Üniversite Öğrencilerinde Psikolojik Yorgunluk, Siber Zorbalık ve Siber Mağduriyet: Karşıt Empatinin Aracı Rolü

Öz

Bu araştırmanın amacı, üniversite öğrencilerinde sosyal medya kullanımına ilişkin psikolojik yorgunluğun siber zorbalık ve siber mağduriyet ile ilişkisinde karşıt empatinin iki alt boyutu olan başkalarının acısından zevk alma ve başkalarının mutluluğundan rahatsız olmanın aracı rolünü incelemektir. Araştırma nicel araştırma yaklaşımlarından ilişkisel tarama modeli ile yürütülmüştür. Çalışma grubunu 515 üniversite öğrencisi oluşturmuştur. Araştırmada Sosyal Medya Kullanım Yorgunluğu, Karşıt-Empati ve Üniversite Öğrencileri İçin Siber Zorbalık/Siber Mağduriyet Ölçekleri kullanılmıştır. Veriler SPSS ve AMOS programlarıyla analiz edilmiştir. Yapısal eşitlik modellemesi kapsamında iki ayrı model test edilmiştir. Birinci modelde bağımlı değişken siber zorbalık, ikinci modelde ise siber mağduriyet olarak ele alınmıştır. Bulgular, psikolojik yorgunluğun başkalarının acısından zevk alma ve başkalarının mutluluğundan rahatsız olma alt boyutlarını pozitif yönde ve anlamlı biçimde yordadığını göstermiştir. Siber zorbalık modelinde psikolojik yorgunluğun doğrudan etkisi anlamlı bulunmazken, her iki karşıt empati alt boyutu üzerinden gerçekleşen dolaylı etkiler anlamlıdır. Siber mağduriyet modelinde ise psikolojik yorgunluğun hem doğrudan etkisi hem de iki aracı değişken üzerinden dolaylı etkileri anlamlı bulunmuştur. Sonuçlar, sosyal medya kullanımına bağlı psikolojik yorgunluğun siber zorbalık ve siber mağduriyetle ilişkisini açıklamada karşıt empati alt boyutlarının önemli sosyal-duygusal mekanizmalar olduğunu göstermektedir.

Anahtar Kelimeler

• Sosyal medya kullanım yorgunluğu
• karşıt empati
• siber zorbalık
• siber mağduriyet
• yapısal eşitlik modeli

Destekleyen Kurum

Bu çalışma herhangi bir kurum veya kuruluş tarafından desteklenmemiştir.

Etik Beyan

Araştırma süreci etik ilkelere uygun olarak yürütülmüştür. Çalışma için Mersin Üniversitesi Rektörlüğü Eğitim Bilimleri Etik Kurulundan etik kurul izni alınmıştır. Etik kurul onayı 11.05.2026 tarihli, 9 toplantı sayılı ve 145 karar numaralı belge ile verilmiştir. Bu araştırmada tüm süreçler American Educational Research Association (AERA, 2011), American Psychological Association (APA, 2020) ve Millî Eğitim Bakanlığı PDR Hizmetleri Etik Yönergeleri (MEB, 2020) tarafından belirtilen standartlar çerçevesinde yürütülmüştür. Katılımcılardan ad-soyad, adres, iletişim bilgisi, okul adı ve kimlik numarası gibi doğrudan ya da dolaylı olarak tanımlayıcı bilgiler istenmemiştir. Elde edilen verilerin bireysel değil, toplu olarak değerlendirileceği katılımcılara bildirilmiştir. Katılımcılara araştırmaya katılımın gönüllülüğe dayalı olduğu ve istedikleri anda herhangi bir neden belirtmeden çalışmadan ayrılabilecekleri açıklanmıştır.

Teşekkür

Yazar, araştırmaya gönüllü olarak katılan tüm katılımcılara teşekkür eder.

