Writing a mini research paper on a article that is provided.

E M P I R I C A L R E S E A R C H

Cyber Bullying and Physical Bullying in Adolescent Suicide: The Role of Violent Behavior and Substance Use

Brett J. Litwiller • Amy M. Brausch

Received: 6 November 2012 / Accepted: 29 January 2013 / Published online: 5 February 2013

� Springer Science+Business Media New York 2013

Abstract The impact of bullying in all forms on the

mental health and safety of adolescents is of particular

interest, especially in the wake of new methods of bullying

that victimize youths through technology. The current

study examined the relationship between victimization

from both physical and cyber bullying and adolescent

suicidal behavior. Violent behavior, substance use, and

unsafe sexual behavior were tested as mediators between

two forms of bullying, cyber and physical, and suicidal

behavior. Data were taken from a large risk-behavior

screening study with a sample of 4,693 public high school

students (mean age = 16.11, 47 % female). The study’s

findings showed that both physical bullying and cyber

bullying associated with substance use, violent behavior,

unsafe sexual behavior, and suicidal behavior. Substance

use, violent behavior, and unsafe sexual behavior also all

associated with suicidal behavior. Substance use and vio-

lent behavior partially mediated the relationship between

both forms of bullying and suicidal behavior. The com-

parable amount of variance in suicidal behavior accounted

for by both cyber bullying and physical bullying under-

scores the important of further cyber bullying research. The

direct association of each risk behavior with suicidal

behavior also underscores the importance of reducing risk

behaviors. Moreover, the role of violence and substance

use as mediating behaviors offers an explanation of how

risk behaviors can increase an adolescent’s likelihood of

suicidal behavior through habituation to physical pain and

psychological anxiety.

Keywords Adolescence � Suicide � Bullying � Cyber bullying � Substance abuse � Violence

Introduction

For American youth between the ages of 10 and 24, suicide

ranks as the third leading cause of death (Murphy et al.

2012). Recent increases in adolescent suicide rates have

motivated attempts to identify and understand the causes of

adolescent suicide (Cash and Bridge 2009). Research

findings (e.g., Klomek et al. 2010) and media reports of

adolescent suicides (e.g., Cloud 2010) have identified

bullying as an environmental stress that substantially

increases an adolescent’s suicide risk. A large amount of

theoretical and empirical evidence supports this relation-

ship between bullying and adolescent suicide. Bullying

consists of intentional and repeated aggression that

involves a disparity of power between the victim and the

perpetrator (Olweus 1993). Recent studies of bullying

prevalence show that approximately 20–35 % of adoles-

cents report involvement in bullying as a bully, victim, or

both (Levy et al. 2012). Given the high prevalence of

bullying in adolescence and its association with suicide

risk, it is crucial to further study this relationship.

Bullying in adolescence has been identified as occurring

in different forms, with different prevalence rates for the

various forms. Bullying behavior generally takes one of

four forms: physical (i.e., assault), verbal (i.e., threats or

insults), relational (exclusion or rumor spreading), and

cyber (i.e., aggressive texts or social network posts) (Wang

et al. 2009). Previous findings from longitudinal and cross-

B. J. Litwiller

Industrial/Organizational Psychology, University of Oklahoma,

455 West Lindsey Street, Norman, OK 73019, USA

A. M. Brausch (&) Department of Psychology, Western Kentucky University,

1906 College Heights Blvd., Bowling Green, KY 42101, USA

e-mail: [email protected]

123

J Youth Adolescence (2013) 42:675–684

DOI 10.1007/s10964-013-9925-5

sectional research have shown that each of these types of

bullying can increase the risk of a victimized adolescent

experiencing suicidal thoughts and behaviors (Klomek

et al. 2010). Several differences between cyber bullying

and more traditional forms of bullying have been identified.

Specifically, cyber bullying is perceived as different from

other types of bullying by victims (Slonje and Smith 2008)

more likely to occur outside of school (Smith et al. 2008).

Unlike victims of the other three types of bullying, victims

of cyber bullying are more likely to report depressive

symptoms than cyber bullies or bully-victims (Wang et al.

2011). Current research suggests that cyber bullying occurs

with less prevalence than the other types of bullying, but

still affects around 10–20 % percent of adolescents who

report being bullied or bullying others electronically

(Ybarra, Boyd, et al. 2012; Ybarra, Mitchell, et al. 2012).

The experience of bullying in childhood and adolescence is

important to study as research has shown that childhood

bullying predicts adult suicide attempts (Meltzer et al.

2011) as well as suicide deaths by the age of 25 (Klomek

et al. 2009).

