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Journal of Interpersonal Violence
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Digital Dating Abuse
Among a National
Sample of U.S. Youth
Sameer Hinduja, PhD1
and Justin W. Patchin, PhD2
Digital dating abuse is a term used to describe physical, sexual, or
psychological/emotional violence that occurs between romantic partners
through the use of texting, social media, and related online mediums.
Survey data were obtained from a nationally representative sample of 2,218
American middle and high school students (12–17 years old) who have
been in a romantic relationship. About 28% of students in a relationship
in the previous year had been the victim of digital dating abuse. Males
were more likely to report having experienced it (32% compared to 24%),
though no other demographic differences emerged. Several covariates
did emerge as significantly related to experience with digital dating abuse,
including depressive symptoms, sexual intercourse, sexting, and being the
victim of cyberbullying. Experiencing offline dating abuse was by far the
strongest correlate. Implications for prevention and policy within schools
and the community are discussed, along with considerations for future
research in this important area.
digital dating abuse, teen dating violence, adolescent development, online
1Florida Atlantic University, Jupiter, FL, USA
2University of Wisconsin-Eau Claire, Eau Claire, WI, USA
Sameer Hinduja, Florida Atlantic University, Parkside Drive, Jupiter, FL 5353, USA.
897344JIVXXX10.1177/0886260519897344Journal of Interpersonal ViolenceHinduja and Patchin
2 Journal of Interpersonal Violence 00(0)
Much of adolescent development now takes place online, allowing youth to
create, explore, produce, and define their identities and relationships through
texting, social media interaction, multiplayer gaming, and related forms of
connectivity. Most youth seem to use online technology in positive ways
(Ahola Kohut et al., 2018; Bers, 2010; Blank & Lutz, 2018; Lytle et al., 2018;
Metzger et al., 2018), but numerous recent studies have empirically identified
problem behaviors that have arisen (Werner et al., 2010), including cyberbul-
lying (Hinduja & Patchin, 2015; Kowalski et al., 2014), sexting (Hinduja &
Patchin, 2012; Rice et al., 2012; Temple et al., 2012), catfishing (D’Costa,
2014), revenge porn (Citron & Franks, 2014; Englander & McCoy, 2017),
and sextortion (Patchin & Hinduja, 2020; Wolak et al., 2018).
Another novel behavioral problem at the intersection of adolescence and
technology which manifests itself within the context of a romantic relation-
ship has been termed “digital dating abuse” (also referred to as “electronic
dating violence”). Defined as “a pattern of behaviors that control, pressure, or
threaten a dating partner using a cell phone or the Internet” (Reed et al., 2016,
p. 1), digital dating abuse is the 21st century evolution of teen dating violence,
which has been an issue of concern for decades (Lavoie et al., 2000; Levy,
1991; O’Keeffe et al., 1986; Spencer & Bryant, 2000). The Centers for Disease
Control and Prevention (CDC, 2017) succinctly conceptualize teen dating vio-
lence as physical, sexual, or psychological/emotional violence that occurs
within a dating relationship. Digital dating abuse can be considered a type of
cyberbullying, defined as “willful and repeated harm inflicted through com-
puters, cell phones, and other electronic devices” (Hinduja & Patchin, 2015,
p. 11) and potentially can involve behaviors classified as cyberstalking, which
uses technology to repetitively harass another person with the intent to con-
trol, coerce, intimidate, annoy, or threaten them (Spitzberg & Hoobler, 2002).
With regard to its frequency among youth, findings from the CDC’s national
Youth Risk Behavior Survey in 2017 (the latest year available) identified that
8% of high schoolers experienced a physical form of dating abuse while 7%
experienced a sexual form of dating abuse (CDC, 2018). Nevertheless, a recent
meta-analysis on prevalence rates of teen dating violence suggests that the CDC
percentages may be conservative. Wincentak et al. (2017) examined 96 studies
of physical dating violence involving youth aged 13 to 18 and found an overall
victimization rate of 20% (with a variability range of 1%–61%). They also
examined 31 studies of sexual dating violence and identified an overall victim-
ization rate of 9% (with a variability range of <1% to 64%).
There are multiple ways in which teens can exploit online communications
to cause harm to a romantic partner (Dank et al., 2014; Korchmaros et al., 2013;
Van Ouytsel et al., 2016). Teens may be excessively mean-spirited and hurtful to
their significant other when interacting with them online for the same reasons
Hinduja and Patchin 3
that those who cyberbully or troll others do (Hinduja & Patchin, 2009; Leisring
& Giumetti, 2014; Melander, 2010). In addition, privacy violations can occur as
youth incessantly check up on, keep track of, and even stalk their partners via
their device(s) (Baker & Carreño, 2016; Draucker & Martsolf, 2010; Lucero
et al., 2014; Randell et al., 2016). Teens can also hack into or otherwise obtain
unauthorized access into their partner’s personal social media or email accounts
(Borrajo et al., 2015). Relatedly, some aggressors have improperly obtained and
used private pictures or videos to blackmail, extort, or otherwise manipulate
their romantic partner into saying or doing something against their will (Patchin
& Hinduja, 2020; Wittes et al., 2016; Wolak et al., 2018).
Given that participation in romantic relationships increases when moving
through adolescence into young adulthood (Carlson & Rose, 2012; Connolly
et al., 2004; Lefkowitz & Gillen, 2006; Manning et al., 2006) and that in
recent years, partners are constantly in touch with each other via their devices
(Draucker & Martsolf, 2010; Subrahmanyam & Greenfield, 2008; Toscano,
2007), more opportunities for digital dating abuse can arise (Breiding et al.,
2014; Hickman et al., 2004; Ybarra et al., 2016). A handful of studies in the
United States over the last decade illuminate the prevalence of this phenom-
enon among youth. One benchmark study of 3,745 7th to 12th graders across
three states in a current or recent dating relationship found that 26.3% had
experienced some type of “cyber dating abuse victimization” in the prior
year, while 11.8% reported perpetration (Zweig, Dank, Yahner, & Lachman,
2013). This can be compared to an examination of over 4,200 9th graders
from 11 states, where 56% revealed they were victimized and 29% were
aggressors (Cutbush et al., 2010), a smaller study of high schoolers from
Texas, where 22.3% had experienced victimization and 17.7% were perpetra-
tors over the last year (Temple et al., 2016), and a study of almost 800 7th
graders from four schools, where 51% reported this type of victimization
while 32% revealed they had perpetrated the behavior (Cutbush et al., 2018).
To be sure, these numbers vary significantly. A recent critical review of digi-
tal dating abuse studies discovered a youth victimization incidence range
from 6% to 91% (Brown & Hegarty, 2018, p. 47) due to significant “vari-
ability in terminology use, construct definitions, the specific behaviors elic-
ited, and other issues related to instrument design.”
