Category Archives: mind
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.
As promised, posting the full Power Point slides of my “Hacking Happiness” presentation from NY Quantified Self meetup. In this self-tracking experiment, I looked at how different aspects of well-being, personal values and everyday activities predict my happiness.
In December and January, I have been tracking some aspects of my everyday life in order to test a couple of psychological and behavioral theories of happiness. The preliminary results of this experiment will be presented tomorrow at the Quantified Self NYC meetup, and of course, I will be posting the PowerPoint slides of my presentation later this week. Unfortunately, 10 minutes are not enough to cover everything in depth, so I thought I would dedicate a separate post that would discuss the most interesting findings of this experiment in more detail. My personal favorite was quantification of how not being able to live according to my personal values affects my happiness.
In last post, I showed how I mapped 24 emotional states against two dimensions of mood (valence, a.k.a. pleasure, and arousal) using my self-tracking data from January. The resulting “map of emotions” proved that tracking mood using two-dimensional approach is more effective than using a single question (e.g., “how do you feel”). It also showed that I can drop the individual emotions from my log and use only mood dimensions to capture my emotional states. In this post, I will share results of additional analyses. Specifically, I looked if pleasure and arousal dimensions of mood can replace stress and happiness measures.
I am very excited to start this year with some new awesome self-tracking projects and experiments! For now, the major emphasis remains on areas like sleep, fitness, diet, cognition, and psyche, but I will be covering a bit productivity and finance, too. Here is a quick preview of what I am tracking (and working on) this month.
In this post, I would like to raise a question that in some degree reflects my personal concerns about current trends in Quantified Self movement. Since this opinion is based primarily on my personal observations, I would really appreciate any feedback or comments from QS community. Please correct me if I am wrong, but why do we have so many tools and projects that focus on diet, sleep, exercise, but when it comes to tracking psyche, in particular, psychological states and traits, the inventory and range of QS projects is rather limited?
Last month I looked at my sleep data produced by Bodymedia and Sleep Time app, statistically comparing their sleep quality scores with each other, and with my own subjective sleep assessment. In October and first weeks of November, I replicated experiment, adding another device – Zeo. With over 30 nights of data, I finally was able to look at four different metrics, side by side, to see how comparable and interchangeable they are. The results will surprise you.
One of the self-tracking projects that I always wanted to do was to determine the impact of sleep, diet and exercise regimen on my mental and cognitive abilities. So last month, I turned to the app store to look for mobile tools that could help me to measure and track my cognitive performance. After three weeks of searching and testing, I finally found three apps that I can use with confidence in my self-tracking experiments.
As you may know, I have been searching for a short yet reliable metric to track my happiness levels. In the past three months, I have tested three different methods, and the most recent tool, a short version of Ryff’s subjective well-being scales looks very promising. Hopefully, I will start using these questions to track happiness on a daily and/or weekly basis, and will be sharing with you soon some insights based on that data. In this post, however, I would like to review another great tool that enables you not only track happiness and life satisfaction at more granular levels and on a long-term basis, but also provides a diagnostic feedback on how you could improve your well being.
If you downloaded my September data (you can do it here, absolutely free!), you probably noticed that the research agenda behind data collection that month was focusing primarily on diet, exercising (#fitsperiment!), and sleep. I finally found time to look closer at some of that data, and in this post, will share some interesting results of my sleep data analysis.