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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.

Euro-Canadians and Chinese typically hold different theories about change; Euro-Canadians often engage in linear thinking whereas Chinese often engage in non-linear thinking. The present research investigated the effects of culture-specific theories of change in two related gambling fallacies: the gambler’s fallacy (GF; the belief that one is due for a win after a run of losses) and the hot-hand fallacy (HHF; the belief that one’s winning streak is likely to continue). In Study 1, participants predicted the outcome of a coin toss following a sequence of tosses. Study 2 involved predicting and betting on the outcome of a basketball player’s shot following a sequence of shots. In Study 1, Asians (mainly Chinese) were significantly more likely than Euro-Canadians to believe that they would win (correctly predict the coin toss) after a series of losses (a non-linear thinking pattern), suggesting greater susceptibility to the gambler’s fallacy. In Study 2, Euro-Canadians were more likely than Chinese to predict outcomes consistent with a basketball player’s streaks (a linear thinking pattern), suggesting greater susceptibility to the hot hand fallacy. By illustrating the role of cultural differences in cognition, these findings contribute to our understanding of why certain cultural groups, such as Chinese, are more susceptible to gambling.

Regulatory policies for responsible gambling practices in Asia are constantly evolving as the gambling industry and technological landscape change over time. Malaysia makes an interesting case study for a commentary on gambling participation and policies, as this country has a unique dual justice system with religious and ethnic diversity that may impact on the way in which gambling activities are regulated. This regulatory ecosystem has important consequences on behaviour change, treatment approaches and recovery processes involved in gambling disorder. This commentary will discuss evidence for Malaysian gambling antecedents, public policy and socioeconomic impacts of gambling, possible costs and benefits of gambling legalization, and issues pertinent to regulating gambling activities in Malaysia.