The Internet has been known as an effective tool in various scientific areas, business, education, culture, and policy [1, 2]. It has grown significantly in recent years, and it has dramatically revolutionized the ways we communicate. Despite all its benefits, overuse can be costly [3]. Internet addiction is one of the destructive consequences of the Internet and a new type of mental health disorder in the 21 century [4]. As far as we know, the diagnostic and statistical manual of mental disorders (DSM) does not include a separate category that has been considered for Internet addiction disorder, but its diagnostic criteria overlap with those of impulse control disorders, compulsive gambling, and substance dependence [5]. Addiction is a condition characterized by a persistent physical or mental desire to use drugs [6]. Researchers tend to classify people who are addicted to the Internet as addicts because they show the same signs and symptoms as people with drug and alcohol addiction. Griffiths believes that Internet addiction consists of six common components with other addictions, salience (dominance of thought, feeling, and behavior), mood modification (Internet as a coping mechanism), tolerance (increase the amount of Internet activity to achieve the former level of pleasure), withdrawal (unpleasant feelings and physical symptoms when Internet activity is reduced or stopped), conflict (between the addict and other people, other activities or within the individual), and relapse (tendency to repeat patterns of excessive use after reducing or stopping) [7]. Young people, especially students, have shown a great interest in the Internet in the last two decades [8]. 
According to available statistics in Iran, the number of Internet users in schools and universities is 15 million people daily, which is a significant number. Internet addiction among university students can affect social life (relationships with family members, friends, coworkers, and neighbors), health (headache, spine pain, and vision problems), attitude (bad mood, anxiety, and depression), as well as study (classes, exams, tests, tasks, and grades) [9, 10, 11]. 
The main point is that not everyone who has used the Internet for a long time is recognized as Internet addict. Only those who experience excessive anxiety and disturbance due to using the Internet, so that it negatively affects their physical, psychological, social, and economic performance are classified as Internet addicts [12]. Many disciplines have been trying to find the possible cause(s) of Internet addiction, especially among young people. For example, biological theories link the cause to chemical fluctuations in the brain and neurotransmitters, hereditary and congenital factors. The results of the research conducted by some researchers in biology have shown that increased activity in the orbitofrontal cortex and decreased activity in the anterior belt of people with Internet addiction can be seen [12]. Cognitive theories have emphasized false cognitions and false cognitive processing of these people [13]. Findings obtained from research on the personality factors affecting Internet addiction show that people with Internet addiction are more Introverted and emotional, and the level of Internet addiction in these people is higher than in extroverted people. In another research, it was highlighted that extroverted and conscientious people are less likely to be addicted to the Internet [14].  
Epidemiologic studies conducted in the United Kingdom, the United States, Taiwan, Australia, and Central European countries have reported that the prevalence of Internet addiction among university students is 5% to 25% [15]. In our country, several types of research have been conducted to investigate the same topic. In a study conducted by Solhi and colleagues in the student association of Tehran University of Medical Sciences on students aged 19-25 years, the prevalence of Internet addiction was shown to be 18% [9]. Various studies have shown that adolescents and young people are the most vulnerable to Internet addiction [16]. 
Youth is the largest population block in our country (Iran), and the age group with the highest levels of internet penetration is made up of young people.  Thus, it is natural that the risk of Internet addiction in our country is higher than in other countries. Undoubtedly, Internet has many advantages, but this novel technology can disrupt the daily life of young people and their performance. Internet addicts may experience a high level of mental and physical problems. The first step to reduce such problems, especially among young people, is the early diagnosis of this addiction. As far as the author of the present study knows, few researchers have investigated Internet addiction among university students of Gonabad City, Iran. Therefore, this study aims at determining the prevalence of Internet addiction among students of Payam Noor and Islamic Azad Universities of Gonabad City in 2015-2016.
2. Methods 
This research was a cross-sectional descriptive study. The statistical population included all students of Payam Noor and the Islamic Azad University of Gonabad Branch studying in the second semester of the academic year 2015-2016. Simple random sampling was used. The sample size was determined according to the goals of the research, previous studies, and Daniels' Running Formula. 
The sample size of 1091 people was chosen using Daniel’s formula, and according to the prevalence of 18% obtained in previous studies, with accuracy of 0.03 and 99% confidence. Finally, 1200 people were included in the study due to the possibility of not completing the research tools correctly by the research participants. Five hundred fifty students from Payam Noor University and 650 students from Islamic Azad University randomly participated in the study. They were between the ages of 18-28 years and were studying for both bachelor’s and master’s degrees. Informed consent was obtained to conduct the research, and then the questionnaires containing demographic information, such as age, sex, section, marital status, the field of study, place of residence, and university, and Internet addiction questionnaire were provided to assess the possibility of Internet addiction. The goals of the research were briefly described to the participants, and they were asked to answer each question honestly. The inclusion criteria included signing informed consent, having physical and mental health, having the ability to write and read, being a student of Payam Noor or the Islamic Azad University of Gonabad, studying in the given fields, and being a student at the time of the research. The Young’s Internet Addiction Diagnostic Questionnaire (IADQ) was used to assess the students’ Internet addiction status. In addition, demographic survey questions were used to collect demographic information related to age, gender, educational level, marital status, place of residence, the field of study, and university. 
Internet addiction test (IAT): Young’s IAT measures self-reported compulsive use of the Internet and assesses symptoms of Internet addiction under different conditions. It consists of 20 questions. Each response is scored on a 5-point Likert scale, rarely, rarely, sometimes, frequently, and almost always. The scores range from 20 to 100. Higher scores represent a greater possibility of Internet addiction. The scores between 20-49 show the average Internet users who are not addicted to the Internet (ordinary users), scores of 50-79 indicate people who sometimes have problems due to Internet use (mild addiction), and scores between 80-100 indicate people who are addicted to Internet [1]. It is a standard test, and its reliability and validity have been confirmed in many studies. In Kim’s study, Cronbach’s alpha was 0.90 [17]. In the current study, the reliability of the test was calculated using Cronbach’s alpha, and the value of this statistic was equal to 0.88. Data were analyzed using SPSS software version 16 and the Chi-squared test. Results were reported by frequency and percentage. The significance level of 0.05 was considered.
3. Results
Since all questionnaires were not completed correctly, the sample size of Payam Noor University students was 545 people (46.1%), and the sample size of Islamic Azad University students was 637 people (53.9%). Table 1 lists the demographic findings of the study. 


