|AWARD PAPER: DR. B. B. SETHI AWARD II
|Year : 2015 | Volume
| Issue : 1 | Page : 47-54
Internet addiction: Do two diagnostic criteria measure the same thing?
Vijay Parkash, Debasish Basu, Sandeep Grover
Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh, India
|Date of Web Publication||3-Aug-2015|
Dr. Sandeep Grover
Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh - 160 012
Source of Support: None, Conflict of Interest: None
Aim and Objective: To assess the agreement or concordance between two diagnostic criteria for Internet addiction (IA) and to study the relationship between IA as per these criteria and socio-demographic and Internet use profile. Methodology: A cross-sectional design was followed. Six hundred participants, aged 18-40 years, having a personal Internet connection and using Internet for at least 1 year were evaluated using a semi-structured interview, on the Young's Diagnostic Questionnaire, and IA diagnostic criteria developed by Tao et al., (2009). Results: Prevalence of IA varied from 1.2% to 21% depending on the assessment instrument. There is good level of concordance between Young's IA criteria and Tao et al. "2 + 1" criteria, but the level of concordance reduced with the use of course and dysfunction criteria of Tao et al. Among the different Internet variables, age at first use, age at which the person starts regular use and total duration of nonessential use were related to development of IA. Conclusion: Findings of the present study suggest that there is good level of concordance between Young's IA criteria and Tao et al. "2 + 1" criteria but the level of concordance reduces with the use of course and dysfunction criteria. This study also suggests that chances of IA increases with regular use of Internet and for a longer duration for nonessential uses.
Keywords: Diagnostic criteria, Internet addiction, Nosology
|How to cite this article:|
Parkash V, Basu D, Grover S. Internet addiction: Do two diagnostic criteria measure the same thing?. Indian J Soc Psychiatry 2015;31:47-54
|How to cite this URL:|
Parkash V, Basu D, Grover S. Internet addiction: Do two diagnostic criteria measure the same thing?. Indian J Soc Psychiatry [serial online] 2015 [cited 2020 Jun 2];31:47-54. Available from: http://www.indjsp.org/text.asp?2015/31/1/47/162003
| Introduction|| |
Over the last 2 decades or so, Internet has greatly facilitated social interactions and communications, entertainment like gambling, academics and research, commercial activities, and many other areas which may have addictive potential. ,, Such a phenomenal spread of technology has significantly influenced the ways of life all over the world. Its immense utility in many areas has made it an indispensable part of the human being in a modern era. However, some people get captivated or engrossed by Internet and use it excessively. 
The excessive use of Internet has been described in the literature since 1970s; however, the first description of it appeared in the medical and psychological literature in early 1990s. , New York psychiatrist Ivan Goldberg in 1995 first proposed that excess use of Internet may be considered as Internet addiction (IA).  However, no formal diagnostic criteria were available till mid-1990s. Young  was the first person to describe "problematic Internet use" and study IA. Young,  modified the diagnostic criteria of pathological gambling of Diagnostic and Statistical Manual of Mental Disorders version IV (DSM-IV) to construct diagnostic criteria for "problematic Internet use." According to her, if a subject fulfilled 5 or more of 8 characteristic symptoms, then the person should be considered to have "problematic Internet use." After this, over the years, many researchers have given different diagnostic criteria for IA but still the universally acceptable criteria has yet to come. ,,, Concerns continue to grow regarding problematic Internet use behaviors.  A recent review reported that excessive Internet use has been shown to be associated with depression, hostility, low self-esteem, and emotional instability.  Taking into account the harmful consequences of excessive Internet use, DSM-IV has listed Internet Gaming Disorder in its section-III, along with other conditions, for which more research is required before these might be considered for inclusion into the formal classification. 
