1. Cognitive Distortions as a Major Risk Factor in Online Gambling Terri-Lynn MacKay Addictive Behaviours Laboratory, University of Calgary tlmackay@ucalgary.ca

3. Prevalence General Canada-1.5-3.1% (2007) US-4% (2006) UK-7.2% (2006), 8.8% (2007), 9.7% (2008), 10.6% (2009). Among sub-populations Guest entering a US casino-36.5% Undergraduate US-23% Undergraduate UK-22%

4. Problem Gambling Internet gamblers are more likely to be problem gamblers (Griffiths & Barnes, 2008; Griffiths, Parke, Wood & Rigby, 2009; Griffiths, Wardle, Orford, Sproston & Erens, 2009; Ladd & Petry, 2002; McBride & Derevenski, 2008; Petry, 2006; Petry & Weinstock, 2007; Wood & Williams, 2007, Wood & Williams, 2009) Why? Characteristics of the Internet? People that gamble online possess a number of general risk factors for problem gambling?

5. Why gamble online? Accessibility, convenience, event frequency, money value, and demonstration games (Griffiths). Primary reasons individuals reported for preferring online gaming over land-based gaming were because of the convenience, ease, comfort, accessibility and privacy (Wood, Williams, & Lawton, 2007). Main reasons reported for gambling online were convenience, entertainment, comfort, accessibility, monetary incentive, anonymity and privacy (American Gaming Association, 2006)

7. Risk factors for online gambling (empirical findings) Being male and younger Scoring lower on general health measures (mental and physical) Drinking at least twice the recommended amount in one day

8. Main Research Questions What makes online players more susceptible to problems? Do online gamblers initiate via the Internet or are they land-based gamblers? What factors contribute to problems among online gamblers?

9. Sample, method, analysis 377 undergraduates (46% male) Completed online questionnaire 38.7% online gamblers Significant univariate analyzed via logistic regression Multiple regression analysis for problem gambling level among online gamblers

10. DomainRisk FactorInstrument DemographicAge (younger)CPGI GenderCPGI Ethnicity (Asian)Statistics Canada AcademicGPA Problem GamblingSeverity (higher)CPGI Medium relatedFrequency (higher)CPGI Expenditures (higher)CPGI Age of onsetCPGI Early wins (yes)CPGI CognitiveDistortions (higher)Gambler’s Beliefs Erroneous beliefs (higher) Gambling Fallacies Scale ConcurrentAlcohol abuseAUDIT Drug useDAST DepressionBDI AnxietyLeibowitz Anxiety Scale ImpulsivityBarratt Impulsivity Scale

11. Results Internet gamblers are primarily land-based gamblers who are also using an online medium. The most significant predictors of online gambling are the number of activities (particularly land- based) and cognitive distortions. Cognitive distortions predict severity above and beyond medium related variables.

12. Results (for those who like stats..) The full model correctly classified 76% of gamblers (84% land-based, 63% online). Two variables made independent contributions: number of gambling activities and cognitive distortions. Only 3% of online gamblers began by gambling on the Internet and 13% started both at the same age. When problem gambling severity was analyzed for Internet gamblers with a multiple regression analysis in blocks: demographics (1), play variables (2), cognitive distortions (3) the final model was significant.

14. Next Steps… Collaboration between the U of A Poker Research Group. Looking at skill vs. luck component of poker. Are online players really distorting?

15. BURNING QUESTIONS?