不同成瘾状态大学生网络使用者的认知心理特征研究
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摘要
互联网作为一种新兴媒体,已经被越来越多的人所接受,它给网络用户带来了巨大的影响。大学生作为网络普及率最高的人群,也具有较高的网络成瘾率。因沉迷于网络而产生的一系列行为和心理问题已不容忽视。由于网络使用和网络成瘾现象不断发展,为了使人们能更好地了解和利用互联网络,发挥它的巨大潜力,本研究在健康行为领域中阶段认知理论和Precede-Proceed模式等的思想指导下,围绕大学生的上网行为展开。
本研究采用问卷调查和脑电信号分析相结合的研究方法,对杭州四所高校的942名大学生的不同网络成瘾状态进行了研究,探讨不同网络成瘾状态大学生的人口资料、上网行为、脑电信号、人格心理特征以及网络使用行为的影响因素构成模型。研究数据采用因素分析、相关分析、卡方、方差分析以及结构方程建模等多种统计分析方法。经过分析和讨论,本研究得出以下主要结论:
1.1大学生网络使用者可划分为网络成瘾、网络成瘾倾向和网络未成瘾3种状态,所占比例分别是10.0%、74.7%和15.3%。不同性别的大学生网络用户中,3种网络成瘾状态的比例有显著差异,其中网络成瘾组中男生的比例高于女生,而网络未成瘾组和网络成瘾倾向组中男生的比例低于女生。
1.2不同网络成瘾状态大学生在中文网络成瘾量表得分、上网时间、上网地点、上网活动以及对网络影响和网络成瘾的认识方面都有显著差异。
1.3不同网络成瘾状态大学生自发EEG的C(n)、MF和MPF指标在大脑额部、央部、顶部、颞部以及枕部有显著差异。不同活动状态、不同脑区对C(n)、MF和MPF均有显著影响。
1.4不同网络成瘾状态大学生在网络无关或无“网”刺激条件下诱发的ERP各成分的波幅和潜伏期均没有显著差异,在网络有关或有“网”刺激条件下诱发的P3成分有显著差异。在顶部及枕部脑区,网络成瘾组被试的P3波幅高于网络成瘾倾向组和网络未成瘾组,网络成瘾倾向组被试P3波幅高于网络未成瘾组。
1.5不同网络成瘾状态大学生被试的抑郁、焦虑、孤独、自尊和自我控制能力的测量得分均有显著差异。网络成瘾组被试的抑郁、焦虑和孤独得分均显著高于网络成瘾倾向组被试,网络成瘾倾向组被试的抑郁、焦虑和孤独得分均显著高于网络未成瘾组被试;网络成瘾组被试的自尊得分和自我控制能力均显著低于网络成瘾倾向组被试,网络成瘾倾向组被试的自尊得分和自我控制能力均显著低于网络未成瘾组被试。
1.6本研究修编的大学生网络使用行为的倾向、促成和强化影响因素问卷具有良好的信度和效度,达到了心理测量学的要求,可以作为大学生网络使用行为的倾向、促成和强化影响因素的测量工具。
1.7网络使用行为受倾向、促成和强化3类因素的直接或间接影响,是认知、态度、信念等倾向因素,网络可用程度等促成因素,以及家庭、社会影响等强化因素综合相互作用的结果。
As a newly developed media, internet had been accepted by more and more people. It exerted great impact on internet users. Undergraduate was the group that had the most popular rate of internet use and it also had the highest rate of internet addiction. A series of behavioral and psychological problems resulted from addicting internet can not be neglected. As the development of internet use and internet addiction phenomenon, on the purpose of knowing and using internet better to bring its great potential, this study focused on undergraduate's internet using, based on phases cognitive theories and Precede-Proceed model in health behavior area.
