Antecedents of cyber bullying behaviors of high school students: A case study of Facebook

Abstract

The objectives of this study were (1) to examine cyber bullying behaviors of high school students (2) to examine factors associated with cyber bullying behaviors of high school students and (3) to provide suggestions and recommendations for solving the problem. The samples of this study were 242 high school students of a school in the eastern region of Thailand. The questionnaire was employed as a research tool to collect data. The data then were analyzed using stepwise multiple regression analysis technique. The findings indicated that jealousy, media violence, and depression had a positive relationship with cyber bullying behaviors. However, domestic violence and authoritarian parenting style had no relationship with cyber bullying behaviors. Several theoretical and practical suggestions and recommendations of the findings that may extend our knowledge on cyber bullying are noted

Full text

Conference of the International Journal of Arts & Sciences,
CD-ROM. ISSN: 1943-6114 :: 10(02):295–304 (2017)
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ANTECEDENTS OF CYBER BULLYING BEHAVIORS OF HIGH
SCHOOL STUDENTS: A CASE STUDY OF FACEBOOK
Rattiya Deenamjued and Waiphot Kulachai
Burapha University, Thailand
The objectives of this study were (1) to examine cyber bullying behaviors of high school students (2) to
examine factors associated with cyber bullying behaviors of high school students and (3) to provide
suggestions and recommendations for solving the problem. The samples of this study were 242 high
school students of a school in the eastern region of Thailand. The questionnaire was employed as a
research tool to collect data. The data then were analyzed using stepwise multiple regression analysis
technique. The findings indicated that jealousy, media violence, and depression had a positive
relationship with cyber bullying behaviors. However, domestic violence and authoritarian parenting
style had no relationship with cyber bullying behaviors. Several theoretical and practical suggestions
and recommendations of the findings that may extend our knowledge on cyber bullying are noted
Keywords: Cyber bullying, Facebook, Media violence, Jealousy, Depression.
Introduction
The internet has increasingly played an important role in daily life of people and becomes as a part of
people life. It facilitates many things including education, work, communication, entertainment, and
recreation. Hence, it has grown dramatically, especially the popularity of Facebook. There are about 400
million new users register on Facebook daily. Hence, it becomes the biggest online society in the world
(Mungkornpis, 2010 as cited in Korpornprasert, 2014). The National Statistics Office (2015) reported that
the social media users, especially Facebook and Twitter, were about 22 million. In addition, the active
users of the age cohort of 15-19 years old were about 4 million.
Continuous development of communication technology results in popularity of mobile phone, and
the internet. The internet has become a new channel of communication infiltrating into every dimension
of the society (Donner, 2010). Smart phone nowadays has various features such as camera, video, and
online application which enhance people to access into online social network easily (Saipradit, 2006).
These mobile phone attributes have met the needs of teenagers who employ the gadget to express their
identities. It has been used to develop a sexual relationship among teenagers. Furthermore, the mobile
phone and social media have been increasingly used to bully others (Boonmongkol et al., 2012 as cited in
Samor, 2013).
Traditionally, bullying among teenagers is associated with physiological attacks such as punching,
slapping, and general bullying (Sriwattanaphong & Thaninphong, 2015). Such bullying leads to various
impacts. Bullying may cause the victims to have depression, anxiety, loss of self-confidence, and
committing suicide. On the other hand, individual who bullies others are at risk to cause violence in their
families when they grow up (Sakarinkhul & Wacharasindhu, 2014). Cyber bullying has increased
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dramatically since it is easy to bully others through social media. Facebook has been employed as a new
tool to bully others among teenagers since it’s hard for their parents to monitor (Sriwattanaphong &
Thaninphong, 2015). We, therefore, are interested in finding antecedents of cyber bullying among
teenagers on Facebook and would like to provide recommendations for related people in dealing with this
issue.
Literature Review
Cyber Bullying Behaviors
Bullying referred to the aggressive behaviors of a powerful individual who performs anti-social behaviors
intending to harm the less powerful individual (Olweus, 2003). Sticca and Perren (2013) added that cyber
bullying can be defined as an aggressive behavior of an individual or group against a defenseless
individual through certain electronic forms such as mobile phone and the internet. Text message, emails,
and posting embarrassing things on social media are general examples of cyber bullying. According to
Sriwattanaphong and Thaninphong (2015), defamation, rude words, sending embarrassed message on
internet, and text message is also related to bullying behaviors on cyber. They also claimed that such
behavior must be repeatedly and consistently performed by an individual in order to harm the less
powerful individual. Cyber bullying can be categorized into 5 types; gossip, defamation, claiming falsely,
reveal personal secret information, and deletion or block others in the group (Wiiard, 2006 as cited in
Tutkuea, 2014). However, Li (2007) categorized cyber bullying into 7 types which are flaming, online
harassment, cyber stalking, denigration, masquerading, trickery and outing, and exclusion.
