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Anales de Psicología

versión On-line ISSN 1695-2294versión impresa ISSN 0212-9728

Anal. Psicol. vol.37 no.2 Murcia may./sep. 2021  Epub 21-Jun-2021

https://dx.doi.org/10.6018/analesps.37.2.338071 

Clinical and Health Psychology

The modelling effect of emotional competence on cyberbullying profiles

Efecto modelador de la competencia emocional en los perfiles de ciberacoso

Joan Guerra-Bustamante1  , Rocío Yuste-Tosina2  , Víctor M López-Ramos1  , Santiago Mendo-Lázaro1 

1 Department of Psychology, Faculty of Teacher Training College, University of Extremadura (Spain).

2 Department of Educational Science, Faculty of Teacher Training College, University of Extremadura (Spain).

Abstract

Emotional competencies are fundamental in preventing involvement in cyberbullying situations. The main goal of this research is to study the involvement profile in cyberbullying situations according to the mediating effect of variables such as perceived emotional intelligence, gender and age in the adult population. To this end, measures are taken through self-reports exploring the profiles of cyberbullying and the dimensions of Perceived Emotional Intelligence (PEI), among a sample of 848 subjects enrolled in Massive Open Online Courses (MOOCs), ages between 21 and 62 years (M = 40.52; SD = 11.65). Measures are taken through self-reports that explore cyberbullying profiles (Victim 18.9%, Aggressor 12.3%, Victim / Aggressor 16.3% and Without profile 52.6%), and the dimensions of Perceived Emotional Intelligence (Attention, Clarity and Repair). Multivariate and binomial regression analyses are carried out, showing that the majority of participants who have difficulties in understanding and regulating their emotional states are involved in situations of cyberbullying, and pointing to emotional intelligence skills as a clear protective factor against cyberbullying. These results show the need to pay greater attention to the phenomenon of cyberbullying in the adult population, as well as the relevance of emotional intelligence skills in the prevention of cyberbullying.

Key words: Cyberbullying; Emotional intelligence; Cyberbullying profiles; Adults

Resumen

Las competencias emocionales son fundamentales en la prevención de la implicación en situaciones de ciberacoso. En el presente trabajo, se plantea como principal objetivo, estudiar el perfil de implicación en situaciones de ciberacoso en función del efecto mediador de las variables inteligencia emocional percibida, género y edad en población adulta. Para ello, en una muestra de 848 sujetos matriculados en “Cursos Abiertos Masivos en Línea” MOOC, se toman medidas a través de autoinformes que exploran los perfiles de ciberacoso y las dimensiones de Inteligencia Emocional Percibida (IEP). Se llevan a cabo análisis multivariado y de regresión binomial, que muestran que la mayoría de los participantes que presentan dificultades para comprender y regular sus estados emocionales están implicados en situaciones de ciberacoso y señalan a las habilidades de inteligencia emocional como un claro factor de protección del ciberacoso. Estos resultados demuestran la necesidad de prestar mayor atención al fenómeno del ciberacoso en población adulta y la relevancia de las habilidades de inteligencia emocional en la prevención del ciberacoso.

Palabras clave: Ciberacoso; Inteligencia emocional; Perfiles de ciberacoso; Adultos

Introduction

Emotional intelligence is an important and rapidly growing area of research at the current time (Fernández-Berrocal et al, 2018), although its conceptualisation and measurement are the source of some controversy (Mayer et al, 2008). Nonetheless, one of the most widely used definitions views emotional intelligence as the ability to control emotions, differentiate them and use the resulting information to guide thoughts and behaviour (Salovey & Mayer, 1990), or, more specifically, the ability to perceive emotions, access and generate emotions facilitating thought, understand and be aware of emotions, and regulate emotions (Mayer & Salovey, 2007).

Research on emotional intelligence began in the 1990s and was led by Salovey and Mayer (1990), although it was not until the end of the last decade and beginning of the current decade that the first concrete attempts were made to empirically observe its effects on people (Extremera & Fernández-Berrocal, 2004), such as improving intrapersonal and interpersonal wellbeing and fostering an ability to control one’s own emotions and those of others in a given situation (Rauf et al, 2013).

Research has focused on establishing the usefulness of the construct in a number of key areas, with the aim of demonstrating the ways in which it shapes behaviour and the areas in which it has a significant influence (Extremera & Fernández-Berrocal, 2004). The emotional intelligence skills described in Mayer and Salovey’s (1997) model are emotional perception, emotional understanding, emotional facilitation and emotional regulation. These skills influence various spheres of life. Thus, the ability for emotional repair (Hodzic et al, 2016) interacts with stress in predicting life satisfaction in high-stress situations: subjects with the poorest emotional repair skills are less satisfied with their lives. Meanwhile, a negative correlation is observed between neuroticism and various aspects such as emotional management and control (Enríquez, 2011), as people with greater emotional intelligence also display greater empathy and lower levels of emotional inhibition (Ramos et al, 2007).

It is important to emphasise the correlation between emotional intelligence and social relations (Martin-Raugh et al, 2016). Statistically significant differences in terms of patterns of social behaviour have been observed between profiles, with subjects belonging to groups with high overall emotional intelligence and high levels of emotional regulation displaying higher scores in positive social behaviours (Gázquez et al, 2015). The ability to regulate emotions is associated with a healthy personality. In a study examining the optimum profile for extrinsic regulation, inter-regulation or hetero-regulation (Company et al, 2012), the authors observed that it consisted of aspects such as high situation modification, the ability to de-dramatise and distract oneself, the ability to make a cognitive change at the appropriate time, the absence of repression of others, the ability to avoid uncontrolled interactions, the ability to avert conflict, and high expression regulation or assertiveness.

