Department of Psychology, Arizona State University, 950 S. McAllister, P.O. Box 871104, Tempe, AZ 85287, USA.
Psychol Assess. 2012 Mar;24(1):101-13. doi: 10.1037/a0024712. Epub 2011 Jul 18.
There is growing evidence that psychiatric disorders maintain hierarchical associations where general and domain-specific factors play prominent roles (see D. Watson, 2005). Standard, unidimensional measurement models can fail to capture the meaningful nuances of such complex latent variable structures. The present study examined the ability of the multidimensional item response theory bifactor model (see R. D. Gibbons & D. R. Hedeker, 1992) to improve construct validity by serving as a bridge between measurement and clinical theories. Archival data consisting of 688 outpatients' psychiatric diagnoses and item-level responses to the Brief Symptom Inventory (BSI; L. R. Derogatis, 1993) were extracted from files at a university mental health clinic. The bifactor model demonstrated superior fit for the internal structure of the BSI and improved overall diagnostic accuracy in the sample (73%) compared with unidimensional (61%) and oblique simple structure (65%) models. Consistent with clinical theory, multiple sources of item variance were drawn from individual test items. Test developers and clinical researchers are encouraged to consider model-based measurement in the assessment of psychiatric distress.
越来越多的证据表明,精神障碍存在层次关联,其中一般因素和特定领域因素起着突出作用(见 D. Watson,2005)。标准的、单一维度的测量模型可能无法捕捉到这些复杂潜在变量结构的有意义细微差别。本研究通过充当测量和临床理论之间的桥梁,考察多维项目反应理论双因素模型(见 R. D. Gibbons 和 D. R. Hedeker,1992)提高结构有效性的能力。从大学心理健康诊所的档案中提取了 688 名门诊患者的精神诊断和对简明症状量表(BSI;L. R. Derogatis,1993)的项目水平反应的档案数据。与单维(61%)和斜交简单结构(65%)模型相比,双因素模型对 BSI 的内部结构具有更好的拟合度,并提高了样本的整体诊断准确性(73%)。与临床理论一致,来自各个测试项目的多个项目方差来源。鼓励测试开发人员和临床研究人员在评估精神困扰时考虑基于模型的测量。