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. Author manuscript; available in PMC: 2024 Jan 12.
Published in final edited form as: Child Youth Serv Rev. 2022 Apr 29;138:106520. doi: 10.1016/j.childyouth.2022.106520

The Effect of Sexual Concerns on Placement Changes and School Transfers for Youth in the Child Welfare System

Kaitlin M Sheerin 1, Crosby A Modrowski 1,2, Shannon Williamson 2, Kathleen A Kemp 1,2
PMCID: PMC10785607  NIHMSID: NIHMS1896063  PMID: 38223234

Abstract

Youths in the child welfare system experience high rates of placement changes and school transfers; therefore, prior research focused on variables that may be linked with such disruptions. Indeed, researchers have established that mental health symptoms (e.g., PTSD symptoms) are linked with placement disruptions. However, an important aspect of mental health for youth in the child welfare system has largely been ignored: sexual concerns (e.g., distress, preoccupation). Thus, the present study evaluated whether higher levels of sexual preoccupation and distress among a sample of child welfare-involved youths (N = 124) in a northeastern state predicted placement changes and school transfers above and beyond variables previously linked with these disruptions. Our hypotheses were partially supported such that higher levels of sexual distress were linked with increased odds of experiencing a placement change (OE = 2.60; p <.01). Counter to our hypotheses, higher levels of sexual preoccupation were linked with lower odds of experiencing both placement changes (OE = −2.98; p <.01) and school transfers (OR = 0.18; p < .05). Furthermore, sexual preoccupation and sexual distress were not linked with increased rates of placement changes. The current findings have implications for the assessment of sexual concerns and the prevention of placement changes among youth in the child welfare system.

Keywords: child welfare, placement disruptions, sexual concerns, children, adolescents

1. Introduction

Nearly a half million youths reside in foster care annually, with approximately 250,000 youths entering the foster care system in 2019 alone (U.S Department of Health and Human Services, 2020). The system’s ultimate goal for these youths is to facilitate a permanent placement either with their parents of origin or, if not possible, in another stable, safe environment. Unfortunately, many youths involved in the child welfare system experience instability in numerous domains. For example, it is estimated that nearly half of youth in foster care will experience a placement change (Connell et al., 2006). In addition, researchers have also established that youths involved in the child welfare system are two to three times more likely than youth who are not involved in the system to transfer schools (Frerer et al., 2013; Parra & Martinez, 2015). This instability for child welfare-involved youths is concerning, as research demonstrates that placement changes and school transfers confer risk for additional adverse outcomes throughout childhood and adolescence.

Specifically, youths in the child welfare system who experience a greater number of school changes are more likely to experience behavioral concerns (Sullivan et al., 2010) and drop out of school (Zetlin & Weinberg, 2003). Furthermore, placement instability for child welfare youths can also lead to detrimental effects, such as involvement in the juvenile justice system (Ryan & Testa, 2005). Therefore, it is vital for research to focus on better understanding of correlates and risk factors that are associated with an increased risk for experiencing placement changes and school transfers among child welfare-involved youths, as this could better identify those youth who are at the greatest risk for experiencing negative outcomes. Guided by the theory of social ecology, this study sought to investigate the extent to which individual factors, namely mental health symptoms and sexual concerns (defined as sexual preoccupation and distress), contributed to placement changes and school transfers among child welfare-involved youth.

1.1. Theory of Social Ecology

One theoretical approach that provides a useful framework for understanding the predictors and correlates of placement changes and school transfers among youths involved in the child welfare system is Bronfenbrenner’s (1994) theory of social ecology. This theory posits that youths are nested within interconnected social systems (e.g., families, schools), which exert influence on the individual youth. In addition, Bronfenbrenner posited that influences between the youth and various systems would be reciprocal, such that a youth may also influence their social systems. When applied to the context of instability among child welfare involved youths, this theoretical framework provides a lens to investigate the ways in which child-specific characteristics are associated with instability within the larger child welfare system, and vice versa. Further, applying this approach is novel to studying instability among youths in the child welfare system, as much of the research to date that has focused on placement changes and school transfers among youth involved in the child welfare system has been unidirectional and only studied how such system-level experiences might affect the individual youth. Conversely, the influence of youths’ behaviors (e.g., mental health symptoms, sexual concerns) may influence larger social systems, including placement changes and school transfers. Therefore, to understand the complex reciprocal interplay between youth behaviors and these disruptions, we must have a better understanding of whether and how youth behaviors predict placement changes and school transfers.

