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Addressing racial equity in health psychology research: An application of the multicultural orientation framework.

Trisha L RaqueAmanda M MitchellM Nicole ColemanJeremy J ColemanJesse Owen
Published in: The American psychologist (2022)
Health psychology research emphasizes biological and positivist methods, giving less attention to the multifaceted sociocultural and political forces at play in health processes and outcomes. In this article, we present a new sociostructural approach for working toward racial equity in health psychology research, consistent with public psychology goals. This new approach uses the multicultural orientation framework (MCO) to guide health psychologists to consider the sociocultural and political history of their work, systems of oppression and privilege embedded in health research, and a path toward using research to achieve social change, antiracism, and health equity. We identify MCO as a tool for health psychology researchers to engage in ongoing self-reflection, cultivate cultural humility, and act upon opportunities to examine cultural factors at each step of the research process. After describing the MCO's components of cultural humility, cultural opportunities, and cultural comfort, we introduce questions that researchers can use to guide self-reflexivity and the implementation of MCO into health psychology research focused on racial equity. Specifically, we present the issue of Black women's perinatal health to embody the importance of applying MCO to health disparities research. We then walk through how to apply MCO in health research study development, data collection, and data dissemination. As we outline how to apply MCO to promote antiracist health research, we aim to enact social change consistent with the public psychology goals of building and fostering strong community relationships that inform social policy. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Keyphrases
  • healthcare
  • mental health
  • public health
  • health information
  • emergency department
  • health promotion
  • risk assessment
  • metabolic syndrome
  • pregnant women
  • human health
  • adipose tissue
  • deep learning
  • insulin resistance