To Estimate the Prevalence of Internet Addiction and Comorbidities Among School Going Adolescents

Authors

  • Dheeraj Saini PG Resident, Department of Pediatrics, Mahatma Gandhi University of Medical Sciences & Technology, Jaipur, Rajasthan, India
  • Yashu Saini Professor, Department of Pediatrics, Mahatma Gandhi University of Medical Sciences & Technology, Jaipur, Rajasthan, India
  • Abhishek Saini Associate Professor, Department of Pediatrics, Mahatma Gandhi University of Medical Sciences & Technology, Jaipur, Rajasthan, India
  • Jitendra Kumar Gupta Professor, Department of Pediatrics, Mahatma Gandhi University of Medical Sciences & Technology, Jaipur, Rajasthan, India
  • Rupesh Masand Professor & Head, Department of Pediatrics, Mahatma Gandhi University of Medical Sciences & Technology, Jaipur, Rajasthan, India

Abstract

Background: The digital revolution has fundamentally transformed adolescent behavior patterns, with Internet addiction emerging as a significant concern. Despite extensive research, considerable debate exists regarding its conceptualization and measurement, particularly among adolescents in developing nations. This study aimed to estimate the prevalence of Internet addiction and associated comorbidities among school-going adolescents aged 10-18 years. Methodology: A cross-sectional study was conducted among 340 adolescents from rural and urban schools in Jaipur district using purposive sampling. Data collection employed validated instruments including the Chen Internet Addiction Scale (CIAS), Hamilton Depression Rating Scale (HDRS) and Hamilton Anxiety Rating Scale (HAM-A). Statistical analysis was performed using SPSS version 20, with chi-square tests and Pearson correlation analysis. Results: The study revealed significant Internet addiction patterns with 26.2% showing normal usage, 17.4% mild addiction, 36.5% moderate addiction and 20.0% severe addiction. Residential area (p=0.021) and school category (p=0.042) were significantly associated with Internet addiction levels. Depression was prevalent with 47.9% showing moderate and 32.1% severe depression. Anxiety affected 49.4% moderately and 20.6% severely. A significant positive correlation existed between Internet addiction and depression (r=0.233, p<0.01), while the correlation with anxiety was weaker (r=0.086, p=0.114). Conclusion: Internet addiction is highly prevalent among adolescents with significant associations with depression and anxiety. Urban residence, private schooling and increased screen time emerged as key risk factors. The findings emphasize the urgent need for comprehensive screening protocols and targeted interventions addressing both technological behavior and mental health outcomes.

Keywords:

Internet Addiction, Adolescents, Depression, Anxiety, Prevalence, Mental Health, Digital Behavior

References

1. Papacharissi Z, Rubin AM. Predictors of Internet use. J Broadcasting Electron Med 2000;44:175-96.

2. Griffiths M. Does internet and computer "addiction" exist? Some case study evidence. CyberpsycholBehav 2000;3:211-8.

3. Swaminath G. Internet addiction disorder: Fact or Fad? Nosing into nosology. Indian J Psychiatry 2008;50:158-60.

4. Young KS, Rogers RC. The relationship between depression and internet addiction. CyberpsycholBehav 1998;1:25-8.

5. Young KS. Internet addiction: The emergence of a new clinical disorder. CyberpsycholBehav 1996;1:237-44.

6. Block JJ. Issues for DSM-V: Internet addiction. Am J Psychiatry 2008;165:306-7.

7. American Psychiatric Association. The Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Arlington. American Psychiatric Publishing; 2013.

8. Christakis DA. Internet addiction: A 21st century epidemic? BMC Med 2010;8:61.

9. Poli R. Internet addiction update: Diagnostic criteria, assessment and prevalence. Neuropsychiatry 2017;7:04-8.

10. Balhara YP, Mahapatra A, Sharma P, Bhargava R. Problematic internet use among students in South-East Asia: Current state of evidence. Indian J Public Health 2018;62:197-210.

11. Grover S, Chakraborty K, Basu D. Pattern of Internet use among professionals in India: Critical look at a surprising survey result. IndPsychiatry J 2010;19:94-100.

12. Parkash V, Basu D, Grover S. Internet addiction: Do two diagnostic criteria measure the same thing? Indian J Soc Psychiatry 2015;31:47-54.

13. Johansson A, Götestam KG. Internet addiction: characteristics of a questionnaire and prevalence in Norwegian youth (12–18 years). Scandinavian journal of psychology. 2004 Jul;45(3):223-9.

14. Ha JH, Yoo HJ, Cho IH, Chin B, Shin D, Kim JH. Psychiatric comorbidity assessed in Korean children and adolescents who screen positive for Internet addiction. Journal of Clinical Psychiatry. 2006 May 15;67(5):821.

15. Ramezani M, Salehi M, Namiranian N, Salehi M. Validity and reliability of the Chen internet addiction scale. J FundamMent Health. 2012;14(3):236-45.

16. Thompson E. Hamilton rating scale for anxiety (HAM-A). Occupational Medicine. 2015 Oct 1;65(7):601.

17. Hamilton M. A rating scale for depression. Journal of neurology, neurosurgery, and psychiatry. 1960 Feb;23(1):56.

18. Kawabe K, Horiuchi F, Ochi M, Oka Y, Ueno SI. Internet addiction: Prevalence and relation with mental states in adolescents. Psychiatry and clinical neurosciences. 2016 Sep;70(9):405-12.

