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Article

Self-Regulation as a Protective Factor against Bullying during Early Adolescence

by
Christopher Williams
1,2,*,
Kenneth W. Griffin
3,
Caroline M. Botvin
1,4,
Sandra Sousa
1 and
Gilbert J. Botvin
1,5
1
National Health Promotion Associates, White Plains, NY 10604, USA
2
School of Natural and Social Sciences, SUNY at Purchase College, Purchase, NY 10577, USA
3
Department of Global and Community Health, George Mason University, Fairfax, VA 22030, USA
4
Teachers College, Columbia University, New York, NY 10027, USA
5
Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, USA
*
Author to whom correspondence should be addressed.
Youth 2024, 4(2), 478-491; https://doi.org/10.3390/youth4020033
Submission received: 7 February 2024 / Revised: 18 March 2024 / Accepted: 27 March 2024 / Published: 1 April 2024
(This article belongs to the Special Issue Promoting Resilience, Wellbeing, and Mental Health of Young People)
Versions Notes

Abstract

:
Self-regulation has been shown to play a protective role against youth substance abuse, but less is known about its influence on bullying behavior. In the present study, we examined several forms of bullying (physical, social, cyber, and all forms combined) and roles (bullies, victims, and bully-victims). Students (N = 1977, ages 11 to 13) from 27 middle schools throughout the United States (US) completed an online self-reported assessment of bullying and its hypothesized etiologic determinants. Across the outcomes, analyses revealed that social bullying was most prevalent, followed by physical bullying and cyberbullying. For bullying roles, almost two-thirds of students reported bullying victimization, nearly one-quarter reported bullying perpetration, and one in five students reported both. Of those reporting perpetration, 9 of 10 reported being victimized. Multivariate logistic regression models were used to examine the associations between self-regulation, bystander intervention skills, and bullying. For all forms of bullying combined, self-regulation was protective against bullying perpetration (OR 0.51, 95% CI: 0.42, 0.63) and perpetration/victimization (OR 0.55, 95% CI: 0.44, 0.68), while bystander intervention skills were not protective. Similar patterns emerged for physical, social, and cyberbullying. Collectively, these findings indicate that building self-regulation skills may be a critical component of interventions aimed at preventing bullying among school-aged youth.

1. Introduction

Bullying is a prevalent form of interpersonal aggression and is linked to serious psychological and behavioral problems. Bullying involves intentional and repeated attempts by an individual or group to hurt, humiliate, and cause distress [1,2]. Bullying often occurs among young children and adolescents in school settings. National survey data indicate that bullying is highest among middle school students (sixth through eighth grades), boys, and people who are perceived as different [1,3]. Bullying often involves physical acts including hitting, pushing, or property destruction, but can also be more social in nature, involving name-calling, spreading rumors, and social rejection. Bullying perpetration and victimization are most prevalent in person; however, cyberbullying is also common. Cyberbullying is distinct from in-person bullying, because those who are targeted can feel a deep sense of ongoing victimization due to the permanent and ubiquitous nature of online communications and a seemingly unlimited number of digital onlookers [4,5]. With advances in electronic communications and the saliency of social media in the lives of adolescents, cyberbullying through social networking sites, texts, or instant messaging has gained considerable research attention [5,6,7].

1.1. Bullies, Victims, and Bully-Victims

Bullying, in all its forms, is widespread and has serious consequences for adolescent development [8]. Youth can be involved in bullying incidents as the bully, victim, or bully-victim (those who report both perpetration and victimization). Bullies are at increased risk of becoming involved in delinquency, conduct problems, and crime [9,10] and are more likely to exhibit social problems, aggression, and externalizing behaviors [11,12]. Youth who are victims of bullying have been shown to exhibit a number of important social deficits, including low levels of social acceptance, poor friend and peer support, inadequate social skills and social assertiveness, and greater loneliness [13,14,15]. Victims also have poorer school attendance and academic achievement [16,17] and are at greater risk of depressive symptoms and anxiety [18,19,20]. Several studies have shown that bullying behavior and substance use often co-occur in the same individuals [21,22,23], although the rates vary as a function of bullying roles. Studies have found that bullies are at an elevated risk of using tobacco, alcohol, and other drugs compared to victims [9,21,22,23,24,25,26]. Other research has found that victims are more likely to engage in substance use compared to students who are not involved in bullying [25,26].
One consistent finding from the extant literature suggests that bullying perpetration and victimization are not mutually exclusive categories [27,28,29,30]. However, research on bully-victims is somewhat limited, despite findings indicating that many who bully have also been bullied [31,32]. Bully-victims may be both proactively aggressive and vulnerable and may engage in bullying to cope with their victimization. They have the highest risk of negative outcomes compared to youth who are either victims or bullies, including externalizing behaviors, depressive and other psychological symptoms, low social support, as well as higher rates of school and interpersonal problems [31,33,34].

1.2. Theoretical Models

The influence of individual social competence and peer influences are important considerations in the etiology of adolescent problem behaviors. One of the most popular conceptual models of bullying etiology, both from a scientific and lay perspective, emanates from stress and coping theory, which postulates that this form of interpersonal aggression may function as a mechanism for coping with stressful life events that are common during early adolescence (e.g., a lack of peer acceptance). Accordingly, youth may engage in bullying and other problem behaviors in response to their own victimization [35]. For instance, youth may engage in bullying and substance use to cope with negative school experiences and psychological distress. These adolescents may try to offset negative emotions by behaving forcibly toward a person who is perceived to be vulnerable or less powerful. Another widely cited conceptual model is problem behavior theory [36], which postulates that negative behaviors such as bullying and substance use are learned through a process of modeling, imitation, and reinforcement and that youth with poor intra- and interpersonal social competencies are more vulnerable to negative social influences that promote these behaviors. Problem behavior theory postulates that adolescents with poor competence skills may engage in bullying, substance use, and other problem behaviors to achieve goals that they are unable to meet using other, more prosocial self-management strategies.

1.3. Self-Regulation

Irrespective of one’s role in bullying incidents—bully, victim, or bully-victim—the negative effects of bullying can be chronic, persistent, and last into adulthood [18,33,37]; as such, it is important for youth to develop competencies that may be effective in avoiding or reducing bullying. Furthermore, an important developmental milestone for school-aged youth is to develop and master emotional and behavioral competencies in various social contexts. One such competency is conceptualized as self-regulation—a cognitive, affective, and behavioral regulatory process involving the ability to control one’s thoughts, feelings, and behavior—which has been linked to healthy psychosocial development [38,39]. Several studies have demonstrated strong positive associations between self-regulation and social competence [40], as well as between academic achievement and school engagement [38,41]. Youth with higher self-regulation have been shown to be more effective in setting goals, making decisions, communicating effectively, and managing their stress levels [42,43]. They are less likely to use impulsive or maladaptive solutions, including aggression and interpersonal violence, in response to challenges and expectations from others [44].
Youth with lower self-regulation skills exhibit aggression and externalizing behaviors [45,46], as well as early use of alcohol and cigarettes [38,42,47] and cannabis [48,49]. The literature regarding self-regulation as a predictor or correlate of bullying is scant. However, from the available research, self-regulation appears to be a negative correlate of both bullying victimization and perpetration [38,50,51]. One study revealed no association between self-regulation and bullying perpetration but did report that lower self-regulation was associated with bullying victimization [52]. Youth with poor self-regulation skills may be less likely to achieve goals and prosocial pursuits, making the prospect of engaging in problem behaviors like bullying more attractive and functional.

