Estimating Smartphone Addiction Proneness Scale through the State of Use of Terminal and Applications
Estimating Smartphone Addiction Proneness Scale through the State of Use of Terminal and Applications
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DOI：
10.1145/3267305.3267700
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
S. Minagawa;K. Fujinami
中科院分区：
文献类型：
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作者：
S. Minagawa;K. Fujinami
过度使用智能手机应用程序会导致智能手机成瘾，影响用户的身心健康。提供有说服力的信息和控制应用程序的使用等干预措施需要评估智能手机成瘾的程度。为了测量这种成瘾水平，已经提出了智能手机成瘾倾向量表（SAPS）。然而，它需要用户回答15个问题，这使得它负担沉重，不可靠（因为它是基于用户的响应而不是他们的行为），并且缓慢（估计需要时间）。为了克服这些局限性，我们提出了一种技术，自动识别的SAPS分数的基础上，实际的日常使用的智能手机设备。我们的技术使用回归模型来估计SAPS分数，该模型将智能手机的使用状态作为解释变量（特征）。我们描述了有效的功能和回归模型。
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.