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Psychosocial Predictors of Relapse in Cocaine-Dependent Patients in Treatment

Published online by Cambridge University Press:  10 January 2013

Emilio Sánchez-Hervás*
Affiliation:
Agencia Valenciana de Salud (Spain)
Francisco J. Santonja Gómez
Affiliation:
Universidad de Valencia (Spain)
Roberto Secades Villa
Affiliation:
Universidad de Oviedo (Spain)
Gloria García-Fernández
Affiliation:
Universidad de Oviedo (Spain)
Olaya García-Rodríguez
Affiliation:
Universidad de Oviedo (Spain)
Francisco Zacarés Romaguera
Affiliation:
Universidad de Oviedo (Spain)
*
Correspondence concerning this article should be addressed to Emilio Sánchez Hervás. Unidad de Conductas Adictivas. Centro de Salud, Avd. Rambleta s/n. 46470 - Catarroja. Valencia (Spain). Phone: +34-961223505. Fax: +34-961223504. E-mail: esh455k@gmail.com

Abstract

Relapses in cocaine abusers in treatment are an important problem. The majority of patients are incapable of sustaining abstinence over any length of time. To identify the factors associated to relapses risk in the cocaine use can be an optimal choice to improve the treatment strategies. The aim of this study was to analyze relapse-risk factors in cocaine-dependent patients on treatment. Participants were 102 patients who had begun outpatient treatment at a public health center in Spain. Some functional areas and cocaine use are evaluated for a period of six months. A structural equations model was used to identify possible predictive variables. The results show that social-family environment and economic-employment situation were associated with greater risk of relapse. Likewise, the social-family environment was related to severity of addiction. It is concluded that the incorporation of family intervention strategies and vocational/employment counseling may help to reduce relapse rates in cocaine addicts receiving treatment.

Las recaídas en el consumo siguen siendo un problema común en el tratamiento de las personas dependientes a la cocaína. La mayoría de los pacientes son incapaces de mantener la abstinencia de forma continuada, por lo que la identificación de factores que se relacionen con un mayor riesgo de recaída en el consumo permite mejorar las estrategias de tratamiento. El objetivo de este estudio fue analizar potenciales factores de riesgo de recaída durante el tratamiento en dependientes a la cocaína. Participaron 102 pacientes que iniciaban tratamiento en una unidad de tipo ambulatorio de la red sanitaria pública de España. Se evaluaron diversas áreas de funcionamiento y el uso de cocaína durante un período de seis meses. Para identificar las posibles variables con valor predictivo se utilizó una modelización matemática con ecuaciones estructurales. Los resultados de este trabajo subrayan que factores psicosociales como el entorno sociofamiliar y la situación económico-laboral tienen capacidad para predecir las recaídas en este tipo de pacientes. También que el entorno sociofamiliar influye en la severidad adictiva. Se concluye que la incorporación de estrategias de intervención familiar y de consejo vocacional puede ayudar a reducir las tasas de recaída en adictos a la cocaína en tratamiento.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2012