1.4. Goals of the Present Study

The present study focuses on psychosocial risk and protective factors associated with bullying among young adolescents. We examined whether self-regulation and bystander intervention skills, taught in some contemporary primary prevention programs, are protective against bullying. Our specific goals were to (1) determine the prevalence of various forms of bullying (physical, social, and cyberbullying); (2) examine risk and protective factors for bullying and compare and contrast them for different bullying roles (bullies, victims, and bully-victims); and, (3) assess behavioral and emotional self-regulation skills and their association with bullying. The extent to which bullying can be predicted by self-regulation is understudied. Based on a growing body of research on adolescent affective, social, and behavioral regulatory processes and well-established psychosocial theoretical models, we hypothesized that higher self-regulation skills would be protective against bullying even after controlling for demographic variables and substance use. By identifying the key protective factors for various forms and types of bullying, our findings have the potential to inform the development of effective preventive interventions aimed at bullying among children and adolescents.

2. Materials and Methods

2.1. School Recruitment

Information material describing study procedures and activities were randomly emailed to a nationwide mailing list of principals, teachers, and district-level administrators to recruit schools to participate in the present study. Schools that expressed interest and met eligibility requirements (i.e., ≥25 students, access to computers by students) were enrolled. The final roster included 27 middle schools (6th through 8th grade) from 12 states throughout the US: California, Florida, Indiana, Massachusetts, Michigan, New York, North Dakota, Ohio, Pennsylvania, Texas, Washington, and Wisconsin.

2.2. Participants

Participants included 1977 students who were enrolled in regular education courses. The mean age of participants was 11.67 (SD = 0.76). Most participants were 11 (41.1%), 12 (44.7%), or 13 (10.3%) years old and in the 6th (60.4%) or 7th (33.6%) grades. Students were 55.2% female and predominantly White (44.2%), with smaller numbers who were Black (11.5%), Asian (2.5%), or multiracial (5.8%). Approximately 21.4% of participants reported that they were Latino/Hispanic. Race/ethnicity was missing for 14.6% of participants. A substantial portion of participants (40.6%) reported that they received their school lunch for free or at a reduced price (a proxy indicator of socioeconomic status).

2.3. Procedures

During regular classroom periods, participants completed an online survey that assessed self-reported demographics, bullying perpetration and victimization, and several psychosocial variables that were hypothesized to be associated with bullying. Unique identification codes were used to maintain confidentiality of survey responses. Students were informed that their responses would only be reviewed by research staff and would not be made available to parents or school personnel. The majority of data were collected during the 9-month school terms of 2018 and 2019. Further details on study procedures are outlined in Williams et al. [53]. Prior to any research activities, the study protocol was reviewed and approved by an authorized Institutional Review Board.

2.4. Measures

2.4.1. Outcomes

A total of twenty-two items selected from the Bully Survey were used to assess physical, social, and cyberbullying, and all forms combined [54]. All bullying items included the stem “About how often (if ever)” and were anchored on a 9-point frequency response scale from (1) “never” to (9) “more than once a day.”
Physical Bullying: Physical bullying perpetration was measured using three items: “Have you pushed or shoved another student to make them feel bad?”; “Have you beat up another student to make them feel bad?”; and “Have you broken another student’s belongings on purpose to hurt them?”. Physical bullying victimization was measured using the same three items, but reworded to reflect victimization (e.g., “Have you been pushed or shoved by another student on purpose?”).
Social Bullying: Social bullying perpetration was measured using four items: “Have you excluded or ignored another student on purpose?”; “Have you spread rumors about another student to try to hurt their reputation?”; “Have you made fun of other students?”; and “Have you said mean things about other students behind their backs?”. Social bullying victimization was measured using the same four items, but reworded to reflect victimization (e.g., “Have other students excluded you or ignored you on purpose?”).
Cyberbullying: Cyberbullying perpetration was measured using four items: “Have you written or commented mean things about another student online?”; “Have you sent unwanted messages to another student online?”; “Have you threatened to post someone’s personal information, photos, or videos online in order to hurt them?”; and “Have you posted someone’s personal information, photos, or videos online in order to hurt them?”. Cyberbullying victimization was measured using the same four items, but reworded to reflect victimization (e.g., “Have other students written or commented mean things about you online?”). Cronbach alpha for the 11 bullying perpetration items was 0.94, and for the 11 bullying victimization items, it was 0.91.
For each type of bullying (physical, social, cyber), we counted the number of items that each student endorsed for the past year in terms of perpetration (bullies), victimization (victims), and both perpetration and victimization (bully-victims). Summary scores representing “all forms” or overall bullying were created based on the sum of physical, social, and cyberbullying items combined.

2.4.2. Predictor and Control Variables

Predictor variables included self-regulation skills, bystander intervention skills, and substance use behavior.
Self-regulation skills: A total of 10 items (alpha = 0.77) with established psychometric properties were used to assess self-regulation [55]. Respondents indicated the extent to which they agreed or disagreed with statements using a five-point Likert scale with response options ranging from (1) “strongly disagree” to (5) “strongly agree”. Three items assessed goal-setting skills (e.g., “I set personal goals for myself.”); two items assessed decision-making skills (e.g., “If I need to make an important decision, I take the time to clarify the decision, consider alternatives, and choose the best option.”); and five items assessed relaxation skills (e.g., “To cope with anxiety, I relax all the muscles in my body, starting with my feet and legs.”). For each skill, a mean summary score was calculated that ranged from 1 to 5, with higher scores representing better skills. An overall score was calculated based on the participant’s responses to all ten items.
Bystander intervention skills: With the stem “If I saw someone being bullied,” students answered three questions including: (1) “I would cause a distraction to make it stop”; (2) “I would look for someone who could help me intervene”; and (3) “I would report it to a teacher, parent, or other adult” using responses that ranged from (1) “strongly disagree” to (5) “strongly agree”.
Substance use: Four items assessed respondents’ frequency of alcohol use, vaping/e-cigarette use, cigarette use, and marijuana use. All used the stem “About how often (if ever) do you …” with a nine-point scale that ranged from (1) “never” to (9) “more than once a day”. A summary score was calculated that represented the number of substances used in the past year.
Control variables included gender, age, and race/ethnicity, which were assessed using standard survey items. Dummy codes were created for gender and race/ethnic background, with female and non-White as reference groups. We also assessed academic performance by asking participants “What grades do you normally get in school?”, with response options ranging from (1) “Mostly As” to (5) “Ds or lower”. A dummy code was created so that lower grades were the reference group (C and below).

