Correlates of Repeat Victimization and Sex Differences in South Korean Youth

Abstract

Interest in the correlates of victimization has significantly increased in criminology, while focusing on a few criminological theories, risky lifestyles/routine activities, and self-control. This study is to explore the applicability of five criminological theories, including social control theory, collective efficacy, and strain theories as well as risky lifestyles/routine activities and self-control to explain the correlates of repeat victimization. The current study also explores sex differences/similarities of Korean youth in the correlates of repeat victimization. Current study analyzes data from two waves of Korean Youth Panel Survey by using logistic regression. Results show that risky lifestyle/routine activities, social control, and general strain variables better explained the chance of repeat victimization than other theories (i.e., self-control and collective efficacy). In addition, this study suggests future study to focus on peer-related issues for girls’ repeat victimization and by addressing family-related issues for boys’ repeat victimization.

Keywords

victimization South Korea self-control risky lifestyles social control strain collective efficacy

Introduction

The volume of research on correlates of victimization has increased in criminology due not only to the detrimental effect of victimization on victims’ mental health, such as depression, anxiety, suicide attempts, and posttraumatic stress disorder symptoms (Mesman-Moore, Long, & Siegfried, 2000), but more importantly to the similarities between offenders and victims, suggesting the applicability of criminological theories to victimization (Jennings, Piquero, & Reingle, 2012). Risky lifestyle/routine activity and self-control theory are two major frameworks applied to explain the correlates of victimization. Past studies using these theories have found that variables of both theories had significant relationships with victimization in general; furthermore, models simultaneously including variables from both theories provided more reliable estimates of the relationships among them. This result confirms the importance of considering an individual’s daily routines and level of self-control to explain the risk of future victimization (Pratt, Turanovic, Fox, & Wright, 2014; Turanovic & Pratt, 2014).

Despite the considerable increase of victimization research, two major issues have not been fully addressed. The first issue is relevant to the correlates of repeat victimization. According to the National Crime Victimization Survey (NCVS), between 2000 and 2009, 15.6% of violent crime and 2.6% of property crime were repeat victimizations (Lauritsen, 2012). However, research on victimization has used primarily single or initial victimization. The limited studies on repeat victimization have focused on personal relationships between victims and offenders (Deadman & MacDonald, 2004; Ousey, Wilcox, & Fisher, 2011), victims’ demographic characteristics, and certain types of victimization (Carbone-Lopez, Esbensen, & Brick, 2010). These repeat victimization studies generally utilize the risky lifestyle/routine activity and self-control theories.

The second issue relates to sex differences in the correlates of repeat victimization. Recent research has shown that criminological theories might not apply to males and females in the same way; moreover, correlates of crime might vary across the sexes to a certain degree (Augustyn & McGloin, 2013; Jo & Bouffard, 2014; Jo & Zhang, 2014). The personal and social similarities between victims and offenders suggest the possibility of sex differences in the correlates of victimization as well. Indeed, a few studies examining sex differences in correlates of victimization have provided supportive evidence that some family and neighborhood characteristics, such as single parent status, length of residence, household income, immigration status, and residential instability, affect violence victimization for either males or females (DeWees & Parker, 2003; Lauritsen & Carbone-Lopez, 2011). Still, these studies have failed to separate single victimization from repeat victimization, thereby requiring more research on how sex affects repeat victimization.

The current study is an effort to fill the gap in the literature of victimization to help both researchers and practitioners better understand the correlates of repeat victimization as well as the influence of sex. Drawing on results from two waves of the Korea Youth Panel Survey, the study examines the applicability of several criminological theories, including social control, strain, collective efficacy, risky lifestyle/routine activity, and self-control theories, to estimate their relative influence on repeat victimization. In addition, the current study explores both similarities and differences in correlates of repeat victimization between males and females.

Literature Review

Recent research on victimization has examined, among other factors, the applicability of criminological theories to the etiology of victimization (Hawdon & Ryan, 2009a; Holtfreter, Reisig, & Pratt, 2008; Wilcox, Tillyer, & Fisher, 2009). Routine activity/lifestyles and low self-control have often been included as the correlates of victimization whereas much less attention has been paid to relevant variables in other criminological theories, such as social control, collective efficacy, and strain theories. This section reviews findings on victimization from several theoretical viewpoints to identify the limitations of the current victimization literature.

Lifestyles/Routine Activities, Low Self-Control, and Victimization

According to lifestyles/routine activity theory, characteristics of an individual’s life routines are significantly related to the risk of victimization (Hindelang, Gottfredson, & Garofalo, 1978). In particular, three elements should converge in time and space for an individual to be involved in victimization during a crime: motivated offenders, the presence of a suitable target, and the absence of capable guardians (Cohen & Felson, 1979; Holtfreter et al., 2008; Mustain & Tewksbury, 2002). Early studies using this theory focused on demographic and social status variables. For example, people who are younger, non-White, male, nonmarried, unemployed, and of lower social status are more likely to be victims than their counterparts (Cohen & Cantor, 1980; Mustaine & Tewksbury, 1998). More recent research has frequently used prior delinquency and deviant peer association as indicators of risky lifestyles/routine activities to explain both victimization and repeat victimization as well as show the strong relationships between them (Jennings et al., 2012; Schreck, Ousey, Fisher, & Wilcox, 2012; Schreck, Stewart, & Osgood, 2008). For example, previous studies have found a significant association between property and violent victimization and delinquent behaviors among teenage students (Stewart, Schreck, & Simons, 2006; Zaykowski & Gunter, 2012). Other studies have identified significant relationships between victimization and drug and cyber delinquency among both teenage students and college students (Bossler & Holt, 2009; Franklin, Franklin, Nobles, & Kercher, 2012).

