To build a method to explain the cause for changes in mood, we need to start measuring. This post is about what to measure, and an idea on how to do it.
Setting the level of ambition
So let’s set the level of ambition. If we really ought to measure everything, there wouldn’t be any time left to actually live life. On the other hand, if we don’t measure enough, there won’t be anything valuable to analyze, or we might miss the most important part. This will be a fairly ambitious approach trying measure as much as possible of the things that seem relevant. Yea pretty vague, but in general, if it would take over life that would be depressing, and then you need to measure how much energy you put into measuring and make that a variable, and then that would be an endless chain of measuring the measuring. So, a decent amount of measuring seems optimal.
Grouping what to measure
There are different levels of what to measure, and some kind of grouping is preferred. Here is the wish list of what to measure, divided into five groups.
- What is done: How do I split my time between different activities (e.g. “I worked 8 hours last thursday”)?
- Time-stamped lifelogging of activities and location each day, including sleep.
- Time spent on smartphone and computer, preferably with specified activity.
- Amount of movement each day, both when exercising and just moving around.
- Amount of music listened to.
- How it’s done: What is the subjective or objective measures of the activities I perform (e.g. “I felt the stress level at work today was 7/10” or “today my lunch was non-vegetarian and contained 30% fat”)
- Objective sleep quality (times awake, times restless)
- Subjective sleep quality
- Workout intensity
- Food: when and what I eat, how much sugar, fat and protein, vegetarian or non-vegetarian, cold or hot, organic or non-organic, amount of dairy and gluten.
- Drinks: amount of water and other drinks consumed each day, including coffee and alcohol.
- Perceived stress level and other subjective measures at work
- What type of music is listened to
- Quality of social interactions
- How the body responds: How well is my body functioning, objectively and subjectively (e.g. my breathing rate has been calm today)?
- Level of stress in the brain
- Balance in the autonomic nervous system (Heart rate variability)
- Breathing pattern
- Weight and body fat
- Bowel movements (yea, not the most appealing measurement, but quite an important factor).
- Heart rate when exercising
- Blood glucose
- Cognitive capacity
- The external influences: What external factors are affecting me (e.g. “Today it was 9 degrees celsius and sunny”)?
- Weather
- Significant events happening, positive or negative that I can’t influence
- How do I feel: The experience of the present moment, in terms of mood, energy etc? This is slightly overlapping the body response group, but since this is the value that everything should correlate to, it deserves a category of it’s own.
- Mood
- Energy level
- Perceived coping with difficulties
- Other measurements of wellbeing
So that’s quite a list, and it might be impossible to measure all of it. Let’s see this as a working hypothesis. Below I’ll have a closer look into the five categories, the choices of measurements and initial thoughts on how to measure it.
Measuring what is done and external influences
Regarding measuring time spent on various activities over the course of the day, most of this has to be measured manually by entering when shifting from one activity to the next. There are a lot of life logging tools out there that let you log everything you do either manually, automatically or in combination, such as Saga, Instant, Optimized and Hours. I’m assuming there will be some trial and error to find the optimal way of measuring it all. Surely the hardest part here is to determine the level of detail. Is “work” too blunt a category to be useful in an analysis, and is “talking to my colleague Johan whilst drinking coffee” too detailed? Time will tell.
Some activities such as time spent in transit, places visited or time slept can be logged automatically with the apps mentioned above or activity trackers such as Fitbit or Jawbone. They are also pretty handy when it comes to tracking movement.
When it comes to time spent of smartphones and computers, there are also tools for this, like RescueTime and Moment. However, using Apple products, there are no options to really get an analysis of what has been done on your smartphone, just the time spent. A preferred split would be to see how much time is spent on social media, entertainment and work.
Connecting to last.fm you can get reports on what music you listened to each day, also with a split on artists.
Weather history is easily available, or can be logged in apps. When it comes to significant events, I’m hoping to find some way of quantifying this by analyzing the news.
Measuring how it’s done
The beauty of the new activity trackers are that you can get a range of analysis, including quantified sleep reports, and combining this with a subjective measurement of your sleep quality will provide both a good snapshot of the night, and a possible analysis of the discrepancy between the objective and subjective measures.
When it comes to food and drinks, the app store is overflowing with alternatives for measuring what you put in your mouth.
For the subjective measures, such as quality of social interactions or perceived intensity of workout, this will also be registered through some sort of life logging app, such as Optimized.
Measuring feelings and how the body responds
Breathing pattern, heart rate variability, heart rate and brain activity can be measured with wearables, such as Spire, pulse bands and Muse head band. Weight and body fat can be tracked with the new versions of old fashioned scales. And well, bowel movements…we’ll just see about that.
Measuring feelings and energy levels; this will probably be the hardest part, and even though there are lots of apps and research, finding what to use and how to use it will take some effort put into it.
So let’s start logging. Updates and reviews will come, and next up is thought on how to create a good study design to measure the cause and effect.
