Family-Controlled Trafficking in the United States: Victim Characteristics, System Response, and Case Outcomes
Emily E. Edwards, Jennifer S. Middleton & Jennifer Cole (2022): Family Controlled Trafficking in the United States: Victim Characteristics, System Response, and Case Outcomes, Journal of Human Trafficking, DOI: 10.1080/23322705.2022.2039866
Though limited research has explored trafficker relationships involving family members as perpetrators, it is well documented that some victims of child trafficking are exploited by a family member or by a non-relative facilitated by a family member. This study utilized administrative data from the United States’ Kentucky child welfare system to examine how victim characteristics, case factors, system responses, and case outcomes are related to whether a child is trafficked by a family member perpetrator versus non-relative (only) perpetrator. Analyses were based on 698 alleged victims of child trafficking reported between 2013 and 2017. Findings suggest that victims of family controlled trafficking were more likely to have a higher number of perpetrators, live in rural communities, and be younger. Further, instances of family-controlled trafficking were found to be more likely reported by anonymous, non-relative community members, and relative reporting parties compared to reporting parties of professionals, law enforcement, courts, and juvenile justice, as reflected in previous literature. Important findings revealed that having a family member involved as the perpetrator of trafficking predicted that the case would not be substantiated and/or founded, compared to cases not involving a family member. Implications for future research regarding the dynamics of family-controlled trafficking cases are discussed. Findings suggest opportunities for enhanced practices, training, and capacity in rural communities. To make a significant impact on the reduction of family-controlled trafficking, this study sheds light on the need for enforced penalties for family members as traffickers.
Human trafficking is the fastest growing criminal industry in the world today (Office of Refugee Resettlement. United States Department of Health and Human Services, 2012) generating $9.5 billion yearly in the United States (United Nations News Story, 2007). Troublingly, 83% of all confirmed human trafficking cases in the United States involve American born citizens and 98% of sex trafficking victims are women and girls (Department of Justice/Office of Justice Programs Report, 2011). According to the U.S. DOJ, children first fall victim to commercial sexual exploitation, on average, between 12 and 14 years of age (Adams et al., 2010) and one in 11 youth receive an unwanted online sexual solicitation or approach (K. Mitchell et al., 2014). Victims are becoming younger, largely because exploiters are concerned about victims having HIV or AIDS (Franchino-Olsen, 2021; Hall, 2010). Many victims tend to come from vulnerable populations with a serious history of previous abuse. Risk factors that increase youths’ vulnerability to trafficking include sexual or physical abuse or maltreatment, running away or being homeless, system-involvement, such as with the juvenile justice and child welfare systems, being LGBTQIA+, substance abuse, poverty, and early adverse childhood experiences (Bryan, 2014; IOM (Institute of Medicine) and NRC (National Research Council), 2013). Children, in particular, are at high risk for human trafficking and oftentimes trafficking by a family member. In the United States, per federal law, states’ child welfare systems are tasked with the prevention, investigation, and intervention of child trafficking. As a result, state child welfare systems collect substantial amounts of data pertaining to the scope and characteristics of child trafficking. For the purposes of the current study, child trafficking data were derived from a state child welfare agency and thus offer a unique, specific vantage point in better understanding human trafficking in the United States Child trafficking, which includes commercial sexual exploitation, domestic, sex trafficking, and labor trafficking of minors (Ijadi-Maghsoodi et al., 2014) results in high rates of posttraumatic stress disorder, depression, suicidal ideation, drug addiction, and a multitude of somatic symptoms among the victims (Middleton et al., 2018; Zimmerman et al.,2008). Specifically, most victims experience symptoms of complex trauma, resulting from events that include entrapment; relocation; exposure to the abuse of others; and extended physical, sexual, psychological abuse (Courtois, 2008). Trafficked youth are also at increased risk for suicide (DuBois & Felner, 2016; Frey et al., 2018), which is likely exacerbated by the difficulty in accessing these youth in order to ensure accurate clinical assessment and prompt follow-up care (Martinez, 2006).
Some victims of child trafficking are exploited by a family member as the perpetrator or by a non relative along with a family member facilitating exploitation. Though few studies have examined this type of child trafficking, family member involvement in child trafficking has been identified in the literature (Kennedy & Pucci, 2007), with terms coined “familial trafficking” (Sprang & Cole, 2018) and “family facilitated juvenile sex trafficking” (Reid et al., 2015). Frequently used in the Kentuckiana region is the term describing this experience as family-controlled trafficking (Arvizu, 2019) to encompass the wider range of experiences of human trafficking survivors whose families were involved in their exploitation. The literature review below serves to unpack family-controlled trafficking and is divided into four key sections: prevalence, risk factors, consequences, and the local community landscape of family-controlled trafficking.
Prevalence of Family-Controlled Trafficking in the United States
In the United States, awareness regarding the phenomenon of family-controlled trafficking is increas ing, as substantiated cases involving family members and/or caregivers as perpetrators are becoming more prevalent. Over 10 years ago, K. J. Mitchell et al. (2010) found that 12% of juvenile prostitution cases involved personal relationships between the child victim and perpetrator, including caretakers and family members who were paid for the child’s commercial sexual exploitation and sexual abuse. Similarly, in a report by Polaris Project (2012), researchers identified a small but meaningful percen tage of child trafficking victims being recruited by caregivers and over 11% of child trafficking recruitment occurring while the child is at home. Additionally, the National Human Trafficking Resource Center (NHTRC; 2015) identified 314 child welfare-involved cases of child trafficking from 2007 to 2012 in which the children were allegedly trafficked by a parent, legal guardian, and/ or foster parent. More recent literature focusing on the tactics of traffickers reveals that 14.4% of sex traffickers were found to victimize their children, spouses, partners, siblings, and other family members (Feehs & Richmond, 2018), and this percentage increased to 37.8% the following year (Currier & Feehs, 2019).
Research explains that for some children and youth who are victims of trafficking, a family history and culture of survival sex may be seen as a “family business” (Miccio-Fonseca, 2017, p. 567). This is congruent with existing research, which has shown the prevalence of close relationships between sex traffickers and their victims, including family members (Malm & Bichler, 2011; Malm et al., 2010; McGloin, 2005; Natarajan, 2006). Researchers have postulated that working in small groups, cliques, or subgroups with these types of intimate and biological relationships provides safety and protection to sex traffickers (Malm & Bichler, 2011; Malm et al., 2010; Natarajan, 2006) and limits detection by law enforcement (Sabon et al., 2021). Though the research on family-controlled trafficking is growing in recent years, there remains a gap in the literature regarding the complexities of family-controlled trafficking and a lack of clarity or empirical support for predisposing factors related to this phenomenon.
There are several reasons for the small body of research addressing family-controlled trafficking. Human trafficking alone is complex, and the dynamics of family-controlled trafficking add a layer of complexity and enhance the barriers to rigorous examination and measurement. The human trafficking industry is underground and invisible (Franchino-Olsen, 2021) and many victims do not realize they are being exploited (McClain & Garrity, 2011). Furthermore, for victims with family members as traffickers, trafficking is embedded within the intimate relationships, characterizing intimidation, violence, and control, as well as affection and dependency (Verhoeven et al., 2015). Thus, evidence clearly suggests researchers are met with difficulties collecting data that reflects the volume, frequency, and complexities of child trafficking (Franchino-Olsen, 2021), which arguably, points to more inherent challenges when researching family-controlled trafficking nested within the field of child trafficking. As a result, more research is needed to continue exploring and examining various exploitation typologies, inclusive of those with family member involvement.
