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As online gambling becomes more prevalent, understanding the motives of online gamblers has become a key focus for research and practice. The aim of this study was to understand differences in gambling-related outcome expectancies between mixed (both online and offline) gamblers and offline-only gamblers, by incorporating gambling harm risk categories from the problem gambling severity index (PGSI). This study comprised a secondary data analysis of the 2015 Northern Territory Gambling Prevalence and Wellbeing Survey. A sample of 1207 individuals in the Northern Territory who had reported gambling at least once in the previous 12 months were used in the analyses. General linear and structural equation modelling were used to ascertain differences in gambling outcome expectancies, in relation to gambling modality (i.e., mixed, offline-only) and PGSI scores. Mixed gamblers tended to score higher on all outcome expectancies than their offline-only counterparts. Outcome expectancy scores were higher in individuals in higher-risk PGSI categories. The escape outcome expectancy was dependent on both modality and risk category. Invariance testing of a low and problem gambling risk subsample revealed differential relationships for both the escape and excitement outcome expectancies for mixed and offline-only gamblers. The results provide an important contribution to the existing literature regarding motivation and outcome expectancies in relation to gambling modality and problem gambling severity. The findings highlight the importance of considering both gambling outcome expectancies and modality when considering problem gambling. [ABSTRACT FROM AUTHOR]

There is some uncertainty on how to best conceptualise and measure problem gambling and debate as to whether it is helpful to differentiate the behavioral features of problematic gambling from the negative consequences of gambling. The current study explores this issue by examining the factor structure of a commonly-used problem gambling measure, the Problem Gambling Severity Index (PGSI), as administered to respondents in the 2018 Northern Territory Gambling Prevalence and Wellbeing Survey (n = 3,740 gamblers). Confirmatory factor analyses revealed a two-factor solution offered significant improvement in fit over the one-factor model. Further, the two factors explained unique variance in the number of gambling-related harms experienced by respondents. Although the two factors were highly correlated, the current findings indicate problem gambling behaviors are related to the negative consequences of gambling, but these are not necessarily synonymous. This suggests isolating behavioral and consequential elements of gambling may have utility in public health interventions for gambling that, while concerning, falls below a clinically-significant threshold. Similarly, clinically-oriented research may benefit by measuring the behavioral features, as these components are important targets for individual-level interventions. [ABSTRACT FROM AUTHOR]