Search

Background: Psychiatric patients are more likely to be victims of crime than others in the community. Dual diagnosis patients with comorbid psychiatric and substance use disorders are especially prone to victimization. Victimization is associated with substance abuse, more severe symptomatology and homelessness. There is a strong need for interventions to reduce victimization in this population. We developed the Self-wise, Other-wise, Streetwise (SOS) training to reduce victimization in patients with dual diagnosis. Methods/design: This study is a randomized controlled trial using a parallel group design to determine the effectiveness of adding the SOS training to care as usual. Patients with dual diagnosis (N = 250) will be allocated to either care as usual plus SOS training (N = 125) or care as usual only (N = 125) using computer-generated stratified block randomization. To compare effectiveness participants will be interviewed at baseline and 2, 8 and 14 months follow-up. The primary outcome measure is treatment response (yes/no), defined as either no victimization at 14 months follow-up or at least a 50% reduction in incidents of victimization at 14 months follow-up compared to baseline assessment. Victimization is measured with the Safety Monitor, an adequate self-report instrument used by Statistics Netherlands to measure victimization on a large scale in the Netherlands. Outcome assessors are blind to treatment allocation. An economic evaluation will be performed alongside the randomized controlled trial and will take the societal perspective. Discussion: This study is the first randomized controlled trial to examine the effectiveness of an intervention that aims to reduce victimization in patients with dual diagnosis. If the intervention is effective it can be implemented in mental health care and contribute to the safety and well-being of patients. [ABSTRACT FROM AUTHOR]

Background: Internet-based interventions are seen as attractive for harmful users of alcohol and lead to desirable clinical outcomes. Some participants will however not achieve the desired results. In this study, harmful users of alcohol have been partitioned in subgroups with low, intermediate or high probability of positive treatment outcome, using recursive partitioning classification tree analysis. Methods: Data were obtained from a randomized controlled trial assessing the effectiveness of two Internet-based alcohol interventions. The main outcome variable was treatment response, a dichotomous outcome measure for treatment success. Candidate predictors for the classification analysis were first selected using univariate regression. Next, a tree decision model to classify participants in categories with a low, medium and high probability of treatment response was constructed using recursive partitioning software. Results: Based on literature review, 46 potentially relevant baseline predictors were identified. Five variables were selected using univariate regression as candidate predictors for the classification analysis. Two variables were found most relevant for classification and selected for the decision tree model: 'living alone', and 'interpersonal sensitivity'. Using sensitivity analysis, the robustness of the decision tree model was supported. Conclusions: Harmful alcohol users in a shared living situation, with high interpersonal sensitivity, have a significantly higher probability of positive treatment outcome. The resulting decision tree model may be used as part of a decision support system but is on its own insufficient as a screening algorithm with satisfactory clinical utility. [ABSTRACT FROM AUTHOR]