakfast or a large hotel. In the old town, or in the hip neighborhood more to the edge of the city. And so on.
We could start with the data we had based on millions and millions of recommendations. But the real challenge came in capturing data that didn’t interfere with business and still made sense scientifically. To be honest, predicting happiness is another thing altogether then measuring it, so it was a very ambitious endeavour.
But is was a fun project! :) Do you run into similar measuring data/predicting outcomes type of problems, and if so, how do you deal with them?
Yes. This is huge. I’ll start with the question of measuring:
It’s easy to measure objective things like weight, caloric intake, steps taken, body temperature, hours spent on the computer, etc. Great. Measuring subjective, or more subtle things, is the “holy grail” of the Quantified Self movement, in my opinion because they are so difficult to track but so valuable.
Ultimately, it is the abstract ideas like “happiness”, “quality of life”, and “productivity” that are the most useful metrics. But these are elusive. It seems like often the best measures of these things are through combining quantifiable objective measures. For example, you might create a formula for measuring “quality of life” made up of quantifiable things like weight, resting heart rate, income, daily steps taken, number of friends on Facebook, etc. The idea is to find objective correlates of the subjective measure you are really interested in and combine them to emulate the objective measure as best as you can.
I envision a future where we manage to quantify happiness by means of neuroscience. If we live in a world where we are purely physical creatures and our subjective consciousness is actually a physical phenomenon that we have yet to understand and quantify, which I believe we do, then I think we can objectively measure things like happiness, quality of life, sadness, and love.
It may not be the romantic vision of soulful creatures that we were promised as children, but I think the future in a world of such quantification will be interesting. Advances in our ability to measure the brain, the connectome, the nervous system, and the endocrine system in real time would enable such quantification.
Going back to our present reality, though, it seems that our best measurement tools are often still spreadsheets with a simple subjective rating on a scale of 1–5. Asking someone, On a scale of 1–5, how happy do you feel?, even with all of its inherent bias and subjectiveness, is still one of our best measurements of happiness.
