BYSTANDER APATHY

Journal of Child and Family Studies (2020) 29:2390–2401 https://doi.org/10.1007/s10826-020-01739-9

ORIGINAL PAPER

Parental Support, Health, and Cyberbullying among Adolescents with Intellectual and Developmental Disabilities

Michelle F. Wright1,2 ● Sebastian Wachs3

Published online: 27 May 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020

Abstract Some studies reveal that adolescents with intellectual disabilities and developmental disabilities are more likely to be victims of both face-to-face bullying and cyberbullying. Research also suggests that these adolescents are likely to witness bullying victimization. More research is needed to better understand the negative outcomes associated with their experiences. The purpose of this short-term longitudinal study was to investigate the buffering effect of parental social support on the associations of cyberbullying victimization and bystanding to subjective health complaints, suicidal ideation, and non- suicidal self-harm. Participants were 121 adolescents (63% male; M age= 14.10 years) with intellectual disabilities and developmental disorders who completed questionnaires on their face-to-face and cyberbullying victimization and bystanding, parental social support, subjective health complaints, suicidal ideation, and non-suicidal self-harm during the 7th grade (Time 1). In 8th grade (Time 2), they completed questionnaires on subjective health complaints, suicidal ideation, and non-suicidal self-harm. The findings revealed that the positive associations between Time 1 cyberbullying victimization and Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm were stronger at lower levels of Time 1 parental social support, while high levels of Time 1 parental social support diminished these relationships. Similar patterns were found for Time 1 cyberbullying bystanding and Time 2 subjective health complaints. Parental social support has a buffering effect on the relationships among cyberbullying victimization, bystanding, and health outcomes among adolescents with intellectual and developmental disorders.

Keywords Bystander ● Victimization ● Health ● Suicidal Ideation ● Self-Harm

Highlights ● Parental social support was related negatively to cyberbullying victimization. ● Positive associations between cyberbullying victimization and subsequent subjective health complaints, suicidal ideation,

and non-suicidal self-harm. ● Parental social support diminished the positive relationships among cyberbullying victimization, subsequent subjective

health complaints, suicidal ideation, and non-suicidal self-harm.

The internet has the potential to help individuals with dis- abilities by removing the physical barriers (e.g., accessibility of locations) associated with face-to-face interactions (Dom- ingo 2012; Hassett et al. 1992; Seltzer 1995). Almost all adolescents, including those with disabilities, have embraced the internet, new media, and digital technologies, with some reporting that they are constantly connected. Adolescents’ frequency of technology use is a risk factor associated with their exposure to cyberbullying (Didden et al. 2009; Smith et al. 2008). Approximately 87% of adolescents with dis- abilities in one study reported that they owned a cell phone, 97% used a computer at home, 57% played online games,

* Michelle F. Wright [email protected]

1 Department of Psychology, Pennsylvania State University, University Park, PA 16802, USA

2 Faculty of Social Studies, Masaryk University, 60200 Brno, Czech Republic

3 Department of Educational Studies, University of Potsdam, 14476 Potsdam, Germany

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43% used email, 31% downloaded pictures and videos, and 24% chatted on a website (Didden et al. 2009), indicating that these adolescents utilize technology and more attention is needed to investigate their online experiences. Furthermore, adolescents with disabilities are more likely to develop close relationships online and disclose more personal information in these relationships than their nondisabled peers (Wells and Mitchell 2014). Disclosing more information online is another risk factor associated with cyberbullying victimization, further highlighting the importance of focusing research attention on disabled adolescents’ online experiences. The majority of cyberbullying experiences for adolescents involve being bystanders and the literature indicates that disabled adoles- cents also experience cyberbullying as cyberbystanders (Heiman et al. 2015; Smith et al. 2008). Witnessing cyber- bullying and being victimized by cyberbullying are both related to negative adjustment difficulties, such as depression and anxiety (Bauman et al. 2013; Campbell et al. 2012; Hinduja and Patchin 2008; Kowalski and Limber 2013; Wright 2015; Wright et al. 2018).

Cyberbullying victimization is defined as being subjected to intentionally hostile, intimidating, and embarrassing behaviors perpetrated through information and commu- nication technologies, such as email, online games, gaming consoles, mobile devices, and social networking websites (Grigg 2010; Walker et al. 2011). Researchers are con- cerned with cyberbullying because it is associated with negative adjustment difficulties (e.g., depression, anxiety, loneliness, poor academic performance; Bauman et al. 2013; Campbell et al. 2012; Hinduja and Patchin 2008; Kowalski and Limber 2013; Wright 2015) and suicidal ideation and non-suicidal self-harm (e.g., Bauman et al. 2013; John et al. 2018). Other than the psychological issues related to cyberbullying victimization, some research has focused on the association between experiencing cyber- bullying and subjective health concerns (e.g., stomach- aches, headache). Studies on the relationship between physical health concerns and cyberbullying victimization revealed that adolescent victims of cyberbullying reported more sleeping difficulties, headaches, poor appetite, and skin problems than uninvolved adolescents (Beckman et al. 2012; Kowalski and Limber 2007; Sourander et al. 2010). Controlling for traditional face-to-face bullying victimiza- tion and computer use, Vieno et al. (2015) and Laftman et al. (2013) replicated findings concerning the positive association between cyberbullying victimization and somatic health consequences among adolescents.

