The Prevalence of Potentially Victimizing Events,Poly-Victimization,and Its Association to Sociodemographic Factors

Abstract

Studying the extent to which children are exposed to victimizing events is important to fully understand the effect of such exposure in shaping them as adults. The aim of this study was to use self-report by adolescents to measure the prevalence of victimizing events and of poly-victimization. A representative sample of 5,960 students (aged 17) from high schools in Sweden was given the self-administrated version of the Juvenile Victimization Questionnaire (JVQ) along with questions concerning gender, birthplace, parents’ birthplace and employment, residence, educational program, and municipality size. The results show that 84.1% (83.0% young men and 85.2% young women) of the students had experienced victimization during their lifetime, and 10.3% were categorized as poly-victims (8.1% young men and 12.5% young women; OR = 1.62, 95% confidence interval [CI] = [1.35, 1.94]). Adolescents living with both parents were at lower risk of any form of victimization for both genders, while females were at higher risk of maltreatment, peer victimization, and, most significantly, sexual victimization. In conclusion, the vast majority of young people have been victimized during their lifetime. A greater awareness of the impact of these victimizing events on children and adolescents is important as a basis for providing a safer milieu and establishing better interventions, especially for those that have been victimized on multiple occasions. The high-exposure group was determined by using ≥10 events as a cutoff. Findings on this group corresponded with findings in other international studies regarding distribution, elevated risk for females, and the possibility of limiting the effects of victimization by modifying living conditions.

Keywords

JVQ victim youth poly-victimization sociodemographics

Children are exposed to a variety of adverse events during their childhood, and research has documented high levels of childhood exposure to abuse, violence, and crime. This research has also highlighted the damage that this can cause to their physical and mental health (Augoustinos, 1987; Beitchman, Zucker, Hood, DaCosta, & Akman, 1991; Felitti et al., 1998; Hawker & Boulton, 2000; Kaufman, 1991; Olofsson, Lindqvist, Shaw, & Danielsson, 2012; van Oort, Ormel, & Verhulst, 2012; Wolfe, 1999). International research on children and adolescents has historically focused on specific types of victimizing events, mainly physical and sexual abuse (Brown & Bzostek, 2003), bullying (Nansel, Ovevpeck, Haynie, Ruan, & Scheidt, 2003), community violence (Hill & Jones, 1997), and domestic violence (Wolak & Finkelhor, 1998). Some researchers have specialized in studying a specific type of victimization, along with the associated symptoms and negative psychosocial development (DuRant, Getts, Cadenhead, Emans, & Woods, 1995; Fantuzzo et al., 1991). Researchers have also studied the link between psychological disorders and specific forms of maltreatment, such as child physical abuse (Dodge, Pettit, & Bates, 1997; Toth, Manly, & Cicchetti, 1992), child sexual abuse (Browne & Finkelhor, 1986; Feiring, Taska, & Lewis, 2002), neighborhood violence (Osofsky, Wewers, Hann, & Fick, 1993; Richters & Martinez, 1993), peer bullying (Bond, Carlin, Thomas, Rubin, & Patton, 2001; Espelage & Holt, 2001), and witnessing parental violence (Edleson, Mbilinyi, Beeman, & Hagemeister, 2003; Kitzmann, Gaylord, Holt, & Kenny, 2003).

Finkelhor and others (Finkelhor, Ormrod, & Turner, 2007b; Turner, Finkelhor, & Ormrod, 2006) argue that by focusing on specific victimization variables, we are likely to underestimate the degree to which children are exposed to victimization and, thus, underestimate its full impact, and also underestimate the correlation between victimization and child mental health (Turner et al., 2006). Focusing on specific types of victimization can lead to a serious overestimation of the impact of that specific type of victimization because outcomes may be related to other events (Finkelhor et al., 2007b). A fragmented approach to children’s exposure to victimization may also hamper the identification of the most frequently victimized children, who are at the greatest risk of serious mental health problems and who have the greatest need for intervention.

Using data from a large national representative study, we examined the prevalence of both a large number of potentially victimizing events and poly-victimization in the lives of young Swedish students. Second, because previous researchers have called attention to the lack of detailed analysis of the impact of sociodemographic factors on frequency of exposure to victimizing events, we have focused on sociodemographic factors.

Prevalence

Several studies have been published that used screening instruments adapted to the complexity of multiple exposures to victimization. These instruments are psychometrically sound and are frequently used, but we have found several limitations in using them given our aims. The Childhood Trauma Questionnaire (CTQ; Bernstein et al., 1994) lacks questions about the perpetrator, and the continuous scaled questions are not ideal for measuring prevalence. The Life Incidence of Traumatic Experiences (LITE; Greenwald & Rubin, 1999) was found by us to be limited in the number of events measured. The Linköping Youth Life Experience Scale (LYLES; Nilsson, Gustafsson, Larsson, & Svedin, 2010) lacks information about the time when the event occurred. As our ambition was to describe the full extent of victimization and to compare the results internationally, the Juvenile Victimization Questionnaire (JVQ) was chosen as it covers most types of events and includes a great variety of locations and perpetrators (Hamby & Finkelhor, 2001; Hamby, Finkelhor, Ormrod, & Turner, 2004).

Assessing children and adolescents (2-17 years) with the JVQ, Finkelhor, Ormrod, and Turner (2009b) found lifetime victimization (LT) to be very common (79.6%), with a mean of 3.7 different types of victimization. Studies that used the JVQ or modified versions have reported that between 63% and 88.4% of youth experienced victimization in the previous year (measuring victimization in the most recent 12 months of the adolescents’ life; Soler, Paretilla, Kirchner, & Forns, 2012; Ellonen & Salmi, 2011). When using age groups similar to our sample (15-17 years), Cyr et al. (2013) found lifetime prevalence of 87%. Radford et al. (2011) reported that 18.6% of the 11- to 17-year-olds in their NSPCC (National Society for the Prevention of Cruelty to Children) study had experienced severe maltreatment during childhood.

There are few Swedish studies of child and adolescent victimization by peers and adults. Of these, only two studies used comprehensive questionnaires that covered a broad array of potentially traumatic events. In the first (Nilsson, Gustafsson, & Svedin, 2010), two cross-sectional samples of school-aged children (N = 270) and adolescents (N = 400) answered LITE. Of the respondents, 63% of schoolchildren and 89.5% of adolescents reported experiencing at least one traumatic event during their childhood. In the other study, 188 adolescents aged 17 years completed the LYLES (Nilsson, Gustafsson, Larsson, & Svedin, 2010). The LYLES instrument was developed from the LITE instrument but includes additional questions that cover more chronic adverse childhood circumstances (ACCs). Almost all adolescents (99.5%) had experienced one lifetime traumatic event. Those with greater exposure to potentially traumatic events reported more ACCs per unit time.

