National Institute of Justice

Office of Juvenile Justice and Delinquency Prevention

U.S. Department of Justice

Office of Justice Programs

J u s t i c e Re s e arc h

NOVEMBER 2016 Nancy Rodriguez • Director, NIJ Robert L. Listenbee • Administrator, OJJDP

THE ROLE OF TECHNOLOGY IN YOUTH HARASSMENT VICTIMIZATION

T

his bulletin discusses key findings from the Technology Harassment Victimization 

study that the National Institute of Justice sponsored. It is a follow-up study to the 

second National Survey of Children’s Exposure to Violence (NatSCEV II) that the Office 

of Juvenile Justice and Delinquency Prevention sponsored. The study, conducted between 

December 2013 and March 2014, examined technology-involved harassment within the 

context of other types of youth victimization and risk factors to improve current policy and 

practice regarding the issue.

Background

Youth, Technology and Harassment Victimization

The first, second and third Youth Internet Safety Surveys (YISS-1, YISS-2 and YISS-3) were 

comprehensive national assessments that examined dynamic changes in youth Internet use 

and victimization patterns over time. Results of YISS-1 (conducted in 2000)1

 revealed that 

six percent of young Internet users experienced online harassment in the previous year. 

YISS-2 (conducted in 2005)2

 revealed that nine percent 

of respondents experienced online harassment during 

the previous year, and that number rose to 11 percent 

in the 2010 YISS-3 results.3

 The data suggest that 

greater occurrences of negative interactions between 

girls and more social network website communications 

predominantly drove the increase.1

 Because technologybased harassment rates are lower than other forms of 

youth victimization, the experiences that youth have 

with technology must be considered in conjunction with 

broader patterns of peer and sibling victimization, child 

maltreatment, conventional crime, sexual victimization, 

witnessing and indirect victimization, and other adverse 

life events to fully understand the causes, nature and 

impact of the problem. 

Previous studies that measured online harassment 

and other peer victimization among the same sample 

all found that online harassment and cyberbullying 

occur at lower rates than in-person harassment and 

bullying.2-4 For example, in 2007, about 32 percent of 

students between the ages of 12 and 18 reported bullying 

victimization at school during the academic year, 

compared to four percent who reported experiencing 

cyberbullying.4

 However, another study found that 64 

percent of youth who reported online harassment in 

the previous year did not report experiencing bullying 

This bulletin was written by Kimberly J. Mitchell, Ph.D., research associate professor of psychology 

at the Crimes against Children Research Center (CCRC), University of New Hampshire; Lisa M. 

Jones, Ph.D., research associate professor of psychology at CCRC; Heather Turner, Ph.D., professor 

of sociology and research associate at CCRC; Dara Blachman-Demner, Ph.D., social science 

analyst at the National Institute of Justice (NIJ); and Kristen Kracke, M.S.W., senior social science 

specialist, Office of Juvenile Justice and Delinquency Prevention. 

The authors would like to thank Amy Leffler, a Fellow with NIJ’s Office of Research and 

Evaluation, for her careful review of earlier drafts of this bulletin.
2 n J u s t i c e R e s e a r c h

in school.5 Some experts suggest that the anonymity of 

technology encourages bad behavior because people 

are not face-to-face with their targets and that, perhaps, 

online perpetrators have no accountability, so they 

engage in rude or harassing behavior when they would 

not typically have done so in person.6-9 Such findings 

raise critical questions about the nature of technologyrelated victimization and its similarities to, differences 

from and co-occurrence with other peer victimization 

behaviors. If technology facilitates peer harassment 

and bullying through anonymity and remoteness,10, 11

it is unclear why equal or greater levels of this behavior 

are not being observed in comparison to in-person 

harassment or bullying behavior.

Another deficit in the empirical literature involves 

documenting the emotional impact of technologyrelated harassment in comparison to the emotional 

impact of in-person harassment. Some suggest that the 

impact of harassment involving new technology can be 

worse because online harassers can post, comment or 

create pictures or videos that are available to widespread 

audiences.8, 10 In addition, the aggression can reach 

targets anywhere and at any time.8

 Online harassment 

can be more visible and permanent, and other 

aggravating features may also be present. For example, 

almost one in four perpetrators of online harassment 

are reportedly 18 years of age or older.12 Youth who are 

harassed online by adults are significantly more likely to 

report distress because of the experience.12 On the other 

hand, technology may provide an emotional distance 

that lessens the impact compared to in-person verbal 

or physical aggression. Without further research, the 

emotional toll different forms of harassment have on an 

individual remains unclear. 

A New Approach to Studying 

Harassment Victimization

One issue complicating the understanding of 

technology-facilitated harassment is that no research 

exists examining the intersection of technology-based 

harassment and offline peer victimization at the incident 

level — for example, data on how often technology-based 

harassment is an extension of in-person harassment 

(i.e., school, work or other locations). Although 

some harassment happens solely through the use of 

technology, increasing numbers of victims know their 

aggressors from school or neighborhood contact.1

Considering how much technology currently infuses 

youth communication and peer interaction, it is not 

surprising that peer problems in school spill over into the 

online environment.13 In addition, a notable proportion 

of technology harassment victims are likely to be bullied 

in school. For these youth, technology-based harassment 

may be a direct extension of other forms of victimization. 

