Skip to main content

Is cyberbullying perpetration associated with anxiety, depression and suicidal ideation among lebanese adolescents? Results from a cross-sectional study

Abstract

Background

As cyberbullying is a new area of investigation, results worldwide point to the prevalence of cyberbullying perpetration. This study aimed to assess the association between cyberbullying perpetration, anxiety, depression and suicidal ideation among Lebanese adolescents.

Methods

This cross-sectional study was conducted between May and June 2021 and included a sample of adolescents aged between 13 and 16 years old, recruited from private schools chosen in a convenient way from all Lebanese districts. A total of 520 students accepted to participate in our study. To collect data, a questionnaire was shared by google form including: Cyber Bully/Cyber victim questionnaire; Lebanese Anxiety Scale; and Patient Health Questionnaire for Adolescents.

Results

The results of the linear regressions, taking anxiety and depression as dependent variables, showed that female gender, having kind of hard and very/extremely hard influence of problems on daily work, sexual cyberbullying in cyberspace, embarrassing and inserting malicious content in cyberspace and older age were significantly associated with more anxiety and depression. Having kind of hard influence of problems on daily work compared to not at all, higher anxiety, higher depression and higher household crowding index (lower socioeconomic status) were significantly associated with higher odds of having suicidal ideation in the last month.

Conclusion

Cyberbullying perpetration and its associated factors reported in this study are significant enough to call for early detection and prevention strategies for Lebanese adolescents. At the school level, effective programs implemented in the school years are needed, aiming to develop social/emotional control, and conflict resolution skills as they might decrease engagement in cyberbullying perpetration among adolescents. Preventive interventions are needed to reduce the engagement of Lebanese adolescents in cyberbullying perpetration.

Peer Review reports

Background

Bullying represents one of the most serious public health issues. It is defined as a continual aggressive act committed by a group or an individual over time against a victim who is unable to defend him/herself [1]. Given the rapid development and the emergence of communication and information technology (i.e. text messages, smartphones, and social media platforms), new ways to take out frustrations and aggression among adolescents emerged. Adolescents can easily form a large number of online groups, which are difficult to control, with a potentially increased risk of becoming cyberbullies [2]. Hence, the term “Cyberbullying” referring to bullying through the internet has emerged and grabbed the attention of researchers and communities globally [3].

As cyberbullying is a new area of investigation [4], results worldwide point to the prevalence of cyberbullying perpetration [5]. The Middle East and North Africa region was named among the countries with the highest rates of bullying among adolescents aged 11 to 15 in 2018 [6]. In Lebanon, approximately 90% of bullying acts occur in schools, with 41.9% of adolescents being bullying perpetrators [7].

Cyberbullying is characterized by the absence of physical interaction; the victim has no opportunity to defend him/herself at all times; the chances of identifying and punishing perpetrators are pretty low [8]. Because cyberbullying perpetrators are usually anonymous, their harmful behavior might be exacerbated. Victims can be abused in the security of their own home, at any time, and even if the victim removed himself from the online site, the messages can still accumulate without being able to escape from this negative situation [9]. Unlike direct traditional bullying, which can be identified right away by parents or teachers, cyberbullying takes more time to be identified [9].

Excessive risky online use, moral disengagement, narcissism, self-efficacy, social norms, and substance use have all been identified as risk factors that increase a person’s likelihood of becoming a cyberbullying perpetrator [10]. Similarly, the outcomes of cyberbullying perpetration were found to be associated with a variety of problems such as depression, anxiety, loneliness, low self-esteem, aggressive cognition, moral disengagement, and substance use. It was also associated with lower academic achievement and life satisfaction [9, 11]. Furthermore, cyberbullies were at a higher risk of self-harm, suicidal ideation, and suicide attempts [12, 13].

The COVID-19 pandemic affected all people worldide and imposed strict restrictions such as social distancing, school closure, distanced learning experience, and online conferences, all of which increasing internet usage [14, 15]. In line with this situation, Lebanese were at a higher risk of social isolation, depression, loneliness, excessive internet use and cyberbullying, with 49% of adolescents being cyberbullying perpetrators [7, 16, 17]. Although multiple studies have addressed factors associated with cyberbullying perpetration occurrence, research thoroughly investigating consequences of this behavior is still needed to preempt incidents. Given the high rates of mental health issues among Lebanese adolescents (28.9% suicidal ideation [18] and 57.2% of moderate to high depressive symptoms [19]) and the rising prevalence of cyberbullying perpetration found among Lebanese adolescents and the crisis imposing higher internet use, we realized that it is important to shed the light on cyberbullying perpetration behavior and its consequences on bullies. Therefore, this study aimed to assess the association between cyberbullying perpetration and anxiety, depression and suicidal ideation among a sample of Lebanese adolescents.

