I Haase1, O Kuhnt, K Klimczyk. 1. Forschung, Entwicklung und Qualitätssicherung, m&i-Klinikgruppe Enzensberg, Höhenstrasse 56, Hopfen am See, Germany. ingo.haase@enzensberg.de
Abstract
BACKGROUND: The recommended treatment for chronic pain is multidisciplinary with a cognitive approach. The aim of this study was to investigate whether the education level of patients was predictive of main outcome dimensions (pain intensity, disability, depression, physical functioning and return to work). PATIENTS AND METHODS: This was a secondary analysis of 413 patients who participated in an in-patient multidisciplinary pain treatment program. All patients were studied at baseline and after 6 months. The aim was to find predictors for the changes in scores of outcome measures (from admission to follow-up). Possible predictors were educational level and other available variables that are considered prognostic of treatment outcome, including age, gender, body mass index, endurance of pain, pain intensity, depressive symptoms and work status. Classification trees were used to predict outcome variables. RESULTS: The outcome was markedly improved in the sampling collective at follow-up compared with baseline. Education was the best predictor of treatment outcome and affected 4 out of the 5 outcome dimensions analyzed. CONCLUSION: If education level proves to be an intervening variable in further research, education adjusted treatment programs should be developed and evaluated.
BACKGROUND: The recommended treatment for chronic pain is multidisciplinary with a cognitive approach. The aim of this study was to investigate whether the education level of patients was predictive of main outcome dimensions (pain intensity, disability, depression, physical functioning and return to work). PATIENTS AND METHODS: This was a secondary analysis of 413 patients who participated in an in-patientmultidisciplinary pain treatment program. All patients were studied at baseline and after 6 months. The aim was to find predictors for the changes in scores of outcome measures (from admission to follow-up). Possible predictors were educational level and other available variables that are considered prognostic of treatment outcome, including age, gender, body mass index, endurance of pain, pain intensity, depressive symptoms and work status. Classification trees were used to predict outcome variables. RESULTS: The outcome was markedly improved in the sampling collective at follow-up compared with baseline. Education was the best predictor of treatment outcome and affected 4 out of the 5 outcome dimensions analyzed. CONCLUSION: If education level proves to be an intervening variable in further research, education adjusted treatment programs should be developed and evaluated.
Authors: Claudia M Witt; Lena Schützler; Rainer Lüdtke; Karl Wegscheider; Stefan N Willich Journal: Clin J Pain Date: 2011 Jul-Aug Impact factor: 3.442