Sleep quality, mental health, lifestyle factors, and academic performance among medical students in three Syrian Universities: a cross-sectional study

Abstract

Background

Sleep quality significantly impacts cognitive function and mental health, yet medical students globally report high rates of sleep disturbances. This cross-sectional study investigates the prevalence of poor sleep quality and its associations with mental health and academic performance among medical students in three Syrian universities.

Methods

An online survey was administered to 722 medical students from Kalamoon University, Al Sham Private University, and Syrian Private University. Validated tools, including `assessed sleep quality and psychological distress. Academic performance was measured via self-reported GPA. After exclusions, 682 participants were analyzed using SPSS v27, with chi-square tests and regression models (α = 0.05).

Results

Poor sleep quality (PSQI ≥ 5) was prevalent in 83.3% of participants, with significant variations across universities (p = 0.011). Sleep quality correlated with academic year (p = 0.037), physical inactivity (p = 0.001), unhealthy diet (p = 0.001), smoking (p = 0.001), and low academic attendance (p = 0.001). Poor sleepers exhibited higher depression (p = 0.001), anxiety (p = 0.001), and stress (p = 0.001) scores. No direct association emerged between sleep quality and GPA (p = 0.8). Preparatory-year students (OR = 0.355, p = 0.009), those with severe depression (OR = 0.537, p = 0.023), and severe stress (OR = 0.493, p = 0.034) were likelier to be low academic achievers.

Conclusion

Poor sleep quality is alarmingly high among Syrian medical students and strongly linked to mental health challenges and modifiable lifestyle factors. Academic performance (GPA) showed no direct relationship with sleep quality, stress and depression .Targeted interventions promoting sleep hygiene, physical activity, and mental health support are urgently needed. Further longitudinal studies should explore causal pathways and cultural influences on sleep behaviors.

Background

Since sleep is essential for physical and mental well-being as well as cognitive functioning .sleep deprivation can negatively affect medical students’ academic performance [1]. Sleep quality is a multidimensional construct that includes both quantitative objective and subjective aspects of sleep [2, 3]. Adults are generally recommended to sleep between 7 and 9 h per night, while teenagers require approximately 9.5 h, deviations from these ranges may indicate disturbances in the sleep-wake cycle and can contribute to the development of sleep disorders and psychopathologies [4]. Sleep disorders have become a prevalent health issue globally, with their incidence increasing annually [5]. Large-scale studies conducted across diverse socio-cultural contexts have consistently demonstrated a high prevalence of poor sleep quality and sleep disorders among medical students [6–9]. Moreover, high levels of stress, which are common in medical students, have been shown to adversely affect both their physical and mental health [10]. Stress can impair cognitive functions such as concentration and memory, leading to poorer academic performance [11].

Despite the well-documented benefits of sufficient sleep, medical students often develop poor sleeping habits, especially during periods leading up to examination [1], they are more vulnerable to poor sleep quality compared to non-medical students due to the prolonged duration and high intensity of their study schedules [10, 12, 13].

Among the instruments used to assess sleep quality, the Pittsburgh Sleep Quality Index (PSQI) is widely recommended for measuring global sleep quality and insomnia symptoms [9].

From a Syrian perspective, understanding medical students ‘sleep quality and its relationship with their academic performance is crucial due to the unique socio-political and educational challenges they face. Therefore, this study aims to evaluate the association between sleep quality and academic performance among medical students in Syrian universities.

Methods

This cross-sectional study was conducted online among medical students at three private Syrian universities: the University of Kalamoon (UOK), Al Sham Private University (ASPU), and the Syrian Private University (SPU). Prior to data collection, the research protocol was reviewed and approved by the respective research and ethics committees of each participating university. Data were collected over a 3-week period (June 30–July 20, 2024), which corresponded to a non-examination period, to minimize potential fluctuations in sleep patterns related to academic stress.

To ensure broad dissemination, local collaborators at each institution distributed the survey link through social media platforms and direct messaging to their classmates and student networks. Participation was voluntary, and the online questionnaire began with an introductory section explaining the study’s purpose, followed by an informed consent form. Participants were informed that they could withdraw at any time without penalty, and anonymity and confidentiality were guaranteed. The survey required approximately 10 min to complete.

The study employed a convenience, non-probability sampling approach, which may have introduced selection and volunteer biases, limiting the generalizability of findings beyond these institutions and the socioeconomic strata typical of private universities.

