PTSD,depression,and migration-related experiences among Syrian refugees living in camp vs urban settings

Abstract

Despite the increased heterogeneity of living conditions of refugees in recent years, there is a lack of robust epidemiological data about the relationship between refugees’ mental health and their living contexts. The current study aims to compare frequencies of pre-migration traumatic events and post-migration difficulties between refugees living in camps and those living in cities; and to identify the prevalence of post-traumatic stress disorder (PTSD), depression, and factors associated with them. A field survey was conducted among 1,470 refugees living in camps and urban settings of Turkey. The survey instruments included a socio-demographic form, the Harvard Trauma Questionnaire, the Post-migration Living Difficulties Scale, and the PTSD and depression modules of the Mini-International Neuropsychiatric Interview. Both PTSD and depression were more common in urban settings than in camps. Both disorders were associated with living context and migration-related experiences. Pre-migration traumas were more frequent among refugees living in cities than in those living in camps, while post-migration difficulties were more common in the refugees living in camps. The living context is potentially a critical determinant of refugee mental health. Camp and urban refugees may have different experiences and needs. In particular, refugees living in some urban settings may be at higher risk for having psychological problems.

Keywords

depression post-traumatic PTSD refugee camp Syrian refugees urban refugee

Introduction

By the end of 2022, the number of forcibly displaced people worldwide had reached 104 million due to persecution, conflict, violence, and human rights violations (UNHCR, 2023). Numbers are dramatically increasing each year and displacement has become a long-term phenomenon rather than a short-term emergency. More refugees than ever before have resettled in urban settings rather than in camps that offer isolated temporary shelters (UNHCR, 2018). This shift has made cities major settlement places for refugees. For example, in Turkey, the largest refugee-hosting country worldwide, there are 3.7 million Syrian refugees. While 2% of them live in camps, 98% live in urban settings. Little is known about the mental health consequences of this contextual difference.

The refugee experience is associated with an elevated risk for psychological difficulties since the migration trajectory exposes refugees to a number of specific mental health risk factors. The migration trajectory consists of premigration, migration, and postmigration resettlement experiences (Kirmayer et al., 2011). Before displacement and during flight, conflict-related traumatic events such as combat situations, torture, deprivation from basic needs, and loss of loved ones (de Jong et al., 2001; Selmo et al., 2021; Steel et al., 2009); and after arriving at a new country, difficulties due to acculturative stress, social isolation, discrimination, legal status, and financial difficulties (Chen et al., 2017; Miller and Rasmussen, 2017; Silove et al., 2017), all may contribute to the development of mental disorders. Due to social, cultural, and contextual factors, each refugee community experiences these stressors to a different degree.

The World Health Organization (WHO) estimates the point prevalence of mental disorders (depression, anxiety, post-traumatic stress disorder (PTSD), bipolar disorder, and schizophrenia) as 22.1% among conflict-affected populations. Estimates ranged from 8.1 to 14.2% for depression, 9.9–23.5% for PTSD, and 16.7–28.3% for anxiety disorders (Charlson et al., 2019). However, studies show substantial variations. A 2009 meta-analysis of the mental health of refugees and other conﬂict-affected populations reported that the prevalence rates varied from 0 to 99% for PTSD and 3 to 85.5% for depression (Steel et al., 2009). The wide variation in prevalence rates may be due to differences in context, methodology of studies, or both (Rodin and van Ommeren et al., 2009). Regarding methodological factors, differences in assessment tools and sampling techniques yielded different prevalence results (Rodin & van Ommeren et al., 2009; Steel et al., 2009). Concerning context, socioeconomic, cultural, environmental factors and living conditions are known to be important determinants for the health of refugees (WHO, 2018).

In this regard, the context of living is likely to be a significant factor since it involves many cultural and environmental variables. For example, one study found that there were differences in rates of mental disorders between internally displaced persons in northern Syria and refugees resettled in Turkey (Tekeli-Yeşil et al., 2018). People who were displaced from the same region but settled in different countries also have different mental health indices (Bogic et al., 2015). For example, refugees resettled in Europe and Africa had higher levels of mental disorders than those resettled in other places (Porter & Haslam, 2005).

