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A general factor model for the Beck Depression Inventory-II: validation in a sample of patients hospitalized with

Brett D Thombs1, Roy C Ziegelstein, Christine A Beck

  • 1Department of Psychiatry, Sir Mortimer B. Davis-Jewish General Hospital and McGill University, Montreal, Quebec, Canada. brett.thombs@mcgill.ca

Journal of Psychosomatic Research
|July 29, 2008
PubMed

Insights

This study validates a new model for the Beck Depression Inventory-II (BDI-II) in acute myocardial infarction (AMI) patients. The General-Somatic-Cognitive model better distinguishes depression from physical symptoms, improving outcome research for AMI survivors.

Area of Science:

  • Cardiology
  • Psychiatry
  • Psychometrics

Background:

  • Depression following acute myocardial infarction (AMI) is linked to adverse health outcomes, including mortality.
  • This association may be confounded by somatic symptoms common in AMI patients, potentially biasing depression assessments.
  • Validating measurement tools is crucial for accurate depression assessment in this population.

Purpose of the Study:

  • To validate a factor model for the Beck Depression Inventory-II (BDI-II) specifically for post-AMI patients.
  • To develop a model that can differentiate depressive symptoms from somatic symptoms related to AMI.
  • To enable more accurate assessment of depression's impact on health outcomes in AMI survivors.

Main Methods:

  • Administered the BDI-II to 477 hospitalized post-AMI patients across 10 cardiac care units.
  • Employed confirmatory factor analysis for ordinal data using MPLUS.
  • Tested a General-Somatic-Cognitive (G-S-C) model against standard correlated two-factor models.

Main Results:

  • The G-S-C model demonstrated comparable or superior fit to existing models.
  • The General Depression factor accounted for 73% of the variance in BDI-II scores.
  • Uncorrelated Somatic and Cognitive factors explained 11% and 13% of the variance, respectively.

Conclusions:

  • The G-S-C model offers a novel and statistically advantageous approach to interpreting the BDI-II measurement structure.
  • This model provides a valid method for assessing depression in AMI patients by isolating somatic symptom overlap.
  • It facilitates robust testing of the relationship between depression and health outcomes in AMI survivors.
Abstract

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