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A second mechanism by which players migrated from social casino games to online gambling was via the inflated payout rates on social casino games. Note this mechanism was also identified in the two pathways model proposed by King and Delfabbro (2016). Specifically, participants felt an increased confidence in winning should they have engaged in real-money gambling. Further, several participants stated that their frequent wins on social casino games propelled them to try engaging in online gambling. This is in line with previous research, which found that a portion of casino gamers play these games to build up their ‘skill’ before migrating to gambling in land-based or online gambling venues (see Kim et al. 2016). However, the inflated payout rates may give players an inflated belief in the skill, and, of course, there is no skill if the game of choice is one of pure-chance, like a slot machine. In fact, social casino game outcomes are not based on random odds and mathematics, but are rather designed to enhance player enjoyment (Wohl et al. 2017). Because of this, the social casino gamer wins more than he loses (Sévigny et al. 2005), which in turn, may falsely increase their confidence in winning, as proposed by King and Delfabbro (2016). Providing further support that frequent wins and perception of skills as a process by which social casino games to lead to online gambling, Hollingshead et al. (2016) showed that playing social casino games for skill purposes have been linked to problematic gambling behaviors. In this light, it would behoove regulators to enforce payout rates that are similar to gambling activities, or at very least mandate social casino gaming operators to inform players of that social casino games are not based on random odds as their gambling counterparts. According to Blaszczynski and Nower’s (2002) pathways model of problem and pathological gambling, there are three distinct subgroups of gamblers, each with different pathways that manifest in problem gambling behaviors. In the model, the starting point is ecological factors, which include increased availability and accessibility. In this way, social casino games may influence the development of problem gambling among young adults by providing ease of access and increased availability. Indeed, one of the concerns of social casino games is that although they purport to have age verifications, a UK study found that 300,000 youths aged 11–16 reported having engaged in free online gambling games in the past week (Parke et al. 2013). Furthermore, it is plausible that if social casino games lead to the development of problem gambling, it does through Pathway 1, the behaviourally conditioned gambler. This pathway includes cognitive mechanisms such as irrational beliefs and illusion of control, which may manifest due to the inflated payout rates on social casino games. That said, this is an assertion and would be in need of empirical support. Limitations. Some limitations of the current study should be noted. First, we did not recruit a sufficient number of female online gamblers to ascertain different trends and cognitions that may be gender-specific. That said, studies have consistently found that online gamblers tend to be young males (Griffiths et al. 2009; for a review see Gainsbury 2015). Thus, we have confidence that the observed results maintain ecological validity. Secondly, the findings of the current project are not intended to be reflective of the college population as a whole. Rather, the findings are qualitative in nature and should be used to guide future research initiatives. Lastly, we recruited online gamblers to participant in the focus groups, rather than social casino gamers. Thus, the current study cannot speak to social casino games being a deterrent to online gambling (e.g., knowing you can’t win). Conclusion. The Internet has drastically shaped the way in which people engage with the world, including with gambling activities. Furthermore, social networking sites have become a fabric of the modern day world. While the Internet and specifically social networking sites are a great medium to stay connected with loved ones, they have increasingly become an avenue to engage in gambling activities, including simulated forms of gambling (i.e., social casino games). The present research explored the motivations that push young adults to engage in online gambling, including the role of social casino games. Further research and attention is needed in this domain to mitigate the potential migration from gaming to gambling, specifically amongst those most vulnerable. References. Abarbanel, B, Gainsbury, S. M., King, D., Hing, N., & Delfabbro, P. H. (2016). Gambling games on social platforms: How do advertisements for social casino games target young adults? Policy & Internet, 9, 184–209. ArticleGoogle Scholar Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97, 487–499. ArticleGoogle Scholar Derevensky, J. L., & Gainsbury, S. M. (2016). Social casino gaming and adolescents: Should we be concerned and is regulation in sight? International Journal of Law and Psychiatry, 44, 1–6. ArticleGoogle Scholar Derevensky, J., Sklar, A., Gupta, R., & Messerlian, C. (2010). An empirical study examining the impact of gambling advertisements on adolescent gambling attitudes and behaviors. 