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Self-Cutting and Suicidal Ideation among Adolescents:
Gender Differences in the Causes and Correlates of Self-Injury
The data used in this research were collected by the University of Delaware Center for Drug and
Alcohol Studies as part of a study supported by the Centers for Disease Control and Prevention.
The views and conclusions expressed in this manuscript are those of the authors and do not
necessarily represent those of the University of Delaware or the sponsoring agencies.
Abstract
In recent years, non-suicidal self-injury (NSSI) among adolescents has been identified as
alarmingly common place. Some studies have suggested that more than one in eight adolescents
have engaged in self-cutting or other self-injuring behaviors. Even more of a concern is that self-
injury often foreshadows suicide or suicide attempts. With self-cutting common in middle and
high schools, understanding the antecedents and correlates of such behavior may help counselors
and others public health officials identify troubled students and initiate preventative measures.
This study utilizes data from 2,639 high school students from the Delaware Youth Risk Behavior
Survey to investigate the gender differences in NSSI and suicidal ideation. Overall, 13%
reported engaging in NSSI within the past year, with females reporting significantly higher rates
(17%) of NSSI than males (9%). Results indicate that there are significant gender differences in
NSSI and suicidal thoughts based upon previous victimization experiences, reported substance
use, depression, health behaviors, and sexual orientation.
This is an Author's Accepted Manuscript of an article as published. Originally published in Deviant
Behavior. For citation and published article, see:
http://dx.doi.org/10.1080/01639625.2011.584054
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Self-Cutting and Suicidal Ideation among Adolescents:
Gender Differences in the Causes and Correlates of Self-Injury
It is well known, at least anecdotally, that some portion of adolescents intentionally hurt
themselves, usually secretly. It is also known that self-injury, unlike more expressive or euphoric
forms of delinquency, is often related to other psychological issues among those engaging in the
acts. Recent studies (e.g., Hilt, Nock, Lloyd-Richardson, and Prinstein 2008) have indicated that
these acts, often called non-suicidal self-injury (NSSI), are more common than once believed.
NSSI is most often referred to as the direct, deliberate destruction or alteration of body tissue
devoid of any conscious suicidal intent (Pattinson and Kahan 1983; Favazza 1998). While this
topic has been subject to a growing interest over the past decade, there exist only a handful of
studies examining NSSI among adolescents (see Heath, Ross, Toste, Charlebois, and Nedecheva
2009; Laye-Gindhu and Schonert-Reichl 2005; Ross and Heath 2002). Much of the extant
research on NSSI and other self-harming behaviors have primarily been concerned with
establishing prevalence rates among clinical samples and adults (Briere and Gil 1998; Haw and
Horton 2008; Klonsky, Oltmanns, and Turkheimer 2003). However, knowing that self-harm
behaviors often originate during adolescence and may transcend into adulthood (van der Kolk,
Perry, and Herman 1991), it is important for researchers and clinicians to recognize and identify
those risk factors early on in development for effective intervention and treatment.
Prevalence estimates of NSSI across studies have been remarkably inconsistent, making
cross-study comparisons difficult (see Table 1). Among those studies using community samples
of adolescents, it is estimated that about 8% of middle school students engage in NSSI, with
about one-third of them hurting themselves at least once per month (Hilt and Nock et al. 2008).
By the time students reach high school, that number has typically increased to between 9% and
25% (Brausch and Gutierrez 2010; Lloyd-Richardson, Muehlenkamp and Gutierrez 2004, 2007;
Perrine, Dierker, and Kelley 2007; Ross and Heath 2003). The generalizability of these
prevalence rates must be questioned based on the variable sampling frames and populations of
interest that have been utilized in previous research. Prevalence rates of NSSI have ranged from
7% to 25% among community samples of middle and high school students in the United States,
England, and Canada (Brausch and Gutierrez 2010; Hilt and Nock et al. 2008; Lay-Gindhu and
Schonert-Reichl 2005; Rodham, Hawton, and Evans 2004; Ross and Heath 2002), to rates as
high as 46.5% (Lloyd-Richardson et al. 2007). As is the case with all convenience-based
samples, the representativeness and generalizability of the results remains uncertain.
Despite recognizing that prevalence rates reach as high as one in eight individuals among
high school populations, little research has further explored this phenomenon. As has been
discussed, many studies have examined a small number of potential correlates among limited
samples of students. Also of interest is the limited research examining gender differences in the
prevalence and correlates of NSSI among adolescents in non-clinical samples. Females have
consistently been found to have higher prevalence rates in self-harming behaviors when
compared to males (Laye-Gindhu and Schonert-Reichl 2005; Patton et al. 1997; Rodham et al.
2004; Ross and Heath 2002). Fewer studies, however, have examined and compared the
correlates of NSSI and self-harming behaviors across male and female adolescents. Noting the
existence of competing gender roles, social expectations, and socialization experiences, it cannot
be assumed that both males and females engage in self-harming behavior for the same reasons. It
is generally understood that gender differences exist in the prevalence, nature, and motivations
behind many risk factors, thus the same must be anticipated when examining NSSI. The primary
NSSI 2
goal of this research seeks to build on this foundation by empirically assessing the gender
differences in the antecedents and correlates of NSSI and suicidal ideation using a large,
representative sample of high school students.
The Correlates of Self-Injury and Suicidal Ideation
As already discussed, relatively few studies have empirically assessed the predictors/correlates of
NSSI and suicidal ideation in the general adolescent population. Research has confirmed a strong
relationship between these behaviors, suggesting that individuals who engage in NSSI are at a
greater likelihood of making a suicide attempt (Miller and Smith 2008; Nock, Joiner, Gordon,
Lloyd-Richardson, and Prinstein 2006; Zlotnick, Donaldson, Sprirto, and Pearlstein 1997).
Despite the increased awareness of NSSI and suicidal ideation as problem behaviors,
methodological and sampling concerns have limited the generalizability of the substantive
findings concerning these often co-occurring antisocial behaviors. Before attempting to provide
such a study, an overview of prior empirical findings is presented. Note that this is not an attempt
to provide a full history. Rather, it is an overview of select categories of correlates and potential
correlates of self-injury and suicidal ideation that are relevant to the dataset available for this
empirical study.
Victimization and Substance Use
The first area of potential predictors/correlates of NSSI to be tested is prior victimization.
This is a particularly widespread category, as victimization varies dramatically by type, intensity,
and many other factors. Bullying has been found to be a major contributor in an adolescent’s
decision to engage in self-harming behavior. Children who are victimized through bullying
constitute roughly 11% of school-age children (Nansel, Craig, Overpeck, Saluja, and Ruan 2004)
and have been found to experience a wide range of negative consequences, including self-
harming behavior and suicidal ideation (Barker, Arseneault, Brendgen, Fontaine, and Maughan
2008; Fortune, Sinclair, and Hawton 2008; Kim, Koh, and Leventhal 2005; Rigby 1998;
Sourander et al. 2006). A study of 2,008 adolescents in Scotland found that males who reported
being bullied in school were twice as likely to engage in self-harming behaviors, while females
who reported being bullied in school were three times as likely (O’Connor, Rasmussen, Miles,
and Hawton 2009). Another common area of victimization linked to non-suicidal self-injury is
childhood sexual abuse and sexual assault (Gratz 2006). Childhood physical abuse in general has
similarly been linked to NSSI later in life. Overall, these two types of victimization have a strong
history of empirical support linking them to self-injury (e.g., Boudewyn and Liem 1995; Briere
and Gil 1998; Gratz, Conrad, and Roemer 2002; Gratz 2006; Zlotnick et al. 1996; Zoroglu et al.
