Longitudinal Patterns of Electronic Teen Dating Violence Among Middle School Students

Abstract

We investigated rates and developmental trends of electronic teen dating violence (TDV) perpetration and victimization overall and by gender. Data were collected from a single cohort of seventh-grade students from four schools using paper-and-pencil surveys administered at 6-month intervals (N = 795). Data were analyzed with descriptive statistics and longitudinal growth models to estimate change over time in TDV. Overall, 32% of youth reported electronic TDV perpetration, and 51% reported electronic TDV victimization. Victimization was more prevalent for boys (42%) than for girls (31%) at baseline only (t = 2.55, p < .05). Perpetration did not differ at any wave. Perpetration and victimization each decreased significantly from the beginning of seventh grade to the end of eighth grade, β = −.129 (.058), p < .05, for perpetration, and β = −.138 (.048), p < .01, for victimization. Gender moderated the decrease in reported victimization, with simple slopes indicating girls showed almost no change in victimization, β = .006 (.066), ns, whereas boys decreased significantly over the 2 years, β = −.292 (.069), p < .001. Although moderation by gender of change in perpetration was not conventionally significant, the simple slopes revealed that girls again showed a nonsignificant change in TDV across seventh and eighth grades, β = −.067 (.078), ns, whereas boys showed a significant decline in reported electronic TDV perpetration, β = −.197 (.083), p < .05. The high prevalence of electronic TDV underscore the need for addressing these behaviors within TDV prevention interventions.

Keywords

teen dating violence electronic aggression cyberbullying adolescents middle school

Introduction

Teen dating violence (TDV) is a serious public health concern that is garnering increased attention from researchers, practitioners, and policy makers (Break the Cycle, 2009; Library of Congress, 2011). Despite the upsurge in TDV research in recent years, most empirical findings have focused on physical, psychological, or sexual TDV. Far fewer studies have investigated TDV that occurs electronically. The purpose of this study is to identify rates of electronic TDV perpetration and victimization among middle school students and to determine whether they differ by gender. Furthermore, this study will examine developmental trends of electronic TDV over time, including whether the developmental trends vary by gender.

Electronic TDV

Youth increasingly construct their identities, relationships, and social worlds through technology practices, including texting, instant messaging, creating and circulating online photos and videos, and interacting with social platforms (Baker & Carreo, 2016; Lenhart, 2014). According to Lenhart, 95% of teens use the Internet, and 78% have a cell phone. Teens report texting as their preferred communication choice, with 75% of teens texting, and a median of 60 texts per day among teens who text. Adolescents commonly use technology to initiate and dissolve dating relationships, often via text messages or posts to social media platforms (Baker & Carreo, 2016).

Although this proliferation of digital media allows for positive interpersonal communication and contact, it also creates a unique medium for harmful and abusive behaviors (Baker & Carreo, 2016). The Centers for Disease Control and Prevention defines electronic aggression as any kind of harassment or bullying that occurs through technology or electronic media, including texting, instant messaging or web chats, social networking platforms, email, websites, and blogs (Centers for Disease Control and Prevention, 2014). Electronic TDV, then, is the occurrence of electronic aggression specifically within teen dating relationships, wherein a dating partner monitors, controls, harasses, or otherwise abuses a dating partner via technology (Temple et al., 2016). Electronic aggression often functions as a mechanism of power and control in relationships, frequently originating from distrust and jealousy (Baker & Carreo, 2016; Lucero, Weisz, Smith-Darden, & Lucero, 2014). Attributes of electronic TDV include near-ubiquitous access to and possible surveillance and isolation of victims, and the possibility of broadcasting perpetration to wider audiences (Baker & Carreo, 2016). Abusive behaviors commonly occur via spying/monitoring on current location, activities, and companions; sexting; and password sharing/account access (Lucero et al., 2014; Randell et al., 2016). The unique characteristics attributable to electronic TDV warrant a focused research effort.