Although each form of bullying has been shown to relate

to adolescent suicide, significant uncertainty exists

regarding the relationship between victimization from

bullying and suicidal behavior. Currently, there are no

empirically supported answers to questions of why vic-

timization increases the risk for suicidal behavior or how

the effects of cyber bullying compare to the effects of

specific traditional forms of bullying (e.g., physical, verbal,

and relational). A widely supported theory of suicide eti-

ology, called the interpersonal theory of suicide, appears to

have tremendous value for explaining the effects of bul-

lying on suicidal behavior (Joiner 2005). The interpersonal

theory of suicide posits that thwarted belongingness and

perceived burdensomeness cause suicidal desire. The the-

ory further states that individuals with high amounts of

suicidal desire only become capable of engaging in suicidal

behavior through habituation to the physically painful and

anxiety provoking nature of self-harming behaviors (Van

Orden et al. 2010).

Bullying and Suicidal Behavior

In the context of the interpersonal theory of suicide, vic-

timization from bullying would represent an environmental

cause of thwarted belongingness, perceived burdensome-

ness, and ultimately suicidal desire. Victimization from

bullying has been shown to associate with low self-esteem

(Juvonen et al. 2000), anxiety (Kumpulainen et al. 1998),

and depression (Fekkes et al. 2004; Klomek et al. 2007).

Low self-esteem, anxiety, and depression also have all

been identified as correlates of thwarted belongingness and

perceived burdensomeness (Van Orden et al. 2008; Van

Orden et al. 2012). To result in suicidal behavior, victim-

ized adolescents who are habituated to the physical and

psychological pain associated with suicidal behavior may

then develop suicidal desire and capability. Consequently,

one attempt to explain how bullying results in suicidal

behavior is to examine risk behaviors that co-vary with

both bullying and suicidal behavior and may habituate

adolescents to physical pain and psychological anxiety.

Joiner (2005) proposed that painful and provocative

behaviors, such as drug use, prostitution, and violent

behavior may provide pathways to an acquired capability

for suicidal behavior. In adults, these painful and provoc-

ative behaviors have been shown to increase an individ-

ual’s capability for self-harm (Van Orden et al. 2008). The

current study attempted to examine some behaviors that

may result in habituation to physical pain and emotional

distress that also relate to bullying in an adolescent sample.

Risk Behaviors

Several painful and provocative behaviors have been iden-

tified consistently as behaviors that relate to both bullying

and adolescent suicidal behavior. Of all such risk behaviors,

alcohol and/or illicit drug use has most frequently been

shown to relate to bullying and suicidal behavior. Victim-

ization from bullying generally has been shown to associate

with or predict adolescent alcohol/drug use (Mitchell et al.

2007; Windle 1994). Findings from these studies of bullying

victimization and alcohol use suggest that experiences of

bullying produce negative psychological states that increase

the probability than an adolescent will engage in substance

use. This view of alcohol use as a means to cope with neg-

ative affect is consistent with past research related to the

etiology of adolescent substance use (Sher, Grekin, and

Williams 2005). Findings from other studies also have

shown substance use to increase an adolescent’s risk of

performing suicidal behaviors (Bolognini et al. 2003; Dey-

kin and Buka 1994; Fombonne 1998; Spirito et al. 2003).

These findings suggest that substance use may contribute to

habituation of physical pain and psychological anxiety

associated with self-harm. Specifically, substance use may

enable adolescents already experiencing suicidal desire

to perform suicidal behaviors by decreasing inhibition,

encouraging self-harming behaviors, and exacerbating pre-

existing negative moods (Gould et al. 1998).

Like substance use, the amount of violent or physically

aggressive behavior exhibited by adolescents also relates

positively to victimization from bullying and suicidal

behavior. In particular, adolescents who experience phys-

ically violent victimization have been shown to be more

likely to act violently towards others (Cleary 2000; Ma

2001; Nickerson and Slater 2009). Klomek et al. (2007)

found that adolescents who reported being both a bully and

676 J Youth Adolescence (2013) 42:675–684

123

a victim of bullying were most at risk. Taken together,

these findings related to bullying and the performance of

violent behavior suggest a possible cyclical relationship

between being a victim of violent bullying and violently

bullying others. Additional studies also have shown that

engaging in violent behavior increases the probability that

an adolescent will perform suicidal behavior (Borowsky

et al. 2001; Evans et al. 2001). The findings regarding

bullying, violent behavior, and suicidal behavior support

theoretical views that physical pain and psychological

anxiety provoked by violent behavior may habituate ado-

lescents to the physical and psychological pain associated

with suicidal behavior (Joiner 2005).

