Examining factors predicting sexual exploitation among victims of human trafficking

Abstract

The primary aim of this study is to investigate the factors predicting sexual exploitation among victims of human trafficking, specifically examining how traffickers’ means of control, types of sexual services, nature of recruiter relationships and female age groups play a role in this phenomenon. The data analysed spanned from 2002 to 2019 and were sourced from anonymised public data provided by the Counter-Trafficking Data Collaborative (CTDC), a global hub collecting information from counter-trafficking organisations worldwide. Utilising a binary logistic regression approach, the study identified that traffickers employ various means of control, such as debt bondage, taking earnings, threats, sexual abuse, false promises, use of psychoactive substances, exploitation of children, threat of law enforcement and withholding necessities, aligning with Biderman's Theory of Coercion. Additionally, victims experience prostitution, pornography and private sexual services, often recruited by intimate partners and friends. Furthermore, the study revealed that young women aged 30 years and above were less likely to experience sexual exploitation compared to younger girls.

Keywords

human trafficking sexual exploitation traffickers victims

Introduction

The purpose of the present study is to explore how traffickers’ means of control, types of sexual services, nature of recruiter relationships and female age groups predict sexual exploitation among victims of human trafficking. Human trafficking, as defined in Article 3(a) of the United Nations Protocol on Trafficking (2000), involves the recruitment, transportation, transfer, harbouring or receipt of persons through the threat or use of force, coercion, abduction, fraud, deception, abuse of power, or exploitation of a position of vulnerability. It also includes the giving or receiving of payments or benefits to achieve the consent of a person having control over another person, for the purpose of exploitation. Exploitation encompasses, at a minimum, the exploitation of the prostitution of others, or other forms of sexual exploitation, forced labour or services, slavery or practices similar to slavery, servitude or organ removal. Sexual exploitation of victims involves the exchange of commercial sex acts, such as stripping, pornography or prostitution, for something of monetary value through the means of threat or use of force, coercion, abduction, fraud, deception, abuse of power or vulnerability or giving payments or benefits to a person in control of the victim (TVPA, 2000; UN Protocol, 2000). There is no single profile of a trafficking victim, human trafficking victims can be anyone, regardless of race, colour, national origin, disability, religion, age, gender, sexual orientation, gender identity, socioeconomic status, education level or citizenship status (U.S. Department of Justice, 2023).

Most victims of human trafficking exploited by traffickers are often members of marginalised communities and other vulnerable individuals, including children in the child welfare system or those who have been involved in the juvenile justice system; runaway and homeless youth; unaccompanied children; persons without lawful immigration status; Black people and other individuals of colour; American Indians, Alaska Natives, Native Hawaiians, Pacific Islanders and other indigenous peoples of North America; Lesbian, Gay, Bisexual, Transgender, Queer and Intersex (LGBTQI+) individuals; migrant labourers; persons with disabilities; and individuals with substance use disorder (U.S. Department of Justice, 2023). Research on the means of control, types of sexual services, recruiter relationships and female age groups among sexually exploited victims of human trafficking is still limited. This is partly because, given its secrecy and brutality, such exploitation remains challenging to study. Data relating to sex exploitation are often elusive since it is a submerged and illegal phenomenon (Hom and Woods, 2013). Nevertheless, the existing body of research on sexual exploitation focuses on risk factors such as high rates of alcohol or substance use, child protective services (CPS) custody, a history of runaway behaviour, family violence, exposure to child maltreatment and homelessness, affiliation with deviant peers and juvenile justice involvement (Chohaney, 2016; Cole, 2018; Franchino-Olsen, 2021; Godsoe, 2015; Goldberg et al., 2017; Moore et al., 2020).

