Advertisement

Journal of Gambling Studies

, Volume 33, Issue 1, pp 167–186 | Cite as

Principles for Developing Benchmark Criteria for Staff Training in Responsible Gambling

  • Stefan Oehler
  • Raphaela Banzer
  • Agnes Gruenerbl
  • Doris Malischnig
  • Mark D. Griffiths
  • Christian Haring
Original Paper
  • 296 Downloads

Abstract

One approach to minimizing the negative consequences of excessive gambling is staff training to reduce the rate of the development of new cases of harm or disorder within their customers. The primary goal of the present study was to assess suitable benchmark criteria for the training of gambling employees at casinos and lottery retailers. The study utilised the Delphi Method, a survey with one qualitative and two quantitative phases. A total of 21 invited international experts in the responsible gambling field participated in all three phases. A total of 75 performance indicators were outlined and assigned to six categories: (1) criteria of content, (2) modelling, (3) qualification of trainer, (4) framework conditions, (5) sustainability and (6) statistical indicators. Nine of the 75 indicators were rated as very important by 90 % or more of the experts. Unanimous support for importance was given to indicators such as (1) comprehensibility and (2) concrete action-guidance for handling with problem gamblers, Additionally, the study examined the implementation of benchmarking, when it should be conducted, and who should be responsible. Results indicated that benchmarking should be conducted every 1–2 years regularly and that one institution should be clearly defined and primarily responsible for benchmarking. The results of the present study provide the basis for developing a benchmarking for staff training in responsible gambling.

Keywords

Responsible gambling Staff training Performance indicators Benchmarking Delphi method 

Notes

Acknowledgments

This research was funded by the Austrian Lotteries. Funding bodies had no influence over the design and conduct of the study, and analysis and interpretation of the data.

Funding

Austrian Lotteries.

Compliance with Ethical Standards

Conflict of interest

This research was funded by the Austrian Lotteries. Funding bodies had no influence over the design and conduct of the study, and analysis and interpretation of the data.

