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.