Multivariable analysis of health-related quality of life determinants among medical students at a Single Syrian University in a conflict-affected setting: a cross-sectional study using the Arabic SF-36

Abstract

Background

Health-related quality of life (HRQoL) among medical students is particularly vulnerable to academic stressors, especially in populations exposed to armed conflict. This study evaluated the internal consistency and construct validity of the Arabic version of the 36-Item Short Form Health Survey (SF-36) in a cohort of medical students at a single university in Syria and examined determinants of HRQoL during the Syrian civil war.

Methods

A cross-sectional survey was conducted among 181 of 300 medical students (60.3%) from the Faculty of Medicine at Aleppo University who attended continuing medical education sessions between September and November 2024. Self-administered questionnaires captured sociodemographic and clinical characteristics, Arabic SF-36 scores across eight domains, and the Physical Component Summary (PCS) and the Mental Component Summary (MCS). Reliability was assessed using Cronbach’s α and composite reliability. Statistical associations were evaluated using t-tests, analysis of variance (ANOVA), and backward-elimination multivariable linear regression.

Results

Participants had a median age of 21 years (IQR: 20–22), with 63.5% male. Mean PCS scores (66.6 ± 18.5) were higher than mean MCS scores (55.9 ± 21.3), indicating relatively better physical than mental HRQoL. Among the eight SF‑36 domains, Bodily Pain (74.4 ± 24.3) and Role Physical (73.5 ± 36.9) showed the highest mean scores. Lower body mass index, higher religiosity, and absence of chronic conditions were associated with better HRQoL. In contrast, smoking and daily transport exceeding two hours were independently associated with lower mental domain scores (all p < 0.05). Cronbach’s alpha coefficients ranged from 0.467 to 0.91. Four of the eight domains met the conventional reliability threshold of at least 0.70, while the PCS and MCS demonstrated strong internal consistency.

Conclusions

The findings demonstrate that Syrian medical students at Aleppo University experience suboptimal mental HRQoL despite relatively preserved physical functioning. The Arabic SF‑36 showed acceptable overall reliability and appropriate structural correlations for the main summary components and core physical domains. However, several mental and general health domains exhibited lower item consistency. These psychometric characteristics should be considered when interpreting domain-level scores and when adapting the instrument for similar populations affected by conflict.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12909-026-09937-7.

Introduction

Health-related quality of life (HRQoL) refers to an individual’s subjective perception of physical, mental, and social functioning. Medical training commonly impairs these dimensions, adversely affecting both physical and mental health among students [1, 2]. Medical education is associated with reduced cognitive performance, anxiety, depression, burnout, dropout, substance use, and suicidality [3]. Moderating factors such as social support, resilience, and self-control may mitigate these adverse outcomes [4]. Lins et al. reported that physical and emotional disturbances impair social functioning among medical students [5]. Similarly, Domantay et al. identified depression, stress, and burnout as significant predictors of reduced HRQoL [6] .

Medical students at different stages of training experience varying degrees of physical and mental health impairment [7]. Dyrbye et al. reported that students in later years exhibited consistently higher psychological distress than both the general population and age-matched peers [7]. Gender differences are also evident in HRQoL, with female medical students frequently reporting lower scores than their male counterparts [8]. Systematic reviews have shown that regular physical activity improves physical HRQoL and reduces burnout among medical students, although most of the evidence comes from Western studies [9]. A meta-analysis by Quek et al. estimated a global prevalence of anxiety of 33.8% (95% CI: 29.2–38.7%) among medical students, with higher rates observed in Middle Eastern subgroups. However, no studies from Syria were included [10]. This absence underscores a substantial regional research gap that warrants targeted investigation.

Although numerous Western studies have examined HRQoL determinants among medical students, their findings have limited generalizability to Eastern contexts [3]. In the Middle East, research on medical students’ quality of life remains comparatively scarce [10]. Egyptian studies have reported high levels of psychological stress, depression, anxiety, and poor sleep quality among medical students across all six academic years [11]. In Saudi Arabia, sleep quality has shown significant associations with depression, anxiety, and stress in medical students [12]. However, cultural, educational, and social differences within the region restrict the generalizability of these findings to other national contexts.

In Syria, medical education faces additional challenges related to prolonged war and conflict [13]. Multiple studies have shown that armed conflict adversely affects mental and physical health, leading to post-traumatic stress disorder and persistent unmet daily needs [14]. Al Saadi et al. reported a high prevalence of anxiety, depression, and stress among Syrian medical students across various training years during the wartime period [15]. These observations highlight the urgent need to identify the determinants of HRQoL among medical students in war-affected settings such as Syria. To our knowledge, this is the first study to investigate predictors of HRQoL among Syrian medical students using the 36-Item Short Form Health Survey (SF-36). The study aims to evaluate the internal consistency, composite reliability, and construct validity of the Arabic version of the SF-36 within this institutional cohort and to examine correlations between its physical and mental health domains.

Methods

Study design

This cross-sectional study included undergraduate medical students from all six academic years at the Faculty of Medicine, University of Aleppo, Syria. The six-year medical curriculum comprises three years of preclinical training in the basic sciences, followed by three years of clinical training through hospital-based rotations. Extracurricular teaching activities for medical students are delivered through the Continuing Medical Education (CME) laboratory. The cross-sectional design allowed simultaneous assessment of students across different training levels within the same academic period. Given the established infrastructural challenges in Syrian medical training, a cross-sectional design was the optimal strategy for a comprehensive evaluation.

