Current Addiction Reports

, Volume 3, Issue 4, pp 437–444 | Cite as

Assessing Problem Gambling: a Review of Classic and Specialized Measures

  • Kyle Caler
  • Jose Ricardo Vargas Garcia
  • Lia Nower
Gambling (J Derevensky, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Gambling


Purpose of Review

The rapid expansion of legalized gambling opportunities over the past 20 years has generated interest in problem gambling and gambling disorder. This review will provide an overview of classic and newer instruments in the field.

Recent Findings

Early instruments in the field of gambling studies were focused exclusively on population prevalence or diagnosis of disorder. However, a growing body of research, particularly in the clinical and neurobiological areas, have led to the development of a targeted measurement instruments and increased specialization designed for screening of a gambling disorder. Newer instruments and those that with renewed clinical and research interest are focused on specific areas such as cognitive distortions, and control of urges and cravings, which are key components of sustained recovery.


Measurement in the field of problem gambling is moving away from solely measuring population prevalence and psychiatric disorder toward targeting the specific mechanisms that underlie problem gambling and barriers to recovery. Future advances in measurement will necessitate using standardized measures to assess various facets of problem gambling and adopting a holistic approach to assessing facets synergistically to identify sub-groups and inform targeted treatment strategies.


Assessment Gambling disorder Pathological gambling Problem gambling Measurement Gambling treatment 


Compliance with Ethical Standards

Conflict of Interest

Kyle Caler, Jose Ricardo Vargas Garcia, and Lia Nower report no conflicts of interest regarding this review. Lia Nower has served as an expert witness in gambling-related legal cases and as a consultant for government, industry, and research projects; she has received funding for research grants from international state and provincial funding agencies.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.


Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.••
    Stinchfield R: A review of problem gambling assessment instruments and brief screens. In: David CSR, Blaszczynski A, Nower L, editors. The Wiley-Blackwell handbook of disordered gambling. 2013. The purpose of the assessment should dictate the measure used; the level of problem severity may or may not be relevant to all factors assessed. Google Scholar
  2. 2.
    Edgren R, Castrén S, Mäkelä M, Pörtfors P, Alho H, Salonen AH. Reliability of instruments measuring at-risk and problem gambling among young individuals: a systematic review covering years 2009–2015. J Adolesc Health. 2016;58(6):600–15.CrossRefPubMedGoogle Scholar
  3. 3.
    Lesieur HR, Blume SB. The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers. JAMA Psychiatry. 1987;144(9):1184–8.Google Scholar
  4. 4.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders, 3rd edition. Author; 1980.Google Scholar
  5. 5.
    Stinchfield R. Reliability, validity, and classification accuracy of the South Oaks Gambling Screen (SOGS). Addict Behav Rep. 2002;27(1):1–9.CrossRefGoogle Scholar
  6. 6.
    Goodie AS et al. Evaluating the South Oaks Gambling Screen with DSM-IV and DSM-5 criteria results from a diverse community sample of gamblers. Assessment. 2013;20(5):523–31.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Duvarci İ, Varan A, Coşkunol H, Ersoy MA. DSM-IV and the South Oaks Gambling Screen: diagnosing and assessing pathological gambling in Turkey. J Gambl Stud. 1997;13(3):193–206.CrossRefPubMedGoogle Scholar
  8. 8.
    Strong DR, Lesieur HR, Breen RB, Stinchfield R, Lejuez CW. Using a Rasch model to examine the utility of the South Oaks Gambling Screen across clinical and community samples. Addict Behav Rep. 2004;29(3):465–81.CrossRefGoogle Scholar
  9. 9.
    Room R, Turner NE, Ialomiteanu A. Community effects of the opening of the Niagara casino. Br J Addict. 1999;94(10):1449–66.CrossRefGoogle Scholar
  10. 10.
    Gerstein D et al. Gambling impact and behavior study: report to the national gambling impact study commission. Chicago: National Opinion Research Center; 1999.Google Scholar
  11. 11.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders, 4th edition. Author; 1994.Google Scholar
  12. 12.
    Hodgins DC. Using the NORC DSM Screen for Gambling Problems as an outcome measure for pathological gambling: psychometric evaluation. Addict Behav Rep. 2004;29(8):1685–90.CrossRefGoogle Scholar
  13. 13.
    Wulfert E, Hartley J, Lee M, Wang N, Franco C, Sodano R. Gambling screens: does shortening the time frame affect their psychometric properties? J Gambl Stud. 2005;21(4):521–36.CrossRefPubMedGoogle Scholar
  14. 14.
    Wickwire Jr EM, Burke RS, Brown SA, Parker JD, May RK. Psychometric evaluation of the national opinion research center DSM-IV screen for gambling problems (NODS). Am J Addict. 2008;17(5):392–5.CrossRefPubMedGoogle Scholar
  15. 15.
    Toce-Gerstein M, Gerstein DR, Volberg RA. The NODS–CLiP: a rapid screen for adult pathological and problem gambling. J Gambl Stud. 2009;25(4):541–55.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Volberg RA, Munck IM, Petry NM. A quick and simple screening method for pathological and problem gamblers in addiction programs and practices. Am J Addict. 2011;20(3):220–7.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Gebauer L, LaBrie R, Shaffer HJ. Optimizing DSM-IV-TR classification accuracy: a brief biosocial screen for detecting current gambling disorders among gamblers in the general household population. Can J Psychiatr. 2010;55(2):82–90.Google Scholar
  18. 18.
    Brett EI, Weinstock J, Burton S, Wenzel KR, Weber S, Moran S. Do the DSM-5 diagnostic revisions affect the psychometric properties of the Brief Biosocial Gambling Screen? Int Gambl Stud. 2014;14(3):447–56.CrossRefGoogle Scholar
  19. 19.
    Himelhoch SS et al. Evaluation of brief screens for gambling disorder in the substance use treatment setting. Am J Addict. 2015;24(5):460–6.CrossRefPubMedGoogle Scholar
  20. 20.
