Prevalence of cyberbullying and associated factors among adolescents in Dubai schools: complex design survey – 2019

ABSTRACT

Cyberbullying is a recognized public health threat with established links to physical and mental health problems. A 2-stage stratified random cluster analysis of data from a self-administered survey on health-related behaviours including 1,683 adolescents from 28 government and private schools estimated the prevalence of cyberbullying and examined potentially related psychological and behavioural factors. We identified loneliness, sleep disturbances, loss of appetite, sadness, lack of parental understanding, tobacco use, school absenteeism, and physical fights as associated factors. However, logistic regression found statistically significant higher odds only for experiencing sadness and loneliness, school absenteeism and physical fights, indicating reduction in these factors as the primary goals of comprehensive cyberbullying prevention programs to protect the health and wellbeing of adolescent.

KEYWORDS:

• Adolescent health
• cyberbullying
• mental health
• prevalence
• United Arab Emirates

Background

Despite being relatively new, cyberbullying is well recognized as a serious public health threat increasing the risk of poor health, social and educational outcomes in childhood and adolescence (Armitage, 2021). Cyberbullying is bullying that takes place over digital devices on social media, online forums, chats or gaming rooms. It occurs on a broader, omnipresent scale compared to traditional bullying and includes sending, posting or sharing private or negative content with the capacity to do significant harm to the reputation, emotional well-being and social relationships of a child or adolescent (Suciu, 2022). Although cyberbullying and traditional bullying share common features, cyberbullying can be a more threatening form of aggression as it can remain anonymous, causing bullying to be viewed repeatedly and shared with others without limit. The literature revealed that the majority of victims of cyberbullying are also victims of traditional bullying (Armitage, 2021).

Adolescence is the phase of life between childhood and adulthood, from ages 10 to 19 years. It is a unique stage of development and an important time for laying the foundations of good physical and mental health (World Health Organization [WHO], 2022). Adolescents are connected to social media at a time when their levels of social and emotional development leave them vulnerable to peer pressure and cyberbullying (Hamm et al., 2015). Cyberbullying has established links to physical and mental health problems including depression, suicidality, substance abuse and somatic symptoms (David-Ferdon et al., 2016; Kumar & Goldstein, 2020). Moreover, a dose–response relationship has been found between the frequency of bullying and the severity of negative health consequences (Armitage, 2021).

Globally, there are wide variations in cyberbullying prevalence rates. A study of university students in Al Ain, UAE reported a cyberbullying prevalence of 4.7% (Al-Darmaki et al., 2022), further a study investigating parent’s perspective of cyberbullying in the UAE described 9% of children were exposed to cyberbullying (Rehim et al., 2020). In the Kingdom of Saudi Arabia, a study of high school students reported a cyberbullying prevalence of 18%, significant risk factors including being traditionally bullied, e-cigarette use and male gender (Alrasheed et al., 2022).

A study of high school students in Turkey reported a cyberbullying prevalence of 17% (Eyuboglu et al., 2021) whilst the Centers for Disease Control (CDC) estimated a wide-ranging prevalence of cyberbullying to be between 9% and 35% among adolescents (CDC, 2022). Further, the Office for National Statistics for England & Wales (2020) reported one in five children aged 10 to 15 years (19%) experienced at least one type of online bullying behaviour. Worldwide, there are large variations in cyberbullying estimates due to differences in target groups, estimation tools and methodologies (Hasan et al., 2023; Zhu et al., 2021).

Protective factors identified in lowering the likelihood of cyberbullying include (a) individual factors such as higher self-esteem, strong parent–child relationships and emotional intelligence (b) environmental factors such as positive school climate and residence in safer neighbourhoods (Kowalski et al., 2019).

Prevalence rates are of interest to local and international researchers and policymakers, particularly since there are wide variations in cyberbullying rates as this phenomenon is significantly influenced by cultural contexts (Barlett et al., 2014). Despite the GCC (Gulf Cooperation Council) region and the UAE (United Arab Emirates) being the highest users of social media (Radcliffe et al., 2023), data on the prevalence of cyberbullying amongst the adolescent population of the region are scarce, with even less being known about psychological and behavioural factors in this important population.

