Tag Archives: mood
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.
In 2007, Jon Cousins started tracking his mood to help NHS psychiatrists decide if he was cyclothymic (a mild form of bipolar disorder). After a few months of tracking, he started sharing his scores with a friend, who expressed concern when his score was low. Jon’s mood sharply improved, apparently because of the sharing. This led him to start Moodscope, a website that makes it easy to track your mood and share the results.
I was curious about the generality of what happened to Jon — how does sharing mood ratings affect other people? In January, Jon kindly posted a short survey about this. More than 100 people replied.
Their answers surprised me. First, in a survey about sharing your mood — not about tracking your mood — most respondents did not share their mood. It is as if, in a survey about being tall, most respondents were not tall. Second, although Jon’s mood sharply rose as soon as he started sharing, this was not the usual experience. Sharing helped, some people said, but other people said sharing hurt. For example, one person said her mood was used against her in arguments. Finally, the respondents gave all sorts of persuasive reasons that rating their mood helped them. To me, at least, the value of mood rating isn’t obvious. I can list a dozen hypothetical benefits but whether they actually happen is unclear to me. I rated my mood for years and did it only to learn about the effects of morning faces. MoodPanda, another mood-rating site, gives a few brief vague unenthusiastic reasons to track your mood. And their site is all about mood rating.
In contrast, Moodscope users were clear and enthusiastic about the value of tracking. Here are some reasons they liked mood-tracking:
It is useful to look back sometimes to help you find ways of ‘keeping up’ a positive mood/outlook.
My mood range has definitely narrowed since starting mood stabilizers, so using Moodscope has given me solid evidence that the treatment is working well. I also run statistical analyses of my mood charts against variables like sleep, medication use, and alcohol consumption. The correlations were not particularly meaningful using a 9-point Likert-like scale from a standard mood chart. When I used my Moodscope scores instead, I suddenly found that some of the correlations are (ridiculously!) statistically significant, which also made me feel more certain about what I need to do and change to better manage my mental health.
I could express my miserableness in total safety, without leaning on anybody else. It has proved wonderful. My profile has risen from a score of 7 on day 1 (11 months ago) to the 90s now. Being able to track my reasons for feeling better or worse has been part of this. The patterns are visible, ditto the triggers that send me up or down.
The great benefit of Moodscope has been to confirm the advantages of my own lifestyle management for coping with bipolar disorder. It has shown that what I felt was bad for me, is indeed bad, and what I felt was good for me, is indeed good. (I know that I have to take the meds.)
It helps that I can post things about sleep hours in the comments and see the correlation to the chart.
I have found the tool immensely helpful in gaining insight into how my own behaviour and thoughts can impact upon my mental health. I have gained more control.
It helps me to gain insight into my moods, take responsibility for them and steer a calmer, more productive course through life.
It allows me not to panic when I am low as I can see that ups and downs are all part of life.
Pre-Moodscope, I would not realize i was on the way down until 10 or so days had passed, and so I had done nothing. But with Moodscope, I can see if it’s a trend and do something immediately. It means I deliberately intervene earlier.
I use my scores, and comments, to understand what triggers my low mood and take steps to stop it getting lower, in so far as I am able.
I view it as a diary of sorts, private for my own contemplation.
I want to catch myself before I make a deep plunge and stay down too long. I do use the info with my doctor. I love having something concrete to show and talk about.
It has helped me feel like there is a greater safety net there, and given me a greater awareness of when I’m slipping back into my treacle pit; I now know that any score between 20 and 30 means I am in dangerous territory and need to take some remedial action, and if I get below 20 then I’m really in a bad way.
Moodscope has helped me identify incidents in my life with my mood. For example if I have to assert myself strongly with someone, I feel exhilarated and very proud of myself for about two day then gradually my mood will lower and a week later I will feel apathetic and down. I love that it is helping me make sense of my emotions and as a result I am not judgmental of them.
I’ve found Moodscope really useful in finding out what influences my moods. I am bipolar and after 20 years on lithium I’m managing without any meds. Don’t worry, I came off it slowly, under medical supervision!
I use Moodscope as a sort of diary of how I am feeling. Looking back I can see what really pushed my mood down and oddly it’s not always the major things that you’d imagine. In my case depression is brought on more by physical health problems – I am a CFS sufferer.