Risk Factors Associated with Victims of Family-Controlled Trafficking
Though an emerging area of research, very little exists in the literature on risk factors for the involvement of family members as perpetrators in child trafficking. Generally, childhood trauma has been found to be associated with child trafficking. For example, Middleton and Vavrousek (2016) found that 48% of the youth reporting being sex-trafficked had Adverse Childhood Experiences (ACEs) of seven or more. The ACEs predicting sex trafficking included experiencing emotional abuse, sexual abuse, emotional neglect, physical neglect, and witnessing domestic abuse. Other risk factors for child trafficking include the child’s history of running away and early alcohol/drug use (J. A. Reid, 2011), as well as having a history of child maltreatment and a caregiver with alcohol/drug use, mental health problems, domestic violence (J. Reid, 2012).
While limited, the research regarding known risk factors for child trafficking facilitated by a family member runs parallel to the risk factors for child trafficking. For example, Twis (2020) discovered that child victims with a family member as the trafficking perpetrator were more likely to have a history of child welfare involvement, whereas child victims with juvenile justice system involvement were more likely to be trafficked by a stranger and/or third party trafficker. In addition, early findings calling for more research on family-controlled trafficking revealed that child victims of family-controlled trafficking were mostly from suburban communities, were the least likely to have a known history of running away (K. J. Mitchell et al., 2010) and had family members involved in sex work (Fedina et al., 2016). More recent research on risk factors for family-controlled trafficking include living in rural or micropolitan areas and children of young age (Sprang & Cole, 2018).
Consequences of Family-Controlled Trafficking
Child trafficking increases risk for many complex difficulties as children grow up and the consequences can be detrimental or even fatal. For example, Frey et al. () found that among a sample of youth experiencing homelessness and sex trafficking, 53% reported experiencing suicidal ideation and 84.4% had attempted suicide in their lifetime. Importantly, the one consistent protective factor against child trafficking and its severe consequences is that of supportive interpersonal relationships (Landers et al., 2019; O’Brien, 2018). However, in cases of family-controlled trafficking, a relative, primary caregiver, or guardian in a position of trust is an involved perpetrator causing harm to the child. This type of context of perpetrator relationship is critical to consider because children who experience abandonment, sexual abuse, and betrayal trauma from caregivers endure immense psychological and social consequences (Arata et al., 2007; Freyd, 2003; Norman et al., 2012; Stroebel et al., 2012). Thus, children who experience trafficking facilitated by a family member are at-risk for similar, if not more significant negative outcomes.
When studying the characteristics and dynamics of 19 family-controlled trafficking cases, Reid et al. (2015) found similar psychological and social consequences among victims such as anxiety, depression, interpersonal relationship difficulties, and problems with authority figures. Of the 19 victims, 90% were diagnosed with a mental health disorder (including posttraumatic stress disorder, bipolar disorder, depression, conduct disorder, and attention-deficit hyperactivity disorder) and almost half were diagnosed with more than one mental health disorder. Other consequences included suicidal ideation, as well as self-harming behavior and psychiatric hospitalizations due to suicidal attempts. While the above-mentioned consequences are parallel to the literature regarding consequences of child trafficking in general, Reid et al. (2015) also found that social consequences of family-controlled trafficking included low frustration tolerance and uncontrollable anger at the caregiver facilitating trafficking and authority figures in general.
Family-Controlled Trafficking in Kentucky
Cole and Anderson (2013) conducted surveys of 323 professionals (i.e., court designated workers, DOJ personnel, providers for at-risk youth and victim services) in Kentucky, with 49.8% having worked with definite or alleged victims of child trafficking. They found that the most commonly reported trafficker-victim relationship of the three most recent cases was a family member (62%) followed by a third-party perpetrator (e.g., pimp, family friend, intimate partner, stranger). To better understand the dynamics of family-controlled trafficking in Kentucky, Sprang and Cole (2018) examined 31 children in Kentucky’s child welfare system who were receiving mental health assessment and treatment. Of these cases, the researchers explored characteristics of the victims (e.g., gender, resi dence, experiences), the trafficking situation, the case outcomes, and the relationships between the victims and traffickers. All the cases examined involved a family member as the trafficker, including the mother (64.5%), father (32.3%), and other family members (3.2%). In almost half of cases, there were also indications of third-party traffickers who were non-family members. In a vast majority of the cases, parents were trafficking their children to receive illicit drugs as currency. Child victims were trafficked for prostitution, pornography, and strip club involvement, and recruited by threats and authority intimidation by caregivers. Of these cases, 64.5% resulted in a criminal charge against the trafficker (e.g., child abuse), however, only a third resulted in criminal, human trafficking charges. It is important to note that labeling family-controlled trafficking as child abuse without the commercial element results in less severe charges (Smith et al., 2009).
The United States’ Trafficking Victims Protection Act (TVPA) of 2000 established federal policies and methods of prosecuting traffickers, preventing human trafficking, and protecting victims and survivors of trafficking, including children. The act established human trafficking and related offenses as federal crimes and helped to inform new state-level policies about the prevention and intervention of trafficking of children throughout the United States. In June 2013, the Human Trafficking Victims’ Rights Act, which is a safe harbor law, was enacted in Kentucky. One of the key provisions of the law was to mandate the state child welfare agency, the Department of Community Based Services (DCBS), to be responsible for investigating reports of human trafficking involving a juvenile, handling cases of human trafficking like any other dependency, neglect, or abuse case, and providing services to juvenile victims, regardless of the relationship of the trafficker to the alleged victim (Human Trafficking Victims’ Rights Act, Kentucky Revised Ann. Statutes § 529.120). Since Kentucky’s safe harbor law in 2013, child trafficking reports increased between the years 2014 and 2017 (Cole & Sprang, 2020). However, the substantiation rates for child trafficking (confirmed by law enforcement) were lower than substantiation rates for child neglect (as reported in the Anne E. Casey Foundation, 2019) and child sexual abuse (Cole & Sprang, 2020). The status of substantiation rates relates to the level of evidence available to the investigating party (Reid et al., 2017) and the literature suggests that more research is needed to uncover the child welfare and law enforce ment processes that occur after reports of suspected human trafficking to determine if there are system break downs or challenges that prevent successful identification and investigation of human trafficking cases. (Cole & Sprang, 2020, p. 8)
Cole and Sprang (2020) postulated that successful identification and investigation of complex human trafficking cases might be prevented by system breakdowns and challenges related to investi gative techniques involving diverse types of sex trafficking scenarios (e.g., family-controlled trafficking).