2003).
Substance use has also been connected to self-injurious behavior. One study (Gupta and
Trzepacz 1997) found that individuals who had a history of substance abuse or substance
dependence had an increased likelihood of engaging in self-injuring behaviors. Another analysis
(Putnins 1995) investigating specific drugs found that hallucinogens, sedatives, stimulants, and
inhalants were all significant predictors of NSSI, while alcohol and marijuana were not. A study
(Hilt and Nock et al. 2008) attempting to follow-up on these studies using a larger community-
based sample also found a significant relationship between hard drug use and self-injury.
Specifically, the results indicated that participants who had used drugs to get high or smoking
NSSI 3
cigarettes were significantly more likely to engage in NSSI than those who had not.
1
Similarly, a
study of 633 high school students found that moderate and severe self-injurers were more likely
to use alcohol or drugs during their NSSI (Lloyd-Richardson et al. 2007).
Suicidal Ideation
Although NSSI and suicide attempts are separate and distinct behavioral phenomenon,
they often co-occur within individuals (Brown, Comtois, and Linehan 2002; Dulit, Fyer, Leon,
Brodsky, and Frances 1994; Nock et al., 2006). More importantly, it is thought that self-harming
behaviors such as NSSI may often be a precursor to planning a suicide, or the more severe act of
actually attempting suicide. Joiner and colleagues (2005) advanced a comprehensive theory
about self-injurious behaviors and suicide by claiming that a repeated engagement in NSSI may
make individuals more courageous, competent, and willing to make a suicide attempt,
reinforcing the both suicidal ideation and action. A study examining 89 adolescents admitted to
an adolescent psychiatric inpatient unit who had engaged in NSSI in the previous 12 months
found that 70% of these individuals had engaged in a lifetime suicide attempt, with 55%
reporting multiple attempts (Nock et al. 2006). These findings illustrate the significant overlap
between NSSI and suicidal ideation and actual suicide attempts, highlighting the importance of
early identification of risk factors for adolescents engaging in NSSI.
Health Behaviors
Another area of interest relating to NSSI is unhealthy eating and dieting behaviors.
Though the exact prevalence rate for self-injury among individuals with eating disorders varies
greatly (22%-62%) depending on the sample used, whether it involves youth or adults, and how
the eating disorder is measured, all studies on the relationship agree that individuals with eating
disorders are at an increased risk for self-injuring behavior (Favaro and Santonastaso 2000; Hilt
and Nock et al. 2008; Stein, Linenfeld, Wildman, and Marcus 2004; Welch and Fairburn 1996).
In some studies, eating disorders were diagnosed or individuals’ histories of such diagnoses were
used (Favaro and Santonastaso 2000; Stein et al. 2004; Welch and Fairburn 1996). In other cases,
specific negative eating behaviors were measured, including fasting and purging (Hilt and Nock
et al. 2008).
2
In an effort to understand the motivations behind NSSI and suicidal ideation, researchers
have continued to explore the relationship of these behaviors to depression. There exists an
underlying assumption that individuals who engage in NSSI, suicidal ideation, and other self-
harming behaviors suffer from depression (Favazza 1998; Feldman 1988). Though there is little
empirical work examining the relationship between NSSI and depression using community
samples of adolescents, a small number of studies have found that adolescents reporting NSSI
and suicidal ideation also reported significantly increased antisocial behavior, depression, and
other health risk behaviors (Laye-Gindhu and Schonert-Reichl 2005; Martin, Rozanes, Pearce,
and Allison 1995). Similarly, results from clinical samples of adolescents and adult samples have
also inferred the causal linkage between feelings of loneliness and depression as motivations for
deliberate self-harming behavior (Osuch, Noll, and Putnam 1999; Rodham et al. 2004; Suyemoto
1998). Explanations concerning this relationship characterize deliberate self-harming behaviors,
1
While the term ‘hard drugs’ was used to describe the respondent’s substance use, specific drugs constituting this
category of illicit substance was never clearly specified.
2
For a comprehensive overview of studies indicating intentional self-injury is more common among individuals
with eating disorders, see Sansone and Levitt’s (2002) summary report on the topic.
NSSI 4
such as cutting, as a way for individuals who suffer from anxiety or depression to cope and
internalize these negative emotions (Nixon, Cloutier, and Aggarwal 2002; Wilson and Deane
2010).
Sexual behavior and sexual orientation have had a more brief history in the academic
literature regarding NSSI. Sexual behavior is theoretically a predictor of self-injury because it
too is considered a risk behavior (Hilt and Nock et al. 2008). However, an empirical relationship
was not observed except in cases involving the combination of sexual intercourse and substance
use (Hilt and Nock et al. 2008). The use of sexual orientation as a risk factor for NSSI has been
limited in previous empirical studies. When utilized, however, it has been found to be a key risk
factor for both suicide and self-harming behaviors among gay, lesbian, and bisexual youth. One
such study that has examined sexual orientation and NSSI did find that male and female students
who were worried about their sexual orientation status were significantly more likely to have
engaged in self-harming behaviors during their lifetime (O’Connor et al. 2009). A similar study
examining female college students found that those reporting sexual minority status were at a
higher risk for engaging in deliberate self-harm (Gratz 2006).
A wider breadth of studies has examined the relationship between sexual minority status
and suicide attempts/ideation. One study found that 19% of gay college students had made
suicide attempts, many of which were related to conflict concerning their sexual orientation
(Savin-Williams and Cohen 1996). More recent studies have found that roughly one-third of a
community-based sample of self-identified sexual minority youth (15-19 years) had attempted
suicide (D’Augelli et al. 2005, D’Augelli, Hershberger, and Pilkington 2001). Similarly, a study
of 55 transgender youth between the ages of 15 and 21 found that those risk factors significantly
related to having made a suicide attempt included suicidal ideation related to transgender
identity, experiences of past physical abuse, and lower having a lower body self-image
(Grossman and D’Augelli 2007).
The Present Study
Having established the varying prevalence rates in community-based samples, and the
correlates of NSSI and suicide found in clinical or otherwise non-community samples, the
present study seeks to expand on this research by estimating the correlates of NSSI and suicidal
ideation with a large, community-based sample. Further, the study will employ separate gender
models to address the possibility that the correlates of NSSI and suicidal ideation differ by
gender. Moreover, by examining both NSSI and suicidal ideation within the same sample and
models, a comparison may be made to examine the potential differences and similarities of the
causes and correlated of these often co-occurring behaviors.