Methods

Study design

This cross-sectional study was conducted between May and June 2021 and included a sample of adolescents aged between 13 and 16 years old, recruited from private schools chosen in a convenient way from all Lebanese districts. Following the restrictions imposed by the Lebanese government due to COVID-19 and the online teaching adopted by schools, the collection of the data was done using an online form. The questionnaire was tested on 25 students, prior to data collection, with the aim of clarifying questions if necessary, correcting errors and assessing the length of the questionnaire; the results of the pilot study was not included in the analysis. We contacted the directors of fifteen selected schools, explained the objective of the study and presented the questionnaire to them; the anonymity of the school and students was ensured. We contacted three schools in each governorate; the description of the data collection is summarized in Table 1.

Table 1 Description of data collection

Participants

The study sample consisted of 520 students from grades 7, 8 and 9 in private schools in all Lebanese districts; the governorates were classified according to their geographical proximity: Beirut, Mount Lebanon, North Lebanon (including Akkar), South Lebanon (including Nabatieh) and Bekaa (including Baalback-Hermel). All students randomly selected from classes and aged exactly 13 to 16 years of age (date of taking the tests) were eligible to take part of this study. Exclusions consisted of those who did not meet those criteria or refused to participate in this study. It should be noted that the objective of the study, the anonymity of the participants, the lack of personal profit, the agreement of the ethics committee, the lack of compensation of any kind, the freedom of choice to participate or not, were explained in the introductory paragraph of the Google Form. After approving those statements and asking for the parents’ approval, the student was guided to the actual questions.

Minimal sample size calculation

According to the G-power software, and based on an effect size f2 = 2%, an alpha error of 5% and a power of 80%, while taking into account 20 factors to be captured in the multivariate analysis, the results showed that a minimum number of 395 participants was needed to conduct this study.

Questionnaire

The questionnaire consisted of three measuring instruments used to separately assess each of the four variables studied and questions studying the socio-demographic characteristics of the participants (age, gender, parents’ status, influence of problems on work (including all student behaviors at school and associated consequences such as school dropout, getting remarks and repeating a year), and household crowding index). The latter reflects the socio-economic status of the family and was calculated by dividing the number of people by the number of rooms in the house, except the bathrooms and the kitchen [20]. In addition, a question about the presence of suicidal ideation the last month has been asked to students with a dichotomous answer (yes/no). The digital questionnaire was self-administered in Arabic, the participants’ mother tongue. The calculated time to complete the questionnaire was fifteen minutes.

Cyber bully/cyber victim questionnaire

The “Cyber Bully/Cyber Victim Scale” has been translated into Arabic via the ‘Forward-and-Backward’ method. This scale was translated first from English to Arabic by a professional translator, secondly from Arabic to English by another professional translator. A comparison was made between the original English version and the English translated copy by a mental health professional, with no major corrections made to the final Arabic version. The Cyber Bully/Cyber Victim Questionnaire was used to assess cyberbullying behavior [21]. Authorization to translate and use the scale was obtained from Dr. Mehmet Horzum. This scale consists of 15 items and is divided into two sub-dimensions: the first is composed of seven items and evaluates cyber sexual harassment in cyberspace, and the second is composed of eight items and evaluates the insertion of embarrassing and malicious content on cyberspace. It should be noted that this scale is used to assess at the same time or separately the behavior of perpetration and/or victimization. We used only the part about the harasser. Questions were rated from 1 = Never to 5 = all the time. Points are scored by adding all the points of the elements on the scale. The total score on “made by me” is considered the cyber stalker’s score and the total score on “made for me” is considered the cyber-victim score. In our study, a higher score on “made by me” items indicates a higher level of harassing behavior.

Lebanese anxiety scale (LAS-10)

This ten-item self-report scale was developed in Lebanon and validated among adults [22], and adolescents [23]. Seven of the ten items are rated on a 5-point Likert scale, whereas the other three questions are scored on a 4-point Likert scale [22]. The total score was obtained by adding up all responses, with higher scores indicating higher anxiety.

Patient health questionnaire for adolescents (PHQ-A)

This scale was being tested for use in adolescents and provides an effective tool for the early detection and recognition of mental disorders in this high-risk group [24]. The Arabic translation was validated by Al-Amer et al. (2020) [25]. It is a scale composed of (1) nine items that can be self-administered, which assess the symptoms experienced in the previous two weeks; all items receive a response using a four-point Likert scale (0 = Not at all to 3 = almost every day); 2) An item that extends over the year preceding the award; 3) An item on the effect of his suffering and on his daily performance; 4) An item that extends over one month before the handover; and 5) An item that assesses the presence of suicide attempts in the past. PHQ-A measures functional impairment, suicidal ideation and suicide attempts [24]. To calculate the total of the scale, it is a question of adding all the scores of the items together. The total score can range from 0 to 27 (0 to 4: no severe depression/5 to 9: mild depression/ 10 to 14: moderate/ 15 to 19: moderately severe/ 20 to 27: Severe) [26].