In recent years, high-profile cases of electronic TDV have yielded serious outcomes, including suicide (Alvarez, 2012). Recent data also suggest links between electronic TDV and higher levels of recent depressive symptoms; anger and hostility; anxiety; insecure parental attachment; anxious partner attachment; delinquent behavior; sexual activity and sexual risk behaviors; reproductive and sexual coercion; sexual harassment; bullying and cyberbullying; physical, psychological, and sexual TDV; and nonpartner sexual assault (Cutbush, Williams, & Miller, 2016; Dick et al., 2014; Peskin et al., 2017; Randell et al., 2016; Reed, Tolman, Ward, & Safyer, 2016; Temple et al., 2016; Wright, 2015; Yahner, Dank, Zweig, & Lachman, 2015; Zweig, Lachman, Yahner, & Dank, 2013). Qualitative studies have identified several ways in which electronic TDV occurs, including perpetrating verbal or emotional aggression against a partner and monitoring or controlling the activities or whereabouts of a partner (Baker & Carreo, 2016; Draucker & Martsolf, 2010; Lucero et al., 2014).

Empirical studies investigating electronic TDV are scarce, and most focus on high-school- and college-aged samples (Bonomi, Anderson, Nemeth, Rivara, & Buettner, 2013; Cutbush, Ashley, Kan, Hampton, & Hall, 2010; Dick et al., 2014; Felmlee & Faris, 2016; Korchmaros, Ybarra, Langhinrichsen-Rohling, boyd, & Lenhart, 2013; Randell et al., 2016; Temple et al., 2016; A Thin Line, 2009; Wright, 2015). Few studies have investigated these behaviors among middle-school-aged youth. Of those that do (Dank, Lachman, Zweig, & Yahner, 2013; Picard, 2007; Smith-Darden, Kernsmith, Victor, & Lathrop, 2017; Zweig, Dank, Yahner, & Lachman, 2013; Zweig, Lachman, et al., 2013; Zweig, Lachman, Yahner, & Dank, 2014), samples span middle- and high-school-aged youth. Results from a large sample of more than 5,647 youth in Grades 7 to 12 found that 26% of teens in a current/recent relationship reported having been victims of electronic TDV in the past year, and 12% reported having perpetrated electronic TDV. Girls in a current/recent relationship were more likely to report being victims of electronic TDV than boys (Zweig, Dank, Yahner, et al., 2013). In another study of 727 middle- and high-school-aged students who reported dating history in the past year, electronic TDV perpetration was positively associated with adverse childhood experiences, whereas electronic TDV perpetration inversely associated with parental involvement and perceived safety in the community (Smith-Darden et al., 2017). Two studies of electronic TDV among only middle-school-aged youth exist: In one study of seventh-grade students, 32% reported having been victims of and 18% reported having perpetrated electronic TDV against a girlfriend/boyfriend in the preceding 6 months; rates were similar by gender (Cutbush et al., 2012). In a separate study of a predominantly ethnic-minority sample of sixth graders who reported ever having had a boyfriend/girlfriend, almost 15% indicated perpetrating electronic TDV at least once during their lifetime (Peskin et al., 2017). To our knowledge, no peer-reviewed findings exist from longitudinal studies examining developmental trends of electronic TDV among middle-school-aged youth.

Focus on Middle School Youth

Despite the dearth of research on electronic TDV and the scant attention given to middle-school-aged youth in particular (Foshee & Matthew, 2007), the spotlight has recently been cast upon youth in middle school by national initiatives funded by the Robert Wood Johnson Foundation (Start Strong: Building Healthy Teen Relationships) and the Centers for Disease Control and Prevention (Dating Matters: Strategies to Promote Healthy Teen Relationships Initiative). Recent studies underscore the need to investigate TDV among middle school students, given their high rates of involvement in dating relationships and engagement in other forms of TDV. Miller, Gorman-Smith, Sullivan, Orpinas, and Simon (2009) found that 53% of sixth-grade youth reported having had a boyfriend or girlfriend in the last 3 months. Swahn et al. (2008) found that, among seventh graders who had dated in the past year, 23% reported dating violence perpetration and 30% reported dating violence victimization. Taylor, Stein, Mack, Horwood, and Burden (2010) similarly found that, in a sample of sixth- and seventh-grade students, 21% reported having perpetrated at least one act of dating violence in their lifetime. While some research points to prevalence of other forms of TDV among middle school youth, there is a scarcity of literature investigating the phenomenon of electronic TDV, and it is further compounded by the absence of data on gender differences.

