Assessment of Sleep Quality and Depression among Medical Students: A Cross-Sectional Study

Assessment of Sleep Quality and Depression among Medical Students: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of Sleep Quality and Depression among Medical Students: A Cross-Sectional Study Taleb Alsalloum, Abdallah Alawaisheh, Asma Daoud, Asmaa Alnajjar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5453920/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Objective Medical students are especially vulnerable to sleep disturbances and depression due to intense academic pressures and demanding schedules. Yet, the interplay between these issues remains underexplored in the Middle East and North Africa (MENA) region. This study aims to determine the prevalence of poor sleep quality and depression among medical students in the MENA region. It also aims to analyze the relationship between these factors, offering insights that could help improve their overall well-being. Methods In this study, 773 medical students from Palestine, Algeria, Egypt, Syria, Yemen, and Jordan participated. The questionnaire, also filled out by each student, consisted of demographic and lifestyle data, the Beck Depression Inventory (BDI), and the Pittsburgh Sleep Quality Index (PSQI). BDI assesses the level of depression, while PSQI assesses sleep quality. Results A total of 773 medical students participated in the study. There was a significant correlation between sleep quality and depression level (Spearman’s rho = 0.920, p < 0.001). The average PSQI was 6 and the average BDI score was 15. The results identified that 51.5% of all respondents reported poor sleep quality and around 71.3% had depressive symptoms. Conclusion This study reveals a robust association between poor sleep quality and depression among medical students in the MENA region, highlighting significant repercussions for both academic performance and overall well-being. In response, academic institutions must prioritize the implementation of targeted mental health initiatives, integrate comprehensive sleep hygiene education into their medical curricula, and develop culturally sensitive support systems. Furthermore, collaboration between universities and regional policymakers is crucial to establish sustainable strategies that bolster not only student health but also the resilience of the broader healthcare system. Sleep quality Medical education Public health Depression Figures Figure 1 INTRODUCTION Adequate sleep is essential for both mental and physical well-being [ 1 ]. However, poor sleep and depression significantly impair the mental health and overall well-being of medical students [ 2 ]. The rigorous demands of medical education, which include long hours of study, strenuous work schedules, and intense competition, contribute to heightened risks of sleep disturbances and depression [ 3 ]. Sleep deprivation impairs cognitive functions such as memory, attention, and overall mental clarity, thereby hindering both academic performance and personal well-being [ 4 ]. As Curcio et al. observed, the quality and quantity of sleep are key factors influencing learning and academic success among students [ 5 ]. The prevalence of poor sleep quality among medical students has been reported in various countries, including India (49.16%), Ethiopia (62%) and Yemen (68%) [ 1 , 6 , 7 ]. Key factors influencing sleep quality include gender, academic level, and socioeconomic status [ 8 ]. While certain studies have found that female medical students report poorer sleep quality compared to their male counterparts, other research emphasizes that these gender differences vary based on context-specific factors such as stress intensity, hormonal fluctuations, and cultural expectations [ 9 , 10 ]. Moreover, sleep quality often declines with advancing academic level, and students from lower socioeconomic backgrounds typically experience more pronounced sleep disturbances [ 11 – 14 ]. In addition to sleep disturbances, depression is a prevalent mental health issue among medical students, marked by persistent sadness, loss of interest in activities, and a wide range of emotional and physical symptoms [ 15 ]. A meta-analysis by Long Zhail et al. found that individuals who sleep less than or more than the recommended 7–9 hours per night are more likely to experience depressive symptoms than those with normal sleep patterns [ 16 ]. Similarly, Perotta et al. demonstrated that medical students with higher depression scores also report greater daytime sleepiness [ 3 ]. Despite extensive investigations into sleep quality and mental health among medical students globally, studies specifically focusing on the Middle East and North Africa (MENA) region remain scarce [ 17 ]. This gap highlights the need for region-specific studies to understand how cultural, academic, and socio-economic factors influence sleep quality and depression in medical students from MENA countries, such as Jordan, Syria, Algeria, Palestine, Egypt, and Yemen. This study seeks to fill this gap by examining the intersection of sleep disturbances and depression in medical students across these countries, with a focus on how socio-demographic factors impact these outcomes. Therefore, this study aims to answer the following research question: To what extent do sleep disturbances correlate with depressive symptoms among medical students in MENA countries, and how do socio-demographic factors such as gender, academic level, and socioeconomic status moderate this relationship? METHODS Study design This was an online, multicenter, cross-sectional study that targeted medical students from Algeria, Egypt, Syria, Jordan, Palestine, and Yemen and was conducted in April and May 2024. The study initially adopted a convenience sampling technique, obtaining information from medical students who were readily available and willing to participate. This method was chosen for its simplicity and ease of access, allowing rapid data collection. However, convenience sampling may introduce selection bias since participants might not fully represent the broader medical student population. To augment the sample diversity, snowball sampling was subsequently employed, where initial participants referred other medical students