Living in camps or urban settings can also result in differences in mental health symptomatology and in exposure to pre- and post-migratory stressors. In a study conducted in Jordan, refugees living in camps reported concerns with housing, security, domestic violence, and sexual violence, whereas refugees living in urban areas stated having experienced unemployment, poverty, and poor access to health care services (Al-Rousan et al., 2018). Another study in sub-Saharan Africa found that refugees living in camps had lower physical and environmental health (Crea et al., 2015). Moreover, some studies showed that living in a camp can be a risk factor for development of mental disorders (Dubow et al., 2004; Porter and Haslam, 2005; Steel et al., 2009).

The difference in mental problems and exposure to the stressors of migration trajectory among refugees living in camps and urban settings is still unclear due to lack of evidence. This study aims to (1) compare the prevalence of depression and PTSD between Syrian refugees living in camps and urban settings, (2) identify differences in exposure to pre- and post-migratory stressors, and (3) identify factors associated with PTSD and depression.

Methods

Participants

In total, 1,470 Syrian refugees participated the study. Our target population consisted of adult Syrian refugees (aged >18 years) who fled Syria after the civil war and were living in either a camp or an urban setting.

Four provinces of Turkey with the highest number of Syrian refugees were selected as research sites in this study. These are the provinces of Istanbul, Sanliurfa, Gaziantep, and Hatay. However, the Directorate General of Migration Management did not allow conducting this study in Hatay due to security concerns. At the time of data collection, there was an ongoing armed conflict and bombings near the Hatay border of Syria. Thereupon, Kahramanmaraş province, which has no security problem as indicated by authorities, was included in the study. Since there were no camps in Istanbul, data were collected only by interviewing urban refugees. In the provinces of Gaziantep, Şanlıurfa, and Kahramanmaraş, data were obtained from both camps and urban settings. Camps without security and access difficulties, as defined by the Provincial Directorates, were included in the study.

The design of this study started in December 2017, and the data collection phase started in June 2018. During this period, there were 3.3 million Syrian refugees in Turkey. Approximately 7% of the refugees were living in camps (N = 227,947) and 93% in urban settings (N = 3,131,968). The total number of camps was 21 (Disaster and Emergency Management Presidency, 2017).

Procedure

Between June and November 2018, we conducted a field survey among Syrian refugees living in Turkey. To select the households to interview, we used a two-stage cluster-sampling technique. Neighborhoods and streets both in camps and cities were considered as clusters. It should be noted that streets are the smallest units of neighborhoods in Turkey. In camps, the settlement maps consisting of neighborhoods were obtained. Camp neighborhoods that were more than half empty were excluded from the selection list. Given population density, all neighborhoods in Gaziantep camp and three randomly selected neighborhoods in Şanlıurfa and Kahramanmaraş camps were included in this study. Data were collected from each street within the selected neighborhoods of the camps. In Gaziantep camp two households, and in Sanliurfa and Kahramanmaraş camps three households, from each street were randomly selected, and only one individual from each household was interviewed. In urban settings, outside of the camps, we identified 10 neighborhoods with the highest population of refugees. Three of them were randomly chosen. Data were collected from all the streets of selected neighborhoods. Five households from each street were randomly selected, and only one individual from each household was interviewed. Syrian interviewers who were experienced with mental health surveys administered the scales. All the interviewers participated in a two-day training and ﬁeld exercise for the application of scales. Researchers supervised them during data collection. The percentage of individuals who rejected participation in study was around 4%.

Questionnaires and measures

Sociodemographic form

This 11-item questionnaire, developed by the authors of this study, included age, sex, marital status, education level, household makeup, working status before and after migration, self-reported economic status, receipt of support after migration, and time spent in Turkey. Alcohol/drug abuse was also included in the survey with the following question: “Do you use alcohol or any other addictive substance, including tobacco products?” The form was translated into Arabic following a forward-back translation process, considered the best practice in measure translation (Beaton et al., 2000).

Harvard Trauma Questionnaire

The Harvard Trauma Questionnaire (HTQ) asks about a variety of traumatic events, as well as the emotional symptoms which are considered to be associated with trauma (Mollica et al., 1992). It has been translated into many languages, including Arabic. We used the Iraqi version of the HTQ (Shoeb et al., 2007). It consists of five parts, the first of which was used in this study. In this part, participants were asked to indicate which of 43 traumatic events they had experienced.