1.2. Mental Health Symptoms, Placement Changes, and School Transfers

Focusing on the role of mental health symptoms may enhance our understanding of which child welfare involved youths are at the greatest risk for experiencing home and school disruptions. Indeed, youths’ in the child welfare system experience several difficulties in their social ecologies (e.g., exposure to trauma, caregiver instability) that would be implicated in the development of mental health concerns. Although many trauma-exposed youths in the child welfare system are resilient, these youths also experience disproportionately high rates of behavioral and mental health symptoms compared to youth not involved in the child welfare system (Bronsard et al., 2016). Indeed, compared to children and adolescents in the general population, youths involved in the child welfare system are up to four times more likely to meet diagnostic criteria for a mental health disorder (Bronsard et al., 2016). Previous research has established that youth who experience mental health symptoms are more likely to experience instability while involved in the child welfare system. For example, prior work has established that several types of mental health concerns are associated with an increased risk for experiencing a housing placement change (Aarons et al., 2010) among youth in the child welfare system, including externalizing concerns (e.g., disruptive behaviors), anxiety, depression, and posttraumatic stress (Konijn et al., 2019; Villodas et al., 2016). Similarly, previous studies of child welfare-involved have demonstrated that mental health concerns predict behavioral problems in the school setting and often precede a school transfer for youths in the child welfare system (Stone, 2007). Thus, future research focusing on identifying specific types of mental health concerns that may be particularly relevant to the child welfare population when considering predictors of school transfers.

1.3. Sexual Concerns

Atypical sexual development is another negative trauma-related sequelae that has been the focus of prior studies on youth in the child welfare system. Although most of this research to date focuses on problematic sexual behaviors (Baker et al., 2008; Elkovitch et al., 2009; Friedrich, 2005), youth exposed to trauma may also think differently about sex than their same-aged peers in such a way that can be impairing. This includes sexual preoccupation (i.e., difficulty stopping thinking about sex) and sexual distress (i.e., aversion or fear of sexual topics). Researchers have demonstrated that such sexual concerns are prevalent among youth in the child welfare in that nearly a third of trauma-exposed youths in the system endorse experiencing clinically significant levels of sexual preoccupation or distress (Collin-Vezina et al., 2011). Furthermore, the experience of sexual concerns has been linked with several poor outcomes for youth in the child welfare system. For example, sexual preoccupation has been linked with other concerning behaviors, including sexually coercive (e.g., Kjellgren et al., 2008) and antisocial behaviors (e.g., Lee & Forbey, 2010). Conversely, the extant literature suggests that sexual distress may be linked with avoidance of sex in adulthood (Noll et al., 2003; Simon & Feiring, 2008; Trickett et al., 2005). Although it is evident that sexual concerns are impairing, it is unclear how such concerns might affect the social ecologies, including placement changes and school transfers, of youth in the child welfare system.

1.4. Limitations to Extant Literature

There are several significant limitations in the extant literature which merit addressing by researchers. First, although sexual preoccupation and distress are well-established trauma-related sequelae, there has been no work to date connecting them with placement changes or school transfers. Given that prior work has established that other trauma-related behavioral health concerns are linked with such changes and transfers, it seems intuitive to consider whether sexual concerns may also be related above and beyond these behavioral health issues. Second, when prior studies have considered mental health symptoms, they have used broad symptom measures. As such, it is important that future research not only consider the relevance of other mental health symptoms, but also pay particular attention to the influence of symptoms that are especially relevant to the context of child welfare involvement, such as posttraumatic stress symptoms. Third, prior research is limited in that the measures of sexual issues used have focused solely on the most problematic and severe sexual behaviors (e.g., inappropriately touching peers); although these behaviors are encompassed within the spectrum of sexual issues among youth, these behaviors represent a narrow index of sexual developmental issues and fail to capture the full construct. Therefore, it is important to capture the developmentally atypical ways in which youths may think about sex and how those concerns impact placement changes and school transfers.

