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Victims of Child Grooming: An Evaluation in University Students

Patricia Alonso-Ruido
Iris Estévez
Bibiana Regueiro
Cristina Varela-Portela
Department of Pedagogy and Didactics, University of Santiago de Compostela, 15782 A Coruña, Spain
Author to whom correspondence should be addressed.
Societies 2024, 14(1), 7;
Submission received: 4 December 2023 / Revised: 31 December 2023 / Accepted: 4 January 2024 / Published: 9 January 2024


The appearance of new ways of committing sexual violence via technological media and virtual spaces has produced countless situations where sexual abuse of minors may occur. This is the digital scenario surrounding the phenomenon of grooming. The present study focuses on analyzing grooming experienced by Spanish university students during childhood. The sample comprised 3293 students in higher education, 68.3% of whom were female, 30.5% were male, and 1.2% identified as non-binary. The mean age was 18.83 years (SD = 2.28). The results confirmed that sexual abuse of minors has moved towards virtual environments, indicating a prevalence of 12.2% for grooming, which was more likely to have affected women and non-binary people. In addition, student victims of grooming were more often also victims of sextortion. Consumption of pornography was also shown to be particularly important, with the results indicating that students who consumed it and started consuming it before they were 16 years old were more often victims of grooming. These findings should encourage the educational community to develop preventive actions that match the reality of online child sexual abuse. In summary, the only path towards preventing and detecting grooming is to invest in high-quality digital education and sex education from a gender perspective.

1. Introduction

Child sexual abuse is one of the most concerning aspects of child mistreatment, given its grave physical and psycho-emotional consequences for the youngest members of society [1,2]. It covers a range of behaviors or sexual interactions with children, perpetrated using threats, deception, intimidation, or the use of force [3].
International treaties have defined child sexual abuse as a violation of the rights of the child, specifically in Articles 19 and 34 of the Convention on the Rights of the Child [4] and Article 24 of the Charter of Fundamental Rights of the European Union [5]. The EU has also expressed its concerns about this type of mistreatment with the recent approval of Directive 2011/93 [6] about the fight against child pornography, sexual exploitation, and other forms of sexual abuse. This is a struggle that falls within the Sustainable Development Goals [7], as SDG16 explicitly notes the need to eliminate all forms of violence and mistreatment during childhood.
Despite efforts to raise awareness of this mistreatment, there are certain socially shared beliefs about sexual abuse that make it hard to detect. For example, people tend to believe that it only refers to sexual practices that include penetration or that it only involves isolated cases and does not happen to those around us [8]. Nothing could be further from the truth in the light of empirical evidence. At an international level, the prevalence of being a victim of sexual abuse is 7.5% [9]. In Spain, the figure is between 2 and 18.5% [1,2]. These results are no trifling matter, particularly due to the physical, behavioral, and psychosocial consequences in the lives of the children affected [10]. Sexual abuse during childhood involves a wide range of behaviors that fall under a power imbalance in terms of victims’ maturity or age [11]. This range of strategies or possibilities for sexual abuse does not exclude virtual environments. Bearing in mind that societies are increasingly digital and that the use of ICRT (Information, Communication, and Relationship Technologies) [12] is widespread among young people in the context of “cyber-relationships” [13], it is no surprise that child sexual abuse has moved online [14].
The first study of online sexual abuse behaviors was conducted more than ten years ago and identified “unwanted sexual solicitations online” [15] as one of its manifestations. This raised awareness of the experiences of being the victim of digital sexual abuse through sexual advances from adults. However, technological media and virtual spaces are providing more—and more dangerous—spaces in a framework of sexual violence, especially given the anonymity offered by social networks. These virtual spaces facilitate sexual aggressors’ contact with children and make it easier to have sexual conversations with them and sexually harass them [16]. Even sexual abuse that occurs or starts offline has a digital component, for example, through messaging apps that help abusers contact their victims more privately [17].
The methods that abusers use to contact and perpetrate sexual abuse have become more devious. It is no longer through intimidation or direct contact but is now through building close, friendly relationships that hide the sexual goal [18]. This is called grooming.

