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



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.

revenge porn; victim blaming; sexting; sex shaming; online victim; technologically mediated sexual violence; real life; victimisation; online abuse
Author biographies

Alison Attrill-Smith

University of Wolverhampton, United Kingdom

Alison Attrill-Smith, PhD, Senior Fellow HEA, is a Senior Lecturer in Cyberpsychology in the Department of Psychology at the University of Wolverhampton. Her research interests revolve around self-presentation online with criminal intent and digital sexual misconduct.

Caroline J. Wesson

University of Wolverhampton, United Kingdom

Caroline J. Wesson, PhD is a Senior Lecturer in the Department of Psychology at the University of Wolverhampton. Her research interests combine social, cyber and forensic psychology with a current focus on online behaviours and victim-blaming.

Michelle L. Chater

University of Wolverhampton, United Kingdom

Michelle L. Chater is a PhD student in the Department of Psychology's Cyberpsychology Research Group. She is investigating victim blaming in incidents of online sexual misconduct.

Lucy Weekes

University of Wolverhampton, United Kingdom

Lucy Weekes, at the time of this research, was a postgraduate student on the MSc Cyberpsychology within the School of Psychology who contributed to this research as part of a work experience placement.


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Additional information

Editorial Record

First submission received:
October 19, 2020

Revisions received:
July 12, 2021
September 30, 2021
October 6, 2021

Accepted for publication:
October 7, 2021

Editor in charge:
Kristian Daneback

Full text


In recent decades, technological advances have opened up a wealth of possibility for people to interact with others the world over. Whilst this global connectivity afforded by Internet use has advantages, there are also disadvantages and potentially negative and damaging consequences of online interactions. The current study focuses on the latter. More specifically, it considers the now criminal act that has become known as revenge porn, which is the sharing of sexually explicit material (SEM) via any technological means with the intention to harm, cause shame, humiliation and/or embarrassment to another person (GOV, 2016). Revenge porn can consist of images, texts, and/or videoed content, often alongside identifying demographic information that can be sent to a targeted recipient such as a spouse, partner, or other family member. It can also be more widely shared on social networks and open websites to reach potentially unlimited numbers of viewers. Although being a victim of revenge porn can have diverse wide-reaching consequences (Calvert, 2013), there is currently very little research using real life victim experiences from which to build an understanding of peoples’ views and attitudes towards both victims and perpetrators of revenge porn. These views are important because they may not only influence the perpetuation of revenge porn but could also potentially impact whether a victim will report an occurrence of revenge porn. This is especially important since it is known from research around rape that often rape myths (M. R. Burt, 1980) and victim blame prevail and prevent a victim from reporting a sexual crime (Grubb & Turner, 2012).

What’s in a Name?

The act of revenge porn is quite specific to the unwanted and unauthorised sharing of sexual content that was either originally provided by a victim, or that has been acquired without a victim’s awareness. In line with Zvi and Schechory-Bitton’s (2020) recent suggestions, the current work will call the former self-taken and the latter stealth-taken sexually explicit material. This reflects that differences of acquisition for SEM occur. For example, SEM might initially be shared by a victim with a trusted other, most commonly a potential or existing romantic partner (self-taken) or it might be obtained by a perpetrator through covert actions without the victim being aware of its existence (stealth-taken). There is a third category of SEM used in revenge porn which is content created by a victim which is stolen or misappropriated by the perpetrator without the victim’s awareness. It is also worth acknowledging that many researchers also incorporate revenge porn into wider acts of digitally-mediated sexual misconduct. It has, for example, been included under the umbrella term of technologically mediated sexual violence (Powell & Henry, 2019), been called image based sexual abuse (e.g., Henry et al., 2020), referred to as non-consensual pornography (Eaton & McGlynn, 2020; Uhl et al., 2018) and has been placed on a continuum of image-based sexual abuse (McGlynn et al., 2017). For review of the debate around the labelling and names given to various sexual violence and sexually abusive acts, please see Henry et al. (2020) and McGlynn et al. (2021). Given that the reported work very specifically tested acts of the unauthorised sharing of SEM that constitute specific acts of revenge porn, and in line with the UK legal system and laws relating to revenge porn, the current work will retain the term revenge porn to convey both videoed and imaged sexually-explicit material that has been either shared with others or made public without consent. It is however noted that the term does often evoke connotations of victim blame, which also renders it relevant to the current exploration of blaming victims when an act of revenge porn occurs. The reported work thus considers whether participants directly (overtly) or indirectly (covertly) perceive victims to be to blame for initially sharing SEM compared to when material is acquired without their knowledge. Given that work on acts of physical sexual crimes has shown gender and sex effects on victim blaming (Grubb & Turner, 2012; van der Bruggen & Grubb, 2014), the research also explores whether these effects carry over to the online crime of revenge porn. It is also considered whether potential differences in victim blaming for revenge porn occur for video and image-based SEM. In order to provide context for this developing area of research, attention is first given to a brief review of selected relevant literature.

Revenge Porn and Sexting

A growing body of literature suggests that perpetrators commit an act of revenge porn with an intent to harass, humiliate, or harm an ex-partner (Stroud, 2014), or even to cause them destructive distress (Daswani & Pearson, 2014). Whilst this may often occur as a punishment for dissolving a relationship, it can also occur through unhappy friendships or rebuttals to draw attention to a victim that are not borne from revenge per se. Public revenge to open websites is more generally used for blackmail when a partner finds out that their other half has had an extramarital affair (Henry & Powell, 2015), or to demonstrate power and control over a victim (Citron & Franks, 2014). Revenge porn is not unique to the Internet. In the 1980s-90s home-made sex tapes were being leaked to the mass media in bitter celebrity spats. Fast forward to 2021 and an era where a snap decision to share any type of SEM can resurface years later to cause untold harm. Since the introduction of the new law to criminalise revenge porn in the UK (Ministry of Justice - Criminal Justice and Courts Act, 2015) prosecutions for revenge porn initially increased from 206 cases in 2015–2016, to 465 cases in 2016–2017 and then dropped to 464 reported cases in 2017–2018 (Crown Prosecution Service, 2019) Actual incidences of revenge porn are likely to be considerably higher than this, with police data indicating that one in three allegations of revenge porn are withdrawn by the complainant (BBC, 2018). Reports of exponentially rising figures during the UK Covid lockdowns throughout 2020–2021 are also prevalent amongst sexual abuse and revenge porn helplines (e.g., SWGfl, 2020). Ascertaining overall data for the UK for 2020 is not yet possible. However, data from the Metropolitan Police Force (London), suggests that incidences are almost doubling year on year, and that in fact higher levels of the illegal disclosure of sexual images and films occurred amongst males (140) than females (117) in the first quarter of 2020 (MetHq Information and Insight, 2020).

