Sexual Victimization and Psychological and Behavioral Outcomes Among Children and Adolescents in South Korea

Hyun Ji Lee; Jungtae Choi; Jae-Won Kim; Kihyun Kim

doi:10.30773/pi.2024.0289

Psychiatry Investig > Volume 22(5); 2025 > Article

Lee, Choi, Kim, and Kim: Sexual Victimization and Psychological and Behavioral Outcomes Among Children and Adolescents in South Korea

Original Article

Psychiatry Investigation 2025;22(5):564-573.

Published online: May 15, 2025

DOI: https://doi.org/10.30773/pi.2024.0289

Sexual Victimization and Psychological and Behavioral Outcomes Among Children and Adolescents in South Korea

Hyun Ji Lee^1,²

, Jungtae Choi¹

, Jae-Won Kim^3,⁴

, Kihyun Kim¹

¹Department of Social Welfare, Sungkyunkwan University, Seoul, Republic of Korea

²Eunpyeonggu Family Center, Seoul, Republic of Korea

³Department of Psychiatry, Seoul National University Hospital, Seoul, Republic of Korea

⁴Division of Child and Adolescent Psychiatry, Department of Psychiatry & Behavioral Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea

Correspondence: Kihyun Kim, PhD Department of Social Welfare, Sungkyunkwan University, 25-2 Sungkyunkwan-ro, Jongno-gu, Seoul 03063, Republic of Korea Tel: +82-2-760-0638, Fax: +82-2-760-0630, E-mail: kihyun.kim@skku.edu

Received September 12, 2024 Revised January 1, 2025 Accepted February 24, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective

By focusing on a person-centered approach using latent class analyses (LCA), this study examined the patterns of sexual victimization among children and adolescents in South Korea and compared the psycho-behavioral outcomes of these classes.

Methods

Participants were 546 females aged 6-17, including 117 sexual victimization survivors and 429 non-victims in South Korea. LCA, an analysis of covariance, and Bonferroni post-hoc tests were conducted. Psychological and behavioral outcomes were measured using the Korean version of the Child Behavior Checklist 6-18 and the Youth Self Report. Variables include internalizing (anxious/depressed, withdrawn/depressed, somatic complaints), externalizing (rule-breaking, aggressive behavior), social, thought, and attention problems.

Results

Based on the fit statistics, proportion of each class, and interpretability, a three-class solution was selected as the best fitting model. Profile 1 mainly involved survivors of rape, which first occurred in adolescence through social relations involving alcohol, drugs, or filming. Profile 2 mainly comprised survivors of both rape and physical sexual harassment by close relations, such as family members or relatives, more than once. Profile 3 mainly comprised survivors of sexual harassment by strangers or social relations. Statistically significant differences were suggested in the psych-behavioral outcomes of the profiles compared with the non-victim group.

Conclusion

These findings highlight the importance of examining experiences of sexual violence in a multifaceted manner. This approach may provide more effective interventions for survivors and allow clinicians to gain an in-depth understanding of sexual victimization in children and adolescents while also increasing the understanding of potential psycho-behavioral consequences.

Keywords: Child sexual abuse, Sexual violence, Child development, Child behavior, Latent class analysis

INTRODUCTION

In general, the worldwide prevalence rate of sexual victimization under 18 years of age ranges between 8%-31% for girls and 3%-17% for boys [1]. In South Korea, the number of sexual violence crimes reported in 2021 was 32,898, which is 63.7 per 100,000 people. Of all sexual violence crimes, survivors aged 16-20 years accounted for 17.1% and those under 16 years old for 10.1%. As sexual crime survivors under 19 years of age are defined as children and adolescents in South Korea, approximately 27% of these crimes represent sexual crimes against children and adolescents. Moreover, in South Korea, 88.7% of survivors under 13 years old are female, and among those aged 13-20 years, 91.1% are female survivors [2].

Studies suggest that childhood sexual victimization is associated with several negative consequences. These include posttraumatic stress disorder (PTSD) [3,4], depression [5,6], suicide risk [7], anxiety [8-10], risky sexual behavior, alcohol and/or substance use [7], academic performance [11], eating disorders [12], and sleep problems [13]. Much of what we know comes from studies focusing on the characteristics of victimization that best predict a child’s subsequent problems. For instance, the worst psychological sequelae are expected in those who experienced victimization involving forcible or incapacitated rape [14] or drug- or alcohol-facilitated rape [15]. Other findings indicate that sexual victimization severity (e.g., degree of perpetrator(s) violence, severity of sexual victimization, physical injury) is important for understanding survivors’ psychological sequelae [16,17].

According to numerous studies [18-23], however, sexual victimization differs in many dimensions because factors associated with the victimization may co-occur or relate to each other in complex ways. Consequently, research focusing on the impact of one or more victimization factors cannot provide a thorough understanding of how these different experiences relate to negative outcomes. A person-centered approach methodologically using latent class analyses (LCA) advances unidimensional dichotomous examinations of sexual victimization to multidimensional assessments based on various indicators; that is, it enables researchers to understand unique patterns of sexual victimization multidimensionally [24]. This approach identifies meaningful subgroups based on the interrelationships among multiple factors that contextualize one’s victimization experience.

