Tag Archives: Self Induced

Tracking Upsets Yields Insight

I find tracking Upsets yields insight as it tells me about the events that trigger negative reactions in me. These things can be immediate dangers or just imaginings I might have. With this insight I can understand some of my behavior. In my first quantified self study I tracked Upsets and learned a lot. I wanted to repeat the study eighteen months later.

Tracking Upsets Yields Insight

I have explored many techniques to reduce the number and duration of my Upsets. I wanted to see if I could measure changes in the source of Upsets based on the work I had done. And I wanted to see if the proportion of Direct and Self Induced Upsets had changed.

A Direct Upset is the result of something happening in the moment like a car nearly hitting me in the crosswalk. Some element of actual danger is occurring in that moment. An Upset is Self Induced when I am sitting in a quiet room worrying about whether my insurance policy is properly paid up. There is no environmental reason for the worry. I am creating that disaster scenario from pure thought.

My Question

Had my Upsets changed source and type in the last eighteen months?

What I Did 

I logged Upsets for 27 days. There were two conditions for me to log an Upset as occurring. The first was if I had a repeated negative thought. The second was I felt a heat in my body that I associated with being irritated or worried.

How I Did It

I set up my DIY Tracker on an iPhone. The entry was a text box in which I would write the source of the Upset. In a spreadsheet I added three categories to each Upset which were Self Induced/Direct, past/present/future, and source.

What I Learned

Work, other people’s actions, a move to a new house and travel were the leading topics that triggered Upsets in this study:

Tracking Upsets Yields Insight

Eighteen months ago the source profile was similar. Adjusting for different category names, I was thoughtful about work and other people’s actions 50% of the time versus 46% in this study. Technology malfunctions moved from 5% to 10% due to a house move that put me in the position of having to set up a lot of new gadgets. I was on the road much less so the percent for travel dropped from 11% to 6%. Overall the categories had not changed much and where they had the reasons were understandable.

The majority of Upsets were Self Induced. For most of the logged events I was sitting in a comfortable environment dreaming up disaster scenarios:

Tracking Upsets Yields Insight

In the first study I had done the percentage of Self Induced had been much higher. Here are the percentages from the three studies:

Apr-14 May-14 Oct-15
Self Induced 77% 62% 66%
Direct 23% 38% 34%

Tracking Upsets yields insight and the awareness that results seems to reduce the amount of time spent dreaming up disaster scenarios which is a good thing.

As in the earlier studies I was more concerned for the future than regretful of the past.

Tracking Upsets Yields Insight

Looking at only Self Induced Upsets shows that the vast majority of my disaster scenarios are anticipating something bad in the future.

Tracking Upsets Yields Insight

Eighteen months ago my Upsets about the past were 16%. I’m pleased that the past Upsets remain a small percent. There is nothing I can do about a meeting I screwed up in the past. Regret is a fruitless exercise.

Scientists may dislike this type of tracking as it is self reported and completely subjective. Data points about thoughts and emotion are difficult to control for and make statistical validity nearly impossible. Wearables companies are wise to avoid it as they would have no market making potential. Measuring thought is very distant from step counts.  I, however,  find this type of tracking hugely useful as it gives me insight about myself. And that is what quantified self is all about.

Sign up for the QuantXLaFont Newsletter
Get our lifestyle tips and studies delivered to your inbox.
Thank you! We don't spam :)

Managing Imagination

Since April of 2014 I have been posting my findings here as part of a systematic way to understand and mitigate Upsets. I logged Upsets as they occurred, measured my heart rate variability during periods of stress and connected types of Upsets to different types of thought.

The first real insight that came from self reporting Upsets was that the majority of them were Self Induced and of those the majority were anticipating future negative events. The fundamental tool we have which is the ability to imagine a future scenario is the source of most of the stress – thoughts that anticipate a negative future outcome.

Another insight is the volume of thought. Thinking I was capturing a high number of Upsets in my reporting was completely blown apart by watching how often my physiology altered based on thought. Was looked at the beginning to be a 5 to 8 time a day volume was actually up to 450 thoughts a day that could potentially cause Upset. And that volume is constant. So any plan that includes eliminating thought is irrelevant. The plan must be based in how I respond to Upsets.

Looking at the lessons learned the core skill to develop is managing imagination. Imagination is our engine of progress, it shows us what is possible. It is also the source of what we believe are our misfires, misalignments and Upsets. Believing too much in imagination immerses us in our miserable misfires. Completely eradicating imagination robs us of our ability to be motivated, plan and progress. Somehow we have to find a middle ground of practical imagination, a place where we see what is inspiring and possible while knowing when to discount those scenarios that are impossibly negative and exaggerated.

