Skip to main content

Advertisement

SpringerLink
Log in

Subtypes of Adolescent Video Gamers: a Latent Class Analysis

  • Published:
International Journal of Mental Health and Addiction Aims and scope Submit manuscript

Abstract

Objective Excessive video gaming may represent a behavioural addiction among adolescents. The objective of this study was to identify and describe the taxonomy of problem gamers based on responses to the Problem Video Game Playing (PVP) scale. Methods Data based on 3338 Ontario high schoolers sampled from 103 schools (aged 11–20; male = 51 %) who completed self-administered questionnaires. Following latent class extraction, a regression assessed the association between the derived classes and the covariates sex and socioeconomic status. We also assessed self-rated physical and mental health as auxiliary variables in the model to evaluate the predictive validity of the extracted classes. Results A 4-class model provided the best statistical fit to the nine PVP symptoms. The Severe PVP, High PVP, Low PVP and Normative classes comprised 1.9 %, 12.2 %, 36.0 % and 50.0 % of the sample, respectively. The Severe PVP class was characterized by having the highest probabilities of endorsing the PVP items. The High PVP class was differentiated from the Severe PVP class by having lower probabilities of endorsing the disregard for consequences and the lies and deception items and moderate probabilities of endorsing withdrawal and escape items. Significantly poorer physical and mental health outcomes differentiated the Severe PVP class from the remaining classes. Conclusions Adolescent problem video gamers are not homogeneous. They experience differing patterns of symptoms requiring attention of prevention programmers and clinicians.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

    Book  Google Scholar 

  • Asparouhov, T., & Muthén, B. (2008). Multilevel mixture models. In G. R. Hancock & K. M. Samuelsen (Eds.), Advances in latent variable mixture models (pp. 27–51). Charlotte, NC: Information Age.

    Google Scholar 

  • Biddle, S. J. H., Gorely, T., Marshall, S. J., Murdey, I., & Cameron, N. (2004). Physical Activity and Sedentary Behaviours in Youth: Issues and Controversies. Journal of the Royal Society for the Promotion of Health, 124, 29–33. doi:10.1177/146642400312400110.

    Article  PubMed  Google Scholar 

  • Bioulac, S., Arfi, L., & Bouvard, M. P. (2008). Attention Deficit/Hyperactivity Disorder and Video Games: a Comparative Study of Hyperactive and Control Children. European Psychiatry, 23, 134–141. doi:10.1016/j.eurpsy.2007.11.002.

    Article  PubMed  Google Scholar 

  • Blaszczynski, A., & Nower, L. (2002). A Pathways Model of Problem and Pathological Gambling. Addiction, 97, 487–499. doi:10.1046/j.1360–0443.2002.00015.x.

    Article  PubMed  Google Scholar 

  • Canadian Society of Exercise Physiology. (2011). Canadian Physical Activity Guidelines. Retrieved September 27, 2013, from http://www.csep.ca/CMFiles/Guidelines/CSEP-InfoSheets-youth-ENG.pdf.

  • Carson, V., & Janssen, I. (2012). Neighborhood Disorder and Screen Time Among 10–16 Year old Canadian Youth: a Cross-Sectional Study. International Journal of Behavioural Nutrition and Physical Activity, 9, 66. doi:10.1186/1479–5868–9–66.

    Article  Google Scholar 

  • Centre for Addiction and Mental Health. (2012). Ontario Student Drug Use and Health Survey. Retrieved September 27, 2013, from http://www.camh.ca/research/osduhs.aspx.

  • Cole, T. J., Bellizzi, M. C., Flegal, K. M., & Dietz, W. H. (2000). Establishing a Standard Definition for Child Overweight and Obesity Worldwide: International Survey. British Medical Journal, 320, 1240–1243.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Croon, M. (2002). Ordering the Classes. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied Latent Class Analysis (pp. 137–162). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • D’Arcy, C. (1998). Social distribution of health among Canadians. In D. Coburn, C. D’Arcy, & G. M. Torrance (Eds.), Health and Canadian Society: Sociological Perspectives (3rd ed., pp. 73–101). Toronto: University of Toronto Press.