Because adolescents of different backgrounds have fully embraced technologies, they all are at risk for experiencing cyberbullying and therefore it is important to focus on cyberbullying victimization among different types of ado- lescents, especially those with disabilities. It is further imperative to focus on these adolescents because adolescents

with disabilities were more likely to report that cyberbully- ing victimization was distressing to them than adolescents without disabilities (Wells and Mitchell 2014). In the lit- erature on face-to-face bullying victimization, researchers have found that adolescents with disabilities reported nega- tive adjustment difficulties (e.g., depression, anxiety) asso- ciated with victimization (Hu et al. 2016; Van Roekel et al. 2010). The one available study on adjustment consequences of cyberbullying victimization among disabled adolescents revealed that adolescents with intellectual disabilities and developmental disorders reported greater depression when they were victimized online (Wright 2016).

Adolescents have different roles in cyberbullying, and one of the most common ways for adolescents to be involved in cyberbullying is by being bystanders (Wachs 2012; Wright et al. 2018). Thus, greater research attention is being given to adolescents’ experience of cyberbullying as cyberbystanders. Cyberbystanding is defined as seeing/ witnessing behavior occurring between cyberbully(ies) and cybervictims(s), and not becoming involved in the situation (Smith et al. 2008). Cyberbystanders are less likely to report cyberbullying to adults than offline bullying because there are less adults present in the online worlds of adolescents, the bystander might not know the individuals involved in the situation, and the increased potential for the situation to involve almost an infinite amount of bystanders, which might lead to the perception that someone else will report the situation (e.g., bystander effect; Barlinska et al. 2018). One of the few studies to focus on the negative adjustment difficulties associated with witnessing cyberbullying found a positive relationship among witnessing cyberbullying, depression, and anxiety (Wright et al. 2018). Similar pat- terns are found concerning offline bullying such that negative bystander behavior (e.g., not intervening in bul- lying incidences) is associated positively with adolescents’ anxiety, depression, and academic problems (Evans et al. 2018; Rivers et al. 2009). No studies have focused on the relationship between witnessing cyberbullying and sub- jective health complaints. Given that cyberbystanders might feel anxious and powerless that they could be the next one targeted for cyberbullying, not intervening in cyberbullying and wishing to intervene could increase cognitive dis- sonance among adolescents (Wright et al. 2018), and sub- sequently increase health concerns (Hull 2002). Findings concerning face-to-face bystanding suggest that witnessing bullying can lead to co-victimization and negative health outcomes, which might also occur for cyberbystanders (Kuther 1999). It is unclear how witnessing cyberbullying might relate to suicidal ideation and non-suicidal self-harm.

Little attention has been given to adolescents with intellectual disabilities and developmental disorders’ experience of witnessing cyberbullying. In one closely- related study, Heiman et al. (2015) found that adolescents

Journal of Child and Family Studies (2020) 29:2390–2401 2391

with ADHD experienced cyberbullying victimization and were also witnesses of cyberbullying. However, no studies have been conducted on the relationship between witnes- sing cyberbullying and negative adjustment difficulties among adolescents with intellectual disabilities and devel- opmental disorders. Considering the research on the simi- larities between disabled and nondisabled adolescents’ adjustment difficulties for cyberbullying victimization and that nondisabled adolescents experience such difficulties after witnessing cyberbullying, it might be reasonable to propose that adolescents with intellectual disabilities and developmental disorders could experience negative adjust- ment difficulties. Research linking negative adjustment difficulties with cyberbullying victimization and cyberbys- tanding underscores the importance of considering moder- ating variables in these associations.

Parental social support might reduce the subjective health complaints, suicidal ideation, and non-suicidal self- harm among adolescents with intellectual disabilities and developmental disorders. Defined as adolescents’ percep- tions that they are cared about, respected, and are part of a social network of people who are concerned with their welfare, perceived social support reduces the negative consequences related to adolescents’ peer victimization (Cohen et al. 2000; Davidson and Demaray 2007; Holt and Espelage 2007). After experiencing a negative event, it is important for adolescents to have someone who can provide physical, social, and psychological support. Such support enables adolescents to feel cared for and believe that they have someone who is there for them during challenging times and in difficult situations.