Post-migration living difficulties checklist

A post-migration living difficulties checklist (PMLD) was developed to measure the challenges experienced by asylum seekers after migration (Silove et al., 1997). The 24-item scale includes items regarding immigration issues, family unity, employment and financial-related challenges, access to health care services, experience of isolation, and loneliness. Participants were asked to indicate which of the 24 listed problems they had experienced over the last 12 months. Since an Arabic version of the checklist was not available, it was translated into Arabic using the same procedure as the sociodemographic form.

Mini-International neuropsychiatric interview

The Mini-International neuropsychiatric interview (MINI 5.0.0) is a structured diagnostic interview that explores the main psychiatric diagnoses of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition and the International Classification of Diseases, 10th Revision (Sheehan, 1998) in a standardized manner. We used the depression and PTSD modules of the Arabic-validated version of the MINI 5.0.0 (Kadri et al., 2005).

Data analysis

Numeric variables were reported as mean ± SD and categorical variables as frequencies and percentages. We conducted the Pearson x² test (Pearson, 1900) to examine bivariate differences between categorical variables where the assumption that the expected count less than 5 should not exceed 20% for variables was satisﬁed; if otherwise, we used the Fisher exact x² test (Fisher, 1934). We determined the goodness-of-ﬁt test of numeric variables to a normal distribution by using the Shapiro–Wilk (n ≤ 50) (Shapiro & Wilk, 1965) or Kolmogorov–Smirnov (n > 50) test (Massey, 1951). We used independent samples t-tests if the normality assumption was satisﬁed (Student, 1908); otherwise, we used the Mann–Whitney U test (Mann & Whitney, 1947) for group differences. A new categorization process was followed due to insufﬁcient observations in some of the sociodemographic variables. We grouped self-reported economic status before and after migration into very good or good, average, and very bad or bad. We divided receiving help after migration into a binary, yes or no, variable. We performed Pearson x² (Pearson, 1900) or Mann–Whitney U tests (Mann & Whitney, 1947) and included the group variables that were statistically significant in the logistic regression models as predictors of Depression and PTSD scores. We assessed the model assumption by Hosmer–Lemeshow statistics (Hosmer et al., 1980). We accepted a p-value less than .05 as signiﬁcant. We reported the results as odds ratios and their 95% conﬁdence intervals.

For both dependent variables, we performed binary logistic regression (Cox, 1958). Before that, to avoid ambiguity in data analysis and interpretation, we categorized items of HTQ and PMLD based on literature review and field experience. First, we reviewed the literature and kept variables with high predictive power as distinct variables. Then, we categorized the variables that were studied together in previous studies and that we thought were related to each other based on field experiences. We summarized the number of items that the participants responded ‘yes’ to in each category and made a mean split of the summed-up number to create dichotomized outcome variables. Therefore, mean scores were accepted as cut-off points. For HTQ, we included three new variables: self-experienced traumatic events (mean = 5.9, SD = 3.1, median = 3), witnessing the trauma (mean = 3.1, SD = 2.4, median = 2), and traumas experienced by friends and/or family (mean = 1.9, SD = 1.9, median = 2). Only torture was not placed into any category and was kept as a distinct variable due to its predictive power reported in the literature (de Jong et al., 2001; Steel et al., 2009; Turrini et al., 2017). For PMLD, we have included four new variables: asylum difficulties (mean = 0.5, SD = 0.9, median = 0), difficulties with accessing health care services (mean = 1.1, SD = 1.6, median = 0), difficulties with accessing official aid (mean = 1.5, SD = 0.7, median = 2), and isolation (mean = 2, SD = 1.2, median = 2). Since some studies (Chen et al., 2017; Silove et al., 1997) reported that discrimination and unemployment were strongly associated with mental health issues, they were kept as distinct variables. To investigate the effect of exposure levels of post-migration living difficulties and traumatic events, we added two additional variables called PLMD, n (mean = 10.9, SD = 6.3, median = 10), and traumatic experiences, n (mean = 10.9, SD = 6.3, median = 10), using the same procedure. Using these new variables, we performed binary logistic regression by following four steps for both PTSD and depression. For PTSD, in the ﬁrst step, we entered living area as the independent variable (model 1). In the second step, we included marital status, whom they live with, education level, working status after migration, receipt of economic support after migration, and use of alcohol/drugs in the model in addition to the variables in model 1 (model 2). Model 3 included model 2 covariates and pre-migration traumatic events: self-experienced trauma, witnessing trauma, traumatic events experienced by friends and/or family, torture, and traumatic experiences, n. The ﬁnal model adjusted for post-migration living difficulties: asylum difficulties, isolation, discrimination, unemployment, and PLMD, n in addition to model 3 (model 4). For depression, in the ﬁrst step, we entered living area as the independent variable (model 1). In the second step, we included sex, whom they live with, education level, working status after migration, receipt of economic support after migration, and self-expressed economic status after migration in the model in addition to the variables in model 1 (model 2). Model 3 included model 2 covariates and self-experienced trauma, witnessing trauma, traumatic events experienced by friends and/or family, torture, and traumatic experiences, n. The ﬁnal model adjusted for asylum difficulties, isolation, difficulties with accessing official aid discrimination, and PMLD, n in addition to model 3 (model 4).