Methodology

The current study surveyed a national sample of youth 

to (a) define technology-involved harassment incidents 

and identify their adverse consequences; (b) explore the 

role that harassment characteristics (e.g., duration and 

relationship with the aggressor) have on the impact of 

technology-involved harassment; (c) assess how often 

and how deeply bystanders are involved in technologybased youth harassment and (d) determine whether 

polyvictimized youth, who have experienced 12 or more 

types of victimization in their life, are at particular risk 

for technology-based harassment. 

Participants 

The Technology Harassment Victimization study is a 

telephone survey that drew its sample from a subset 

of households that completed a previous survey, the 

second National Survey of Children’s Exposure to 

Violence in 2011-12. The Technology Harassment 

Victimization study included questions about technology 

use, perpetration of harassment, bystander experiences, 

psychosocial characteristics and general victimization 

history. Conducted from December 2013 to March 2014, 

the study targeted the subset of NatSCEV II youth who 

were ages 8-17 at baseline (n = 2,197). A total of 791 

(36 percent of the eligible sample pool) interviews were 

completed with youth ages 10-20 for the Technology 

Harassment Victimization study. Sample weights were 

adjusted for differential attrition in wave 2 using age, 

race/ethnicity, household income, number of children 

in the household, parent demographics, and child’s 

victimization and delinquent behavior as determined 

in wave 1. The final study methodology report contains 

more details about wave 2 methodology, nonresponse 

analysis and weight construction.1

Caregivers provided demographic information, including 

the child’s gender (49 percent male), age (mean = 14.7), 
T h e R o l e o f T e c h n o l o g y i n Y o u t h H a r a s s m e n t V i c t i m i z a t i o n n 3

HISTORY OF THE NATIONAL SURVEY OF CHILDREN’S 

EXPOSURE TO VIOLENCE 

Under the leadership of then-Deputy Attorney General Eric Holder in June 1999, 

the Office of Juvenile Justice and Delinquency Prevention (OJJDP) created the 

Safe Start Initiative to prevent and reduce the impact of children’s exposure to 

violence. As a part of this initiative and with a growing need to document the full 

extent of children’s exposure to violence, OJJDP launched the National Survey of 

Children’s Exposure to Violence (NatSCEV I) with the support of the Centers for 

Disease Control and Prevention (CDC). CDC partnered with OJJDP to support 

the assessment of safe, stable and nurturing relationships and environments as 

protective factors for vulnerable youth. 

NatSCEV I was the first national incidence and prevalence study to 

comprehensively examine the extent and nature of children’s exposure to violence 

across all ages, settings and timeframes. Conducted between January and May 

2008, it measured the past-year and lifetime exposure to violence for children 

age 17 and younger across several major categories: conventional crime, child 

maltreatment, victimization by peers and siblings, sexual victimization, witnessing 

and indirect victimization (including exposure to community violence and family 

violence), school violence and threats, and Internet victimization. This survey 

marked the first attempt to measure children’s exposure to violence in the home, 

school and community across all age groups from one month to age 17, and the 

first attempt to measure the cumulative exposure to violence over the child’s lifetime. 

The survey asked children and their adult caregivers about the incidents of 

violence that children suffered and witnessed themselves and also about other 

related crime and threat exposures, such as theft or burglary from a child’s 

household, being in a school that was the target of a credible bomb threat and 

being in a war zone or an area where ethnic violence occurred. OJJDP directed 

the development of the study, and the Crimes against Children Research Center 

(CCRC) at the University of New Hampshire designed and conducted the research. 

It provided data on the full extent of violence in the daily lives of children. 

NatSCEV I documented the incidence and prevalence of children’s exposure to a 

broad array of violent experiences across a wide developmental spectrum. The 

research team asked follow-up questions about specific events, including where 

the exposure to violence occurred, whether injury resulted, how often the child 

was exposed to a specific type of violence, and the child’s relationship to the 

perpetrator and (when the child witnessed violence) the victim. 

In addition, the survey documented differences in exposure to violence across 

gender, race, socioeconomic status, family structure, region, urban/rural 

residence and developmental stage of the child; specified how different forms of 

violent victimization “cluster” or co-occur; identified individual-, family- and

race/ethnicity (58.8 percent white non-Hispanic, 12.6 

percent black non-Hispanic, 8.1 percent other race 

non-Hispanic and 20.6 percent Hispanic any race), 

and socioeconomic status. Socioeconomic status is a 

composite based on the sum of the highest standardized 

household income and standardized parental education 

scores, which was then restandardized. Family structure 

was categorized into children living with two biological 

or adoptive parents (53.1 percent), one biological parent 

and a partner (8.6 percent), a single biological parent 

(34.1 percent), or other nonparent caregiver such as a 

grandparent or foster parent (4.2 percent). 

Procedure

The research team mailed an advance letter, reply form 

and $5 cash to the 2,127 sample households. Interviewers 

called the households if they did not mail back the forms. 

Interviews with 791 respondents were completed; the 

average time to complete a survey was 58 minutes. 

