Tag Archives: mood
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!
Sami Inkinen, triathalete, self-quantifier, and founder of Trulia, measures his mood on a five point scale every morning, within five minutes of waking up. This method fascinates me. I do something similar (though I use only a three point scale). Sami has found that this quick and easy measurement reliably correlates with his athletic performance, suggesting that it indeed measures something significant about his overall well being in the day ahead.
Read Sami’s full post here: What the first 2 minutes after waking up can tell you about the day ahead?
“How do you feel right now?” Such a short question can lead us toward profound insights into our lives. But how do we ask ourselves that question? How do we keep track of our answers? There are many different ideas out there about how to tackle this seemingly simple question. Many of them focus on mood, which we’ve covered in previous Toolmaker Talks (see our posts about Happiness and Mood Panda). We’re going to explore another idea in his week’s Toolmaker Talk with Jonathan Cohen, the man behind the new (and soon to be released) app, Expereal.
Q: How do you describe Expereal? What is it?
Jonathan: Expereal is a simple iPhone app that allows people to rate, analyze, share and compare their lives. It was created to help people better understand their lives holistically, answering a most human question that cognitive biases can distort: “How’s my life going now relative to other time periods, friends and other users around the world?” In order to arrive at an answer, the app requires active participation, which it prompts via push messages (which can be turned off), requiring users to consistently rate their lives over time. Though it is unclear of whether millions of users care to actively measure their life, I went this route as a minimal viable product, because I was unconvinced of passive measurement’s efficacy, which crashes on the rocks of language interpretation and context.
Q: What’s the backstory? What led to it?
Jonathan: I read Daniel Kahneman’s book “Thinking, Fast and Slow,” which outlined the duality and inconsistencies in the experiencing and remembering selves. I wondered if there might be some value in capturing the subjective opinion of the experiencing self over time to counterbalance the remembering self’s so-called “peak-end bias.” What I found quite interesting was that the peak end bias doesn’t only affect our view of past events; it also influences how we think of our lives holistically in the present tense. Imagine walking out of a terrible meeting in which your boss publicly reprimanded you for incompetence, and someone asks how your life is going. How would our answer be influenced? Would that answer accurately reflect our perceptions across a wider swath of time? It is unlikely, as the preceding moment would act as an “anchor” in assessing our present moment lives.
From what I can discern, Kahneman doesn’t necessarily argue that the remembering self is “wrong” per se; he merely illuminates that it inaccurately captures the experiencing self. In his book and TED talk, he slyly asks the rhetorical question if we had to plan a vacation, would we plan it to satisfy our experiencing or remembering selves? In any cae, I thought that it would be valuable to have a more holistic perspective on my life that offered an alternate, longitudinal vantage point than what the ever-present peak end bias might offer. Furthermore, I hoped that such information might help me “know myself better” and potentially make better decisions. I then wondered if others had similar questions and desires.
Q: What impact has it had? What have you heard from users?
Jonathan: The app is in alpha testing. I have received a range of feedback – some quite positive (about the design and the app’s social nature) and some quite negative (“It’s not very useful for me. It takes a lot for me to really think about my mood, not just a 1-10 rating.” as well as “What exactly am I rating 1-10?”) The strongest critique, which strikes at the app’s very viability as a product and business, is that most people are not really that interested in measuring themselves, particularly actively over time. Consequently, Expereal needs to offer something immediate and compelling to encourage people to interact with the app. What’s the immediate feedback that makes it both useful and “sticky”?
Q: What makes it different, sets it apart?
Jonathan: Simplicity: I created the initial capture mechanism to be dead simple: “How’s your life going right now? 1-10.” If the user has to think about it, he’s overthinking. It wasn’t intended to measure “mood”, though it could be used as such. The Capture Details screen is totally optional, allowing additional information to be ascribed to a rating.
Aesthetics: Expereal was designed to look different from other apps, not so simple given that there are several hundred thousand. I was most inspired by the LACMA exhibition catalog “Living in a Modern Way: California Design 1930-1965” and, to a slightly lesser extent, Edward Tufte’s data visualization books. I also respect the work of numerous “quantified selfers”, “data visualizationalists” and artists, including Jonathan Harris, Nicholas Felton, Jer Thorp, Jan Willem Tulp and countless others – many of whom consistently speak at the Eyeo Festival.
