Examining the Relationship between Adolescence Problems and Computer (Computer, Internet, Game) Addiction with Canonic Correlation Analysis in Turkish Generation K Adolescents: Ordu Province Center (Altinordu) Example

Year 2023, Volume: 7 Issue: 1, 81 - 91, 28.04.2023

Nevin Günaydın Yeliz Kaşko Arıcı

https://doi.org/10.29058/mjwbs.1098894

Abstract

Aim: This study was conducted to examine the relationship between computer addiction (computer,
internet, game addiction) and adolescent problems in Turkish generation K adolescents with correlation
analysis.
Material and Methods: This study is a cross-sectional study. This research was carried out in three
high schools in the city center of a city selected according to their success ranking in the high school
entrance exam. In the study, a total of 665 students who received parental and student permission were
included. Adolescents’ Computer (computer/internet/game) Addiction Scale and Adolescence Problems
Scanning List were used to gathering data. In the study, subscales of computer addiction scale for
adolescence (computer, internet, game) were determined as Set 1, and subscales of adolescence
problems scanning list (physical, social, relationship with the opposite sex and sexual information,
psychological, future expectations) were determined as Set 2. Expected relationships between these
Set 1 and Set 2 explained in an efficient manner by canonical weights and loadings.
Results: Three canonical variate pairs were ranging from 0.688 to 0.150. It was observed that the
first and the second pairs were significant (p<0.001). In the Adolescents’ Computer Addiction Scale,
computer game addiction was the most significant parameter (1.064). In order to obtain high value for
U1 canonical variate, while game addiction should be increased because of positively correlated, CA
should be shrunk because of negatively correlated. Therefore, when the game addiction subscale is
high and the computer and internet addiction subscales are low, it is expected that the psychological
and social problems subscales will take high values. In the adolescence problems scanning list,
psychological development problems were the most significant parameters (0.702). The value for
V1 canonical variate increases with the increase of psychological development problems and social
development problems. In contrast, the increase in the physical development problems reduces the
value of the V1 canonical variable.
Conclusion: Present data revealed that there were positive and moderate correlations between
computer addiction and adolescence problems of generation K. Canonical correlation analysis showed that the adolescence problems had a significant variance in explaining the adolescent’s computer (computer/internet/game) addiction, while
the adolescent’s computer addiction had significant variance in explaining the adolescence problems.

Keywords

computer addiction, internet addiction, game addiction, adolescence problems, canonical correlation, K generation adolescents

Supporting Institution

oRDU Unıversıty Scientific Research Projects Unit

Project Number

ar-1406

Thanks

The authors would like to thank the Scientific Research Projects Coordination Unit of the University and the adolescents who gave their time to participate in this study as well as the administrators of the schools

Türk K Kuşağı Ergenlerinde Ergenlik Sorunları ile Bilgisayar (Bilgisayar, İnternet, Oyun) Bağımlılığı Arasındaki İlişkinin Kanonik Korelasyon Analizi ile İncelenmesi: Ordu İl Merkez (Altınordu) Örneği