Unsafe sexual behavior, such as unprotected sex,

anonymous sex, or coerced sex, constitutes a third painful

and provocative behavior that co-varies with both bullying

and adolescent suicidal behavior. Specifically, adolescents

who reported being victims of relational or verbal bullying

have been found to be more likely to engage in unsafe

sexual behavior (Zweig et al. 2002). These findings suggest

that sexual behavior may represent a means of coping with

negative psychological consequences of victimization.

Investigations of these behaviors demonstrate that unsafe

sexual behavior may have consequences comparable to

victimization. Several studies have shown that unsafe

sexual behavior increased the likelihood that an adolescent

would engage in suicidal behavior (Houck et al. 2008;

Silverman et al. 2001). Like violent behavior and substance

use, repeated experiences of unsafe sexual behavior may

habituate adolescents to the physical pain and psycholog-

ical anxieties associated with suicidal behavior and exac-

erbate any suicidal desire caused by being a victim of

bullying.

Rationale and Hypotheses

The present study attempted to examine the role of

painful and provocative risk behaviors as potential

explanations for how adolescents who are bullied acquire

the ability to perform suicidal behaviors. This study also

attempted to determine if a novel form of bullying, cyber

bullying, had a similar relationship with suicidal behavior

as a physical bullying. To examine these research ques-

tions, the study tested two different models that predicted

adolescent suicidal behavior. Each model used a different

form of bullying, cyber or physical, to predict suicidal

behavior. Both models hypothesized that the amount of

bullying experienced by an adolescent would positively

predict substance use, violent behavior, unsafe sexual

behavior, and ultimately suicidal behavior. Additionally,

hypotheses presented by the models posited that sub-

stance use, violent behavior, and unsafe sexual behavior

would each uniquely predict suicidal behavior and

mediate the relationship between both forms of bullying

and suicidal behavior. If supported as mediators, sub-

stance use, violent behavior, and unsafe sexual behavior

would provide three related explanations for how ado-

lescents who experienced bullying acquired the capability

to perform suicidal behavior.

Method

Participants and Procedure

Data for the current study were accessed from an existing

database of a large-scale community mental health

screening in a rural area of a Midwestern state in the US

The data collection occurred in the spring of 2008 and was

collected from 27 high schools in a seven-county region.

All high schools in the region received the opportunity

to participate in the survey. Regional enrollment for all

high schools for the academic year was 7,232 and 4,693

students completed the survey, for a participation rate of

65 %. A local coalition, sponsored by the community hos-

pital, conducts biennial screenings of area high schools for

prevalence and prevention purposes, and received approval

from the hospital’s Human Subjects Review Board. Simi-

larly, the authors consulted with the university Institutional

Review Board with whom both authors were previously

affiliated, and received approval for analyzing an archival

data set. The coalition utilized passive parental consent,

and students were not asked to sign assent documents to

protect confidentiality of students at schools with low

enrollment (e.g., total student body \100). Adolescents were between the ages of 14 and 19 years

old (M = 16.11, SD = 1.20) and were all high school

students. The ethnic distribution of the sample was 89 %

White, 1.5 % Black, 1.5 % Hispanic, 1.0 % Asian, 2.0 %

American Indian, 1.0 % Native Hawaiian or other Pacific

Islander, and 3.6 % multi-racial. The sample had a near

equal distribution of participants in the freshmen, sopho-

more, junior, and senior grade levels. Participant sex was

equally distributed with 47 % percent of the sample male,

47 % female, and 6 % of participants not identifying a sex.

Data collection took place at schools attended by the

adolescents during school days. Generally, data was col-

lected from large groups of students who sat at individual

desks in classrooms. Before beginning the survey, research

assistants and staff from the coalition instructed adoles-

cents that their participation was completely voluntary and

that they could stop at any time for any reason. Students

were told to mark their responses on a bubble sheet and

avoid marking any identifying information on the response

sheet or survey packet. Throughout the survey, project staff

J Youth Adolescence (2013) 42:675–684 677

123

members were present to collect response sheets and

answer any participant questions.

Measures

During the study, adolescents completed a packet of survey

questions which mainly included items from the Youth Risk

Behavior Survey (YRBS; CDC 2008), but also included

items written by coalition members or consulting board

members to further assess health and risk behaviors of

interest to the region. The Youth Risk Behavior Survey is a

scale created by the Centers for Disease Control and Pre-

vention (CDC) to assess the prevalence of risk behaviors that

contribute to the leading causes of death, disability, and

social problems among youth and adults in the United States.

