Farahani Malihe, Alavi Seyyed Salman, Mirzamani Bafghi Mahmood, Esmaili Alamuti Sudeh, Taghavi Zohreh, Mohammadi Mohammadreza
West Tehran Branch-Azad University, Department of Psychology, Tehran, Iran.
Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Iran J Psychiatry. 2018 Apr;13(2):103-110.
Problematic internet use is an important social problem among adolescents and has become a global health issue. This study identified predictors and patterns of problematic internet use among adult students. In this study, 401 students were recruited using stratified sampling technique. Participants were selected among students from 4 universities in Tehran and Karaj, Iran, during 2016 and 2017. Internet Addiction Test (IAT), Millon Clinical Multiaxial Inventory - Third Edition (MCMI-III), Structured Clinical Interview for DSM (SCID-I), and semi-structured interview were used to diagnose internet addiction. Then, the association between main psychiatric disorders and internet addiction was surveyed. Data were analyzed using SPSS18 software by performing descriptive statistics and multiple logistic regression analysis methods. P- Values less than 0.05 were considered statistically significant. After controlling the demographic variables, it was found that narcissistic personality disorder, obsessive- compulsive personality disorder, anxiety, bipolar disorders, depression, and phobia could increase the odds ratio (OR) of internet addiction by 2.1, 1.1, 2.6, 1.1, 2.2 and 2.5-folds, respectively (p-value<0.05), however, other psychiatric or personality disorders did not have a significant effect on the equation. The findings of this study revealed that some mental disorders affect internet addiction. Considering the sensitivity and importance of the cyberspace, it is necessary to evaluate mental disorders that correlate with internet addiction.
网络使用问题是青少年中一个重要的社会问题,并且已经成为一个全球性的健康问题。本研究确定了成年学生网络使用问题的预测因素和模式。在本研究中,采用分层抽样技术招募了401名学生。研究对象选自2016年至2017年期间伊朗德黑兰和卡拉季4所大学的学生。使用网络成瘾测试(IAT)、明尼苏达多项人格测验第三版(MCMI-III)、精神疾病诊断与统计手册结构化临床访谈(SCID-I)以及半结构化访谈来诊断网络成瘾。然后,调查主要精神障碍与网络成瘾之间的关联。使用SPSS18软件进行描述性统计和多元逻辑回归分析方法对数据进行分析。P值小于0.05被认为具有统计学意义。在控制人口统计学变量后,发现自恋型人格障碍、强迫型人格障碍、焦虑症、双相情感障碍、抑郁症和恐惧症可分别使网络成瘾的优势比(OR)增加2.1倍、1.1倍、2.6倍、1.1倍、2.2倍和2.5倍(p值<0.05),然而,其他精神或人格障碍对该方程没有显著影响。本研究结果表明,一些精神障碍会影响网络成瘾。考虑到网络空间的敏感性和重要性,有必要评估与网络成瘾相关的精神障碍。