AAPI Convergence: Microagressions and Community

According to CNN, the nonprofit Stop AAPI Hate logged reports of “at least 503 anti-Asian hate incidents … between January 1 and February 28” (cnn.com/2021/03/16/us/asian-americans-hate-incidents-report/index.html) Yet prejudice against AAPI communities during COVID-19 has also occured on a much more subtle and pernicious plane: microagressions.

To put it simply, a microagression is an act of implicit racism. The term was coinced by Dr. Chester Pierce, a psychiatrist at Harvard, in 1974. Microagressions play out in the workplace, on college campuses, in medical institutions, and countless other places, eating away at the self-esteem and self-confidence of students.

In the context of COVID-19, AAPI individuals have experienced microagressions as an insidious outlet for xenophobia and anti-Asian sentiment. As explained in an article in the Harvard Medical Student Review, “[whether] intentional or inadvertent, these slights indicate systemic perpetuation of Eurocentric/white supremacy, designating Asian/AAPI folks as inferior” (https://www.hmsreview.org/covid/the-other-covid-crisis).

What can be done to mitigate the effects of micro- and macro-agressions for AAPI individuals during (and after) the pandemic? A recent study in the journal Stigma and Health may shed some insights onto this issue.

In the study (https://psycnet.apa.org/fulltext/2020-77454-001.html), researchers Suyeon Lee and Sara Waters example a sample of approximately 400 Asian-identifying individuals in the US. The main result of the paper is that “social support” as measured by the Multidimensional Scale of Perceived Social Support could help mitigate discrimination, anxiety, and other negative effects. In Table 1, the authors find negative correlations between the “Social support” and “COVID-19 impact” variables, and also between “Social support” and “Discrimination composite,” hinting that there may be some underlying way in which said support plays a mitigating role.

Figure created in RStudio using computed correlation coefficients from Table 1 of the following paper by by Lee and Waters: https://psycnet.apa.org/fulltext/2020-77454-001.html. Here, A, D, P, S, C, and E represent Anxiety, Depression, Physical, Sleep, COVID-19 impact, and Discrimination composite respectively.

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