Prevalence studies from various parts of the world suggest a wide variation in the prevalence of IA ranging from 0.3% to 38%. , The major reason for this wide variation is varying diagnostic criteria used in these studies to define IA, and this suggests that still there is no consensus with regard to how to define IA as a disorder. Emerging literature suggest that the different instruments mostly evaluate the negative outcomes and compulsive use as the key elements of IA.  As there is no consensus on the evaluation instrument, the challenge to researchers/clinicians is to develop a diagnostic criteria that are not only convincing but decisive, covering all ages, gender, and educational levels. Recently, Tao et al.,  have developed diagnostic criteria for IA and applied the same among the Chinese population and claimed high sensitivity and specificity of the instrument. It is possibly one of the few instruments for assessment of IA for which psychometric properties have been evaluated. Further, very few studies have compared the various diagnostic criteria in the same set of subjects to show the concordance rates and superiority of one over the other. 
Therefore, the present study aimed to investigate the agreement or concordance between Young's most accepted IA diagnostic criteria and latest diagnostic criteria developed by Tao et al.  Furthermore, an attempt was made to study the relationship of IA as per these criteria and socio-demographic and Internet use profile especially in Indian context.
| Methodology|| |
This was a cross-sectional study approved by the Institute Ethics Committee. Participants were selected by purposive sampling. To be included in the study, participants were required to be in the age group of 18-40 years and using the personal Internet connection for at least 1 year. An additional inclusion criterion was the requirement of use of Internet for nonessential purposes which were defined as "use other than that required for educational and professional purposes and beyond causal checking for mails. Use of Internet for gaming, watching pornography, excessive social networking, get rid of boredom, etc., was categorized as nonessential use." Participants with a history of psychotic disorders or bipolar I disorder (current or in the past) were excluded.
Participants were approached and explained the purpose of the study, those who consented were evaluated on selection criteria. Written informed consent was obtained from participants meeting the selection criteria. By using a semi-structured interview, participants were evaluated on the Young's Diagnostic Questionnaire,  and IA diagnostic criteria developed by Tao et al.  Data on Internet use pattern were collected using a checklist designed for the study.
Young's Diagnostic Questionnaire
Young,  developed the first questionnaire for diagnosing IA. This 8-item screening instrument was based on the DSM-IV diagnostic criteria for pathological gambling. The eight questions incorporated the following aspects of addiction: Preoccupation with the Internet; tolerance (needing to spend increasing amounts of time on the Internet to achieve satisfaction); inability to cut back or stop Internet use; spending more time online than intended; adverse consequences in interpersonal, educational or vocational spheres of life; lying to conceal the true extent of Internet use; and use of the Internet as an attempt to escape from problems. According to this questionnaire, if a person replies affirmatively to 5 or more items, then he is considered to have IA. It considers only nonessential usage (nonbusiness, nonacademic) and requires ruling out of mania. However, the questions do not have an attached time reference (e.g., past month, past year).
Tao et al.'s questionnaire for Internet addiction
It is the latest diagnostic criteria given in this field.  It is synthesized on the concept of drug dependence as defined in ICD-10 and DSM-IV. Questionnaire is detailed and has explicit criteria and rating instructions. It is derived from Young's Diagnostic Questionnaire and those of Ko et al. criteria for IA.  Items 1-8 of initial symptom criterion list include most of the items used in other diagnostic criteria of IA such as Young's DQ and those of Ko et al.  However, item 5 of the Young's Diagnostic Questionnaire ("has stayed online longer than originally intended") and item 8 of Ko et al.'s diagnostic criteria ("excessive effort spent on activities necessary to obtain access to the Internet") were omitted by Tao et al.  Unlike Ko et al.,  in items 5 and 7 of their symptom criterion list, "use of Internet for a period of time longer than expected" and "excessive time spent on Internet activities and leaving the Internet" - the variable "time," are defined in terms of daily Internet use for at least 6 h, and meets the symptom criterion for at least 3 months. This questionnaire was evaluated for the psychometric properties and a cut-off score of "2 + 1," in which the client has to endorse the first 2 items (preoccupation, withdrawal symptoms) and one or more of the last 5 items resulted in the best diagnostic accuracy (99.26%), specificity (100.0%) and positive predictive value (100.0%).
