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Distinct neuropsychological profiles within ADHD: a latent class analysis of cognitive control, reward sensitivity and timing

Published online by Cambridge University Press:  07 August 2014

B. M. van Hulst*
Affiliation:
NICHE Laboratory, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
P. de Zeeuw
Affiliation:
NICHE Laboratory, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
S. Durston
Affiliation:
NICHE Laboratory, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
*
*Address for correspondence: B. M. van Hulst, MD, Department of Psychiatry – HP A 01.126, University Medical Center Utrecht, 3500 VW Utrecht, The Netherlands. (Email: b.vanhulst@umcutrecht.nl)

Abstract

Background

Multiple pathway models of attention deficit hyperactivity disorder (ADHD) suggest that this disorder is the behavioural expression of dysfunction in one of several separable brain systems. One such model focuses on the brain systems underlying cognitive control, timing and reward sensitivity. It predicts separable subgroups among individuals with ADHD, with performance deficits in only one of these domains. We used latent class analysis (LCA) to identify subgroups of individuals with ADHD based on their overall pattern of neuropsychological performance, rather than grouping them based on cut-off criteria. We hypothesized that we would find separable subgroups with deficits in cognitive control, timing and reward sensitivity respectively.

Method

Ninety-six subjects with ADHD (of any subtype) and 121 typically developing controls performed a battery assessing cognitive control, timing and reward sensitivity. LCA was used to identify subgroups of individuals with ADHD with a distinct neuropsychological profile. A similar analysis was performed for controls.

Results

Three subgroups represented 87% of subjects with ADHD. Two of our three hypothesized subgroups were identified, with poor cognitive control and timing. Two of the ADHD subgroups had similar profiles to control subgroups, whereas one subgroup had no equivalent in controls.

Conclusions

Our findings support multiple pathway models of ADHD, as we were able to define separable subgroups with differing cognitive profiles. Furthermore, we found both quantitative and qualitative differences from controls, suggesting that ADHD may represent both categorical and dimensional differences. These results show that by addressing heterogeneity in ADHD, we can identify more homogeneous subsets of individuals to further investigate.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2014 

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