A Resource Model of Change: Client Factors that Influence Problem Gambling Treatment Outcomes
- 384 Downloads
This study examined a resource-based model of change whereby poor problem gambling (PG) treatment outcomes and relapse are viewed as resulting from client coping resources being diminished or overwhelmed. Specifically, client factors that work like resources to facilitate treatment (i.e., social support, self-efficacy, motivation, readiness for change, and emotion-focused coping) or use up resources and hinder treatment (i.e., co-morbid depression and life stress) were examined. The 50 participants were followed for 4 months after entering treatment for PG and were assessed at baseline, 1 month into treatment, 2 months into treatment, and during a follow-up 4 months after treatment began. Of the 50 participants, 20 dropped-out of treatment and 24 completed the follow-up measure. The results suggest that self-efficacy and depression, measured at baseline, are good predictors of 1- and 2-month outcomes, whereas depression and life stress, measured after 2 months of treatment, are good predictors of 4-month outcomes. In the strongest of these models, baseline scores of client self-efficacy and depressed affect explained as much as 48.7 % of the variance in gambling behaviors 2 months later.
KeywordsProblem gambling Self-efficacy Change process Relapse Depression Life stress
The authors would like to acknowledge the financial support of the Ontario Problem Gambling Research Centre and the support of the Problem Gambling Research Group at the University of Windsor.
- Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck Depression Inventory—II. San Antonio, TX: Psychological Corporation.Google Scholar
- Brady, K. T., & Sonne, S. C. (1999). The role of stress in alcohol use, alcoholism treatment and relapse. Alcohol Research & Health, 23, 263–271.Google Scholar
- Brown, S. A., Vik, P. W., Patterson, T. L., Grant, I., & Schuckit, M. A. (1995). Stress, vulnerability, and adult alcohol relapse. Journal of Alcohol Studies, 56, 538–545. Retrieved from http://search.proquest.com/docview/618933877?accountid=14789.
- Hofmann, W., Rauch, W., & Gawronski, B. (2007). And deplete us not into temptation: Automatic attitudes, dietary restraint, and self-regulatory resources as determinants of eating behaviour. Journal of Experimental Social Psychology, 43, 497–504. doi: 10.1016/j.jesp.2006.05.004.CrossRefGoogle Scholar
- Kodl, M. M., Fu, S. S., Willenbring, M. L., Gravely, A., Nelson, D. B., & Joseph, A. M. (2008). The impact of depressive symptoms on alcohol and cigarette consumption following treatment for alcohol and nicotine dependence. Alcoholism, Clinical and Experimental Research, 32, 92–99. doi: 10.1111/j.1530-0277.2007.00556.x.CrossRefPubMedGoogle Scholar
- Majer, J. M., Jason, L. A., Ferrari, J. R., Olson, B. D., & North, C. S. (2003). Is self-mastery always a helpful resource? Coping with paradoxical findings in relation to optimism and abstinence self-efficacy. The American Journal of Drug and Alcohol Abuse, 29, 385–399. doi: 10.1081/ADA-120020520.CrossRefPubMedGoogle Scholar
- McBride, C. M., Curry, S. J., Stephens, R. S., Wells, E. A., Roffman, R. A., & Hawkins, J. D. (1994). Intrinsic and extrinsic motivation for change in cigarette smokers, marijuana smokers, and cocaine users. Psychology of Addictive Behaviours, 8(4), 243–250. doi: 10.1037/0893-164X.8.4.243.CrossRefGoogle Scholar
- McKay, J. R., Foltz, C., Stephens, R. C., Leahy, P. J., Crowley, E. M., & Kissin, W. (2005). Predictors of alcohol and crack cocaine use outcomes over a 3-year follow-up in treatment seekers. Journal of Substance Abuse Treatment, 28(S1), S73–S82. doi: 10.1016/j.jsat.2004.10.010.CrossRefPubMedGoogle Scholar
- Prochaska, J. O., & DiClemente, C. C. (1992). Stages of change in the modification of problem behaviours. Progress in Behaviour Modification, 28, 183–218.Google Scholar
- Project MATCH Research Group. (1997). Matching alcoholism treatments to client heterogeneity: Project MATCH posttreatment drinking outcomes. Journal of Studies on Alcohol, 58, 7–29. Retrieved from http://search.proquest.com/docview/619053086?accountid=14789.
- Shaffer, H. J., LaBrie, R. A., & LaPlante, D. (2004). Laying the foundation for quantifying regional exposure to social phenomena: Considering the case of legalized gambling as a public health toxin. Psychology of Addictive Behaviors, 18, 40–48. doi: 10.1037/0893-164X.18.1.40.CrossRefPubMedGoogle Scholar
- Smith, D., Harvey, P., Battersby, M., Pols, R., Oakes, J., & Baigent, M. (2010). Treatment outcomes and predictors of drop out for problem gamblers in South Australia: A cohort study. Australian and New Zealand Journal of Psychiatry, 44, 911–920. doi: 10.3109/00048674.2010.493502.CrossRefPubMedGoogle Scholar
- Tabachnick, B. G., & Fidell, L. S. (2006). Using multivariate statistics (5th ed.). Boston, MA: Allyn and Bacon.Google Scholar
- Tate, S. R., Wu, J., McQuaid, J. R., Cummins, K., Shriver, C., Krenek, M., et al. (2008). Comorbidity of substance dependence and depression: Role of life stress and self-efficacy in sustaining abstinence. Psychology of Addictive Behaviors, 22, 47–57. doi: 10.1037/0893-164X.22.1.47.CrossRefPubMedGoogle Scholar
- Walker, M., Schellink, T., & Anjoul, F. (2008). Explaining why people gamble. In M. Zangeneh, A. Blaszczynski, & N. Turner (Eds.), In the pursuit of winning (pp. 179–197). New York, NY: Springer.Google Scholar
- Wampold, B. E. (2001). The great psychotherapy debate: Model, methods, and findings. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
- Wynne, J. (2003). Introducing the Canadian problem gambling index. Edmonton, Canada: Wynne Resources.Google Scholar