Winslow Strong of Biohack Yourself (check out his awesome blog, by the way!) recently posted a great question on Quantified Self Facebook page, asking about ways to quantify restraint. This is when I remembered about my attempt to track willpower in March that was partially inspired by our conversation with Hiren Patel of Becoming the Best (another awesome blog!). My method for tracking willpower (self-restraint/self-control) was rather simple and straightforward.
Instead of measuring some subjective “willpower” construct, I decided to operationalize it by tracking how often I was “tempted” to break certain routines, and how many time I would succumb to those temptations. I decided to focus on the following routines:
- Diet: eating healthy
- Fitness: going to the gym, biking, or walking during lunch (whichever was scheduled for that day)
- Finance: restraining from unnecessary expenses
- Learning: sticking to my evening Rosetta Spanish and programming lessons
To track temptations and failures, I set up the following trackers in my rTracker log (you can also use Track-and-Share app) for all three dayparts. The rest was easy: at the end of every morning, afternoon, and evening, I would check off the appropriate boxes if I was tempted with breaking the routine and if I broke it:
If I sum up all the temptations and failures for every day, this is how my internal struggles in March would look like (blue bars represent number of temptations on that day, red bars – number of failures):
One way to quantify the “restraint” or “willpower” is to compute ratio of total number of failures to total number of temptations, subtract it from 1 and convert to percentage. For example, 0 failures would translate to 100% willpower. The 2 failures out of 4 temptations would translate to 50% of willpower; and total succumbence to temptations would result in willpower of 0%:
Armed with this metrics, you can delve into deeper analytics, like correlations with stress, mood and sleep. Perhaps, including more routines (going to bed on time, brushing teeth, etc.) could further improve measurement. Overall, I believe this approach has a good potential. What do you think?