An Examination of Victimization Trajectories Among a Sample of South Korean Adolescents: Risk and Protective Factors

Abstract

Although a large body of criminological studies have examined trajectories of offending, only a handful of studies have attempted to explore victimization trajectories. The purpose of the current study is to use group-based modeling to explore victimization trajectories among Korean youth and to identify factors that protect and jeopardize victims over the life course. The present study uses data from five waves of Korean Youth Panel Survey (KYPS). Results show three distinct victimization trajectories and identify several risk and protective factors of repeat victimization. Suggestions for future research are discussed.

Keywords

victimization trajectories victim careers repeat victimization risk and protective factors group-based trajectory analysis

Throughout the past several decades, many studies have identified factors that place individuals at higher risk for victimization of crime. These studies have generated considerable theoretical improvements on the nature and patterns of victimization. An important finding is the homogeneity of victim–offender populations. Although this overlap accounts for only a small portion of the entire victim population, this finding is particularly relevant as victims tend to be repeatedly victimized over the life course (Farrell, Tseloni, & Pease, 2005; Ousey, Wilcox, & Brummel, 2008). For example, using a nationally representative sample of adolescents, Chang, Chen, and Brownson (2003) reported that 52% of respondents experienced repeated victimization. Farrell and Pease (1993) showed that approximately 4% of respondents have at least five victimization experiences. This small group comprised 45% of all victimization reports. Reid and Sullivan (2009) demonstrated that while 62% of persons reported no or rare victimization incidents, 11% of respondents were assigned to multiple victimization groups. Despite the recent academic efforts to explore repeat victimization, the extent of within-individual stability or change in victimization is still unclear, as most studies on victimization have relied on cross-sectional data. In addition, only a handful of studies examine this topic and most use American samples. To fill this gap, the present study explores victimization trajectories among a sample of Korean adolescents to identify risk and protective factors for victimization across the life course.

Repeat Victimization

Victim careers are conceptually defined as repeated victimization throughout the life course (Farrell, Tseloni, Wiersema, & Pease, 2001). Examining repeat victimization is important to enhance our understanding of victimization and to inform efforts to prevent further victimization. First, studying repeat victimization helps researchers understand the general causal processes influencing offending and uncover factors that put victims at increased vulnerability for offending (Sparks, 1981). Second, the lack of knowledge on the distribution and complexity of victimization can inform misleading explanations of the nature and characteristics of victimization (Farrell et al., 2005; Planty & Storm, 2007; Ybarra & Lohr, 2002). Third, studies investigating repeat victimization have important implications for prevention policy, as initial victimization leads to an increased likelihood of subsequent victimization (Farrell, 1995; Farrell & Pease, 1993; Pease, 1998). Therefore, research on repeat victimization not only has theoretical and scholastic value but can also lead to efficient use of prevention resources.

Two perspectives explain the mechanisms through which repeated victimization occurs. First, the risk heterogeneity perspective assumes that certain individuals are attractive victims in the eyes of perpetrators. Such individuals have a set of latent and persistent characteristics that put them at increased risk of being victimized repeatedly. For example, environmental characteristics such as proximity to high crime areas and absence of capable guardianship can facilitate repeated victimization (Eck, 2001; Farrell, Phillips, & Pease, 1995; Lauritsen & Quinet, 1995; Wittebrood & Nieuwbeerta, 2000). Enduring characteristics, referring to biological and psychological factors such as physical weakness, aggression, impulsiveness, and insensitivity, can also increase risk of chronic victimization (Lauritsen & Quinet, 1995). Farrington (1993) found that depression, shyness, and anxiety were related to serial victimization. This hypothesis is also known as “flag theory” because heterogeneity serves as a flag of higher risk of repeat victimization.

Second, state dependence, or “boost theory,” postulates that initial victimization is related to subsequent victimization. There are two distinct state dependence hypotheses. Hindelang, Gottfredson, and Garofalo (1978) were the first to suggest the “once bitten, twice shy” hypothesis. They argued that once victimized, victims change their behaviors so as to reduce their risk of being victimized again. Therefore, these modifications are expected to decrease an individual’s future risk of victimization. Although Hindelang et al. (1978) emphasized the necessity of longitudinal studies to support their argument, most studies testing the hypothesis have analyzed cross-sectional data (Ferraro, 1995; Lavrakas, 1981; Lurigio, 1987; Rountree & Land, 1996). However, several studies relying on longitudinal data have found results that run counter to the “once bitten, twice shy” hypothesis (Averdijk, 2011; Miethe, Stafford, & Sloan, 1990). For example, Miethe et al. (1990) analyzed a two-wave panel from the National Crime Survey and explored the relationship between changes in lifestyles and changes in victimization. They found that changes in more risky lifestyles were related to an increased risk of victimization, whereas increases in precautionary actions were not related to a reduced risk of victimization.

