Skip to main content
SpringerLink
Log in

Personality, Perceived Luck and Gambling Attitudes as Predictors of Gambling Involvement

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

Abstract

A quantitative observational study was undertaken to examine the relationship between individual factors and level of gambling involvement, in particular problem gambling (PG). The specific factors under study were personality, perceived luck, and attitudes towards gambling. A sample of university students (N = 185) completed a battery of questionnaires, consisting of the 16PF, Canadian Problem Gambling Index, Belief in Good Luck Scale (BIGL), Gambling Attitudes Scale (GAS), and the Impulsive Non-Conformity subscale (ImpNon) from the Oxford-Liverpool Inventory of Feelings and Experiences. Four groups were formed (Non-PG, Low-Risk, Moderate-Risk, and PG). Personality profiles varied between groups, and there were significant main effects and interaction effects on gender and personality factors. The PG group was higher on impulsivity, and belief in luck, and had more positive attitudes towards gambling. Multiple Regression Analysis and Discriminant Functions Analysis, using variables including some 16PF factors, BIGL and GAS variables, produced models that were highly predictive of gambling severity and gambling membership. In both models, impulsivity was the strongest predictor. These results were discussed in terms of their implications for future research and treatment of PG.

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

Similar content being viewed by others

References

  • Anderson, G., & Brown, R. I. F. (1987). Classical and operant paradigms in the management of compulsive gamblers. Behavioural Psychotherapy, 15, 111–122.

    Article  Google Scholar 

  • Blaszczynski, A. P., & McConaghy, N. (1989). The medical model of pathological gambling: Current short-comings. Journal of Gambling Behavior, 5(1), 42–52.

    Article  Google Scholar 

  • Blume, S. B. (1987). Compulsive gambling and the medical model. Journal of Gambling Behaviour, 3, 237–249.

    Article  Google Scholar 

  • Brown, R. I. (1986). Arousal and sensation seeking components in the general explanation of gambling and gambling addictions. International Journal of the Addictions, 21, 1001–1016.

    CAS  PubMed  Google Scholar 

  • Carlton, P. L., & Manowitz, P. (1994). Factors determining the severity of pathological gambling in males. Journal of Gambling Studies, 10(2), 147–157.

    Article  Google Scholar 

  • Cattell, H. B. (1989). The 16PF: Personality in depth. Champaign, IL: IPAT.

    Google Scholar 

  • Cattell, R. B., Eber, H. W., & Tatsuoka, M. M. (1970). Handbook for the sixteen personality factor questionnaire (16PF). Champaign. IL: Institute for Personality and Ability Testing, Inc.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Darke, P. R., & Freedman, J. L. (1997). The belief in good luck scale. Journal of Research in Personality, 31, 486–511.

    Article  Google Scholar 

  • Day, L., & Maltby, J. (2003). Belief in good luck and psychological well-being: The mediating role of optimism and irrational beliefs. Journal of Psychology, 137, 99–110.

    PubMed  Google Scholar 

  • Desai, R. A., Maciejewski, P. K., Pantalon, M. V., & Potenza, M. N. (2005). Gender differences in adolescent gambling. Annals of Clinical Psychiatry, 17(4), 249–258.

    Article  PubMed  Google Scholar 

  • Ferris, J., & Wynne, H. (2001). The canadian problem gambling index final report–Phase II.–inter-provincial taskforce on problem gambling. Canada: Canadian Centre of Substance Abuse.

    Google Scholar 

  • Gibson, D., & Sanbonmatsu, D. M. (2004). Optimism, pessimism, and gambling: The downside of optimism. Personality and Social Psychology Bulletin, 30(2), 149–160.

    Article  PubMed  Google Scholar 

  • Gray, J. A. (1981). A critique of Eysenck’s theory of personality. In H. J. Eysenck (Ed.), A model of personality (pp. 246–276). Berlin: Springer.

    Google Scholar 

  • Greenson, T. (1947). On gambling. American Imago, 4, 61–65.

    CAS  Google Scholar 

  • Griffiths, M. D. (1989). Gambling in children and adolescents. Journal of Gambling Behaviour, 5, 66–83.

