The subscale structure of the Inventory of Depressive Symptomatology Self Report (IDS-SR) in older persons

BACKGROUND: Using symptom dimensions may be more effective than using categorical subtypes when investigating clinical outcome and underlying mechanisms of late-life depression. Therefore, this study aims to identify both the factor and subscale structure of late-life depression underlying the Inventory of Depressive Symptomatology Self Report (IDS-SR) in older persons.

METHOD: IDS-SR data of 423 participants in the Netherlands Study of Depression in Older Persons (NESDO) were analyzed by exploratory (EFA) and confirmatory factor analysis (CFA). The best-fitting factor solution in a group of older persons with a major depressive disorder diagnosis in the last month (n = 229) was replicated in a control group of older persons with no or less severe depression (n = 194). Multiple group (MG-CFA) was performed to evaluate generalizability of the best-fitting factor solution across subgroups, and internal consistency coefficients were calculated for each factor.

RESULTS: EFA and CFA show that a 3-factor model fits best to the data [comparative fit index (CFI) = 0.98; Tucker Lewis Index (TLI) = 0.99; and root mean square error of approximation (RMSEA) = 0.052], consisting of a 'mood', 'motivation' and 'somatic' factor with adequate internal consistencies (alpha coefficient 0.93, 0.83 and 0.70, respectively). MG-CFA shows a structurally similar factor model across subgroups.

CONCLUSION: The IDS-SR can be used to measure three homogeneous symptom dimensions that are specific to older people. Application of these dimensions that may serve as subscales of the IDS-SR may benefit both clinical practice and scientific research.