1 THE RELATIONSHIP BETWEEN TYPE OF BULLYING EXPERIENCED IN CHILDHOOD AND PSYCHOSOCIAL FUNCTIONING IN YOUNG ADULTHOOD By JENNIFER A. HERETICK A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PA RTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012
2 2012 Jennifer A. Heretick
3 ACKNOWLEDGMENTS First, I thank God for giving me the amazing family and frie nds who have supported me through this process. I thank my mom, dad, brother, and sister for keeping me grounded with their humor and always asking about the progress of my I thank my roommates, Carly and Lindsay, for rehearsing with me and keeping me sane by spending countless hours listening to me talk about my study while fast walking through Gainesville. I thank Montana for encouraging me and making it a point to celebr ate every little accomplishment and gain along the way. I thank the members of my cohort especially Susan, Cathy, and Stacey, who motivated me and spent hours working with me in the local Ga inesville establishments I thank many members of the School Psyc hology program, especially those teachers who allowed me to use their class time t o administer my questionnaires. I thank the NCIPP team for their consistent support through all the years in my program. I thank Jungah, my stats expert, for her time and pa tience in explaining the details Finally, I thank my chairs and other committee members for their feedback and guidance in a process that I would never have been able to complete without their help.
4 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 3 LIST OF TABLES ................................ ................................ ................................ .......................... 6 ABSTRACT ................................ ................................ ................................ ................................ .... 8 CHAPTER 1 REVIEW OF THE LITERATURE ................................ ................................ ....................... 10 Introduction ................................ ................................ ................................ ........................... 10 Forms of Bullying ................................ ................................ ................................ ................. 12 Overt Bullying ................................ ................................ ................................ ................ 13 Relational Bullying ................................ ................................ ................................ ........ 13 Cyberbullying ................................ ................................ ................................ ................. 14 Roles in Bullying ................................ ................................ ................................ ................... 16 Prevalence of Bullying Type ................................ ................................ ............................... 16 Risk Factors ................................ ................................ ................................ .......................... 19 Gender ................................ ................................ ................................ ............................ 19 Age ................................ ................................ ................................ ................................ .. 21 Race/Ethnicity ................................ ................................ ................................ ................ 22 Disa bilities ................................ ................................ ................................ ...................... 23 Sexual Orientation ................................ ................................ ................................ ........ 24 Social Context ................................ ................................ ................................ ............... 24 School Conte xt ................................ ................................ ................................ .............. 25 Psychosocial Adjustment ................................ ................................ ................................ .... 27 Internalizing Problems ................................ ................................ ................................ .. 29 Aggre ssion and Externalizing Behavior Problems ................................ .................. 32 School Functioning ................................ ................................ ................................ ....... 34 Theories Used to Understand the Psychosocial Effects of Bully ing ............................ 35 Social Cognitive Theory and Social Information Processing Theory ........................... 35 Conclusion & Problem Statement ................................ ................................ ..................... 37 2 METHODS AND PROCEDURES ................................ ................................ ..................... 41 Participants and Settings ................................ ................................ ................................ .... 41 Procedures ................................ ................................ ................................ ............................ 43 Measures ................................ ................................ ................................ ............................... 44 Bullying Experiences ................................ ................................ ................................ .... 44 Psychosocial Functioning ................................ ................................ ............................ 49 3 RESULTS ................................ ................................ ................................ .............................. 55 Mean Group Differences in Type of Bullying Experienced ................................ ............ 57 Preva lence of Bullying Types ................................ ................................ ............................. 60
5 Regression Analyses ................................ ................................ ................................ ........... 61 4 DISCUSSION ................................ ................................ ................................ ....................... 90 Introduction ................................ ................................ ................................ ........................... 90 Summary and Implications of Key Findings ................................ ................................ ..... 92 Overt Bullying ................................ ................................ ................................ ................ 93 Relational Bullying ................................ ................................ ................................ ........ 94 Cyber Bullying ................................ ................................ ................................ ............... 96 Total Aggression ................................ ................................ ................................ ........... 97 Total Victimization ................................ ................................ ................................ ......... 98 Mean Group Differences in Relation to Bullying Types ................................ .......... 98 Current Bullying Involvement ................................ ................................ ...................... 99 Summary of Implications ................................ ................................ ........................... 100 Limitations ................................ ................................ ................................ ........................... 101 Study Design and Sample ................................ ................................ ......................... 102 Measurement and Analyses ................................ ................................ ...................... 103 Directions for Future Research ................................ ................................ ........................ 105 APPENDIX A INFORMED CONSENT ................................ ................................ ................................ .... 108 B QUESTIONNAIRE ................................ ................................ ................................ ............. 111 LIST OF REFERENCES ................................ ................................ ................................ .......... 118 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ...... 131
6 LIST OF TABLES Table page 2 1 Demographic information of the entire sample ................................ .................. 54 2 2 Breakdown of financial aid within participating schools ................................ ...... 54 3 2 I ndividual item loadings for the 3 three factor model of the aggression scale .... 69 3 3 Correlation matrix of individual items on the relational victimization questionnaire ................................ ................................ ................................ ..... 70 3 4 Correlation matrix of individual aggression items from the relational victimization questionnaire ................................ ................................ ................ 70 3 5 Correlation matrix of individual aggression and victimization items from the relational victimization questionnaire ................................ ................................ 71 3 6 Factor coefficients of individual items on the relational victimization questionnaire with victimization and aggression items within first component ... 71 3 7 Gender differences in mean scores on the bullying measures ........................... 72 3 8 Differences in mean scores on the bullying measures in relation to sexual orientation ................................ ................................ ................................ ......... 72 3 9 Differences in mean scores on the bullying measures in relation to ethnicity ..... 73 3 10 Frequency of bullying types experienced ................................ ........................... 74 3 11 Mean scores on psychosocial variables ................................ ............................. 74 3 12 Correlations between bullying variables ................................ ............................. 75 3 13 Correlations between psychosocial variables ................................ ..................... 76 3 14 Correlations between bullying variables and psychosocial variables .................. 77 3 15 Regression analyses relating bullying types and demographics to loneliness .... 78 3 16 Reg ression analyses relating bullying types and demographics to fear of negative evaluation ................................ ................................ ........................... 79 3 17 Regression analyses relating bullying types and demographics to social stress ................................ ................................ ................................ ................ 80 3 18 Regression analyses relating bullyi ng types and demographics to anxiety ......... 81
7 3 19 Regression analyses relating bullying types and demographics to depression 82 3 20 Regression analyses relating bullying types and demographics to sense of inadequacy ................................ ................................ ................................ ........ 83 3 21 Regression analyses relating bullying types and demographics to Internalizing problems ................................ ................................ ....................... 84 3 22 Regression analyses relating bullying types and demographics to inattention/hyperactivity ................................ ................................ ..................... 85 3 23 Regression analyses relating bullying types and demographics to sensation seeking ................................ ................................ ................................ .............. 86 3 24 Regression analyses relating bullying types and demographics to alcohol abuse ................................ ................................ ................................ ................ 87 3 25 Regression analyses relating bullying types and demographics to school maladjustment ................................ ................................ ................................ ... 88 3 26 Regression analyses relatin g bullying types and demographics to self esteem ................................ ................................ ................................ .............. 89
8 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosoph y THE RELATIONSHIP BETWEEN TYPE OF BULLYING EXPERIENCED IN CHILDHOOD AND PSYCHOSOCIAL FUNCTIONING IN YOUNG ADULTHOOD By J ennifer A. H eretick August 2012 Chair: Nancy Waldron Co Chair: Diana Joyce Major: School Psychology Bullying is well recognized as a n experience with negative and po tentially adverse consequences. S pecifically, research has consistently shown that involvement in bullying has been linked to a wide range of psychosocial difficulties. There are three forms of bullying that have been ident ified in the literature: Overt bullying, relational bullying, and cyber bullying. Although many studies have investigated the relationship between one specific type of bullying and one or two psychosocial constructs, there is limited research that has focu sed on all three bullying types, and even fewer studies focused on the long term relationship. The purposes of this study were to comprehensively examine the relationship between each specific bullying type identified in the research (overt, relational, an d cyber) and long term psychosocial functioning and to investigate whether specific bullying types were more prevalent among specific risk factors. A total of 277 undergraduates from Gainesville, FL participated in this study. Gender differences existed, s uch that females reported a higher rate of involvement as victims of cyber bullying, and males reported a higher rate of involvement as overt
9 aggressors. Each bullying type was related to specific psychosocial difficulties, with relational victimization be ing associated with the most psychosocial difficulties. In regards to overt bullying, overt aggression was related to current symptoms of Internalizing Problems, Inattention/Hyperactivity, sensation seeking, depression, and school maladjustment. Overt vic timization was related to symptoms of depression in young adulthood. Specific to relational bullying, relational aggression was related to school maladjustment and relational victimization was related to loneliness, fear of negative evaluation, social stre ss, anxiety, depression, low self esteem, and internalizing problems. In regards to cyber bullying, cyber victimization was related to symptoms of sensation seeking. Finally, the study found that higher rates of involvement as a perpetrator of aggressive b ullying behaviors were positively associated with self esteem and negatively associated with school maladjustment. In regards to victimization, higher rates of victimization were negatively associated with sensation seeking behaviors and positively associa ted with social stress in young adulthood.
10 CHAPTE R 1 REVIEW OF THE LITERATURE Introduction As many people are all too familiar with, bullying can have devastating e ffects on children and students. Bullying h as become a widespread problem a ffecting homes schools, and communities. Kent State. Columbine. Virginia Tech. These names along with many others stir memories and bring to mind disturbing images and sounds. These are schools that are located throughout the nation and places where traumatic and well publicized violent acts and fatal shootings occurred. Bullying has been linked to these incidents as well as many other school shootings, incidents of school violence, and suicides ( i SAFE, 2009; Connolly, Pepler, Craig, & Taradash, 2000 ; Wi llard, 2007a ) Bullying involvement can result in many other negative consequences. For example, b ullying has been linked to school avoidance, psychosocial and academic difficulties, higher referral rates, substance abuse issues and higher rates of assau lt problems at school, home, and in the community (Connolly et al., 2000; Gini & Pozzoli, 2009; Juvonen, Graham, & Schuster, 2003; Nansel, Overpeck, Pilla, Ruan, Simons Morton, & Scheidt, 2001 ; Olweus, 2001 ). Despite the significant negative effects that b ullying may have on students, there is no universal standard to how schools will respond to bullying incidents a nd what c onsequences will occur. Some schools may adopt a zero tolerance policy and bullying may result in immediate suspension, where as other schools may only issue a simple warning or a referral. Although we are beginning to recognize the serious detrimental effects bullying is having youth and efforts to draft mandated prevention and intervention legislation are being
11 made (Di amanduros, Downs, & Jenkins, 2008; Srabstein, Berkman, & Pyntikova, 2008, Willard, 2007a), there are still areas within the bullying literature that need to be investigated further. For purposes of the introduction to this study a comprehensive literatur e review of the research on bullying will be presented. This review will include a general definition of each identified bullying type (overt, relational, and cyber) and the roles involved within these types. Following this, the general prevalence rates of each bullying type and the risk factors for involvement will be reviewed Throughout these sections, limitations to interpreting these prevalence rates and limitations in the research base will be highlighted The next section will discuss the related psy chosocial correlates of the various bullying types and describe several theories that may provide a rationale for the development of these psychosocial difficulties. Specifically, a n emphasis will be placed on social cognitive theory and socia l information processing theory. Following a review of the literature, a brief description of the current study and the re search methodology will be described. Within the methodology, the demographics and characteristics of the research participants will be highlighte d and the variou s research measures that were utilized will be explained. In addition, an overall general procedure for the administration of these measures and the collection of data will be described. Next, the results of the statistical analyses of the data and the results will be described in detail. The final section will discuss the implications and limitations of these results related to the existing literature as well as future directions in regards to prevention and intervention as well as future r esearch. The goal of this study is to determine the relationship between the various types of bullying experienced in
12 childhood and psychosocial functioning in young adulthood and to identify various trends in the data to better inform the development of f uture bullying prevention and intervention efforts. Forms of Bullying Many researchers have differing ideas as to how bullying is defined based on setting and geographic location (Bauman, 2008; Griffin & Gross, 2004; Ireland & Ireland, 2003) The bullying literature, the definition of bullying, and the identification of bullying types has been evolving for over 40 years. Dan Olweus, a well recognized bullying expert and the first to conduct a systematic bull ying research study in the 1970 s initially define d traditional b ullying as repeated, physical, verbal, or psychological intimidations or attacks that are directed towards a victim who cannot properly defend him or herself (Olweus, 1994). According to Patchin and Hinduja (2006), bullying has been linke d to the concept of harassment and tends to become more insidious as it occurs over time. In addition, although harassment associated with bullying can occur anywhere, the term bullying often means behavior that occurs proximal or internal to the school se tting such as hallways, bathrooms a nd on playgrounds. However, bullies can also follow victims to other venues such as malls, restaurants, or neighborhood hangouts to continue harassments. In general though, in the past, an interaction in a physical conte xt was required for bullying to occur (Patchin & Hinduja, 2006). violence, physical, or psychological, conducted by an individual or a group directed against an individual who is not able t o defend himself in the actua l situation (p. 21). Nelson and colleagues (2009) encompass all of these views into a widely agreed upon definition that defines traditional bullying as a specific type of aggression that involves
13 behavior that (1) is intended to harm or disturb, (2) occurs repeatedly over time and (3) includes a power imbalance, with a more powerful person or group attacking a less powerful one. It is important to note that other researchers (Elinoff, Chafouleas, & Sassu, 2004; Garritty, Jens, Porter, & Stoker, 2002) feel that this definition should also include a fourth component that specifies that there are multiple forms of bullying (e.g. direct and indirect, verbal and nonverbal). Overt Bullying According to researchers ( Crick & Grotpeter 1995; Ttofi, Farrington, & Baldry, 2010; Olweus, 1 994), there are two distinct forms of bullying: overt bullying and relational bullying Overt, or direct, aggression is the most studied form of bullying and involves both physical bullying behaviors and verbal bullying behaviors. Both physical (e.g. hitting, pushing, kicking, pinching, flicking etc. ) and direct verbal bullying (e.g. malicious teasing, intimidating, threatening, taunting etc. ) occur in face to face interactions ( Bauman 2008; Prinstein, Bo ergers, & Vernberg, 2001) Relational Bullying Indirect bullying or relational aggression is a more covert form o f aggression, altering the face to face component of bullying. According to Crick and Grotpeter (1995), relational aggression is the behavior of harming others through purposeful or intentional manipulation and damage to their peer relationships. Relational aggression may consist of spreading rumors, excluding an individual from a small group of fri ends, pressuring students through threats to th eir social status, and spreading personal information ( Crick, 1996; Crick & Grotpeter, 1995; Tomada & Schneider, 1997 ; Ttofi, Farrington, & Baldry, 2010 ). However, according to Olweus (1994), relational aggression can still occur in a physical environment. For example, a child taunting
14 another student in front of a peer group on school grounds in order to inflict isolation could be considered relational aggression Cyberbullying The introduction of the I nternet and electronic devices has further transform ed bullying from a physical to virtual form. A new form of direct and indirect, or relational bullying has emerged from the use of I nternet and electronic devi ces: cyberbullying (Mason, 2008). Cyberbullying can be defined as sending or posting harmful or e mbarrassing text or images through using the I nternet (i.e. instant messages, e mails, chat rooms, social networking, etc) or other digital communication devices such as cell phones (Feinberg & Robey, 2008 ; Patchin & Hinduja, 2006). Although similar to tra ditional bullying, no physical setting is involved with cyberbullying (Willard, 2005). Cyberbullying typically involves stalking, making threats, harassment, impersonation, humiliation, trickery and exclusion (Feinberg & Robey, 2008). Similar to the tra ditional definition of bullying, the behavior involved in cyberbullying is intended to harm others with a repeated nature (Willard, 2005). According to the National Crime Preventions Council website (2008), behaviors of some youth who cyberbully include: ( a) pretending to be other people online to trick others, (b) tricking people into revealing personal information, (c) spreading lies and rumors, (d) sending mean text messages, and (e) posting unflattering pictures of victims without consent. Unlike the definition of traditional bullying, the power differences between bullies and victims do not necessarily exist within cyberbullying. According to Willard (2005), the absence of physical contact in cyberspace allows for social climbing and victims to easily retaliate. Research has shown that some adolescents, who use the Internet to socialize, probably have been involved in some f orm of cyber bullying (Trolley et al.,
15 2006). Research suggest s that there are six different potential roles which include: (1) ent itlement bullies who believe they are superior to others, (2) targets of entitlement bullies, (3) retaliators, who use the internet to retaliate from being a victim of bullying (4) victims of retaliators, (5) bystanders who are part of the problem or choos e not to be involved and (6) bystanders that are part of the solution, who seek to stop the cyberbullying and help the victim ( Mason, 2008; Trolley et al., 2006; Willard, 2005). Recent cyberbullying research hypothesizes that cyberbullying may be a gr eater danger than traditional bullying. First, cyberbullying can occur at any time and any location and it allows access to the victim 24 hours a day, seven days a week, without a chance for escape. Traditional bullying can only occur during school hours a nd when the victim leaves school grounds he or she can escape to the safety of his or her home and get away from the bully. Second, in cyberbullying the threats, harassments, embarrassing information, derogatory impersonations, humiliations, trickery, and exclusions are distributed worldwide and access is unlimited if it is posted on the I nternet. Typically, in traditional bullying, the embarrassing information is only accessible to those students present during the bullying incident, except when it is spre ad by word of mouth. Third, in comparison to traditional bullying, it is much more difficult to target and find the bully when cyberbullying occurs because bullies can be anonymous and create fake names online. Finally, in cyberbullying it is difficult to determine if the threats posted in the cyberworld are real or just jokes. With technology and printed text, body language and voice inflection cannot be seen or heard and as a result, it is very difficult to decipher whether a remark is intended to harm an other or is simply sarcastic and this could lead to u n necessary retaliations All of these potential
