An umbrella review of the prevalence, characteristics, and impacts of cyberbullying among elementary students | #childpredator | #kidsaftey | #childsaftey

Abstract

Cyberbullying is an escalating public health and educational concern that increasingly affects children at younger ages. While global research has expanded, evidence focused on elementary students in developing countries remains fragmented. This umbrella review synthesizes empirical studies examining cyberbullying among elementary school children in low-and-middle income contexts. Guided by PRISMA 2020 standards, records pertaining to the assessment of prevalence, mental health consequences, risk and protective factors, and prevention and intervention strategies were retrieved from multiple databases (Scopus, Web of Science, PubMed, EMBASE, PsycINFO, and ERIC) and exported into a reference manager, where automatic deduplication was performed prior to screening. Due to unified export and deduplication, per-database yield disaggregation was not retained. Findings indicate wide variability in prevalence estimates due to definitional and measurement inconsistencies, with emerging evidence suggesting elevated rates in urban settings. Cyberbullying is consistently associated with anxiety, depressive symptoms, and academic disengagement. However, culturally validated instruments and context specific intervention models remain limited. The review highlights the need for developmentally appropriate frameworks, standardized measurement approaches, and integrated school-based prevention strategies tailored to resource constrained environments.

1 Introduction

Cyberbullying has become a significant public health and educational concern in the digital era. The expansion of internet connectivity, mobile device ownership, and social media engagement has reshaped patterns of peer interaction among children and adolescents. While digital technologies have enhanced access to information and communication, they have also facilitated new forms of interpersonal aggression. Cyberbullying differs from traditional bullying in its persistence, reach, and potential anonymity. Harmful content can be disseminated rapidly, remain accessible indefinitely, and transcend physical boundaries. These features intensify victim exposure and complicate prevention and response mechanisms. Globally, cyberbullying victimization among school aged children is estimated at approximately 11 percent, with considerable variation across regions and measurement approaches (Li et al., 2022). Evidence suggests that cyberbullying frequently co-occurs with traditional bullying, with overlapping victim profiles and shared psychosocial risk factors. Victimization has been associated with anxiety, depressive symptoms, reduced academic engagement, sleep disturbances, and suicidal ideation (Gaffney et al., 2019). The cumulative burden is substantial, particularly when exposure occurs during formative developmental stages.

Elementary school represents a critical period marked by identity formation, peer affiliation, emotional regulation development, and early digital socialization. Children are now introduced to online environments at increasingly younger ages, often before acquiring the cognitive and socioemotional skills necessary to manage digital conflict. Early exposure to cyberbullying may disrupt developmental trajectories, undermine school adjustment, and shape long term patterns of social vulnerability. Despite this, research attention has disproportionately focused on adolescents, implicitly assuming that meaningful online aggression emerges later in development. The elementary years remain comparatively underexamined. The contextual dimension further sharpens the concern. In many developing countries, digital expansion has outpaced the development of regulatory frameworks, school based digital literacy programs, and accessible mental health services. Rapid urbanization, high youth population density, and uneven access to support systems compound vulnerability. Preliminary studies from parts of Southeast Asia and Latin America indicate rates that may exceed global averages in some urban school settings (Ngo et al., 2021). However, surveillance systems are often weak, and national level data remain limited. Consequently, prevalence estimates may be conservative and fragmented.

Methodological limitations constrain current knowledge. Definitions of cyberbullying vary in their treatment of repetition, intent, and power imbalance. Measurement tools differ in recall periods and platform coverage. Many instruments have not been culturally validated in low and middle income contexts. Studies frequently rely on cross sectional designs and single site samples, limiting causal inference and generalizability. Moreover, intervention research remains sparse at the elementary level. Existing programs are often adapted from adolescent or traditional bullying models without accounting for platform specific dynamics such as anonymity, algorithmic amplification, and digital permanence. Evidence regarding context appropriate prevention strategies in resource constrained school systems is limited. Taken together, three interrelated gaps are evident. First, there is insufficient synthesis focused specifically on elementary students, despite earlier digital exposure and distinct developmental vulnerabilities. Second, empirical evidence from developing countries remains fragmented and under-integrated, obscuring regional patterns and context specific determinants. Third, inconsistencies in conceptualization and measurement hinder reliable prevalence estimation and the identification of effective prevention and intervention approaches.

This umbrella review addresses these gaps by synthesizing empirical evidence on cyberbullying among elementary students in developing countries. It examines prevalence patterns, mental health consequences, risk and protective factors, and the effectiveness of prevention and intervention strategies. Guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 standards and drawing from Scopus and Web of Science indexed studies, the review seeks to clarify conceptual inconsistencies, identify context sensitive insights, and inform policy, school practice, and future research in settings where digital expansion intersects with structural vulnerability.

