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Abstract

While previous studies have identified that school bullying and cyberbullying victimization among adolescents is associated with suicidal thoughts and attempts, no work has measured the severity of bullying incidents and their impact on the youth at school within that context. As such, a survey was distributed to a representative sample of U.S. youth between the ages of 12 and 17, and students who experienced either school-based or online bullying were significantly more likely to report suicidal thoughts. Students who reported being bullied at school and online were even more likely to report not just suicidal thoughts, but also attempts. Those who were bullied or cyberbullied in a way that affected them at school were also at a higher risk for suicidal thoughts and attempts. We discuss how school communities can provide substantive instructional and emotional support to all teens, particularly with the increased prominence of these issues over the last decade.
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Journal of School Violence
ISSN: 1538-8220 (Print) 1538-8239 (Online) Journal homepage: http://www.tandfonline.com/loi/wjsv20
Connecting Adolescent Suicide to the Severity of
Bullying and Cyberbullying
Sameer Hinduja & Justin W. Patchin
To cite this article: Sameer Hinduja & Justin W. Patchin (2018): Connecting Adolescent
Suicide to the Severity of Bullying and Cyberbullying, Journal of School Violence, DOI:
10.1080/15388220.2018.1492417
To link to this article: https://doi.org/10.1080/15388220.2018.1492417
Published online: 22 Aug 2018.
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Connecting Adolescent Suicide to the Severity of Bullying and
Cyberbullying
Sameer Hinduja
a
and Justin W. Patchin
b
a
School of Criminology and Criminal Justice, Florida Atlantic University, Jupiter, Florida, USA;
b
Department of
Political Science, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, USA
ABSTRACT
While previous studies have identified that school bullying and cyberbully-
ing victimization among adolescents is associated with suicidal thoughts
and attempts, no work has measured the severity of bullying incidents and
their impact on the youth at school within that context. As such, a survey
was distributed to a representative sample of U.S. youth between the ages
of 12 and 17, and students who experienced either school-based or online
bullying were significantly more likely to report suicidal thoughts. Students
who reported being bullied at school and online were even more likely to
report not just suicidal thoughts, but also attempts. Those who were bullied
or cyberbullied in a way that affected them at school were also at a higher
risk for suicidal thoughts and attempts. We discuss how school commu-
nities can provide substantive instructional and emotional support to all
teens, particularly with the increased prominence of these issues over the
last decade.
ARTICLE HISTORY
Received 13 October 2017
Accepted 14 May 2018
KEYWORDS
Suicide; suicidal ideation;
bullying; cyberbullying;
adolescence
According to the Centers for Disease Control and Prevention (CDC; 2015), suicide was the
second leading cause of death in the United States among 10- to 17-year-olds in 2015. What is
more concerning is that from 2000 through 2015, there was a marked rise (21%) of the age-
adjusted suicide rate (2015) of this same groupingofadolescents.Thesefiguresunderscorethe
significance of suicide as a top public health concern and call for a redoubling of our efforts to
understand why it occursas well as what schools, families, and communities can do to
prevent it.
Apart from these facts, numerous high-profile tragedies over the last 15 years have ostensibly
linked experience with school bullying and/or cyberbullying to teen suicideeven though the
weight of research has not identified a direct, causal link (Hinduja & Patchin, 2010,2015). At the
same time, there has been an increase in the exploration of this link by researchers who seek to
determine how and why peer victimization can be a persistent risk factor for youth suicidal
ideation, attempts, and completions (Bauman, Toomey, & Walker, 2013; Hinduja & Patchin,
2010; Kim & Leventhal, 2008;Klomek,Sourander,&Gould,2010;LeBlanc,2012;VanGeel,
Vedder, & Tanilon, 2014).
In the current study, we analyze recent data from a national sample of middle and high
schoolers in the United States to measure the association between school bullying, cyberbully-
ing, and suicidal thoughts and attempts. We move beyond previous inquiries into these
relationships by then focusing specifically on the school bullying and cyberbullying incidents
thatrespondentsdeemedtobeofaseriousnature,or that significantly impacted their ability to
learn at school. Implications stemming from the findings are discussed in conclusion with a
CONTACT Sameer Hinduja hinduja@fau.edu School of Criminology and Criminal Justice, Florida Atlantic University,
Jupiter, FL, USA
© 2018 Taylor & Francis Group, LLC
JOURNAL OF SCHOOL VIOLENCE
https://doi.org/10.1080/15388220.2018.1492417
focus on mitigating the impact of school bullying and cyberbullyingasapossiblewayto
prevent teen suicide.
Nature and extent of school bullying, cyberbullying, and youth suicide
Due to its presence at the forefront of scholarly research agendas in disciplines that work with
adolescents, the CDC recently convened a number of experts to develop the following uniform
definition of bullying: any unwanted aggressive behavior(s) by another youth or group of youths
who are not siblings or current dating partners that involves an observed or perceived power
imbalance and is repeated multiple times or is highly likely to be repeated(Gladden, Vivolo-
Kantor, Hamburger, & Lumpkin, 2014, p. 7). This largely mirrors definitions historically posited by
other researchers (Espelage & Swearer, 2003; Manning, Heron, & Marshal, 1978; Nansel et al., 2001;
Olweus, 1995). What is more, these definitions have informed conceptualizations of cyberbullying
(arguably a subset of the general term bullying), which has been defined as willful and repeated
harm inflicted through the use of computers, cell phones, and other electronic devices(Hinduja &
Patchin, 2015, p. 11). Essentially, cyberbullying is bullying perpetrated online or otherwise carried
out using technology.
According to the 2015 Youth Risk Behavior Surveillance System data (the most recent year
available), slightly more than one fifth (20.2%) of students in Grades 912 reported that they were
bullied at school, while 15.5% were bullied online during the previous year (Kann, 2016). Similarly,
the National Crime Victimization Surveys School Crime Supplement report that 20.8% of students
had been bullied at school (also in 2015), and 11.5% of those said it happened online or by text
(National Center for Education Statistics, 2016). Often, targets have no escape from mistreatment as
studies have indicated an overlap where those who are bullied at school are also bullied online
(Erdur-Baker, 2010; Juvonen & Gross, 2008; Raskauskas & Stoltz, 2007; Wang, Iannotti, & Nansel,
2009), and that in some of those cases, it is the very same aggressor who seeks to inflict harm
(Ybarra, Diener-West, & Leaf, 2007). What is more, a compounding effect of victimization may
result, as youth targets experience multiple forms of bullying (physical, relational, verbal, and cyber)
at or around the same time (e.g., in one recent study, 50.3% of those who had been bullied reported
experiencing all four forms in the past month; Waasdorp & Bradshaw, 2015).
With regard to demographics, research generally shows that boys are more heavily involved in
school bullying (as a victim and offender), while girls are just as likely if not more likely to be
involved in online bullying (Hinduja & Patchin, 2015). Findings do vary, though, depending on how
school bullying and cyberbullying are defined and measuredwith girls often partaking in more
indirect and relational forms of aggression while boys are more likely to physically bully their peers
(Archer, 2004; Carbone-Lopez, Esbensen, & Brick, 2010; Li, 2006). Finally, studies that have
examined school bullying and cyberbullying by race have been largely inconclusive (Peskin,
Tortolero, & Markham, 2006; Wang et al., 2009). Students from all racial backgrounds experience
and participate in bullying, with no clear group consistently shown to be significantly more involved
than the others.