1.5. Present Study

The present study sought to fill a significant gap in the extant literature and investigate the associations among youth-reported sexual concerns and placement changes and school transfers in a sample of diverse youths involved in the child welfare system. Specifically, we evaluated the effect of sexual concerns, namely sexual preoccupation and distress, on home and school placement changes for youths in the child welfare system, while including other demographic (i.e., age, race, gender) and psychological factors (i.e., self-reported trauma exposure, posttraumatic stress, depression, anxiety, dissociation, anger) that have been demonstrated to be related to placement changes and school disruptions in prior studies. Based on prior work, we hypothesized that: 1) sexual concerns would be associated with an increased likelihood of experiencing any placement change or school transfer, and 2) greater numbers of reported sexual concerns would be linked with greater number of both placement changes and school transfers.

2. Method

2.1. Participants

One-hundred and thirty youths ultimately met inclusion criteria and their charts were reviewed for the present study. However, one youth did not complete any completed measures in their chart and was excluded from the present analyses. Furthermore, five more youths were not able to be located during the follow-up period and were also excluded from the present study. Therefore, a total of 124 youths had completed measures and had complete follow-up data available for the chart review.

In line with the inclusion criteria for the court-led child welfare program from which the current study was drawn from, participants ranged in age from 8 to 16 years old (M = 10.61; SD = 2.03) and were majority female (58%). The participants endorsed the following racial identities: White/Caucasian (44%), Black/African American (10%), Asian (3%), Multiracial (10%), and Other/Unknown (33%). In addition, nearly a third of the participants identified as Hispanic/Latino (27%), all of whom had identified their race as “Other/Unknown.” The majority of the sample was involved in the child welfare system due to neglect charges (82%). The remaining youths became involved in the child welfare system due to a combination of dependent and neglect charges (7%), and neglect and abuse charges (10%). Of note, dependent charges are filed in the state in which the study took place when a child has been deemed to be without proper care or supervision.

2.2. Procedures

Participants in the current study were enrolled as part of a larger court-led child welfare program evaluating the impact of evidence-based mental health assessment on linkages to effective treatment for youths involved the child welfare system. Pertaining to the program, youths were recruited through the family court of a Northeastern state. To participate in the court program, youths had to be between the ages of 8 to 16 years old, currently removed from the home, in the pretrial phase of child welfare court involvement, and endorse experiencing at least one traumatic event on the Child Trauma Screen (Lang & Connell, 2017). Youths completed self-report measures pertaining to their experiences of traumatic and stressful events and mental health symptoms at their baseline program appointment. These same youths had their system involvement tracked for the year following this initial appointment.

Family court staff approached youths and their families in the courtroom after they presented for court to be screened for eligibility for the program among child welfare-involved youths. Parents and guardians were also notified that only the youth and not their guardians were being evaluated. Then, court staff scheduled a separate appointment during which the youth would complete the baseline measures. Measures regarding demographics and experiences of trauma were read aloud to youth by court staff. Subsequently, self-report measures regarding mental health and sexual concerns were either completed independently by the youth or with the assistance of court staff based on the youth’s ability to complete measures without assistance.

For the purposes of the present study, a chart review was conducted to collect baseline variables, including demographic information and measures of mental health symptoms and sexual behavior problems. Further, a court record review was conducted to collect information on youths’ child welfare involvement postbaseline. As such, the procedures for the present study were considered to be exempt by the Lifespan Institutional Review Board.

A one-year follow-up was conducted by the court-led program to allow for sufficient time for placement changes and school transfers to occur. Throughout the year following the baseline appointment, family court staff completed forms tracking the youths’ further involvement in the court system and other relevant outcomes on a quarterly basis. To do so, court staff used online court and child welfare records. Pertinent to the present study, court staff recorded whether or not youths changed placements or transferred schools and the number of times each youth did so, which was included as part of the chart review data.

2.3. Baseline Measures

Measures pertaining to youth demographics, exposure to trauma, mental health symptoms, and sexual concerns were completed at baseline.