Inclusion criteria were:

1. Being a currently enrolled medical student at one of the three aforementioned universities.

2. Being 18 years of age or older.

Exclusion criteria were:

1. Having a chronic medical condition (e.g., self-reported asthma, diabetes mellitus, or hypertension).

2. Having self-reported diagnoses of sleep or mental health disorders (such as depression, anxiety, or insomnia), or currently receiving treatment for such conditions.

3. Responses with substantial missing or inconsistent data (e.g., incomplete sections on sleep quality, mental health, or GPA).

A total of 722 students completed the questionnaire. After applying the exclusion criteria, 40 participants were removed (28 were under 18 years of age, 5 reported chronic illnesses, 4 omitted key sections, and 3 provided blank or contradictory responses). Thus, 682 valid responses were included in the final analysis.

Both standardized instruments used—the Pittsburgh Sleep Quality Index (PSQI) [14] and the Depression, Anxiety, and Stress Scale (DASS-21) [15]—had previously demonstrated acceptable internal consistency in this sample (Cronbach’s α = 0.73 for PSQI; α = 0.81 for DASS-21). To ensure semantic equivalence and cross-cultural comparability, the Arabic versions used in this study were those that had undergone linguistic and cultural validation in prior regional research.

Questionnaire contents

The questionnaire consisted of several sections. The first section collected socio-demographic data, including gender, physical health status, smoking habits, screen time, and living conditions. A full summary of these variables is presented in Table 1.

Table 1.

The table shows a summary of demographic and lifestyle factors (*The results are statistically significant (p < 0.05))

	Good	Poor	P value
	Sleepers (n = 114)	Sleepers (n = 568)
Gender			0.147
Male	41(36%)	247(43.5%)
Female	73(64%)	321(56.5%)
Academic year			0.037*
PYP	1.8%	5.5%
Preclinical years	34.2%	42.3%
Clinical years	64.0%	52.3%
Dietary habits			< 0.001*
Unhealthy	28.1%	51.2%
Healthy	71.9%	48.8%
Physical activity			0.001*
Inactive	22.8%	38.7%
Active	77.2%	61.3%
Smoking			< 0.001*
No	93.9%	77.1%
Yes	6.1%	22.9%
Screen time			0.181
Up to 5 h	36.0%	35.4%
Five to 10 h	59.6%	54.9%
More than 10 h	4.4%	9.7%
Quran reading			0.540
No	50.0%	46.8%
Yes	50.0%	53.2%
Living condition			0.056
Alone	18.4%	25.2%
Roommate	9.6%	14.8%
Family	71.9%	60.0%
Attendance			< 0.001*
Irregular	7.0%	22.7%
Regular	93.0%	77.3%
Teamwork			0.462
All the time	11.4%	8.3%
Sometimes	71.1%	71.0%
Not at all	17.5%	20.8%
GPA
High	80.7%%	79.4%
Low	19.3%	20.6%
University			0.011*
Kalamoon Private University	7.9%	19.5%
Syrian Private University	52.6%	47.4%
Private Alsham University	39.5%	33.1%

To assess sleep quality and psychological distress, two widely validated instruments were used:

1. The Pittsburgh Sleep Quality Index (PSQI) [14], which evaluates sleep disturbances and overall sleep quality over the past month. The global PSQI score ranges from 0 to 21. A score of ≥ 5 indicates poor sleep quality, while a score < 5 denotes good sleep quality.

2. The Depression Anxiety Stress Scales (DASS-21) [15], which consists of 21 items divided equally among three subscales: depression, anxiety, and stress. Each item is rated on a 4-point Likert scale (0 = did not apply to me at all; 3 = applied to me very much or most of the time). Each subscale yields a score from 0 to 21 and classifies participants into normal, mild, moderate, severe, or extremely severe categories using standardized cutoff values [16].

Although the instruments employed in this study (PSQI and DASS-21) are widely recognized and validated, internal consistency was assessed within the current sample, yielding Cronbach’s alpha coefficients of 0.73 for the PSQI and 0.81 for the DASS-21, reflecting acceptable to good reliability.

Academic performance was assessed via self-reported GPA, where participants were asked to report their precise GPA for the previous academic year. While GPA is a commonly used measure of academic achievement in research [17–19], it is important to acknowledge that self-reported GPA may be subject to recall bias, social desirability bias, and inconsistencies in GPA scales between institutions. Therefore, interpretations based on GPA should be viewed with caution.