In terms of consequences, research has regularly found that experience with both school bullying
and cyberbullying contribute to a host of maladaptive emotional, psychological, behavioral, and even
physical problems. These include, but are not limited to: anger, self-pity, depression, anxiety, eating
disorders, and chronic illness (Bauman et al., 2013; Cowie & Berdondini, 2002; Gámez-Guadix,
Orue, Smith, & Calvete, 2013; Klomek, Marracco, Kleinman, Schonfeld, & Gould, 2007; Kowalski &
Limber, 2013;Natvig, Albrektsen, & Quarnstrom, 2001; Patchin & Hinduja, 2010,2012; Seals &
Young, 2003; Takizawa, Maughan, & Arseneault, 2014). Minor and moderate forms of school
misbehaviors and violence have also been associated with cyberbullying in recent years (Ericson,
2001; Hay & Meldrum, 2010; Hinduja & Patchin, 2007; Nixon, 2014).
Suicide among school-aged youth is also an issue of great concern. The aforementioned Youth
Risk Behavior Surveillance System sheds light on the proportion of U.S. high school students who
2S. HINDUJA AND J. W. PATCHIN
report suicidal ideation and attempts. In 2015, 17.7% seriously considered attempting suicide, 14.6%
made a plan, 8.6% attempted suicide, and 2.8% attempted suicide in a way that had to be treated by a
medical professional during the 12 months before the survey (Kann, 2016). For these attempts, girls
were involved more than boysconsonant with findings in other research (Lewinsohn, Rohde,
Seeley, & Baldwin, 2001). With respect to race and ethnicity, research has found that White students
are more likely than African-American and Hispanic students to attempt suicide, although the rate
among African-American adolescents has significantly grown since the turn of the century (Mueller,
James, Abrutyn, & Levin, 2015).
Bullying and suicidal ideation
Many studies have been conducted over the last two decades to measure the relationship between
face-to-face bullying and suicidal ideation (see e.g., Kaltiala-Heino, Rimpelä, Marttunen, Rimpelä, &
Rantanen, 1999; Kim, Koh, & Leventhal, 2005; Klomek et al., 2007; Mills, Guerin, Lynch, Daly, &
Fitzpatrick, 2004; Roland, 2002), and statistically significant associations have been found in ele-
mentary (van der Wal, De Wit, & Hirasing, 2003), middle (Seals & Young, 2003), and high school
(Klomek et al., 2007). A recent meta-analysis involving 34 studies and 66 independent effect sizes,
found that peer victimization was significantly related to suicidal ideation (OR = 2.23; 95% CI [2.10
2.37]), while an examination of nine studies and 13 independent effect sizes showed that peer
victimization was significantly related to suicide attempts (OR = 2.55; 95% CI [1.95, 3.34]) among
adolescents (Van Geel et al., 2014).
The body of research exploring the relationship between cyberbullying and suicide has continued
to grow in recent years (Bauman, 2014). Hinduja and Patchin (2010) surveyed approximately 2,000
middle-school youth and found that school bullying victims were 1.7 times more likely and offenders
were 2.1 times more likely to have attempted suicide than those not involved in bullying. Similarly,
cyberbullying victims were 1.9 times more likely and offenders were 1.5 times more likely to have
attempted suicide than those not involved in cyberbullying (Hinduja & Patchin, 2010). Finally,
cyberbullying victimization was more strongly related to suicidal thoughts and behaviors than school
bullying victimization (Hinduja & Patchin, 2010).
These findings have been duplicated in more recent work (Hay & Meldrum, 2010; Van Geel et al.,
2014) and in general, cyberbullying victimization tends to be a consistent covariate of suicidal
ideation (Bauman, 2014; Jasso Medrano, Lopez Rosales, & Gámez-Guadix, 2017), although possibly
mediated by depressive symptomatology (Bauman et al., 2013). Indeed, the weight of empirical
evidence consistently points out that students who are involved in bullying offending and victimiza-
tion (Kindrick, Castro, & Messias, 2013; Messias, Kindrick, & Castro, 2014; Mills et al., 2004;
Sampasa-Kanyinga, Roumeliotis, & Xu, 2014; van der Wal et al., 2003) and/or cyberbullying
offending and victimization (Hay & Meldrum, 2010; Schneider, ODonnell, Stueve, & Coulter,
2012; Van Geel et al., 2014) have an increased likelihood of suicidal thoughts, attempts, and
completed suicides.
The present work further examines the nature of the connection between suicide and bullying
(face-to-face and cyber) among a youthful population. It is clear that not all who experience bullying
consider suicide; however, those who are bullied appear to be at a higher risk. The present work
explores the self-reported seriousness and impact of the bullying victimization as a way to distin-
guish among bullying incidents. It is hypothesized that students who report that their experience
with school bullying or cyberbullying was relatively serious (based on their own subjective assess-
ment), or that the school bullying or cyberbullying significantly affected them at school, will be more
likely to report suicidal ideation and attempts.
JOURNALOFSCHOOLVIOLENCE 3
Participants and method
Data for the current study came from a survey administered to a nationally representative sample of
English-speaking 12- to 17-year-old middle and high school students residing in the United States
(Mage = 14.5). A survey was distributed via e-mail between August and October of 2016 that
examined perceptions of, and experiences with, school bullying, cyberbullying, and related teen
behaviors, and took 23 minutes on average to complete. Nested age, sex, and region quotas were
used to ensure a diverse sample of respondents that was representative of students across the nation.
Parental consent and child assent was obtained for all participants, leading to a final response rate of
15%. Admittedly, this is lower than other methods of data collection and not ideal (Baruch &
Holtom, 2008; Kaplowitz, Hadlock, & Levine, 2004), and should be kept in mind when interpreting
the results (Fricker & Schonlau, 2002; Manfreda et al., 2008). However, as Cook, Heath, and
Thompson (2000, p. 821) persuasively argued, response representativeness is more important
than response rate in survey research(see also Johnson & Wislar, 2012). And our final sample of
2,670 was evenly divided by sex (49.9% female, 49.6% male) and comparable to the population of
middle and high school students in the U.S. (Office of Adolescent Health, 2016) by race (66% of the
sample is White/Caucasian, 12% is Black/African American, 11.9% is Hispanic/Latin American, and
10% were another race).
Measures
Suicidal ideation and suicide attempt
Two dependent variables were utilized in this study. The first, suicidal ideation, included four items
adapted from the American School Health Association (1989) National Adolescent Student Health
Survey. They included: In the past year, have you (a) felt so sad or hopeless almost every day for two
weeks or more in a row that you stopped doing some usual activities; (b) seriously thought about
attempting suicide; (c) made a specific plan about how you would attempt suicide; and (d) seriously
attempted suicide. Respondents indicated either yesor noto each of these questions, and so our
resultant summary scale ranges from 04(M= 0.26; SD = 0.72) with higher values representing
more suicidal thoughts (Cronbachsα= .73). We also used factor analysis (PCR) to establish
construct validity and found that all items loaded on a single factor (loadings ranged from .634 to
.872; eigenvalue = 2.60). To account for a negatively skewed distribution, responses were ultimately
dichotomized where respondents who scored 0 on the summary scale were coded 0 and those who
scored 14 were coded 1. In addition to suicidal ideation, we also wanted to focus on the subset of
students who have attempted suicide. Suicide attempt is a single-item indicator where students who
said they had actually attempted suicide in the previous year were coded 1 while those who did not
were coded 0.
