Quality of Life and Well-Being of Syrian Refugees: Insights from Spain and Jordan.

Quality of Life and Well-Being of Syrian Refugees: Insights from Spain and Jordan

Abstract

Syrian refugees face numerous challenges, including conflict, displacement, family separation, human rights violations, limited access to basic needs, and exposure to violence and torture. These experiences significantly affect their physical, psychological, social, and environmental quality of life (QoL). The aim of this study was to assess the QoL of Syrian refugees in Spain and Jordan and to examine the association between sociodemographic characteristics, living conditions, and experiences of discrimination with different QoL domains. This study used a cross-sectional correlational design in Syrian refugee centers, homes, and camps across Spain and Jordan. A convenience sample of Syrian refugees with confirmed status in the past ten years was recruited. Demographic data were collected via a demographic form, and the World Health Organization Quality of Life—Brief Questionnaire (WHOQOL-BREF) was used to assess their quality of life. Data analysis included descriptive statistics, Chi-square tests, one-way ANOVA, and independent t-tests. The two hundred participants were predominantly aged 18–29 (43%), female (52.5%), married (51.5%), with secondary school education (46.5%), and unemployed (70%), with low monthly family income (60.5%). While 69% experienced low levels of discrimination, 33% were satisfied with their health, and 47.5% rated their QoL as neutral. Refugees in Spain reported higher QoL across physical, psychological, social, and environmental domains compared to those in Jordan (p < 0.05). The QoL was related to socio-demographic factors: higher among married participants (p = 0.044), urban residents (p < 0.001), and recent immigrants (<5 years, p < 0.001), but lower among those with low income (p = 0.011). Gender differences showed that males had better physical (p = 0.001) and psychological (p = 0.032) QoL than females. Lower discrimination levels and employment were associated with higher QoL across multiple domains. This study highlights the lasting association of the Syrian conflict on refugees’ QoL, emphasizing the need for holistic healthcare that addresses physical, psychological, social, and environmental challenges both before and after displacement. Findings call for comprehensive support systems, including early mental health interventions, anti-discrimination efforts, and community inclusion programs, to enhance refugees’ resilience and integration. The study identifies specific subgroups at greater risk of lower QoL—including women, older adults, those with low income, the unemployed, camp residents, and those experiencing discrimination—providing actionable insights for policymakers to target resources and interventions effectively. Tailored rehabilitation and psychological care are essential for empowering refugees to rebuild their lives and fostering social cohesion in host communities.

Keywords: quality of life, physical quality of life, psychological quality of life, social quality of life, environmental quality of life, Syrian refugees, Spain, Jordan, host countries

1. Introduction

Refugees endure persecution, conflict, displacement, family separation, human rights violations, and limited access to essential needs such as food, water, and shelter (Abu-Awwad et al., 2020; Klingberg et al., 2020). Many are also subjected to physical violence, sexual abuse, and torture. The displacement of Syrians remains one of the world’s largest and most protracted refugee situations. According to the United Nations High Commissioner for Refugees (UNHCR) Syria Regional Refugee Response, more than 4.7 million Syrian refugees were registered across the main countries and regions of asylum, including 1.79 million registered by UNHCR in Egypt, Iraq, Jordan, and Lebanon, 2.87 million registered by the Government of Türkiye, and more than 43,000 registered in North Africa (UNHCR, 2025).

Studies show that refugees generally experience poor quality of life (QoL), which correlates with the severity of mental health issues (Leiler et al., 2019). Moreover, war-associated events can negatively affect refugees and persist for years, destructively influencing their QoL even after hostile acts have ceased (Akinyemi et al., 2012; Matanov et al., 2013). Jordan has been one of the main countries of refuge for Syrians since the beginning of the Syrian conflict and has hosted a large Syrian refugee population for more than a decade. Syrian refugees in Jordan live both inside and outside formal refugee camps, with the majority residing in host communities (Obi, 2021). The Jordanian response has been implemented through collaboration between national authorities, UNHCR, and humanitarian and development organizations, with strategies addressing access to basic services, protection, livelihoods, self-reliance, and social resilience (UNHCR, 2025). This context is particularly relevant to QoL because socioeconomic vulnerability, employment opportunities, housing conditions, access to healthcare, and reliance on humanitarian assistance may shape refugees’ physical, psychological, social, and environmental well-being (Stillman et al., 2022). In Jordan, for example, a study found that 87% of Syrian refugees living outside camps earned less than 300 JD monthly, 63.6% had low educational levels, and nearly half lived in small, overcrowded households. Despite receiving humanitarian aid, they reported poor QoL across physical, psychological, environmental, and social domains (Alwedyan, 2022). Refugees living in camps in Jordan reported lower QoL than those outside, although camps provide a safety net for those unable to leave (Obi, 2021).

In Germany, a study of 114 Syrian refugees showed that older age was linked to lower QoL, especially in psychological and physical health, with refugees in housing having better mental health than those in camps. Long-term refugees also reported better psychological outcomes than recent arrivals (Al Masri et al., 2021). Similarly, in Sweden, depression and anxiety affected 61.9% of Syrian refugees, with younger age, male gender, social support, and cohabitation being linked to better health-related QoL (Gottvall et al., 2020).

Despite the growing body of research on Syrian refugee QoL in individual host countries, no study to date has directly compared the QoL of Syrian refugees residing in a neighboring middle-income country (Jordan) with those in a European high-income country (Spain). This comparison provides a unique opportunity to examine how refugee quality of life may vary across two markedly different host-country contexts, characterized by distinct economic conditions, social welfare systems, migration policies, and integration opportunities. Such a comparison is critical because the host-country context—including asylum policies, economic opportunities, social acceptance, and living conditions—may shape refugee QoL in distinct ways (Iglesias-Martínez & Estrada, 2018; Bris & Bendito, 2017).

To move beyond a purely descriptive approach, this study adopts an integrated stress-ecological perspective. According to Miller and Rasmussen’s Ecological Model of Refugee Adjustment, QoL is associated not only with prior war-related trauma but also with ongoing post-displacement challenges (including discrimination, social isolation, and material scarcity), as well as the coping strategies and resources available to individuals (Miller & Rasmussen, 2017). This model differentiates between risk factors that negatively affect QoL (such as low income, unemployment, and extended camp stays) and protective factors that help mitigate these difficulties (such as employment, family support, and stable housing).

Guided by this framework, the present study addresses the following research question: To what degree are sociodemographic characteristics, living conditions, and perceived discrimination associated with QoL among Syrian refugees, and how do these patterns differ between Spain and Jordan? We propose the following hypotheses: (1) Due to variations in economic prospects and reception systems, refugees in Spain will report higher QoL across all four WHOQOL-BREF domains than those in Jordan. (2) In both countries, resilience factors (including male gender, marriage, urban residence, full-time employment, higher income, shorter time since immigration, and low perceived discrimination) will be associated with higher QoL. (3) In contrast, risk factors (including low income, unemployment, camp residence, longer immigration duration, and perceived discrimination) will be associated with lower QoL.

Accordingly, the present study has two primary aims. First, we describe and compare the physical, psychological, social, and environmental QoL of Syrian refugees in Jordan and Spain using the WHOQOL-BREF. Second, we examine the associations between sociodemographic characteristics, living conditions, employment status, income, time since immigration, and perceived discrimination with each QoL domain, while interpreting these factors through a risk-and-resilience lens. By addressing these aims, this study seeks to inform tailored interventions and policies that address the specific needs of Syrian refugees in different host country settings.

2. Materials and Methods

2.1. Study Design and Sampling

This study employed a cross-sectional correlational design to assess and compare QoL among Syrian refugees in Jordan and Spain. This design was chosen to gather valuable data to inform the planning and allocation of mental health services and ultimately enhance refugees’ QoL. Syrian nationals with confirmed refugee status within the past ten years were recruited through multiple methods, including invitations at participating sites, social media posts, and referrals from other refugees (snowball sampling). The final sample comprised 200 participants, with 100 respondents recruited in each country (Jordan and Spain). Recruitment followed a consecutive sampling approach and continued until the target sample size was reached. This sample size was determined to be sufficient based on statistical power calculations and comparable studies in refugee mental health research. It allows for robust comparative analyses between the two countries while remaining feasible given the challenges of accessing refugee populations. Although larger samples could provide additional granularity, 200 participants represent a balance between statistical reliability and practical constraints.