    Article  Google Scholar 

  • Gupta, R., Derevensky, J. L., & Ellenbogen, S. (2006). Personality characteristics and risk-taking tendencies among adolescent gamblers. Canadian Journal of Behavioural Science, 38(3), 201–213.

    Google Scholar 

  • Hardoon, K. K., Gupta, R., & Derevensky, J. L. (2004). Psychosocial variables associated with adolescent gambling. Psychology of Addictive Behaviours, 18(2), 170–179.

    Article  Google Scholar 

  • Hing, N., & Breen, H. (2001). Profiling lady luck: An empirical study of gambling and problem gambling amongst female club members. Journal of Gambling Studies, 17(1), 47–79.

    Article  CAS  PubMed  Google Scholar 

  • Hoorens, V. (1994). Unrealisitic optimism in health and safety risks. In D. R. Rutter & L. Quine (Eds.), Social psychology and health: European perspectives (pp. 153–174). Aldershot, UK: Avebury.

    Google Scholar 

  • Jacobs, D. (1986). A general theory of addictions: A new theoretical model. Journal of Gambling Behavior, 2, 15–31.

    Article  Google Scholar 

  • Kassinove, J. I. (1998). Development of the gambling attitude scales: Preliminary findings. Journal of Clinical Psychology, 54(6), 763–771.

    Article  CAS  PubMed  Google Scholar 

  • Kassinove, J. I., Tsytsarev, S. V., & Davidson, I. (1998). Russian attitudes toward gambling. Personality and Individual Differences, 24(1), 41–46.

    Article  Google Scholar 

  • Kerber, C. S. (2005). Problem and pathological gambling among college athletes. Annals of Clinical Psychiatry, 17(4), 243–247.

    Article  PubMed  Google Scholar 

  • Ladouceur, R. (1991). Prevalence estimates of pathological gamblers in Quebec, Canada. Canadian Journal of Psychiatry, 36, 732–734.

    CAS  Google Scholar 

  • Ladouceur, R., Boisvert, J. M., Pepin, M., Loranger, M., & Dumont, M. (1994). Social cost of pathological gambling. Journal of Gambling Studies, 10(4), 399–409.

    Article  Google Scholar 

  • Ladouceur, R., & Mireault, C. (1988). Gambling behaviours among high school students in the Quebec area. Journal of Gambling Behaviour, 4, 3–12.

    Article  Google Scholar 

  • Langewisch, M. W. J., & Frisch, G. R. (1998). Gambling behaviour and pathology in relation to impulsivity, sensation seeking, and risky behaviour in male college students. Journal of Gambling Studies, 14(3), 245–262.

    Article  Google Scholar 

  • Lesieur, H. R., & Blume, S. B. (1987). The South Oaks gambling screen (the SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 44, 1184–1188.

    Google Scholar 

  • Lesieur, H. R., & Klein, R. (1987). Pathological gambling among high school students. Addictive Behaviours, 12, 129–135.

    Article  CAS  Google Scholar 

  • Lorenz, V. C., & Yaffee, R. A. (1988). Pathological gambling: psychosomatic, emotional and marital difficulties as reported by the spouse. Journal of Gambling Behaviour, 4, 13–26.

    Article  Google Scholar 

  • Mason, O., & Claridge, G. (2006). The Oxford-Liverpool inventory of feelings and experiences (O-LIFE): Further description and extended norms. Schizophrenia Research, 82, 203–211.

    Article  PubMed  Google Scholar 

  • Mason, O., Claridge, G., & Jackson, M. (1995). New scales for the assessment of schizotypy. Personality and Individual Differences, 18(1), 7–13.

    Article  Google Scholar 

  • Moore, S. M., & Ohtsuka, K. (1999). Beliefs about control over gambling among young people, and their relation to problem gambling. Psychology of Addictive Behaviours, 13(4), 339–347.

    Article  Google Scholar 

  • Moran, E. (1970). Varieties of pathological gambling. British Journal of Psychiatry, 116, 593–597.

    Article  CAS  PubMed  Google Scholar 

  • Myers, D. G. (1993). Social psychology (4th ed.). New York: McGraw-Hill.