In terms of gender differences, a number of studies have identified that
girls experience digital dating abuse more so than boys (Dick et al., 2014;
Felmlee & Faris, 2016; Yahner et al., 2015; Zweig, Dank, Lachman, & Yahner,
2013; Zweig et al., 2014), although others have found mixed differences
(Wright, 2015) or even the opposite (Cutbush et al., 2018). With regard to
offending, some studies have found that girls are more likely to be aggressors
(Cutbush et al., 2010), while others have found no difference (Peskin et al.,
4 Journal of Interpersonal Violence 00(0)
2017) or have found that it depends on the type of digital dating abuse perpe-
trated (with boys engaging in more threatening, pressuring, and sexual forms,
and girls using more monitoring and possessive forms) (Reed et al., 2016,
2017; Zweig, Dank, Yahner, & Lachman, 2013).
Research has linked digital dating abuse to a number of emotional and
psychological struggles including depressive symptomatology, anxiety, anger
(Reed et al., 2015, 2016; Zweig, Dank, Yahner, & Lachman, 2013), and sui-
cidality (Van Ouytsel et al., 2017). It also seems to occur in a constellation of
other social and relational problem behaviors including teen dating violence
(Bennett & Guran, 2011; Temple et al., 2016; Yahner et al., 2015), stalking
(Cutbush et al., 2010), bullying and cyberbullying (Van Ouytsel et al., 2017;
Yahner et al., 2015), risky sexual activity (Dick et al., 2014; Van Ouytsel
et al., 2016), and sexual assault (Bonomi & Kelleher, 2007; Olshen et al.,
2007). Finally, digital dating abuse has been associated with other online risk
behaviors (Van Ouytsel et al., 2016), general forms of delinquency (Zweig
et al., 2014), and certain adverse childhood experiences (Smith-Darden et al.,
2017). All of this highlights the significant impact of this form of victimiza-
tion on the lives and trajectories of adolescents today.
Additionally, research on traditional teen dating violence has identified an
overlap where students report experience with both victimization and perpe-
tration (Jennings et al., 2011; Langhinrichsen-Rohling, 2010; Straus, 2011);
a finding duplicated in other digital dating abuse research (Duerksen &
Woodin, 2019; Reed et al., 2016; Stonard, 2018; Zweig, Dank, Yahner, &
Lachman, 2013). More research is necessary to corroborate this and to deter-
mine the direction of causality, but it potentially mirrors what has been found
in the cyberbullying literature with targets and aggressors often being one
and the same (Kowalski & Limber, 2007; Mishna et al., 2012).
The current work seeks to clarify the extent to which youth are experienc-
ing digital forms of dating abuse, as well as to identify salient correlates
related to those experiences. No previous study to our knowledge has exam-
ined these behaviors with a large, nationally representative sample of stu-
dents in the United States. As such, we hope to share findings that are more
generalizable to youth across the nation so that educators, counselors, and
health professionals are equipped to prioritize the most relevant covariates in
their prevention and response efforts.
Data for this study came from a questionnaire administered to a national sam-
ple of English-speaking 12- to 17-year-old middle and high school students
Hinduja and Patchin 5
residing in the United States. Distributed via email in the fall of 2016, it
examined the perceptions of, and experiences with, bullying, cyberbullying,
and related adolescent behaviors, including teen dating violence. The utiliza-
tion of electronic surveys has become a popular, cost-effective method for
obtaining large diverse samples (Lenhart et al., 2015; Schauer et al., 2016;
Strickland & Stoops, 2019; Ybarra & Mitchell, 2014). Active parental con-
sent and child assent was obtained for all participants. Nested age, sex, and
region quotas were used to ensure a diverse sample of respondents that was
representative of students across America. The total sample size was 5,539,
and the participation rate for this survey was approximately 15%. The project
methodology was approved by the institutional review board of a university
of one of the authors.
Dating abuse. Two measures of dating abuse were utilized in this study. Digital
dating abuse represents responses to five questions assessing experience with
abusive behaviors carried out via technology during the last year (Table 1). For
example, 21.5% of respondents said their significant other had looked through
Table 1. Experience With Digital Dating Abuse (In the Last Year) (n = 2,218).
Form of Victimization M SD %
Digital dating abuse victimization (Cronbach’s α = .854) 0.28 0.45
He or she looked through the contents of your phone,
tablet, or other device without permission
He or she prevented you from using your cell phone,
tablet, or other device
He or she threatened you in a cell phone text message 9.5
He or she posted something publicly online to make fun
of, threaten, or embarrass you
He or she posted online, or shared with others, a private
picture of you without permission
One or more of the above 28.1
Traditional dating abuse victimization (Cronbach’s α = .840) 0.36 0.48
He or she tried to keep you from doing something you
wanted to do
He or she called you names or criticized you 22.7
He or she pushed, grabbed, or shoved you 10.1
He or she threatened to hit or throw something at you 9.8
He or she slapped, hit, or punched you 9.0
One or more of the above 35.9
6 Journal of Interpersonal Violence 00(0)
Table 2. Relationship Between Traditional and Digital Forms of Dating Abuse.
Digital Dating Abuse Victimization
No Yes Total
Traditional dating abuse
No n = 1,301 n = 120 n = 1,421
58.7% 5.4% 64.1%
Yes n = 294 n = 503 n = 797
13.3% 22.7% 35.9%
Total n = 1,595 n = 623 n = 2,218
71.9% 28.1% 100.0%
Note. χ2 = 755.5(1); Cramer’s V = .584; p < .001.
the contents of their phone, tablet, or other device without permission, while
8.7% said their romantic partner posted online, or shared with others, a private
picture of them without permission. Responses to these questions in the origi-
nal survey were “never,” “once,” “a few times,” or “many times” but were re-
coded and combined to represent those who had experienced any of the
behaviors or not (Cronbach’s alpha = .854).
Similarly, traditional dating abuse also represented five questions
assessing experience with abusive offline behaviors during the last year.
For example, 26.8% of respondents said their partner tried to keep them
from doing something they wanted to do, while 9% had been slapped, hit,
or punched. The response choices were the same for traditional dating
abuse and were also combined and dichotomized for the purpose of analy-
sis (Cronbach’s α = .840).
Covariates. We included several demographic variables, such as age, gen-
der, sexual orientation, and race in our analyses to control for their potential
influence (Table 2). Age was included as a continuous variable representing
the respondent’s age in years (range 12–17; M = 14.9). Gender represents
the student’s self-reported gender identity (male, female, transgender [male
living as female], and transgender [female living as male]). Due to small
numbers (n=20), transgender students were removed from the analysis and
the resulting gender variable was dichotomous (1 = male and 0 = female),
resulting in a sample evenly divided across gender (49.9% female, 49.7%
male). Sexual orientation was determined by asking participants to self-
report their sexual orientation. The clear majority of the sample said that
they were heterosexual (92.8%), while 0.7% said they were lesbian, 0.5%
said they were gay, 2.8% said they were bisexual, 2.3% said they were
Hinduja and Patchin 7
questioning, and the remaining 0.9% selected “other” as a response choice.