Electronic TDV and Gender

The question of whether the prevalence rates of electronic dating violence perpetration and victimization differ by gender, or vary as a function of gender, is still unresolved. Most studies within the field have focused on gender differences in physical, psychological, or sexual TDV (Champion, Wagoner, Song, Brown, & Wolfson, 2008; Foshee et al., 2009; McDonell, Ott, & Mitchell, 2010; Rothman, Johnson, Azrael, Hall, & Weinberg, 2010; Simon, Miller, Gorman-Smith, Orpinas, & Sullivan, 2010); far fewer studies have investigated gender differences in electronic TDV. Among those that have, three studies have reported significantly different rates of electronic TDV by gender, with females experiencing victimization more frequently than males: Dick et al. (2014) indicated more female than males experiencing past 3-month electronic TDV among a sample of high school students seeking care at school-based health centers. In another study of high school students, Felmlee and Faris (2016) assessed the occurrence of electronic TDV in the past week and also found females were more frequent victims than males. Similarly, in a large study of middle- and high-school-aged students (Dank et al., 2013; Yahner et al., 2015; Zweig, Dank, Lachman, & Yahner, 2013; Zweig, Dank, Yahner, et al., 2013), females experienced past-year electronic TDV victimization more frequently than males. However, one study of 12th graders showed comparable rates (Wright, 2015). Within yet another study of middle- and high-school-aged students, findings were mixed, such that boys were twice as likely to perpetrate past-year coercive sexting, but gender was not associated with past-year cyberstalking or electronic harassment (Smith-Darden Joanne et al., 2017). To our knowledge, no studies have examined gender differences in prevalence and rates over time of electronic TDV among middle school students only.

Current Study

Middle-school-aged youth are clearly engaging in dating relationships and TDV behaviors, and as digital natives, they are simultaneously clamoring for access to cell phone and social media platforms. Developmentally, given this dynamic conjuncture—that is, the onset of dating and dating violence behaviors vis-à-vis the uptake of digital technologies—it is critical that prevention science begin amassing longitudinal data to sort out behavioral trends among middle-school-aged youth.

This study aims to fill two key gaps in the literature: (a) It contributes to the extremely limited literature base on electronic TDV among middle school youth, including differences between girls and boys, and (b) no peer-reviewed findings exist from longitudinal studies examining developmental trends of electronic TDV among middle school students. This study will fill these gaps by investigating two research questions:

Research Question 1: What is the prevalence of electronic TDV perpetration and victimization among middle-school-aged youth, and do rates differ by gender?

Research Question 2: What is the developmental change over time in these behaviors, and do these changes vary by gender?

Additional research is needed about electronic TDV among middle school youth to build an evidence base and inform TDV prevention programs. This study will advance TDV prevention efforts aimed at ameliorating harmful behaviors at salient, developmentally appropriate junctures.

Method

Study Design

Data for this study were drawn from comparison schools participating in an independent evaluation of the Start Strong: Building Healthy Teen Relationships initiative (Blue Shield of California Foundation & Robert Wood Johnson Foundation, 2013). Start Strong, a national program of the Robert Wood Johnson Foundation and the Blue Shield of California Foundation, in collaboration with Futures Without Violence, was implemented in 11 sites across the country.¹ Sites collectively represented midsized and large urban areas, regional diversity, and racial/ethnic diversity. The quasi-experimental design matched four comparison schools to the intervention schools on the following criteria: school size, percentage of students receiving free or reduced-price lunch, race/ethnicity, and metropolitan area characteristics. Across the schools, the percentage of students on free or reduced school lunch ranged from 43% to 95%. Four waves of data were collected at 6-month intervals from one cohort of middle school students enrolled in the fall of their seventh-grade year. Analyses invoke data from all four time points: Wave 1 (fall, seventh grade), Wave 2 (spring, seventh grade), Wave 3 (fall eighth grade), and Wave 4 (spring eighth grade).

