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I spend a lot of time testing, tracking, and analyzing data. I’m not talking about the work I do here at Ogilvy–I’m talking about all of the daily efforts I undertake to manage my Type 1 diabetes. My life is full of numbers and tech gadgets, from a meter to test my blood glucose to mobile apps like dLife (for recording insulin doses) and Low Carb Diet Assistant (for counting everything from carbs to glasses of water consumed). Being somewhat of a geek, I’m always looking for the next best tool to help me track—and, even better, to help me analyze and interpret—data about my own health behaviors.

And so it was within this context that my ears perked up during last week’s DHCX conference, as Ernesto Ramirez of the Center for Wireless and Population Health Systems shared his thoughts on the role of self-tracking as an effective tool for health behavior change.

In his work, Ernesto focuses on how to apply emerging technologies (e.g., sensors, mobile, social networking) to better the health of individuals and populations through measurement and analysis of behavioral patterns. Think Fitbit for counting steps or Zeo for measuring sleep—or even Hugo Campos’ project to photograph every meal he eats and post to Flickr.


What does “quantified self” mean?

Quantified self started as a group [see the Quantified Self website: “a collaboration of users and tool makers who share an interest in self knowledge through self-tracking”] but people are increasingly using the term to reference a movement and as a catchall for self-data collection. There are over 50 Quantified Self Meetup groups around the world made up of people who use self-tracking for personal use, people that build tools and apps for businesses, researchers, etc.

The important thing to remember is that this is not just about creating spreadsheets—it’s about collecting data in whatever form is important to you…whether it is tracking colors that represent how you feel or taking photos of what you eat.

How does the quantified self lead to behavior change?

You get instantaneous feedback. For example, you can plug a blood pressure cuff into an iPhone and wirelessly send the data to yourself or to your doctor. You can also look at longitudinal data about yourself—both trends over time as well as correlations between things. With the ability to look at all kinds of different inputs, we can see better how things connect to each other. And we can create adaptive models for specific and meaningful behavior change in individuals. The behavior change model closely mirrors the scientific method—you observe, make a hypothesis, and so on. It’s really about what happens to you when you start to understand information about yourself.

How do we motivate people to use self-data collection tools?

It isn’t so much about motivating people to use the tools—you can put people on the path but you can’t make people be self-motivated. That said, things like gamification and good design can help by making things fun, easy, and worthwhile.

How might we collect this kind of data on a population level?

People think of the quantified self as “this is me” but we can quickly scale up. Large-scale data sharing would allow us to focus on specific groups rather than the model we typically use, which is based off of population distribution. We could really flip research on its head and start the other way—with a focused segment rather than with everyone. When people start collecting data about themselves, they begin to understand and care about how policy affects their health, how their workplace environment affects their health, and so on in terms of how their personal health is connected to the bigger picture.

Would you say quantified self falls under prevention or treatment?

If I had to choose where to start, I would say prevention first because this is where you’ll get the biggest bang for your buck. But we’re seeing the biggest adoption with treatment—for example, people who have recently been diagnosed with a condition become invested in their own health through self-data collection. They become evangelists and advocates, and they often have a strong desire to share their methods with others.

What will need to happen to take the quantified self movement to the next level?

We need to try, fail, and learn. Instead of an ROI model, I’d like to see us focus on a “Return on Health” model. This is a very long-tail discussion—you’ll see the real results in the next 20-30 years.

For more on the topic of quantified self, see:

This post was originally published on the Social Marketing exCHANGE blog.

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