Holm, Abby K. Johnson, authorHenry, Kimberly L., advisorCrain, Tori, committee memberFaw, Meara, committee member2020-06-222020-06-222020https://hdl.handle.net/10217/208420This work uses Crenshaw's (1989) Intersectionality to quantitatively study intersectional experiences of discrimination and depressive symptoms among historically marginalized and ignored populations. Using a series of multiple mediation models, discrimination (attributed to gender, sexual orientation and/or race/ethnicity) was modeled as a mediator between identity and depressive symptoms among seven diverse identity-based subgroups from Project STRIDE (75% sexual minority, 50% racial/ethnic minority; Meyer et al., 2006). I hypothesized marginalized subgroups would experience more discrimination, and in turn, more depressive symptoms. All models were compared against the eighth, least marginalized subgroup: straight White men. Discrimination partially mediated the effect of identity on depressive symptoms for sexual minority Black women, but only when accounting for discrimination on the basis of all three marginalized identities (woman, Black, and lesbian/bisexual). Sexual minority Black men experienced significantly less/less frequent depressive symptoms relative straight White men; after holding constant discrimination (at 0 for both groups), this was also true for sexual minority White men. Despite the nuances to quantitatively modeling intersectionality and potential issues of generalizability, this work might serve as a framework for carrying out future quantitative intersectionality-based studies. Enacted, this work has the potential to create a healthier and more equitable society for allborn digitalmasters thesesengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.discriminationintersectionalityhealth disparitiesdepressive symptomsPerceived discrimination and depressive symptoms among marginalized groups using an intersectionality frameworkText