Procedures

Students were given a letter from research staff for their parents that explained the study and included a consent form to be returned by the student to school. Students received a US$5 gift card incentive for returning the forms, regardless of permission status. Teachers who collected 80% of students’ signed parent permission forms, regardless of permission status, received a US$40 gift card incentive. Surveys were administered using a paper-and-pencil questionnaire in groups during regular school hours. At the beginning of data collection, trained project staff read an assent script and obtained passive student assent. The study and data collection procedures were approved by the Institutional Review Board of RTI International.

Participants

Across the eight schools participating in the outcome evaluation, a total of 2,626 seventh-grade students were eligible to participate. Eligibility criteria included being able to complete the instrument in English and not being in a self-contained classroom (i.e., an instructional setting for students who have substantial disabilities). After securing parent consent and student assent, we collected data on 1,517 students, for a participation rate of 58%. A total of 795 students were available for this study from the comparison group. The sample was evenly split along gender lines (50.4% female). Thirty-four percent reported being African American, 26% White, 24% Hispanic, and 15% Other or Multiple races. Some attrition occurred over time, though most attrition was attributable to students’ withdrawing from the school (rather than not taking the survey).² Across the time points, overall attrition was approximately 18% (Wave 1 to Wave 2, 4.0%; Wave 2 to Wave 3, 9.9%; Wave 3 to Wave 4, 4.2%). Attrition was not significantly different by race/ethnicity, F(3, 790) = 1.79, ns, or gender, F(1, 790) = 3.10, ns, Missing data from attrition and other sources were thus assumed to be missing at random or ignorable (Little & Rubin, 2002).

Measures

Dating status was not explicitly defined within the instrument. Instead, dating status was inferred based on responses to the electronic TDV indicators. These items were framed within the context of dating relationship by invoking “boyfriend or girlfriend” in the question stem, and thus, respondents could be assumed to have had a current or past dating relationship. Students with nonmissing responses, which indicated the presence or absence of specific TDV perpetrator or victim behaviors, on one or more of these items were deemed to have engaged in dating behaviors and were used in all analyses.

Electronic TDV was assessed with an eight-item scale (derived from Picard) (Picard, 2007) for perpetration and also for victimization that asked, “How many times in the last 6 months have you done these things to a boyfriend or girlfriend using a cell phone, email, IM [instant messaging], text messaging, web chat, a blog, or a networking site like MySpace or Facebook?” (perpetration) and “How many times in the last 6 months has a boyfriend or girlfriend done these things to you . . . ?” (victimization). Items included “showed private or embarrassing pictures of you to others,” “made you afraid,” or “spread rumors about you.” Items were rated on a 4-point scale: never, 1 to 3 times, 4 to 9 times, and 10 or more times. Response options were coded dichotomously, such that any student who endorsed one or more items was “ever” instead of “never” for all items. Cronbach’s alphas across all four waves for electronic TDV scales were α = .81, .86, .88, .89 (perpetration) and α = .85, .87, .86, .86 (victimization), respectively.

Race/ethnicity was included as a control variable; response categories included White, Black/African American, Hispanic, and Other/Multiple/Unknown.

Analysis

The prevalence of electronic TDV at each wave was estimated for the overall sample, as well as separately for each gender. Differences in rates were examined with t tests. Change over time was examined with longitudinal growth models (LGMs). Models were estimated in a multilevel framework where repeated observations were nested within students and included random effects for intercepts and linear slopes. Nesting of student within schools was not included because of the small number of schools in the sample (four). Quadratic models centered time at the midpoint of the trajectory (i.e., between the spring of seventh-grade and the fall of eighth-grade assessments). Random effects for quadratic slopes were not included because of insufficient variability in that variance component across models. All models controlled for student race/ethnicity. Models of overall change over time included gender as a control measure. An interaction term of gender and the linear slope was added to models to examine differences in TDV trajectories as a function of gender. Gender-by-acceleration (quadratic slope) interactions were not examined because of the low variability in that parameter. All models were estimated in Mplus (Version 6.12) and accounted for missing-at-random data, and incorporated binary response distribution of the outcomes (Muthén & Muthén, 1998-2012).