16 factors may lead to more severe outcomes than that of traditional bullying (Willard, 2007a). Roles in Bullying The re are three distinct roles that students can assume in a bullyi ng situation : the aggressor, the victim, or the bystander. These general roles are broken down into the direct and distinct role of the aggressor or the victim and the indirect role of the bystander Bystanders are those students who initially witness the acts of bullying but do not engage in bullying behavior as an aggressor or a victim (Wang et al., 2009) Within traditional bullying, the bully tends to be the the victim takes on a passive role (Wil lard, 2005). According to Chan (2006) the role of the victim or the aggressor can be further divided. Aggressors can be serial bullies who victimize multiple students repeatedly and deliberately intend to harm or an aggressor can victimize one student and only do so one time or infrequently. Victims can be further categorized into those who are targeted by one student or those who are targeted by multiple students (Chan, 2006). In addition to the distinct bully and victim role, children can also take on th Eitel, Crump, Saylor, Yu, et al., 2001; Wang, Iannotti, & Nansel, 2009). A bully victim encompasses both of these roles at some point in time. A bully victim is an individual who both bu llies other people and is bullied by others. It is possible that bully victims come about as a result of a victim who feels the need to retaliate against a specific bully or others as a result of repeated victimizations by an aggressor (Wang et al., 2009). Prevalence of Bullying Type Although bullying is described as a widespread problem exact prevalence rates are difficult to determine. Within the professional literature researchers have differe nt
17 definitions when defining and measuring s various constructs, therefore, it is difficult to compare prevalence rates across studies ( Bauman 2008 ; Griffin & Gross, 2004; Smith, Cowie, Olafsson, & Liefooghe, 2002 ). I n a review of the bullying literature Griffin and Gross (2004) found that the re search on prevalence rates for involvement in bullying ranged from 5 90%. Another potential confounding factor to determining prevalence is that many researchers rely on participants completing self report measures to determine inciden ce rates. These mea sures require participants to endorse whether one has been or currently is involved in bullying behavior and this may have a negative connotation or stigma associated wi th it, dissuading individuals from report ing their involvement accurately This negati ve stigma may similarly influence teacher and parent reporting rates ( Stockdale, Hangaduambo, Duys, Larson, & Sarvela, 2002 ). Recent estimates suggest that 1 in 3 children will experience bullying during the school year either as a bully and/ or as the vi ctim ( Hamburger, Basile & Vivole, 201 1) This conclusion is consistent with previous findings by Nansel and colleagues (2001) who conducted the larg est national study in the United States to date with 15,685 adolescents in grades 6 through 10 The study a ssessed whether students were involved in bullying in any way, as aggressors or victims and found that 10.6% of the students reported engaging in peer aggressive behavior and 8.4 % reported being victimized once or more than once a week. It is important to note that the survey administered in this study did not inquire into cyber victimization or cyber aggression behaviors. The prevalence estimates obtained by Nansel and colleagues are similar to those obtained in a cross international study of 28 different countries, in which 16% of
18 American males and 11% of American females reported being victimized (Due et al., 2005). In a more recent youth risk behavior survey, researchers found that in a nationally representative sample of students in grades 9 12 18.7% of males and 21.2 % of females reported being bullied on school property (Eaton et al., 2010) Specific to relational aggression, research indicates that relati onal victimization makes up at least half of the reported bullying experiences of high school stu dents (Prinstein et al., 2001). Determining accurate prevalence rates for cyber aggression and cyber victimization is particularly difficult because the field is just beginning to emerge. The growing number of network sites and cellular technology has incr eased the difficulty in pinpointing the number of new cases emerging. Current research indicates that cyber victimization rates for ado lescents can range anywhere from 6% to 57 % ( Li, 2006; Patchin & Hinduja, 2006; The Berkman Center for Internet and Soci e t y 2008 ; Ybarra & Mitchell, 2007 ). These differences in reported rates may be due to whether researchers use a broad definit ion for cyber victimization or inquire as to specific cyber victimization behaviors. For example, in a study by Dempsey, Sulkows ki, Nichols, and Storch ( 2009) the researchers asked participants to respond to whether they had experienced specific cyberaggressive behavior (e.g. A student sent me an email that was mean or threatened me ). Research has found that when children are simply asked if they have experienced cyberbullying, lower rates are reported (Ybarra & Mitchell, 2004) than the rates obtained in those studies that specify what cyberbullying behavior entails ( Dempsey et al., 2009; Li, 2006; Patchin & Hinduja, 2006 ; Ybarra & M itchell, 2007 ). However, it is also possible that these increased rates in the more recent studies are
19 technology. Risk Factors Although some of the research findings are c onflicting, it is important to recognize the prevalence and risk factors across the different types of bullying. The bullying research indicates that several factors may contribute to a higher rate of bullying involvement, as either the bully and/or victim T he following sections will highlight the prevalent factors identified in the bullying research Specifically, the research related to gender, age, race/ethnicity, students identified with disabilities, and sexual orientation will be emphasized In addit ion, the influence of the social and school environment on bullying will be discussed. Gender The research regarding overt and physical aggression is consistent in finding that the use of overt aggression is more prevalent in males compared to females ( Co ie, Dodge & Kupersmidt, 1990; Crick & Grotpeter, 1996; Nansel et al., 2001; Prinstein et al., 2001). Although research in dicates that males are more likely to engage in acts of overt aggression, the research regarding which gender reports experiencing mor e overt victimization varies. Most studies ( Crick & Grotpeter, 1996; Nansel et al., 2001; Prinstein et al., 2001) indicate that males report higher rates of overt victimization, where as others ( Archer, 2004; Leadbeater & Hoglund, 2009) have foun d similar reported rates of overt victimization among both males and females. Furthermore, international research indicates that overt aggressive behavior in girls i s increasing in the U.S. and in other industrial countries ( Borntrager, Davis, Bernstein, & Gorman,
20 2 009; Henington, Hughes, Cavell, & Thompson, 1998; Leschied, Cummings, van Brunschot, Cunningham, & Saunders, 2001). Initially, it was assumed that relational aggression was a type of bullying used and experi enced predominantly by females. H owever, as the literature base has expanded research findings reflect differ ing rates of prevalence by gender and age Some studies have found that females are more likely to engage in relational aggression (Crick & Grotpeter, 1995; Ostrov & Keating, 2004 ) and be victim s of relational aggression ( Crick, Casas, & Ku, 1999; Crick & Grotpeter, 1995; Finkelhor et al., 2009; Ostrov & Keating, 2004 ; Wang et al., 2009 ), where as other studies have found that males are more likely to be victims of relational aggression (La Greca & Harrison, 2005) There are also several studies ( Espelage, Mebane, & Swearer; 2004; Nansel et al., 2001; Prinstein et al., 2001; Storch, Brassard, & Masia Warner, 2003; Storch, Crisp, Roberti, Bagner, & Masia Warner, 2005) that indicate no significant ge nder differences and have found that both males and females report similar rates of relational victimization and aggression The literature presents mixed results as to whether boys or girls have a higher involvement rate in cyberbullying. Willard (2006) indicates that girls are more involved in online activity and communication and therefore more frequently involved in cyberbullying. In contrast, another study by Mason (2008) indicates that gender differences were accounted for and males (22%) reported a higher rate of being the cyberbully than females (12%). However, this same study indicated that there were no significant gender differences in students who were victims of cyberbullying. In another recent study conducted by Dempsey and colleagues (2009), researchers surveyed 1,684 middle school students and found that a larger percentage of females (17%)
21 reported being victims of cyberbullying than males (11%). As with much of the current cyberbullying literature, this particular study did not examine the prevalence of cyber aggression F uture research will need to examine the rates of both cyber ag g ression and cyber victimization Age In general, researchers have found that bullying occurs at the highest rate during adolescence and the middle school years and decreases over the high school years (Finkelhor, Turner, Ormrod, Hamby, & Kracke, 2009; Nansel et al., 2001; Ross, 1996). Adolescence is the pe ak of social activity and is a critical period when children form their identities and develop who they will be as an adult (Fergus & Zimmerman, 2005 ; Pelligrini & Long, 2002 ). D uring this time, adolescents are struggling to identify themselves and the ranking of their peer group. Following this, bullying can serve as a potential method to assert a specific indiv play a role in this social power struggle (Pelligrini & Long, 2002). Dependent on the age of the population, the reported rates of relational aggression do differ. In studies that examined prevalence of relation al aggression in preschool and elementary school aged children, researchers found that girls reported higher rates of peer victimization than boys ( Crick, Casas, & Ku, 1999; Crick & Grotpeter, 1995), where as in studies that surveyed adolescents, researche rs found similar reported rates of relational aggression among both males and females (Nansel et al., 2001; Prinstein et al., 2001; Storch et al., 2005). When examining the reported rates of relational aggression over time, Cric k (1996) found that the prev alence rate of relational aggression in girls from 3 rd to 6 th grade was stable, indicating that relational aggression is just as prevalent at a young age In a meta analysis conducted by
22 Scheitauer (2002), research indicated that the reported rates of rela tional victimization are higher in girls younger than 7 years old and then between the ages of 8 and 12 similar rates we re report ed among both males and females. After the age of 13, the number of girls who reported being relationally victimized significan tly surpassed that of the males (as cited in Smith, 2004) Race/ Ethnicity Although research on the rates of bullying by ethnicity is limited, there are some conflicting studies that suggest that c hild ren s ethnicity may place them at a higher risk for be ing involved in bullying (Stein et al., 2007) For example, s ome r esearch indicates that Hispanic youth r eport being the victims of bully ing more frequently than their Cauc asian peers ( Storch, Nock, Masia Warner, & Barlas, 2003; Wang et al., 2009) where as another study found that Hispanic children in grades 1, 2, and 4 were less likely to be victimized in comparison to their African American and Caucasian peers (Hanish & Guerra, 2000). Stein and colleagues (2007) found that youth who identified themselves as of race/ethnicity were more likely to be the vic tims of bullying in comparison to self identified Hispanic, African American, and Caucasian peers. In a large national study conducted by Nansel and colleagues (2001) they found that African Americ an students in grades 6 through 10 were more likely to be victimized than their Caucasian peers. In contrast, The Health Behaviors in Sch ool aged Children Survey (2007) found that African American students in the exact same age range (grades 6 through 10) reported a lower rate of victimization in comparison to their Caucasian and Hispanic peers (Spriggs, Iannotti, Nansel, & Haynie, 2007). Some results do consistently suggest that children who speak languages other than English or do not speak English at hom e are more likely to be victimized or report feelings of victimization
23 (U.S. Department of Health and Human Services, 2003; Yu, Huang, Schwalberg, Overpeck, & Kogan, 2003). Disabilities In regards to disabilities and disorders, the bullying research has indicated that children with disabilities or special needs are more likely to be bullied than children without disabilities or special needs (Rigby, 2002 ; Rose, Espelage, & Monda Amaya, 2009 ). Specifically, children who have been identified with learning d isabilities were more likely to report being victims of bullying (Mishna, 2003; Flynt & Morton, 200 7 ; Rigby, 2002). International research also suggest s that children with learning disab ilities are twice as likely to be physically aggressive when compared to general education peers ( Kaukiainen Salmivalli, Lagerspetz, Tamminen, Vauras, Mki, et al., 2002). Rose and coll eagues (2009) conducted a large scale study with American middle school students (n = 7331) and high school students (n = 14,315) in general education and special education (inclusion and self contained) and found that those students enrolled in special education reported higher rates of physical aggression, relational aggression, and experiences of victimization. Furthermore, the study also f ound that students receiving special education services in a more restrictive setting (self contained ) reported higher rates of physical aggression, relational aggression, and experiences of victimization in com parison to peers in a less restrictive settin g (inclusion). In addition to students with learning disabilities and those receiving special education services the literature suggests that children with medical conditions that affect their physical appearance are also more likely to report being victi ms of bullying (Storch & Ledley, 2005).
24 Sexual Orientation Another consistent finding in the literature is that lesbian, gay, bisexual and transgender (LGBT) students are more likely to be victimized than heterosexual students ( Berlan, Corliss, Field, G oodman, & Austin, 2010; Savin Williams, 1994). In the 2003 Massachusetts Youth Risk Behavior Survey, researchers found that twice as many self identified sexual minority youth (42%) reported being victimized in the last year in comparison to heterosexual youth (21%). In another and Hershberger (2002) examined victimization by specific bullying type and found that more than half of those students who identified as LGBT were victimized verbally, 25% were threatened with violence and 10% were physically attacked Furthermore, the earlier these students identified themselves as being LGBT in high school the higher the reported incident rate of victim ization. Social Context One potential reason for the mixed research findings reg arding prevalence rates by specific bullying type could be due to the social context and implied norms a child internalizes (Crothers, Field, & Kolbert, 2005; Underwood, Galen, & Paquette, 2001). Based on an ecological framework, there are many factors (in dividual, peer, family, school, community, etc.) that may influence a child (Bronfenbrenner, 1977). Geographic region and location, community variables (e.g. support programs, adult involvement), and school district level var iables (e.g. school size and demographics) can influence the societal context and what children may adhere to or internalize when determining what behavior is appropriate (Kosciw, Greytak, & Diaz, 2009). Specifically, in relation to the use of overt aggres sion versus relational aggression, it may be more socially acceptable for a male to display physically
25 aggressive behavior where as in this same social environment a female may need to su ppress the urge to display this type of aggression and resort to othe r means (e.g. relational aggression) (Crothers, Field, & Kolbert, 2005). The homophily hypothesis is another potential explanation for the mixed research results. This hypothesis generally states that children will act in such a way that is congruent with the behavior of that of their peers, or the social context or group to which they want to belong. In one particular study that investigated the hom o phily hypothesis, researcher s found that children were more likely to display aggression if the peers in the ir social group also frequently displayed aggression (Espelage, Holt, & Henkel, 2003). Specific to cyberbullying, some preliminary research indicates if a student has negative social expectations and/or a lack of empathy towards peers and other s cyberbull ying rates may increase (Willard, 2004). School Context Although the research has found mixed results regarding the varying prevalence rates of bullying in different school environments, b ullying has been found to be present in all types of school setting s (suburban, rural, and urban) and with all socioeconomic levels (high poverty, middle class, affluent) ( Due, Damsgaard, Rikke, & Holstein, 2009; Holt, Finkelhor, & Kantor, 2006; Stockdale et al., 2002; Sullivan, Farrell, & Kliewer, 2006; Werner & Nixon, 2 005). In addition, the particular school environment itself can serve as a potential moderating factor for the prevalence of bullying. When students perceive the school environment to be hostile and the school staff to be unwelcoming or disrespectful rese arch indicates that the reported rate of bullying increases ( Langdon & Preble, 2008; Meyers Adams & Conner, 2008; Williams & Guerra, 2007) For example, i f there are deficits in academic and behavior supports (e.g. low availability of teachers,
26 lack of pos itive reinforcers, etc ) or a lack of school pride students may perceive the school climate to be negative. Also related to this, research indicates that when students have a negative perception of their peers bullying rates increase. If students perceiv e that their peers are not trustworthy, respectful, and helpful this affects their overall peer perception and school climate perception ( Langdon & Preble, 2008; Williams & Guerra, 2007). Specific to cyberbullying, research indicates that the higher the ra te of physical and verbal bullying at school, the higher the rate of cyberbullying at home. In other words, if schools have higher incidents of traditional bullying it is predicted that the rates of cyberbullying will also increase (Willard, 2006; Williams & Guerra, 2007). This risk factor is also tied to social status and cyberbullying can be a continuation of bullying that occu rs in school. Students who are bullied at school may use the anonymity of the Internet to retaliate at home (Willard, 2006). Anoth er risk factor sp ecific to cyberbullying and related to the school context is access (Hinduja & Patchin, 2008; Pollock & McKevitt, 2009; Willard, 2006). Research indicates that the rate of cyberbullying increases with access to Internet, cell phone, digita Patchin (2008) found that the more time children spent online and the higher their computer proficiency rating, the higher likelihood of increased rates of cyberbullying. According to a survey of 512 girls in the 7 th 12 th grades, more than 60% shared their password over the Internet and reported taking risks online (e.g. meeting people who they have met online in perso n ) ( The Berkman Center for Internet and Societ y 2008). Researc
27 education sites only, promote Internet recess, no monitoring, etc.), higher rates of cyberbullying are reported (Pollock & McKevitt, 2009; Willard, 2006). In one particular study (Li, 2006), researchers found that half of those students who were cyberbullied were actually cyberbullied at school. Finally a general lack of knowledge in the school can contribute to higher incidents of cyberbullying Specifically, research indi cates that a lack of student education regarding Inte rnet safety and responsible use and a lack of teacher education or professional development regarding appropriate educational use of technolog ies may influence reported rates (i SAFE, 2009; Willard, 2006 ). Psychosocial Adjustment Numerous studies have shown the negative and deleterious effects bullying can & Summers 2009 ; Dempsey et al., 2009; Grotpeter & Crick, 1996; Hawker & Boulton, 2000; Hoglund, 20 07; Holt et al., 2007 ; Juvonen, Graham, & Schuster, 2003; Kaltiala Heino, Rimpelae, & Rantanen, 2001 ; Prinstein et al., 2001; Ybarra & Mitchell, 2004 ) Most of these studies concurrently survey bullying behaviors and psychosocial functioning using cross se ctional research designs Although some research uses longitudinal designs (Bond, Carlin, Thomas, Rubin, & Patton, 2001; Hodges & Perry, 1999 ; Leadbeater & Hoglund, 2009 ; Storch et al., 2005 ) and suggest s that bullying has negative long term effe cts on psy chosocial functioning, this literature base is limited and most of these longitudinal studies only followed children Furthermore, m ost of the longitudinal studies cited in the literature have been conducted int ernationally (Bond, Carlin, Thomas, Rubin, & Patton, 2001; Due et al., 2009 ; Rigby, 2003 ; Sourander, Jensen, Ronning, Elonheimo, Niemela, Helenius, Kumpulainen, et al. 2007 ).
28 It is difficult to establish a causal relationship between the experience of bu llying and psychosocia l difficulties (Swearer, Espelage, Vaillancourt, & Hymel, 2010) First, it is not possible to randomly assign participants to specific conditions and determine cause and effect Furthermore, it is difficult to determine whether the ps ychosocial difficulties lead to bullying or whether bullying leads to psychosocial difficulties. It is possible that children with psychosocial difficulties display the behaviors associated with their psychological or social difficulties and therefore, are more likely to be involved in bullying as an aggressor or a victim The transactional theory of developmental psychopathology support s this and hypothesize s susceptibilities transact with the dangers in their environment t o exacerbate or maintain their psychological difficulties or maladjustment (Cicchetti & Rogosh, 2002; Leadbeater & Hoglund, 2009). The few studies (Dempsey & Storch, 2008 ; Ledley, Storch, Coles, Heimberg, Moser, & Bravata, 2006) that have been conducted wi th American children and examined the relationship between bullying and psychosocial functioning over an extended period of time have utilized retrospective met hodological designs. These studies ask participants to recall their experiences with bullying du ring a specific time period (e.g. in high school) and then provide them with psychosocial measures to examine current psychosocial functioning. Unfortunately, because these studies rely on it is possible that the reported rates are subject to bias of current moods and inaccurate memory (Dempsey & Storch 2009 ) The literature has consistently identified several externalizing and internalizing problems associated with bu llying (Crick & Grotp eter, 2006; Espelage & Holt, 2007;
29 Prinstein et al., 2001; Ybarra & Mitchell, 2004 ) Some of the research has investigated whether these specific problems have been related to specific bullying types (overt, relational, cyber) or specific bullying roles (b ully, victim, bully victim), where as other studies simply group the types and the roles together. For purposes of this review efforts will be made to describe the results within these categories. Internalizing Problems O vert, relational, and /or cyber vic timization have all be en shown to be associated with various problems within the individual, or internalizing problems (e.g. anxiety and depression) (Juvonen et al., 2003; Prinstein et al., 2001). Furthermore, research suggests that the experience of multi ple victimization types increases ones likelihood to have internalizing problems ( Dempsey & Storch, 2008; Kochenderfer & Ladd, 1996; Prinstein et al., 2001 ; Storch, Nock, Masia Warner, & Barlas, 2003 ). Specifically, research indicates that individuals who have experienced overt, relational, and/or cyber victimization report higher rates of social anxiety, loneliness, depression, and low self esteem or self worth in comparison to non victimized peers ( Bond et al., 2001; Espelage & Holt, 2007; Hawker & Boulto n, 2000; Juvonen et al., 2003; Prinstein et al., 2001; Ybarra & Mitchell, 2004). Due and colleagues (2009) conducted a longitudinal study with 614 British children exposed to bullying from ages 15 to 27 and investigated the effects this had on participant bullying was associated with increased risk for depression at the 12 year follow up. In addition, females and children from less af fluent backgrounds were more at risk for depression symptomology Notably, although this study used a rigorous methodological design and surveyed the same population longitudinally, like much of the current
30 bullying research, the researchers did not distinguish among the bullying types and simply asked part which may lead to inconsistencies in reporting In another study by Juvonen and colleagues (2000), researchers examined the effects of self perceived peer victimization (specifically etc.) on three specific psychological adjustment domains: loneliness, depression, and self worth. The results of the study suggested that self perceived peer victimization was predictive of all thr ee psycholog ical difficulties. This is consist ent with previous research indica ting that children who were victimized by peers had low er self esteem (Crick & Grotpeter, 1996; Koch enderfer & Ladd, 1996) and blame d themselves for being the vic tims of bullyin g, which may have led to an exacerbation of psychosocial difficulties (Graham, 2006; Graham & Juvonen, 1998; Lansford, Malone, Stevens, Dodge Bates, & Pettit, 2006b ). It is important to note that there are mixed findings across research studies regarding specific internalizing disorders and specific bullying types. For example, where as Ybarra & Mitchell (2004) found that those individual s who experienced cyber victimization were more likely to report depressive sympt oms than non victimiz ed peers, a more re cent study conducted by Dempsey and colleagues (2009) found that experiences with cyber victimization was not significantly associated with symptoms of depression, but rather only with social anxiety. It is important to note that Dempsey and colleagues ask ed pa rticipants about specific cyber bullying behaviors where as Ybarra and Mitchell simply asked about harassment on the Internet.
