Prevalence and Predictors of Perpetration of Cyberviolence Against a Dating Partner: A Cross-Cultural Study with Moroccan and Spanish Youth

Abstract

The rise in the levels of cyberviolence in adolescent couples has become a social, educational, and public health problem of enormous magnitude. This study analyzed the nature and dimensions of cyberviolence among adolescents and its association with other forms of offline violence by country of origin (Morocco or Spain) and gender. The objective of the study was to identify the predictors of the perpetration of cyberviolence against a dating partner. The predictor variables were five types of dating victimization (cyber, physical, sexual, emotional with a social impact, and emotional with an individual impact), history of violence, and parental monitoring knowledge. The sample consisted of Spanish (n = 802) and Moroccan students (n = 241) who had dated and attended secondary schools in southeastern Spain. Over half of the participants had perpetrated cyberviolence against their partners; the prevalence was higher among girls and Moroccan youth. Boys reported more physical victimization than girls. For all groups, the strongest predictor of cyberviolence perpetration was cyberviolence victimization. The influence of other forms of victimization, history of offline violence, and parental monitoring differed by the youth’s country of origin and gender. The study reinforces the need for intersectional and cross-cultural analyses of online behaviors.

Keywords

cyberviolence online violence offline violence cross-cultural Moroccan youth Spanish youth

Introduction

With the rise in the use of the Internet and technological applications, there has also been a worrying increase in electronic violence (Cava & Buelga, 2018). This violence may affect relationships with peers, family members, romantic partners, and even strangers for people of any age (Subrahmanyam & Greenfield, 2008). Given the breadth of the field, this study focuses on adolescents’ electronic violence against a romantic partner or cyber dating violence. Virtual aggressions may include threats, insults, humiliations, monitoring of the partner’s whereabouts, public exposure of private conversations and images, control and surveillance behaviors, spread of rumors, and harassment of a current or former partner (U.S. Department of Health and Human Services, 2021). These behaviors can occur both during the relationship and after the breakup (Borrajo et al., 2015a; Reed, et al., 2020; Van Ouytsel et al., 2020). They may start in early preadolescence and increase with age, peaking at age 17 (Thulin et al., 2022).

Controversies related to the difficulty in defining, delimiting, and measuring cyberviolence are numerous (Backe et al., 2018). As a sign of this difficulty, the prevalence of perpetration and victimization of cyberviolence varies enormously among studies (Caridade et al., 2019; Peña-Cárdenas et al., 2018). In the Spanish context, perpetration ranges from 91% of young people reporting having ever perpetrated cyberbullying (Rodríguez-Domínguez et al., 2018) to 3% of adolescents aged 14–18 years (Muñiz-Rivas et al., 2019). Victimization also varied widely in two studies in Spanish schools. Machimbarrena et al. (2018) found that half of the youth (average age 14 years) reported cyber dating violence victimization, while Ortega-Barón et al. (2020) found that 23% reported being victims of partner control and 15% reported being victims of direct online aggression.

Another critical debate in understanding virtual abusive behaviors is establishing its association with offline violence, that is, experienced, perpetrated, or observed off-screen. The association between online and offline violence has been inconclusive (Schokkenbroek et al., 2022). A widely held position is that online violence results from the displacement of the inequalities and violence occurring offline, primarily gender inequalities, to the inside of virtual networks (Borrajo et al., 2015b; Cutbush et al., 2012; Marganski & Melander, 2018; Peskin et al., 2017; Temple et al., 2016; Zweig et al., 2013). For example, Ojanen et al. (2015) concluded that people who have experienced offline violence are 10 times more likely to perpetrate online violence than those who have not. In contrast, Smith and Steffgen (2013) suggested a relative autonomy of cyber and offline violence.

Researchers have analyzed the association between offline and online violence from the perspective of predictor variables of cyberviolence. Peskin et al. (2017) and later Muñoz-Fernández and Sánchez-Jiménez (2020) identified four levels of predictor variables: (1) demographic and contextual, such as age and gender; (2) individual characteristics, such as antisocial behaviors, psychoticism, anxious-depressive disorders, substance abuse, aggressiveness, anger, and lack of empathy; (3) developmental variables related to family and peers, such as intrafamily violence, history of aggression in childhood, intimate partner violence, and aggressive behaviors with peers; and (4) the couple’s context, which considers the quality and dynamics of bonds, and the existence of violent attitudes or behaviors. The last three levels incorporate different dimensions of offline violence. Cutbush et al. (2012) and Caridade et al. (2020) have argued that emotional or psychological aggression and control are associated to a greater extent with cyberviolence. However, whether this association is relevant across cultural groups and contexts remains to be determined.

In this regard, the scarce analysis of cultural and ethnic–racial differences in online and offline teen dating violence is worth noting, as studies tend to homogenize romantic patterns. However, some authors have emphasized the enormous importance of these dimensions, as partner violence tends to be higher in marginalized or underrepresented groups (McNaughton Reyes et al., 2017; Roberts et al., 2018). Likewise, authors have highlighted the influence of cultural values and family or kinship relationships on adolescent violence. Kowalski et al. (2014) argued that collectivist countries with a high-power differential might have different manifestations of cyberbullying than individualistic countries with a low-power distance (“i.e., members of the culture operate on a more equal playing field relative to one another”) (p. 1128).

Some evidence suggests moderate levels of domestic violence among Moroccan immigrants in Spain. In the Observatory against Domestic and Gender Violence of Spain (2019), Morocco is one of the three countries contributing the highest number of fatalities, victims, and aggressors. However, the figures on dating violence do not show statistically significant differences from other groups in Spain, possibly related to the strong differentiation of gender roles and a higher normalization of violence (Arnoso et al., 2022).

Present Study

The setting for this research was Southern Spain, in the province of Almería, a cross-border area with the African continent. Using small boats, African immigrants, especially from Morocco, cross the Mediterranean Sea in a 198-km journey to reach the Spanish coast, searching for work and a better standard of living. Some immigrants who arrive at the coast of Almería settle in this province, while others move to other Spanish localities or travel to another European country. In 2020, according to the Institute of Statistics and Cartography of Andalusía, slightly over 200,000 people resided in the province of Almería, of which 23,361 were immigrants with legal documentation. Of them, 53% arrived from Morocco. Due to the 1990 family reunification act, the first Moroccan students enrolled in the schools of Almería were the children of economic immigrants.

Almería has 278 public schools (kindergarten, primary, and secondary) and six private schools. Most immigrants attend public schools, which are built and subsidized by the government of Andalucía.

This study has three objectives. First, compare the prevalence of cyberviolence perpetration against and victimization from a dating partner by country of origin (Moroccan, Spanish) and gender. Second, examine the history of violence (parental fights, forced sexual activity, hit by an adult) and parental monitoring knowledge (of where and with whom the adolescent is when not in school) by country of origin (Moroccan, Spanish) and gender. Third, identify the predictors of the perpetration of cyberviolence against a dating partner. The predictor variables were five types of dating victimization (cyber, physical, sexual, emotional with a social impact, and emotional with an individual impact), history of violence, and parental monitoring knowledge.

