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Article

Perpetration of and Victimization in Cyberbullying and Traditional Bullying in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Impulsivity, Frustration Intolerance, and Hostility

1
Department of Psychiatry, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
2
Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan
3
Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195-6560, USA
4
Department of Psychiatry, Children’s Hospital and Regional Medical Center, Seattle, WA 98105, USA
5
School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
6
Department of Child and Adolescent Psychiatry, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Kaohsiung 83301, Taiwan
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(13), 6872; https://doi.org/10.3390/ijerph18136872
Submission received: 8 May 2021 / Revised: 20 June 2021 / Accepted: 24 June 2021 / Published: 26 June 2021

Abstract

:
Victimization and perpetration of cyberbullying and traditional bullying are prevalent among adolescents with attention-deficit/hyperactivity disorder (ADHD). This study examined the associations of impulsivity, frustration discomfort, and hostility with victimization and with the perpetration of cyberbullying and traditional bullying in adolescents with ADHD. Self-reported involvement in cyberbullying and traditional bullying was assessed in 195 adolescents with a clinical diagnosis of ADHD. Adolescents also completed questionnaires for impulsivity, frustration discomfort, and hostility. Caregivers completed the Child Behavior Checklist for adolescents’ ADHD, internalization, oppositional defiance, and problems with conduct. The associations of impulsivity, frustration discomfort, and hostility with victimization and perpetration of cyberbullying and traditional bullying were examined using logistic regression analysis. The results demonstrated that after the effects of demographic characteristics and behavioral problems were controlled for, frustration intolerance increased the risks of being cyberbullying victims and perpetrators whereas hostility increased the risks of being the victims and perpetrators of traditional bullying. Impulsivity was not significantly associated with any type of bullying involvement. Prevention and intervention programs should alleviate frustration intolerance and hostility among adolescents with ADHD.

1. Introduction

The experiences of victimization and perpetration of cyberbullying and traditional bullying are prevalent among children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Cyberbullying refers to the bullying behaviors perpetrated through electronic means [1]. Traditional bullying can involve physical acts, verbal utterances, social exclusion, property theft, and other behaviors [2]. Compared with those without ADHD, adolescents with ADHD have higher risks of being victims and perpetrators of cyberbullying [3,4,5] and traditional bullying [6,7,8]. Victimization in cyberbullying is significantly associated with depression and suicidality in adolescents with ADHD [4]. Moreover, victimization in and perpetration of traditional bullying are significantly associated with depression in adolescents with ADHD [9]. Therefore, the factors predicting the involvement in cyberbullying and traditional bullying in adolescents with ADHD should be examined, and prevention programs should be developed based on the risk factors identified.
Research has demonstrated that demographic characteristics (i.e., adolescents’ age and parental occupational socioeconomic status), behavioral problems (i.e., symptoms of ADHD and Internet addiction), and behavioral temperament (i.e., low reward responsiveness) predict cyberbullying victimization and perpetration in adolescents with ADHD [4]. Demographic characteristics (i.e., adolescents’ age), behavioral temperament (i.e., high behavioral inhibition and fun seeking), and poor family relationships are the predictors of victimization and perpetration in traditional bullying in adolescents with ADHD [10]. These results of previous studies have supported that the individual and environmental factors relate to adolescents’ involvement in cyberbullying and traditional bullying.
Social-Emotional Development (SED) Model is one of hypothetical models to understand the developmental processes of individuals’ social relationships with others [11]. SED includes understanding, regulating, and expressing emotions in a way that is appropriate for one’s age and development, as well as the ability to establish, maintain, and develop healthy relationships with peers and adults [11]. SED is central to navigating challenges in social interactions in everyday life and to adapting flexibly to situational demands [11]. Research has supported the role of deficits in SED for bullying involvement in adolescents [12,13,14,15]. The present study examined the roles of three social-emotional difficulties, including impulsivity, frustration discomfort, and hostility for victimization in and perpetration of both cyberbullying and traditional bullying in adolescents with ADHD. All impulsivity [16], frustration discomfort [17,18,19], and hostility [20,21] are psychological and behavioral characteristics of difficulties in emotional regulation and expression commonly found in adolescents with ADHD. However, their relationships with involvement in cyberbullying and traditional bullying have not been examined in adolescents with ADHD.
Impulsivity is characterized by the underestimation of harm, nonreflective responses, difficult-to-control desires, and repetitive behaviors to obtain pleasure and gratification [22]. Research has demonstrated that high impulsivity is significantly associated with self-harm [23], craving for illicit substances [24], and Internet addiction [25]. High impulsivity has also been linked to cyberbullying [26] and bullying perpetration [27,28,29,30,31]. Impulsivity is one symptom of ADHD [32]. Whether impulsivity also predicts the involvement in cyberbullying and traditional bullying in adolescents receiving treatment for ADHD warrants further study.
Frustration intolerance refers to the difficulty in accepting that reality does not correspond to one’s personal desires [33]. Research has demonstrated that frustration intolerance is significantly related to depression [34], anxiety [35], substance dependence [36], and Internet addiction [37]. Because frustration intolerance is a type of irrational belief related to emotional and behavioral problems [38] and because it is associated with problems of self-control [39], it is reasonable to hypothesize that adolescents with ADHD with high frustration intolerance have a high risk of perpetrating cyberbullying or traditional bullying. However, the relationships of frustration intolerance with victimization in and perpetration of both cyberbullying and traditional bullying in adolescents with ADHD have not been examined.
Hostility is an emotional state that indicates the intention to harm an individual, and it also denotes expressive characteristics that indicate the potential intent for physical aggression and assault [40]. Hostility is associated with mental health problems such as depression [41], suicide [42], and Internet addiction [43]. Research has found that hostility mediates the relationship between prior bullying victimization and subsequent bullying perpetration [44]. Hostility also increases the risk of the co-occurrence of traditional bullying and cyberbullying [45]. However, the role of hostility in victimization in cyberbullying and traditional bullying in adolescents with ADHD has not been examined.
This study examined the associations of impulsivity, frustration discomfort, and hostility with victimization in and perpetration of both cyberbullying and traditional bullying in adolescents with ADHD. As illustrated in Figure 1, we hypothesized that high impulsivity, frustration discomfort, and hostility are significantly associated with the risks of being victims and perpetrators of cyberbullying and traditional bullying in adolescents with ADHD.