Study population and sampling

The study population included all 300 undergraduate medical students who attended CME lectures between September and November 2024 were eligible to participate. A total of 181 students (response rate 60.3%) provided informed consent and completed the survey, forming a convenience sample. Convenience sampling was used due to logistical constraints in a post-conflict environment, facilitating the efficient recruitment of students attending structured teaching sessions. Such approaches are frequently adopted in resource-constrained settings, although they may introduce selection bias by preferentially including more motivated individuals. The minimum sample size was calculated using the Cochran formula with the finite population correction, assuming a total eligible population  N=300, a standard normal deviate  Z=1.96 for a 95% confidence level, a margin of error  e=0.05, and a conservative anticipated proportion  p=0.5, with  q=1-p:

This calculation indicated a minimum requirement of 169 participants. Recruitment of 181 students exceeded this threshold, providing adequate precision for the planned analyses. Internal reliability and clarity of the questionnaire were assessed in a pilot test involving 30 medical students who did not participate in the main study, which demonstrated Cronbach’s alpha values above 0.7 for the principal scales.

Ethical considerations

Ethical approval was obtained from the Aleppo University Research Ethics Committee (registration number: 2403; ISRCTN14425442). The study adhered to the principles of the Declaration of Helsinki. All participants were informed of the study aims, potential risks, and anticipated benefits. Written informed consent was obtained from each participant. Participation was voluntary, and no incentives were provided. Participants were asked to complete all questionnaire items to minimize missing data.

Data collection instruments and procedures

Data were collected using self-administered paper questionnaires that were distributed and completed during a single CME lecture session. No follow-up distributions were arranged in order to accommodate students’ academic schedules. The questionnaire consisted of two sections.

Section 1: sociodemographic and clinical variables

The first section collected information on gender, age, body mass index (BMI), academic year, relationship status, household composition, self-reported financial status, daily time spent in transport, daily social media use, smoking status, self-reported religiosity, parental medical background, parental education, maternal education, and the presence of chronic medical conditions. Self-reporting was chosen for feasibility in a classroom setting. Pilot testing addressed potential recall bias.

Section 2: Health-Related Quality of Life (HRQoL)

The second section assessed HRQoL using the Arabic SF-36, which has been widely applied in medical student populations [16]. Translation and cultural adaptation followed International Quality of Life Assessment (IQOLA) guidelines, with modifications for the Syrian context. The SF-36 comprises eight domains: Physical Functioning (PF), Role limitations due to Physical health problems (Role Physical, RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Functioning (SF), Role limitations due to Emotional problems (Role Emotional, RE), and Mental Health (MH). SF-36 items were scored from 0 (poorest health) to 100 (best health) using standard scoring algorithms for the Arabic version. Domain scores were calculated as unweighted averages of their constituent items, with recoding applied where necessary so that higher scores reflected better HRQoL. The Physical Component Summary (PCS) score was derived from the physical functioning, role physical, bodily pain, and general health domains. The Mental Component Summary (MCS) was derived from the vitality, social functioning, role emotional, and mental health domains [17, 18]. These summary indices were used as primary measures of physical and mental HRQoL.

Internal consistency of the SF‑36 domains and summary scores was assessed using Cronbach’s alpha and composite reliability. Subscales containing four or more items (physical functioning, role physical, general health, mental health, vitality) were evaluated against the standard acceptability threshold of Cronbach’s alpha ≥ 0.70. Subscales with fewer than four items (bodily pain, social functioning, role emotional) were evaluated against a lower threshold of α ≥ 0.50, acknowledging that shorter scales typically produce lower alpha values. Aggregate summary scores (PCS and MCS) were expected to achieve Cronbach’s alpha values of at least 0.70.

Statistical analysis

Statistical analysis was performed using Jamovi software (version 2.3.28) for descriptive statistics, inferential tests, and regression modeling [19]. Continuous variables were assessed for normality using the Shapiro-Wilk test. Normally distributed data were summarized as mean ± standard deviation (SD), whereas non-normal distributed data were summarized as median and interquartile range (IQR). Categorical variables were presented as frequencies and percentages.

Independent-samples t-tests and one-way analysis of variance (ANOVA) were used to examine univariate associations between sociodemographic characteristics or clinical characteristics and continuous SF-36 domain or summary scores. Chi-square tests were employed to compare categorical variables. Levene’s test was applied to assess the homogeneity of variances. Statistical significance was set at p < 0.05.

Multivariable linear regression models were constructed for each SF-36 domain and summary score to identify independent predictors. A backward-elimination procedure was used, beginning with all candidate variables. The least significant variable (p ≥ 0.20) was iteratively removed until all remaining predictors met a retention criterion of p < 0.20. Gender was included as an adjustment variable in all models to control for potential confounding [20]. Model fit was evaluated using adjusted R² values. Inter-domain correlations were examined using Pearson’s correlation coefficient (r) for normally distributed variables and Spearman’s rank correlation coefficient (ρ) for non-normally distributed variables, to verify the theoretical structure of the SF‑36. No adjustments for multiple comparisons were applied, in view of the exploratory nature of the analysis.

Results

Participant characteristics

A total of 181 medical students from Aleppo University were included in this cross-sectional study, representing a response rate of 60.3% among 300 eligible students who attended CME lectures between September and November 2024. The overall cohort had a median age of 21 years (IQR: 20–22) and a median BMI of 21.6 kg/m² (IQR: 19.4–24.1). Most participants were male (n = 115, 63.5%) and in their fourth year of study (n = 61, 33.7%). Additional sociodemographic and clinical characteristics are summarized in Table 1. The majority of students identified as religious (n = 171, 94.5%), reported no chronic medical conditions (n = 150, 82.9%), and lived with their families (n = 141, 77.9%).

Table 1.

