Gender differences in videoed accounts of victim blaming for revenge porn for self-taken and stealth-taken sexually explicit images and videos

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Abstract

Using video recounts from revenge porn victims, this study explores whether levels of victim blaming differs for the sharing of self- and stealth-taken sexually explicit images and videos. Building on previous work which has demonstrated victim blame for both self- and stealth generated images in occurrences of revenge porn (Zvi & Schechory-Bitton, 2020), the reported study presents an original and ecologically valid methodological approach whereby 342 (76 male, 266 female) participants (Mage= 39.27, SD = 11.70) from the UK watched videoed accounts of real experiences of falling victim to revenge porn, rather than using text based, often fictional, vignettes to attribute blame which dominate studies in this area. All data was collected in 2019. The results demonstrated that significantly more blame was assigned to victims when participants were indirectly rather than directly asked who was to blame for the occurrence of revenge porn, supporting the notion of an unconscious processing bias in attributing blame. More blame was also assigned to those victims who themselves generated the material compared to when it had been acquired without their awareness by a perpetrator, suggesting the cognitive bias to be in line with a just world hypothesis. Male participants were more likely to blame a victim than were female participants, although sex of victim and mode of shared sexually-explicit material (video or image) did not appear to affect levels of victim-blame. Findings are considered in terms of extant research and the need for future work in the area of victim blame and revenge pornography.

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APA

Attrill-Smith, A., Wesson, C. J., Chater, M. L., & Weekes, L. (2021). Gender differences in videoed accounts of victim blaming for revenge porn for self-taken and stealth-taken sexually explicit images and videos. Cyberpsychology, 15(4). https://doi.org/10.5817/CP2021-4-3

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