A recent meta-analysis conducted a comprehensive review of 37 studies to examine the overlap between offending and victimization (Bossler & Holt, 2009; Jennings et al., 2012). According to the results of the 37 studies, 31 provided strong support for the link between offending and victimization while the remaining studies showed mixed/limited support. Notably, the identified relationship remained significant across different types of analytical techniques and data. Furthermore, research has shown that a delinquent peer association had both direct and indirect influences on violent victimization through unstructured supervision (Schreck, Wright, & Miller, 2002). This relationship remained significant even after controlling for participants’ self-control levels (Schreck, Stewart, & Fisher, 2006; Schreck et al., 2008). In addition, friends’ violence has significant influences on overall victimization, nonviolent victimization, and differential (neither violent nor nonviolent) victimization (Schreck et al., 2012). Finally, delinquent peer affiliation is a significant predictor of violent and theft victimization among adolescents from 30 countries (Posick, 2013).

Whereas lifestyles theory emphasizes the situational factors of victimization, self-control theory highlights an internal factor—namely, low self-control—as the major cause of crime and analogous behavior. According to M. R. Gottfredson and Hirschi (1990), people with low self-control are short-sighted and insensitive to the feelings of others; they exhibit low tolerance for frustration, lack persistence and tenacity, prefer physical activities to mental ones, and enjoy thrill-seeking activities. Thus, people with low self-control are more likely to be driven by momentary pleasure without considering the consequences of their activities, making them more exposed or vulnerable to trouble and risky situations, including crime (Holtfreter et al., 2008; Schreck, Stewart, & Fisher, 2006).

Since Schreck (1999) first reformulated the general theory to explain victimization, using findings that low self-control significantly increases the possibility of victimization, empirical studies have provided specific evidence that low self-control is related to property and violent crime victimization, such as burglary, auto theft, assault, robbery, theft, homicide, and bullying (Baron, Forde, & Kay, 2007; Gibson, 2012; Schreck et al., 2006; Tillyer, Fisher, & Wilcox, 2011; Unnever & Cornell, 2003). However, some studies have also demonstrated that the effect of low self-control on violent and cybercrime victimization is mediated by risky lifestyles (Bossler & Holt, 2009; Vazsonyi, Machakova, Sevcikova, Smahel, & Cerna, 2012). In their recent meta-analysis, Pratt et al. (2014) reviewed 66 studies examining the association between self-control and victimization. The results indicated that, although low self-control was a consistent predictor of victimization, the effect of low self-control significantly decreased when controlling for risky lifestyles and behaviors. This finding implies that lifestyle variables either partially or fully mediate the association between low self-control and victimization.

Social Control, Collective Efficacy, Strain, and Victimization

Compared with the risky lifestyles/routine activities and low self-control explanations of victimization, the social control, collective efficacy, and strain theories have received much less attention from researchers. Hirschi (1969) proposed four fundamental concepts of social control theory—namely, attachment, commitment, involvement, and belief—that cause people to disconnect from delinquent behaviors (Wiatrowski, Griswold, & Roberts, 1981). For example, according to Hirschi’s (1969) theory, attached adolescents do not want to disappoint the person to whom they are attached or lose a good relationship with him or her. In addition, adolescents committed to conventional institutions avoid the risk of losing the stakes they have in a community. Involvement in conventional activities makes adolescents spend most of their time and energy on these activities, leaving them no time for delinquent behaviors (Hirschi, 1969; Matsueda & Heimer, 1987). Adolescents who subscribe to conventional norms also internalize these norms and attempt to avoid criminal activities due to their inconsistency with the norms (Hindelang, 1973). Thus, individuals who are attached, committed, and involved with conventional systems and who believe in following the law are less likely to become involved in risky behaviors, thereby lessening their chance of being victimized.

Studies using the social control theory have primarily examined the correlates of victimization at school. Some such studies found that attachments to teachers and school, commitment to school performance, and law-abiding beliefs negatively influence violent victimization, such as being threatened, shot or stabbed, jumped, and bullied (Cunningham, 2007; Payne, Gottfredson, & Gottfredson, 2003), as well as both property and violent crime victimization (Popp & Peguero, 2012). Research on the relationship between family bonding and victimization showed that low family bonding and negative parenting styles (e.g., hostile, harsh, and abusive) are related to children’s physical and relational victimization and the onset of poly victimization (Finkelhor, Ormrod, Turner, & Holt, 2009; Menard & Grotpeter, 2011; Schwartz, Dodge, Pettit, & Bates, 1997). Finally, Wilcox et al. (2009) found that the associations between social control variables and victimization are conditioned by sex. Specifically, significant relationships are evident among parental and peer attachment, theft victimization, and assault victimization for girls, but only among involvement with school performance, peer attachment, and assault victimization for males.

Collective efficacy, a refinement of social disorganization theory, is considered one way to control crime. Sampson and colleagues (Sampson, Morenoff, & Earls, 1999; Sampson, Raudenbush, & Earls, 1997) defined collective efficacy as the social cohesion to intervene in social problems and pursue the common good. Sampson (1997) articulated this concept as “the linkage of mutual trust and shared willingness and intention to intervene for the common good” (p. 919). Communities with high levels of collective efficacy can reduce potential problems by providing community-level social control, such as supervising adolescents and providing resources for their community (Smith & Jarjoura, 1988). Such collective efficacy decreases the possibility of adolescents’ involvement in delinquent behaviors by providing community-level protection; consequently, it can decrease potential victimization of the adolescents as well.

Sampson et al. (1997) further used residential stability to measure collective efficacy, finding a negative relationship between collective efficacy and violent victimization in the Chicago area. A series of subsequent studies have provided supporting evidence that local friendship networks, control of street-corner teenage peer groups, and the prevalence of organizational participation significantly reduce community victimization rates (Lowenkamp, Cullen, & Pratt, 2003; Vesey & Messner, 1999). The significant relationship between community social control (i.e., collective efficacy) and victimization also appeared in studies using data from Chicago (Browning, Feinberg, & Dietz, 2004) and South Carolina (Hawdon & Ryan, 2009b). Finally, using Police Service Survey data, Velez (2001) showed that high levels of community social control significantly decrease household victimization rates.