Social: I initially wanted to make the app solitary, because I was concerned that sharing one’s Expereal Ratings with friends would skew results, where users would only rate their lives when they were going well. I ended up taking a middle course: one can optionally share an Expereal Rating to Facebook, and one’s ratings and descriptions are used in anonymous aggregates. It could become more social depending on audience demand, but I want Expereal to remain true its core of helping users better understand their lives. It’s not meant to be another social network or to replicate Facebook, Path or Twitter, which could all be future partners.
Q: What are you doing next? How do you see Expereal evolving?
Jonathan: Expereal should be available in the app store in November. I have numerous ideas and dreams, but it will ultimately depend on user interest. Again, the core challenge is giving people who haven’t shown interest in active measurement inspiration to continually engage. I suspect that for most potential users, the social component will be a greater driver of interest and usage than advanced personal analytics, but am happy to be proven wrong and will adapt accordingly.
Q: Anything else you’d like to say?
Jonathan: Going from an idea to an app is an incredible challenge, yet even after it “ships”, it feels like the beginning of infinity. There are just so many possible permutations and extensions of what might happen. In another chapter of “Thinking,” Kahneman wonders why so many people start businesses without considering the terrible odds against succeeding. Right now, without question, I feel that it’s been a worthwhile endeavor. I’d give my life right now a ‘9’, describing it “rewarding”, “exciting” and “harrowing.” I love a challenge
This is the 17th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned? In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at or Ernesto Ramirez.
Evan Savage has panic attacks, especially triggered by caffeine while driving. In late 2011, he was having multiple panic attacks a week. He didn’t want to take drugs, so he made his own recovery plan – logging his food, exercise, and panic attacks. He eliminated caffeine, and thought he had recovered, then relapsed. In the video below, Evan tells the courageous and entertaining story of how he has navigated through recovery and relapse multiple times, and what he has learned about how to thrive. (Filmed by the Bay Area QS Show&Tell meetup group.)
In talking with many toolmakers, I find myself constantly surprised by how different people approach the same, and seemingly simple, issue with very different perspectives. A few months ago I wrote about Mood Panda which went from private to community. In contrast, Michael Forrest’s Happiness has evolved from shared to private. I also find Michael’s experimentation with the look of his app both beautiful and fascinating.
Q: How do you describe Happiness? What is it?
Forrest: Happiness is an iOS mood tracking app. You get randomized reminders to record your mood, and then can view this data graphically and as a journal. The idea is that by using this app, you’ll be able to make better decisions in your life.
Q: What’s the back story? What led to it?
Forrest: I’ve always been inspired by technology’s potential to solve old problems in new ways. I was looking for novel ways to solve mental health problems without resorting to pharmaceutical hacks like antidepressants. I came across Daniel Gilbert’s TED talk “Why Are We Happy?” and read his book where he talks about the marked differences between what we think will make us happy versus what will actually make us happy.. My idea was that even if we can’t make good predictions about how we’ll feel in the future, we can at least start gathering accurate data about our past and use that to reflect on the present moment. I first built a Facebook app, and then moved to the iPhone.
Q: What impact has it had? What have you heard from users?
Forrest: I’ve sold a few copies without doing a great deal of marketing – people seem to discover it on their own. The feedback I have had has been amazing – when it helps people, it is helping them with a fundamental aspect of their life so it didn’t seem beyond the bounds of reason when one user told me it was the ‘single best reason for owning an iPhone’. I have seen an increase in uptake since I put this page together http://goodtohear.co.uk/happiness – people are finally starting to see the point of it and I’ve been getting useful feedback about details of the UI and so on. I’m still really only starting out though.
Q: What makes it different, sets it apart?
Forrest: I know my app isn’t the only way to track your mood, but I want it to be the best way to do so. A lot of decisions have gone into this seemingly simple app.
Single focus: I have deliberately avoided trying to track any other information because happiness has an infinite variety of possible influences that I would never presume to be able to predict for any particular user.
Design: It was important to me that I give the app a personality of its own. Finding a look that wouldn’t interfere with the user’s mood (or annoy them) but still had some personality was not trivial. Initially I drew from artists like Kandinsky and Miro (see here) for the style but over time realised that a journal was a more appropriate look. I have avoided smiley faces in the latest and came up with a very tactile way to report mood from a blank canvas – I don’t want the app to influence the user’s mood in any way at the reporting stage by suggesting anything (but it should still look good!).