These responses were dichotomized where 1 = heterosexual and 2 = non-
heterosexual. Race was a categorical variable where 1 = White, 2 = Afri-
can American, 3 = Hispanic, and 4 = Other. Comparable to the population
of middle and high school students in the United States (Office of Adoles-
cent Health, 2016), 69% of the sample was White/Caucasian, 11% was
Black/African American, 11% was Hispanic/Latin American, and 9% was
Next, we explored a series of other variables that could be related to expe-
rience with digital abuse. Depressive symptoms was a dichotomous single-
item variable where students who responded yes to the following question
were coded as 1: “In the past year, did you feel so sad or hopeless almost
every day for two weeks or more in a row that you stopped doing some of
your usual activities?” Those who responded no were coded as 0. Perhaps
digital dating abuse leads to depressive symptoms or those who are exhibit-
ing depressive behaviors make better targets of digital abuse, given the rela-
tionship between (offline) teen dating violence and depression (Banyard &
Cross, 2008; Exner-Cortens et al., 2013; Holt & Espelage, 2005). Had sexual
intercourse was a dichotomous single-item variable where students who
reported that they had had sex in the previous year were coded 1 (if not, they
were coded 0). Having sex with someone establishes a connection with them
that could be subject to manipulation or abuse (Demissie et al., 2018; Hird &
Jackson, 2001; Jackson et al., 2000). Sent a sext was a two-item measure
which asked respondents to report if they had ever sent (a) a boyfriend or
girlfriend, or (b) someone who was not a current boyfriend or girlfriend a
sext. Respondents were informed that “Sexting is when someone takes a
naked or semi-naked (explicit) picture or video of themselves, usually using
their phone, and sends it to someone else. The image or video is called a
‘sext’.” Students who reported that they had ever sent a sext to anyone were
coded 1, while the others were coded 0. Here again, if a student sends a sext
to another person, the recipient could have control over the sender, since the
sender might fear that the images be distributed to others or that authorities
might be told (Choi et al., 2016; Henry & Powell, 2018; Stanley et al., 2018).
Finally, victim of cyberbullying represented students who had been cyberbul-
lied more than once in their lifetime. Cyberbullying was defined as “when
someone repeatedly threatens, harasses, mistreats, or makes fun of another
person (on purpose to hurt them) online or while using cell phones or other
electronic devices.” Those who had been cyberbullied were coded 1, while
the others were coded 0. As dating violence sometimes has been conceptual-
ized as a form of bullying (Corvo & deLara, 2010; Linder et al., 2002), digital
dating abuse may be considered another form of cyberbullying.
8 Journal of Interpersonal Violence 00(0)
Among the 5,539 total respondents of our national sample, 40% reported that
they had been in a romantic relationship at some point in the previous year.
As we are interested in experiences with digital dating abuse within the last
12 months, we excluded the 60% who had not been in a relationship during
that time, leaving us with a final sample size of 2,218. As a result, the sample
includes more older students (those who are more likely to have been in a
We began by calculating prevalence rates for experience with digital dat-
ing abuse, for the total sample, and then different demographic groups. We
utilized t-tests to determine if there were any statistically significant differ-
ences across gender, sexual orientation, race, and age with respect to experi-
ence with digital dating abuse (reference groups noted in the table). Next, a 2
× 2 cross-tabulation table was utilized to assess the relationship between
digital dating abuse and traditional dating abuse (using chi-square and
Cramer’s V). We then computed a series of logistic regression models, testing
the unique influence of each of the covariates of interest while controlling for
age, gender, sexual orientation, and race. Quantitative statistical analyses
were performed using SPSS 18, and p value < .05 was considered statisti-
cally significant (two-tailed).
As displayed in Table 1, 28.1% of teens who had been in a romantic relation-
ship at some point in the previous year said they had been the victim of at
least one form of digital dating abuse. In addition, 35.9% had been the victim
at least one form of traditional (offline) dating abuse. Table 2 depicts a sig-
nificant connection between digital and traditional forms of dating abuse: the
vast majority of students who had been abused online had also been abused
offline. Specifically, 81% of the students who had been the target of digital
dating abuse had also been the target of traditional dating abuse (503 of 623).
Similarly, most of the students who had been the victim of offline dating
violence also had been the victim of online dating violence, though the per-
centage (63%) was lower (503 out of 797).
Next, we examined the demographic factors related to experience with
digital dating abuse. Males were significantly more likely to have experienced
digital dating abuse (32.3%) compared to females (23.6%) (see Table 3). No
other differences emerged with respect to demographic characteristics (sexual
orientation, race, and age).
Finally, we explored the relationship between several covariates and expe-
rience with digital dating abuse. As a reminder, each of the covariates was
Hinduja and Patchin 9
entered into separate models while controlling for demographic controls
(age, gender, sexual orientation, and race). For comparison purposes, we first
estimated a base model to calculate the amount of variance explained by only
the demographic controls. Given that gender was the only factor significantly
related to digital dating abuse, it is not surprising that the amount of variance
explained by the control variables was less than 2%. Moreover, as expected,
experience with traditional (offline) dating abuse was strongly associated
with experience with digital dating abuse. Specifically, students who had
been victimized offline were approximately 18 times more likely to have also
experienced online abuse compared to those who were not victimized offline.
In fact, this one measure explained close to half of the variance in experience
with digital dating abuse (R2 =.42) (see Table 4).
All of the other covariates explored were also significantly related to
digital dating abuse. Students who reported depressive symptoms were
about four times as likely to have experienced digital dating abuse. In
addition, students who said they had engaged in sex (Exp[B] = 2.53) or
who had sent a sext (Exp[B] = 4.81) were significantly more likely to
have been targeted for digital dating abuse. Finally, those who had been
the target of cyberbullying were also likely to have been the target of digi-
tal dating abuse (Exp[B] = 3.33).
Table 3. Experience With Digital Dating Violence by Gender, Sexual Orientation,
Race, and Age.
Variable Sample Size (%) % Victim of Digital Dating Abuse
Total 2,218 28.1
Male 1,144 (51.9) 32.3***
Female 1,059 (48.1) 23.6
Heterosexual 1,986 (89.5) 27.8
Nonheterosexual 232 (10.5) 30.6
Whitea1,530 (69.0) 28.0
African American 251 (11.3) 28.7
Hispanic 236 (10.6) 28.0
Other 201 (9.1) 27.9
12 181 (8.2) 21.6
13 339 (15.3) 25.7
14a315 (14.2) 26.0
15 448 (20.2) 32.1
16 477 (21.5) 30.2
17 458 (20.6) 27.7
aRepresents reference group.