Method

Setting and Participants

For this cross-sectional study, 18 secondary schools located in disadvantaged, rural, suburban, and multicultural areas of Southeastern Spain were selected by probability sampling. The total sample of the project consisted of 2,125 adolescents aged 13–20 years from 45 different countries of origin attending secondary public schools in Almería—equivalent to grades 7–12 in the United States.

The present study focused on a subset of that sample (n = 1,784), students whose origins were Spanish (n = 1,256) or Moroccan (n = 528) since these were the two largest groups. Because the study focuses on dating violence, the analyses excluded youth who reported never having a romantic partner (n = 444 Spaniards, n = 276 Moroccan) and 22 students who did not respond to the question about dating. Thus, the final sample for this analysis consisted of 1,043 students (Table 1): 802 Spanish students (77%) and 241 first- or second-generation Moroccan immigrant youth (Portes & Rumbaut, 2001). Most students who self-identified as Moroccan reported being Muslims (94%), and over half of the youth who self-identified as Spaniards indicated being Catholics (56%). The average age of the students was 15.3 years (standard deviation = 1.39). The samples of Moroccans and Spaniards were evenly distributed by gender.

Table 1.

Demographic Characteristics of Moroccan and Spanish Youth Who Are Dating or Have Dated (n = 1,043).

Demographic Characteristics	Moroccan, N (%)	Spanish, N (%)	Total, N (%)
Gender
Male	117 (50.6)	382 (48.2)	499 (48.8)
Female	107 (46.3)	394 (49.7)	501 (49.0)
Gender fluid		7 (0.9)	7 (0.7)
Trans man	2 (0.9)	3 (0.4)	5 (0.5)
Trans woman	1 (0.4)	2 (0.3)	3 (0.3)
I refuse to answer	4 (1.7)	4 (0.5)	8 (0.8)
Religion
Atheist	7 (2.9)	278 (35.1)	285 (27.6)
Catholic	4 (1.7)	446 (56.4)	450 (43.1)
Muslim	225 (93.8)	10 (1.3)	235 (22.5)
Protestant		3 (0.4)	3 (0.3)
Evangelist		8 (1.0)	8 (0.8)
Buddhist or Hindu		2 (0.3)	2 (0.2)
Jehovah’s Witness		3 (0.4)	3 (0.3)
Jew		1 (0.1)	1 (0.1)
Agnostic	4 (1.7)	33 (4.2)	37 (3.6)
Other		7 (0.9)	7 (0.7)
Relationship status
I am dating someone	63 (26.1)	338 (42.1)	401 (38.4)
I am not dating anyone. but have been for the last 2 months	54 (22.4)	129 (16.1)	183 (17.5)
I am not dating but have been dating for more than 2 months	124 (51.5)	335 (41.8)	459 (44.0)
Sexual orientation
Heterosexual	206 (89.6)	670 (84.4)	876 (85.5)
Gay/Lesbian	2 (0.9)	15 (1.9)	17 (1.7)
Bisexual	10 (4.3)	75 (9.4)	85 (8.3)
Something different	2 (0.9)	3 (0.4)	5 (0.5)
Don’t know	10 (4.3)	31 (3.9)	41 (4.0)

Note. Some numbers do not add to the total due to missing responses.

Instruments

Sociodemographic variables

The sociodemographic measures included in the survey were age, gender, country of birth, country of origin of the family, religion professed, and sexual orientation. Participants also reported their relationship status using four categories: currently dating, not currently dating but dated in prior 2 months, not currently dating but dated over 2 months ago, and have never dated.

History of violence

Three questions assessed the history of violence: How frequently have you seen your parents hit each other? Has someone ever forced you to do something sexual that you did not want? Has an adult hit you intending to harm you? The response categories were never (0), 1–4 times (1), 5–9 times (2), and more than 10 times (3).

Parental monitoring knowledge

Two questions estimated the students’ perceived knowledge that parents have about their whereabouts outside the classroom and knowledge of with whom they are (McNaughton Reyes & Foshee, 2013). The items asked, “When you are away from home, but not at school, do your parents know where you are?” “Do they know who you go with?”. The response categories were never (0), sometimes (1), frequently (2), and always (3).

Perpetration of Cyber dating Abuse is a subscale of the Teen Dating Violence Perpetration Scale (10 items, Omega = .88; Soriano-Ayala et al., 2021). Cyber dating abuse refers to repeated online behaviors aimed at harming, undermining, or controlling the partner. Examples of cyberviolence are invading the partner’s privacy through co-opting passwords, spying on personal emails, threatening to show or publish private images or information without consent, and usurping the partner’s persona in online networks (Martín-Montilla et al., 2016). Response categories were never (0), a few times (1), frequently (2), and always (3). The items measure control and surveillance of the partner using online social networks. The scale was computed as the average of the 10 items, with higher scores indicating more cyber dating perpetration. The goodness-of-fit (GIF) indicators for the confirmatory factor analysis were good: minimum discrepancy per degree of freedom (CMIN/DF) = 4.08, comparative fit index (CFI) = .911, incremental fit index (IFI) = .912, GFI = .926, and root mean square error of approximation (RMSEA) = .052.

Teen Dating Violence Victimization Scale

The Teen Dating Violence Victimization Scale (31 items) measures the frequency of victimization by a romantic partner (Soriano-Ayala et al., 2021). Students indicated how frequently “my partner did it to me” using the following response categories: never (0), a few times (1), frequently (2), and always (3). The scale contains five subscales of victimization: cyberviolence (13 items, Omega = .73, e.g., “My partner does not let me chat online with friends and gets angry if I do.”); physical violence (4 items, Omega = .76, e.g., “When my partner gets angry, he/she slaps me.”); sexual violence (5 items, Omega = .81, e.g., “My partner has treated me as a sexual object.”); emotional violence of social impact—psychological aggression that harms the victim’s relationships with others (4 items, Omega = .81, e.g., “My partner has tried to keep me from talking or seeing my friends or family.”); emotional violence of individual impact—psychological aggression that harms the victim emotionally (5 items, Omega = .76, e.g., “My partner blames me for provoking his/her aggressive behavior.”). Emotional violence builds on levels of harm that can affect the individual or have a social impact, fostering alienation, increasing isolation, and severing social ties. Both forms of harm may vary by gender (Karakurt & Silver, 2013). The scale was computed as the average of the items, with higher scores indicating more partner victimization. The confirmatory factor analysis confirmed five factors. The GFI indicators for the confirmatory factor analysis were good: CMIN/DF = 3.9, CFI = .915, IFI = .916, TLI (Tucker- Lewis Index) = .90, GFI = .926, and RMSEA = .051.

