Should you quantify your life?
Should you quantify your life?
Everything's a numbers game
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8 min read
It was the early evening of my baby’s due date, and I was having contractions. I called my doctor. He told me to time the contractions, and to head to the hospital when they were 2 to 3 minutes apart, lasting for an average of one minute, for at least an hour.
In the flurry of excitement, fear, and pain, calculating and remembering these numbers seemed an insurmountable task.
Then my husband suggested downloading a Contraction Timer app1.
The next couple hours progressed as follows: As is my nature, I began frantically trying to check things off of my to-do list. I called my sister to wish her happy birthday. I cleaned up the kitchen. I put a few phone chargers and fuzzy socks in my hospital bag. I ate some cookies (not on my to-do list, but still important). I then sat at my computer, maniacally typing some work I’d promised to finish before maternity leave. Every 2 to 4 minutes, I stopped typing, pressed the “contraction starting” button on my phone, closed my eyes, took a few loud, long breaths, pressed “contraction stopping,” and started typing again.
The app produced a beautiful chart of contraction times, lengths, and distances apart, along with calculations of the averages of each. Unhelpfully, it also provided scary, red-text warnings to contact a medical provider and go to a hospital right away every few minutes. Eventually we took the app’s advice.
The opportunities for numerical tracking have only increased since the baby was born. Smart bassinets to track sleep. Smart scales to track weight. Apps to track everything from feedings to diaper changes to growth spurts. Every minute of my child’s day can be documented, recorded, and with a few quick calculations, turned into a handy chart with averages rates, trend lines, and statistics. Each time we go to the doctor, the baby’s height2 and weight measurements are plotted on a growth curve and converted to percentile scores for comparison with other babies of the same age. They always ask if we want a copy of the growth chart. Of course we do.
It’s no surprise that options for pregnancy and baby tracking abound. It’s a logical extension of our own enthusiasm for quantifying our lives—applying numbers, tracking output, and calculating summary stats in nearly every domain.
Technology isn’t required for quantification, but its presence has made it easier, more passive, and more pervasive.
What is quantification?
There are various flavors of tech-enabled quantification.
There is individual quantification. These are the personalized step counters, the sleep trackers, the heart rate monitors—health-tracking tools typically subsumed under the “quantified self” movement. There are the products we use specifically to track such data, like Whoop, Oura, and Fitbit, and the products we use for other purposes, but which soon lure us into checking our stats, like the iPhone Health app (steps, distance, speed, sleep), Headspace (total minutes and days in a row meditated), and Kindle3 (days and weeks in a row read, days read per month, number of titles read).
There is also social quantification. A key feature of social media, for example, is that it is quantifiable, with numerical metrics in the form of feedback on the things we post, i.e., likes, views, shares, comments, retweets, upvotes, rankings, etc. Even text messaging is not immune to quantifiability. Each message is attached to a time, with response speed easily calculable. Sometimes, quantification is some combination of the two—both individual and social. The Strava app, for example, boasts 76 million users who track their bike rides and runs, share their stats (including route map, pace, mileage, elevation gain, etc.), and then wait for the “kudos” (Strava’s equivalent of likes) to roll in.
Why? Why are we so attracted to quantification? Why, when I ask my husband how he slept, does he glance at his Whoop to report that he spent a combined total of 4 hours and 12 minutes in R.E.M. and Slow Wave Sleep? Why, when I speak with teens about posting on Instagram, do they describe regularly refreshing the app to track the pace of accumulating likes and comments? Why won’t I stop measuring my pace when I go out for a jog, even when I have no plans to race anyone, anywhere, anytime soon (except my child, who is becoming an alarmingly fast roller)?
What fitness trackers and Instagram likes have in common
Though these flavors of quantification seem different—and in many ways they are—they are bound, I believe, by a singular motivation: to understand ourselves.
Disciples of the quantified self movement, or those who believe in monitoring things like sleep, heart rate, and physical activity, share a stated goal of “self-knowledge through numbers.” The idea is simple. We know very little about what goes on in our bodies, and we are terrible at estimating things like how many calories we consume, how many days last month we exercised, or even how our mood changes after a given activity. Tracking these experiences can give us unparalleled insight into our behaviors. We can know ourselves better by quantifying our experiences.
On social media, though not explicitly stated, our goals are often similar. Why else do we post things, if not to get feedback, to learn more about who we are through the eyes—and clicks—of others? What do they think of us? How do they see us? Are we liked? Respected? How do we stack up?
By attaching numbers to ourselves, we gain a sense of control. A sense of knowing something more about the confusing mess of humanness that resides in us—a sliver of insight into who we are, what we’re doing, and why we’re doing it. And this is something we desperately want.
The case for quantification
When this self-knowledge leads to positive behavior change, the results can be powerful. Evidence suggests that the simple act of monitoring a behavior can result in desired changes to that behavior.
A meta-analysis published in 2009 provides a comprehensive investigation of self-monitoring in relation to physical activity and healthy eating. Combining the results of 122 studies (over 44,000 participants), they find that self-monitoring is effective in changing behavior, particularly if it is combined with at least one other “self-regulation technique” (e.g., setting goals in advance, reviewing those goals regularly, or receiving feedback on performance).
There’s also more recent evidence, from a 2021 meta-analysis, suggesting that people randomized to wear fitness trackers walk, on average, 1850 more steps per day than those who are not (see this post from Emily Oster for the full rundown of this study).
Quantification is a critical component of well-established psychological treatments like Cognitive Behavioral Therapy, as well. Tracking behaviors, moods, and emotions allows patients to identify patterns (e.g., a reliable dip in mood after sitting on the couch for a few hours after work), and to challenge assumptions (when we’re depressed, we often cannot remember moments when our mood was not a 1 out of 10). This type of self-knowledge can be life-changing.