2.3.1. Demographic variables

For the purposes of the present study, we included age, gender, and race as youth demographic variables. Age was calculated using the time in years from a youth’s date of birth until their baseline assessment date. In regards youth gender, youths’ chose from a dichotomous variable (male vs. female). For the purposes of the present study, we collapsed race and ethnicity, such that we compared White, Non-Hispanic youths to youths who identified as either racially or ethnically minoritized.

2.3.2. Trauma Exposure

The Child Trauma Screen (CTS; Lang & Connell, 2017) was used to determine the participants’ experience of different types of trauma. The CTS was developed for youths ages 6 through 17 to identify youths who have been exposed to trauma. Specifically, the 4-item Trauma Exposure subscale from this measure was used for this present study. Participants answered “yes” or “no” to whether or not they have been the victim of violence, witnessed violence, experienced sexual abuse, or experienced other forms of trauma. Items are summed to create a trauma exposure score. In prior research by Lang and Connell (2018), the child report version of the CTS has demonstrated strong psychometric properties, including internal consistency (Cronbach’s alpha = .78), convergent validity (r = .83), and divergent validity (mean r = .31).

2.3.3. Mental Health Symptoms

Mental health symptoms were assessed using the Trauma Symptom Checklist for Children (TSCC; Briere, 1996). The TSCC is a 54-item measure which assesses posttraumatic stress and other mental health symptoms related to trauma in children and adolescents ages 6 to 16. Responses are on a 4-point (0–3) Likert scale, ranging from “never” to “almost all of the time.” It is one of the most widely utilized measures of trauma-related mental health symptoms and has well-established reliability and validity (Briere, 1996; Elhai et al., 2005). Further, the TSCC yields age and gender-based t-scores that are based off of an ethnically diverse normative sample (Briere, 1996). The TSCC includes subscales evaluating youth experiences of anxiety (e.g., “worrying about things), depression (e.g., “feeling sad or unhappy”), anger (e.g., “feeling mad”), dissociation (e.g., “feeling like I’m not in my body”, and PTSD (e.g., “remembering scary things”).

2.3.4. Sexual Concerns

The TSCC was also used to evaluate sexual concerns among youths in the present study.

The TSCC has two separate scales that evaluate sexual concerns. Consistent with the other scales, responses are on a 4-point Likert scale ranging from “never” (0) to “almost all of the time” (3). First, the 7-item Sexual Preoccupation subscale evaluates a youth’s developmentally atypical interest in sexual activities (e.g., thinking about sex too much, thinking about touching others’ private parts). Second, the 4-item Sexual Distress subscale evaluates whether the youth avoids or is fearful of sexual content (e.g., getting upset when thinking about sex, thinking about sex without wanting to). The sexual concern subscales of the TSCC have demonstrated convergent validity with other measures of youth sexual concerns (Crouch et al., 1999).

2.4. Measure of Placement Changes and School Transfers

One year after youths completed baseline measures, information was collected through court child welfare system records regarding youths’ continued court involvement and other indices of well-being. Pertinent to the present study, information on youths’ changes in home placements and school placements were also collected; specifically, information was gathered about whether or not a youth experienced a placement change, as well as the number of placement changes. Of note, achieving permanency or being placed back with caregivers of origin was not included in the number of placement changes each youth experienced.

2.5. Analytic Strategy

Two different analytic strategies were used to first determine the effect of demographic variables, trauma exposure, mental health symptoms, and sexual concerns on school and home placement changes. This decision was made in light of the fact that the number of placement changes and school transfers had markedly different distributions. Indeed, youths experienced home placement changes with great frequency (45%) and many youths experienced more than one placement change (22%). Thus, an analytic approach that could account for both (a) whether or not a youth experienced a placement change and (b) the number of times a youth experienced a placement change were deemed most appropriate. Conversely, a lower number of youths experienced a school placement change (15%), with only one youth experiencing more than one change. Therefore, an approach that only accounted for whether or not a school placement change occurred was warranted. It should be noted that demographic differences were not investigated in either analysis due to sample size.