Results

Prevalence of Middle School Electronic TDV

The prevalence rates of electronic TDV perpetration and victimization at four assessments across seventh and eighth grades are shown in Table 1. As shown in the overall Wave 1 to Wave 4 column, about one in three students (32%) reported having perpetrated some form of electronic TDV at one or more of the four time points, whereas roughly one in two students (51%) reported having been a victim of electronic TDV during at least one assessment wave. For the most part, electronic TDV did not significantly differ in prevalence by gender. Boys and girls reported similar rates of electronic TDV perpetration at all waves of data and similar rates of electronic TDV victimization at three of four waves, with boys (about 42%) reporting significantly more victimization than girls (31%: t = 2.55, p < .05) at baseline.

Table 1.

Observed Proportions of Electronic Perpetration and Victimization—Overall and by Gender.

	Wave 1	Wave 2	Wave 3	Wave 4	Wave 1-Wave 4
	n (%)	n (%)	n (%)	n (%)	n (%)
Electronic perpetration
Overall	111 (21.6%)	85 (17.3%)	65 (13.9%)	74 (15.5%)	223 (32.3%)
Girls	55 (20.4%)	49 (19.3%)	34 (14.9%)	39 (16.7%)	120 (34.2%)
Boys	56 (22.8%)	36 (15.2%)	31 (13.0%)	33 (14.2%)	103 (30.4%)
Electronic victimization
Overall	189 (36.1%)	149 (30.1%)	115 (24.8%)	127 (27.3%)	351 (50.6%)
Girls	85 (31.0%)	81 (32.1%)	60 (26.2%)	73 (31.2%)	172 (49.0%)
Boys	104 (41.8%)^a	68 (28.0%)	55 (23.5%)	54 (23.3%)	179 (52.2%)

Estimate for boys differed significantly from estimate for girls at that wave.

Change Over Time in Middle School Electronic TDV

The developmental trajectories of electronic TDV perpetration and victimization across the two middle school years were evaluated with a series of quadratic LGMs to incorporate the nonlinear change apparent in the observed rates shown in Table 1. The first model estimated the developmental change for each behavior in the overall sample. Next, the gender-by-linear time interaction was added to the model to determine whether change over time varied significantly by gender. The simple slopes, or gender-specific linear rates of change, were extracted from this second model and examined.

Table 2 displays the intercept and slope estimates from the quadratic LGM for each outcome. Overall, both electronic TDV perpetration and victimization showed a significant (linear) decrease from the beginning of seventh grade to the end of eighth grade, β = −.129 (.058), p < .05, for perpetration, and β = −.138 (.048), p < .01, for victimization. Electronic victimization showed a significant deceleration in the rate of decrease over time, β = .111 (.053), p < .05.

Table 2.

Quadratic Longitudinal Growth Model (LGM) estimates of Electronic Perpetration and Victimization—Overall and by Gender.

	Quadratic Model			Quadratic With Interaction
	Interceptest.(SE)	Slope-Linearest.(SE)	Slope-Quadraticest.(SE)	Simple Slopes
	Interceptest.(SE)	Slope-Linearest.(SE)	Slope-Quadraticest.(SE)	Linear Slope × Genderest.(SE)	Boysest.(SE)	Girlsest.(SE)
Electronic perpetration
Overall	−1.882 (.189)***	−.129 (.057)*	.105 (.065)
Overall with gender interaction	−1.875(.189)	−.067(.078)	.104(.065)	−.130(.114)	−.197(.083)*	−.067(.078)
Electronic victimization
Overall	−1.013(.159)***	−.138(.048)**	.111(.053)*
Overall with gender interaction	−1.004(.160)***	.006(.066)	.109(.054)*	−.298(.096)**	−.292(.069)***	.006(.066)

Note. Intercept and slope estimates are from model without interaction term.

p < .05. **p < .01. ***p < .001.

The gender-by-time interaction was significant for victimization, β = −.298 (.096), p < .01. The simple slopes indicated that whereas girls showed almost no change in their reported victimization, β = .006 (.066), ns, boys’ reports decreased significantly over the 2 years, β = −.292 (.069), p < .001. The moderation of electronic TDV perpetration by gender was not significant, β = −.130 (.114), ns. However, the simple slopes revealed that girls again showed a nonsignificant change in TDV across seventh and eighth grades, β = −.067 (.078), ns, whereas boys showed a significant decline in reported electronic TDV perpetration, β = −.197 (.083), p < .05 (see Figure 1).