Sociodemographics and Risk Factors

Most studies have not accounted for the complexity and impact of sociodemographic background on the occurrence of victimization or poly-victimization. However, Finkelhor, Ormrod, Turner, and Holt (2009) did consider sociodemographic background and identified four distinct pathways to becoming a poly-victim: (a) residing in a dangerous community, (b) living in a dangerous family, (c) living in a chaotic and complex family environment, and (d) having emotional problems. Other studies have shown that living in a dangerous neighborhood increases the risk of being exposed to community violence (Cohen, Mannarino, Murray, & Igelman, 2006) as does living in a family where domestic violence occurs (Annerbäck, Wingren, Svedin, & Gustafsson, 2010). Poly-victims and victimized children are less likely to come from intact, two-parent families than from single-parent households (Berger, 2004; Finkelhor, Ormrod, & Turner, 2009a; Radford et al., 2011) or reconstituted families (Ondersma, Delaney-Black, Covington, Nordstrom, & Sokol, 2006; Turner, Finkelhor, & Ormrod, 2007). Low household income has also been shown to increase the risk of assault with dangerous weapons, attempted assault, multiple peer assault, rape or attempted rape, and emotional abuse (Finkelhor, Ormrod, Turner, & Hamby, 2005b). Being exposed to neglect, harsh verbal treatment, physical violence, and coerced sexual activity was more common among children from lower social classes (more disadvantaged groups; Radford et al., 2011) than among children from higher social classes. Furthermore, parental factors such as illness, psychiatric problems, and substance abuse have all been found to increase the risk of victimization (Ondersma et al., 2006). Poly-victimized children were substantially more likely to have a parent with an enduring physical disability, learning disabilities, or mental health issues (Radford et al., 2011). Finally, Finkelhor and coworkers (2009), in their poly-victimization pathway study, highlighted the significance of a child having emotional problems that increase risk behavior, engender antagonism, and compromise the child’s capacity to protect himself or herself (especially among younger children), resulting in an increased risk for being poly-victimized.

To summarize, it is difficult to compare victimization levels in different countries and cultures due to differences in the approaches to research on victimization. Also, most studies do not consider the importance of sociodemographic factors in the understanding of children’s vulnerability. The aim of this study was to provide the first comprehensive epidemiological surveys of child victimization, including poly-victimization, in Sweden. Through using a nationally representative sample of adolescents, we specifically set out to study the lifetime prevalence of victimization and poly-victimization in adolescents, and how these relate to a multitude of background factors.

Method

Subjects

Sweden consists of 290 municipalities, which are classified into nine categories according to Swedish Association of Local Authorities and Regions (SKL) on the basis of structural parameters such as population, commuting patterns, and economic structure, using a system that was developed by the Swedish Association of Local Authorities and Regions (SALAR, 2009). The goal for the sampling procedure was to obtain a representative sample (approximately 5%) of high school students aged 17 (Swedish upper secondary grade school, Year 2) evenly distributed among the nine SKL categories. All Swedish youth who have completed compulsory school are entitled to three years of upper secondary school education. Students enter at age 16 and can study until the age of 20. The upper secondary school offers three programs: (a) higher education preparatory programs, typically including humanities, natural science, and social science; (b) vocational programs, such as health and social care, building and construction, hotel management, and tourism; and (c) introductory programs, such as preparatory education, program-oriented individual options, vocational introduction, individual alternative, and introductory language (The Swedish National Agency for Education, 2013).

Municipalities and schools were selected from the registers of the Swedish National Agency for Education (2007) to represent the national average concerning gender, birthplace, enrollment from other municipalities, and educational program. From a geographical perspective, the selection of municipalities and schools was made based on convenience; if two schools were similar within the same category, the school that was easiest to reach was selected. If possible, all high schools in a municipality were chosen. One municipality category, which includes sparsely populated municipalities (SKL 5), was omitted due to lack of high schools. All schools were public schools, except for some private schools in the SKL 3 category.

A total of 53 schools were asked to participate in the survey, of which two schools declined to participate. One reported that the school had already participated in other surveys, and the other school did not present any reason. The 51 participating schools enrolled a total of 7,849 high school students (upper secondary school, year two). A total of 6,096 students (78%) were present at the time of the scheduled survey. The missing students were absent by plan or absent without notice (skipping class). Out of the 6,096 students present, 136 were missing. Another 82 students were not willing or able to complete the survey, and, in addition, 54 cases were lost due to “other” (unknown issues). In summary, external attrition was 22%, and internal attrition was 2.2%. Overall attrition rates are good for this type of study. We could speculate that the dropout group consists of a greater percentage of students of lower socioeconomic status than the non-dropout group, and therefore, students from the dropout group may have had more experience of victimization than those of the non-dropout group.

The sample corresponds well regarding distribution in municipality categories with ±10% variation from the goal. The sample of 5,960 students had an even distribution of men (50.4%) and women (49.6%) and a mean age of 17.3 years (range = 16 to 20 years; SD = 0.652), which represented 4.5% of all 17-year-olds in Sweden (Statistics Sweden, 2014). The original nine-category sample was condensed to three municipality categories with 17.1% of the sample in large municipalities (>200,000 inhabitants), 47.9% in medium municipalities (50,000 to 200,000 inhabitants), and 35% in small municipalities (<50,000 inhabitants).

The majority of sociodemographic variables were in line with population measures. The study group had a higher percentage of adolescents residing with both parents than observed in the total population, and the parents had a higher unemployment rate than the rate in the total population. For sociodemographic data concerning adolescent birthplace, parents’ birthplace and employment, residence, and educational program, see Table 1.

Table 1.

Sociodemographic Data (N = 5,960).

Variable	Sample		Reference Group
Variable	%	n	%
Gender^a
Male	50.4	3,002	51.6
Female	49.6	2,958	48.4
Birthplace: Adolescent^a
Sweden	91.1	5,428	91.0
Europe	4.1	247	2.4
Outside Europe	4.8	285	6.6
Birthplace: Parents^a
Both parents born in Sweden	78.5	4,679	81.5^b
One or both in Europe	8.6	510	18.0^b
One or both outside Europe	12.9	771	—
Employment parents^a
Both employed	68.9	4,107	87.3^c
At least one unemployed^d	31.1	1,853	12.7
Residency^a
Both parents^e	75.1	4,478	59.2
One parent	19.9	1,185	39.9
Alone or other	5.0	297	0.9
Education program^a
Theoretical	44.4	2,648	34.6^f
Practical	54.0	3,219	55.7^f
Introductory	1.6	93	9.8^f
Municipality size (inhabitants)^a
Large: >200,000	17.1	1,018	21.2^g
Medium: 50,000 to 200,000	47.9	2,857	46.6^g
Small: <50,000	35.0	2,085	32.2^g

Note. All values in percent. SCB (Statisc Sweden) registers contain data of the population by sex, age, marital status, country of birth and citizenship for all of Sweden, in each county, in county-blocks, metropolitan areas, and in each municipality. Asylum-seekers who have not yet obtained a permit to stay are not included in the population statistics. In 2008, there was a total population of 9,256,347: male = 4,603,710; female = 4,652,637. Total number of 17-year-olds was 131,366: male = 67,836; female = 63,530. The Swedish National Agency for education report total second grade students at 83,953: male = 42,097; female = 41,856. SCB =

Variable put into the multiple logistic regression analysis.

Statistics Sweden, both within and outside Europe, biological born abroad or adopted abroad excluded.

Statistics Sweden, Unemployment 15 to 74 years.

Unemployment = unemployed, being a student, on parental leave, not working due to disability or chronic or temporary illness.

Living with both parents of origin or alternate residence.

The Swedish National Agency for Education.

Statistics Sweden, three categories made from nine SCB categories.

The students were grouped into the theoretical program (n = 2,648, 44.4%), vocational program (n = 3,219, 54.0%), or introductory program (n = 93, 1.6%).

Procedure

A standardized information letter was sent to 51 schools following the initial contact and request to conduct the survey. Participating schools were asked to set up a suitable room for the survey, arrange a schedule, and appoint a teacher responsible for each class. School registers were updated with the help of the appointed teacher. Student attendance was noted on the register. All students were initially given one printed page providing information about the project, including contact information for local counseling services in the event that answering the questions made them very uneasy. Prior to data collection, the students were informed that they would be anonymous and that they were free to refuse participation.

