|Year : 2018 | Volume
| Issue : 1 | Page : 131-140
Prevalence of excessive internet use and its association with psychological distress among university students in South India
Nitin Anand1, Praveen A Jain2, Santosh Prabhu3, Christofer Thomas4, Aneesh Bhat5, PV Prathyusha6, Shrinivasa U Bhat7, Kimberly Young8, Anish V Cherian9
1 Department of Clinical Psychology, Dr. MV Govindaswamy Centre, National Institute of Mental Health and Neuro Sciences (NIMHANS), An Institute of National Importance, Bengaluru, India
2 Department of Psychiatry, Kasturba Medical College, Manipal, India
3 Department of Psychiatry, K. S. Hegde Medical College, Mangalore, India
4 Department of Physiology, Sapthagiri Institute of Medical Science and Research Center, Bengaluru, India
5 Department of Psychiatry, MIMER Medical College, Talegoan Dabhade, Pune, Maharashtra, India
6 Department of Biostatistics, Dr. MV Govindaswamy Centre, National Institute of Mental Health and Neuro Sciences (NIMHANS), An Institute of National Importance, Bengaluru, India
7 Department of Psychiatry, Kasturba Medical College, Manipal, Karnataka, India
8 Department of Strategic Communication, and Strategic Leadership, St. Bonaventure University, New York, USA
9 Psychiatric Social Work, Dr. MV Govindaswamy Centre, National Institute of Mental Health and Neuro Sciences (NIMHANS), An Institute of National Importance, Bengaluru, India
|Date of Web Publication||15-Oct-2018|
Dr. Anish V Cherian
Department of Psychiatric Social Work, Dr. MV Govindaswamy Centre, National Institute of Mental Health and Neuro Sciences, An Institute of National Importance, Hosur Road, Bengaluru - 560 029, Karnataka
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Excessive internet use, psychological distress, and its inter-relationship among university students can impact their academic progress, scholastic competence, career goals, and extracurricular interests. Thus, a need exists to evaluate the addictive internet use among university students. Objectives: This study was set up to examine the internet use behaviors, internet addiction (IA), and its association with psychological distress primarily depression among a large group of university students from South India. Methods: Totally 2776 university students aged 18–21 years; pursuing undergraduate studies from a recognized university in South India participated in the study. The patterns of internet use and socioeducational data were collected through the internet use behaviors and demographic data sheet, IA test (IAT) was utilized to assess IA and psychological distress primarily depressive symptoms were evaluated with Self-Report Questionnaire-20. Results: Among the total n = 2776, 29.9% (n = 831) of university students met criterion on IAT for mild IA, 16.4% (n = 455) for moderate addictive use, and 0.5% (n = 13) for severe IA. IA was higher among university students who were male, staying in rented accommodations, accessed internet several times a day, spent more than 3 h per day on the Internet and had psychological distress. Male gender, duration of use, time spent per day, frequency of internet use, and psychological distress (depressive symptoms) predicted IA. Conclusions: IA was present among a substantial proportion of university students which can inhibit their academic progress and impact their psychological health. Early identification of risk factors of IA can facilitate the effective prevention and timely initiation of treatment strategies for IA and psychological distress among university students.
Keywords: Depression, excessive internet use, internet addiction, psychological distress, university students
|How to cite this article:|
Anand N, Jain PA, Prabhu S, Thomas C, Bhat A, Prathyusha P V, Bhat SU, Young K, Cherian AV. Prevalence of excessive internet use and its association with psychological distress among university students in South India. Ind Psychiatry J 2018;27:131-40
|How to cite this URL:|
Anand N, Jain PA, Prabhu S, Thomas C, Bhat A, Prathyusha P V, Bhat SU, Young K, Cherian AV. Prevalence of excessive internet use and its association with psychological distress among university students in South India. Ind Psychiatry J [serial online] 2018 [cited 2018 Dec 10];27:131-40. Available from: http://www.industrialpsychiatry.org/text.asp?2018/27/1/131/243311
Internet addiction (IA) is a quickly growing global phenomenon among adolescents and young adults , and is one among the most significant challenges emerging from the use of the Internet.,, The prevalence of IA among young adults is reportedly high and is known to vary from 1.5% to 24.2%.,,, To make communication easier, quicker, and to facilitate safe exchange of information Internet was developed. Over the years, ever-increasing use of the Internet for work and leisure activities has led to its omnipresent presence across all activities of the day, and this has disguised the boundaries between functional and dysfunctional internet use. The use of the Internet in a healthy manner can be understood as achieving a desired goal within an appropriate time frame without experiencing intellectual or behavioral discomfort.
