Cyberbullying Experience and Gender Differences Among Adolescents in Different Educational Settings

Abstract

Cyberbullying refers to a negative activity aimed at deliberate and repeated harm through the use of a variety of electronic media. This study examined the Internet behavior patterns and gender differences among students with learning disabilities who attended general education and special education classes, their involvement in cyberbullying, and the relationships among being cyberbullied, their responses, and their coping strategies. The sample consisted of 149 students with learning disabilities (LD) attending general education classes, 116 students with comorbid LD attending special education classes, and 242 typically achieving students. All the students, studying in middle and high schools, completed a self-report cyberbullying questionnaire. Findings indicate that although no significant differences emerged in the amount of surfing hours and students’ expertise in the use of the Internet, students attending special education classes are more likely to be cybervictims and cyberperpetrators; girls are more likely to be cybervictims, whereas boys are more likely to be cyberperpetrators. These results contribute to our understanding of students’ involvement in cyberbullying and can serve as a basis for developing preventive programs as well as intervention programs for students and for educational school teams.

Keywords

cyberbullying learning disabilities general classes special classes gender

With advances in technology, students are finding new methods of cyberbullying. But relatively little is known about the experiences of cyberbullying of students with learning disabilities (LD). The present study explored the prevalence of cyberbullying while also examining gender differences. Studies have found that the number of youth who report making rude or nasty comments to someone online has doubled from 14% to 28%, that more than 30% of youth experience cyberbullying, and that up to 71% of adolescents report either witnessing or personally experiencing racial victimization on the Internet (Hinduja & Patchin, 2013; Tynes, Rose, & Williams, 2010). Cyberbullying has also been found to be associated with multiple forms of psychosocial harm and delinquency (Ybarra & Mitchell, 2004).

Literature Review

Bullying has been described as aggressive intentional behavior within a situation of an imbalance of power against a victim who cannot easily defend himself or herself (Li, 2007; Slonje & Smith, 2008; Smith et al., 2008). Bullying behavior can be demonstrated in different ways, including direct behaviors, such as physical behavior (hitting, pushing, kicking, and stealing) or indirect verbal behavior (such as calling names, provoking, threatening, spreading insults, spreading rumors, excluding or isolating socially), which occurs repeatedly over time and creates an ongoing pattern of harassment and abuse (Olweus, 1993). In addition, significant relationships have been observed between bullying and lower scholastic achievements, social and emotional problems, risk of depression, and low self-esteem (Kim & Leventhal, 2008).

For the past decade, computer and Internet facilities have created new opportunities for children and adolescents with and without LD, as it is an easier environment for requesting academic help or for creating social connections as compared to face-to-face relationships (Raskind, Margalit, & Higgins, 2006). The Internet and, in particular, social networking have become an inseparable part of children’s daily lives and provide a new form of social space in which children and adolescents might be exposed to online bullying.

Prevalence and Involvement in Cyberbullying

Cyberbullying may be viewed as a new form of bullying that involves the use of electronic devices and/or other forms of information technology. Definitions of cyberbullying refer to a negative activity aimed at deliberate and repeated harm through the use of a variety of electronic media, such as social networks, chat rooms, email, and cell phones, through which threatening and offensive messages are sent and received. This violent use of the Internet by a person or a group of people is mostly carried out anonymously to harm another person who cannot defend himself or himself, and in contrast to other forms of bullying, cyberbullying reaches a far wider audience at rapid speed, transcending boundaries of time and physical and personal space (Kowalski, Limber, & Agaston, 2008; Smith et al., 2008). Findings analyzing youngsters’ usage patterns of social networks and their consequences for children and adolescents (O’Keeffe & Clarke-Pearson, 2011) indicate that, in recent years, the Internet has become a daily tool for teenagers.

