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27 - Feedback Models for Gambling Control: The Use and Efficacy of Online Responsible Gambling Tools

from Part V - Ongoing and Future Research Directions

Published online by Cambridge University Press:  13 July 2020

By
Mark D. Griffiths
Edited by
Steve Sussman
Steve Sussman
Affiliation:
University of Southern California
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Summary

Social responsibility in gambling has become a major issue for the gaming industry. This has been coupled with the rise of behavioural tracking technologies that allow companies to track every behavioural decision and action made by gamblers on online gambling sites, slot machines, and/or any type of gambling that utilizes player cards. This chapter has a number of distinct but related aims including: (a) a brief overview of behavioral tracking technologies accompanied by a critique of both advantages and disadvantages of such technologies for both the gaming industry and researchers; and (b) results from a series of studies completed using behavioral tracking data to evaluate the efficacy of online responsible gambling tools (particularly in relation to data concerning the use of social responsibility tools such as limit setting, pop-up messaging, and personalized feedback to gamblers).

Keywords

behavioral tracking technologylimit settingpop-up messagingpersonalized feedback
Type
Chapter
Information
The Cambridge Handbook of Substance and Behavioral Addictions , pp. 333 - 339
Publisher: Cambridge University Press
Print publication year: 2020

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References

Auer, M. & Griffiths, M. D. (2013). Voluntary limit setting and player choice in most intense online gamblers: An empirical study of gambling behaviour. Journal of Gambling Studies, 29, 647–660.Google Scholar
Auer, M. & Griffiths, M. D. (2014a). Personalised feedback in the promotion of responsible gambling: A brief overview. Responsible Gambling Review, 1, 27–36.Google Scholar
Auer, M. & Griffiths, M. D. (2014b). An empirical investigation of theoretical loss and gambling intensity. Journal of Gambling Studies, 30, 879–887.CrossRefGoogle ScholarPubMed
Auer, M. & Griffiths, M. D. (2015a). Testing normative and self-appraisal feedback in an online slot-machine pop-up message in a real-world setting. Frontiers in Psychology, 6, 339. doi: 10.3389/fpsyg.2015.00339Google Scholar
Auer, M. & Griffiths, M. D. (2015b). The use of personalized behavioral feedback for problematic online gamblers: An empirical study. Frontiers in Psychology, 6, 1406. doi: 10.3389/fpsyg.2015.01406.CrossRefGoogle ScholarPubMed
Auer, M. & Griffiths, M. D. (2015c). Theoretical loss and gambling intensity (revisited): A response to Braverman et al. (2013). Journal of Gambling Studies, 31, 921–931.Google Scholar
Auer, M. & Griffiths, M. D. (2016). Personalized behavioral feedback for online gamblers: A real world empirical study. Frontiers in Psychology, 7, 1875. doi: 10.3389/fpsyg.2016.01875Google Scholar
Auer, M. & Griffiths, M. D. (2017a). Self-reported losses versus actual losses in online gambling: An empirical study. Journal of Gambling Studies, 33, 795–806.Google Scholar
Auer, M. & Griffiths, M. D. (2017b). Cognitive dissonance, personalized feedback, and online gambling behavior: An exploratory study using objective tracking data and subjective self-report. International Journal of Mental Health and Addiction. Epub ahead of print. doi: 10.1007/s11469-017-9808-1CrossRefGoogle Scholar
Auer, M., Malischnig, D. & Griffiths, M. D. (2014). Is ‘pop-up’ messaging in online slot machine gambling effective? An empirical research note. Journal of Gambling Issues, 29, 1–10.CrossRefGoogle Scholar
Auer, M., Schneeberger, A. & Griffiths, M. D. (2012). Theoretical loss and gambling intensity: A simulation study. Gaming Law Review and Economics, 16, 269–273.CrossRefGoogle Scholar
