Empirical classification of XXXX with JIA: a multidimensional approach to @entity158 and well-being.

@entity1 @entity308 @entity625 @entity4932 @entity148 @entity158 @entity2720 @entity6659
OBJECTIVE: To investigate the relationship between @entity1 's @entity625 self-efficacy, trait- @entity148 , @entity308 , clinical state of the disease ( @entity158 , disability, number of somatic complaints and @entity2720 ) and age of the @entity1 . METHODS: Trait @entity148 and @entity308 of JIA @entity1 were measured by standardized scales (STAIC and @entity6659 ). For assessing self-efficacy CASE-scale was used. @entity158 , CHAQ and active joint count were used as indicators of the disease severity. The K-means cluster procedure was used to classify 145 consecutively recruited @entity1 aged 8 to 15, regarding age, trait- @entity148 and @entity308 . One-way multivariate analysis of variance (MANOVA) followed by separate ANOVA's was used for comparisons between the cluster groups. Associations between the cluster groups and the @entity1 's self-efficacy were then evaluated using multivariate analysis of variance (MANOVA). RESULTS: Four cluster groups were identified based on the degree of @entity308 and trait- @entity148 . Clinical disease-related parameters differed significantly in the cluster groups. @entity158 was not necessarily related to the severity of the disease or to the diagnosis ( @entity4932 , oligoextended and @entity625 ). A higher level of self-efficacy was related to lower levels of @entity308 , trait @entity148 and @entity158 . CONCLUSION: In JIA, the clinical classification of disease activity and severity did not directly correspond with @entity308 and trait- @entity148 in @entity1 with JIA. Instead, these were regulated by a self-efficacy, which was associated with less @entity158 and somatic complaints.