2.2. Data Collection

Participants were recruited from various refugee camps, centers, residences, communities, and villages in Jordan and Spain. Data collection took place between February 2023 and February 2024. Each participant spent approximately 45 min completing the self-reported questionnaires in a single session.

All study materials were provided in Arabic using validated Arabic-language versions of the instruments. Participants completed the questionnaires independently, and no interpreter support or additional translation assistance was required during data collection. No missing values were found in the dataset. All 200 participants completed all items of the demographic form and all 26 items of the WHOQOL-BREF. Completeness was ensured through real-time verification by research assistants during data collection.

2.3. Study Tools

2.3.1. Demographic Characteristics

A structured demographic form was developed based on prior refugee quality of life literature and input from local refugee service organizations. The form collected information on nationality, gender, age, marital status, educational level, living arrangement, employment status, monthly family income, years since immigration, and perceived discrimination.

Nationality and refugee status were verified through official Syrian documentation, with eligibility requiring confirmed refugee status within the past ten years. Gender was recorded as male or female. Age was recorded in years and subsequently categorized into five groups: 18–29, 30–39, 40–49, 50–59, and 60 years or older. Marital status options included married, single, widowed, and divorced. Educational level was assessed using eight categories: illiterate, elementary, secondary, diploma, bachelor’s, master’s, and doctoral.

Living arrangement was assessed using an item adapted from UNHCR living condition classifications, with response options including big cities, large towns, smaller villages or rural areas, low social support (defined as a single-person household with no local network), and camps. Employment status was categorized as not employed, part-time employment (fewer than 35 h per week), full-time employment (35 or more hours per week), or retired. Monthly family income was self-rated as low, middle, or high relative to each country’s cost of living and refugee assistance levels. This subjective approach was chosen because absolute income comparisons between Jordan and Spain are not meaningful given the different economies and support systems. Years since immigration was categorized as 10 years, 9–5 years, or less than 5 years.

Perceived discrimination was measured using three self-developed single-item questions based on qualitative work with Syrian refugees and guidance from local non-governmental organizations. The first item asked, “In the past 12 months, how often have you felt discriminated against because of your refugee status or nationality?”, with response options of never, rarely, sometimes, often, or always. Responses were coded as low (never or rarely), medium (sometimes), or high (often or always). The second item asked, “In what areas have you experienced discrimination? (Select all that apply)”, with options including employment, housing, healthcare, education, public services, and others; this item was used for descriptive purposes only. The third item asked, “How much has discrimination affected your daily life and well-being?”, with responses ranging from not at all to extremely, and was also used for descriptive purposes only. These single-item measures were chosen for pragmatic reasons: to minimize participant burden, as total survey time was capped at 45 min including the WHOQOL-BREF, and to align with partner organization requests for a rapid, actionable screening tool. The primary item measuring frequency of discrimination was used in statistical analyses as a three-level categorical variable. Full wording and justification are provided here to ensure transparency.

2.3.2. World Health Organization Quality of Life—Brief Questionnaire (WHOQOL-BREF)

The WHOQOL-BREF is one of the best-known tools developed for cross-cultural comparisons of QoL and is available in more than 40 languages, including Arabic (World Health Organization Quality of Life Group, 1994). The WHOQOL-BREF contains 26 items that cover four different domains of QoL, (1) physical QoL, which consists of seven items; (2) psychological QoL, which consists of six items; (3) social QoL, which consists of three items; and (4) environmental QoL, which consists of eight items, so that the total scores for the questionnaire range from (0–130) and (0–100) for each dimension separately, as the minimum score is zero and the maximum score is 100. The WHOQoL-BREF uses a 5-point Likert scale from 1 to 5 for each item, and it contains two main items that ask about the general QoL and are not calculated in the QoL rate, which are items No. 1 and 2, and three reversed items, No. 3, 4, and 26 (The WHOQOL Group, 1995, 1998). The study by Skevington et al. (2004) showed that the WHOQoL-BREF is valid and reliable. This scale was applied to the participants and scored by the researcher using the Arabic version (Ohaeri & Awadalla, 2009).

For the purpose of the analyses, overall quality of life was operationalized as a categorical variable using a cut-off score of 50 on the 0–100 transformed total scale. Participants with a total WHOQOL-BREF score of 50 or above were classified as having ‘High QoL,’ while those with a total score below 50 were classified as having ‘Low QoL.’ This cut-off was selected because a score of 50 represents the midpoint of the 0–100 scale and has been used in previous refugee and immigrant health research as a threshold for distinguishing poorer from better quality of life (insert references if available). The categorical operationalization was used for the descriptive comparison to facilitate interpretation of the distribution of sociodemographic characteristics across lower and higher overall QoL groups.

2.4. Ethical Considerations

Ethical approval for the study was granted by the Research Ethics Committee of the University of Salamanca (protocol code 958—26 May 2023). Participation was entirely voluntary, with participants free to withdraw at any point. After receiving a thorough explanation of the study, participants signed a consent form detailing the study’s purpose, potential risks, and researcher information. Personal data remained confidential, and participants were identified by ID numbers. While the study did not pose health risks or involve any treatment, some questions could have caused negative feelings or emotional discomfort. To mitigate this, psychological support was made available, and all participant concerns were fully addressed.

2.5. Data Analysis

Statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS) version 25.0. Categorical variables, including demographics and QoL, were described using frequencies and valid percentages. These were expressed as numbers and percentages. The WHOQOL-BREF domain scores were used to descriptively characterize the multidimensional QoL profile of participants in each country. Domain-specific scores were not prespecified as separate hypothesis tests in the analysis plan and were therefore not subjected to additional post hoc inferential comparisons. Categorical variables were compared between the Spanish and Jordanian groups using the chi-square test, whereas continuous variables were compared using the independent-samples t-test. The normality of the data was assessed through histograms and the Shapiro–Wilk test, and confirmed by the Kolmogorov–Smirnov test. For group comparisons of continuous variables, independent t-tests and one-way ANOVA were applied, as the data followed a normal distribution. A p-value of less than 0.05 was considered statistically significant (α = 0.05). For one-way ANOVA with statistically significant results (p < 0.05), post hoc comparisons were performed using Fisher’s Least Significant Difference (LSD) test to identify specific group differences. Where overall ANOVA was significant, but no pairwise LSD comparisons reached statistical significance, this is explicitly noted in the results.

Two operationalisations of quality of life were used in this study. First, for the descriptive comparison, overall QoL was treated as a categorical variable (Low vs. High) using a cut-off of 50 on the 0–100 transformed total scale. This categorization was used solely to compare the distribution of sociodemographic and relevant characteristics between participants with lower versus higher overall QoL and to facilitate interpretability of group differences. Second, for all subsequent analyses (the four WHOQOL-BREF domain scores (physical, psychological, social, and environmental) were analyzed as continuous variables using independent-samples t-tests and one-way ANOVA. This approach was chosen because continuous domain scores preserve the full variability of the data, provide greater statistical power, and avoid the loss of information associated with dichotomization. The categorical operationalization was therefore limited to the descriptive analysis, while the continuous operationalization was used for all inferential analyses examining associations between sociodemographic factors and QoL domains.

3. Results

Table 1 provides an overview of the socio-demographic and relevant characteristics of the participants, with 100 residing in Jordan and 100 in Spain. Of the total sample, 43% were aged 18–29 years. About half of the participants were married (51.5%), female (52.5%), and had a secondary school education (46.5%). Most participants resided in urban areas or nearby municipalities (60%), were unemployed (70%), and had a low monthly family income (60.5%). Additionally, 69% reported low levels of discrimination, while 36.5% had immigrated to host countries 10 years ago, 33% were satisfied with their health, and 47.5% rated their QoL as neutral (neither poor nor good).

Table 1The sociodemographic and relevant characteristics of the participants.

