【作者】 彭阳；

【导师】 周世杰；

【作者基本信息】 中南大学 ， 应用心理学， 2007， 硕士

【摘要】 目的:(1)研究网络成瘾大学生的网络行为特点;(2)研究大学生网络成瘾的社会风险因素。方法:依照随机整群抽样原则,在湖南科技学院与永州职业技术学院抽取490名有大学生作为被试,采用网络成瘾诊断问卷、家庭环境量表中文版(FES-CV)、父母教养方式评价量表、依恋问卷、社会支持量表及青少年网络行为问卷进行调查,采用spss13.0进行统计检验,包括卡方检验、单因素方差分析、相关分析和非条件Logistic回归。结果:(1)所测被试中,网络成瘾的检出率为7.6%。(2)网络成瘾者男性显著多于女性;成瘾组与正常组父亲文化程度有显著差异,年级、专业、城乡、是否独生子女、母亲文化程度、父亲职业、母亲职业无显著差异。(3)网络成瘾组第一次上网年龄低于正常组,在从第一次上网到现在的时间、一天最多的上网次数、平均每天上网次数、一周最多的上网次数、平均每周上网次数、最长的单次在线时间、平均每次上网时间、平均每天上网时间、平均每周上网时间各方面均显著高于正常组。成瘾组在学生宿舍有便利的上网条件和自己的电脑。成瘾组与正常组在上网内容的比较上,网络人际关系、技术与信息无差异(p＞0.05),而在网络娱乐、性与赌博上,成瘾组得分显著高于正常组(p＜0.001)。在网络态度的比较上,网络控制感、对网络的积极评价、网络行为倾向无显著差异(p＞0.05),而在对网络的消极评价上两组有极其显著的差异(p＜0.001),成瘾组得分显著高于正常组。在网络情感的比较上,上网焦虑、网络满意感都存在显著差异(p＜0.05),成瘾组得分显著高于正常组。(4)家庭环境量表(FES-CV)结果显示,成瘾组家庭矛盾性得分显著高于正常组(p＜0.05);在亲密度、情感表达、独立性、成功性、知识性、娱乐性、组织性、控制性方面,两组无差异(p＞0.05)。父母教养方式量表结果显示,网络成瘾组与正常组在父情感温暖、父过度保护、父过分干涉、父拒绝否认、父惩罚严厉、母严厉惩罚、母情感温暖、母拒绝否认上差异显著(p＜0.05—0.001),母亲的干涉保护两组得分无显著差异(p＞0.05)。依恋问卷结果显示,成瘾组与正常组在母爱缺失、父爱缺失、父亲拒绝、母亲消极纠缠、父亲消极纠缠、对母亲愤怒、对父亲愤怒存在显著差异(p＜0.05—0.001),成瘾组的得分均高于正常组。社会支持量表结果显示,成瘾组与正常组在社会支持总分和主观支持分上存在显著差异(p=0.001),成瘾组得分明显低于正常组;而客观支持分与对支持的利用度两组无差异(p＞0.05)。(5)Logistic回归分析显示:通过网络行为可以较好的预测大学生是否网络成瘾。男大学生网络成瘾的预测因素有:主观支持分、母亲消极纠缠、对网络的积极评价、对网络的消极评价、网络满意度、最长的单次在线时间。女大学生网络成瘾的预测因素有:上网焦虑、平均每周上网次数、平均每次上网时间。结论:(1)网络成瘾大学生在初次上网年龄、上网时间、次数、网络行为特点上与非网络成瘾大学生有显著差异。(2)家庭社会各因素对网络成瘾大学生的网络行为有显著影响。(3)通过网络行为特点可以较好的预测大学生网络成瘾,男大学生的网络成瘾受家庭社会因素与网络行为的共同作用;女大学生网络成瘾则主要由网络行为特点预测。更多还原

【Abstract】 Objective: 1. To investigate the features of network behavior of the college with Internet Addiction Disorder. 2.To investigate the social risk factors of the college with Internet Addiction Disorder.Method: 490 students, who have network behavior in Hunan University of Science and Engineering and Yongzhou Vocational and Technical College, were selected by cluster sampling. They were assessed with Internet Addiction Disorder test and FES-CV and Egma Minnen av Bardndonsnaupp for stran(EMBU) and Attachment Questionnaire and Social Support Scale and self-made investigate questionnaire of the youth . Four methods had been used in analyzing, such as x~2-test, analysis of variance, correlation analysis and logistic regression.Result: (1) 7.6% subjects can be defined as IAD according to Internet Addiction Disorder Test. (2) There were significant difference between two group in sex and father’s cultural degree. There was no obvious difference between two group in the grade, specialty, urban and rural, only child , mother’s cultural degree, father’s profession, mother’s profession (p>0.05) .(3) IAD group have a lower score in the first age on-line, while have a higher score in the year of on-line, the most frequency of a day, every day on-line frequency, the most frequency of a week, every week on-line frequency, the most time of single on-line, time per on—line, every day on-line time, every week on-line time. IAD group have convenient condition and own computer in the dormitory; In network content, there was no obvious difference between two group in network interpersonal relation , technology and information . while IAD group have a higher score in network entertainment, sex and gambling (p<0.001) . In network attitude, there was no obvious difference between two group in network control feeling, network positive evaluation, network behavior tendency (p>0.05) . while there was obvious difference between two group in network passive evaluation. In network emotion, IAD group have a higher score in anxiety about on-line and satisfaction with network (p<0.05) . (4) In FES-CV, IAD group have a higher score in contradictoriness (p<0.05) .In EMBU, there were significant difference between two group in father’s warmth, over-protection, over-interference, rejection、refusal, severe punishment, mother’s severe punishment, warmth, rejection, refusal (p<0.05～0.001) . There was no obvious difference between two group in mother’s interference and protection (p>0.05). IAD group have a higher score in lack of maternal love, lack of fatherly love, father’s rejection, parent’s passive entangle, angry with parent (p<0.05～0.001) . IAD group have a lower score in the total score of social support and the score of subjective support (p= 0.001) .(5) By the logistic regression analysis, We can forecast the Internet Addition Disorder of the college by network behavior. The affective factors of young male’s Internet Addiction Disorder were as following: the score of subjective support, mother’s passive entangle, network positive evaluation, network active evaluation, satisfaction with network, the most time of single on-line. Subjective support and network active evaluation were protective factors. The affective factors of young female’s Internet Addiction Disorder were anxiety about on-line, every week on-line frequency, time per on—line.Conclusion: (1) IAD group have significant characteristics in the first age on-line, time on-line, frequency on-line and the features of network behavior. (2) The social factors have significant influence on the behavior of the youth with Internet Addiction Disorder. (3) Internet Addiction Disorder of the college can be forecast through network behavior, the young male’s Internet Addiction Disorder was affect by the social factors and network behavior.更多还原