Abstract

Amaç: Bu çalışma, Türk K kuşağı ergenlerinde bilgisayar bağımlılığı (bilgisayar, internet, oyun bağımlılığı) ile ergen sorunları arasındaki
ilişkiyi korelasyon analizi ile incelemek amacıyla yapılmıştır.
Gereç ve Yöntemler: Bu çalışma kesitsel bir çalışmadır. Bu araştırma, lise giriş sınavı başarı sıralamasına göre seçilen bir il merkezindeki
üç lisede gerçekleştirilmiştir. Araştırmada veli ve öğrenci izni alınan toplam 665 öğrenci çalışmaya dahil edilmiştir. Veri toplamak için Ergen
Bilgisayar (bilgisayar/internet/oyun) Bağımlılığı Ölçeği ve Ergenlik Sorunları Tarama Listesi kullanılmıştır. Çalışmada ergenler için bilgisayar
bağımlılığı ölçeğinin alt ölçekleri (bilgisayar, internet, oyun) Set 1 olarak belirlenmiş ve ergenlik sorunları tarama listesi (fiziksel, sosyal, karşı
cinsle ilişki ve cinsel bilgiler, psikolojik, gelecek beklentileri) alt ölçekleri Set 2 olarak belirlenmiştir. Bu Set 1 ve Set 2 arasındaki beklenen
ilişkiler kanonik ağırlıklar ve yüklemeler ile etkin bir şekilde açıklanmıştır.
Bulgular: Çalışmada, 0,688 ile 0,150 arasında değişen üç kanonik değişken çifti vardı. Birinci ve ikinci çiftlerin anlamlı olduğu gözlendi
(p<0,001). Ergenlerin Bilgisayar Bağımlılığı Ölçeğinde bilgisayar oyunu bağımlılığı en önemli parametredir (1,064). U1 kanonik değişkeninin
yüksek değer elde etmesi için pozitif korelasyon nedeniyle oyun bağımlılığının arttırılması, negatif korelasyon nedeniyle CA’nın küçültülmesi
gerekmektedir. Dolayısıyla, oyun bağımlılığı alt ölçeği yüksek olduğunda, bilgisayar ve internet bağımlılığı alt ölçekleri ise düşük olduğunda
psikolojik ve sosyal problemler alt ölçeklerinin yüksek değerler alması beklenmektedir. Ergenlik sorunları tarama listesinde psikolojik gelişim
sorunları, en önemli parametre (0,702) idi. V1 kanonik değişkeninin değeri, psikolojik gelişim sorunları ve sosyal gelişim sorunları arttıkça
artmaktadır. Buna karşılık fiziksel gelişim problemlerindeki artış V1 kanonik değişkeninin değerini düşürmektedir.
Sonuç: Mevcut veriler, bilgisayar bağımlılığı ile K kuşağı ergenlerinin ergenlik sorunları arasında pozitif ve orta düzeyde ilişki olduğunu
ortaya koymuştur. Kanonik korelasyon analizi, ergenlik sorunlarının ergenin bilgisayar (bilgisayar/internet/oyun) bağımlılığını açıklamada
önemli bir varyansa sahip olduğunu, ergenin bilgisayar bağımlılığının ise ergenlik sorunlarını açıklamada önemli bir varyansa sahip olduğunu
göstermiştir.

Keywords

bilgisayar bağımlılığı, internet bağımlılığı, oyun bağımlılığı, ergenlik problemleri, kanonik korelasyon, K kuşağı ergenleri