2. Methods

2.1. Participants

Adolescents aged between 11 and 18 years who visited the child and adolescent psychiatric outpatient clinics of two medical centers and who had been diagnosed with ADHD according to the DSM-5 [32] were consecutively invited to participate in this study from June 2019 to January 2021. ADHD was diagnosed based on the outcomes of diagnostic interviews with adolescents and caregivers that were conducted by child psychiatrists. Adolescents and caregivers with intellectual disabilities, schizophrenia, bipolar disorder, autistic disorder, communication difficulties, or cognitive deficits that adversely affected their ability to understand the study’s purpose or complete the questionnaires were excluded. A total of 208 adolescents who had been diagnosed with ADHD and their caregivers were selected for this study; 195 (93.8%) agreed to participate in this study. This study was approved by the Institutional Review Boards of Kaohsiung Medical University (KMUHIRB-SV(I)-20190034) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (201900432A3). Written informed consent was obtained from all participants before assessment.

2.2. Measures

2.2.1. Cyberbullying Experience Questionnaire

Adolescents reported their experiences of cyberbullying perpetration and victimization on social media (Facebook, Twitter, and Plurk) or through pictures or video clips, emails, or blogs in the previous year using the six-item cyberbullying experience questionnaire [4]. Each item is scored on a 4-point Likert scale ranging from 0 (never) to 3 (all the time). The first three items for cyberbullying perpetration are related to the posting of mean or hurtful comments, the posting of upsetting pictures, photos, or videos, and the spreading of rumors online. The final three items are related to the experiences of cyberbullying victimization resulting from the actions described in the first three items. The Cronbach’s α values of the items for cyberbullying victimization and perpetration were 0.70 and 0.65, respectively. Participants with a score of 1, 2, or 3 on any item among the first and final three items were defined to be as self-reported perpetrators and victims of cyberbullying, respectively.

2.2.2. Chinese Version of the School Bullying Experience Questionnaire

In this study, adolescents reported their experiences of traditional bullying victimization and perpetration in the previous year using the Chinese version of the 16-item School Bullying Experience Questionnaire (C-SBEQ) [46,47]. Each item is scored on a 4-point Likert scale ranging from 0 (never) to 3 (all the time). The first eight items evaluate the experiences of victimization from social, verbal, and physical bullying; the final eight items evaluate the experiences of perpetrating bullying in terms of actions that perpetrate social, verbal, and physical bullying (in the first eight items). Participants who scored 2 or 3 on any item among the first and final eight items were defined to be victims and perpetrators of traditional bullying, respectively. A previous study demonstrated the reliability and validity of the C-SBEQ [47]. In the present study, the Cronbach’s α values of the items for victimization and perpetration of traditional bullying were 0.76 and 0.72, respectively, for adolescents with ADHD.

2.2.3. Impulsivity

In this study, the Barratt Impulsiveness Scale version 11-Taiwan (BIS-11-TW) was used to evaluate the self-reported level of adolescents’ impulsivity [22,48]. The BIS-11-TW contains 25 items measuring multiple aspects of impulsivity, including the inability to plan, the lack of foresight and perseverance and self-control, and a proclivity toward seeking novelty and hastily making decisions. All items are measured on a 4-point scale ranging from 1 (rarely/never) to 4 (almost always/always), with a higher score indicating higher impulsivity. The BIS-11-TW has acceptable psychometric properties [22]. The Cronbach’s α of the BIS-11-TW was 0.90 in the present study.

2.2.4. Frustration Intolerance

The Chinese version of the Frustration Discomfort Scale (FDS) was used to evaluate the self-reported frustration intolerance of adolescents [39,49,50]. The FDS contains 28 items evaluated on a 5-point Likert scale, with scores ranging from 28 to 140; a higher total score indicates higher frustration intolerance. The Cronbach’s α of the FDS was 0.88 in the present study.

2.2.5. Hostility

The Buss–Durkee Hostility Inventory-Chinese version-Short Form (BDHIC-SF) was used to measure the self-reported level of adolescents’ hostility [51,52]. The BDHIC-SF comprises 20 items measuring hostility cognition, hostility affect, expressive hostility behavior, and suppressive hostility behavior. These items are rated from 1 (strongly disagree) to 5 (strongly agree), with a higher total score indicating higher hostility. The BDHIC-SF has acceptable psychometric properties [52]. In this study, the Cronbach’s α of the BDHIC-SF was 0.85.

2.2.6. Child Behavior Checklist for Ages 6–18

The 112-item caregiver-reported Chinese version of the Child Behavior Checklist for Ages 6–18 (CBCL/6-18) was used to measure adolescents’ behavior problems [53,54,55]. We used the recommended T-score transformations of raw behavior scores, which were adjusted for age and sex differences in behavior found in normative samples. We used the domains of internalizing problems (which includes scales for anxiety/depression, withdrawal/depression, and somatic complaint syndrome), ADHD, oppositional defiant disorder (ODD), and conduct symptoms for analysis.

2.2.7. Demographic Characteristics

The present study examined adolescents’ age and sex and caregivers’ age, sex, educational duration, marital status (married and living together vs. divorced or separated), and occupational socioeconomic status. We assessed the caregivers’ occupational socioeconomic status using the Close-Ended Questionnaire of the Occupational Survey [56], which classifies paternal and maternal occupational socioeconomic status into five levels (level 1 to level 5). A higher level indicates a higher occupational socioeconomic status.

2.3. Statistical Analysis

The descriptive statistics used were the frequency and percentage for categorical variables and as the mean and standard deviation (SD) for continuous variables. Correlations between the variables were examined using Spearman’s rank-order correlation. Because of multiple comparisons, the significance level for Spearman’s rank-order correlation was adjusted with p < 0.003 (0.05/13) indicating the significance.
Demographic characteristics, impulsivity, frustration intolerance, hostility, and behavioral problems were compared between victims and nonvictims and between perpetrators and nonperpetrators using the t-test and chi-square test. The variables with significant differences were included in a logistic regression with conditional forward selection to examine their associations with involvements in cyberbullying and traditional bullying. Odds ratios and 95% confidence intervals were used to represent statistical significance. A two-tailed p value of <0.05 indicated statistical significance.

