Relationships of Problematic Internet Use, Online Gaming, and Online Gambling with Depression and Quality of Life Among College Students
Abstract views: 616
/ 
PDF downloads: 205
DOI:
https://doi.org/10.33200/ijcer.594164Keywords:
Problematic Internet use, Online gaming, Online gambling, Depression, Quality of lifeAbstract
Young adults on college campuses have easy access to information and communications technology (ICT) which they use extensively for study, work, and leisure. The purpose of this study was to investigate the prevalence and extent of problematic Internet use, online gaming behavior, and online gambling behavior (together referred to as dysfunctional online behaviors), and their relationships with depression and quality of life among college students. Two hundred and twenty two valid surveys were used in the data analyses. Five instruments, Beck Depression Inventory-II (BDI-II), the WHO Quality of Life Scale-BREF (WHOQOL-BREF), the Internet Addiction Test (IAT), the Problematic Online Gaming Questionnaire (POGQ), and the Online Gambling Symptom Assessment Scale (OGSAS), were selected to measure the variables being studied. A non-experimental research design was employed to answer one descriptive and two research questions. The results of the analyses indicated that dysfunctional online behaviors predicted a higher level of depression (R2 = .14, p < .05) and a lower level of quality of life (R2 = .20, p < .05). The findings of the current study inform clinical practice and the treatment of dysfunctional online behaviors among college students.
References
Abreu, C. N., & Goes, D. S. (2011). Psychotherapy for Internet addiction. In Kimberly S. Young and Cristiano Nabuco de Abreu (Eds). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, NJ: John Wiley & Sons, Inc.
American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
Amichai-Hamburger, Y., & Ben-Artzi, E. (2003). Loneliness and Internet use. Computers in Human Behavior, 19, 71-80. doi:10.1016/S0747-5632(02)00014-6
Amichai-Hamburger, Y., & Furnham, A. (2007). The Positive Net. Computers in Human Behavior, 23(2), 1033-1045. doi:10.1016/j.chb.2005.08.008
Beck, A. T., Steer, R. A., & Brown, G. (1996). Beck Depression Inventory II manual. San Antonio, TX: The Psychological Corporation.
Beck, A. T., Steer, R. A., Ball, R., & Ranieri, W. F. (1996). Comparison of Beck Depression Inventories-IA and-II in psychiatric outpatients. Journal of Personality Assessment, 67(3), 588-597. doi:10.1207/s15327752jpa6703_13
Bell, V. (2007). Online information, extreme communities and Internet therapy: Is the Internet good for our mental health? Journal of Mental Health, 16(4), 445-457. doi:10.1080/09638230701482378
Berlim, M. T., Pavanello, D. P., Caldieraro, M. A. K., Fleck, M. P. A., (2005). Reliability and validity of WHOQOL-BREF in a sample of Brazilian outpatients with major depression. Quality of Life Research, 14(2), 561-564. doi:10.1007/s11136-004-4694-y
Brooks, G. P., & Barcikowski, R. S. (2012). The PEAR method for sample sizes in multiple linear regression. Multiple Linear Regression Viewpoints, 38(2), 1-16. Retrieved from www.mlrv.ua.edu/ejournal.html
Brown, J. D., & Bobkowski, P. S. (2011). Older and newer media: Patterns of use and effects on adolescents' health and well-being. Journal of Research on Adolescence, 21(1), 95-113. doi:10.1111/j.1532-7795.2010.00717.x
Business Insights (2010, March 1), The Future of Digital Gambling: The Impact of Regulation, the Rise of Online Services and the Evolving Competitive Environment. Market Research. Retrieved from http://www.marketresearch.com/product/display.asp?productid=2637052&xs=r&g=1&curr=USD&kw=&view=toc
Caplan, S. E. (2002). Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive-behavioral measurement instrument. Computers in Human Behavior, 18, 553-575. doi:10.1016/S0747-5632(02)00004-3
Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and psychosocial well-being among MMO players. Computers in Human Behavior, 25(6), 1312-1319. doi:10.1016/j.chb.2009.06.006
Cassidy-Bushrow, A. E., Johnson, D. A., Peters, R. M., Burmeister, C., & Joseph, C. L. M. (2015). Time Spent on the Internet and Adolescent Blood Pressure. The Journal of School Nursing, 31(5), 374-384. http://doi.org/10.1177/1059840514556772
Castro, P. C., Driusso, P., & Oishi, J. (2014). Convergent validity between SF-36 and WHOQOL-BREF in older adults. Revista de Saude Publica, 48(1), 63-67. doi:10.1590/S0034-8910.2014048004783
Ceyhan, A. A., & Ceyhan, E. (2008). Loneliness, depression, and computer self-efficacy as predictors of problematic Internet use. CyberPsychology & Behavior, 11(6), 699-701. doi:10.1089/cpb.2007.0255
Chang, S.-M., Yeh, Y.-C., Chen, S.-K., & Lin, S. S. J. (2013). High risk college Internet users' deadly attraction: a blending of social charms with practical and critical activities. Presented at the 2013 annual meeting of American Psychological Association, Hawaii, USA.