Bullying victimization
The current analysis utilized two measures of bullying: one for school bullying and another for
cyberbullying. School bullying represents the respondents experience in the previous 30 days as a
victim of 10 different forms of school bullying. As noted in Table 1, the measure included a
variety of behaviors representing relatively minor and common forms of bullying (I was called
mean names) to more serious and less common forms (I was threatened with a weapon). The
response set for these questions was never, once, a few times,andmany times.Assuch,our10-
item summary scale ranges from 0 to 30 (M= 4.93; SD = 6.42) with higher values representing
more experience as a victim of bullying at school (Cronbachsα= .91). Factor analysis results
indicated that all items loaded on a single factor (loadings ranged from .734 to .806;
eigenvalue = 6.00).
Cyberbullying represents the respondents experience in the previous 30 days as a victim of eleven
different forms of cyberbullying. As noted in Table 1, this measure also included a variety of
4S. HINDUJA AND J. W. PATCHIN
behaviors (Someone posted mean or hurtful comments about me online;Someone threatened to
hurt me while online.). The response set for these questions was also never, once, a few times, and
many times. As such, our 11-item summary scale ranges from 0 to 33 (M= 2.70; SD = 5.98) with
higher values representing more experience as a victim of cyberbullying (Cronbachsα= .95). Factor
analysis results indicated that all items loaded on one factor (loadings ranged from .751 to .875;
eigenvalue = 7.83).
Finally, to explore the importance of the magnitude (or relative seriousness) of the bullying
experience, we included four single-item indicators (two each for school bullying and cyberbullying)
that assess the respondents view of how serious the bullying incident was. We first asked students
who reported that they had been bullied (at school or online) to rate on a scale of 0 to 10 their overall
experience with school bullying and cyberbullying during the last 30 days, with 0 meaning they were
not bothered at all and 10 meaning they were really hurt and bothered (school bullying M= 3.76;
school bullying SD = 3.14; cyberbullying M= 4.64; cyberbullying SD = 3.31). Each measure was
dichotomized where those who rated their experiences as a 5 or lower were coded 0 while those who
rated their experiences as a 6 or higher were coded 1. Next, we asked respondents whether they had
been bullied or cyberbullied in a way that really affected their ability to learn and feel safe at
school.Students who responded that they had were coded 1 and those who had not were coded 0.
In addition to these primary variables of interest, we also included age, sex, and race in all models
to control for any effect these demographic features may have on suicidal ideation or attempts. Age
Table 1. Descriptive statistics: Experience with bullying and suicide (N= 2,670).
Variable MSDRange % Cronbachsα
School bullying victimization 6.60 6.93 030 .906
I was called mean names, was made fun of, or teased in a hurtful way 50.9
Other students left me out of things on purpose, excluding me from their group of
friends, or completely ignored me
46.9
Other students told lies or spread false rumors about me and tried to make others
dislike me
43.3
I was bullied at school 38.6
I was bullied with mean names, comments, or gestures with a sexual meaning 30.1
I was threatened or forced to do things I didnt want to do 22.6
I was bullied with mean names or comments about my race or color 21.4
I was hit, kicked, pushed, shoved around, or locked indoors 20.5
I had money or other things taken away from me or damaged 19.2
I was threatened with a weapon such as a knife or gun while at school 8.3
I was bullied in a way that really affected my ability to learn and feel safe at school 40.5
On a scale of 010, bullied at school 6 or higher 24.5
Cyberbullying victimization 2.27 5.26 033 .945
Someone posted mean or hurtful comments about me online. 22.1
Someone spread rumors about me online, through text messages, or emails. 19.6
I was cyberbullied 16.5
Someone posted mean names, comments, or gestures about me with a sexual
meaning.
12.3
Someone threatened to hurt me while online. 11.7
Someone threatened to hurt me through a cell phone text message. 11.5
Someone posted a mean or hurtful picture online of me. 10.7
Someone pretended to be me online and acted in a way that was mean or hurtful
to me.
9.9
Someone posted mean names or comments online about my race or color. 9.7
Someone posted a mean or hurtful video online of me. 6.9
Someone created a mean or hurtful web page about me. 6.7
I was cyberbullied in a way that really affected my ability to learn and feel safe at
school
15.7
On a scale of 010, cyberbullied 6 or higher 20.7
Suicide
Suicidal ideation 0.26 0.72 04 0.730
Students who experienced suicidal ideation 16.1
Suicide attempts 2.1
JOURNALOFSCHOOLVIOLENCE 5
was a continuous variable ranging from 1217 (M = 14.4; SD = 1.66); Sex was dichotomized into
male respondents and female respondents (1 = male, 0 = female), while Race was dichotomized into
White and non-White (1 = White; 0 = African American, Asian, Hispanic, or another race). The
sample is evenly distributed when it comes to gender (49.6% were male) but less so when it comes to
race (68% were White).
Analysis
Statistical analyses were conducted using SPSS (version 20.0). Descriptive statistics were initially
computed to obtain baseline data on suicidal ideation and attempts, as well as with bullying and
cyberbullying experiences among the sample (see Table 1). Next, a series of logistic regression
models were computed to assess the effect of bullying and cyberbullying on suicidal ideation and
attempts. We first examined the relationship between bullying and suicide by focusing on subgroups
of targets who experienced (a) only school bullying, (b) only cyberbullying, and (c) both forms of
bullying. We computed models for these three indicators for suicidal ideation (Table 2, Models 13)
and suicide attempt (Table 3, Models 46). Then, we estimated odds ratios for the relationship
Table 2. Logistic regression analysis: The effect of bullying and cyberbullying victimization on suicidal ideation (N= 2,670).
Model 1 Model 2 Model 3
Variable b (SE) Exp(B) (95% CI) b (SE) Exp(B) (95% CI) b (SE) Exp(B) (95% CI)
Constant 3.14
(0.50)
0.04*** 2.98
(0.49)
0.05*** 3.58
(0.52)
0.03***
Male 0.04 (0.10) 1.04 [0.85, 1.27] 0.04 (0.10) 1.04 [0.86,
1.27]
0.04 (0.11) 1.04 [0.85, 1.28]
White 0.09 (0.12) 1.09 [0.86, 1.37] 0.11 (0.12) 1.12 [0.89,
1.41]
0.04 (0.12) 1.04 [0.82, 1.32]
Age 0.09 (0.03) 1.10** [1.03,
1.17]
0.08 (0.03) 1.09* [1.02,
1.16]
0.11 (0.03) 1.11** [1.04,
1.19]
School bullying (victimization only) 0.49 (0.14) 1.63*** [1.25,
2.12]
Cyberbullying (victimization only) 0.47 (0.21) 1.59* [1.06,
2.40]
Both school bullying and
cyberbullying
1.69 (0.13) 5.41*** [4.20,
6.98]
Nagelkerke R
2
0.013 0.008 0.108
*p< .05; **p< .01; ***p< .001 (two-tailed).
Table 3. Logistic regression analysis: The effect of bullying and cyberbullying victimization on suicide attempts (N= 2,670).