Sociodemographic and clinical characteristics of participants

Characteristics	Category	n (%) of respondents (total respondents, N = 181)
Gender	Male	115 (63.5)
	Female	66 (36.5)
Age (years)	≥ 21	107 (59.1)
	< 21	74 (40.9)
Body mass index (BMI, kg/m²)	< 18.5	35 (19.3)
	18.5–24.9	107 (59.1)
	≥ 25	39 (21.5)
Academic year	1st-Year Medical Student	56 (30.9)
	2nd-Year Medical Student	21 (11.6)
	3rd-Year Medical Student	13 (7.2)
	4th-Year Medical Student	61 (33.7)
	5th-Year Medical Student	10 (5.5)
	6th-Year Medical Student	20 (11)
Relationship status	Single	173 (95.6)
	Married	8 (4.4)
Household composition	Living alone	16 (8.8)
	Living with friend(s)	24 (13.3)
	Living with family	141 (77.9)
Self-reported financial status	Low	20 (11)
	Middle	145 (80.1)
	High	16 (8.8)
Daily time spent in transport (hours)	< 1	89 (49.2)
	1	46 (25.4)
	> 1 to ≤ 2	34 (18.8)
	> 2	12 (6.6)
Daily social media use (hours)	0–3	98 (54.1)
	4–6	68 (37.6)
	> 6	15 (8.3)
Smoking status	Current smoker	15 (8.3)
	Never smoker	159 (87.8)
	Former smoking	7 (3.9)
Self-reported religiosity	No	10 (5.5)
	Yes	171 (94.5)
Parental medical background	None	147 (81.2)
	≥ 1 parent physician	34 (18.8)
Paternal education	Primary school	15 (8.3)
	Middle school	18 (9.9)
	High school	32 (17.7)
	College degree	98 (54.1)
	Postgraduate	18 (9.9)
Maternal education	Primary school	26 (14.4)
	Secondary school	28 (15.5)
	High school	35 (19.3)
	College degree	81 (44.8)
	Postgraduate	11 (6.1)
The presence of chronic medical conditions	Yes	31 (17.1)
	No	150 (82.9)

Reliability of the Arabic version of the SF-36

The Arabic version of the SF-36 demonstrated acceptable internal consistency in this population. Cronbach’s alpha coefficients ranged from 0.467 for the general health domain to 0.91 for the physical functioning domain. Composite reliability values exceeded 0.70 for all domains except general health (0.691), meeting conventional thresholds for group-level comparisons (≥ 0.70 for most domains and ≥ 0.50 for domains with fewer items). Domain-specific reliability coefficients, along with their corresponding means and SDs, are presented in Table 2. These reliability patterns are consistent with previous validations of the Arabic SF-36 in Middle Eastern populations, in which relatively lower reliability has been reported for the general health and vitality domains. SF-36 Domain and Summary Scores.

Table 2.

Internal consistency reliability, and Spearman correlation coefficients among SF-36 quality-of-life domains and summary scores

Domain	No. of Items	Mean (SD)	Cronbach’s α	Composite Reliability	Spearman Correlation Coefficient (ρ)
					MCS	PCS
Physical functioning (PF)	10	63.7 (30.1)	0.91	0.925	0.03	0.84
Role physical (RP)	4	73.5 (36.9)	0.856	0.903	0.30	0.58
Role emotional (RE)	3	53.0 (42.4)	0.808	0.887	0.86	0.17
Vitality (VT)	4	49.8 (16.9)	0.591	0.755	0.68	0.27
Mental health (MH)	5	56.4 (17.1)	0.654	0.779	0.69	0.24
Social functioning (SF)	2	71.1 (23.4)	0.653	0.853	0.64	0.22
Bodily pain (BP)	2	74.4 (24.3)	0.860	0.933	0.31	0.35
General health (GH)	5	63.9 (15.4)	0.467	0.691	0.44	0.35
Mental component summary (MCS)	14	55.9 (18.1)	0.834	0.867	—	0.24
Physical component summary (PCS)	21	66.6 (18.5)	0.846	0.860	—	—

Mean SF‑36 domain scores indicated a moderate level of HRQoL, with physical domains generally scoring higher than mental domains (scale range: 0 = worst, 100 = best). The highest scores were observed for bodily pain (74.4 ± 24.3) and role physical (73.5 ± 36.9). Intermediate scores were recorded for physical functioning (63.7 ± 30.1), general health (63.9 ± 15.4), and social functioning (71.1 ± 23.4). In contrast, mental health domains showed lower scores, including role emotional (53.0 ± 42.4), mental health (56.4 ± 17.1), and vitality (49.8 ± 16.9). All domain scores are presented in Table 2. Importantly, because the general health and vitality subscales demonstrated weak internal consistency (Cronbach’s alpha 0.467 and 0.591, respectively), subsequent analyses involving these domains should be interpreted with caution due to a higher risk of measurement error.

Inter-domain and inter-scale correlations

Spearman correlation analysis supported the theoretical structure of the SF-36 (Table 2). Physical functioning showed a strong correlation with PCS (ρ = 0.84), while role emotional showed a strong correlation with MCS (ρ = 0.86), consistent with convergent validity. Mental health domains (vitality, social functioning, role emotional, mental health) demonstrated moderate-to-strong correlations with MCS (ρ = 0.64–0.86), whereas physical domains (physical functioning, role physical) were more strongly correlated with PCS (ρ = 0.58–0.84). Weak correlations between certain domains, such as physical functioning and MCS, were compatible with discriminant validity. Pearson inter-scale correlations yielded consistent patterns, supporting the instrument’s construct validity (Supplementary Table 1). PCS correlated most strongly with physical functioning (r = 0.825, p < 0.001) and role physical (r = 0.611, p < 0.001), whereas MCS correlated strongly with role emotional (r = 0.822, p < 0.001), mental health (r = 0.769, p < 0.001), and vitality (r = 0.751, p < 0.001). The overall pattern of statistically significant correlations (predominantly p < 0.001) supports the construct validity of the SF-36 in this Arabic-speaking medical student population.