Interviewers used a computer-assisted telephone 

interviewing system. After briefly surveying the parent or 

guardian, the interviewers asked the parent or guardian 

and the child for their consent to proceed to the child 

portion of the interview. The interviewers sent youth 

respondents who completed the survey a $25 check. 

The interviewers completed most wave 2 parental 

interviews (96 percent) with the same parent or guardian 

who participated in wave 1. A clinical member of the 

research team trained in telephone crisis counseling 

recontacted respondents who disclosed serious threats or 

ongoing victimization during the interview and stayed 

in contact with the respondent until the situation was 

appropriately addressed locally. The institutional review 

board of the University of New Hampshire authorized 

all procedures and ensured that they complied with the 

confidentiality guidelines that the U.S. Department of 

Justice has set forth. 

Measures

Harassment Screening Questions

Peer harassment was the key measure in this study. 

The researchers purposely used a broad definition 

of peer harassment to capture a range of harassment 

experiences. Incidents included components of standard 

(Continued on page 4)
4 n J u s t i c e R e s e a r c h

HISTORY OF THE NATIONAL SURVEY OF 

CHILDREN’S EXPOSURE TO VIOLENCE (Continued from page 3)

community-level predictors of violence exposure among children; examined 

associations between levels/types of exposure to violence and children’s mental and 

emotional health; and assessed the extent to which children disclose incidents of 

violence to various individuals and the nature and source of assistance or treatment 

provided (if any).

In 2012, in response to its solicitation for research proposals on children exposed 

to violence with identified focus areas of polyvictimization and Internet harassment, 

the National Institute of Justice received an application from CCRC that was funded 

through a competitive review process to conduct the Technology Harassment 

Victimization study. Capitalizing on the existence of NatSCEV, the Technology 

Harassment Victimization study followed up with a subsample of NatSCEV II to 

provide an in-depth exploration of the nature and consequences of technologyinvolved harassment, the impact of a range of incident-level characteristics, and 

the role of bystanders. In addition, a unique strength of the study was the ability 

to use the longitudinal nature of the sample and the existence of earlier data on 

polyvictimization and other relevant experiences to examine the relationship between 

technology-based harassment and other forms of victimization.

cyberbullying but were not limited to cyberbullying. 

The interviewers asked the youth whether they 

had experienced in-person or technology-involved 

harassment from nonfamily peers during the past year. 

Some specific types of harassment that the interviewers 

prompted the youth to think about included: 

• Someone calling them mean names, making fun of 

them or teasing them in a hurtful way.

• Someone excluding or ignoring them or getting others 

to turn against them.

• Someone spreading false rumors about them or 

sharing something that was meant to be private (such 

as something they wrote or a private picture or video 

of them). 

• Someone hitting, kicking, pushing, shoving or 

threatening to physically hurt them. 

If a youth had experienced such harassment in the 

past year, the interviewer asked the youth to identify 

as many as two unique incidents for detailed followup questioning. The interviewers used the following 

hierarchy for selecting incidents: 

• If at least two technology-involved harassment events 

were reported, details were gathered about both (most 

recent time and worst or most serious time). 

• If one technology-involved harassment event and 

one nontechnology-involved harassment event were 

reported, details were gathered on both. 

• If no technology-involved events but one or more 

in-person harassment events were reported, details 

were gathered on as many as two of those events (most 

recent time and worst or most serious time). 

Confirming Technology Involvement

Once they identified unique incidents, the interviewers 

asked the youth respondents a detailed series of followup questions about each specific harassment incident. 

The researchers designed all of the questions specifically 

for the Technology Harassment Victimization study. 

Follow-up questions confirmed the involvement of 

technology and what types of technology were used. 

Specifically, youth were asked whether the incident 

happened (a) when they were at school or on school 

grounds; (b) on the way to or from school, either on the 

bus or while walking; (c) at home; (d) at work; (e) at a 

friend’s home; (f) in a car or (g) online or texting. The 

survey permitted respondents to have multiple responses 

to each question. 

Next, interviewers asked the youth what kinds of 

technology were involved in the harassment incidents. 

Multiple responses were permitted, including (a) email; 

(b) cell phones; (c) text messages; (d) instant messages; 

(e) social networking sites, such as Facebook and 

Twitter; (f) a gaming website and (g) some other type of 

technology. 

Finally, youth were asked to choose a statement that best 

described the incident. Response options included (a) 

it started online and stayed online; (b) it started online 

and then moved offline to other places like school or 

work; (c) it started offline someplace, such as school or 

work, before it moved online or (d) it started online and 

offline at about the same time. The interviewers recoded 

incidents, changing the category from nontechnology 

involved to technology involved (or vice versa), if 

necessary, to reconcile any discrepancy between the 

technology and nontechnology harassment screening 

responses and the follow-up questions.
T h e R o l e o f T e c h n o l o g y i n Y o u t h H a r a s s m e n t V i c t i m i z a t i o n n 5

Incident Characteristics

Through a series of detailed incident follow-up questions, 

interviewers asked the youth respondents about the 

perpetrator(s) of the harassment, including the number 

of perpetrators, their ages, genders and their relationship 

to the respondent. The interviewers also asked about 

the duration and location of the event; the type of 

harassment (e.g., verbal, exclusion, rumors or physical); 

aggravating features (e.g., sexual elements, weapons 

use, physical injury, social power differentials, bias 

content and mutual harassment); bystander involvement; 

and disclosure (whether the youth told anyone what 

happened and whom). The interviewers also asked youth 

a series of questions to assess the emotional impact of the 

incident — specifically, whether it made them feel upset, 

afraid, embarrassed, worried, angry, sad, untrusting or 

unsafe. Responses to each of these items were rated on a 

scale from 1 (not at all) to 5 (extremely). The researchers 

constructed dummy variables for each item and coded 

them as 1 if the youth rated the impact at 4 or 5 on the 

scale. They also created a total emotional impact score, 

which combined scale responses on each of the eight 

items for each incident. 

