Cyber Victimization,Psychological Intimate Partner Violence,and Problematic Mental Health Outcomes Among First-Year College Students

Abstract

Both cyber victimization and psychological intimate partner violence (IPV) have been associated with negative mental health outcomes among adolescents and young adults. The present study examined relations among cyber victimization, psychological IPV, and mental health outcomes (depressive symptoms, antisocial behavior) among first-year college students. Consistent with polyvictimization theory, we hypothesized that cyber victimization and psychological IPV would be related to each other. We also hypothesized that each would uniquely contribute to depressive symptoms and antisocial behavior, after accounting for the other. Participants (N = 342, M age = 18.33 years; 50% male) completed questionnaires during a single lab visit. Results indicated that cyber victimization and psychological IPV were related to each other, and both contributed uniquely to depressive symptoms, but only cyber victimization contributed uniquely to antisocial behavior. Exploratory analyses indicated that experiencing both cyber victimization and psychological IPV was necessary for increased depressive symptoms and antisocial behavior. This study is the first to establish a unique relation between cyber victimization and mental health problems, after accounting for psychological IPV. The findings also suggest a need to consider multiple forms of victimization when considering relations between specific types of victimization and mental health problems.

Introduction

Cyber victimization is typically conceptualized as experiencing intentional interpersonal aggression perpetrated via technology (e.g., cellular phones, online forums).^1,2 Examples of cyber victimization include being the target of harassing messages, hurtful comments, embarrassing photos, and threats via electronic messaging or social media. Between 9% and 22% of college students are estimated to experience cyber victimization at some point during their years in college.^3–6 Moreover, cyber victimization has been linked to many different types of adjustment problems, including depressive symptoms and antisocial behavior (e.g., theft, weapon-carrying, drug use).^5,7–13 The prevalence and consequences of cyber victimization have led to calls for additional research on the phenomenon.¹²

Psychological intimate partner violence (IPV), including emotional abuse (e.g., accusations of infidelity, put-downs, tracking a partner's whereabouts) and threatening behavior (e.g., threatening to destroy something the partner values, or ending the relationship), is another type of victimization experience that is very prevalent on college campuses. More than 80% of college students of both sexes report such victimization in their college dating relationships,¹⁴ and more than half report experiencing it within the past year.¹⁵ Notably, psychological IPV occurs three times as often as physical IPV in both adolescent and adult samples.^16,17 Among adolescents and young adults, experiencing psychological IPV is prospectively associated with antisocial behavior with men,¹⁸ and depressive symptoms with both men and women.^16,18–20

Polyvictimization theory and research²¹ raises questions about the unique contributions of cyber victimization and psychological IPV to college students' behavioral and psychological adjustment. Specifically, theory and research on polyvictimization suggest that both cyber victimization and psychological IPV are part of an individual's broader experience of victimization. Cyber victimization, for example, is likely associated with psychological IPV, and it may need to be considered in the context of psychological IPV to truly understand how it influences college students' adjustment. That is, cyber victimization may be redundant with experiences of psychological IPV, with respect to its relation with mental health outcomes. This is consistent with the results of studies showing that cyber victimization only negligibly predicts psychosocial functioning, after accounting for other forms of interpersonal victimization.²² Alternatively, it might be argued that it is a combination of victimization experiences (e.g., cyber victimization + psychological IPV) that are responsible for the documented relations with adjustment problems. For example, cyber victimization alone might not be associated with adjustment problems, but it is associated when considered in the context of other victimization experiences.

It might also be hypothesized that the effects of certain types of victimization experiences are additive, and they contribute to mental health problems, after accounting for the effects of other forms of victimization. For example, it seems possible that cyber victimization is uniquely harmful to young adults, in ways that are different from other forms of victimization. Technology offers a repertoire of aggressive acts unavailable through traditional means, such as widespread dissemination of images and advanced tracking capabilities (e.g., Global Positioning System; GPS), that may be especially distressing or threatening due to the scope and depth of privacy invasion.² In addition, the 24-hour nature of technology use makes cyber victimization a constant threat. Cyber victimization may also invoke an expectation of lifelong pain, humiliation, or shame due to the lasting online record.^2,23,24 Additionally, young adults are the most frequent users of technology²⁵ and, therefore often cyber victims.