31 A few studies have examined the relationship between the bullying type experienced and strength of the internalizing symptom s. Some research has suggested that youth who have experienced relational victimization report more severe symptom s of depression than youth who have experienced only overt victimization (Bauman & Summers, 2009 ; Storch et al. 2003 b ). Bauman and Summers (2 009) investigated this relationship in Mexican American middle sch ool students and found that al though both forms of victimization (relational and overt) were associated with depressive symptoms, relational victimization increased the likelihood of depress ive symptoms. In another study, Storch and colleagues (2005) investigated the relationship between overt and relational victimization and social phobia and social anxiety with 144 ninth graders. At the one year follow up, the researchers found that only re lational victimization was predictive of social phobia. As with many other current studies this study only investigated a few specific internalizing disorders and did not comprehensively address all the psychological disorders that research has indicated t o be associated with the experience of bullying. Other studies have investigated the relationship between the bullying role and the strength of internalizing disorders ( Craig, 1998; Estevez, Murgui, & Musitu, 2009; Kumpulainen, Rsnen, Henttonen, Almqvist Kresanov, Linna, et al., 1998 ; Stein, Dukes, & Warren, 2007 ) For example, a few studies have found support for the hypothesis that those individuals who fulfill both the bully and the victim role, a bully victim, report more serious psychosocial problems than those individuals who identify solely as the bully or solely as the victim (Kumpulainen et al., 1998 ; Stein et al., 2007 ) I n an international study (Estevez et al., 2009) conducted with 1 319 students aged 11
32 to 16 in Valencia, Spain, researchers co mpared the relationship between various psychosocial constructs and groups of students involved in bullying (bully, victims, and bully victims) as well as a comparison group of students not involved in bullying. The researchers found that in comparison to the students not involved in bullying, those involved in bullying reported more stress and expressed less satisfaction with life. In addition, victims reported the strongest symptoms of loneliness and both victims and bully victims reported higher depres sive symptomology than bullies and those not involved in bullying. Similar to these results, other research (Stein et al., 200 9) that has compared symptomology across all roles (bully, victims, and bully victims), found that bully victims had the poorest p sychosocial functioning (low self esteem, low control of life and lowest life satisfaction) and that bully victims and victims have the highest reported depressive and anxiety symptoms (Espelage & Holt, 2007) Aggression and External izing Behavior Problem s Some research has indicated the youth who bully others are at increased risk for externalizing problems and aggressive behavior (Connolly, Pepler, Craig, & Taradash, 2000; Sourander, Jensen, Ronning, Elonheimo, Niemela, Helenius, et al., 2007). Connolly and colleagues (2000) surveyed 196 adolescents who self identified as bullies in the past few months and found that these individuals were significantly more likely to report being ph ysically and verbally aggressive with their boyfriends and girlfriends. I n a longitudinal study that followed 2,551 Finnish boys from the ages of 8 to 16 to 20 years old, researchers examined the relationship between the reported rates of victimization and aggression in childhood and incidents of juvenile criminality. In order to gain a comprehensive and accurate rate of victimization experiences and bullying aggression, multiple sources (teachers, parents, and children) were surveyed. The results of the
33 study indicated that those youth who were identified as frequent bullies an d frequent bully victims committed 33% of all juvenile crimes during the four year time frame The study indicated that those who were identified as frequent bully victims predicted repeated offending (committing more than 2 crimes) and those that were id entified as frequent bullies predicted both occasional ( committing 1 to 2 crimes) and repeated offending. In relation to specific crimes committed those identified as frequent bullies committed the highest repeated violent offenses (overt aggressive behav ior towards another human being) and occasional drug offenses ( importing, possessing, manufacturing, exporting, purchasing, distributing, or purchasing illegal drugs) ; where as those identified as frequent bully victims committed the highest property offen ses (covert aggressive behavior targeted at propert y ), traffic offenses (reckless driving and driving without a license), and drunk driving offenses (Sourander et al., 2007). Initially, it was widely believed that physical victimization was the only type o f victimization related to externalizing problems, but current research also suggests that other types of victimization can lead to externalizing problems (Crick & Grotpeter, 2006; Prinstein et al., 2001). In regards to aggressive behavior, some studies ha ve indicated there is a positive relationship between social rejection (relational victimization) and increased antisocial behavior or aggression (Dodge & Pettit, 2003; Dodge et al., 2003). In relation to aggression and externalizing difficulties, some re search has identified d ifferences based on bullying role (Craig, 1998; Sourander et al., 2007; Stein et al., 2007). Stein and colleagues (2007) found that bully victims reported more problem behaviors (delinquency, substance abuse, and weapons possession) and physical injury in comparison to non involved peers and peers who reported being solely the
34 bully or the victim. Another study (Craig, 1998) found that younger (5 th grade) male bully victims are more likely to be physically and verbally aggressive than other youth who identified as only a victim or a bully. Following this trend, research indicates that physically victimized adolescent s are less likely to be aware of when a conflict arises and this could potentially lead to physical retaliation (Hoglund & Leadbeater, 2007). In the abovementioned studies, it is not evident whether the bully victims were victims first and then became the bully to retaliate, or whether the bully victims were bullies first and then became the victim, or if the involvement occurred concurrently. However, if the bully victims were the victims first and were retaliating, victims are identified as having high er rates of aggressive behav ior. Although a causal relationship has not been determined, reports indicate that cyberbullying has also been linked to other deviant behavior among adolescents. In comparison to peers, cyberbullying victims may have higher rates of school problems and re ferrals. Research by Hinduja and Patchin (2008) indicates that those students who are involved in cyberbullying are also more likely to have substance abuse issues and higher rates of assaultive problems at school, home, and the community. School Functioni ng In general, bullying has consistently been shown to be associated with difficulties and problems in school (Juvonen et al., 2000; Stein et al., 2007). Research indicates that children who are victims of bullying are more likely to have academic problems and a negative attitude towards school (Arseneault, Walsh, Trzesniewski, Newcombe, Caspi, & Moffitt, 2006; Gini & Pozzoli, 2009; Kochenderfer & Ladd, 1996). In addition, research has also indicated that bullies have negative attitudes towards school, and are
35 at in creased risk for truancy issues and dropping out of school (Nansel et al., 2001, Stein et al., 200 7; Swear er et al., 2010) Cyberbullying has also been indicated to impact students in other ways. S tudents who are the victims of cyberbullying repor t that they do not feel safe at school and are therefore more likely to avoid attending school which may eventually result in school failure (Hinduja & Patchin, 2008; Willard, 2007a). Research by Kuligowski and Ubertini (2009) indicates that cyberbullying may also lead to other refusal behaviors that may Theories Used to Understand the Psychosocial Effects of Bullying There are several different theories in the bully ing literature that can provide a potential explanation for the development of psychosocial difficulties in children who are involved in bullying. The specific theories that will be discussed, social cognitive theory and social inf ormation processing theor y, are closely intertwined and both highlight the critical influence of how a child processes bullying experiences. The theories emphasize Social Cognitive Theory and Social Information Processing Theory Social cognitive theory may explain the future development of externalizing and internalizing problems following bullying experiences Based on this theory, through repeated victimizations in a social situation, childr en may develop generalized negative cognitive representations of themselves or others. In general, this theory states that children interpret their environment and process social in formation (Bandura, 1989; Fontaine, Burks, & Dodge 2002). For example, if the victims of bullying interpret negative peer interactions as a negative reflection of themselves, then they are going to be more likely
36 to develop internalizing problems (e.g. de pression, anxiety, etc.) because they feel that there is something wrong with them that led to th e bullying (Lansford et al., 2006b; Leahy & Holland, 2006). However, if victims of bullying feel that there is something wrong with their peers and develop a n egative attitudes towards them it is possible that the victimized child will develop externalizing problems (e.g. aggression) and react with hostility towards others whether or not they are truly provoked (Dodge, Lochman, Harnish, Bates, & Pettit, 1997; D odge, Price, Bachorowski, & Newman, 1990; Fontaine, Burks, & Dodge 2002; Leahy & Holland, 2006). Following this, the attribution of the bullying experience could be critical to the development of psychosocial difficulties. Social information processing th eory can be used to explain the potentially negative thought patterns that may result in children who are both the aggressors and victims of bullying. This theory proposes that an actual deficit in how one processes social situations, may be associated wit h more aggressive behavior and lead to bullying behavior (Lansford, Malone, Dodge, Crozier, Pettit, & Bates, 2006a). Furthermore, when victimization occu rs, children may also develop negative expectations of violence from others. Combining this with socia l cognitive theory, children form cognitions or beliefs that they will encounter violence in everyday interactions with other children and may develop generalized cognitive representations of themselves (Crick & Dodge, 1994). Following the development of t he generalized cognitive representations of others and the self, a child will use these perceptions to determine not only their behavioral Dodge, Price, & Laird, 1999). Fo r example, a child who is repeatedly victimized may come to believe that he or she will always be victimized when he or she interacts with
37 other children. If approached by another student, the victimized child may automatically assume (based on deficits in their processing in combination with their cognitive representations) that the other student is going to be hostile and react in a way that is congruent with this expectation. In support of this, Storch and colleagues (2005) found that males, who repeated ly experienced relational victimization over time, were more likely to show increases in symptoms of social anxiety and social phobia. Crick and Dodge (1994) have also developed a social information processing model based on different types of aggression. Based on their research they have found that adolescents who are found to be more physically aggressive are more likely to make hostile attributions biases when they are in instrumentally provocative situations (e.g. bumped in the hall) where as relationa lly aggressive youth are more likely to create hostile attributions based on a perceived social aggravation or threat ( Crick & Dod ge, 1996; Werner & Nixon, 2005). In addition, within this model they have defined reactive and proactive aggression. Reactive aggression typic ally is defined as a retalia tive defensive action against another based on the perception or misinterpretation of an attack. This misinterpretation may lead to a chain of misinterpretations and result in a negative bias regarding the action s of others. Proactive aggression is a purposeful or deliberate aggressive act that is not provoked by anything and results in biases later (Crick & Dodge, 1996). Conclusion & Problem Statement Based on the literature review, it is apparent that bullying continues to be a major problem with potentially deleterious eff ects. R ecent estimates indicate that one in three children will experience bullying of some form in the upcoming school year ( Hamburger et al., 2011) T hree primary forms of bullying have been consistently identified : overt,
38 relational, and cyber. Overt bullying is the oldest and most commo nly studied form of bullying that involves both physical bullying behaviors and verbal bullying behaviors ( Bauman, 2008; Prinstein, Boergers, & Vernberg, 200 1), whereas r elational bullying is a more recently identified form of bullying that consists of harming others through purposeful or intentional manipulation and damage to their peer relationships (Crick & Grotpeter, 1995) Finally, the most recently ident ified form of bullying is cyberbullying, which consists of sending or posting harmful or embarrassing text or images using the Internet or other digital communication devices (Feinberg & Robey, 2008; Patchin & Hinduja, 2006). The current literature re view indicates that the prevalence rates of these various bullying types differ not only by type but also by different demographic characteristics and risk factors (e.g. age, gender, ethnicity LGBT youth, children who have been identified with learning disabil ities and social and school context ). T he literature is replete with findings that indicate bullying experiences are related to psychosocial difficulties. I n general, children who are involved in bullying as an aggressor and/or victim are more likely to r eport psychosocial difficulties than their non involved peers (Crick & Grotpeter, 2006; Espelage & Holt, 2007; Prinstein et al., 2001; Ybarra & Mitchell, 2004) The bullying research has investigated a wide variety of different psychological and social con structs and several psychosocial issues are related to bullying experiences. Specifically, researchers have consistently found that various internalizing problems such as low self esteem loneliness, and symptoms of depression and social anxiety are associ ated with bullying experiences (Bauman & Summers, 2009 ; Dempsey et al., 2009; Juvonen et al., 2000; Storch et al., 2003b, Storch et al., 2005 ) In addition, various external izing behavior problems such as anger
39 and related disruptive conduct problems (e.g. alcohol and drug abuse, possession of a weapon, violence towards others) are associated with bullying experiences (Prinstein et al. 2001; Sourander et al., 2007; Stein et al., 2007). Finally, a review of the literature has also indicated that involvement in bullying is closely related to issues in school (e.g. 2000; Stein et al., 2007; Swearer, et al. 2010). Despite the fact that bullyin g has been researched for ove r 4 0 years, current prevalence rates remain high and may continue to grow with the development of new forms of bullying and technology Following this, i t is critical that research on this topic continue with new studies addressing the limitations that ex ist with in the bullying literature. A s mentioned previously, many of the existing research studies on bullying do not define the term bullying which may be one factor contributing to the inconsistencies in results ( Bauman, 2008; Griffin & Gross, 2004; Ire land & Ireland, 2003) Furthermore, when studies do define bullying they may use a n all inclusive definition and not distinguish among the different types of bullying. From this review, it i s apparent that specific bullying types may be associated with spe cific risk factors and/or psychosocial outcomes and it may be necessary to define the bullying types in order to reach definitive conclusions. Another significant limitation in the litera ture is that many studies do not include all the various bullying rol es (aggr essor and victim) and only assess outcomes for victims of bullying. However, s tu dies in this review indicated different negative psychosocial outcomes for aggressors victims and those who were both the aggressor and the bully, bully victims high light ing the importance of distinguishing between roles ( Craig, 1998; Estevez et al., 2009; Stein, et al., 2007).
40 Another significant limitation in the bullying literature is that there are only a f ew studies that have investigate d th e long term relationsh ip between bullying and psychosocial functioning with American participants ( Jantzer, Hoover, & Narloch, 2006) Although there are research studies that have used longitudinal designs (Bond, Carlin, Thomas, Rubin, & Patton, 2001; Hodges & Perry, 1999; Lead beater & Hogl und, 2009; Storch et al., 2005), most of these studies only followed chi ldren for a few years at most and the studies (Dempsey & Storch, 2008; Ledley, Storch, Coles, Heimberg, Moser, & Bravata, 2006) that have been conducted with American chil dren have not examined the long term effects of all the various bullying types. The proposed study will comprehensively examine the relationship between each specific bullying type identified in the research (overt, relational, and cyber) and long term ps ychosocial functioning This study will utilize measures that assess specific descriptions of each bullying behavior in order to determine which bullying type participants were involved in. In addition, whereas p r evious studies have investigated psychosoci al outcomes within a few constructs, this study will investigate psychosocial functioning across a variety of psychosocial factors that have been identified to be related to bullying experiences. The findings of the proposed study can be utilized in the fu ture development of targeted bullying prevention and intervention strategies based on specific roles in bullying and the specific bullying type. Specifically, the primary research question of the proposed study is as follows: What is the relationship bet ween recalled type of bullying experienced in childhood (overt, relational, and cyber) and psychosocial functioning in you ng adulthood?
41 CHAPTER 2 M ETHODS AND PROCEDURE S Participants and Settings Partic ipants were undergraduate students enrolled in the Un iversity of Florida (UF) or Santa Fe College (SFC) in Gainesville, FL. The students were recruited through a variety of different sources: the School of Human Development and Organizational Studies in Education (SHDOSE) organized human participant research pool five Intro duction to Psychology classes at S anta Fe Community Co llege, and four Introduction to Diversity for Educators classes within the College of Education (COE) at UF. The target population was limited to students who were enrolled in courses for the Fall 2010 and Spring 2011 terms. S tudent demographics as reported by The Office of Institutional Planning and Research (2011) indicates that t he University of Florida population in terms of race ( 58 % White 8 % Black 14% Hispanic, 9 % Asian/ Pacific Islander < 1% American Indian /Alaskan Native, and 3 % Other/Unknown ) and gender ( 45% male and 55 % female) differ s somewhat from Santa Fe College demographics in terms of race ( 64.1 % White 17.9 % Black 10 .1% Hispanic, 2.9% Asian/Pacific Islander, .5% Ameri can Indian, 1.7 % Non Resident alien, 2.8% O ther ) and gender ( 46 % male and 54 % female) as reported in the Fall 2010 Facts by Santa Fe College (20 11) The original sample inclu ded 300 participants, however 26 participants were excluded from the final dat a analysis because they did not meet the age requirements to participate in this study (were not between the ages of 18 and 25 years old). Also, an additional 12 participants were excluded from the regression a nalyses due to questionable response patterns on the psychosocial measures. Thus, the total sample
42 size for the study w as 277 participants, but only 26 5 utilized during the regression analyses. Demographic information o f the sample is presented in T able 2 1. Approximatel y 5 5 % of the s ample was enrolled at UF and 45 % was enrolled at SF C In regards to gender, the sample was predominantly female (66%). In regards to sexuality, the majority of the sample (94%) indicat ed that they were heterosexual and the other remaining 6 % reported being bisexual, homosexual (lesbian or gay), and/or asexual. The distribution of the reported ethnicities was similar to that reported by UF and SF: 68.1% W hite; 13.4 % Hispanic; 12.3% Black ; 2.5 % Asian; and 3.6% other. Participants ranged in age from 18 to 25, but the majority of the p articipants were under 20 years old (61.3%) and the average age of participants was 19.5 (SD = 1.57) years old In relation to eligibility for financial aid as reported by UF students approximately 46 % of UF student s indicated that they were eligible for federal grants, 40 % indicated that they were eligible for need based scholarships, 48% indicated that they were eligible for student loans, and 28% indicated that they were eligible for student employment. In relatio n to eligibility for financial aid as reported by SFC students, approximately 50% of SFC students indicated that they were eligible for federal grants, 18 % indicated that they were eligible for need based scholarships, 55 % indicated that they were eli gible for student loans, and 20 % indicated that they were eligible for student employment. In total, a pproximately 71.8 % of the sample indicated that they qualified for some type of financial aid (federal, need based, loans, or student employment). This is simi lar to the percentage of students who receive financial aid a s reported by both UF (more than
43 70%) and SFC as a whole (72%). The breakdown of eligibility for financial as sistance is provided in Table 2 2. Procedures The procedures and protocol for this stu dy were submitted to the University of for approval. Following approval, the que stionnaires and measures were administered to students during the Fall 2010 and Spring 2011 semester s during the months of December January, and February The principa l investigator (PI) recruited participants through individual instructors and classes at UF and SFC. The PI contac t ed several instructors via email and determine d if they we re willing to allow questionnaires to be adminis tered to students during class time for extra credit. The PI provide d each instructor with an information sheet on the study and what it entails. Following a review of this sheet, the instructors inform ed the PI whether they w ould allow their class to part icipate. The PI then ma de arrangements with each course professor to attend class at a agreed upon day to administer the measures to those students who elected to participate. On the arranged day, t he professor introduce d the PI and then left the room whil e the PI e xplained the questionnaire packet. The students were informed about the purpose and nature of the study and given the informed consent for m to complete. Participants were informed that they could withdrawal from the study and leave the classroom at any time without penalty. Students who were not eligible for participation (18 to 25 years old) w ere removed from the analysis, but still given the opportunity to complete the measures for extra credit purposes. Next each participant was given a manil a envelope that contained all measures and questionnaires Each pac ket took approximately 45 50 minutes to complete. Once the students complete d the questionnaire they return ed the
44 manila envelope to the PI Foll owing this, participants were given the cont act Measures Participants complete d several questionnaires to determine their specific experiences ( aggressor or victim ) with each bullying type (overt, relational, and cyber) in chi ldhood. In addition, they c omplete d several measures to assess their current psychosocial functioning in young adulthood along several domains. Finally, participants were asked to provide demographic information ( age, gender, ethnicity, and sexual orien tation). Bullying Experiences For purposes of this study, all measures that addres s specific experiences with bullying (Revised Peer Experiences Questionnaire, Cyber Aggression and Victimization Questionnaire, and the Relational Victimization Questionnair e) were revised to ask participants if they have ever experienced each form of victimization or aggression in childhood (5 to 18 years old) rather than in the past 30 days or in high school If individuals are asked to recall any bullying experience in chi ldhood with a broader time possible that the specific bullying memories recalled will be the experiences that were the most significant and salient and had the greatest em otional impact. In referencing the trauma literature on memory, researchers indicate that the greater significance an individual attributes to an experience at the time it occurs, the more likely it is to be ; Rothschild, 2000). In addition, research on autobiographical memories indicates that memories that are more likely to be recalled the most vividly are those that are associated with emotional events and
45 have a greater emotional charge for the individual (Christianson, 1992; Christianson & Loftus, 1990; Hamann, 2001; Rothschild, 2000). Following this, it is hypothesized that the bullying experiences that are recalled when individuals are asked to think about a broad time frame, will be the experiences that had the most emotional impact and This revision also allow s participants to reflect on a broader time range and focus on all childhood bullying experiences without li miting participants experience to a spe cific time period. Although most of the bullying literature suggests that bullying occurs at higher rates in adolescence (Finkelhor, Turner, Ormrod, Hamby, & Kracke, 2009; Nansel et al., 2001; Ross, 1996), there is ot her research that indicates that this rate may change based on bullying type. For example, Crick (1996) found that reported relational aggression rates were just as prevalent in girls across 3 rd to 6 th gr ade Based on the differing findings in the bullying literature, it is possible that each bullying type may have been experienced during differing age ranges for participants Because this current study investigated all bullying types, it is important to not just focus on a particular time period. Specifica lly because cyberbullying is a relatively new field, it is likely that specific cyberbullying experiences could have occurred at an older age for participants, where as overt or relational bullying experiences could have occurred at a younger age. The rev ision to the measures ensure d that there were not any time range restrictions and participants were prompted to report each bullying ty pe. The measures will be described in detail in the sections below. Revised p eer e xperiences q uestionnaire The Revised P eer Experiences Questionnaire (RPEQ) is a revision of the Peer Experience Questionnaire (PEQ; Vernberg, Jacobs, & Hershberger, 1999) that
46 measures the frequency of engaging in or being a victim of overt and/or relational aggression (Prinstein V ernberg, & Boergers, 2001). The measure has been shown to have a stable four factor structure for each of these domains (relational aggression, overt aggression, relational victimization, and overt victimization). The RPEQ is a self report measure consisting of 18 it ems that asks participants to rate the frequency in which they experienced each form of victimization or aggression on a scale of 1 (never) to 5 (a few times per week). The respon ses within each subscale were summed to obtain a score between 5 to 25 for re lational behaviors and 4 and 20 for overt behaviors. The RPEQ studies that have utilized the measure to examine the rates of adolescent aggression and victimization (Dempsey et al., 20 09; L a Greca & Harrison, 2005; Prinstein et al., 2001) Specific to validity, b oth discriminant and concurrent validity have been established. Dempsey and colleagues (2009) used factor analyses to establish the discriminant validity of the subscales and co ncurrent validity was established through comparisons of peer correlations with the RPEQ ( De Los Reyes & Prinstein, 2004) and parental and teacher correlations with the PEQ (Vernberg, Jacobs, & Hershberger, 1999). The reliability of the measure has been sh own through its internal consistency with s alphas in the adequate range for both the overt victimization scale ( = .71 .78) and the re lational victimization scale ( = .81 .84) ( De Los Reyes & Prinstein, 2004; Dempsey et al., 2 009; La Greca & Ha rrison, 2005) In the current study, the
47 Cyber a ggression and v ictimization q uestionnaire The RPE Q has since been revised to include cyber victimization and cyber aggression questions ( Dempsey, Sulkowski, Dempsey, & Storch, 2011 ; Dempsey, Sulkowski, Nichols, & Storch, 2009). The cyberbullying subscales, the Cyber Aggression and Victimization Questionn aire (CAV), of the Revised Peer Expe rience Questionnaire (RPEQ) were also administered to determine the recalled rates of cyber bullying type The cyberbullying scale contains an 8 item self report measure that addresses the freq uency in which respondents w ere either an aggressor and/ or victim for four cyber aggressive behaviors: (a) creation of a web page revealing embarrassing or hurtful information; (b) sending/receiving a text message, email, instant message, or web space posting containing mean or thre atening content; (c) using trickery to send a mean message from the victim's account; and (d) sending a message containing personal information to a large group of peers. For each question, participants indicate the frequency of being a cyber aggressor and /or cyber victim for each behavior on a rating scale that ranges from one (never) to five (a few times a week). For the purposes of this study, o ne of the cyber victimization questions was modified slightly to include a more comprehe nsive cyber victimizati on behavior. The statement was change d student sent me a text message or instant message that was mean or that threatened to others or me a text message or instant message about me that The cyber agg ression question was to be modified as
48 Several studies have established the reliability and validity of the CAV (Dempsey et al., 2009 ; Dempsey et al. 2011 ) Dempsey and colleagues (20 11 ) established both the convergent and discriminant validity of the CAV through an exploratory factor analysis of the measure. CAV items were found to correlate with both overt and relational victimization and aggression items (convergent validity) and a lso showed that the cyber aggression and victimization items were separate sub factors from the overt and relational aggression and victimization items (discriminant validity). In addition, previous analyses using the internal c onsistency indicate that the reliabilities of the cyber victimization subscale ( = .74) and the cyber aggression subscale ( = .85) are adequate (Dempsey et al., 2009; Dempsey et al., 2011). In the curr adequate for the c yber but not In addition, C t relational, and cyber items Relation al v ictimization q uestionnaire T o gain a more accurate assessment of the rate of relational aggression and victimization among the sample, an adapted version of the Relational Victim ization Questionnaire (RVQ) was administered (Dempsey & Storch, 2009). Th e RVQ is a 7 item, self report measure that examines the recalled frequency of being a victim of relational aggression through direct and indirect behaviors. The RVQ is more comprehensive in that it does not solely focus on exclusion behavior, but also ack nowledges the other forms of relational aggression (e.g. spreading rumors, pressuring students through threats to their social status, and spreading personal
49 information) cited in the literature (Crick, 1996; Crick & Grotpeter, 1995; Tomada & Schneider, 19 97 ; Ttofi, Farrington, & Baldry, 2010 ). Dempsey and Storch (2009) conducted a n exploratory factor analysis of the psychometric properties of the scale and = .79) and support for the co nvergent validity of the measure through its relationship with other measures that assess psychological distress (e.g. B Inventory). In addition recalled frequency of being a victim of relational aggress ion the questionnaire was frequency of being a perpetrator of relationally aggress ive behavior as defined by the seven behavior statements. Th e statements were revised to ask participants to respond to the statemen often did The current study found adequate for the RVQ ( = .86 ) and the adapted questionnaire to assess frequency of engaging in relationally aggressive behavior ( = .81). Psychosocial Functioning For the purposes of this study, one broad and several narrow measures were chosen to assess participant s current psychosocial functioning. The broad me asure that was chosen, The Behavior Assessment System for Children, Second Edition, Self Report of Personality, College Version (BASC 2 SRP CV) provides a comprehensive assessment of various social and emotional constructs and addresses many of the psycho social areas that the literature has identified as being associated with experiences of bullying, specifically self esteem (Juvonen et al., 2000) depression
50 (Bauman & Summers, 2009 ; Dempsey et al., 2009; Storch et al., 2003b) anger and associated conduct problems (Prinstein et al. 2001; Sourander et al., 2007; Stein et al., 2007) school problems (Juvonen et al., 2000; Stein et al., 2007; Swearer, et al. 2010) and anxiety or difficulties with social interactions (Storch et al., 2005) The narrow measures that were chosen, the UCLA Loneliness Scale, Version 2 (UCLA LS) and the Brief Fear of Negative Evaluation (B FNE) have been utilized in previous studies that have assessed psychosocial outcomes of bullying, specifically social anxiety and loneliness (De mpsey & Storch, 2009; Prinstein et al., 2001) These two measures were chosen, not only because of their previous use, but because symptoms of social anxiety and loneliness are two areas that have been consistently identifie d in the bullying literature to be associated with bullying (Bond et al., 2001; Dempsey et al., 2009; Hawker & Boulton, 2000; Juvonen et al. 2003; Prinstein et al., 2001) and these additional narrow measures provide d a more comprehensive assessment of these symptoms then what is assesse d with the BASC 2 SRP CV These measures will be discussed in more detail in the following sections Behavior a ssessment s ystem for c hildren, s econd e dition, s elf r eport c ollege f orm (BASC 2, SRP COL) The Behavior Assessment System for Children, Second E dition, Self Report of Personality, College Version (BASC 2 SRP CV ) (Reynolds & Kamphaus, 2004) is designed to facilitate the differential diagnosis and educational classification of various emotional and behavioral disorders in young adults aged 18 to 25 years old. The BASC 2 SRP COL is a 185 item, self report measure of psychopathology and personality that takes approximately 20 30 minutes to complete The first half of the norm referenced measure contains a True and False response format and the second h alf contains a
51 four point likert type rating response scale (ranging from never to almost always ) The inventory is designed to quantify self report ratings of college students across psychological, social, and emotional factors (Hardy, Rock inson Szapkiw, West, Phillips, & Hood, 2010; Nowinski, Furlong, Rahban, & Smith, 2007; Reynolds & Kamphaus, 2004). The measure contains 16 primary scales ( Alcohol, Anxiety, Attention, Atypicality, Depression, Hyperactivity, Interpersonal Relations, Locus of Control, Rela tions with Parents, School Adjustment, Self Esteem, Self Reliance, Sensation Seeking, Sense of Inadequacy, Social Stress, and Somatization) 4 content scales (Anger Control, Ego Strength, Mania, and Test Anxiety) and 4 global or composite scores (Emotiona l Symptoms Index, Inattention/Hyperactivity, Internalizing Problems, and Personal Adjustment) Based on the initial norming of the measure, Reynolds and Kamphaus (2004) indicate that the measure is valid and reliable. The reliability of the system, as mea sured by the internal consistency of the measure and is in the adequate range ( = .80 .90). Furthermore the test retest reliability was also found to be in the adequate range (r = .74 .99). Specific to validity, co variance struc ture analyses indicated that each scale and its related composite s core are moderately correlated with each other, indicating that they are measuring a common dimension (ranging from r = .54 .98) (Reynolds & Kamphaus, 2004). The concurrent validity of the measure in comparison to other behavioral rating systems (e.g. BDI, Achenbach System of Empirically Based Assesment Young Adults Form, Brief Symptom Inventory, and Minnesota Multiphasic Personality Inventory 2) has also been established ( Nowinski et al., 2007 ).