There is, therefore, a correlation between emotional intelligence and positive or disruptive social behaviour. Some studies (Saadi et al, 2012) show that training in emotional intelligence reduces aggression and enhances the capacity for individual and social adaptation. This data demonstrates the necessity of implementing programmes to develop and improve emotional intelligence on a preventive basis in order to avoid violence.

Through its constructs, emotional intelligence allows the socioemotional characteristics influencing different behaviours linked to cyberbullying profiles to be ascertained (Bernal & Ramírez, 2019). In this respect, it is important to consider the significant rise in cases of cyberbullying associated with the development of new information technologies and the emotional backdrop underpinning the issue. The use of Information and Communications Technology (ICT) is an inherent part of modern societies, providing a tool facilitating necessary processes of communication and socialisation (Polo del Río et al, 2017) and helping to maintain interpersonal relations, forge emotional bonds and foster closeness in communication (Colás et al, 2013). The spread of this form of technology has displaced traditional spaces for socialisation (Díaz-Gandasegui, 2011), leading to changes to conventional types of bullying (Heirman & Walrave, 2009), with new characteristics such as the anonymity of the aggressor, the scope and size of the audience and the inability to escape (Valera, 2012). Cyberbullying can extend into the victim’s own home, removing the existence of safe spaces and provoking a sense of helplessness and vulnerability (Polo del Río et al, 2017). This form of abuse occurs in the context of other cyberbullying behaviours based on the relationship of domination/submission between the individual abusing his or her power and the target of their abuse (Avilés et al, 2011). It consists of intentional, recurrent aggression, drawing regularly on digital forms of social contact to reach the victim (León et al, 2012).

Cyberbullying may therefore be defined as the use of ICT, especially mobile telephones, to harass peers (Garaigordobil & Aliri, 2013). In this context, the intensive use of smartphones is a source of concern (Gómez et al, 2014) as it conditions social relationships (Bianchi & Phillips, 2005; Kamibeppu & Sugiura, 2005) and leads to behavioural, emotional and social problems (Pedrero et al, 2012). It is for this reason that increasing numbers of researchers are conducting research with the aim of exploring the consequences when cyberbullying is mediated by the use of information and communications technology (Elipe et al., 2012). As we know, cyberbullying has a significant impact on coexistence, because it replaces mutual respect and moral reciprocity with abusive forms of domination and submission (Ortega, 2010). In this regard, some studies link emotional intelligence to cyberbullying, aiming to detect deficiencies in emotional competencies and maladjustment in aggressive individuals in order to design specific interventions to improve their condition (Montoya et al, 2011). With this in mind, being a victim of cyberbullying can lead to significant emotional and psychological imbalances, affecting areas of great importance such as life satisfaction (García et al, 2019).

Research has demonstrated a correlation between high levels of antisocial behaviour and involvement in cyberbullying in any role (as a victim, aggressor or spectator) and the use of more aggressive strategies as a way to resolve interpersonal conflicts (Garaigordobil, 2017). In this context, perceived emotional intelligence is a moderating variable between cybervictimisation and emotional impact, as it either increases or reduces this impact, while cyberbullying provokes negative emotions in victims (Elipe et al, 2015). In any case, a deficiency in the ability to perceive the emotions of others may lead individuals to attribute erroneous intentions to other people in social interactions and to assess situations in a more negative manner than an individual with good emotional perception skills (García-Sancho et al, 2015). It also gives rise to a lack of social self-efficacy and low levels of social development in aggressors (Romera et al, 2016)

On the basis of this empirical evidence, cyberbullying encompasses emotional indicators, such as emotional distress among victims and aggressors (Ybarra & Mitchell, 2004), which suggest that it may indicate a lack of empathy (Ortega et al, 2009). It is important to note that there is a correlation between suffering bullying and subsequently perpetrating it (Avilés et al., 2011; Romera, Del-Rey & Ortega, 2011), as cybervictimisation is linked to involvement in bullying as an aggressor (Elipe et al, 2012). A study focusing on secondary school pupils showed that individuals involved in bullying are perceived as unable to manage their emotions, with the victims displaying the weakest ability to understand and manage them (Elipe, 2012).

Other relevant aspects to consider when studying cyberbullying are gender and age differences. With regard to gender, the data are inconclusive. Some studies find no correlation between the two variables (Finn, 2004). Others observe a significant association between cyberbullying and gender (Li, 2006), noting that men commit more acts of cyberbullying (as the aggressors) while women tend to occupy the role of the victim (Calvete et al, 2010; Finn & Banach, 2000). Meanwhile, the age variable has been the main focus of research on cyberbullying to date. Studies have shown a particular interest in cyberbullying among adolescents and university students (Sticca, Ruggieri, Alsaker & Perren, 2013; Elipe, 2012), who are considered to be the groups most at risk (Weare, 2004). However, recent research has demonstrated that adults who participate in cyberbullying display higher incidences of behaviours classified as verbal abuse (Betts et al, 2019).

This article aims to explore the phenomenon of cyberbullying and provide information on its prevalence in adults in terms of gender and age. Drawing on previous research among children, adolescents and young people, the main objective of this article is to use logistic regression analysis to investigate the mediating effect of emotional intelligence in relation to cyberbullying among adults, creating models to predict cybervictimisation and cyberaggression based on inadequate Perceived Emotional Intelligence (PEI). In this context, and in light of empirical evidence linking deficiencies in emotional intelligence with cyberbullying, the authors hope to uncover differences based on the involvement profile.