2 Research methodology

2.1 Search strategy and information sources

This umbrella review followed the PRISMA 2020 guidelines. Comprehensive electronic searches were conducted across multiple databases including PubMed, EMBASE, Web of Science, Scopus, PsycINFO, and ERIC, utilizing controlled vocabulary and Boolean operators combining concepts related to cyberbullying, bullying, elementary students, school-age children, mental health impacts, intervention effectiveness, and developing countries. Search terms included: (“cyberbully” OR “cyber bully” OR “cyber-bully” OR “online bullying” OR “electronic bullying” OR “social media harassment”) AND (”elementary school” OR “primary school” OR “grade school” OR “school-aged children” OR “young people” OR “adolescent”) AND (“developing countr” OR “low-income countr” OR “middle-income countr” OR “LMIC” OR “Asia” OR “Africa” OR “Latin America” OR “Caribbean” OR “South Asia” OR “Southeast Asia”).

Search terms were adapted for each database to accommodate their specific indexing systems. Additional search strategies included hand-searching reference lists from included studies, consulting with experts in the field, and reviewing relevant organization websites (i.e., WHO, UNESCO, UNICEF). The searches were conducted between January 2010 and December 2024, with no language restrictions during initial screening (though final review was limited to English-language publications due to resource constraints).

2.2 Eligibility criteria

This review applied clear inclusion and exclusion criteria to ensure methodological rigor and contextual relevance (Table 1). Included studies were peer reviewed articles published in Q1 Scopus indexed or Web of Science indexed journals. Eligible designs comprised quantitative, qualitative, mixed methods, and meta analytic studies. Studies were required to explicitly examine cyberbullying, online bullying, cybervictimization, or related forms of online aggression. Only research conducted in developing countries, based on World Bank classification, or involving populations from developing countries was considered. The review focused on elementary or primary school students, typically aged 5 to 13 years, although some studies including older elementary students up to 14 or 15 years were retained. Articles had to report prevalence, mental health outcomes, risk or protective factors, intervention effectiveness, or implementation findings. A minimum sample size of 30 participants was required, with exceptions for qualitative studies and case series that included at least 14 participants.

Studies were excluded if they focused solely on high income countries without comparison to developing contexts, or if they examined university or adult populations. Case reports, editorials, opinion papers, and theoretical works without empirical data were omitted. Research addressing cyberstalking, online child exploitation, or other online harms that did not meet bullying definitions was excluded. Non English publications were not considered due to resource limitations. Studies published before 2010 were also excluded to ensure contemporary relevance.

2.3 Study selection and data extraction

Two independent reviewers screened all titles and abstracts against eligibility criteria using Covidence umbrella review software. Studies deemed potentially relevant underwent full-text review by paired assessors. A standardized, pilot-tested data extraction form captured the following: author and publication year; country and geographic region; study design (i.e., RCT, quasi-experimental, cross-sectional, qualitative, meta-analysis); participant characteristics including age, gender, socioeconomic status, ethnicity; sample size; cyberbullying assessment method and outcome measures; prevalence rates; mental health outcomes and effect sizes; intervention characteristics; study quality indicators; and author conclusions. Disagreements regarding study inclusion or data extraction were resolved through discussion or third-reviewer consultation. A data extraction manual ensured consistency across reviewers.

2.4 Quality assessment and risk of bias

Risk of bias was assessed using (1) Cochrane Risk of Bias 2 (RoB 2) tool for randomized controlled trials, (2) ROBINS-I tool for non-randomized studies, (3) AMSTAR 2 for systematic reviews and meta-analyses, and (4) GRADE framework for certainty of evidence assessment. Two independent reviewers assessed quality, with disagreements resolved by consensus. Studies were classified as low, some concerns, or high risk of bias. Quality assessment addressed: randomization adequacy, blinding of participants/assessors, outcome measurement validity, selective reporting, attrition, and other sources of bias specific to cyberbullying research (e.g., reliance on self-report measures, potential social desirability bias).

3 Study characteristics and evidence landscape

3.1 Systematic search results and study selection

The comprehensive electronic search strategy yielded 876 unique citations after removing duplicates from 1,247 original records. Title and abstract screening resulted in 142 articles deemed potentially relevant. Full-text review of these articles identified 50 studies meeting all inclusion criteria for narrative synthesis, with 28 studies contributing to quantitative syntheses (meta-analyses). The PRISMA flow diagram in Figure 1 illustrates this selection process.

Reasons for exclusion of the remaining 92 articles were: (1) focus on secondary school or adolescent students rather than elementary/primary school students (n = 31); (2) conducted exclusively in high-income countries (n = 24); (3) insufficient focus on cyberbullying or online harassment (n = 18); (4) inadequate sample size or study design (n = 12); (5) duplicate publications or secondary analyses (n = 7).

3.2 Characteristics of included studies

The 50 included studies comprised diverse designs: 12 meta-analyses, 8 systematic reviews, 15 quantitative surveys/cross-sectional studies, 10 qualitative studies, 3 mixed-methods studies, and 2 quasi-experimental evaluations. Geographic distribution revealed: 8 studies from East Asia (China, Taiwan, Japan, South Korea), 6 from South Asia (India, Indonesia, Bangladesh, Pakistan), 5 from Southeast Asia (Vietnam, Philippines, Thailand), 4 from sub-Saharan Africa (Ethiopia, Nigeria, Kenya, Uganda), 3 from Latin America (Brazil, Chile, Mexico), and 24 global meta-analyses and multi-country studies. Total sample sizes ranged from 14 participants (qualitative studies) to 266,888 participants in meta-analytic reviews (Li et al., 2022).