It also seems possible that psychological IPV is damaging to young adults in ways that are unique from other forms of victimization, including cyber victimization. From a developmental perspective, dating relationships become more serious and important during the early college years for many individuals,²⁶ and young adults are the most frequent victims of IPV.²⁷ Given the prevalence, repetitiveness, and persistence of psychological IPV, coupled with its insidious nature (it includes actions that evoke fear, undermine self-worth, and adversely affect beliefs about the stability and security of close relationships), experiencing psychological IPV might be especially harmful during this developmental period. Notably, experiencing psychological IPV has been found to predict emotional distress, after accounting for physical forms of victimization.^{16,19,26,28–29}

The results from a handful of studies of middle-school and high-school students suggest that cyber victimization relates to adolescent adjustment outcomes (e.g., depressive symptoms), after accounting for traditional, non-technology based victimization (e.g., physical or relational peer bullying).^{10,11,25,30–31} However, to our knowledge, no study has examined the unique contribution of cyber victimization over and above psychological IPV (or vice versa). Evaluation of the contribution of cyber victimization to mental health outcomes after accounting for psychological IPV (and vice versa) may represent an especially conservative test, particularly as both victimization experiences are common among young adults and are characterized by hurtful, non-physical acts that can cause lasting psychological harm.

The present study examines relations among cyber victimization, psychological IPV, and mental health outcomes among first-year college students. We hypothesize that: (1) cyber victimization and psychological IPV will be positively correlated with one another; (2) cyber victimization and psychological IPV will be uniquely, positively associated with depressive symptoms; and (3) cyber victimization and psychological IPV will be uniquely, positively associated with antisocial behavior. Exploratory analyses will examine group differences in depressive symptoms and antisocial behavior based on students' experiences of cyber victimization alone, psychological IPV alone, both, or none. Because there have been inconsistent findings regarding sex differences in victimization,^32,33 we test for sex differences in our analyses, but we offer no specific hypotheses.

Methods

Participants

Participants (n = 341) were recruited through required first-year wellness classes at a mid-sized private university in the Southwestern United States. Participants ranged in age from 18 to 28 (M = 18.33, SD = 0.82), and 170 (50%) were men. Most identified as White (69%), followed by Asian (16%), Hispanic or Latino/a (5%), African American (3%), American Indian/Alaska Native (less than 1%), and multi-racial (6%); less than 1% indicated “unknown” or did not report their race. The sample was demographically representative of first-year students from the university at which the students were recruited.

Procedures

The university's institutional review board approved all study procedures. The study was cross-sectional, and students completed questionnaires during a single lab visit at the university. Data were collected 2–3 months into the academic year; thus, participants had entered college only recently.

Measures

Cyber victimization

Students completed a modified version of the 12-item Partner Cyber-abuse Questionnaire (PCAQ).³⁴ The items on the measure were changed for the current study from “My partner…” to “Someone…” to capture all cyber victimization rather than cyber victimization committed only by an intimate partner. Sample items include “Someone sent angry or insulting messages to me,” and “Someone wrote something negative about me on social media, such as Facebook or Twitter.” Students reported the frequency of cyber victimization experiences since beginning college, on a scale ranging from 0 (never) to 5 (five or more times). A total sum score was calculated, with higher scores indicating greater victimization. Internal consistency for the current sample was α = 0.71. Prior research indicates that scores on the PCAQ relate to theorized outcomes of cyber victimization, such as depressive symptoms.³⁴

