2.37 CAPTURING THE NEURAL CORRELATES OF TRAIT DIFFERENCES IN ATTENTIONAL REGULATION: THE IMPACT OF QUESTIONNAIRE DESIGN

Objectives: Focused on the characterization of symptom severity in ADHD, myriad-standardized rating scales have emerged for quantifying domains of attentional dysregulation (i.e., inattention and hyperactivity). Unfortunately, the majority of these assessments, such as Conners Rating Scale, the Child Behavior Checklist (CBCL), and the Behavior Assessment System for Children (BASC), are based on problem behaviors. These problem-based scales potentially fail to capture meaningful dimensional variation among nonclinical populations, thereby skewing the distribution. In contrast, the Strengths and Weaknesses of ADHD-Symptoms and Normal-Behaviors (SWAN) is designed to capture the full range of behavior, yielding a normal distribution. The present study examined commonalities and distinctions in the neural correlates of trait differences in attentional regulation identified using the SWAN, Conners, BASC, and CBCL -- four widely used questionnaires in clinical practice. Methods: Parents of 104 participants (ages 6-17 years) in the Nathan Kline Institute-Rockland Sample completed all scales. Shapiro-Wilk test was used to assess scales for normal distribution. Kendall's W and Cronbach's α were used to assess concordance and consistency between scales. To identify regions for which full-brain connectivity patterns varied with interindividual variation in scale scores, we applied a Multivariate Distance Matrix Regression (MDMR) approach to multiband resting-state fMRI data. Results: Behavioral analysis indicated high concordance and consistency between the measures (W = 0.65, α = 0.85). MDMR analyses yielded similar patterns of voxel-wise results for the differing questionnaires, although the findings with the SWAN were more robust; as a result, only results for the SWAN passed a statistical threshold. Conclusions: Consistent with prior work, all questionnaires examined showed high concordance with one another. The SWAN may be more sensitive and may be more capable of representing neural correlates of ADHD subtypes because of its normal distribution. The ability of the SWAN to measure both strengths and weaknesses of ADHD make it the preferred tool for behavioral, population, and neuroimaging studies and for clinical assessment and treatment.