Thongraweewong (2015) said that this behavior might affect an individual’s privacy and may result in
committing suicide of the victim. Leung et al. (2017) found the negative relationship between life
satisfaction and cyber bullying of both victimization and perpetration. Some victims of cyber bullying had
experienced anger, poor academic performance, and psychological problems (Glasner, 2010). Some
previous studies found that cyber bullying led to crying, feeling embarrassed, absent from school,
depression, insomnia, and committing suicide (Akbulut & Cuhadar, 2011; Schenk & Fremouw,
2012).Furthermore, the study by Selkie, Kota, Chan, and Moreno (2015) found that students engaged in
cyber bullying led to higher rates of depression and alcohol use for both bullies and victims.
Family Violence and Cyber Bullying Behaviors
Kumchoo (2012) defined family violence as an act of a family member intending to harm other members
physically, and mentally. It can be divided into 5 types; physical abuse, emotional abuse, sexual abuse,
neglect, and deceit. She proposed that family violence led to physical and mental pain. It also affected the
relationship between family members, separation, and divorce. In addition, children who experienced
family violence could absorb and familiar with violence and imitate such behavior when they grow up.
However, Kumar (2012) categorized the family violence into 3 types; physical abuse, sexual abuse, and
psychological and emotional abuse. Physical abuse is associated with biting, hitting, kicking, slapping,
stabbing, gun shot, using belt or stick, using of acid, pulling, yelling, and dragging. Sexual violence
involves forced sexual intercourse, mutilation of genitalia, painful sex, forced oral sex, anal mutilation,
digital penetration, and forced nakedness. Psychological and emotional abuse involves phobia, guilt
feeling, insecurity, poor impulse control, nightmares, impaired sleep, humiliation, shame, isolation of
victim, and forced weakness. A study by Alkhalayleh and Newlyn (2015) found linkage between family
violence and school bullying. However, school bullying is a traditional form of bullying that may develop
to be cyber bullying due to an advancement of communication technology like smart phone and the
internet. The studies by Laeheem, (2011); Ishida (2010) and Kitsukjit (2016) also confirmed the

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relationship between family violence and cyber bullying behaviors. Hence, we proposed that there might
be linkage between family violence and cyber bullying behaviors;
H1: Family violence has a positive influence on cyber bullying behaviors.
Authoritarian Parenting Style and Cyber Bullying Behaviors
Parenting style means the ways employed by parents to raise their children. Baumrind (1991) divided it
into four categories; authoritative, authoritarian, permissive, and uninvolved parenting style. According to
authoritative parenting style, the parents raise their children up on the reasoning basis. Children were
given freedom to do or to act independently. The parents are warm and treat their children with care,
kindness, and respect. They employ rules to control and monitor their children’s behaviors. However,
controlling and monitoring their children are based on reasoning. Authoritarian parents are persons who
attempt to raise their children without considering their feelings. The children have to follow the rules set
by their parent without any explanation from them. Parents are very strict and highly dictated. This
parenting style may lead to aggressive behaviors. Permissive parenting style refers to raising children
with love. Parents are not very demanding and allow their children to behave independently. Hence,
permissive parents are more responsive compared to the parents who are authoritarians. Finally,
uninvolved parenting style means that parents are not engaged or involved in their children lives. They
don’t control, monitor, and demand the children. They have little communication with their children.
Sometimes, children are not supported. In extreme case, children may be neglected and rejected by their
parents. Hence, all kinds of parenting styles are very important factors affecting child’s behaviors. Efobi
and Nwokolo (2014) conducted a research on 1,000 senior high school students of 60 public secondary
schools in Nigeria. They found the relationship between parenting style and cyber bullying behaviors.
According to Georgiou (2008) and Punya (2014), authoritarian parenting style was the best predictor of
bullying behavior among children. Hence, we proposed that there might be linkage between authoritarian
parenting style and cyber bullying behaviors;
H2: Authoritarian parenting style has a positive influence on cyber bullying behaviors.
