Online and Health Risk Behaviors in High School Students

An Examination of Bullying

Meghan N. Long; Elizabeth B. Dowdell

Disclosures

Pediatr Nurs. 2018;44(5):223-228. 

In This Article

Methods

This study is a secondary analysis of a quantitative 2009 data set from an Office of Juvenile Justice and Delinquency Prevention (OJJDP) study that asked about selected health risk behaviors, as well as the usage and Internet risk behaviors of high school students. The OJJDP data set gathered information from 2,077 high school students, grades 9 through 12, ranging in age from 15 to 18 years old. The paper and pencil instrument included questions derived from the Youth Risk Behavior Survey (YRBS) developed by the CDC to assess health risk behaviors, specifically about smoking cigarettes, drinking alcohol, physical fighting, and underage driving (CDC, 2009). The YRBS has undergone multiple testretest reliability assessments with Kappa values that range from 47.0% to 90.5%, with a mean of 60.7% and a median of 60.0% (Brener et al., 2002). A modified version of the Youth Internet Safety Survey (YISS) (Finkelhor, Mitchell, & Wolak, 2000) and a socio-demographic form that identified areas such as age, ethnicity, and student experiences was also used to collect basic information.

Prior to the beginning of data analysis, permission was obtained to conduct this research from the authors' organization's Institutional Review Board (IRB). For the current study, a subsample of high school students who experienced bullying was selected. Inclusion criteria included all students in grades 9 to 12 who answered "yes" to the following two questions: Have you ever bullied other kids? and Have you ever been bullied or beat up by other kids? Frequencies were run on all selected variables, and a series of Pearson correlations was used to determine a relationship or interaction between variables. If there was an interaction between variables, then a cross-tabulation was used to determine significance. When determining the level of significance for results, a p value of 0.05 was considered the minimum. Chi-square analysis was also conducted on all dichotomous variables, and analysis of variance (ANOVA) was used for all continuous variables to determine any significant group differences.

Comments

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