Topic Archives: QS Books
The book discussed in this post is Making Time: Lillian Moller Gilbreth — A Life Beyond “Cheaper by the Dozen”.
When we repurpose tools of science and management for distinctly personal ends, we’re extending a path laid down for us by many ingenious predecessors. I want to take advantage of the last hours of the day to honor one of the greatest early biometricians, Lillian Moller Gilbreth, and to revive a question posed, at least implicitly, by her work.
Gilbreth began her career in the early part of the last century as a disciple of the founder of scientific management, Frederick Taylor. Even before she got her PhD, she was doing time motions studies with her husband Frank Gilbreth with the aim of improving worker efficiency. Frank Gilbreth died in 1924. By the time Lillian died, in 1972 at age 94, she’d taken what began as Taylorist dogma and turned it into a practice of close observation and participatory learning that almost turned it on it’s head. Instead of seeing human beings as a factor of production, to be exploited like any other resource until worn and replaced, she asked about the human factor in production: what was work for, what were its conditions and benefits, and how could it be improved.
Gilbreth was very well known in her day, so she’s easy to learn about and there’s no need to crib from sources you can consult yourself. Perhaps my favorite biographical detail is that, after being denied a PhD in 1912 by the University of California, Berkeley because her family and business responsibilities prevented her from being on campus during the last year of her studies, Gilbreth published her research as a series of articles in Industrial Engineering and Engineering Digest, and then as a book, and then just went ahead and got a PhD from Brown. Although it’s quite something to become a towering figure in a new field, developing many novel research methods, and it’s of course no small honor to be a member of the National Academy of Engineering (she was the first woman elected), my academic friends will surely bow in awe before somebody who deals with a recalcitrant and small minded graduate department by marching off to a competing school and writing a second dissertation.
She was like that all her life. Jane Lancaster’s biography of Gilbreth, Making Time, gives a sympathetic but critically aware portrait of a person who embodied, challenged, compromised with, exploited, and suffered from conflicting ideals and demands of women’s work. Gilbreth made her living consulting for corporations, especially those whose employees and customers were women. She was a key link between scientific management and consumer culture, taking techniques developed for studying workers on the shop floor and applying them to home life. In 1927 she wrote a practical guide called The Home-maker and Her Job, and for many years after she continued to do close observational studies and produced a nearly endless stream of advice for coping.
From today’s vantage point we easily see that increasing the efficiency housework didn’t bring about the general emancipation it promised. For many people, time saved washing dishes is lost to doing paid work at stagnant wages; while savings from the lower cost of manufactured goods is eaten up by the price of healthcare and childcare. The cheery scientism of late Victorian elites looks naive from a century’s distance; that is, when its unhesitant racism doesn’t make it simply revolting. Gilbreth, at least at the beginning of the century, hoped that “positive eugenics” could improve the human species. Lancaster doesn’t go very deeply into this side of the rationalist ethos, except to note that Gilbreth wasn’t in favor of sterilization or murder, instead believing that people of high intelligence should have as many children as possible. She lived her faith, giving birth to twelve, one of whom wrote a memoir, Cheaper By the Dozen, in which she is reduced to a feminine caricature.
You can read Cheaper By the Dozen and watch both of the movies made from it without learning any of the most interesting things about Gilbreth’s research. For instance, in 1926 she undertook an unprecedented study on menstruation and menstrual pads, for which she canvassed, Lancaster writes, “a long list of potential informants, ranging form the Women’s Bureau through the American Federation of Labor to gynecologists, prison workers, and laundries.” In the early 1930’s she launched a project involving over 100 interviews and 20,000 questionnaires collecting data on sex and age discrimination. Before Frank died, he and Lillian Gilbreth carried out some of the very first, and certainly the most thorough, studies of how people with disabilities can benefit from kitchens designed specially for them, and after he died she continued to advocate passionately for better design to support independent living. Paid by Macy’s to improve the efficiency of their cashiers, she went to work on the sales floor herself, coming to understand in an intimate way the different meaning of “tiredness” for women of different ages working for different reasons.
Gilbreth didn’t merely link scientific management to consumer culture through her research, she also embodied – through her seemingly supernatural productivity – it’s greatest tensions. Gilbreth was a non-conforming rationalist engineer, and a bourgeois advocate of domesticity. (She argued for what she called a “50-50 marriage” of shared domestic labor but backed down in the face of ridicule, paying at least lip service the idea of a woman’s sphere.) She spent a good part of her life addressing the problems of working women, while of course working herself, and yet her greatest public fame came from the “biological wonder” of her twelve children.