One of the more common sources of social support for adolescents are their parents (Marini et al. 2006). Ample research attention has been given to the protective role of perceived parental social support in reducing adolescents’ exposure to face-to-face bullying victimization. Galand and Hospel (2013) found that lower perceptions of family social support were linked positively to offline peer victimization among high school students. Research on face-to-face bullying victimization and parental social support also has revealed that such social support buffers against the negative consequences associated with peer victimization. Low parental social support and frequent peer victimization were related to poor mental health among adolescents in Australia (Rigby 2000). Other studies have revealed that high levels of social support from family and externalizing behaviors were less related at higher levels of offline peer victimization (Williams et al. 2005) and that high levels of social support related to less depression and anxiety when adolescents experience greater victimization (Davidson and Demaray 2007; Holt and Espelage 2007; Tanigawa et al. 2011). Rothon et al. (2011) found that per- ceived social support from family reduced victims’ risk of poor academic progress.

Some research attention has been given to the role of parental social support in adolescents’ experience of cyberbullying victimization. In one study, Fanti et al. (2012) found that greater perceived family social support dimin- ished adolescents’ cyberbullying victimization, especially when their friendships were low quality and unsupportive or when they were from single-parent households. Further- more, Smokowski et al. (2014) found that perceived social support from parents, teachers, and friends reduced ado- lescents’ cyberbullying victimization, with the effects being strongest for parental social support. Other research further supports the importance of perceived parental social support for reducing the likelihood of experiencing cyberbullying and the associated effects of depression and anxiety (Navarrro et al. 2015; Wright 2015). Few studies have been conducted on the moderating effect of parental social sup- port on the associations between cyberbullying victimiza- tion and adjustment difficulties among adolescents with intellectual disabilities and developmental disorders. In one related study on this topic, Wright (2016) found that par- ental social support reduced self-reports of depression fol- lowing cyberbullying victimization among adolescents with intellectual disabilities and developmental disorders. It is unclear whether parental social support would reduce the effects of cyberbystanding among disabled adolescents, as no research has been conducted on this topic.

The aim of this study was to investigate the moderating effect of parental social support in the longitudinal rela- tionship of cyberbullying victimization and witnessing cyberbullying to subjective health complaints, suicidal ideation, and non-suicidal self-harm among adolescents with intellectual disabilities and developmental disorders. These associations were examined over one year, from 7th to 8th grade, and traditional face-to-face bullying victimi- zation and bystanding were controlled for in the analyses, given the high correlations among these variables (Smith et al. 2008; Wright and Li 2013; Wright et al. 2018). We were unconcerned with whether there might be differences for cyberbullying victimization and witnessing cyberbully- ing when it comes to the negative outcomes. Early ado- lescents were the focus of this research because of their higher rates of cyberbullying involvement when compared to children and older adolescents (Sevcikova and Smahel 2009). This research was guided by two research questions:

What are the associations among cyberbullying victimi- zation, witnessing cyberbullying, parental social support, and health issues (i.e., subjective health complaints, suicidal ideation, and non-suicidal self-harm)?

What moderating effect, if any, does parental social support have on the longitudinal relationships of cyberbul- lying victimization and witnessing cyberbullying to health issues (i.e., subjective health complaints, suicidal ideation, and non-suicidal self-harm)?

2392 Journal of Child and Family Studies (2020) 29:2390–2401

Methods

Participants

Participants were 121 8th graders (63% male; M age= 14.10 years; ages range from 13–15 years old) with intel- lectual disabilities and/or developmental disorders from the suburbs of a large Midwestern city in the United States. The ten schools had inclusion classrooms, with adolescents spending some time throughout the day in these classrooms. Adolescents’ IQ scores were between 56 and 121, with 84% of them having an IQ below 85. Some adolescents had developmental disorders (e.g., attention-deficit/hyper- activity disorder, autism spectrum disorder, learning dis- ability) and/or behavioral and emotional problems. The majority of adolescents identified as White (68%), followed by Black/African American (20%), Latinx (8%), biracial (2%), Asian (1%), and other (1%). No income data were collected from adolescents’ families but the schools were located in middle-class neighborhoods. Overall, 23% through 29% of adolescents from the ten schools received free or reduced cost lunch. A power-analysis was conducted with five predictors for multiple regression analyses, which yielded a minimum sample size of 101 participants.

Procedure

Prior to contacting data collection sites, the research received ethical approval from the Pennsylvania State University. Approval was also obtained from seven school districts to conduct research in eight of the schools (two schools were in the same school district). Principal approval was obtained from the other two schools. APA ethical standards were followed throughout the study. Research assistants were present during data collection at Time 1 (2016; 7th grade) and Time 2 (2017; 8th grade) to ensure compliance with procedures and answer questions. They were led by a graduate student with training on working with adolescents who had intellectual disabilities and developmental disorders.

