Why did You do that to Me?: a Systematic Review of Cyberbullying Impact on Mental Health and Suicide Among Adolescents

Abstract

With the new implementation of distance learning, adolescents have more time to access the internet. Lack of surveillance from parental figures and developing senses of mental stability make adolescents susceptible to the negative influence of the internet such as cyberbullying. This systematic literature review aims to examine the incidence of cyberbullying and its effect on the risk of mental health disorders and suicide among adolescents during the COVID-19 pandemic. A total of 10 cross-sectional studies were sorted out from major electronic journal databases: PubMed, Science Direct, BMC, Sage Journal, and Google Scholar using the following search term combinations: “adolescents” “cyberbullying” “suicide” “depression”. The range for adolescents age was 11-18 years. These studies identified and examined general internet use, the experience of cyberbullying, effects on mental health disorder, and risk of suicide published from January 2020 to July 2021. Cyber victimization was positively associated with stress, suicidal ideation, and avoidance which is also a significant predictor of self-harm. Adolescents who experienced cyberbullying were 2-3.14 times more likely to report experiencing suicidal ideations. Suicidal attempts were significantly 2.14 times higher on adolescents who have cyberbullying experience. Previously victimized adolescents have a 15.5% higher chance of being cyberbullied. Internet usage and addiction have direct effects on mediating cyber victimization and adolescents’ psychological symptoms. This study has given broader insight into how cyberbullying can affect mental health in adolescents and identify the gaps for further longitudinal research on cyberbullying among adolescents.

Children’s Online Safety: Predictive Factors of Cyberbullying and Online Grooming Involvement

“…Indeed, the Kaiser-Meyer-Olkin tests returned an overall value of Measure of Sampling Adequacy (MSA) above 0.7, meaning that the variables are adequate for factor analysis [73]; moreover, Bartlett's test result was significant, meaning that the correlation matrix has significant correlations among at least some of the variables in a dataset, a prerequisite for factor analysis to work. Given that factor analysis is well suited for our data, we implemented factor analysis (function factanal in the stats R package) [74], by letting the number of factors range in [2,10]. In this way, by using the scree plot (number of factors vs. resulting eigenvalue) and the elbow method, we realized that the optimal number of factors is seven; although, a better interpretation of the results is reached by using only four factors, which still achieve good performance in terms of explained variance.…”

“…According to the finding of a study coordinated by the Joint Research Centre of the European Commission, with data from eleven European countries collected between June and August 2020, Italy was among the highest ranked in terms of increase in cyberbullying victimisation rates and in the exposure of children to gory or violent content during the COVID-19 spring lockdown [4]. For this reason, in recent years, research interest in cyberbullying is growing and studies attempting to measure its spread [3,5], to identify the main risk and protective factors [6][7][8] and to study its psychophysical consequences compared to those of traditional bullying [9,10] have proliferated. However, the different definitions adopted by researchers and, consequently, the variety of measurement tools and research methodologies employed have often led to inconsistent results.…”