Thombs Brett D, Ziegelstein Roy C, Beck Christine A, Pilote Louise
Department of Psychiatry, Sir Mortimer B. Davis-Jewish General Hospital and McGill University, Montreal, Quebec, Canada.
J Psychosom Res. 2008 Aug;65(2):115-21. doi: 10.1016/j.jpsychores.2008.02.027. Epub 2008 May 29.
Many studies have linked symptoms of depression after an acute myocardial infarction (AMI) to negative health outcomes, including mortality. It has been suggested, however, that this link may be due to biased measurement of depressive symptoms in post-AMI patients related to confounding with somatic symptoms related to AMI. The objective of this study was to validate a factor model for the Beck Depression Inventory-II (BDI-II) that would allow for modeling of depressive symptoms after explicitly removing bias related to somatic symptom overlap.
A total of 477 hospitalized post-AMI patients from 10 cardiac care units were administered the BDI-II. Confirmatory factor analysis models for ordinal data were conducted with MPLUS to test the fit of a model with a single General Depression factor (all 21 BDI-II items) and uncorrelated Somatic (5 items) and Cognitive (8 items) factors (G-S-C model) compared to standard correlated two-factor models.
The G-S-C model fit as well or better than previously published correlated two-factor models. Seventy-three percent of variance in BDI-II scores is accounted for by the General Depression factor, whereas 11% and 13% respectively are accounted for by uncorrelated Somatic and Cognitive factors.
The G-S-C model is a novel approach to understanding the measurement structure of the BDI-II, presents advantageous statistical and interpretive properties compared to standard correlated factor models, and provides a viable mechanism to test links between symptoms of depression, as measured by the General Depression factor, and health outcomes among patients with AMI after explicitly removing variance from somatic symptoms unrelated to the General Depression factor.
许多研究已将急性心肌梗死（AMI）后出现的抑郁症状与包括死亡率在内的不良健康结局联系起来。然而，有人提出，这种联系可能是由于对AMI后患者抑郁症状的测量存在偏差，这与与AMI相关的躯体症状的混杂有关。本研究的目的是验证贝克抑郁量表第二版（BDI-II）的一个因素模型，该模型将允许在明确消除与躯体症状重叠相关的偏差后对抑郁症状进行建模。
对来自10个心脏护理单元的477名住院AMI后患者进行了BDI-II测试。使用MPLUS对有序数据进行验证性因素分析模型，以测试一个单一的一般抑郁因素（所有21个BDI-II项目）以及不相关的躯体因素（5个项目）和认知因素（8个项目）的模型（G-S-C模型）与标准相关双因素模型的拟合情况。
G-S-C模型的拟合情况与之前发表的相关双因素模型一样好或更好。BDI-II得分中73%的方差由一般抑郁因素解释，而不相关的躯体因素和认知因素分别解释了11%和13%。
G-S-C模型是理解BDI-II测量结构的一种新方法，与标准相关因素模型相比具有有利的统计和解释特性，并且提供了一种可行的机制，用于测试由一般抑郁因素测量的抑郁症状与AMI患者健康结局之间的联系，前提是明确消除与一般抑郁因素无关的躯体症状的方差。