Other Key Measures

The research team assessed victimization history using 

the Juvenile Victimization Questionnaire (JVQ),14-16 a 

comprehensive inventory of childhood victimization. The 

questionnaire includes 53 items that assess a broad range 

of victimizations across five modules: conventional crime 

(e.g., having something stolen), child maltreatment (e.g., 

being physically abused), peer and sibling victimization 

(e.g., being hit by other kids), sexual victimization (e.g., 

being forced to do something sexual) and witnessing 

violence (e.g., seeing parents hit each other). Each 

question refers to a specific form of victimization (e.g., 

aggravated assault or dating violence). The specific 

items used to screen for these victimization types have 

been published elsewhere.17 Youth who experienced 12 

or more kinds of victimization over their lifetime were 

defined as polyvictims. 

The researchers used 15 items to measure adversity due 

to nonviolent traumatic events and chronic stressors, 

13 of which they took from a scale that Turner and 

colleagues developed and two of which they constructed 

for NatSCEV II.17, 18 Nonviolent traumatic events include 

serious illnesses, accidents and parental imprisonment. 

Chronic stressors include substance abuse by family 

members and homelessness. The interviewers asked the 

youth respondents whether each adversity happened in 

their lifetime. They used the average score across items in 

the current analyses, with higher scores reflecting more 

adversity. 

Highlights of Study Results

Harassment Prevalence and Technology 

Involvement

Of the 791 respondents, 230 (34 percent) reported 311 

unique harassment incidents in the past year (see figure 

1).19 Of youth reporting harassment incidents, 45 percent 

were ages 10-12 at the time of the wave 2 interview, 23 

percent were ages 13-15, 22 percent were 16-17, and 10 

FIGURE 1. Prevalence of Past-Year Harassment 

No harassment

(66%)

In-person only

(17%)

Any technology

(17%)
6 n J u s t i c e R e s e a r c h

FIGURE 2. Rates of Technology Involvement in Harassment Incidents 

In-person only

(54%)

Technology only

(15%)

Mixed

(31%)

FIGURE 3. Percentage of Technology Involvement in Peer Harassment Incidents by Age Group 

0%

10%

20%

30%

40%

50%

60%

70%

In-person only Mixed Technology only

Note: Detail may not total 100% because of rounding.

Percentage of technology involvement 

in peer harassment incidents

61% 10 - 12

13 - 15

16 - 17

18 - 20

17% 19%

2%

27%

30% 29%

14%

22%

25%

20%

32%

FIGURE 4. Percentage of Technology Involvement in Peer Harassment Incidents by Gender 

0%

10%

20%

30%

40%

50%

60%

70%

In-person only Mixed Technology only

Percentage of technology involvement 

in peer harassment incidents

80% 77%

Boys Girls

23%

38%

62%

53%

47%
T h e R o l e o f T e c h n o l o g y i n Y o u t h H a r a s s m e n t V i c t i m i z a t i o n n 7

percent were 18-20. Sixty-one percent of harassment 

victims were boys and 60 percent were white and nonHispanic. 

More than half (64 percent) of such youth lived in a 

household of average socioeconomic status, 45 percent 

lived with both biological parents and 35 percent lived 

with a single parent. 

Seventeen percent (n = 137) of all respondents and 

46 percent of victims (n = 230) reported at least one 

technology-involved harassment incident, amounting 

to 148 unique incidents. All harassment incidents 

were in three mutually exclusive groups: (a) in-person 

only, no technology involved (54 percent, n = 136); (b) 

technology involved, no in-person elements (15 percent, 

n = 58); and (c) mixed harassment, involving both inperson and technology elements (31 percent, n = 117) 

(see figure 2).

Youth reporting in-person-only harassment incidents 

were significantly younger than those in the other two 

categories (see figure 3). Technology-only incidents 

involved a similar number of boys and girls, but more 

girls were in mixed-harassment incidents (see figure 

4). No significant differences emerged across groups 

in terms of race and ethnicity, family structure or 

socioeconomic status.

Harassment Incident Characteristics to 

Predict Emotional Harm

The researchers identified specific harassment incident 

characteristics most likely to result in emotional 

harm (e.g., upset, afraid, angry, sad). The average total 

emotional impact score was lowest for technology-only 

incidents (mean = 15.3, standard error = 0.9) and highest 

for mixed incidents (mean = 23.1, standard error = 

1.2). Compared to in-person-only incidents, emotional 

impact scores for victims were significantly lower for 

technology-only incidents (p < .05) and significantly 

higher for mixed-harassment incidents (p < .05). It 

follows that emotional impact scores were significantly 

higher for youth victimized in mixed-harassment 

incidents than for youth harassed in technology-only 

incidents (p < .001).19

Thus, mixed-harassment incidents produced the highest 

negative emotional impact. Other features that increased 

the likelihood of emotional harm included physical 

VICTIMS’ RESPONSES TO AN INCIDENT OF HARASSMENT 

Before asking the harassed youth a series of specific details about an incident, 

interviewers asked them to briefly describe, in their own words, what happened. 