Our site select procedure began with a list of 153 public schools in the suburbs of a large Midwestern city in the United States. From this list, 20 schools were randomly selected and then a recruitment email was sent to school principals. The recruitment email described the purpose of the study, methodology (i.e., questionnaires), and the time commitment for the study. Of the 20 schools, ten school principals agreed to allow their school to participate in the study. The principal investigator met with school principals and 7th and 8th grade teachers to discuss the study’s pur- pose, who would be invited to participate, and how long the study would take. Prior to making classroom announce- ments, school counselors identified adolescents with an IQ

of at least 50, diagnosed with an intellectual disability and/ or developmental disorder, and were able to read ques- tionnaires without assistance from a paraprofessional. Based on these criteria, 243 eligible adolescents were identified and a special announcement was made to these adolescents. The purpose of the study, what adolescents would be expected to do, and how long the study would take were explained to adolescents, with a graduate research assistant present who had training with special needs students. There were 243 permission slips distributed, and of these, 186 were returned with permission, 36 were returned without permission, and 21 were unreturned.

Adolescents completed self-report questionnaires on demographic information (i.e., age, gender, ethnicity), face- to-face bullying victimization and bystanding, cyberbully- ing victimization and bystanding, parental social support, subjective health complaints, suicidal ideation, and non- suicidal self-harm during the fall of 7th grade (2016; Time 1). Questionnaires were available in large-print to accom- modate adolescents enrolled in the study. Prior to admin- istering questionnaires, adolescents provided their own permission to participate in the study. There were 33 ado- lescents who either declined to participate in the study or were absent on the two days of data collection. At Time 1, the sample size was 153 adolescents.

During the fall of 8th grade (2017; Time 2), adolescents were asked to complete questionnaires on their subjective health complaints, suicidal ideation, and non-suicidal self- harm. Prior to data collection, a reminder letter was sent home to adolescents’ parents/guardians. If parents/guar- dians did not want their child to participate, they were asked to write their child’s first and last name on the letter and return the letter to their child’s school. Ten parents recorded their child’s name on the letter. Like Time 1 data collection, adolescents were asked again for their permission to parti- cipate in the study at Time 2. There were 22 adolescents who either declined to participate in the study again or who were absent on the two days of data collection. At Time 2, the final sample was 121. Debriefing was provided after adolescents completed the last measure. The debriefing sheet provided adolescents with community resources that were recommended by their schools’ guidance counselor. Adolescents were encouraged to contact the resources if they felt upset or concerned about anything discussed on the measures.

Measures

Face-to-face bullying victimization and bystanding

Adolescents were asked how often they experienced face-to- face bullying victimization and witnessed face-to-face bully- ing (Wright et al. 2014, 2018). Twelve items were included

Journal of Child and Family Studies (2020) 29:2390–2401 2393

on this questionnaire, with six assessing face-to-face bullying victimization and six assessing face-to-face bullying bystanding. The items assess both relational and verbal forms of face-to-face bullying victimization and bystanding. Con- firmatory factor analysis determined that a one factor solution fit the questionnaire better than a two factor solution. Therefore, the items were averaged to form one score for face-to-face bullying victimization and one score for face-to- face bullying bystanding. Items were rated on a scale of 1 (not at all) to 5 (all of the time) and were answered according to what adolescents experienced within the current school year. For face-to-face bullying victimization, sample items inclu- ded: “A peer called me insulting names” and “A peer spread rumors about me to get others not to like me”. Sample items for face-to-face bullying bystanding included: “Witnessed someone being insulted” and “Witnessed someone being called mean names”. Cronbach’s alphas were 0.88 for face-to- face bullying victimization and 0.86 for bystanding. This questionnaire was administered at Time 1 only.

Cyberbullying victimization and bystanding

Twelve items were included on this questionnaire to ask adolescents how often they experienced cyberbullying victi- mization and witnessed cyberbullying (Wright and Li 2013; Wright et al. 2018). Six items (e.g., was insulted online by someone, called mean names online) were included for cyberbullying victimization and six items (e.g., witnessed someone being insulted online, witnessed someone being called mean names online) assessed witnessing cyberbullying. The items assessed verbal and relational forms of cyberbul- lying and bystanding, and confirmatory factor analysis was performed. It revealed a one factor solution and therefore one factor was retained. Adolescents were asked to answer the items according to what they have witnessed or experienced during the current school year. Items were averaged sepa- rately to form separate scores for cyberbullying victimization and bystanding. All items were rated on a scale of 1 (never) to 5 (all the time), with Cronbach’s alphas of 0.89 for cyber- bullying victimization and 0.93 for bystanding. This ques- tionnaire was administered at Time 1 only.