***p < .001, t-test.
10 Journal of Interpersonal Violence 00(0)
Table 4. Logistic Regression Examining Correlates of Digital Dating Abuse.
Victim of Digital Dating Abuse
B (SE) Exp(B) 95% CI
Victim of offline dating
35.9 2.89 (.121) 17.96*** [14.17, 22.76] .421
Depressive symptoms 21.3 1.36 (.157) 3.88*** [2.86, 5.27] .112
Had sexual intercourse 24.2 0.93 (.112) 2.53*** [2.03, 3.15] .061
Sent a sext 25.1 1.57 (.107) 4.81*** [3.91, 5.94] .154
Victim of cyberbullying 27.5 1.20 (.107) 3.33*** [2.70, 4.11] .099
Note. CI = confidence interval.
aAll analyses include individual indicator (bivariate) while controlling for age, gender, sexual
orientation, and race.
***p < .001.
Digital dating abuse is a pattern of technology-facilitated, controlling behav-
iors, exhibited by one person toward another within a current or former
romantic relationship. Research on this phenomenon is still incipient, and
this study adds some details to the nascent knowledgebase based on a large,
nationally representative sample of youth. It is clear that a nonnegligible
number of middle and high school students have experienced digital dating
abuse; specifically, about one-third of boys and about one-quarter of girls
have been victimized.
Within the context of a gendered and heteronormative developmental per-
spective of teen dating violence, and understanding that boys and girls have
grown up learning certain problem-solving tactics in their sex-segregated
friendships (Rose & Rudolph, 2006), it has been argued that youth of a cer-
tain sex may use behaviors more typical of the opposite sex when dealing
with conflict in relationships (Wincentak et al., 2017). Specifically, girls may
use more violence on their boyfriends to try to solve their relational prob-
lems, while boys may try to constrain their aggressive impulses when trying
to negotiate discord with their girlfriends (McIsaac et al., 2008; Shute &
Charlton, 2006). In an effort to better understand this, we examined the indi-
vidual indicators used in our composite measure of digital dating abuse vic-
timization, hypothesizing that one specific form might be unduly influencing
the overall results. Boys were significantly more likely to experience all
types of digital dating abuse—including physical aggression (aligning with
Hinduja and Patchin 11
previous teen dating violence research uncovering the acceptability of girls to
hit their boyfriends; Simon et al., 2010).
Moreover, we found significant overlap between digital dating abuse and
its traditional counterpart (paralleling findings from other studies involving
local convenience samples of students; Duerksen & Woodin, 2019; Stonard,
2018). It is impossible in these cross-sectional studies to determine which
came first, but the correlation is consistent with what has been observed in
other forms of online and offline harm (e.g., bullying; Hinduja & Patchin,
2015; Kowalski et al., 2012; Waasdorp & Bradshaw, 2015) and self-harm
(Patchin & Hinduja, 2017). Indeed, the correlation was so substantial that
we examined their connection using exploratory factor analysis (principal
component) and found that all 10 variables from Table 1 loaded into a single
factor (Eigenvalue = 6.26; minimum individual component = 0.704).
Considering the two forms of dating abuse (traditional and digital) as dis-
tinct entities actually may be inappropriate, but further research is necessary
to know with more certainty.
Finally, we uncovered a number of risk factors significantly associated
with digital dating abuse. Those who reported that they had sexual inter-
course were 2.5 times as likely to have experienced digital dating abuse.
Perhaps dating abuse is more likely when a relationship progresses to the
point where the couple has engaged in sex, or if intercourse occurs early in
the relationship it creates an unhealthy power dynamic where one can take
advantage of the other due to fear or embarrassment of that information being
disclosed (Choi et al., 2016; Demissie et al., 2018; Hird & Jackson, 2001;
Jackson et al., 2000). Most notably, those students who had sent a sext to
another person were nearly five times as likely to be the target of digital dat-
ing abuse as compared to those who had not sent a sext. It may be that send-
ing explicit images to others opens one up for extortion, manipulation, or
coercion (e.g., sextortion; Patchin & Hinduja, 2020). Threats of distribution
to a third party might force a partner to endure abuse or to resist reporting
such abuse to the authorities (for fear of being prosecuted themselves for
violating child pornography laws; Crofts et al., 2015; Mabrey & Perozzi,
2010; Nelson, 2018; Podlas, 2011).
Results from this study came from a national sample of 12- to 17-year-old
students, and while many efforts were taken to ensure the sample was diverse
and representative (e.g., sampling quotas by sex, age, race, and region of the
country), it is impossible to know whether results here are truly generaliz-
able. This is particularly true given the online nature of the sampling frame
and the relatively low response rate. While lower than other methods of data
collection and not ideal (Baruch & Holtom, 2008; Kaplowitz et al., 2004), it
is still satisfactory for a preliminary inquiry to an understudied problem
12 Journal of Interpersonal Violence 00(0)
(Fricker & Schonlau, 2002; Manfreda et al., 2008). We mentioned earlier that
prevalence rates of digital dating abuse across the literature base vary widely
because of sampling and measurement differences. As a nascent but increas-
ingly important topic of empirical scrutiny, a crucial step for future inquiry
should be the development of a universal definition and measurement tool
that can produce standardized observations (we offer our own as an option).
It should be mentioned that this study was unable to ascertain the temporal
ordering of key variables in a way that would have allowed predictions to be
made regarding causality. While it is plausible that having sex with someone—
or sending that person a sexually explicit image—lends itself to a power
dynamic conducive to abuse, it is also possible that one could utilize abusive
tactics to wear a person down enough to comply with a request for sex or
explicit images. Similarly, exhibiting depressive symptoms might make a per-
son a good target for abuse, while also being also its consequence. In short, a
longitudinal exploration of these relationships is certainly warranted.
Finally, the standard caveats concerning self-report surveys must also be
offered here (Brenner & DeLamater, 2014; Hindelang et al., 1981; Phillips &
Clancy, 1972). We inquire about sensitive and deviant behaviors and there-
fore need to be mindful about potential underreporting. We attempted to
minimize this by using an anonymous reporting mechanism and reminding
respondents that their responses would be kept confidential to the maximum
extent allowable by law. It is also true that retrospective surveys that inquire
about past behavior could be inaccurate due to historical mistakes (Jenkins
et al., 2002). We asked about experiences within the last year in an effort to
account for this problem.
