Journal of Bullying and Social Aggression

Volume 1, Number 1, 2018

              The relationship between trait impulsivity and cyberbullying behavior is accounted for by sensation seeking

  Anandi C. Ehman, Elicia C. Lair, & Alan Gross

The University of Mississippi


This study leveraged a recent theoretical distinction between sensation seeking and
impulsivity (Zuckerman & Glicksohn, 2016) to investigate if the relationship between trait
impulsivity and cyberbullying behavior is accounted for by sensation seeking. College
students (N = 500) participated in an online survey and completed measures of impulsivity,
sensation seeking, empathy, cyberbullying toward known and unknown targets, and
demographics. Conditional process modeling revealed a direct and indirect pathway for
cyberbullying of known targets, such that higher impulsivity led to increased cyberbullying
toward known targets, but this was accounted for by increased sensation seeking.
Additionally, conditional process modeling revealed an indirect pathway for cyberbullying of
unknown targets, such that higher impulsivity led to increased cyberbullying toward
unknown targets, via increased sensation seeking. Empathy was not related to sensation
seeking or cyberbullying but was weakly correlated with impulsivity. Results and
implications of findings are discussed.

Keywords: cyberbullying, impulsivity, sensation seeking, college students


The relationship between trait impulsivity and cyberbullying behavior is accounted for by

sensation seeking

Cyberbullying is a repeated intentional act of aggression carried out by one individual
against another through the use of electronic media (Calvete et al, 2010; Hinduja & Patchin,
2007; Smith et al., 2008). This aggression can take many forms (Calvete et al., 2010; Hinduja
& Patchin, 2007; Kokkinos et al., 2014; Pelfrey & Weber, 2013; Pettalia et al., 2013; Smith et
al., 2008). Research suggests cyberbullying victimization rates range between 11 and 40%,
while perpetration rates tend to range from 5-35% (Kowalski et al., 2014; Junoven & Gross,
2008; Kowalski & Limber, 2013; Tokunaga, 2010; Twyman et al., 2010; Bastiaensens et al.,
2014; Cappadocia et al., 2014; Kowalski et al., 2014; Patchin & Hinduja, 2006).

In addition to being an undesirable behavior, cyberbullying is associated with a variety of
negative outcomes for both victims and perpetrators (Tokunga et al., 2010). These outcomes
include higher scores on measures of depression and anxiety (Campbell et al., 2015;
Kowalski & Limber, 2013; Patchin & Hinduja, 2008), and lower scores on measures of
academic performance and self-esteem (Kowalski & Limber, 2013). Some studies have
additionally demonstrated that both cyberbullying perpetration and victimization are linked to
offline delinquent behaviors such as underage drinking, illegal drug use, criminal activity,
and various forms of interpersonal violence (Patchin & Hinduja, 2008; Pelfrey &Weber,
2013; Schenk, Fremouw & Keelan, 2013). To date, research on cyberbullying has primarily
focused on individuals aged 11-17 (Bastiaensens et al., 2014; Cappadocia et al., 2014;
Junoven & Gross, 2008; Kowalski & Limber, 2013; Mishna et al., 2012; Tokunaga, 2010;
Twyman et al., 2010). Research on cyberbullying among college age populations is limited.
However, preliminary studies have demonstrated similar trends in the prevalence, as well as
in the negative impact of both perpetration and victimization (Kokkinos et al., 2014). The

increasing prevalence of cyberbullying, alongside the negative outcomes for those involved,
creates a growing need for researchers to understand who might be most likely to cyberbully.
The current work examines whether personality differences may be used to make this
distinction. Specifically, the present study examines how impulsivity relates to
cyberbullying, and whether or not individual differences in sensation seeking account for this
relationship. Moreover, there is also a gap in the current research with regards to whether
cyberbullying, like traditional bullying, occurs largely between peers and friends, or whether
unknown individuals are also targeted. As such, the present research investigates how
personality factors influence cyberbullying of both known and unknown targets.

