Factor Analysis of the Zung Self-Rating Depression Scale in a Large Sample of Patients With Major Depressive Disorder in Primary Care

Irene Romera; Helena Delgado-Cohen; Teresa Perez; Luis Caballero; Immaculada Gilaberte


BMC Psychiatry. 2008;8(4) 

In This Article

Abstract and Background

Background: The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS).
Methods: A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV).
Results: A clinical interpretable four-factor solution consisting of a core depressive factor (I); a cognitive factor (II); an anxiety factor (III) and a somatic factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843).
Conclusion: Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: core depressive, cognitive, anxiety and somatic, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles.

Depression can be manifested as a combination of a wide variety of symptoms: loss of interest, depressed mood, psychic anxiety, somatic anxiety, altered appetite, altered sleep, painful symptoms, etc.[1] In the primary care (PC) setting, approximately two thirds of patients with depression report somatic symptoms solely as the reason for consultation.[1] Indeed, depression is mostly difficult to recognize in such patients being the major reason for underdiagnosis and undertreatment of depression in PC.[1,2,3,4]

Traditionally, the heterogeneous symptoms of depression have been grouped into different symptomatic dimensions according to their clinical significance but there is no consensus on how this is best done.[1,5] Hence, depressive symptoms have been grouped into psychological and somatic;[1] into affective, cognitive, vegetative, behavioural, physical and impulsive-control;[6,7] or into affective, somatic and cognitive symptoms,[8] etc. However, from a clinical perspective, the grouping of depressive symptoms into symptomatic dimensions is purely intuitive and lacks empirical evidence. There is evidence that patients with different depressive symptom profiles are likely to have different prognosis and therefore might require a different therapeutic approach.[9] Furthermore, depressive symptoms have shown to differentially predict survival in patients with coronary artery disease.[10] Therefore, identifying the symptomatic dimensions of depression is relevant because of their diagnostic and therapeutic implications.[3,4]

There are few studies that identify or empirically group depressive symptoms into symptomatic dimensions. Some have analysed the factor structure of commonly used diagnostic instruments for depression, such as the Zung self-rating depression scale (ZSDS) or the Hamilton depression rating scale (HAMD-D), to examine the degree to which the emerged factors represent symptoms clusters and to assess whether the obtained factor structures are or not equivalent across subgroups (age, gender, diagnosis, etc.).[9]

In particular, the factor structure of the ZSDS has been studied in different populations, such as healthy subjects over the age of 65,[11] pregnant women,[12] patients with heart disease,[10] cancer[13,14] or chronic muscle pain,[15] students,[16,17] workers[18,19] etc., obtaining different factor structures. To date, and to our knowledge there are no studies examining the factor structure of the ZSDS in patients with depression in the PC setting.

Because of the underdiagnosis and undertreatment of depression in PC[2,3,4,20,21] as well as the possible future implications of different symptomatic profiles in the prognosis of depression, we believe that studying the symptomatic dimensions in this population is of great interest. We hypothesized that depressive symptoms in patients with MDD would be empirically grouped into symptomatic dimensions and that this grouping would be of clinical significance. For this purpose, we examined the factor structure and the composition of the resulted factors in a large sample of patients with MDD in PC by means of a factor analysis of the ZSDS.


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