Clemson Research Reveals How Bullying Severity, Motivation Predict Mental Health Effects

The severity of and intentionality behind bullying go hand in hand to predict negative mental health effects on bullying victims, according to recently published research out of Clemson University.

Skye Wingate, an assistant professor in Clemson’s Department of Communication, found that when bullying messages were severe — whether they occurred frequently or not — and the victim perceived those messages to be about innate characteristics that victims cannot change (race, gender, sexuality), the effects on mental health were the most negative for the victim.

The research, published in the Journal of Social and Personal Relationships, is novel because of its examination of bullying severity and intention as opposed to the frequency of bullying, which is often the metric used when examining the effects of bullying on a victim.

“The frequency of bullying is certainly important, and our study still accounted for it, but I wanted to establish a more nuanced indicator or methodology to get at the unique levels of intensity within bullying experiences,” Wingate said. “No two communications or situations are the same, so I felt that we should tap into that complex aspect a little more.”

Wingate and research assistants collected data using surveys from college-age students and then coded their responses to open-ended questions to gauge levels of bullying severity and then levels of the victim’s emotional reaction, hurt, depression and general anxiety.

Wingate also assessed the perceived goals of the bully, separating them into three different categories: upward-mobility goals, personal-attacking goals and highlight-differences goals. Bullies with upward-mobility goals often used attacks to “climb the social ladder” by ridiculing peers. Personal attacks were often motivated by revenge or envy. Targeting someone to highlight differences covers a wide range of reasons, from the victim being perceived as “not an average person” to them not conforming to a social norm.

Coded responses provided the data that revealed the relationship between all of these factors. Wingate said the topic contains so many variables and exceptions that boiling it down to a simple equation or predicted outcome is impossible, but the data can begin to reveal how these factors relate to one another.

Prepared by Clemson University.