Internet addiction in college students and its relationship with cigarette smoking and alcohol use in Northeast China.
Internet addiction in college students and its relationship with cigarette smoking and alcohol use in Northeast China.
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东北地区大学生网络成瘾及其与吸烟、饮酒的关系.
DOI：
10.1111/appy.12281
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Zhang,Huiping
中科院分区：
文献类型：
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作者：
Mei,Songli;Gao,Tingting;Li,Jiaomeng;Zhang,Ying;Chai,Jingxin;Wang,Lingyan;Zhang,Zhao;Zhang,Huiping
网络成瘾是一种冲动控制障碍，损害真实的生活关系，特别是在年轻人中。网络成瘾和药物滥用可能具有共同的特征（Black & Monrouxe，2014; Dietz等人，2013; Machowicz，Ciechanska，Zycinska等人，2013年）。物质滥用是指过度使用香烟，酒精或其他滥用药物，对身心健康产生负面影响（Mitrovic，Hadzi-Pesic，Stojanovic，Milicevic，2014）。本研究采用横断面研究方法，对东北地区1,092名大学生进行网络成瘾调查，探讨网络成瘾与吸烟、饮酒的关系。使用卡方（χ2）检验比较有和无网络成瘾的吸烟（或饮酒）者的比例。在上述学生中，91人（8.3%）是网络成瘾者，376人（34.2%）是酒精使用者（其中36人或9.6%是网络成瘾者），112人（10.3%）是吸烟者（其中21人或18.8%是网络成瘾者）。网络成瘾者中吸烟者比例显著高于网络成瘾者（χ2= 17.73，P<0.01）。010)而非饮酒者（χ2= 1.24，P>. 050）。以个人和家庭特征为协变量进行多因素回归分析。表1总结了关于性别、吸烟、饮酒、家庭所在地或其他协变量（如教育程度和自尊）对网络成瘾影响的logistic回归分析结果。模型1、模型2、模型3均为阳性（P<.模型2，P<.模型3，P<. 001）。我们的研究结果表明，吸烟可能会影响中国大学生的网络成瘾风险，
Internet addiction is an impulse control disorder impairing real life relationships, particularly in young people. Internet addiction and substance abuse may share common features (Black & Monrouxe, 2014; Dietz et al., 2013; Machowicz, Ciechanska, Zycinska, et al., 2013). Substance abuse means excessive use of cigarette, alcohol, or other drugs of abuse, resulting in negative effects on both physical and mental health (Mitrovic, Hadzi-Pesic, Stojanovic, & Milicevic, 2014). This study aimed to investigate the prevalence of Internet addiction in college students and the association of Internet addiction with cigarette smoking or alcohol use.In a cross-sectional study, 1,092 college students from Northeast of China were assessed for Internet addiction. The proportions of cigarette (or alcohol) users with and without internet addiction were compared using chi-square (χ2) tests. Among the above students, 91 (8.3%) were Internet addicts, 376 (34.2%) were alcohol users (36 or 9.6% of them were Internet addicts), and 112 (10.3%) were cigarette smokers (21 or 18.8% of them were Internet addicts). A significantly higher proportion of Internet-addicted students were cigarette smokers (χ2= 17.73, P<. 010) but not alcohol users (χ2= 1.24, P>. 050). Multivariate regression analysis was performed with individual and family characteristics as covariates. Table 1 summarizes logistic regression analysis results regarding the influence of gender, cigarette smoking, alcohol use, family location, or other covariates (eg, degree of education and self-esteem) on Internet addiction. Three models showed positive results (model 1, P<. 001; model 2, P<. 001; model 3, P<. 001). Our findings suggest that the risk for Internet addiction in Chinese college students could be influenced by cigarette smoking,