This was a preliminary survey to evaluate the Internet addiction and impact of Internet use in a purposive Indian sample. In the present study, more male subjects were addicted to the Internet compared with their female counterparts. Available data from the community and online surveys as well as clinical samples[33
] suggest that Internet addiction appears to have a male preponderance. In a Finnish study, men had significantly higher mean score on the Internet Addiction Test (IAT) than did women.[39
] A study that included adolescents revealed 50% increased odds for males to be addicted to the Internet (OR=1.5, 95% CI=1.1–2.2) when compared with females.[40
] It is suggested that the gender distribution may be explained by the fact that men are more likely to express interest in games, pornography, and gambling activities that have all been associated with problematic Internet use.[33
Studies have found that the Internet addiction usually manifests itself in the late 20s or early 30s.[41
] The mean age (27.73±5.14 years) of the subjects in the index study also support the same. Black et al
] reported a lag time of 11 years from the initial use to the problematic use. Other studies have also reported a 3-year history of problematic use at the time of interview.[41
] Subjects in the present study had a lag period of approximately 6 years (73.43±44.51 months) from the initial computer use to the index assessment for Internet addiction, which is in the range of that reported in the other studies.[41
] Subjects in the present study used Internet for 2.13 h/day, which translates into 14.91 h/week, which is lower compared with that reported by other studies.[9
In the index study the most commonly endorsed items on Internet use questionnaire were the need to use the Internet everyday (53.8%), Internet use helping to overcome bad moods (50%), staying online longer than one originally intends to (43.3%), eating while surfing (24%), physical activity going down since one has started using the Internet (22.1%), using Internet to escape from problems (18.3%), becoming upset on attempting to cut down Internet use (17.3%), surfing being responsible for spending less time with family members (16.3%), surfing causing a change in sleep pattern (16.3%), and so on. Previous studies from other countries have also reported similar positive and negative impact of Internet use as found by us.[25
] A study from India too reported that those who were dependent on Internet would delay their work to spend time online, lose sleep due to logging in till late night, feel lonelier, and feel life would be boring without the Internet as compared with nondependent subjects.[44
The studies that have estimated the prevalence of Internet addiction have come up with varying results (0.9-38%) depending on the criteria used and the sample studied.[34
] In a methodologically rigorous study that involved a random telephone survey of 2513 adults aged 18 years and older and employed four criteria sets, prevalence rates varied from 0.3 to 0.7%.[13
] The only published study from India, which evaluated Internet addiction by using Davis Online Cognition Scale in school-going children aged 16-18 years, reported a prevalence of 18%.[44
The reasons for huge variation in the prevalence rates could be as follows: difficulty in conceptualizing Internet addiction, heterogeneity of population studied, lack of availability of standard diagnostic criteria, studies failing to differentiate between essential and nonessential Internet use, and nonconsideration of psychiatric comorbidity in some of the studies.[13
] More surprisingly, the studies that have used Young's IAT have also come up with varied prevalence rates. This suggests that a single instrument cannot reliably pick up the cases of Internet addiction. Another fact that contributes to a wide variation in the prevalence rates is the fact that Internet addiction has been viewed from different theoretical perspectives such as an impulse control disorder, obsessive compulsive disorder, and substance use disorder.[16
] However, there is very little agreement between these on the crucial components and dimensions of Internet addiction. In the present study, the prevalence rate of 51.9% as per ICD-10 substance dependence criteria seems to be overinflated whereas the prevalence of 3.8% as per IADQ is probably an underestimate, although both the figures are very near to range reported in the literature.
This wide variation suggests that some conceptual issues have to be addressed before we even plan to define Internet addiction and estimate its prevalence. For example, are we going to diagnose Internet addiction in people who are compelled to use Internet for prolonged periods of time because of the nature of their occupation? What about people who are logged on to Internet all the time just checking their mails intermittently? Should it be appropriate to diagnose Internet addiction in a job seeker or a researcher who try to keep abreast of the recent developments by logging on to the Internet? What about people who use Internet as a medium of sexual gratification? Sexual compulsion may be a more appropriate diagnosis in such cases. The Internet, like mobile phones and other electronic gadgets, has become a part and parcel of modern life. An in-depth interview of the subject, with corroboration of history from the family members, might be a more reasonable approach to diagnose Internet addiction. A diagnostic questionnaire at best can serve as a screening instrument to detect the population at risk of Internet addiction rather than identifying the persons having full blown disorder.
The findings of the present study must be considered within its limitations. The sample size was small and the sampling was nonrandom. No face-to-face interview was conducted to explore the phenomenology of Internet addiction; data were exclusively gathered by the self-reporting Internet use questionnaire. The instrument used in the index study has not been validated. Items were generated from various questionnaires developed to identify Internet addiction and some items were constructed keeping the ICD-10 criteria of substance dependence in mind. It can be argued that ICD-10 dependence criteria are developed for psychoactive substance dependence and hence cannot be applied to those substance-neutral behaviors commonly performed in daily life. Thus, the item for assessing the criterion craving (item 1: Do you feel the need to use the Internet everyday?) would easily capture the work-related Internet users for whom daily Internet use is essential. The questionnaire is self-administered and thus the authors cannot clarify the meaning of such items. That is why more than 50% of the subjects replied ‘Yes’. However, when the hardcore physical dependence features, i.e., tolerance and withdrawal, are concerned, only about 15% of subjects fulfill such criteria. As mentioned earlier, this study did not differentiate between essential and nonessential Internet use. The issue of the presence of psychiatric comorbidity in the subjects was also not considered.
Nevertheless, in view of the current ongoing debate on Internet addiction after its inclusion in the proposal draft of DSM-V, this study from India could provide some insights into the impact of Internet use and, more importantly, the issues facing the delineation of a syndrome of ‘Internet addiction’. The sharp difference in the prevalence estimates of Internet addiction depending on the type of criteria used shows the fragility of the construct of Internet addiction. This study should not be cited as a usual ‘prevalence’ study of a particular disorder, because of both sampling issues and methodological issues as mentioned. Moreover, the issue of whom to treat and whom not to still remains open. Before embarking on any kind of major manipulation to the diagnostic system, a through understanding of the concept of Internet addiction is required. This study brings into focus some of these conceptual and methodological issues that must be debated before any decisive action in this regard is taken.