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Testing a Model of Black Cultural Strength Using Structural Equation Modeling

The present study examined a model of Black Cultural Strength and its relation to psychosocial health (N = 496). The purpose of the current study was to test a model of Black Cultural Strength, an interdependent combination of Black racial identity, communalism, cultural spirituality, positive racial socialization, and effective racism-related coping. Further, the study sought to understand if Black Cultural Strength could predict psychosocial health, a combination of life satisfaction and psychological well-being. The Black Cultural Strength model, which was tested through Structural Equation Modeling (SEM), hypothesized that higher levels of Black Cultural Strength lead to increased self-reported psychological well-being and life satisfaction. Results from this study indicated that Black Americans’ levels of mature racial identity, exposure to positive racial socialization (preparation for bias and cultural socialization), effective racism related coping (constrained resistance, empowered action, confrontation, and spiritual coping), culturally-based spirituality, and communalism were all interdependent and loaded onto one factor, Black Cultural Strength. Further, results showed that Black Cultural Strength was positively predictive of Blacks’ psychosocial health. Although the proposed hypotheses were supported, and an overall acceptable model fit was found, two modifications were made to the original proposed model. These modifications were conducted with theory and past empirical findings in consideration, therefore the current study provides strong evidence to support that interdependent Black cultural values are positively predictive of psychosocial health. Limitations, clinical implications, and further directions of research are discussed.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D88G8Z4R
Date January 2017
CreatorsJohnson, Veronica Elaine
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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