    Google Scholar 

  • Demetrovics, Z., Urban, R., Nagygyorgy, K., Farkas, J., Griffiths, M. D., Papay, O., Kokonyei, G., Felvinczi, K., & Olah, A. (2012). The Development of the Problematic Online Gaming Questionnaire (POGQ). PloS One, 7(5), e36417.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Desai, R. A., Krishnan-Sarin, S., Cavallo, D., & Potenza, M. N. (2010). Video-Gaming Among High School Students: Health Correlates, Gender Differences, and Problematic Gaming. Pediatrics, 126, e1414–1424. doi:10.1542/peds.2009–2706.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ferguson, C. J., Coulson, M., & Barnett, J. (2011). A Meta-Analysis of Pathological Gaming Prevalence and Comorbidity with Mental Health, Academic and Social Problems. Journal of Psychiatric Research, 45, 1573–1578. doi:10.1016/j.jpsychires.2011.09.005.

    Article  PubMed  Google Scholar 

  • Gentile, D. A. (2009). Pathological Video-Game Use Among Youth Ages 8 to 18: a National Study. Psychological Science, 20, 594–602. doi:10.1111/j.1467–9280.2009.02340.x.

    Article  PubMed  Google Scholar 

  • Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., & Khoo, A. (2011). Pathological Video Game use Among Youths: a Two-Year Longitudinal Study. Pediatrics, 127, e319–e20. doi:10.1542/peds.2010–1353.

    Article  PubMed  Google Scholar 

  • Goldberg, D. P., & William, P. (1998). A user’s guide to the General Health Questionnaire. Windsor, UK: NFER-N.

    Google Scholar 

  • Goldberg, D. P., Gater, R., Sartorius, N., Ustun, T. B., Piccinelli, M., Gureje, O., & Rutter, C. (1997). The Validity of Two Versions of the GHQ in the WHO Study of Mental Illness in General Health Care. Psycholical Medicine, 27, 191–197.

    Article  CAS  Google Scholar 

  • Goodman, E., Adler, N. E., Kawachi, I., Frazier, A. L., Huang, B., & Colditz, G. A. (2001). Adolescents’ Perceptions of Social Status: Development and Evaluation of a New Indicator. Pediatrics, 108, e31. doi:10.1542/peds.108.2.e31.

    Article  CAS  PubMed  Google Scholar 

  • Griffiths, M. D., Parke, J., & Derevensky, J. L. (2011). Remote gambling in adolescence. In J.L. Derevensky, D.T. Shek & J. Merrick J (Eds.), Youth Gambling: The Hidden Addiction (pp. 125–143). Berlin/Boston: De Gruyter.

    Google Scholar 

  • Griffiths, M. D., King, D. L., & Demetrovics, Z. (2014). DSM-5 Internet Gaming Disorder Needs a Unified Approach to Assessment. Neuropsychiatry, 4, 1–4.

    Article  Google Scholar 

  • Groves, R., & Peytcheva, E. (2008). The Impact of Nonresponse on Nonresponse Bias: a Meta-Analysis. Public Opinion Quarterly, 72, 167–189.

    Article  Google Scholar 

  • Gupta, R., & Derevensky, J. (2011). Defining and assessing binge gambling. In J.L. Derevensky, D.T. Shek & J. Merrick J (Eds.), Youth Gambling: The Hidden Addiction (pp. 79–97). Berlin/Boston: De Gruyter.

    Google Scholar 

  • Hagenaars, J. A., & McCutcheon, A. L. (2002). Applied Latent Class Analysis. New York: Cambridge University Press.

    Book  Google Scholar 

  • King, D. L., & Delfabbro, P. H. (2013). Issues for DSM-5: Video-Gaming Disorder? Australia and New Zealand Journal of Psychiatry, 47, 20–22. doi:10.1177/0004867412464065.

    Article  Google Scholar 

  • King, D. L., Delfabbro, P. H., Zwaans, T., & Kaptsis, D. (2013). Clinical Departures and Axis 1 Comorbidity of Australian Adolescent Pathological Internet and Video Game Users. Australia and New Zealand Journal of Psychiatry, 47, 1058–1067. doi:10.1177/0004867413491159.

    Article  Google Scholar 

  • Korn, E., & Graubard, B. I. (1999). The Analysis of Health Surveys. New York: John Wiley.