As one, French et al. [19] used an LCA to explore the sexual victimization patterns of 657 participants (285 male and 373 female) aged 14-26 years in the United States. Including the coercive tactics used (i.e., verbal coercion, substance facilitated, and physical force) and the range of sexual behavior (i.e., completed vaginal, oral, or anal intercourse; attempted vaginal, oral, or anal intercourse; kissing or fondling) for the LCA, French et al. [19] determined four distinct classes that describe sexual victimization patterns. Additionally, exploring the psychological and behavioral outcomes related to these classes, results revealed that the poly-victimization class, with a high probability of having experienced all kinds of sexual coercion tactics, showed the most serious psycho-behavioral consequences.

Using the National Survey of Child and Adolescent Well-Being data from the United States, McCrae et al. [21] conducted factor mixture modeling (i.e., a form of latent class analysis) on 597 children and adolescents aged 3-14 years who had been investigated for sexual abuse. To examine the complexity in children’s lives regarding sexual abuse and compare the psychopathology symptoms of each class, McCrae et al. [21] included abuse characteristics (i.e., abuse severity, duration, relationship with the perpetrator, and maltreatment co-occurrence) and additional family problems (i.e., family’s prior maltreatment report and low social support) in the factor mixture modeling. Accordingly, the results revealed that sexual abuse severity was an important distinguishing factor and that such severity of sexual abuse was associated with depressive symptoms among 8-11-year-olds.

Similar to McCrae et al. [21], who included additional variables such as family problems to understand sexual victimization, Masters et al. [20] included sexual victimization outcomes (i.e., contact, attempted rape, and rape), assault tactics (i.e., verbal coercion, physical force, and incapacitation such as drugs or alcohol), repeated victimization, injury beyond the assault itself, level of upset at the time, and history of childhood sexual abuse for the LCA. Using the data of 667 women aged 21-30 years in the United States, the results revealed that those in the forceful severe assault class had significantly higher levels of depression and anxiety.

To date, however, although many studies have examined patterns of sexual victimization using LCA (e.g., 16-18), few have focused on children and adolescents in South Korea. For instance, Kim et al. [22] used a two-step cluster analysis to understand the pattern of sexual victimization among 1,077 survivors in South Korea and examined the association of the classes with the victim support services utilized. Sexual victimization outcomes (i.e., rape, sexual harassment, and others), duration, repeated victimization, and age at the time of victimization were included. Kim et al. [22] conducted a separate cluster analysis of children and adolescents, excluding adult survivors, to examine the patterns of victimization in these age groups. The results revealed three classes: sexual victimization (both rape and sexual harassment) by family and relatives, rape victimization by those besides family or relatives, and sexual harassment victimization by those besides family or relatives. However, Kim et al. [22] did not examine the psycho-behavioral sequelae in these classes.

Choi et al. [18] and Kim et al. [23] analyzed female adults in South Korea and compared their mental health outcomes for each class. Choi et al. [18] included sexual victimization outcomes (i.e., rape, attempted rape, severe sexual harassment, mild sexual harassment, and verbal sexual harassment), age at the time of victimization, repeated victimization, and relationship with the perpetrator for the LCA. The results revealed that Profile 1 (i.e., severe sexual victimization by close person) and Profile 2 (i.e., sexual victimization by business relation) showed significantly higher levels of mental health problems than Profile 4 (i.e., mild sexual victimization by a stranger). Kim et al. [23] included sexual victimization outcomes (i.e., rape and sexual touching), primary perpetrator (intimate partner and college, friend, or peer), frequency, age at the time of victimization, any physical violence, and alcohol and/or drugs for profile analysis. The results revealed four classes: Profile 1 (i.e., sexual touching by social relations), Profile 2 (i.e., rape by social relations, with a high frequency of one-time occurrence), Profile 3 (i.e., rape in the context of an intimate relationship), and Profile 4 (i.e., rape by strangers). Accordingly, all four profiles showed significantly higher mean scores for PTSD, depression, anxiety, and dissociation than non-victims, with Profiles 2 and 3 exhibiting higher mean scores than Profiles 1 and 4.

These studies contribute to a multidimensional understanding of sexual victimization. However, the existing literature lacks a person-centered analysis that characterizes 1) the victimization experiences of children and adolescent girls in South Korea using 2) a comprehensive set of sexual victimization characteristics, and 3) predicts the psycho-behavioral outcomes associated with these victimization experiences. For instance, McCrae et al.’s [21] and Masters et al.’s [20] study included additional variables such as low social support and levels of upset at the time that do not represent the characteristics of the sexual victimization experience itself. Furthermore, French et al. [19] examined both male and female survivors together. However, Choi et al. [18] and Kim et al. [23] included or excluded certain age groups and thus did not provide information exclusively for children and adolescents. Kim et al. [22] did not relate these classes with their psycho-behavioral trajectories.

In addition, studies have shown somewhat inconsistent findings regarding gender differences in psycho-behavioral problems among children and adolescents with a history of child victimization. While much of the existing literature reports greater internalizing problems among girls and greater externalizing problems among boys [25,26], other studies suggest no gender differences in these issues [27] or even indicate greater internalizing problems among boys [28,29]. Given this scenario, specifying gender in relation to the psychopathology of sexual victimization may give more accurate information.

Therefore, this study aimed to examine the following two questions: First, what are the patterns of sexual victimization among female children and adolescents in South Korea? Using an LCA, we hypothesized that the best fitting model would consist of multiple latent classes. Second, how do classes predict psycho-behavioral outcomes? Here, we focused on psychological and behavioral problems, including internalizing and externalizing, social, thought, and attention problems.