Exploration: The charts in Happiness have evolved a lot over time. My original designs were largely tag cloud based. As I personally accumulated entries (I have over 700 reports in my database!) I realised that time-based reporting would become increasingly important. After a lot of trial and error I settled on a monthly reporting cycle. I also made the graphs simple by moving away from multicoloured heatmaps to simple areas filled with red or green. The algorithms used to calculate these areas need to be complex enough to find patterns but self-evident enough that when users look at the reports these seem to match their input. Details of the reports give the tool different usage styles. Simply by numbering my ranked taggings I’ve now started setting myself challenges (e.g. move “Music” from #2 in my life to #1!). There’s also something interesting about getting a blank slate each month to see if you can do better than last month.
Price: Happiness isn’t a free app, and this is a conscious decision. I want users to feel invested immediately since you don’t get instant gratification. The price will always stay around this level while I continue to add value to the app in a multitude of ways.
Privacy: A big benefit of making this app as a native iPhone app is that the data can be stored locally. I want users to feel they can be 100% honest when writing in their diary. There’s even a passcode lock feature to make sure people definitely can’t get in, even if your phone is unlocked.
Q: What are you doing next? How do you see Happiness evolving?
Forrest: Soon I’ll be releasing an iPad version of the app that will sync data via iCloud, and enable larger, more in-depth views of the data. I’ve done some fun experiments around bringing in information and media from users’ social networks which really helps contextualise the more private comments. I like the idea of people being able to share their mood maps as artworks so I have some ideas around this – making this possible without necessarily revealing details to the world.
Q: Anything else you’d like to say?
Forrest: I’m working as a one-man-team on this project. I love that it’s possible to achieve so much on my own but I’d also prefer to be working more collaboratively. I’m looking into clinical trials, and enabling others to build their own visualizations. Happiness is such a fertile subject that I’ve barely scratched the surface of what is possible with this tool. So if anybody feels inspired by what I’ve done so far and can see opportunities to work together, get in touch.
Price: $1.99 / £1.49
This is the 15th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned? In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at firstname.lastname@example.org.
Gareth MacLeod is a developer/entrepreneur interested in making QS techniques easy to incorporate into daily life. He built an app that sends him text messages to ask about his sleep, mood, romantic encounters, tooth brushing, etc. He then looks for correlations among the different data streams, and even spent 100 hours building a correlation heat map. In the video below, Gareth talks about how to engineer the perfect day, and interesting things he has learned, like if he watches TV before bed, he feels grumpy the next day. (Filmed by the Toronto QS Show&Tell meetup group.)
Randy Sargent has an hypothesis that eating certain foods, like tomatoes, makes him irritable and anxious. He asked himself, “How can I structure an experiment on myself so that I don’t know whether I’m eating tomatoes or not?” and “How would I go about quantifying my irritability?” In the video below, he explores ways to go about designing the experiment, with some fun input from the audience. (Filmed by the Pittsburgh QS Show&Tell meetup group.)
I have finally figured out my mood! After 16 months and 300,000 words of mood tracking data, which I shared with a friend, I have a painstakingly compiled list of hacks that balance my extreme mood swings and make life much smoother for me.
So, like a good QS’er, I’m sharing what I learned. Maybe it will help someone else out there. I’ve broken down the insights into four categories.
1. Accept, accept, accept
The practice of acceptance has been incredibly transformative. If you can accept yourself as you are, accept other people as they are, 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, say that someone you love promises to do something for you, and then doesn’t do it. You have a choice here – layer frustration and anger on top of the situation, or accept it and check in with the person to see what happened. Maybe they forgot because they were feeling sick, or are stressed out at work. It probably doesn’t mean they don’t care.
As Zen master Suzuki Roshi said, “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.
Expectations come into play here as well. What I’ve learned is, the fewer expectations you have, especially 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. And if you do have a particular expectation, make sure to communicate it to the people who you’re expecting to meet it!
