Mapping the Cyber Interpersonal Violence among Young Populations: A Scoping Review
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NOVA National School of Public Health, NOVA University of Lisboa, 1600-560 Lisboa, Portugal
2
Center for Research in Psychology, School of Psychology, University of Minho, 4710-057 Braga, Portugal
3
Nursing Department, Vale do Ave School of Health, North Polytechnic Institute of Health, Vila Nova de Famalicão, 4760-409 Gandra, Portugal
4
Interdisciplinary Centre for Social Sciences (CICS), Comprehensive Health Research Centre (CHRC), National School of Public Health, NOVA University, 1099-085 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
Soc. Sci. 2022, 11(5), 207; https://doi.org/10.3390/socsci11050207
Submission received: 18 March 2022
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Revised: 28 April 2022
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Accepted: 3 May 2022
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Published: 10 May 2022
(This article belongs to the Special Issue Violence, Victimization and Prevention)
Abstract
:The increase in digital practices and networking has introduced important changes to social interactions. The extensive use of technology among young people has allowed for cyber communication, which has numerous benefits but can also trigger violence in relationships. Interpersonal violence affecting young people is becoming more widely recognized as a public health issue. The aim of this scoping review is to map and systematize the published academic literature on Cyber Interpersonal Violence (CIV) amongst young people, following the methodological approach proposed by Arksey and O’Malley. Five databases were searched: PubMed, Scopus, CINAHL (EBSCOhost), Science Direct and Social Sciences Citation Index. Eighteen studies in English, Portuguese, Spanish and French, published from 2004 onwards, were included. Three main areas arose in the CIV: cyber dating abuse, cyberbullying and cyber-harassment. Investing in prevention is the key to preventing cyber violence.
1. Introduction
Adolescents and young people are vanguards of the consumption of new technologies. Young people’s accessibility to technological tools has exploded, causing the youth to lose many communication and social interaction skills (Reed et al. 2016). Digital practices increase the risk of being exposed to cyber interpersonal violence (CIV) once everyone has access to the digital conversation, everywhere, with everyone. The use of digital tools confers numerous benefits to the social processes of adolescents; nevertheless, digital practices increase young people’s exposure to interpersonal invasiveness, making them more susceptible to experiencing cyber dating abuse (CDA), cyberstalking, cyberbullying and sexting (Caridade et al. 2019; Jun 2020). According to recent studies, these forms of violence have received several labels, such as electronic abuse, online abuse, sexual abuse, online sexual abuse, cyber harassment (Flach and Deslandes 2017). The current literature uses aggression, abuse and violence as commutable, although they are not the same (Geffner 2016). Hence, the term abuse indicates not a single behaviour but the victim’s context, motive and outcomes. Nevertheless, the existing measures do not contemplate these characteristics and are more dedicated to evaluating a specific behaviour. Defining these forms of violence represents an ongoing challenge for investigators in understanding the phenomenon in future research.
According to the objectives of the present scoping review, we will use all the possible terms, such as abuse, aggression and violence, to bring together the most significant number of manuscripts possible. We will be analysing violent interpersonal behaviours which occur via technological devices, such as game consoles, cell phones, computers and the internet (European Institute for Gender Equality 2020; Smith et al. 2019), amongst our target group, i.e., young students. When it occurs in younger communities, interpersonal violence victimisation always constitutes an adverse childhood experience with potentially harmful lifetime effects (Kowalski et al. 2019).
Online interactions have unique features that promote and encourage intimidating tactics, such as control and monitoring (Stephenson et al. 2018). Hence, aggression can occur at any moment, and physical proximity with the victim loses importance in the online context. Additionally, the aggressor does not see the victim’s reaction, so it is tempting to diminish the consequences of their acts (Muñoz-Fernández and Sánchez-Jiménez 2020). Lastly, the aggressor may feel immune due to the anonymity that the online context provides, while the victim experiences more humiliation due to a growing potential audience (Stonard 2020).
In this work, we explore all the various aspects understood to be part of CIV. The World Health Organization (WHO) has stated that “interpersonal violence is the fourth leading cause of death in adolescents and young people globally”, and one in eight young people report sexual abuse (World Health Organization 2021).