Psychological IPV

Students completed the 10-item emotional abuse and 4-item threatening behavior subscales of the Conflict in Adolescent Dating Relationships Inventory–Revised (CADRI),³⁵ reporting the frequency of victimization since starting college on a scale from 0 (never) to 4 (four or more times). Sample emotional abuse items include “My partner insulted me with putdowns” and “My partner accused me of flirting with another person.” Sample threatening behavior items include “My partner destroyed or threatened to destroy something I valued” and “My partner threatened to hurt me.” These subscales were combined in analyses into one psychological IPV variable (only 2 individuals reported experiencing threatening behavior without experiencing emotional abuse). Scores were calculated by summing items, with higher scores indicating greater victimization. Internal consistency for the current sample was α = 0.86. Prior research indicates that scores on the CADRI correlate with theorized outcomes of violence victimization, such as depressive symptoms.³⁶

Depressive symptoms

Students completed the 20-item Center for Epidemiological Studies–Depression Scale (CES-D),³⁷ indicating how often they experienced symptoms in the past week on a 4-point scale ranging from 1 (Rarely or none of the time) to 4 (Most or all of the time). Sample items include “I was bothered by things that don't usually bother me” and “I had trouble keeping my mind on what I was doing.” The CES-D is scored by calculating the sum of all items, with higher scores indicating greater depressive symptoms. Internal consistency for the current sample was α = 0.89. Prior research indicates that CES-D scores are positively associated with other self-report measures of depression.³⁷

Antisocial behavior

Students completed the 9-item Honest Conduct Scale (HCS),³⁸ reporting whether they had engaged in any of the behaviors described on the scale (0 = no, 1 = yes) since they had been at college. Sample items include: “Have you ever hit, slapped or pushed other people or gotten into a physical fight with them?” “Have you ever written things or spray painted on walls or sidewalks or cars, where you were not supposed to do that?” The HCS is scored by calculating the sum of all items, where higher scores indicate greater antisocial behavior. Internal consistency in the current sample was α = 0.59. However, given the variety of behaviors assessed, we did not expect high internal consistency. Prior research indicates that HCS scores are associated in the expected direction with theorized correlates of antisocial behavior, such as honesty³⁹ and peer-nominated aggression.³⁹

Results

Ten students did not answer either the depressive symptoms or psychological IPV questionnaire; thus, 332 participants were used in the analyses. In the current sample, depressive symptoms (M = 32.54, SD = 9.06) and antisocial behavior (M = 0.53, SD = 0.97) were comparable to those of other college-student samples.^38,40 Because the distribution of depressive symptoms was skewed (skewness = 1.30), the scores were log transformed for analyses. The distribution for antisocial behavior was skewed as well (skewness = 2.69), and it evidenced a zero-inflated distribution; thus, it was dichotomized (0 = absent, 1 = present). Similarly, the distributions of cyber victimization (M = 2.73, SD = 4.75, skewness = 2.72) and psychological IPV (M = 5.12, SD = 7.23, skewness = 1.78) were positively skewed and evidenced a zero-inflated distribution. We thus dichotomized these scores (0 = absent, 1 = present).

Ninety-three participants indicated experiencing no form of victimization, 167 participants indicated experiencing cyber victimization, and 199 indicated experiencing psychological IPV. Table 1 summarizes correlations among the study variables. Race and sex were correlated with the study variables; thus, both were included as control variables in tests of hypotheses 2 and 3. Age did not correlate with study variables; thus, it was not included as a control variable.

Table 1.

Correlations Among Study and Demographic Variables

Variable	1	2	3	4	5	6
1. Cyber victimization	—
2. Psychological IPV	0.33^**	—
3. Depressive symptoms	0.17^**	0.20^**	—
4. Antisocial behavior	0.13^*	0.09	0.10	—
5. Race	−0.00	0.03	−0.14^*	0.15^**	—
6. Sex	0.06	0.13^*	0.15^**	−0.17^**	0.04	—
7. Age	−0.04	0.09	−0.01	−0.07	−0.07	−0.02

All measures were scored so that higher scores reflect greater levels of the variable measured. Race was coded 1 = White, 0 = non-White. Sex was coded 0 = male, 1 = female. ^*p < 0.05, ^**p < 0.01.

IPV, intimate partner violence.