Variables Jordan (N = 100) Spain (N = 100) p-Value Total(N = 200)

n % n % n %

Age

  18–29 50 58.1 36 41.9 0.260 86 43

  30–39 28 48.3 30 51.7 58 29

  40–49 16 40 24 60 40 20

  50–59 4 33.3 8 66.7 12 6

  ≥60 2 50 2 50 4 2

Gender

  Male 57 60 38 40 0.007 95 47.5

  Female 43 41 62 59 105 52.5

Marital Status

  Married 36 35 67 65 0.000 103 51.5

  Single 55 69.6 24 30.4 79 39.5

  Widow 5 62.5 3 37.5 8 4

  Divorced 4 40 6 60 10 5

Living Arrangement

  Big cities 35 29.2 85 70.8 0.000 120 60

  Large towns 10 50 10 50 20 10

  Smaller villages and rural 15 78.9 4 21.1 19 9.5

  Low social support 0 0 1 100 1 0.5

  Camps 40 100 0 0 40 20

Educational Level

  Illiterate 2 66.7 1 33.3 0.653 3 1.5

  Elementary 17 40.5 25 59.5 42 21

  Secondary 45 48.4 48 51.6 93 46.5

  Diploma 13 56.5 10 43.5 23 11.5

  Bachelor’s 18 56.3 14 43.8 32 16

  Master’s 3 75 1 25 4 2

  Doctoral 2 66.7 1 33.3 3 1.5

Employment Status

  Not employed 63 45 77 55 0.013 140 70

  Part-time employment 26 74.3 9 25.7 35 17.5

  Full-time employment 9 40.9 13 59.1 22 11

  Retired 2 66.7 1 33.3 3 1.5

Discrimination

  Low 69 50 69 50 0.750 138 69

  Medium 26 48.1 28 51.9 54 27

  High 5 62.5 3 37.5 8 4

Years of Immigration

  10 years 65 89 8 11 0.000 73 36.5

  9–5 years 31 44.3 39 55.7 70 35

  Less than 5 4 7 53 93 57 28.5

Monthly Family Income

  Low income 63 52.1 58 47.9 0.121 121 60.5

  Middle income 37 49.3 38 50.7 75 37.5

  High income 0 0 4 100 4 2

Quality of Life Rate

  Very poor 10 50 10 50 0.024 20 10

  Poor 20 66.7 10 33.3 30 15

  Neither poor nor good 52 54.7 43 45.3 95 47.5

  Good 16 34.8 30 65.2 46 23

  Very good 2 22.2 7 77.8 9 4.5

The Level of Satisfaction with Your Health

  Very dissatisfied 8 44.4 10 55.6 0.002 18 9

  Fairly dissatisfied 17 54.8 14 45.2 31 15.5

  Neither dissatisfied nor satisfied 21 70 9 30 30 15

  Satisfied 38 57.6 28 42.4 66 33

  Very satisfied 16 29.1 39 70 55 27.5

Statistical comparisons between Jordan and Spain for categorical variables were conducted using chi-square tests (Table 1). Independent t-tests were used to compare continuous QoL domain scores between two groups (e.g., gender, country of residence), while one-way ANOVA with post hoc LSD tests was used for comparisons involving three or more groups (e.g., age, income, years of immigration). All statistically significant findings (p < 0.05) are indicated in the tables.

Values are presented as mean ± SD for continuous variables and n (%) for categorical variables. Between-group comparisons were performed using the independent-samples t-test for continuous variables and the chi-square test for categorical variables.

In Jordan, most participants were male (60%), single (69.6%), most had immigrated 10 years ago (89%), and 57.6% were satisfied with their health. Notably, all participants living in refugee camps were based in Jordan. In contrast, in Spain, most participants were female (59%), married (67%), and residing in large cities (70.8%). Most participants who had immigrated less than five years ago were in Spain (93%), and 70% of those highly satisfied with their health were from Spain.

3.1. Comparison of QoL Between Spain and Jordan

A total of 200 Syrian adults aged 18 and above participated in the study, completing the questionnaires. Figure 1 presents the mean WHOQOL-BREF scores across the four QoL domains for participants from Spain and Jordan. Overall, participants from Spain showed higher mean QoL scores than participants from Jordan across the assessed domains. These differences were complemented by the categorical distribution of QoL presented in Table 2. Statistically significant differences in the distribution of QoL categories were observed between the two countries for physical QoL (p < 0.001), psychological QoL (p < 0.001), social QoL (p = 0.023), and environmental QoL (p < 0.001).

Table 2Distribution of WHOQOL-BREF quality-of-life categories among Syrian refugees in Jordan and Spain.

Variables Jordan (N = 100) Spain (N = 100) p-Value Total(N = 200)

n % n % n %

Quality of life *

Physical Quality of Life

  Very poor 4 50 4 50 0.000 8 4

  Poor 19 59.4 13 40.6 32 16

  Average 41 77.4 12 22.6 53 26.5

  Good 28 42.4 38 57.6 66 33

  Excellent 8 19.5 33 80.5 41 20.5

Psychological Quality of life

  Very poor 6 46.2 7 53.8 0.000 13 6.5

  Poor 18 54.5 15 45.5 33 16.5

  Average 52 63.4 30 36.6 82 41

  Good 21 46.7 24 53.3 45 22.5

  Excellent 3 11.1 24 88.9 27 13.5

Social Quality of Life

  Very poor 12 63.2 7 36.8 0.023 19 9.5

  Poor 19 55.9 15 44.1 34 17

  Average 41 58.6 29 41.4 70 35

  Good 21 42 29 58 50 25

  Excellent 7 25.9 20 74.1 27 13.5

Environmental Quality of Life

  Very poor 16 88.9 2 11.1 0.000 18 9

  Poor 37 78.7 10 21.3 47 23.5

  Average 40 54.8 33 45.2 73 36.5

  Good 6 18.2 27 81.8 33 16.5

  Excellent 1 3.4 28 96.6 29 14.5

* World Health Organization Quality of Life—Brief Questionnaire (WHOQOL-BREF).

For physical QoL, participants from Jordan were more frequently classified in the very poor, poor, and average categories, whereas participants from Spain were more frequently classified in the good and excellent categories. For example, 57.6% of participants classified as having good physical QoL and 80.5% of those classified as having excellent physical QoL were from Spain. A similar pattern was observed for psychological QoL, with 88.9% of participants classified as having excellent psychological QoL being from Spain, compared with 11.1% from Jordan. For environmental QoL, the difference was particularly pronounced, with 88.9% of participants classified as having very poor environmental QoL and 78.7% of those classified as having poor environmental QoL being from Jordan, whereas 96.6% of those classified as having excellent environmental QoL were from Spain. The distribution of social QoL categories also differed significantly between countries, although the magnitude of the difference was smaller than for the other domains.

Table 2 represents the QoL among adult Syrian refugees overall and by residency. Overall, over half of the participants reported between average (26.5%) and good (33%) physical QoL, between average (41%) and good (22.5%) psychological QoL, between average (35%) and good (25%) social QoL, and between poor (23.5%) and average (36.5%) environmental QoL. In Jordan, scores were lower than in Spain in physical QoL (average (77.4%) vs. good (57.6%) to excellent (80.5%), p = 0.000), psychological QoL (average (63.4%) vs. average (36.6%), good (53.3%) to excellent (88.9%), p = 0.000), social QoL (average (58.6%) vs. average (41.4%) to good (58%), p = 0.023), and environmental QoL (poor (78.7%) to average (54.8%) vs. average (45.2%), p = 0.000).

These domain-level differences are presented descriptively to characterize the multidimensional QoL profiles of the two groups.

3.2. Association Between Resilience Factors (Employment, Urban Living, Marriage, Recent Immigration) and QoL

Table 3 shows the QoL according to the sociodemographic and relevant characteristics among adult Syrian refugees overall and by residency. Overall, married participants showed higher QoL levels than unmarried participants (p = 0.044). Higher QoL was also observed among participants living in large cities (p < 0.001) and among those who had immigrated within the previous five years (p < 0.001). Lower QoL was observed among participants reporting low family income (p = 0.011). In Jordan, QoL was low among those who had low monthly family income levels (68.3%, p = 0.007). In Spain, QoL was high among individuals living in big cities (87.1%, p = 0.001).