Procedures

To gain access to the secondary schools, the Provincial Delegation of Education granted authorization to the researchers, and the Human Research Bioethics Committee of the University of Almería approved the study. In addition, the school board authorized the research once the parents gave their permission. Students completed the questionnaire in their classrooms in the teacher’s presence. Before completing the questionnaire, students were informed of the research objectives, the anonymity of the responses, and the use of the data solely for academic purposes. The questionnaires were administered in the classroom, and all students who were present that day were invited to participate. Only 17 students refused to complete the survey.

Students did not receive an incentive for participation, a common practice in Spanish research. Because the state funded this research project, the schools and the collaborating teachers received a certificate of recognition for their involvement.

Analysis

First, descriptive calculations were performed by country of origin and gender. To estimate the prevalence of dating violence, we dichotomized the scales into never suffered violence (0 points in any scale item) and one or more times (from 0.1 to 3 points). We used chi-square to assess significant differences among the four groups (Moroccan boys and girls, Spanish boys and girls). We used adjusted standardized residuals to identify cells significantly higher or lower than expected by chance that contributed to the overall significance.

Second, hierarchical linear regression analyses were performed to predict the perpetration of cyberviolence from the five types of partner victimization, history of violence, and parental monitoring knowledge. The Durbin–Watson test was performed to determine the possibility of conducting the regression analysis; values between 1.5 and 2 confirmed that there was no autocorrelation and that the assumption of independence of the errors was fulfilled. In addition, we verified that the data met the criteria of linearity, homoscedasticity, and non-multicollinearity, obtaining values greater than 0.10 for tolerance and less than 10 for VIF. The data were analyzed using SPSS 26.0.

Results

Perpetration of Online Violence and Online–Offline Violence Victimization by Country of Origin and Gender

Over half of the students reported cyberviolence (Table 2). Of the respondents, 53.3% of young people recognized that they had perpetrated online violence against their partners. More Moroccan youth (61.5%) than Spaniards (49.3%) reported having perpetrated cyberviolence. The difference between the four groups of origin and gender was statistically significant (χ² = 29.54; p < .001), with significantly more Moroccan girls and fewer Spanish boys (Table 2).

Table 2.

Proportion of Moroccan and Spanish Youth Reporting Perpetration of Cyberviolence and Dating Violence Victimization.

Dating Violence Constructs	Total	Total	Moroccan Boys	Moroccan Girls	Spanish Boys	Spanish Girls	Overall Chi-Square Gender and Origin
Dating Violence Constructs	n	% Yes*	% Yes (ASR)	% Yes (ASR)	% Yes (ASR)	% Yes (ASR)	χ²	p
Dating perpetration
Cyberviolence	839	53.3	59.4 (1.1)	74.7 (4.3)	44.1 (−4.3)	55.1 (0.9)	29.54	<.001
Dating victimization
Cyberviolence	855	62.1	69.0 (1.2)	78.3 (3.4)	58.3 (−1.8)	60.1 (−1.0)	14.26	.003
Physical	893	28.9	62.4 (7.2)	17.5 (−2.6)	39.7 (5.7)	13.8 (−8.2)	112.43	<.001
Sexual	861	23.3	28.7 (1.2)	21.7 (−0.4)	22.9 (−0.2)	22.9 (−0.2)	1.50	.681
Emotional—social impact	875	38.6	41.8 (0.6)	36.5 (−0.5)	36.2 (−1.2)	40.9 (1.1)	2.18	.535
Emotional—individual impact	866	32.2	36.7 (0.9)	33.3 (0.2)	30.0 (−1.1)	33.1 (0.4)	1.67	.642
Family
Witnessed domestic violence	991	7.6	6.0 (−0.7)	12.7 (2.1)	5.5 (−2.0)	8.7 (1.1)	7.35	.062
Sexual aggression	992	9.1	4.3 (−1.9)	10.6 (0.6)	2.4 (−5.8)	16.6 (6.7)	51.31	<.001
Hit by a family member	986	30.8	38.3 (1.8)	31.7 (0.2)	27.3 (−1.9)	31.9 (0.6)	5.44	.142
Parental monitoring whereabouts	995	96.1	88.7 (−4.3)	100 (2.2)	94.2 (−2.4)	99.0 (3.8)	33.16	<.001
Parental monitoring companions	995	95.6	83.5 (−6.7)	98.1 (1.3)	95.8 (0.3)	98.2 (3.3)	47.94	<.001

Note. ASR from ±1.96 are statistically significant. Negative ASR reflects a lower-than-expected probability of engaging in the behavior; positive ASR reflects a higher-than-expected probability of engaging in the behavior. Bold highlights a significant difference between Moroccan and Spanish youth. ASR = corrected standardized residual.

Respondents who indicated violence in any of the items of the scale.

Similarly, cyberviolence was the most frequent form of victimization. It was reported by 74.2% of Moroccan and by 59.2% of Spanish youth, with a statistically significant difference between the four groups (χ² = 14.26; p = .003). The prevalence among Moroccan girls was significantly higher (Table 2).

Victimization through physical violence differed by country of origin and gender (62.4% of Moroccan boys, 17.5% of Moroccan girls, 39.7% of Spanish boys, and 13.8% of Spanish girls), with statistically significant differences between the two countries of origin and gender (χ² = 112.43; p < .001), with boys reporting 3–4 times more physical victimization than girls and Moroccan youth 1.4 times more than Spaniards. An item analysis of the victimization scale revealed that gender differences were concentrated in two of the four physical victimization items. More boys than girls reported being pinched and pushed while hitting hard and slapping showed no gender differences.

Approximately a fourth of the youth reported sexual victimization, and a third indicated emotional victimization that impacts their social environment or themselves. These proportions did not vary by country of origin or gender.

History of Violence and Parental Monitoring Knowledge Country of Origin and Gender

Table 2 details the proportion of youth reporting dating perpetration, dating victimization, history of violence, and parental monitoring by country of origin and gender; it also indicates significant differences among the groups based on the adjusted standardized residuals. Less than 1 in 10 youth reported witnessing domestic violence with a marginally significant difference by group, with more Moroccan girls and fewer Spanish boys. Overall, almost 1 in 10 participants reported sexual aggression. The prevalence was significantly higher for Spanish girls and lower for Spanish boys. About one-fourth of students acknowledged being hit by a family member without statistically significant differences between the four groups of origin and gender. Parental monitoring knowledge of whereabouts was very high for all respondents (96% overall); in other words, most respondents always tell their relatives where they go. However, the prevalence among girls was significantly higher than boys, at or close to 100%. Parental monitoring knowledge of companions was also very high (96% overall); in other words, most respondents always tell their relatives about the people they go out with and share their leisure activities. Frequencies were significantly higher for Spanish girls and lower for Moroccan boys.

Hierarchical linear regression analysis was conducted to identify the predictors of the perpetration of cyberviolence against a dating partner. The predictor or independent variables were dating victimization, history of violence, and parental monitoring knowledge. The analyses were conducted separately by country of origin and gender.