The scale contains approximately 98 self-report items

designed to measure the frequency and severity of behaviors

within six categories: violent and self-injurious behavior,

tobacco use, alcohol and other drug use, sexual behavior,

unhealthy dietary behaviors, and physical inactivity (CDC

2008). Several studies have examined the psychometric

properties of the YRBS. The results of these examinations

indicate that the YRBS has sufficient levels of test–retest

reliability and that adolescents accurately report behaviors

on the measure (Brener et al. 1995, 2002, 2003). No formal

subscales or scoring procedure exists for the YRBS. In the

present study, subscales were created by grouping items by

content, and also through the use of internal consistency

analyses. Any item that lowered a subscale’s alpha value

below .70 was discarded. Through internal consistency

analyses, six subscales were derived. These subscales mea-

sured physical bullying, cyber bullying, suicidal behavior,

drug use, violence, and sexual behavior.

Physical Bullying

The physical bullying subscale consisted of 3 items from

the Youth Risk Behavior Survey (YRBS; CDC 2008)

intended to measure how frequently adolescents were

victims of bullying at school. All items were presented

with Likert scales that asked adolescents to rate how fre-

quently they experienced physical bullying or fears of

physical bullying victimization during the past 30 days

(e.g., ‘‘On how many days did you not go to school because

you felt you would be unsafe on your way to or from

school?’’, ‘‘During the past 30 days, how many times has

someone threatened or injured you with a weapon, such as

gun, knife, or club on school property?’’, and ‘‘During the

past 30 days, how often has someone threatened or injured

you on school property?’’). The 3 items were summed with

higher scores corresponding to more experiences of being

physically bullied. The subscale demonstrated a satisfac-

tory level of internal consistency (a = .77).

Cyber Bullying

The cyber bullying subscale consisted of 3 items written by

coalition members intended to measure how frequently

adolescents were bullied by peers through electronic

communication mediums (i.e., text message, social net-

working). All items were presented with dichotomous

scales that asked participants to respond ‘‘Yes’’ or ‘‘No’’ to

questions about cyber bullying (e.g., ‘‘Has someone spread

a rumor about you online, in a chat room, through a social

networking website, in emails, or through a text mes-

sage?’’, ‘‘Has there even been an inappropriate photo post

of you online (illegal activity or sexually compromising)?’’,

and ‘‘Has anyone sent you a threatening or aggressive,

e-mail, instant message, or text message?’’). The format of

these items was consistent with the recommended item

format for studying cyber bullying (Wang et al. 2009). The 3

items were summed with higher scores corresponding to

more experiences of being victimized by cyber bullying.

The subscale demonstrated a satisfactory level of internal

consistency (a = .71).

Suicidal Behavior

The suicidal behavior subscale contained four items from

the Youth Risk Behavior Survey (YRBS; CDC 2008),

which were used to assess how many suicidal thoughts

and behaviors adolescents experienced during the past year.

The items asked adolescents to respond ‘‘no’’ or ‘‘yes’’ to

items measuring suicidal ideation (e.g., ‘‘During the past

12 months, did you ever seriously consider attempting sui-

cide?’’), suicide planning (e.g., ‘‘During the past 12 months

did you make a plan about how you would attempt sui-

cide?’’), self-injury and suicide attempts (e.g., ‘‘During the

past 12 months, how many times did you actually attempt

suicide?’’). The suicidal behavior subscale had good internal

consistency (a = .88).

Substance Use

The substance use subscale consisted of 17 items from

Monitoring the Future survey (MTF; Johnston et al. 2009)

and 7 coalition-authored items designed to assess adoles-

cent’s history of using alcohol, marijuana, inhalants, LSD,

ecstasy, cocaine, crack, heroine, methamphetamine, tran-

quilizers, cigarettes, and smokeless tobacco. Adolescents

rated their responses on Likert scales which assessed fre-

quency of use. Higher ratings indicated more frequent,

reckless, or earlier use of a specific substance (e.g., ‘‘During

your life how many times have you used methampheta-

mines?’’). The substance use subscale demonstrated suffi-

cient internal consistency (a = .87).

678 J Youth Adolescence (2013) 42:675–684

123

Violent Behavior

The violent behavior subscale contained 4 items from the

Youth Risk Behavior Survey (YRBS; CDC 2008) which

measured the violent or threatening behavior exhibited by

adolescents. The items asked adolescents to rate how fre-

quently they hurt another student, threatened another stu-

dent, and carried a weapon during the last 30 days (e.g.,

‘‘During the past 30 days, on how many days did you carry

a gun?’’ or ‘‘During the past 30 days, how many times were

you in a physical fight on school property?’’). Adolescents

rated their responses to each item on Likert scales. The

violent behavior subscale had good internal consistency

(a = .81).