The emergence of the Internet as a medium to interact is turning into an absolute need and an effective space for interchange of ideas, establishing risk free social connections with strangers, free expression of thoughts, possibility to access prohibited content, involvement in unique games, and use of numerous other functions in substantial privacy draws individuals of divergent interests which has led to exponential rise in use of the Internet.,, Internet use is becoming an unavoidable requirement for many of the individuals, mostly young adolescents and adults.,
Some individuals cannot control their use of the Internet whereas others can limit their use. Excessive use of the Internet has been termed by researchers by use of varied terminologies such as compulsive internet use, problematic internet use, pathological internet use, and IA., This research study would use the term IA which describes it as an individual's inability to control his or her own use of the Internet causing disturbances and impairment in fulfillment of work, social and personal commitments.,
Research literature suggests that depression is a leading comorbid disorder with IA., Self-esteem is one of the core components of depression. It is individual's attitude to himself, and it can be either negative or positive. Thus, individuals with negative self-esteem are potential candidates who engage in addictive internet behaviors which helps to momentarily free themselves of their negative self-esteem, irrational cognitive assumptions, and associated unpleasant emotions.,
The occurrence of depression among the young individuals with IA and existence of IA among the depressed individuals has been observed. The presence of low self-esteem, low motivation, fear of negative evaluation, social avoidance observed in depressed individuals are hypothesized to lead to excessive/addictive usage of the Internet in depressed individuals. Social isolation caused by IA may also lead to depression.
The primary mental illness is depression or IA is debatable with respect to research evidence. The objective of this study is to investigate the severity of IA and depression and its interrelationship among the university students. Research information offered by this study can be of use to a wide array of health professionals such as psychiatrists, psychologists, psychosocial counselors, and mental health professionals at primary care levels to understand the severity of the phenomenon and the relationships between psychological factors and IA.
| Methods|| |
The present study employed a cross-sectional study design. Totally 2776 students pursuing undergraduate studies aged between 18 and 21 years, studying in science, commerce, and humanities subject streams at recognized universities, participated in the study. All these university students were using the Internet for at least 1 year duration, were fluent in their ability to read, write, and comprehend English and gave written informed consent for the study were included in the study. Two university colleges situated in South Indian city of Mangalore were considered to collect the sample as per the convenience of the research team.
All the students of these two colleges who were present on the day of data collection were invited to participate in the study. Totally 2776 students who gave a written informed consent were included in the study. The undergraduate students were chosen as sample for this study as presence of addictive internet behaviors in this population can have far-reaching consequences on the individual's academic progress in their respective field and at a larger level impact the professional progress of these individuals. Ethical approval was received from the institute ethics board of K. S. Hegde Medical Academy, NITTE University, Mangalore, Karnataka, India before initiation of the study.
The schedule was constructed by the research team to document information about sociodemographic data and internet usage variables, namely duration, frequency, devices used, time spent on the Internet, craving for internet use, attempts to reduce internet use, and similar other variables.
Internet addiction test
It is a 20 item self-report scale based on a 5-point Likert scale to assess the IA and its severity., The scores for the individual items were summed up for obtaining a total scale which ranges from 20 to 100. The total score was interpreted with the norm criteria of the scale which indicates mild, moderate, or severe categories IA. IA test (IAT) shows good-to-moderate internal consistency (alpha coefficients - 0.54–0.82). IAT has been evaluated for its content and convergent validity, internal consistency (ἀ = 0.88), and test-retest reliability (r = 0.82).