We conducted 1,524 interviews, but 54 were excluded by the supervisor after a quality check due to improper application. Thus, surveys with missing data were not included in the analysis.

Ethics

The study was approved by the Human Research Ethics Committee of Istanbul Bilgi University (project number 2018-20016-55). Verbal informed consents were obtained from the participants upon detailed background information about the study.

Results

In this study, 1,470 interviews were analyzed; of them, 770 were from urban settings and the remaining 700 were from the camps. Table 1 shows the characteristics of the study population.

Table 1.

Sociodemographic characteristics of the participants: Camps and urban settings.

Sociodemographics	Camp (N = 700), Mean ± SD or n (%)	Urban setting (N = 770) Mean ± SD or n (%)	Total (N = 1470) Mean ± SD or n (%)	p
Age (n = 1470)	37.15 ± 10.64	34.12 ± 10.38	35.56 ± 10.61	.695
Sex
Male	314 (44.9)	379 (49.2)	693 (47.1)	.094
Female	386 (55.1)	391 (50.8)	777 (52.9)	.094
Marital Status
Married	653 (93.3)	528 (68.6)	1181 (80.3)	<.001
Divorced or widowed	13 (1.9)	49 (6.0)	59 (4.1)
Single	34 (4.9)	196 (25.5)	230 (15.6)
Living with				<.001
Family	683 (97.6)	652 (84.6)	1335 (90.8)
Alone	13 (1.9)	62 (8.1)	75 (5.1)
Other	4 (0.6)	56 (7.3)	60 (4.1)
Education level
İlliterate	161 (23.0)	76 (9.9)	237 (16.1)	<.001
Can read and write	84 (12.0)	60 (7.8)	144 (9.8)
Primary school	189 (27.0)	162 (21.0)	351 (23.9)
Secondary school	88 (12.6)	137 (17.8)	225 (15.3)
High school	119 (17.0)	199 (25.8)	318 (21.6)
University or college	59 (8.4)	136 (17.7)	195 (13.3)
Working status before migration
Unemployed	394 (56.3)	398 (51.7)	792 (53.9)
Employed	101 (14.4)	108 (14.0)	209 (14.2)	.003
Temporary jobs	157 (22.4)	231 (30.0)	388 (26.4)
Farmer	48 (6.9)	33 (4.3)	81 (5.5)
Working status after migration
Unemployed	529 (75.6)	412 (53.5)	941 (64.0)	<.001
Temporary jobs	143 (20.4)	290 (37.7)	433 (29.5)
Employed	28 (4.0)	68 (8.8)	96 (6.5)
Self-expressed economic status after migration
Very good or good	83 (11.9)	188 (24.4)	271 (18.4)	<.001
Average	70 (52.9)	390 (50.6)	760 (51.7)
Very bad or bad	247 (35.3)	192 (24.9)	439 (29.9)
Receipt of economic support after migration
Yes	39.8 (56.9)	375 (48.7)	773 (52.6)	.002
No	302 (43.1)	395 (51.3)	697 (47.4)	.002
Time in Turkey
1 year or less	11 (1.6)	56 (7.3)	67 (4.6)	<.001
2 years	45 (6.4)	137 (17.8)	182 (12.4)
3 years	115 (16.4)	211 (27.4)	326 (22.2)
4 years	194 (27.7)	183 (23.8)	377 (25.6)
5 years or more	335 (47.9)	183 (23.8)	518 (35.2)
Use of alcohol/drugs
Yes	234 (33.4)	334 (43.4)	568 (38.6)	<.001
No	466 (66.6)	436 (56.6)	902 (61.4)

The prevalence of PTSD in total, camps, and urban settings was 13.1%, 9.1%, and 16.6%, respectively. The prevalence of depression in total, camps, and cities was 47.1%, 39.7% and 53.8%, respectively. The differences in the prevalence of PTSD and depression between camps and cities were statistically significant. Both depression and PTSD rates were higher in cities.