Numerous studies have demonstrated that cyberbullying has become a worldwide phenomenon, with growing occurrence every year (Shariff & Hoff, 2007; Ybarra & Mitchell, 2004). Findings indicated that around 25% of school pupils are directly involved in cyberbullying (Vandebosch & Van Cleemput, 2009). Most of the studies indicate that although the cyberbullying phenomenon might begin in elementary school and can continue to college, it occurs mostly during early adolescence and adolescence (Tokunaga, 2010; Williams & Guerra, 2007). A comprehensive study conducted in the United States found that one in five young online users was involved in cyberbullying in some way (Ybarra & Mitchell, 2004), more than 53% reported they knew someone who had been victimized on the Internet (Li, 2006), and approximately 20% of the students reported experiencing cyberbullying in their lifetimes (Cyberbullying Research Center, 2010). A study conducted in Canada revealed that more than 40% of the 2,186 students who participated in the study reported an involvement in cyberbullying (Mishna, Khoury-Kassabri, Gadalla, & Daciuk, 2012); in Israel it was found that 13% of adolescents reported they had sent a hurtful message, 45% had received hurtful messages on instant message software, 16% in chat rooms, and 6% via emails (Goldsmith, 2011; Lemish, Ribak, & Aloni, 2009). In another study, 8% of the middle school students reported cyberbullying incidents (Trablus, Heiman, & Olenik-Shemesh, 2011), whereas in an additional study (Heiman, Olenik-Shemesh, & Eden, 2011) conducted on about 1,000 students from various schools in Israel, the percentage of students reporting cyberbullying rose to 11%.

Types of Cyberbullying: Perpetrators, Victims, and Witnesses

Perpetrators

The population actively or passively involved in cyberbullying includes three types of participants: A perpetrator or a cyberbully is a person who deliberately sends verbal or visual messages to threaten, intimidate, hurt, or humiliate another person. Several studies have pointed out that cyberbully children are prone to negative behavior also in non-Internet settings, which includes physical aggression, vandalism, theft, and cigarette and alcohol consumption (Ybarra & Mitchell, 2004), and are likely to have a low level of peer social support and/or low school achievements (Calvete, Orue, Estevez, Villardon, & Padilla, 2010; Li, 2007; Williams & Guerra, 2007).

Victims

The victims are children or adolescents who receive hurtful messages via the Internet, have their social network account broken into, have rumors spread about them, and so on. Studies examining the characteristics of cyberbullying victims have suggested that they have low social status within their age group, a low level of social integration, low self-esteem, behavioral problems at school, and a problematic relationship with their parents (Katzer, Fetchenhauer, & Belschak, 2009). In addition, it was found that both victimization and perpetration of cyberbullying are related to greater computer proficiency, frequent Internet use, more use of electronic communication tools, more Internet risk behavior since online activity in social networks requires creating a personal profile, and more revealing of personal details or ways of making contact (Huang & Chou, 2010; Katzer et al., 2009; Mesch, 2009; Vandebosch & Van Cleemput, 2009).

Witnesses

The witnesses are those who see the hurtful messages sent to others on the net. Occasionally the witnesses take an active part in cyberbullying, forwarding the messages on to others or responding “behind the scenes.” Usually, the witnesses are highly exposed to peer pressure, are considerably affected by the perpetrators, want to be valued by them, and belong to the stronger group (Druck & Kaplowitz, 2005). Coloroso (2003) describes the witnesses of cyberbullying as a supportive group that encourages and empowers the cyberbullies. Their support for cyberbullies may range from minimal to active and intensive support.

Cyberbullying and Disabilities

Various studies have examined online victimization among adolescent students with special needs, suggesting that these types of students perpetrate more and are more victimized than their typical peers. It has been pointed out that students with disabilities enrolled in self-contained classes reported more perpetration as well as victimization than those in inclusive settings (Carter & Spencer, 2006; Rose, Monda-Amaya, & Espelange, 2011; Son, Parish, & Peterson, 2012). Scholars have examined students with intellectual disability (Christensen, Fraynt, Neece, & Baker, 2012; Didden et al., 2009; Estell et al., 2009), students with learning difficulties (Kaukiainen et al., 2002), and students with attention-deficit/hyperactivity disorder (ADHD) and Asperger syndrome (Kowalski & Fedina, 2011).