It is clear that digital dating abuse affects a meaningful proportion of teen-
agers. As this problem continues to be studied, we hope to learn much more
about context, contributing factors, and consequences. Research is slowly
uncovering a number of individual- and familial-level factors that are corre-
lated with being either an abuser or victim of digital dating abuse; focusing
on these can help inform general programmatic strategies implemented
within schools and communities (Peskin et al., 2017; Van Ouytsel et al.,
2017). In this way, youth-serving adults can be mindful of who might be most
susceptible to this phenomenon and can concentrate their efforts on those
teenagers. In addition, recent research by Walters and Espelage (2018) found
that reducing dating violence offending among boys is more likely if attempts
are made to address prior dating violence victimization as well as depression,
while reducing the same among girls can occur if adults work to address prior
delinquency and bullying perpetration. We must be aware that relational
aggression in the form of dating violence seems to occur within a collection
of other associated behaviors, and that there exist root issues that contribute
Hinduja and Patchin 13
to any manifestation of “acting out” (Ellis et al., 2009; Linder et al., 2002;
Werner & Crick, 2004).
There also appears to be a general lack of knowledge associated with what
exactly can be done about digital dating abuse apart from more conversations
with youth about healthy romantic relationships and the positive use of social
media and general internet safety practices (Miller et al., 2018; Peskin et al.,
2017; Stonard et al., 2017; Van Ouytsel et al., 2016). Research to date has
identified that educational and informational efforts can change cognitive
beliefs around the acceptability of dating violence, but specific implementa-
tions have not borne much fruit in reducing offending or victimization (De La
Rue et al., 2017). It is one thing to affect attitudes and beliefs, but if those
attitudes and beliefs do not translate to behavioral changes among youth, we
must more fully explore them and resolve the disconnect.
In addition, there are laws that enable police to step in and address domes-
tic and dating violence in practically every jurisdiction, and a growing num-
ber specific to threats, stalking, sextortion, and revenge porn (DeMatteo
et al., 2017; Hinduja & Patchin, 2015; National Center for Victims of Crime,
2012; Patchin & Hinduja, 2020; Wittes et al., 2016). Law enforcement and
other responding entities need, however, to be perceived as capable, compas-
sionate entities who can deal with the problem in a way that does not make it
worse for the victim—especially when considering the relative vulnerability
of youthful targets. Research has consistently identified a reluctance on the
part of domestic and sexual violence victims to contact authorities (Campbell,
2005; Orth, 2002; Wemmers, 2013), and this is disappointing because it
denies the opportunity to receive help when and where it is most needed. A
deeper understanding of the emotional and psychological mind-set—and the
situational circumstances—of current-day adolescents may markedly inform
the policy and practice we need to develop to address digital dating abuse.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: The data utilized in this study were col-
lected through a grant from the Digital Trust Foundation (#31-3).
Sameer Hinduja https://orcid.org/0000-0001-5300-5006
14 Journal of Interpersonal Violence 00(0)
Ahola Kohut, S., LeBlanc, C., O’leary, K., McPherson, A., McCarthy, E., Nguyen, C., &
Stinson, J. (2018). The internet as a source of support for youth with chronic condi-
tions: A qualitative study. Child: Care, Health and Development, 44(2), 212–220.
Baker, C. K., & Carreño, P. K. (2016). Understanding the role of technology in ado-
lescent dating and dating violence. Journal of Child and Family Studies, 25(1),
Banyard, V. L., & Cross, C. (2008). Consequences of teen dating violence:
Understanding intervening variables in ecological context. Violence Against
Women, 14(9), 998–1013.
Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in orga-
nizational research. Human Relations, 61(8), 1139–1160.
Bennett, D. C., & Guran, E. L. (2011). College students’ electronic victimization in
friendships and dating relationships: Anticipated distress and associations with
risky behaviors. Violence and Victims, 26(4), 410–429.
Bers, M. U. (2010). Beyond computer literacy: Supporting youth’s positive develop-
ment through technology. New Directions for Youth Development, 2010(128),
Blank, G., & Lutz, C. (2018). Benefits and harms from internet use: A differentiated
analysis of Great Britain. New Media & Society, 20(2), 618–640.
Bonomi, A. E., & Kelleher, K. (2007). Dating violence, sexual assault, and suicide
attempts among minority adolescents: Ending the silence. Archives of Pediatrics
& Adolescent Medicine, 161(6), 609–610.
Borrajo, E., Gámez-Guadix, M., Pereda, N., & Calvete, E. (2015). The development
and validation of the cyber dating abuse questionnaire among young couples.
Computers in Human Behavior, 48, 358–365.
Breiding, M. J., Chen, J., & Black, M. C. (2014). Intimate partner violence in the
United States—2010. https://www.cdc.gov/violenceprevention/pdf/cdc_nisvs_
Brenner, P. S., & DeLamater, J. D. (2014). Social desirability bias in self-reports of
physical activity: Is an exercise identity the culprit? Social Indicators Research,
Brown, C., & Hegarty, K. (2018). Digital dating abuse measures: A critical review.
Aggression and Violent Behavior, 40, 44–59.
Campbell, R. (2005). Survivors’ help-seeking experiences with the legal and medical
systems. Violence and Victims, 20(1), 55–68.
Carlson, W., & Rose, A. J. (2012). Brief report: Activities in heterosexual romantic
relationships: Grade differences and associations with relationship satisfaction.
Journal of Adolescence, 35(1), 219–224.
Centers for Disease Control and Prevention. (2017). Teen dating violence fact sheet.
Centers for Disease Control and Prevention. (2018). Youth risk behavior survey: Data
summary and trends report, 2007-2017. https://www.cdc.gov/healthyyouth/data/
Hinduja and Patchin 15
Choi, H., Van Ouytsel, J., & Temple, J. R. (2016). Association between sexting and
sexual coercion among female adolescents. Journal of Adolescence, 53, 164–168.
Citron, D. K., & Franks, M. A. (2014). Criminalizing revenge porn. Wake Forest Law
Review, 49(U of Maryland Legal Studies Research Paper No. 2014-1). https://
Connolly, J., Craig, W., Goldberg, A., & Pepler, D. (2004). Mixed-gender groups,
dating, and romantic relationships in early adolescence. Journal of Research on
Adolescence, 14(2), 185–207.
Corvo, K., & deLara, E. (2010). Towards an integrated theory of relational violence:
Is bullying a risk factor for domestic violence? Aggression and Violent Behavior,
Crofts, T., Lee, M., McGovern, A., & Milivojevic, S. (2015). Sexting as child pornog-
raphy. In Sexting and young people (pp. 43–55). Springer.
Cutbush, S., Ashley, O., Kan, M., Hampton, J., & Hall, D. (2010). Electronic aggres-
sion among adolescent dating partners: Demographic correlates and associa-
tions with other types of violence [Paper presentation]. The Poster presented at the
American Public Health Association, Annual Meeting. https://www.researchgate
Cutbush, S., Williams, J., Miller, S., Gibbs, D., & Clinton-Sherrod, M. (2018).
