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Journal of Gambling Studies

, Volume 33, Issue 3, pp 881–897 | Cite as

Internet Gamblers Differ on Social Variables: A Latent Class Analysis

  • Yasser KhazaalEmail author
  • Anne Chatton
  • Sophia Achab
  • Gregoire Monney
  • Gabriel Thorens
  • Magali Dufour
  • Daniele Zullino
  • Stephane Rothen
Original Article

Abstract

Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression–Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression–Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

Keywords

Internet gambling Poker Latent class analysis Impulsivity Loneliness Depression Debt 

Notes

Acknowledgements

The authors wish to thank the participants of the study. This research was supported by a grant from a Swiss Inter-Cantonal program aiming to prevent gambling addiction.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Abarbanel, B. L., & Bernhard, B. J. (2012). Chicks with decks: The female lived experience in poker. International Gambling Studies, 12(3), 367–385. doi: 10.1080/14459795.2012.680900.CrossRefGoogle Scholar
  2. Afifi, T. O., Cox, B. J., Martens, P. J., Sareen, J., & Enns, M. W. (2010). Demographic and social variables associated with problem gambling among men and women in Canada. [Research Support, Non-U.S. Gov’t]. Psychiatry Research, 178(2), 395–400. doi: 10.1016/j.psychres.2009.10.003.CrossRefPubMedGoogle Scholar
  3. Auer, M., Malischnig, D., & Griffiths, M. (2014). Is “pop-up” messaging in online slot machine gambling effective as a responsible gambling strategy? Journal of Gambling Issues, 29, 1–10.CrossRefGoogle Scholar
  4. Barrault, S., Untas, A., & Varescon, I. (2014). Special features of poker. International Gambling Studies, 14(3), 492–504.CrossRefGoogle Scholar
  5. Barrault, S., & Varescon, I. (2013). Cognitive distortions, anxiety, and depression among regular and pathological gambling online poker players. Cyberpsychology, Behavior, and Social Networking, 16(3), 183–188. doi: 10.1089/cyber.2012.0150.CrossRefGoogle Scholar
  6. Barrault, S., & Varescon, I. (2016). Online and live regular poker players: Do they differ in impulsive sensation seeking and gambling practice? J Behav Addict, 5(1), 41–50.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Billieux, J., Rochat, L., Ceschi, G., Carre, A., Offerlin-Meyer, I., Defeldre, A. C., et al. (2012a). Validation of a short French version of the UPPS-P Impulsive Behavior Scale. Comprehensive Psychiatry, 53(5), 609–615. doi: 10.1016/j.comppsych.2011.09.001.CrossRefPubMedGoogle Scholar
  8. Billieux, J., Van der Linden, M., Khazaal, Y., Zullino, D., & Clark, L. (2012b). Trait gambling cognitions predict near-miss experiences and persistence in laboratory slot machine gambling. British Journal of Psychology, 103(3), 412–427. doi: 10.1111/j.2044-8295.2011.02083.x.CrossRefPubMedGoogle Scholar
  9. Bjerg, O. (2010). Problem gambling in poker: Money, rationality and control in a skill-based social game. International Gambling Studies, 10(3), 239–254. doi: 10.1080/14459795.2010.520330.CrossRefGoogle Scholar
  10. Canale, N., Vieno, A., Griffiths, M. D., Marino, C., Chieco, F., Disperati, F., et al. (2016). The efficacy of a web-based gambling intervention program for high school students: A preliminary randomized study. Computers in Human Behavior, 55, 946–949S.CrossRefGoogle Scholar
  11. Castren, S., Basnet, S., Salonen, A. H., Pankakoski, M., Ronkainen, J. E., Alho, H., et al. (2013). Factors associated with disordered gambling in Finland. Substance Abuse Treatment, Prevention, and Policy, 8, 24. doi: 10.1186/1747-597X-8-24.CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cole, T., Barrett, D. J., & Griffiths, M. D. (2011). Social facilitation in online and offline gambling: A pilot study. International Journal of Mental Health and Addiction, 9(3), 240–247.CrossRefGoogle Scholar