2. Create social algorithms
I used to have massive social anxiety coupled with an intense fear of abandonment, which often led me to isolation and depression. I was even afraid to go to QS meetups for a long while! Here are three tips I learned to make socializing smoother for me:
- Always have a buddy. Before I go to a meetup or a conference, I always ask someone to be my buddy. It has to be someone I feel safe with and who is also going to the same event (or willing to be invited.) Being a buddy means I can sit next to them, and check in with them for a hug or a quick update on how I’m feeling. At first it was hard to ask, but I soon realized that other people were also often relieved to have a buddy!
- Figure out how you engage best. For me, conference calls and group meetings are death. Coffee shops and most restaurants are too loud. So I suggest one-on-one walks with people, usually in a beautiful park or outside nature space. Again, most folks are happy to have this option of getting fresh air and exercise as well as connection. And I’m more comfortable, so I’m able to listen, give, and connect better.
- Spread out social events. Everyone will have their own balance for this one. I noticed that I get depressed if I’ve been at home for more than two days in a row, and I get a tad too manic if I’m out having meetings for more than two days in a row. This is a simple heuristic that makes it easy to decide when to put things in my calendar.
3. Pay attention to sensory experiences
I became aware of the importance of sensory experience after reading up on sensory processing differences and a sensory theory of autism. Once I tuned in and started noticing my environment, I discovered I could:
- Comfort my skin. Wearing uncomfortable clothes makes me irritable. So I gave away all my jeans, high heels, bras, anything that felt constricting or tight. I’m so much happier wearing comfy clothes all the time.
- Protect my ears. Loud machines are very draining. I noticed that riding on a train or airplane, walking down a busy street, or working at a coffee shop with that grinder going off periodically was tiring me out quite a lot. So I bought myself a pair of Bose QC15 noise canceling headphones, and I wear them every day. It also helps to put me in the zone for productive work, with playlists full of beats (for coding), love songs (for community building), or mellow ambient music (for chats.)
- Improve my sleep. I started tracking sensory experiences that interfered with my sleep, and discovered sound and light to be the main challenges. I now wear blue blockers for the last two hours before bed, have a white noise machine in my room, wear these earplugs, and try to make sure everyone in my house has used the bathroom before I go to bed so they won’t have to come in and turn on the light too often. My sleep is so much better, and my mood is too!
- Have awesome hugs! After hearing about Temple Grandin’s experience of being calmed by a squeeze machine, I started noticing that hugs (especially good, solid, squeezy hugs) really calmed me down too. People who I feel safe enough to hug deeply will notice it after ten or twenty seconds – my body just starts to melt and relax. So I started offering to hug people more, and even proudly broadcast on my social media descriptions and chat status that I love hugs. Now people send me random hugs by chat, which always make me smile. I also get more hugs in person, which further helps me to be comfortable in social situations!
4. Do the opposite from what you feel
This is the final piece that made me feel like I’d finally solved mood. Credit goes to Marcin Kowrygo from QS Poland and Simon Frid from the first QS discussion group for giving me the pieces of this last puzzle.
Basically, if you’re depressed, act as you would if you were excited, and if you’re manic, act as you would if you were depressed.
So now when I’m feeling down, I go for a fast walk in the bright sunshine with loud music, I eat less, try to chat with people more or invite someone out, and try to wake up extra early. When I’m feeling too hyper, I slow down, lie in a dark room with quiet or sad music, eat a bit extra, try to be alone, and try to get lots of sleep.
This is going against what my body feels like doing in the moment, but it definitely works to curb the extreme ups and downs that I otherwise feed and amplify. I like to think of it as CBT (cognitive behavioral therapy) without the C.
So these are my distilled insights from 16 months of intense mood tracking, at least an hour of writing a day. If you have any insights or hacks of your own on how you balance mood, I’d love to hear them in the comments below!!
As for my next experiment, I think it might have to do with measuring and modifying time perception. Stay tuned for that…
Our QS Conferences are organized to maximize discovery and serendipity. The entire program results from us inviting attendees to present and participate. You’re never quite sure what you’ll get, but it’s hardly ever boring! I didn’t know what to expect when Caspar Addyman took the stage in Amsterdam to talk about “Tracking your brain on booze”, but he very quickly grabbed my attention. His talk reminded me that, as Malcolm Gladwell once reported, “How much people drink may matter less than how they drink it.”
Q: How do you describe Boozerlyzer? What is it?