METHODS

Participants

In total, 546 female child and adolescent participants from South Korea were included: 117 sexual victimization survivors and 429 non-victims. Participants’ ages ranged from 6-17 years. The inclusion criteria for both sexual victimization survivors and non-victims included no history of 1) intellectual disability, 2) congenital genetic disorder or congenital brain injury, 3) acquired brain damage such as cerebral palsy, 4) spastic disorders, other neurological diseases, or uncorrected sensory disorders, 5) developmental disorders such as autism, 6) schizophrenia, bipolar disorder, major depressive disorder, or other childhood psychosis, 7) dependence on alcohol or drugs, 8) language impairment or severe learning disability, and 9) risk of pregnancy.

Participant recruitment procedures were as follows. First, female sexual victimization survivors (n=117) were recruited through a national crisis center for survivors of sexual violence in South Korea. Survivors under 19 years of age who visited eight different centers nationwide were asked to participate in the study. We limited the participants to those who had experienced sexual victimization within three months. The survey was provided in a paper-and-pencil format in a private setting, and parental consent was obtained prior to participation. Second, a non-victim female comparison group (n=429) was recruited. One method to do so included advertising through institutions, such as schools and community centers, in areas where study participants who survived sexual victimization reside (n=110). The other group participated via an online survey platform at their own convenience (n=319) using their electronic devices. Participants were informed that they could discontinue at any time during the survey if they did not wish to respond. The Institutional Review Board (IRB) for Human Subjects of Seoul National University Hospital (IRB No. 1506-073-680) was obtained prior to data collection.

Measures

Sexual victimization

Sexual victimization case records from eight rape crisis centers were evaluated and coded for research use. To reduce researcher bias during inspection, all evaluation procedures, contents, and instructions were structured and produced as a manual, and the evaluation was conducted according to the manual. Table 1 summarizes the six variables used in this study. First, the action type was recoded as rape, physical sexual harassment, or non-physical sexual harassment. Second, the age of onset (i.e., age at the time of first victimization) was recoded as child if the first victimization occurred before 13 years of age and adolescent for 13 years or above [22]. Third, the frequency of the sexual victimization was recoded as once or twice or more. Fourth, the involvement of alcohol, drugs, or sleep (i.e., drug-facilitated sexual abuse), was recoded as involved or not involved. Fifth, the number of perpetrators was recoded as one or two or more. Finaly, the relationship with the perpetrator(s) was recoded as family or relative, social relation, or stranger.

Psychological and behavioral outcomes

Psychological and behavioral outcomes were measured using the Korean version (K-CBCL) [30] of the Child Behavior Checklist for ages 6-18 (CBCL 6-18) [31] and the Korean version (K-YSR) [32] of the Youth Self Report (YSR) [31]. Specifically, participants under 13 years of age were assessed using the parent report of the K-CBCL, and participants aged 13-17 years were assessed using the self-report of the K-YSR. These measures are widely used in national research as indicators of mental health in children and adolescents. The scales included internalizing (i.e., anxious or depressed, withdrawn or depressed, and somatic complaints), externalizing (i.e., rule-breaking behavior and aggressive behavior), social, thought, and attention problems. The reliability coefficients of the K-CBCL and K-YSR have been reported as 0.62-0.95 and 0.59-0.93 [33], respectively. The items were standardized using t-scores, with higher scores representing more problems.

The CBCL and YSR have nearly identical content and structure, but discrepancies between different informants’ reports of child and adolescent outcomes pose major challenges. However, participants aged six years were too young to use self-report measures, such as the YSR. In addition, Rescorla et al. [34] examined the CBCL 6-18 and YSR with the same participants across 25 societies and found that South Korea’s parent-adolescent agreement was high compared with that of Japan. Thus, we combined both measures to assess the psychological and behavioral outcomes of children and adolescents.

Data analysis

The present study aimed to classify participants into optimal grouping categories based on their sexual victimization experiences [35] and compare the related psychological and behavioral correlates of these classes.

To achieve this, an LCA was conducted using MPlus (version 8.0) [36]. LCA is a multivariate person-centered analysis that utilizes observed latent variables to model the heterogeneity inherent in patterns of abuse experiences. Predictors of class membership (i.e., latent variables) included the outcome of sexual victimization, age at the time of first victimization, frequency, involvement of alcohol, drugs, or sleep, number of perpetrators, and relationship with the perpetrator(s). Statistical criteria were used in conjunction with model interpretability to determine the optimal number of classes, including the Akaike information criterion (AIC), Bayesian information criteria (BIC), adjusted Bayesian information criteria (aBIC), bootstrap likelihood ratio test (BLRT), and entropy. The p-value can be used to indicate the model fit of LCA using Pearson and log-likelihood chi-square tests. Mplus provides a chi-square test of model fit. After the best fitting model was selected using these criteria, an additional descriptive analysis was conducted to summarize the victimization characteristics of each class.

Furthermore, to compare the psychological and behavioral correlates between the classes derived by the LCA, an analysis of covariance (ANCOVA), followed by a Bonferroni post hoc test, was conducted. To focus specifically on the sexual victimization experience, we included a comparative group (i.e., the non-victim comparison group) along with the classes during the analysis. Current age and perceived economic status were included as covariates, and SPSS version 28.0 (IBM Corp.) was used.