In response to the mixed empirical results for Hindelang and colleagues’ (1978) “once bitten, twice shy” hypothesis, Farrell & Pease (1993) proposed an opposing perspective, referred to as the “once bitten, twice bitten” hypothesis. This proposes that those who were previously victimized face a higher risk of further victimization. A victim-labeling process offers insight into such an interpretation of repeat victimization, assuming that the vulnerability or attractiveness of the victim increases after the first victimization. In addition, victims who may attempt to revenge put themselves at further risk for victimization. Thus, future risk of chronic victimization increases after initial victimization (Farrell & Pease, 1993; Lauritsen & Quinet, 1995). Farrington (1993) found that bullies choose victims based on perceived vulnerability. Labeled targets may be isolated by peers and consequently chosen by another perpetrator. A victim’s changed self-identity can also influence the likelihood of being victimized repeatedly. For example, individuals may engage in submissive behaviors as a result of victimization, influencing their repeated victimization (Schwartz, Dodge, & Coie, 1993).

Prior studies on repeat victimization have been based on both cross-sectional and longitudinal research designs. Most cross-sectional surveys ask respondents about victimization experiences in the past year. Although cross-sectional studies offer valuable information, they typically provide a simple description or estimation of victimization, given that these surveys encompass a relatively short time span. As this approach can only capture victimization within a small time period, cross-sectional designs are unable to delve into causal relationships or underlying mechanisms of chronic victimization.

Longitudinal research is necessary to uncover a more accurate picture of victimization. Many researchers advocate longitudinal designs as they can provide better understandings of sequential patterns, continuity, stability, and key features of victimization (Farrington, Ohlin, & Wilson, 1986; Menard, 2000; Sampson & Laub, 1993, 1995; Tonry, Ohlin, & Farrington, 1991). Menard (2000) maintained that “in all likelihood, many of the individuals who would have been classified as repeat victims in a longer time perspective were not identified as such in the cross-sectional research” (p. 568). Lauritsen and Quinet (1995) explored victimization patterns using five waves of the National Youth Survey (NYS). Results showed that experience with previous victimization modified victims’ behaviors, thus supporting the victim labeling hypothesis. Finkelhor, Ormrod, and Turner (2009) examined revictimization patterns across two waves of a national sample of children and adolescents. They found that experiencing any type of victimization increased the risk of subsequent victimization, regardless of the type of victimization. For example, being victimized via property crime was related to increased likelihood of sexual victimization the next year.

Victim Careers

Since the work of Blumstein, Cohen, Roth, and Visher (1986) distinguishing “criminal careers” from “career criminals,” a criminal career paradigm has developed over a period of several decades. While the term career criminals initially proposed by Hirschi and Gottfredson (1983) refers to offenders who commit serious offenses at high rates and over extended periods of time, “a criminal career is the characterization of the longitudinal sequence of crimes committed by an individual offender” (Blumstein et al., 1986, p. 12). The criminal career paradigm provides more explanatory factors by differentiating distinct offending stages: onset, duration, and desistance (Blumstein et al., 1986). Empirical studies focusing on the long-term consequences of crimes have posited that an individual’s early onset of criminal activity is the most powerful predictor of that individual’s continuation of criminal activity across the life course (Farrington, Lambert, & West, 1998). Given that the offender–victim link is well established, it is highly plausible that if there are criminal careers, victim careers also may exist.

Although there has been substantial growth in the study of criminal careers, little is known about victim careers from a longitudinal perspective. A victim career is “the existence, frequency, duration and seriousness of victimization experiences across the lifetime” (Farrell et al., 2001, p. 2). Sullivan, Wilcox, and Ousey (2011) examined the existence of distinct patterns of victimization trajectories by analyzing four-wave panel data and found evidence of four latent victimization longitudinal patterns: Two were relatively stable and the other two were temporal. The two relatively stable classes (Class 1 and Class 3) accounted for 96% of the data. Class 1 showed a moderate and downward pattern, and youth with the lowest level of victimization belonged to Class 3. The other two classes (Class 2 and Class 4) showed different types of trajectories representing 4% of the sample. Class 2 began with a high victimization level and sharply declined. Class 4 was characterized by upward trend. This class started with the lowest victimization group (Class 3), the first wave, but exhibited increasing levels of victimization. Higgins, Jennings, Tewksbury, and Gibson (2009) analyzed Gang Resistance Education and Training (GREAT) data and explored the relationship between violent victimization trajectories and low self-control. Results support the relative stability of self-control over time and the long-term effects of self-control on violent victimization. They found three violent victimization trajectories. Group 1 showed little or almost no violent victimization experiences. Group 2 began with low levels of victimization at 12 years old but declined by 16 years old. Group 3 started with low levels of victimization at 12 years old, desisted until 14 years old, and then showed a sharply increasing high level of violent victimization.