In line with the scholarship criteria applied by the universities included in this study, a GPA of 2.5 was considered the minimum requirement for satisfactory academic performance. Based on this cutoff, participants were categorized into two groups:

• High achievers (GPA ≥ 2.5).

• Low achievers (GPA < 2.5).

Data analysis

Statistical analysis was conducted using IBM SPSS Statistics software (version 27 for Windows 10). A p value of < 0.05 was considered statistically significant. Descriptive statistics (frequencies and percentages) were used to summarize participants’ socio-demographic characteristics and survey responses.

To examine associations between sleep quality, mental health variables, and academic performance, we employed a combination of statistical tests. The chi-square (χ²) test was used to assess associations between categorical variables. We first conducted bivariate analyses to explore potential associations between each predictor (sleep quality, stress, anxiety, depression) and academic achievement (categorized as high vs. low GPA).

Subsequently, we performed binary logistic regression to identify independent predictors of low academic achievement, controlling for potential confounders. Variables that showed significance in the bivariate analysis (p < 0.05) were included in the multivariate regression model. This allowed us to examine the adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) for each factor.

Given the lack of a direct association between sleep quality and GPA, but a significant relationship between mental health variables (stress, depression) and GPA, we interpreted these findings in the context of possible mediating or confounding effects, which are further discussed in the discussion section.

Results

Socio-demographic characteristics

The results showed significant differences between good and poor sleepers across several factors. Clinical year students were more likely to have good sleep compared to preclinical years (p = 0.037). Healthy dietary habits were strongly associated with good sleep (71.9% vs. 48.8%, p < 0.001). Physical activity was also higher among good sleepers (77.2% vs. 61.3%, p = 0.001). Smoking was significantly more prevalent among poor sleepers (22.9% vs. 6.1%, p < 0.001). Regular class attendance was more common in good sleepers (93.0% vs. 77.3%, p < 0.001). Moreover, university type showed a significant association, with Kalamoon Private University students reporting more poor sleep (p = 0.011). In contrast, no significant differences were observed for gender (p = 0.147), screen time (p = 0.181), Quran reading (p = 0.540), living conditions (p = 0.056), or teamwork (p = 0.462).

(Table 1 shows a summary of demographic and lifestyle factors.)

Academic performance

The majority of students (80%) reported regular attendance at academic events, and 71% enjoyed participating in group academic activities. High achievers (GPA ≥ 2.5) constituted 80% of the sample, while low achievers (GPA < 2.5) represented 20%. The universities showed significant differences in sleep quality: the proportions of good sleepers were 7.9%, 52.6%, and 39.5% at Kalamoon Private University, Syrian Private University, and Al Sham Private University, respectively; poor sleepers accounted for 19.5%, 47.4%, and 33.1% in these universities.

Subjective sleep quality (PSQI)

PSQI scores ranged from 1 to 19, with a mean of 7.82 (SD = 3.365). Only 16.7% of students were classified as good sleepers (PSQI < 5). Sleep quality was significantly associated with academic year (P = 0.037), dietary habits (P = 0.001), physical activity (P = 0.001), smoking status (P = 0.001), academic event attendance (P = 0.001), and university (P = 0.011). However, no significant association was found between sleep quality and GPA (P = 0.8). Gender, screen time, Quran reading, and living conditions did not differ significantly between good and poor sleepers.

(Table 1 presents significant differences in sleep quality across demographic, lifestyle, and academic variables.)

Depression anxiety stress scales (DASS-21)

The results indicate strong associations between sleep quality and psychological factors. For depression, good sleepers were more likely to fall within the normal range (58.8% vs. 22.4%), whereas poor sleepers reported higher rates of severe (13.2% vs. 4.4%) and extremely severe depression (22.5% vs. 1.8%) (p < 0.001). Similarly, anxiety levels differed significantly (p < 0.001): normal anxiety was more common among good sleepers (59.6% vs. 28.0%), while severe (10.9% vs. 2.6%) and extremely severe anxiety (27.1% vs. 6.1%) were notably higher among poor sleepers. Stress also showed a significant association (p < 0.001). Normal stress was reported by 79.8% of good sleepers compared to 39.8% of poor sleepers, while severe (16.9% vs. 4.4%) and extremely severe stress (13.0% vs. 0.9%) were substantially higher in poor sleepers. Overall, poor sleep was consistently linked with more severe depression, anxiety, and stress.