Internet use profile sheet
A specific "Internet use profile sheet" was constructed for this study to record age at first use of Internet, age since using the Internet regularly, duration since the subject has a personal Internet connection, duration of essential use/day, duration of nonessential use/day, purpose (essential and nonessential) of Internet use, family history of substance dependence, personal history of regular use of nicotine, alcohol or other substance and personal history of any other psychiatric disorder etc.
Data were analyzed using SPSS version 14.0 for Windows SPSS for Windows, Version 14.0. Chicago, SPSS Inc. Mean and standard deviation was calculated for continuous variables. Frequencies and percentage were computed for discontinuous variables. Cohen's Kappa and Pearson's correlation coefficient were calculated to study the concordance between the two diagnostic criteria. Comparisons were done using t-test or Chi-square test. Relationship between IA and other variables was studied using Pearson correlation coefficient and Spearman Rank correlation coefficient test.
| Result|| |
Totally, 1000 participants were approached and evaluated on inclusion and exclusion criteria. Of these, 360 participants were excluded as they were not fulfilling the eligibility criteria. Among 640 participants who were fulfilling the eligibility criteria, 40 participants refused to participate in the study. Hence, the final study sample was of 600 participants.
The details of the socio-demographic profile, Internet connection, and Internet use profile are shown in [Table 1]. The mean age of the study sample was 21.84 years (18-37 years), with only 20% (n = 59) aged more than 25 years and only 1% (n = 7) aged ≥30 years. Three-fourth of the study sample comprised of males and almost all (98%) were unmarried at the time of assessment. More than two-third (71.3%) of the participants belonged to nuclear families, and the majority (83%) of them were Hindu by religion. Majority of the participants were continuing their graduation course (61.7%), slightly more than one-fourth of them were pursuing postgraduation courses (28%) and another one-tenth were pursuing their postdoctoral courses. The mean number of years of education was 15.35 years (standard deviation [SD] - 2.22; range: 13-25). Three-fourth (76.7%) of the participants belonged to urban locality, and another one-fourth (23.3%) came from the rural background. With regard to the type of Internet connection more than one-third (36.8%) relied upon Wi-Fi connection and another 30% were using data card connections in addition to the Wi-Fi connection. A small proportion of the participants relied on only the broadband connection (13.3%) or the data card (19.2%) only.
|Table 1: Socio-demographic and Internet use profile of the study sample |
Click here to view
The mean age for first use of Internet was 15.9 (SD - 3.09; range 8-30) years and the age since the person was using Internet regularly was 17.92 (SD - 3.12; range 8-30) years. On an average, the participants had a personal Internet connection for 30.18 (SD - 22.32; range 1-180) months prior to assessment for the study. Participants spent more than 1 h a day on essential use (checking of E-mail, academic related activities) of Internet and 2 h a day for nonessential use (pornography, gaming, gambling) of Internet. In addition, the participants spent on an average 1 ½ h on mixed use (included activities such as shopping, chatting, and social networking) activities on Internet. When the extra time during the weekend was taken into account, total duration of nonessential use was 14.28 h (SD - 16.17) per week.
Prevalence of Internet addiction
Among the eight criteria of Young's IA Diagnostic Questionnaire, the criterion which was most commonly met by the study participants was "need to use the Internet with increasing amounts of time in order to achieve satisfaction" and this was closely followed by "staying on-line longer than originally intended." Both these criteria were met by more than two-fifth of the study sample. The criterion which was met by least number of participants was "Have you jeopardized or risked the loss of a significant relationship, job, educational, or career opportunity because of the Internet." When the number of criteria endorsed by the participants was evaluated, about one-fifth (21.8%) did not meet any criterion. More than half (57.2%) endorsed 1-4 criteria of Young IA Questionnaire and only one-fifth (21%) met the criteria of IA as per Young IA Questionnaire.
When the participants were evaluated on Tao et al.'s IA criteria, of the 7 criteria, "the need for use of Internet with increasing amount of time in order to achieve satisfaction" and "preference for Internet use over other areas of interest/entertainment and hobbies which were previously interesting" were met by two-fifth of the participants [Table 2].
