Evaluating the Hierarchical Structure of ADHD Symptoms and Invariance Across Age and Gender

Abstract

The bifactor model of attention-deficit/hyperactivity disorder (ADHD) has been extensively explored, yet the tendency of the bifactor model to overfit data necessitates investigation of alternative, more parsimonious models, such as a modified bifactor structure. The present study used item response theory to compare unidimensional, correlated factors, bifactor, and modified bifactor models of ADHD symptoms in a clinical sample of youth ( N = 1,612) and examined differential item functioning (DIF) by age (<11 and ≥11 years) and gender. Results suggested that two restricted bifactor models showed superior fit compared with alternative models, and support strong general and inattention dimensions, with unreliable hyperactivity and impulsivity dimensions. No DIF was found across gender or age. The present study confirms that the general dimension (i.e., inhibition) and one specific dimension (i.e., sustained attention) represent distinct variability in ADHD symptoms that may improve prediction of symptom persistence, treatment response, or functional outcomes.

Measurement Invariance of the ADHD Rating Scale–IV Home and School Versions Across Age, Gender, Clinical Status, and Informant

“…Previous studies showed that several items from other ADHD rating scales can function differently across boys and girls, younger and older children (Makransky & Bilenberg, 2014), and children with or without a diagnosis of ADHD (Li, Reise, Chronis-Tuscano, Mikami, & Lee, 2016). However, these results are mixed, with more recent findings showing no differential item functioning by age and gender (Sturm et al, 2017).…”

“…ADHD-RS-IV allows clinicians the opportunity to obtain data from both parents (ADHD-RS-IV Home version; DuPaul, Anastopoulos, et al, 1998) and teachers (ADHD-RS-IV School version; DuPaul et al, 1997) regarding the frequency of each characteristic ADHD symptom according to established Diagnostic and Statistical Manual of Mental Disorders , fourth edition ( DSM-IV; APA, 2000 ) criteria. Regarding the factorial structure of ADHD-RS-IV results, exploratory factor analysis tested a one-factor, two-factor, three-factor, and, more recently, modified two-factor solution (Döpfner et al, 2006; DuPaul, Anastopoulos, et al, 1998; DuPaul et al, 1997; Martel, Von Eye, & Nigg, 2010; Sturm, McCracken, & Cai, 2017). Results of confirmatory factor analysis (CFA) sustained a two-factor structure of the scale, with inattention and hyperactivity being the two factors considered in a Chinese sample (Su et al, 2015), Japanese samples (Takayanagi et al, 2016; Tani, Okada, Ohnishi, Nakajima, & Tsujii, 2010), an Icelandic sample (Magnússon, Smári, Grétarsdóttir, & Prándardóttir, 1999), participants from 10 European countries (Döpfner et al, 2006), and another multinational study comprising participants from several European countries and Australia, Israel, and South Africa (Zhang, Faries, Vowles, & Michelson, 2005).…”

Psychometric Properties and Structures of the IAT, GPIUS and GAS Scales: A Bifactor Approach

“…The differences between a bifactor model and a bifactor MIRT model are as follows. On the one hand, thus far, all evaluations of a bifactor model have been conducted in the factor analytic framework using limited-information estimation methods, and all evaluations rely on a complete pairwise correlation matrix (Forero, Maydeu-Olivares, & Gallardo-Pujol, 2009;Sturm, McCracken, & Cai, 2017). However, many applications of Journal of Pacific Rim Psychology 5 bifactor MIRT are based on marginal maximum likelihood estimation with the expectation maximization algorithm (MML-EM; Bock & Aitkin, 1981) according to the IRT framework.…”

“…However, many applications of Journal of Pacific Rim Psychology 5 bifactor MIRT are based on marginal maximum likelihood estimation with the expectation maximization algorithm (MML-EM; Bock & Aitkin, 1981) according to the IRT framework. This method often is called a "full-information" item-factor analysis because it employs the entire item response matrix as part of the calibration (Gibbons & Hedeker, 1992;Sturm et al, 2017).…”

Early life predictors of attention deficit/hyperactivity disorder symptomatology profiles from early through middle childhood

“…Instead, variations in inattentive and hyperactive-impulsive symptomatology are used to describe the current ‘presentation’ of the disorder, with an understanding that an individual's symptom presentation may vary across time (American Psychiatric Association, 2013). At the same time, a growing number of psychometrically oriented studies have questioned the merits of distinguishing inattentive and hyperactive-impulsive symptomatology (Arias, Ponce, Martinez-Molina, Arias, & Nunez, 2016; Sturm, McCracken, & Cai, 2017; Toplak et al, 2009; Ullebo, Breivik, Gillberg, Lundervold, & Posserud, 2012; Wagner et al, 2016). These studies have consistently emphasized that a general propensity for ADHD underlies inattentive and hyperactive-impulsive symptoms and that little reliable variation remains in either dimension (especially hyperactive-impulsivity) after accounting for their shared variation.…”