Social support, socio-emotional competencies and cybervictimisation: a longitudinal analysis among primary school students 1
Apoyo social, competencias socioemocionales y cibervictimización: estudio longitudinal en estudiantes de Educación Primaria
https://doi.org/10.4438/1988-592X-RE-2022-397-542
Juan Manuel Rodríguez-Álvarez
https://orcid.org/0000-0001-6458-4699
Consejería de Educación, Cultura y Deporte. Castilla-La Mancha
Raúl Navarro
https://orcid.org/0000-0003-4284-4300
Santiago Yubero
https://orcid.org/0000-0002-7148-7958
Elisa Larrañaga
https://orcid.org/0000-0001-6458-4699
Universidad de Castilla La Mancha
Abstract
Cyberbullying is a serious social and health problem for children. Cyberbullying behaviours occur among peers at school, affecting day-to-day life in the classroom, and are reported among students in the final years of primary education. This study analyses the relationships between social support from friends, socio-emotional competencies and cybervictimisation in early adolescence (10-13 years old). A short-term longitudinal design (two assessments with a six-month interval) was used. The final sample comprised 566 students in Years 5 and 6 at primary school in the Madrid and Castilla-La Mancha regions (Spain). Students provided self-reports on cyberbullying and bullying frequency (T1 and T2), social support from friends and socio-emotional competencies (T1). At the end of the academic year, cybervictimisation was found to be stable. The results showed that being a cybervictim at the end of the academic year was significantly associated with being a cyberperpetrator and victim of bullying in the same period. Participants with stronger social support from friends and socio-emotional competencies at the start of the academic year (T1) were less likely to experience cybervictimisation at the end of the academic year T2). In conclusion, the results point to the importance of detecting cyberbullying and promoting early intervention by schools. Socio-emotional competencies and social support from friends are relevant strategies for preventing cyberbullying. Teachers and other educational actors outside schools should work to improve socio-emotional competencies among children in order to foster positive relationships between them.
Keywords: cyberbullying, social support, socio-emotional competencies, school bullying, longitudinal, early adolescence
Resumen
El ciberacoso es un grave problema social y para la salud de los menores. Los comportamientos de ciberacoso se producen entre los compañeros de la escuela por lo que también afectan al desarrollo diario de la vida en el aula. La cibervictimización aparece en los últimos cursos de Educación Primaria por lo que consideramos que el último ciclo de Educación Primaria es un periodo fundamental de intervención y de prevención. En el presente estudio se analiza la relación del apoyo social de los amigos, las competencias socioemocionales y la cibervictimización en la adolescencia temprana (entre los 10 y los 13 años). Se realizó un diseño longitudinal a corto plazo (dos evaluaciones con 6 meses de diferencia). La muestra fue de 566 estudiantes de 5º y 6º de Educación Primaria de las comunidades de Madrid y Castilla-La Mancha (España). Los estudiantes informaron sobre los comportamientos de victimización y de perpetración de ciberacoso y de acoso escolar (T1 y T2); el apoyo social de los amigos y las competencias socioemocionales (T1). Se constata la estabilidad de la cibervictimización. Ser cibervíctima al final del curso está significativamente asociado con ser ciberperpetrador y víctima de acoso escolar en el mismo periodo. Los menores con mayor apoyo social de los amigos y con más competencias socioemocionales en el inicio del curso (T1) presentan menos probabilidad de experimentar cibervictimización al final del curso (T2). En conclusión, estos datos ponen de manifiesto la necesidad de detectar el ciberacoso e intervenir tempranamente en las escuelas. Las competencias socioemocionales y el apoyo social de los amigos son estrategias relevantes de intervención y prevención de la cibervictimización. Los maestros, junto con los agentes educativos externos a la escuela, deben fomentar las dinámicas socioemocionales en el grupo social de los menores para fomentar las relaciones de convivencia.