Braverman, J., LaPlante, D. A., Nelson, S. E. & Shaffer, H. J. (2013). Using crossgame behavioral markers for early identification of high-risk Internet gamblers. Psychology of Addictive Behaviors, 27, 868–877.CrossRefGoogle ScholarPubMed
Braverman, J. & Shaffer, H. J. (2012). How do gamblers start gambling: Identifying behavioral markers for high-risk Internet gambling. European Journal of Public Health, 22, 273–278.Google Scholar
Braverman, J., Tom, M. A. & Shaffer, H. J. (2014). Accuracy of self-reported versus actual online-gambling wins and losses. Psychological Assessment, 26, 865–877.Google Scholar
Broda, A., LaPlante, D. A., Nelson, S. E., et al. (2008). Virtual harm reduction efforts for Internet gambling: Effects of deposit limits on actual Internet sports gambling behaviour. Harm Reduction Journal, 5, 27.Google Scholar
Buchanan, T. (2000). Potential of the Internet for personality research. In Birnbaum, M. H. (Ed.), Psychological Experiments on the Internet. San Diego: Academic Press, pp.121–140.CrossRefGoogle Scholar
Buchanan, T. (2007). Personality testing on the Internet: What we know, and what we do not. In Joinson, A. N., McKenna, K. Y. A., Postmes, T. & Reips, U. R. (Eds.), Oxford Handbook of Internet Psychology. Oxford: Oxford University Press, pp. 447–459.Google Scholar
Delfabbro, P. H., King, D. L. & Griffiths, M. D. (2012). Behavioural profiling of problem gamblers: A critical review. International Gambling Studies, 12, 349–366.CrossRefGoogle Scholar
Dragicevic, S., Percy, C., Kudic, A. & Parke, J. (2015). A descriptive analysis of demographic and behavioral data from internet gamblers and those who self-exclude from online gambling platforms. Journal of Gambling Studies, 31, 105–132.CrossRefGoogle ScholarPubMed
Forsström, D., Hesser, H. & Carlbring, P. (2016). Usage of a responsible gambling tool: A descriptive analysis of latent class analysis of user behavior. Journal of Gambling Studies, 32, 889–904.Google Scholar
Gainsbury, S. M. (2015). Online gambling addiction: The relationship between Internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193.CrossRefGoogle ScholarPubMed
Gray, H. M., LaPlante, D. A. & Shaffer, H. J. (2012). Behavioral characteristics of Internet gamblers who trigger corporate responsible gambling interventions. Psychology of Addictive Behaviors, 26, 527–535.CrossRefGoogle ScholarPubMed
Griffiths, M. D. (2003). Internet gambling: Issues, concerns and recommendations. CyberPsychology and Behavior, 6, 557–568.CrossRefGoogle ScholarPubMed
Griffiths, M. D. (2010). The use of online methodologies in data collection for gambling and gaming addictions. International Journal of Mental Health and Addiction, 8, 8–20.CrossRefGoogle Scholar
Griffiths, M. D. & Auer, M. (2011). Approaches to understanding online versus offline gaming impacts. Casino and Gaming International, 7(3), 45–48.Google Scholar
Griffiths, M. D. & Parke, J. (2002). The social impact of Internet gambling. Social Science Computer Review, 20, 312–320.CrossRefGoogle Scholar
Griffiths, M. D. & Whitty, M. W. (2010). Online behavioural tracking in Internet gambling research: Ethical and methodological issues. International Journal of Internet Research Ethics, 3, 104–117.Google Scholar
Griffiths, M. D. & Wood, R. T. A. (2008a). Gambling loyalty schemes: Treading a fine line? Casino and Gaming International, 4(2), 105–108.Google Scholar
Griffiths, M. D. & Wood, R. T. A. (2008b). Responsible gaming and best practice: How can academics help? Casino and Gaming International, 4(1), 107–112.Google Scholar
Griffiths, M. D., Wood, R. T. A. & Parke, J. (2009). Social responsibility tools in online gambling: A survey of attitudes and behaviour among Internet gamblers. CyberPsychology and Behavior, 12, 413–421.Google Scholar
Griffiths, M. D., Wood, R. T. A., Parke, J. & Parke, A. (2007). Gaming research and best practice: Gaming industry, social responsibility and academia. Casino and Gaming International, 3, 97–103.Google Scholar
Harris, A. & Griffiths, M. D. (2017). A critical review of the harm-minimisation tools available for electronic gambling. Journal of Gambling Studies, 33, 187–221.Google Scholar
