Prevalence of Cyber Bullying Victims and its Associated Factors among Form 2 and Form 4 Secondary School Students in Kuala Terengganu, Malaysia

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AJMB, Official Journal of Faculty of Medicine, Universiti Sultan Zainal Abidin, Malaysia. Intan et al.

Prevalence of Cyber Bullying Victims and its Associated Factors among Form 2 and Form 4 Secondary School Students in Kuala Terengganu, Malaysia

Intan Suhana Munira Mat Azmi^1*, Myat Moe Thwe Aung¹, San San Oo¹, Azmi Hassan¹, Safiya Amaran¹

1Community Medicine Unit, Faculty of Medicine, Universiti Sultan Zainal Abidin, Medical Campus, Jalan Sultan Mahmud, 20400 Kuala Terengganu, Terengganu, Malaysia.

*ismunira@unisza.edu.my

Abstract

The number of cases of cyber bullying reported in schools had been alarming in these recent years. Increased accessibility of mobile phone and internet among secondary school students have made them more susceptible of becoming cyber bullying victims. These victims consequently will encounter mental health problems such as depression and anger that may lead to psychosomatic disorder and suicidal attempt in severe cases. This study focussed on determining the prevalence of cyber bullying and its associated factors among secondary school students. A cross sectional study was conducted among 482 of Form 2 and Form 4 school students in Kuala Terengganu. Data were collected using self-administered questionnaires. Data were analysed by using SPSS version 22. The descriptive statistics was applied to obtain frequency and percentage for categorical data. Simple logistic regression and Pearson Chi-square were used to determine the association between the independent variables and cyber bullying victimisation. The prevalence of cyber bullying victims in this study was 2.1% and total of 8.1% reported had been cyber bullied for lifetime. Four factors were found to be significantly associated with being a victim of cyber bullying; age (p = 0.010), type of school (p = 0.036), gender (p = 0.011) and perception towards family relationship (p = 0.006). In conclusion, the prevalence of cyber bullying victimisation in Kuala Terengganu is low in comparison to worldwide data. Although the prevalence is low, cyber-victimisation is progressing in numbers by year and there is a need to plan for proper intervention programs to enhance awareness among secondary school students to curb this issue.

Keywords: cyber bullying, secondary school, prevalence, associated factors

*Author for Correspondence:

Received (Jan 19^th, 2021), Accepted (March 30^th, 2021) & Published (April 30^th, 2021)

Cite as: Intan Suhana Munira, M. A.., Myat Moe, T. A., San, S. O., Azmi, H., Safiya, A. (2021). Prevalence of Cyber Bullying Victims and its Associated Factors among Form 2 and Form 4 Secondary School Students in Kuala Terengganu, Malaysia, Asian Journal of Medicine and Biomedicine, 5(1), 33-40.

doi:https://doi.org/10.37231/ajmb.2021.5.1.412 DOI: https://doi.org/10.37231/ajmb.2021.5.1.412

Asian Journal of Medicine and Biomedicine, Vol 5:1.

Original Article Open Access

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Introduction

The act of bullying has becoming a major concern among public. Bullying refers to the repetitive act towards a person with intention to harm either physically or mentally, and can occur anytime and anywhere ^[1]. A person is said to be a victim to bullying when he or she is unable to defend him or herself and repeatedly being bullied two or three times in a month ^[2,3]. There are several types of bullying i.e. physical, verbal, relational, indirect, and cyber bullying ^[4]. Traditional bullying differs from cyber bullying. Cyber bullying can be defined as any intentional act by a person or a group of people repetitively aided with a gadget against a person who is weak ^[5,6]. Cyber bullying falls into a number of sub-categories involving uploading unwanted picture or video clip on social media, texting harassing messages, bullying through emails, chat-room, phone calls, as well as websites and creating fake account to impersonate someone else or accessing private files from other person’s computer ^[7–9]. The unique characteristic of cyber bullying is the presence of anonymity in cyber bullying as no face to face contact is involved as in the traditional bullying ^[10].