1.1. Theoretical Background: What Do We Know about Grooming?

There are various terms for referring to online sexual contact, communication, and extortion of children, but grooming is the most common [19]. This behavior occurs through a process in which an adult manipulates the child and builds a relationship of trust with sexual intentions. In an attempt to illuminate the conceptualization of the phenomenon, [20] noted various points that should be included in the current definition of grooming. They indicated that any definition of grooming needed to specify that grooming involved sexual preparation that was a process (not exclusively conscious) of deceptive “steps” with the goal of committing child sexual abuse. It should also include a broad view of “sexual preparation” that may also occur after the initial abuse, facilitating further abuse or avoiding discovery. This holistic view of the phenomenon must avoid indicating specific behaviors, not blame the victims, and include a broad range of grooming offenders in its terminology [20]. This conceptualization emphasizes how grooming involves different stages that go from making friends up to where there is sexual behavior online between victim and perpetrator [21]. In this regard, the model of sexual grooming has recently been validated [22], which outlines five phases of the process: (1) victim selection, (2) gaining access and isolating the victim from their surroundings, (3) developing a climate of trust, (4) desensitizing the victim to sexual content and physical contact, and (5) maintaining the relationship following the abuse.
The qualitative narrative is very revealing with regard to the definition of these phases. Initial persuasion involves using language that is closer to how children speak; obtaining information focuses on all aspects of a victim’s life, particularly collecting data about experience of previous mistreatment or simply the gaps in the family system; and the strategies used involve deception, bribery, and emotional manipulation [23]. Nonetheless, there seems to be some difference of opinion about the strategies used by sexual aggressors to involve children in sexual activities online. According to the results from Broome et al. [24], this type of online sexual exploitation may occur without deception when aggressors use discursive strategies with a positive tone (e.g., flattering the victims). Other studies have also identified pressure as the most common strategy [25] or the escalation of threats [26].
This shows how the perverse seduction dynamic of grooming involves parallel strategies of sextortion [3]. Once aggressors have established an online relationship, they threaten their victims with spreading sexual material they already have in order to obtain more sexual content or to perpetrate more sexual abuse [27]. This process shows how sexual abusers mask their intentions under ordinary behaviors to avoid detection [28]. They even sometimes use technological devices that allow them to share sexual abuse or aggression with other abusers [29] and produce child pornography [30]. The ultimate aim of the sexual abuser is to commit sexual abuse, although groomers mask this with a range of varied behaviors. On the one hand, there are sexual abusers who adapt their identity to the characteristics of the child; others seek “romantic” or “intimate” long-term relationships; and at the other extreme, some are driven by their sexual impulses and seek to satisfy them immediately [29].
The different profiles of online sexual abusers show that they can be known or unknown to the victim [20], but are generally male [31]. There also seems to be a certain amount of “repeat offending” in grooming behaviors, as perpetrators have abused various children online [32].
The victims are mostly girls [31,33]. This does not mean that boys are not victims of abuse, especially those who identify with a different sexual orientation [18]. The age range of potential victims is difficult to identify because children are starting to use smartphones at increasingly early ages [34].
Paradoxically, the risk of grooming is occasionally overlooked by the younger generation, who were born and grew up with constant access to technology and the internet. They consider online spaces to be a natural place for social interaction, which may produce a low perception of risk or a certain naivete about the risks of sexual behaviors that may lead to them blithely sharing personal information online [35]. This may mean they assume it is easy to detect what they call a “dirty old man” under the narcissistic perception that “it won’t happen to me” [18]. Despite these perceptions, grooming is not an isolated event in children’s lives, and the prevalence rates show that.
Despite the difficulties of detecting grooming [36], the literature reports rates of being a victim at around 23% [37]. More specifically, the meta-analysis by Madigan et al. [38] indicated rates of 11.5% for unwanted sexual solicitations and 20.3% for unwanted exposure to sexually explicit material.
In Spain, being a victim of grooming was already one of parents’ most pressing concerns as far back as 2011 [39]. The first empirical evidence suggested that 9% of children aged 11 to 16 had received sexual messages online [40]. Subsequent studies examined types of grooming and noted a prevalence of 6% for online sexual harassment and 8.4% for online sexual solicitation [41]. The study by Villacampa and Gómez [42] reported that 5% of Spanish adolescents had received requests to talk about sex, and almost 3% had been asked to perform sexual acts. Qualitative research has been particularly important, showing that sexual interactions transcend the virtual and occur both online (exchanging sexual content) and offline (sexual meetups) [23].
More recently, research has indicated that around 13–17% of Spanish youth have received sexual solicitations online from adults to which they had responded or interacted with when they were minors [43]. The longitudinal study by Ortega-Baron et al. [44] highlighted the variety in prevalence, identifying ranges of 4–7% for sexualized interactions to 11–16% for sexual solicitations children received online.
Given the threat grooming poses to young people’s lives, we need to bear in mind that it is not an isolated risk. Research has linked various high-risk online behaviors and established common points between grooming, sexting, and the consumption of pornography [45,46].

