Tracking sleep and meal duration

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.)

sleep
figure 1 – tracking percentage of sleep lasting 7 hours for adults and 9 hours for kids over the course of the year

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.

Eating-and-drinking-550
figure 2 – OECD Time spent eating and drinking

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

dinner
figure 3 – Percentage of family dinners lasting at least 40 minutes

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.

Author: Sergio

Since 2013, I have been experimenting with family data science – or the process of drawing deeper understanding and insights to help my wife and daughters grow, stay healthy and be happy. I am just a curious dad who is convinced that a little 21st century IT along with a stream of the right data and analytics can help reinstate a healthy dose of household conscientiousness in between the joy, pressures and chaos of everyday family life.

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