Psychological Fatigue, Cyberbullying, and Cybervictimization Among University Students: The Mediating Role of Counter-Empathy

Öz

The aim of this study was to examine the mediating role of the two subdimensions of counter-empathy—pleasure in others’ pain and discomfort with others’ happiness—in the relationship between psychological fatigue related to social media use and cyberbullying and cybervictimization among university students. The study was conducted using a quantitative research approach and a correlational survey design. The study group consisted of 515 university students. The Social Media Use Fatigue Scale, the Counter-Empathy Scale, and the Cyberbullying/Cybervictimization Scale for University Students were used as data collection instruments. The data were analyzed using SPSS and AMOS. Within the scope of structural equation modeling, two separate models were tested. In the first model, cyberbullying was treated as the dependent variable, whereas in the second model, cybervictimization was treated as the dependent variable. The findings showed that psychological fatigue positively and significantly predicted both pleasure in others’ pain and discomfort with others’ happiness. In the cyberbullying model, the direct effect of psychological fatigue was not significant; however, the indirect effects through both subdimensions of counter-empathy were significant. In the cybervictimization model, both the direct effect of psychological fatigue and the indirect effects through the two mediator variables were significant. The results indicate that the subdimensions of counter-empathy are important socio-emotional mechanisms in explaining the relationship between psychological fatigue related to social media use and cyberbullying and cybervictimization.

Anahtar Kelimeler

• Social media use fatigue
• counter-empathy
• cyberbullying
• cybervictimization
• structural equation modeling

Destekleyen Kurum

This study was not supported by any institution or organization.

Etik Beyan

The research process was conducted in accordance with ethical principles. Ethical approval for the study was obtained from the Educational Sciences Ethics Committee of Mersin University Rectorate. The ethics committee approval was granted with the document dated 11.05.2026, meeting number 9, and decision number 145. All procedures in this study were carried out within the framework of the standards specified by the American Educational Research Association (AERA, 2011), the American Psychological Association (APA, 2020), and the Ministry of National Education Psychological Counseling and Guidance Services Ethical Guidelines (MoNE, 2020). Participants were not asked to provide any directly or indirectly identifying information, such as name and surname, address, contact information, school name, or identification number. Participants were informed that the data obtained would be evaluated collectively rather than individually. They were also informed that participation in the study was voluntary and that they could withdraw from the study at any time without providing any reason.

Teşekkür

The author would like to thank all participants who voluntarily took part in the study.

Kaynakça

1. American Educational Research Association (2011). Code of ethics. https://www.aera.net/About-AERA/AERA-Rules-Policies/Professional-Ethics
2. American Psychological Association (2020). Publication manual of the American Psychological Association (7th ed.). American Psychological Association.
3. Ang, R. P., & Goh, D. H. (2010). Cyberbullying among adolescents: The role of affective and cognitive empathy, and gender. Child Psychiatry & Human Development, 41(4), 387–397. https://doi.org/10.1007/s10578-010-0176-3
4. Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831–858. https://doi.org/10.2307/41409963
5. Barnett, R. C., Brennan, R. T., Gareis, K. C., Ertel, K. A., Berkman, L. F., & Almeida, D. M. (2012). Conservation of Resources theory in the context of multiple roles: an analysis of within- and cross-role mediational pathways. Community, Work & Family, 15(2), 131–148. https://doi.org/10.1080/13668803.2010.539066
6. Batmaz, H., Türk, N., Kaya, A., & Yıldırım, M. (2022). Cyberbullying and cyber victimization: Examining mediating roles of empathy and resilience. Current Psychology, 42(35), 30959–30969. https://doi.org/10.1007/s12144-022-04134-3
7. Bayar, A., Kurt, B. S., Mutlu, M., Öven, Ç., & Bayar, Y. (2023). The validity and the reliability study of a Cyber Victimization/Bullying Scale for university students. Research on Education and Psychology, 7(1), 149-163. https://doi.org/10.54535/rep.1297063
8. Belsey, B. (2008). Cyberbullying. Cyberbullying.org. http://www.cyberbullying.org

