TYDE awarded five fellowships to undergraduates conducting research tied to mental health and technology. Read about their experiences below!
Emma Brazier (Psychology)
This summer I worked as a member of UVA’s PIT CREW lab and its Coping Power Rural project, which is focused on integrating social emotional learning interventions into rural schools. I developed a series of (six) digital media literacy modules and lesson plans that will serve as a continuation of the original Coping Power Rural curriculum. As I continue to collaborate with the team, I will be involved in the creation of focus groups to receive community input on the proposed lessons, as well as the creation of additional lesson materials and a scoping review focused on the implementation of digital media literacy interventions in schools. Being fully immersed in the research lab was an integral experience to my development as a psychology student and solidified my desire to pursue psychology at the post-graduate level.
Mia deLadurantaye (Systems and Information Engineering)
This summer I worked in the Link Lab under Professor Afsaneh Doryab on a project supporting a digital footprint study planned for Fall 2025. The study seeks to examine how undergraduates’ digital behaviors—such as their search history, YouTube activity, Maps usage, and Gmail interactions—relate to their self-reported emotional, physical, and mental states. Over the course of the summer, I focused on building the technical foundation for this study. This included developing a data pipeline to parse and structure Google Takeout files, writing Python parsers to handle the different data sources, and prototyping an interactive dashboard. The dashboard is designed to allow participants to visualize their digital activity over time, retroactively label events with context or reflections, and explore behavioral patterns. We are now working to finalize the dashboard prototype so that the study can be successfully conducted in Fall 2025.
Kylie Fischer (Systems and Information Engineering)
This summer I worked on a project titled “Optimal Emergency Alert Messaging: A Stochastic Modeling Approach to Maximize Sheltering and Minimize Anxiety,” which aimed to improve emergency communication strategies at UVa. Using student survey data and a Markov Decision Process model, our team evaluated how different emergency alert frequencies impact awareness, sheltering behavior, and anxiety. I found that medium-frequency messaging (15-minute intervals) provided the best balance between rapid action and minimized psychological distress. I presented these findings to UVA’s Emergency Management which validated the practical relevance. We secured funding to extend this project as my capstone during the coming academic year, where I will explore implementing adaptive, state-based messaging policies and dive deeper into the large amounts of data that UVa has on Emergency Management. We plan to publish the findings to an IEEE conference in Spring 2026.
Xin He (School of Data Science)
My summer research investigated the effects of screen time usage on youth’s psychological and physiological health. Specifically, I explored how varying patterns of digital media engagement influence mental well-being, cognitive development, and physical health outcomes among children and adolescents. This work aims to inform evidence-based recommendations for healthier digital habits essential for thriving in today’s technology-driven society. Specifically, my research focused on how screentime affects young teens’ CBCL score (Child Behavior Checklist), and how their corresponding fmri data works as a mediator between the relationship of the screentime data and CBCL data. We plan to complete a paper by mid-September and submit to Science Direct.
Maddie Rose Mattox (School of Education and Human Development)
Thus summer I continued my work in the REAL Lab by launching a Standards of Teaching and Learning (SoTL) project focused on the use of generative artificial intelligence in higher education classrooms. Specifically, the project examined AI-assisted Feynman dialogues completed by students in an undergraduate child development course. Over the course of the fellowship, I developed a codebook and made substantial progress on data analysis. A major milestone was our successful submission to the National Council on Measurement in Education’s Artificial Intelligence in Measurement and Education Conference (AIME-Con). Our paper, titled “Talking to Learn: A SoTL Study of Generative AI-Facilitated Feynman Reviews,” was accepted and will be presented in late October.