During a similar time period, Middleton and Edwards (2020) examined child trafficking cases through administrative data in Kentucky’s child welfare system between the years 2013 and 2017, following the safe harbor law. Building on previous findings on child trafficking and family-controlled trafficking (Cole & Anderson, 2013; Cole & Sprang, 2020; Sprang & Cole, 2018), Middleton and Edwards (2020) found similar results in case characteristics and outcomes. Among 698 alleged victims of child trafficking, 57.7% of trafficking victims were controlled by family members and 61.2% of the alleged victims were at home when the allegations of child trafficking were received. Reflecting previous literature, multiple perpetrators were more likely to be involved in cases involving young children, drugs, and family-controlled trafficking. The current study utilizes the same administrative data involving child trafficking cases to further examine how victim characteristics, case factors, system responses, and case outcomes are related to whether a child is trafficked by a family member perpetrator versus non-relative (only) perpetrator. Specifically, the current study aims to answer the following research questions about child welfare cases: (1) What victim characteristics are associated with family-controlled trafficking cases? (2) What case factors are associated with family-controlled trafficking cases? (3) What system responses are associated with family-controlled trafficking cases? (4) What case outcomes are associated with family-controlled trafficking cases?
Methods
Participants
The authors conducted a comprehensive case review of 698 alleged child trafficking cases reported to the Kentucky Department of Community Based Services (DCBS) between 2013 and 2017. In Kentucky, all residents are considered mandated reporters and any individual can file a report of child abuse and neglect. Reports can be submitted using the hotline phone number if they are considered emergent, or via an online portal if they are considered to be non-emergent. When child abuse and neglect reports are received through the hotline, the DCBS asks one question about whether child trafficking is suspected. The dataset included 29 questions answered by the reporting party. In addition to specific questions asked when making reports, each case had an open-ended question for additional comments and a brief description of the allegations reported.
Of the 698 alleged victims included in the reports of possible human trafficking to the state child welfare agency from 2013 to 2017, the mean age of the alleged victims was 13.7, with nearly one-third of alleged victims (32.1%) being 13 years old or younger, 30.2% were 14 and 15 years old, and the remaining 37.6% of alleged victims were 16 and 17 years old. The majority of victims were female (83.5%). The vast majority of victims (97.6%) were born in the U.S. Furthermore, most victims (89.0%) had prior involvement with the child welfare agency. The majority of alleged victims (59.5%, n = 415) had at least one perpetrator who was a family member, 40.5% (n = 283) of alleged victims had their only perpetrator (or all of their perpetrators, if multiple) who were not family members. The numbers of alleged victims reported to the child welfare agency as possible victims of human trafficking increased over time as indicated in the report years: 2013 (n = 22), 2014 (n = 102), 2015 (n = 115), 2016 (n = 208), and 2017 (n = 251).
Procedures
The authors worked with the Department of Community Based Services (DCBS) to obtain a data sharing agreement and design a data extraction tool to be used to collect pertinent information and specific variables for the case file review. Research-based characteristics of child trafficking victims informed the data elements to be included in the data extraction tool utilized to collect data from the DCBS case worker intake assessment form (aka: ADT CPS Assessment for Abuse/Neglect form).
Measures
Operational Definitions
In the data, if at least one perpetrator was a family member, then the case was classified as “family controlled trafficking.” Included in the report being made was a question, “Was the perpetrator a caretaker?” Further, additional questions asked, “What was the caretaker’s relationship to the victim?” and “What was the non-caretaker’s relationship to the victim?” The authors condensed this variable into the question, “Was the perpetrator a family member?” which resulted in two outcomes: Nonrelative, encompassing all relationships of perpetrators not related to the alleged child victim; and Family Member, encompassing biological, legal, or adoptive relationships including aunt, uncle, brother, sister, father, mother, stepmother, stepfather, adoptive mother, adoptive father, grandmother, and grandfather.
In the reports, case outcome (e.g., whether a case was substantiated and/or founded) was included as an outcome variable and of interest to the authors due to the need to further examine the substantiation process in Kentucky (Cole & Sprang, 2020). Ninety-five cases involving a family member as the perpetrator/trafficker resulted in being substantiated, 141 cases involving a non
family member as the perpetrator/trafficker resulted in being founded; and 26 cases involving both a family member and non-family member as perpetrators/traffickers resulted in being both substan tiated and founded. To account for the overlapping cases, specifically the 26 cases involving victims trafficked by both a family member and non-family member, the authors subtracted 26 from the total sample (n = 236), resulting in 210 cases. Thus, the authors created one variable that accounted for all cases (n = 210) confirmed either by law enforcement investigation (founded) and/or by a DCBS investigation (substantiated).
Community type was classified as metropolitan or rural (non-metropolitan) based on United Nations News Story, 2007) data. Included in the reports was a variable accounting for the child victim’s county of residence. The authors differentiated metropolitan from rural/non-metropolitan by separating the three highest-populated counties in Kentucky from the rest of the state: Jefferson County (pop. 741,096), Fayette County (pop. 295,803), and Kenton County (pop. 159,720).
Data Analysis Approach
To not violate the assumption of independence in the statistical tests used in the bivariate and multivariate analysis, the unit of analysis was at the case-level and not the victim-level. We randomly selected one of the victims in cases involving multiple victims to include in the bivariate and multi variate statistical tests. Two variables had more than 5% of cases with missing values: drug involvement of victim (n = 79, 13.9%) and charges related to human trafficking (n = 50, 8.8%). A third variable, Referral source, had two categories that could not be assigned to the dummy variable, referral by the justice system (Yes/No), that was used in the logistic regression: anonymous (n = 93, 16.4%) and unknown (n = 9, 1.6%), thus, the dummy variable had 101 cases missing values. To reduce bias, missing values analysis was conducted. Multiple imputation was conducted using all the variables in the dataset to maximize information to impute values (Donders et al., 2006; Van der Heijden et al., 2006). The missing patterns showed monotonicity. Missing values were assumed to be missing at random and were imputed with the use of multivariate imputation by chained equations for variables in SPSS 27.0. Five imputed datasets were generated and used for bivariate and multiple analyses involving the variables with the higher frequencies of missing values. In these cases, the results were combined to estimate pooled regression parameters. For the other analyses involving variables with lower frequencies of missing values, bivariate and multivariate analyses were conducted on the original dataset.
Bivariate associations of family-controlled trafficking with victim characteristics, case factors, system responses, and case outcomes were assessed with chi-square tests of independence for categorical variables and student’s t test for continuous variables. To examine the research questions, two logistic regression models were conducted to investigate the association separately of multiple (1) case factors (including victim characteristics), and system responses, and (2) case outcomes with the dichotomous variable, family-controlled trafficking (vs. non-relative trafficking). With the exception of two variables (victim’s nationality and cases involving sex trafficking), all the victim characteristic, case factors, and system factors examined in the bivariate tests were included as predictor variables in the binary logistic regression model with the outcome variable, family member perpetrator. The reason these two variables were not included in the logistic regression is they had small variance; almost all victims had a U.S. nationality and almost all cases involved allegations of sex trafficking. For all logistic regression models, the Nagelkerke R2 was used to assess the variability accounted for on the dependent variable by the predictor variables. The overall model significance for the logistic regression models was examined by the collective effect of the independent variable, presented with a β coefficient. Individual predictors were assessed by the Wald coefficient. Predicted probabilities of an event were determined by the odds ratio.