The rise in owning a mobile phone and accessibility to the internet indicate that cyber bullying has evolved to become a common type of aggression among primary and secondary school students ^[6]. Data from Cyber bullying Research Centre among the US high school students aged 12 to 17 years old reported increased number of cyber- victimisation from year 2007 (18.8%) compared to 2019 (36.5%) that had been cyber bullied (lifetime) ^[11]. Another data from regional census of high school students in Massachusetts involving 20, 406 students resulted in 15.8% reported cyber bullying ^[12]. While in the European countries, cyber-victimisation was also found to be an issue. A cross sectional study was conducted among 14 to 17 years old students to determine the prevalence of cyber- victimisation. The highest prevalence was recorded in Romania (37.3%) whereas the lowest was in Spain with 13.3% ^[13]. Nonetheless, data analysed from the population-based survey in the UK among 120, 115 school students showed that only 406 (<1%) reported cyber bullying compared to 33, 363 (30%) with traditional bullying ^[14]. Study on cyber-victimisation from other localities such as in Southeast Asia countries was less well documented ^[15]. The use of internet in Brunei, Singapore, and Malaysia was high, with Thailand and Philippines recorded their usage 27.5% above the world average usage

[16]. This will make their population more susceptible to becoming victims of cyber bullying. Study conducted by Microsoft (2012) among youth population in Singapore and Malaysia reported that 58% and 33% had experienced cyber bullying respectively.

Whilst the prevalence of cyber bullying is increasing worldwide, there is a need to determine predictors of involvement in cyber-victimisation. By understanding what factors influencing the act of perpetrators in harming other individuals, further consequences faced by the cyber victims can be prevented. The experience of cyber- victimisation could lead to lower self-esteem or inferiority

complex ^[18], emotional and psychological stress ^[19], mental health issues, absence from school, bad academic performance ^[20], and attempt to commit suicide ^[18]. Such predictors could be age and gender differences, individual and family risk factors involvement, class and type of school factors, identity-based or targeting one’s disability.

Little is known about cyber bullying among secondary school students in Malaysia. Thus, this current study aimed to determine the prevalence of cyber bullying among this target group and its associated factors. The importance of this study was to highlight the existence of aggression and harassment through electronic communication among secondary school students to teachers and parents. Data obtained from this study will give an overview of cyber bullying victims among selected secondary schools. The findings revealed incidence of cyber bullying victims and this can help the public health professionals, school authorities as well as parents to prepare further actions in preventing cyber bullying from happening in the future.

Methodology

Study design and subjects

A cross-sectional study was conducted from 30^th December 2018 to 19^th February 2019. All consented Form 2 and Form 4 students from selected secondary schools in Kuala Terengganu were included in the study.

These two forms were chosen as they were not involved with major examination during the period of the study. On the other hand, those who were not willing to participate, did not get the consent from their parents, and absent during data collection were excluded from the study. All available consented students were selected for this study.

Sample size was calculated using a two proportion formula. Proportion of cyber bullying among male subjects (P0) as 30.5% ^[21] and estimated proportion of cyber bullying among female subjects (P1) as 45.5% were used. Power of the study was set at 80% and level of significance was 0.05. The required sample size was 163 for each school. Thus, after adding 30% expected missing data, minimum of 423 subjects were required from both schools.

Research tool.

A self-administered questionnaire was used. This questionnaire was checked for its validity and reliability prior to data collection. The questionnaire consisted of nine main sections with 68 questions as listed below:

a. Section A: 15 questions on socio-demographic data

b. Section B: 8 questions on perception towards relationship with family

c. Section C: 5 questions on perception towards relationship with friends

d. Section D: 4 questions on perception towards time spent alone

e. Section E: 6 questions on perception towards level of self-satisfaction

f. Section F: 8 questions on perception towards school and its environment

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g. Section G: 10 questions on perception towards cyber bullying

h. Section H: 5 questions on accessibility to mobile phone and internet

i. Section I: 7 questions on experience of being cyber bullied.

Five-level Likert scale was applied in statements for section B, C, D, E and F. Scores ranged from “strongly agree” to “strongly disagree”. Section G, H and I were provided with two answer options; “yes” or “no”. Pilot study was conducted among 91 consented Form 2 and Form 4 secondary school students of another school in Kuala Terengganu for validity and reliability purposes.