Most of these studies have pointed to the increased rates of involvement in cyberbullying and victimization experiences among children with mild or multiple disabilities (including LD and emotional and behavioral disorders) studying in special education settings compared to typically achieving students (Estell et al., 2009; Farmer et al., 2012; Son et al., 2012; Swearer, Wang, Maag, Siebecher, & Frerichs, 2012). Other studies have specifically examined the relationships among cyberbullying, victimization, and students with LD (Kaukiainen et al., 2002). Within Mishna’s (2003) review comparing cyberbullying involvement among students with and without disabilities, it was found that students with LD are at higher risk to be cyberbullying and to be victims. In addition, several aspects were identified that could cause a negative impact on children with LD who are victims, such as low social status, poor social relationships, lack of social support, adjustment problems, feelings of rejection, symptoms of anxiety and depression, and low self-esteem. Another study (Baumeister, Storch, & Geffken, 2008) found that students with LD were more aggressive than typically achieving students and reported a higher level of peer bullying and victimization compared to non-LD students. Students with LD and comorbid diagnoses, probably because of their severe social skills deficits, academic difficulties, or attention difficulties reported on a greater amount of peer victimization compared to students without a comorbid diagnosis. Similar results (Kaukiainen et al., 2002) revealed that children with LD scored high on bullying and also tended to be victimized by others; thus, it appears they are likely to have bully–victim behavior.

Students diagnosed with LD are considered to be at higher risk for social and emotional difficulties, including a greater sense of loneliness, poorer social skills, social behavioral problems, rejection by peers or by their classmates, and/or lower self-esteem (e.g., Lackaye & Margalit, 2006), whereas adolescents diagnosed with multiple LD (reading and math) as well as students diagnosed with a single LD (reading or math) reported poorer functioning in school adjustment, poorer social behavior, and more emotional symptoms compared to typically achieving students (Martinez & Semrud-Clikeman, 2004). Svetaz, Ireland, and Blum (2000), whose study was based on data from the National Longitudinal Study of Adolescent Health, with a sample of 20,780 adolescents and 1,301 students with a learning disability, found that adolescents with LD had twice the risk of emotional distress, whereas females had twice the risk for violent involvement as cybervictims than their peers.

Gender differences

Different studies examined the relationships between gender and aggressive behavior, pointing out that across countries, boys are more likely to respond in an aggressive manner than are girls (e.g., Esther & Izaskun, 2012; Lansford et al., 2012), but it appears that only a few studies have examined the relationships among victimization or bullying, gender, and disabilities. Some findings have not found gender differences for bullying and victimization (Kaukiainen et al., 2002; Mishna et al., 2012; Swearer et al., 2012). As to cyberbullying findings, studies have found that boys are more likely to be bullies than are girls (Huang & Chou, 2010; Li, 2006; Smith et al., 2008) and that girls are more likely to be victims on the net. In addition, girls with LD were more likely than boys with LD to be victims (Mishna, 2003). Other studies have found no significant differences between boys’ and girls’ involvement in cyberbullying (Hinduja & Patchin, 2008; Katzer et al., 2009), similarly for children with intellectual and developmental disabilities (Didden et al., 2009). Until now, no specific study has been conducted on gender differences among students with LD and their involvement in cyberbullying.

Educational placement

In Israel, children diagnosed with LD are mostly included in general education classes, where there is one general education teacher for each subject matter. The students with LD receive learning assistance during or after school hours—an average of 2 to 5 hours per week—according to the student’s needs. In such classes, responsibility is shared by the mainstream teacher and the special education teacher who work together to identify the student’s needs and help him or her.

The alternative framework of educational placement for students with LD with additional challenges is separate classes within mainstream schools. These students have one special education teacher, and most of the time they study similar learning materials to the typically achieving students, but teaching strategies are more strictly oriented toward final exams (as in math, literature, language), whereas most of the class activities (school events, out-of-school activities) take place with the other classes on their grade level.