Model 4 Model 5 Model 6
Variable b (SE) Exp(B) (95% CI) b (SE) Exp(B) (95% CI) b (SE) Exp(B) (95% CI)
Constant 6.88
(1.31)
0.00*** 6.98
(1.31)
0.00*** 8.29
(1.37)
0.00***
Male 0.20 (0.25) 1.22 [0.75,
1.97]
0.20 (0.25) 1.22 [0.75,
1.97]
0.21 (0.26) 1.24 [0.75, 2.05]
White 0.77 (0.35) 2.16* [1.07,
4.31]
0.76 (0.35) 2.13* [1.07,
4.26]
0.63 (0.36) 1.87 [0.93, 3.79]
Age 0.16 (0.09) 1.18 [0.99,
1.39]
0.17 (0.09) 1.18* [1.00,
1.40]
0.21 (0.09) 1.23* [1.04, 1.46]
School bullying (victimization
only)
0.27
(0.41)
0.76 [0.34,
1.71]
Cyberbullying (victimization only) 0.23 (0.60) 1.02 [0.32,
3.33]
Both school bullying and
cyberbullying
2.44 (0.29) 11.42*** [6.49,
20.09]
Nagelkerke R
2
0.022 0.021 0.165
*p< .05; **p< .01; ***p< .001 (two-tailed).
6S. HINDUJA AND J. W. PATCHIN
between serious school bullying and cyberbullying (Table 4) among a subsample of only those
respondents who had been bullied or cyberbullied (while controlling for age, sex, and race).
Results
Across our sample, 16.1% of respondents experienced suicidal ideation (16.7% of females; 15.3% of
males) while 2.1% reported they had attempted suicide (2.2% of females; 2.0% of males). Even
though females have a markedly higher incidence rate of suicidal ideation than males during
adolescence (Lewinsohn et al., 2001), major gender disparities were not found in the current
study. With regard to school bullying, prevalence rates for individual behaviors ranged from 8.3%
to 50.9%. The most frequently cited form of school bullying was: I was called mean names, was
made fun of, or teased in a hurtful way.In terms of cyberbullying, prevalence rates for individual
behaviors ranged from 6.7% to 22.1% with the most commonly reported form being: Someone
posted mean or hurtful comments about me online.It is worth noting that the mean for the
summary scores for both school bullying (6.60) and cyberbullying (2.27) are on the lower end of
their range, indicating relatively infrequent experiences with bullying overall among this population.
Recall that the primary purpose of the current study was to establish if experience with school
bullying and cyberbullying was correlated with suicidal ideation and attempts. Before presenting
those results, it is necessary to account for the effect of age, race, and gender on suicidal ideation and
attempts. As noted in Tables 2 and 3, older students were generally more likely to report suicidal
ideation and to have attempted suicide, while White students were more likely to have attempted
suicide in two out of the six models (Table 3, Models 4 and 5).
Table 2 presents results of the logistic regression analysis examining the relationship between school
bullying and cyberbullying on suicidal ideation. Students who experienced only school bullying and
only cyberbullying were significantly more likely to report suicidal ideation (OR = 1.63 and 1.59,
respectively). Students who experienced both forms of bullying, however, were more than 5 times as
likely to report suicidal ideation compared to those who had not been bullied or cyberbullied (OR =
5.41). The explained variance of the model as a whole also demonstrates the disproportionate impact
of experiencing bullying in multiple environments. Only about 1% of the variation in suicidal ideation
can be explained by experience with school bullying or cyberbullying alone, but experiencing both
forms of bullying accounted for over 10% of the variation in suicidal ideation. Comparable results were
also identified when examining the relationship between experience with bullying and suicide attempts
(Table 3). Those who experienced only school bullying or only cyberbullying were at no greater risk for
attempted suicide, while those who experienced both forms of bullying were more than 11 times as
likely to attempt suicide compared to those who had not been bullied (OR = 11.42).
Finally, Table 4 presents the impact of serious bullying on suicidal thoughts and attempts among
subsamples of only those who had been bullied at school or online. As expected, even among those
who had been bullied, the more serious incidents all had a significant and positive association with
suicidal ideation and suicide attempts. Specifically, respondents who ranked their experience with
Table 4. Logistic regression analysis: The effect of serious bullying and cyberbullying victimization on suicide.
Suicidal ideation Suicide attempt
Variable OR 95% CI OR 95% CI
Among those bullied
a
Bullying affected me at school 3.38*** [2.26, 5.07] 10.88*** [1.42, 83.63]
Bullying score of 6 or higher on seriousness scale (010) 3.31*** [2.61, 4.21] 4.21*** [2.37, 7.47]
Among those cyberbullied
b
Cyberbullying affected me at school 3.21*** [2.38, 4.34] 7.17*** [3.30, 15.62]
Cyberbullying score of 6 or higher on seriousness scale (010) 3.07*** [2.29, 4.10] 2.25** [1.24, 4.08]
Note. Odds ratios adjusted for age, sex, and race.
a
n= 1,786.
b
n= 943.
**p< .01; ***p< .001 (two-tailed).
JOURNALOFSCHOOLVIOLENCE 7
school bullying or cyberbullying as 6 or higher on a scale that ranged from 0 to 10, or indicated that
the experience seriously affected them at school, were more than three times as likely to report
suicidal ideation compared to those who had relatively less serious experiences with school bullying
and cyberbullying. Odds ratios were even higher in three out of four of the models examining the
effect of serious school bullying and cyberbullying on attempted suicide. In all cases, though,
students who reported that their experience with school bullying or cyberbullying affected them at
school were at the highest risk for suicidal ideation and attempted suicide.
Discussion
The current work explored the nature of the association between experience with school bullying
and cyberbullying, and suicidal ideation and attempts. In line with findings from previous studies
(Bauman, 2014; Hinduja & Patchin, 2010; Van Geel et al., 2014), middle and high school students
who experienced either school-based or online bullying were significantly more likely to report
suicidal ideation. Contrary to the relatively consistent finding in the limited research base that
cyberbullying victimization is more strongly tied to suicidal ideation and attempts than school
bullying (Hay & Meldrum, 2010; Hinduja & Patchin, 2010; Van Geel et al., 2014), we found a
stronger relationship with the latter. That said, experiencing both forms of bullying compounds the
negative effects and greatly increases the likelihood of suicidal ideation among adolescents.
When it comes to suicidal attempts, the present research did not find a significant association
with school-based or online bullying by themselvescontrary to findings from previous studies (see
e.g., Van Geel et al., 2014). However, experiencing both together was linked to an exponentially
higher likelihood of trying to take ones own life. Perhaps some students can manage the emotional
and psychological harm associated with a limited amount of victimization in one environment or the
other, but are seemingly much less so able when the impact is amplified through its occurrence and
persistence both at school and online.
This point is supported by the relationship between the severity of incidents and suicidal ideation
and attempts. Those adolescents who rated their victimization as more severe (in terms of a general
evaluation of how much they were hurt and bothered, as well as its specific impact on their feelings
of safety at school and their ability to learn) were much more likely to report suicidal thoughts (more
than three times as likely) and attempts (from twice as likely for serious cyberbullying to more than
ten times as likely for school-based bullying), compared to those who experienced milder forms of
bullying. Collectively, these findings bear out the very tangible impact that bullying can have on the
mental health of youth today, especially if multiple forms combine and are magnified to plague a
student in pointedly negative ways.