According to strain theories, the strains caused by limited legal instruments to achieve economic or social status success are major sources of criminal or similar behaviors. Merton (1957) asserted that, when individuals cannot legally attain culturally defined goals, they use illegal means to get what they want. Agnew (1992) expanded the definition of strains by arguing that they can occur when individuals are not treated as expected or cannot avoid undesired situations, such as rejection by peers, hostility from parents, or negative experiences at school. The strain correlates negative emotions, including anger and frustration, thereby forcing individuals to become involved in delinquent behaviors as corrective actions (Agnew, 1992, 2001). These negative emotions can also lead to thinking problems, such as difficulty making reasonable and ethical decisions and considering the outcomes of one’s behaviors (Carmichael & Piquero, 2004). The cognitive problems result in inappropriate treatment and behaviors, leading to a greater risk of victimization.

Ladd, Kochenderfer, and Coleman (1997) used data from 116 kindergarten children to examine the linkage between loneliness, one school adjustment measure, and peer victimization. They found that children’s loneliness is significantly associated with peer victimization. Using parents’ and teachers’ observations of children’s negative emotions, Hanish et al. (2004) found similar relationships among negative emotions—namely, aggression and anger—and peer victimization among a sample of 154 preschool and kindergarten students. Children’s aggression and anger toward their friends during the fall semester directly influenced peer victimization in the subsequent spring semester. Kochenderfer-Ladd (2004) similarly found that children’s negative emotions in the fall semester affected their maladaptive coping skills, such as asking for help less often and seeking revenge, which were linked to their peer victimization in the subsequent spring semester.

Research on Victimization in Contemporary South Korean Context

Confucianism is one of the major characteristics which has influenced the current South Korean culture. Moral systems in South Korea have been influenced by Confucianism from Choson Dynasty (Hong, Lee, Lee, Lee & Garbarino, 2014). Based on Confucianism, all power and benefits from family are given to sons who have important responsibility to inherit and accumulate family’s property. Therefore, male chauvinism, which strongly related to the paternalism, was widespread from family to society while daughters’ rights and status were suppressed (Chung & Gupta, 2007). However, thanks to significant changes in the society including feminism, the economic crisis, and lower birthrates, girls are encouraged to live more actively and to get involved in more social activities, which might influence their lifestyles such that peer-related factors become more important than other factors (Chung & Gupta, 2007). In contrast, boys’ lifestyles might be more influenced by family factors given that parents monitor their sons more closely than before (J. I. Kim & Chung, 2012).

Those changes in environments and expected sex-role seem to lead to changes in correlates of victimization; however, there was very limited literature on criminal victimization in South Korea until Criminal Victimization Survey in Korea was first conducted with a national sample in 1995. The Criminal Survey in Korea/Korean Crime Victim Survey¹ was conducted 8 times until 2015 by Korean Institute of Criminology. The survey focused mainly on the prevalence of criminal victimization across different types of victimization and correlates of victimization using neighborhood and lifestyle variables instead of testing diverse criminological theories. The major limitation of this survey is that it was conducted with a different sample each time failing to examining issues relevant to repeat victimization (i.e., getting victimized again and again over years) (Choi, Kim, Whang, & Park, 2015).

Around 2000, the first Korean Youth Panel Survey which included victimization items was collected. However, research on correlates of victimization with the data was recently conducted within the frameworks of criminological theories (Cho, Wooldredge, & Sun Park, 2016; Jo & Lee, 2017; S. Kim, 2010; Lee & Kim, 2017; Moon, Morash, Jeong, & Yoon, 2016; Park, 2015). Although these studies tested the applicability of criminological theories to victimization such as routine activity/lifestyles, self-control, social control, collective efficacy, and strain theories, there are handful literatures which explored repeat victimization issues by using criminological theories (Cho et al., 2016; Jo & Lee., 2017; Lee & Kim, 2017; Moon et al., 2016; Park, 2015) The results showed significant relationships between those theoretical variables and victimization in general with no significant effect of lifestyle variables (Noh, 2007). Due to availability of the national victimization data and the youth panel data, interest in victimization has been increased in South Korea; however, research on sex issues in relation to correlates of repeat victimization were very limited.

Limitations of Previous Studies

Despite a significant increase in the application of criminological theories to understand the correlates of victimization, two notable limitations exist in the current victimization literature. First, as previously noted, lifestyles/routine activities and self-control theories have received disproportionate attention from researchers, even though other theories could be used as alternative explanations of repeat victimization (Farrell, 1995; Schreck et al., 2006; Turanovic & Pratt, 2014). In addition, the types of repeat victimization analyzed are limited to a few specific types of violent crime, such as sexual assault, intimate assaults, and child abuse, instead of using general violent victimization (Finkelhor, Ormrod, & Turner, 2007; Planty & Strom, 2007; Ruback, Clark, & Warner, 2014).

Second, previous research on repeat victimization seemed to treat sex as one of control variables, generating findings that males are more likely than females to experience repeated victimization of violent and property crime (Menard, 2000; Menard & Huizinga, 2001). To date, very few studies have explored sex differences in the etiology of repeat victimization within criminological theory frameworks. Ruback et al. (2014) examined sex differences in the relationship between first victimization and revictimization using three-wave data. The results indicated that males’ first victimization indirectly influenced their revictimization through their involvement in violent offending. Meanwhile, for females, initial victimization was indirectly related to subsequent victimization, specifically through heavy drinking.

The goal of the current study is to address two hypotheses using a nationally representative sample of South Korean youth. First, other criminological theories, such as social control, collective efficacy, and strain theories, can explain repeat victimization as well as risky lifestyle/routine activity and self-control theories. Second, boys and girls would have different correlates of repeat victimization.