2.5. Statistical Analysis

Data analyses included an examination of various forms and roles of bullying among young adolescents. First, prevalence rates for each behavior were calculated. Secondly, multivariate logistic regression analyses examined how self-regulation skills, bystander intervention skills, and substance use were associated with the bullying outcomes while adjusting for demographic variables and academic performance. Significance was defined as p < 0.05 using a two-tailed alpha. All analyses were conducted using IBM SPSS Statistics v 20 [56].

3. Results

3.1. Prevalence Rates

Of the entire sample, nearly two-thirds (63.9%) reported victimization by bullying in the past year, 43.7% reported victimization without perpetration, 22.8% reported perpetration, 2.5% reported perpetration without victimization, 20.2% reported both victimization and perpetration (bully-victims), and 33.5% reported neither. Victimization was very common among perpetrators, so of those who reported perpetration (n = 450), the vast majority (400 of 450, or 88.9%) also reported being victimized. Only 50 of 450 (11.1%) reported perpetration without also reporting victimization.
The most reported form of bullying in the past year was social bullying victimization (55.9%), followed by physical bullying victimization (44.9%) and cyberbullying victimization (21.1%) (shown in Table 1). Perpetration was substantially lower relative to victimization. The most reported form of perpetration was social bullying perpetration (20.9%), followed by physical bullying perpetration (9.4%) and cyberbullying perpetration (6.9%). Across all forms and roles of bullying, males reported higher rates than females, with the exception of cyberbullying and social bullying victimization. For all forms combined, multiracial students reported higher rates of bullying perpetration and victimization.

3.2. Logistic Regression Analyses

For each behavioral outcome, the predictor and control variables were entered into a logistic regression equation. The odd ratios (ORs) and 95% confidence intervals (CIs) for each individual variable are shown in Table 2 separately for bullying perpetration (bullies), victimization (victims), and perpetration/victimization (bully-victims) and for the different forms of bullying (overall or all forms combined, physical, social, and cyberbullying).
For perpetration, substance use increased the odds of all forms of bullying combined (OR 2.37, 95% CI: 1.94, 2.90, p < 0.001), physical (OR 2.63, 95% CI: 2.17, 3.18, p < 0.001) and social (OR 2.39, 95% CI: 1.96, 2.91, p < 0.001) bullying, as well as cyberbullying (OR 3.11, 95% CI: 2.54, 3.81, p < 0.001). Conversely, self-regulation decreased the odds of bullying perpetration. Youth who reported more self-regulation had decreased odds of all forms of bullying combined (OR 0.51, 95% CI: 0.42, 0.63, p < 0.001), physical (OR 0.49, 95% CI: 0.36, 0.67, p < 0.001) and social (OR 0.54, 95% CI: 0.44, 0.67, p < 0.001) bullying, as well as cyberbullying (OR 0.44, 95% CI: 0.30, 0.63, p < 0.001). Bystander intervention skills were not associated with bullying perpetration when controlling for gender, race/ethnicity, and academic performance.
For victimization, substance use increased the odds of all forms of bullying combined (OR 1.49, 95% CI: 1.21, 1.84, p < 0.001), physical (OR 1.69, 95% CI: 1.40, 2.04, p < 0.001) and social (OR 1.44, 95% CI: 1.20, 1.73, p < 0.001) bullying, as well as cyberbullying (OR 2.10, 95% CI: 1.75, 2.52, p < 0.001). By contrast, self-regulation only decreased the odds of bullying victimization for cyberbullying. Youth who reported more self-regulation had decreased odds of cyberbullying victimization (OR 0.66, 95% CI: 0.54, 0.82, p < 0.001). Self-regulation skills were not associated with other forms of victimization. Bystander intervention skills were not associated with bullying victimization when controlling for gender, race/ethnicity, and academic performance.
For perpetration and victimization (bully-victims), substance use increased the odds of all forms of bullying combined (OR 2.12, 95% CI: 1.76, 2.54, p < 0.001), physical (OR 2.56, 95% CI: 2.12, 3.08, p < 0.001) and social (OR 2.16, 95% CI: 1.80, 2.58, p < 0.001) bullying, as well as cyberbullying (OR 2.93, 95% CI: 2.41, 3.57, p < 0.001). Conversely, self-regulation decreased the odds of bullying perpetration/victimization. Specifically, youth who reported more self-regulation skills had decreased odds of all forms combined (OR 0.55, 95% CI: 0.44, 0.68, p < 0.001), physical (OR 0.54, 95% CI: 0.38, 0.76, p < 0.01) and social (OR 0.58, 95% CI: 0.46, 0.72, p < 0.001) bullying, as well as cyberbullying (OR 0.48, 95% CI: 0.32, 0.73, p < 0.01). Bystander intervention skills were not associated with bullying perpetration/victimization when controlling for gender, race/ethnicity, and academic performance.