52 For the purposes of this study, several scales were targeted to assess specific areas found to be associated with bullying in the literature. Within the primary scales, particular attention was Depression, School Adjustment, Self Esteem, Sensation Seeking, Sense of Inadequacy, and Social Stress scales. In addition, the composite scale s of Inattention/Hyperactivity and Internalizing Problems were analyzed. UCLA l oneliness s cale ( v ersion 3) In or der to assess participants feelings of loneliness t he UCLA Loneliness Scale, Version 2 (UCLA LS) was administered. The UCLA LS is a 20 question self report by the scale, is the difference between actual social contact and desired social contact. The scale asks participants to rank statements associated with how often they feel the various feelings and emotions that are related to the experience of loneliness on a scale fr om 1 (never) to 4 (always). Thi s results in a total score (ranging from 20 to 80 ), with a higher score indicating a higher frequency of loneliness Russell (1996) conducted several psychometric analyses that indicated the measure provides a reliable and va lid measure of loneliness. These analyses indicated a dequate reliability related to internal consistency ( = .89 .94 ) and test retest reliability over a 1 year period (r = .73). In relation to validity, convergent validity of the measure was established through correlations (r = .65 .72) with other measures of loneliness (NYU Loneliness Scale and Differential Loneliness Scale) and construct validity was established with other similar constructs (e.g. depression and self esteem) and measures of health an d well being.
53 Brief f ear of n egative e valuat ion T he Brief Fear of Negative Evaluation ( B FNE ) was administered (Leary, 1983). The Brief Fear of Negative Evaluation is a 12 question self report or fear about being negatively evaluated by others, a core characteristic associated with social anxiety. The scale was adapted from the Fear of Negative Evaluation Scale a 30 item scale (Watson & Friend, 1969). The scale asks respondents to rate various statement s associated with concerns or worries about negative evaluation on a scale from 1 (not at all characteristic of me) to 5 (extremely characteristic of me). These ratings are then summed to yield a total score (rang ing from 12 to 60), with a higher score indicating increased fear of negative evaluation. Research studies (Collins, Westra, Dozois, & Stewart, 2004; Leary, 1983) have indicated that the scale has adequate reliability and validity. Collins and colleagues ( 2004) conducted a factor analysis of the scale and found support for the construct validity of the scale and concurrent validity of the scale based on correlations with other similar scales ( e.g. social avoidance discriminant validity was verified through significant differentiations with other types of psychological adjustment (social phobia and panic disorder). In relation to reliability, analyses (Collins et al., 2004; Duke, Krishnan, Faith, & Storch, 2006; Lear y, 19 83) have indicated the scale has adequate internal consistency ( = .90 .94 ) and test re test reliability (r = .75 .94). The research question of the proposed study is as follows: What is the relationship between recalled type of bullying experienced i n childhood (overt, relational, and cyber) and psychosocial functioning in young adulthood?
54 Table 2 1. Demographic i nformation of the e ntire s ample Variable Mean (SD) N % Gender Male 93 3 4 Female 184 66 Ethnicity White 18 8 68 Black 3 4 12 Hispanic 37 1 3 Asian 7 3 Other 10 4 Age 19.5 (1.57) 18 81 29 19 89 32 20 55 20 21 22 8 22 14 5 23 6 2 24 5 2 25 5 2 Sexual Orientation Heterosexual 259 94 Other (Bisexual, Homosexual, Asexual) 16 6 School University of Florida 151 5 5 Santa Fe College 126 4 5 Note. N = 277 Table 2 2. Breakdown of f ina ncial a id within p articipating s chools School N (%) Federal Grant Need Based Scholarships Loans Student Employment UF 151 (54) 70 (46) 60 (40) 72 (48) 43 (28) SF 126 (46) 63 (50) 23 (18) 69 (55) 25 (20)
55 CHAPTER 3 RESULTS The current study utilized quantitative methodology to evaluate the relationship between the recalled type of bullying experienced in childh ood and psychosocial functioning in young adulthood Participants completed several self report questionnaires to determine their specific experiences (aggressor or victim) with each bullying type (overt, relational, and cyber) in childhood. In addition, p articipants completed several measures to assess their current psychosocial functioning along several domains. Finally, participants were asked to provide demographic information (age, gender, ethnici ty, and sexual orientation). The primary goal of the cur rent study was to determine whether different types of bullying experiences were related to different psychosocial outcomes. That is, the study aimed to evaluate whether an experience with a specific type of bullying (e.g. cyber bullying) was more closely related to a specific type of psychosocial domain (e.g. anxiety) than another type of bullying. Chapter 3 will present the results of the study using qua ntitative analyses to evaluate the relationship between the recalled type of bullying experienced in childhood and psychosocial functioning in young adulthood Data analysis. Because wording modifications were made to the RPEQ with the cyber victimization scale and the RVQ was modified to address relational aggression, sev eral factor analyses were conducte d to determine the underlyin g dimensions of the domain s (e.g., overt victimization) within the scales. The RPEQ with the CAV scale and the RVQ with Aggression questions were appropriate for factor analysis because the individual items were rated on interva l scales and the sample size was adequate (greater than 100 participants and 5 times the number of items ) ( Suhr, 2006). For all of
56 the factor analyses, the principal component analysis utilized wa s the extraction method and Varimax with Kaiser Normalizati o n was the rotation method used. modified wording to the cyber victimization items formed a three factor structure with distinct overt victimization, relational victimization, and cy ber victimization items another factor analysi s was conducted. The Keyser Meyer Olkin Meas ure of Sampling Adequacy was .82 X 2 ( 78 ) = 1509.45 ; p < .001, indicating that the data were s uitable for factor analysis. From this analyses it was determined, that the proposed 3 facto r model was appropriate. Table 3 1 report s the individual item loadings for each factor (overt victimization, relational victimization, and cyber victimization). D there was no wording modifications to the cyber aggression question s within the CAV aggression scale however; a final factor analyses was still the RPEQ with the cyber aggression items formed a three factor structure with distinct overt aggression, relational aggression, and cyber aggression items. The Keyser Meyer Olkin Meas ure of Sampling Adequacy was .81 sphericity for the sample was significant ( X 2 (78) = 1263.127 ; p < .00 1, indicating that the data was suitable for factor analysis. From this analyses it was determined, that the proposed 3 factor model was appro priate. Table 3 2 reports the individual item loadings for each factor (overt aggression relational aggression, and cyber aggression ). The final exploratory factor analys i s that was conducted was to determine whether the modified RVQ with relational aggression items was distinct from the RVQ
57 victimization items. The exploratory factor analyses of the RVQ versus the RVQ with aggression questions helped identify whether the measure was appropriate for measuring the underlying structure of a domain of functioning (e.g. relational aggression and relational victimizati on) (Costello & Osborne, 2005). The Keyser Meyer Olkin sample was significant ( X 2 (91) = 1471.5; p < .001, indicating that the data were suitable for factor analysis. From this analyses it was determined, that the aggression and victimization questions did not overlap and the questions were grouped within t he appropriate scale. The item correlations between the individual RVQ victimization items are listed in Table 3 3, the correlations between the individual aggression items adapted from the RVQ are listed in Table 3 4 and the correlations between the individual aggression and victimization items from the RVQ are listed in Table 3 5. Table 3 6 reports the factor coefficien ts of the individual aggression and victimization items within the first factor. Mean Group Differences in Type of Bullying Experienced Overall, there were eight student self report variables from the bullying questionnaires: overt victimization (OV), over t aggression (OA), relational aggression (RA ) which is calculated from the revised aggression items from the RVQ relational victimization (RV ) which is calculated from the victimization items from the RVQ, cyber victimization (CV), cyber aggression (CA), total victimization ( T Vic ) which is calculated from the victimization items from the RPEQ/CAV, and total aggression ( T Agg ) which is calculated from the aggression items from the RPEQ/CAV. In order to determine whether there were any mean group differences (gender, ethnicity, and sexuality) in the reported rate of bullying types, a three way 8 (OV, RV, CV, TVic, OA, RA, CA, TAgg ) x
58 9 (Gender: male/female; Ethnicity: White, Black, Hispan ic, Asian, Other; and Sexuality: heterosexual/minority) multivariate ana lyses of variance (MANOVA) was conducted. This provided insight into whether the severity or frequency of bullying type based on gende r, ethnicity, and/or sexuality wa s significant (Ott, 1993). Two of the variables, gender and sexuality, had to be dummy co ded. Sexual ity was divided into two groups: majority (heterosexual) and minority (bisexual, homosexual, and asexual) According to the observed covariance matrices of the dependent variables are not equal across groups. This model violates is robust to this violation and it was utilized to determine significance. In addition, ( p < .05) the observed variability in three of the bullying groups (relational victimization, cyber victimization, and overt aggression) may not be equal. Ther e were no significant interaction effects between any of the in dependent variables. A multivariate affect was found for gender, F ( 8, 252 ) = 3.20 Trace = .00 2. A multivariate effect was not found for sexuality F ( 8, 252 ) = .99, p = .448 or ethnicity F (32 255 ) = 1.22, p = .190 Table 3 7 displays the gender differenc es in the means scores and standard deviations for each bullying type, Table 3 8 displays the mean scores and standard deviations for each bullying type in relation to sexual orientation, and Table 3 9 displays the means and standard deviations of each bul lying type in relation to ethnicity (White, B lack, Hispanic, Asian, and other) in relation to each bullying type.
59 Victimization As noted in Table 3 7 t here were no s ign ificant gender differences found in the report of overt victimization F ( 1 259 ) = 3 .6 7, p = .057 or relational victimization, F ( 1, 259 ) = .53, p = .465 However, s ignificant gender differences were found in the reports of cyber victimization F ( 1, 259 ) = 6.61, p < .05 F emales (M = 5.20, SD = 1.91) report ed higher rates of cyber victimi zation than males (M = 4.76, SD = 1.35). Finally, there were no significant gender differences found in the total victimization score F ( 1 259 ) = .34, p = .56 2 In Table 3 8, a lthough there was not a multivariate effect f ound for sexuality, there was tren d level significant main effect found in the reported rate of relational victimization based on sexuality, F (1, 259) = 4.1 5 p < .05. Those participant s who indicated other (bisexual, homosexual, and/or transgender) as their sexual orientation were found t o report higher rates of relational victimization (M = 17.56, SD = 6.64) than heterosexual participants (M = 13.44, SD = 4.56). Aggression Specific to involvement as a perpetrator of overt aggression (Tabl e 3 7 ) there were s ignificant gend er differences found, F ( 1 259 ) = 7.06, p < .01. M ales (M = 6.61, SD = 2.51) report ed a higher rate of involvement as a perpetrator of overt aggression than females (M = 4.82, SD = 1.46) There were no s ig nificant gender differences found in the reported rate of being a perpetrator of relational aggression F (1, 259) = 3.23 p = .07 3 or a perpetrator of cyber aggression F (1 259 ) = .15, p = .696 Finally, there were no significant gender differences found in the total aggression score F ( 1 259 ) = 1.57, p = .21 1
60 Pr evalence of Bullying Types In order to determine the amount of participants who had reported experiencing a specific bullying type at least once in childhood, the frequencies of each bullying type ent as a victim or perpetrator in any of the bullying behaviors was examined. Table 3 10 displays the frequency of participants who indicated that they experienced each bullying type at least once in childhood as well as their current involvement as a vict im or perpetrator in any of the bullying behaviors. Victimization In Table 3 10 72% (N = 199) of the participants in the sample indicated that they had been victims of overt aggression at least one time in childhood. Specific to relational victimization, 92 % (N = 255) of the participants in the sample indicated that they had been victims of relational aggression at least one time in childhood. In relation to cyber victimization, 43% (N = 119) of the participants in the sample indicated that they had been victims of cyber aggression at least one time in childhood. Finally, when asked about current experiences with being victims of overt, relational, and /or cyber bullying behaviors, 9 % (N= 24) of participants indicated that they were current victims of bully ing. Aggression In Table 3 10 52% (N=144) of the participants in the sample indicated that they had been perpetrators of overt aggression at least one time in childhood. Specif ic to relational aggression, 86 % (N = 237) of the participants in the sample indicated that they had been perpetrators of relational aggression at least one time in childhood. In r elation to cyber aggression, 24 % (N = 66) of the participants in the sample indicated
61 that they had been perpetrators of cyber aggression at least once i n childhood. Finally, when asked about their current experiences with being perpetrators of overt, relational, and /or cyber bullying behaviors, 9 % (N= 26) of participants indicated that they were current aggressors of bullying. It is important to note that out of the sample, only 1% (N = 3) of the participants indicated that they were not involved in any type of bullying in childhood, either as an aggressor or a victim. Regression Analyses Following these preliminary analyses, multiple regression analyses w ere conducted to examine the relationship between each bullying type and psychosocial functioning. Specifically, the relationship between each of the independent variables ( cyber victim ization, relational victimization, overt victimization total victimiza tion, cyber aggression, relational aggression overt aggression, and total aggression ) with respect to each of the 12 dependent variables ( social anxiety, loneliness, alcohol use, anxiety, depression, school adjustment, level of self esteem, sensation seek ing, sense of inadequacy, social stress, inattention/hyperactivity and internalizing problems ) was examined. Prior to these analyses, it was determined that all the assumptions (independence, linearity, equality of variances, and normality) required t o co nduct regression analyses were met. In addition, the correlations between each of the independent variables were analyzed to ensure that they were not dependent on one an other and that multicollinearity did not exist ( Ott, 1993 ). Twenty four separate analy ses were conducted, two f or each psychosocial construct, one with the full model and one with the reduced model (only demographic variables ) The full model contained all of the bullying variables (OV, RV, CV, TV, OA, RA, CA, and TA) as well as the
62 demogra phic variables (gend er, sexuality, and ethnicity). Once again, two of the demographic variables, gender and sexuality, were dummy coded. Sexuality was divided in to two groups: majority (heterosexual) and minority (bisexual, homosexual lesbian or gay, and asexual). The reduced model contained only the demographic variables. In the regression analyses the ethnicity category of was deleted from the analysis because it was constant or contained missing correlations. Table 3 11 presents the mean scores and standard deviation s for the whole sample in relation to each of the psychosocial outcome variables Correlations between the bullying variables are presented in Table 3 12 correlations between the psychosocial variables are presented in Table 3 13 an d correlations between the bullying variable and psychosocial variables are presented in Table 3 14 Loneliness In the full model with l oneliness as the dependent variable, the variables accounted for 15 % of the tot al variance, F (14, 264) = 3.15 p < .01 Similar to what was hypothesized, i ncreased recall of relational victimization was related to current experience of loneliness (p < .05). In addition, Black participants were negatively related to higher rates of loneliness (p< .05), meaning Black partic ipants reported a significantly lower average loneliness score than that of participants of other ethnicities. In the reduced model, the control variables were non significant F (6, 264) = 1.9 8 p = .070 and accounted for 4.4 % of the total variance. Thus, 10.6 % of the total variance in loneliness is associated with recalled relational victimization. Summaries of the regression a nalyses are presented in Table 3 15
63 Fear of negative e valuation To predict fear of negative evaluation, the variable s in the fu ll model accounted for 25.1 % of the total variance, F (14, 264) = 5.97 p < .01. Once again, as what was hypothesized, increased recall of relational victimization was positively related to greater reports of current fear of negative evaluation (p < .01). In addition, Hispanic participants were negatively related to higher rates of fear of negative evaluation (p< .05), indicating Hispanic participants reported a significantly lower average fear of negative evaluation score. In the reduced model, the control variables were non significant, F (6, 264) = 1. 91 p = .080 and accounted for 4.2 % of the total variance. Thus, 20.9 % of the total variance in curr ent fear of negative evaluation is associated with recalled relational victimization. Summaries of the regre ssion a nalyses are presented in Table 3 16 Social s tress In the full model with social stress as the dependent variable the variables accounted for 33.2 % of the tot al variance, F (14, 264) = 8.82 p < .01. Increased recall of relational victimization (p < .01) and higher reports of total victimization (p < .01) w ere positively related to higher rates of current social stress. This is congruent with what was expected regarding total victimization. It was hypothesized that those with higher total victimiza tion scores would report greater psychosocial difficulties. In addition, Hispanic participants were negatively related to social stress (p< .01), indicating Hispanic participants reported significantly less symptoms of social stress than that of participan ts of other ethnicities. In the reduced model, the control variables were non significan t, F (6, 262) = 0.57 p = .756 and accounted for 1.3% of the total variance. Therefore, 31.9 % of the total variance in current social stress is associated with the
64 bull ying variables (relational victimization and higher rates of total victimization). Summaries of the regression analyses are presented in Table 3 17 Anxiety In the full model with anxiety as the dependent variable the variables accounted for 20.9 % o f th e total variance, F (14, 262 ) = 4.67 p < .01. Specifically, recalled r elational victimization was positively related to current anxiety (p < .01). Unlike what was hypothesized, cyber victimization was not related to symptoms of anxiety. In the reduced mod e l the control variables were non significant, F (6, 262) = 1.20 p = .307 and accounted for 2.7 % o f the total variance. Thus, 18.2 % of the total variance in current anxiety is associated with recalled relational victimization experiences. Summaries of the regression a nalyses are presented in Table 3 18 Depression In the full model with depression as the dependent variable the variables accounted for 22.2 % of the tot al variance, F (14, 262) = 5.06 p < .01. In the full model, recalled experiences of over t v ictimization (p < .05), relational victimization (p < .01 ) and being a perpetrator of overt ly aggressive behaviors (p < .05) in childhood were all positively related to current symptoms of depression. Once again, unlike what was hypothesized, cyber vic timization was not related to symptoms of depression. In addition, White (p < .01) and Hispanic (p < .05) participants were negatively related to higher rates of depressive symptoms, indicating Hispanic and White participants reported significantly less s ymptoms of depression than that of participants of other ethnicities. In the reduced model, the control variables were non significant, F (6, 262) = 0.93 p = .474 and accoun ted for 2.1 % of the total variance. Although the variance in the reduced model w as non significant, White participants were negatively related (p =