(Table 2 displays the relationship between sleep quality and DASS-21 scores.)

Table 2.

The table displays the significance values of subjective sleep quality compared to the DASS-21 (*The results are statistically significant (p < 0.05))

	Good	Poor	P value
	Sleepers (n = 114)	Sleepers (n = 568)
Depression			< 0.001*
Normal	58.8%	22.4%
Mild	14.0%	16.9%
Moderate	21.1%	25.0%
Severe	4.4%	13.2%
Extremely severe	1.8%	22.5%
Anxiety			< 0.001*
Normal	59.6%	28.0%
Mild	12.3%	7.4%
Moderate	19.3%	26.6%
Severe	2.6%	10.9%
Extremely severe	6.1%	27.1%
Stress			< 0.001*
Normal	79.8%	39.8%
Mild	10.5%	12.5%
Moderate	4.4%	17.8%
Severe	4.4%	16.9%
Extremely severe	0.9%	13.0%

Predictors of academic performance

Univariate analysis showed that academic year, severity of depression, and severity of stress were significantly associated with academic achievement. Preparatory-year students were less likely to be high achievers compared to preclinical students (OR = 0.355, P = 0.009). Similarly, students with extremely severe depression were less likely to be high achievers compared to those with moderate depression (OR = 0.537, P = 0.023). Students with severe stress were also less likely to be high achievers compared to those with moderate stress (OR = 0.493, P = 0.034). In the multivariate regression model, the effects of gender, age, GPA, and Quran reading remained relatively stable. The full regression model is provided in Table 3.

Table 3.

The regression model is given in this table (*The results are statistically significant (p < 0.05))

	Univariate		Multivariate
	OR	95% CI	OR	95% CI
Academic year
PYP	0.355(P = 0.009)*	0.163–0.770	0.348(P = 0.011)*	0.155–0.784
Clinical year	0.734(P = 0.130)	0.493–1.095	1.391(P = 0.268)	0.776–2.495
Preclinical year	1	Ref	1	Ref
Sleep quality
Poor sleep	0.922(P = 0.753)	0.555–1.531	0.917(P = 0.739)	0.549–1.531
Good sleep	1	Ref	1	Ref
Depression
Normal	1.305(P = 0.340)	0.755–2.258	1.327(P = 0.316)	0.763–2.308
Mild	1.099(P = 0.766)	0.592–2.039	1.103(P = 0.758)	0.591–2.057
Moderate	1	Ref	1	Ref
Severe	0.885(P = 0.717)	0.457–1.712	0.932(P = 0.836)	0.476–1.823
Extremely severe	0.537(P = 0.023)*	0.314–0.918	0.540(P = 0.026)*	0.314–0.928
Anxiety
Normal	1.198(P = 0.505)	0.705–2.034	1.267(P = 0.388)	0.741–2.166
Mild	0.597(P = 0.153)	0.294–1.211	0.606(P = 0.170)	0.297–1.239
Moderate	1	Ref	1	Ref
Severe	0.570(P = 0.099)	0.292–1.112	0.547(P = 0.081)	0.278–1.077
Extremely severe	0.660(P = 0.123)	0.389–1.120	0.641(P = 0.104)	0.376–1.095
Stress
Normal	1.018(P = 0.952)	0.573–1.807	1.041(P = 0.893)	0.580–1.868
Mild	0.990(P = 0.979)	0.469–2.091	0.949(P = 0.892)	0.446–2.019
Moderate	1	Ref	1	Ref
Severe	0.493(P = 0.034)*	0.257–0.947	0.481(P = 0.030)*	0.249–0.930
Extremely severe	0.692(P = 0.319)	0.335–1.429	0.664(P = 0.275)	0.319–1.384

Discussion

The primary objective of this study was to evaluate the prevalence of poor sleep quality among medical students in Syria. The findings indicated that approximately 83.3% of the students were classified as poor sleepers. Among the three universities, Kalamoon University had the highest proportion of poor sleepers, followed by Al-Sham University, while the Syrian Private University (SPU) had the lowest. These figures are considerably higher than those reported in other Middle Eastern countries, such as 37.1% in Lebanon [20] and 55.7% in Egypt [21].

However, these prevalence estimates should be interpreted cautiously due to potential selection bias inherent in the online, convenience sampling approach, and the exclusion of students with prior sleep or mental health diagnoses, which may have actually reduced the estimated prevalence.