Details about full description of the research, confidentiality and voluntary participation were explained to all subjects of the study.

Data analysis

Data was entered and analysed using SPSS version 22.

The descriptive statistics was applied to obtain frequency and percentage for categorical data while mean and standard deviation (SD) for normally distributed numerical data. Median and interquartile range (IQR) was used for skewed data. Inferential statistic was employed to estimate the prevalence of cyberbullying. The results were presented with frequency and percentage with 95%

confidence interval (CI) values. As for categorical independent variable, simple logistic regression analysis, Pearson Chi-square or Fisher exact test were applied depending on the expected count of <5. For numerical independent variable, independent t-test was applied.

Ethics approval

The ethical approvals to conduct this study were obtained from Ministry of Education, Jabatan Pelajaran Negeri Terengganu (JPNT) and UniSZA Human Research Ethics Committee (UHREC).

Results

Sociodemographic characteristics of the subjects.

Data were collected from a total of 482 Form 2 and Form 4 secondary school students from two different schools;

one school from cluster school of excellence (69.7%) and another one was a selected daily high school (30.3%).

There were about 239 Form 2 students (49.6%) and 243 Form 4 students (50.4%) involved in this study. Majority of the students were Malay (98.3%). The proportion of gender was nearly equal. Regarding the level of education of the parents, 54.6% of the students’ fathers and 53.1%

of mothers pursued their education up to the level of tertiary education. Majority of fathers (86.7%) and mothers (54.6%) were employed. Total of 404 (83.8%) of their parents were married, while 78 (16.2%) were divorced or single parent. Most of the students’ family income were RM4000 and below (66.2%), while 163 (33.8%) were above RM4000. Almost all students (99.2%) had no disability (Table 1).

Table 1 Socio-demographic characteristics of Form 2 and Form 4 secondary school students (n = 482)

Variables Frequency (%)

School

Cluster school of excellence Daily high school

336 (69.7) 146 (30.3)

Form Form 2 Form 4

239 (49.6) 243 (50.4) Gender

Male Female

240 (49.8) 242 (50.2) Race

Malay Non-Malay

474 (98.3) 8 (1.7) Religion

Muslim Non-Muslim

475 (98.5) 7 (1.5) Father’s occupation

Unemployed Employed

64 (13.3) 418 (86.7) Mother’s occupation

Unemployed Employed

219 (45.4) 263 (54.6) Father’s education

Secondary education Tertiary education

219 (45.4) 263 (54.6) Mother’s education

Secondary education Tertiary education

226 (46.9) 256 (53.1) Marital Status

Married

Divorced or Single parent

404 (83.8) 78 (16.2) Income

≤ RM 4000

> RM 4000

319 (66.2) 163 (33.8) Disability

No Yes

478 (99.2) 4 (0.8)

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Access to mobile phones and internet among subjects.

Table 2 shows that 453 (94.0%) owns a mobile phone with access to internet, 446 (92.5%). Total of 310 (64.3%) students have a computer in their homes with an access to the internet. Most of them spent 5 hours or less than that duration surfing the internet through their mobile phones or computers daily.

Table 2 Access to mobile phones and internet among Form 2 and Form 4 secondary school students (n = 482)

Experience of cyber bullying among subjects.

Table 3 presents experience of cyber bullying among Form 2 and Form 4 secondary school students. Out of those students, 25 (5.2%) received disturbing and harassing messages, 16 (3.3%) faced misused password or profile name, and 17 (3.5%) sent email, message, photo or video of them to someone else to embarrass them. About 11 (2.3%) received posts of inappropriate comments or pictures of themselves on social media while 12 (2.5%) received pictures, messages or videos that were sexual in nature via their phone. Besides, 14 (2.9%) of them were purposely ignored by certain individuals from a group in the internet. Only 1 (0.2%) was bullied in the internet through other ways.