RESULTS

Characteristics of the study participants

The characteristics of participants are described in Table 2. Total of 546 female child and adolescent participants, 117 sexual victimization survivors and 429 non-victims, from South Korea were included. The mean age of sexual victimization survivors was 12.89 years (standard deviation [SD]=3.09) and the non-victim comparison group was 11.90 years (SD=3.37). In terms of perceived economic status, 46.4% reported their economic status as middle class, followed by 28.9% as lower-middle class, 13.9% as upper-middle class, 9.5% as lower class, and 1.3% as upper class.

Patterns of sexual victimization

Latent class analysis

An LCA was conducted for 117 sexual victimization survivors to determine the optimal number of classes based on the six characteristics of sexual victimization. Table 3 presents the fit statistics for the two-, three-, and four-class solutions. Accordingly, the three-class solution had the lowest AIC and relatively low aBIC of the eligible classes, and the BLRT indicated the three-class solution provided a better fit than the fourclass solution. All entropy ratings were greater than 0.7, indicating an acceptable fit. Thus, based on the fit statistics, the proportion of each class, and interpretability, we determined a three-class solution as the best fitting model.

To further assess the adequacy of the three-class solution, we examined the p-values from various statistical tests. The Pearson chi-square test produced a p-value of 0.898, while the likelihood ratio chi-square test generated a p-value of >0.999. Both p-values exceed the conventional significance level of 0.05, allowing us to conclude that the model is well-suited to the observed data.

Class characteristics

Table 4 summarizes the characteristics and prevalence of the three latent classes. Profile 1 which was named as rape by social relation was characterized by a high probability of rape (94.9%), which first occurred in adolescence (94.7%), followed by a high probability of involvement in alcohol, drugs, or sleep (69.2%). This class had sexual victimization that mostly occurred once (94.9%) by one perpetrator (76.9%), with whom they had a social relationship (73.7%). Specifically, the most common classification in social relations was a date or friend, accounting for 50.0% of the 73.7%. Profile 2, named as rape or physical sexual harassment by family or social relation, experienced both rape (41.9%) and physical sexual harassment (58.1%) mostly two or more times (89.7%) without alcohol, drugs, or sleep (96.8%). The victimization occurred by only one perpetrator (58.0%), who was a family member or relative. Finally, Profile 3, named as sexual harassment by social relation or the stranger, consisted of 59.6% physical sexual harassment, followed by 23.4% categorized as non-physical sexual harassment. A high proportion of this class experienced their first victimization in childhood (74.4%), mostly by one perpetrator (83.0%) who was not a family member or relative (0.0%). Specifically, 53.2% of the perpetrators were strangers, followed by those with social relations (46.8%).

Psychological and behavioral outcomes of each class

One-way ANCOVAs were conducted to examine the statistically significant differences among the classes and the non-victim comparison group in terms of psychological and behavioral outcomes (Table 5). All subscales of the psychological and behavioral outcomes differed significantly. Specifically, the Bonferroni post hoc test revealed that all three profiles had negative psychological and behavioral outcomes compared to the non-victim group. As presented in Table 5, Profile 1 showed the most problematic scores compared with the scores of the other three groups. Overall, Profiles 2 and 3 did not differ in terms of psychological and behavioral outcomes.

DISCUSSION

The present study aimed to fill a gap in the literature by 1) identifying patterns of sexual victimization experiences among female child and adolescent survivors in South Korea and 2) exploring the psychological and behavioral correlates of these classes. Among 117 sexual victimization survivors aged 6-17 years in South Korea, three distinct patterns of sexual victimization experience were identified, and among 546 participants (i.e., 117 sexual victimization survivors and 429 nonvictims), the psychological and behavioral problems of these classes differed significantly from those of the non-victim comparison group.

Latent class analysis of 117 sexual victimization survivors revealed three distinct patterns. First, Profile 1 was characterized as rape by a social relation, involving alcohol, drugs, or sleep. Participants in Profile 2 were mainly survivors of both rape and physical sexual harassment by a close relation, such as a family member or relative, more than once. Profile 3 mainly involved survivors of sexual harassment by a stranger or social relation. This supports numerous studies suggesting that, under what we categorize as sexual violence, survivors have a wide range of experiences [18-23].

Specifically, Profile 1 were survivors of rape that first occurred in adolescence and involved alcohol, drugs, or filming. The relationship with the perpetrator in Profile 1 was mainly social, such as a date partner or friend. Specifically, approximately 95% of Profile 1 experienced their first onset of victimization during adolescence, defined as age 13 and above. In South Korea, unlike child survivors who are victimized more by adult perpetrators [37], adolescents stand out as being victimized by their peers [38]. Adolescents’ victimization by peer perpetrators often involves complexities such as the victim’s use of alcohol, drugs, or filming [38]. Similar to the case in South Korea, in McCrae et al.’s [21] study, the factor mixture modeling of participants aged 12-14 years suggested a “severe type of sexual abuse by non-family perpetrators involving the presence of substance use” as one profile. Interestingly, the present study is consistent with Kim et al.’s22 in that we identified “sexual victimization by a family member or relative” as a characteristic.

Consistent with extant studies, participants in Profile 1 (i.e., rape by social relation) demonstrated the most problematic psychological and behavioral outcomes compared with all the other classes, with the non-victim comparison group demonstrating the least distress. This suggests that survivors of “severe violence, such as rape involving alcohol, drugs, or sleep” are considered a high-risk group in terms of their psychological and behavioral trajectories. For example, according to McCrae et al. [21], participants who experienced “severe sexual abuse by a non-family perpetrator involving the presence of substance use” demonstrated significantly higher internalizing problems than those with “less severe sexual abuse by a family member or relative, over a shorter duration.”

