Social Network Addiction Scale: The Validity and Reliability Study of Adolescent and Adult Form

Yıl 2019, , 396 - 414, 15.10.2019

İbrahim Gökdaş , Yaşar Kuzucu

https://doi.org/10.21449/ijate.505863

Cited By: 4

Öz

In this study, it was aimed to develop a valid
and reliable social network addiction scale for adolescents and young adults.
In the Exploratory Factor Analysis of the scale, the application was conducted
to 425 high school students between 14-17 years of age and 310 young adults
between 18-43 years of age. Confirmatory Factor Analysis was performed on a
different group and for this purpose, 322 high school students and 197 young
adults were included in the analysis. As a result of the analyses performed,
the scale exhibited a-10-item and three-factor structure in both groups. The
total variance explained was 71.51% for adolescents and 70.96% for young
adults. The total Cronbach Alpha reliability coefficient of the scale was .87
for adolescents and .84 for young adults. With the 1st and 2nd level
Confirmatory Factor Analysis performed on a similar study group, a good model
was revealed for both adolescents and young adults. The Social Network
Addiction Scale developed within the scope of this study is thought to have the
adequate validity and reliability structure that can be used to measure social
network addiction levels of adolescents and young adults.

Anahtar Kelimeler

Social network addiction scale, social media addiction, social media usage

Social Network Addiction Scale: The Validity and Reliability Study of Adolescent and Adult Form

Öz

In this study, it was aimed to develop a valid and reliable social network addiction scale for adolescents and young adults. In the Exploratory Factor Analysis of the scale, the application was conducted to 425 high school students between 14-17 years of age and 310 young adults between 18-43 years of age. Confirmatory Factor Analysis was performed on a different group and for this purpose, 322 high school students and 197 young adults were included in the analysis. As a result of the analyses performed, the scale exhibited a-10-item and three-factor structure in both groups. The total variance explained was 71.51% for adolescents and 70.96% for young adults. The total Cronbach Alpha reliability coefficient of the scale was .87 for adolescents and .84 for young adults. With the 1st and 2nd level Confirmatory Factor Analysis performed on a similar study group, a good model was revealed for both adolescents and young adults. The Social Network Addiction Scale developed within the scope of this study is thought to have the adequate validity and reliability structure that can be used to measure social network addiction levels of adolescents and young adults.