Multiple logistic regression analysis of the factors predicting the likelihood of PTSD is presented in Table 2. Living in urban settings was of significance in all models. Sociodemographic variables showed no significant association with PTSD. Although education level was significant in Model 2, its significance disappeared with the introduction of pre-migration variables. In the final model, living area (β = .553, p < .001), self-experienced traumas (β = .665, p < .05), traumas experienced by friends and family (β = .322, p < .001), witnessing trauma (β = .456, p < .001), asylum difficulties (β = .682, p < .05), isolation (β = .501, p < .001), and unemployment (β = .667, p < .05) predicted the likelihood of PTSD.

Table 2.

Multiple logistic regression analysis of the factors predicting the likelihood of PTSD: Camps and urban settings.

	Model 1	Model 2	Model 3	Model 4
Living areaCamp	1	1	1	1
Urban setting	0.505***(0.367–0.695)	0.581***(0.418–0.806)	0.579**(0.412–0.815)	0.553***(0.387–0.789)
Education level No formal education		0.380***(0.225–0.642)	0.743(0.425–1.298)	0.719(0.404–1.280)
Primary or secondary school		0.595*(0.386–0.916)	0.963(0.609–1.524)	0.969(0.604–1.555)
High school		0.784(0.495–1.241)	1.068(0.658–1.733)	1.153(0.702–1.891)
University or college		1	1	1
Self-experienced trauma Low			1	1
High			0.596**(0.406–0.876)	0.665*(0.449–0.984)
Witnessing trauma Low			1	1
High			0.445***(0.313–0.633)	0.456***(0.318–0.654)
Traumatic events experience by friends and/or family Low			1	1
High			0.314***(0.210–0.470)	0.322***(0.221–0.500)
Asylum difficulties Low				1
High				0.682*(0.483–0.963)
Isolation Low				1
High				0.501***(0.359–0.698)
Unemployment Low				1
High				0.667*(0.445–1.000)

Model summary of the final model: Hosmer-Lemeshow test (p = 0.100); Nagelkerke R² = 0.202; classification rate = 86.7%.

*p < .05; ** p < .01; *** p < .001.

Regression analysis of the factors predicting the likelihood of depression is presented in Table 3. Living in urban settings was of significance in all models, although its impact was altered slightly with the introduction of demographic variables in the model and again with the entry of post- and pre-migration variables in the models. Receipt of economic support was significant in model 2 but become insignificant with the introduction of pre-migration variables. In the final model, living area (β = .514, p < .001), sex (β = .619, p < .001), living alone (β = .384, p < .05), education level (β = 1.899, p < .01), self-expressed economic status (β = .673, p < .01), number of traumatic events (β = .649, p < .01), traumas experienced by friends and family (β = .740, p < .05), torture (β = .415, p < .01), isolation (β = .434, p < .001), and discrimination (β = .687, p < .01) predicted the likelihood of depression.

Table 3.

Multiple logistic regression analysis of the factors predicting the likelihood of depression: Camps and urban settings.

