Bystander intentions: An analysis of adolescents' judgments and responses to cyberbullying

• In Event: Poster Session 12
  In Poster Session: PS 12 Topic - Social Relationships

Abstract

Cyberbullying is a serious threat to adolescents' wellbeing (Kowalski & Limber, 2013). Research on cyberbullying has mainly focused on the victim and the bully (Gaffney et al., 2019), with less research exploring bystander intervention online. Previous research has found that bystander intervention can reduce cyberbullying incidents (e.g., Ma et al., 2019). However, while effective, there are very few cyberbullying interventions, especially those targeting bystander intervention (Gaffney et al., 2019). Further, while research has documented correlates associated with bystander behavior in traditional bullying, much less is known about bystander behavior responses in cyberbullying.
To address these gaps, we examined adolescents’ (6th grade: N = 425, Mage = 11.31, SD = 0.62, 49.6% female; and 9th grade: N = 403, Mage = 14.31, SD = 0.52, 47.9% female) self-reported bystander behavior in response to cyberbullying. Participants reported their expected active or inactive bystander behaviors and rated the acceptability of cyberbullying. Participants also completed measures of empathy, attachment with their parents, family management, and experiences of racial discrimination as predictors of bystander judgments and responses.
The regression predicting moral judgment about the acceptability of cyberbullying revealed that there were four significant main effects (final model): gender (B = -0.15, β = -0.08, p = .023), sympathy (B = -0.34, β = -0.28, p < .001 ), family management (B = -0.73 , β = -0.08, p = .022), and teacher discrimination (B = 0.28 , β = 0.23, p < .001). Therefore, females, those with greater sympathy, and those with more positive family management styles rated cyberbullying as less acceptable, but participants who experienced discrimination from their teachers rated cyberbullying as more acceptable (Table 1).
For active forms of bystander intervention, there were five significant predictors of active intervention responses to cyberbullying (3rd model): gender (B = 0.18, β = 0.08, p = .022), affective empathy (B = 0.10, β = 0.08, p = .018), sympathy (B = 0.52, β = 0.36, p < .001), cognitive empathy (B = 0.15, β = 0.09, p = .005), and attachment (B = 0.25, β = 0.11, p = .001).Females, those high in affective empathy, cognitive empathy, and sympathy, and youth with high levels of attachment were more likely to say that they would actively intervene (Table 2).
There were two significant predictors of inactive intervention responses in cyberbullying (final model): sympathy (B = -0.36, β = -0.20, p < .001), and teacher discrimination (B = 0.27, β = 0.15, p = .002). More sympathetic participants were less likely to respond in inactive ways to cyberbullying and participants who had higher levels of experience with teacher discrimination were more likely to use inactive responses to cyberbullying (Table 2).
This study is an important step in addressing cyberbullying as findings document how different individual, family-related and school-related factors might shape bystanders’ judgments and responses to cyberbullying. This study is especially pertinent now as cyberbullying may increase as adolescents move to mostly online interactions in the digital era.

Authors

• Emily A Herry, Ohio State University
  Presenting Author

• Secil Gonultas, North Carolina State University
  Non-Presenting Author

• Kelly Lynn S Mulvey, North Carolina State University
  Non-Presenting Author