Jealousy and Cyber Bullying Behaviors
Jealousy has been known as a negative emotion arising when a relationship is threatened by an undesired
individual (Harris, 2004). Jealousy can be occurred tween friends. It is common that jealousy starts when
individuals are at the early adolescence. Then, it will decline very quickly in accordance with adolescence
progress (Selman, 1980). Adolescents whose mothers psychologically control on them tend to have
jealousy (Kim, Parker, & Marciano, 2017). According to the study of Kaewpoonpakorn (1998), jealousy
resulted in aggressive behavior among early adolescents.
Hence, we proposed that there might be linkage between jealousy and cyber bullying behaviors;
H4: Jealousy has a positive influence on cyber bullying behaviors.
Media Violence and Cyber Bullying Behaviors
Anderson and Bushman (2001) defined violence on media as any media that depict intentional attempts
by an individual audience to harm others. However, media violence in this study refers to violence that
students perceive from various channels of media such as social network, television program, and printed
materials. The violent video game was a classic example that had a correlation with aggression (Anderson
& Dill, 2000). According to Steward and Follina (2006), exposure to aggressive and violent material on
media would lead to aggressive thoughts, feelings, and behaviors.Yaowabutr et al. (2014); and
Sriwattanaphong and Thaninphong (2015) found that violence and media resulted in bullying behaviors
through cyber world. Hence, we proposed that there might be linkage between media violence and cyber
bullying behaviors;
H4: Media violence has a positive influence on cyber bullying behaviors.

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Depression and Cyber Bullying Behaviors
According to WHO (2012), depression referred to a common mental disorder such as depressed mood,
loss of interest or pleasure, decreased energy, feelings of guilt or low self-worth, disturbed sleep or
appetite, and poor concentration. It usually comes with anxiety.
Depression leads to various consequences such as disease burden, poor growth in young children
(Rahman et al, 2008). Ferguson et al. (2002) found that depression resulted in teen's socialization, family
relations, and performance at school. Depression led to increased hospitalization, and social role
outcomes (Aalto-Setala et al., 2002). Merry et al. (2011) added that depression could affect academic
achievement, social dysfunction, teenage pregnancy and substance abuse of depressed early adulthood.
Averdijk et al. (2011) and Farrington et al. (2011) found that bullying significantly predicted later anxiety
and depression of the victims. However, Pitanupong and Anantapong (2014) claimed that depression
could lead to aggressive behavior such as cyber bullying. Hence, we proposed that there might be linkage
between depression and cyber bullying behaviors;
H5: Depression has a positive influence on cyber bullying behaviors.
Method
Participants
The participants of this study were 242 high school students of a public school in Rayong, Thailand. The
majority was female accounting for 56.60%. About 51.70 percent of participants were in Grade 12.
Approximately 84% of the respondents reported that they had been bullied by their friends on Facebook.
About 88% of them reported that they used to bully their high school friends through Facebook. They also
reported that they were bullied on Facebook by an anonymous (39.70%). About 17% of them reported
they bullied their friends through Facebook as an anonymous.
Measures
For all measures in the study, except demographic questions, respondents indicated their level of
agreement with the items using a 5-point’s Likert response scale anchored by (1) strongly disagree and (5)
strongly agree. Each measure is illustrated as followings;
Family violence was measured using the ten items of family violence scale (FVS) developed by the
authors. This measurement revealed scores showing an alpha reliability of .844. Example items include “I
used to be bullied by my family members” “I used to be intimidated by my family members” and “I
would like to report violence in my family to someone.”
Authoritarian parenting style was measured using the ten items of authoritarian parenting style scale
(APSS) developed by the authors. This measurement revealed scores showing an alpha reliability of .942.
Example items include “I feel like I am lonely” “I will be severely punished by my parents if I do
something wrong” and “My parents always force me to follow rules set by them strictly.”
Jealousy was measured using the nine items of jealousy scale (JS) developed by the authors. This
measurement revealed scores showing an alpha reliability of .939. Example items include “I am not
happy to see others’ accomplishment” “I would like others to pay attention on me” and “I feel anxiously,
uncomfortably, and unhappy to hear a story of one’s success.”
Media violence was measured using the eight items of media violence scale (MVS) developed by the
authors. This measurement revealed scores showing an alpha reliability of .821. Example items include “I
behave like an actor/actress on the TV series” “I play a game with violent content” and “When I am
watching the series, I always act aggressively as appeared on TV.”