The survey was administered on PCs provided by the school or the researcher, and the researcher was present for information and answering any questions that may have arisen. None of the items could be omitted, limiting internal attrition on the item level. The students completed the survey in 30 to 40 min and were given a movie voucher. Data collection took place during 2008-2009. The Regional Ethical Review Board in Linköping approved the study.

Measures

The introductory survey asked for information about location, gender, birthplace, age, education program, parents’ birthplaces, parents’ employment, and residence. This survey was followed by five questionnaires: (a) Child Self-Administered Questionnaire of the Juvenile Victimization Questionnaire (SAQ/JVQ), (b) the LITE, (c) the Strengths and Difficulties Questionnaire (SDQ), (d) the Social Phobia Scales Questionnaire for Children (SPSQ-C), and (e) the Trauma Symptom Checklist for Children (TSCC). Certain questions regarding peritraumatic reactions were added to the JVQ. The four final questions were on debut age and consumption level of alcohol, age of first sexual experience, contact with professionals, BRIS (Children’s Rights in Society), school psychologist, school counselor, social worker, child psychiatrist, or other psychiatry professionals), and finally whether respondents were ever medicated for mood disorder, hyperactivity, or insomnia. This article will only present the findings for the introductory questions and the SAQ/JVQ.

The JVQ was designed to be a more comprehensive instrument than instruments used in previous research. The JVQ inventory included most major forms of offense against young people, including non-violent victimization and other events not typically conceptualized as crimes (Finkelhor et al., 2005b). The JVQ obtains reports on 34 forms of offense against young people that cover five general domains of concern: Conventional Crime, Child Maltreatment, Peer and Sibling Victimization, Sexual Victimization, and Witnessing and Indirect Victimization. For the purpose of the current research, a modified self-administered version of the questionnaire (SAQ) was used. One item section concerning sexual victimization, the item that asked, “Did you do sexual things with anyone 18 years or older, even things you both wanted?” was excluded due to differences in the legal systems between the United States and Sweden. This resulted in a total of 33 JVQ items. LT was assessed by asking for prior year (PY) number of occasions and before prior year (BPY) number of occasions. If victimization occurred in PY and/or BPY and resulted in injury or the need for medical attention, the participant was instructed to answer follow-up questions regarding peritraumatic reactions and perpetrator characteristics.

The JVQ has been tested for construct validity using TSCC (Briere, 1996), measuring trauma symptoms. The JVQ shows moderate but significant correlations with trauma symptoms for all the domains (Pearson’s r = .14 to .35) and for most screener items as well. The correlations are in the same range as those found in most assessments of community samples of victimized children (Finkelhor, Hamby, Ormrod, & Turner, 2005). The JVQ has been tested for reliability. Overall, concerning test–retest, there was an agreement after 3 to 4 weeks of the results from 100 adolescents with a 95% range (77-100), and the test–retest reliability was good (Pearson’s r = .59). The Cohen’s kappa (κ) for screener items ranged between .22 and 1.0 with a mean of κ = .63 (Finkelhor et al., 205). Internal consistency reliability is reported for the full scale JVQ as Cronbach’s alpha with a value of .80. The Cronbach’s alpha varied between the five domains from .35 to .64 (Finkelhor et al., 2005). The internal consistencies (Cronbach’s α) in this survey were as follows: for the full JVQ scale, α = .83; for Conventional crime, α = .66; Child Maltreatment, α = .55; Peer and Sibling Victimization, α = .52; Sexual Victimization, α = .64; and Witnessing and Indirect Victimization, α = .51. Polyvictimization was operationalised by a simple count of endorsed screeners from the JVQ (“endorsed” denotes a yes response to a victimization screener question), using the so-called Screener Sum Version (SSV; Finkelhor, Ormrod, Turner, & Hamby, 2005a). Poly-victimization was defined as the most extreme 10% of the sample corresponding to 10 or more events during a lifetime.

Statistical Analyses

The prevalence rates are reported as point prevalence. For categorical variables, group differences were calculated by the use of chi-squared analysis. Differences in means were analyzed using an independent samples t test. Logistic regression was used to assess the odds of presenting with victimization in relation to gender, birthplace, parents’ birthplace and employment, residence, educational program, and municipality size. Multiple logistic regression analysis was performed to evaluate the background items’ mutual relationships concerning total JVQ, the five domains, and poly-victimization. All analyses were performed using SPSS version 19.0 (SPSS, Inc., Chicago, Il, USA).

Background Variables

A series of Spearman rank-order correlations was conducted to determine if there were any significant relationships between the dependent variables (matrix not shown). The parents’ birthplace was related to the adolescent’s place of birth, r_S (5958) = .509, p < .01. Parental employment was related to parents’ place of birth, r_S (5958) = .292, p < .01, and to adolescent’s place of birth, r_S (5958) = .214, p < .01. The adolescent’s residence was related to gender, r_S (5958) = −.069, p < .01; parents’ place of birth, r_S (5958) = .050, p < .01; and to parents’ employment, r_S (5958) = .249, p < .01. Education program was related to gender, r_S (5958) = .059, p < .01; adolescent birthplace, r_S (5958) = −.055, p < .01; parents’ birthplace, r_S(5958) = −.146, p < .01; parents’ employment, r_S (5958) = .050, p < .01; and residence, r_S (5958) = .126, p < .01. The findings were that only the parents’ birthplace and the adolescent’s birthplace correlated strongly.

Results

Lifetime Prevalence and Gender

LT was found in 84.1% of the sample (males = 83.0%, females = 85.2%), and, in relation to the five domains, 66.4% had experienced conventional crime, 24% child maltreatment, 54.4% peer and sibling victimization, 21.8% sexual victimization, and 54% had experienced witness victimization. Females experienced significantly more child maltreatment, χ²(1, 5332) = 184.22, p < .001; peer and sibling victimization, χ²(1, 5960) = 21.42, p < .001; sexual victimization, χ²(1, 5960) = 447.51, p < .001; and witnessed victimization, χ²(1, 5960) = 4.74, p < .001. Males experienced significantly more conventional crime in their lifetime, χ²(1, 5332) = 16.58, p < .001. (For more detailed information concerning different screening items, see Table 2.)

Table 2.

Prevalence of Lifetime Victimizing Events: Gender and Birthplace (N = 5,960).