1.2. The Present Study

The evidence in the specialist literature indicates the urgent need to examine and expand our knowledge of the phenomenon with a rigorous, systematic, and thorough approach. In consequence, the overall objective of the present study is to analyze Galician university students’ experiences of grooming during childhood and adolescence. This objective was subdivided into the following objectives: (a) evaluate the prevalence of grooming in university students’ life histories; and (b) analyze the differences in being victims of grooming based on student gender, experience of sextortion, consumption of pornography, and age at which consumption of this type of online sexual material began.
In line with those objectives, this study followed an empirical–analytical perspective and was quantitative in nature. The starting point was a cross-sectional design, given that the data were collected at a single time point. It applied a descriptive-correlational design, taking into account the nature of the objectives set.

2. Materials and Methods

2.1. Participants

A total of 3293 students from the University of Santiago de Compostela-USC (Spain) participated in this study. They were in the first or second years of undergraduate degree courses in the five knowledge areas (social and legal sciences; health science; science; engineering and architecture; and arts and humanities). Just over two-thirds (68.3%, n = 2249) of the sample identified as female, 30.5% (n = 1004) identified as male, and 1.2% (n = 40) identified as non-binary. The sampling was non-probabilistic and intentional. The first- and second-year degree courses were selected. Our aim was to select the youngest within the university population that had reached its majority (according to national legislation). Looking at the most recent data about the USC student population (the 2019–2020 academic year), there were a total of 19,060 students seeking undergraduate degrees. The questionnaires were administered at 21 out of a total of 23 college sites. This means that the present study reached 17% (n = 3293) of the undergraduate students, with the participation of 91.30% of the college sites, and consequently is representative of the context under study.
It is worth bearing in mind that one of the objects of this study (grooming) refers to sexual abuse suffered during childhood and adolescence. This means that the participants in the first and second years of university are the adults who might have suffered this abuse most recently.
The mean age of the sample was 18.83 years (SD = 2.28; Min. = 18; Max. = 56), and 94.4% of the sample were between 17 and 21 years old. The distribution by course year was 1st year (60.2%, n = 1984) and 2nd year (39.8%, n = 1309).

2.2. Instrument

Information was collected using a questionnaire, given the nature of the topic being studied and the fact that this study followed a quantitative design. We selected the Questionnaire for Online Sexual Solicitation and Interaction with Adults (QOSSIA), as it has demonstrated suitable psychometric indices [47]. This 10-item questionnaire has a two-dimensional factorial structure: (a) sexual solicitations (e.g., an adult asked me for pictures or videos of myself with sexual content) and (b) sexual interactions (e.g., I have maintained a flirtatious relationship with an adult online). Responses are given on a Likert-type scale from 0 (never) to 3 (6 or more times). The original instrument was validated with a sample of Spanish adolescents, who were asked to respond to the items by thinking about whether they had experienced the situations the items described “when they were minors”. Bearing this in mind and based on the principle of research rigor, we analyzed validity (via exploratory factorial analysis) and reliability (by calculating Cronbach’s alpha) to determine how much the psychometric properties were replicated in the university sample. Kaiser–Meyer–Olkin’s measure of sampling adequacy was 0.90, and Bartlett’s test of sphericity, χ²(45) = 16,367, p < 0.001, indicated that correlations between items were sufficiently large for factor analyses. Subsequently, principal component extraction with Varimax rotation (Kaiser normalization) produced two factors that reproduced the structure of the scale. Both factors together explained 65.02% of the variance. Following that, we analyzed the reliability of the two factors, which produced suitable indices of internal consistency: Factor 1—sexual solicitations (α = 0.877) and Factor 2—sexual interactions (α = 0.814).
In addition, the questionnaire included various yes/no questions created for this study to evaluate being a victim of grooming (when you were young, did an adult ever deceive you with a fake profile to make sexual or intimate requests through social media?), sextortion (have you ever been the victim of pressure, threats, or extortion before or after sexting (sextortion)?), and consumption of pornography (do you consume or have you ever consumed pornography? How old were you when you first consumed pornographic material?).