Table 3Quality of life according to the sociodemographic and relevant characteristics of the participants based on their country of residence.

Variable Jordan(N = 100) p-Value Spain(N = 100) p-Value Total(N = 200) p-Value

Low QoL High QoL Low QoL High QoL Low QoL High QoL

n % n % n % n % n % n %

Gender

  Male 31 54.4 26 45.6 0.399 5 13.2 33 86.8 0.244 36 18 59 29.5 0.867

  Female 27 62.8 16 37.2 14 22.6 48 77.4 41 20.5 64 32

Marital State

  Married 22 61.1 14 38.9 0.160 11 16.4 56 83.6 0.210 33 16.5 70 35 0.044

  Single 28 50.9 27 49.1 4 16.7 20 83.3 32 16 47 23.5

  Widow 4 80 1 20 1 33.3 2 66.7 5 2.5 3 1.5

  Divorced 4 100 0 0 3 50 3 50 7 3.5 3 1.5

Living Arrangement

  Big cities 19 54.3 16 45.7 0.211 11 12.9 74 87.1 0.001 30 15 90 45 0.000

  Large towns 4 40 6 60 4 40 6 60 8 4 12 6

  Small village 12 80 3 20 3 75 1 25 15 7.5 4 2

  Low social 0 0 0 0 1 100 0 0 1 0.5 0 0

  Camps 23 57.5 17 42.5 0 0 0 0 23 11.5 17 8.5

Employment Status

  Not employed 41 65.1 22 34.9 0.090 15 19.5 62 80.5 0.937 56 28 84 42 0.165

  Part-time 14 53.8 12 46.2 2 22.2 7 77.8 16 8 19 9.5

  Full-time 3 33.3 6 66.7 2 15.4 11 84.6 5 2.5 17 8.5

  Retired 0 0 2 100 0 0 1 100 0 0 3 1.5

Discrimination

  Low 39 56.5 30 43.5 0.903 11 15.9 58 84.1 0.248 50 25 88 44 0.574

  Medium 16 61.5 10 38.5 8 28.6 20 71.4 24 12 30 15

  High 3 60 2 40 0 0 3 100 3 1.5 5 2.5

Years of Immigration

  10 years 38 58.5 27 41.5 0.946 2 25 6 75 0.825 40 20 33 16.5 0.000

  9–5 years 18 58.1 13 41.9 8 20.5 31 79.5 26 13 44 22

  Less than 5 2 50 2 50
9 17 44 83
11 5.5 46 23

Monthly Family Income

  Low 43 68.3 20 31.7 0.007 13 22.4 45 77.6 0.442 56 28 65 32.5 0.011

  Middle 15 40.5 22 59.5
6 15.8 32 84.2
21 10.5 54 27

  High 0 0 0 0
0 0 4 100
0 0 4 2

Note: Low QoL = total WHOQOL-BREF score < 50 (0–100 transformed scale). High QoL = total WHOQOL-BREF score ≥ 50. The cut-off of 50 represents the midpoint of the scale and was used solely for the descriptive comparison presented in this table. All subsequent analyses.

3.3. Association Between Risk Factors (Low Income, Unemployment, Camp Residence, Discrimination) and QoL

Table 4 compares the differences between the participants’ sociodemographic and relevant characteristics based on their QoL, regardless of their country of residence. An independent-samples t-test was conducted to compare the psychological QoL between male and female genders. There was a significant difference in the scores for males (M = 56.80, SD = 19.975) and females (M = 50.44, SD = 21.472); t(198) = 2.163, p = 0.032. These results suggest that Syrian adult male refugees experience higher levels of psychological QoL compared to their female counterparts.

Table 4The differences between the participants’ sociodemographic and relevant characteristics based on their quality of life.

Variable Total

Physical Psychological Social Environmental

µ SD p µ SD p µ SD p µ SD p

Age (Y) 18–29 62.17 19.967 0.112 56.37 19.448 0.281 52.77 23.386 0.059 49.01 22.507 0.489

30–39 60.22 18.909 53.16 18.635 59.59 23.225 53.12 19.339

40–49 52.13 23.258 47.43 26.782 45.30 27.047 48.35 25.380

50–59 61.08 19.491 53.17 20.511 57.75 26.677 57.58 22.637

≥60 67.50 5.745 56.50 15.242 62.50 14.434 59.50 8.266

Gender Male 61.82 19.875 0.151 56.80 19.975 0.032 52.51 23.161 0.498 50.95 21.392 0.926

Female 57.67 20.744 50.44 21.472 54.87 25.744 50.66 22.787

Marital State Married 59.09 21.727 0.169 51.86 22.032 0.200 56.53 25.272 0.155 52.80 23.157 0.519

Single 62.37 18.901 57.03 17.565 52.65 23.410 48.59 20.374

Widow 48.50 10.928 46.13 23.216 41.38 23.784 53.25 19.833

Divorced 52.70 20.548 47.60 29.964 43.60 22.677 45.60 25.992

Living Arrangement Big cities 63.92 20.166 0.000 57.59 20.435 0.000 57.12 23.766 0.007 58.02 19.964 0.000

towns 56.55 19.088 55.15 22.312 55.60 23.175 56.75 20.191

village 45.89 16.872 37.21 17.303 40.21 21.395 39.16 18.476

Low social 13.00
13.00
0.00
25.00

Camps 56.05 18.701 48.95 18.508 50.48 25.689 32.33 17.432

Educational Level Illiterate 31.67 10.970 0.094 37.67 6.506 0.435 29.00 3.464 0.334 23.00 20.224 0.233

Elementary 61.10 22.270 50.24 21.159 52.19 22.523 51.71 22.918

Secondary 61.74 19.506 55.90 20.491 54.83 24.748 51.30 21.787

Diploma 55.04 19.841 54.48 19.904 49.70 21.726 47.22 24.125

Bachelors 55.72 20.504 49.94 24.158 54.56 29.818 50.97 20.958

Masters 72.00 10.392 64.00 17.068 72.00 3.464 68.50 14.434

Doctoral 62.67 18.502 54.33 7.506 64.67 13.051 52.00 3.464

Employment Status None 59.21 21.624 0.259 51.70 21.597 0.056 53.42 25.249 0.629 50.09 22.044 0.037

Part-time 56.31 17.197 52.91 17.001 51.43 23.621 45.66 19.909

Full time 66.95 16.888 64.55 20.722 57.73 22.442 61.82 23.730

Retired 65.00 3.464 60.67 15.631 66.67 14.434 62.67 6.506

Discrimination Low 60.29 21.802 0.189 56.01 22.005 0.035 53.88 25.666 0.272 52.71 23.571 0.175

Medium 56.50 16.539 47.46 16.449 51.52 21.744 46.94 16.068

High 69.63 15.766 50.00 23.483 66.50 19.828 43.75 28.080

Years of Immigration 10 years 52.82 17.190 0.000 50.08 19.258 0.151 46.67 22.584 0.008 40.08 18.634 0.000

9–5 years 60.03 19.473 53.90 19.732 57.50 23.971 51.50 22.451

<5 years 67.89 22.367 57.25 23.995 58.19 25.873 63.65 18.619

Monthly Family Income Low 57.13 21.793 0.040 51.50 21.084 0.018 51.41 25.466 0.068 46.17 21.453 0.000

Middle 62.77 17.355 55.21 19.945 56.29 22.614 56.61 20.763

High 76.75 16.256 80.00 19.782 76.50 15.801 81.50 18.230

A one-way ANOVA revealed that there was a statistically significant difference in environmental QoL scores between the employment status groups (F(3, 196) = 2.875, p = 0.037). An LSD test for multiple comparisons found that the mean value of environmental QoL was different between not employed and full-time employment (p = 0.020, 95% CI = [−21.57, −1.88]), and between part-time and full-time employment (p = 0.007, 95% CI = [−27.84, −4.48]). Also, a one-way ANOVA revealed that there was a statistically significant difference in psychological QoL scores between the discrimination groups (F(2, 197) = 3.418, p = 0.035). An LSD test for multiple comparisons found that the mean value of psychological QoL was different between low and medium discrimination (p = 0.011, 95% CI = [1.99, 15.10]).