65 .050) to depressive symptoms. Thus, 20.1 % of the total variance in depression is associated with the bullying variables (overt victimization, relational victimization, and overt aggression ). Summaries of the regression ana lyses are presented in Table 3 19 Sense of i nadequacy In the full model with sense of inadequacy as the dependent variable the variables did not predict a significant portion of the variance F (14, 26 2) = 1.32 p = .193 R^2 = .070 In the reduced model, the control variables were also non signi ficant, F (6, 262) = 0.41 p = .870 R^2 = .010. Summaries of the regression ana ly ses are presented in Table 3 20 Internalizing p roblems To predict Internalizing Problems, the v ariables in t he full model accounted for 30.8 % of the tot al variance, F (14, 262) = 7.89 p < .01. In the full model, recalled experiences of relation al victimization (p < .01) and being a perpetrator of overt ly aggressive behaviors (p < .05) in childhood were all positively related to current symptoms of depression. In addition, White (p < .01 5), Black (p < .05) and Hispanic (p < .05) parti cipants were negatively related to Internalizing Problems indicating these participants reported significantly less symptoms associated with Internalizing Problems than that of participants of other ethnicities. In the reduced model, the control variables were no n significant, F (6, 262) = 0.44 p = .855 and accounted for 1.0 % of the total variance Thus, 29.8 % of the t otal variance in Internalizing Problems is associated with the bullying variables ( relational victimization and being a perpetrator of overt aggression). Summaries of the regression ana lyses are presented in Table 3 21
66 Inattention/Hyperactivity To predic t Inattention/Hyperactivity, the variables in the full model accounted for 11 % of the tot al variance, F (14, 262) = 2.20 p < .01. Specifically, recalled involvement as the perpetrator in overtly aggressive behaviors was related to current symptoms of Inat tention/Hyperactivity (p < .05). In addition, Black participants were negatively related to higher rates of Ina ttention/Hyperactivity (p< .05), indicating Black participants reported significantly less symptoms of Inattention/Hyperactivity than that of par ticipants of other ethnicities. In the reduced model, the control variables were non significant, F (6, 262) = 1.00 p = .425 and accounted for 2.3 % of the total varia nce. Thus, 8.7 % of the total variance in Inattention/Hyperactivity is associated with recalled involvement in overt aggression. Summaries of the regression a nalyses are presented in Table 3 22 Sensation s eeking In the full model with sensation seeking as the dependent variable, the variables i n the full model accounted for 11 .8 % of the t ot al variance, F (14, 262) = 2.38 p < .01. Specifically, recalled cyber victimization (p < .01) and being a perpetrator of overt aggression (p < .05) were positively related to current involvement in sensation seeking behaviors and higher rates of total v ictimization (p < .05) were negatively related to sensation seeking behaviors This is congruent with the hypothesis that perpetrators of overt ly aggressive behaviors would report greater difficulties on those constructs that measure externalizing and risk taking behaviors. In the reduced model, the control variables were no n significant, F (6, 262) = 0.59 p = .736 and accounted for 1.4 % of the total variance indicating that the demographic variables do not help predict the response Thus, 10.4 % of the tot al variance in sensation seeking is associated with the
67 bullying variables (cyber victimization, total victimization, and overt aggression). Summaries of the regression a nalyses are presented in Table 3 23 Alcohol a buse In the full model with alcohol abu se as the dependent variable, the variables did not predict a significant portion of the variance, F (14, 26 2) = 1.67 p = .063, R^2 = .086 In the reduced model, the control variables were also non significant F (6, 262) = 1.99 p = .067, R^2 = .045 Sum maries of the regression ana lyses are presented in Table 3 24 School m aladjustment In the full model with school maladjustment as the dependent variable, the variables in the full model did not predict a significant portion of t he variance, F (14, 262) = 1.66 p = 064, R^2 = .086 Although the variance was non significant, recalled involvement as a perpetrator of overt aggression (p < .01) and a perpetrator of relational aggression ( p < .01 ) were both positively related to current school maladjustment I n addition, higher rates of total aggression (p < .01) were negatively related to current school maladjustment. T h e findings regarding relational aggression and overt aggression are consistent with what was expected In the reduced model, the control varia bles were non significant, F (6, 262) = 0.52 p = .794 and accounted for 1 .2% of the total variance indicating that the demographic variables do not help predict the response Thus, 7 .4 % of the total variance in school maladjustment is associated with reca lled bullying experiences (overt aggression relational aggression, and total aggression ). Summaries of the regression anal yses are presented in Table 3 25
68 Self Esteem To predict self esteem, the variables i n t he full model accounted for 16.3 % of the tot al variance, F (14, 262) = 3.4 4 p < .01. Specifically, recalled relational victimization (p < .05) was negatively related to self esteem and higher rates of total aggression (p < .05) w ere positively related to self esteem In the reduced model, the contr ol variables accounted for 5.7 % of the total variance in self esteem, F (6, 262) = 2.58, p < .05. Specifically, sexual orientation was a significant predictor of se lf esteem (p < .05). Thus, 10.6 % of the total variance in self esteem is associated with th e bullying variables (relational victimization and total aggression) Summaries of the regression a nalyses are presented in Table 3 26
69 Ta ble 3 1. Individual item loadings for the three factor model of the victimization s cale Item Factor 1: Overt V ictimization (OV) Factor 2: Relational Victimization (RV) Factor 3: Cyber Victimization (CV) OV1 0.818 OV2 0.787 OV3 0.745 OV4 0.741 RV1 0.853 RV2 0.845 RV3 0.823 RV4 0.788 RV5 0.667 CV1 0.851 CV2 0.759 CV3 0.682 CV4 0.582 Table 3 2. Individual item loadings for the 3 three factor model of the aggression s cale Item Factor 1: Overt Aggression (OA) Factor 2: Relational Aggression (RA) Factor 3: Cyber Aggression (CA) OA1 0.819 OA2 0.786 OA3 0.780 OA4 0.755 RA1 0.865 RA2 0.834 RA3 0.830 RA4 0.779 RA5 0.756 CA1 0.757 CA2 0.736 CA3 0.712 CA4 0.486
70 Table 3 3. Correlat ion matrix of individual items on the relational victimization q uestionnaire Spread Rumors (RV1) Exclude (RV2) I gnore (RV3) Divulge Info (RV4) Cause Fights (RV5) Pick Last (RV6) Ridicule (RV7) RV1 1 0.536 0.453 0.494 0.498 0.481 0.471 RV2 1 0.738 0.440 0.382 0.590 0.498 RV3 1 0.417 0.361 0.501 0.444 RV4 1 0.392 0.424 0.415 RV5 1 0.449 0.409 RV6 1 0.567 RV7 1 Note. For specific item wordings for RV items, Dempsey & Storch (2008). RV = relational victimization item from RVQ Table 3 4. Correlation matrix of indivi dual aggression items from the relational victimization q uestionnaire Spread Rumors (RA1) Exclude (RA2) Ignore (RA3) Divulge Info (RA4) Cause Fights (RA5) Pick Last (RA6) Ridicule (RA7) RA1 1 0.474 0.425 0.512 0.328 0.224 0.348 RA2 1 0.629 0.402 0.342 0.418 0.412 RA3 1 0.351 0.291 0.369 0.403 RA4 1 0.257 0.235 0 .365 RA5 1 0.322 0.418 RA6 1 0.473 RA7 1 Note: RA = relationa l aggression item adapted from R elational Victimization Questionnaire
71 Table 3 5. Correlation matrix of individual aggression and victimization i tems from the relational victimization q uestionnaire Spread Rumors (RA1) Exclude (RA2) Ignore (RA3) Divulge Info (RA4) Cause Fights (RA5) Pick Last (RA6) Ridicule (RA7) RV1 0.299 0.216 0.224 0.199 0.103 0.121 0.153 RV2 0.209 0.168 0.179 0.112 0.016 0.043 0.132 RV3 0.238 0.189 0.271 0.135 0.070 0.092 0.179 RV4 0.243 0.212 0.256 0.334 0.133 0.050 0.209 RV5 0.118 0.138 0.266 0.025 0.191 0.162 0.205 RV6 0.111 0.112 0.126 0.036 0.117 0.104 0.163 RV7 0.178 0.101 0.209 0.068 0.085 0.057 0.275 Note: RA = relational agg ression item adapted from Relational Victimization Questionnaire; RV = relational victimization item from Relational Victimization Questionnaire Table 3 6. Factor coefficie nts of individual items on the relational v i ctimization q uestionnaire with victim ization and aggression items within first c omponent Item Factor Coefficient RV1 0.188 RV2 0.226 RV3 0.198 RV4 0.150 RV5 0.183 RV6 0.231 RV7 0.207 RA1 0.032 RA2 0.050 RA3 0.015 RA4 0.066 RA5 0.036 RA6 0.039 RA7 0.012 Note: RA = relational aggression item adapted from Relational Victimization Questionnaire; RV = relational victimization item from Relational Victimization Questionnaire
72 Table 3 7 Gender differences in mean scores on the bullying m easures Measure Males Mean (S D) Females Mean (SD) Total Mean (SD) F P (sig) RPEQ Overt Victimization Subscale 7.59 (2.61 ) 5.89 0 (2.17) 6.46 (2.46) 3.67 .0 57 RVQ Relational Victimization Scale 13.24 (4.36) 13.91 (4.98) 13.56 (4.79) 0.53 .4 65 RPEQ Cy ber Victimization Subscale 4.76 (1.35) 5.20 (1.91) 5.05 (1.75) 6.61 .01 1 RPEQ Total Victimization 22.88 (6.29) 22.30 (6.06) 22.50 (6.13) 0.34 .56 2 RPEQ Overt Aggression Subscale 6.61 (2.51) 4.82 (1.46) 5.42 (2.06) 7.06 .0 08 ** RVQ Relational Aggression Scale 11.63 (3.87) 10.57 (3.24) 10.92 (3.49) 3.23 .07 3 RPEQ Cyber Aggression Subscale 4.57 (1.25) 4.33 (.923) 4.41 (1.05) 0.15 696 RPEQ Total Aggression 19.91 (5.91) 17.90 (4.30) 18.58 (4.98) 1.57 21 1 *p <.05. **p <.01 Table 3 8 Differences in mean scores on the bullying measures in relation to sexual o rientation Measure Heterosexual Mean (SD) Other (Bisexual, Homosexual, Transgender) Mean (SD) F P (sig) RPEQ Overt Victimization S ubscale 6.36 (2.38) 8.19 (3.15) 0.79 .37 4 RVQ Relational Victimization Scale 13.44 (4.56) 17.56 (6.64) 4.15 .04 3 RPEQ Cyber Victimization Subscale 5.03 (1.70) 5.56 (2.48) 0.70 .4 05 RPEQ Total Victimization 22.22 (5.91) 27. 00 (7.95) 1.61 .2 05 RPEQ Overt Aggression Subscale 5.37 (2.01) 6.25 (2.62) 0.06 .80 2 RVQ Relational Aggression Scale 10.89 (3.50) 11.38 (3.42) 0.00 .97 6 RPEQ Cyber Aggression Subscale 4.40 (1.05) 4.56 (.964) 0.00 .96 2 RPEQ Total Aggression 18.56 (5.02) 18.88 (4.46) 1.01 .3 17 *p <.05. **p <.01
73 Table 3 9 Differences in mean scores on the bullying measures in relation to e thnicity Measure White Black Hispanic Asian Other F P (sig) RPEQ Overt Victimization Subscale 6.41 (2.46) 6.79 (2.61) 6.95 (2.59) 5.14 (1.46) 5.60 (1.51) 1.10 .3 57 RVQ Relational Victimization Scale 13.78 (4.87) 13.24 (5.68) 13.73 (3.65) 14.57 (5.74) 12.60 (3.47) 0.53 .7 15 RPEQ Cyber Victimization Subscale 5.19 (1.93) 4.33 (.817) 4.97 (1.32) 4.71 (.951) 5.50 (1.90) 0.30 .88 0 RPEQ Total Victimization 22.87 (6.11) 20.58 (6.41) 23.00 (5.96) 21.43 (6.95) 20.80 (5.28) 1.27 .28 1 RPEQ Overt Aggression Subscale 5.17 (1.76) 6.03 (2.28) 5.84 (2.10) 7.86 (5.3 4) 4.80 (.789) 0.73 .57 3 RVQ Relational Aggression Scale 10.75 (3.42) 10.94 (4.23) 11.46 (3.06) 13.43 (4.31) 10.40 (2.80) 0.86 .4 88 RPEQ Cyber Aggression Subscale 4.43 (1.08) 4.18 (1.13) 4.51 (.989) 4.57 (1.13) 4.20 (.632) 0.28 .8 89 To tal Aggression 18.46 (4.73) 18.67 (6.36) 18.95 (5.09) 20.00 (6.68) 18.10 (3.50) 0.35 .8 46 *p <.05. **p <.01
74 Table 3 10 Frequency of bullying types e xperienced Endorsing Victimization Endorsing Aggression Overt Relational Cyber Current Involvement Overt Relational Cyber Current Involvement Non Involved N (%) 199 (72) 255 (92) 119 (43) 24 (9) 144 (52) 237 (86) 66 (24) 26 (9) 3 (1) Table 3 11 Mean scores on psychosocial v ariables Variables Minimum Maxi mum Mean Standard Deviation Loneliness 31 65 52.33 4.72 Fear of Negative Evaluation 12 48 30.60 6.72 Social Stress 34 74 47.29 9.12 Anxiety 29 81 49.41 9.87 Depression 40 81 47.12 6.82 Sense of Inadequacy 35 79 47.12 8.02 Internalizing Problems 34 7 6 47.43 7.78 Inattention/Hyperactivity 30 84 48.60 9.52 Sensation Seeking 23 79 50.32 9.83 Alcohol Abuse 41 105 48.95 8.37 School Maladjustment 43 83 48.81 9.62 Self Esteem 21 64 52.83 8.15 Note. N = 265.
75 Table 3 12. Correlations between bullying variables OV RV CV TVic OA RA CA TAgg OV 1 .466** .317** .714** .534** .261** .185** .370** RV 1 .478** .767** .199** .399** .254** .337** CV 1 .607** .126* .277** .496** .316** TVic 1 .314** .399** .314** .428** OA 1 .451** .430 ** .721** RA 1 .466** .710** CA 1 .631** TAgg 1 Note. N = 269. OV = overt victimization; RV = relational victimization; CV = cyber victimization; TVic = total victimization; OA= overt aggression; RA = relational aggression; CA = cyber aggression; TAgg = total aggression *p <.05. **p <.01
76 Table 3 13 Correlations between psychosocial v ariables Variables 1 2 3 4 5 6 7 8 9 10 11 12 1. Loneliness 1 .402** .378** .345** .239** .147* .306** 0.088 0.064 0.107 .188** .192* 2. FNE .402** 1 .395** .514** .342** .241** .438** .190** 0.025 .158* .203** .398** 3. Social Stress .378** .395** 1 .588** .605** .459** .791** .344** 0.067 0.087 .406** .558** 4. Anxiety .345** .514** .588** 1 .502** .472** .774** .344** .138* .131* .404** .515** 5.Depression .239** .342** .605** .502** 1 .549** .789** .272** 0.003 .185** .441** .545** 6. Sense of Inad .147* .241** .459** .472** .549** 1 .709** .332** 0.016 .167** .557** .458** 7. Inter Prob .306** .438** .791** .774** .789** .709** 1 .463** 0.008 .176** .525** .618** 8. Inatt/ Hyper 0.088 .190** .344** .344** .272** .332** .463** 1 .270** .165** .404** .295** 9. Sens Seek 0.064 0.025 0.067 .138* 0.003 0.016 0.008 .270** 1 .305** 0.080 0.100 10. Alc Abuse 0.107 .158* 0.087 .131* .185** .167** .176** .165** .305** 1 0.112 .191** 11. Sch Malad .188** .203** .406** .404** .441** .557** .525** .404** 0.080 0.112 1 .365** 12. Self Esteem .192** .398** .558** .515** .545** .458** .618** .295** 0.100 .191* .365** 1 Note. N = 265 participants. FNE = fear of negative evaluation; Sense of Inad = sense of inadequacy; Inter Prob = internalizing problems composite scale; Inatt/Hyper = inattention hyperactivity composite scale; Sens Seek = sensation seeking; Al c Abuse = alcohol abuse; Sch Malad = school maladjustment *p <.05. **p <.01
77 Table 3 14 Correlations between bullying variables and psychosocial v ariables Variables OV RV CV Tvic OA RA CA Tagg Loneliness .125* .293** 0.112 .264** 0.065 .199** 0.081 .156* Fear Neg Ev .231** .446** .186** .402** 0.041 .209** 0.100 .140* Social Stress .394** .484** .211** .520** .171** .180** 0.087 .172** Anxiety .217** .398** .185** .350** 0.066 0.108 0.061 0.065 Depression .351** .344** .194** .340** .187** 0.054 0.067 0.080 Sense of Inad .158* .175** .146* .177** 0.062 0.027 0.074 0.039 Inter Prob .362** .475** .286** .452** .175** 0.115 0.112 .122* Inatt/Hyper .207** .203** .158** .246** .208** .159** 0.094 .182** Sens Seek 0.010 0.076 0.120 0.072 .162** 0.120 0.060 .133* Alc Abuse 0.052 0.073 .145* 0.061 0.077 0.104 .152* .156* Sch Malad 0.076 0.109 0.085 0.105 0.118 .156* 0.047 0.056 Self Esteem .195** .284** .175** .291** 0.082 0.047 0.108 0.031 Note. N = 265 participants. FNE = fear of negative e valuation; Sense of Inad = Sense of Inadequacy; Inter Prob = Internalizing Problems composite scale; Inatt/Hyper = Inattention Hyperactivity composite scale; Sens Seek = Sensation Seeking; Alc Abuse = Alcohol Abuse; Sch Malad = School Maladjustment; OV = o vert victimization; RV = relational victimization; CV = cyber victimization; TVic = total victimization; OA= overt aggression; RA = relational aggression; CA = cyber aggression; TAgg = total aggression *p <.05. **p <.01
78 Table 3 15 Regression analys es relating bullying types and d emograp hics to l oneliness Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 3.15 0.150 Overt Victimization 0.032 0.758 Relational Victimization 0.212 0.024* Cyber Victimization 0.120 0.145 Total Victimization 0.126 0.344 Overt Aggression 0.070 0.491 Relational Aggression 0.114 0.168 Cyber Aggression 0.014 0.858 Total Aggression 0.019 0.865 Gender 0.136 0.054 White 0.175 0.228 Black 0.282 0.015* Asian 0.136 0.075 His panic 0.135 0.249 Sexuality 0.009 0.882 Reduced Model 0.070 1.98 0.044 Gender 0.121 0.055 White 0.116 0.438 Black 0.232 0.051 Asian 0.085 0.271 Hispanic 0.074 0.538 Sexuality 0.038 0.536 0.106 Note. *p<.05. *p<.01.
79 Table 3 16 Reg ression analyses relating bullying types and demographics to fear of negative e valuation Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 5.97 0.251 Overt Victimization 0.017 0.860 Relational Vi ctimization 0.318 0.000** Cyber Victimization 0.119 0.123 Total Victimization 0.202 0.106 Overt Aggression 0.111 0.246 Relational Aggression 0.065 0.399 Cyber Aggression 0.067 0.369 Total Aggression 0.012 0.912 Gender 0.066 0.317 White 0.190 0.165 Black 0.209 0.055 Asian 0.010 0.884 Hispanic 0.228 0.039* Sexuality 0.039 0.498 Reduced Model 0.080 1.91 0.042 Gender 0.014 0.830 White 0.099 0.508 Black 0.178 0.134 Asian 0.068 0.381 Hispanic 0.1 47 0.224 Sexuality 0.111 0.074 0.209 Note. *p<.05. **p<.01.
80 Table 3 17 Regression analyses relating bullying types and demographics to social s tress Standardized Beta Coefficient P (sig) F R^2 Social Stress 0.000** 8.82 0.332 Overt Victimization 0.038 0.685 Relational Victimization 0.241 0.004** Cyber Victimization 0.143 0.052 Total Victimization 0.417 0.000** Overt Aggression 0.106 0.239 Relational Aggression 0.003 0.969 Cyber Aggression 0.050 0.483 Total Aggression 0.123 0.229 Gende r 0.010 0.878 White 0.241 0.062 Black 0.175 0.091 Asian 0.101 0.136 Hispanic 0.289 0.006** Sexuality 0.060 0.271 Reduced Model 0.756 0.57 0.013 Gender 0.027 0.677 White 0.124 0.414 Black 0.110 0.365 Asian 0.035 0.656 Hispanic 0.176 0.150 Sexuality 0.038 0.550 0.319 Note. *p<.05. **p<.01.
81 Table 3 18 Regression analyses relating bullying types and demographics to a nxiety Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 4.67 0.209 Overt Victimization 0.008 0.939 Relational Victimization 0.333 0.000** Cyber Victimization 0.057 0.477 Total Victimization 0.160 0.212 Overt Aggression 0.156 0.112 Relational Aggression 0.023 0.774 Cyber Aggression 0.051 0. 505 Total Aggression 0.204 0.067 Gender 0.045 0.504 White 0.116 0.405 Black 0.211 0.061 Asian 0.093 0.206 Hispanic 0.183 0.105 Sexuality 0.024 0.688 Reduced Model 0.307 1.20 0.027 Gender 0.060 0.346 White 0.033 0.827 Black 0.152 0.206 Asian 0.023 0.764 Hispanic 0.097 0.424 Sexuality 0.063 0.317 0.182 Note. *p<.05. **p<.01.
82 Table 3 19 Regression analyses relating bullying types and demographics to d epression Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 5.06 0.222 Overt Victimization 0.201 0.046* Relational Victimization 0.264 0.004** Cyber Victimization 0.027 0.730 Total Victimization 0.036 0.775 Overt Aggression 0.201 0.039* Relational Agg ression 0.062 0.437 Cyber Aggression 0.059 0.437 Total Aggression 0.187 0.090 Gender 0.050 0.456 White 0.368 0.008** Black 0.216 0.053 Asian 0.098 0.182 Hispanic 0.228 0.041* Sexuality 0.054 0.357 Reduced Model 0.474 0.9 3 0.021 Gender 0.010 0.882 White 0.299 0.050* Black 0.148 0.219 Asian 0.066 0.404 Hispanic 0.150 0.219 Sexuality 0.027 0.672 0.201 Note. *p<.05. **p<.01.
83 Table 3 20 Regression analyses relating bullying t yp es and demographics to sense of i nadequacy Standardized Beta Coefficient P (sig) F R^2 Full Model 0.193 1.32 0.070 Overt Victimization 0.112 0.308 Relational Victimization 0.132 0.179 Cyber Victimization 0.053 0.543 Total Victimization 0.008 0. 957 Overt Aggression 0.070 0.510 Relational Aggression 0.036 0.678 Cyber Aggression 0.081 0.332 Total Aggression 0.106 0.379 Gender 0.038 0.606 White 0.241 0.113 Black 0.160 0.188 Asian 0.056 0.149 Hispanic 0.167 0.173 S exuality 0.083 0.199 Reduced Model 0.870 0.41 0.010 Gender 0.020 0.755 White 0.205 0.180 Black 0.139 0.252 Asian 0.044 0.580 Hispanic 0.127 0.298 Sexuality 0.038 0.553 0.060 Note. *p<.05. **p<.01.
84 Tab le 3 21 Regression analyses relating bullying types and d emographics to I nternalizing p roblems Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 7.89 0.308 Overt Victimization 0.088 0.354 Relational Victimization 0.364 0.000** Cyb er Victimization 0.045 0.545 Total Victimization 0.138 0.249 Overt Aggression 0.215 0.019* Relational Aggression 0.044 0.556 Cyber Aggression 0.063 0.378 Total Aggression 0.203 0.051 Gender 0.026 0.687 White 0.296 0.024* Black 0 .217 0.040* Asian 0.115 0.096 Hispanic 0.249 0.019* Sexuality 0.066 0.232 Reduced Model 0.855 0.44 0.010 Gender 0.013 0.837 White 0.208 0.174 Black 0.156 0.197 Asian 0.054 0.498 Hispanic 0.154 0.207 Sexuality 0.043 0.4 94 0.298 Note. *p<.05. **p<.01.
85 Table 3 22 Regression analyses relating bullying types and demographics to inattention/h yperactivity Standardized Beta Coefficient P (sig) F R^2 Full Model 0.008** 2.20 0.110 Overt Victimization 0.007 0.945 Relational Victimization 0.069 0.470 Cyber Victimization 0.047 0.581 Total Victimization 0.106 0.435 Overt Aggression 0.222 0.033* Relational Aggression 0.053 0.532 Cyber Aggression 0.038 0.641 Total Aggression 0.048 0.68 4 Gender 0.018 0.801 White 0.190 0.200 Black 0.252 0.035* Asian 0.062 0.425 Hispanic 0.182 0.127 Sexuality 0.018 0.773 Reduced Model 0.425 1.00 0.023 Gender 0.045 0.484 White 0.163 0.282 Black 0.216 0.074 Asian 0. 036 0.649 Hispanic 0.145 0.232 Sexuality 0.064 0.307 0.087 Note. *p<.05. **p<.01.
