Top

Published in:

24-01-2022 | Original Paper

Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors

Authors: William H. B. McAuliffe, Eric R. Louderback, Timothy C. Edson, Debi A. LaPlante, Sarah E. Nelson

Published in: Journal of Gambling Studies | Issue 4/2022

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.

Available only for authorised users

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.

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.CrossRef

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.CrossRef

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.PubMedCrossRef

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.PubMedPubMedCentralCrossRef

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.PubMedCrossRef

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.PubMedCrossRef

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.CrossRef

Deng, X., Lesch, T., & Clark, L. (2019). Applying data science to behavioral analysis of online gambling. Current Addiction Reports, 6(3), 159–164.CrossRef

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.PubMedCrossRef

Embretson, S. E., & Reise, S. P. (2013). Item response theory. Psychology Press.CrossRef

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.PubMedCrossRef

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.PubMedPubMedCentralCrossRef

Goodwin, B. C., Browne, M., Rockloff, M., & Rose, J. (2017). A typical problem gambler affects six others. International Gambling Studies, 17(2), 276–289.CrossRef

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.PubMedCrossRef

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.CrossRef

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.CrossRef

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.PubMedCrossRef

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.CrossRef

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.PubMedPubMedCentralCrossRef

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.PubMedPubMedCentralCrossRef

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.CrossRef

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.PubMedCrossRef

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.PubMedCrossRef

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.PubMedCrossRef

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.CrossRef

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/adb0000628CrossRefPubMed

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.PubMedCrossRef

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.PubMedCrossRef

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.PubMedPubMedCentralCrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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.PubMedCrossRef

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.CrossRef

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.CrossRef

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.PubMedCrossRef

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.CrossRef

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.CrossRef

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.CrossRef

Title: Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors
Authors: William H. B. McAuliffe
Eric R. Louderback
Timothy C. Edson
Debi A. LaPlante
Sarah E. Nelson
Publication date: 24-01-2022
Publisher: Springer US
Published in: Journal of Gambling Studies / Issue 4/2022
Electronic ISSN: 1573-3602
DOI: https://doi.org/10.1007/s10899-021-10097-0

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 4/2022

Longitudinal Assessment of a Manualized Group Treatment Program for Gambling Disorder: The Ohio Problem Gambling Treatment Model for Adults with Co-Occurring Disorders

The Bounded Ending Effect in the Domain of Football Gambling: High Risks Are Not Always Preferred at the End

Socio-Demographics, Gambling Participation, Gambling Settings, and Addictive Behaviors Associated with Gambling Modes: A Population-Based Study

Gambling Outlets Location in Urban Areas: A Case Study of Madrid

Problem gambling and anxiety disorders in the general swedish population – a case control study

Behavior Change Techniques and Delivery Modes in Interventions Targeting Adolescent Gambling: A Systematic Review