Profiles 2 (i.e., rape or physical sexual harassment by family or social relation) and Profile 3 (i.e., sexual harassment by social relation or the stranger) were similar in that the age at first onset predominantly fell within childhood (under 13 years), and both groups had experienced sexual harassment. However, they differed significantly in that Profile 2 reported experiencing two or more incidents of victimization by relatives or acquaintances, whereas Profile 3 experienced a single incident of victimization by a stranger. Nevertheless, despite the differences in victimization characteristics between the two groups, the analysis indicated that both profiles generally exhibited similar levels of psychological and behavioral trajectories across all domains. This finding contradicts the numerous literatures suggesting that those abused by close relations, such as family or relatives, exhibit the greatest negative symptoms compared to those abused by strangers [39]. Therefore, replication of this finding is needed, emphasizing the importance of understanding sexual victimization experiences as complex events shaped by multiple intersecting characteristics [19].

Similarly, although Profile 1(i.e., rape by social relation) had the highest scores for each problem, no significant differences showed among the three classes (i.e., Profiles 1, 2, and 3) in terms of withdrawal or depression, aggressive behavior, and social, thought, and attention problems. Results suggest that psychological and behavioral sequelae may differ depending on the characteristics of sexual victimization, which simply cannot be reduced to the severity of the victimization. There may be more serious or severe types of sexual violence, but no act is trivial for the survivors [19]. Long-term follow-up studies suggest that we cannot conclude that the symptoms are less serious in some incidents, as these individuals demonstrate different adjustment or developmental trajectories than do survivors of more severe sexual violence [40].

Implications

Participants in this study comprised those who visited crisis support centers in South Korea. We used the centers’ case records to define the sexual victimization experiences of the participants. This approach helps researchers avoid incredibility and inaccuracy during the retrospective self-reporting of sexual victimization. Moreover, because the participants in this study included those who visited crisis support centers, the characteristics of victimization tended to be relatively severe. In terms of the victimization outcome, there was a higher proportion of rape cases. In terms of age at the time of first victimization, a higher proportion involved victimization that first occurred in adolescence. In terms of the relationship with the perpetrator(s), a higher proportion involved close relations such as a family member, relative, date, or friend. Although sexual violence or rape by a family member or relative tends to be classified as a severe victimization experience, a pressing need exists for more research because of the difficulty in securing a sufficient number of such cases. The results of the LCA in our study offer important contributions in this context, as we included a sufficient number of relatively severe cases.

These results demonstrate that we cannot specify a victim’s experience of sexual violence based solely on one aspect. The experience of sexual violence is complex; hence, it is necessary to understand and provide tailored interventions for each subgroup. By understanding the needs and difficulties of various subgroups of sexual victimization and providing differentiated counseling, education, and treatment based on these types, a more efficient and effective support system may be established. Additionally, different types of sexual victimization experiences appear to be differentially associated with negative outcomes. It remains socially important to emphasize that all sexual violence is illegal and detrimental to survivors; however, clinically, recognizing the heterogeneity in children’s and adolescents’ experiences of sexual violence may affect the work toward survivors’ recovery. The focus should not be on which factor is more severe or important but on recognizing that each individual presents differently.

In South Korea, the Ministry of Gender Equality and Family operates the Sunflower Center, an integrated support center for survivors of sexual violence, and provides support to private counseling centers to deliver specialized counseling and psychological treatment services. Despite these extensive efforts, support organizations for sexual violence survivors face challenges such as overall budget constraints, poor working conditions, high turnover rates among counselors, and a decline in professional expertise [41,42]. Therefore, considering the individual challenges faced by survivors and the substantial social costs that may arise, there is a pressing need for national efforts, including the allocation of additional budgetary resources, to ensure the provision of specialized services for the treatment and recovery of child and adolescent survivors of sexual violence.

Limitations

Because of the cross-sectional design of our study, we were unable to investigate causality and could only establish a correlation between class membership and levels of distress. In addition, the decision to choose a three-class model based on LCA presented statistical limitation. Statistically, BIC values continued to increase from the two- to four-class models and entropy was 0.01 lower than the other classes. Also, BLRT pvalue of three-class had no significant difference from the twoclass model. Nevertheless, the present study considered not only the statistical fit but also the interpretability of each class and proportion.

Meanwhile, to obtain more accurate information regarding the psychopathology of sexual victimization, the present study specified the sex of participants as female children and adolescents. However, there is a need for further studies on male survivors. Also, as our primary focus was on the patterns of sexual victimization experiences and their psychological and behavioral outcomes, we did not investigate other risk factors (i.e., social support and childhood abuse history) associated with psycho-behavioral problems. For example, Lee et al. [43] examined adolescent girls in South Korea and suggested a significant moderating effect of co-occurring child abuse on the relationship between sexual victimization and mental health, including PTSD, depression, dissociation, and suicidal thoughts. These findings suggest that further research should consider the co-occurrence of other abuse experiences as a multifaceted factor predicting psycho-behavioral outcomes.

In many cases, counselors fill in information about victimization experiences in the case-management system during the initial consultation. However, this approach inevitably generates missing data and dichotomous responses [22]. In addition, as the information is centered around the victimization experience that directly led to the support center visit, there is a clear limitation in comprehensively understanding victims’ lifetime experiences of sexual violence up until this reported victimization. We expect that future research will address these limitations.