Impulsivity and Cyberbullying
One personality trait that has been examined in relation to aggression and
cyberbullying is impulsivity. Impulsivity is defined as an action “performed without regard
for the consequences… based on minimal or automatic cognitive appraisal” (Howard, 2011).
Greater levels of impulsivity are related to aggressive behavior in a variety of populations,
including but not limited to: prison inmates, individuals in inpatient psychiatric facilities, as
well as traditional adolescent and college-aged individuals (Fanti & Kimonis, 2013; Ferguson
et al., 2005; Garcia-Forero et al., 2009; Holland, 2009; Krakowski & Czbor, 2014; Low
& Esplange, 2014). Some aspects of online interactions also appear to be driven by
impulsivity, as higher scores on the impulsivity subscale of the Youth Psychopathy Inventory
(YPI) (Kokkinos, Antoniadou, & Markos, 2014) were predictive of involvement in
cyberbullying, accounting for approximately 12% of the variance in this behavior for
undergraduates (Kokkinos, Antoniadou, & Markos, 2014). This study also demonstrated that
those who reported both cyberbullying behaviors and victimhood scored higher on this
impulsivity subscale, relative to individuals who were only cyberbullies, victims, or those
who belong to neither category. These findings suggest those with higher levels of

impulsivity might be more prone to cyberbully, which would be consistent with the
aggression model of cyberbullying. There may be, however, a different factor underlying this
Sensation Seeking and Cyberbullying
Studies emphasizing peer-relationship aspects of cyberbullying place a great deal of
emphasis on a cyberbully’s intention to cause harm to their victim (Li, 2007; Francisco et al.,
2015; Wingate et al., 2013). Among college age students, however, one of the most
commonly stated reasons for engaging in cyberbullying behavior is for entertainment
(Francisco et al., 2015; Rafferty & Ven, 2014; Smith et al., 2008; Thacker & Griffiths, 2012).
This suggests that for college aged individuals, an individual’s primary motivation for
cyberbullying is entertainment, and that the harm one causes may be perceived as incidental.
This sort of hostility for amusement is well documented in the broader literature of
aggression, and is referred to as appetitive aggression. In contrast to reactive aggression,
which occurs to redress an emotional state caused by an outside source (Runions, 2013),
appetitive aggression is described as “infliction of harm on a victim for the purpose of
experiencing violence-related enjoyment beyond secondary rewards like status or material
benefits” (Weierstall et al., 2013). This definition matches exceedingly well with present
research on this behavior among college students, which indicates that approximately 30-40%
of individuals engage in cyberbullying behaviors simply for fun (Baldasare et al., 2012;
Francisco et al., 2015; Rafferty & Ven, 2014). Thus, although impulsivity is associated with
higher levels of cyberbullying in general, for college aged students this relationship is likely
accounted for by a different mechanism: sensation seeking.
Sensation seeking is defined as “a personality trait characterized by the extent of a
person’s desire for novelty and intensity of sensory stimulation” (Arnett, 1996). Level of
sensation seeking has been associated with aggression, with higher levels of sensation

seeking being predictive of aggressive behavior (Joireman, 2003; Dahlen et al., 2003;
Wilson and Scarpa, 2013). Kokkinos, Antoniadou, and Markos (2014) determined that
individuals who endorsed involvement as cyberbullies, or cyberbully/victims scored higher
on the Brief Sensation Seeking Scale- 8 (BSS-8) than individuals who were victims, as well
as individuals who were uninvolved in cyberbullying. This prior work indicates that those
who have higher levels of sensation seeking are more likely to cyberbully than those with low
levels of sensation seeking. Although both impulsivity and sensation seeking have been
linked to cyberbullying behavior, there is presently a limited body of research involving both
of these traits in this domain. Specifically, there is no research to date that determines
whether impulsivity and sensation seeking each have an independent influence on
cyberbullying. The primary goal of the current research will explore whether sensation
seeking accounts for the relationship between impulsivity and cyberbullying.
Impulsivity and Sensation Seeking
Although there has been limited research on the combined effects of impulsivity and
sensation seeking on cyberbullying, there exists a body of research linking these two traits in
other domains. Both traits have been linked to a variety of behaviors including, obesity,
substance use, risky sexual behavior, aggression, and gambling (Dietrich, de Wit &
Horstmann, 2016; Holmes et. al., 2016; Charnigo et. al., 2013; Fuentes et. al., 2016; Estevez
et. al., 2015). Though these constructs are similar, they appear to have differential effects on
these behaviors and demonstrate different developmental trajectories (Collado et. al., 2014;
Quinn & Hardin 2013). In order to better understand how these variables fit into existing
models of personality, Zuckerman and Glicksohn (2016) recently theorized that impulsivity is
related to physiological arousal, while sensation seeking is related to arousability. Thus, an
individual’s level of impulsivity would dictate whether or not a situation is itself arousing,
while their level of trait sensation seeking would determine how much arousal that situation