Depression was measured using the six items of depression scale (DS) developed by the authors.
This measurement revealed scores showing an alpha reliability of .791. Example items include “I feel
depressed” “I don’t want to talk with anyone” and “My life is full of failures.”

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Cyber bullying behaviors were measured using the ten items of cyber bullying behavior scale
(CBBS) developed by the authors. This measurement revealed scores showing an alpha reliability of .870.
Example items include “I used to ridicule others on Facebook” “I used to post something on Facebook in
order to make them shame” and “I used to make a rumor about someone on Facebook.”
Analysis
Stepwise regression analysis was employed to analyze the gathered data. Hair et al. (2010) recommended
that this statistical technique is suitable for getting a regression model which has the fewest number of
statistically significant independent variables. It also provides maximum predictive accuracy.
Results
According to stepwise multiple regression technique, independent variables are added into the equation
model one by one at each stage. This technique also requires a correlation between each independent
variables and dependent variables as illustrated in Table 1. The partial correlations between each variable
ranges from a high of .610 to a low of .310. Since depression (BL) was highly correlated with cyber
bullying behaviors (CB), it should be the first variable entered into the model, followed by media violence
(ME), and jealousy (EN) in that order. However, authoritarian parenting style (NU), and family violence
(FV) were excluded from the model. The results of stepwise regression analysis are illustrated in Table 2.
Table 1. Correlations matrix
Variables FV NU EN ME BL CB
FV -
NU .610** -
EN .442** .509** -
ME .323** .373** .464** -
BL .443** .429** .480** .380** -
CB .336** .310** .403** .388** .439** -
**Correlation is significant at the 0.05 level (2-tailed)
Table 2. Results of stepwise multiple regression analysis
Model Unstandardized Coefficients Standardized
Coefficients t Sig.
B Std. error Beta
Constant 1.129 0.173 6.513 .000
BL 0.253 0.059 0.278 4.316 .000
ME 0.218 0.070 0.200 3.130 .002
EN 0.185 0.070 0.177 2.633 .009
R = 0.521, R2 = 0.271, Adjusted R2 = 0.268, Std.Error = 0.617, F = 6.934, Sig. = 0.009

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Results from Table 2 show that depression (BL), media violence (ME), and jealousy (EN) (adjusted
R2 = 0.268, F = 6.934, p- value < 0.05) have contributed toward the R2 value. Based on the R2 value of
0.271, these facets of factors could explain 27.1% in the variation of cyber bullying behaviors (CB). From
Table 2, the predictive equation would be written;
CB = 1.129 + 0.253BL + 0.218ME + 0.185EN
According to the equation, depression (BL) was the most influential factor, followed by media violence
(ME), and jealousy (EN) in that order. Furthermore, we found that authoritarian parenting style, and
family violence had no relationship with cyber bullying behaviors.
Discussions
This study found that family violence or domestic violence did not have the relationship with cyber
bullying behaviors. This result was contrasted with the results of previous studied (Ishida, 2010;
Laeheem, 2011; Kitsukjit, 2016). There was no relationship between authoritarian parenting style and
cyber bullying behaviors which was inconsistent with previous research (Georgiou, 2008; Sakarinkul and
Watcharasindhu, 2011; Efobi & Nwokolo, 2014). However, the results indicated the positive relationship
between jealousy and cyber bullying behaviors among senior high school students. This was consistent
with the findings of Kaewpoonpakorn (1998) who claimed that young people may have mood disorder
leading to jealousy. The jealousy itself resulted in aggressive behavior like bullying. Violence on media
was an important factor leading to cyber bullying behaviors. This finding supported the results of
previous studies conducted by Yaowabutr et al. (2014); and Sriwattanaphong and Thaninphong (2015).
They explained that media advancement allowed easy access to both audio and visual. Many media
provided contents which illustrate violence so young people can absorb such kind of violence and imitate
behaviors they have experienced from the media. Finally, this study found the relationship between
depression and cyber bullying behaviors. The more likely the students have depression, the more likely
they will perform bullying behaviors through Facebook. This finding was consistent with previous studies
(Pitanupong & Anantapong, 2014).