Cyber victimization and psychological IPV (hypothesis 1)

As presented in Table 1, cyber victimization and psychological IPV were correlated with each other. Experiencing both forms of victimization was more common among participants than experiencing one or the other alone. Specifically, 127 participants indicated experiencing both cyber victimization and psychological IPV, 40 participants indicated experiencing cyber victimization only, and 72 participants indicated experiencing psychological IPV only.

Victimization and depressive symptoms (hypothesis 2)

We conducted a multiple regression analysis with cyber victimization and psychological IPV as predictor variables, race and sex as control variables, and depressive symptoms as the dependent variable. When both cyber victimization and psychological IPV were considered simultaneously, both were uniquely, positively associated with depressive symptoms (Table 2). Student race and sex were also associated with depressive symptoms: Non-White students (M = 34.41, SD = 10.14) and women (M = 33.80, SD = 9.31) were more likely to report depressive symptoms than White students (M = 31.71, SD = 8.40) and men (M = 31.28, SD = 8.61).

Table 2.

Regression of Depressive Symptoms and Antisocial Behavior on Cyber Victimization, Psychological IPV, and Mental Health Outcomes

Variable	β	B (SE)	Effect size
Depressive symptoms			sr²
Cyber victimization	0.15^*	0.06 (0.03)	0.01
Psychological IPV	0.12^*	0.07 (0.03)	0.02
Race	−0.16^*	−0.09 (0.03)	0.02
Sex	0.15^*	0.07 (0.03)	0.02
Antisocial behavior			Odds ratio
Cyber victimization		0.60^* (0.26)	1.83
Psychological IPV		0.31 (0.27)	1.36
Race		0.82^* (0.29)	2.80
Sex		−0.87^* (0.25)	0.42

Depressive symptoms: F(4, 326) = 8.95, p < 0.001, R² = 0.10. Antisocial behavior: χ²(4, N = 332) = 27.15, p < 0.001.

p < 0.05.

Victimization and antisocial behavior (hypothesis 3)

We conducted a logistic regression analysis with cyber victimization and psychological IPV as predictors, race and sex as control variables, and antisocial behavior as the dependent variable. When both cyber victimization and psychological IPV were considered simultaneously, cyber victimization was uniquely, positively associated with antisocial behavior, but psychological IPV was not. Student race and sex were associated with antisocial behavior, such that White students (M = 0.36, SD = 0.48) and men (M = 0.39, SD = 0.49) were more likely than non-White students (M = 0.21, SD = 0.41) or women (M = 0.24, SD = 0.43) to report antisocial behavior.

Exploratory analyses

We divided the sample into four groups: no victimization (n = 93), cyber victimization alone (n = 40), psychological IPV alone (n = 72), and both cyber victimization and psychological IPV (n = 127). To explore differences in depressive symptoms among the four groups, we conducted a multiple regression, which included the interaction of cyber victimization and psychological IPV, and then examined specific contrasts between each victimization group (controlling for race and sex). Results indicated that there was no significant interaction between cyber victimization and psychological IPV on depressive symptoms, p = 0.61. Contrasts indicated that individuals who experienced both types of victimization reported significantly more depressive symptoms (M = 35.00, SD = 9.59) than participants who reported: no victimization (M = 30.03, SD = 7.42), p < 0.001, only cyber victimization (M = 31.80, SD = 10.24), p = 0.04, and only psychological IPV (M = 32.22, SD = 8.52), p = 0.04. No other groups were different from one another.

To explore differences in antisocial behavior among the four groups, we conducted a logistic regression with the interaction of cyber victimization and psychological IPV, which was then followed by dummy variable contrasts between the victimization groups (controlling for race and sex). Results indicated that there was no interaction between cyber victimization and psychologcal IPV on antisocial behavior, p = 0.49. Experiencing both types of victimization (M = 0.38, SD = 0.49) was more strongly associated with antisocial behavior than experiencing no abuse (M = 0.22, SD = 0.41), p = 0.01, but no other comparisons were different from one another.

