# ADHD heterogeneity, mechanisms, and risk profile

> **NIH NIH R37** · OREGON HEALTH & SCIENCE UNIVERSITY · 2021 · $856,032

## Abstract

ADHD remains a serious public health concern particularly in relation to long-term outcome, with recent
follow up data from other projects, such as the MTA study, suggesting that current assessment and
sustained treatment practices do not much alter clinical course. In addition, societal and clinical concerns
remain about mis-identification of children with ADHD who need care, because some children seem to
improve developmentally, while others have poor outcomes. While a great deal is known about the
correlates of developmental course, little of this knowledge has translated to clinical practice, and in
particular to clinical prediction—essentially, deciding whether a child, presenting with ADHD, requires
intervention or for whom a clinician can afford to wait and observed. We have previously made progress
here by re-conceptualizing ADHD as a problem in self-regulation involving cognitive control as well as
emotion regulation and emotionality. This has helped us find new and valid sub-profiles that are clinically
predictive. We follow that up here and add new effort to use advanced computational tools to predict
clinical course over a developmental period from 7-19 years of age, using a range of measures at different
levels of analysis, and thus to develop algorithms that could point the way toward next-generation clinical
translation from longitudinal studies.
RELEVANCE (See instructions):
ADHD continues to be a serious and impairing syndrome for millions of children, affecting families, schools,
and life quality. While a great deal is known about the correlates of ADHD, this information has not
translated sufficiently into more efficient clinical decision-making that recognizes the variety of children
within this population. This project seeks to use advanced analytics and long-term follow up data to identify
better ways to identify groups of children with ADHD with characteristic profiles to improve clinical care.

## Key facts

- **NIH application ID:** 10071921
- **Project number:** 5R37MH059105-19
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** JOEL T NIGG
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $856,032
- **Award type:** 5
- **Project period:** 1999-09-20 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10071921

## Citation

> US National Institutes of Health, RePORTER application 10071921, ADHD heterogeneity, mechanisms, and risk profile (5R37MH059105-19). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10071921. Licensed CC0.

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