An-Najah National University Faculty of Graduate Studies THE EFFECT OF CORONA VIRUS (COVID-19) ON MENTAL HEALTH OUTCOMES AMONG PALESTINIAN CHILDREN VICTIMS OF BULLYING: SOCIAL SUPPORT AS MEDIATING VARIABLE By Shahd Mansour Supervisors Dr. Fayez Mahamid Dr. Guido Veronese This Thesis is Submitted in Partial Fulfillment of the Requirements for The Degree of Master of Clinical Psychology, Faculty of Graduate Studies, An-Najah ‎National University, Nablus- Palestine. 2022 ii THE EFFECT OF CORONA VIRUS (COVID-19) ON MENTAL HEALTH OUTCOMES AMONG PALESTINIAN CHILDREN VICTIMS OF BULLYING: SOCIAL SUPPORT AS MEDIATING VARIABLE By Shahd Mansour This Thesis was Defended Successfully on 26/6/2022 and approved by iii Dedication This thesis work is dedicated to my family. A special feeling of gratitude to my caring, supporting parents, who have always loved me unconditionally and whose great examples have taught me to work hard for issues that I aspire to achieve. iv Acknowledgements I would like to thank my supervisors Dr. Fayez Mahamid and Dr. Guido Veronese for their guidance and leadership. Lastly, I would like to express my deepest appreciation to my family especially my parents who generously provided love, support and their belief in me kept my spirits and motivation high during this process. v vi List of Contents Dedication ...................................................................................................................... iii Acknowledgements ...................................................................................................... iv Declaration ..................................................................................................................... iv List of Contents ................................................................................................................ vi List of Tables .................................................................................................................. vii List of Figures ................................................................................................................ viii List of Appendices ........................................................................................................... ix ABSTRACT ...................................................................................................................... x Chapter One: Theoretical Background ....................................................................... 1 1.1 COVID-19 and Mental health ..................................................................................... 2 1.2 COVID-19, Bullying and Cyberbullying .................................................................... 6 1.3 Mental health, Bullying and Cyberbullying ............................................................... 7 1.4 COVID-19, mental health, bullying and cyberbullying ............................................. 8 1.5 Mental Health and Social Support .............................................................................. 9 1.6 Bullying and Social Support ..................................................................................... 10 1.7 COVID-19, Mental Health, Bullying and Social Support ........................................ 11 1.8 Arab Palestinian children who live in Israel ............................................................. 11 Chapter Two: Methodology ............................................................................................ 14 2.1 Participants ................................................................................................................ 14 2.2 Measures ................................................................................................................... 14 2.3 Procedure .................................................................................................................. 17 2.4 Statistical Plan ........................................................................................................... 18 Chapter Three: Results .................................................................................................... 20 Chapter Four: Discussion ................................................................................................ 33 Chapter Five: Conclusion................................................................................................ 37 References ....................................................................................................................... 38 Appendices ...................................................................................................................... 48 ب‌ .............................................................................................................................. الملخص vii List of Tables Table 1: Descriptive statistics for research variables (N= 141) ...................................... 20 Table 2: Means of variables by gender ........................................................................... 21 Table 3: Means of variables by Class ............................................................................. 23 Table 4: Means of variables by Age ............................................................................... 24 Table 5: Means of variables by Parents Marital Status ................................................... 26 Table 6: The correlation between the variables .............................................................. 27 Table 7: Tests of Between-Subjects Effects ................................................................... 30 Table 8: Post Hock Table - Multiple Comparisons ........................................................ 31 viii List of Figures Figure 1: Conceptualized model of fear of COVID-19 .................................................. 32 Figure 2: Structural equation modeling of fear of COVID-19........................................ 32 ix List of Appendices Appendix 1: Consent form .............................................................................................. 48 Appendix 2: DEMOGRAPHIC FORM .......................................................................... 49 Appendix 3: Multidimensional Bullying Victimization Scale (MBVS) ......................... 50 Appendix 4: Adolescents Cyber-Victimization Scale (CYBVICS) ............................... 53 Appendix 5: The Strengths and Difficulties Questionnaire (SDQ) ................................ 56 Appendix 6: Fear of covid .............................................................................................. 58 Appendix 7: The Revised Child Anxiety and Depression scale (RCADS) .................... 59 Appendix 8: Multidimensional Scale of Perceived Social Support (MSPSS) ................ 62 Appendix 9: Extra review questions about bullying ....................................................... 64 Appendix 10: Reflection ................................................................................................. 65 x THE EFFECT OF CORONA VIRUS (COVID-19) ON MENTAL HEALTH OUTCOMES AMONG PALESTINIAN CHILDREN VICTIMS OF BULLYING: SOCIAL SUPPORT AS MEDIATING VARIABLE By Shahd Mansour Supervisors Dr. Fayez Mahamid Dr. Guido Veronese ABSTRACT Introduction: Previous studies showed that COVID-19 has negative effects on mental health by increasing depression and anxiety (Mahamid et al., 2021; Li et al., 2020). Moreover, bullying- according to previous studies- could affect mental health negatively. However, social support could positively affect mental health. Accordingly, this study aimeds at examining the effect of COVID-19 on children's mental health among victims of bullying and cyberbullying. Moreover, social support was tested as a mediating variable. The sample of this study consisted of (141) bullied children between the ages (9-13) years old. All of them were Palestinian Arabs living in Israel and from different primary schools. They were chosen by school counselors and class educators. Results: Data was collected using; Multidimensional Bullying Victimization Scale (MBVS), Adolescents Cyber-Victimization Scale (CYBVICS), the Strengths and Difficulties Questionnaire (SDQ), Questionnaire measuring the effect of COVID-19 on mental health outcomes, the Revised Child Anxiety and Depression Scale (RCADS), and Multidimensional Scale of Perceived Social Support (MSPSS). There was a positive correlation between Fear of COVID-19 and traditional bullying, cyber bullying, depression, and anxiety. Moreover, social support was correlated negatively with traditional bullying and cyber bullying. Also, there erre differences in traditional bullying, cyber bullying, depression, and parents' difficulties reported, as a function of parent marital status. Conclusion: This study was a comprehensive investigation that can be used extendedly on victims of bullying by training teachers and guiding parents to construct an emotional intervention plan to support those children emotionally and socially. Keywords: Covid19, Mental health, Depression, Anxiety, Bullying, Cyber bullying, Social support. 