Skip to main content
SpringerLink
Log in

Shallow Value Weighting Predicts Problem Gambling: A Parameter Estimation Analysis Using Cumulative Prospect Theory

  • Original Paper
  • Published:
Journal of Gambling Studies Aims and scope Submit manuscript

Abstract

Problem gambling is a non-substance-based addictive disorder that can cause significant distress and dramatic consequences. Despite extensive research in neuroscience and clinical/social psychology, few contributions have been made from formal models of behavioural economics. We apply Cumulative Prospect Theory (CPT) to provide a formal analysis of cognitive distortions in problem gambling. In two experiments, participants made decisions between pairs of gambles and completed a standard gambling assessment. We estimated the parameter values specified by CPT for each participant and used those estimates to predict gambling severity. In Experiment 1, severe gambling behaviour was associated with a shallow valuation curve, a reversal of loss aversion, and decreased influence of subjective value on decisions (i.e., more noise or variability in preference). Experiment 2 replicated the effect of shallow valuation but did not demonstrate reversed loss version or noisier decisions. Neither experiment provided evidence of differences in probability weighting. We explore implications of the findings and conclude that problem gambling at least partially reflects a fundamental distortion to subjective valuation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

All data, experiment scripts, and analysis scripts are available at https://osf.io/mpjk2/.

Notes

  1. Nilsson et al.’s (2011) estimation procedure requires complete data for each participant, making removing individual trials inappropriate.

  2. However, the probability weighting parameter for gains approached conventional significance in all cases.

References

  • American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders. Washington, DC.

  • Blaszczynski, A., & Steel, Z. (1998). Personality disorders among pathological gamblers. Journal of Gambling Studies, 14(1), 51–71.

    Article  PubMed  Google Scholar 

  • Blaszczynski, A., Steel, Z., & McConaghy, N. (1997). Impulsivity in pathological gambling: The antisocial impulsivist. Addiction, 92(1), 75–87.

    Article  CAS  PubMed  Google Scholar 

  • Brand, M., Kalbe, E., Labudda, K., Fujiwara, E., Kessler, J., & Markowitsch, H. J. (2005). Decision-making impairments in patients with pathological gambling. Psychiatry Research, 133(1), 91–99.

    Article  PubMed  Google Scholar 

  • Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment. Psychological Review, 100(3), 432–459.

    Article  CAS  PubMed  Google Scholar 

  • Calado, F., & Griffiths, M. D. (2016). Problem gambling worldwide: An update and systematic review of empirical research (2000–2015). Journal of Behavioral Addictions, 5(4), 592–613.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ciccarelli, M., Nigro, G., Griffiths, M. D., Cosenza, M., & D’Olimpio, F. (2016). Attentional biases in problem and non-problem gamblers. Journal of Affective Disorders, 198, 135–141.

    Article  PubMed  Google Scholar 

  • Farrell, S., & Lewandowsky, S. (2010). Computational models as aids to better reasoning in psychology. Current Directions in Psychological Science, 19(5), 329–335.

    Article  Google Scholar 

  • Ferris, J. A., & Wynne, H. J. (2001). The Canadian problem gambling index (pp. 1–59). Ottawa, ON: Canadian Centre on Substance Abuse.

  • Grant, A., Johnstone, D., & Kwon, O. K. (2021). A cumulative prospect theory explanation of gamblers cashing-out. Journal of Mathematical Psychology, 102, 102534.

    Article  MathSciNet  Google Scholar 

  • Grant, J. E., Schreiber, L., Odlaug, B. L., & Kim, S. W. (2010). Pathologic gambling and bankruptcy. Comprehensive Psychiatry, 51(2), 115–120.

    Article  PubMed  Google Scholar 

  • Håkansson, A., Karlsson, A., & Widinghoff, C. (2018). Primary and secondary diagnoses of gambling disorder and psychiatric comorbidity in the Swedish health care system—A nationwide register study. Frontiers in Psychiatry, 9.

  • Jamieson, R. K., & Pexman, P. M. (2020). Moving beyond 20 questions: We (still) need stronger psychological theory. Canadian Psychology/psychologie Canadienne, 61(4), 273.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.

    Article  MathSciNet  Google Scholar 

  • Karlsson, A., & Håkansson, A. (2018). Gambling disorder, increased mortality, suicidality, and associated comorbidity: A longitudinal nationwide register study. Journal of Behavioral Addictions, 7(4), 1091–1099.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kennedy, S. H., Welsh, B. R., Fulton, K., Soczynska, J. K., McIntyre, R. S., O’Donovan, C., Milev, R., le Melledo, J. M., Bisserbe, J. C., Zimmerman, M., & Martin, N. (2010). Frequency and correlates of gambling problems in outpatients with major depressive disorder and bipolar disorder. The Canadian Journal of Psychiatry, 55(9), 568–576.

