Tag Archives: DIY Tracker

Are To Do Lists Really Useful?

I was grinding through my daily “To Do” list, moving and consolidating the various seemingly urgent items, when I wondered if such a practice was really effective. I was spending a lot of time tracking what needed to be done on these lists. I was using online tools, notebooks, and scraps of paper. But I had never examined the practice itself and was wondering. Are To Do lists really useful?

TODOLIST

These lists played a significant role in my day. I would start with a list early in the morning and use it until evening.  It seems we all have a complex relationship with our To Do lists. Psychologists study why we use them, and why we don’t follow them. In the tradition of Quantified Self, I decided to study my own relationship with my To Do lists.

My Question

Was my practice of making and following a To Do list really useful?

What I Did

Over the course of 21 days I logged my To Do’s as they arose. I captured my frame of mind as I first thought of the item and my feeling after I had explored it. I also logged what would happen if I did not complete the item, and what I thought was the underlying goal behind the item. I call these underlying goals Source Code Stories. I was looking for Source Code Stories that were driving the impulse to do something. For example, if the To Do was to get a report to my colleague, the Source Code Story could be that I wanted to be seen as responsive.

How I Did It

I used a Google Form and my iPhone to create a mini-survey. The format was similar to my Upset log that I have described here before. When I felt the urge to do something and log it on a To Do list, the first entry on the Form was my state of mind on a scale of 1 to 5. The next entry was the item. The third was what would happen if I did not complete the item. The fourth entry captured what I thought I was trying to achieve, which was the indicator of the Source Code Story. The fifth and final entry again rated my state of mind from 1 to 5. Using this simple survey I was able to capture 105 To Do impulses over the course of 21 days.

What I Learned

My habit of creating To Do lists was not really useful. The majority of impulses to get something done came from a stressed state and the impact of not following these impulses on my situation was negligible. My To Do lists were capturing non-essential impulses that were not driving big outcomes.  What was least useful is the existence of the list kept dragging my attention back to these small matters, robbing me of attention of being available for more creative, larger outcomes.

Looking at my state of mind when To Do’s arise, I found that 79.1% of the time I was in a negative mental state. That meant I was worried or in a state where my mind was racing. Only 20.9% of the time was I in a positive state considering creative things to do. Here is an image of my state during To Do’s:

Are To Do Lists Really Useful

Looking at what would happen if I did not take action on the To Do’s, I found that nearly all of the recorded To Do’s had no immediate impact on the situation if I did not do them. Over half, if not done, would have no impact at all. For a portion eventually I would be reminded to do the item by another person or I could do it later. Here is the breakdown of results if I did not pursue the To Do’s:

Are To Do Lists Really Useful

Only 3 of the 105 logged impulses would result in something creative and interesting that I was initiating coming to a halt. That meant that the creation of the To Do list was not driving big, creative outcomes at all. It was rooting action back in the long list of stress based low level tactical activity.

Looking at my state of mind, when I felt I had an obligation to another person my average start mood was 2.35. When the To Do was a mechanical item like getting a car washed, the average start mood was 2.9. There was a statistically significant difference in state of mind between those To Do’s that were obligations to a person versus getting something mechanical done.

This tied into my Source Code Stories. Looking at the most prominent of these stories, I found that having people appreciate my effort and seeing me as knowledgeable were the most numerous. Other stories like being organized or balancing my checkbook lagged far behind.

Looking at my Source Code Stories and counting the number of To Do’s by type, I saw that despite that fact that connecting with people had a disproportionate importance for me, 63% of my To Do lists were tactical, mechanical items. Are to do lists really useful? I’ve found they aren’t for me.

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Part 2: Takeaways from pre-workout caffeine’s effects on performance

Post by: Tim Hanrahan

About 6 weeks ago, I came to a realization. I had been trying to drink coffee 30 minutes before a workout based on some hearsay and research to confirm its positive effect… but I had never been tracking my pre-workout caffeine’s effects on performance. I thought I was feeling good, but sometimes I didn’t really feel any change. How can I know for sure? And because I do different forms of workouts at different times of the day, what’s the best combination of variables for the highest boost?