1 Chapter One Theoretical Background The year 2020 began with a new epidemic that originated in China and outbroke around the world. It has affected our lives, our physical health, our mental health, our economy and more- it is called COVID-19 (Mahamid et al., 2021). On 31 December 2019, World Health Organization (WHO) learned about a new virus which has been recently called a SARS-CoV-2 (COVID-19) as a result of reports about „viral pneumonia‟ in Wuhan in the Republic of China. The most common symptoms of COVID-19 are dry cough, fever, and fatigue as well as Shortness of breath, high temperature, Loss of appetite, and persistent pain or pressure in the chest. Also, there are other symptoms but less common like loss of taste or smell, headache, chills, dizziness, muscle or joint pain, and more. Everyone can be diagnosed with COVID-19 but people aged 60 years and over with underlying medical problems are the most vulnerable for severe illness from COVID-19 who are more likely to become seriously ill or die (World Health Organization [WHO], 2020). Morbidity among children infected by COVID-19 is largely asymptomatic and does not reflect the degree of exposure of children to the virus (National Center for Disease, 2021). Li et al. (2020) found that COVID-19 does not only affect the body but also the mind. COVID-19 generates negative emotion. They found that the same group before and after the discovery of COVID-19 showed an increase in depression, anxiety, indignation, and sensitivity to social risks with decreasing life satisfaction. The Covid 19 experiences negative impact on mental health outcomes (Stress, Anxiety, and Depression) and Functional Impairment. Researchers found that those who believe in the existence of COVID-19, have been diagnosed with COVID-19, knowing someone who was diagnosed or died from COVID-19, shows a poorer mental health outcome. They are predicted to have symptoms of depressive and anxiety disorders, as well as a higher level of stress and functional impairment (Gallagher et al., 2020). The Central Bureau of Statistics Israel (2020) published that parent's reporting of their children‟s emotional state, which worsened due to the corona, rose to 25.8% (Arzi and Sabag, 2020). 2 According to Dali (2021), during a COVID-19 period, there is an increase in mental distress, an increase in cases of self-harm attempts 1.5 increase compared to 2019. Dali emphasized the findings of the Israeli Ministry of Health in the Mental Health for Children and Adolescents, which according to the Arryan Association, an organization that provides psychological first aid over the phone, reported a 30% increase in adolescent inquiries compared to the year 2019. Internalizations based on difficulties in interpersonal relationships (28%), symptoms of anxiety and crisis following the COVID-19 (20%) and severe mental distress (20%). 1.1 COVID-19 and Mental health Depression may appear as a depressed mood or more complex way associated with other symptoms. It has different severity; mild, moderate, or severe (Wegner et al., 2020). It is characterized by three hierarchically structured ways: Depressed mood includes sadness, unhappiness, irritability, and a lack of interest or pleasure in previously rewarding or enjoyable activities. Depressive syndromes include disturbance in sleep and appetite, psychomotor agitation or retardation, cognitive symptoms, affective perturbations, tiredness and poor concentration (Palmer et al., 2019). Clinical diagnosis showed a major depressive disorder, in which five or more of the symptoms have been present during the same two-week period with at least loss of interest or depressed mood. The other symptoms include weight loss or gain, insomnia\hypersomnia, psychomotor agitation\retardation, fatigue or loss of energy, and more (Diagnostic and Statistical Manual of Mental Disorder 5 [DSM-5], 2013). The clinical diagnosis included depressed mood and depressive syndromes. According to Ministry of Health of Israel, depression is a combination of several risk factors such as heredity, early traumas (abuse, neglect or abandonment), separation and loss, post-traumatic stress disorder, previous mental disorder, deterioration in physical condition, chronic pain following injury, accident or illness, old age or widowhood, and adaptive response to change in status or place of residence. Also, it could be a result of interpersonal violence trauma (Vibhakar et al., 2019), and obesity, especially among female (Sutaria et al., 2019). During the COVID-19 pandemic, children had to separate from their parents, especially the health workers, in order to reduce the spread of the virus; it was sudden and mysterious separation. Also, there were children who separated from their grandparents who usually take care of them, specifically because the 3 COVID-19 poses a danger to them. some of those lost their caregivers cause of the pandemic. It wasn‟t the only early trauma, there were children who even lost their peers and friends. The Sudden loss that was caused by the pandemic leaded to deterioration in mental health. Moreover, there are children who suffered from health disease caused by the infection of the virus, some of them have a chronic pain following illness. According to the Clalit Health Service in Israel (2021), more than a quarter of a million children and adolescents up to the age of 18 (Arabs and Jews) were diagnosed with COVID-19, they are considered about a third of all COVID-19 nationals in the country. The percentage of Arab children out of the total number of children diagnosed with COVID-19 is 27.5% (The Israeli Ministry of Health, March 2021). Approximately, 163 were in a severe / moderate condition (mainly due to background illnesses), and 7 of them died. The Israeli Ministry of education (May 2021) published that online learning is correlated negatively with a school achievement. Also there is a negative correlation between the duration of learning from home and motivation for learning and level of involvement. It leads to lack of self-satisfaction with academics, which could be a risk factor fordepression (Grover et al., 2019) . Liu et al. (2021) found that age played an important role in children and adolescents‟ depression, primary school students are more vulnerable and prone to suffer from depression (Xie et al., 2020). This can be explained by the fact that children are more engaged in indoor activities with reduced social interactions (Liu et al., 2021). Schafer et al. (2022) examined the prevalence rates of depressive symptoms between the pre-and peri COVID-19 eras. They found that pre-COVID-19 era rate of depressive symptoms is 8.7%, which ranges from 6.2% to 11.5%. However, the peri-COVID-19 era rate of depressive symptoms was 18.3%, which ranges from 13.5% to 24.3%. Consequently, COVID-19 has a negative effect on mental health due to the fact that people showed more symptoms of depression. Not only depression can be the result of COVID-19 but also anxiety. Tang et al. (2021) found that COVID-19 is associated with anxiety and depression among quarantined respondents; they showed higher anxious and depressive symptom than those not quarantined. 4 Anxiety is an anticipation of future threat (DSM-5, 2013), an emotion characterized by feelings of tension, recurring intrusive worried thoughts, and physical changes (American Psychological Association [APA], 2019). It is associated with muscle tension and vigilance in preparation for future danger and caution or avoidant behavior (DSM-5, 2013) . Anxiety is a reaction to stress in life that can be manifested by severe worries and accompanied by physical reaction. Anxiety has three dimensions: cognitive, identifying cues and interpreting them negatively; behavioral, avoidance of the cause of anxiety; and physiological, stimulation of the sympathetic system (Rothberg et al., 2008). There are different types of anxieties among children; for example, children with Generalized Anxiety Disorder [GAD] get worried about a variety of things. They feel that the worst possible thing could happen, they worry about relationships with their peers, family problems, family member health, their own health, money, or performance in school. However; children with panic disorder fear small things accompanied by strong physical reactions without having reasonable reasons. Due to covid-19, children show worries and fears about relationships with their peers as a result of the social distance; about their performance in school that is affected negatively by the quarantine and online learning; about family problems such as a economy and health which are negatively affected by the pandemic. These worries are similar to the GAD symptoms. Children with Separation Anxiety Disorder get worried about the person they love might abandon them and their parent's safety. They refuse to sleep away from home or to go to school. The quarantine cause of covid-19 gave a legitimacy to the refusale's behaviors. Children with Social Anxiety Disorder fear social and performance situations; they fear meeting or talking to people and in some cases, they find themselves unable to talk. Also, children who suffer from specific phobia fear certain things or situations such as animals, heights, water, darkness and more for at least six months or longer with physical distress (Brennan, 2020; Shaw, 2020). Schafer et al. (2022) examined the prevalence rates of anxiety symptoms between the pre-and peri COVID-19 eras. They found that pre-COVID-19 era rate of anxiety symptoms is 8.9%, which ranges from 5.5% to 14.4%. and peri-COVID-19 era rate of anxiety symptoms is 22.6%, which range from 18.3% to 27.3%. It shows that COVID- 19 has a negative effect on mental health and that people showed more anxiety symptoms. 