Variable	Gender		χ²	p	Birthplace^a			χ²	p
	Male	Female			Swedish	EU	Non-EU
	n = 3,002	n = 2,958			n = 5,428	n = 247	n = 285
	%	%			%	%	%
Total^b	83.0	85.2	4.90	*	84.0	86.8	82.2	1.90
Conventional crime^b	69.0	63.7	16.58	***	66.0	72.7	68.5	4.75
1. Robbery	16.0	12.1	17.99	***	13.6	20.2	17.9	12.33	**
2. Personal theft	41.2	43.3	2.87		41.9	48.2	43.9	4.14
3. Vandalism^b	27.6	24.2	8.10	**	25.6	28.2	30.7	3.68
4. Assault with a weapon	15.4	11.6	18.36	***	12.9	22.3	17.2	21.17	***
5. Assault without a weapon^b	39.0	30.1	46.91	***	34.5	37.3	35.7	0.81
6. Attempted assault	19.0	10.2	90.51	***	14.5	17.0	15.4	1.36
7. Kidnapping	2.0	2.3	0.51		2.0	3.6	4.2	9.45	**
8. Bias attack (hate crimes)	5.7	4.7	2.61		4.5	12.1	13.3	68.46	***
Child maltreatment	16.6	31.6	184.22	***	23.4	27.1	33.0	15.01	***
9. Physical abuse by caregiver	9.1	15.4	56.00	***	11.5	17.4	22.5	36.75	***
10. Psychological/emotional abuse	8.9	22.3	205.44	***	15.1	18.6	21.1	9.17	*
11. Neglect	3.0	6.6	42.01	***	4.8	4.0	4.9	0.33
12. Custodial interference/abduction	2.5	3.9	8.83	**	3.2	3.2	2.5	0.54
Peer/sibling victimization	51.5	57.4	21.42	***	55.1	52.6	43.5	14.96	***
13. Gang or group assault	15.9	6.8	121.49	***	11.3	14.2	10.9	2.06
14. Peer or sibling assault	21.7	25.7	13.24	***	23.9	23.5	19.3	3.20
15. Nonsexual genital assault	11.8	2.3	201.21	***	6.9	10.1	8.4	4.61
16. Bullying	14.6	23.4	75.69	***	19.4	13.8	15.1	7.85	*
17. Emotional bullying	19.7	34.6	168.26	***	27.6	22.7	21.1	8.36	*
18. Dating violence	9.9	11.3	3.08		10.6	13.4	7.4	5.14
Sexual victimization	10.6	33.2	447.51	***	22.2	20.2	16.8	4.87
19. Sexual assault by known adult	1.1	5.7	97.83	***	3.4	4.5	2.8	1.14
20. Nonspecific sexual assault	0.9	3.9	58.90	***	2.3	3.6	2.5	1.85
21. Sexual assault by peer	1.1	8.4	177.17	***	4.7	4.9	4.2	0.16
22. 22. Rape: Rape and attempted rape	2.6	14.7	278.71	***	8.8	9.7	5.3	4.57
23. Flashing/sexual exposure	2.7	7.4	69.01	***	5.1	4.9	3.9	0.89
24. Verbal sexual harassment	6.3	18.2	195.85	***	12.4	10.1	9.5	3.21
Witnessing and indirect victimization	52.7	55.5	4.74	*	53.7	61.9	53.7	6.45	*
26. Witness to domestic violence	4.1	9.3	64.93	***	6.1	10.1	13.7	30.02	***
27. Witness to parent assault of sibling	3.0	6.5	40.33	***	4.3	7.3	10.2	24.26	***
28. Witness to assault with a weapon	20.1	18.3	2.88		18.9	26.3	19.3	8.46	*
29. Witness to assault without a weapon	35.4	32.8	4.54	*	34.8	32.0	23.2	16.80	***
30. Burglary of family household	12.9	16.3	14.12	***	14.8	14.2	11.9	1.77
31. Murder of family member or friend	4.0	4.9	2.67		3.7	10.5	13.0	77.70	***
32. Witness to murder	2.1	0.5	26.81	***	1.0	4.9	3.9	42.12	***
33. Exposure to random shootings. terrorism	9.5	6.2	22.11	***	6.8	19.8	17.5	94.85	***
34. Exposure to war or ethnic conflict	2.6	2.2	1.04		1.0	20.2	12.3	504.88	***

Note. EU = Born in Europe. Non-EU = Born outside Europe.

Swedish = Born in Sweden.

5,332 participants due to technical error.

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

Prior Year Prevalence and Gender

Prior year victimization was found in 63.6% (males 63% and females 64.1%). In relation to the five domains of JVQ, approximately 41% had experienced conventional crime, 14.5% child maltreatment, 30% peer and sibling victimization, about 13% sexual victimization, and 34% had witnessed or experienced indirect victimization. Females experienced significantly more child maltreatment, χ²(1, 5960) = 184.22, p < .001, and sexual victimization, χ²(1, 5960) = 447.51, p < .001, than males, whereas males experienced significantly more conventional crime, χ²(1, 5332) = 16.58, p < .001, and had witnessed and experienced indirect victimization than females, χ²(1, 5960) = 4.74, p < .05. There was no significant gender difference as concerns peer and sibling victimization.

Lifetime Prevalence and Immigration Status

Roughly 9% were not born in Sweden, and 21.5% were second-generation immigrants with at least one parent born abroad (see Table 1). Adolescents born outside of Europe experienced significantly more events in the domain of child maltreatment, χ²(2, 5960) = 15.01, p < .001, with more physical abuse by a caregiver, χ²(2, 5960) = 36.75, p < .001, and less peer and sibling victimization, χ²(2, 5960) = 14.96, p < .001. Immigrants witnessed significantly more victimization, χ²(2, 5960) = 6.45, p < .05, with more witnessing of domestic violence, χ²(2, 5960) = 30.02, p < .001, including parent assault of sibling, χ²(2, 5960) = 24.26, p < .001 (see Table 2).

Lifetime Prevalence and Family Employment

A majority of the parents, 68.9%, worked (83.7% of the fathers and 77.9% of the mothers). Unemployment significantly increased victimization for conventional crime, χ²(1, 5332) = 31.66, p < .001; child maltreatment: χ²(1, 5960) = 78.34, p < .001; and sexual victimization: χ²(1, 5960) = 10.80, p < .001, as did some witnessing items including witnessing domestic violence, χ²(1, 5960) = 65.24, p < .001, and witnessing parental assault on a sibling, χ²(1, 5960) = 24.20, p < .001 (see Table 3).

Table 3.

Prevalence of Lifetime Victimizing Events: Employment and Residency (N = 5,960).