Despite the potential for SEM to be used in acts of revenge porn through it being shared with others, to social media, and more specifically to specialist harmful websites, people are still sharing SEM with one another, with what appears to be a blind faith that a recipient will safeguard the material and remain respectful to the sender even in the face of a relationship breakdown. This sharing frequently occurs through sexting. Sexting can be defined as the sending and receiving of sexually explicit content such as videos, images and text-based messages via mobile phones and the Internet (e.g., Salter et al., 2013). This can have dire consequences for the original sender, which can include psychological impacts such as post-traumatic stress disorder (PTSD), depression, anxiety and trust issues with new romantic partners, as well as financial and social losses through humiliation and social judgement (Bates, 2017). If the victim is blamed for having sexted the SEM in the first place, they might not only avoid reporting the crime but might also receive less empathy and consideration from others for falling victim to revenge porn. These risks appear to be largely ignored by many, with research showing frequent sexting amongst 12–17 year-olds (Lenhart, 2009), as well as amongst adults in committed relationships (McDaniel & Drouin, 2015; Parker et al., 2013). Whilst accurate current reports of levels of sexting are difficult to ascertain across all age groups as most work appears to focus on identifying sexting activities in teenagers and younger adults, there does appear to be a steady increase in either sharing or receiving SEM with an increase in age. Patchin and Hinduja (2016) found, for example, that this figure rose steadily from 14 year olds (27%) to 16 year olds (39.6%) to 44.8% of 17 year olds in one study reportedly having engaged in the sending or receiving of SEM. Indeed, amongst teenagers in some parts of the world, there is a badge of honour culture for collecting and sharing such SEM (Ringrose et al., 2013), which might imply that there is an increase in the social acceptance of sharing SEM. It would seem that at the moment of sending SEM to a current or potential lover, the sender rarely considers whether they are putting themselves at risk a) of that material being shared on, and b) of being blamed for making themselves a victim should that SEM subsequently be shared (e.g., Livingstone & Görzig, 2012). They might also resist reporting the occurrence of revenge porn for fear of being blamed for sharing the SEM with the perpetrator in the first place. There is however a misnomer that revenge porn occurs only for such self-taken and shared SEM.

Self-Taken and Stealth-Taken SEM

Contrary to the notion that the sharing of SEM occurs in a consensual relationship as a declaration of visual love (Larkin, 2014), oftentimes victims are not aware that images or video of their sexual activities exist until they surface as revenge porn (Bates, 2017). There is evidence that people as young as 13 years of age are habitually sending one another stealth-taken intimate images and videos, creep shots (sexualised images taken of a person in public without their knowledge) and up-skirting images (Project deSHAME, 2017). Further stealth-taken SEM examples include sexual encounters being filmed or imaged via a hidden camera, naked footage being generated whilst a person is inebriated or sleeping, as well as people being filmed in semi-public areas such as swimming pool changing rooms or, more recently, in holiday homes. There are two notable studies that have considered stealth-taken occurrences of SEM which was subsequently used for revenge porn. The first is offered by Bates’ (2017) report of her discussions with 18 revenge porn victims, one victim disclosed that her ex-husband and his friend drugged her and then filmed themselves raping her. It was only when he sent a video of the assault to her workplace that she became aware of the incident. Finding out that a loved one has betrayed trust to this extent, and the humiliation associated with falling victim to this type of sexual exploitation could be extremely traumatic to a victim. This was recently evidenced in the first civil action case brought in England and Wales, UK, when Chrissy Chambers successfully brought a case against an ex-partner for harassment, breach of confidence and misuse of private information after he had shared stealth-taken SEM covertly obtained during their relationship (Kleeman, 2018). The fall out and emotional turmoil experienced by the victim far outweighed embarrassment, humiliation or feeling revenged against, with the laying bare of her sexual life in court causing extensive long-lasting trauma. The second study was reported by Zvi and Schechory-Bitton (2020) in which they observed that victims were considered blameworthy for the occurrence of revenge porn for both self- and stealth-taken images. They did, however, focus on images as SEM. Given the aforementioned observation that revenge porn can also occur for videoed SEM, it is timely and of utmost importance to begin to unpick the consequences of revenge porn for victims of both self- and stealth taken revenge porn videos and images (Powell & Henry, 2018). In the current study, images are considered to be static photographic representations of a sexual nature whereas videos represent a clip of moving visual imagery. For inclusivity, and as mentioned above, it is acknowledged that stealth-taken SEM can take a number of forms, including the acquisition of SEM without consent or knowledge which a victim has willingly created, but has not shared that with another person. They often store the SEM on a personal device, smart phone or PC which a perpetrator then accesses without the victim’s awareness or consent. SEM can also be acquired when a perpetrator actively records or photographs sexually explicit behaviour without a victim’s knowledge or awareness. In line with victim precipitation theory (Petherick, 2017), if a victim has themselves generated and stored the SEM, they might be perceived to be responsible for it subsequently being used in an act of revenge porn against them. With origins in the criminal justice system, Schafer’s (1968) original conceptualisation of precipitation theory sought to contradict the perception that victims are always seen as good and perpetrators as bad. If precipitation theory holds true in cases of self-taken revenge porn, it would indeed be likely that people would be more likely to blame the victim than when stealth-taken SEM is involved, given that the victim would be seen to have originally generated the content that led to the crime.