Statistical analysis

SPSS software v.23 was used to analyze the data. The normality of distribution of the anxiety and depression scores was confirmed since the skewness and kurtosis values fell within the − 2 and + 2 range. Therefore, the Student t test was used to compare two means, whereas the ANOVA test was used to compare three or more means. Correlations between two continuous variables were tested using the Pearson test. Two linear regressions were conducted, taking the anxiety and depression scores as dependent variables.

Regarding suicidal ideation, the Chi-square test was used to compare two categorical variables, whereas the Student t test was used to compare two means. A logistic regression was conducted, taking the presence/absence of suicidal ideation in the last month as the dependent variable. All variables that showed a p < 0.25 in the bivariate analysis were entered as independent ones in the multivariable models. Significance was set at p < 0.05.

Results

The internal reliability of the scales was as follows: total cyberbullying scale (0.892), sexual cyberbullying in cyberspace (0.824), embarrassing and inserting malicious content in cyberspace (0.833), depression (0.875), and anxiety (0.899).

A total of 520 students enrolled in this study. The mean age was 14.05 ± 0.89 years, with 57.7% females. Other details about the sample can be found in Table 2.

Table 2 Sociodemographic and other characteristics of the participants (N = 520)

Bivariate analysis of factors associated with anxiety and depression

Female gender was significantly associated with higher anxiety and mild depression. Having very/extremely hard influence of problems on daily work, sexual cyberbullying in cyberspace, embarrassing and inserting malicious content in cyberspace were associated with higher anxiety and moderate depression. Also, older age was significantly correlated with more anxiety and depression (Table 3).

Table 3 Bivariate analysis of factors associated with anxiety and depression

Multivariable analysis of factors associated with anxiety and depression

The results of the linear regressions taking anxiety and depression as dependent variables, showed that female gender, having kind of hard and very/extremely hard influence of problems on daily work, sexual cyberbullying in cyberspace, embarrassing and inserting malicious content in cyberspace and older age were significantly associated with more anxiety and depression (Table 4).

Table 4 Multivariable analyses

Bivariate analysis of factors associated with suicidal ideation

A higher percentage of females compared to males, of those who have very/extremely hard influence of problems on daily work, sexual cyberbullying in cyberspace, and embarrassing and inserting malicious content in cyberspace was significantly found in adolescents who had suicidal ideation in the last month. Moreover, higher mean age, household crowding index, anxiety and moderate depression were significantly found in adolescents who had suicidal ideation in the last month (Table 5).

Table 5 Bivariate analysis of factors associated with the presence/absence of suicidal ideation in the last month as the dependent variable

Multivariable analysis of factors associated with suicidal ideation

Having kind of hard influence of problems on daily work compared to not at all (aOR = 2.42), higher anxiety (aOR = 1.10), higher depression (aOR = 1.13) and higher household crowding index (aOR = 1.86) were significantly associated with higher odds of having suicidal ideation in the last month (Table 6).

Table 6 Multivariable analysis: Logistic regression using the ENTER model taking the presence/absence of suicidal ideation in the last month as the dependent variable

Discussion

Cyberbullying perpetration, anxiety and depression

Our study showed that sexual cyberbullying perpetrators, and those inserting malicious and embarrassing content in cyberspace have more anxious and depressive symptoms, corroborating the findings of previous studies [9, 27]. The majority of studies in the literature highlighted the effect of bullying victimization and ignored the idea that involvement in sexual bullying has mental health consequences, regardless of involvement as a victim or a perpetrator [28]. Findings suggested that 10% of students in grades 7 to 12 report cyber sexual harassment perpetration [29]. Authors explained that this might be due to increased impulsivity, low empathy, decreased self-esteem, anger, traditional beliefs about masculinity, exposure to pornography, and early sexual initiation [30]. When inserting malicious and embarrassing content and performing cyberbullying, the perpetrator devaluates their victims and therefore, their own worth and self-respect, which increases their anxiety and depression [31]. Additionally, for cyberbullies, the need to harm others originates from lack of empathy [32] indicating lack of social skills [33] and therefore more anxiety and depression [34, 35].

