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

Area of Science:

• Pediatric Psychology
• Neurodevelopmental Disorders
• Clinical Data Science

Background:

• The Attention Deficit Hyperactivity Disorder (ADHD) Teen Integrative Data Analysis Longitudinal (TIDAL) dataset combines data from four randomized controlled trials.
• It includes longitudinal data from 854 adolescents (ages 10-17) with ADHD, assessed over 12 months.
• Data sources comprise parent, self, and teacher ratings, observations, and school records, harmonized via an Integrative Data Analysis (IDA) approach.

Purpose of the Study:

• To identify distinct clinical profiles within the heterogeneous ADHD population.
• To determine if these profiles predict treatment response.
• To investigate factors influencing treatment response heterogeneity, including treatment characteristics and adjunctive supports, and to explore potential mediators and moderators of treatment effects.

Main Methods:

• Utilized an Integrative Data Analysis (IDA) approach to harmonize data from multiple randomized trials.
• Collected comprehensive data including multi-informant ratings (parent, self, teacher), observational measures, and school records.
• Employed longitudinal assessments across three time points over 12 months.

Main Results:

• The dataset is designed to facilitate research into clinically meaningful subgroups of ADHD.
• It will enable the examination of predictors for treatment response and response heterogeneity.
• The data allows for the investigation of how treatment variables and support systems influence outcomes.

Conclusions:

• The ADHD TIDAL Dataset will be made publicly available to the research community.
• This open sharing aims to maximize the dataset's utility for advancing ADHD research.
• Facilitates further investigation into personalized treatment approaches for adolescents with ADHD.