Study designs demonstrated substantial methodological heterogeneity regarding cyberbullying measurement, mental health assessment tools, and outcome variables (Table 2). Cyberbullying assessment employed: Revised Olweus Bully/Victim Questionnaire, custom-developed surveys, social media monitoring, peer nomination procedures, and self-report inventories measuring frequency, duration, and forms of victimization and perpetration. Mental health outcomes were assessed using standardized instruments (Patient Health Questionnaire-9, Generalized Anxiety Disorder Scale-7, Beck Depression Inventory, Strengths and Difficulties Questionnaire) and custom measures. Publication dates ranged from 2010 to 2024, reflecting the evolving research landscape. Publication bias assessment using funnel plots and Egger’s regression suggested minimal publication bias across meta-analytic reviews.

3.3 Synthesis of study quality and evidence certainty

Using GRADE methodology, the certainty of evidence varied by outcome (Table 3). For depression and anxiety outcomes in association with cyberbullying, evidence was rated as high certainty (based on multiple meta-analyses with large sample sizes and consistent findings across populations). For suicidal ideation and self-harm outcomes, evidence was moderate-to-high certainty (fewer studies, but consistent effect directions and magnitudes). For school-based intervention effectiveness, evidence was moderate certainty (heterogeneous intervention types, variable follow-up periods, and modest effect sizes). For implementation factors in developing countries, evidence was low-to-moderate certainty (limited number of studies, most conducted in higher-income countries with limited adaptation for developing contexts).

4 Prevalence, epidemiology, and characterization of cyberbullying

4.1 Global prevalence and regional variations

Cyberbullying victimization affects a substantial proportion of school-age children globally, with meta-analytic estimates indicating pooled prevalence of 11.10% (95% CI: 9.12–13.44%) across diverse populations (Li et al., 2022). However, these aggregate estimates mask substantial heterogeneity across geographic regions, measurement approaches, and age groups. A meta-analysis examining 42 studies with 266,888 participants found victimization prevalence rates ranging from 2% to 72%, with highest rates in South and Southeast Asia (15%–25%), intermediate rates in East Asia (8%–15%), and more variable patterns in Africa and Latin America (Li et al., 2022) (Table 4).

The three-month prevalence of cyberbullying victimization among urban adolescents in Vietnam was estimated at 11.6%, with an additional 28.3% reporting observation of cyberbullying incidents (Ngo et al., 2021). Among Taiwanese high school students, qualitative interviews revealed cyberbullying as common, frequently occurring anonymously on social media platforms (Wang et al., 2019). In Indonesia, mental health problems among adolescents were significantly elevated, with cyberbullying-related harassment contributing substantially to these difficulties (Pandia et al., 2021).

Traditional bullying victimization demonstrates even higher prevalence at 24.32% (95% CI: 20.32–28.83%) globally (Li et al., 2022). The relationship between traditional and cyberbullying victimization reveals critical epidemiological patterns: approximately 33% of traditional bullying victims also experience cyberbullying, while conversely, only about 33% of cyberbullying victims are free from traditional bullying victimization. This overlap suggests that targeting one form of bullying in prevention efforts may have spillover benefits, as approximately 8% of students experience both forms concurrently.

4.2 Forms, perpetration patterns, and gender differences

Cyberbullying manifests in diverse forms reflecting the affordances of digital platforms (Table 5). Most common forms include: (1) spread of rumors or harmful information (cited in 73% of studies); (2) exclusion from online groups or activities; (3) sending threatening or demeaning messages; (4) sharing embarrassing photos or videos without consent; (5) impersonation or identity theft; (6) unwanted contact or sexual harassment (Lahti et al., 2024). Notably, exclusion appears particularly damaging in collectivistic Asian societies where interpersonal harmony is highly valued, producing isolation, helplessness, and hopelessness in victims (Wang et al., 2019).

Cyberbullying perpetration rates are considerably lower than victimization rates, with estimates suggesting 2.8–5.2% of students engage in cyberbullying behaviors (Li et al., 2022). However, this distinction between perpetrators and victims is less clear-cut than in traditional bullying, as some individuals simultaneously engage in perpetration and experience victimization (bully-victims). Perpetration is often motivated by entertainment, revenge, jealousy, discrimination, or punishment of peers perceived as violating social norms (Wang et al., 2019).

Gender differences in cyberbullying show nuanced patterns. While some studies show no significant gender differences in overall victimization prevalence (Lahti et al., 2024), others indicate that females experience higher rates of certain cyberbullying forms, particularly those involving social exclusion, rumor-spreading, appearance-based harassment, and sexual content (Rajkumar et al., 2022). Males demonstrate somewhat higher perpetration rates and more frequently engage in aggressive messaging and group-based bullying. These gender differences likely reflect broader sociocultural patterns regarding online communication styles, peer dynamics, and gender norms (Wang et al., 2023).

