• Architecture and Design
  • Asian and Pacific Studies
  • Business and Economics
  • Classical and Ancient Near Eastern Studies
  • Computer Sciences
  • Cultural Studies
  • Engineering
  • General Interest
  • Geosciences
  • Industrial Chemistry
  • Islamic and Middle Eastern Studies
  • Jewish Studies
  • Library and Information Science, Book Studies
  • Life Sciences
  • Linguistics and Semiotics
  • Literary Studies
  • Materials Sciences
  • Mathematics
  • Social Sciences
  • Sports and Recreation
  • Theology and Religion
  • Publish your article
  • The role of authors
  • Promoting your article
  • Abstracting & indexing
  • Publishing Ethics
  • Why publish with De Gruyter
  • How to publish with De Gruyter
  • Our book series
  • Our subject areas
  • Your digital product at De Gruyter
  • Contribute to our reference works
  • Product information
  • Tools & resources
  • Product Information
  • Promotional Materials
  • Orders and Inquiries
  • FAQ for Library Suppliers and Book Sellers
  • Repository Policy
  • Free access policy
  • Open Access agreements
  • Database portals
  • For Authors
  • Customer service
  • People + Culture
  • Journal Management
  • How to join us
  • Working at De Gruyter
  • Mission & Vision
  • De Gruyter Foundation
  • De Gruyter Ebound
  • Our Responsibility
  • Partner publishers

cyber bullying literature review

Your purchase has been completed. Your documents are now available to view.

Cyberbullying in adolescents: a literature review

Cyberbullying is a universal public health concern that affects adolescents. The growing usage of electronic gadgets and the Internet has been connected to a rise in cyberbullying. The increasing use of the Internet, along with the negative outcomes of cyberbullying on adolescents, has required the study of cyberbullying. In this paper author reviews existing literature on cyberbullying among adolescents. The concept of cyberbullying is explained, including definitions, types of cyberbullying, characteristics or features of victims and cyberbullies, risk factors or causes underlying cyberbullying, and the harmful consequences of cyberbullying to adolescents. Furthermore, examples of programs or intervention to prevent cyberbullying and recommendations for further studies are presented.

Research funding: None declared.

Author contributions: Author has accepted responsibility for the entire content of this manuscript and approved its submission.

Competing interests: Author states no conflict of interest.

Informed consent: Not applicable.

Ethical approval: Not applicable.

1. Ovigli, D, Colombo, P. Information and communication technologies (ICT) in educational research in science museums in Brazil. IJEDICT 2020;16:272–86. Search in Google Scholar

2. Eleuteri, S, Saladino, V, Verrastro, V. Identity, relationships, sexuality, and risky behaviors of adolescents in the context of social media. Sex Relatsh Ther 2017;32:354–65. https://doi.org/10.1080/14681994.2017.1397953 . Search in Google Scholar

3. Saladino, V, Eleuteri, S, Verrastro, V, Petruccelli, F. Perception of cyberbullying in adolescence: a brief evaluation among Italian students. Front Psychol 2020;11:1–7. https://doi.org/10.3389/fpsyg.2020.607225 . Search in Google Scholar PubMed PubMed Central

4. Beale, AV, Hall, KR. Cyberbullying: what school administrators (and parents) can do. Clearing House 2007;81:8–12. https://doi.org/10.3200/tchs.81.1.8-12 . Search in Google Scholar

5. Brody, N, Vangelisti, AL. Bystander intervention in cyberbullying. Commun Monogr 2016;83:94–119. https://doi.org/10.1080/03637751.2015.1044256 . Search in Google Scholar

6. Athanasiou, K, Melegkovits, E, Andrie, EK, Magoulas, C, Tzavara, CK, Richardson, C. Cross-national aspects of cyberbullying victimization among 14–17-year-old adolescents across seven European countries. BMC Publ Health 2018;18:800. https://doi.org/10.1186/s12889-018-5682-4 . Search in Google Scholar PubMed PubMed Central

7. González-Cabrera, J, Tourón, J, Machimbarrena, JM, Gutiérrez-Ortega, M, Álvarez-Bardón, A, Garaigordobil, M. Cyberbullying in gifted students: prevalence and psychological well-being in a Spanish sample. Int J Environ Res Public Health 2019;16:2173. 10.3390/ijerph16122173 Search in Google Scholar PubMed PubMed Central

8. Lee, C, Shin, N. Prevalence of cyberbullying and predictors of cyberbullying perpetration among Korean adolescents. Comput Hum Behav 2017;68:352–8. https://doi.org/10.1016/j.chb.2016.11.047 . Search in Google Scholar

9. Safaria, T. Prevalence and impact of cyberbullying in a sample of Indonesian junior high school students. The Turk Online J Educ Technol 2016;15:82–91. Search in Google Scholar

10. Lee, M-S, Wu, W, Svanström, L, Dalal, K. Cyber bullying prevention: intervention in Taiwan. PLoS One 2013;8:e64031. https://doi.org/10.1371/journal.pone.0064031 . Search in Google Scholar PubMed PubMed Central

11. Whittaker, E, Kowalski, RM. Cyberbullying via social media. J Sch Violence 2015;14:11–29. https://doi.org/10.1080/15388220.2014.949377 . Search in Google Scholar

12. Vaillancourt, T, Faris, R, Mishna, F. Cyberbullying in children and youth: implications for health and clinical practice. Can J Psychiatry 2016;62:368–73. https://doi.org/10.1177/0706743716684791 . Search in Google Scholar PubMed PubMed Central

13. Nixon, C. Current perspectives: the impact of cyberbullying on adolescent health. Adolesc Health Med Ther 2014;5:143–58. https://doi.org/10.2147/ahmt.s36456 . Search in Google Scholar PubMed PubMed Central

14. Heiman, T, Shemesh, D. Cyberbullying experience and gender differences among adolescents in different educational settings. J Learn Disabil 2013;48:146–55. https://doi.org/10.1177/0022219413492855 . Search in Google Scholar PubMed

15. Paris, S, Robert, D. Cyberbullying by adolescents: a preliminary assessment. Educ Forum 2006;70:21–36. 10.1080/00131720508984869 Search in Google Scholar

16. Patchin, JW, Hinduja, S. Bullies move beyond the schoolyard A preliminary look at cyberbullying. Youth Violence Juv Justice 2006;4:148–69. https://doi.org/10.1177/1541204006286288 . Search in Google Scholar

17. Kowalski, RM, Limber, SP. Electronic bullying among middle school students. J Adolesc Health 2007;41(6 Suppl 1):S22–30. https://doi.org/10.1016/j.jadohealth.2007.08.017 . Search in Google Scholar PubMed

18. Raskauskas, J, Stoltz, AD. Involvement in traditional and electronic bullying among adolescents. Dev Psychol 2007;43:564–75. https://doi.org/10.1037/0012-1649.43.3.564 . Search in Google Scholar PubMed

19. Menesini, E, Nocentini, A, Palladino, BE, Frisén, A, Berne, S, Rosario, R. Cyberbullying definition among adolescents: a comparison across six European countries. Cyberpsychol Behav Soc Netw 2012;15:455–63. https://doi.org/10.1089/cyber.2012.0040 . Search in Google Scholar PubMed PubMed Central

20. Dooley, JJ, Pyżalski, J, Cross, D. Cyberbullying versus face-to-face bullying: a theoretical and conceptual review. Z Psychol 2009;217:182–8. https://doi.org/10.1027/0044-3409.217.4.182 . Search in Google Scholar

21. Nocentini, A, Calmaestra, J, Anja, A, Scheithauer, H, Ortega, R, Menesini, E. Cyberbullying: labels, behaviours and definition in three European countries. Aust J Guid Counsell 2010;20:129–42. https://doi.org/10.1375/ajgc.20.2.129 . Search in Google Scholar

22. Aboujaoude, E, Savage, MW, Starcevic, V, Salame, WO. Cyberbullying: review of an old problem gone viral. J Adolesc Health 2015;57:10–8. https://doi.org/10.1016/j.jadohealth.2015.04.011 . Search in Google Scholar PubMed

23. Ferrara, P, Ianniello, F, Villani, A, Corsello, G. Cyberbullying a modern form of bullying: let’s talk about this health and social problem. Ital J Pediatr 2018;44:14. https://doi.org/10.1186/s13052-018-0446-4 . Search in Google Scholar PubMed PubMed Central

24. Smith, PK, Mahdavi, J, Carvalho, M, Fisher, S, Russell, S, Tippett, N. Cyberbullying: its nature and impact in secondary school pupils. JCPP (J Child Psychol Psychiatry) 2008;49:376–85. https://doi.org/10.1111/j.1469-7610.2007.01846.x . Search in Google Scholar PubMed

25. Garett, R, Lord, LR, Young, SD. Associations between social media and cyberbullying: a review of the literature. mHealth 2016;2:46. https://doi.org/10.21037/mhealth.2016.12.01 . Search in Google Scholar PubMed PubMed Central

26. Li, Q. Bullying in the new playground: research into cyberbullying and cyber victimisation. Australas J Educ Technol 2007;23:435–54. 10.14742/ajet.1245 Search in Google Scholar

27. Zeljka, D, Vesna, C, Rajkovača, I, Včev, A, Miskic, D, Miskic, B. Cyberbullying in early adolescence: is there a difference between urban and rural environment? Am J Biomed Sci Res 2019;1:191–6. 10.34297/AJBSR.2019.01.000542 Search in Google Scholar

28. Ybarra, ML, Mitchell, KJ, Wolak, J, Finkelhor, D. Examining characteristics and associated distress related to internet harassment: findings from the second youth internet safety survey. Pediatrics 2006;118:e1169–77. https://doi.org/10.1542/peds.2006-0815 . Search in Google Scholar PubMed

29. Li, Q. Cyberbullying in schools: a research of gender differences. Sch Psychol Int 2006;27:157–70. 10.1177/0143034306064547 Search in Google Scholar

30. Ybarra, ML, Mitchell, KJ. Youth engaging in online harassment: associations with caregiver–child relationships, Internet use, and personal characteristics. J Adolesc 2004;27:319–36. https://doi.org/10.1016/s0140-1971(04)00039-9 . Search in Google Scholar

31. Dhond, V, Richter, S, McKenna, B, editors. Exploratory research to identify the characteristics of cyber victims on social media in New Zealand . Cham: Springer International Publishing; 2019. 10.1007/978-3-030-11395-7_18 Search in Google Scholar

32. Ybarra, ML, Mitchell, KJ. Prevalence and frequency of Internet harassment instigation: implications for adolescent health. J Adolesc Health 2007;41:189–95. https://doi.org/10.1016/j.jadohealth.2007.03.005 . Search in Google Scholar PubMed

33. Zhong, J, Zheng, Y, Huang, X, Mo, D, Gong, J, Li, M. Study of the influencing factors of cyberbullying among Chinese college students incorporated with digital citizenship: from the perspective of individual students. Front Psychol 2021;12:621418. https://doi.org/10.3389/fpsyg.2021.621418 . Search in Google Scholar PubMed PubMed Central

34. Wong-Lo, M, Bullock, LM, Gable, RA. Cyber bullying: practices to face digital aggression. Emot Behav Difficulties 2011;16:317–25. https://doi.org/10.1080/13632752.2011.595098 . Search in Google Scholar

35. Barlett, C, Gentile, D. Attacking others online: the formation of cyberbullying in late adolescence. Psychol Popular Media Culture 2012;1:123–35. https://doi.org/10.1037/a0028113 . Search in Google Scholar

36. Mason. Cyberbullying: a preliminary assessment for school personnel. Psychol Sch 2008;45:323–48. 10.1002/pits.20301 Search in Google Scholar

37. Pratto, F, Stewart, AL, Zeineddine, F. When inequality fails: power, group dominance, and societal change. J Soc Polit Psychol 2013;1:132–60. https://doi.org/10.5964/jspp.v1i1.97 . Search in Google Scholar

38. Koski, JE, Xie, H, Olson, IR. Understanding social hierarchies: the neural and psychological foundations of status perception. Soc Neurosci 2015;10:527–50. https://doi.org/10.1080/17470919.2015.1013223 . Search in Google Scholar PubMed PubMed Central

39. Walker, C, Sockman, B, Koehn, S. An exploratory study of cyberbullying with undergraduate university students. TechTrends 2011;55:31–8. 10.1007/s11528-011-0481-0 Search in Google Scholar

40. Pratto, F, Sidanius, J, Levin, S. Social dominance theory and the dynamics of intergroup relations: Taking stock and looking forward. Eur Rev Soc Psychol 2006;17:271–320. https://doi.org/10.1080/10463280601055772 . Search in Google Scholar

41. Sidanius, J, Pratto, F, Van Laar, C, Levin, S. Social dominance theory: its agenda and method. Polit Psychol 2004;25:845–80. https://doi.org/10.1111/j.1467-9221.2004.00401.x . Search in Google Scholar

42. Closson, LM. Aggressive and prosocial behaviors within early adolescent friendship cliques: what’s status got to do with it? Merrill-Palmer Q 2009;55:406–35. https://doi.org/10.1353/mpq.0.0035 . Search in Google Scholar

43. Salmivalli, C, Kärnä, A, Poskiparta, E. Counteracting bullying in Finland: the KiVa program and its effect on different forms of being bullied. IJBD (Int J Behav Dev) 2011;35:405–11. https://doi.org/10.1177/0165025411407457 . Search in Google Scholar

44. Chisholm, JF. Review of the status of cyberbullying and cyberbullying prevention. J Inf Syst Educ 2014;25:77–87. Search in Google Scholar

45. Bonanno, RA, Hymel, S. Cyber bullying and internalizing difficulties: above and beyond the impact of traditional forms of bullying. J Youth Adolesc 2013;42:685–97. https://doi.org/10.1007/s10964-013-9937-1 . Search in Google Scholar PubMed

46. Wolke, D, Copeland, WE, Angold, A, Costello, EJ. Impact of bullying in childhood on adult health, wealth, crime, and social outcomes. Psychol Sci 2013;24:1958–70. https://doi.org/10.1177/0956797613481608 . Search in Google Scholar PubMed PubMed Central

47. Foody, M, Samara, M, Carlbring, P. A review of cyberbullying and suggestions for online psychological therapy. Internet Interv 2015;2:235–42. https://doi.org/10.1016/j.invent.2015.05.002 . Search in Google Scholar

48. Dredge, R, Gleeson, J, Garcia, X. Cyberbullying in social networking sites: an adolescent victim’s perspective. Comput Hum Behav 2014;36:13–20. https://doi.org/10.1016/j.chb.2014.03.026 . Search in Google Scholar

49. Schenk, AM, Fremouw, WJ. Prevalence, psychological impact, and coping of cyberbully victims among college students. J Sch Violence 2012;11:21–37. https://doi.org/10.1080/15388220.2011.630310 . Search in Google Scholar

50. Burger, C, Bachmann, L. Perpetration and victimization in offline and cyber contexts: a variable- and person-oriented examination of associations and differences regarding domain-specific self-esteem and school adjustment. Int J Environ Res Publ Health 2021;18:10429. https://doi.org/10.3390/ijerph181910429 . Search in Google Scholar PubMed PubMed Central

51. Price, M, Dalgleish, J. Cyberbullying: experiences, impacts and coping strategies as described by Australian young people. Youth Stud Aust 2010;29:51–9. Search in Google Scholar

52. Jang, H, Song, J, Kim, R. Does the offline bully-victimization influence cyberbullying behavior among youths? Application of General Strain Theory. Comput Hum Behav 2014;31:85–93. https://doi.org/10.1016/j.chb.2013.10.007 . Search in Google Scholar

53. Ybarra, ML, West, M, Leaf, PJ. Examining the overlap in internet harassment and school bullying: implications for school intervention. J Adolesc Health 2007;41(6 Suppl 1):S42–50. https://doi.org/10.1016/j.jadohealth.2007.09.004 . Search in Google Scholar PubMed

54. Mishna, F, Kassabri, M, Gadalla, T, Daciuk, J. Risk factors or involvement in cyber bullying: victims, bullies and bully–victims. Child Youth Serv Rev 2012;34:63–70. https://doi.org/10.1016/j.childyouth.2011.08.032 . Search in Google Scholar

55. Wong, DSW, Chan, HC, Cheng, CHK. Cheng. Cyberbullying perpetration and victimization among adolescents in Hong Kong. Child Youth Serv Rev 2014;36:133–40. https://doi.org/10.1016/j.childyouth.2013.11.006 . Search in Google Scholar

56. Bauman, S, Toomey, RB, Walker, JL. Associations among bullying, cyberbullying, and suicide in high school students. J Adolesc 2013;36:341–50. https://doi.org/10.1016/j.adolescence.2012.12.001 . Search in Google Scholar PubMed

57. Fletcher, A, Yau, N, Jones, R, Allen, E, Viner, RM, Bonell, C. Brief report: cyberbullying perpetration and its associations with socio-demographics, aggressive behaviour at school, and mental health outcomes. J Adolesc 2014;37:1393–8. https://doi.org/10.1016/j.adolescence.2014.10.005 . Search in Google Scholar PubMed

58. Kraft, EM, Wang, J. Effectiveness of cyber bullying prevention strategies: a study on students’ perspectives. Int J Cyber Criminol 2009;3:513. Search in Google Scholar

59. Williford, A, Elledge, LC, Boulton, AJ, DePaolis, KJ, Little, TD, Salmivalli, C. Effects of the KiVa antibullying program on cyberbullying and cybervictimization frequency among Finnish youth. J Clin Child Adolesc Psychol 2013;42:820–33. https://doi.org/10.1080/15374416.2013.787623 . Search in Google Scholar PubMed

60. Menesini, E, Zambuto, V, Palladino, BE. 10 - online and school-based programs to prevent cyberbullying among Italian adolescents: what works, why, and under which circumstances. In: Campbell, M, Bauman, S, editors. Reducing cyberbullying in schools . Cambridge: Academic Press; 2018:35–43 pp. 10.1016/B978-0-12-811423-0.00010-9 Search in Google Scholar

61. David, A, Rio, J, Pueyo, A, Calvo, G. Effects of a cooperative learning intervention program on cyberbullying in secondary education: a case study. Qual Rep 2019;24:2426–40. Search in Google Scholar

62. Leung, ANM, Wong, N, Farver, JM. Farver. Testing the effectiveness of an E-course to combat cyberbullying. Cyberpsychol Behav Soc Netw 2019;22:569–77. https://doi.org/10.1089/cyber.2018.0609 . Search in Google Scholar PubMed

63. Barón, J, Buelga, S, Ayllón, E, Ferrer, B, Cava, M. Effects of intervention program Prev@cib on traditional bullying and cyberbullying. Int J Environ Res Publ Health 2019;16:527. 10.3390/ijerph16040527 Search in Google Scholar PubMed PubMed Central

64. Doane, A, Ehlke, S, Kelley, M. Bystanders against cyberbullying: a video program for college students. Int J Bull Prev 2020;2:41–52. https://doi.org/10.1007/s42380-019-00051-5 . Search in Google Scholar

© 2022 Walter de Gruyter GmbH, Berlin/Boston

  • X / Twitter

Supplementary Materials

Please login or register with De Gruyter to order this product.

