Corrine Liu

Ms. Corrine Liu

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Daniel F. SarpongDaniel F. Sarpong
Daniel F. Sarpong
CLCorrine Liu
Corrine Liu
TGTandeca King Gordon
Tandeca King Gordon
Angela SyAngela Sy
Angela Sy
BMBibiana Mancera
Bibiana Mancera
FCfor the RCMI Community Engagement Consortium
for the RCMI Community Engagement Consortium
As of the end of 2024, the NIH-funded Research Centers in Minority Institutions (RCMI) Program supported 21 specialized centers at minority-serving institutions. Its goal is to strengthen biomedical research infrastructure and enhance the capacity of investigators focused on health disparities. Since 2017, the centers have operated under a unified framework that includes four core components, one of which is Community Engagement (CEC). In 2021, the RCMI Coordinating Center established the CEC consortium to unify expertise across minority-serving institutions, which include historically Black colleges and Hispanic-serving institutions. This consortium promotes cross-institutional collaboration and innovation in community-engaged research to advance health equity. This paper examines how RCMI CECs strategically enhance research relevance, advance public health outcomes, and address social determinants of health (SDOH) through inclusive, bidirectional partnerships that position communities as co-leaders in the research process. Drawing on data from NIH RePORTER, the 2024 Community Engagement Consortium Signature Programs Monograph, and RCMI Common Data Elements, we analyze the collective contributions of the Community Engagement Core (CECs) across 21 RCMI centers. Findings underscore the role of tailored strategies, cultural competence, and academic-community partnerships in mitigating health disparities and promoting equity in underserved communities.

6 October 2025 in Interactive Journal of Medical Research
Verified
Journal Article
Open access
NBNoah Brazer
Noah Brazer
BTBaylah Tessier-Sherman
Baylah Tessier-Sherman
DGDeron Galusha
Deron Galusha
SSSakinah C Suttiratana
Sakinah C Suttiratana
CLCorrine Liu
Corrine Liu
KWKaren H Wang
Karen H Wang
Background: Little is known regarding patient attitudes toward automatic sharing of race, ethnicity, and language (REL) data in health care settings despite the universal practice of data sharing across health care institutions and providers. Objective: This study aims to assess public comfort with disclosing and automatically sharing REL data in health care settings and understand the social factors associated with these attitudes. Methods: Using the 2022 DataHaven Community Wellbeing Survey from 1196 adult Connecticut residents, we examined factors associated with public comfort with disclosing and automatically sharing REL data across health care settings. We generated unadjusted and adjusted logistic models to examine associations between factors and responses to the data-sharing questions. Results: Most residents surveyed were White (n=873, 73%), followed by African American or Black (n=167, 14%), Asian or Native Hawaiian or other Pacific Islander (n=31, 2.6%), multiracial (n=31, 2.6%), and American Indian or Alaska Native (n=12, 1%). The majority of respondents were not Hispanic or Latino (n=1051, 87.9%). More than half of respondents reported excellent or very good self-rated health (SRH; n=635, 53.1%), and most participants reported almost always trusting their health care provider (n=939, 78.5%). Most participants reported being willing to share race and ethnicity data at a hospital or clinic (n=1008, 84.3%) and REL data automatically (n=947, 79.2%) in health care settings. Hispanic or Latino (adjusted odds ratio [AOR] 0.049, 95% CI 0.25-0.94) and multiracial (AOR 0.32, 95% CI 0.14-0.76) respondents were less likely to be willing to disclose race and ethnicity data compared to those who were not Hispanic or Latino and who were White, respectively. Individuals who sometimes trust health care providers (AOR 0.57, 95% CI 0.35-0.94) or rarely/never (AOR 0.35, 95% CI 0.15-0.85) were less likely to be willing to disclose race and ethnicity data than those who almost always trust health care providers. African American or Black (AOR 0.46, 95% CI 0.29-0.72) and American Indian or Alaska Native (AOR 0.18, 95% CI 0.04-0.75) individuals were less likely to be willing to share REL data automatically than White individuals. Those who sometimes trust health care providers (AOR 0.48, 95% CI 0.31-0.74) or rarely/never trust health care providers (AOR 0.25, 95% CI 0.11-0.56) were less likely to be willing to share REL data automatically than those who almost always trust health care providers. Those with poor/fair SRH versus very good/excellent SRH were less likely to be willing to share REL data automatically (AOR 0.54, 95% CI 0.34-0.85). Conclusions: Racial and ethnic identity, SRH, and trust in health care providers affect willingness to share REL information with providers and other health systems.