Gilbreth understood efficiency, and yet her work leaves us with a question: what does efficiency cost? The promise is mastery, sufficiency, ease of accomplishment, when unnecessary friction has been eliminated. Do things the “one best way” and look what you get: Two dissertations. Twelve children. A long shelf of original and useful publications. She made it look easy. But as Lancaster makes clear, the ease is an illusion. Automation and routinization works best under controlled circumstance, but controls fail, and someone has to clean up the mess. Gilbreth mainly cleaned her own messes, though not all of them. The book’s most provocative minor character is the man who worked for decades as her main domestic servant, Tom Grieves. He’s presented as grumbly but affectionate, a practical person with a cigarette always on his lips, doing dishes and straightening rooms, chasing children around, and generally needed to maintain the conditions of predictability required for rational management to function. Grieve’s comment on his employer’s obsession with efficiency was succinct: She was, he said, trying to “make it easy for folks to work hard.”
Gilbreth exposed the realities of women’s work both inside and outside the home, but always with the promise that good technique could lift the burden. The promise is still with us; but, then again why is it still just a promise? I think it honors Gilbreth’s legacy to keep asking this question, even as it takes us outside the domain of efficiency she pioneered.
Welcome to the sixth and final part of the QS book on mood tracking that Robin Barooah and I wrote. This chapter has some thoughts on what the future of mood tracking might look like. Thanks for being on this journey with us!
At this point, you should have a good understanding of the nuances and methods of tracking mood. You could stop reading here and be well-versed and ready to go. If you want a peek into some possible new ways to track mood in future, read on.
Passive Body Position and Movement
What if your mood could be measured without you having to do anything or enter any data? Would this be helpful, or is the act of reflecting on your mood the useful part? We mentioned a few existing examples earlier, like tracking what music you listen to, and your voice patterns. Here are a few other efforts happening:
A sensor called LUMOback can be stuck on your back to detect your posture throughout the day and report to you via your smartphone if you are slouching. They don’t specifically talk about mood tracking as an application for this, but posture is a known sign of mood. When we’re depressed, we don’t stand up tall.
Other experimental ways to passively capture mood include keystroke logging, which involves detecting how quickly and actively you are typing on your keyboard, and using your webcam to take random pictures or continuous video of yourself while you’re at your computer. Moritz Stefaner did a project in which he automated hourly webcam pictures of himself. He then had 13585 of the pictures analyzed for mood, with the following result.
A lot of his “sad” photos are really just him concentrating, mislabeled as sadness. but Moritz’s project shows the potential power of the cheap, universally available webcam as a passive mood tracking device.
Reverse Mood Tracking
A fascinating way of using mood tracking in a clinical setting has been pioneered by Dr. Alan Greene. He was kind enough to share his story with us here:
“Most mood trackers I know tend to notice, record, and track their moods in order to gain insights about themselves. I’ve come to also do the reverse: track my moods to gain insight about others.
It all started when I walked through a door.
Welcome to part 5 of the QS book on mood tracking that Robin Barooah and I wrote. This chapter has some tips that we’ve found helpful for getting started with mood tracking. Enjoy!
Once you’ve been tracking mood for a while, and have a good baseline established, it’s time to play. What if you could influence the factors that shape your mood? What if you had a trusted buddy to confide in, to make your tracking more robust? If we know ourselves better, we can make choices that help us to make the most of our lives. We’ll explore how and why to experiment with and share your mood in this chapter.
There’s a concept called heutagogy that applies nicely to self-tracking activities. Heutagogy is basically the idea that people direct their own learning, using personal experiences to update their models of themselves and the world around them. Stewart Hase and Chris Kenyon, who came up the term, write that “people only change in response to a very clear need… involving confusion, dissonance, fear, or intense desire.”
At Quantified Self, we usually see intense desire as a motivator, but fear creeps in too, often for health concerns. If you do want to change your mood, it’s helpful to know how others with similar motivations have gone about doing it, to get some ideas and approaches to adapt to your needs.
Welcome to part 4 of the QS book on mood tracking that Robin Barooah and I wrote. This chapter has some tips that we’ve found helpful for getting started with mood tracking. Enjoy!
The excitement of starting a tracking project can lead to a classic newbie behavior of tracking too many things at once. This can get tiring and confusing, so it’s important to be mindful of keeping it simple and not overdoing it. This chapter offers some tips and insights for getting started with the practicalities of mood tracking.