Some additional research has focused on factors such as ethnic minority status, living in a rural area, lack of educational attainment, having a disability, inadequate family protection and migration (Barnitz, 2001; Butler, 2015; Choi, 2015; Gjermeni et al., 2008; Ocen, 2015; Perkins and Ruiz, 2017; Staiger, 2005; Van de Glind, 2010). Moreover, previous studies have often been exploratory, confined to specific geographical locations and based on small samples, particularly in cases of street prostitution or instances involving minor victims (Baldwin et al., 2015; Doychak and Raghavan, 2018; Kennedy et al., 2007; Moore et al., 2020; Stark, 2007; Twis and Preble, 2020). Guided by the Biderman theory, this paper aims to provide a deeper understanding of the tactics traffickers use to control trafficked victims. Previous studies utilising the Biderman theory have often been exploratory and qualitative in nature (Baldwin et al., 2015; Dando et al., 2016). Additionally, this paper explores the influence of female age groups on sexual exploitation, the types of sex services victims experience and their relationships with recruiters. Utilising a large and recent global dataset from the Counter-Trafficking Data Collaborative (CTDC) database, this study aims to enhance the understanding of factors predicting sexual exploitation and to develop more informed strategies beneficial to victim assistance providers and law enforcement in combating sexual exploitation.

Literature review

Traffickers means of control

Physical abuse is a fundamental method of coercive control employed by sex traffickers, taking various forms such as beatings, forced drug use, starvation and rape (Baldwin et al., 2015; Hom and Woods, 2013; Doychak and Raghavan, 2018). This abuse can lead to direct physical injuries, including broken bones, bruises, contusions, cuts, burns or indirect harm such as chronic headaches, dizziness, insomnia or, in extreme cases, homicide or suicide (Zimmerman et al., 2008). Traffickers utilise physical abuse to establish control and instill fear in victims (Stark, 2007). Incidents that may lead to physical abuse include not meeting quotas set by the trafficker, being suspected of talking to the police, attempting to exit the trade or simply ‘getting out of line’ (Kennedy et al., 2007). Furthermore, traffickers assert and maintain control by fostering chemical dependencies (Dalla et al., 2003). Coerced drug and alcohol use eventually become addictive for women and are also used to compel women to endure longer shifts (Hom and Woods, 2013). Other methods of control involve false promises of love and security (Baldwin et al., 2014; Dando et al., 2016; Kennedy et al., 2007). Many, if not most, trafficking victims fall prey to this practice because they seek a better life or enhanced economic opportunities (Litam 2017; Toney-Butler et al., 2023). Consequently, they become vulnerable to false promises of good jobs and higher wages (Bales, 2007). Traffickers are increasingly employing covert methods, including threatening victims that they may not see their children again, depriving women of basic needs to cultivate dependency, constant monitoring and restricting victims’ movement (Baldwin et al., 2015; Dando et al., 2016; Ioannou and Oostinga, 2015; Matthews, 2015). Traffickers provide victims with gifts, clothing, money or drugs under the guise of freedom, only to later inform them that they have accumulated a large debt. This debt is then used to control them into sexual exploitation to pay off these debts (Kennedy et al., 2007). Additionally, women typically bear the costs of traveling to another country through the mechanism of ‘debt bondage’. Traffickers cover the transportation costs, and women incur the expenses as debt, repaying it from future earnings (Aghatise, 2004; Hodge and Lietz, 2007). Extended work hours, withholding of travel documents, restriction of medical treatment, controlled access to food, water, shelter and sleep, as well as withheld medical care, are standard methods of control within sex trafficking rings (Baldwin et al., 2015; Hopper and Hidalgo, 2006; Morselli and Savoie-Gargiso, 2014; Zimmerman et al., 2003).

Type of sexual services

Previous research has indicated that a significant number of female survivors of human trafficking are trafficked for prostitution, often with little control over the acts they are required to perform (Raymond, 2004; Tsutsumi et al., 2008). Many women entering the sex trade find themselves experiencing street prostitution as a last resort to meet traffickers demands, and once involved, they often feel it is challenging to leave (Kennedy et al., 2007; Nixon et al., 2002). According to a survey of survivors of sex trafficking, 84.3 percent used substances such as alcohol, marijuana, and cocaine during their exploitation (Lederer and Wetzel, 2014).

The use of private sexual services, is an emerging type of sexual service. In this context, women are expected to be on call for 24-hour shifts, pay a high fee per shift, cannot choose how many shifts they do per week and are forced to engage in street prostitution between shifts to meet their financial needs (Kennedy et al., 2007). The Internet has created opportunities for traffickers to subject their victims to pornography (Flowers, 2001; Long, 2004). Young women and girls can be exploited online in areas where online pornography is legalised or tolerated (Hodge and Lietz, 2007; Hughes, 2000; Hughes, 2003).

