Advertisement

Encouraging Gamblers to Think Critically Using Generalised Analytical Priming is Ineffective at Reducing Gambling Biases

  • Tess Armstrong
  • Matthew Rockloff
  • Matthew Browne
  • Alexander BlaszczynskiEmail author
Original Paper

Abstract

Gambling has been associated with an array of fallacious beliefs that foster risky gambling decisions. Research into other belief systems suggests that the endorsement of non-evidence based beliefs, such as the paranormal or conspiracy theories, can be reduced when people think more analytically. The purpose of this study was to explore whether an intervention designed to elicit analytical thinking was effective in altering the gambling beliefs and simulated gambling behaviour of 178 regular electronic gaming machine (EGM) gamblers (102 males, 76 female). Participants were randomly allocated to complete either an analytic or a neutral priming task, followed by completion of belief measures (erroneous and protective) and play on a simulated EGM game. Results failed to show that priming for analytical thinking changed betting on an EGM; including features of bet size, bet change, persistence and theoretical losses. Contrary to expectations, results suggest that priming analytical thinking using generalised interventions does not appear to be effective in altering peoples’ simulated gambling involvement or gambling beliefs. In fact, priming people to think more critically might be counterproductive by contributing to greater positive expectations about gambling outcomes. The results further suggested that the number of times a player alters their bet is a good indicator of theoretical gambling losses and is associated with irrational gambling cognitions. Interventions designed to promote safer thinking in gamblers should be implemented with care, as results from our study suggest that encouraging critical thinking in at-risk or problem gamblers may not be effective in reducing risky gambling.

Keywords

Gambling beliefs Analytic prime Gambling intensity Cognitive style 

Notes

Funding

Part of this research was supported under the Commonwealth Government’s Research Training Program/Research Training Scheme. I gratefully acknowledge the financial support provided by the Australian Government and Central Queensland University. Funding agencies have had no involvement in the research design, methodology, conduct, analysis or write-up of this manuscript.

Compliance with Ethical Standards

Ethical Approval

This research involved human participants and received ethics approval from the Central Queensland Human Research Ethics Committee [Project Number: H16/04-075].

Informed Consent

Informed consent was provided by all participants included in the study.

