Perspectives on late adolescent cyberbullying victimization: Gender differences in behavioural health effects

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Aungkana Jattamart
Achaporn Kwangsawad


Even though information technology has brought great benefits to its users, its growing popularity has also increased the risk of cyberbullying. This research fills an empirical gap by exploring both the perceptions of late adolescent victims and gender differences in the behavioral health effects of online bullying. It presents a perspective on changing health behavior that aligns with the conceptual framework of social cognitive theory (SCT). The sample comprised 578 undergraduate students (286 males and 292 females) from three university campuses in Thailand that were selected by using a multistage random sampling technique. The causal relationships between factors in the model were analyzed using partial least squares structural equation modeling (PLS‐SEM). The results indicated that social media addiction and self-disclosures on social media are key environmental factors, for both males and females, leading to victimization by cyberbullying. In particular, late adolescents who compare themselves with others (i.e., social comparison) are more severely affected by cyberbullying. In addition, these findings reveal a new relationship between victimization and sleep disorders: For both men and women, social comparison mediates the relationship between cyberbullying victimization and sleep disorders. This study's results clarify how health behaviors are affected by the environment and the personal behavior of victims of online bullying.


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Aizenkot, D. (2020). Social networking and online self-disclosure as predictors of cyberbullying victimization among children and youth. Children and Youth Services Review 119: 105695.

Appel, H., Gerlach, A. L. and Crusius, J. (2016). The interplay between Facebook use, social comparison, envy, and depression. Current opinion in psychology 9: 44–49.

Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, N.J: Prentice-Hall.

Cannarella, J. and Spechler, J. A. (2014). Epidemiological modeling of online social network dynamics. [Online URL:] accessed on June 15, 2021.

Cao, X., Khan, A. N., Ali, A. and Khan, N. A. (2019). Consequences of cyberbullying and social overload while using SNSs: A study of users’ discontinuous usage behavior in SNSs. Information Systems Frontiers 22(6): 1343–1356.

Chang, F. C., Lee, C. M., Chiu, C. H., Hsi, W. Y., Huang, T. F. and Pan, Y. C. (2013). Relationships among cyberbullying, school bullying, and mental health in Taiwanese adolescents. Journal of School Health 83(6): 454–462.

Cho, M.-K., Kim, M. and Shin, G. (2017). Effects of cyberbullying experience and cyberbullying tendency on school violence in early adolescence. The Open Nursing Journal 11: 98–107.

Dash, G. and Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change 173: 121092.

Edwards, A., Edwards, L. and Martin, A. (2020). Cyberbullying Perceptions and Experiences in Diverse Youth. In I. Corradini, E. Nardelli and T. Ahram. (Eds.), Advances in Human Factors in Cybersecurity (AHFE 2020): Advances in Intelligent Systems and Computing, Vol 1219, pp. 9–16. Cham: Springer.

Fang, J., Wang, X., Wen, Z. and Huang, J. (2020). Cybervictimization and loneliness among Chinese college students: A moderated mediation model of rumination and online social support. Children and Youth Services Review 115: 105085.

Fornell, C. and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18(1): 39–50.

Gámez-Guadix, M., Villa-George, F. and Calvete, E. (2014). Psychometric properties of the Cyberbullying Questionnaire (CBQ) among Mexican adolescents. Violence and Victims 29(2): 232–247.

Giordano, A. L., Prosek, E. A. and Watson, J. C. (2021). Understanding adolescent cyberbullies: Exploring social media addiction and psychological factors. Journal of Child and Adolescent Counseling 7(1): 42–55.

Gumpel, T. P. and Sutherland, K. S. (2010). The relation between emotional and behavioral disorders and school-based violence. Aggression and Violent Behavior 15(5): 349–356.

Hair, J. F., Black, W. C., Babin, B. J. and Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective. 7th ed. New Jersey: Pearson Prentice Hall Publishing.

Hair, J. F., Risher, J. J., Sarstedt, M. and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review 31(1): 2–24.