provided. Though this theoretical framework has not yet been explored empirically, it
suggests that impulsivity is more likely to influence sensation seeking rather than the reverse.
Given this framework, we predict that impulsivity will likely lead or contribute to sensation
seeking, which will then in turn lead to cyberbullying behavior.
Empathy and Cyberbullying
In addition to sensation seeking and impulsivity, empathy has been shown to be
related to cyberbullying behavior as well as to aggressive behavior more broadly. Empathy is
typically defined as “a vicarious emotional response to the perceived emotional experience of
others” (Olweus & Endresen, 1998). The relationship between aggressive behavior and
empathy has been extensively examined across a variety of groups, with empathy typically
being negatively correlated with aggressive behavior (Kaukiainen et al., 1999; Lovett &
Sheffiled, 2006; Yeo et al., 2011; Loudin,, 2003; Jolliffe & Farrington, 2004; van
Langen et al., 2014; Olewus & Endersen, 1998; Steffgen,, 2011). Among college aged
individuals specifically, Kokkinos, Antoniadou and Markos (2014) found that cyberbullying
was associated with lower empathy (as indicated by higher scores on the callous/unemotional
sub-scale of the Youth Psychopathy Inventory).
In the current work, a secondary goal is to examine whether trait empathy is related to
cyberbullying in college students. Previous research has demonstrated links between
proactive and to a lesser extent reactive aggression and callous-unemotional traits (Fanti,
Frick & Georgiou, 2009; White, Gordon, & Guerra, 2015). These traits include a lack of
empathy, emotional expression, and concern for others (White, Gordon, & Guerra, 2015). As
such, lower empathy has arguably been linked to higher levels of proactive and reactive
aggression. However, the relationship between appetitive aggression and empathy has yet to
be explored. Given this gap in the literature, we investigate whether trait empathy plays a
role in cyberbullying for college students. If cyberbullying in this population is better

explained by appetitive aggression, we would expect to see a weaker or non-existent
relationship for empathy and cyberbullying.
Cyberbullying and the Interpersonal Context
Most research on cyberbullying focuses on the peer-relationship aspect of this
behaviour, with a particular emphasis on how cyberbullying can be used as a method of
“social control” (Fransisco, 2015). Much of the research cite data demonstrating that
anywhere from “40-50%” (Kowalski & Limber, 2007) to “two-thirds” of victims of cyber-
bullying know their perpetrators (Juvonen & Gross, 2008). However, these figures fail to
account for the remaining one-third to half of victims who do not know their attacker(s).
Some studies argue that aggressor anonymity exists due to the anonymous nature of
interactions on the internet (Patchin & Hinduja, 2006). These same studies posit that victims
simply do not know their aggressors because aggressors are more successful at concealing
their identities due to being more “Computer-literate” (Hinduja & Patchin, 2007; Patchin &
Hinduja, 2006). While this may be true in some cases, this argument falls short in that it fails
to take into account a fundamentally unique aspect of the internet: the internet, as a medium
enables us to interact with (and possibly subsequently aggress against) individuals with
whom we have no real world connection (Bartlett, 2015; Runions, 2013). When surveying
individuals who had reportedly participated in cyberbullying behavior, Patchin and Hinduja
(2006) found that 26% of offenders did not appear to know their victim in person. Thus, it
appears that a good proportion of online aggressors may be cyberbullying a stranger.
However, present research has yet to explore in depth what distinguishes individuals
who cyberbully known versus unknown individuals. One possible explanation for this
difference in targets may be related to the concepts of impulsivity and sensation seeking, as
well as college students’ perceptions of cyberbullying behaviour. Many college students do
not consider themselves to be cyberbullies and argue that they engage in this behaviour for

fun or as a joke (Baldasare et al., 2012). If this need for entertainment is driven by traits such
as sensation seeking and impulsivity, a subset of individuals very well may utilize the
anonymity of the internet to cyberbully or otherwise harass strangers as well as known
persons in order to satisfy their need for entertainment.
The Current Work
The primary goal of this work is to examine whether the relationship between
impulsivity and cyberbullying is accounted for by sensation seeking. The personality traits of
impulsivity and sensation seeking have been shown to be related to cyberbullying behavior,
but it is still unclear whether both of these traits independently influence cyberbullying.
Given Zuckerman and Glicksohn’s (2016) theory on impulsivity, sensation seeking, and
arousal vs. arousability, it was hypothesized that impulsivity would lead to sensation seeking,
which in turn would lead to cyberbullying behavior. The second goal of this work is to
determine if cyberbullying of unknown targets follows the same pattern as cyberbullying
known targets. Additional goals of this work include exploring empathy’s role in
cyberbullying behavior, as well as extending the literature on cyberbullying behaviors in
college students.