Results
Frequencies of Variables by the Unit of Analysis of Victims
A total of 567 cases involving 698 victims were reported as possible human trafficking to the child agency in the report years 2013–2017. Among the 73 cases involving multiple victims, there were 204 alleged victims, with an average of 2.8 victims per case and a median of 2.0 victims. Among cases involving multiple victims (n = 73), the majority (63.0%) involved 2 victims with an additional 21.9% involving 3 victims, and the remaining 15.1% involving 4 − 10 alleged victims.
Bivariate Associations with Family-Controlled Trafficking
Two variables examined in the bivariate analyses had more than 5% of cases with missing values: drug involvement of victim (n = 79, 13.9%), and charges related to human trafficking (n = 50, 8.8%). The chi-square tests with these two variables were conducted on the multiply imputed dataset. Table 1 presents the results of bivariate associations of victim characteristics and case factors with family member perpetrator vs. non-relative perpetrator. The mean age of victims was significantly lower in cases involving a family member perpetrator. Cases involving family member perpetrators had a higher average number of perpetrators compared to cases with non-relative perpetrators. A significantly higher percentage of cases with family member perpetrators were in rural (nonmetropolitan) communities than cases with non-relative perpetrators. A smaller percentage of cases with family member perpetrators had notes in their file that indicated the victim was using, given, or sold for drugs when compared to cases with non-relative perpetrators. Gender, victim’s original nationality, prior involvement with child welfare, and allegations of sex trafficking (i.e., commercial sex) did not differ significantly by type of perpetrator.
Table 2 presents the results of bivariate associations of system responses and case outcomes with type of perpetrator (i.e., family member perpetrator vs. non-relative perpetrator). First, referral source was significantly associated with the type of perpetrator. Nearly half of cases with non-relative perpetrators were referred by a professional (other than school, mental health, or criminal justice
Note: The following variables had the following number of cases with missing values: age of alleged victim (n = 3), gender of alleged victim (n = 2), number of perpetrators (n = 5), victim was using drugs, given drugs, or sold for drugs (n = 79). Because 13.9% of cases had missing values for the variable, drug-involvement of victim, this chi square test was conducted on the multiply imputed dataset. **p < .01, ***p < .001.
professional) compared to only 24.1% of cases with family member perpetrators. Nearly one-fourth of cases with family member perpetrators were reported to the child welfare agency by an anonymous person compared to only 6.0% of cases with non-relative perpetrators. Compared to cases with family member perpetrators, significantly more cases with non-relative perpetrators were reported to the child welfare agency by law enforcement and the juvenile justice system or court system. Compared to cases with non-relative perpetrators, significantly more cases with family member perpetrators were reported to the child welfare agency by a non-relative community member and a relative. The remaining referral categories did not differ by perpetrator type. Significantly more cases with non relative perpetrators had notes in their records that criminal charges related to human trafficking were filed compared to cases with relative perpetrators. In significantly more cases with family member perpetrators, children were removed from the home because of the reported incident when compared to non-relative perpetrator cases.
Type of perpetrator was significantly associated with both outcome variables (charges of human trafficking were filed and a finding of substantiation or founding). Significantly more cases with non relative perpetrators had notes in their records that criminal charges related to human trafficking were filed compared to cases with relative perpetrators. Significantly more cases with non-relative perpe trators had a case outcome of substantiation or founding when compared to cases with family member perpetrators. Law enforcement involvement and whether an interview was conducted at a child advocacy center were not associated with type of perpetrator.
Multivariate Analysis
A binary logistic regression was performed to ascertain the association of the having a family member as an alleged perpetrator of human trafficking and the following victim characteristics, case factors, and system response factors as predictor variables: time (defined as report year), victims’ age, gender, type of community in which the victim resided (urban vs. rural), prior involvement with the child welfare agency, drug involvement, number of perpetrators, referral by the justice system, involvement of law enforcement in the case, interview was conducted at a Child Advocacy Center, and the child was removed as a result of the incident (see, Table 3). Because two of the included predictor variables had a high percent of missingness (e.g., Referral by the justice system and drug involvement), this logistic regression was conducted on the multiply imputed dataset. The β coefficients were pooled. Naïve pooling was used for the Hosmer-Lemeshow statistic.
The logistic regression model was statistically significant, Χ2 (11) = 185.329, p < .001. The model explained 37.5% (Nagelkerke R2 = .375) of the variance in family-controlled trafficking among the cases reported to the state child welfare agency and correctly classified 76.5% of cases. Five of the 11 predictor variables were significantly associated with an alleged perpetrator being a family member, while controlling for the other variables. Specifically, with each year’s report, the odds of an alleged perpetrator being a family member decreased. Reported cases involving younger victims had greater odds of having an alleged perpetrator being a family member. Alleged victims living in rural counties (OR = 2.988) had greater odds of having a family member perpetrator. The number of alleged perpetrators was significantly, positively associated with having a family member perpetrator. Among the victim characteristics and case factors, gender of the alleged victim and having prior involvement with the child welfare agency were not significantly associated with family-controlled trafficking.
Associations of system responses to reports of human trafficking of children with family controlled trafficking were examined with a logistic regression model (see, Table 4). One of the categories included in the referral source variable (i.e., anonymous) could not be recoded into the dichotomous variable, referral by law enforcement, the court, or the juvenile justice system. Thus, for the dichotomous variable 101 (17.5%) cases had a missing value. This logistic regression was conducted on the multiply imputed dataset. The β coefficients were pooled. Naïve pooling was used for the Hosmer-Lemeshow statistic. The logistic regression model was statistically significant, Χ2 (4) = 13.893, p < .01. The model explained a small amount of the variance, 3.3% (Nagelkerke R2 = .033), in family-controlled trafficking among the cases reported to the state child welfare agency and correctly classified 58.6% of cases. Two of the four predictor variables were significantly associated with an alleged perpetrator being a family member. Specifically, cases referred by law enforcement, the court, or the juvenile justice system had lower odds of an alleged perpetrator being a family member. Second, the alleged victim being removed from the household because of the report/investigation was greater for cases with family member perpetrators. There was no associa tion of law enforcement involvement and having an interview conducted in the child advocacy center and having a family member perpetrator.