Anahtar Kelimeler

Social network addiction scale, Social media addiction, Social media usage

Kaynakça

• Aksu, G., Eser, M. T., & Güzeller, C. O. (2017). Açımlayıcı ve Doğrulayıcı Faktör Analizi ile Yapısal Eşitlik Modeli Uygulamaları. Ankara: Detay yayıncılık.
• Allen, K. A., Ryan, T., Gray, D. L., Mclnerney, D. M., & Waters, L. (2014). Social media use and social connectedness in adolescents: The positives and the potential pitfalls. The Australian Educational and Developmental Psychologist, 31, 18 - 31. https://doi.org/10.1017/edp.2014.2
• Andreassen, C. S. (2015). Online social network site addiction: A comprehensive review. Technology and Addiction (M Griffiths, Section Editor). Current Addiction Reports. 2, 175–184. DOI 10.1007/s40429-015-0056-9
• Augner, C., & Hacker, G.W. (2012). Associations between problematic mobile phone use and psychological parameters in young adults. International Journal of Public Health. 57(2), 437-41. DOI: 10.1007/s00038-011-0234-z
• APA (American Psychiatric Association). (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5). American Psychiatric Association Publishing.
• Ayğar Bakır, B. & Uzun, B. (2018). Sosyal Medya Bağımlılığı Ölçeği’nin geliştirilmesi: Geçerlik ve güvenirlik çalışmaları. [Developing the Social Media Addiction Scale: Validity and Reliability Studies] Addicta: The Turkish Journal on Addictions, 5, 507‒525. http://dx.doi.org/10.15805/addicta.2018.5.3.0046
• boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer - Mediated Communication, 13, 2010 - 2030. https://doi.org/10.1111/j.1083-6101.2007.00393.x
• Brunborg, G. S., Mentzoni, R. A., Molde, H., Myrseth, H., Skouverøe, K. J. M., Bjorvatn, B., & Pallesen, S. (2011). The relationship between media use in the bedroom, sleep habits, and symptoms of insomnia. Journal of Sleep Research, 20, 569-575. https://doi.org/10.1111/j.1365-2869.2011.00913.x
• Cakir Balta, O. & Horzum M. B. (2008). İnternet bağımlılığı testi. [Internet addiction test]. Eğitim Bilimleri ve Uygulama, 7(13), 87-102
• Can, L., & Kaya, N. (2016). Social networking sites addiction and the effect of attitude towards social network advertising. Procedia-Social and Behavioral Sciences, 235, 484-492. https://doi.org/10.1016/j.sbspro.2016.11.059
• Cao, F., & Su, L., (2006). Internet addiction among Chinese adolescents: prevalence and psychological features. Child Care Health and Development. 33(3), 275–281. https://doi.org/10.1111/j.1365-2214.2006.00715.x
• Cecilia, C., & Yee-lam L. A., (2014). Internet addiction prevalence and quality of (real) life: a meta-analysis of 31 nations across seven world regions, Cyberpsychology, Behavior, and Social Networking.17(12), 755-760.
• Cheung, L. M., & Wong, W. S. (2011). The effects of insomnia and internet addiction on depression in Hong Kong Chinese adolescents: An exploratory cross-sectional analysis. Journal of Sleep Research, 20, 311–317. http://dx.doi.org/10.1111/j.1365-2869.2010.00883.x
• Choi, S. B., & Lim, M. S. (2016). Effects of social and technology overload on psychological well-being in young South Korean adults: The mediatory role ofsocial network service addiction. Computers in Human Behavior, 61, 245-254.
• Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2012). Sosyal Bilimler için Çok Değişkenli İstatistik SPSS ve LISREL Uygulamaları. Ankara: Pegem.Net
• De Beer, M. (2004). Use of differential item functioning (DIF) analysis for bias analysis intest construction. South African Journal of Industrial Psychology, 30(4), 52-58.
• Dewald, J. F., Meijer, A. M., Oort, F. J., Kerkhof, G. A., & Bögels, S. M. (2010) The influence of sleep quality, sleep duration and sleepiness on school performance in children and adolescents: a meta-analytic review. Sleep Medicine Reviews, 14, 179-189.
• Echeburúa, E., & De, Corral. P. (2010). Addiction to new technologies and to online socialnetworking in young people: A new challenge. Adicciones,22(2), 91-95.
• Erkuş, A. (2012). Psikolojide Ölçme ve Ölçek Geliştirme-1 temel kavramlar ve işlemler. Ankara: Pegem Akademi.
• Esgi, N. (2016). Development of social media addiction test (SMART17). Journal of education and training studies. 4(10), 174-181
• Gao, W., Liu, Z., & Li, J. (2017). How does social presence influence SNS addiction? A belongingness theory perspective. Computers in Human Behavior 77 (2017) 347-355. http://dx.doi.org/10.1016/j.chb.2017.09.002
• Griffiths, M. D. (2013). Social networking addiction: emerging themes and issues. Journal of Addiction Research & Therapy, 4(5). http://dx.doi.org/10.4172/2155-6105.1000e118
• Griffiths, M. D., Kuss, D. J., & Demetrovics, Z. (2014). Social networking addiction: anoverview of preliminary findings. In Behavioral addictions. Criteria, evidence, and treatment (pp. 119-141). New York: Elsevier.
• Gültaş, M. (2014). Work Discipline Compound Personality Scale Development with Item Response Theory. Unpublished dissertation thesis. Middle East Technical University, Graduate School of Social Sciences, Ankara.
• Huang, H., & Leung, L. (2009). Instant messaging addiction among teenagers in China: Shyness, alienation, and academic performance decrement. Cyberpsychology and Behavior,12(6), 675-679. http://dx.doi.org/10.1089/cpb.2009.0060