Risk and Protective Factors

Violent Offending

Empirical studies found that individuals who experience victimization share similarities with individuals who participate in violent behaviors (Berg, Stewart, Schreck, & Simons, 2012; Felson, 1986, 1992; Jennings, Higgins, Tewksbury, Gover, & Piquero, 2010; Jennings, Piquero, & Reingle, 2012; Jensen & Brownfield, 1986; Lauritsen & Laub, 2007; Mustaine & Tewksbury, 1998, 2000; Schreck, Stewart, & Osgood, 2008; Singer, 1981). These findings not only highlight the similarity in individual characteristics, but also indicate the importance of engaging in violence as a risk factor of victimization. Theoretical explanations for the role of violent offending in predicting victimization are derived from routine activities and lifestyle theories (Cohen & Felson, 1979; Garofalo, 1987; Hindelang et al., 1978; Lauritsen, Sampson, & Laub, 1991; Schreck et al., 2008; Smith & Ecob, 2007). These theoretical perspectives propose that, by virtue of engaging in violent conduct, these individuals are at a heightened risk of victimization during their everyday life. Thus, violent behavior ultimately predicts victimization. According to this perspective, victimization and violent offending are connected via a reciprocal relationship.

Low Self-Control

It is well known that low self-control is related to victimization (Higgins et al., 2009; Piquero, MacDonald, Dobrin, Daigle, & Cullen, 2005; Schreck, 1999; Schreck, Stewart, & Fisher, 2006). Vulnerability to crime is a by-product of low self-control (Schreck, 1999). Previous studies demonstrate the relationship between low self-control and being victimized by assault, theft, and fraud (Holtfreter, Reisig, & Pratt, 2008; Schreck, 1999; Schreck, Wright, & Miller, 2002). The features of low self-control increase the odds of victimization as individuals with low self-control tend not to recognize the long-term consequences of their behaviors. It is likely that impulsive individuals pursue instant gratification without consideration of later results of their actions. The preference for risk seeking and physical activities also induce individuals with low self-control to put themselves at risky situations. Using a sample of high school students, Schreck et al. (2002) demonstrated the effects of low self-control and delinquent peer association on victimization. This research also revealed the indirect effect of having low self-control on being victimized through association with delinquent peers. In addition, Stewart, Elifson, and Sterk (2004) showed significant association between low self-control and victimization. Baron, Forde, and Kay (2007) found that the risk-taking feature of low self-control was a significant predictor of violent victimization. Although these studies are limited by their use of cross-sectional data, studies using longitudinal data offer new insight. Relying on the California Youth Authority data, Piquero et al. (2005) established that low self-control is a risk factor of victimization. Using three waves of adolescent panel data, Schreck et al. (2006) demonstrated a direct effect of low self-control on violent victimization, as well as an indirect effect of low self-control on victimization when mediated via delinquent peer association. Higgins et al. (2009) used group-based models to reveal the association between self-control trajectories and violent victimization trajectories. These findings showed that a high self-control group was less likely to experience victimization, whereas individuals in the low self-control group experienced the majority of victimization. In addition, low self-control was identified as the most significant factor in distinguishing the three victimization trajectories, compared with school commitment, parental monitoring, and sex (Jennings et al., 2010).

Delinquent Peer Association

Delinquent companions intensify individuals’ exposure to delinquency and increase opportunities to engage in deviant conduct. Youth who spend considerable time with friends is generally under less supervision from parents or teachers. It is highly plausible that unsupervised/unstructured social activity may lead to greater engagement in delinquency and greater victimization (Osgood, Wilson, O’Malley, Bachman, & Johnston, 1996). Although the effect of delinquent peers on delinquent behaviors may be explicit or implicit, involvement with delinquent peers is likely to place juveniles at higher risk of victimization. When socializing with delinquent friends, youth may spend time with potentially motivated offenders. Contrary to public perception, an individual’s gang membership cannot guarantee individual’s safety. The unprotected nature of gang membership has been found for both boys and girls (Miller & Decker, 2001). Youth gang members are more likely to experience victimization than nonmembers (Esbensen & Huizinga, 1993; Huizinga, Weiher, Espiritu, & Esbensen, 2003; Miller & Decker, 2001; Taylor, Freng, Esbensen, & Peterson, 2008; Taylor, Peterson, Esbensen, & Freng, 2007; Thornberry & Krohn, 2003).