The questionnaire had 605 respondents. Those who did not complete the
questionnaire (n = 34), those with duplicated IP addresses, (n = 37) and those who were
identified as multivariate outliers by Mahalanobis distance (n = 34) were excluded from the
analysis, which left 500 participants (30.6% male) for our analyses. Our sample consists of
undergraduate students attending a large public University located in the southeastern U.S.
Students received research credit in their psychology classes for participating in the present
study. The majority of participants were Caucasian (84.6%) with African American (9.2%),

Hispanic/Latino (1.6%), Asian American (2.4%), and Other (2.2%) forming the remainder of
the sample. Students who selected the “other” option for their ethnicity included those who
identified as multi-racial or Native American. The average age of the sample is 18.81 (SD=
1.30), with 49.5% reporting 18 years of age, 48.9% reported ages from 19 and 22, 1.6%
reporting an age older than 22, and 1 person chose not to report their age.
Participants were recruited through the University’s online system, and re-directed via
a link to Qualtrics, an online survey platform. On Qualtrics, participants completed informed
consent, demographic questions, as well as questions pertaining to their internet and social
media usage. Next they completed a cyberbullying scale about known targets, and then again
about unknown targets. Then, participants completed scales for sensation seeking,
impulsivity, and empathy. All participants received measures in this order to prevent the
possibility that participants would receive the empathy scale before the cyberbullying scale as
we were concerned that participants would respond in a socially desirable manner in another
order. Participants were then debriefed.
Demographics and Technology Use
Participants were asked to provide basic demographic information (age, gender, and
race/ethnicity) as well as information regarding what forms of technology/social media they
use. Instagram (93.2%), SnapChat (90.6%), Facebook (88.4%), GroupMe (67.6%), Twitter
(66.2%) were used by most of our sample, YikYak (32.6%), Vine (27%), and Tumblr
(17.6%) were used by some of our sample, whereas Google+ (10.4%), Online Gaming
(8.6%), Reddit (6.2%), LinkedIn (3.8%), StumbleUpon (1.2%), WordPress (.6%), Flickr
(.6%), Myspace (.4%), 4Chan (.4%), or Other Social Media (2.4%) were platforms less

frequently reported. Participants also reported the average daily number of hours they spent
online (M = 3.09, SD = 1.39) and on social media specifically (M = 2.80, SD = 1.30).

The Abbreviated Impulsiveness Scale (ABIS) (Coutlee et al., 2014) is an abbreviated
version of the Barratt Impulsiveness scale version 11 (BIS-11; Patton, 1995). The BIS-
11 is a psychometrically sound, widely validated measure of impulsive behavior in adults.
The ABIS is a 13 item scale with questions ranging on a four point scale: 1=rarely/never,
2=occasionally, 3=often, 4=almost always/always. Scores were calculated by averaging all
items together (Cronbach’s α = .868).
Sensation Seeking
The Brief Sensation Seeking Scale-8 (BSSS-8) (Hoyle et al., 2002) is a modified
version of Zuckerman’s Sensation Seeking Scale Form V (SSS-V; Zuckerman, 1996). The
scale asks participants to respond to questions regarding thrill and adventure seeking,
experience seeking, disinhibition, and susceptibility to boredom with eight items (responses
range 1= strongly disagree to 5= strongly agree). Item responses are combined as a total sum,
with higher scores indicating higher levels of sensation seeking (Cronbach’s α= .815).
The Eight Question Empathy scale or EQ-8 (Lawrence, et al., 2004; Lowen,
2010) is a psychometrically sound, eight item version of the Empathizing Quotient. This
measure assesses social skills, cognitive empathy and emotional reactivity. Participants
respond to eight questions on a four point Likert type scale (1=strongly agree to 4=strongly
disagree). Item responses are combined as a total sum, with higher scores indicating a greater
capacity for empathy (Cronbach’s α = .709).