International Journal of Adolescent Medicine and Health

Journal and Issue

Articles in the same issue.

Cyberbullying: A Systematic Literature Review to Identify the Factors Impelling University Students Towards Cyberbullying

Ieee account.

  • Change Username/Password
  • Update Address

Purchase Details

  • Payment Options
  • Order History
  • View Purchased Documents

Profile Information

  • Communications Preferences
  • Profession and Education
  • Technical Interests
  • US & Canada: +1 800 678 4333
  • Worldwide: +1 732 981 0060
  • Contact & Support
  • About IEEE Xplore
  • Accessibility
  • Terms of Use
  • Nondiscrimination Policy
  • Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Cyberbullying in adolescents: a literature review

Affiliation.

  • 1 Department of Health Education and Behavioral Sciences, Faculty of Public Health, Mahidol University, Bangkok 10400, Thailand.
  • PMID: 35245420
  • DOI: 10.1515/ijamh-2021-0133

Cyberbullying is a universal public health concern that affects adolescents. The growing usage of electronic gadgets and the Internet has been connected to a rise in cyberbullying. The increasing use of the Internet, along with the negative outcomes of cyberbullying on adolescents, has required the study of cyberbullying. In this paper author reviews existing literature on cyberbullying among adolescents. The concept of cyberbullying is explained, including definitions, types of cyberbullying, characteristics or features of victims and cyberbullies, risk factors or causes underlying cyberbullying, and the harmful consequences of cyberbullying to adolescents. Furthermore, examples of programs or intervention to prevent cyberbullying and recommendations for further studies are presented.

Keywords: adolescents; cyberbullying; literature review.

© 2022 Walter de Gruyter GmbH, Berlin/Boston.

Publication types

  • Adolescent Behavior*
  • Bullying* / prevention & control
  • Crime Victims*
  • Cyberbullying*
  • Risk Factors

Cyberbullying detection and machine learning: a systematic literature review

  • Published: 24 July 2023
  • Volume 56 , pages 1375–1416, ( 2023 )

Cite this article

cyber bullying literature review

  • Vimala Balakrisnan 1 &
  • Mohammed Kaity 1  

781 Accesses

Explore all metrics

The rise in research work focusing on detection of cyberbullying incidents on social media platforms particularly reflect how dire cyberbullying consequences are, regardless of age, gender or location. This paper examines scholarly publications (i.e., 2011–2022) on cyberbullying detection using machine learning through a systematic literature review approach. Specifically, articles were sought from six academic databases (Web of Science, ScienceDirect, IEEE Xplore, Association for Computing Machinery, Scopus, and Google Scholar), resulting in the identification of 4126 articles. A redundancy check followed by eligibility screening and quality assessment resulted in 68 articles included in this review. This review focused on three key aspects, namely, machine learning algorithms used to detect cyberbullying, features, and performance measures, and further supported with classification roles, language of study, data source and type of media. The findings are discussed, and research challenges and future directions are provided for researchers to explore.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

cyber bullying literature review

Similar content being viewed by others

cyber bullying literature review

Can Machine Learning Really Detect Cyberbullying?

Leevesh Pokhun & Yasser M. Chuttur

cyber bullying literature review

Harnessing the Power of Interdisciplinary Research with Psychology-Informed Cyberbullying Detection Models

Deborah L. Hall, Yasin N. Silva, … Katie Baumel

cyber bullying literature review

Cyber Analyzer—A Machine Learning Approach for the Detection of Cyberbullying—A Survey

https://trends.google.com/trends/explore?date=2011-01-01%202022-12-31&q=deep%20learning&hl=en .

Agrawal S, Awekar A (2018) Deep learning for detecting cyberbullying across multiple social media platforms. In European Conference on Information Retrieval (pp. 141–153). Springer, Cham

Aizenkot D, Kashy-Rosenbaum G (2018) Cyberbullying in WhatsApp classmates’ groups: evaluation of an intervention program implemented in israeli elementary and middle schools. New Media & Society 20(12):4709–4727

Article   Google Scholar  

Akhter MP, Zheng JB, Naqvi IR, Abdelmajeed M, Sadiq MT (2020) Automatic Detection of Offensive Language for Urdu and Roman Urdu. IEEE Access 8:91213–91226.

Aldhyani TH, Al-Adhaileh MH, Alsubari SN (2022) Cyberbullying identification system based deep learning algorithms. Electronics 11(20):3273

Al-Garadi MA, Hussain MR, Khan N, Murtaza G, Nweke HF, Ali I, …, Gani A (2019) Predicting cyberbullying on social media in the big data era using machine learning algorithms: review of literature and open challenges. IEEE Access 7:70701–70718

Al-garadi MA, Varathan KD, Ravana SD (2016) Cybercrime detection in online communications: the experimental case of cyberbullying detection in the Twitter network. Comput Hum Behav 63:433–443

Al-Harigy LM, Al-Nuaim HA, Moradpoor N, Tan Z (2022) Building towards Automated Cyberbullying Detection: A Comparative Analysis. Computational Intelligence and Neuroscience, 2022

Alom Z, Carminati B, Ferrari E (2020) A deep learning model for Twitter spam detection. Online Social Networks and Media 18:100079

Alpaydin E (2010) Introduction to machine learning, 2nd edn. MIT Press

Ates EC, Bostanci E, Guzel MS (2021) Comparative performance of machine learning algorithms in cyberbullying detection: using turkish language preprocessing techniques. arXiv preprint arXiv :2101.12718

Ayo FE, Folorunso O, Ibharalu FT, Osinuga IA (2020) Machine learning techniques for hate speech classification of twitter data: state-of-the-art, future challenges and research directions. Comput Sci Rev 38:100311

Balakrishnan V (2015) Cyberbullying among young adults in Malaysia: the roles of gender, age and internet frequency. Comput Hum Behav 46:149–157

Balakrishnan V, Khan S, Arabnia HR (2020a) Improving cyberbullying detection using Twitter users’ psychological features and machine learning. Computers & Security 90:101710

Balakrishnan V, Khan S, Arabnia HR (2020b) Improving cyberbullying detection using Twitter users’ psychological features and machine learning. Computers & Security 90:101710

Balakrishnan V, Khan S, Fernandez T, Arabnia HR (2019) Cyberbullying detection on twitter using Big Five and Dark Triad features. Pers Individ Differ 141, 252–257.

Bretschneider U, Wöhner T, Peters R (2014) Detecting online harassment in social networks.

Buan TA, Ramachandra R (2020) Automated Cyberbullying Detection in Social Media Using an SVM Activated Stacked Convolution LSTM Network. In Proceedings of the 2020 the 4th International Conference on Compute and Data Analysis (pp. 170–174)

Camerini AL, Marciano L, Carrara A, Schulz PJ (2020) Cyberbullying perpetration and victimization among children and adolescents: a systematic review of longitudinal studies. Telematics Inform 49:101362

Chatzakou D, Kourtellis N, Blackburn J, De Cristofaro E, Stringhini G, Vakali A (2017) Mean birds: Detecting aggression and bullying on twitter. In Proceedings of the 2017 ACM on web science conference (pp. 13–22)

Chavan VS, Shylaja SS (2015) Machine learning approach for detection of cyber-aggressive comments by peers on social media network. In 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 2354–2358). IEEE

Cheng L, Guo R, Silva YN, Hall D, Liu H (2021) Modeling temporal patterns of cyberbullying detection with hierarchical attention networks. ACM/IMS Trans Data Sci 2(2):1–23

Cheng L, Li J, Silva YN, Hall DL, Liu H (2019) Xbully: Cyberbullying detection within a multi-modal context. In Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining (pp. 339–347)

Chen Y, Zhou Y, Zhu S, Xu H (2012) Detecting offensive language in social media to protect adolescent online safety. In 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing (pp. 71–80). IEEE

Dadvar M, De Jong F (2012) Cyberbullying detection: a step toward a safer internet yard. In Proceedings of the 21st International Conference on World Wide Web (pp. 121–126)

Dadvar M, Jong FD, Ordelman R, Trieschnigg D (2012) Improved cyberbullying detection using gender information. In Proceedings of the Twelfth Dutch-Belgian Information Retrieval Workshop (DIR 2012) . University of Ghent

Dadvar M, Trieschnigg D, Ordelman R, de Jong F (2013) Improving cyberbullying detection with user context. In European Conference on Information Retrieval (pp. 693–696). Springer, Berlin, Heidelberg

Dey R, Bag S, Sarkar RR (2021) Identification of stable housekeeping genes for normalization of qPCR data in a pathogenic fungus. J Microbiol Methods 180:106106

Google Scholar  

Dinakar K, Picard R, Lieberman H (2015) Common sense reasoning for detection, prevention, and mitigation of cyberbullying. In IJCAI International Joint Conference on Artificial Intelligence .

Dinakar K, Reichart R, Lieberman H (2011) Modeling the detection of textual cyberbullying. In Proceedings of the International Conference on Weblog and Social Media 2011

Divyashree VH, Deepashree NS (2016) An effective approach for cyberbullying detection and avoidance. International Journal of Innovative Research in Computer and Communication Engineering , 14

Djuraskovic O, Cyberbullying Statistics F (2020) and Trends with Charts: First Site Guide; 2020. Available from: https://firstsiteguide.com/cyberbullying-stats/

Elmezain M, Malki A, Gad I, Atlam ES (2022) Hybrid deep learning model–based prediction of images related to Cyberbullying. Int J Appl Math Comput Sci 32(2):323–334

MATH   Google Scholar  

Fahrnberger G, Nayak D, Martha VS, Ramaswamy S (2014) SafeChat: A tool to shield children’s communication from explicit messages. In 2014 14th International Conference on Innovations for Community Services (I4CS) (pp. 80–86). IEEE

Fang Y, Yang S, Zhao B, Huang C (2021) Cyberbullying detection in social networks using bi-gru with self-attention mechanism. Information 12(4):171

Foong YJ, Oussalah M (2017), September Cyberbullying system detection and analysis. In 2017 European Intelligence and Security Informatics Conference (EISIC) (pp. 40–46). IEEE

Galán-García P, Puerta JGDL, Gómez CL, Santos I, Bringas PG (2016) Supervised machine learning for the detection of troll profiles in twitter social network: application to a real case of cyberbullying. Log J IGPL 24(1):42–53

MathSciNet   Google Scholar  

García-Recuero Á (2016) Discouraging abusive behavior in privacy-preserving online social networking applications. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 305–309)

Ge S, Cheng L, Liu H (2021) Improving cyberbullying detection with user interaction. In Proceedings of the Web Conference 2021 (pp. 496–506)

Goodboy AK, Martin MM (2015) The personality profile of a cyberbully: examining the Dark Triad. Comput Hum Behav 49:1–4

Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press

Haidar B, Chamoun M, Serhrouchni A (2017a) Multilingual cyberbullying detection system: Detecting cyberbullying in Arabic content. In 2017 1st Cyber Security in Networking Conference (CSNet) (pp. 1–8). IEEE

Haidar B, Chamoun M, Serhrouchni A (2017b) A multilingual system for cyberbullying detection: arabic content detection using machine learning. Adv Sci Technol Eng Syst J 2(6):275–284

Hani J, Nashaat M, Ahmed M, Emad Z, Amer E, Mohammed A (2019) Social media cyberbullying detection using machine learning. Int J Adv Comput Sci Appl 10(5):703–707

Hinduja S, Patchin JW (2010) Bullying, cyberbullying, and suicide. Archives of suicide research 14(3):206–221

Hosmer DW Jr, Lemeshow S, Sturdivant RX (2013) Applied Logistic Regression. Wiley

Hosseinmardi H, Mattson SA, Rafiq RI, Han R, Lv Q, Mishra S (2015b) Detection of cyberbullying incidents on the instagram social network. arXiv preprint arXiv:1503.03909

Hosseinmardi H, Mattson SA, Rafiq RI, Han R, Lv Q, Mishr S (2015a) Prediction of cyberbullying incidents on the instagram social network. arXiv preprint arXiv:1508.06257

Hosseinmardi H, Rafiq RI, Han R, Lv Q, Mishra S (2016) Prediction of cyberbullying incidents in a media-based social network. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 186–192). IEEE

Huang Q, Singh VK, Atrey PK (2014) Cyber bullying detection using social and textual analysis. In Proceedings of the 3rd International Workshop on Socially-Aware Multimedia (pp. 3–6)

Hutter F, Kotthoff L, Vanschoren J (2019) Automated machine learning: methods, systems, challenges. Springer

Kaity M, Balakrishnan V (2019) An automatic non-english sentiment lexicon builder using unannotated corpus. J Supercomputing 75(4):2243–2268

Kelleher JD, Tierney B, Tierney B (2018) Data science: an introduction. CRC Press

Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering. Tech Rep EBSE 1:1–57

Koutsou A, Tjortjis C (2018) Predicting hospital readmissions using random forests. IEEE J Biomedical Health Inf 22(1):122–130

Kumar A, Nayak S, Chandra N (2019) Empirical analysis of supervised machine learning techniques for Cyberbullying detection. In International Conference on Innovative Computing and Communications (pp. 223–230). Springer, Singapore

Kumar A, Sachdeva N (2020) Multi-input integrative learning using deep neural networks and transfer learning for cyberbullying detection in real-time code-mix data. Multimedia Systems

Kumar A, Sachdeva N (2021) Multimodal cyberbullying detection using capsule network with dynamic routing and deep convolutional neural network. Multimedia Syst, 1–10

LeCun Y, Bengio Y, Hinton G (2015) Deep Learn Nat 521(7553):436–444

Li W, Li X (2021) Cyberbullying among college students: the roles of individual, familial, and cultural factors. Int J Environ Res Public Health 18(11):1–17

López-Vizcaíno MF, Nóvoa FJ, Carneiro V, Cacheda F (2021) Early detection of cyberbullying on social media networks. Future Generation Computer Systems 118:219–229

Lu N, Wu G, Zhang Z, Zheng Y, Ren Y, Choo KKR (2020) Cyberbullying detection in social media text based on character-level convolutional neural network with shortcuts. Concurrency and Computation: Practice and Experience, e5627

Maity K, Sen T, Saha S, Bhattacharyya P (2022) MTBullyGNN: a graph neural network-based Multitask Framework for Cyberbullying Detection. IEEE Transactions on Computational Social Systems

Malik CI, Radwan RB (2020) Adolescent victims of cyberbullying in Bangladesh- prevalence and relationship with psychiatric disorders. Asian J Psychiatr 48:101893

Mangaonkar A, Hayrapetian A, Raje R (2015) Collaborative detection of cyberbullying behavior in Twitter data. In 2015 IEEE international conference on electro/information technology (EIT) (pp. 611–616). IEEE