Suicidal ideation

Higher anxiety and depression were shown significantly associated with more suicidal ideation worldwide [36,37,38,39] and specifically among Lebanese [40, 41]. Studies revealed that depressed adolescents experience less pleasure when positively stimulated, but more pleasure in negative experiences; those with suicidal ideation are more prone to appraising positive experiences as negative ones. Also, among adolescents with depressive symptoms the amygdala–hippocampus/brain stem and amygdala–precuneus functions are impaired causing the persistence of depressive symptoms [42] and suicidal ideation among adolescents [43]. Regarding anxiety, worry represents a key indicator of anxiety, and is clinically present among those with suicidal ideation [44]. Despite the various studies showing that anxiety is correlated with suicidal ideation, this association is still inconclusive since anxiety may trigger depressive symptoms associated with suicide [45, 46].

Socio-demographics and mental health

In accordance with previous studies [47, 48], female gender was associated with more anxiety and depression in our study. Researchers explained that this association is due to the onset of ovarian cycling, during adolescence, contributing to increased anxiety and depressive disorders among females. These reproductive events lead to changes in hormones and hormonal metabolites, and therefore affect brain systems and mood regulation [49]. Additionally, our study was conducted during the COVID-19 pandemic, where the vulnerability to anxiety and depression increases among females as compared to males as shown in previous studies, due to the lack of emotional support [50,51,52,53].

Additionally, in line with previous studies conducted in Middle Eastern countries [48, 54], older age was associated with more anxiety and depression in our study. According to researchers, many neurodevelopmental processes that can take place between adolescence and early adulthood, are thought to be correlated with higher levels of anxiety and depression. Modifications to the grey and white matter, such as axonal myelination and increased axon diameter, are examples of neuroplasticity mechanisms allowing environmental experiences to have an impact on brain development, therefore, adolescents became very susceptible to stressful or negative experiences and consequently poorer mental health [55]. Moreover, adolescence and early adulthood are times when persons gain independence, take on responsibilities and often rebel against them, which makes them more susceptible to anxiety and depressive symptoms [56].

Moreover, our findings revealed that higher household crowding index is significantly associated with higher odds of having suicidal ideation, in accordance with previous studies [24, 57, 58]. Researchers raised the question whether household crowding index can directly lead to psychological distress or factors related to housing conditions such as poverty and associated conditions can affect psychological distress. Studies explained that adolescents living in an overcrowded house can develop more mental health illness until their adulthood [59], since they might find it very difficult to escape negative interactions. In addition, the presence of different generations in the same house can increase conflicts or violence [58].

Influence of problems on daily work, anxiety, depression and suicidal ideation

A significant association was found between having kind of hard and very/extremely hard influence of problems on daily work and anxiety and depression in our study. Researchers explained that the probability of repeating a year, dropping out of school or taking special education increases among adolescents with depression [60, 61]. They justified this correlation by reduced self-worth caused by attention reduction, inability to organize work and memory impairment due to depressive and anxious symptoms [62]. Additionally, connectedness to school (i.e. feeling safe, happy, having friends, etc.) reduces the risk of mental health problems, whereas, low school connectedness lead to higher depression, anxiety and bullying [63].

Last but not least, our findings revealed a significant association between hard influence of problems on daily work and suicidal ideation among adolescents. Students who are affected perceive dropping out as a personal failure, and having to repeat a year as a sort of punishment, causing additional stress and consequently more suicidal ideation [64]. Researchers also revealed that students failing coursework and struggling with reading and writing are also at a higher risk of suicidal ideation [64, 65]. Recent studies conducted in Japan [66] and France [67] showed that school closure due to COVID-19 pandemic decreased psychological burdens among adolescents and reduced suicide rates. Authors explained that lockdown disrupt school harassment and social withdrawal and lead to higher feelings of connectedness and belonging, thus, less suicidal ideation [67, 68].

Limitations and strengths

Many limitations can be found in our study. First, the cross-sectional type of the study limiting us from establishing causal relationships between variables. In addition, data obtained was self-reported; responders may have over- or under-estimated some questions, leading to information bias. Other factors related to bullying perpetration have not been assessed in the questionnaire, predisposing us to a confounding bias. The cyber bully/ cyber victim scale used in this paper has not been validated in Lebanon yet. A selection bias is present because of the snowball technique followed to collect the data and the inability to know the refusal rate of participation. Despite these limitations, this study was the first in Lebanon aiming to assess the association between cyberbullying perpetration, and anxiety, depression and suicidal ideation among Lebanese adolescents. Although our results consolidate the findings from international studies, our findings cannot be representative of the whole Lebanese population since our sample was recruited in a convenient way.

Clinical implications

Cyberbullying perpetration and its associated factors reported in this study are significant enough to call for early detection and the creation of prevention strategies for Lebanese adolescents. Females reported higher rates of depression and anxiety than males in our study, which might reflect the need to directly target females with preventative programs developed to be relevant to them. At the school level, effective programs implemented in the school years are needed, aiming to develop social/emotional control, and conflict resolution skills as they might decrease engagement in cyberbullying perpetration among adolescents. Moreover, cyberbullying perpetration in this age group may be avoided by educating families on how to provide appropriate supervision and clear rules and checkup attentively on their kids’ behavior in order to prevent future cyberbullying perpetration.