Figure 1.

Quadratic Longitudinal Growth Model (LGM) estimates for electronic perpetration and victimization—Overall and by gender.

Discussion

This study, which investigated electronic TDV within a large, racially diverse sample of middle school students, adds to the extremely limited empirical base on electronic TDV. Students reported high rates of electronic aggression within their dating relationships: 32% reported perpetrating electronic TDV, and 51% reported being victims of electronic TDV. These results reinforce the significant extent to which new media serve as venues for young adolescents’ dating relationships as well as fertile ground for electronic TDV. Features of this environment (e.g., easy access, potential widespread audience) may amplify unhealthy relationship dynamics and intensify negative consequences on victims (Alvarez, 2012). Electronic TDV may also be a convenient strategy to maintain power and control over a dating partner—for example, by tracking someone’s whereabouts and monitoring their activity with others. Unlike in-person interactions, adolescents using new media may feel emboldened to behave in ways they otherwise might not enact.

At three of the four time points, the proportion of students reporting electronic TDV victimization did not differ by gender. The one time point within our study that did yield significantly different rates of victimization showed boys reporting greater victimization than girls. Interestingly, these overall results diverge from previous studies (Dank et al., 2013; Dick et al., 2014; Felmlee & Faris, 2016; Yahner et al., 2015; Zweig, Dank, Lachman, et al., 2013; Zweig, Dank, Yahner, et al., 2013), where girls reported higher levels of electronic TDV victimization. Differences could be attributable to the older students comprising each of these other three study samples (i.e., high school or spanning middle and high school vs. middle school only in this study) or the measurement time frame (e.g., past week, past 3 months, and past year vs. past 6 months in this study). However, our findings—gender parity at three of four time points—at least partially reflect Wright (2015) findings of gender parity among 12th graders, thereby casting doubt on the suggestion that the younger sample age could be driving our divergent findings. Per Smith-Darden et al (2017) mixed findings on the perpetration of cyberstalking, electronic harassment, and coercive sexting among a sample of sixth and ninth graders, perhaps there are specific dimensions of electronic TDV victimization that vary by gender driving this unique finding, yet our measures failed to capture these various dimensions. Future studies should include qualitative data collection (e.g., focus groups) aimed at eliciting additional specific dimensions.

At all four time points, the proportion of students reporting electronic TDV perpetration did not differ by gender. These findings diverge from other studies of electronic TDV perpetration: In one sample of sixth graders (Peskin et al., 2017) and in one sample of ninth graders (Cutbush et al., 2010), females were more likely to perpetrate electronic TDV than males. In another study of mostly high school students, males were more likely to perpetrate sexual forms of electronic TDV, whereas females were more likely to perpetrate nonsexual forms of electronic TDV (Zweig, Dank, Yahner, et al., 2013). Because no clear pattern of perpetration by gender has emerged within the literature, additional qualitative and quantitative study of electronic TDV is needed to suss out a pattern and subsequent explanation for these divergent findings.

This is the first study to report on longitudinal patterns of electronic TDV among middle school youth. Boys, but not girls, reported decreasing levels of perpetration and victimization over time. Given the limited empirical base on gender differences in electronic TDV, it is difficult to interpret these findings. The decrease in electronic TDV for boys is consistent with the bullying literature, where a similar decline in aggression is found among boys in middle school (Pellegrini, 2001; Pellegrini & Bartini, 2001). It is also possible to expect a decrease for girls and boys owing to testing effects, or students being sensitized to the questions. On the contrary, we might anticipate an increase for both genders, as increasing numbers of young teens get phones in middle school (Lenhart, Ling, Campbell, & Purcell, 2010). Adolescents rely heavily on cell phones for communication, and perhaps this increased access promotes electronic TDV. Higher rates might also be expected for girls, who may be more likely than boys to use the Internet to socialize (Wartberg et al., 2015). Unfortunately, data were not collected on frequency and modality technology use, and we cannot ascertain whether usage influenced longitudinal gendered patterns.

