Abstract
Online gambling poses novel risks for problem gambling, but also unique opportunities to detect and intervene with at-risk users. A consortium of gambling companies recently committed to using nine behavioral "Markers of Harm'' that can be calculated with online user data to estimate risk for gambling-related harm. The current study evaluates these markers in two independent samples of sports bettors, collected ten years apart. We find over a two-year period that most users never had high enough overall risk scores to indicate that they would have received an intervention. This observation is partly due to characteristics of our samples that are associated with lower risk for gambling-related harm, but might also be due to overly high risk thresholds or flaws in the design of some markers. Users with higher average risk scores had more intraindividual variability in risk scores. Younger age and male gender were not associated with higher average risk scores. The most active users were more likely than other users to have ever exceeded risk thresholds. Several risk scores significantly predicted proxies of gambling-related harm (e.g., account closure). Overall, the current Markers of Harm system has some correctable limitations that future risk detection systems should consider adopting.
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Notes
We pre-registered the use of false discovery rate corrections when inferring statistical significance, but we abandoned that plan because we realized we did not have a concrete plan for how we would implement them among the many subsets of tests that we conducted. Furthermore, some models did not converge to proper solutions, which would have affected how many test results factored into the corrections.
References
Baggio, S., Dupuis, M., Berchtold, A., Spilka, S., Simon, O., & Studer, J. (2017). Is gambling involvement a confounding variable for the relationship between Internet gambling and gambling problem severity? Computers in Human Behavior, 71, 148–152.
Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R. H. B., Singmann, H., & Scheipl, F. (2012). Package ‘lme4’. CRAN. R Foundation for Statistical Computing, Vienna, Austria. https://rdrr.io/cran/lme4/man/convergence.html
Bollen, K. A., & Barb, K. H. (1981). Pearson’s r and coarsely categorized measures. American Sociological Review, 1, 232–239.
Braverman, J., & Shaffer, H. J. (2012). How do gamblers start gambling: Identifying behavioural markers for high-risk internet gambling. The European Journal of Public Health, 22(2), 273–278.
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.
Brosowski, T., Olason, D. T., Turowski, T., & Hayer, T. (2020). The Gambling Consumption Mediation Model (GCMM): A multiple mediation approach to estimate the association of particular game types with problem gambling. Journal of Gambling Studies, 1, 1–34.
Chóliz, M., Marcos, M., & Lázaro-Mateo, J. (2019). The risk of online gambling: A study of gambling disorder prevalence rates in Spain. International Journal of Mental Health and Addiction, 1, 1–14.
Conolly, A., Davies, B., Fuller, L., Heinze, N., & Wardel, H. (2018). Gambling behavior in Great Britain in 2016. Gambling Commission. http://www.gamblingcommission.gov.uk/PDF/survey-data/Gambling-behaviour-in-Great-Britain-2016.pdf
Currie, S. R., Hodgins, D. C., & Casey, D. M. (2013). Validity of the problem gambling severity index interpretive categories. Journal of Gambling Studies, 29(2), 311–327.
Currie, S. R., Hodgins, D. C., Casey, D. M., & el-Guebaly, N., Smith, G. J., Williams, R. J., & Schopflocher, D. P. (2017). Deriving low-risk gambling limits from longitudinal data collected in two independent Canadian studies. Addiction, 112(11), 2011–2020.
Dragicevic, S., Tsogas, G., & Kudic, A. (2011). Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection. International Gambling Studies, 11(3), 377–391.
Deng, X., Lesch, T., & Clark, L. (2019). Applying data science to behavioral analysis of online gambling. Current Addiction Reports, 6(3), 159–164.
Dowle, M. & Srinivasan, A. (2019). data.table: Extension of `data.frame`. R package version 1.12.8. https://CRAN.R-project.org/package=data.table
Demin, G. (2020). expss: Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics. R package version 0.10.6. https://CRAN.R-project.org/package=expss
Effertz, T., Bischof, A., Rumpf, H. J., Meyer, C., & John, U. (2018). The effect of online gambling on gambling problems and resulting economic health costs in Germany. The European Journal of Health Economics, 19(7), 967–978.