Methodology

Participants

Sampling was not probabilistic for the sake of convenience, as the aim of the researchers was to gain access to the largest possible number of adult subjects with knowledge of and access to information technologies. In order to achieve this, 5,300 subjects enrolled on a MOOC (Massive Open Online Course) were invited to participate. A total of 848 Spanish-speaking adults of 15 nationalities (14 Latin American n = 478; and Spanish n = 370) were recruited, of whom 79.9% were women and 23.1% were men, with an average age of 40.52 (SD = 11.65). 45% of the sample were aged between 21 and 30 (young adults: M = 24.45; SD = 2.91) while 55% were aged between 31 and 62 (adults: M = 45.45; SD = 8.43).

Instruments

European Cyberbullying Intervention Project Questionnaire (ECIPQ). To establish types of involvement in cyberbullying, the Spanish version (Ortega-Ruiz et al, 2016) of the European Cyberbullying Intervention Project Questionnaire (ECIPQ) (Del Reyet al., 2015) was used. The ECIPQ encompasses 22 items with a Likert-type scale offering five response options, ranging from 0 to 4 (0 = never, 1 = once, 2 = once or twice a month, 3 = around once a week, and 4 = more than once a week). The questionnaire examines two dimensions: cybervictimisation and cyberaggression, with high levels of reliability (total α = .87, victimisation α = .80, aggression α = .88). For both dimensions, the items refer to actions such as swearing, spreading rumours, impersonating others, etc., all via electronic media and covering the two months prior to participation in the study. The profiles - victim, aggressor, victim/aggressor and no profile (not involved) - were identified by cross-referencing the responses to both questions. Participants were considered to be victims if they scored ≥2 on victimisation and 0 on aggression; aggressors if they scored 0 on victimisation and ≥2 on aggression; victim-aggressors if they scored ≥2 on both dimensions; and no profile (not involved) if they scored ≤1on both dimensions.

Trait Meta Mood Scale-24, (TMMS-24) (Salovey & Mayer, 1990). In order to evaluate perceived emotional intelligence, the Spanish version of the Trait Meta Mood Scale-24 questionnaire was used (TMMS-24, Fernández-Berrocal et al., 1998). This instrument allows perceived intrapersonal emotional intelligence to be measured or, in other words, it provides a personal assessment on reflexive aspects of individual emotional experience (Salovey, Mayer, Goldman, Turvey & Palfai, 1995). The questionnaire includes 24 items, with a Likert-type scale offering 5 response options (1= Strongly disagree, 5= Strongly agree). It assesses three different dimensions (8 items per dimension): Attention to feelings (the ability to feel and express feelings adequately); Clarity of feelings (understanding of emotional states) and Mood repair (adequate emotional regulation). The reliability for each component is Attention (α = 0.90); Clarity (α = 0.90); Repair (α = 0.86), demonstrating adequate test-retest reliability.

Procedure

MOOCs offer thousands of adults the opportunity to access online courses free of charge. These educational programmes allowed us to access a sample of adults who use information technologies. Via the miradax.net platform, students enrolled on MOOCs in July 2017 were asked to participate in the study. The TMMS-24 and ECIPQ questionnaires were administered online via the Google Forms application (a Google Drive tool). In accordance with the ethical guidelines issued by the American Psychological Association (APA, 2009), all participants gave their informed consent before completing the questionnaires, guaranteeing the anonymity and confidentiality of the data and their exclusive use for research purposes.

Data analysis

The SPSS 21.0 programme was used to perform statistical analysis on the collected data. The reliability of the instruments used was calculated using Cronbach's alpha. Descriptive analyses were carried out and, after checking assumptions of normality and homocedasticity, a multivariate analysis (MANOVA) and binomial regression analysis were performed.

Results

Firstly, the distribution of the participants on the basis of their cyberbullying profiles and levels of Attention, Clarity and Repair is presented (Table 1).

Table 1:  Distribution of participants on the basis of cyberbullying profiles and levels of Attention, Clarity and Repair. 

With regard to cyberbullying, it is relevant to note that almost half of the participants had experienced cybervictimisation or cyberaggression: 35.2% of the participants had suffered cyberbullying, while 28.6% admitted to perpetrating cyberbullying (Table 1). Comparisons of these percentages revealed differences by gender, χ2 = 16.611(3), p < .001, in the profiles of victim (women = 17.2%; men = 24.5%), aggressor (women = 13.5%; men = 8.2%) and no profile (women = 54.9%; men = 44.9%), and age, χ2 = 30.041(3), p < .001, in the profiles of aggressor (young people = 18.3%; adults = 9.6%), victim-aggressor (young people = 25.8%; adults = 14.2%) and no profile (young people = 38.7%; adults = 57.1%).

With regard to PEI, comparisons of the attention, clarity and repair groups with the cyberbullying profile showed differences in Clarity, χ2 = 56.584(6), p < .001, and Repair, χ2 = 36.091(6), p < .001, and were equivalent in Attention, χ2 = 4.184(6), p = .652. In this respect, 73.1% of the subjects involved in cyberbullying required improvement in terms of Clarity while 92.3% needed to improve their Repair (Table 1).

In order to confirm whether the TMMS-24 displayed any differences in relation to the cyberbullying profile, a multivariate analysis (MANOVA) was performed, which revealed significant multivariate main effects of the profile on the analysed variables (Wilks λ = .877, F(9. 2049) = 12.635, p < .001, ƞ = .043). The univariate contrasts demonstrate the existence of a significant main effect of the cyberbullying profile on the factors Clarity (F(3. 844) = 34.713, p < .001, ƞ = .110) and Repair (F(3. 844) = 17.169, p < .001, ƞ = .058). In addition, the multiple comparisons performed indicate that in both the Clarity and Repair factors on the TMMS-24: 1) the subjects without a specific profile obtained higher scores (p < .05) than subjects with victim and victim/aggressor profiles (Clarity: No profile-Victim p < .001; No profile-Victim/aggressor, p < .001; Repair: No profile-Victim, p = .011; No profile-Victim/aggressor, p < .001). 2) aggressors obtained higher scores (p < .05) than victim/aggressors (Clarity, p = .018; Repair, p = .005).