    Castrén S, Salonen AH, Alho H, Lahti T, Simojoki K. Past-year gambling behaviour among patients receiving opioid substitution treatment. Subst Abuse Treat Prev Policy. 2015;10(1):1–6.CrossRefGoogle Scholar
  21. 21.
    LaPlante DA, Nelson SE, Gray HM. Breadth and depth involvement: understanding internet gambling involvement and its relationship to gambling problems. Psychol Addict Behav. 2014;28(2):396–403.CrossRefPubMedGoogle Scholar
  22. 22.
    Tom MA, LaPlante DA, Shaffer HJ. Does Pareto rule internet gambling? Problems among the “vital few” & “trivial many”. Journal of Gambling Business & Economics. 2014;8(1):73–100.Google Scholar
  23. 23.
    Ferris J, Wynne H. The Canadian problem gambling index. Canadian Centre on Substance Abuse: Ottawa, ON; 2001.Google Scholar
  24. 24.
    Jackson AC, Wynne H, Dowling NA, Tomnay JE, Thomas SA. Using the CPGI to determine problem gambling prevalence in Australia: measurement issues. Int J Ment Health Addict. 2010;8(4):570–82.CrossRefGoogle Scholar
  25. 25.
    Colasante E et al. An assessment of the psychometric properties of Italian version of CPGI. J Gambl Stud. 2013;29(4):765–74.CrossRefPubMedGoogle Scholar
  26. 26.
    Back KJ, Williams RJ, Lee CK. Reliability and validity of three instruments (DSM-IV, CPGI, and PPGM) in the assessment of problem gambling in South Korea. J Gambl Stud. 2015;31(3):775–86.CrossRefPubMedGoogle Scholar
  27. 27.
    Abbott MW, Volberg RA. The measurement of adult problem and pathological gambling. Int Gambl Stud. 2006;6(2):175–200.CrossRefGoogle Scholar
  28. 28.
    Boldero JM, Bell RC. An evaluation of the factor structure of the Problem Gambling Severity Index. Int Gambl Stud. 2012;12(1):89–110.CrossRefGoogle Scholar
  29. 29.
    Miller NV, Currie SR, Hodgins DC, Casey D. Validation of the problem gambling severity index using confirmatory factor analysis and rasch modelling. Int J Methods Psychiatr Res. 2013;22(3):245–55.PubMedGoogle Scholar
  30. 30.••
    Currie SR, Hodgins DC, Casey DM. Validity of the problem gambling severity index interpretive categories. J Gambl Stud. 2013;29(2):311–27. In a test of temporal stability, PGSI was valid validity for non-problem and problem gambling categories but not low-risk and moderate-risk categories; the authors suggest scoring changes to better distinguish risk-levels.CrossRefPubMedGoogle Scholar
  31. 31.
    Derevensky JL, Gupta R. Prevalence estimates of adolescent gambling: a comparison of the SOGS-RA, DSM-IV-J, and the GA 20 questions. J Gambl Stud. 2000;16(2–3):227–51.CrossRefPubMedGoogle Scholar
  32. 32.
    Kuley NB, Jacobs DF. The relationship between dissociative-like experiences and sensation seeking among social and problem gamblers. J Gambl Behav. 1988;4(3):197–207.CrossRefGoogle Scholar
  33. 33.
    Ursua MP, Uribelarrea LL. 20 questions of gamblers anonymous: a psychometric study with population of Spain. J Gambl Stud. 1998;14(1):3–15.CrossRefPubMedGoogle Scholar
  34. 34.
    Toneatto T. Reliability and validity of the gamblers anonymous twenty questions. J Psychopathol Behav Assess. 2008;30(1):71–8.CrossRefGoogle Scholar
  35. 35.
    Johnson EE, Hamer R, Nora RM, Tan B, Eisenstein N, Engelhart C. The Lie/Bet Questionnaire for screening pathological gamblers. Psychol Rep. 1997;80(1):83–8.CrossRefPubMedGoogle Scholar
  36. 36.
    Larsen CV, Curtis T, Bjerregaard P. Gambling behavior and problem gambling reflecting social transition and traumatic childhood events among Greenland Inuit: a cross-sectional study in a large indigenous population undergoing rapid change. J Gambl Stud. 2013;29(4):733–48.CrossRefPubMedGoogle Scholar
  37. 37.
    Engel RJ, Rosen D. Pathological gambling and treatment outcomes for adults age 50 or older in methadone maintenance treatment. J Gerontol SocWork. 2015;58(3):306–14.Google Scholar
  38. 38.
    Algren MH, Ekholm O, Davidsen M, Larsen CV, Juel K. Health behaviour and body mass index among problem gamblers: results from a nationwide survey. J Gambl Stud. 2015;31(2):547–56.CrossRefPubMedGoogle Scholar
  39. 39.
