The shift toward a health equity framework for eliminating the health disparities burden of racial/ethnic minority populations has moved away from a disease-focused model to a social determinants framework that aims to achieve the highest attainment of health for all. The New York University Center for the Study of Asian American Health (CSAAH) has identified core themes and strategies for advancing population health equity for Asian American populations in New York City that are rooted in the following: social determinants of health; multisectoral, community-engaged approaches; leveraging community assets; improved disaggregated data collection and access to care; and building sustainability through community leadership and infrastructure-building activities. We describe the strategies CSAAH employed to move the dial on population health equity.
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http://dx.doi.org/10.2105/AJPH.2015.302626 | DOI Listing |
BMC Public Health
January 2025
Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, 3052, Australia.
Background: In a world confronted with new and connected challenges, novel strategies are needed to help children and adults achieve their full potential, to predict, prevent and treat disease, and to achieve equity in services and outcomes. Australia's Generation Victoria (GenV) cohorts are designed for multi-pronged discovery (what could improve outcomes?) and intervention research (what actually works, how much and for whom?). Here, we describe the key features of its protocol.
View Article and Find Full Text PDFRandomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk remains unclear. In this study, we developed TrialTranslator, a framework designed to systematically evaluate the generalizability of RCTs for oncology therapies.
View Article and Find Full Text PDFPurpose Of Review: This review aims to evaluate the impact of artificial intelligence (AI) on cancer health equity, specifically investigating whether AI is addressing or widening disparities in cancer outcomes.
Recent Findings: Recent studies demonstrate significant advancements in AI, such as deep learning for cancer diagnosis and predictive analytics for personalized treatment, showing potential for improved precision in care. However, concerns persist about the performance of AI tools across diverse populations due to biased training data.
Nat Nanotechnol
January 2025
Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, USA.
The forward design of biosensors that implement Boolean logic to improve detection precision primarily relies on programming genetic components to control transcriptional responses. However, cell- and gene-free nanomaterials programmed with logical functions may present lower barriers for clinical translation. Here we report the design of activity-based nanosensors that implement AND-gate logic without genetic parts via bi-labile cyclic peptides.
View Article and Find Full Text PDFSci Rep
January 2025
Lyra Health, 270 East Ln, Burlingame, CA, 94010, USA.
Blended care therapy (BCT), which augments live, video-based psychotherapy sessions with asynchronous digital tools, has the potential to increase access to evidence-based treatments for posttraumatic stress disorder (PTSD). However, its effectiveness in diverse, real-world settings is not well-understood. This evaluation aimed to assess clinical outcomes of a BCT program for PTSD symptoms.
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