    Book  Google Scholar 

  • Kuss, J. D., & Griffiths, M. D. (2011). Internet Gaming Addiction: A Systematic Review of Empirical Research. International Journal of Multimedia & its Applications, 10, 278–296. doi:10.1007/s11469-011-9318-5.

    Google Scholar 

  • McDowell, I. (2006). Measuring health: A guide to rating scales and questionnaires (3rd ed.). New York: Oxford University Press.

    Book  Google Scholar 

  • Mentzoni, R. A., Brunborg, G. S., Molde, H., Myrseth, H., Skouverøe, K. J., Hetland, J., & Pallesen, S. (2011). Problematic Video Game use: Estimated Prevalence and Associations with Mental and Physical Health. Cyberpsychology, Behavior and Social Networking, 14, 591–596. doi:10.1089/cyber.2010.0260.

    Article  PubMed  Google Scholar 

  • Moffitt, T. E. (2006). Life-course-persistent versus adolescence-limited antisocial behavior. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology (Risk, disorder, and adaptation, 2nd edition, Vol. 3, pp. 570–598). Hoboken, NJ: John Wiley & Sons.

    Google Scholar 

  • Muthén, B. (2002). Should Substance use Disorder be Considered as Categorical or Dimensional? Addiction, 101, 6–16. doi:10.1111/j.1360–0443.2006.01583.x.

    Article  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (1998–2011). Mplus User’s Guide Version 11.2. Los Angeles, CA: Muthén and Muthén.

    Google Scholar 

  • Nower, L., & Blaszczynski, A. (2004). The Pathways Model as Harm Minimization for Youth Gamblers in Educational Settings. Child and Adolescent Social Work Journal, 21, 25–45. doi:10.1023/B:CASW.0000012347.61618.f7.

    Article  Google Scholar 

  • Nylund, K. L., Asparouhov, T., & Muthén, B. (2007). Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: a Monte Carlo Simulation Study. Structural Equation Modeling, 14, 535–569.

    Article  Google Scholar 

  • Paglia-Boak, A., Adlaf, E. M., & Mann, R. E. (2011). Drug use among Ontario students, 1977–2011: Detailed OSDUHS findings (CAMH Research Series Document 33). Toronto, ON: Centre for Addiction and Mental Health.

    Google Scholar 

  • Pápay, O., Urban, R., Griffiths, M. D., Nagygyorgy, K., Farkas, J., Kokonyei, G., Felvinczi, K., Olah, A., Elekes, Z., & Demetrovics, Z. (2013). Psychometric Properties of the Problematic Online Gaming Questionnaire Short-Form (POGQ-SF) and Prevalence of Problematic Online Gaming in a National Sample of Adolescents. Cyberpsychology, Behavior and Social Networking, 16, 340–348.

    Article  PubMed Central  PubMed  Google Scholar 

  • Patterson, B. H., Dayton, M., & Graubard, B. I. (2002). Latent Class Analysis of a Complex Sample Survey Data: Application to Dietary Data. Journal of the American Statistical Association, 97, 721–741. doi:10.1198/016214502388618465.

    Article  Google Scholar 

  • Pearson, N., & Biddle, S. J. (2011). Sedentary Behavior and Dietary Intake in Children, Adolescents, and Adults: a Systematic Review. American Journal of Preventive Medicine, 41, 178–188. doi:10.1016/j.amepre.2011.05.002.

    Article  PubMed  Google Scholar 

  • Ramaswany, V., De Sarbo, W., Reibstein, D., & Robinson, W. (1993). An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data. Marketing Science, 12, 103–124.

    Article  Google Scholar 

  • Rehbein, F., Psych, G., Kleimann, M., Mediasci, G., & MoBle, T. (2010). Prevalence and Risk Factors of Video Game Dependency in Adolescence: Results of a German Nationwide Survey. Cyberpsychology, Behavior and Social Networking, 13, 269–277. doi:10.1089/cyber.2009.0227.

    Article  PubMed  Google Scholar 

  • Tejeiro Salguero, R. A., & Morán, R. M. B. (2002). Measuring Problem Video Game Playing in Adolescents. Addiction, 97, 1601–1606. doi:10.1046/j.1360–0443.2002.00218.x.

    Article  PubMed  Google Scholar 

  • Tejeiro Salguero, R. A., Gomez-Vallecillo, J. L., Pelegrina, M., Wallace, A., & Emberley, E. (2012). Risk Factors Associated with the Abuse of Video Games in Adolescents. Psychology, 3, 310–314. doi:10.4236/psych.2012.34044.