likely to be interested in the study. This approach helps broaden the participation but may also lead to network bias, as recruits could share similar characteristics or be confined to the same social circles. By combining these methods, we aimed to maximize data collection; however, the non-probability nature of these techniques limits the generalizability of our findings, which should be considered when interpreting the results. A target of a minimum of 384 participants was set after calculating the required sample size using the following equation: A target minimum of 384 participants was set after calculating the required sample size using the following equation: N = (z^2 * p * q) / d^2 Where N is the sample size, z is the reliability coefficient, which is equivalent to 1.96 to get a 95% coefficient of confidence, p = 0.5 to get the largest sample size, this is the expected proportion, q = 1 – p = 0.5 and d = 0.05 the maximum acceptable error margin. [ 18 ] However, a much larger sample was obtained, with 773 in number, which increased the statistical strength of this study. We used the STROBE cross-sectional reporting guidelines [ 19 ]. Materials and data collection In this study, data were collected through an online self-completed questionnaire, which was simultaneously in Arabic and could be completed by any participant residing anywhere with an internet connection. Students were urged to complete the survey via different social media channels and platforms of the universities, students’ groups in Telegram, mailing lists containing students, etc. The data were collected without any identification information of the subjects involved in the study. It has to be pointed out that all the respondents were volunteering, and no gifts, discounts, or other types of incentives were to be offered. The instruments used in this study were the Pittsburgh Sleep Quality Index (PSQI) and the Beck Depression Inventory (BDI). Recognizing the linguistic diversity and dialectal variations across countries in the Middle East and North Africa (MENA) region, the survey was conducted in Arabic with careful consideration of these differences. Each author was personally engaged in the dissemination of the survey and the adaptation to the local dialects of their respective countries. The questions were meticulously translated and culturally adapted to ensure that the original meanings were preserved across different dialects and cultural contexts. This process aimed to enhance the clarity and relevance of the survey, facilitating better understanding among participants. The adapted questionnaires were then retested for content validity by a panel of experts from the MENA region. This panel assessed the translated items for linguistic clarity, cultural appropriateness, and conceptual equivalence to the original instruments. Before the main study, the instruments were piloted on 25 medical students to evaluate their comprehensibility and reliability. Data collected from this pilot study were not included in the final analysis. The questionnaire comprised a section for demographic data and the following standardized instruments: Pittsburgh Sleep Quality Index (PSQI): The PSQI is one of the most frequently utilized self-administered questionnaires that assess sleep quality and its interruptions [ 20 ]. It comprises 19 individual items, assembled into seven component scores: self-reported sleep quality, sleeping amount of activity, total night’s sleep, habitual sleep efficiency, nighttime awakenings, prescription sleep medications, and daytime impairment. Every factor is assessed using the scale of figures ranging from 0 to 3, in which Fig. 3 denotes the worst possible scenario. The scores of the seven components are then added up to obtain the global PSQI score, which ranges from 0–21. The global PSQI score was used, where a higher value of the score indicated poorer sleep quality. Thus, a PSQI global score above 5 was considered as poor sleep quality and a PSQI global score of 5 or below was considered as good sleep quality. It was also gauged that the reliability of the scale was high as noticed from Cronbach’s alpha, which was 0. 886. Beck Depression Inventory (BDI): BDI is a well-known self-completed 21-item scale that measures the level of depressive symptoms in adolescents and adults [ 21 ]. They bring four statements each corresponding to one of the symptoms of depression, something like pessimism, guilt, loss of appetite, and so on. These statements are extended to observe the severity level and respondents chose that statement which describes their feelings in recent days. They get indices from 0 to 3, and higher numeration reflects more severe depressive symptoms. The BDI points total all 21 items, ranging from 0 to 63. The interpretation of BDI scores is as follows: score range: 0 to 9 points No depression; 10 to 18 points Mild depression; 19 to 29 points Moderate depression; 30 to 63 points Severe depression. Inner consistency was checked by way of Cronbach’s Alpha reliability coefficient of 0.891 . Arabic versions of the PSQI and BDI that have been previously translated and normed were employed in this study [ 22 , 23 ]. Ethical consideration Prior to participation, informed consent was obtained from all participants. The procedures of this study complied with the ethical standards outlined in the Declaration of Helsinki. Ethical approval was granted by the Institutional Review Board (IRB) of Al-Balqa Applied University (Approval No. 26/3/2/1279) and the ethical committees of the universities in the six participating countries. Participants received detailed information about the study's purpose, procedures, potential risks and benefits, and assurances of confidentiality. Before completing the questionnaire, they provided consent by agreeing to an assent form, affirming that they met the eligibility criteria and were willing to partake in the research. They were informed that their participation was voluntary and that they had the right to withdraw from the study at any time without penalty. All personal data were kept confidential and securely stored, with results reported in aggregate form to protect individual identities. Data were anonymized by assigning codes to each participant, and