9. Bilge, Y., & Bilge, Y. (2024). Turkish Adaptation of Counter-Empathy Scale and its Psychometric Properties. Psikiyatride Güncel Yaklaşımlar, 16(1), 249-261. https://doi.org/10.18863/pgy.1539181
10. Bright, L. F., Kleiser, S. B., & Grau, S. L. (2015). Too much Facebook? An exploratory examination of social media fatigue. Computers in Human Behavior, 44, 148–155. https://doi.org/10.1016/j.chb.2014.11.048
11. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage.
12. Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). Routledge.
13. Cao, B., & Lin, W. Y. (2015). How do victims react to cyberbullying on social networking sites? The influence of previous cyberbullying victimization experiences. Computers in Human Behavior, 52, 458-465. https://doi.org/10.1016/j.chb.2015.06.009
14. Cao, X., Khan, A. N., Zaigham, G. H. K., & Khan, N. A. (2018). The stimulators of social media fatigue among students: Role of moral disengagement. Journal of Educational Computing Research, 57(5), 1183–1207. https://doi.org/10.1177/0735633118781907
15. Cecconi, C., Poggi, I., & D’Errico, F. (2020). Schadenfreude: Malicious joy in social media interactions. Frontiers in Psychology, 11, 558282. https://doi.org/10.3389/fpsyg.2020.558282
16. Chan, T. K. H., Cheung, C. M. K., & Lee, Z. W. Y. (2021). Cyberbullying on social networking sites: A literature review and future research directions. Information & Management, 58(2), Article 103411. https://doi.org/10.1016/j.im.2020.103411
17. Chan, T. K. H., Cheung, C. M. K., & Wong, R. Y. M. (2019). Cyberbullying on social networking sites: The crime opportunity and affordance perspectives. Journal of Management Information Systems, 36(2), 574–609. https://doi.org/10.1080/07421222.2019.1599500
18. Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
19. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
20. Curran, P. G. (2016). Methods for the detection of carelessly invalid responses in survey data. Journal of Experimental Social Psychology, 66, 4–19. https://doi.org/10.1016/j.jesp.2015.07.006
21. Decety, J., & Cowell, J. M. (2014). The complex relation between morality and empathy. Trends in Cognitive Sciences, 18(7), 337–339. https://doi.org/10.1016/j.tics.2014.04.008
22. Dhir, A., Yossatorn, Y., Kaur, P., & Chen, S. (2018). Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management, 40, 141–152. https://doi.org/10.1016/j.ijinfomgt.2018.01.012
23. Fang, J., Wang, X., Yuan, K. H., Wen, Z., Yu, X., & Zhang, G. (2020). Callous-unemotional traits and cyberbullying perpetration: The mediating role of moral disengagement and the moderating role of empathy. Personality and Individual Differences, 157, Article 109829. https://doi.org/10.1016/j.paid.2020.109829
24. Gahagan, K., Vaterlaus, J. M., & Frost, L. R. (2016). College student cyberbullying on social networking sites: Conceptualization, prevalence, and perceived bystander responsibility. Computers in Human Behavior, 55, 1097–1105. https://doi.org/10.1016/j.chb.2015.11.019
25. Giumetti, G. W., & Kowalski, R. M. (2015). Cyberbullying matters: Examining the incremental impact of cyberbullying on outcomes over and above traditional bullying in North America. In Cyberbullying across the globe: Gender, family, and mental health (pp. 117-130). Springer. https://doi.org/10.1007/978-3-319-25552-1_6
26. Giumetti, G. W., & Kowalski, R. M. (2022). Cyberbullying via social media and well-being. Current Opinion in Psychology, 45, Article 101314. https://doi.org/10.1016/j.copsyc.2022.101314