Another aim of the study was to explore the relationship between sleep quality and various factors, including academic performance, academic year, dietary habits, smoking status, attendance, and levels of stress, anxiety, and depression. The results demonstrated that good sleepers were significantly more likely to engage in physical activity compared to poor sleepers (p = 0.001), supporting findings from other studies which have shown a bidirectional relationship between physical activity and sleep quality [22]. Furthermore, good sleepers were more likely to maintain healthier dietary habits (p = 0.001), consistent with literature suggesting correlations between sleep quality and certain macronutrients and micronutrients [23, 24].

Smoking was another variable that significantly affected sleep quality. Good sleepers were more likely to be non-smokers (p = 0.001), which aligns with evidence indicating the negative effects of nicotine on the central nervous system, such as contributing to insomnia, neurodegenerative changes, and cerebrovascular risks [24]. Additionally, good sleepers were more commonly found among students in higher academic years (p = 0.037) and those who reported higher attendance in academic activities (p = 0.001), possibly reflecting more structured schedules and better time management skills.

In contrast, poor sleepers exhibited higher scores in depression, anxiety, and stress. These findings are consistent with other research suggesting a strong link between poor sleep and mental health disturbances [20, 21]. In our study, moderate levels of depression, anxiety, and stress were reported in 24.3%, 11.73%, and 15.54% of students respectively, while severe levels were observed in 11.73%, 8.2%, and 10.99%. These rates appear lower than those documented in a study from Egypt, where depression, anxiety, and stress affected 65%, 73%, and 59.9% of students, respectively [21].

Interestingly, no significant association was found between GPA and sleep quality in our sample (p = 0.8). This might be due to compensatory behaviors among medical students, such as prolonged study hours, caffeine consumption, and strategic napping to counterbalance the effects of poor sleep [25, 26]. These suggestions are speculative and should be empirically tested in future studies, potentially using formal mediation analyses or structural equation modeling (SEM) with bootstrap to assess whether depression and stress mediate the relationship between sleep and academic performance.The mention of compensatory behaviors, such as extended study hours or caffeine use, was intended as a plausible explanatory hypothesis rather than a confirmed mechanism .These suggestions are speculative and are proposed as avenues for future research to be empirically investigated. This finding contradicts some regional studies, including one in Saudi Arabia that reported higher academic performance among students with poor sleep habits [27]. One potential approach to contextualize these findings is through the theory of allostatic homeostasis, which conceptualizes sleep as an adaptive regulator whose disruption imposes physiological overload, subsequently contributing to psychological and academic vulnerability. Another valuable perspective is the effort-reward imbalance theory applied to student life, which elucidates how excessive academic demands can disrupt rest rhythms and, through psychosocial strain, impair learning outcomes.

The data suggest that sleep should be understood as a relational phenomenon, intertwined with cultural practices, coping habits, and high-uncertainty academic environments. From this perspective, the lack of a direct association with GPA may reflect students’ use of compensatory strategies—such as caffeine consumption, extended study hours, and strategic napping—to maintain academic performance. This does not negate the impact of sleep per se, but rather shifts its primary effect onto the emotional and psychological domain [25–27].

This discrepancy may be partially attributable to the reliance on self-reported GPA, which is subject to recall and social desirability biases. Additionally, compensatory behaviors among medical students, such as extended study hours, caffeine intake, and strategic napping, may mitigate the impact of poor sleep on academic performance. These factors, combined with potential measurement limitations, should be considered when interpreting the results.The reliance on GPA as the sole indicator of academic performance presents important limitations. Academic achievement is a multidimensional construct that extends beyond numerical grades to encompass aspects such as deep learning, long-term knowledge retention, critical thinking, and clinical competence. Evaluating performance solely through GPA may therefore overlook these crucial dimensions and provide an incomplete understanding of students’ true academic abilities. It is essential to acknowledge the cultural and political context affecting Syrian students. Factors such as ongoing socio-political instability, economic hardship, and disrupted educational infrastructure may significantly shape study habits, mental health, and academic outcomes. Recognizing these contextual influences allows the findings to move beyond simple percentage comparisons with neighboring countries, offering a richer and more analytically meaningful interpretation of the data.

Additionally, our study did not find a statistically significant relationship between sleep quality and gender, screen time, Quran reading, or living conditions.