Conclusion

The present study examined two objectives: 1) identifying patterns of sexual victimization experiences among 117 female child and adolescent survivors in South Korea and 2) exploring the psycho-behavioral correlates of these classes with 429 non-victim counterparts. The results highlight the importance of examining the experiences of sexual violence in a multifaceted manner. This approach may provide more effective interventions for survivors and allow clinicians to gain an in-depth understanding of sexual victimization in children and adolescents while also increasing the understanding of potential psycho-behavioral consequences. Further research for survivors in South Korea is suggested.

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Kihyun Kim, Hyun Ji Lee. Data curation: Kihyun Kim, Hyun Ji Lee. Funding acquisition: Kihyun Kim, Jae-Won Kim. Project administration: Kihyun Kim, Jae-Won Kim. Writing—original draft: Hyun Ji Lee. Writing—review & editing: Kihyun Kim, Jungtae Choi.

Funding Statement

This work was funded by the National Research Foundation of Korea (2019-S1A5A2A03 2019S1A4A2A03045289) and partly the Korea Mental Health Technology R&D (HM15C1107).

Acknowledgments

None

Table 1.

Sexual victimization variables

Variables	Items
Action type
Rape	Rape involving physical force or explicit threat of force/ alcohol-related incapacitated rape/attempted rape
Physical sexual harassment	Oral copulation (mouth to genital contact or genital to mouth contact)/sexual touching
Non-physical sexual harassment	Filming with camera/lewd act using devices such as phone, computer, mail/sexual trespassing in public places/indecent act in crowded public places
Age at first onset
Child	Under 13 years
Adolescent	13 years and above
Frequency
Once	One time
More than one/once	Twice or more (irregularly)/once a month/several times a month/once a week/several times a week/every day
Alcohol, drugs, or sleep
Involved	Alcohol/drugs/sleep/alcohol and drugs/alcohol and sleep/drugs and sleep/alcohol, drugs, and sleep
Not involved	Not involved
Number of perpetrators
One	One perpetrator
Two or more	Two or more perpetrators
Relationship with the perpetrator(s)
Family or relative	Family/relative
Social relation	Current date/past date/blind date/chatting partner/work relation (supervisor, senior or junior, co-worker)/teacher/religion-related person/neighbor/friends (senior or junior, peers)/friend’s acquaintance/institution workers
Stranger	Stranger (person who you met for the first time)

Table 2.

Demographic characteristics of the participants (N=546)

Characteristics	Total (N=546)	Sexual victimization survivors (N=117)	Non-victim (N=429)
Female sex	546 (100)	117 (100)	429 (100)
Age (yr)	12.11±3.33	12.89±3.09	11.90±3.37
Perceived economic status
Upper class	7 (1.3)	0 (0)	7 (1.6)
Upper-middle class	75 (13.9)	7 (6.2)	68 (16.0)
Middle class	250 (46.4)	41 (36.3)	209 (49.1)
Lower-middle class	156 (28.9)	39 (34.5)	117 (27.5)
Lower class	51 (9.5)	26 (23.0)	25 (5.9)

Mean±standard deviaion for age and frequency (%) for perceived economic status

Table 3.

Model fit indices for latent class models (N=117)

Model	AIC	BIC	aBIC	BLRT	Entropy	Classes: N (%)
2-Class	926.95	973.91	920.17	<0.001	0.77	41 (35.0)	76 (65.0)
3-Class^*	915.12^*	986.93^*	904.74^*	0.01^*	0.76^*	39 (33.3)^*	31 (26.5)^*	47 (40.2)^*
4-Class	918.46	1,015.13	904.50	0.22	0.77	10 (8.5)	38 (32.5)	40 (34.2)	29 (24.8)

^* indicates the best fit.

AIC, Akaike information criterion; BIC, Bayesian information criteria; aBIC, adjusted Bayesian information criteria; BLRT, bootstrap likelihood ratio test

Table 4.

Variables distinguishing the classes (N=117)

Child and adolescent Sexual victimization characteristics	Latent class groups
	Profile 1 (N=39)	Profile 2 (N=31)	Profile 3 (N=47)
	Rape by social relation	Rape or physical sexual harassment by family or social relation	Sexual harassment by social relation or the stranger
Action type
Rape	37 (0.95)	13 (0.42)	8 (0.17)
Physical sexual harassment	2 (0.05)	18 (0.58)	28 (0.60)
Non-physical sexual harassment	0	0	11 (0.23)
Age at first onset
Child	2 (0.05)	18 (0.58)	35 (0.74)
Adolescent	36 (0.95)	13 (0.42)	12 (0.26)
Frequency
Once	37 (0.95)	3 (0.10)	39 (0.83)
Twice or more	2 (0.05)	26 (0.90)	8 (0.17)
Alcohol, drugs, or sleep
Involved	27 (0.69)	1 (0.03)	0
Not involved	12 (0.31)	30 (0.97)	47 (1.00)
Number of perpetrators
One	30 (0.77)	31 (1.00)	39 (0.83)
Two or more	9 (0.23)	0	8 (0.17)
Relationship with the perpetrator(s)
Family or relative	0	18 (0.58)	0
Social relation	28 (0.74)	13 (0.42)	22 (0.47)
Stranger	10 (0.26)	0	25 (0.53)

Age at first onset and the relationship with the perpetrator(s) has one missing value. Frequency has two missing values. Values are presented as number (proportion)

Table 5.