27. Goldberg, X. (2023). Social comparison links social media use and well-being. Nature Reviews Psychology, 2(11), 658. https://doi.org/10.1038/s44159-023-00244-2
28. Han, B. (2016). Social media burnout: Definition, measurement instrument, and why we care. Journal of Computer Information Systems, 58(2), 122–130. https://doi.org/10.1080/08874417.2016.1208064
29. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford.
30. Hinduja, S., & Patchin, J. W. (2009). Bullying beyond the schoolyard: Preventing and responding to cyberbullying. Corwin Press.
31. Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513–524. https://doi.org/10.1037/0003-066X.44.3.513
32. Hobfoll, S. E., Halbesleben, J., Neveu, J. P., & Westman, M. (2018). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behavior, 5, 103–128. https://doi.org/10.1146/annurev-orgpsych-032117-104640
33. Hornik, J., Rachamim, M., Shaanan Satchi, R., & Grossman, O. (2021). A dark side of human behavior: Development of a malicious sentiments scale to others’ success or failure. Computers in Human Behavior Reports, 4, Article 100112. https://doi.org/10.1016/j.chbr.2021.100112
34. Hoşgör, H. K. (2025). Dijital yerliler için sosyal medya kullanım yorgunluğu ölçeği’nin geliştirilmesi. İstanbul Arel Üniversitesi İletişim Çalışmaları Dergisi, 27, 1-25. https://izlik.org/JA49MX72SF
35. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
36. Jie, J., & Wang, Y. (2023). Development and validation of the counter-empathy scale. Psychological reports, 126(4), 2078-2095. https://doi.org/10.1177/00332941221076775
37. Jose, P. E., Kljakovic, M., Scheib, E., & Notter, O. (2012). The joint development of traditional bullying and victimization with cyber bullying and victimization in adolescence. Journal of Research on Adolescence, 22(2), 301–309. https://doi.org/10.1111/j.1532-7795.2011.00764.x
38. Kim, H. Y. (2013). Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis. Restorative Dentistry & Endodontics, 38(1), 52–54. https://doi.org/10.5395/rde.2013.38.1.52
39. Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Publications.
40. Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). The Guilford Press.
41. Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140(4), 1073–1137. https://doi.org/10.1037/a0035618
42. Krasnova, H., Widjaja, T., Buxmann, P., Wenninger, H., & Benbasat, I. (2015). Why following friends can hurt you: An exploratory investigation of the effects of envy on social networking sites among college-age users. Information Systems Research, 26(3), 585–601. https://doi.org/10.1287/isre.2015.0588
43. Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51–61. https://doi.org/10.1016/j.chb.2015.08.011
44. Livingstone, S., & Smith, P. K. (2014). Annual research review: Harms experienced by child users of online and mobile technologies: The nature, prevalence and management of sexual and aggressive risks in the digital age. Journal of Child Psychology and Psychiatry, 55(6), 635–654. https://doi.org/10.1111/jcpp.12197
45. Martínez-Monteagudo, M. C., Delgado, B., García-Fernández, J. M., & Ruíz-Esteban, C. (2020). Cyberbullying in the university setting: Relationship with emotional problems and adaptation to the university. Frontiers in Psychology, 10, Article 3074. https://doi.org/10.3389/fpsyg.2019.03074
46. Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12(1), 23–44. https://doi.org/10.1037/1082-989X.12.1.23
47. Meade, A. W., & Craig, S. B. (2012). Identifying careless responses in survey data. Psychological Methods, 17(3), 437–455. https://doi.org/10.1037/a0028085