5 COVID-19 will probably be the first major global health threat that children have been exposed to. The perspective that the world is not safe, COVID-19 may disrupt children's way of thinking especially with strict measures enforced. In addition to the uncertainty about the virus, the multitude of messages about the omnipresent threat, serious symptoms appear and symptoms similar to another disease appear with the difficulty to distinguish between them. (Haig-Ferguson et al., 2021). It is more difficult for children to understand abstract information. Their cognitive ability to process and understand complex information is limited. (Inhelder & Piaget, 1958). The shutdown of schools, quarantine at home, cancelation of sporting events, and distance learning - all increase the risk of anxiety for adolescents (Qi et al., 2020). Moghanibashi-Mansourieh (2020) found that the risk of suffering from anxiety increased for people who have at least one family member, relative, or friend with COVID-19 disease. Liu et al. (2021) found that suicidal ideation, quarreling with parents, insomnia, inattention during online learning and being physically distant from their teachers, anxious and depressed mood were positively associated with depression and anxiety. (Liu et al., 2021, p.5). Qi et al. (2020) found that enough sleep, moderate physical exercise, and regular study duration (participating in distance learning) and participating in daily life activities are associated with decreased risks of anxiety for adolescents during COVID-19. Matos et al. (2022) researched the impact of the perceived threat of COVID-19 on anxiety, depression, stress, and social safeness, across 21 countries from Europe, North America, Middle East, South America, Oceania and Asia. They found that perceived threat of COVID-19 is correlated with higher scores in depression, anxiety, and stress and associated with lower scores in social safety. Moreover, they found that "self- compassion moderates the relationship between perceived threat of COVID-19 on depression, anxiety, and stress, whereas compassion from others moderates the effects of fears of contracting COVID-19 on social safety" (Matos et al., 2022, p.1). Panchal et al. (2021) conducted a systematic review about the impact of COVID-19 lockdown on child and adolescent mental health. They found that children show a higher score of depression and anxiety symptoms during the lockdown compared to 6 rates observed before the lockdown. They also found that COVID-19 lockdown is associated with psychological distress, loneliness, anger, fear, irritability, stress, and boredom. Children and adolescents reported more anxious and depressive symptoms with high levels of fear and concern regarding the impact of COVID-19 on their lives than pre- COVID-19 pandemic rates. It is worth mentioning that older adolescent age, neurodiversity, female gender, and the presence of chronic physical conditions are associated with worse COVID-19 mental health outcomes (Samji et al., 2021). 1.2 COVID-19, Bullying and Cyberbullying Bullying is defined as “unwanted, aggressive behavior among school-aged children that involves a real or perceived power imbalance. The behavior is being repeated or having the potential to be repeated over time. Both kids who are bullied and who bully others may have serious and lasting problems" (Stop Bullying An official website of the United States government, May 30, 2019). Bullying can be direct, by openly and physically attacking a victim (Olweus, 1994); or indirect, by causing social isolation and intentional exclusion from a group (Olweus, 1994); Individually or collectively; face to face or online; verbal or written or video or picture or physical- any behavior that can damage the relationship and reputation of the target youth. Also bullying can be carried out by property damage of the target, theft, alteration. (Gladden et al., 2014). Bullying can be between children and adolescents at school, colleagues at workplace, and siblings at home, who act as bullies, victims, and witnesses. Cyberbullying is commonly defined as “an aggressive intentional act carried out by a group or individual, using electronic forms of contact, repeatedly and over time against a victim who cannot easily defend him or her-self” (Smith et al., 2008, p.376). Cyberbullying has increased due to the development of electronic devices such as computers, cell phones, tablets, and iPad and the widespread use of social media (Facebook, Instagram, Snapchat, and Tik Tok) and technology (Peker, 2020). Cyberbullying can be permanent, persistent, and hard to notice, easy to access, rapid social dissemination, and anonymous, compared with traditional bullying, which make it more complex (Extremera, et al., 2018). 7 According to Vaillancourt, et al. (2021), who studied the school bullying before and during COVID‐19, found that students reported far less rates of bullying involvement during the pandemic than before the pandemic across all forms of bullying (traditional, physical, social, verbal), except for cyberbullying. Also, they found that boys reported less than girls for being bullied, but more than girls by bullying others. They also found that secondary school students reported less than elementary school students on bullying involvement. 1.3 Mental health, Bullying and Cyberbullying Bullying is stipulated as (criterion A1) in the Diagnostic and Statistical Manual and Mental Disorders [DSM]. This manual is used by psychologists as a main reference for diagnosis (Samara et al., 2017). Bullying is a repetitive and persistent aggressive behavior against people and animals which breach the basic rights of other or major age-appropriate societal norms or rules, including traditional bullying and cyberbullying (DSM, 2013). Several mental health symptoms are noticed among children who suffer from bullying such as depression, anxiety and stress. According to Copeland et al. (2013), victims of bullying show higher levels of depressive disorders, anxiety disorders, generalized anxiety, panic disorder, and agoraphobia, and suicidality. Also, they found that both bullies and victims of bullying had higher levels of anxiety and depressive disorders. The results are valid for a community sample from eleven counties in North Carolina, among adolescents. In this study I will investigate the effect of bullying on Palestinian children who live in Israel. According to Palmer et al. (2019), bullying during childhood can predict negative mental health outcomes through adolescence. Several mental health outcomes were diagnosed among children who were exposed to bullying such as depression, anxiety and stress (Arseneault et al., 2010). Jadambaa et al. (2020) conducted a systematic review, meta-analysis and relative risk estimates for bullying victimization and health outcomes. According to 22 longitudinal studies that they investigated, it was found that there is an association between bullying victimization in childhood and later development of anxiety and depressive disorders. The results showed that "bullied children are at a significantly increased risk of later developing anxiety and depressive 8 disorders compared with children who were not involved in bullying" (Jadambaa et al., 2019, P. 5) . Also, Karmilasari, Winarni, and Windarwati (2020) who has done a systematic review of 26 articles from different countries to identify the impacts of bullying on the mental health of adolescents. Those articles have been published between 2015-2019 on five databases as Science Direct, Springer Link, PubMed, Clinical Key, and ProQuest. Bullying has negative effects on psychosocial and social health and leads to physical problems. They found that bullied victim could suffer from depression, anxiety, stress, discomfort feeling, suicide ideation, low self-esteem, self-isolation, lack of confidence, social isolation, loneliness, drugs misuse, low school attendance, low academic achievement (Karmilasari et al., 2020). Moreover, they could suffer from low subjective wellbeing, and high emotional and behavioral problems (Arslan et al., 2020) . As stated by Chu et al. (2019) mental health outcomes can be predictors for both traditional bullying and cyberbullying. Depression and general anxiety are common among traditional bullying and cyberbullying victims. For traditional bullying victimization, stress is a specific predictor. whereas, self-esteem, social anxiety and loneliness were specific predictors for cyberbullying victimization (Chu et al., 2019). 1.4 COVID-19, mental health, bullying and cyberbullying The sudden withdrawal from school, social and daily activities due to COVID-19 pandemic has put a huge burden on children; separation from their parents or caregivers, loss of a family member, unemployment and financial bankruptcy of parents (de Figueiredo et al., 2021), and domestic violence. The number of police cases opened for violent crimes between spouses increased about 13% during COVID-19 period (Avgar, 2020). These sudden changes increase the risk of developing psychiatric disorders among children in the future- unconditional mental health disorders histories (de Figueiredo et al., 2021). On another hand the lockdown has a positive effect on children especially who suffer from traditional bullying at school, or who suffer from drug abuse; such children had the opportunity to stay clean and under parental supervision. Also, as a result of the lockdown, the children have to fulfil their time by being creative and learning „new‟ skills, hobbies, playing indoor games, music, sport, reading or spending quality time 9 with elders (Chawla et al., 2021). However, during quarantine children started learning from home using online applications thus they avoided having direct contact with children who may bully them, and that will make them feel better. Also, the quarantine makes people spend more time on social media. Cyberbullying as a result increases and bullying victims will suffer more. However, there is a need to mention that children at home can have protection from their parents, siblings, or a caregiver, as a result, the risk of having cyber bullying would be decreased. Bullying has a negative effect on mental health, especially its effect on depression and anxiety. Also, COVID-19 has a negative effect on mental health such as depression and anxiety. However, how both COVID-19 and bullying together affect mental health. In view of the fact that COVID-19 forced schools to be online, which means that there wasn't face to face meeting for children in school. This situation created a social distance especially for those in primary schools who were less equipped with communication instruments. The same social distance - especially between the victim and the bully- will probably help the victim to experience a less bullying environment which will affect their mental health positively. Basically, it is valid for those who are bullied within the school setting (traditional bullying) and it is not known if it is valid for those who are bullied online. However, children who are bullied online are at home most of the time so they are among their parents and family . 