Cyberbullying has become a growing concern for adolescents, but little research has been carried out so far on cyberbullying and students with LD attending mainstreamed and special classes, taking gender into consideration. The goals of the present study were to examine the surfing patterns of adolescents, with and without LD, attending different educational settings (general classes and special education classes) and to better understand their involvement and response to cyberbullying, compared to non-LD students and considering gender differences. We can assume that students with LD will be more vulnerable as well as more involved as victims and/or perpetrators in cyberbullying. Specifically, students with LD attending special education classes, because of their multiple behavioral, social, or emotional difficulties, are expected to bully and/or be bullied more than students attending general education classes.

Based on the disabilities literature review, we expected to find differences among the participants, mainly resulting from the degree of their disability. The research questions and hypotheses were the following:

What are the surfing patterns of students attending different educational settings? It was expected that typically achieving students would make use of the Internet more extensively than the other students.

Are students with LD more involved as cybervictims/cyberperpetrators? It was expected that students with LD would be more cybervulnerable than typically achieving students.

Do students with LD react differently to cyberbullying experiences than non-LD students? It was assumed that students with LD would respond with limited strategies compared to typically achieving students.

What behavioral and emotional reactions are raised to cyberbullying experiences as related to the different student groups? We assumed that cybervictimization experiences among students with LD might evoke more behavioral and emotional concerns than seen among typically achieving students.

Are there gender differences among the student groups? We expected that boys would more often be bullies than girls and that girls would be more vulnerable across the groups.

Method

Participants

The study included 507 students: 275 boys and 232 girls attending three middle schools and two high schools (from the 7th grade to 10th grade) in Israel. The age range was from 12 to 17 years (M = 14.4, SD = 1.18). Of the entire sample, 105 (20.71%) were in 7th grade, 190 (37.48%) were in 8th grade, 99 (19.53%) were in 9th grade, and 113 (22.28%) were in 10th grade (see Table 1).

Table 1.

Participants’ Characteristics by Education Settings.

	Students With LD, General Education Classes (n = 149)		Students With LD, Special Classes (n = 116)		Typically Achieving Students (n = 242)
Variable	n	%	n	%	n	%
Grade
7th grade	38	25.5	19	16.3	49	20.2
8th grade	61	40.9	46	39.7	83	34.3
9th grade	16	10.7	25	21.6	58	24.0
10th grade	34	22.8	26	22.4	52	21.5
Gender
Male	78	52.3	82	70.7	117	48.3
Female	71	47.6	34	29.3	125	51.7

The sample consisted of three groups: 149 students with LD attending general education classes, 116 students with comorbid LD attending special education classes, and 242 typically achieving students, as a comparison group. No significant age differences emerged between groups, F(2, 507) = 2.75, p = .65; significant differences emerged for gender between groups, χ²(2, 507) = 22.82, p = .00, η = .23, as within special education classes, there were fewer girls and more boys compared to the other groups.

Students with LD

The students with LD had been formally diagnosed either by the psychological services agency or by a private psychologist, prior to entering the school and/or the class. The Israeli criteria for LD classification include results from a battery of tests, such as achievement test scores with a marked deficit in academic achievement for at least 2 years below grade level and average or above-|average intelligence. In addition, the definition of LD incorporates exclusion criteria such as absence of neurological problems, sensory impairments, and absence of problems presumed to be the result of environmental, economic, or cultural factors. All participants with LD were identified as having problems, such as difficulties with reading, writing, and/or spelling in the first language (Hebrew).

Students with LD in special education classes

These students were diagnosed with comorbid LD, especially with behavior and/or emotional problems, conduct disorders, ADHD, communication impairment, and/or language impairment. After comprehensive educational and psychological tests, they were advised to attend special education classes.

According to the Israeli Law of Special Education and the Israeli regulations for privacy protection (Ministry of Education, Culture and Sports, 1996), specific test scores were not available to the research team. However, by definition, for an LD diagnosis, the IQ score must be in the normal range.

Procedure

After receiving approval from the Ministry of Education Ethics Board and the local school principal, letters were sent to parents via the class teachers explaining the goals of the study. Parents could object to their child’s participation by signing a letter. The students’ participation was voluntary, based on parental approval, and 95% of the parents approved their child’s participation in the study. All the questionnaires were distributed to the students in the schools during class time for one hour under the supervision of one of the researchers. Students completed the questionnaire anonymously.

