Emerging
Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.

The Mutually Reinforcing Cycle of Poor Data Quality and Racialized Stereotypes That Shape Asian American Health

Yi, S. S., Kwon, S. C., Suss, R., Ðoàn, L. N., John, I., Islam, S.N., Trinh-Shervin, C.

Release Date:

Peer Review Study

Data Collection and Analysis
Education Access and Quality
Social and Community Context
Tools Included
Outside U.S.
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Data Collection and Reporting

The article focuses on two key examples of structural racism in the health context for Asian Americans: poor-quality data infrastructure and biases on the part of researchers, healthcare providers, and the public health community, fueled by pervasive stereotypes about the Asian American community (that is, model minority, perpetual foreigner, and healthy immigrant). The authors provide recommendations on how to implement systems-level change and educational reform to infuse racial equity in future policy and practice for Asian American communities.

Resource Details

Outcomes of Interest

Improve Data Infrastructure

Priority Population(s)

Asian

Setting(s) of Implementation

Geographic Area of Implementation

Implementation Period

2020-2021