In most parts of the world, cyber violence is becoming a significant concern, affecting an increasing number of people, particularly women and young people (Council of Europe 2020). Furthermore, it has been stated that cyber violence is not an isolated phenomenon, often following the same patterns as offline violence (European Institute for Gender Equality 2020). The Council of Europe (CE) defines cyber violence as “(…) the use of computer systems to cause, facilitate, or threaten violence against individuals that results in, or is likely to result in, physical, sexual, psychological, or economic harm or suffering and may include the exploitation of the individual’s circumstances, characteristics, or vulnerabilities” (Council of Europe 2020).
The current literature (Buelga et al. 2020; Caridade and Braga 2019; Galende et al. 2020; Gkiomisi et al. 2017) focuses on CDA or cyberbullying features. These are particularly concerning issues among teenagers, either because they are at a vulnerable age or because empirical evidence reveals that 56% of teens in dating relationships have experienced CDA (Cava et al. 2020). On the other hand, prevalence rates vary in terms of patterns of victimization or perpetration. Regarding cyber control behaviours, 10.6% of teenagers admitted to committing direct cyber abuse against their partners. This rate increased to 82% when it came to direct cyber aggression against their partner (Borrajo et al. 2015). Prevalence of victimization rates follow the same patterns, depending on whether direct cyber aggression (14%) or cyber control (75%) was measured.
In the cyberbullying field, a study carried out by Jun {Formatting Citation} states that 34% of the adolescents were involved in cyberbullying as cyberbullies (6.3%), victims (14.6%), or both cyberbullies and victims (13.1%). Even if data on cyber violence varies, these are significant issues that require attention, particularly in adolescence.
This article outlines a scoping review on the emerging theme of CIV with considerable impact on the interpersonal functioning of young people. Hence, the primary aim of the scoping review is to map and systematize the published academic literature on the mentioned subject. The secondary objectives are three, as follows: (i) to develop a descriptive overview of the existing academic literature to reveal the most relevant research trends on CIV amongst young people; (ii) to systematically map and categorise the wide variety of instruments designed to identify and assess CIV, in general and amongst our target group; (iii) to identify research gaps, and, consequently, to develop recommendations.
2. Methods
2.1. Search Strategy for Identifying Relevant Studies
This review follows the search strategy recommended by the Joanna Briggs Institute Manual {Formatting Citation}, which includes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist (Tricco et al. 2018). The search strategy was conducted in the following databases: PubMed, Scopus, CINAHL (EBSCOhost), Science Direct and Social Sciences Citation Index. The search was conducted between September and December 2020. No geographical restraint was applied.
A search strategy was designed to retrieve as many potentially eligible studies as possible: [(Youth) OR (Adolescen*) OR (Adolescent) OR (Students) OR (Universities)] AND [(Abuse) OR (Violence) OR (aggression) OR (aggress*)] AND [(Cyber) OR (Digital) OR (Digit*)].
2.2. Inclusion and Exclusion Criteria
The inclusion criteria referred to (1) studies on cyber interpersonal violence using a quantitative or qualitative approach; (2) studies on the adolescent population, which mainly comprised of university students; (3) studies published as of 2004; and (4) studies published in English, Portuguese, Spanish, and French.
The exclusion criteria referred to (1) studies not including cyber interpersonal violence (such as cyberbullying, cyber dating abuse, cyber harassment); (2) studies on a primarily adult population (where the sample is not comprised of students); (3) articles that focused on face-to-face violence; (4) studies published before 2004; and (5) clinical trials with no results.
2.3. Data Collection
Titles and abstracts were read by two reviewers, including the Principal Investigator (PI) and a co-investigator, to decide if they met the eligibility criteria. After the database search, the selected studies were carried out on Mendeley software, used for database organisation and removal of the duplicated articles. All studies that met the defined criteria were analysed in full text. Any issues regarding a study’s eligibility have been handled after a debate with a third reviewer. The studies considered for inclusion were categorized according to the primary features: authors, year publication, geographic location, sample characteristics (N, age, sex), CIV domain, objectives, and main findings.
3. Results
Figure 1 summarizes the PRISMA (Moher et al. 2009) literature procedure. The scoping review covered a total of 18 studies. Out of 457 identified studies, we retrieved 85 references after applying the duplication process.
3.1. Overview of Included Studies
The eighteen articles included presented an overview of the existing research carried out about CIV, including the instruments produced and applied up until the present (Table 1).
