It’s been a while since my last post. Here are some new things I’ve been doing and reading during this time. There’s a lot to talk about!
On the data collection and analysis side of things, I started tracking new variables including mood, energy levels, sleep/meal duration and quality, continuous-learning activities, ongoing projects, and Church attendance.[1] This data joins twenty-three other aspects of my family’s well-being that I’ve been tracking since 2013. Together the data is giving me a holistic view of our growth, health and happiness across the six dimensions of well-being I care about — Spiritual, Social, Intellectual, Physical, Financial and Environment.
For example, I now have indicators tracking my family’s sleep duration goals over the course of the year (see figure 1.)

A separate indicator allows me to track time we spend at the dinner table. The indicator was inspired by OECD and their chart showing the time spent eating & drinking each day across countries (see figure 2.) It also supports my belief in quality time together at the dinner table.

The indicator tracks the percentage of dinners lasting at least 40 minutes, with a goal of at least 80% each year.

These are just a few examples. I am tracking fifteen more indicators and dozens of time-series charts across the six dimensions of well-being I mentioned earlier. I am also working on a new experiment in the area of stress, anxiety and resilience. I hope to cover this and other aspects of family-tracking in the coming months – stay tuned!
Regarding general news and trends in the area of personal health tracking, digital well-being, personal informatics or, more generally the quantified self, it definitely feels that we are in the midst of a bubble of great promise and hype. Three general observations I have during this period are:
- The digital divide is real. The market for digital well-being / personal health tracking will continue to be constrained by inadequate data skills in citizen scientists.
- Collection fatigue is also real. This applies to the commercial wearables industry. In my opinion, these companies are only stressing out their customers; weighing them down with low-value data collection tasks. Without a clear path to transform raw data into truly useful and actionable insights, customers will continue to be underwhelmed and dissapointed.
- This creates a big opportunity to provide users with actionable well-being insights without overburdening them with data collection, or the need to acquire sophisticated data science skills to make sense of the data.
[1] My self-tracking projects are powered by ostlog – an open-source Personal Well-being Library.