tracking entropy in everyday life by measured me blogThe 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.

At the end of every morning, afternoon, and evening, I would record if there were any significant occasions in my life when the things were beyond my control. Depending on whether such occasion had a negative or positive impact, and degree of that impact, I would then assign that morning/afternoon/evening to one of the following five categories: “chaos”, “disorder”, “normality”, “surprise”, or “miracle”. A perfect example of the morning in the “chaos” category would be that morning in March when my bike’s tire blew on my way to work. An example of the “miracle” afternoon would be the day in January when early office closure was announced due to the impending snowstorm. At the end I had to combine categories due to low incidence levels (there were only a couple of miracles in my life, and just a handful of chaotic events), so I ended up with three levels of entropy: “negative entropy”, “normality”, and “positive entropy”.

The first thing I did was to look at the distribution of entropy in my everyday life. As you can see, most of the time (about 82%) my life is relatively “normal” (read: boring), but both negative and positive random events have a notable share (about 9% of the time each). More interesting pattern emerged when I broked down distributions by dayparts: mornings had relatively higher share of negative entropy, and lower share of positive entropy. The pattern in the evenings was completely opposite: a disproportional share of positive random events in my life tend to happen in the evening:

Measured Me - Tracking Entropy in Everyday Life

I then looked at the potential effect of entropy on my psychological states. All three aspects of my mood (positivity, intensity, and dominance) are clearly affected by entropy. The differences in the emotional dominance (whether I feel being in control of my mood and emotions) are especially defined: I feel more submitted to my emotions in case of negative random events, and dominate my emotions in case of positive entropic events. In other words, I tend to overdramatize the negative events and suppress my feelings in positive occasions:

Measured Me - Effects of Entropy on Mood

Measured Me Entropy Tracking Experiment: How Random Events Affect Mood

Naturally, negativity or positivity of entropy also affects my happiness: on pleasantly surprising occasions I tend to feel more happy than during disastrous events.  The negative random events also lead to higher stress:

Measured Me - Effects of Entropy on Happiness and Stress

Measured Me Entropy Tracking Experiment: How Entropy Affects Happiness and Stress

The entropy, however, does not affect my self-esteem: I did not feel differently about my “worthiness” in uncontrollable situations. However, there were very interesting differences in my locus of control. The locus of control measures the perceived degree of control that I have over my life; I started tracking it in March using a 10-point scale, with higher scores indicating me being more in control. As you can see, in case of negative chaotic events, my locus of control drops; however, it goes up when the events are more favorable:

Measured Me - Effects of Entropy on Self Esteem and Locus of Control

While the methodology was somewhat limited (I was not classifying individual events, but rather parts of the day; the classification was somewhat subjective; analysis is based on less than three months of data), tracking entropy still helped me to answer some of the questions that I mentioned in the opening to this post. Random uncontrollable events occur relatively often, and they do have an influence on certain aspects of my life. I will most likely continue tracking entropy in the future, but may revise the approach.

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