Finally, in evaluating predictors of academic performance, students in the preclinical years performed better than those in the preparatory year, and a significant association was found between academic performance and levels of depression and stress, but not anxiety. These results reinforce the detrimental impact of emotional distress on academic outcomes, consistent with prior research [28].

Conclusion

This cross-sectional study identified a high prevalence of poor sleep quality (83.3%) among medical students from three Syrian universities, exceeding rates reported in neighboring countries. Poor sleep was more common among students in lower academic years and those with physical inactivity, unhealthy eating habits, smoking, or irregular class attendance. No significant association was found between sleep quality and GPA, which may be influenced by unmeasured compensatory behaviors such as extended study hours or stimulant use.

Poor sleep quality was also linked to higher levels of depression, anxiety, and stress, highlighting the multifaceted relationship between lifestyle and mental well-being in demanding academic settings.

Universities may consider promoting programs that encourage healthy sleep practices, regular exercise, balanced nutrition, and mental health awareness. These recommendations should be viewed as preliminary, given the cross-sectional design, which precludes causal inference. Future longitudinal or interventional studies are needed to clarify temporal relationships and assess the impact of targeted strategies on sleep and psychological health among university students.

While the article contains useful comparative elements, practical implications, and theoretical mechanisms, a more explicit acknowledgment of potential selection bias, information bias from self-reports, and the speculative nature of compensatory mechanisms strengthens the interpretive validity. Future work should adopt longitudinal or mediation models to formally test these pathways.

Limitations

It can be stated explicitly that the institutional recommendations derived from this study are based on observed associations, and their effectiveness should be evaluated in longitudinal or experimental studies. Additionally, if the aim is to generalize the absence of a sleep–GPA association, it is important to harmonize academic performance metrics across institutions, given potential variability in grading standards.

This cross-sectional study cannot support causal inferences, and all interpretations regarding the relationship between sleep quality, mental health, and academic performance should be framed as associative rather than causal.

This study has several limitations. First, its cross-sectional design precludes causal inferences regarding the relationships between sleep quality, mental health, and academic performance. Second, reliance on self-reported data may have introduced recall or social desirability biases, particularly for sleep habits, GPA, and psychological distress. Third, the sample was limited to three private Syrian universities, restricting the generalizability of findings to broader populations or different cultural contexts.

Regarding the sample, convenience sampling limits generalization and should be explicitly acknowledged as a methodological constraint. Furthermore, the exclusion of students with chronic medical conditions may have further narrowed the applicability of the results.

Although the sample size was relatively large, non-random recruitment via local collaborators could have introduced selection bias. Furthermore, GPA was used as the sole measure of academic performance, which does not capture other influencing factors such as teaching quality, personal motivation, or socioeconomic background. We acknowledge the limitations of using self-reported GPA as the sole indicator of academic performance, including potential recall and social desirability biases and inter-university variability in grading standards. While no alternative objective measures were available for this study, we ensured data quality through careful verification of responses and emphasize that interpretations of academic outcomes were made with caution, acknowledging these constraints on internal validity.

Moreover, compensatory behaviors (e.g., caffeine consumption, strategic napping), which might mediate the relationship between sleep and GPA, were not directly assessed, making such interpretations speculative. The potential impact of cultural factors on the interpretation of standardized tools such as the PSQI and DASS-21 was not evaluated, possibly affecting response validity. Lastly, unmeasured confounders, including genetic predispositions or environmental stressors, may have influenced the observed associations.

Future research should explicitly consider longitudinal designs, incorporate objective sleep measurements (e.g., actigraphy), and include more diverse and representative samples to enhance validity and generalizability.

Author contributions

M.S., B.S., A.O.: study design. M.S.: data analysis and results. H.A.,Z.M., S.E.,Me.N., S.A., M.N.: interpretationof the results. SH.A., Seb.A.,F.A. Saj.A. Rim. A., Sara. S., T.A., A.O., Masa, A., R.K. : drafting the manuscript. M.S. , R.Alj., B.A., B.S.: critical revision. M.S.: supervision. All authors read and approved the final version of the manuscript.

Funding

Not applicable.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board (IRB) of the Faculty of Medicine at Hama University and Syrian Private University, in accordance with the Declaration of Helsinki. All participants provided informed consent before participation.

Consent for publication

All participants gave their consent for the anonymous publication of their data.

Competing interests

The authors declare no competing interests.