Using investigation and electroencephalo-graph, this study investigated the different addiction states in 942 undergraduate internet users from four colleges in Hangzhou, Zhejiang Province, working on their electroencephalo-graph signal characters, personalities and the influential factors of internet using. The data were dealt with statistical analysis of factor, correlation, Chi-square, ANOVA and AMOS structural equation models etc. After detailed analysis and discussion, the study got following conclusions:
1.1 Undergraduate internet users can be grouped into internet addiction, internet addiction intent and none internet addiction groups accounting for 10.0%, 74.7% and 15.3% respectively. The ratios of these three groups were different between male and female undergraduate. In group of internet addiction, the ratio of male users is higher than that of female users. In other two groups, the ratio of male users is lower than that of female users.
1.2 Undergraduate internet users in different groups had significant difference in the score of Chinese Internet Addiction Scale, time spent on the internet, place, activities and the opinion on internet effect and internet addiction.
1.3 Undergraduate internet users in different groups had significant difference in C(n), MF and MPF of spontaneous EEG signal. Activities and brain sections had significant effect on C(n), MF and MPF.
1.4 The ERP induced by different stimulus were P1, N2 and P3. There was significant difference in 3 groups at the amplitude of P3 that induced by Internet related stimulus or stimulus with "internet". The amplitude of P3 in group of internet addiction was higher than that in other two groups, and the amplitude of P3 in group of internet addiction intent was higher than that in group of none internet addiction.
1.5 Undergraduate internet users in different groups had significant difference in depression, anxiety, loneliness, self-esteem and self-control. The scores of depression, anxiety and loneliness in group of internet addiction were higher than those in other two groups, and those in group of internet addiction intent were higher than those in group of none internet addiction. The score of self-esteem and self-control ability in group of internet addiction were lower than those in other two groups, and those in group of internet addiction intent were lower than those in group of none internet addiction.
1.6 The revised undergraduate internet using behavior questionnaire had a good reliability and validity. It can be applied as an instrument to evaluate factors that influence the internet use for undergraduates.
1.7 Internet using behavior was influenced by intent, causable and reinforcing factors directly or indirectly. Internet using behavior was the interactional outcome of different factors which were intent, causable, reinforcing factors such as cognitive, attitude, belief, internet reachable, family and social impact etc.
本研究采用问卷调查和脑电信号分析相结合的研究方法,对杭州四所高校的942名大学生的不同网络成瘾状态进行了研究,探讨不同网络成瘾状态大学生的人口资料、上网行为、脑电信号、人格心理特征以及网络使用行为的影响因素构成模型。研究数据采用因素分析、相关分析、卡方、方差分析以及结构方程建模等多种统计分析方法。经过分析和讨论,本研究得出以下主要结论:
1.1大学生网络使用者可划分为网络成瘾、网络成瘾倾向和网络未成瘾3种状态,所占比例分别是10.0%、74.7%和15.3%。不同性别的大学生网络用户中,3种网络成瘾状态的比例有显著差异,其中网络成瘾组中男生的比例高于女生,而网络未成瘾组和网络成瘾倾向组中男生的比例低于女生。
1.2不同网络成瘾状态大学生在中文网络成瘾量表得分、上网时间、上网地点、上网活动以及对网络影响和网络成瘾的认识方面都有显著差异。
1.3不同网络成瘾状态大学生自发EEG的C(n)、MF和MPF指标在大脑额部、央部、顶部、颞部以及枕部有显著差异。不同活动状态、不同脑区对C(n)、MF和MPF均有显著影响。
1.4不同网络成瘾状态大学生在网络无关或无“网”刺激条件下诱发的ERP各成分的波幅和潜伏期均没有显著差异,在网络有关或有“网”刺激条件下诱发的P3成分有显著差异。在顶部及枕部脑区,网络成瘾组被试的P3波幅高于网络成瘾倾向组和网络未成瘾组,网络成瘾倾向组被试P3波幅高于网络未成瘾组。
1.5不同网络成瘾状态大学生被试的抑郁、焦虑、孤独、自尊和自我控制能力的测量得分均有显著差异。网络成瘾组被试的抑郁、焦虑和孤独得分均显著高于网络成瘾倾向组被试,网络成瘾倾向组被试的抑郁、焦虑和孤独得分均显著高于网络未成瘾组被试;网络成瘾组被试的自尊得分和自我控制能力均显著低于网络成瘾倾向组被试,网络成瘾倾向组被试的自尊得分和自我控制能力均显著低于网络未成瘾组被试。
1.6本研究修编的大学生网络使用行为的倾向、促成和强化影响因素问卷具有良好的信度和效度,达到了心理测量学的要求,可以作为大学生网络使用行为的倾向、促成和强化影响因素的测量工具。
1.7网络使用行为受倾向、促成和强化3类因素的直接或间接影响,是认知、态度、信念等倾向因素,网络可用程度等促成因素,以及家庭、社会影响等强化因素综合相互作用的结果。