Methods
Data Collection and Sample
The data used in this study come from the Delaware High School Youth Risk Behavior
Survey (YRBS-H). The survey primarily includes questions developed by the Centers for
Disease Control and Prevention and the University of Delaware Center for Drug and Alcohol
Studies. The survey was administered to a random sample of public school ninth through twelfth
grade classrooms in Delaware between January and May 2007. Students were asked to complete
a self-administered, anonymous, questionnaire. Eighty-three percent of students enrolled in the
randomly selected classrooms were present on the day of administration, 99% of whom agreed to
NSSI 5
participate and returned a completed survey. An additional 4% of cases were deleted from the
data used for this study, as the participants did not provide a response for either of the dependent
variables used for this study, resulting in a final sample of 2,548 high school students. The
participants were 50% male and 50% female. By race/ethnicity, 54% were non-Hispanic White,
25% were non-Hispanic Black, 10% were Hispanic, and the remaining 11% reported a different
race or multiple races.
Variables
The primary dependent variable for this study is the question is, “During the past 12
months, did you do something to purposely hurt yourself without wanting to die, such as cutting,
scraping, or burning yourself on purpose?” Thirteen percent of high school students in the
present sample reported engaging in NSSI during the past year, which falls around the average
prevalence rates found in previous high school samples (Lloyd-Richardson et al. 2007; Ross and
Heath 2003). An additional dependent variable of interest is, “During the past 12 months, did
you ever seriously consider attempting suicide?” Both variables provided dichotomous yes/no
response categories. As will be discussed in greater detail in the analysis section, these variables
are moderately correlated (r = .45) and will be analyzed together as related outcomes. The
descriptive statistics for these and all other variables to be used are presented in Table 2.
Most independent variables used here are formed through factor extraction as a part of
factor analysis. These factors include having been bullied, being in fights, substance use,
hardcore drug use, and sexual behavior.
Bullied: The bullying factor was constructed using the following three variables: “During
the past 30 days, on how many days were you harassed or bullied on school property?”, “During
the past 30 days, on how many days has someone tried to hurt you by hitting, punching, or
kicking you on school property?”, and “During the past 12 months, how many times has
someone stolen or deliberately damaged your property, such as your car, clothing, or books on
school property?” The first two of these questions included possible responses of 0 days, 1 day, 2
or 3 days, 4 or 5 days, and 6 or more days. The latter question included responses of 0 times, 1
time, 2 or 3 times, 4 or 5 times, 6 or 7 times, 8 or 9 times, 10 or 11 times, and 12 or more times.
When combined together with factor extractions, the factor retains 62% (1.87 Eigenvalues) of
the variance (alpha = .69). As with all other factors created for these analyses, this factor is
standardized to have a mean of zero and a standard deviation of one.
Fighting: The fighting factor was also constructed using three indicators. These questions
include: “During the past 12 months, how many times were you in a physical fight?”, “During
the past 12 months, how many times were you in a physical fight in which you were injured and
had to be treated by a doctor or nurse?”, and “During the past 12 months, how many times were
you in a physical fight on school property?” These questions use the same number of times
format as used for the final bullying measure (0 times to 12 times or more), except for the injury
question which concludes with 6 or more times. The factor extracted from these questions
includes 68% (2.04 Eigenvalues) of the combined variance (alpha = .67).
Substance Use: As before, three indicators were used to capture this factor, including:
“During the past 30 days, on how many days did you smoke cigarettes?”, “During the past 30
days, on how many days did you have at least one drink of alcohol?”, and “During the past 30
days, how many times did you use marijuana?” For cigarettes and alcohol, possible responses
included 0 days, 1 or 2 days, 3 to 5 days, 6 to 9 days, 10 to 19 days, 20 to 29 days, and all 30
days. Marijuana use, however, included responses of 0 times, 1 or 2 times, 3 to 9 times, 10 to 19
NSSI 6
times, 20 to 39 times, and 40 or more times. The factor extracted from these variables retained
66% (1.99 Eigenvalues) of the variance (alpha = .74).
Hardcore Drug Use: This factor, as with the ones to follow, was constructed using two
indicators. Using only two indicators in the construction of a factor limits the advantages of
factor extraction, as both variables will always load equally on the factor due to the nature of
calculating factor loadings. Essentially, factor extraction in this situation is statistically
equivalent to forming an index. For the analyses in this study, however, factor extractions were
still used on these item grouping, as this keeps the constructs more uniform in design and result
in constructs consistently being standardized to the same metric. This particular factor was
created using the questions, “During the past 30 days, how many times did you use any form of
cocaine, including powder, crack, or freebase?” and “During the past 30 days, how many times
have you sniffed glue, breathed the contents of aerosol spray cans, or inhaled any paints or
sprays to get high?” Both had the response category also used for marijuana use (0 times to 40 or
more times). These variables scaled together with moderate reliability (alpha = .81).
Sexual Behaviors: Two questions were used to measure sexual activity: “During your
life, with how many people have you had sexual intercourse?” and “During the past 3 months,
with how many people did you have sexual intercourse?” Both questions provide responses for
each possible number of people, concluding with 6 or more people. These variables scale
together moderately well (alpha = .75).
Additional Indicators: In addition to the factors being used as predictors of cutting and
considering suicide, several demographic variables (gender, race, and sexual orientation) will
also be used as independent/control variables. Several other single indicator items will also be
included, all of which are dichotomous yes/no questions. First, a measure will be used to tap into
depression: “During the past 12 months, did you ever feel so sad or hopeless almost every day
for two weeks or more in a row that you stopped doing some usual activities?” Second, a
question about sexual assault: “Have you ever been physically forced to have sexual intercourse
when you did not want to?” Third, a series of three questions will be used to measure unhealthy
weight loss strategies: “During the past 30 days, did you go without eating for 24 hours or more
(also called fasting) to lose weight or to keep from gaining weight?”, “During the past 30 days,
did you take any diet pills, powders, or liquids without a doctor’s advice to lose weight or to
keep from gaining weight? (Do not include meal replacement products, such as Slim Fast)”, and
“During the past 30 days, did you vomit or take laxatives to lose weight or to keep from gaining
weight?” These individual indicators that serve as proxies for measures of eating disorders were
not combined into a single factor because they correspond with different types of eating
abnormalities and weight management, and therefore may have differing effects.
Analysis
Because the dependent variables are of a dichotomous nature, using ordinary least
squares (OLS) regression would violate the assumption that the dependent variable is
continuous. Typically, a logit-based regression (i.e. logistic regression) is used in such situations
because it accounts for the non-continuous nature of such variables by using the natural log
rather than the variable itself. In this case, however, an added characteristic in the data, the
correlated dependent variables, provides an additional need in the choice of a regression
technique. Though the estimates of separately performed logistic regressions would indeed be
actuate in describing the relationships between the independent variables and each of the
dependent variables, using a technique that recognizes and controls for the correlation between
NSSI 7
the related dependent variables provides the added benefit of allowing for each dependent
variable to control for each other without actually having to enter the alternative variable itself
into the model as a cause of the other (Greene 1995). Therefore, the models in this study will be
estimated using bivariate probit regression. For purposes of interpreting the output of such
estimations, the substantive conclusions of a probit model is virtually always the same as a logit
model for most models (Liao 1994). Moreover, the coefficients can be interpreted similar to
those of a logistic regression with one difference. In a logistic regression, the dependent variable
is the log of the odds that some characteristic is present, whereas a probit model estimates the
cumulative normal probability that the characteristic is present (Liao 1994). In other words, the
estimated value of the dependent variable in a probit model is analogous to a Z score of the
probability that Y = 1.
