Lab Members
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.
Graduate Student, 3rd Year
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. My research is currently supported by the National Science Foundation Graduate Research Fellowship Program.
Graduate Student, On Internship at the Warren Alpert Medical School of Brown University
Ilana Ladis is currently on internship at the Warren Alpert Medical School of Brown University.
There, she treats postpartum depression and OCD as a therapist at the Women & Infants Day Hospital Program in Providence, RI.
She is interested in the development of scalable digital mental health interventions and understanding proximal risk factors
for suicide and other mental health problems.
Graduate Student, 1st Year
(Pronunciation: th-un-vee) I am interested in understanding anxiety, depression, and suicidality real-world to understand how environment, context, and everyday interactions influence the trajectories of symptoms. To do so, I use digital technology for ecological data collection and passive sensing. My work is motivated by a desire to increase intervention efficacy through personalized and adaptive interventions, as well as to increase access to interventions for diverse populations of adults and adolescents within existing care settings and systems, to maximize their reach.
Graduate Student, 6th Year
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.
Graduate Student, 2nd Year
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.
Project Coordinator & Lab Manager
My research interests include ways to adapt digital and mobile mental health interventions for anxiety and mood disorders to be more
inclusive and accessible, including alongside active and passive sensing techniques in developing just-in-time adaptive interventions. I am particularly interested in
developing scalable versions of these interventions including micro-sessions and single-session interventions, examining what the short-term benefits can be and
how symptoms can be alleviated in-the-moment.
Graduate Student, 5th Year
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.
Graduate Student, 3rd Year
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.
Former Graduate Students
Jessica Beadel
Miranda Beltzer
Elise Clerkin
Meghan Cody
Katie Daniel
Jeremy Eberle
Christina Emeh
Karl Fua
Jeff Glenn
Tynessa Gordon
Gena Gorlin
Jennifer (Simpson) Green
Joshua Magee
Meg Reuland
Jena Saporito
Allie Silverman
Shannan Smith-Janik
Shari Steinman
Alexandra Werntz Czywczynski
Sarah Coe-Odess
Erin Maresh
Nauder Namaky
Sam Portnow
Former Post-Docs
Philip Chow
Alexander Daros
Julie Ji
Ann Lambert
Craig Marker
Fred Smyth
Alexandra Werntz Czywczynski
Former Lab Staff
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
Former Visiting International Scholars
Nicola Hohensee
Wilson Melo
Bogdan Tulbure