Although age-related differences have been reported in gambling disorder, prior studies have not examined how age may influence recovery in gambling disorder. Recovery may be influenced by positive factors (e.g., spirituality and recovery capital) and negative factors (e.g., depression, anxiety, and stressful life events). The current study examined associations between these positive and negative factors and gambling disorder DSM-5 symptom improvement in younger and older adults. Younger (less than 55 years of age; n = 86) and older (55 years or older; n = 54) adults, with lifetime gambling disorder treated currently or within the past 5 years in five treatment centers in Israel were assessed using structured scales on past-year and lifetime DSM-5 gambling disorder, intrinsic spirituality, recovery capital, anxiety, depression and stressful life-events. Among younger adults, recovery capital and intrinsic spirituality were associated with gambling disorder symptom improvement. Among older adults, only recovery capital was associated with gambling disorder symptom improvement. Correlations between recovery capital and spirituality (z = 2.34, p = 0.02) and recovery capital and stressful life events (z = 2.29, p = 0.02) were stronger in younger than in older adults. Recovery capital is an important resource that should be considered across older and younger adults with gambling disorder. Spirituality and stressful life events may operate differently across age groups in gambling disorder. Future studies should investigate whether the findings may extend to other groups and the extent to which promoting recovery capital should be integrated into treatments for gambling disorder.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Abbott, M., Romild, U., & Volberg, R. (2018). The prevalence, incidence, and gender and age-specific incidence of problem gambling: Results of the Swedish longitudinal gambling study (Swelogs). Addiction, 113(4), 699–707.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Publishing.
Best, D., Honor, S., Karpusheff, J., Loudon, L., Hall, R., Groshkova, T., et al. (2012). Well-being and recovery functioning among substance users engaged in posttreatment recovery support groups. Alcoholism Treatment Quarterly, 30(4), 397–406.
Burns, J., & Marks, D. (2013). Can recovery capital predict addiction problem severity? Alcoholism Treatment Quarterly, 31(3), 303–320.
Cloud, W., & Granfield, R. (2008). Conceptualizing recovery capital: Expansion of a theoretical construct. Substance Use and Misuse, 43(12–13), 1971–1986.
Clyde, M. A. (2018). BAS: Bayesian variable selection and model averaging using Bayesian adaptive sampling. R Package Version 1.4.9. CRAN Comprehensive R Archive Network [Computer software]. https://doi.org/10.5281/zenodo.1212636.
Clyde, M. A., Ghosh, J., & Littman, M. L. (2011). Bayesian adaptive sampling for variable selection and model averaging. Journal of Computational and Graphical Statistics, 20(1), 80–101. https://doi.org/10.1198/jcgs.2010.09049.
Dawson, D. A., Grant, B. F., & Ruan, W. J. (2005). The association between stress and drinking: Modifying effects of gender and vulnerability. Alcohol and Alcoholism, 40(5), 453–460.
Fragoso, T. M., Bertoli, W., & Louzada, F. (2018). Bayesian model averaging: A systematic review and conceptual classification. International Statistical Review, 86(1), 1–28. https://doi.org/10.1111/insr.12243.
Gavriel-Fried, B. (2018). The crucial role of recovery capital in individuals with a gambling disorder. Journal of Behavioral Addictions, 7(3), 792–799.
Gavriel-Fried, B., Moretta, T., & Potenza, M. N. (2019a). Associations between recovery capital, spirituality, and DSM–5 symptom improvement in gambling disorder. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0000492.
Gavriel-Fried, B., Moretta, T., & Potenza, M. N. (2019b). Modeling intrinsic spirituality in gambling disorder. Addiction Research & Theory. https://doi.org/10.1080/16066359.2019.1622002.
Gonzalez-Ibanez, A., Mora, M., Gutierrez-Maldonado, J., Ariza, A., & Lourido-Ferreira, M. (2005). Pathological gambling and age: Differences in personality, psychopathology, and response to treatment variables. Addictive Behaviors, 30(2), 383–388.