3.2. Year of Publication and Location
The studies included in this study were published between the years of 2010 (Mishna et al. 2010) and 2020 (Buelga et al. 2020; Caridade et al. 2020; Galende et al. 2020; Jun 2020; Rebollo-Catalan and Mayor-Buzon 2020; Reed et al. 2016). The year with the most publications was 2020 (n = 6), followed by 2018 (n = 3) and 2019, and 2017 and 2015 (n = 2). Most of the studies were conducted in Spain (n = 4) (Buelga et al. 2020; Galende et al. 2020; Rebollo-Catalan and Mayor-Buzon 2020; Sánchez et al. 2015). Three studies were conducted in Portugal (Caridade et al. 2019, 2020; Pereira et al. 2016), and three included several countries (Athanasiou et al. 2018; Caridade et al. 2019; Del Rey et al. 2015). Two studies each were conducted in the United States of America (Peskin et al. 2017; Reed et al. 2020) and Canada (Mishna et al. 2010; Smith et al. 2018). Two studies were conducted in Asia: one in Korea (Jun 2020) and one in China (Lee et al. 2013). Approximately 67% of the studies were conducted in Europe (n = 12), mostly in Spain. One study was conducted in Italy (Morelli et al. 2018) and Greece (Gkiomisi et al. 2017).
3.3. Sample Characteristics
The sample size of the studies ranged from 61 (Lee et al. 2013) to 13,798 (Athanasiou et al. 2018). There were some disparities in the sample frame, including: students in general (n = 14) (Buelga et al. 2020; Caridade et al. 2019, 2020; Del Rey et al. 2015; Galende et al. 2020; Gkiomisi et al. 2017; Jun 2020; Pereira et al. 2016; Morelli et al. 2018; Peskin et al. 2017; Rebollo-Catalan and Mayor-Buzon 2020; Reed et al. 2016; Sánchez et al. 2015), university/college students (n = 1) (Caridade et al. 2019), and middle and high school students (n = 3) (Lee et al. 2013; Mishna et al. 2010; Smith et al. 2019). The age of the participants ranged from a minimum of 11 (Del Rey et al. 2015; Galende et al. 2020; Peskin et al. 2017) to a maximum of 30 (Caridade et al. 2019).
3.4. Field of the Studies
All 18 analysed studies self-report as regarding CIV. However, it was possible to understand some emerging fields: cyber dating violence/cyber dating abuse (n = 8) (Caridade and Braga 2019; Caridade et al. 2019, 2020; Galende et al. 2020; Morelli et al. 2018; Peskin et al. 2017; Sánchez et al. 2015; Smith et al. 2018), cyberbullying (n = 7) (Athanasiou et al. 2018; Buelga et al. 2020; Del Rey et al. 2015; Gkiomisi et al. 2017; Jun 2020; Lee et al. 2013; Mishna et al. 2010), cyber harassment (n = 2) (Pereira et al. 2016; Reed et al. 2020) and cyber bystanders (n = 1) (Rebollo-Catalan and Mayor-Buzon 2020).
3.5. Assessment Tools
CIV was assessed using various methods given their importance for the operationalization of CIV. As one of the critical objectives of the current investigation, we discuss them in Table 2.
In the field of CDA/CDV, the measurement tools that emerged were the Cyber Dating Abuse Questionnaire (CDAQ) developed by Borrajo et al. (2015) (n = 8), the Cyber Dating Violence Inventory (CDVI) (n = 1) (Morelli et al. 2018), the Cyber Dating Q_A Scale (n = 2) and Cyber Dating Abuse Victimization (CDAV) (n = 3). Many of the tools assess both victimization and perpetration, while a smaller number of instruments focus only on victimization (n = 1) or perpetration (n = 1).
In the field of cyberbullying, the measurement tools that emerged were Cyberbullying and Online Aggression (n = 1), a cyberbullying survey (n = 1), Achenbach’s Youth Self Report (n = 1), self-complied questionnaire (n = 1), one study including several questions about the experience of cyber bullying (Gkiomisi et al. 2017), the CYB-AGS cyber-aggressor scale (n = 1) and one study including the European Cyberbullying Intervention Project Questionnaire, which included European countries such as Spain, Germany, Italy, Poland, United Kingdom and Greece (Del Rey et al. 2015).
Cyber-harassment measures included the Cyber-harassment Assessment Scale (n = 2) while one study analysed general items about sexual harassment experienced online (n = 1) (Reed et al. 2020).