3. Results

Table 1 presents the data on demographic characteristics, cyberbullying and bullying involvement, impulsivity, frustration intolerance, hostility, and behavioral problems. In total, 31 girls and 164 boys participated in this study. Their mean age was 13.5 years (SD = 2.3 years). Among them, 14.4% were victims of cyberbullying, 8.7% were perpetrators of cyberbullying, 27.7% were victims of traditional bullying, and 17.9% were perpetrators of traditional bullying.
Table 2 presents the results of Spearman’s rank-order correlation examining the correlations between studied variables. The significant correlations included: negative correlation between child’s age and ODD problems; positive correlations of being cyberbullying victims with being cyberbullying perpetrators and frustration intolerance; positive correlation between being cyberbullying perpetrators and ODD symptoms; positive correlations of being traditional bullying victims with being traditional bullying perpetrators, hostility, and internalizing problems; positive correlations of being traditional bullying perpetrators with frustration intolerance and hostility; positive correlations of impulsivity with frustration intolerance, hostility, ADHD, ODD and conduct problems; positive correlation between frustration intolerance and hostility; positive correlation between hostility and ODD symptoms; positive correlation of internalizing problems with ADHD, ODD and conduct problems; positive correlation of ADHD problems with ODD and conduct problems; and positive correlation between ODD and conduct problems.
Table 3 presents the differences in demographic characteristics, impulsivity, frustration intolerance, hostility, and behavioral problems between victims and nonvictims and between perpetrators and nonperpetrators. The results demonstrated that cyberbullying victims had higher frustration intolerance and hostility relative to cyberbullying nonvictims. Cyberbullying perpetrators had higher ODD problems and frustration intolerance relative to cyberbullying nonperpetrators. Traditional bullying victims were younger and had higher internalizing problems, impulsivity, and hostility relative to traditional bullying nonvictims. Traditional bullying perpetrators had higher impulsivity, frustration intolerance, and hostility relative to traditional bullying nonperpetrators.
The significant variables were included in logistic regression analysis with conditional forward selection as independent variables to examine their associations with involvements in cyberbullying and traditional bullying (Table 4). The results demonstrated that after demographic characteristics and behavioral problems were controlled for, frustration intolerance increased the risks of being cyberbullying victims and perpetrators, whereas hostility increased the risks of being traditional bullying victims and perpetrators. Impulsivity was not significantly associated with any type of bullying involvement.

4. Discussion

The present study shows that impulsivity, frustration intolerance, and hostility play various roles in the bullying involvement of adolescents with ADHD. Frustration intolerance increased the risks of being cyberbullying victims and perpetrators, whereas hostility increased the risks of being traditional bullying victims and perpetrators. Impulsivity was not significantly associated with any type of bullying involvement.
Adolescents with ADHD with higher frustration intolerance had higher risks of being cyberbullying victims and perpetrators. Adolescents with ADHD with high frustration intolerance may have difficulties in making and maintaining peer relationships [57,58] and in achieving adequate academic performance [59]. Research has shown that frustration intolerance is associated with behavior avoidance [39]. Adolescents with ADHD may feel uncomfortable and spend more time and energy on Internet activities to feel a sense of achievement [60], increasing the risk of Internet addiction [37]. Internet addiction is a well-known risk factor for cyberbullying perpetration [4] and victimization [61]. Moreover, adolescents with ADHD with high frustration intolerance may work off their frustration by perpetrating cyberbullying; their acts of cyberbullying may provoke others to fight back and thus increase the perpetrator’s risk of victimization. The results of the present study indicate that interventions are required in adolescents with ADHD with high frustration intolerance to reduce their risk of involvement in cyberbullying. Research has found that overlapping cognitive deficits may underlie both classical ADHD symptoms, such as low frustration tolerance and mood instability; stimulants or atomoxetine may alleviate both types of symptoms when they co-occur [62,63]. Supportive interventions [61], rational emotive behavior therapy [64], and cognitive behavioral therapies [65] may also alleviate ADHD youths’ emotional instability due to frustration intolerance.
Consonant with previous studies [44,45], the present study demonstrates that adolescents with ADHD with high hostility had higher risks of being victims and perpetrators of traditional bullying. Individuals with high hostility may enact their intention to harm others in the form of physical and verbal aggression. Moreover, victims of traditional bullying may feel unsafe, increasing their awareness of possible harassment from others at any moment; thus, their hostility may increase. Adolescents with ADHD with high hostility may also overreact to the ordinary words and behaviors of others; thus; they have an increased risk of victimization. Although the result of this study demonstrated the necessity of implementing interventions for hostility in adolescents with ADHD, alleviating hostility in this patient group is a challenge. Previous studies have found no evidence for the efficacies of methylphenidate [66,67] or atomoxetine [68]. Furthermore, no formal, evidence-based model of psychotherapy is available for reducing hostility in individuals with high hostility.
Because high hostility has been found to increase the risk of Internet addiction [43] and because Internet addiction increases the risk of cyberbullying involvement in adolescents with ADHD [37], it is reasonable to hypothesize that hostility may increase the risks of victimization in and perpetration of cyberbullying in adolescents with ADHD. However, the results of this study did not support this hypothesis. Research examining the difference between hostility in the real world and online has demonstrated that the level of hostility is lower online than offline [69]. This may partially account for the different roles of hostility in the involvement in cyberbullying and traditional bullying.
Impulsivity is associated with reactive aggression in impulsive adolescents who cannot control emotion and delay gratification [70]. It is reasonable to hypothesize that ADHD adolescents with high impulsivity may perpetrate bullying due to dissatisfaction when interacting with others. Moreover, ADHD adolescents with high impulsivity may have difficulties in following the rules and thus become the target of being rejected by others. However, incongruent with our hypothesis and the results of previous studies [26,27,28,29,30,31], our findings did not demonstrate a significant association between impulsivity and any type of bullying involvement. The first possible reason accounting for the discrepancy between the result and the hypothesis is the source of participants recruited into this study. Adolescents in this study were recruited from clinical units and are currently receiving medication or psychotherapy for their ADHD. Research has supported the effectiveness of methylphenidate and atomoxetine on reducing the core symptoms of ADHD [71,72,73]. Thus, impulsivity and related problems might be attenuated. Second, victims and perpetrators of traditional bullying tended to have higher impulsivity, respectively; however, the difference in impulsivity became nonsignificant in the multivariate logistic regression analysis. This result indicates that in adolescents receiving treatment for ADHD, other factors such as hostility may play a more significant role in traditional bullying involvement than impulsivity does. Impulsivity indicates a difficult-to-control desire to obtain pleasure and gratification [16]. Contrarily, hostility indicates the intention to harm others and denotes expressive intent for physical aggression and assault [34]. According to Dan Olweus, bullying is a negative action occurred when a person intentionally inflicts injury or discomfort upon another person [74]. Therefore, hostility may play a more direct and stronger role in perpetrating bullying compared with impulsivity.
To our knowledge, this study is one of the first studies to examine the relationships of impulsivity, frustration intolerance, and hostility with involvement in cyberbullying and traditional bullying among adolescents with ADHD. However, several limitations of this study warrant being addressed. First, the causal relationships of impulsivity, frustration intolerance, and hostility with bullying involvement could not be determined in this cross-sectional study. Second, the data of this study were provided by the adolescents except for behavioral problems reported by caregivers, which might result in shared-method variance. Third, the participants of this study were recruited from outpatient clinics; the results of this study might not be generalized to adolescents who did not visit medical units for help. Fourth, research revealed that stimulants such as methylphenidate can lessen involvement in the bullying cycle in adolescents with ADHD [75], whereas the effect of non-stimulants such as atomoxetine on reducing the risk of bullying involvement is still clear. We did not collect the kinds of pharmacological and psychological treatments that the adolescents with ADHD received and could not determine the treatment effects on the associations between impulsivity, frustration discomfort, and hostility with victimization in and perpetration of bullying in adolescents with ADHD.

