OBJECTIVE: This paper illustrates the process of constructing, selecting and applying simple measures in order to empirically derive patterns of course of psychotic episodes in schizophrenia. METHOD: Data were collected with a composite instrument constructed for a multi-centre, follow-up randomized controlled trial of adherence therapy for people with schizophrenia. The instrument included a retrospective weekly assessment of psychotic/non-psychotic status, which was used to derive the measures, and the DSM-IV course specifiers. RESULTS: The measures discriminated well between different course patterns and identified homogeneous clusters of subjects which correlated with the groups derived from the DSM-IV course specifiers. CONCLUSIONS: The new measures provide an empirical basis to identify specific patterns of course and to differentiate patients according to pre-defined criteria. They can be used in follow-up studies as measures of outcome, to investigate correlations between variables and to identify potential predictors of outcome.
OBJECTIVE: This paper illustrates the process of constructing, selecting and applying simple measures in order to empirically derive patterns of course of psychotic episodes in schizophrenia. METHOD: Data were collected with a composite instrument constructed for a multi-centre, follow-up randomized controlled trial of adherence therapy for people with schizophrenia. The instrument included a retrospective weekly assessment of psychotic/non-psychotic status, which was used to derive the measures, and the DSM-IV course specifiers. RESULTS: The measures discriminated well between different course patterns and identified homogeneous clusters of subjects which correlated with the groups derived from the DSM-IV course specifiers. CONCLUSIONS: The new measures provide an empirical basis to identify specific patterns of course and to differentiate patients according to pre-defined criteria. They can be used in follow-up studies as measures of outcome, to investigate correlations between variables and to identify potential predictors of outcome.
Authors: Karen Leffondré; Michal Abrahamowicz; Armelle Regeasse; Gillian A Hawker; Elizabeth M Badley; Jane McCusker; Eric Belzile Journal: J Clin Epidemiol Date: 2004-10 Impact factor: 6.437
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Authors: Martijn J Kikkert; Maarten W J Koeter; Jack J M Dekker; Lorenzo Burti; Debbie Robson; Bernd Puschner; Aart H Schene Journal: Int J Methods Psychiatr Res Date: 2011-06 Impact factor: 4.035