Sexual Behavior

The sexual behavior subscale consisted of 5 items from the

Youth Risk Behavior Survey (YRBS; CDC 2008). These

items measured how early adolescents began having sex,

their number of sexual partners, their history of sexually

transmitted disease, pregnancy, and the amount of protec-

tion they used while having sex. Adolescents rated their

history of sexual behavior on Likert scales. A lower score

indicated a lower amount of potentially dangerous sexual

behavior (e.g., ‘‘The last time you had sexual intercourse,

what one method did you or your partner use to prevent

pregnancy?’’ or ‘‘During the past three months, with how

many people did you have sexual intercourse?’’). The

sexual behavior subscale had a sufficient level of internal

consistency (a = .87).

Missing Data

As a result of the large scale nature of data collection and

the limited amount of time available to complete the

questionnaire, a number of participants failed to complete

the survey or skipped survey items. Of the original 4,693

participants, only 3838 participants completed all items.

Missing data were replaced by multiple imputation, a

procedure for generating multiple simulated values for

each missing data point (Schafer 1997) to create an analytic

sample of 4,376. Complete data sets were created from the

original data sets using the SPSS Missing Values 20 pro-

gram. One thousand Monte Carlo Marko Chain imputa-

tions were calculated, with every 200 imputations used to

create a total of 5 data sets. Statistical analyses were con-

ducted on each data set and then combined to yield a single

set of results applying ‘‘Rubin’s rules’’ for combining the

results of an analysis of multiple imputed data sets (Rubin

1987).

Results

Descriptive statistics and intercorrelations amongst study

variables appear in Table 1. Prevalence rates of cyber

bullying, physical bullying were comparable to prevalence

rates from previously reviewed studies (e.g., Levy et al.

2012; Ybarra, Mitchell, et al. 2012) and the prevalence rate

of suicidal ideation and suicidal behavior was higher than

in previous studies. Subscale responses indicated that 33 %

of adolescents reported being a victim of physical bullying,

23 % of adolescent reported being a victim of cyber bul-

lying, and 30 % of adolescents reported experiencing sui-

cidal ideation or performing suicidal behavior in the past

year. All study variables were significantly correlated with

each other. The observed correlations supported the two

hypothesized multiple mediator models. To test both

mediational models, a bootstrapping approach was used.

The bootstrapping (or resampling) approach to mediational

analysis enables the inclusion of multiple mediators in a

single model that does not impose the assumption of nor-

mality of the sampling distribution (Preacher and Hayes

2008). This analytic approach provides more accurate Type

1 error rates and greater power for detecting mediating

effects (Preacher and Hayes 2008). In models with multiple

mediators, bootstrapping entails repeatedly sampling from

the data set and estimating the total indirect effect and

specific indirect effects in each resampled data set. These

Table 1 Subscale, Cronbach’s alpha values, descriptive statistics and zero-order correlations between bullying, risk behaviors, and suicidal behavior

Scale a M SD Skew 1 2 3 4 5 6

1 Physical bullying .77 4.72 2.86 2.01 –

2 Cyber bulling .71 5.38 1.60 .60 .55* –

3 Substance use .87 40.72 18.96 1.29 .70* .57* –

4 Violence .81 6.62 3.71 2.09 .79* .53* .63* –

5 Sexual behavior .87 12.20 7.03 .48 .42* .29* .65* .44* –

6 Suicidal behavior .88 6.72 2.28 1.17 .73* .68* .74* .67* .45* –

* p \ .001

J Youth Adolescence (2013) 42:675–684 679

123

estimates are used to construct confidence intervals for the

total and specific indirect effects. The total indirect effect

describes cumulatively how all of the mediators transmits

the effect of the predictor variable on the outcome variable

and the specific indirect effects describe how each indi-

vidual mediator transmit the effect of the predictor variable

on the outcome variable.

The analytic diagram (see Fig. 1) presents the concep-

tual meaning of each coefficient in both multiple mediator

models. The ‘‘a’’ coefficients represent the effect of the

predictor variable on each mediator, the ‘‘b’’ coefficients

represent the effect of each mediator on suicidal behavior

when controlling for the effect of the predictor variable, the

‘‘c’’ represents the total effect of the predictor on the out-

come, and the ‘‘c0’’ coefficient represents the direct effect of the predictor variable on suicidal behavior. In addition to

the variables featured in the analytic diagram, both multi-

ple mediation models controlled for the effects of gender,

age, and ethnicity. An SPSS Macro for multiple mediation

was used to examine the hypotheses (Preacher and Hayes

2008). The analyses used 1000 bootstrap samples to create

a population of indirect effects. This population of indirect

effects enabled the creation of ninety-five percent confi-

dence intervals that evaluated the significance and magni-

tude of indirect effects generated through the bootstrapping

technique. A significant effect does not have a confidence

interval that includes zero. The regression coefficients

generated by both multiple mediation models are unstan-

dardized. The scale of unstandardized coefficients is

determined by the scale of measurement of variables

included in the analysis Unstandardized metrics are the

preferred metric in causal modeling because standardized

effect sizes provide no additional meaning and can actually

obscure interpretation of the effects of some predictors

(Hayes 2009).