Estimated mean and standard error of psychological and behavioral outcomes (N=546)

	Profile 1 (N=39)	Profile 2 (N=31)	Profile 3 (N=47)	Non-victims (N=429)	F
Total problems	67.62 (2.36)^‡§ǁ	57.21 (2.63)^†ǁ	57.16 (2.14)^†ǁ	43.11 (0.69)^†‡§	46.83^*
Internalizing	67.14 (2.10)^§ǁ	60.16 (2.34)^ǁ	57.96 (1.91)^†ǁ	46.10 (0.61)^†‡§	45.43^*
Anxious/depressed	65.43 (1.27)^§ǁ	60.97 (1.42)^ǁ	60.09 (1.15)^†ǁ	52.79 (0.37)^†‡§	44.73^*
Withdrawn/depressed	63.48 (1.31)^ǁ	59.32 (1.46)^ǁ	59.51 (1.19)^ǁ	53.32 (0.38)^†‡§	27.18^*
Somatic complaints	63.28 (1.19)^§ǁ	60.30 (1.33)^ǁ	57.51 (1.08)^†ǁ	53.52 (0.35)^†‡§	28.09^*
Externalizing	62.96 (2.10)^‡§ǁ	52.18 (2.34)^†ǁ	55.33 (1.91)^†ǁ	43.18 (0.61)^†‡§	37.77^*
Rule-breaking behavior	63.54 (1.11)^‡§ǁ	57.65 (1.23)^†ǁ	59.26 (1.01)^†ǁ	52.59 (0.32)^†‡§	41.55^*
Aggressive behavior	57.87 (1.00)^ǁ	55.15 (1.12)	56.82 (0.91)^ǁ	52.16 (0.29)^†§	17.11^*
Social problems	60.15 (1.08)^ǁ	56.62 (1.20)^ǁ	57.75 (0.98)^ǁ	52.56 (0.31)^†‡§	23.26^*
Thought problems	62.91 (1.19)^ǁ	60.47 (1.32)^ǁ	58.96 (1.08)^ǁ	53.31 (0.35)^†‡§	31.59^*
Attention problems	59.36 (1.18)^ǁ	56.76 (1.31)^ǁ	58.39 (1.07)^ǁ	52.57 (0.34)^†‡§	18.85^*

Age and perceived economic status were included as covariates.

^* p<0.001;

^† differs significantly from Profile 1;

^‡ differs significantly from Profile 2;

^§ differs significantly from Profile 3;

^ǁ differs significantly from non-victims

REFERENCES

1. Barth J, Bermetz L, Heim E, Trelle S, Tonia T. The current prevalence of child sexual abuse worldwide: a systematic review and meta-analysis. Int J Public Health 2013;58:469-483.

2. Supreme Prosecutors’ Office. 2022 Crime Analysis. Available at: https://www.spo.go.kr/site/spo/crimeAnalysis.do. Accessed June 14, 2023.

3. Kingston S, Raghavan C. The relationship of sexual abuse, early initiation of substance use, and adolescent trauma to PTSD. J Trauma Stress 2009;22:65-68.

4. Noll JG. Child sexual abuse as a unique risk factor for the development of psychopathology: the compounded convergence of mechanisms. Annu Rev Clin Psychol 2021;17:439-464.

5. Boney-McCoy S, Finkelhor D. Is youth victimization related to trauma symptoms and depression after controlling for prior symptoms and family relationships? A longitudinal, prospective study. J Consult Clin Psychol 1996;64:1406-1416.

6. Kilpatrick DG, Ruggiero KJ, Acierno R, Saunders BE, Resnick HS, Best CL. Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: results from the National Survey of Adolescents. J Consult Clin Psychol 2003;71:692-700.

7. Silverman JG, Raj A, Mucci LA, Hathaway JE. Dating violence against adolescent girls and associated substance use, unhealthy weight control, sexual risk behavior, pregnancy, and suicidality. JAMA 2001;286:572-579.

8. Choi JY, Oh KJ. The effects of multiple interpersonal traumas on psychological maladjustment of sexually abused children in Korea. J Trauma Stress 2013;26:149-157.

9. Kendall-Tackett KA, Williams LM, Finkelhor D. Impact of sexual abuse on children: a review of synthesis of recent empirical studies. Psychology Bulletin 1993;110:164-180.

10. Maniglio R. Child sexual abuse in the etiology of anxiety disorders: a systematic review of reviews. Trauma Violence Abuse 2012;13:96-112.

11. Trickett PK, McBride-Chang C, Putnam FW. The classroom performance and behavior of sexually abused females. Development and Psychopathology 1994;6:183-194.

12. Caslini M, Bartoli F, Crocamo C, Dakanalis A, Clerici M, Carrà G. Disentangling the association between child abuse and eating disorders: a systematic review and meta-analysis. Psychosom Med 2016;78:79-90.

13. Noll JG, Trickett PK, Susman EJ, Putnam FW. Sleep disturbances and childhood sexual abuse. J Pediatr Psychol 2006;31:469-480.

14. Brown AL, Testa M, Messman-Moore TL. Psychological consequences of sexual victimization resulting from force, incapacitation, or verbal coercion. Violence Against Women 2009;15:898-919.

15. Zinzow HM, Resnick HS, McCauley JL, Amstadter AB, Ruggiero KJ, Kilpatrick DG. The role of rape tactics in risk for posttraumatic stress disorder and major depression: results from a national sample of college women. Depress Anxiety 2010;27:708-715.