Parental social support

Perceived social support from parents was assessed with the parent subscale of the Child and Adolescent Social Support Scale (Malekci et al. 1999). The subscale included 12 items (e.g., My parent or parents show they are proud of me), rated on a scale of 1 (never) to 6 (always). Items were averaged to form one final score on parental social support. High scores indicate greater perceived parental social sup- port. Cronbach’s alpha was 0.86. The questionnaire was administered at Time 1 only.

Subjective health complaints

The Health and Behaviour in School-aged Children Symptom Checklist was used to assess common health symptoms experienced with or without a diagnosis (Haug- land and Wold 2001). Adolescents rated eight health com- plaints experienced in the last six months, including headache, stomachache, backache, feeling low, feeling irritable or bad tempered, feeling nervous, difficulties in getting to sleep, and dizziness, on a scale of 1 (rarely or never) to 5 (about every day). Items were averaged to form one score on subjective health complaints, with higher scores indicating greater subjective health complaints. Cronbach’s alphas were 0.81 for Time 1 and 0.83 for Time 2.

Suicidal ideation

Adolescents answered two questions (i.e., during the past 12 months, how often have you seriously considered attempting suicide; during the past 12 months, did you make a plan about how you would attempt suicide; Center for Disease Control and Prevention 2011) regarding their suicidal ideation. The two items were rated on a scale of 1 (never) to 5 (very often), with both items averaged to form a final score on suicidal ideation. The correlation between the two items was 0.76. After data were brought back to the researchers’ laboratory, research assistants scored this questionnaire manually to identify any adolescent at risk for suicide. No adolescents were identified but if there were then a call would have been made to the schools’ guidance counselor and a referral would have been made.

Non-suicidal self-harm

The Self-Harm Inventory was administered to ask adoles- cents if they had ever intentionally engaged in specific behaviors without suicidal intent (Sansone et al. 1998). There were 22 items, answered with yes/no responses. Sample items included: hit yourself, cut yourself on pur- pose, and prevented wounds from healing. All items were combined to form a final score of non-suicidal self-harm, with points ranging from 0 to 22. This questionnaire was completed at Time 1 and Time 2, with Kuder-Richardson reliability of 0.83 for both time points.

Data Analyses

Six multiple hierarchical regression analyses were con- ducted. Predictors variables included cyberbullying victi- mization, cyberbullying bystanding, and parental social support. The outcome variables were Time 2 subjective health complaints, suicidal ideation, and non-suicidal

2394 Journal of Child and Family Studies (2020) 29:2390–2401

self-harm. Control variables included gender, face-to-face bullying victimization, face-to-face bullying bystanding, and Time 1 outcome variables. For example, in the model with Time 2 subjective health complaints, Time 1 subjective health complaints was included as a control variable, Time 1 suicidal ideation was included as a control variable for Time 2 suicidal ideation, and Time 1 non-suicidal self-harm was included as a control variable for Time 2 non-suicidal self-harm. For the hierarchical multiple regression analyses, Block 1 included gender, face-to-face bullying victimiza- tion, and Time 1 respective outcome variables. Block 2 included cyberbullying victimization or cyberbullying bystanding. Block 3 included parental social support. Block 4 included a two-way interaction between cyberbullying victimization or cyberbullying bystanding and parental social support. Continuous variables were centered. Sig- nificant interactions were probed using the Interaction program (Soper 2010). This program provides the simple slopes of the regression lines, unstandardized betas, and significance levels.

Results

In this study, we were interested in examining the asso- ciations among cyberbullying victimization, witnessing cyberbullying, parental social support, and health issues (i.e., subjective health complaints, suicidal ideation, non- suicidal self-harm). This purpose was examined through correlations and hierarchical multiple regression analyses. We also investigated the potential moderating effect of perceived parental social support in the relationships between cyberbullying victimization and bystanding and health issues. For this second purpose, we utilized hier- archical multiple regression analyses and the Interaction program to test any significant moderation effects (Soper 2010).

We conducted correlations among face-to-face bullying victimization, face-to-face bullying bystanding, cyberbul- lying victimization, cyberbullying bystanding, subjective health complaints, suicidal ideation, and non-suicidal self- harm (see Table 1 for complete table). We found that greater Time 1 face-to-face bullying victimization and cyberbullying victimization were related to higher Time 1 cyberbullying bystanding, Time 1 and Time 2 subjective health complaints, Time 1 and Time 2 suicidal ideation, and Time 2 non-suicidal self-harm. Greater Time 1 face-to-face bullying victimization and greater Time 1 face-to-face bullying bystanding were related. High Time 1 parental social support was related to lower Time 1 face-to-face bullying victimization, face-to-face bullying bystanding, cyberbullying victimization, and cyberbullying bystanding. Furthermore, greater Time 1 parental social support was Ta

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Journal of Child and Family Studies (2020) 29:2390–2401 2395

related to lower Time 1 and Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm. Each of the Time 1 and Time 2 subjective health com- plaints, suicidal ideation, and non-suicidal self-harm were associated with each other (Table 2).