The Mean±SD of the participant’s scores were 52.17±22.27. The lowest score was 27, and the highest score was 99, which showed the severe extent of Internet addiction among them. Given the way of answering the questions of Young’s IAT, the research samples were classified into three groups, without Internet addiction, at risk of Internet addiction, and with Internet addiction. According to the findings, 612 participants (51.8%) were not addicted to the Internet, 401 (33.9%) were at risk of Internet addiction, and 169 (14.3%) were addicted to the Internet. Table 2 presents the frequency of Internet addiction by gender, age, level of education, marriage, place of residence, field, and university in research participants.


In Table 2, the results obtained from the Chi-square analysis showed that the prevalence of Internet addiction disorder has no significant relationship with gender, marital status, and field of study (P>0.05). In contrast, a significant relationship was observed between age, level of education, place of residence, and University (P<0.05).
4. Discussion
The results obtained from this study showed that 14.3% of the participants suffered from Internet addiction. Different estimations exist about the prevalence of Internet addiction, so in some studies, the percentage of the prevalence of Internet addiction among university of students has been estimated at 20% to 30 %. In a study conducted by Frangos and colleagues, the percentage of IA (Internet addiction) among university students was 11.6% [18]. This percentage was 12.26% and 6% for university students in Taiwan and Turkey, respectively [19, 20]. The prevalence of Internet addiction in some studies shows higher numbers compared to ours. Such differences in the percentages may be due to the effects of the measurement tool, different demographic contexts, the age range of the sample, study time, and internet access.  
The results of the study showed that 33.9% of university students were at risk of Internet addiction. In another research, it has been reported that 3.2% of university students were at risk of Internet addiction, which shows a lower percentage than the present study [21]. No significant relationship was observed between gender and the prevalence of Internet addiction, which is consistent with the results of the study conducted by Oktug [22]. Of course, gender differences in the incidence of this addiction have been confirmed in many studies. For example, Alavi and colleagues showed that male students are more at risk of Internet addiction (1.8%) than female students [23], which is inconsistent with the findings of our study and the findings obtained from studies conducted by Davis [13] and Canan [24]. In the present study, no significant relationship is observed between the field of study and Internet addiction, which is inconsistent with the results of the studies conducted by Hosseini [25]. The other finding of the present study was that the prevalence of Internet addiction has no significant relationship with marital status and level of education, which is consistent with the results of Kiany’s study [26]. In other studies, it has been identified that single students are 3.5 times more at risk of Internet addiction than married students, which is inconsistent with the results of the present study [20].
Regarding the difference in the prevalence of Internet addiction in different societies among different samples and the consistency and inconsistency of the findings of other studies with the present study, it can be said that such differences can be due to the differences in sample size and its specific characteristics, skills and expertise of researchers in conducting the research process, Internet addiction diagnostic tools and cultural and social differences among societies. 
In our study, age has a significant relationship with the prevalence of Internet addiction disorder. The lowest and the highest prevalence of Internet addiction disorder were observed among people aged 28 years and 22 years, respectively, which is consistent with the results obtained by Tsai and Lin [27]. It has been shown in numerous studies that age is a strong predictor of Internet addiction, and the prevalence of Internet addiction is higher among young people and university students. It can be described that the unique and special features of the Internet, such as simplicity, attractiveness, low cost, anonymity and so on, have attracted young people all over the world. Many young people overuse the Internet to acquire social support, friendship, fun, and entertainment. Today, young people, especially university students, mainly communicate and obtain information via the Internet. University students can use this novel technology to communicate with their professors and other experts in the field of their study inside and outside the country. They even perform many academic activities with it. Not only can young people use the Internet to perform academic and scientific activities but also they can experience new, exciting things. The Internet environment paves the way for these aims by providing a space with an unknown and changing identity so that young people become strongly dependent on it.