Palabras clave: ciberacoso, apoyo social, competencias socioemocionales, acoso escolar, estudio longitudinal, adolescencia temprana
School bullying has been defined as an intentional act of aggression perpetrated by a group or individual on a recurrent basis over a period of time against a victim who cannot easily defend themselves (Smith et al., 2008). It is a serious social issue with a significant impact on children’s health (Garaigordobil, 2011). When information and communication technologies (ICT) are used to carry out this bullying, it is known as cyberbullying (Smith et al. 2008). Kowalski et al. (2012a) define cyberbullying as an intentional, aggressive, repeated behaviour exercised by a more powerful individual over a more vulnerable person using new technologies. Cyberbullying differs from traditional bullying in aspects such as the anonymity of perpetrators and the potentially far greater audience (Slonje, & Smith, 2008),
A number of studies carried out in Spain have reported cyberbullying among students in the final years of primary education (Delgado, & Escortell, 2018; García-Fernández et al., 2017; Machimbarrena, & Garaigordobil, 2018). Although they remain lower than school bullying rates, cybervictimisation rates in primary schools (García-Fernández et al., 2017; Machimbarrena, & Garaigordobil, 2018) stand at between 7% (Cross et al., 2015) and 13.8% (Machimbarrena, & Garaigordobil, 2018). Some studies have observed higher levels of cybervictimisation among boys than girls (García-Fernández et al., 2015), others have found no significant differences (Monks et al., 2012; Navarro et al., 2016), and others still have found higher levels of cybervictimisation among girls (Delgado, & Escortell, 2018). Experiences of cybervictimisation begin at primary school, so the final stage of primary education (from age 10) is considered a key period for intervention and prevention.
Longitudinal studies have demonstrated the existence of stable victims, or victims who remain in this role over time. Stability refers to the repetition and consistency of a student’s victimisation over a specific period of time, which can range from months to years (Rueger et al., 2011), even if it is not perpetrated by the same individual (Pouwels et al. 2016).
Most studies have examined the stability of victimisation in school bullying during the transition from primary to secondary school. The stability of school bullying during this period is around 10% (Oncioiu et al., 2020; Zych et al., 2020). In a meta-analysis of 77 longitudinal studies, Pouwels et al. (2016) found that stability was lower during primary education. Meanwhile, Hellfeldt et al. (2018) studied 3,347 students from 44 primary schools and found that 1.6% were ongoing victims of school bullying. They observed no differences by gender. With regard to cyberbullying, Jose et al. (2012) conducted a longitudinal study of 1,700 students aged 11-16 over a two-year period and found a lower stability of cyberbullying than school bullying among adolescents. However, few studies have specifically analysed the stability of cyberbullying (Gonzalez-Cabrera et al., 2021) and we are not aware of any that specifically analyze the stability of cyberbullying during the final two years of primary education. Therefore, it is necessary to analyse the stability of cybervictimisation during this period in children’s education.
Several studies conducted in different countries have observed simultaneous bullying and cyberbullying in all age groups, with perpetrators and victims extending (or alternating) their roles from the real to the virtual world or vice versa (Evangelio et al., 2022; Kowalskiet al., 2012b).
Participation in school bullying and cyberbullying, as a victim and a perpetrator, has been identified as a risk factor for cybervictimisation (del Rey et al., 2012; Fanti et al., 2012; Sticca et al., 2013). However, research data on the influence of school bullying as an explanatory factor for cyberbullying are not conclusive (García-Fernández et al., 2016). Other studies have found no evidence of this relationship (Raskauskas, & Stoltz, 2007; Slonje, & Smith, 2008).
Meanwhile, research has shown a positive relationship between victimisation and perpetration (Mitchell et al., 2011; Zhou, et al., 2020), identifying an overlap between the two roles, although the causal relationship remains unclear (Fanti et al., 2012). With regard to cyberbullying, the results of a study by Li (2007) indicate that the best predictor of cybervictimisation is cyberperpetration. It is also likely that cybervictims will become cyberperpetrators (del Rey et al., 2012; Sticca et al., 2013). Longitudinal studies have found stronger correlations between cybervictimisation and cyberperpetration as the period between measurements progresses (Chu et al., 2018; Pabian, & Vandebosch, 2016). Lozano et al. (2020) performed a meta-analysis of 22 research studies, finding that adolescents tend to be cybervictims before becoming cyberperpetrators.
Therefore, it is important to conduct longitudinal research to analyse the relationship between bullying and cyberbullying and between the roles of victim and perpetrator. Research is particularly crucial during the stage of primary education when these behaviours begin to emerge.
