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Title
Abstract
Method
Results
Factor Analysis of Gambling Frequency
Discussion
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Medicine and Health Sciences
Medical Sciences

Gambling, gambling activities, and problem gambling

Profile image of Thomas HoltgravesThomas Holtgraves

2009, Psychology of Addictive Behaviors

https://doi.org/10.1037/A0014181
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Abstract

This research examined similarities and differences between gambling activities, with a particular focus on differences in gambling frequency and rates of problem gambling. The data were from populationbased surveys conducted in Canada between 2001 and 2005. Adult respondents completed various versions of the Canadian Problem Gambling Index (CPGI), including the Problem Gambling Severity Index (PGSI). A factor analysis of the frequency with which different gambling activities were played documented the existence of two clear underlying factors. One factor was comprised of Internet gambling and betting on sports and horse races, and the other factor was comprised of lotteries, raffles, slots/Video Lottery Terminals (VLTs), and bingo. Factor one respondents were largely men; factor two respondents were more likely to be women and scored significantly lower on a measure of problem gambling. Additional analyses indicated that (1) frequency of play was significantly and positively related to problem gambling scores for all activities except raffles, (2) the relationship between problem gambling scores and frequency of play was particularly pronounced for slots/VLTs, (3) problem gambling scores were associated with playing a larger number of games, and (4) Internet and sports gambling had the highest conversion rates (proportion who have tried an activity who frequently play that activity).

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References (34)