That’s what I was intrigued to find out and I tracked and reported my initial takeaways at the end of August. The summary: I found that drinking coffee 30 minutes before a workout does in fact give me a boost, but it varied between how much of a boost it gave me. Going forward into September, I wanted to hone these results in even more and test a few more variables.

Below is a breakdown of my process, results, and new takeaways.

 

Process:

I again used Apple Health to track the quantity and frequency of caffeine consumption. By the end of my last tracking period in August, I had become a 3-cup a day coffee drinker, primarily using my trusty Kuerig and K-cups that contained 150mg of caffeine.

I also used QXL’s own DIY Tracker to gauge my feelings after a workout and analyze my performance. I was extremely disciplined to record my results and in general reflect about my fitness. I was of course hoping for that “Very High Boost” and the results began to show a pattern after another month tracking my progress.

pre-workout caffeine's effects on performance
My custom survey to rate how big a boost the caffeine had on my workout, using the QXL DIY Tracker.

 

Results:

As part of my initial tracking, I made sure to note when I was having coffee before working or with breakfast in the morning. It was good background information to have, but after 4 weeks, I began to understand my daily routine and didn’t feel the need track these instances. This decluttered my data to only show the times of my workout routines and my boost rating from there, noting on the side the days I had 2 or 3 cups of coffee.

Having said that, here’s a look at my data of my reflections on the caffeine’s effects, illustrated through the DIY Tracker’s automatic recordings to a Google Doc.

pre-workout caffeine's effects on performance
An overview of my September data, focusing more on just the caffeine intake before a workout.

 

Takeaways:

I believe I have found my sweet spot.

When only focusing on my desired “Very High Boosts”, the common element was that it came after a 3rd coffee, before I played basketball at night around 8pm. During these instances, I felt a noticable change multiple times. I was playing with a sharp attention span and ability to make quick decisions, essential for being a point guard. I play recreationally in competitive leagues and had some of my best games in the past 2 months with these pre-workout variables lined up. In fact, drinking a 3rd cup of coffee 30 minutes before playing basketball led to an 89% chance of getting the optimal “Very High” boost.

To also arrive at this conclusion, I compared my “3rd cup of coffee” variable to my performance playing at the same time (8pm) but having only 2 cups of coffees during the day (1 of which, 30 minutes before). I also included my performance after doing a Pilates workout, which was almost always after my 2nd cup of coffee during the day. I noticed there was a high propensity for a boost, whether slight or solid 79% of the time, but only the optimal “Very High” boost 14% of the time.

Conversely, I compared the boosts to a few morning pilates workouts I did during this time period too. I failed to really feel more than a slight boost, providing the first piece of evidence to me that I’m just not a morning person (as my routine also dictates now). This inspires me now to research… What is the cummulative effect of caffeine throughout the day as more and more is consumed?

Finally, I was also able to quickly answer one of my other questions from back in August. I wanted to test the variable of consuming more caffeine than usual during the 30 minute pre-workout period and see how that would affect my performance. I already felt comfortable with my K-cup amount, but I had to see if even more would be even better.

pre-workout caffeine's effects on performance
I tried a large Dunkin Donuts coffee (20 fl. oz, 244mg caffeine) because I had to play in a tournament in the morning. I felt the jitters and it affected my game. Too much caffeine?

Au contraire. It actually made my performance worse. The added caffeine made me too antsy and anxious. I actually was conscious of quick, edgy, and fidgety movements that translated poorly on the court. I played like I was trying to do much and go too fast instead of letting the game come to me. In basketball, just like in consuming caffeine, or life in general, it’s all about finding that balance. I’m glad it only took me a couple of different gamedays (and losses) to keep my caffeine intake in moderation. Sometimes it means going too far the other way to better hone in the optimal place along the spectrum.