Longitudinal patterns of electronic teen dating violence among middle school
students. Journal of Interpersonal Violence. Advance online publication. https://
Dank, M., Lachman, P., Zweig, J. M., & Yahner, J. (2014). Dating violence expe-
riences of lesbian, gay, bisexual, and transgender youth. Journal of Youth and
Adolescence, 43(5), 846–857.
D’Costa, K. (2014). Catfishing: The truth about deception online. Anthropology in
De La Rue, L., Polanin, J. R., Espelage, D. L., & Pigott, T. D. (2017). A meta-analysis
of school-based interventions aimed to prevent or reduce violence in teen dating
relationships. Review of Educational Research, 87(1), 7–34.
DeMatteo, D., Wagage, S., & Fairfax-Columbo, J. (2017). Cyberstalking: Are we on
the same (web) page? A comparison of statutes, case law, and public perception.
Journal of Aggression, Conflict and Peace Research, 9(2), 83–94.
Demissie, Z., Clayton, H. B., Vivolo-Kantor, A. M., & Estefan, L. F. (2018). Sexual
teen dating violence victimization: Associations with sexual risk behaviors
among US high school students. Violence and Victims, 33(5), 964–980.
Dick, R. N., McCauley, H. L., Jones, K. A., Tancredi, D. J., Goldstein, S., Blackburn,
S., . . . Miller, E. (2014). Cyber dating abuse among teens using school-based
health centers. Pediatrics, 134, e1560–e1567.
Draucker, C. B., & Martsolf, D. S. (2010). The role of electronic communication
technology in adolescent dating violence. Journal of Child and Adolescent
Psychiatric Nursing, 23(3), 133–142.
16 Journal of Interpersonal Violence 00(0)
Duerksen, K. N., & Woodin, E. M. (2019). Technological intimate partner violence:
Exploring technology-related perpetration factors and overlap with in-person
intimate partner violence. Computers in Human Behavior, 98, 223–231.
Ellis, W. E., Crooks, C. V., & Wolfe, D. A. (2009). Relational aggression in peer and
dating relationships: Links to psychological and behavioral adjustment. Social
Development, 18(2), 253–269.
Englander, E. K., & McCoy, M. (2017). Pressured sexting and revenge porn in a
sample of Massachusetts adolescents. International Journal of Technoethics,
Exner-Cortens, D., Eckenrode, J., & Rothman, E. (2013). Longitudinal associa-
tions between teen dating violence victimization and adverse health outcomes.
Pediatrics, 131(1), 71–78.
Felmlee, D., & Faris, R. (2016). Toxic ties: Networks of friendship, dating, and cyber
victimization. Social Psychology Quarterly, 79(3), 243–262.
Fricker, R. D., & Schonlau, M. (2002). Advantages and disadvantages of internet
research surveys: Evidence from the literature. Field Methods, 14(4), 347–367.
Henry, N., & Powell, A. (2018). Technology-facilitated sexual violence: A literature
review of empirical research. Trauma, Violence, & Abuse, 19(2), 195–208.
Hickman, L. J., Jaycox, L. H., & Aronoff, J. (2004). Dating violence among ado-
lescents: Prevalence, gender distribution, and prevention program effectiveness.
Trauma, Violence, & Abuse, 5(2), 123–142.
Hindelang, M. J., Hirschi, T., & Weis, J. G. (1981). Measuring delinquency.
Hinduja, S., & Patchin, J. W. (2009). Bullying Beyond the Schoolyard: Preventing
and Responding to Cyberbullying. Sage.
Hinduja, S., & Patchin, J. W. (2012). School climate 2.0: Preventing cyberbullying
and sexting one classroom at a time. Corwin Press.
Hinduja, S., & Patchin, J. W. (2015). Bullying beyond the schoolyard: Preventing and
responding to cyberbullying (2nd ed.). Sage.
Hird, M. J., & Jackson, S. (2001). Where “angels” and “wusses” fear to tread: Sexual
coercion in adolescent dating relationships. Journal of Sociology, 37(1), 27–43.
Holt, M. K., & Espelage, D. L. (2005). Social support as a moderator between dat-
ing violence victimization and depression/anxiety among African American and
Caucasian adolescents. School Psychology Review, 34(3), 309–328.
Jackson, S. M., Cram, F., & Seymour, F. W. (2000). Violence and sexual coercion
in high school students’ dating relationships. Journal of Family Violence, 15(1),
Jenkins, P., Earle-Richardson, G., Slingerland, D. T., & May, J. (2002). Time depen-
dent memory decay. American Journal of Industrial Medicine, 41(2), 98–101.
Jennings, W. G., Park, M., Tomsich, E. A., Gover, A. R., & Akers, R. L. (2011).
Assessing the overlap in dating violence perpetration and victimization among
South Korean college students: The influence of social learning and self-control.
American Journal of Criminal Justice, 36(2), 188–206.
Kaplowitz, M. D., Hadlock, T. D., & Levine, R. (2004). A comparison of web and
mail survey response rates. Public Opinion Quarterly, 68(1), 94–101.
Hinduja and Patchin 17
Korchmaros, J. D., Ybarra, M. L., Langhinrichsen-Rohling, J., Boyd, D., &
Lenhart, A. (2013). Perpetration of teen dating violence in a networked society.
Cyberpsychology, Behavior, and Social Networking, 16(8), 561–567.
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014).
Bullying in the digital age: A critical review and meta-analysis of cyberbullying
research among youth. Psychological Bulletin, 140(4), 1073.
Kowalski, R. M., & Limber, S. P. (2007). Electronic bullying among middle school
students. Journal of Adolescent Health, 41, S22–S30.
Kowalski, R. M., Morgan, C. A., & Limber, S. P. (2012). Traditional bullying as a poten-
tial warning sign of cyberbullying. School Psychology International, 33(5), 505–519.
Langhinrichsen-Rohling, J. (2010). Controversies involving gender and intimate part-
ner violence in the United States. Sex Roles, 62(3–4), 179–193.
Lavoie, F., Robitaille, L., & Hébert, M. (2000). Teen dating relationships and aggres-
sion: An exploratory study. Violence Against Women, 6(1), 6–36.
Lefkowitz, E. S., & Gillen, M. M. (2006). “Sex is just a normal part of life”: Sexuality
in emerging adulthood. In J. J. Arnett & J. L. Tanner (Eds.), Emerging adults in
America: Coming of age in the 21st century. American Psychological Association.
Leisring, P. A., & Giumetti, G. W. (2014). Sticks and stones may break my bones,
but abusive text messages also hurt: Development and validation of the Cyber
Psychological Abuse scale. Partner Abuse, 5(3), 323–341.
Lenhart, A., Smith, A., & Anderson, M. (2015). Teens, technology and romantic rela-
tionships. Pew Research Center.
Levy, B. (1991). Dating violence: Young women in danger. Seal Press Seattle.
