Abstract
Objective: To evaluate alternative models of symptom clusters for the 22-item Neurobehavioral Symptom Inventory.
Participants: Three military samples, including 2 nonclinical samples (n = 2420, n = 4244) and 1 sample of individuals with recent head injury (n = 617).
Methods: In the first sample, exploratory factor analysis of Neurobehavioral Symptom Inventory responses was performed with tests of significant factors and model fit. In the other 2 samples, confirmatory factor analysis evaluated the fit of 3 models: 2- and 3-factor models based on the initial exploratory factor analysis, and a 9-factor model based on prior research.
Main Outcome Measures: The exploratory factor analysis used 2 tests for the number of factors: Parallel Analysis and Minimum Average Partial test. Confirmatory factor analysis models were evaluated using 2 measures of model fit, Root Mean Square Error of Approximation and Comparative Fit Index.
Results: Postconcussive symptoms can be described accurately by the 9 factors. However, the model of 3 intercorrelated factors, reflecting cognitive, affective, and somatic/sensory symptoms, fits the data more parsimoniously with little loss in model fit.
Conclusion: Although the 9-cluster result from prior research provides a valid description of the relations among items of the inventory, a 3-factor model, consisting of somatic/sensory, affective, and cognitive factors, provides nearly as good a fit to the data, with greater parsimony. We encourage clinicians and researchers to conceptualize the Neurobehavioral Symptom Inventory in terms of 3 coherent clusters of symptoms rather than as 22 individual items.