Project Number

ar-1406

References

• 1. James RJE, Tunney RJ. The relationship between gaming disorder and addiction requires a behavioral analysis. J Behav Addict 2017;6(3):306-309.
• 2. Costa S, Barberis N, Gugliandolo MC, Liga F, Cuzzocrea F, Verrastro V. Examination of the psychometric characteristics of the Italian version of the game addiction scale for adolescents. Psychol Rep 2020;123(4):1365-1381.
• 3. Ho RC, Zhang MW, Tsang TY, Toh AH, Pan F, Lu Y, Cheng C, Yip PS, Lam LT, Lai CM, Watanabe H, Mak KK. The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry 2014;14:183.
• 4. American Psychiatric Association (APA). Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Washington, DC: American Psychiatric Association; 2013.
• 5. Nadir Aykın, S, Caylan A. Adolescent, and young health monitoring. Türkiye Klinikleri J Fam Med-Special Topics 2013;4(5):70-77.
• 6. Onur B. Developmental psychology. İmge Bookstore Publications, Ankara, 2010
• 7. World Health Organization. (2017). Global accelerated action for the health of adolescents (AA-HA!): Guidance to support country implementation. https://apps.who.int/iris/bitstream/han dle/10665/255415/9789241512343-eng.pdf
• 8. UNICEF, 2019. Adolescent Demographics. Accessed: https:// data.unicef.org/topic/adolescents/demographics/ Accessed date: 20.12.2021
• 9. Li W, Garland EJ, Howard MO. Family factors in Internet addiction among Chinese youth: A review of English and Chinese-language studies. Comput Hum Behav 2014;31:393- 411.
• 10. Tran BX, Huong LT, Hinh ND, Nguyen LH, Le BN, Nong VM, Thuc VT, Tho TD, Latkin C, Zhang MW, Ho RC. A study on the influence of internet addiction and online interpersonal influences on health-related quality of life in young Vietnamese. BMC Public Health 2017;17(1):138.
• 11. OECD 2019. Children, Technology and Teaching. Helping our youngest to learn and grow: policies for early learning. https:// www.oecd-ilibrary.org/education/helping-our-youngest-tolearn- and-grow_f21353a9-en Accessed date: 15.10.2021
• 12. IWS (Internet World State) (2020). Top 20 countries in internet users rest of the world-June 30 2019 https://www. internetworldstats.com/top20.htm Accessed date: 02.04.2022
• 13. Ektiricioğlu C, Arslantaş H, Yüksel R. The disorder of the Era in adolescents: Technology addiction. Arch Med Rev J 2020;29 (1):51-64.
• 14. Özparlak A, Karakaya D. Familial factors associated with internet addiction in adolescents and nursing care. Turkiye Klinikleri J Nurs Sci 2020;12(2):291-299.
• 15. Otsuka Y, Kaneita Y, Itani O, Tokiya M. Relationship between internet addiction and poor mental health among Japanese adolescents. Iran J Public Health 2020;49(11):2069-2077.
• 16. Danovitch JH. Growing up with Google: How children’s understanding and use of internet-based devices relates to cognitive development. Hum Behav Emerg Technologies 2019;1:81-90.
• 17. Green CS, Bavelier D. Action video game modifies visual selective attention. Nature 2003;423(6939):534-537.
• 18. Sioni SR, Burleson MHM, Bekerian DA. Internet gaming disorder: Social phobia and identifying with your virtual self. Comput Hum Behav 2017;71:11-15.
• 19. Hertz N. Generation K: Who are they and what do we know about them?. 2015a https://womenintheworld.com/2015/04/21/ generation-k-who-are-they-and-what-do-we-know-about-them/ Accessed date: 10.11.2020
• 20. Hertz N What it means to be a teen?. 2015b. https://www. ft.com/content/1642f9d2-e3ac-11e4-9a82-00144feab7de Accessed date: 10.11.2020
• 21. Heilpern W. Here’s what you should know about ‘Generation K’ — the teens shaped by terrorism, technology, and anxiety. Business Insider. 2016 https://www.businessinsider.com/whatyou- need-to-know-about-generation-k-2016. Accessed date: 19.11.2021
• 22. Gray J. PLSA AC 18: How to engage “Generation K”. 2018. Available at: http://www.pensionsage.com/pa/PLSA-AC-18- How-to-engage-Generation-K.php. Accessed: 07.11.2020
• 23. Shandwick W. Generation-K. 2019 http://webershandwick. co.uk/wp-content/uploads/2014/01/GenK_Sellsheet_Talent. pdf Accessed: 08.11.2020.
• 24. Taylor R. Raising Generation K. 2016 https://blog.rakkoon. com/raising-generation-k/ Accessed: 08.11.2020
• 25. Király O, Griffiths MD, Urbán R, Farkas J, Kökönyei G, Elekes Z, Tamás D, Demetrovics Z. Problematic internet use and problematic online gaming are not the same: Findings from a large nationally representative adolescent sample. Cyberpsychol Behav Soc Netw 2014;17(12):749-754.
• 26. Pal B, Seal B. Multivariate relationships between physiologic and anthropometric variables: A data-based analysis. Int J Stat Probab 2014;3(2),30-45.
• 27. Sokal RR, Rohlf FJ. Biometry: The principles and practice of statistics in biological research. 3rd ed, San Francisco: WH Freeman;1995.
• 28. Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate Data Analysis, 5th edition. Englewood Cliffs, NJ: Prentice-Hall,1998.
