The Inventory of Complicated Grief—A Systematic Psychometric Review and Conceptual Replication Study of the Structural Validity. (July 2023)

• Record Type: Journal Article
• Authors: Schakowski, Alexander; Tönnies, Justus; Friederich, Hans-Christoph; Hartmann, Mechthild; Haun, Markus W.
• Is Part Of: Assessment. Volume 30:Number 5(2023)
• Page Start: 1418
• Page End: 1434
• Publication Date: 2023-07
• Subjects: Inventory of Complicated Grief -- COSMIN -- exploratory structural equation modeling -- unidimensionality; Psychological tests -- Periodicals; Psychodiagnostics -- Periodicals; Personality tests -- Periodicals; 150.287
• DOI: 10.1177/10731911221100980
• Languages: English
• ISSNs: 1073-1911

Abstract

The Inventory of Complicated Grief (ICG) is a commonly used self-report measure in psycho-oncology, best supportive care, and palliative medicine. However, existing validation studies yielded conflicting results regarding the structural validity. This study provides a psychometric review and conceptual replication of the ICG latent structure to test the hypothesis that existing studies overfit unreliable sources of variance, which overshadow the unidimensionality of the ICG. All proposed latent models identified in the psychometric review were tested in a series of confirmatory and exploratory structural equation models. Specifically, at least five to six latent intercorrelated factors were necessary to reach acceptable model fit. However, a general CG factor accounted for most variance and ICG sum scores showed predictable associations with anxiety and depressive symptoms, which suggests that the ICG is essentially unidimensional. There are indications that other measures of pathological grief show similar inconsistencies. Overall, potentially emerging subfacets of the ICG should not be interpreted as distinct "symptom clusters." If time constraints are an issue as is often the case in clinical research, complicated grief may just be measured by a reduced item set without a significant loss of information or complexity.