  1. Anderson, G., & Brown, R. (1984). Real and laboratory gambling: Sensation-seeking and arousal. British Journal of Psychology, 75, 401- 410.
  2. Bagby, R. M., Vachon, D., Bulmash, E. L., Toneatto, T., Quilty, L. C., & Costa, P. T. (2007). Pathological gambling and the five-factor model of personality. Personality and Individual Differences, 43, 873-880.
  3. Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97, 487-499.
  4. Breen, R. B., & Zimmerman, M. (2002). Rapid onset of pathological gambling in machine gamblers. Journal of Gambling Studies, 18, 31-43.
  5. Cameron, B., & Myers, J. (1966). Some personality correlates of risk taking. The Journal of General Psychology, 74, 51-60.
  6. Dowling, N., Smith, D., & Thomas, T. (2005). Electronic gaming ma- chines: Are they the "crack cocaine" of gambling? Addiction, 100, 33-45.
  7. Ferris, J., & Wynne, H. (2001). The Canadian problem gambling index: Final report. Ottawa: Canadian Centre on Substance Abuse.
  8. Gemini Research (1994). Social gaming and problem gambling in British Columbia. Report to the British Columbia Lottery Corporation. Northampton, MA: Author.
  9. Gilley, W. F., & Uhlig, G. E. (1993). Factor analysis and ordinal data. Education, 14, 258 -264.
  10. Griffiths, M. D. (1993). Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies, 9, 101-120.
  11. Griffiths, M. D. (1999). Gambling technologies: Prospects for problem gambling. Journal of Gambling Studies, 15, 265-283.
  12. Holtgraves, T. (1988). Gambling as self-presentation. Journal of Gambling Behavior, 4, 78 -91.
  13. Holtgraves, T. (in press). Evaluating the Problem Gambling Severity Index. Journal of Gambling Studies.
  14. Ipsos-Reid & Gemini Research. (2003). British Columbia problem gam- bling prevalence study. Victoria, BC: Ministry of Public Safety and Solicitor General.
  15. Joreskog, K. G., & Moustaki, I. (2000). Factor analysis of ordinal vari- ables: A comparison of three approaches. Multivariate Behavioral Re- search, 36, 347-387.
  16. Kessler, R. C., Hwang, I., LaBrie, R., Petukhova, M., Sampson, N. A., Winters, K. C., et al. (2008). The prevalence and correlates of DSM-IV pathological gambling in the national comorbidity survey replication. Psychological Medicine, 38, 1351-1360.
  17. Kuley, N. B., Jacobs, D. F. (1988). The relationship between dissociative- like experiences and sensation seeking among social and problem gam- blers. Journal of Gambling Behavior, 4, 197-207.
  18. Ladd, G. T., & Petry, N. M. (2002). Disordered gambling among university-based medical and dental patients: A focus on Internet gam- bling. Psychology of Addictive Behaviors, 16, 76 -79.
  19. Ladouceur, R., & Mayrand, M. (1984). Evaluation of the "illusion of control": Type of feedback, outcome sequence, and number of trials among regular and occasional gamblers. Journal of Psychology, 117, 37-46.
  20. Market Quest Research Group Inc. (2005). Newfoundland and Labrador gambling prevalence study. Prepared for the Department of Health and Community Services. St. John's, Newfoundland: Government of New- foundland and Labrador.
  21. Mizerski, D., Jolley, B., & Mizerski, K. (2002). Disputing the "crack cocaine of gambling" label for electronic gaming machines. In A. Blaszczynski (Ed.), Culture and the gambling phenomenon. Proceedings of the 11th Conference of the National Association of Gambling Studies (pp. 276 -283). Melbourne, Australia: National Association for Gam- bling Studies.
  22. Patton, D., Brown, D., Dhaliwal, J., Pankratz, C., & Broszeit, B. (2002). Gambling involvement and problem gambling in Manitoba. Manitoba, Canada: Addictions Foundation of Manitoba.
  23. Petry, N. M. (2003). A comparison of treatment-seeking pathological gamblers based on preferred gambling activity. Addiction, 98, 645-655.
  24. Productivity Commission. (1999). Australia's gambling industries. Can- berra, Australia: AusInfo.
  25. Shaffer, H. J., M. N. Hall, & J. Vander Bilt. (1997). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A meta-analysis. Boston, MA: Harvard Medical School Divi- sion on Addictions.
  26. Slowo, D. (1998). Are all gamblers the same? An exploration of person- ality and motivational characteristics of individuals with different gam- bling preferences. In G. Coman, B. Evans, & R. Wooten (Eds.), Respon- sible gambling: A future winner. Proceedings of the 8th conference of the National Association for Gambling Studies (pp. 339 -351). Adelaide: National Association for Gambling Studies.
  27. Slutske, W. S., Caspi, A., Moffitt, T. E., & Poulton, R. (2005). Personality and problem gambling: A prospective study of a birth cohort of young adults. Archives of General Psychiatry, 52, 769 -775.
  28. Smith, G. J., & Wynne, H. J. (2004). VLT Gambling in Alberta: A preliminary analysis. Retrieved December 16, 2007, from https:// dspace.ucalgary.ca/bitstream/1880/1632/1/VLT_Gambling_Alberta.pdf
  29. Smith, G. J., & Wynne, H. J. (2002). Measuring gambling and problem gambling in Alberta using the Canadian Problem Gambling Index (CPGI): Final report. Edmonton: Alberta Gaming Research Institute.
  30. Volberg, R. A. (1997). Gambling and problem gambling in Oregon. Report to the Oregon Gambling Addiction Treatment Foundation. Retrieved Decem- ber 16, 2007, from http://www.gamblingaddiction.org/oregonreport/ OregonReportPrint.htm
  31. Wiebe, J., Mun, P., & Kauffman, N. (2006). Gambling and problem gambling in Ontario 2005. Toronto: Responsible Gambling Council (Ontario).
  32. Wiebe, J., Single, E., & Falkowski-Ham, A. (2001). Measuring gambling and problem gambling in Ontario. Toronto: Canadian Centre on Sub- stance Abuse and Responsible Gambling.
  33. Wong, I. L., & So, E. M. (2003). Prevalence estimates of problem and pathological gambling in Hong Kong. American Journal of Psychiatry, 160, 1353-1354.
  34. Wynne, H. J. (2002). Gambling and problem gambling in Saskatchewan. Ottawa: Canadian Center on Substance Abuse.

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