• 29. Ayas T, Çakır Ö, Horzum MB. Computer addiction scale for adolescents. Kastamonu Educ J 2011;19(2):439-448.
• 30. Tekelioğlu FY. The Comparison of Adolescence Problems of Youth of the Same Age and the 13-17 Age Group Students Living in Orphanage and Their Families Living and Studying with Their Families. Master Thesis, Marmara University, Istanbul; 1993.
• 31. Birinci M, Ersoy Quadir S, Yaylacı Y, Özdemir CÇ, Şahan G. Investigation of social and psychological problems of adolescents in orphanage. J Soc Hum Sci 2020;12 (1):34-50.
• 32. Weiss DJ. Canonical correlation analysis in counseling psychology research. J Couns Psychol 1972;19(3):241-252.
• 33. Sharma S. Applied multivariate techniques. Willey, Canada. 1996:493.
• 34. Sheskin DJ. Handbook of Parametric and Nonparametric Statistical Procedures. Chapman&Hall/CRC, 2007.
• 35. Hardoon DR, Szedmak S, Shawe-Taylor J. Canonical correlation analysis: An overview with application to learning methods. Neural Comput 2004;16(12):2639-2664.
• 36. Tabachnick BG, Fidell LS. Using multivariate statistics. Boston: Pearson, 2015.
• 37. Tsigilis N. Personality traits and excessive computer and internet usage: A Robust Relation? Int J Soc Sci Res 2019;7(2):1-13.
• 38. Haşimoğlu A, Aslandoğan A. Adolescent problems and emotion of high school students examining the relationship between regulatory strategıis. ARHUSS 2018;1(2):71-83.
• 39. Gentile D, Choo H, Liau A, Sim T, Li D, Fung D, Khoo A. Pathological video game use among youths: A two-year longitudinal study. Pediatrics 2011;127(2):319-329.
• 40. Griffiths MD, Kuss DJ, Demetrovics Z. Social networking addiction: An overview of preliminary findings. Rosenberg K, Feder L (editor), Behavioral addictions: Criteria, evidence, and treatment. Elsevier Academic Press, 2014: 119-141.
• 41. Sallayıcı Z, Yöndem ZD. The Relationship between level of computer game addiction and behavioral problems in children. J Depend 2020;21(1):13-12.
• 42. Wölfling K, Thalemann R, Grüsser-Sinopoli SM. Computerspielsucht: ein psychopathologischer symptomkomplex im jugendalter [Computer game addiction: a psychopathological symptom complex in adolescence]. Psychiatr Prax 2008;35(5):226-232.
• 43. Esen E, Siyez DM. An investigation of psychosocial variables that predict internet addiction in adolescents. Tur J Psychol Couns Guidance 2011;4(36):127-138.
• 44. Taş İ. The examination of internet addiction and psychological symptoms among adolescents according to various variables. Journal of Social Sciences of Mus Alparslan University 2018;6(1):31-41.
• 45. 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.
• 46. Hazar Z, Hazar K, Gökyürek B, Hazar M, Çelikbilek S. Investigation of the relationship between playfulness, digital game addiction and aggression levels of secondary school students in terms of various variables. J Hum Sci 2017;14(4):4320-4332.
• 47. Dalbudak E, Evren C, Aldemir S, Evren B. The severity of Internet addiction risk and its relationship with the severity of borderline personality features, childhood traumas, dissociative experiences, depression, and anxiety symptoms among Turkish university students. Psychiatry Res 2014;219(3):577- 582.
• 48. Yıldırım S. Examining perceived value influence mobile game addiction: A case of Turkish young adults. In Leveraging Consumer Behavior and Psychology in the Digital Economy, IGI Global, 2020:133-152.
• 49. Kök Eren H, Örsal Ö. Computer game addiction and loneliness in children. J Public Health 2018;47(10):1504-1510.
• 50. Duygulu S. The effect of new media technologies on the communication of generation k with parents. TRT Acad 2018;3(6):632-653.
• 51. Andreassen CS, Pallesen S. Social network site addiction-An overview. Curr Pharm Des 2014;20(25):4053-4061.
• 52. Baloğlu M, Özteke Kozan Hİ, Kesici Ş. Gender differences in and the relationships between social anxiety and problematic internet use: Canonical analysis. J Med Internet Res 2018;20(1):e33.
• 53. Kawabe K, Horiuchi F, Oka Y, Ueno SI. Association between sleep habits and problems and internet addiction in adolescents. Psychiatry Invest 2019;16(8):581-587.
• 54. Muslu B, Bolışık B. Using the internet in children and adolescents. TAF Prev Med Bull 2009;8(5):445-450.
• 55. Mota J, Ribeiro J, Santos MP, Gomes H. Obesity, physical activity, computer use, and TV viewing in Portuguese adolescents. Pediatr Exerc Sci 2006;17:113-112.
• 56. Taşpınar M, Gümüş Ç. Environment and user profile of internet cafes in Turkey: evaluation of ınformation society. J Electron Soc Sci 2005;4(14):80-93.
• 57. Fradelo EC, Kourakos M, Velentza O, Polykandriotis T, Papathanasiou IV. Internet addiction in children and adolescents: Etiology, signs of recognition and implications in mental health nursing practice. Medrech 2016;264-272.