As mentioned earlier, no research has shown a direct link between experience with school
bullying or cyberbullying and suicide (Hinduja & Patchin, 2010,2015). That remains true when
considering the findings at hand. While there have been several tragic examples where teens have
taken their lives after being bullied, most youth who are bullied do not. To be sure, the factors that
lead to suicide are varied and complex, and at the mercy of many situational and contextual factors
(see Rodway et al., 2016 for a review of these across 145 studied suicides). The point is that there
exists a number of critical elements that can increase ones suicide risk, particularly when they co-
occur with peer-based victimization. As such, an amalgamation of various painful internal and
external experienceswhich may also consist of harm from school bullying or cyberbullyingseems
to most commonly lead to the ultimate tragic decision to end ones life.
Limitations
As with any social science study, the current analysis suffers from methodological limitations that
merit acknowledgement. The primary shortcoming stems from the cross-sectional nature of the data.
Since the data were collected at one point in time, it is impossible to conclude that experience with
8S. HINDUJA AND J. W. PATCHIN
school bullying or cyberbullying caused one to have suicidal thoughts or to attempt suicide (Bauman,
2014). The common concerns associated with asking students to self-report deviant behaviors also
need to be kept in mind when evaluating the current work. Even though the survey was conducted
online and respondents were reassured that their results would remain confidential to the maximum
extent allowable by law, experience with bullying or cyberbullying, along with suicidal thoughts and
attempts, may have been underreported or overreported for a variety of reasons. Relatedly, recall bias
may also have occurred. Some have argued that data which stem from individualsrecollection about
the past is inherently unreliable because of the tendency for individuals to misrepresent, distort, or
forget facts from a previous time period (Himmelweit, Biberian, & Stockdale, 1978; Horvath, 1982;
Morgenstern & Barrett, 1974). However, we sought to minimize the influence of these concerns
through careful wording and revision of survey items, and feel reasonably confident that they do not
compromise the intentions and implications of the research.
Additionally, though we sought to obtain a nationally representative sample of middle and high
school students across the United States, we can never be certain of the generalizability of the sample
of youth who ultimately completed the surveys. Even though the demographic characteristics of the
sample are relatively consistent with those of U.S. youth as a whole, there could be uncontrolled for
differences between those who ultimately agreed to complete our survey and those who did not. This
is of particular concern given the relatively low response rate.
Prevention and future considerations
Even though most bullied youth do not commit suicide, the grave possibility that a small number
will necessitates that more be done at school and in the community to safeguard vulnerable youth
(Messias et al., 2014). The breadth and depth of bullying prevention programming is many times still
left to the discretion of individual schools, who are at the mercy of time, personnel, and resource
constraints (Ttofi & Farrington, 2011). These findings should motivate them to redouble their efforts
and make sure they are intentional about addressing peer harassment in order to forestall any serious
consequences. The blurring of boundaries and distinctions between online and offline interactions
among kids accentuates a deep need to pay attention to bullying wherever it is occurring, and best
practices are evolving to guide administrators in the proper direction (Bauman, 2011; Davis &
Nixon, 2012; Hinduja & Patchin, 2012; Kärnä et al., 2011; Patchin & Hinduja, 2016; Pearce, Cross,
Monks, Waters, & Falconer, 2011; Ttofi & Farrington, 2011).
A few research-based suicide prevention initiatives have also demonstrated success at preventing
bullying, including: Sources of Strength (Katz et al., 2013; Wyman et al., 2010), Signs of Suicide
(SOS; Aseltine Jr & DeMartino, 2004; Aseltine, James, Schilling, & Glanovsky, 2007), and the Good
Behavior Game (Greenberg, Domitrovich, & Bumbarger, 1999; Katz et al., 2013; Wilcox et al., 2008).
Generally speaking, these programs seek to accomplish a variety of risk-reduction goals such as:
increasing positive ties to adults and the school in general; teaching positive coping techniques;
imparting life skills; shaping attitudes and perspectives about bullying, suicide, and other behaviors;
promoting the acceptability of seeking help; encouraging stepping up on behalf of others; and
developing connectedness and belongingness. While these programs do not vary their content (or
their delivery method) based on each students individual background and learning style, they cover
a spectrum of possible antecedents that include personal, social, and familial issues. If a schools goal
is to prevent suicidal ideation resulting from bullying, it may be beneficial to intentionally combine
specifically applicable portions from these evidence-based programs after carefully considering and
evaluating the needs of their student population (Katz et al., 2013).
Furthermore, it is critical that every schoolat all levelshave formal suicide prevention pro-
grams in place (Kalafat, 2003), as health care providers often fail to screen for suicidal ideation
markers in adolescents and thereby miss an opportunity to meaningfully assist (Borowsky,
Taliaferro, & McMorris, 2013). School programming should provide life skills training, health and
wellness content, positive coping mechanisms, tie-ins to mental health services and helplines, and
JOURNALOFSCHOOLVIOLENCE 9
provide some sort of screening functionality to identify those students most at-risk (Haas et al., 2010;
Joshi, Hartley, Kessler, & Barstead, 2015; Zenere & Lazarus, 2009). Indeed, a whole school approach
that views bullying as systemic and involves all stakeholders can successfully reduce bullying, which
canperhapsprevent suicidal attitudes and actions (Borowsky et al., 2013).
Results from the present research clarified that students who experienced particularly serious
forms of school bullying and cyberbullying were most at risk for suicidal thoughts and attempts.
School professionals must earnestly and consistently convey that they are available to assist targeted
students, and will do so in a mutually-agreeable manner since many teens are hesitant to report for
fear of retaliation, overreaction, or ineffectiveness (Eliot, Cornell, Gregory, & Fan, 2010; Hinduja &
Patchin, 2012; Mishna & Alaggia, 2005). Also, the provision of mechanisms to report bullying
privately and even anonymously are useful through a drop box on campus, a form on the schools
webpage, or a phone or text line they can use (Patchin & Hinduja, 2016; Whitted & Dupper, 2005).
All reportsregardless of perceived severityshould then be properly investigated by an adminis-
trator to make sure bullying is addressed or prevented, and that all students feel safe. Perhaps
supporting a child through a mild or minor victimization incident may keep certain ill effects of
bullying from iteratively building upon themselves and causing significant harm that largely was
avoidable (Hinduja & Patchin, 2015; Rigby, 2007).
As a final point, suicide prevention programming is incomplete if only championed and led by
school personnel. While it is not known (or easily measurable) how many bystanders are present in
cyberbullying incidents, research has found that bystanders are present in most bullying incidents
(Holfeld, 2014; Lynn Hawkins, Pepler, & Craig, 2001; Salmivalli, 2014). Youth observe and assess
how others are treated as they witness various forms of bullying taking place, and based on their own
experiences or reference points likely have an accurate idea of what might be classified as mild or
severe mistreatment. Even if they do not intervene, what they witness does typically prompt an
emotional and even physiological response and bothers them on some level (Barhight, Hubbard, &
Hyde, 2013).
Students must realize that their individual and collective voice is powerful, and that they should
press past their hesitations and fears and use it to: raise awareness; set (or reset) appropriate social
norms and considerations around bullying and suicide; promote vulnerability, acceptance, tolerance,
and kindness; and collectively stand against hate and harassment of all forms (Mitra, 2008; Patchin &
Hinduja, 2014; Smith et al., 2011). Toward this end, educators would do well to supplement their
formal schoolwide programming by repeatedly reminding the student body that they need to come
through for their classmates with intentionality by encouraging, defending, supporting, and rallying
to their aid as necessary (Davis & Nixon, 2012,2014; DeSmet et al., 2012). If this messaging is part of
the culture on campus, targeted youth may more readily seek support from their peer group, and
nontargeted youth may look for opportunities to come through for those struggling because doing so
has been institutionalized as normative in that environment (Eliot et al., 2010; Hinduja & Patchin,
2012; Orpinas & Horne, 2009).