Keep it Simple
Ernesto Ramirez of Quantified Self Labs wrote a “QS 101” post on lessons learned from self-tracking:
“Lesson #1: Something is better than nothing. Engaging yourself in some experiment, no matter how flawed it may be, is better than never starting. The best way to learn is to do. So go out and do something!
Lesson #2: When you decide to start something, try and do the simplest thing that you think might give you some insight. It’s great to have ambitious ideas, but keeping it simple ensures your experiment is manageable.
Lesson #3: Mistakes are worthwhile. Some of our best knowledge comes from learning from our failures, so don’t be afraid of failing. By keeping it simple you also keep the mistakes small and manageable.
Lesson #4: Seek help from others. We have a great network of individuals around the world who are ready and willing to help you on your tracking journey. Find a Quantified Self meetup in your area and don’t be afraid to ask for help!”
Welcome to part 3 of the QS book on mood tracking that Robin Barooah and I wrote. This chapter explains how to prepare for your self-tracking journey. We hope it helps you in your future tracking adventures!
Before you start tracking something new, there’s an important first step you can do to lay the groundwork for a rewarding self-tracking experience. How you approach tracking your mood and looking at your results can make a significant difference in what you end up learning from it. So in this chapter we’ll explore how to cultivate a helpful mindset, accept what you discover about yourself, and keep your mind and body open to building intuition.
Cultivate The Right Mindset
When you look in the mirror, what goes through your mind? Do you judge that part of your body that you just can’t bring yourself to like? Do you gush with warm appreciation? Do you notice something out of place and calmly adjust it or make a mental note to investigate?
It’s an interesting exercise to do on its own, noticing what thoughts you have when you see a reflection of yourself. According to several recent studies, a healthy mindset involves being mindful of your thoughts without jumping into problem-solving mode, and being kind to yourself.
If you think about self-tracking as a different kind of mirror, the same logic applies. What you record about yourself is actually a very personal reflection of your inner world, and so the kind of self that you bring to bear on it will influence what effect the information has on you. If you bring a judgmental mindset to looking at your data, you will feel like you’re being judged. If you bring a curious attitude to it, it may be easier to see new patterns in what you’ve collected.
Many of the activities that make up our fast-paced modern life are easier to handle if we can make quick decisions to get results based on patterns of judgment we’ve learned through personal experience. An important principle behind the training that professional scientists receive is to learn to step back from this routine mode of thinking and consider what the data could be telling them that they haven’t noticed before.
Because we’re not used to working this way in our daily routines, it’s easy to fall back on our normal problem solving methods, and in the case of mood this often includes self-judgement.
Of course, it’s easy for us to suggest avoiding a problem-solving mindset when looking at your data, but practically speaking, how can we change our own minds?
One thing we’ve found to be effective is to name some alternative mindsets that we can cultivate. These are mindsets that most of us have experienced at one time or another, and there is nothing mysterious about them. Often just remembering that there’s another way of looking at things is enough to find a different perspective.
Here are some of the attributes we’ve found helpful when cultivating a mindset for looking at our own data:
You might find yourself starting out with reflexive judgments when you start looking at your data. “How can I be depressed again? What’s wrong with me?” This approach can lead to a painful feeling of defeat, and sometimes people give up tracking entirely soon after they begin.
If this judgmental voice comes up in your head, redirecting it towards being realistic and pragmatic can help. For example, if you’ve been depressed for much of your life, it’s pragmatic to realize that simply by recording your mood, you’re learning something, as opposed to expecting an instant cure.
This attitude can also help you weather and understand the ups and downs you will find in your mood, without necessarily trying to optimize for being up all the time. Each mood can be respected for what it is without wanting to only be happy. Another consideration is that extreme moods may interfere with tracking, and this should be expected rather than considered to be a failure.
So, a mindset of clarity can help you be more gentle with yourself, as well as not delude yourself. It’s important to look at your empirical evidence carefully, in order to avoid flights of fantasy, and to not make up negative stories about yourself. The evidence for the conclusions you reach may be in the data, or may be in obvious life history that you can remember, but you want to make sure what you conclude is based on facts, not judgments.
When you see your data, a common reaction is to want to compare yourself to others. “I hope my moods aren’t the most wildly swinging ones in the office!” This is a competitive flavor of the unkind, judgmental voice that can lead to depression. When this voice comes up, just observe your data without judgment, be very kind and gentle to yourself, and get curious.