According to socio-ecological theory (Bronfenbrenner, 1977), victimisation through cyberbullying is likely to originate and continue over time as the result of interaction between personal and social factors (Cross et al., 2015; Fanti et al., 2012).
One of these personal factors is socio-emotional competencies, which constitute resources and strategies for positive social relationships (Collaborative for Academic Social, and Emotional Learning, 2018). Students with strong socio-emotional skills have proven to be good at communicating, negotiating conflicts in a constructive manner and seeking help when necessary, as well as demonstrating socially responsible behaviour (DeLay et al., 2016; Wang et al., 2019). A number of studies have shown that socio-emotional competencies could protect against cyberperpetration (Romera et al., 2017; Zych et al, 2018; Zych et al., 2019), but the effect of socio-emotional competencies on cybervictimisation remains unclear (Beltrán-Catalán et al., 2018). Several studies have identified weak socio-emotional competencies among cyberbullying victims (Gómez-Ortiz et al., 2017), while others have found no significant differences in socio-emotional competencies between students who do not participate in cyberbullying and victims (Romera et al., 2016; Zych et al., 2018).
With regard to social factors, research has suggested that social support from friends is negatively associated with school bullying and cyberbullying in adolescence (Katzer et al., 2009; Yubero et al., 2010). In early adolescence, several authors have highlighted the importance of analysing bullying in the context of friendships at school (Mishna et al., 2008; Wei, & Jonson-Reid, 2011). Young teenagers tend to attach more importance to their friendships and develop more exclusive relationships with their friends (Pronk, & Zimmer-Gembeck, 2010), turning to them as their main source of support (Holfeld, & Leadbeater, 2017). However, the relationship between cyberbullying and the role of friends remains unclear (Fanti et al., 2012). Whereas Navarro et al. (2015) report that cybervictims at primary school tend to have weak social support and few friends, Mishna et al. (2016) found no association between social support and cybervictimisation.
These contradicting results and the lack of studies with primary school students point to the need for more in-depth analysis of the relationship between cyberbullying, social support from friends and cybervictimisation. It is important to identify the factors that make primary school cybervictims vulnerable so that adequate prevention measures can be taken and they can be equipped with coping strategies.
The first study objective was to analyse the prevalence of stable cybervictimisation in the final years of primary education. In this regard, stable cybervictimisation is expected (H1) to occur throughout the academic year in the final years of primary education (Hellfeldt et al., 2018).
The second study objective was to analyse cybervictimisation in relation to experiences of school bullying and cyberbullying, socio-emotional factors and social support from friends. Based on previous studies, we expect to find longitudinal relationships between victimisation through cyberbullying at the end of the academic year and victimisation through cyberbullying at the start of the academic year (T1, stability of cyberbullying, Jose et al., 2012), and transversal relationships with involvement as cyberperpetrators (T2, overlapping of roles, Li, 2007) and victimisation through school bullying (T2, simultaneity, Evangelio et al., 2022). It is also anticipated that children with stronger socio-emotional competencies (Gómez-Ortiz et al., 2017) and greater social support from friends (Navarro et al., 2015) (T1) will be less likely to be cybervictims at the end of the academic year (H2).
A longitudinal study was carried out during a single academic year using two measures: time 1 at the start of the academic year (October-November, T1) and time 2 at the end of the academic year (May-June, T2). A total of 1,130 students completed the questionnaire in full in T1, while 735 (65%) did so in T2. The participants were students in Years 5 and 6 at public primary schools in two regions in central Spain: Madrid (48.7%) and Castilla-La Mancha (51.3%). 44.4% of the sample lived in urban areas (towns with more than 10,000 inhabitants) and 55.6% were attending schools in rural environments (villages with fewer than 10,000 inhabitants).
Of the 13 schools that participated in T1, 5 refused to participate at the end of the academic year. A total of 566 students (50% of the original sample), who completed every item on the questionnaire on both times, were included in the study. 48.6% of the participants were girls, with ages ranging from 10 to 13 years old (M= 10.82, SD= 0.74), and 52.9% were in Year 5.