Block 3 was the highest significant block for Time 2 non- suicidal self-harm (both cyberbullying victimization and bystanding) and for the model with Time 1 cyberbullying bystanding and Time 2 suicidal ideation. Thus, results from these three models will be interpreted within this section. Gender was not related to Time 2 non-suicidal self-harm for cyberbullying victimization and bystanding, and it was unrelated to Time 2 suicidal ideation for cyberbullying bystanding. Time 1 non-suicidal self-harm was related positively to Time 2 non-suicidal self-harm, and Time 1 suicidal ideation was related to Time 2 suicidal ideation. Higher Time 1 face-to-face bullying victimization, cyber- bullying victimization, and cyberbystanding were each related to Time 2 suicidal ideation and non-suicidal self- harm. Less Time 1 parental social support was related to higher Time 2 suicidal ideation and non-suicidal self-harm.

Significant two-ways interactions were found between cyberbullying victimization and parental social support for Time 2 subjective health complaints and suicidal ideation. Probing the interactions further revealed that the association between greater Time 1 cyberbullying victimization and higher Time 2 subjective health complaints (+1 SD: B=−0.23, SE= 0.08, p < 0.001; see Fig. 1a) and suicidal ideation (+1 SD: B=−0.17, SE= 0.03, p < 0.01; see Fig. 1b) were weaker when adolescents reported more parental social support. In addition, when adolescents reported less parental social support, greater Time 1 cyberbullying vic- timization was related to greater Time 2 subjective health complaints (−1 SD: B= 0.18, SE= 0.03, p < 0.01) and suicidal ideation (−1 SD: B= 0.17, SE= 0.04, p < 0.01).

The interaction between cyberbullying bystanding and parental social support was significant for Time 2 subjective health complaints only. When adolescents reported greater parental social support, the association between higher Time 1 cyberbullying bystanding and greater Time 2 sub- jective health complains was weaker (+1 SD: B=−0.15, SE= 0.02, p < 0.05; see Fig. 2). The opposite pattern was found when adolescents reported lower parental social support (+1 SD: B= 0.13, SE= 0.02, p < 0.05).

Discussion

This one-year longitudinal study examined the moderating effect of parental social support in the associations between cyberbullying victimization and bystanding and subjective health complaints, suicidal ideation, and non-suicidal self-harm among adolescents with intellectual disabilities

and developmental disorders. This study contributes to the broader literature on the protective factors that might reduce the negative adjustment difficulties associated with cyber- bullying victimization and bystanding. Our findings further highlight the importance of directing more research atten- tion to the online experiences of early adolescents with disabilities.

Time 1 parental social support was correlated negatively with cyberbullying victimization. Parents are a source of support and guidance in adolescents’ lives (Baldry and Farrington 2005; Davidson and Demaray 2007; Smokowski et al. 2014; Williams and Guerra 2007). Such support and guidance might allow opportunities for parents to discuss online risks with their children, reducing the likelihood that they might encounter such risks, including experiencing cyberbullying (Livingstone et al. 2011; Mesch 2009; Wright 2015, 2016). Conversations between parents and adolescents might involve strategies for dealing with cyberbullying, potentially leading some adolescents to avoid online situations that could result in negative experiences. Consistent with one study (i.e., Wright 2016), our findings suggest that adolescents with intellectual dis- abilities and developmental disorders also benefit from parental social support, reducing their cyberbullying victi- mization. Follow-up research should be conducted to better understand how parental social support might differ between adolescents with disabilities and without disabilities.

We found that Time 1 cyberbullying victimization was related positively to Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm. These findings are supported by the literature linking cyberbullying victi- mization to negative adjustment difficulties, including depression and anxiety (Bauman et al. 2013; Campbell et al. 2012; Kowalski and Limber 2013). Our findings extend this literature to other difficulties associated with cyberbullying victimization, specifically subjective health complaints. The literature has revealed that victims of cyberbullying are more likely to report somatic health complaints, such as poor appetite, headaches, and sleeping problems (Beckman et al. 2012; Laftman et al. 2013; Sourander et al. 2010; Vieno et al. 2015). Bauman et al. (2013) and John et al. (2018) found positive associations between cyberbullying victimization, suicidal ideation, and non-suicidal self-harm. Our findings are consistent with these studies and further extend literature on cyberbullying victimization to adoles- cents with intellectual disabilities and developmental disorders.