For example, you might want to ask questions like whether your moods correlate to things like sleep or exercise, as the Optimism iPhone app does:
Long-time self-trackers have an almost insatiable curiosity. When a really good or really bad mood day happens, the analytical mind kicks in to try to see patterns. Comparing this time to previous times that were similar in some way, we try to figure out possible variables. “I took extra vitamin D this morning” or “I haven’t seen people for two days.” Then we can test these variables and see if the high or low mood is reproducible.
A benefit of this kind of self-experimentation is that it’s personalized. Rather than relying only on scientific studies that look at population averages, you can start to tease out individual ways in which you respond to your internal and external environments that may be different from conventional wisdom. More on experimentation in Chapter Four.
Finally, a good baseline attitude for life in general is one of compassion. We’ve found that self-compassion is an essential part of maintaining a tracking practice. A good technique for increasing self-compassion is to think of all the people out there who are in the same situation as you – anxious about a job interview, stressed out from dealing with fighting kids, completely in love, whatever it is. Think kind thoughts towards them, and it will help you be kind to yourself. Your data is what it is, and it’s ok. It’s nothing to be embarrassed about.
Closely related to compassion when trying to make sense of data about our own lives is the idea of humility. In our experience, mood tracking can lead to powerful and helpful insights, but they don’t always come quickly. It’s an inevitable part of the process to be confused and to not have answers when we’re learning and exploring. The reality is that a lot of the time, we just don’t know what our tracking data means, and there’s no reason why we should.
Humor is another powerful tool for developing compassion, rather than taking yourself or your data too seriously. As the Buddhist saying goes, quoted by Mihalyi Csikszentmihalyi, “Act always as if the future of the universe depends on what you do, and laugh at yourself for thinking that whatever you do makes any difference.”
Accept What You Discover
The practice of acceptance can be incredibly transformative. If you can accept yourself as you are, accept other people as they are, accept your data as it is, and accept situations around you, you will be free from secondary layers of emotion that prevent you from just dealing with whatever you need to deal with.
For example, let’s say you discover that every time you see your mother-in-law, you get angry followed by a week of depression. You have a choice here – layer frustration and resentment on top of the situation, or accept it and think about what your options are. Maybe you can talk to your spouse about finding a way to ease the trauma. It might not be as complex as you think to minimize the harm of the situation, but if you’re frustrated, you’re less likely to see the answer.
As Zen master Suzuki Roshi says, “It’s like putting a horse on top of a horse and then climbing on and trying to ride. Riding a horse is hard enough. Why add another horse?” Acceptance helps you just ride one horse at a time.
Also, feelings change us simply by being accepted and experienced even if we don’t have a plan for what to try in response to them.
Expectations come into play here. What we’ve learned is, the fewer expectations you have, about how you will respond to any particular experiment or about other people doing anything in particular, the easier life becomes. Keep moving strongly towards your inspiring intentions, just don’t expect anything to work out in the exact way you imagine.
Humans have been learning new skills for thousands of years, since long before the advent of modern science or even reason. Learning from our experiences is an innate gift we all have. The question is, which experiences do we learn from? We’d like to suggest that the experiences we learn from are the ones we pay attention to. There’s no need to take this at face value – it’s a question you can answer for yourself.
So the major gift that acceptance brings is that simply by trusting yourself to have your experiences and not trying to figure out what to change, you are still learning. Mood tracking can help us to pay attention to our mood and learn from it directly.
Build Your Intuition
This is one of the main benefits of self-tracking. A dedicated effort to look at something over time can help you to see patterns you didn’t know existed, and give you a greater awareness of yourself and how you function in the world. In the case of mood, building an intuitive understanding of how different triggers affect you makes it easier to manage and even change your mood.
A general principle we talk about at Quantified Self is: use a tool, learn a lesson, incorporate it into your life and body, then drop the tool because you don’t need it anymore. Of course, some people like to continue tracking for the sake of having data to look back on in the future, but sometimes it’s more helpful to track one or a few things deeply, until you’ve learned what you need to learn, then move on. There’s no hard and fast rule about when to be done with a particular form of tracking, but it’s worth periodically evaluating why you are tracking something and what you hope to gain from it, rather than continuing out of duty or habit.