Conclusion

Our study shed the light on the association between gender, age, hard daily work problems and sexual cyberbullying on adolescents’ mental health. Our findings also highlight that the association between hard problems affecting daily work, higher anxiety, higher depression, higher household crowding index and higher odds of having suicidal ideation. Future studies should try to understand which personality traits, environmental and social variables might predict the engagement of adolescents in cyberbullying perpetration.

Data Availability

All data generated or analyzed during this study are not publicly available to maintain the privacy of the individuals’ identities. The dataset supporting the conclusions is available upon request to the corresponding author.

References

  1. Waseem M, Nickerson AB. Bullying. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 [cited 2022 Jul 18]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK441930/

  2. Cassidy W, Jackson M, Brown KN. Sticks and Stones Can Break my Bones, but how can Pixels Hurt me?: students’ Experiences with Cyber-Bullying. School Psychol Int. 2009 Aug;30(4):383–402.

  3. Kowalski RM, Limber SP. Electronic bullying among middle school students. J Adolesc Health. 2007 Dec;41(6 Suppl 1):22–30.

  4. Lee C, Shin N. Prevalence of cyberbullying and predictors of cyberbullying perpetration among korean adolescents. Comput Hum Behav. 2017 Mar;68:352–8.

  5. Zhu C, Huang S, Evans R, Zhang W. Cyberbullying among adolescents and children: a Comprehensive Review of the Global Situation, Risk factors, and preventive measures. Front Public Health. 2021 Mar;11(9):634909.

  6. Richardson D, Fen CH. Developing a global indicator on bullying of school-aged children [Internet]. UNICEF-IRC. 2018 [cited 2022 Jul 19]. Available from: https://www.unicef-irc.org/publications/979-developing-a-global-indicator-on-bullying-of-school-aged-children.html

  7. Awad E, Haddad C, Sacre H, Hallit R, Soufia M, Salameh P, Obeid S, Hallit S. Correlates of bullying perpetration among lebanese adolescents: a national study. BMC Pediatr. 2021 Apr;28:21:204.

  8. Bilić V, Flander GB, Rafajac B. Life satisfaction and school performance of children exposed to classic and cyber peer bullying. Coll Antropol. 2014 Mar;38(1):21–9.

  9. Kowalski RM, Giumetti GW, Schroeder AN, Lattanner MR. Bullying in the digital age: a critical review and meta-analysis of cyberbullying research among youth. Psychol Bull. 2014 Jul;140(4):1073–137.

  10. Chen L, Ho SS, Lwin MO. A meta-analysis of factors predicting cyberbullying perpetration and victimization: from the social cognitive and media effects approach. New Media & Society. 2017 Aug;19(8):1194–213.

  11. Guo S, A META-ANALYSIS OF THE PREDICTORS OF CYBERBULLYING PERPETRATION. AND VICTIMIZATION: cyberbullying perpetration and victimization. Psychol Schs. 2016 Apr;53(4):432–53.

  12. Bonanno RA, Hymel S. Cyber bullying and internalizing difficulties: above and beyond the impact of traditional forms of bullying. J Youth Adolesc. 2013 May;42(5):685–97.

  13. Daine K, Hawton K, Singaravelu V, Stewart A, Simkin S, Montgomery P. The power of the web: a systematic review of studies of the influence of the internet on self-harm and suicide in Young People. García AV. editor PLoS ONE. 2013 Oct;30(10):e77555.

  14. Bitar Z, Hallit S, Khansa W, Obeid S. Phubbing and temperaments among young Lebanese adults: the mediating effect of self-esteem and emotional intelligence. BMC Psychol. 2021 May 22;9(1):87.

  15. Wiederhold BK. Social Media Use during Social Distancing. Cyberpsychology, Behavior, and Social Networking. 2020;23(5):275–6.

  16. El Frenn Y, Hallit S, Obeid S, Soufia M. Association of the time spent on social media news with depression and suicidal ideation among a sample of Lebanese adults during the COVID-19 pandemic and the Lebanese economic crisis. Curr Psychol [Internet]. 2022 May 13 [cited 2022 Jul 23]; Available from: https://doi.org/10.1007/s12144-022-03148-1

  17. Youssef L, Hallit R, Kheir N, Obeid S, Hallit S. Social media use disorder and loneliness: Any association between the two? Results of a cross-sectional study among Lebanese adults.BMC Psychology. 2020 Jun 1

  18. Chahine M, Salameh P, Haddad C, Sacre H, Soufia M, Akel M, Obeid S, Hallit R, Hallit S. Suicidal ideation among lebanese adolescents: scale validation, prevalence and correlates. BMC Psychiatry. 2020 Jun;15(1):304.