  13. Corney, R., & Davis, J. (2010). The attractions and risks of Internet gambling for women: A qualitative study. Journal of Gambling Issues, 24, 121–139. doi: 10.4309/jgi.2010.24.8.CrossRefGoogle Scholar
  14. Currie, S. R., Hodgins, D. C., & Casey, D. M. (2013). Validity of the Problem Gambling Severity Index interpretive categories. [Research Support, Non-U.S. Gov’t]. Journal of Gambling Studies, 29(2), 311–327. doi: 10.1007/s10899-012-9300-6.CrossRefPubMedGoogle Scholar
  15. Donati, M. A., Ancona, F., Chiesi, F., & Primi, C. (2015). Psychometric properties of the Gambling Related Cognitions Scale (GRCS) in young Italian gamblers. Addictive Behaviors, 45, 1–7. doi: 10.1016/j.addbeh.2015.01.001.CrossRefPubMedGoogle Scholar
  16. D’Orta, I., Burnay, J., Aiello, D., Niolu, C., Siracusano, A., Timpanaro, L., et al. (2015). Development and validation of a short Italian UPPS-P Impulsive Behavior Scale. Addictive Behaviors Reports, 2, 19–22.CrossRefGoogle Scholar
  17. Dufour, M., Brunelle, N., & Roy, E. (2013). Are Poker Players All the Same? Latent Class Analysis. Journal of Gambling Studies. doi: 10.1007/s10899-013-9429-y.Google Scholar
  18. Gainsbury, S. M. (2015). Online gambling addiction: The relationship between internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Gainsbury, S. M., Russell, A., Blaszczynski, A., & Hing, N. (2015). Greater involvement and diversity of Internet gambling as a risk factor for problem gambling. The European Journal of Public Health, 25(4), 723–728.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Gainsbury, S. M., Russell, A., Hing, N., Wood, R., Lubman, D. I., & Blaszczynski, A. (2014a). The prevalence and determinants of problem gambling in Australia: Assessing the impact of interactive gambling and new technologies. Psychology of Addictive Behaviors, 28(3), 769–779. doi: 10.1037/a0036207.CrossRefPubMedGoogle Scholar
  21. Gainsbury, S. M., Suhonen, N., & Saastamoinen, J. (2014b). Chasing losses in online poker and casino games: Characteristics and game play of Internet gamblers at risk of disordered gambling. Psychiatry Research. doi: 10.1016/j.psychres.2014.03.033.PubMedGoogle Scholar
  22. Grall-Bronnec, M., Bouju, G., Sébille-Rivain, V., Gorwood, P., Boutin, C., Vénisse, J. L., et al. (2012a). A French adaptation of the Gambling-Related Cognitions Scale (GRCS): A useful tool for assessment of irrational thoughts among gamblers. Journal of Gambling Issues, 27, 1–21. doi: 10.4309/jgi.2012.27.9.CrossRefGoogle Scholar
  23. Grall-Bronnec, M., Wainstein, L., Feuillet, F., Bouju, G., Rocher, B., Venisse, J. L., et al. (2012b). Clinical profiles as a function of level and type of impulsivity in a sample group of at-risk and pathological gamblers seeking treatment. [Research Support, Non-U.S. Gov’t]. Journal of Gambling Studies, 28(2), 239–252. doi: 10.1007/s10899-011-9258-9.CrossRefPubMedGoogle Scholar
  24. Griffiths, M., Parke, J., Wood, R., & Rigbye, J. (2010). Online poker gambling in university students: Further findings from an online survey. International Journal of Mental Health and Addiction, 8(1), 82–89.CrossRefGoogle Scholar
  25. Griffiths, M., Wardle, H., Orford, J., Sproston, K., & Erens, B. (2008). Sociodemographic correlates of internet gambling: Findings from the 2007 British gambling prevalence survey. CyberPsychology & Behavior, 12, 199–202.CrossRefGoogle Scholar
  26. Hing, N., & Breen, H. (2001). Profiling lady luck: An empirical study of gambling and problem gambling amongst female club members. [Comparative Study]. Journal of Gambling Studies, 17(1), 47–69.CrossRefPubMedGoogle Scholar