Zero Inflated Poisson (ZIP) regressions were used to determine the effect of demographic variables (age, gender, race), trauma exposure, anxiety, depression, dissociation, PTSD, sexual preoccupation, and sexual distress on both (a) whether or not a youth changed home placements and (b) the number of home placement changes. ZIP regressions are appropriate for data which are censored and include both binary (i.e., whether a placement change occurred) and continuous outcomes (i.e., the number of times a placement change occurred; Yang et al., 2017). ZIP regressions yield two different estimates: odds estimates (OEs) and rate estimates (REs). OEs estimate the effect of baseline variables on the relative odds of whether or not a placement change occurred, whereas, REs estimate the effect of baseline variables on the relative rates with which placement changes occurred. Negative OEs and REs indicate that an increase in a level of a predictor would be linked with decreased odds and rates of a placement change, whereas, a positive OE or RE would indicate that increased levels of a predictor was associated with increased odds and rates of a placement change. ZIP regressions were conducted using R (Version 4.1.0).

Logistic regression was employed to evaluate the impact of trauma exposure, mental health symptoms, sexual preoccupation, and sexual distress on whether or not youth in the present study experienced a school transfer. Logistic regressions are appropriate for data which have binary outcome variables (e.g., transferred schools vs. did not transfer schools; McCullagh & Nadler, 2018). Further, logistic regression models also allow for variables to be entered in a stepped process. As such, we entered demographic variables and level of trauma exposure into our first step of the model. Second, we entered PTSD and other mental health symptoms in our second step. In our final step, we added in indices of sexual preoccupation and distress to evaluate whether or not adding in these variables had added value in predicting school transfers. Odds ratio values greater than 1.00 indicate that a predictor variable increases the likelihood of an outcome. Logistic regression analyses were conducted in SPSS (Version 27).

3. Results

3.1. Preliminary Analyses

First, data were examined for missingness and less than 5% of the data were identified as missing. Bivariate correlations between age, mental health symptoms, sexual preoccupation, and sexual distress were conducted. Age was not correlated with sexual distress or any other mental health concerns but was negatively correlated with sexual preoccupation (r = −.20; p < .05). Significant correlations were also evidenced between the sexual concern subscales and all indices of mental health. Specifically, sexual preoccupation was correlated as follows with other subscales on the TSCC: anxiety (r = .40; p <.001), depression (r = .44; p <.001), anger (r = .47; p <.001), posttraumatic stress (r = .36; p < .001) and dissociation (r = .40; p <.001). Furthermore, sexual distress evidenced correlations with the following variables: anxiety (r = .32; p <.001). depression (r = .30; p <.01), anger (r = .21; p <.05), posttraumatic stress (r = .29; p <.01), and dissociation (r = .25; p <.01). Sexual distress and sexual preoccupation were also significantly correlated (r = .48; p <.001). Notably, neither sexual preoccupation nor distress were related to the number of trauma exposures. In addition, Table 1 displays means and standard deviations for t-scores on mental health and sexual concerns. A chi-square test also indicated that home and school placement changes were not related to one another (X2 = 1.61; p = .20).

Table 1.

Means, Standard Deviations, and Ranges for T-Scores of Mental Health Symptoms

Variable M SD Range
Anxiety 49.09 14.34 35–98
Depression 46.90 11.34 35–86
Anger 45.18 11.01 25–82
PTSD 49.56 12.66 26–83
Dissociation 49.93 12.43 35–93
Sexual preoccupation 46.31 10.00 37–111
Sexual distress 52.14 15.37 41–111
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Note. All mental health t-scores were derived from the TSCC. M = mean; SD = standard deviation. T-scores above 65 are considered clinically significant for all scales, except for Sexual Preoccupation and Distress. For the Sexual Concerns subscales, a t-score of 70 or above is considered clinically significant.