Manning CD, Raghavan P, Schütze H (2008) Introduction to Information Retrieval. Cambridge University Press

McEvoy MP, Williams MT (2021) Quality Assessment of systematic reviews and Meta-analyses of physical therapy interventions: a systematic review. Phys Ther 101(4):pzaa226

Mercado RNM, Chuctaya HFC, Gutierrez EGC (2018) Automatic cyberbullying detection in spanish-language social networks using sentiment analysis techniques. Int J Adv Comput Sci Appl 9(7):228–235

Monteiro RP, Santana MC, Santos RM, Pereira FC (2022) Cyberbullying victimization and mental health in higher education students: the mediating role of perceived social support. J interpers Violence, 1–23

Nahar V, Al-Maskari S, Li X, Pang C (2014) Semi-supervised learning for cyberbullying detection in social networks. In Australasian Database Conference (pp. 160–171). Springer, Cham

Nahar V, Unankard S, Li X, Pang C (2012) Sentiment analysis for effective detection of cyber bullying. Asia-Pacific Web Conference

Nandhini BS, Sheeba JI (2015) Online social network bullying detection using intelligence techniques. Procedia Comput Sci 45:485–492

Niu M, Yu L, Tian S, Wang X, Zhang Q (2020) Personal-bullying detection based on Multi-Attention and Cognitive Feature. Autom Control Comput Sci 54(1):52–61

Noviantho, Isa SM, Ashianti L (2018) Cyberbullying classification using text mining. In Proceedings - 2017 1st International Conference on Informatics and Computational Sciences , ICICoS 2017

Patil C, Salmalge S, Nartam P (2020) Cyberbullying detection on multiple SMPs using modular neural network. Advances in Cybernetics, Cognition, and machine learning for Communication Technologies. Springer, Singapore, pp 181–188

Chapter   Google Scholar  

Pawar R, Raje RR (2019) Multilingual Cyberbullying Detection System. In 2019 IEEE International Conference on Electro Information Technology (EIT) (pp. 040–044). IEEE

Pires TM, Nunes IL (2019) Support vector machine for human activity recognition: a comprehensive review. Artif Intell Rev 52(3):1925–1962

Pradhan A, Yatam VM, Bera P (2020) Self-Attention for Cyberbullying Detection. In 2020 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA) (pp. 1–6). IEEE

Pérez PJC, Valdez CJL, Ortiz MDGC, Barrera JPS, Pérez PF (2012) MISAAC: Instant messaging tool for cyberbullying detection. In Proceedings of the 2012 International Conference on Artificial Intelligence , ICAI 2012 (pp. 1049–1052)

Rafiq RI, Hosseinmardi H, Han R, Lv Q, Mishra S (2018) Scalable and timely detection of cyberbullying in online social networks. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (pp. 1738–1747)

Raisi E, Huang B (2018) Weakly supervised cyberbullying detection with participant-vocabulary consistency. Social Netw Anal Min 8(1):38

Reynolds K, Kontostathis A, Edwards L (2011) Using machine learning to detect cyberbullying. In 2011 10th International Conference on Machine learning and applications and workshops (Vol. 2, pp. 241–244). IEEE

Rosa H, Matos D, Ribeiro R, Coheur L, Carvalho JP (2018) A “deeper” look at detecting cyberbullying in social networks. In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1–8). IEEE

Rosa H, Pereira N, Ribeiro R, Ferreira PC, Carvalho JP, Oliveira S, Coheur L, Paulino P, Veiga Simão AM, Trancoso I (2019) Automatic cyberbullying detection: A systematic review. Computers in Human Behavior, 93, 333–345

Salawu S, He Y, Lumsden J (2017) Approaches to automated detection of cyberbullying: a survey. IEEE Trans Affect Comput.

Sanchez H, Kumar S (2011) Twitter bullying detection. ser. NSDI , 12 (2011), 15

Shah N, Maqbool A, Abbasi AF (2021) Predictive modeling for cyberbullying detection in social media. J Ambient Intell Humaniz Comput 12(6):5579–5594

Singh A, Kaur, M (2020) Intelligent content-based cybercrime detection in online social networks using cuckoo search metaheuristic approach [Article]. J Supercomput 76(7):5402–5424

Singh VK, Ghosh S, Jose C (2017) Toward multimodal cyberbullying detection. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2090–2099)

Soni D, Singh VK (2018) See no evil, hear no evil: Audio-visual-textual cyberbullying detection. Proceedings of the ACM on Human-Computer Interaction , 2 (CSCW), 1–26

Squicciarini A, Rajtmajer S, Liu Y, Griffin C (2015) Identification and characterization of cyberbullying dynamics in an online social network. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 (pp. 280–285)

Sugandhi R, Pande A, Agrawal A, Bhagat H (2016) Automatic monitoring and prevention of cyberbullying. Int J Comput Appl 8:17–19

Tahmasbi N, Rastegari E (2018) A socio-contextual approach in automated detection of public cyberbullying on Twitter. ACM Trans Social Comput 1(4):1–22

Tan SH, Zou W, Zhang J, Zhou Y (2020) Evaluation of machine learning algorithms for prediction of ground-level PM2.5 concentration using satellite-derived aerosol optical depth over China. Environ Sci Pollut Res 27(29):36155–36170

Tarwani S, Jethanandani M, Kant V (2019) Cyberbullying Detection in Hindi-English Code-Mixed Language Using Sentiment Classification. In International Conference on Advances in Computing and Data Sciences (pp. 543–551). Springer, Singapore

Tomkins S, Getoor L, Chen Y, Zhang Y (2018) A socio-linguistic model for cyberbullying detection. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 53–60). IEEE

van Geel M, Goemans A, Toprak F, Vedder P (2017) Which personality traits are related to traditional bullying and cyberbullying? A study with the big five, Dark Triad and sadism. Pers Indiv Differ 106:231–235

Van Hee C, Jacobs G, Emmery C, Desmet B, Lefever E, Verhoeven B, …, Hoste V (2018) Automatic detection of cyberbullying in social media text. PLoS ONE, 13(10), e0203794

Van Hee C, Lefever E, Verhoeven B, Mennes J, Desmet B, De Pauw G, …, Hoste V (2015) Detection and fine-grained classification of cyberbullying events. In International Conference Recent Advances in Natural Language Processing (RANLP) (pp. 672–680)

Wang W, Xie X, Wang X, Lei L, Hu Q, Jiang S (2019) Cyberbullying and depression among chinese college students: a moderated mediation model of social anxiety and neuroticism. J Affect Disord 256:54–61

Whiting P, Savović J, Higgins JP et al (2016) ROBIS: a new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol 69:225–234

Witten IH, Frank E, Hall MA (2016) Data Mining: practical machine learning tools and techniques, 4th edn. Morgan Kaufmann Publishers

Wright MF (2017) Cyberbullying in cultural context. J Cross-Cult Psychol 48(8):1136–1137

Wu J, Wen M, Lu R, Li B, Li J (2020) Toward efficient and effective bullying detection in online social network. Peer-to-Peer Netw Appl, 1–10

Wu T, Wen S, Xiang Y, Zhou W (2018) Twitter spam detection: survey of new approaches and comparative study. Computers & Security 76:265–284

Yin D, Xue Z, Hong L, Davison BD, Kontostathis A, Edwards L (2009) Detection of harassment on web 2.0. Proceedings of the Content Analysis in the WEB , 2 , 1–7

Zhang X, Tong J, Vishwamitra N, Whittaker E, Mazer JP, Kowalski R, Hu H, Luo F, Macbeth J, Dillon E (2017) Cyberbullying detection with a pronunciation based convolutional neural network. In Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016

Zhao R, Mao K (2017) Cyberbullying detection based on semantic-enhanced marginalized denoising auto-encoder. IEEE Trans Affect Comput 8(3), 328–339. Article 7412690

Zhao R, Zhou A, Mao K (2016) Automatic detection of cyberbullying on social networks based on bullying features. In Proceedings of the 17th international conference on distributed computing and networking (pp. 1–6)

Zhong H, Li H, Squicciarini AC, Rajtmajer SM, Griffin C, Miller DJ, Caragea C (2016) Content-Driven Detection of Cyberbullying on the Instagram Social Network. In IJCAI (pp. 3952–3958)

Download references

Author information

Authors and affiliations.

Faculty of Computer Science and Information Systems, Universiti Malaya, Kuala Lumpur, 50603, Malaysia

Vimala Balakrisnan & Mohammed Kaity

You can also search for this author in PubMed   Google Scholar

Contributions

VB wrote the original draft; performed analysis; revised the article; MK performed data collection; performed analysis; revised the article; All authors reviewed the manuscript.

Corresponding author

Correspondence to Vimala Balakrisnan .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Balakrisnan, V., Kaity, M. Cyberbullying detection and machine learning: a systematic literature review. Artif Intell Rev 56 (Suppl 1), 1375–1416 (2023). https://doi.org/10.1007/s10462-023-10553-w

Download citation

Accepted : 08 July 2023

Published : 24 July 2023

Issue Date : October 2023

DOI : https://doi.org/10.1007/s10462-023-10553-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Cyberbullying
  • Machine learning
  • Systematic literature review
  • Find a journal
  • Publish with us
  • Track your research
  • 315 Montgomery Street, 10 th Floor, Suite #900, San Francisco, CA 94104, USA
  • [email protected]
  •   +1-628-201-9788
  • NLM Catalog

Blogger

  • Crossmark Policy

irispublishers

For Authors

  • Author Guidelines
  • Plagiarism policy
  • Peer review Process
  • Manuscript Guidelines
  • Online submission system
  • Processing Fee

For Editors

  • Editor Guidelines
  • Associate Editor Guidelines
  • Reviewer Guidelines

To Register as

  • Associate Editor
  • Submit Manuscript

Online Submission

NLM Catalog Journals

  • Archives in biomedical engineering & biotechnology
  • Online journal of complementary & alternative medicine
  • Archives in Neurology & Neuroscience
  • Global Journal of Pediatrics & Neonatal Care
  • World Journal of Gynecology & Womens Health
  • Anaesthesia & Surgery Open Access Journal
  • Global Journal of Orthopedics Research
  • Annals of urology & nephrology

Journal Flyer

Open Access Journal of Addiction and Psychology - OAJAP

  • ISSN: 2641-6271

Managing Editor: Nikki Fenn

Contact us at:

Mini Review

Effects of cyber bullying on teenagers: a short review of literature.

Mir Ali Raza Talpur 1 , Tabinda Touseef 2 , Syed Daniyal Ahmed Jilanee 1 , Muhammad Mubashir Shabu 3 and Ali Khan 4 *

1 Liaquat National Medical College and Hospital, Pakistan

2 Jinnah Medical and Dental College, Pakistan

3 Karachi Medical and Dental College, Pakistan

4 Dow University of Health and Sciences, Pakistan

Corresponding Author

Ali Khan, 4Dow University of Health and Sciences, Karachi, Pakistan.

Received Date: November 07, 2018;   Published Date: November 26, 2018

Among the numerous advantages of the internet, there is an unintended outcome of the internet’s extensive reach: the growing rate of harmful offences against children and teens. Cyber-bullying victimization has recently received a fair amount of attention due to some heart-breaking events orbiting in schools and even at homes. Although research has already demonstrated a number of serious consequences of cyber-victimization, many questions remain unanswered concerning the impact of cyber-bullying. This study gathers literature from 18 studies pieces together only the factors that kick-start cyber-bullying perpetration and victimization but also the effects of bullying on the victims as well as the bullies.

Keywords: Cyber-bully; Teenagers; Effects; Perpetrators; Victims

  • Introduction

Cyber-bullying interactions are usually defined as “repeated, harmful interactions which are deliberately offensive, humiliating, threatening, and power assertive, and are enacted using electronic equipment, such as cell (mobile) phones or the Internet, by one or more individuals towards another” [1]. It might be a continuation of real life bullying but can also exist on its own [2].

Smith et al divided cyber-bullying in seven sub-categories, namely: text message bullying, picture/ video clip bullying, phone call bullying, email bullying, chat-room bullying, bullying through instant messaging (18%) and bullying via websites among which picture/video clip and phone call were perceived to have the most impact [3]. Even though chat room, instant messaging and email bullying were perceived to have the least impact on the victim another study deems it most common among all (18% and 13.8%, respectively) [4].

  • Review of Literature

Literature search strategy

A thorough search of medical literature was conducted on Pubmed, Google scholar and Scopus databases. The key MeSH and non-MeSH terms were “Cyber-bully”, “teenagers”, “Effects”, “Perpetrators” and “Victims”. Literature search was confined to English language literature only. Medical literature from the past two decades was included in this research. Studies reporting the outcomes of cyber-bullying in healthy teenagers (13-19 years of age) were included whereas studies reporting psychological outcome in relation to other pathologies, victims primarily being older than 19 years of age and outcomes in mentally disabled subjects were excluded from the study.

Nature of harassment

The nature of harassment ranges from ignoring, disrespecting, threatening, calling names, spreading rumors, email bombing, picking on and ridiculing [4] to hiding names while sending SMS or when in a chat room, kicking someone out of a chat room, and violating the privacy of someone by a webcam [5].

Comparison with traditional bullying

Electronic communications allows perpetrators to maintain anonymity, access to a wide audience and 24/7 attainability. In addition, private nature of the communication devoid of non-verbal quos makes cyber-bullying different from traditional bullying. Perpetrators may feel reduced responsibility and accountability leaving victims more vulnerable [6-8].

Causes of cyberbullying perpetration

According to studies there was no correlation between age and cyber-bullying (p=0.39) [1]. Males were more likely to cyber-bully others than females (p=0.021) [9]. Only 43.6% of cyber-bullies thought that their bullying behavior was harsh to very harsh on the victims (Cyber victims: 66.4%), similarly, only 26% thought their actions had an impact on their victim’s life (Cyber victims: 34.6%). Those who bullied others scored higher on the peer relationship problems scale (p=0.001) [1]. Cyber-bully statuses were independently predicted by conduct (OR = 2.6; 95% CI, 1.5-4.5; P < .001) and hyperactivity problems (OR = 2.4; 95% CI, 1.4-3.9; P< .001) and pro-social problems (OR = 2.3; 95% CI, 1.5-3.4; P< .001). No significant difference was observed between children of two biological parents and children living in a family with other than two biological parents [4]. Traditional bullies tended to be cyberbullies as well (p < 0.001). Within a group of school bullies, 85.5% reported that they were also victims and even though almost 30% in this group were cyber-bullies, 27.3% were cyberbully victims [10].

Anonymity associated with electronic communication tools promotes cyberbullying and makes it difficult to prevent [7,10]. The frequencies of public school students who indicated being cyberbullies were higher than those of the private school students [5].

Although the frequent use of communication tools significantly promoted cyber-bullying in female students (p = 0.001), male students did not have the same effect (p =0.431). On the other hand, the role of risky internet use in promoting cyber-bullying was not significant for female students (p=0.721), it was significant for male students (p = 0.001) [11].

Causes of cyberbullying victimization

Age: Although a decrease is seen in exclusive school bullying from ages 14 (16.6%) to 18 (7.1%), cyber-bullying actually increases between the ages 14 (6.2%) to 18 (7.4%) [10].

Gender: Although some studies show no significant difference between the proportion of male and female adolescents who reported being bullied (p=0.91) [9]. There are reports indicating higher occurrence of cyber-bullying among females than males (18.3% vs 13.2%) [12,13].

Race/Ethnicity: Whites/Caucasians were more prone to be victimization [14].

Physical appearance: Females seen as less or more attractive than others were at the highest risk for harassment while some students were also targeted on the basis of disability [9].

Traditional bullying victim: Traditional bully victims were also likely to be cyber-victims (p = 0.022) [15].

Family composition: Cyber-victim only status was associated with living in a family with other than 2 biological parents (6.2% vs 4%) [4].

exual orientation: Youngsters who identified themselves as heterosexual were less likely to be victimized as compared to their non-heterosexual counterparts (6% vs 10.5%) [12].

School performance: Students who performed poorly in school (D & F grade holders) were more than twice as likely to be victims of either traditional or online harassment, or both, as compared to students who received A-grades (16.1% vs 7.4%) [12].

Technology use: The risky internet use and usage frequency predicted cyber-bullying victimization significantly when compared with traditional victimization among female (ΔR2 = .133, F (2, 83) = 6.78, p = .002) as well as male students (ΔR2 = .216, F (2, 108) = 15.98, p = .000). (11) In another study, Eric Rice reported high levels of texting (OR = 2.1; 95% CI = 1.1, 4.0; P < .05) and Internet use (OR = 2.0; 95% CI = 1.0, 3.64; P < .05) were associated with being a cyber-victim [14].

Type of school: Public school students reported experiencing cyber harassment more frequently than those studying in the private school [5].