To measure school bullying and cyberbullying, the Spanish version (Rodríguez-Álvarez et al. (2021) of the Bullying Harassment and Aggression Receipt Measure (Bullyharm, Hall, 2016) was used. The measure comprises 14 Likert-type items for each dimension of perpetration and victimisation, with four response options from 0 to 3 (0=Not in the past month, 1=1 or 2 times in the past month, 2=About 1 time a week, and 3=About 2 or more times a week). Students were asked to evaluate the frequency of their participation in different behaviours throughout the last month. The measure provides information about school bullying (physical, verbal and social, 11 items, e.g. ‘I was called a bad name’ or ‘A false rumour was spread about me’) and cyberbullying (3 items, e.g. ‘A mean comment was made about me on the internet’). It is important to note that the questionnaire did not provide information about the elements of intentionality or power imbalance that would constitute victimisation through bullying. The instrument displayed adequate reliability in recent studies with adolescents (Larrañaga et al., 2018). The internal consistency, measured using Cronbach’s α, was .88 in T1 and .78 in T2 for victimisation through school bullying, .66 in T1 and .73 in T2 for cybervictimisation; .79 in T1 and .82 in T2 for perpetration of school bullying, and .67 in T1 and .77 in T2 for cyberperpetration.
The score was dichotomised according to the same criteria as previous studies (Sticca et al., 2013). Participants who obtained a score exceeding 1 in at least one of the victimisation through school bullying and cyberbullying items were classified as victims of bullying and cyberbullying respectively. The same criteria were applied to perpetration.
To evaluate perceived social support from friends, the friends dimension of the AFA-R measure was used (González, & Landero, 2014). It contains seven Likert-type items (e.g. ‘I trust my friend(s) to talk about things that worry me’) with five response options from 1 to 5: 1=Never, 2=Rarely, 3=Sometimes, 4=Often, 5=Always. The score is the sum of the items, ranging from 7 to 35 points. The higher the score, the greater the student’s social support. This subscale displayed adequate reliability in recent studies with adolescents (Fernández-Zabala et al., 2020). In this study of primary school students, the consistency of the subscale was also high (α=.89).
Socio-emotional competencies were measured using the Delaware Social Emotional Competencies Scale–Student (DSECS-S, Mantz et al. 2018), which has already proved suitable for use with primary school students (Yang et al., 2020). The DSECS-S collects information on four dimensions: responsible decision-making, relationship skills, self-management and social awareness. It contains 12 items (e.g. ‘I am good at solving conflicts with others’ and ‘I feel responsible for how I act’), which students must respond to using a Likert-type scale from 1=Never to 4=Always. The internal consistency coefficient measured using Cronbach’s α was .79.
For ethical reasons, informed consent was first sought from the children’s legal guardians. 0.9% of the families in T1 and 3.5% in T2 did not respond, so their children did not participate in the data collection for the corresponding period.
The questionnaire was administered by the children’s teachers, with support from members of the research team. It was administered in the classroom with authorisation from the school headteachers and teachers. Students were informed that participation was voluntary and their answers would remain anonymous. The approximate mean response time was 30 minutes in T1 and 15 minutes in T2 (only Bullyharm was used in the second time). The study met all Spanish and international ethical standards, including the Helsinki Declaration and personal data protection laws. The project was approved by the Ethics Committee at Hospital Virgen de la Luz (PI0519).
The data were processed using the statistical programme SPSS. Firstly, the percentage of cybervictimisation in T2 and T1 was calculated, analysing the differences using McNemar’s test. The stability of cybervictimisation was analysed using a contingency table and the chi-squared test. The relationship between sex and cybervictimisation was evaluated using the chi-squared test. To study the relationship between the variables, the degree of association between them was calculated for T1 and T2 by sex using Pearson’s correlation coefficient. Cohen’s proposal (1988) was used for the interpretation: around r=0.1 represents a small effect; around 0.3 is medium, and around 0.5 is large. A multiple linear regression was then carried out. Victimisation through cyberbullying in T2 was used as the dependent variable. Sex was introduced as a control variable. In all cases, the probability of making a Type I error of p ≤ .05 was used to consider a result statistically significant.
In the final measure (T2), 6.1% (n= 34) of the students had been victimised at least once via one of the forms of cyberbullying analysed. With regard to sex, no significant differences were found (χ2= 0.28, p= .363): 5.6% of boys (n= 16) and 6.7% of girls (n= 18) reported cybervictimisation.