2.3. Procedure

Data collection followed a standard process. Once approval for this study had been granted by the Bioethics Committee at the University of Santiago de Compostela, the various university sites (on two university campuses) were asked to participate in order to be sufficiently representative of the five knowledge areas and the degree courses in each one. Direct contact was then made with the teachers of the various courses offered by USC, asking them to collaborate and agree on sessions to administer the instrument—giving part of their class time to that end. Various members of the research team were sent to the classrooms to apply the scale in group sessions. Those responsible for the data collection were present during the sessions to inform participants of the study objectives and the voluntary nature of participation, emphasizing data confidentiality and participant anonymity. In addition, they verified proper completion of the instrument and offered help where needed, and they also underscored the importance of answering honestly. Students were free to participate by completing the questionnaire or not; it was entirely voluntary. They were also provided with fundamental data about this study, such as the objectives, financing, the researchers involved, and any other issues suggested by the Bioethics Committee supervising this study.
The questionnaire took about ten minutes to complete and was completed in appropriate conditions (without significant distractions). The instrument was administered digitally, using the university’s (Microsoft 365) Forms platform.

2.4. Data Analysis

This study followed a quantitative, descriptive-correlational design research methodology. Consequently, we undertook numerical and statistical treatment of the data.
The initial analysis was to assess the scale’s psychometric properties. Subsequently, the variables associated with the two factors making up the grooming scale were constructed. This was followed by a descriptive analysis of the newly constructed variables and an analysis of differences in means in response to the study objectives. Following that, post hoc tests were performed using Sheffé’s test, and the partial eta-squared coefficient (ηp2) was used to determine the effect size. Interpretation was based on Cohen’s (1988) criteria, indicating a small effect when ηp2 = 0.01 (d = 0.20), a moderate effect when ηp2 = 0.059 (d = 0.50), and a large effect when ηp2 = 0.138 (d = 0.80). Analysis of variance (ANOVA) and Student’s t test used the following as independent variables: gender, violence by sextortion, consumption of pornography, and age at which consumption of pornography began. The dependent variables were the two grooming-related factors (FI: sexual solicitations and F2: sexual interactions). In the analysis of the difference of means, compliance with the principle of homoscedasticity was assessed using Levene’s statistic. Where the significance of the statistic prevented verification of the supposition of homogeneity of variance, we used robust Brown–Forsythe (F*) or (t*) tests, and subsequently, Games-Howell post hoc tests.

3. Results

3.1. Preliminary Descriptive Analysis

The exploratory-descriptive results from the preliminary analysis are given below. They indicate that 12.2% of the sample had been a victim of grooming. This means a total of 401 people: 321 girls, 73 boys, and 7 non-binary participants (Table 1). There were statistically significant percentage differences by gender. Women and non-binary people were more commonly victims of grooming (Pearson Chi-squared = 32.97, df-2, p < 0.001).

3.2. Being a Victim of Grooming as a Function of Gender

Looking more deeply into the analysis of this phenomenon in the university population, we made an operational differentiation between sexual solicitations online and sexual interactions online, according to the factorial structure of the scale. The mean scores in both variables were low (sexual solicitations: M = 0.34; SD = 0.60; Min. = 0; Max. = 3; sexual interactions: M = 0.21; SD = 0.45; Min. = 0; Max. = 3). However, there were statistically significant differences by gender in the variable sexual solicitations (F*(2, 73) = 29.02; p < 0.001; ηp2 = 0.026; d = 0.20, with a small effect). Looking at the results from the post hoc Games-Howell tests, girls (M = 0.40; SD = 0.6; Min. = 0; Max. = 3) and non-binary people (M = 0.56; SD = 0.86) reported having experienced sexual requests online from adults more commonly than boys (M = 0.19; SD = 0.51; Min. = 0; Max. = 3). No statistically significant differences by gender were found for the sexual interaction factor.

