Online Gambling Technological vs. Social Students

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1 Ph.D. program included on the gambling addiction research line at CEIA Online Gambling Technological vs. Social Students Online gambling among university students: Characterization and comparison between technological and social sciences Rui Magalhães 1, Henrique Lopes 2 and Jeffrey Derevensky 3 1 Ph.D. Student at ISCTE Lisbon University Institute, Portugal 2 Ph.D. Supervisor, Director of R&D Centre CEIA, Lisbon, Portugal 3 Professor, McGill University, Canada 9th European Conference on Gambling Studies and Policy Issues, 2012

2 Gambling in Portugal: Background Legal gambling: 11 private Casinos State monopoly for Lotteries Small bingo expression Non legal gambling: Big online gambling expression Huge sales of other gambling Revenues: 10 millions inhabitants 70% per capita GNP of the average EU University students with similar cultural patterns of Western Europe Legal millions Non legal (projected) between 600 and 1,000 millions Between 0,3% - 0,9% gambling addicted (depending on the age group)

3 Gambling Addiction research line CEIA / UCP Calibration of gambling evaluation tools for language and culture. National epidemiology of adult population Gambling Addiction Social Knowledge. Working paper phase Epidemiology of University students. Ph.D. work. Behavior of online gamblers. Field phase. National epidemiology of High School students. Field phase

4 Portuguese Online Gambling Market 408 online gambling sites (including online casinos and online poker rooms) 22 jurisdictions (Top: Malta; Netherlands Antilles; Gibraltar) 135 online payment methods (Top: Visa and MasterCard) source: Casino City - Sept millions EUR (2009/10), sports/race bets, casinos and poker with the large share of revenue (2002: 2,2 millions EUR ; 2012 e 81,1 millions EUR). Market Share 4-5% of the Portuguese gambling market (2003: 0,2%; 2012e: 6,1%) source: H2GC- Mai 2012

5 Epidemiology of University students. Ph.D. work. Working Paper main topics Internet gambling prevalence rate Demographic characteristics of the online gamblers Online gamblers patterns and preferences Internet gambling behaviors Online problem gamblers

6 Research Problem Understanding the behaviors and different characteristics of university students in technological sciences and social sciences who are online gamblers

7 Method Sample Technological Sciences Social Sciences Total Population (y) Valid Answers (n) University Students n = n og = 82 Technological Sciences n TS = Social Sciences n SS = 160

8 Method Tool Application of an online survey (structure-sections): 1.Internet/Online gambling (CTS) 2.Pathological Gambling (SOGS PT version) 3.Demographics (PPGM)

9 Research Hypotheses H1: Statistically different characteristics between Internet gamblers and non-internet gamblers H2: Dependency relationship between online gambling prevalence rates and the study area H3: Dependency relationship between online problem gambling and the study area H4: Relationship between intensity of Internet usage and frequency of online gambling H5: Relationship between intensity of Internet usage and online problem gambling H6: Differences between the online gambling average monthly expenditure of the technological science university students and the online gambling average monthly expenditure of the social sciences university students

10 Results Online Gambling Prevalence Rate 1,5% Online Gambling Social Knowledge 5,5% Online Gambling PROBLEM Prevalence Rate (Univ. Students): Pathological Gamblers 0,7% At Risk Gamblers 1,5% Online Gambling PROBLEM Prevalence Rate (U. Students Gamblers): Pathological Gamblers 12,2% At Risk Gamblers 26,8% Social Science University students that indicated having migrated from traditional casino to Internet gambling Social Sciences U. Students Gamblers, that admit that the online gambling practice interfere with their feeding and resting patterns 1:4 1:3

11 Conclusions Internet Gambling Prevalence Rate The prevalence rate and the online gambling consumptions are independent from the study area χ 2 (2, n = 82) = 0,997, p-value = 0,318 The intensity of Internet usage is not significantly correlated with intensity of online gambling r s (2) = 0,015, p-value = 0,894

12 Conclusions Demographic Characteristics of university students online gamblers The characteristics that better predict that an university student is an online gambler are: a) Having high SOGS classification, i.e. being at-risk or a pathological gambler b) Being male c) Being an undergrad student d) Having consumed alcoholic beverages in the last 6 months The observed gamblers have the following demographic characteristics: a) Being male b) Young adults between years old c) Undergraduates d) Family annual declared average income between and

13 Conclusions Gambling Preferences and Patterns of University Student Online Gamblers University students are multifunctional and heavy Internet users The great majority (70,7%) play online games with no money stakes Positive correlations, with moderate association, between the two types of online games (with and without money stakes), especially concerning intensity of gaming and age of beginning. Respective stats: r s = 0,415, p-value = 0,001; r s = 0,340, p-value = 0,011. The online gambling occurs primarily at home, with minimum intensity, during the night, solitarily The majority of the university students began to gamble online, home alone and were self-motivated to initiate this behavior

14 Conclusions Internet gambling and associated behaviors Online poker is the preferred game, followed by sports/race wagering and casino games The majority of university students recognize both advantages and disadvantages of Internet Gambling over traditional land-based forms of gambling Disadvantages where referred by more individuals then the advantages The most commonly identified advantages where the convenience and 24/7 availability The most frequently referred disadvantages included: a) Lack of face-to-face contact; b) Larger odds for gambling addiction problems; c) Difficulty validating the fairness of the games; d) Poorer physical and social environment; e) Concerns about the security of money deposits and effective prize payments The principal vectors on the online gambling site election are Safety and Marketing

15 Conclusions Online Gambling Problem Online gambling problem prevalence rates are dependent on the study area (H3) χ 2 (2, n = 82) = 14,625, p-value = 0,001 Online gambling problem was not found to be significantly correlated with intensity of Internet usage r s (2) = 0,110, p-value = 0,323 There is a positive, but weak, correlation between the online gambling problems and frequency and intensity of Internet gambling r s = 0,242, p-value = 0,028

16 Thank you! Rui Magalhães Henrique Lopes CEIA/ISEC

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