The Self-Report Questionnaire (SRQ) is a 20-item self-administered tool developed by the World Health Organization specifically for the use in developing countries for screening of mental health conditions at community settings. SRQ-20 offers a Yes/No response format to the individual and is designed to identify psychological distress, inclusive of depression, and suicidality. This study had utilized the original form of the questionnaire.
The research team had approached two university colleges situated in the South Indian city of Mangalore who were offering undergraduate and postgraduate degrees in science, commerce, and humanities subject streams. On gaining the permission from each of the university colleges for conducting this research study, the research assistants approached the undergraduate students during their free hour in the classroom setup on the days of data collection designated by the university college. Each of these university undergraduate students was explained about the nature of the study and was invited to participate in this research survey. Totally 2776 undergraduate university students who showed willingness to participate and gave a written informed consent were included in the study. Each of these university undergraduate students then completed a set of assessment tools which included a sociodemographic interview schedule, IAT, and the SRQ. Each Individual took around 45–60 min to complete the self-report tools. It took around 6 months for the collection of data across the two university colleges.
There were a total of around 10 research professionals/research assistants who were involved in different capacities for this nonfunded research project. Out of the 10, three were Faculty from Department of Psychiatry; K. S. Hegde Medical Academy, NITTE University, Mangalore, Karnataka, India; one faculty and six research assistants from the Department of Psychology, St. Aloysius College, Mangalore, Karnataka. The qualifications of this research team ranged from M.D. in Psychiatry, M. Phil and PhD in Psychiatric Social Work, and Master's Degree and PhD in Psychology.
All the study data were analyzed using IBM SPSS Version 22 for Windows (IBM Corporate, Armonk, New York, USA). Spearman's rank correlation was used to assess the relationship among the IA and SRQ scores. Mann-Whitney U test and Kruskal- Wallis tests were utilized to detect the difference among groups. Logistic Regression analysis was carried out to identify the predictors of IA. The significance value for the study results has been set at P<0.05.
| Results|| |
Sociodemographic characteristics of the sample [Table 1]
|Table 1: The distribution of scores by sociodemographic characteristics of the sample|
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The study sample of n = 2776 comprised undergraduate university students of which 1680 (60.50%) were female, and 1096 (39.50%) were male participants. The ages of the study sample ranged from 18 to 21 years with the mean age being 18.61 (1.03) years. One-third of the samples (35.50%) initiated internet use between the ages of 10 and 15 years and more than half of the study samples (52.00%) had the first use of the Internet between ages of 16 and 18 years. Mental health consultation was reportedly sought by around (n = 49) 1.80% of the study sample for engaging in problematic/excessive use of the Internet.
Internet use characteristics and internet addiction test scores [Table 2]
|Table 2: Distribution of mean scores of the students on the Internet addiction test according to some of the characteristics of their internet usage|
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Of the total n = 2776, 29.9% (n = 831) of university students met criterion on IAT for mild addictive internet use, 16.4% (n = 455) for moderate addictive internet use, and 0.5% (n = 13) for severe IA. Addictive internet use behaviors were significantly higher among male university students (P ≤ 0.001). A trend toward positive correlation (rs= 0.163; P ≤ 0.001) was observed between age and IA scores which suggests that as an individual's age increases (in this age range of 18–21 years) their risk for addictive internet use becomes higher. University students who engaged in excessive/addictive use of internet were staying in rented accommodations (P ≤ 0.765), used both laptops and mobiles (P ≤ 0.001), spent 180 min or more in a day on the Internet (P ≤ 0.001), accessed internet several times in a day (P ≤ 0.001), used internet for >4 years (P ≤ 0.001), expressed craving for use of the Internet (P ≤ 0.001) and had made lesser attempts to reduce excessive internet use (P ≤ 0.003).
Internet use characteristics and Self-Report Questionnaire scores [Table 3]
|Table 3: Distribution of the mean scores of the students on the self-report questionnaire according to some of their characteristics of internet usage|
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Psychological distress on SRQ was nearly equal among female and male university students (P = 0.337). University students who experienced psychological distress were staying away from home in rented accommodations (P = 0.013), used both laptops and mobiles to access internet (P ≤ 0.001), spent 180 min or more in a day on the Internet (P ≤ 0.001), used internet for >2 years (P ≤ 0.001), accessed internet several times a day (P ≤ 0.001), expressed craving for use of the Internet (P ≤ 0.001) and had made no significant attempts to reduce the usage of the Internet (P ≤ 0.703).