• Huang, X., Zhang, H., Li, M., Wang, J., Zhang, Y., & Tao, R., (2010). Mental health, personality, and parental rearing styles of adolescents with internet addiction disorder. Cyberpsychology, Behavior, and Social Networking. 13(4), 401-406. DOI: 10.1089=cyber.2009.0222
• Kang, I., Shin, M. M., & Park, C. (2013). Internet addiction as a manageable resource:A focus on social network services. Online Information Review, 37(1), 28-41.
• Kim, E. J., Namkoong, K., Ku, T., & Kim, S.J., (2008). The relationship between online game addiction and aggression, self-control and narcissistic personalitytraits. European Pschiatry, 23, 212-218.
• Kim, K., Ryu, E., Chon, M. Y., Yeun, E. J., Choi, S. Y., Seo, J. S., &Nam, B.W., (2006). Internet addiction in Korean adolescents and its relation to depression andsuicidal ideation: a questionnaire survey. Intertional Journal of Nursing Studies, 43, 185-192.
• Kuss, D. J., & Griffiths, M. D. (2011). Online social networking and addiction-A review of the psychological literature. International Journal of Environmental Research and Public Health, 8, 3528-3552; DOI:10.3390/ijerph8093528
• Kuss, D. J., & Griffiths, M. D. (2012). Internet gaming addiction: A systematic reviewof empirical research. International Journal of Mental Health and Addiction, 10(2), 278-296.
• Kuşay, Y. (2013). Sosyal Medya Ortamında Çekicilik ve Bağımlılık- Facebook Üzerine Bir Araştırma. İstanbul: Beta Yayıncılık.
• LaRose, R., Connolly, R., Lee, H., Li, K., & Hales, K. D. (2014). Connection overload? Across cultural study of the consequences of social media connection. Information Systems Management, 31(1), 59-73. https://doi.org/10.1080/10580530.2014.854097
• Lavin, M. J., Yuen, C.N., Weinman, M., & Kozak, K., (2004). Internet dependence in the collegiate population: The role of shyness. CyberPsychology & Behavior. 7, 379-383.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657. DOI: 10.1089/cyber.2014.0070
• Park, S. K., Kim, J. Y., & Cho, C. B. (2008). Prevalence of Internet addiction and correlations with family factors among South Korean adolescents. Adolescence,43(172), 895-909.
• Ryan, T., Chester, A., Reece, J., & Xenos, S. (2014). The uses and abuses of Facebook: A review of Facebook addiction. Journal of Behavioral Addictions 3(3), 133-148. DOI: 10.1556/JBA.3.2014.016
• Salehan, M., & Negahban, A. (2013). Social networking on smartphones: Whenmobile phones become addictive. Computers in Human Behavior, 29(6), 2632-2639.
• Satici, S. A., & Uysal, R. (2015). Well-being and problematic Facebook use. Computers in Human Behavior, 49, 185-190. DOI:10.1016/j.chb.2015.03.005
• Suganuma, N., Kikuchi, T., Yanagi, K., Yamamura, S., Morishima, H., Adachi, H., Kumanogo, T., Mikami, A., Sugita, Y., & Takeda, M. (2007). Using electronic media before sleep can curtail sleep time and result in self-perceived insufficient sleep. Sleep and Biological Rhythms, 5, 204-214.
• Şahin, C. (2018). Social media addiction scale - Student form: The reliability and validity study, TOJET: The Turkish Online Journal of Educational Technology,17(1), 169-182. ERIC Number: EJ1165731
• Şahin, C., & Yağcı, M. (2017). Sosyal medya bağımlılığı ölçeği- Yetişkin formu: Geçerlilik ve güvenirlik çalışması [Social Media Addiction Scale - Adult Form: The Reliability and Validity Study Social Media Addiction Scale - Adult Form: The Reliability and Validity Study], Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi (KEFAD), 18(1), 523-538.
• Taş, İ. (2017). Ergenler için sosyal medya bağımlılığı ölçeği kısa formunun (SMBÖ-KF) geçerlik ve güvenirlik çalışması, [The Study of Validity And Reliability of The Social Media Addiction Scale Short Form For Adolescents], Online Journal of Technology Addiction & Cyberbullying, 4(1), 27-40.
• Tekin, C., Gunes, G., & Colak, C. (2014). Adaptation of problematic mobile phone use scale to Turkish: a validity and reliability study. Medicine Science3(3), 1361-81. DOI: 10.5455/medscience.2014.03.8138
• Turel, O., & Serenko, A. (2012). The benefits and dangers of enjoyment with socialnetworking websites. European Journal of Information Systems,21(5), 512-528.
• Tutgun-Ünal, A. (2015). Sosyal medya bağımlılığı: üniversite öğrencileri üzerine bir araştırma. [Social media addiction: a research on university Students], (Yayınlanmamış Doktora Tezi) Marmara Üniversitesi Sosyal Bilimler Enstitüsü Gazetecilik Ana Bilim Dalı, Bilişim Bilim Dalı. İstanbul.
• Van den Eijnden, R. J. J. M., Lemmens, J. S., & Valkenburg, P. M. (2016). The social media disorder scale. Computers in Human Behavior. 61, 478-487.
• Vilca, L. W., & Vallejos, M. (2015). Construction of the risk of addiction to socialnetworks scale (Cr. ARS). Computers in Human Behavior, 48, 190-198.
• We are Social (2017). Digital in 2017 Global Overview Report. https://wearesocial.com/uk/special-reports/digital-in-2017-global-overview
• Wu, A. D., Li, Z. ve Zumbo, B. D. (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Practical Assessment, Research & Evaluation, 12, 1-26.
• Yang, S., Liu, Y., & Wei, J. (2016). Social capital on mobile SNS addiction: Aperspective from online and offline channel integrations. Internet Research,26(4), 982-1000.
• Young, K. S. (1998). Internet addiction: The emergence of a new clinical disorder. Cyberpsychology and Behavior, 1(3), 237-244. https://doi.org/10.1089/cpb.1998.1.237