Screening for Human Trafficking among Refugees in Germany: Determining Prevalence and Test Accuracy of a Modified Version of the Adult Human Trafficking Screening Tool

doi:10.21203/rs.3.rs-2948250/v1

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Screening for Human Trafficking among Refugees in Germany: Determining Prevalence and Test Accuracy of a Modified Version of the Adult Human Trafficking Screening Tool

https://doi.org/10.21203/rs.3.rs-2948250/v1

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Background

Human trafficking consists of the exploitation of a person by means of force, intimidation or deceit. Though it occurs all over the world, its true extent is still unknown. Refugees are especially vulnerable to human trafficking due to language barriers and difficult living conditions. Therefore, the purpose of this study was to design a screening tool to identify survivors of human trafficking among refugees in a German state registration and reception centre.

Methods

In a joint project with the Ministry of Justice and Migration Baden-Württemberg and the Regional Administrative Authority of Karlsruhe (‘Regierungspräsidium’), we asked newly arrived refugees at the initial reception centre in Heidelberg about their experiences with human trafficking. We used a combination of the Adult Human Trafficking Screening Tool and one question borrowed from a publication by Mumma et al. to address all forms of exploitation. The results of the screening tool were cross-checked by a short interview afterwards.

Results

In total, 13 of the 176 asylum seekers had experienced trafficking, which corresponded to a prevalence of 7.3%. The questionnaire had a sensitivity of 76.9% and a specificity of 84.0% at a newly selected cut-off of six positive responses. In an exploratory descriptive analysis on subregions, refugees from West Africa had a substantially higher prevalence (33.3%) for human trafficking within our sample, especially women. However, when we excluded this region from our analysis, we found no significant gender difference for the rest of the sample.

Conclusions

The screening tool distinguishes reliably those who had experienced human trafficking from other refugees. The high prevalence of trafficking in most regions, regardless of gender, suggests that more effort is needed to identify and protect all trafficked persons.

Human Trafficking

Modern Slavery

Exploitation

Refugees

Screening Tool

Identification

Human trafficking is one of the most horrific crimes of our time. It is defined as the recruitment, movement or harbouring of persons by deception, the use of threats, coercion or a position of vulnerability for the purpose of exploitation (1). Exploitation includes forced labour, sexual exploitation, slavery or servitude, forced criminal activity as well as the removal of organs. Available data suggests that the majority of trafficked men are forced into labour exploitation, while women are mainly forced into domestic work, sexual exploitation and forced marriage (2, 3). Until now, the media primarily portrays defenceless female survivors that need to be rescued from sex trafficking, oversimplifying the complexity of trafficking situations, neglecting male and LGBTQ victims (4, 5). Human trafficking is a massive human rights violation of global proportions that is largely undetected, and it is still unknown how many people are truly trafficked today (6). For a rough estimate, according to the European Commission, 14,000 trafficking survivors were registered in the European Union between 2017–2018 (7).

Migrants account for a considerably large share of detected victims of human trafficking and are especially vulnerable to promises about jobs, money, and security (8, 2, 6). Because of a lack of knowledge about the local culture and regulations, the distance to relatives and friends, language barriers and socioeconomic hardship, they are more likely to get lured into trafficking (9). Hereby, the West African subregion is the largest non-European region of origin to contribute to trafficking flows into Western and Southern Europe (10, 6). Therefore, a screening process to identify human trafficking among migrants is an important step towards an improved victim identification.

There are various screening tools of different lengths to identify human trafficking. A review by Macy et al. (11) demonstrated that most of these instruments were developed by practice-oriented and non-governmental organizations in the U.S. and were therefore best suited for this particular population. Some were developed for specialized settings such as healthcare providers as they are often the only ones to talk to trafficked persons outside their trafficking situation (12, 13). Recent reviews not only criticized the absence of a reliable gold standard, but also found that only few screening tools had been thoroughly evaluated (14, 11). Two of these tools were the Adult Human Trafficking Screening Tool (AHTST) by Macias Konstantopoulos & Owens (15) and the screening for emergency settings by Mumma et al. (16). The AHTST was designed to identify people currently or at risk of being trafficked. It provides a guideline to recognise the signs and red flags presented by victims of human trafficking in health care and social work based on self-disclosure. The trauma-informed and culturally sensitive screening tool contains eight questions about different trafficking situations. A positive result was defined as answering at least once with “yes” to any screening question. The original version, however, was not validated nor was its sensitivity and specificity published (15). The AHTST is suitable for the application in different domains and has been used in different contexts (17). However, to our knowledge, the AHTST has solely been used in the United States of America thus far. For example, the tool succeeded in detecting three trafficked women out of 145 patients in two clinics in Oklahoma (13).