Victim Blaming

To further elaborate on this suggestion, victim blaming occurs when a person against whom a crime or violent act has been committed is blamed for inciting or inviting the act through their own actions (van der Bruggen & Grubb, 2014). It can be particularly damaging to a victim’s notion of self and psychological well-being, often causing a sense of secondary victimisation, whereby the victim assumes that their behaviour led to the criminal act against them (Campbell & Raja, 1999). Research has established that this is particularly the case for victims of physical rape who are often blamed for the offence committed towards them (Strömwall et al., 2013; Stubbs-Richardson et al., 2018; Suarez & Gadalla, 2010), as are victims of domestic violence and/or intimate partner violence (Gracia, 2014), and child sex abuse (Back & Lips, 1998; Davies & Rogers, 2009). It can be argued that in revenge porn, a victim is often blamed for sharing the SEM with a potential perpetrator or simply for holding that material on their own technological device(s). An onlooker may perceive them to have been too trusting or too impulsive to have created and/or shared the material. This can often lead to onlookers adopting a just world hypothesis when considering victims of such crimes (Lerner, 1980). This cognitive bias leads to the assumption that the crime has befallen a victim as a morally fair consequence of their own actions or vice versa and that bad things only happening to bad people. Thus, if someone falls victim of revenge porn because they either shared or stored SEM, they are viewed to have brought those actions upon themselves and will ultimately be blamed therefore. The majority of people who engage in these cognitive biases do so as a distancing and self-protection mechanism: If such acts only befall bad people, and they conceive of themselves as good people, they believe themselves to be spared therefrom. Oftentimes, such biases are non-conscious and people will not be aware that their victim blame decisions are being driven by such cognitions (Dalbert, 2009). The current study will therefore involve both direct and indirect questioning on levels of victim blame in the occurrence of revenge porn. These cognitive fallacies cannot, however, account for the victim blame associated with those who are the subject of stealth-taken SEM being shared, unless it is attributed to a victim for engaging in sexual conduct. It should be noted though, that this would not explain victim blame in the case of completely non-compliant, stealth-taken revenge porn, such as up-skirting, covert photography or filming of a victim. It is therefore essential to further explore whether victims of both self- and stealth-taken revenge porn are chastised as victims of the consequences of their own actions.

Research focusing on victim blaming in cases of revenge porn is emerging. Of note is a study on the influence of perpetrator-victim sex in which Scott and Gavin (2018) found that participants without previous sexting experience were more likely to blame revenge porn victims. Starr and Lavis (2018) explored the effect of mode of sexting, either via text message or Snapchat, on victim blame in cases of revenge porn. Sending SEM via text can be seen as a potentially permanent record of the SEM whereas sharing SEM via the time limited medium of Snapchat, where material is viewable for 1 to 10 seconds only, may provide the illusion of being temporary and thus less risky. However, this does not prevent the receiver making a permanent record of the SEM via a screenshot. In their study, Starr and Lavis did not find mode of sexting to affect levels of victim blame. They did however find that people with higher levels of interpersonal trust demonstrated less victim-blaming toward victims of revenge porn. Weekes and Wesson (2017) found in their qualitative study that whilst participants often felt that trust had been violated when perpetrators shared SEM that had previously been gifted to them as part of a loving relationship, revenge porn victims were still considered responsible for having initially shared the SEM with the perpetrator. They also found that victims were perceived to be irresponsible if they created SEM and stored it on their own personal devices. Although not sharing the SEM with anyone else, participants perceived this to be putting oneself at risk of having that material stolen and subsequently used for an act of revenge porn. In a precursor to the current study, Van Den Eekhout and Attrill-Smith (2018) found that less blame was apportioned when SEM was acquired without victim’s awareness or knowledge compared to when it had been self-taken or shared. There is thus some evidence to suggest that levels of victim blame may differ depending on whether SEM was initially shared with a perpetrator, or whether it was acquired without the victim’s knowledge. These factors have not yet been considered in direct relation to revenge porn. There is however some work around physical rape that may help further elucidate when a victim may be blamed. For example, Strömwall et al. (2013) used vignettes depicting a rape scenario and found that the belief in a just world was a positive indicator of victim blame attribution. Belief in a just world enables bystanders to psychologically distance themselves from the possibility of falling victim to similar crimes by believing that heinous crimes only happen to bad people or those who deserve it. Belief in a just world thus provides a psychological buffer against potential crimes and provides onlookers with a sense of personal control over their own destiny (Furnham, 2003), albeit a false sense of control where the on-sharing of SEM is concerned. Belief in a just world has been demonstrated as a predictor of blame attribution towards victims of rape, with observers working on the assumption that victims somehow deserved the rape as a result of their own actions (Pinciotti & Orcutt, 2021; Strömwall et al., 2013; Vonderhaar & Carmody, 2015).

Distancing oneself from a victim as a self-protective mechanism is also at the core of Shaver’s (1970) defensive attribution theory. Shaver suggests that distinguishing oneself from a victim promotes a sense of security by rejecting the notion that misfortunes can happen to anyone. Thus, if an act of sexualised violence occurs to someone dissimilar to oneself or in a situation in which the observer is unlikely to find themselves, then the observer perceives themselves as being unlikely to befall a similar fate. Accordingly, misfortune is not borne from justice, but happens to people dissimilar to oneself. Those perceived to be similar to oneself are blamed less, whilst dissimilar others are blamed more for their own fate (D. L. Burt & DeMello, 2003). This may help account for the lower levels of victim-blaming reported by Starr and Lavis (2018) amongst participants who show higher levels of interpersonal trust: their higher levels of trust may make them more likely to also share SEM with the belief this would never go further than the intended recipient. However, trust was not found to interact with mode of transmission of SEM – sexting via text or Snapchat. Whilst Starr and Lavis considered the means by which SEM was shared, the origins of both conditions were self-taken SEM. The current study will therefore consider whether victim blaming occurs equally for self- and stealth-taken SEM along with a number of other factors that have been shown to impact levels of victim blame for rape, one being the gender of the perpetrator and of the victim.

Gender Differences

One way in which people distinguish themselves from a victim is through sex and gender differences. In a study on victim blaming, Grubb and Turner (2012) found that women apportioned more blame to male victims, and men blamed women more than men. In line with this finding, Bothamley and Tully (2017) also found that men were more likely than women to apportion blame to female victims in their consideration of public perceptions of revenge porn and victim blaming. Other studies report that women demonstrate a just world bias by perceiving male revenge porn victims as deserving of their fate, especially following infidelity (Buss, 2018; Pina et al., 2017). Whilst there appears to be a pattern of results emerging, there may be an inconsistency in the perception and judgement of revenge porn victims which is, in part, due to the diverse methodologies employed in currently available and outlined studies. The current work therefore explores gender differences based on reports from real revenge porn victims as opposed to researcher created vignettes

In terms of gender differences, it has been argued that revenge porn is an act of gendered violence (Hearn & Hall, 2019; Henry & Powell, 2016; McGlynn et al., 2019; Patella-Rey, 2018) and should be seen within the framework of norms around gender, sex and sexuality (Hearn & Hall, 2019). McGlynn et al. (2019) argue that revenge porn is driven by “misogyny, men’s entitlement and ‘laddish’ attitudes” (p. 5) with male perpetrators being more motivated by how others see them than by revenge. Branch et al. (2017) see the sharing of SEM as a means of “doing gender” – socio-cultural norms teach women to publicise their bodies in sexually explicit ways, owing to the normalisation of nudity in mainstream media, and teach men to consume SEM. The sharing of this SEM enables men to “do gender” by exerting their sexual control over women (Branch et al., 2017) and sexualising women in negative ways, for example by framing the victim of the revenge porn as promiscuous (Hearn & Hall, 2019).