Once the existence of a correlation between emotional intelligence and the four cyberbullying profiles had been confirmed, the researchers attempted to ascertain whether or not emotional intelligence was able to significantly predict victimisation and cyberaggression. In order to determine the TMMS-24 variables which most precisely predict cyberbullying, a binary logistic regression analysis was performed (Table 2). The analysis included the factors Attention, Clarity and Repair as predictor variables, grouped as dichotomous variables (pays: little attention; excessive attention; inadequate clarity or inadequate repair, yes/no).

Table 2:  Results of the logistic regression analysis for predicting cybervictimisation and cyberaggression on the basis of inadequate EI. 

Three predictive models were created (Table 2). The predictive model for cybervictimisation allows a correct estimate to be made in 67.7% of cases (χ2 = 47,546(4), p < .001), while the model for cyberaggression allows for a correct estimate in 71% of cases (χ2 =29.329(4). p < .001) and the model for cybervictimisation/aggression allows for a correct estimate in 83.7% of cases (χ2 =39.982(4). p < .001). The setting value for the models was between 5.5% and 7.5% for the victimisation model (Cox & Snell R2 = .055; Nagelkerke R2 = .075), between 3.4% and 4.9% for the aggression model (Cox & Snell R2 =.034; Nagelkerke R2 = .049) and between 4.6% and 7.8% for the victimisation/aggression model (Cox & Snell R2 =.046; Nagelkerke R2 = .078). The odds ratios for the logistic models show that: 1) the probability of being a victim is 77.6%, 166% and 170 % greater in subjects with excessive attention, inadequate clarity and inadequate repair respectively, 2) the probability of being an aggressor is 136% greater in subjects with inadequate clarity and 190% greater in subjects with inadequate repair, 3) the probability of being a victim/aggressor is 118% greater in subjects with excessive attention and 330% greater in those with inadequate clarity.

Discussion

The aim of this study was to investigate the correlation between PEI and cyberbullying in adults. Firstly, the distribution of the participants on the basis of their cyberbullying profiles and PEI was analysed, examining potential differences in the various cyberbullying profiles by gender and age. After the presence of differences in PEI between individuals who were involved and not involved in cyberbullying was confirmed, the mediating effect of emotional intelligence on the profiles involved in cyberbullying - victim, aggressor or victim/aggressor - was analysed.

With regard to cyberbullying, the study followed the approach taken by previous studies (Elipe et al., 2009; Polo et al., 2017) by differentiating between subjects who were involved and not involved in cyberbullying, as well as dividing those involved by profile: victims, aggressors and victim/aggressors. Almost half of the participants had been involved in cyberbullying in the two months prior to the study. This demonstrates that the rise of cyberbullying and the normalisation of violent behaviour exerted via social media and electronic devices (Li et al., 2012) affects both young people and adults.

In terms of the influence of gender and age on cyberbullying, the findings of previous studies have been inconsistent and even divergent on the matter of gender.

A number of studies observe no differences by gender (Finn, 2004; Katzer et al., 2009; Sentse et al., 2015). Others demonstrate that men are more commonly involved than women (Durán & Martínez, 2015; Navarro et al., 2016), while others still indicate the contrary (Holfeld & Grabe, 2012). However, in most cases, as in this study, the findings corroborate the presence of gender differences in cyberbullying. More specifically, the results show that while the percentage of women involved in cyberbullying is generally lower than that of men, the percentage of female aggressors and male victims is higher. This corroborates the findings of other studies, which observed that men are more likely to be victims of cyberbullying than women, (Gofin & Avitzour, 2012; Pelfrey & Weber, 2013), diverging from those which found that women are more often victims (Brighi et al., 2012; Fenaughty & Harré, 2013; Olenik-Shemesh et al., 2012). Another group of studies observe no differences in victimisation by gender (Caballo et al., 2012; Monks et al., 2012). It is thus difficult to generalise on the relationship between gender and cyberbullying.

In terms of age, the findings demonstrate far greater involvement in cyberbullying as aggressors and victim/aggressors among young people. This confirms that young people are the group at greatest risk (Weare, 2004), as their use of mobile telephones is more extensive than that of people in other age groups (Kubey et al., 2001; Morahan-Martin & Schumacher, 2000; Treuer et al., 2001). However, no differences were found with regard to involvement as a cybervictim, suggesting that both age groups experience similar levels of vulnerability to cyberbullying and indicating that victimisation is a particularly relevant variable when studying cyberbullying in adults.

With regard to the comparisons between PEI and cyberbullying profiles, it is relevant to note that most of the participants in the study whose Clarity and Repair needed improvement, that is, those who had difficulty understanding and regulating their emotional states, were involved in cyberbullying. Among those involved, victims and victim/aggressors displayed the lowest levels of understanding and regulation of their emotional states. On this matter, a number of studies indicate the presence of significant differences between those involved and not involved in bullying, with those involved displaying poorer emotional repair skills. Victims in particular are characterised by greater attention and poorer clarity and repair (Elipe et al., 2009).

