Using network analysis and random forest regression, this study identified attention-deficit/hyperactivity disorder (ADHD) symptoms most important for indicating impairment in various functional domains. Participants comprised a nationally representative sample of 1249 adults in the United States. Bridge symptoms were identified as those demonstrating unique relations with impairment domains that, in total, were stronger than those involving other symptoms. Results suggested three inattentive (i.e., difficulty organizing; does not follow through; makes careless mistakes) and one hyperactive (difficulty engaging in leisure activities) bridge symptoms. Random forest regression results supported bridge symptoms as most important (compared to other symptoms) for predicting global and specific impairment domains. Hyperactive/impulsive symptoms appeared more strongly related to impairment in women, whereas difficulty organizing and easily distracted appeared more related to impairment in men. Clarification of bridge symptoms may help identify core characteristics of ADHD in adulthood and specify screening and intervention targets to reduce risk for related impairment.
Keywords: ADHD; bridge items; impairment; machine learning; network analysis.