The results of our study showed that the rate of Internet addiction in students who live in the dormitory is higher than in students who do not live in the dormitory. It can be described that the former group (students in dormitories) are far from home, so they tend to spend their time on the Internet. This finding is inconsistent with Beheshtian’s result, which shows that the prevalence of Internet addiction among students who live in the dormitory was lower than among students who do not live in the dormitory [25]. Nevertheless, few types of research have been conducted on the relationship between these two variables. In the present study, a significant difference is observed between both groups of universities in terms of the prevalence of Internet addiction. The prevalence in students of the Islamic Azad University of Gonabad was higher than students of Payam Noor University. This finding is consistent with the results obtained by Sepehrian and colleagues [28]. This difference may be due to Islamic Azad University students having more access to the Internet and attending classes more than Payam Noor students.
Given the findings of our study and that a large number of our young people tend to overuse the Internet due to the lack of enough entertainment and recreation, we suggest that the executive officials consider appropriate and desirable entertainment programs for them to solve this problem to increase their quality of life and their educational, professional and social performances. Cognitive-behavioral therapy (CBT) is the best intervention to reduce Internet addiction among young people. In this method, the therapist tries to increase the people’s sense of control of themselves and their conditions to take over the situation. In this way, first, they reduce the hours being on the Internet and then their mental dependence on it. As can be seen from the results of the present study since the prevalence of Internet addiction is high among university students, it is expected that more attention will be paid to students with an Internet addiction disorder, and this intervention will be used to treat them.
Pre-treatment prevention is vital in any disorder. We hope that the results of the present study can inform people, especially the youth in our country, that despite being attractive, enjoyable, and useful, the Internet can have many adverse effects on their physical and mental health if used excessively.
5. Conclusion
The overall prevalence of Internet addiction in the present study was 14.3%, which is relatively high. Despite the lack of consensus on the definition of an Internet addiction disorder and its prevalence, most scientists in the field of social sciences, psychology, and psychiatry believe that Internet addiction disorder is a widespread problem among young people [29]. It is essential to pay enough attention to people with Internet addiction. Sometimes this addiction is caused by depressive disorder, social anxiety disorder, or obsessive-compulsive disorder, and a person may tend to use the Internet excessively to reduce the annoying symptoms of these disorders. This study aimed to determine the frequency of Internet addiction disorder. Undoubtedly, accurate statistics on the prevalence of Internet addiction disorder can help design and develop effective treatment programs for this group in a much better way.
Limitation 
The present study had some limitations. The studied sample was only students studying at Islamic Azad and Payam Noor Universities in some special fields. This research was conducted only in Gonabad City, and it is prudent to generalize its results to adolescents in other cities and provinces. Mental, physical, family and social conditions have a key role in the occurrence of Internet addiction, but their predictive role was not considered in this study. The present study was a cross-sectional descriptive study. In this method, research data is collected in a limited time, and therefore, the results obtained from it should be generalized with caution.