To the best of our knowledge, this is the first study examining the prevalence of cyberbullying among adolescents in Dubai schools, whilst contributing to the picture of cyberbullying prevalence rates from around the world.

It sets out to estimate self-reported cyberbullying experiences of adolescents and examine any psychological and behavioural correlates in order to guide evidence-based policies and prevention strategies.

Objectives

To estimate prevalence of cyberbullying among adolescents in Dubai, 2019, and identify associated factors.

Methods

The data were obtained from the Adolescent Risk Behavior Survey 2019 (ARBS-Dubai-2019). The ARBS is a two-stage stratified cluster cross-sectional survey used to estimate health-related behaviours and conditions among adolescents in Dubai schools. The two sampling stages involved firstly randomly selecting schools with a probability proportional to the school enrolment size. The total number of schools surveyed was 28 (private and government). Second, randomly selecting classes based on enrolment size of the school. The total number of surveyed classes was 100. All students in the randomly selected classes were invited to participate in the survey.

The survey questionnaire was adapted from the Youth Risk Behavior Survey (YRBS) developed by the CDC. The questionnaire was translated into Arabic then back translated to English and validated by a group of experts from the Public Health Protection Department (PHPD) – Dubai Health Authority (DHA). Both versions were piloted on adolescent students before the survey.

The sample size was calculated using Epi-info online version (7.02.27). The total sample required was 1,723 students, taking into consideration: (a) student size in grades 8–12. (b) Standard error = 0.05. (c) Analysis of two subgroups sex and grade level. (d) Design effect (Deff) = 2. (e) Nonresponse rate of 20%. (f) Z statistic 1.95 for 95% confidence interval (CI). (g) Average number of students in the class.

The study received ethical approval from the Dubai Scientific Research Committee. To participate in the study, parents were asked to provide their signed informed consent, and additionally students were assented on the day of the survey. An email contact address was given to parents should they require any further information. In order to ensure student confidentiality, student participation was anonymous and voluntary. Anthropometric measures, included height and weight, were measured by a trained school health nurse according to the standardized procedures using calibrated tools in the school clinic.

Data collection

During the months of May–July 2019, assented students answered a self-administered electronic questionnaire in their language of preference Arabic or English. In line with the recommendation of education authorities and school heads, questionnaires were administered during a 45-minute tutorial classes. A school nurse and doctor trained in administering the survey questionnaire were available to provide additional support to any student who required assistance during or after completing the questionnaire.

Inclusion & exclusion criteria

Inclusion criteria were any school having at least one class from grades: 8, 9, 10, 11 or 12. Sample stratification was based on two criteria: (a) male, female and mixed schools and (b) lower grade classes 8 and 9 and higher-grade classes 10, 11 and 12.

Exclusion criteria were students who were absent on the day, gave no assent or parental dissent.

Statistical analysis

Stata 12 software was used for data analyses. The correction factors included weight, PSU and cluster. Accordingly, all presented percentages in this paper are weighted. An Adjusted Wald test was used to test the difference of percent between groups according to sex and grade. A p value <0.05 was the cut-off level for significance.

Logistic regression was used and reported with odds ratio (OR), and the model goodness of fit was calculated using the F-adjusted mean residual test for complex-design surveys, where a non-significant p-value suggested no evidence of lack of fit (Archer & Lemeshow, 2006).

Results

The total eligible sample for the ARBS-2019 included 1,683 adolescents (Grades 8–12). The school response rate was 75.7%, the student response rate was 98.6%, and overall response rate was 74.6%.

Sample demographics

Table 1 shows demographic characteristics of the adolescent study population. It can be seen that females accounted for 51.7% of the sample and males 48.3%. The 13–18-year age group constituted 93% of the sample. The sample contained only 3.3% of adolescents, aged 12 years of age, and only 3.7% of 18-year-olds. The sample had a balanced grade representation with 8th grade constituting 23.3%, 9th grade students 20.7%, 10th grade students 19.9%, 11th grade students 18.2% and 12th grade students 17.9%.

Table 1. Adolescents in grades 8–12 by demographics in Dubai, 2019.

