BACKGROUND: The Internet is a widely used tool known to foster addictive behavior, and Internet addiction threatens to develop into a major public health issue in the near future in a rapidly developing country like India. OBJECTIVE: This cross-sectional study intends to estimate prevalence, understand patterns, and evaluate risk factors for Internet addiction among college students in the city of Bengaluru, India. MATERIALS AND METHODS: Out of a total of 554 data samples from eight colleges selected through multistage cluster sampling, 515 samples were analyzed. Young's 20-item Internet Addiction Test (IAT), an inventory including demographic factors and patterns of internet use, was administered. RESULTS: This study of college students aged 16-26 years (mean ± SD 19.2 ± 2.4 years), with marginally high female representation (56%), identified 34% [95% confidence interval (CI) 29.91-38.09%] and 8% (95%, CI 5.97-10.63%) as students with mild and moderate Internet addiction respectively. Binary logistic regression found Internet addiction to be associated with male gender [adjusted odds ratio (AOR) 1.69, 95% CI, 1.081- 2.65, P = 0.021], continuous availability online (AOR 1.724, 95% CI, 1.018-2.923, P = 0.042), using the Internet less for coursework/assignments (AOR 0.415, 95% CI, 0.263-0.655, P < 0.001), making new friendships online (AOR 1.721, 95% CI, 1.785-2.849, P = 0.034), getting into relationships online (AOR 2.283, 95% CI, 1.424-3.663, P = 0.001). CONCLUSION: The results highlight the vulnerability of college students to Internet addiction. The findings provide explanations on the addictive behavior of the internet users, support the inclusion of "Internet Addiction" in the DSM-VI, and open up new paths for further research.
BACKGROUND: The Internet is a widely used tool known to foster addictive behavior, and Internet addiction threatens to develop into a major public health issue in the near future in a rapidly developing country like India. OBJECTIVE: This cross-sectional study intends to estimate prevalence, understand patterns, and evaluate risk factors for Internet addiction among college students in the city of Bengaluru, India. MATERIALS AND METHODS: Out of a total of 554 data samples from eight colleges selected through multistage cluster sampling, 515 samples were analyzed. Young's 20-item Internet Addiction Test (IAT), an inventory including demographic factors and patterns of internet use, was administered. RESULTS: This study of college students aged 16-26 years (mean ± SD 19.2 ± 2.4 years), with marginally high female representation (56%), identified 34% [95% confidence interval (CI) 29.91-38.09%] and 8% (95%, CI 5.97-10.63%) as students with mild and moderate Internet addiction respectively. Binary logistic regression found Internet addiction to be associated with male gender [adjusted odds ratio (AOR) 1.69, 95% CI, 1.081- 2.65, P = 0.021], continuous availability online (AOR 1.724, 95% CI, 1.018-2.923, P = 0.042), using the Internet less for coursework/assignments (AOR 0.415, 95% CI, 0.263-0.655, P < 0.001), making new friendships online (AOR 1.721, 95% CI, 1.785-2.849, P = 0.034), getting into relationships online (AOR 2.283, 95% CI, 1.424-3.663, P = 0.001). CONCLUSION: The results highlight the vulnerability of college students to Internet addiction. The findings provide explanations on the addictive behavior of the internet users, support the inclusion of "Internet Addiction" in the DSM-VI, and open up new paths for further research.
Authors: Nitin Anand; Praveen A Jain; Santosh Prabhu; Christofer Thomas; Aneesh Bhat; P V Prathyusha; Shrinivasa U Bhat; Kimberly Young; Anish V Cherian Journal: Ind Psychiatry J Date: 2018 Jan-Jun
Authors: Bach Xuan Tran; Hue Thi Mai; Long Hoang Nguyen; Cuong Tat Nguyen; Carl A Latkin; Melvyn W B Zhang; Roger C M Ho Journal: Addict Behav Rep Date: 2017-07-08