Indeed, while men and women can be both victims and perpetrators of revenge porn, women are disproportionality victimised and may experience more adverse impacts of said victimisation than men (Henry & Powell, 2016; Patella-Rey, 2018). These impacts are also gendered: women are “slut shamed” whereas the distribution of such images of men affirms their masculinity (Henry & Powell, 2016; Patella-Rey, 2018), highlighting the societal double standards surrounding sexual behaviour in males and females whereby women are punished and men are rewarded (Patella-Rey, 2018). Such socio-cultural norms underpin the cognitive biases seen in victim-blaming.

In a study of both male and female participants, Gavin and Scott (2019) found that the experience of revenge porn was often trivialised for male victims in the sharing of self-images that were subsequently used in revenge porn. Their work focused on self-taken images, and victims blamed for consenting to originating the SEM in the first place. Gavin and Scott suggest that blame could have been minimised had the victim not consented to the material being generated, by asking a perpetrator to destroy images on dissolution of the relationship, or by agreeing with their partner (and later their perpetrator) that self-taken SEM did not imply consent for the later sharing thereof outside of the relationship. Whilst this research demonstrates victim blame for self-taken SEM (see also Henry et al., 2017), it did not explore whether that blame also holds true for stealth-taken SEM. One of their other noteworthy findings was that males were less likely to consider an occurrence of revenge porn as serious when there was a female perpetrator and male victim (see also Scott & Gavin, 2018). This discrepancy was in line with previous work which had demonstrated that male self-taken images of their bodies are often considered to affirm and demonstrate their masculinity and sexual ability (e.g., Patella-Ray, 2018; Ringrose et al., 2013). There is, however, a danger associated with this masculinity conception in that it perpetuates the male rape myth (Sleath & Bull, 2010). That is, that men should welcome, if not be flattered by, sexual attention from females regardless of the form of that attention. More recently, Banet-Weiser (2021) wrote on the #himtoo movement to consider that when accused of sexual misconduct crimes, that the accused men often adopt the mantel of themselves having been a victim. The #himtoo movement gained traction after the data collection reported in this paper but given that the connotations thereof have been gradually filtering through the mass media with reports of men in privileged positions increasingly defending themselves in response to the #metoo movement, it may be the case that men are equally perceived to be victims of revenge porn when it happens to them.

Taking all of these considerations together, it is essential to explore gender differences in revenge porn victim blaming, not least because this could play a role in the reporting of such crimes and how they are interpreted and experienced by a victim. Scott and Gavin (2019) also note that a victim’s knowledge around the creation and existence of SEM is an important factor in whether they are subsequently blamed for its use in revenge porn. The current study therefore not only considers differences for self- and stealth-taken SEM, but also whether gender differences occur for levels of victim blame. The work will also extend Starr and Lavis’s (2018), Gavin and Scott’s (2019) and Zvi and Schechory-Bitton’s (2020) focus on images in sexting and revenge porn by exploring a role of mode of SEM (videos and images) in victim blaming for revenge porn.

Mode of Sexually Explicit Material

A final factor considered in the current work is the type of SEM used in revenge porn. Static images (or photos) and videos (motion movement with duration of at least one second) can impact on the viewer differently. How sexual content is depicted can, for instance, influence viewers’ perceptions of the level of enjoyment of the person in the video or image (Flood, 2009). These attitudes and perceptions may, in turn, impact on the level of victim blame associated with revenge porn. If a video is self-taken, it may be more likely to depict the victim’s voluntary involvement. An image on the other hand may not evoke a sense of victim involvement. The authors could not find any research in this area which tested differences in levels of victim blaming between videoed and imaged SEM. The current study therefore includes this as a factor and will test whether participant views differ when the victim partook in consensual videos and images compared to stealth-taken images and videos.

Current Study and Hypotheses

The current study explores victim blaming in revenge porn by presenting participants with a series of videos in which actors recount the stories and experiences of real-life revenge porn victims. The stories told are based on publicly available celebrity videos and reports that were turned into scripts and re-told by actors to camera. Given that previous studies have shown that using videos appears to make stories more realistic to participants (e.g., Sleed et al., 2002), this was considered a good method for anonymising the reports and for counterbalancing length of story and content. The video accounts were created for both male and female victims, for self- and stealth-taken videos and images of a sexual nature. The use of videoed accounts of real-life experiences of revenge porn victimology as opposed to text-based, often fictional, vignettes which dominate studies in this area allows for an original and ecologically valid methodological approach to be taken in the current study.

It was predicted that male participants would engage in more victim blaming than females, regardless of the mode (video or images) and acquisition (self-taken or stealth-taken) of the shared SEM (H1). Secondly, female victims were expected to attract higher levels of blame than male victims regardless of mode and acquisition of SEM (H2). Participants were also expected to demonstrate higher levels of blame for SEM that had been self-taken than when stealth-taken (H3), and to be higher for a victim of videoed than imaged revenge porn (H4), regardless of whether it was self- or stealth-taken (H5). The final hypothesis considered whether a non-conscious processing bias was at work in assigning victim blame regardless of both perpetrator and victim sex, type of SEM and mode of acquisition (H6) by having participants complete both direct (explicit conscious processing) and an indirect (implicit non-conscious processing) measures of victim blame


All work reported received ethical clearance from the Faculty of Education, Health and Wellbeing ethics committee at the University of Wolverhampton.


Participants were recruited from the general population via social media websites such as Facebook using a snowball sampling method. This was expanded across different types of social media pages, shared by academics, students and family members to achieve as wide a demographic sample as possible. A total of 76 English speaking males and 266 females from the UK, with a mean age of 39.37 (SD = 11.70; range 18–68 years) took part in this study during the summer of 2019, only 69 of whom reported currently being a student.

