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The Scientific World Journal
Volume 2012, Article ID 104304, 9 pages
http://dx.doi.org/10.1100/2012/104304
Research Article

Internet Addiction Phenomenon in Early Adolescents in Hong Kong

Daniel T. L. Shek1,2,3,4,5 and Lu Yu1

1Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong
2Public Policy Research Institute, The Hong Kong Polytechnic University, Hong Kong
3Department of Social Work, East China Normal University, Shanghai 200241, China
4Kiang Wu Nursing College of Macau, Macau
5Division of Adolescent Medicine, Department of Pediatrics, Kentucky Children's Hospital, University of Kentucky College of Medicine, Lexington, KY 40506, USA

Received 2 October 2011; Accepted 8 November 2011

Academic Editor: Joav Merrick

Copyright © 2012 Daniel T. L. Shek and Lu Yu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present study investigated the prevalence and demographic correlates of Internet addiction in Hong Kong adolescents as well as the change in related behavior at two time points over a one-year interval. Two waves of data were collected from a large sample of students (Wave 1: 3,328 students, age = 1 2 . 5 9 ± 0 . 7 4 years; Wave 2: 3,580 students, age = 1 3 . 5 0 ± 0 . 7 5 years) at 28 secondary schools in Hong Kong. Comparable to findings at Wave 1 (26.4%), 26.7% of the participants met the criterion of Internet addiction at Wave 2 as measured by Young’s 10-item Internet Addiction Test. The behavioral pattern of Internet addiction was basically stable over time. While the predictive effects of demographic variables including age, gender, family economic status, and immigration status were not significant, Internet addictive behaviors at Wave 1 significantly predicted similar behaviors at Wave 2. Students who met the criterion of Internet addiction at Wave 1 were 7.55 times more likely than other students to be classified as Internet addicts at Wave 2. These results suggest that early detection and intervention for Internet addiction should be carried out.