1.5 Mental Health and Social Support Social support correlates negatively to depression and anxiety symptoms (Osborn et al., 2019). Borowsky et al., (2013) found that the relationship between involvement in bullying and suicidal ideation or attempts mitigated by parent connectedness and perceived caring by friends and other adults. Social support is any help that is received by family members, close friends, neighbors, caregivers, support group and association. School support and parent support are a part of social support. Social support helps to face biological, psychological and social stressors (APA, 2019). "Perceived social support provides particularly strong regulation of negative emotions in social contexts" (Palmer etal., 2019, P.726). Social support is about having a close relationship with others, talking with them, being cared for, or feeling loved . 10 Hsiu-Chi et al. (2013) mentioned five general categories of social support: informational support including knowledge or facts, like advice or feedback on actions; emotional support including caring, concern, empathy, and sympathy; esteem support including helps to raise skills, abilities, and intrinsic value; social network including helps to enhance one's sense of belonging to a specific group with similar interests or situations; tangible support including providing physically needed goods and services to recipients. 1.6 Bullying and Social Support Being a victim of bullying is affected by the experiences with primary caregivers; children who grow up with a negative parenting become powerless, less able to assert their needs and less-confident. However, children who are exposed to positive parenting become more resilient and adaptive with a strong self-esteem (Lereya et al., 2013). According to previous research, if the child has a supportive caregiver or teacher, the risk of experiencing bullying will decrease (Espelage & Sung Hung, 2019). Higher parental support and the more time spent with parents reduce the involvement in bullying (Wang et al., 2009; Mann et al., 2015). "children with low peer acceptance and children actively rejected by peers were buffered from the risk of peer victimization when they enjoyed a supportive relationship with their teacher" (Elledge et al., 2015, P.699). Smigelskas et al. (2018) conducted a study that focused on social support and bullying among children aged 11-15 from nine countries; Armenia, Estonia, Israel, Latvia, Lithuania, Moldova, Poland, Russia, and Ukraine. They found that social support, such as parental support, teacher support, and peer support, act as a very strong and comprehensive protective factor. Family support serves as the most potentially protective shield against fighting and bullying, especially when they have a close relation with the parents in the family. Also, teacher support plays a significant role in the phenomenon of bullying but it is important to note that teachers with authoritative methods of enforcing discipline, authoritarian and inflexible methods make a distance between those students and their teachers which reduces trust between them and that exacerbates the phenomenon. In addition, peer support is considered as a protective factor; the risk of the child being a victim of bullying decreases if he/she has friends and 11 enjoys supportive relationships while promoting social skills and supportive attitudes. However, if those friends show dangerous behavior, such as using a substance, smoking, or getting drunk, the possibility of taking part in bullying increases. 1.7 COVID-19, Mental Health, Bullying and Social Support Bullying dramatically affects mental health and increases depression, anxiety, and stress. However, social support has a positive effect on mental health. In this research, I will investigate this correlation among Arab Palestinian children lives in Israel who have been bullied. Tang et al. (2021) found that parent-child discussion about COVID-19 was a protective factor for mental health; the children experienced less depression, anxiety, and stress, which are negatively correlated with psychopathological symptoms. Also, parent-child discussion about COVID-19 is positively correlated with life satisfaction. Szkody et al. (2021) study the stress‐buffering role of social support during COVID‐19. They found that the worst psychological health was reported by individuals who were worried about COVID-19. Worrying is one of the symptoms of anxiety disorders. It is associated with depressive symptoms. It makes individuals have a negative world view as a result of reducing mental resources. They came to the conclusion that having social support is correlated to reporting a higher score in psychological health. Magson et al. (2021) found that the social connection is affected by the COVID-19 and has an effect on mental health. Adolescents show anxiety as a result of not meeting their friends, and adults show anxiety as a result of family members who were infected by COVID-19. Their longitudinal investigation into the effect of COVID-19 virus showed that social disconnection is associated with higher levels of anxiety and depressive symptoms and lower levels of life satisfaction. Adolescents who have a conflict with their parents and who are left alone at home all day showed higher scored reports (Magson et al., 2021). Depression and anxiety increased as a result of loneliness and social isolation (Loades et al., 2020) . 1.8 Arab Palestinian children who live in Israel There are 1.956 million Palestinian Arabs who live in Israel, they are (21.1%) of all Israeli citizens; Arabs (Muslim, Christian, and Druze), Jews, and other (Israeli central 12 bureau of statistics, December 2020), and are 27.7% of all Palestinian people. According to Israel central bureau of statistics (2022), the Jews status on the most measures is better than that of the Arabs in Israel; they are better status on quality of employment, security, health, housing and infrastructure, education, civic engagement and governance, personal and social well-being, material standard of living, leisure, culture and community, and at information technologies. The identity of Palestinian Arabs who live in Israel is a complex of two conflicted components: the native component, they are a citizen of Israel. And the national component, they are a Palestinian people. The conflict between the native and national components are reflected on four main circles which the identity of them is formed and influenced by it: the local circle, which indicate the changes on the internal structures of the Arab population, the values and the life patterns. The national circle, the status of the Arabs in a Jewish country, their relations with the Jews, and the formal policy that taken towards them. The regional circle, the Arabs and Palestinian's cultural and national. The religious circle, the influence of the ethnic identity of the Muslim Arabs, Christians, and Druze. The conflict leads to a paradoxical situation of "double periphery". On one hand the Palestinian who live in Israel improve their status and promote their rights equality within Israeli society. On the other hand, they strengthen their ties with their people, Palestinian people and the Arab ones, they support an independent Palestinian country. In both situations, they are in the margins, there are differences between them; politically, economically and socially (Al-Hajj, 2000). The Israeli psychological-counseling service in the Ministry of Education received inquiries from students and parents; there have been 13,261 inquiries about loneliness and sadness, 9,586 about distress and anxiety, 8,612 about difficulties in the family; 519 about suicide and 19,738 inquiries about children at risk (Arzi & Sabag, 2020). Bullying is a common phenomenon among Israeli children and adolescents; 69% reported a bullying experience over the year 2017 (Buniel-Nissim, Demri and Rolider, November 2018). Bullying exists both in the physical world (school) and in the virtual one (cyber). Buniel-Nissim et al. (2018) found that the rate of physical bullying at school is significantly higher among children; (83%) among third– fourth grade, (69%) among fifth– seventh grade and (62%) among eighth–ninth grade- regardless of gender. In addition, approximately 48% of children reported bullying in the virtual world- 13 regardless of age. However; there is a significant difference between boys and girls, where girls reported (52%) bullying in the virtual space while boys reported (40%). The research hypotheses: 1. Fear of COVID-19 will be related positively with mental health outcomes, bullying and cyberbullying. 2. Bullying and cyberbullying will be correlated positively with mental health outcomes . 3. Social support mediating the correlation between fear of COVID-19 and mental health outcomes among Arab Palestinian -Israeli child bullying victims. 4. Social Support will be negatively correlated with mental health problems, bullying and cyberbullying. 5. The current study hypothesizes that fear of covid as predicter variable; the mental health as outcome variable, social support, bullying and cyber bullying as mediating variables. This model will be tested among 141 Palestinian children using structural equation modeling (SEM). 14 Chapter Two Methodology 2.1 Participants Participants (N=141) are (9-13) years old; they all were Arab Palestinian-Israeli children who were victims of bullying- regardless of gender (63 male and 78 female). They are fourth grade children (N= 61), fifth grade (N= 33), and sixth grade (N= 47), from different elementary schools. They were recruited by school counselors in consultation with the class educators. The sample also included children who underwent a boycott, with special education, or had conflicts with peers, each of them having a high risk of being bullied. They have parental and school approval to participate in research . Exclusion criteria: participants who have psychological treatment or any treatment as a result of bullying were excluded. 