Measure

The Cyberbullying Self-Report Questionnaire (Smith et al., 2008) includes 20 items regarding general information on Internet usage (e.g., “How often do you use the Internet?”); students’ experiences as victims (e.g., “Have you ever been cyberbullied?”), perpetrators (e.g., “Have you ever taken part in cyberbullying?”), and witnesses (e.g., “Do you know of anyone who has been cyberbullied?”); strategies to use if being exposed to cyberbullying (e.g., “What do you think are the best ways to stop cyberbullying?”); and the emotional aspects of being cyberbullying (e.g., “How do you think someone who has been cyberbullied would feel?”). A dichotomous response scale (yes/no) was created for students who responded positively to one or more experience (being a victim, a perpetrator, a witness) versus none. In addition, demographic information was collected.

Results

Surfing Patterns

Examining the different usage patterns of surfing the net by groups, including surfing in one’s room, in another room, or at a friend’s house, revealed no significant differences among the groups. The only significant differences were found for the item “surfing for preparing homework,” as students in special classes reported a lower rate than did the other groups, χ²(2, 507) = 36.33, p < .001, η = .29, and students in LD general education classes reported a higher tendency toward downloading music from the net compared to the other groups, χ²(2, 507) = 15.00, p < .01, η = .19.

The students from the different groups spent almost the same number of hours on the Internet (range between 0.5 hour to 24 hours per day), with a mean of 3.6 per day (SD = 3.2), with no significant differences among the groups. In addition, students were asked to estimate their expertise on the net from low (1) to excellent (4). This measure had a mean of 3.15 (SD = .73), with no significant differences among the groups.

Cyberbullying Experiences

The students’ responses to their experiences of being a victim, a perpetrator, or a witness or knowing someone who was hurt on the net were transformed into a dichotomous categorization (yes/no). In all, 75 participants (14.9%) reported being victimized at least one time in the previous year, 64 students (13%) reported being a perpetrator, 160 students (33.8%) were witness to cyberbullying, 188 students (37.6%) were familiar with others who were hurt because of cyberbullying acts, and a lower percentage of the participants were both victims and perpetrators (n = 22, 4.5%).

To further examine differences among the three groups (LD in general classes, LD in special classes, typically achieving students), chi-square analyses were conducted with the five categories of cyberbullying. Results revealed that students with LD in special education classes were more often cybervictims than were students from the other groups, χ²(2, 505) = 6.9, p < .05, η = .12, reported being cyberperpetrators more often than the other students, χ²(2, 492) = 10.5, p < .05, η = .14, and were more often both victim and perpetrator, χ²(2, 492) = 6.9, p < .05, η = .14. It was found that for being a witness and knowing someone who was hurt by the net, more typically achieving students reported yes compared to the other groups, respectively, χ²(2, 500) = 6.9, p < .05, η = .13; χ²(2, 475) = 6.3, p < .05, η = .13.

Gender Differences

To further examine differences between participants’ genders, chi-square analyses were conducted with the different types of cyberbullying. Results revealed significant differences, as 18.2% of boys versus 5.8% of girls responded affirmatively to being cyberperpetrators, χ²(2, 494) = 18.29, p < .001, η = .19. Regarding cybervictims, 62.8% of the girls versus 50.5% of the boys reported themselves as victims, χ²(2, 494) = 3.13, p < .05, η = .08. No significant differences were found for being a cyberwitness, 27.6% boys versus 33.9% girls, χ²(2, 494) = 2.34, ns, nor for the question of knowing someone who was a victim, 35.6% boys versus 40.3% girls, χ²(2, 494) = 1.15, ns.

