Using Machine-Learning Algorithms to Predict Self-Reported Problem Gambling Among a Sample of Online Gamblers

Allami, Y., Hodgins, D. C., Young, M., Brunelle, N., Currie, S., Dufour, M., Flores-Pajot, M., & Nadeau, L. (2021). A meta-analysis of problem gambling risk factors in the general adult population. Addiction, 116, 2968–2977.

Article  PubMed  PubMed Central  Google Scholar 

American Gaming Association (2025). AGA commercial gaming revenue tracker. Retrieved February 17, 2025, from: https://www.americangaming.org/resources/aga-commercial-gaming-revenue-tracker/

American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing.

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(4), 647–660.

Article  PubMed  Google Scholar 

Auer, M. M., & Griffiths, M. D. (2015). The use of personalized behavioral feedback for online gamblers: an empirical study. Frontiersin psychology, 6, 1406.

Auer, M., & Griffiths, M. D. (2018). 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, 16, 631–641.

Article  PubMed  Google Scholar 

Auer, M., & Griffiths, M. D. (2020). The use of personalized messages on wagering behavior of Swedish online gamblers: An empirical study. Computers in Human Behavior, 110, Article 106402.

Article  Google Scholar 

Auer, M., & Griffiths, M. D. (2023a). Predicting self-reported problem gambling using machine learning and player tracking data: An empirical study. Journal of Gambling Studies, 39(4), 1121–1140.

Google Scholar 

Auer, M., & Griffiths, M. D. (2023b). Nudging online gamblers to withdraw money: The impact of personalized messages on money withdrawal among a sample of real-world online casino players. Journal of Gambling Studies, 40(3), 1227–1244.

Article  PubMed  PubMed Central  Google Scholar 

Auer, M., & Griffiths, M. D. (2023c). An empirical attempt to operationalize chasing losses in gambling utilizing account-based player tracking data. Journal of Gambling Studies, 39(4), 1547–1561.

Article  PubMed  Google Scholar 

Auer, M., Malischnig, D., & Griffiths, M. D. (2014). Is “pop-up” messaging in online slot machine gambling effective as a responsible gambling strategy? An empirical research note. Journal of Gambling Issues, 29, 1–10.

Article  Google Scholar 

Auer, M., Hopfgartner, N., & Griffiths, M. D. (2018). The effect of loss-limit reminders on gambling behavior: A real-world study of Norwegian gamblers. Journal of Behavioral Addictions, 7(4), 1056–1067.

Article  PubMed  PubMed Central  Google Scholar 

Auer, M., Hopfgartner, N., & Griffiths, M. D. (2020a). The effects of voluntary deposit limit-setting on long-term online gambling expenditure. Cyberpsychology, Behavior, and Social Networking, 23(2), 113–118.

Article  PubMed  Google Scholar 

Auer, M., Reiestad, S. H., & Griffiths, M. D. (2020b). Global limit setting as a responsible gambling tool: What do players think? International Journal of Mental Health and Addiction, 18, 14–26.

Article  Google Scholar 

Auer, M., Hopfgartner, N., & Griffiths, M. D. (2021). An empirical study of the effect of voluntary limit-setting on gamblers’ loyalty using behavioural tracking data. International Journal of Mental Health and Addiction, 19(6), 1939–1950.

Article  Google Scholar 

Auer, M., Hopfgartner, N., Helic, D., & Griffiths, M. D. (2024). Self-reported deposits versus actual deposits in online gambling: An empirical study. Journal of Gambling Studies, 40(2), 619–637.

Article  PubMed  Google Scholar 

Bland, J. M., & Altman, D. G. (2000). The odds ratio. BMJ (Clinical Research Ed.), 320(7247), 1468.

Article  CAS  PubMed  Google Scholar 

Bradley, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), 1145–1159.

Article  Google Scholar 

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.

Article  PubMed  Google Scholar 

Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.

Article  Google Scholar 

Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Wadsworth & Brooks/Cole.

Carran, M. (2022). Consumer protection in European online gambling. Regulation. Monitoring gambling engagement and problem gambling prevalence within selected European jurisdictions. City Law School City, University London. London. Retrieved February 17, 2025, from: https://www.egba.eu/uploads/2022/05/Monitoring-Gambling-Prevalence-Study-01May2022.pdf

Catania, M., & Griffiths, M. D. (2021). Understanding online voluntary self-exclusion in gambling: An empirical study using account-based behavioral tracking data. International Journal of Environmental Research and Public Health, 18, 2000.

