The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Understanding Bullying and Victimization During Childhood and Adolescence: A Mixed Methods Study
Abstract
In the present study, quantitative and qualitative data are presented to examine individual and contextual predictors of bullying and victimization and how they vary by age and gender. Two waves of survey data were collected from 2,678 elementary, middle, and high school youth attending 59 schools. In addition, 14 focus groups were conducted with 115 youth who did not participate in the survey. Changes in both bullying and victimization were predicted across gender and age by low self-esteem and negative school climate, with normative beliefs supporting bullying predicting increases in bullying only. Focus group comments provided insights into the dynamics of bullying, highlighting its connection to emergent sexuality and social identity during adolescence. Findings are discussed in terms of their implications for preventive antibullying interventions in schools.
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Cites
Designing and Conducting Mixed Methods Research
Robinson, P. (2007) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1753-6405.2007.00096.x · Cited by 23,258
Determining Validity in Qualitative Inquiry
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Bullying at school: what we know and what we can do
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Bullying Behaviors Among US Youth: Prevalence and Association With Psychosocial Adjustment
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Relation of threatened egotism to violence and aggression: The dark side of high self-esteem.
Baumeister, R. F., Smart, L., & Boden, J. M. (1996) · Psychological Review · doi:10.1037/0033-295x.103.1.5 · Cited by 2,378
Multiple Imputation of Missing Values
Royston, P. (2004) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0400400301 · Cited by 2,340
Bullying at School: Basic Facts and Effects of a School Based Intervention Program
Olweus, D. (1994) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1994.tb01229.x · Cited by 1,888
Prevalence estimation of school bullying with the Olweus Bully/Victim Questionnaire
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Predictors of bullying and victimization in childhood and adolescence: A meta-analytic investigation
Cook, C. R., Williams, K. R., Guerra, N. G., Kim, T. E., & Sadek, S. (2010) · School Psychology Quarterly · doi:10.1037/a0020149 · Cited by 1,758
Self-citation
Cited by
Bullying Prevalence Across Contexts: A Meta-analysis Measuring Cyber and Traditional Bullying
Modecki, K. L., Minchin, J., Harbaugh, A. G., Guerra, N. G., & Runions, K. C. (2014) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2014.06.007 · Cited by 1,659
Self-citationAssociations among bullying, cyberbullying, and suicide in high school students
Bauman, S., Toomey, R. B., & Walker, J. L. (2013) · Journal of Adolescence · doi:10.1016/j.adolescence.2012.12.001 · Cited by 665
Yeager, D. S., Fong, C. J., Lee, H. Y., & Espelage, D. L. (2015) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2014.11.005 · Cited by 472
El Zaatari, W., & Maalouf, I. (2022) · Sage Open · doi:10.1177/21582440221134089 · Cited by 182
van Geel, M., Goemans, A., Zwaanswijk, W., Gini, G., & Vedder, P. (2018) · Developmental Review · doi:10.1016/j.dr.2018.07.001 · Cited by 161
Metadata
- Authors
- Guerra, N. G., Williams, K. R., & Sadek, S.
- Venue
- Child Development
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-01-01
- Volume
- 82
- Issue
- 1
- Pages
- 295-310
- ISSN
- 0009-3920 (ISSN-L)
- 1467-8624
- OpenAlex
- W1902669537
- Cited by
- 324
- References
- 47
- FWCI
- 35.84
- Type
- journal article
- Language
- en
- Open access
- closed
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- Guerra, N. G., Williams, K. R., & Sadek, S. (2011). Understanding Bullying and Victimization During Childhood and Adolescence: A Mixed Methods Study. Child Development. https://doi.org/10.1111/j.1467-8624.2010.01556.x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.