Does Money Control Enhance the Effectiveness of CBT for Gambling Disorder?
Several therapy modalities have been developed for gambling disorder (GD), and the cognitive behavioral therapy (CBT) is one of the most promising approaches. The objective of this study was to explore the impact of patients’ adherence to guidelines concerning money control on the effectiveness and outcomes of a CBT program. Sample included n = 998 gambling disorder (GD) patients aged between 18 and 80 years old, who were consecutively attended in a Spanish reference-university-based hospital specialized in gambling treatment. The CBT program consisted of 16 weekly group sessions (each lasting about 90 min) aimed to achieve definitive abstinence from all types of gambling. Money control was integrated during the complete treatment. Different assessments were made: at baseline, during the CBT program, and at the end of the intervention. The risk of dropout during therapy was lower in patients who reported money control (19.1% versus 76.4%, p = 0.001), and differences were also found in the Kaplan-Meier cumulative survival functions of dropout (χ2 = 118.9, p < 0.001). No differences were found for the risk of relapse (defined in this study as the occurrence of gambling episodes during the intervention) (26.4% versus 28.0%, p = 0.775) or in the cumulative survival function of relapse (χ2 = 0.16, p = 0.689). At the end of the intervention, patients with money control had lower levels of gambling severity and comorbid psychopathology. The benefits of money control as a stimulus control during the CBT highlight the need to design intervention programs with reliable adherence strategies addressed to achieve complete abstinence from the gambling activities. Personalized interventions for GD should identify patients with higher needs of stimulus control training.
KeywordsCognitive behavioral therapy Dropout Gambling disorder Money control Outcome
We thank the CERCA Programme/Generalitat de Catalunya for institutional support.
This manuscript and research were supported by grants from the Ministerio de Economía y Competitividad (PSI2015–68701-R), Instituto de Salud Carlos III (ISCIII) (FIS PI14/00290 and PI17/01167) and cofunded by FEDER funds /European Regional Development Fund (ERDF), a way to build Europe. CIBERobn and CIBERSAM are both initiatives of ISCIII. This research was partially funded by the Delegación del Gobierno para el Plan Nacional sobre Drogas (2017I067) and received the support of the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia. TMM, CVA and MLM are supported by a predoctoral Grant of the Ministerio de Educación, Cultura y Deporte (FPU16/02087; FPU16/01453; FPU15/02911). HLG is supported by the Beatriu de Pinos program of the Secretariat for Universities and Research of the Department of Business and Knowledge of the Government of Catalonia (grant number 2017 BP00035).
Compliance with Ethical Standards
Conflict of Interest
All authors declare that they have no conflict of interest.
The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
All procedures followed were in accordance with the ethical standards of the Ethics Committee of the Bellvitge University Hospital (approval reference of the project: PR338/17), and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.
- American Psychiatric Association. (2010). Diagnostic and statistical manual of mental disorders (Fourth Edition-Rev) (4th Rev). Washington, DC: American Psychiatric Association.Google Scholar
- Buth, S., Wurst, F. M., Thon, N., Lahusen, H., & Kalke, J. (2017). Comparative analysis of potential risk factors for at-risk gambling, problem gambling and gambling disorder among current gamblers-results of the Austrian representative survey 2015. Frontiers in Psychology, 8, 2188. https://doi.org/10.3389/fpsyg.2017.02188.CrossRefPubMedPubMedCentralGoogle Scholar