A logistic regression model examined multivariate associations of family-controlled trafficking cases, community type, and time (i.e., report year) as predictor variables with the case outcome of substantiation or a finding as the dependent variable (see, Table 5). The logistic regression model was statistically significant, Χ2(3) = 27.723, p < .001. The model explained 6.1% (Nagelkerke R2 = .061) of the variance in family-controlled trafficking among the cases reported to the state child welfare agency and correctly classified 71.3% of cases. One of the three predictor variables was significantly associated with an outcome of substantiation or finding. Specifically, cases involving family member perpetrators
Discussion
Emerging research demonstrates that individuals are more likely to be trafficked within their own communities and sex trafficking networks in particular, are often family based (Denton, 2016; Mancuso, 2014; Sabon et al., 2021). The key findings of this study expound upon the existing literature and serve to increase awareness of the issue of family-controlled child trafficking and inform future directions regarding research, practice, and policy. In regard to the researchers’ first question, “What victim characteristics are associated with family-controlled trafficking cases,” the results indicate that victims of family-controlled trafficking were more likely to have a higher number of perpetrators, live in rural communities, and be younger. The association of family-controlled trafficking with higher numbers of perpetrators is a novel finding not previously explored in the literature, and the role of rurality is still not fully understood as it has only been explored and addressed in one other study (Sprang & Cole, 2018). The finding regarding age as a significant factor associated with family controlled trafficking runs parallel to the existing literature on human trafficking in general (Clawson et al., 2009; Hardy et al., 2013. However, this finding is noteworthy in that it suggests that family members as traffickers may have access to younger children as compared to third-party traffickers. Investigation of research question number two, pertaining to case factors associated with family-controlled trafficking cases, revealed that family-controlled trafficking cases were less likely to involve drugs (e.g., victim was using, given, or sold for drugs) when compared to cases with non relative perpetrators. While this is also a novel finding and has not been found to be the case in previous literature regarding family-controlled trafficking (e.g., Sprang & Cole, 2018, found the opposite to be true), it may point to other risk factors such as economic vulnerability or material need, which have been found to be associated with child sex trafficking in general (Cole & Sprang, 2015). In regard to the third research question regarding system responses associated with family-controlled trafficking cases, results indicate that issues of family-controlled trafficking were found to be more likely reported by anonymous, non-relative community members, and relative reporting parties compared to reporting parties of professionals, law enforcement, courts, and juvenile justice, as reflected in previous literature. More specifically, this finding may reinforce the notion proposed by Twis (2020) that the presence or absence of systems in children’s lives can predict who might exploit them. In addition, results indicate that cases involving family members as perpetrators were less likely to have human trafficking related criminal charges filed and less likely to involve the removal of the child or children. This finding, while concerning from a practice and policy standpoint, is also congruent with the existing child trafficking literature. For example, a recent study found that approximately two-thirds of the family-controlled traffickers were criminally charged, but only approximately one-third of these were charged with a crime associated with human trafficking (Sprang & Cole, 2018). This may indicate a lack of understanding regarding the dynamics and implications of family-controlled trafficking by the systems that respond to and investigate child trafficking (Cole & Sprang, 2015).
Importantly, in regard to the fourth research question pertaining to case outcomes associated with family-controlled trafficking cases, findings revealed that having a family member involved as the perpetrator of trafficking predicted that the case would not be substantiated and/or founded, com pared to cases not involving a family member. While this finding follows the adjacent trend regarding criminal charges mentioned above, it is novel in that no other studies to date have explored or confirmed the predictive relationship between family-controlled trafficking and diminished substantiations and confirmed cases.
Implications
In light of the novel findings of this study, the researchers purport a number of implications for research, practice, and policy in the following section. Before the implications are delineated, it is important to note that some of the research implications presented regarding data will first require administrative changes orchestrated by the government agencies (e.g., public child welfare systems). It is important that government agencies work closely with researchers to align administrative data collection processes with the current and emerging research in order to increase their capacity to evaluate their efforts and to account for and better understand the complexities associated with family controlled trafficking. In addition, when considering the potential for significant policy changes, it is noteworthy to acknowledge that states and governments are still exploring how to best address this issue of child trafficking, never mind the specific issue of family-controlled trafficking nested within the child trafficking field of study. However, in examining the broader issue of child trafficking from a multilevel, multisystem, socio-ecological perspective (Bronfenbrenner, 1994; Ogbu, 1990), it seems that macro-level interventions must consider addressing the large range of circumstances that make minors vulnerable to abuse and neglect, such as poverty, structural violence, and inequality (Duger, 2015; Rafferty, 2016). By the same token, micro-level interventions should include policy changes to better protect individual children via government agencies, including social services, law enforcement, and child protection teams (Rafferty).
Research Implications
Given the rising awareness of issues of family-controlled trafficking, there is a significant gap in the existing literature regarding the subject. To further understand this issue, future research should include more details on the cases of child trafficking, such as safety and risk assessments, record of contact (ROC) notes, and Child and Adolescent Needs and Strengths (CANS) data from child welfare systems. This supplemental data can help to give context in order to better understand the complex ities surrounding family members as perpetrators of child trafficking.
The findings from this study revealed that cases with a family member as the perpetrator compared to a non-relative perpetrator predicted lower odds of the case being confirmed by DCBS or law enforcement. Future research on family-controlled trafficking must address this discrepancy. Possible explanations for the differences in case outcomes based on family-controlled trafficking include the potential for barriers to conducting assessments on families or a lack of expertise among child welfare workers on the dynamics of this issue to effectively identify and intervene in family-controlled trafficking. Other possible explanations exist in the investigation process, including the complexities of receiving a child’s testimony. Instances of the family member perpetrator threatening the child with the possibility of family disruption, being separated from siblings, or the child’s fear of the ramifications for the perpetrator would create murky waters for confirming an allegation of family-controlled trafficking.
The case determination process (e.g., substantiated/founded determination) is unclear and must be examined to better understand, address, and ultimately reduce the problems of family-controlled trafficking. Potential ways forward in researching this process are to randomly select cases that are substantiated and/or founded and cases not substantiated nor founded and interview child welfare workers on the details of the process for confirming or not confirming the allegations. Another potential research avenue includes partnering with law enforcement to review case studies of family controlled trafficking, child welfare workers, and prosecutors regarding the process of confirming allegations.
Practice Implications
Family-controlled trafficking accounts for over 40% of five years of alleged child trafficking cases in Kentucky. The one consistent protective factor against child trafficking and its severe consequences is supportive interpersonal relationships (Landers et al., 2019; O’Brien, 2018). However, in cases of family-controlled trafficking, a parent, relative, or primary caregiver is responsible for the abuse. Thus, children who experience trafficking facilitated by family members are at greater risk for more significant negative outcomes. Therefore, early identification is key.
Tip sheets (see, Appendix A), screening tools and assessments used to identify victims of child trafficking, including family-controlled trafficking, should be informed by current research. These resources for professionals and community members screening for and identifying victims should include the research on the known risk factors such as the four Adverse Childhood Experiences (ACEs): sexual abuse, domestic violence, emotional abuse, and physical neglect (Middleton et al., 2018). These resources should also include awareness of the cluster of factors associated with family
controlled trafficking such as previous involvement with child welfare (Twis, 2020), children of younger ages (Sprang & Cole, 2018), children in rural communities (Sprang & Cole, 2018), and children with multiple perpetrators (Middleton & Edwards, 2020). This cluster of associated factors should also be included in the design and implementation of prevention and early intervention programs.
There is a significant lack of training on the issue of child trafficking and even less training on how to identify and effectively intervene in cases of child trafficking including family members as perpetrators. The findings of this study draw attention to the role that systems such as child welfare, law enforcement, and juvenile justice need to play in the issue of family-controlled trafficking. Specifically, this study as well as previous literature (Twis, 2020) revealed that there is a significantly smaller proportion of professionals in these systems identifying victims of family-controlled trafficking compared to child trafficking victims with a non-relative perpetrator. Thus, findings highlight the importance for systems to receive thorough and regular training regarding the complex dynamics of child trafficking.