Attachment and Supervision

Social bonding theory (Hirschi, 1969) provides a theoretical rationale for why some people do not commit a crime. This perspective argues that if juveniles have a strong social bond, they are less likely to commit deviant acts. Social bonding theory also helps us to understand how a positive relationship with another individual can function as a protective factor for delinquency and victimization. Attachment, one of the elements of the social bond, refers to the affective relationship between people. Although there are many controversies over the theory, Hirschi (1969) considered youth’s affective ties to parents as the most salient source of attachment and suggested five measures of this concept: supervision, emotional attachment, intimacy of communication flowing from the child to the parent, identification with the parent, and parental disciplinary techniques. Despite mixed results, earlier studies generally showed that as parental attachments weaken, the likelihood of delinquency increases or, at least, has an indirect effect on delinquency (Canter, 1982; Cernkovich & Giordano, 1987; Wells & Rankin, 1988; Wiatrowski, Griswold, & Roberts, 1981). In addition, juveniles who are under more parental monitoring are less likely to be victimized (Cernkovich & Giordano, 1987; Jennings et al., 2010; Matsueda & Heimer, 1987; Patterson & Dishion, 1985). Hirschi indicated that attachment to school is a relevant factor; youth’s relationship with teachers is also important. Liska and Reed (1985) highlighted the importance of ties to conventional institutions represented by the school. Agnew’s (1985) research suggested that ties to school and teacher attachment are stronger predictors of delinquency than parental attachment.

Cultural and Social Context of South Korean Juveniles

To properly assess the risk and protective factors of the progression of victimization among Korean youths, exploring the cultural and social background is necessary. Developmental studies tracing individuals’ life spans have identified the importance of one’s environment in predicting life outcomes (Farrington, 2003). South Korea is a developed country with a westernized social and education system. Although there may not be dramatic differences compared with findings from Western studies, certain distinct cultural features must be considered.

A particularly distinctive cultural characteristic of South Korea is the phenomenon of “grouped thinking” that stems from the collectivistic tradition (Cha, 1994). The collectivistic tradition places utmost importance on group norms, as opposed to individual autonomy and individual values that are prioritized in individualistic cultures in the West (Hofstede, 1991; Ojala & Nesdale, 2004). Grouped thinking influences institutions such as the workplace and schools, which in turn shape individual relationships with family and peers.

Grouped thinking prioritizes the well-being of the group over the individual and can translate to attempts to ignore, hide, or justify an individual’s victimization to protect group reputations (Ojala & Nesdale, 2004). For example, being bullied (one type of victimization) in school is often concealed to avoid soiling the school’s reputation. Also, individuals who fail to fulfill the demands of group norms may be victimized for the benefits of reinforcing adherence to the group’s principles (Koo, Kwak, & Smith, 2008). Under such circumstances, having a positive relationship with peers and teachers could serve as a protective factor to prevent victimization, as individuals could potentially avoid scrutiny and targeting.

In addition, South Korea is characterized by a widespread emphasis on education (Lee & Larson, 2000; Sorensen, 1994). Mandatory education is limited to junior high school in South Korea; yet more than 99% of juveniles continue their education until high school, and more than 70% of the nation’s youth enter into higher education (Kim, 2012; Korean Statistical Information Service [KOSIS], 2013). Given this context, Korean youth spend the majority of their time at school, which increases interaction with peers. Time spent in the school setting is supposed to be supervised by teachers and other elders who could potentially prevent victimization. However, the Korean Educational Development Institute (1998) found that more than half of students experienced verbal and physical bullying at school. Similarly, Kim, Koh, and Leventhal’s (2004) study also reported that 40% of students experienced victimization inside of school, which includes social exclusion and physical abuse. However, only a limited number of teachers recognize such victimization in the classroom (Korean Educational Developmental Institute, 1998), and prevention strategies (e.g., school transferring) fail to stop repeated victimization (Yang, 2005). It is possible that teachers’ inability to prevent victimization may be a result of grouped thinking in a collectivistic culture, wherein victimization can be regarded as an important step in the process of group formation.

The Current Study

Despite the necessity of a long-term approach in understanding victimization, very few longitudinal studies have examined this topic. Moreover, longitudinal studies on victimization have almost exclusively relied on American samples, and there is a dearth of longitudinal research on repeat victimization in different cultural contexts. The current study attempts to fill this gap by examining victim careers in five waves of data on youth in South Korea. A semi-parametric group-based approach is used to identify distinct groups of adolescent victimization. The present study aims to identify risk and protective factors for victimization by classifying juveniles into developmental pathways.