As a newly developed media, internet had been accepted by more and more people. It exerted great impact on internet users. Undergraduate was the group that had the most popular rate of internet use and it also had the highest rate of internet addiction. A series of behavioral and psychological problems resulted from addicting internet can not be neglected. As the development of internet use and internet addiction phenomenon, on the purpose of knowing and using internet better to bring its great potential, this study focused on undergraduate's internet using, based on phases cognitive theories and Precede-Proceed model in health behavior area.
Using investigation and electroencephalo-graph, this study investigated the different addiction states in 942 undergraduate internet users from four colleges in Hangzhou, Zhejiang Province, working on their electroencephalo-graph signal characters, personalities and the influential factors of internet using. The data were dealt with statistical analysis of factor, correlation, Chi-square, ANOVA and AMOS structural equation models etc. After detailed analysis and discussion, the study got following conclusions:
1.1 Undergraduate internet users can be grouped into internet addiction, internet addiction intent and none internet addiction groups accounting for 10.0%, 74.7% and 15.3% respectively. The ratios of these three groups were different between male and female undergraduate. In group of internet addiction, the ratio of male users is higher than that of female users. In other two groups, the ratio of male users is lower than that of female users.
1.2 Undergraduate internet users in different groups had significant difference in the score of Chinese Internet Addiction Scale, time spent on the internet, place, activities and the opinion on internet effect and internet addiction.
1.3 Undergraduate internet users in different groups had significant difference in C(n), MF and MPF of spontaneous EEG signal. Activities and brain sections had significant effect on C(n), MF and MPF.
1.4 The ERP induced by different stimulus were P1, N2 and P3. There was significant difference in 3 groups at the amplitude of P3 that induced by Internet related stimulus or stimulus with "internet". The amplitude of P3 in group of internet addiction was higher than that in other two groups, and the amplitude of P3 in group of internet addiction intent was higher than that in group of none internet addiction.
1.5 Undergraduate internet users in different groups had significant difference in depression, anxiety, loneliness, self-esteem and self-control. The scores of depression, anxiety and loneliness in group of internet addiction were higher than those in other two groups, and those in group of internet addiction intent were higher than those in group of none internet addiction. The score of self-esteem and self-control ability in group of internet addiction were lower than those in other two groups, and those in group of internet addiction intent were lower than those in group of none internet addiction.
1.6 The revised undergraduate internet using behavior questionnaire had a good reliability and validity. It can be applied as an instrument to evaluate factors that influence the internet use for undergraduates.
1.7 Internet using behavior was influenced by intent, causable and reinforcing factors directly or indirectly. Internet using behavior was the interactional outcome of different factors which were intent, causable, reinforcing factors such as cognitive, attitude, belief, internet reachable, family and social impact etc.
引文
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72 Green W, Kreuter W. Health Promotion Planning: An Educational and Ecological Approach, Third Edition. Mayfield, 1999.
73 Greenfield D N. The nature of internet addiction: Psychological factors in compulsive internet use. http://www.virtual-addiction.com/internetaddiction.htm, 1999.
74 Griffiths M. Does Internet and computer addiction exist? Some case study evidence. Paper presented at the 105th annual meeting of the American Psychological Association, 1997.
