Typology of online lotteries and scratch games gamblers' behaviours: A multilevel latent class cluster analysis applied to player account-based gambling data.

OBJECTIVES

Internet gambling is often considered as a risk factor for gambling problems compared with land-based gambling. In parallel, this online activity generates data that can be useful to characterize Internet gambling behaviours. The objectives were to define a typology of online lotteries and scratch games gamblers' behaviours in order to identify early risky gambling behaviours and to classify gamblers in order to identify individuals with global risky gambling behaviours.

METHODS

We performed a multilevel latent class cluster based on player account-based data of 10,000 gamblers from a French online operator.

RESULTS

We identified seven clusters of online lotteries and scratch games gamblers' behaviours. A small cluster (3%) was characterized by a very high gambling activity, a high probability of chasing behaviour, a large proportion of bets concerning instant lotteries and scratch games, and a high proportion of women. We also found a group of gamblers having an 81% probability of being each month in this cluster.

CONCLUSIONS

The identification of distinct clusters of gambling behaviours and of groups of gamblers having different probabilities of being in these clusters through time could allow the implementation of personalized prevention measures according to the gamblers' profile.