3.6. Objectives and Main Findings
Many studies (n = 13) estimated prevalence rates. The number of participants who considered conducting CIV ranged from 8.1% (Caridade et al. 2019) to 93.7% (Sánchez et al. 2015). CDV was the field with the highest rates of perpetration (93.7%), followed by cyberbullying (54.1%).
The prevalence of victimization also differed significantly between research, ranging from 1% (Sánchez et al. 2015) in a study where the authors analysed cyber sexual harassment in young populations in the USA, to 92% (Caridade et al. 2019), also found in the USA study. In terms of different fields, CDV was the field with the highest victimisation rates (92%), followed by cyberbullying.
A European study also found that Romania has registered the highest rate, with 37.3%, in terms of cyberbullying victimisation, and Spain the lowest with 13.3%. In Italy, a study on CDV also found similar rates of perpetration and victimisation in digital psychological violence (67% vs. 64%) and digital relational violence (13% vs. 14.3%).
In the CDV field, the primary outcomes are: the necessity of a conceptual and methodological standardization (Caridade et al. 2019); that dating prevention programs should be included in schools (Smith et al. 2019); the necessity of a qualitative approach; and integration of psycho-educational and intervention programs (Pereira et al. 2016). In the cyberbullying field, the primary outcomes are: cyberbullying can assume several forms; the higher the interaction with parents, the lower the cyberbullying experience rate; it is necessary to develop teaching materials in order to prevent cyberbullying in the academic field (Jun 2020); cyberbullying victimization is associated with social network sites; integrating internet communication technology instruction in educational contexts should be emphasized as a preventive approach (Athanasiou et al. 2018); most cyberbullying is perpetrated by and against friends; and teens practice cyberbullying because it makes them feel funny, famous and influential (Mishna et al. 2010).
3.7. Measures to Assess CIV
One of the main goals of several of the studies examined (n = 6) was developing and validating measures.
A study conducted in Portugal validated the Cyber Dating Abuse Questionnaire (CDAQ) with good reliability (Caridade and Braga 2019). Morelli et al. (2018) validated the cyber dating violence inventory with good reliability in Italy. Overall, all the studies obtained adequate measures through Cronbach’s alpha, ranging from 0.71 (Sánchez et al. 2015) to 0.91 (Caridade et al. 2019). In the cyberbullying field in Spain, Buelga et al. (2020) analysed the psychometric properties of the CYB-AGS cyber-aggressor scale.
4. Discussion
We successfully found 18 studies in the present scoping review. Our results reveal that the interest of the scientific community in the study of cyber violence has increased considerably in the last five years. Other structured literature reviews also found recent interest (Caridade et al. 2019; Flach and Deslandes 2017). This result is something to be expected considering the technological revolution that we have witnessed in recent decades, with teenagers being the primary users of digital tools in their daily lives (Guadix et al. 2018). The current interest in CIV emphasizes the need to find an international construct regarding a problem that affects boys and girls in their interpersonal relationships. Our results corroborated this perspective once we obtained a high variability in the existing instruments regarding dimensions, definitions, methodology, and approach to the cyber violence problem. Contemporary research on CIV has produced highly variable and complex results to interpret, with a considerable amount of content (Caridade et al. 2019; Flach and Deslandes 2017; Guadix et al. 2018; Brown and Hegarty 2018). On the other side, prevalence rates are also variable, with victimization rates ranging from 1% to 92% and perpetration rates between 8.1% (Caridade et al. 2019) to 93.7% (Sánchez et al. 2015).
This variability can be understood by considering the inherent features of the online space where cyber violence occurs, which finds itself undergoing continuous development. The digital world represents an endless opportunity, with vanguardist solutions, both in terms of internet access, progress, and technological advances, including more sophisticated computers, smartphones and other devices. These advances offer the youth new tools but also represent new opportunities for aggression and victimization (Lucero et al. 2014). This progress and development can justify the variability in results, such as the methodology, instruments concept, and the difficulties in developing a solid construct in the cyber violence field.
Different constructs have been used to describe cyber violence, such as cyber sexual harassment, cyber-harassment victimization, cyber dating abuse, cyber dating violence, cyberbullying, cyber violence, electronic aggression and online teen dating violence. Our scoping review found that three fields emerged: CDA/CDV, cyberbullying and cyber-harassment.
