Dwyer Debra S, Kreier Rachel, Sanmartin Maria X
SUNY Farmingdale, Farmingdale, NY USA.
St. Joseph's College, Patchogue, NY USA.
Atl Econ J. 2020;48(4):475-489. doi: 10.1007/s11293-020-09683-1. Epub 2020 Nov 4.
There is growing evidence of risks associated with excessive technology use, especially among teens and young adults. However, little is known about the characteristics of those who are at elevated risk of being problematic users. Using data from the 2012 Current Population Survey Internet Use Supplement and Educational Supplement for teens and young adults, this study developed a conceptual framework for modeling technology use. A three-part categorization of use was posited for utilitarian, social and entertainment purposes, which fit observed data well in confirmatory factor analysis. Seemingly unrelated regression was used to examine the demographic characteristics associated with each of the three categories of use. Exploratory factor analysis uncovered five distinct types of users, including one user type that was hypothesized to likely be at elevated risk of problematic use. Regression results indicated that females in their twenties who are in school and have greater access to technology were most likely to fall into this higher-risk category. Young people who live with both parents were less likely to belong to this category. This study highlighted the importance of constructing models that facilitate identification of patterns of use that may characterize a subset of users at high risk of problematic use. The findings can be applied to other contexts to inform policies related to technology and society as well.
The online version of this article (10.1007/s11293-020-09683-1) contains supplementary material, which is available to authorized users.
越来越多的证据表明过度使用科技存在风险，尤其是在青少年和年轻人当中。然而，对于那些有成为问题使用者高风险的人群的特征，我们知之甚少。本研究利用2012年当前人口调查互联网使用补充资料以及青少年和年轻人的教育补充资料中的数据，构建了一个用于模拟科技使用情况的概念框架。针对功利性、社交性和娱乐性目的提出了一种三部分的使用分类，该分类在验证性因素分析中与观测数据拟合良好。使用看似不相关的回归分析来检验与这三类使用相关的人口统计学特征。探索性因素分析揭示了五种不同类型的使用者，其中一种使用者类型被假设可能存在较高的问题使用风险。回归结果表明，二十多岁还在上学且更容易接触到科技的女性最有可能属于这一高风险类别。与父母双方同住的年轻人属于这一类别的可能性较小。本研究强调了构建模型的重要性，这些模型有助于识别可能表征有问题使用高风险的一部分使用者的使用模式。研究结果也可应用于其他情境，为与科技和社会相关的政策提供参考。
本文的在线版本（10.1007/s11293-020-09683-1）包含补充材料，授权用户可获取。