19. Vigna-Taglianti F, Brambilla R, Priotto B, Angelino R, Cuomo G, Diecidue R. Problematic internet use among high school students: Prevalence, associated factors and gender differences. Psychiatry research. 2017 Nov 1;257:163-71.

20. Seyrek S, Cop E, Sinir H, Ugurlu M, Şenel S. Factors associated with Internet addiction: Cross-sectional study of Turkish adolescents. Pediatrics international. 2017 Feb;59(2):218-22.

21. Xin M, Xing J, Pengfei W, Houru L, Mengcheng W, Hong Z. Online activities, prevalence of Internet addiction and risk factors related to family and school among adolescents in China. Addictive behaviors reports. 2018 Jun 1;7:14-8.

22. Prabhakaran MA, Patel VR, Ganjiwale DJ, Nimbalkar MS. Factors associated with internet addiction among school-going adolescents in Vadodara. Journal of family medicine and primary care. 2016 Oct 1;5(4):765-9.

23. Tsitsika A, Critselis E, Louizou A, Janikian M, Freskou A, Marangou E, Kormas G, Kafetzis DA. Determinants of Internet addiction among adolescents: A case-control study. The Scientific World Journal. 2011;11(1):866-74.

24. Tang J, Yu Y, Du Y, Ma Y, Zhang D, Wang J. Prevalence of internet addiction and its association with stressful life events and psychological symptoms among adolescent internet users. Addictive behaviors. 2014 Mar 1;39(3):744-7.

25. Afolabi AA, Ilesanmi OS, Adebayo AM. Prevalence and pattern of internet addiction among adolescents in Ibadan, Nigeria: a cross-sectional study. Cureus. 2022 Feb;14(2).

26. Tereshchenko S, Kasparov E, Smolnikova M,Shubina M, Gorbacheva N, Moskalenko Ο. Internet addiction and sleep problems among Russian adolescents: a field school-based study. International Journal of Environmental Research and Public Health. 2021 Oct 2;18(19):10397.

27. Kavici S, Ayaz-Alkaya S. Internet addiction, social anxiety and body mass index in adolescents: A predictive correlational design. Children and Youth Services Review. 2024 May 1;160:107590.

28. Mohamed NF, Jiun Ting T, Ab Manan N, MohdSenari IF, Muhammad Firdaus Chan MF, Rahmatullah B, Govindasamy P, Abdulla K. Prevalence and predictors of social anxiety disorders among Malaysian secondary school students during the COVID-19 pandemic: Exploring the influence of internet gaming disorder and impulsivity. Clinical Child Psychology and Psychiatry. 2024 Jan 1:13591045231206967.

29. Zhao M, Huang Y, Wang J, Feng J, Zhou B. Internet addiction and depression among Chinese adolescents: anxiety as a mediator and social support as a moderator. Psychology, Health & Medicine. 2023 Sep 14;28(8):2315-28.

30. Tang J, Ma Y, Lewis SP, Chen R, Clifford A, Ammerman BA, Gazimbi MM, Byrne A, Wu Y, Lu X, Chang H. Association of internet addiction with nonsuicidal self-injury among adolescents in China. JAMA network open. 2020 Jun 1;3(6):e206863-.

31. Shen Y, Wang L, Huang C, Guo J, De Leon SA, Lu J, Luo X, Zhang XY. Sex differences in prevalence, risk factors and clinical correlates of internet addiction among Chinese college students. Journal of affective disorders. 2021 Jan 15;279:680-6.

32. Tao Y, Wang S, Ma Z, Zhang L, Liu X. The effect of long-term online learning on anxiety, depression, and internet addiction among secondary school students: insight from a cross-lagged panel network approach. Current Psychology. 2024 Sep;43(35):28613-24.

33. de Ávila GB, Dos Santos ÉN, Jansen K, Barros FC. Internet addiction in students from an educational institution in Southern Brazil: prevalence and associated factors. Trends in psychiatry and psychotherapy. 2020 Jun 5:42:302-10.

34. Lai CM, Mak KK, Watanabe H, Jeong J, Kim D, Bahar N, Ramos M, Chen SH, Cheng C. The mediating role of Internet addiction in depression, social anxiety, and psychosocial well-being among adolescents in six Asian countries: a structural equation modelling approach. Public health. 2015 Sep 1;129(9):1224-36.

35. Narayanappa PH, Nirgude AS, Nattala P, Philip M. Does psychoeducation module-based community intervention address Internet addiction among school-going adolescents? A quasi-experimental study from Mangalore, India. Journal of Family Medicine and Primary Care. 2024 Oct 1;13(10):4237-43.

36. Rajan RE, Gunasekaran S, Duraisamy V, Mathew BM, Vinolia TM, Gainneos PD. Internet gaming disorder: The prevalence and associated gaming behavior, anxiety, and depression among 8-12-year-old children of private schools in Salem city, India. Journal of Indian Society of Pedodontics and Preventive Dentistry. 2024 Apr 1;42(2):98-103.

Published

2025-09-20
Statistics
Abstract Display: 0
PDF Downloads: 0

Issue

Vol. 16 No. 9 (2025): Volume16,Issue9

Section

Articles