A high proportion of participants reported being married (49.4%). This had not been considered in the initial design of the study. The occurrence of revenge porn could have different consequences amongst a married compared to a non-married sample, and so levels of victim blaming might be inflated amongst this group (see Lenhart, 2009; Livingstone & Görzig, 2012). An independent samples t-test revealed, however, that no significant difference in mean victim blame scores between married (M = 2.20, SD = 0.85) and non-married participants (M = 2.25, SD = 0.87), (t(340) = 0.523, p = .601) was present. This difference is therefore given no further statistical consideration.

Design and Materials

This study employed a mixed groups design with one between groups factor of victim sex (male vs. female victim). Mode of revenge porn (image vs. video) and SEM acquisition (self-taken vs. stealth-taken) provided the two within groups factors. Levels of victim blame for the person in each video constituted the first dependent variable, and a forced choice measure of who was to blame for the publication of the SEM as revenge porn provided a second dependent variable.

Victim Blame

A search of the literature produced no scales that had previously been used to relate victim blaming to revenge porn. Therefore, based on reading of the limited research available in this area, 6 statements were created for which participants rated their agreement on a scale of 1 (not at all) to 5 (completely agree), with a higher mean score indicating higher levels of victim blame: The person in the video is a victim (reverse scored); They were silly to share the material in the first place; They are a victim of a crime (reverse scored); They only have themselves to blame for what happened to them; It is not their fault that the material was subsequently shared (reverse scored); It could have been prevented, had the material not been shared in the first place. Reliability analyses showed these six items to reach an acceptable level of reliability (Cronbach’s α = .74).

In addition, participants were given a direct forced choice question of who was to blame for making the video/image public, the person in the video (victim), the person who uploaded video/image (perpetrator), or the media (e.g., website or social media) that allows such sharing (facilitator). Frequency scores were created for each response.

Video Creation

A pilot study was used to create the videos based on four scripts using real life celebrity stories of revenge porn from Rihanna, Mischa Barton, Joel Dommett and Jennifer Lawrence as they were already in the public domain. The scripts were compiled by transcribing interviews and reports in which the celebrities spoke about their experiences of being a victim of revenge porn. The scripts were counterbalanced to include important factors and make clear whether the SEM used against them had been shared with the perpetrator. One self-taken video script was used (Joel Dommett) and one self-taken image script (Rhianna). One script of a stealth-taken video that had been filmed without awareness was used (Mischa Barton), as was a stealth-taken image script (Jennifer Lawrence). All identifying information was removed from the scripts, but they did include the key factors that were being tested for this study (SEM acquisition, mode of revenge porn, and victim’s sex). In all scripts the perpetrator of the revenge porn was of the opposite sex to the victim (Appendix).

Actors. Five actors (three female and two male) aged between 18 and 30 years were recruited from various schools of performing arts and local amateur dramatics societies. Maintaining this age range was important to retain the authenticity of the stories that would be read to camera. All actors who came forward to participate were invited along to filming sessions. The actors were informed that participation in the filming was voluntary, without payment and that they could withdraw from the process at any time without explanation. It was also made clear that the actors would not be named and they were assured that all participants in the study proper would be informed that they were actors at the end of their participation. The resulting videos were also only made available to researchers involved in the project, and actors were advised that after publication of the work they would be able to use the videos for their own show reels, and that the videos would not be released to anyone else other than for replication of the current study.

Filming. The scripts were emailed to the actors prior to filming, which took place at the University of Wolverhampton by the Psychology Department Technicians. The set up included a stool in front of a blank wall with appropriate lighting and video recording equipment. This ensured consistency across all of the recordings and minimised social cues. Resulting videos were edited to an equal length of around two minutes each, with a fade in and out of reading. All actors were given a dry run and were allowed more than one attempt at reading each script. The two male and three female actors read all four scripts to camera to ensure equal processing of all actors and scripts, resulting in 20 videos being created.

Video Evaluation. The videos were uploaded to YouTube with privacy settings ensuring that they could only be seen by the researcher and users provided with the URL link. A total of 25 males and 72 females with a mean age of 38.21 years (SD = 12.49; range = 18–71 years) were recruited using a snowball method via social media to rate the 20 videos on measures of perceived attractiveness (On a scale of 1 [not at all attractive] – 5 [very attractive] how attractive would you rate the person in the video), perceived actor age (how old do you think the person in the video is?), credibility (do you think the person in the video was telling their own story?) and sincerity (do you think the person in the video was sincere?) of the actors, as well as whether participants recognised the story. The videos were accessed via links to the YouTube uploads within the online survey which was hosted on Each participant saw two videos, one male and one female of either a video or image revenge porn victim. One of the videos they saw was for self-taken SEM and the other for stealth-taken SEM. The order of presentation was completely randomised using a total of 24 combinations of the 20 videos.

Video Generation Results. The mean scores for perceived actor attractiveness (Table 1) and perceived actor age (Table 1) were reviewed to highlight which male and female actors appeared to have more similar ratings, given that one of the purposes of this study was to eliminate any actor appearance factors creating a rating bias in the main study. Female 3 presented as the most centrally scoring female actor. However, the scores for plausibility (credibility and sincerity) fell below centre, whilst female 2 yielded a more favourable consistency across scores (see Table 1). In terms of male actors, male 2 achieved more consistently central scores for age, attractiveness, sincerity and credibility from the two male actors. The perceived age range for female 2 was between 20-23 years and between 30 - 34 years for male 2. The relevant literature around victim blaming suggests that there are no significant victim age differences in apportioning blame (Davies et al., 2009), which suggested retention of these different perceived ages to be acceptable. Given these considerations, the videos for Female 2 and Male 2 were chosen as the best counterbalanced and were retained for the main study.

The final 8 videos from the two actors (Female 2 and Male 2; self-taken image and video, stealth-taken image and video) were embedded into a survey hosted on to create eight combination blocks of presentation according to a Latin Square design for the main study. This ensured that each participant viewed one male and one female victim video, each of whom were the victim of either self- or stealth-taken video or image SEM.

Table 1. Mean Scores for Pilot Study Video Evaluations. Standard Deviations in Brackets.





Story Recognition***

Actor Sincerity

Actor Credibility


SEM Acquisition











Female 1































Female 2































Female 3































Male 1































Male 2































Note. *Mean years; **mean percentage; ***mean percentage for Yes recognition; mean percentage for Yes responses.