Univariate associations

Univariate analyses identified several sociodemographic and clinical factors associated with SF‑36 domains and summary scores (Tables 3 and 4). BMI was significantly associated with physical functioning (p = 0.014) and social functioning (p = 0.019), with underweight participants (< 18.5 kg/m²) showing higher scores than normal-weight and overweight participants. The presence of chronic medical conditions was associated with significantly lower scores in bodily pain (p = 0.004), role physical (p = 0.001), and general health (p = 0.001), as well as lower PCS score (p = 0.010). Although the association with the general health subscale was statistically significant, the interpretation of this domain should take into account its reduced internal consistency in this cohort.

Table 4.

Univariate associations of lifestyle, family, and clinical characteristics with SF-36 quality-of-life domains and summary scores

Characteristic	Category	PF	BP	RP	RE	MH	SF	VT	GH	Physical measure	Mental measure
Smoking status	Current smoker	55.33 (35.02)	78.67 (25.41)	73.33 (42.75)	46.67 (46.80)	45.87 (22.21)	63.33 (30.05)	41.67 (21.68)	61.33 (17.67)	62.41 (25.77)	47.33 (24.39)
	Never smoker	64.69 (29.38)	73.49 (24.38)	72.80 (36.93)	52.83 (42.15)	57.43 (16.25)	71.70 (22.78)	50.31 (16.13)	63.93 (15.21)	66.89 (17.67)	56.45 (17.16)
	Former smoking	58.57 (37.72)	86.07 (18.81)	89.29 (19.67)	71.43 (40.50)	55.43 (20.19)	73.21 (20.95)	54.29 (21.10)	68.57 (14.35)	69.42 (20.51)	61.07 (22.19)
	p-value	0.470	0.320	0.520	0.440	0.043	0.405	0.128	0.589	0.618	0.360
Household composition	Living alone	53.44 (36.46)	76.72 (22.30)	79.69 (36.76)	52.08 (42.11)	55.75 (23.75)	74.22 (20.14)	48.44 (19.30)	66.25 (16.28)	63.71 (22.24)	55.51 (21.91)
	Living with friend(s)	71.46 (24.16)	75.42 (29.96)	73.96 (38.64)	50.00 (43.96)	52.50 (14.51)	68.75 (25.00)	50.21 (15.21)	63.96 (14.52)	70.53 (19.44)	53.63 (16.55)
	Living with family	63.51 (30.12)	73.97 (23.63)	72.70 (36.83)	53.66 (42.50)	57.13 (16.73)	71.10 (23.53)	49.82 (17.02)	63.62 (15.47)	66.28 (17.90)	56.30 (18.03)
	p-value	0.190	0.890	0.770	0.923	0.469	0.770	0.944	0.811	0.471	0.800
Self-reported religiosity	No	71.50 (32.24)	84.00 (18.64)	95.00 (15.81)	33.33 (41.57)	48.00 (19.32)	60.00 (32.70)	40.50 (17.87)	69.50 (9.26)	76.69 (15.96)	44.43 (22.47)
	Yes	63.22 (30.05)	73.85 (24.53)	72.22 (37.42)	54.19 (42.32)	56.89 (16.95)	71.71 (22.67)	50.29 (16.76)	63.57 (15.59)	66.03 (18.49)	56.54 (17.70)
	p-value	0.400	0.200	0.001	0.130	0.110	0.120	0.080	0.085	0.076	0.040
Parental medical background	None	64.83 (29.94)	74.69 (23.88)	73.81 (36.35)	52.83 (42.17)	58.10 (16.59)	72.02 (22.16)	50.07 (16.20)	64.39 (15.66)	67.37 (17.85)	56.66 (17.88)
	≥ 1 parent physician	58.68 (30.93)	73.16 (26.44)	72.06 (39.77)	53.92 (44.20)	49.06 (17.84)	66.91 (28.02)	48.38 (19.95)	61.76 (13.97)	63.34 (20.98)	52.46 (19.06)
	p-value	0.290	0.740	0.800	0.890	0.010	0.250	0.600	0.371	0.250	0.220
Paternal education	Primary school	70.33 (29.85)	82.33 (17.23)	80.00 (28.66)	51.11 (39.57)	56.53 (16.83)	75.00 (19.48)	45.00 (15.24)	67.33 (12.08)	72.60 (16.32)	54.71 (17.17)