	Number (n=1,683)	Weighted % (95% CI)
Sex
Female	820	51.7 (45.1–58.2)
Male	863	48.3 (41.8–54.9)
Age (Years)
12	94	3.3 (1.9–5.4)
13	343	15.6 (11.4–21.0)
14	419	21.9 (17.4–27.2)
15	323	21.5 (15.7–28.7)
16	254	18.8 (15.1–23.3)
17	196	15.2 (11.0–20.7)
18	54	3.7 (2.0–6.6)
Grades
Grade 8	505	23.3 (15.8–33.0)
Grade 9	462	20.7 (13.6–30.2)
Grade 10	209	19.9 (11.9–31.3)
Grade 11	291	18.2 (12.7–25.5)
Grade 12	216	17.9 (10.6–28.7)

Statistical analyses

The prevalence of being bullied on at least 1 day during the 30 days prior to the survey among adolescents was 21.7% (95% CI: 18.6–25.2), while the prevalence of cyber bullying was 14.8% (95% CI: 12.2–17.7) (Table 2).

Table 2. Bullying and cyberbullying in grades 8–12 adolescents in Dubai, 2019.

Bullying	Number (n=1,683)	Weighted (%) 95% CI
Adolescents bullied on at least 1 day during the 30 days before the survey	374	21.7 (18.6–25.2)
Adolescents electronically bullied (through texting, Instagram, Facebook, other social media)	245	14.8 (12.2–17.7)
Cyberbullying from total bullying	245	65.5% from total bullied

*Weighted Percentages.

Table 3 shows the association between cyberbullying with various demographic characteristics. This study did not find a significant (p < 0.05) association between cyberbullying and sex, age, grade, BMI or number of friends.

Table 3. Cyberbullying by sex, age, grade, BMI and number of friends amongst adolescents of grades 8–12 in Dubai schools, 2019.

Associated Factors			No Cyberbullying	Cyberbullying	Total ( N=1683)	Adjusted Wald	P value
Sex	Female	No	749	114	863	Adjusted F(1, 67)	0.07
		%	87.78	12.22	100
		95% CI	84.8–90.3	9.8–15.2
		Deft	1.19	1.19
	Male	No	689	131	820
		%	82.9	17.1	100
		95% CI	77.7–87.1	12.95–22.3
Age	12 years	No	85	9	94	Adjusted F(7, 61) = 1.3211	P = 0.26
		%	90.69	9.314	100
		95% CI	82.3–95.3	4.7–17.7
		Deft	0.79	0.79
	13 years	No	294	49	343
		%	84.44	15.56	100
		95% CI	76.8–89.9	10.1–23.3
		Deft	1.46	1.46
	14 years	No	357	62	419
		%	85.86	14.14	100
		95% CI	80.4–90.0	10.0–19.6
		Deft	1.32	1.32
	15 years	No	264	59	323
		%	81.37	18.63	100
		95% CI	73.5–87.3	12.7–26.5
		Deft	1.68	1.68
	16 years	No	217	37	254
		%	84.76	15.24	100
		95% CI	78.9–89.2	10.8–21.1
		Deft	1.27	1.27
	17 years	No	171	25	196
		%	88.47	11.53	100
		95% CI	82.7–92.5	7.5–17.3
		Deft	1.21	1.21
	18 years	No	50	4	54
		%	92.14	7.865	100
		95% CI	81.7–96.8	3.2–18.3
		Deft	1.02	1.02
Grades	Years 8–10	No	988	189	1177	F(6, 62)=1.1231	0.36
		%	83.05	16.95	100
		95% CI	78.7–86.7	13.3–21.4
		Deft	1.76	1.76
	Years 11–12	No	450	56	506
		%	89.18	10.82	100
		95% CI	86.5–91.4	8.6–13.5
		Deft	0.96	0.96
BMI	Underweight	No	40	7	47	F(3, 65)=0.9242	0.430
		%	84.0	16.0	100
		95% CI	68.6–92.6	7.4–31.4
		Deft	1.05	1.05
	Healthy weight	No	801	128	929
		%	86.52	13.48	100
		95% CI	82.2–89.9	10.1–17.8
		Deft	1.74	1.74
	Over weight	No	355	70	425
		%	81.9	18.2	100
		95% CI	76.4–86.3	13.7–23.6
		Deft	1.33	1.33
	Obesity	No	242	40	282
		%	86.4	13.6	100
		95% CI	80.6–90.7	9.3–19.4
		Deft	1.19	1.19
Friends-How many close friends do you have?	0 friends	No	78	24	102	F(3, 65) = 1.8669	P = 0.14
		%	80.0	20.1	100
		95% CI	70.0–87.2	12.8–30.0
		Deft	1.03	1.03
	1 friend	No	94	24	118
		%	80.6	19.4	100
		95% CI	66.9–89.5	10.5–33.1
		Deft	1.63	1.63
	2 friends	No	204	46	250
		%	83.55	16.45	100
		95% CI	77.3–88.4	11.6–22.7
		Deft	1.21	1.21
	3 or more	No	1061	151	1212
		%	86.6	13.5	100
		95% CI	83.2–89.3	10.7–16.8
		Deft	1.56	1.56