4. Discussion

Bullying is a prevalent form of interpersonal youth violence with negative consequences that can persist into adulthood. Because bullying victimization can occur chronically from childhood through the adolescent years for some, the negative consequences can be profoundly disruptive to normative development. Although bullying is most prevalent in school, it is not limited to formal class settings. Indeed, bullying is most likely to occur in settings where there is less direct and immediate supervision by school personnel. Students who are frequently bullied often avoid less supervised settings and activities for fear of being victimized. This may prevent bullied students from attending extracurricular activities that offer opportunities to develop non-academic interests (e.g., sports, clubs) [57]. This avoidance represents lost opportunities to develop important social skills, nurture new friendships, and bond with peers, and these social deficits can carry forward to adult relationships. Finally, among parents and caregivers, bullying is a major source of concern [58]. Among teachers, bullying is ranked as the most pressing school safety concern nationally. A recent report conducted by the Rand Corporation indicates that teachers across the US viewed bullying as a more important concern than gun violence in the US [59].
A preponderance of research on bullying has focused on bullying perpetration and victimization. Fewer studies have looked at youth who are both perpetrators and victims. In this study, we sought to examine the prevalence and predictors of the three most common bullying roles in an early adolescent sample: bullies, victims, and bully-victims. The findings from this study and other similar research illustrate several common misconceptions about bullying. One such misconception is that bullying only impacts a small number of students. In the present study, we found that almost two in three youth were directly involved in bullying in some capacity over the past year. This is considerably larger than recent meta-analytic findings that 35% of adolescents are involved in bullying situations in some role [60]. While prevalence estimates vary across studies due to different time frames and definitions of bullying, it is clear that bullying is a widespread phenomenon that impacts many teens, who are directly involved as bullies, victims, or both. Also consistent with previous research, we observed that many more students reported victimization relative to perpetration [61,62]. A second common misconception is that bullying perpetrators are relentless victimizers. In the present study, we found that victimization was very common among perpetrators, with almost 9 in 10 perpetrators also reporting being victimized. This is consistent with previous research demonstrating that many of those who victimize others are indeed victimized themselves [31,63,64]. This suggests that many bully perpetrators understand personally what it feels like to be victimized, which should be a focus of future research, because it may shed light on the role of empathy in prevention efforts.
In addition to examining the prevalence and predictors of different bullying roles, the present study contributes to the literature by also factoring in different forms of bullying, including physical, social, and cyberbullying. The preponderance of bullying studies does not disaggregate prevalence rates by form of bullying [61,65,66], or these studies limit their analysis to bully roles without consideration of bullying forms [61,66]. We found that social bullying victimization was most prevalent, followed by physical and cyberbullying victimization. These results are consistent with other studies assessing physical and cyberbullying victimization and perpetration [61,65,66].
An important contribution of the present study was a comparison of physical and social bullying, as well as cyberbullying. With the ubiquity of digital communications, public attention has increasingly focused on cyberbullying, as youth are gaining access to mobile phones at earlier ages [67]. Furthermore, in the aftermath of the COVID-19 pandemic, young adolescents are increasingly isolated and spend an inordinate amount of time on social media sites [4,47]. Findings from the present study suggest that while cyberbullying is less prevalent than in-person forms of bullying, the risk and protective factors are similar across each of these forms of bullying. In particular, self-regulation skills were protective against all forms of bullying, including cyberbullying. This has important implications for prevention, in that the same prevention approach can potentially address multiple forms of bullying behavior.
Competence enhancement training may be a fruitful approach in this context, as it is grounded in the recognition that a lack of social competence skills for coping with life challenges increases vulnerability to internal and external influences that promote bullying and other problem behaviors. Our findings provide empirical support for stress and coping theory, which suggests that youth may engage in problem behaviors in response to their own victimization [35]. As such, youth may engage in bullying to cope with school trauma or perceived shortcomings. Problem behavior theory [36] is also relevant for interpreting our findings, as it postulates that when youth do not have socially acceptable ways to achieve desired goals or gain esteem from their friends and peer group, they are more likely to engage in substance use and bullying as a functional behavioral strategy for identity formation and esteem enhancement [36,68]. Collectively, these findings offer empirical evidence of the functional role that these problem behaviors may hold for at-risk youth as they seek to achieve a sense of maturity and key developmental milestones.
Another goal of the present study was to examine whether general personal competency (i.e., self-regulation skills) and bullying-specific bystander intervention skills were protective against various roles of bullying. In the present study, self-regulation was robustly protective against bullying perpetration and bullying perpetration/victimization. Notably, bystander intervention skills were unrelated to bullying outcomes. We also found that self-regulation skills were less protective for victimization. This may be because individual skills and characteristics have a more limited role in helping one avoid victimization, which is less under one’s personal control. The protective role of self-regulation skills persisted even after controlling for demographic variables, bystander intervention skills, and substance use. Our findings suggest that promoting the development of self-regulation skills may decrease the desire to perpetrate bullying and ultimately reduce bullying in all its forms (physical, social, and cyberbullying). Furthermore, because substance abuse often co-occurs with bullying, we examined the extent to which self-regulation was protective against bullying after controlling for early-stage substance use. Others have found that youth with lower self-regulation skills are at risk of premature alcohol use and cigarette smoking [38,42,47] and cannabis use [48,49]. Our analysis confirmed the hypothesis that higher self-regulation would be protective against bullying perpetration, even when controlling for young adolescent substance use. More research examining the influence of self-regulatory processes on young adolescent bullying with consideration of related problem behaviors is warranted.

4.1. Implications for Prevention Education

Competency in life skills has been linked to more positive life outcomes, and preventive interventions that teach such skills have been consistently shown to enhance child development [69]. The findings from this study have several implications for prevention science and practice. First, to intervene as bystanders to bullying, during threatening incidents, individuals should be able to identify the early signs of bullying, classify incidents as requiring intervention, take responsibility for acting, and demonstrate a sufficient level of self-efficacy [70]. Having the ability to intervene, distract, and seek help from authority figures in bullying situations may be an important competency for youth to master. A recent meta-analysis indicates that many bullying prevention programs include training in bystander intervention skills, which have been associated with lower bullying [71]. However, in the present study, we did not find bullying intervention skills to be protective against various forms or roles of bullying. This finding suggests that in the absence of social competency training, programs that emphasize bystander intervention training may be less effective than more comprehensive approaches. Broad competence enhancement approaches that integrate self-regulation skills training may lead to greater reductions in bullying than bystander intervention training alone. One preventive intervention found that adolescents who were exposed to behavioral training in social and interpersonal competencies including a variety of self-regulation strategies, when combined with bystander intervention skills training, were found to have reduced bullying perpetration compared to those who had not received such training [53]. Other school-based interventions indicate the importance of skills training in leadership training [72], empathy [73], and conflict resolution [74]. Interventions that address common risk and protective factors by teaching self-regulation and other life skills hold promise for preventing multiple problem behaviors.

4.2. Limitations and Strengths

This study has important public health relevance for its examination of risk and protective factors that are linked to bullying. Our study is among the first to examine self-regulation across different forms and roles of bullying. There are, however, important limitations to be considered. First, the cross-sectional design precludes the ability to investigate the causality or temporal sequence among variables. Secondly, although middle schools were recruited from diverse geographical regions across the country, they are a convenience sample and therefore may not be entirely representative of the US population. Thirdly, the study was based on students’ self-reporting, and therefore, the significant relationships among the variables may partly reflect shared method variance.
Despite these limitations, this study had several notable strengths. First, the sample was diverse in terms of important demographic characteristics (e.g., gender, academic performance, race/ethnicity). Secondly, we used validated measures to assess self-regulation and bullying. Thirdly, this study provided a more comprehensive examination of different bullying forms and roles within the same study, while most of the extant literature is siloed, with research examining perpetration, victimization, and victimization/perpetration in separated studies. Fourthly, we used a series of multivariate analyses to control for potential confounders between the hypothesized risk and protective factors.

5. Conclusions

Bullying is a serious threat to youth wellbeing and its effect can have long-term negative physical, mental, and emotional outcomes. The results of the current study present several important findings with implications for research and practice. First, this study shows that bullying is a widespread phenomenon that impacts many teens, who are directly involved as bullies, victims, or both. Second, perpetration and victimization are not mutually exclusive—students who bully others have often been victims themselves. Third, the most prevalent form of bullying in this sample was social bullying, followed by physical bullying and cyberbullying. Fourth, while cyberbullying is less prevalent than in-person bullying, the risk and protective factors are similar for each form of bullying. Fifth, self-regulation skills were protective for all forms of bullying, including cyberbullying. Sixth, bystander intervention skills were not found to be protective. Thus, while it may be intuitively appealing to focus on teaching bystander intervention skills to reduce bullying, these skills may not be sufficient in and of themselves. Instead, the results of this study suggest that effective approaches for preventing bullying should include an emphasis on enhancing self-regulation, as well as teaching emotional, cognitive, and behavioral skills associated with bullying and other problem behaviors that emerge during early adolescence. The findings from this study are timely and important given the growing concern for bullying and the critical need for effective prevention approaches. Taken together, these findings suggest the possibility of preventing multiple forms of bullying and other problem behaviors with a single approach that targets shared risk and protective factors.