3.3. Co-Occurrence of Being a Victim of Grooming and Extortion

Another objective of our study was to analyze the co-occurrence of grooming and sextortion in order to assess whether the students had been victims of pressure, blackmail, or extortion after sexting (sextortion). It is worth noting first that 7.2% (n = 238) of the participants had been victims of sextortion at some point in their lives. We examined whether there were differences in being the victims of grooming based on having experienced sextortion. The results indicated that there were statistically significant differences both in sexual solicitations online from adults (t (3198, 249) = 12.83; p < 0.001; d = 1.25; with a large effect) and in sexual interactions online (t*(3170, 243) = 7.36; p < 0.001; d = 0.74; with a moderate effect). In both cases, the mean scores from those who had experienced sextortion were higher (sexual solicitations: Yes (M = 0.99; SD = 0.28; Min. = 0; Max. = 3); No (M = 0.29; SD = 0.54; Min. = 0; Max. = 3)) than those who had not (sexual interactions: Yes (M = 0.51; SD = 0.65; Min. = 0; Max. = 3; No (M = 0.18; SD = 0.42; Min. = 0; Max. = 3)) (see Figure 1).

3.4. Analysis of the Relationship between Grooming and Consumption of Pornography

The first thing to note in the results relating to the final study objective is that 51.9% (n = 1708) of the sample consumed or had consumed pornography, whereas 46.8% (n = 1542) of the students reported not having consumed pornography. In addition, as Table 2 shows, consumption of pornography was significantly higher in men and non-binary people than in women (Pearson Chi-squared = 710.181; df-2, p < 0.001).
The mean age at which pornography consumption began was 14.49 years old (SD=1.98), with a minimum of 6 and a maximum of 21.
Analysis of differences in means showed that there were statistically significant differences in being a victim of grooming as a function of consuming (or not consuming) pornography, both in having received sexual solicitations (t* (3193, 3171) = 3.14; p < 0.005; d = 0.11; with a small effect) and in having had sexual interactions online (t* (3166, 2927) = 8.18; p < 0.001; d = 0.286; with a small effect). The mean score in relation to sexual solicitations in those who consumed or had consumed pornography was M = 0.36 (SD = 0.64; Min. = 0; Max. = 3) compared to a mean of M = 0.30 (SD = 0.53; Min. = 0; Max. = 3) from those who had not. For the variable sexual interactions, the mean score from the group who had consumed pornography was M = 0.27 (SD = 0.51; Min. = 0; Max. = 3), and from those who had not used this type of virtual space, it was M = 0.14 (SD = 0.35; Min. = 0; Max. = 3).
Finally, we analyzed the relationship between being a victim of grooming (sexual solicitations and interactions as dependent variables) and the age at which consumption of pornography began (control variable). To analyze this, we recoded the control variable, producing a dichotomous variable: under-16 (group 1: n = 1032) and 16-and-over (group 2: n = 645). The reason for this cut-off point is that the age of sexual consent in Spanish and European law is 16 (Código Penal, 1996).
The results indicate statistically significant differences in the frequency of sexual interactions (t* 1675, 1518) = 3.80; p < 0.001; d = 0.18; with a small effect) based on the age people began to consume pornography. Those who had contact with audio–visual sexual material at an earlier age (under-16: M = 0.30 (SD = 0.57; Min. = 0; Max. = 3); at 16 and over: M = 0.21 (SD = 0.41; Min. = 0; Max. = 3)) reported having suffered from grooming more. There were no statistically significant differences in the sexual solicitations factor, although the pattern was the same (under 16: M = 0.39 (SD = 0.68; Min. = 0; Max. = 3); at 16 and over: M = 0.34 (SD = 0.58; Min. = 0; Max. = 3)).