Table 3 presents the results of the hierarchical regressions for Moroccan and Spanish youth. Cyberviolence victimization was the strongest predictor of perpetration of cyberviolence against the partner for both Morrocan (β = .648; R² = .42) and Spanish (β = .435; R² = .19) adolescents. For Moroccan youth, emotional violence and a history of child abuse significantly decreased the perpetration of cyberviolence; this final model explained 47.2% of the variation in perpetration. For Spanish youth, parental monitoring of whereabouts decreased the perpetration of cyberviolence, and being a victim of physical violence by the dating partner increased perpetration; this final model explained 20.5% of the variation of perpetration of cyberviolence.

Table 3.

Hierarchical Regression Analysis for Variables Predicting Cyberviolence Perpetration Against the Dating Partner—Moroccan and Spanish Youth.

Moroccan Youth (n = 170)					Spanish Youth (n = 657)
	R ²	β	t	p		R ²	β	t	p
Model 1	.420				Model 1	.190
Victim cyberviolence		.648	11.217	.001	Victim cyberviolence		.435	12.553	.001
Model 2	.459				Model 2	.200
Victim cyberviolence		.844	10.756	.001	Victim cyberviolence		.433	12.555	.001
Victim emotional—Individual		–0.279	–3.563	.001	Parental monitoring—Place		–.103	–2.974	.003
Model 3	.472				Model 3	.205
Victim cyberviolence		.836	10.741	.001	Victim cyberviolence		.415	11.679	.001
Victim emotional—Individual		–.253	–3.216	.002	Parental monitoring—Place		–.098	–2.831	.005
Background physical abuse		–.115	–2.037	.043	Victim physical		.073	2.049	.041

Table 4 presents the results of the hierarchical regressions for Moroccan and Spanish youth by gender. Similarly, cyberviolence victimization was the strongest predictor of perpetration of cyberviolence against the dating partner for both genders, being the only predictor for Moroccan adolescent boys with a high specific weight (β = .840; R² = .706). This single variable explained over 70% of the variance.

Table 4.

Hierarchical Regression Analysis for Variables Predicting Cyberviolence Perpetration Against the Dating Partner—Moroccan and Spanish Youth by Gender.

Moroccan Girls (n = 93)					Spanish Girls (n = 330)
	R ²	β	t	p		R ²	β	t	p
Model 1	.294				Model 1	.108
Victim cyberviolence		.542	6.154	.000	Victim cyberviolence		.329	6.302	.000
Model 2	.425				Model 2	.125
Victim cyberviolence		.888	8.033	.000	Victim cyberviolence		.316	6.073	.000
Victim emotional—Individual		–.501	–4.53	.000	Parental monitoring—Place		–.130	–2.494	.013
Model 3	.454				Model 3	.138
Victim cyberviolence		.907	8.35	.000	Victim cyberviolence		.276	5.044	.000
Victim emotional—Individual		–.530	–4.857	.000	Parental monitoring—Place		–.130	–2.512	.012
Parental monitoring—Person		–.172	–2.174	.032	Victim physical		.122	2.243	.026
Model 4	.485				Model 4	.150
Victim cyberviolence		.925	8.690	.000	Victim cyberviolence		.349	5.434	.000
Victim emotional—Individual		–.500	–4.657	.000	Parental monitoring—Place		–.126	–2.45	.015
Parental monitoring—Person		–.179	–2.320	.023	Victim physical		.136	2.496	.013
Background physical abuse		–.181	–2.290	.024	Victim sexual		–.135	–2.143	.033
Moroccan Boys (n = 77)					Spanish Boys (n = 327)
	R ²	β	t	p		R ²	β	t	p
Model 1	.706				Model 1	.347
Victim cyberviolence		.840	13.415	.001	Victim cyberviolence		.589	13.156	.000
					Model 2	.380
					Victim cyberviolence		.468	8.897	.000
					Victim sexual		.218	4.145	.000
					Model 3	.395
					Victim cyberviolence		.475	9.106	.000
					Victim sexual		.213	4.088	.000
					Parental monitoring—Place		–.121	–2.788	.006

For Moroccan adolescent girls, Models 2, 3, and 4 incorporated emotional victimization with individual impact, parental monitoring of adolescent friendships, and history of being hit by an adult as a child; these three variables had a negative association with perpetration, that is, they decrease the likelihood of perpetration of cyberviolence against the partner. The final model explained almost half of the variance (48.5%).

For Spanish adolescent girls, communication with the family about their whereabouts in their free time reduced the perpetration of cyberviolence. Models 3 and 4 introduced physical and sexual violence victimization from a dating partner. Physical violence was associated with an increase and sexual violence with a decrease in the perpetration of cyberviolence. The final model explained 15% of the variance.

For Spanish adolescent boys, in addition to cyberviolence victimization, the final model incorporated two additional variables with explanatory potential. Being a victim of sexual violence was associated with an increase and parental monitoring of whereabouts with a decrease in the perpetration of cyberviolence. The final model explained 39.5% of the variance.

Discussion

During the past decades, immigrants from Northern Africa, particularly Morocco, have arrived in Southern Spain, bringing their culture and traditions. Research on the prevalence of violence toward a dating partner and associated risk factors among these adolescent immigrants is scarce. The present study examined cyberviolence perpetration against a romantic partner and dating victimization among youth living in southern Spain who self-identified as Moroccans or Spaniards. A sample of 1,043 adolescents who reported dating or had dated completed a questionnaire designed and cross-culturally validated for this purpose (Soriano-Ayala et al., 2021).

The prevalence of cyberviolence against a dating partner was high, both perpetration and victimization. More than half of the participants reported perpetrating cyber aggression toward their partner, coinciding with other studies conducted in Spain (Borrajo et al., 2015a; Caridade et al., 2020; Muñoz-Fernández & Sánchez-Jiménez, 2020). Furthermore, 60–70% of adolescents admitted to being victims of cyberviolence (Cava &Buelga, 2018; Machimabarrena et al., 2018). These figures make cyber aggression the most common form of violence young people suffer. More students reported victimization than perpetration, which is not uncommon. Lara (2020) and Stonard (2019) explained this phenomenon by the difficulty young people have in seeing themselves as aggressors.

Although the prevalence was high for everyone, not all groups were equal. In this study, more girls than boys reported cyberviolence perpetration and victimization, especially Moroccan girls. Semenza (2021) posited that girls’ higher prevalence of perpetration of cyberviolence against a partner might reflect an indirect pattern of violence, which he called the spillover effect. In other words, it is easier for girls to respond to violence and inequalities suffered both offline and online through social networks—indirect mechanisms with less exposure—than through other channels. Rodríguez-Castro et al. (2021) argued that the use of technology varied by gender, with girls engaging in more cyberstalking and boys using more sexting and consuming pornography. However, the present study measured only one kind of cyberviolence—control and surveillance of the partner—and could not differentiate among different types of cyber abuse. Another explanation is the bidirectional violence in adolescent couples maintaining a reciprocal dynamic (Castro & Casique, 2019). Likewise, the major differences between perpetration and victimization may also be related to women’s greater sensitivity to and awareness of violence. At the same time, men may have a higher threshold to recognize it; that is, they need to use stronger, explicit, or intense forms of violence to understand it as such. This idea is consistent with the findings from Delgado-Álvarez et al. (2015); the authors concluded that men are less likely than women to perceive psychological violence in romantic relationships.

