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

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.

Research Questions 1.What are the comparative demographic and health characteristics of Internet versus land-based gamblers? 2.What demographic characteristics are predictive of Internet gambling? 3.What are the game play patterns and preferences of Internet gamblers? 4.What are the comparative gambling expenditures of Internet versus land-based gamblers? 5.What is the comparative rate of problem gambling among Internet versus land-based gamblers? 6.What factors are predictive of Internet and problem-Internet gambling?

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

Data Collection  Questionnaires asked about: 1.Land-based gambling activity (i.e. time, expenditure, game preference) 2.Internet gambling activity 3.Stock market speculation 4.Definitions of gambling (i.e. which activities constitute gambling) 5.Gambling attitudes (i.e. morality, legality, social harm) 6.Gambling knowledge and beliefs (i.e. fallacies, knowledge of odds) 7.Problem gambling (CPGI, SOGS, NODS)  Online questionnaire provided additional interactive feedback: 1.Graph comparisons to other gamblers, regarding gambling attitudes, knowledge / beliefs, propensity for problem gambling, and projected expenditures. 2.Online treatment resources for problem gamblers.

Weighting Procedure  Canadian RDD sample was weighted by: 1.provincial size 2.household size 3.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.

Canadian Phone Survey International Online Survey % Male82.4%84.8% Age Educational Level Household Income Gambling Attitude Score Gambling Fallacies Score # Gambling Types Played Net Win/Loss Monthly Average-$ $ Net Win/Loss Monthly Median-$89.00-$ CPGI Total Demographic Characteristics and Gambling Behaviour of Canadian Internet Gamblers from both the Telephone and Online Surveys (Unweighted)

Demographic Characteristics and Gambling Behaviour of Canadian Internet Gamblers from both the Telephone and Online Surveys (Weighted) Canadian Phone Survey International Online Survey % Male82.4%85.9% Age Educational Level Household Income Gambling Attitude Score Gambling Fallacies Score # Gambling Types Played Net Win/Loss Monthly Average-$ $ Net Win/Loss Monthly Median-$89.00-$90.00 CPGI Total1.62

Demographic Characteristics Internet GamblersNon-Internet Gamblers Gender Male78%Male58% Female22%Female42%

Demographic Characteristics Internet GamblersNon-Internet Gamblers Age (%) < 180.4< Average45.7Average51.2

Demographic Characteristics Internet GamblersNon-Internet Gamblers Marital Status (%) Married53.2Married61.9 Living with partner13.3Living with partner8.6 Widowed2.1Widowed3.7 Divorced or separated11.8Divorced or separated11.6 Never Married19.6Never married14.2

Demographic Characteristics Internet GamblersNon-Internet Gamblers Education (%) Less than high school 4.3 Less than high school 5.5 Completed high school 18.2 Completed high school 19.7 Some technical school/college/ university 28.4 Some technical school/college/ university 26.9 Completed technical school 8.0 Completed technical school 8.1 Completed college/university 30.2 Completed college/university 27.8 Professional or graduate degree 11.0 Professional or graduate degree 11.9

Demographic Characteristics Internet GamblersNon-Internet Gamblers Employment (%) Employed full-time62.7Employed full-time58.0 Employed part-time 7.0 Employed part-time 6.3 Homemaker3.4Homemaker3.9 Unemployed and seeking work 2.4 Unemployed and seeking work 4.7 Retired16.6Retired22.6 Student4.4Student1.8 Disability/Leave/ Strike 3.5 Disability/Leave/ Strike 2.6

Demographic Characteristics Internet GamblersNon-Internet Gamblers Household Income (%) Less than $29,999 US21.5Less than $29,999 US20.8 $30,000 - $49,999 US19.0$30,000 - $49,999 US21.5 $50,000 - $69,999 US16.3$50,000 - $69,999 US19.1 $70,000 - $89,999 US14.3$70,000 - $89,999 US13.5 $90,000 - $119,999 US13.2$90,000 - $119,999 US12.8 $120,000 - $149,999 US7.3$120,000 - $149,999 US4.9 More than $150,000 US8.3More than $150,000 US7.5 Average$60,100 USAverage$57,600 US

Demographic Characteristics Internet GamblersNon-Internet Gamblers Household Debt Less than $1,000 US32.3Less than $1,000 US32.4 Median$10,000 USMedian$14,000 US Average$76,728 USAverage$66,948 US

Demographic Characteristics Internet GamblersNon-Internet Gamblers Ethnicity (%) Aboriginal, Inuit, Métis 2.1 Aboriginal, Inuit, Métis 1.6 African2.4African2.8 Asian (Eastern)1.5Asian (Eastern)2.4 Asian (Southern)1.0Asian (Southern)1.0 European (Eastern)17.7European (Eastern)20.0 European (Western) 63.1 European (Western) 56.4 Latin American3.0Latin American2.6 Other9.2Other13.1

Health Characteristics Internet GamblersNon-Internet Gamblers Substance Use (%) Past month tobacco use44.3Past month tobacco use33.1 Past month alcohol use72.9Past month alcohol use66.4 Past month other drug use 11.7 Past month other drug use 5.5 Addictions (%) History of substance abuse or dependence 22.5 History of substance abuse or dependence 19.5 History of other addictions 23.6 History of other addictions 29.6 Health (%) Past year serious mental health problem 10.3 Past year serious mental health problem 10.6 Physical disability or chronic health problem that limits activity 14.9 Physical disability or chronic health problem that limits activity 15.0