Recruiter relationship type

Much of the existing literature on the relationships between sex-trafficked victims and their traffickers focuses primarily on minors and relies on anecdotal evidence or lacks theoretical grounding (Marcus et al., 2014; Twis and Shelton, 2018; Twis et al., 2020). The relationships between victims and traffickers can be categorised into friends, romantic partners, family members, strangers and cases where no outside trafficker is involved (Twis et al., 2020). Domestic minor sex trafficking victims may find themselves in multiple types of relationships with their traffickers, or they may initially perceive one type of relationship only to discover later that the circumstances have changed (Twis et al., 2020; Williamson and Cluse-Tolar, 2002).

These intimate or romantic relationships create a duality, serving as avenues for coercion and abuse on the one hand and intimacy and affection on the other (Baldwin et al., 2015; Hom and Woods, 2013; Reid, 2016). In certain countries, social or cultural practices lead families to entrust their children to more affluent friends or relatives who exploit them for sex trafficking. Some parents accept payment for their children, often rationalised as an ‘advance on wages’, driven not only by financial motives but also the hope that their children will escape poverty for a better life and more opportunities (Bales, 2007). Studies have indicated that over 12 percent of prostituted women reported being forced to work on the streets by their mothers, fathers, foster parents or older siblings (Kennedy et al., 2007). Sex-trafficking victims are often romantically involved with their traffickers and may even have children with them. Simultaneously, they endure commercial sex with numerous partners in the context of coercion (Matthews, 2015; Monto, 2004).

Female age groups and sexual exploitation

Researchers face significant challenges in capturing the experiences and needs of trafficked children and young people due to their high vulnerability, coupled with concerns about safety and confidentiality within this group (Cho, 2015). Previous studies indicate that human traffickers recruit, kidnap and abduct young girls aged between 11 and 17 (Dyantyi and Pritz, 2009). Traffickers specifically target this age group because clients often prefer younger girls, believing them to be compliant and docile, and therefore more likely to comply with their sexual demands (Bernat and Zhilina, 2010). However, few studies have exclusively focused on determining which age groups of females are less vulnerable to trafficking, limiting our knowledge of the influence of female age groups on sexual exploitation. Addressing this gap in understanding is crucial for the comprehensive attainment of awareness and sensitisation campaigns targeted at female victims.

Biderman theory and its application to trafficker's means of control

Biderman's theory of coercion, initially formulated to comprehend the suffering of prisoners of war (Biderman, 1957), outlines eight methods of coercion used to elicit compliance from such prisoners. These methods include isolation, monopolisation of perception, induced debility or exhaustion, threats, occasional indulgences, demonstration of omnipotence, degradation and enforcing trivial demands. Applying Biderman's 1957 model to the context of human trafficking, traffickers employ various strategies. Isolation is achieved by restricting victims’ movements, taking control of their earnings and withholding necessities. Monopolisation of perception involves limiting victims’ exposure to and understanding of the outside world, instilling psychological trauma by monopolising their attention. To control victims, traffickers use induced debility and exhaustion techniques, including the use of victims’ children and forced use of psychoactive substances. Exhaustion techniques involve subjecting victims to physical abuse through long hours of work.

Threats are frequently used to control victims, such as false reports to law enforcement, instilling fears of arrest or deportation. Occasional indulgences and false promises are employed by traffickers to counter their abusive behaviour and provide positive motivation for compliance. Degradation is a powerful tactic involving sexual abuse, insults, humiliation and reducing victims through debt bondage, leaving them powerless. Focusing on trivial demands helps traffickers develop compliance habits, a form of psychological abuse that leaves victims uncertain about completing small tasks without error. Previous studies using the Biderman theory have been exploratory and qualitative. Therefore, applying the Biderman theory in quantitative analysis can enhance our understanding of how sex traffickers control and gain victims’ submission. This insight is valuable for researchers, the general public, policymakers and organisations on the front lines of assisting victims of sexual exploitation.

The current study

This study examines the impact of traffickers’ means of control, based on Biderman's theory, on the sexual exploitation of trafficked victims. The variables under consideration include debt bondage, taking earnings, the use of threats, psychological, physical and sexual abuse, false promises, exposure to psychoactive substances, restriction of movement, use of children, the threat of law enforcement, and withholding of necessities. Additionally, the paper aims to explore how types of sexual services, the nature of recruiter relationships and female age groups predict sexual exploitation among victims of human trafficking. The research questions guiding the study are as follows:

How does the trafficker's means of control predict sexual exploitation?

