Tag Archives: experiments

Introducing iMeRG: The Individual Metabolic Research Group

Here at QS Labs we take great pride in supporting a worldwide network of meetup groups. From Bucharest to the Bay Area, we have over 100 groups meeting to discuss self-tracking, share experiences, and learn from each other.

We wanted to highlight a new group, based in southern Oregon, that is using self-tracking to expand and influence medical knowledge within the healthcare system. Dr. Dawn Lemanne, a board certified and practicing oncologist, has started the new Individual Metabolic Research Group (iMeRG) to develop, test, and explore inexpensive way to prevent and treat chronic diseases related to lifestyle, through rigorous N of 1 research methods.


Currently the iMERG is a composed of physicians and other health care professionals frustrated by the rising rates of lifestyle driven chronic disease, and the failure of the large randomized controlled trial (RCT) to provide effective interventions. Inspired by QS, they are working together to develop and use rigorous N of 1 research designs, while using themselves (not their patients) as subjects. Members propose projects, and together they figure out how to do it. QS devices and philosophies play a major role in the data collection and analysis methods being talked about at the group.  Current proposals have included:

  • How best to measure the effect of combining intermittent fasting and exercise on blood ketone levels and inflammatory markers in a sedentary postmenopausal woman
  • The clinical manifestations of Familial Mediterranean Fever gene heterozygosity.

Join the group! If you hold a license to practice a health profession (MD, DO, DDS, DMD, RN, NP, PA, DC, ND, LAc, etc.), you’re interested in N of 1 research design and methods, and you’d like to be involved, please contact Dawn. All individuals are welcome, regardless of geographic location. If you’re in the southern Oregon area you can join their meetup group on February 28th. We’ll be posting updates from the group as their research progresses.

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What would you do with your microbiome sequence?

If you had access to free microbiome sequencing tests, to detect and analyze bacteria living in the nose, mouth, skin, gastro-intestinal, and/or urogenital areas of the body, what experiments would you think up?

Would you compare oral bacteria in people with lots of cavities vs. people with no cavities, look for differences between people with clear skin and acne, or sample your gut flora as you travel or change your diet? These are just examples — there are countless ideas.

As it turns out, we DO have up to 100 free microbiome profiles being offered to the QS community, thanks to Pathogenica and QS sponsor Autodesk.  Now we just have to think up some cool experiments to do.

So the challenge is on – propose an experiment in the comments, and the top experiments will be done with some of the free tests. The deadline for submitting ideas is August 31. Also, all the data will be made openly available.

Check out some background reading on microbiome sequencing at the Human Microbiome Project website and Wikipedia.

Let’s come up with awesome ideas!


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Micro Experiments

What’s the smallest thing you’ve tracked that had a short turnaround time but generated useful results? I’ve noticed that the kinds things we try here in the Quantified Self community are often longer-term experiments that seem to be a week or two long at a minimum. I think this is primarily due to the effects of what we try need time to emerge. (This brings up the issue of how much value there is in investigating subtle results, which came up at our recent Boston QS Meetup – recap here.)

However, as I work to adopt an experimental mindset about life, I’ve noticed these efforts can vary in scope, duration, and complexity. Because interesting things happen at extremes, I’ve been exploring the very smallest class of activity, what I call micro experiments. I’ve found that trying little things like these is a great way to test-drive treating things as experiments, and maybe offer the chance for non-QS’ers to dip their toes in the idea of tracking on a tiny scale. (Of course you shouldn’t risk shortening your life over any.) Researching the idea didn’t turn up much, though Micro-Experiments and Evolution was stimulating.

Here are some examples I’ve tried and their results. Are they true experiments? Are they useful? I’m curious to know what you think.

Jing: I tried using Jing, a free tool for doing short screencasts, to explain a bug I found in my site. I usually write them up, but because it was complex, it would have taken a lot to explain it. Instead I created a four-minute screencast, emailed the link to my developer, and measured the results. Conclusion: Worked great! Time to record: 4 minutes. His understanding of the problem: High. Enjoyment level of trying a new tool: Fun.

Testing expectations: Left unchecked, I tend to be pessimistic and anxious, which I continue working to improve. Here’s a technique I stumbled on that works well in micro experiment form. The idea is to treat your expectations as a model, make your assumptions and predictions explicit, then put them to the test. I applied it to two difficult phone calls I had scheduled, and found that my expectations were way off. In one case I was asking a fellow writer for a favor (mentioning an ebook I created), and instead of turning me down (my working model), he was happy to help. The other was a sales call in my last career to a prospective client, which I expected to go swimmingly. Instead it was a disaster! After analyzing what happened and comparing it to my model, I formed a couple of new ideas on how to do future ones. Surprisingly, the minute I thought of these as an experiments and wrote down my expectations, I felt immediate relief before the calls.

Pay for someone’s parking: As a touchy-feely micro experiment, I was standing in line to pay for parking at a garage, and on a lark I decided to pay the next person’s fee (it’s almost always $0.50). I didn’t know how they’d react (find it odd and refuse, for example), but the result: Evident happiness level of subject: High (I got a nice smile). My feeling: Walked away with a lighter step.