Granero, R., Penelo, E., Stinchfield, R., Fernandez-Aranda, F., Savvidou, L. G., Fröberg, F., et al. (2014). Is pathological gambling moderated by age? Journal of Gambling Studies, 30(2), 475–492.
Hennessy, E. A. (2017). Recovery capital: A systematic review of the literature. Addiction Research & Theory, 25(5), 349–360.
Hodge, D. R. (2003). The intrinsic spirituality scale: A new six-item instrument for assessing the salience of spirituality as a motivational construct. Journal of Social Service Research, 30(1), 41–61.
Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401.
Jorm, A. F. (2000). Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychological Medicine, 30(1), 11–22.
Kausch, O. (2004). Pathological gambling among elderly veterans. Journal of Geriatric Psychiatry and Neurology, 17(1), 13–19.
Kelly, J. F., & Hoeppner, B. (2015). A biaxial formulation of the recovery construct. Addiction Research & Theory, 23(1), 5–9.
Krentzman, A. R. (2013). Review of the application of positive psychology to substance use, addiction, and recovery research. Psychology of Addictive Behaviors, 27(1), 151.
Kroenke, K., & Spitzer, R. L. (2002). The PHQ-9: A new depression diagnostic and severity measure. Psychiatric Annals, 32(9), 509–515.
Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Cambridge: Academic Press.
Moberg, D. O. (2005). Research in spirituality, religion, and aging. Journal of Gerontological Social Work, 45(1–2), 11–40.
Morey, R. D., & Rouder, J. N. (2018). BayesFactor: Computation of Bayes factors for common designs [Computer software]. Retrieved from https://CRAN.R-project.org/package=BayesFactor.
Potenza, M. N., Steinberg, M. A., Wu, R., Rounsaville, B. J., & O’Malley, S. S. (2006). Characteristics of older adult problem gamblers calling a gambling helpline. Journal of Gambling Studies, 22(2), 241–254.
Ramseyer, G. C. (1979). Testing the difference between dependent correlations using the Fisher Z. The Journal of Experimental Education, 47(4), 307–310.
Schönbrodt, F. D., Wagenmakers, E.-J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological Methods, 22(2), 322.
Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097.
Sterling, R., Slusher, C., & Weinstein, S. (2008). Measuring recovery capital and determining its relationship to outcome in an alcohol dependent sample. The American Journal of Drug and Alcohol Abuse, 34(5), 603–610.
Streiner, D. L., Cairney, J., & Veldhuizen, S. (2006). The epidemiology of psychological problems in the elderly. The Canadian Journal of Psychiatry, 51(3), 185–191.
Team, R. C. (2018). R: A language and environment for statistical computing: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/.
Vilsaint, C. L., Kelly, J. F., Bergman, B. G., Groshkova, T., Best, D., & White, W. (2017). Development and validation of a brief assessment of recovery capital (BARC-10) for alcohol and drug use disorder. Drug and Alcohol Dependence, 177, 71–76.
Wagenmakers, E. J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., et al. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3.
Welte, J. W., Barnes, G. M., Tidwell, M.-C. O., & Hoffman, J. H. (2011). Gambling and problem gambling across the lifespan. Journal of Gambling Studies, 27(1), 49–61.
West, R. (2016). Using Bayesian analysis for hypothesis testing in addiction science. Addiction, 111(1), 3–4. https://doi.org/10.1111/add.13053.
This study was supported by a seed Grant awarded to Belle Gavriel-Fried by the National Center for Responsible Gaming (NCRG) in 2017. Marc N. Potenza’s involvement was supported by the National Center for Responsible Gaming, the Connecticut Council on Problem Gambling, and the Connecticut Department of Mental Health and Addiction Services.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Belle Gavriel-Fried: Visiting scholar at Yale University (2018–2019).
About this article
Cite this article
Gavriel-Fried, B., Moretta, T. & Potenza, M.N. Recovery Capital and Symptom Improvement in Gambling Disorder: Correlations with Spirituality and Stressful Life Events in Younger but Not Older Adults. J Gambl Stud 36, 1379–1390 (2020). https://doi.org/10.1007/s10899-019-09905-5
- Age differences
- Recovery capital
- Gambling disorder
- Symptom improvement