Rewards of Bridging the Divide Between Measurement and Clinical Theory: Demonstration of a Bifactor Model for the Brief Symptom Inventory

Department of Psychology, Arizona State University, 950 S. McAllister, P.O. Box 871104, Tempe, AZ 85287, USA.
Psychological Assessment (Impact Factor: 2.99). 07/2011; 24(1):101-13. DOI: 10.1037/a0024712
Source: PubMed

ABSTRACT 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.

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    ABSTRACT: In this supplement, the three complementary statistical methods that were used are explained in more detail. We used Mokken Scale Analysis (MSA), (multidimensional) IRT and bifactor analysis, which are all excellent methods to evaluate the psychometric properties and underlying structure of questionnaire data. We argue that using more than one method can provide a more complete picture of psychometric properties of questionnaire data; each of the methods have their strengths and weaknesses, and using more than one method allows the researchers to take the properties of the methods into account when interpreting the findings. Note that the description of MSA in this text was partly based on the description of MSA in the doctoral thesis of the �rst author of this paper (Paap, 2011), for which she gave her consent.
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    ABSTRACT: Research on comorbidity of psychiatric disorders identifies broad superordinate dimensions as underlying structure of psychopathology. While a syndrome-level approach informs diagnostic systems, a symptom-level approach is more likely to represent the dimensional components within existing diagnostic categories. It may capture general emotional, cognitive or physiological processes as underlying liabilities of different disorders and thus further develop dimensional-spectrum models of psychopathology. Exploratory and confirmatory factor analyses were used to examine the structure of psychopathological symptoms assessed with the Brief Symptom Inventory in two outpatient samples (n=3171), including several correlated-factors and bifactor models. The preferred models were correlated with DSM-diagnoses. A model containing eight correlated factors for depressed mood, phobic fear, aggression, suicidal ideation, nervous tension, somatic symptoms, information processing deficits, and interpersonal insecurity, as well a bifactor model fit the data best. Distinct patterns of correlations with DSM-diagnoses identified a) distress-related disorders, i.e., mood disorders, PTSD, and personality disorders, which were associated with all correlated factors as well as the underlying general distress factor; b) anxiety disorders with more specific patterns of correlations; and c) disorders defined by behavioural or somatic dysfunctions, which were characterised by non-significant or negative correlations with most factors. This study identified emotional, somatic, cognitive, and interpersonal components of psychopathology as transdiagnostic psychopathological liabilities. These components can contribute to a more accurate description and taxonomy of psychopathology, may serve as phenotypic constructs for further aetiological research, and can inform the development of tailored general and specific interventions to treat mental disorders.
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