I sum up their reasons like this: 1. Helps understand causality (what causes mood to be low or high?). 2. Immediate guidance (should I take action to raise it?). 3. Self-expression (similar to diary). 4. Reassurance (low moods are “part of life”). Alexandra Carmichael wrote about the value of mood-tracking and mood-sharing. Her experience did not repeat Jon’s: She found little initial benefit of sharing, but great eventual benefits (“a kind of deep, healing therapy”). This was the main benefit of tracking for her — that it allowed this sharing. Kari Sullivan also tried Moodscope. She didn’t share her mood. The benefits she list fall under the heading of Reason #1 (helps understand causality). For example, she learned “most social interaction lowers my mood,” which surprised her.
Not everyone liked tracking:
My girlfriend . . . stopped using Moodscope. In her words, “I don’t want Moodscope to remind me how terrible I’m doing.”
She has now decided to give up on taking the test as it just reinforces her feelings of general greyness and sometimes despair.
At a website devoted to collecting new ideas about health, Moodscope ranked #1 out of about 500 ideas.
When I started my self-experimentation I didn’t get anywhere for a long time (after initial success with acne). After 1990, however, I was astonished at the progress I made. One useful discovery after another — how to lose weight, sleep better, be in a better mood, and so on. Over the next 20 years, I improved my health considerably more than all the other scientists in the world put together. I came to see what was happening as a kind of catalysis. The useful information was already there; my personal science was the catalyst that turned it into something useful. (Lack of people like me was why the discoveries were so abundant — a counter-example to Tyler Cowen’s lack-of-low-hanging fruit explanation for stagnation.) Professional scientists were too restricted in what they did.
The Moodscope story is similar. Psychologists have been studying and measuring mood for a long time. The Profile of Mood States is an important result of their research. But no psychologist saw it as an agent of change. It was simply a research tool, albeit a popular one. Only when Jon Cousins started using it for his own selfish purposes did it become clear how useful it could be. He was the catalyst.
Both my story and Jon’s are examples of what I say about DIYization of science: It gets tools into the hands of a larger and more diverse group of possible innovators, who are less “stuck” — less committed to old ways of doing things — than the professionals. They are also more motivated to do something useful than the professionals, who are weighed down with other big concerns — about status, job security, money, and so on.
In 2006, PhD student Ian Li created Moodjam to let people track their moods in color. At the QS Europe conference last November, he met artist Laurie Frick, who creates beautiful works of art from her data. She mentioned that she was using Moodjam, and this inspired Ian to make a new version of it! In the video below, he walks through the sparkling new version, including some not-yet-released features like aggregated happy vs. sad colors and sentiment analysis. (Filmed by the Pittsburgh QS Show&Tell meetup group.)
About three years ago, Gary Wolf wrote a detailed post on Measuring Mood — some tools are complicated enough to get you grouchy! Gallup goes through a lot of trouble to gauge the US happiness level on a daily basis. Others take a simple approach, such as Eric Kennedy’s recent talk at the Seattle QS meetup on Tracking Happiness.
Ross Larter believes an emphasis on simplicity and community (especially of people who you don’t know elsewhere) has been key to broad acceptance of his happiness-tracking MoodPanda.
Q: How do you describe MoodPanda? What is it?
Larter: MoodPanda.com is a mood tracking website and iphone app. Tracking is very simple: you rate your happiness on a 0-10 scale, and optionally add a brief twitter-like comment on what’s influencing your mood.
MoodPanda is also a large community of friendly people, sharing their moods, celebrating each others’ happiness, and supporting each other when they’re down.
People post many times a day – some tracking their mood from the moment they wake to the point their head hits the pillow at night! We organize people’s posts into their personal mood diary where they can view it many different ways: graphically, as a mood feed, broken down by metrics and even location based on a map.
Q: What’s the back story? What led to it?
Larter: MoodPanda got started in a pub in Bristol, England. A friend was asking people round the table how their day was and somebody replied with a 10/10. My response was if today was the best day ever what happens if tomorrow is the same as today but then something else amazing happens (I think it included the “pussy cat dolls”), and we chatted for a while on this. The next day I started thinking about the question and told Jake (Co-Founder) about the idea and it went from there. We both work in software development so building the site was not an issue.
We are on MoodPanda version 3 at the moment. For the first 2 versions of the site we built it to track just your own mood. It was only once we added commenting and “hugs” to the current version that we realised that people wanted the interaction with each other. This is when our user based really started to grow.