Stepwise regression analysis [Table 4]
|Table 4: Stepwise regression analysis for predictors of internet addiction|
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The stepwise regression analysis indicated that university students who were male (odds ratio [OR] = 2.801, P ≤ 0.001), used the Internet for duration of > 4 years (OR = 1.959; P ≤ 0.001), spent more than 180 min in day on internet (OR = 6.357, P ≤ 0.001), accessed internet several times a day (OR = 2.471, P ≤ 0.001) and were experiencing psychological distress, namely depression (OR = 1.175; P ≤ 0.001) were at higher risk for engaging in IA.
The university students (n = 2776) attained a mean score of 4.87 (standard deviation [SD] = 3.90) on the SRQ and 29.62 (SD = 18.95) on the IAT. A positive correlation was found between psychological distress (depression) and IA (rs= 0.363; P ≤ 0.001). The students who have higher SRQ scores were likely to engage in the addictive use of the Internet.
| Discussion|| |
Internet addiction and prevalence
The university students engaged in severe addictive use of the Internet were 0.5% and 16.4% qualified for moderate IA as per the criteria offered by IAT. The present study findings on the prevalence of severe IA are similar to those indicated by other studies on university students - medical (1.2%; 0.7%) and dental students (2.3%; 4.7%) from India., The studies on undergraduate university students too have indicated a prevalence rate of severe IA ranging from 0.3% in India, 2.2% in Iranian university students  2.8% in Iran medical students, 5.6% in Greece, 9.7% in Turkey, 11.5% in Chile, and 13.2% in Iran.
The present study findings are similar to prevalence rates of moderate IA reported by other Indian studies which ranged from 7.45% in medical students  to 7.4% and 15.2% in university undergraduates. A study from Iran indicated 8% of university students were engaged in moderate levels of IA. The variations in sample sizes, instruments used, and different populations which were assessed across different periods of time may be the likely factors for the difference in results of prevalence reported across studies.
Internet addiction and sociodemographic characteristics
The regression and correlation analysis findings of the study indicate that university students who are comparatively older in the study age range were at higher risk for indulging in IA. These findings are in overall agreement to those reported among university students in China. The initial years of university education offer a sudden shift to minimal parental control and increases opportunities for self-expression, use of self-control, and coping strategies. Those young individuals who lack self-control in context of decreased parental monitoring are at higher risk for IA.
Our study indicated that IA behaviors were significantly higher among male university students in comparison to female university students (P ≤ 0.001). In our study, male gender also predicted IA. The present study finding is similar to other study results from India., Studies conducted in Iran, Greece, Taiwan, also reveal similar findings with respect to gender differences. The findings of meta-analytic research of studies conducted between 1996 and 2006 support the vulnerability of male gender to IA. It can be understood that since socialization offers lesser restriction to males in a majority of cultural contexts, there is a higher involvement of males in internet chatting, online gaming, online gambling, virtual sex, and pornography ,,, which increases the probability of males becoming addicted to the Internet. In addition, the potential risk for males for IA increases as they are more efficient at using computers, mobile phones, internet tools, receive lesser supervision by parents and thus end up using the Internet more for entertainment needs and in the process intensifying their opportunities for IA.
University students staying away from their families, in rented accommodations, were at a higher risk of developing IA. This study finding is in alignment with studies done in India  and Iran  which too suggested IA is higher among students who stay independently. The experience of boredom, loneliness, and availability of privacy, ease of the Internet access, and minimal presence of parental supervision are factors which likely escalate the excessive use of the Internet.