Effects of cyberbullying on the perpetrator

The association between cyberbully perpetrator and their mental health and well-being is equally important to take under consideration. Many studies reported that cyberbullyng does not only has negative effects on the its victims but also on the perpetrator as well It was observed that 39% of students who harassed others online dropped out of school and 37% showed delinquent behavior [1]. About 32% of online harassers were frequent substance abusers, while some reported frequent smoking and drunkenness. A study reported that about 16% perpetrators were severely depressed [1] while in another study there reports of bullies feeling unsafe in school [4]. This study also states a strong correlation between psychiatric, psychosocial and psychosomatic disorders with being a cyberbully or a cybervictim [4]. With the rise of cyberbullying there arise a hypothesis that students who cyberbully may feel greatly powerful by taking the advantage of immense anonymity and by targeting much bigger and wider audience [16]. It has also been speculated that the lack of immediate retaliation by the victim may provoke perpetrator towards harsher bullying [17]. A study ny Gini et al has shown that bullies are morally capable enough to judge actions but still have potential deficiencies with respect to moral sentiments and appear to have high levels of moral disengagement which is why they lack empathy for victim [18].

Effects on cybervictims

In relation to combating cyber-bullying males responded more actively and with physically retaliatory behavior, whereas females’ responses indicated more passive and verbally retaliatory behavior [15]. About 1 in every 4 individuals reported fear for their safety most of whom most reported getting targeted by an adult. Sourander et al reported association between victimization and sleeping problems (p < 0.001), bed-wetting, headaches (p < 0.001), recurrent abdominal pain and stomachaches. The same study states that victims experience numerous perceived problems, social anxiety, emotional disturbances and peer problems [4]. Hoff et al in their study found that students who were the targets of cyber bully reported several negative psychological effects. They experienced high levels of aggressiveness, powerlessness, sadness, and fear [15]. Girls who were victimized by cyberbully were significantly (P=0.003) more likely to reports 2-week sadness (36% vs. 21%), suicidal ideation (19% vs. 12%), suicide plan (15% vs. 11%), attempt (10% vs. 6%), and treatment for attempt (3% vs. 2%) as compared to victimized boys. This study also shows a strong association of suicidality in teens with victimization of bully, especially cyberbully [19].

Students categorized as “other” race (20%) and Hispanics (14%) presented with higher suicide ideation, as well as were more likely to report having made a suicide attempt (10% and 11%, respectively) compared to Caucasians (6%) and African-Americans (8%) [19]. The analysis showed that female cybervictims were more likely to inform adults than males (p = 0.012) and among students who knew someone being cyber bullied, only 30.1% told adults with no correlation to gender [9]. Non-heterosexual groups were far more likely to report bullying (33.1% vs 14.5%) [12].

Both public and private school students revealed seeking help from their friends (28.6% vs 43.6%) however only a few of the public school students stated that they had asked for help from their teachers while none of the private school students reported asking help from them [5]. A study by ML Ybarra et al states that the victims of cyberbully undergoes variety of social problems which results in having them caught in detentions, suspensions and school avoiding behavior [20]. The same study shows that cyberbully victims experience paranoia due to which they tend to carry weapons with them [20]. The cyberbully victims are more likely to develop aggression against bullies and tend to become cyber bullies to take revenge and may experience the same negative impacts as being experienced by a perpetrator [20].

Interventions

Educating children: Warning from the dangers that lurk in cyber space and training of children must start at a young age, involving them in discussions about the dangers of bullying and how to by an ally when they see cyber-bullying behavior and who to report to? [15]

Educating teachers: Educators should become “safe contacts,” giving students a place to turn if they are victims or want to report perpetrators [15].

Educating parents: Monitoring their child’s online behavior, implementing internet usage rules and what to do if they discover that their child is a participant or a target is part of parent education in combating cyber-bullying [15]. The percentage of youth reporting the existence of parental rules on Web sites (p < 0.01), time allowed online (p < 0.01), and filter restricting online activities (p < 0.05) is higher among non-victims than among victims [13].

Role of school: Another role of schools is to help students cope with social tension especially those that center on relationship issues, assess of students in order to determine bullying behavior and get to the root of it [15].

Technological coping strategies: Instituting strict privacy settings on Internet-based technologies such as instant messengers and e-mails, changing usernames and or e-mail addresses [21].

Cyber-bullying is a multi-conceptual topic which requires immense research. After a thorough search of literature, we’ve concluded that cyber-bullying is one of the worst forms of bully which imparts its devastating effects on teenagers. Perpetrators of cyber-bully misuse the cyber resources in various ways to bully people online for the sake of their psychological satisfaction which badly influence the targeted victims as well as the active perpetrator.

A targeted victim, as a consequence of cyber-bully, may experience insecurities, poor school performance, addictions, psychosomatic disorders, retaliatory behavior, emotional distress, suicidal tendencies etc. This altogether adds to destruction of normal psychology of a teenager. Cyber-bullying also impacts the perpetrators with serious psychosomatic, psychiatric and psychosocial disorders. All the individuals involved in cyber-bully, either as a victim or a perpetrator, face some serious outcomes of this problem which can only be reduced by active measures to combat it.

  • Acknowledgment
  • Conflict of Interest

Authors declare no conflict of interest.

  • Campbell MA, Slee PT, Spears B, Butler D, Kift S (2013) Do cyberbullies suffer too? Cyberbullies’ perceptions of the harm they cause to others and to their own mental health. School Psychology International 34(6): 613-629.
  • Brandtzaeg PB, Staksrud E, Hagen I, Wold T (2009) Norwegian children’s experiences of cyberbullying when using different technological platforms. Journal of Children and Media. 3(4): 349-365.
  • Smith PK, Mahdavi J, Carvalho M, Tippett N (2006) An investigation into cyberbullying, its forms, awareness and impact, and the relationship between age and gender in cyberbullying.
  • Sourander A, Klomek AB, Ikonen M, Lindroos J, Luntamo T, et al. (2010) Psychosocial risk factors associated with cyberbullying among adolescents: A population-based study. Arch Gen Psychiatry. 67(7): 720- 728.
  • Topçu C, Erdur-Baker O, Capa-Aydin Y (2008) Examination of cyberbullying experiences among Turkish students from different school types. Cyberpsychol Behav 11(6): 643-648.
  • Huang Y-y, Chou C (2010) An analysis of multiple factors of cyberbullying among junior high school students in Taiwan. Computers in Human Behavior. 26(6): 1581-1590.
  • Dehue F, Bolman C, Völlink T (2008) Cyberbullying: Youngsters’ experiences and parental perception. Cyberpsychol Behav 11(2): 217- 223.
  • Heirman W, Walrave M (2008) Assessing concerns and issues about the mediation of technology in cyberbullying. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2(2).
  • Li Q (2006) Cyberbullying in schools: A research of gender differences. School Psychology International 27(2): 157-170.
  • Li Q (2007) New bottle but old wine: A research of cyberbullying in schools. Computers in Human Behavior 23(4): 1777-1791.
  • Erdur-Baker Ozgur (2010) Cyberbullying and its correlation to traditional bullying, gender and frequent and risky usage of internetmediated communication tools. New media & society 12(1): 109-125.
  • Schneider SK, O’Donnell L, Stueve A, Coulter RW (2012) Cyberbullying, school bullying, and psychological distress: A regional census of high school students. Am J Public Health 102(1): 171-177.
  • Mesch GS (2009) Parental mediation, online activities, and cyberbullying. Cyberpsychol Behav 12(4): 387-393.
  • Rice E, Petering R, Rhoades H, Winetrobe H, Goldbach J, et al. (2015) Cyberbullying perpetration and victimization among middle-school students. Am J Public Health. 105(3): e66-e72.
  • Hoff DL, Mitchell SN (2009) Cyberbullying: Causes, effects, and remedies. Journal of Educational Administration. 47(5): 652-665.
  • Steffgen G, König A, Pfetsch J, Melzer A (2011) Are cyberbullies less empathic? Adolescents’ cyberbullying behavior and empathic responsiveness. Cyberpsychol Behav Soc Netw 14(11): 643-648.
  • Conn K (2004) Bullying and harassment: A legal guide for educators: ASCD.
  • Gini G, Pozzoli T, Hauser M (2011) Bullies have enhanced moral competence to judge relative to victims, but lack moral compassion. Personality and Individual Differences 50(5): 603-608.
  • Messias E, Kindrick K, Castro J (2014) School bullying, cyberbullying, or both: correlates of teen suicidality in the 2011 CDC Youth Risk Behavior Survey. Compr Psychiatry 55(5): 1063-1068.
  • Ybarra ML, Diener-West M, Leaf PJ (2007) Examining the overlap in Internet harassment and school bullying: Implications for school intervention. J Adolesc Health 41(6 Suppl 1): S42-S50.
  • Tokunaga RS (2010) Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior 26(3): 277-287.
  • Download PDF
  • DOI: 10.33552/OAJAP.2018.01.000511
  • Volume 1 - Issue 3, 2018
  • Open Access

Mir Ali Raza Talpur, Tabinda Touseef, Syed Daniyal Ahmed Jilanee, Muhammad Mubashir Shabu, Ali Khan. Effects of Cyber Bullying on Teenagers: a Short Review of Literature. Open Access J Addict & Psychol. 1(3): 2018. OAJAP.MS.ID.000511.

Disability, Physical disability, Disease Control, Prevention, Quality of life, Optimism, Nigerian, Diabetes, Comorbidity, Behaviour, Optimistic, Neurological, Cognitive, Mental capacity, Cyber-bullying, Internet Addiction, Hacking, Phone, Cybervictim

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License .

newsletter-subscription

Track Your Article

Refer a friend, suggested by, referrer details, advertise with us.

Creative Commons License

  • Follow us on Facebook
  • Follow us on Twitter
  • Criminal Justice
  • Environment
  • Politics & Government
  • Race & Gender

Expert Commentary

Bullying in a networked era: Research views on scope and frequency of cyberbullying

2012 and 2013 reports from Harvard's Berkman Center for Internet & Society and the University of New Hampshire examine and consolidate the research findings of recent studies.

Girl sitting on school desk (iStock)

Republish this article

Creative Commons License

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Cynthia Thaler, The Journalist's Resource September 19, 2013

This <a target="_blank" href="https://journalistsresource.org/education/bullying-networked-era-literature-review/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

The suicide of Rutgers University student Tyler Clementi in September 2010 brought increased national attention to the issues of cyber-bullying and bias-based bullying . A number of states and localities have subsequently sought to develop legislation to address what is seen as a growing problem. But societal problems with bullying, of course, continue, and new reports seem to emerge in the media on a weekly basis. For example, in September 2013 a 12-year-old Florida girl, Rebecca Ann Sedwick, is alleged to have committed suicide because of persistent harassment in social media, according to law enforcement officials . The world of mobile apps has made this problem only more complicated, as the New York Times has reported .

Although such reports can seem terrifying in their particulars — and feed into a pervasive sense that the Internet is a threatening place for youth — it is useful to keep in mind the more general research findings about the true scope, scale and frequency of this problem, and the Web’s precise role in enabling it.

A 2013 study sheds more light on aspects of this phenomenon. In “Cyber Bullying and Physical Bullying in Adolescent Suicide: The Role of Violent Behavior and Substance Use,” published in the Journal of Youth and Adolescence , researchers Brett J. Litwiller of the University of Oklahoma and Amy M. Brausch of Western Kentucky University examine a sample of nearly 4,700 high school students. It is one of the first studies to examine empirically why there is a connection between bullying and suicide, among other negative behaviors. The findings suggest that “both types of bullying, cyber and physical, positively predicted suicidal behavior, substance use, violent behavior, and unsafe sexual behavior.” In terms of their findings specifically for online behavior, Litwiller and Brausch note:

Cyber bullying had a similar sized effect on suicidal behavior, substance use, violent behavior, and unsafe sexual behavior as physical bullying. This finding provides further evidence of the potential consequences of cyber bullying. In contrast to physical bullying, cyber bullying has been found to be more difficult to avoid, anonymous, and likely to coincide with other forms of bullying…. Although not specifically examined in this study, victims of cyber bullying may more be likely to experience negative psychological states, thus contributing to feelings of thwarted belongingness and perceived burdensomeness. If cyber bullying activates feeling like one does not belong or is a burden to others, an adolescent’s risk of suicidal behavior may increase, especially if adolescents are also engaging in risk behaviors that may habituate them to pain and fear of death.

Another 2013 study, “Characteristics of College Cyberbullies,” published in Computers in Human Behavior , provides more empirical evidence about the phenomenon among slightly older young persons. The authors, Allison M. Schenk, William J. Fremouw and Colleen M. Keelan of West Virginia University, examined the personality traits of 60 persons who self-reported having participated at least four times in cyberbullying someone else (these profiles were drawn from a survey of more than 800 students.) There were 36 females and 24 males among the cyberbullies. The survey also recorded the experiences of 19 victims. The authors conclude:

Cyberbullies and cyberbully/victims scored higher than control participants on general distress, interpersonal sensitivity, depression, hostility, phobic anxiety, paranoia, and psychotic symptoms. Although it is not known how these symptoms directly relate to cyberbullying, these significant differences indicate a disparity in psychological functioning between those individuals involved in cyberbullying their uninvolved peers. This elevated level of psychological impairment for cyberbullies and cyberbully/victims was also reflected in an increase of suicidal thoughts and tendencies overall than control participants. Cyberbully/victims also were more likely than pure cyberbullies and controls to have told someone they were thinking about committing suicide.

A 2012 report from Harvard’s Berkman Center for Internet & Society, “Bullying in a Networked Era: A Literature Review,” examines and consolidates the findings of other studies published between 2008 and 2012. The data focus on American youth in middle and high school. The authors — Nathaniel Levy, Sandra Cortesi, Urs Gasser,  Edward Crowley, Meredith Beaton, June Casey and Caroline Nolan — define bullying as having three primary characteristics: It is intentional, involves a power imbalance between aggressor(s) and victim, and is repetitive.

The report highlights the following findings:

  • “Youth play a variety of roles in the bullying dynamic. Bullying involvement can be characterized by four basic roles: (a) bully, (b) victim, (c) bully-victim (actors who both bully and are victimized by others) and (d) bystander. The role of the bully-victim shows that those of bullies and victims are not always clear-cut. Certain types of bullying, such as ‘relational’ aggression (both online and offline), are more likely to involve bully-victims. Certain types of youth are more likely to be victimized, including lesbian, gay, bisexual and transgender ( LGBT ) youth and youth with disabilities.”
  • “In one national study of 2,400 6-17 year olds, between 34-42% of youths were bullied frequently in the past year…. Based on nationally representative 2001 data from the National Institute of Child Health and Human Development of the National Institutes of Health, which surveyed 15,686 students in the 6th to 10th grades, roughly 33% of students were involved in bullying as victims, bullies or both…. Based on 2005-2006 data from the School Survey on Crime and Safety, the U.S. Department of Education found that nearly 25% of public schools principals reported bullying to be a daily or weekly occurrence.”
  • “The anonymity of the bully is not as prevalent online as some research has suggested. One anonymous survey of over 1,400 teens ages 12-17 showed that 73% of participants who were victims of cyberbullying knew the identity of their bully (within this group, 43% from the Internet and 71% from offline — please note that participants were allowed to indicate multiple answers to the survey questions)…. A nationally representative study of over 1,000 teens ages 12-17 notes a lower percentage — 54% of online victims who participated knew their bully’s identity.”
  • “Youth bullied offline for their sexual orientation or gender identity face a greater likelihood of more severe consequences than other victims. Although fewer studies have compared bias based bullying or harassment of multiple varieties, initial comparisons suggest that experiencing any kind of bias-based victimization can have a greater negative impact than other forms of bullying.” This includes substance abuse, psychological distress, negative views of their school environment, missing school and having lower grades.
  • “A national survey of 5,621 youth ages 12-18 found that 64% of all respondents who experienced offline bullying in various forms did not report it to teachers or school officials.”
  • “School policies can guide prevention and intervention efforts by establishing a framework for action and communicating this framework, and the school’s commitment to it, to the broader community…. ‘Zero tolerance’ and other highly punitive disciplinary approaches have been shown not to work; a balance of consistent disciplinary action and support for students has been more effective.”
  • “A recent study of over 7,300 students in the 9th grade and 2,900 teachers randomly selected from 290 high schools found that students who seek help for being bullied are less likely to be bullied again.”
  • One study shows that “teachers were also more likely to respond to an incident — either when informed of or observing one — when they felt prepared to respond, indicating a role for training programs to provide such preparation.”
  • “As of January 2012, 10 states required (and one encouraged) schools or school districts to provide school staff with professional development or training to better understand the relevant school district’s bullying policy, many of which cover reporting and response processes. 16 states required and six encouraged that schools or school districts provide staff with professional development or training in bullying prevention.”
  • “The climate, or culture, of a school can have an impact on the prevalence of bullying and students’ comfort levels — and likelihood — of reporting acts of bullying to adults in school. Students’ feelings of being connected to and supported by school are prime characteristics of positive school climate, which are associated with lower levels of bullying. Positive relationships with peers and adults within school, and a sense of being treated fairly by teachers, are in turn important aspects of a connected and supportive school climate.”