4.3 Age-Related patterns and developmental considerations

Cyberbullying risk peaks during early adolescence (ages 11–15 years), though as elementary students increasingly access digital technologies, victimization at younger ages (9–11 years) has become more prevalent (Gaffney et al., 2019) (Table 6). This age group demonstrates particular vulnerability due to: (1) limited digital literacy and online safety knowledge; (2) developing executive function and emotional regulation capacities; (3) heightened sensitivity to peer influence and social comparison; (4) greater impulsivity in online interactions; (5) limited awareness of permanence and reach of online communications.

In developing countries, the age-prevalence relationship may differ from developed country patterns due to: (1) variable digital access concentrated among older elementary and younger secondary students; (2) limited digital literacy education; (3) different patterns of social media platform adoption; (4) varying developmental trajectories related to socioeconomic factors. Longitudinal research from developing countries remains sparse, making precise age-prevalence trajectories difficult to establish (Meherali et al., 2021).

5 Mental health and psychosocial consequences of cyberbullying victimization

5.1 Depression and anxiety: prevalence and associations

Cyberbullying victimization demonstrates robust associations with depression and anxiety disorders across multiple studies and populations (Table 7). Meta-analytic evidence from 42 studies with 266,888 participants indicates that cyberbullying victims are 1.85 times more likely to experience depressive symptoms (95% CI: 1.62–2.11) and 1.72 times more likely to experience anxiety symptoms (95% CI: 1.51–1.97) compared to non-victimized peers (Li et al., 2022). These effect sizes remain statistically significant and clinically meaningful even after controlling for traditional bullying and other potential confounds.

In developing countries, baseline rates of depression and anxiety may be elevated due to socioeconomic adversity, limited access to mental health services, and exposure to other environmental stressors, making cyberbullying an additional burden on already vulnerable populations (Chen et al., 2022a, b). Among rural Indian adolescents, a meta-analysis of 35 studies found overall depression and anxiety prevalence at 12%–18%, with online interactions and social media usage contributing to these difficulties (Rajkumar et al., 2022). The temporal relationship between cyberbullying and affective disorders remains complex; some evidence suggests cyberbullying precipitates affective onset, while bidirectional relationships are also plausible, with pre-existing depression/anxiety increasing cyberbullying vulnerability (Chen et al., 2022a, b).

5.2 Suicidal ideation and self-harm: high-risk outcomes

Among the most concerning consequences of cyberbullying victimization are suicidal ideation and self-harm behaviors. Meta-analytic evidence demonstrates that cyberbullying victims are 1.95 times more likely to report suicidal ideation (95% CI: 1.68–2.27) and 1.42 times more likely to engage in self-harm behaviors (95% CI: 1.21–1.67), with dose-dependent relationships observed (Li et al. 2022). Risk and protective factors of self-harm and suicidality in adolescents demonstrates that bullying victimization ranks as the most attributed environmental exposure for suicidality, with particular vulnerability in sexual and gender minority youth (Richardson et al., 2024).

School-based suicide prevention interventions show significant protective effects, reducing suicidal ideation (OR = 0.87, 95% CI) and suicide attempts (OR = 0.66, 95% CI) by 13% and 34% respectively (Walsh et al., 2022). These interventions demonstrate particular effectiveness when implemented over extended periods (≥12 months), involving multiple stakeholders, and targeting suicidal thoughts and behaviors as primary outcomes.

In developing countries, where mental health services are severely limited and suicide prevention infrastructure is underdeveloped, cyberbullying-induced suicidality may have particularly severe consequences. The absence of accessible mental health services, combined with cultural stigma around suicide, may result in underreporting and inadequate intervention (Grande et al., 2023).

5.3 Psychosocial consequences: self-esteem, social isolation, academic impact

Beyond clinical mental health disorders, cyberbullying produces constellation of psychosocial difficulties including: (1) reduced self-esteem and negative self-perception; (2) social isolation and loneliness; (3) academic performance decline; (4) sleep disturbances and fatigue; (5) increased alcohol and substance use; (6) school avoidance and truancy (Gabrie lli et al., 2022; Yosep et al., 2023). These consequences extend beyond immediate victimization period, with longitudinal research suggesting cyberbullying can disrupt normative developmental trajectories and interfere with identity formation and peer relationship development.

Academic impairment is particularly significant in developing countries where educational opportunities are more limited, and educational achievement has substantial implications for socioeconomic mobility. Cyberbullying victimization may indirectly perpetuate educational inequity by creating barriers to academic success for vulnerable students, particularly those already disadvantaged by poverty or limited home support (Grande et al., 2023).

Peer-victimization research demonstrates that school support acts as significant buffer against mental health consequences, being effective in both male and female adolescents, with importance increasing in older students (Stadler et al., 2010). Parental support appears particularly protective for victimized girls entering secondary school. Since effects of peer-victimization can be substantially reduced through parental and school support, educational interventions and family engagement become critically important.

6 Risk factors and vulnerability in developing country contexts

6.1 Individual and behavioral risk factors

Individual characteristics significantly influence susceptibility to cyberbullying victimization. Pre-existing mental health vulnerabilities including depression, anxiety, low self-esteem, and social anxiety increase victimization risk, though causality remains unclear (Wang et al., 2023). Personality traits associated with increased victimization include introversion, low assertiveness, difficulty setting boundaries in online spaces, and limited social skills (Maisarah & Chen, 2025).

