Abstract

Growth of Internet gambling has fuelled concerns about its contribution to gambling problems. However, most online gamblers also gamble on land-based forms, which may be the source of problems for some. Studies therefore need to identify the problematic mode of gambling (online or offline) to identify those with an online gambling problem. Identifying most problematic form of online gambling (e.g., EGMs, race betting, sports betting) would also enable a more accurate examination of gambling problems attributable to a specific online gambling form. This study pursued this approach, aiming to: (1) determine demographic, behavioral and psychological risk factors for gambling problems on online EGMs, online sports betting and online race betting; (2) compare the characteristics of problematic online gamblers on each of these online forms. An online survey of 4,594 Australian gamblers measured gambling behavior, most problematic mode and form of gambling, gambling attitudes, psychological distress, substance use, help-seeking, demographics and problem gambling status. Problem/moderate risk gamblers nominating an online mode of gambling as their most problematic, and identifying EGMs (n = 98), race betting (n = 291) or sports betting (n = 181) as their most problematic gambling form, were compared to non-problem/low risk gamblers who had gambled online on these forms in the previous 12 months (n = 64, 1145 and 1213 respectively), using bivariate analyses and then logistic regressions. Problem/moderate risk gamblers on each of these online forms were then compared. Risk factors for online EGM gambling were: more frequent play on online EGMs, substance use when gambling, and higher psychological distress. Risk factors for online sports betting were being male, younger, lower income, born outside of Australia, speaking a language other than English, more frequent sports betting, higher psychological distress, and more negative attitudes toward gambling. Risk factors for online race betting comprised being male, younger, speaking a language other than English, more frequent race betting, engaging in more gambling forms, self-reporting as semi-professional/professional gambler, illicit drug use whilst gambling, and more negative attitude toward gambling. These findings can inform improved interventions tailored to the specific characteristics of high risk gamblers on each of these online activities.

Highlights

  • Participation in online gambling continues to increase in tandem with its deregulation, prolific advertising, the widespread uptake of computer and mobile technologies, and increased availability of high speed internet access (Wood and Williams, 2011; Gainsbury, 2012; Hing et al, 2014a)

  • While previous studies have identified risk factors for problem gamblers who engage in Internet gambling (e.g., McBride and Derevensky, 2009; Wood and Williams, 2009; Potenza et al, 2011; Hing et al, 2016e), these analyses have not considered whether or not their gambling problems are related to specific gambling forms and to engaging with them online

  • More frequent online electronic gaming machines (EGMs) gambling increased the risk of gambling problems, which aligns with findings from risk curve analyses based on several large representative datasets in Canada (Currie et al, 2006, 2008)

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Summary

Introduction

Participation in online gambling continues to increase in tandem with its deregulation, prolific advertising, the widespread uptake of computer and mobile technologies, and increased availability of high speed internet access (Wood and Williams, 2011; Gainsbury, 2012; Hing et al, 2014a) These developments have fuelled concerns that online gambling contributes substantially to gambling problems, prompting research into online problem gamblers, including their characteristics, prevalence, and associated risk factors (Wood and Williams, 2007, 2009; Wardle et al, 2011; Gainsbury et al, 2013; Hing et al, 2014b). To automatically attribute gambling problems amongst online gamblers to their use of online modes of gambling is inaccurate and overestimates the impact of Internet technologies on problem gambling

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