Identifying meaningful subgroups of adults with severe mental illness

Abstract

Objective: The authors describe work conducted to identify, describe, and validate subgroups, or clusters, of adults with severe mental illness.

Methods: Clusters were first identified by using functional assessment ratings and statistical clustering procedures. Seven separate cluster analyses were accomplished, involving agencies in 15 counties in Ohio. Brief prose descriptions of the clusters were developed on the basis of the results of the statistical analyses. These descriptions were then used as stimuli in an extended expert-based validation and enhancement process that included work groups of consumers, family members, and providers.

Results: This sequential process produced generalizable, holistic descriptions of five core clusters of individuals with common strengths, problems, treatment histories, and life situations: older people in poor health who have psychiatric symptoms; individuals who have both psychiatric and substance use disorders; chronically mentally ill persons who have long treatment histories and severe disabilities; persons who appear to function well in the community but who are isolated as a result of anxiety, depression, or trauma-related social fears; and mental health consumers who function well in the community and who use personal and professional support systems to manage their mental health problems.

Conclusions: The results support the hypothesis that there is meaningful, but predictable, heterogeneity among persons who have severe mental illness. The clusters identified in this study can be used to plan, manage, and evaluate services.