Author Contributions

Conceptualization, C.W. and K.W.G.; methodology, C.W. and K.W.G.; formal analysis, C.W. and K.W.G.; writing—original draft preparation, C.W.; writing—review and editing, K.W.G., G.J.B., S.S. and C.M.B.; supervision, C.W.; funding acquisition, C.W., K.W.G. and G.J.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of Child and Human Development, Grant Number: R44HD074319.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board at National Health Promotion Associates (protocol code 4319-2021 on 2 February 2017).

Informed Consent Statement

Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the National Institutes of Health (NIH) guidance and institutional requirements.

Data Availability Statement

The raw data used in this study are available from the corresponding author upon request.

Acknowledgments

The authors wish to acknowledge Megan Wolff, Lynn Ibekwe, and Eric Kondel for their assistance with the conduct of this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Burr, R.; Kemp, J.; Wang, K. Crime, Violence, Discipline, and Safety in the U.S. Public Schools: Findings from the School Survey on Crime and Safety: 2021–2022 (NCES 2024-043); U.S. Department of Education: Washington, DC, USA; National Center for Education Statistics: Washington, DC, USA, 2024. Available online: https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2024043 (accessed on 2 February 2024).
  2. Centers for Disease Control and Prevention. Violence Prevention: Fast Fact: Preventing Bullying. Available online: https://www.cdc.gov/violenceprevention/youthviolence/bullyingresearch/fastfact.html. (accessed on 15 November 2022).
  3. Gower, A.L.; Rider, G.; Brown, C.; Eisenberg, M.E. Diverse sexual and gender identity, bullying, and depression among adolescents. Pediatrics 2022, 149, e2021053000. [Google Scholar] [CrossRef] [PubMed]
  4. Barlett, C.P.; Simmers, M.M.; Roth, B.; Gentile, D. Comparing cyberbullying prevalence and process before and during the COVID-19 pandemic. J. Soc. Psychol. 2021, 161, 408–418. [Google Scholar] [CrossRef] [PubMed]
  5. Patchin, J.W.; Hinduja, S. Cyberbullying among tweens in the United States: Prevalence, impact, and helping behaviors. J. Early Adolesc. 2022, 42, 414–430. [Google Scholar] [CrossRef]
  6. Meldrum, R.C.; Patchin, J.W.; Young, J.T.; Hinduja, S. Bullying victimization, negative emotions, and digital self-harm: Testing a theoretical model of indirect effects. Deviant Behav. 2022, 43, 303–321. [Google Scholar] [CrossRef]
  7. Englander, E. Childhood access to technology and cyberbullying. J. Pediatr. Pediatr. Med. 2019, 3, 1–4. [Google Scholar] [CrossRef]
  8. Biswas, T.; Scott, J.G.; Munir, K.; Thomas, H.J.; Huda, M.M.; Hasan, M.M.; de Vries, T.D.; Baxter, J.; Mamun, A.A. Global variation in the prevalence of bullying victimisation amongst adolescents: Role of peer and parental supports. EClinicalMedicine 2020, 20, 100276. [Google Scholar] [CrossRef] [PubMed]
  9. Arcadepani, F.B.; Eskenazi, D.Y.G.; Fidalgo, T.M.; Hong, J.S. An exploration of the link between bullying perpetration and substance use: A review of the literature. Trauma Violence Abus. 2021, 22, 207–214. [Google Scholar] [CrossRef] [PubMed]
  10. Espelage, D.L.; Van, R.M.J.; Holt, M.K. Trajectories of bullying perpetration across early adolescence: Static risk factors, dynamic covariates, and longitudinal outcomes. Psychol. Viol. 2018, 8, 141–150. [Google Scholar] [CrossRef]
  11. Morgan, P.L.; Farkas, G.; Woods, A.D.; Wang, Y.; Hillemeier, M.M.; Oh, Y. Factors Predictive of Being Bullies or Victims of Bullies in US Elementary Schools. Sch. Ment. Health 2023, 15, 566–582. [Google Scholar] [CrossRef] [PubMed]
  12. Ye, Z.; Wu, D.; He, X.; Ma, Q.; Peng, J.; Mao, G.; Feng, L.; Tong, Y. Meta-analysis of the relationship between bullying and depressive symptoms in children and adolescents. BMC Psychiatry 2023, 23, 215. [Google Scholar] [CrossRef] [PubMed]
  13. Ladd, G.W.; Kochenderfer-Ladd, B. Research in educational psychology: Social exclusion in school. In Social Exclusion; Riva, P., Eck, J., Eds.; Springer: Cham, Switzerland, 2016. [Google Scholar] [CrossRef]
  14. Almeida, T.S.; Ribeiro, O.; Freitas, M.; Rubin, K.H.; Santos, A.J. Loneliness and social functioning in adolescent peer victimization. Front. Psychol. 2021, 12, 664079. [Google Scholar] [CrossRef] [PubMed]
  15. Sentse, M.; Kretschmer, T.; Salmivalli, C. The longitudinal interplay between bullying, victimization, and social status: Age-related and gender differences. Soc. Dev. 2015, 24, 659–677. [Google Scholar] [CrossRef]
  16. Laith, R.; Vaillancourt, T. The temporal sequence of bullying victimization, academic achievement, and school attendance: A review of the literature. Aggress. Violent Behav. 2022, 64, 101722. [Google Scholar] [CrossRef]
  17. Riffle, L.N.; Kelly, K.M.; Demaray, M.L.; Malecki, C.E.; Santuzzi, A.M.; Rodriguez-Harris, D.J.; Emmons, J.D. Associations among bullying role behaviors and academic performance over the course of an academic year for boys and girls. J. Sch. Psychol. 2021, 86, 49–63. [Google Scholar] [CrossRef]
  18. Klomek, A.B.; Sourander, A.; Elonheimo, H. Bullying by peers in childhood and effects on psychopathology, suicidality, and criminality in adulthood. Lancet Psychiatry 2015, 2, 930–941. [Google Scholar] [CrossRef] [PubMed]
  19. Biagioni, S.; Baldini, F.; Baroni, M.; Cerrai, S.; Melis, F.; Potente, R.; Scalese, M.; Molinaro, S. Adolescents’ psychoactive substance use during the first COVID-19 lockdown: A cross sectional study in Italy. In Child & Youth Care Forum; Springer: New York, NY, USA, 2023; Volume 52, No. 3; pp. 641–659. [Google Scholar]