The authors conclude by noting that online activity can also “produce positive experiences, including exposure to diverse perspectives, which is helpful for positive social and intellectual growth.”  They recommend that “when cultivating a school, home, or community environment, educators, parents, and other adults can learn of ways to leverage or encourage the development of youths’ positive social interactions online.”

A 2013 report from the Crimes Against Children Research Center at the University of New Hampshire, “Trends in Bullying and Peer Victimization,” finds that bullying rates have declined markedly since the early 1990s.  But the author cautions that bullying is still a major problem among American youth: “[These findings should] not be interpreted as the problem having been solved. First, the rates are still incredibly high. For example, more than one in 10 high school students said they were in a physical fight on school property in the last year. We would not tolerate a level of work place danger that was so high, nor should we.”

Tags: youth, safety, technology, bullying

About The Author

' src=

Cynthia Thaler

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

  • Advanced Search
  • Journal List
  • J Child Adolesc Trauma
  • v.11(1); 2018 Mar

Logo of jcat

Cyberbullying and LGBTQ Youth: A Systematic Literature Review and Recommendations for Prevention and Intervention

Roberto l. abreu.

1 Department of Educational, School, and Counseling Psychology, College of Education, University of Kentucky, 251 Dickey Hall, Lexington, KY 40506 USA

Maureen C. Kenny

2 Leadership and Professional Studies, College of Arts, Science and Education, Florida International University, Miami, FL USA

Research has demonstrated that cyberbullying has adverse physical and mental health consequences for youths. Unfortunately, most studies have focused on heterosexual and cisgender individuals. The scant available research on sexual minority and gender expansive youth (i.e., LGBTQ) shows that this group is at a higher risk for cyberbullying when compared to their heterosexual counterparts. However, to date no literature review has comprehensively explored the effects of cyberbullying on LGBTQ youth. A systematic review resulted in 27 empirical studies that explore the effects of cyberbullying on LGBTQ youth. Findings revealed that the percentage of cyberbullying among LGBTQ youth ranges between 10.5% and 71.3% across studies. Common negative effects of cyberbullying of LGBTQ youth include psychological and emotional (suicidal ideation and attempt, depression, lower self-esteem), behavioral (physical aggression, body image, isolation), and academic performance (lower GPAs). Recommendations and interventions for students, schools, and parents are discussed.

Technology has become a conventional and widely used form of communication among individuals. Youth in particular appear to be drawn to different forms of technology, and use it regularly. According to a 2015 study by the Pew Research Center, 92% of teens go online on a daily basis and 56% access online material several times a day (Lenhart 2015 ). While the Internet provides many benefits (e.g., connecting with others, vast information), there are risks related to privacy, security, and harassment. Specifically, readily available access to the Internet has opened the door for a new form of bullying among youth, commonly known as cyberbullying (other names include cyber victimization, online victimization, and online aggression). Although different definitions for cyberbullying are found in the literature, researchers have identified this form of aggression as behaviors performed through the use of digital media or technology with the goal of communicating aggression and inflicting harm in an individual or a group of people (e.g., Hinduja and Patchin 2014 ; Pham and Adesman 2015 ). Research shows that exposure to cyberbullying has severe consequences for adolescents’ and young adults’ physical and mental health, including academic problems, substance abuse, and suicide (Flanagan 2014 ; Pham and Adesman 2015 ). A current systematic literature review of 25 empirical studies revealed that a significant number of children and adolescents (20% - 40%) report being victims of cyberbullying (Aboujaoude et al. 2015 ). Cyberbullying among children and adolescents is a serious threat and collective efforts headed by schools, policy-makers, and medical and mental health providers must be put in place in order to protect youth from the hazards associated with an ever dependent digital world (Aboujaoude et al. 2015 ).

Specific to sexual and gender minority youth, there is a dearth of research on the experiences of LGBTQ youth and cyberbullying. However, extensive research exists on traditional bullying (i.e., face-to-face) of LGBTQ students. This body of research shows that LGBTQ youth are being bullied, harassed, and victimized in schools at disproportionate rates when compared to their heterosexual and cisgender counterparts (Black et al. 2012 ; Espelage et al. 2015 ; Kosciw et al. 2016 ). As a result, LGBTQ students have lower GPAs, higher rates of depression, lower self-esteem, and more suicidal ideation and suicide attempts (Kosciw et al. 2016 ; Montoro et al. 2016 ). In a national study of sexual minority high school students by the Centers for Disease Control and Prevention (CDC), LGB high school students reported higher levels of violence and bullying than their heterosexual counterparts, including forced to have sex (17.8% vs. 5.4%) and experiences of bullying at school (34.5% vs. 18.5%; Kann et al. 2016 ).

Regarding the experiences of cyberbullying, Aboujaoude et al. ( 2015 ) and Zych et al. ( 2015 ) found that sexual minorities are among one of the most vulnerable populations. Another systematic literature review of 39 empirical studies on the psychological and health outcomes of sexual minority and gender expansive youth revealed that victimization related to sexual identity is linked to increased depressive symptoms, suicidality, and substance abuse (Collier et al. 2013 ). Although cyberbullying has been briefly mentioned in reviews that explore the victimization of sexual minority and gender expansive youth and sexual minorities have been mentioned as a population of interest in cyberbullying youth literature reviews, to date no systematic literature review has exclusively explored the correlates of cyberbullying on LGBTQ youth. That is, the authors were not able to locate a single systematic literature that has brought together all of the available empirical research on LGBTQ youth cyberbullying. Therefore, the aim of the present review is to provide a comprehensive and integrative review of cyberbullying among sexual minority and gender expansive youth, including prevalence, correlates, and recommendations for prevention and intervention.

Search Strategy

The authors conducted a computer-based search of the databases Academic Search Complete, PsycINFO, PubMed, and Web of Science to locate studies. Variations of the term cyberbullying (i.e., cyberbullying, cyber-bullying, online bulling, cyber aggression, cyber violence, and online victimization) were used in combination with keywords related to sexual and/or gender identity (i.e., LGBT, GLBT, LGB, GLB, GLBTQ, gay, homosexuality, male homosexuality, bisexuality, lesbianism, transgender, sexual orientation, sexual identity, and sexual minority). In order to make sure the search led to exhaustive results, keywords related to bullies’ potential motives (i.e., homophobia, homophobic, biphobia, and transphobia) were also used in combination with variations of the term cyberbullying. In addition, a search of victims’ characteristics (i.e., gender expression, gender identity, feminine, femininity, masculine, masculinity, gender atypical, gender bending, gender incongruence) was used in combination with variations of the term cyberbullying.

Considering the lack of research in the area of cyberbullying and LGBTQ individuals (Evans and Smokowski 2016 ), in the initial search, the authors did not narrow their search to a specific country, setting, or developmental age, to intentionally find all studies that captured the experience of cyberbullying among LGBTQ people before creating any inclusion and exclusion criteria. However, all of the studies found were conducted with LGBTQ adolescents, with school settings ranging from middle school to college/university level, with most studies ( n  = 22) including middle and high school students. In addition to the database search, a second method for literature searching included an ancestral approach (White 1994 ), which entailed reviewing the reference lists of each selected article to identify additional studies for possible inclusion. The search was conducted during the months of August 2016 through March 2017, and no time parameters were used. Duplicate publications were excluded.

Inclusion and Exclusion Criteria

Inclusion criteria included studies that were: (a) empirically based; (b) report original research findings (this included school climate surveys); (c) conducted among LGBTQ (or other sexual or gender minorities) youth; (d) explored cyberbullying toward LGBTQ adolescents in any setting; and (e) explored prevalence, correlates, consequences (including physical and psychological), and/or prevention efforts/recommendations in relation to LGBTQ youth cyberbullying. Both authors reviewed the abstracts of all citations produced by the database search and conducted ancestral approach to determine which citations met these criteria. Considering we were not able to locate any previously published literature review specific to LGBTQ youth and cyberbullying, we did not have a criterion for time frame (e.g., publications on and/or after a certain year). It was the authors’ intention to capture all of the current available empirical research on the experiences of cyberbullying among LGBTQ youth. Exclusion criteria included articles that: (a) did not assess for cyberbullying (i.e., studies that only reported on traditional bullying, or face-to-face) or (b) did not assess for sexual or gender identity of participants. It is important to note that not all selected studies included exclusive samples of LGBTQ participants. Over half of studies ( n  = 14) included a large sample (i.e., over 70%) of heterosexual participants. We included any study that reported on the experiences of cyberbullying among LGBTQ youth participants, regardless if the study’s sample also included heterosexual and/or cisgender participants. For those studies that included a mixed sample of heterosexual and cisgender and LGBTQ participants, we focused on the results and analysis that, in any way, involved LGBTQ youth. As a result of the inclusion and exclusion criteria, 27 studies were included in the review. After each author was done with their individual review of each article (documented in a table form), tables were exchanged and reviewed for discrepancies. Discrepancies were discussed and reconciled among both authors.

Results of Literature Review

The studies were conducted in the United States ( n  = 19), Canada ( n  = 3), Australia ( n  = 3), Sweden ( n  = 1), and United Kingdom ( n  = 1). Most of the participants were collected from a nationwide sample ( n  = 9), followed by school counties/districts/zones ( n  = 6), single state/province/region ( n  = 5), single university ( n  = 4), and multiple states/provinces/regions ( n  = 3). Most of the reviewed studies were quantitative ( n  = 21), followed by mixed-method ( n  = 5) and qualitative ( n  = 1). Study sample size (all participants) ranged between 18 and 20,406 participants, with the smallest sample coming from the one qualitative study (i.e., Varjas et al. 2013 ). The range of LGBTQ participants ranged between 3.84% and 100%. For the purpose of this review, we organized the results and findings for each study into three different categories: (a) prevalence ( n  = 26), (b) correlates and impact ( n  = 9), and (c) prevention and intervention strategies ( n  = 11). Only three of the 11 studies that discussed prevention strategies for cyberbullying mentioned LGBTQ-specific prevention strategies (i.e., GLSEN et al. 2013 ; Hinduja and Patchin 2012 ; Ramsey et al. 2016 ). See Table ​ Table1 1 for more details about each study.

Description of the Studies on LGBTQ Cyberbullying Included in the Systematic Review

Studies and Participants’ Diversity

Age and educational level.

The majority of the studies ( n  = 20) reported on the age of participants (range of 11–25 years old), while seven studies only reported the grade or educational level. Most studies ( n  = 22) were conducted with secondary-age school students, including middle and high school or a combination thereof. Nine studies were conducted with only high school students, while nine studies were conducted with middle and high school students combined and only one study (Rice et al. 2015 ) with middle school students. On the other hand, only five studies included participants from postsecondary institutions, including colleges and universities. Noticeably, the five studies that reported data from private schools (GLSEN et al. 2013 ; Guasp 2012 ; Hillier et al. 2010 ; Kosciw et al. 2012 ; Kosciw et al. 2016 ) were all large scale, nationwide climate surveys. In addition, only two studies (Blais et al. 2013 ; Blumenfeld and Cooper 2010 ) collected data from both secondary and postsecondary schools combined.

Race and Ethnicity

The racial and ethnic diversity varied greatly among studies. More specifically, White participants made up the largest range across studies (3.3% - 92%), followed by Hispanics/Latinas/os (5% - 59.62%), African American/Black (2.8% - 41%), Asian/Pacific Islander (2.4% - 19%), Biracial/Multiracial (1.26% - 16.6%), “Other” (0.8% - 6.4%), and Native American/Indigenous people (0.41% - 6%). In addition, only three studies (Cénat et al. 2015 ; Kosciw et al. 2012 ; Kosciw et al. 2016 ) reported racial and ethnic demographic data on Middle Eastern participants. Furthermore, seven studies (Blais et al. 2013 ; Hillier et al. 2010 ; Hinduja and Patchin 2012 ; Mace et al. 2016 ; Priebe and Svedin 2012 ; Robinson and Espelage 2011 ; Walker 2015 ) did not report specific data on racial and/or ethnic diversity. Moreover, four studies (Cénat et al. 2015 ; Guasp 2012 ; Schneider et al. 2015 ; Stoll and Block 2015 ) did not provide a breakdown of the percentage of racial and ethnic diversity in their sample and only reported White vs. non-White participants.

Sexual Identity

Although the sexual identity of participants ranged across studies, there are important trends. Most studies ( n  = 19) provided a combined sample of heterosexual and non-heterosexual participants, with the goal of comparing prevalence, correlates, and outcomes between these groups. Fourteen of the 19 studies had a significantly large sample of heterosexual participants (range of 71% - 94.4%) and did not provide a breakdown of the non-heterosexual sample (i.e., participants were identified as only heterosexual or non-heterosexual). In fact, only eight studies (Duong and Bradshaw 2014 ; GLSEN et al. 2013 ; Guasp 2012 ; Hillier et al. 2010 ; Kosciw et al. 2012 ; Kosciw et al. 2016 ; Sterzing et al. 2017 ; Varjas et al. 2013 ) had a sample of 100% LGBT participants and only three studies (Blumenfeld and Cooper 2010 ; Cooper and Blumenfeld 2012 ; Hillier et al. 2010 ) had a large sample (over 75%) of LGBT participants. Of the studies that provided a breakdown of sexual identities ( n  = 13), the category of gay participants made up the largest range across studies (0.7% - 82%), followed by lesbian and gay combined (0.65% - 62.9%), bisexual (2.4% - 42%), lesbian (1.4% - 39%), and queer/questioning/unsure (0.09% - 12%). Furthermore, one study (Duong and Bradshaw 2014 ) did not report the number of LGB identified individuals despite the fact that these participants were part of the results and analysis.

Gender also varied greatly by study. Female participants made up the largest percentage in most studies ( n  = 17), with only five studies (Bouris et al. 2016 ; Guasp 2012 ; Kosciw et al. 2016 ; Rice et al. 2015 ; Varjas et al. 2013 ) reporting a higher percentage of males than females. In addition, only 11 studies (Blais et al. 2013 ; Blumenfeld and Cooper 2010 ; Cooper and Blumenfeld 2012 ; GLSEN et al. 2013 ; Guasp 2012 ; Hillier et al. 2010 ; Kosciw et al. 2012 ; Kosciw et al. 2016 ; Ramsey et al. 2016 ; Sterzing et al. 2017 ; Taylor et al. 2011 ) reported on transgender participants, with a range between 0.25% and 15.2%. Noticeably, the study by Sterzing et al. ( 2017 ) included the largest percentage of genderqueer participants (20.5%). Furthermore, only two studies (Blumenfeld and Cooper 2010 ; Cooper and Blumenfeld 2012 ) reported on intersex participants (0.1% and 0.6%). Three studies (Hinduja and Patchin 2012 ; Robinson and Espelage 2011 ; Sinclair et al. 2012 ) did not provide a percentage for gender.

As noted by Aboujaoude et al. ( 2015 ) in a review of the literature on cyberbullying (overall, not specific to LGBTQ youth), it is challenging to accurately estimate the prevalence of online victimization. However, across this literature review one finding is clear: sexual minority and gender expansive adolescents are disproportionally more often victims of cyberbullying than their heterosexual and cisgender counterparts. Also, although the percentage of cyberbullying among LGBTQ youth seems to differ from one study to another, the range appears to be between 10.5% and 71.3% across studies. An interesting finding by Schneider et al. ( 2015 ) is that cyberbullying among sexual minority youth decreased by 3% between 2006 and 2012 (47% vs. 50%). However, they assert that regardless of this decline and promising trend, sexual minority youth consistently report significantly higher levels of cyberbullying when compared to their heterosexual counterparts (Schneider et al. 2015 ), and this still translates to almost half of all sexual minority youth as victims of cyberbullying.

Sexual minority and gender expansive youth reported being more exposed to anonymous forms of cyberbullying than their heterosexual counterparts (Bauman and Baldasare 2015 ; Guasp 2012 ). In addition, according to Blais et al. ( 2013 ), after rejection and humiliation, cyberbullying is consistently ranked among the highest form of prejudice toward sexual minority students, affecting between 28% and 48.95% of these youth. Moreover, when compared to traditional bullying, Duong and Bradshaw ( 2014 ) found that LGB students experienced more cyberbullying than traditional bullying (9.7% vs. 8.2%). The following sections will present prevalence of cyberbullying among sexual minority and gender expansive youth, divided by: (a) gender and cyberbullying, (b) reasons for not reporting cyberbullying and help seeking behaviors, and (c) people of color and cyberbullying. Before proceeding with this section it is important to note that only eight of the studies included in this review used a representative sample, with most studies ( n  = 19) using an ad hoc sampling approach. Considering that a prevalence rate is intended to inform about the percentage of victims in a population and only representative samples can yield conclusions about populations, these prevalence rates should be interpreted with caution.