How do the types of sex services experienced by victims predict sexual exploitation?

How does the victim's relationship with their recruiters predict sexual exploitation?

Which age groups of females are more vulnerable to being trafficked?

Methods

Data source

The present study utilises anonymised public data spanning from 2002 to 2019, sourced from the Counter-Trafficking Data Collaborative (CTDC). This collaborative initiative involves several counter-trafficking agencies, including the IOM, Polaris, Recollective (formerly: the Liberty Shared) and the Portuguese Observatory on Trafficking in Human Beings (OTSH). Technological contributions are provided by Microsoft® and Tech against Trafficking. The CTDC initiative is supported by donors such as the US Department of State Bureau of Population, Refugees, and Migration (PRM); the US Department of Labour (DOL) through the International Labour Organization (ILO)'s Research to Action (RTA) project; the Global Fund to End Modern Slavery (GFEMS) under a cooperative agreement with the US Department of State (DOS); the IOM Development Fund; and the Ministry of Foreign Affairs of the Netherlands (BZ). The Counter-Trafficking Data Collaborative (CTDC) has a dataset, known as the global victim of trafficking dataset, which is the largest global repository on victims of human trafficking. This dataset, containing information on 48,801 trafficking victims from over 144 nationalities trafficked to more than 170 destination countries between 2002 and 2019, is maintained through collaboration with contributing agencies and a case management system. To protect individual-level data, a two-stage process is employed: the elimination of personal identifiers and k-anonymisation, a mathematical technique offering an advanced level of protection. The global k-anonymised dataset used in our analysis is publicly accessible to researchers and policymakers through the CTDC website (https://www.ctdatacollaborative.org/dataset/global-k-anonymized-data-and-resources). This dataset encompasses diverse aspects of victims’ trafficking experiences, including means of control such as debt bondage, restriction of financial access, threats, psychological and sexual abuse, false promises, use of psychoactive substances, restriction of movements, use of children, withholding of necessities and the threat of law enforcement. Additionally, the database includes information on the type of sexual services victims endured, their relationship with recruiters, gender and age.

Measures

Dependent variable

The dependent variable in this study is sexual exploitation, indicating whether the victim was exposed to sexual exploitation. This variable was dichotomously measured, with 0 representing ‘No’ and 1 representing ‘Yes’.

Independent variables

The current study aimed to assess the impacts of trafficker's means of control, type of sexual services, recruiter relationship and age group of females on exposure to sexual exploitation. The independent variables within the trafficker's means of control category include debt bondage, taking earnings, use of threats, psychological abuse, physical abuse, sexual abuse, false promises, exposure to psychoactive substances, restriction of movements, use of children, threat of law enforcement and withholding necessities. These variables were dichotomously measured and coded as 0 = No and 1 = Yes. In the type of sexual services category, the independent variable comprises prostitution, pornography and private sexual services. Similarly, these variables were dichotomously measured and coded as 0 = No and 1 = Yes. Under the type of recruiter relationship category, the independent variable includes friends, intimate partner, family and relations. These variables were dichotomously measured and coded as 0 = No and 1 = Yes. The last set of independent variables pertains to age groups of females, measured as a categorical variable with the following codes: 1 = 9–17 years, 2 = 18–20 years, 3 = 21–23 years, 4 = 24–26 years, 5 = 27–29 years, 6 = 30–38 years, 7 = 39–47 years and 8 = 48 + years.

Control variables

The effects of victim's gender was measured as binary variables, where 0 = male and 1 = female were controlled in our analysis.

Analytic strategy

To achieve our primary objective, which involved assessing the impacts of trafficker's means of control, types of sexual services, nature of recruiter relationships and age groups of females on sexual exploitation, as well as testing our research questions, we employed various analyses. Descriptive statistics were utilised to illustrate the distribution of variables among respondents, while logistic regression analysis was conducted to evaluate the effects of independent variables on the outcome variable. To handle missing data, a listwise deletion method was employed, involving the omission of cases with missing data and analysing the remaining data (Allison, 2001).

