Principles of Cyberbullying Research

Definitions, Measures, and Methodology

Sheri Bauman, Donna Cross, Jenny Walker, Sheri Bauman, Donna Cross, Jenny Walker

• Publisher: Routledge
• Year: 2012
• ISBN:
  9781136192746
• Edition: 1
• Topic: Psychology
• Subtopic: History & Theory in Psychology
• Index: Psychology

In 2010, the International Cyberbullying Think Tank was held in order to discuss questions of definition, measurement, and methodologies related to cyberbullying research. The attendees' goal was to develop a set of guidelines that current and future researchers could use to improve the quality of their research and advance our understanding of cyberbullying and related issues. This book is the product of their meetings, and is the first volume to provide researchers with a clear set of principles to inform their work on cyberbullying. The contributing authors, all participants in the Think Tank, review the existing research and theoretical frameworks of cyberbullying before exploring topics such as questions of methodology, sampling issues, methods employed so far, psychometric issues that must be considered, ethical considerations, and implications for prevention and intervention efforts. Researchers as well as practitioners seeking information to inform their prevention and intervention programs will find this to be a timely and essential resource.

Part I

Introduction

1 Introduction

Jenny Walker, Rhonda G. Craven, and Robert S. Tokunaga

Cyberbullying is a global concern that many governments and schools are struggling to address (Shariff, 2009). While cyberbullying is a relatively recent development, researchers are beginning to gather a body of scholarly literature addressing this issue.¹ This introduction summarizes key findings from this literature to contextualize the remainder of the book, addresses current challenges in cyberbullying research, and considers the ways forward for research. These key findings include similarities and differences between cyberbullying and noncyberbullying; overlap between the two forms of bullying; prevalence; age, grade, and developmental differences; gender; motivation; consequences and correlates for perpetrators, targets, and dual perpetrator/targets, including the relationship between cyberbullying and problem behaviors, and cyberbullying and mental and emotional problems; the content and context of cyberbullying messages; and possible adaptive functions of cyberbullying. The section on challenges in current research addresses conceptual and methodological limitations in cyberbullying literature and discusses the importance of theory building on empirical research. The chapter concludes by reviewing what appears to be working in non-cyberbullying research and how that knowledge can inform research on cyberbullying.

KEY FINDINGS IN THE LITERATURE TO DATE

Similarities and Differences between Cyberbullying and Non-Cyberbullying

Some studies suggest a close correlation between cyberbullying and noncyberbullying (Hinduja & Patchin, 2008, 2009; Ybarra & Mitchell, 2004b), but the “jury is still out” on whether or not cyberbullying is a variation of non-cyberbullying (Bauman, 2011, p. 17 [for an overview of non-cyberbullying versus cyberbullying, see pp. 17–27]). Although some have argued that cyberbullying is similar to non-cyberbullying in a number of significant ways, there are also considerable differences. Researchers (Agatston, Kowalski, & Limber, 2007; Brown, Jackson, & Cassidy, 2006; Kowalski & Limber, 2007; Kowalski, Limber, & Agatston, 2008; McKenna, 2000; McGrath, 2009; Shariff & Hoff, 2007; Slonje & Smith, 2008; Smith, Mahdavi, Carvalho, Fisher, Russell, & Tippet, 2008) have speculated about some of the key differences between non-cyberbullying and cyberbullying:

• The level of disinhibition involved in cyberbullying;

• The potential anonymity and the resultant lack of accountability facilitating antisocial behavior;

• The unique power and control issues resulting from the “flattening” of the playing field in the virtual world;

• The difficulty of escaping cyberbullying because of the 24/7 connection afforded by technology;

• The potential lesser role for bystanders in cyberbullying;

• The lack of immediate verbal and nonverbal feedback;

• The immediate availability and connectivity of technology allowing for more opportunity to “share” cyberbullying;

• The ability of targets to retaliate more easily via technology;

• The possibility that there may be different age trends in utilizing technology;

• The lesser inclination young people may have to tell an adult about being cyberbullied for fear the adults may overreact or remove access to the technology (this is especially true if families have not discussed cyberbullying ahead of time);

• The lesser awareness adults may have of cyberbullying because it can seem less “visible” to them than non-cyberbullying;

• The increased evidence left behind after cyberbullying—text messages, photos, e-mails, social network pages can all be traced.