Cyber violence areas revealed similar levels of victimization to those detected in in-person violence (Caridade et al. 2019). For that reason, it has been questioned whether cyber violence constitutes a new form of violence or an extension of face-to-face violence (Muñoz-Fernández and Sánchez-Jiménez 2020; Stephenson et al. 2018). In the CDA field, some authors assume the first option and revise their measures to the online context (Morelli et al. 2018); others believe in the second option since cyber violence has unique characteristics that are distinct from face-to-face violence (Peskin et al. 2017). In terms of the cyberbullying context, most authors consider that regardless of the similarities with bullying, cyberbullying has its specific attributes and manners of aggression in the online world (Buelga et al. 2020; Jun 2020). For example, in cyberbullying, cyberspace allows anonymity to the aggressor and, although there is no physical aggression, the audience is much vaster so that the suffering may be more prominent for victims. Lastly, some authors (e.g., Sánchez et al. 2015) consider cyber harassment an extension of face-to-face violence, while others (e.g., Pereira et al. 2016) agree that it has specificities that can only be observed online. For example, young people today face a troubling reality when they come across sexual content shared without permission, which causes harm to young people. In the virtual world, everything is public, so anyone can see and share it, making it practically impossible to completely remove this content. Therefore, CIV can be understood as several abusive typologies (e.g., psychological, physical, sexual, control and direct aggression), such as those found in face-to-face dating violence (Caridade et al. 2019; European Commission 2021; European Institute for Gender Equality 2020).
Different tools were used to measure CDA/CDV, cyberbullying and cyber-harassment. In the CDA/CDV field, six different tools were used. In the cyberbullying field, seven tools were used, and in cyber-harassment, five tools emerged. All the tools were developed and validated for the different proposals, and all used different criteria (e.g., victimization, perpetration or both; specific versus broad behaviours).
Furthermore, five of the studies tried to design and verify measures using exploratory and confirmatory factor analyses to confirm various conceptually different factors. We also found significant differences in other methodological aspects of the studies, namely, the sample size and sampling context and the time assessed (e.g., from the last week to life), which explains the varying prevalence rates. This lack of consensus in terms of conceptions, methods, and methodological aspects can result in a wide range of prevalence estimates, meaning CIV knowledge is currently limited. As a result, there is a higher need for scientific investigation and explanation of CIV (Borrajo et al. 2015; Buelga et al. 2020; Del Rey et al. 2015; Reed et al. 2016; Sánchez et al. 2015).
The evidence demonstrates the importance of focusing on the development of prevention and intervention policies for these different forms of CIV.
CIV is a real problem for our society, with high rates of perpetration and victimization, 63.2% and 58.8%, respectively, in this instance in Portugal (Caridade and Braga 2019). Cyber-harassment perpetration is also very common among adolescents, with perpetration rates of 66.1% (Pereira et al. 2016). Digital psychological violence is also a problem, with levels of perpetration of 67% and victimization of 64%. This could be explained by the fact that some of the authors that have discussed these adolescents often do not recognize the numerous forms of digital emotional abuse and cyber control as violence (Lucero et al. 2014), something that should be further understood and studied, as it will condition responses to the violence process. Some authors are also alert that this fact could lead adolescents, who may be unaware of this, to admit online control behaviours more readily than direct aggression (Caridade et al. 2019).
This scoping review also broadened our understanding of CIV perpetration and victimization-related characteristics. The perpetuation of CIV has been linked to a wide range of factors. Individual factors (demographic, psychosocial, behavioural and psychological) accounted for most of the variables, while others included relationships (peer and family) and community influences (Buelga et al. 2020; Guadix et al. 2018; Peskin et al. 2017). The studies evaluating gender as a specific demographic factor produced mixed results. Some studies (Jun 2020; Pereira et al. 2016; Smith et al. 2018) supported gender differences in CIV perpetration and others (Borrajo et al. 2015; Jun 2020; Smith et al. 2018) showed similar rates of CIV-perpetrating behaviours among males and females. These mixed-gender findings corroborate what has been verified in dating violence in person (Cava et al. 2020) and reveal the need to deepen research in this domain, given the growing gender equity in access to the digital world. More individual factors were assessed, including psychosocial factors such as jealousy and sexist beliefs. In addition, behavioural factors, including bullying perpetration, conduct disorders and drug use, were analysed. Psychological factors were also included, such as narcissism, with findings revealing that they were linked to CIV perpetration (Caridade and Braga 2019; Jun 2020; Peskin et al. 2017). In CIV, these characteristics can become more harmful because, with digital dissemination, it is easier to have followers that share the same beliefs, potentially causing the aggression to be magnified (Lucero et al. 2014).
