The Effect of Internet Addiction in Students on Quality of School Life

Abstract

Aim: Internet addiction in children is a mental disorder that negatively affects the quality of life. In this day and age, internet usage, and school life, which takes a significant amount of time for students, are specified as engaged concepts that affect each other. Therefore, this study has been addressed to investigate the effects of internet addiction on primary, middle, and high school students on school life quality. Material and Method: This research was conducted as a questionnaire study by Dr. Sami Ulus Training and Research Hospital Pediatric Neurology in the 2018-2019 academic year for Primary School, Middle, and High School students. The questionnaire consisted of sociodemographic information, Internet Addiction Scale (IAS), and Quality of School Life Scale (QSLS). Results: Seven hundred eighty-eight students were included in the study. Mean age was 12.94 ± 2.79 years (range 8 - 17). Internet addiction scores were 57.67 ± 20.63, and 106 (13.80%) children had internet addiction. The Quality of School Life Scale total scores were found as 112.65 ± 18.42. It was observed that school success and school life quality decreased as the internet addiction score increased. It was observed that the students' education and puzzle games compared to other websites caused lower IAS scores. The most significant differences were observed among high school students. While it was observed that IAS scores, internet addiction, family negative relationships, and exposure to violence rates were highest in high school students, QSLS scores, and course success were found below. Conclusion: There is a need to develop programs that would minimize the excessive and useless internet use of students and improve the environmental factors that regulate their relationships in the family, school, and other settings.

Keywords

• Internet Addiction
• Quality of School Life
• Children
• Student
• Internet tendency problems

Öğrencilerde İnternet Bağımlılığının Okul Yaşam Kalitesine Etkisi

Abstract

Amaç: Çocuklarda internet bağımlılığı yaşam kalitesini olumsuz etkileyen mental bir bozukluktur. Yaşam kalitesinin niteliğini en az mental ve fiziksel sağlık kadar okul performans ve akademik başarılar da etkilemektedir. Bu nedenle ilkokul, ortaokul ve lise öğrencilerin internet bağımlığının okul yaşam kalitesine etkilerinin araştırılması amacıyla bu çalışma ele alınmıştır. Gereç ve Yöntem: Dr. Sami Ulus Eğitim ve Araştırma Hastanesi Çocuk Nörolojisi tarafından 2018-2019 eğitim-öğretim yılında İlkokul, Ortaokul ve Lise öğrencilerine yönelik anket çalışması yapıldı. Çalışma gereçleri olarak sosyodemografik bilgiler formu, İnternet Bağımlılık Ölçeği (İBÖ) ve Okul Yaşam Kalitesi Ölçeği (OYKÖ) kullanıldı. Bulgular: Çalışmaya 788 öğrenci dahil edildi. Yaş ortalaması 12,94 ± 2,79 (8 -17) idi. İnternet bağımlılık skoru 57,67 ± 20,63 idi. Öğrencilerin %13,8(106)’inde internet bağımlılığı saptandı. Okul yaşam kalitesi ölçeği toplam puanları 112,65 ± 18,42 idi. İnternet bağımlılık skoru artıkça okul başarısının ve okul yaşam kalitesinin düştüğü görüldü. Eğitim amaçlı ve puzzle şeklinde oyun sitelerini ziyaret eden öğrenciler daha düşük internet bağımlılık skoruna sahip idi. En belirgin farklılıkların lise öğrencileri arasında olduğu saptandı. Lise öğrencilerinde internet bağımlılığı, ailevi olumsuz ilişkiler ve şiddete maruz kalma oranlarının en yüksek olduğu görülürken, okul yaşam kalitesi puanları ve ders başarısının düşük olduğu görülmüştür. Sonuç: Öğrencilerin aşırı ve faydasız internet kullanımını en aza indirecek, aile, okul ve diğer ortamlarda ilişkilerini düzenleyen çevresel faktörleri iyileştirecek programların geliştirilmesine ihtiyaç vardır.

Keywords

• İnternet Bağımlılığı
• Okul Yaşam Kalitesi
• Çocuk
• Öğrenci
• İnternet eğilim sorunları

References

1. 1. Canan F, Ataoglu A, Nichols LA, Yildirim T, Ozturk O. Evaluation of psychometric properties of the internet addiction scale in a sample of Turkish high school students. Cyberpsychol Behav Soc Netw 2010;13(3):317-20.
2. 2. Surís J-C, Akre C, Piguet C, Ambresin A-E, Zimmermann G, Berchtold A. Is Internet use unhealthy? A cross-sectional study of adolescent Internet overuse. Swiss Med Wkly 2014;144: w14061.
3. 3. Miniwatts M. World internet users statistics and 2019 world population stats. [accessed 2020-02-28]. Available from: https://www internetworldstats com/stats htm.
4. 4. Nuutinen T, Roos E, Ray C, Villberg J, Välimaa R, Rasmussen M, et al. Computer use, sleep duration and health symptoms: a cross-sectional study of 15-year olds in three countries. Int J Public Health. 2014;59(4):619-28.
5. 5. Association AP. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC; American Psychiatric Association. Developmental Considerations in Treatment. 1994.
6. 6. Huang C-H. Clinical and health psychology. Development and validation of a quality of life scale for elementary school students. Int J Clin Health Psychol 2017;17:180-91.
7. 7. Ravens-Sieberer U, Karow A, Barthel D, Klasen F. How to assess quality of life in child and adolescent psychiatry. Dialogues Clin Neurosci 2014;16(2):147-58. 8. Mok MMC. Determinants of students' quality of school life: A path model. Learn Environ Res 2002;5:275-300.
8. 9. Kindt S, Szász-Janocha C, Rehbein F, Lindenberg K. School-related risk factors of internet use disorders. Int J Environ Res Public Health 2019;16(24):4938.