Overlap between Cyberbullying and Non-Cyberbullying

Many studies indicate that youth use multiple strategies and platforms to bully others, moving quickly and easily between their online and offline worlds (Hinduja & Patchin, 2009; Maher, 2008; Marsh, McGee, Nada-Raja, & Williams, 2010; Perren, Dooley, Shaw, & Cross, 2010). Some research concludes that non-cyberbullies and victims are most likely to be cyberbullies and cybervictims (Hinduja & Patchin, 2008, 2009; Li, 2007a, 2007b; Raskauskas & Stoltz, 2007). Victims of cyberbullying are likely to experience non-cyberbullying as well (Dempsey, Sulkowski, & Nichols, 2009; Hinduja & Patchin, 2007, 2009; Kowalski & Limber, 2007; Perren et al., 2010; Raskauskas & Stoltz, 2007; Smith et al., 2008; Twyman, Saylor, Taylor, & Comeaux, 2009; Vandebosch & Van Cleemput, 2009; Ybarra, Diener-West, & Leaf, 2007). Although some overlap exists between cyberbullying and non-cyberbullying, studies have found that the majority of youth who are cyberbullied do not also report being bullied at school (Ybarra et al., 2007).

A connection may exist between cyberbullying victimization and later perpetration. A number of studies have found that being victimized by cyberbullying was associated with other forms of victimization and the perpetration of bullying in school (Beran & Li, 2007; Burgess-Proctor, Patchin, & Hinduja, 2009; Kowalski & Limber, 2007; Li, 2007a; Perren et al., 2010; Raskauskas & Stoltz, 2007; Twyman et al., 2009; Vandebosch & Van Cleemput, 2009; Ybarra & Mitchell, 2004a). Other studies (Slonje & Smith, 2008), however, conclude that non-cybervictims are not generally found to be cyberbullies.

Prevalence of Cyberbullying

Research indicates that cyberbullying is not uncommon among youth, but prevalence rates vary significantly based on the age and demographic makeup of those studied, how cyberbullying is defined and measured, the time period in question (previous week, month, year, etc.), and the way the data were collected (Patchin & Hinduja, 2012, p. 15). Patchin and Hinduja (2012) provide two illustrative bar graphs detailing cyberbullying victimization and offending rates across 27 peer-reviewed journals. Victimization rates range from 5.5% to 72%, with an average of 24.4%, while perpetration rates range from 3% to 44.1%, with an average of 18% (p. 17). While it is difficult to identify definitive prevalence rates, research suggests that cyberbullying is the most common risk that minors face online (Palfry, boyd, & Sacco, 2009). Hasebrink, Livingstone, Haddon, and Olafsson (2009) provide prevalence rates for cyberbullying and cybervictimization by European country. The approximate median response for aggressive contact (been bullied/harassed/stalked) is 15%–20%, and the approximate median response for aggressive conduct (sent bullying/harassing messages) is 12%. Tokunaga (2010) cited studies that have found, on average, approximately 20%–40% youths who report being victimized by a cyberbully. McGrath (2009) provides a list of prevalence studies that suggest between 4% and 42% of all young people are cyberbullied. Patchin and Hinduja’s (2012) results from seven of their own studies from 2004 to 2010 indicate that, on average, 16.8% of youth reported bullying others (p. 17). Bauman (2011) also provides an Appendix of 38 recent cyberbullying research studies, including prevalence rates, location of the study, sample, findings, and limitations. While prevalence rates are difficult to measure, most studies have found that rates for cyberbullying are lower than for non-cyberbullying (Lenhart, 2007; Li, 2007a; Smith et al., 2008; Williams & Guerra, 2007).

Age, Grade, and Developmental Differences

The majority of research has focused on cyberbullying victimization among minors under the age of 18, although it is worth noting that cyberbullying is not specifically restricted by age (Tokunaga, 2010). Much of the research suggests that cyberbullying (and non-cyberbullying) appears to be most prominent among middle school-aged youth (Cassidy, Jackson, & Brown, 2009; Patchin & Hinduja, 2012; Li, 2007b; Williams & Guerra, 2007). Within that age group, in a study of 3,767 students in grades six through eight, Kowalski and Limber (2007) found that eighth grade students cyberbullied more frequently than sixth or seventh graders, although there were no differences among these grades for cybervictimization. Other studies have found that rates of cyberbullying and victimization are higher for primary school than for secondary school students (Dehue, Bolman, & Vollink, 2008), while still others identify high school students (9th to 12th grade) as more likely to be involved in cyberbullying (Perren et al., 2010; Raskauskas & Stoltz, 2007; Ybarra & Mitchell, 2004). Studies conducted among college age students illustrate that while cyberbullying decreases, it does not diminish entirely among older students (Baldasare, Bauman, Goldman, & Robie, 2012; Kowalski, Giumetti, Schroeder, & Reese, 2012; Smith, Grimm, Lombard, & Wolfe, 2012). The limited data available suggest that the relations between age and cyberbullying follows an inverse U pattern, where rates start out low, increase until about the mid-teenage years, and then begin to decrease over time (Dooley, Cross, Hearn, & Treyvaud, 2009, p. 75).