Relationship of Young's Internet addiction questionnaire and Tao et al. diagnostic criteria
As shown in [Table 3], there was a significant relationship between the Young's IA Questionnaire and Tao's diagnostic criteria. Kappa value, Chi-square value, and Pearson correlation coefficient was significant for Young's IA criteria and those who fulfilled the first two criteria, 2 + 1 criteria, met the dysfunction criteria, met the course criteria of more than 6 h of daily use, course criteria of regular use of Internet for 3 months, course criteria of both regular Internet use for more than 3 months and 6 h of daily use, 2 + 1 along with the course criteria and all the criteria as given by Tao et al. (i.e., 2 + 1, course + dysfunction).
|Table 3: Relationship of Young's IA Questionnaire and Tao et al. diagnostic criteria |
Click here to view
Factors associated with Internet addiction
Different correlates of IA as per Young's diagnostic criteria were evaluated in the whole study sample. As is evident from [Table 4], compared to those without IA, those with IA belonged to families with higher income, had lower age at first Internet use, started using Internet regularly at an younger age, used Internet for longer duration for nonessential use, mixed use and overall spent more time per day on Internet use. As expected those with IA endorsed a higher number of Young's IA Questionnaire. There was no significant difference on any other socio-demographic variable, prevalence of comorbid substance use in self or family history of substance use and other Internet use variables.
|Table 4: Comparison of demographic and Internet use profile of those with met IA criteria and those did not meet IA criteria |
Click here to view
As is evident from [Table 4], those with IA as per Tao et al. criteria, used Internet for a longer duration for nonessential use, mixed use and overall spent more time per day on Internet use. Those with IA also more frequently reported a history of failure in a major examination; more frequently attributed failure to excessive Internet use and more often remained awake more than their usual time to use Internet. There was no significant difference on any other variables.
| Discussion|| |
Although many studies have used different criteria to diagnose IA, very few studies have compared the various diagnostic criteria in the same set of subjects to show the concordance rates and superiority of one over the other. In one of studies done from this center, it was seen there was a wide variation in the prevalence rate of IA in the same sample (3.8-52%)  according to the definition used. Accordingly, there is a further need to evaluate the diagnostic criteria for IA.
The present study included participants aged 18-37 years with a mean of 21.84 years and three fourth of the study sample comprised of males. Three-fourth (76.7%) of the study participants belonged to urban locality. Participants were specifically selected with this profile, in view of the available literature which suggests that IA is more common in males, ,,,,,,,,,,,,,,,,, those living in metropolitan areas,  and in younger people. ,
The mean age in years for first use of Internet was 15.9 (SD - 3.09; range 8-30) and the age since the person was using Internet regularly was 17.92 (SD - 3.12; range 8-30) years. On an average, the participants had a personal Internet connection for 30.18 (SD - 22.32; range 1-180) months prior to assessment for the study. When we compare this Internet use profile, the age at first use, and regular use are higher compared to some of the studies from China.  The higher age at the first use compared to some of the studies from South East Asia may also be a reflection of differences in the evolution of Internet technology in different countries. Participants spent 2 h a day for nonessential use (pornography, gaming, gambling) of Internet. In addition, the participants spent on an average 1½ h on mixed use (included activities such as shopping, chatting, and social networking) activities on Internet, all of which could also be categorized as nonessential use. In total participants spent on an average 3½ h a day on nonessential use of Internet. This was much less than that reported by other studies which have evaluated IA from different parts of the world. 
Typology of excessive Internet use
Of eight questions of Young's Diagnostic Questionnaire, the criteria which were most commonly endorsed was "need to use the Internet with increasing amounts of time in order to achieve satisfaction" (45.8%), closely followed by "staying on-line longer than originally intended" (42.5%). About two-fifth of the participants (38%) also endorsed "they use Internet as a way of escaping from problems or of relieving a dysphoric mood." On Tao et al. criteria, participants endorsed the similar criteria with same frequency and another one criteria, that is, "Have you preferred Internet use over other areas of interest/entertainment and hobbies which were previously interesting before Internet use?" was endorsed by 40.1%. This profile is similar to many studies which have evaluated IA either in term of frequency of endorsement for different criteria or hierarchy of the criteria endorsed. ,
Prevalence of Internet use as per Young's criteria and Tao et al.'s criteria
In the present study, 21% of participants met the criteria of IA as per the Young's criteria and 14.3% of participants fulfilled "2 + 1" criteria of Tao et al.  However, when the course criterion was taken into account, only 5.8% of participants met the criteria for IA. Further when the criterion for dysfunction was added, the prevalence of IA reduced to 1.2%.