Table 4 presents cyberbullying with other behavioural and psychological factors. From the cyberbullied group, 27.3% (95% CI: 22.1–33.3) reported feeling lonely most of the time compared to only 8.7% (95% CI: 6.4–11.7) who reported never or rarely feeling lonely, the result was statistically significant (P < 0.05). Almost a third 29.1% (95% CI: 23.6–35.3) of cyberbullied adolescents experienced sleep disturbances due to worry compared to only 11.3% (95% CI: 8.7–14.4) of the group which did not reporting sleep disturbances (P < 0.05). Loss of appetite due to worry in the cyberbullied adolescents was 35.5% (95% CI: 26.3–46.0) only 12.8% (95% CI: 10.7–15.3), reported no loss of appetite, the difference was statically significant (P < 0.05). Similarly, a quarter 25.5% (95% CI: 20.7–31.0) of the cyberbullied group reported feelings of sadness or hopelessness preventing usual activities compared to only 8.7% (95% CI: 6.7–11.3) of students not reporting sadness, the difference was statistically significant (P < 0.05). Regarding parental understanding, 19.2% (95% CI: 15.4–23.7) of cyberbullied adolescents reported that parents never or rarely understood them compared to only 10.6% (95% CI: 7.8–14.3) of cyberbullied adolescents who stated that their parents understood them always/most of the time, with the difference being statistically significant (P < 0.05).

Table 4. Cyberbullying by associated factors amongst adolescents of grades 8–12 in Dubai schools, 2019.