Gender

Research on gender differences in cyberbullying is “fraught with inconsistent findings” (Tokunaga, 2010, p. 280). Tokunaga’s meta-synthesis of research suggests that neither gender is victimized more than the other (p. 280). Some studies, however, find that girls are as likely, if not more likely, than boys to be involved in cyberbullying (Lenhart, 2007; Wolak, Mitchell, & Finkelhor, 2006; Kowalski & Limber, 2007). Hinduja and Patchin’s (2011) review of 13 published papers notes that 21.8% of girls and 19.5% of boys reported being victims of cyberbullying (p. 20). These same studies found that 14.1% of girls and 18.5% of boys admitted to cyberbullying others (p. 20). Other studies suggest that girls are more likely to report being cyberbullied (Kowalski & Limber, 2007; Lenhart, 2007; Li, 2007b; Mesch, 2009; Slonje & Smith, 2008; Vandebosch & Van Cleemput, 2009), while others indicate that boys are more likely to be cyberbullies (Aricak et al., 2008; Li, 2006, 2007a; Slonje & Smith, 2008; Vandebosch & Van Cleemput, 2009). Still others have found no significant gender differences in cyberbullying (Li, 2006; Patchin & Hinduja, 2006; Smith et al., 2008; Williams & Guerra, 2007), or that gender differences are uncertain (Gross, 2004; Hinduja & Patchin, 2008).

Some studies indicate that when boys bully with cyber tools, they tend to make more physical threats and more sexually explicit comments, while girls are more likely to resort to name-calling and mocking others for their physical appearance (Beale & Hall, 2007; Burgess-Proctor et al., 2009; Rivers & Noret, 2010). Boys also receive more hate-related messages than girls, while girls are subject to more name-calling than boys (Rivers & Noret, 2010). When specifically examining texting as a form of cyberbullying, some results show that girls are more likely to receive unwanted text messages (Marsh et al., 2010), girls are more likely than boys to be identified as cyberbullies (Raskauskas, 2009), or that there are no gender differences for victims (Raskauskas, 2009).

Motivation

Cyberbullying is often a quick and easy option (Lenhart, 2007) that can satisfy a number of needs: asserting power; gaining satisfaction or prestige; acting out aggressive fantasies online; retaliating after being bullied; gaining attention; looking cool and tough; and satisfying jealousy, all of which can be accomplished with a low chance of getting caught (Kowalski et al., 2008, p. 59). Other motivations include “fun” and to relieve boredom (Cross et al., 2009; Li, 2007; Slonje & Smith, 2008; Varjas, Talley, Meyers, Parris, & Cutts, 2010), or because perpetrators feel humorous, popular, and powerful (Mishna, Cook, Gadella, Daciuk, & Solomon, 2010), or feel good (Cross et al., 2009; Patchin & Hinduja, 2006). Varjas et al. (2010) found that high school students more often identified internally motivated reasons for cyberbullying (for example, redirecting feelings) than externally motivated reasons (no consequences or nonconfrontational). Older youth have identified cyberbullying as a way to negotiate and navigate their relationships (Spears, Slee, Owens, & Johnson, 2009), especially with regard to popularity and sexuality (Guerra, Williams, & Sadek, 2011).

Consequences and Correlates

Research indicates that experience with cyberbullying (both as a target and a perpetrator) can have “a significant effect on the emotional and psychological well-being of adolescents” (Patchin & Hinduja, 2012, p. 24). Some research suggests that the consequences of cyberbullying may be similar to those of noncyberbullying (Mason, 2008). Others (Raskauskas & Stoltz, 2007) suggest that cyberbullying may have an even greater impact upon the emotional development of youth than non-cyberbullying because of the potential anonymity of cyberbullying and the resulting power imbalance between the perpetrator and the target. Effects can range from trivial levels of distress and frustration to serious psychosocial and life problems (Tokunaga, 2010, p. 281).

Cybervictimization is associated with increased social anxiety (Dempsey et al., 2009); feelings of anger, frustration, and sadness (Patchin & Hinduja, 2006); an inability to concentrate, which negatively affects grades (Beran & Li, 2007); depreciated levels of self-esteem (Didden et al., 2009; Patchin & Hinduja, 2010); fear, and a clear sense of helplessness (Spears et al., 2009); depression (Didden et al., 2009; Patchin & Hinduja, 2006; Perren et al, 2010; Ybarra et al., 2007); and suicidal ideation and behaviors (Hinduja & Patchin, 2010). Other reported academic problems include increased absences and truancy (Katzer, Fetchenhauer, & Belschak, 2009), increased detentions and suspensions, and carrying weapons onto school campuses (Ybarra et al., 2007). Different forms and features of cyberbullying can have differential impact on the victims (Gerson & Rappaport, 2011, p. 68). For example, young people ranked bullying involving photos or video clips as more harmful than bullying over text messages or e-mail (Slonje & Smith, 2008). Additional research is needed to clarify if specific elements of cybervictimization are associated with poorer mental health outcomes for young people (Perren et al., 2010, p. 8).

Youth who perpetrate cyberbullying also are at higher risk (Mishna et al., 2010). They are more likely to concurrently engage in rule breaking, to have problems with aggression (Ybarra & Mitchell, 2007), and t...