Moroccan youth, especially women, reported more cyberviolence perpetration and victimization than youth who self-identified as Spaniards. A higher prevalence of cyberviolence against a dating partner has been observed in ethnic, sociocultural, and racialized disadvantaged groups, such as Latinos and African Americans residing in the United States. Scholars have associated violence with the living conditions of these young people, marked by racism, segregation, and worse socioeconomic conditions (Foshee et al., 2008; Haynie et al., 2013; Moral de la Rubia & Ramos-Basurto, 2016). For example, in a sample of low-income, urban, and predominantly African American and Latino youth, Fedina et al. (2016) concluded that levels of victimization and perpetration of partner violence were high and strongly associated with each other. Ludin et al. (2018) complemented this view by resorting to sociocultural explanations. The authors postulated that violence among Mexican adolescents responds to a great extent to the culture’s view of relationships and gender roles supporting machismo, toxic masculinity, and chivalry. These results could be extrapolated to Moroccan youth living in Spain, who are in a worse socioeconomic situation than the natives, suffer ethnic–religious discrimination, and maintain cultural patterns with traditional gender roles.

Beyond offline violence, boys and young people of Moroccan origin reported more physical violence victimization in their romantic relationships. Scholars have frequently concluded that males report more physical victimization (Luo, 2018; Vives-Cases et al., 2021). However, the gender differences in this study were concentrated in mild forms of physical victimization such as pinching and pushing, highlighting the value of item analysis. Our study suggests the need to delve deeper into the meanings of specific behaviors in adolescent relationships, especially for boys, and analyze the thresholds of perception of violence or its concealment. Physical dating victimization is more prevalent in youth from disadvantaged groups in the United States (Boothe et al., 2014) and children of migrants or foreign-born parents in Spain, likely related to gender role stereotypes (Vives-Cases et al., 2021). More research is needed, given that early victimization predicts later dating violence and the health consequences of victimization are severe (Foshee et al., 2004; Orpinas et al., 2017).

Families play a vital role in the lives of adolescents, modeling strategies to solve conflict and promoting health and well-being. A well-researched family characteristic that increases the risk of violence is observing aggression in the home or being hit by a family member. In this study, the prevalence of young people who have witnessed domestic violence between parents ranged between 6% and 13%, with figures lower than those described by Fusco and Fantuzzo (2009). According to Roberts and Price (2019), females report more domestic violence than males because women consider a broader range of behaviors as domestic violence, particularly emotional and financial aggression. Furthermore, at least a quarter of participants (and over a third of Moroccan boys) reported being hit by a family member on at least one occasion. These figures are very high, given that corporal punishment is against the law in Spain. Sexual aggression was markedly gendered. Spanish girls reported having suffered it five times more than Spanish boys and Moroccan girls more than twice as much as Moroccan boys. Segato (2019) argued that sexual violence is the central sphere through which gender inequalities are reproduced and maintained.

The predictors of cyberviolence perpetrated allow delimiting common and differentiated patterns among the four groups analyzed, examining how violence is related, expressed, and manifested. This study did not confirm the influence of offline violence on online aggression (Barter et al., 2017; Cutbush et al., 2012; Zweig et al., 2013); offline violence had a small but significant effect on most groups. In contrast, for young people of all cultural backgrounds and gender, the strongest predictor of cyberviolence perpetrated was the cyberviolence suffered, coinciding with the close association between the two in other studies (Semenza, 2021). Virtual social networks could favor violence because of the anonymity and distance they generate (Smith & Steffgen, 2013). Furthermore, this digital environment makes it challenging to establish emotional regulation, which may favor jealousy, hostility, and narcissism (Branson & March, 2021). The nature of virtual space can also make cyberviolence enormously humiliating and harmful due to its speed, ease, continuity, ubiquity, public exposure, and social questioning, favoring constant revictimization. For young Moroccan boys, the only form of violence that explained the perpetration of cyberviolence was cyberviolence received.

Offline violence played a differentiated role among Spaniards and Moroccan girls; parental monitoring and other forms of partner violence were the most important predictors. According to social control theory (Hirschi, 1969), trust and communication with the family protected against cyberviolence, although the effect in our study was generally small and the type of monitoring differed by country of origin. Parents’ knowledge of where the child is and parents’ knowledge with whom the child interacts outside school are proxy measures for a strong family bond. Multiple studies support that social bonding and parental supervision prevent adolescents from engaging in antisocial behavior, such as the perpetration of online and offline partner violence (Foshee et al., 2011; Gault-Sherman, 2012; McNaughton Reyes & Foshee, 2013).

For Spanish youth, the best predictor was parental knowledge of where youth are, and for Moroccan girls, parental knowledge of with whom they are. Gracia-Leiva et al. (2020) concluded that closeness, communication, and affection to parents and partners reduced the risk of suicide in people who were victims of offline intimate partner violence by reducing feelings of loneliness and psychoemotional disorders. Peskin et al. (2017) explained the protective role of family bonds, as they indirectly reduce antisocial behaviors and promote positive emotional attachments. Regarding family models, Padilla-Medina et al. (2022) exposed the importance of family ties in violence in young people belonging to ethnic minorities in the United States. These results reinforce the value of culturally sensitive interventions to promote parental–filial communication in preventing violence.

As expected, physical dating victimization among Spanish girls and sexual victimization among Spanish boys were associated with higher perpetration of cyberviolence. Contrary to expectations, some instances of violence were associated with less perpetration of cyberviolence: emotional partner victimization and a family background of physical abuse among Moroccan girls, and sexual partner victimization among Spanish girls. This inverse association in girls could be explained by the effect of learned helplessness, psychoemotional disorders linked to the violence suffered, or discipline associated with gender patterns (González-Ortega et al., 2008). Cuevas et al. (2020) also suggested that exposure to aversive or violent events can, in some instances, trigger a greater perception of vulnerability, stimulate protection and risk avoidance mechanisms, and decrease interactions with the threatening stimuli, reducing the risk of perpetrating other forms of violence. The results of this study suggest that not all social groups experience, elaborate, and react in the same way to the violence suffered. The directionality and types of interaction of offline–online violence cannot be simplified or homogenized, as Izaguirre and Calvete (2017) discussed; the authors found different gender patterns in the influence of exposure to violence on the perpetration of aggression.