Hair Jr, J. F., Hult, G. T. M., Ringle, C. and Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). California: Sage publications.

Henseler, J., Hubona, G. and Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems 116(1): 2–20.

Hinduja, S. and Patchin, J. W. (2010). Bullying, cyberbullying, and suicide. Archives of Suicide Research 14(3): 206–221.

Jattamart, A. and Kwangsawad, A. (2020). Prediction of intention to change sleep behavior among undergraduates: Social media and perception of quality of sleep. International Journal of Applied 13(1): 49–57.

Jattamart, A. and Kwangsawad, A. (2021). What awareness variables are associated with motivation for changing risky behaviors to prevent recurring victims of cyberbullying? Heliyon 7(10): e08121.

Jattamart, A. and Leelasantitham, A. (2019). The influence of social media lifestyle interventions on health behaviour: A study on patients with major depressive disorders and family caregivers. The Open Public Health Journal 12: 387–405.

Jattamart, A. and Leelasantitham, A. (2020). Perspectives to social media usage of depressed patients and caregivers affecting to change the health behavior of patients in terms of information and perceived privacy risks. Heliyon 6(6): e04244.

Keawsomnuk, P. (2021). A structural equation model of factors relating to smart cities that affect the management of the world heritage site. Humanities, Arts and Social Sciences Studies 21(1): 35–42.

Kemp, S. (2019). Digital 2019: Global Internet Use Accelerates. [Online URL:] accessed on June 20, 2021.

Kim, S., Kimber, M., Boyle, M. H. and Georgiades, K. (2019). Sex differences in the association between cyberbullying victimization and mental health, substance use, and suicidal ideation in adolescents. The Canadian Journal of Psychiatry 64(2): 126–135.

Korda, H. and Itani, Z. (2013). Harnessing social media for health promotion and behavior change. Health Promotion Practice 14(1): 15–23.

Kowalski, R. M., Giumetti, G. W., Schroeder, A. N. and Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin 140(4): 1073–1137.

Kowalski, R. M. and Limber, S. P. (2007). Electronic bullying among middle school students. Journal of Adolescent Health 41(6): S22–S30.

Liu, C., Liu, Z. and Yuan, G. (2020). The longitudinal influence of cyberbullying victimization on depression and posttraumatic stress symptoms: The mediation role of rumination. Archives of Psychiatric Nursing 34(4): 206–210.

Livazović, G. and Ham, E. (2019). Cyberbullying and emotional distress in adolescents: The importance of family, peers and school. Heliyon 5(6): e01992.

Longobardi, C., Settanni, M., Fabris, M. and Marengo, D. (2020). Follow or be followed: Exploring the links between Instagram popularity, social media addiction, cyber victimization, and subjective happiness in Italian adolescents. Children and Youth Services Review 113: 104955.

Makri-Botsari, E. and Karagianni, G. (2014). Cyberbullying in Greek adolescents: The role of parents. Procedia -Social and Behavioral Sciences 116: 3241–3253.

Mishna, F., McInroy, L. B., Lacombe-Duncan, A., Bhole, P., Van Wert, M., Schwan, K., Birze, A., Daciuk, J., Beran, T., Craig, W., Pepler, D. J., Wiener, J., Khoury-Kassabri, M. and Johnston, D. (2016). Prevalence, motivations, and social, mental health and health consequences of cyberbullying among school-aged children and youth: Protocol of a longitudinal and multi-perspective mixed method study. JMIR Research Protocols 5(2): e83.

Nunnally, J. C. (1994). Psychometric Theory 3E. New York: Tata McGraw-Hill Education.

Oksanen, A., Oksa, R., Savela, N., Kaakinen, M. and Ellonen, N. (2020). Cyberbullying victimization at work: Social media identity bubble approach. Computers in Human Behavior 109: 106363.

Owens, H., Christian, B. and Polivka, B. (2017). Sleep behaviors in traditional‐age college students: A state of the science review with implications for practice. Journal of the American Association of Nurse Practitioners 29(11): 695–703.