16. Pegram SE, Abbey A. Associations between sexual assault severity and psychological and physical health outcomes: similarities and differences among African American and Caucasian survivors. J Interpers Violence 2019;34:4020-4040.

17. Ullman SE, Townsend SM, Filipas HH, Starzynski LL. Structural models of the relations of assault severity, social support, avoidance coping, self-blame, and PTSD among sexual assault survivors. Psychology of Women Quarterly 2007;31:23-37.

18. Choi J, Kim K, Kim JY. [Profile of sexual assault experiences among the adult female: analysis of the nationwide survey of sexual assault in Korea]. Korean Journal of Social Welfare Studies 2019;50:271-296. Korean.

19. French BH, Bi Y, Latimore TG, Klemp HR, Butler EE. Sexual victimization using latent class analysis: exploring patterns and psycho-behavioral correlates. J Interpers Violence 2014;29:1111-1131.

20. Stappenbeck CA, Kaysen D, Kajumulo KF, Davis KC, George WH, et al. A person-centered approach to examining heterogeneity and subgroups among survivors of sexual assault. J Abnorm Psychol 2015;124:685-696.

21. Chapman MV, Christ SL. Profile of children investigated for sexual abuse: association with psychopathology symptoms and services. Am J Orthopsychiatry 2006;76:468-481.

22. Kim K, Kim JW, Park H, Ryou B. [Profile of sexual violence experiences among the survivors using victim support services in Korea]. Korean Journal of Social Welfare Studies 2016;47:255-280. Korean.

23. Kim K, Ryou B, Choi J, Kim JW. Profile analysis of sexual assault experiences among adult women and their implications for mental health. Psychiatry Investig 2021;18:312-323.

24. Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. Hoboken: Wiley; 2010.

25. Darves-Bornoz JM, Choquet M, Ledoux S, Gasquet I, Manfredi R. Gender differences in symptoms of adolescents reporting sexual assault. Soc Psychiatry Psychiatr Epidemiol 1998;33:111-117.

26. Feiring C, Taska L, Lewis M. Age and gender differences in children’s and adolescents’ adaptation to sexual abuse. Child Abuse Negl 1998;23:115-128.

27. Maikovich-Fong AK, Jaffee SR. Sex differences in childhood sexual abuse characteristics and victims’ emotional and behavioral problems: findings from a national sample of youth. Child Abuse Negl 2010;34:429-437.

28. Coohey C. Gender differences in internalizing problems among sexually abused early adolescents. Child Abuse Negl 2010;34:856-862.

29. Lewis T, McElroy E, Harlaar N, Runyan D. Does the impact of child sexual abuse differ from maltreated but non-sexually abused children? A prospective examination of the impact of child sexual abuse on internalizing and externalizing behavior problems. Child Abuse Negl 2016;51:31-40.

30. Oh KJ, Kim YA, Ha EH, Lee HR, Hong KE. Child behavior checklist 6-18: CBCL 6-18. Seoul: Huno; 2010.

31. Achenbach TM, Rescorla LA. Manual for the ASEBA School-Age Forms & Profiles. Burlington: University of Vermont, Research Center for Children, Youth, & Families; 2001.

32. Oh KJ, Ha EH, Lee HR, Hong KE. K-YSR Youth Self Report. Seoul: Huno; 2001.

33. Kim MY, Lee J, Kim YA, Ha EH, Oh KJ. Secular changes in behavior problems of Korean youths based on the Korean-CBCL and-YSR. Kor J Psychol 2015;34:769-793.

34. Rescorla LA, Ginzburg S, Achenbach TM, Ivanova MY, Almqvist F, Begovac I, et al. Cross-informant agreement between parent-reported and adolescent self-reported problems in 25 societies. J Clin Child Adolesc Psychol 2013;42:262-273.

35. Nylund K, Asparouhov T, Muthen B. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural Equation Modeling 2007;14:535-569.

36. Muthén LK, Muthén BO. Mplus User’s Guide. Eighth Edition. Los Angeles: Muthén & Muthén; 1998.

37. Kang EY, Kim HG, Lee HS. Analysis of the characteristics of domestic and foreign child sexual abuse crimes and study on the child victim protection system. Seoul: Ministry of Gender Equality and Family; 2010 Jul. 221 p. Report No.: TRKO201600013202.

38. Kim K, Lee M, Lee I, Ryou B. [Study on the experiences of using victim support program in Korea: cases of female adolescent survivors of peer sexual violence]. Korean Association of Victimology 2014;22:5-35. Korean.

39. Ullman SE. Relationship to perpetrator, disclosure, social reactions, and PTSD symptoms in child sexual abuse survivors. J Child Sex Abus 2007;16:19-36.

40. Trickett PK, Noll JG, Putnam FW. The impact of sexual abuse on female development: lessons from a multigenerational, longitudinal research study. Dev Psychopathol 2011;23:453-476.

41. Yoon SM. [The problems and improving plans of the sexual violence victims support system - centering around The Sexual Violence Consultation Office]. Korean Journal of Victimology 2006;14:381-405. Korean.

42. Ryu HJ, Kim KH, Kim JW. [Sexual victimization and depression in children: the impact of sleep disorders and perception of neighborhood safety]. Korean Journal of Social Welfare Studies 2020;51:133-172. Korean.

43. Lee HJ, Kim K, Kim JW. [Impact of the co-occurrence of child abuse on mental health: a test of the stress sensitization model among adolescent victims of sexual violence]. Journal of the Korean Society of Child Welfare 2023;72:39-73. Korean.