Predictors of gambling and problem gambling in Victoria, Australia

Abstract

In 2016, the gambling habits of a sample of 3361 adults in the state of Victoria, Australia, were surveyed. It was found that a number of factors that were highly correlated with self-reported gambling frequency and gambling problems were not significant predictors of gambling frequency and problem gambling. The major predictors of gambling frequency were the degree to which family members and peers were perceived to gamble, self-reported approval of gambling, the frequency of discussing gambling offline, and the participant's Canadian Problem Gambling Severity Index (PGSI) score. Age was a significant predictor of gambling frequency for certain types of gambling (e.g. buying lottery tickets). Approximately 91% of the explainable variance in the participant's PGSI score could be explained by just five predictors: Positive Urgency; Frequency of playing poker machines at pubs, hotels or sporting clubs; Participation in online discussions of betting on gaming tables at casinos; Frequency of gambling on the internet, and Overestimating the chances of winning. Based on these findings, suggestions are made as to how gambling-related harm can be reduced.

Fig 1. Clustered bar graphs for the percentage of Victorians self-reporting participating in the 12 surveyed gambling activities and the perceived participation of their family members, peers, and people in general.

Clusters marked with asterisks indicate a statistically significant difference on frequency ratings for gambling activity depending on the person(s) doing the gambling (self, family members, peers, and people in general) as indicated by a non-parametric Friedman test. N = 3361. *p < .001.

Fig 2. Clustered bar graphs showing the percentage of Victorians who approve of each of the 12 gambling activities and what percentage of their family members, peers, and people in general, respectively, they believe approve of each of the 12 gambling activities.

Clusters marked with asterisks indicate a statistically significant difference in approval ratings as a function of approval category (self, family members, peers, and people in general), as indicated by a non-parametric Friedman test. N = 3361. *p < .001.