Furthermore, considering the potential issue of multicollinearity, we examined the variance inflation factor (VIF). Variance Inflation Factor (VIF) can be used in solving multicollinearity in a regression analysis. Multicollinearity is considered problematic if the VIF value exceeds 4.0 or the tolerance falls below 0.2 (Hair et al., 2010). In the current study, the calculated VIFs did not surpass 4.0, and the tolerance was not less than 0.2 (VIF tables available upon request), indicating that multicollinearity was not a significant concern.

Results

The descriptive statistics for the variables used in the current analysis are presented in Table 1. In terms of means of control, 51 percent of the victims were under debt bondage, about 70 percent had their earnings taken away from them, approximately 77 percent were controlled through threats, 80 percent of the victims reported psychological abuse, 74 percent had been physically abused by traffickers and about 57 percent were subjected to sexual abuse. Traffickers controlled 71 percent of the victims by employing false promises, 65 per cent were exposed to psychoactive substances and about 79 percent had restrictions in their movement. Approximately 80 per cent of the victims were controlled by the use of their children, about 39 percent experienced the threat of being reported to law enforcement and 53 percent of victims had their necessities withheld from them by traffickers.

Table 1.

Descriptive statistics of study variables (n = 48801)

Variables	%
Means of control
Debt bondage	51.3
Takes earnings	69.5
Threats	76.9
Psychological abuse	80.0
Physical abuse	74.9
Sexual abuse	56.5
False promises	71.8
Psychoactive substances	65.0
Restricts movement	78.6
Uses of children	79.5
Threat of law enforcement	38.8
Withholds necessities	53.0
Type of sex services
Prostitution	23.8
Pornography	2.5
Private sexual services	0.8
Recruiter relationships
Intimate partner	4.1
Friend	5.2
Family	4.7
Sexual exploitation
No	32.7
Yes	67.3
Victim’s characteristics
Age
9–17 years	17.7
18–20 years	9.1
21–23 years	8.6
24–26 years	7.1
27–29 years	5.4
30–38 years	14.5
39–47 years	5.8
48+ years	3.2
Gender (Female)	72.8

Regarding the type of sex services performed by victims, about 24 percent experienced prostitution, less than 1 percent experienced private sexual services and about 3 percent were recruited into the pornography industry. Concerning the type of relationship victims had with their recruiters, about 5 percent were recruited into sex trafficking by their family relations, 5 percent through their friends and 4 per cent by their intimate partner. Regarding the gender of sexually trafficked victims, about 73 percent were females and 27 percent were males. In terms of age, less than 3 percent were between the ages of 0–8 years, about 18 percent were 9−17 years, 9 percent of the victims were between ages 18–20 years, about 9 percent of the victims were between ages 21–23 years, 7 percent of the victims were 24–26 years, less than 5 percent of the victims were between ages 27–29 years, about 15 percent of victims were 30–38 years and 6 percent of the victims were 39–47 years of age. Less than 3 percent of the victims were above 48 years and about 73 percent were females. Also, 67 percent of the victims experienced sexual exploitation.

To estimate the effects of variables that predict sexual exploitation among victims of human trafficking, we conducted a binary logistic regression. The results of the analysis are presented in Table 2. The model was significant (χ² = 20996.2, p < .001), and the Nagelkerke pseudo-r-square indicated that this model is better than the baseline model. We find that debt bondage significantly predicts sexual exploitation (Wald = 62.6, p < .01). Victims with debt bondage had lower odds of sexual exploitation. The taking of victims’ earnings significantly predicts sexual exploitation (Wald = 14.70, p < .01). Victims whose earnings were taken had lower odds of sexual exploitation. Also, the use of threats significantly predicts sexual exploitation (Wald = 28.72, p < .01). Victims who were threatened had higher odds of sexual exploitation. Sexual abuse significantly predicts sexual exploitation of victims (Wald = 52.54, p < .01). Victims who were sexually abused had higher odds of sexual exploitation.

Table 2.