  19. Sfeir E, Geara C, Hallit S, Obeid S. Alexithymia, aggressive behavior and depression among lebanese adolescents: a cross-sectional study. Child Adolesc Psychiatry Ment Health. 2020;14:32.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Melki IS. Household crowding index: a correlate of socioeconomic status and inter-pregnancy spacing in an urban setting. J Epidemiol Community Health. 2004 Jun;58(1):476–80.

  21. Horzum mehmet barış. CYBER BULLY/VICTIM SCALE DEVELOPMENT STUDY. Akademik Bakış.2010 Jan1;19:1–17.

  22. Hallit S, Obeid S, Haddad C, Hallit R, Akel M, Haddad G, Soufia M, Khansa W, Khoury R, Kheir N, Abi Elias Hallit C, Sacre H, Salameh P. Construction of the lebanese anxiety scale (LAS-10): a new scale to assess anxiety in adult patients. Int J Psychiatry Clin Pract. 2020 Sep;24(3):270–7.

  23. Merhy G, Azzi V, Salameh P, Obeid S, Hallit S. Anxiety among Lebanese adolescents: scale validation and correlates. BMC Pediatr. 2021 Jun 22;21(1):288.

  24. Johansson LM, Sundquist J, Johansson SE, Qvist J, Bergman B. The influence of ethnicity and social and demographic factors on swedish suicide rates. A four year follow-up study. Soc Psychiatry Psychiatr Epidemiol. 1997 Apr;32(3):165–70.

  25. Al-Amer R, Maneze D, Ramjan L, Villarosa AR, Darwish R, Salamonson Y. Psychometric testing of the arabic version of the Patient Health Questionnaire among adolescent refugees living in Jordan. Int J Ment Health Nurs. 2020 Aug;29(4):685–92.

  26. APA_DSM5_Severity-Measure-For-Depression-Child-Age-11-to-17.pdf [Internet]. [cited 2023 Jan 8]. Available from: https://www.psychiatry.org/File%20Library/Psychiatrists/Practice/DSM/APA_DSM5_Severity-Measure-For-Depression-Child-Age-11-to-17.pdf

  27. Ojeda M, Del Rey R, Hunter SC. Longitudinal relationships between sexting and involvement in both bullying and cyberbullying. J Adolesc. 2019 Dec;77:81–9.

  28. Bucchianeri MM, Eisenberg ME, Wall MM, Piran N, Neumark-Sztainer D. Multiple types of harassment: Associations with Emotional Well-Being and unhealthy behaviors in adolescents. J Adolesc Health. 2014 Jun;54(6):724–9.

  29. Hill C, Kearl H. Crossing the Line: Sexual Harassment at School [Internet]. American Association of University Women. American Association of University Women; 2011 [cited 2022 Jul 25]. Available from: https://eric.ed.gov/?id=ED525785

  30. Leemis RW, Espelage DL, Basile KC, Mercer Kollar LM, Davis JP. Traditional and cyber bullying and sexual harassment: a longitudinal assessment of risk and protective factors. Aggress Behav. 2019 Mar;45(2):181–92.

  31. Rinehart SJ, Espelage DL, Bub KL. Longitudinal Effects of Gendered Harassment Perpetration and victimization on Mental Health Outcomes in Adolescence. J Interpers Violence. 2020 Dec;35(23–24):5997–6016.

  32. Ang RP, Goh DH. Cyberbullying among adolescents: the role of Affective and Cognitive Empathy, and gender. Child Psychiatry Hum Dev. 2010 Aug;41(4):387–97.

  33. Savage MW, Tokunaga RS. Moving toward a theory: testing an integrated model of cyberbullying perpetration, aggression, social skills, and internet self-efficacy. Comput Hum Behav. 2017 Jun;71:353–61.

  34. Calandri E, Graziano F, Testa S, Cattelino E, Begotti T, Empathy. and Depression Among Early Adolescents: The Moderating Role of Parental Support. Frontiers in Psychology [Internet]. 2019 [cited 2022 Jul 25];10. Available from: https://www.frontiersin.org/articles/https://doi.org/10.3389/fpsyg.2019.01447

  35. Gambin M, Sharp C. Relations between empathy and anxiety dimensions in inpatient adolescents. Anxiety, Stress, & Coping. 2018 Jul 4;31(4):447–58.

  36. Boden JM, Fergusson DM, John Horwood L. Anxiety disorders and suicidal behaviours in adolescence and young adulthood: findings from a longitudinal study. Psychol Med. 2007 Mar;37(03):431.