48. Melchers, M., Li, M., Chen, Y., Zhang, W., & Montag, C. (2015). Low empathy is associated with problematic use of the Internet: Empirical evidence from China and Germany. Asian Journal of Psychiatry, 17, 56–60. https://doi.org/10.1016/j.ajp.2015.06.019
49. Millî Eğitim Bakanlığı [MEB]. (2020, Ağustos). Rehberlik ve psikolojik danışma hizmetleri etik yönergesi. https://orgm.meb.gov.tr/meb_iys_dosyalar/2020_08/31230349_RPDH_Etik_Yonergesi_.pdf O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673-690. https://doi.org/10.1007/s11135-006-9018-6
50. Park, S. Y., & Baek, Y. M. (2018). Two faces of social comparison on Facebook: The interplay between social comparison orientation, emotions, and psychological well-being. Computers in Human Behavior, 79, 83–93. https://doi.org/10.1016/j.chb.2017.10.028
51. Peluchette, J. V., Karl, K. A., Wood, C., & Williams, J. (2015). Cyberbullying victimization: Do victims’ personality and risky social network behaviors contribute to the problem? Computers in Human Behavior, 52, 424–435. https://doi.org/10.1016/j.chb.2015.06.028
52. Ravindran, T., Yeow Kuan, A. C., & Hoe Lian, D. G. (2014). Antecedents and effects of social network fatigue. Journal of the Association for Information Science and Technology, 65(11), 2306–2320. https://doi.org/10.1002/asi.23122
53. Razali, N. M., & Wah, Y. B. (2011). Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21-33. https://www.nrc.gov/docs/ML1714/ML17143A100.pdf
54. Renati, R., Berrone, C., & Zanetti, M. A. (2012). Morally disengaged and unempathic: Do cyberbullies fit these definitions? An exploratory study. Cyberpsychology, Behavior, and Social Networking, 15(8), 391–398. https://doi.org/10.1089/cyber.2012.0046
55. Runions, K. C., & Bak, M. (2015). Online moral disengagement, cyberbullying, and cyber-aggression. Cyberpsychology, Behavior, and Social Networking, 18(7), 400–405. https://doi.org/10.1089/cyber.2014.0670
56. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23–74.
57. Sheng, N., Yang, C., Han, L., & Jou, M. (2023). Too much overload and concerns: Antecedents of social media fatigue and the mediating role of emotional exhaustion. Computers in Human Behavior, 139, Article 107500. https://doi.org/10.1016/j.chb.2022.107500
58. Smith, R. H., & Kim, S. H. (2007). Comprehending envy. Psychological Bulletin, 133(1), 46–64. https://doi.org/10.1037/0033-2909.133.1.46
59. Smith, R. H., & van Dijk, W. W. (2018). Schadenfreude and gluckschmerz. Emotion Review, 10(4), 1–12. https://doi.org/10.1177/1754073918765657
60. Steffgen, G., König, A., Pfetsch, J., & Melzer, A. (2011). Are cyberbullies less empathic? Adolescents’ cyberbullying behavior and empathic responsiveness. Cyberpsychology, Behavior, and Social Networking, 14(11), 643–648. https://doi.org/10.1089/cyber.2010.0445
61. Suler, J. (2004). The online disinhibition effect. CyberPsychology & Behavior, 7(3), 321–326. https://doi.org/10.1089/1094931041291295
62. Sümer, N. (2000). Yapısal eşitlik modelleri: Temel kavramlar ve örnek uygulamalar. Türk Psikoloji Yazıları, 3(6), 49–74.
63. Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
64. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (5th ed., pp. 481–498). Pearson.
65. Takahashi, H., Kato, M., Matsuura, M., Mobbs, D., Suhara, T., & Okubo, Y. (2009). When your gain is my pain and your pain is my gain: Neural correlates of envy and schadenfreude. Science, 323(5916), 937–939. https://doi.org/10.1126/science.1165604
66. Tampke, E. C., Fite, P. J., & Cooley, J. L. (2020). Bidirectional associations between affective empathy and proactive and reactive aggression. Aggressive Behavior, 46(5), 394–404. https://doi.org/10.1002/ab.21891
67. Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26(3), 277–287. https://doi.org/10.1016/j.chb.2009.11.014
68. Topcu, Ç., & Erdur-Baker, Ö. (2012). Affective and cognitive empathy as mediators of gender differences in cyber and traditional bullying. School Psychology International, 33(5), 550–561. https://doi.org/10.1177/0143034312446882
69. van de Ven, N. (2018). Schadenfreude and gluckschmerz are emotional signals of (im)balance. Emotion Review, 10(4), 305–306. https://doi.org/10.1177/1754073918768883 van Dijk, W. W., & Ouwerkerk, J. W. (Eds.). (2014). Schadenfreude: Understanding pleasure at the misfortunes of others. Cambridge University Press. https://doi.org/10.1017/cbo9781139084246
70. Verduyn, P., Gugushvili, N., Massar, K., Täht, K., & Kross, E. (2020). Social comparison on social networking sites. Current Opinion in Psychology, 36, 32–37. https://doi.org/10.1016/j.copsyc.2020.04.002
71. Vismara, M., Girone, N., Conti, D., Nicolini, G., & Dell’Osso, B. (2022). The current status of cyberbullying research: A short review of the literature. Current Opinion in Behavioral Sciences, 46, Article 101152. https://doi.org/10.1016/j.cobeha.2022.101152
72. Vogel, E. A., Rose, J. P., Roberts, L. R., & Eckles, K. (2014). Social comparison, social media, and self-esteem. Psychology of Popular Media Culture, 3(4), 206–222. https://doi.org/10.1037/ppm0000047
73. Wang, L., & Ge, T. (2021). Does victimization predict cyberbullying perpetration? Examining depression as a mediator and self-control as a moderator. Personality and Individual Differences, 183, Article 111135. https://doi.org/10.1016/j.paid.2021.111135
74. Wang, S., Lilienfeld, S. O., & Rochat, P. (2019). Schadenfreude deconstructed and reconstructed: A tripartite motivational model. New Ideas in Psychology, 52, 1–11. https://doi.org/10.1016/j.newideapsych.2018.09.002
75. Wang, X., Wang, S., & Zeng, X. (2023). Does sensation seeking lead to adolescents’ cyberbullying perpetration? The mediating role of moral disengagement and the moderating role of perceived social support. Child Psychiatry & Human Development, 55(6), 1724–1735. https://doi.org/10.1007/s10578-023-01527-8
76. Wei, L., & Liu, B. (2020). Reactions to others’ misfortune on social media: Effects of homophily and publicness on schadenfreude, empathy, and perceived deservingness. Computers in Human Behavior, 102, 159–168. https://doi.org/10.1016/j.chb.2019.08.002
77. Xiao, L., & Mou, J. (2019). Social media fatigue: Technological antecedents and the moderating roles of personality traits: The case of WeChat. Computers in Human Behavior, 101, 297–310. https://doi.org/10.1016/j.chb.2019.08.001
78. Zalaquett, C. P., & Chatters, S. J. (2014). Cyberbullying in college: Frequency, characteristics, and practical implications. Sage Open, 4(1), https://doi.org/10.1177/2158244014526721
79. Zheng, H., & Ling, R. (2021). Drivers of social media fatigue: A systematic review. Telematics and Informatics, 64, Article 101696. https://doi.org/10.1016/j.tele.2021.101696
80. Zych, I., Baldry, A. C., Farrington, D. P., & Llorent, V. J. (2019a). Are children involved in cyberbullying low on empathy? A systematic review and meta-analysis of research on empathy versus different cyberbullying roles. Aggression and Violent Behavior, 45, 83–97. https://doi.org/10.1016/j.avb.2018.03.004
81. Zych, I., Farrington, D. P., & Ttofi, M. M. (2019b). Protective factors against bullying and cyberbullying: A systematic review of meta-analyses. Aggression and Violent Behavior, 45, 4–19. https://doi.org/10.1016/j.avb.2018.06.008