Ethical Considerations
Compliance with ethical guidelines
This research was approved by the Ethics Committee of Bushehr University of Medical Sciences (Code: IR.BPUMS.REC.1400.146).

Funding
This research did not received any grant from funding agencies in the public, commercial, or non-profit sectors.

Authors' contributions
All authors equally contributed to preparing this article.

Conflict of interest 
The authors declared no conflict of interest.

Acknowledgment
We are very grateful to the presidents of Islamic Azad University and Payam Noor of Gonabad City, and all the students who participated in all stages of the research process.


References

1. Malak MZ, Khalifeh AH, Shuhaiber AH. Prevalence of internet addiction and associated risk factors in jordanian school students. Comput Hum Behav. 2017; 70:556-63.[DOI:10.1016/j.chb.2017.01.011]
2. Alhajjar BI. Internet addiction and psychological morbidity among nursing students in Gaza-Palestine. Am J Appl Psychol. 2014; 3(4):99-103. [DOI:10.11648/j.ajap.20140304.13]
3. Lin MP, Wu JY, You J, Hu WH, Yen CF. Prevalence of internet addiction and its risk and protective factors in a representative sample of senior high school students in Taiwan. J Adolesc. 2018; 62:38-46. [DOI:10.1016/j.adolescence.2017.11.004] [PMID]
4. Bidi F, Namdari-Pejman M, Kareshki H, Ahmadnia H. The mediating role of metacognition in the relationship between internet addiction and general health. Addict Health. 2012; 4(1-2):49-56. [PMCID] [PMID]
5. Lu L, Xu DD, Liu HZ, Zhang L, Ng CH, Ungvari GS, et al. Internet addiction in Tibetan and Han Chinese middle school students: Prevalence, demographics and quality of life. Psychiatry Res. 2018; 268:131-6. [DOI:10.1016/j.psychres.2018.07.005] [PMID]
6. Yücens B, Üzer A. The relationship between internet addiction, social anxiety, impulsivity, self-esteem, and depression in a sample of Turkish undergraduate medical students. Psychiatry Res. 2018; 267:313-8. [DOI:10.1016/j.psychres.2018.06.033] [PMID]
7. Griffiths, M. Internet addiction: Does it really exist? In: Gackenbach J, editor. Psychology and the Internet: Intrapersonal, interpersonal, and transpersonal implications. Cambridge: Academic Press; 1998. [Link]
8. Marazziti D, Mucci F, Vanelli F, Renda N, Baroni S, Piccinni A. Prevalence of internet addiction: A pilot study in a group of italian students. Eur Psychiatry. 2017; 41:S248. [DOI:10.1016/j.euroneuro.2016.07.029]
9. Fitzpatrick JJ. Internet addiction: Recognition and interventions. Arch Psychiatr Nurs. 2008; 22(2):59-60 [DOI:10.1016/j.apnu.2007.12.001] [PMID]
10. Aboujaoude E. Problematic internet use: An overview. World Psychiatry. 2010; 9(2):85-90. [DOI:10.1002/j.2051-5545.2010.tb00278.x] [PMID] [PMCID]
11. Tang CSK, Wu AMS, Yan ECW, Ko JHC, Kwon JH, Yogo M, et al. Relative risks of internet-related addictions and mood disturbances among college students: A 7-country/region comparison. Public Health. 2018; 165:16-25. [DOI:10.1016/j.puhe.2018.09.010] [PMID]
12. 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(2):158-62. [DOI:10.4103/0253-7176.92068] [PMID] [PMCID]