References

  1. Armstrong, T., Donaldson, P., Langham, E., Rockloff, M., & Browne, M. (2018). Exploring the effectiveness of an intelligent messages framework for developing warning messages to reduce gambling intensity. Journal of Gambling Issues,38, 67–84.  https://doi.org/10.4309/jgi.2018.38.4.CrossRefGoogle Scholar
  2. Armstrong, T., Rockloff, M., Browne, M., & Blaszczynski, A. (2019). Beliefs about gambling mediate the effect of cognitive style on gambling problems. (unpublished manuscript).Google Scholar
  3. Armstrong, T., Rockloff, M., Browne, M., & Blaszczynski, A. (2019b). Development and validation of the Protective Gambling Beliefs Scale (PGBS). International Gambling Studies,9(1), 1–18.  https://doi.org/10.1080/14459795.2018.1500624.CrossRefGoogle Scholar
  4. Armstrong, T., Rockloff, M., & Donaldson, P. (2016a). Crimping the Croupier: Electronic and mechanical automation of table, community and novelty games in Australia. Journal of Gambling Issues,33, 103–123.  https://doi.org/10.4309/jgi.2016.33.7.CrossRefGoogle Scholar
  5. Armstrong, T., Rockloff, M., Greer, N., & Donaldson, P. (2016b). Rise of the machines: A critical review on the behavioural effects of automating traditional gambling games. Journal of Gambling Studies,33(3), 735–767.  https://doi.org/10.1007/s10899-016-9644-4.CrossRefGoogle Scholar
  6. Auer, M., & Griffiths, M. (2015). Testing normative and self-appraisal feedback in an online slot-machine pop-up in a real-world setting. Frontiers in Psychology.  https://doi.org/10.3389/fpsyg.2015.00339.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Barrault, S., & Varescon, I. (2013). Cognitive distortions, anxiety, and depression among regular and pathological gambling online poker players. Cyberspace,16(3), 183–188.  https://doi.org/10.1089/cyber.2012.0150.CrossRefGoogle Scholar
  8. Bernardo, A. B. I., Zhang, L.-F., & Callueng, C. M. (2002). Thinking styles and academic achievement among filipino students. The Journal of Genetic Psychology,163(2), 149–163.  https://doi.org/10.1080/00221320209598674.CrossRefPubMedGoogle Scholar
  9. Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction,97(5), 487–499.  https://doi.org/10.1046/j.1360-0443.2002.00015.x.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Boudry, M., & Braeckman, J. (2012). How convenient! The epistemic rationale of self-validating belief systems. Philosophical Psychology,25(3), 341–364.  https://doi.org/10.1080/09515089.2011.579420.CrossRefGoogle Scholar
  11. Bouju, G., Hardouin, J.-B., Boutin, C., Gorwood, P., Le Bourvellec, J.-D., Feuillet, F., et al. (2014). A shorter and multidimensional version of the Gambling Attitudes and Beliefs Survey (GABS-23). Journal of Gambling Studies,30(2), 349–367.  https://doi.org/10.1007/s10899-012-9356-3.CrossRefPubMedGoogle Scholar
  12. Chau, A. W., & Phillips, J. G. (1995). Effects of perceived control upon wagering and attributions in computer blackjack. The Journal of General Psychology,122(3), 253–269.  https://doi.org/10.1080/00221309.1995.9921237.CrossRefGoogle Scholar
  13. Cloutier, M., Ladouceur, R., & Sévigny, S. (2006). Responsible gambling tools: Pop-up messages and pauses on video lottery terminals. The Journal of Psychology,140, 434–438.CrossRefGoogle Scholar
  14. Cosenza, M., Ciccarelli, M., & Nigro, G. (2019). Decision-making styles, negative affectivity, and cognitive distortions in adolescent gambling. Journal of Gambling Studies,35(2), 517–531.  https://doi.org/10.1007/s10899-018-9790-y.CrossRefPubMedGoogle Scholar
  15. Cunningham, J. A., Hodgins, D. C., & Toneatto, T. (2014). Relating severity of gambling to cognitive distortions in a representative sample of problem gamblers. Journal of Gambling Issues,29, 1–6.  https://doi.org/10.4309/jgi.2014.29.2.CrossRefGoogle Scholar
  16. Davidson, T., & Rodgers, B. (2010). 2009 Survey of the nature and extent of gambling and problem gambling, in the Australian Capital Territory. Canberra: Gambling and Racing Commission. Retrieved Nov, 2019, from https://www.gamblingandracing.act.gov.au/__data/assets/pdf_file/0005/745043/ACT-Gambling-Prevalence-Study.pdf.