This study indicated that depression, media violence, and jealousy were important factors leading to
cyber bullying behaviors. Parents, therefore, should monitor and pay attention to their children. Providing
times to have an activity with them at home and showing them support and love. Teachers and school
managements should set up a policy against cyber bullying in school and on social media. Students
should be informed about the drawbacks of using social media. In addition, the students should be
provided information how to appropriately use social media like Facebook or Twitter. Counseling
services on bullying issue should be provided so students can report and release their stress by talking to
someone.
Finally, the government should concern this issue as an important social problem that may lead to
violence in the Thai society.
References
1. Aalto-Setala, T, Marttunen, M., Tuulio-Henriksson, A., Poikolainen, K., & Lonnqvist, J. (2002). Depressive
symptoms in adolescence as predictors of early adulthood depressive disorders and maladjustment. American
Journal of Psychiatry, 159(7), pp.1235-1237.
2. Akbulut, Y., & Cuhadar, C. (2011). Reflection of preservice information technology teachers regarding
cyberbullying. Turkish Online Journal of Qualitative Inquiry, 2(3), pp. 67-76.
3. Alkhalayleh, H., & Newlyn, D. (2015). Domestic violence and school bullying: An examination of the
inextricable link between the two and the use of restorative justice to break the cycle. International Journal of
Business, Economics and Law, 8(4), pp. 147-154.

Rattiya Deenamjued and Waiphot Kulachai
301
4. Anderson, C. A., & Bushman, B. J. (2002b). Media violence and the American public revisited. American
Psychologist, 57, pp. 448–450.
5. Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the
laboratory and in life. Journal of Personality and Social Psychology, 78(4), pp. 772-790.
6. Averdijk, M., Müller, B., Eisner, M., & Ribeaud, D. (2011). Bullying victimization and later anxiety and
depression among pre-adolescents in Switzerland. Journal of Aggression, Conflict and Peace Research, 3(2),
pp. 103-109.
7. Baumrind, D. (1991). The influence of parenting style on adolescents’ competence and substance use. Journal
of Early Adolescence, 11(1), pp. 56-95.
8. Efobi, A., & Nwokolo, C. (2014). Relationship between parenting styles and tendency to bullying behavior
among adolescents. Journal of Education & Human Development 3(1), pp. 507-521.
9. Farrington, D.P., Loeber, R., Stallings, R., & Ttofi, M.M. (2011). Bullying perpetration and victimization as
predictors of delinquency and depression in the Pittsburgh Youth Study. Journal of Aggression, Conflict and
Peace Research, 3(2), pp.74-81.
10. Fergusson, D.M., Woodward, L.J. (2002). Mental health, educational, and social role outcomes of adolescents
with depression. Archives of General Psychiatry, 59(3), pp. 225-231.
11. Georgiou, S. N. (2008). Bullying and victimization at school: The role of mothers. British Journal of
Educational Psychology, 78, pp. 109-125.
12. Glasner, A. T. (2010). On the front lines: Educating teachers about bullying and prevention methods. Journal of
Social Sciences, 6(4), pp. 535-539.
13. Harris, C. (2004). The evolution of jealousy. American Scientist, 92, pp. 62-71.
14. Ishida, S. (2010). A study of violent behaviors among young students. Unpublished master thesis, Graduate
School, Srinakharinwirot University. [in Thai]
15. Kaewpoonpakron, H. (1998). Effect of anger control and social skills training on decreasing aggressive
behaviors of vocational school students. Unpublished master thesis, Graduate School, Chulalongkorn
University. [in Thai]
16. Kim, H., Parker, J.G., & Marciano, A.R.W. (2017). Interplay of self-esteem, emotion regulation, and parenting
in young adolescents' friendship jealousy. Journal of Applied Developmental Psychology, 52, pp. 170-180.
17. Kitsukjit, P. (2017). The factors causing adolescent female bullies in secondary girls schools in the Bangkok
Metropolis according to Ronald L. Akers’ s social learning theory. Academic Services Journal, Prince of
Songkla University, 27(1), pp. 72-80. [in Thai]
18. Korpornprasert, B. (2014). Behaviors in using Facebook of students in Bangkok. Rompreuk Journal, 32(2), pp.
1-24. [in Thai]
19. Kumar, R. (2012). Domestic violence and mental health. Delhi Psychiatry Journal, 15(2), pp. 274-278.
20. Kumchoo, A. (2012). Family violence: Causes, consequences, and assistant guidelines. Thammasat University
Journal, 31(3), pp. 130-143. [in Thai]
21. Laeheem, K. (2011). Cyber bullying behaviors of students. Kasetsart Journal of Social Science, 32(1), pp. 158-
166. [in Thai]
22. Leung, A.N.M., et al. (2017). Cyberbullying in Hong Kong Chinese students: Life satisfaction, and the
moderating role of friendship qualities on cyberbullying victimization and perpetration. Personality and
Individual Differences, http://dx.doi.org/10.1016/j.paid.2017.07.016
23. Li, Q. (2007). Bullying in the new playground: Research into cyberbullying and cyber victimisation. Australian
Journal of Educational Technology, 3(4), 435e454. doi: 10.14742.