Variable	Employment		χ²	p	Residency^a			χ²	p
	Both Parents Employed	One or Both Parents Unemployed^b			With Both Biological Parents	With One Biological Parent	Other
	n = 4,107	n = 1,853			n = 4,478	n = 1,185	n = 297
	%	%			%	%	%
Total^c	83.4	85.5	3.50		82.4	88.6	91.0	35.48	***
Conventional crime^c	63.9	71.7	31.66	***	63.7	73.4	77.8	53.25	***
1. Robbery	12.8	16.8	16.50	***	12.5	17.5	24.6	48.07	***
2. Personal theft	41.1	44.7	6.54	*	40.9	45.9	48.5	14.74	***
3. Vandalism^c	23.9	30.5	26.08	***	24.2	30.3	34.4	27.33	***
4. Assault with a weapon	11.6	17.8	42.60	***	11.4	18.8	23.6	70.83	***
5. Assault without a weapon^c	32.1	40.2	33.26	***	31.7	42.2	48.7	67.43	***
6. Attempted assault	13.4	17.3	15.61	***	13.1	17.8	25.3	44.95	***
7. Kidnapping	1.7	3.1	12.87	***	1.9	2.5	4.4	9.49	**
8. Bias attack (hate crimes)	4.0	7.9	39.10	***	4.8	5.8	8.1	7.07	*
Child maltreatment	20.7	31.3	78.34	***	19.3	37.1	42.4	221.07	***
9. Physical abuse by caregiver	10.2	16.9	53.94	***	9.9	17.9	25.3	104.94	***
10. Psychological/emotional abuse	13.3	20.4	48.45	***	12.7	23.6	26.6	115.03	***
11. Neglect	3.6	7.5	42.32	***	3.1	8.8	14.5	128.93	***
12. Custodial interference/abduction	2.3	5.3	37.65	***	1.3	9.2	8.4	217.12	***
Peer/sibling victimization	54.4	54.6	0.02		52.9	58.3	61.6	17.47	***
13. Gang or group assault	10.9	12.3	2.39		11.0	12.2	13.1	2.38
14. Peer or sibling assault	23.5	24.1	0.23		22.6	26.6	29.0	13.24	***
15. Nonsexual genital assault	6.7	7.9	2.61		6.9	7.7	7.4	0.91
16. Bullying	19.0	18.9	0.01		18.7	19.5	20.5	0.85
17. Emotional bullying	27.0	27.1	0.01		26.1	29.4	33.0	10.76	**
18. Dating violence	10.0	11.9	5.10	*	8.6	15.9	19.2	77.95	***
Sexual victimization	20.6	24.4	10.80	***	19.7	26.7	35.4	60.53	***
19. Sexual assault by known adult	2.6	5.2	25.74	***	2.5	5.4	9.1	54.65	***
20. Nonspecific sexual assault	2.2	2.8	2.26		1.9	3.0	6.7	30.15	***
21. Sexual assault by peer	4.2	5.8	7.93	**	3.9	7.0	7.7	27.29	***
22. Rape: Rape or attempted rape	8.0	10.1	7.35	**	7.2	12.5	14.1	44.90	***
23. Flashing/sexual exposure	4.5	6.3	9.22	**	4.2	7.4	7.7	24.95	***
24. Verbal sexual harassment	11.6	13.4	3.97	*	11.1	14.8	18.5	23.67	***
Witnessing victimization	53.3	55.6	2.70		52.3	59.5	59.3	23.05	***
26. Witness to domestic violence	4.9	10.5	65.24	***	4.4	13.2	14.8	150.30	***
27. Witness to parent assault of sibling	3.8	6.7	24.20	***	3.8	7.0	10.4	44.57	***
28. Witness to assault with a weapon	18.4	20.9	5.28	*	18.4	20.5	25.6	10.86	**
29. Witness to assault without a weapon	35.0	32.1	5.05	*	33.1	36.7	39.7	9.97	**
30. Burglary of family household	14.8	14.1	0.45		14.3	15.7	14.5	1.44
31. Murder of family member or friend	3.7	6.0	16.56	***	3.9	5.7	7.1	12.57	**
32. Witness to murder	1.0	1.9	7.01	**	1.2	1.5	2.4	3.48
33. Exposure to random shootings, terrorism	6.5	10.7	30.24	***	7.7	7.7	9.8	1.62
34. Exposure to war or ethnic conflict	1.3	4.6	60.27	***	2.3	2.5	2.0	0.30

Living together with both parents of origin, one parent of origin, or alone/apart from the family, including foster home or institution.

One or both parents’ unemployed.

5,332 participants due to technical error.

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

Lifetime Prevalence and Residence

Most of the participating adolescents (75.1%) were living with both their biological parents; 19.9% lived with only one parent (alone or together with a stepparent), and 5.0% lived alone, in a foster family, or in an institution (see Table 1). The living situation was significantly different for adolescents who had experienced some form of lifetime victimization compared with those who had no such experience, χ²(2, 5332) = 35.48, p < .001. In all domains, adolescents living with both parents experienced significantly fewer victimization events (see Table 3). The most noteworthy significant difference that concerned the domain of child maltreatment was linked to adolescent living arrangements: 19.3% of the adolescents living with both parents had experienced some form of maltreatment compared with 37.1% among those who lived with just one of their biological parents, and 42.4% of those who lived under other circumstances: χ²(2, 5960) = 221.07, p < .001.

Lifetime Prevalence and Educational Program

The majority of the students were studying at a vocationally oriented practical program (54.0%), or at a theoretical program, a program preparing for further studies (44.4%). A minority (1.6%) were studying at a program adapted to the individual, such as an introductory program (see Table 1).

In total, adolescents from theoretical programs reported significantly more experiences of victimization, χ²(2, 5960) = 15.22, p < .001, and witnessing violence, χ²(2, 5960) = 44.38, p < .001, compared with their peers in both practical programs and the introductory programs (see Table 4). In contrast, child maltreatment was reported more often among adolescents in the introductory program, χ²(2, 5960) = 8.86, p < .01, whereas peer/sibling victimization was less common among students in the introductory program, χ²(2, 5960) = 8.61, p < .05.

Table 4.

Prevalence of Lifetime Victimizing Events: Education Program and Municipality Size (N = 5,960).

Variable	Education Program^a			χ²	p	Municipality Size^b			χ²	p
	T	P	I			Large	Medium	Small
	n = 2,648	n = 3,219	n = 93			n = 1,018	n = 2,857	n = 2,085
	%	%	%			%	%	%
Total^c	86.1	82.9	75.3	15.22	***	88.5	84.1	81.9	22.51	***
Conventional crime^c	66.9	66.1	63.4	0.74		73.9	65.7	63.5	34.03	***
1. Robbery	13.4	14.4	19.4	3.49		19.7	13.7	11.8	36.07	***
2. Personal theft	43.6	41.0	45.2	4.29		47.8	42.2	39.6	19.18	***
3. Vandalism^c	24.8	26.5	34.4	5.54		32.0	25.9	23.0	28.84	***
4. Assault with a weapon	11.9	14.7	18.3	12.06	**	16.4	12.6	13.4	9.51	**
5. Assault without a weapon^c	34.7	34.8	31.2	0.52		40.3	33.9	32.8	17.87	***
6. Attempted assault	13.8	15.2	19.4	3.99		13.7	14.8	14.8	0.94
7. Kidnapping	1.7	2.4	5.4	7.48	*	1.5	2.2	2.4	2.84
8. Bias attack (hate crimes)	5.2	5.0	11.8	8.47	*	6.7	4.7	5.1	5.85
Child maltreatment	22.7	24.8	34.4	8.86	**	25.3	24.2	23.1	1.95
9. Physical abuse by caregiver	11.4	12.6	21.5	9.48	**	12.8	12.6	11.6	1.45
10. Psychological/emotional abuse	14.1	16.6	21.5	9.33	**	14.4	15.6	16.0	1.31
11. Neglect	4.3	5.1	10.8	9.09	**	4.8	4.6	5.1	0.79
12. Custodial interference/abduction	2.6	3.4	11.8	25.97	***	2.7	3.6	2.9	3.47
Peer/sibling victimization	55.6	53.9	40.9	8.61	*	54.9	54.8	53.7	0.75
13. Gang or group assault	10.1	12.4	12.9	7.73	*	12.1	12.0	10.1	4.89
14. Peer or sibling assault	25.1	22.7	17.2	6.96	*	25.0	24.0	22.5	2.72
15. Nonsexual genital assault	7.3	6.9	7.5	0.50		8.3	7.2	6.3	3.98
16. Bullying	21.1	17.4	12.9	15.78	***	19.1	18.7	19.3	0.32
17. Emotional bullying	28.5	26.3	12.9	13.04	***	23.0	27.7	28.2	10.50	**
18. Dating violence	7.1	13.2	17.2	61.41	***	12.7	8.8	12.0	18.43	***
Sexual victimization	21.5	22.2	18.3	1.14		21.3	22.0	21.9	0.20
19. Sexual assault by known adult	2.2	4.2	10.8	34.46	***	3.0	3.2	3.9	2.28
20. Nonspecific sexual assault	2.1	2.5	4.3	2.92		2.9	2.1	2.4	2.16
21. Sexual assault by peer	3.9	5.3	5.4	6.07	*	4.3	4.5	5.1	1.50
22. Rape: Rape or attempted rape	7.9	9.2	9.7	2.94		9.3	8.2	8.9	1.49
23. Flashing/sexual exposure	5.6	4.5	7.5	4.80		6.6	5.0	4.3	7.66	*
24. Verbal sexual harassment	12.0	12.3	11.8	0.15		9.7	12.1	13.4	8.78	*
Witnessing victimization	58.6	50.8	38.7	44.38	***	59.9	55.7	49.0	38.89	***
26. Witness to domestic violence	6.0	6.9	16.1	15.29	***	7.1	7.1	5.8	4.09
27. Witness to parent assault of sibling	4.9	4.6	6.5	0.92		5.4	5.3	3.6	8.42	*
28. Witness to assault with a weapon	20.0	18.7	14.0	3.18		20.9	19.8	17.5	6.80	*
29. Witness to assault without a weapon	38.1	31.2	20.4	38.50	***	34.7	35.9	31.4	10.85	**
30. Burglary of family household	17.0	12.7	10.8	22.93	***	15.4	15.2	13.4	3.55
31. Murder of family member or friend	4.6	4.2	7.5	2.73		5.6	4.8	3.3	10.55	**
32. Witness to murder	1.0	1.5	3.2	5.19		2.4	1.1	1.2	10.55	**
33. Exposure to random shootings. terrorism	9.3	6.6	7.5	14.06	***	13.6	8.5	4.1	88.89	***
34. Exposure to war or ethnic conflict	2.5	2.1	5.4	4.65		4.2	2.1	1.9	18.55	***

