Bethany Teachman is a Professor, and the Director of Clinical Training and Co-Director of Diversity, Equity and Inclusion at the University of Virginia in the Department of Psychology. Her lab investigates biased thinking that contributes to the development and maintenance of psychopathology, especially anxiety disorders. The lab also does work on technology-based assessments and interventions, including mobile monitoring of mood and emotion regulation, and digital interventions to reduce anxious thinking. She received her PhD from Yale University, and her BA from the University of British Columbia. She has had continuous funding from the National Institutes of Health and private foundations, and has more than 250 publications, including the books Introduction to clinical psychology: Bridging science and practice and Treatment planning in psychotherapy: Taking the guesswork out of clinical care. Dr. Teachman is Director of the public web sites MindTrails (https://mindtrails.virginia.edu/), a web-based research infrastructure that has offered digital interventions to reduce anxious thinking to thousands of visitors around the world, and Project Implicit Health (www.projectimplicithealth.com), an educational web site that allows visitors to assess their implicit associations tied to mental and physical health topics.
Dr. Teachman has been awarded an American Psychological Association Distinguished Scientific Early Career Award, multiple national mentoring awards, and she is a Fellow of multiple associations, including the American Association for the Advancement of Science. Dr. Teachman serves on the Board for the Society for Digital Mental Health, she was the inaugural Chair of the Coalition for the Advancement and Application of Psychological Science, and she received a Presidential Citation from the American Psychological Association.
Katharine Daniel, MA, is a PhD candidate in clinical psychology with a secondary concentration in quantitative psychology at the University of Virginia. While at UVA, Katie was a graduate student researcher in the Department of Psychology’s Program for Anxiety, Cognition, and Treatment Lab and in the School of Medicine’s Department of Family Medicine and Center for Behavior Health and Technology. She has been supported by a PEO Scholar Award, a Jefferson Scholars Foundation Fellowship, and an International Max Planck Institute for Human Development Fellowship. She is currently completing her clinical internship at Massachusetts General Hospital/Harvard Medical School on the CBT track at the Center for Digital Mental Health and the Center for OCD and Related Disorders. Katie’s research uses real-time monitoring and intensive longitudinal analytic methods to understand the real-world effects of anxiety and emotion dysregulation across changing contexts to inform the development of technology-assisted interventions. She is particularly interested in leveraging actively- and passively-sensed data to personalize the content and timing of mHealth interventions.
Jeremy Eberle is a PhD candidate in clinical psychology also pursuing a minor in
quantitative psychology. His research seeks to elucidate the cognitive, affective, and behavioral processes that
maintain emotional disorders and the pathways by which psychological treatments can change those processes. By
identifying mechanisms of disorder and change, he hopes to advance the development and dissemination of optimized,
streamlined, and personalized interventions. He also has interests in methodology and open science. Jeremy is a member
of the Raven Society and the department's outgoing student representative for the Psychological Clinical Science
Accreditation System. He received a BS in psychology and BA in philosophy from Tulane University and an MA in clinical
psychology from the University of Virginia. He is currently on clinical internship at the Stony Brook University
Consortium Internship Program and working in the Lab for Scalable Mental Health at Northwestern University.
Website: jeremyeberle.com
Twitter: @JeremyWEberle
My research focuses on using real-time monitoring and digital phenotyping to understand the everyday experiences of individuals with anxiety and related disorders, and to improve our prediction and treatment of these disorders. I hope to use this research to develop novel digital mental health interventions that use passive sensing and prediction to deliver treatment when it is most beneficial. I am also interested in understanding the systemic factors and everyday minority stressors that contribute to higher rates of mental illness among transgender, gender diverse, and LGBTQ+ individuals.
I use a mixed-methods approach to develop scalable digital mental health interventions.
As a secondary line of research, I am interested in understanding proximal risk factors for suicide and other
mental health problems, with an emphasis on problematic social media use and sleep disturbance. I am currently
funded by the National Science Foundation’s Graduate Research Fellowship Program.