Identification of cyber bullying perpetrator

Total of 21 (4.4%) students claimed that the perpetrator was from their class, while 18 (3.7%) claimed the perpetrator was from another class but from the same form. About 17 (3.5%) claimed that the perpetrator was older than them and 5 (1.0%) claimed that the perpetrator was younger than them. Besides, 9 (1.9%) claimed that they knew the perpetrator but he or she was from another school and 3 (0.6%) claimed that they knew the

perpetrator, but the perpetrator was not a student. About 20 (4.1%) claimed that they did not know who the perpetrator was.

Table 3 Experience of cyber bullying among Form 2 and Form 4 secondary school (n = 482)

Actions taken after being cyber bullied.

During the cyber bullying, 10 (2.1%) felt lost and could not do anything. About 37 students (7.7%) told their friend about the incident, 7 (1.5%) told their teacher, 28 (5.8%) told their parents or guardian and 5 (1.0%) told other people.

Do you have a cell phone?

No Yes

29 (6.0) 453 (94.0) If you have a mobile

phone, do you have access to the internet?

No Yes

36 (7.5) 446 (92.5) Do you have a computer

in your home?

No Yes

172 (35.7) 310 (64.3) How long do you spend

your time surfing internet through mobile phone or computer daily?

≤ 5 hours

> 5 hours

396 (82.2) 86 (17.8)

I receive messages that disturb and harasses me

No Yes

457 (94.8) 25 (5.2) An individual misuses my

password or my profile name or pursue my identity as me on social media to embarrass / make me look bad

No Yes

466 (96.7) 16 (3.3) An individual sends an

email, message, photo or video to someone else to embarrass/ make me look bad

No Yes

465 (96.5) 17 (3.5) An individual posts

inappropriate comments / pictures on social media about me

No Yes

471 (97.7) 11 (2.3)

Sexting (An individual sends pictures, messages or videos that are sexual in nature to me using his/her cell phone)

No Yes

470 (97.5) 12 (2.5) I am purposely ignored by

certain individuals from a group in the internet

No Yes

468 (97.1) 14 (2.9) I am bullied in the internet

through other ways No

Yes

481 (99.8) 1 (0.2)

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Factors associated with cyber bullying among subjects.

After adjusting the confounding variables using simple logistic regression analysis, findings revealed that type of school (p = 0.036), form (p = 0.010), gender (p = 0.011) and total perception score towards relationship with their family (p = 0.006) were found to be significantly associated with prevalence of cyber bullying among Form 2 and Form 4 secondary school students (Table 4).

Table 4 Factors associated with cyber bullying among Form 2 and Form 4 secondary school students (n = 482).

Variables

Having experience of cyberbullying X²

(df) P- value No

n (%) Yes n (%) School

Cluster school of excellence

326 (97.0)

10 (3.0)

0.036^b

Daily high school

146 (100.0)

0 (0.0)

Form

Form 2 230

(96.2)

9 (3.8) 0.010^b

Form 4 242

(99.6)

1 (0.4) Gender

Male 231

(96.3)

9 (3.8) 0.011^b

Female 241

(99.6)

1 (0.4) Race

Malay 464

(97.9) 10 (2.1)

>0.950^b Non –

Malay

8 (100.0)

0 (0.0)

Religion

Muslim 465

(97.9) 10 (2.1)

>0.950^b Non –

Muslim

7 (100.0)

0 (0.0)

Father’s Job

Unemployed 64 (100.0)

0 (0.0) 0.372^b

Employed 408

(97.6) 10 (2.4) Mother’s Job

Unemployed 216 (98.6)

3 (1.4) 0.359^b

Employed 256

(97.3)

7 (2.7) Father’s

Education Secondary education

216 (98.6)

3 (1.4) 0.359^b

Tertiary education

256 (97.3)

7 (2.7)

Mother’s Education

Secondary education

224 (99.1)

2 (0.9) 0.113^b

Tertiary education

248 (96.9)

8 (3.1)

Marital status

Married 394

(97.5) 10 (2.5)

0.378^b Divorced or

Single parent

78 (100)

0 (0.0)

Income

≤ RM 4000 313 (98.1)

6 (1.9) 0.740^b

>RM 4000 159 (97.5)

4 (2.5) Disability

No 469

(97.9) 10 (2.1)

>0.950^b

Yes 3

(100.0)

0 (0.0) Do you have a

cell phone?