In addition, there was a statistically significant difference in physical QoL scores between the years of immigration groups (F(2, 197) = 9.514, p = 0.000). An LSD test for multiple comparisons found that the mean value of physical QoL was different between 10 years and less than 5 years of immigration (p = 0.000, 95% CI = [−21.89, −8.25]). Also, a one-way ANOVA revealed that there was a statistically significant difference in social QoL scores between the years of immigration groups (F(2, 197) = 4.989, p = 0.008). An LSD test for multiple comparisons found that the mean value of social QoL was different between 10 years and less than 5 years of immigration (p = 0.007, 95% CI = [−19.90, −3.14]). Moreover, a one-way ANOVA revealed that there was a statistically significant difference in environmental QoL scores between the years of immigration groups (F(2, 197) = 22.178, p = 0.000). An LSD test for multiple comparisons found that the mean value of environmental QoL was significantly different between 10 years and less than 5 years of immigration (p = 0.000, 95% CI = [−30.56, −16.58]).

In this line, the one-way ANOVA revealed that there was a statistically significant difference in physical QoL scores between the monthly family income groups (F(2, 197) = 3.282, p = 0.040). Also, a one-way ANOVA revealed that there was a statistically significant difference in psychological QoL scores between the monthly family income groups (F(2, 197) = 4.124, p = 0.018). An LSD test for multiple comparisons found that the mean value of psychological QoL was different between low and high monthly family income (p = 0.007, 95% CI = [−49.19, −7.81]). Also, a one-way ANOVA revealed that there was a statistically significant difference in environmental QoL scores between the monthly family income groups (F(2, 197) = 9.941, p = 0.000). An LSD test for multiple comparisons found that the mean value of environmental QoL was significantly different between low and high monthly family income (p = 0.001, 95% CI = [−56.52, −14.13]).

3.4. Country-Specific Patterns of QoL-Associated Factors

Table 5 compares the differences in participants’ sociodemographic and relevant characteristics based on their QoL, categorized by their country of residence.

Table 5The differences in participants’ sociodemographic and relevant characteristics based on their quality of life, categorized by their country of residence.

Variable Jordan Spain

Physical Psychological Social Environmental Physical Psychological Social Environmental

µ SD p µ SD p µ SD p µ SD p µ SD p µ SD p µ SD p µ SD p

Age (Y) 18–29 54.26 16.011 0.016 51.66 16.289 0.047 48.90 23.347 0.110 37.12 15.706 0.090 73.17 19.888 0.191 62.92 21.710 0.636 58.14 22.672 0.176 65.53 20.058 0.805

30–39 55.79 17.366 49.18 15.137 50.89 20.154 42.50 16.745 64.37 19.627 56.87 20.969 67.70 23.259 63.03 16.232

40–49 40.13 15.353 37.13 19.252 36.75 23.382 32.13 14.366 60.13 24.424 54.29 29.181 51.00 28.269 59.17 25.542

50–59 56.25 10.210 53.25 16.317 51.50 15.801 40.75 19.568 63.50 23.071 53.13 23.388 60.88 31.270 66.00 19.957

≥60 66.00 4.243 53.50 13.435 75.00 0.000 59.50 4.950 69.00 8.485 59.50 21.920 50.00 0.000 59.50 13.435

Gender Male 52.81 14.66 0.964 50.96 16.60 0.134 50.68 22.94 0.196 40.65 15.68 0.114 75.34 19.11 0.001 65.55 21.57 0.013 55.24 23.53 0.203 66.39 19.55 0.213

Female 52.65 19.43 45.79 17.15 44.77 21.88 35.47 16.62 61.15 21.06 53.66 23.62 61.87 26.05 61.19 20.49

Marital State Married 49.00 18.476 0.195 43.14 19.155 0.013 46.86 22.749 0.630 35.75 19.808 0.201 64.51 21.521 0.020 56.55 22.176 0.440 61.73 25.182 0.314 61.96 19.418 0.639

Single 55.98 15.749 53.67 14.689 50.27 23.527 40.55 14.050 77.00 17.560 64.71 21.243 58.08 22.687 67.04 20.838

Widow 46.20 10.402 40.00 10.464 38.80 16.053 43.80 8.843 52.33 12.897 56.33 37.647 45.67 37.687 69.00 25.000

Divorced 50.00 16.269 42.25 12.816 42.00 12.936 26.50 5.745 54.50 24.321 51.17 38.463 44.67 28.668 58.33 26.643

Living Arrangement Big cities 51.29 15.140 0.225 53.29 15.639 0.015 46.94 21.073 0.247 41.69 14.728 0.010 69.12 19.735 0.004 59.36 21.947 0.084 61.31 23.655 0.046 64.74 17.887 0.005

towns 54.70 15.370 50.10 11.090 56.30 18.239 48.30 12.157 58.40 22.921 60.20 29.518 54.90 28.286 65.20 23.541

village 46.00 14.885 36.67 13.968 39.27 17.898 40.47 13.543 45.50 25.955 39.25 29.647 43.75 35.075 34.25 33.935

Low social - - - - - - - - 13.00 . 13.00 . 0.00 . 25.00 .

Camps 56.05 18.701 48.95 18.508 50.48 25.689 32.33 17.432 - - - - - - - -

Educational Level Illiterate 28.50 13.435 0.254 37.50 9.192 0.760 28.00 4.243 0.220 15.50 21.920 0.012 38.00 . 0.564 38.00 . 0.410 31.00 . 0.770 38.00 . 0.809

Elementary 51.29 17.287 44.24 16.943 47.82 19.771 35.76 17.598 67.76 23.102 54.32 23.034 55.16 24.152 62.56 19.700

Secondary 54.31 16.840 49.60 17.449 46.40 23.558 36.89 14.898 68.71 19.413 61.81 21.522 62.73 23.399 64.81 18.331

Diploma 50.62 13.781 48.08 13.871 42.23 16.833 35.85 11.503 60.80 25.376 62.80 23.994 59.40 24.309 62.00 28.577

Bachelor’s 51.61 18.118 50.83 19.669 53.56 26.351 43.56 16.621 61.00 22.800 48.79 29.720 55.86 34.769 60.50 22.633

Master’s 69.00 10.392 58.33 15.631 73.00 3.464 64.33 14.434 81.00 . 81.00 . 69.00 . 81.00 .

Doctoral 53.50 13.435 50.00 0.000 62.50 17.678 50.00 0.000 81.00 . 63.00 . 69.00 . 56.00 .

Employment Status None 49.86 17.280 0.086 46.08 17.802 0.242 46.84 23.352 0.348 35.32 15.245 0.021 66.86 21.906 0.647 56.30 23.387 0.079 58.81 25.609 0.950 62.18 19.239 0.432

Part-time 55.50 15.613 53.42 14.191 47.85 21.273 41.00 14.439 58.67 22.062 51.44 24.409 61.78 28.195 59.11 27.547

Full time 62.00 13.332 52.78 17.218 52.11 21.257 48.00 22.028 70.38 18.693 72.69 19.444 61.62 23.240 71.38 20.484

Retired 66.00 4.243 53.50 13.435 75.00 0.000 59.50 4.950 63.00 . 75.00 . 50.00 . 69.00 .