  37. Gledhill J, Hodes M. Depression and suicidal behaviour in children and adolescents.Psychiatry. 2008Aug;7(8):335–9.

  38. Izadinia N, Amiri M, Jahromi R, ghorban, Hamidi S. A study of relationship between suicidal ideas, depression, anxiety, resiliency, daily stresses and mental health among Tehran university students. Procedia - Social and Behavioral Sciences. 2010;5:1615–9.

    Article  Google Scholar 

  39. Nguyen Thi Khanh H, Nguyen Thanh L, Pham Quoc T, Pham Viet C, Duong Minh D, Le Thi Kim A. Suicidal behaviors and depression “among adolescents in Hanoi, Vietnam: A multilevel analysis of data from the Youth Risk Behavior Survey 2019. Health Psychol Open. 2020 Sep 11;7(2):2055102920954711.

  40. Farran N. Mental health in Lebanon: tomorrow’s silent epidemic. Ment Health Prev. 2021 Dec;24:200218.

  41. Zakhour M, Haddad C, Sacre H, Fares K, Akel M, Obeid S, Salameh P, Hallit S. Suicidal ideation among Lebanese adults: scale validation and correlates.BMC Psychiatry. 2021 Feb16;21(1):100.

  42. Cullen KR, Westlund MK, Klimes-Dougan B, Mueller BA, Houri A, Eberly LE, Lim KO. Abnormal Amygdala Resting-State Functional Connectivity in Adolescent Depression. JAMA Psychiatry. 2014 Oct 1;71(10):1138.

  43. Alarcón G, Sauder M, Teoh JY, Forbes EE, Quevedo K. Amygdala Functional Connectivity during Self-Face Processing in Depressed Adolescents with recent suicide attempt. J Am Acad Child Adolesc Psychiatry. 2019 Feb;58(2):221–31.

  44. Ibrahim N, Amit N, Suen MWY. Psychological Factors as Predictors of Suicidal Ideation among Adolescents in Malaysia. Mazza M, editor. PLoS ONE. 2014 Oct 23;9(10):e110670.

  45. Malik S, Kanwar A, Sim LA, Prokop LJ, Wang Z, Benkhadra K, Murad MH. The association between sleep disturbances and suicidal behaviors in patients with psychiatric diagnoses: a systematic review and meta-analysis. Syst Reviews. 2014 Feb;25(1):18.

  46. McDowell AK, Lineberry TW, Bostwick JM. Practical Suicide-Risk Management for the Busy Primary Care Physician. Mayo Clinic Proceedings. 2011 Aug;86(8):792–800.

  47. AlFaris E, Irfan F, Qureshi R, Naeem N, Alshomrani A, Ponnamperuma G, Al Yousufi N, Al Maflehi N, Al Naami M, Jamal A, van der Vleuten C. Health professions’ students have an alarming prevalence of depressive symptoms: exploration of the associated factors. BMC Med Educ. 2016 Oct 21;16(1):279.

  48. Alkhadhari S, Alsabbrri AO, Mohammad IHA, Atwan AA, Alqudaihi F, Zahid MA. Prevalence of psychiatric morbidity in the primary health clinic attendees in Kuwait. J Affect Disord. 2016 May;195:15–20.

  49. Altemus M, Sarvaiya N, Epperson CN. Sex differences in anxiety and depression clinical perspectives. Front Neuroendocrinol. 2014 Aug;35(3):320–30.

  50. Herrera-Añazco P, Urrunaga-Pastor D, Benites-Zapata VA, Bendezu-Quispe G, Toro-Huamanchumo CJ, Hernandez AV. Gender Differences in Depressive and Anxiety Symptoms During the First Stage of the COVID-19 Pandemic: A Cross-Sectional Study in Latin America and the Caribbean. Frontiers in Psychiatry [Internet]. 2022 [cited 2022 Jul 25];13. Available from: https://www.frontiersin.org/articles/https://doi.org/10.3389/fpsyt.2022.727034

  51. Salari N, Hosseinian-Far A, Jalali R, Vaisi-Raygani A, Rasoulpoor S, Mohammadi M, Rasoulpoor S, Khaledi-Paveh B. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis. Global Health. 2020 Dec;16(1):57.

  52. Xiong J, Lipsitz O, Nasri F, Lui LMW, Gill H, Phan L, Chen-Li D, Iacobucci M, Ho R, Majeed A, McIntyre RS. Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J Affect Disord. 2020 Dec;277:55–64.

  53. El Othman R, Touma E, El Othman R, Haddad C, Hallit R, Obeid S, Salameh P, Hallit S. COVID-19 pandemic and mental health in Lebanon: a cross-sectional study. Int J Psychiatry Clin Pract. 2021 Jun;25(1):152–63.