2.2 Measures In this study, the measures that are used are translated into Arabic and reviewed by Arab experts in English language (see appendix 10). It was updated and conducted according to age and culture. The original measures, which are written in English, are valid and some of them used before in another research. Consent form: parents received a preliminary letter explaining the topic of the study and its purpose, procedures, and risks. They were informed they could withdraw from the study whenever they liked. The participants were aware that they can communicate with the experimenter for questions. This is a consent form with guidelines that must be signed by parents. (Appendix 1) The Demographic Form: It includes information about participants‟ gender (male, female), age, school, class, parents‟ marital status (married, divorced, separated), and whether they are going through or finished psychotherapy (and if it is related to bullying). (Appendix 2) Multidimensional Bullying Victimization Scale (MBVS) is a bullying victimization scale about adolescents. It includes three subscales of bullying: direct, indirect, and 15 evaluative. It indicates 24 items; 11 Direct Bullying item, which evaluate experiencing bullying in a personal, direct, and face to-face manner; 6 Indirect Bullying items, which assess experiences of bullying through other people or through other mediums; and 7 Evaluative bullying items, which evaluate experiences of bullying that are judgmental or negatively evaluating a person‟s traits or attributes (Harbin, 2016). The child needs to rate the items indicating how often each item is true, how often it happened to him/her, by ranging from 0 = “never” to 3 = “very often". (Appendix 3). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.915). An example of item is a “Post negative comments on my pictures, comments, or statuses (Facebook, Twitter, Instagram, Tiktok, Snapchat)”. Adolescents Cyber-Victimization Scale (CYBVICS) is a self-report adolescent Cyber- Victimization Scale which measures the adolescent‟s experience as a victim of cyberbullying in the past 12 months. The participants rate the items from 1 = “never” to 5 = “Many times (more than 10)". It includes 18 items of direct and indirect cyber- victimization. The direct indicates the experiences of being cyber-victimized that involve verbal direct attacks and social-type behaviors. However, the indirect handles the experiences of being victimized including the manipulation of images, false profile of the victim, hacking, identity theft (Buelga et al., 2019). (Appendix 4). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.896). An example of item is a “Someone insulted or ridiculed me in social networks or groups like WhatsApp to really hurt me”. The Strengths and Difficulties Questionnaire (SDQ) is a parent report questionnaire including a brief behavioral screening questionnaire of the child's behavior over the last six months or this school year. The participants rate each item as Not True, Somewhat True or Certainly True. It includes 25 items: 11 items about strengths, and 14 items about difficulties. These items divided to 5 scales: Emotional Symptoms (items: 3, 8, 13, 16, 24), Conduct Problems (items: 5, 7, 12, 18, 22), Hyperactivity (items: 2, 10, 15, 21, 25), Peer Problems (items: 6, 11, 14, 19, 23), and Prosocial Behavior (items: 1, 4, 9, 17, 20) (Goodman, 1997). (Appendix 5). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.771). An example of item is a “Often complains of headaches, stomach-aches or sickness”. 16 Fear of Covid19 Questionnaire measures the effect of COVID-19 on mental health outcomes is a self-report questionnaire designed to measure the effect of COVID-19 period on mental health outcomes; depression (items 11 to 17), anxiety (items 6 to 11), and stress (items 1 to 5). Each participant needs to indicate how much the statement applied to him/her over the past week, from 0 "never" – 3 "almost always". (Appendix 6). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.891). An example of item is a “I am afraid of losing my life to COVID-19” (Mahamid et al, 2021). The Revised Child Anxiety and Depression Scale (RCADS) is a youth self-report questionnaire. It is include 47 items which divided to 6 subscales: separation anxiety disorder (items: 5, 9, 17, 18, 33, 45, 46), social phobia (items: 4, 7, 8, 12, 20, 30, 32, 38, 43), generalized anxiety disorder (items: 1, 13, 22, 27, 35, 37), panic disorder (items: 3, 14, 24, 26, 28, 34, 36, 39, 41), obsessive compulsive disorder (items: 10, 16, 23, 31, 42, 44), and major depressive disorder (items: 2, 6, 11, 15, 19, 21, 25, 29, 40, 47). The participants need to answer how often each of these things happens to him/her, by rating from 0 "never" to 3 "always" (Mathyssek et al. 2013). (Appendix 7). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.958). An example of item is a “I feel worried when I think someone is angry with me”. Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet et al., 1988), There are 12 items that assessed social support; family support (items 3, 4, 8, and 11), friends support (items 6, 7, 9 and 12), and other significant support (items 1, 2, 5 and 10). It is a self-report which the participant needs to indicate how they feel about each item, from 1 (Very Strongly Disagree) – 7 (Very Strongly Agree), the “4” is Neutral. (Appendix 8). In this study, the Cronbach's alpha of indicated appropriate internal consistency (α=0.948). An example of item is a “I get the emotional help and support I need from my family”. Extra review questions about bullying which include 8 questions about exposed traditional bullying and cyberbullying, received support, and recognizing bullying victims. It is a yes/no question. (Appendix 9) 17 2.3 Procedure The researcher applied to a number of elementary schools, but succeeded in scheduling a meeting with the principals of three elementary schools and elementary education centers. The researcher met with each of the school's principals and explained to them the purpose of the research, the methodology, and the importance of being a part of this research. Then, she asks for permission to contact the school counselors, the children and their parents. After the school principals agreed, the researcher met the counselors of each school and explained to them the purpose of the research and the methodology. The researcher asked them to provide the bullying victims' parents with forms which include Information about the study; Consent form, Demographic Form, and a Strengths and Difficulties Questionnaire (SDQ). These electronic forms were sent as a link to parents via the WhatsApp application by the educator of 4th, 5th, and 6th classes. It is important to mention that the same forms were distributed again as paper forms for parents who did not complete the electronic google forms. In addition, the researcher asked educators to send them to the children's parents who underwent a boycott, or have special education, or have conflicts with peers. Also, the researcher used her personal account on Facebook to reach children from other cities and villages who participate in the study. She also sent to various teachers who teach in different elementary schools through WhatsApp to help her to reach more children by passing on the research forms to their students. It's important to note that the researcher emphasizes that the participants in the research must be a bullying victim. After she had a parent's agreement, the researcher gave each child a user number in order to match his answers to the data that she received from the parents without writing a personal name. She asked the children to answer the Multidimensional Bullying Victimization Scale (MBVS), Adolescents Cyber-Victimization Scale (CYBVICS), Questionnaire measures the effect of COVID-19 on mental health outcomes, and The Revised Child Anxiety and Depression Scale (RCADS). Then to fill out the multidimensional scale of perceived social support (MSPSS) and to answer some 18 review questions about bullying. Based on the pilot study children understand the questions and the timing is accurate. The children continuously answered all the questionnaires together within 30-45 minutes through electronic forms, some of them are filled in at home and some at school. Special adjustments were made to accommodate children who could not complete the questionnaire under standard conditions- especially those who were COVID-19 patients or were isolated or had reading problems. The researcher analyzed statistically the data after excluding children who have done psychotherapy, parents who filled out the same form several times, and others who partially filled their forms. She collected 200 parental consent and data from 170 children, but she analyzed 141 of them. Data for this study was collected at the end of the second wave for the COVID-19 period and before the start of the third wave; during the period that adults were receiving vaccines and children were not- that was one week after the students returned to school. The experiment was stopped due to the war which broke out between Israel and Gaza. Children who participated in the research were mentally affected by the war thus the received data would not necessarily be reliable so the researcher preferred not to run the study. Also, after the end of the war the researcher decided not to run the study again due to the dramatic decrease in COVID-19 cases, knowing that this research investigates the effect of the COVID-19 on mental health. The research was conducted following guidelines outlined by the An-Najah IRB committee and the Declaration of Helsinki (1964). 2.4 Statistical Plan The correlational design will be used to examine the effect of COVID-19 on mental health outcomes among children who are victims of bullying. However, social support will be used as a mediating variable. 19 The study data were analyzed using the IBM SPSS Statistics 20 software. The analysis included range, minimum, maximum, mean, standard deviations (SD), and variance statistic measures. The analysis of the conclusion was based on Multiple analysis of variance (MANOVA), which determines the effects of independent categorical variables on multiple continuous dependent variables, with reference to demographic participants‟ factors; gender (male, female), age, grade, and parents‟ marital status (married, divorced, widow). In addition to performing a Pearson correlation coefficient to measure linear correlation between the variables. To analyze the conceptual model, structural equation modeling (SEM) was performed using IBM SPSS, where fear of covid-19 as a predictor variable; the mental health as outcome variable, social support, bullying and cyber bullying as mediating variables. 