Internet addiction and internet use characteristics
The amount of time an individual spends on the Internet is a crucial factor which increases risk of IA. Our study findings suggest that university students who were engaging in more than 3 h of internet use per day in nonacademic internet activities had higher levels of IA (P ≤ 0.001). Our study indicated that time spent on internet per day and daily frequencies of internet use were variables which predicted IA. The severity levels of IA increase with increase in duration of internet use is consistently suggested by research evidence from many studies.,, Thus, findings apparently imply that when the time spent by students on internet use becomes greater, the risk of becoming addicted to internet multiplies and becomes higher.
University students who accessed internet several times a day (P ≤ 0.001) and remained online throughout the day also had higher levels of IA. Another study from India  corroborated with the findings of the present study. Individuals who were using both mobiles and computer tablets experienced higher levels of IA. Mobile phones and computer tablets have become nearly inseparable gadgets of youth as it offers easy accessibility, affordability, and connectivity to the Internet throughout the day and these characteristics in itself appear to intensify internet addictive behaviors.
Our study also indicates that students who had higher levels of IA scores were using the Internet for more than 4 years and the duration of use was a variable which predicted IA. Duration of internet use was also predictor for IA among university students in Turkey. In our sample, 43.72% of university students had internet use of 4 years and above. However, this finding does not necessarily highlight the time duration required for the emergence of IA since its initial use by the individual. Another study conducted in India suggested time duration of 6 years between first use and development of IA. However, this time duration may steadily reduce over the years with the increase in accessibility of the Internet at cheaper rates in India. It is interesting to note the occurrence that why new challenges keep arising with invention of newer technologies which are created in the first place to solve existing challenges. Nearly 55.5% university students who were aware about IA had made attempts to reduce internet use. This indicates that the first initial step toward the healthy use of technology can be awareness generation about IA among university students and faculty.
Internet addiction and psychological distress
The presence of psychological distress appears to be a significant factor which has the potential to increase the risk of IA. Regression analysis indicated university students who had psychological distress (depressive symptoms) predicted IA or were at risk for engaging in IA behaviors. The correlation between depression and IA observed in this study has been reported by other studies.,,,, It is to be observed that a noticeable proportion of the present study sample 1.80% (n = 49) had in the recent past approached a mental health professional for excessive internet use.
The beginning of an undergraduate course in university brings with itself a set of challenges and a phase of transition in youth life. Many students stay in rented accommodations or in university hostel to address the requirements of the course. In addition, this transition requires them to solve everyday challenges of staying out of home, taking care of one's health, form new interpersonal relationships, and gather social and emotional support. The individuals who are vulnerable can experience boredom, loneliness, and depression during this phase of transition in young adulthood.
In this context, the Internet can be viewed by some individuals as a medium to cope up with the psychological distress caused by the new challenges. To establish new interpersonal relationships, seek information, guidance, and for entertainment, the Internet can be used by students. However, the risk for IA increases with excessive use of the Internet which has potential to cause depression. The individuals who are predisposed to depression or are experiencing depression are engaging in addictive use of the Internet., Individuals with depression understandably experience sadness, loneliness, low self-esteem, decreased energy and lack of motivation , which likely drives them to use the Internet to overcome/escape these unpleasant emotional states including depression ,,, Gaining of social approval, enhancement of self-esteem, and overcoming of loneliness can be achieved through the Internet. On the contrary, an individual who starts skipping opportunities and diverts time and meant for social gatherings, outdoor events, sports activities, family events toward internet use ends up isolating oneself and predisposes oneself toward depression. University students who are engage in excessive internet use may at a point of time find it difficult to engage in social interactions and relate socially to others; thus they may move away from real people and escape into the online world with virtual people with whom social interactions and rewards are more controllable making emotions predictable.,,, Thus, exacerbation of IA and depression can occur when both psychological conditions interact with each other.,
| Conclusions and Suggestions|| |
In South India, IA appears to be an emergent and significant mental health condition among university students. Psychological distress (depression) and IA were positively correlated, and it is a variable which predicts IA. University students must be screened for IA and psychological distress as there is a substantial possibility that they coexist and can magnify each other. Early intervention can be offered to young adults if efforts are directed toward the identification and timely referrals to specialized centers of psychological care. Nearly 55.5% of university students who knew about IA had made attempts to reduce internet use. Thus, awareness generation initiatives about IA and its risk factors among students and faculty will be a valuable initial step towards healthy use of the Internet. Upcoming studies can evaluate the relationship of IA and depression in a manner which is more inclusive.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Saville BK, Gisbert A, Kopp J, Telesco C. Internet addiction and delay discounting in college students. Psychol Rec 2010;60:273-86.