  20. Moore, S.E.; Norman, R.E.; Suetani, S.; Thomas, H.J.; Sly, P.D.; Scott, J.G. Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis. World J. Psychiatry 2017, 7, 60–76. [Google Scholar] [CrossRef] [PubMed]
  21. Afifi, T.O.; Taillieu, T.; Salmon, S.; Davila, I.G.; Stewart-Tufescu, A.; Fortier, J.; Struck, S.; Asmundson, G.J.G.; Sareen, J.; MacMillan, H.L. Adverse childhood experiences (ACEs), peer victimization, and substance use among adolescents. Child Abus. Negl. 2020, 106, 104504. [Google Scholar] [CrossRef] [PubMed]
  22. Durand, V.; Hennessey, J.; Wells, D.S.; Crothers, L.M.; Kolbert, J.B.; Lipinski, J.; Hughes, T.L. Bullying and substance use in children and adolescents. J. Addict. Res. Ther. 2013, 4, 10–4172. [Google Scholar]
  23. Radliff, K.M.; Wheaton, J.E.; Robinson, K.; Morris, J. Illuminating the relationship between bullying and substance use among middle and high school youth. Addict. Behav. 2012, 37, 569–572. [Google Scholar] [CrossRef]
  24. Baiden, P.; Tadeo, S.K. Examining the association between bullying victimization and prescription drug misuse among adolescents in the United States. J. Aff. Disord. 2019, 259, 317–324. [Google Scholar] [CrossRef] [PubMed]
  25. Gaete, J.; Tornero, B.; Valenzuela, D.; Rojas-Barahona, C.A.; Salmivalli, C.; Valenzuela, E.; Araya, R. Substance use among adolescents involved in bullying: A cross-sectional multilevel study. Front. Psychol. 2017, 8, 1056. [Google Scholar] [CrossRef] [PubMed]
  26. Valdebenito, S.; Ttofi, M.; Eisner, M. Prevalence rates of drug use among school bullies and victims: A systematic review and meta-analysis of cross-sectional studies. Aggress. Violent Behav. 2015, 23, 137–146. [Google Scholar] [CrossRef]
  27. Baldry, A.C.; Farrington, D.P.; Sorrentino, A. School bullying and cyberbullying among boys and girls: Roles and overlap. J. Aggress. Maltreatment Trauma 2017, 26, 937–951. [Google Scholar] [CrossRef]
  28. Veenstra, R.; Lindenberg, S.; Oldehinkel, A.J.; De Winter, A.F.; Verhulst, F.C.; Ormel, J. Bullying and victimization in elementary schools: A comparison of bullies, victims, bully/victims, and uninvolved preadolescents. Dev. Psychol. 2005, 41, 672. [Google Scholar] [CrossRef] [PubMed]
  29. Haltigan, J.D.; Vaillancourt, T. Joint trajectories of bullying and peer victimization across elementary and middle school and associations with symptoms of psychopathology. Dev. Psychol. 2014, 50, 2426–2436. [Google Scholar] [CrossRef] [PubMed]
  30. Espelage, D.L.; Swearer, S.M. Research on school bullying and victimization: What have we learned and where do we go from here? Sch. Psychol. Rev. 2003, 32, 365–383. [Google Scholar] [CrossRef]
  31. Imuta, K.; Song, S.; Henry, J.D.; Ruffman, T.; Peterson, C.; Slaughter, V. A meta-analytic review on the social–emotional intelligence correlates of the six bullying roles: Bullies, followers, victims, bully-victims, defenders, and outsiders. Psychol. Bull 2022, 148, 199. [Google Scholar] [CrossRef]
  32. Lereya, S.T.; Samara, M.; Wolke, D. Parenting behavior and the risk of becoming a victim and a bully/victim: A meta-analysis study. Child Abus. Negl. 2013, 37, 1091–1108. [Google Scholar] [CrossRef] [PubMed]
  33. Wolke, D.; Lereya, S.T. Long-term effects of bullying. Arch. Dis. Child. 2015, 100, 879–885. [Google Scholar] [CrossRef] [PubMed]
  34. Simmons, J.A.; Antshel, K.M. Bullying and depression in youth with ADHD: A systematic review. In Child & Youth Care Forum; Springer: New York, NY, USA, 2021; Volume 50, pp. 379–414. [Google Scholar]
  35. Lazarus, R.S. Coping theory and research: Past, present, and future. Psychosom. Med. 1993, 55, 234–247. [Google Scholar] [CrossRef] [PubMed]
  36. Jessor, R.; Jessor, S.L. Problem Behavior and Psychosocial Development. A Longitudinal Study of Youth; Academic Press: New York, NY, USA, 1977. [Google Scholar]
  37. Fergusson, D.M.; Boden, J.M.; Horwood, L.J. Childhood self-control and adult outcomes: Results from a 30-year longitudinal study. J. Am. Acad. Child Adolesc. Psychiatry 2013, 52, 709–717. [Google Scholar] [CrossRef]
  38. Robson, D.A.; Allen, M.S.; Howard, S.J. Self-regulation in childhood as a predictor of future outcomes: A meta-analytic review. Psychol. Bull. 2020, 146, 324. [Google Scholar] [CrossRef] [PubMed]
  39. Griffin, K.W.; Lowe, S.R.; Acevedo, B.P.; Botvin, G.J. Affective self-regulation trajectories during secondary school predict substance use among urban minority young adults. J. Child Adolesc. Subst. Abus. 2015, 24, 228–234. [Google Scholar] [CrossRef]
  40. Russell, B.S.; Lee, J.O.; Spieker, S.; Oxford, M.L. Parenting and preschool self-regulation as predictors of social competence in 1st grade. J. Res. Child Educ. 2016, 30, 153–169. [Google Scholar] [CrossRef]
  41. Edossa, A.K.; Schroeders, U.; Weinert, S.; Artelt, C. The development of emotional and behavioral self-regulation and their effects on academic achievement in childhood. Int. J. Behav. Dev. 2018, 42, 192–202. [Google Scholar] [CrossRef]
  42. Epstein, J.A.; Griffin, K.W.; Botvin, G.J. Competence skills help deter smoking among inner city adolescents. Tob. Control 2000, 9, 33–39. [Google Scholar] [CrossRef] [PubMed]
  43. Griffin, K.W.; Botvin, G.J.; Doyle, M.M.; Diaz, T.; Epstein, J.A. A six-year follow-up study of determinants of heavy cigarette smoking among high-school seniors. J. Behav. Med. 1999, 22, 271–284. [Google Scholar] [CrossRef] [PubMed]