To maximize training efforts for identifying and responding to child trafficking among the systems of child welfare, law enforcement, and juvenile justice, the authors recommend that each state institutes a full-time human trafficking investigator position to be housed within the statewide child welfare system (e.g., the Kentucky Department for Community Based Services). In the U.S., child welfare systems are required to respond to cases of child trafficking and lead most of the child trafficking investigations at this time. Thus, hiring a full-time human trafficking investigator in the child welfare system creates the opportunity for a ripple effect on other systems (e.g., law enforcement, juvenile justice). This ripple effect would help build capacity for co-training with other systems and provide much-needed education for child welfare workers in other jurisdictions to better identify, respond to and understand cases of child trafficking. More awareness of and multidisciplinary approaches to child trafficking would create more options for case outcomes, services for victims, and ultimately prevention efforts toward reducing instances of this heinous crime.
Taking a multidisciplinary approach to ending family-controlled trafficking should also include a more expansive range of professionals and community members in addition to the systems of child welfare, law enforcement, and juvenile justice. Victims of family-controlled trafficking are more likely to be younger than victims with a non-relative perpetrator. Professionals and community members who work and interact with children, particularly young children, and their families must be trained and provided with research-informed resources for identifying family-controlled trafficking. These professionals and community members include but are not limited to pediatricians, daycare workers, school personnel, and parent visitors in home visitation programs for any new or expectant parents (e.g., the Kentucky Health Access Nurturing Development Services) are perhaps the most likely community members to identify risk factors and indicators of family-controlled trafficking.
Policy Implications
Important to note in the findings of this study is the greater likelihood of a victim of family-controlled trafficking residing in a rural community, compared to child trafficking victims with a non-relative perpetrator. The lack of resources in rural communities is a potential risk factor or predictor of family controlled trafficking, making it imperative to build capacity in rural communities for specialized training and coordinated investigations among multidisciplinary teams. The authors recommend creating a systematic process for coordinating investigations of child trafficking in rural communities. This process would be made possible by having a regional consultant specializing in child trafficking, including family-controlled trafficking, to be a primary contact for identifying and providing services for victims and potential victims at risk for child trafficking.
Findings from an earlier study (Middleton & Edwards, 2020) showed increased likelihood of child trafficking cases being confirmed if a forensic interview was conducted at a child advocacy center. Thus, the authors recommend the regional consultants be partnered and perhaps housed with regional child advocacy centers. Having this type of team available to respond to child welfare workers in rural communities and address issues of child trafficking and family-controlled trafficking would develop expertise regarding this issue among these regions.
Finally, the authors urge policymakers and lawmakers to hold family member perpetrators accountable for family-controlled trafficking. This study revealed that significantly more cases with non-relative perpetrators (39.6%) had a case outcome of substantiation or founding when compared to cases with family member perpetrators (21.1%). Furthermore, focus group participants in an earlier child trafficking study (Middleton & Edwards, 2020) reported concerns about family members as traffickers being less likely to be charged, or receiving a reduced charge or finding. Labeling family controlled trafficking of minors as child sexual abuse without acknowledging the commercial element may allow perpetrators to be charged with offenses that carry less severe penalties (Smith et al., 2009). Moreover, identification of the commercial aspect of the sexual exploitation can allow law enforce ment to broaden the scope of the investigation to potentially include buyers of commercial sex. Until more buyers of commercial sex are arrested and charged with criminal offenses, the demand forcommercial sex with children will continue unabated. In addition, appropriate charges can help to strengthen crime victim services in general and law enforcement’s victim identification practices at all levels, including state and local anti-trafficking task forces.
Limitations
The data analyzed in this study were collected over a five-year period and focused only on cases of alleged child trafficking reported to the Kentucky Department of Community Based Services (DCBS) through the child abuse hotline. Further details on the data obtained by DCBS and/or law enforce ment, including final case outcomes, were not included in the data provided to the authors. Additional data from investigators’ notes, interviews, and observations could provide more context on the processing of cases, such as the process for substantiating allegations of family-controlled trafficking.
Conclusion
When examining family-controlled trafficking in the literature, the authors discovered a cluster of associated factors including having a higher number of perpetrators, living in rural communities, and being younger. Reporting parties of family-controlled trafficking were more likely to be anonymous, non-relative community members, and relatives compared to reporting parties of child trafficking by a non-relative which were more likely to be professionals, law enforcement personnel, court officials, and juvenile justice professionals. This finding reinforces the notion proposed by Twis (2020) that the presence or absence of systems in children’s lives can predict who might exploit them. Further, important findings in this study draw attention to the likelihood that family-controlled trafficking cases, when compared to cases with non-relative traffickers, would not be substantiated and/or founded.
These findings first highlight the need for more research regarding the dynamics of family controlled trafficking. More specifically, the authors call for future research to hone in on the case outcomes of family-controlled trafficking such as the dynamics that predict family-controlled trafficking cases to be unsubstantiated and unfounded. To build capacity among systems and specifically in rural communities, there is a need for research-informed tip sheets and screening tools for child welfare workers, as well as enhanced training across disciplines for a multidisciplinary approach to ending family-controlled trafficking.
To enhance resources in rural communities, the research highlights the need for partnerships between child advocacy centers and consultants specializing in family-controlled trafficking to be stationed in each region. With the reallocation of funding and restructuring of systems such as child welfare, law enforcement, and juvenile justice, creating multidisciplinary teams with specializations in family-controlled trafficking is a feasible step toward building capacity and much-needed resources in rural communities. Finally, to significantly impact the issue of family-controlled trafficking, anti
trafficking proponents emphasize the need to enforce the penalties for family members as traffickers of children. The accurate labeling of this offense could potentially enhance services for child victims of family-controlled trafficking, identification processes for systems addressing this issue, and ultimately move in the direction of reducing the instance of family-controlled trafficking.
Notes on contributor
Emily E. Edwards, M.Ed., Research Associate, School of Public Health and Information Sciences, University of Louisville; Jennifer Middleton, Ph.D., M.S.W., Associate Professor, Kent School of Social Work, University of Louisville; Jennifer Cole, Ph.D., Associate Professor, Center on Drug & Alcohol Research, University of Kentucky.
Data for this study was collected with funding from a two-year grant from the Kentucky Children’s Justice Act Task Force, in partnership with the Kentucky Department of Community Based Services and the Kentucky Office of the Attorney General.
