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Routine Outcome Monitoring in Mental Health Outpatient

Shalvata Mental Health Center · 2014
ClinicalTrials.gov · Datasets · License: Public Domain · 2014
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allianceanxiety-disordersnapersonality-disorderspsychotherapypsychotic-disorders
Scientific Background: Inherent gaps exist between the worlds of research and clinical therapy, especially in mental-health systems. Developed as an important strategy aimed to bridge them, widening efforts worldwide have implemented Routine Outcome Monitoring (ROM), a method devised for systematic ongoing quantitative measurements used in diverse clinical practices, from psychotherapies to psychiatric management. The efficacy of this approach has been repeatedly demonstrated in various measures, such as satisfaction with treatment by patients and therapists, lower drop-out rates, symptomatic benefits, and more. Objectives: The aim of the current study is to test the feasibility and the clinical benefits of implementation of a Routine Outcome Monitoring System in a public clinical center, as a pioneering project in Israel, at the "Shalvata" Mental Health Center. Working Hypotheses: Incorporation of a ROM system in routine clinical practice is hypothesized to improve patients' and therapists' overall satisfaction, allow for early detection and intervention in therapeutic raptures, decrease drop-out rates, and improve various clinical outcome measures. Methods: The suggested study is a two-stage (implementation and intervention) open trial. 900 new outpatients in 'Shalvata' clinics will be recruited and randomized to intervention (ROM) and control groups. Assessment questionnaires will be filled periodically using 'CORE-NET', a computerized system enabling repeated measurements and feedback in a user-friendly and efficient manner. Data Analysis: The evaluation of the differential influence of monitoring processes on overall efficiency as compared to control group will be tested using Multiple Analysis of Variance (MANOVA). The predictive value of possible variables on process and outcome of therapy will be assessed using stratified regression analyses. The possible causal effects between specific lagged variables will be assessed using Hierarchical Linear Modeling
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