Take the following mood chart, published by the Center for Quality Assessment and Improvement in Mental Health, which is operated by Tufts and Harvard Universities. It’s a great tool to start to be able to see your mood patterns, and can be especially useful for people with Bipolar Disorder, but you might not need to use it forever.
As part of preparing your mental state for tracking mood, recognize that by tracking you’ll get to know yourself better and that the learning isn’t just a list of facts – it affects how you feel about yourself, and you may not always have words to describe it.
For example, a person can know that she likes the taste of banana when he eats it without having to say “I like banana” in her head. Similarly, you know the mood of a painting, or a song, or someone’s expression, whether you say it to yourself or not. And after two years of mood tracking, Alex (from the story in the Introduction) can feel if she’s getting too depressed or manic and needs to change her behavior with some mood hacks to compensate. We’ll talk more about mood hacking in Chapter Four.
So armed with the right mindset of clarity, curiosity, and compassion, as well as a sense of acceptance and intuition, you’re now ready to start tracking mood. Tips for getting started are coming up in the next part of the book.
Welcome to part 2 of the QS book on mood tracking that Robin Barooah and I wrote. This chapter walks through the various ways of measuring mood. Please enjoy, and share anything we’ve missed in the comments!
How Is Mood Measured?
When someone asks you how you’re feeling, how do you reply? With a number? A color? A dot on a two-axis grid? Probably not. Chances are, you answer with words, incorporating body language, facial expressions, and maybe a verbal description of events that led to your current mood.
The person who asked you pieces all that together into a reasonable idea in their own mind of how you must be feeling. But how can that idea be captured, recorded, compared to other people’s moods, or even to your earlier moods? Are there standard, reproducible ways to measure mood that are both widely applicable and personally relevant?
The answer is… maybe. Many attempts have been made to quantify mood, from psychological assessments to online color palettes to analyses of phone conversations. We’ll explore them here, and discuss some of the ongoing debates. Think of it as a journey through the wild landscape of the mood tracking space.
POMS (Profile of Mood States) – the gold standard
If you’re looking for a psychological assessment for measuring mood fluctuations that is used in clinical and research settings, POMS is your answer. The assessment consists of 65 emotion adjectives that are each rated on a five-point scale, where 0= not at all; 1=a little; 2=moderately; 3=quite a bit; and 4=extremely. The answers are then grouped into seven dimensions to give you an overview of your mood state:
A second form of POMS has also been developed specifically for looking at Bipolar Disorder. The dimensions are slightly different:
The downside of POMS is that the questions are not freely available, and you have to be a qualified psychological professional to order them.
Circumplex vs. Evaluative Space Model – are positive and negative moods opposite?
There is some debate among psychologists whether happiness and sadness are opposites on a spectrum or can exist concurrently. Can you be happy and sad at the same time?
The circumplex camp says no. They arrange emotions on a two-dimensional grid, with one axis moving from pleasantness to unpleasantness, also called valence, and the other axis moving from activation to deactivation, also called arousal. Depending on how positive and how energetic you feel, you should be able to place a dot on an appropriate part of the grid to record your current mood, and notice how the dots move around over time.
The evaluative space camp disagrees. They argue that while emotions are often experienced as opposites, there are situations or times in life when people experience both happiness and sadness. According to this model, you should measure your positive and negative emotions separately.
There have also been studies showing that different individuals have different ways of experiencing emotions. Some people experience a strong opposite effect, others can have multiple emotions at the same time that fluctuate independently, and still others have emotions that do depend on each other but not in an opposite way. So it’s not clear that there is a single method that will work for everyone.
The fact that scientists disagree on fundamental questions such as whether we can experience more than one mood at the same time, or whether we even all experience moods in the same way, is a major reason why we believe this area is so ripe for self-experimentation. Each of us has access to our own individual experience in a way that no scientist does, and we can answer these questions for ourselves and make use of the knowledge we gain, confident that what we’ve discovered applies to us.
Mood Scoring – Moodscope
For the numerically inclined, one quick way to get a daily number for your mood is to use the PANAS-based app Moodscope. PANAS stands for Positive Affect Negative Affect Schedule. Moodscope’s adaptation of the PANAS consists of ten questions for positive affect, or mood, and ten questions for negative affect, on a 0-3 scale. The scores are then combined into one number that represents your overall mood percentage, where 100% is extremely positive and 0% is extremely negative.
At Moodscope, you rate your mood once a day and are given graphs to see how it is changing over time. The questions are presented as cards, to make it fun and to increase the accuracy of your answers by introducing a bit of extra time to stop and reflect. What the cards and graphs look like are shown below.
