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Cyberbullying Prevalence Among US Middle and High School–Aged Adolescents: A Systematic Review and Quality Assessment
Open accessAbstract
Purpose Cyberbullying (CB) has established links to physical and mental health problems including depression, suicidality, substance use, and somatic symptoms. Quality reporting of CB prevalence is essential to guide evidence-based policy and prevention priorities. The purpose of this systematic review was to investigate study quality and reported prevalence among CB research studies conducted in populations of US adolescents of middle and high school age.Methods Searches of peer-reviewed literature published through June 2015 for "CB" and related terms were conducted using PubMed, PsycINFO, CINAHL Plus, and Web of Science. Included manuscripts reported CB prevalence in general populations of US adolescents between the ages of 10 and 19 years. Using a review tool based on the Strengthening the Reporting of Observational Studies in Epidemiology statement, reviewers independently scored study quality on study methods, results reporting, and reported prevalence.Results Search results yielded 1,447 manuscripts; 81 manuscripts representing 58 unique studies were identified as meeting inclusion criteria. Quality scores ranged between 12 and 37 total points of a possible 42 points (mean = 26.7, standard deviation = 4.6). Prevalence rates of CB ranged as follows: Perpetration, 1%-41%; victimization, 3%-72%; and overlapping perpetration and victimization, 2.3%-16.7%.Conclusions Literature on CB in US middle and high school-aged students is robust in quantity but inconsistent in quality and reported prevalence. Consistent definitions and evidence-based measurement tools are needed.
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“These variances were attributed to inconsistent definitions and conceptualizations, timeframes (e.g., past week, month etc.), and measurement tools (44, 47–49, 51).”
From A thematic analysis of adolescents’ perceptions of cyberbullying and cyberaggression: definitional distinctions and educational gaps (2026) · cites this paper as [44]
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“Furthermore, several reviews have identified substantial issues concerning variations in prevalence rates (44, 45, 47–50).”
From A thematic analysis of adolescents’ perceptions of cyberbullying and cyberaggression: definitional distinctions and educational gaps (2026) · cites this paper as [44]
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“Additionally, there is also evidence of cyberbullying being used as an all-encompassing term (42, 44, 60).”
From A thematic analysis of adolescents’ perceptions of cyberbullying and cyberaggression: definitional distinctions and educational gaps (2026) · cites this paper as [44]
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Metadata
- Authors
- Selkie, E. M., Fales, J. L., & Moreno, M. A.
- Affiliations
- Seattle Children's Hospital (US)
- Washington State University Vancouver (US)
- Corresponding author
- Selkie, Ellen M.
- Venue
- Journal of Adolescent Health
- Publisher
- Elsevier BV
- Published
- 2016-02
- Volume
- 58
- Issue
- 2
- Pages
- 125-133
- ISSN
- 1054-139X (ISSN-L)
- PMC
- PMC4724486
- OpenAlex
- W2264177151
- Cited by
- 318
- References
- 98
- Citations by year
- 2026: 14 · 2025: 21 · 2024: 28 · 2023: 36 · 2022: 37 · 2021: 35 · 2020: 33 · 2019: 35 · 2018: 47 · 2017: 19 · 2016: 13
- FWCI
- 4.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Adolescent Health (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (2t32mh020021-26)
- National Institute of Mental Health (T-32MH020021, 2T32MH020021-16)
- Topics
- Social Sciences › Psychology › Social Psychology › Bullying, Victimization, and Aggression
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Keywords
- cyberbullying, prevalence, adolescents, junior high school students, high school students, cyberbullying perpetration, cyber victimization, study quality, reporting quality
- MeSH terms
- Humans, Students, United States, Prevalence, Crime Victims, Internet, Bullying, Observational Studies as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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