Method

Data

The current study used fourth-grade cohort data extracted from the 2004 and 2005 Korea Youth Panel Survey conducted by the National Youth Policy Institute. This survey examined the influences of individual characteristics, family, school, peers, and community-related variables on job selection, leisure time, delinquency, and victimization. To obtain a nationally representative sample, a stratified multistage cluster sampling design was used. First, 84 elementary schools were randomly selected from 15 South Korean jurisdictions, based on the number of students in each jurisdiction. Next, one fourth-grade class from each school was randomly selected. The total number of students who were eligible for the survey was 2,970 (K. S. Lee & Jo, 2004). After an orientation session regarding confidentiality and the study’s purposes and procedures, 2,844 students (participation rate was 95.76%) whose parents consented were included in the survey. In 2004, the first survey was conducted in each student’s respective classroom; a follow-up telephone survey was conducted with each participant’s parents. A face-to-face individual survey was conducted to collect students’ reported data of the 2005, and the parents’ data were collected using telephone survey (K. S. Lee & Baek, 2005). However, the current study used only students’ reported data due to significant number of missing cases in the survey with parents. Of the 2,844 students, 2,678 males and females participated in the 2005 follow-up survey. After deleting cases with missing values, which accounted for less than 1% of a variable, data from 2,552 students (1,191 females and 1,361 males) were used in the analyses.

Two groups (one included in the analyses and the other excluded from the analyses) were compared in all independent variables to examine any selection bias caused by attrition or missing data. The additional analyses showed no significant difference in all the independent variables except for strain from peer, total delinquency, violent delinquency, and Internet-related delinquency. The mean values of the four variables of the youth excluded from the analyses were greater than those of the sample included in the analyses. The group differences in the variables were significant at p < .05 (see the appendix for more information of group differences in the variables).

Measures²

All the independent variables were extracted from 2004 data, while the dependent variable was based on the responses in 2004 and 2005 data.

Dependent variable

Victimization was measured using six items. The youth were asked to respond to the following question: Have you ever experienced the following during the last year? (being severely teased or bantered, being threatened, being collectively bullied, being severely beaten [assaulted], being sexually assaulted [harassed], being robbed). Responses were coded as 0 = no and 1 = yes, with a higher score indicating a higher chance of being victimized. Repeat victimization is a dichotomous variable, with individuals who were victimized in both years labeled as 1 (repeat victimization) and those victimized in only 1 year (or neither year) labeled as 0 (nonrepeat victimization).

Independent variables

Five types of theoretical variables were used to examine their relative influences on repeat victimization: collective efficacy, lifestyles/routine activity, self-control, social control, and strain. Social control variables include attachment to parents, parental monitoring, abuse at home, and attachment to teachers which are relevant to attachment among the four elements of social control suggested by Hirschi (1969) and often included in prior research (Low & Espelage, 2014; Menard & Grotpeter, 2011; Wilcox et al., 2009). Attachment to parents, parental monitoring, and attachment to teachers were measured by the sum of six, four, and three items, respectively, on a 5-point scale (1 = never to 5 = always). For example, respondents were asked to respond to statements such as “My parents and I try to spend much time together” for attachment to parents (α = .76); “When I go out, my parents usually know where I am” for parental monitoring (α = .79); and “I can talk about all my troubles and worries to my teachers without reservation” for attachment to teachers (α = .55). In addition, abuse at home (α = .69) was added as a social control variable because previous studies show that negative parenting styles (e.g., hostile, harsh, and abusive) are related to children’s physical and relational victimization and the onset of poly victimization (Finkelhor et al., 2009; Schwartz et al., 1997). A composite scale of four items was used to measure abuse at home, in which respondents were asked to respond to statements such as “I am often verbally abused by my parents.” Responses were coded 1 = never to 5 = always.

Few studies examined the influence of collective efficacy on victimization (DeKeseredy, Alvi, & Tomaszewski, 2003; Sampson et al., 1997; Sapouna, 2010). A global measure of collective efficacy was included by summing four items (α = .59). For this measure, participants were asked to respond to statements such as “My neighbors have close relationships with each other.” Responses were coded as 1 = never to 5 = always, with a higher score indicating a higher attachment to neighbors.

Self-control was measured using six items (α = .64) that tapped the six dimensions of low self-control identified by M. R. Gottfredson and Hirschi (1990) (Piquero, MacDonald, Dobrin, Daigle, & Cullen, 2005; Pratt et al., 2014; Schreck, 1999, 2006; Schreck et al., 2002; Tillyer et al., 2011). For example, the participants were asked to indicate how strongly they agreed with statements such as “I abandon a task once it becomes hard and laborious to do,” “I am apt to enjoy risky activities,” and “I lose my temper whenever I get angry.” Responses for each item were coded as 1 = never to 5 = always, with higher scores indicating a lower level of self-control.

Five types of strain (parent-, school-, peer-, body-, and money-related strains) were measured using four (parent-related) or three (remaining types) 5-point scale items (Agnew, 2006; Hanish et al., 2004; Iratzoqui, 2018). The participants were asked to respond to statements such as “I get stressed by disputes with my parents” for parent-related strain (α = .83), “I get stressed by poor school grades” for school-related strain (α = .82), “I get stressed by a lack of recognition from my friends” for peer-related strain (α = .80), “I get stressed by weight issues” for body-related strain (α = .71), and “I get stressed by lack of pocket money” for money-related strain (α = .75). Responses for each item were coded as 1 = never to 5 = always, with higher scores indicating higher levels of strain.