Moreover, the results of the regression analysis confirm that PEI is useful in distinguishing between the various profiles of subjects involved in cyberbullying among adults, largely corroborating prior research focusing on younger people (Ortega et al, 2009). In the case of victims more specifically, they may be differentiated from other individuals involved in cyberbullying by their intense attention to their emotions and weak ability to understand and regulate their own emotions. Meanwhile, aggressors are characterised by poor skills in understanding and regulating their own emotions, confirming the lack of social self-efficacy present in this group (Romera et al., 2016). On this matter, Guerra et al. (2019) find that individuals with poor clarity and weak emotional repair skills are most likely to perceive themselves as unhappy, which could go some way to explaining the relationship between an inadequate PEI and aggressive behaviour and cyberbullying.

On the other hand, victim/aggressors differ from the other profiles due to their excess of emotional attention and weak ability to understand their own emotions. These findings corroborate other studies which associate high attention with inadequate clarity (Extremera & Fernández-Berrocal, 2005) and demonstrate a clear link between clarity and repair (Extremera et al., 2007). They also show that, given the correlation between being a victim of cyberbullying and subsequently perpetrating it (Avilés et al., 2011; Elipe et al. 2012; Romera et al., 2011), it is relevant to identify individuals who are victim/aggressors and differentiate them from those who are either victims or aggressors when researching the phenomenon (Polo et al. 2017). However, it is important to recall that a deficiency in the ability to perceive emotions makes it more difficult to interpret others’ intentions, giving rise to potential errors in evaluating certain behaviours (García-Sancho et al., 2015). This offers a partial explanation for the fact that it is inadequate clarity which has predictive power over the three cyberbullying profiles analysed.

Among the limitations of this study, it is important to emphasise the bias inherent in the use of self-reports as a single data collection method, as well as the bias inherent in the transversal study design, which makes it more difficult to make greater inferences on the correlation between the study variables. Meanwhile, the scarcity of previous research on cyberbullying among adults hinders discussion of the findings, while confirming the innovative nature of research on this topic. Despite these limitations, these findings may serve as a starting point for subsequent studies, demonstrating the need to pay closer attention to the phenomenon of cyberbullying among adults and to study it in greater depth, while also enhancing training and prevention programmes aimed at both young people and adults.

Finally, given the significance of emotional intelligence as a factor in protecting individuals from cyberbullying, it is recommended that emotional education is incorporated into any actions taken to prevent and/or minimise cyberbullying behaviours. In this regard, Kırcaburun et al. (2019) highlight the importance of implementing programmes for adults to improve social connection, self-esteem and group membership and reduce depression as a protective element against participation in cyberbullying.

References

Avilés, J. M., Irurtia, M. J., García-López, L. J., & Caballo, V. E. (2011). El maltrato entre iguales: “Bulling” (El maltrato entre iguales: “Bulling”). Psicología Conductual, 19, 57-90. [ Links ]

Bernal, N. C., & Ramírez, F. C. (2019). El programa CIE: intervención en ciberacoso escolar mediante el desarrollo de la inteligencia Emocional (The CIE program: intervention in school cyberbullying through the development of Emotional intelligence). European Journal of Health Research:(EJHR), 5(1), 39-49. [ Links ]

Berrocal, P., Ruiz-Aranda, D., Salguero, J. M., Palomera, R. & Extremera, N. (2018). The Relationship of Botín Foundation's Emotional Intelligence Test (TIEFBA) with Personal and Scholar Adjustment of Spanish Adolescents. Revista de Psicodidáctica, 23(1), 1-8. [ Links ]

Betts, L. R., Baguley, T. & Gardner, S. E. (2019). Examining adults’ participant roles in cyberbullying. Journal of Social and Personal Relationships. [ Links ]

Bianchi, A. & Phillips, J. G. (2005). Psychological Predictors of Problem Mobile Phone Use. Cyberpsychology & Behavior, 8, 39-51. [ Links ]

Brighi, A., Guarini, A., Melotti, G., Galli, S. & Genta, M. L. (2012). Predictors of victimization across direct bullying, indirect bullying and cyberbullying. Emotional Behavioural Difficulties, 17, 375-388. [ Links ]

Caballo, V. E., Calderero, M., Arias, B., Salazar, I. C. & Irurtia, M. J. (2012). Desarrollo y validación de una nueva medida de autoinforme para evaluar el acoso escolar (Bullying) (Development and validation of a new self-report measure to assess bullying). Psicología Conductual, 20, 625-647. [ Links ]

Calvete, E., Orue, I., Estévez, A., Villardón, L. & Padilla, P. (2010). Cyberbullying in Adolescents: Modalities and Aggressors’ Profile. Computers in Human Behavior, 26, 1128-1135. [ Links ]

Colás, P., González, T. & De Pablos, J. (2013). Juventud y redes sociales: Motivaciones y usos preferentes (Youth and social networks: Motivations and preferential uses). Comunicar, 40, 15-23. [ Links ]

Company, R., Orbest, U. & Sánchez, F. (2012). Regulación emocional interpersonal de las emociones de ira y tristeza (Interpersonal emotional regulation of the emotions of anger and sadness). Boletín de Psicología, 104, 7-36. [ Links ]

Del Rey, R., Casas, J. A., Ortega-Ruiz, R., Schultze-Krumbholz, A., Scheithauer, H., Smith, P. & Guarini, A. (2015). Structural validation and cross-cultural robustness of the European Cyberbullying Intervention Project Questionnaire. Computers in Human Behavior, 50, 141-147. [ Links ]

Díaz-Gandasegui, V. (2011). Mitos y realidades de las redes sociales. Información y comunicación en la Sociedad de la Información (Myths and realities of social networks. Information and communication in the Information Society). Prisma Social, 6, 1-26. [ Links ]

Durán, M. & Martínez, R. (2015) Ciberacoso mediante teléfono móvil e Internet en las relaciones de noviazgo entre jóvenes (Cyberbullying through mobile phones and the Internet in dating relationships among young people). Comunicar, 22(44), 159-167. [ Links ]