    Article  PubMed  Google Scholar 

  • Lawrence, A. J., Luty, J., Bogdan, N. A., Sahakian, B. J., & Clark, L. (2009). Impulsivity and response inhibition in alcohol dependence and problem gambling. Psychopharmacology (berl), 207(1), 163–172.

    Article  CAS  PubMed  Google Scholar 

  • Leonard, C. A., & Williams, R. J. (2016). The relationship between gambling fallacies and problem gambling. Psychology of Addictive Behaviors, 30(6), 694–704.

    Article  PubMed  Google Scholar 

  • Lewandowsky, S. (1993). The rewards and hazards of computer simulations. Psychological Science, 4(4), 236–243.

    Article  Google Scholar 

  • Ligneul, R., Sescousse, G., Barbalat, G., Domenech, P., & Dreher, J. C. (2013). Shifted risk preferences in pathological gambling. Psychological Medicine, 43(5), 1059–1068.

    Article  CAS  PubMed  Google Scholar 

  • Lorains, F. K., Cowlishaw, S., & Thomas, S. A. (2011). Prevalence of comorbid disorders in problem and pathological gambling: Systematic review and meta-analysis of population surveys. Addiction, 106(3), 490–498.

    Article  PubMed  Google Scholar 

  • Muthukrishna, M., & Henrich, J. (2019). A problem in theory. Nature Human Behaviour, 3(3), 221–229.

    Article  PubMed  Google Scholar 

  • Nilsson, H., Rieskamp, J., & Wagenmakers, E. J. (2011). Hierarchical Bayesian parameter estimation for cumulative prospect theory. Journal of Mathematical Psychology, 55(1), 84–93.

    Article  MathSciNet  Google Scholar 

  • Odlaug, B. L., Schreiber, L. R., & Grant, J. E. (2012). Personality disorders and dimensions in pathological gambling. Journal of Personality Disorders, 26(3), 381.

    Article  PubMed  Google Scholar 

  • Peel, D., & Law, D. (2009). A more general non-expected utility model as an explanation of gambling outcomes for individuals and markets. Economica, 76(302), 251–263.

    Article  Google Scholar 

  • Oberauer, K., & Lewandowsky, S. (2019). Addressing the theory crisis in psychology. Psychonomic Bulletin and Review, 26(5), 1596–1618.

    Article  PubMed  Google Scholar 

  • Rieskamp, J. (2008). The probabilistic nature of preferential choice. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(6), 1446–1465.

    PubMed  Google Scholar 

  • Scherrer, J. F., Xian, H., Shah, K. R., Volberg, R., Slutske, W., & Eisen, S. A. (2005). Effect of genes, environment, and lifetime co-occurring disorders on health-related quality of life in problem and pathological gamblers. Archives of General Psychiatry, 62(6), 677–683.

    Article  PubMed  Google Scholar 

  • Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing transparency through a multiverse analysis. Perspectives on Psychological Science, 11(5), 702–712.

    Article  PubMed  Google Scholar 

  • Szollosi, A., & Donkin, C. (2019). Neglected sources of flexibility in psychological theories: From replicability to good explanations. Computational Brain and Behavior, 2(3), 190–192.

    Article  Google Scholar 

  • Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315, 515–518.

    Article  ADS  CAS  PubMed  Google Scholar 

  • Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323.

    Article  Google Scholar 

  • van Rooij, I. (2022). Psychological models and their distractors. Nature Reviews Psychology, 1(3), 127–128.

    Article  Google Scholar 

  • von Neumann, J., & Morgenstern, O. (1947). Theory of games and economic behavior (2nd rev. ed.). Princeton University Press.

  • World Health Organization, 1994. International Statistical Classification of Diseases and Health Related Problems, Tenth Version (ICD-10). Geneva.

  • Wynne, H. (2003). Introducing the Canadian problem gambling index. Edmonton, AB: Wynne Resources.

Download references

Funding

This research was supported by a grant provided through the Dr. Edgar and Yves Smutny Research Fund at Booth University College awarded to E. T. Curtis.

Author information

Authors and Affiliations

  1. Booth University College, 447 Webb Place, Winnipeg, MB, R3B 2P2, Canada

    E. T. Curtis & J. L. Curtis

Authors
  1. E. T. Curtis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. L. Curtis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. T. Curtis.

Ethics declarations

Conflict of interest

The authors report no competing interests.

Ethical Approval

The research was approved by the Booth University College Research Ethics Board.

Informed Consent

Informed consent was obtained from all individuals who participated in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Curtis, E.T., Curtis, J.L. Shallow Value Weighting Predicts Problem Gambling: A Parameter Estimation Analysis Using Cumulative Prospect Theory. J Gambl Stud 40, 333–348 (2024). https://doi.org/10.1007/s10899-023-10218-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10899-023-10218-x

Keywords

Search

Navigation