	Secondary school	67.50 (34.31)	74.44 (22.95)	77.78 (35.24)	31.48 (40.38)	55.33 (17.53)	71.53 (22.61)	43.89 (16.32)	58.06 (14.77)	67.87 (17.35)	49.27 (16.61)
	High school	66.25 (28.26)	67.58 (23.69)	64.84 (40.59)	61.46 (40.70)	56.00 (17.15)	69.14 (25.20)	50.31 (16.36)	63.59 (16.03)	65.48 (18.89)	57.42 (18.71)
	College degree	62.55 (29.60)	77.42 (23.61)	75.77 (35.62)	55.44 (43.06)	58.94 (15.93)	73.98 (20.83)	51.84 (15.79)	65.46 (15.52)	67.18 (17.71)	58.31 (17.12)
	Postgraduate studies	55.83 (33.35)	63.47 (31.01)	66.67 (44.56)	48.15 (43.12)	44.22 (19.81)	54.86 (31.25)	47.22 (23.96)	58.89 (15.10)	59.35 (23.71)	47.44 (22.10)
	p-value	0.630	0.050	0.490	0.170	0.022	0.171	0.262	0.177	0.327	0.078
Maternal education	Primary school	62.31 (26.35)	78.17 (25.93)	77.88 (34.15)	38.46 (40.76)	56.77 (15.26)	64.42 (25.42)	48.08 (16.68)	63.27 (12.24)	67.01 (18.23)	51.46 (16.93)
	Secondary school	69.11 (32.18)	67.68 (25.80)	77.68 (32.16)	50.00 (39.02)	53.14 (18.53)	74.55 (22.17)	49.82 (19.41)	60.71 (15.26)	68.61 (19.00)	54.58 (17.91)
	High school	66.57 (28.12)	72.64 (22.96)	64.29 (41.69)	60.00 (42.63)	59.77 (15.21)	71.43 (20.47)	51.29 (14.21)	66.29 (15.97)	66.65 (17.74)	59.06 (17.05)
	College degree	59.94 (31.28)	74.94 (23.85)	72.53 (37.63)	55.56 (43.14)	56.69 (18.20)	71.91 (23.51)	50.93 (16.79)	63.46 (16.35)	64.60 (18.72)	56.98 (18.25)
	Postgraduate studies	71.36 (31.71)	84.32 (23.13)	88.64 (30.34)	54.55 (47.78)	50.91 (15.60)	70.45 (29.72)	40.00 (19.10)	69.09 (12.41)	75.35 (18.51)	51.36 (23.61)
	p-value	0.520	0.310	0.310	0.350	0.478	0.588	0.334	0.494	0.444	0.445
The presence of chronic medical conditions	Yes	63.71 (26.80)	63.06 (26.49)	49.19 (44.48)	60.22 (42.53)	53.55 (20.54)	66.53 (24.45)	46.61 (20.43)	55.81 (16.03)	59.00 (20.41)	54.85 (20.94)
	No	63.67 (30.86)	76.75 (23.25)	78.50 (33.15)	51.56 (42.41)	56.99 (16.38)	72.00 (23.11)	50.40 (16.10)	65.57 (14.72)	68.19 (17.73)	56.09 (17.56)
	p-value	0.990	0.004	0.001	0.300	0.310	0.240	0.337	0.001	0.010	0.730
Daily time spent in transport (hours)	< 1	63.88 (31.09)	74.94 (24.88)	72.47 (38.07)	49.06 (43.55)	57.30 (17.05)	72.75 (22.10)	48.26 (16.03)	64.55 (14.57)	66.73 (19.62)	55.16 (18.14)
	1	63.26 (32.10)	78.32 (20.89)	79.35 (34.68)	60.87 (39.94)	58.35 (15.36)	72.28 (24.28)	51.52 (16.09)	65.98 (14.97)	68.41 (16.47)	58.93 (16.72)
	> 1 to ≤ 2	63.82 (24.77)	70.00 (24.43)	72.79 (34.47)	56.86 (42.27)	57.65 (15.16)	70.96 (20.58)	53.82 (16.88)	63.38 (15.75)	66.02 (15.45)	58.29 (17.87)
	> 2	63.33 (32.78)	67.92 (31.17)	60.42 (43.25)	41.67 (42.94)	38.67 (21.46)	54.17 (31.68)	42.50 (23.98)	52.50 (18.28)	60.63 (25.13)	42.62 (19.82)
	p-value	1.000	0.360	0.440	0.330	0.003	0.075	0.146	0.052	0.634	0.036
Daily social media use (hours)	0–3	62.45 (31.84)	74.16 (23.61)	70.66 (37.65)	56.80 (43.13)	57.55 (18.64)	71.94 (24.28)	51.63 (17.90)	64.18 (15.44)	65.54 (19.46)	57.76 (19.76)
	4–6	64.26 (29.90)	73.97 (25.65)	76.84 (36.98)	47.06 (42.41)	54.76 (16.31)	68.57 (22.70)	45.66 (15.48)	63.53 (16.05)	67.41 (18.30)	52.48 (16.62)
	> 6	69.00 (18.24)	78.00 (23.95)	76.67 (32.00)	55.56 (37.09)	56.27 (8.75)	76.67 (19.97)	56.00 (12.85)	63.67 (12.02)	70.05 (11.92)	58.95 (10.44)
	p-value	0.530	0.840	0.540	0.340	0.590	0.410	0.030	0.960	0.620	0.090