Gender and LGBTQ Cyberbullying

Overall, a review of these studies show that both male and female sexual minority youth report substantially higher levels of cyberbullying than their heterosexual and cisgender counterparts (e.g., Hillier et al. 2010 ; Schneider et al. 2015 ; Wensley and Campbell 2012 ). In addition, Cooper and Blumenfeld ( 2012 ) found that 19% of LGBT participants reported being harassed for their biological sex and 41% for their gender identity or expression. The study by GLSEN et al. ( 2013 ) took the findings by Cooper and Blumenfeld ( 2012 ) a step further and reported that participants who identified as cisgender non-heterosexual females, transgender youth, and youth with “other” genders reported higher levels of cyberbullying than those who identified as cisgender gay and bisexual males. These findings seem to be consistent with Hinduja and Patchin ( 2012 ) and Rice et al. ( 2015 ), whose findings show that sexual minority females reported greater frequency of cyberbullying than male sexual minority youth. Unfortunately, there seems to be a discrepancy across studies regarding which gender is more often victimized among LGBT students. Specifically, Schneider et al. ( 2015 ) report that sexual minority males were more likely to report cyberbullying than both their heterosexual counterparts and sexual minority females.

Furthermore, some studies suggest that bisexual youth might not only be more susceptible to a higher prevalence of cyberbullying than heterosexual youth (Cénat et al. 2015 ) but also more susceptible than other sexual minority youth (Robinson & Espelage 2011 ). For example, Taylor et al. ( 2011 ) found that bisexual female students were more likely to experience cyberbullying than lesbian participants (38.5% vs. 28.1%). However, the same trend was not found for gay versus bisexual males. That is, gay males were more likely to be bullied than bisexual males (28.2% vs. 18.9%; Taylor et al. 2011 ). Furthermore, some studies seem to suggest that there is a gender difference in victimization among bisexual youth. For instance, Cénat et al. ( 2015 ) found that bisexual and questioning males were more likely than bisexual and questioning females to report cyberbullying.

Reasons for LGBTQ Youth not Reporting Cyberbullying and Support Seeking

sexual minority and gender expansive youth often do not report cyberbullying to their parents or school personnel (i.e., counselors, teachers, and administrators). Blumenfeld and Cooper ( 2010 ) found that heterosexual participants were more likely to tell their parental figure about being exposed to cyberbullying than their LGBT counterparts (37% vs. 18%). The number one reason for not reporting cyberbullying to parents among LGBT students was fear that parents would restrict their use of technologies, which was significantly higher than their heterosexual counterparts (56% vs. 37%; Cooper and Blumenfeld 2012 ). Some other reasons for LGBT students not reporting were the belief that parents could not do anything about the incidents of cyberbullying, lack of understanding and support by parents, getting in trouble with parents, suffering further retaliation by the bully, and fear of being made fun of by others (Blumenfeld and Cooper 2010 ; Cooper and Blumenfeld 2012 ). Qualitative data revealed that LGBT participants were fearful of reporting cyberbullying because of their sexual and gender identities and potential exposure of these identities (Blumenfeld and Cooper 2010 ). Similar to the reasons for not reporting to parents, it appears that sexual minority and gender expansive youth do not report cyberbullying to school personnel due to the belief that the school will not take action to stop it, fear of not being understood by the school, retaliation from the bully, and belief that they had to handle the situation themselves (Cooper and Blumenfeld 2012 ). However, it is important to note that Priebe and Svedin ( 2012 ) found that participants identified parents as a main source of support after being cyberbullied.

This literature review revealed mixed findings regarding support-seeking behaviors from sexual minority and gender expansive youth. Mace et al. ( 2016 ) revealed that sexual minority victims of cyberbullying had higher levels of access to perceived social support than their heterosexual peers. Also, sexual minority youth who experienced cyberbullying had similar levels of perceived social support than that of their heterosexual counterparts (Mace et al. 2016 ). However, the authors point out that these findings are at odds with the findings of Flaspohler et al. ( 2009 ) and Holt and Espelage ( 2007 ) who found that sexual minority individuals reported fewer social supports, which was associated with greater risk for bullying. Further, Priebe and Svedin ( 2012 ) found that although sexual minority youth reported that they had sought more support than their heterosexual counterparts due to incidents of cyberbullying, they did not receive the support that they needed. Some encouragement is provided by Varjas et al. ( 2013 ) who report that sexual minority students perceived that school policies are being put in place to reduce cyberbullying. However, these students believe that cyberbullying will still take place without staff awareness or ability to stop it (Varjas et al. 2013 ).

Although research on the reasons why LGBTQ students do not report or seek support for cyberbullying is scant and provides mixed findings, studies from the general bullying literature might help further explicate this phenomenon. Overall, research shows that the main reasons why students do not report bullying are: (a) concerns that the staff will blame them for the incident (i.e., victim-blaming), (b) beliefs that staff will not accurately handle the issue or will downplayed the incident, and (c) feeling powerless, shameful and fearful (e.g., Bjereld 2016 ; DeLara 2012 ). A unique reason for LGBTQ students not reporting bullying is distrust that the school personnel will not keep confidentiality about their sexual and/or gender identity and will, instead, out them to other staff and family members. In addition, another striking and disturbing finding unique to LGBTQ students and traditional bullying is the fact that some of these students identify school personnel as the perpetrators of harassment and bullying (Kosciw et al. 2016 ) and, therefore, these students feel powerless to report their experiences due to the fact that those whose duty is to protect them are the actual perpetrators.

LGBTQ Youth of Color and Cyberbullying

Although limited, some of the data provides information about the intersection of sexual and gender identity and race and ethnicity. Cooper and Blumenfeld ( 2012 ) found that in the last 30 days, 14% of LGBT youth reported being harassed based on their race or ethnicity. However, this finding does not seem to be corroborated by other studies in this literature review. Specifically, GLSEN et al. ( 2013 ) found that African American and Asian LGBT participants were the least exposed to cyberbullying when compared to their White counterparts. On the other hand, two studies found that there were no differences in overall reporting of cyberbullying by race or ethnicity (Schneider et al. 2012 ; Stoll and Block 2015 ).

Correlates and Impact

This literature review revealed nine studies that reported findings on the correlates of cyberbullying for LGBT youth. Overall, there is a higher correlation between being a victim of cyberbullying and negative outcomes for sexual minority and gender expansive youths than for their heterosexual and cisgender counterparts. There is no doubt that when sexual minorities and gender expansive youths feel “outed,” exposed, and harassed due to their sexual and gender identity they are vulnerable to negative mental health outcomes including isolation and psychological distress (Cénat et al. 2015 ). For the purpose of this review, the authors have classified correlates and impact into three main categories: (a) psychological and emotional, (b) behavioral, and (c) academic.

Psychological and Emotional Correlates of Cyberbullying among LGBTQ Youth

Psychological and emotional correlates of cyberbullying are perhaps the most well researched correlate for cyberbullying among sexual minority and gender expansive youth. We have classified the different areas of psychological and emotional correlates under the categories of: (a) suicidal ideation and attempt, (b) depression, and (c) lower self-esteem.

This literature review revealed a correlation between suicidal ideation and attempt and cyberbullying alone and a combination of cyberbullying with traditional bullying (Cénat et al. 2015 ; Cooper and Blumenfeld 2012 ; Duong and Bradshaw 2014 ; Schneider et al. 2012 ; Sinclair et al. 2012 ), with many participants reporting the need for medical attention after serious suicide attempts (Sinclair et al. 2012 ). Cooper and Blumenfeld ( 2012 ) found that 35% of LGBT participants reported having suicidal thoughts while 14% reported attempting suicide as a result of being cyberbullied. Also, Duong and Bradshaw ( 2014 ) found that LGB participants attempted suicide in the past 12 months at a rate of 3.07 times higher after being cyberbullied. In addition, in the study by Cénat et al. ( 2015 ), sexual minority youth who reported being victims of cyberbullying reported higher rates of suicidal ideation than those sexual minority participants who were not victims (55.6% vs. 24.7%). Similarly, Schneider et al. ( 2012 ) found that suicide attempt was highest among participants who had been cyberbullied versus those who had experienced face-to-face school bullying (9.4% vs. 4.2%). In addition, gender seems to play a role among sexual minorities who report suicidal ideation and attempts as a result of cyberbullying. Cénat et al. ( 2015 ) found that bisexual and questioning girls and bisexual boys were more likely to report suicidal ideations than heterosexual boys, with bisexual girls reporting higher levels than other sexual minority youth.

It is important to note that participants who experienced two forms of bullying (i.e., face-to-face and cyberbullying) reported greater rates of serious suicide attempts than those who only reported being bullied face-to-face (5.03 vs. 4.20 times). Also, those who experienced two forms of bullying reported making serious suicide attempts and engaged in more suicidal behaviors than those who reported only one form of bullying (Duong and Bradshaw 2014 ). Compared to participants who did not report any form of bullying, the risk of attempted suicide was 4.72 times greater for LGB youth who experienced one form of victimization and 8.30 times greater for students who experienced two forms of victimization (Duong and Bradshaw 2014 ). Similar findings were reported by Schneider et al. ( 2012 ), who found the highest percentage of suicide among those who reported both face-to-face and cyberbullying combined (15.2%).

Sexual minority youth who have been exposed to cyberbullying report higher levels of depression compared to those who have not (GLSEN et al. 2013 ; Ramsey et al. 2016 ; Sinclair et al. 2012 ). Specifically, Cooper and Blumenfeld ( 2012 ) found that feelings of depression were the highest ranked emotional response correlated to cyberbullying among LGBT participants. Similarly, Schneider et al. ( 2012 ) found that 33.9% of those participants who reported being cyberbullied reported symptoms of depression. On the other hand, similar to findings about suicide ideation and attempt, those who experience both traditional and cyberbullying reported higher symptoms of depression. Cyberbullying has also been associated with lower self-esteem for sexual minorities and gender expansive youth (Cénat et al. 2015 ; GLSEN et al. 2013 ; Priebe and Svedin 2012 ). Furthermore, although not widely explored in this review, bisexual and questioning girls and bisexual boys were more likely to report lower self-esteem, with bisexual girls reporting lower levels than other sexual minority youth (Cénat et al. 2015 ).

Behavioral Correlates of Cyberbullying among LGBTQ Youth

While there is no evidence to support that cyberbullying alone leads sexual minorities to engage in more physical fights, being a victim of cyberbullying and traditional bullying exacerbates physical fights among these youth and their peers (Duong and Bradshaw 2014 ). It is important to note that research shows that when LGBT students stand up for themselves against being bullied and harassed they face harsher consequences than the perpetrator (Golgowki 2014 ). Other behavioral correlates are poor body image, isolating themselves from friends and family and fear of going to school (Cooper and Blumenfeld 2012 ).

Academic Correlates of Cyberbulling among LGBTQ Youth

According to GLSEN et al. ( 2013 ), LGBT youth who were cyberbullied reported significantly lower GPAs and overall academic success than youth who were less frequently cyberbullied. Participants who were victims of cyberbullying reported lower school performance (e.g., receiving failing academic grades) and lower school attachment (Cooper and Blumenfeld 2012 ; Schneider et al. 2012 ).

Prevention and Intervention Recommendations

Despite the rates of cyberbullying in sexual minorities and gender expansive youth, there is an absence of empirically evaluated prevention efforts addressing this problem. As stated by Ramsey et al. ( 2016 ), “Few interventions exist that are specifically developed to decrease… cyberbullying, and no interventions of this kind exist for sexual minority populations in particular” (p. 497). Taking into consideration existing research that supports the notion that a one-size fits all does not protect LGBTQ students against bullying (Kull et al. 2015 ), we propose that cyberbullying prevention and intervention programs be tailored for LGBTQ students. Our recommendations for students, schools and parents are based on anti-cyberbullying interventions discussed in 11 of the identified studies in this literature review and a comprehensive review of two bodies of literature: (a) overall cyberbullying prevention efforts and (b) LGBT bullying prevention strategies.

Student-Focused Interventions

Blumenfeld and Cooper ( 2010 ) and Ramsey et al. ( 2016 ) recommend raising awareness among students about the effects of LGBTQ cyberbullying by using educational programs that are peer-driven as an important intervention. Although no LGBTQ-specific programs exist, peer-driven interventions have proven to be effective in increasing awareness and reducing incidents of cyberbullying among students. While not used with LGBTQ students, in evaluating a peer-led approach (i.e., NoTrap!) to reduce cyberbullying among high school students, Palladino et al. ( 2016 ) found it had long-term effects in reducing cyberbullying for both boys and girls. Putting students in charge of delivering information to other students is an effective way of getting buy-in and increasing awareness and decreasing behaviors that constitute cyberbullying. Applying these findings to LGBTQ students, it is recommended that LGBTQ victims be involved in these awareness and prevention efforts. That is, with the consent of the LGBTQ student and protection of school personnel to make sure further harassment is not perpetrated, LGBTQ students should be active in the content selection, development, and implementation of a peer-led model. This will be crucial as bullying research suggests that when individuals are able to make an emotional connection with what is being presented to them, they are more likely to intervene (Case and Meier 2014 ).

Technology is also being used as an intervention to increase knowledge about what constitutes cyberbullying and its consequences, foster empathy toward victims, reduce the impact (e.g., depression) on victims, and teach coping skills to current and potential victims. Doane et al. ( 2016 ) developed and implemented a program, Theory of Reasoned Action-TRA , to measure the effectiveness of a video-based intervention with students. Although not focused on LGBT youth, results revealed that compared to students who were not exposed to the intervention (i.e., control group), those who were showed an increase in knowledge of cyberbullying and more empathy toward victims immediately after the intervention and at a one-month follow-up. Although this technology-based program has been successful in reducing cyberbullying and increasing empathy among students, we pose that this and similar programs must incorporate understanding of the needs of sexual minority and gender expansive youth, including how these platforms can be a source of support for LGBTQ youth (Hillier et al. 2010 ). For example, GLSEN et al. ( 2013 ) report that a substantial number of LGBT youth report searching for or reading about sexuality-related information online, thus, making the Internet an appropriate platform where these youth can access different sources of information, including information about cyberbullying, without having to be “outed.” Hillier et al. ( 2010 ) suggest that schools create online forums for LGBTQ students to connect safely with others. Similar to face-to-face interventions, online interventions must include specific information and scenarios to bring visibility to the higher prevalence of cyberbullying among sexual minority and gender expansive youth.

Other interventions include empowering youth to serve as “upstanders” and not bystanders. These methods would encourage them to intervene when they witness or become aware of cyberbullying (Blumenfeld and Cooper 2010 ). Flanagan ( 2014 ) proposed using cognitive behavioral techniques to teach individual and group interventions to students such as how to appropriately address conflict with others, impulse control management, cultivating a positive self-esteem, and fostering self-efficacy.

School-Focused Interventions

The need to have a supportive and safe school environment for sexual minority and gender expansive youth is essential. It is recommended that schools include cyberbullying into their already existing traditional bullying intervention and education programs (Schneider et al. 2012 ). For example, Bauman and Baldasare ( 2015 ) suggest that teachers across grade levels include a statement on their syllabus about what behaviors constitute cyberbullying, available resources for victims, and consequences for perpetrators. Also, researchers agree that schools must create and enforce explicit policies against students who tease, threaten, exclude, or mistreat other students based on sexual orientation or gender identity and/or expression, including cyberbullying (Blumenfeld and Cooper 2010 ; Hinduja and Patchin 2012 ). LGBTQ participants in the study by Blumenfeld and Cooper ( 2010 ) recommend that schools create online methods for students to anonymously report incidences of cyberbullying or having witnessed someone being cyberbullied, as it could allow for early opportunities to intervene and educate. These online reporting sites need to be accessed regularly and swift action taken by school authorities. These policies not only deliver the message that school personnel are invested in ending cyberbullying against LGBTQ students but are crucial in reducing harassment against this vulnerable population. Guasp ( 2012 ) found that sexual minority students were significantly less likely to be bullied in schools that responded quickly to homophobic bullying than in schools that did not respond to these incidents.

Additional training for school personnel would include education about their state’s laws regarding cyberbullying, including states that include sexual minority and gender expansive youth as part of these laws. Although currently all of the United States and the District of Columbia (with the exception of Alaska and Wisconsin) have laws against cyberbullying, only 14 states 1 and the District of Columbia include gender identity/expression. Eighteen states 2 and the District of Columbia are inclusive of sexual orientation in their anti-cyberbullying laws (Cyberbullying Research Center 2016 ; Stop Bullying 2015 ). While these laws exist, the extent to which school personnel alert law enforcement is unknown.