Binary logistics regression model estimating the effects on sexual exploitation

Covariates	B	S.E	Wald	P	Odds Ratio
Means of control
Debt bondage	−.018	.002	62.614	.001	.982
Takes earnings	−.008	.002	14.704	.001	.992
Threats	.011	.002	28.722	.001	1.011
Psychological abuse	.002	.002	2.128	.145	1.002
Physical abuse	.000	.002	.000	.996	1.000
Sexual abuse	.022	.003	52.547	.001	1.022
False promises	−.022	.002	115.147	.001	.978
Psychoactive substances	.021	.004	35.817	.001	1.022
Restricts movement	−.002	.002	1.052	.305	.998
Uses of children	−.033	.003	133.513	.001	.967
Threat of law enforcement	−.024	.004	42.381	.001	.977
Withholds necessities	−.017	.002	65.579	.001	.983
Type of sex services
Prostitution	−.054	.002	1152.65	.001	.947
Pornography	.081	.006	216.771	.001	1.085
Private sexual services	−.031	.005	34.780	.001	.970
Recruiter relationships
Intimate partner	.906	.208	18.939	.001	2.476
Friend	−1.200	.179	44.981	.001	.301
Family	.290	.191	2.299	.129	1.337
Victim age (9–17 years = RC)			1313.42	.001
18–20 years	2.132	.101	441.266	.001	8.432
21–23 years	2.096	.101	428.454	.001	8.135
24–26 years	1.554	.108	206.581	.001	4.729
27–29 years	1.166	.123	89.367	.001	3.208
30–38 years	−.665	.107	38.651	.001	.514
39–47 years	−1.905	.178	114.798	.001	.149
48 + years	−.992	.335	8.737	.003	.371
Victim gender = Female	3.299	.100	1097.09	.001	27.098
Constant	-6.178	.566	119.290	.001	.002
Model fit
−2LL 8402
X² 20996.2***
R² .830

The model R² is the Nagelkerke for logistic regression models. Using a listwise deletion method, the final sample size used in the analysis was 22,934.

RC = Reference category.

We find that controlling victims by false promises significantly predicts sexual exploitation (Wald = 115.14, p < .01). Victims who experienced false promises had lower odds of sexual exploitation. The use of psychoactive substances significantly predicts sexual exploitation (Wald = 35.8, p < .01). Victims who were exposed to psychoactive substances had higher odds of sexual exploitation. Also, we find that controlling victims by means of their children significantly predicts sexual exploitation (Wald = 133.5, p < .01). Victims who were controlled with the use of their children had lower odds of sexual exploitation. The use of threats of law enforcement significantly predicts sexual exploitation (Wald = 42.38, p < .01). Victims who experienced threats of law enforcement had lower odds of sexual exploitation. Threats of withholding necessities significantly influenced sexual exploitation (Wald = 65.57, p < .01). Victims who were threatened with necessities had lower odds of sexual exploitation.

Also, we find that sex services involving prostitution significantly predicts sexual exploitation (Wald = 1152.6, p < .01). Victims who experienced prostitution had lower odds of being sexually exploited. We also find that sex services involving pornography significantly predicts sexual exploitation (Wald = 216.7, p < .01). Victims who experienced pornography had higher odds of being sexually exploited. Private sexual services significantly predicts sexual exploitation (Wald = 34.78, p < .01). Victims experiencing private sexual services had lower odds of being sexually exploited. In terms of recruiter relationships, we find that an intimate partner relationship with a trafficker significantly predicts sexual exploitation (Wald = 18.93, p < .01). Victims who were in an intimate partner relationship with a trafficker had higher odds of being sexually exploited. Also, we find that a friendship relationship with the trafficker significantly predicts sexual exploitation (Wald = 44.98, p < .01). Victims who were friends with the trafficker had lower odds of sexual exploitation. Additionally, we find that the age groups of females significantly predicts sexual exploitation. Female victims aged 30 and above had lower odds of sexual exploitation.

Discussion

This study sought to explore how traffickers’ means of control, types of sexual services, nature of recruiter relationships and female age groups predict sexual exploitation among victims of human trafficking. The research questions that guided this study were:

How does the trafficker's mean of control predict sexual exploitation?

How do the types of sex services experienced by victims predict sexual exploitation?

How does the victim's relationship with their recruiters predict sexual exploitation?

Which age groups of females are more vulnerable to be trafficked?