Limitations

This article contains a number of limitations. Although the sample was large and racially/ethnically diverse, it is not nationally representative and low response rates may negatively affect its generalizability. In addition, the measures did not capture data on the sexual identity of the perpetrator or victim owing to strong resistance from some schools. Methodological limitations include the lack of school-level clustering and the narrow scope of study measures. While it is certainly plausible that trajectories of TDV are influenced by school-level factors and would thus be reflected by a nonzero school random effect for slopes or intercepts, the practical impact is likely to be limited. The larger evaluation of Start Strong found little difference across evaluation models that did and did not incorporate school-level variation. Regarding measurement, most studies, including this one, rely on counts of behavioral acts (e.g., 1-3 times, 4 or more times). However, such measures do not take into account important contextual factors, such as whether the victim experienced fear or was injured. The measures used in this study offer important insights into this phenomenon, but additional measurement development studies examining various dimensions of these electronic perpetration and victimization are sorely needed in the field. Another potential limitation is possible variation in students’ interpretation of the survey items, and whether survey items captured the intent of their behaviors. For example, some behaviors may be viewed as being playful, which may remain harmless or escalate into more serious situations (Sullivan, Erwin, Helms, Masho, & Farrell, 2010). These behaviors may also represent a “poking courtship” and a relatively safe way to assess the interest of a potential partner (Pellegrini & Long, 2003). If the interest is not reciprocated, the young teen then saves face by not expressing more overt romantic interest.

Implications and Future Directions

Despite these limitations, the study adds to the extremely limited body of research on electronic TDV by showing that a sizable proportion of early adolescents is involved in electronic TDV. These findings underscore the need for further investigation of electronic TDV behaviors, correlates, and consequences.

Qualitative and empirical studies are needed to suss out more nuanced understanding of behavioral motivations (e.g., jealousy, surveillance), intentions (e.g., harm, control), correlates (e.g., anger/hostility, depressive symptoms), consequences (e.g., fear, suicidal ideations), as well as the contextual factors surrounding these behaviors (e.g., one-sided or mutual behaviors within relationship, correlates with other types of TDV) among young adolescents. Studies are also needed to further situate these behaviors within the myriad types of electronic environments (e.g., one-on-one texting vs. social networking sites), and to understand whether motivations, intentions, correlates, consequences, and contextual factors vary by modality (e.g., public vs. private electronic communications).

Additional research is needed to improve the measurement and assessment of electronic TDV, including its various dimensions (Hamby & Turner, 2013). Further measurement studies are also needed to develop, expand, test, refine, and validate electronic TDV measures given the field’s nascent state, the lack of consensus around measurement, and the subsequent challenges in comparing data across studies.

Finally, and most importantly, the impact of emerging technologies on communication, relationships, society, and culture should not be underestimated. Smartphone ownership among American teens has increased substantially, with “half of teen smartphone owners now saying they mostly go online using their phone” (Madden et al., 2013). Youth are increasingly accessing and owning smartphones at younger ages. In our networked era, it is therefore critical that we encourage youth’s thoughtfulness about their online interactions, and that we engage young people in conversations about identity, privacy, safety, danger, bullying (boyd, 2014), and, as the present study indicates, electronic TDV. This study’s findings spotlight the need to develop and integrate age-appropriate content germane to electronic TDV within prevention and intervention programming for middle-school-aged youth. Programs should include content designed to help young people identify electronic TDV, reduce the acceptance of electronic TDV, and reach out for help when experiencing electronic TDV. In addition, cyberbullying programs can incorporate dating relations as one social context in which these behaviors may occur. As prevention researchers and practitioners, it is incumbent upon us to generate programs aimed at inoculating our youth against the underbelly of digital technologies.

Footnotes

Acknowledgements

We would like to acknowledge the participation of students in Start Strong: Building Healthy Relationships Initiative.

Authors’ Note

All authors certify that the above-mentioned manuscript represents valid work and has not been submitted for publication elsewhere. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Robert Wood Johnson Foundation.