  44. Griffin, K.W.; Scheier, L.M.; Botvin, G.J. Developmental trajectories of self-management skills and adolescent substance use. Health Addict. 2009, 9, 3–16. [Google Scholar]
  45. Lonigan, C.J.; Allan, D.M.; Phillips, B.M. Examining the predictive relations between two aspects of self-regulation and growth in preschool children’s early literacy skills. Dev. Psychol. 2017, 53, 63. [Google Scholar] [CrossRef]
  46. Finigan-Carr, N.M.; Cheng, T.L.; Gielen, A.; Haynie, D.L.; Simons-Morton, B. Using the theory of planned behavior to predict aggression and weapons carrying in urban African American early adolescent youth. Health Educ. Behav. 2015, 42, 220–230. [Google Scholar] [CrossRef]
  47. Hennessy, E.A.; Johnson, B.T.; Acabchuk, R.L.; McCloskey, K.; Stewart-James, J. Self-regulation mechanisms in health behavior change: A systematic meta-review of meta-analyses, 2006–2017. Health Psychol. Rev. 2020, 14, 6–42. [Google Scholar] [CrossRef] [PubMed]
  48. Egerton, G.A.; Colder, C.R.; Lee, Y. Testing the dual process model of adolescent cannabis use with prospective three-way interactions between self-regulation, negative outcome expectancies, and implicit cannabis attitudes. Addict. Behav. 2021, 118, 106902. [Google Scholar] [CrossRef] [PubMed]
  49. Holtmann, M.; Buchmann, A.F.; Esser, G.; Schmidt, M.H.; Banaschewski, T.; Laucht, M. The child behavior checklist-dysregulation profile predicts substance use, suicidality, and functional impairment: A longitudinal analysis. J. Child Psychol. Psychiatry 2011, 52, 139–147. [Google Scholar] [CrossRef] [PubMed]
  50. Montroy, J.J.; Bowles, R.P.; Skibbe, L.E.; Foster, T.D. Social skills and problem behaviors as mediators of the relationship between behavioral self-regulation and academic achievement. Early Child. Res. Q. 2014, 29, 298–309. [Google Scholar] [CrossRef]
  51. Garner, P.W.; Hinton, T.S. Emotional display rules and emotion self-regulation: Associations with bullying and victimization in community-based after-school programs. J. Community Appl. Soc. Psychol. 2010, 20, 480–496. [Google Scholar] [CrossRef]
  52. Toblin, R.L.; Schwartz, D.; Gorman, A.H.; Abou-ezzeddine, T. Social–cognitive and behavioral attributes of aggressive victims of bullying. J. Appl. Dev. Psychol. 2005, 26, 329–346. [Google Scholar] [CrossRef]
  53. Williams, C.; Griffin, K.W.; Botvin, C.; Sousa, S.; Botvin, G.J. Effectiveness of digital health tools to prevent bullying among middle school students. Adolescents 2023, 3, 110–130. [Google Scholar] [CrossRef]
  54. Swearer, S.M.; Turner, R.K.; Givens, J.E.; Pollack, W.S. “You’re so gay!”: Do different forms of bullying matter for adolescent males? Sch. Psychol. Rev. 2008, 37, 160–173. [Google Scholar] [CrossRef]
  55. Epstein, J.A.; Botvin, G.J.; Diaz, T.; Baker, E.; Botvin, E.M. Reliability of social and personal competence measures for adolescents. Psychol. Rep. 1997, 81, 449–450. [Google Scholar] [CrossRef] [PubMed]
  56. IBM Corp. IBM SPSS Statistics for Windows, Version 28.0; IBM Corp: Armonk, NY, USA, 2023. [Google Scholar]
  57. Sheridan, S.; Clary, L.K.; Webb, L.; Stuart, E.A.; Mendelson, T. Associations of extracurricular activity participation with bullying victimization among US middle and high school students: A nationally representative sample. J. Sch. Violence 2022, 21, 475–490. [Google Scholar] [CrossRef]
  58. Stives, K.L.; May, D.C.; Mack, M.; Bethel, C.L. Understanding responses to bullying from the parent perspective. In Frontiers in Education; Frontiers Media SA: Lausanne, Switzerland, 2021; Volume 6, p. 642367. [Google Scholar]
  59. Jackson, B.A.; Diliberti, M.K.; Moore, P.; Schwartz, H.L. Teachers’ Views on School Safety: Consensus on Many Security Measures, But Stark Division about Arming Teachers. American Educator Panels; Research Report. RR-A2641-1; RAND Corporation: Santa Monica, CA, USA, 2023. [Google Scholar]
  60. Modecki, K.L.; Minchin, J.; Harbaugh, A.G.; Guerra, N.G.; Runions, K.C. Bullying prevalence across contexts: A meta-analysis measuring cyber and traditional bullying. J. Adolesc. Health 2014, 55, 602–611. [Google Scholar] [CrossRef] [PubMed]
  61. Flowers, J.; Marr, D.; McCleary, D. Bullying Prevalence: An Online Survey of Adolescents. J. Appl. Sch. Psychol. 2021, 37, 377–390. [Google Scholar] [CrossRef]
  62. Lebrun-Harris, L.A.; Sherman, L.J.; Miller, B. State-level prevalence of bullying victimization among children and adolescents, National Survey of Children’s Health 2016–2017. Public Health Rep. 2020, 135, 303–309. [Google Scholar] [CrossRef] [PubMed]
  63. Dillon, C.E.; Lochman, J.E. Correcting for norm misperception of anti-bullying attitudes. Int. J. Behav. Dev. 2022, 46, 443–452. [Google Scholar] [CrossRef]
  64. Bradshaw, C.P.; Sawyer, A.L.; O’Brennan, L.M. Bullying and peer victimization at school: Perceptual differences between students and school staff. Sch. Psychol. Rev. 2007, 36, 361–382. [Google Scholar] [CrossRef]
  65. Li, R.; Lian, Q.; Su, Q.; Li, L.; Xie, M.; Hu, J. Trends and sex disparities in school bullying victimization among US youth, 2011–2019. BMC Public Health 2020, 20, 1583. [Google Scholar] [CrossRef] [PubMed]
  66. Jetelina, K.K.; Gonzalez, J.M.R.; Cuccaro, P.M.; Peskin, M.F.; Pompeii, L.; Atem, F.; Elliott, M.N.; Earnshaw, V.A.; Davies, S.L.; Schuster, M.A. Self-reporting discrepancies of bullying victimization and perpetration measures. Ann. Epidemiol. 2019, 32, 58–63. [Google Scholar] [CrossRef] [PubMed]
  67. Auxier, B.; Anderson, M.; Perrin, A.; Turner, E. Parenting Children in the Age of Screenings. Pew Research Center. 2020. Available online: https://www.pewresearch.org/internet/2020/07/28/parenting-children-in-the-age-of-screens/ (accessed on 1 March 2024).
