Ran across this study done by Kira Newman. She tracked her moods for a month using an alarm each hour. In her report there are comparisons, correlations and good insights. I commend Kira for the work she has done which has great detail. Her insight that her stories effect her happiness is an important one.
When it comes to the “science” of Quantified Self we should continue to improve our rigor, and we should not be afraid to try new things. I found myself very rusty on statistics and had to go back to the basics just to understand how to get a correlation out of an excel spreadsheet. It was painful, and after some hours on Khan Academy I got myself back in the game a bit. And I am having a lot of fun.
Thanks for the inspiration Kira and on we go!
Here is a call I had with USAA regarding a change to a policy. During the call I wore a Garmin heart rate monitor, recorded the call on a digital audio recorder and had Taplog open to record what I was thinking. There had been some confusion on the issue I was trying to resolve as it involved multiple policies, multiple states and different types of usage on a second car. I had called before. I called with the goal of consolidating coverage into one policy. You see the heart rate profile here.
My resting heart rate is between 65 and 72. So we see elevation until resolution during a call that lasted about 26 minutes. In the beginning the rep hesitated and asked me questions as if there was a problem. That spiked me to near 94bpm. Throughout the discussion of the problem is bounced along in the high 70’s and low 80’s. As it comes toward resolution the trend is downward until final resolution I return to resting. Interestingly, the highest spike occurs at the end when I try to be sociable with the rep and attempt to get a laugh.
So I achieved my goal in the discussion with a heartrate profile that showed me elevated throughout. This is part of the base case series from which I will begin applying techniques from Getting More to see if there are changes.
Part of the 800 number project is to understand how my emotional state correlates with achieving my objectives when dialing an 800 number. They key to the exercise is to maintain focus on the desired outcome. One approach is to maintain a calm demeanor and reach out to the other person as a human being. This is usually achieved with direct conversation and covered in great clarity in Stuart Diamond’s Getting More.
Here is an indirect example of how to do it, and after the laugh it is actually a stroke of genius. A few pointers from the Getting More arsenal of techniques:
-The persons involved never say they are not going to pay the bill
-They acknowledge the person on the other end (Edy Mills)
-Unrelenting persistence. The company realized this was never going to end and it was easier to simply walk away.
Brilliant on all measures. Worth the read.
I used to think happiness was an event. Something that would occur after I acquired something or got something done. I believe external events would cause happiness. But my exercises in Quantified Self have revealed that as in statistics, when it comes to happiness correlation is not causation.
When certain conditions are in place happiness is more likely to occur, but those conditions do not cause happiness. If I buy that new car it might contribute to a variety of conditions that elevate my mood, but acquiring the car does not create happiness.
Unlocking these relationships is the purpose of my work in Quantified Self.
A nice article on why Nike shut down its Fuelband effort that calls the move “an indictment” on wrist wearables. I think the indictment is on a magic bullet that device manufacturers are keen to create, market and dominate with sales. In the article there is the statement that Apple will come out with the ultimate device, but it is not likely that they will create the magic bullet either.
This blog is about Quantified Self and experiments that can be done with a variety of devices and methods. What is hardest is thinking of the desired outcome and designing the activity. The tracking is easy. Tracking devices are abundant, methods to set goals and design activity are hard to find.
Real life changing effect of wearables will come from accepted methods of combining data with activity. And this space of “try this and watch” is the true open space in the Quantified Self arena.
At a teaser from my upcoming speech at the 2014 European Quantified Self Conference I have looked at the relationship of temperature to average intensity of upset reactions over the course of each day. The warmer the temperature the less intense the upsets if they are self induced – meaning if I am imagining some disaster scenario then my imagining is less intense when I am sitting on the beach!
However, there is no change in “direct” reactions like someone almost hitting me with a car. So I get just as upset almost getting hit while walking from the beach as I do when walking in snow boots from the ski slope.
The method here is that I captured intensity of my reactions for a period where I was travelling in San Francisco, London and Abu Dhabi. Good temperature ranges to sample from! I took the intensity data via Taplog and exported it to excel, then manually added weather data. Using a Pearson R function I determine the correlation for Direct and Self Induced reactions.
Of course weather does not cause reactions, they simply have a relationship. For purists, my reaction intensity may have caused the weather. If I ever confirm that hypothesis I will report it here.
Have been crunching numbers and calculating Pearson R correlations between different types of upsets based on a further data set I gathered in March. During that period I did periodic “mood gathering” by setting an alarm on the Fitbit and entering how I felt from 1 (relaxed and calm) to 10 (palpable rage or fear). I also logged upsets with their intensity so I got around 15 to 25 events logged a day between the alarm triggered entries and the noticing entries. The resulting data set has led to some interesting insights.
First, there is a strong positive correlation (r=.66) between my upset score across the day and the amount of sleep I had the night prior. That means the more I slept the more I triggered the next day. A surprising result that needs further study as qualitatively I feel better when I sleep more.
There was a strong negative correlation (r=-.62) between my upset score daily and the amount of high intensity exercise. That means less upset on days I exercised. This makes sense as my qualitative experience is that exercise relaxes me.
I looked at each hour of the day (above) to see if there was a clear pattern around day parts, but it does not appear that I am a “morning” or “night” person by mood level. The intensity seems to gradually drop over the course of the day. When I pulled out the 1300 (1pm) logs you see below for 21 different triggers logged during that hour there is no clear pattern on the upsets:
So there does not seem to be a consistent bad hour of the day nor a corresponding happy hour. I have crunched additional relationships for a future post, and once all this is put together I will bring another video. More insights to come.
I have been considering new categories for the current study and specifically the concept of “self induced” versus “direct” triggered upset reactions. As I looked at the heartbeat work and the upset trigger work two categories emerged. In moments where upset was triggered I was either remembering something or anticipating something. In both cases I was creating a picture in my head that formed the basis for a narrative. The activities are the same in both cases though one is looking back in time the other projecting forward. So I combined them into the category Memticipation – the state of creating a picture and a narrative about the world around me that induces an upset feeling.
After doing the first two stress studies I have determined that a large source of upset is when I interact with operating processes that do not work as I expect them to. Restaurant greet and seat. Airline customer service. Airbnb reservations and experience. So I have devised an experiment to see if I can reduce my upset reaction in those situations by going to the process that has a rich minefield of potential upsets – the toll free 800 number.
In this experiment I will log calls to 800 numbers and measure the following:
- During each call I will use my Garmin heart rate monitor, Taplog app and an audio recorder. I will conduct the call on speaker phone. During the call when I feel a judgement or anger I will use Taplog to record the time stamp. Aftwerward I will look at heart rate spikes, Taplog time stamps and the recording of the what was happening in those moments to get a snapshot of the key moments in the call.
- For five calls I will not use any technique. I will call using my normal preparation and record the results.
- For ten calls I will use the techniques for negotiating with large companies outlined Getting More by Stuart Diamond. I have read the book and used some of the techniques, but I have not systematically applied the method.
- At the end I will group the key moments by call and see if there was a reduction in stress moments and look for other patterns.
Of course, I will bring back the results by video for you here.