It took 6 weeks, and some untracked experiences before that, to A.) confirm my research and hypothesis that caffeine 30 minutes before a workout positively impacts my performance, and B.) find the right balance of how much caffeine both at the time and throughout the day yields my optimal boost for best performance. It’s a gratifying point in my journey: to understand myself even more to gain a better chance to achieve my goals on the court. That’s what QS is all about and that’s what you can do too. Everyone’s different, so you can create the DIY Tracker to help you follow whatever passion you want to pursue too.

pre-workout caffeine's effects on performance
This was me, but playing basketball. This could be YOU: rock climbing or _____________.

Realizing 10K steps walking isn’t enough (for me)

Guys, I have to admit: this wasn’t a great week of exercise for me.

I was attached to my computer the first three days of this work week. I otherwise blamed a sore ankle and other family and friend commitments for not hitting the gym at night. It happens. But this week made me realize a change is in store.

I can’t be satisfied with walking 10K steps a day as a substitute for real cardio and think that I’ll maintain shape.

One metric that helps me conclude this: I gained 4 lbs in this week of general inactivity and none of my usual cardio. I thought I would be able to maintain, especially after a day where I literally went on a scavanger hunt through Chicago! There was a lot of walking amidst public transport, but I looked at the data afterwards and didn’t even arrive at 10K steps for the day.

10K steps walking isn't enough
84% of my total day’s steps were from a scavanger hunt through Chicago. (Data via Moves)

Do you ever feel that after a long 20/30 minute walk you got your workout for the day? That’s how I felt after my walk around Lincoln Park. Because I know the area so well, I can visualize the distance I covered and embellish it to be longer than it actually is. As you can see below, it’s only 1.4 miles.

10K steps walking isn't enough
My longest walk of the day — just 2K steps over 28 minutes.

Reflecting on this now, I remember feeling satisfied both during the above walk and after the scavanger hunt was done. My friend, and QS expert Mark Moschel, can attest: we went on the scavanger hunt together and I remember telling him “I feel kinda good, we got to walk around the city today.”

I was a little bit tired, but certainly would have had enough energy left for a workout after some rest. I didn’t push for it though because I thought for sure I walked over 10K steps already. As I’m finding out, I didn’t even reach that standard and even if I did, a few days a week of this amount of walking is not enough to substitute for little to no cardio.

Just today, in tracking my more typical work day, I arrived at the same conclusion. My longest walk so far has been 16 minutes, covering nearly a mile of downtown Chicago.

10K steps walking isn't enough
My longest walk so far today. Again, it looks longer and feels like more steps than it really is.

Since I’ve gotten settled back home after my trip this summer to San Francisco, I have arrived at the same takeaway I initially gathered out in the Bay. As I detailed here, I averaged about 7.5K steps a day for my trip, typically struggling to reach 10K with the mindset to walk more and explore the city. Likewise to this smaller sample size, I gained weight over 3 weeks given this activity combined with limited opportunities for cardio.

***

I hope by now you can take something out of my experience and apply it to yourself. But that’s the last point I want to make: for you.

I still have dreams of regaining my peak shape from my college years and still want to play basketball in competitive leagues for another few years going forward. For that type of athletic competition, I have to be in better shape, simple as that.

My conclusion is that 10K steps a day, though the standard healthy zone, isn’t enough. For instance though, 10K steps/day for my parents (in their 60s) is an amazing goal. That’s the beauty of what QuantXLaFont is setting out to achieve. Everyone is different and responds different to cardio, nutrition, sleep, you name it.

 

Up next: Give the DIY Tracker a free download and join me in tracking your own progress. For me, I intend on rating my physical activity and energy at the end of each day. I’m hoping the results will further drive home my conclusion and give me daily reminders that I’m still far away from my goal, whether walking or running. And with that… I’m going to hit the treadmill tonight!

10K steps walking isn't enough
Create your own QS tracker, which automatically records your resposnes in a Google spreadsheet, here.

BONUS: I also plan to use the data from my Chicago tourist scavanger hunt as part of a future follow-up with my past step count writeups: SF and at Lollapalooza. Stay tuned, looking forward to it!