    Steenbergh TA, Meyers AW, May RK, Whelan JP. Development and validation of the Gamblers’ Beliefs Questionnaire. Psychol Addict Behav. 2002;16(2):143.CrossRefPubMedGoogle Scholar
  40. 40.
    Joukhador J, Blaszczynski A, Maccallum F. Superstitious beliefs in gambling among problem and non-problem gamblers: preliminary data. J Gambl Stud. 2004;20(2):171–80.CrossRefPubMedGoogle Scholar
  41. 41.
    Myrseth H, Brunborg GS, Eidem M. Differences in cognitive distortions between pathological and non-pathological gamblers with preferences for chance or skill games. J Gambl Stud. 2010;26(4):561–9.CrossRefPubMedGoogle Scholar
  42. 42.
    MacKillop J, Anderson EJ, Castelda BA, Mattson RE, Donovick PJ. Convergent validity of measures of cognitive distortions, impulsivity, and time perspective with pathological gambling. Psychol Addict Behav. 2006;20(1):75–9.CrossRefPubMedGoogle Scholar
  43. 43.
    Barrault S, Varescon I. Cognitive distortions, anxiety, and depression among regular and pathological gambling online poker players. Cyberpsychol Behav Soc Netw. 2013;16(3):183–8.CrossRefPubMedGoogle Scholar
  44. 44.
    Broussard J, Wulfert E. Can an accelerated gambling simulation reduce persistence on a gambling task?. Int J Ment Health Addict. 2015:1–11. doi:10.1007/s11469–015–9620-8Google Scholar
  45. 45.
    Ejova A, Delfabbro PH, Navarro DJ. Erroneous gambling-related beliefs as illusions of primary and secondary control: a confirmatory factor analysis. J Gambl Stud. 2015;31(1):133–60.CrossRefPubMedGoogle Scholar
  46. 46.
    MacKay TL, Bard N, Bowling M, Hodgins DC. Do pokers players know how good they are? Accuracy of poker skill estimation in online and offline players. Comput Human Behav. 2014;31:419–24.CrossRefGoogle Scholar
  47. 47.
    Tanner J, Mazmanian D. Gambling attitudes and beliefs associated with problem gambling: the cohort effect of Baby Boomers. Int Gambl Stud. 2016;16(1):98–115.CrossRefGoogle Scholar
  48. 48.
    Situ J, Mo Z. Risk propensity, gambling cognition and gambling behavior: the role of family and peer influences. J Educ Develop Psychol. 2016;6(1):77–95.CrossRefGoogle Scholar
  49. 49.
    Marchetti D et al. Psychometric evaluation of the Italian translation of the Gamblers’ Beliefs Questionnaire. Int Gambl Stud. 2016;16(1):17–30.CrossRefGoogle Scholar
  50. 50.
    Winfree WR, Meyers AW, Whelan JP. Validation of a Spanish translation of the Gamblers’ Beliefs Questionnaire. Psychol Addict Behav. 2013;27(1):274–8.CrossRefPubMedGoogle Scholar
  51. 51.
    Raylu N, Oei TP. The Gambling Related Cognitions Scale (GRCS): development, confirmatory factor validation and psychometric properties. Br J Addict. 2004;99(6):757–69.CrossRefGoogle Scholar
  52. 52.
    Arcan K, Karanci AN. Adaptation study of the Turkish version of the Gambling-Related Cognitions Scale (GRCS-T). J Gambl Stud. 2015;31(1):211–24.CrossRefPubMedGoogle Scholar
  53. 53.
    Grall-Bronnec M et al. A French adaptation of the Gambling-Related Cognitions Scale (GRCS): a useful tool for assessment of irrational thoughts among gamblers. Journal of Gambling Issues. 2012;27. doi: 10.4309/jgi.2012.27.9.
  54. 54.
    Yang Y, Wu D, Wen Y, Lu X, Li M. Psychometric properties of the Chinese version of the Gambling Related Cognitions Scale in Chinese mainland sample. Addict Behav. 2014;39(1):341–4.CrossRefPubMedGoogle Scholar
  55. 55.
    Yokomitsu K, Takahashi T, Kanazawa J, Sakano Y. Development and validation of the Japanese version of the Gambling Related Cognitions Scale (GRCS-J). Asian J Gambl Issues and Public Health. 2015;5(1).doi: 10.1186/s40405–015–0006-4Google Scholar
  56. 56.••
    Taylor RN, Parker JD, Keefer KV, Kloosterman PH, Summerfeldt LJ. Are gambling related cognitions in adolescence multidimensional?: factor structure of the gambling related cognitions scale. J Gambl Stud. 2014;30(2):453–65. Gambling cognitions were powerful predictors of disordered gambling among adolescents, using the Gambling Related Cognitions Scale (GRCS); however, strong associations among the subscales call into question the multidimensionality of the GRCS in this population. CrossRefPubMedGoogle Scholar
  57. 57.
