Can You Measure Well-Being?
An inside look from scientists working to quantify feelings
Co-authored with Jocelyn Harmon
How are you doing these days?
Take a moment, and really think about it. Is your answer emotional, like “I’m feeling stressed,” or physical, like “I’m feeling worn down”? Or maybe your response falls somewhere on a scale from “abysmal,” let’s say, to “outstanding.”
For most people, there are many ways to assess well-being, and the way you introspect on it might even change from day-to-day. But from a scientific perspective, well-being can only be understood with a shared, theory- and evidence-based definition that implies reliable and valid ways of measuring it.
As we all navigate the ups and downs of a Covid-19 world, you may be tuning into your well-being and mental health more often than usual. You may find yourself interested in trying something new, like meditation or therapy. But how will you know if it works for you?
Measuring well-being is the link between how you feel and what you should do about it. As two professionals at Healthy Mind Innovations (an affiliated nonprofit with the neuroscience research center the Center for Healthy Minds at the University of Wisconsin, Madison) committed to translating science into tools to cultivate and measure well-being, measurement is always at the forefront of our work.
By taking a snapshot of our state of well-being at a given point in time, we create a baseline against which to compare how we’re doing after we engage in a stressful or calming activity. And when hundreds, thousands, or even millions of people join us by using these tools to measure their own well-being, that data can give scientists the information they need to systematically assess interventions — and point to what works.
Richard Davidson, PhD, neuroscientist and professor, equates this search for well-being measurement to the search for a measurement for Alzheimer’s.
“You can’t really change something until you can effectively measure it,” Davidson says. “[Recently], Bill Gates gave a lot of money for Alzheimer’s research. 100% of the money he gave is dedicated to finding a measure — because there is no objective measure of Alzheimer’s. It’s based on more impressionistic measures, the only definitive measure is a measure you get at autopsy. I thought that was so interesting, that [Gates] had the vision to understand that we can’t really make progress in treating this disease unless we have a really good measure for it. And I think the same is true for well-being.”
Measurements of well-being allow us to track in a consistent manner how “we are doing” over time, telling us whether the interventions we turn to in times of distress — like meditation, physical exercise, or therapy — are resulting in changes in our minds and lives. Do they really increase psychological well-being and improve mental health and resilience? How can we tell? Is it possible to know when someone really is more calm, more focused, or more caring?
When you go to a physical trainer, you can take, for example, speed and flexibility measurements on your first visit and then check back in to see what’s improved. You can see your body change, or your speed or flexibility improve, by measurable units like minutes or inches. Well-being and training the mind, on the other hand, are abstract. You can’t directly see the thing we call “well-being” changing. Instead, you have to infer it via something more concrete and observable.
Measurements of well-being allow us to track in a consistent manner how “we are doing” over time, telling us whether the interventions we turn to in times of distress are resulting in changes in our minds and lives.
When you’re trying something new to improve your well-being, you may begin to feel that you are more emotionally stable, that your body feels less tense, or maybe others note a change in your demeanor. By applying numbers to those feelings, measurement allows scientists to mathematize them and apply statistical techniques that, when used wisely, can help answer compelling questions about human nature.
What this process — theoretical inference combined with numeric measurement — does for us is a big deal. Here’s one major example.
A few decades ago, neuroscientists thought the brain only developed in childhood, and once we hit adulthood, it stopped growing. This view mirrors what we sometimes believe about ourselves (whether we’re aware of it or not): that our patterns and personalities are fully formed, and can’t change. It might seem like people who are calm and confident are just born that way, and those of us who are more easily overwhelmed are pretty much stuck with the hand we were dealt at birth.
But we now know that this doesn’t have to be true. Advances in contemplative neuroscience have revealed that we can train the mind and rewire the brain to feel more calm, more focused, more caring — and less distracted and disconnected from the people we care about and the things we truly value. And the only way these advancements are possible is by knowing what it means to be more calm, more focused, and more caring: in other words, via measurement.
At our research center, measures began with specifying a theory (or framework) about the thoughts, emotions, and behaviors that reflect well-being. This grew out of decades of neuroscientific study of contemplative practices (like meditation) and the brain. This framework is based on the notion that anyone can train their mind for more well-being and consists of four pillars to cultivate: awareness, connection, insight, and purpose.
With valid, reliable measures, researchers can find out what works for different people in different contexts.
Then we asked, how can we assign numbers to represent these concepts? Right now, most of our efforts have focused on developing surveys. Our goal is to use something tangible — how people respond to the survey — to infer something intangible: their underlying level of the concept (awareness, connection, insight, and/or purpose).
To develop the survey, neuroscientists, behavioral scientists, and even a Buddhist scholar wrote and evaluated questions based on the theory we had about the thoughts, emotions, and behaviors that reflect well-being. Then, we vetted the questions among real people to find out if the questions were understandable and meaningful, which inspired revisions.
Next, we validated the questions.
Validation is a process of collecting evidence about whether a measure produces numbers that are a useful representation of its theory. We poke holes and ask questions and try to find out if the measure has the features required to produce a useful representation. For example, does it correlate with other well-being measures, like the ones outlined in the WHO-5? Are the numbers stable over time, or changing and unstable, as the theory expects? Once validated, the data informs more about our theory and its concepts, becoming a cycle of learning and development. This work is iterative. In a sense, it’s never done.
As you might imagine, this process is really hard. But as a result, we’re now able to offer these surveys widely — as measurement tools that you can engage with from your phone, via a meditation app.
Historically, measurement hasn’t always been this systematic. Psychological measurement is a complex field, and measurement has a rich empirical and philosophical history in all sciences, posing a challenge even in the physical sciences.
Imagine checking in on your well-being on your phone and then getting recommendations for what you might do to improve it.
For example, the first way of measuring heat, a thermoscope, could tell you whether something was warmer than another thing, but could not actually measure specific numeric quantities. Establishing a numeric scale for heat was not trivial; it was a deep philosophical challenge that required advances in technology and other sciences.
Psychology is a science with a short history and an even shorter measurement history. But like other sciences, it stands to gain from improved measurement, which in turn can take advantage of advances in technology.
We also have plans to make more measures that suit different needs. Here’s one example of a measure that would provide the intensive longitudinal data we need to track the ups and downs of well-being as experienced in everyday life. When we want to know if a thing has changed, we usually measure it more than once, often before and after an intervention. But this is like hearing only the first and last note of a song.
To better capture the rhythm and melody — the natural ups and downs of well-being in everyday life — we’re devoting effort to developing experience sampling methods, where we’ll send notifications to users of an app that ask people how they’re doing at particular moments in the day, at regular intervals. This will hopefully better capture well-being as people live it in the moment, rather than as they retrospectively judge it in a survey.
Measurement can also help researchers develop personalized, just-in-time interventions. With valid, reliable measures, researchers can find out what works for different people in different contexts. Imagine checking in on your well-being on your phone and then getting recommendations for what you might do to improve it. An approach like this could help people choose the best psychological well-being interventions to meet their needs at that moment, in real-time.
That’s a future that’s only possible with improved measurement.
So, the next time you are asked, “How are you doing?” think about a future where this is answered with a validated numerical representation — one that is designed to guide you in self-reflection, self-knowledge, and resilience to the challenges and uncertainty we all find ourselves in today.
