An experiment in self-tracking
February 2, 2011 § 2 Comments
Today, we spend the majority of our lives within meters of a personal monitoring device, capable of tracking data about our surrounding environment. Location services like Foursquare and Facebook Places have introduced us to the concept of “checking in”, or considered more broadly, Manual data capture. As a concept, altering behaviour to track and shed light on certain aspects of our lives has been around a while, but curious, I decided to experiment myself.
This post is not proposing any grand ideas, simply a light exploration into what is out there.
I wanted to pick an aspect of daily life that anyone could relate to. The goal was simply to explore different approaches in manually capturing data to establish how hard this is to incorporate into a lifestyle. I wanted to understand a little more about whether this additional information would actually justify the extra effort put in to track it and how much potential there was for automation.
I decided to track what I ate.
A popular app on the high-detail end of the spectrum. It encourages users to input very specific information on everything consumed. There’s a large database of existing pre-packaged foods, intended to improve accuracy and speed when entering meals, although things get much more complicated when cooking yourself or eating out.
2. Daytum / Google Forms
Not strictly dieting apps but these both offer the flexibility to create custom forms incorporating as much information as you’d like to monitor. You then just add a bookmark to your homescreen, providing easy access to the form. The nice thing here is allowing users to define how serious they want to be, perhaps you just want to track the time you eat? Or maybe a short meal description and calorie count?
My favourite concept, ideal for the lazy user. Based on the notion that “Keeping a Food Diary Doubles Weight Loss“, users are simply asked to take photos of what they eat. There is no fiddly data entry or calorie counting, just a fuzzy sense of what you’re consuming. The images also act as a dataset for a nutritionist to advise on how to tackle basic eating concerns.
After trying MyFitnessPal for a couple of days the level of complexity felt too severe. The shortcuts I had to take to make it usable lead the data to be more or less useless. Perhaps this wouldn’t be a problem if I was serious about dieting and this level of detail already existed in my behaviour. I decided not to take on the Google form approach because I didn’t have any specific information I wanted to track.
Given that DietPicture hasn’t launched yet I decided to try the concept by simply capturing photos in Evernote. The barrier to entry was very low, in fact, a lot of people don’t need encouragement to take photos of their food. I’m not sure a serious dieter would take much note of this but I found enforcing the behaviour change was helpful in making me more conscious of what I was consuming. For those curious, here is what I ate/drank over three days:
Overall, I found the times I was most willing to adjust my behaviour were when it didn’t get in the way of my experience. Taking a photo before a meal felt suitably minor, but the trade-off was clearly the lack of usable data to apply any analysis to. As smartphones & infrastructure evolve and make automated self-tracking more feasible there’s a lot of potential for applications that can contextualise this information, providing us with personalised analyses of how to refine and iterate on the lifestyles & habits we’ve formed.
Have you tried any self-tracking experiments? I’d be very interested to learn more about the aspects that have worked well and types of interaction that have been worth sticking with.