Broadly speaking, I am interested in understanding how people with emotional disorder symptoms (e.g., anxiety, depression) experience and react to distressing situations. My research leverages ecological momentary assessment, lab-based tasks, and qualitative interview methods to better understand how individuals experience emotions (e.g., anxiety) and attempt to regulate them. A related line of work uses passive sensing (i.e., via smartwatches) to detect social contexts and social anxiety, which will ultimately inform the development and deployment of just-in-time adaptive interventions. I hope that my work will allow us to refine our understanding of how individuals experience emotions in-the-moment, how they regulate those emotions, and how we can best support them in making effective emotion regulation choices in their daily lives.
My research interests encompass the use of mobile technologies
(i.e., smartphones, wearable sensors) to better understand and treat emotional disorders such as anxiety and
depression. I hope to identify objective markers of symptomatology in real-world contexts and leverage this data to
develop and deliver just-in-time interventions via smartphones. I have a particular interest in using mobile
interventions to make mental health care more accessible to those with limited resources and in adapting
interventions for Latinx and youth populations.
My research interests include ways to adapt digital and mobile mental health interventions for anxiety and mood disorders to be more
widely used and accepted, including alongside active and passive sensing techniques in developing
just-in-time adaptive interventions that can be administered when and where people need them most. Additionally, I am interested in
what the short-term benefits of these interventions are, looking at how symptoms can be alleviated in-the-moment.
Allie Silverman’s research focuses on testing novel approaches to disseminate
evidence-based mental health services, with the goal to increase access to effective care particularly among
communities who have limited access to high-quality options. To do this, she has tested direct-to-consumer marketing
approaches to increase demand for services. She is also interested in developing and evaluating digital mental health
interventions for marginalized populations, and examining contexts in which these tools can be implemented to
reach more people.
My research leverages tools from complex systems science and computational modeling to psychological problems like anxiety and loneliness. In particular, I am interested in identifying the dynamic interactions among psychological and social factors that contribute to these problems. To do so, I use experimental paradigms, real-time data collection methods (e.g., passive sensing technology; ecological momentary assessment), and computational modeling to iteratively develop, formalize, test, and refine psychological theories and examine how psychological processes unfold across timescales and contexts. I hope this work will advance our understanding of the mutually reinforcing interactions among components of complex systems that produce and reinforce states of mental disorder so that we may ultimately improve treatment.
I pursue two primary lines of research: the first is concerned with improving
dissemination of and engagement with evidence-based digital mental health tools in community and health care
settings. My research in this area explores collaborative and integrated care models, using qualitative and mixed
methods that center patient experience and seek to understand real-world implementation hurdles. Secondly, I am
interested in discerning the impact of minority stress on cognitive biases in anxious LGBTQ+ individuals. I hope
to apply technology such as EMA (ecological momentary assessment) to better understand the day-to-day stressors
impacting this population, with the ultimate goal of synthesizing scalable digital interventions to improve anxiety
in LGBTQ+ individuals across the lifespan.
Jessica Beadel
Miranda Beltzer
Elise Clerkin
Meghan Cody
Christina Emeh
Karl Fua
Jeff Glenn
Tynessa Gordon
Gena Gorlin
Jennifer (Simpson) Green
Joshua Magee
Meg Reuland
Jena Saporito
Shannan Smith-Janik
Shari Steinman
Alexandra Werntz Czywczynski
Sarah Coe-Odess
Erin Maresh
Nauder Namaky
Sam Portnow
Philip Chow
Alexander Daros
Julie Ji
Ann Lambert
Craig Marker
Fred Smyth
Alexandra Werntz Czywczynski
Henry Behan
Claudia Calicho-Mamani
Nauder Namaky
Julia Schildwachter
Sarah Tolman
Alexandra Werntz Czywczynski
Diheng Zhang
Yueqin (Jean) Hu
Dan Martin
Joey Meyers
Bobby Moulder
Gus Sjobek
Nicola Hohensee
Wilson Melo
Bogdan Tulbure