Current Projects

The Bettering ADHD Outcomes (BAO) Lab is working to reshape how ADHD is understood, assessed, and treated, with a particular commitment to improving outcomes for Asian American and Native Hawaiian/Pacific Islander (AA & NH/PI) communities. Our work sits at the intersection of quantitative methods (machine learning, ecological momentary assessment, network analysis) and community-engaged research. Below are our three main lines of active work.

What It’s Like to Work in the Lab

We believe strongly in mentoring students toward independence as scholars. Graduate students in the lab are given ownership over projects and are actively supported in pursuing first-author publications and presentations from early in their training. If any of these projects sound exciting to you, we encourage you to apply.

Streamlining ADHD Diagnosis with Network Analysis and Machine Learning

ADHD is one of the most time-intensive disorders in the DSM-5 to assess, requiring evaluation across 18 symptoms. Our lab is asking: do we really need all 18? Using machine learning on data from clinical youth and adult samples, we’ve identified a streamlined set of just nine symptoms that predicts ADHD diagnosis, impairment, and comorbidity as accurately as the full symptom list. We’re now extending this work using a large-scale dataset of roughly 100,000 youth to build predictive models of school absenteeism in youth with ADHD, an outcome these students are at heightened risk for, but one that current assessment tools don’t do a good job of anticipating. Interestingly, our models suggest that the most powerful predictors extend well beyond the standard ADHD checklist to include disruptive behavior, depressed mood, and parenting factors, pointing toward a broader phenotype than the DSM currently captures.

Students on this project get hands-on experience with: applied machine learning (e.g., classification, variable selection), network analysis, large secondary datasets, and translating data-driven findings into assessment tools that could be used in real-world clinical and school settings.

Beyond the Checklist: Temperament and Emotional Dysregulation in ADHD

DSM-5 symptoms alone explain relatively little of the variability in outcomes among people with ADHD. Our lab is working to expand the definition of ADHD by examining temperament traits and emotional dysregulation, risk markers strongly tied to ADHD’s impact on daily life but not found in current diagnostic criteria. Using data from the Undergraduate Learning, Emotion, and Attention Research Network (U-LEARN), a nine-university consortium, we’ve shown that emotional dysregulation is nearly as important as inattentive symptoms, and more important than hyperactive/impulsive symptoms, in distinguishing college students with ADHD who experience significant impairment and internalizing problems from those who don’t. Building on this, we’ve also identified distinct ADHD profiles (e.g., a “Primarily Inattentive/Emotional Dysregulation Present” profile vs. a “High Severity/Emotionally Impulsive” profile) that may respond differently to intervention.

Students on this project get hands-on experience with: multi-site collaborative research, person-centered statistical approaches (e.g., profile/cluster analyses), conceptual work on how ADHD phenotypes are defined and measured, and a range of data collection methods including ecological momentary assessment, semi-structured interviews, computerized tasks, and intelligence testing.

Understanding and Reducing ADHD Service Disparities in AA & NH/PI Communities

AA & NH/PI communities are among the fastest-growing populations in the U.S., yet show some of the lowest rates of ADHD service use, and we still know very little about why. Our lab is working to change that. We’ve found that Asian American parents rate their children’s ADHD symptoms significantly lower than parents from other racial/ethnic groups, suggesting systematic under-identification driven by cultural factors in symptom recognition. We’ve also shown that AA & NH/PI college students with ADHD report less ADHD knowledge and more stigma than their White peers, and that knowledge gaps in particular help explain disparities in problem recognition. Currently, with support from an Ola HAWAII Team-Science Pilot Projects Grant, we’re conducting interviews with local caregivers in Hawai’i (in partnership with After-School All-Stars Hawaii) to understand what shapes families’ decisions to seek or avoid ADHD care. Early themes point to distrust of Western healthcare systems and the role of extended family support networks. This work will directly inform a community-centered intervention we’re co-developing with local caregivers, providers, and youth advocates to improve ADHD service engagement, the first of its kind for this population.

Students on this project get hands-on experience with: qualitative and mixed-methods research, community-engaged/participatory methods, and intervention development from the ground up.