75 Griffiths M. Internet gambling: issues, concerns, and recommendations. Cyberpsychology &behavior, 2003, 6(6): 557-568.
76 Grohol J. Internet addiction guide. http://psychcentral.com/netaddiction/, 1999.
77 Hada M, Porjesz B, Begleiter H et al. Auditory P3: a assessment of male alcoholics. Biol Psychiatry, 2000, 48: 276-286.
78 Hacker K, Brown E, Cabral H etc. Applying a transtheoretical behavioral change model to HIV/STD and pregnancy prevention in adolescent clinics. Journal of Adolescent Health, 2005, 37 (3): 80-93.
79 Hall A S, Parsons J. Internet addiction: college student case study using best practice in cognitive behavior therapy. Journal of Mental Health, 2001, 23(4): 312-327.
80 Hills P, Argyle M. Uses of the internet and their relationships with individual differences in personality. Computers in Human Behavior, 2003, 19: 59-70.
81 John S. To get what you need: Healthy and pathological Internet use. Cyber psychology &behavior, 1999, 2(3): 385-394.
82 Kaspar F, Schusyer H. Easily calculable measure for the complexity of spatiotemporal pattern. Physical Review Annual. 1987, 36(2): 842-848.
83 Kim K, Ryu E, Chon M Y etc. Internet addiction in Korean adolescents and its relation to depression and suicidal ideation: a questionnaire survey. International journal of nursing studies, 2006, 43: 185-192.
84 King S A. Is the internet addictive, or are addicts using the internet. http://www.concentric.net/～Astorm/iad.html, 1996.
85 Kolmogorov A N. Three approaches to the quantitative definition of information. Problems in Information Transmission, 1965,1(1): 4-7.
86 Kraut R, Patterson M, Lundmark V, Kielser S, Mukopadhyay T, Scherlis W. Internet Paradox : A social Technology that Reduces Social and Involvement and Psychological Well-being. American Psychologist, 1998, 9: 1017-1031.
87 Kubey R W, Lavin M J, Barrows J R. Internet Use and Collegiate Academic Performance Decrements: Early Findings. Journal of Communication, 2001, 51(2): 366-382.
88 Lach H W, Everard K M, Highstein G etc. Application of the Transtheoretical Model to Health Education for Older Adults. Health Promotion Practice, 2004, 5 (1): 88-93.
89 Leary M R, Tambor E S, Terdal S K, Downs D L. Self-esteem as an interpersonal monitor: The sociometer hypothesis. Journal of Personality and Social Psychology, 1995, 2: 518-530.
90 Lemple, Ziv. On the complexity of finite sequence. IEEE trans on IT, 1976, 22(1): 75-81.
91 Li S M, Chung T M. Internet function and Internet addictive behavior. Computers in human behavior, 2006, 22: 1067-1071.
92 Lin S J, Tsai C C. Sensation seeking and Internet dependence of Taiwanese high school adolescents. Computers in human behavior, 2002, 18: 411-426.
93 Matheson, Zanna. Computer-mediated communications: The focus in on me. Social Science Computer Review, 1990, 8(1): 1-12.
94 Mckenna K, Bargh J. Plan 9 from cyberspace: the implications of the Internet for personality and social psychology. Personality and Social Psychology, 2000, 4: 5775.
95 McKie L, MacInnes A, Hendry J et al. The food consumption patterns and perception of dietary advice of older people. Journal of Human Nutrition &Dietetics, 2000, 13(3): 173-183.
96 Michio H, Bernice P, David B et al. Auditory P3, a deficit s in male subjects at high risk for alcoholism. Biol Psychiatry, 2001, 49: 726-738.
97 Morahan-Martin J, Schumacher P. Incidence and correlates of pathological Internet use among college students. Computers and human behavior, 2000, 16: 13-29.
98 Niemz K, Griggtths M, Banyard P. Prevalence of pathological internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and Disinhibition. CyberPsychology & Behavior, 2005, 8(6): 562-570.