References

  1. Blaszczynski, A., Collins, P., Fong, D., Ladouceur, R., Nower, L., Shaffer, H. J., & Venisse, J.-L. (2011). Responsible gambling: General principles and minimal requirements. Journal of Gambling Studies, 27(4), 565–573.CrossRefPubMedGoogle Scholar
  2. Blaszczynski, A., Ladouceur, R., & Shaffer, H. J. (2004). A science-based framework for responsible gambling: The Reno model. Journal of Gambling Studies, 20(3), 301–317.CrossRefPubMedGoogle Scholar
  3. Bortz, J. (2005). Statistik für Human-und Sozialwissenschaftler: mit… 242 Tabellen. Berlin: Springer.Google Scholar
  4. Breen, H., Buultiens, J., & Hing, N. (2005). The responsible gambling code in Queensland, Australia: Implementation and venue assessment. UNLV Gaming Research and Review Journal, 9(1), 43–60.Google Scholar
  5. Camp, R. C. (1995). Business process benchmarking: Finding and implementing best practices (Vol. 177). Milwaukee, WI: ASQC Quality Press.Google Scholar
  6. Camp, R. C. (1998). Global cases in benchmarking: Best practices from organizations around the world. Milwaukee, WI: ASQ Quality Press.Google Scholar
  7. Codling, S. (1992). Best practice benchmarking: A management guide. London: Gower Publishing Ltd.Google Scholar
  8. Dufour, J., Ladouceur, R., & Giroux, I. (2010). Training program on responsible gambling among video lottery employees. International Gambling Studies, 10(1), 61–79.CrossRefGoogle Scholar
  9. Dusenbury, L., & Falco, M. (1995). Eleven components of effective drug abuse prevention curricula. [Research support, non-U.S. Gov’t]. Journal of School Health, 65(10), 420–425.CrossRefPubMedGoogle Scholar
  10. Giroux, I., Boutin, C., Ladouceur, R., Lachance, S., & Dufour, M. (2008). Awareness training program on responsible gambling for casino employees. International Journal of Mental Health and Addiction, 6(4), 594–601.CrossRefGoogle Scholar
  11. Gläser, J., & Laudel, G. (2010). Experteninterviews und qualitative Inhaltsanalyse. Wiesbaden: Springer.CrossRefGoogle Scholar
  12. Gray, H. M., Tom, M. A., LaPlante, D. A., & Shaffer, H. J. (2014). Using opinions and knowledge to identify natural groups of gambling employees. Journal of Gambling Studies,. doi: 10.1007/s10899-014-9490-1.Google Scholar
  13. Griffiths, M. D. (2000). Employers need to be aware of gambling in workplace and potential effects on job performance and company health. Report on Problem Gambling, 2, 23–29.Google Scholar
  14. Griffiths, M. D. (2012). Internet gambling, player protection, and social responsibility. London: Routledge.Google Scholar
  15. Griffiths, M. D., & Wood, R. T. A. (2009). Centralised gaming models and social responsibility. Casino and Gaming International, 5(2), 65–69.Google Scholar
  16. Häder, M. (2002). Delphi-Befragungen. Wiesbaden: Springer.CrossRefGoogle Scholar
  17. Hank, K., & Trenkel, H. (1994). Zukünftige Erscheinungsformen landwirtschaftlicher Betriebe - Eine Prognose mit Hilfe der Delphi Technik. Berichte über Landwirtschaft, 72, 123–145.Google Scholar
  18. Heidenreich, T., & Michalak, J. (2004). Achtsamkeit («Mindfulness») als Therapieprinzip in Verhaltenstherapie und Verhaltensmedizin. Verhaltenstherapie, 13(4), 264–274.CrossRefGoogle Scholar
  19. Kalke, J., Farnbacher, G., Verthein, U., & Haasen, C. (2006). Das Gefährdungs-und Abhängigkeitspotenzial von Lotterien-Erkenntnisstand in Deutschland. Suchtmedizin, 4, 183–188.Google Scholar
  20. Kalke, J., Verthein, U., Farnbacher, G., & Haasen, C. (2007). Aktive Spielsuchtprävention bei Lotterien und Sportwetten in Hamburg. Prävention und Gesundheitsförderung, 2(4), 249–253.CrossRefGoogle Scholar
  21. Kolb, A. Y., & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning and Education, 4(2), 193–212.CrossRefGoogle Scholar
  22. Ladouceur, R., Boutin, C., Doucet, C., Dumont, M., Provencher, M., Giroux, I., & Boucher, C. (2004). Awareness promotion about excessive gambling among video lottery retailers. Journal of Gambling Studies, 20(2), 181–185.CrossRefPubMedGoogle Scholar
  23. LaPlante, D. A., Gray, H. M., LaBrie, R. A., Kleschinsky, J. H., & Shaffer, H. J. (2012). Gaming industry employees’ responses to responsible gambling training: A public health imperative. Journal of Gambling Studies, 28(2), 171–191.CrossRefPubMedGoogle Scholar
  24. Lewis, C., Battistich, V., & Schaps, E. (1990). School-based primary prevention: What is an effective program? New Directions for Child and Adolescent Development, 50, 35–59.CrossRefGoogle Scholar
  25. McCormack, A., & Griffiths, M. D. (2013). A scoping study of the structural and situational characteristics of internet gambling. International Journal of Cyber Behavior, Psychology and Learning, 3(1), 29–49.CrossRefGoogle Scholar
  26. Meyer, G., Häfeli, J., Mörsen, C., & Fiebig, M. (2010). Die Einschätzung des Gefährdungspotentials von Glücksspielen. SUCHT-Zeitschrift für Wissenschaft und Praxis/Journal of Addiction Research and Practice, 56(6), 405–414.CrossRefGoogle Scholar
  27. Nation, M., Crusto, C., Wandersman, A., Kumpfer, K. L., Seybolt, D., Morrissey-Kane, E., & Davino, K. (2003). What works in prevention: Principles of effective prevention programs. American Psychologist, 58(6–7), 449–456.CrossRefPubMedGoogle Scholar
  28. Otieno, G. O., Hinako, T., Motohiro, A., Daisuke, K., & Keiko, N. (2008). Measuring effectiveness of electronic medical records systems: Towards building a composite index for benchmarking hospitals. International Journal of Medical Informatics, 77(10), 657–669.CrossRefPubMedGoogle Scholar
  29. Shaffer, H. J., Bilt, J. V., & Hall, M. N. (1999). Gambling, drinking, smoking and other health risk activities among casino employees. American Journal of Industrial Medicine, 36(3), 365–378.CrossRefPubMedGoogle Scholar
  30. Shaffer, H. J., & Hall, M. N. (2002). The natural history of gambling and drinking problems among casino employees. Journal of Social Psychology, 142(4), 405–424.CrossRefPubMedGoogle Scholar
  31. Smitheringale, B. (2001). The manitoba problem gambling customer assistance program: Summary report. Winnipeg: Addictions Foundation of Manitoba.Google Scholar
  32. Wahl, D. (2002). Mit Training vom trägen Wissen zum kompetenten Handeln? Zeitschrift für Pädagogik, 48(2), 227–241.Google Scholar
  33. Wood, R. T. A., Shorter, G. W., & Griffiths, M. D. (2014a). 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, 94–112.CrossRefGoogle Scholar
  34. Wood, R. T. A., Shorter, G. W., & Griffiths, M. D. (2014b). Selecting the right responsible gambling features, according to the specific portfolio of games. Responsible Gambling Review, 1(1), 51–63.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Stefan Oehler
    • 1
  • Raphaela Banzer
    • 1
  • Agnes Gruenerbl
    • 2
  • Doris Malischnig
    • 3
    • 5
  • Mark D. Griffiths
    • 4
  • Christian Haring
    • 1
    • 6
  1. 1.Department for Psychiatry and Psychotherapy BState Hospital Hall in TyrolHall in TirolAustria
  2. 2.Embedded IntelligenceDFKIKaiserslauternGermany
  3. 3.Department PreventionCasinos Austria-Austrian LotteriesViennaAustria
  4. 4.International Gaming Research Unit, Psychology DivisionNottingham Trent UniversityNottinghamUK
  5. 5.Institute of Psychology and Cognition ResearchUniversity of BremenBremenGermany
  6. 6.Addiction Help ServicesBINInnsbruckAustria

Personalised recommendations