In addition, we examined the differences between girls and boys separately by groups for each cyberbullying type (a victim, a perpetrator, a witness, and knowing someone who was cyberbullied). As presented in Table 2, chi-square analyses revealed that girls with LD attending special classes reported being victims on the net more often, χ²(2, 226) = 16.40, p < .001, η = .27, and were often perpetrators on the net compared to the other groups, χ²(2, 226) = 5.93, p < .05, η = .15. Among the boys, the only significant difference was found for the question “Do you know someone who was hurt on the net?” Typically achieving students reported a significantly lower rate than did students from the other groups, χ²(2, 275) = 11.22, p < .001, η = .21. Furthermore, we examined the distribution of the students who reported being a victim as well as a perpetrator in each one of the groups and among genders. Among all 273 male participants, 16 boys (5.9%) reported on both experiences, whereas among 226 female participants, only 6 (2.7%) were both victims and bullies. Significant differences emerged only for the groups of girls, as more girls in special classes reported both being bullied and bullying others compared to girls from the other groups, χ²(2, 226) = 7.88, p < .05, η = .18.

Table 2.

Involvement in Cyberbullying by Gender and by Student Groups.

	Students With LD, General Education Classes (n = 149)		Students With LD, Special Classes (n = 116)		Typically Achieving Students (n = 242)
Variable	n	%	n	%	n	%
Have you been a victim on the net?
Boys	9	11.8	11	14.7	13	11.2
Girls	9	15.5	11**	25.5	19	15.3
Have you been a perpetrator on the net?
Boys	3	4.2	3	9.7	7	5.6
Girls	15	16.9	21*	22.6	14	12.5
Have you been a witness to cyberbullying on the net?
Boys	30	39.0	33	40.2	32	27.6
Girls	15	21.1	8	25.8	42	33.9
Do you know someone who was hurt on the net?
Boys	32	41.6	37	45.1	28**	24.1
Girls	27	38.0	15	48.4	49	39.5
Being a victim and a perpetrator on the net
Boys	4	5.26	6	7.32	6	5.66
Girls	0	0.0	3	10.7*	3	2.42

p < .05. **p < .001.

Students’ Responses to Being Cyberbullied

To examine specific student responses of being cyberbullied, an ANOVA was conducted on the students’ responses, according to student groups and gender. As presented in Table 3, significant results were found for groups, F(2, 287) = 3.56, p < .05, η = .16. A post hoc Scheffe test revealed that students with LD in special classes more often used cyberattack response as a strategy, fewer shared the cyberbullying event with others, more reported laughing about being cyberbullied, and fewer used “switched off the Internet” as a strategy compared to the other groups. No significant differences were found for gender, F(1, 287) = 0.82, ns.

Table 3.

Students’ Responses to Being Cyberbullied or Being a Cybervictim.

	Students With LD, General Education Classes (n = 149)		Students With LD, Special Classes (n = 116)		Typically Achieving Students (n = 242)
Variable	n	%	n	%	n	%
Ignored	40	26.8	29	25.0	82	33.9
Attack back	31	20.8	41	35.3*	59	24.4
Told a friend	29	19.5	19	16.4*	49	20.2
Laughed about it	27	18.1	28	24.1*	46	19.0
Stopped using the net	26	17.4	15	12.9*	58	24.0
Asked cyberbully to stop	23	15.4	18	15.5	51	21.1
Told parents	17	11.4	14	12.1	37	15.3
Told teacher	9	6.0	3	2.6*	17	7.0
Called police	6	4.0	3	2.6*	15	6.2
Documented the event	6	4.0	3	2.6*	9	3.7

p < .05.

Correlations

Pearson correlations were conducted to examine the relationships between each student’s educational settings—being a cybervictim, student reports of scholastic grades, attention span, and variation within social status—with the following three questions: (a) Did your involvement in cyberbullying change your scholastic grades? (b) Did your involvement in cyberbullying change your social situation? and (c) Did your involvement in cyberbullying change your ability to concentrate when learning? Almost similar results were found for the various student groups. A significant positive correlation was found for cybervictims and social status (non-LD, r = .17, p < .05; LD general class, r = .49, p < .001; LD special class, r = .24, p < .05), for cybervictims and students’ scholastic grades (for non-LD, r = .03, ns; LD general class, r = .34, p < .001; LD special class, r = .14, ns), and for cybervictims and students’ attention span (for non-LD, r = .23, p < .01; LD general class, r = .31, p < .01; LD special class, r = .50, p < .001).