Method

Data

Data for the present study are drawn from five waves of the Korean Youth Panel Survey (KYPS), which consists of consecutive panel surveys following students from Grade 8 through their final year in high school. Data collection spanned from 2003 to 2007. The first wave includes 3,449 juveniles from 104 junior high schools. The KYPS data include data related to education, antisocial behaviors, and adolescent development. Data collection proceeded in three steps. First, to avoid potential bias, paper and pencil responses were used for problematic behavior questions. Second, skilled interviewers conducted interviews about other questions. Third, parents and juveniles participated in a telephone survey that was designed to gather information on family backgrounds, the education level of parents, and socioeconomic status.

The analytic sample for the current study is comprised of youth who participated in all five waves of surveys. Attrition generally occurred after the first wave, and most participants who completed the first- and second-year surveys remained in the study for all five waves. Participants lost to attrition were excluded from all waves, leaving the total sample for the current study at approximately 80% of the original KYPS sample. To identify the systematic bias from the sample selection, this study conducted independent samples t test using the first-year survey. Results revealed minimal differences between the analytic sample and those lost to attrition; mean differences for victimization, self-control, delinquent peer association, peer attachment, parental attachment, parental supervision, and teacher attachment were not statistically significant at the .05 level.

Measures

To investigate developmental trajectories of victimization, the present study assessed victimization across all five waves of the KYPS data. Risk and protective factors were measured in Wave 1 to examine factors that may distinguish participant membership in victimization trajectory groups. Four domains of risk and protective factors were examined: individual, parental, peer, and school factors. Individual factors consisted of sex (female = 0, male = 1), violent offending, and self-control. Parental factors included parental attachment and parental supervision. Peer factors were peer attachment and peer violence, and school factors included teacher attachment.

Victimization

Five dichotomous items were used to measure victimization. Respondents were asked whether they have been (a) threatened in the last year, (b) bullied in the last year, (c) seriously beaten up in the last year, (d) sexually assaulted or harassed in the last year, and (e) teased or ridiculed in the last year. Victimization is measured as the prevalence of any of these five types of victimization. During the first year of the KYPS, 16.5% of the sample reported victimization, 8.1% reported victimization during a second wave, and 4.0%, 2.8%, and 2.0% in consecutive years. Most frequent type of victimization was teasing, whereas sexual violence was the least frequent victimization type (see more details in Appendix).

Violent offending

Violent offending is composed of four items with dichotomous responses. Respondents were asked whether they have (a) threatened someone in the last year, (b) seriously beat someone up in the last year, (c) robbed someone up in the last year, and (d) engaged in a gang fight in the last year. Of the total sample, 14.9% reported ever engaging in violence, with the most frequent type of violent offending being severely beating other person, comprising of 8.3% of the total sample.

Self-control

Self-control was measured by summing responses to six questions (α = .629). Items represent the five characteristics of low self-control identified by Gottfredson and Hirschi (1990): impulsivity, avoidance of difficult tasks in favor of simple tasks, risk-taking, self-centeredness, and short-temper. Participants responded to each question on a 5-point Likert-type scale. For example, the items “I abandon a task soon once it becomes hard and laborious to do” and “I don’t do my homework habitually” captured the preference for simple tasks. Impulsivity was measured by the item “I jump into exciting things even if I have to take an exam tomorrow.” The item “I am apt to enjoy risky activities” assessed risk-taking characteristics, and “I enjoy teasing and harassing other people” tapped into a self-centered personality. Last, “I lose my temper whenever I get angry” captured volatile temper of respondents. High scores represent lower self-control (Yu, 2010).

Parental attachment

Parental attachment was measured as the sum of two items (α = .723): (a) “I am comfortable sharing my thoughts and feelings with my parents,” and (b) “I often talk about what happens to me outside home.” Participants responded to each item on a 5-point Likert-type scale. Higher values indicate greater parental attachment (Kim, Kwak, & Yun, 2010).

Parental supervision

Four items were used to measure parental supervision with a 5-point Likert-type scale (α = .844): (a) “When I go out, parents usually know where I am,” (b) “When I go out, parents usually know whom I am with,” (c) “When I go out, parents usually know what I am doing,” and (d) “When I go out, parents usually know when I will return.” Higher values indicate greater parental supervision (Han & Grogan-Kaylor, 2013).

Peer violence

Association with violent peers was measured with seven dichotomous items asking whether youth had friends who threaten and bully other people, rob money, engage in gang fights, and commit physical and sexual violence in last year. Higher values represent a respondent has greater delinquent peer association (Kim et al., 2010).