  17. Delfabbro, P. (2004). The stubborn logic of regular gamblers: Obstacles and dilemmas in cognitive gambling research. Journal of Gambling Studies,20(1), 1–21.  https://doi.org/10.1023/B:JOGS.0000016701.17146.d0.CrossRefPubMedGoogle Scholar
  18. Delfabbro, P., Lahn, J., & Grabosky, P. (2006). It’s not what you know, but how you use it: Statistical knowledge and adolescent problem gambling. Journal of Gambling Studies,22(2), 179–193.  https://doi.org/10.1007/s10899-006-9009-5.CrossRefPubMedGoogle Scholar
  19. Delfabbro, P., & Winefeld, A. H. (2000). Predictors of irrational thinking in regular slot machine gamblers. The Journal of Psychology,134(2), 117–128.  https://doi.org/10.1080/00223980009600854.CrossRefPubMedGoogle Scholar
  20. Denes-Raj, V., & Epstein, S. (1994). Conflict between intuitive and rational processing: When people behave against their better judgment. Journal of Personality and Social Psychology,66(5), 819–829.  https://doi.org/10.1037/0022-3514.66.5.819.CrossRefPubMedGoogle Scholar
  21. Dixon, L., Trigg, R., & Griffiths, M. (2007). An empirical investigation of music and gambling behaviour. International Gambling Studies,7(3), 315–326.  https://doi.org/10.1080/14459790701601471.CrossRefGoogle Scholar
  22. Ellerby, Z. W., & Tunney, R. J. (2017). The effects of heuristics and apophenia on probabilistic choice. Advances in Cognitive Psychology,13(4), 280–295.  https://doi.org/10.5709/acp-0228-9.CrossRefPubMedPubMedCentralGoogle Scholar
  23. Emond, M. S., & Marmurek, H. H. C. (2010). Gambling related cognitions mediate the association between thinking style and problem gambling severity. Journal of Gambling Studies,26(2), 257–267.  https://doi.org/10.1007/s10899-009-9164-6.CrossRefPubMedGoogle Scholar
  24. Epstein, S. (2008). Intuition from the perspective of cognitive-experiential self-theory. In H. Plessner, C. Betsch, & T. Betsch (Eds.), Intuition in judgement and decision making (pp. 23–37). New York: Lawrence Erlbaum Associates.Google Scholar
  25. Ferris, J., & Wynne, H. (2001). The Canadian Problem Gambling Index: Final report. Ottawa: Canadian Centre on Substance Abuse.Google Scholar
  26. Finlay, K., Kanetkar, V., Londerville, J., & Marmurek, H. H. C. (2006). The physical and psychological measurement of gambling environments. Environment and Behavior,38(4), 570–581.  https://doi.org/10.1177/0013916505283419.CrossRefGoogle Scholar
  27. Fortune, E. E., & Goodie, A. S. (2012). Cognitive distortions as a component and treatment focus of pathological gambling: A review. Journal of the Society of Psychologists in Addictive Behaviors,26(2), 298–310.  https://doi.org/10.1037/a0026422.CrossRefGoogle Scholar
  28. Friedman, B. (2000). Designing casinos to dominate the competition: The Friedman international standards of casino design. Reno, NV: Institute for the Study of Gambling and Commercial Gaming.Google Scholar
  29. Gaboury, A., & Ladouceur, R. (1989). Erroneous perceptions and gambling. Journal of Social Perceptions and Gambling,4, 411–420.Google Scholar
  30. Gervais, W. M., & Norenzayan, A. (2012). Analytic Thinking Promotes Religious Disbelief. Science,336(6080), 493–496.  https://doi.org/10.1126/science.1215647.CrossRefPubMedGoogle Scholar
  31. Gilbert, D. T., Krull, D. S., & Malone, P. S. (1990). Unbelieving the unbelievable some problems in the rejection of false information. Journal of Personality and Social Psychology,59(4), 601–613.CrossRefGoogle Scholar
  32. Gilovich, T. (1983). Biased evaluation and persistence in gambling. Journal of Personality and Social Psychology,44(6), 1110–1126.CrossRefGoogle Scholar
  33. Gilovich, T., & Douglas, C. (1986). Biased evaluations of randomly determined gambling outcomes. Journal of Experimental Social Psychology,22, 228–241.CrossRefGoogle Scholar
  34. Goodie, A. S., & Fortune, E. E. (2013). Measuring cognitive distortions in pathological gambling: Review and meta-analyses. Journal of the Society of Psychologists in Addictive Behaviors,27(3), 730–743.  https://doi.org/10.1037/a0031892.CrossRefGoogle Scholar