Embretson, S. E., & Reise, S. P. (2013). Item response theory. Psychology Press.
Ferris, J. A., & Wynne, H. J. (2001). The Canadian problem gambling index (pp. 1–59). Canadian Centre on Substance Abuse.
Field, A. P., & Wilcox, R. R. (2017). Robust statistical methods: A primer for clinical psychology and experimental psychopathology researchers. Behaviour Research and Therapy, 98, 19–38.
Fox, J., Friendly, G. G., Graves, S., Heiberger, R., Monette, G., Nilsson, H., & Suggests, M. A. S. S. (2007). The car package. R Foundation for Statistical Computing.
Gainsbury, S. M. (2015). Online gambling addiction: The relationship between internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193.
Goodwin, B. C., Browne, M., Rockloff, M., & Rose, J. (2017). A typical problem gambler affects six others. International Gambling Studies, 17(2), 276–289.
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(3), 527–535.
Håkansson, A., & Henzel, V. (2020). Who chooses to enroll in a new national gambling self-exclusion system? A general population survey in Sweden. Harm Reduction Journal, 17(1), 1–12.
Hamel, A., Bastien, C., Jacques, C., Moreau, A., & Giroux, I. (2021). Sleep or play online Poker?: Gambling behaviors and tilt symptoms while sleep deprived. Frontiers in Psychiatry, 11, 1540.
Hing, N., Russell, A., Tolchard, B., & Nower, L. (2016). Risk factors for gambling problems: An analysis by gender. Journal of Gambling Studies, 32(2), 511–534.
Hing, N., Russell, A. M., Thomas, A., & Jenkinson, R. (2019). Hey big spender: An ecological momentary assessment of sports and race betting expenditure by gambler characteristics. Journal of Gambling Issues, 42, 1.
Ivanova, E., Magnusson, K., & Carlbring, P. (2019). Deposit limit prompt in online gambling for reducing gambling intensity: A randomized controlled trial. Frontiers in Psychology, 10, 639.
Kessler, R. C., Hwang, I., LaBrie, R., Petukhova, M., Sampson, N. A., Winters, K. C., & Shaffer, H. J. (2008). DSM-IV pathological gambling in the National Comorbidity Survey Replication. Psychological Medicine, 38(9), 1351–1360.
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1.
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(3), 347–362.
LaPlante, D. A., Nelson, S. E., & Gray, H. M. (2014). Breadth and depth involvement: Understanding Internet gambling involvement and its relationship to gambling problems. Psychology of Addictive Behaviors, 28(2), 396–403.
LaPlante, D. A., Nelson, S. E., LaBrie, R. A., & Shaffer, H. J. (2008a). Stability and progression of disordered gambling: Lessons from longitudinal studies. The Canadian Journal of Psychiatry, 53(1), 52–60.
LaPlante, D. A., Schumann, A., LaBrie, R. A., & Shaffer, H. J. (2008b). Population trends in Internet sports gambling. Computers in Human Behavior, 24(5), 2399–2414.
Louderback, E. R., LaPlante, D. A., Currie, S. R., & Nelson, S. E. (2021). Developing and validating lower risk online gambling thresholds with actual bettor data from a major Internet gambling operator. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0000628
Luquiens, A., Vendryes, D., Aubin, H. J., Benyamina, A., Gaiffas, S., & Bacry, E. (2018). Description and assessment of trustability of motives for self-exclusion reported by online poker gamblers in a cohort using account-based gambling data. British Medical Journal Open, 8(12), 1.
Makowski, D., Ben-Shachar, M. S., Patil, I. & Lüdecke, D. (2020). Methods for correlation analysis. CRAN.
Maechler, M., Rousseeuw, P., Croux, C., Todorov, V., Ruckstuhl, A., Salibian-Barrera, M., & Maechler, M. M. (2020). Package ‘robustbase’. Basic Robust Statistics.
Mächler, M. (2015). Arbitrarily Accurate Computation with R: The Rmpfr Package. version 0.8–1. https://CRAN.R-project.org/package=Rmpfr
Mansournia, M. A., Geroldinger, A., Greenland, S., & Heinze, G. (2018). Separation in logistic regression: Causes, consequences, and control. American Journal of Epidemiology, 187(4), 864–870.
