Identifying potentially marker symptoms of attention-deficit/hyperactivity disorder

Abstract

BackgroundFor the diagnosis of attention-deficit/hyperactivity disorder (ADHD), the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) proposes that adherence to six symptoms in either group (inattention and hyperactivity/impulsivity) will lead to the diagnosis of one of three presentations of the disorder. Underlying this diagnostic algorithm is the assumption that the 18 symptoms have equal relevance for the diagnosis of ADHD, all are equally severe, and all have the same power to detect the presence of the disorder in all its degrees of severity, without considering the possibility of using marker symptoms. However, several studies have suggested that ADHD symptoms differ in both their power to discriminate the presence of the disorder and the degree of severity they represent. The aim of the present study was to replicate the results of previous research by evaluating the discriminative capacity and relative severity of ADHD symptoms, as well as to extend the investigation of this topic to Spanish-speaking Latin American samples.MethodsThe properties of ADHD symptoms rated by the parents of 474 Chilean children were analyzed. Symptom parameters were estimated using the graded response model.ResultsThe results suggest that symptoms of ADHD differ substantially in both the accuracy with which they reflect the presence of the disorder, and their relative severity. Symptoms “easily distracted by extraneous stimuli” and “have difficulty sustaining attention in tasks” (inattention) and “is on the go, acting as if driven by motor” (hyperactivity/impulsivity) were the most informative, and those with relatively lower severity thresholds.DiscussionThe fact that symptoms differ substantially in the probability of being observed conditionally to the trait level suggests the need to refine the diagnostic process by weighting the severity of the symptom, and even to assess the possibility of defining ADHD marker symptoms, as has been done in other disorders.

A data mining and item response mixture modeling method to retrospectively measure Diagnostic and Statistical Manual of Mental Disorders‐5 attention deficit hyperactivity disorder in the 1970 British Cohort Study

“…This could be partially explained by findings from Li et al (2015), who evaluated the full scale and found that two of the items missing from our scale had significant local dependence (di5 and di7; Li et al, 2015). Also, Arias et al (2018) analyzed the full scale and found that the most information was provided by three items (dh5, di2, and di8; relative weakness of dh6, we did not consider this an aberration, because other studies using typical levels of scale measurement also found dh6 to be a weaker item in terms of information provided (Arias et al, 2018;Gomez, 2011;Li et al, 2015). Our method extends previous work that aimed to identify ADHD in BCS70 (Brassett-Grundy & Butler, 2008) by adhering more closely to the current definition of ADHD and estimating a more precise dimensional measure.…”

“…This could be partially explained by findings from Li et al (), who evaluated the full scale and found that two of the items missing from our scale had significant local dependence (di5 and di7; Li et al, ). Also, Arias et al () analyzed the full scale and found that the most information was provided by three items (dh5, di2, and di8; Table ), all of which were in our scale, possibly offsetting the absent items.…”

“…We accepted the high difficulty because it provides information at higher levels of the trait, which is desirable for our purposes. Regarding the relative weakness of dh6, we did not consider this an aberration, because other studies using typical levels of scale measurement also found dh6 to be a weaker item in terms of information provided (Arias et al, ; Gomez, ; Li et al, ).…”

“…The present study adds to the literature on IRT models of ADHD, which has primarily focused on evaluating psychometric properties of items (e.g., Arias et al, 2018;Gomez et al, 2011;Li et al, 2015;Polanczyk et al, 2010). Our approach aimed additionally to minimize error and estimate a theta score as precisely as possible, through use of a large nonclinical sample and adjustment for the zero-inflated distribution of symptomatology.…”

“…IRT models have been widely recommended for measuring psychiatric and health-related constructs (Edelen & Reeve, 2007;Gorter et al, 2015;Muthen & Asparouhov, 2006;Sturm, Kuhfeld, Kasari, & Mccracken, 2017). Importantly, other authors have used IRT to evaluate psychometric item properties of DSM ADHD criteria (Arias, Esnaola, & Rodríguez-Medina, 2018;Gomez, 2007Gomez, , 2008Gomez, , 2011Gomez, , 2012Gomez, Vance, & Gomez, 2011;Li, Reise, Chronis-Tuscano, Mikami, & Lee, 2015), compare model fit in subsamples (Polanczyk et al, 2010), and provide quantitative verification of diagnosis (Lindhiem, Yu, Grasso, Kolko, & Youngstrom, 2015). These IRT studies reported good indicators of model fit in a variety of clinical and nonclinical samples.…”