The models will be estimated twice; once without demographic controls and once with all
variables entered into the model. Additionally, because prior research has noted differential rates
of cutting by gender, separate models will be performed for male and female participants. For
cases missing data for a few predictors, mean substitution will be used. Cases missing on at least
four variables will be excluded from analyses.
Results
The results of the full sample bivariate probit are presented in Table 3. First, victimization
appears to have a significant effect on self-injury and suicidal thoughts. Specifically, individuals
who reported high levels of having been bullied were more likely to engage in self-injury than
those who reported low levels of bullying. Though bullying has limited exposure in the empirical
literature, these results support the long standing link between childhood physical abuse and self-
injury (Gratz et al. 2002; Gratz 2006; O’Conner et al. 2009; Zoroglu et al. 2003) and extend the
empirical support to less severe forms of abuse such as harassment. Previous research has also
linked childhood sexual abuse to NSSI (Boudewyn and Liem 1995; Briere and Gil 1998; Gratz et
al. 2002; Gratz 2006; Zlotnick et al. 1996; Zoroglu et al. 2003). The data in this larger school-
based sample also support the assertion that sexual assault increases the likelihood of engaging in
self-injury. In fact, having been the victim of a sexual assault changes the likelihood of NSSI
from 5% to 12% (holding all other variables constant). However, the same form of victimization
displays no significant effects on suicidal thoughts. Fighting was the only predictor of the three
to indicate no significant relationship with either variable of interest. This could be because the
fighting measures do not distinguish between victimization, perpetration, and mutual fighting.
Regarding the various measures of delinquency, there are mixed results. Substance use
was significantly correlated with both self-injury and suicidal thoughts, though the effect was
more pronounced for the former. More hardcore substances, including cocaine and inhalants,
were not related however. This is especially interesting, as the significance of softer drugs and
lack of significance for harder drugs is the reverse of the findings in a previous study
investigating individual drugs (Putnins 1995). It is possible this contrast arises from the prior
study’s very specific sample, involving incarcerated youth in Australia. Sexual behavior was
related to NSSI, though not with suicidal thoughts. This departs from previous findings
indicating no significant relationship with self-injury (Hilt and Nock et al. 2008). Interestingly,
individuals who were more sexually active were less likely to engage in self-injury. Though
several possible explanations could be given for this trend, such speculation will be withheld
NSSI 8
until these models are split into separate gender models, as those results may affect the possible
explanations.
The sole indicator for depression, feeling sad or hopeless, is the strongest predictor of
both self-injury and suicide. In fact, it increases the probability of engaging in such acts by
nearly a full standard deviation. For NSSI, the probability increases from 5% to 21%. The effect
on considering suicide is slightly more pronounced, increasing from 4% to 22%.
Finally, certain eating disorders were also predictive of self-injury and suicidal thoughts.
Consistent with prior findings (Hilt and Nock et al. 2008), individuals who fasted were more
likely to report affirmative answers for both questions. Purging, however, was the stronger
predictor of the two, especially for NSSI. Individuals who purged were more much likely (16%)
to self-injure than those who did not purge (5%). Overall, this first self-injury and suicidal
thoughts models explains 20% and 19% of the variance in the respective dependent variables.
Adding race, gender, and sexual orientation to the model has little substantive impact on
the effects of the independent variables; most coefficients change by only a small amount. The
variables themselves are in some cases predictive of NSSI and considering suicide. Females are
more likely than males to self-injure, but statistically equal for suicidal thoughts. The White
dummy variables was not significantly different from the holdout category of mixed/other (the
most likely category to engage in these behaviors), though Black students were less likely to
engage in self-injuring behaviors and Hispanic students were less likely to have suicidal
thoughts. The most influential variable of the demographic predictors was sexual orientation.
Students who identified as homosexual or bisexual were more likely to self-injure (18% vs. 5%)
and have suicidal thoughts (17% vs. 5%) than students identifying as heterosexual when holding
all other variables constant.
The results of separate male and female models are presented in Table 4. Several gender
differences appear to emerge when looking gender-specific coefficients. Bullying’s significance
is overall unchanged, yet fighting is now significant for females. The previous non-significance
appears to have been the result of the negative direction for females being weakened by the non-
significant positive direction for males. Exactly why fighting decreases the likelihood of self-
injury is unclear, though it may be related to the fact that physical fighting is a more masculine
trait and taps some dimension of aggression which would be an entirely different coping
mechanism than internalizing coping methods. Having been the victim of sexual assault is again
significant, though only for females. It is also significant for suicidal thoughts in the female
model.
The substance use measures again illustrate a contrast between the genders. For males,
more common forms of substance use, including cigarettes, alcohol, and marijuana, are
predictive of self-injury and considering suicide. For females, it is more intensive drug use,
including cocaine and inhalants, which have such a relationship.
The sexual behavior indicator that was previously significant has now dropped to non-
significance in both male and female models. Though part of this drop may be due to the
decreased sample size for both of the models, it cannot explain it entirely because both gender-
specific coefficients are lower than the original coefficient. Given that the drop occurred first
when gender was entered into the model, it is likely that part of the original relationship was
capturing part of gender via reported sexual behavior as a proxy. The data indicate that males, on
average, report more sexual partners overall and in the past three months. Thus, the relationship
between sexual behavior and NSSI/suicidal thoughts in the original model was likely the second
half of a mediated relationship between gender and NSSI/suicidal thoughts.
NSSI 9
Not unexpectedly, feeling sad or hopeless continues to have a significant effect in both
gender-specific models. The most influential of these relationships is on considering suicide
among males, where it increases the probability from 6% to 30%. The unhealthy dieting
measures continue to have an effect, but only for the female high school students. As before,
fasting and purging are significant predictors of self-injury. This is not entirely unexpected, as
taking extreme measures to lose weight is more often associated with girls. The effects of fasting
and purging, however, are no longer significant for suicidal thoughts. As before, taking diet pills
is not significantly related to NSSI or suicidal thoughts. Identifying as homosexual or bisexual
also continues to have a significant effect on the likelihood of NSSI and considering suicide,
though gay males are not significantly different than straight males when controlling for other
variables in the model. Overall, the gender specific models continue to explain between one-fifth
and one-fourth of the variance in the dependent variables.
Discussion
Despite the increased awareness of NSSI and suicidal ideation as adolescent problem behaviors,
few studies have addressed the social and interpersonal antecedents and correlates associated
with these antisocial behaviors. Most notably has been the absence of gender specific analyses in
the empirical literature. This study has investigated the gender differences in the prevalence and
correlates of NSSI and suicidal ideation among a large sample of high school students. The
results suggest that NSSI is continuing to be a prevalent problem affecting adolescents. Overall,
13% of the high school students reported engaging in NSSI during the past year, with females
reporting significantly higher rates than males (17% and 9% respectively). The prevalence rates
found in this study are consistent with prior research examining adolescents in community
samples, with reported past year rates ranging between 7% and 25% (see Brausch and Gutierrez
2010; Hilt and Nock et al. 2008; Lay-Gindhu and Schonert-Reichl 2005; Muehlenkamp and
Gutierrez 2004, 2007; Rodham et al. 2004; Ross and Heath 2002).