99 Oreilly. Michael. Internet addicts can get online help, CMAJ: Canadian medical association journal, 2000, 163 (2): 199.
100 Orzack M H. Internet addiction treatment. Electronic message posted to research discussion list. http://www.cmhc.com/mlists/research/, 1996.
101 Pearlin, Leonard I. The sociological study of stress. Journal of Health and Social Behavior, 1989, 30: 241-256.
102 Petrie H, Gunn D. Internet addiction: The effects of sex, age, depression and introversion. Paper presented at the British psychological. Society London Conference, 1998.
103 Papacharissi Z, Rubin A M. Predictors of internet use, Journal of broadcasting and electronic media, 2000, 44: 175-196.
104 Prochaska J O, DiClemente C C. Stages and processes of self-change in smoking: Towards integrative models of change. Journal of Consulting and Clinical Psychology, 1983, 51: 390-395.
105 Robert L, Carolyn L, Matthew E. Unregulated internet usage: addiction, habit, or deficient self-regulation? Media Psychology, 2003, 5(3): 25-29.
106 Robinson T E, Berridge K C. Addiction. Annual Review of Psychology, 2003, 54: 25-53.
107 Rockstroh B, Elbert T, Lutzenberger W, Birbaumer N. The Effects of Slow Cortical Potentials on Response Speed. Psychophysiology, 1982, 19: 211-217.
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73 Greenfield D N. The nature of internet addiction: Psychological factors in compulsive internet use. http://www.virtual-addiction.com/internetaddiction.htm, 1999.
74 Griffiths M. Does Internet and computer addiction exist? Some case study evidence. Paper presented at the 105th annual meeting of the American Psychological Association, 1997.
75 Griffiths M. Internet gambling: issues, concerns, and recommendations. Cyberpsychology &behavior, 2003, 6(6): 557-568.
76 Grohol J. Internet addiction guide. http://psychcentral.com/netaddiction/, 1999.
77 Hada M, Porjesz B, Begleiter H et al. Auditory P3: a assessment of male alcoholics. Biol Psychiatry, 2000, 48: 276-286.
78 Hacker K, Brown E, Cabral H etc. Applying a transtheoretical behavioral change model to HIV/STD and pregnancy prevention in adolescent clinics. Journal of Adolescent Health, 2005, 37 (3): 80-93.
79 Hall A S, Parsons J. Internet addiction: college student case study using best practice in cognitive behavior therapy. Journal of Mental Health, 2001, 23(4): 312-327.
80 Hills P, Argyle M. Uses of the internet and their relationships with individual differences in personality. Computers in Human Behavior, 2003, 19: 59-70.
81 John S. To get what you need: Healthy and pathological Internet use. Cyber psychology &behavior, 1999, 2(3): 385-394.
82 Kaspar F, Schusyer H. Easily calculable measure for the complexity of spatiotemporal pattern. Physical Review Annual. 1987, 36(2): 842-848.
83 Kim K, Ryu E, Chon M Y etc. Internet addiction in Korean adolescents and its relation to depression and suicidal ideation: a questionnaire survey. International journal of nursing studies, 2006, 43: 185-192.
84 King S A. Is the internet addictive, or are addicts using the internet. http://www.concentric.net/～Astorm/iad.html, 1996.
85 Kolmogorov A N. Three approaches to the quantitative definition of information. Problems in Information Transmission, 1965,1(1): 4-7.
86 Kraut R, Patterson M, Lundmark V, Kielser S, Mukopadhyay T, Scherlis W. Internet Paradox : A social Technology that Reduces Social and Involvement and Psychological Well-being. American Psychologist, 1998, 9: 1017-1031.
87 Kubey R W, Lavin M J, Barrows J R. Internet Use and Collegiate Academic Performance Decrements: Early Findings. Journal of Communication, 2001, 51(2): 366-382.