  27. Hing, N., Russell, A. M., & Gainsbury, S. M. (2016a). Unpacking the public stigma of problem gambling: The process of stigma creation and predictors of social distancing. Journal of Behavioral Addictions, 5(3), 448–456. doi: 10.1556/2006.5.2016.057.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Hing, N., Russell, A. M., Gainsbury, S. M., & Nuske, E. (2016b). The public stigma of problem gambling: Its nature and relative intensity compared to other health conditions. Journal of Gambling Studies, 32(3), 847–864. doi: 10.1007/s10899-015-9580-8.CrossRefPubMedGoogle Scholar
  29. Hing, N., Russell, A., Tolchard, B., & Nower, L. (2016c). Risk factors for gambling problems: An analysis by gender. Journal of Gambling Studies, 32, 511–534.CrossRefPubMedGoogle Scholar
  30. Hodgins, D. C., Stea, J. N., & Grant, J. E. (2011). Gambling disorders. [Review]. Lancet, 378(9806), 1874–1884. doi: 10.1016/S0140-6736(10)62185-X.CrossRefPubMedGoogle Scholar
  31. Holdsworth, L., Hing, N., & Breen, H. (2012). Exploring women’s problem gambling: A review of the literature. International Gambling Studies, 12(2), 199–213. doi: 10.1080/14459795.2012.656317.CrossRefGoogle Scholar
  32. Holtgraves, T. (2009). Evaluating the problem gambling severity index. [Evaluation Studies Research Support, Non-U.S. Gov’t]. Journal of Gambling Studies, 25(1), 105–120. doi: 10.1007/s10899-008-9107-7.CrossRefPubMedGoogle Scholar
  33. Hopley, A. A., & Nicki, R. M. (2010). Predictive factors of excessive online poker playing. [Research Support, Non-U.S. Gov’t]. Cyberpsychology, Behavior, and Social Networking, 13(4), 379–385. doi: 10.1089/cyber.2009.0223.CrossRefGoogle Scholar
  34. Husky, M. M., Michel, G., Richard, J. B., Guignard, R., & Beck, F. (2015). Gender differences in the associations of gambling activities and suicidal behaviors with problem gambling in a nationally representative French sample. Addictive Behaviors, 45, 45–50.CrossRefPubMedGoogle Scholar
  35. Joseph, S., Linley, P. A., Harwood, J., Lewis, C. A., & McCollam, P. (2004). Rapid assessment of well-being: The Short Depression–Happiness Scale (SDHS). [Validation Studies]. Psychology and Psychotherapy, 77(Pt 4), 463–478. doi: 10.1348/1476083042555406.CrossRefPubMedGoogle Scholar
  36. Khazaal, Y., Achab, S., Billieux, J., Thorens, G., Zullino, D., Dufour, M., et al. (2015). Factor structure of the internet addiction test in online gamers and poker players. JMIR Mental Health, 2(2), e12. doi: 10.2196/mental.3805.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Khazaal, Y., Billieux, J., Thorens, G., Khan, R., Louati, Y., Scarlatti, E., et al. (2008a). French validation of the internet addiction test. CyberPsychology & Behavior, 11(6), 703–706.CrossRefGoogle Scholar
  38. Khazaal, Y., Chatton, A., Bouvard, A., Khiari, H., Achab, S., & Zullino, D. (2013). Internet poker websites and pathological gambling prevention policy. Journal of Gambling Studies, 29(1), 51–59. doi: 10.1007/s10899-011-9288-3.CrossRefPubMedGoogle Scholar
  39. Khazaal, Y., Chatton, A., Cochand, S., Jermann, F., Osiek, C., Bondolfi, G., et al. (2008b). Quality of web-based information on pathological gambling. Journal of Gambling Studies, 24(3), 357–366.CrossRefPubMedGoogle Scholar
  40. Khazaal, Y., van Singer, M., Chatton, A., Achab, S., Zullino, D., Rothen, S., et al. (2014). Does self-selection affect samples’ representativeness in online surveys? An investigation in online video game research. Journal of Medical Internet Research, 16(7), e164. doi: 10.2196/jmir.2759.CrossRefPubMedPubMedCentralGoogle Scholar
  41. Kim, H. S., Hodgins, D. C., Bellringer, M., & Abbott, M. (2016). Gender differences among helpline callers: Prospective study of gambling and psychosocial outcomes. Journal of Gambling Studies, 32(2), 605–623. doi: 10.1007/s10899-015-9572-8.CrossRefPubMedGoogle Scholar
  42. Ladouceur, R., Goulet, A., & Vitaro, F. (2013). Prevention programmes for youth gambling: A review of the empirical evidence. International Gambling Studies, 13(2), 141–159.CrossRefGoogle Scholar
