IDEAS home Printed from https://ideas.repec.org/a/taf/intgms/v15y2015i3p489-505.html
   My bibliography  Save this article

Impulsivity and predictive control are associated with suboptimal action-selection and action-value learning in regular gamblers

Author

Listed:
  • M.S.M. Lim
  • G. Jocham
  • L.T. Hunt
  • T.E.J. Behrens
  • R.D. Rogers

Abstract

Heightened impulsivity and cognitive biases are risk factors for gambling problems. However, little is known about precisely how these factors increase the risks of gambling-related harm in vulnerable individuals. Here, we modelled the behaviour of 87 community-recruited regular, but not clinically problematic, gamblers during a binary-choice reinforcement-learning game, to characterize the relationships between impulsivity, cognitive biases and the capacity to make optimal action selections and learn about action-values. Impulsive gamblers showed diminished use of an optimal (Bayesian-derived) probability estimate when selecting between candidate actions, and showed slower learning rates and enhanced non-linear probability weighting while learning action values. Critically, gamblers who believed that it is possible to predict winning outcomes (as 'predictive control') failed to use the game's reinforcement history to guide their action selections. Extensive evidence attests to the ease with which gamblers can erroneously perceive structure in the reinforcement history of games when there is none. Our findings demonstrate that the generic and specific risk factors of impulsivity and cognitive biases can interfere with the capacity of some gamblers to utilize structure when it is available in the reinforcement history of games, potentially increasing their risks of sustaining gambling-related harms.

Suggested Citation

  • M.S.M. Lim & G. Jocham & L.T. Hunt & T.E.J. Behrens & R.D. Rogers, 2015. "Impulsivity and predictive control are associated with suboptimal action-selection and action-value learning in regular gamblers," International Gambling Studies, Taylor & Francis Journals, vol. 15(3), pages 489-505, December.
    • Handle: RePEc:taf:intgms:v:15:y:2015:i:3:p:489-505
    DOI: 10.1080/14459795.2015.1078835
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14459795.2015.1078835
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14459795.2015.1078835?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Lattimore, Pamela K. & Baker, Joanna R. & Witte, Ann D., 1992. "The influence of probability on risky choice: A parametric examination," Journal of Economic Behavior & Organization, Elsevier, vol. 17(3), pages 377-400, May.
    6. Pamela K. Lattimore & Joanna R. Baker & A. Dryden Witte, 1992. "The Influence Of Probability on Risky Choice: A parametric Examination," NBER Technical Working Papers 0081, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dickinson, David L. & Reid, Parker, 2023. "Gambling Habits and Probability Judgements in a Bayesian Task Environment," IZA Discussion Papers 16306, Institute of Labor Economics (IZA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    2. Häckel, Björn & Pfosser, Stefan & Tränkler, Timm, 2017. "Explaining the energy efficiency gap - Expected Utility Theory versus Cumulative Prospect Theory," Energy Policy, Elsevier, vol. 111(C), pages 414-426.
    3. M. Pelé & M. Broihanne & B. Thierry & J. Call & V. Dufour, 2014. "To bet or not to bet? Decision-making under risk in non-human primates," Journal of Risk and Uncertainty, Springer, vol. 49(2), pages 141-166, October.
    4. Christopher Schwand & Rudolf Vetschera & Lea Wakolbinger, 2010. "The influence of probabilities on the response mode bias in utility elicitation," Theory and Decision, Springer, vol. 69(3), pages 395-416, September.
    5. Han Bleichrodt & Jose Luis Pinto & Peter P. Wakker, 2001. "Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility," Management Science, INFORMS, vol. 47(11), pages 1498-1514, November.
    6. Foster, Gigi & Frijters, Paul & Schaffner, Markus & Torgler, Benno, 2018. "Expectation formation in an evolving game of uncertainty: New experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 379-405.
    7. Ariane Charpin, 2018. "Tests des modèles de décision en situation de risque. Le cas des parieurs hippiques en France," Revue économique, Presses de Sciences-Po, vol. 69(5), pages 779-803.
    8. Luís Santos-Pinto & Adrian Bruhin & José Mata & Thomas Åstebro, 2015. "Detecting heterogeneous risk attitudes with mixed gambles," Theory and Decision, Springer, vol. 79(4), pages 573-600, December.
    9. Syngjoo Choi & Jeongbin Kim & Eungik Lee & Jungmin Lee, 2022. "Probability Weighting and Cognitive Ability," Management Science, INFORMS, vol. 68(7), pages 5201-5215, July.
    10. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    11. Loreto Llorente & Josemari Aizpurua, 2008. "A Betting Market: Description and a Theoretical Explanation of Bets in Pelota Matches," Theory and Decision, Springer, vol. 64(2), pages 421-446, March.
    12. Galarza, Francisco, 2009. "Choices under Risk in Rural Peru," MPRA Paper 17708, University Library of Munich, Germany.
    13. Wang, Di, 2021. "Attention-driven probability weighting," Economics Letters, Elsevier, vol. 203(C).
    14. Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," LSE Research Online Documents on Economics 159, London School of Economics and Political Science, LSE Library.
    15. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    16. Kontek, Krzysztof & Birnbaum, Michael H., 2019. "The impact of middle outcomes on lottery valuations," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 78(C), pages 30-44.
    17. Fehr-Duda, Helga & Epper, Thomas & Bruhin, Adrian & Schubert, Renate, 2011. "Risk and rationality: The effects of mood and decision rules on probability weighting," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1), pages 14-24.
    18. Zahra Murad & Martin Sefton & Chris Starmer, 2016. "How do risk attitudes affect measured confidence?," Journal of Risk and Uncertainty, Springer, vol. 52(1), pages 21-46, February.
    19. Peter Brooks & Simon Peters & Horst Zank, 2014. "Risk behavior for gain, loss, and mixed prospects," Theory and Decision, Springer, vol. 77(2), pages 153-182, August.
    20. Hüseyin İlker Erçen & Hüseyin Özdeşer & Turgut Türsoy, 2022. "The Impact of Macroeconomic Sustainability on Exchange Rate: Hybrid Machine-Learning Approach," Sustainability, MDPI, vol. 14(9), pages 1-19, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:intgms:v:15:y:2015:i:3:p:489-505. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RIGS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.