Daily Energy Curve: Blue Mondays

I’ve been enjoying debunking my own cherished stories about my Daily Energy Curve and I went after a good one about the restorative power of the weekend. I always thought that I had a fresh start each Monday after a weekend of rest. I thought each Monday I was like this guy, ready to get going and make it happen.

happybusinessguy

 

I was curious about this because I would assign work to either Friday or Monday based on how stressful I thought it would be. Given my story, I would move the tough stuff to Monday thinking I was more rested.

My Question

Was I more rested, awake and ready to go on Mondays vs. Fridays?

What I Did

I captured how alert I was and how much stress I was feeling eight times a day for 25 consecutive days. I then compared Monday to Friday’s in terms of mental alertness and stress.

How I Did It

I set my alarm so it would alert me eight times a day. When the alarm went off, I used my DIY Tracker on my iPhone.

IMG_0112

 

The DIY Tracker captures a score of 1 – 5 on my alertness and stress level. After 25 days I took the data generated and cut it by Monday and Friday, doing a TTest comparing the two days.

What I Learned

I was no more mentally alert on Monday than I was on Friday. The TTest on Mental Alertness showed that there was no significant difference between Monday and Friday.

 

Awake Mental Alert Stress
Friday vs. Monday 0.10 0.50 0.04

 

Stress, however, was significantly higher on Monday than on Friday (p = .04). This made sense as I was moving tasks to Monday for no real reason other than my story about being rested. I have to conclude that I was overloading my Mondays as a result. What a lousy way to start my week.

Another story I had is that I was more alert in the morning than I was in the afternoon. I had even organized my day so that I would do my heavy lifting mental work in the mornings. Turns out that was wrong. Looking at the entire data set and comparing morning to afternoon, not a single measured dimension was significantly different.

 

Awake Mental Alert Stress
Morning vs. Afternoon 0.23 0.22 0.72

 

So combining the two, I think I was generating my own Blue Mondays by believing these two stories. I would try and shift all my hard work to Monday mornings, and the result was not better output, just more stress.

I will look to spread out the work more evenly and compare that to this baseline. At the very least, I will look to try and make Mondays less hectic.

 

Exploring caffeine 30 minutes before a workout

This is a guest post by Tim Hanrahan, Editor-In-Chief at Gowhere Hip Hop.

before a workout

 

 

Earlier this summer, I was put on to a pre-workout strategy that I have since adopted: drinking coffee 30 minutes before a workout.

A friend had suggested I try it, knowing that I love coffee and play basketball when I can. He provided this Men’s Fitness link to kickstart my own research, and even this month, I later found a recent, more scientific and detailed article on BodyBuilding.com.

Heading into the test, I made drinking a cup of coffee 30 minutes before a workout a daily habit (or a daily habit on days I workout). I didn’t have any data yet, but I felt internally that it was giving me an extra boost. These last 10 days were the first time I decided to track it.

 

Some background:

I’m an active exerciser and a daily coffee consumer already. I always have 1 cup of coffee with my breakfast or by lunch at the very latest. I usually have cup #2 between 3 and 4 in the afternoon and proceed to do a daily 20 minute stretching routine, followed by a 30 minute pilates routine at home (3-4 days/week). This was a great first week to track the caffeine’s effect because I was preparing for a 3-on-3 basketball tournament and played basketball 5 times in 7 days. In fact, the experiment began on Sunday, August 17th when I was inspired to go to the gym late that night and shoot around. I came straight from a movie and did not have a chance to drink coffee before going. Given the situation, and the general fact it was late at night, I felt extremely sluggish.

For the purposes of this test, I consumed the same two brands of coffee K-Cups (Starbucks Breakfast Blend & Dunkin Donuts Original Blend), each containing 150 mg of caffeine per cup.

 

The data:

I used both Apple Health & QuantXLaFont’s free DIY Tracker to record my caffeine intake and my observations of its effect. Both were conveniently on my smartphone and the DIY Tracker allowed me to customize my observations and essentially create my own rating system.

before a workout
A graph of my caffeine intake for the last 7 days of my test, using Apple Health.
before a workout
I manually inputed the data on Apple Health while I waited for each cup of coffee to brew.