  • Ohtsuka, K., Bruton, E., DeLuca, L., & Borg, V. (1997). Sex differences in pathological gambling using gaming machines. Psychological Reports, 80(3, pt.1), 1051–1057.

    CAS  PubMed  Google Scholar 

  • Oskamp, S. (1991). Attitudes and opinions. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Peltzer, K., & Thole, J. M. (2000). Gambling attitudes among black South African university students. Psychological Reports, 86, 957–962.

    Article  CAS  PubMed  Google Scholar 

  • Powell, J., Hardoon, K., Derevensky, J., & Gupta, R. (1996). Gambling and risk taking behaviour amongst university students. Paper presented at the meeting of the 10th national conference on gambling behaviour, Chicago, MI.

  • Productivity Commission. (1999). Australia’s gambling industries: Final report. Canberra: Government Press.

    Google Scholar 

  • Raylu, N., & Oei, T. P. S. (2002). Pathological gambling: A comprehensive review. Clinical Psychology Review, 22, 1009–1061.

    Article  PubMed  Google Scholar 

  • Rosecrance, J. (1986). "The next best thing": A study of problem gambling. International Journal of the Addictions, 20(11–12), 1727–1739.

    Google Scholar 

  • Rotter, J. B. (1955). The role of the psychological situation in determining the direction of human behaviour. In M. R. Jones (Ed.), The Nebraska symposium on motication (Vol. 3, pp. 245–269). Lincoln, Nebraska: University of Nebraska.

    Google Scholar 

  • Russell, M. T., & Karol, D. L. (1994). The 16PF fifth edition administrator’s manual. Champaign, IL: Institute for Personality and Ability Testing.

    Google Scholar 

  • Schuerger, J. M. (1992). The sixteen personality factor questionnaire and its junior versions. Journal of Counselling and Development, 71, 231–244.

    Google Scholar 

  • Shaffer, H. J., Hall, M. N., & Vander Bilt, J. (1997). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A meta-analysis. Boston Massachusetts: Harvard Medical School Division on Addictions.

    Google Scholar 

  • Sharpe, L., & Tarrier, N. (1993). Towards a cognitive-behavioural theory of problem gambling. British Journal of Psychiatry, 162, 407–412.

    Article  CAS  PubMed  Google Scholar 

  • Shepherd, R., Ghodse, H., & London, M. (1998). A pilot study examining gambling behavior before and after the launch of the national lottery and scratch cards in the UK. Addiction Research, 6(1), 5–12.

    Article  Google Scholar 

  • Simmel, E. (1920). On psychoanalysis of the gambler. International Zeitschrift Psychoanalogie, 6, 397–425.

    Google Scholar 

  • Steel, Z., & Blaszczynski, A. (1996). Factorial structure of pathological gambling. Journal of Gambling Studies, 12, 3–20.

    Article  Google Scholar 

  • Volberg, R. A. (1994). The prevalence and demographics of pathological gamblers: implications for public health. American Journal of Public Health, 84, 237–241.

    Article  CAS  PubMed  Google Scholar 

  • Volberg, R. A., & Steadman, H. J. (1988). Refining prevalence estimates of pathological gambling. American Journal of Psychiatry, 145, 502–505.

    CAS  PubMed  Google Scholar 

  • Walker, M. B., & Dickerson, M. G. (1996). The prevalence of problem and pathological gambling: A critical analysis. Journal of Gambling Studies, 12(2), 233–249.

    Article  Google Scholar 

  • Watt, C., & Nagtegaal, M. (2000). Luck in action? Belief in good luck, psi-mediated instrumental response, and games of chance. The Journal of Parapsychology, 64, 33–52.

    Google Scholar 

  • Weiner, B., Frieze, I., Kukla, A., Reed, L., Rest, S., & Rosenbaum, R. (1971). Perceiving the causes of success and failure. New York: General Learning Press.

  • Wohl, M. J. A., & Enzle, M. E. (2003). The effects pf near wins and losses on self-perceived personal luck and subsequent gambling behaviour. Journal of Experimental Social Psychology, 39, 184–191.