Measuring your mood once a day is a great start, but you may find that you want a more nuanced view of how your moods change within a day. Moodscope also allows sharing your mood with a friend for support, and lets you add descriptive words and comments to each measurement. We’ll discuss sharing mood in Chapter Four.
Artistic Expression – Moodjam
In common language, people sometimes describe their moods in color, like “I’m feeling blue.” Ian Li, a graduate student at Carnegie Mellon University, built an app that takes that a step further. It’s called Moodjam, and it lets you choose up to ten colors to represent your mood at any time of day, annotate it, and share it publicly if you like.
The act of pausing to look inward and choose colors and words to describe how you’re feeling can be an inspiring, releasing part of your day. The result is a beautiful visual representation of your mood over time. Here’s what it looks like to record a mood and to see moods of other people at Moodjam.
Text Analysis – 750 words
Perhaps the most traditional way of recording mood as part of life events is to keep some kind of written journal or diary. The practice of writing free-flowing text can be cathartic and insightful. A modern version of the daily journal is a web app called 750 words. A beautifully simple interface encourages you to write 750 words every day, which are completely private.
One benefit of an online journal is that the text can be analyzed. 750 words uses sentiment analysis to break down what common moods or thoughts your chosen words reveal. Looking at the charts can give you new clues about what your typical thoughts are. However, the primary benefit may still be just in the act of writing, allowing your subconscious to find patterns and your intuition to develop.
Emotional Stroop Test
As it turns out, there is also a cognitive measurement that can objectively detect different emotions being experienced by a person. If you’ve ever seen those cognitive tests where the word “blue” is written in the color red, and you have to name the color instead of reading the word, that’s a Stroop test.
The emotional version of the Stroop test is to show people a series of words, some of which are emotional, and ask them to name the color of the word when it appears. If a person is feeling anxious, they will delay slightly before naming the color of the word “anxiety” compared to naming the color of an emotion they’re not experiencing or a non-emotional word. The delay in the response time indicates the level of emotion. No online version of this test is currently available.
So these are some of the active ways of tracking mood, where your input is required in some way. There are also a few passive ways emerging that are worth noting.
Voice Analysis – Cogito Health
Researchers at MIT have discovered that analyzing the spectral and temporal patterns of voice conversations can identify depression or psychological distress. A company called Cogito Health is commercializing this technology to help call centers become more effective as well as track behavioral health at a population level.
Presumably, the same technology could be made available to individuals to monitor their own phone calls. Imagine talking to a friend by phone and getting a text message signaling you that she is depressed, even if you can’t necessarily tell by the way she is talking. Faking a cheerful mood with each other would become more challenging! And you might become more empathetic friends.
Facial Recognition and Skin Conductance – Affectiva
What about measuring emotional states just by looking at people’s faces, or detecting arousal from skin conductance? Affectiva is a company working on both of these methods. Their Affdex system uses webcams to measure people’s reactions to marketing campaigns, as a way to detect whether consumers are engaged, surprised, confused, or turned off by their ads. A very commercial application to begin with, but a system like this made available to individuals could help you figure out things like whether checking email always leaves you in distress, especially when your cranky Aunt Edna writes to you.
Affectiva’s other product is called Q Sensor. It’s a wireless wristband that detects electrical activity on your skin as you go about your day. High activity means you’re excited or anxious, low activity means you’re bored or relaxed. It is currently being used for clinical and academic research, and is prohibitively expensive for many individuals, but it’s a fascinating signal of what’s coming down the road. One fascinating application is helping people with autism to communicate their internal states. Instead of seeming perfectly calm and then erupting into an unexpected meltdown, autistic individuals can use the Q Sensor to show their caregiver the rising stress level they feel well before meltdown occurs, and the caregiver is able to intervene with calming activities or a change in environment.
Music Patterns – Last.fm
The music we choose to listen to, and whether we choose to listen to music or not, can be other good indicators of how we’re feeling. At a Quantified Self meetup in Amsterdam, Remko Siemerink described how he discovered a pattern of listening to music intensely when he’s feeling good, and not listening to music when he is feeling depressed, usually in the summer.
Last.fm is an online radio station that tracks all the music you listen to, and provides an API for external services like LastGraph to display your music listening habits over time as beautiful charts. It could be a useful proxy for measuring mood.