- Caillon, J., Grall-Bronnec, M., Perrot, B., Leboucher, J., Donnio, Y., Romo, L., & Challet-Bouju, G. (2019). Effectiveness of at-risk gamblers’ temporary self-exclusion from internet gambling sites. Journal of Gambling Studies, 35(2), 601–615. https://doi.org/10.1007/s10899-018-9782-y.CrossRefPubMedGoogle Scholar
- Cloninger, C. R., Przybeck, T. R., Syrakic, D. M., & Wetzel, R. D. (1994). The temperament and character inventory (TCI). A guide to its development and use. Washington University: Center for Psychobiology of Personality.Google Scholar
- Dar, R., Stronguin, F., Marouani, R., Krupsky, M., & Frenk, H. (2005). Craving to smoke in orthodox Jewish smokers who abstain on the Sabbath: a comparison to a baseline and a forced abstinence workday. Psychopharmacology, 183(3), 294–299. https://doi.org/10.1007/s00213-005-0192-3.CrossRefPubMedGoogle Scholar
- Dar, R., Rosen-Korakin, N., Shapira, O., Gottlieb, Y., & Frenk, H. (2010). The craving to smoke in flight attendants: relations with smoking deprivation, anticipation of smoking, and actual smoking. Journal of Abnormal Psychology, 119(1), 248–253. https://doi.org/10.1037/a0017778.CrossRefPubMedGoogle Scholar
- Derogatis, L. R. (1994). SCL-90-R: Symptom Checklist-90-R. administration, scoring and procedures manual—II for the revised version. Towson: Clinical Psychometric Research.Google Scholar
- Dupont, W. D. (2009). Statistical modeling for biomedical researchers: a simple introduction to the analysis of complex data, second edition. In Statistical modeling for biomedical researchers: a simple introduction to the analysis of complex data. https://doi.org/10.1017/CBO9780511575884.
- Echeburúa, E., Báez, C., Fernández, J., & Páez, D. (1994). Cuestionario de juego patológico de south oaks (SOGS): Validación española (south oaks gambling screen (SOGS): Spanish validation). Análisis de Modificación de Conducta, 20, 769–791.Google Scholar
- Gonzalez De Rivera, J. L., Derogatis, L. R., De las Cuevas, C., Gracia Marco, R., Rodríguez-Pulido, F., Henry-Benitez, M., & Monterrey, A. (1989). The Spanish version of the SCL-90-R. Normative data in the general population. Towson: Clinical Psychometric Research.Google Scholar
- Gutiérrez-Zotes, J. A., Bayón, C., Montserrat, C., Valero, J., Labad, A., Cloninger, C. R., & Fernández-Aranda, F. (2004). Temperament and character inventory revised (TCI-R). Standardization and normative data in a general population sample. Actas Españolas de Psiquiatría, 32(1), 8–15 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14963776.PubMedGoogle Scholar
- Hodgins, D., & Holub, A. (2007). Treatment of pathological gambling. In G. Smith, D. Hodgins, & R. Williams (Eds.), Research and measurement issues in gambling studies (pp. 372–399). Toronto: Elsevier.Google Scholar
- Hollingshead, A. B. (2011). Four factor index of social status. Yale Journal of Sociology, 8, 21–51.Google Scholar
- Jiménez-Murcia, S., Stinchfield, R., Alvarez-Moya, E., Jaurrieta, N., Bueno, B., Granero, R., Aymamí, M. N., Gómez-Peña, M., Martínez-Giménez, R., Fernández-Aranda, F., & Vallejo, J. (2009). Reliability, validity, and classification accuracy of a Spanish translation of a measure of DSM-IV diagnostic criteria for pathological gambling. Journal of Gambling Studies, 25(1), 93–104. https://doi.org/10.1007/s10899-008-9104-x.CrossRefPubMedGoogle Scholar
- Mostazir, M., Taylor, R. S., Henley, W., & Watkins, E. (2019). An overview of statistical methods for handling nonadherence to intervention protocol in randomized control trials: a methodological review. Journal of Clinical Epidemiology, 108, 121–131. https://doi.org/10.1016/j.jclinepi.2018.12.002.CrossRefPubMedGoogle Scholar