As expected, both male and female students who reported being the victims of bullying
were at an increased risk for both NSSI and suicidal ideation. Studies have consistently shown
that adolescents who are victimized through bullying are at an increased risk for negative
consequences. Despite the limited use of bullying as a correlate to NSSI and suicidal ideation in
prior research, these results support the research linking this victimization experience to these
self-harming behaviors (see Barker et al. 2008; Kim et al. 2005; O’Connor et al. 2009).
Similarly, students reporting having been a victim of sexual assault changed the likelihood of
NSSI from 5% to 12%. This was particularly salient for female victims of sexual assault, who
were significantly more likely to report both NSSI and suicidal ideation. This finding is
consistent with previous research linking childhood sexual abuse to self-harming behaviors and
suicidal ideation later in life (Boudewyn and Liem 1995; Briere and Gil 1998; Zlotnick et al.
1996), although few studies have explored the gender differences in such behaviors.
Similarly, measures of substance use were significantly related to both NSSI and suicidal
ideation. Previous research has linked substance use to NSSI and suicidal ideation, however
discrepancies exist in exactly which classifications of drugs have the most influence on these
harmful behaviors. For instance, various studies have linked NSSI and suicidal ideation to
hardcore substance use, such as hallucinogens, sedatives, stimulants, and inhalants (Gupta and
Trzepacz 1997; Putnins 1995). Conversely, other empirical research points to more typical
substance use that is regularly associated with adolescent populations (i.e., cigarettes, alcohol,
NSSI 10
and marijuana) to explain this association (Hilt and Nock et al. 2008; Lloyd-Richardson et al.
2007). Given the unique nature of the data, the current study is able to add more clarity to the
relationship by examining these behaviors separately for both male and female students.
Interestingly, the more common measure of substance use (i.e., cigarettes, alcohol, and
marijuana) had a significant effect on male self-injury and suicidal ideation, while the more
stringent hardcore substance use (i.e., crack, cocaine, and inhalants) measure had similar
significant effects for females. Exactly why the type of substance use that corresponds to self-
injury varies so dramatically by gender is unclear, and worthy of additional research.
Little research has been explored regarding possible gender differences in NSSI and
suicidal ideation as they relate to self-reported depression. The results of this study indicate that
male and female respondents reporting negative emotional states were more likely to report both
NSSI and suicidal ideation. This was particularly true for male students, where the probability of
suicidal thoughts increased from 6% to 30% among those who reported past year depression.
While not surprising, these findings are important given that this is one of the few studies to
make an empirical linkage between these self-harming behaviors and depression using a
contemporary, community-based adolescent sample (see also Laye-Gindhu and Schonert-Reichle
2005). It is reasonable to presume that students in a depressive mental state use deliberate self-
harming behaviors and suicidal ideation as a way to internalize these negative emotions and to
reduce high levels of anxiety (Favazza and Conterio 1989; Nock and Prinstein 2004).
While unhealthy dieting behaviors had no effect on student suicidal ideation or on NSSI
among male students, females reporting fasting or purging were at an increased risk for NSSI.
This gender difference is not entirely surprising considering that these types of extreme measures
used to lose weight are predominantly associated with females. Similar findings have been found
in studies using community samples of adolescents, where maladaptive eating habits (i.e., fasting
and bingeing) were more prevalent among students reporting NSSI (Hilt and Nock et al. 2008),
as well as in studies linking eating disorders and self-harming behaviors in adults and older
adolescents (Favaro and Santonastaso 2000; Sansone and Levitt 2002; Stein et al. 2004).
Differences again emerged in the self-reported NSSI and suicidal ideation among
students identifying themselves as sexual minorities. Overall, students that were self-identified as
a sexual minority were more likely to self-injure (18% vs. 5%) and have suicidal thoughts (17%
vs. 5%) than students identifying as heterosexual. Among those students reporting sexual
minority status, males were significantly more likely to report suicidal ideation, while females
were more likely to report both NSSI and suicidal ideation. Despite the limited utilization of
sexual orientation as a risk factor for NSSI in previous empirical studies, the current findings
support previous research linking sexual minority status with both self-harming behaviors and
suicidal ideation/attempts (O’Conner et al. 2009; Gratz 2006; Grossman and D’Augelli 2007).
Being that this study utilizes a sample of high school students, it is well documented that
adolescence is a time when socialization pressures from peers and family members encourage
the acceptance of traditional sex-role related behavior (Barrett and White 2002; Lytton and
Romney 1991). Any deviation from traditional gender behavior becomes less tolerated and more
socially enforceable as youth move through adolescence to young adulthood. Research has
suggested that gay and lesbian youth are highly vulnerable to social anxiety, victimization by
bullying from peers, substance abuse, and sexual identity conflicts, all of which increase the risk
of engaging in self-injurious behaviors and suicidal ideation as a means to cope with the stressors
of their sexual minatory status (Russell 2003; van Wormer, Wells, and Boes 2000).
NSSI 11
As with any study, these findings are not without limitations. First, although this study
offered an important examination of NSSI and suicidal ideation, the assessment of these risk
behaviors were assessed using single-item measures. More detailed measures, particularly for
NSSI among adolescents, should be explored in future research. Though this study provides a
critical look at the prevalence and correlates of NSSI, being able to differentiate between exactly
what conduct characterize these self-harming behaviors (i.e., cutting, burning, self-hitting) would
be useful in determining the severity of these actions. Second, the data used here are self-
reported actions and thoughts. While self-report data is generally favorable to official data for
measures of deviance (Bachman and Paternoster 2009), it is not without weaknesses. In this case,
it is not impossible that different students interpreted the various questions differently,
particularly when dealing with self-injurious behaviors and suicidal ideation. Nevertheless, the
strengths of self-report data outweigh any limitations of this nature. Third, this study uses a
cross-sectional design. Ideally, longitudinal data would provide an increased understanding of
the temporal progression and etiological factors that precede NSSI and suicidal ideation,
providing evidence of the casual framework associated with these behaviors. Prospective
longitudinal and cohort studies on this topic are necessary in the creation and implementation of
effective and reliable intervention strategies, and must be the focus concerning future work in
this area. Finally, while this study did use a large, randomly selected community-based sample
which is unique for empirical studies examining NSSI, these data did come from only one state
which may limit its generalizability. Thus, further research replicating this design is needed.
Despite these limitations, the current study provides noteworthy information regarding
the prevalence, correlates, and antecedents of NSSI and suicidal ideation among adolescents. As
discussed previously, the high rate of NSSI among young adolescents illustrates that this remains
a problem behavior. The results indicate that there are significant gender similarities and
differences in NSSI and suicidal ideation as it relates to substance use, victimization, depression,
health behaviors, and sexual orientation. These findings should be useful for practitioners and
clinicians attempting to identify adolescents at a higher risk for NSSI and suicidal thoughts,
informing both prevention and intervention efforts. Future studies should continue to examine
the developmental changes that occur during adolescence, as such information could help
counselors and others public health officials identify troubled students and initiate any necessary
anticipatory or preventative measures.