Peer attachment

Four questions were combined to assess peer attachment (α = .753). The first question asked about their willingness to maintain the friendship and following questions asked their enjoyment of friendship, shared feelings, and candid conversation with peers (Kim et al., 2010). Higher values indicate greater peer attachment (Kim et al., 2010).

Teacher attachment

Three items were used to measure teacher attachment (α = .710): (a) “I can share and discuss my problem with teachers,” (b) “Teachers show their love and affection to me,” and (c) “I want myself to be a person like teachers in school.” Respondents showed their agreement to each item by responding on a 5-point Likert-type scale. Higher values indicate greater teacher attachment (Kim et al., 2010).

Analytic Strategy

To assess victimization trajectories (Waves 1-5, ages 14-18 years) and explore risk and protective factors (Wave 1), semi-parametric group-based models were estimated using Stata 13 software. Initially, to identify the optimal number of latent trajectory groups, five different cubic specifications were examined. Next, the different orders of polynomials were assessed within the number of trajectory groups identified as optimal. Bayesian information criterion (BIC), a criterion for model selection, was chosen to evaluate model fit. BIC based on the log likelihood value of the fitted model is a recommended option to identify the correct number of components. The minimized BIC (close to 0) indicates the best trajectory model (Brame, Nagin, & Wasserman, 2006; Nagin, 2005). In addition, the mean posterior probability was computed to assess the fitness of the selected model (Nagin, 2005). Within the selected victimization trajectory model, bivariate odds ratios between risk and protective factors and each pair of comparisons were measured. Multiple imputation was used to handle the missing values in the analysis.

Results

Table 1 presents baseline information of the examined variables. Table 2 shows the optimal number of trajectory group selection by comparing the BIC score in five different cubic specifications. Within these five cubic specifications, BIC were minimized (−2,894.81), and it was determined that the optimal number of trajectory groups was three. The best fitting order of polynomials and the mean posterior probability were estimated for these three trajectory groups (see Table 3 and 4). Each group showed a higher mean posterior probability than the .70 cutoff by Nagin (2005; non-victimization group = .785; sharp-decreasing group = .771; decreasing group = .857).

Table 1.

Descriptive Statistics (N = 2,721).

	M	SD	Maximum
Victimization (Wave 1)	0.221	0.415	1
Victimization (Wave 2)	0.110	0.312	1
Victimization (Wave 3)	0.049	0.215	1
Victimization (Wave 4)	0.033	0.180	1
Victimization (Wave 5)	0.021	0.145	1
Sex (Wave 1)	0.503	0.500	1
Violent offending (Wave 1)	0.235	0.424	1
Self-control (Wave 1)	10.063	3.957	24
Parental attachment (Wave 1)	6.301	1.948	8
Parental supervision (Wave 1)	8.902	3.424	16
Peer violence (Wave 1)	0.383	0.486	1
Peer attachment (Wave 1)	12.228	2.585	16
Teacher attachment (Wave 1)	4.394	2.474	12

Table 2.

The Optimal Number of Groups Using BIC in Five Different Cubic Specifications.

Number of groups	Victimization
1	−3,067.86
2	−2,908.02
3^a	−2,894.81
4	−2,914.59
5	−2,933.48

Note. BIC = Bayesian information criterion.

Selected model.

Table 3.

Model Selections With Different Orders of Polynomials.

Victimization	BIC
(3 3 3)	−2,894.81
(0 3 3)^a	−2,886.51

Note. BIC = Bayesian information criterion.

Selected model.

Table 4.

Trajectory Group Posterior Probabilities.

Victimization	M	SD
1. Non-victimization	0.7854	0.0274
2. Sharp-decreasing	0.7709	0.0970
3. Decreasing	0.8572	0.2022

Figure 1 graphically shows the examined victimization trajectories. Consistent with previous studies, more than half of respondents (62.1%) belong to the non-victimization group. The sharp-decreasing group, which makes up about 28.3% of the sample, starts with relatively high victimization, sharply declines after age 14 years, and then overlaps with the non-victimization group at ages 16 to 18 years. The decreasing group (high victimization group), which comprises of 9.5% of the sample, begins with high victimization and gradually declines but still shows relatively high victimization experiences compared with two other groups.

Figure 1.

Group-based trajectories of South Korean juveniles’ victimization.