Discrimination Low 52.06 17.468 0.308 50.14 16.825 0.422 47.46 22.587 0.230 38.17 16.857 0.396 68.52 22.693 0.137 61.87 24.955 0.038 60.29 27.083 0.602 67.25 20.159 0.005

Medium 52.38 14.397 46.23 15.085 46.69 22.590 40.69 11.902 60.32 17.708 48.61 17.821 56.00 20.305 52.75 17.407

High 64.00 17.986 42.40 27.410 65.00 19.183 30.00 25.817 79.00 3.464 62.67 6.506 69.00 25.000 66.67 12.897

Years of Immigration 10 years 51.89 15.840 0.701 48.82 18.294 0.927 45.88 21.951 0.387 37.48 16.438 0.494 60.38 25.923 0.507 60.38 24.876 0.961 53.13 28.063 0.630 61.25 22.927 0.664

9–5 years 53.81 19.201 49.00 14.674 52.03 23.661 39.29 15.998 64.97 18.461 57.79 22.401 61.85 23.615 61.21 22.246

<5 years 58.25 13.793 45.50 13.178 54.75 24.636 47.00 14.989 68.62 22.805 58.13 24.467 58.45 26.171 64.91 18.369

Monthly Family Income Low 50.57 16.627 0.092 47.57 16.329 0.371 44.92 21.344 0.062 34.83 15.275 0.003 64.26 24.494 0.362 55.76 24.705 0.122 58.47 27.794 0.384 58.50 20.450 0.010

Middle 56.43 16.628 50.73 18.012 53.62 23.817 44.54 16.120 68.95 15.939 59.58 20.983 58.89 21.373 68.37 17.936

High - - - - - - - - 76.75 16.256 80.00 19.782 76.50 15.801 81.50 18.230

Note: For statistically significant ANOVA results (p < 0.05), post hoc LSD comparisons were conducted. Significant pairwise differences (p < 0.05) are indicated in the text (Section 3.4).

3.4.1. Jordan Subgroup Analyses

In Jordan, a one-way ANOVA revealed a statistically significant difference in physical QoL scores between the age groups (F(4, 95) = 3.211, p = 0.016). Post hoc LSD comparisons showed that physical QoL was significantly higher among participants aged 18–29 compared to those aged 40–49 (p = 0.003, 95% CI [4.96, 23.31]), higher among those aged 30–39 compared to 40–49 (p = 0.002, 95% CI [5.65, 25.67]), and higher among those aged ≥60 compared to 40–49 (p = 0.034, 95% CI [−49.82, −1.93]).

Similarly, a one-way ANOVA revealed a statistically significant difference in psychological QoL scores between the age groups (F(4, 95) = 2.508, p = 0.046). Post hoc LSD comparisons revealed significantly higher psychological QoL among participants aged 18–29 compared to 40–49 (p = 0.003, 95% CI [5.15, 23.92]), and among those aged 30–39 compared to 40–49 (p = 0.022, 95% CI [1.82, 22.29]).

A one-way ANOVA revealed a statistically significant difference in psychological QoL scores between marital status groups (F(3, 96) = 3.799, p = 0.013). Post hoc LSD comparisons showed that single participants reported significantly higher psychological QoL than married participants (p = 0.003, 95% CI [−17.46, −3.61]).

Regarding living arrangements, a one-way ANOVA revealed a statistically significant difference in psychological QoL scores between living arrangement groups (F(3, 96) = 3.675, p = 0.015). Post hoc LSD comparisons revealed that participants living in big cities reported significantly higher psychological QoL than those in small villages (p = 0.001, 95% CI [6.63, 26.61]).

In relation to environmental QoL scores, there was a statistically significant difference between educational level groups (F(6, 93) = 2.915, p = 0.012). Post hoc LSD comparisons showed significantly higher environmental QoL among participants with master’s degrees compared to those with elementary education (p = 0.004, 95% CI [−47.65, −9.48]) and secondary education (p = 0.003, 95% CI [−45.62, −9.27]), and among those with bachelor’s degrees compared to illiterate participants (p = 0.016, 95% CI [−50.77, −5.34]).

Regarding employment status, a one-way ANOVA revealed a statistically significant difference in environmental QoL scores between employment status groups (F(3, 96) = 3.392, p = 0.021). Post hoc LSD comparisons revealed that full-time employed participants reported significantly higher environmental QoL than unemployed participants (p = 0.025, 95% CI [−12.93, 1.56]).

Additionally, a one-way ANOVA revealed a statistically significant difference in environmental QoL scores between monthly family income groups (F(2, 97) = 4.800, p = 0.010). Post hoc LSD comparisons found that environmental QoL was significantly higher among participants with middle income compared to low income (p = 0.017, 95% CI [−17.93, −1.81]), and among those with high income compared to low income (p = 0.024, 95% CI [−24.92, −3.03]).

3.4.2. Spain Subgroup Analyses

In Spain, an independent-samples t-test was conducted to compare physical QoL between male and female participants. There was a significant difference in scores for males (M = 75.34, SD = 19.113) and females (M = 61.15, SD = 21.063); t(98) = 3.386, p = 0.001. These results suggest that Syrian adult male refugees experience higher levels of physical QoL compared to their female counterparts. Similarly, an independent-samples t-test comparing psychological QoL between male and female participants showed a significant difference in scores for males (M = 65.55, SD = 21.574) and females (M = 53.66, SD = 23.616); t(98) = 2.524, p = 0.013.

A one-way ANOVA revealed a statistically significant difference in physical QoL scores between marital status groups (F(3, 96) = 3.421, p = 0.020). Post hoc LSD comparisons showed that single participants reported significantly higher physical QoL than married participants (p = 0.013, 95% CI [−22.25, −2.74]) and divorced participants (p = 0.019, 95% CI [3.79, 41.21]).

Regarding living arrangement, a one-way ANOVA revealed statistically significant differences in physical QoL scores between living arrangement groups (F(3, 96) = 4.755, p = 0.004), in social QoL scores (F(3, 96) = 2.771, p = 0.046), and in environmental QoL scores (F(3, 96) = 4.579, p = 0.005). Post hoc LSD comparisons indicated that participants living in big cities reported significantly higher QoL across these domains compared to those in smaller villages and rural areas (physical: p = 0.002; social: p = 0.035; environmental: p = 0.001).

A one-way ANOVA revealed a statistically significant difference in psychological QoL scores between discrimination groups (F(2, 97) = 3.390, p = 0.038). Post hoc LSD comparisons found that participants reporting low discrimination had significantly higher psychological QoL than those reporting medium discrimination (p = 0.011, 95% CI [3.06, 23.46]). Similarly, a one-way ANOVA revealed a statistically significant difference in environmental QoL scores between discrimination groups (F(2, 97) = 5.666, p = 0.005). Post hoc LSD comparisons showed that participants reporting low discrimination had significantly higher environmental QoL than those reporting medium discrimination (p = 0.001, 95% CI [5.91, 23.08]).

For the remaining statistically significant ANOVA results reported in Table 3, Table 4 and Table 5, post hoc LSD comparisons revealed no statistically significant pairwise differences, and this has been indicated in the corresponding footnotes.

Figure 2 presents a conceptual summary of the risk and resilience factors identified through bivariate comparisons. A conceptual model of risk and resilience factors associated with quality of life among Syrian refugees, based on bivariate findings from the present study. Arrows indicate direction of association; factors shown were statistically significant (p < 0.05) in at least two QoL domains.

4. Discussion

While the present study employed bivariate comparisons to document QoL differences between Jordan and Spain, interpreting these findings through a risk-and-resilience lens provides valuable integrative insight. Factors associated with lower QoL across domains—including low income, unemployment, camp residence, longer immigration duration (>10 years), and perceived discrimination—can be understood as post-displacement risk factors that erode refugee well-being. Conversely, factors associated with higher QoL—such as urban residence, full-time employment, shorter immigration duration (<5 years), and low discrimination—function as resilience factors or protective resources. Notably, some factors showed domain-specific effects: marriage was protective for psychological QoL in Spain but not Jordan, while recent immigration was consistently associated with a higher physical, social, and environmental QoL. This risk-and-resilience interpretation aligns with the ecological model of refugee adjustment (Miller & Rasmussen, 2017) and suggests that interventions should simultaneously reduce risks (e.g., poverty, discrimination) while strengthening resources (e.g., employment, urban integration). However, a limitation of our bivariate approach is that it cannot isolate the unique contribution of each factor after controlling for others; future studies should employ multivariable regression to test these pathways directly.

Most participants in the present study were unemployed, possessed secondary education qualifications, and earned low incomes. These characteristics are consistent with the broader literature indicating that the Syrian conflict led to widespread displacement, including that of academics and educators, which exacerbated educational challenges and created demands on host countries (Seydi, 2013). However, given our convenience sampling approach, these proportions should not be assumed to reflect the broader Syrian refugee population. Preceding the crisis, Syria faced educational disparities linked to regional and parental backgrounds, alongside rising dropout rates among older adolescents (Welker et al., 2021). The conflict, ongoing since 2011, has severely disrupted what were once high enrollment rates in primary and secondary education, placing immense strain on Syria’s educational system (Al Hessan et al., 2021). Syrian refugees in neighboring countries, particularly Lebanon, encountered significant obstacles to accessing education, even though it remained a high priority for families (Akesson et al., 2020).