In a different approach, Mumma et al. (16) conducted a study in order to evaluate the feasibility of a screening instrument in the emergency department. Answering “yes” to any of the screening questions was defined as a positive survey screen. Among 143 participants, 39 were initially screened positive, including ten that were ultimately identified as victims of sex trafficking. All ten “true positive” cases answered one question about abuse positively which, according to the authors, could suffice for extremely quick assessments. The sensitivity of the overall screening tool with 14 questions was 100% [CI 70%-100%], specificity was 78% (CI [70–85%]. However, its focus on sex trafficking limits the overall screening to just one form of trafficking in persons.

The presented study aimed at a) the combination of the two screening tools and its adjustment for a refugee sample in a German state registration and reception centre, b) the assessment sensitivity and specificity of the screening tool and c) determining the prevalence of human trafficking in a German state registration and reception centre.

Study design and ethical considerations

This study is a prospective cross-sectional study that sought to conduct a survey on the topic of human trafficking among refugees in a state registration and reception centre. It intended to assess the prevalence rate as well as sensitivity and specificity of the respective instrument. The study was approved by the local ethics committee (Ethics Committee, Medical Faculty of Heidelberg University, S249/2021; 05.05.2021) and was in line with the Declaration of Helsinki.

Sample Size and Power Calculation

To the best of our knowledge, no systematic study about the prevalence of trafficking among refugees within a registration and reception centre in Germany exists currently. Reports from the International Organization for Migration estimated in 2016 that about 80 percent of all Nigerian women and girls arriving by sea in Italy or other countries of the European Union were likely to be targeted for sexual exploitation (18). In 2017, the IOM reported that 37% of all interviewed migrants who had taken Mediterranean routes to Europe had personal experience indicating human trafficking (10). Therefore, we estimated the prevalence for trafficking survivors among refugees from various nations conservatively to be around 10%. Furthermore, the results of the AHTST and the single question by Mumma et al. (16) indicate that trafficking survivors differ significantly in their responses from non-trafficked persons. We therefore expected our questionnaire to have high sensitivity and followed the recommendations of (19) for the sample size: In their Monte Carlo study, they calculated that the ideal sample size with good expected sensitivity and a prevalence of 10% is at least 120 people.

Participants

Our target group were all refugees in the registration and reception centre who fulfilled our inclusion criteria. Inclusion criteria were an age of 18 or older and the ability to understand one of the following languages: Arabic, German, English, French, Farsi, Georgian, Kurmanji, Hausa, Pashto, Serbian, Somali, Turkish and, due to the high number of refugees fleeing from the war in Ukraine after March 2022, also Russian and Ukrainian. A total of 176 people took part in the study. Within our three gender categories, 35 (19.9%) identified as being female, 140 (79.5%) as being male and one (0.6%) person as being diverse. The average age was 30.9 years (SD = 8.2 years). 47.7% of the participants had children. As can be seen in Table 1, most participants came from West Asia and Central Asia. Accordingly, Arabic, Turkish and Farsi were the most commonly spoken languages and Islam the most common religion.

Table 1

Regions of Origin, Languages and Religion of all Participants (N = 176)
Region of Origin	Percentage
West Asia	38.1
Central Asia	17.6
East Europe	16.5
West Africa	13.6
North Africa	11.4
East Africa	1.1
Bahamas	0.6
Unknown	1.1
Language	Percentage
Arabic	25.0
Turkish	19.3
Farsi	16.5
English	14.2
Georgian	10.2
French	7.4
Russian	2.3
German	2.3
Serbian	1.7
Pashtu	0.6
Ukrainian	0.6
Religion	Percentage
Islam	66.5
Christianity	25.6
Atheism	3.9
Alevis	1.1
Hinduism	0.6
Other	2.3
Note. The allocation of individual countries to regions is found in the supplement. The order is based on the percentages.

---------------------------------------- Table 1about here -------------------------------------------------

Setting

The Patrick Henry Village Heidelberg (PHV) is where asylum-seekers are registered for the first time in the state of Baden-Württemberg. It usually accommodates between 1200 to 2400 newly arrived asylum-seekers. During their stay at PHV, state employees verify their identity, register their personal data and carry out a medical examination for communicable diseases as part of the asylum procedure. After around five weeks, asylum-seekers are redistributed to communal accommodations.

