Does Gender Inclusive Language Affect Psychometric Properties of the Illinois Rape Myth Acceptance Scale-Short Form? A Two-Sample Validation Study

UNCW Author/Contributor (non-UNCW co-authors, if there are any, appear on document)
Sasha Canan (Creator)
Institution
The University of North Carolina Wilmington (UNCW )
Web Site: http://library.uncw.edu/

Abstract: The Illinois-Rape Myth Acceptance-Short Form (IRMA-SF) is a widely used scale measuring people's endorsement of rape myths. However, it uses heavily gendered wording and makes gender-based assumptions that may affect its generalizability to various subgroups of people, including sexual and gender minorities who may view gender constructs outside of the heteronormative gender binary. This study validates the psychometric properties of a modified form of the IRMA-SF that is gender inclusive. Participants were adults with a range of sexual orientations and gender identities. Two sets of data were merged and then the sample was randomly split with a 20/80 weight. Data in the 20% split were used for exploratory factor analyses. Data in the 80% split were used for confirmatory factor analyses. According to the exploratory factor analysis, we found a theoretically predicted one-factor model was best (41% variance explained). Further, we found acceptable absolute model fit according to the confirmatory factor analysis (RMSEA = .07, p < .001; SRMR = .06) but unsatisfactory incremental fit (CFI = .82). These model issues were likely due to a floor-effect of low item variability which may call into question the utility of this scale in determining differences in rape myth acceptance overall. Overwhelmingly, participants in this study rejected rape myths. Researchers should explore the use of gender inclusive wording with an updated rape myth scale for use with sexual and gender minorities and, perhaps the general population, as some of these statements may be lacking in cultural relevance.

Additional Information

Publication
https://doi.org/10.1177/08862605221106144
Language: English
Date: 2022
Keywords
bisexual, gay, lesbian, psychometrics, queer, rape myth acceptance, sexual and gender minority, transgender

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