Cyberbullying behavior
The Cyberbullying Scale (Stewart, 2014) is a 16-item measure of cyberbullying
behavior in youth. Two questions explicitly assess forms of technology (i.e. text messaging,
social media, smart phone apps, etc.) through which participants have been bullied, or have
bullied others. Using a five point Likert-type scale, the remaining 14 questions ask
participants to rate how often they have been victims of cyberbullying in the past few months,
with higher scores indicative of more experiences as a victim of.
Since a psychometrically sound measure of cyberbullying among college students did
not exist at the outset of the study, the CBS was modified for use with this population. This
process involved changing references to kids or children into more age appropriate modifiers
such as person. Additionally, the CBS was further modified to focus on acts of aggressors
rather than experiences of their victims; this new version was designated CBS-A. The first
two questions of the CBS-A, which ask participants to explicitly select the various
technological domains (such as Email, Instant Message, Social Media, etc.) where they have
experienced or engaged in cyberbullying, were not altered. The remaining questions were
altered to ask how often participants engaged in specific cyberbullying behaviors instead of
asking how often they had experienced them 1 . Participants took this scale twice, once asking
about whether they had engaged in cyberbullying against known targets (CBS-A Known or
CBS-AK, Cronbach’s α= .761), and whether they had engaged in cyberbullying against
unknown targets (CBS-A Unknown or CBS-AU, Cronbach’s α= .836).
Cyberbullying Victimization. The first question for each administration (CBS-AK and
CBS-AU) was used as the measure of victimization for study participants. This item “Do
others use any of the following to bully you?” asks participants to indicate all of the
following options that apply: email, text messages/Twitter, picture messages, instant

messaging, online video clips, social networking sites, chatrooms, virtual world (like Second
Life or the Sims), or developed a mean website or message board about you. Those
individuals who indicated they had been bullied using at least one form of technology were
categorized as having been admitted victims of cyberbullying, while those who did not
indicate that they had been bullied via at least one form technology were classified as having
no admitted victimization. Overall, 33.3% of participants reported being victims of
Explicit cyberbullying perpetration. The second question from the CBS-AK and the
CBS-AU were used as the measure of explicit admitted perpetration of cyberbullying. This
item asked “Do you use any of the following to bully people?” and the same responses given
in the victimization item were repeated here. Individuals were asked to indicate all of the
following methods they had used to cyberbully others (or through which they had been
cyberbullied). If participants indicated they had used at least one method of technology to
bully others, they were classified as having explicitly admitted to engaging in cyberbullying.
Participants who did not indicate that they used at least one method of technology were
classified as having no explicitly admitted cyberbullying. Overall, 14.3% of participants
explicitly admitting to engaging in cyberbullying.
Cyberbullying behaviors. A sum score was then calculated for questions 3-16 for
each administration (CBS-AK, Cronbach’s α= .761; and CBS-AU, Cronbach’s α= .836), for
items which do not explicitly use bullying to describe the behavior but still assess
cyberbullying behaviors, such as, “How often do you tell lies about another person in texts or
online to make others not like that person anymore?”. These scales calculate the extent of
cyberbullying behavior each participant reported engaging in. With higher scores being
indicative of more cyberbullying behavior towards both known (CBS-AK) and unknown
(CBS-AU) persons. Overall, 59% of the sample reported engaging in some cyberbullying of

known targets (CBS-AK), and 31% of the sample reported engaging in some cyberbullying
of unknown targets (CBS-AU). These scales are separated from explicitly admitted
cyberbullying, as it was hypothesized that many college students would endorse
cyberbullying behavior, but would not classify themselves as having cyberbullied .
Normality Assumptions and Missing Data
When we assessed our measures for normality, impulsivity, sensation seeking, and
empathy were normally distributed. However, the cyberbullying scales were not normally
distributed with skew (CBS-AK = 2.005; CBS-AU = 3.391), and kurtosis (CBS-AK = 4.388;
CBS-AU = 12.431) outside of the normal range. Given the social desirability against
admitting cyberbullying behaviors, and with the fact that many in our sample did not report
engaging in any cyberbullying this non-normality was unsurprising. To correct for this and
preserve a meaningful 0-point on the scale, a logarithmic transformation log10 (total score
+1) was used (following Tabachnick & Fidell, 2001). This transformation normalized the
CBS-AK scores (Skewnewss = .563, Kurtosis = -.815). However, kurtosis remained slightly
outside of the normal range for the CBS-AU scores (Skewnewss = 1.699, Kurtosis = 2.068).
As such, models including the values from the CBS-AU should be interpreted with some
An additional concern when using self-report measures to determine rates of sensitive
behaviors (i.e. mental health issues, potentially anti-social behavior, etc.) missing responses
may actually be systematic rather than random. Little’s Missing Completely at Random
(MCAR) was used to determine if missingness was problematic for any scale items.
Subsequently, mean imputation was used to replace any missingness when creating a total
score (Downey & King, 1998). The only scale affected by missingness was the self-report of
cyberbullying unknown victims (CBS-AU). As such, results from the subsequent model
containing this scale (CBS-AU) should be interpreted with caution.