In the initial measure (T1), 8.8% (n= 49) of the students reported being victimised at least once via one of the forms of cyberbullying analysed. With regard to sex, no significant differences were found here either (χ2= 0.13, p= .416): 8.4% of boys (n= 24) and 9.3% of girls (n= 25) reported cybervictimisation. The prevalence of cybervictimisation was similar in both periods (p= .072).
Although the prevalence was similar at the start and end of the academic year, this was not the case for all cybervictimised students: some managed to escape the cyberbullying they had suffered at the start of the year (n= 38) and others became cybervictims at the end of the academic year (n=23), while cybervictimisation was a constant in some children’s school experiences (stable cybervictims).
22% of the cybervictims in T1 reported also being cybervictims in T2. This means that 2% (n= 11) of the sample reported stable cybervictimisation, cybervictimisation in T1 and cybervictimisation in T2 (χ2= 25.71, p<.001). Therefore, 32.4% of the victims of cyberbullying in T2 were also victims of cyberbullying in T1. With regard to sex, no significant differences were found (χ2= 1.04, p= .792): 4% of boys (n= 4) and 7% of girls (n= 7) reported stable cybervictimisation.
The correlations between the study variables were analysed for Time 1 and Time 2 (see Table 1). Table 1 shows that, among the boys, the Pearson’s correlation coefficient was not significant for the relationship between cybervictimisation in T1 and T2. Stable victimisation was only found in bullying (r= .57). The relationship was significant for the overlapping of roles (cybervictimisation/cyberperpetration: r= .70) and for simultaneity of victimisation through bullying and cyberbullying (r= .32). A small effect was observed in the relationship between support from friends and cybervictimisation (r= -.17). Among the girls, a medium effect was observed in Pearson’s correlation coefficient for stability of cybervictimisation (r= .40), overlapping of roles (r= .36) and simultaneity of victimisation through bullying and cyberbullying (r= .26). The relationships between cybervictimisation and social support from friends (r= -.22) and cybervictimisation and socio-emotional competencies (r= -.20) were also significant, with a medium effect size. The result for stability of victimisation was higher for bullying (r= .57). Among both sexes, the correlation between social support from friends and socio-emotional competencies was significant (Boys: r= .39; Girls: r= .49).
TABLE 1. Correlations between study variables by sex
|
VBT1 |
VCT1 |
PBT1 |
PCT1 |
VBT2 |
VCT2 |
PBT2 |
PCT2 |
SSF |
SES |
|
|
VBT1 |
-- |
.55*** |
.51*** |
.19*** |
.57*** |
.00 |
.23*** |
.04 |
-.10 |
-.27** |
|
VCT1 |
.36*** |
-- |
.19** |
.36*** |
.27*** |
.02 |
-.01 |
-.00 |
.00 |
-.01 |
|
PBT1 |
.59*** |
.23*** |
-- |
.36*** |
.35*** |
.02 |
.48*** |
.12* |
-.00 |
-.36*** |
|
PCT1 |
.12* |
.27*** |
.12* |
-- |
.20*** |
-.03 |
.05 |
.04 |
-.02 |
-.12 |
|
VBT2 |
.63*** |
.23*** |
.33*** |
.03 |
-- |
.32*** |
.42*** |
.25*** |
-.16* |
-.13* |
|
VCT2 |
.19*** |
.40*** |
.14* |
.41*** |
.26*** |
-- |
.34*** |
.70*** |
-.17* |
.01 |
|
PBT2 |
.42*** |
.22*** |
.59*** |
.12* |
.36*** |
.18** |
-- |
.62*** |
-.00 |
-.17* |
|
PCT2 |
.02 |
.18** |
-.01 |
-.01 |
.06 |
.14* |
.36*** |
-- |
.04 |
-.02 |
|
SSF |
-.08 |
-.12* |
-.07 |
-.06 |
-.07 |
-.22** |
-.06 |
-.04 |
-- |
.39*** |
|
SES |
-.15 |
-.10 |
-.32*** |
-.01 |
-.02 |
-.20** |
-.17* |
-.09 |
.49*** |
-- |
Nb. The values for the boys are above the line, while those below the line correspond to the girls. VBT1= Victimisation Bullying T1, VCT1= Victimisation Cyberbullying T1, PBT1= Perpetration Bullying T1, PCT1= Perpetration Cyberbullying T1, VBT2= Victimisation Bullying T2, VCT2= Victimisation Cyberbullying T2, PBT2= Perpetration Bullying T2, PCT2= Perpetration Cyberbullying T2, SSF= Social Support from Friends, SES= Socio-Emotional Skills. *p<.05; **p<.01; ***p<.001
Source: compiled by the authors
To estimate the protective capacity of social support from friends and socio-emotional competencies against cybervictimisation in T2, a linear regression analysis was performed (Table 2). The results showed a significant association with both variables (Social support from friends: β=-0.83, p<.05, Socio-emotional competencies: β= -.041, p<.05) and their interaction (β= -1.06, p<.05). The results also showed an association between cybervictimisation in T2 and cybervictimisation in T1 (β= 0.19, p<.01), and with the variables of cyberperpetration (β= 0.48, p<.001) and victimisation through bullying (β= .029, p<.001) in T2. The resulting model proved significant and explained 33% of the variance.