Robin, one of the authors of this book, has been tracking his meditation practice for the past 3 years. His main goal in doing this was to help him get into the habit of a regular daily meditation practice. Unexpectedly, this turned out to be a rich source of information about his mood.
“I discovered that the periods of time when I wasn’t meditating corresponded with times when I was suffering from depression. These were long gaps, of a month or more, and it was very easy to remember how I’d been feeling and what was going on in my life during those times. I could see that the gaps corresponded with life events that altered my routines of work and connection with friends.
The surprise for me was that looking at the simple long term pattern of my meditation practice provided me with insights about major changes in my mood that I couldn’t see from looking at my daily mood diary.
I’ve now learned that skipping meditation for more than a couple of days is generally a warning sign that I’m at risk of falling into a depression. Medicine is starting to recognize meditation as one of the most effective treatments for depression, so it’s likely that the meditation itself is protecting me. Tracking helped me to see how disruption in my life both brought on depression and disrupted my meditation practice at the same time.
Since learning this, I’ve been able to take action when I start to notice the pattern – both by making meditation more of a priority in times of stress, and by recognizing that a few days of missed meditations means that I need to be more gentle with myself as I adapt to change.
I’ve known for a long time that meditation was very helpful for depression, but it wasn’t until I saw my pattern for myself that I really understood how important it was in my own life.”
These last two examples illustrate how behavior can be an indirect way to investigate mood, and how different methods of tracking can provide us with different kinds of insights. They also show how we can learn different things about our mood depending on the timescale we are looking at. It’s possible that you’re already doing something that could give you insight into your mood if you tracked it – maybe how often you shower, or how many text messages you send at what times, or your patterns of food consumption.
Whatever method you choose, whether active or passive, clinical or colorful, it helps to know how to go about using the tool. In the following chapters we’ll share some principles for how to think about mood tracking to maximize benefit to your life, followed by practical details for getting started.
If you’re curious about mood tracking, you’re in for a treat. Robin Barooah and I have written a book compiling our knowledge and experiences of mood tracking, and we’ll be posting chapters of the book here for your enjoyment and feedback.
Without further ado, here is the introduction!
Alex’s story: I can honestly say that mood tracking saved and transformed my life. I’ve battled depression off and on for twenty years, but tracking my mood every day for the past two and a half years has brought more positive change than I could have imagined when I started.
At Quantified Self, we ask people to tell their stories by answering three questions: What did you do? How did you do it? What did you learn?
What I did was to record my mood, one to eight times per day, whenever I felt like it.
How I did it was to write. A lot. Whatever was on my mind, from how the day went to processing painful experiences to celebrating insights. And, importantly, I shared what I was writing with a trusted friend, who was also sharing his mood with me. Knowing that someone was reading and listening to my posts helped me to be more gentle with myself and make faster progress.
What I learned could fill a book in itself! In a nutshell, I’ve learned to notice and accept up and down patterns of my mood, to welcome emotions rather than try to bury them only to have them come back stronger, to discover sensory sensitivities and design my environment to minimize their impact on my well-being, and to increase my awareness of how different foods and social situations affect me.
Tracking has also created a safe space where it’s okay to pour out any kind of emotion, no matter how hard or how wonderful it is. This space is very comforting, because I know I’m never alone. And I know that when I’m down, things will go back up again, because I can see that they always have in the past.
So for me, mood tracking makes the dark times seem less dark, and helps me to see patterns in my life that I like and want to reinforce, or that I think need to be changed for me to thrive. It has made me much more aware of myself and how I’m influenced by people and things around me. I’ve also made an amazing, trusted friend. Wins all around!
Robin’s story: My first experiences with mood tracking came in my teenage years. I was inspired by one of my schoolmates who was keeping a secret diary. He guarded it closely, and would occasionally read excerpts to his friends. I was struck by how listening to him seemed to bring a lightness and excitement to the kinds of events that had previously seemed mundane or challenging.
This was in the days before laptops, and I wasn’t good at writing quickly and comfortably with a pen, so I borrowed an electric typewriter and started to type out my thoughts and experiences.
I think this was the first time I’d written anything without being told to by an adult and the process was so cathartic that I quickly went through a whole ribbon. By chance, this helped me discover something that has stayed with me through my life. Being a schoolboy, I couldn’t afford to replace the expensive carbon ribbon, so I tried to make the ribbon go backwards by taking apart the cartridge and turning over the spools. The typewriter worked again but the text it produced was broken up and I could only read it if I looked carefully.