The graph and data already illustrate a few takeaways. One of the more general ones was that these were the first couple of weeks I upped my coffee intake to 3 cups/day. I have been steady at 2 cups/day for the past year-plus. I started to feel I needed a morning/afternoon/evening routine on days I played basketball at night.

That made it easy to visualize when I played basketball. I usually had that 3rd cup before playing just after 8pm at night. Over the weekend, I only had 1 cup of coffee each day. But one of those days was our 3-on-3 tournament that started at 10:30 in the morning.

before a workout
My custom survey to rate how big a boost the caffeine had on my workout, using the QXL DIY Tracker.

I made sure to be diligent and record my observation after I finished my workout using the DIY Tracker. It was easy to tell if I still felt sluggish, had just enough boost to maintain a sufficient energy level, or best case scenario: a very high boost where I had an extra hop in my step and an extra level of mental awareness on the court.

I knew going into it that the sluggish workouts would be few and far between. The coffee at least gave me enough of a boost to start drinking it consistently heading into the test. After my first “Very High Boost” day, I was really curious how often coffee would give me this best case scenario.

Here are the results, recorded into a Google Spreadsheet in real-time via the DIY Tracker.

before a workout
The automatic Google Spreadsheet of response results from the DIY Tracker.

 

The Takeaways:

The results proved encouraging! 3 of the 4 times I drank coffee before playing basketball I experienced a very high boost. I noticed I had an extra spring in my step and was able to see the floor and make quicker decisions comapred to the 1 off-day I didn’t have a very high boost during this period.

(Beginner’s Tip: If you try this yourself before basketball, make sure to hydrate yourself even more than usual in between games. Your body needs to adjust to the caffeine, which naturally makes you more dehydrated. After a few days of this, you shouldn’t feel extra dehydrated but take it from me, I learned the hard way!)

Additionally, I did pilates after my mid-afternoon cup of coffee 5 times in these 10 days and experienced only 1 day where I still felt sluggish. This one off day helped me realize that coffee isn’t the end all, be all solution to having a quality workout. In other words, it was a pleasant reminder that you still have to get reasonable sleep and eat well to have a quality workout no matter what. I remember vividly not having those basic factors fulfilled on this particular day.

However, the results also gave me a number, albeit in a small sample size. 80% of the time I’ll feel a noticable boost in my workout (basketball, pilates, stretching) thanks to consuming a cup of coffee 30 minutes before. Again, I felt it was helping me internally all summer, but now I had a high success rate to keep me even more disciplined to have that pre-workout coffee.

 

Looking ahead:

From here, I intend to continue to gather data, track how much caffeine I consume each day, and add variables to arrive at even more concrete conclusions. For instance: how does the amount of caffeine in the pre-workout cup of coffee effect my workout. The one day I consumed 180 mg of caffeine was due to a large Dunkin Donuts coffee I bought on the run. I noticed a very high boost in playing basketball 30 minutes later.

What do you guys think? Is there anything more you would like to see added to my test? I personally believe in the science behind it (if you missed the links in the intro, I suggest you give those a read) but perhaps there’s an ingredient here that it’s all mental. You know, like when the TuneSquad drank “MJ’s Secret Stuff” at halftime. 🙂

Let me know your thoughts and suggestions on Twitter @QuantSelfLaFont or @TimHanrahan10 and perform your own experiment like this by simply using Apple Health (already installed on your iPhone) and your own custom response survey via the QuantXLaFont DIY Tracker.

***

N of 1 Testing: Butter Redeemed

I had a self-created story about butter. It was such a strong story that it was changing my behavior around what I ate. I had come to believe butter “gummed me up” and after eating it my body would react by feeling lousy.

bloay

Two months ago I transitioned to a low carb, medium protein, ketogenic diet. As I described at the time, the experience of weaning myself off carbohydrates involved feeling poorly for a number of the early days. As butter was a good source of fats I was eating a lot of it, so I started associated feeling lousy with butter. And I developed the story, “This butter is throwing me a beating.”

I didn’t like the story because it cut down on my food options. And I knew from my early QS studies that the majority of my stories were self-induced fictions.  Was this story about butter a fiction or did it have some basis in fact?

