Measuring Responsible Gambling amongst Players: Development of the Positive Play Scale

The modern gambling industry has, by-in-large, assumed a duty of care to minimize the risks associated with gambling, which has manifested in responsible gambling (RG) programming (e.g., educating players about the odds of success). The current study fills a void in gambling operators, regulators, and researchers ability to measure RG beliefs and behavior in their player-base, with the development and validation of the Positive Play Scale (PPS). In Study 1, we reviewed the literature and consulted 30 players as well as 10 RG experts to help generate a definition of RG beliefs and behavior that helped guide item generation. In Study 2, regular players (N = 1,551) of a Canadian provincial gambling operator completed a positive play survey. Four components from a principal components analysis (PCA) were extracted: Honesty and Control, Pre-commitment, Personal Responsibility, and Gambling Literacy. The PPS subscales were either not associated with gambling frequency or had small-to-moderate negative relationships with frequency of play for games most often associated with disordered gambling (e.g., electronic games). In Study 3 (N = 413), the factor structure of the PPS was confirmed and refined in a new sample of players. Moreover, a 1-month follow-up session demonstrated that the PPS has high test-retest reliability. The PPS is the first validated scale that reliably assesses the extent to which a consumer base has positive beliefs about gambling and gambles in a positive manner. The PPS can be used by the gambling industry to objectively assess the efficacy of their RG strategy, pinpoint specific areas for future focus, as well as examine the utility of new RG initiatives that aim to promote healthy patterns of gambling consumption. Furthermore, by examining the PPS scores for different player segments (e.g., sex, age, games played) it becomes possible to tailor RG strategy to the needs of specific players. In this way, RG strategy can be optimized by focusing resources where they will be most effective.