13. Davis RA. A cognitive behavioral model of pathological internet use. Comput Hum Behav. 2001; 17(2):187-95. [DOI:10.1016/S0747-5632(00)00041-8]
14. Tamannaifar MR, Seddighi Arfai F, Gandomi Z. [The relationship between internet addiction and personality traits of high school students (Persian)]. Zahedan J Res Med Sci. 2012; 14(1):67-71. [Link]
15. Young KS. Internet addiction: The emergence of a new clinical disorder. Cybersychol Behav. 1996; 1(3):237-44. [DOI:10.1089/cpb.1998.1.237]
16. Erfanian M, Javadinia SA, Abedini MR, Bijari B. Iranian Students and social networking sites: Prevalence and pattern of usage. Procedia Soc Behav Sci. 2013; 83:44-6. [DOI:10.1016/j.sbspro.2013.06.009]
17. 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(2):185-92. [DOI:10.1016/j.ijnurstu.2005.02.005] [PMID]
18. 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 Econ Sci Appl Res. 2010; 3(1):49-74. [Link]
19. Yao MZ , Zhong ZJ. Loneliness, social contacts and internet addiction: A cross.lagged panel study. Comput Hum Behav 2014; 30:164-70. [DOI:10.1016/j.chb.2013.08.007]
20. Kayri M, Günüç S. The adaptation of internet addiction scale into Turkish: The study of validity and reliability. J Fac Educ Sci. 2009; 42:157-75. [DOI:10.1501/Egifak_0000001142]
21. Kuss DJ, Griffiths MD, Binder JF. Internet addiction in students: Prevalence and risk factors. Comput Hum Behav. 2013; 29(3): 959-66. [DOI:10.1016/j.chb.2012.12.024]
22. Oktuğ BZ. Gender differences in internet addiction and tendency to express emotions. J Counsel Educ. 2012; 1(4), 39-54. [Link]
23. Alavi SS, Maracy MR, Jannatifard F, Eslami M. The effect of psychiatric symptoms on the internet addiction disorder in Isfahan's University students. J Res Med Sci. 2011; 17(2):57-65. [PMID] [PMCID]
24. Canan F, Ataoglu A, Ozcetin A, Icmeli C. The association between internet addiction and dissociation among Turkish college students. Compr Psychiatry. 2012; 53(5):422-6. [DOI:10.1016/j.comppsych.2011.08.006] [PMID]
25. Hosseini Beheshtian SM. [The relationship between addiction to internet and personality characteristics among university students in tehran (Persian)]. Sociol cult stud. 2012; 3(1):79-96. [Link]
26. Kiany T, Fallahi Khoshknab M, Dalvandi A, Hosaini MA, Nourozi K. [Internet addiction and its related factors among nursing students in Tehran University of Medical Sciences in 2013 (Persian)]. J Nurs Educ. 2014; 2(4):50-62. [Link]
27. Tsai CC, Lin SS. Analysis of attitude toward computer networks and internet addiction of Taiwanese adolescents. Cyberpsychol Behav 2001; 4(3):373-6. [DOI:10.1089/109493101300210277] [PMID]
28. Sepehrian F, Jokar L. [The relationship of internet addiction with anxiety in A&B personality types (Persian)]. Res Cogn Behav Sci. 2013; 2(2):17-30. [Link]
29. Al-Hantoushi M, Al-Abdullateef S. Internet addiction among secondary school students in Riyadh city, its prevalence, correlates and relation to depression: A questionnaire survey. Int J Med Sci Public Health. 2014; 3(1):10-5. [DOI:10.5455/ijmsph.2013.130920131]