Mindfulness and Valued Living in the Face of Racism‑Related Stress

Autor: Jennifer H. Martinez, Karen L. Suyemoto, Tahirah Abdullah, Inger Burnett-Zeigler, Lizabeth Roemer
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Mindfulness (N Y)
Popis: OBJECTIVES: Racism-related stress is associated with significant mental health costs, necessitating the development of coping strategies to mitigate the negative sequelae. Mindfulness and valued living (MVL)–based strategies may be uniquely beneficial in addressing the negative effects of racism-related stress for people of color (POC) by decreasing internalized messages, while increasing self-compassion, coping flexibility, and engagement in values-based actions. It is imperative that clinicians applying or recommending MVL strategies to POC for coping with racism-related stress understand the complex nature of racism and, given that complexity, consider how MVL may need to be adapted to be effective. This paper offers guidance to clinicians seeking to use MVL strategies with clients of color to cope with racism-related stress. METHODS: We provide a brief contextual literature review on the nature of racism, mental health impacts of racism-related stress for POC, and selected models of coping with racism-related stress. We also review existing mindfulness literature in relation to coping with racism-related stress, while offering considerations for adapting MVL strategies specifically for coping with racism-related stress. RESULTS: Altogether, the research points to the promise of MVL strategies as beneficial interventions for coping with racism-related stress, although more research is warranted. We recommend that clinicians consider the suggestions outlined to present MVL strategies to clients in culturally responsive, validating ways. CONCLUSIONS: Further research is needed to evaluate links between MVL strategies and mental health, and to evaluate whether discrimination-specific adaptations are beneficial in mitigating the mental health impacts of racism-related stress.
Databáze: OpenAIRE