European Journal of Molecular & Clinical Medicine

Abstract

Introduction:
Internet addiction has become a 21st Century epidemic. To prevent and treat internet addiction, evaluation of current prevalence and its associated factors are needed.
Aim:
To find the prevalence and associated factors of internet addiction in Tamil Nadu.
Materials and methods:
Internet addiction severity was assessed by internet addiction scale (TN). A Semi structured questionnaire was used to collect associated factors. Statistical analysis was done and results were evaluated.
Results:
1367 people participated in this study. Among them 61.7% were male. Prevalence of mild, moderate and severe internet addiction were   57.6%, 29.8%, and 9.1% respectively.
Among gender, Prevalence of moderate and severe internet addiction in males were 31.3% and 10.3% respectively, and 27.3% and 7% respectively among females.
Considering age, Prevalence of moderate and severe internet addiction in less than 18 age group were 42.9% and 7.1%, and between 18 to 40 age group, these were 33.5% and 10.4% respectively. In the above 40 age group, the prevalence of moderate and severe addiction were 19.4% and 6.3% respectively.
Considering internet content, among facebook users, moderate and severe internet addiction were 36.1% and 11.4% respectively. In videogame players, moderate and severe internet addiction were 24% and 32% respectively. Among whatsapp users, moderate and severe internet addiction were 24.2% and 4%   respectively. And among youtube watchers moderate and severe internet addiction were 30.6% and 9.8% respectively.
Conclusions:
In general, Prevalence of problematic   internet addiction was 38.9% among which moderate and severe   internet addiction were   29.8% and 9.1% respectively.  Males were found to be more addicted . Internet addiction was found to decrease with increase in age.  Unmarried population were more addicted than married. Considering content, Videogames have the most addictive potential followed by facebook and youtube. Whatsapp users showed the least addiction. Age, sex, education, economy, marital status and content influence internet addiction.