Factors Predicting Depressive Symptoms of Cyberbullying Victims in Middle-School Students

Authors

  • Anchalee Jeerat Faculty of Nursing, Thammasat University
  • Nutchanart Bunthumporn Faculty of Nursing, Thammasat University
  • Sararud Vuthiarpa Faculty of Nursing, Thammasat University

Keywords:

depressive symptoms, cyberbullying victims, middle-school students

Abstract

This predictive correlational study aimed to examine depressive symptoms, factors influencing, and factors predicting depressive symptoms of cyberbullying victims in middle-school students. The sample consisted of 300 participants. The instruments used for collecting the data were 1) demographic characteristics questionnaires; 2) the Center for Epidemiologic Studies- Depression Scale (CES-D) 3) the self -esteem scale; 4) coping strategies scale; 5) learning style questionnaires; 6) parenting style questionnaires; 7) family relationships questionnaires; 8) friendship intimacy questionnaires; 9) social support questionnaires and 10) social media addiction questionnaires. The reliability test of questionnaires 2- 10 were 0.90, 0.83, 0.84, 0.95, 0.85, 0.83, 0.83, 0.93, and 0.92, respectively. Data were analyzed using descriptive statistics, Spearman’s rank correlation coefficient, Pearson’s product correlation coefficient, and stepwise multiple regression analysis.

Study found that the mean score of depressive symptoms was 20.61. (M = 20.61, SD = 9.89).The result revealed the depressive symptoms were at a mild to moderate level. By examining the stepwise multiple regression for predicting depressive symptoms, the six factors that could predict depressive symptoms included emotion-focused coping (ß=-0.332, p < .001), neglectful parenting style (ß = 0.290, p < .001), more than 1 type of cyberbullying (ß = 0.243, p < .001), female (ß = 0.174, p < .001), problem-focused coping (ß = 0.165, p < .05) and perceived characteristics (introverted personality and sentimental) (ß = 0.127, p < .05). All six variables were able to predict depressive symptoms at 34.7%

The findings of this study showed that cyberbullying victims in middle-school students are a high risk group for depressive symptoms. Academic Administrator and Mental health professionals aimed at enhancing coping strategies to this population group.

References

National statistical office. The 2021 household survey on the use of information and communication technology. Bangkok: NSO Data Catalog; 2022 (in Thai)

Srivichai C. Self-Care of Addiction Social Media adolescent. Journal of The Royal Thai Army Nurses. 2018; 19(2): 31-6. (in Thai)

Slonje, Smith. The nature of cyberbullying, and strategies for prevention. Computers in Human Behavior. 2013; 29(1): 26-32.

Kowalski, Limber. Psychological, Physical, and Academic Correlates of Cyberbullying and Traditional Bullying. Journal of Adolescent Health. 2013; 53(1): 13-20.

Underwood, M. K., Ehrenreich, S. E. The power and the pain of adolescents’ digital communication: Cyber victimization and the perils of lurking. American Psychologist. 2017; 72(2): 144-58

Charoenwanit S. Cyber Bullying: Impacts and Preventions in Adolescents. Thai Science and Technology Journal.2017; 25(4): 639-45.

Thutisud B. When being bullied. 1sted. Bangkok: Good printing and packaging group; 2019 (in Thai)

Calvete, E., Orue, I., Gamez-Guadix, M. Cyberbullying victimization and depression in adolescents: the mediating role of body image and cognitive schemas in a one-year prospective study. European Journal of Criminal Policy and Research. 2017; 22: 271–84.

Robin, M.K., Susan, P.L.Psychological, physical, and academic correlates of cyberbullying and traditional bullying. Adolescent. Health. 2013.

Machmutow, K., Perren ,S., Sticca, F., Alsaker, F. Peer victimisation and depressive symptoms Can specific coping strategies buffer the negative impact of cybervictimisation? Emotional and Behavioural Difficulties. 2012; 17(3): 403-20.

Liu, C., Liu, Z., Yuan, G. The longitudinal influence of cyberbullying victimization on depression and posttraumatic stress symptoms: The mediation role of rumination Journal of Health Psychology.2020; 34: 206-10.

