TY - JOUR
T1 - Defining and measuring cyberbullying within the larger context of bullying victimization
AU - Ybarra, Michele L.
AU - Boyd, Danah
AU - Korchmaros, Josephine D.
AU - Oppenheim, Jay
N1 - Funding Information:
The project described was supported by award number R01-HD057191 from the National Institute of Child Health and Human Development. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development. The authors thank Dr. Kimberly Mitchell, Ms. Amanda Lenhart, and Dr. Donna Cross for their input in the study design; Ms. Tonya Prescott for her tireless help with formatting and proofreading; and the study participants for their participation in this study.
PY - 2012/7
Y1 - 2012/7
N2 - Purpose: To inform the scientific debate about bullying, including cyberbullying, measurement. Methods: Two split-form surveys were conducted online among 6-17-year-olds (n = 1,200 each) to inform recommendations for cyberbullying measurement. Results: Measures that use the word "bully" result in prevalence rates similar to each other, irrespective of whether a definition is included, whereas measures not using the word "bully" are similar to each other, irrespective of whether a definition is included. A behavioral list of bullying experiences without either a definition or the word "bully" results in higher prevalence rates and likely measures experiences that are beyond the definition of "bullying." Follow-up questions querying differential power, repetition, and bullying over time were used to examine misclassification. The measure using a definition but not the word "bully" appeared to have the highest rate of false positives and, therefore, the highest rate of misclassification. Across two studies, an average of 25% reported being bullied at least monthly in person compared with an average of 10% bullied online, 7% via telephone (cell or landline), and 8% via text messaging. Conclusions: Measures of bullying among English-speaking individuals in the United States should include the word "bully" when possible. The definition may be a useful tool for researchers, but results suggest that it does not necessarily yield a more rigorous measure of bullying victimization. Directly measuring aspects of bullying (i.e., differential power, repetition, over time) reduces misclassification. To prevent double counting across domains, we suggest the following distinctions: mode (e.g., online, in-person), type (e.g., verbal, relational), and environment (e.g., school, home). We conceptualize cyberbullying as bullying communicated through the online mode.
AB - Purpose: To inform the scientific debate about bullying, including cyberbullying, measurement. Methods: Two split-form surveys were conducted online among 6-17-year-olds (n = 1,200 each) to inform recommendations for cyberbullying measurement. Results: Measures that use the word "bully" result in prevalence rates similar to each other, irrespective of whether a definition is included, whereas measures not using the word "bully" are similar to each other, irrespective of whether a definition is included. A behavioral list of bullying experiences without either a definition or the word "bully" results in higher prevalence rates and likely measures experiences that are beyond the definition of "bullying." Follow-up questions querying differential power, repetition, and bullying over time were used to examine misclassification. The measure using a definition but not the word "bully" appeared to have the highest rate of false positives and, therefore, the highest rate of misclassification. Across two studies, an average of 25% reported being bullied at least monthly in person compared with an average of 10% bullied online, 7% via telephone (cell or landline), and 8% via text messaging. Conclusions: Measures of bullying among English-speaking individuals in the United States should include the word "bully" when possible. The definition may be a useful tool for researchers, but results suggest that it does not necessarily yield a more rigorous measure of bullying victimization. Directly measuring aspects of bullying (i.e., differential power, repetition, over time) reduces misclassification. To prevent double counting across domains, we suggest the following distinctions: mode (e.g., online, in-person), type (e.g., verbal, relational), and environment (e.g., school, home). We conceptualize cyberbullying as bullying communicated through the online mode.
KW - Bullying
KW - Cyberbullying
KW - Measurement
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U2 - 10.1016/j.jadohealth.2011.12.031
DO - 10.1016/j.jadohealth.2011.12.031
M3 - Article
C2 - 22727077
AN - SCOPUS:84862906827
SN - 1054-139X
VL - 51
SP - 53
EP - 58
JO - Journal of Adolescent Health
JF - Journal of Adolescent Health
IS - 1
ER -