Internet use patterns represent significant risk factor. Adolescents spending excessive time online, engaging in problematic social media use, or frequent self-disclosure demonstrate elevated victimization risk (Lahti et al., 2024). Interestingly, reduced internet use is not protective, as non-users miss opportunities to develop digital literacy and coping skills. The relationship between internet use and vulnerability is moderated by activity quality—one-to-one communication with trusted contacts appears protective, while exposure to negative content or engagement with strangers increases risk (Marciano et al., 2022).

Problematic social media use shows moderate but statistically significant correlations with depression (r = 0.273, p < .001), anxiety (r = 0.348, p < .001), and stress (r = 0.313, p < .001) (Shannon et al., 2021). During the COVID-19 pandemic, adolescents experienced positive associations between ill-being and social media use (r = 0.171, p = 0.011) and between ill-being and media addiction (r = 0.434, p = 0.024), though not all digital media use had adverse consequences—purposeful one-to-one communication and positive online experiences mitigated loneliness and stress (Marciano et al., 2022).

6.2 Structural and systemic vulnerabilities in developing countries

Developing countries face unique structural factors amplifying cyberbullying risk. Limited digital literacy education means adolescents often lack foundational understanding of online safety, consent, privacy, and appropriate online communication (Meherali et al., 2021). School-based digital literacy programs are frequently absent or minimal, leaving youth vulnerable to exploitation and bullying. Additionally, inadequate regulation of online platforms creates environments where bullying flourishes with limited accountability (Shannon et al., 2021).

Poverty and socioeconomic disadvantage intersect with cyberbullying in complex ways. While digital access itself may be limited by economic barriers, adolescents from lower socioeconomic backgrounds who do access the internet may face additional vulnerabilities including less parental supervision of online activities, limited resources for seeking help, and greater exposure to negative online content (Rajkumar et al., 2022). In developing countries, the intersection of online and offline bullying may be more pronounced where peer hierarchies are rigidly enforced, and school environments offer limited safety protections.

Gender inequality in developing countries creates additional vulnerabilities for girls. Conservative gender norms may restrict girls’ online participation and freedom, potentially reduce cyberbullying exposure but limit digital development, while simultaneously creating unique risks related to sexual harassment and exploitation (Meherali et al., 2021). Adolescents from rural areas face additional barriers due to limited digital access, lower digital literacy, and reduced availability of mental health services (Rajkumar et al., 2022).

6.3 Mental health Status and trauma history as risk factors

Pre-existing mental health conditions significantly increase cyberbullying vulnerability. Among Australian school children, mental health problems including emotional symptoms, conduct problems, and hyperactivity-inattention were prevalent, with rates varying by school level and residence area (Gunawardena et al., 2024). In association studies, anxiety was found 1.89 times more likely and depression 1.61 times more likely among those reporting cyberbullying (Armoon et al., 2022).

Previous trauma exposure creates additional vulnerability. Adverse childhood experiences (ACEs) including maltreatment, family dysfunction, and exposure to violence increase both cyberbullying vulnerability and severity of mental health consequences (Liu et al., 2020). Cumulative adversity—where students experience both offline and online victimization, poverty, and family stress—creates particularly high-risk profiles.

7 Protective factors and building resilience

7.1 Individual-Level protective factors and resilience

Resilience, defined as the capacity to maintain or regain psychological health despite adversity, is a critical protective factor in the context of cyberbullying (Abate et al., 2024). Meta analytic evidence indicates that students with higher levels of resilience report significantly lower psychological distress following victimization (Maisarah and Chen, 2025). Resilience is not a fixed trait. It is a dynamic capacity shaped by supportive relationships, opportunities for skill development, and processes that promote meaning and adaptive coping.

Empirical findings show that resilience partially mediates the relationship between bullying victimization and mental health outcomes, with both significant direct effects and indirect effects operating through resilience pathways (Maisarah and Chen, 2025). Intervention studies further demonstrate that resilience can be strengthened through structured programs. A brief six session health coaching intervention for middle school students produced moderate improvements in resilience, suggesting that even low intensity approaches can yield measurable benefits (Lee et al., 2020). These findings support the feasibility of integrating resilience building into school based prevention frameworks.

Protective factors that contribute to resilience include cognitive competence, positive self perception, emotional self regulation, spiritual or religious engagement, and a clear sense of purpose (Abate et al., 2024). Meta analytic analyses also highlight the importance of social support, community cohesion, and self regulation capacity as meaningful buffers against adversity. Together, these findings underscore the value of multi level resilience strengthening strategies in mitigating the psychological impact of cyberbullying.

7.2 Family and social support systems

Strong family relationships represent one of the most powerful protective factors (Ramamurthy et al., 2023). Families maintaining open communication, providing emotional support, and modeling healthy problem-solving enable adolescents to process cyberbullying experiences and develop coping strategies. This protection may be particularly important in developing countries where school-based mental health support is limited, making family the primary psychological resource (Abate et al., 2024).

Family support partially mediated associations between cyberbullying experience and observation with levels of psychological problems among adolescents in Vietnam (β=0.35, p < .05) (Ngo et al., 2021). Despite majority of cyberbullying observers attempting to intervene (reporting or helping victims), only 48.2% of victims took action to stop perpetrators, highlighting the importance of adult support.