Linder, J. R., Crick, N. R., & Collins, W. A. (2002). Relational aggression and victim-
ization in young adults’ romantic relationships: Associations with perceptions of
parent, peer, and romantic relationship quality. Social Development, 11(1), 69–86.
Lucero, J. L., Weisz, A. N., Smith-Darden, J., & Lucero, S. M. (2014). Exploring gen-
der differences: Socially interactive technology use/abuse among dating teens.
Affilia, 29(4), 478–491.
Lytle, M. C., Silenzio, V. M., Homan, C. M., Schneider, P., & Caine, E. D. (2018).
Suicidal and help-seeking behaviors among youth in an online lesbian, gay,
bisexual, transgender, queer, and questioning social network. Journal of
Homosexuality, 65(13), 1916–1933.
Mabrey, V., & Perozzi, D. (2010, April 1). “Sexting”: Should child pornography laws
apply? ABCnews. https://abcnews.go.com/Nightline/phillip-alpert-sexting-teen-
Manfreda, K. L., Bosnjak, M., Berzelak, J., Haas, I., Vehovar, V., & Berzelak, N.
(2008). Web surveys versus other survey modes: A meta-analysis comparing
response rates. International Journal of Market Research, 50(1), 79–104.
Manning, W. D., Giordano, P. C., & Longmore, M. A. (2006). Hooking up: The
relationship contexts of “nonrelationship” sex. Journal of Adolescent Research,
McIsaac, C., Connolly, J., McKenney, K. S., Pepler, D., & Craig, W. (2008). Conflict
negotiation and autonomy processes in adolescent romantic relationships: An
18 Journal of Interpersonal Violence 00(0)
observational study of interdependency in boyfriend and girlfriend effects.
Journal of Adolescence, 31(6), 691–707.
Melander, L. A. (2010). College students’ perceptions of intimate partner cyber
harassment. Cyberpsychology, Behavior, and Social Networking, 13(3), 263–268.
Metzger, M. J., Wilson, C., & Zhao, B. Y. (2018). Benefits of browsing? The preva-
lence, nature, and effects of profile consumption behavior in social network sites.
Journal of Computer-Mediated Communication, 23(2), 72–89.
Miller, E., Jones, K. A., & McCauley, H. L. (2018). Updates on adolescent dating
and sexual violence prevention and intervention. Current Opinion in Pediatrics,
Mishna, F., Khoury-Kassabri, M., Gadalla, T., & Daciuk, J. (2012). Risk factors for
involvement in cyber bullying: Victims, bullies and bully–victims. Children and
Youth Services Review, 34(1), 63–70.
National Center for Victims of Crime. (2012). Stalking laws. Stalking Resource Center.
Nelson, T. (2018). Minnesota prosecutor charges sexting teenage girl with child
Office of Adolescent Health. (2016). Current population survey: Projected popula-
tion by single year of age, sex, race, and Hispanic origin for the United States:
2014 to 2060. https://www.hhs.gov/ash/oah/facts-and-stats/changing-face-of-
O’Keeffe, N. K., Brockopp, K., & Chew, E. (1986). Teen dating violence. Social
Work, 31(6), 465–468.
Olshen, E., McVeigh, K. H., Wunsch-Hitzig, R. A., & Rickert, V. I. (2007). Dating
violence, sexual assault, and suicide attempts among urban teenagers. Archives of
Pediatrics & Adolescent Medicine, 161(6), 539–545.
Orth, U. (2002). Secondary victimization of crime victims by criminal proceedings.
Social Justice Research, 15(4), 313–325.
Patchin, J. W., & Hinduja, S. (2017). Digital self-harm among adolescents. Journal of
Adolescent Health, 61(6), 761–766.
Patchin, J. W., & Hinduja, S. (2020). Sextortion among adolescents: Results from
a national survey of U.S. youth. Sexual Abuse: A Journal of Research and
Treatment, 32(1), 30–54.
Peskin, M. F., Markham, C. M., Shegog, R., Temple, J. R., Baumler, E. R., Addy, R. C.,
. . . Thiel, M. (2017). Prevalence and correlates of the perpetration of cyber dating
abuse among early adolescents. Journal of Youth and Adolescence, 46(2), 358–375.
Phillips, D. L., & Clancy, K. J. (1972). Some effects of “social desirability” in survey
studies. American Journal of Sociology, 77(5), 921–940.
Podlas, K. (2011). The legal epidemiology of the teen sexting epidemic: How the
media influenced legislative outbreak. Pittsburgh Journal of Technology Law
and Policy, 12, 1–48.
Randell, K. A., Bair-Merritt, M., Miller, M., Williams, D., Evans, S. E., Schnitzer, P.,
. . . Dowd, M. D. (2016). Cyber adolescent relationship abuse and reproductive
Hinduja and Patchin 19
coercion: Victimization and perpetration among adolescents utilizing a pediatric
emergency department. Journal of Adolescent Health, 58(2), S75–S76.
Reed, L. A., Tolman, R. M., & Safyer, P. (2015). Too close for comfort: Attachment
insecurity and electronic intrusion in college students’ dating relationships.
Computers in Human Behavior, 50, 431–438.
Reed, L. A., Tolman, R. M., & Ward, L. M. (2016). Snooping and sexting: Digital
media as a context for dating aggression and abuse among college students.
Violence Against Women, 22(13), 1556–1576.
Reed, L. A., Tolman, R. M., & Ward, L. M. (2017). Gender matters: Experiences and
consequences of digital dating abuse victimization in adolescent dating relation-
ships. Journal of Adolescence, 59, 79–89.
Rice, E., Rhoades, H., Winetrobe, H., Sanchez, M., Montoya, J., Plant, A., & Kordic,
T. (2012). Sexually explicit cell phone messaging associated with sexual risk
among adolescents. Pediatrics, 130(4), 667–673.
Rose, A. J., & Rudolph, K. D. (2006). A review of sex differences in peer relationship
processes: Potential trade-offs for the emotional and behavioral development of
girls and boys. Psychological Bulletin, 132(1), 98–131.
Schauer, G. L., King, B. A., Bunnell, R. E., Promoff, G., & McAfee, T. A. (2016).
Toking, vaping, and eating for health or fun: Marijuana use patterns in adults, US,
2014. American Journal of Preventive Medicine, 50(1), 1–8.
Shute, R., & Charlton, K. (2006). Anger or compromise? Adolescents’ conflict reso-
lution strategies in relation to gender and type of peer relationship. International
Journal of Adolescence and Youth, 13(1–2), 55–69.
Simon, T. R., Miller, S., Gorman-Smith, D., Orpinas, P., & Sullivan, T. (2010).
Physical dating violence norms and behavior among sixth-grade students from
four US sites. The Journal of Early Adolescence, 30(3), 395–409.
Smith-Darden, J. P., Kernsmith, P. D., Victor, B. G., & Lathrop, R. A. (2017).
