Changing behavior and improving lives through mood data collection and display for users over time.
- Moodtivities was designed as an iPhone app that users can employ to track their activities and mood over time, and then use graphs and charts to compare their mood to their different activities.
- The prototype exists only in a very rough stage, and is optimized for iPhone and remains a rough implementation, but for the curious, it can be found here.
Part of the user research process entailed creating paper prototypes each member of the team gave to a small group of people, to test the burden of filling out something describing their activity, mood, and feelings throughout the day. Paper prototypes, developed in Illustrator, were designed to fit a pocket-sized 3 x 5 piece of paper. Users reported that while it was slightly annoying to remember to take out a piece of paper and fill it out several times a day, they all actually enjoyed the process of picking out emotions. From user interviews, I developed additional recommendations for the application, such as only prompting the user to enter information three or so times per day.
A color-coded scale for mood was implemented, with green indicating a good feeling, and red indicating a bad feeling. User testing will show how effective this scale is. One potential issue with the current prototype is that it may be unusable for those who are red-green colorblind, though I plan to perhaps offer more than one color scale. The third screen allows the user to select their specific feelings. The user may select more than one feeling at a time, and these paper prototypes showed that users enjoyed this feature and often picked two or more moods each time.
Visualizations were developed to how the wide-bredth of options of showing data to a user. Attempting to express a variety of data in a single space, including general mood, specific moods, activitiy, and time, this chart was one concise view for showing users the data most relevant to them and showing between data points. Multiple visualization frameworks were explored, but none adequately provided enough flexibility to develop into the kinds of visualizations our team thought most relevant. As such, we did
One of the main goals of the moodtivities application is to first hook users into using the system. To this end, extensive game dynamic mechanisms were designed to make sure the site is fun to use. A leaderboard of the top users in various categories is populated by providing points to users as they do things in the system. Users can get point bonuses by tracking mood with friends, using the system at various times, and for other secret reasons users can uncover. Users have the option of exporting their activity to social spaces like Facebook and Twitter to show-off their actions and to encourage others to make them accountable to their in-system goals.
Once users are engaged with the system, and when visualizations can provide helpful ways for users to understand how their actions and moods connect, we still would like to drive effective behavior change from this knowledge. Moodtivities provides a special space for this activity, where smart system algorythms provide users with helpful tips based on their actions. If the system sees a user is always unhappy when they party, it may suggest less partying. If users neglect to perform one of the preset actions in moodtivities for a long time, the system might suggest they do this activity to live a more balanced life. These suggestions can also be based on time, such that if users are always having bad days during weekdays, the system might suggest they treat themselves on these days. Incorporating visualizations of per-day happiness and connecting the emotions to the corresponding activities, users can have clear ideas of what they ought to be doing, and not doing, to improve their well-being.
Working on the moodtivities mobile-optimized site brought a great deal of education on the difficulties of driving effective behavior change and developing effective visualizations for personal informatics devices. Working with the team, I believe we developed some insightful and useful ways to connect users with an accurate look at how their activities drive their moods. Implementing the site, though never fully finished, taught us a great deal about the problems of converting brilliant design into brilliant code. We found that designers should stick with what they do best — design — and not limit those design aspirations based on what might be technically possible with a limited team. I believe this is a product that warrent further development and has the potential to be integrated across a variety of spaces, including twitter, foursquare, facebook, and more. Overall, it was a very enlightening process.