Below are examples of the victims’ responses.

In-person-only harassment incidents

• 12-year-old male: “We were eating lunch and one of the kids sitting nearby 

me called me something. Some of the kids that heard it joined in and kept 

rubbing it in and making it worse.” 

• 11-year-old female: “Someone said something that was not true and spread it 

around the school, and then people started looking at me in a funny way.”

• 15-year-old female: “We were taking pictures for the school play and a girl 

who didn’t like me pushed me on the floor in front of the play director because 

she wanted to be in the middle. I had a bruised elbow and I got a restraining 

order against her because of it.”

• 10-year-old male: “I was playing outside with my friends and big girls came 

over here and called me names, hit me, kicked me, and literally tried to kill me, 

like pushing me in the road.”

Technology-only harassment incidents

• 12-year-old female: “This girl got very jealous of me, and she didn’t like me 

having other friends, and she started calling me all these names, and I just 

blocked her from Facebook and other things. This happened two times. She 

got on her grandma’s Facebook and was messaging me that she wasn’t friends 

with me but she was messaging me.”

• 18-year-old male: “My ex-girlfriend’s new boyfriend sent a text message 

threatening to beat me up.”

• 14-year-old female: “It was on Instagram. There were two girls, and the 

girls were being rude, and they were calling me names and said I was ugly. I 

blocked them.”

Mixed-harassment incidents

• 15-year-old female: “I got in a fight last year and people keep posting it on 

Facebook. The comments made on there are ridiculously rude. I got cut down 

and called fat, was told fat people should not fight a skinny person and that I 

should be ashamed of myself.”

• 19-year-old female: “I had two girls who were, at one point, friends. 

They started talking about my boyfriend, saying things that weren’t true.

(Continued on page 8)
8 n J u s t i c e R e s e a r c h

VICTIMS’ RESPONSES TO AN INCIDENT OF HARASSMENT

They were prank-calling me and my boyfriend for a few years. They were

saying I was pregnant. They made an Instagram page calling me names, and 

they said I made the page, even though it was kind of fake. They made it look 

like I made the fake page.”

• 16-year-old female: “I have a stalker ex-boyfriend, and he likes to bother my 

whole family. He is a hacker, so he can hack into all my friends’ accounts, and 

pretends to be my friend, but I can tell.”

(Continued from page 7)

injury, exclusion, a perpetrator who was using alcohol or 

drugs, a social power differential between the victim and 

perpetrator and the perpetrator being a schoolmate or 

acquaintance. The ability to stop the harassment reduced 

the likelihood of a negative emotional impact. Girls and 

white, non-Hispanic youth were more likely to report a 

negative emotional impact from harassment incidents.

The Role of Youth Bystanders

Eighty percent of the 311 peer harassment incidents 

involved the presence of at least one youth bystander 

in addition to the respondent and the perpetrator.20

Sixty-five percent involved one to 10 bystanders, 24 

percent involved 11 to 25 bystanders, and 12 percent 

involved more than 25 bystanders. There were no 

significant differences between the groups of one or 

more bystanders, but 26 or more bystanders witnessed 20 

percent of technology-only incidents, compared to three 

percent of in-person incidents. 

The most common youth bystander reactions during 

harassment incidents were supportive in nature. In 70 

percent of incidents, victims reported that a bystander 

tried to make them feel better. In 55 percent of the 

incidents, a bystander told the victim that they were 

sorry it happened, and in 53 percent of the incidents, a 

bystander told the harasser to stop. Ambiguous responses 

were common in about half of the incidents. Bystanders 

avoided the harasser (58 percent), came closer or stayed 

to see the harassment happen (51 percent) or left the 

situation (43 percent). In some cases, bystanders tried to 

intervene to help the victim — in 43 percent of incidents, 

a bystander told an adult what happened, and in 26 

percent of the incidents, a bystander tried to get other 

youth to help or threatened the perpetrator (27 percent) 

in an attempt to stop the harassment. 

Negative bystander behaviors were less common. In 24 

percent of incidents, bystanders joined in or made the 

harassment worse. In 23 percent of incidents, bystanders 

laughed at the victim. Incidents that involved both 

in-person and technology elements were more likely 

than those that only occurred in person and those that 

only occurred online to involve bystanders who told the 

victim they were sorry it happened, talked with other 

kids to get them to help, came closer or stayed to see 

the harassment happen or joined in the harassment and 

made it worse. 

Harassment Victimization in the 

Broader Context of Violence Exposure

The researchers were able to draw on data from 

NatSCEV II at wave 1 and the Technology Harassment 

Victimization study at wave 2 to examine predictors and 

risk factors for technology-involved harassment. 

