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Internet Gambling in Comparative Perspective: Patterns, Problems, and Interventions

Internet Gambling in Comparative Perspective: Patterns, Problems, and Interventions. Dr. Robert Wood & Dr. Robert Williams University of Lethbridge. Current Study.

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Internet Gambling in Comparative Perspective: Patterns, Problems, and Interventions

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  1. Internet Gambling in Comparative Perspective:Patterns, Problems, and Interventions Dr. Robert Wood & Dr. Robert Williams University of Lethbridge

  2. Current Study • Funded by a three-year grant from the Ontario Problem Gambling Research Centre (final research report now published on OPGRC website). • Preliminary descriptive results presented at AGRI 2008 conference. • The present study seeks to overcome past limitations by generating a sample that is large, and also weighted for representativeness. • Moreover, our study is based on a sample of both Internet and non-Internet gamblers, thereby allowing direct and systematic comparison of the two groups.

  3. Research Questions • What are the comparative demographic and health characteristics of Internet versus land-based gamblers? • What demographic characteristics are predictive of Internet gambling? • What are the game play patterns and preferences of Internet gamblers? • What are the comparative gambling expenditures of Internet versus land-based gamblers? • What is the comparative rate of problem gambling among Internet versus land-based gamblers? • What factors are predictive of Internet and problem-Internet gambling?

  4. Data Collection • Two-phased approach to data collection. • Random digit dial survey of Canadian adults. • Managed by Institute for Social Research, at York University. • Adults surveyed from all 10 provinces (January 2006 to June 2007). • Response rate of 46% (completions over eligible respondents). • N = 8,498. • 70.7% gamblers, and 2.1 % Internet gamblers (N = 179). • Online, self-selected survey of gamblers. • Survey hosted at www.gamblinginformation.org, in seven languages. • Banner ad-links placed at www.casinocity.com gambling portal. • 2 million exposures, from June 2007 to December 2007. • 7,921 gamblers, including 1,954 Internet gamblers • 76% of respondents from, USA and 10% from Canada (105 countries represented in total).

  5. Data Collection • Questionnaires asked about: • Land-based gambling activity (i.e. time, expenditure, game preference) • Internet gambling activity • Stock market speculation • Definitions of gambling (i.e. which activities constitute gambling) • Gambling attitudes (i.e. morality, legality, social harm) • Gambling knowledge and beliefs (i.e. fallacies, knowledge of odds) • Problem gambling (CPGI, SOGS, NODS) • Online questionnaire provided additional interactive feedback: • Graph comparisons to other gamblers, regarding gambling attitudes, knowledge / beliefs, propensity for problem gambling, and projected expenditures. • Online treatment resources for problem gamblers.

  6. Weighting Procedure • Canadian RDD sample was weighted by: • provincial size • household size • age by gender. • Canadian subset of the International online sample was weighted, such that it became more congruent with the Canadian RDD sample. • The same weighting was then applied to the entire International online sample.

  7. Demographic Characteristics and Gambling Behaviour of Canadian Internet Gamblers from both the Telephone and Online Surveys (Unweighted)

  8. Demographic Characteristics and Gambling Behaviour of Canadian Internet Gamblers from both the Telephone and Online Surveys (Weighted)

  9. Demographic Characteristics

  10. Demographic Characteristics

  11. Demographic Characteristics

  12. Demographic Characteristics

  13. Demographic Characteristics

  14. Demographic Characteristics

  15. Demographic Characteristics

  16. Demographic Characteristics

  17. Health Characteristics

  18. Advantages of Gambling on the Internet

  19. Disadvantages of Gambling on the Internet

  20. Past Year Involvement

  21. Weekly Involvement

  22. Percentage of Gambling, by Game Type, Conducted on the Internet

  23. Comparative Net Monthly Gambling Expenditures

  24. Rates of Problem Gambling

  25. Types of Gambling Perceived to Contribute Most to Problem

  26. Help Seeking for Problem Gambling

  27. Logistic Regression • Characteristics statistically differentiating Internet gamblers from non-Internet gamblers. • A test of the full model with all 22 predictors against a constant-only model was statistically significant, χ2 (40) = 3223.6, p < .0001. • Variance accounted for was moderate, with Nagelkerke R squared = 33.4%. • Overall prediction success was 72.8%, with 71.0% of Non-Internet Gamblers correctly classified, and 74.5% of Internet Gamblers correctly classified.

  28. Significant Predictors of Internet Gambling • Greater number of gambling formats. • Higher CPGI score • Male gender. • Living in Hungary, United Kingdom, Italy, Canada, Switzerland, or Costa Rica • Tobacco use. • Fewer gambling fallacies. • Being employed. • Younger age. • More positive attitudes toward gambling. • Higher gambling expenditure. • Not being Asian. • Never married (single). • Alcohol use. • Illicit drug use. • Higher household income.

  29. Logistic Regression • Characteristics statistically differentiating Internet problem gamblers from Internet non-problem gamblers. • A test of the full model with all 21 predictors against a constant-only model was statistically significant, χ2 (39) = 725.8, p < .0001. • Variance accounted for was moderate, with Nagelkerke R -squared = 35.0%. • Overall prediction success was 73.7%, with 77.1% of Internet problem gamblers correctly classified and 70.4% of Internet non-problem gamblers correctly classified.

  30. Significant Predictors of Internet Problem Gambling • Gambling on a greater number of gambling formats. • Higher gambling expenditure. • Having mental health problems. • Family history of problem gambling. • Asian ancestry. • Single (never married). • Lower household income. • More gambling fallacies. • Negative attitudes toward gambling. • History of other addictions.

  31. Perceived Usefulness of Normative Feedback

  32. Expected Future Change in Gambling Behaviour

  33. Open-Ended Comments • “This was a good site for me, I am going through gambling withdrawal…. this site reinforced what bad shape I am in.” • “It was a great insight into a problem that I wasn’t even aware that I had.” • “A wake-up call.” • “I think your survey is skewed to be against gambling.” • “I do not think that I have a problem, even a minor problem.” • What if I am a professional gambler? You are still telling me I have a problem! I will have a problem if I don’t gamble, because that’s the way I make a living.

  34. Recent Relevant Publications Wood, Robert T. and Robert J. Williams. (2009). Internet Gambling: Prevalence, Patterns, Problems, and Policy Options. Final research report prepared for the Ontario Problem Gambling Research Centre. http://www.gamblingresearch.org/contentdetail.sz?cid=2973&pageid=1813&r=s Wood, Robert T. and Robert J. Williams. (2007). “Problem Gambling on the Internet: Implications for Internet Gambling Policy in North America.” New Media & Society, 9(3):169-191. Wood, Robert T, Robert J. Williams, Paul K. Lawton. (2007). “Why Do Internet Gamblers Prefer Online Versus Land-Based Venues? Some Preliminary Findings and Implications.” Journal of Gambling Issues, 20: 235-252. Wood, Robert T. & Robert J. Williams (2007). "Internet Gambling: Past, Present, and Future." In Gary Smith, David Hodgins & Robert Williams (eds.), Research and Measurement Issues in Gambling Studies (pp. 491-514). Toronto: Elsevier Publishing.

  35. Dr. Robert Wood Department of Sociology Phone: (403) 329-5137 Email: robert.wood@uleth.ca Dr. Robert Williams School of Health Sciences Phone: (403) 382-7128 Email: robert.williams@uleth.ca Researcher Contact Info: University of Lethbridge 4401 University Drive Lethbridge, AB T1K 3M4, Canada

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