References
Adler, P. A., and P. Adler. 2007. “The Demedicalization of Self-Injury: From Psychopathology
to Sociological Deviance.” Journal of Contemporary Ethnography 36:537-570.
Bachman, R. and R. Paternoster 2009. Statistical Methods for Criminology and Criminal Justice.
3rd ed. New York: McGraw-Hill.
Barker, E. D., L. Arseneault, M. Brendgen, N. Fontaine, and B. Maughan. 2008. “Joint
Development of Bullying and Victimization in Adolescence: Relations to Delinquency
and Self-Harm.” Journal of the American Academy of Child and Adolescent Psychiatry
47:1030-1038.
Barrett, A. E., and H. R. White. 2002. “Trajectories of Gender Role Orientations in Adolescence
and Early Adulthood: A Prospective Study of Mental Health Effects of Masculinity and
Femininity.” Journal of Health and Social Behavior 43:451-468.
NSSI 12
Boudewyn, A. C., and J. H. Liem. 1995. “Childhood Sexual Abuse as a Precursor to Depression
and Self-Destructive Behavior in Adulthood.” Journal of Traumatic Stress 8:445-459.
Brausch, A. M., and P. M. Gutierrez. 2010. “Differences in Non-Suicidal Self-Injury and Suicide
Attempts in Adolescents.” Journal of Youth and Adolescence 39:233-242.
Briere, J., and E. Gil. 1998. “Self-Mutilation in Clinical and General Population Samples:
Prevalence, Correlates, and Functions.” American Journal of Orthopsychiatry 68:609-
620.
Brown, M. Z., K. A. Comtois, and M. M. Linehan. 2002. “Reasons for Suicide Attempts and
Nonsuicidal Self-Injury in Women with Borderline Personality Disorder.” Journal of
Abnormal Psychology 111:198-202.
D’Augelli, A. R., A. H. Grossman, N. P. Salter, J. J. Vasey, M. T. Starks, and K. O. Sinclair.
2005. “Predicting the Suicide Attempts of Lesbian, Gay, and Bisexual Youth.” Suicide
and Life-Threatening Behavior 35:646-660.
D’Augelli, A. R., S. L. Hershberger, and N. W. Pilkington. 2001. “Suicidality Patterns and
Sexual Orientation Related Factors Among Lesbian, Gay, and Bisexual Youths.” Suicide
and Life-Threatening Behavior 31:250-264.
Dulit, R. A., M. R. Fyer, A. C. Leon, B. S. Brodsky, and A. J. Frances. 1994. “Clinical
Correlates of Self-Mutilation in Borderline Personality Disorder.” American Journal of
Psychiatry 151:1305-1311.
Favaro, A., and P. Santonastaso. 2000. “Self-Injurious Behavior in Anorexia Nervosa.” Journal
of Nervous and Mental Disease 188:537-542.
Favazza, A. R. 1998. “The Coming of Age of Self-Mutilation.” The Journal of Nervous and
Mental Disease 186:259-268.
Favazza, A. R., and K. Conterio. 1989. “Habitual Female Self-Mutilators.” Acta Psychiatrica
Scandinavica 79:283-289.
Feldman, M. D. 1988. “The Challenge of Self-Mutilation: A Review.” Comprehensive
Psychology 29:252-269.
Fortune, S., J. Sinclair, and K. Hawton. 2008. “Adolescents’ Views on Preventing Self-Harm: A
Large Community Study.” Social Psychiatry and Psychiatric Epidemiology 43:96-104.
Gratz, K. L., S. D. Conrad, and L. Roemer. 2002. “Risk Factors for Deliberate Self-Harm
Among College Students.” American Journal of Orthopsychiatry 72:128-140.
Gratz, K. L. 2006. “Risk Factors for Deliberate Self-Farm Among Female College Students: The
Role and Interaction of Childhood Maltreatment, Emotional Inexpressivity, and Affect
Intensity/Reactivity.” American Journal of Orthopsychiatry 76:238-250.
Greene, W. H. 1995. LIMDEP Version 7.0 User's Manual. Bellport, NY: Econometric Software.
Grossman, A. H., and A. R. D’Augelli. 2007. “Transgender Youth and Life-Threatening
Behaviors.” Suicide and Life-Threatening behavior 37:527-537.
Gupta, B., and P. T. Trzepacz. 1997. “Serious Overdosers Admitted to a General Hospital:
Comparison with Nonoverdose Self-Injuries and Medically Ill Patients with Suicidal
Ideation.” General Hospital Psychiatry 19:209-215.
Haw, C., and K. Hawton. 2008. “Life Problems and Deliberate Self-Harm: Associations with
Gender, Age, Suicidal Intent and Psychiatric and Personality Disorder.” Journal of
Affective Disorders 109:139-148.
Heath, N. L., S. Ross, J. R. Toste, A. Charlebois, and T. Nedecheva. 2009. “Retrospective
Analysis of Social Factors and Nonsuicidal Self-Injury Among Young Adults.” Canadian
Journal of Behavioral Science 41:180-186.
NSSI 13
Hilt, L. M., C. B. Cha, and S. Nolen-Hoeksema. 2008. “Nonsuicidal Self-Injury in Young
Adolescent Girls: Moderators of the Distress-Function Relationship.” Journal of
Consulting and Clinical Psychology 76:63-71.
Hilt, L. M., M. K. Nock, E. E. Lloyd-Richardson, and M. J. Prinstein. 2008. “Longitudinal Study
of Nonsuicidal Self-Injury among Young Adolescents: Rates, Correlates, and Preliminary
Test of an Interpersonal Model.” Journal of Early Adolescence 28:455-469.
Joiner, T. E., Y. Conwell, K. Fitzpatrick, T. Witte, N. B. Schmidt, M. T. Berlim, M. P. Fleck,
and D. M. Rudd. 2005. “Four Studies on How Past and Current Suicidality Related Even
When ‘Everything but the Kitchen Sink’ is Covaried.” Journal of Abnormal Psychology
114:291-303.
Kim, Y. S., Y-J. Koh, and B. Leventhal. 2005. “School Bullying and Suicidal Risk in Korean
Middle School Students.” Pediatrics 115:357-363.
Klonsky, E. D. and T. M. Olino. 2008. “Identifying Clinically Distinct Subgroups of Self-
Injurers Among Young Adults: A Latent Class Analysis.” Journal of Consulting and
Clinical Psychology 76:22-27.
Klonsky, E. D., T. F. Oltmanns, and E. Turkheimer. 2003. “Deliberate Self-Harm in a Non-
Clinical Population: Prevalence and Psychological Correlates.” American Journal of
Psychiatry 160:1501-1508.
Laye-Gindhu, A., and K. A. Schonert-Reichl, K. A. 2005. “Nonsuicidal Self-Harm Among
Community Adolescents: Understanding the “Whats” and “Whys” of Self-Harm.”
Journal of Youth and Adolescence 34:447-457.
Liao, T. F. 1994. Interpreting Probability Models: Logit, Probit, and Other Generalized Linear
Models. Thousand Oaks, CA: Sage.