Youth who experienced mixed-harassment victimization 

at wave 2 reported the highest average number of 

different types of prior victimization (mean = 8.4), 

were most likely to be lifetime polyvictims (34 

percent) at wave 1, and were more than four times 

as likely than nonpolyvictims to experience mixedharassment victimization two years later. Specific 

types of victimization at wave 1 were more predictive 

of later mixed-harassment results at wave 2, including 

prior life adversity events, prior Internet victimization, 

physical assault, property crime incidents, peer-sibling 

victimization, sexual victimization and exposure to 

community violence. 

Study Limitations

The limitations of this research should be kept in 

mind when interpreting the findings. The main focus 

of the study was on technology-involved harassment, 

so such incidents are slightly overrepresented. Youth’s 

need to respond to answers in a way that they thought 

the interviewers expected may have influenced their 

responses. Unmeasured factors, such as a greater 

willingness among some respondents to disclose personal 

experiences, may have influenced some findings. Finally, 
T h e R o l e o f T e c h n o l o g y i n Y o u t h H a r a s s m e n t V i c t i m i z a t i o n n 9

the measures used to record levels of distress during 

incidents were limited when compared to standard 

trauma measures.

Implications for Future Research

This research makes an important contribution as one 

of the first national studies to provide detailed incidentlevel data on the role of online technology in youth 

harassment and to explore the connection between 

harassment victims’ experiences and prior victimizations 

across a range of domains. These findings point to several 

important areas for future inquiry. 

First, the finding that certain incident features (e.g., 

physical injury and the victim’s or bystander’s ability 

or willingness to stop the incident) and perpetrator 

characteristics (e.g., social power differential, the 

relationship between the victim and aggressor and 

the involvement of alcohol or drugs) correlated more 

strongly to emotional harm than the use of technology 

speaks to the important role of context. Future research 

may reveal how these factors play out in the daily 

victimization experiences of youth. 

Second, the fact that this study examined harassment at 

the incident level as well as the participant level provided 

a unique vantage point. The use of a broad range of 

methods and approaches is required to advance the 

science. Yet, since this approach only collected data on as 

many as two incidents, detailed information was missing 

from those youth who experience high numbers of 

harassment incidents and it may not capture all “mixed 

harassment” experiences if they were not identified as 

being part of the same incident. Next steps may be to 

examine repeated victimization experiences that involve 

different perpetrators, within and across domains, to 

further explore the complexity of these relationships and 

the impact on youth experiences. 

Third, the range of bystander behaviors reported across 

types of incidents suggests that it is not useful to think 

of bystander behavior as simple; it can be quite complex 

and contradictory. More research on the impact of a 

range of bystander behaviors, both positive and negative, 

on youth outcomes may guide the development of more 

useful intervention and prevention efforts. 

Fourth, the findings that link prior polyvictimization to 

the increased likelihood of youth experiencing mixedharassment incidents is consistent with previous research 

on populations that experience polyvictimization. 

Longitudinal research could explore the developmental 

pathways associated with or resulting in a range of 

victimization experiences over time. This type of research 

may identify potential interventions where victims 

can learn how to prevent or reduce the impact of these 

incidents in the future. 

Finally, understanding the role that gender, ethnicity 

and other relevant demographic variables have in these 

processes would provide valuable insights. Future work 

with more specific subsamples could explore some of the 

preliminary findings related to gender and ethnicity.

Implications for Policy and Practice

There has been a great amount of public anxiety 

around the use of technology in peer harassment and 

bullying incidents (i.e., cyberbullying). Experts have 

expressed concern that technology-based harassment 

and bullying could cause greater harm than traditional 

forms because content can be transmitted anonymously, 

involve many other youth quickly and reach victims 

anywhere and at any time.6,9,10,21 Findings from the 

Technology Harassment Victimization study are both 

reassuring and a cause for concern. It is reassuring that 

technology-only peer harassment is the least distressing 

kind of harassment for youth and the least likely to 

involve features that are assumed to amplify harm.6,8,10,21

Technology-only incidents were easier to stop than 

in-person-only incidents and were less likely to involve 

other harassment characteristics that research has 

shown to be related to greater distress, such as multiple 

perpetrators and power imbalances.22

The picture becomes more complex, however, when 

considering the impact of mixed-harassment incidents, 

which include both in-person and online technology 

elements. These incidents were the most distressing for 

their victims and shared many features with in-persononly harassment, such as repeated harassment over 

time and the involvement of victims and aggressors in 

deeper relationships. These findings do not mean that 

technology-only incidents are not sometimes serious 

— only that, when mixed-harassment environments are 

in play, the likelihood of more serious consequences is 

increased. 
1 0 n J u s t i c e R e s e a r c h

Mixed-Harassment Incidents, 

Young Victims and Their Peers

Youth who experienced mixed forms of harassment said 

they could not get away from the harassment because 

they were being victimized across multiple environments 

at school, at home and with online technology. The 

perpetrators were often current or past friends or 

romantic partners and thus more likely to know personal 

details about their victims. Texting was the predominant 

type of technology used in mixed-harassment incidents,19

suggesting that these interactions were more direct and 

private than communication through websites or social 

networking pages. 