Many characteristics associated with CIV victimization have been identified, such as depressive symptoms, anxiety, emotional/psychological distress, delinquency, prior cyber victimization, bad grades in school and parental closeness, among others (Buelga et al. 2020; Forbes et al. 2019; Peskin et al. 2017).
Protective factors are explored in this context. Given the importance of correlations in designing intervention and preventative measures, further study in this area is needed (Kowalski et al. 2019; Peskin et al. 2017).
To summarise, it is a vital requirement for additional research to characterise the dimensions that comprise cyber dating violence and other types of CIV, such as cyberbullying and cyber harassment. The studies in the field should pursue a path of standardisation to develop and produce robust and valid instruments that allow us to recognise and compare the prevalence data. This will make it possible to obtain a more inclusive understanding of the phenomenon and encourage possible prevention and intervention programs in schools and universities (Backe et al. 2018). This study is particularly crucial for the adolescent population, which appears to be a highly susceptible group to the impacts of being involved in cyber violence.
Our study has some weaknesses. First, violence through new technologies is an emergent phenomenon that lacks conceptual standardization. Furthermore, due to the variability of terminology available, some manuscripts may not have been selected. The following limitation is closely connected to the analysis of this phenomenon. Due to new violent behaviours, sometimes and in some cases and realities, it is challenging to discover their nature and underlying intentions. For example, impersonation of peers on social media can be recognised as controlling behaviour when it is performed to acquire information about a friend or relation if the intention is to disrupt the partner’s peer relationships. To enable awareness, upcoming measures should accurately describe the measured behaviours. Finally, for a deeper understanding of cyber violence, studies with a longitudinal methodology are necessary. This methodology will allow more precise temporal inferences and more explicit identification of distinct variables such as lifestyle factors or the effects of various types of cyber violence. Longitudinal approaches should prove to be useful in deepening the variables related to CIV. Future studies should also focus on the influence of CIV on adolescents’ lives and whether the impact of CIV varies depending upon the nature of the communications tools used. Such practices are essential to better education and focusing future policy and intervention actions.
5. Conclusions
This scoping review has attempted to gather knowledge of the existing academic literature to reveal the most relevant research trends in cyber violence among youth. In addition, it summarises the available instruments used to measure adolescent cyber violence, such as CDA/CDV, cyberbullying and cyber-harassment. According to our results, CIV can be thought of as a multidimensional construct with sexual and nonsexual behaviours, grouped into different dimensions and among several fields, as stated above. This analysis provides an awareness of cyber violence as an extension of the many forms of face-to-face violence, granting the expression and refinement of new behaviours such as control/monitoring, cyber sexual violence, or public aggression.
Lastly, the current literature uses aggression, abuse and violence as commutable. Authors must define these terms in their theoretical framework; a conceptual and methodological uniformity is required to achieve higher generalizability of the findings in this research field and to prevent and intervene successfully. It is also essential to define how we measure aggression, abuse, or violence among young people. For example, insulting a peer once via technology can be understood as aggression but not considered as abuse. Hence, it would require numerous instances in order to be considered abuse, as with face-to-face abuse. However, nowadays, young people use public broadcasts or videos with sexual content as a form of revenge. In this case, aggression might be considered abuse because there is a clear intention to hurt the victim and the consequences are severe. Future research should analyse if public exposure modulates the perception of aggression or abuse and evaluate the efficiency of prevention and intervention educational programmes, which we believe is the next step for research in this area.
Author Contributions
Conceptualization, B.M. and S.C.; methodology, B.M.; software, B.M.; validation, I.A., P.L.F. and S.C.; formal analysis, B.M.; investigation, B.M.; resources, B.M.; data curation, B.M.; writing—original draft preparation, B.M.; writing—review and editing, S.C.; visualization, I.A.; supervision, P.L.F.; project administration, B.M.; funding acquisition, S.C. All authors have read and agreed to the published version of the manuscript.
Funding
This study was conducted at the Psychology Research Centre (PSI/01662), School of Psychology, University of Minho, supported by the Foundation for Science and Technology (FCT) through the Portuguese State Budget (Ref.: UIDB/PSI/01662/2020).