Values represent mean (SD). P-values reflect between-group comparisons using independent t-tests or one-way ANOVA as appropriate

Significant statistics (p < 0.05) are indicated in bold

PF physical functioning, BP bodily pain, RP Role physical, RE Role emotional, MH mental health, SF social functioning, VT vitality, GH general health

Table 3.

Univariate associations of sociodemographic characteristics with SF-36 quality-of-life domains and summary scores

Characteristic	Category	PF	BP	RP	RE	MH	SF	VT	GH	Physical measure	Mental measure
Gender	Male	64.35 (27.71)	73.46 (24.17)	67.61 (38.90)	53.04 (41.63)	57.46 (15.03)	71.52 (22.31)	50.70 (15.77)	63.48 (14.44)	65.63 (17.32)	56.59 (16.80)
	Female	62.50 (34.15)	76.06 (24.66)	83.71 (30.85)	53.03 (44.14)	54.55 (20.32)	70.27 (25.26)	48.11 (18.77)	64.62 (16.92)	68.34 (20.37)	54.63 (20.31)
	p-value	0.709	0.489	0.003	0.998	0.311	0.729	0.320	0.631	0.340	0.490
Age (years)	≥ 21	65.05 (30.76)	75.40 (23.86)	76.17 (36.40)	52.96 (43.43)	58.13 (17.24)	72.55 (23.44)	50.05 (16.20)	64.95 (15.32)	68.13 (18.85)	56.77 (18.34)
	< 21	61.69 (29.31)	72.97 (25.04)	69.59 (37.53)	53.15 (41.26)	53.89 (16.82)	68.92 (23.25)	49.32 (18.01)	62.36 (15.38)	64.43 (17.83)	54.58 (17.87)
	p-value	0.460	0.510	0.240	0.980	0.100	0.310	0.780	0.266	0.190	0.420
Body mass index (BMI)	< 18.5	73.29 (21.99)	75.36 (23.64)	75.00 (36.38)	56.19 (41.04)	59.31 (16.70)	78.93 (15.98)	52.00 (15.11)	60.43 (15.78)	70.75 (15.38)	59.36 (15.15)
	18.5–24.9	58.88 (33.53)	73.76 (25.31)	71.96 (38.04)	53.89 (43.59)	56.15 (18.06)	68.81 (25.14)	47.57 (17.91)	63.93 (15.45)	63.99 (19.66)	55.10 (19.64)
	≥ 25	68.21 (23.72)	75.32 (22.59)	76.28 (34.86)	47.86 (41.04)	54.46 (14.87)	70.19 (22.87)	52.95 (15.29)	66.92 (14.40)	70.12 (16.76)	54.86 (16.19)
	p-value	0.014	0.913	0.790	0.670	0.467	0.019	0.187	0.192	0.070	0.450
Academic year	1st-Year	63.13 (28.88)	73.93 (22.15)	71.88 (37.56)	51.79 (40.66)	54.79 (15.44)	69.87 (22.59)	49.20 (18.01)	62.14 (14.11)	65.59 (18.42)	54.70 (17.62)
	2nd-Year	68.33 (27.49)	73.21 (27.40)	70.24 (37.60)	61.90 (39.84)	55.05 (15.23)	72.62 (19.21)	52.86 (14.19)	63.57 (17.26)	68.03 (14.90)	58.40 (14.33)
	3rd-Year	59.62 (27.04)	86.15 (14.81)	80.77 (27.30)	74.36 (41.17)	56.00 (14.33)	80.77 (15.82)	47.31 (13.17)	62.69 (13.33)	66.90 (13.09)	60.99 (14.45)
	4th-Year	64.26 (32.67)	73.32 (25.56)	72.95 (39.08)	53.55 (42.29)	61.18 (16.82)	70.49 (26.02)	51.23 (16.19)	64.92 (15.23)	66.94 (19.58)	58.03 (18.77)
	5th-Year	63.50 (27.39)	75.75 (25.33)	67.50 (44.17)	36.67 (45.68)	58.80 (18.09)	75.00 (22.82)	45.00 (13.94)	70.50 (12.79)	67.10 (21.42)	52.43 (18.04)
	6th-Year	61.25 (34.10)	72.00 (27.87)	81.25 (31.28)	40.00 (46.64)	46.80 (22.14)	66.25 (25.68)	47.50 (22.15)	63.50 (19.61)	66.62 (21.87)	48.32 (22.12)
	p-value	0.970	0.640	0.800	0.180	0.035	0.606	0.759	0.712	0.997	0.272
Relationship status	Single	63.61 (30.44)	74.62 (24.44)	73.84 (36.95)	52.99 (42.37)	56.44 (17.06)	70.66 (23.56)	49.51 (16.81)	63.93 (15.34)	66.69 (18.57)	55.75 (18.00)
	Married	65.00 (24.05)	69.69 (22.22)	65.63 (37.65)	54.17 (46.93)	55.50 (20.22)	79.69 (17.60)	55.00 (19.64)	63.13 (16.68)	65.12 (17.61)	58.53 (21.91)
	p-value	0.900	0.580	0.540	0.940	0.880	0.290	0.370	0.885	0.820	0.670
Self-reported financial status	Low	72.25 (19.09)	73.13 (29.04)	72.50 (38.81)	53.33 (45.11)	55.00 (18.53)	65.63 (24.63)	50.00 (16.30)	56.75 (17.72)	68.69 (15.03)	54.73 (16.99)
	Middle	63.14 (31.03)	74.90 (23.33)	73.45 (37.06)	52.41 (42.99)	57.27 (16.38)	71.72 (22.00)	50.14 (16.05)	64.79 (15.09)	66.62 (18.32)	56.26 (17.71)
	High	57.81 (32.50)	71.56 (28.00)	75.00 (35.36)	58.33 (35.49)	50.25 (21.66)	71.88 (33.07)	45.94 (24.65)	64.69 (12.97)	64.03 (24.07)	53.84 (23.66)
	p-value	0.146	0.848	0.980	0.830	0.279	0.550	0.807	0.087	0.760	0.840

Values represent mean (SD). P-values reflect between-group comparisons using independent t-tests or one-way ANOVA as appropriate

Significant statistics (p < 0.05) are indicated in bold

PF physical functioning, BP bodily pain, RP Role physical, RE Role emotional, MH mental health, SF social functioning, VT vitality, GH general health

Female participants reported greater limitations in role physical compared with males (83.71 ± 30.85 vs. 67.61 ± 38.90; p = 0.003). The academic year was associated with mental health domain scores (p = 0.035), with fourth-year students reporting the highest values (61.18 ± 16.82). Smoking was significantly associated with lower mental health scores (p = 0.043). Having at least one physician parent (p = 0.010) and higher paternal education (p = 0.022) were also associated with lower mental health scores. Daily transport time exceeding two hours was associated with lower mental health (p = 0.003) and MCS scores (p = 0.036). Higher self-reported religiosity was associated with higher MCS scores (56 vs. 44; p = 0.040). No statistically significant gender differences were observed in overall PCS or MCS scores (p > 0.05).

multivariable linear regression

Multivariable linear regression analysis, adjusted for gender, age, BMI, chronic conditions, and smoking status, identified independent sociodemographic and clinical covariates of SF‑36 domains and summary scores (Supplementary Table 2). Variables with p < 0.20 in univariate analysis were entered into the models and retained using backward elimination. BMI showed a non-monotonic association with HRQoL domains relative to the underweight reference category (< 18.5 kg/m2). Normal-weight participants (18.5–24.9 kg/m2) had lower physical functioning (β = −16.3) and social functioning (β = −11.03) scores than the underweight participants, whereas those with an elevated BMI (≥ 25 kg/m2) exhibited a smaller reduction in physical functioning (β = −7.56) and social functioning (β = −10.02) scores compared with the underweight group.