Note. ^aT = Theoretical; P = Practical; I = Introductory.

Large > 200,000 inhabitants. Medium = 50,000 to 200,000 inhabitants. Small < 50,000 inhabitants.

5,332 participants due to technical error.

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

Lifetime Prevalence and Municipality Size

The majority (47.9%) of the adolescents lived in medium-sized communities (50,000 to 200,000 inhabitants) whereas 35% lived in small communities (<50,000 inhabitants; see Table 1). The remainder, or 17.1%, came from a large city (>200,000 inhabitants). Community size was a significant factor for the total lifetime experiences, χ²(2, 5332) = 22.51, p < .001, as well as within the domains of conventional crimes, χ²(2, 5332) = 34.03, p < .001, and witnessing victimizing events, χ²(2, 5960) = 38.98, p < .001. Generally, adolescents living in small communities had fewer experiences of victimizing events, especially within these two domains (see Table 4).

Multivariate Analyses

All domains (dependent variables) and background data used in the binary analyses in Tables 1 to 4 (independent variables), together with poly-victimization (dependent variable), were put into seven different multiple logistic regression models (see Table 5). Girls were exposed to significantly fewer conventional crimes compared with boys (adjusted odds ratio [aOR] = 0.75, 95% confidence interval [CI] = [0.67, 0.84]), yet they registered significantly more frequent experiences of maltreatment (aOR = 2.29, CI = [2.02, 2.60]), peer victimization (aOR = 1.24, CI = [1.12, 1.37]), and sexual victimization (aOR = 4.12, CI = [3.58, 4.74]).

Table 5.

Logistic Regression With Total JVQ Score: Conventional Crime, Maltreatment, Peer/Victimization, Sexual Victimization, and Witness Victimization as Dependent Variables Adjusted for Background Variables in the Six Different Models (Domains) and for Poly-Victimization.

Variable	Total JVQ Score		Conventional Crime		Child Maltreatment		Peer/Sibling Victimization		Sexual Victimization		Witnessing/Indirect Victimization		Poly-Victimization^a
Variable	aOR	95% CI	aOR	95% CI	aOR	95% CI	aOR	95% CI	aOR	95% CI	aOR	95% CI	aOR	95% CI
Gender
Male (ref)
Female	1.12	[0.96, 1.30]	0.75	[0.67, 0.84]	2.29	[2.02, 2.60]	1.24	[1.12, 1.37]	4.12	[3.58, 4.74]	1.08	[0.97, 1.19]	1.53	[1.28, 1.84]
Birthplace adolescent
Sweden (ref)
Europe	1.33	[0.85, 2.09]	1.09	[0.77, 1.55]	1.08	[0.77, 1.53]	1.06	[0.79, 1.42]	1.00	[0.68, 1.46]	1.21	[0.90, 1.64]	1.38	[0.89, 2.14]
Outside Europe	0.90	[0.60, 1.33]	0.94	[0.68, 1.30]	1.29	[0.94, 1.76]	0.80	[0.60, 1.06]	0.84	[0.58, 1.22]	0.88	[0.66, 1.16]	0.99	[0.63, 1.55]
Birthplace parents
Sweden (ref)
One or two in Europe	0.80	[0.62, 1.03]	1.09	[0.88, 1.34]	1.14	[0.92, 1.41]	0.78	[0.65, 0.93]	0.86	[0.69, 1.09]	1.11	[0.92, 1.33]	1.33	[0.99, 1.78]
One or two outside Europe	0.79	[0.60, 1.03]	0.94	[0.77, 1.16]	1.19	[0.96, 1.48]	0.69	[0.57, 0.83]	0.76	[0.60, 0.96]	1.10	[0.91, 1.33]	1.27	[0.94, 1.72]
Employment parents
Both employed (ref)
At least one unemployed	1.09	[0.91, 1.29]	1.30	[1.13, 1.49]	1.32	[1.15, 1.52]	1.06	[0.94, 1.20]	1.20	[1.04, 1.40]	1.01	[0.89, 1.14]	1.53	[1.26, 1.86]
Residence
Both parents (ref)
One parent	1.68	[1.36, 2.07]	1.49	[1.27, 1.74]	2.16	[1.86, 2.50]	1.26	[1.10, 1.44]	1.35	[1.15, 1.58]	1.36	[1.18, 1.55]	2.07	[1.68, 2.54]
Alone or other	2.44	[1.60, 3.73]	2.12	[1.58, 2.85]	2.67	[2.07, 3.43]	1.47	[1.15, 1.88]	1.94	[1.49, 2.54]	1.50	[1.18, 1.92]	2.84	[2.07, 3.91]
Education program
Theoretical (ref)
Practical	0.78	[0.66, 0.91]	0.97	[0.86, 1.10]	1.10	[0.97, 1.26]	0.89	[0.80, 0.99]	1.04	[0.91, 1.19]	0.76	[0.68, 0.85]	1.16	[0.96, 1.42]
Introductory	0.49	[0.30, 0.81]	0.74	[0.48, 1.16]	1.53	[0.96, 2.44]	0.57	[0.37, 0.87]	0.89	[0.50, 1.57]	0.45	[0.29, 0.70]	1.58	[0.89, 2.84]
Municipality size
Small (ref)
Medium	1.17	[0.99, 1.38]	1.09	[0.96, 1.24]	1.06	[0.92, 1.22]	1.08	[0.96, 1.21]	1.06	[0.92, 1.23]	1.23	[1.10, 1.39]	1.15	[0.70, 1.06]
Large	1.68	[1.33, 2.12]	1.61	[1.35, 1.92]	1.07	[0.89, 1.29]	1.12	[0.95, 1.31]	1.03	[0.84, 1.26]	1.38	[1.18, 1.62]	0.86	[0.89, 1.48]

Note. Significant items in bold. JVQ = Juvenile Victimization Questionnaire; CI = confidence interval; aOR = adjusted odds ratio.

Cutoff ≥ 10 victimization events.

Parental unemployment was also associated with a significant increase in victimization within the three domains of conventional crime (aOR = 1.30, CI = [1.13, 1.49]), maltreatment (aOR = 1.32, CI = [1.15, 1.52]), and sexual victimization (aOR = 1.20, CI = [1.04, 1.40]). A higher rate of victimization was found throughout all domains when adolescents did not reside with both of their parents (see Table 5).