Associated Factors			No Cyberbullying	Cyberbullying	Total ( N=1683)	Adjusted Wald	P value
Loneliness- During the past 12 months, how often have you felt lonely?	Never or Rarely	No	817	76	893	F(2, 66)=17.0283	*P = 0.00
		%	91.3	8.7	100
		95% CI	88.3–93.6	6.4–11.7
		Deft	1.36	1.36
	Sometimes	No	397	79	476
		%	83.03	16.97	100
		95% CI	77.29	12.45
			87.55	22.71
		Deft	1.54	1.54
	Most of the time	No	223	90	313
		%	72.7	27.3	100
		95% CI	66.7–78.0	22.1–33.3
		Deft	1.13	1.13
Sleep Disturbance - During the past 12 months, how often have you been so worried about something that you could not sleep at night?	No	No	1222	154	1376	F(1, 67) = 23.2902	*P = 0.00
		%	88.7	11.3	100
		95% CI	85.6–91.3	8.7–14.4
		Deft	1.65	1.65
	Yes	No	216	91	307
		%	70.9	29.1	100
		95% CI	64.7–76.4	23.6–35.3
		Deft	1.17	1.17
Loss of appetite - During the past 12 months, how often have you been so worried about something that you could not eat or you lost your appetite for food?	No	No	1343	196	1539	F(1, 67) = 14.2417	*P = 0.00
		%	87.2	12.8	100
		95% CI	84.7–89.4	10.7–15.3
		Deft	1.37	1.37
	Yes	No	94	49	143
		%	64.5	35.5	100
		95% CI	54.0–73.7	26.3–46.0
		Deft	1.25	1.25
Sadness -During the past 12 months, did you ever feel so sad or hopeless almost every day, for two weeks or more in a row, that you stopped doing your usual activities?	No	No	1024	96	1120	F(1, 67) = 38.0764	*P = 0.00
		%	91.3	8.7	100
		95% CI	88.7–93.3	6.7–11.3
		Deft	1.33	1.33
	Yes	No	413	149	562
		%	74.5	25.5	100
		95% CI	69.0–79.3	20.7–31.0
		Deft	1.47	1.47
	Total	No	1437	245	1682
		%	85.3	14.8	100
		95% CI	82.3–87.8	12.3–17.7
		Deft	1.57	1.57
Parental Understanding -During the past 30 days, how often did your parents or guardians understand your problems and worries?	Never or Rarely	No	498	124	622	F(2, 66) = 7.5954	*P = 0.00
		%	80.8	19.2	100
		95% CI	76.3–84.6	15.4–23.7
		Deft	1.34	1.34
	Sometime	No	259	45	304
		%	84.7	15.3	100
		95% CI	78.3–89.5	10.5–21.7
		Deft	1.35	1.35
	Always	No	680	75	755
		%	89.4	10.6	100
		95% CI	85.7–92.2	7.8–14.3
		Deft	1.43	1.43
Tobacco Use: Currently using any tobacco product (including cigarettes, e-cigarettes, e-cigars, medwakh, sheesha, chewing or sniffing tobacco) on at least 1 day during the 30 days before the survey)	No	No	1256	172	1428	F(1, 67) = 11.1498	*P = 0.00
		%	87.6	12.4	100
		95% CI	84.3–90.2	9.8–15.7
		Deft	1.68	1.68
	Yes	No	181	73	254
		%	73.4	26.6	100
		95% CI	66.1–79.7	20.3–33.9
		Deft	1.29	1.29
School Absenteeism - During the past 30 days, on how many days did you not go to school because you felt you would be unsafe at school or on your way to or from school?	0 days	No	1306	175	1481	F(4, 64) = 4.8517	*P = 0.00
		%	88.1	11.9	100
		95% CI	85.8–90.2	9.8–14.2
		Deft	1.30	1.30
	1 day	No	46	27	73
		%	60.7	39.3	100
		95% CI	47.4–72.5	27.5–52.6
		Deft	1.19	1.19
	2–3 days	No	40	26	66
		%	57.6	42.4	100
		95% CI	43.3–70.7	29.3–56.7
		Deft	1.11	1.11
	4–5 days	No	17	7	24
		%	65.9	34.1	100
		95% CI	41.9–83.8	16.2–58.1
		Deft	1.10	1.10
	6 or more	No	29	10	39
		%	79.3	20.7	100
		95% CI	59.2–91.0	9.0–40.8
		Deft	1.10	1.10
Physical Fighting - during the past 12 months, how many times were you in a physical fight?	0 times	No	913	111	1024	F(4, 64) = 3.4822	*P = 0.01
		%	88.46	11.54	100
		95% CI	84.6–91.5	8.5–15.4
		Deft	1.74	1.74
	1 time	No	184	34	218
		%	83.6	16.4	100
		95% CI	75.6–89.4	10.6–24.4
		Deft	1.32	1.32
	2–5 times	No	251	65	316
		%	79.9	20.1	100
		95% CI	73.5–85.1	14.9–26.5
		Deft	1.27	1.27
	6–9 times	No	39	10	49
		%	81.4	18.6	100
		95% CI	66.1–90.8	9.2–33.9
		Deft	1.06	1.06
	10 or more	No	51	25	76
		%	67.2	32.8	100
		95% CI	52.9–78.8	21.2–47.1
		Deft	1.17	1.17

More than a quarter 26.6% (95% CI: 20.3–33.9) of cyberbullied adolescents reported using tobacco products (cigarettes, e-cigarettes, medwakh or shisha) compared to only 12.4% (95% CI: 9.8–15.7) did not report tobacco use, and the difference was statistically significant (P < 0.05).

School absenteeism was higher in the cyberbullied group 42.4% (95% CI: 29.3–56.7) reported missing 2–3 days of school due to feeling unsafe at school or on the way to or from only 11.9% (95% CI: 9.8–14.2) did not report missing days of school due to safety concerns the difference was statistically significant (P < 0.05). Of the cyberbullied adolescents, 32.8% (95% CI: 21.2–47.1) reported being in 10 or more physical fights compared to 11.5% (95% CI: 8.5–15.4) of cyberbullied students not being in a physical fight. The difference was statistically significant (P < 0.05).