Funding
This work was supported by the Digital Trust Foundation [31-3].
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14 S. HINDUJA AND J. W. PATCHIN
... Regarding conflicts in general, studies show that one in four students has witnessed some type of school conflict, be it a simple disruption or more complex problems such as conduct disorders or violence. The latest OCDE report [26] states that 14% of schools have at least one conflict caused by student behaviour per week and 25% of students experience bullying or cyberbullying [27][28][29][30]. The other types of conflict students face are related to indiscipline, demotivation, apathy, failure to adapt to the peer group, lack of emotional Children 2023, 10, 231 3 of 16 control, and impulsivity. ...
... Two thirds of the participating guidance counsellors agree that managing conflicts in their centres is part of their duties as a counsellor and consider that conflicts can be prevented. However, the same percentage indicates that some conflicts are difficult to anticipate and prevent because the variables that cause them do not lie exclusively in the educational centres [25,28,29]. Some authors argue that, even though conflicts have multiple causes, serious forms of conflict have indicators that help to intervene early [25][26][27][28][29][30][31][32]. ...
... However, the same percentage indicates that some conflicts are difficult to anticipate and prevent because the variables that cause them do not lie exclusively in the educational centres [25,28,29]. Some authors argue that, even though conflicts have multiple causes, serious forms of conflict have indicators that help to intervene early [25][26][27][28][29][30][31][32]. On the other hand, almost half of the guidance counsellors say that the conflicts that most worry them are those that concern relations within the centres themselves-with their colleagues and with families-and not so much with students. ...
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This article identifies the socio-emotional competencies of school counsellors working with children and adolescents. The aim is to address problems related to mental health and conflict and to implement training programmes. The study sample was composed of 149 counsellors working in schools. The instruments used were the CCPES-II (questionnaire on teacher competences) and a series of open-ended questions on conflict resolution. A mixed methodology was used, with a concurrent triangulation design with two phases: a quantitative one (QUAN) and a qualitative one (QUAL). Univariate, bivariate, and correlation quantitative analyses were performed. Parametric and non-parametric tests were applied depending on the number of dependent and independent variables. The qualitative analysis was performed with the NVivo 12 computer programme, which determines word frequencies using a classic content analysis. The results confirm the relationship between socio-emotional training and rapid response to school conflict; the generalised view that conflicts are difficult to anticipate and, thus, to prevent; and the demand for specific training in socio-emotional competences, intervention strategies, more specialised school staff, more time for intervention with and support for families, and more socio-professional recognition.
... It has been shown that the population of adolescents with paranoid tendencies positively and significantly predicts the frequency of their cyberbullying perpetration [42]. This may be because paranoid thinking tends to make adolescents behave paranoid [43], thus increasing adolescents' aggressive behavior, which is consistent with previous studies [44]. ...
... When adolescents engage in cyberbullying, individuals may have negative experiences (i.e., adverse effects caused by inconsistent knowledge and actions) within themselves because their moral code is challenged [34]. Additionally, to mitigate this negative experience, individuals trigger their internal moral excuses mechanism, i.e., rationalizing their behavior by blaming their behavior on the bully themselves [44]. This may be because paranoid tendencies and moral disengagement as a mental tendency will directly or indirectly impact externally problematic behavior, and are not as much affected by age [41]. ...
... Finally, let us take the above two points together. We can find that if we intervene in youth cyberbullying from the perspective of moral excuses, we need to start from both cognitive-emotional regulation and behavioral shaping; in terms of cognitive-emotional, both schools and families should correct the wrong beliefs of individuals with high moral excuses, help them establish correct moral value judgment standards and a sense of shame in line with usual social norms, so they do not wantonly justify immoral behaviors [44]. In terms of behavior, both families and schools should adopt a "zero tolerance" attitude towards bullying, help high moral-deferring individuals by encouraging moral behaviors, reducing the frequency of using retaliatory means in conflict situations, and gradually helping them to improve their moral judgment and behavior strategies in ethical conditions. ...
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BACKGROUND: Cyberbullying has become an essential public health psychological issue affecting people’s lives in the online ecology. However, previous studies have rarely examined adolescent paranoia, moral cognition, and cyberbullying in association. Therefore, this study was based on cognitive-behavioral theory to investigate the relationship between child-like paranoid tendencies, cyberbullying, and moral disengagement. METHODS: This study used the Paranoia Scale, Cyberbullying Scale, and Moral Disengagement Scale to conduct an anonymous online survey of 1519 adolescents in China. RESULTS: (1) Paranoid tendencies, moral disengagement, and cyberbullying were all significantly and positively correlated. Boys showed higher rates of moral disengagement, while girls showed higher rates of paranoid tendencies. (2) The direct effect of paranoid tendency on cyberbullying was significant (β = 0.31, p < 0.01). (3) There was a mediating effect of moral disengagement in the influence of paranoid tendencies on cyberbullying, with an effect proportion of 20.5%. CONCLUSION: Adolescent cyberbullying should be regulated at the family and social levels to enhance juvenile mental health issues and help them establish proper moral standards.
... In addition, a common limitation of previous ACEs research has been the narrow definition and outcome measures used to explore adverse experiences. For instance, the initial ACEs study by Felitti et al. [28] explored 10 adverse experiences; five that involved direct harm to the child and five that affected the environment in which they grew up. This limited categorisation fails to account for additional adverse experiences and stressors CYP commonly encounter. ...
... The findings also suggest that a group of CYP in our sample were living in circumstances in which their household or parents may have presented with more than one difficulty at the same time. The clusters identified here are in keeping with the existing ACEs literature, which suggests that ACEs fall into one of two domains: factors that involve direct harm to the child, and factors that affect the environment in which they grow up [28]. However, it should be noted that ACEs in these two domains are often likely to co-occur; indeed, the findings in the present study do not preclude the family situation influencing the home situation, and vice versa, but instead suggest that for CYP presenting in the ED for suicidal crisis, these appear to be two separate sets of associations. ...
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Suicide is a major public health issue and a leading cause of death among children and young people (CYP) worldwide. There is strong evidence linking adverse childhood experiences (ACEs) to an increased risk of suicidal behaviours in adults, but there is limited understanding regarding ACEs and suicidal crises in CYP. This study aims to examine the ACEs associated with CYP presenting at Emergency Departments for suicidal crises, and specifically the factors associated with repeat attendances. This is a case series study of CYP (aged 8–16) experiencing suicidal crisis who presented in a paediatric Emergency Department in England between March 2019 and March 2021 (n = 240). The dataset was subjected to conditional independence graphical analysis. Results revealed a significant association between suicidal crisis and several ACEs. Specifically, evidence of clusters of ACE variables suggests two distinct groups of CYP associated with experiencing a suicidal crisis: those experiencing “household risk” and those experiencing “parental risk”. Female sex, history of self-harm, mental health difficulties, and previous input from mental health services were also associated with repeat hospital attendances. Findings have implications for early identification of and intervention with children who may be at a heightened risk for ACEs and associated suicidal crises.
... Because bullies reveal their identity, they commit their acts of harassment discreetly without realizing the consequences for both their victims and themselves. The study in [16] concluded that cyberbullying victimization tends to be a consistent covariate of suicidal ideation and that students who experience online bullying have an increased likelihood of suicidal thoughts, attempts and completed suicides. ...