Development of the screening tool

In our study, we used a combination of the eight questions of the AHTST (15) and the single question about abuse which was developed by Mumma et al. (16). The AHTST applies to different forms of human trafficking while the screening questions by Mumma et al. (16) originally aimed at the identification of victims of sex trafficking in the emergency department but was so accurate in the original publication that we included it in our questionnaire (see Appendix A). We considered both valuable instruments for all forms of exploitation that were trauma-informed and culturally sensitive, which we assumed to be especially important for our sample of refugees. For each of the presented items, there were four answer categories: “Yes”, “No”, “Don’t know”, and “I Decline to answer”. Other than in the U.S. population, for which the original version of the AHTST was created, we expected a threshold of one positive answer as too low for our context, as most asylum-seekers experience similar forms of violence outside of a trafficking situation (20). We translated the English version into eleven other languages (Arabic, Farsi, French, German, Georgian, Hausa, Kurmanji, Pashto, Serbian, Somali, Turkish), and when the numbers of Ukrainian refugees increased in March 2022, we also provided a Russian and Ukrainian version of our study.

Data Collection

The study took place during the Covid-19 pandemic in late 2021 until summer 2022. During the first four months of the study, all participants had to remain under quarantine for ten to twelve days due to pandemic requirements. During their fifth to eighth day of isolation, when they were already tested negative but were only allowed to step out a few meters outside, we spoke to the participants in front of their accommodation. From March 2022 onwards, the quarantine for refugees wasn’t obligatory anymore, so they were free to go outside anytime. The screening was restricted by specific precautions, such as wearing a mask or keeping a distance of two metres between participants and two female researchers. The researchers approached one accommodation at a time and asked the participants to meet them outside one by one in order to lower the risk of infections. There, the following data was collected:

Demographic information and screening tool

In this phase, participants used a tablet that the researchers provided. They completed several demographic questions concerning their age, gender, country of origin, religion, and parenthood. Next, participants filled out the Adult Human Trafficking Screening Tool followed by the central question found in Mumma et al. (16), as described earlier.

Verification of human trafficking

Independent from their answers provided in the screening tool, every participant answered five additional questions about indicators for human trafficking. In this short semi-structured interview, we cross-checked whether a participant had experienced trafficking according to the questions below about working hours, imprisonment, control over payment, experiences of violence and debt. The researcher posed the following questions with the support of a multilingual neural machine translation within five to ten minutes.

Have you ever been in a situation where you had to work for long hours every day without any day off?
Have you ever been in a situation where you worked in a house that you were not allowed to leave?
Have you ever worked and someone else was in control of your income?
Have you ever been in a situation where you or someone you worked with was beaten and made feel pain for working slowly or trying to leave?
Have you ever been forced to work because you felt you were bonded by debt?

Participants that described trafficking experiences were invited to present themselves at a psychosocial walk-in clinic (21) or at the local counselling service. If the trafficking survivors gave their consent, the researchers reached out to the local specialised counselling centre for trafficked people, social workers within the state registration and reception centre, and the coordinator for accommodation of asylum-seekers of vulnerable groups.

Data Analysis

All calculations were performed with Microsoft Excel 2019. We first added up how many questions the participants answered with "Yes". Then, for each possible cut-off of one to nine "Yes" answered questions, we calculated how many True Positive, False Positive, True Negative, and False Negative results the questionnaire yielded. With this, we calculated the sensitivity, specificity, positive predictive value, negative predictive value, correct classification rate, and positive likelihood ratio of the questionnaire. The choice of the final cut-off was based on several principles: Since the group of people who did not experience human trafficking was expected to be larger, we aimed at a cut-off that would generate as few false positives as possible. At the same time, the cut-off, if it were to indicate a positive result, should be relevant and clearly indicate human trafficking. We therefore also chose the cut-off with the highest possible relevance and positive likelihood ratio. As described in the introduction, the West African subregion is the non-European region of origin with the highest contribution to trafficking flows into Western and Southern Europe (6). We therefore decided to conduct an additional exploratory analysis comparing West African participants with the rest of our sample. Because only 24 of 176 participants were from the West African region, this analysis resulted in a particularly uneven sample size. Since this uneven sample size did not provide enough power for significance testing, the comparison was descriptive.

Participation Rates

During the survey period, 1426 people lived in the accommodations that were visited by the research assistants, including both adults and their children. 343 of them were asked to participate in the study. Of the 343 people approached, 45 did not meet our inclusion criteria. The most common reason why someone did not meet the inclusion criteria was that the person did not speak any of the fourteen languages which we provided. Of the remaining 298 individuals, 120 refused to participate, for a participation rate of 59.7%. Most people declined to participate without stating reasons. Two participants dropped out of the survey, leaving a total of 176 participants in the study.