This study had some limitations. The data collection coincided with the COVID-19 pandemic. From September 2020 onwards, most schools limited the number of students who could access the building; each week, half of the students attended in person and the other half virtually. For data collection, we used the COVID protocol specific to each establishment. In schools that allowed access, the researchers administered and collected the questionnaires; in schools that restricted access, teachers were trained to do so. The population of Moroccan students remained stable, given that the borders with Morocco were closed. The restrictions to access schools and the increased in-school absenteeism in some schools may have influenced the data collection and student participation. Given that the results are based on self-reports, validity and reliability are usual concerns. One question about sexual violence was embedded with other questions related to family violence. However, the question did not specify the perpetrator (relatives, partners, or strangers). Possibly, some students indicated sexual abuse while thinking about their dating partners. However, many students who did not date or who did not report sexual victimization from their partner did confirm sexual abuse to this question in the family context. For ethical and legal reasons, the university’s Bioethics Committee and the Education Department, which reviewed and approved the research, allowed only to ask three questions about the students’ history of violence.

Conclusions

This study contributes to understanding virtual violence in dating relationships of young people living in Spain, highlighting similarities and differences by gender and country of origin. This research is one of the first to examine the romantic relationships of Moroccan youth living in Spain and compare them to students who self-identified as Spaniards. The prevalence of cyberviolence was very high for all groups, and cyber victimization was the strongest predictor of online perpetration. Reports of perpetration and victimization were higher among Moroccan youth and girls. Given the potentially devastating impact of cyberviolence, these results highlight the need to educate youth about the appropriate use of technology and social media. More scholarly work is needed to understand the types of cyber abuse, its consequences, and the best strategies to curtail it. Furthermore, researchers, parents, and educators should examine the meaning of these behaviors within gender and cultural contexts as youth prepare for entering the adult world of working and developing long-term relationships.

Footnotes

Acknowledgements

The authors are grateful for the valuable support of the professors and students who participated with their contributions to this study.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is part of a large research project, “Teen Dating Violence: Cross-cultural research for prevention and intervention in socio-educational contexts” (RTI2018-101668-B-I00), funded by the Ministerio de Ciencia e Innovación del Gobierno de España (Ministry of Science and Innovation of the Government of Spain).

ORCID iDs

Encarnación Soriano-Ayala

Verónica C. Cala

Author Biographies

Encarnación Soriano-Ayala, PhD, is a Professor in Research Methods in Education at the University of Almería, Spain. Her research focuses on transcultural health education and teen dating violence prevention, particularly in adolescents from different ethnic and cultural groups.

Verónica C. Cala, PhD, is a Lecturer in Research Methods in Education at the University of Almería. PhD in Transcultural health education with migrant adolescents. Her research focuses on medical anthropology applied to education. At this moment, her main activity is oriented toward understanding the cultural aspects involved in teen dating violence.

Pamela Orpinas, PhD, is a Professor in the Department of Health Promotion and Behavior, College of Public Health at the University of Georgia. She has conducted extensive research on preventing violence in schools and families, particularly among immigrants. She has studied peer bullying, dating aggression, and family violence in the United States and Latin America.

References

Arnoso

Elgorriaga

(2022). The intercultural role of attitudes towards violence against women among Moroccan immigrants. Violence Against Women, 28(12–13). https://doi.org/10.1177/10778012211051400

Backe

E. L.

Lilleston

McCleary-Sills

(2018). Networked individuals, gendered violence: A literature review of cyberviolence. Violence and Gender, 5(3), 135–146. https://doi.org/10.1089/vio.2017.0056

Barter

Stanley

Wood

Lanau

Aghtaie

Larkins

Øverlien

(2017). Young people’s online and face-to-face experiences of interpersonal violence and abuse and their subjective impact across five European countries. Psychology of Violence, 7(3), 375–384. https://doi.org/10.1037/vio0000096

Boothe

M. A.

Wilson

R. M.

Lassiter

T. E.

Holland

(2014). Differences in sexual behaviors and teen dating violence among Black, Hispanic, and White female adolescents. Journal of Aggression, Maltreatment & Trauma, 23(10), 1072–1089. https://doi.org/10.1080/10926771.2014.964436

Borrajo

Gámez-Guadix

Calvete

(2015a). Cyber dating abuse: Prevalence, context, and relationship with offline dating aggression. Psychological Reports, 116(2), 565–585. https://doi.org/10.2466/21.16.PR0.116k22w4

Borrajo

Gámez-Guadix

Calvete

(2015b). Justification beliefs of violence, myths about love and cyber dating abuse. Psicothema, 27(4), 327–333. https://doi.org/10.7334/psicothema2015.59

Branson

March

. (2021). Dangerous dating in the digital age: Jealousy, hostility, narcissism, and psychopathy as predictors of cyber dating abuse. Computers in Human Behavior, 119, 106711. https://doi.org/10.1016/j.chb.2021.106711

Caridade

Braga

Borrajo

(2019) Cyber dating abuse (CDA): Evidence from a systematic review. Aggression & Violent Behavior, 48, 152–168. https://doi.org/10.1016/j.avb.2019.08.018

Caridade

Pedrosa

Sousa

H. F.

Pimenta Dinis

M. A.

(2020). Cyber and offline dating abuse in a Portuguese sample: Prevalence and context of abuse. Behavioral Sciences, 10(10), 152. https://doi.org/10.3390/bs10100152

10.

Castro

Casique

(2019). Patrones de direccionalidad de la violencia en el noviazgo: prevalencia y posibles explicaciones. In Casique

(Ed.), Nuevas rutas y evidencias en los estudios sobre violencia y sexualidad de adolescentes mexicanos (pp. 75–111). Centro Regional de Investigaciones Multidisciplinarias, Universidad National Autónoma de México.

11.

Cava

M. J.

Buelga

(2018). Propiedades psicométricas de la escala de ciber-violencia en parejas adolescentes (Cib-VPA). Suma Psicológica, 25(1), 51-61. https://dx-doi-org.web.bisu.edu.cn/10.14349/sumapsi.2018.v25.n1.6

12.

Cuevas

C. A.

Sabina

Kushner

Goggin

Van Westendorp

(2020). Is dating aggression victimization a risk factor or a consequence of other forms of victimization? A longitudinal assessment with Latino youth. Psychology of Violence, 10(5), 520–530. https://doi.org/10.1037/vio0000289

13.

Cutbush

Williams

Miller

Gibbs

Clinton-Sherrod

(2012). Longitudinal patterns of electronic teen dating violence among middle school students. Journal of Interpersonal Violence, 36(5–6), NP2506–NP2526. https://doi.org/10.1177/0886260518758326

14.

Delgado-Álvarez

M. C.

Estrada-Aranda

López-Huerto

J. A.

(2015). Gender and cultural effects on perception of psychological violence in the partner. Psicothema, 27(4), 381–387. https://doi.org/10.7334/psicothema2015.54

15.

Fedina

Howard

D. E.

Wang

M. Q.

Murray

(2016). Teen dating violence victimization, perpetration, and sexual health correlates among urban, low-income, ethnic, and racial minority youth. Community Health Equity Research & Policy, 37(1), 3–12. https://doi.org/10.1177/0272684X16685249

16.

