Category Archives: projects
The pursuit of creativity and self-expression are among the personal values that influence my happiness. Unfortunately, most of the creativity tests that exist today require you to perform certain tasks (e.g., solve a problem, draw something, etc.), involve other people rating your performance, and thus are not suitable for everyday self-tracking. I needed something more simple and more general, so one of my Quantified Self challenges this year was to develop a method to measure and track my creativity on a regular basis. After several unsuccessful tests in January-February, I finally ended up with a 4-question measure that may have a great potential.
In an attempt to understand what causes psychological stress and how it affects quality of my life, I have been tracking its various sources. Contemporary stress theory recognizes three major types of stressors: intrapersonal (my personal thoughts, emotions, inner conflicts, etc.), interpersonal(relationships and interactions with other people, and non-personal (weather, workload, time constraints, etc.). I have been rating exposure to each of these stressors three times a day throughout March, using 10-point scale in my rTracker log. The objective was to find out what kind of stressors bother me most often, my sensitivity to each of them, and how stressors influence my everyday psychological states and behavior. This week, I finally had a chance to aggregate all that data, and run some quick analysis.
The ultimate purpose of self-tracking, in my opinion, is control. Control over health conditions, performance, mood, and other aspects of your everyday life. To paraphrase the famous adage, we measure so we could manage. We also measure things that we can’t manage (e.g., weather). Because self-discovery through self-tracking leads to knowledge, and knowledge is another form of control. Or at least, it gives us a sense of control. But how much of our everyday life we can actually control? How this lack of control affects our everyday life? To some of us, these questions may sound philosophical, but I believe the answers can be found in our own data. In February and March, I have been tracking “entropy” in my everyday life: those occasions when things go beyond my control, and happen exclusively due to some external forces. The ultimate objective was to investigate to what extent such random uncontrollable events influence different aspects of my life.
I have been using RunKeeper to keep track of my walks and bike rides for a while now. In addition to distance and pace, RunKeeper offers an estimate of calories burned that is most likely derived based on my weight/age and distance information. Last month I had an idea to compare these estimates with those provided by my Bodymedia tracker, and to do that, I had to conduct an experiment, which lasted for about two weeks. The estimates provided by both trackers turned out to be very close.
Self-esteem refers to individual’s emotional evaluation of his/her own worth and personal abilities and capacities. Psychologists believe that self-esteem influences how we feel, act and relate to other people, which makes it one of the central concepts in positive psychology. In general, self-esteem considered to be a trait (a psychological construct that is relatively stable over-time, like personality characteristics), although some psychologists recognize also more short-terms expressions of self-esteem (self-esteem states). I have been tracking my self-esteem since February, and this week finally had a chance to look at the data. I was particularly interested to see its stability over time and throughout the day, and how self-esteem is related to everyday stress, mood and happiness.
Can you predict your day based on how you feel immediately upon waking up? In an attempt to replicate Sami Inken’s analysis, I have been rating my mood every morning within 15 minutes of waking up, and then three times throughout the day: in the morning (around 11 a.m.), afternoon (around 5 p.m.), and evening (around 10 p.m.). After about a month of tracking (22 days of data), I looked at the correlations, and the results were rather disappointing.
The March is almost over, so I thought it is a good time to tell what kind of things I am have been tracking and what self-experiments I have been conducting this month. As usual, at the end of the month I will export data from my rTracker log , analyze it and will share any interesting insights and findings with you.
If you have not noticed yet, the “modus operandi” for this blog and my self-tracking efforts is a bit different this year. The month of January was spent collecting data, testing apps and services, and blogging about various QS issues, and month of February was dedicated to analyzing collected data, reviewing tools, and sharing insights and recommendations. So I thought it would be helpful if I summarized briefly what I learned during the last two month, in one post.
One of the diet-related tools that I tested in January was 80 Bites app. Dubbed as a “pedometer for your mouth”, this simple app let’s you track how many “mouthfuls” (“bites”) of food you take during the day, and how much time, on average, you spend chewing the food between the bites. The premise behind the app is that eighty “bites” a day is usually enough to feel full and satisfied, and limiting your food intake on the long run can help you to shrink your stomach and eat less. I am not sure about the latter, but using this app for several weeks definitely helped me learn to eat my meals more mindfully. I also discovered something new and interesting about my eating habits from the data that I collected.