Intensity Study Wrapup

The Intensity Study was based on 242 logged events over 24 days looking at multiple factors that could effect the intensity of my upset reactions. In four previous blog posts I have shared the details of Direct vs. Self Induced triggers, Past vs. Future triggers, Movement vs. Stillness, and various environmental factors like water intake.  Here are some summarised thoughts of what I think I saw in the data:

1. The standard unit of a day may be too long for meaningful correlations. Averaging noticed intensity over the day did not yield much against other factors like sleep and activity. I don’t think this proves or disproves anything. It just means that the day as a period of measure is inconclusive in the type of work I am doing.

2. Dreaming up future mini-disaster scenarios is the brain’s specialty and the numbers show it is a rich source of the stress triggers I experienced. If I am going to create some hacks to short circuit stress triggers, I will start with defusing the constant thought stream of future bad outcomes.

3. Movement and stillness consistently delivers a different experience of the stress triggers. When moving there is something in navigation and solving for the locomotion of oneself that pushes aside more distant concerns. Seems obvious, and there are some hacks that I am already considering using that dynamic.

4. Conscious self reporting has its limits. As of 8am this morning I have logged over 3,361 incidents where I noticed myself being angry or anxious. The first logged entry was on 7 Sept 2012. I think as a practitioner of this particular form of logging I can be considered experienced. Yet work with Heart Rate Variability (HRV) monitors show me that I miss a large number of moments when my physiology is showing a stress reaction, and when I stop and notice there is indeed some thought bubbling around down there.

My next study will be with the aid of HRV monitors to see if the tactical triggering of physiological stress brings us to the same conclusions around future scenarios and movement.

 

 

 

More Water Please

Looking for correlations with factors that effect the intensity of the upset reactions over the course of a day I compared the average intensity of different stress states for the day with the following factors:

  • Sleep the night prior
  • Water intake on the day
  • Coffee intake on the day
  • Number of minutes of Paced Breathing work
  • Minutes very active (walking/cardio)
  • How hydrated I was on average over the course of the day

Across these factors I looked at the average daily intensity for:

  • All upsets
  • Direct upsets where the trigger was in the immediate environment when logged
  • Self Induced upsets where the cause was not in the immediate environment
  • Self Induced upsets when Standing
  • Self Induced upsets when Sitting

The was only one strong negative correlation (r=-.43) and that was Water consumption and Self Induced upsets. Coffee intake had a moderate negative correlation (r=-34) on Self Induced and minutes very active had a moderate negative correlation to Self Induced while Sitting (r=-.33). My actual state of hydration had no correlation to upset intensity.

Of interest was that none of these factors had any significant correlation to the intensity of Direct upsets. Water had a weak correlation (r=-.24) to Direct and every other factor was not correlated at all. Direct upsets seem to have an intensity that is related to the environmental factors.

So adding to our other insights we see that controllable factor of water & coffee consumption can help with the category that has the highest intensity & number combination, Self Induced upsets. So it seems that drinking some water and taking a walk might be efficient ways to reduce thinking about future disaster scenrios. But of course, that remains to be tested.

 

Intensity Study – Stillness & Movement

One of the new dimensions I wanted to look at with respect to Direct and Self Induced upsets that I describe in my first post on this study is my physical state when I logged the upset. So using Taplog I created category buttons for lying, sitting, standing and walking and captured those states when I logged the upset. Over the period here are the volumes of triggers based on these states:

Image

 

Sitting and standing are the states that predominate my entries. I noticed qualitatively that when I started walking the simple problem of navigation arose to displace a lot of rumination. This bore out in the numbers. Here is the breakdown of Direct and Self Induced by physical state:

Image

 

Standing and sitting both had an almost equal number of Self Induced upsets. It looked like my mind would wander when being physically still. The types of Direct upsets that arose when sitting were encroachments of space, usually while travelling. Looking at the average intensity by physical state showed that standing upsets were more intense than sitting:

Image

 

So comparing the future and past orientation of upsets I reported yesterday with this data would show that the largest category of stress if I combine number, type and intensity would be standing and ruminating about some disaster scenario that I think may occur some days hence. So if I were to prioritise remedies the easiest would be to notice when I am standing and thinking about some future event to breathe deeply and start walking.

 

Intensity Study – Direct vs. Self Induced

With 242 logged events over 24 days I have some initial results of the current intensity study. I always break the upset events into two categories, Direct and Self Induced. In this study I logged more specifically whether the source of the upset was in the immediate environment. The rule was that I would call it Direct if I could physically see the source. If the source of the upset was not visible I logged it as Self Induced. The result:

Image

 

If you recall in the first study I found 75% of the upsets were Self Induced. The second study showed 65%. In the first study I had seen the number of Self Induced upsets drop as I observed them. The second study’s lower % may be from training myself in the first study. The trend continued in this study of showing a lower percent, though even with training and focus 60%+ of upsets are Self Induced. I can say qualitatively I am dreaming up fewer disaster scenarios.

Tomorrow I will share breakdowns of intensity based on the physical state of lying, sitting, standing or walking.