Using a snowball sampling method, the link to the study was shared across various social media outlets. Upon clicking the link, participants were taken to the Qualtrics hosted survey and were presented with the study information and requirements, along with ethical considerations. They were informed that they could exit the study at any time by clicking on a Quit button that would appear on every page, prior to being asked to confirm consent for their participation. After providing non-identifying demographic information, participants were randomly assigned to view one male self-taken or stealth-taken image or video, and a counterbalanced female actor video (e.g., male self-taken video and female stealth-taken image or female stealth-taken video and male self-taken image). The victim blame questionnaire and direct questions of who was to blame for sharing the SEM, the originator or the sharer, were completed at the end of each of the two videos for each participant. Upon completion of their second video and questionnaires, participants were provided with debrief information and thanked for their participation.


Two scores were calculated for each video, a direct forced choice victim blaming score and a questionnaire victim blaming score. The former provides a direct overt answer to whether a victim is to blame, whereas the second provides a more indirect covert line of questioning.

Direct Victim Blame

A Chi-square test revealed a significant difference in blame attribution for the frequency of responses to the direct question of who was responsible for the act of revenge porn, χ2(N = 342, df = 3) = 529.93, p < .001. Significantly more participants reported that the person who uploaded the SEM was to blame (N = 269) than was the website (N = 42) or the person in the video (N = 31). Significantly more participants also believed that the Website was responsible (N = 42) than was the victim (N = 31), χ2(N = 73, df = 2) = 36.51, p < .001. Participants thus attributed blame to the perpetrator rather than victim or facilitator when asked directly who was to blame for the act of revenge porn.

Indirect Victim Blame

Mean scores were calculated for self-taken and stealth-taken videos and images as a function of both participant and victim sex (Table 2).

Table 2. Mean Levels of Victim Blame as a Function of Participant and Victim Sexes, and Acquisition
of SEM (SD in Brackets)









Victim Sex



Victim Sex















































































Overall Mean







A three way between groups ANOVA revealed a non-significant interaction of SEM acquisition x actor sex x mode of revenge porn, F(1,334) = 1.58, p = .210, partial η² = .005).

In line with the first hypothesis that males would engage in higher levels of victim blaming than females regardless of the mode (video or images) and acquisition (self-taken or stealth-taken) of the SEM, male participants reported significantly higher levels of blame (M = 2.43, SD = 0.80) than female participants (female M = 2.17, SD = 0.86), F(7,326) = 5.64, p < .01, partial η² = .66.

Whilst there was a significant interaction of SEM acquisition x victim sex, (F(1,334) = 4.86, p < .05, partial η² = .015), this was due to the higher levels of SEM acquisition (Hypothesis 3) rather than a significant effect of victim sex (Hypothesis 1), as evidenced by a significant main effect of SEM acquisition, F(1, 334) = 18.77, p < .001, but not of victim sex, F(1,334) = 0.03, p = .853, partial η² = .000. The second hypothesis that female victims would attract more blame than male victims regardless of mode and acquisition of SEM was therefore not supported, as the main effect of victim sex failed to reach significance, F(1,334) = 0.03, p = .853, partial η² = .000.

In line with hypothesis three, blame was higher for females when they self-taken shared SEM (M = 2.32, SD = 0.73) than when it was stealth-taken acquired (M = 2.12, SD = 0.87). Blame was also higher when men shared self-taken SEM (M = 2.53, SD = 0.98) than when it was stealth-taken (M = 1.95, SD = 0.72). An independent samples t-test also confirmed that a significantly higher level of blame was assigned to victims who had shared self-taken SEM (M = 2.42, SD = 0.87), than when it was stealth-taken (M = 2.03, SD = 0.80), t(340) = 4.29, p < .001.

Hypothesis 4 was not supported as there was no significant main effect of mode of revenge porn (Video M = 2.17, SD = 0.85; Image M = 2.28, SD = 0.86), F(1,334) = 1.81 p = .18, partial η² = .005.


The current pattern of results suggests that although participants overtly report not blaming the victim when directly asked who is to blame for the occurrence of revenge porn, the indirect line of questioning employed suggests that whether the SEM was self-taken or stealth-taken acquired does impact on their level of victim blaming, thus demonstrating a non-conscious cognitive bias in attributing victim blame. Participants were more likely to blame a victim if they had initially self-taken and shared the SEM with the perpetrator, regardless of whether the SEM was image or video-based, and regardless of victim sex. This is in line with Lerner’s (1980) just world hypothesis, and with Petherick’s (2017; see also Schafer, 1968) outline of precipitation theory. In this instance, it might be the case that the victims are not necessarily seen as innocent and good, but as receiving blame because they enticed or initiated the act of revenge porn against them. In other words, participants may have believed that if a person created and/or shared SEM in the first place, it is their own fault that it is subsequently used against them in an act of revenge porn. This supposition not only fits with Weekes and Wesson’s (2017) observation that people are often perceived to be irresponsible for creating and/or storing SEM on their devices in the first place. Victim blame when SEM is self-taken may however be modified by where or on what platform the self-taken SEM is held, both before and after sharing with a perpetrator. If saved on a non-password protected phone, for example, people might be more likely to apportion blame than if the SEM is saved in a password protected file on a password protected computer, which is also in line with the self-protective blaming of rape victims observed by D. L. Burt and DeMello (2003), whereby victims similar to oneself are blamed less than those dissimilar to oneself. In line with previous rape myth studies (e.g., D. L. Burt & DeMello, 2003), males apportioned more blame to victims. This is contrary to what might be expected given the recent surge in public awareness campaigns such as #itstillmatters and #weseeyou which highlight that both males and females can fall victim to both online and offline sexual crimes. This awareness may also go some way to elucidating the absence of a significant difference in blaming men and women victims as was predicted by hypothesis two.

