Public Events and Series

The Health Equity Resources and Outreach (HERO) program organizes, sponsors, and participates in events and projects designed to build skills and knowledge related to health equity and inclusion of diverse populations in research. Most events are open to the public and free of charge.

  • The Integrating Special Populations into Research (INSPIRE) Mini-Medical Schools feature clinicians and scientists sharing self-care fundamentals and health implications of the latest research into common chronic conditions. These events are adapted to the language, culture, accessibility, and health concerns of our main stakeholder groups: children, adolescents and young adults, and older adults, as well as other populations underrepresented in research.
  • Lunch and Learn presentations by staff and faculty address the equity dimensions of the myriad elements of the research process, on topics such as data equity and bias, community roles in research, and strategies for inclusion diverse participants. Engagement Dialogues are opportunities to bring the knowledge of internal leaders and community partners to bear on health research, as community members and scientists engage in public dialogue on doing science in and with the community.
  • Advisory boards and collaboratives convene clinicians, investigators, and patient stakeholder for mutual learning, review, and participation in developing research agendas and implementations.

HERO also takes on multidimensional projects involving professional and lay researchers, artists, community-based groups and local leaders on topics of shared interest, such as dementia and dementia caregiving in communities of color, or the delivery of health care services in remote rural areas.

Spotlight Events

During 2022 the Clinical and Translational Science Center HERO program held online events to spotlight important health and data equity topics. Each event listing below includes the presentation, video and any resource or tool mentioned during the event.

Clinical research has the potential to help advance health for everyone. But for that to work, it must include people from all groups. When communicating about research results, it is vital to explain who was being studied. This session includes subject matter experts that can help you learn more about how to address race in your research.

  • Defining Race/Ethnic Categories and Genetic Ancestry in Cancer Research: The importance of defining these constructs based on your research questions. Laura Fejerman, Ph.D.’s research focuses on the discovery of genetic and non-genetic factors that contribute to breast cancer risk and prognosis in Hispanic/Latina women.
  • Data Visibility and Equity in Hmong Americans During the COVID-19 Pandemic. Kao Kang Kue “Kaykay” Vang, Ph.D., R.N., P.H.N. will discuss data visibility in Asian American subgroups, describe research in Hmong Americans and need for visibility, and report findings from research on COVID-19 mitigation behaviors in Hmong Americans.

This resource can be searched by keywordfiltered and sorted by field(s). If you have questions about the tool or would like a consultation, please contact us at HERO@ucdavis.edu or 916-734-3746.

Tip: Not seeing any results? Clear the prior keyword searches, filters and sorts and try again.

This presentation focuses on helpful tools, resources, and methods for researchers. Topics include:

  • Health Equity and the Library
  • Health Equity Data Resources
  • Identifying Special Populations in EMR Data and
  • Combating Inequities in Health Data Analysis

This resource can be searched by keywordfiltered and sorted by field(s). If you have questions about the tool or would like a consultation, please contact us at HERO@ucdavis.edu or 916-734-3746.

Tip: Not seeing any results? Clear the prior keyword searches, filters and sorts and try again

Alice Popejoy, Ph.D., presents her research and a graph-based data model and mobile application that facilitate the collection, storage, aggregation, and use of open-ended, as well as structured, data types. Categorical and free-text data from different studies can be combined to reveal complexity in human populations that racialized frameworks have erased. Objectives include characterizing the history of racial and ethnic classification in research and medicine and to investigate a novel approach using graph-based data model.

This resource can be searched by keyword, filtered and sorted by field(s). If you have questions about the tool or would like a consultation, please contact us at HERO@ucdavis.edu or 916-734-3746.