Satoru Minagawa
ABSTRACT
Overuse of smartphone applications causes addiction to smartphone, which affects the user's physical and mental health. Interventions such as providing persuasive messages and controlling the use of applications need to assess the level of addiction to smartphone. To measure this addiction level, Smartphone Addiction Proneness scale (SAPS) has been proposed. However, it requires the user to answer 15 questions, which makes it burdensome, unreliable (because it is based on user response rather than their behavior), and slow (the estimation takes time). To overcome these limitations, we propose a technique for automatic recognition of SAPS score based on the actual daily use of the smartphone device. Our technique estimates the SAPS score using a regression model that takes the smartphone's states of use as explanatory variables (features). We describe the effective features and the regression model.
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Index Terms
- Estimating Smartphone Addiction Proneness Scale through the State of Use of Terminal and Applications
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