Although much previous work has noted this gender bias in blaming victims of sexually related crimes (e.g., McCaul et al., 1990; Schneider et al., 1994), most studies have hitherto used fictional vignettes and hypothetical cases. We consider the current use of portrayals of real-life occurrences of revenge porn in the carefully created video accounts to have provided more authenticity than those fictional scenarios, thus affording a greater level of ecological validity. Nonetheless, further use of these and similar videos would establish whether the non-significant gender biases prevail in revenge porn victim blaming. Moreover, whilst this work tested Gavin and Scott’s (2019) suggestion that gender differences might occur for self-taken rather than stealth-taken SEM, it did not explicitly test the notion that implicit trust and agreement of the destruction of self-taken SEM could lead to heightened levels of victim blame. This remains a consideration for future research, as does a further exploration of whether people are more likely to blame female victims whilst minimising the risk and fallout for male victims of revenge porn as suggested by Gavin and Scott’s (2019) work. If people are persuaded by reports in the mass media and are prone to blaming victims dissimilar to themselves (Grubb & Turner, 2012), given our current sample of more females than males, we might have expected the result to favour female victims and blame male victims more. This suggestion could be further expected given the prominence of female revenge porn cases reported in the mass media. It may also simply be a case that generally, when people think of sex crime victims, that they are more prone to think of women as victims rather than males (Bothamley & Tully, 2017) despite statistics indicating that men and women are equally likely to be victims of revenge porn (Henry et al., 2017). Whilst Gavin and Scott’s findings suggest there to be such a difference, the current findings do not. This discrepancy could possibly be due to the videos used, that this study focused on both self-taken and stealth-taken images and videos, or in there being a difference in how males and females experience being a victim of revenge porn, with males often being assigned a macho-style reputation when their sex tapes and images are leaked online (Gavin & Scott, 2019). Alternatively, females may simply be more likely to have engaged in defensive attributions (Shaver, 1970), identifying more with female participants. If this was the case, however, we would also have expected to see a higher level of victim blaming for the male than the female victims, especially given the larger sample size of females in the current study. There is clearly a discrepancy amongst the limited research available in terms of clarifying the gender roles in revenge porn victim blame. Where work is available, it has considered a raft of different types of digitally-mediated sexual misconduct rather than focusing specifically on revenge porn (e.g., Eaton & McGlynn, 2020), has focused specifically on images (e.g., Zvi & Schechory-Bitton, 2020), or has used self-reported views and opinions in response to vignette-based studies (e.g., Bothamley & Tully, 2017). Further research is thus tasked with finding a more parsimonious account of blame for male and female victims which also considers the impact of both the #metoo and #himtoo movements (Banet-Weiser, 2021) in a possible replication of the novel video-based approach adopted here to relay real victim accounts of revenge porn. In doing so, it might also consider whether the current male (76) to female (266) ratio could have influenced the current pattern of findings. Whilst there is no statistical evidence in the current study to suggest that this may have caused a bias in the results, it is a limitation common of much research where participants self-select to take part that more females than males often contribute to the work.

That participants overwhelmingly blame the perpetrator when directly questioned for the outlined acts of revenge porn is in line with an external attribution (Heider, 1958) of the victims not being to blame for something that happened outside of their control. The current work was not focused on establishing tools for direct and indirect questioning of participants on their levels of victim blame. It does however provide a good step towards understanding factors that may affect attributions of blame. For example, the current study although implying a direct and indirect questioning difference synonymous with performance of a cognitive bias, did not explore whether participants put themselves into the position of either victim or perpetrator. If, for instance, a participant has been a victim of any form of revenge porn, then asking them directly about this could have instigated a firm shift of blame to the perpetrator. More indirect questioning may, however, evoke some sense of self-blame that directs their responses. Clearly, further work is needed to unpack these intricate differences and establish what role personal experience and self-blame play in assigning victim blame for any type of revenge porn. Whilst Scott and Gavin (2017) observed that people with no experience of sexting were more likely to blame revenge porn victims, their study did not offer comparisons of blame for the sharing of video compared to image-based SEM. Nor did it ascertain whether being a victim oneself of revenge porn would impact on levels of victim blame. As the current study did not explicitly test the emergence of sexting and social acceptance as a contributor to either promoting or eroding levels of victim blaming in instances of revenge porn, future work to consider this more in relation to Scott and Gavin’s (2017) observations would help our current understanding of the role of participant experiences in attributions of blame in technologically mediated sexual violence. Thus, establishing whether participants themselves are active sexters, have fallen victim to revenge porn or even committed an act of revenge porn, are all factors that should be considered in future work. These considerations also link to a limitation of the current work, in that it did not consider whether victims were perceived to have adhered to social norms, behaved independently, or had in fact felt pressured to share the SEM which was subsequently used for the revenge porn. The aim of the current study was to relay the victim accounts with as much accuracy and detail as possible. As none of the victim reports included an outline of whether peer pressure, abusive pressure or adhering to social normative behaviours was a factor, it was felt that including these would confound the clearly counterbalanced reports. That is not to say that such factors may have been at play in the victim stories relayed, but to draw any conclusions about these would be erroneous and should be focused on in future work.

It was also hypothesised that participants would be more likely to blame individuals who partook in videoed SEM than imaged SEM, especially in the self-taken condition, given that previous work has shown that people in videos are often rated as showing some level of enjoyment from their sexual activities (Flood, 2009). Regardless of whether the SEM was self- or stealth-taken, participants may have perceived victims to have willingly partook in the sexual conduct shown. Whilst every effort was made to provide actor-relayed counterbalanced accounts of the revenge porn experiences, actors’ expressions of hurt, embarrassment, anger or other emotions were not controlled for in the current videos. Previous work has shown that videos do offer a more human, empathetic, and realistic presentation (e.g., Sleed et al., 2002) than do vignettes, suggesting that the use of videos on this occasion was a good methodological decision. It might, however, be useful to ensure that levels of enjoyment for partaking in, and control over SEM be more fully considered and counterbalanced in future work. It could also be argued that participants were less likely to pay attention to the video reports than they might have done had they had to read the reports. It might be the case that they were not able to empathise with the victims from the video representations, or that they did not find these as real as they might have a written account. Future work therefore also needs to compare levels of victim blaming for written and videoed reports to establish whether this did indeed present a confounding factor in the current study. This would also control for any judgements made by participants about the actors’ appearances. Whilst every effort was taken to ensure that the male and female actors were counterbalanced on all factors considered important, there does remain a risk that participants may have used social cues available in the videos to determine their responses. A comparison of vignette and videoed recounts of victims’ stories would eliminate these factors. It is also worth noting that participants’ other conscious and unconscious biases might also have influenced how participants perceived the actors and the levels of blame assigned. Moreover, viewing the videos may have been triggering for some participants, or may have evoked a sense of anger or frustration against the offender (e.g., Zvi & Schechory-Bitton, 2020), or even against the victim for sharing SEM in the first place. It might however be the case that participants over-empathised with victims (e.g., Zvi & Schechory-Bitton, 2020). Future research is tasked with exploring this further, for example, by possibly exploring what participants actually feel themselves and in relation to the victims and/or offenders. Ascertaining whether levels of education in general and more specifically around the legalities of sharing SEM influences levels of victim blame might also elucidate whether knowledge, feelings, and emotions impact victim blame. Alongside unconscious racial biases and stereotypical judgements of appearance, other factors for consideration that might play into levels of victim blame is one’s own religious beliefs. Those who consider themselves devout to their chosen religion that exemplifies moralistic behaviour might, for example, be more likely to victim blame than those engaged in more pluralistic religious beliefs.