Delinquency and deviant peer association (α = .78), often used in the literature of victimization as lifestyle/routine activity variables (Jennings et al., 2012; Schreck et al., 2012; Vézina et al., 2011), were included in the analyses. Four types of delinquencies (violent, nonviolent, substance-related, and Internet-related delinquency) were measured by summing six, eight, two, and six items, respectively. The youth were asked to answer the following question: Have you ever done the following acts during the last year? (i.e., threatening other friends and severely beating other people for violent delinquency, stealing and running away for nonviolent delinquency, drinking and smoking for substance-related delinquency, and using illegal software downloaded from the internet and using an unauthorized internet ID or someone else’s registration number for internet-related delinquency). The responses were coded as 0 = no and 1 = yes, with a higher score indicating more involvement in delinquency. A measure of association with delinquent peers using a sum of 16 items was included. The youth were asked to respond to the following question: Among your close friends, how many times did each of the following events take place during last year? (i.e., drinking, smoking, having unexcused absences from school, severely beating other people, robbing, and stealing). Responses were coded as 0 = none and 1 = one or more, with a higher score indicating a stronger affiliation with delinquent peers.

Finally, respondents were asked to indicate their sex (0 = female and 1 = male), which was included as a control variable.

Multicollinearity was checked by examining correlation coefficients among variables and variance inflation factor (VIF) values. The highest correlation coefficient was .62 between strain from parent and strain from school, and the highest VIF was 1.95 (strain from parent). Therefore, the multicollinearity assumption is not violated.

Analysis

All the analyses were conducted using IBM SPSS Statistics 19. First, descriptive statistics were identified, and a series of t tests were conducted to examine the mean differences in all variables between male and female youths. Second, two separate logistic regressions, which used logit link function, were conducted with the total sample to examine the relative effects of the theoretical variables on repeat victimization after controlling for sex. The first model included total strain and total delinquency along with other variables, while total strain and total delinquency were broken into five and four subcategories, respectively, in the second model to specify the relationships. Finally, like the models for the total sample, two models were used for female and male youths separately to explore sex differences in the relationships among the variables.

Findings

Table 1 provides the means, standardized deviations, and results of t tests between males and females. No significant difference emerged in repeat victimization between male and female youths, although more males were repeatedly victimized than females. Significant sex differences appeared in 13 out of 18 independent variables, including all four social control variables, collective efficacy, self-control, one strain variable, and all four delinquency variables, along with deviant peer association. More specifically, females exhibited significantly higher levels of attachment to parents and teachers and received more close monitoring by parents, whereas males were more likely to be abused at home. In addition, females tended to perceive higher community-level control than males did. Boys showed more interaction with deviant peers, lower levels of self-control, and more involvement in all types of delinquency while girls developed higher levels of body-related strain. Interestingly, both sexes had similar levels of strain in parent-, school-, peer-, and money-related variables.

Table 1.

Descriptive Statistics and t Test.

	Total (N = 2,552)		Female (n = 1,191)		Male (n = 1,361)		t Test
	M	SD	M	SD	M	SD	t Value
Dependent variable
Repeated victimization (1 = yes)	0.06	0.24	0.06	0.23	0.07	0.25	−1.07
Independent variables
Sex (1 = male)	0.53	0.50	N/A		N/A		N/A
Attachment to parent	22.38	4.38	23.05	4.22	21.80	4.43	7.22***
Parental monitoring	13.68	3.83	14.38	3.63	13.07	3.89	8.77***
Abuse at home	6.21	2.68	5.85	2.49	6.53	2.81	−6.45***
Attachment to teacher	8.23	2.70	8.83	2.63	7.71	2.65	10.62***
Collective efficacy	14.19	3.31	14.41	3.13	14.00	3.45	3.07**
Low self-control	13.29	4.10	12.37	3.82	14.09	4.16	−10.84***
Deviant peer association	2.22	2.48	1.86	2.16	2.53	2.69	−6.92***
Total strain	30.19	11.19	30.28	11.16	30.12	11.21	0.36
Strain from parent	7.59	3.50	7.45	3.42	7.71	3.56	−1.86
Strain from school	6.63	3.12	6.62	3.10	6.63	3.13	−0.06
Strain from peer	5.32	2.64	5.27	2.56	5.36	2.71	−0.91
Strain from body	5.60	2.71	5.98	2.78	5.27	2.61	6.64***
Strain from money	5.06	2.55	4.96	2.47	5.15	2.61	−1.84
Total delinquency	1.75	1.88	1.45	1.61	2.01	2.05	−7.62***
Violent delinquency	0.33	0.74	0.23	0.62	0.42	0.83	−6.31***
Nonviolent delinquency	1.02	0.93	0.94	0.88	1.10	0.97	−4.39***
Substance-related delinquency	0.08	0.29	0.04	0.20	0.11	0.34	−6.31***
Internet-related delinquency	0.31	0.69	0.24	0.59	0.38	0.77	−5.23***

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

Table 2 provides the results of logistic regression, with repeat victimization being regressed on sex and theoretical variables with the total sample. Total delinquency and total strain were included in the first model; in the second model, these variables were replaced with four and five subcategories, respectively, to provide more specific sources of victimization. The first model explained approximately 11% of the variance in repeat victimization, with four variables having significant influences on repeat victimization: abuse at home, deviant peer association, total delinquency, and total strain. The more the youth are abused at home, hang out with deviant friends, get involved in delinquency, and develop strain, the more likely they are to be victimized again. A one-unit increase in abuse at home results in youths being 1.09 times more likely to be victimized. Likewise, youths experiencing a one-unit increase in deviant peer association, total delinquency, and total strain are 1.07, 1.18, and 1.04 times more likely, respectively, to be repeatedly victimized.

Table 2.

Logistic Regression With Total Sample.