Foshee

V. A.

Benefield

T. S.

Ennett

S. T.

Bauman

K. E.

Suchindran

(2004). Longitudinal predictors of serious physical and sexual dating violence victimization during adolescence. Preventive Medicine, 39(5), 1007–1016. https://doi.org/10.1016/j.ypmed.2004.04.014

17.

Foshee

V. A.

Karriker-Jaffe

K. J.

Reyes

H. L. M.

Ennett

S. T.

Suchindran

Bauman

K. E.

Benefield

T. S.

(2008). What accounts for demographic differences in trajectories of adolescent dating violence? An examination of intrapersonal and contextual mediators. Journal of Adolescent Health, 42(6), 596–604. https://doi.org/10.1016/j.jadohealth.2007.11.005

18.

Foshee

V. A.

McNaughton Reyes

H. L.

Ennett

S. T.

Suchindran

Mathias

J. P.

Karriker-Jaffe

K. J.

Bauman

K. E.

Benefield

T. S.

(2011). Risk and protective factors distinguishing profiles of adolescent peer and dating violence perpetration. Journal of Adolescent Health, 48(4), 344–350. https://doi.org/10.1016/j.jadohealth.2010.07.030

19.

Fusco

R. A.

Fantuzzo

J. W.

(2009). Domestic violence crimes and children: A population-based investigation of direct sensory exposure and the nature of involvement. Children and Youth Services Review, 31(2), 249–256. https://doi.org/10.1016/j.childyouth.2008.07.017

20.

Gault-Sherman

(2012). It’s a two-way street: The bidirectional relationship between parenting and delinquency. Journal of Youth and Adolescence, 41(2), 121–145. https://doi.org/10.1007/s10964-011-9656-4

21.

González-Ortega

Echeburúa

De Corral

(2008). Variables significativas en las relaciones violentas en parejas jóvenes: Una revisión. Psicología Conductual, 16(2), 207–225.

22.

Gracia-Leiva

Puente-Martínez

Ubillos-Landa

González-Castro

J. L.

Páez-Rovira

(2020). Off- and online heterosexual dating violence, perceived attachment to parents and peers and suicide risk in young women. International Journal of Environmental Research and Public Health, 17(9), 3174. https://doi.org/10.3390/ijerph17093174

23.

Haynie

D. L.

Farhat

Brooks-Russell

Wang

Barbieri

Iannotti

R. J.

(2013). Dating violence perpetration and victimization among US adolescents: Prevalence, patterns, and associations with health complaints and substance use. Journal of Adolescent Health, 53(2), 194–201. https://doi.org/10.1016/j.jadohealth.2013.02.008

24.

Hirschi

(1969). Causes of delinquency. University of California Press.

25.

Izaguirre

Calvete

(2017). Exposure to family violence as a predictor of dating violence and child-to-parent aggression in Spanish adolescents. Youth & Society, 49(3), 393-412. https://doi.org/10.1177/0044118X16632138

26.

Karakurt

Silver

K. E.

(2013). Emotional abuse in intimate relationships: The role of gender and age. Violence and Victims, 28(5), 804–821. https://doi.org/10.1891/0886-6708.vv-d-12-00041

27.

Kowalski

R. M.

Giumetti

G. W.

Schroeder

A. N.

Lattanner

M. R.

(2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140(4), 1073-1137. https://doi.org/10.1037/a0035618

28.

Lara

(2020). Cyber dating abuse: Assessment, prevalence, and relationship with offline violence in young Chileans. Journal of Social and Personal Relationships, 37(5), 1681–1699. https://doi.org/10.1177/0265407520907159

29.

Ludin

Bottiani

J. H.

Debnam

Solis

M. G. O.

Bradshaw

C. P.

(2018). A cross-national comparison of risk factors for teen dating violence in Mexico and the United States. Journal of Youth and Adolescence, 47(3), 547–559. https://doi.org/10.1007/s10964-017-0701-9

30.

Luo

(2018). Gender and dating violence perpetration and victimization: A comparison of American and Chinese college students. Journal of Interpersonal Violence, 36(11–12), 5581–5607. https://doi.org/10.1177/0886260518804168

31.

Machimbarrena

J. M.

Calvete

Fernández-González

Álvarez-Bardón

Álvarez-Fernández

González-Cabrera

(2018) Internet risks: An overview of victimization in cyberbullying, cyber dating abuse, sexting, online grooming and problematic internet use. International Journal of Environmental Research and Public Health, 15(11), 2471.https://doi.org/10.3390/ijerph15112471

32.

Marganski

Melander

(2018). Intimate partner violence victimization in the cyber and real world: Examining the extent of cyber aggression experiences and its association with in-person dating violence. Journal of Interpersonal Violence, 33(7), 1071–1095. https://doi.org/10.1177/0886260515614283

33.

Martín-Montilla

Pazos-Gómez

Montilla-Coronado

M. V. C.

Romero-Oliva

(2016). Una modalidad actual de violencia de género en parejas de jóvenes: Las redes sociales [A current mode of gender violence in young couples: Social networks]. Educación XXI, 19(2), 405–429. https://doi.org/10.5944/educxx1.16473

34.

McNaughton Reyes

H. L.

Foshee

V. A

. (2013). Sexual dating aggression across grades 8 through 12: Timing and predictors of onset. Journal of Youth and Adolescence, 42(4), 581–595. https://doi.org/10.1007/s10964-012-9864-6

35.

McNaughton Reyes

H. L.

Foshee

V. A.

Chen

M. S.

Ennett

S. T

. (2017). Patterns of dating violence victimization and perpetration among Latino youth. Journal of Youth and Adolescence, 46(8), 1727–1742. https://doi.org/10.1007/s10964-016-0621-0

36.

Moral de la Rubia

Ramos Basurto

(2016). Machismo, victimización y perpetración en mujeres y hombres mexicanos. Estudios sobre las Culturas Contemporáneas, 22(43), 37–66.

37.

Muñiz-Rivas

Vera

Povedano-Díaz

(2019). Parental style, dating violence and gender. International Journal of Environmental Research and Public Health, 16(15), 2722. https://doi.org/10.3390/ijerph16152722

38.

Muñoz-Fernández

Sánchez-Jiménez

(2020). Cyber-aggression and psychological aggression in adolescent couples: A short-term longitudinal study on prevalence and common and differential predictors. Computers in Human Behavior, 104, 106191. https://doi.org/10.1016/j.chb.2019.106191

39.

Observatory against Domestic and Gender Violence of Spain. (2019). Report on mortal victims of gender violence in the sphere of the partner or ex-partner in the years 2016 to 2018. https://www.poderjudicial.es/cgpj/es/Temas/Violencia-domestica-y-de-genero/Actividad-del-Observatorio/Informes-de-violencia-domestica-y-de-genero/

40.