Data Availability Statement
The database will be made available upon request to barbara.saphira@hotmail.com.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Flowchart of selection of studies. Note: PRISMA figure adapted from Moher, Liberati, Tetzlaff, Altman, The PRISMA Group (Moher et al. 2009); Creative Commons.
Figure 1.
Flowchart of selection of studies. Note: PRISMA figure adapted from Moher, Liberati, Tetzlaff, Altman, The PRISMA Group (Moher et al. 2009); Creative Commons.
Table 1.
Description of studies (n = 18) included in the scoping review protocol.
| Author/s and Publication Year | Location | Sample Characteristics (N, Age) | Objectives | Main Results | Field | Type of Study | ||
|---|---|---|---|---|---|---|---|---|
| Prevalence | Outcomes | |||||||
| Perp. | Vict. | |||||||
| Galende et al. (2020) | Spain | Adolescents (aged 11 to 19 years) |
| NA | NA |
| Cyber Dating Violence | Systematic review |
| Caridade et al. (2020) | Portugal, France and Spain | Students (aged 12 to 30 years) |
| 8.1% to 93.7% (large variety in terms of gender differences) | 5.8% to 92% (large variety in terms of gender differences) |
| Cyber Dating Violence | Systematic review |
| Peskin et al. (2017) | USA | Adolescents (aged 11 to 15 years) N = 424 |
| 15% | NA |
| Cyber Dating Abuse | Survey |
| Smith et al. (2018) | Canada | High school students (aged 14 to 18 years) N = 190 |
| 33% | 35.6% |
| Cyber Dating Violence | Survey |
| Caridade and Braga (2019) | Portugal | University students (average age of 28.41) N = 272 |
| 63.2% online control 66.9% any CDA | 58.8%% online control 59.2% any CDA |
| Cyber Dating Abuse | Cyber Dating Abuse Questionnaire |
| Pereira et al. (2016) | Portugal | Adolescents (aged 12 to 16 years) N = 627 |
| 66.1% | NA |
| Cyber-harassment victimization | Cyber-harassment scale |
| Sánchez et al. (2015) | Spain | Adolescents and young adults (aged 12 to 21 years) N = 626 |
| 93.7% (males have more intrusive behaviours compared with females) | NA |
| Cyber Dating | Mix approach: focus group and survey |
| Morelli et al. (2018) | Italy | Adolescents (aged 13 to 22 years) N = 1405 |
| 67% of digital psychological violence 13% of digital relational violence | 64% of digital psychological violence 14.3% of digital relational violence |
| Cyber Dating Violence | Cyber Dating Violence Inventors |
| Jun (2020) | Korea | Adolescents N (2017) = 4500 N (2018) = 4662 N (2019) = 4779 |
| 54.1% | 57.1% |
| Cyberbullying | National Information Society Agency survey |
| Rebollo-Catalan and Mayor-Buzon (2020) | Spain | Adolescents (aged 13 to 17 years) N = 1468 |
| NA | NA |
| Cyber Violence | Survey |
| Athanasiou et al. (2018) | Germany, Greece, Island, Netherland, Poland, Romania and Spain | Adolescents (aged 14 to 17 years) N = 13,708 |
| NA | Higher rate 37.3% (Romania) and lowest in 13.3% (Spain) |
| Cyberbullying | Survey |
| Caridade et al. (2020) | Portugal | Adolescents and young adults (mean age of 25.36 years) N = 173 |
| 43.4% | 38.2% |
| Cyber Dating Abuse | Survey |
| Mishna et al. (2010) | Canada | Middle and high school students (5th to 12th grade) N = 2186 |
| 33.7% | 49.5% |
| Cyberbullying | Survey |
| Lee et al. (2013) | China | High school students N = 61 |
| NA | NA |
| Cyberbullying | Survey |
| Reed et al. (2020) | USA | Young populations |
| NA | Girls/female 2.5% to 25% Boys/male 0.8% to 24.4% Total 1% to 58.7% |
| Cyber sexual harassment | Review |
| Buelga et al. (2020) | Spain | Adolescents (aged 12 to 16 years) N = 1318 |
| NA | NA |
| Cyberbullying | Adolescent Cyber-Aggressor scale |
| Gkiomisi et al. (2017) | Greece | Adolescents (aged 12 to 15 years) N = 666 |
| NA | 62% |
| Cyberbullying | Survey |
| Del Rey et al. (2015) | Spain, Germany, Italy, Poland, United Kingdom and Greece | Adolescents (aged 11 to 13 years) N = 5679 |
| NA | NA |
| Cyberbullying | Survey |
NA—Not applied; Vict—Victimization; Perp—Perpetration; EFA—Exploratory factor analysis; CFA—Confirmatory Factor Analysis.