all electronic data were stored on a secure, password-protected server accessible only to the research team. The collected data will be used solely for research purposes. Additionally, participants were encouraged to ask any questions they had about the study, and they received comprehensive answers to ensure they fully understood before providing consent. Compliance with national regulations and ethical guidelines in each participating country was maintained throughout the research. Statistical analysis To test the research questions and hypotheses, the data were analyzed by employing Jamovi version 2.3.28. Assessment of Data Normality: Data normality was evaluated using the Shapiro-Wilk test. Given that the test yielded a p-value below 0.05, we concluded that the continuous variables did not follow a normal distribution. As a result, non-parametric methods were deemed more appropriate for subsequent analyses. Descriptive Statistics: For non-normally distributed continuous variables, descriptive statistics are reported as the median accompanied by the interquartile range (IQR). Group Comparisons: To compare non-normally distributed continuous variables across more than two groups (e.g., country income level, hours of social media use, caffeine consumption, napping habits, and age), the Kruskal-Wallis test was employed. For comparisons involving two groups (e.g., gender, education level, residency area, place of living, and sleep cycle), the Mann-Whitney U test was used. Addressing Confounding Factors: To investigate the relationship between sleep quality and depression, a linear regression analysis was conducted with the PSQI as the dependent variable and the BDI as the independent variable. This model allowed us to control for potential confounding variables by including them as covariates. Each confounder was evaluated to ensure that it met the underlying assumptions of linear regression, such as linearity, independence, and homoscedasticity. The regression coefficient (β) provided insight into the magnitude of the association, while the accompanying p-value determined its statistical significance. RESULTS Demographics Our cross-sectional study aims to explain the prevalence and connection between sleep quality and depression within the target medical students. The sample size of our study was 773 individuals, and most participants were 21–25 years old (64.8%). The identified proportion of females compared to males was 64.2% and 35.8%, respectively. Most participants were distributed between preclinical and clinical with a difference of 49.9% and 50.1%, respectively. The countries where our participants came from are Palestine 14.1%, Egypt 14.5%, Algeria 20.1%, Jordan 20.4%, Syria 15.1%, and Yemen 15.8%. Most students living in urban areas make up 74.9% of the population and are in the middle of family income, 78.8%. The percentage of students living with families and on-campus housing is 78.4% and 21.6% respectively. Examining lifestyle patterns, an overwhelming majority allocate roughly three or more hours daily to social media engagement (69.9%) and often consume caffeine once or twice daily (46.8%). With occasional nappers representing 52.4% of the group, sleep is most common at night for almost three-quarters of participants (74.6%) (Table 1 ). Table 1 Sociodemographic and behavioral characteristics Variable Total Good sleep (N = 375) Poor sleep (N = 398) No Depression (N = 222) Mild depression (N = 251) Moderate depression (N = 194) Severe depression (N = 107) N (%) N (%) N (%) N (%) N (%) N (%) N (%) Country Algeria 155 (20.1%) 68 (8.8%) 87 (11.3%) 32 (4.1%) 53 (6.9%) 42 (5.4%) 28 (3.6%) Egypt 112 (14.5%) 53 (6.9%) 59 (7.6%) 36 (4.7%) 30 (3.9%) 28 (3.6%) 18(2.3%) Jordan 158 (20.4%) 84 (10.9%) 74 (9.6%) 55 (7.1%) 52 (6.7%) 37 (4.8%) 14 (1.8%) Palestine 109 (14.1%) 44 (5.7%) 65 (8.4%) 24 (3.1%) 31 (4%) 31 (4%) 23 (3%) Syria 117 (15.1%) 56 (7.2%) 61 (7.9%) 30 (3.9%) 40 (5.2%) 38 (4.9%) 9 (1.2%) Yemen 122 (15.8%) 70 (9.1%) 52 (6.7%) 42 (5.4%) 48 (6.2%) 16 (2.1%) 16 (2.1%) Income level Low income 108 (14%) 36 (4.7%) 72 (9.3%) 23 (3%) 30 (3.9%) 32 (4.1%) 23 (3%) Middle income 609 (78.8%) 311 (40.2%) 298 (38.6%) 175 (22.6%) 211 (27.3%) 145 (18.8%) 78 (10.1%) High income 56 (7.2%) 28 (3.6%) 28 (3.6%) 21 (2.7%) 13 (1.7%) 15 (1.9%) 7 (0.9%) The number of hours you use social media Less than an hour a day 31 (4%) 15 (1.9%) 16 (2.1%) 9 (1.2%) 12 (1.6%) 8 (1%) 2 (0.3%) One or two hours a day 202 (26.1%) 106 (13.7%) 96 (12.4%) 71 (9.2%) 63 (8.2%) 51 (6.6%) 17 (2.2%) Three or more hours a day 540 (69.9%) 254 (32.9%) 286 (37%) 139 (18%) 179 (23.2%) 133 (17.2%) 89 (11.5%) Caffeine consumption (coffee, tea, Yerba mate) daily Less than a cup daily 225 (29.1%) 122 (15.8%) 103 (13.3%) 66 (8.5%) 77 (10%) 47 (6.1%) 35 (4.5%) One or two cups daily 362 (46.8%) 179 (23.2%) 183 (23.7%) 108 (14%) 126 (16.3%) 89 (11.5%) 39 (5%) Three or more cups daily 186 (24.1%) 74 (9.6%) 112 (14.5%) 45 (5.8%) 51 (6.6%) 56 (7.2%) 34 (4.4%) Napping No 307 (39.7%) 131 (16.9%) 176 (22.8%) 69 (8.9%) 104 (13.5%) 83 (10.7%) 51 (6.6%) Yes, sometimes 40 5(52.4%) 215 (27.8%) 190 (24.6%) 132 (17.1%) 133 (17.2%) 91 (11.8%) 49 (6.3%) Yes, always 61 (7.9%) 29 (3.8%) 32 (4.1%) 18 (2.3%) 17 (2.2%) 18 (2.3%) 8 (1%) Age 25 37 (4.8%) 14 (1.8%) 23 (3%) 8 (1%) 14 (1.8%) 9 (1.2%) 6 (0.8%) Gender Female 496 (64.2%) 231 (29.9%) 265 (34.3%) 129 (16.7%) 162 (21%) 125 (16.2%) 80 (10.3%) Male 277 (35.8%) 144 (18.6%) 133 (17.2%) 90 (11.6%) 92 (11.9%) 67 (8.7%) 28 (3.6%) Education level Preclinical stage (1-2-3) 386 (49.9%) 189 (24.5%) 197 (25.5%) 109 (14.1%) 133 (17.2%) 101 (13.1%) 43 (5.6%) Clinical stage (4-5-6-7) 387 (50.1%) 186 (24.1%) 201 (26%) 110 (14.2%) 121 (15.7%) 91 (11.8%) 65 (8.4%) Residence area City 579 (74.9%) 282 (36.5%) 297 (38.4%) 160 (20.7%) 201 (26%) 145 (18.8%) 73 (9.4%) Countryside 194 (25.1%) 93 (12%) 101 (13.1%) 59 (7.6%) 53 (6.9%) 47 (6.1%) 35 (4.5%) Do you currently live in on-campus or with family On campus 167 (21.6%) 78 (10.1%) 89 (11.5%) 41 (5.3%) 52 (6.7%) 51 (6.6%) 23 (3%) With family 606 (78.4%) 297 (38.4%) 309 (40%) 178 (23%) 202 (26.1%) 141 (18.2%) 85 (11%) Sleep Cycle Daytime sleep 196 (25.4%) 73 (9.4%) 123 (15.9%) 35 (4.5%) 65 (8.4%) 53 (6.9%) 43 (5.6%) Night sleep 577 (74.6%) 302 (39.1%) 275 (35.6%) 184 (23.8%) 189 (24.5%) 139 (18%) 65 (8.4%) N = Number Relationship between PSQI and BDI This study showed a strong relationship between PSQI as a dependent variable and BDI as an independent variable. Indeed, linear regression analysis generated an estimated value of 0.415 and a p-value of Less than 0.001 (Table 2 )(Supplemental Table). Table 2 linear regression taking the PSQI score as the independent variable 95% Confidence Interval 95% Confidence Interval Predictor Estimate Lower Upper p Stand. Estimate Lower Upper BDI 0.415 0.4030 0.426 < .001 0.930 0.904 0.956 Sleep Quality The median PSQI score in the population was 6. Algeria and Syria had average scores of 6, and Egypt had 6.5, while the lowest score was in both Yemen and Jordan at 5 and the highest was in Palestine at 8. Concerning sleep quality, the data revealed that 48.5% (n = 375) reported having good sleep, while 51.5% (n = 398) indicated poor sleep quality. Our study showed that the percentage of poor sleep quality was highest in Palestine at 59.6%. However, the highest prevalence of good sleep quality was in Yemen at 57.4% ( Fig. 1 ) . 62.6% of participants never use sleep medication, however, only 25.4% reported having good sleep, while 67.7% had good sleep efficiency. 43.3% of the students had a good sleep duration, and 90.7% experienced daytime dysfunction. Only 6.0% of students showed that they did not have any sleep disturbance. However, 21.7% of the students needed less than 15 minutes to fall asleep. Participants’ PSQI scores were significantly affected by several factors: the country of living (p = 0.031), income level (p = 0.017), usage of social media per day (p = 0.016), caffeine consumption (p = 0.004), gender (p = 0.010), and sleep patterns (p < 0.001). Conversely, Participants’ PSQI scores weren’t affected by the frequency of naps (p = 0.50), age groups (p = 0.076), the level of education (p = 0.702), residential area (p = 0.538), and changes in living arrangements (p = 0.183) (Table 3 ). Table 3 Bivariate analysis of factors associated with the BDI Variable Median IQR Country Algeria 6 7 Egypt 6.50 7 Jordan 5 6 Palestine 8 8 Syria 6 5 Yemen 5 5 P-value (Kruskal Wallis) 0.031 Effect size 0.0159 Income level Low income 7.50 7 Middle income 5 7 High income 5.50 8 p-value (Kruskal- Wallis) 0.017 Effect size 0.0105 The number of hours you use social media Less than an hour a day 6 6.50 One or two hours a day 5 6 Three or more hours a day 6 6 P-value (Kruskal-Wallis) 0.016 Effect size 0.0107 Caffeine consumption (coffee, tea, Yerba mate) daily Less than a cup daily 5 7 One or two cups daily 6 6 Three or more cups daily 8 7 P-value (Kruskal-Wallis) 0.004 Effect size 0.0146 Napping No 7 6 Yes, sometimes 5 6 Yes, always 6 7 P-value (Kruskal-Wallis) 0.050 Effect size 0.00776 Age 25 6 5 P-value (Kruskal-Wallis) 0.076 Effect size 0.00666 Gender Female 6 6 Male 5 6 P-Value (Mann-Whitney U) 0.010 Effect size 0.112 Education level Preclinical stage (1-2-3) 6 6.75 Clinical stage (4-5-6-7) 6 6.50 P-Value (Mann-Whitney U) 0.702 Effect size 0.0158 Residence area City 6 6 Countryside 6 8 P-Value (Mann-Whitney U) 0.538 Effect size 0.0294 Do you currently live in on-campus housing or with family? On campus 6 6 With family 6 7 P-Value (Mann-Whitney U) 0.183 Effect size 0.0670 Sleep Cycle Daytime sleep 8 8 Night sleep 5 6 P-Value (Mann-Whitney U) < 0.001 Effect size 0.222 Depression The median Beck Depression Inventory (BDI) score was 15. Algeria had an average score of 17, Egypt had 14.5, Syria had 15, and Jordan had 13.5. The lowest score was in Yemen at 12, and the highest was in Palestine at 18. Based on our findings, the distribution of BDI levels among participants was no depression in 28.7% (n = 222), mild in 32.4% (n = 251), moderate in 25.1% (n = 194), and severe in 13.8% (n = 107). The highest prevalence of no depression was observed in Jordan, at 34.8%. In contrast, Yemen reported the highest prevalence of mild depression at 39.4%. Syria had the highest rate of moderate depression, with 33.3%, while Palestine recorded the highest prevalence of severe depression at 21.1%. The overall prevalence of depression among medical students was highest among Algerian medical students, at 78.7%. (Fig. 1 ). The percentages of students who reported feeling sad, guilty, punished, disappointed, and having an inferiority complex were 36.4%, 31.2%, 57.8%, 40.4%, and 42.3% respectively. About half of the students felt like failures, discouraged about the future, cried more than usual, felt bad, slept more than normal, and worried. Those who were satisfied with things were 33.2%, and those who could make decisions and work like in the past were 47.7% and 33.9%. Additionally, 38.3% of students thought of killing themselves, while 66.9% felt more tired. 64.0% of students were more irritated, and 72.8% lost interest in others. Only 28.6% noticed the change in their interest in sex. Finally, 43.1 and 38.3% of students experienced a worsening of their appetite and weight. Participants’ BDI scores were significantly affected by several factors, including differences across countries (p = 0.001), income levels (p = 0.032), usage of social media per day (p = 0.016), caffeine consumption (p = 0.026), napping frequency (p = 0.008), gender (p = 0.008), and sleep patterns (p < 0.001). Conversely, Participants’ BDI scores weren’t affected by age (p = 0.086), education level (p = 0.597), residential area (p = 0.584), and changes in living arrangements(p = 0.143)(Table 4 ). Table 4 Bivariate analysis of factors associated with the BDI. Variable Median IQR Country Algeria 17 15 Egypt 14.5 17.3 Jordan 13.5 13.8 Palestine 18 14 Syria 15 14 Yemen 12 13 P-value (Kruskal -Wallis) 0.001 Effect size 0.0264 Income level Low income 19 15 Middle income 14 16 High income 15 21.5 P-value (Kruskal-Wallis) 0.032 Effect size 0.00893 The number of hours you use social media Less than an hour a day 12 14.5 One or two hours a day 14 15.8 Three or more hours a day 15 16 P-value (Kruskal -Wallis) 0.016 Effect size 0.0107 Caffeine consumption (coffee, tea, Yerba mate) daily Less than a cup daily 14 16 One or two cups daily 14 14.8 Three or more cups daily 17.5 16 P-Value (Kruskal-Wallis) 0.026 Effect size 0.00945 Napping No 16 15 Yes, sometimes 14 15 