Survivors of Human Trafficking

Of the 176 participants in our study, we identified 13 who experienced human trafficking. This corresponds to a proportion of 7.3%. Among these 13 people, six were women and seven were men. In other words, within our sample of 35 women and 140 men, the probability of having experienced trafficking as a woman was 17.1%. As a man, the probability was 5.0%.

Calculations of Cut-Offs

The results of our analysis are displayed in Table 2 and Fig. 1. We decided on a cut-off value of six questions answered with "Yes" for a positive screening result. This decision was made because this cut-off was most in line with our principles. With a sensitivity of 76.7% and a specificity of 84.0%, this cut-off captures most survivors of human trafficking and generates few false positives. It also has the second highest positive likelihood ratio and the second highest relevance. In other words, a positive result with this cut-off strongly indicates human trafficking. In our sample, ten out of 13 trafficked people screen positive when applying a cut-off of six questions answered with "yes".

Table 2

Analysis of possible Cut-Offs for the screening tool.
Cut-Off	Sensitivity	Specificity	PPV	NPV	CCR	PLQ
1	100.0%	20.9%	9.2%	100.0%	26.7%	1.3
2	100.0%	37.4%	11.3%	100.0%	42.0%	1.6
3	92.3%	50.9%	13.0%	98.8%	54.0%	1.9
4	92.3%	60.1%	15.6%	99.0%	62.5%	2.3
5	84.6%	76.7%	22.4%	98.4%	77.3%	3.6
6	76.9%	84.0%	27.8%	97.9%	83.5%	4.8
7	38.5%	91.4%	26.3%	94.9%	87.5%	4.5
8	15.4%	95.1%	20.0%	93.4%	89.2%	3.1
9	7.7%	99.4%	50.0%	93.1%	92.6%	12.5
Note. Cut-Off 6 is highlighted to show that this is the cut-off we have chosen. PPV = positive predictive value, NPV = negative predictive value, CCR = correct classification rate, PLQ = positive Likelihood-Quotient.

--------------------------------------------------- Table 2 ----------------------------------------------------

--------------------------------------------------- Fig. 1 ---------------------------------------------------

Subsample Analysis of West African Participants

The results of our explorative descriptive analysis can be seen in Table 3. The comparison between West African refugees and participants from other regions revealed a difference in the frequency of being trafficked. One in three refugees from West Africa experienced trafficking, compared to only one in thirty refugees from other regions. In other words, refugees from West Africa were ten times more likely to be trafficked than refugees from other regions. In an explorative analysis of gender differences, we found that women from West Africa were 14 times more likely to be trafficked than women from other regions. Men from West Africa were six times more likely to be trafficked than men from other regions. Furthermore, in the sample excluding West Africa, we found no difference between men and women in the prevalence of being trafficked. A post hoc significance test revealed that the difference was not significant, 95%-CI for difference [-0.074, 0.087].

Table 3

Comparison of West African Refugees with the rest of the researched sample
	West African Refugees		Rest of Sample
	N	Percentage	N	Percentage
Total	24	100	152	100
Female	9	37.5	26	17.1
Male	15	62.5	125	82.2
Diverse	0	0.0	1	0.7
With Children	11	45.8	73	48.0
HTS	8	33.3	5	3.3
Female HTS	5	55.6	1	3.8
Male HTS	3	20.0	4	3.2
Note. HTS = Human Trafficking Survivor.

-------------------------------------------------- Table 3 -----------------------------------------------------

The presented modified screening tool, consisting of a combination of the AHTST (15), and the single question by Mumma et al. (16), effectively detected survivors of human trafficking among refugees in a German registration and reception centre. Our newly determined cut-off resulted in good specificity and sensitivity for the refugee sample. The screening result was cross-checked by a short semi-structured interview with all participants and has proven to distinguish survivors of trafficking correctly from non-trafficked persons with a probability of 83.5%. To our knowledge, this study is the first to systematically document the prevalence of human trafficking in a German registration and reception centre. It identified survivors of trafficking among vulnerable subgroups, such as West African refugees, as well as trafficked men, who are rarely the focus of research on trafficking (22). Therefore, the screening tool ensures a quick and easy implementation of the screening for all genders in fourteen languages.