9. 10. Nichols LA, Nicki R. Development of a psychometrically sound internet addiction scale: A preliminary step. Psychol Addict Behav. 2004;18(4):381-4.
10. 11. Houben-van Herten M, Bai G, Hafkamp E, Landgraf JM, Raat H. Determinants of health-related quality of life in school-aged children: a general population study in the Netherlands. PLoS One 2015;10(5):e0125083. DOI: 10.1371/journal.pone.0125083.
11. 12. Simões C, Santos S, Biscaia R. Validation of the Portuguese version of the Personal Outcomes Scale. Int J Clin Health Psychol 2016;16(2):186-200.
12. 13. Sari M. Assessment of school life: reliability and validity of quality of school life scale. Hacettepe University Journal of Education 2012;42:344-55.
13. 14. Carbonell X, Chamarro A, Oberst U, Rodrigo B, Prades M. Problematic use of the internet and smartphones in university students: 2006–2017. Int J Environ Res Public Health 2018;15(3):475.
14. 15. Cheng H, Treglown L, Green A, Chapman BP, Κornilaki EN, Furnham A. Childhood onset of migraine, gender, parental social class, and trait neuroticism as predictors of the prevalence of migraine in adulthood. J Psychosom Res 2016;88:54-8.
15. 16. Tepecik Böyükbaş İ, Çıtak Kurt AN, Tural Hesapçıoğlu S, Uğurlu M. Relationship between headache and Internet addiction in children. Turk J Med Sci 2019;24;49(5):1292-1297.
16. 17. Şaşmaz T, Öner S, Kurt AÖ, Yapıcı G, Yazıcı AE, Buğdaycı R, et al. Prevalence and risk factors of Internet addiction in high school students. Eur J Public Health 2014;24(1):15-20.
17. 18. Caplan SE. Problematic Internet use and psychosocial well-being: development of a theory-based cognitive–behavioral measurement instrument. Comput Human Behav 2002;18(5):553-75.
18. 19. Canan F, Ataoglu A, Ozcetin A, Icmeli C. The association between Internet addiction and dissociation among Turkish college students. Compr Psychiatry 2012;53(5):422-26.
19. 20. Aktepe E, Olgaç-Dündar N, Soyöz Ö, Sönmez Y. Possible internet addiction in high school students in the city center of Isparta and associated factors: a cross-sectional study. Turk J Pediatr 2013;55(4):417-25.
20. 21. Lee S-J, Chae Y-G. Children's Internet use in a family context: Influence on family relationships and parental mediation. Cyberpsychol Behav 2007;10(5):640-44.
21. 22. Ghotra S, McIsaac J-LD, Kirk SF, Kuhle S. Validation of the “Quality of Life in School” instrument in Canadian elementary school students. PeerJ 2016;4:e1567. DOI: 10.7717/peerj.1567.
22. 23. Liberman LC, Altuzarra MP, Öst L-G, Ollendick T. How I feel about things: Psychometric data from a sample of Spanish-speaking children. Int J Clin Health Psychol 2012;12(3):419-33.
23. 24. Liberman LC, Larsson K, Altuzarra MP, Öst L-G, Ollendick T. Self-reported life satisfaction and response style differences among children in Chile and Sweden. J Child Fam Stud 2015;24(1):66-75.
24. 25. Park SK, Kim JY, Cho CB. Prevalence of Internet addiction and correlations with family factors among South Korean adolescents. Adolescence 2008;43(172): 895-909.
25. 26. Strittmatter E, Kaess M, Parzer P, Fischer G, Carli V, Hoven CW, et al. Pathological Internet use among adolescents: Comparing gamers and non-gamers. Psychiatry Res 2015;228(1):128-35.
26. 27. Cheng C, Li AY-l. Internet addiction prevalence and quality of (real) life: A meta-analysis of 31 nations across seven world regions. Cyberpsychol Behav Soc Netw 2014;17(12):755-60.
27. 28. Brunborg GS, Mentzoni RA, Frøyland LR. Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems? J Behav Addict 2014;3(1):27-32.
28. 29. Stavropoulos V, Alexandraki K, Motti-Stefanidi F. Recognizing internet addiction: prevalence and relationship to academic achievement in adolescents enrolled in urban and rural Greek high schools. J Adolesc 2013;36(3):565-76.
29. 30. Herrero Romero R, Hall J, Cluver L. Exposure to violence, teacher support, and school delay amongst adolescents in South Africa. Br J Educ Psychol 2019;89(1):1-21.