A systematic review of illness representation clusters in chronic conditions.

A person's beliefs about their chronic condition (illness representations) influence health and treatment outcomes. Recently, researchers have used clustering approaches to identify subgroups with different patterns of beliefs about their illness, with some subgroups having more favorable health outcomes than others. To date, these findings have not been synthesized. The purpose of this systematic review of the literature was to synthesize results of studies that used clustering approaches to analyze illness representation in chronic disease populations, in order to characterize the clusters and their relationship to health outcomes. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines we searched CINAHL, PsycInfo, and PubMed. To be included, studies had to be (a) peer reviewed, (b) in English, (c) performing a cluster analysis (CA), latent class analysis (LCA), or latent profile analysis (LPA), (d) using only illness representation (IR) subscales to form clusters, (e) measuring illness representation with the Illness Perception Questionnaire (IPQ-R), (f) in a chronic condition sample, and (g) measuring health-related outcomes. Twelve studies were included. Across studies, the number of clusters found ranged from two to three. In all studies, an association was found between illness representation group and at least one of their health outcomes. Illness representation clusters associated with favorable outcomes usually included lower disease-related consequences, fewer symptoms, less negative emotion, and a more stable disease pattern. The results of this review indicate that the relationship between the patterns of the illness representation profiles and health outcomes transcend diseases. Additionally, some dimensions of illness representation may be more important drivers of group membership than others.