In addition to the limitations and directions for future research already noted, it is also worth noting a case for future work to evidence the just world hypothesis more explicitly. Participants in the current study were unfortunately not questioned directly about this processing bias which would form an excellent basis for future research.

Concluding Comments

This study used carefully created stimuli to recount real stories of revenge porn. In doing so, it tested whether people were more likely to blame female than male revenge porn victims when they had willingly shared imaged or videoed SEM or when it had been acquired without their knowledge. Although there were a number of non-significant findings, the study did highlight that when directly asked, participants were more likely to blame a perpetrator of revenge porn than a victim thereof for its occurrence. However, in a more indirect line of questioning, not only were males more likely to blame people for falling victim of revenge porn, but participants were also more likely to blame a victim who had initially shared the SEM than when it had been stealth-taken. These findings are considered important because they highlight that whilst a person may believe themselves to be less judgemental towards a revenge porn victim, certain factors and processing biases could sway their attributions of blame. The findings are indicative of a just world hypothesis, but future research needs to consider this in more detail. Given the newness of revenge porn and a dearth of relevant research that considers the occurrence of revenge porn for both images and videos of SEM, this work contributes to current understanding of the role of victim blaming in this area of technology mediated sex abuse for real life events rather than for fictional or hypothetical cases.


Scripts learned and recited to camera for the four counts of revenge porn.

Video Self-Taken

Recently, after being a relative recluse sexually for my entire life, with the exception of the odd drunken experience, after a stupid error on my part there is now a video of my private parts on the Internet.
I was Cat fished a long time ago by somebody pretending to be somebody else on the Internet and was lured into explicit Skype sex.
I thought I knew who I was skyping and that we had a mutual relationship and I trusted them, I thought the acts I performed were for their eyes only.
It turns out the Skype sessions were entirely fake, the other person was not who I believed and it has now come back to bite me after a cruel troll released the footage on the Internet. 
It’s a genuinely horrific thing for another human being to do, to take advantage of what is private and make it public for everyone to see.  Some people do not know where to draw the line.
Pictures of my private parts and a video were released on the Internet for everyone to see, my family, my friends, even my mom!
I didn’t know what to do, I was horrified and tried to limit the damage by posting a message to everyone to make a joke of the situation – what could I say or do?
For any individuals who have suffered the same cruel fate as me, I can only reassure you that you will recover in time, no matter how embarrassing.  There is a lot of help out there for you.
This is a new type of crime and it's not just happening to the rich and famous.

Video Stealth-Taken

I wanted to share my story to help protect others from going through the same pain and humiliation that I did.
I have been put through an incredibly hard and trying time. This is a painful situation and my absolute worst fear was realised when I learned that someone I thought I loved and trusted was filming my most intimate and private moments without my consent, with hidden cameras.
I learned something even worse – that someone is trying to sell these videos and make them public!
I came forward to fight this, not only for myself but also for all the men and women out there. I want to protect them from the pain and humiliation that I have had to go through. No one should have to go through this.
It has been a horrific experience, it’s a hard thing to do, but I am glad that I am finally standing up for myself!
The videos were made without my consent or knowledge – it’s a form of domestic abuse! There’s a name for this disgusting conduct I know now that: Revenge pornography is a form of sexual assault, and it is also a crime!
The footage was shot within the last 12 months during which time I was in what I believed to be a loving and trusting relationship with my partner.
Everyone has the right   to choose what images or videos of our own body will be made public; no one has the right to exploit another for revenge or financial gain.
Revenge porn is a very common crime, for all, not just the rich and famous … it’s scary to stand up like this, but it’s important for everyone to stand up for

Image Stealth-Taken

Recently my apple iCloud account was hacked and sexually explicit pictures of my self were leaked online – there for everyone to see.
I was devastated and didn’t know what to say to anyone I knew.  My family and friends could see my nude pictures.
At first I just couldn’t say anything, I mean what could you say? Every single thing that I tried to write or say made me cry or get angry. And even if I wasn’t in a loving, healthy, trusting relationship, even if the photos were just for my own enjoyment, hacking my account and leaking my private pictures is a crime. It is a sex crime. It is a sexual violation. It’s disgusting!  I thought it just happened to the rich and famous!
Even people who I know and love say: “Oh, yeah, I looked at the pictures.” I don’t want to get mad, but at the same time I’m thinking, I didn’t tell you that you could look at my naked body. I am moving on, time does heal, you know. I’m not crying about it anymore. I can’t be angry any more. When I had to make that phone call to my dad and tell him what happened… Fortunately, he was playing golf, so he was in a good mood

Image Self-Taken

A couple of years ago, after splitting up from my ex, I woke up to find nude images, that I had sent them of me had been leaked onto the Internet.
My ex denied all allegations of responsibility, but I hadn’t shared these images with anyone else.  We were in an exclusive loving and trusting relationship.
I was so shocked and embarrassed, all my family and friends saw these images and they were quite explicit.  I didn’t know how to face my nearest and dearest.
I remember one of the first things I did was to send my mother flowers.  What was I going to say to her?
I was just so shocked and couldn’t believe this could happen to me!  I thought it only happened to the rich and famous! I was freaked out; it was the worst thing that could possibly ever happen.
I just felt like my whole privacy was taken from me, when those pictures came out!   I thought, oh great, so now there’s nothing my family and friends don’t know about me.
In these pictures I was stood in a bathroom with my face halfway covered, but you could tell it was me.  Everyone one could see my private parts! It was humiliating and it was embarrassing especially my mom having to see thatThe pictures were only ever meant for my ex who was my partner at the time; I never dreamed they would be flashed all over the Internet like that.





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