Young KS. Internet addiction: A new clinical phenomenon and its consequences. Am Behav Sci 2004;48:402-15.
Bertagna BR. The internet-disability or distraction – An analysis of whether internet addiction can qualify as a disability under the americans with disabilities act. Hofstra Lab Emp LJ 2007;25:419.
Wan CS, Chiou WB. The motivations of adolescents who are addicted to online games: A cognitive perspective. Adolescence 2007;42:179-97.
Murali V, George S. Lost online: An overview of internet addiction. Adv Psychiatr Treat 2007;13:24-30.
Petersen KU, Weymann N, Schelb Y, Thiel R, Thomasius R. Pathological internet use – Epidemiology, diagnostics, co-occurring disorders and treatment. Fortschr Neurol Psychiatr 2009;77:263-71.
Tsai HF, Cheng SH, Yeh TL, Shih CC, Chen KC, Yang YC, et al
. The risk factors of internet addiction – A survey of university freshmen. Psychiatry Res 2009;167:294-9.
Üneri ÖS, Tanidir C. Evaluation of internet addiction in a group of high school students: A cross-sectional study. Dusunen Adam 2011;24:265.
Whang LS, Lee S, Chang G. Internet over-users' psychological profiles: A behavior sampling analysis on internet addiction. Cyberpsychol Behav 2003;6:143-50.
Livingstone SM, Lievrouw LA. Handbook of New Media: Social Shaping and Consequences of ICTs. London, United Kingdom: Sage; 2002.
Teo TS, Lim VK. Gender differences in internet usage and task preferences. Behav Inf Technol 2000;19:283-95.
Young KS. Internet addiction: Symptoms, evaluation and treatment. Innovations in Clinical Practice: A Source Book. Vol. 17. Sarasota, FL: Professional Resource Press; 1999. P. 19-31.
Hoffman DL, Novak TP, Venkatesh A. Has the internet become indispensable? Communications of the ACM. 2004;47:37-42.
Kuss DJ, Griffiths MD. Adolescent online gaming addiction. Educ Health 2012;30:15-7.
Meerkerk GJ, Van Den Eijnden RJ, Vermulst AA, Garretsen HF. The compulsive internet use scale (CIUS): Some psychometric properties. Cyberpsychol Behav 2009;12:1-6.
Caplan SE. Problematic internet use and psychosocial well-being: Development of a theory-based cognitive – Behavioral measurement instrument. Comput Hum Behav 2002;18:553-75.
Young KS. Internet addiction: The emergence of a new clinical disorder. Cyberpsychol Behav 1998;1:237-44.
Huang C. Internet addiction: Stability and change. Eur J Psychol Educ 2010;25:345-61.
Chen K, Tarn JM, Han BT. Internet dependency: Its impact on online behavioral patterns in E-commerce. Hum Syst Manage 2004;23:49-58.
Carli V, Durkee T, Wasserman D, Hadlaczky G, Despalins R, Kramarz E, et al.
The association between pathological internet use and comorbid psychopathology: A systematic review. Psychopathology 2013;46:1-3.
Yen JY, Ko CH, Yen CF, Wu HY, Yang MJ. The comorbid psychiatric symptoms of internet addiction: Attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. J Adolesc Health 2007;41:93-8.
Fennell MJ. Low self-esteem: A cognitive perspective. Behav Cogn Psychother 1997;25:1-26.
Rosenberg M. The Measurement of Self-Esteem, Society and the Adolescent Self-Image. Princeton: New Jersey, United States; Princeton University Press; 1965. p. 16-36.
Craig RJ. The role of personality in understanding substance abuse. Alcohol Treat Q 1995;13:17-27.
Griffiths M. Does Internet and computer “addiction” exist? Some case study evidence. Cyber Psychol Behav 2000;3:211-8.
