A structure-based expert model of the ICD-10 mental disorders.
BACKGROUND: Many authors have highlighted that a classificatory system such as the ICD-10 or the DSM-IV should attempt to integrate categorical as well as dimensional aspects rather than relying only on a categorical distinction. METHODS: In the current study, a method is presented that allows both perspectives to be considered. Based on their clinical experience, 20 therapists were asked to rate a selection of ICD-10 mental disorders in terms of their similarity. The resulting data were processed by nonmetric multidimensional scaling on individual basis as well as mean basis and a cluster analysis. RESULTS: From a categorical point of view, the resulting mean cognitive map and the cluster analytic groups showed a good concordance with the ICD-10 F groups. Additionally, analogies to the critical observations with regard to the classification systems could be observed. From the dimensional point of view, there were two dimensions found (cognition and psychosis) which showed high correlations in the mean map. CONCLUSIONS: The method presented in this study offers an opportunity to account for dimensional as well as categorical aspects of classification by exploring the structure of the ICD-10 mental disorders directly from the point of view of therapists and thus creating the basis for an expert model.