Similar to cyberbullying victimization, our findings revealed that Time 1 parental social support was correlated negatively with cyberbystanding, which is consistent with research by Wright (2016). Furthermore, Time 1 cyberbys- tanding was related positively to Time 2 subjective health

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Table 2 Multiple regression analyses: cyberbullying victimization and bystanding, parental social support, subjective health complaints, suicidal ideation, and non-suicidal self-harm

Time 2 Subjective Health Complaints

Time 2 Suicidal Ideation Time 2 Non-Suicidal Self-Harm

β R2 ΔR2 β R2 ΔR2 β R2 ΔR2

Cyberbullying Victimization

Block 1 0.23 0.23*** 0.26 0.26*** 0.20 0.20***

Gender 0.01 0.05 0.02

Time 1 Face-to-face Bullying Victimization 0.25* 0.28** 0.22*

Time 1 Dependent Variable 0.36*** 0.35*** 0.30***

Block 2 0.30 0.07*** 0.31 0.05*** 0.25 0.05***

Gender 0.01 0.04 0.01

Time 1 Face-to-face Bullying Victimization 0.23* 0.21* 0.21*

Time 1 Dependent Variable 0.30*** 0.32*** 0.30***

Time 1 Cyberbullying Victimization 0.26** 0.24* 0.23*

Block 3 0.39 0.09*** 0.37 0.06*** 0.29 0.04***

Gender 0.02 0.03 0.01

Time 1 Face-to-face Bullying Victimization 0.20* 0.24* 0.20*

Time 1 Dependent Variable 0.29*** 0.30*** 0.29***

Time 1 Cyberbullying Victimization (CV) 0.25* 0.24* 0.23*

Time 1 Parental Social Support (PSS) −0.22* −0.20* −0.21*

Block 4 0.43 0.04*** 0.44 0.07*** 0.29 0.01

Gender 0.02 0.03 0.01

Time 1 Face-to-face Bullying Victimization 0.19* 0.23* 0.18

Time 1 Dependent Variable 0.26** 0.30*** 0.24

Time 1 Cyberbullying Victimization (CV) 0.21* 0.23* 0.18

Time 1 Parental Social Support (PSS) −0.18* −0.19* −0.19

Interaction: CV × PSS −0.11* −0.15* −0.05

Cyberbullying Bystanding

Block 1 0.23 0.23*** 0.26 0.26*** 0.20 0.20***

Gender 0.01 0.05 0.02

Time 1 Face-to-face Bullying Bystanding 0.27* 0.26** 0.24*

Time 1 Dependent Variable 0.34*** 0.34*** 0.30***

Block 2 0.27 0.04*** 0.30 0.04*** 0.23 0.03***

Gender 0.01 0.03 0.02

Time 1 Face-to-face Bullying Bystanding 0.25* 0.24* 0.23*

Time 1 Dependent Variable 0.32*** 0.33*** 0.30***

Time 1 Cyberbullying Bystanding (CBy) 0.26** 0.10 0.11

Block 3 0.34 0.07*** 0.32 0.02*** 0.26 0.03***

Gender 0.02 0.03 0.01

Time 1 Face-to-face Bullying Bystanding 0.23* 0.23* 0.22*

Time 1 Dependent Variable 0.31*** 0.31*** 0.32***

Time 1 Cyberbullying Bystanding (CBy) 0.25* 0.11 0.09

Time 1 Parental Social Support (PSS) −0.24* −0.19* −0.20*

Block 4 0.40 0.06*** 0.32 0.01 0.26 0.01

Gender 0.03 0.02 0.02

Time 1 Face-to-face Bullying Bystanding 0.22* 0.23 0.21

Time 1 Dependent Variable 0.30*** 0.30 0.30

Time 1 Cyberbullying Bystanding (CBy) 0.25* 0.10 0.08

Time 1 Parental Social Support (PSS) −0.21* −0.18 −0.18

Interaction: CBy × PSS −0.12* −0.03 −0.02

Time 1 dependent variable corresponds to the respective Time 2 dependent variable. For example, for Time 2 subjective health complaints, Time 1 dependent variable is Time 1 subjective health complaints. For Time 2 suicidal ideation, Time 1 dependent variable is Time 1 suicidal ideation. For Time 2 non-suicidal self-harm, Time 1 dependent variable is Time 1 non-suicidal self-harm