The presence of chronic medical conditions was associated with lower role physical (β = −25.7), bodily pain (β = −11.8), and general health (β = −9.68) scores. Smoking was associated with lower mental health scores (β = −10.01). Prolonged daily transport time showed a dose-response pattern with poorer mental health outcomes (β = −15.3 for > 2 hours), lower social functioning (β = −17.96), and lower MCS scores (β = −12.5). Female sex was associated with higher role physical scores (β = 13.22). Model fit was strongest for the mental health domain, which showed the highest explained variance (adjusted R² = 0.41), followed by role physical (adjusted R² = 0.32) and physical functioning (adjusted R² = 0.28). In contrast, social functioning had lower explanatory power (adjusted R² = 0.22), suggesting that additional unmeasured factors may account for variability in this domain.

Discussion

This cross-sectional study found that health-related HRQoL was moderate among Aleppo University medical students, with physical domain scores exceeding mental domain scores on the Arabic SF-36. Multivariable analyses identified higher BMI, the presence of chronic medical conditions, current smoking, and prolonged daily time spent in transport as independent covariates of poorer physical and mental HRQoL. Higher self-reported religiosity was associated with better mental HRQoL in unadjusted analyses. The Arabic SF‑36 demonstrated acceptable internal consistency and construct validity for the physical and mental component summaries, although certain individual domains — particularly general health and vitality — showed suboptimal internal consistency. Sociodemographic, clinical, and environmental factors appeared to interact within the protracted war context, which is characterized by infrastructure damage and elevated psychological burdens [21].

Sociodemographic and gender influences

Household composition was not associated with HRQoL in this sample, in contrast to prior reports that parental co-residence may protect mental health through social support [22]. One possible explanation is that Syrian students may have developed adaptive responses to unstable living conditions arising from conflict-driven family displacements.

Gender effects were limited in the present cohort, with females reporting higher role physical scores, a pattern that differs from several prior studies reporting poorer HRQoL among female students. Domantay et al. reported lower vitality, role emotional, and general health scores among female students compared to males [6]. These patterns align with Philippine cultural norms that may discourage acknowledgment of physical or emotional limitations among males. Conversely, other studies have reported higher scores in the physical, psychological, and social domains among young women [23]. Multiple studies have found higher rates of stress, depression, anxiety, and lower psychological scores among female medical students [11, 24]. In the Syrian context, the higher role physical scores observed among females may reflect cultural expectations of physical resilience despite increased vulnerability to stress.

Commuting time and academic stressors

Daily commuting in excess of two hours was independently associated with lower mental health, reduced social functioning, and lower MCS scores. This association likely reflects severe commuting stress compounded by damaged road infrastructure, fuel shortages, and security concerns [25]. However, only 6.6% (n = 12) of students reported commuting durations exceeding two hours; the small size of this subgroup increases uncertainty around the estimated effect and warrants external validation. This finding aligns with literature linking prolonged commuting to social isolation and academic impairment in high-pressure educational settings [26, 27].

Measures of academic stressors were significantly associated with SF‑36 mental health domains. Notably, fourth-year medical students had the highest overall scores while exhibiting the lowest social functioning scores. This pattern may reflect an intensified from basic sciences to clinical training, which could reduce opportunities for social interaction and promote isolation as students adapt to clinical demands. Domantay et al. reported that fourth-year students had the lowest social functioning scores [6]. In contrast, a cross-sectional study found higher physical and mental HRQoL among students in advanced academic years [28]. Another study reported the highest quality of life among fifth-year students, attributing this finding to reduced curriculum demands and lower anxiety levels [29]. A Malaysian study of senior medical students linked depression and anxiety with lower scores in the psychological, social, and environmental domains [24]. These divergent findings highlight the importance of context-specific stressors during clinical transition periods.

Religiosity and mental health

Consistent with findings from Brazilian medical students [30], higher self-reported religiosity was univariately associated with higher MCS scores. Although spiritual beliefs have been associated with psychological resilience and mitigation of war-related trauma [31], this specific association should be interpreted cautiously. In this cohort, 94.5% (n = 171) identified as religious, leaving a very small non-religious comparison group (5.5%, n = 10). This marked sample asymmetry increases the risk of a type I error, particularly given the absence of multiple-comparisons corrections. Therefore, this observation should be considered preliminary and hypothesis-generating rather than definitive evidence of a cultural protective effect.

Clinical factors: BMI, smoking, and chronic conditions

The global obesity epidemic has intensified, with adiposity rates doubling in 70 countries over the past 25 years, primarily due to lifestyle changes [32]. Overweight prevalence among medical students was 19.7% in the United States [33], 21% in Pakistan [34], and 21.5% in the present cohort. However, direct comparisons with international cohorts require caution because of differences in socioeducational and environmental contexts. Students in the United States and Pakistan train within relatively intact educational systems with stable resources, whereas the single-center Syrian cohort faces prolonged conflict-related infrastructure disruption, acute financial strain, and pervasive daily transport challenges. Consequently, similar BMI prevalence across these geopolitical settings may reflect distinct factors — nutritional scarcity, altered activity patterns, and chronic stress responses — rather than uniform lifestyle mechanisms.

Consistent with studies linking excess weight to impaired daily activities and social participation in young adults [35], the present study found that normal and elevated BMI were associated with lower physical and social functioning scores compared with an underweight reference (< 18.5 kg/m2). Notably, the relationship was non-monotonic: normal-weight students (18.5–24.9 kg/m2) showed larger deficits in physical and social scores than underweight peers, whereas the overweight group (≥ 25 kg/m2) did not. This finding contrasts with Western literature, which typically reports a dose–response pattern, in which HRQoL declines incrementally as adiposity increases [36]. In the context of protracted conflict in Syria, the non-monotonic pattern may reflect unmeasured socioeconomic heterogeneity. This non-linear trend underscores that standard assumptions linking weight and well-being may not apply uniformly in populations living under acute, resource-scarce crises.