5. Conclusions

The present study shows that frustration intolerance and hostility are significantly associated with various types of bullying involvement of adolescents with ADHD. Mental health professionals should take frustration intolerance and hostility into consideration when developing prevention and intervention strategies to reduce the risks of victimization and perpetration in cyberbullying and traditional bullying among adolescents with ADHD. Mental health professionals should evaluate routinely the levels of frustration intolerance and hostility in adolescents with ADHD. The possibility of involvement in bullying victimization and perpetration should be monitored among those with high levels of frustration intolerance and hostility. Necessary psychological and pharmacological intervention should be provided for adolescents with ADHD to increase frustration tolerance and reduce hostility and the risks of bullying involvement.

Author Contributions

T.-L.L. analyzed the data and drafted the manuscript. C.-F.Y. formulated the study aims. R.C.H. revised the manuscript. W.-J.C. conducted the study. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by grants from the Chang Gung Memorial Hospital Medical Research Project (108-CMRPG8J0651 and 109-CMRPG8K0971). The funding agency played no role in this study.

Institutional Review Board Statement

The Institutional Review Boards of Kaohsiung Medical University (KMUHIRB-SV(I)-20190034) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (201900432A3) approved the study.

Informed Consent Statement

All participants provided their written informed consent.

Data Availability Statement

The data will be available upon reasonable request to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kowalski, R.M.; Limber, S.P. Psychological, physical, and academic correlates of cyberbullying and traditional bullying. J. Adolesc. Health 2013, 53, S13–S20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Wolke, D.; Woods, S.; Bloomfield, L.; Karstadt, L. The association between direct and relational bullying and behaviour problems among primary school children. J. Child Psychol. Psychiatry 2000, 41, 989–1002. [Google Scholar] [CrossRef] [PubMed]
  3. Kowalski, R.M.; Fedina, C. Cyber bullying in ADHD and asperger syndrome populations. Res. Autism. Spectr. Disord. 2011, 5, 1201–1208. [Google Scholar] [CrossRef]
  4. Yen, C.F.; Chou, W.J.; Liu, T.L.; Ko, C.H.; Yang, P.; Hu, H.F. Cyberbullying among male adolescents with attention-deficit/hyperactivity disorder: Prevalence, correlates, and association with poor mental health status. Res. Dev. Disabil. 2014, 35, 3543–3553. [Google Scholar] [CrossRef]
  5. Dawson, A.E.; Wymbs, B.T.; Evans, S.W.; DuPaul, G.J. Exploring how adolescents with ADHD use and interact with technology. J. Adolesc. 2019, 71, 119–137. [Google Scholar] [CrossRef] [PubMed]
  6. Park, I.; Gong, J.; Lyons, G.L.; Hirota, T.; Takahashi, M.; Kim, B.; Lee, S.Y.; Kim, Y.S.; Lee, J.; Leventhal, B.L. Prevalence of and factors associated with school bullying in students with autism spectrum disorder: A cross-cultural meta-analysis. Yonsei Med. J. 2020, 61, 909–922. [Google Scholar] [CrossRef]
  7. Thomas, H.J.; Connor, J.P.; Lawrence, D.M.; Hafekost, J.M.; Zubrick, S.R.; Scott, J.G. Prevalence and correlates of bullying victimisation and perpetration in a nationally representative sample of Australian youth. Aust. N. Z. J. Psychiatry 2017, 51, 909–920. [Google Scholar] [CrossRef] [Green Version]
  8. Verlinden, M.; Jansen, P.W.; Veenstra, R.; Jaddoe, V.W.; Hofman, A.; Verhulst, F.C.; Shaw, P.; Tiemeier, H. Preschool attention-deficit/hyperactivity and oppositional defiant problems as antecedents of school bullying. J. Am. Acad. Child Adolesc. Psychiatry 2015, 54, 571–579. [Google Scholar] [CrossRef]
  9. Hu, H.F.; Chou, W.J.; Yen, C.F. Anxiety and depression among adolescents with attention-deficit/hyperactivity disorder: The roles of behavioral temperamental traits, comorbid autism spectrum disorder, and bullying involvement. Kaohsiung J. Med. Sci. 2016, 32, 103–109. [Google Scholar] [CrossRef] [Green Version]
  10. Chou, W.J.; Liu, T.L.; Yang, P.; Yen, C.F.; Hu, H.F. Bullying victimization and perpetration and their correlates in adolescents clinically diagnosed with ADHD. J. Atten. Disord. 2018, 22, 25–34. [Google Scholar] [CrossRef]
  11. Malti, T.; Noam, G.G. Social-emotional development: From theory to practice. Eur. J. Dev. Psychol. 2016, 13, 652–665. [Google Scholar] [CrossRef]
  12. Agley, J.; Jun, M.; Eldridge, L.; Agley, D.L.; Xiao, Y.; Sussman, S.; Golzarri-Arroyo, L.; Dickinson, S.L.; Jayawardene, W.; Gassman, R. Effects of ACT Out! Social issue theater on social-emotional competence and bullying in youth and adolescents: Cluster randomized controlled trial. JMIR Ment. Health 2021, 8, e25860. [Google Scholar] [CrossRef] [PubMed]
  13. Liu, T.L.; Hsiao, R.C.; Chou, W.J.; Yen, C.F. Social anxiety in victimization and perpetration of cyberbullying and traditional bullying in adolescents with autism spectrum disorder and attention-deficit/hyperactivity disorder. Int. J. Environ. Res. Public Health 2021, 18, 5728. [Google Scholar] [CrossRef] [PubMed]