To my great surprise, I found myself writing even faster and expressing the more difficult emotional issues that plagued me. It turned out that not being able to clearly read what I had written freed me from getting caught up in judging and analyzing my thoughts, and this helped me to feel better.
Over the years, I experimented with many different variations of this process. I would often turn to such writing when I experienced particular turmoil or challenge. At some point in the last five years, I realized that I was only writing when there was something seriously wrong, and that I associated the writing itself with pain and angst.
Around the same time I started to believe that I tend to grow in the direction where I place my attention and so I felt a growing desire to know more about my experiences in the positive times in my life.
I played with a number of mood recording tools, in the end settling on making simple notes in a calendar – just one word if necessary, or more if I felt like it. Simply having this record has helped me to see how I change from day to day, and week to week. In particular, it lets me see the slow changes in myself that I wouldn’t have seen without it, and that have helped me to become more accepting.
I too chose to share my mood records with a friend, and this has created another set of benefits for me. While not without challenges to be negotiated, sharing my mood record has helped me to feel a sense of community and connectedness that I’ve always felt was weak in my life. Having a witness to my own challenges has helped me learn to communicate more gently with myself as well as with others, and seeing another person’s vulnerable struggle has helped me to feel more human when I am struggling.
Everyone feels happy, angry, anxious, and depressed sometimes. Mood changes are a normal part of everyday life, and some people can roll with them smoothly. For many, though, mood can be a challenging thing to manage. Depression affects about 121 million people worldwide, with many more going undiagnosed, and is the leading cause of disability. Anxiety disorders touch 16% of people globally at some point in their lives.
The question is, can tracking your mood improve your mood, or make life easier in some way? Is there any evidence of this beyond anecdotes like our stories above?
Well, yes, there is. People who live with Bipolar Disorder use mood tracking to understand and lessen the effects of their mood swings. When a change in mood is happening, it can be detected early to give them advance warning for some kind of intervention. Charting moods, in combination with other psychosocial strategies like cognitive behavioral therapy, has been shown to help people better regulate extreme moods.
Researchers also use mood tracking to predict different people’s response to a particular drug, to differentiate and diagnose different kinds of mood disorders, and to help doctors and therapists monitor their patients’ mood progression under the influence of different treatments.
Great, you say, so is this just for people with mood disorders, or will it help me be happier in my life? That’s an excellent question. The recent explosion of mood tracking apps with names like Track Your Happiness suggests that being more aware of your moods and what affects them can steer you towards greater happiness in life. The folks behind the app Mood Panda aggregated statistics from all of their global users in 2011 and looked for patterns. They discovered that work has the biggest influence on mood at a population level, and women are unhappy on Wednesdays. However, one can find any pattern in data if one looks closely enough. Well-designed longitudinal studies to test the effect of mood tracking as an intervention on overall mood have yet to be done.
An important thing to realize is that happiness is not necessarily the goal of mood tracking.
An excessive focus on happiness would seem to be almost disrespectful to the wide range of possible human emotions that lift us up, teach us, and make life rich and varied. A more thoughtful goal, or intention, or reason to try tracking mood, is simply to increase awareness. The act of pausing to check in with yourself about how you’re feeling in different situations, as well as looking back to similar situations in the past, can help you see trends and influences on your mood that you may not ever have noticed. You may also find yourself being able to differentiate moods in a more granular way, building a vocabulary of emotion and increasing the dimensionality of your mood perception abilities.
There is a significant difference between the knowledge that we discover for ourselves, and knowledge that we receive from others. If you have ever cooked a dish from a recipe, you’ll know that simply reading the recipe doesn’t mean that you know the dish it describes. You learn the dish by trying to make it, by tasting as you go along and experimenting. Along the way, the things that the author of the recipe could never know – your local ingredients, your stove, your cooking style, and your tastes, get incorporated into what you do, and the dish becomes your own.
So it is with self-knowledge. When you monitor and experiment with your own moods and emotions, you learn about yourself through direct experience, and the knowledge you gain becomes part of who you are.
If there’s one thing that we would like this book to convey, it is the idea that experimenting with your life and paying attention to how you feel, using all the tools available in our modern world, can help you grow as a human being and ultimately make more sense of your life.
In the following chapters, we will flesh out these topics, give you an overview of the different ways to go about tracking mood, share inside tips on how to get started easily and effectively, and discuss the importance of subtler points like mood sharing, feedback loops, and your environment. Stay tuned!