The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Cyberbullying victimisation in adolescence: relationships with loneliness and depressive mood
Abstract
Cyberbullying is deliberate, aggressive activity carried out through digital means. Cybervictimisation in adolescence may be related to negative psychosocial variables such as loneliness and depressive mood. The purpose of the present study, the first of its kind in Israel, was to examine the association between adolescent cybervictimisation and two socio-emotional variables: loneliness and depressive mood. The sample consisted of 242 Israeli adolescents, aged 13–16 years, who completed questionnaires regarding Internet use, cyberbullying, traditional bullying, loneliness and depressive mood. In total, 16.5% of the participants reported being cybervictims and 32.5% reported knowing someone who was cybervictimised. The results revealed a relationship between cybervictimisation and loneliness (social, emotional and general) as well as depressive mood. A logistic hierarchical regression found that loneliness, gender and depressive mood each explained some variance in cybervictimisation in adolescents. As an anchor for comparison, and in order to shed light on the findings, results are presented in comparison to traditional bullying. The results make a contribution to national and international cyberbullying research and broaden the knowledge about potential risk factors for cybervictimisation.
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In the citing paper
“Victims often experience isolation and negative emotions69, leading to hopelessness and depression145, which are, in turn, linked to self-harm and suicidal ideation149.”
From Umbrella review of meta-analyses on the risk factors, protective factors, consequences and interventions of cyberbullying victimization (2024) · cites this paper as [69]
In the citing paper
“Hurtful online comments can make victims feel isolated and emotionally distressed, resulting in feelings of hopelessness, lowered self-esteem and increased anxiety, which often culminate in depression69,145.”
From Umbrella review of meta-analyses on the risk factors, protective factors, consequences and interventions of cyberbullying victimization (2024) · cites this paper as [69]
In the citing paper
“Victims, often distanced from social groups owing to such antisocial or aggressive tendencies, appear more susceptible to bullies and are prone to seek interactions through online media69,70, increasing their risk of encountering perpetrators151.”
From Umbrella review of meta-analyses on the risk factors, protective factors, consequences and interventions of cyberbullying victimization (2024) · cites this paper as [69]
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Metadata
- Authors
- Olenik-Shemesh, D., Heiman, T., & Eden, S.
- Affiliations
- Open University of Israel (IL)
- Bar-Ilan University (IL)
- Venue
- Emotional and Behavioural Difficulties
- Publisher
- Informa UK Limited
- Published
- 2012-09
- Volume
- 17
- Issue
- 3-4
- Pages
- 361-374
- ISSN
- 1363-2752 (ISSN-L)
- 1741-2692
- OpenAlex
- W2138491614
- Cited by
- 176
- References
- 41
- Citations by year
- 2025: 7 · 2024: 19 · 2023: 10 · 2022: 23 · 2021: 12 · 2020: 16 · 2019: 14 · 2018: 10 · 2017: 15 · 2016: 14 · 2015: 18 · 2014: 13 · 2013: 5
- FWCI
- 17.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Emotional and Behavioural Difficulties (publishedVersion)
- 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, adolescents, loneliness, depressive mood, traditional bullying, gender differences, risk factors, Israeli youth
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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