  14. Nickerson, A.B.; Fredrick, S.S.; Allen, K.P.; Jenkins, L.N. Social emotional learning (SEL) practices in schools: Effects on perceptions of bullying victimization. J. Sch. Psychol. 2019, 73, 74–88. [Google Scholar] [CrossRef] [PubMed]
  15. Yang, C.; Chan, M.K.; Ma, T.L. School-wide social emotional learning (SEL) and bullying victimization: Moderating role of school climate in elementary, middle, and high schools. J. Sch. Psychol. 2020, 82, 49–69. [Google Scholar] [CrossRef]
  16. Winstanley, C.A.; Eagle, D.M.; Robbins, T.W. Behavioral models of impulsivity in relation to ADHD: Translation between clinical and preclinical studies. Clin. Psychol. Rev. 2006, 26, 379–395. [Google Scholar] [CrossRef] [Green Version]
  17. Scime, M.; Norvilitis, J.M. Task performance and response to frustration in children with attention deficit hyperactivity disorder. Psychol. Sch. 2006, 43, 377–386. [Google Scholar] [CrossRef]
  18. Seymour, K.E.; Macatee, R.; Chronis-Tuscano, A. Frustration tolerance in youth with ADHD. J. Atten. Disord. 2019, 23, 1229–1239. [Google Scholar] [CrossRef]
  19. Walcott, C.M.; Landau, S. The relation between disinhibition and emotion regulation in boys with attention deficit hyperactivity disorder. J. Clin. Child Adolesc. Psychol. 2004, 33, 772–782. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Ercan, E.; Ercan, E.S.; Atilgan, H.; Basay, B.K.; Uysal, T.; Inci, S.B.; Ardic, U.A. Predicting aggression in children with ADHD. Child Adolesc. Psychiatry Ment. Health 2014, 8, 15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Farbiash, T.; Berger, A.; Atzaba-Poria, N.; Auerbach, J.G. Prediction of preschool aggression from DRD4 risk, parental ADHD symptoms, and home chaos. J. Abnorm. Child Psychol. 2014, 42, 489–499. [Google Scholar] [CrossRef] [PubMed]
  22. Li, C.S.; Chen, S.H. Obsessive-compulsiveness and impulsivity in a non-clinical population of adolescent males and females. Psychiatry Res. 2007, 149, 129–138. [Google Scholar] [CrossRef]
  23. Müller, A.; Claes, L.; Smits, D.; Brähler, E.; de Zwaan, M. Prevalence and correlates of self-harm in the German general population. PLoS ONE 2016, 11, e0157928. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Zilberman, M.L.; Tavares, H.; el-Guebaly, N. Relationship between craving and personality in treatment-seeking women with substance-related disorders. BMC Psychiatry 2003, 3, 1. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Li, W.; Zhang, W.; Xiao, L.; Nie, J. The association of Internet addiction symptoms with impulsiveness, loneliness, novelty seeking and behavioral inhibition system among adults with attention-deficit/hyperactivity disorder (ADHD). Psychiatry Res. 2016, 243, 357–364. [Google Scholar] [CrossRef] [PubMed]
  26. Khoury-Kassabri, M.; Mishna, F.; Massarwi, A.A. Cyberbullying perpetration by Arab youth: The direct and interactive role of individual, family, and neighborhood characteristics. J. Interpers. Violence 2019, 34, 2498–2524. [Google Scholar] [CrossRef] [PubMed]
  27. Bosworth, K.; Espelage, D.L.; Simon, T.R. Factors associated with bullying behavior in middle school students. J. Early Adolesc. 1999, 19, 341–362. [Google Scholar] [CrossRef] [Green Version]
  28. Georgiou, S.N.; Charalambous, K.; Stavrinides, P. Mindfulness, impulsivity, and moral disengagement as parameters of bullying and victimization at school. Aggress. Behav. 2020, 46, 107–115. [Google Scholar] [CrossRef] [Green Version]
  29. Hoaken, P.N.S.; Shaughnessy, V.K.; Pihl, R.O. Executive cognitive functioning and aggression: Is it an issue of impulsivity? Aggress. Behav. 2003, 9, 15–30. [Google Scholar] [CrossRef]
  30. Jolliffe, D.; Farrington, D.P. Is low empathy related to bullying after controlling for individual and social background variables? J. Adolesc. 2011, 34, 59–71. [Google Scholar] [CrossRef] [PubMed]
  31. Neumann, A.; Barker, E.D.; Koot, H.M.; Maughan, B. The role of contextual risk, impulsivity, and parental knowledge in the development of adolescent antisocial behavior. J. Abnorm. Psychol. 2010, 119, 534–545. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed.; American Psychiatric Association: Washington, DC, USA, 2013. [Google Scholar]
  33. Harrington, N. Frustration intolerance beliefs: Their relationship with depression, anxiety, and anger, in a clinical population. Cogn. Ther. Res. 2006, 30, 699–709. [Google Scholar] [CrossRef]
  34. Drieling, T.; van Calker, D.; Hecht, H. Stress, personality and depressive symptoms in a 6.5-year follow-up of subjects at familial risk for affective disorders and controls. J. Affect. Disord. 2006, 91, 195–203. [Google Scholar] [CrossRef] [PubMed]
  35. MacDonald, E.M.; Pawluk, E.J.; Koerner, N.; Goodwill, A.M. An examination of distress intolerance in undergraduate students high in symptoms of generalized anxiety disorder. Cogn. Behav. Ther. 2015, 44, 74–84. [Google Scholar] [CrossRef] [PubMed]
  36. McHugh, R.K.; Otto, M.W. Profiles of distress intolerance in a substance-dependent sample. Am. J. Drug Alcohol. Abus. 2012, 38, 161–165. [Google Scholar] [CrossRef] [PubMed]
  37. Lu, W.-H.; Chou, W.-J.; Hsiao, R.C.; Hu, H.-F.; Yen, C.-F. Correlations of Internet addiction severity with reinforcement sensitivity and frustration intolerance in adolescents with attention-deficit/hyperactivity disorder: The moderating effect of medications. Front. Psychiatry 2019, 10, 268. [Google Scholar] [CrossRef]
