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Activity Number: 59 - Data-Driven Ethics as Statistical Practice
Type: Topic Contributed
Date/Time: Sunday, August 7, 2022 : 4:00 PM to 5:50 PM
Sponsor: Conference on Statistical Practice Steering Committee
Abstract #322909
Title: Correlation and Structural Equation Analysis on the Effects of Anti-Discrimination Policies and Resources on the Well Being of Lesbian, Gay, and Bisexual College Students
Author(s): Brandy R Sinco* and Michael R Woodford and Alex Kulick and Jason C Garvey and Jun Sung Hong
Companies: U Michigan Center for Healthcare Outcomes and Policy and Wilfrid Laurier University and UC-Santa Barbara and University of Vermont / Higher Education and Student Affairs Administration and Wayne State University School of Social Work
Keywords: LGBQ+; College Students; Discrimination; Ethical Policy; Structural Equation Model; Correlation Matrix
Abstract:

Methods: Among a convenience sample of cisgender LGBQ college students (n=268), we examined the association between college- and state-level structural factors and students’ experiences of campus hostility and microaggressions, psychological distress, and self-acceptance. Relationships between these outcomes were first examined with Pearson and Spearman correlation coefficients. Structural Equation Modeling (SEM) was used to explore the meditating relationship of college-level structural factors on discrimination, distress, and self-acceptance. Bootstrapping was used to estimate the mediating effect from an inclusive non-discrimination policy to (hostility and microaggressions), then to psychological well-being. Results: Both the correlation matrix and SEM results suggested positive benefits from select college policies and resources, particularly non-discrimination policies that included both gender identity and sexual orientation (versus only sexual orientation). Based on the SEM and correlation matrix, a non-discrimination policy that included both sexual orientation and gender identity was significantly associated with lower microaggressions and overt hostility.


Authors who are presenting talks have a * after their name.

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