No 28

(96.6)

1 (3.4) 0.466^b

Yes 444

(98.0)

9 (2.0) If you have a

mobile phone, do you have access to the internet?

No 35

(97.2)

1 (2.8) 0.543^b

Yes 437

(98.0)

9 (2.0) Do you have a

computer in your home?

No 170

(98.8)

2 (1.2) 0.506^b

Yes 302

(97.4)

8 (2.6) If you have a

computer, do you have access to the internet?

No 233

(98.7)

3 (1.3) 0.340^b

Yes 239

(97.2)

7 (2.8) How long do

you spend your time surfing internet through mobile phone or computer daily

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≤ 5 hours 388 (98)

8 (2.0) 0.695^b

> 5 hours 84 (97.7)

2 (2.3) Total

perception score towards relationship with their family

33.64 (4.83)^d

29.30 (6.91)^d

4.34 (0.61,

9.30)

0.006^c

Total perception score towards relationship with friends

16.88 (2.57)^d

15.90 (2.96)^d

0.98 (- 1.15, 3.10)

0.237^c

Total perception score towards time spent alone

10.88 (3.26)^d

11.30 (3.74)^d

-0.42 (- 3.11, 2.27)

0.687^c

Total perception score towards level of self- satisfaction

20.76 (4.59)^d

20.80 (3.36)^d

-0.04 (- 2.46, 2.39)

0.980^c

Total perception score towards school and its environment

31.39 (4.83)^d

28.50 (4.67)^d

2.89 (- 0.47, 6.25)

0.061^c

Total perception score towards cyberbullying

35.07 (4.13)^d

36.80 (3.79)^d

-1.73 (- 4.46, 1.00)

0.190^c

aPearson chi-square; ^bFisher’s Exact test; ^cIndependent t- test; ^dMean and standard deviation

Discussion

The first objective of this study was to assess the prevalence of cyber-victimisation among Form 2 and Form 4 students in two selected secondary schools. Form 2 and Form 4 students are 14 and 16 years old respectively.

Secondary school in Malaysia starts from Form 1 until Form 5 in which from the age of 13 to 17 years old. The findings revealed that the prevalence of cyber- victimisation was 2.1%. In comparison with data from United States (26%) and United Kingdom (6.24%), the prevalence of cyber-victimisation in Kuala Terengganu was lower ^[21,22]. A number of studies were conducted in Malaysia in determining the prevalence of cyber bullying.

However, the target groups were different i.e. students in higher learning institution and after school age. Lai and colleagues performed a survey on 712 higher learning students from private college and universities. Total of 66% experienced cyber-victimisation ^[23]. Meanwhile, study among individuals who have completed secondary school (17 to 30 years old) showed that cyber- victimisation occurred to those who were younger.

The current study also aimed to investigate factors associated with cyber-victimisation among secondary school students in Kuala Terengganu. The findings revealed that age was a significant factor (p = 0.010) that influenced cyber-victimisation. Students in Form 2 (1.87%) were more prone to become cyber bully victims in comparison with Form 4 students (0.21%). In agreement with a study carried out in Canada, there was a significant association of cyber bullying with lower secondary schools, less in sixth‐form colleges and among those respondents, students in the age of 12 to 14 years old were cyber bullied more compared to the age of 10 to 11 years old ^[24]. From both of these findings, age 14 is more susceptible of becoming cyber-victim than other forms/grades in school. This statement is in line with studies by Ybarra, Mitchell, Wolak, & Finkelhor (2006) and Kowalski & Limber (2013) which stated that the peak age of victimisation were in between the age of 13 to 14

[25,26]. After these age, the rates of cyber-victimisation will decline as reported in a meta-analysis from 25 studies of cyberbullying ^[27]. In a perspective, among all forms in a secondary school, younger students could be more truthful in admitting being a cyberbully victim as compared to elder students who tend to hide the actual fact which in turn contributed to its lower prevalence in the current study.

Apart from that, type of school has also shown to have a significant contribution to cyber-victimisation. In the current study, two different schools were selected. One of the schools was a school from Cluster of Excellence whereas the other school was a daily secondary school.