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References

Alterman, A. I., McKay, J. R., Mulvaney, F. D., Cnaan, A., Cacciola, J. S., Tourian, K. A., … Merikle, E. P. (2000). Baseline prediction of 7-month cocaine abstinence for cocaine dependence patients. Drug and Alcohol Dependence, 59, 215221. http://dx.doi.org/10.1016/S0376-8716(99)00124-6CrossRefGoogle ScholarPubMed
American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders text revised, DSM-IV-TR (4th Ed.). Washington, DC: American Psychiatric Association.Google Scholar
Anderson, K. G., Ramo, D. E., Schulte, M. T., Cummings, K., & Brown, S. A. (2008). Impact of relapse predictors on psychosocial functioning of SUD youth one year after treatment. Substance Abuse, 29, 97106. http://dx.doi.org/10.1080/08897070802093411Google Scholar
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561571. http://dx.doi.org/10.1001/archpsyc.1961.01710120031004Google Scholar
Bentler, P. (2005). EQS 6 Structural equations program manual. Encino, CA: Multivariate Software Inc.Google Scholar
Bohnert, A., German, D., Knowlton, A., & Latkin, C. (2010). Friendship networks of inner-city adults: A latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use. Drug and Alcohol Dependence, 107, 134140. http://dx.doi.org/10.1016/j.drugalcdep.2009.09.012CrossRefGoogle ScholarPubMed
Buchanan, A., & Latkin, C. (2008). Drug use in the social network of heroin and cocaine Users before and after drug cessation. Drug Alcohol Depend, 96, 286289. http://dx.doi.org/10.1016/j.drugalcdep.2008.03.008Google Scholar
Byrne, B. M. (2006). Structural Equations modeling with EQS. Mahwah, New Jersey, NJ: Lawrence Erlbaum Associates.Google Scholar
Derogatis, L. R., Lipman, R. S., & Covi, L. (1973). SCL-90: An outpatient psychiatric rating scale-preliminary report. Psychopharmacological Bulletin, 9, 1328.Google ScholarPubMed
Dobkin, P., De Civita, M., Paraherakis, A., & Gill, K. (2002). The role of social support in treatment retention and outcomes among outpatient adult substance abusers. Addiction, 97, 347356. http://dx.doi.org/10.1046/j.1360-0443.2002.00083.xCrossRefGoogle ScholarPubMed
Dolan, S., Martin, R., & Rohsenow, D. (2008). Self-efficacy for cocaine abstinence: Pretreatment correlates and relationship to outcomes. Addictive Behaviors, 33, 675688. http://dx.doi.org/10.1016/j.addbeh.2007.12.001CrossRefGoogle ScholarPubMed
Dutra, L., Stathopoulou, G., Basden, S. L., Leyro, T. M., Powers, M. B., & Otto, M. W. (2008). A meta-analytic review of psychosocial interventions for substance use disorders. American Journal of Psychiatry, 165, 179187. http://dx.doi.org/10.1176/appi.ajp.2007.06111851CrossRefGoogle ScholarPubMed
Fernández-Montalvo, J., & López-Goñi, J. (2010). Comparison of completers and dropouts in psychological treatment for cocaine addiction. Addiction Research & Theory, 18, 433441. http://dx.doi.org/10.3109/16066350903324826CrossRefGoogle Scholar
Grella, C., Hser, Y. I., & Hsieh, S. (2003). Predictors of drug treatment re-entry following relapse to cocaine use in DATOS. Journal of Substance Abuse Treatment, 25, 145154. http://dx.doi.org/10.1016/S0740-5472(03)00128-4CrossRefGoogle ScholarPubMed
Hair, J. E., Tatham, R. L., Anderson, R. E., & Black, W. C (2001). Multivariate data analysis. New York, NY: Prentice Hall.Google Scholar
Hawks, R., & Chiang, C. (1986). Urine testing for drugs of abuse. Research Monograph, n°73. Maryland, MD: National Institute for Drug Abuse (NIDA).Google Scholar
Heinz, A. J., Wu, J., Witkiewitz, K., Epstein, D. D., & Preston, K. L. (2009). Marriage and relationship closeness as predictors of cocaine and heroin use. Addictive Behaviors, 34, 258263. http://dx.doi.org/10.1016/j.addbeh.2008.10.020CrossRefGoogle ScholarPubMed
Hser, Y. I., Evans, E., Huang, D., & Anglin, M. D. (2004). Relationship between drug treatments services, retention, and outcomes. Psychiatric Services, 55, 767774. http://dx.doi.org/10.1176/appi.ps.55.7.767Google Scholar