    Taylor RN, Parker JD, Keefer KV, Kloosterman PH, Summerfeldt LJ. Gambling related cognitive distortions in adolescence: relationships with gambling problems in typically developing and special needs students. J Gambl Stud. 2015;31(4):1417–29.CrossRefPubMedGoogle Scholar
  58. 58.
    Stewart SH, Zack M. Development and psychometric evaluation of a three-dimensional Gambling Motives Questionnaire. Br J Addict. 2008;103(7):1110–7.CrossRefGoogle Scholar
  59. 59.
    Parhami I, Siani A, Campos MD, Rosenthal RJ, Fong TW. Gambling in the Iranian-American community and an assessment of motives: a case study. Int J Ment Health Addict. 2012;10(5):710–21.CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Hodgins DC, Racicot S. The link between drinking and gambling among undergraduate university students. Psychol Addict Behav. 2013;27(3):885–92.CrossRefPubMedGoogle Scholar
  61. 61.
    Quinlan CK, Goldstein AL, Stewart SH. An investigation of the link between gambling motives and social context of gambling in young adults. Int Gambl Stud. 2014;14(1):115–31.CrossRefGoogle Scholar
  62. 62.
    Sztainert T, Wohl MJ, McManus JF, Stead JD. On being attracted to the possibility of a win: reward sensitivity (via gambling motives) undermines treatment seeking among pathological gamblers. J Gambl Stud. 2014;30(4):901–11.CrossRefPubMedGoogle Scholar
  63. 63.
    Dechant K, Ellery M. The effect of including a monetary motive item on the gambling motives questionnaire in a sample of moderate gamblers. J Gambl Stud. 2011;27(2):331–44.CrossRefPubMedGoogle Scholar
  64. 64.
    Dechant K. Show me the money: incorporating financial motives into the Gambling Motives Questionnaire. J Gambl Stud. 2014;30(4):949–65.CrossRefPubMedGoogle Scholar
  65. 65.
    Schellenberg BJ, McGrath DS, Dechant K. The Gambling Motives Questionnaire financial: factor structure, measurement invariance, and relationships with gambling behaviour. Int Gambl Stud. 2016;16(1):1–6.CrossRefGoogle Scholar
  66. 66.
    Pilatti A, Benjamín F. Evaluation of the psychometric properties of the Gambling Motives Questionnaire in Argentinian young people and adults. Adicciones. 2015;27(1):17–25.CrossRefPubMedGoogle Scholar
  67. 67.
    Rousseau FL, Vallerand RJ, Ratelle CF, Mageau GA, Provencher PJ. Passion and gambling: on the validation of the Gambling Passion Scale (GPS). J Gambl Stud. 2002;18(1):45–66.CrossRefPubMedGoogle Scholar
  68. 68.
    Lee CK, Back KJ, Hodgins DC, Lee TK. Examining antecedents and consequences of gambling passion: the case of gambling on horse races. Psychiatry Investig. 2013;10(4):365–72.CrossRefPubMedPubMedCentralGoogle Scholar
  69. 69.
    Lee J, Chen CC, Song HJ, Lee CK. The role of responsible gambling strategy and gambling passion in the online gamblers’ decision-making process: revising the theory of planned behavior. J Gambl Stud. 2014;30(2):403–22.CrossRefPubMedGoogle Scholar
  70. 70.
    Lee CK, Chung N, Bernhard BJ. Examining the structural relationships among gambling motivation, passion, and consequences of internet sports betting. J Gambl Stud. 2014;30(4):845–58.CrossRefPubMedGoogle Scholar
  71. 71.
    Raylu N, Oei TP. The gambling urge scale: development, confirmatory factor validation, and psychometric properties. Psychol Addict Behav. 2004;18(2):100–5.CrossRefPubMedGoogle Scholar
  72. 72.••
    Smith DP, Pols RG, Battersby MW, Harvey PW. The Gambling Urge Scale: reliability and validity in a clinical population. Addict Res Theory. 2013;21(2):113–22. Findings indicate the Gambling Urge Scale (GUS) is a valid and reliable instrument for problem gambling screening and may also predict relapse in problem gambling.CrossRefGoogle Scholar
  73. 73.
    Wong SS, Tsang SK. Validation of the Chinese version of the gamblers’ belief questionnaire (GBQ-C). J Gambl Stud. 2012;28(4):561–72.CrossRefPubMedGoogle Scholar
  74. 74.
    Oei TP, Gordon LM. Psychosocial factors related to gambling abstinence and relapse in members of gamblers anonymous. J Gambl Stud. 2008;24(1):91–105.CrossRefPubMedGoogle Scholar
  75. 75.