  35. Gooding, P., & Tarrier, N. (2009). A systematic review and meta-analysis of cognitive-behavioural interventions to reduce problem gambling: Hedging our bets? Behaviour Research and Therapy,47(7), 592–607.  https://doi.org/10.1016/j.brat.2009.04.002.CrossRefPubMedGoogle Scholar
  36. Griffiths, M. D. (1994). The role of cognitive bias and skill in fruit machine gambling. British Journal of Psychology,85(3), 351–369.CrossRefGoogle Scholar
  37. Griffiths, M. D. (1999). Gambling technologies: Prospects for problem gambling. Journal of Gambling Studies,15(3), 265–283.CrossRefGoogle Scholar
  38. Griffiths, M. D. (2003). Internet gambling: Issues, concerns, and recommendations. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society,6(6), 557–568.  https://doi.org/10.1089/109493103322725333.CrossRefGoogle Scholar
  39. Griffiths, M. D., Parke, A., Wood, R., & Parke, J. (2006). Internet Gambling: An overview of psychosocial impacts. UNVL Gambling Research and Review Journal,10(1), 27–39.Google Scholar
  40. Hammond, K. R. (1996). Coping with uncertainty: The rivalry between intuition and analysis. In Human Judgement and Social Policy. Retrieved Aug, 2015, from https://books.google.com.au/books?id=Z_DZ3nKHg2cC&dq=human+judgement+and+social+policy&source=gbs_navlinks_s.
  41. Hare, S. (2006). Factors that influence gambler adherence to pre-commitment decisions. Brisbane: Schottler Consulting for Gambling Research Australia.Google Scholar
  42. Hare, S. (2009). A study of gambling in VictoriaProblem gambling from a public health perspective August 2008 to October 2009. Victoria: Department of Justice. Retrieved July, 2019, from http://www.responsiblegambling.vic.gov.au/__data/assets/pdf_file/0013/4027/Gambling-in-victoria-problem-gambling-from-a-public-health-perspective.pdf.
  43. Johnston, M. (2016). What more can we learn from early learning theory? The contemporary relevance for behaviour change interventions. British Journal of Health Psychology,21(1), 1–10.  https://doi.org/10.1111/bjhp.12165.CrossRefPubMedGoogle Scholar
  44. Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. The American Psychologist,58(9), 697–720.  https://doi.org/10.1037/0003-066X.58.9.697.CrossRefPubMedGoogle Scholar
  45. Kane, M. J., Core, T. J., & Hunt, R. R. (2010). Bias versus bias: Harnessing hindsight to reveal paranormal belief change beyond demand characteristics. Psychonomic Bulletin & Review,17(2), 206–212.  https://doi.org/10.3758/PBR.17.2.206.CrossRefGoogle Scholar
  46. Khasawneh, (2011). Thinking style preferences of vocational students at the university level: A prospective workforce development approach. International Journal of Applied Education Studies,10(1), 78–89.Google Scholar
  47. Kranes, D. (1995). Playgrounds. Journal of Gambling Studies,11, 91–102.CrossRefGoogle Scholar
  48. Kučinskienė, R. (2003). Methodological foundation for rational individual career decision making. Management of Organizations: Systematic Research,25, 139–148.Google Scholar
  49. Ladouceur, R., & Mayrand, M. (1984). Evaluation of the “illusion of control”: Type of feedback, outcome sequence, and number of trials among regular and occasional gamblers. The Journal of Psychology,117, 37–46.CrossRefGoogle Scholar
  50. Leonard, C. A. (2018). Fallacious beliefs: Gambling specific and belief in the paranormal. Odedeji: University of Lethbridge.Google Scholar
  51. Lole, L., Li, E., Russell, A., Greer, N., Thorne, H., & Hing, N. (2019). Are sports bettors looking at responsible gambling messages? An eye-tracking study on wagering advertisements. Journal of Behavioral Addictions,8(2), 1–9.  https://doi.org/10.1556/2006.8.2019.37.CrossRefGoogle Scholar
  52. Marmurek, H. H. C., Switzer, J., & D’Alvise, J. (2015). Impulsivity, gambling cognitions, and the Gambler’s Fallacy in University Students. Journal of Gambling Studies,31(1), 197–210.  https://doi.org/10.1007/s10899-013-9421-6.CrossRefPubMedGoogle Scholar