Article  PubMed  PubMed Central  Google Scholar 

Connor, B. (2024). The consequences of America's big bet on sports gambling. The Regulatory Review. Retrieved February 17, 2025, from: https://www.theregreview.org/2024/12/10/connor-the-consequences-of-americas-big-bet-on-sports-gambling/

Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273–297. https://doi.org/10.1007/BF00994018

Article  Google Scholar 

Costes, J. M., Kairouz, S., Fiedler, I., Bartczuk, R. P., Lelonkek-Kuleta, B., Minutillo, A., & Notari, L. (2023). Online gambling practices and related problems in five European countries: Findings from the Electronic Gam(bl)ing Multinational Empirical Survey (E-GAMES) Project. Journal of Gambling Studies. Advance online publication. https://doi.org/10.1007/s10899-023-10229-8

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(1), 105–132.

Article  PubMed  Google Scholar 

Elton-Marshall, T., Leatherdale, S. T., & Turner, N. E. (2016). An examination of internet and land-based gambling among adolescents in three Canadian provinces: Results from the Youth Gambling Survey (YGS). BMC Public Health, 16, 477.

Article  Google Scholar 

European Gaming and Betting Association (2019). Market reality report 2018–2019. Retrieved February 17, 2025, from: https://www.egba.eu/uploads/2019/06/EGBA-Market-Reality-Report-2019.pdf

European Gaming and Betting Association (2022). Annual report 2022: The state of online gambling in Europe. Retrieved February 17, 2025, from: https://www.egba.eu/uploads/2023/02/230203-European-Online-Gambling-Key-Figures-2022.pdf

Ferris, J., & Wynne, H. (2001). The Canadian problem gambling index: Final report. Ottawa: Canadian Centre on Substance Abuse

Friedman, J. H. (2001). Greedy function approximation: A gradient boosting machine. Annals of Statistics, 29(5), 1189–1232. https://doi.org/10.1214/aos/1013203451

Article  Google Scholar 

Gabellini, E., Lucchini, F., & Gattoni, M. E. (2023). Prevalence of problem gambling: A meta-analysis of recent empirical research (2016–2022). Journal of Gambling Studies, 39(3), 1027–1057.

Article  PubMed  Google Scholar 

Gainsbury, S. M. (2014). Review of self-exclusion from gambling venues as an intervention for problem gambling. Journal of Gambling Studies, 30(2), 229–251.

Article  PubMed  Google Scholar 

Gainsbury, S. M. (2015). Online gambling addiction: The relationship between internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193.

Article  PubMed  PubMed Central  Google Scholar 

Gainsbury, S. M., Russell, A., Hing, N., Wood, R., Lubman, D., & Blaszczynski, A. (2015). How the internet is changing gambling: Findings from an Australian prevalence survey. Journal of Gambling Studies, 31(1), 1–15.

Article  PubMed  Google Scholar 

Håkansson, A. (2020). Changes in gambling behavior during the COVID-19 pandemic—a web survey study in Sweden. International Journal of Environmental Research and Public Health, 17(11), 4013.

Article  PubMed  PubMed Central  Google Scholar 

Håkansson, A., & Henzel, V. (2021). Who chooses to enroll in a new national gambling self-exclusion system? A general population survey in Sweden. Harm Reduction Journal, 18(1), Article 82.

Article  Google Scholar 

Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29–36.

Article  CAS  PubMed  Google Scholar 

Hayer, T., & Meyer, G. (2011). Internet self-exclusion: Characteristics of self-excluded gamblers and preliminary evidence for its effectiveness. International Journal of Mental Health and Addiction, 9(3), 296–307.

Article  Google Scholar 

Hing, N., Cherney, L., Blaszczynski, A., Gainsbury, S. M., & Lubman, D. I. (2014). Do advertising and promotions for online gambling increase gambling consumption? An exploratory study. International Gambling Studies, 14(3), 394–409.

Article  Google Scholar 

Hing, N., Russell, A. M., Black, A., Rockloff, M., Browne, M., Rawat, V., Greer, N., Stevens, M., Dowling, N. A., Merkouris, S., King, D. L., Salonen, A. H., Breen, H., & Woo, L. (2022). Gambling prevalence and gambling problems amongst land-based-only, online-only and mixed-mode gamblers in Australia: A national study. Computers in Human Behavior, 132, Article 107269. https://doi.org/10.1016/j.chb.2022.107269

Article  Google Scholar 

Hopfgartner, N., Auer, M., Griffiths, M. D., & Helic, D. (2023a). Predicting self-exclusion among online gamblers: An empirical real-world study. Journal of Gambling Studies, 39(1), 447-465.5.

Article  PubMed  Google Scholar 

Hopfgartner, N., Auer, M., Helic, D., & Griffiths, M. D. (2023b). The efficacy of voluntary self-exclusions in reducing gambling among a real-world sample of British online casino players. Journal of Gambling Studies, 39(4), 1833–1848.

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