Objective: The main aim of the current study was to test the psychometric properties of the Internet Gaming Disorder Scale (IGDS), both the long (27-item) and short (9-item) polytomous versions, which are survey instruments that measure Internet gaming disorder (IGD) on the basis of the 9 criteria from the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).
Method: Participants were evaluated by applying the 27-item IGDS and the Young’s Internet Addiction Test-Short Form (YIAT-SF). The psychometric properties of the IGDS were tested through an online survey completed by volunteers who are university students in Ankara, active Internet game players, as well as individuals who are in the e-mail database of an Istanbul-based company which organizes e-sports tournaments.
Results: A single component on the nine-item IGDS reached the criterion of an Eigenvalue greater than one (5.926), and the variance accounted for by this component was 65.85%. Confirmatory factor analyses demonstrated that the structural validity (i.e., the dimensional structure) of the nine-item IGDS was satisfactory. This short version of the scale was also reliable (i.e., internally consistent with Cronbach’s ? of 0.931) demonstrating good criterion-related validity, as indicated by positive correlations with time spent playing games, and the YIAT-SF score. Correlation between the 27-item IGDS and the nine-item IGDS was very high (n=457; r=0.988, p<0.001). Test-retest correlation for both the 27-item IGDS (n=261, r=0.759) and nine-item IGDS (n=261, r=0.756) were high. When the DSM-5 threshold for diagnosis (experiencing 5 or more criteria) was applied, the prevalence of disordered gamers ranged between 3.9% and 9.2%, according to the cutoff point chosen for each item.
Conclusion: The results of the validity and reliability testing of the Turkish version of the nine-item IGDS were found to be similar to the findings of the original scale. These findings support the Turkish versions of the nine-item IGDS, which measure a unidimensional construct as being valid and reliable IGD screening instrument in determining IGD which can become problematic among young adults and also for the purposes of early diagnosis and use in other relevant research.
Amaç: Bu çalışmanın temel amacı İnternet Oyun Oynama Bozukluğunu (İOOB) ölçmek için değerlendirme araçları olan ve Zihinsel Bozuklukların Teşhis ve İstatistik El Kitabı’nın (DSM-5) beşinci baskısından kaynaklanan 9 ölçüte dayanarak değerlendiren, hem uzun (27 madde) hem de kısa (9 maddelik) çoklu cevaplı İnternet Oyun Oynama Bozukluğu Ölçeği (İOOBÖ) versiyonlarının psikometrik özelliklerini test etmektir.
Yöntem: Katılımcılar 27 maddelik İOOBÖ ve Young’ın İnternet Bağımlılığı Testi Kısa Formu (YİBT-KF) kullanılarak değerlendirildi. İOOBÖ’nin psikometrik özellikleri, Ankara’daki gönüllü üniversite öğrencileri ile İnternet’te oyun oynayan ve e-spor turnuvaları düzenleyen İstanbul’da bulunan bir şirketin e-posta veritabanında bulunan kişiler arasında çevrimiçi anketle test edildi.
Bulgular: Dokuz maddeli İOOBÖ’de tek bileşen, birden büyük (5.926) bir özdeğer değeri gösterdi ve bu bileşen tarafından hesaplanan varyans %65.85 idi. Doğrulayıcı faktör analizleri dokuz maddeli İOOBÖ’nin yapısal geçerliliğinin (yani boyutsal yapısının) tatminkar olduğunu ortaya koymuştur. Ölçeğin bu kısa versiyonu ayrıca güvenilir (Cronbach’ın alfası 0.931) ve oyun oynamak için harcanan süre ve YİBT-KF puanı ile pozitif korelasyonlar gösterdiğinden iyi ölçüt-ilişkili geçerlilik göstermiştir. 27 madde İOOBÖ ile dokuz-madde İOOBÖ arasındaki korelasyon çok yüksekti (n=457; r=0.988, p<0.001). Hem 27 madde İOOBÖ (n=261, r=0.759) hem de dokuz madde İOOBÖ (n=261, r=0.756) için test-tekrar test korelasyonu yüksektir. Teşhis için (5 veya daha fazla ölçüt yaşanması) DSM-5 eşiği uygulanıyorsa, her bir madde için seçilen kesme noktasına göre bozukluk olan oyuncuların yaygınlığı %3.9 ile %9.2 arasında değişiyordu.
Sonuç: Dokuz maddeli İOOBÖ’nin Türkçe versiyonunun geçerlik ve güvenirlik değerlendirmesinin sonuçları orijinal ölçeğin bulguları ile benzer bulunmuştur. Bu bulgular, tek yönlü bir yapı ölçen dokuz maddeli İOOBÖ’nin Türkçe versiyonunun, genç yetişkinler arasında problem oluşturan İOOB’yi belirlemede ve ayrıca erken teşhis ve diğer ilgili araştırmalarda kullanılabilecek geçerli ve güvenilir İOOB tarama aracı olduğunu desteklemektedir.
REFERENCES
1. Gentile DA, Choo H, Liau A, Sim T, Li D, Fung D, Khoo A. Pathological video game use among youth: a two-year longitudinal study. Pediatrics 2011; 127:e319-e329.
[CrossRef]
2. Griffiths M. A “components” model of addiction within a biopsychosocial framework. J Subst Use 2005; 10:191-197.
[CrossRef]
3. Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol 2009; 12:77-95.
[CrossRef]
4. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author, 2000.