A critical intervention for incidents of LGBTQ bullying and cyberbullying is the identification of “safe” faculty and administrators who students can turn to for help (Duong and Bradshaw 2014 ). According to Mace et al. ( 2016 ) school personnel are crucial in identifying LGBTQ victims of bullying, including cyberbullying, and helping students access support services within the school. School participants in a study by Liboro et al. ( 2015 ) were in agreement that the more confident and comfortable the teachers were in supporting LGBT students, the safer they felt. In addition, Duong and Bradshaw ( 2014 ) found that having an adult to talk to at school was protective against engaging in physical fights, attempting suicide, and making serious suicide attempts for cyberbullied sexual minority youth. The authors maintain that adults, administrators, teachers, and staff, who are openly supportive of (and knowledgeable about) LGBTQ perspectives and issues, should make themselves available as a resource to students (Hinduja and Patchin 2012 ). Actions that increase LGBTQ visibility in schools, such as having a Gay-Straight Alliance (GSA) club in school, positive representations of LGBTQ people and events in classroom discussions, LGBTQ-inclusive library materials, sex education, and signage, can potentially reduce incidents of cyberbullying.

Parent-Focused Interventions

Parents need to be aware of the risks associated with the use of technology, including high incidents of cyberbullying (Ramsey et al. 2016 ). In addition, providing parents education about youth reports on cyberbullying and the reasons for not reporting cyberbullying can help inform educational programs for parents and potentially increase parents’ supportive responses in the case of victimization. Youth often do not want to report cyberbullying because they are fearful that their technology devices will be taken away (Blumenfeld and Cooper 2010 ).

Many parents do not feel competent enough with technology to be involved in their child’s technology activities, and believe their children are the experts (Schneider et al. 2015 ). Therefore, parents should be proactive and seek information about their child’s technology use by directly asking the child (Flanagan 2014 ). Recognizing that it is not feasible for parents to monitor their child’s use of technology at all times, scholars recommend that parents discuss, share, and have their child sign a family contract that outlines responsible and healthy ways of using technology (e.g., Scola 2014 ; for more information and ideas for parent-child media agreements visit https://mediatechparenting.net/contracts-and-agreements/ ). In addition, it is important to recognize that regarding parents and family involvement in LGBTQ-specific cyberbullying there are added layers of concerns that must be considered. For instance, the LGBTQ adolescent being bullied might not be out to their parents. Thus, when discussing family contracts, parents should openly mention information about cyberbullying prevalence and consequences about LGBTQ youth, regardless of their child’s sexual and/or gender identity. This delivers a message of safety and may lead to potentially encouraging the child to disclose and have a conversation regarding LGBTQ-specific bullying instances.

A Collaborative Approach to Cyberbullying Prevention

These authors suggest a comprehensive prevention effort among students, school personnel and parents in order to target cyberbullying, rather than individual, disconnected efforts. Research suggests that when schools work together with students, parents, and community partners and leaders, there is a decrease in cybervictimization among youth (Couvillon and Ilieva 2011 ; Flanagan 2014 ). When planning for cyberbullying programming, involving the various stakeholders in youths’ lives increases consistency in policy development and enforcement (Couvillon and Ilieva 2011 ; Flanagan 2014 ; Simmons and Bynum 2014 ). For example, attorneys can help schools, teachers, and parents understand the legal ramifications for engaging in cyberbullying and different ways to access already established legal supports for victims of cyberbullying (Flanagan 2014 ). These authors recommend that schools establish a community-wide LGBTQ-cyberbullying taskforce to assess their school’s LGBTQ-bullying climate and develop and implement programs to protect sexual minority and gender expansive students. Schools should build relationships with local community organizations that specifically work with LGBTQ youth in order for them to provide their expertise in addressing LGBTQ cyberbullying.

This literature review explored the prevalence and correlates for LGBTQ victims of cyberbullying and provided interventions and recommendations for this vulnerable population. The 27 studies reviewed differed in location, sample size, and methodology, with most studies employing quantitative methods ( n  = 21) and only one qualitative study. LGBTQ youth are disproportionally more likely to experience cyberbullying and suffer negative outcomes (i.e., psychological and emotional, behavioral, academic, and relational) than their heterosexual and cisgender counterparts. In addition, to date no LGBTQ specific cyberbullying interventions exist. This literature review revealed 11 studies that provided recommendations based on the larger literature on cyberbullying prevention efforts. Based on the recommendations presented in this literature review and other studies on cyberbullying and LGBTQ prevention strategies we have provided recommendations tailored specifically to target and hopefully reduce LGBTQ cyberbullying.

Gaps and Recommendations

As presented in this paper, perhaps the most important and noticeable limitation is the absence of LGBTQ-specific cyberbullying interventions and prevention research. The authors of this paper propose that in order to decrease the prevalence of cyberbullying among LGBTQ youth, researchers need to be intentional about understanding the needs of this marginalized population and create interventions grounded on specific needs of LGBTQ youth. Currently, not only there are no programs that address LGBTQ cyberbullying, but there are few programs that provide interventions and prevention for traditional bullying of LGBTQ youth as well. An observation across studies was the lack of representation of LGBTQ students of color. That is, although racial, ethnic, sexual, and gender identities were reported by most studies, analyses rarely included a consideration of LGBTQ students of color and their experiences of cyberbullying. Notably, only four studies (i.e., Cooper and Blumenfeld 2012 ; GLSEN et al. 2013 ; Schneider et al. 2012 ; Stoll and Block 2015 ) included race and ethnicity as part of their analysis and results. Unfortunately, there seems to exist a discrepancy, with two of these studies (i.e., Schneider et al. 2012 ; Stoll and Block 2015 ) reporting no differences in overall reporting of cyberbullying by race or ethnicity. Considering that research on traditional bullying and discrimination among LGBTQ students of color suggest that these students might suffer greater victimization than their White peers, we pose that cyberbullying of LGBTQ people of color needs to be further explored and systematically researched. In addition, it is important to note that LGBTQ youth may also have other oppressed intersecting identities that may make them more susceptible to bullying, including race and ethnicity, gender expression (e.g., performing one’s gender in a more masculine or feminine way than expected), body type, socioeconomic status, and religious identity. In a school climate study of 2130 LGBTQ students of color, Diaz and Kosciw ( 2009 ) found that over 80% of these students were harassed in the past year for their sexual identity and “more than half of African American (51%), Latino/a (55%), Asian/Pacific Islander (55%), and multiracial students (59%) report[ing] being verbally harassed in school for this reason” (p. xi). Also, LGBT students might experience higher rates of cyberbullying for reasons (e.g., depression, lower self-esteem) other than their sexual and gender identity. For example, while bullying has been associated with depression among children and adolescents, studies have revealed that it is also true that depressed children and adolescents tend to be more bullied and victimized than their peers (e.g., Kochel et al. 2012 ; Schacter and Juvonen 2017 ). In a longitudinal study of 486 fourth through sixth graders, Kochel et al. ( 2012 ) found that higher symptoms of depression among participants indicated higher levels of victimization. Considering that LGBTQ individuals, including youth, suffer higher prevalence of depression and lower self-esteem (e.g., Institute of Medicine 2011 ), it would be beneficial to further investigate the relationship between negative consequences and cyberbullying, and vice versa, in order to more accurately capture and understand to what extent cyberbullying affects LGBTQ youth.

Experiences of transgender and other gender expansive individuals are either conflated with sexual identity or outright ignored in most studies. Also, in studies where transgender participants are included, conclusions are drawn from a small sample of participants, with as little as only 0.25% of the sample being comprised of gender expansive students. Future research should thoroughly explore the experiences of cyberbullying of transgender and other gender expansive students. It is possible that the experiences of gender expansive students are as different, and perhaps more pervasive and negative than LGB and heterosexual students and, therefore, different cyberbullying prevention strategies might be needed. Moreover, the studies that have been presented in this literature review specifically capture those who identify with a particular label (LGBTQ). As stated by Kosciw et al. ( 2012 ), conclusions cannot be drawn from youth who might engage in same-sex relationships but who do not particularly identify with a label or as a sexual minority or gender expansive youth. Therefore, further research should also assess for cyberbullying among individuals who identify with other sexual identities, or no specific sexual identities, but engage in same-sex relationships.

Methodological Concerns

An important limitation is sampling strategy. That is, most studies recruited participants in school settings or LGBTQ-related organizations. While these are reasonable and understandable recruitment sites, it is plausible to believe that the results and experiences discussed in this paper reflect only those of LGBTQ individuals who have connections to these organizations or who felt safe enough to participate in the study (e.g., Kosciw et al. 2012 ).

Cyberbullying research lacks theoretical and conceptual clarity, including differences in definition, operationalization, and cut-off values (i.e., the frequency of experiences and/or behaviors a person must experience to be considered cyberbullying; Zych et al. 2016 ). Specific to this paper, 11 studies used multiple items to assess cyberbullying, nine used a one-item scale, and seven did not specify how many items were used (including the one qualitative study). In addition, some researchers have made the case that research should focus on wide-range experiences of cyber-aggression, and not specifically cyberbullying (e.g., Smith 2016 ), while other researchers argue that cyberbullying is a specific form of cyber-aggression that must be studied separately (e.g., Smith et al. 2013 ). We pose that as researchers further develop and test new ways of defining and assessing for cyberbullying, that the experiences of LGBTQ youth are taken into consideration.

Suggestions for Future Research

Most studies in this review used a cross sectional research design, making it challenging for researchers to accurately understand the long term consequences of cyberbullying and limiting the ability to make causal inferences (Cénat et al. 2015 ; Duong and Bradshaw 2014 ). Future research should employ longitudinal research designs to better assess the effects of cyberbullying on LGBTQ youth over time and establish causation (Ramsey et al. 2016 ). Also, efforts should be made to cast a wider net and try to reach LGBTQ youth who might be isolated or not have LGBTQ-related organizations readily available within their communities (e.g., rural communities, communities with large numbers of LGBTQ people of color). In addition, the lack of uniformity regarding the definitions and evaluation measurements of cyberbullying makes it difficult for researchers to accurately describe and make definitive deductions regarding the prevalence and impact of cyberbullying (e.g., Hamm et al. 2015 ). Lack of consistency and representative sampling approach makes it challenging for researchers to precisely capture the extent to which cyberbullying affects LGBTQ youth, thus affecting their ability to recommend evidence-based interventions to combat and dismantle LGBTQ cyberbullying.

LGBTQ youth are harassed and cyberbullied at rates higher than their heterosexual and cisgender counterparts, resulting in psychological and behavioral effects. These youth, who are often already experiencing traditional bullying, lack support from their peers, parents, schools and community and frequently do not report cyberbullying. Current cyberbullying interventions do not target these youth in their efforts and notably absent is programming geared toward LGBTQ youth of color. It is recommended that schools work collaboratively with parents, LGBTQ students, and community partners to create policies to protect these students. Parents are encouraged to dialogue openly with their children about the risks of social media and provide supportive responses when youth disclose cyberbullying. Comprehensive school policies that create a climate of awareness for LGBTQ-specific cyberbullying are recommended to begin to combat cyberbullying. There is also a need to create therapeutic communities to assist victims in recovering from this traumatic form of bullying and decrease psychological distress.

Acknowledgements

The authors would like to thank Lorena Perez, Marina Marchena, and Haiying Long for their assistance in manuscript preparation.

Compliance with Ethical Standards

On behalf of all authors, the corresponding author states that there is no conflict of interest.

1 Arkansas, California, Connecticut, Delaware, Illinois, Iowa, Maine, Maryland, Massachusetts, Minnesota, New Jersey, North Carolina, Rhode Island, and Vermont

2 Arkansas, California, Colorado, Connecticut, Delaware, Illinois, Iowa, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New Mexico, New York, North Carolina, Rhode Island, Vermont and Washington

Contributor Information

Roberto L. Abreu, Email: [email protected] .

Maureen C. Kenny, Email: ude.uif@mynnek .

References marked with an asterisk (*) indicate studies included in the meta-analysis.