TABLE 2. Linear regression to identify predictors of cybervictimisation in T2
|
β |
t |
p |
CI 95% |
|
|
Sex Victimisation Bullying T1 Perpetration Bullying T1 Victimisation Cyberbullying T1 Perpetration Cyberbullying T1 Victimisation Bullying T2 Perpetration Bullying T2 Perpetration Cyberbullying T2 Socio-Emotional Competencies Social Support from Friends Socio-Emotional Competencies x Support from Friends |
0.07 -0.09 0.14 0.19 -0.00 0.29 -0.10 0.48 -0.41 -0.83 -1.06 |
1.19 -1.14 1.96 2.84 -0.02 4.24 -1.06 6.19 -2.13 -2.07 -2.09 |
.236 .256 .051 .005 .981 .000 .288 .000 .034 .040 .037 |
-0.04 – 0.16 -0.03 – 0.01 0.00 – 0.06 0.06 – 0.32 -0.25 – 0.25 0.02 – 0.05 -0.06 – 0.02 0.42 – 0.82 -0.90 - -0.03 -0.82 - -0.02 -0.80 - -0.25 |
|
Nagelkerke R2 |
.33 |
|||
|
F |
11.04*** |
|||
|
df |
11 |
|||
Nb: β= standardised coefficient; t = Student’s t; p= significance; CI 95% = confidence interval; df= degrees of freedom; ***p<.001
Source: compiled by the authors
Cyberbullying is an important social issue due to its impact on children’s health and education (Garaigordobil, 2011; Li, 2007; Ybarra et al., 2007). The study of factors associated with experiences of cybervictimisation plays a central role in designing strategies to tackle the issue in schools. Few studies have provided longitudinal data on predictors of victimisation through cyberbullying among primary school students. In this study, the participants were students in Years 5 and 6 of primary education, who completed the questionnaire at the start and end of an academic year.
For some children, victimisation at primary school can mark the start of a history of victimisation throughout their academic lives (Hellfeldt et al. 2018; Lozano et al., 2020). The main aim of this study was to analyse the prevalence of stable cybervictimisation in the final years of primary education. The results confirmed the stability of cybervictimisation among primary school students over the course of an academic year (H1), with 2% of victims reporting stable cybervictimisation. No differences were observed by sex. A significant correlation of .36 was also found between cybervictimisation in T1 and T2, corroborating the findings of Giesbrecht et al.’s (2011) study of adolescents. This is the first research study to specifically analyse the temporal stability of cybervictimisation over the course of an academic year among primary school students.
Online victimisation at the start of the academic year was a strong predictor of cybervictimisation six months later (H2). This finding is reinforced by previous research focusing on a broader sample of age groups (Jose et al., 2012; Zych et al., 2020). It demonstrates the need for immediate intervention to address cyberbullying as it emerges to prevent ongoing victimisation via ICT tools.