Peer support and positive peer relationships provide additional protection. Schools creating positive, inclusive climates where students feel valued and supported demonstrate lower bullying rates overall (Gabrielli et al., 2021). Peer support programs where trained peer leaders provide support show promise in reducing victimization impact, though evidence base remains limited (King & Fazel, 2021). Examination of school-based peer-led interventions found that although widespread, evidence on mental health effectiveness remains sparse.

7.3 School-Level protective factors and positive school climate

A positive school climate, defined by safety, respect, inclusion, and consistent adult support, serves as a central protective factor against bullying and cyberbullying (Stadler et al., 2010). When students perceive their school environment as fair and supportive, the psychological impact of victimization is reduced. School support functions as a buffer, particularly as students’ progress into higher grade levels where peer dynamics intensify. Evidence from comprehensive whole school programs shows sustained reductions in both perpetration and victimization, indicating that systemic approaches are more effective than isolated interventions (Gaffney et al., 2021).

The strength of school level protection depends on adaptation and cultural responsiveness. Teachers who are trained to recognize cyberbullying, apply developmentally appropriate strategies, and deliver trauma informed responses are better positioned to intervene effectively (Ganiyeva et al., 2025). However, evaluations of in service training programs reveal persistent gaps in quality and competency development, suggesting that many programs do not fully equip teachers with the required skills (Grmua, 2023). Strengthening teacher preparation remains a priority for sustainable prevention.

Digital literacy education further reinforces school based protection. When students are equipped with skills related to privacy awareness, informed consent, critical evaluation of online content, and empathetic communication, they are better prepared to navigate digital risks (Meherali et al., 2021; Ramamurthy et al., 2023). Integrating digital citizenship into existing curricula, rather than introducing stand-alone modules, improves feasibility and long term sustainability within school systems (Yosep et al., 2023). Collectively, these school level factors create layered protection that addresses both behavioral norms and digital competence.

8 Prevention and intervention strategies: effectiveness and implementation

8.1 Whole-School anti-bullying programs: evidence and effectiveness

School-based anti-bullying programs represent the most extensively evaluated cyberbullying prevention approach. Meta-analysis of 100 school-based program evaluations found significant reductions in bullying perpetration (OR = 1.309; 95% CI: 1.24–1.38) and victimization (OR = 1.244; 95% CI: 1.19–1.31), with these effects remaining significant under both random-effects and multivariate adjustment models (Gaffney et al., 2021). Whole-school approaches engaging students, teachers, parents, and administrators demonstrate superior effectiveness compared to single-component interventions (Gaffney et al., 2019).

Individual participant data meta-analysis of 39,793 children across 10 anti-bullying interventions found that interventions significantly reduced self-reported victimization (d = 0.14) and perpetration (d = 0.07), with effects stronger for younger participants (under age 12) and youth most heavily victimized at baseline (Hensums et al., 2022). Non-punitive disciplinary methods showed an iatrogenic effect particularly for girls, increasing bullying perpetration in youth already bullying frequently at baseline, suggesting the need for more nuanced, developmentally sensitive approaches.

Effective whole-school programs typically include: (1) clear school policies against bullying and cyberbullying; (2) classroom curricula addressing social-emotional skills, digital citizenship, and bystander intervention; (3) staff training on recognizing and responding to bullying; (4) restorative justice approaches emphasizing accountability and repair; (5) parent engagement and education; (6) peer support programs; (7) positive reinforcement of prosocial behavior (Gabrielli et al., 2021). The KiVa program, extensively evaluated in multiple countries, demonstrates effectiveness though implementation quality significantly influences outcomes (Axford et al., 2020).

8.2 Digital literacy and cybersafety education

Digital literacy interventions aim to equip students with knowledge and skills for safe, responsible online engagement. A systematic review of digital literacy interventions in developing countries found that these programs effectively improved sexual and reproductive health decision-making, with particular effectiveness for empowering adolescent girls in LMICs (Meherali et al., 2021). However, broader outcomes related to cyberbullying prevention remain understudied.

Effective digital literacy programs address: (1) online privacy and security; (2) understanding consent and appropriate sharing of personal information; (3) critical evaluation of online information; (4) understanding permanence and reach of online communications; (5) strategies for reporting harassment and seeking help; (6) empathy and perspective-taking in online interactions; (7) recognition of cyberbullying forms and consequences (Ramamurthy et al., 2023).

In developing countries, digital literacy faces implementation challenges including limited teacher training, lack of culturally appropriate curriculum materials, and competing educational priorities. However, rapid digital expansion creates urgency for these programs. Evidence suggests that integrating digital citizenship content into existing curricula, rather than creating separate programs, enhances feasibility and sustainability (Yosep et al., 2023). Programs should employ participatory approaches involving adolescents in content development to ensure cultural appropriateness and youth engagement (Meherali et al., 2021).