	Model 1				Model 2
	B	SE	Wald	Exp(B)	B	SE	Wald	Exp(B)
Sex	−0.06	0.18	0.10	0.94	−0.05	0.18	0.09	0.95
Attachment to parent	0.04	0.02	2.71	1.04	0.03	0.02	1.48	1.03
Parental monitoring	−0.05	0.03	3.51	0.95	−0.05	0.03	4.12	0.95*
Abuse at home	0.09	0.03	8.44	1.09**	0.08	0.03	7.62	1.09**
Attachment to teacher	−0.02	0.03	0.25	0.98	−0.03	0.03	0.70	0.97
Collective efficacy	0.01	0.03	0.21	1.01	0.03	0.03	0.95	1.03
Low self-control	−0.03	0.02	1.58	0.97	−0.03	0.02	1.61	0.97
Deviant peer association	0.07	0.03	5.45	1.07*	0.05	0.03	3.00	1.06
Total strain	0.04	0.01	20.39	1.04***
Strain from parent					−0.03	0.03	0.80	0.97
Strain from school					−0.02	0.04	0.20	0.98
Strain from peer					0.24	0.04	46.64	1.28***
Strain from body					0.01	0.04	0.15	1.01
Strain from money					−0.02	0.04	0.25	0.98
Total delinquency	0.16	0.04	18.89	1.18***
Violent delinquency					0.17	0.10	3.01	1.19
Nonviolent delinquency					0.26	0.09	8.06	1.29**
Substance-related delinquency					−0.58	0.30	3.78	0.56
Internet-related delinquency					0.19	0.11	3.29	1.21
Constant	−4.83	0.76	40.06	0.01	−4.62	0.77	35.87	0.01
	R² = .110				R² = .155

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

When total delinquency and total strain are broken into subcategories in the second model, the explanatory power of the model increases to around 16%. Only nonviolent delinquency and strain from peers were found to be significantly related to repeat victimization, along with parental monitoring and abuse at home. The more the youth are abused at home, become involved in nonviolent delinquency, and face conflicts with their peers, the higher their chance of being repeatedly victimized. On the contrary, the more closely a child’s behaviors are monitored by their parents, the less likely he or she is to become victims. The significant relationship between deviant peer association and victimization found in the first model disappears in the second model.

As in the analyses involving the total sample, two separate logistic regressions were conducted for each sex, with one model including total delinquency and total strain (Model 1 for females, and Model 3 for males) and the other model having subtypes of delinquency and strain (Model 2 for females, and Model 4 for males). In the first model shown in Table 3, the relationships between repeat victimization and deviant peer association, total delinquency, and total strain reached statistical significance. Increases in association with deviant peers, number of delinquent acts, and levels of strain led to an increase in repeat victimization. In the second model, the influence of deviant peer association remained significant. Similar to the second model with the total sample, both nonviolent delinquency and strain from peers affected the likelihood of being victimized again for female adolescents.

Table 3.

Logistic Regression Across Sex.

	Females								Males
	Model 1				Model 2				Model 3				Model 4
	B	SE	Wald	Exp(B)	B	SE	Wald	Exp(B)	B	SE	Wald	Exp(B)	B	SE	Wald	Exp(B)
Attachment to parent	0.02	0.04	0.42	1.02	0.03	0.04	0.72	1.03	0.05	0.03	2.72	1.05	0.04	0.03	1.38	1.04
Parental monitoring	−0.04	0.04	1.07	0.96	−0.07	0.04	2.50	0.93	−0.05	0.03	2.80	0.95	−0.05	0.03	2.46	0.95
Abuse at home	0.04	0.05	0.75	1.04	0.03	0.05	0.38	1.03	0.11	0.04	9.07	1.12**	0.12	0.04	9.74	1.13**
Attachment to teacher	−0.00	0.05	0.00	1.00	−0.01	0.05	0.01	1.00	−0.03	0.04	0.49	0.97	−0.04	0.05	0.90	0.96
Collective efficacy	0.02	0.04	0.27	1.02	0.04	0.04	0.84	1.04	0.00	0.03	0.01	1.00	0.02	0.04	0.31	1.02
Low self-control	−0.00	0.04	0.00	1.00	0.00	0.04	0.00	1.00	−0.05	0.03	2.66	0.95	−0.06	0.03	3.18	0.95
Deviant peer association	0.13	0.05	6.03	1.13*	0.11	0.05	4.17	1.11*	0.04	0.04	1.19	1.04	0.03	0.04	0.48	1.03
Total strain	0.03	0.01	7.35	1.03**					0.04	0.01	11.97	1.04***
Strain from parent					0.07	0.05	2.30	1.08					−0.11	0.04	6.21	0.90*
Strain from school					−0.11	0.06	3.50	0.90					0.05	0.05	1.19	1.06
Strain from peer					0.26	0.06	21.54	1.30***					0.23	0.05	25.21	1.26***
Strain from body					0.04	0.05	0.46	1.04					0.00	0.05	0.00	1.00
Strain from money					−0.10	0.06	2.96	0.90					0.04	0.05	0.61	1.04
Total delinquency	0.20	0.06	11.50	1.22**					0.15	0.05	8.21	1.16**
Violent delinquency					0.09	0.17	0.29	1.10					0.21	0.12	2.90	1.24
Nonviolent delinquency					0.33	0.15	4.90	1.39*					0.21	0.12	3.25	1.23
Substance-related delinquency					0.05	0.54	0.01	1.05					−0.83	0.38	5.09	0.43*
Internet-related delinquency					0.18	0.18	1.05	1.20					0.17	0.13	1.59	1.18
Constant	−5.06	1.22	17.21	0.01	−5.23	1.29	16.51	0.01	−4.59	0.95	23.38	0.01	−4.46	0.95	22.12	0.01
	R² = .118				R² = .173				R² = .114				R² = .174

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

The associations between the theoretical variables and repeat victimization for male youths appeared in Models 3 and 4. Model 3 demonstrated that abuse at home, total delinquency, and total strain were positively related to male youths’ victimization. As expected, when a boy is abused at home, becomes involved in deviant behaviors, and develops strain, his probability of becoming a repeat victim increases. When subcategories of delinquency and strain were added to the model (Model 4), in addition to abuse at home, substance-related delinquency, strain from parents, and strain from peers appeared to affect repeat victimization.