In this sense, quantification is irreplaceable.
What’s in a number?
I recognize the benefits, but I cannot help but feel a sense of unease about the growing presence of quantification in our lives. We often discuss the risks of social quantification, of the psychological toll of relying on others’ judgments in the form of trackable status metrics on social media. Here, the downside is clear. But is individual quantification—a devotion to the quantified self—so different? Is the desire to convert our everyday behaviors into numbers and charts and averages, just an extension of our innate desire to see how we stack up—against others, but also, against ourselves?
When every behavior has a numerical corollary, surely something gets lost in the translation. A walk in the woods converted to steps, an afternoon nap converted to minutes in R.E.M, a marriage or birth announcement converted to likes and views. Do we lose some element of presence, of engagement in our offline lives, when every experience can be filtered through a wearable sensor, accelerometer, or app, and attached to some numerical output?
I’m reminded of a piece David Sedaris wrote for The New Yorker back in 2014, during the heyday of the FitBit and, shockingly, before the iPhone Health app had even been released. Sedaris has written extensively about his obsession with tracking steps, often walking as many as 30 miles per day.
At the end of my first sixty-thousand-step day, I staggered home with my flashlight knowing that I’d advance to sixty-five thousand, and that there will be no end to it until my feet snap off at the ankles… he writes. Why is it some people can manage a thing like a Fitbit, while others go off the rails and allow it to rule, and perhaps even ruin, their lives?
Quantification may stem from a desire for self-knowledge, a brief glimpse into who we are and how we’re measuring up, a sense of control over our lives in the form of steps, heart rate variability, minutes of sleep, likes, views. But when we discover—as Sedaris has—that a quantifiable metric has begun to control us, the limits of the numbers are laid bare.
Numbers are tempting in our quest for self-knowledge. They have the veneer of objectivity. A count of 15,024 steps, or of 457 likes, is much easier to understand than a feeling of excitement, or fear, or self-consciousness. When does the desire for self-knowledge transition into nothing more than a flailing attempt at managing the unpredictability of our messy, unquantifiable lives?
When we arrived at the hospital at the behest of the all-knowing Contraction Timer app, we reported our data to the nurse. Contractions occurring an average of two minutes and 32 seconds apart, lasting an average of 54 seconds, happening for the past 90 minutes. The nurse asked me to rate my pain on a scale of 1 to 10. I have no idea, I thought, as I keeled over at the waist, lowered my head, and rested my hands on a nearby table. 6? 7?
An hour later it became clear that, despite what the data had to say, despite how clear the numbers had seemed, I was nowhere near ready to have a baby. It would be almost another 24 hours before he made his arrival.
As a research psychologist, my career is built on data. On attaching cold, hard numbers to the most complex of human constructs: happiness, motivation, depression, life satisfaction. But these numbers can only tell us so much. They cannot tell us about the excruciating pain of a one-minute contraction, or the heart-bursting joy of a baby’s first cry, or the anxiety of sitting with a child at the doctor’s office.
The numbers can provide us a shred of self-knowledge, of hope that we may understand who we are and why we act the way we do. But in the end, we are human. And the human experience is hard to quantify.
Speaking of data obsession, I am incredibly curious about the KPIs for this Contraction Timer app. On the one hand, each user will only download and use it at the time in which they are actively having a child, so probably not that many lifetime use cases. Monthly Returning Users is probably…zero? On the other hand, it’s the first contraction timer that comes up when you search in the app store, and when you’re in the middle of having a child, you’re not scrolling very far down the list. So Monthly New Users is probably…high? They also offer a “premium” version, which costs $2.99 and gives users the option to “edit” contractions (i.e., if you accidentally pressed “contraction stopping” too early; important for calculating accurate averages). Despite possibly being unethical due to the vulnerability of users at the time of purchase decision, this is probably pretty profitable. Either way, it seems the makers of Contraction Timer are confident in their product, noting: “Thousands of pregnant women around the world have become mothers using our app.” Wait. What? I hate to break to you, Contraction Timer, but I’m relatively certain that becoming a mother is a bit more complicated than that.
Am I the only person who is appalled by the inaccuracy of the system for measuring this? They lay the baby down on the exam table paper, draw a line at his head and feet, and then put a tape measurer to it. By the time the line is drawn at his feet, the baby has usually squirmed at least an inch or two away from the original placement of his head. On more than one occasion, the foot-line has been drawn not straight down from the head-line, but rather a few inches to the right or left, with the measurement then happening on a diagonal. Anyone who has taken Geometry knows this will result in a measurement that is longer than the straight line. And then the difference between a baby in the 25th versus 75th percentiles for height is often less than 2 inches, which clearly is subsumed within the margin for error here. Have these people never heard of measurement error? Confidence intervals? At a recent appointment, our nurse was describing to a trainee how to take the foot-line measurement (“make sure his toes are flexed up at a right angle to his ankle”). This is we’re focusing our efforts? We need a new system.
I only recently discovered that Kindle tracks these reading-based stats. But if the device is collecting data on my reading habits, why are the targeted ads not more…targeted? I have a Kindle Paperwhite, which displays ads on the lock screen each time the device is turned off. The advertised books are so far afield from my interests, it almost seems purposeful. Science fiction novels about a newly discovered alien race? A high-school romance novel about a “bad boy” and “girl next door” with “a million reasons why they should have stayed away from each other”? C’mon, Kindle. The last thing I read was a book about evidence-based parenting. In an era of constant data tracking and harvesting, there’s almost something quaint about it.
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