Results from the first mediation model showed that

physical bullying had significant and positive direct effects

on substance use, violent behavior, sexual behavior, and

suicidal behavior. Tests of the direct effects of the medi-

ators on the outcome showed that substance use and violent

behavior had significant direct positive effects on suicidal

behavior. Sexual behavior, however, did not have a sig-

nificant direct effect on suicidal behavior in the presence of

other mediators. The total effect of physical bullying on

suicidal behavior was also significant and positive. Overall,

the model that used physical bullying as a predictor

explained 64 % of the variance in suicidal behavior (see

Fig. 2).

The hypothesized mediators of physical bullying’s

effects on suicidal behavior had a significant total indirect

effect on suicidal behavior and several significant specific

indirect effects on suicidal behavior. The total indirect

effect was significant (CI.95 = .26, .32) (see Table 2).

Examination of the proportion of effects mediated shows

that 50 % of the total effect of physical bullying on suicidal

behavior was mediated by substance use and violent

behavior. The specific indirect effects derived by the model

indicate substance use (CI.95 = .22, .27) and violent

behavior (CI.95 = .02, .08) both uniquely mediated the

effects of physical bullying on suicidal behavior (see

Table 2).

Results from the multiple mediator model that used

cyber bullying as the predictor showed direct effects sim-

ilar to the ones found by the physical bullying model.

Specifically, results showed that cyber bullying had sig-

nificant and positive direct effects on substance use, violent

Substance Use

Bullying

(Cyber & Physical) Suicidal Behavior

Violent Behavior

Sexual Behavior

Bullying Suicidal Behavior c

b1

b2 b3

a1 a2

a3

c’

Fig. 1 Analytic diagram for the multiple mediation model proposed

Substance Use

Physical Bullying Suicidal Behavior R2 adj = .64

Violent Behavior

Sexual Behavior

Physical Bullying Suicidal Behavior .58*

.29*

.05*

.001

.046*

4.60*

1.04*

1.06*

Fig. 2 Physical bullying, risk behaviors and suicidal behavior. * p\.001

Table 2 Total and specific mediated effects and their

corresponding bootstrap

confidence intervals for physical

bullying and cyber bullying

Indirect Effects Physical bullying Cyber bullying

Estimate SE 95 % CIs Estimate SE 95 % CIs

Substance use .25 .011 (.22, .27) .32 .012 (.28, .35)

Physical violence .048 .02 (.02, .08) .16 .01 (.14, .19)

Sexual behavior \.001 .01 (.00, .001) .003 .005 (.00, .015) Total .29 .01 (.26, .32) .48 .013 (.45, .51)

680 J Youth Adolescence (2013) 42:675–684

123

behavior, sexual behavior, and suicidal behavior. Tests of

the direct effects of the mediators on the outcome showed

that substance use and violent behavior had significant

direct positive effects on suicidal behavior. Additionally,

sexual behavior did not have a significant direct on suicidal

behavior in the presence of other mediators. The total

effect of cyber bullying on suicidal behavior was also

significant and positive. Overall, the model that used cyber

bullying as a predictor explained 67 % of the variance in

suicidal behavior (see Fig. 3).

The hypothesized mediators of cyber bullying’s effects

on suicidal behavior had a significant total indirect effect on

suicidal behavior and several significant specific indirect

effects on suicidal behavior. The total indirect effect was

significant (CI.95 = .45, .51) (see Table 2). Examination of

the proportion of effects mediated showed that 48 % of the

total effect of cyber bullying on suicidal behavior was

partially mediated by substance use and violent behavior.

The proportion of effect mediated in the cyber bullying

model is substantially larger than the proportion of effect

mediated in the physical bullying model. The specific

indirect effects derived by the cyber bullying model indi-

cated that substance use (CI.95 = .28, .35) and violent

behavior (CI.95 = .14, .19) both uniquely mediated the

effects of cyber bullying on suicidal behavior (see Table 2).

Discussion

With suicide remaining one of the leading causes of death

for adolescents, recent research has emphasized the iden-

tification of factors in adolescent suicide risk (Brausch and

Gutierrez 2010). Bullying victimization repeatedly has

been found to associate with or predict adolescent suicide

risk (Kim and Leventhal 2008). Although clear evidence

for links between bullying victimization and suicide exists,

no previous research has attempted to determine empiri-

cally why bullying might increase an adolescent’s risk for

suicidal behavior. Behavioral outcomes associated with

being a victim of bullying may increase an adolescent’s

suicide risk (e.g., Wang et al. 2011).

