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Research Article

Assessing severity of problem gambling – confirmatory factor and Rasch analysis of three gambling measures

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Pages 403-417 | Received 09 Mar 2022, Accepted 13 Nov 2022, Published online: 07 Dec 2022

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).
  • Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97(5), 487–499. https://doi.org/10.1046/j.1360-0443.2002.00015.x
  • Bond, T. G., & Fox, C. M. (2013). Applying the Rasch model: Fundamental measurement in the human sciences. Psychology Press.
  • Bowen, N. K., & Guo, S. (2011). Structural equation modeling. Oxford University Press.
  • Calado, F., & Griffiths, M. D. (2016). Problem gambling worldwide: An update and systematic review of empirical research (2000-2015). Journal of Behavioral Addictions, 5(4), 592–613. ( PubMed). https://doi.org/10.1556/2006.5.2016.073
  • Cappelleri, J. C., Lundy, J. J., & Hays, R. D. (2014). Overview of classical test theory and item response theory for quantitative assessment of items in developing patient-reported outcome measures. Clinical Therapeutics, 36(5), 648–662. https://doi.org/10.1016/j.clinthera.2014.04.006
  • Christensen, D. R., Williams, R. J., & Ofori Dei, S. M. (2019). The multidimensional structure of problem gambling: An evaluation of four gambling categorization instruments from an international online survey of gamblers. Journal of Gambling Studies, 35(4), 1079–1108.
  • Cowlishaw, S., Merkouris, S. S., Dowling, N. A., Rodda, S., Suomi, A., & Thomas, S. L. (2019). Locating gambling problems across a continuum of severity: Rasch analysis of the quinte longitudinal study (QLS). Addictive Behaviors, 92, 32–37. https://doi.org/10.1016/j.addbeh.2018.12.016
  • Enders, C. K., Mistler, S. A., & Keller, B. T. (2016). Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation. Psychological Methods, 21(2), 222. https://doi.org/10.1037/met0000063
  • Ferris, J., & Wynne, H. (2001). The Canadian problem gambling index: Final report.
  • Gerstein, D., Volberg, R. A., Toce, M., Harwood, H., Johnson, R., Buie, T., Christiansen, E., Chuchro, L., Cummings, W., & Engelman, L. (1999). Gambling impact and behavior study: Report to the national gambling impact study commission. National Opinion Research Center.
  • Hodgins, D. C. (2004). Using the NORC DSM screen for gambling problems as an outcome measure for pathological gambling: Psychometric evaluation. Addictive Behaviors, 29(8), 1685–1690. https://doi.org/10.1016/j.addbeh.2004.03.017
  • Holtgraves, T. (2009). Evaluating the problem gambling severity index. Journal of Gambling Studies, 25(1), 105. https://doi.org/10.1007/s10899-008-9107-7
  • Kang, H. (2013). The prevention and handling of the missing data. Korean Journal of Anesthesiology, 64(5), 402–406. https://doi.org/10.4097/kjae.2013.64.5.402
  • Linacre, J. M. (2002). What do infit and outfit, mean-square and standardized mean?. Rasch Measurement Transactions, 16(2), 878.
  • Merkouris, S. S., Greenwood, C., Manning, V., Oakes, J., Rodda, S., Lubman, D., & Dowling, N. A. (2020). Enhancing the utility of the problem gambling severity index in clinical settings: Identifying refined categories within the problem gambling category. Addictive Behaviors, 103, 106257. https://doi.org/10.1016/j.addbeh.2019.106257
  • Miller, N. V., Currie, S. R., Hodgins, D. C., & Casey, D. (2013). Validation of the problem gambling severity index using confirmatory factor analysis and rasch modelling. International Journal of Methods in Psychiatric Research, 22(3), 245–255. https://doi.org/10.1002/mpr.1392
  • Molander, O., Volberg, R., Sundqvist, K., Wennberg, P., Månsson, V., & Berman, A. H. (2019). Development of the gambling disorder identification test (G-DIT): Protocol for a delphi method study. JMIR Research Protocols, 8(1), e12006. https://doi.org/10.2196/12006
  • Molander, O., Wennberg, P., & Berman, A. H. (2021). The gambling disorders identification test (GDIT): Psychometric evaluation of a new comprehensive measure for gambling disorder and problem gambling. Assessment, 10731911211046044. https://doi.org/10.1177/10731911211046045
  • Molde, H., Hystad, S. W., Pallesen, S., Myrseth, H., & Lund, I. (2010). Evaluating lifetime NODS using Rasch modelling. International Gambling Studies, 10(2), 189–202.
  • Orford, J., Wardle, H., Griffiths, M., Sproston, K., & Erens, B. (2010). PGSI and DSM-IV in the 2007 British gambling prevalence survey: Reliability, item response, factor structure and inter-scale agreement. International Gambling Studies, 10(1), 31–44. https://doi.org/10.1080/14459790903567132
  • Petry, N. M., Blanco, C., Stinchfield, R., & Volberg, R. (2013). An empirical evaluation of proposed changes for gambling diagnosis in the DSM-5. Addiction, 108(3), 575–581. https://doi.org/10.1111/j.1360-0443.2012.04087.x
  • R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
  • Toce-Gerstein, M., Gerstein, D. R., & Volberg, R. A. (2003). A hierarchy of gambling disorders in the community. Addiction, 98(12), 1661–1672. https://doi.org/10.1111/j.1360-0443.2003.00545.x
  • Wickwire, E. M., Burke, R. S., Brown, S. A., Parker, J. D., & May, R. K. (2008). Psychometric evaluation of the national opinion research center DSM-IV screen for gambling problems (NODS). American Journal on Addictions, 17(5), 392–395. https://doi.org/10.1080/10550490802268934
  • Williams, R. J., & Volberg, R. A. (2013). The classification accuracy of four problem gambling assessment instruments in population research. International Gambling Studies, 14(1), 1–14. https://doi.org/10.1080/14459795.2013.839731
  • Williams, R. J., Volberg, R. A., & Stevens, R. M. G. (2012). The population prevalence of problem gambling: Methodological influences, standardized rates, jurisdictional differences, and worldwide trends [Technical Report]. Ontario Problem Gambling Research Centre. https://opus.uleth.ca/handle/10133/3068
  • Wilson, M. (2004). Constructing measures: An item response modeling approach: An item response modeling approach. Routledge. https://doi.org/10.4324/9781410611697
  • Wind, S., & Hua, C. (2021). Rasch measurement theory analysis in R: Illustrations and practical guidance for researchers and practitioners. Bookdown. org,[Epub].
  • Wright, B. D., & Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8(3), 370.