We Never Fight on Wednesday

Project Infobox
Self researcher(s)	Paul LaFontaine
Related tools	Taplog
Related topics	Mood and emotion, Stress, Anxiety and Anger triggers
Builds on project(s)
Has inspired	Projects (0)

Show and Tell Talk Infobox
Featured image
Date	2014/05/11
Event name	2014 QS Europe Conference
Slides	We-never-fight-on-wednesday.pdf

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We Never Fight on Wednesday is a Show & Tell talk by Paul LaFontaine that has been imported from the Quantified Self Show & Tell library.The talk was given on 2014/05/11 and is about Mood and emotion, Stress, and Anxiety and Anger triggers.

Description

A description of this project as introduced by Quantified Self follows:

When Paul LaFontaine was a soldier in 1991, he was very alert and quite calm. However, in 2006, after a negotiation he felt physical panic. So he was interested in how he reacted to certain situations and devised a study to capture his reactions. In this video, he talks about how six months of tracking mood alongside events, time, and people gave him some surprising lessons about conflict and other topics.

Video and transcript

https://vimeo.com/101714346

A transcript of this talk is below:

Paul LaFontaine We Never Fight on Wednesday

So in 1991, I was a soldier, and I was in combat and I was very alert and I felt quite calm. In 2006, I was in Istanbul in a negotiation and one comment was made and I felt physical panic. So I was always interested in how I reacted to certain situations, because there didn’t seem to be any logic at all. So I devised this study to capture how I reacted to specific situations, not really mood tracking but my reactions. So I set up this study over a six-month period. It was pretty basic and I used an app called Taplog, which is an android app and you can configure buttons and categories and it captures your time and your date stamps. And it’s a very malleable tool and really easy to use. So if I was doing self-reporting, I would just literally hit a button every time I had something that I wanted to log. But most importantly, this is an app where you can export to Excel. So very easy to quickly download it into Excel, and begin to play with the data and look for correlations and patterns, which of course is very important to I started logging my reactions to certain situations. I looked really to anxiety and anger and what I did I trained myself that when I felt something in my body I would log it, or if I had a recurring thought like I need to mail that letter, I need to mail that letter, I need to mail that letter, I would then actually log that as well. Here’s my log entry volume of the six month period, about 720 logged events. You can see the volume actually went down over time, so it started about six a day in the beginning and went to one per day and it never went below one per day. Why did that occur? Well I think qualitatively I was feeling less stress. I could actually feel myself less stress in certain situations. But also, we have to factor in some exhaustion in it, because it’s self-reporting. It was a lot of me actually taking actions, so I kind of got tired over it over time that was part of it. Here are the categories, 50% of it was work, 26% of total was me being angry or upset about my co-workers, 24% was me worrying about what they thought about me; that was 50% of worrying. 14% was health that could be a toothache or wondering if I was looking fat here on stage. 11% was travel, I travelled almost full time for my work, so little things like was I going to get on a plane or not, and I’ll talk about travel in the second. So this was 75% of my report was in those categories, but what I found in six months was I did not get upset ones with my wife on a Wednesday, so I proudly announced to her we never fight on Wednesday and it became our special day; so who says Quantified Self is not romantic. The fact that I was barely home on Wednesday we will leave aside. This graph really surprised me when I looked at day parts, because I would have expected to have more upsets in the middle of the day, but in fact it heavily loaded towards the beginning of the day specifically around my co-workers and the red box that you would see pop up here is actually the work hours. So if you actually look at when I was getting upset. It was mostly before the date even started. I did not expect this at all, because this was not about my reaction. What this was about me getting up in the morning and beginning to anticipate the day, and in fact, instead of me as I thought at the beginning of this study, reacting to the way that people were treating me, it was me actually, the creator of the stress. And it would start as soon as I got up, and went all the way up until work and then it went on when I visited my co-workers, so they are stress curves probably looked a little higher in the middle of the day. Travel, really important category, and looked at that as well. Mostly I travelled basically once a week for work, so that would be to plane trips and I’ll show you the data in the second on how many trips I took, but a big part of my life and a big part of my stress. What you are going to see next is a graph that actually shows in red the number of trips I took and it was no less than eight a month. And then in blue the number of upset incidents. So you can see that it dramatically dropped over time which was really curious to me and I would not have expected that. So I went back into the data to look at what was it that was upsetting me about travel. Very little was in the plane or the airport. It was all me anticipating some future event. Am I going to be late, am I actually going to miss my flight, is my bag not going to have room and is this person not going to do this or that or the other thing. So again, like the coworker it was mostly me anticipating the future and not the actuality. So my original question was is there a way I can observe my reactions and is there something about my reactions that I can learn about that. But in actuality what I found was the vast majority of my stress was coming from me anticipating some disastrous scenario in the future and this was not what at all I expected. So of course I wanted to dig into that a little bit more and I basically broke it into two categories; I called it direct so it coincided with my calendar, so I went back and relabeled all of the entries as direct if it happened right in the moment. And I just called it self-induced if I was just sitting in my living room and just suddenly started stressing about something, because I wanted to see what percentage of each and here it is. 77% of my stress or my reactions were the things that I was just dreaming up in my own head; the majority of my stress was completely self-induced. I noticed from the travel I reduced the observed instances of being upset so I wanted to see the effect of observation on both categories. So I went back in and actually looked at the number across the whole six month by direct and self-induced and got the most surprise of all is that the direct remained relatively constant, and remembering that you have to adjust to the fact that the volume went down over time. But actually self-induced went down dramatically and this was in a variety of categories. So the act of observing actually seemed to be dropping self-induced. So was I changing my reactions? No, that actually wasn’t it. What I was doing was teaching myself to not worry about the future as much by simply logging or observing. Well of course that was a great start and it just got me even more curious, so I did a little mini study after that, so not a lot of data, but I went back into the same thing and added intensity. So now how intense was my reaction and started logging by direct and self-induced directly to take a look at that, and here’s what I found. The log entry volume was higher because I set my Fitbit silent alarm to remind me to log more, so I got about 15 a day versus anywhere from 3.3 was my average in the other study. So it was only a couple of week study, but it was around 250 logged incidences, and in fact the intensity of my self-induced reactions was higher than direct and the standard deviation was actually smaller, meaning I’m more predictably reacted when I was stressed out based on my own imaginings. The effect of exercise during that period because I began to bring in my Fitbit and some other data is that exercise negatively correlated with intensity, meaning that on those days of exercise my intensity on average went down which is not a surprise; exercise helps. I was in a few different places with different temperatures, so temperature negatively correlated when on self-induced, which meant that I was dreaming up less scenarios when it was warmer. When it was cooler I was coming up with more disaster scenarios, again, a small dataset but I thought that was interesting. And it changed from previous state meant the distance from where I had previously been to the next state it actually positively correlated, not strongly but positively correlated meaning that when I did self-induced I was just getting myself a little bit more upset pretty consistently, where with the direct I would just react in accordance with the situation. So my conclusions from the two were actually two types of stresses I experienced; the direct and self-induced. Exercise helps across the board, and actually logging helps reduce that disastrous scenario mentality which is 77% of the stressors in the most intense. You can check me out in my blog as well as my Twitter as I continue to push along these lines.

I’m Paul LaFontaine and now I’ll take your questions.

About the presenter

Paul LaFontaine gave this talk.