Advantages of Gambling on the Internet Advantage Internet Gamblers (%) 24 hour availability/convenience56.5 Don’t have to drive / leave the house50.8 More physically comfortable23.3 Lower secondary costs (travel, food, drinks)23.1 No crowds22.5 Greater privacy / anonymity22.3 No unpleasant people20.5 Better game experience18.4 Less smoke16.9 Less noise16.5 Land-based gambling unavailable or illegal14.0 Able to smoke12.5 Higher payout rates7.6 Other4.3

Disadvantages of Gambling on the Internet Disadvantage Internet Gamblers (%) Difficulty verifying fairness of games36.1 Worry about monetary deposits being safe / having wins paid out in timely fashion 25.4 Lack of face-to-face contact makes betting more difficult25.3 Illegality18.9 Poorer social atmosphere (no crowds, too isolating)18.5 Easier to spend more money18.5 Poorer game experience17.5 Too convenient16.3 Poorer physical atmosphere (lacks the lights and noise of a real casino, etc.) 15.9 Have to use credit cards rather than cash13.0 More addictive11.7 Difficulty excluding underage gamblers9.0 Other2.8

Past Year Involvement Game Internet Gamblers (%) Non-Internet Gamblers (%) Lotteries Instant Win Games of Skill against other Individuals EGMs Casino Table Games Sports Betting Horse & Dog Racing Bingo Average Number of Games Played4.12.6

Weekly Involvement Game Internet Gamblers (%) Non-Internet Gamblers (%) Games of Skill against other Individuals Lotteries Sports Betting Instant Win EGMs Horse & Dog Racing Casino Table Games Bingo3.90.6

Percentage of Gambling, by Game Type, Conducted on the Internet Game Internet Gamblers (%) Sports Betting65.9 Games of Skill60.0 Horse & Dog Racing57.9 Bingo43.5 Lotteries34.3 CasinosN/A

Comparative Net Monthly Gambling Expenditures Game Internet Gamblers Non- Internet Gamblers Casino table games-$ $ EGMs-$94.37-$70.55 Sports betting-$39.47-$14.45 Horse and dog racing-$35.71-$24.69 Games of skill (includes poker)-$35.21+$9.13 Bingo-$30.57-$20.78 Lottery ticket purchases-$28.05-$13.48 Instant win tickets-$13.22-$8.17 Total Expenditure Average-$ $70.93 Total Expenditure Median-$80.00-$19.26

Rates of Problem Gambling CPGI Category Internet Gamblers (%) Non- Internet Gamblers (%) Non-problem gambler At-risk gambler Moderate problem gambler Severe problem gambler Average CPGI score

Types of Gambling Perceived to Contribute Most to Problem Game Internet Problem Gamblers (%) Non-Internet Problem Gamblers (%) Slot Machines Poker Internet Gambling11.30 Blackjack Roulette Instant Win Tickets Horse/Dog Racing4.30 High Risk Stocks Lotteries Games of skill against other people1.70 Video Lottery Terminals Bingo Baccarat Electronic Keno Other6.13.8

Help Seeking for Problem Gambling Internet Gamblers (%) Non-Internet Gamblers (%) Ever sought help for problems? Yes No Where did you seek help from? Gamblers Anonymous Counseling Service17.90 Friends Psychologist10.70 Psychiatrist10.70 Family Doctor7.10 Family7.10 Pastor/Minister/Priest7.10 Telephone help/hot line7.10 If you were to seek help where would you be most comfortable seeking it from? Face-to-face counseling Internet counseling

Logistic Regression  Characteristics statistically differentiating Internet gamblers from non-Internet gamblers. o A test of the full model with all 22 predictors against a constant-only model was statistically significant, χ 2 (40) = , p < o Variance accounted for was moderate, with Nagelkerke R squared = 33.4%. o Overall prediction success was 72.8%, with 71.0% of Non-Internet Gamblers correctly classified, and 74.5% of Internet Gamblers correctly classified.

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.

Logistic Regression  Characteristics statistically differentiating Internet problem gamblers from Internet non-problem gamblers. o A test of the full model with all 21 predictors against a constant-only model was statistically significant, χ 2 (39) = 725.8, p < o Variance accounted for was moderate, with Nagelkerke R -squared = 35.0%. o 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.

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.

Perceived Usefulness of Normative Feedback All Participants % Internet Gamblers % Non-Internet Gamblers % Problem Gamblers % Non-Problem Gamblers % How useful was the information we provided? Not at all useful Not very useful Somewhat useful Very useful

Expected Future Change in Gambling Behaviour All Participants % Internet Gamblers % Non-Internet Gamblers % Problem Gamblers % Non-Problem Gamblers % What changes do you expect in your gambling behaviour in the next couple of months? I expect it to decrease I expect no change I expect it to increase

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.

Recent Relevant Publications 1.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. =s =s 2.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): 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: 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 ). Toronto: Elsevier Publishing.

Researcher Contact Info: Dr. Robert Wood Department of Sociology Phone: (403) Dr. Robert Williams School of Health Sciences Phone: (403) University of Lethbridge 4401 University Drive Lethbridge, AB T1K 3M4, Canada