The analyses reveal that traffickers use various control tactics to exploit their victims sexually, which is consistent with the Biderman theory of coercion. Specifically, we found that the use of debt bondage by traffickers negatively predicts sexual exploitation of victims. Victims who paid their debts were less likely to be exposed to sexual exploitation. There are justifications to explain this observation; it could be that the victims are advanced in age, and traffickers have maximised economic gain invested in the victim. The victim and the trafficker may be in an intimate relationship where sex has been used to settle the debts between the trafficker and the victim, with the trafficker no longer willing to expose the victim to sexual exploitation (Toney-Butler et al., 2023). The current study's finding is consistent with prior research, which found that monetary debt does not impede exit from conditions of sex trafficking (Agustín, 2005; Andrijasevic, 2003, 2010). The present study also found that the taking of victims’ earnings negatively predicts sexual exploitation of victims. Victims whose earnings were taken were less likely to be exposed to sexual exploitation. A plausible explanation could be that the victim is a new recruit, and traffickers do not want her to keep her earnings for fear of escape.

In addition, we found that the use of threats positively predicts sexual exploitation. Victims who received threats from traffickers were more likely to experience sexual exploitation. A plausible explanation would be that victims are afraid that they could sustain severe injuries or, in extreme cases, lose their lives and those of their children and loved ones should they fail to comply with the trafficker's directives. This result aligns with prior studies (Bales and Soodalter, 2009). The use of sexual abuse positively predicts sexual exploitation. Victims who received sexual abuse from traffickers were more likely to experience sexual exploitation. A plausible explanation is that the victims have lost their sense of self-worth and self-esteem due to sexual trauma and are now being dehumanised and degraded, considering themselves as sex objects for the pleasure of the trafficker and potential clients. This result aligns with prior studies (Ottisova et al., 2016). Consistent with Asefach, 2018, we found that the use of false promises negatively predicts the sexual exploitation of victims. Victims who had false promises made to them by traffickers were less likely to experience sexual exploitation. A possible explanation for this finding is that these false promises of love or a better life are initial tactics employed by the trafficker to woo and lure their victims to a specific location or country to later force or coerce them into prostitution, pornography and domestic servitude.

The use of psychoactive substances is positively associated with exposure to sexual exploitation. Victims who received psychoactive substances from traffickers were more likely to experience sexual exploitation. A plausible explanation is that the victims, having been exposed to psychoactive substances such as opioids and marijuana, suffer from substance use disorder and lack self-consciousness, being exploited by the trafficker much more. Also, it could be that the victims may be addicted to these substances and would be willing to experience more acts of sexual exploitation in reward for these substances from their traffickers. It may be the case that the victims are using these psychoactive substances to cope with the trauma that they are experiencing and also to increase sexual performance during sexual exploitation. This result aligns with prior studies (Fedina et al., 2019; Moore et al., 2020). The present study also found that the use of children by traffickers negatively predicts the sexual exploitation of victims. Victims who had children were less likely to be exposed to sexual exploitation. A plausible explanation would be that these children were conceived for the trafficker following an intimate relationship with the victims; as such, the traffickers may be careful not to expose the victims to sexual exploitation because the trafficker now considers the victim and children as part of his family. In addition, we found that threats of reporting to law enforcement negatively predict sexual exploitation. Victims who received threats of being reported to law enforcement were less likely to experience sexual exploitation. A plausible explanation for this finding is that the victim is fully aware and knowledgeable that such non-coercive threats are merely a bluff by the trafficker and would continue to refuse to submit to the trafficker’s demand to endure sexual exploitation. Also, we found that withholding necessities negatively predicts the sexual exploitation of victims. Victims who had necessities and documents withheld were less likely to experience sexual exploitation. A plausible explanation for this finding is that such non-coercive threats do not perturb the victim and they would continue to refuse to submit to the trafficker's demands to endure sexual exploitation.

Pertaining to the second research question on the type of sex service, we found that prostitution negatively predicts the sexual exploitation of victims. Victims who experience prostitution were less likely to be sexually exploited. A plausible explanation would be that there is a greater possibility of victims coming into contact and being interrogated by law enforcement agencies in street prostitution than in other types of sex services; as such, traffickers would want to avoid having their victims engaging in street prostitution to protect the trafficker's identity and would opt for other forms of enclosed sexual services such as pornography, which is more discreet. We found that pornography is positively associated with exposure to sexual exploitation. Victims who experienced pornography are more likely to be sexually exploited. A plausible explanation is that pornography is a discreet form of sexual service, and traffickers would be much more comfortable subjecting their victims to pornography since it is most often performed indoors at a secluded location and much more difficult for victims to come into contact with law enforcement and anti-trafficking agencies (Humphreys et al., 2019). Also, we found that private sexual services negatively predict sexual exploitation of victims. Victims of private sexual services were less likely to be sexually exploited.