  38. Digiuseppe, R.A.; Doyle, K.A.; Dryden, W.; Backx, W. A Practitioner’s Guide to Rational-Emotive Behavior Therapy; Oxford University Press: New York, NY, USA, 2015. [Google Scholar]
  39. Harrington, N. Dimensions of frustration intolerance and their relationship to self-control problems. J. Ration. Emon. Cogn. Behav. Ther. 2005, 23, 1–20. [Google Scholar] [CrossRef]
  40. Beck, A.T. Prisoners of Hate: The Cognitive Basis of Anger, Hostility, and Violence; HarperCollins: New York, NY, USA, 1999. [Google Scholar]
  41. Bird, T.; Tarsia, M.; Schwannauer, M. Interpersonal styles in major and chronic depression: A systematic review and meta-analysis. J. Affect. Disord. 2018, 239, 93–101. [Google Scholar] [CrossRef] [Green Version]
  42. Lemogne, C.; Fossati, P.; Limosin, F.; Nabi, H.; Encrenaz, G.; Bonenfant, S.; Consoli, S.M. Cognitive hostility and suicide. Acta Psychiatr. Scand. 2011, 124, 62–69. [Google Scholar] [CrossRef] [Green Version]
  43. Ko, C.H.; Yen, J.Y.; Chen, C.S.; Yeh, Y.C.; Yen, C.F. Predictive values of psychiatric symptoms for internet addiction in adolescents: A 2-year prospective study. Arch. Pediatr. Adolesc. Med. 2009, 163, 937–943. [Google Scholar] [CrossRef] [Green Version]
  44. Walters, G.D.; Espelage, D.L. From victim to victimizer: Hostility, anger, and depression as mediators of the bullying victimization-bullying perpetration association. J. Sch. Psychol. 2018, 68, 73–83. [Google Scholar] [CrossRef] [PubMed]
  45. Tural Hesapcioglu, S.; Ercan, F. Traditional and cyberbullying co-occurrence and its relationship to psychiatric symptoms. Pediatr. Int. 2017, 59, 16–22. [Google Scholar] [CrossRef]
  46. Kim, Y.S.; Koh, Y.J.; Noh, J. Development of Korean-Peer Nomination Inventory (K-PNI): An inventory to evaluate school bullying. J. Korean Neuropsychiatr. Assoc. 2001, 40, 867–875. [Google Scholar]
  47. Yen, C.F.; Kim, Y.S.; Tang, T.C.; Wu, Y.Y.; Cheng, C.P. Factor structure, reliability, and validity of the Chinese version of the School Bullying Experience Questionnaire. Kaohsiung J. Med. Sci. 2012, 28, 500–505. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Patton, J.H.; Stanford, M.S.; Barratt, E.S. Factor structure of the Barratt Impulsiveness Scale. J. Clin. Psychol. 1995, 51, 768–774. [Google Scholar] [CrossRef]
  49. Harrington, N. The Frustration Discomfort Scale: Development and psychometric properties. Clin. Psychol. Psychother. 2005, 12, 374–387. [Google Scholar] [CrossRef]
  50. Ko, C.H.; Yen, J.-Y.; Yen, C.F.; Chen, C.S.; Weng, C.C.; Chen, C.C. The association between internet addiction and problematic alcohol use in adolescents: The problem behavior model. CyberPsychol. Behav. 2008, 11, 571–576. [Google Scholar] [CrossRef]
  51. Buss, A.H.; Durkee, A. An inventory for assessing different kinds of hostility. J. Consult. Psychol. 1957, 21, 343–349. [Google Scholar] [CrossRef]
  52. Lin, T.K.; Weng, C.Y.; Wang, W.C.; Chen, C.C.; Lin, I.M.; Lin, C.L. Hostility trait and vascular dilatory functions in healthy Taiwanese. J. Behav. Med. 2008, 31, 517–524. [Google Scholar] [CrossRef]
  53. Achenbach, T.M.; Edelbrock, C.S. Psychopathology of childhood. Annu. Rev. Psychol. 1984, 35, 227–256. [Google Scholar] [CrossRef]
  54. Achenbach, T.M.; Dumenci, L.; Rescorla, L.A. Ratings of Relations between DSM-IV Diagnostic Categories and Items of the CBCL/6-18, TRF, and YSR; University of Vermont: Burlington, VT, USA, 2001; pp. 1–9. [Google Scholar]
  55. Chen, Y.; Huang, H.L.; Chao, C.C. Achenbach System of Empirically Based Assessment; Psychological Publishing: Taipei, Taiwan, 2009. [Google Scholar]
  56. Hwang, Y.J. An analysis of the reliability and validity of the close-ended questionnaire of the occupational survey in the educational research. Bull. Edu. Res. 2005, 51, 43–71. [Google Scholar]
  57. Kok, F.M.; Groen, Y.; Fuermaier, A.B.; Tucha, O. Problematic peer functioning in girls with ADHD: A systematic literature review. PLoS ONE 2016, 11, e0165119. [Google Scholar] [CrossRef] [PubMed]
  58. Nixon, E. The social competence of children with attention deficit hyperactivity disorder: A review of the literature. Child Psychol. Psychiatry Rev. 2001, 6, 172–180. [Google Scholar] [CrossRef]
  59. Arnold, L.E.; Hodgkins, P.; Kahle, J.; Madhoo, M.; Kewley, G. Long-term outcomes of ADHD: Academic achievement and performance. J. Atten. Disord. 2020, 24, 73–85. [Google Scholar] [CrossRef] [PubMed]
  60. Leung, L. Net-generation attributes and seductive properties of the internet as predictors of online activities and internet addiction. Cyberpsychol. Behav. 2004, 7, 333–348. [Google Scholar] [CrossRef] [PubMed]
  61. Wachs, S.; Vazsonyi, A.T.; Wright, M.F.; Ksinan Jiskrova, G. Cross-national associations among cyberbullying victimization, self-esteem, and Internet addiction: Direct and indirect effects of alexithymia. Front. Psychol. 2020, 11, 1368. [Google Scholar] [CrossRef]
  62. Childress, A.C.; Sallee, F.R. Emotional lability in patients with attention-deficit/hyperactivity disorder: Impact of pharmacotherapy. CNS Drugs 2015, 29, 683–693. [Google Scholar] [CrossRef]