86 Table 3 23 Regression analyses relating bullying types and demographics to sensation s eeking Standardized Beta Coefficient P (sig) F R^2 Full Model 0.004** 2.38 0.118 Overt Victimization 0.006 0.959 Relational Victimization 0.047 0.210 Cyber Victimization 0.334 0.000** Total Victimization 0.306 0.024* Overt Aggression 0.208 0.045* Relational Aggression 0.127 0.135 Cy ber Aggression 0.140 0.086 Total Aggression 0.026 0.826 Gender 0.001 0.987 White 0.079 0.592 Black 0.028 0.811 Asian 0.024 0.754 Hispanic 0.109 0.357 Sexuality 0.025 0.685 Reduced Model 0.736 0.59 0.014 Gender 0.049 0.44 4 White 0.155 0.311 Black 0.054 0.658 Asian 0.042 0.592 Hispanic 0.166 0.174 Sexuality 0.023 0.713 0.104 Note. *p<.05. **p<.01.
87 Table 3 24 Regression analyses relating bullying types and demographics to a lcoh ol a buse Standardized Beta Coefficient P (sig) F R^2 Full Model 0.063 1.67 0.086 Overt Victimization 0.067 0.539 Relational Victimization 0.119 0.224 Cyber Victimization 0.143 0.094 Total Victimization 0.240 0.083 Overt Aggression 0.032 0.763 Relational Aggression 0.000 1.000 Cyber Aggression 0.021 0.803 Total Aggression 0.155 0.194 Gender 0.063 0.393 White 0.024 0.874 Black 0.140 0.247 Asian 0.080 0.304 Hispanic 0.065 0.592 Sexuality 0.067 0.289 Reduc ed Model 0.067 1.99 0.045 Gender 0.066 0.298 White 0.004 0.981 Black 0.154 0.197 Asian 0.094 0.227 Hispanic 0.086 0.475 Sexuality 0.076 0.226 0.041 Note. *p<.05. **p<.01.
88 Table 3 25 Regression analyses rel ating bullying types and demographics to school m aladjustment Standardized Beta Coefficient P (sig) F R^2 Full Model 0.064 1.66 0.086 Overt Victimization 0.022 0.837 Relational Victimization 0.042 0.667 Cyber Victimization 0.041 0.628 Tota l Victimization 0.039 0.778 Overt Aggression 0.304 0.004** Relational Aggression 0.240 0.006** Cyber Aggression 0.012 0.884 Total Aggression 0.320 0.008** Gender 0.120 0.103 White 0.208 0.167 Black 0.210 0.082 Asian 0.087 0.273 Hispanic 0.145 0.230 Sexuality 0.060 0.342 Reduced Model 0.794 0.52 0.012 Gender 0.055 0.388 White 0.185 0.225 Black 0.162 0.182 Asian 0.045 0.570 Hispanic 0.101 0.408 Sexuality 0.019 0.765 0.074 Note. *p<. 05. **p<.01.
89 Table 3 26 Regression analyses relating bullying types and demographics to self e steem Standardized Beta Coefficient P (sig) F R^2 Full Model 0.000** 3.44 0.163 Overt Victimization 0.044 0.672 Relational Victimization 0. 207 0.027* Cyber Victimization 0.031 0.701 Total Victimization 0.185 0.161 Overt Aggression 0.160 0.112 Relational Aggression 0.028 0.738 Cyber Aggression 0.123 0.122 Total Aggression 0.246 0.032* Gender 0.080 0.251 White 0.048 0.736 Black 0.207 0.074 Asian 0.031 0.679 Hispanic 0.102 0.380 Sexuality 0.059 0.330 Reduced Model 0.019* 2.58 0.057 Gender 0.063 0.313 White 0.021 0.887 Black 0.170 0.152 Asian 0.021 0.781 Hispanic 0.029 0.806 Sexuality 0.129 0.038* 0.106 Note. *p<.05. **p<.01.
90 CHAPTER 4 DISCUSSION Introduction Bullying is well recognized as an experience with negative and potentially adverse consequences. Research has consistently shown that involvement in bullying has been linke d to a wide range of psychosocial difficulties, behavior problems, and issues or dissatisfaction related to school (Bauman & Summers, 2009; Juvonen et al., 2000; Nansel et al., 2001; Stein et al., 2007; Swearer, et al. 2010). Despite the recognition of the dangers associated with bullying, incident rates continue to remain prevalent and bullying continues to evolve. There are three forms of bullying that have been identified. Overt bullying is what is typically thought of in the traditional sense of bullyin g and consists of physical and verbal bullying behaviors (Bauman, 2008; Prinstein, Boergers, & Vernberg, 2001). Relational bullying involves harming others through directed or purposeful manipulation and damage to their peer relationships (Crick & Grotpete r, 1995). As technology has developed, the most recently identified form of bullying has e merged cyberbullying. Cyberbullying entails posting or sending harmful or embarrassing text or images using the Internet or other digital communication devices (Fein berg & Robey, 2008; Patchin & Hinduja, 2006). There are several limitations within the bullying literature that need to be addressed in new studies on bullying. Although many studies have investigated the relationship between one specific type of bullying and one or two psychosocial constructs, there is limited research that has focused on all three bullying types in which each type of bullying is clearly defined ( Bauman, 2008; Griffin & Gross, 2004; Ireland & Ireland, 2003) From the definitions of each s pecific bullying type, it is apparent that each type of bullying is
91 distinguished from another. Therefore, it is possible that each bullying type may be associated with differing psychosocial outcomes. In addition, because of the differing elements to each bullying type, it is possible that a specific bullying type is associated with specific risk factors (e.g. age, gender, ethnicity, sexuality, etc.) and few studies have investigated these risk factors in relation to all types and roles in bullying Anothe r limitation in the bullying literature is that many studies have only investigated the outcomes for victims of bullying and not focused on all the various bullying roles (aggressor and victim). A final limitation in the bullying literature is that few stu dies have investigated the long term relationship between bullying and psychosocial functioning ( Jantzer, Hoover, and Narloch, 2006) Furthermore, the few studies (Demsey & Storch, Ledley et al., 2006) that have been conducted within the U.S. have followed children for a few years at most and have not investigated all of the identified bullying types. If research can identify how specific bullying types relate to specific outcomes, there will be a better understanding of the effects of bullying as a whole. This research can be used to inform practitioners of the various risk factors and psychosocial outcomes of each bullying type and be better able to make sound recommendations for bullying prevention and intervention efforts that are targeted to specific bu llying types. In addition, this research can help teachers, parents, and students to be aware of what each bullying type entails, the risk factors and consequences associated with each bullying type, and what steps may aid in prevention and intervention ef forts. The purpose of this study was to comprehensively examine the relationship between each specific bullying type identified in the research (overt, relational, and cyber) and long term psychosocial functioning. Specifically, the study aimed to evaluate whether
92 a recalled experience with a specific type of bullying and role (e.g. cyber victim, cyber aggressor, etc.) in childhood was related to a specific type of psychosocial construct (e.g. anxiety) in young adulthood. In addition, this study investigate d whether specific bullying types were more prevalent among specific populations ( e.g. based on gender, sexual identity, and ethnicity). Chapter 4 will highlight the key findings of this study and discuss how these findings relate to or differentiate from the existing bullying literature and how they can be applied to future bullying prevention and intervention efforts. In addition, the limitations of the current study will be reviewed and directions for future research will be emphasized. Summary and Impli cations of Key Findings The main goal of this study was to determine the relationship between the recalled types of bullying experienced in childhood and psychosocial functioning in young adulthood. Many studies have investigated the effect that bullying h as had on children, but very few studies have comprehensively measured and defined everything that ether or not this statement is true, it highlights that experiencing a certain type of bullying (e.g. being punched by a peer vs. discovering a rumor about you posted on facebook) is likely to have differing long term implications and effects on a child. T herefore, it is important that research examine all three types of bullying in order to gain a better understanding of what children may have experienced, how to intervene, and how to prevent these experiences from happening again. For the purposes of disc ussing the keys findings of the present study, the results will be grouped by bullying type.
93 Overt Bullying Overt a ggression Specific to overt aggression, the current study found that recalled involvement as the perpetrator in overtly aggressive behaviors was related to current symptoms of Internalizing Problems, Inattention/Hyperactivity, sensation seeking, depression, and school maladjustment. The findings regarding sensation seeking, school maladjustment, and Inattention/Hyperactivity are consistent wit h what was hypothesized. The behaviors associated with sensation seeking as described on the BASC 2 entail taking risks and BASC 2 the behaviors associated with school maladjustment are described as disliking and wanting to quit attending school or feeling overwhelmed and pressured in school. These behaviors are consistent with what would be expected of an individual who engages in overtly aggressive behaviors. In addit ion, the impulsive and hyperactive symptoms or behaviors associated with the Inattention/Hyperactivity composite score are also consistent with the expected behavior of an individual who engages in overtly aggressive behavior and is not able to control his or her anger. Previous studies have supported these findings and indicated that aggressors are more likely to engage in risky behaviors (Sourander, 2007) and are at a higher risk for truancy issues and dropping out of school (Nansel et al., 2001, Stein et al., 2007; Swearer et al., 2010). The findings that indicate that recalled involvement as the perpetrator in overtly aggressive behaviors was related to current symptoms of Internalizing Problems and depression were not what was specifically hypothesized, however; these results are not surprising given previous research. First, according to the psychopathology literature, childhood depression and externalizing disorders are frequently comorbid, although the
94 exact developmental sequence is debated (Ezpeleta Domenech, & Angold, 2006; Weitmann, 2006). In addition, childhood depression often presents itself externally (Weitmann, 2006). Second, it is possible that the participants in this current study who identified as overt aggressors also identified as a vi ctim in one of three bullying types, making these individuals a bully victim. The literature does indicate that bully victims report more serious psychosocial problems than those individuals who identify solely as the bully or solely as the victim (Kumpula inen et al., 1998; Stein et al., 2007). Specifically, another study found that bully victims and victims have the highest reported depressive symptoms (Espelage & Holt, 2007). Overt v ictimization The results of the current study found that recalled involv ement of being a victim of overt aggression was related to symptoms of depression in young adulthood. This is consistent with what was hypothesized and is supported by the existing literature that has found that overt victimization is related to symptoms o f depression (Bauman & Summers, 2009; Storch, 2003b). However, this finding expands upon the literature because it examined the long term relationship between overt victimization and depression. Relational Bullying Relational a ggression As was expected, r ecalled involvement of being a perpetrator of relational aggression was related to school maladjustment. Previous research indicates that aggressors are more likely to have a negative attitude toward school and are at a higher risk for truancy issues and d ropping out of school (Nansel et al., 2001, Stein et al., 2007; Swearer et al., 2010). Once again, this finding contributes to the literature because it identifies a specific type of bullying aggression, relational aggression, as being related to long term school
95 maladjustment. This finding highlight s the need for bullying prevention and intervention efforts to be comprehensive and address relational bullying as well. Relational v ictimization Of all the bullying types investigated, recalled experiences with being a victim of relational aggression was associated with the most psychosocial constructs that this study measured. The present study found that relational victimization was related to loneliness, fear of negative evaluation, social stress, anxiety, de pression, low self esteem, and internalizing problems. These results are not surprising for several reasons. First, many of the psychosocial variables that were related to relational victimization overlap with one another. For example, fear of negative eva luation, social stress, and anxiety all address similar behaviors associated with anxiety or social anxiety. Items from the depression, self esteem, and anxiety scale both combine to form the internalizing problems score. Second, previous research has show n that relational victimization is associated with depression (Bauman & Summers, 2009 ; Dempsey & Storch, 2008; Storch et al., 2003b ), social phobia (Storch et al., 2005), and social anxiety (Dempsey & Storch 2008 ) and this is consistent with findings in t his study that indicated that being a victim of relational aggression is associated with loneliness, fear of negative evaluation, social stress, anxiety, depression, low self esteem, and internalizing problems. Given the multitude of long term psychosocial difficulties associated with relational victimization, it is evident that schools need to be more aware of the behaviors involved in relational bullying and take steps to inform parents, students, and teachers of what it looks like and what it may entail. In addition, using the RVQ with both the victimizati on and aggression questions a s a initial screener and progress monitoring tool may help to
96 identify what students ar e involved in relational bullying and who may need additional support. Cyber Bullying C yber v ictimization Despite previous findings that indicated that cyber victimization was weakly associated with symptoms of social anxiety (Dempsey et al., 2009), it was expected that cyber victimization would be associated with social anxiety and, in gen eral, more of the psychosocial difficulties in this current study than the other bullying victimization types. Cyber bullying can occur at any time and the information posted is available to everyone if it is on the Internet (Willard, 2007a). However, when examining the data in depth, it is apparent that a substantially greater amount of participants indicated that they experienced overt victimization (N = 157) and relational victimization (N = 243) more than once in childhood in comparison to those who ind icated that they had experienced cyber victimization more than once (N = 67). Given this, it is possible that other types of bullying victimizations were more recurrent in nature and may therefore resul t in greater psychosocial difficulties. It is also pos sible that given the age of this population (M = 19.5 years old), social networks (e.g., formspring, facebook, etc.) and other technology associated with cyber bullying are relatively new to this age group and the participants in this study did not have a s many opportunities for exposure to this type of bullying during their formative years of childhood. This present study did find that recalled involvement of being a victim of cyber aggression was related to sensation seeking in young adulthood. T he most recent cyber bullying literature hypothesizes that victims of cyberbullying may retaliate in school and have higher rates of school problems and referrals ( Hinduja & Patchin, 2008). It is
97 possible that being a victim of cyberbullying leads the victim to se nsation seeking behavior through means of retaliation. This finding highlights the need that specific efforts to prevent cyber bullying need to be made in schools and in homes. It is possible that being a victim of cyber bullying will just lead to retalia tion in the schools, and the cycle will continue. Total Aggression The results of the current study found that higher rates of involvement as a perpetrator of aggressive bullying behaviors were positively associated with self esteem and negatively associa ted with school maladjustment in young adulthood Specific to self esteem, this finding is consistent with more recent research ( Baumeister, Smart, & Boden, 2006) that indicates that aggressors have high self esteem, are extremely confident, and feel a sen se of entitlement to push others around if this self concept is threatened. The finding regarding the negative relationship between higher aggression scores and school maladjustment was unex pected based on the previous research (Nansel et al., 2001, Stein et al., 2007; Swearer et al., 2010) that indicates that aggressors are more likely to have a negative attitude toward school and are at a higher risk for truancy issues and dropping out of school However, w hen looking at the behaviors associated with scho ol maladjustment on the BASC with high self esteem are well liked, accepted by their peers and fee l a sense of belonging. T his is consistent with previous bullying research that indicates that bullies are among the most popular students as ranked by peers (Thunfors & Cornell, 2008) and the more popular a student is, the more connected and central they are in the school, and the more likely they are to act aggressively (Feris & Felmlee, 2011).
98 Total Victimization The results of the current study found that higher rates of victimization were associated negatively with sensation seeking behaviors and posi tively with social stress in young adulthood. The finding regarding higher rates of victimization being associated with long term social stress was consistent with what was hypothesized. In applying social information processing theory and social cognitive theory to this finding, a child who is repeatedly victimized may come to believe that he or she will always be victimized when he or she interacts with other children or eventually, other adults in young adulthood, hence, long term social stress (Crick & Dodge, 1994). The finding regarding higher rates of victimization being negatively associated with sensation seeking behavior is consistent with research regarding the behavior of individuals with high levels of arousal. This research indicates that indivi duals with high levels of arousal have increased sensitivity to punishment and will tend to avoid stimulating situations in order to avoid punishment or anxiety ( Connor, 2002 ; Knyazev, Slobodskaya, & Wilson, 2002). This theory of arousal would help explain why indiv iduals who are recurrently victimized report low sensation seeking levels. Mean Group Differences in Relation to Bullying Types The present study also aimed to determine whether there were any mean group differences between the demographic varia bles of gender, ethnicity, and sexuality and the six bullying types (overt aggression, overt victimization, relational aggression, relational victimization, cyber aggression, and cyber victimization). The study found no significant interaction between the demographic variables, but a significant main effect was found for gender. Specifically, males reported higher rates of overt aggression than females. This was expected and consistent with previous research (Coie, Dodge, & Kupersmidt, 1990;
99 Crick & Grotpet er, 1996; Nansel et al., 2001; Prinstein et al., 2001). In addition, females were found to report higher rates of cyber victimization than males. In the limited cyber bullying research, there have been mixed findings in the literature regarding the prevale nce of cyber victimization based on gender, however; this finding contributes to what was found by Dempsey and colleagues (2009), although it was a weak relationship. Finally, although a significant main effect was not found for sexuality, there was a sign ificant difference in the reported rates of relational victimization with those participants who indicated other (bisexual, homosexual, and/or transgender) as their sexual orientation reporting higher rates than the heterosexual majority. This finding is c onsistent with previous research that indicates that lesbian, gay, bisexual, and transgender (LGBT) students are more likely to be victimized than heterosexual students ( Berlan, Corliss, Field, Goodman, & Austin, 2010; Savin Williams, 1994) and give s furt her evidence to what specific type of bullying is more likely to be encountered by LGBT youth. It is important to note that based on previous findings it was hypothesized that a significant main effect be found for sexuality. However, this was not the case and it is likely that the small sample of participants who identified as LGBT (N = 16) may have contributed to this lack of finding. Future large scale studies should investigate the relationship between sexual orientation and specific bullying types in order to target prevention and intervention efforts. Current Bullying Involvement This present study also asked participants whether they were currently involved in any of the bullying behaviors as a victim or aggressor. The research indicates that bully ing occurs at the highest rate during adolescence and the middle school years and decreases over the high school years (Finkelhor et al., 2009; Nansel et al., 2001). Given
100 this it was expected that in surveying a college population, the current bullying r ates would be minimal. In this present study, 9% of participants indicated that they were currently victims of bullying and 9% indicated that they were aggressors of bullying. A few studies (Chapell, Hasselman, Kitchin, Lomon, Maclver, & Sarullo, 2004; Zac chilli & Valerio, 2011) have investigated the prevalence of bullying in college but the numbers regarding prevalence rates vary. For example, Zachilli and Valerio (2011) found that when college students were asked about bullying during their freshmen year, only 1% of their sample reported that they had been bullied in college and 1.5% reported that they were aggressors of bullying in college; where as when seniors were asked retrospective ly about bullying in college, 9 % of their sample reported that they ha d been bullied in college and 3.6 % reported that they were aggressors of bullying in college. It is important to note that the participants in study were sampled from a small, Catholic, private liberal arts college and this may have led to differing results. In another study, Chapell and colleagues (2004) found that 24.7% of college students had witnessed someone else bully another student occasionally. In this present study, it is possible that current bullying experiences could have influenced participants psychosocial functioning. Given the prevalence rates found in this study, it is evident that bullying continues to be an issue in college and prevention and intervention efforts need to continue with this age group. Summary of Impl ications All of the findings in this current study highlight that the psychosocial difficulties associated with bullying may extend into young adulthood. School and mental health practitioners need to recognize the potentially deleterious consequences of a ll bullying types and provide those students who are involved immediate services as quickly as
101 possible. Given the findings in this present study, it is possible for professionals in the school to look for the emerging signs related to the specific psychos ocial difficulties associated with bullying. Hopefully, early intervention effort s will reduce the long term effects of the bullying experiences and children will receive the appropriate coping strategies to deal with their emotions as well as future incid ents with bullying. This study highlights that overt bullying, relational bullying, and cyber bullying are all associated with negative long term psychosocial difficulties and all deserve specific targeted prevention and intervention efforts. More specifi cally, this study highlights that it is not just traditional bullying that will have negative consequences, but also the specific behaviors associated with relational bullying and cyber bullying. Bullying prevention and intervention programs must incorpora te measures to assess, prevent, and intervene with all three types of bullying. Many times students may another student for bullyin g them because it may simply result in experiencing more bullying. It is hoped that if teachers, parents, and maybe even other students become more aware of what these bullying behaviors look like, there will be somebody to recognize if it is occurring and action can be taken immediately. Bullying prevention and intervention programs should have evidence based specific guidelines and techniques for preventing and intervening with each specific type of bullying. If the bullying literature continues to recognize the importance of researching each bullying type, these strategies will become more targeted and effective. Limitations Although the results of this study contributed to the bullying literature, there are some limitations that should be considered when interpreting the results of the study. For
102 purposes of this section, these limitation s will be described by limitations in the study design and limitations related to measurement and analyses procedures Study Design and Sample One of the limitations specific to the study design is related to the sample utilized. The study consisted of co llege students from only one college and one university in the Gainesville, Florida area. Although the sample demographics were representative of the schools enrollment as a whole, this sample may not be generalizable to the population of all college stude nts. The demographics for students enrolled elsewhere (e.g. community colleges, public universities, private universities, online programs, etc.) may differ in their demographic representation and careful consideration should be utilized in attempting to a pply the result of this study to another population. In addition, it is important to note that the findings of this study cannot be applied to different age groups that that of this sample population. For example, the long term relationship emphasized betw een bullying type and psychosocial functioning may not be generalizable to that of middle school students or high school students. Another limitation in relation to the study design is that it was a retrospective study in which participants were asked to recall their bullying experiences during a relatively l ong past time frame (5 to 18 years old). This could be problematic for several reasons. First, it is likely that the retrospective design may not have accurately captured all of a nces with bullying. With such a large time frame to think about, it is he or she may not have responded accurately regarding the frequency of each bullying type ex perienced. However, it is hoped that by asking about specific bullying behaviors, this may have increased the accuracy of recall. In addition, although the question is
103 meant to capture a long term period in order to determine the long term relationship bet ween bullying experiences and psychosocial functioning, the survey did not require the participant to indicate at what age exactly the bullying was experienced. Therefore, it is difficult to draw conclusion as to how long bullying experiences within differ ent developmental periods it is a retrospective design, we are limited in drawing conclusions about the causal relationship between bullying and psychosocial functioning. A longitudinal stud y in which participants were followed over time would better serve this purpose. Measurement and Analyses One limitation of the study related to measurement is due to a failure to modify one of the cyber aggression questions within the cyber aggression sc ale. The statement or others a text message or instant message about a student that was mean or threatened that s tudent modification should have been made to both the cyber victimization and cyber aggression scales in order to expand upon the original statement and further increase the likelihood that all potential cyber behavior be captured. It is possible t hat the failure to make this modification may have resulted in a lesser number of participants endorsing cyber aggressive behaviors. The internal consistency reliability of the cyber aggression scale is another major s alpha analyses were conducted to examine the internal consistency reliability of the scale and the analysis of the cyber aggression scale indi cated that the reliability was be low recommended reliability coefficients (Charter, 2003) This is significantly different than w hat another study (Dempsey, 2011 )
104 found for the ). One potential reason for this difference is that this other study had a very d ifferent participant sample than this current study and was conducted with middle school students in a very rural area. It is important to note that in this study, out of this current sample, involvement in cyber aggression was the least endorsed bullying type and all other types were endorsed at least double that of the cyber aggression frequency. This small sample size could possibly have influenced the reliability of the scale. Another limitation within the study is related to the interpretation of the f indings regarding the relationship between a recalled bullying type and psychosocial outcome variable. It is important to note that when a specific bullying type is significantly related to a specific psychosocial outcome, it does not mean that the outcome score on the psychosocial scale is clinically significant. When interpreting the results of this study, it is important to keep in mind that the significance simply indicates that a specific bullying type was related to significantly higher or lower (for negative relationship) symptoms of a specific psychosocial outcome variable not necessarily a clinically significant level. When interpreting the results of this study, this should be kept in mind. s related to the MANOVA results The MANOVA results indicated that two tests were significant: Equality of Covariance Matrices is significant the observed covariance matrices of the dependent variables are not equal across groups. As was done in this study, when this
105 dependent variable s in the MANOVA and indicated that the observed variability in three of the bullying groups (relational victimization, cyber victimization, and overt aggression) may not be equal. Although some step s were taken to address these limitation s (e.g. bullying types and the demographic variables (gender, ethnicity, and sexuality) should be interpreted with caution. Directi ons for Future Research The findings of this current study emphasize the need for continued bullying research that focuses on all of the specific types of bullying identified. This study highlights that psychosocial difficulties associated with bullying ma y extend into early adulthood. Given the findings and limitations of this current study, there are many future research directions that can be taken. First, although the findings of the current study indicate that specific bullying experiences are related to specific psychosocial difficulties, causality is not determined. Future research may want to utilize a study with a longitudinal design in which children are followed from childhood into adulthood while consistently assessing their experiences with bull ying and current psychosocial functioning at multiple points. This could also provide information about the prevalence of specific bullying types at specific ages and information regarding the trend of bullying and when specific types increase or decrease. Next, future research may want to consider utilizing a larger sample size. The sample size of the present study did not allow the researcher to investigate several other comparison groups that would have been beneficial to examine more closely. First, al though this study provided valuable information regarding those who had experiences with bullying, there was no comparison group for those who had no experiences with
106 bullying. In addition, the present study did not allow the researcher to investigate psyc hosocial functioning related to all of the bullying roles, more specifically those who were bully victims. Future research may want to utilize a larger sample size to capture a control group for each bullying types and also examine the psychosocial functio ning of those who were bully victims in comparison to aggressors only or victims only. Finally, a larger sample size would allow the research to establish the psychometric properties of the modified measures, specifically the RVQ with aggression questions and the cyber aggression questions. Another area for future research that was highlighted by this present study is bullying among college students. The study found that 9% of participants indicated that there were still experiencing bullying in college, bu t the design of the survey only asked about current involvement as an aggressor or victim without differentiation among the bullying types. Future studies may consider investigating current prevalence rates in college students related to specific bullying types. It is apparent that bullying continues to be prevalent in this age range and future studies that confirm these results may aid in lobbying for prevention and intervention efforts at the college level. Finally, although this study examined the relati onship between bullying and many psychosocial constructs, the majority of constructs examined were focused on internalizing problems (e.g. self esteem, depression, anxiety). Previous bullying research (Connolly et al., 2000; Dodge & Petit, 2003; Sourander et al., 2007) indicates that bullying is also related to aggressive behavior and externalizing problems Future research on the psychosocial long term effects of bullying should also include various
107 narrow external measures focused on anger and violence i n order to capture all of the possible psychosocial difficulties associated with bullying.