Logistic regression

Logistic regression analysis as seen in Table 5 was used to identify the odds of being cyberbullied. It shows the odds of feeling lonely or sad were higher among adolescents that were cyberbullied [OR 1.43 (95% CI: 1.13–1.81)] and [OR: 2.60 (95% CI: 1.68–4.03)], respectively. The odds of feeling unsafe at school or on the way to or from school was higher [OR: 1.44 (95% CI: 1.20–1.74)] in adolescents reporting cyberbullying than in students not reporting cyberbullying. Further, higher odds were observed for physical fights [OR: 1.25 (95% CI: 1.07–1.47)] among the cyberbullied adolescents.

Table 5. Logistic regression analysis for correlates of cyberbullying amongst adolescents of grades 8–12 in Dubai schools, 2019.

Cyberbullying (n=1682)	Odds Ratio	95% CI.	P value
During the past 12 months, how often have you felt lonely?
Yes	1.43	1.13–1.81	0.03
No	Reference group
During the past 12 months, did you ever feel so sad or hopeless almost every day, for two weeks or more in a row, that you stopped doing your usual activities?
Yes	2.60	1.68–4.03	0.00
No	Reference group
During the past 30 days, on how many days did you not go to school because you felt you would be unsafe at school or on your way to or from school?
Yes	1.44	1.20–1.74	0.00
No	Reference group
During the past 12 months, how many times were you in a physical fight?
Yes	1.25	1.07–1.47	0.02
No	Reference group
The design based Goodness of fit test for logistic regression Number of observations = 1682 F-adjusted test statistic = F(8,60) = 0.894 Prob > F = 0.528

The goodness-of-fit test used to assess the logistic regression model revealed a non-significant p-value suggesting no evidence of lack of fit for our regression model.

Discussion

Prevalence of cyberbullying

Cyberbullying is known to exist in educational settings worldwide, however to the best of our knowledge, there are no published data on the prevalence of cyberbullying among adolescents in Dubai schools. The current findings highlight a cyberbullying prevalence of 14.8%, constituting 65.5% from the total bullying among the adolescent population.

The findings of this study were within the lower end of global cyberbullying estimates which vary widely between 9% and 35% (CDC, 2022; IPSOS, 2018; Krešić Ćorić & Kaštelan, 2020; WHO, 2022). Worldwide estimates reported from Norway, UK, Spain, Turkey and Italy were 9%, 19%, 25.7%, 17% and 5.9%, respectively (Eyuboglu et al., 2021; Ferrara et al., 2018; Kaiser et al., 2020; Office for National Statistics [ONS], 2020; Yudes et al., 2020).

Comparing prevalence rates of cyberbullying worldwide is challenging as rates vary greatly. This may reflect real differences in cyberbullying across countries because this phenomenon is significantly influenced by cultural contexts (Barlett et al., 2014). However, differences could also be attributable to the use of different research methods or strategies. This includes an unclear definition of the term cyberbullying (Olweus & Limber, 2018). The estimation of prevalence of cyberbullying is heavily affected by research methods, such as recall period (lifetime, last year, last 6 months, last month or last week, etc.), demographic characteristics of the survey sample (age, gender, race, etc.), perspectives of cyberbullying experiences (victims, perpetrators or both victim and perpetrator) and instruments (scales, study-specific questions). Additionally, variations in economic development, cultural backgrounds, human values, internet penetration rates and frequency of using social media may lead to different conclusions across countries (Zhu et al., 2021).

Risk factors associated with cyberbullying

Factors associated with cyberbullying were found to be loneliness, sleep disturbances, loss of appetite, sadness, lack of parental understanding, tobacco use, school absenteeism and physical fights. However, when all the mentioned factors were plugged into the logistic regression model to adjust for potentially confounding effects, only loneliness, sadness, school absenteeism and physical fights continued to exhibit a statistically significant relationship with cyberbullying.