The exploratory findings provide new insight to gender differences among survivors of trafficking, as we could show that male refugees are as vulnerable as women in all subregions but West Africa. Within our sample, women from West African countries had a high probability of being trafficked, which is consistent with former reports (10, 18). Overall, we collected more data from male participants due to the fact that we encountered more men in the state registration and reception centre. We raised the number of positive answers necessary to count as a positive screen up to six, due to the high probability that refugees had experienced similar forms of violence in contexts other than a trafficking situation. The rate of true positive-screens was high, particularly given the assumption that survivors of trafficking could be hindered by fear, shame or distrust (23), and the fact that they were still waiting for a response to their asylum application. So far, asylum-seekers in Germany are not screened for trafficking by a standard procedure.

Our study aimed to establish a standardised screening in a registration and reception centre for asylum-seekers with a high vulnerability to human trafficking. The participants were often curious, seldom reluctant, and those that had experienced trafficking were especially thankful to share their story. The screening tool is easy to assess, quick, and trauma-informed. It could therefore be used in various contexts, for all forms of exploitation and all genders. It therefore serves well as pre-selection to indicate which refugees are most likely to have been trafficked. Nevertheless, human trafficking is a complex crime that varies substantially from case to case. Therefore, it is not possible to base the final decision on whether someone has experienced trafficking on a screening tool alone. Migrants are exposed to extreme violence during their flight, including incarceration, pressure to earn money for a living or to pay smugglers (e.g. survival sex). Others may be sold into forced marriage within their home countries and may not get paid for endless work which also counts as Modern Slavery (24). To call this human trafficking is a matter of interpretation, which is why we recommend conducting a longer conversation after the fact to clarify whether and how human trafficking has occurred.

Limitations

This study has several limitations. First, as for all studies about human trafficking, no gold standard to identify survivors exists. It is possible that trafficked asylum-seekers were overlooked because they had false negative screens, or that they were hindered by language barriers due to the use of the translation machine. The generalisation of our results is limited by the fact that we could not survey all refugees because some did not meet the inclusion criteria of language or were illiterate. The use of interpreters could address this problem and include illiterate people if the resources are available. Third, our exploratory analysis on the West African subgroup was only descriptive due to the uneven sample size. As a result, we did not have enough power for significance testing. Finally, this study focussed on adult survivors of human trafficking and is not intended for use with minors.

Implications for future research

Future studies might focus on the subgroup of refugees from West Africa as, in our sample, trafficking was highly prevalent in this region. In our descriptive analysis, women from West African countries were almost fifteen times more likely to become trafficked than women from other regions. For all other regions, the prevalence for trafficking was almost equally high among men and women, which was highly surprising. The numbers for the entire sample were so heavily skewed by the West African subset that there originally appeared to be a gender gap for the total sample. This is a lesson learned: Even if the overall perception suggests that women are particularly affected by human trafficking, it is always worth taking a closer look. If future studies with larger samples show similar results, this proves that men from other subregions than West Africa are just as vulnerable to human trafficking as other genders.

Conclusion

This paper proposes a new approach to the identification of trafficked people in registration and reception centres for asylum seekers. Applicated on a broad scale, more asylum-seekers could receive support upon their arrival in receiving countries (7). This is the first study to systematically document the prevalence of human trafficking among refugees in Germany with a practice-oriented screening tool. Our research enables a gender-neutral identification of trafficking survivors and proves that asylum-seekers are highly vulnerable to human trafficking.

Ethics Approval

The study was approved by the local ethics committee (Ethics Committee, Medical Faculty of Heidelberg University, S249/2021; 05.05.2021) and is in line with the Declaration of Helsinki.

Consent for Publication: Not applicable.

Availability of Data and Materials

The datasets generated and/or analysed during the current study are available in the Heidelberg Open Research Data (heiDATA) repository, permanent link: https://doi.org/10.11588/data/DUNN8C

Competing Interests

The authors declare that they have no competing interests.

Funding

This work was funded by the Ministry of Justice and Migration Baden-Württemberg as “Screening auf Menschenhandel im Ankunftszentrum des Landes Baden-Württemberg / RE-TRA-C-Study”, DMA-ID 11537.

Authors’ Contributions

ETS, CN and IR contributed to conception and design of the study. ETS carried out the study and organized the database. IR performed the statistical analysis. ETS wrote the first draft of the manuscript. IR wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Acknowledgements: Not applicable.

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No competing interests reported.

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Screening for Human Trafficking among Refugees in Germany: Determining Prevalence and Test Accuracy of a Modified Version of the Adult Human Trafficking Screening Tool

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