Elipe, P., Ortega, R., Hunter, S. C. & Del Rey, R. (2012). Inteligencia emocional percibida e implicación en diversos tipos de acoso escolar (Perceived emotional intelligence and involvement in various types of bullying). Psicología Conductual, 20(1), 169-181. [ Links ]

Elipe, P., Mora-Merchán, J. A., Ortega, R. & Casas, J. A. (2015). Perceived Emotional Intelligence as a Moderator Variable between Cybervictimization and Its Emotional Impact. Frontiers in Psychology, 6, 486. [ Links ]

Enríquez, H. (2011). Inteligencia emocional plena: Hacia un programa de regulación emocional basado en la conciencia plena(Inteligencia emocional plena: Hacia un programa de regulación emocional basado en la conciencia plena) (doctoral thesis). Universidad de Málaga. [ Links ]

Extremera, N. & Fernández-Berrocal, P. (2004). Inteligencia emocional, calidad de las relaciones interpersonales y empatía en estudiantes universitarios (Emotional intelligence, quality of interpersonal relationships and empathy in university students). Clínica y Salud, 14, 117-137. [ Links ]

Extremera, N. & Fernández-Berrocal, P. (2005). Inteligencia emocional percibida y diferencias individuales en el metaconocimiento de los estados emocionales: una revisión de los estudios con el TMMS (Perceived emotional intelligence and individual differences in meta-knowledge of emotional states: a review of studies with the TMMS). Ansiedad y estrés, 11(2-3), 101-122. [ Links ]

Fenaughty, J. & Harré, N. (2013). Factors associated with distressing electronic harassment and cyberbullying. Computers in Human Behavior, 29, 803-811. [ Links ]

Fernández-Berrocal, P., Ruiz-Aranda, D., Salguero, J. M., Palomera, R., & Extremera, N. (2018). La relación del Test de Inteligencia Emocional de la Fundación Botín (TIEFBA) con el ajuste personal y escolar de adolescentes españoles (The relationship of the Botín Foundation Emotional Intelligence Test (TIEFBA) with the personal and school adjustment of Spanish adolescents). Revista de Psicodidáctica, 23(1), 1-8. [ Links ]

Finn, J. (2004). A survey of Online Harassment at a University Campus. Journal of Interpersonal Violence 19, 468-483. [ Links ]

Finn, J. & Banach, M. (2000). Victimization Online: The Down -side of Seeking Human Services for Women on the Internet. Cyber Psychology & Behavior, 3, 785-797. [ Links ]

Garaigordobil, M. & Aliri, J. (2013). Ciberacoso ("cyberbullying") en el país vasco: Diferencias de sexo en víctimas, agresores y observadores (Cyberbullying in the Basque Country: Sex differences in victims, aggressors and observers). Psicología Conductual, 21(3), 461. [ Links ]

Garaigordobil, M. (2017). Conducta antisocial: conexión con bullying/cyberbullying y estrategias de resolución de conflictos (Antisocial behavior: connection with bullying / cyberbullying and conflict resolution strategies). Psychosocial Intervention, 26(1), 47-54. [ Links ]

García, L., Quintana-Orts, C., & Rey, L. (2019). Cibervictimización y satisfacción vital en adolescentes: la inteligencia emocional como variable mediadora (Cybervictimization and life satisfaction in adolescents: emotional intelligence as a mediating variable). Revista de Psicología Clínica con Niños y Adolescentes encia emocional como variable mediadora. Retrieved from http:// www.revistapcna.com/sites/default/files/1915.pdfLinks ]

Gofin, R. & Avitzour, M. (2012). Traditional versus internet bullying in junior high school students. Maternal and Child Health Journal, 16, 1625-1635. [ Links ]

Romera, E. M., Cano, J. J., García-Fernández, C. M. & Ortega-Ruiz, R. (2016). Cyberbullying: competencia social, motivación y relaciones entre iguales (Cyberbullying: Social Competence, Motivation and Peer Relationships). Comunicar, 24(48), 71. [ Links ]

García-Sancho, E., Salguero, J.M. & Fernández-Berrocal, P. (2015). Déficits en el reconocimiento facial de las emociones y su relación con la agresión: Una revisión sistemática (Deficits in facial recognition of emotions and their relationship with aggression: A systematic review). Ansiedad y Estrés, 19(5), 584-591. [ Links ]

Gázquez, J. J., Pérez-Fuentes, M.C., Díaz-Hierro, A., García-Fernández, J.M. & Inglés, C. J. (2015). Perfiles de inteligencia emocional y conducta social en adolescentes españoles (Profiles of emotional intelligence and social behavior in Spanish adolescents). Psicología Conductual, 23(1), 141-160. [ Links ]

Gómez, P., Rial, A., Braña, T., Varela, J. & Barreiro, C. (2014). Evaluation and early detection of problematic Internet use in adolescents. Psicothema, 26, 21-26. [ Links ]

Guerra, J., León, B., Yuste, R., López, V., & Mendo, S. (2019). Emotional Intelligence and Psychological Well-Beingin Adolescents. Int. J. Environ. Res. Public Health, 16, 1720. https://doi.org/10.3390/ijerph16101720. [ Links ]

Heirman, W. & Walrave, M. (2009). Asseing Issues and Concerns about the Mediation of Technology in Cyberbullying. Trípodos Extra 1, 317-329. [ Links ]

Hodzic, S., Balagué, P. R., Costa, H. & Zenasni, F. (2016). ¿Los estudiantes con una mayor inteligencia emocional son más resistentes al estrés? El efecto modulador de la atención, la claridad y la reparación emocional (Are students with higher emotional intelligence more resistant to stress? The modulating effect of attention, clarity and emotional repair). Psicología Conductual, 24(2), 253-272. [ Links ]

