Self-e: Smartphone-supported guidance for customizable self-experimentation

Abstract

The ubiquity of self-tracking devices and smartphone apps has empowered people to collect data about themselves and try to self-improve. However, people with little to no personal analytics experience may not be able to analyze data or run experiments on their own (self-experiments). To lower the barrier to intervention-based self-experimentation, we developed an app called Self-E, which guides users through the experiment.We conducted a 2-week diary study with 16 participants from the local population and a second study with a more advanced group of users to investigate how they perceive and carry out self-experiments with the help of Self-E, and what challenges they face. We fnd that users are infuenced by their preconceived notions of how healthy a given behavior is, making it difcult to follow Self-E's directions and trusting its results. We present suggestions to overcome this challenge, such as by incorporating empathy and scafolding in the system.