  63. Skirrow, C.; McLoughlin, G.; Kuntsi, J.; Asherson, P. Behavioral, neurocognitive and treatment overlap between attention-deficit/hyperactivity disorder and mood instability. Expert Rev. Neurother. 2009, 9, 489–503. [Google Scholar] [CrossRef]
  64. David, D.; Szentagotai, A.; Eva, K.; Macavei, B. A synopsis of rational-emotive behavior therapy (REBT); Fundamental and applied research. J. Ration. Emon. Cogn. Behav. Ther. 2005, 23, 175–221. [Google Scholar] [CrossRef]
  65. Coelho, L.F.; Barbosa, D.L.; Rizzutti, S.; Muszkat, M.; Bueno, O.F.; Miranda, M.C. Use of cognitive behavioral therapy and token economy to alleviate dysfunctional behavior in children with attention-deficit hyperactivity disorder. Front. Psychiatry 2015, 6, 167. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. King, S.; Waschbusch, D.A.; Pelham, W.E., Jr.; Frankland, B.W.; Andrade, B.F.; Jacques, S.; Corkum, P.V. Social information processing in elementary-school aged children with ADHD: Medication effects and comparisons with typical children. J. Abnorm. Child Psychol. 2009, 37, 579–589. [Google Scholar] [CrossRef] [PubMed]
  67. Rösler, M.; Retz, W.; Fischer, R.; Ose, C.; Alm, B.; Deckert, J.; Philipsen, A.; Herpertz, S.; Ammer, R. Twenty-four-week treatment with extended release methylphenidate improves emotional symptoms in adult ADHD. World J. Biol. Psychiatry 2010, 11, 709–718. [Google Scholar] [CrossRef] [PubMed]
  68. Reed, V.A.; Buitelaar, J.K.; Anand, E.; Day, K.A.; Treuer, T.; Upadhyaya, H.P.; Coghill, D.R.; Kryzhanovskaya, L.A.; Savill, N.C. The safety of atomoxetine for the treatment of children and adolescents with attention-deficit/hyperactivity disorder: A comprehensive review of over a decade of research. CNS Drugs 2016, 30, 603–628. [Google Scholar] [CrossRef]
  69. Yen, J.Y.; Yen, C.F.; Wu, H.Y.; Huang, C.J.; Ko, C.H. Hostility in the real world and online: The effect of internet addiction, depression, and online activity. Cyberpsychol. Behav. Soc. Netw. 2011, 14, 649–655. [Google Scholar] [CrossRef]
  70. Orue, I.; Calvete, E.; Gamez-Guadix, M. Gender moderates the association between psychopathic traits and aggressive behavior in adolescents. Pers. Indiv. Dif. 2016, 94, 266–271. [Google Scholar] [CrossRef]
  71. De Crescenzo, F.; Cortese, S.; Adamo, N.; Janiri, L. Pharmacological and non-pharmacological treatment of adults with ADHD: A meta-review. Evid. Based Ment. Health 2017, 20, 4–11. [Google Scholar] [CrossRef] [Green Version]
  72. Ercan, E.S.; Akyol Ardic, U.; Kabukcu Basay, B.; Ercan, E.; Basay, O. Atomoxetine response in the inattentive and combined subtypes of attention deficit hyperactivity disorder: A retrospective chart review. Atten. Defic. Hyperact. Disord. 2013, 5, 377–385. [Google Scholar] [CrossRef]
  73. Storebø, O.J.; Ramstad, E.; Krogh, H.B.; Nilausen, T.D.; Skoog, M.; Holmskov, M.; Rosendal, S.; Groth, C.; Magnusson, F.L.; Moreira-Maia, C.R.; et al. Methylphenidate for children and adolescents with attention deficit hyperactivity disorder (ADHD). Cochrane Database Syst. Rev. 2015, 11, CD009885. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Olweus, D.; Solberg, M.E.; Breivik, K. Long-term school-level effects of the Olweus Bullying Prevention Program (OBPP). Scand. J. Psychol. 2020, 61, 108–116. [Google Scholar] [CrossRef]
  75. Tural Hesapcıoglu, S.; Kandemir, G. Association of methylphenidate use and traditional and cyberbullying in adolescents with ADHD. Pediatr. Int. 2020, 62, 725–735. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Hypothetical frame of this study.
Figure 1. Hypothetical frame of this study.
Ijerph 18 06872 g001
Table 1. Demographic characteristics, bullying involvement, impulsivity, frustration intolerance, hostility, and behavioral problems (N = 195).
Table 1. Demographic characteristics, bullying involvement, impulsivity, frustration intolerance, hostility, and behavioral problems (N = 195).
Variablen (%)Mean (SD)Range
Adolescents
Sex
Female31 (15.9)
Male164 (84.1)
Age (years) 13.5 (2.3)11–18
Cyberbullying
Victims28 (14.4)
Perpetrators17 (8.7)
Bullying
Victims54 (27.7)
Perpetrators35 (17.9)
Impulsivity on the BIS-11 61.5 (9.7)35–94
Frustration discomfort on the FDS 68.4 (24.1)28–129
Hostility on the BDSI-CS 55.2 (16.4)20–94
Child Behavior Checklist
Internalizing problems 58.7 (10.6)33–83
Attention-deficit/hyperactivity problems 61.7 (7.6)40–80
Oppositional defiant problems 59.5 (7.9)50–80
Conduct problems 57.9 (8.3)50–86
Caregivers
Sex
Female156 (80)
Male39 (20)
Age (years) 45.4 (6.4)31–69
Educational level (years) 14.1 (3.2)6–28
Marriage status
Married and living together155 (79.5)
Divorced or separated40 (20.5)
Paternal occupational socioeconomic status 2.7 (1.0)1–5
Maternal occupational socioeconomic status 2.2 (1.1)1–5
BDHIC-SF: Buss-Durkee Hostility Inventory-Chinese version-Short Form; BIS-11: Barratt Impulsiveness Scale version 11; FDS: Frustration Discomfort Scale; SD: standard deviation.
Table 2. Correlation between studied variables: Spearman’s rank-order correlation.
Table 2. Correlation between studied variables: Spearman’s rank-order correlation.
VariablesSpearman’s Rho Coefficient
1.2.3.4.5.6.7.8.9.10.11.12.13.
1. Adolescents’ sex1
2. Adolescents’ age−0.1101
3. Cyberbullying victims0.0580.0891
4. Cyberbullying perpetrators0.0850.0110.4961
5. Bullying victims0.050−0.1770.1390.0931