Smoking was negatively associated with mental health scores; this association may reflect nicotine dependence and increased anxiety in conflict-affected environments. Chronic medical conditions were associated with lower role physical, bodily pain, and general health scores. This effect was likely exacerbated by Syria’s degraded healthcare infrastructure, which limits effective chronic disease management. Szemik et al., using the World Health Organization Quality of Life – BREF (WHOQOL-BREF) questionnaire, reported reduced quality of life among patients with chronic diseases, which was associated with fatigue, weakness, and depressive symptoms [37]. These modifiable factors highlight opportunities for targeted interventions adapted to wartime constraints.

Conflict context in Syria

Since 2011, the armed conflict in Syria has disrupted medical education through attacks on facilities, faculty shortages, and frequent curriculum interruptions. As data were collected exclusively at Aleppo University, intense local conflict dynamics and regional infrastructure collapse likely exerted a localized effect on participants’ mental health. They may not reflect the experiences of medical students in more stable or differently affected regions of Syria. Such localized disruptions likely contributed to impaired mental HRQoL. Unmeasured confounders — particularly trauma exposure and individual resilience — likely contributed to the modest performance of the social functioning model, as indicated by an adjusted R² of 0.22. These findings extend prior research on the conflict-driven health system erosion and underscore the need for resilient educational strategies and targeted student support in conflict-affected settings.

Methodological considerations and internal consistency

Only four of eight SF-36 domains — physical functioning, role physical, role emotional, and bodily pain — met the conventional internal consistency threshold (Cronbach’s alpha ≥ 0.70). Internal consistency was low for general health (α = 0.467), vitality (α = 0.591), and mental health (α = 0.654). Suboptimal alpha values for general health and vitality have been reported in regional Arabic SF-36 validations and are often attributed to cultural variation in the interpretation of constructs such as health and fatigue. In a conflict-affected environment, the combination of academic pressures and environmental trauma may further destabilize item covariance patterns within subjective mental-state scales, producing additional measurement noise.

Because these domain-level vulnerabilities increase measurement error, caution is warranted when interpreting isolated multivariable associations involving the general health, vitality, and mental health subscales. In contrast, aggregation into the 14-item MCS (MCS) captured shared variance more effectively and demonstrated robust internal consistency (α = 0.834). This result supports the primary use of summary measures (MCS and PCS) to assess aggregate psychological and physical trends in this setting, while acknowledging the limited psychometric utility of certain standalone subscales.

The reduction in alpha coefficients from the pilot (where principal scales initially showed α ≥ 0.70) to the final sample reflects expected psychometric scaling effects. The pilot sample (n = 30) represented a narrow, localized cluster, while the final sample (N = 181) included broader sociodemographic variation, diverse academic tracks, and heterogeneous stress exposures. This broader variation increased response diversity and exposed semantic ambiguities in translated subscales. Consequently, lower internal consistency values were observed in the full cohort.

Several limitations of this study warrant consideration. The cross-sectional design precludes causal inference; observed relationships should be interpreted only as associations. Key predictors (BMI, chronic conditions, religiosity, and commuting) were self-reported and are subject to recall error, social-desirability bias, and measurement inaccuracy. As this study was exploratory, no adjustments were applied for multiple comparisons across the numerous univariate tests, increasing the risk of Type I error. Several statistically significant associations were observed in small subgroups (non-religious students, n = 10; former smokers, n = 7; commuters > 2 h, n = 12), resulting in low power and unstable estimates. These results should be regarded as hypothesis-generating. Omission of relevant conflict-related variables (including trauma exposure, economic hardship, social support, faculty shortages, and access to mental health care) likely reduced model explanatory power. Future research should employ longitudinal designs, include validated measures of mental health and trauma, consider confounder selection guided by causal diagrams, and apply multiple-comparison-controlling methods or present adjusted results alongside unadjusted values to improve inferential reliability.

Conclusion

Medical students at Aleppo University demonstrated moderate HRQoL, with higher scores in physical domains and lower scores in mental domains on the Arabic SF-36 questionnaire. Independent predictors of poorer HRQoL included higher BMI, the presence of chronic conditions, smoking, and daily transport durations exceeding two hours, while higher levels of religiosity were associated with better outcomes. In this conflict-affected cohort, the Arabic SF‑36 demonstrated acceptable internal consistency and a coherent component structure for the main summary scores and core physical subscales, although certain mental and general health domains showed notable item-level inconsistencies. These findings underscore the need for lifestyle modifications, structured psychological support programs, and infrastructural improvements within this institution. Future longitudinal, multicenter studies that incorporate detailed trauma exposure assessments are required to clarify causal relationships and to inform comprehensive well-being strategies for medical students.

Abbreviations

HRQoL

Health-related Quality of Life

SF-36

36-Item Short Form Health Survey

CME

Continuing Medical Education

BMI

Body Mass Index

IQOLA

International Quality of Life Assessment

PF

Physical Functioning

RP

Role Physical

BP

Bodily Pain

GH

General Health

VT

Vitality

SF

Social Functioning

RE

Role Emotional

MH

Mental Health

PCS

Physical Component Summary

MCS

Mental Component Summary

SD

Standard Deviation

IQR

Interquartile Range

WHOQOL-BREF

World Health Organization Quality of Life - BREF

Authors’ contributions

M.C: Conceptualization, methodology, investigation, data curation, writing original draft, writing review, and editing.A.Q: Investigation, visualization, writing original draft, writing review, and editing.M.K: Formal Analysis, visualization, writing original draft, writing review, and editing.B.A: Data curation, visualization, writing original draft.A.S: Supervision, validation, writing original draft, writing review, and editing.M.M.E: Supervision, validation, writing review, and editing.

Funding

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

Data availability

All relevant data are within the manuscript and its Supporting Information files. The datasets used and analyzed during the current study are available without restriction from the corresponding author (Ayham Qatza, ayhamqatza714@gmail.com).

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and received ethical approval from the Institutional Review Board of the University of Aleppo (registration number: 2403; ISRCTN14425442).

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.