Both differences and similarities in sources of repeat victimization exist between male and female youths. Strain from peer relationships significantly affected repeat victimization for both sexes. Hanging out with deviant peers and getting involved in nonviolent delinquency had significant effects on female repeat victimization, while being verbally and/or physically abused at home, drinking alcohol and/or smoking cigarettes, and experiencing strain from parents were identified as major sources of repeat victimization for males.

Discussion

This study contributes to the literature of victimization in two ways. First, variables from five major criminological theories (i.e., social control, self-control, risky lifestyle/routine activities, collective efficacy, and strain) were utilized to examine their relative effects on the risk of repeat victimization. Second, the current study explored sex differences in the relationships between the theoretical variables and repeat victimization. To this end, data from 2,552 South Korean youths were analyzed.

Several interesting findings emerged. Some theories (i.e., risky lifestyle/routine activities, social control, and strain) better explained the chance of repeat victimization than other theories (i.e., self-control and collective efficacy). More specifically, this study found that nonviolent delinquency, parental monitoring, abuse at home, and strain from peers influenced adolescents’ repeat victimization. These findings are consistent with those of previous studies. For example, family connection reduces the risk of violence victimization (Shlafer, McMorris, Sieving, & Gower, 2013), while abuse at home and rejection from peers at school increase the risk of victimization (Salmivalli & Isaacs, 2005; Schwartz et al., 1997).

However, self-control and collective efficacy did not have a significant influence on repeat victimization. These findings somewhat contrast with those of prior research. According to prior studies, people with low self-control are more likely to put themselves into risky situations and make themselves more vulnerable to ramifications of crime (Baron et al., 2007; Gibson, 2012; Piquero, MacDonald, Dobrin, Daigle & Cullen, 2005; Schreck et al., 2006; Tillyer et al., 2011; Unnever & Cornell, 2003). As previously noted, this nonsignificant impact of low self-control might be explained by the mediation of risky behaviors between low self-control and repeat victimization (Bossler & Holt, 2010; Pratt et al., 2014; Vazsonyi et al., 2012). In other words, an individual’s level of self-control affects the probability of his or her involvement in risky behaviors, which directly influences the chance of being victimized. For example, low self-control influences offline perpetration, which influences cyber-bullying victimization (Bossler & Holt, 2010; Vazsonyi et al., 2012). Although previous studies found a significant relationship between collective efficacy and victimization (Hawdon & Ryan, 2009b; Velez, 2001), collective efficacy did not have a significant effect on repeat victimization in the current study. It is possible that individual-level ties fully mediate the influence of neighborhood-level ties on victimization (D. C. Gottfredson & DiPietro, 2011). For example, including closeness ties with teachers and conventional beliefs about delinquent behaviors in the equation results in school social capital not having an effect on victimization (D. C. Gottfredson & DiPietro, 2011).

The current study also found that relationships between delinquency measures and repeat victimization are partially consistent with those of prior search (Finkelhor & Asdigian, 1996;Stewart et al., 2006; Taylor, Freng, Esbensen, & Peterson, 2008; Turanovic & Pratt, 2014; Zaykowski & Gunter, 2012). Most previous studies used one overall measure of delinquency, although more recent studies tended to measure each type of delinquency (i.e., violence, property damage, minor offending, heavy drinking, and drug use) to specify its association with repeat victimization. Consistent with the current study, studies using one overall measure of delinquency showed a significant effect of delinquency on repeat victimization (Carbone-Lopez et al., 2010; Deadman & MacDonald, 2004; Ousey et al., 2011). The current study also demonstrated a significant effect of nonviolent delinquency on victimization, thereby supporting the results of previous research (Schreck et al., 2006; Wittebrood & Nieuwbeerta, 2000). However, some results of the current study contrasted with those of prior studies presenting significant relationships between violent offending, drug use, and heavy drinking and repeat victimization (Ruback et al., 2014; Turanovic & Pratt, 2014; Zaykowski & Gunter, 2012).

Finally, considerable sex differences as well as similarities in the correlates of repeat victimization exist. Although overall delinquency had a significant effect on repeat victimization for both girls and boys, sex differences appeared in the relationship between types of delinquency and repeat victimization. In other words, nonviolent delinquency influenced only girls’ repeat victimization while substance abuse influenced only boys’ repeat victimization. These results are somewhat consistent with those of prior studies. For example, males’ substance abuse (e.g., drug use and heavy drinking) is linked to their repeat victimization, but females’ substance abuse is not (Ruback et al., 2014; Zaykowski et al., 2013). Property offending experience is linked to property victimization, to which females are more vulnerable (Wittebrood & Nieuwbeerta, 2000).

Although overall strain levels influenced repeat victimization for both male and female students, sex differences were found in the relationships between types of strain and repeat victimization. For example, girls’ repeat victimization was affected by strain from peers while boys’ repeat victimization was influenced by strain from parents and peers. In addition, relationships with peers (e.g., deviant peer association) influenced girls more than boys, while relationships with family members (e.g., abuse at home) tended to affect boys more than girls. These findings are consistent with those of previous studies in term of the significant effects of family-related factors on victimization for boys (Ousey et al., 2011). However, there exist differences that peer-related factors affected repeat victimization for both male and female students (Carbone-Lopez et al., 2010; Ousey et al., 2011) with girls being more influenced by the factors than boys (Zimmer-Gembeck, Pronk, Goodwin, Mastro, & Crick, 2013). In addition, these findings contradict traditional beliefs that girls are more likely than boys to be influenced by their relationships with family members because of paternalism in South Korean culture. Yet the findings also seem to reflect changes in the South Korean culture regarding parenting and sex-role as addressed earlier. These findings are consistent with those of a few prior studies indicating that female victimization is affected by risky lifestyles and peer relationship (Vézina et al., 2011; Zimmer-Gembeck et al., 2013) while male victimization is connected with parental abuse and harsh parenting (Hosser, Raddatz, & Windzio, 2007).