Even after controlling for a wide range of possible 

aggravating factors, mixed-harassment incidents 

remained significantly more distressing for youth than 

either in-person or technology-only harassment. It is 

possible that when harassment incidents happen in 

multiple contexts, the perpetrators have more animosity 

toward their victims and the harassment is more personal 

or meaningful in ways that are difficult to measure. It 

is telling that the types of emotional reactions from 

victims of mixed-harassment incidents were most often 

anger, sadness and lack of trust,19 and the incidents were 

marked by more intense, personal and complex negative 

interactions that had high emotional salience for those 

involved. 

Peer harassment and bullying typically occur in the 

presence of other youth,23,24 and many prevention 

programs focus their educational efforts on bystanders 

to shift social norms and provide youth with the skills to 

support victims.25 To be successful, however, prevention 

education must address and provide solutions for the 

various ways that bystanders react during and after 

incidents, different types of incidents, all levels of severity 

and in different contexts, including emerging contexts. The 

current study has attempted to address these issues. 

Bystanders play an active role in 80 percent of harassment 

incidents and can offer to help or support the victim, watch 

what happens, leave the scene or, much less often, join in 

the harassment. There were no clear differences in how 

bystanders reacted in terms of technology involvement, but 

mixed-response incidents had the highest rates of bystander 

activity, both positive and negative, suggesting that some 

types of harassment are more likely to draw involvement 

from extended peer groups. 

Youth experiencing mixed-harassment incidents are the 

most likely to have been polyvictims: prior victims of 12 

or more types of victimization. Not only do polyvictims 

experience the highest negative emotional impact from 

harassment, but they are also more likely to have elevated 

rates of delinquency, trauma and lifetime adversity. 

Conclusion

The results of this study appear to indicate that — among 

mixed-, in-person- and technology-only peer harassment 

incidents — technology-only harassment is the least 

distressing to young victims. This finding does not 

mean that harassment involving the use of technology 

alone cannot be severe or damaging. However, the data 

from this study and others suggest that focusing solely 

on victimization involving the use of technology as a 

research priority topic could distract educators and 

policymakers from a deeper understanding of the types 

of peer victimization that are actually the most harmful 

to youth. 

What the data clearly reveal is that mixed-peer harassment 

— involving both in-person- and technology-based 

elements — is the most traumatic for victims, especially 

those who have been victimized in multiple ways in the 

past and are facing numerous stressors in their present 

lives. Finding ways to prevent and successfully intervene 

in mixed and in-person peer harassment incidents is a 

productive focus for future research.

For More Information

This bulletin was adapted from Mitchell, K.J., L.M. Jones, 

H.A. Turner, A. Shattuck and J. Wolak, “The Role of 

Technology in Peer Harassment: Does It Amplify Harm for 

Youth?,” Psychology of Violence 6 (2) (2016): 193-204, http://

www.apa.org/pubs/journals/releases/vio-a0039317.pdf.

For more information about the National Survey of 

Children’s Exposure to Violence (NatSCEV), visit the 

Crimes against Children Research Center website, 

http://www.unh.edu/ccrc, and access the Office of 

Juvenile Justice and Delinquency Prevention’s NatSCEV 

publication series at http://www.ojjdp.gov/publications/

PubResults.asp?sei=94.

For more information about the Technology Harassment 

Victimization study, download the final report: 

https://www.ncjrs.gov/pdffiles1/nij/grants/249003.pdf.
T h e R o l e o f T e c h n o l o g y i n Y o u t h H a r a s s m e n t V i c t i m i z a t i o n n 1 1

Endnotes

1. Jones, L.M., K.J. Mitchell and D. Finkelhor, “Online 

Harassment in Context: Trends From Three Youth 

Internet Safety Surveys (2000, 2005, 2010),” Special 

Issue: Technology and Violence: Risk, Prevention, 

Intervention, and Methodology, Psychology of 

Violence 3 (1) (2013) 53-69. 

2. Ybarra, M.L., K.J. Mitchell and D. Espelage, 

“Comparisons of National Bully Victimization Rates 

at School and via Technology,” in Pediatrics, Book 

2, ed. O. Ozdemir and F. Ovali, Istanbul, Turkey: 

InTech - Open Access Publisher, in press. 

3. Wang, J., R.J. Iannotti and T.R. Nansel, “School 

Bullying Among Adolescents in the United States: 

Physical, Verbal, Relational, and Cyber,” Journal of 

Adolescent Health 45 (4) (2009): 368-375.

4. Robers, S., J. Zhang and J. Truman, Indicators of 

School Crime and Safety: 2010, Washington, D.C.: U.S. 

Department of Justice, Office of Justice Programs; 

U.S. Department of Education and Bureau of Justice 

Statistics, National Center for Education Statistics, 2010.

5. Ybarra, M.L., M. Diener-West and P.J. Leaf, 

“Examining the Overlap in Internet Harassment 

and School Bullying: Implications for School 

Intervention,” Journal of Adolescent Health 41 

(6, Suppl.) (2007): S42-S50.

6. Fredstrom, B.K., R.E. Adams and R. Gilman, 

“Electronic and School-Based Victimization: 

Unique Contexts for Adjustment Difficulties 

During Adolescence,” Journal of Youth & 

Adolescence 40 (4) (2011): 405-415.