Regarding the third research question on recruiter relationships, we found that the intimate partner relationship made victims more likely to experience sexual exploitation. A plausible explanation is that the intimate partners were initially led to believe they were in a romantic relationship with their trafficker and were forced into highly exploitative situations. In other cases, victims take to the streets to support their intimate partners, who are considered pimps, thus consenting to be sexually exploited. This is consistent with prior research findings (Anderson et al., 2014). In addition to the above observations, we also found that a relationship based on friendship predicts exposure to sexual exploitation. Victims who were friends with traffickers were less likely to be sexually exploited, and this could be justified by the point that the victim is now an accomplice who is aiding the trafficker to recruit new clients through peer networks and is receiving monetary or other forms of rewards such as exclusion from sexual exploitation by the trafficker. The finding is supported by prior literature (Adams et al., 2010; Curtis et al., 2008). However, contrary to prior literature (Kennedy et al., 2007), we found that recruiter relationships based on the family did not predict exposure to sexual exploitation. The fourth research question focused on determining which age groups of females are less vulnerable to be trafficked; we found that females aged 30 years and above were less likely to be sexually exploited. A plausible explanation is that young girls compared to young women are perceived as disease-free and therefore possess the potential to attract more clients than young women (Lutya, 2010). In addition, the increasing number of HIV/AIDS infections has popularised the socio-cultural myth that having sexual intercourse with young girls will cure HIV/AIDS disease (Dyantyi and Pritz, 2009; Gould, 2008).

There are limitations to the study that should be considered when interpreting the findings. Firstly, the secondary data used for the statistical analyses did not contain trafficker's demographic characteristics such as age, sex, race, educational status, religion and gender. These variables may weigh heavily in designing a comprehensive sexual exploitation mitigation and resilience strategy. Secondly, considering the global dimension of the phenomenon of sex exploitation, it might be appropriate to understand better how the culture and norms of the source countries are involved in aiding sex trafficking; these particular variables were not provided in the dataset. Thirdly, we could not capture the victims’ educational and economic status before having contact with traffickers. This is essential, as most sexually exploited victims are from poor countries and may fall victims to traffickers who falsely promise them financial freedom once they leave their country in search of greener pastures (Clawson et al., 2009; Miko, 2000). This raises the need to address the root cause of sexual exploitation—economic disparity between developed and developing countries—if sexual exploitation must be combated and eradicated. Future research should explore this process in more detail. Lastly, it is also important to note that some studies have suggested that race is a significant risk factor in studying human trafficking (Ocen, 2015; Phillips, 2015). Thus, it is essential to factor in the race of the victim and the trafficker at the point of entry into sexual exploitation for a better understanding of the dynamic of the victim-trafficker relationship type.

In conclusion, the current study aimed to explore how traffickers’ means of control, types of sexual services, nature of recruiter relationships and victims’ age group predicts sexual exploitation among victims of sex trafficking. This study also attempted to utilise the Biderman theory in the quantitative analysis to understand better how sex traffickers control and gain the submission of their victims. The overall results of this study generally support the Biderman theory in the sense that traffickers gain control of their victims by isolation, monopolisation of perception, induced debility or exhaustion, threats, occasional indulgences, demonstration of omnipotence, degradation and enforcing trivial demands, which are manifested in the form of debt bondage, taking earnings, threats, sexual abuse, false promise, use of psychoactive substances, restriction of movement, use of children, withholding of necessities and the threat of law enforcement. To effectively regulate prostitution, pornography and private sexual services, the source and destination nations must work together to establish and enforce strict regulatory guidelines in regions where these activities are legalised. This collaboration is crucial to ensure that voluntary sex workers are not forced into providing sexual services due to economic constraints. Additionally, it is essential for source and destination nations to enlighten young girls, who are particularly vulnerable to sex trafficking, about the warning signs in intimate partner relationships that may lead to sexual exploitation.

Footnotes

Declaration of conflicting interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

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

ORCID iD

BE Kooffreh

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