Usage of a Responsible Gambling Tool: A Descriptive Analysis and Latent Class Analysis of User Behavior
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Gambling is a common pastime around the world. Most gamblers can engage in gambling activities without negative consequences, but some run the risk of developing an excessive gambling pattern. Excessive gambling has severe negative economic and psychological consequences, which makes the development of responsible gambling strategies vital to protecting individuals from these risks. One such strategy is responsible gambling (RG) tools. These tools track an individual’s gambling history and supplies personalized feedback and might be one way to decrease excessive gambling behavior. However, research is lacking in this area and little is known about the usage of these tools. The aim of this article is to describe user behavior and to investigate if there are different subclasses of users by conducting a latent class analysis. The user behaviour of 9528 online gamblers who voluntarily used a RG tool was analysed. Number of visits to the site, self-tests made, and advice used were the observed variables included in the latent class analysis. Descriptive statistics show that overall the functions of the tool had a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.
KeywordsResponsible gambling tool Decrease gambling User behavior Latent class analysis Initial high usage Low repeated usage
The current study was made possible thanks to a Grant from the Svenska Spel’s independent research council to the last author. The granting source was not involved in the preparation or execution of the current study, and was not a part of the statistical analyses or drafting of the manuscript. The authors of the current study would like to thank Playscan for supplying the data for the study (Playscan was also not involved the statistical analyses and drafting of the manuscript).
- Braverman, J., & Shaffer, H. J. (2012). How do gamblers start gambling: Identifying behavioural markers for high-risk internet gambling. European Journal of Public Health, 22(2), 273–278. doi: 10.1093/eurpub/ckp232.
- Broda, A., LaPlante, D. A., Nelson, S. E., LaBrie, R. A., Bosworth, L. B., & Shaffer, H. J. (2008). Virtual harm reduction efforts for Internet gambling: Effects of deposit limits on actual Internet sports gambling behavior. Harm Reduction Journal, 5(1), 27. doi: 10.1186/1477-7517-5-27.CrossRefPubMedPubMedCentralGoogle Scholar
- Donkin, L., & Glozier, N. (2012). Motivators and motivations to persist with online psychological interventions: A qualitative study of treatment completers. Journal of Medical Internet Research, 14(3).Google Scholar
- Dufour, M., Brunelle, N., & Roy, É. (2013). Are poker players all the same? Latent class analysis. Journal of Gambling Studies. doi: 10.1007/s10899-013-9429-y.
- Gainsbury, S., Parke, J., & Suhonen, N. (2013b). Consumer attitudes towards Internet gambling: Perceptions of responsible gambling policies, consumer protection, and regulation of online gambling sites. Computers in Human Behavior, 29(1), 235–245. doi: 10.1016/j.chb.2012.08.010.CrossRefGoogle Scholar
- Goldstein, A. L., Faulkner, B., Cunningham, R. M., Zimmerman, M. A., Chermack, S., & Walton, M. A. (2012). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction, 11(1), 13–30. doi: 10.1007/s11469-012-9396-z.CrossRefGoogle Scholar
- Health, S. I. O. P. (2012). Spel om pengar och spelproblem i Sverige 2009/2010 [Gambling and gambling problems in Sweden 2009/2010]. Retrieved from: http://www.folkhalsomyndigheten.se/pagefiles/12792/R2012-04-Spel-om-pengar-och-spelproblem-i-Sverige-2009-2010.pdf.
- McCutcheon, A. L. (1987). Latent class analysis. Newbury Park, Calif: Sage Publications.Google Scholar
- Miller, W., & Rollnick, S. (2002). Motivational interviewing: Preparing people for change. New York, NY: Guilford.Google Scholar
- Muthén, L. K., & Muthén, B. O. (1998-2011). Mplus user guide, 6th edition. Los Angeles, CA: Muthén & Muthén.Google Scholar
- Neighbors, C., Rodriguez, L. M., Rinker, D. V., Gonzales, R. G., Agana, M., Tackett, J. L., & Foster, D. W. (2015). Efficacy of personalized normative feedback as a brief intervention for college student gambling: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 83(3), 500–511. doi: 10.1037/a0039125.CrossRefPubMedPubMedCentralGoogle Scholar
- Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007a). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535–569. doi: 10.1080/10705510701575396.CrossRefGoogle Scholar
- Studer, J., Baggio, S., Mohler-Kuo, M., Simon, O., Daeppen, J.-B., & Gmel, G. (2015). Latent class analysis of gambling activities in a sample of young swiss men: Association with gambling problems, substance use outcomes, personality traits and coping strategies. Journal of Gambling Studies. doi: 10.1007/s10899-015-9547-9.
- Vaughn, M. G., DeLisi, M., Gunter, T., Fu, Q., Beaver, K. M., Perron, B. E., & Howard, M. O. (2011). The severe 5%: A latent class analysis of the externalizing behavior spectrum in the United States. Journal of Criminal Justice, 39(1), 75–80. doi: 10.1016/j.jcrimjus.2010.12.001.CrossRefPubMedPubMedCentralGoogle Scholar
- Walker, D., Litvin, S., Sobel, R., & St-Pierre, R. (2014). Setting win limits: An alternative approach to “Responsible Gambling”? Journal of Gambling Studies, 1–22. doi: 10.1007/s10899-014-9453-6.
- Wanner, M., Martin-Diener, E., Bauer, G., Braun-Fahrländer, C., & Martin, B. W. (2010). Comparison of trial participants and open access users of a web-based physical activity intervention regarding adherence, attrition, and repeated participation. Journal of Medical Internet Research, 12(1), e3. doi: 10.2196/jmir.1361.CrossRefPubMedCentralGoogle Scholar
- Wohl, M. A., Santesso, D., & Harrigan, K. (2013). Reducing erroneous cognition and the frequency of exceeding limits among slots players: A short (3-minute) educational animation facilitates responsible gambling. International Journal of Mental Health and Addiction, 11(4), 409–423. doi: 10.1007/s11469-012-9424-z.CrossRefGoogle Scholar
- Wood, R. T. A., Shorter, G. W., & Griffiths, M. D. (2014). Rating the suitability of responsible gambling features for specific game types: A resource for optimizing responsible gambling strategy. International Journal of Mental Health and Addiction, 12(1), 94–112. doi: 10.1007/s11469-013-9473-y.