4. Discussion

Over recent years, research about child sexual abuse has increased due to it being one of the most serious forms of child mistreatment. Nevertheless, one reason why grooming has still not received sufficient academic attention may lie in the difficulty in identifying all the variables involved [20], a fundamental issue for the prevention and detection of sexual abuse. The results of our study are in line with the most alarming research results indicating that child sexual abuse is a serious global problem [36], bearing in mind that the anonymity of social networks gives cover to groomers and allows sexual abusers to manipulate children or subject them to sextortion from an early age. This not only involves online abuse but may extend to physical meetings that may allow sexual abuse to occur. The seriousness of grooming is that “it may escalate and be a precursor to other types of more serious offences such as human trafficking, child sexual exploitation, and child pornography” [48].
It is important to note that more than 12% of the university students in our study have been victims of grooming, a slightly lower percentage than from previous research [43], albeit somewhat higher for women and non-binary people. This trend indicates, once again, that girls are more often the victims, especially when it comes to online sexual solicitation, something that national [49] and international research [31] confirms. Therefore, boys may be perpetrators of online advances, as indicated by previous research [50]. However, it is important to note that boys can also be susceptible to this type of aggression, as they are more likely to take risks, often have more open, exposed attitudes, and find it more fun than girls to interact with strangers online [51,52].
Nonetheless, gender differences among students were not the only risk factor. Another point was that being a victim of grooming increases the likelihood that someone has suffered from sextortion. The relationship between the variables of grooming and sextortion shows the blurred line between the two [45]. This is because the dynamic of seduction that is involved in grooming involves parallel strategies of sextortion. Given that experiencing grooming seriously affects all areas of life, the finding that people could also be victims of sextortion makes the situation worse and confirms that technological media and virtual spaces allow increasing numbers of strategies for sexual violence [52]. Along these lines, a recent theoretical review confirmed that the Internet increases accessibility to and isolation of the victims of these types of situations [17].
As our results show, online offenses occur in a wide range of forms: unwanted sexual solicitation, taking and sharing sexual images without consent, and even sexual harassment online. But in contrast to what one might suspect initially—as the narratives around online risks often emphasize the strangers people encounter online—most of the offenders are known to the victim [20]. This leads to the risk of the messaging in this framework, as it may fail in its attempts at protection if it does not give a complete account of the nature of the problem. In this regard, both young people and parents may not be sensitive to the risks if they are only warned about strangers and adults. They may not be aware of the true dynamics of being victims and may not notice the warning signs. Education should warn and train people about behaviors that are inappropriate from any source, rather than focusing on certain types of people [53,54].
Another interesting finding linked to the need to invest in teaching to prevent online sexual abuse is that more than half of the sample consumes or has consumed pornography. That consumption was significantly higher in men and non-binary people than in women. This underscores the urgency of providing sex and emotional education to university students [55] as a protective factor against grooming. This is particularly true in light of our data indicating that young people who consumed pornography (beginning at a mean age of 14.49 years old) reported more sexual interactions. This is alarming given one of our critical findings, showing that consumption of pornography was associated with being a victim of grooming. Age is not an unimportant issue, as students who began to consume pornography at earlier ages (before they were 16 years old) reported having experienced more violence via grooming. This is an important finding, especially considering the data pointing to the normalization of pornography consumption—from increasingly earlier ages—and its consequences [56].
Based on this, there is an unquestionable need for more research about the phenomenon of grooming, which is still a novel line of research from a psychological perspective [47] or from the study of internet-related risks [57], leaving aside the educational community (teachers and family) and the importance of parental supervision [58]. Hence, as Montiel et al. [18] noted, it is essential to study the current aspects of the phenomenon in order to be able to establish a complete theoretical–empirical framework to serve as a guide to proper intervention. This should always come from a gender-based perspective [59]. It is worth noting that grooming is a growing social problem, and this should underscore the critical importance of being aware of it and proposing solutions that can help children and young adults learn about the prevention and safe use of ICRT [60]. This is especially true, considering our results that point to a triad of dangers based on being a victim of grooming, harassment produced by sextortion, and the dangerous consumption of pornography. The action framework therefore revolves around education, with the educational community playing a key role.
Despite the contribution this study makes to research about the phenomenon of grooming and its associated variables, it would be interesting to undertake qualitative or mixed-approach studies that provide more clarifying information about the grooming process and the strategies sexual abusers use in order to design effective preventative pedagogical strategies.