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Cyberbullying is a hurtful phenomenon that spreads widely on social networks and negatively affects the lives of individuals. Detecting this phenomenon is of utmost necessity to make the digital environment safer for youth. This study uses a bilingual classification of cyberbullying on Ara-bic and English datasets. A four-module approach is proposed. It consists of preprocessing the textual data, generating sentence embeddings, performing the classification, and evaluating the results of the models. The approach relies on two strategies based on transfer learning of pre-trained NLP models. The first uses PLMs (ELMo, Universal Sentence Encoder, BERT, distilBERT, and RoBERTa) to generate sentence embeddings, while the second adopts a fine-tuning procedure of BERT-based PLMs for cyberbullying classification. Due to the frequent class imbalance problem in the research literature, this study used cost-sensitive learning algorithms trained to maximize the Recall/F1 score. The aim is to search for the best classification model that most accurately separates the cyber-bullying and non-cyberbullying classes. The models achieve 75-84%.
... Their review reveals that after controlling for traditional bullying, cyberbullying is associated with anxiety, depression, suicidal ideation and suicide attempts, psychosomatic complaints, poorer physical health, and post-traumatic stress disorder (PTSD), as well as compromised academic functioning . Other studies and reviews document the association between cyberbullying victimization and risk for anxiety, depression, and suicidal ideation (Fahy et al. 2016;Hasse et al. 2019;Hinduja and Patchin 2019) as well as substance use (see Hasse et al. 2019). According to Hasse and colleagues' review (2019), cyberbullying perpetration is associated with substance use, depression and anxiety, and suicidal ideation. ...
... Moreover, the literature provides evidence that suffering cyberbullying may be related to more severe consequences, such as deliberate self-harm and suicide risk (Heerde and Hemphill, 2019;John et al., 2018). In fact, cybervictimized adolescents show a greater likelihood of suicidal ideation (Baiden and Tadeo, 2020;Hinduja and Patchin, 2019). Specifically, a systematic review reported that these adolescents were 2.15 times more likely to experience suicidal ideation (John et al., 2018). ...
Article
Previous research reports that cybervictims are more likely to experience suicidal ideations. Gratitude and life satisfaction have shown to predict suicide risk, but they have rarely been explored in the cyberbullying context. Hence, this study examined the roles of gratitude and life satisfaction in suicide risk in cyberbullying situations. An initial sample of 858 adolescents participated in a prospective study, completing questionnaires assessing gratitude, life satisfaction, cyberbullying experiences and suicidal ideation. Results showed that low levels of gratitude and life satisfaction influence suicidal ideation in cybervictimized adolescents. Limitations and implications of this study are discussed.
... Bullying done directly is apparent to anybody who witnesses it; however, in an ever-changing world running on technology, bullying is no longer restricted to face-to-face interaction (Hamm et al. 2015). Cyberbullying behaviour (CBB), is described as 'hostile behaviour including the use of information and communication technology (ICT) to harm or distress another person' (Camacho, Hassanein, and Head 2014;Hinduja and Patchin 2019;Ansary 2020). CBB has been a significant concern in recent years. ...
Article
The pandemic compelled more exposure to online media in different forms like online education, interactions, gaming, and collaboration, which aggravated the cyberbullying issue. Cyberbullying can now occur in several different mediums due to the renewed lifestyle challenges spawned by the pandemic. Hence, it is imperative to assess the antecedents of cyberbullying behaviour (CBB). General Strain Theory (GST) is taken as a grounded theory to understand the underlying mechanisms of strain and anger and their impact on deviant outcomes like CBB. The current study adds to the GST literature by investigating the association between stress and anger, leading to cyberbullying behaviour. The study also examines the extent to which parenting factors (monitoring, communication, and trust) moderate adolescents’ involvement in cyberbullying. An online survey was used to collect data from 221 high school Indian students for this purpose. As per the results, there is a direct relationship between strain, anger, and cyberbullying. The study confirms an indirect relationship between strain and cyberbullying through anger. The findings suggest that parental influences are important in moderating the relationship between strain and anger in adolescent cyberbullying behaviour. The study recommends strategies for parents, educators, and healthcare providers when dealing with cyberbullying behaviour.
Article
Child abuse is considered to be an essential factor in the development of aggressive behavior. The intensity of the positive relations between child abuse and aggressive behavior differed considerably among researches despite the fact that abundant studies have observed this relation. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, a three-level meta-analysis was employed to obtain reliable estimates for the sizes of effects and investigate some potential moderators of the relation between child abuse and aggressive behavior. The present study obtained 51 studies (30,566 participants; 680 effect sizes) through performing the detailed literature search. It was found that child abuse was positively associated with aggressive behavior in the current study. In addition, the present meta-analysis observed significant moderating effects for type of child abuse, culture, measurement of child abuse, and publication year in the association between child abuse and aggressive behavior. This study suggests that child abuse is a predictor for the development of aggressive behavior in humans. Moreover, child abuse is an important aspect for consideration in efforts toward strengthening of interventions targeting individuals’ aggressive behavior.
Article
Purpose: Suicide is the second leading cause of death for adolescents in the United States; however, suicide is preventable and a better understanding of circumstances that contribute to death can inform prevention efforts. While the association between adolescent suicide and mental health is well established, multiple circumstances contribute to suicide risk. This study examines characteristics of adolescents who died by suicide and differences in circumstances between those with and without known mental health conditions at the time of death. Methods: Logistic regression models were used to estimate adjusted odds ratios and 95% confidence intervals of circumstances contributing to suicide between decedents with and without known mental health conditions using data from the 2013 to 2018 National Violent Death Reporting System (analyzed in 2021). Results: Decedents with a known mental health condition were 1.2-1.8 times more likely to experience problematic alcohol misuse, substance misuse, family and other nonintimate relationship problems, and school problems; however, there were no significant differences between those with and without a known mental health condition for the preceding circumstances of arguments or conflicts, criminal or legal problems, or any crisis occurring within the two weeks prior to death. Discussion: A comprehensive suicide prevention approach can address not only mental health conditions as a risk factor but also life stressors and other crises experienced among adolescents without known mental health conditions.
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Full download: http://www.tandfonline.com/eprint/IQ9hC766sPiUCKhYKR3C/full The main objective of this study was to analyze the direct and indirect relationships among sexting, cybervictimization, depression, and suicidal ideation. The sample consisted of 303 university students from Mexico (mean age = 19.73, SD = 1.73) who completed a questionnaire about the variables of interest. The relationships among the variables were analyzed using structural equation modeling. The results show that sexting was associated with being the victim of cyberbullying, which, in turn, was related to depressive symptoms. In addition, sexting, cybervictimization, and depressive symptoms were significantly associated with suicidal ideation. These results contribute to a better understanding of the relationship between online risk behaviors, such as sexting, and their possible negative consequences, such as cybervictimization, depression, and suicidal ideation.
