bioRxivNeurosciencePreprint
Ethnic Identity Profiles Among Adolescents in the ABCD Study: Associations with Resting State Functional Connectivity and Perceived Discrimination
Taylor R. JanceticiD, Micaela LemboiD, Chloe L. HampsoniD, Donisha D. SmithiD, Julio A. PerazaiD, Erin Thompson, Mariana SáncheziD, Raúl GonzáleziD, Alan MecaiD, Angela R. LairdiD
Abstract
Ethnic identity refers to how individuals perceive and experience themselves in the context of social groups, racial background, or culture (Phinney & Ong., 2007). Ethnic identity is positively associated with psychological well-being (Rivas-Drake et al., 2014) and negatively associated with depression and anxiety (Forstmeier et al., 2021). Those with strong ethnic identity may display resiliency to the negative effects of discrimination on psychological well-being (Urzua et al., 2021). Phinneys model describes four profiles for how people put effort into, participate in, and reflect upon their ethnic identity (Phinney, 1989). Despite prior work addressing ethnic identity and psychosocial outcomes (for review, see Meca et al., 2023), few studies have considered its neurobiological underpinnings. In the current study, we identified profiles of ethnic identity among participants in The Adolescent Brain Cognitive Development Study (ABCD Study) using latent profile analysis. Next, we examined resting state functional connectivity differences across observed profiles and assessed the moderating effects of perceived discrimination. Results indicated heightened cingulo-parietal (CPAR) network connectivity among adolescents with highly diffuse ethnic identities; among moderately achieved ethnic identities, perceived discrimination moderated the association between ethnic identity and CPAR connectivity. We discuss how these findings may be related to attentional shift, error monitoring, autobiographical memory, and social judgements.
- organism: human
- assay: electronic health records
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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