20 Chapter Three Results and discussion In this section, the results of the research will present. Table 1 includes descriptive statistics about the traditional bullying, cyberbullying, depression, anxiety, social support, family support, friend support, significant other support, parent's child difficulties report, and fear of COVID-19 on mental health. Results indicate that participants report low scores on traditional bullying, cyber bullying, depression, anxiety, and fear of COVID-19 on mental health. On the other hand, participants report a high score on social support, family support, friend support, and significant other support. Also, the parents of participants report a low score on the child difficulties questionnaire. Table 1 Descriptive statistics for research variables (N= 141) Variable Mean S.D Min Max Range Variance Bullying Cyber- Bullying .2417 .33612 .00 2.13 2.13 .113 1.170 6 .34475 1.00 3.44 2.44 .119 fear of COVID-19 .5420 .57746 .00 2.79 2.79 .333 Depression .5440 .54055 .00 3.00 3.00 .292 Anxiety .8582 .72565 .00 3.00 3.00 .527 Social Support (total) 5.206 3 1.74041 1.00 7.00 6.00 3.029 Family Support 5.648 9 1.80153 1.00 7.00 6.00 3.246 Friend Support 4.656 0 1.94053 1.00 7.00 6.00 3.766 Significant Other Support 5.313 8 1.96587 1.00 7.00 6.00 3.865 Parent Report .6618 .23409 .32 1.52 1.20 .055 21 Results of the study showed significant differences in gender on traditional bullying, anxiety, social support and fear of COVID-19. Boys reported higher scores than girls regarding bullying. However, boys reported less scoring than girls on anxiety, fear of COVID-19, social support, family support, friend support, and significant other support. It is worth mentioning that both boys and girls have fairly equal reporting of cyber bullying, depression, and parent's child difficulties. (See table 2). Table 2 Means of variables by gender Gender Bullying Cyber-Bullying fear of COVID-19 Depression Anxiety Social Support Family Support Friend Support Significant Other Support Parent Report boys Mean .3036 1.2134 .4002 .5222 .7249 4.9444 5.3651 4.4167 5.0516 .6844 N 63 63 63 63 63 63 63 63 63 63 SD .39870 .40002 .50533 .49788 .68140 2.05290 2.15331 2.13789 2.25141 .20724 girls Mean .1918 1.1360 .6566 .5615 .9658 5.4177 5.8782 4.8494 5.5256 .6436 N 78 78 78 78 78 78 78 78 78 78 SD .26788 .29077 .60904 .57530 .74650 1.41864 1.43118 1.75548 1.68627 .25357 Total Mean .2417 1.1706 .5420 .5440 .8582 5.2063 5.6489 4.6560 5.3138 .6618 N 141 141 141 141 141 141 141 141 141 141 SD .33612 .34475 .57746 .54055 .72565 1.74041 1.80153 1.94053 1.96587 .23409 22 Results of the study showed significant differences in child‟s grade on anxiety, depression and fear of COVID-19. Children in the 5th class reported higher scores than the children at 4th geade and 6th grade on anxiety, depression and fear of COVID-19. Children at 4th grade reported a higher score than children at 6th grade on anxiety, but they didn't show a significant difference on depression and fear of COVID-19 on mental health. It is worth mentioning that children at 4th grade and 5th grade have fairly equal reporting of traditional bullying, cyberbullying, social support, family support, friend support, and significant other support, and parent's child difficulties report (see table 3). 23 Table 3 Means of variables by Class Class Bullying Cyber- Bullying fear of COVID-19 Depression Anxiety Social Support Family Support Friend Support Significant Other Support Parent Report 4.00 Mean .2158 1.1284 .5070 .5049 .8306 5.0861 5.5164 4.5902 5.1516 .6984 N 61 61 61 61 61 61 61 61 61 61 Std. Deviation .29082 .36325 .59214 .57949 .79553 1.85717 1.91804 1.98223 2.08030 .23873 5.00 Mean .2652 1.2104 .6580 .6121 1.0455 5.5682 6.1288 4.7348 5.8409 .6461 N 33 33 33 33 33 33 33 33 33 33 Std. Deviation .34230 .37827 .52785 .49671 .70498 1.32426 1.21694 1.75884 1.62718 .17780 6.00 Mean .2589 1.1974 .5061 .5468 .7624 5.1082 5.4840 4.6862 5.1543 .6255 N 47 47 47 47 47 47 47 47 47 47 Std. Deviation .38786 .29301 .59255 .52372 .62915 1.83769 1.95771 2.04266 2.00377 .25915 Total Mean .2417 1.1706 .5420 .5440 .8582 5.2063 5.6489 4.6560 5.3138 .6618 N 141 141 141 141 141 141 141 141 141 141 Std. Deviation .33612 .34475 .57746 .54055 .72565 1.74041 1.80153 1.94053 1.96587 .23409 24 Results of the study showed significant differences in age regarding anxiety. Children at age 10-11 report anxiety more than the children at age 9-10, and both have a higher anxiety reporting than the children aged 11-13. On the other hand, children at each age have fairly equal reporting of traditional bullying, cyberbullying, depression, fear of COVID-19, social support, family support, friend support, and significant other support, and parent's child difficulties report (see table 4). Table 4 Means of variables by Age Age Bullying Cyber- Bullying fear of COVID-19 Depression Anxiety Social Support Family Support Friend Support Significant Other Support Parent Report 9-10 Mean .2329 1.1674 .5587 .5479 .8904 5.0537 5.5582 4.4863 5.1164 .6860 N 73 73 73 73 73 73 73 73 73 73 Std. Deviat ion .31586 .40809 .59050 .57521 .80470 1.81761 1.83453 1.97462 2.09127 .22761 10-11 Mean .2970 1.1487 .5415 .5871 .9624 5.6210 5.9919 4.8871 5.9839 .6813 N 31 31 31 31 31 31 31 31 31 31 Std. Deviat ion .43750 .21773 .63802 .53836 .72993 1.47523 1.68261 1.83353 1.51923 .22850 11-13 Mean .2128 1.1952 .5097 .5000 .7072 5.1599 5.5405 4.7973 5.1419 .5978 N 37 37 37 37 37 37 37 37 37 37 Std. Deviat ion .27687 .29763 .50848 .47900 .52323 1.77793 1.84420 1.97979 1.96545 .24548 Total Mean .2417 1.1706 .5420 .5440 .8582 5.2063 5.6489 4.6560 5.3138 .6618 N 141 141 141 141 141 141 141 141 141 141 Std. Deviat ion .33612 .34475 .57746 .54055 .72565 1.74041 1.80153 1.94053 1.96587 .23409 25 Results of the study showed significant differences in parents' marital status on traditional bullying, cyberbullying, depression, anxiety, social support, family support, friend support, significant other support, parent's child difficulties report, and fear of COVID-19. Children with widowed parents had higher scores than those whose parents are divorced on traditional bullying, cyberbullying, and parent's child difficulties report, and both have a higher score than the child whose parents married. Children whose parents are divorced had higher scores than those with widowed parents on depression and anxiety, and both have higher scores than the children whose parents married. Children with widowed parents had higher scores than those whose parents are married on social support, family support, friend support, significant other support, and fear COVID-19, and both have higher scores than children whose parents divorced. (See table 5). 26 Table 5 Means of variables by Parents Marital Status Parents Marital Status Bullying Cyber- Bullying Fear Of Corona Depression Anxiety Social Support Family Support Friend Support Significant Other Support Parent Report married Mean .2178 1.1389 .5446 .5070 .8242 5.1960 5.6777 4.6152 5.2949 .6459 N 128 128 128 128 128 128 128 128 128 128 Std. Deviation .30024 .26794 .58264 .51485 .70503 1.72818 1.77863 1.92167 1.96335 .22511 divorced Mean .4417 1.3500 .3714 .9200 1.2333 4.9333 5.0500 4.5500 5.2000 .8040 N 10 10 10 10 10 10 10 10 10 10 Std. Deviation .48837 .45289 .37008 .76129 .85418 2.05285 2.25709 2.22923 2.25093 .28687 widowed Mean .5972 1.9259 1.0000 .8667 1.0556 6.5556 6.4167 6.7500 6.5000 .8667 N 3 3 3 3 3 3 3 3 3 3 Std. Deviation .82741 1.32559 .84213 .25166 1.08440 .55486 .80364 .00000 .86603 .26026 Total Mean .2417 1.1706 .5420 .5440 .8582 5.2063 5.6489 4.6560 5.3138 .6618 N 141 141 141 141 141 141 141 141 141 141 Std. Deviation .33612 .34475 .57746 .54055 .72565 1.74041 1.80153 1.94053 1.96587 .23409 A Pearson product-moment correlation coefficient was computed to assess the relationship between variables, traditional bullying positively correlated with cyber bullying (r=.619, p<.001), fear of COVID-19 (r=.269, p=.001), depression (r=.384, p<.001), anxiety (r=.360, p<.001), parent marital status (r=.320, p<.001). In addition, cyber bullying positively correlated to depression (r=.304, p<.001), anxiety (r=.217, p=.010), while negatively correlated to social support (r=-.179, p=.033), significant other support (r=-.244, p=.004). 27 Moreover, fear of COVID-19 positively correlated to depression (r=.345, p<.001), anxiety (r=.394, p<.001), Social support (r=.166, p=.049), family support (r=.176, p=.037), parent marital status (r=.218, p=.009). Also, depression positively correlated with anxiety (r=.698, p<.001), parent marital status (r=.382, p<.001). Furthermore, anxiety positively correlated with social support (r=.225, p=.007), family support (r=.194, p=.021), parent marital status (r=.274, p=.001). Also, social support is strongly and positively correlated to family support (r=.900, p<.001), friend support (r=.910, p<.001), and other significant support (r=.933, p<.001). Finally, family support is strongly and positively correlated to friend support (r=.708, p<.001), other significant support (r=.774, p<.001). Also, friend support is strongly and positively correlated to other significant support (r=.780, p<.001). (See table 6). Table 6 The correlation between the variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Bullying 1 .619 ** .269 ** .384 ** .360 ** -.156 -.136 -.144 -.147 .320 ** Cyber-Bullying 1 .156 .304 ** .217 ** -.179 * -.139 -.106 -.244 ** .129 fear of COVID-19 on mental health 1 .345 ** .394 ** .166 * .176 * .153 .129 .218 ** Depression 1 .698 ** .033 .065 -.015 .042 .382 ** Anxiety 1 .225 ** .194 * .141 .281 ** .274 ** Social Support 1 .900 ** .910 ** .933 ** .051 Family Support 1 .708 ** .774 ** .012 Friend Support 1 .780 ** .035 Significant Other Support 1 .090 Parent Report 1 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). 