The three-dimensional community structure of attention-deficit hyperactivity disorder (ADHD) traits captured by the Adult ADHD Self-Report Scale: An exploratory graph analysis

Abstract

Objective: To employ a novel analytic method—namely, exploratory graph analysis (EGA)—to subclinical attention-deficit hyperactivity disorder (ADHD) trait scores in order to reveal their dimensional structure, as well as compare EGA's performance with traditional factor-analytic techniques in doing so. Method: 1149 respondents from a survey panel completed the ASRS, a common ADHD scale made up of 18 distinct trait measures. EGA and factor analysis were applied to identify traits which associate with each other. Results: EGA revealed 3 distinct communities, and ruled out a 2-community structure. This was in contrast to the 2-factor structure suggested by the factor analysis, and the conventional division of ADHD into two subdimensions (hyperactivity and inattention). Conclusion: A dimensional structure of three clusters (hyperactivity, impulsivity and inattention) may better reflect the traits underlying ADHD. EGA has benefits in terms of both analytic approach and interpretability of findings.