Ojanen

T. T.

Boonmongkon

Samakkeekarom

Samoh

Cholratana

Guadamuz

T. E.

(2015). Connections between online harassment and offline violence among youth in Central Thailand. Child Abuse & Neglect, 44, 159-169. https://doi.org/10.1016/j.chiabu.2015.04.001

41.

Orpinas

Nahapetyan

Truszczynski

(2017). Low and increasing trajectories of perpetration of physical dating violence: 7-year associations with suicidal ideation, weapons, and substance use. Journal of Youth and Adolescence, 46(5), 970–981. https://doi.org/10.1007/s10964-017-0630-7

42.

Ortega-Barón

Montiel

Machimbarrena

J. M.

Fernández-González

Calvete

González-Cabrera

(2020). Epidemiology of cyber dating abuse victimization in adolescence and its relationship with health-related quality of life: A longitudinal study. Youth & Society, 54(5), 711–729. https://doi.org/10.1177/0044118X20980025

43.

Padilla-Medina

D. M.

Williams

J. R.

Ravi

Ombayo

Black

B. M.

(2022). Teen dating violence help-seeking intentions and behaviors among ethnically and racially diverse youth: A systematic review. Trauma, Violence, & Abuse, 23(4), 1063–1078. https://doi.org/10.1177/1524838020985569

44.

Peña-Cárdenas

Rojas-Solís

J. L.

García-Sánchez

P. V.

(2018). Uso problemático de internet, cyberbullying y ciber-violencia de pareja en jóvenes universitarios. Diversitas: Perspectivas en Psicología, 14(2), 205–219.

45.

Peskin

M. F.

Markham

C. M.

Shegog

Temple

J. R.

Baumler

E. R.

Addy

R. C.

Hernandez

Cuccaro

Gabay

E. K.

Thiel

Emery

S. T.

(2017). Prevalence and correlates of the perpetration of cyber dating abuse among early adolescents. Journal of Youth and Adolescence, 46(2), 358–375. https://doi.org/10.1007/s10964-016-0568-1

46.

Portes

Rumbaut

R. G.

(2001). Legacies: The story of the immigrant second generation. University of California Press.

47.

Reed

L. A.

Boyer

M. P.

Maleskunas

Tolman

R. M.

Ward

L. M.

(2020). How do adolescents experience “sexting” in dating relationships? Motivations to sext and responses to sexting requests from dating partners. Children and Youth Services Review, 109, 104696. https://doi.org/10.1016/j.childyouth.2019.104696

48.

Roberts

Tamene

Orta

O. R.

(2018). The intersectionality of racial and gender discrimination among teens exposed to dating violence. Ethnicity & Disease, 28(Suppl 1), 253–260. https://doi.org/10.18865/ed.28.S1.253

49.

Roberts

Price

(2019). Gendered perceptions of domestic violence: How young females are more likely than young males to know controlling domestic violence behaviours (Working Paper). CASS, University of Sunderland.

50.

Rodríguez-Castro

Martínez-Román

Alonso-Ruido

Adá-Lameiras

Carrera-Fernández

M. V.

(2021). Intimate partner cyberstalking, sexism, pornography, and sexting in adolescents: New challenges for sex education. International Journal of Environmental Research and Public Health, 18(4), 2181. https://doi.org/10.3390/ijerph18042181

51.

Rodríguez-Domínguez

Durán

Martínez-Pecino

(2018). Ciberagresores en el noviazgo adolescente y su relación con la violencia psicológica, el sexismo y los celos. Health and Addictions/Salud y Drogas, 18(1), 17–27. https://doi.org/10.21134/haaj.v18i1.329

52.

Schokkenbroek

J. M.

Ouytsel

J. V.

Hardyns

Ponnet

(2022). Adults’ online and offline psychological intimate partner violence experiences. Journal of Interpersonal Violence, 37(15–16), NP14656–NP14671. https://doi.org/10.1177/08862605211015217

53.

Segato

L. R.

(2019) Una mañana con Rita Segato: Debates con adolescentes. Entrevista realizada por Gabriela Wiener en el CCCB. https://www.cccb.org/es/multimedia/videos/una-manana-con-rita-segato/230087

54.

Semenza

D. C.

(2021). Gender differences in the victim-offender relationship for on- and offline youth violence. Journal of Interpersonal Violence, 36(19–20), 9255–9276. https://doi.org/10.1177/0886260519864358

55.

Smith

P. K.

Steffgen

(Eds.). (2013). Cyberbullying through the new media: Findings from an international network. Psychology Press.

56.

Soriano-Ayala

Sanabria-Vals

Cala

V. C.

(2021). Design and validation of the scale TDV-VP teen dating violence: Victimisation and perpetration [Violencia en parejas adolescentes: Victimización y perpetración] for Spanish speakers. International Journal of Environmental Research and Public Health, 18(2), 421. https://doi.org/10.3390/ijerph18020421

57.

Stonard

K. E.

(2019). Technology-assisted adolescent dating violence and abuse: A factor analysis of the nature of electronic communication technology used across twelve types of abusive and controlling behaviour. Journal of Child and Family Studies, 28(1), 105–115. https://doi.org/10.1007/s10826-018-1255-5

58.

Subrahmanyam

Greenfield

(2008). Online communication and adolescent relationships. Future of Children, 18(1), 119–146. https://doi.org/10.1353/foc.0.0006

59.

Temple

J. R.

Choi

H. J.

Brem

Wolford-Clevenger

Stuart

G. L.

Peskin

M. F.

Elmquist

J. A.

(2016). The temporal association between traditional and cyber dating abuse among adolescents. Journal of Youth and Adolescence, 45(2), 340–349. https://doi.org/10.1007/s10964-015-0380-3

60.

Thulin

E. J.

Zimmerman

M. A.

Kusunoki

Kernsmith

Smith-Darden

Heinze

J. E.

(2022). Electronic teen dating violence curves by age. Journal of Youth and Adolescence, 51(1), 45-61. https://doi.org/10.1007/s10964-021-01517-w

61.

U.S. Department of Health and Human Services. (2021). What is cyberbullying? https://www.stopbullying.gov/cyberbullying/what-is-it

62.

Van Ouytsel

Ponnet

Walrave

. (2020). Cyber dating abuse: Investigating digital monitoring behaviors among adolescents from a social learning perspective. Journal of Interpersonal Violence, 35(23–24), 5157–5178. https://doi.org/10.1177/0886260517719538

63.

Vives-Cases

Pérez-Martínez

Davó-Blanes

Sánchez-SanSegundo

Gil-González

Abiétar

D. G.

Sánchez-Martínez

Forcadell-Díez

Pérez

Sanz-Barbero

(2021). Dating violence and associated factors among male and female adolescents in Spain. PloS One, 16(11), e0258994. https://doi.org/10.1371/journal.pone.0258994

64.

Zweig

J. M.

Dank

Yahner

Lachman

(2013). The rate of cyber dating abuse among teens and how it relates to other forms of teen dating violence. Journal of Youth and Adolescence, 2(7), 1063–1077. https://doi.org/10.1007/s10964-013-9922-8