28 There was a statistically significant interaction effect between gender on the combined dependent variables, F(9,125)=2.252, p=.023; Wilks' Λ=.860. (See table 8). In order to examine whether there are significant differences in fear of COVID-19 regarding gender, a MANOVA analysis of variance was conducted. The analysis yielded a significant result, F(1)=6.996, P=.009 (See table 7). The analysis showed that Boys (M=0.40, SD=0.50) are less affected than girls (M=0.66, SD= 0.61) (See table 2). In addition, in order to examine whether there are significant differences in anxiety regarding gender, a MANOVA analysis of variance was conducted. The analysis yielded a significant result, F(1)=4.35, P=.039 (See table 7). The analysis showed that boys (M=0.72, SD=0.68) are less anxious than girls (M=0.96, SD= 0.75) (See table 2) . Also, in order to examine whether there are significant differences in social support regarding gender, a MANOVA analysis of variance was conducted. The analysis yielded a significant result, F(1)=3.936, P=.049 (See table 7). The analysis showed that boys (M=4.94, SD=2.05) are less supported than girls (M=5.41, SD=1.42).(See table 2). Moreover, in order to examine whether there are significant differences in cyberbullying due to parental marital status, a MANOVA analysis of variance was conducted. The analysis yielded a significant result, F(2)=10.87, P<0.001 (See table 7). Post hoc table shows that there is a significant difference in mean scores regarding Cyberbullying between married parent status and divorced parent status (p=.049), and between married parent status and widower parent status (p <.001), and between divorced parent status and widower parent status (p =.008) (See table 8). Children with widower parents (M=1.92, SD=1.32) had higher scores than those whose parents are divorced (M=1.35,SD=0.45) regarding cyber bullying, and both have higher scores than those whose parents married (M=1.14, SD=0.27).(See table 2) . In order to examine whether there are significant differences in traditional bullying due to parental marital status, a MANOVA analysis of variance was conducted. The analysis showed significant differences, F(2)=4.46, P=.013 (See table 7). Post hoc Table shows that there are significant differences in mean scores regarding bullying between married parent status and divorced parent status (p=.040), However, there is no significant differences between married parent status and widower parent status (p =n.s.), nor between divorced parent status and widower parent status (p =n.s.) (See table 8).Children with widower parents (M=0.60, SD=0.83) received higher scores than those 29 whose parents are divorced (M=0.44, SD=0.49) regarding bullying, and both have a higher score than those whose parents are married (M=0.22, SD=0.30) (See table 2). In order to examine whether there are differences in depression due to parental marital status, a MANOVA analysis of variance was conducted. The analysis showed significant differences, F(2)=4.14, P=.018 (See table 7). Post hoc table shows that there are significant differences regarding mean scores for depression between married parent status and divorced parent status (p=.019), however, there are no significant differences in scores between married parent status and widower parent status (p =n.s.), nor between divorced parent status and widower parent status (p =n.s.) (See table 8). Children whose parents are divorced (M=0.92 SD=0.76) had higher depression report scores than those with widower parents (M=0.87, SD=0.25). In both cases there were more than a child whose parents were married (M=0.50, SD=0.51) (See table 2) . Furthermore, in order to examine whether there are significant differences in scores regarding parent's difficulties due to parental marital status, a MANOVA analysis of variance was conducted. The analysis had a significant difference in scores, F(2)=3.23, P=.042 (See table 7) Post hoc table showed that there are significant differences in the mean scores for parent's difficulties report between married parent status and divorced parent status (p=.038), but not between married parent status and widower parent status (p=n.s.), nor between divorced parent status and widower parent status (p =n.s.) (See table 8). Children with widower parent (M=0.86, SD=0.26) received higher scores than those whose parents are divorced (M=0.80, SD=0.29) on parent's child difficulties report, and both have a higher score than the children whose parents are married (M=0.64, SD=0.22) (See table 2). 30 Table 7 Tests of Between-Subjects Effects Source Dependent Variable Type III Sum of Squares df Mean Square F Sig. Gender Bullying .331 1 .331 3.134 .079 Cyberbullying .164 1 .164 1.592 .209 Fear Of COVID-19 2.238 1 2.238 6.966 .009 Depression .089 1 .089 .314 .576 Anxiety 2.192 1 2.192 4.350 .039 Social Support 11.577 1 11.577 3.936 .049 Family Support 11.053 1 11.053 3.464 .065 Friend Support 10.732 1 10.732 2.902 .091 Significant Other Support 13.009 1 13.009 3.498 .064 Parent Report .037 1 .037 .703 .403 Age Bullying .414 2 .207 1.959 .145 Cyberbullying .294 2 .147 1.426 .244 Fear Of COVID-19 .046 2 .023 .071 .931 Depression .692 2 .346 1.219 .299 Anxiety .959 2 .480 .952 .389 Social Support 11.886 2 5.943 2.021 .137 Family Support 5.829 2 2.915 .914 .404 Friend Support 12.855 2 6.427 1.738 .180 Significant Other Support 20.564 2 10.282 2.765 .067 Parent Report .143 2 .072 1.362 .260 Class Bullying .400 2 .200 1.894 .155 Cyberbullying .649 2 .325 3.153 .046 Fear Of COVID-19 .544 2 .272 .847 .431 Depression .901 2 .451 1.588 .208 Anxiety 1.120 2 .560 1.112 .332 Social Support 7.058 2 3.529 1.200 .304 Family Support 8.301 2 4.151 1.301 .276 Friend Support 6.192 2 3.096 .837 .435 Significant Other Support 9.372 2 4.686 1.260 .287 Parent Report .038 2 .019 .359 .699 Parents Marital Status Bullying .943 2 .471 4.463 .013 Cyberbullying 2.238 2 1.119 10.871 .000 Fear Of COVID-19 1.086 2 .543 1.690 .188 Depression 2.349 2 1.175 4.140 .018 Anxiety 2.479 2 1.239 2.460 .089 Social Support 8.352 2 4.176 1.420 .245 Family Support 5.887 2 2.943 .923 .400 Friend Support 15.755 2 7.877 2.130 .123 Significant Other Support 7.416 2 3.708 .997 .372 Parent Report .341 2 .170 3.235 .042 Error Bullying 14.051 133 .106 Cyberbullying 13.691 133 .103 Fear Of COVID-19 42.723 133 .321 Depression 37.738 133 .284 Anxiety 67.004 133 .504 Social Support 391.181 133 2.941 Family Support 424.351 133 3.191 Friend Support 491.861 133 3.698 Significant Other Support 494.600 133 3.719 Parent Report 7.005 133 .053 Corrected total Bullying 15.817 140 Cyberbullying 16.640 140 Fear Of Covid-19 46.684 140 Depression 40.907 140 Anxiety 73.719 140 Social Support 424.064 140 Family Support 454.372 140 Friend Support 527.192 140 Significant Other Support 541.051 140 Parent Report 7.672 140 31 Table 8 Post Hock Table - Multiple Comparisons LSD Dependent Variable (I) ParentsMar italStatus (J) ParentsMari talStatus Mean Differenc e (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Bullying married Divorced -.2239 * .10812 .040 -.4377 -.0101 Widowed -.3794 .19234 .051 -.7598 .0009 divorced Married .2239 * .10812 .040 .0101 .4377 Widowed -.1556 .21677 .474 -.5842 .2731 widowed Married .3794 .19234 .051 -.0009 .7598 Divorced .1556 .21677 .474 -.2731 .5842 Cyber Bullying married Divorced -.2111 * .10635 .049 -.4214 -.0008 Widowed -.7870 * .18918 .000 - 1.1611 -.4130 divorced Married .2111 * .10635 .049 .0008 .4214 Widowed -.5759 * .21322 .008 -.9975 -.1543 widowed Married .7870 * .18918 .000 .4130 1.161 1 Divorced .5759 * .21322 .008 .1543 .9975 Depression married Divorced -.4130 * .17457 .019 -.7581 -.0678 Widowed -.3596 .31053 .249 -.9736 .2544 divorced Married .4130 * .17457 .019 .0678 .7581 Widowed .0533 .34998 .879 -.6387 .7453 widowed Married .3596 .31053 .249 -.2544 .9736 Divorced -.0533 .34998 .879 -.7453 .6387 Parent's Report married Divorced -.1581 * .07558 .038 -.3075 -.0086 Widowed -.2207 .13444 .103 -.4866 .0451 divorced Married .1581 * .07558 .038 .0086 .3075 Widowed -.0627 .15152 .680 -.3623 .2369 widowed Married .2207 .13444 .103 -.0451 .4866 Divorced .0627 .15152 .680 -.2369 .3623 Based on observed means. The error term is Mean Square (Error) = .053. *. The mean difference is significant at the .05 level. The Conceptualized model (Fig. 1) and structural equation modeling (Fig. 2) indicate fear of COVID-19 as a predictor; traditional bullying, cyberbullying, and social support as a mediating variable; depression and anxiety as an outcome variable. It shows that fear of COVID-19 correlated positively with traditional bullying, cyberbullying, depression, and anxiety. Also, social support correlated negatively with traditional bullying and cyberbullying. 