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ArticleGoogle Scholar Gainsbury, S., King, D., Abarbanel, B., Delfabbro, P., & Hing, N. (2015a). Convergence of gambling and gaming in digital media . Melbourne, VIC: Victorian Responsible Gambling Foundation. Google Scholar Gainsbury, S., King, D., Delfabbro, P., Hing, N., Russell, A., Blaszczysnki, A., & Derevensky, J. (2015b). The use of social media in gambling. A report commissioned by Gambling Research Australia. Gainsbury, S. M., King, D. L., Russell, A. M., Delfabbro, P., & Hing, N. (2017). Virtual addictions: An examination of problematic social casino game use among at-risk gamblers. Addictive Behaviors, 64, 334–339. ArticleGoogle Scholar Gainsbury, S. M., Russell, A. M. T., King, D. L., Delfabbro, P., & Hing, N. (2016). Migration from social casino games to gambling: Motivations and characteristics of gamers who gamble. Computers in Human Behavior, 63, 59–67. ArticleGoogle Scholar Gainsbury, S., & Wood, R. (2011). Internet gambling policy in critical comparative perspective: The effectiveness of existing regulatory frameworks. International Gambling Studies, 11 (3), 309–323. ArticleGoogle Scholar Griffiths, M., Wardle, H., Orford, J., Sproston, K., & Erens, B. (2009). Sociodemographic correlates of internet gambling: Findings from the 2007 British Gambling Prevalence Survey. CyberPsychology & Behavior, 12 (2), 199–202. ArticleGoogle Scholar Hollingshead, S. J., Kim, H. S., Wohl, M. J. A., & Derevensky, J. L. (2016). The social casino gaming-gambling link: Motivation for playing social casino games determines whether self-reported gambling increases or decreases among disordered gamblers. Journal of Gambling Issues, 33, 52–67. ArticleGoogle Scholar Kim, H. S., Wohl, M. J. A., Gupta, R., & Derevensky, J. (2016). From the mouths of social media users: A focus group study exploring the social casino gaming-online gambling link. Journal of Behavioral Addictions, 5, 115–121. ArticleGoogle Scholar Kim, H. S., Wohl, M. J., Salmon, M. M., Gupta, R., & Derevensky, J. (2015). Do social casino gamers migrate to online gambling? An assessment of migration rate and potential predictors. Journal of Gambling Studies, 31, 1819–1831. ArticleGoogle Scholar King, D. L., & Delfabbro, P. H. (2016). Early exposure to digital simulated gambling: A review and conceptual model. Computers in Human Behavior , 55 , 198–206. Lucas, A. F., Dunn, W. T., & Singh, A. K. (2005). Estimating the short-term effect of free-play offers in a Las Vegas Hotel Casino. Journal of Travel & Tourism Marketing, 18, 53–68. ArticleGoogle Scholar Martin, C. (2014). Big data and social casino gaming. Canadian Gaming Lawyer Magazine, 1, 4–7. Google Scholar McBride, J., & Derevensky, J. (2009). Internet gambling behavior in a sample of online gamblers. International Journal of Mental Health and Addiction, 7 (1), 149–167. ArticleGoogle Scholar Olason, D. T., Kristjansdottir, E., Einarsdottir, H., Haraldsson, H., Bjarnason, G., & Derevensky, J. L. (2011). Internet gambling and problem gambling among 13 to 18 year old adolescents in Iceland. International Journal of Mental Health and Addiction, 9 (3), 257–263. ArticleGoogle Scholar Parke, J., Wardle, H., Rigbye, J., & Parke, A. (2013). Exploring social gambling: Scoping, classification and evidence review. Final report submitted to the UK Gambling Commission. Räsänen, T., Lintonen, T., & Konu, A. (2013). Adolescent gambling as a public health issue. European Journal of Public Health , 23 (1), 250. Schneider, S. (2012). Social gaming and online gambling. Gambling Law and Review, 16, 711–712. ArticleGoogle Scholar Sévigny, S., Cloutier, M., Pelletier, M. F., & Ladouceur, R. (2005). Internet gambling: Misleading payout rates during the “demo” period. Computers in Human Behavior, 21, 153–158. ArticleGoogle Scholar SuperData. (2016). Social casino market – US player insights 2016. New York, NY: Author. Welte, J. W., Barnes, G. M., Tidwell, M. C. O., & Hoffman, J. H. (2011). Gambling and problem gambling across the lifespan. Journal of Gambling Studies, 27 (1), 49–61. ArticleGoogle Scholar Wohl, M. J. A., Salmon, M. M., Hollingshead, S. J., & Kim, H. S. (2017). An examination of the relationship between social casino gaming and gambling: The bad, the ugly, and the good. Journal of Gambling Issues, 35, 1–23. ArticleGoogle Scholar Wood, R. T., Griffiths, M. D., & Parke, J. (2007). Acquisition, development, and maintenance of online poker playing in a student sample. Cyberpsychology & Behavior, 10 (3), 354–361. ArticleGoogle Scholar., charming queens कैसीनो लाइव रूले ऑनलाइन. Authors' contributions. MW, JD, and RG, conceptualized the research project. RG, conducted the focus groups. HK wrote the first draft of the manuscript and MW, JD, and RG, edited subsequent versions. All authors read and approved the final manuscript. 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