Q: What impact has it had? What have you heard from users?
Larter: Since the iPhone app has gone live it is growing quickly with many thousands of new user every month, over 60% now come from the Apple app store. We’re seeing about 1000 active user ratings a day. Hugs are a very popular feature. Panda users give out hundreds a day.
One thing we’ve learned is that there seems to be a strong demand for a place online where people can share their feelings with others who don’t know them in “real life”, people who won’t judge them. We see this in the data: only about 35% of mood ratings are passed through to Facebook and only 2% to Twitter. And we’ve heard this directly from users who have posted that its nice to talk to people that are interested in mood and wellbeing and don’t judge them.
Feedback from users has been fantastic, and in some cases very heartwarming. We’ve even had users tell us that they’ve “lived with years of hurt until they discovered MoodPanda”.
We’ve now got so many users in the UK that our mood map is pretty representative. Our UK live mood map was quite similar to the UK Government official one from last year. We also put together a nice infographic of all of our data from 2011.
We are always trying out new ideas, and some have not been well received. We had done some complicated graphs and visualization in the past, and we’ve learned that keeping it simple is the key to moodpanda.
I also never quite realised how much time is needed after all the technical work is done. I spend a ton of time talking on the radio, public speaking, blogging, twittering, etc. about MoodPanda.
Q: What makes it different, sets it apart?
Larter: What makes MoodPanda stand apart are its simplicity and community. Other mood tracking apps are very clinical and can often be intimidating to people first trying to track their mood. We keep it simple: rate your happiness from 0-10 and, if you want, say a few words about what is influencing your mood. The design and ethos of MoodPanda has been carefully cultivated to create a friendly, open and easy first step into happiness tracking.
The large community of “moody pandas” is the other major feature, as other mood tracking apps (like our first 2 versions) are private. We of course have users who want to remain private, but 92% of our users are posting as part of of the community. We have people giving “panda hugs” and commenting with help and advice constantly in the site and genuine caring friendships are being formed constantly. We’re working hard to understand what helps this community aspect of MoodPanda and build on it.
Q: What are you doing next? How do you see MoodPanda evolving?
Larter: We recently started tracking hashtags so we could do stats on the sentiment of people’s comments that linked to the mood ratings. We’ve found that #coffee, #friends, and #food are associated with more happiness, and #sick and #work with less. We’re wondering whether we will learn whether some brands are strongly associated with mood (for example whether new #coke is good or bad) in ways that you can’t learn from normal brand sentiment tools.
We are working on the android app, and we’ve got a lot of ideas in the development pipeline involving more community features and technologies like an API.
Jake and I still have to go to work at our day jobs, but MoodPanda is a project that we both care deeply about. We’ve set a budget of $100 a month to spend on MoodPanda, so we do everything ourselves and get as creative as we can.
Q: Anything else you’d like to say?
Larter: Just a big thanks to you guys and girls at quantified self, its nice to talk to others that are as excited and interested in QS, if people continue to use moodpanda it to make themselves happier, we know we have done a good job!
Platform: web, iPhone
This is the ninth 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
-This review was written by Craig Protzel for my class DIY Health at NYU ITP (Tisch School of the Arts). In this class, students design systems of self-care that help people take stock of themselves by exploring ways to measure, reflect and act upon their health and lifestyle.-
Marie Dapuch’s “Mood Tracking” is very much focused on the qualified self and how the user feels. Dapuch created a rating scale based on colors as a visual metric, and a self-reported quantifiable metric, to gauge her mood over periods of time. While her process of assigning values is entirely subjective, and one might argue lacking in “scientific rigor,” Dapuch’s project is extremely relevant, highly impactful, and overwhelmingly touching.
Overall, she was able to design and develop a system of enormous significance in the improvement of her own life. By implementing it on a mobile device, she successfully integrated the tracking process into her daily routine, allowing for even more in depth analysis. All of this effort gave her the awareness and information to make confident choices in her own life, particularly to pursue a career path in advertising, to not spend so much time with her sister, and, most recently, to avoid the A train. Her presentation is inspiring in that you clearly see how a simple yet effective system of self-monitoring can have such a positive effect on a person’s life. (Filmed at the NY Quantified Self Show&Tell #13 at NYU ITP.)