5. Chiou WB, Wan CS. Using cognitive dissonance to induce adolescents’ escaping from the claw of online gaming: the roles of personal responsibility and justification of cost. Cyberpsychol Behav 2007; 10:663-670.
[CrossRef]
6. Gentile D. Pathological video-game use among youth ages 8 to 18: a national study. Psychol Sci 2009; 20:594-602.
[CrossRef]
7. Johansson A, Gotestam KG. Problems with computer games without monetary reward: similarity to pathological gambling. Psychol Rep 2004; 95:641-650.
[CrossRef]
8. Keepers GA. Pathological preoccupation with video games. J Am Acad Child Adolesc Psychiatry 1990; 29:49-50.
[CrossRef]
9. Lemmens JS, Valkenburg PM, Peter J. The effects of pathological gaming on aggressive behavior. J Youth Adolesc 2011; 40:38-47.
[CrossRef]
10. Lemmens JS, Valkenburg PM, Peter J. Psychosocial causes and consequences of pathological gaming. Comput Human Behav 2011; 27:144-152.
[CrossRef]
11. King DL, Haagsma MC, Delfabbro PH, Gradisar M, Griffiths MD. Toward a consensus definition of pathological video-gaming: a systematic review of psychometric assessment tools. Clin Psychol Rev 2013; 33:331-342.
[CrossRef]
12. Lemmens JS, Valkenburg PM, Gentile DA. The Internet Gaming Disorder Scale. Psychol Assess 2015; 27:567-582.
[CrossRef]
13. Demetrovics Z, Urbán R, Nagygyörgy K, Farkas J, Griffiths MD, Pápay O, Kökönyei G, Felvinczi K, Oláh A. The development of the Problematic Online Gaming Questionnaire (POGQ). PLoS One 2012; 7:e36417.
[CrossRef]
14. Huang Z, Wang M, Qian M, Zhong J, Tao R. Chinese internet addiction inventory: developing a measure of problematic internet use for Chinese college students. Cyberpsychol Behav 2007; 10:805-811.
[CrossRef]
15. Rehbein F, Kleimann M, Mössle T. Prevalence and risk factors of video game dependency in adolescence: results of a German nationwide survey. Cyberpsychol Behav Soc Netw 2010; 13:269-277.
[CrossRef]
16. Petry NM, O’Brien CP. Internet gaming disorder and the DSM-5. Addiction 2013; 108:1186-1187.
[CrossRef]
17. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA: American Psychiatric Association; 2013.
18. Petry NM, Rehbein F, Gentile DA, Lemmens JS, Rumpf HJ, Mößle T, Bischof G, Tao R, Fung DS, Borges G, Auriacombe M, González Ibánez A, Tam P, O’Brien CP. An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction 2014; 109:1399-1406.
[CrossRef]
19. Király O, Sleczka P, Pontes HM, Urbán R, Griffiths MD, Demetrovics Z. Validation of the Ten-Item Internet Gaming Disorder Test (IGDT-10) and evaluation of the nine DSM-5 Internet Gaming Disorder criteria. Addict Behav 2017; 64:253-260.
[CrossRef]
20. Pontes HM, Király O, Demetrovics Z, Griffiths MD. The conceptualisation and measurement of DSM-5 internet gaming disorder: the development of the IGD-20 test. PLoS One 2014; 9:e110137.
[CrossRef]
21. Pontes HM, Griffiths MD. Measuring DSM-5 Internet gaming disorder: development and validation of a short psychometric scale. Comput Human Behav 2015; 45:137-143.
[CrossRef]
22. Yalcin-Irmak A, Erdogan S. Validity and reliability of the Turkish version of the Digital Game Addiction Scale. Anatolian Journal of Psychiatry 2015; 16(Suppl.1):10-18.
[CrossRef]
23. Young KS. Caught in the net: how to recognize the signs of internet addiction and a winning strategy for recovery. New York: John Wiley and Sons, 1998.
24. Pawlikowski M, Altstötter-Gleich C, Brand M. Validation and psychometric properties of a short version of Young’s Internet Addiction Test. Comput Human Behav 2013; 29:1212-1223.
[CrossRef]
25. Kutlu M, Savci M, Demir Y, Aysan F. Turkish adaptation of Young’s Internet Addiction Test-Short Form: a reliability and validity study on university students and adolescents. Anatolian Journal of Psychiatry 2015; 17(Suppl.1):69-76.
[CrossRef]
26. Byrne BM. Structural equation modeling with AMOS: Basic concepts, Applications and programming. Second ed., Taylor and Francis, New York, NY: 2010.
27. Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate Data Analysis. Seventh ed., Prentice-Hall, Upper Saddle River, New Jersey, 2010.
28. Grüsser SM, Thalemann R, Griffiths MD. Excessive computer game playing: evidence for addiction and aggression
? Cyberpsychol Behav 2007; 10:290-292. [CrossRef]
29. Ko CH, Yen JY, Yen CF, Lin HC, Yang MJ. Factors predictive for incidence and remission of internet addiction in young adolescents: a prospective study. Cyberpsychol Behav 2007; 10:545-551. [CrossRef]
30. Choo H, Gentile DA, Sim T, Li D, Khoo A, Liau AK. Pathological video-gaming among Singaporean youth. Ann Acad Med Singapore 2010; 39:822-829.
31. Jap T, Tiatri S, Jaya ES, Suteja MS. The development of Indonesian online game addiction questionnaire. PloS One 2013; 8:e61098. [CrossRef]