	Model 1	Model 2	Model 3	Model 4
Living areaCity	0.566***(0.460–0.697)	0.520***(0.415–0.652)	0.516***(0.410–0.649)	0.514***(0.402–0.659)
Urban setting	1	1	1	1
SexFemale		0.627***(0.503–0.782)	0.551***(0.439–0.693)	0.619***(0.489–0.782)
Male		1	1	1
Live withFamily		1	1	1
Alone		0.420*(0.256–0.827)	0.448*(0.214–0.937)	0.384*(0.179–0.821)
Other		0.493*(0.281–0.866)	0.626(0.347–1.131)	0.664(0.361–1.220)
Education levelNo formal education		0.944(0.646–1.349)	1.325(0.887–1.979)	1.306(0.865–1.972)
Primary or secondary school		1.403(0.992–1.984)	1.850**(1.284–2.664)	1.899**(1.306–2.760)
High school		1.053(0.727–1.525)	1.248(0.851–1.831)	1.337(0.902–1.982)
University or college		1	1	1
Self-expressed economic status after migrationVery good or good		1	1	1
Average		0.579***(0.416–0.806)	0.650*(0.464–0.912)	0.673**(0.519–0.874)
Very bad or bad		0.578**(0.451–0.742)	0.638**(0.494–.0823)	0.690(0.488–0.975)
Receipt of economic support after migrationHigh		1	1	1
Low		0.686**(0.552–0.853)	0.679**(0.544–0.848)	0.799(0.634–1.007)
Traumatic experiences, nLow		1	1	1
High			0.608***(0.468–0.789)	0.649**(0.496–0.848)
Traumatic events experienced by friends and/or familyLow			1	1
High			0.741*(0.572–0.960)	0.740*(0.567–0.966)
TortureLow			1	1
High			0.400**(0.217–0.737)	0.415**(0.221–0.779)
IsolationLow				1
High				0.434***(0.345–0.548)
DiscriminationLow				1
High				0.687**(0.545–0.865)

Model summary of the final model: Hosmer-Lemeshow test (p = 0.342); Nagelkerke R² = 0.180; classification rate = 65.5%.

* p < .05; ** p < .01; *** p < .001.

In terms of migration-related experiences, refugees living in urban settings (M = 11.9 SD = 6.68) reported significantly more pre-migration traumatic events than those living in camps (M = 10.1 SD = 5.75), t(1468) = −5.56, p < .001. Refugees living in camps (M = 10.5 SD = 3.48) experienced significantly more post-migration living difficulties than urban refugees (M = 9.8 SD = 3.74), t(1468) = 3.80, p < .001.

Respondents living in camps experienced the following traumatic events before migration more frequently than refugees living in cities: suffering from ill health without access to medical care, suffering from lack of food or clean water, lack of shelter, murder or violent death of a family member. Urban refugees experienced more combat-related pre-migration traumatic events, such as oppression, property damage, imprisonment, and being exposed to a combat situation, than refugees living in camps (Supplementary Table 1).

Among post-migration variables, difficulties like unemployment, poverty, and difficulty in getting help from aid agencies were more frequently experienced by refugees living in camps than those living in the urban settings, whereas difficulties like loneliness and depression, communication difficulties, and difficulties in the asylum process were reported more frequently by urban refugees (Supplementary Table 2).

Discussion

This study compares mental health symptomatology and exposure to migration-related stressors of refugees living in camps with those living in urban settings. The overall prevalence of PTSD in both groups together was 13.1%. This is consistent with estimations by WHO which indicate PTSD rates ranges from 9.9 to 23.5% in conflict-affected settings (Charlson et al., 2019). The prevalence of depression was 47.1%, which is above WHO estimations stating that depression rates range from 8.1 to 14.2% (Charlson et al., 2019). However, it is consistent with studies that identified depression rates in refugees between 40 and 50% (Al Ibraheem et al., 2017; M’zah et al., 2018; Naja et al., 2016). The prevalence of both depression and PTSD was higher in refugees living in cities, suggesting that living in urban settings is associated with developing common mental health disorders. This contradicts the argument that living in a camp is a risk factor for developing mental disorders (Dubow et al., 2004; Porter and Haslam, 2005; Steel et al., 2009). However, some studies showed that lower quality of life in some camps (de Jong et al., 2001), experiencing security problems (Rasmussen et al., 2010), and living in a detention camp (Fenta et al., 2004) are among the risks for mental health problems. These factors are rarely seen in camps in Turkey. In Turkey, camps not only provide shelter but also educational, health, and social facilities, security, and financial aid. Refugees living in camps also have free access to the same social services as refugees living in urban settings. The Prime Ministry's Disaster and Emergency Management Presidency (AFAD) received a public service award in 2015 from the United Nations due to these services for refugees. These better conditions might be associated with better mental health outcomes.