Pliankerd P.Depressive disorder: Nurse’s role in nursing care. Journal of The Royal Thai Army Nurses. 2014; 15(1): 18-21. (in Thai)

Bronfenbrenner, U., Morris, P. A. The bioecological model of human development. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology, Theoretical models of human development. 6th ed. New York: Wiley; 2006.

Beck,A.T. Depression: Clinical, experimental, and theoretical aspects: University of Pennsylvania; 1967

Anuroj K, Pityaratstian N. Cyber-Aggression Perpetration and Victimization Scale Validity and Reliability of Cyber-Aggression Perpetration and Victimization Scale. Journal of the Psychiatric Association of Thailand. 2019; 64(1), 45-60. (in Thai)

Trangkasombat, U., Larbboonsarp, V., Havanond, P. CES-D as a screen for depression in adolescents. Journal of Psychiatric Association of Thailand. 1997; 17(3): 412-29. (in Thai)

Wongpakaran T, Wongpakaran N. Confirmatory factor analysis of Rosenberg self esteem scale : a study of Thai student sample. Journal of the Psychiatric Association of Thailand. 2011; 56(1): 59-70. (in Thai)

Prateepteranun W. The effect of empower program on coping ability of suicidal attempters. Journal of the psychiatric nursing and mental health. 2015; 29(2): 103-15. (in Thai)

Petchboonmee P, The Forecastion of David Kolb’s Experiential Learning Style Using the Classification Rules with Decision Tree Technique. Journal of Science and Technology. 2013; 21(6): 547-57 (in Thai)

Kititussaranee S. The Relationship between Parenting Styles and Depression of the Fourth Level Students. Rama Nurs J.2009, 15(1): 36-47 (in Thai)

Jitaree B. The Factors Influencing Depression Amongst the Elderly at a Community in Nakhon Pathom Province. (thesis). Nakhon Pathom, Christian University; 2012. (in Thai)

Nateetan M. The Factors Influencing Depression in adolescents in Chiang Mai Province. (thesis). Chiang Mai, Chiang Mai University; 2003. (in Thai)

Wichisiri P. Wisdom, social support and psychological well-being of elderly in the elderly club at WatSarod Rat Burana District, Bangkok. Journal of Social Sciences and Humanities. 2012; 38(2): 139-51. (in Thai)

Pernsungnern P, Pornnoppadol C, Sitdhiraksa N, Buntub D. Social media addiction: prevalence and association with depression among 7th-12th Grade Students in Bangkok. Graduate Research Conference 2014; 2014 Mar 28; Khon Kaen, Thailand. Khon Kaen: Khon Kaen University; 2014.

Laisuwannachart P, Suteeprasert T, Bunsiriluck S. (2565). Factors predicting cyberbullying perpetration and victimization among students in central Thailand. Journal of Mental Health of Thailand. 2022; 30(2), 100-13. (in Thai)

Maurya, C., Muhammad, T., Dhillon, P., & Maurya, P. The effects of cyberbullying victimization on depression and suicidal ideation among adolescents and young adults: a three year cohort study from India. Bio Bed Central Psychiatry. 2022; 22(599), 2-14.

Sawasdisutha P. The coping styles among high school students in Bangkok and the relationship between coping mechanisms and depression. Journal of the Psychiatric Association of Thailand. 2016; 61(1), 4152. (in Thai)

Romero-Acosta, K., Gómez-de-Regil, L., Lowe, G. A., Garth, L.,Gibson. R.C. Parenting Styles, Anxiety and Depressive Symptoms in Child/Adolescent.International Journal of Psychological Research.2021; 14(1), 12-32.

Downloads

Published

10-12-2023

How to Cite

1.
Jeerat A, Bunthumporn N, Vuthiarpa S. Factors Predicting Depressive Symptoms of Cyberbullying Victims in Middle-School Students. J Royal Thai Army Nurses [Internet]. 2023 Dec. 10 [cited 2024 Apr. 27];24(3):144-52. Available from: https://he01.tci-thaijo.org/index.php/JRTAN/article/view/260670

Issue

Section

Research Articles