Yang CK, Choe BM, Baity M, Lee JH, Cho JS. SCL-90-R and 16PF profiles of senior high school students with excessive internet use. Can J Psychiatry 2005;50:407-14.
Tsai CC, Lin SS. Internet addiction of adolescents in Taiwan: An interview study. Cyberpsychol Behav 2003;6:649-52.
Young KS. Caught in the Net: How to Recognize the Signs of Internet Addiction – And a Winning Strategy for Recovery. New York, United States: John Wiley & Sons; 1998.
Widyanto L, McMurran M. The psychometric properties of the internet addiction test. Cyberpsychol Behav 2004;7:443-50.
Beusenberg M, Orley JH; World Health Organization. A User's Guide to the Self Reporting Questionnaire (SRQ). Geneva, Switzerland: World Health Organization; 1994.
Gedam SR, Shivji IA, Goyal A, Modi L, Ghosh S. Comparison of internet addiction, pattern and psychopathology between medical and dental students. Asian J Psychiatr 2016;22:105-10.
Jain T, Mohan Y, Surekha S, Svathi MV, Swapna US, Swathy Y, et al
. Prevalence of internet overuse among undergraduate students of a private university in South India. Int J Recent Trends Sci Technol 2014;11:301-4.
Sharma A, Sahu R, Kasar PK, Sharma R. Internet addiction among professional courses students: A study from central India. Int J Med Sci Public Health 2014;3:1069-73.
Bahrainian SA, Alizadeh KH, Raeisoon MR, Gorji OH, Khazaee A. Relationship of internet addiction with self-esteem and depression in university students. J Prev Med Hyg 2014;55:86-9.
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.
] [Full text]
Tsimtsiou Z, Haidich AB, Spachos D, Kokkali S, Bamidis P, Dardavesis T, et al
. Internet addiction in Greek medical students: An online survey. Acad Psychiatry 2015;39:300-4.
Canan F, Ataoglu A, Ozcetin A, Icmeli C. The association between internet addiction and dissociation among Turkish college students. Compr Psychiatry 2012;53:422-6.
Berner JE, Santander J, Contreras AM, Gómez T. Description of internet addiction among chilean medical students: A cross-sectional study. Acad Psychiatry 2014;38:11-4.
Chaudhari B, Menon P, Saldanha D, Tewari A, Bhattacharya L. Internet addiction and its determinants among medical students. Ind Psychiatry J 2015;24:158-62.
] [Full text]
Paul A, Ganapthi C, Duraimurugan M, Abirami V, Reji E. Internet addiction and associated factors: A study among college students in South India. Innov J Med Heal Sci 2015;5:121-5. [doi: 10.15520/ijmhs].
Ni X, Yan H, Chen S, Liu Z. Factors influencing internet addiction in a sample of freshmen university students in China. Cyberpsychol Behav 2009;12:327-30.
Lee S. Problematic Internet use among college students: An exploratory survey research study. The University of Texas at Austin; 2009.
Goel D, Subramanyam A, Kamath R. A study on the prevalence of internet addiction and its association with psychopathology in Indian adolescents. Indian J Psychiatry 2013;55:140-3.
] [Full text]
Frangos CC, Fragkos KC, Kiohos A. Internet addiction among Greek university students: Demographic associations with the phenomenon, using the Greek version of Young's Internet Addiction Test. Int J Eco Sci App Res 2010;3;49-74.
Byun S, Ruffini C, Mills JE, Douglas AC, Niang M, Stepchenkova S, et al.
Internet addiction: Metasynthesis of 1996-2006 quantitative research. Cyberpsychol Behav 2009;12:203-7.
Batigun AD, Kilic N. The relationships between internet addiction, social support, psychological symptoms and some socio-demographical variables. Turk Psikoloji Derg 2011;26:1-13.
Kim K, Ryu E, Chon MY, Yeun EJ, Choi SY, Seo JS, et al.
Internet addiction in Korean adolescents and its relation to depression and suicidal ideation: A questionnaire survey. Int J Nurs Stud 2006;43:185-92.