Electronic displays of aggression in teen dating relationships: Does the social
ecology matter? Computers in Human Behavior, 67, 33–40.
Spencer, G. A., & Bryant, S. A. (2000). Dating violence: A comparison of rural, sub-
urban, and urban teens. Journal of Adolescent Health, 27(5), 302–305.
Spitzberg, B. H., & Hoobler, G. (2002). Cyberstalking and the technologies of inter-
personal terrorism. New Media & Society, 4(1), 71–92.
Stanley, N., Barter, C., Wood, M., Aghtaie, N., Larkins, C., Lanau, A., & Överlien, C.
(2018). Pornography, sexual coercion and abuse and sexting in young people’s
intimate relationships: A European study. Journal of Interpersonal Violence,
Stonard, K. E. (2018). The prevalence and overlap of technology-assisted and offline
adolescent dating violence. Current Psychology, 1–15. Advance online publica-
Stonard, K. E., Bowen, E., Walker, K., & Price, S. A. (2017). “They’ll always find
a way to get to you”: Technology use in adolescent romantic relationships and
its role in dating violence and abuse. Journal of Interpersonal Violence, 32(14),
20 Journal of Interpersonal Violence 00(0)
Straus, M. A. (2011). Gender symmetry and mutuality in perpetration of clinical-level
partner violence: Empirical evidence and implications for prevention and treat-
ment. Aggression and Violent Behavior, 16(4), 279–288.
Strickland, J. C., & Stoops, W. W. (2019). The use of crowdsourcing in addic-
tion science research: Amazon Mechanical Turk. Experimental and Clinical
Psychopharmacology, 27(1), 1–18.
Subrahmanyam, K., & Greenfield, P. (2008). Online communication and adolescent
relationships. The Future of Children, 18, 119–146.
Temple, J. R., Choi, H., Brem, M., Wolford-Clevenger, C., Stuart, G. L., Peskin,
M. L., & Elmquist, J. (2016). The temporal association between traditional and
cyber dating abuse among adolescents. Journal of Youth and Adolescence, 45(2),
Temple, J. R., Paul, J. A., van den Berg, P., Le, V. D., McElhany, A., & Temple,
B. W. (2012). Teen sexting and its association with sexual behaviors. Archives
of Pediatrics & Adolescent Medicine, 166(9), 828–833. https://doi.org/10.1001/
Toscano, S. E. (2007). A grounded theory of female adolescents’ dating experiences
and factors influencing safety: The dynamics of the Circle. BMC Nursing, 6(1),
Van Ouytsel, J., Ponnet, K., & Walrave, M. (2016). Cyber dating abuse victimiza-
tion among secondary school students from a lifestyle-routine activities theory
perspective. Journal of Interpersonal Violence, 33, 2767–2776.
Van Ouytsel, J., Torres, E., Choi, H. J., Ponnet, K., Walrave, M., & Temple, J. R.
(2017). The associations between substance use, sexual behaviors, bullying,
deviant behaviors, health, and cyber dating abuse perpetration. The Journal of
School Nursing, 33(2), 116–122.
Van Ouytsel, J., Walrave, M., Ponnet, K., & Temple, J. R. (2016). Digital forms of
dating violence: What school nurses need to know. NASN School Nurse, 31(6),
Waasdorp, T. E., & Bradshaw, C. P. (2015). The overlap between cyberbullying and
traditional bullying. Journal of Adolescent Health, 56(5), 483–488.
Walters, G. D., & Espelage, D. L. (2018). Prior bullying, delinquency, and victimiza-
tion as predictors of teen dating violence in high school students: Evidence of
moderation by sex. Victims & Offenders, 13, 859–875. https://doi.org/10.1080/
Wemmers, J.-A. (2013). Victims’ experiences in the criminal justice system and their
recovery from crime. International Review of Victimology, 19(3), 221–233.
Werner, N. E., Bumpus, M. F., & Rock, D. (2010). Involvement in internet aggression
during early adolescence. Journal of Youth and Adolescence, 39(6), 607–619.
Werner, N. E., & Crick, N. R. (2004). Maladaptive peer relationships and the devel-
opment of relational and physical aggression during middle childhood. Social
Development, 13(4), 495–514.
Wincentak, K., Connolly, J., & Card, N. (2017). Teen dating violence: A meta-analytic
review of prevalence rates. Psychology of Violence, 7(2), 224–241.
Hinduja and Patchin 21
Wittes, B., Poplin, C., Jurecic, Q., & Spera, C. (2016). Sextortion: Cybersecurity,
teenagers, and remote sexual assault. Brookings Institution.
Wolak, J., Finkelhor, D., Walsh, W. A., & Treitman, L. (2018). Sextortion of minors:
Characteristics and dynamics. Journal of Adolescent Health, 62(1), 72–79.
Wright, M. F. (2015). Cyber aggression within adolescents’ romantic relationships:
Linkages to parental and partner attachment. Journal of Youth and Adolescence,
Yahner, J., Dank, M., Zweig, J. M., & Lachman, P. (2015). The co-occurrence
of physical and cyber dating violence and bullying among teens. Journal of
Interpersonal Violence, 30(7), 1079–1089.
Ybarra, M. L., Espelage, D. L., Langhinrichsen-Rohling, J., & Korchmaros, J. D.
(2016). Lifetime prevalence rates and overlap of physical, psychological, and
sexual dating abuse perpetration and victimization in a national sample of youth.
Archives of Sexual Behavior, 45(5), 1083–1099.
Ybarra, M. L., & Mitchell, K. J. (2014). “Sexting” and its relation to sexual activ-
ity and sexual risk behavior in a national survey of adolescents. Journal of
Adolescent Health, 55(6), 757–764.
Zweig, J. M., Dank, M., Lachman, P., & Yahner, J. (2013). Technology, teen dating
violence and abuse, and bullying. Urban Institute.
Zweig, J. M., Dank, M., Yahner, J., & Lachman, P. (2013). The rate of cyber dating
abuse among teens and how it relates to other forms of teen dating violence.
Journal of Youth and Adolescence, 42(7), 1063–1077. https://doi.org/10.1007/
Zweig, J. M., Lachman, P., Yahner, J., & Dank, M. (2014). Correlates of cyber dating
abuse among teens. Journal of Youth and Adolescence, 43(8), 1306–1321.
Sameer Hinduja, PhD, is a professor of criminology and criminal justice at Florida
Atlantic University. He received his PhD in Criminal Justice from Michigan State
University. His research seeks to understand the causes and consequences of various
forms of online victimization and to identify best practices in prevention and response.
Justin W. Patchin, PhD, is a professor of criminal justice at the University of
Wisconsin-Eau Claire. He received his PhD in Criminal Justice from Michigan State
University. Since 2002, he has been exploring the intersection of teens and technol-
ogy, with particular focus on cyberbullying, social networking, and sexting.