Sex differences

To examine whether sex moderates the relationship between victimization type and our outcome variables, we added two interaction terms (Sex × Cyber Victimization and Sex × Psychological IPV) to the regression models tested earlier. Sex did not moderate the association between cyber victimization and depressive symptoms (β = 0.02, p = 0.71) or antisocial behavior (B = 0.64, p = 0.22). Additionally, sex was not found to be a moderator of the relationship between psychological IPV and depressive symptoms (β = 0.04, p = 0.49), but it did moderate the relationship between psychological IPV and antisocial behavior (B = −1.05, p = 0.04), such that for students who reported psychological IPV, male students (M = 0.49, SD = 0.50) were more likely to indicate antisocial behavior than female students (M = 0.23, SD = 0.42).

Discussion

This study examined relations among cyber victimization, psychological IPV, depressive symptoms, and antisocial behavior. Consistent with our first two hypotheses, we found: (1) cyber victimization and psychological IPV were positively correlated with one another (hypothesis 1), and (2) both cyber victimization and psychological IPV were uniquely, positively associated with depressive symptoms (hypothesis 2). Cyber victimization was also associated with antisocial behavior, after accounting for the contribution of psychological IPV; whereas psychological IPV was not associated with antisocial behavior, after accounting for the contribution of cyber victimization (hypothesis 3). These results echo other findings, indicating that cyber victimization relates to adolescent adjustment outcomes after accounting for non-technology-based forms of victimization.^{10,11,25,30–31} To our knowledge, this is the first study to examine the contribution of cyber victimization over and above psychological IPV in explaining mental health consequences. This is important given the prevalence of psychological IPV and the similar nature of these two victimization experiences: Both are prevalent, both do not involve physical harm to the victim, and both are characterized by antagonistic aggression that seeks to undermine the victim's psychological well-being.

The positive association between cyber victimization and experiences of psychological IPV suggests that these two types of victimizations tend to co-occur. Additionally, our exploratory analyses indicated that only polyvictims (those who experienced cyber victimization + psychological IPV) differed from non-victims on depressive symptoms and antisocial behavior. Groups of students who experienced only cyber victimization or only psychological IPV did not differ from the group of students who were non-victims on either depressive symptoms or antisocial behavior. These exploratory findings suggest a need to consider student victimization experiences in a broader context (i.e., not just cyber victimization or just psychological IPV, but victimization broadly construed), because increased risk for depressive symptoms and antisocial behavior emerged only when multiple types of victimization occurred. These results also suggest that prevention and intervention efforts might need to address multiple types of victimization experiences, as opposed to being targeted at specific types of experiences.

Several limitations of the current study should be acknowledged. First, these data are correlational and cross-sectional; thus, we cannot make directional or causal inferences about the associations that were identified in this study. Second, this study was limited to two forms of victimization. Additionally, the psychological IPV measure was specific to intimate relationships, and the cyber victimization measure did not specify a relationship to a specific perpetrator; thus, it might have included victimization from an intimate partner. A broader and more precise assessment of victimization experiences (e.g., one that included victimization from peer- and partner-perpetrated physical violence, and one that clearly specified the perpetrators of the different forms of violence) would have provided a more clear and conservative test of the hypotheses, particularly those pertaining to the unique contributions of specific victimization experiences to college students' mental health. Third, an examination of these relations while controlling for other potentially confounding variables, such as students' media use, would strengthen the conclusions that could be drawn. Fourth, the data were all based on self-reports. Future research would benefit from assessing victimization and mental health consequences across multiple informants as well as incorporating objective measures (e.g., online or phone records indicative of cyber victimization).

Despite these limitations, the current study highlights that victimization experiences tend to co-occur, and they need to be considered in the context of other victimization experiences. It adds to the literature on the potential destructiveness of cyber victimization, showing that it contributes uniquely to student depressive symptoms and antisocial behavior, after accounting for the effects of psychological IPV. Cyber victimization, however, may need to be considered in the context of other types of victimization experiences to truly understand how it influences college students' well-being.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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