In the novel A Christmas Carol, Scrooge is visited by ghosts showing his future that he will meet with a tragic end if he continues to be cold and miserly. After then, the imagination of future self transforms him into a changed man. We are to adopt this usefulness of imagining the future to help people change their health-related behavior. To investigate this issue, we began with defining the term Consequence Information as a consequence of continuing what a person has done in the past. We conducted a 4-week user study to explore how users interact with Consequence Information. Based on the findings from the study, we also conducted a workshop with designers to find out what designers focus on when designing quantified-self services providing Consequence Information. Finally, we suggested a framework for Consequence Information Quantified-Self Service Design. In addition, we produced a video that shows our interactive mirror concept design as an example of Consequence Information quantified-self service. Video link: https://youtu.be/9oyeeE9qK58
The adoption of self-tracking services to improve health-related behavior is increasing. Although psychologists claim that thinking about the future has a motivational impact on current behavior and cognition, few studies have explored using future forecast in self-tracking services. In this paper, we explore how future forecast information can be used in the design of self-tracking services. We conducted a four-week study that qualitatively investigated 11 participants' perceptions of and practices with future forecast information. Participants used the FutureSelf app that we developed, which forecasts dieters' future weights and expected goal achievement rates based on their current behavior. The findings reveal that predicting future weight based on prior performance induced participants to imagine their future selves and reminded them of their ultimate goals. In fact, the predictions became the participants' primary source of motivation. We also suggest design implications for self-tracking services that forecast users' future statuses.