  68. Haine, R.A.; Brookman-Frazee, L.; Tsai, K.H.; Roesch, S.C.; Garland, A.F. Clinician perspectives of diagnosis and perceived client change in “real world” psychotherapy for youth emotional and behavioral disorders. J. Child Fam. Stud. 2007, 16, 712–728. [Google Scholar] [CrossRef]
  69. Pandey, A.; Hale, D.; Das, S.; Goddings, A.L.; Blakemore, S.J.; Viner, R.M. Effectiveness of universal self-regulation–based interventions in children and adolescents: A systematic review and meta-analysis. JAMA Pediatr. 2018, 172, 566–575. [Google Scholar] [CrossRef] [PubMed]
  70. Latané, B.; Darley, J.M. Bystander “apathy”. Am. Sci. 1969, 57, 244–268. [Google Scholar]
  71. Ng, E.D.; Chua, J.Y.X.; Shorey, S. The effectiveness of educational interventions on traditional bullying and cyberbullying among adolescents: A systematic review and meta-analysis. Trauma Violence Abus. 2022, 23, 132–151. [Google Scholar] [CrossRef] [PubMed]
  72. Domino, M. Measuring the impact of an alternative approach to school bullying. J. Sch. Health 2013, 83, 430–437. [Google Scholar] [CrossRef] [PubMed]
  73. Espelage, D.L.; Low, S.; Polanin, J.R.; Brown, E.C. Clinical trial of Second Step© middle-school program: Impact on aggression & victimization. J. Appl. Dev. Psychol. 2015, 37, 52–63. [Google Scholar]
  74. Ostrov, J.M.; Kamper, K.E. Future directions for research on the development of relational and physical peer victimization. In Future Work in Clinical Child and Adolescent Psychology; Routledge: London, UK, 2018; pp. 367–377. [Google Scholar]
Table 1. Prevalence of all forms combined, physical, social, and cyberbullying.
Table 1. Prevalence of all forms combined, physical, social, and cyberbullying.
NAll Forms (%)Physical (%)Social (%) Cyber (%)
BulliesVictimsBully-VictimsBulliesVictimsBully-VictimsBulliesVictimsBully-Victims Bullies Victims Bully-Victims
Overall197722.863.920.29.444.97.120.955.917.76.921.15.4
Gender
 Female109220.063.217.97.140.85.318.856.816.36.021.64.8
 Male87926.165.022.912.150.19.323.454.919.37.820.66.1
Race
 White87322.266.320.07.846.76.420.559.518.15.720.44.6
 Black22731.357.726.918.140.111.527.849.821.611.926.48.8
 Asian5131.474.531.411.852.99.829.464.727.59.821.67.8
 Multiracial11575.774.823.59.660.99.624.362.620.96.125.26.1
Ethnicity
 Non-Hispanic152022.760.520.39.941.67.020.851.517.88.724.35.2
 Hispanic42322.664.820.19.145.67.321.557.017.76.320.36.1
Table 2. Odds ratios and 95% confidence intervals from logistic regression analyses predicting all forms combined, physical, social, and cyberbullying (N = 1977).
Table 2. Odds ratios and 95% confidence intervals from logistic regression analyses predicting all forms combined, physical, social, and cyberbullying (N = 1977).
BulliesVictimsBully-Victims
All Forms Combined
OR 95% CIOR 95% CIOR 95% CI
Self-Regulation Skills0.51 (0.42, 0.63) ***0.88 (0.74, 1.05)0.55 (0.44, 0.68) ***
Bystander Intervention Skills0.90 (0.77, 1.04)1.06 (0.94, 1.19)0.94 (0.80, 1.10)
Substance Use2.37 (1.94, 2.90) ***1.49 (1.21, 1.84) ***2.12 (1.76, 2.54) ***
Male1.33 (1.06, 1.68) *1.07 (0.89, 1.30)1.27 (1.00, 1.60)
Race/Ethnic Minority1.03 (0.82, 1.30)1.33 (1.10, 1.61) **1.10 (0.87, 1.40)
Academic Performance0.89 (0.79, 1.00)0.93 (0.84, 1.04)0.90 (0.80, 1.02)
Physical
Self-Regulation Skills0.49 (0.36, 0.67) ***0.90 (0.76, 1.07)0.54 (0.38, 0.76) **
Bystander Intervention Skills0.84 (0.68, 1.04)0.97 (0.86, 1.10)0.88 (0.69, 1.12)
Substance Use2.63 (2.17, 3.18) ***1.69 (1.40, 2.04) ***2.56 (2.12, 3.08) ***
Male1.60 (1.13, 2.27) **1.44 (1.19, 1.73) ***1.66 (1.12, 2.47) *
Race/Ethnic Minority0.77 (0.54, 1.08)1.32 (1.10, 1.58) **0.99 (0.67,1.46)
Academic Performance1.16 (0.98, 1.37)0.96 (0.87, 1.07)1.17 (0.98, 1.41)
Social
Self-Regulation Skills0.54 (0.44, 0.67) ***0.85 (0.71, 1.00)0.58 (0.46, 0.72) ***
Bystander Intervention Skills0.86 (0.74, 1.00)1.09 (0.96, 1.22)0.91 (0.77, 1.06)
Substance Use2.39 (1.96, 2.91) ***1.44 (1.20, 1.73) ***2.16 (1.80, 2.58) ***
Male1.23 (0.97, 1.56)0.92 (0.77, 1.11)1.14 (0.89, 1.47)
Race/Ethnic Minority1.08 (0.85, 1.37) *1.39 (0.92, 0.99) **1.21 (0.95, 1.55)
Academic Performance0.90 (0.80, 1.03)0.93 (0.84, 1.02)0.88 (0.77, 1.01)
Cyberbullying
Self-Regulation Skills0.44 (0.30, 0.63) ***0.66 (0.54, 0.82) ***0.48 (0.32, 0.73) **
Bystander Intervention Skills0.87 (0.67, 1.12)1.16 (1.00, 1.35)0.90 (0.68, 1.20)
Substance Use3.11 (2.54, 3.81) ***2.10 (1.75, 2.52) ***2.93 (2.41, 3.57) ***
Male1.04 (0.68, 1.58)0.86 (0.68, 1.09)1.00 (0.63, 1.60)
Race/Ethnic Minority0.95 (0.88, 1.03)1.04 (0.83, 1.31)0.81 (0.51, 1.30)
Academic Performance1.23 (1.00, 1.49) *1.19 (1.05, 1.34) **1.26 (1.02, 1.56) *
* p < 0.05; ** p < 0.01; *** p < 0.001; non-White is reference category for race.
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Williams, C.; Griffin, K.W.; Botvin, C.M.; Sousa, S.; Botvin, G.J. Self-Regulation as a Protective Factor against Bullying during Early Adolescence. Youth 2024, 4, 478-491. https://doi.org/10.3390/youth4020033

AMA Style

Williams C, Griffin KW, Botvin CM, Sousa S, Botvin GJ. Self-Regulation as a Protective Factor against Bullying during Early Adolescence. Youth. 2024; 4(2):478-491. https://doi.org/10.3390/youth4020033

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Williams, Christopher, Kenneth W. Griffin, Caroline M. Botvin, Sandra Sousa, and Gilbert J. Botvin. 2024. "Self-Regulation as a Protective Factor against Bullying during Early Adolescence" Youth 4, no. 2: 478-491. https://doi.org/10.3390/youth4020033

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