32 Figure 1 Conceptualized model of fear of COVID-19 on depression and anxiety, and the mediating role of social support, bullying and cyberbullying Figure 2 Structural equation modeling of fear of COVID-19 on depression and anxiety, and the mediating role of social support, bullying and cyberbullying -.18 -.16 .17 Social support Fear of covid 19 bullying Cyberbullying depression anxiety .70 .22 .30 .36 .39 .35 .27 .16 33 Chapter Four Discussion This study was designed to examine the effect of COVID-19 on children's mental health, especially among Arab Palestinian victims of bullying and cyber bullying who live in Israeli, while social support was used as a mediating variable . The results showed that bullying and cyber bullying positively correlated to mental health outcomes, depression and anxiety. The results of this study are inconsistent with previous studies, where bullying during childhood is shown to predict negative mental health outcomes through adolescence (Palmer et al., 2019; Arseneault et al., 2010). "Bullied children are at a significantly increased risk of later developing anxiety and depressive disorders compared with children not involved in bullying" (Jadambaa et al., 2019, P. 5). This result can be explained by the fact that " Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm" (Gladden et al., 2014, p. 7). This causes harm or distress to their mental health. Especially that bullying is "unwanted, aggressive behavior among school aged children that involves a real or perceived power imbalance. Such behavior is repeated or has the potential to be repeated, over time "(Stop Bullying An official website of the United States government, May 30, 2019)." Also “Bully victim relationships will involve short- term negative conflicts in which participants use strategies such as aggression, giving in, or withdrawing to resolve the conflict" (Barton, 2006. p.3). As a result of unwanted repeated aggressive behavior, the bullying victim goes through with improper coping and inappropriate contact with others, where children can show depressive and anxious symptoms. The result shows that COVID-19 affects mental health, based on the results of a mental health questionnaire which includes the fear, anxiety and depression caused by COVID- 19. Also, it's positively correlated to mental health outcomes, which include anxiety and depression symptoms. This result can be supported by systematic review study which found that during COVID-19, a high score on depression, anxiety, post-traumatic stress disorder, stress, and psychological distress, were reported in China, United State of America, Turkey, Spain, Italy, denmark, Iran, and Nepal (Xiong et al., 2020). It's related to the fact that COVID-19 pandemic has put a huge burden on children as a result of sudden withdrawal from school, withdrawal from social life, withdrawal from 34 daily activities, separation from their parents or caregivers, loss of a family member, unemployment and financial bankruptcy of parents (de Figueiredo et al., 2021), and Domestic violence (Avgar, 2020). These sudden changes increase the risk of developing psychiatric disorders in children in the future and unconditional mental health disorders histories (de Figueiredo et al., 2021). Also, According to Arzi and Sabag (2020) children may experience emotional distress and anxiety due to experiencing the existential threat that they are exposed to as a result of being aware of the mortality reports, parental distress and the way their parents respond to the stressors. Fear, stress and anxiety are contagious and pass from parents to children (Kapetanovic et al., 2021). As shown by Aram's study (2021), parents who are in quarantine show less expressions of love to their children on quarantine days than normal routine days. It can be related to spending long time together with increased attention, which makes it a habit and reduces the parents' need for showing affectionate behaviors. It is worth mentioning that Covid-19 limited our activities and social interactions, children are more limited in indoor activities and the reduction of social interactions which make them more vulnerable and prone to suffer from depression (Liu et al.,2021; Xie et al., 2020). In addition, the study result shows that the negative effect of COVID-19 on mental health outcomes can be linked to the fact that COVID-19 is probably the first major global health threat that children have ever been exposed to. Thus, the perspective that the world is safe is refuted. Having such a limited cognitive ability to process and understand complex information (Inhelder & Piaget, 1958) makes children at risk of having an anxiet symptoms. In accordance with a pervious study showing that bullying victim could suffer from depression, anxiety, stress, discomfort feeling, suicide idea, low self-esteem, self- isolation, lack of confidence, social isolation, loneliness, drugs misuse, low school attendance, low academic achievement (Karmilasari el al., 2020). This study found that children's, who are victims of bullying report low scores at traditional bullying and cyber bullying. Also, they suffer less from mental health which is affected by COVID- 19, depression and anxiety, and their parents report a low score on the child difficulties questionnaire. These results can be explained due to the fact that the bullied victims of children will not meet with those who bullied them at school because of quarantine and social distance with their peers. Moreover, they are at home, having protection from their parents, siblings, or a caregiver, which will decrease the risk of cyber bullying. 35 Also, as a result to the lockdown, children have to fulfill their time by being creative and learned „new‟ skills, hobbies, playing indoor games, music, sport, reading or spending quality time with elders (Chawla et al., 2021). Consequently, that makes them more familiar with themselves, their strengths, releasing negative emotions, and finding new friends. It leads them to suffer from less anxious and depressive symptoms. But it is important to mention that the lockdown cause of COVID-19 affects the mental health negatively, where children show higher scores in depression and anxiety, psychological distress, loneliness, anger, fear, irritability, stress, and boredom (Panchal et al.,2021). This is inconsistent with a previous study of Tang and his collaborator who found that quarantined respondents show a higher anxious and depressive symptom than those who not quarantined. In addition, the results show that these children who report low scores at bullying, cyber bullying, and mental health outcomes, report high scores at social support, including family support, friend support and other support. this is a negative correlation between social support and cyber bullying, can be explained by that "perceived social support provides particularly strong regulation of negative emotions in social contexts" (Palmer et al., 2019, P. 726). With the quarantine of COVID-19, children spend more time with their family and they will have more parental supervision, the parent will be involved in what their children are going through, especially on the internet and Apps, the children will be more protected from cyber bullying. Also, being at home with parents, having a discussion about COVID-19 were protective factors of mental health, the children experienced less depression, anxiety, and stress, and that negatively correlated with psychopathological symptoms. Also, it was found that parent-child discussion about COVID-19 positively correlated with life satisfaction (Tang et al., 2021). The fact of parent-child discussion about COVID-19 (Tang et al., 2021) can be linked to other result which found that there are differences in fear of COVID-19 on mental health and anxiety as a function of gender, which showed that boys are less affected than girls. This finding can be explained by another result indicating that boys are less socially supported than girls. It's consistent with a previous study which shows that children and adolescents reported more anxious and depressive symptoms with high levels of fear and concern regarding the impact of COVID-19 on their lives than pre- COVID-19 pandemic rates. Moreover, older adolescent age, neurodiversity, female 36 gender, and the presence of chronic physical conditions are associated with worse COVID-19 mental health outcomes (Samji et al., 2021). There are significant differences in cyber bullying and traditional bullying. Due to parent marital status, a child with a widowed parent had higher scores than a child whose parents are divorced on cyber bullying and traditional bullying, also both have higher scores than children whose parents are married. Children with widower parents or divorced parents have a higher risk of growing up with negative parenting behavior or overprotective parenting or socially adverse environment. These parenting behaviors are significantly correlated with traditional and Cyber bullying victimization (Lereya et al., 2013). It is worthy mentioning that children whose parents have an unstable relationship, divorced, or have a single parent report a higher score of mental health problems than children whose parents have a stable relationship- or non-divorced (Hannighofer et al., 2017). This study supports the results which show that children with a widower parent or whose parents are divorced received higher scores on depression and parent's child difficulties than those whose parents married. Limitations Firstly, the participants were recruited by school counselors in consultation with the class educators. The sample included children who are bullying victims, cyberbullying victims, underwent a boycott, or with special education, or have conflicts with peers. There is no pre-test to figure out that the participants have been bullied. Secondly, the procedures obstructed due to the beginning of the war between Israel and Gaza which affects the mental health of the children that participate in the research and thus the data they receive are not necessarily reliable. Consequently, the researcher preferred not to run the study and to delete the data that have coincided with the war. Thirdly, the research data is based on translated scales, which aren't tested before in the context of Palestine. 37 Chapter Five Conclusion This study supports previous studies that have examined the correlation between the effect of bullying and COVID-19 on mental health. This study is a comprehensive and continuous investigation that shows the negative psychological effects of COVID-19 on the mental health outcomes among bullied and cyber bullied victims and the difficulties that they go through which are described by the parents while social support mediates this correlation. This study is a basis for extended work on victims of bullying. The Ministry of Education and schools must train teachers and provide guidance for parents about how to construct an emotional intervention plan for those children in order to support them emotionally and socially. The study is valid for development of interventions in the unique context of Palestine, by the mental health, counseling, social workers, and education professionals. 38 References [1] Al-Haj, M. (2000). Identity and orientation among the Arabs in Israel: A situation of dual periphery. The Jewish-Arab Divide in Israel: A Reader. 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