Prior research with adolescents has found that participation in school bullying (del Rey et al., 2012; Fanti et al., 2012; Sticca et al., 2013) and cyberperpetration (Li, 2007) are risk factors for victimisation through cyberbullying. However, in our study of primary school students, neither involvement in traditional school bullying as victims or perpetrators nor cyberperpetration in T1 were related to cybervictimisation in T2. This difference between stages may be explained by the changes occurring in children’s approaches to friendship as they grow older. According to routine activities theory (Cohen et al., 1981), the victim’s appeal can increase the likelihood of victimisation. If the bully loses interest in the victimised student, previous incidents of bullying may lose their value as a predictor. Moreover, in preadolescence, friendship groups are beginning to form and cognitive decentration prompts young people to understand friendship in terms of cooperation and reciprocal support (Fuentes, & Melero, 1993), leading to instability in relationships between peers according to their assessment of these variables. Similarly, bullies may assess their peers and view them as easy targets depending on their degree of support from friends.
The results of this study show that the roles of cybervictim and cyberperpetrator can overlap (H2). In line with other studies (Chu et al., 2018; Pabian, & Vandebosch, 2016) of primary school students, the correlation between cybervictimisation and cyberperpetration was stronger at the end of the academic year (T2) than at the beginning (T1). According to Lozano et al. (2020), children who are cybervictims and feel powerless to escape online bullying may become cyberperpetrators in an attempt to defend themselves. Among primary school students, cyberperpetration occurs primarily through WhatsApp (García-Fernández et al., 2015), which removes the perpetrators’ anonymity; in turn, this loss of anonymity can transform them into victims. This is a relevant consideration for intervention, as longitudinal studies have shown that students who are both cybervictims and cyberperpetrators are more likely to suffer depression and anxiety than their classmates (Lozano et al., 2020). When the victims are aggressive themselves, they are less likely to receive support from their classmates, allowing victimisation to continue (Sugimura et al., 2017).
The results of the study also confirmed the simultaneity of cybervictimisation and victimisation through school bullying at the end of the academic year. This points to the relationship between schools and cyberbullying, which should be taken into consideration when designing strategies for prevention and intervention. According to Kowalski et al. (2021b), in primary and secondary school students, the role of the victim extends from cyberspace into the real world. This is relevant when it comes to intervention, as studies have shown that students who are polyvictimised are more likely to suffer reduced wellbeing than their classmates (Lozano et al., 2020).
In this study, it was expected that social support from friends and socio-emotional competencies would act as protective factors against cybervictimisation (H2). The findings support this hypothesis: children with greater social support from friends and stronger socio-emotional competencies at the start of the academic year (T1) had a lower likelihood of experiencing cybervictimisation at the end of the year (T2).
Other studies, such as Mishna et al. (2016), found no association between social support and cybervictimisation. The significant relationship observed in this study may be due to the fact that rising internet use among children has also increased support from friends online, serving as a protective factor against cyberbullying. Interpersonal relationships offline are maintained in online environments (Ortega-Ruiz et al., 2014), so social support from friends via a social network may also protect against becoming a victim (Eliot et al., 2010). The findings of this study echo those of research by Schoeps et al. (2018) with secondary school students, which shows a reduction in the longitudinal incidence of cybervictimisation in students aged 12-15 following the implementation of a programme to develop socio-emotional skills.
The interaction between the two factors (socio-emotional competencies and social support) corroborates previous research, which has shown that students with strong socio-emotional competencies tend to seek help to resolve conflicts (DeLay et al., 2016; Wang et al., 2019). In this quest for assistance, support from friends can contribute to constructive negotiation between peers to resolve conflict and reduce cybervictimisation.
Despite its online nature, cybervictimisation is a key issue for schools. Research has demonstrated the importance of schools in fighting school bullying in the final years of primary education, as students transition to secondary education (Coffey, 2013; Waters et al., 2012). However, the fact that cyberbullying occurs outside school premises and hours (Hinduja, & Patchin, 2012) has led some to argue that schools and teachers have little responsibility for intervening to prevent it (Englander, 2012).
This study indicates that early adolescence, from the age of 10, is a key period in preventing cyberbullying. It is important to adopt a short and long-term approach to the issue, as the results of this study show that cybervictimisation can become stable over time.