Yes, always 14 18 P-value (Kruskal -Wallis) 0.008 Effect size 0.0126 Age 25 16 15 P-value (Kruskal -Wallis) 0.086 Effect size 0.00636 Gender Female 16 16 Male 13 14 P-value (Mann -Whitney U) 0.008 Effect size 0.114 Education level Preclinical stage (1-2-3) 14 15.8 Clinical stage (4-5-6-7) 15 17 P-Value (Mann-Whitney U) 0.597 Effect size 0.0220 Residence area City 14 15 Countryside 15 17 P-Value (Mann -Whitney U) 0.584 Effect size 0.0262 Do you currently live on-campus or with family? On campus 17 15 With family 14 16 P-Value (Mann-Whitney U) 0.143 Effect size 0.0739 Sleep Cycle Daytime sleep 18 17 Night sleep 14 15 P-Value (Mann-Whitney U) < 0.001 Effect size 0.219 DISCUSSION Sleep Quality: Comparisons with MENA and Non-MENA Regions Our study found that 51.5% of medical students in the MENA region experienced poor sleep quality, with Palestine reporting the highest prevalence (59.6%) and Yemen the lowest (42.6%). The median Pittsburgh Sleep Quality Index (PSQI) score was 6, indicating moderate student sleep disturbances. Several factors significantly influence sleep quality, including country of residence, income level, social media usage, caffeine consumption, gender, and sleep patterns. Comparison with MENA Studies Similar studies across the MENA region have consistently reported high rates of poor sleep quality among medical students. For example, in Saudi Arabia, 64% of medical students exhibited poor sleep quality, while even higher rates were observed in Jordan (74%), Iran (71.1%), Iraq (87%), Qatar (70%), Syria (79.5%), and the UAE (84.3%) [24-30]. Similarly, in North Africa, the prevalence was 72.5% in Tunisia, 76.67% in Libya, and 81.7% in Morocco [31-33]. Variations in the prevalence of sleep disturbance among students across countries may stem from differing social and cultural environments. Our findings regarding PSQI scores align with previous studies in Egypt, where the median PSQI was reported as 6.01. However, higher median PSQI scores have been reported in Iran (7.95), Iraq (8.24), Morocco (7.02), Qatar (7.57), and Jordan (8.16), suggesting more severe sleep disturbances in these countries [25-28,33,34]. The high prevalence of poor sleep quality among medical students in the MENA region can be attributed to multiple factors, including academic pressure, long study hours, high levels of stress, and lifestyle habits. The demanding nature of medical education, irregular sleep schedules, and excessive screen time likely exacerbate these disturbances. A study conducted among medical and nursing students in Morocco and Spain found that intense or weak physical activity and smartphone addiction were correlated with poor sleep quality. The multivariate analysis revealed that factors such as the country of study, involvement in nursing studies, and chronic diseases were significantly associated with poor sleep quality [33]. Furthermore, a systematic review and meta-analysis focusing on African university students identified several factors significantly associated with poor sleep quality, including being stressed during the second academic year, using electronic devices at bedtime, and having a comorbid chronic illness [35]. These findings underscore the multifaceted contributors to sleep disturbances among medical students in the MENA region, highlighting the need for targeted interventions to address these issues. Interestingly, our study found that Yemen had the lowest PSQI score, indicating better sleep quality compared to other MENA countries. This finding does not align with a study by Ahmed Attal et al., which reported a PSQI score of 6.85 and a poor sleep quality prevalence of 68% among Yemeni medical students [36]. These discrepancies may stem from differences in study populations, sample sizes, or variations in academic workload and social environments. Conversely, Palestine had the highest prevalence of poor sleep quality, which is consistent with the findings of Aldabbour et al. (2024), who reported a prevalence of 77.9% among medical students in Gaza [37]. This could be attributed to heightened stress levels associated with political instability, economic hardships, and limited access to mental health and healthcare resources. Chronic exposure to external stressors may contribute to disrupted sleep patterns and poor overall sleep health in Palestinian students [37]. Comparison with non-MENA Studies Globally, the prevalence of poor sleep quality among medical students varies. Some countries report prevalence rates consistent with our findings, such as Vietnam (50.27%, PSQI = 5.8) and India (45%, PSQI = 5.8) [38,39]. However, higher prevalence rates have been observed in Brazil (87.1%), Indonesia (>85%), and Macedonia (>60%, PSQI = 8), suggesting more severe sleep disturbances in these regions [40,41]. In contrast, Pakistan reported a lower prevalence (39.5%), indicating comparatively better sleep quality [42,43]. A meta-analysis found a 65% prevalence of poor sleep quality among European medical students, with similar rates in France (65%, PSQI = 7.2) and North America (59.92%) [44,45]. These findings highlight that sleep disturbances are a widespread issue among medical students globally, influenced by academic stress, lifestyle factors, and socioeconomic conditions. Depression Among Medical Students: MENA vs. Non-MENA Regions Prevalence in the MENA Region Our study found a high prevalence of depression (71.3%) among medical students in the MENA region, with 13.8% experiencing severe depression. Palestine had the highest rate of severe depression (21.1%), while Jordan had the lowest overall prevalence (34.8% of students were not depressed). The median BDI score was 15, ranging from 18 in Palestine to 12 in Yemen. Depression levels were significantly influenced by country of residence, income, social media use, caffeine intake, gender, sleep habits, and napping frequency. Comparison with MENA Studies Depression rates vary across MENA countries, likely due to differences in assessment tools, cultural attitudes, and academic stressors. Studies reported prevalence rates of 64% in Tunisia and 69% in Palestine, which consists of our findings, with the lower prevalence found at 40% in Bahrain and 45% in Libya [37,46-48]. In Lebanon, about one-third of medical students