3.2. Primary Analyses

3.2.1. Placement Changes

Results of the ZIP regression model demonstrated that several variables were linked with increased odds of experiencing a home placement change (see Table 2). Indeed, several variables were linked with the odds of experiencing a placement change. Specifically, younger age (OE = −0.63; p < .05), identifying as racially or ethnically minoritized (OE = −3.61; p <.01), and higher levels of anger (OE = 2.77; p < .05 and sexual distress (OE = 2.60; p <.01) were linked with increased odds of experiencing a placement change. Higher levels of PTSD symptoms (OE = −2.36; p <.05) and higher levels of sexual preoccupation (OE = −2.98; p <.01) were both related to decreased odds of experiencing a placement change. Anger was the only variable linked with the frequency of placement changes, such that higher levels of anger was related to a higher number of placement changes.

Table 2.

Zero-Inflated Poisson Regression Model for Placement Changes

Variable OE 95% CI RE 95% CI
 Gender 0.45 [−1.50, 2.39] 0.09 [−0.38, 0.56]
 Age −0.63* [−1.19, −0.07] −0.01 [−0.14, 0.11]
 Race −3.61** [−6.35, −0.88] −0.31 [−0.79, 0.17]
 Trauma exposure −0.78 [−1.96, 0.40] −0.05 [−0.30, 0.20]
 Anxiety 0.63 [−1.65, 2.92] 0.15 [−0.39, 0.69]
 Depression −0.53 [−2.27, 1.21] −0.28 [−0.73, 0.18]
 Anger 2.77* [0.42, 5.13] 0.48* [0.03, 0.94]
 PTSD −2.36* [−4.58, −0.15] −0.16 [−0.62, 0.30]
 Dissociation 0.50 [−1.26, 2.26] −0.02 [−0.47, 0.42]
 Sexual preoccupation −2.98** [−5.11, −0.84] −0.17 [−0.49, 0.15]
 Sexual distress 2.60** [0.83, 4.38] 0.24 [−0.15, 0.62]
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Note. OE = odds estimates; REs = rate estimates.

*

p < .05

**

p < .01

3.2.2. School Transfers

Step One of the logistic regression model for school transfers included age, gender, race, and trauma exposures (see Table 3). At this step, the model, step, and individual variables did not emerge as significant. In Step Two of the model, trauma-related mental health symptoms (i.e., anxiety, depression, anger, PTSD, and dissociation) were added into the model. Again, none of the variables emerged as significant and neither the step nor model were significant. In the final and third step of the model, sexual preoccupation and sexual distress were entered into the model. At this point, the overall model and step were significant (p < .05). In addition, higher levels of sexual preoccupation (OR = 0.18; p < .05) and female gender (OR = 0.28; p < .05) were linked with decreased odds of a school transfer.

Table 3.

Logistic Regression Model for School Transfers

Variable OR 95% C.I. OR 95% C.I. OR 95% CI
 Step 1
  Gender 0.38 [0.13, 1.07] 0.34 [0.11, 1.01] 0.28* [0.09, 0.90]
  Age 1.28 [0.99, 1.64] 1.30 [0.96, 1.70] 1.18 [0.88, 1.57]
  Race 1.35 [0.48, 3.81] 1.80 [0.60, 5.40] 1.74 [0.55, 5.50]
  Trauma exposure 0.77 [0.46, 1.31] 0.70 [0.39, 1.27] 0.82 [0.42, 1.58]
 Step 2
  Anxiety -- -- 0.63 [0.18, 2.15] 0.56 [0.14, 2.25]
  Depression -- -- 0.64 [0.22, 1.84] 0.63 [0.20, 1.91]
  Anger -- -- 1.41 [0.63, 3.14] 2.13 [0.81, 5.63]
  PTSD -- -- 2.32 [0.80, 6.69] 2.24 [0.71, 7.12]
  Dissociation -- -- 0.96 [0.32, 2.93] 0.99 [0.30, 3.29]
 Step 3
  Sexual preoccupation -- -- -- -- 0.18* [0.04, 0.81]
  Sexual distress -- -- -- -- 1.12 [0.56, 2.25]
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Note. OR = odds ratio; 95% CI = 95% confidence interval.