Lloyd-Richardson, E. E., Perrine, N., Dierker, L., and Kelley, M. L. 2007. “Characteristics and
Functions of Non-Suicidal Self-Injury in a Community Sample of Adolescents.”
Psychological Medicine 37:1183-1192.
Lytton, H., and D. M. Romney. 1991. “Parents’ Differential Socialization of Boys and Girls: A
Meta-Analysis.” Psychological Bulletin 109:267-296.
Martin, G., P. Rozanes, C. Pearce, and S. Allison. 1995. “Adolescent Suicide, Depression, and
Family Dysfunction.” Acta Psychiatrica Scandinavica 92:336-344.
Miller, A. L. and H. L. Smith. 2008. “Adolescent Non-Suicidal Self-Injurious Behavior: The
Latest Epidemic to Assess and Treat.” Applied and Preventative Psychology 12:178-188.
Muehlenkamp, J. J., and P. M. Gutierrez. 2004. “An Investigation of Differences Between Self-
Injurious Behavior and Suicide Attempts in a Sample of Adolescents.” Suicide and Life-
Threatening Behavior 34:12-23.
Muehlenkamp, J. J., and Gutierrez, P. M. 2007. “Risk for Suicide Attempts Among Adolescents
Who Engage in Non-Suicidal Self-Injury.” Archives of Suicide Research 11:1-14.
Nansel, T. R., W. Craig, M. D. Overpeck, G. Saluja, and J. Ruan. 2004. “Cross-National
Consistency in the Relationship Between Bullying Behaviors and Psychosocial
Adjustment.” Archives of Pediatrics & Adolescent Medicine 15:730-736.
Nixon, M. K., P. F. Cloutier, and S. Aggarwal. 2002. “Affect Regulation and Addictive Aspects
of Repetitive Self-Injury in Hospitalized Adolescents.” Journal of the American Academy
of Child and Adolescent Psychiatry 41:1333-1341.
Nock, M. K., T. E. Joiner Jr., K. H. Gordon, E. Lloyd-Richardson, and M. J. Prinstein. 2006.
“Nonsuicidal Self-Injury Among Adolescents: Diagnostic Correlates and Relation to
Suicide Attempts.” Psychiatry Research 144:65-72.
NSSI 14
Nock, M. K., and M. J. Prinstein. 2004. “A Functional Approach to the Assessment of Self-
Mutilative Behavior.” Journal of Consulting and Clinical Psychology 72:885-890.
O’Connor, R. C., S. Rasmussen, J. Miles, and K. Hawton. 2009. “Self-Harm in Adolescents:
Self-Report Survey in Schools in Scotland.” The British Journal of Psychiatry 194:68-72.
Osuch, E. A., J. G. Noll, and F. W. Putnam. 1999. “The Motivations for Self-Injury in
Psychiatric Patients.” Psychiatry: Interpersonal and Biological Processes 62:334-346.
Pattison, E. M., and J. Kahan. 1983. “The Deliberate Self-Harm Syndrome.” American Journal
of Psychiatry 140:867-872.
Patton, G. C., R. Harris, J. B. Carlin, M. E. Hibbert, C. Coffey, M. Schwartz, and G. Bowes.
1997. “Adolescent Suicidal Behaviors: A Population-Based Study of Risk.”
Psychological Medicine 27:715-724.
Putnins, A. L. 1995. “Recent Drug Use and Suicidal Behaviour Among Young Offenders.” Drug
& Alcohol Review 14:151-158.
Rigby, K. 1998. “The Relationship Between Reported Health and Involvement in Bully/Victim
Problems Among Male and Female Secondary School Children.” Journal of Health
Psychology 3:465-476.
Rodham, K., K. Hawton, and E. Evans. 2004. “Reasons for Deliberate Self-Harm: Comparison
of Self-Poisoners and Self-Cutters in a Community Sample of Adolescents.” Journal of
the American Academy of Child and Adolescent Psychiatry 43:80-87.
Ross, S., and N. L. Heath. 2002. “A Study of the Frequency of Self-Mutilation in a Community
Sample of Adolescents.” Journal of Youth and Adolescence 31:67-77.
Ross, S., and N. L. Heath. 2003. “Two Models of Adolescent Aelf-Mutilation.” Suicide and Life
Threatening Behavior, 33, 277-287.
Russell, S. T. 2003. “Sexual Minority Youth and Suicide Risk.” American Behavioral Scientist
46:1241-1257.
Sansone, R. A., and J. L. Levitt L. 2002. “Self-Harm Behaviors Among Those with Eating
Disorders: An Overview.” Eating Disorders 10:205-213.
Savin-Williams, R. C., and K. M. Cohen. 1996. The Lives of Lesbians, Gays, and Bisexuals:
Children to Adults. Fort Worth, TX: Harcourt Brace.
Sourander, A., M. Arommaa, L. Pihlakoski, A. Haavisto, P. Rautava, H. Helenius, and M.
Sillanpää. 2006. “Early Predictors of Deliberate Self-Harm Among Adolescents. A
Prospective Follow-Up Study from Age 3 to 15.” Journal of Affective Disorders 93:87-
96.
Stein, D., L. R. Lilenfeld, P. C. Wildman, and M. D. Marcus. 2004. “Attempted Suicide and
Self-Injury in Patients Diagnosed with Eating Disorders.” Comprehensive Psychiatry
45:447-451.
Suyemoto, K. 1998. “The Functions of Self-Mutilation.” Clinical Psychological Review 18:531-
554.
van der Kolk, B. A., J. C. Perry, and J. L. Herman. 1991. “Childhood Origins of Self-Destructive
Behaviors.” American Journal of Psychiatry 148:1665-1671.
van Wormer, K., J. Wells, and M. Boes. 2000. Social Work with Lesbians, Gays, and Bisexuals:
A Strengths Perspective. Boston, MA: Allyn and Bacon.
Welch, S. L., and C. G. Fairburn. 1996. “Impulsivity or Comorbidity in Bulimia Nervosa: A
Controlled Study of Deliberate Self-Harm and Alcohol and Drug Misuse in a Community
Sample. British Journal of Psychiatry 169:451-458.
NSSI 15
Wilson, C. J., and F. P. Deane. 2010. “Help-Negation and Suicidal Ideation: The Role of
Depression, Anxiety, and Hopelessness.” Journal o f Youth and Adolescence 39:291-305.
Zlotnick, C., D. Donaldson, A. Spirito,, T. & Pearlstein. 1997. “Affect Regulation and Suicide
Attempts in Adolescent Inpatients. Journal of the American Academy of Child &
Adolescent Psychiatry 36:793-798.
Zlotnick, C., M. T. Shea, T. Pearlstein, E. Simpson, E. Costello, and A. Begin. 1996. “The
Relationship Between Dissociative Symptoms, Alexithymia, Impulsivity, Sexual Abuse,
and Self-Mutilation. Comprehensive Psychiatry 37:12-16.
Zoroglu, S. S., U. Tuzun, V. Sar, H. Tutkun, H. A. Savas, M. Ozturk, B. Alyanak, and M. E.
Kora. 2003. Suicide Attempt and Self-Mutilation Among Turkish High School Students
in Relation with Abuse, Neglect and Dissociation. Psychiatry and Clinical Neurosciences
57:119-126.