Disabling email: I continue to struggle keeping email from sucking my time and attention, so I tried disabling my email program for a day. This email vacation was helpful, but surprisingly uncomfortable. Not being able to monitor it clearly indicated a bit of an addiction. I didn’t end up adopting it.

Decisions and glue: I sometimes stress about getting something new perfect the first time. Yes it’s unrealistic, but that’s the brain I’m stuck with. Treating the decision as a micro experiment helps me enjoy things more. For example, I had to repair two broken lawn chairs at home, and couldn’t decide which of two glues to try. Then I realized this was a natural parallel type of experiment, and tried them both, one per chair. Result: Gorilla glue worked far better than the GOOP. Trivial? Maybe, but next time I don’t have to wonder.

Not eating before exercise: Eating breakfast is commonly considered important, so I wondered what would happen if I skipped eating all morning then mountain biking at 1pm for an hour. Result: My performance was just fine, but I was hungry afterwards! Now I don’t worry so much if I’m pressed for time.

Getting a bank fee waived: My wife needed a document notarized, so I brought her to the mega-bank where I was forced to do business for a time. The teller said she couldn’t do notarize it because my wife wasn’t listed on my account. In a bold (for me) move I did a social experiment by asking for the manager, who ended up OK’ing it, no problem. I was a little embarrassed until I thought of it experimentally.

Chocolate skin, cranberry sauce: There are lots of ways to experiment in the kitchen; here are two micro experiments I tried. First, I drink hot chocolate every morning (melt the expensive dark stuff into milk) and it sometimes develops a skin on top. (Hey – I discovered pudding!) To avoid that, I tried putting the heat on high and stirring constantly, instead of my usual medium heat with less stirring. The question was whether heat/time would affect skin forming. Result: ~50% reduction. As a second example, we had some leftover cranberries (I live in New England) and I wanted to make a sauce, but I was too lazy to follow a time-consuming recipe. Instead I microwaved a handful of them in a bowl with a little orange juice and honey. Result: An explosion of flavor. (Literally – it blew up while cooking.) Edibility was marginal.

[Image from windsordi]

(Matt is a terminally-curious ex-NASA engineer and avid self-experimenter. His projects include developing the Think, Try, Learn philosophy, creating the Edison experimenter’s journal, and writing at his blog, The Experiment-Driven Life. Give him a holler at matt@matthewcornell.org)

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A Billion Little Experiments

I have been participating in the QS Show & Tell meetings since they started.  What those of us in the QS are working on today, and the interest we take in tracking and analyzing all aspects of our lives, is not quite mainstream yet. But many of us feel that like those pioneers in the Homebrew Computer Club what we’re doing will eventually have a huge impact on everyone’s lives. I have written a paper “A Billion Little Experiments” on the potential to dramatically improve healthcare and medicine by harnessing petabytes of data from individuals taking care of their own health, and on the necessary shifts in mindset required. 
In summary, the paper argues that we can and must:
  • Enable self-care success with great personal health management tools.
  • Empower self-experimentation through education, encouragement, and assistance.
  • Exploit the data from these experiments to advance health care and science.
The gist of the story is …
Optimal health practices will vary, at least somewhat, across individuals and circumstances.  Today’s health science is too limited to be able to say exactly what is the best health practice for a particular person in his specific circumstance.  Optimal health practices will also vary over time  Therefore health requires continuous optimization, and constant experimentation to identify changes and seek optimal practices.
People are in fact constantly experimenting, trying new foods, activities, medications, etc.  We could theoretically benefit tremendously from this experimentation.  Health science would benefit if good data was collected from thousands, even millions, of people and properly analyzed.  Today we don’t do this, especially because few people are collecting and/or providing good health data.  This is an opportunity wasted.
How can we collect this data?  How can we get people to track their health, when we know from long experience that adherence is poor?  I propose it demands a fundamental re-examination of the problem of non-adherence, and a focus on supporting people’s desires rather than telling them what to do.
Poor adherence is labeled as a problem of poor motivation and discipline.  This is wrong.  Adherence is poor because it is nearly impossible, in the context of daily living where health is just one of many competing priorities.  People need help, need much better tools, to improve adherence.  Such tools are possible, but most of the tools offered to-date are simply inadequate and inappropriate.  Far better personal health management tools need to be developed.  This is an issue that must be addressed — good experimentation is impossible without the ability to carry out the experiments properly.
Just as important is recognizing that people’s priorities, appropriately, are on living rather than on health.  No matter how valuable their health data could be to the advancement of health science, people cannot be expected to take on the chore of tracking.  We, who want the data, must focus on addressing their need — to live better today to make life easier today– and do it in a way that will provide the data we want.  That’s our design challenge, a burden we must bear, not one to impose on people.
We can do this.  We can develop personal health management tools that make people’s day-to-day lives easier, that provide them with help they want, and provide the data that will help us advance health science.  We must do this.  Without rich data from a broad swath of people, advancement in health science will continue to be hampered by a dearth of data.   We must change our mindsets and provide the product & services to inspire and harness a billion little experiments.
Rajiv Mehta is founder and CEO of Zume Life, and also consults on driving radical innovation.

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