Regarding sociodemographic variables, consistent with the literature, depression was associated with being female (Acartürk et al., 2018; Cantekin & Gençöz, 2017) and with lower levels of education (Bogic et al., 2012; Craig et al., 2008). Furthermore, living alone and being of low or average self-reported economic status after migration was significantly associated with depression. These findings are also in line with research showing that loneliness (Cantekin & Gençöz, 2017) and low socioeconomic status (Bogic et al., 2012; Craig et al., 2008) are predictive of depression. However, PTSD was not associated with any sociodemographic variable in this study. This contradicts studies which found that sex (Alpak et al., 2015; Cantekin & Gençöz, 2017; Yaseen & Khedir, 2018), age (Georgiadou et al., 2018; Tekeli-Yeşil et al., 2018), marital status (Al-Shagran et al., 2015; Tekeli-Yeşil et al., 2018), and education level (Al-Shagran et al., 2015) are associated with PTSD. On the other hand, meta-analysis and review studies found that the effects of sociodemographic variables disappeared in the analysis with multiple variables (Bogic et al., 2015; Steel et al., 2009). Since PTSD and other mental health issues in refugee populations are complex phenomena, a multitude of factors can potentially influence the results of different studies.

In line with the literature (Cantekin & Gençöz, 2017; Tinghög et al., 2017), high levels of exposure to traumatic events, torture and trauma experienced by friends and families were associated with depression. Traumatic events that were self-experienced, witnessed, or experienced by friends and family were also associated with PTSD. These findings are compatible with other studies conducted with Syrian refugees (Acartürk et al., 2018; Al-Shagran et al., 2015; Tinghög et al., 2017). High levels of exposure to traumatic events did not predict the likelihood of PTSD. Similarly, a study conducted with children who were exposed to the 9/11 attacks showed that a dose-response relationship occurred with participants with a low number of traumatic events but not with those with medium to high cumulative life trauma (Mullett-Hume et al., 2008). This might suggest that when multiple traumatic events are experienced, PTSD might be associated with factors related to the traumatic event or individual differences rather than with numbers or exposure levels.

Isolation predicted both depression and PTSD in our study. This is consistent with research showing that loneliness and social isolation increase the likelihood of mental problems (Bogic et al., 2015; Chen et al., 2017; Silove et al., 1997). Moreover, in line with previous research, depression was associated with discrimination and PTSD with asylum difficulties (Laban et al., 2004; Silove et al., 1997) and unemployment (Tekeli-Yeşil et al., 2018).

The frequency of pre-migration traumatic events was higher in refugees living in urban settings. This might be because refugees who were exposed to many combat situations in the past wanted to be away from the camps that are reminiscent of war. On the other hand, the frequency of post-migration living difficulties was higher in camps. This could be due to the restrictive nature of camp life. Restrictions associated with living in camps could elevate post-migratory stressors by introducing barriers to issues such as employment and social integration.

Refugees living in camps reported traumatic events related to deprivation of basic needs more than refugees living in cities. This might suggest that refugees who were deprived of basic needs such as health services, food, water, and shelter before migration tend to live in camps where all these needs are met. Refugees living in urban settings reported traumatic experiences related to war events more frequently than refugees living in camps. In other words, refugees who had been exposed to combat situations more intensely tended to live in urban settings. This could be because camp life is a concept closely related to refugee and war life. Camps might be perceived as the continuation or a result of war experiences and might contain triggering and reminding factors of previous traumatic experiences. In cities, refugees may be meeting their need for normalization by defining their own boundaries and being involved in communal life. It should be noted that these explanations are inferences based on our results and field experiences since there is not much research on this specific topic to support the arguments.

In sum, this study demonstrated that refugees living in camps and those living in urban settings have different migration-related experiences, and in turn, different mental health needs. Living context is likely an important determinant of the mental health of refugees. Especially, urban refugees are at higher risk of having mental health symptoms.