ORCID
Emily E. Edwards http://orcid.org/0000-0001-8985-2418
References
Adams, W., Owens, C., & Small, K. (2010). Effects of federal legislation on the commercial sexual exploitation of children. US Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Arata, C. M., Langhinrichsen-Rohling, J., Bowers, D., & O’Brien, N. (2007). Differential correlates of multi-type maltreatment among urban youth. Child Abuse & Neglect, 31(4), 393–415. https://doi.org/10.1016/j.chiabu.2006.09. 006
Bronfenbrenner, U. (1994). Ecological models of human development. In M. Gauvain & M. Cole (Eds.), Readings on the Development of Children, 2nd Ed (2nd ed., Vol. 3, pp. 37–43). International Encyclopedia of Education. Elsevier. Bryan, C. (2014). What Judges Need to Know About Human Sex Trafficking: Screening and Assessment and Matching to
Empirically Based Treatment. Presented at the NCJFCJ Annual Conference July 14, 2014, Chicago, IL. Annie E. Casey Foundation. (2019). 2019 KIDS COUNT data book. The Annie E Casey Foundation. https://www.aecf. org/resources/2019-kids-count-data-book
Clawson, H. J., Dutch, N., Solomon, A., & Grace, L. G. (2009). Human trafficking into and within the United States: A review of the literature. U.S. Department of Health and Human Services. https://aspe.hhs.gov/report/human trafficking-andwithin-united-states-review-literature
Cole, J., & Anderson, E. (2013). Sex trafficking of minors in Kentucky. University of Kentucky Center on Drug & Alcohol Research.
Cole, J., & Sprang, G. (2015). Sex trafficking of minors in metropolitan, micropolitan, and rural communities. Child Abuse & Neglect, 40, 113–123. https://doi.org/10.1016/j.chiabu.2014.07.015
Cole, J., & Sprang, G. (2020). Post-implementation of a Safe Harbor law in the US: Review of state administrative data. Child Abuse & Neglect, 101, 104320. https://doi.org/10.1016/j.chiabu.2019.104320
Courtois, C. (2008). Complex trauma, complex reactions: Assessment and treatment. Psychotherapy: Theory, Research, Practice, Training, 41(4), 412–425. https://doi.org/10.1037/0033-3204.41.4.412
Currier, A., & Feehs, K. (2019). 2018 Federal human trafficking report. Human Trafficking Institute. https://www. traffickinginstitute.org/wp-content/uploads/2020/04/2018-Federal-Human-Trafficking-Report-Low-Res.pdf#new_ tab
Denton, E. (2016). Anatomy of trafficking: Human trafficking in the United States 2006-2011. Journal of Human Trafficking, 2(1), 32–62. https://doi.org/10.1080/23322705.2016.1136540
Department of Justice/Office of Justice Programs Report. (2011). Most Suspected Incidents of Human Trafficking Involved Allegations of Prostitution of an Adult or Child. http://ojp.gov/newsroom/pressreleases/2011/BJS11093.htm Donders, A. R. T., Van Der Heijden, G. J., Stijnen, T., & Moons, K. G. (2006). A gentle introduction to imputation of
missing values. Journal of Clinical Epidemiology, 59(10), 1087–1091. https://doi.org/10.1016/j.jclinepi.2006.01.014 “DuBois, D. L., & Felner, J. (2016). Mentoring for youth with backgrounds of involvement in commercial sex activity: National mentoring resource center population review. Office of Justice Programs. https://www.ojp.gov/ncjrs/virtual library/abstracts/mentoring-youth-backgrounds-involvement-commercial-sex-activity
DuBois, D. L., & Felner, J. (2016). Mentoring for youth with backgrounds of involvement in commercial sex activity: National mentoring resource center population review. Final report submitted to National Mentoring Resource Center. Duger, A. (2015). Rights of children vulnerable to sex trafficking. Health and Human Rights, 17(1), 114–123. https://doi. org/10.2307/healhumarigh.17.1.114
Fedina, L., Williamson, C., & Perdue, T. (2016). Risk factors for domestic child sex trafficking in the United States. Journal of Interpersonal Violence, 34(13), 2653–2673. https://doi.org/10.1177/0886260516662306 Feehs, K., & Richmond, J. C. (2018). 2017 Federal human trafficking report. Human Trafficking Institute. https://www. traffickinginstitute.org/wp-content/uploads/2020/04/2017-Federal-Human-Trafficking-Report-WEB-Low-Res.pdf
JOURNAL OF HUMAN TRAFFICKING 17
Franchino-Olsen, H. (2021). Vulnerabilities relevant for commercial sexual exploitation of children/domestic minor sex trafficking: A systematic review of risk factors. Trauma, Violence & Abuse, 22(1), 99–111. https://doi.org/10.1177/ 1524838018821956
Frey, L. M., Middleton, J., Gattis, M. N., & Fulginiti, A. (2018). Suicidal ideation and behavior among youth victims of sex trafficking in Kentuckiana. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 40(4), 240–248. https://doi.org/10.1027/0227-5910/a000557
Freyd, J. J. (2003). What is a betrayal trauma? What is betrayal trauma theory? https://scholarsbank.uoregon.edu/xmlui/ bitstream/handle/1794/65/defineBT.html?sequen
Hall, J. A. (2010). Sex offenders and child sex tourism: The case for passport revocation. Va. J. Soc. Pol’y & L, 18, 153. https://scholarsbank.uoregon.edu/xmlui/bitstream/handle/1794/65/defineBT.html?sequen Hardy, V. L., Compton, K. D., & McPhatter, V. S. (2013). Domestic minor sex trafficking. Affilia, 28(1), 8–18. https://doi. Q38 org/10.1177/0886109912475172
Ijadi-Maghsoodi, R., Todd, E. J., & Bath, E. P. (2014). Commercial sexual exploitation of children and the role of the child psychiatrist. Journal of the American Academy of Child and Adolescent Psychiatry, 53(8), 825–829. https://doi. org/10.1016/j.jaac.2014.05.005
IOM (Institute of Medicine) and NRC (National Research Council). (2013). Confronting commercial sexual exploitation and sex trafficking of minors in the United States. The National Academies Press.
Kennedy, M. A., & Pucci, N. J. (2007). Domestic minor sex trafficking assessment report—Las Vegas, Nevada. Shared Hope International. http://alexiskennedy.org/wp-content/uploads/2014/06/Las-Vegas-SH-Assessment.pdf Landers, M., Johnson, M. H., Armstrong, M. I., McGrath, K., & Dollard, N. (2019). Exploring relationships as mediators of treatment outcomes among commercially sexually exploited youth. Child Abuse & Neglect, 104095. http:// alexiskennedy.org/wp-content/uploads/2014/06/Las-Vegas-SH-Assessment.pdf
Malm, A., & Bichler, G. (2011). Networks of collaborating criminals: Assessing the structural vulnerability of drug markets. Journal of Research in Crime and Delinquency, 48(2), 271–297. https://doi.org/10.1177/0022427810391535 Malm, A., Bichler, G., & Van De Walle, S. (2010). Comparing the ties that bind criminal networks: Is blood thicker than water? Security Journal, 23(1), 52–74. https://doi.org/10.1057/sj.2009.18
Mancuso, M. (2014). Not all madams have a central role: Analysis of a Nigerian sex trafficking network. Trends in Organized Crime, 17(1–2), 66–88. https://doi.org/10.1007/s12117-013-9199-z
Martinez, R. J. (2006). Understanding runaway teens. Journal of Child and Adolescent Psychiatric Nursing, 19(2), 77–88. https://doi.org/10.1111/j.1744-6171.2006.00049
McClain, N. M., & Garrity, S. E. (2011). Sex trafficking and the exploitation of adolescents. Journal of Obstetric, Gynecologic, and Neonatal Nursing, 40(2), 243–252. https://doi.org/10.1111/j.1552-6909.2011.01221 McGloin, J. M. (2005). Policy and intervention considerations of a network analysis of street gangs. Criminology & Public Policy, 4(3), 607–636. https://doi.org/10.1111/j.1745-9133.2005.00306.x
Miccio-Fonseca, L. C. (2017). The anomaly among sexually abusive youth: The juvenile sex trafficker. Journal of Aggression, Maltreatment & Trauma, 26(5), 558–572. https://doi.org/10.1080/10926771.2017.1304476 Middleton, J., & Edwards, E. E. (2020). A five-year analysis of child trafficking in the United States: Exploring case characteristics and outcomes to inform child welfare system response. International Journal of Forensic Research and Criminology, 8(5), 192–203. doi:10.15406/frcij.2021.09.00335.