My Question

Did my body feel lousy after eating butter?

What I Did

Each morning I would take butter or an alternative source of fat with my coffee. The alternative was usually flaxseed or coconut oil. I randomly determined which I would take each day. Four hours after my coffee I would capture how I was feeling in a Google Spreadsheet via a Google Form tool I call my DIY Tracker.

How I Did It

I used a Google Spreadsheet to generate a random “one” or “zero” for each day in the period. This gave me instructions on what to put in my coffee each morning, butter or the alternative. This was important because I needed to not choose what I took based on some bias, or more importantly, the story about butter. If I felt rough in the morning and arbitrarily chose the alternative fat source because of my belief  butter  would make me feel worse I would skew the data. So I stuck to my random schedule when I took my coffee after a workout at around 7am.

I captured how I felt each morning at 11am using my DIY Tracker. This provided my data for how I was reacting to butter and the alternative.

IMG_0112

I threw out data that did not meet my control criteria, which is a fancy way to say if something out of the norm was happening I did not use that data. If I did not follow the randomly generated instruction or the amount of fat I consumed was not within a set range, I considered the reading invalid. I also only included readings on days I had exercised for 20 to 30 minutes prior to the coffee.

After thirty-seven days I had twenty-seven good data points. I separated the list into a “butter” and “other” list and ran a T-Test for butter and a value for feeling lousy that was embedded in the way the DIY Tracker poll solicited information.

What I Learned

Butter was redeemed. I compared it both to an average score that would indicate I was consistently feeling lousy and to the oil based source of fat. The way I gathered information in the DIY tracker a consistent score of “2” (Yawny, tired) would have shown I was feeling lousy.

The data showed I wasn’t consistently feeling lousy. There was a statistically significant difference between the feeling score after eating butter (avg of 3.6) and the expected average score of feeling lousy (avg of 2.5). The T-Test returned a value of .004. Within the data I only felt lousy on two of the 27 days.

When I consumed the oil based sources of fat my average feeling score was higher than with butter, but the results were not statistically significant when I compared oil to butter (T-Test returned .17). So butter remains in the morning coffee mixture rotation.
butter

Behold the redeemed!

Try Your Own Test

Do you have a food story? A cherished belief that you can’t eat a certain food because it makes you feel bloated, or bad? N of 1 Testing is quite easy to set up when you have a specific question you are asking based on a story you have. Get free instructions on how to create you own DIY Tracker or we can help you out at QuantXLaFont.

DIY Tracking the Daily Energy Curve

I have reported in earlier posts that I am mapping my Daily Energy Curve so I can make changes in diet, exercise and mental frameworks that will maximize my physically feeling good. In the world of self quantifying we tend to maximize for a desired weight, blood glucose level, steps we take in a day or distance we can run. It gives us an organizing principle for our activity and measurements. My current work is to maximize just like this guy does:

feeling good

I needed a simple way to capture how I was feeling at different times. I like Taplog but it is only for Android and I had just switched to iPhone. I could not find an iPhone app that I liked. So I created a Google Form that would be easily accessible on the iPhone and I could capture my data often.  The survey on the phone looks like this:

IMG_0112

I started gathering reports along three dimensions, six times a day. The dimensions were how awake I felt, how mentally sharp I felt and how stressed I felt.

I am very early days so I can’t describe what I have learned yet. I can show you what the early data looks like and how much data you can gather with a DIY tool like the one I created. This represents four days of data and 37 data points.

Here is the early data on how Awake I felt over the course of the day:

Awake

I was surprised to see how much the curve held up in the back end of the day. Here is mental alertness:

Mental Alert

Too early to be definitive but the drop the afternoon seems to be interesting.  The curve for how stressed I felt has a different and flatter curve:

Stress

I can now start running randomized experiments on the day parts. I am pleased to have created this tracker because I have a lot of control over what I can capture and I already have expansion ideas. And it keeps my tracking top of mind.

I encourage you to make your own DIY tracker. To help you out I have created a set of step-by-step instructions in a PDF and you can download it for free on QuantXLaFont.

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