When one looks at the available literature, data suggest that the prevalence of IA varies from 0.3-38%. , Findings of the present study are within this range. This suggests that at least a proportion of people who use Internet get hooked to the same and suffer from dysfunction. Taking this into account it can be said that there is a need to evaluate excessive Internet use as a diagnostic category and the American Psychiatric Associations's decision to include Internet Gaming Addiction in the appendix of DSM-5  as a disorder for which further research is required to be in the nosological system is a step in the right direction.
However, the present study highlights the fact that the prevalence of IA varies according to the diagnostic criteria even in the same study population and echo the findings of Grover et al.  who reported the prevalence of IA to be 3.8% according to Young's criteria, which increased to as high as 52% when IA was evaluated by use of ICD-10 criteria. However, this study was based on self-rated questionnaires and not on clinical interview. Hence, it can be concluded that whenever an attempt is made to define IA, concurrent validity of the proposed criteria must be established more stringently possibly against a clinical interview by a qualified psychiatrist, who specialize in drug dependence.
Concordance between the two diagnostic criteria
Results of the present study showed a significant relationship between the Young's IA Questionnaire and Tao's diagnostic criteria. Kappa value, Chi-square value, and Pearson correlation coefficient was significant for Young's IA criteria and those who fulfilled the first 2 criteria, 2 + 1 criteria, met the dysfunction criteria, met the course criteria of more than 6 h of daily use, course criteria of regular use of Internet for 3 months, course criteria of both regular Internet use for more than 3 months and 6 h of daily use, 2 + 1 along with the course criteria and all the criteria as given by Tao et al.(i.e., 2 + 1, course + dysfunction). However, it was seen that Kappa value was highest for "2 + 1" symptom criteria and least for duration criteria for 3 months, closely followed by all the criteria (symptom, dysfunction, and course) evaluated together against the Young's criteria. These findings suggest that there is a need to refine the course criterion of Tao et al.
Correlates of Internet addiction
Earlier studies have reported that IA is more prevalent in males, ,,,,,,,,,,,,,,,,, and those living in metropolitan areas  and in younger people. , However, in the present study, we did not find any relationship of IA with any socio-demographic variables except that participants who fulfilled Tao et al. "2 + 1" criteria had higher family income.
Among the different Internet variables age at first use, age at which the person starts regular use, total duration of nonessential use had an association with IA. Similar finding has been reported by studies from other parts of the world. These findings can have policy level implications, that is, for prevention of IA, it is important that regular use of IA should be delayed and the parents or those using Internet regularly should keep a track of total duration of nonessential Internet use.
Evaluation of Internet addiction as per Tao et al. criteria
Only 14.3% of participants met the "2 + 1" criteria of Tao et al. and as the IA criteria were made more stringent, the prevalence of IA came down to 1.2%. When one compares the findings of the present study with Tao et al., certain important limitations of these criteria emerge. First, Tao et al., suggested a cut-off of 6 h/day for considering IA. This was based on the finding of mean duration of nonessential use for more than 9 h/day in their study sample. It appears that the criterion of "more than 6 h" is arbitrary, and some persons may fulfill all other criteria including the presence of dysfunction, except for the 6 h duration. This could be just because of the person's lifestyle and other commitments in life, but they may still be distressed by the time they are spending on Internet.