Unfortunately, it is too early to make any suggestion regarding sex-specific victimization programs due to the paucity of research on sex differences in the correlates of repeat victimization. However, considering the sex differences found in the current study, repeat victimization might be more successfully prevented by focusing on peer-related issues for girls and by addressing family-related issues for boys. As previous studies have shown, a whole-school approach and targeted intervention seem to be effective in reducing adolescents’ victimization (DeRosier, 2004; Vreeman & Carroll, 2007). Especially for girls, such interventions should focus on eliminating bullying at school, providing counseling to resolve conflicts in peer groups, and teaching social skills to enhance friendships and interactions with peers. One representative program is the Olweus Bullying Prevention Program, which focuses on changing the climate in the community and school. Previous research has demonstrated the effectiveness of this program in reducing bullying (Limber, 2011; Olweus & Limber, 2010). In the case of male adolescents, it might be more effective for practitioners to help develop healthy family environments. For example, parental responsiveness and modeling behavior such as warmth, empathy, and compassion influence children’s self-esteem and interactions with other people; thus, improving communication styles between parents and sons or helping boys avoid social exclusion might reduce the risk of repeat victimization (Craig, Konarski, & Dev, 1998; Georgiou, 2008).

The findings of the current study should be interpreted with caution due to several limitations inherent in this research. First, the length of the study was limited. The current victimization scale did not measure victimization experience over the lifetime including, for example, third or sixth grade. Due to limitations of the current victimization items in the data set, we could not measure victimization over the lifetime, instead we used the victimization variables in fourth and fifth grades to divide the sample into two subgroups (nonrepeat victimization and repeat victimization). Therefore, it is possible that a participant in the nonrepeat victimization group experienced victimization before the first survey or after the last survey. This is an important issue to be considered for future research. Recently, several scholars have suggested applying a developmental perspective to study correlates of victimization as well as better understand the change in risk of victimization and the change in correlates of victimization over time (Finkelhor & Kendall-Tackett, 1997; Schnoll, Connolly, Josephson, Pepler, & Simkins-Strong, 2015). Although the current study cannot address this issue, it is one of a few studies that examined the correlates of repeat victimization using longitudinal data. Another limitation is that the victimization items were only relevant to violent victimization. Given the more detrimental outcomes compared with property victimization in general, this focus is understandable. However, it is also important to examine whether the correlates of victimization vary across different types of victimization. The correlates of property victimization might differ from those found in the current study. Last limitation is that results of this study are difficult to apply to victims in other age groups. Due to a lack of relevant data, we could not test this possibility, but we strongly encourage future researchers to pay more attention to these issues.

Despite these limitations, the current study contributed to the literature on victimization by examining the applicability of criminological theories not often used to explain repeat victimization. In addition, this study is one of the few to explore sex differences in the correlates of repeat victimization.

Footnotes

Appendix

Differences in Variables Between the Youth Included and the Youth Excluded.

Variable	Group	M	p Value
Sex	Excluded	0.55	.69
Sex	Included	0.53	.69
Attachment to parent	Excluded	22.52	.66
Attachment to parent	Included	22.38	.66
Parental monitoring	Excluded	14.00	.24
Parental monitoring	Included	13.68	.24
Abuse at home	Excluded	6.57	.06
Abuse at home	Included	6.21	.06
Attachment to teacher	Excluded	8.12	.56
Attachment to teacher	Included	8.23	.56
Collective efficacy	Excluded	14.18	.97
Collective efficacy	Included	14.19	.97
Low self-control	Excluded	13.65	.36
Low self-control	Included	13.29	.36
Deviant peer association	Excluded	2.30	.08
Deviant peer association	Included	2.22	.08
Total strain	Excluded	31.49	.13
Total strain	Included	30.19	.13
Strain from parent	Excluded	7.81	.39
Strain from parent	Included	7.59	.39
Strain from school	Excluded	6.98	.12
Strain from school	Included	6.63	.12
Strain from peer	Excluded	5.82	.02
Strain from peer	Included	5.32	.02
Strain from body	Excluded	5.97	.06
Strain from body	Included	5.60	.06
Strain from money	Excluded	5.17	.53
Strain from money	Included	5.06	.53
Total delinquency	Excluded	2.09	.01
Total delinquency	Included	1.75	.01
Violent delinquency	Excluded	0.47	.01
Violent delinquency	Included	0.33	.01
Nonviolent delinquency	Excluded	1.10	.21
Nonviolent delinquency	Included	1.02	.21
Substance-related delinquency	Excluded	0.09	.71
Substance-related delinquency	Included	0.08	.71
Internet-related delinquency	Excluded	0.43	.04
Internet-related delinquency	Included	0.31	.04

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.

Notes

Author Biographies

Bora Lee is an assistant professor in the Department of Criminal Justice at the College at Brockport, State University of New York. Her recent research focuses on adolescent victimization.

Youngoh Jo is a research fellow in Korean Institute of Criminology. His recent research focuses on correlates of crime and victimization in developmental perspective.

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Correlates of Repeat Victimization and Sex Differences in South Korean Youth

Abstract

Keywords

Introduction

Literature Review

Lifestyles/Routine Activities, Low Self-Control, and Victimization

Social Control, Collective Efficacy, Strain, and Victimization

Research on Victimization in Contemporary South Korean Context

Limitations of Previous Studies

Method

Data

Measures 2

Dependent variable

Independent variables

Analysis

Findings

Discussion

Footnotes

Appendix

Declaration of Conflicting Interests

Funding

Notes

Author Biographies

References

Measures²