Digital Health

The Case for Including Disability in Social Science Demographics

October 15, 2024
by Mango Jane Angar. As we celebrate Disability Awareness Month at the D-Lab alongside the UC Berkeley scholarly community, how can we, as social scientists, individually promote accessibility and inclusion? To advance accessibility, we should focus on addressing the barriers faced by individuals with disabilities, using our research to provide insights for effective policy recommendations. Although most of us do not focus on disability-related issues, including disability as a demographic characteristic in our data collection can greatly enhance our understanding of diverse populations and improve the comprehensiveness of our analyses. This small step can contribute to broader efforts toward inclusion and social equity.

Claudia von Vacano, Ph.D.

Availability: By appointment only

Consulting Areas: Digital Humanities, Mixed Methods, Qualitative methods, Surveys, Sampling & Interviews, MaxQDA, Career Development

Elaine (Hua) Luo

Data Science Fellow 2024-2025
Graduate School of Education

Elaine (Hua) Luo is a PhD candidate in the Graduate School of Education, School Psychology PhD program. Her research interests focus on adolescents’ identity development and well-being under the transactional influence of entities in their socio-ecological systems. In her research, Elaine has utilized not only quantitative but also qualitative and mixed methods to study her research topics of interest. Before coming to Berkeley, Elaine earned her Master’s in Human Development and Psychology from Harvard Graduate School of Education and her Bachelor of Art in Education Sciences from...

Conceptual Mirrors: Reflecting on LLMs' Interpretations of Ideas

April 23, 2024
by María Martín López. As large language models begin to engrain themselves in our daily lives we must leverage cognitive psychology to explore the understanding that these algorithms have of our world and the people they interact with. LLMs give us new insights into how conceptual representations are formed given the limitations of data modalities they have access to. Is language enough for these models to conceptualize the world? If so, what conceptualizations do they have of us?

The More Things Change the More They Stay the Same?

December 18, 2023
By Tonya D. Lindsey, Ph.D. Think about how often you hear someone gripe about the deterioration of society and then blame the Internet or social media. This blog suggests that the things we are exposed to virtually are not new but instead present us with more and frequent opportunities to reflect on perennial social problems and find solutions even as we better understand ourselves as individuals in a global community.

Artificial Intelligence and the Mental Health Space: Current Failures and Future Directions

October 31, 2023
by María Martín López. María Martín López, a PhD student in the department of psychology whose research focuses on large language models within the context of mental illness, gives an overview of current failures and possible future directions of NLP models in the mental health space. She brings up questions that must be considered by all researchers working in this space and encourages these individuals to think creatively about the use of AI beyond direct treatment.

Monica Donegan

Data Science Fellow
Environmental Science, Policy, and Management

Monica is a third-year Ph.D. candidate in the Environmental Science, Policy, and Management program. She uses computational tools to study the evolution and ecology of agricultural plant pathogens. Previously, she worked on a data science team at a biotech company in Boston.

Caroline Figueroa, MD, Ph.D.

Research Fellow, Digital Health Social Justice Project Lead
School of Social Welfare
Digital Health Social Justice

Caroline Figueroa, MD Ph.D., is a Postdoctoral Scholar at UC Berkeley School of Social Welfare. She obtained her MD degree and Ph.D. degree at the University of Amsterdam in the Netherlands. Her Ph.D. research took place at the University of Amsterdam and at the University of Oxford, where she studied cognitive and neurobiological vulnerability factors for recurrence of depression in patients remitted from Major Depressive Disorder. Current research interest is on digital interventions for depression, with an emphasis on developing cutting-edge innovations that tailor to the needs of...

Alison Victoria White

Changemaker Technology Project
Digital Health Social Justice

Alison (she/her) is a recent graduate of UC Berkeley with a B.A. in Cognitive Science and minors in Data Science and Journalism. She is interested in precision medicine and the intersection of computer science, data science, and the fields of neuroscience and psychopathology. She now works as a Research Coordinator in Dr. Ian Gotlib's Stanford Neurodevelopment, Affect and Psychopathology Lab. In the past, she served as a Research Assistant in labs at UC Berkeley, UCSF, and Stanford in the areas of computational psychiatry, developmental psychopathology, and digital health. She...

We Are Working On Digital Health Social Justice: Here’s Why.

December 1, 2020

If you have ever used a mobile app to track your exercise, train in mindfulness, or collect diet tips, you may have noticed an overwhelming number of apps to choose from.

In 2017, app stores included around 300,000 health and wellness apps, such as meditation or fitness apps. Approximately 200 new apps surfaced daily. In 2020, there are almost 50,000 medical apps. These apps...