    Article  Google Scholar 

  • Tremblay, M. S., LeBlanc, A. G., Kho, M. E., Saunders, T. J., Larouche, R., Colley, R. C., Goldfield, G., & Connor Gorber, S. (2011a). Systematic Review of Sedentary Behaviour and Health Indicators in School-Aged Children and Youth. International Journal of Behavioural Nutrition and Physical Activity, 8, 98. doi:10.1186/1479–5868–8–98.

    Article  Google Scholar 

  • Tremblay, M. S., Leblanc, A. G., Janssen, I., Kho, M. E., Hicks, A., Murumets, K., Colley, R. C., & Duggan, M. (2011b). Canadian Sedentary Behaviour Guidelines for Children and Youth. Applied Physiology, Nutrition, and Metabolism, 36, 59–71. doi:10.1139/H11–012.

    Article  PubMed  Google Scholar 

  • Turner, N. E., Jain, U., Spence, W., & Zangeneh, M. (2008). Pathways to Pathological Gambling: Component Analysis of Variables Related to Pathological Gambling. International Gambling Studies, 8, 281–298.

    Article  Google Scholar 

  • Turner, N. E., Ialomiteanu, A., Paglia-Boak, A., & Adlaf, E. M. (2011). A Typological Study of Gambling and Substance Use Among Adolescent Students. Journal of Gambling Issues, 25, 88–107. doi:10.4309/jgi.2011.25.7.

    Article  Google Scholar 

  • Turner, N. E., Paglia-Boak, A., Ballon, B., Cheung, J. T. W., Adlaf, E. M., Henderson, J., Chan, V., Rehm, J., Hamilton, H., & Mann, R. E. (2012). Prevalence of Problematic Video Gaming Among Ontario Adolescents. International Journal of Mental Health and Addiction, 10, 877–889. doi:10.1007/s11469–11012–19382–11465.

    Article  Google Scholar 

  • Van Rooij, A. J., Schoenmakers, T. M., Vermulst, A. A., van den Eijnden, R. J. J. M., & van de Mheen, D. (2010). Online Video Game Addiction: Identification of Addicted Adolescent Gamers. Addiction, 106, 205–212. doi:10.1111/j.1360–0443.2010.03104.x.

    Article  PubMed  Google Scholar 

  • Vermunt, J. K. (2008). Latent Class and Finite Mixture Models for Multilevel Data Sets. Statistical Methods in Medical Research, 17, 33–51.

    Article  PubMed  Google Scholar 

  • Vermunt, J. K., & Magidson, J. (2002). Latent Class Cluster Analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied Latent Class Analysis (pp. 89–106). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • World Health Organization. (2011). BMI Classification. Retrieved September 27, 2013, from http://apps.who.int/bmi/index.jsp?introPage=intro_3.html.

Download references

Acknowledgments

Preparation of this work was funded in part by ongoing support from the Ontario Ministry of Health and Long Term Care. We would like to thank all the schools and students that participated in the study, and the Institute for Social Research at York University for assistance with the survey design and data collection.

Conflict of Interest

The authors do not have a financial relationship with the organization that sponsored the research. Guy Faulkner, Hyacinth Irving, Edward Adlaf and Nigel Turner declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Faculty of Kinesiology and Physical Education, University of Toronto, 55 Harbord Street, Toronto, ON, Canada, M5S 2W6

    Guy Faulkner

  2. Centre for Addiction and Mental Health, Toronto, Canada

    Guy Faulkner, Hyacinth Irving, Edward M. Adlaf & Nigel Turner

  3. Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

    Edward M. Adlaf & Nigel Turner

  4. Department of Psychiatry, University of Toronto, Toronto, Canada

    Edward M. Adlaf

Authors
  1. Guy Faulkner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hyacinth Irving
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Edward M. Adlaf
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nigel Turner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guy Faulkner.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Faulkner, G., Irving, H., Adlaf, E.M. et al. Subtypes of Adolescent Video Gamers: a Latent Class Analysis. Int J Ment Health Addiction 13, 1–18 (2015). https://doi.org/10.1007/s11469-014-9501-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11469-014-9501-6

Keywords

Search

Navigation