A correlation matrix was first computed for all variables of interest (Table 1). Given
the fact that empathy only demonstrated a weak correlation with impulsivity, and was
unrelated to any of the other variables of interest, it was excluded from our models.

Table 1. Correlation Matrix
Measure 1 2 3 4 5
1. Cyberbullying Known Targets (CBS-AK) —
2. Cyberbullying Unknown Targets (CBS-AU) .624** —
3. Empathy .036 .047 —
4. Impulsivity .146** .085 .190** —
5. Sensation Seeking .220** .142** -.043 .432** —
**. Correlation is significant at the 0.01 level (2-tailed).

Conditional process modelling (Hayes, 2013) was first used to examine the indirect
effect of impulsivity on CBS-AK through sensation seeking. The model revealed that
sensation seeking accounts for the relationship between impulsivity and cyberbullying
(Figure 1).
Figure 1. Relationship between impulsivity and cyberbullying behavior of known targets
accounted for by sensation seeking.

Impulsivity Cyberbullying of
Known Targets


.406** .011**

.008** (.003)

The initial direct relationship between impulsivity and CBS-AK (the total effect) was
significant (c-path; b = .008, p = .001), showing greater impulsivity leading to greater

cyberbullying. There was also a significant positive relationship between impulsivity and
sensation seeking (a-path; b=.406, p < .001). When testing sensation seeking as a predictor
of CBS-AK evidence was found of a significant relationship (b-path; b =.011, p < .001). For
the crucial test of an indirect effect, the indirect path between impulsivity, sensation seeking
and CBS-AK was significant (ab path; b=.0045, p < .05). This effect is significantly different
from zero by bias-corrected bootstrap confidence interval (95% CI: [.002, .007]) based on
20,000 bootstrap samples (κ 2 = .076, 95% CI: [.040, .117]). In short, once sensation seeking
was accounted for when predicting CBS-AK, there was not a significant effect of impulsivity
on participants’ tendency to engage in cyberbullying (; b=.003, p=.194). This finding
suggests that level of sensation seeking accounts for the relationship between level of
impulsivity and participant’s tendency to engage in cyberbullying against known targets.
Conditional process modeling was next used to examine the indirect effect of
impulsivity on CBS-AU through sensation seeking. The model revealed impulsivity
indirectly influences cyberbullying behavior through sensation seeking (Figure 2).
Figure 2. Indirect pathway between impulsivity, sensation seeking, and cyberbullying
behavior of unknown targets.

Impulsivity Cyberbullying of
Unknown Targets


.406** .006**

.004 (.001)

The initial direct relationship between impulsivity and CBS-AU (the total effect) was not
significant (c-path; b = .0038, p = .058), indicating a lack of a direct relationship. Despite
this, there was a significant indirect path between impulsivity, sensation seeking and CBS-

AU. The same positive relationship between impulsivity and sensation seeking emerged as in
the previous model (a-path; b=.406, p < .001). When testing sensation seeking as a predictor
of CBS-AU evidence was found of a significant relationship (b-path; b =.006, p = .009). For
the crucial test of an indirect effect, the indirect path between impulsivity, sensation seeking
and CBS-AK was significant (ab path; b=.0025, p < .05). This effect is significantly different
from zero by bias-corrected bootstrap confidence interval (95% CI: [.0008, .0043]) based on
20,000 bootstrap samples (κ 2 = .051, 95% CI: [.016, .086]). Although there was not a
significant direct relationship between impulsivity and participants’ tendency to engage in
cyberbullying toward unknown targets, this relationship diminished further once sensation
seeking was accounted for (c’-path; b=.001, p=.592). This finding suggests there is an
indirect relationship between level of impulsivity and participant’s tendency to engage in
cyberbullying against known persons, via sensation seeking. These results are described in a
manner consistent with the Baron and Kenny method (Baron & Kenny, 1986) for ease of
understanding, however it should be noted that all variables were tested in each models at
once, using bias-corrected bootstrapping procedures (Hayes, 2013).
Given that impulsivity and sensation seeking are related constructs, two additional
models were additionally run that explored the relationship between sensation seeking and
cyberbullying when accounting for impulsivity, but neither of the indirect effects for these
models were significant.