Hser, Y. I., Joshi, V., Anglin, M. D., & Fletcher, B. (1999). Predicting post-treatment cocaine abstinence for first-time admissions and treatment repeaters. American Journal of Public Health, 89, 661671. http://dx.doi.org/10.2105/AJPH.89.5.666Google Scholar
Hser, Y. I., Stark, M. E., Paredes, A., Huang, D., Anglin, D., & Rawson, R. (2006). A 12-year follow-up of a treated cocaine-dependent sample. Journal of Substance Abuse Treatment, 30, 219226. http://dx.doi.org/10.1016/j.jsat.2005.12.007Google Scholar
Kokkevi, A., & Hartgers, C. (1995). European adaptation of a multidimensional assessment instrument for drug and alcohol dependence. European Addiction Research, 1, 208210. http://dx.doi.org/10.1159/000259089CrossRefGoogle Scholar
López, A., Becoña, E., Casete, L., Lage, T., García-Janeiro, J., Senra, A., … Cancelo, J. (2009). Variables significativas para explicar el consumo de cocaína a los dos años de demanda de tratamiento [Significant variables to explain cocaine use two years after treatment demand]. Behavioural Psychology/Psicología Conductual, 17, 203216.Google Scholar
Marlatt, A. (1996). Models of relapse and relapse prevention: A commentary. Experimental and Clinical Psychopharmacology, 4, 5560. http://dx.doi.org/10.1037//1064-1297.4.1.55CrossRefGoogle Scholar
Marlatt, A., & Gordon, R. (1985). Relapse Prevention: Maintenance strategies in the treatment of addictive behaviors. New York, NY: Guilford Press.Google Scholar
Marlatt, G. A., Parks, G. A., & Witkiewitz, K. (2002). Clinical guidelines for implementing Relapse Prevention Therapy: A guideline developed for the Behavioral Health Recovery Management Project. Seattle, WA: University of Washington, Addictive Behaviors Research Center.Google Scholar
McCamant, L., Zani, B., McFarland, B., & Gabriel, R. (2007). Prospective validation of substance abuse severity measures from administrative data. Drug and Alcohol Dependence, 86, 3745. http://dx.doi.org/10.1016/j.drugalcdep.2006.04.016Google Scholar
McKay, J., Merikle, E., Mulvaney, F., Weiss, R., & Koppenhaver, J. (2001). Factors accounting for cocaine use two years following initiation of continuing care. Addiction, 96, 213225. http://dx.doi.org/10.1046/j.1360-0443.2001.9622134.xCrossRefGoogle ScholarPubMed
McLellan, T., Kushner, H., Metzger, D., Peters, R., Smith, I., Grison, G., … Argelou, M. (1992). The 5th Edition of the addiction severity index. Journal of Substance Abuse Treatment, 9, 199213.CrossRefGoogle Scholar
McMahon, R. (2001). Personality, stress, and social support in cocaine relapse prediction. Journal of Substance Abuse Treatment, 21, 7787. http://dx.doi.org/10.1016/S0740-5472(01)00187-8Google Scholar
McMahon, R. (2008). Substance abuse problems, psychiatric symptoms, and post-treatment status in MCMI psychopathology subgroups of cocaine dependent. American Journal of Drug and Alcohol Abuse, 34, 195202. http://dx.doi.org/10.1080/00952990701877094CrossRefGoogle ScholarPubMed
Messina, N., Farabee, D., & Rawson, R. (2003). Treatment responsivity of cocaine-dependent patients with antisocial personality disorder to cognitive–behavioral and contingency management interventions. Journal of Consulting and Clinical Psychology, 71, 320329. http://dx.doi.org/10.1037/0022-006X.71.2.320Google Scholar
Miller, P., & Tonigan, J. (1996). Assessing drinkers' motivation for change. The Stages of Change Readiness Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behaviors, 10, 8189. http://dx.doi.org/10.1037//0893-164X.10.2.81Google Scholar
Poling, J., Kosten, T., & Sofuoglu, M. (2007). Treatment outcomes predictors for cocaine dependence. American Journal Drug Alcohol Abuse, 33, 191206. http://dx.doi.org/10.1080/00952990701199416Google Scholar
Polivy, J., & Herman, C. P. (2002). If at first you don't succeed: False hopes of self change. American Psychologist, 57, 677689. http://dx.doi.org/10.1037//0003-066X.57.9.677CrossRefGoogle ScholarPubMed