24. Merry, S.N., Hetrick, S.E., Cox, G.R., Brudevold-Iversen, T., Bir, J.J., & McDowell, H. (2011). Psychological
and educational interventions for preventing depression in children and adolescents. Cochrane Database
System Review, doi(12):CD003380.
25. The National Statistics Office. (2015). Internet users classified by age and internet using purposes 2015.
Retrieved August 4, 2016 from http://service.nso.go.th/nso/nso_center/ project/table/files/S-ict-hh-
q/2558/000/00_S-ict-hh-q2558_000_010000_02400.xls
26. Olweus, D. (2003). A profile of bullying at school. Educational Leadership, 60, pp. 12–17.

302
Antecedents of Cyber Bullying Behaviors of High School Students: A Case Study ...
27. Rahman A., Patel V., Maselko J., & Kirkwood B. The neglected ‘m’ in MCH programmes–why mental health
of mothers is important for child nutrition. Trop Med International Health, 13: pp. 579-83.
28. Pitanuphong, J., & Anantapong, K. (2014). Mental health of university student facebook users. Journal of the
Psychiatric Accociation of Thailand, 59(3), pp. 257-265. [in Thai]
29. Saipradit, P. (2006). Attitudes of internet users toward media integration. Retrieved October 5, 2015 from
https://tampoo.files.wordpress.com
30. Sakarinkhul, C., & Wacharasindhu, A. (2011). Prevalence of bullying and associated psychosocial factors
among lower secondary school students in Muang, Chiangmai. Journal of Psychiatrist Association Thailand,
59(3), pp. 221-230. [in Thai]
31. Samor, N. (2013). Perceptions of teenagers towards cyber bullying. Unpublished master thesis, Graduate
School, Mahidol University. [in Thai]
32. Schenk, A. M., & Fremouw, W. J. (2012). Prevalence, psychological impact, and coping of cyberbully victims
among college students. Journal of School Violence, 11, pp. 21-37.
33. Selkie, E. M., Kota, R., Chan, Y.-F., & Moreno, M. (2015). Cyberbullying, depression, and problem alcohol
use in female college students: A multisite study. Cyberpsychology, Behavior, and Social Networking, 18(2),
pp. 79-86.
34. Selman, R. L. (1980). The growth of interpersonal understanding. New York, NY: Academic Press.
35. Sriwattanaphong, W., & Thaninphong. (2016). Bullying on electronic media and internet among students in
Chiangmai. NIDA Journal of Communication and Management, 1(1), pp. 128-144. [in Thai]
36. Steward, J., & Follina, F. (2006). Informing policies in forensic settings: a review of research investigating the
effects of exposure to media violence on challenging/offending behaviour", The British Journal of Forensic
Practice, 8(2), pp.31-46.
37. Sticca, F., & Perren, S. (2013). Is cyberbullying worse than traditional bullying? Examining the differential
roles of medium, publicity, and anonymity for the perceived severity of bullying. Journal of Youth and
Adolescence, 42, pp. 739-750.
38. Thongraweewong, K. (2015). Legal measures for protecting persons’ right from cyber-bullying which leads to
suicide: A study of the Cyber-safety Act of Nova Scotia. Proceedings of National Academic Conference,
Bangkok, Thailand. [in Thai]
39. Tutkuea, T. (2014). A development of cyber bullying behavioral indicators for youth in Songkhla Province.
Unpublished master thesis, Graduate School, Prince of Songkla University. [in Thai]
40. World Health Organization, (2012). World suicide prevention day 2012. Retreived October 4, 2016 from
http://www.who.int/mediacentre/events/annual/world_ suicide_prevention _day/en/
41. Yaowabutr, A., T. (2016). Factors predicting bullying behaviors of early adolescence in Bangkok. Journal of
public health nursing, 29(2), pp. 71-84.