Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis

Abstract

An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.

Figure 1

Average MAMBAC, MAXCOV, and L-Mode curves for the research data along with taxonic and dimensional comparison data for the nine DBQ inattention indicators. To stabilize the shape of the curves, the analyses were replicated 10 times by randomly shuffling the cases with equal scores on the input indicator and recalculating the output indicator, with the average values across the 10 replications serving as the final results (Ruscio et al., 2006). Dark lines on the curves represent the actual data and the lighter lines represent one standard deviation above and below the average for each type of comparison data. CCFI = Comparison Curve Fit Index.

Figure 2

Average MAMBAC, MAXCOV, and L-Mode curves for the nine DBQ hyperactivity/impulsivity indicators.

Figure 3

Average MAMBAC, MAXCOV, and L-Mode curves for the five ADHD indicators.