  • Aboujaoude E, Savage M, Starcevic V, Salame W. Cyberbullying: Review of an old problem gone viral. Journal of Adolescent Health. 2015; 57 :10–18. doi: 10.1016/j.jadohealth.2015.04.011. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • *Bauman, S., & Baldasare, A. (2015). Cyber aggression among college students: Demographic differences, predictors of distress, and the role of the university. Journal of College Student Development, 56 , 317–330. doi:10.1353/csd.2015.0039
  • Bjereld Y. The challenging process of disclosing bullying victimization: A grounded theory study from the victim's point of view. Journal of Health Psychology. 2016; 1 :1–9. [ PubMed ] [ Google Scholar ]
  • Black WW, Fedewa AL, Gonzalez KA. Effects of “Safe School” programs and policies on the social climate for sexual-minority youth: A review of the literature. Journal of LGBT Youth. 2012; 9 :321–339. doi: 10.1080/19361653.2012.714343. [ CrossRef ] [ Google Scholar ]
  • *Blais, M., Gervais, J., Boucher, K., Hébert, M., & Lavoie, F. (2013). Prevalence of prejudice based on sexual minority status among 14 to 22-year-old youths in the province of Quebec (Canada). International Journal of Victimology, 11 , 1–13.
  • *Blumenfeld, W. J., & Cooper, R. M. (2010). LGBT and allied youth responses to cyberbullying: Policy implications. The International Journal of Critical Pedagogy, 3 , 114–133.
  • *Bouris, A., Everett, B. G., Heath, R. D., Elsaesser, C. E., & Neilands, T. B. (2016). Effects of victimization and violence on suicidal ideation and behaviors among sexual minority and heterosexual adolescents. LGBT Health, 3 , 153–161. doi:10.1089/lgbt.2015.0037 [ PMC free article ] [ PubMed ]
  • Case KA, Meier SC. Developing allies to transgender and gender-nonconforming youth: Training for counselors and educators. Journal of LGBT Youth. 2014; 11 :62–82. doi: 10.1080/19361653.2014.840764. [ CrossRef ] [ Google Scholar ]
  • *Cénat, J. M., Blais, M., Hébert, M., Lavoie, F., & Guerrier, M. (2015). Correlates of bullying in Quebec high school students: The vulnerability of sexual-minority youth. Journal of Affective Disorders, 183 , 315–321. doi:10.1016/j.jad.2015.05.011 [ PMC free article ] [ PubMed ]
  • Collier KL, van Beusekom G, Bos HM, Sandfort TG. Sexual orientation and gender identity/expression related peer victimization in adolescence: A systematic review of associated psychosocial and health outcomes. Journal of Sex Research. 2013; 50 :299–317. doi: 10.1080/00224499.2012.750639. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • *Cooper, R. M., & Blumenfeld, W. J. (2012). Responses to cyberbullying: A descriptive analysis of the frequency of and impact on LGBT and allied youth. Journal of LGBT Youth, 9 , 153–177.
  • Couvillon MA, Ilieva V. Recommended practices: A review of schoolwide preventative programs and strategies on cyberbullying. Preventing School Failure: Alternative Education for Children and Youth. 2011; 55 :96–101. doi: 10.1080/1045988X.2011.539461. [ CrossRef ] [ Google Scholar ]
  • Cyberbullying Research Center (2016). Bullying laws across America . Retrieved from http://cyberbullying.org/bullying-laws .
  • DeLara EW. Why adolescents don't disclose incidents of bullying and harassment. Journal of School Violence. 2012; 11 :288–305. doi: 10.1080/15388220.2012.705931. [ CrossRef ] [ Google Scholar ]
  • Diaz EM, Kosciw JG. Shared differences: The experiences of lesbian, gay, bisexual, and transgender students of color in our nation's schools. New York: GLSEN; 2009. [ Google Scholar ]
  • Doane AN, Kelley ML, Pearson MR. Reducing cyberbullying: A theory of reasoned action- based video prevention program for college students. Aggressive Behavior. 2016; 42 :136–146. doi: 10.1002/ab.21610. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • *Duong, J., & Bradshaw, C. (2014). Associations between bullying and engaging in aggressive and suicidal behaviors among sexual minority youth: The moderating role of connectedness. Journal of School Health, 84 , 636–645. [ PubMed ]
  • Espelage DL, Basile KC, De La Rue L, Hamburger ME. Longitudinal associations among bullying, homophobic teasing, and sexual violence perpetration among middle school students. Journal of Interpersonal Violence. 2015; 30 :2541–2561. doi: 10.1177/0886260514553113. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Evans, C. B., & Smokowski, P. R. (2016). Negative bystander behavior in bullying dynamics: Assessing the impact of social capital deprivation and anti-social capital. Child Psychiatry & Human Development , 1–16. [ PubMed ]
  • Flanagan, A. Y. (2014). Cyberbullying and harassment. NetCE . Retrieved from https://www.netcegroups.com/1127/Course_66421.pdf .
  • Flaspohler PD, Elfstrom JL, Vanderzee KL, Sink HE, Birchmeier Z. Stand by me: The effects of peer and teacher support in mitigating the impact of bullying on quality of life. Psychology in the Schools. 2009; 46 :636–649. doi: 10.1002/pits.20404. [ CrossRef ] [ Google Scholar ]
  • *GLSEN, CiPHER & CCRC (2013). Out online: The experiences of lesbian, gay, bisexual and transgender youth on the Internet . New York: GLSEN.
  • Golgowki, N. (2014. Transgender teen bullied at school faces criminal charges for fight which only suspended other girls. The New York Daily News. Retrieved from http://www.nydailynews.com/news/national/bullied-transgender-teen-faces-criminal-charges-fight-article-1.1571349 .
  • *Guasp, A. (2012). The school report. The experiences of gay young people in Britain’s schools in 2012 . London: Stonewall.
  • Hamm MP, Newton AS, Chisholm A, Shulhan J, Milne A, Sundar P, et al. Prevalence and effect of cyberbullying on children and young people: A scoping review of social media studies. JAMA Pediatrics. 2015; 169 :770–777. doi: 10.1001/jamapediatrics.2015.0944. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • *Hillier, L., Jones, T., Monagle, M., Overton, N., Gahan, L., Blackman, J., & Mitchell, A. (2010). Writing themselves in 3: The third national study on the sexual health and wellbeing of same sex attracted and gender questioning young people . Carlton: National Centre in HIV Social Research, La Trobe University.
  • *Hinduja, S., & Patchin, J. W. (2012). Cyberbullying research summary: Bullying, cyberbullying, and sexual orientation. Cyberbullying Research Center . Retrieved from http://cyberbullying.org/cyberbullying_sexual_orientation_fact_sheet.pdf .
  • Hinduja, S. & Patchin, J. W. (2014). Cyberbullying identification, prevention, and response. Cyberbullying research center. Retrieved from www.cyberbullying.us .
  • Holt MK, Espelage DL. Perceived social support among bullies, victims, and bully-victims. Journal of Youth and Adolescence. 2007; 36 :984–994. doi: 10.1007/s10964-006-9153-3. [ CrossRef ] [ Google Scholar ]
  • Institute of Medicine (US) The health of lesbian, gay, bisexual, and transgender people: Building a foundation for better understanding. Washington, DC: National Academies Press; 2011. [ PubMed ] [ Google Scholar ]
  • Kann L, Olsen EO, McManus T, Harris WA, Shanklin SL, Flint KH, et al. Sexual identity, sex of sexual contacts, and health-related behaviors among students in grades 9–12 — United States and selected sites, 2015. US Department of Health and Human Services/Centers for Disease Control and Prevention. 2016; 65 :1–202. [ PubMed ] [ Google Scholar ]
  • Kochel KP, Ladd GW, Rudolph KD. Longitudinal associations among youth depressive symptoms, peer victimization, and low peer acceptance: An interpersonal process perspective. Child Development. 2012; 83 :637–650. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • *Kosciw, J. G., Greytak, E. A., Bartkiewicz, M. J., Boesen, M. J., & Palmer, N. A. (2012). The 2011 national school climate survey: The experiences of lesbian, gay, bisexual and transgender youth in our nation’s schools . New York: GLSEN.
  • *Kosciw, J. G., Greytak, E. A., Giga, N. M., Villenas, C. & Danischewski, D. J. (2016). The 2015 national school climate survey: The experiences of lesbian, gay, bisexual, transgender, and queer youth in our nation’s schools . New York: GLSEN.
  • Kull RM, Kosciw JG, Greytak EA. From statehouse to schoolhouse: Anti-bullying policy efforts in US states and school districts. New York: GLSEN; 2015. [ Google Scholar ]
  • Lenhart, A. (2015). Teens, social media and technology overview 2015. Pew Research Center . Retrieved from http://www.pewinternet.org/2015/04/09/teens-social-media-technology-2015/ .
  • Liboro RM, Travers R, St. John A. Beyond the dialectics and polemics: Canadian catholic schools addressing LGBT youth issues. The High School Journal. 2015; 98 :158–180. doi: 10.1353/hsj.2015.0000. [ CrossRef ] [ Google Scholar ]
  • *Mace, S., Campbell, M., & Whiteford, C. (2016). Coping with victimization in heterosexual and sexual minority university students. Journal of Gay & Lesbian Social Services, 28 , 159–170.
  • Montoro R, Igartua K, Thombs BD. The association of bullying with suicide ideation and attempt among adolescents with different dimensions of sexual orientation. European Psychiatry. 2016; 33 :S71. doi: 10.1016/j.eurpsy.2016.01.984. [ CrossRef ] [ Google Scholar ]
  • Palladino BE, Nocentini A, Menesini E. Evidence-based intervention against bullying and cyberbullying: Evaluation of the NoTrap! program in two independent trials. Aggressive Behavior. 2016; 42 :194–206. doi: 10.1002/ab.21636. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Pham T, Adesman A. Teen victimization: Prevalence and consequences of traditional and cyberbullying. Current Opinion in Pediatrics. 2015; 27 :748–756. doi: 10.1097/MOP.0000000000000290. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • *Priebe, G., & Svedin, C. G. (2012). Online or off-line victimization and psychological well-being: A comparison of sexual-minority and heterosexual youth. European Child & Adolescent Psychiatry, 21 , 569–582. [ PubMed ]
  • *Ramsey, J. L., DiLalla, L. F., & McCrary, M. K. (2016). Cyber victimization and depressive symptoms in sexual minority college students. Journal of School Violence, 15 , 483–502.
  • *Rice, E., Petering, R., Rhoades, H., Winetrobe, H., Goldbach, J., Plant, A., …Kordic, T. (2015). Cyberbullying perpetration and victimization among middle-school students. American Journal of Public Health, 105 , e66-e72. [ PMC free article ] [ PubMed ]
  • *Robinson, J. P., & Espelage, D. L. (2011). Inequities in educational and psychological outcomes between LGBTQ and straight students in middle and high school. Educational Researcher, 40 , 315–330.
  • Schacter, H. L., & Juvonen, J. (2017). Depressive symptoms, friend distress, and self-blame: Risk factors for adolescent peer victimization. Journal of Applied Developmental Psychology . doi:10.1016/j.appdev.2017.02.005. [ PMC free article ] [ PubMed ]
  • *Schneider, S. K., O'Donnell, L., & Smith, E. (2015). Trends in cyberbullying and school bullying victimization in a regional census of high school students, 2006–2012. Journal of School Health, 85 , 611–620. [ PubMed ]
  • *Schneider, S. K., O'Donnell, L., Stueve, A., & Coulter, R. W. (2012). Cyberbullying, school bullying, and psychological distress: A regional census of high school students. American Journal of Public Health, 102 , 171–177. [ PMC free article ] [ PubMed ]
  • Scola, B. (2014). Family contract for responsible electronic device use. Pitcairn . Retrieved from http://www.pitcairn.com/electronic-device-contract/ .
  • Simmons K, Bynum Y. Cyberbullying: Six things administrators can do. Education. 2014; 134 :452–456. [ Google Scholar ]
  • *Sinclair, K. O., Bauman, S., Poteat, V. P., Koenig, B., & Russell, S. T. (2012). Cyber and bias-based harassment: Associations with academic, substance use, and mental health problems. Journal of Adolescent Health, 50 , 521–523. [ PubMed ]
  • Smith PK. Bullying: Definition, types, causes, consequences and intervention. Social and Personality Psychology Compass. 2016; 10 :519–532. doi: 10.1111/spc3.12266. [ CrossRef ] [ Google Scholar ]
  • Smith PK, Del Barrio C, Tokunaga RS. Definitions of bullying and cyberbullying: How useful are the terms. In: Bauman S, Cross D, Walker J, editors. Principles of cyberbullying research: Definitions, measures, and methodology. London: Routledge; 2013. pp. 26–40. [ Google Scholar ]
  • *Sterzing, P. R., Ratliff, G. A., Gartner, R. E., McGeough, B. L., & Johnson, K. C. (2017). Social ecological correlates of polyvictimization among a national sample of transgender, genderqueer, and cisgender sexual minority adolescents. Child Abuse & Neglect, 67 , 1–12. doi:10.1016/j.chiabu.2017.02.017. [ PubMed ]
  • *Stoll, L. C., & Block, R. (2015). Intersectionality and cyberbullying: A study of cybervictimization in a Midwestern high school. Computers in Human Behavior, 52 , 387–397.
  • Stop Bullying (2015). Policies and laws . Retrieved from http://www.stopbullying.gov/laws/ .
  • *Taylor, C. & Peter, T., with McMinn, T.L., Elliott, T., Beldom, S., Ferry, A., Gross, Z., Paquin, S., & Schachter, K. (2011). Every class in every school: The first national climate survey on homophobia, biphobia, and transphobia in Canadian schools. Final report. Toronto: Egale Canada Human Rights Trust.
  • *Varjas, K., Meyers, J., Kiperman, S., & Howard, A. (2013). Technology hurts? Lesbian, gay, and bisexual youth perspectives of technology and cyberbullying. Journal of School Violence, 12 , 27–44.
  • *Walker, C. (2015). An analysis of cyberbullying among sexual minority university students. Journal of Higher Education Theory and Practice, 15 , 44–50.
  • *Wensley, K., & Campbell, M. (2012). Heterosexual and nonheterosexual young university students’ involvement in traditional and cyber forms of bullying. Cyberpsychology, Behavior, and Social Networking, 15 , 649–654. [ PubMed ]
  • White HD. Scientific communication and literature retrieval. In: Cooper H, Hedges LV, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994. pp. 41–56. [ Google Scholar ]
  • Zych I, Ortega-Ruiz R, Del Rey R. Systematic review of theoretical studies on bullying and cyberbullying: Facts, knowledge, prevention, and intervention. Aggression and Violent Behavior. 2015; 23 :1–21. doi: 10.1016/j.avb.2015.10.001. [ CrossRef ] [ Google Scholar ]
  • Zych, I., Ortega-Ruiz, R., & Marín-López, I. (2016). Cyberbullying: A systematic review of research, its prevalence and assessment issues in Spanish studies. Psicología Educativa, 22 , 5–18. doi:10.1016/j.pse.2016.03.002.

IMAGES

  1. (PDF) Cyberbullying: A Systematic Literature Review to Identify the

    cyber bullying literature review

  2. PPT

    cyber bullying literature review

  3. (PDF) Bullying and cyberbullying and deaf and hard of hearing children

    cyber bullying literature review

  4. J.c. van leeuwen 2012

    cyber bullying literature review

  5. (PDF) Cyberbullying in the World of Teenagers and Social Media:: A

    cyber bullying literature review

  6. (PDF) Cyberbullying: A narrative review

    cyber bullying literature review

VIDEO

  1. Cyber bullying CCS Middle Schools

  2. Безопасное поведение в интернете: как ученикам защититься от кибербуллинга

  3. Spun

  4. Anti-Bullying Music Video

  5. Impact of Rising Cyberbullying on High School Performance

  6. gay bullying it is wrong.it get better.maverick mista majah p🏳️‍🌈🌈

COMMENTS

  1. (PDF) Cyberbullying: A Review of the Literature

    PDF | On Jan 1, 2021, Saurav Chakraborty and others published Cyberbullying: A Review of the Literature | Find, read and cite all the research you need on ResearchGate

  2. PDF Cyberbullying: A Review of the Literature

    A review of literature is provided and results and analysis of the survey are discussed as well as recommendations for future research. Erdur-Baker's (2010) study revealed that 32% of the students were victims of both cyberbullying and traditional bullying, while 26% of the students bullied others in both cyberspace and physical environments ...

  3. Cyberbullying Among Adolescents and Children: A Comprehensive Review of

    Methods: A systematic review of available literature was completed following PRISMA guidelines using the search themes "cyberbullying" and "adolescent or children"; the time frame was from January 1st, 2015 to December 31st, 2019. Eight academic databases pertaining to public health, and communication and psychology were consulted ...

  4. Systematic literature reviews in cyberbullying/cyber harassment: A

    Abstract. A number of systematic literature reviews have been conducted in order to understand cyberbullying phenomenon. Tertiary studies are carried out to provide a holistic view of an area by collating literature at a meta-level. This study appraises systematic literature reviews in cyberbullying to investigate different dimensions, trends ...

  5. Cyberbullying on social networking sites: A literature review and

    In the first stage, literature searches were conducted to identify journal articles that examined SNS bullying. To identify peer-reviewed journal articles on SNS bullying, we began by conducting an abstract search using keywords related to cyberbullying and social networking sites, such as "cyberbullying," "social network," and "SNS. ...

  6. Cyberbullying in higher education: A literature review

    This literature review was created to raise awareness of this continuing trend of cyberbullying among college students with higher education students, administrators, and faculty. ... Cyber bullying: Overview and strategies for school counsellors, guidance officers, and all school personnel.

  7. Cyberbullying in adolescents: a literature review

    Cyberbullying is a universal public health concern that affects adolescents. The growing usage of electronic gadgets and the Internet has been connected to a rise in cyberbullying. The increasing use of the Internet, along with the negative outcomes of cyberbullying on adolescents, has required the study of cyberbullying. In this paper author reviews existing literature on cyberbullying among ...

  8. Cyberbullying: A Systematic Literature Review to Identify the Factors

    Therefore, this study aims to conduct a systematic review of literature targeting university students specifically to understand the underlying causes that give rise to the problem of cyberbullying within the university environment so that the issue could be adequately addressed. In this attempt, this study observed 32 studies out of a total of ...

  9. Cyberbullying in adolescents: a literature review

    In this paper author reviews existing literature on cyberbullying among adolescents. The concept of cyberbullying is explained, including definitions, types of cyberbullying, characteristics or features of victims and cyberbullies, risk factors or causes underlying cyberbullying, and the harmful consequences of cyberbullying to adolescents.

  10. Cyberbullying and its influence on academic, social, and emotional

    The data were collected using the Revised Cyber Bullying Survey, which evaluates the frequency and media used to perpetrate cyberbullying, and the College Adjustment Scales, which evaluate three aspects of development in college students. ... a literature review. Comput. Hum. Behav. 2017; 69:268-274. [Google Scholar] Webber M.A., Ovedovitz A ...

  11. A systematic review and content analysis of bullying and cyber-bullying

    A systematic search was conducted for all bullying and cyber-bullying measurement strategies published between 1985 and 2012. First, key search terms were drawn from a review of the literature and included such terms as bully*, violen*, aggress*, victim*, harass*, exclude*, bystand*, measure*, tool*, and survey*.

  12. Cyberbullying detection and machine learning: a systematic literature

    The rise in research work focusing on detection of cyberbullying incidents on social media platforms particularly reflect how dire cyberbullying consequences are, regardless of age, gender or location. This paper examines scholarly publications (i.e., 2011-2022) on cyberbullying detection using machine learning through a systematic literature review approach. Specifically, articles were ...

  13. Review Cyberbullying in higher education: A literature review

    This literature review was created to raise awareness of this continuing trend of cyberbullying among college students with higher education students, administrators, and faculty. Ultimately, the literature presented has led the writers of this review to examine areas for future research as discussed below. This review defined cyberbullying as any.

  14. Cyberbullying : a literature review

    Cyberbullying : a literature review . Abstract . Technology is becoming more prevalent each day, with that a new form of bullying is happening. The new form is cyberbullying. It is form of bullying that takes place over cell phones, email, websites, and chat rooms. While cyberbullying is a form of bullying, there are differences between ...

  15. Associations between social media and cyberbullying: a review of the

    There was a steady increase in the number of cyberbullying studies published during the 3-year review period: 1 each in 2013 and 2014 (4.5%, respectively), 7 in 2014 (31.8%), and 11 in 2015 (50%). Appendix A summarizes the 22 papers that were reviewed. There was a general consensus that cyberbullying only affects youths.

  16. Cyberbullying in elementary and middle school students: A systematic review

    Abstract. The goal of the present study was to extend the scope of previous reviews on cyberbullying to focus on elementary and middle school students, ages when research indicates that children begin to use mobile phones and social media. From 2016 to 2020, a total of 43 articles were included in the final selection, and purpose/s, sample ...

  17. Effects of Cyber Bullying on Teenagers: a Short Review of Literature

    Cyber-bullying victimization has recently received a fair amount of attention due to some heart-breaking events orbiting in schools and even at homes. Although research has already demonstrated a number of serious consequences of cyber-victimization, many questions remain unanswered concerning the impact of cyber-bullying. ... Review of Literature

  18. Bullying in a networked era: Research views on scope and frequency of

    Cyber bullying had a similar sized effect on suicidal behavior, substance use, violent behavior, and unsafe sexual behavior as physical bullying. ... A Literature Review," examines and consolidates the findings of other studies published between 2008 and 2012. The data focus on American youth in middle and high school. The authors ...

  19. Cyberbullying and LGBTQ Youth: A Systematic Literature Review and

    This literature review revealed a correlation between suicidal ideation and attempt and cyberbullying alone and a combination of cyberbullying with traditional bullying (Cénat et al. 2015; Cooper and Blumenfeld 2012; Duong and Bradshaw 2014; Schneider et al. 2012; Sinclair et al. 2012), with many participants reporting the need for medical ...