Hello, Quantified Selfers! Press release
***** We are still looking for test users. *****
It is part of my Ph.D. dissertation research, and I intend to find out which kind of mood measures are more effective and would bring a higher user satisfaction. You can read about the application here: https://www.uni-due.de/2019-02-27-volunteers-wanted-for-mood-tracking and install it here:
PAX mood tracker is specifically designed to figure out the best method for capturing the mood in a long term use. Therefore it includes several different mood measures based on theories and users will randomly be assigned to one of them to use.
The app installation starts with a short pre-survey which will take no more than 7 minutes. Every day, you may answer the questions in which takes no more than 2 minutes and you can modify the time of the question via the app setting. After two weeks of use, you have another survey in which takes no more than 10 minutes. You may continue using the app as long as you wish.
To thank you, we have a raffle for 20 participants with a total value of 250 Euro. You need android 5.0 or higher to use the application.
Please help me figure out the mood trackers. Thank you
How many questions a day will it ask?
Will there be a data to get my own data out, API?
Will it continue working after the study is completed?
…It seems like an interesting app, but personally I’m most interested in measurements I can track and correlate over the years. If you open source the code I could always transfer my data and continue using afterwards if I find it good
Hi Helma - How is your research going? Did you get many sign ups? There are a lot of people in the QS community who have tried mood tracking using all kinds of different methods, some of them quite novel. (For instance, these projects by Jon Cousins.) I suspect you’ll get more satisfaction from discussing your work here than from recruiting users.
the design is two questions per day and optionally through setting a third one. You can modify the time window of the questions in the setting. You may use the application as long as you like. We intent to leave the application as open source after publishing our results. The code could be accessed later in Github.
Here is a press release:
We are still looking for participants.
Thank you for your suggestion. I am quite familiar with Cousins work. I agree. This community is great. At the same time in order to develop a new algorithm and using machine learning methods, we also need user data. This study is designed to get us the baseline for an accurate measure for longterm use. Getting the data together with the users’ experience will help me to develop a mood-aware system.
Therefore, it would be great if I also can get the support of our community.
Here is a link to the press release: https://www.uni-due.de/2019-02-27-volunteers-wanted-for-mood-tracking
We still need volunteers.