Measuring Electronically Shared Rape Myths: Scale Creation and Correlates
Increased access to information online (e.g., social media) provides opportunities for exposure to rape myths (i.e., false beliefs about incidents of sexual assault). Social media, in particular, may serve a critical role in shaping rape culture. Thus, it is important to identify ways to assess onli...
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2024
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| In: |
Journal of interpersonal violence
Year: 2024, Volume: 39, Issue: 1/2, Pages: 369-392 |
| Online Access: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Drawer...
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| Check availability: | HBZ Gateway |
| Keywords: |
MARC
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| 100 | 1 | |a Thulin, Elyse J. |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a Measuring Electronically Shared Rape Myths: Scale Creation and Correlates |
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| 520 | |a Increased access to information online (e.g., social media) provides opportunities for exposure to rape myths (i.e., false beliefs about incidents of sexual assault). Social media, in particular, may serve a critical role in shaping rape culture. Thus, it is important to identify ways to assess online exposure to rape myths, especially given the influence online exposure may have on offline behaviors. Data were analyzed from 2,609 18–25-year-old participants (mean age = 20.9 years; 46.1% male; 71.6% White) recruited in 2017 through social media to complete an online survey on experiences and perceptions of sexual violence. We used exploratory and confirmatory factor analyses (EFA, CFA) to evaluate the relatedness of nine items adapted to reflect rape myths posted by friends on social media. We split the sample into training (50%) and testing (50%) sets for the EFA and CFA, respectively, then evaluated the correlation between experiences of sexual violence, substance use, and social media use and exposure to online rape myths. Eigenvalues (1-factor: 5.509; 2-factor: 0.803; 3-factor: 0.704; 4-factor: 0.482), factor loadings, fit statistics (RMSEA: 0.03; CFI: 0.99; TLI: 0.99; SRMR: 0.057), interpretability, and existing theory supported a 1-factor solution, which was supported by CFA fit statistics (RMSEA: 0.021; CFI: 0.99; TLI: 0.99; SRMR: 0.038). Cronbach’s alpha of the nine items was .77. Greater exposure to online rape myths was associated with greater likelihood of attempted rape perpetration (β = .052, SE = .016, p < .005), rape victimization (β = .045, SE = .009, p < .005), use of illicit drugs (β = .021, SE = 0.008, p < .05), being male (β = .017, SE = .008, p < .05), and being younger (β = −.008, SE = .002, p < .005). Our findings support assessing exposure to online rape myths, which may be important for informing sexual violence prevention and intervention efforts. | ||
| 650 | 4 | |a Sexual Assault | |
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| 700 | 1 | |a Philyaw-Kotov, Meredith L. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Walton, Maureen A. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Bonar, Erin E. |e VerfasserIn |4 aut | |
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