Muggleton, N., Parpart, P., Newall, P., Leake, D., Gathergood, J., & Stewart, N. (2021). The association between gambling and financial, social and health outcomes in big financial data. Nature Human Behaviour, 1, 1–8.
Narayan, N. (2020, April 08). BGC to take over assets and responsibilities of SENET GROUP. Retrieved March 12, 2021, from https://europeangaming.eu/portal/latest-news/2020/04/08/68038/bgc-to-take-over-assets-and-responsibilities-of-senet-group/
Nelson, S. E., Edson, T., Louderback, E. R., Tom, M., Grossman, A., & LaPlante, D. (2020). Changes to the playing field: A contemporary study of actual online sports betting. https://doi.org/10.31234/osf.io/tc8ps
Nelson, S. E., LaPlante, D. A., Peller, A. J., Schumann, A., LaBrie, R. A., & Shaffer, H. J. (2008). Real limits in the virtual world: Self-limiting behavior of Internet gamblers. Journal of Gambling Studies, 24(4), 463–477.
Parhami, I., Siani, A., Rosenthal, R. J., Lin, S., Collard, M., & Fong, T. W. (2012). Sleep and gambling severity in a community sample of gamblers. Journal of Addictive Diseases, 31(1), 67–79.
Parke, A., & Parke, J. (2019). Transformation of sports betting into a rapid and continuous gambling activity: A grounded theoretical investigation of problem sports betting in online settings. International Journal of Mental Health and Addiction, 17(6), 1340–1359.
Percy, C., França, M., Dragičević, S., & d’Avila Garcez, A. (2016). Predicting online gambling self-exclusion: An analysis of the performance of supervised machine learning models. International Gambling Studies, 16(2), 193–210.
Philander, K. S., & MacKay, T. L. (2014). Online gambling participation and problem gambling severity: Is there a causal relationship? International Gambling Studies, 14(2), 214–227.
Pratt, K. (2020, April 14). UK Bans Use Of Credit Cards To Pay For Gambling. Retrieved May 14, 2020, from https://www.forbes.com/sites/advisoruk/2020/04/14/uk-bans-use-of-credit-cards-to-pay-for-gambling/#5b27de46190c
PwC & Responsible Gambling Council. (2017). Remote gambling research: Interim report on Phase 2. London: Gamble Aware. https://about.gambleaware.org/media/1549/gamble-aware_remote-gambling-research_phase-2_pwc-report_august-2017-final.pdf
R Core Team (2020). R: A language and environment for statistical computing (Version 4.0. 0). R Foundation for Statistical Computing.
Revelle, W. (2019) psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA. https://CRAN.R-project.org/package=psych Version = 1.9.12.
Sleczka, P., & Romild, U. (2021). On the stability and the progression of gambling problems: Longitudinal relations between different problems related to gambling. Addiction, 116(1), 116–125.
Shaffer, H. J., Peller, A. J., LaPlante, D. A., Nelson, S. E., & LaBrie, R. A. (2010). Toward a paradigm shift in Internet gambling research: From opinion and self-report to actual behavior. Addiction Research & Theory, 18(3), 270–283.
Simonsohn, U. (2018). Two lines: A valid alternative to the invalid testing of U-shaped relationships with quadratic regressions. Advances in Methods and Practices in Psychological Science, 1(4), 538–555.
Steyer, R., Mayer, A., Geiser, C., & Cole, D. A. (2015). A theory of states and traits—Revised. Annual Review of Clinical Psychology, 11, 71–98.
Swanton, T. B., & Gainsbury, S. M. (2020). Gambling-related consumer credit use and debt problems: A brief review. Current Opinion in Behavioral Sciences, 31, 21–31.
Wardle, H., Parke, J., & Excell, D. (2014). Machines research programme: Report 1–theoretical markers of harm for machine play in a bookmaker’s: a rapid scoping review. Responsible Gambling Trust. https://about.gambleaware.org/media/1169/report-1-theoretical-markers-of-harm-for-machine-play-in-a-bookmakers-a-rapid-scoping-review.pdf
Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Wood, R. T., 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.
