ArticleJournal of racial and ethnic health disparities2026
"Am I Not Native Enough?" A Qualitative Exploration of Experienced Discrimination Among American Indian/Alaska Native Emerging Adults.
Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Centuries of trauma, displacement, and discrimination have taken a toll on American Indian/Alaska Native (AI/AN) life expectancy and health outcomes. Despite resilience, AI/AN emerging adults (EAs) face mental and behavioral health disparities, including substance use, posttraumatic stress, and suicide. Research has consistently shown that AI/AN EAs are at risk of experiencing discrimination, which can range from linguistic taunts to physical threats and violence, as well as institutional discrimination. Discrimination is a key driver of health, and yet, there has been limited research to understand what types of discrimination events occur in this population, and how these experiences may be perceived and processed by AI/AN EAs. Interviews with a subsample of 20 participants from a larger clinical trial explored dimensions of discrimination, including types of experiences; perceived motivation and impact; and how participants coped. Results highlight nuances in experienced discrimination, including vivid accounts of verbal and physical aggression. Some participants identified teachers or highly educated colleagues who were perceived to contribute to the problem. A surprising finding was the experience of discrimination in social interactions with tribal communities and other minority groups. This complements prior evidence of discrimination in and around AI/AN areas, suggesting that additional mechanisms of discrimination should be studied further. Results also highlight how participants were resilient, for example, by accessing support in the form of tribal workshops or professional mentoring. This study highlights opportunities for additional research, as well as actionable details that could inform programming to help AI/AN EAs cope with discrimination.
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