108 APPENDIX A INFORMED CONSENT Informed Consent Protocol Title: Bullying Experiences in Childhood Please read this consent document carefully before you dec ide to participate in this study. Purpose of the research study: The purpose of this study is to examine the effects of childhood bullying on current behaviors and feelings. What you will be asked to do in the study: The researcher will provide a brief ove rview of the purpose and the nature of the study. You will then be given a manila envelope that contains several measures and questionnaires. These measures should take approximately 45 minutes to complete. The measures will ask you about your different ex periences with bullying in childhood. In addition, you will also complete several measures that ask you about how you currently feel and behave. You can refuse to answer any question for any reason and you are free to withdraw your consent to participate a nd may discontinue your participation at any time without any type of consequence. Once you complete all questionnaires, you will return the manila envelope to the researcher. The researcher will provide you with an additional sheet that contains contact i counseling center. Time required: 1 hour Risks and Benefits: There are no direct benefits to participating in this study. However, potential indirect benefits of this study include helping resea rchers and educators to better understand the long term consequences of bullying and guide the development of targeted bullying prevention and intervention strategies. We do not anticipate any risks with participating in this study. Should you find yoursel f
109 UF Counseling and Wellness Center 3190 Radio Road Phone: (352) 392 1575 Fax: (352) 392 8452 Santa Fe Counse ling Center Building S. Room 254 3000 NW 83rd street Gainesville, Fl 32606 Phone: (352) 395 5508 Fax: (352) 395 4475 Compensation: You will receive extra credit or course credit for participating in this study. Upon completion of the packet, please turn i n the separate sheet of paper with your name to the researcher. If you choose to not participate in this study but would still like the opportunity to receive extra credit, you can choose to complete the non research alternative. In order to obtain extra c redit, you can write a 3 page research paper on the consequences of bullying and turn this in to your course instructor. Confidentiality: Your identity will be kept confidential to the extent provided by law. Your information will be assigned a code number and no identifying information will be connected to your responses to the questionnaires. Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from the study at anytime without consequence. Whom to contact if you have questions about the study: XXXXXXXXXXX M.Ed. Graduate Student Department of Special Education, School Psychology, & Early Childhood XXXXXXXXXXX Ph.D.
110 Whom to contact about your rights as a research participant in the study: IRB02 Office, Box 112250, University of Florida, Gainesville, FL 32611 2250; phone 392 0433. Agreement: I have read the procedure described above. I voluntarily agree to participat e in the procedure and I have received a copy of this description. Participant: ___________________________________________ Date: _________________ Principal Investigator: ___________________________________ Date: _________________
111 APPENDIX B QUESTI ONNAIRE This survey asks you a number of questions about your past experiences in school and what you think. This is not a test. There are no right or wrong answers. To answer the questions, please circle the number on this sheet that best applies to you Circle only one answer for each question. Do not put your name on this sheet. You are the only one who will know how you answered each question, so we want you to be honest as you go through this survey. PART 1: WHAT HAPPENS TO YOU Instructions: The se questions ask how often a student bullied or picked on you. These can be things that happened at school or somewhere else, as long as they involved other students. Please answer each question based on your memories and recollections. You should circle O NE number to show how often each action happened to you in childhood (5 to 18 years old) Never Once or Twice A Few Times About Once a Week A Few Times a Week 1. A student hit, kicked, or pushed me in a mean way. 1 2 3 4 5 2. A student threatened to hurt or beat me up. 1 2 3 4 5 3. A student chased me like he or she was really trying to hurt me. 1 2 3 4 5 4. A student grabbed, held, or touched me 1 2 3 4 5 5. A student left me out of what h e or she was doing. 1 2 3 4 5 6. A student left me out of an activity or conversation that I really wanted to be included in. 1 2 3 4 5 7. A student did not invite me to a party or other social event even though he or she knew that I wanted to go. 1 2 3 4 5 8. A student I wanted to be with would not sit near me at lunch or in class. 1 2 3 4 5 9. A student gave me the silent treatment (did not talk to me on purpose). 1 2 3 4 5 10. A student sent others or me a text message or instant message about me th at was mean or that threatened me. 1 2 3 4 5
112 11. A student posted a comment on my web space wall that was mean or that threatened me. 1 2 3 4 5 12. A student sent me an email that was mean or that threatened me. 1 2 3 4 5 13. A student created a web pa ge about me that had mean or embarrassing information and/or photos. 1 2 3 4 5 During Childhood (5 to 18 years old), how often did other students Never Rarely Sometimes Often Always 1. Spread rumors about you? 1 2 3 4 5 2. Purposely exclude yo u from social interactions? 1 2 3 4 5 3. Purposely ignore or refuse to talk to you? 1 2 3 4 5 4. Divulge personal information about you that was originally shared in confidence? 1 2 3 4 5 5. Try to cause fights or arguments among you and other peers? 1 2 3 4 5 6. Pick you last for an activity, for reasons NOT related to your ability 1 2 3 4 5 7. Ridicule you in front of other people? 1 2 3 4 5 Are you currently experiencing any of the above behaviors listed on this page? Circle one: Yes No
113 PART 2: WHAT YOU DO Instructions: The next questions ask how often you bullied or picked on another student. You should circle ONE number to show how often you did each action in childhood (5 to 18 years old) During Childhood Never Once or Twice A Few Times About Once a Week A Few Times a Week 14. I hit, kicked, or pushed a student in a mean way. 1 2 3 4 5 15. I threatened to hurt or beat a student up. 1 2 3 4 5 16. I chased a student like I was really trying to hurt him or her. 1 2 3 4 5 17. I grabbed, held, or touched a student in 1 2 3 4 5 18. I left a student out of what I was doing. 1 2 3 4 5 19. I left a student out of an activity or conversation that he or she reall y wanted to be included in. 1 2 3 4 5 20. I did not invite a student to a party or other social event even 21. though I knew that he or she wanted to go. 1 2 3 4 5 21. I would not sit near a student at lunch or in class that wanted to sit by me. 1 2 3 4 5 22. I gave a student the silent treatment (did not talk to a student on purpose). 1 2 3 4 5 23. I sent a student a text message or instant message that was mean or that threatened that student. 1 2 3 4 5 space wall that was mean or that threatened that student. 1 2 3 4 5 25. I sent a student an email that was a mean or that threatened that student. 1 2 3 4 5 26. I created a web page about a student that had mean or embarrassing information and/or photos. 1 2 3 4 5
114 During Childhood (5 to 18 years old), how often did you Never Rarely Sometimes Often Always 1. Spread rumors about a student? 1 2 3 4 5 2. Purposely exclude a student from social interactions? 1 2 3 4 5 3. Purposely ignore or refuse to ta lk to a student? 1 2 3 4 5 4. Divulge personal information about a student that was originally shared in confidence? 1 2 3 4 5 5. Try to cause fights or arguments among another student and your peers? 1 2 3 4 5 6. Pick a student last for an activity, fo r reasons NOT related to their ability 1 2 3 4 5 7. Ridicule a student in front of other people? 1 2 3 4 5 Are you currently involved in any of the above behaviors listed on this page? Circle one: Yes No
115 Instructions: The fol lowing statements describe how people sometimes feel. For each statement, please indicate how often you feel the way described by writing a number in the space provided. Here is an example: How often do you feel happy? If you never felt happy, you would NEVER RARELY SOMETIMES ALWAYS 1 2 3 4 ____ ____ 2. How often do you feel that you lack companionship? ____ 3. How often do you feel that there is no one you can turn to? ____ 4. How often do you feel alone? ____ 5. How often do you feel part of a group of friends? ____ 6. How often do you feel that you have a lot in common wit h the people around you? ____ 7. How often do you feel that you are no longer close to anyone? ____ 8. How often do you feel that your interests and ideas are not shared by those around you? ____ 9. How often do you feel outgoing and frie ndly? ____ 10. How often do you feel close to people? ____ 11. How often do you feel left out? ____ 12. How often do you feel that your relationships with others are not meaningful? ____ 13. How often do you feel that no one really knows you well? ____ 1 4. How often do you feel isolated from others? ____ 15. How often do you feel you can find companionship when you want it? ____ 16. How often do you feel that there are people who really understand you? ____ 17. How often do you feel shy? ____ 18. How oft en do you feel that people are around you but not with you? ____ 19. How often do you feel that there are people you can talk to? ____ 20. How often do you feel that there are people you can turn to?
116 Instructions: Read each of the followin g statements carefully and indicate how characteristic it is of you according to the following scale: 1 = Not at all characteristic of me 2 = Slightly characteristic of me 3 = Moderately cha racteristic of me 4 = Very characteristic of me 5 = Extremely characteristic of me _____ 1. I worry about what other people will think of me even when I know it doesn't make any difference. _____ 2. I am unconcerned even if I know people are forming an unfavorable impression of me _____ 3. I am frequently afraid of other people noticing my shortcomings. _____ 4. I rarely worry about what kind of impress ion I am making on someone. _____ 5. I am afraid others will not approve of me. _____ 6. I am afraid that people will find fault with me. _____ 7. Other people's opinions of me do not bother me. _____ 8. When I am talking to someone, I worry ab out what they may be thinking about me. _____ 9. I am usually worried about what kind of impression I make. _____ 10. If I know someone is judging me, it has little effect on me. _____ 11. Sometimes I think I am too concerned with what other people th ink of me. _____ 12. I often worry that I will say or do the wrong things.
117 Instructions. Please provide the following information: What is your age? _______________________ What is your gender? Please circle one: Male Female What is your sexual ori entation? Please circle one: Heterosexual Homosexual Bisexual Transgender What is your ethnicity? Please circle one: White (Non Hispanic) Black Asian Hispanic Native American Other Where do you attend school? Please circle one : University of Florida Santa Fe College Check which forms of financial aid you may be eligible for: _____ Federal Grant _____ Merit Based Scholarships _____ Need Based Scholarships _____ Loans _____ Student Employment
118 LIST OF REFERE NCES Alfano, C. A., Beidel, D. C., & Turner, S. M. (2008). Negative self imagery among adolescents with social phobia: A test of an adult model of the disorder. Journal of Clinical Child and Adolescent Psychology, 37, 327 336 Archer, J. (2004). Sex differ ences in aggression in real world settings: A meta analytic review. Review of General Psychology, 8, 291 322. Arseneault, L., Walsh, E., Trzesniewski, K., Newcombe, R., Caspi, A., & Moffitt, T. E. (2006). Bullying victimization uniquely contributes to ad justment problems in young children: A nationally representative cohort study. Pediatrics, 118(1), 130 138. Bandura, A. (1989). Social cognitive theory. In R. Vasta (Ed.), Annals of child development. Vol.6. Six theories of child development (pp. 1 60). Gr eenwich, CT: JAI Press. Bauman, S. (2008). The Association Between Gender, Age, and Acculturation, and Depression and Overt and Relational Victimization Among Mexican American Elementary Students. The Journal of Early Adolescence, 28 (4), 528 554. Bauman, S. & Summers, J. (2009). Peer victimization and depressive symptoms in mexican american middle school students: Including acculturation as a variable of interest. Hispanic Journal of Behavioral Sciences, 31 (4), 515 535 Baumeister, R. F., Smart, L., & Bod en, J.M. (2006). Relation of threatened egotism to violence and aggression: The d ark s ide of h igh s elf e steem, Psychological Review, 103, 5 33. Berlan, E. D., Corliss, H. L., Field, A. E., Goodman, E., & Austin, S. B. (2010). Sexual orientation and bullyin g among adolescents in the Growing Up Today study. Journal of Adolescent Health, 46, 366 371. Bond, L., Carlin, J. B., Thomas, L., Rubin, K., & Patton, G. (2001). Does bullying cause emotional problems? A prospective study of young teenagers British Medic al Journal, 323, (7311), 480 484 Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. The American Psychologist, 32, 513 531. doi:10.1037/0003 066X.32.7.513. Burks, V. S., Dodge, K. A., Price, J. M., & Laird, R. D. (1999). Inter nal representational models of peers: Implications for the development of problematic behavior. Developmental Psychology, 35(3), 802 810. Chapell, M. S., Hasselman, S. L., Kitchin, T., Lomon, S. N., Maclver, K. W., & Sarullo, P. L. (2006). Bullying in elem entary school, high school, and college. Adolescence, 41, 633 648.
119 Charter, R. A. (2003). A breakdown of reliability coefficients by test type and reliability method, and the clinical implications of low reliability. Journal of General Psychology, 130(3), 290 304. Christianson, S. A. (1992). Emotional stress and eyewitness memory: A critical review. Psychological Bulletin, 112, 284 309 Christianson, S. memories. Bulletin of the Psychonomi c Society, 28, 195 198. Cicchetti, D. & Rogosch, F.A. (2002). A developmental psychopathology perspective on adolescence. Journal of Consulting and Clinical Psychology, 70 (1), 6 20. Coie, J. D., Dodge, K. A., & Kupersmidt, J. B. (1990). Peer group behavi or and social status. In S. R. Asher & J. D. Coie (Eds.), Peer rejection in childhood (pp. 17 59). New York: Cambridge University Press. Collins, K. A., Westra, H. A., Dozois, D. J. A., & Stewart, S. (2005). The validity of the brief version of the Fear of Negative Evaluation Scale. Journal of Anxiety Disorders, 19, 345 359. Connolly, J., Pepler, D., Craig, W., & Taradash, A. (2000). Dating experiences of bullies in early adolescence. Child Maltreatment, 5(4), 299 210. Connor, D. F. (2002). Aggression & ant isocial behaviour in children and adolescents: Research and treatment. London: The Guildford Press. Copelan, R., & Ashley, D. (2005). Adolescent and child urgent threat evaluation. Lutz, FL: Psychological Assessment Resources, Inc Costello, A. B., & Osbor ne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment Research and Evaluation, 10(7). Available online: http://pareonline.net/getvn.asp?v=10&n=7 Craig, W. M. (199 8). The relationship among bullying, victimization, depression, anxiety and aggression in elementary school children. Personality and Individual Differences, 24, 123 130 Craig, W. M., Henderson, K., & Murphy, J. G. (2000). Prospective teachers' attitudes toward bullying and victimization. School Psychology International, 21, 5 21. Crick, N. R. (1996). The role of overt aggression, relational aggression, and prosocial behavior in the prediction of children's future social adjustment. Child Development, 67(5 ), 2317 2327. Crick, N. R., Casas, J. F., & Ku, H.C. (1999). Relational and physical forms of peer victimization in preschool. Developmental Psychology, 35, 376 385.
120 Crick, N. R., & Dodge, K. A. (1994). A review and reformulation of social information proc essing mechanisms in children's social adjustment. Psychological Bulletin, 115, 74 101. and overt aggression. Development and Psychopathology, 8, 367 380. Crother s, L. M., Field, J. E., & Kolbert, J. B. (2005). Navigating power, control, and being Development, 83, 349 354. Cuming, S., Rapee, R. M., Kemp, N., Abbott, M. J., Peters, L., & Ga ston, J. E. (2009). A self report measure of subtle avoidance and safety behaviors relevant to social anxiety: Development and psychometric properties. Journal of Anxiety Disorders, 23, 879 883. 02). Incidence and mental health impact of sexual orientation victimization of lesbian, gay, and bisexual youths in high school. School Psychology Quarterly, 17, 148 167. De Los Reyes, A., & Prinstein, M. J. (2004). Applying d epression d istortion h ypothes es to the a ssessment of p eer v ictimization in a dolescents. Journal of Clinical Child and Adolescent Psychology, 33, 325 335. Dempsey, A.G. (2009). Aggression and victimization in middle school: A mixed methods analysis of the process and effectiveness of i mplementing a prevention program. (Doctoral dissertation) Retrieved from University of Florida online dissertations ( UFE0022 510 ) Dempsey, A. G., Sulkowski, M. L., Dempsey, J., & Storch, E. A. ( 2011 ). Has cyber technology produced a new group of peer aggressors? Cyberpsychology, Behavior, and Social Networking 14, 297 302. doi:10.1089/cyber.2010.0108. Dempsey, A. G, Sulkowski, M. L., Nichols, R., & Storch, E. A. (2009). Differences between peer victimization in cyber and physical settings and associated psychosocial adjustment in early adolescence. Psychology in the Schools, 46, 962 972 Diamanduros, T., Downs, E., & Jenkins, S. J. (2008). The role of school psychologist in the assessment, prevention, and intervention of cyberbullying. Psychology in the Schools, 45, 693 704. Dodge, K. A., Lochman, J. E., Harnish, J. D., Bates, J. E., & Pettit, G. S. (1997). "Reactive and proact ive aggression in school children and psychiatrically impaired chronically assaultive youth." Journal of Abnormal Psychology, 106, 37 51.