  53. McInnes, A., Hodgins, D. C., & Holub, A. (2014). The gambling cognitions inventory: Scale development and psychometric validation with problem and pathological gamblers. International Gambling Studies,14(3), 410–431.  https://doi.org/10.1080/14459795.2014.923483.CrossRefGoogle Scholar
  54. Menzel, S. (2013). Are emotions to blame? The impact of non-analytic information processing on decision-making and implications for fostering sustainability. Biological Economics,96, 71–78.  https://doi.org/10.1016/j.ecolecon.2013.10.001.CrossRefGoogle Scholar
  55. Miller, N. V., & Currie, S. R. (2008). A Canadian population level analysis of the roles of irrational gambling cognitions and risky gambling practices as correlates of gambling intensity and pathological gambling. Journal of Gambling Studies,24(3), 257–274.  https://doi.org/10.1007/s10899-008-9089-5.CrossRefPubMedGoogle Scholar
  56. Monaghan, S., & Blaszczynski, A. (2005). Warning signs on electronic gaming machines: Recall and effects on cognitions and beliefs. In Proceedings of the 15th national association for gambling studies conference (pp. 166–186). Alice Springs N.T.Google Scholar
  57. Monaghan, S., & Blaszczynski, A. (2007). Recall of electronic gaming machine signs: A static versus a dynamic mode of presentation. Journal of Gambling Issues,20, 253–267.CrossRefGoogle Scholar
  58. Monaghan, S., & Blaszczynski, A. (2010). Electronic gaming machine warning messages: Information versus self-evaluation. The Journal of Psychology,144, 83.CrossRefGoogle Scholar
  59. Monaghan, S., Blaszczynski, A., & Nower, L. (2009). Do warning signs on electronic gaming machines influence irrational cognitions? Psychological Reports,105, 173–187.CrossRefGoogle Scholar
  60. Myrseth, H., Brunborg, G. S., & Eidem, M. (2010). Differences in cognitive distortions between pathological and non-pathological gamblers with preferences for chance or skill games. Journal of Gambling Studies,26(4), 561–569.  https://doi.org/10.1007/s10899-010-9180-6.CrossRefPubMedGoogle Scholar
  61. Oei, T. P. S., Lin, J., & Raylu, N. (2008). The relationship between gambling cognitions, psychological states, and gambling: A cross-cultural study of Chinese and caucasians in Australia. Journal of Cross-Cultural Psychology,39(2), 147–161.  https://doi.org/10.1177/0022022107312587.CrossRefGoogle Scholar
  62. Parke, J., & Griffiths, M. (2006). The psychology of the Fruit Machine: The role of structural characteristics (Revisited). International Journal of Mental Health and Addiction,4(2), 151–179.  https://doi.org/10.1007/s11469-006-9014-z.CrossRefGoogle Scholar
  63. Paxton, J. M., Ungar, L., & Greene, J. D. (2012). Reflection and reasoning in moral judgment. Cognitive Science,36(1), 163–177.  https://doi.org/10.1111/j.1551-6709.2011.01210.x.CrossRefPubMedGoogle Scholar
  64. Raylu, N., & Oei, T. P. S. (2004a). The Gambling Related Cognitions Scale (GRCS): Development, confirmatory factor validation and psychometric properties. Addiction,99, 757–769.CrossRefGoogle Scholar
  65. Raylu, N., & Oei, T. P. S. (2004b). The gambling urge scale: Development, confirmatory factor validation, and psychometric properties. Journal of the Society of Psychologists in Addictive Behaviors,18(2), 100–105.  https://doi.org/10.1037/0893-164X.18.2.100.CrossRefGoogle Scholar
  66. Riley-Smith, B., & Binder, J. (2003). Testing of harm minimisation messages for gaming machines. Government of New South Wales: Department of Gaming and Racing.Google Scholar
  67. Risen, J. L. (2016). Believing what we do not believe: Acquiescence to superstitious beliefs and other powerful intuitions. Psychological Review,123(2), 182–207.  https://doi.org/10.1037/rev0000017.CrossRefPubMedGoogle Scholar
  68. Riva, P., Sacchi, S., & Brambilla, M. (2015). Humanizing machines: Anthropomorphization of slot machines increases gambling. Journal of Experimental Psychology. Applied,21(4), 313–325.  https://doi.org/10.1037/xap0000057.CrossRefPubMedGoogle Scholar