Living in a large community increased the odds that children would be exposed to both conventional crime (aOR = 1.61, CI = [1.35, 1.92]) and to witnessing victimization (aOR = 1.38, CI = [1.18, 1.62]). Attending a theoretical program increased the odds ratios on the total JVQ score as compared with the practical program and the introductory program, concerning the total score, peer victimization, and witnessing victimization (see Table 5).

There was no increased risk factor in any domain for a participant who was an immigrant or had at least one parent born abroad. On the contrary, having parents born outside of Europe seemed to be a protective factor as concerned both peer victimization (aOR = 0.69, CI = [0.57, 0.83]) and sexual victimization (aOR = 0.76, CI = [0.60, 0.96]). Some isolated issues were more often experienced by immigrant adolescents from Europe, such as murder of a family member (aOR = 3.27, CI = [1.87, 5.71]), witnessing murder (aOR = 4.85 CI = [2.01, 11.72]), and exposure to murder, random shootings and terrorism (aOR = 2.28, CI = [1.52, 3.43]). This was also true for exposure to war or ethnic conflicts for adolescents both from Europe (aOR = 14.22, CI = [7.71, 26.21]) and outside Europe: (aOR = 2.31, CI = [1.38, 3.87]). Having parents born outside of Sweden increased the risk for bias attacks (hate crime), physical abuse, being a witness to domestic violence, exposure to random shootings or terrorism, war, and other ethnic conflicts.

Poly-Victimization

Students reported a mean number of 4.1 (SD = 4.0) for experiencing different types of victimization events during their lifetime (boys: M = 3.8, SD = 3.8 and girls: M = 4.5, SD = 4.2, p < .001). Breaking this figure down in the different domains showed that the students had experienced on average 1.5 (SD = 1.6) different forms of conventional crime (boys: M = 1.6, SD = 1.7 and girls: M = 1.4, SD = 1.6; p < .001), 0.4 (SD = 0.7) different forms of child maltreatment events (boys: M = 0.2, SD = 0.6 and girls: M = 0.5, SD = 0.8; p < .001), 1.0 (SD = 1.2) different forms of peer and sibling victimization (boys: M = 0.9, SD = 1.2 and girls: M = 1.0, SD = 1.2, p < .001), 0.4 (SD = 0.8) forms of sexual victimization (boys: M = 0.2, SD = 0.5 and girls: 0.6 SD = 1.0; p < .001), and 1.0 (SD = 1.2) forms of witness victimization (boys: M = 0.9, SD = 1.2 and girls: M = 1.0, SD = 1.2; p = .257).

When using the Lifetime SSV with a cutoff ≥10 victimization events, 10.3% of the respondents (8.1% boys vs. 12.5% girls, OR = 1.62, CI = [1.35, 1.94]) had the experience of being highly victimized (poly-victimized). As shown in Table 6, values are highly elevated at the 90th percentile, with four events for conventional crime, three events for witnessing/indirect victimization, three events for peer/sibling victimization, one event for sexual victimization, and one event for child maltreatment. When analyzing this highly exposed group with logistic regression, including the same background variables as above, our research showed that the following factors increased the odds of being highly victimized: being female (aOR = 1.53, CI = [1.27, 1.84]), having an unemployed parent (aOR = 1.53, CI = [1.26, 1.86]), not living with both biological parents (living with one parent: aOR = 2.07, CI = [1.68, 2.54]), and living alone or in other living arrangements (aOR = 2.84, CI = [2.07, 3.91]).

Table 6.

Mean Number of Lifetime Victimizing Events.

Variable Percentiles	Total JVQ Score^a	Conventional Crime^a	Child Maltreatment	Peer/Sibling Victimization	Sexual Victimization	Witnessing/Indirect Victimization
Variable Percentiles	n = 5,332	n = 5,332	n = 5,960	n = 5,960	n = 5,960	n = 5,960
10	0	0	0	0	0	0
20	1	0	0	0	0	0
30	1	0	0	0	0	0
40	2	1	0	0	0	0
50	3	1	0	1	0	1
60	4	1	0	1	0	1
70	5	2	0	1	0	1
80	7	3	1	2	1	2
90	10	4	1	3	1	3

Note. JVQ = Juvenile Victimization Questionnaire.

5,332 participants due to technical error.

Discussion

This study is the first epidemiological study using the JVQ for studying victimization and poly-victimization among young people in Sweden. The aim was twofold. The first aim of the study was to establish the prevalence of different victimizing events and poly-victimization. The second aim was to establish their association with a set of sociodemographic background factors. The main results from the study are summarized in five findings.

First, the frequency of experiencing lifetime victimization was high, with 83.0% of young men and 85.2% of young women experiencing some type of lifetime victimization. This figure for women is lower than the 97.8% of female college students in the United States experiencing lifetime victimization, as reported in the JVQ (Elliott, Alexander, Pierce, Aspelmeier, & Richmond, 2009). The prevalence rating in our sample is also lower than the findings for a similar sample of 14- to 17-year-olds in the United States, which was 86.8% (Turner, Finkelhor, & Ormrod, 2010). Taking into account that victimization increases with age, our results point to a lower prevalence in Sweden than in the United States, possibly reflecting different living conditions in the two countries. A study from China with a similar sample (N = 18.431, 15-17 years) found a prevalence of 71.4%, possibly related to the fact that “parental supervision is relatively strict” in China (Chan, 2013). The results highlight that the vast majority of adolescents within the countries studied have experienced victimization. The most common experiences included different forms of community violence or crime, followed by peer/sibling victimization and witnessing victimization, all of which were experienced by more than 50% of the sample.

It has been shown that having experiences of violence during childhood or adolescence increases the risk for health and psychological problems later in life (Olofsson et al., 2012). Victimized individuals are a majority of those in need of health care (Björklund, Häkkänen-Nyholm, Huttunen, & Kunttu, 2010) for higher levels of anxiety (van Oort et al., 2012), as well as depression, loneliness, low self-esteem and poor self-concept, generalized anxiety, and social anxiety (Hawker & Boulton, 2000). Therefore, providing interventions to decrease the prevalence of victimization in childhood and adolescence would benefit overall health in the population. Being able to identify key factors that increase the likelihood of victimization and being able to recognize the symptoms of this type of trauma would help establish targeted interventions and help those with some of the greatest health concerns. Most types of victimization are experienced in the general community in locations such as schools and public places. Evidently, more effort is needed to keep young people safe in their community and in schools.

Second, slightly more than 10% of the respondents were categorized as poly-victims, which meant that their lives were marked by multiple (10 or more) violent events, indicating that they come from very vulnerable and complex backgrounds. Previous research has shown that those who have experienced poly-victimization are burdened with adverse symptoms later in life (Turner et al., 2010) and are at the greatest risk of re-victimization (Finkelhor, Ormrod, & Turner, 2007c). In samples from groups of hospital inpatients, poly-victimization accounts for more psychosocial impairment than demographics and psychiatric diagnoses account for (Ford, Connor, & Hawke, 2009). More research should be conducted on the consequences of victimization, consequences including mental illness and potential traumatization.