Our findings are broadly consistent with prior research highlighting the substantial challenges Syrian refugees face in accessing education, achieving stable income, and securing employment in host countries. For example, studies conducted in Turkey have reported that only 38.6% of refugees were employed, primarily in unpaid or irregular jobs (Kayaoglu & Erdoğan, 2019), while research in Jordan found that less than 20% of refugees were engaged in work, mostly within informal or illegal sectors (Krafft et al., 2019). Direct comparisons should be made cautiously given differences in sampling and context. In the Netherlands, Syrian refugees often participate in volunteer work alongside language classes but rarely pursue employment or formal education (Miltenburg & Dagevos, 2021). Education remains a pressing concern, with limited access to basic education in Turkey (Bircan & Sunata, 2015) and low school enrollment rates reported in Jordan (Krafft et al., 2019). Key factors shaping employment opportunities include language proficiency, age, education level, and gender (Kayaoglu & Erdoğan, 2019; Miltenburg & Dagevos, 2021).

Research shows that refugees in Spain endure precarious conditions during their initial five years of integration, including economic instability, inadequate housing, and job insecurity (Iglesias-Martínez & Estrada, 2018). The Spanish refugee reception system has faced criticism for failing to adequately address these challenges (Iglesias-Martínez & Estrada, 2018; Maristany, 2020). The refugee crisis has attracted considerable media attention, with press coverage often emphasizing visual depictions of the conflict (Guijarro & Cuba, 2018). Spain’s approach of delegating its refugee system to NGOs through subsidies has been deemed both unsustainable and ineffective in responding to the rising demand for asylum (Bris & Bendito, 2017).

At the same time, in the present sample, participants reported QoL scores ranging from average to good in the physical, psychological, and social domains, while environmental QoL scores varied from poor to average. These findings reflect the experiences of our specific sample and may not be representative of all Syrian refugees in Jordan or Spain. Among participants in our study, those residing in Jordan reported lower physical, psychological, social, and environmental QoL compared to those residing in Spain. While these differences were statistically significant, they may reflect the specific characteristics of our sample, including differences in living arrangements, employment status, and duration of displacement between the two subsamples. Within our sample, married individuals, those living in large cities, and recent immigrants (less than five years) reported higher QoL, whereas QoL was lower among those with low income. These associations were identified through bivariate analyses and should be interpreted as exploratory; multivariable analyses are needed to determine whether these factors independently predict QoL after controlling for potential confounders. Physical QoL was higher among those living in big cities and significantly lower among those with low income and those who had been immigrants for ten years.

Contrary to our findings, research in Jordan has reported poor to average QoL across physical, psychological, social, and environmental domains, with scores below 50 on a 100-point scale (Alwedyan, 2022; Nashwan et al., 2022). Comparatively, Syrian refugees in Germany showed low QoL scores across all domains, particularly in social relations and psychological aspects (Al Masri et al., 2021). Factors influencing QoL included marital status, income, employment, and health conditions (Cevik et al., 2022). Education level was also significant, with higher education associated with better QoL among older refugees (Cevik et al., 2022). In Germany, asylum duration and housing type were linked to psychological and social relationship domains (Al Masri et al., 2021). Despite support provided in host countries, Syrian refugees continue to face challenges in maintaining their overall QoL (Alwedyan, 2022).

Psychological QoL was higher among males, those living in big cities, and those exposed to little or no discrimination, but lower among individuals with low income. Social QoL was higher among those living in big cities and lower among those who had been immigrants for ten years. Environmental QoL was higher among those living in big cities, those with full-time employment, and those who had been immigrants for less than five years, but lower among individuals with low income.

In Jordan, QoL was lower among individuals with low income. Physical QoL was lower among those aged 40 to 49 years. Psychological QoL was lower among individuals aged 40 to 49 years and those living in villages, but higher among single individuals. Environmental QoL was lower among those residing in camps, the illiterate, the unemployed, and those with low income. Conversely, it was higher among individuals with higher education levels.

Previous studies have also found that Syrian refugees face significant challenges in QoL across various domains. Research in Jordan, Germany, and Turkey has shown that Syrian refugees generally score lower on QoL measures compared to host populations (Alwedyan, 2022; Al Masri et al., 2021; Nashwan et al., 2022; Cevik et al., 2022). Factors positively associated with higher QoL include experiencing less discrimination, having full-time employment, and living in big cities (Al Masri et al., 2021). Conversely, larger family sizes and low income negatively impact QoL (Alwedyan, 2022; Nashwan et al., 2022). Psychological well-being is particularly linked to refugees scoring lower in this domain compared to host populations (Nashwan et al., 2022). However, some studies found that better housing conditions and longer asylum duration were associated with improved environmental and psychological QoL (Al Masri et al., 2021). Surprisingly, this finding contradicts our results, as poorer general, social, and environmental QoL were reported among individuals with longer immigration periods, while significantly higher QoL was observed among those residing for less than five years. This discrepancy may be explained by homesickness and ongoing conflicts in Syria, which may eventually affect the level of support provided by host countries to Syrian refugees. Nevertheless, this finding requires more detailed examination, and future studies are recommended.

In our study, Syrian refugees residing in Jordan reported mostly average scores in physical, psychological, and social QoL, but average to poor environmental QoL. One previous study in Jordan, comparing Syrian refugees to low-socioeconomic-status Jordanians, found that refugees had significantly lower scores in social relationships and psychological health but higher scores in the environmental domain (Abdo et al., 2019). Physical health scores were similar between the two groups. Factors positively influencing QoL included being married, having higher income, and being employed (Abdo et al., 2019). These findings warrant further investigation in future research.

Among participants residing in Spain, QoL was higher among those living in big cities. This finding is consistent with previous research suggesting that urban residence may facilitate access to services and employment opportunities (Al Masri et al., 2021), although our cross-sectional design precludes causal inference and our convenience sample limits generalizability. Physical QoL was higher among males, single individuals, and those living in big cities. Psychological QoL was higher among males and lower among those exposed to medium levels of discrimination. Social QoL was higher among those living in big cities. Environmental QoL was lower among those living in villages and those with low income, but higher among those exposed to no or low discrimination.

Previous studies conducted in Spain have reported that immigrants generally report poorer mental health than natives, with perceived discrimination being a significant predictor of both physical and mental health (Sevillano et al., 2014). Our findings regarding discrimination and QoL are consistent with this literature, though our single-item measure of discrimination and convenience sample warrant caution in interpretation. In Germany, Syrian refugees showed lower QoL scores compared to the general population, with asylum duration and housing influencing psychological and social domains (Al Masri et al., 2021). Syrian refugees in Kurdistan camps scored higher on social relationship QoL compared to general population norms but lower on physical and psychological domains (Aziz et al., 2014). In Sweden, Syrian refugees reported lower health-related QoL than the general population, with post-migration stressors such as high financial strain, social strain, competency strain, and discrimination significantly lowering their health-related QoL (Sengoelge et al., 2022).

The present study assessed discrimination and social support as broad, retrospective contextual factors. However, a growing body of research suggests that these processes also operate as recurring, everyday experiences that may affect well-being in more immediate and dynamic ways. For example, Krüger (2024) used ecological momentary assessment to examine everyday discrimination, co-ethnic social support, and mood changes among young adult immigrants in Germany, including Syrian refugees. This study found that within-person increases in discrimination were associated with immediate declines in mood, and that perceived social support had a consistent positive main effect on mood regardless of whether discrimination occurred. Notably, the buffering effect of social support was modest, and the level of perceived support mattered more than the ethnic origin of the support provider (intra-ethnic vs. inter-ethnic). These findings complement broader quality-of-life research by capturing the temporal dynamics of discrimination and support as they unfold in daily life. Future research could build on the present findings by incorporating ecological momentary assessment or daily diary methods to examine how everyday discrimination and social support shape quality of life among Syrian refugees in different host-country contexts.

