Why do people track? Why Self-Tracking? Why pursue a quantified self?
In this post, I want to explore what motivates people to track their lives. Whether it’s a quantified self adherent or simply someone tracking their weight, health or fitness, a lot of people are tracking their lives today, and there hundreds of ways to do it. To help understand the space more, we will look the general categories tracking falls into. We will then look at a couple of research papers that attempt to survey and define the QS and self-tracking community. The goal of these papers is to understand what motivates someone to pursue self-tracking and create their self-tracking projects and experiments.
Why do people track? Why Self-Tracking? Why pursue a quantified self?
In this post, I’d like to explore what motivates people to track their lives. Whether it’s a quantified self adherent or someone simply tracking their weight, health, or fitness, many people are tracking their lives in order to better comprehend this space, let us explore the general categories into which tracking falls. After reviewing a few research papers attempting to define and survey the QS and self-tracking communities, we will then analyze a few of our own. These papers aim to reveal what compels someone to conduct self-tracking, which often yields the creation of their self-tracking projects and experiments.
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Apple Watch Seems A Little Tricker So…
QS App: Simplest Way to Export Apple Health Data
The first and easiest option for exporting your Apple Health data is to use the QS Access App, a free iOS app developed by Gary Wolf, Kevin Kelly, and the team at Quantified Self. It’s purpose is simple: export your data from Apple Health into a useable format, like CSV, so you can explore it.
After installing the app, select the specific data points you want to export. (NOTE: You may receive a popup about access permissions. Accept these and allow access.) Once you’ve selected the data points you want, hit “Create Table.” the process may take a several minutes, depending on the amount of data you have in Apple Health. This delay might be longer if you have a lot of data from several years and are exporting your steps and heart rate.
The end result of QS Access export is a well-structured CSV file, which you can open and explore in any spreadsheet application. This is also also good format to use in Tableau, R, Python, and even just a spreadsheet application like Excel or Google Sheets.
The one thing to notice about this export format is that it will add blank records for non-data. This means if you export your Blood Pressure data, you’ll end up with potentially thousands of extra and blank rows. In the case of steps, this is a good thing, since you’ll then have noted hours where you did zero walking. In other data points, this export format makes less sense and results in a lot of unnecessary and confusing data.
The only thing missing from the QS Access export is your workout data. Fortunately, as I explained in detail in How to Track Your Workouts, you can use Workout Export app to get your workout data into a CSV too.
Self-tracking is the act of measuring or documenting something about yourself.
The purpose of this definition is to demonstrate that, like people and animals, trackers have different motivations. The point of most self-tracking, as we shall see in this post, is to gain meaning or to make improvements, but there is also a significant connection to the conscious engagement and understanding of technology in human lives today.
The following 16 general categories are used to categorize tracking apps:
- Activity & Fitness
- Data Collection
- Diet
- Goals
- Habits
- Health
- Heart
- Media Consumption
- Mind & Cognition
- Mood
- Sleep
- Tally
- Time
- Wealth or money
In addition to these area-specific categories, there are two others worth mentioning: In this category, you will find sites and apps that aggregate data from multiple sources into a unified view and often provide visualizations and correlations.
When a single automation program uses an event in one service to trigger an action in another service, the two are connected. For example, I can add my activity in Strava to Google Sheets or a chat program like Telegram.A full breakdown of these categories and the various examples of tracking goes beyond this post.
Reasons for Tracking Data: What the Research Says
This first talk gave inspiration to a QS tradition: show and tell. In other words, participants take turns describing what they’ve tracked, how they tracked it, and what they learned.
Regarding the motivation to start QS, Wolf explained that it wasn’t to launch a movement but to simply explore people and technology. The following meetup notwithstanding, Quantified Self has expanded all over the world, as seen in the previous section, where dozens of apps and wearables appeared to track our bodies and lives.
This of the search terms, self-tracking (blue), lifelogging (red) and quantified self (yellow), shows rise of quantified self in early 2010 to a peak in 2014:
there are a few self-tracking practices that Quickeners use. Self-tracking can take many forms, but generally refers to any deliberate, methodical approach aimed at improving a particular aspect of a person or the environment they live in.
In the section called “The Practice of Self-Tracking,” Butterfield attempts to categorize what’s happening with self-monitoring apps. As he writes, “Grouping by domain, such as sleep or weight, is one method of describing self-monitoring programs. However, I identified three dimensions that can be used to describe or locate self-tracking projects within these paradigms.” The three axes are as follows:
- “technological involvement,” i.e. how much does the project rely on technology, devices, laboratory tests and sensors or can it be done with simple paper and pencil?
- “level of complexity in the design of the self-tracking project,” i.e. these projects might be called “self-experiments” since they rely on a more rigor or scientific method of collecting data, testing hypotheses, and exploring correlations.
- “goal driven or exploratory,” i.e. is the project driven by a life change or self-improvement? Or it mostly about simply exploring and more general understanding?
Compared to Butterfield’s analysis, which divides self-tracking projects into three categories with the goal-driven category being broken down into three motivational axes, Gimpel’s framework places self-tracking into five categories, with the goal-driven category broken down into three motivational axes:
- self-healing = becoming healthier
- self-discipline = rewarding aspects of it
- self-design = control and optimize “yourself”
- self-association = associated with movement
- self-entertainment = entertainment value
The researchers observed anecdotally that those motivated by self-healing often had “a certain rebellion against the healthcare system” and were searching for alternative therapies. We see this a lot in our customers at www.labme.ai. Often they simply want “control” and nothing more. They will rarely look at the test results – its as if ordering it and having that ability soothes the craving.
Trackers often seek control over their lives when it comes to self-design: no matter what their health, fitness, or mood, self-trackers are generally fascinated by the idea of controlling their own lives by taking responsibility and optimizing them.”
This gives rise to a relation between the number of motivations that people hold to and how much they will track those motivators There is a correlation between the number of motivators people have and the amount of tracking they do.
A person, who works with any system or service-type of occupation in regards to providing tracking of well-being, nutrition, or medical aspects of day-to-day life, will be most effective if they provide it while drawing in parts of the ‘Self-design’ and ‘Self-healing’ patterns.
The three primary ways people record their life is through self-healing, self-design, and vicarious experience. The reasons for this vary, but all of them can be described as stemming from one of five factors.
Although many track for self-interest, potentially behind this pursuit of self lies a desire to understand humans and society. We track for self-interest, but also for ourselves.
Why Do We Need This Data?
Because many metabolic, sleep induced and regulated cellular processes are not subjective in the sense of a feeling. How can you feel your REM sleep improving 67%? How can you tell that your RHV has declined 20%? Many times you can’t.
It’s better to see and to know than not see and to guess.