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Gambling activities are rapidly migrating online. Algorithms that effectively detect at-risk users could improve the prevention of online gambling-related harms. We sought to identify machine learning algorithms capable of detecting self-reported gambling problems using demographic and behavioral data. Online gamblers were recruited from all licensed online gambling platforms in France by the French Online Gambling Regulatory Authority (ARJEL). Participants completed the Problem Gambling Severity Index (PGSI), and these data were merged and synchronized with past-year online gambling behaviors recorded on the operators' websites. Among all participants (N = 9,306), some users reported betting exclusively on sports (N = 1,183), horseracing (N = 1,711), or poker (N = 2,442) activities. In terms of Area Under the Receiver Operating Characteristic Curve (AUC), our algorithms showed excellent performance in classifying individuals at a moderate-to-high (PGSI 5+; AUC = 83.20%), or high (PGSI 8+; AUC = 87.70%) risk for experiencing gambling-related harms. Further, these models identified novel behavioral markers of harmful online gambling for future research. We conclude that machine learning can be used to detect online gamblers at-risk for experiencing gambling problems. Using algorithms like these, operators and regulators can develop targeted harm prevention and referral-to-treatment initiatives for at-risk users. [ABSTRACT FROM AUTHOR]

Lotteries are one of the most prevalent forms of gambling and generate substantial state revenues. They are also argued to be one of the least harmful forms of gambling. This paper is one of the first to examine exclusive lottery gamblers and compares their gambling patterns and problems as well other associated risky behaviours to those who are not exclusive lottery gamblers. Data were derived from two large surveys conducted with representative adult samples in France (n = 15,635) and Québec (n = 23,896). Participants were separated into two groups: exclusive lottery gamblers (ELGs) and non-exclusive lottery gamblers. Using multivariate analysis, study results reveal that ELGs, who represent two thirds of gamblers, generally exhibit less intensive gambling patterns and are less likely to report other risky behaviours. However, harms associated with moderate risk and problem gambling are found to be concentrated in specific subpopulations for both groups, primarily males, older individuals, and those who report lower income and education level. Given widespread participation in lotteries and concentration of harm within specific subgroups, these findings point to the need for prevention efforts despite the lower levels of harm associated with lottery gambling. [ABSTRACT FROM AUTHOR]

Few empirical studies have examined the relationships between differing regulatory approaches and patterns of gambling behaviors. This article reports on a correlational cross-cultural comparison of differences in the regulatory approaches and gambling behavior among general adult populations in France and Québec, Canada. We drew data from two large population surveys conducted in France and Québec (N=27 653 and N=11 888, respectively). We found diverging and converging aspects of government regulatory policies. Statistical analyses demonstrated significantly higher participation rates and prevalence of 'assiduous gamblers' in Québec. In France, among assiduous gamblers, the proportion of moderate-risk and probable pathological gamblers is significantly higher. Future research should examine environmental conditions and varying gambling offerings, as well as gambling regulation, to determine their potential influence on gambling behaviors. [ABSTRACT FROM AUTHOR]

In 2010 France enacted a law to regulate supply and consumption of online gambling. Its primary aim was to protect citizens from gambling-related harm. This study aims to assess differences in gambling patterns and related harm between online gamblers who use licensed versus unlicensed sites. Participants (N = 3860) completed a self-administered online survey on gambling practices. Pairwise logistic regressions examined the association between the legal statuses of gambling sites people patronized and demographic variables and gambling types. Multivariate logistic regression models explored associations between gambling patterns and related problems according to the legal status of sites people have gambled on. Overall, 53.7 % of online gamblers report gambling exclusively on licensed sites. Those who bet on regulated activities on unlicensed sites, versus licensed sites, are more likely to be female, younger, less educated, inactive in the labor market and are more likely to perceive their financial situation to be difficult. Gambling on unlicensed sites is associated with more intense gambling patterns and more gambling-related problems compared to licensed sites. Findings demonstrate that gambling activities carried out on state licensed sites are associated with less overall harm to gamblers. Implications of these findings on future policy are discussed and prospective research directions are outlined. [ABSTRACT FROM AUTHOR]