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Cited by 362

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Traditional Bullying and Cyberbullying: Identification of Risk Groups for Adjustment Problems

Gradinger, Petra, Strohmeier, Dagmar, Spiel, Christiane·2009·Zeitschrift für Psychologie / Journal of Psychology

Abstract

We investigated the co-occurrence of traditional bullying, cyberbullying, traditional victimization, and cybervictimization, and analyzed whether students belonging to particular groups of bullies (e.g., traditional, cyber, or both), victims (e.g., traditional, cyber, or both), and bully-victims differed regarding adjustment. Seven hundred sixty-one adolescents (49% boys) aged 14–19 years (M = 15.6 years) were surveyed. More students than expected by chance were totally uninvolved, more students were traditional bully-victims, and more students were combined bully-victims (traditional and cyber). The highest risks for poor adjustment (high scores in reactive and instrumental aggression, depressive, and somatic symptoms) were observed in students who were identified as combined bully-victims (traditional and cyber). In addition gender differences were examined.

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Metadata

Authors
Gradinger, P., Strohmeier, D., & Spiel, C.
Venue
Zeitschrift für Psychologie / Journal of Psychology
Published
2009-01
Volume
217
Issue
4
Pages
205-213
ISSN
0044-3409 (ISSN-L)
OpenAlex
W1951116805
Cited by
362
References
28
FWCI
26.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Traditional Bullying and Cyberbullying: Identification of Risk Groups for Adjustment Problems. https://app.cochat.ai/papers/10.1027/0044-3409.217.4.205
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Gradinger, P., Strohmeier, D., & Spiel, C. (2009). Traditional Bullying and Cyberbullying: Identification of Risk Groups for Adjustment Problems. Zeitschrift für Psychologie / Journal of Psychology. https://doi.org/10.1027/0044-3409.217.4.205

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.