Holfeld, B. & Grabe, M. (2012). An examination of the history, prevalence, characteristics, and reporting of cyberbullying in the United States. Q. Li, D. Cross, & P.K. Smith (editors), Cyberbullying in the global playground: Research from international perspectives (117-142). USA: Blackwell Publishing Ltd. [ Links ]

Instituto Nacional de Estadística (INE) (2014). Encuesta sobre Equipamiento y Uso de Tecnologías de Información y Comunicación en los Hogares (TIC-H) (Encuesta sobre Equipamiento y Uso de Tecnologías de Información y Comunicación en los Hogares (TIC-H).). Madrid: Instituto Nacional de Estadística. Retrieved from http://www.ine.es/prensa-/np864.pdfLinks ]

Katzer C., Fetchenhauer, D. & Belschak, F. (2009). Cyberbullying: Who are the victims? A comparison of victimization in Internet chatrooms and victimization in school. Journal of Media Psychology, 21, 25-36. [ Links ]

Kamibeppu, K. & Sugiura, H. (2005). Impact of the mobile phone on junior high-school students´ friendships in the Tokio metropolitan area. Cyberpsychology & Behaviour, 8, 121-130. [ Links ]

Kırcaburun, K., Kokkinos, C. M., Demetrovics, Z., Király, O., Griffiths, M. D., & Çolak, T. S. (2019). Problematic online behaviors among adolescents and emerging adults: Associations between cyberbullying perpetration, problematic social media use, and psychosocial factors. International Journal of Mental Health and Addiction, 17(4), 891-908. [ Links ]

Kubey, R. W., Lavin, M. J. & Barrows, J. R. (2001). Internet use and collegiate academic performance decrements: early findings. Journal of Communication, 51, 366-382. [ Links ]

León, B., Felipe, E., Fajardo, F. & Gómez, T. (2012). Cyberbullying in a sample of secondary students: modulating variables and social networks. Electronic Journal of Research in Educational Psychology, 10, 771-788. [ Links ]

Li, Q. (2006). Cyberbullying in schools: a research of gender differences. School Psychology International, 27, 157-170. [ Links ]

Li, Q., Smith, P.K., & Cross, D. (2012) Research into Cyberbullying: Context. Q. Li, D. Cross & P.K. Smith (editors), Cyberbullying in the Global Playground: Research from International Perspectives(3-12). Wiley-Blackwell. [ Links ]

Martin-Raugh, M. P., Kell, H. J. & Motowidlo, S. J. (2016). Prosocial knowledge mediates effects of agreeableness and emotional intelligence on prosocial behavior. Personality and Individual Differences, 90, 41-49. [ Links ]

Mayer, J. D., Roberts, R. D. & Barsade S.G. (2008). Human Abilities: Emotional Intelligence. The Annual Review of Psychology, 59, 507-536. [ Links ]

Mayer, J. D. & Salovey, P. (1997). What is Emotional Intelligence? En P. Salovey & D. Sluyter (Eds.), Emotional Development and Emotional Intelligence: Implications for Educators (3-34). New York: Basic Books. [ Links ]

Mayer, J. D., Salovey, P. & Caruso, D. R. (2000). Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) item blocket, Research version. Toronto-Ontario, Canada: MHS Publishers. [ Links ]

Mayer, J. D. & Salovey, P. (2007). Mayer-Salovery-Caruso emotional intelligence test. Multi-Health Systems Incorporated. [ Links ]

Monks, C. P., Robinson, S. & Worlidge, P. (2012). The emergence of cyberbullying: a survey of primary school pupils' perceptions and experiences. School Psychology International, 33, 477-491. [ Links ]

Montoya, I., González, R. & Palanca, C. (2011). Educación emocional y violencia escolar. P., Fernández-Berrocal, N., Extremera, R., Palomera, D., Ruiz-Aranda, J.M., Salguero & R., Cabello (coordinators). Inteligencia Emocional: 20 años de investigación y desarrollo (Emotional Intelligence: 20 years of research and development). II Congreso de Inteligencia Emocional (443-448). Santander: Fundación Botín. [ Links ]

Morahan-Martin, J. & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among college students. Computers in Human Behavior, 16, 13-29. [ Links ]

Navarro, R., Larrañaga, E. & Yubero, S. (2016) Gender identity, gender-typed personality traits and school bullying: Victims, bullies and bully-victims. Child Indicators Research, 9(1), 1-20. [ Links ]

Olenik-Shemesh, D., Heiman, T. & Eden, S. (2012). Cyberbullying victimisation in adolescence: relationships with loneliness and depressive mood. Emotional and Behavioural Difficulties, 17, 361-374. [ Links ]

Ortega, R. (2010). Treinta años de investigación y prevención del bullying y la violencia escolar. R. Ortega (coordinator), Agresividad injustificada, bullying y violencia escolar (Unjustified aggression, bullying and school violence) (15-30). Madrid: Alianza. [ Links ]

Ortega, R., Calmaestra, J. & Mora-Merchán, J. A. (2008). Cyberbullying. International Journal of Psychology and Psychologic al Therapy, 8, 183-192. [ Links ]

Ortega, R., Elipe, P. & Calmaestra, J. (2009). Emociones de agresores y víctimas de cyberbullying: un estudio preliminar en estudiantes de secundaria (Emotions of bullies and victims of cyberbullying: a preliminary study in high school students). Ansiedad y Estrés, 15, 151-165. [ Links ]