8.3 Mental health and therapeutic interventions for cyberbullying victims

Cognitive-behavioral therapy (CBT) represents the most evidence-supported individual intervention for addressing mental health consequences of cyberbullying. CBT targets dysfunctional thoughts (catastrophizing, over-generalizing), maladaptive behaviors (avoidance, social withdrawal), and emotional dysregulation. Meta-analysis of school-based mental health interventions for anxiety and depression found small positive effects (ES = 0.24, p = 0.002), with improved outcomes for studies using cognitive behavioral therapy, delivered by clinicians, in secondary school populations (Zhang et al., 2022).

For cyberbullying victims experiencing post-traumatic stress symptoms, trauma-focused CBT incorporating exposure therapy and cognitive processing shows effectiveness (Grande et al., 2023). Resilience-building interventions teaching adolescents to develop psychological strength and adaptive coping strategies demonstrate medium-effect improvements (Lee et al., 2020). Emotion regulation interventions including mindfulness, relaxation techniques, and dialectical behavior therapy (DBT) skills effectively reduce anxiety (SMD=0.54) and depression (SMD=0.28) with moderate effectiveness (Hamdani et al., 2022). Face-to-face delivery shows superior outcomes (SMD=0.47) compared to online delivery (SMD=0.22) for anxiety, suggesting therapeutic alliance importance.

Physical activity interventions show promise as adjunctive mental health support. Exercise was significantly more effective than control conditions in improving mental health (SMD=0.37, 95% CI: 0.20–0.53), with particularly strong effects on stress reduction (SMD=0.86) and social competence enhancement (SMD=0.56) (Fu et al., 2025). Resistance training shows positive impacts on self-efficacy (Hedges g = 0.538), physical self-worth (Hedges g = 0.319), and global self-worth (Hedges g = 0.409) (Collins et al., 2019).

8.4 Digital mental health and technology-enabled interventions

Digital mental health interventions offer potential to address cyberbullying consequences in developing countries where in-person services are scarce. Meta-analysis during COVID-19 found that digital mental health interventions produced small reductions in depression (SMD=0.49) and moderate reductions in anxiety (SMD=0.66) (Zhong et al., 2022). Web-based programs (32.3%), videoconferencing (24.6%), smartphone apps (21.5%), and SMS text messaging (7.7%) represent primary delivery modes.

A chatbot-based intervention addressing body image in Brazilian adolescents demonstrated small significant improvements in state body image (Cohen d = 0.30), trait body image (d = 0.10–0.26), affect, and self-efficacy (Matheson et al., 2022). However, intervention attrition was high (61.9%), reflecting broader digital intervention challenges. The findings suggest microinterventions and chatbot technology are acceptable and effective but require optimization for engagement.

Digital peer support interventions show promise for mental health. Peer support specialists using technology delivered integrated medical and psychiatric self-management interventions with feasibility and acceptability, with improvements in self-efficacy and empowerment (Fortuna et al., 2022). Online peer support programs based on acceptance and commitment therapy reduced psychological inflexibility, stress, anxiety, and depression in university students (Grgoire et al., 2022). However, more rigorous research on mechanism of action and long-term effectiveness is needed (Fortuna et al., 2019).

9 Implementation challenges and contextual considerations in developing countries

9.1 Structural resource limitations and healthcare system barriers

Implementation of cyberbullying prevention and intervention programs in developing countries faces substantial structural barriers. Limited financial resources constrain: (1) comprehensive staff training programs; (2) ongoing technical support and fidelity monitoring; (3) development of culturally appropriate materials and curricula; (4) access to evidence-based measurement tools; (5) evaluation of program effectiveness (Grande et al., 2023).

School infrastructure limitations including unreliable electricity, limited internet connectivity, inadequate classroom space, and minimal technology access complicate technology-based interventions and digital literacy education. Teaching staff often lack training in mental health issues, digital citizenship, and trauma-informed approaches, necessitating substantial capacity-building investments (Carta et al., 2015).

Child and adolescent mental health policy in low-income and middle-income countries faces multiple challenges: (1) poor public awareness and low political willingness; (2) significant stigma against mental disorders; (3) biased cultural values toward children and adolescent mental health; (4) lack of comprehensive data and evidence; (5) shortage of human resources (trained mental health professionals), service facilities, and funding; (6) unintended consequences of international support (reducing local responsibility, fragmenting planning, creating unsustainability) (Zhou et al., 2020).

Mental health service accessibility in low-income and middle-income countries is characterized by health inequalities involving biological factors (gender, age, comorbidities); social factors (race, culture, stigma, trust, family support, attitude, economic status, literacy); and structural factors (place of residence, distance, accessibility, service availability) (Albarqi et al., 2024). Stigma associated with mental disorders emerges as leading inequality factor, preventing help-seeking and treatment engagement.

9.2 Sociocultural adaptation and contextual considerations

Effective prevention and intervention programs must be adapted to local cultural contexts. Concepts of bullying, appropriate peer relationships, and acceptable online communication vary across cultures and differ from Western-developed frameworks (Rajkumar et al., 2022). Cyberbullying manifests differently across cultural contexts—for example, exclusion from online groups causes particular harm in collectivistic Asian societies where interpersonal harmony is paramount (Wang et al., 2019).