In the present study, the mean duration of nonessential use per day was only 2 h/day, and only a minority (n = 102; 20.1%) of sample fulfilled the 6 h duration criteria. When we evaluated the participants who fulfilled the 6 h criteria and looks for the prevalence of IA as per Young's criteria, presence of "2 + 1" criteria of Tao et al., 3 months duration criterion and dysfunction criterion, as shown in [Table 5], at least 14 participants met all other criteria, which actually means increase in prevalence of IA to double as per Tao's et al. criteria (except for the inclusion of 6 h/day criteria). Further when the criterion of duration per day of nonessential use was reduced to 3-5 h, the prevalence of IA kept on increasing and the prevalence was 3.5% (n = 21) with 4 h/day as the cut-off, that is three times that of the IA prevalence as per the original criteria. Accordingly, it can be proposed that Tao et al. criteria with modifications in the course and dysfunction criteria [Table 6] will have better sensitivity and specificity. Future studies should evaluate the suggested modifications for the establishment of the validity of the same against the diagnosis made by a psychiatrist.
|Table 5: Relationship of duration of Internet use per day with other Internet dependence variables |
Click here to view
|Table 6: Modifications in Tao et al. criteria based on the findings in current study |
Click here to view
The present study is limited by purposive sampling and cross-sectional assessment. The present study also did not evaluate the impact of IA and various other factors which could be closely associated with IA.
To conclude, this study suggests that prevalence of IA varies from 1.2% to 21% depending on the assessment instrument. There is a good level of concordance between Young's IA criteria and Tao et al. "2 + 1" criteria but the level of concordance reduces with the use of course and dysfunction criteria. These findings suggest that there is need to refine the course criterion of Tao et al. by reducing the duration of daily nonessential use to 4 h, duration of regular nonessential use to an excess of 3 months and validation of the same against the diagnosis made by a psychiatrist. Taken together, these findings show the fragility in the construct of IA as understood at present and there is a need for a cautious approach in adopting and accepting IA into nosological system as understood now. This study also suggests that chances of IA increases with regular use of Internet and for a longer duration for nonessential uses. Hence, regular nonessential use of Internet for longer duration should be discouraged both at family and government level to prevent dependence on it.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Shaffer HJ. Strange bedfellows: A critical view of pathological gambling and addiction. Addiction 1999;94:1445-8.
Silver G, editor. The Dope Chronicles: 1850-1950. San Francisco: Harper and Row; 1979.
US Census Bureau. Computer and Internet Use in the United States: 2003. Washington, DC: US Department of Commerce, Economics and Statistics Administration, US Census Bureau; 2005.
Chou C, Hsiao MC. Internet addiction, usage, and gratifications - The Taiwan′s college student′s case. Comput Educ 2000;35:65-80.
Young KS. Psychology of computer use: XL. Addictive use of the Internet: A case that breaks the stereotype. Psychol Rep 1996;79:899-902.
OReilly M. Internet addiction: A new disorder enters the medical lexicon. CMAJ 1996;154:1882-3.
Young KS. Internet addiction: The emergence of a new clinical disorder. Cyberpsychol Behav 1998;1:237-44.
Shapira NA, Lessig MC, Goldsmith TD, Szabo ST, Lazoritz M, Gold MS, et al.
Problematic Internet use: Proposed classification and diagnostic criteria. Depress Anxiety 2003;17:207-16.
Aboujaoude E, Koran LM, Gamel N, Large MD, Serpe RT. Potential markers for problematic Internet use: A telephone survey of 2,513 adults. CNS Spectr 2006;11:750-5.
Ko CH, Yen JY, Chen CC, Chen SH, Yen CF. Proposed diagnostic criteria of Internet addiction for adolescents. J Nerv Ment Dis 2005;193:728-33.
Leung L. Net-generation attributes and seductive properties of the Internet as predictors of online activities and Internet addiction. Cyberpsychol Behav 2004;7:333-48.
Widyanto L, McMurran M. The psychometric properties of the Internet addiction test. Cyberpsychol Behav 2004;7:443-50.
Wallace P. Internet addiction disorder and youth: There are growing concerns about compulsive online activity and that this could impede students′ performance and social lives. EMBO Rep 2014;15:12-6.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Health Disorders: DSM-5. 5 th
ed. Washington, DC: American Psychiatric Publishing; 2013.
Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M. Proposed diagnostic criteria for Internet addiction. Addiction 2010;105:556-64.
Grover S, Chakraborty K, Basu D. Pattern of Internet use among professionals in India: Critical look at a surprising survey result. Ind Psychiatry J 2010;19:94-100.
Morahan-Martin J, Schumacher P. Incidence and correlates of pathological Internet use among college students. Comput Hum Behav 2000;16:13-29.
Kaltiala-Heino R, Lintonen T, Rimpela A. Internet addiction? Potentially problematic use of the Internet in a population of 12-18 year old adolescents. Addict Res Theory 2004;12:89-96.
Yoo HJ, Cho SC, Ha J, Yune SK, Kim SJ, Hwang J, et al.
Attention deficit hyperactivity symptoms and Internet addiction. Psychiatry Clin Neurosci 2004;58:487-94.
Johansson A, Götestam KG. Internet addiction: Characteristics of a questionnaire and prevalence in Norwegian youth (12-18 years). Scand J Psychol 2004;45:223-9.
Jang KS, Hwang SY, Choi JY. Internet addiction and psychiatric symptoms among Korean adolescents. J Sch Health 2008;78:165-71.
Siomos KE, Dafouli ED, Braimiotis DA, Mouzas OD, Angelopoulos NV. Internet addiction among Greek adolescent students. Cyberpsychol Behav 2008;11:653-7.
Rehbein F, Kleimann M, Mössle T. Prevalence and risk factors of video game dependency in adolescence: Results of a German nationwide survey. Cyberpsychol Behav Soc Netw 2010;13:269-77.
Xie YB, Zhou P, Xu LP, Peng ZW. Prevalence of Internet addiction and the related factors in middle school students in Guangzhou. Nan Fang Yi Ke Da Xue Xue Bao 2010;30:1801-4.
Lin MP, Ko HC, Wu JY. Prevalence and psychosocial risk factors associated with Internet addiction in a nationally representative sample of college students in Taiwan. Cyberpsychol Behav Soc Netw 2011;14:741-6.
Frangos CC, Frangos CC, Sotiropoulos I. Problematic Internet Use among Greek university students: An ordinal logistic regression with risk factors of negative psychological beliefs, pornographic sites, and online games. Cyberpsychol Behav Soc Netw 2011;14:51-8.
Cao H, Sun Y, Wan Y, Hao J, Tao F. Problematic Internet use in Chinese adolescents and its relation to psychosomatic symptoms and life satisfaction. BMC Public Health 2011;11:802.
Ross MW, Månsson SA, Daneback K. Prevalence, severity, and correlates of problematic sexual Internet use in Swedish men and women. Arch Sex Behav 2012;41:459-66.
Haagsma MC, Pieterse ME, Peters O. The prevalence of problematic video gamers in the Netherlands. Cyberpsychol Behav Soc Netw 2012;15:162-8.
Müller KW, Koch A, Beutel ME, Dickenhorst U, Medenwaldt J, Wölfling K. Internet addiction as a co-morbid disorder among patients of german addiction rehabilitation facilities: An exploratory investigation of clinical prevalence. Psychiatr Prax 2012;39:286-92.
Durkee T, Kaess M, Carli V, Parzer P, Wasserman C, Floderus B, et al.
Prevalence of pathological Internet use among adolescents in Europe: Demographic and social factors. Addiction 2012;107:2210-22.
Poli R, Agrimi E. Internet addiction disorder: Prevalence in an Italian student population. Nord J Psychiatry 2012;66:55-9.
Dargahi H, Razavi SM. Internet addiction and factors related with it in Tehran city. Q J Payesh 2007;6:265-72.
Ghamari F, Mohammadbeigi A, Mohammadsalehi N, Hashiani AA. Internet addiction and modeling its risk factors in medical students, Iran. Indian J Psychol Med 2011;33:158-62.
Wang H, Zhou X, Lu C, Wu J, Deng X, Hong L. Problematic Internet Use in high school students in Guangdong Province, China. PLoS One 2011;6:e19660.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]