Yang SC, Tung CJ. Comparison of Internet addicts and non-addicts in Taiwanese high school. Comput Hum Behav 2007;23:79-96.
Ko CH, Yen JY, Chen CS, Chen CC, Yen CF. Psychiatric comorbidity of internet addiction in college students: An interview study. CNS Spectr 2008;13:147-53.
Asiri S, Fallahi F, Ghanbari A, Kazemnejad-Leili E. Internet addiction and its predictors in Guilan medical sciences students, 2012. Nurs Midwifery Stud 2013;2:234-9.
Ceyhan E, Ceyhan AA, Gürcan A. Validity and reliability studies of problematic internet use scale. Kuram Uygulamada Eğit Bilimleri Derg 2007;7:387-416.
Salehi M, Norozi Khalili M, Hojjat SK, Salehi M, Danesh A. Prevalence of internet addiction and associated factors among medical students from Mashhad, Iran in 2013. Iran Red Crescent Med J 2014;16:e17256.
Boonvisudhi T, Kuladee S. Association between internet addiction and depression in Thai medical students at faculty of medicine, ramathibodi hospital. PLoS One 2017;12:e0174209.
Krishnamurthy S, Chetlapalli SK. Internet addiction: Prevalence and risk factors: A cross-sectional study among college students in Bengaluru, the Silicon Valley of India. Indian J Public Health 2015;59:115-21.
] [Full text]
Senormancı O, Saraçlı O, Atasoy N, Senormancı G, Koktürk F, Atik L, et al.
Relationship of internet addiction with cognitive style, personality, and depression in university students. Compr Psychiatry 2014;55:1385-90.
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.
] [Full text]
Ha JH, Yoo HJ, Cho IH, Chin B, Shin D, Kim JH, et al.
Psychiatric comorbidity assessed in Korean children and adolescents who screen positive for internet addiction. J Clin Psychiatry 2006;67:821-6.
Bernardi S, Pallanti S. Internet addiction: A descriptive clinical study focusing on comorbidities and dissociative symptoms. Compr Psychiatry 2009;50:510-6.
Ho RC, Zhang MW, Tsang TY, Toh AH, Pan F, Lu Y, et al.
The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry 2014;14:183.
Facer K, Sutherland R, Furlong R, Furlong J. What's the point of using computers? The development of young people's computer expertise in the home. New Med Soc 2001;3:199-219.
Ko CH, Yen JY, Chen CC, Chen SH, Yen CF. Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. J Nerv Ment Dis 2005;193:273-7.
Kraut R, Patterson M, Lundmark V, Kiesler S, Mukopadhyay T, Scherlis W, et al.
Internet paradox. A social technology that reduces social involvement and psychological well-being? Am Psychol 1998;53:1017-31.
Billieux J, Thorens G, Khazaal Y, Zullino D, Achab S, Van der Linden M. Problematic involvement in online games: A cluster analytic approach. Comput Hum Behav 2015;43:242-50.
Kuss DJ, Griffiths MD. Online Gaming Addiction in Children and Adolescents: A Review of Empirical Research. Akadémiai Kiadó: Springer Science+Business Media BV, Formerly Kluwer Academic Publishers BV; 2012.
Kuss DJ, Griffiths MD, Karila L, Billieux J. Internet addiction: A systematic review of epidemiological research for the last decade. Curr Pharm Des 2014;20:4026-52.
Weinstein A, Feder LC, Rosenberg KP, Dannon P. Internet addiction disorder: Overview and controversies. Behav Addict 2014;5:99-117.
Wartberg L, Sack PM, Petersen KU, Thomasius R. Psychopathology and achievement motivation in adolescents with pathological internet use. Prax Kinderpsychol Kinderpsychiatr 2011;60:719-34.
Young KS, Rogers RC. The relationship between depression and Internet addiction. Cyberpsychol Behav 1998;1:25-8.
Cho SM, Sung MJ, Shin KM, Lim KY, Shin YM. Does psychopathology in childhood predict internet addiction in male adolescents? Child Psychiatry Hum Dev 2013;44:549-55.
[Table 1], [Table 2], [Table 3], [Table 4]