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.
Keywords: ADHD; EGA; attention deficit hyperactivity disorder; exploratory graph analysis; factor analysis; network analysis; traits.
© 2023 The Authors. International Journal of Methods in Psychiatric Research published by John Wiley & Sons Ltd.