had major depression, while in Saudi Arabia, 30.9% reported depressive symptoms, with 2.9% experiencing severe depression [49,50]. Comparison with non-MENA Regions Depression among medical students outside the MENA region varies, with some countries reporting lower prevalence while others show comparably high rates. Lower but still concerning rates are reported in Pakistan (19.5%), China (29%), Africa (38.8%), Brazil (40%), Bulgaria (47.1%), and India (50%) [35,51-55]. These findings indicate that depression is a widespread issue among medical students, although regional variations are affected by academic stress, cultural expectations, and socioeconomic factors. Notably, Peru (71.6%) and Turkey (>70%) report depression rates similar to those in the MENA region, indicating that certain stressors may be shared across different countries [54-56]. The high prevalence in these countries might be attributed to intense academic workloads, financial burdens, and limited access to mental health support. A systematic review and meta-analysis reported a pooled prevalence of depression among medical students in the Middle East at 43.6%, which is higher compared to other regions such as North and South America (30.2%), Europe (23.9%) and Asia (26.6%) [57]. This disparity may be attributed to better mental health infrastructure, greater psychological well-being awareness, and stronger student support systems in these regions. The Relationship Between Depression and Poor Sleep Quality Our study identified a significant positive correlation between poor sleep quality and increased depression scores among medical students. This finding aligns with previous research indicating that students experiencing higher levels of depression are more prone to sleep disturbances and vice versa [37,52,57,58]. The bidirectional relationship between sleep and depression is well-documented, suggesting that poor sleep quality can exacerbate depressive symptoms, while depression itself is linked to sleep disorders such as insomnia and frequent nighttime awakenings [59,60]. For instance, a systematic review highlighted that poor sleep quality is significantly associated with depression or depressive symptoms among college students. The review emphasized the importance of sleep quality as a relevant variable in this relationship [61]. Disruptions in circadian rhythms (the body's internal biological clock) have been strongly linked to depression. These disturbances can impair melatonin secretion, a hormone critical for regulating sleep, leading to sleep problems and exacerbating depressive symptoms. Research also suggests that individuals with depression often experience reduced nocturnal melatonin release, which may contribute to the sleep disturbances commonly reported among depressive patients [62,63]. Factors Influencing Sleep and Depression: A Global Perspective Our study identified several key factors influencing both sleep quality and depression, including social media usage, caffeine consumption, and gender. These findings align with global research indicating that excessive social media use and high caffeine intake are associated with sleep disturbances and increased psychological stress. We observed that female medical students generally experienced poorer sleep and higher depression levels, a pattern well-documented in the literature [28,30,32,43,45,46,53,55]. Studies suggest that biological factors such as hormonal fluctuations, as well as psychological and sociocultural influences like increased family responsibilities, contribute to these disparities [64,65]. Contrary to expectations, a study conducted in Yemen found that males were at a higher risk of poor sleep than females [36]. However, several studies have reported no significant correlation between gender and sleep quality or depression [25,31,34,37,66]. Our study found a negative correlation between caffeine consumption and sleep quality, reinforcing existing evidence that caffeine, as a central nervous system stimulant, disrupts sleep patterns and reduces sleep efficiency [67,68]. However, a study conducted in Jordan found no significant correlation between caffeine intake and sleep quality [25], suggesting that individual tolerance levels and consumption habits may moderate its effects. Consistent with our findings, research by Jassem et al. and Bousgheiri et al. highlighted a significant correlation between smartphone use and poor sleep quality [29,33]. Excessive use of electronic devices before bedtime disrupts sleep due to blue light exposure, which suppresses melatonin secretion and alters circadian rhythms [69]. A meta-analysis of multinational observational studies assessing the prevalence of smartphone addiction among Asian medical students reported that the prevalence was 41.93%. The study also found that smartphone addiction was positively correlated with poor sleep quality, stress, anxiety, depression, neuroticism, and overall health issues among this population [70]. Our findings also support the association between lower socioeconomic status and depression, consistent with the study by Amamou et al. among medical students in Tunisia [46]. Financial stress has been widely recognized as a risk factor for depression in both general and student populations [71-73]. These findings highlight the importance of addressing economic stressors as part of mental health interventions for medical students. Recommendations Based on the findings of this study and supporting literature, the following recommendations are proposed to improve sleep quality, mental well-being, and academic performance among medical students: 1. Implement Psychological and Behavioral Interventions for Sleep Improvement Given the strong link between poor sleep quality and depression, medical schools should integrate evidence-based psychological interventions such as Cognitive-Behavioral Therapy for Insomnia (CBT-I) and Mindfulness-Based Stress Reduction (MBSR). A meta-analysis by Saruhanjan et al. demonstrated that psychological interventions significantly improve sleep quality and reduce sleep disturbances [74]. Additionally, MBSR has been shown to effectively reduce anxiety and depression among medical students and should be incorporated into wellness programs [75]. Future research should explore the long-term impact of these interventions in high-demand academic settings to ensure their feasibility and effectiveness. 