Wright, M. (2020, November, 9). Withdrawal reversals to be blocked on all gambling sites. Retrieved February 2, 2021, from https://onlinebingo.co.uk/news/withdrawal-reversals-blocked
Yani-de-Soriano, M., Javed, U., & Yousafzai, S. (2012). Can an industry be socially responsible if its products harm consumers? The case of online gambling. Journal of Business Ethics, 110(4), 481–497.
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This research was supported primarily by a research contract between the Division on Addiction and GVC Holdings PLC (hereafter, GVC). GVC is a large international gambling and online gambling operator. GVC had no involvement with the development of our research questions or protocol. They will not see any associated materials (i.e., retrieved studies, charted data, and manuscripts in preparation) while the study is in progress or have any editorial rights to any resulting manuscripts. GVC communication about this work will require approval of the Division on Addiction. GVC is now called Entain (https://entaingroup.com/). When this article was published, the Division on Addiction was also receiving funding from DraftKings, Inc., a sports betting and gaming company; EPIC Risk Management; Foundation for Advancing Alcohol Responsibility, a not-for-profit organization founded and funded by a group of distillers; Massachusetts Department of Public Health, Office of Problem Gambling Services via Health Resources in Action; MGM Resorts International via the University of Nevada, Las Vegas; National Institutes of Health (National Institute of General Medical Sciences and National Institute on Drug Abuse) via The Healing Lodge of the Seven Nations; Substance Abuse and Mental Health Services Administration via the Addiction Treatment Center of New England; and Substance Abuse and Mental Health Services Administration via the Gavin Foundation. During the 5 years prior to the publication of this article, the Division on Addiction has also received funding from David H. Bor Library Fund, Cambridge Health Alliance; Fenway Community Health Center, Inc.; Greater Boston Council on Alcoholism; Integrated Centre on Addiction Prevention and Treatment of the Tung Wah Group of Hospitals, Hong Kong; Massachusetts Department of Public Health, Bureau of Substance Addiction Services; Massachusetts Department of Public Health, Bureau of Substance Addiction Services via St. Francis House; and the Massachusetts Gaming Commission, Commonwealth of Massachusetts. During the past five years, Debi A. LaPlante has served as a paid grant reviewer for the National Center for Responsible Gaming (NCRG; now International Center for Responsible Gaming), received travel funds, speaker honoraria, and a scientific achievement award from the ICRG, has received speaker honoraria and travel support from the National Collegiate Athletic Association, received honoraria funds for preparation of a book chapter from Universite Laval, received publication royalty fees from the American Psychological Association, and received course royalty fees from the Harvard Medical School Department of Continuing Education. Dr. LaPlante is a non-paid member of the New Hampshire Council for Responsible Gambling. During the past 5 years, Eric R. Louderback has received research funding from a grant issued by the National Science Foundation (NSF), a government agency based in the United States. His research has been financially supported by a Dean’s Research Fellowship from the University of Miami College of Arts & Sciences, who also provided funds to present at academic conferences. He has received travel support funds from the Hebrew University of Jerusalem to present research findings and has provided consulting services on player safety programs for Premier Lotteries Ireland. During the past five years, Sarah E. Nelson has served as a paid grant reviewer for the National Center for Responsible Gaming (NCRG; now International Center for Responsible Gaming [ICRG]), GambleAware, Manitoba Responsible Gaming, Alberta Gambling Research Institute, and the National Institutes of Health (NIH). She has also received travel reimbursement and speaker honoraria from the ICRG and Responsible Gaming Association of New Mexico, travel reimbursement from the American Bar Association, and Foundation for Advancing Alcohol Responsibility. She received honoraria funds for preparation of a book chapter from Universite Laval and publication royalty fees from the American Psychological Association, and received course royalty fees from the Harvard Medical School Department of Continuing Education. William H. B. McAuliffe and Timothy C. Edson have no funding disclosures to declare.
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McAuliffe, W.H.B., Louderback, E.R., Edson, T.C. et al. Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors. J Gambl Stud 38, 1337–1369 (2022). https://doi.org/10.1007/s10899-021-10097-0
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DOI: https://doi.org/10.1007/s10899-021-10097-0