The role of critical ethnic awareness and social support in the discrimination–depression relationship among Asian Americans: Path analysis.

Abstract

This study used a path analytic technique to examine associations among critical ethnic awareness, racial discrimination, social support, and depressive symptoms. Using a convenience sample from online survey of Asian American adults (N = 405), the study tested 2 main hypotheses: First, based on the empowerment theory, critical ethnic awareness would be positively associated with racial discrimination experience; and second, based on the social support deterioration model, social support would partially mediate the relationship between racial discrimination and depressive symptoms. The result of the path analysis model showed that the proposed path model was a good fit based on global fit indices, χ²(2) = 4.70, p = .10; root mean square error of approximation = 0.06; comparative fit index = 0.97; Tucker-Lewis index = 0.92; and standardized root mean square residual = 0.03. The examinations of study hypotheses demonstrated that critical ethnic awareness was directly associated (b = .11, p < .05) with the racial discrimination experience, whereas social support had a significant indirect effect (b = .48; bias-corrected 95% confidence interval [0.02, 1.26]) between the racial discrimination experience and depressive symptoms. The proposed path model illustrated that both critical ethnic awareness and social support are important mechanisms for explaining the relationship between racial discrimination and depressive symptoms among this sample of Asian Americans. This study highlights the usefulness of the critical ethnic awareness concept as a way to better understand how Asian Americans might perceive and recognize racial discrimination experiences in relation to its mental health consequences.

Perceived Racial/Ethnic Discrimination and Mental Health: a Review and Future Directions for Social Epidemiology

“…Regression analysis was primarily used, but some employed more sophisticated methods, such as latent class analysis and latent profile analysis to create categories of various exposure variables, including discriminatory experience, cultural stressors, and coping styles [22,28,30,31,44,45]. Techniques were employed by some studies to examine potential intermediary pathways between discrimination and mental health, such as through depressive symptoms or anxiety [19,24,43,46], avoidant coping strategies [33,47], trans diagnostic factors [48], general stress [40], stronger belief in an unjust world [49], acculturation-related and social support variables [13,50,51], anger [46], prosocial behavior [33], and perfectionism [52]. Other studies employed mediation techniques to examine if discrimination was on the pathway between a more upstream exposure, such as childhood adversity [53], historical trauma [28], a perpetual foreigner stereotype [37], white composition of one’s environment [29], critical ethnic awareness [50], and nativity [54], and a mental health outcome.…”

Annual review of Asian American Psychology, 2014.

“…O. Lee & Prescott, 2014; Nelson, Bishop, Sarapas, Kittles, & Shankman, 2014), lifetime psychiatric disorders ( n = 2; Hong, Walton, Tamaki, & Sabin, 2014; H. Y. Oh & DeVylder, 2014), trauma/Post Traumatic Stress Disorder (PTSD, n = 2; Koo, Nguyen, Gilmore, Blayney, & Kaysen, 2014; Mollica et al, 2014), Autistic Spectrum Disorder ( n = 2; Becerra et al, 2014; Chiang, 2014), gambling ( n = 2; I. Kim, Kim, & Nochajski, 2014; J.…”

“…Most studies targeted emerging adults ( n = 11; e.g., Kushins, 2014) or adults ( n = 8; e.g., Kushins, 2014), with only two studies focusing on adolescents (Cooc & Gee, 2014; Niwa, Way, & Hughes, 2014). Most studies used quantitative designs, such as experimental ( n = 4; e.g., Gibson, Losee, & Vitiello, 2014) and correlational designs, among which were cross-sectional ( n = 10; e.g., I. Kim, 2014) and longitudinal designs (Niwa et al, 2014).…”

“…Y. Chung, 2014) or mixed methods (Juang & Syed, 2014). Analytical methods involved regression ( n = 6; e.g., Khan, 2014), analysis of variance ( n = 5; e.g., Shih, Wout, & Hambarchyan, 2014), structural equation modeling (Festekjian, Tram, Murray, Sy, & Huynh, 2014; I. Kim, 2014), and group-mixture modeling (Niwa et al, 2014).…”

“…For example Kim, Parton et al’s (2014) paper was published in December 2014, but not indexed into the EBSCO PsycINFO database until May 2015. Additionally, between May 2015 and July 2015, we found three articles that were published in 2014 that would have been included in the annual review (Bell et al, 2014; Becerra, Herring, Marshak, & Banta, 2014; I. Kim & Kim, 2014).…”