2. Encourage Healthy Lifestyle Habits and Stress Management Adopting sleep hygiene practices is essential for improving sleep quality, as a review by Irish et al. highlights that consistent sleep timing, stress management, noise reduction, and avoiding caffeine, nicotine, and alcohol contribute to better rest [76]. Medical schools should implement sleep education programs and stress management workshops to promote these practices. Additionally, regular physical activity has been shown to mitigate the negative impact of smartphone addiction on sleep quality and should be encouraged as a protective strategy [77]. Structured mental health programs should also incorporate mindfulness and relaxation techniques, including meditation, breathing exercises, and stress management strategies, to support students' overall well-being. 3. Address Caffeine Consumption and Its Impact on Sleep Reducing excessive caffeine consumption is crucial, as high caffeine intake among medical students negatively impacts sleep quality. A literature review by Behling identified effective strategies for reducing caffeine use, including gradual dose tapering, caffeine intake journaling, daily exercise, and professional counseling [78]. Additionally, a case study by McIntosh & Heath demonstrated that a structured caffeine reduction plan, combined with behavioral tracking, successfully reduced caffeine intake over two months [79]. To support students in managing their caffeine intake, medical schools should implement structured interventions such as counseling, self-monitoring tools, and awareness campaigns. A randomized controlled trial by Evatt et al. showed that a brief, therapist-guided intervention significantly reduced caffeine consumption with sustained long-term effects [80]. Future research should assess the effectiveness of these interventions on sleep quality, academic performance, and mental health. 4. Mitigate the Impact of Screen Time on Sleep Quality Limiting blue light exposure before bedtime is essential, as excessive screen use negatively impacts sleep quality. A study by Guarana et al. found that wearing blue-light filtering glasses improved both the quantity and quality of sleep. This led to enhanced work engagement, better task performance, and a reduction in counterproductive behaviors [81].To reduce the impact of blue light, medical students should use blue-light filtering glasses, enable blue-light reduction settings on their devices, and limit their screen time before sleep. Institutions should promote awareness of the impact of blue light on cognitive performance and sleep. Further research is needed to assess the long-term benefits of blue-light filtration on student health and academic performance. 5. Explore Technological Aids for Sleep Enhancement A study by Barnes et al. demonstrated that closed-loop acoustic stimulation, a sound-based wearable technology, significantly improved sleep quality, leading to higher work engagement, task performance, and organizational citizenship behaviors [82]. Future research should investigate the use of sleep-enhancing wearable devices as a practical and cost-effective tool for medical students. Furthermore, sleep hygiene education programs should incorporate technological solutions alongside behavioral strategies to enhance sleep quality and overall well-being. Limitations and strengths Limitations 1. Convenience Sampling: The study adopted a convenience sampling technique, which may introduce selection bias as it relies on students willing and able to participate. This method may not fully represent the entire population of medical students in the target countries, potentially affecting the generalizability of the results. 2. Snowball Sampling: While snowball sampling helped expand the scope and obtain a more diverse sample, it carries a risk of network bias. Participants may tend to recruit peers from similar social circles, which might limit the diversity of the sample and introduce biases related to specific groups or demographics. 3. Geographical Limitations: The study was conducted in a limited number of MENA countries, which may not fully capture the diversity and variations across the entire region. Future research should aim to include a broader range of countries to validate and extend the findings. 4. Self-Reported Data: The reliance on self-reported data from participants may introduce recall bias and social desirability bias. Participants may not accurately recall or report their behaviors and experiences, which could affect the accuracy of the data. 5. Cross-Sectional Design: The study's cross-sectional design does not establish causality between variables. While associations can be identified, it is not possible to determine cause-and-effect relationships. 6. Resource Constraints: Limited resources and logistical challenges restricted the ability to include a larger and more representative sample. This limitation highlights the need for increased funding and support for future research. Strengths 1. Comprehensive Evaluation: This study provides one of the first reviews of sleep quality and depression among medical students in multiple countries across the MENA region, offering valuable insights into these critical health issues. 2. Diverse Sample: The inclusion of students from six different countries enhances the generalizability of the findings and provides a broader perspective on the prevalence and factors associated with poor sleep quality and depression in the region. 3. Use of Standardized Instruments: The study utilized well-established and validated instruments (PSQI and BDI) to assess sleep quality and depression, ensuring the reliability and comparability of the results with other studies. 4. Mixed Sampling Methods: The combination of convenience and snowball sampling techniques allowed for the inclusion of a diverse group of participants, increasing the representativeness of the sample and helping to capture a wide range of experiences and perspectives. 5. Pilot Testing: The generated questions were retested for content validity before being used in the main study. This step ensured that the questions were culturally and contextually appropriate for the target population. 