AI Article Synopsis

  • The Beck Depression Inventory-II (BDI-II) is a widely used self-report tool for assessing the severity of depression, but there is no consensus on its optimal scoring or interpretation.
  • Researchers conducted a study using confirmatory factor analysis on data from a consistent clinical sample of 425 patients with major depressive disorder to evaluate different models of depression symptoms.
  • Their findings support the Ward (2006) model, which identifies three main factors of depression: General, Somatic, and Cognitive, while also endorsing the use of the overall BDI-II score in clinical settings.

Article Abstract

The Beck Depression Inventory-II (BDI-II) is a self-report instrument frequently used in clinical and research settings to assess depression severity. Although investigators have examined the factor structure of the BDI-II, a clear consensus on the best fitting model has not yet emerged, resulting in different recommendations regarding how to best score and interpret BDI-II results. In the current investigation, confirmatory factor analysis was used to evaluate previously identified models of the latent symptom structure of depression as assessed by the BDI-II. In contrast to previous investigations, we utilized a reliably diagnosed, homogenous clinical sample, composed only of patients with major depressive disorder (N = 425)--the population for whom this measure of depression severity was originally designed. Two 3-factor models provided a good fit to the data and were further evaluated by means of factor associations with an external, interviewer-rated measure of depression severity. The results contribute to a growing body of evidence for the Ward (2006) model, including a General (G) depression factor, a Somatic (S) factor, and a Cognitive (C) factor. The results also support the use of the BDI-II total scale score. Research settings may wish to model minor factors to remove variance extraneous to depression where possible.

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http://dx.doi.org/10.1037/a0019698DOI Listing

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