Feelings of loneliness and sadness were higher among adolescents that were cyberbullied [OR 1.43 (95% CI: 1.13–1.81)] and [OR: 2.60 (95% CI: 1.68–4.03)], respectively. A number of studies have reported similar findings showing an association between cyberbullying and psychological indicators such as depression, sadness, and loneliness (Kumar & Goldstein, 2020; Nixon et al., 2014), other studies found an almost two-three-fold higher risk of depression in cyberbullied victims (Thai et al., 2022; Tran et al., 2021). Cyberbullied university students in Qatar reported symptoms of depression, anxiety and PTSD (Alrajeh et al., 2021).

The odds of feeling unsafe at school or on the way to or from school were higher among cyberbullied adolescents [OR: 1.44 (95% CI: 1.20–1.74)]. School absenteeism is considered to be a significant educational and health problem (van den Toren SJ et al., 2019). Our findings agree with other studies reporting cyberbullying was significantly associated with school absences. A study amongst high school students in the US reported that the relative risk of missing 2–3 days of school per month increased by a factor of 2 for those experiencing cyberbullying (Grinshteyn & Yang, 2017). A UAE study on bullying suggests that feeling safe at school is negatively and independently related to both being bullied and bullying (Rigby et al., 2019).

Further, this study found a higher odds of physical fighting [OR: 1.25 (95% CI: 1.07–1.47)] among the cyberbullied adolescents similarly to other studies where cyberbullying was more likely in students reporting depressive symptoms, self harm, risky behaviours, suicidal ideation, carrying a weapon and engaging in a physical fight (Alhajji et al., 2019; Ranney et al., 2020; Ossa et al., 2023).

Limitations of the study

This study used information collected on a self-reported basis and is therefore prone to recall bias. The cross-sectional design is useful for identifying associations but cannot attribute causation; hence, further studies are needed to study any cause and effect relationship. This research was conducted prior to the COVID-19 pandemic and should be repeated as the internet behaviour patterns during and after the pandemic changed with adolescents spending even more time engaged online.

Despite the above limitations, the strength of the study lies in the size and population survey design for examining the prevalence of cyberbullying and associated factors.

Conclusion

This is the first study examining cyberbullying in the adolescents of Dubai schools. The study found students experiencing cyberbullying had a higher odds of experiencing sadness, loneliness, school absenteeism and physical fights.

The current findings set a baseline for monitoring cyberbullying and associated factors for the adolescent population of Dubai, in addition to contributing to the picture of cyberbullying prevalence rates from around the world.

The study is informative for cyberbullying prevention and control programmes. It highlights the importance of studying further the relationship between health conditions, cyberbullying and violence.

Ethical approval

The research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki and was approved by Dubai Scientific Research Ethics Committee (DSREC)No. DSREC-02/2019_10. Parent gave consent and adolescents were assented before participating in the survey.

Acknowledgement

The authors appreciate the contribution of the Adolescent Risk Behavioural Survey Working Team 2019, and all staff of Public Health Program & Studies Section & School Health Section of Public Health Protection Department. Also our thanks to the Ministry of Health and Prevention (MOHAP), Ministry of Education and all participating students and schools.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are not publicly available due to the organizations administrative policy and procedures. However, the data are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by Dubai Health Authority.

Notes on contributors

Sabya Farooq

Dr. Sabya Farooq. Holds a MBBS from Queen Mary University of London, Ph.D. & M.Sc. in Public Health & Epidemiology from the London School of Hygiene & Tropical Medicine. Currently working as a senior researcher at programs and studies section in the Public Health Protection Department, Dubai Health Authority. Research interests include adolescent health, mental health, non-communicable diseases and population health.

Mona Abdullatif

Dr. Mona Abdullatif. Consultant Community Medicine from the Arab Board of Health Specializations (ABHS). Currently, a senior researcher at programs and studies section in the Public Health Protection Department, Dubai Health Authority. Research interests include adolescent health, mental health, community health and epidemiology.

Ayesha Altheeb

Dr. Ayesha Altheeb. Consultant Community Medicine from the Arab Board of Health Specializations (ABHS), M.Sc. Quality and Safety in Health Care Management (RCSI). Head of Public Health Programs and Studies Section and Senior Researcher in the Public Health Protection Department, Dubai Health Authority. Research interests include adolescent health, mental health, non-communicable diseases, environmental health and population health.