*

p < .05

4. Discussion

Youths involved in the child welfare system often experience instability while involved in the system, including disruption in both housing and school placements. Furthermore, these youths often exhibit mental health concerns and other negative trauma-related sequelae. However, the extent to which trauma-specific sexual concerns (i.e., sexual distress, sexual preoccupation), are associated with disruption in housing and school transfers is not well established. To that end, this study sought to evaluate whether sexual concerns predicted the likelihood of experiencing greater disruptions in placements and school transfers, and whether sexual concerns were associated with the number of placement and school transfers, while accounting for experiences of trauma, trauma-related mental health symptoms, and demographic variables, in a sample of youth involved in the child welfare system.

Overall, our hypotheses were partially supported. As hypothesized, sexual concerns were related to increased odds of experiencing a home placement change, though this was only true for sexual distress specifically. Given that sexual distress can be construed as an internalizing concern, our results are consistent with prior work demonstrating that internalizing concerns are linked with subsequent placement changes (Aarons et al., 2010). Furthermore, sexual distress is also a potential posttraumatic reaction and the link between sexual distress and placement changes established in the present study builds on prior work demonstrating the link between trauma-related behavioral health concerns and placement instability (Clark et al., 2020). Although it was beyond the scope of the present study to determine for whom sexual distress may be particularly important in predicting placement changes, future work would benefit from further determining potential moderators of the relation between sexual distress and placement changes. For example, prior work suggests that child welfare-involved girls may be more likely to experience trauma-related concerns than their male peers (Hagborg et al., 2017), suggesting the possibility that there may be differences in the likelihood for instability between child-welfare involved boys and girls.

Our results were surprising in two important ways. First, neither sexual preoccupation nor distress were linked with the number of placement changes experienced and sexual distress was not linked with school transfers. Second, also contrary to our hypotheses, higher levels of sexual preoccupation were linked to a reduced odds of experiencing both a home placement change and school transfer. There are several possible pathways by which sexual preoccupation may have actually reduced the odds of placement changes and school transfers. First, it is possible that youth sexual preoccupation may have directly impacted decisions to have a youth transfer placements and schools. For example, it could be the case that youths with higher levels of sexual preoccupation who shared their thoughts and experiences were prevented from transferring to a placement that may have been more appropriate for them due to the stigma regarding sexual concerns (Chaffin, 2008). Such stigma in future placements and schools may impact whether the youth may be accepted to such placements. Although placement changes and school transfers typically have a negative impact on youths, there are less common individual cases in which it may be indicated.

Conversely, youth sexual preoccupation may have also affected placement changes and school transfers through indirect pathways that were not examined in the present study. One possible indirect pathway that was not focus of the current study could be through youths’ stigmatizing thoughts about their own behaviors, such that youths’ with higher levels of sexual preoccupation may feel guilt and shame about their symptoms and, as such, be less likely to share their concerns with caregivers. Thus, these youths may appear to have less identifiable mental health concerns by their caregivers and be less likely to be moved to a new placement. Alternatively sexual preoccupation among child welfare-involved youth may indeed be adaptive. Because youth in the child welfare system often receive inadequate support from adults (Perry, 2006), they may not have adults to rely on for information regarding their sexual development. Therefore, child welfare-involved youth may spend more time on their own thinking about sexual matters as part of their healthy sexual development. In addition to these possible pathways, the idea that these findings also arose through statistical suppressor effects also merits consideration, given the unexpected direction of these findings. Future work is needed to both replicate this surprising finding and to better understand the pathways by which sexual preoccupation may impact placement changes.

Although some of our findings were contrary to initial hypotheses, the current results align with Bronfenbrenner’s (1994) theory of social ecology individual characteristics of youths in the present study appeared to exert influence on their social environment (i.e., home and school). Given prior literature suggesting that the home and school settings affect the mental health of child welfare-involved youths (e.g., Sullivan et al., 2010) and that youth sexual concerns are linked with placement changes (Lyons et al., 2009), our results suggest that a reciprocal relationship between youth characteristics, including sexual concerns, and their social environments may exist. However, our study only measured the effect in one direction (i.e., individual characteristics on home and school). As such, further work which incorporates multiple measurement time points will be needed to examine the likely reciprocal nature of this relationship. For example, such work would allow researchers to evaluate whether placement instability leads to higher rates of sexual distress, which, in turn, leads to even higher rates of instability.