  54. Abu-Bader S, Hamed E, Alqdah T. Prevalence of Depression among Older Arab Individuals in the Middle East: A Study of Egypt and Jordan.Journal of Muslim Mental Health. 2017 Aug 17;11.

  55. Blakemore SJ. Adolescence and mental health. The Lancet. 2019 May;18(10185):2030–1.

  56. Jurewicz I. Mental health in young adults and adolescents – supporting general physicians to provide holistic care. Clin Med (Lond). 2015 Apr;15(2):151–4.

  57. Gray AP, Richer F, Harper S. Individual- and community-level determinants of Inuit youth mental wellness.Can J Public Health. 2016 Oct20;107(3):e251–7.

  58. Pepin C, Muckle G, Moisan C, Forget-Dubois N, Riva M. Household overcrowding and psychological distress among Nunavik Inuit adolescents: a longitudinal study. Int J Circumpolar Health. 2018 Nov 1;77(1):1541395.

  59. Rajaleid K, Nummi T, Westerlund H, Virtanen P, Gustafsson PE, Hammarström A. Social adversities in adolescence predict unfavourable trajectories of internalized mental health symptoms until middle age: results from the Northern Swedish Cohort. Eur J Public Health. 2016 Feb;26(1):23–9.

  60. Quiroga CV, Janosz M, Lyons JS, Morin AJS. Grade Retention and Seventh-Grade Depression symptoms in the course of School Dropout among high-risk adolescents. Psychology. 2012 Sep;25(09):749.

  61. Robles-Piña RA, Defrance E, Cox DL. Self-Concept, Early Childhood Depression and School Retention as Predictors of Adolescent Depression in Urban Hispanic Adolescents.School Psychology International. 2008 Oct1;29(4):426–41.

  62. Owens M, Stevenson J, Hadwin JA, Norgate R. Anxiety and depression in academic performance: An exploration of the mediating factors of worry and working memory. School Psychology International. 2012 Aug 1;33(4):433–49.

  63. Schulte-Körne G. Mental Health problems in a School setting in children and adolescents. Dtsch Arztebl Int. 2016 Mar;113(11):183–90.

  64. Daniel SS, Walsh AK, Goldston DB, Arnold EM, Reboussin BA, Wood FB. Suicidality, School Dropout, and reading problems among adolescents. J Learn Disabil. 2006 Nov;39(1):507–14.

  65. Kosidou K, Dalman C, Fredlund P, Magnusson C. School Performance and the risk of suicidal thoughts in young adults: Population-Based study. PLoS ONE. 2014 Oct;27(10):e109958.

  66. Tanaka T, Okamoto S. Increase in suicide following an initial decline during the COVID-19 pandemic in Japan. Nat Hum Behav. 2021 Feb;5(2):229–38.

  67. Mourouvaye M, Bottemanne H, Bonny G, Fourcade L, Angoulvant F, Cohen JF, Ouss L. Association between suicide behaviours in children and adolescents and the COVID-19 lockdown in Paris, France: a retrospective observational study. Arch Dis Child. 2021 Sep;106(9):918–9.

  68. Carballo JJ, Llorente C, Kehrmann L, Flamarique I, Zuddas A, Purper-Ouakil D, Hoekstra PJ, Coghill D, Schulze UME, Dittmann RW, Buitelaar JK, Castro-Fornieles J, Lievesley K, Santosh P, Arango C, STOP Consortium. Psychosocial risk factors for suicidality in children and adolescents. Eur Child Adolesc Psychiatry. 2020 Jun;29(6):759–76.

Download references

Acknowledgements

The authors would like to thank all students who participated in this study.

Funding

None.

Author information

Authors and Affiliations

Authors

Contributions

MBE involved in study design. ZB wrote the manuscript. SH involved in data analysis and interpretation. MBE collected the data and helped with the writing. SO and all authors reviewed the paper for intellectual content. All authors approved its final version.

Corresponding authors

Correspondence to Souheil Hallit or Sahar Obeid.

Ethics declarations

Ethical approval and consent to participate

The study protocol was approved by the ethics committee of the Lebanese International University (2021RC-045-LIUSOP). Students were asked to get their parents’ consent before filling the survey. Submitting the form online was considered equivalent to obtaining a written informed consent. Hence, written informed consent was taken from all participants/ their parents/legal guardians for minors to participate in the study. All methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

None to declare.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Zeinab Bitar and Marie-Belle Elias are first coauthors.

Sahar Obeid and Souheil Hallit are last coauthors.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bitar, Z., Elias, MB., Malaeb, D. et al. Is cyberbullying perpetration associated with anxiety, depression and suicidal ideation among lebanese adolescents? Results from a cross-sectional study. BMC Psychol 11, 53 (2023). https://doi.org/10.1186/s40359-023-01091-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40359-023-01091-9

Keywords