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Background: There is concern about the mental health of children and young people and a possible rise in suicidal behaviour in this group. We have done a comprehensive national multi-agency study of suicide in under 20s in England. We aimed to establish how frequently suicide is preceded by child-specific and young person-specific suicide risk factors, as well as all-age factors, and to identify contact with health-care and social-care services and justice agencies. Methods: This study is a descriptive examination of suicide in a national consecutive sample of children and young people younger than 20 years who died by suicide in England between Jan 1, 2014, and April 30, 2015. We obtained general population mortality data from the Office for National Statistics (ONS). We collected information about antecedents considered to be relevant to suicide (eg, abuse, bullying, bereavement, academic pressures, self-harm, and physical health) from a range of investigations and inquiries, including coroner inquest hearings, child death investigations, criminal justice system reports, and the National Health Service, including data on people in contact with mental health services in the 12 months before their death. Findings: 145 suicides in people younger than 20 years were notified to us during the study period, of which we were able to obtain report data about antecedents for 130 (90%). The number of suicides rose sharply during the late teens with 79 deaths by suicide in people aged 18-19 years compared with 66 in people younger than 18 years. 102 (70%) deaths were in males. 92 (63%) deaths were by hanging. Various antecedents were reported among the individuals for whom we had report data, including academic (especially exam) pressures (35 [27%] individuals), bullying (28 [22%]), bereavement (36 [28%]), suicide in family or friends (17 [13%]), physical health conditions (47 [36%]), family problems (44 [34%]), social isolation or withdrawal (33 [25%]), child abuse or neglect (20 [15%]), excessive drinking (34 [26%]), and illicit drug use (38 [29%]). Suicide-related internet use was recorded in 30 (23%) cases. In the week before death 13 (10%) individuals had self-harmed and 35 (27%) had expressed suicidal ideas. 56 (43%) individuals had no known contact with health-care and social-care services or justice agencies. Interpretation: Improved services for self-harm and mental health are crucial to suicide prevention, but the wide range of antecedents emphasises the roles of schools, primary care, social services, and the youth justice system. Funding: The Healthcare Quality Improvement Partnership.
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One question that arises when discussing the usefulness of web-based surveys is whether they gain the same response rates compared to other modes of collecting survey data. A common perception exists that, in general, web survey response rates are considerably lower. However, such unsystematic anecdotal evidence could be misleading and does not provide any useful quantitative estimate. Metaanalytic procedures synthesising controlled experimental mode comparisons could give accurate answers but, to the best of the authors' knowledge, such research syntheses have so far not been conducted. To overcome this gap, the authors have conducted a meta-analysis of 45 published and unpublished experimental comparisons between web and other survey modes. On average, web surveys yield an 11% lower response rate compared to other modes (the 95% confidence interval is confined by 15% and 6% to the disadvantage of the web mode). This response rate difference to the disadvantage of the web mode is systematically influenced by the sample recruitment base (a smaller difference for panel members as compared to one-time respondents), the solicitation mode chosen for web surveys (a greater difference for postal mail solicitation compared to email) and the number of contacts (the more contacts, the larger the difference in response rates between modes). No significant influence on response rate differences can be revealed for the type of mode web surveys are compared to, the type of target population, the type of sponsorship, whether or not incentives were offered, and the year the studies were conducted. Practical implications are discussed.
Article
This study investigated the prevalence of bullying and victimization among students in grades 7 and 8. It also explored the relationship of bullying and victimization to gender, grade level, ethnicity, self-esteem, and depression. Three survey instruments were used to obtain data from a convenience sample of 454 public school students. Twenty-four percent reported bullying involvement. Chi-square tests indicated significantly more male than female bullying involvement, seventh graders reported more involvement than did eighth graders, and there were no statistically significant differences in involvement based on ethnicity. Both bullies and victims manifested higher levels of depression than did students who were neither bullies nor victims. There were no significant differences between groups in terms of self-esteem.
Article
Problem: Priority health-risk behaviors contribute to the leading causes of morbidity and mortality among youth and adults. Population-based data on these behaviors at the national, state, and local levels can help monitor the effectiveness of public health interventions designed to protect and promote the health of youth nationwide. Reporting period covered: September 2014-December 2015. Description of the system: The Youth Risk Behavior Surveillance System (YRBSS) monitors six categories of priority health behaviors among youth and young adults: 1) behaviors that contribute to unintentional injuries and violence; 2) tobacco use; 3) alcohol and other drug use; 4) sexual behaviors related to unintended pregnancy and sexually transmitted infections (STIs), including human immunodeficiency virus (HIV) infection; 5) unhealthy dietary behaviors; and 6) physical inactivity. In addition, YRBSS monitors the prevalence of obesity and asthma and other priority health behaviors. YRBSS includes a national school-based Youth Risk Behavior Survey (YRBS) conducted by CDC and state and large urban school district school-based YRBSs conducted by state and local education and health agencies. This report summarizes results for 118 health behaviors plus obesity, overweight, and asthma from the 2015 national survey, 37 state surveys, and 19 large urban school district surveys conducted among students in grades 9-12. Results: Results from the 2015 national YRBS indicated that many high school students are engaged in priority health-risk behaviors associated with the leading causes of death among persons aged 10-24 years in the United States. During the 30 days before the survey, 41.5% of high school students nationwide among the 61.3% who drove a car or other vehicle during the 30 days before the survey had texted or e-mailed while driving, 32.8% had drunk alcohol, and 21.7% had used marijuana. During the 12 months before the survey, 15.5% had been electronically bullied, 20.2% had been bullied on school property, and 8.6% had attempted suicide. Many high school students are engaged in sexual risk behaviors that relate to unintended pregnancies and STIs, including HIV infection. Nationwide, 41.2% of students had ever had sexual intercourse, 30.1% had had sexual intercourse during the 3 months before the survey (i.e., currently sexually active), and 11.5% had had sexual intercourse with four or more persons during their life. Among currently sexually active students, 56.9% had used a condom during their last sexual intercourse. Results from the 2015 national YRBS also indicated many high school students are engaged in behaviors associated with chronic diseases, such as cardiovascular disease, cancer, and diabetes. During the 30 days before the survey, 10.8% of high school students had smoked cigarettes and 7.3% had used smokeless tobacco. During the 7 days before the survey, 5.2% of high school students had not eaten fruit or drunk 100% fruit juices and 6.7% had not eaten vegetables. More than one third (41.7%) had played video or computer games or used a computer for something that was not school work for 3 or more hours per day on an average school day and 14.3% had not participated in at least 60 minutes of any kind of physical activity that increased their heart rate and made them breathe hard on at least 1 day during the 7 days before the survey. Further, 13.9% had obesity and 16.0% were overweight. Interpretation: Many high school students engage in behaviors that place them at risk for the leading causes of morbidity and mortality. The prevalence of most health behaviors varies by sex, race/ethnicity, and grade and across states and large urban school districts. Long-term temporal changes also have occurred. Since the earliest year of data collection, the prevalence of most health-risk behaviors has decreased (e.g., riding with a driver who had been drinking alcohol, physical fighting, current cigarette use, current alcohol use, and current sexual activity), but the prevalence of other behaviors and health outcomes has not changed (e.g., suicide attempts treated by a doctor or nurse, smokeless tobacco use, having ever used marijuana, and attending physical education classes) or has increased (e.g., having not gone to school because of safety concerns, obesity, overweight, not eating vegetables, and not drinking milk). Monitoring emerging risk behaviors (e.g., texting and driving, bullying, and electronic vapor product use) is important to understand how they might vary over time. Public health action: YRBSS data are used widely to compare the prevalence of health behaviors among subpopulations of students; assess trends in health behaviors over time; monitor progress toward achieving 21 national health objectives for Healthy People 2020 and one of the 26 leading health indicators; provide comparable state and large urban school district data; and help develop and evaluate school and community policies, programs, and practices designed to decrease health-risk behaviors and improve health outcomes among youth.