By John F. Kelly, William L. White
Dependancy restoration administration: idea, examine, and perform is the 1st booklet at the restoration administration method of dependancy remedy and post-treatment help providers. unique in combining concept, study, and perform in the similar textual content, this ground-breaking identify comprises authors who're the foremost theoreticians, researchers, structures directors, clinicians and restoration advocates who've constructed the version. State-of-the paintings and the definitive textual content at the subject, dependancy restoration administration: concept, learn, and perform is obligatory analyzing for clinicians and all execs who paintings with sufferers in restoration or who're attracted to the sphere.
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Additional resources for Addiction Recovery Management: Theory, Research and Practice (Current Clinical Psychiatry)
Example text
1999;56:507 14. 57. Simpson DD, Joe GW, Broome KM. A national 5 year follow up of treatment outcomes for cocaine dependence. Arch Gen Psychiatry. 2002;59:538 44. 58. Institute of Medicine (IOM). Improving the quality of health care for mental and substance use conditions. Washington, DC: National Academy Press; 2006. 59. Rawson, R. Building a treatment system: elements and challenges. Presentation at the Hawaii Addiction Conference/AAPI Workgroup Scientific Conference; May 2009; Honolulu, Hawaii.
However, if addiction treatment providers are being held accountable for improved quality of life of their patients, what are the mechanisms and resources for service providers to achieve such performance goals? Additional issues include allocation of resources for longterm and comprehensive services and defining measureable outcomes. Perhaps the most important question is whether this system would produce better outcomes. ROSC as an evidence-based practice requires a system-level outcome evaluation.
Cambridge, MA: Harvard University Press; 2005. 26. Muthen B. Latent variable analysis: growth mixture modeling and related techniques for longitudinal data. In: Kaplan D, editor. Handbook of quantitative methodology for the social sciences. Newbury Park, CA: Sage Publications; 2004. p. 345 68. 27. Muthen B, Asparouhov T. Growth mixture analysis: models with non Gaussian random effects. In: Fitzmaurice G, Davidian M, Verbeke G, Molenberghs G, editors. Advances in longitudinal data analysis. Boca Raton, FL: Chapman & Hall/CRC Press; 2006.