Does Crude Measurement Contribute to Observed Unidimensionality of Psychological Constructs? A Demonstration With DSM-5 Alcohol Use Disorder

Mental disorders are complex, multifaceted phenomena that are associated with profound heterogeneity and comorbidity. Despite the heterogeneity of mental disorders, most are generally considered unitary dimensions. We argue that certain measurement practices, especially using too few indicators per construct, preclude the detection of meaningful multidimensionality. We demonstrate the implications of crude measurement for detecting construct multidimensionality with alcohol use disorder (AUD). To do so, we used a large sample of college heavy drinkers (N = 909) for whom AUD symptomology was thoroughly assessed (87 items) and a blend of confirmatory factor analysis, exploratory factor analysis, and hierarchical clustering. A unidimensional AUD model with one item per symptom criterion fit the data well, whereas a unidimensional model with all items fit the data poorly. Starting with an 11-item AUD model, model fit decreased and the variability in factor loadings increased as additional items were added to the model. Additionally, multidimensional models outperformed unidimensional ones in terms of variance explained in theoretically relevant external criteria. All told, we converged on a hierarchically organized model of AUD with three broad, transcriterial dimensions that reflected tolerance, withdrawal, and loss of control. In addition to introducing a hierarchical model of AUD, we propose that thorough assessment of psychological constructs paired with serious consideration of alternative, multidimensional structures can move past the deadlock of their unidimensional representations.