Middleton, J., Gattis, M., Frey, L., & Roe-Sepowitz, D. (2018). Youth Experiences Survey (YES): Exploring the scope and complexity of sex trafficking in asample of youth experiencing homelessness. Journal of Social Service Research, 44(2), 1–17. https://doi.org/10.1080/01488376.2018.1428924
Middleton, J., & Vavrousek, J. (2016). Human Trafficking Alliance Community Needs Assessment. Human Trafficking Alliance Steering Committee Presentation.
Mitchell, K. J., Finkelhor, D., & Wolak, J. (2010). Conceptualizing juvenile prostitution as child maltreatment: Findings from the National Juvenile Prostitution Study. Child Maltreatment, 15(1), 18–36. https://doi.org/10.1177/ 1077559509349443
Mitchell, K., Jones, L., Finkelhor, D., & Wolak, J. (2014). Trends in unwanted sexual solicitations: Findings from the youth internet safety studies. Crimes Against Children Research Center.
Natarajan, M. (2006). Understanding the structure of a large heroin distribution network: A quantitative analysis of qualitative data. Journal of Quantitative Criminology, 22(2), 171–192. https://doi.org/10.1007/s10940-006-9007-x Norman, R. E., Byambaa, M., De, R., Butchart, A., Scott, J., & Vos, T. (2012). The long-term health consequences of child
physical abuse, emotional abuse, and neglect: A systematic review and meta-analysis. PLoS medicine, 9(11), e1001349. https://doi.org/10.1371/journal.pmed.1001349
O’Brien, J. E. (2018). “Sometimes, somebody just needs somebody–anybody–to care:” The power of interpersonal relationships in the lives of domestic minor sex trafficking survivors. Child Abuse & Neglect, 81, 1–11. https://doi.org/ 10.1016/j.chiabu.2018.04.010
Office of Refugee Resettlement. United States Department of Health and Human Services. (2012). Report to Congress. FY2012. http://www.acf.hhs.gov/sites/default/files/orr/fy_2012_orr_report_to_congress_final_041014.pdf Ogbu, J. (1990). Understanding cultural diversity: Summary comments. Education and Urban Society, 22(4), 425–429. https://doi.org/10.1177/0013124590022004009
18 E. E. EDWARDS ET AL.
Polaris Project (2012). Human trafficking trends: National Human Trafficking Resource Center 2007–2012. http://www. traffickingresourcecenter.org/sites/default/files/Human%20Trafficking%20Trends%20in%20the%20US%2007-2012. pdf
Polaris Project. (2015). Sex trafficking in the U.S.: A closer look at U.S. citizen victims.
Rafferty, Y. (2016). Trauma as an outcome of child trafficking for commercial sexual exploitation: A human rights-based perspective. Psychology & Society, 8(2), 77–94.
Reid, J. A. (2011). An exploratory model of girl’s vulnerability to commercial sexual exploitation in prostitution. Child Maltreatment, 16(2), 146–157. https://doi.org/10.1177/1077559511404700
Reid, J. A. (2012). A girl’s path to prostitution: Linking caregiver adversity to child susceptibility. LFB Scholarly Publishing.
Reid, J. A., Baglivio, M. T., Piquero, A. R., Greenwald, M. A., & Epps, N. (2017). Human trafficking of minors and childhood adversity in Florida. American Journal of Public Health, 107(2), 306–311.
Reid, J. A., Huard, J., & Haskell, R. A. (2015). Family-facilitated juvenile sex trafficking. Journal of Crime and Justice, 38 (3), 361–376. https://doi.org/10.1080/0735648X.2014.967965
Sabon, L., Yang, S., & Zhang, Q. (2021). Social network analysis of a Latino sex trafficking enterprise. Journal of Human Trafficking 17(1), 2332-2705. https://doi.org/10.1080/23322705.2021.1898830
Smith, L., Vardaman, S. H., & Snow, M. (2009). The national report on domestic minor sex trafficking: America’s prostituted children. Shared Hope International.
Sprang, G., & Cole, J. (2018). Familial sex trafficking of minors: Trafficking conditions, clinical presentation, and system involvement. Journal of Family Violence, 33(3), 185–195. https://doi.org/10.1007/s10896-018-9950-y Stroebel, S. S., O’Keefe, S. L., Beard, K. W., Kuo, S. Y., Swindell, S. V., & Kommor, M. J. (2012). Father–daughter incest: Data from an anonymous computerized survey. Journal of Child Sexual Abuse, 21(2), 176–199. https://doi.org/10. 1080/10538712.2012.654007
Twis, M. K. (2020). Predicting different types of victim-trafficker relationships: A multinomial logistic regression analysis. Journal of Human Trafficking, 6(4), 450–466. https://doi.org/10.1080/23322705.2019.1634963 United Nations News Story. (2007). UN and partners launch initiative to end ‘modern slavery’ of human trafficking. http://www.un.org/apps/news/story.asp?NewsID=22009#.VI3ZyGTF8mV
Van der Heijden, G. J., Donders, A. R. T., Stijnen, T., & Moons, K. G. (2006). Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: A clinical example. Journal of Clinical Epidemiology, 59(10), 1102–1109. https://doi.org/10.1016/j.jclinepi.2006.01.015
Verhoeven, M., Van Gestel, B., De Jong, B., & Kleemans, E. (2015). Relationships between suspects and victims of sex trafficking: Exploitation of prostitutes and domestic violence parallels in Dutch trafficking cases. European Journal of Criminal Policy and Research, 21(1), 49–64. https://doi.org/10.1007/s10610-013-9226-2
Victims of Trafficking and Violence Protection Act of 2000 (2000) Pub. (2000) L. No. 106–386, 114 Stat. 1464–1548 W, Arvizu. (2019,February12).Personal Communication.
Zimmerman, C., Hossain, M., Yun, K., Gajdadziev, V., Guzun, N., Tchomarova, M., Ciarrocchi, R. A., Johansson, A., Kefurtova, A., Scodanibbio, S., Motus, M. N., Roche, B., Morison, L., & Watts, C. (2008). The Health of Trafficked Women: A Survey of Women Entering Posttrafficking Services in Europe. American Journal of Public Health, 98(1), 55–59. https://doi.org/10.2105/AJPH.2006.108357
Appendix A. Tip Sheet for Child Welfare Workers
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