Addyman: The Boozerlyzer is a drinks-tracking app for Android phones. It lets you count your drinks and their calories and tells you your current blood alcohol. Crucially, it also lets you record your mood and play a range of simple games that measure your coordination, reaction time, memory and judgment.
What Boozerlyzer explicitly does not do is tell people how much to drink. We think people would find it patronizing and off-putting. Rather we hope that it will help people get better insight into how drinking affects them.
In addition, if users agree, their data is sent to our servers to contribute to our research on how drink affects people. I’m a researcher with the Center for Brain and Cognitive Development, Birkbeck College, University of London, and this project was started as a way to collect data beyond the artificial setting of a laboratory.
Addyman: I originally had the idea back in 2003 while doing my undergraduate psychology degree. I was interested in how to study the affects of recreational drugs. The web technology of the time couldn’t be used when people were out at the pub or club so I didn’t pursue it.
In summer of 2010 I took part in a science & technology hack day in London and the idea occurred to me again, this time using smartphones. So I told a few friends about it. Mark Carrigan, a sociologist at Warwick University, opened my eyes to the more sociological types of data that we could gather. This broadened the aims from my initial very cognitive focus to think about the emotional and social experiences involved with drugs and alcohol. That was at the end of 2010. All that remained then was to invent the app. I’m not really a developer and have been working on this in my spare time so it has taken longer than I’d expected.
Q: What impact has it had? What have you heard from users?
Addyman: I have been using the app myself for 6 months now and the thing that has surprised me the most is how rapidly the drinks accumulate if I’m out with friends. A few drinks early in an evening, then a couple of glasses of wine with a meal and then more drinks all through the night. Over a particularly sociable weekend I find myself drinking a disturbing amount even though it doesn’t seem that way at the time.
We started our first public beta in December 2011 and have a hundred or so users. I still have to analyse the first batch of data and usage statistics. But, a first look at the data from December and January showed something surprising: the Christmas season seems to ratchet up drinking levels, normalising heavy drinking on into January. Unfortunately, I don’t think I’ve got enough data to tell if this is real trend.
In terms of direct feedback from users, generally, we’ve had positive reaction to the idea but there are plenty of things we can improve. One of the biggest problems with the enterprise is that our users forget to actually use the app when in the bar, or when they’ve stopped drinking. Also, people are willing to track their drinks and their mood as they go along, as that takes very little time. But at the moment the games take a little too long to play, and the game feedback is a bit too abstract. We aren’t yet giving estimates of drunkeness based on game performance. Here we are in a bit of Catch 22: more compelling feedback ought to be possible once we’ve got a reasonable base set of group data to run some regression analysis but without interesting feedback we have trouble getting people to play the game in the first place.
Q: What makes it different, sets it apart?
Addyman: One big difference between our app and many tools in the personal health world is that our focus is not on behavior change, but instead on data for scientific research and self-learning.
Also, this is an academic, non-commercial project. Our app will always be free. We will never collected any data that could directly identify you nor will we sell any of the data we collect. We believe in open systems, open data and open minds. The code we write is open sourced. The data we collect will be available to anyone that wants to study it.
Q: What are you doing next? How do you see Boozerlyzer evolving?
Addyman: The Boozerlyzer is our first app and there are still plenty of improvements to make to it. But, in addition, we want to broaden our scope and apply the same principle to recreational drugs and the effects of various medications.
As an example, I met Sara Riggare Sara Riggare from the Parkinson’s Movement at the Amsterdam QS conference. She pointed out that a version of Boozerlyzer could help Parkinson’s patients track their medication intake and quantify the effects of the medications on mood, coordination, memory, etc. We are starting a collaboration to redesign the app for this purpose.
Meanwhile, my own motivation for starting this project was always to be able to do better research into recreational drugs. This has never been a more pressing concern, and I am hoping that a drugs tracker app can help. Obviously, this is fraught with legal and ethical difficulties so we are having to tread carefully. See here and here for more background on this.
Q: Anything else you’d like to say?
Addyman: We have already benefited greatly from our contact with QS community. The conference was a great inspiration and I wish could get to more of the lively London meet ups. If anyone out there would like to get involved with our project, we’d love to hear from you. Any advice or experience you could lend us would be greatly appreciated. Our project is both open source and open science. We believe in the power of collaboration and so would love to hear from anyone with similar projects in mind.
This is the 12th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned? In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at email@example.com.