Gender norms significantly influence cyberbullying patterns and intervention approaches. In some developing country contexts, conservative gender norms restrict girls’ online freedom, potentially reducing cyberbullying exposure but limiting digital development, while creating unique vulnerabilities for sexual harassment and exploitation (Meherali et al., 2021). Interventions must navigate this tension thoughtfully, promoting girls’ digital empowerment while maintaining safety.

Family structure and parenting patterns vary substantially across developing country contexts, requiring adaptation of family-based interventions (Abate et al., 2024). Shared decision-making in child and adolescent mental health services must accommodate varying cultural approaches to parental involvement, recognizing that family decision structures differ across cultures (Liverpool et al., 2020). Community-based approaches recognizing traditional healers, spiritual leaders, and community structures may enhance acceptability and effectiveness (Kohrt et al., 2018).

9.3 Digital access disparities and technology-related factors

Digital access disparities create unique implementation challenges. While cyberbullying requires internet access, in developing countries this access may be limited, concentrated among wealthier populations, and primarily mobile-based. This digital divide means prevention and intervention efforts must account for variable access and predominance of mobile-only users (Kardefelt-Winther et al., 2020). Adolescents may use different social media platforms and communication technologies compared to developed country youth, requiring interventions to address context-specific platforms (Lahti et al., 2024).

Offline-online integration is more pronounced in developing countries where same peer groups interact both in-person and online, creating potential for bullying to seamlessly extend between contexts (Lahti et al., 2024). School-based interventions must address this seamless integration, recognizing that separation of “online” and “offline” domains is artificial in many developing country adolescent contexts.

Community-based mental health services in low- and middle-income countries show promising evidence, with non-specialist-delivered interventions in community platforms demonstrating greater accessibility and acceptability compared to healthcare facilities (Kohrt et al., 2018). Activities including awareness-raising, psychoeducation, skills training, and psychological treatments delivered through homes, schools, refugee camps, and technology-aided platforms can extend reach.

10 Discussion, research gaps, and future directions

This review demonstrates that cyberbullying is consistently associated with significant mental health risks among school age children, with meta-analytic evidence indicating elevated odds of depression, anxiety, suicidal ideation, and self-harm among victims, as well as modest but reliable reductions in perpetration and victimization through structured school-based programs (Li et al., 2022; Gaffney et al., 2021). Despite this strong global evidence base, substantial conceptual, contextual, and methodological gaps remain. The literature is heavily concentrated on adolescents, leaving elementary students underrepresented even as digital engagement begins earlier and developmental vulnerabilities differ in cognitive maturity, emotional regulation, and peer dependency (Hensums et al., 2022). Research from developing countries is comparatively sparse and often cross sectional, limiting causal inference and obscuring developmental trajectories. Measurement inconsistency further complicates interpretation, as definitions of cyberbullying vary across studies and culturally validated instruments are rarely employed in low-and-middle income contexts. Mechanistic pathways linking victimization to psychological distress are insufficiently examined within sociocultural frameworks that account for family structure, school climate, community norms, gender expectations, and socioeconomic inequality. Intervention research is particularly limited in resource constrained settings, with few rigorous randomized controlled trials, minimal reporting on fidelity and adaptation, and little attention to cost effectiveness or scalability. Evidence on integrating digital citizenship education into elementary curricula, leveraging peer and family-based strategies, and developing culturally responsive technological safeguards remains fragmented. Collectively, these gaps hinder the development of context sensitive, developmentally appropriate, and sustainable prevention frameworks tailored to elementary students in developing countries.

11 Conclusions

Cyberbullying represents a significant and growing public health threat to school-age children globally, with particularly acute impacts in developing countries where protective infrastructure remains limited. This umbrella review synthesized evidence from 50 Scopus-indexed and WOS-indexed journals, identifying consistent and robust associations between cyberbullying victimization and adverse mental health outcomes including depression, anxiety, suicidal ideation, and self-harm behaviors. Evidence-based school-based prevention programs demonstrate effectiveness, though their implementation in developing country contexts requires substantial adaptation and capacity-building.

Elementary students, a developmentally vulnerable population with limited digital literacy and emerging emotion regulation capacities, warrant particular attention in prevention and intervention efforts. The convergence of rapid digital expansion in developing countries with limited prevention infrastructure and inadequate mental health services creates urgency for research, intervention development, and policy action. Future efforts must integrate evidence-based approaches with culturally sensitive adaptation, address systemic barriers to implementation, and prioritize building local capacity for sustainable prevention and response.

Key findings highlight that: (1) cyberbullying victimization increases depression risk 1.85-fold and anxiety risk 1.72-fold; (2) whole-school prevention programs reduce perpetration and victimization by approximately 30%; (3) resilience, family support, and positive school climate provide critical protective factors; (4) implementation in developing countries faces substantial resource, structural, and sociocultural barriers; (5) research specifically examining elementary students in developing countries remains sparse.

Successful cyberbullying prevention in developing countries requires collaborative efforts among researchers, educators, policymakers, technology companies, families, and adolescents themselves. Multi-level interventions addressing individual, family, school, and community factors, combined with digital platform accountability, offer the most promising approach. Investment in high-quality research, teacher capacity-building, mental health service expansion, and culturally adapted interventions is essential to create safer digital environments that support healthy development and mental well-being for elementary students in developing countries.

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