Background: The COVID-19 pandemic-related “stay-at-home” and confinement orders has led individuals to be more engaged with technology use (eg, internet use). For a minority of individuals, excessive use can become problematic and addictive. However, the investigation of problematic internet use in the COVID-19 context is only just emerging. Therefore, the present study investigated the changes in internet use behaviors and addiction rates in comparison with prior Bangladeshi studies.
Methods: An online cross-sectional study was carried out among a total of 601 Bangladeshi students between October 7 and November 2, 2020. The survey included questions relating to socio-demographic, behavioral health, online use behaviors, and psychopathological variables.
Results: A quarter of the participants (26%) reported having low levels of internet addiction, whereas 58.6% were classed as having moderate internet addiction and 13% severe internet addiction. A total of 4% of the sample were classed as being at risk of severe internet dependency (ie, scoring over ≥ 80 on IAT). Risk factors for internet addiction included smartphone addiction, Facebook addiction, depression, and anxiety. However, the final hierarchical regression model comprising all variables explained a total of 70.6% variance of problematic internet use.
Conclusion: Based on the present findings, it is concluded that individuals are at elevated risk of problematic internet use like other psychological impacts that have been reported during the COVID-19 pandemic. Therefore, risk-reducing measures and healthy control use strategies should be implemented for vulnerable individuals.



中文翻译：

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COVID-19 大流行如何影响互联网使用行为并促进有问题的互联网使用？孟加拉研究

背景：与 COVID-19 大流行相关的“居家”和禁闭令导致个人更多地参与技术使用（例如，互联网使用）。对于少数人来说，过度使用可能会成为问题和上瘾。然而，在 COVID-19 环境下对有问题的互联网使用的调查才刚刚出现。因此，本研究与之前的孟加拉国研究相比，调查了互联网使用行为和成瘾率的变化。
方法：在 2020 年 10 月 7 日至 11 月 2 日期间，对总共 601 名孟加拉国学生进行了一项在线横断面研究。调查包括与社会人口、行为健康、在线使用行为和精神病理学变量有关的问题。
结果：四分之一的参与者（26%）报告有低水平的网络成瘾，而 58.6% 的参与者被归类为中度网络成瘾和 13% 的重度网络成瘾。总共有 4% 的样本被归类为有严重互联网依赖的风险（即 IAT 得分超过 80）。网络成瘾的风险因素包括智能手机成瘾、Facebook 成瘾、抑郁和焦虑。然而，包含所有变量的最终层次回归模型解释了互联网使用问题的 70.6% 方差。
结论：根据目前的调查结果，得出的结论是，与 COVID-19 大流行期间报告的其他心理影响一样，个人面临互联网使用问题的风险较高。因此，应对弱势个体实施降低风险的措施和健康的控制使用策略。