Project MATCH Research Group. (1997). Matching alcoholism treatments to client heterogeneity: Project MATCH posttreatment drinking outcomes. Journal of Studies on Alcohol, 58, 729.CrossRefGoogle Scholar
Ray, G. T., Weisner, C. M., & Mertens, J. R. (2005). Relationship between use of psychiatric services and five-year alcohol and drug treatment outcomes. Psychiatric Services, 56, 164171. http://dx.doi.org/10.1176/appi.ps.56.2.164CrossRefGoogle ScholarPubMed
Rodríguez, J., Fernandez, A., Valdés, M., Hernandez, E., Ramirez, S., & Roman, A. (2008). A comparison of the peers method and tradicional methodologies and risk behaviors in studies of the prevalence of drug comsumption in a population of female, chilean students. The Spanish Journal of Psychology, 11, 564572.Google Scholar
Sánchez Hervás, E., Secades, R., Santonja, F., Zacares, F., & Garcia, O. (2009). Addictive severity in cocaine addicts measured with the EuropASI: Differences between composite scores and severity ratings. The American Journal on Addictions, 18, 375378. http://dx.doi.org/10.1080/10550490903077952Google Scholar
Santonja, F., Sánchez-Hervás, E., Secades, R., Zacares, F., García-Rodríguez, O., & García-Rodriguez, G. (2010). Pretreatment characteristics as predictors of retention in cocaine-dependent outpatients. Addictive Disorder and Their Treatment, 9, 9398. http://dx.doi.org/10.1097/ADT.0b013e3181bff7ecGoogle Scholar
Seltzer, M. L. (1971). The Michigan Alcoholism Screening Test: The quest for a new diagnostic instrument. The American Journal of Psychiatry, 127, 16531658.Google Scholar
Simpson, D., Joe, G., & Broone, K. (2002). A national 5-year follow-up of treatment outcomes for cocaine dependence. Archives of General Psychiatry, 59, 538544. http://dx.doi.org/10.1001/archpsyc.59.6.538Google Scholar
Siqueland, L., Crits-Christoph, P., Frank, A., Daley, D., Weiss, R., Chittams, J., … Luborsky, L. (1998). Predictors of dropout from psychosocial treatment of cocaine dependence. Drug and Alcohol Dependence, 52, 113. http://dx.doi.org/10.1016/S0376-8716(98)00039-8Google Scholar
Sun, A. (2007). Relapse among substance-abusing women: Components and processes. Substance Use & Misuse, 42, 121. http://dx.doi.org/10.1080/10826080601094082Google Scholar
Tate, S. R., Wu, J., McQuaid, J. R., Cummins, K., Shriver, C., Krenek, M., & Brown, S. A. (2008). Comorbidity of substance dependence and depression: role of life stress and self efficacy in sustaining abstinence. Psychology of Addictive Behaviors, 22, 4757. http://dx.doi.org/10.1037/0893-164X.22.1.47Google Scholar
Tate, S., Brown, S., Unrod, M., & Ramo, D. (2004). Context of relapse for substance-dependent adults with and without comorbid psychiatric disorders. Addictive Behaviors, 29, 17071724. http://dx.doi.org/10.1016/j.addbeh.2004.03.037CrossRefGoogle ScholarPubMed
Terra, M. B., Barros, H. M., Stein, A. T., Figueira, I., Athayde, L. D., Ott, D. R., … Da Silveira, D. X. (2008). Predictors of relapse in 300 Brazilian alcoholic patients: A 6-month follow-up study. Substance Use & Misuse, 43, 403411. http://dx.doi.org/10.1080/10826080701202999Google Scholar
Waldrop, A., Back, S., Verduin, M., & Brady, K. (2007). Triggers for cocaine and alcohol use in the presence and absence of posttraumatic disorder. Addictive Behaviors, 32, 634639. http://dx.doi.org/10.1016/j.addbeh.2006.06.001CrossRefGoogle Scholar
Weiss, R. D., Griffin, M. L., Mazurick, C., Berkman, B., Gastfriend, D. R., Frank, A., … Moras, K. (2003). The relationship between cocaine craving, psychosocial treatment, and subsequent use. American Journal of Psychiatry, 160, 13201325. http://dx.doi.org/10.1176/appi.ajp.160.7.1320CrossRefGoogle Scholar
Witkiewitz, K., & Marlatt, G. A. (2004). Relapse prevention for alcohol and drug problems: That was Zen, this is Tao. American Psychologist, 59, 224235. http://dx.doi.org/10.1037/0003-066X.59.4.224CrossRefGoogle ScholarPubMed