The present findings, while exploratory, offer several actionable insights for policymakers, service providers, and stakeholders working with Syrian refugee populations. First, the identification of specific subgroups at greater risk of lower QoL—including women, older adults (particularly those aged 40–49), individuals with low income, the unemployed, camp residents, those in rural areas, and those who have experienced discrimination—can inform targeted screening and resource allocation. For example, gender-sensitive mental health services and psychosocial support programs may be particularly beneficial for female refugees, who reported lower physical and psychological QoL than their male counterparts in our sample.

Second, the consistent association between low income and poorer QoL across multiple domains underscores the importance of economic integration policies. Vocational training, microfinance initiatives, credential recognition, and formal employment pathways are concrete measures that can address poverty as a fundamental determinant of refugee well-being. The finding that full-time employment was associated with higher environmental QoL in both countries further supports the value of employment-focused interventions.

Third, the link between perceived discrimination and lower psychological and environmental QoL highlights the need for anti-discrimination legislation, intercultural awareness campaigns, and accessible mental health services for those who experience discrimination. Policymakers should consider embedding anti-discrimination measures within broader refugee integration strategies.

Fourth, the particularly poor environmental QoL reported by camp residents in Jordan suggests that improvements in camp infrastructure, housing conditions, and access to basic services should remain a priority. For refugees in Spain, where urban residence was associated with higher QoL, policies that support affordable housing and community integration in urban areas may help sustain these benefits.

Finally, the finding that recent immigrants (less than five years) reported higher QoL than those displaced for longer periods (10 years or more) suggests that early resettlement assistance may have lasting protective effects. Policymakers should consider strengthening support during the initial resettlement period, with particular attention to family support programs, language training, and community integration initiatives. While these recommendations require validation in representative samples, they provide a starting point for evidence-informed policy development and program design.

Limitations

Several methodological limitations should be acknowledged when interpreting these findings. First, while bivariate comparisons (t-tests, ANOVA) were appropriate for our primary aim of documenting cross-country differences in QoL, this approach does not allow us to isolate the unique contribution of each sociodemographic or contextual factor after controlling for potential confounders. For example, the observed association between urban living and higher QoL may be partially explained by greater employment opportunities or better access to services in cities. Although the present study identified several factors associated with quality of life, the use of bivariate analyses does not allow determination of the independent contribution of each variable while controlling for potential confounders. Future studies should employ multivariable analytical approaches to better understand the relative association of socio-demographic, contextual, risk, and resilience-related factors on quality-of-life outcomes among refugee populations.

Second, the numerous group comparisons presented increase the risk of Type I error (false positives). We have not applied corrections (e.g., Bonferroni) given the exploratory and descriptive nature of the study; therefore, findings should be interpreted cautiously pending replication.

Third, perceived discrimination was assessed using self-developed single-item measures rather than a validated multi-item scale (e.g., the Everyday Discrimination Scale). This decision was pragmatic, driven by the need to limit survey length to 45 min at the request of our community partners. While our single-item measure captured the frequency and perceived impact of discrimination, it may not fully capture its multidimensional nature (e.g., chronic versus acute experiences, attributional ambiguity). Nevertheless, single-item discrimination measures have been used successfully in refugee health research and demonstrate acceptable test–retest reliability and convergent validity. Future studies should incorporate validated Arabic-language discrimination scales where feasible.

Fourth, monthly family income was measured using country-relative self-rating (low/middle/high) rather than absolute figures, which limits cross-country comparability but improves within-country interpretability. Finally, the demographic form was not independently validated, though all items were reviewed by refugee service providers and piloted with five Syrian refugees per country prior to data collection. Despite these limitations, the study provides valuable comparative insights into the QoL of Syrian refugees in two distinct host countries.

Fifth, the study employed a convenience sample of 200 Syrian refugees (100 in Jordan and 100 in Spain), recruited through invitations at participating sites, social media posts, and snowball sampling. As such, the sample cannot be considered representative of the broader Syrian refugee population in either host country. Participants who were more accessible, more engaged with services, or more willing to participate may be overrepresented. Consequently, the findings should be interpreted as exploratory and hypothesis-generating rather than definitive. Prevalence estimates and associations observed in this sample may not generalize to the wider refugee population, and caution is warranted when extrapolating these results to policy or clinical practice. Future studies should employ probability sampling methods, where feasible, to enhance representativeness and external validity.

Sixth, the dichotomization of overall QoL into ‘Low’ and ‘High’ categories using a cut-off of 50 for the descriptive analysis in Table 3 necessarily simplifies the continuous nature of quality of life and may obscure variability within each category. While this categorization was used solely to facilitate interpretation of group differences, future research should consider using continuous measures throughout or applying established cut-offs validated in refugee populations.

5. Conclusions

While these findings provide valuable insights into the QoL of Syrian refugees in Spain and Jordan, they should be interpreted in light of the study’s limitations, particularly the use of a convenience sample. Future research with representative samples is needed to confirm and extend these results.

This study provides insights into the enduring impact of the Syrian conflict on the quality of life and well-being of refugees, highlighting the challenges they face even years after resettlement. The findings underscore the necessity of a holistic healthcare framework that addresses the intricate interplay between physical, psychological, social, and environmental dimensions of QoL, both before and after displacement. Recognizing the structure of the pre-conflict Syrian education system and the educational barriers refugees encounter is pivotal for designing targeted interventions and policies that facilitate integration, learning, and empowerment in host countries.

From a policy perspective, this study identifies specific demographic categories of Syrian refugees who may be at greater risk of lower QoL—including women, older adults (40–49 years), those with low income, the unemployed, camp residents, those in rural areas, and those who have experienced discrimination. These findings can inform targeted screening, resource allocation, and intervention planning. For example, gender-sensitive mental health services, economic empowerment programs, anti-discrimination initiatives, and improvements in camp infrastructure are concrete measures that policymakers and service providers can prioritize.

The findings also call for comprehensive support systems that address both pre-displacement trauma and the ongoing challenges of resettlement. Early identification of needs and tailored interventions—spanning mental health, social reintegration, and environmental stability—can substantially enhance outcomes for this vulnerable population. Furthermore, this research emphasizes the critical role of anti-discrimination efforts, community inclusion, and immediate psychological support in fostering resilience and mental well-being.

To support successful adjustment and long-term mental health, this study advocates robust psychological and psychiatric care, alongside rehabilitation programs tailored to the unique needs of refugees. These initiatives are essential not only for alleviating the psychological burden of displacement but also for empowering refugees to rebuild their lives with dignity and purpose. By addressing these interconnected challenges holistically, host nations may be better equipped to support refugees in rebuilding their lives. However, confirmation of these findings in representative samples is necessary before definitive policy recommendations can be made.

Abbreviations

The following abbreviations are used in this manuscript:

ANOVA Analysis of Variance

BREF Brief Version

CI Confidence Interval

ID Identification Number

LSD Least Significant Difference

QoL Quality of Life

SD Standard Deviation

SPSS Statistical Package for the Social Sciences

UNHCR United Nations High Commissioner for Refugees

WHO World Health Organization

WHOQOL-BREF World Health Organization Quality of Life—Brief Questionnaire

Author Contributions

Conceptualization: D.A.-H., M.A.-W., R.L.-R. and I.L.-R.; methodology, D.A.-H., M.A.-W., R.L.-R. and I.L.-R.; formal analysis, D.A.-H.; investigation, D.A.-H., M.A.-W., J.J.A.-O., D.G.-G., R.L.-R. and I.L.-R.; writing—original draft preparation, D.A.-H., M.A.-W., J.J.A.-O., D.G.-G., R.L.-R. and I.L.-R.; writing—review and editing, D.A.-H., M.A.-W., J.J.A.-O.; D.G.-G.; R.L.-R. and I.L.-R.; supervision, I.L.-R.; project administration I.L.-R. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Salamanca (protocol code: 958-26; date of approval: 26 May 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding authors upon reasonable request due to privacy.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding Statement

This research received no external funding.

Footnotes

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Associated Data

Data Availability Statement

The data that support the findings of this study are available from the corresponding authors upon reasonable request due to privacy.