Table 5 displays the factors related to the transition of victimization over time. The non-victimization group shows a difference from the sharp-decreasing and the decreasing groups in similar factors except for teacher attachment. Among the within-individual characteristics, violent offending predicts membership to the sharp-decreasing and decreasing groups when compared with the non-victimization group. The level of self-control showed no meaningful explanation for the prediction of victimization trajectories. Parental supervision indicates a negative association with both the sharp-decreasing and decreasing group memberships when compared with the non-victimization group. Such results may indicate that parental supervision could prevent juvenile’s victimization, but does not predict decreasing patterns. Association with violent peers showed no meaningful explanatory power to distinguish the non-victimization group membership from the other victimization experience groups. However, peer attachment shows that it could prevent membership to the victimization experience groups and could be the chief factor in distinguishing observed decreasing victimization patterns. Juveniles who have strong peer attachment are more likely to be associated with the non-victimization group; in addition, the level of peer attachment predicts the upcoming transition of victimization trajectories. Considering the school-related factor, attachment to teacher is only associated with the non-victimization group when compared with the sharp-decreasing victimization group. Juveniles who have a stronger attachment to a teacher are more likely to be in the non-victimization group when compared with the sharp-decreasing group.

Table 5.

Multinomial Logistic Regression of Each Pair of Comparisons.

	1 vs. 2		1 vs. 3		2 vs. 3
	OR	SE	OR	SE	OR	SE
Individual factors
Sex	1.201	0.128	1.239	0.207	1.032	0.192
Violent offending	2.005	0.295***	2.358	0.520***	1.176	0.284
Self-control	1.002	0.012	1.005	0.018	1.003	0.020
Parental factors
Parental attachment	1.009	0.030	1.031	0.049	1.021	0.054
Parental supervision	0.946	0.016**	0.921	0.024**	0.973	0.028
Peer factors
Peer violence	1.228	0.188	0.975	0.241	0.794	0.212
Peer attachment	0.955	0.015**	0.891	0.022***	0.933	0.026*
School factors
Teacher attachment	0.944	0.021**	0.971	0.034	1.028	0.040

Note. 1 = non-victimization; 2 = sharp-decreasing; 3 = decreasing.

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

Discussion

Using longitudinal data from five waves of South Korean adolescents, the current study explored victimization trajectories. Three victimization trajectories were revealed, each with distinct variation. Consistent with prior research, only a small number of respondents were placed in the repeat victimization group. This group was only comprised of about 9.5% of the total sample, but these individuals tend to report continuous but decreasing victimization. This finding is in concert with that of other studies (Higgins et al., 2009; Sullivan et al., 2011), although Sullivan and colleagues (2011) discovered four trajectory groups using group-based latent growth curve models. Overall, findings from the present study are similar to those of studies using American data. However, both American studies found evidence of an increasing victimization trajectory, whereas the present study did not.

It is unclear precisely why increasing victimization patterns were not observed among South Korean juveniles’ victimization trajectories. This unexpected finding may be explained by the “once bitten, twice shy” perspective, which assumed that victims will change their behaviors to prevent subsequent victimization (Hindelang et al., 1978). Hindelang and colleagues (1978) stated that the “behavioral effects of crime or the fear of crime appear more as subtle adjustments in behavior than as major shifts in what can be called behavioral policies” (p. 224). Victims may learn from the previous victimization and adapt, attempting to protect themselves from future crimes. Although studies testing the effects of victimization on lifestyle changes have yielded mixed results, there has been some empirical support for the “once bitten, twice shy” hypothesis (Dugan, 1999; Ferraro, 1995; Lavrakas, 1981; Lurigio, 1987; Rountree & Land, 1996; Skogan, 1987; Skogan & Maxfield, 1981; Xie & McDowall, 2008). For example, Skogan and Maxfield (1981) reported that victims are more likely to change their behaviors as a result of crime, compared with non-victims. Averdijk (2011) analyzed longitudinal data from the National Crime Victimization Survey (NCVS) and explored the relationship between victimization and routine activities. Results were somewhat mixed; however, Averdijk did find some support for the “once bitten, twice shy” hypothesis. A significant behavioral change was found among victims of violent crimes.

Another possible explanation for the emergence of only decreasing trajectories may be the developmental changes that South Korean juveniles undergo within the educational systems. The current study examined victimization trajectories, ages between 14 and 18 years. In these periods, youths are tirelessly required to pay increased attention to academic performance and school achievements. To get offered admission into prestigious universities, South Korean students typically spend the majority of their time in public and private education systems, eventually isolating them from the other juveniles who may be delinquent. In particular, South Korean juveniles transition from junior high school to high school at age 16 years. High schools very strongly emphasize the importance of attending universities, and such a focus may steer youth away from increasing patterns of victimization. Increasing victimization trajectory groups may be present among youths who drop out of schools, although these individuals were not included in the KYPS data.