  43. Lee, H. W., Choi, J. S., Shin, Y. C., Lee, J. Y., Jung, H. Y., & Kwon, J. S. (2012). Impulsivity in internet addiction: A comparison with pathological gambling. [Comparative Study]. Cyberpsychol Behav Soc Netw, 15(7), 373–377. doi: 10.1089/cyber.2012.0063.CrossRefPubMedGoogle Scholar
  44. Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144(9), 1184–1188.CrossRefPubMedGoogle Scholar
  45. Liley, J., & Rakow, T. (2010). Probability estimation in poker: A qualified success for unaided judgment. Journal of behavioral decision making, 23(5), 496–526. doi: 10.1002/bdm.670.CrossRefGoogle Scholar
  46. Lim, L. L., & Kua, E. H. (2011). Living alone, loneliness, and psychological well-being of older persons in singapore. Current Gerontology and Geriatrics Research, 2011, 673181. doi: 10.1155/2011/673181.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Linnet, J., Frøslev, M., Ramsgaard, S., Gebauer, L., Mouridsen, K., & Wohlert, V. (2012). Impaired probability estimation and decision-making in pathological gambling poker players. Journal of Gambling Studies, 28(1), 113–122. doi: 10.1007/s10899-011-9244-2.CrossRefPubMedGoogle Scholar
  48. Lloyd, J., Doll, H., Hawton, K., Dutton, W. H., Geddes, J. R., Goodwin, G. M., et al. (2010). How psychological symptoms relate to different motivations for gambling: An online study of internet gamblers. [Research Support, Non-U.S. Gov’t]. Biological Psychiatry, 68(8), 733–740. doi: 10.1016/j.biopsych.2010.03.038.CrossRefPubMedGoogle Scholar
  49. 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. [Meta-Analysis Research Support, Non-U.S. Gov’t Review]. Addiction, 106(3), 490–498. doi: 10.1111/j.1360-0443.2010.03300.x.CrossRefPubMedGoogle Scholar
  50. Maclaren, V. V., Fugelsang, J. A., Harrigan, K. A., & Dixon, M. J. (2011). The personality of pathological gamblers: A meta-analysis. Clinical Psychology Review, 31(6), 1057–1067. doi: 10.1016/j.cpr.2011.02.002.CrossRefPubMedGoogle Scholar
  51. MacLaren, V. V., Harrigan, K. A., & Dixon, M. (2012). Gambling motives and symptoms of problem gambling in frequent slots players. Journal of Gambling Issues, 27, 1–13. doi: 10.4309/jgi.2012.27.8.CrossRefGoogle Scholar
  52. McCormack, A., Shorter, G. W., & Griffiths, M. D. (2014). An empirical study of gender differences in online gambling. Journal of Gambling Studies, 30(1), 71–88. doi: 10.1007/s10899-012-9341-x.CrossRefPubMedGoogle Scholar
  53. McDaniel, S. R., & Zuckerman, M. (2003). The relationship of impulsive sensation seeking and gender to interest and participation in gambling activities. Personality and Individual Differences, 35(6), 1385–1400.CrossRefGoogle Scholar
  54. Michalczuk, R., Bowden-Jones, H., Verdejo-Garcia, A., & Clark, L. (2011). Impulsivity and cognitive distortions in pathological gamblers attending the UK National Problem Gambling Clinic: A preliminary report. [Research Support, Non-U.S. Gov’t]. Psychological Medicine, 41(12), 2625–2635. doi: 10.1017/S003329171100095X.CrossRefPubMedPubMedCentralGoogle Scholar
  55. Mihaylova, T., Kairouz, S., & Nadeau, L. (2012). Online poker gambling among university students: Risky endeavour or harmless pastime? Journal of Gambling Issues, 27, 1–18.Google Scholar
  56. Milosevic, A., & Ledgerwood, D. M. (2010). The subtyping of pathological gambling: A comprehensive review. [Research Support, Non-U.S. Gov’t Review]. Clinical Psychology Review, 30(8), 988–998. doi: 10.1016/j.cpr.2010.06.013.CrossRefPubMedGoogle Scholar
  57. Monney, G., Penzenstadler, L., Dupraz, O., Etter, J.-F., & Khazaal, Y. (2015). mHealth app for cannabis users: Satisfaction and perceived usefulness. Frontiers in Psychiatry. doi: 10.3389/fpsyt.2015.00120.Google Scholar
  58. Müller, K. W., Dreier, M., Beutel, M. E., & Wölfling, K. (2016). Is Sensation Seeking a correlate of excessive behaviors and behavioral addictions? A detailed examination of patients with gambling disorder and internet addiction. Psychiatry Research. doi: 10.1016/j.psychres.2016.06.004.Google Scholar