Furthermore, the relationship between being a cybervictim and not being a cybervictim was examined by the students’ self-reported scholastic achievements (lower, higher, did not change), by the amount of the students’ attention span (lower, higher, did not change), and by social status (having fewer or more friends, did not change). The results of chi-square analyses revealed that students with LD in general education who reported being cybervictims reported lower scholastic achievement, χ²(2, 74) = 4.60, p < .05, and lower concentration, χ²(2, 74) = 5.8, p < .05, but no significant differences were reported on changes in their social status. Students with LD in special classes reported only lower concentration, χ²(2, 81) = 6.12, p < .05, but no significant differences were reported for changes to their grades or their social status. No differences were found for typically achieving students, between being a cybervictim and not being a cybervictim for grades, attention, or social status.

To examine the differences among the three groups regarding specific reactions to cyberbullying, an ANOVA was conducted on students’ responses, F(2, 287) = 5.48, p < .05, η = .19. Post hoc tests revealed significant differences between student groups, as students in special classes reported lower percentages of emotional and behavioral reactions, such as being less anxious, sad, or stressed, than did students in general classes; fewer reported problems with friends, at school, or at home (see Table 4). No significant results were found for gender.

Table 4.

Specific Reaction to Being a Cyberbully or Cybervictim.

	Students With LD, General Education Classes (n = 149)		Students With LD, Special Classes (n = 116)		Typically Achieving Students (n = 242)
Variable	n	%	n	%	n	%
Angry	52	34.9	49	42.2	97	40.1
Anxious	44	29.5	22	19.0*	100	41.3
Sad	35	23.5	22	19.0*	64	26.4
Stressed	31	20.8	20	17.2*	66	27.3
Frustrated	29	19.5	19	16.4*	46	19.0
Sleep problems	23	15.4	14	12.1*	47	19.4
Loss of appetite	19	12.8	10	8.6	19	7.9
Problems with friends	27	18.1	15	12.9*	38	15.7
Unwilling to go to school	25	16.8	16	13.8*	51	21.1
Problems at home	24	16.1	13	11.2*	47	19.4
Learning problems	14	9.4	11	9.5	29	12.0

p < .05.

Discussion

The aims of the present study were to examine the behavioral patterns of students with LD attending different educational settings, to identify their involvement in and experience with cyberbullying, and to examine if there were gender differences in the various types of cyberbullying, assuming that students diagnosed with comorbid LD problems in a special education setting might be more involved in and vulnerable to cyberbullying compared to other students. Previous research has shown that students with mild disabilities were cyberbullies more often than the other children (Estell et al., 2009). The results of the present study are consistent with those of previous studies that show that students with LD have greater involvement in cyberbullying and cybervictim than do typically achieving students (Mishna, 2003). As few studies have been conducted regarding the cyberexperiences of students with LD attending special education classes, the main contribution of the present study was to focus on students with different levels of severity of LD and their cyberinvolvement and vulnerability. All students who participated in the study considered themselves to have good to excellent expertise on the Internet, and they reported using the Internet almost the same number of hours per day, either for homework or for pleasure and social communication. The higher percentage of all the study participants who are involved in cyberbullying and violence is a reason to be concerned in particular with regard to students who are a priori at higher risk for social and emotional vulnerability.

Our results indicated that students diagnosed with LD attending special education classes were more often victims and perpetrators of cyberbullying. The findings also showed that student involvement within the social net, as victims or as perpetrators, may increase the risk of being hurt, and being a cybervictim was correlated with lower grades and lower concentration. Considering the severity of students with comorbid LD, they might have a higher predisposition to be vulnerable or at risk than the other students. For example, it was found that students attending special education classes respond in a more aggressive way on the net and are less willing to share their experience with another person (a parent, a teacher, the police) documenting the event compared to other groups. Thus, we assume that these students’ responses are the result of their mild disability temperament, as was found in previous studies, which estimated that more than 50% of the children with LD and ADHD faced interpersonal difficulties because of their tendency to respond in an aggressive way, impatiently, or in a loud voice (Moon, Zentall, Grskovic, Hall, & Stormont, 2001). These results are consistent with those of a previous study (De Boo & Prins, 2007), indicating that children diagnosed with ADHD and LD often encounter social problems in developing and/or maintaining social interactions and interpreting social codes and often behave and respond in an impulsive way, tend to be aggressive, and tend to be overpowering toward others.