88 Lach H W, Everard K M, Highstein G etc. Application of the Transtheoretical Model to Health Education for Older Adults. Health Promotion Practice, 2004, 5 (1): 88-93.
89 Leary M R, Tambor E S, Terdal S K, Downs D L. Self-esteem as an interpersonal monitor: The sociometer hypothesis. Journal of Personality and Social Psychology, 1995, 2: 518-530.
90 Lemple, Ziv. On the complexity of finite sequence. IEEE trans on IT, 1976, 22(1): 75-81.
91 Li S M, Chung T M. Internet function and Internet addictive behavior. Computers in human behavior, 2006, 22: 1067-1071.
92 Lin S J, Tsai C C. Sensation seeking and Internet dependence of Taiwanese high school adolescents. Computers in human behavior, 2002, 18: 411-426.
93 Matheson, Zanna. Computer-mediated communications: The focus in on me. Social Science Computer Review, 1990, 8(1): 1-12.
94 Mckenna K, Bargh J. Plan 9 from cyberspace: the implications of the Internet for personality and social psychology. Personality and Social Psychology, 2000, 4: 5775.
95 McKie L, MacInnes A, Hendry J et al. The food consumption patterns and perception of dietary advice of older people. Journal of Human Nutrition &Dietetics, 2000, 13(3): 173-183.
96 Michio H, Bernice P, David B et al. Auditory P3, a deficit s in male subjects at high risk for alcoholism. Biol Psychiatry, 2001, 49: 726-738.
97 Morahan-Martin J, Schumacher P. Incidence and correlates of pathological Internet use among college students. Computers and human behavior, 2000, 16: 13-29.
98 Niemz K, Griggtths M, Banyard P. Prevalence of pathological internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and Disinhibition. CyberPsychology & Behavior, 2005, 8(6): 562-570.
99 Oreilly. Michael. Internet addicts can get online help, CMAJ: Canadian medical association journal, 2000, 163 (2): 199.
100 Orzack M H. Internet addiction treatment. Electronic message posted to research discussion list. http://www.cmhc.com/mlists/research/, 1996.
101 Pearlin, Leonard I. The sociological study of stress. Journal of Health and Social Behavior, 1989, 30: 241-256.
102 Petrie H, Gunn D. Internet addiction: The effects of sex, age, depression and introversion. Paper presented at the British psychological. Society London Conference, 1998.
103 Papacharissi Z, Rubin A M. Predictors of internet use, Journal of broadcasting and electronic media, 2000, 44: 175-196.
104 Prochaska J O, DiClemente C C. Stages and processes of self-change in smoking: Towards integrative models of change. Journal of Consulting and Clinical Psychology, 1983, 51: 390-395.
105 Robert L, Carolyn L, Matthew E. Unregulated internet usage: addiction, habit, or deficient self-regulation? Media Psychology, 2003, 5(3): 25-29.
106 Robinson T E, Berridge K C. Addiction. Annual Review of Psychology, 2003, 54: 25-53.
107 Rockstroh B, Elbert T, Lutzenberger W, Birbaumer N. The Effects of Slow Cortical Potentials on Response Speed. Psychophysiology, 1982, 19: 211-217.
108 Sanders et al. The relationship of Internet use to depression and social isolation among adolescents. Adolescence, 2000, 35(1): 237-242.
109 Shapira N A, Lessig M C, Goldsmith T D. et al. problematic internet use: Proposed classification and diagnostic criteria, Depression and Anxiety, 2003, 17: 107-216.
110 Shapira N A, Goldsmith T D, Keck P E etc. Psychiatric features of individuals with problematic internet use. Journal of affective disorders, 2000, 57: 267-272.
111 Shu Ching Y. Comparison of internet addicts and non-addicts in Taiwanese high school. Computers in Human Behavior, 2007, 23(1): 79-96.
112 Swickert R J, Hittner J B, Harris J L et al. Relationships among Internet use, personality, and social support. Computers in Human Behavior.2002,18: 437-451.
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