Data_Sheet_1_Development of the Smartphone Addiction Risk Rating Score for a Smartphone Addiction Management Application.docx

Smartphone usage characteristics are useful for identification of the risk factors for smartphone addiction. Risk rating scores can be developed based on smartphone usage characteristics. This study aimed to investigate the smartphone addiction risk rating (SARR) score using smartphone usage characteristics. We evaluated 593 smartphone users using online surveys conducted between January 2 and January 31, 2019. We identified 102 smartphone users who were addicted to smartphones and 491 normal users based on the Korean Smartphone Addiction Proneness Scale for Adults. A multivariate logistic regression analysis was used to identify significant risk factors for smartphone addiction. The SARR score was calculated using a nomogram based on the significant risk factors. Weekend average usage time, habitual smartphone behavior, addictive smartphone behavior, social usage, and process usage were the significant risk factors associated with smartphone addiction. Furthermore, we developed the SARR score based on these factors. The SARR score ranged between 0 and 221 points, with the cut-off being 116.5 points. We developed a smartphone addiction management application using the SARR score. The SARR score provided insights for the development of monitoring, prevention, and prompt intervention services for smartphone addiction.

智能手机使用特征可用于识别智能手机成瘾的风险因素，且可基于此类特征构建智能手机成瘾风险评级得分模型。本研究旨在依托智能手机使用特征，探究智能手机成瘾风险评级（Smartphone Addiction Risk Rating, SARR）得分。本研究于2019年1月2日至1月31日期间开展线上调查，共评估593名智能手机使用者。基于成人版韩国智能手机成瘾倾向量表，本研究筛选出102名智能手机成瘾者与491名正常使用者。采用多因素logistic回归分析识别智能手机成瘾的显著风险因素。基于上述显著风险因素，通过列线图计算生成SARR得分。周末平均使用时长、习惯性智能手机使用行为、成瘾性智能手机使用行为、社交型使用以及程序性使用为与智能手机成瘾显著相关的风险因素。此外，本研究基于上述风险因素构建了SARR得分体系。SARR得分的取值范围为0至221分，其临界值为116.5分。本研究依托SARR得分开发了一款智能手机成瘾管理应用程序。该SARR得分可为智能手机成瘾的监测、预防及快速干预服务的开发提供理论参考与实践依据。