As victims of cyberbullying, students in special classes as well as students with LD in general classes confirm that being involved in cyberbullying disturbs their attention and concentration, and for students with LD in general classes, it affects their academic achievement.

Regarding gender differences, similar to previous studies (e.g., Hinduja & Patchin, 2008, 2013; Katzer et al., 2009), it was found that girls are more likely to be cybervictims than are boys and that girls in special education classes are at higher risk for being cybervictims (25.5%) than are girls in other education settings. In addition, more girls in special education reported being perpetrators (22.6%) than mainstream girls, and we assume that, in reality, percentages for being victimized or bullied are much higher. These results are consistent with previous findings that girls are at higher risk of being cybervictims (Farrington, Ttofi, & Losel, 2011).

What might be the reasons that girls in special education classes reported higher rates of involvement in cyberbullying? Might this be because of their special characteristics as having more serious behavioral and/or social-emotional problems? Are they more vulnerable or just more willing to admit their involvement in cyberbullying? Further and more in-depth research is needed.

Limitations and Additional Research

The present study has some limitations: The different comorbid disabilities were not separately dealt with, and the study relied exclusively on student self-report. Further studies are needed to examine more specific disorders, including a larger sample and a wider range of age groups, such as younger children, to determine their experience as perpetrators and/or victims, taking into consideration social and emotional measures, such as social skills, competence, social status, satisfaction with life, and so on.

Additional research should include students in various educational settings, comparing different places (urban, rural) and taking into consideration different aspects of risk and protective aspects, such as students’ age, relationships with parents, and social environment. In addition, studies should be expanded to include the perspective of various school staff, such as supervisors, principals, educational counselors, psychologists, and educational coordinators, as well as parents. It would be desirable to hold personal interviews regarding students’ experiences with cyberbullying. Additional studies might consider using the concept of mixed-methods research, including both quantitative and qualitative methods (Harrits, 2011), to more deeply understand the personal view as perceived by adolescents who are involved in cyberbullying.

Implications

Given the increasing rate of accessibility to technology in both schools and homes, these findings highlight the importance of addressing cyberbullying, with respect to both research and intervention, as a unique phenomenon with equally unique challenges for students, parents, and teachers. The present study adds to the growing literature on the contribution of the education system to the cyberbullying phenomenon regarding students diagnosed with LD with different levels of severity. These students are considered as having social difficulties in the establishment of interpersonal relationships as well as to be more socially and emotionally vulnerable than typically achieving students.

As it appears that cyberbullying has become a new version of aggression that takes place in schools and at home, our study has important implications for the development of cyberbullying prevention programs. There is a need for the educational team in the school to be aware of the possible scholastic, social, and emotional impacts. Moreover, when planning and conducting a constructive intervention program for cybercoping, it is of great importance to adapt the program to students who are in special education classes as they are at higher risk of being bullied.

These specific programs for prevention and intervention should be taught during class lessons, focus on strengthening students’ social skills to establish close and trustworthy relationships to diminish the exposure to cyberbullying, and enhance the children’s awareness of safe Internet behavior. Moreover, the findings highlight the need to identify students who are victimized, in particular children with LD, as they are less likely to seek support or to share their cyberexperience. The results contribute to the LD field of cyberbullying research, showing that LD students are much more involved in cyberbullying, as victims, perpetrators, and witnesses in cyberbullying. Given that students with a severe comorbid LD diagnosis are at higher risk for victimization, social programs and training for social behavior as well as implementation of useful strategies for coping with cyberbullying are recommended.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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