In addition, the present study investigated risk and protective factors of repeat victimization and demonstrated that groups of differing levels of victimization have different protective and risk factors. Initially, juveniles’ violent offending predicted membership to victimization trajectory groups when compared with the non-victimization group. Previous studies have noted a meaningful relationship between engaging in violence and experiencing victimization (Jennings et al., 2010; Jennings et al., 2012; Schreck et al., 2008), and the current study also finds evidence of that relationship, even in a different cultural and social context. In understanding the role of self-control as a risk factor of victimization, theoretical interpretations would suggest that individuals with low self-control are more likely to put themselves in dangerous situations, which would, therefore, result in them being highly vulnerable to victimization. Higgins et al. (2009) found relatively stable self-control trajectories, which are related to violent victimization trajectories, but the current study found no meaningful impact of self-control on victimization trajectories. It is possible that individuals in South Korea may be at a reduced likelihood of victimization related to low self-control compared with individuals in Western contexts. By virtue of possessing low self-control, individuals are expected to put themselves into dangerous circumstances. Yet youth in South Korea spend the majority of their time under supervised circumstances (e.g., long time spent in the school), which may make them especially vulnerable to the impact of peers and parents on victimization. Future research should examine the impact of self-control on victimization across different cultural contexts. For parenting, parental supervision was the factor related to preventing victimization and not attachment. However, when examining peer factors, attachment to peers is a meaningful predictor of being outside of victimization groups. It may be that having a good relationship with peers could prevent the chance of victimization during daily interaction with peers, but having a good relationship with parents has little impact on juvenile’s victimization.

Findings comparing teacher attachment among groups are somewhat difficult to interpret. Only the comparison between the non-victimization group and the sharp-decreasing group showed a statistically meaningful impact of teacher attachment. The descriptive statistics in Table 1 show that the mean of teacher attachment is lower than that of parent and peer attachment. Also, previous studies have consistently shown teachers’ failure to prevent and acknowledge students’ victimization in South Korea (Yang, 2005). Similar to parental relations, teacher attachment can be limited in preventing victimization of juveniles, as the main interaction group of mid and late juveniles’ transitions to peer groups. Considering the role of teachers in school, results might show significant effects when measured variables are related to supervision or monitoring of teachers, other than emotional relations such as attachment. Descriptive statistics show shared mistrust among teachers, yet when teachers have knowledge of occurrences in school, they have the authority to control such behaviors and can eventually prevent victimization in school. Our results suggest that when juveniles maintain positive relationships with teachers, they are less likely to experience victimization, but this is limited in explaining the comparison between the chronic (generally decreasing pattern) and the non-victimization group, due to failure to fully describe teacher’s effects on victimization.

Several limitations were present in the current study. First, the study included only five waves limited to youth in mid to late adolescence. More waves would allow for more long-term observation of participants. Second, collecting surveys from students who are in education system poses another limitation. Future research using other South Korean samples should also include juveniles outside of the educational system. This is necessary to reveal the exact developmental patterns of South Korean juveniles’ victimization and address our speculation that the unique nature of South Korean high schools isolates youth from increasing victimization patterns. Third, this study included limited factors and did not include psychological factors or community factors. One example is the school-related factors only measure the attachment to the teacher. Other than the attachment measure, actual monitoring or supervision might be a more meaningful factor to explain the victimization trajectories. Last, because this study indicated that engaging in violence was an important predictor of victimization trajectory membership, future research should direct more attention to violence, in particular, following the mutual transition of both violence trajectories and victimization trajectories.

Footnotes

Appendix

The Percentages of Each Different Type of Victimization.

	Teasing	Threatening	Bullying	Physical violence	Sexual violence	Ever victimized
Wave 1	9.9	4.5	4.4	3.7	1.1	16.5
Wave 2	5.0	2.2	1.6	2.2	0.4	8.1
Wave 3	2.4	0.8	0.7	0.8	0.4	4.0
Wave 4	2.2	0.4	0.6	0.3	0.6	2.8
Wave 5	1.2	0.6	0.4	0.3	0.3	2.0

Note. The current study used “ever victimized” to investigate victimization trajectories, due to sharp decreasing patterns of each type of victimization experiences after Wave 3 that mostly reported less than 1% of total sample.

Acknowledgements

We thank Dr. Chris Gibson and Dr. Marvin Krohn for their thorough comments on our work.

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) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Yeungjeom Lee is a criminology doctoral student in the Department of Sociology and Criminology & Law at the University of Florida. Her primary interests include life course/developmental criminology and juvenile delinquency.

Jihoon Kim is a PhD student in the Department of Sociology and Criminology & Law at the University of Florida. His research interests lie in the area of life course/developmental theory and quantitative analysis.

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