Research Hot Topics: "Better Targets, Broader Reach: Rethinking TMS Optimization by Balancing Methodological Innovation with Pragmatic Real-World Implementation" and "Toward an Ultra-Brief Digital Intervention for Type 1 Diabetes Distress"

Sponsored by the Mary Duke Biddle Foundation Lectureship in Behavioral Medicine RSVP for in-person attendance: https://duke.qualtrics.com/jfe/form/SV_bdvsKngsinJgdmK Tonisha Kearney-Ramos, PhD, is an Associate Professor of Psychiatry & Behavioral Sciences at Duke University and a clinical neuroscientist whose research focuses on advancing transcranial magnetic stimulation (TMS) across two major translational challenges that often sit in tension: how to optimize TMS precision and efficacy through biologically informed approaches for individual patients, and how to ensure that increasingly technologically sophisticated approaches can be delivered, accessed, and sustained across diverse real-world clinical environments.Her work in precision neuromodulation draws on network-based neuroimaging, neuromechanistic studies, and TMS clinical trials to better understand, target, and individualize treatment. This includes functional connectivity- and task fMRI-informed targeting, neuronavigation-guided treatment, accelerated stimulation paradigms, mechanistic neuroimaging and biomarker development, and high-resolution behavioral assessment (such as ecological momentary assessment) with a particular focus on substance use disorders including cannabis use disorder. Since joining Duke in March 2025, she has expanded her translational TMS research program to include implementation and health services research across psychiatric indications and care settings. This work focuses on developing and adapting implementation strategies to increase treatment reach, improve care pathways, and identify opportunities to streamline TMS delivery. Current efforts include community-engaged, stakeholder-informed research on access to TMS for tobacco smoking cessation, with particular attention to rural populations, as well as development of AI/ML approaches applied to large-scale electronic health record (EHR) data to characterize and optimize TMS care in routine clinical practice across psychiatric populations. Her overarching goal is to advance both better targets for greater clinical efficacy and broader reach in real-world care for greater public health impact.