Consequently, this study examined whether three

behavioral outcomes frequently associated with bullying

and suicidal behavior, substance use, violent behavior, and

unsafe sexual behavior, mediated the frequently observed

relationship between victimization from bullying and

adolescent suicidal behavior. Two types of bullying were

examined in this study, cyber bullying and physically

violent bullying. Generally, the results revealed that both

types of bullying, cyber and physical, positively predicted

suicidal behavior, substance use, violent behavior, and

unsafe sexual behavior. Cyber bullying accounted for

slightly more variance in all four of these behaviors than

physical bullying. Findings from the two models tested also

showed that two risk behaviors, substance use and violent

behavior, positively predicted adolescent suicidal behavior

and partially mediated the relationship between both forms

of bullying and suicidal behavior.

The role of physical bullying as a factor that may

increase the risk of adolescent suicidal behavior supports

previous cross-sectional and longitudinal research that has

shown a relationship between the two variables (Klomek

et al. 2010). The relationship between cyber bullying and

suicidal behavior in the current study, however, extends

findings from limited previous research on cyber bullying

which used measures that were less behaviorally specific

and did not include assessment of communication with

social networks (Klomek et al. 2008; Hinduja and Patchin

2010). The current study also showed that cyber bullying

had a similar sized effect on suicidal behavior, substance

use, violent behavior, and unsafe sexual behavior as phys-

ical bullying. This finding provides further evidence of the

potential consequences of cyber bullying. In contrast to

physical bullying, cyber bullying has been found to be more

difficult to avoid, anonymous, and likely to coincide with

other forms of bullying (Li 2005). Although not specifically

examined in this study, victims of cyber bullying may more

be likely to experience negative psychological states, thus

contributing to feelings of thwarted belongingness and

perceived burdensomeness. If cyber bullying activates

feeling like one does not belong or is a burden to others, an

adolescent’s risk of suicidal behavior may increase, espe-

cially if adolescents are also engaging in risk behaviors that

may habituate them to pain and fear of death.

Bullying, Risk Behaviors and Suicide

The two models tested in this study supported this possible

effect of cyber bullying by showing that substance use and

violent behavior could explain how both physical bullying

and cyber bullying increase suicidal behavior risk for ado-

lescents. Correlates of victimization, such as low self-esteem

(Juvonen et al. 2000), anxiety (Kumpulainen et al. 1998),

and depression (Fekkes et al. 2004), could motivate

Cyber Bullying Suicidal Behavior .97*

Substance Use

Cyber Bullying Suicidal Behavior R2 adj = .67

Violent Behavior

Sexual Behavior

.05*

.13* .02

5.42*

1.22*

.1.33*

.49*

Fig. 3 Cyber bullying, risk behaviors and suicidal behavior. * p \ .001

J Youth Adolescence (2013) 42:675–684 681

123

adolescents to use substances to cope with negative feelings.

If an adolescent’s substance use resulted in painful or pro-

vocative behaviors, such as self-injection, then the adoles-

cent may acquire the capability to overcome the physical

pain and psychological stress that prevents many people with

suicidal desire from actually performing suicidal behavior

(Joiner 2005). This possibility that substance use could help

adolescents become more capable of performing suicidal

behavior draws support from previous research that shows

adolescent substance use to be one of the more frequently

identified predictors of suicidal behavior for adolescents

(e.g., Bolognini et al. 2003; Spirito et al. 2003).

Findings from both multiple mediator models suggest

that violent behavior has a similar role as substance use in

inoculating adolescents to physical pain and psychological

fears that prevent suicidal behavior. Certain behaviors

related to violent behavior, such as participating in physical

fights, have been shown to increase suicidal behavior

capability in adults (Van Orden et al. 2008). Many of the

injury and pain outcomes associated with physical fights

could slowly habituate adolescents to suicidal behavior.

Moreover, the well-established presence of a victim-bully

cycle (Ma 2000; Pellegrini and Bartini 2001) suggests that

violent behavior may mediate the relationship between

bullying victimization and suicidal behavior because ado-

lescents who are bullied are more likely to bully others.

This bullying of others could result in the same type of

violent behavior that has been shown many time to increase

an adolescent’s risk of suicidal behavior (Borowsky et al.

2001; Evans et al. 2001; Swahn et al. 2008).