- Pallesen, S., Molde, H., Arnestad, H. M., Laberg, J. C., Skutle, A., Iversen, E., Støylen, I. J., Kvale, G., & Holsten, F. (2007). Outcome of pharmacological treatments of pathological gambling: a review and meta-analysis. Journal of Clinical Psychopharmacology, 27(4), 357–364. https://doi.org/10.1097/jcp.013e3180dcc304d.CrossRefPubMedGoogle Scholar
- Peter, S. C., Brett, E. I., Suda, M. T., Leavens, E. L. S., Miller, M. B., Leffingwell, T. R., Whelan, J. P., & Meyers, A. W. (2019). A meta-analysis of brief personalized feedback interventions for problematic gambling. Journal of Gambling Studies, 35(2), 447–464. https://doi.org/10.1007/s10899-018-09818-9.CrossRefPubMedGoogle Scholar
- Robinson, T. E., & Berridge, K. C. (2008). Review. The incentive sensitization theory of addiction: some current issues. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 363(1507), 3137–3146. https://doi.org/10.1098/rstb.2008.0093.CrossRefPubMedPubMedCentralGoogle Scholar
- Rodda, S. N., Bagot, K. L., Cheetham, A., Hodgins, D. C., Hing, N., & Lubman, D. I. (2018). Types of change strategies for limiting or reducing gambling behaviors and their perceived helpfulness: a factor analysis. Psychology of Addictive Behaviors, 32(6), 679–688. https://doi.org/10.1037/adb0000393.CrossRefPubMedGoogle Scholar
- Rodda, S. N., Bagot, K. L., Manning, V., & Lubman, D. I. (2019). “It was terrible. I didn’t set a limit”: proximal and distal prevention strategies for reducing the risk of a bust in gambling venues. Journal of Gambling Studies, in press, 35, 1407–1421. https://doi.org/10.1007/s10899-019-09829-0.CrossRefPubMedGoogle Scholar
- Saunders, J. B., Hao, W., Long, J., King, D. L., Mann, K., Fauth-Bühler, M., Rumpf, H. J., Bowden-Jones, H., Rahimi-Movaghar, A., Chung, T., Chan, E., Bahar, N., Achab, S., Lee, H. K., Potenza, M., Petry, N., Spritzer, D., Ambekar, A., Derevensky, J., Griffiths, M. D., Pontes, H. M., Kuss, D., Higuchi, S., Mihara, S., Assangangkornchai, S., Sharma, M., Kashef, A. E., Ip, P., Farrell, M., Scafato, E., Carragher, N., & Poznyak, V. (2017). Gaming disorder: its delineation as an important condition for diagnosis, management, and prevention. Journal of Behavioral Addictions, 6(3), 271–279. https://doi.org/10.1556/2006.6.2017.039.CrossRefPubMedPubMedCentralGoogle Scholar
- Stata-Corp. (2019). Stata statistical software: Release 16. College Station: StataCorp LLC.Google Scholar
- Steyerberg, E. W., Harrell, F. E., Borsboom, G. J., Eijkemans, M. J., Vergouwe, Y., & Habbema, J. D. (2001). Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. Journal of Clinical Epidemiology, 54(8), 774–781. https://doi.org/10.1016/S0895-4356(01)00341-9.CrossRefPubMedGoogle Scholar
- Subramaniam, M., Wang, P., Soh, P., Vaingankar, J. A., Chong, S. A., Browning, C. J., & Thomas, S. A. (2015). Prevalence and determinants of gambling disorder among older adults: a systematic review. Addictive Behaviors, 41, 199–209. https://doi.org/10.1016/j.addbeh.2014.10.007.CrossRefPubMedGoogle Scholar
- Ten Have, T. R., Normand, S.-L. T., Marcus, S. M., Brown, C. H., Lavori, P., & Duan, N. (2008). Intent-to-treat vs. non-intent-to-treat analyses under treatment non-adherence in mental health randomized trials. Psychiatric Annals, 38(12), 772–783. https://doi.org/10.3928/00485713-20081201-10.CrossRefPubMedPubMedCentralGoogle Scholar
- van der Maas, M., Shi, J., Elton-Marshall, T., Hodgins, D. C., Sanchez, S., Lobo, D. S., Hagopian, S., & Turner, N. E. (2019). Internet-based interventions for problem gambling: scoping review. JMIR Mental Health, 6(1), e65. https://doi.org/10.2196/mental.9419.CrossRefPubMedPubMedCentralGoogle Scholar