Nediyana Daskalova
Brown University, Providence, RI, USA
Self-experiments allow people to explore what behavioral changes lead to improved health and wellness. However, it is challenging to run such experiments in a scientifically valid way that is also flexible and able to accommodate the realities of daily life. We present a set of design principles for guided self-experiments that aim to lower this barrier to self-experimentation. We demonstrate the value of the principles by implementing them in SleepBandits, an integrated system that includes a smartphone application for sleep experiments. SleepBandits guides users through the steps of a single-case experiment, automatically collecting data from the built-in sensors and user input and calculating and presenting results in real-time. We released SleepBandits to the Google Play Store and people voluntarily downloaded and used it. Based on the data from 365 active users from this in-the-wild study, we discuss opportunities and challenges with the design principles and the SleepBandits system.
https://doi.org/10.1145/3313831.3376584
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)