Joinson, A. N., Paine, C., Buchanan, T. & Reips, U-D. (2008). Measuring self-disclosure online: Blurring and non-response to sensitive items in web-based surveys. Computers in Human Behavior, 24, 2158–2171.CrossRefGoogle Scholar
Kuss, D. J. & Griffiths, M. D. (2012). Internet gambling behavior. In Yan, Z. (Ed.), Encyclopedia of Cyber Behavior. Pennsylvania: IGI Global, pp. 735–753.CrossRefGoogle Scholar
LaBrie, R. A., Kaplan, S., LaPlante, D. A., Nelson, S. E. & Shaffer, H. J. (2008). Inside the virtual casino: A prospective longitudinal study of Internet casino gambling. European Journal of Public Health, 18(4), 410–416.Google Scholar
LaBrie, R. A., LaPlante, D. A., Nelson, S.E., Schumann, A. & Shaffer, H. J. (2007). Assessing the playing field: A prospective longitudinal study of internet sports gambling behavior. Journal of Gambling Studies, 23, 347–363.Google Scholar
LaPlante, D. A., Kleschinsky, J. H., LaBrie, R. A., Nelson, S. E. & Shaffer, H. J. (2009). Sitting at the virtual poker table: A prospective epidemiological study of actual Internet poker gambling behavior. Computers in Human Behavior, 25, 711–717.CrossRefGoogle Scholar
LaPlante, D. A., Schumann, A., LaBrie, R. A. & Shaffer, H. J. (2008). Population trends in Internet sports gambling. Computers in Human Behavior, 24(5), 2399–2414.Google Scholar
Leino, T., Sagoe, D., Griffiths, M. D., et al. (2017). Gambling behavior in alcohol-serving and non-alcohol-serving venues: A study of electronic gaming machine players using account records. Addiction Research and Theory, 25, 201–207.CrossRefGoogle Scholar
Leino, T., Torsheim, T., Blaszczynski, A., et al. (2015). The relationship between structural characteristics and gambling behavior: A population based study. Journal of Gambling Studies, 31, 1297–1315.CrossRefGoogle Scholar
Miller, W. R. & Rollnick, S. (1991). Motivational Interviewing: Preparing People to Change Addictive Behavior. New York: Guilford Press.Google Scholar
Nelson, S. E., LaPlante, D. A., Peller, A. J., et al. (2008). Real limits in the virtual world: Self-limiting behavior of Internet gamblers. Journal of Gambling Studies, 24(4), 463–477.CrossRefGoogle ScholarPubMed
Wardle, H., Sproston, K., Orford, J., et al. (2007). The British Gambling Prevalence Survey 2007. London: The Stationery Office.Google Scholar
Whitty, M. T. (2004). Peering into online bedroom windows: Considering the ethical implications of investigating Internet relationships and sexuality. In Buchanan, E. (Ed.), Readings in Virtual Research Ethics: Issues and Controversies. Hershey, USA: Idea Group Inc., pp. 203–218.Google Scholar
Wohl, M. J. A., Davis, C. G. & Hollingshead, S. J. (2017). How much have you won or lost? Personalized behavioral feedback about gambling expenditures regulates play. Computers in Human Behavior, 70, 437–455.Google Scholar
Wood, R. T. A. & Griffiths, M. D. (2007). Online data collection from gamblers: Methodological issues. International Journal of Mental Health and Addiction, 5, 151–163.CrossRefGoogle Scholar
Wood, R. T. A. & Griffiths, M. D. (2010). Social responsibility in online gambling: Voluntary limit setting. World Online Gambling Law Report, 9(11), 10–11.Google Scholar
Wood, R. T. A. & Wohl, M. J. (2015). Assessing the effectiveness of a responsible gambling behavioural feedback tool for reducing the gambling expenditure of at-risk players. International Gambling Studies, 15(2), 1–16.Google Scholar
Wood, R. T. A., Griffiths, M. D. & Eatough, V. (2004). Online data collection from videogame players: Methodological issues. Cyberpsychology and Behavior, 7, 511–518.Google Scholar
Wysocki, D. K. (1998). Let your fingers to do the talking: Sex on an adult chat-line. Sexualities, 1, 425–452.Google Scholar
Xuan, Z. M. & Shaffer, H. J. (2009). How do gamblers end gambling: Longitudinal analysis of internet gambling behaviors prior to account closure due to gambling related problems. Journal of Gambling Studies, 25, 239–252.Google Scholar

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