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Journal of Addiction
Volume 2017, Article ID 6415831, 11 pages
https://doi.org/10.1155/2017/6415831
Research Article

Predicting Inpatient Detoxification Outcome of Alcohol and Drug Dependent Patients: The Influence of Sociodemographic Environment, Motivation, Impulsivity, and Medical Comorbidities

1Jewish Hospital Berlin, Clinic for Psychiatry and Psychotherapy, Heinz-Galinski-Str. 1, 13347 Berlin, Germany
2Competence Center for Sleep Medicine, Charité-School of Medicine, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
3Charité-School of Medicine, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany

Correspondence should be addressed to Peter Neu; ed.etirahc@uen.retep

Received 22 December 2016; Accepted 13 February 2017; Published 6 March 2017

Academic Editor: Markus Backmund

Copyright © 2017 Yvonne Sofin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aims. This prospective study aims to identify patient characteristics as predictors for treatment outcome during inpatient detoxification treatment for drug and alcohol dependent patients. Methods. A mixed gender sample of 832 consecutively admitted drug and alcohol dependent patients were interviewed by an experienced physician. The impact of a variety of factors concerning social environment, therapy motivation, impulsivity related variables, medical history, and addiction severity on treatment outcome was examined. Results. 525 (63.1%) of the patients completed detoxification treatment whereas 307 (36.9%) dropped out prematurely. Being female, living in a partnership, having children, being employed, and having good education were predictive for a positive outcome. Family, health, the fear of losing the job, prosecution, and emergency admission were significant motivational predictors for treatment outcome. Being younger, history of imprisonment, and the number of previous drop-outs were predictive for a negative outcome. Conclusions. Variables concerning social environment and the number of previous drop-outs have been identified as best predictors for treatment outcome. Socially stable patients benefit from the current treatment setting and treatment shall be adapted for patients with negative predictors. Treatment may consequently be tailored with respect to intervention type, duration, and intensity to improve the outcome for those patients that fulfil criteria with negative impact on treatment retention.