Exploring Unorthodox Predictors of Smartphone Addiction during the COVID-19 Outbreak

G. H. B. A. De Silva, T. Sandanayaka, M. Firdhous
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Abstract

Smartphones became an integral part of household & corporate management across all industries which resulted in high screen time, & smartphone addiction during the pandemic. This study attempts to examine the association between sociodemographic factors, & perceived smartphone addiction towards real smartphone addiction. Kwon's (2013) validated Smartphone Addiction Survey was used to collect data from the identified subjects (n = 192), and descriptive analyzes and statistical crosstabs were used to infer the associations. The results portray that Sex and Age are strong predictors of smartphone addiction: females over males tend to get addicted to smartphones, while age below 25 is highly addicted to smartphones, and age over 41 is less smartphone addict. The level of education is a moderately fair predictor of smartphone addiction. The higher the level of education, the higher the tendency to become addicted to smartphones. Marital status is not a good predictor of smartphone addiction in context, and there is no difference between being married or not of smartphone addiction. Perceived smartphone addiction is a good predictor of smartphone addiction, who believe they are addicted are more likely to become addicted to smartphones, and vice versa.
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在COVID-19爆发期间探索智能手机成瘾的非正统预测因素
智能手机成为所有行业家庭和企业管理中不可或缺的一部分,这导致了疫情期间的高屏幕时间和智能手机成瘾。本研究试图检验社会人口因素和感知智能手机成瘾与真实智能手机成瘾之间的关系。Kwon(2013)验证的智能手机成瘾调查被用来收集来自确定的受试者的数据(n = 192),并使用描述性分析和统计交叉表来推断关联。结果显示,性别和年龄是智能手机成瘾的重要预测因素:女性比男性更容易对智能手机上瘾,而25岁以下的人对智能手机上瘾程度较高,41岁以上的人对智能手机上瘾程度较低。受教育程度是智能手机成瘾的一个比较公平的预测指标。受教育程度越高,对智能手机上瘾的倾向就越高。婚姻状况并不是智能手机成瘾的一个很好的预测因素,结婚或不结婚对智能手机成瘾没有区别。感知智能手机成瘾是智能手机成瘾的一个很好的预测指标,那些认为自己上瘾的人更有可能对智能手机上瘾,反之亦然。
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