  69. Rockloff, M. J. (2012). Validation of the consumption screen for problem gambling (CSPG). Journal of Gambling Studies,28(2), 207–216.  https://doi.org/10.1007/s10899-011-9260-2.CrossRefPubMedGoogle Scholar
  70. Sadler-Smith, E., & Shefy, E. (2004). The intuitive executive: Understanding and applying “gut feel” in decision-making. Academy of Management Language,18(4), 76–91.Google Scholar
  71. Sadler-Smith, E., Zhang, L.-F., & Sternberg, R. (2009). A duplex model of cognitive style. In Perspectives on the nature of intellectual styles (pp. 3–28). Retrieved from https://books.google.com.au/books?id=6drSmW4AbfEC&pg=PA3&dq=a+duplex+model+of+cognitive+style&hl=en&sa=X&ei=ruUUVbTpLJTW8gWCioGgBg&redir_esc=y#v=onepage&q&f=false
  72. Sévigny, S., & Ladouceur, R. (2003). Gamblers’ irrational thinking about chance events: The “double switching” concept. International Gambling Studies,3(2), 149–161.  https://doi.org/10.1080/1356347032000142261.CrossRefGoogle Scholar
  73. Sproston, K., Hing, N., & Palankay, C. (2012). Prevalence of gambling and problem gambling in New South Wales. Sydney: NSW Office of Liquor, Gaming and Racing.Google Scholar
  74. Srull, T. K., & Wyer, R. S. (1980). Category accessibility and social perception: Some implications for the study of person memory and interpersonal judgments. Journal of Personality and Social Psychology,38(6), 841–856.  https://doi.org/10.1037/0022-3514.38.6.841.CrossRefGoogle Scholar
  75. Sundali, J., & Croson, R. (2006). Biases in casino betting: The hot hand and the Gambler’s Fallacy. Judgement and Decision Making,1, 1–12.Google Scholar
  76. Swami, V., Pietschnig, J., Stieger, S., & Voracek, M. (2011). Alien psychology: Associations between extraterrestrial beliefs and paranormal ideation, superstitious beliefs, schizotypy, and the Big Five personality factors. Applied Cognitive Psychology,25(4), 647–653.  https://doi.org/10.1002/acp.1736.CrossRefGoogle Scholar
  77. Swami, V., Voracek, M., Stieger, S., Tran, U. S., & Furnham, A. (2014). Analytic thinking reduces belief in conspiracy theories. Cognition,133, 572–585.CrossRefGoogle Scholar
  78. Swekoski, D., & Barnbaum, D. (2013). The gambler’s fallacy, the therapeutic misconception, and unrealistic optimism. IRB: Ethics and Human Research,35(2), 1–6.PubMedGoogle Scholar
  79. Tang, C. S.-K., & Wu, A. M. S. (2012). Gambling-related cognitive biases and pathological gambling among youths, young adults, and mature adults in Chinese Societies. Journal of Gambling Studies,28(1), 139–154.  https://doi.org/10.1007/s10899-011-9249-x.CrossRefPubMedGoogle Scholar
  80. The Social Research Centre. (2013). Gambling Prevalence in South Australia. Adelaide: Office for Problem Gambling. Retrieved July, 2019, from http://www.problemgambling.sa.gov.au/professionals/news_and_events/news-items/release-of-the-2012-gambling-prevalence-study-in-south-australia/?a=13625.
  81. Toneatto, T., Blitz-Miller, T., Calderwood, K., Dragonetti, R., & Tsanos, A. (1997). Cognitive distortions in heavy gambling. Journal of Gambling Studies,13(3), 253–266.  https://doi.org/10.1023/A:1024983300428.CrossRefPubMedGoogle Scholar
  82. Turner, N. E., Zangeneh, M., & Littman-Sharp, N. (2006). The experience of gambling and its role in problem gambling. International Gambling Studies,6(2), 237–266.  https://doi.org/10.1080/14459790600928793.CrossRefGoogle Scholar
  83. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuritics and biases. Science,185(4157), 1124–1131.CrossRefGoogle Scholar
  84. Uhlmann, E. L., Poehlman, T. A., Tannenbaum, D., & Bargh, J. A. (2011). Implicit puritanism in American moral cognition. Journal of Experimental Social Psychology,47(2), 312–320.  https://doi.org/10.1016/j.jesp.2010.10.013.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Human, Medical, and Applied SciencesCentral Queensland UniversityWayvilleAustralia
  2. 2.School of Human, Medical, and Applied SciencesCentral Queensland UniversityBundabergAustralia
  3. 3.School of PsychologyThe University of SydneySydneyAustralia

Personalised recommendations