Ortega-Ruiz, R., Del Rey, R. & Casas, J. A. (2016). Evaluar el bullying y el cyberbullying validación española del EBIP-Q y del ECIP-Q (Evaluate bullying and cyberbullying Spanish validation of the EBIP-Q and the ECIP-Q). Psicología Educativa, 22(1), 71-79. [ Links ]

Pedrero, E., Rodríguez, M. T. & Ruíz, J. M. (2012). Adicción o abuso del teléfono móvil. Revisión de la literatura (Mobile phone addiction or abuse. Literature review). Adicciones, 24, 139-152. [ Links ]

Pelfrey Jr., W. V. & Weber, N. L. (2013). Keyboard gangsters: analysis of incidence and correlates of cyberbullying in a large urban student population. Deviant Behavior, 34, 68-84. [ Links ]

Polo del Río, M., Mendo, S., León, B. & Castaño, F. (2017). Abuso del Móvil en Estudiantes Universitarios y Perfiles de victimización y agresión (Mobile Abuse in University Students and Victimization and Aggression Profiles). Adicciones, 29(4), 245-255. [ Links ]

Ramos, N. S., Fernandez-Berrocal, P. & Extremera, N. (2007). Perceived emotional intelligence facilitates cognitive-emotional processes of adaptation to an acute stressor. Cognition and emotion, 21(4), 758-772. [ Links ]

Rauf, F. H. A., Tarmidi, M., Omar, M., Yaaziz, N. N. R. & Zubir, N. I. D. M. (2013). Personal, family and academic factors towards emotional intelligence: A case study. International Journal of Applied Psychology, 3(1), 1-6. [ Links ]

Romera, E.M., Del-Rey, R. & Ortega, R. (2011). Factores asociados a la implicación en bullying: Un estudio en Nicaragua (Factors associated with involvement in bullying: A study in Nicaragua). Psycho -social Intervention, 20, 161-170. [ Links ]

Romera, E. M., Cano, J. J., García-Fernández, C. M. & Ortega, R. (2016). Cyberbullying: Social Competence, Motivation and Peer Relationships. Comunicar, 24(48), 71-79. [ Links ]

Saadi, Z. E., Zadeh Honarmand, M. M., Najarian, B., Ahadi, H. & Askari, P. (2012). Evaluation of the Effect of Emotional Intelligence Training on Reducing Aggression in Second Year High School Female Students. Journal of American Science, 8(5), 209-212. [ Links ]

Salovey, P., & Mayer, J. D. (1990). Emotional Intelligence. Imagination, Cognition, and Personality, 9, 185-211. [ Links ]

Salovey, P., Mayer, J.D., Goldman, S.L., Turvey, C. & Palfai, T.P. (1995). Emotional attention, clarity and repair: exploring emotional intelligence using the Trait Meta-Mood Scale. In J.W. Pennebaker (editor), Emotion, disclosure, and health (125-154). Washington, DC: APA. [ Links ]

Salovey, P. (2006). Epilogue: The Agenda for Future Research. In V. Druskat; F. Sala; G. Mount (editors), Linking EI and Performance at Work - Current Research Evidence with Individuals and Groups (267-272). LEA Inc. [ Links ]

Sánchez, M., Fernández-Berrocal, P., Montañés, J. & Latorre, J. (2008). ¿Es la inteligencia emocional una cuestión de género? Socialización de las competencias emocionales en hombres y mujeres y sus implicaciones (¿Es la inteligencia emocional una cuestión de género? Socialización de las competencias emocionales en hombres y mujeres y sus implicaciones.). Electronic Journal of Research in Educational Psychology, 6(2), 455-474. [ Links ]

Sentse, M., Kretschmer, T. & Salmivalli, C. (2015). The longitudinal interplay between bullying, victimization, and social status: Age-related and gender differences. Social Development, 24(3), 659-677. [ Links ]

Sticca, F., Ruggieri, S., Alsaker, F. & Perren, S. (2013). Longitudinal Risk Factors for Cyberbullying in Adolescence. Journal of Community & Applied Social Psychology, 23, 52-67. [ Links ]

Slonje, R. & Smith, P. K. (2008). Cyberbullying: Another main type of bullying?. Scandinavian Journal of Psychology, 49, 147-154. [ Links ]

Treuer, T., Fabian, Z. & Furedi, J. (2001). Internet addiction associated with features of impulse control disorder: Is it a real psychiatric disorder? Journal of Affective Disorders, 66, 266-283. [ Links ]

Valera, R. M. (2012). Violencia, Victimización y Ciberbullying en adolescentes escolarizados: una perspectiva desde el Trabajo Social (Violence, Victimization and Cyberbullying in school adolescents: a perspective from Social Work) (doctoral thesis). Universidad Pablo de Olavide, Sevilla. [ Links ]

Weare, K. (2004). What impact is having information technology on our young people’s health and well-being? Health Education, 104, 129-131. [ Links ]

Weissberg, R. P. & Greenberg, M.T. (1998). School and community competence-enhancement and prevention programs. I.E. Sigel & K.A. Renninger (editors), Handbook of child psychology: Vol. 4. Child psychology in practice (5th ed., 877-954). Nueva York: John Wiley & Sons. [ Links ]

Ybarra, M. L. & Mitchell, K. J. (2004). Online Aggressor/Targets, Aggressors, and Targets: A Comparison of Associated Youth Characteristics. Journal of Child Psychology and Psychiatry, 45, 1308-1316. [ Links ]

Received: September 12, 2018; Revised: October 22, 2018; Accepted: October 25, 2019

Joan Guerra-Bustamante. Department of Psychology, Faculty of Teacher Training College, University of Extremadura, 10071 Cáceres (Spain). E-mail: joangb@unex.es

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