4.1. Clinical Implications

The current results have a number of clinical implications. First, the findings from the present study imply that sexual concerns could potentially play a role in the overall instability that many child welfare youths encounter, suggesting that this population may benefit from both prevention and intervention strategies related to sexual concerns. For example, many child welfare-involved youths may benefit from being screening for sexual concerns, regardless of whether or not youth endorse prior abusive experiences and/or current posttraumatic stress symptoms (Lyons et al., 2009). Similarly, given the importance of caregiver involvement in the overall functioning of child welfare-involved youths (e.g., Cheung et al., 2012), it may be relevant for caregivers (e.g., foster parents, child welfare workers) to receive psychoeducation related to the overall prevalence, manifestation, and correlates of sexual concerns. Our results would also suggest that all youths in the child welfare system should be screened for sexual concerns. Such screening would be done not to criminalize youth but instead to inform further assessment and intervention. Youths who are identified as having sexual concerns should then be referred to an appropriate treatment modality. One such treatment that may be especially appropriate for treating sexual concerns for trauma-exposed youths would be Trauma-Focused Cognitive Behavioral Therapy (Cohen et al., 2016), which specifically targets treating trauma-related negative sequalae.

4.2. Strengths and Limitations

Among its strengths, the current study utilized one of the few empirically validated measures of sexual concerns for youth. Second, given the focus of earlier research on caregiver-reported sexual behaviors, we evaluated indices of sexual concerns that were based on youth report and captured internal experiences of sexual concerns. Third, we chose school transfers as one of our outcomes given the fact that prior research has not focused on linking youth sexual concerns with school transfers among child welfare-involved youths. This is especially vital given the well-documented negative effect that school transfers have on child welfare-involved youths. Finally, the present study utilized data drawn from an ethnically and racially diverse sample of child welfare-involved youth, a population that is particularly vulnerable to experiencing mental health problems, including sexual behavior problems.

There are several limitations that should be acknowledged. For example, the sample included child welfare-involved youth from one state, and so the current findings may not generalize to other populations of child welfare-involved youth. Additionally, the sample size precluded us from examining differences by sex and race/ethnicity; given that racial and ethnic minoritized youth are more likely to be experience out-of-home placements (Foster et al., 2011), future research should investigate the extent to which racial or ethnic minority status affects placement changes among youth who report sexual concerns. Further, the sample was comprised of youths from a wide developmental age range; this is important to note, as sexual concerns may manifest differently based on developmental stage. Given that the court program from which these data were gathered only included youth between the ages of 8 and 16 years old, we were unable to examine whether sexual concerns were associated with the outcomes of interest among youth younger than 8 years old. In addition, we were unable to do psychometric analyses on our measures due to item-level data not being available through our chart review. However, the psychometrics of our measures have been well-established in prior studies. It should also be noted that the mean score for both sexual concern subscales in the present sample was well below the clinically significant range. Therefore, future studies with larger samples may be better able to have a wider variety of scores and parse apart the effects of clinically significant scores. Furthermore, the reasons for which placement changes and school transfers were initiated were not documented in the present study; as such, we were not able to parse apart changes and transfers that may have had a positive impact on youths. Finally, given the relatively low rates of school transfers, we utilized a dichotomous variable to assess whether or not a youth experienced a transfer; future research may benefit from attempting to replicate the presenting findings wherein the number of school transfers are defined as a continuous variable. Despite these limitations, this study contributes novel findings to the current literature that may have greater implications in regard to how sexual concerns are associated with negative outcomes, including school and placement changes, among child welfare-involved youths.

4.3. Conclusion

In summary, this study used a diverse sample of child welfare-involved youths to examine the effect of sexual concerns on placement changes and school transfers. Our results confirmed that certain types of sexual concerns (i.e., sexual distress) were linked with increased odds of experiencing a placement change; however, other sexual concerns (i.e., sexual preoccupation) were related to decreased odds of experiencing a placement or a school change. Viewed together, our findings indicate that youth sexual concerns do, indeed, impact child welfare-involved youths’ social environments. Even so, future work is needed to replicate our findings and determine the pathways by which youth sexual concerns impact placement changes and school transfers.

Footnotes

We have no known conflicts of interest to disclose.

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