Limitations and future directions

This study has several limitations. First, the cross-sectional design of this study did not provide insight into the trajectory of disorders studied, and causal relationships between the variables cannot be inferred. Second, we only assessed the prevalence of PTSD and depression. Although these are the most studied disorders in conflict-affected populations, studies reported that conflict-affected people suffer from other common mental health disorders as well (Giacco et al., 2018). Additionally, to assess drug/alcohol abuse we did not use a validated scale, which may cause a bias in the results. Third, to categorize items of HTQ and PMLD we created low/high dichotomized variables based on the mean split. Although this approach potentially helped us to avoid ambiguity in data analyses, it caused loss of meaningful information inherent in continuous variables, which could affect the results. When performing regression analyses with PTSD and depression, we did not include them in each other's models in order to have two distinct models. These scores might be potential confounders since they are highly comorbid with each other. Finally, since refugee mental health is a complex issue affected by many factors, it is not possible to generalize our findings to refugees living in other countries and with different origins. Future research should focus on the trajectory of a broad range of mental disorders in populations affected by conflict and on the mental health needs of urban refugees. Despite these challenges, this study provides valuable insight to understand the context-related determinants of the mental health of refugees and the different needs of refugees in different living areas.

Conclusion

The results of this study have potential implications for mental health policy planning for Syrian and possibly other refugee populations. Given the recent trend of refugee resettlement in urban areas rather than camps, this study draws attention to the issues affecting the growing urban refugee population. To our knowledge, there is no other study comparing refugees living in urban settings and those living in camps in terms of migration-related experiences and mental health consequences. The findings of the current study suggest that living conditions are an important contextual factor affecting refugees’ mental health. Refugees living in camps and in urban settings may have different mental health needs. Therefore, we suggest that situational analysis and needs assessments should consider the living context and experiences of conflict-affected Syrians even when they are resettled in the same country. This can help identify and address the context-specific mental health and psychosocial support services (MHPSS) needs of refugees. Considering the increase in refugee numbers and the high levels of mental health symptomatology in this group, special attention should be paid to urban refugees. To address the high rates of mental disorders among Syrians, community MHPSS services should be developed as part of general health care. Given that Syrian refugees hardly access MHPSS services in Turkey (Fuhr et al., 2020), refugees’ access to these services should be facilitated by awareness-raising programs and appropriate policy planning. The MHPSS infrastructures should be capable of addressing the long-term MHPSS needs of urban refugees rather than just providing the emergency needs of the population. In order to provide context-specific MHPSS services for refugees, local authorities should be involved in services. Both governmental and nongovernmental organizations should focus on the problems of urban refugees and bring them to donors’ attention.

Supplemental Material

sj-docx-1-tps-10.1177_13634615241250216 - Supplemental material for PTSD, depression, and migration-related experiences among Syrian refugees living in camp vs urban settings

Supplemental material, sj-docx-1-tps-10.1177_13634615241250216 for PTSD, depression, and migration-related experiences among Syrian refugees living in camp vs urban settings by Esra Isik, Sahika Gulen Sismanlar, and Sidika Tekeli-Yesil in Transcultural Psychiatry

Footnotes

Acknowledgements

The authors would like to thank to participants and community leaders of the Syrian community in Turkey for their generous contributions to study.

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Esra Isik

Supplemental material

Supplemental material for this article is available online.

Esra Isik, PhD, works as an assistant professor in the Department of Psychology at Ankara Haci Bayram Veli University (AHBVU). She is the director and principal investigator of AHBVU Center for Psychological Research and Application. Dr. Isik has been studying the mental health of refugees, internally displaced persons, and host societies in Turkey for 10 years. Her published works focus on refugee mental health, mental health services provided to displaced persons, and the mental health of health care and psychosocial support providers after emergencies.

Sahika Gulen Sismanlar, MD, PhD, is an associate professor of child and adolescent psychiatry at the department of Child and Adolescent Mental Health at Kocaeli University. She is a founding member and vice president of the Kocaeli University Child Protection Application and Research Center. She also works in the Forensic Psychiatry and Trauma commissions of the Child and Youth Psychiatrists Association of Turkey. Dr. Sismanlar studies in the fields of forensic psychiatry, psychological trauma, and child protection. Her published works focus on child abuse and neglect, childhood traumas, and juvenile delinquency.

Sidika Tekeli-Yeşil, PhD, MPH & EMPH, is an epidemiologist. She is currently working as a guest scientist at the Department of Epidemiology and Public Health at the Swiss Tropical and Public Health Institute (SwissTPH). She has been working in disaster risk management and migration health in academic institutions and in the field for more than 20 years. She is also the director of STY Consulting, in which she has provided consulting, research, and training services to several institutions including the World Health Organization and the Turkish Ministry of Health. Her published works focus on migration health, disaster risk management, risk communication, and epidemiology.

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