Parris, L., Varjas, K., Meyers, J. and Cutts, H. (2012). High school students’ perceptions of coping with cyberbullying. Youth & Society 44(2): 284–306.

Peláez-Fernández, M. A., Chamizo-Nieto, M. T., Rey, L. and Extremera, N. (2021). How do cyber victimization and low core self-evaluations interrelate in predicting adolescent problematic technology use? International Journal of Environmental Research and Public Health 18(6): 3114.

Peluchette, J. V., Karl, K., Wood, C. and Williams, J. (2015). Cyberbullying victimization: Do victims’ personality and risky social network behaviors contribute to the problem? Computers in Human Behavior 52: 424–435.

Rainie, L., Smith, A. and Duggan, M. (2013). Coming and Going on Facebook. Washington, D.C.: Pew Research Center’s Internet and American Life Project.

Ringle, C. M., Wende, S. and Becker, J. M. (2015). SmartPLS 3. SmartPLS GmbH, Boenningstedt. [Online URL:] accessed on June 20, 2021.

Şahin, M. (2012). The relationship between the cyberbullying/cybervictmization and loneliness among adolescents. Children and Youth Services Review 34(4): 834–837.

Santos, D., Mateos-Pérez, E., Cantero, M. and Gámez-Guadix, M. (2020). Cyberbullying in adolescents: Resilience as a protective factor of mental health outcomes. Cyberpsychology, Behavior, and Social Networking 24(6): 414–420.

Sarstedt, M. and Cheah, J.-H. (2019). Partial least squares structural equation modeling using SmartPLS: A software review. Journal of Marketing Analytics 7: 196–202.

Sirola, A., Kaakinen, M., Savolainen, I. and Oksanen, A. (2019). Loneliness and online gambling-community participation of young social media users. Computers in Human Behavior 95: 136–145.

Sladek, M. R., Doane, L. D. and Breitenstein, R. S. (2020). Daily rumination about stress, sleep, and diurnal cortisol activity. Cognition and Emotion 34(2): 188–200.

Smith, P. K., López-Castro, L., Robinson, S. and Görzig, A. (2019). Consistency of gender differences in bullying in cross-cultural surveys. Aggression and Violent Behavior 45: 33–40.

Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M. and Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis 48(1): 159–205.

Thompson, S. H. and Lougheed, E. (2012). Frazzled by Facebook? An exploratory study of gender differences in social network communication among undergraduate men and women. College Student Journal 46(1): 88–98.

Tsitsika, A., Janikian, M., Wójcik, S., Makaruk, K., Tzavela, E., Tzavara, C., Greydanus, D., Merrick, J. and Richardson, C. (2015). Cyberbullying victimization prevalence and associations with internalizing and externalizing problems among adolescents in six European countries. Computers in Human Behavior 51: 1–7.

Vhaduri, S. and Poellabauer, C. (2018). Impact of different pre-sleep phone use patterns on sleep quality. Paper presented at 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN). Las Vegas, USA. March 4–7. [Online URL:] accessed on June 15, 2021.

Watts, L. K., Wagner, J., Velasquez, B. and Behrens, P. I. (2017). Cyberbullying in higher education: A literature review. Computers in Human Behavior 69: 268–274.

Wetzels, M., Odekerken-Schröder, G. and Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly 33(1): 177–195.

Willard, N. E. (2007). Cyberbullying and Cyberthreats: Responding to the Challenge of Online Social Aggression, Threats, and Distress. Illinois: Research Press.

Won, J. and Seo, D. (2017). Relationship Between Self-disclosure and Cyberbullying on SNSs. In M. Themistocleous and V. Morabito (Eds.), Information Systems (EMCIS 2017): Lecture Notes in Business Information Processing, Vol 299, pp. 154–172. Cham: Springer.

Zhong, B., Huang, Y. and Liu, Q. (2021). Mental health toll from the coronavirus: Social media usage reveals Wuhan residents’ depression and secondary trauma in the COVID-19 outbreak. Computers in Human Behavior 114: 106524.