Tag Archives: happiness
A long one this time. Enjoy the words, numbers, and images herein.
New biometric tests invade the NBA by Pablo S. Torre and Tom Haberstroh. Data and statistics are nothing new in professional sports. They’ve even made Academy Award nominated movies based the idea that data can help a team win. Until now data on players and teams has come from analysis of practices and gameplay. This great piece opens another discussion about collecting even more personal data about how players in the NBA live their lives off the court. Recall that athletes, coaches, and owners have been talking about out of game data tracking since 2012.
Misleading With Statistics by Eric Portelance. We’ve featured these type of articles before, but the example used here by Eric is not to be missed. So many times the data visualization trumps the actual data when a designer makes editorial choices. After reading this piece you’ll think critically the next time you see a simple line chart.
Handy Tools & Apps by Ray Maker. A great resource for athletes and exercisers who use a variety of tools to capture, export, and work with the activity and workout data we’re collecting.
Happiness Logging: One Year In by Jeff Kaufman. A great post here about what Jeff has learned about himself, what is means to log something like “happiness”, and the power of tagging data. After looking at his data, and a commenter’s from the r/quantifiedself subreddit, I’m wondering about the validity of 10-point scales for this type of self-tracking.
Redshit/f.lux Sleep Experiment by Gwern. Our esteemed friend and amazing experimenter is back with another analysis of his sleep data. This time he explains his findings from using a program that shifts the color temperature on his computer away from blue and towards red.
I ran a randomized experiment with a free program (Redshift) which reddens screens at night to avoid tampering with melatonin secretion and sleep from 2012-2013, measuring sleep changes with my Zeo. With 533 days of data, the main result is that Redshift causes me to go to sleep half an hour earlier but otherwise does not improve sleep quality.
Make sure to join the discussion on the forum!
Schedule Abstracted by Mike McDearmon.
Even a hectic schedule can have a sense of serenity with all text, labels, and interface elements removed.
Location History Visualizer by Theo Platt. The data above is actually my full Location History from Google Takeout. Theo made this simple and fast mapping visualization tool. Try is out yourself!
Lifelogging Lab. No visualizations here, but if you’re a designer, visualizer, or just have some neat data then you should submit it to this sure to amazing curated exhibition.
From the Forum
The ethics of QS
Call For Papers: HCI International 2015 Los Angeles
Pebble for Fitness Tracking
QS Business Models
QS, Light, Sleep, Reaction Timing, and the Quantified Us
Are you using your data to write a reference book or tell a story?
Alex Tarling starting using the Mappiness app to track his happiness along with other contextual data. Over time the ritual of having to ask himself, “How happy am I?” three times a day started to get him thinking about how he thought about his own happiness and what that meant to him. In this talk, presented at the 2014 Quantified Self Europe Conference, Alex talks about his experience, some of the data he gathered, and how a slight change in attitude has increased his self-rating of happiness over time.
You can also view the slides here.
What did you do?
I tracked my own experience of happiness several times per day, along with location, what I was doing and who I was with.
How did you do it?
I used the Mappiness app to track my rating of happiness and other contextual data such as what I was doing and who I was with. –
What did you learn?
I can’t measure my own happiness without affecting it, one way or another. Happiness is a conscious cognitive assessment of feelings, beliefs and behaviours that tends to be a habitual pattern of thinking.
Given that it’s a mental habit, it is possible to make an intentional choice to change it. As Abraham Lincoln said, “Most folks are as happy as they make up their minds to be.”
Today’s gallery image is from the co-organizer of the Chicago QS Meetup group, Mark Moschel. Mark has been experimenting with various methods of self-tracking and has even built a neat SMS-based tracking tool called Ask Me Every. You can read more about his tracking and work at the wonderful Experimentable blog.
This visualization shows 3 months of my happiness data. After reviewing it two years ago, it showed me that I was unhappy when traveling for work and, shortly after, I quit my job.
How can I lead a happier life? I’m sure this is something we’ve all asked ourselves. Maybe it was during a turn through doldrums or maybe you asked yourself how you could sustain your happiness during a moment of joy. Whatever the case happiness, and by extension mood tracking, has been at the forefront of engaging in a Quantified Self practice for many individuals.
Konstanin Augemberg is no exception. A statistician by trade, Konstantin has been involved with numerous self-tracking projects in order to “empirically demonstrate that any aspect of my everyday life can be quantified and logged on a regular basis, and that the knowledge from these numbers can be used to help me live better.” In February Konstanin presented the methods and results of his ongoing Hacking Happiness project at the New York City QS Meetup (read on for a full description):
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 email@example.com.
James Norris asks the Singapore QS audience, “Do you remember your first kiss?” In the 16 years since his first kiss at age 13, James calculated that he has had 1,500 “firsts.” For the past three years, he has been tracking his goals, according to how happy, fulfilled, and productive he feels every day. In the video below, he shares what he learned about his goals, how his personal advisory board works, and tips for maximizing different areas of life. (Filmed by the Singapore 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
Erik Kennedy wanted to automate his happiness, so he started recording mood-changing events every day to find out what really made him happy or unhappy. After gathering 330 events, he categorized them and discovered that friendships and work were making him most frequently happy, while sickness and girl trouble were on the less happy side. Erik shares his thoughtful takeaways in the video below, including the lesson that the recipe for happiness does not have many ingredients. (Filmed by the Seattle QS Show&Tell meetup group.)
George Lawton studies happiness, and how to have more of it. In the video below, he talks about emotional feedback tools, his research on how to incrementally increase happiness, and how he tried to change his mood by changing his facial expressions. George also discusses mirror meditation as a way to increase emotional well-being, engages the audience with healthy laughter, and mentions his next project, on love. (Filmed at the Bay Area Quantified Self meetup held at Adaptive Path).
A reader over at my blog shared the NYT article Wandering Mind Is a Sign of Unhappiness, which reports on research by Killingsworth and Gilbert showing some surprises about distractedness. (My take: First, the least surprising result may be that the world’s happiest activity is reproduction. Second, almost half of the time we are not focused on what we’re doing, and this makes us unhappier.) The timing of this report is perfect given Ian’s recent Self-Tracking Tools post, where he talks about the Track Your Happiness project that the scientists used, along with supporting mobile apps and tools. The study is well-reported, so I’ll riff on it from two perspectives: How do we combine the results with self-experimentation to be happier? and What are the wider implications for citizen science and an experiment-driven life?