Unlike substance use and violent behavior, unsafe sexual

behavior was not found to mediate the relationship between

victimization from either form of bullying and suicidal

behavior in this study. It was also not a significant predictor

of suicidal behavior in either model. This lack of prediction

indicates that unsafe sexual behavior by itself does not

enable suicidal behavior. Especially painful and dangerous

sexual behaviors that were not measured in this study, such

as prostitution or sexual assault, may represent the only

sexual behaviors that can habituate people to the physical

and psychological pain associated with self-harm. Although

unsafe sexual behavior did not predict suicidal behavior,

both forms of bullying did predict sexual behavior. This

finding provides the first known evidence of a link between

bullying and sexual behavior and suggests that negative

emotional states associated with bullying may still have life

altering consequences for adolescents apart from suicidal

behavior, substance use, and violent behavior.

Limitations

A number of limitations existed in this study as a result of

the sample size, measures used, and cross-sectional study

design. The large size of the sample likely inflated the

statistical significance of several regression model findings.

Although statistically significant, several findings from the

study may possess lesser clinical significance than similar

findings obtained from a smaller sample (Odgaard and

Fowler 2010). The use of a cross-sectional design prevents

the testing of directionality of the relationship between

victimization and suicidal behavior. The use of self-report

measures to assess victimization from bullying also may

limit the findings because it excluded other frequently used

methods of collecting victimization data, such as reports

from parents, teachers, and peers, which could have

improved the victimization measure and introduces the

possibility of shared method variance. The bullying mea-

sures also contain several limitations. Specifically, dis-

crepancies in the length assessed between the cyber

bullying and physical bullying measures limit comparisons

of the two forms of bullying in this study. Also, the com-

bination of threats and actual experiences measured in both

of the bullying measures reduce their construct validity and

introduce a need for more precise measurement in future

studies. As another measurement limitation, the measures

of sexual behavior and substance used in this study were

widely used measures of those constructs that did not

specifically assess the pain and fear habituating aspects of

substance use and sexual behavior.

Future Directions

Despite the above limitations, results from this study do

provide the first empirically supported explanation for how

bullying may increase suicide risk. Future research could

extend the findings from this study by further examining

the value of the Interpersonal Theory of Suicide (Joiner

2005) as an explanation for the relationship between bul-

lying and suicidal behavior. Specifically, future studies

related to bullying and suicide should measure constructs

such as perceived burdensomeness, thwarted belonging-

ness, suicidal behavior, and other painful or provocative

behavior that could be included in a model to explain how

bullying ultimately increases an adolescent’s risk for sui-

cidal behavior. With sufficient measurement of the various

types of bullying, future research could also attempt to

determine if relational, physical, verbal, and cyber bullying

differentially affect suicidal behavior.

Conclusion

Models of adolescent risk behavior often examine how a

sequence of events that lead to a risk behavior can occur as a

result of exposure to certain risk factors (Compas et al. 1995).

This cross-sectional study provides the first indication for

682 J Youth Adolescence (2013) 42:675–684

123

how bullying victimization may trigger a sequence of events

that results in suicidal behavior. Rejection by peers and

bullying specifically has been found to trigger psychological

processes that result in externalizing behavior (Deater-

Deckard 2001). Key findings from this study show that

harmful externalizing behaviors that can develop during

adolescence, such as substance use and violent behavior,

mediate the effects between of both cyber and physical

bullying on suicidal behavior. This finding draws support

from theory regarding the importance of habituation to pain

to acquiring the ability to perform self-injury (Joiner 2005)

and provides modifiable behaviors that should receive

attention in interventions aimed at preventing adolescent

suicide. Professionals who aid adolescent victims of bullying

should encourage healthy coping behaviors and support

interventions that diminish the probability of an adolescent

engaging in substance use or violent behavior.

Acknowledgments The authors would like to thank and acknowl- edge Gaye Harrison and the I Sing the Body Electric (888-550-7464;

www.isbe.org) coalition for their support of these analyses by

granting access to their existing data.

Author Contributions BL conceived of the study, participated in its design and coordination, performed the statistical analyses, par-

ticipated in the interpretation of the data, and drafted the manuscript;

AB participated in the design and coordination of the study, partici-

pated in the interpretation of the data, and helped to draft the man-

uscript; All authors read and approved the final manuscript.

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Author Biographies

Brett Litwiller is a Ph.D. candidate in Industrial/Organizational Psychology at the University of Oklahoma. He earned his Master’s in

Clinical Psychology from Eastern Illinois University. His major

research interests include risk-taking behaviors in adolescents, as well

as individual differences and organizational characteristics that

influence physical and mental health outcomes experienced by

employees in the workplace.

Amy Brausch is an Assistant Professor of Psychology at Western Kentucky University. She received her Ph.D. in Clinical Psychology

from Northern Illinois University. Her major research interests

encompass adolescent suicide and non-suicidal self-injury, risk-

taking behaviors, body image, and disordered eating.

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