    Article  Google Scholar 

  • Wohl, M. J. A., Young, M. M., & Hart, K. E. (2007). Self-perceptions of dispositional luck: Relationship to DSM gambling symptoms, subjective enjoyment of gambling and treatment readiness. Substance Use and Misuse, 42, 42–63.

    Article  Google Scholar 

  • Wood, R. T. A., & Griffiths, M. D. (1998). The acquisition, development and maintenance of lottery and scratchcard gambling in adolescence. Journal of Adolescence, 21(3), 265–273.

    Article  CAS  PubMed  Google Scholar 

  • Young, M., & Stevens, M. (2008). SOGS and CPGI: Parallel comparison on a diverse population. Journal of Gambling Studies, 24(3), 337–356.

    Article  PubMed  Google Scholar 

  • Zuckermann, M., Kuhlman, D. M., Thornquist, M., & Kiers, H. (1991). Five (or three) robust questionnaire scale factors of personality without culture. Personality and Individual Differences, 12, 929–941.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Psychology, University of Adelaide, Adelaide, SA, 5005, Australia

    Jamie Chiu & Lance Storm

Authors
  1. Jamie Chiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lance Storm
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lance Storm.

Appendices

Appendix 1

See Table A1.

Table A1 Pearson’s correlations between CPGI and variables used in the MRA
Full size table

Appendix 2

Procedure for the Discriminant Functions Analysis

The following criteria were adopted in order to reduce the large pool of independent variables under consideration. First, for highly correlated variables (r ≥ 0.50), only one of the pair would be included in the DA, which also serves to eliminate the multicollinearity problem (note that Cohen 1988, gives the following guidelines for determining the strength of r: small, r = 0.1; medium, r = 0.3; large, r = 0.5). Second, the significantly-correlated variable in a pair with a non-significant F-ratio would be excluded, or if the F-ratio was significant, the correlating variable with the weakest F-ratio of the two would be excluded (F-ratios are those listed for the ANOVA results in Table 4).

Several 16PF primary factors were highly correlated with each other (e.g. Tension was highly correlated with Apprehension, r = 0.56, p < 0.001). The GAS subscales were also highly correlated with each other, so only GAS-general was included in the DA as the largest differences between the gambling groups were found for this GAS subscale. Gender was also included since significant gambling group differences were found (see Table 3).

Sixteen short-listed variables were considered: gender, BIGL, ImpNon, GAS-general, eleven 16PF factors (i.e. Warmth, Reasoning, Emotional Stability, Dominance, Rule-Consciousness, Social Boldness, Sensitivity, Vigilance, Openness to Change, Perfectionism, and Tension), and Impression Management (IM). From the above 16 variables, the seven with the weakest F-ratios were excluded from the analysis, resulting in nine variables: gender, ImpNon, BIGL, GAS-general, and five 16PF primary factors (i.e. Emotional Stability, Dominance, Perfectionism, Tension, and Reasoning).

A baseline (within-groups) discriminant analysis was run and the accuracy rate was 78.4%. Box’s M test was significant, F(56,33755.68)  = 4.61, p < 0.001, so we concluded that the groups do differ in their covariance matrices, violating an assumption of DA. The DA was re-run using separate-group covariance matrices for classification, but it was considered necessary to check for outliers by examining the Squared Mahalanobis Distance from the centroid. The critical value was 21.67, and there were five cases with a Mahalanobis D2 > 21.67. These five were regarded as outliers, and were omitted, resulting in 33 cases in the Non-PG group, 43 in the Low-Risk group, 89 in the Moderate-Risk group, and 15 in the PG group: 180 cases in all.

The accuracy rate increased by more than 2% after the removal of outliers, but the Box’s M test was still significant, F(90,29905.71)  = 4.60, p < 0.001. It is noted, however, that the DA is a robust procedure and the tolerances for all the IVs were above 0.10, indicating no problem of multicollinearity, which undermines the Box’s M test result.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chiu, J., Storm, L. Personality, Perceived Luck and Gambling Attitudes as Predictors of Gambling Involvement. J Gambl Stud 26, 205–227 (2010). https://doi.org/10.1007/s10899-009-9160-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10899-009-9160-x

Keywords

Search

Navigation