NSSI 16
Table 1: Empirical Studies of Non-Suicidal Self-Injury (NSSI)
Study
Sample
Past Year
NSSI (%)
Community Samples
Gratz (2006)
249 female college students
37% lifetime
Gratz, Conrad, & Roemer (2002)
133 college students
38% lifetime
Hilt, Nock, Lloyd-Richardson, &
Prinstein (2008)
Community sample of 508 students in 6th, 7th,
and 8th grades in northeastern United States
7.5%
Hilt, Cha, & Nolen-Hoeksema
(2008)
94 adolescent girls in the northeastern United
States
56.4%
Laye-Gindhu & Schonert-Reichl
(2005)
424 adolescents from western Canadian high
school
15%
Lloyd-Richardson, Perrine,
Kierker, & Kelley (2007)
633 students (grades 9-12) samples from five
high schools
46.5%
Rodham, Hawton, & Evans
(2004)
6,020 adolescents (15-16 years) from 41 schools
in England
6.9%
Ross & Heath (2002)
440 9th and 10th grade students from two high
schools
13.9%
lifetime
Non-Community Samples
Adler & Adler (2007)
80 in-depth interviews (16-50 years) of those
reporting NSSI online
100%
Briere & Gil (1998)
927 adults (general sample)
390 adults (clinical sample)
4%
21%
Haw & Horton (2008)
4,391 adolescents and adults in a clinical sample
who were admitted after an NSSI episode
100%
Heath, Ross, Toste, Charlebois,
& Nedecheva (2009)
23 self-injuring college students
100%
Klonsky & Olino (2008)
205 college students who reported at least one
NSSI behavior
100%
Klonsky, Oltmanns, &
Turkheimer (2003)
1,986 military recruits
4%
Nock, Joiner Jr., Gordon, Lloyd-
Richardson, & Prinstein (2006)
89 adolescents (12-17 years) selected from an
inpatient psychiatric unit with past year
engagement in NSSI
100%
Note: This is not a comprehensive list of all studies examining NSSI. Additionally, only studies that
included prevalence rates were considered for inclusion.
NSSI 17
Table 2: Descriptive Statistics
Mean
SD
Min
Max
Factor
Loading
Dependent Variables
Cutting
.13
.33
.00
1.00
---
Considered Suicide
.11
.32
.00
1.00
---
Independent Variables
Female
.50
.49
.00
1.00
---
Hispanic
.10
.30
.00
1.00
---
Black
.26
.44
.00
1.00
---
White
.55
.50
.00
1.00
---
Sexual Minority
.05
.21
.00
1.00
---
Sad/Hopeless
.26
.44
.00
1.00
---
Victim of Sexual Assault
.07
.26
.00
1.00
---
Fasting
.11
.31
.00
1.00
---
Diet pills
.05
.21
.00
1.00
---
Purging
.04
.19
.00
1.00
---
Bullied Factor
Harassed
1.27
.84
1.00
5.00
.79
Tried to hurt
1.24
.77
1.00
5.00
.81
Stolen/damaged property
1.39
1.04
1.00
8.00
.76
Fighting Factor
In a fight
1.72
1.43
1.00
8.00
.79
Injured in a fight
1.09
.47
1.00
5.00
.80
Fought at school
1.22
.84
1.00
8.00
.87
Substance Use
Cigarettes
1.77
1.75
1.00
7.00
.82
Alcohol
1.91
1.31
1.00
7.00
.80
Marijuana
1.63
1.31
1.00
6.00
.82
Hardcore Drug Use
Cocaine
1.08
.52
1.00
6.00
.92
Inhalants
1.09
.53
1.00
6.00
.92
Sexual Behavior
Lifetime number of partners
1.79
2.08
.00
6.00
.92
Recent number of partners
.73
1.16
.00
6.00
.92
NSSI 18
Table 3: Bivariate Probit
Model 1
Model 2
Self-Injury
Suicidal Thoughts
Self-Injury
Suicidal Thoughts
b
SE
b
SE
b
SE
b
SE
Bullied
.13
.03*
.14
.04*
.14
.03*
.12
.04*
Fighting
.00
.04*
.02
.04*
.03
.04*
.03
.04*
Sexual Assault
.48
.11*
.04
.04*
.37
.12*
.21
.12*
Substance Use
.17
.04*
.09
.04*
.13
.04*
.08
.04*
Hardcore Drug Use
.07
.04*
.07
.04*
.06
.04*
.06
.04*
Sexual Behavior
-.14
.04*
.04
.04*
-.09
.04*
.05
.04*
Sad/Hopeless
.87
.07*
.99
.08*
.83
.08*
.98
.08*
Fasting
.32
.10*
.29
.10*
.24
.11*
.25
.10*
Diet Pills
-.07
.16*
-.04
.15*
-.15
.17*
-.10
.16*
Purging
.66
.17*
.46
.17*
.68
.17*
.47
.18*
Female
---
---
---
---
.19
.08*
.04
.08*
Sexual Minority
---
---
---
---
.75
.15*
.64
.13*
Hispanic
---
---
---
---
-.21
.16*
-.33
.16*
Black
---
---
---
---
-.50
.15*
-.23
.14*
White
---
---
---
---
-.00
.12*
-.13
.12*
Constant
-1.67
.05
-1.75
.06
-1.66
.12
-1.61
.12
R2 †
.20
.19
.21
.22
ρ
.57 (.04)
.56 (.04)
* p < .05
† Coefficient of determination calculated using separate probit models
NSSI 19
Table 4: Bivariate Probits by Gender
Males
Females
Self-Injury
Suicidal Thoughts
Self-Injury
Suicidal Thoughts
b
SE
b
SE
b
SE
b
SE
Bullied
.18
.05*
.13
.06*
.11
.05*
.14
.06*
Fighting
.08
.06*
.06
.05*
-.18
.09*
-.11
.10*
Sexual Assault
.39
.34*
.05
.32*
.42
.15*
.28
.14*
Substance Use
.17
.07*
.13
.06*
.08
.05*
.01
.06*
Hardcore Drug Use
.02
.08*
.06
.06*
.21
.08*
.17
.06*
Sexual Behavior
-.10
.07*
.02
.06*
-.09
.06*
.07
.07*
Sad/Hopeless
1.01
.13*
1.05
.12*
.74
.10*
.95
.14*
Fasting
.07
.19*
.31
.17*
.32
.13*
.21
.13*
Diet Pills
-.00
.33*
-.70
.43*
-.15
.21*
.22
.20*
Purging
.54
.34*
.58
.37*
.65
.21*
.35
.23*
Sexual Minority
.52
.36*
.71
.29*
.86
.17*
.66
.17*
Hispanic
-.40
.26*
-.44
.26*
-.00
.22*
-.19
.22*
Black
-.58
.25*
-.25
.21*
-.38
.20*
-.19
.20*
White
-.10
.19*
-.19
.19*
-.10
.17*
-.09
.17*
Constant
-1.64
.18
-1.58
.18
-1.59
.17
-1.68
.16
R2 †
.23
.21
.23
.21
ρ
.59 (.07)
.53 (.06)
* p < .05
† Coefficient of determination calculated using separate probit models
