The ADHD teen integrative data analysis longitudinal (TIDAL) dataset: Background, methodology, and aims

Abstract

Background: The Attention Deficit Hyperactivity Disorder (ADHD) Teen Integrative Data Analysis Longitudinal (TIDAL) dataset integrates data from four randomized trials. Method: Participants with ADHD (N = 854; 72.5% male, 92.5% racial/ethnic minority, ages 10-17) were assessed three times across 12 months. Data includes parent, self, and teacher ratings, observations, and school records. The battery was harmonized using an Integrative Data Analysis (IDA) approach to form variables that assign unique values to all participants. Results: The data will be used to investigate: (1) profiles that organize the heterogeneous population into clinically meaningful subgroups, (2) whether these profiles predict treatment response, (3) heterogeneity in treatment response and variables that predict this response, (4) how treatment characteristics and adjunctive supports predict treatment response, and (5) mediators of treatment and whether these mechanisms are moderated by treatment characteristics. Conclusions: The ADHD TIDAL Dataset will be openly shared with the field to maximize its utility.