*p < 0.05; **p < 0.01; ***p < 0.001

Journal of Child and Family Studies (2020) 29:2390–2401 2397

complaints. No literature is available to determine if our findings regarding the linkage between witnessing cyber- bullying and subjective health complaints are consistent with other studies. The closest study on this topic was conducted by Wright et al. (2018) who found a positive relationship among witnessing cyberbullying, depression, and anxiety. The connection between bystanding and negative outcomes might be explained by the co-victimization experienced by bystanders of cyberbullying which might negatively influ- ence their health (Kuther 1999). As a consequence of wit- nessing cyberbullying, adolescents with intellectual disabilities and developmental disorders might experience somatic symptoms. Not intervening in cyberbullying inci- dences might further harm adolescents’ health (Hull 2002). Witnessing cyberbullying was unrelated to suicidal ideation and non-suicidal self-harm. Explanation for such findings is difficult to reconcile with the existing literature as few stu- dies exist on this topic. In a related study, Rivers and Noret (2013) found that witnessing face-to-face bullying was associated positively with suicidal ideation when adolescents felt helpless following the bullying incident. We did not

assess feelings after the cyberbullying incidences, which might explain why we found no relationship between wit- nessing cyberbullying and suicidal ideation. Follow-up research should also examine cyberbystanders’ feelings following witnessing cyberbullying to also understand whether these feelings might help explain why we did not find associations between bystanding, suicidal ideation, and non-suicidal self-harm.

Another purpose of the study was to examine potential moderating effect of parental social support in the rela- tionships between cyberbullying victimization and bystanding and subjective health complaints, suicidal ideation, and non-suicidal self-harm among adolescents with intellectual disabilities and developmental disorders. Our findings revealed that higher levels of parental social support weakened the relationship between cyberbullying victimization and Time 2 subjective health complaints and suicidal ideation; in contrast, this relationship was stronger at lower levels of parental social support. In addition, we found that the relationship between cyberbullying bystanding and Time 2 subjective health complaints was weaker at higher levels of parental social support while this association was much stronger at lower levels of parental social support.

Social support provides adolescents with a social net- work of caring individuals whom they can turn to when they experience conflicts or stress in their lives. Having someone in their lives helps adolescents cope with negative situations/events and reduces or eliminates the negative consequences of stressful situations/events (Baldry and Farrington 2005; Cohen et al. 2000; Davidson and Demaray 2007; Fox and Boulton 2005; Holt and Espelage 2007). Support for this proposal is found in the research linking higher perceived social support to fewer symptoms of depression among adolescents (Camara et al. 2013; Ellonen et al. 2008; Velez et al. 2015). Parental social

Fig. 1 Interactions between cyberbullying victimization and parental social support for Time 2 subjective health complaints and Time 2 suicidal ideation

1

1.5

2

2.5

3

3.5

4

4.5

5

Low Cyberbullying Bystanding High Cyberbullying Bystanding

T im

e 2

Su bj

ec tiv

e H

ea lth

C om

pl ai

nt s

Low Parental Social Support High Parental Social Support

Fig. 2 Interaction between cyberbullying bystanding and parental social support for Time 2 subjective health complaints

2398 Journal of Child and Family Studies (2020) 29:2390–2401

support instills appropriate and effective coping strategies and increases adolescents’ self-efficacy regarding their ability to cope with and potentially avoid negative situa- tions online. Perceiving less parental social support could reduce adolescents’ confidence in their ability to cope effectively with negative situations, potentially increasing their susceptibility to subjective health complaints and suicidal ideation.

Limitations

There are a few notable limitations of the present study. We examined parental social support only, but there are other sources of social support in adolescents’ lives, including their teachers and friends. The moderating effect of social support might differ depending on the source of social support. Furthermore, social support might be perceived differently in various environments, such that adolescents might feel more supported face-to-face than online. Follow- up research should include different sources of social sup- port and consider how different contexts might influence perceptions of social support, as well as examine different forms of social support. The questionnaires used in this research included specific time frames (e.g., current school year, six months, one year). It was necessary to have a time frame on the behaviors and health concerns reported by adolescents as to avoid the likelihood that adolescents would report lifetime prevalence, which might overestimate the influence of cyberbullying victimization. However, the different time frames might have influenced our results, and follow-up research is needed with the same time frames. This study employed a one-year longitudinal design, with two waves of data collection. Such a design limits our understanding of the temporal ordering of the associations between parental social support, cyberbullying victimiza- tion, cyberbullying bystanding, and health issues. Longer- term designs should be conducted with additional waves of data collection to better understanding the buffering effects of parental social support. The sample size for this study was small, limiting the ability to make comparisons between different forms of disabilities and generalize our findings to other populations. Another concern is that we included adolescents who might have emotional issues and did not account for these issues in our analyses, which might have altered our results. Follow-up research should account for adolescents’ pre-existing characteristics, such as emotional issues, when examining the relationships con- sidered in this study.

Author Contributions M.W.: designed and executed the study, assis- ted and coordinated data analyses, and wrote the paper. S.W.: colla- borated with writing of the study and editing of the final manuscript.

Compliance with Ethical Standards

Conflict of Interest The authors declare that they have no conflict of interest.

Ethical Approval IRB approval was obtained from the Pennsylvania State University. Informed consent was obtained from participants in this study. APA standards were maintained throughout the completion of this study.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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