    Balodis IM, Lacadie CM, Potenza MN. A preliminary study of the neural correlates of the intensities of self-reported gambling urges and emotions in men with pathological gambling. J Gambl Stud. 2012;28(3):493–513.CrossRefPubMedPubMedCentralGoogle Scholar
  76. 76.
    Callan MJ, Ellard JH, Shead NW, Hodgins DC. Gambling as a search for justice: examining the role of personal relative deprivation in gambling urges and gambling behavior. Personal Soc Psychol Bull. 2008;34(11):1514–29.CrossRefGoogle Scholar
  77. 77.
    Ashrafioun L, McCarthy A, Rosenberg H. Assessing the impact of cue exposure on craving to gamble in university students. J Gambl Stud. 2012;28(3):363–75.CrossRefPubMedGoogle Scholar
  78. 78.
    Young MM, Wohl MJ. The Gambling Craving Scale: psychometric validation and behavioral outcomes. Psychol Addict Behav. 2009;23(3):512–22.CrossRefPubMedGoogle Scholar
  79. 79.•
    Stewart MJ, Wohl MJ. Pop-up messages, dissociation, and craving: how monetary limit reminders facilitate adherence in a session of slot machine gambling. Psychol Addict Behav. 2013;27(1):268–74. Pop-up messages during slot machine play are an effective money limiting strategy and do not appear to amplify craving.CrossRefPubMedGoogle Scholar
  80. 80.
    Caselli G, Spada MM. Desire thinking: what is it and what drives it? Addict Behav. 2015;44:71–9.CrossRefPubMedGoogle Scholar
  81. 81.
    Brevers D et al. Time course of attentional bias for gambling information in problem gambling. Psychol Addict Behav. 2011;25(4):675–82.CrossRefPubMedPubMedCentralGoogle Scholar
  82. 82.
    May RK, Whelan JP, Steenbergh TA, Meyers AW. The gambling self-efficacy questionnaire: an initial psychometric evaluation. J Gambl Stud. 2003;19(4):339–57.CrossRefPubMedGoogle Scholar
  83. 83.
    Luca M, Giannini M, Gori A, Whelan JP, Meyers AW. Gambling Self-Efficacy Questionnaire (GSEQ): psychometric properties of the Italian version. Counseling: Giornale Italiano Di Ricerca E Applicazioni. 2012;5:89–100.Google Scholar
  84. 84.
    Winfree WR, Meyers AW, Whelan JP. Validation of a Spanish adaptation of the Gambling Self-Efficacy Questionnaire. Int Gambl Stud. 2013;13(2):271–80.CrossRefGoogle Scholar
  85. 85.
    Weinstock J, Massura CE, Petry NM. Professional and pathological gamblers: similarities and differences. J Gambl Stud. 2013;29(2):205–16.CrossRefPubMedGoogle Scholar
  86. 86.
    Winfree WR, Ginley MK, Whelan JP, Meyers AW. Psychometric evaluation of the Gambling Self-Efficacy Questionnaire with treatment-seeking pathological gamblers. Psychol Addict Behav. 2014;28(4):1305–10.CrossRefPubMedGoogle Scholar
  87. 87.
    Hodgins D, Peden N, Makarchuk K. Self-efficacy in pathological gambling treatment outcome: development of a gambling abstinence self-efficacy scale (GASS). Int Gambl Stud. 2004;4(2):99–108.CrossRefGoogle Scholar
  88. 88.
    Casey LM, Oei TP, Melville KM, Bourke E, Newcombe PA. Measuring self-efficacy in gambling: the gambling refusal self-efficacy questionnaire. J Gambl Stud. 2008;24(2):229–46.CrossRefPubMedGoogle Scholar
  89. 89.
    Holub A, Hodgins DC, Peden NE. Development of the temptations for gambling questionnaire: a measure of temptation in recently quit gamblers. Addict Res Theory. 2005;13(2):179–91.CrossRefGoogle Scholar
  90. 90.
    Pallanti S, DeCaria CM, Grant JE, Urpe M, Hollander E. Reliability and validity of the pathological gambling adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS). J Gambl Stud. 2005;21(4):431–43.CrossRefPubMedGoogle Scholar
  91. 91.
    Petry NM. Validity of a gambling scale for the Addiction Severity Index. J Nerv Ment Dis. 2003;191(6):399–407.PubMedGoogle Scholar
  92. 92.
    Blaszczynski A, Nower L. A pathways model of problem and pathological gambling. Br J Addict. 2002;97(5):487–99.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Kyle Caler
    • 1
    • 2
  • Jose Ricardo Vargas Garcia
    • 2
  • Lia Nower
    • 2
  1. 1.Center for Gambling Studies, School of Social WorkRutgers UniversityNew BrunswickUSA
  2. 2.Center for Gambling Studies, School of Social WorkRutgers UniversityNew BrunswickUSA

Personalised recommendations