Published February 2, 2023 | Version v1

Prevalence, Pattern and Risk Factors of Internet Addiction among adolescents

  • 1. Assistant Professor, College of Nursing, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
  • 2. Professor & Principal, The Salvation Army Catherine Booth College of Nursing, Nagercoil, Tamil Nadu, India
  • 3. Student, The Salvation Army Catherine Booth College of Nursing, Nagercoil, Tamil Nadu, India

Description

Adolescence is a crucial period in one’s life. In this stage, the usage of internet is very common. Research and other advances in internet addiction have led a safe and effective means of maintaining mental health. A descriptive cross-sectional study was conducted to assess the prevalence, pattern and risk factors of internet addiction among adolescents studying in a selected school at Kanyakumari District, South India. A total of 150 adolescents were selected to assess the level of internet addiction using Young’s internet addiction test. The result showed that nearly half (41%) of the adolescents were not addicted to internet, whereas more than one third (26%) of adolescents were mildly addicted. There was a statistically significant association between internet addiction and selected demographic varibles such as age (0.03), occupation of the mother (0.003), number of siblings (0.005), and religion (0.00001), gender (0.00001). On the basis of the study findings, it was concluded that socio demographic variables were directly influence the usage of internet among adolescents.

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References

  • 1. Yang, S. C., & Tung, C. J. (2007). Comparison of Internet addicts and non-addicts in Taiwanese high school. Computers in human behavior, 23(1), 79-96.
  • 2. Anderson, K. J. (2001). Internet use among college students: An exploratory study. Journal of American College Health, 50(1), 21-26.
  • 3. Srijampana, V. V. G. R., Endreddy, A. R., Prabhath, K., & Rajana, B. (2014). Prevalence and patterns of internet addiction among medical students. Medical Journal of Dr. DY Patil University, 7(6), 709.
  • 4. Gauzente, C. (2013). An illustrated invitation to use Q-method in IS Research. Systèmes d'Information et Management (French Journal of Management Information Systems), 18(2), 69-109.
  • 5. Kocsis, R. N. (2013). Book review: diagnostic and statistical manual of mental disorders: (DSM-5).
  • 6. Srijampana, V. V. G. R., Endreddy, A. R., Prabhath, K., & Rajana, B. (2014). Prevalence and patterns of internet addiction among medical students. Medical Journal of Dr. DY Patil University, 7(6), 709.
  • 7. Chang, F. C., Chiu, C. H., Chen, P. H., Chiang, J. T., Miao, N. F., Chuang, H. Y., & Liu, S. (2019). Children's use of mobile devices, smartphone addiction and parental mediation in Taiwan. Computers in Human Behavior, 93, 25-32.
  • 8. Şaşmaz, T., Öner, S., Kurt, A. Ö., Yapıcı, G., Yazıcı, A. E., Buğdaycı, R., & Şiş, M. (2014). Prevalence and risk factors of Internet addiction in high school students. The European Journal of Public Health, 24(1), 15-20.