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.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Robert Wood Johnson Foundation.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Notes

Author Biographies

Stacey Cutbush, PhD, is a social scientist in the Violence and Victimization Program in the Center for Justice, Safety, and Resilience. She has more than 15 years of experience in public health research and education efforts targeting the prevention of intimate partner violence (IPV), sexual violence and harassment, teen dating violence (TDV), human trafficking, bullying, and other youth violence. Her research experience includes conducting literature reviews; establishing criteria for evaluability assessments; assessing quality of research designs and methods; designing process and outcome evaluations; developing data collection instruments; collecting quantitative and qualitative data, including cognitive interviewing; monitoring data collection and quality; cleaning quantitative datasets; conducting clustered, multivariate analyses; developing reports and manuscripts; providing program and evaluation technical assistance; developing, planning, and implementing interventions; and developing and conducting trainings and webinars for diverse audiences. Her Research Interests: All study authors study violence and victimization.

Jason Williams, PhD, is a research psychologist in the Risk Behavior and Family Research Program at RTI International. He has more than 6 years of experience in developing advanced statistical methods and applying them to evaluations of interventions and prevention programs. His work focuses on youth substance use and other problem behaviors and on evaluation of small- and large-scale interventions and prevention programs, especially in analyzing longitudinal models of program effects. He is the primary analyst and methodologist for multiple projects at RTI, including the evaluation of the Middle School Coordinator Initiative, the evaluation of the Safe Schools/Healthy Students program, and the evaluation of a web-based alcohol prevention program administered to military personnel. Other methodological and substantive work includes ongoing evaluation of the Adolescents Training and Learning to Avoid Steroids (ATLAS) and Student Athletes Tested Using Random Notification (SATURN) substance use prevention programs. His research interests include program evaluation, substance use and problem behavior prevention, and development of advanced statistical methods to test mediated effects. He has expertise in mediation analysis, missing data techniques, bootstrapping, multilevel models, structural equation modeling, longitudinal growth models, and other latent variable models, such as latent class analysis. He is proficient in various statistical software packages and has particular expertise in SAS and Mplus. His Research Interests: All study authors study violence and victimization.

Shari Miller, PhD, a licensed clinical psychologist and clinical research psychologist, has more than two decades of expertise in developing, implementing, and evaluating school-based interventions targeting prevention of youth violence, substance use, and delinquency. Her background includes data collection in juvenile justice settings, the intersection of exposure to trauma with delinquency, and youth who cross service sectors. She has conducted semistructured key informant interviews, fidelity and process evaluations, and site visits in community-based organizations. She has published extensively in peer-reviewed journals on preventive interventions and basic research on youth violence and delinquency, and she serves on the editorial board of the Journal of Clinical Child and Adolescent Psychology. Her Research Interests: All study authors study violence and victimization.

Deborah Gibbs, MPH, has more than 30 years of experience in developing evaluation designs that combine qualitative and quantitative methods. She has been the project leader in numerous studies related to human trafficking, child welfare, IPV, program implementation, and policy change. She has conducted structured interviews and focus groups with a wide variety of participants, as well as case studies of program implementation in both health and social service agencies. Her Research Interests: All study authors study violence and victimization.

Monique Clinton-Sherrod, PhD, an RTI International research psychologist, has extensive experience in prevention research and training and technical assistance associated with implementation and evaluation of programming for a variety of psychosocial issues. She is program director for the Violence and Victimization Research Program in RTI’s Center for Justice, Safety, and Resilience. She has more than 20 years of research experience in the areas of prevention of family, partner, and sexual violence; substance abuse prevention; and women’s and minorities’ health. Her work has included a focus on technical assistance and training for and evaluation of interventions using culturally appropriate approaches and focus on capacity-building efforts in communities for effective prevention and intervention efforts. She is a member of RTI’s Global Gender Center, a cross-institute center that comprises more than 250 staff members across RTI’s many practice areas. She is well trained in project leadership and management, and conducting qualitative and quantitative data collection and analysis among various populations with varying in-person and virtual modalities. She has coauthored journal articles for such publications as Violence Against Women, Journal of Substance Abuse, and Psychology of Women Quarterly. Her Research Interests: All study authors study violence and victimization.

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