首页> 外文期刊>Journal of affective disorders >The structure and dimensionality of the Inventory of Depressive Symptomatology Self Report (IDS-SR) in patients with depressive disorders and healthy controls.
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The structure and dimensionality of the Inventory of Depressive Symptomatology Self Report (IDS-SR) in patients with depressive disorders and healthy controls.

机译:抑郁症患者和健康对照者的抑郁症状自我报告清单(IDS-SR)的结构和维度。

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BACKGROUND: The Inventory of Depressive Symptomatology Self Report (IDS-SR) is a widely used but heterogeneous measure of depression severity. Insight in its factor structure and dimensionality could help to develop more homogeneous IDS-SR subscales. However previous factoranalytical studies have found mixed results. Therefore, the present study tested which factor structure underlies the IDS-SR and, in addition, if the factors can be used as unidimensional subscales. METHODS: Confirmatory factor analysis (CFA) was done to identify the best-fitting factor structure. The study sample consisted of 2600 individuals (mean age 40.5+/-12.1). We assessed model fit in 4 groups: 957 Major Depressive Disorder (MDD) patients, 450 remitted MDD patients, 570 patients with an anxiety disorder and 623 healthy controls to test the consistency of model fit. Rasch analyses in the full sample were used to evaluate and optimize the unidimensionality and psychometric quality of the factors. RESULTS: CFA indicated that a 3-factor model fits the IDS-SR data best and is consistent across groups, with a 'mood/cognition' factor, an 'anxiety/arousal' factor and a 'sleep' factor. In addition, Rasch analyses indicated that the 'mood/cognition' and 'anxiety/arousal' factors could be optimized to be used as unidimensional subscales. LIMITATIONS: The fit of only 4 models was tested, ranging from a 1- to 4-factor model. CONCLUSIONS: The IDS-SR is a heterogeneous instrument with a multifactorial underlying structure. It is possible to measure more homogeneous symptomatology with IDS-SR subscales, which could be useful in clinical practice and scientific research.
机译:背景:抑郁症症状自我报告清单(IDS-SR)是抑郁症严重程度的一种广泛使用但异类的指标。洞察其因子结构和维度可以帮助开发更均一的IDS-SR子量表。但是,先前的因子分析研究发现结果不一。因此,本研究测试了哪些因素结构是IDS-SR的基础,此外,这些因素是否可以用作一维子量表。方法:进行了验证性因素分析(CFA)以确定最合适的因素结构。研究样本包括2600名个体(平均年龄40.5 +/- 12.1)。我们评估了4组模型的拟合度:957名重度抑郁症(MDD)患者,450例缓解的MDD患者,570例焦虑症患者和623名健康对照组,以测试模型拟合的一致性。完整样本中的Rasch分析用于评估和优化因素的一维性和心理计量学质量。结果:CFA指出,三因素模型最适合IDS-SR数据,并且在各组之间是一致的,具有“情绪/认知”因素,“焦虑/自恋”因素和“睡眠”因素。此外,Rasch分析表明,可以将“情绪/认知”和“焦虑/情绪”因素优化为一维分量表。局限性:仅测试了1到4因子模型之间4种模型的拟合度。结论:IDS-SR是具有多因素基础结构的异类工具。可以使用IDS-SR分量表测量更均一的症状,这可能对临床实践和科学研究有用。

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