  59. Nordmyr, J., Forsman, A. K., Wahlbeck, K., Björkqvist, K., & Österman, K. (2014). Associations between problem gambling, socio-demographics, mental health factors and gambling type: Sex differences among Finnish gamblers. International Gambling Studies, 14(1), 39–52. doi: 10.1080/14459795.2013.840328.CrossRefGoogle Scholar
  60. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535–569.CrossRefGoogle Scholar
  61. O’Leary, K., & Carroll, C. (2013). The online poker sub-culture: Dialogues, interactions and networks. Journal of Gambling Studies, 29(4), 613–630. doi: 10.1007/s10899-012-9326-9.CrossRefPubMedGoogle Scholar
  62. Palomaki, J., Laakasuo, M., & Salmela, M. (2013). “Don’t worry, it’s just poker!”—Experience, self-rumination and self-reflection as determinants of decision-making in on-line poker. Journal of Gambling Studies, 29(3), 491–505. doi: 10.1007/s10899-012-9311-3.CrossRefPubMedGoogle Scholar
  63. Parke, A., & Griffiths, M. D. (2011). Poker gambling virtual communities: The use of computer-mediated communication to develop cognitive poker gambling skills. International Journal of Cyber Behavior, Psychology and Learning, 1(2), 31–44. doi: 10.4018/ijcbpl.2011040103.CrossRefGoogle Scholar
  64. Porter, J., Ungar, J., Frisch, G. R., & Chopra, R. (2004). Loneliness and life dissatisfaction in gamblers. Journal of Gambling Issues, (11). doi: 10.4309/jgi.2004.11.14.
  65. Raylu, N., & Oei, T. P. (2004). The Gambling Related Cognitions Scale (GRCS): Development, confirmatory factor validation and psychometric properties. [Clinical Trial Randomized Controlled Trial]. Addiction, 99(6), 757–769. doi: 10.1111/j.1360-0443.2004.00753.x.CrossRefPubMedGoogle Scholar
  66. Sharpe, D. (2015). Your Chi square test is statistically significant: Now what? Practical Assessment, Research and Evaluation, 20(8), 2–10.Google Scholar
  67. Shen, Y., Kairouz, S., Nadeau, L., & Robillard, C. (2015). Comparing problem gamblers with moderate-risk gamblers in a sample of university students. [Research Support, Non-U.S. Gov’t]. Journal of Behavioral Addictions, 4(2), 53–59. doi: 10.1556/2006.4.2015.002.CrossRefPubMedPubMedCentralGoogle Scholar
  68. Stewart, S. H., & Zack, M. (2008). Development and psychometric evaluation of a three-dimensional Gambling Motives Questionnaire. [Evaluation Studies Research Support, Non-U.S. Gov’t]. Addiction, 103(7), 1110–1117. doi: 10.1111/j.1360-0443.2008.02235.x.CrossRefPubMedGoogle Scholar
  69. Svensson, J., & Romild, U. (2014). Problem gambling features and gendered gambling domains amongst regular gamblers in a Swedish population-based study. Sex Roles, 70, 240–254. doi: 10.1007/s11199-014-0354-z.CrossRefPubMedPubMedCentralGoogle Scholar
  70. Trevorrow, K., & Moore, S. (1988). The association between loneliness, social isolation and women’s electronic gaming machine gambling. Journal of Gambling Studies, 14(3), 263–284.CrossRefGoogle Scholar
  71. Wood, R. T., Griffiths, M. D., & Parke, J. (2007). Acquisition, development, and maintenance of online poker playing in a student sample. CyberPsychology & Behavior, 10(3), 354–361. doi: 10.1089/cpb.2006.9944.CrossRefGoogle Scholar
  72. 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.CrossRefGoogle Scholar
  73. Wood, R. T., & Williams, R. J. (2011). A comparative profile of the Internet gambler: Demographic characteristics, game-play patterns, and problem gambling status. New Media & Society, 13(7), 1123–1141. doi: 10.1177/1461444810397650.CrossRefGoogle Scholar
  74. Young, K. S. (1998). Caught in the net. New York: Wiley.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Geneva University HospitalsGenevaSwitzerland
  2. 2.Faculty of MedicineGeneva UniversityGenevaSwitzerland
  3. 3.Research CenterMontreal University Institute of Mental HealthMontrealCanada
  4. 4.Sherbrooke UniversityMontrealCanada

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