6. Bullying perpetrators0.094−0.0840.1510.0450.4571
7. Impulsivity0.069−0.1810.1350.1340.1920.2051
8. Frustration intolerance0.0230.0570.2370.2010.1440.2160.3471
9. Hostility−0.077−0.0380.2030.1830.2420.2760.4920.6821
10. Internalizing problems−0.059−0.0530.0080.0380.2270.1240.1700.0970.1581
11. ADHD problems−0.050−0.1450.0230.1080.1280.1080.2520.0330.0850.5331
12. ODD problems0.128−0.2390.0550.2090.0830.0600.2430.1560.2590.5180.5911
13. Conduct problems−0.042−0.1440.0090.1030.1100.1020.2090.1260.1800.6050.6480.6971
ADHD: attention-deficit/hyperactivity disorder; ODD: oppositional defiant disorder. Values in bold are significant at the p < 0.003 level.
Table 3. Differences in demographic characteristics, impulsivity, frustration intolerance, hostility, and behavioral problems between victims and nonvictims and between perpetrators and nonperpetrators.
Table 3. Differences in demographic characteristics, impulsivity, frustration intolerance, hostility, and behavioral problems between victims and nonvictims and between perpetrators and nonperpetrators.
VariableCyberbullying VictimsCyberbullying PerpetratorsBullying VictimsBullying Perpetrators
YesNoχ2 or tpYesNoχ2 or tpYesNoχ2 or tpYesNoχ2 or tp
Sex a
Female3
(9.7)
28
(90.3)
0.6570.4181
(3.2)
30
(96.8)
1.3970.2373
(9.7)
28
(90.3)
1.7120.1917
(22.6)
24
(77.4)
0.4810.188
Male25
(15.2)
139
(84.8)
16
(9.8)
148
(90.2)
32
(19.5)
132
(80.5)
47
(28.7)
117
(71.3)
Age (years) b13.9
(2.2)
13.4
(2.3)
−1.0290.30513.6
(2.3)
13.5
(2.3)
−0.1330.89512.9
(2.0)
13.8
(2.3)
2.5580.01113.1
(2.1)
13.6
(2.3)
1.2390.217
Child Behavior Checklist b
Internalizing problems58.4 (10.3)58.8 (10.7)0.1770.86059.5
(10.6)
58.7
(10.7)
−0.3020.76362.5
(10.2)
57.3
(10.5)
−3.1180.00261.5
(11.1)
58.1
(10.5)
−1.7210.087
ADHD problems62.4 (8.3)61.6 (7.5)−0.4800.63264.8
(7.7)
61.4
(7.5)
−1.7400.08463.1
(8.2)
61.2
(7.3)
−1.6340.10463.8
(8.1)
61.3
(7.4)
−1.8000.073
ODD problems60.6 (8.1)59.3 (7.9)−0.8190.41465.8
(9.3)
58.9
(7.5)
−3.543<0.00160.8
(8.7)
59.0
(7.6)
−1.4510.14860.3
(7.7)
59.3
(8.0)
−0.6410.522
Conduct problems58.6 (9.4)57.8 (8.2)−0.4550.65061.6
(10.9)
57.6
(8.0)
−1.9340.05559.4
(9.1)
57.4
(8.0)
−1.5250.12959.9 (9.1)57.5 (8.1)−1.5060.134
Impulsivity b64.1
(5.7)
61.0
(10.2)
−1.5400.12565.2
(6.1)
61.1
(9.9)
−1.6560.09964.5
(8.3)
60.3
(10.0)
−2.7810.00665.3
(7.5)
60.6
(10.0)
−2.6270.009
Frustration intolerance b81.5 (18.7)66.2 (24.2)−3.1750.00282.7
(16.5)
67.0
(24.3)
−2.6020.01073.4
(24.1)
66.5 (23.9)−1.8090.07278.4
(18.0)
66.2
(24.7)
−2.7590.006
Hostilityb63.0
(12.3)
53.8
(16.7)
−2.7770.00664.1
(11.1)
54.3
(16.6)
−2.3660.01961.4
(16.4)
52.8
(15.8)
−3.3760.00164.9
(15.2)
53.0
(16.0)
−4.042<0.001
ADHD: attention-deficit/hyperactivity disorder; ODD: oppositional defiant disorder; SD: standard deviation. a: n (%); b: mean (SD).
Table 4. Factors related to being cyberbullying and traditional bullying perpetrators and victims: Logistic regression analysis with conditional forward selection; CI: confidence interval; ODD: oppositional defiant disorder; OR: odds ratio.
Table 4. Factors related to being cyberbullying and traditional bullying perpetrators and victims: Logistic regression analysis with conditional forward selection; CI: confidence interval; ODD: oppositional defiant disorder; OR: odds ratio.
VariableCyberbullying VictimsCyberbullying PerpetratorsBullying VictimsBullying Perpetrators
Wals χ2pOR
(95% CI)
Wals χ2pOR
(95% CI)
Wals χ2pOR
(95% CI)
Wals χ2pOR
(95% CI)
Age 5.9140.0150.821
(0.700–0.962)
Internalizing problems 6.9280.0081.048
(1.012–1.085)
ODD problems 9.1850.0021.102
(1.035–1.174)
Frustration intolerance9.0310.0031.028
(1.010–1.047)
5.0800.0241.027
(1.003–1.051)
Hostility 8.3750.0041.032
(1.010–1.054)
13.854<0.0011.049
(1.023–1.076)
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Liu, T.-L.; Hsiao, R.C.; Chou, W.-J.; Yen, C.-F. Perpetration of and Victimization in Cyberbullying and Traditional Bullying in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Impulsivity, Frustration Intolerance, and Hostility. Int. J. Environ. Res. Public Health 2021, 18, 6872. https://doi.org/10.3390/ijerph18136872

AMA Style

Liu T-L, Hsiao RC, Chou W-J, Yen C-F. Perpetration of and Victimization in Cyberbullying and Traditional Bullying in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Impulsivity, Frustration Intolerance, and Hostility. International Journal of Environmental Research and Public Health. 2021; 18(13):6872. https://doi.org/10.3390/ijerph18136872

Chicago/Turabian Style

Liu, Tai-Ling, Ray C. Hsiao, Wen-Jiun Chou, and Cheng-Fang Yen. 2021. "Perpetration of and Victimization in Cyberbullying and Traditional Bullying in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Impulsivity, Frustration Intolerance, and Hostility" International Journal of Environmental Research and Public Health 18, no. 13: 6872. https://doi.org/10.3390/ijerph18136872

APA Style

Liu, T. -L., Hsiao, R. C., Chou, W. -J., & Yen, C. -F. (2021). Perpetration of and Victimization in Cyberbullying and Traditional Bullying in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Impulsivity, Frustration Intolerance, and Hostility. International Journal of Environmental Research and Public Health, 18(13), 6872. https://doi.org/10.3390/ijerph18136872

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