Cluster school is registered under the Malaysian Ministry of Education as school with academic and sports excellence. This Cluster School system was created by the Malaysian Ministry of Education with the purpose to boost up school’s performance. There are specific criteria to qualify a student to enrol in this school such as high academic achievement and excellence involvement in non-curricular activities. Thus, there is a difference in terms of academic status in between cluster school and daily secondary school. The latter accepts any students from any primary school without consideration of academic achievements. Findings showed that Cluster School had higher prevalence of cyber-victimisation than daily secondary school with 3.0% and 0% respectively.

Non-equal number of subjects for both schools could be one of the reason to the rate of cyber-victimisation as total of 336 students from Cluster School took part in this study while only 146 students from daily secondary school. The gap of participation depended on the consent given by their parents in which 88% of parents from Cluster School consented for this study whereas only 61% parents from daily secondary school gave their consent. Regarding the type of schools, a number of studies have come to an agreement that factors such as the size of a school ^[28], and location of the school either surrounded by good or bad neighbourhood ^[29] played an important role in determining the rate of cyber-victimisation. In accordance to the current study, in terms of size, the Cluster School was bigger in size (total of students, number of buildings and land area). Although for the location of school, both schools were only 3.1 km apart, but students in Cluster School came from different neighbourhood as compared to students in the daily secondary school whom mostly were from the nearby localities.

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Gender was the third significant factor that was associated with the prevalence of cyber-victimization in this study.

Male students (1.9%) were found to have higher rate of cyber-victimisation compared to female students (0.2%).

This is parallel with the findings from survey among 4, 972 middle and high school students (12 to 17 years old) in the US whereby males (16.1%) were found to have higher prevalence of being cyber bullied than females (13.4%) ^[11]. However, a number of studies found that females had the higher rates of being cyber bully victims

[30–32] whereas some researchers reported no significant difference observed between males and females in cases of cyber-victimisation ^[33,34].

The final factor which was found to be significantly associated with cyber-victimisation was perception towards family relationship. We measured the perception score towards family relationship with eight items covering relationship with parents. Based on this study, cyber bully victims had a lower score on perception towards relationship with their family, mean of 29.3 and standard deviation of 6.91, compared to those who were not being cyber bullied, mean of 33.64 and standard deviation of 4.83. This finding was similar to the study conducted by Ortega-Barón, Buelga-Vasquez, & Cava- Caballero (2016) among 1, 062 Spanish adolescents (11 to 18 years old) ^[35]. They found that cyber bullied victims scored higher when it comes to the presence of family conflict. In line with the results reported by Martins, Simão, Freire, Caetano, & Matos (2016), lack of family support was found to be associated with cyber- victimisation among 6^th to 8^th grades students in Portugal

[36]. To reiterate, the statement from our questionnaire with highest rating of “Strongly Agree” was “I am content with the affection I am receiving from my family” with the percentage of 62%. However, only 29% and 24.5% of the students rated the statement “My parents take notice of what I surf on NET” as “Strongly Agree” and “Agree”

respectively. This shows that it is important for parents to be aware of what their children surf on the internet and to monitor their online activities to prevent their children from being cyber bullied or in worst cases, become the perpetrators. Thus, negative family climate or poor relationship between children and their parents was found to be an important factor associated with cybervictimization.

Conclusion

In conclusion, the prevalence of cyber bullying victimisation in Kuala Terengganu is still low as compared to other research from various localities. The current study strictly took into account three criteria that needed to be fulfilled to meet the requirements of becoming a cyberbully victim. Pertaining to the factors associated with cyber-victimisation, forms, age, gender, type of school and perception towards family relationship have been found to influence cyber-victimisation among secondary school students in Kuala Terengganu, Malaysia.

Conflict of Interest

The authors would like to declare that there was no conflict of interest in this study. The study did not receive any source of funding.

Acknowledgement

The authors would like to thank all Year 3, Group 4, UniSZA Medical Students session 2018/2019 for their contributions in this study. We would also like to take this opportunity to express our sincere gratitude to the Malaysia Ministry of Education for allowing the involvement of the selected schools in this study References

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