7. Hinduja, S., and J.W. Patchin, “Cyberbullying: 

An Exploratory Analysis of Factors Related to 

Offending and Victimization,” Deviant Behavior

29 (2) (2008): 129-156.

8. Kowalski, R.M., and S.P. Limber, “Electronic 

Bullying Among Middle School Students,” Journal of 

Adolescent Health 41 (6, Suppl.) (2007): S22-S30.

9. Mishna, F., M. Saini and S. Solomon, “Ongoing and 

Online: Children and Youth’s Perceptions of Cyber 

Bullying,” Children and Youth Services Review 31 

(12) (2009): 1222-1228.

10. Dempsey, A.G., M.L. Sulkowski, R. Nichols and E.A. 

Storch, “Differences Between Peer Victimization 

in Cyber and Physical Settings and Associated 

Psychosocial Adjustment in Early Adolescence,” 

Psychology in the Schools 46 (10) (2009): 962-972.

11. Juvonen, J., and E.F. Gross. “Extending the School 

Grounds? Bullying Experiences in Cyberspace,” 

Journal of School Health 78 (9) (2008): 496-505.

12. Ybarra, M., K.J. Mitchell, J. Wolak and D. Finkelhor, 

“Examining Characteristics and Associated Distress 

Related to Internet Harassment: Findings from the 

Second Youth Internet Safety Survey,” Pediatrics 118 

(4) (2006): e1169-e1177.

13. Lenhart, A., M. Madden, A. Smith, K. Purcell, K. 

Zickuhr and L. Rainie, Teens, Kindness and Cruelty 

on Social Networking Sites, Washington, D.C.: Pew 

Research Center, 2011.

14. Hamby, S.L., D. Finkelhor, R.K. Ormrod and H.A. 

Turner, The Juvenile Victimization Questionnaire 

(JVQ): Caregiver Version, Durham, N.H.: Crimes 

Against Children Research Center (2004).

15. Hamby, S.L., D. Finkelhor, R.K. Ormrod and H.A. 

Turner, The Juvenile Victimization Questionnaire 

(JVQ): Child Self-Report Version, Durham, N.H.: 

Crimes against Children Research Center (2004).

16. Hamby, S.L., D. Finkelhor, R.K. Ormrod and H.A. 

Turner, The Juvenile Victimization Questionnaire (JVQ):

Administration & Scoring Manual, Durham, N.H.: 

Crimes against Children Research Center (2004).

17. Turner, H.A., D. Finkelhor and R. Ormrod, “The 

Effect of Lifetime Victimization on the Mental 

Health of Children and Adolescents,” Social Science 

& Medicine 62 (1) (2006): 13-27.

18. Turner, H.A., and M.J. Butler, “Direct and Indirect 

Effects of Childhood Adversity on Depressive 

Symptoms in Young Adults,” Journal of Youth and 

Adolescence 32 (2) (2003): 89-103.

19. Mitchell, K.J., L.M. Jones, H.A. Turner, A. Shattuck 

and J. Wolak, “The Role of Technology in Peer 

Harassment: Does It Amplify Harm for Youth?” 

Psychology of Violence 6 (2) (2016): 193-204. 
1 2 n J u s t i c e R e s e a r c h

Points of view or opinions expressed in this 

document are those of the authors and do not 

necessarily represent the official position or 

policies of NIJ, OJJDP, or the U.S. Department 

of Justice.

The National Institute of Justice and the 

Office of Juvenile Justice and Delinquency 

Prevention are components of the Office of 

Justice Programs, which also includes the Bureau 

of Justice Assistance; the Bureau of Justice 

Statistics; the Office for Victims of Crime; and the 

Office of Sex Offender Sentencing, Monitoring, 

Apprehending, Registering, and Tracking.

NCJ 250079

20. Jones, L.M., K.J. Mitchell and H.A. Turner, 

“Victim Reports of Bystander Reactions to 

In-Person and Online Peer Harassment: A National 

Survey of Adolescents,” Journal of Youth and 

Adolescence 44 (12) (2015): 2308–2320.

21. Sticca, F., and S. Perren, “Is Cyberbullying Worse 

Than Traditional Bullying? Examining the Differential 

Roles of Medium, Publicity, and Anonymity for the 

Perceived Severity of Bullying,” Journal of Youth and 

Adolescence 42 (5) (2013): 739-750.

22. Turner, H.A., K.J. Mitchell, L. Jones and A. 

Shattuck, “Assessing the Impact of Harassment 

by Peers: Incident Characteristics and Outcomes 

in a National Sample of Youth,” Journal of School 

Violence (2015), available online at https://doi.org/1

0.1080/15388220.2015.1066257.

23. Craig, W.M., and D.J. Pepler, “Observations of 

Bullying and Victimization in the School Yard,” 

Canadian Journal of School Psychology 13 (2) (1997): 

41-59.

24. Salmivalli, C., “Bullying and the Peer Group: 

A Review,” Aggression and Violent Behavior 15 (2) 

(2010): 112-120.

25. Polanin, J.R., D.L. Espelage and T.D. Pigott, “A 

Meta-Analysis of School-Based Bullying Prevention 

Programs’ Effects on Bystander Intervention Behavior,” 

School Psychology Review 41 (1) (2012): 47-65.