Third, females were victimized significantly more often than males within four domains with an aOR ranging from 1.1 (witnessing victimization) to 4.1 (sexual victimization), but females experienced fewer conventional crimes during their lifetime (aOR = 0.7). The domain of sexual victimization showed the largest differences between the sexes. Being sexually assaulted by a peer (within 2 years age difference) showed an aOR of 8.4 for females. The increased risk of sexual abuse for females is well established. Epidemiological studies have shown that it is 2 to 4 times more common for girls to be exposed to sexual abuse than for boys (Stoltenborgh, van Ijzendoorn, Euser, & Bakermans-Kranenburg, 2011). However, it is important to highlight the vulnerability of girls who are victimized by their peers. Sexual abuse perpetrated by peers has historically been neglected since early studies defined a perpetrator of sexual abuse as someone who is at least 4 to 5 years older than the victim. As the data clearly show, there is an elevated risk for females of experiencing sexual abuse from their peers; therefore, appropriate action to limit exposure to this form of abuse is needed. Further studies are needed to address sexual abuse by peers and the effect of abuse on both the disclosure process and on the psychological well-being of those involved.

Fourth, similar to findings in previous studies of poly-victimization (Finkelhor, Ormrod, & Turner, 2007a), our study found that residing in a larger city means that adolescents are more exposed to people, both adults and peers. City life is more dangerous for adolescents, with higher rates of criminality and with a greater anonymity in cities than in smaller communities.

Finally, the most evident finding regarding background factors was the finding showing the importance of the participants’ living situation and family composition. Being raised by both biological parents was a protective factor that significantly reduced the risk of total victimization. This result correlates well with previous studies (Finkelhor et al., 2009b; Berger, 2004; Radford et al., 2011; Turner et al., 2007) that have stressed the increased risk of victimization for children living with only one parent or living alone, in foster care, or in institutions.

Even if intact families provide a safer environment for children, a substantial percentage of children are victimized in their families through maltreatment or witnessing domestic violence. Individuals and families who are at a higher risk of victimization, such as young women, children living with only one parent, those who are exposed to dangerous environments, and those having a history of victimization, can receive interventions by primary and secondary programs that target these specific issues. Effective, research-based programs (see, for example, California Evidence-Based Clearinghouse, www.cebc4cw.org), such as the Incredible Years and Safe Care®, are becoming more readily available. Programs for traumatized children, such as Eye Movement and Reprocessing for Children and Adolescents (EMDR), Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT), Child-Parent Psychotherapy (CPP), and Prolonged Exposure Therapy for Adolescents (PE-A), can be seen as treatment programs to reduce general health concerns and the symptomatic effects of trauma and reduce the risk of further victimization and possible poly-victimization. The latter is important as there is evidence that symptomatic behavior predisposes one to further victimization (Cuevas, Finkelhor, Ormrod, & Turner, 2009).

The current study findings are consistent with those from earlier studies, which state that child victimization is a large problem, and they highlight the importance of prevention and the early identification of potential victimization cases. The high level of peer victimization in adolescence suggests that interventions need to be implemented that will protect adolescents from the risk of exposure. An ecological approach might be appropriate in the planning of preventive measures. In families, caregivers must try to protect their children and adolescents from risks through providing adequate care and supervision. Schools have a role in educating children about how to protect themselves as well as promoting the qualities of good friendship to bullies and peers who may assault others. On a societal level, structural measures should be taken, which include the provision of safe public places, adult supervision where adolescents gather, and safe public transport at night. Particular attention should be given to children and adolescents living in disrupted families whose parents are not able to restrict risky behavior outside of the home. These children and adolescents have been shown to be more at risk of being targeted by potential perpetrators in society. The social welfare agencies have a key role in the protection of children in abusive and or disrupted families.

Methodological Issues, Strengths, and Limitations

Although the participation rate was good for this type of study (78%), the dropout rate may have affected the results. This complicates the interpretations and generalizations made from the findings. The three main causes of absence were related to vacation, sickness, or truancy. A survey in Uppsala Municipality in Sweden rated normal absences in high schools at 13%. The major cause of absence was sickness, and truancy was more common than granted absence (Utvärderingsenheten, 2005). Underlying factors for absence, such as health issues and lack of motivation, could be related to victimization and in that case the inclusion of these students would have elevated prevalence levels of key variables. Due to the design of the study, providing a second or third opportunity to participate in the survey would have been costly.

Technical failure led to data loss during the initial survey collection and resulted in losing 10.5% of data for two items out of a large group of 5,960 cases. When comparing the missing cases with the answers given by the participant adolescents, the differences between these groups concerning question JVQ 3 (vandalism) and the six other questions in the domain (conventional crime) varied between 0.3% and 3.5%, M = 2.2%, and the differences between the groups concerning JVQ 5 (assault with a weapon) varied between 1.0% to 8.8%, M = 4.8%. Because the percentage difference between the losses on the issues that concerned the same domain (conventional crime) was small, there were no corrections on item level.

Another limitation of the study is the fact that reporting lifetime events requires the use of long-term memory, with the time factor positively correlating with loss of recall, adding to reliability and validity issues (Widom, Raphael, & DuMont, 2004). Loss of recall combined with the fact that victimizing events are usually associated with discomfort and shame may lead to lower prevalence ratings in the study compared with reality.

Methodological limitations related to the group collection of data within a classroom setting have the real or perceived risk of loss of integrity, and, consequently, the potential loss of reported information. The computerized survey did not allow the users to skip questions, and there was no opportunity for comments, thereby limiting alternative answers. Neither the students nor teachers reported integrity issues, and the impression gathered from the researcher was that students were familiar with computerized data collection in public. Overall, when compared with abuse recognized and reported by professionals, self-reported data came closer to measuring the true occurrence of maltreatment (Gilbert et al., 2012). As discussed by Kendall-Tackett and Becker-Blease (2004), a longitudinal approach would limit the study of poly-victims because any known victimization would require formal action to safeguard the child and report the perpetrator. Others suggest longitudinal design with anonymous, record-linked datasets (Gilbert et al., 2012).

Strengths of this study include the use of a large and representative sample and the use of an instrument covering most victimizing events; thus, consequently, even small significant differences are detected in the analysis; however, it is important not to over-interpret these small but significant differences. Another asset of this study is the inclusion of sociodemographic factors into a regression model, which added unique knowledge rarely presented in previous research.

Conclusion

This article contributes a large representative study of victimization among Swedish adolescents. The results show that victimization is a highly prevalent event in Swedish adolescents’ lives and is comparable with the results of other international reports. Girls were overrepresented in all domains, except for conventional crime. The risk of peer sexual assault was greatly elevated among girls. Living conditions were an important factor with regard to the heightened risk of most forms of victimization, including poly-victimization. These factors include having unemployed parents and not living with both biological parents (e.g., living alone or having other living arrangements). As a substantial amount of research has shown, the poly-victimized group suffers from the most symptoms and effects of victimization, as well as having the highest risk of re-victimization.

To conclude, there is an urgent need for intervention through the use of structured measures to assess victimization within school settings, as well as for these assessments to be carried out by social workers and in child psychiatry. Using a form such as the JVQ can prove helpful in establishing a complete assessment of trauma for the individual child.

Footnotes

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: The authors would like to acknowledge the Crime Victim Compensation and Support Authority in Sweden and the Medical Research Council of Southeast Sweden for their financial support of the project.

Author Biographies

Nikolas Aho is a clinical psychologist and PhD student at Linköping University, Sweden, working on a projekt regarding adolescent trauma and health, focusing on prevalence, health outcome as well as genetic, social and psychological interaction effects.

Malin Gren-Landell, MD, PhD, is a clinical psychologist at the Child- and Adolescent Psychiatric Clinic, at Linköping University hospital, Sweden. Her major research interest is in clinical anxiety in children and adolescents.

Carl Göran Svedin, MD, PhD, is a Professor Emeritus in Child and Adolescent Psychiatry, at Faculty of Health Sciences Linkoping University, Sweden. He has long clinical experience and his major research interests are trauma and abuse in children and adolescents.

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