5. Conclusions

Grooming is a serious problem that is closely linked to other forms of violence, such as sextortion, and is related to dangerous behaviors such as the consumption of pornography. Furthermore, it can be the precursor to other types of more serious abuse, which is why it needs to be addressed through a multidisciplinary approach with the collaboration of various elements, key among which are teachers and families. Our findings should encourage the educational community to develop suitable preventive actions that match the reality of online child sexual abuse, especially because it is possible to put up barriers and establish limits on Internet use.
To this end, children urgently need to be offered a digital education that will help them develop the necessary skills and abilities to make safe, responsible use of social networks and online platforms. This will also involve teachers—and university teachers—improving their digital competences [61]. More specifically, it is important for them to acquire knowledge about the phenomenon, as they are key professionals in the detection of these abusive sexual practices between students. Families cannot remain on the sidelines either. They must be actively involved through supervision and mediation strategies for younger members’ internet use, not by prohibition but rather through active supervision, dialogue, and constant openness.
In short, the only possible path to preventing and detecting grooming is to invest in high-quality digital education and sex education, which must consider a gender perspective. It must be a pedagogical strategy that will holistically provide children with the tools, abilities, and skills to navigate the online world safely. This is, without a doubt, the task that must engage the entire academic community.

Author Contributions

Conceptualization, P.A.-R., C.V.-P. and B.R.; methodology, I.E.; formal analysis, I.E.; data curation, I.E. and P.A.-R.; writing—original draft preparation, P.A.-R., I.E., C.V.-P. and B.R.; writing—review and editing, B.R.; supervision, B.R. and P.A.-R.; project administration, P.A.-R., I.E., C.V.-P. and B.R.; funding acquisition, P.A.-R., I.E., C.V.-P. and B.R. All authors have read and agreed to the published version of the manuscript.


This research is funded by the “Research Grants from the University of Santiago de Compostela for the implementation of projects aimed at developing measures of the State Pact against Gender Violence 2022 and 2023” (Ministry of Equality, Government of Spain).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee of the University of Santiago de Compostela, Spain (code: USC 46/2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Mean scores for being a victim of grooming as a function of being a victim of sextortion. Note: Sig. < 0.001 (Likert scale: Min. = 0; Max. = 3).
Figure 1. Mean scores for being a victim of grooming as a function of being a victim of sextortion. Note: Sig. < 0.001 (Likert scale: Min. = 0; Max. = 3).
Societies 14 00007 g001
Table 1. Frequencies and percentages from crossing being a victim of grooming and gender.
Table 1. Frequencies and percentages from crossing being a victim of grooming and gender.
Victim of groomingYesCount321737401
% within being a victim80.0%18.2%1.7%100.0%
% within gender14.3%7.3%17.5%12.2%
% of total9.8%2.2%0.2%12.2%
% within being a victim66.6%32.2%1.1%100.0%
% within gender85.7%92.7%82.5%87.8%
% of total58.5%28.3%1.0%87.8%
% within being a victim68.3%30.5%1.2%100.0%
% within gender100.0%100.0%100.0%100.0%
% of total68.3%30.5%1.2%100.0%
Note: Pearson χ² sig. p < 0.001.
Table 2. Frequencies and percentages of pornography consumption by gender.
Table 2. Frequencies and percentages of pornography consumption by gender.
Note: Pearson χ² sig. p < 0.001.
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Alonso-Ruido, P.; Estévez, I.; Regueiro, B.; Varela-Portela, C. Victims of Child Grooming: An Evaluation in University Students. Societies 2024, 14, 7.

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Alonso-Ruido P, Estévez I, Regueiro B, Varela-Portela C. Victims of Child Grooming: An Evaluation in University Students. Societies. 2024; 14(1):7.

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Alonso-Ruido, Patricia, Iris Estévez, Bibiana Regueiro, and Cristina Varela-Portela. 2024. "Victims of Child Grooming: An Evaluation in University Students" Societies 14, no. 1: 7.

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