Although impulsivity and sensation seeking have been linked to aggressive behavior,
neither have been examined alongside the other in relation to cyberbullying. Our results
provide the first empirical evidence that the relationship between impulsivity and
cyberbullying behavior is accounted for by sensation seeking in college students. This work
has both theoretical and applied implications, as this study provides empirical support in the
domain of cyberbullying behavior for Zuckerman and Glicksohn’s (2016) recent theory about

differences between impulsivity and sensation seeking. This theoretical distinction between
the two has important applied implications because understanding which of these constructs
is associated with cyberbullying behavior will lead to different prescriptions for anti-bullying
interventions. For instance, if college students are engaging in cyberbullying for a sensation
seeking thrill, then interventions can target motives associated with that thrill, whereas
interventions that target the impulsivity of that behavior may not be entirely successful
because impulsivity may only have an indirect relationship to cyberbullying.
Further, our study is the first to examine impulsivity and sensation seeking jointly in
relation to known and unknown cyberbullying targets, and is among the few studies that
makes such a distinction in the cyberbullying literature, more broadly. Cyberbullying is
typically framed within the context of peer relationships, which is supported in that 59% of
our participants reported engaging in cyberbullying behaviors against known targets. In
contrast, 31% of our sample reported engaging in cyberbullying behaviors against unknown
targets. It appears that, among our population of college students, a significant number of
individuals are engaging in cyberbullying outside of their peer networks. This mirrors
findings from a study of youth ages 12-18 conducted by Patchin and Hinduja (2006) that
found approximately 26% of cyberbullies did not personally know their victim. Our findings
suggest that although a direct relationship between impulsivity and cyberbullying of known
targets emerged, this same relationship did not emerge for cyberbullying of unknown targets,
despite the same indirect relationship emerging for both types of cyberbullying. Future
studies should explore other potential differences between these two behaviors and explore
those who are likely to commit them.
The current study provided evidence that empathy is weakly correlated with
impulsivity, but it was not related to cyberbullying behavior or sensation seeking. This
extends the theory that college students may be engaging in cyberbullying behavior as a form

of entertainment rather than as hostile aggression toward others. Future work should seek to
confirm whether cyberbullying is more related to appetitive rather than reactive or proactive
aggression. A limitation of the present research is that the CBS-AU scale failed to satisfy
Little’s MCAR. Consequently, missingness on this particular scale was not completely at
random. It is possible that administering the CBS-AU directly following the CBS-AK scale
created order effects, or participants may have answered in a socially desirable fashion. This
pattern of consistent answers on the CBS-AK, but missingness on the CBS-AU could
potentially reflect that many college aged individuals consider cyberbullying behavior within
peer groups to be normative, but do not consider engaging in the same behavior towards
strangers to be acceptable. Further work should potentially include a measure of participants’
tendency to answer in a socially desirable fashion. This distinction would be a potentially
interesting social discrimination between these two similar subsets of behavior and would
consequently be worth examining in future research
Finally, although our study only makes correlational, not causal claims about the
direction of the relationships between impulsivity, sensation seeking, and cyberbullying
behavior, understanding that sensation seeking underlies the relationship between impulsivity
and cyberbullying behavior is an important first step to increased theoretical and applied
knowledge about cyberbullying behavior. Future work should attempt to experimentally
manipulate or longitudinally examine these variables to explore the causal directions of these
variables. Overall, individual differences such as impulsivity and sensation seeking provide
researchers with an important lens with which to examine cyberbullying behavior.



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1 This work is based on the first author’s master’s thesis research conducted under the
supervision of the second and third authors.
2 Due to experimenter error, question four from the original measure was not included in
either administration of the scale.
3 A measure of participant attention was included to account for individuals who might not be
attending to question content. However, excluding participants according to this item did not
significantly change results. Thus, in order to obtain more statistical power these individuals
were included in the models presented.

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