StepUp Forecast: Predicting Future to Promote Walking

Autor: Asuka Miyake, Ryo Hashimoto, Masami Takahashi, Momoko Nakatani
Rok vydání: 2021
Předmět:
Zdroj: MobileHCI
DOI: 10.1145/3447526.3472020
Popis: With the widespread use of fitness trackers, predicting the future of individuals’ health is becoming easier. However, little is known about how presenting a prediction of an individual's future impacts one's behavior. In this study, we targeted walking behavior and aimed to clarify the impact of presenting a prediction of the number of steps on one's behavior. We conducted a five-week experiment with 36 participants using the application “StepUp Forecast”, which presents prediction on the basis of past lifelogs. We found that self-efficacy and the number of steps increased significantly when the predictions were presented compared with when only records of steps were shown. This was because people were motivated to exceed the predicted value. Furthermore, when additional steps were presented along with the step prediction, neither self-efficacy nor the number of steps increased. Our findings suggest that the prediction should be an achievable value in which the user can exceed, and that a positive feedback loop could be possible by enhancing self-efficacy through the experience of achievement.
Databáze: OpenAIRE