Chen, S. (2012). Internet use and psychological well-being among college students: A latent profile approach. Computers in Human Behavior, 28(6), 2219-2226. doi:10.1016/j.chb.2012.06.029
Chen, S.-K., & Lin, S. S. J. (2016). A latent growth curve analysis of initial depression level and changing rate as predictors of problematic Internet use among college students. Computers in Human Behavior, 54, 380-387. doi:10.1016/j.chb.2015.08.018
Clifton, A., Goodall, D., Ban, S., & Birks, E. (2013). New perspectives on the contribution of digital technology and social media use to improve the mental wellbeing of children and young people: A state of the art review. Neonatal Pediatric & Child Health Nursing, 16(1), 19-26. Retrieved from http://eprints.hud.ac.uk/id/eprint/16790
Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (6th ed.). London, UK: Routledge.
Cotten, S. R. (2008). Students’ technology use and the impacts on well-being. New Directions for Student Services, 124, 55–70. doi:10.1002/ss.295
Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17, 187-195. doi10.1016/S0747-5632(00)00041-8
Demetrovics, Z., Urban, R., Nagygyorgy, K., Farkas, J., Griffiths, M. D., Papay, O., … Olah, A. (2012). The development of the Problematic Online Gaming Questionnaire (POGQ). PLoS ONE, 7(5), 1-9. doi:10.1371/journal.pone.0036417
Frangos, C. C., Frangos, C. C., & Sotiropoulos, I. (2012). A meta-analysis of the reliability of Young’s Internet addiction test. Proceedings of the World Congress on Engineering, 368-371. Retrieved from http://www.iaeng.org/publication/WCE2012/WCE2012_pp368-371.pdf
Green, M. C., Hilken, J., Friedman, H., Grossman, K., Gasiewskj, J., Adler, R., & Sabini, J. (2005). Communication via Instant Messenger: Short- and Long-Term Effects. Journal of Applied Social Psychology, 35(3), 445-462. doi:10.1111/j.1559-1816.2005.tb02130.x
Griffiths, M.D., Parke, J., Wood, R.T.A. & Rigbye, J. (2010). Online poker gambling in university students: Further findings from an online survey. International Journal of Mental Health and Addiction, 8, 82-89. doi:10.1007/s11469-009-9203-7
Harrison, K., & Hefner, V. (2008). Media, body image, and eating disorders. In S. L. Calvert & B. J. Wilson (Eds.), The handbook of children, media, and development (pp. 381-406). Malden, MA: Blackwell.
Hornle, J. & Zammit, B. (2010). Cross-border online gambling law and policy. Cheltenham, UK: Edgar Elgar.
International Classification of Diseases (2018). ICD-11 Revision. Retrieved from https://icd.who.int/dev11/l-m/en
Kalkan, B., & Griffiths, M. D. (2018). The psychometric properties of the Online Gambling Symptom Assessment Scale (OGSAS). International Journal of Mental Health and Addiction.
Kang, S. (2007). Disembodiment in online social interaction: Impact of online chat on social support and psychological well-being. CyberPsychology and Behavior, 10, 475-477. doi: 10.1089/cpb.2006.9929
Khan, A., & Muqtadir, R. (2014). Problematic online gaming in Pakistan. International Journal of Science and Research, 3(6), 2522-2525.
Kim, S. W., Grant, J. E., Potenza, M. N., Blanco, C., & Hollander, E. (2009). The Gambling Symptom Assessment Scale (G-SAS): A reliability and validity study. Psychiatry Research, 166, 76-84. doi:10.1016/j.psychres.2007.11.008
Kiraly, O., Griffiths, M. D., Urban, R., Farkas, J., Kokonyei, G., Elekes, Z., … Demetrovics, Z. (2014). Problematic Internet use and problematic online gaming are not the same: Findings from a large nationally representative adolescent sample. Cyberpsychology, Behavior, and Social Networking, 17(12), 749-754. doi:10.1089/cyber.2014.0475
Ko, C.-H., Yen, J.-Y., Yen, C.-F., Lin, H.-C., & Yang, M.-J. (2007). Factors predictive for incidence and remission of Internet addiction in young adolescents: A prospective study. CyberPsychology & Behavior, 10(4), 545–551. doi:10.1089/cpb.2007.9992
Krägeloh, C. U., Kersten, P., Billington, D. R., Hsu, P. H. C., Shepherd, D., Landon, J., & Feng, X. J. (2013). Validation of the WHOQOL-BREF quality of life questionnaire for general use in New Zealand: Confirmatory factor analysis and Rasch analysis. Quality of Life Research, 22(6), 1451-1457. doi:10.1007/s11136-012-0265-9
Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58(1), 49–74. doi:10.1111/1540-4560.00248
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being? American Psychologist, 53(9), 1017-1031. doi:10.1037/0003-066X.53.9.1017
Lauckner, C., Hill, M., & Ingram, L. A. (2018). An exploratory study of the relationship between social technology use and depression among college students. Journal of College Student Psychotherapy. doi:10.1080/87568225.2018.1508396
Lee, S. (2009). Problematic Internet use among college students: An exploratory survey research study (Doctoral dissertation). Retrieved from https://etd.ohiolink.edu (UMI No. 3439312).
Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of Pathological gamblers. American Journal of Psychiatry, 144(9), 1184-1188. doi:10.1176/ajp.144.9.1184
Linderoth, J. & Ohrn, E. (2014). Chivalry, subordination and courtship culture: Being a “woman” in online games. Journal of Gambling & Virtual Worlds, 6(1), 33-47. doi:10.1386/jgvw.6.1.33_1
Matthews, N., Farnsworth, B., & Griffiths, M. D. (2009). A pilot study of problem gambling among student online gamblers: Mood states as predictors of problematic behavior. CyberPsychology & Behavior, 12(6), 741-745. doi:10.1089/cpb.2009.0050
Pápay, O., Urbán, R., Griffiths, M. D., Nagygyörgy, K., Farkas, J., Kökönyei, G., … Demetrovics, Z. (2013). Psychometric properties of the Problematic Online Gaming Questionnaire short-form and prevalence of problematic online gaming in a national sample of adolescents. Cyberpsychology, Behavior and Social Networking, 16(5), 340-348. doi:10.1089/cyber.2012.0484
Pearson Clinical (n.d.). Beck Depression Inventory - II. Retrieved from http://www.pearsonclinical.com/psychology/products/100000159/beck-depression-inventoryii-bdi-ii.html#tab-details
Petry, N. M., & Gonzalez-Ibanez, A. (2015). Internet gambling in problem gambling college students. Journal of Gambling Studies, 31, 397-408. doi:10.1007/s10899-013-9432-3
Pew Research Center (2018a). Internet/Broadband Fact Sheet. Retrieved from http://www.pewInternet.org/fact-sheet/Internet-broadband/
Pew Research Center (2018b). About a quarter of U.S. adults say they are ‘almost constantly’ online. Retrieved from http://www.pewresearch.org/fact-tank/2018/03/14/about-a-quarter-of-americans-report-going-online-almost-constantly/
PlayUSA, (n.d.). Legal US online gambling guide. Retrieved from https://www.playusa.com/us/
Rawana, J. S., & Morgan, A. S. (2014). Trajectories of depressive symptoms from adolescence to young adulthood: the role of self-esteem and body-related predictors. Journal of Youth and Adolescence, 43(4), 597-611. doi:10.1007/s10964-013-9995-4
Romer, D., Bagdasarov, Z., & More, E. (2013). Older versus newer media and the well-being of United States youth: Results from a national longitudinal panel. Journal of Adolescent Health, 52(5) 613-619. doi:10.1016/j.jadohealth.2012.11.012
Shaw, L. H., & Gant, L. M. (2002). In defense of the Internet: The relationship between Internet communication and depression, loneliness, self-esteem, and perceived social support. Cyberpsychology and Behavior, 5(2), 157-171. doi:10.1089/109493102753770552
Snodgrass, J. G., Lacy, M. G., Dengah II, H. J., Eisenhauer, S., Batchelder, G., Cookson, R. J. (2014). A vacation from your mind: Problematic online gaming is a stress response. Computers in Human Behavior, 38, 248-260. doi:10.1016/j.chb.2014.06.004
The WHOQOL Group (1998). Development of the world health organization WHOQOL-BREF quality of life assessment. Psychological Medicine, 28(3), 551-558. doi:10.1017/S0033291798006667
van der Aa, N., Overbeek, G., Engels, R. C. M. E., Scholte, R. H. J., Meerkerk, G. J., & van der Eijinden, R. J. J. M. (2009). Daily and compulsive Internet use and well-being in adolescence. A diathesis-stress model based on big five personality traits. Journal of Young Adolescence, 38, 765-776. doi:10.1007/s10964-008-9298-3
van Rooij, A. J. (2011). Online video games addiction. Exploring a new phenomenon (PhD Thesis). Rotterdam, The Netherlands: Erasmus University Rotterdam.
Whang, L. S.-M., Lee, S. & Chang, G.-Y. (2003). Internet over-users' psychological profiles: A behavior sampling analysis on Internet addiction. CyberPsychology & Behavior, 6(2), 143-150. doi:10.1089/109493103321640338
Widyanto, L., & McMurran, M. (2004). The psychometric properties of the Internet Addiction Test. CyberPsychology & Behavior, 7(4), 443-450. doi:10.1089/cpb.2004.7.443
Young, K. S. (1998). Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior, 1(3), 237-244. doi:10.1089/cpb.1998.1.237
Young, K. S. (2011). CBT-IA: The first treatment model for Internet addiction. Journal of Cognitive Psychotherapy: An International Quarterly, 25(4), 304-312. doi:10.1891/0889-8391.25.4.304
Young, K. S., Yue, X. D., & Ying, L. (2011). Prevalence estimates and etiological models of Internet addiction. In Kimberly S. Young and Cristiano Nabuco de Abreu (Eds). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, NJ: John Wiley & Sons, Inc.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Bilal Kalkan, Christine Suniti BHAT
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