121 Dodge, K. A., Price, J. M., Bachorowski, J. A., & Newman, J. P. (1990). Hostile attributional biases in severely aggre ssive adolescents. Journal of Abnormal Psychology, 99, 385 392 Dodge, K. A. & Sherrill, M. R. (2007). The interaction of nature and nurture in antisocial behavior. In: D.J Flannery, A. T. Vazsonyi, & I. D. Waldman, (Ed s .); The Cambridge handbook of vio lent behavior and aggression (pp. 215 242). NY: Cambridge University Press. Due, P., Damsgaard, M. T., Rikke, L., & Holstein, B. E. (2009). Is bullying equally harmful for rich and poor children?: A studying of bullying and depression from ages 15 to 27. Oxford University Press, 19 (5), 464 469. Due, P., Holstein, B. E., Lynch, J., Diderichsen, F., Gab Behaviour in School Aged Children Bullying Working Group ( 2005). Bullying and symptoms among school aged children: Internati onal comparative cross sectional study in 28 countries. European Journal of Public Health, 15, 128 132. Duke, D., Krishnan, M., Faith, M., & Storch, E. A. (2006). The psychometric properties of the Brief Fear of Negative Evaluation Scale, 20(6), 807 817. E aton, D. K, Kann, L., Kinchen, S., Shan Wechsler, H. (2010). Youth risk behavior surveillance United States, 2009. Surveillance s ummaries. Morbidity and Mortality Weekly Report 59(No. SS 5), 1 142. Elinoff, M. J., Chafouleas S. M., & Sassu, K. A. (2004). Bullying: Considerations for defining and intervening in school settings. Psychology in the Schools, 41, 887 897. Elzinga, B.M., Spinhoven, P., Berretty, E., de Jong, P., & Roelofs, K. (2010). The role of childhood abuse in HPA axis reactivity in Social Anxiety Disorder: A pilot study. Biological Psychology, 83(1), 1 6. Espelage, D. L., & Holt, M. K. (2007). Dating violence & sexual harassment across the bully victim continuum among middle and high school students. Journal of Youth Adolescence, 36, 799 811. DOI 10.1007/s10964 006 9109 7 Espelage, D. L., Holt, M. K., & Henkel, R. R. (2003). Examination of peer group contextual effects on aggression during early adolescence. Child Development, 74, 205 220. Espelage, D. L., Meban e, S. E., & Swearer, S. M. (2004). Gender differences in bullying: Moving beyond mean level differences. In D. L. Espelage & S. M. Swearer (Eds.), Bullying in American schools: A social ecological perspective on prevention and intervention (pp. 15 35). Mah wah NJ: Lawrence Erlbaum. Estevez, E., Murgui, S., & Musitu, G. (2009). Psychological adjustment in bullies and victims of school violence. European Journal of Psychology of Education, 24(4), 473 483
122 Ezpeleta, L., Domenech, J. M., & Angold, A. (2006). A comparison of pure and comorbid CD/ODD and depression. Journal of Child Psychology and Psychiatry, 47, 704 712. Faris, R., & Felmlee, D. (2011) Status Struggles: Network centrality and gender segregation in same and cross gender aggression. American Socio logical Review, 76(1), 48 73. Feinberg, T. & Robey, N., (2008). Cyberbullying. Principle Leadership (High School Ed), 9, 693 704. Fergus, S. & Zimmerman, M. (2005). Adolescent resilience: A framework for understanding h ealth development in the face of r isk. Annual Review of Public Health, 25, 339 419 exposure to violence: A comprehensive national survey. Washington, DC: U.S. Department of Justice, Office of Justice Program s, Office of Juvenile Justice and Delinquency Prevention. Flynt, S. W., & Morton, R. C. (2007). Bullying prevention and students with disabilities. National Forum of Special Education Journal, 19(1), 1 6. Frick, P. J., Barry, C. T., & Kamphaus, R.W. (2010) Clinical assessment of child and adolescent personality and behavior (3rd ed). New York: Springer. Garritty, C., Jens, K., Porter, W., & Stoker, S. (2002). Bullying in schools: A review of prevention programs. In S. E. Brock, P. J. Lazarus & S. R. Jimers on (Eds.), Best practices in school crisis prevention and intervention (pp. 171 190). Bethesda, MD: National Insititute of School Psychologists. Gini, G., & Pozzoli, T. (2009). Association between bullying and psychosomatic problems: A meta analysis. Pedia trics, 123(3), 1059 1065. Gliem, J. reliability coefficient for Likert type scales. Midwest Research to Practice Conference in Adult, Continuing, and Community Education, 82 88. Goldin, P. R., & Gross, J. J. (2010). Effects of mindfulness based stress reduction (MBSR) on emotion regulation in social anxiety disorder. Emotion, 10(1), 83 91 Goldin, P.R., Manber, T., Hakimi, S., Canli, T., & Gross, J.G. (2009). Neural bases of soci al anxiety disorder: Emotional reactivity and cognitive regulation during social and physical threat. Archives of General Psychiatry, 66, 170 180. Graham, S. (2006). Peer v ictimization in s chool: Exploring the e thnic c ontext. Current Directions in Psycholo gical Science, 15, 317 321.
123 Graham, S. & Juvonen, J. (1998). Self blame and peer victimization in middle school: An attributional analysis. Developmental Psychology, 34, 587 599 Griffin, R., & Gross, A. (2004). Childhood bullying: Current empirical findin gs and future directions for research. Aggression and Violent Behavior, 9, 379 400. doi:10.1016/S1359 1789(03)00033 8 Grotpeter, J. K., & Crick, N. R. (1996). Relational aggression, overt aggression, and friendship. Child Development, 67, 2328 2338. Hackma nn, A., Clark, D. M., & McManus, F. (2000). Recurrent images and early memories in social phobia. Behaviour Research and Therapy, 38, 601 610. Hamann, S. B. (2001). Cognitive and neural mechanisms of emotional memory. Trends in Cognitive Sciences, 5 394 4 00. Hamburger, M. E., Basile, K. C, Vivolo, A. M. (2011). Measuring bullying victimization, perpetration, and bystander experiences: A compendium of assessment tools. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prev ention and Control. Retrieve July 18, 2011 from http://www.stopbullying.gov/community/tip_sheets/assessment_tools.pdf Hanish, L. D., & Guerra, N. G. (2000). The roles of ethnicity and school context in Journal of Community Psychology, 28, 201 223. Hardy, V., Rockinson Szapkiw, A. J., West, L. C., Phillips, T., & Hood, D. (2010). An overview of the Behavior Assessment System for Children. Retrieved April 25, 2010 from http://basc.szapkiw.com/basc_summary .html Hawker, D. S. J., & Boulton, M. and psychosocial maladjustment: A meta analytic review of cross sectional studies, Journal of Child Psychology and Psychiatry and Allied Disciplines, 41, 441 455. Hay, C., Meldrum, R., & Mann, K. (2010). Traditional bullying, cyberbullying, and deviance: A general strain theory. Journal of Contemporary Criminal Justice, 26, 204 233. Haynie, D. L., Nansel, T., Eitel, T., Crump, A. D., Saylor, K., Yu, K., & Simons Mo rton, B. (2001). Bullies, victims, and bully/victims: Distinct groups of at risk youth. Journal of Early Adolescence, 21(1), 290 49. Henington, A., Hughes, J., Cavell, T., & Thompson, B. (1998). The role of relational aggression in identifying aggressive b oys and girls. Journal of School Psychology, 36, 457 477. doi:10.1016/S0022 4405(98)00015 6. Hinduja, S., & Patchin, J. W. (2007). Offline consequences of online victimization. Journal of School Violence, 6, 89 112.
124 Hinduja, S., & Patchin, J. W. (2008). C yberbullying: An exploratory analysis of factors related to offending and victimization. Deviant Behavior, 29, 129 156. Hirsch, C. R., & Clark, D. M. (2004). Information processing bias in social phobia. Clinical Psychology Review, 24, 799 825. Hoglund, W. L. G. (2007). School functioning in early adolescence: Gender linked responses to peer victimization. Journal of Educational Psychology, 99 (4), 683 699. Holt, M. K., Finkelhor, D., & Kantor, G. K. (2006). Multiple victimization experiences of urban eleme ntary school students: Associations with psychosocial functioning and academic performance. Child Abuse and Neglect, 31, 503 515. Huberty, C. J., & Morris, J. D. (1989). Multivariate analysis versus multiple univariate analysis. Psychological Bulletin, 10 5 (2), 302 308. Hunter, S. C., Mora Merchan, J., & Ortega, R. (2004). The long term effect of coping strategy use in victims of bullying. Spanish Journal of Psychology, 7, 3 12. Ireland, J. L., & Ireland, C. A. (2003). How do offenders define bullying? A s tudy of adult, young and juvenile male offenders. Legal and Criminological Psychology, 8, 159 173. i SAFE. (2009). The leader in E safety education: Who we are. Retrieved February 1, 2009, from http://www.isafe.org/ channels/sub.php?ch=ai&sub_id=1 James, R. (2008). Crisis intervention strategies (6th ed.). Belmont, CA: Brooks Cole/Thompson. Juvonen, J., Graham, S., & Schuster, M. A. (2003). Bullying among young adolescents: The strong, the weak, and the troubled. Pediatrics, 112, 1231 1237. Kaltiala Heino, R ., Rimpelae, M., & Rantanen, P. (2001). Bullying at school: An indicator for adolescents at risk for mental disorders, Journal of Adolescence, 23, 661 674. Kaukiainen, A., Salmivalli, C., Lagerspetz, K., Tamminen, M., Vauras, M., Mki, H., & Poskiparta, E. (2002). Learning difficulties, social intelligence, and self concept: Connections to bully victim problems. Scandinavian Journal of Psychology, 43, 269 278. Kochenderfer, B. J., & Ladd, G. W. (1996). Peer victimization: Manifestations and relations to sc hool adjustment in kindergarten. Journal of School Psychology, 34(3), 267 283. Kosciw, J. G., Greytak, E. A., & Diaz, E. M. (2009). Who, what, where, when, and why: Demographic and ecological factors contributing to hostile school climate for
125 lesbian, gay bisexual, and transgender youth. Journal of Youth & Adolescence, 38(7), 976 988. Knyazev, G. G., Slobodskaya, H. R., & Wilson, G. D. (2002). Psychophysical correlates of behavioural inhibition and activation. Personality and Individual Differences, 33, 64 7 660. Kumpulainen, K., Rsnen, E., Henttonen, I., Almqvist, F., Kresanov, K., Linna, school age children. Child Abuse and Neglect, 22, 705 717. La Greca, A. M., & Harrison, H. M. ( 2005). Adolescent Peer Relations, Friendships, and Romantic Relationships: Do They Predict Social Anxiety and Depression? Journal of Clinical Child and Adolescent Psychology, 34, 49 61. Langdon, S., & Preble, W. (2008). The relationship between levels of p erceived respect and bullying in 5th through 12th graders. Adolescence, 43(171), 485 503 Lansford, J. E., Deater Deckard, K., Dodge, K. A., Bates, J. E., & Pettit, G. S. (2004). Ethnic differences in the link between physical discipline and later adolesce nt externalizing behaviors. Journal of Child Psychology and Psychiatry, 45, 801 812. Lansford, J. E., Malone, P. S., Dodge, K. A., Crozier, J. C., Pettit, G. S., & Bates, J. E. (2006a). A 12 year prospective study of patterns of social information process ing problems and externalizing behaviors. Journal of Abnormal Child Psychology, 34, 715 724. Lansford, J. E., Malone, P. S., Stevens, K. I., Dodge, K. A., Bates, J. E., & Pettit, G. S. (2006b). Developmental trajectories of externalizing and internalizing behaviors: Factors underlying resilience in physically abused children. Development and Psychopathology, 18(1), 35 55. Leadbeater, B. J., & Hoglund, W. L. G. (2009). The effects of peer victimization and physical aggression on changes in internalizing fro m first to third grade. Child Development, 80, 843 859. Leary, M. R. (1983). A brief version of the Fear of Negative Evaluation Scale. Personality and Social Psychology Bulletin, 9, 371 376. Ledley, D. R., Storch, E. A., Coles, M. E., Heimberg, R. G., Mos er, J., & Bravata, E. A. (2006). The relationship between childhood teasing and later interpersonal functioning. Journal of Psychopathology and Behavioral Assessment, 28, 33 40. Leschied, A., Cummings, A., van Brunschot, M., Cunningham, A., & Saunders, A. (2001). Aggression in adolescent girls: Implications for policy, prevention, and treatment. Canadian Psychology, 42 200 215. doi:10.1037/h0086892.
126 Li, Q. (2006). Cyberbullying in schools: A research of gender differences. School Psychology International 27 (2), 157 170. Low, G., Jones, D., MacLeod, A., Power, M., & Duggan, C. (2000). Childhood trauma, dissociation, and self harming behavior: A pilot study. British Journal of Medical Psychology, 73, 269 278. Mash, E. J., & Barkley, R. A. (2003). Child psy chopathology. (2nd ed.). New York, NY: The Guilford Press Mason, K. L. (2008). Cyberbullying: A preliminary assessment for school personnel. Psychology in the Schools, 45, 323 347. Mattick, R. P., & Lorna, P. (1988). Treatment of severe social phobia: Eff ects of guided exposure with and without cognitive restructuring. Journal of Consulting and Clinical Psychology, 56, 251 260. Meyer Adams, N., & Conner, B. (2008). School violence: Bullying behaviors and the psychosocial school environment in middle schoo ls. Children and Schools, 30(4), 211 221. Nansel, T. R., Overpeck, M., Pilla, R. S., Ruan, W. J., Simons Morton, B., & Scheidt, P. (2001). Bullying behaviors among U.S. youth: Prevalence and association with psychosocial adjustment. J ournal of the America n Medical Association 285(16), 2094 2100. National Crime Prevention Council (2009) Cyberbullying. Retrieved January 30, 2009 from: http://www.ncpc.org/cyberbullying/?searchterm=cyberbullying Nowinski, L. A., Furlong, M. J., Rahban, R., & Smith, S. R. ( in press). Initial reliability and validity of the BASC 2, SRP, College Version. Journal of Psychoeducational Assessment. The Office of Institutional Planning and Research. (2011). University of Florida Facts. Retrieved July 18, 2011 from http://www.ir.ufl .edu/facts.htm Olweus, D. (1993). Bully/victim problems among schoolchildren: Long term consequences and an effective intervention program. In S. Hodgins (Ed.), Mental disorder and crime (pp. 317 349). Thousand Oaks, CA: Sage Publications. Olweus, D. (1994 ). Bullying at school: Basic facts and effects of a school based intervention Program. Journal of Child Psychology and Psychiatry, 35, 1171 1190. Olweus, D. (2001). Peer harassment: A critical analysis of some important issues. In J. Juvonen & S. Graham (E ds.), Peer harassment in s c hool: The plight of the vulnerable and victimized (pp. 3 20). New York: Guilford.
127 O'Toole, M. E. (2000). The school shooter: A threat assessment perspective. Washington, D.C.: Federal Bureau of Investigation. Ott, R. L. (1993) An Introduction to Statistical Methods and Data Analysis (4th ed.), Pacific Grove, CA: Duxbury. Patchin, J. W., & Hinduja S. (2006). Bullies move beyond the school yard: A preliminary look at cyberbullying. Youth Violence and Juvenile Justice, 4 148 169. Pelligrini, A. D., & Long, J. D. (2002). A longitudinal study of bullying, dominance, and victimization during the transition from primary school to secondary school. British Journal of Developmental Psychology, 20, 259 280. Prinstein, M. J., Boergers, J ., & Vernberg, E. M. (2001). Overt and relationship aggression in adolescent: Social psychological adjustment of aggressors and victims. Journal of Clinical Psychology, 30, 479 491. Reynolds, C. R., & Kamphaus, R. W. (2004). Behavior Assessment System for Children Second Edition manual. Circle Pines, MN: American Guidance Service Publishing. Rigby, K. (2003). Consequences of bullying in schools. Canadian Journal of Psychiatry, 48, 583 590. Rose, C. A., Espelage, D. L., & Monda Amaya, L. E. (2009). Bullying and victimization rates among students in general and special education: A comparative analysis. Educational Psychology, 29 (7), 761 776. Ross, D. M. (1996). Childhood bullying and teasing: What school personnel, other professionals, and parents can do. A lexandria, VA: American Counseling Association. Rothschild, B. (2000). The body remembers: The psychophysiology of trauma and trauma treatment. New York: WW Norton Russell, D. (1996). The UCLA Loneliness Scale (Version 3): Reliability, validity and fact or structure. Journal of Personality Assessment, 66, 20 40. Santa Fe College. (2010). Institutional Effectiveness: Fall Facts Closing Fall 2010. Retrieved July 18, 2011 from http: //www.sfcollege.edu/facts/content/media/mugs/Facts%20 %20Fall%20Closing%202010.pdf Savin Williams, R. C. (1994). Verbal and physical abuse as stressors in the lives of lesbian, gay male, and bisexual youths: Associations with school problems, running away substance abuse, prostitution, and suicide. Journal of Consulting and Clinical Psychology, 62, 261 269.
128 Schneller, J. (2005). Psychosocial Evaluation and Threat Risk Assessment. Lutz, FL: Psychological Assessment Resources Smith, P. K. (2004). Bullying : Recent developments. Child and Adolescent Mental Health, 9, 98 103. Smith, P. K., Cowie, H., Olafsson, R. F., & Liefooghe, A. (2002). Definitions of b ullying: A c omparison of t erms u sed, and a ge and g ender d ifferences, in a f ourteen c ountry i nternational c omparison. Child Development, 73, 1119 1133. Sourander, A., Jensen, P., Ronning, J.A., Elonheimo, H., Niemela, S., Helenius, late adolescence: The Finnish From a Boy to a Man study. Archives of Pediatric Adolescent Medicine, 161, 546 552. Spriggs, A. L., Iannotti, R. J., Nansel, T. R., & Haynie, D. L. (2007) Adolescent bullying involvement and perceived family, peer and school relations: Commonalities and differences acr oss race/ethnicity. Journal of Adolescent Health, 41(3), 283 293 Srabstein, J. C., Berkman, B. E., & Pyntikova, E. (2008). Antibullying l egislation: A p ublic h ealth p erspective. Journal of Adolescent Health, 42, 11 20. Stein, J. A., Dukes, R. L., & Warren J. I. (2007). Adolescent male bullies, victims, and bully victims: A comparison of psychosocial and behavioral characteristics. Journal of Pediatric Psychology, 32, 273 282. Stockdale, M. S., Hangaduambo, S., Duys, D., Larson, K., & Sarvela, P. D. (2002) Rural elementary students', parents', and teachers' perceptions of bullying. American Journal of Health Behavior, 26, 266 277. Storch, E. A., Brassard, M. R., & Masia Warner, C. L. (2003a). The relationship of peer victimization to social anxiety and lon eliness in adolescence. Child Study Journal, 33, 1 18. Storch, E. A., Crisp, H., Roberti, J. W., Bagner, D. M., & Masia Warner, C. (2005). Psychometric evaluation of the social experience questionnaire in adolescents: Descriptive data, reliability, and fa ctorial validity. Child Psychiatry and Human Development, 36, 167 176. Storch, E. A., & Ledley, D. R. (2005). Peer victimization and psychosocial adjustment in children: Current knowledge and future directions. Clinical Pediatrics, 44, 29 38. Storch, E. A. Masia Warner, C. L., Crisp, H., & Klein, R. G. (2005). Peer victimization and social anxiety in adolescence: A prospective study. Aggressive Behavior, 31, 437 452.
129 Storch, E. A., Nock, M. K., Masia Warner, C., & Barlas, M. E. (2003b). Peer victimization and social psychological adjustment in Hispanic and African American children. Journal of Child and Family Studies, 12, 439 452. Suhr, D. D. (2006). Exploratory or c onfirmatory f actor a nalysis ? Statistics and d ata a nalysis, SUGI 31 Proceedings, March 26 2 9, 2006. Sullivan, H. S. (1953). The interpersonal theory of psychiatry. New York: Norton. Sullivan, T. N., Farrell, A. D., & Kliewer, W. (2006). Peer victimization in early adolescence: Association between physical and relational victimization and drug us e, aggression, and delinquent behaviors among urban middle school students. Development and Psychopathology, 18, 119 137. Swearer, S., Espelage, D. L., Vaillancourt, T., & Hymel, S. (2010). What can be done about school bullying? Linking research to educat ional practice. Educational Researcher, 39(1), 38 47. The Berkman Center for Internet and Society at Harvard University. (2008). Enhancing child safety and online technologies: Final report of the internet safety technical task force to the m ulti state working group on social networking of state attorneys gener al of the un ited states. Retrieved January 30, 2009 from: http://cyber.law.harvard.edu/sites/cyber.law.harvard.edu/files/ISTTF_Final_Report Executive_Summary.pdf Thunfors, P., & Cornell, D. (2008). The popularity of middle school bullies. Journal of Schoo l Violence, 7, 65 82. Ttofi, M. M., Farrington, D. P., & Baldry, A. C. ( in press ). Effective programs to reduce school bullying. In D.W. Springer and A.R. Roberts (Eds.), Juvenile Justice and Delinquency (pp. 167 185). Sudbury, Mass: Jones and Bartlett. Un derwood, M. K., Galen, B. R., & Paquette, J. A. (2001). Top ten challenges for Social Development, 10, 248 266. U.S. Department of Health and Human Services, Health Resources and Services Administration (2003). U.S. teens in our world. Rockville, MD: Author. Vernberg, E. M., Jacobs, A. K., & Hershberger, H. L. (1999). Peer victimization and attitudes about violence during early adolescence. Journal of Clinical Child Psychology 28, 386 395. Wang, J., Iannotti, R. J., & Nansel, T. R. (2009). School bullying among adolescents in the United States: Physical, verbal, relational, and cyber. Journal of Adolescent Health, 45, 368 375.
130 Watson, D., & Friend, R. (1969). Measurement of so cial evaluative anxiety. Journal of Consulting and Clinical Psychology, 33, 448 457 Weitmann, D. (2006). Internalizing and externalizing symptoms among children with oppositional defiant disorder, conduct disorder or depression. ETD Collection for Pace Un iversity. Retrieved June 7, 2011 from http://digitalcommons.pace.edu/dissertations/AAI3222743 Werner, N. E., & Nixon, C. L. (2005). Normative Beliefs and Relational Aggression: An Investigation of the Cognitive Bases of Adolescent Aggressive Behavior. Jour nal of Youth and Adolescence, 34, 229 243. communication technologies can impact responsible behavior. Retrieved January 30, from http://www.cyberbully.org/cyberbully/docs/disinhibition.pdf Willard, N. (2006). A briefing for educators: Online social networking communities and youth risk. Retrieved January 28, 2009 from http://www.cyberbully.org/cy berbully/docs/youthriskonlinealert.pdf Willard, N. (2007a). Cyberbullying and cyberthreats: Effectively managing Internet use risks in schools. Retrieved January 28, 2009 from http://www.cyberbully.org/cyberbully/docs/cbctpresentation.pdf Willard, N. (2007 b). Cyberbulling legislation and school policies: Where are the 28, 2009 from http://csriu.org Williams, K. R., & Guerra, N. G. (2007). Preval ence and predictors of Internet bullying. Journal of Adolescent Health, 41, 14 21 Windle. M. (1994), Substance use, risky behaviors, and victimization among a US national adolescent sample. Addiction, 89, 175 182. doi: 10.1111/j.1360 0443.1994.tb00876.x Y barra, M. L., & Mitchell, K. J. (2004). Online aggressor/targets, aggressors, and targets: A comparison of associated youth characteristics. Journal of Child Psychology and Psychiatry, 45, 1308 1316. Ybarra, M., & Mitchell, K. (2007). Prevalence and freque ncy of Internet harassment instigation: Implications for adolescent health, Journal of Adolescent Health, 41, 189 195. Yu, S. M., Huang, Z. J., Schwalberg, R. H., Overpeck, M., & Kogan, M. D. (2003). Acculturation and the health and well being of U.S. immi grant adolescents. Journal of Adolescent Health, 33, 479 488.
131 BIOGRAPHICAL SKETCH Jennifer A. Heretick, the youngest of three siblings, grew up in St. Petersburg, Florida and graduated from St. Petersburg Catholic High School in 2003. She attended Villan ova University in Villanova, Pennsylvania and graduated in 2007, earning her B.A in psychology. She attended graduate school at the University of Florida (UF), earning her M.E d. in school psychology in 2009. In 2011 2012, Jennifer completed her year long p redoctoral internship at The Texas Child Study Center a collaboration between Dell Educational Psychology Department, in Austin, TX. She received her Ph.D. from the Universit y of Florida in the summer of 2012, with a specialization in crisis intervention and therapy in the clinical setting. She hopes to obtain her general licensure in psychology and eventually open a private practice specialized in providing services to childr en with anxiety related disorders.