Table 2.
Tools used to assess CIV.
| Field | Measures/Author(s) | Author(s)/Year Publication | Scale/Factors (Items) |
|---|---|---|---|
| CDA/CDV | Cyber Dating Abuse Questionnaire, developed from the cyberbullying scales of Litwiller and Brausch (2013) | Smith et al. (2018) | Victimization (8) Perpetration (8) |
| 13 items adapted from previous studies (Zweig et al. 2013). | Peskin et al. (2017) Van Ouytsel et al. (2017) | Perpetration (13) | |
| Cyber Dating Abuse Questionnaire (CDAQ) (Borrajo et al. 2015) | Borrajo et al. (2015) Borrajo and Gámez-Guadix (2016) Caridade and Braga (2019) Van Ouytsel et al. (2016, 2017) García-Sánchez et al. (2017) | Perpetration (20) Victimization (20) Direct aggression (10) Control/monitoring (10) | |
| Cyber Dating Q_A Scale | Sánchez et al. (2015) Sánchez Jiménez et al. (2017) | Perpetration emotional communication strategies (ECS) (7) Online control (OC) (6) Online jealousy (OJ) (4) Online intrusive behavior (OIB) (4) Online intimacy (OI) (3) Cyber dating practices (CP) (4) | |
| Cyber Dating Violence Inventory (CDVI) developed from the Conflict in Adolescent Dating Relationship Inventory (CADRI) (Morelli et al. 2018) | Morelli et al. (2018) | Victimization and perpetration psychological violence (12) Relational violence (10) | |
| Cyber Dating Abuse Victimization (CDAV) (Zweig et al. 2014) | Lu et al. (2018) Zweig et al. (2013, 2014) | Victimization (12) | |
| Cyberbullying | Cyberbullying and Online Aggression (Hinduja and Patchin 2011) and 8 items about dating behaviors | Zerach (2016) | Victimization (9) Perpetration (9) |
| Cyberbullying survey | Jun (2020) | Victimization | |
| Achenbach’s Youth Self Report (YSR) | Athanasiou et al. (2018) | Victimization | |
| Several Questions about Experience of cyber bullying | Mishna et al. (2010) | Victimization Perpetration | |
| Self-Compiled Questionnaire | Lee et al. (2013). | Prevention | |
| CYB-AGS Cyber-Aggressor Scale | Buelga et al. (2020) | Victimisation | |
| European Cyberbullying Intervention Project Questionnaire | Del Rey et al. (2015) | Victimization (11) Aggression (11) | |
| Cyber-harassment | Cyber-Harassment Assessment Scale | Pereira et al. (2016) Spitzberg and Hoobler (2002) | Victimization Perpetration (18) |
| General items about sexual harassment experienced online | Korchmaros et al. (2013) Pew Research Center (2014) | ||
| Unwanted sexual solicitation | Marret and Choo (2017) Chang et al. (2016) Jones et al. (2013) | ||
| Unwanted sexual messages/photos | Sánchez Jiménez et al. (2017) Pew Research Center (2014) Choi et al. (2016) Montiel et al. (2016) | ||
| Sexual messages/images shared without permission | Kearl (2018) Pew Research Center (2014) Powell and Henry (2018) |
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Machado, B.; Caridade, S.; Araújo, I.; Faria, P.L. Mapping the Cyber Interpersonal Violence among Young Populations: A Scoping Review. Soc. Sci. 2022, 11, 207. https://doi.org/10.3390/socsci11050207
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Machado B, Caridade S, Araújo I, Faria PL. Mapping the Cyber Interpersonal Violence among Young Populations: A Scoping Review. Social Sciences. 2022; 11(5):207. https://doi.org/10.3390/socsci11050207
Chicago/Turabian StyleMachado, Bárbara, Sónia Caridade, Isabel Araújo, and Paula Lobato Faria. 2022. "Mapping the Cyber Interpersonal Violence among Young Populations: A Scoping Review" Social Sciences 11, no. 5: 207. https://doi.org/10.3390/socsci11050207
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