Digital Health Social Justice: a framework based on our studies in low-income and underserved communities

Computational Social Science Forum
Date: Monday, February 1, 2021
Time: 12:00-1:30 PM Pacific Time
Location: Register to receive the schedule and access links. 

Digital Health Social Justice: a framework based on our studies in low-income and underserved communities

Speakers: Adrian Aguilera, Berkeley School of Social Welfare, Berkeley Digital Health Equity and Access Lab (dHEAL), Latinx Center of Excellence in Behavioral Health; and Caroline Figueroa, Berkeley School of Social Welfare 

Abstract:  Though digital health–the use of apps, text messaging, and online interventions– can help people lead healthier lives, its rapid growth can also increase health inequities. Unequal representation or exclusion of groups, security and privacy vulnerabilities and power imbalances in design and ownership are examples of ethical and social issues that currently receive scarce attention. At the Digital Health Equity and Access Lab, we work on cutting-edge mobile health interventions for vulnerable populations. We will discuss our text-messaging studies for mental health support in low-income English and Spanish speakers. And we will talk about our new app using texting and machine learning to help people become more physically active. Finally, we will discuss a Digital Health Social Justice Toolkit, in collaboration with the Berkeley D-lab. This toolkit will provide guidelines, case studies, and resources for design, testing, and digital health evaluation from a social justice perspective.

The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Weekly meetings are hosted by researchers from BIDS and D-Lab, and participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. We welcome social scientists researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. This Forum is organized as part of the Computational Social Science Training Program, and interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact css-t32@berkeley.edu for more information.