Please join us for an exciting Rutgers Institute for Health Brown Bag *Panel Discussion* covering digital mental health. We are honored to be joined virtually by three experts in the field: Patricia Cavazos-Rehg, PhD, Nicholas Jacobson, PhD, and Edward Selby, PhD.

Along with faculty from IFH’s Center for Population Behavioral Health, the panel will be taking questions from faculty and staff about the overall digital mental health field, including use of digital health tools for social media recruitment or emergency medical assistance and wearable devices and their application to treatment. This panel will be driven by questions from faculty, trainees, and staff, so please send your questions to our moderator, Dr. Carolyn Sartor (csartor@ifh.rutgers.edu), or directly to Nicole Swenarton (nswenarton@ifh.rutgers.edu).

Patricia Cavazos-Rehg, PhD, Professor of Psychiatry, Department of Psychiatry, Washington University School of Medicine in St. Louis

I am a clinically trained licensed psychologist who has been involved in biomedical research for nearly 20 years. My research program is funded by the National Institutes of Health (NIH) and is at the cutting edge of research into the use of technology to combat barriers to addiction and mental health treatment. Specifically, my research portfolio addresses health inequities and the use of technology to improve mental health and substance use assessment and treatment. For example, in a newly funded NIH study my team will implement an ecological momentary assessment (EMA) to track race-related microaggression experiences and drinking behaviors in real time among African American adults to evaluate associations between racial microaggressions and alcohol use in this high-risk group.

I am a Professor and Vice Chair for Diversity, Equity and Inclusion in the Department of Psychiatry at Washington University School of Medicine (WUSM). In 2017, I was named Director of the Mentored Training Program in Clinical Investigation at WUSM, which promotes the career development of junior faculty and postdoctoral fellows who have committed their careers to academic medicine by training them to become clinical and translational researchers. In 2019, I received NIH funding to co-lead the Training Leaders to Accelerate Global Mental Health Disparities in Research, a program funded by the National Institute on Minority Health and Health Disparities (T37MD014218) that focuses on global mental health disparities and trains advanced pre-doctoral students and post-doctoral trainees from diverse backgrounds in the US. In recognition of outstanding mentoring, in 2020 I was named Outstanding Global Health Mentor by the Institute of Public Health at WUSM, and in 2014, 2018 and 2021, I was named Course Master of the Year in the Master of Science in Applied Health Behavior Research program. Most recently, since 2022, I serve as Associate or Co-Director of two institutional Career Development Award programs: a NIDA-funded K12 at WUSM and NCATS-funded KL2 at the Institute for Clinical and Translational Sciences.

Nicholas Jacobson, PhD, Assistant Professor in Biomedical Data Science and Psychiatry, Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College

Nick Jacobson is a tenure-track assistant professor in the departments of Biomedical Data Science and Psychiatry within the Center for Technology and Behavioral Health in the Geisel School of Medicine at Dartmouth College. He directs the AI and Mental Health: Innovation in Technology Guided Healthcare (AIM HIGH) Laboratory.

Dr. Jacobson researches the use of technology to enhance both the assessment and treatment of anxiety and depression. His work has focused on (1) enhancing precision assessment of anxiety and depression using intensive longitudinal data, (2) conducting multimethod assessment utilizing passive sensor data from smartphones and wearable devices, and (3) providing scalable, personalized technology-based treatments utilizing smartphones. He has a strong interest in creating personalized just-in-time adaptive interventions and the quantitative tools that make this work possible. To date, Dr. Jacobson’s smartphone applications which assess and treat anxiety and depression have been downloaded and installed by more than 50,000 people in over 100 countries. Dr. Jacobson is the principal investigator of an R01 Awarded from the National Institute of Mental Health studying the use of personalized deep learning models to predict rapid changes in major depressive disorder symptoms using passive sensor data from smartphones and wearable devices.

Additionally, Dr. Jacobson has a strong quantitative background in analyzing intensive longitudinal data. In his work, he employs many different types of analyses including structural equation modeling, multilevel modeling, time-series techniques, dynamical systems modeling, and machine learning. He created a novel modeling technique, entitled the Differential Time-Varying Effect Model (DTVEM), which allows researchers to discover and model optimal lag times in intensive longitudinal data. He recently developed an anxiety and depression monitoring application entitled Mood Triggers which helps users to learn the triggers of their anxiety and depression in their daily lives. He also created an statistical package (written in R) called the Differential Time-Varying Effect Model (DTVEM) which is used to explore optimal time lags in intensive longitudinal data.

Edward Selby, PhD, Associate Professor & Director of Clinical Training, Department of Psychology, Rutgers University

Dr. Edward A. Selby, Ph.D. is an Associate Professor and the Director of Clinical Training in the Psychology Department at Rutgers University in New Jersey, where he also directs the Emotion and Psychopathology Lab. Dr. Selby’s work explores the roles of various forms of emotion dysregulation in the onset of adolescent and adult psychopathology, especially suicidal and self-injurious behavior, borderline personality disorder, and eating disorders. His work has been cited over 12,000 times and he is best known for his work establishing the Emotional Cascade Model of borderline personality disorder and self-injury, and more recently the Positive Emotion Amplification Model of anorexia nervosa. Recent work includes using novel analytic methods for exploring complex dynamic systems, such as Temporal Bayesian Network modeling, and disseminating a novel, standalone smartphone treatment app “Storm/breaker” – designed directly from his research on emotional cascades. To date, he has published 130+ peer-reviewed publications and book chapters and received extramural funding awards from the National Institute of Mental Health, the National Science Foundation, the Brain and Behavior Research Foundation (NARSAD), and Janssen Pharmaceutica. He has also received major private donations to support his work. He currently serves the Editor-in-Chief for the International Journal of Cognitive Therapy, and he is on the Editorial Boards for Clinical Psychological Science, Suicide and Life-Threatening Behavior, the Journal of Psychopathology and Clinical Science (formerly Journal of Abnormal Psychology), and the Journal of Clinical Child and Adolescent Psychology. Dr. Selby is a licensed clinical psychologist, he earned his Ph.D. in clinical psychology from the Florida State University in 2011, after completing his psychology residency at Brown University Medical School before joining the faculty at Rutgers.