The findings of this study emphasise the importance of educational intervention to develop socio-emotional competencies and social support. In early adolescence, friendships tend to emerge primarily within children’s class groups (Larson, & Verna, 1999) and face-to-face social relationships from school are transferred online (Mikami et al., 2010). Therefore, strengthening social relationships between classmates can help increase social support, prevent the emergence of cyberbullying (Zych et al, 2021) and establish friendships. Of course, friendships between students are neither the school’s nor the teacher’s responsibility, but they can promote positive interaction between students in the classroom in the hope of encouraging new personal relationships. Parents also play an important role in offering opportunities for students to gather and build friendships (Marande et al., 2014).
It is also vital to bring an end to inadequate conflict resolution strategies based on aggression, which give rise to a vicious circle of perpetrators and victims (Navarro et al. 2018). Developing socio-emotional competencies can equip children with the social and emotional skills they need to establish positive relationships and address conflict in an appropriate manner. Primary education is a crucial stage in the development of socio-emotional competencies, as relationships with classmates become more important to children at this time (Rueger et al., 2011).
Providing teachers with sufficient resources to prevent cyberbullying between students is a priority. Actions that enhance socio-emotional development and encourage positive social relationships can help prevent cyberbullying. It is essential that these actions are backed by social actors from outside the school environment to encourage children to develop healthy relationships. Several experiments using reading to boost socio-emotional development and social support have been carried out (see, for example, García-Bacete et al., 2013). This appears to be a helpful intervention strategy, as reading offers the potential for activities to be carried out in classroom libraries, in partnership with school or public libraries (Sánchez-García, & Yubero, 2015). It also encourages collaborative work with parents and creates social spaces for gathering, which can facilitate the establishment of new relationships.
There are several limitations to this study. Experimental mortality was high at 50%, although this is similar to the levels reported in other longitudinal studies (e.g. González-Cabrera et al., 2021). In our study, 5 of the 13 schools that participated in T1 refused to participate at the end of the academic year. At one school, the headteacher had changed; at the others, one or more of the teachers involved declined to participate in the second phase, so the whole school’s participation was cancelled to avoid internal conflicts.
Another limitation is that only three items were used to measure cyberbullying. Measurements of the prevalence of cyberbullying depend on the instrument used to study it (Cross et al., 2015; Romera et al., 2016). Nevertheless, the measure of cyberbullying used in this study encompasses all the main types of cyberbullying considered relevant at this age (Smith et al., 2008). It is important to note that the study only considered types of bullying and provides no information as to their intensity. It also fails to take the power imbalances and elements of intentionality inherent to bullying into consideration. Future studies should employ broader measures of cyberbullying. Coelho and Marchante (2018) have shown that poor socio-emotional competencies are more of a consequence than a cause of participation in cyberbullying. In a study of marginalised students, socio-emotional competencies and experiences between peers were shown to influence one another (García-Bacete et al., 2021). This points to the need for studies using mediation analysis to obtain a more in-depth understanding of these complex relationships. The findings could also be supplemented by a specific analysis of the dimensions of socio-emotional competencies that are associated with cybervictimisation. With regard to social support, another limitation is that the study overlooks other sources of support such as parents or teachers.
This study offers new data about cybervictimisation in primary school students. Firstly, the results confirm the temporal stability of cybervictimisation. Two in ten primary school students suffer cyberbullying throughout the academic year.
The study also found evidence of the association between cybervictimisation at the start of the academic year (T1) and being a cybervictim six months later (T2), but no association was found with previous involvement in school bullying. Cybervictimisation at the end of the academic year was also found to be associated with simultaneity of school bullying and cyberbullying and with overlap in the roles of cybervictim and cyberperpetrator (T2).
Socio-emotional competencies and social support are protective factors against cybervictimisation among primary school students. Children with greater social support from friends and stronger socio-emotional competencies at the start of the academic year (T1) were less likely to experience cybervictimisation at the end of the year (T2).
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Contact address: Raúl Navarro, Universidad de Castilla-La Mancha, Departamento de Psicología, Facultad de Humanidades y Ciencias de la Educación. Campus universitario s/n. CP, 16071, Cuenca. E-mail: Raul.navarro@uclm.es
1 This study is part of R&D&I Project PSI2015-70822-R.