6. Focus on a Neglected Population: By focusing on medical students, the study highlights a group that is often overlooked in mental health research,yet is at high risk for poor sleep quality and depression due to the unique stresses of medical education. 7. Practical Implications: The findings offer practical recommendations for policymakers and educational institutions to address and mitigate the issues of poor sleep quality and depression among medical students, potentially leading to improved mental health outcomes in this population. CONCLUSION This study demonstrates that poor sleep quality and depression are both prevalent and strongly correlated among medical students in the MENA region a finding that directly aligns with our research objectives. These results underscore a serious public health concern, urging policymakers to implement targeted interventions such as enhanced counseling services, integrated mental health education, and robust sleep hygiene programs. Immediate, coordinated action is essential to safeguard students' well-being and academic performance, ultimately fostering a healthier future generation. Abbreviations PSQI: Pittsburgh Sleep Quality Index, BDI: Beck Depression Inventory, MENA: Middle East and North Africa Declarations Collaborators Abrar Nadhem, Ahmed Reda, Ghadeer Al-Surabi Acknowledgments We want to thank Dr. Omar Alrashid Alhirak for providing support and advice Contributor TA, AD, and KF designed the study, TA conducted the analysis, TA, AD, AA, AZA, and AM, collected the data, and wrote the manuscript. All authors contributed substantially to the interpretation of the study findings. All authors reviewed, contributed to, and approved the final manuscript. Competing interests The authors declare they have no competing interests Consent for publication Not applicable Funding None. Data availability statement Data are available in a public, open-access repository. All data related to the analyses and results of this study are freely accessible at the Open Science Framework and can be reused when given appropriate attribution. The data are licensed to the first author and can be obtained at Data.xlsx Ethics approval This study was approved by the ethical committee of Al-Balqa Applied University. The local approval number of IRB was (26/3/2/1279). References Wondie T, Molla A, Mulat H, et al. Magnitude and correlates of sleep quality among undergraduate medical students in Ethiopia: cross-sectional study. Sleep Science Practice 2021; 5 :7. doi:10.1186/s41606-021-00058-2 Neufeld A, Malin G. How medical students cope with stress: a cross-sectional look at strategies and their sociodemographic antecedents. BMC Med Educ 2021; 21 :299. doi:10.1186/s12909-021-02734-4 Perotta B, Arantes-Costa FM, Enns SC, et al. Sleepiness, sleep deprivation, quality of life, mental symptoms and perception of academic environment in medical students. BMC Med Educ 2021; 21 :111. doi:10.1186/s12909-021-02544-8 Omer M. The impact of sleep quality on cognitive function in healthy adults: A cross-sectional study. J Neurol Sci 2023; 455 :121609. doi:10.1016/j.jns.2023.121609 Curcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity and academic performance. Sleep Med Rev 2006; 10 :323–37. doi:10.1016/j.smrv.2005.11.001 Massarat Begum, Dimple Siri Chandana Puchakayala. Study to determine the prevalence of poor sleep quality and its correlation with sleep hygiene practices among medical students. Asian J Med Sci 2022; 13 :151–5. doi:10.3126/ajms.v13i9.46175 Attal BA, Bezdan M, Abdulqader A. Quality of Sleep and Its Correlates among Yemeni Medical Students: A Cross-Sectional Study. Sleep Disord 2021; 2021 :8887870. doi:10.1155/2021/8887870 Schmickler JM, Blaschke S, Robbins R, et al. Determinants of Sleep Quality: A Cross-Sectional Study in University Students. Int J Environ Res Public Health 2023; 20 . doi:10.3390/ijerph20032019 Wong WS, Fielding R. Prevalence of insomnia among Chinese adults in Hong Kong: a population-based study. J Sleep Res. 2011;20:117–26. Wang Y, Li Y, Liu X, Liu R, Mao Z, Tu R, Zhang H, Zhang X, Qian X, Jiang J, et al. Gender-specific prevalence of poor sleep quality and related factors in a Chinese rural population: the Henan rural cohort study. Sleep Med. 2019;54:134–41. Li, Y., Bai, W., Zhu, B. et al. Prevalence and correlates of poor sleep quality among college students: a cross-sectional survey. Health Qual Life Outcomes 18, 210 (2020). https://doi.org/10.1186/s12955-020-01465-2 Sundas N, Ghimire S, Bhusal S, et al. Sleep Quality among Medical Students of a Tertiary Care Hospital: A Descriptive Cross-sectional Study. JNMA J Nepal Med Assoc 2020; 58 :76–9. doi:10.31729/jnma.4813 Yilmaz D, Tanrikulu F, Dikmen Y. Research on sleep quality and the factors affecting the sleep quality of the nursing students. Curr Health Sci J 2017; 43 :20–4. doi:10.12865/CHSJ.43.01.03 Grandner MA, Patel NP, Gehrman PR, et al. Who gets the best sleep? Ethnic and socioeconomic factors related to sleep complaints. Sleep Med 2010; 11 :470–8. doi:10.1016/j.sleep.2009.10.006 Ngasa SN, Sama C-B, Dzekem BS, et al. Prevalence and factors associated with depression among medical students in Cameroon: a cross-sectional study. BMC Psychiatry 2017; 17 :216. doi:10.1186/s12888-017-1382-3 Zhai L, Zhang H, Zhang D. Sleep duration and depression among adults: a meta-analysis of prospective studies. Depress Anxiety 2015; 32 :664–70. doi:10.1002/da.22386 Fawzy M, Hamed SA. Prevalence of psychological stress, depression and anxiety among medical students in Egypt. Psychiatry Res 2017; 255 :186–94. doi:10.1016/j.psychres.2017.05.027 Barlett JE, Kotrlik J, Higgins C. Organizational Research: Determining Appropriate Sample Size in Survey Research. Information Technology, Learning, and Performance Journal 2001;19. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008;61:344–9. doi:10.1016/j.jclinepi.2007.11.008 Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res 1989; 28 :193–213. doi:10.1016/0165-1781(89)90047-4 Salkind MR. Beck depression inventory in general practice. J R Coll Gen Pract 1969; 18 :267–71. Suleiman KH, Yates BC, Berger AM, et al. Translating the Pittsburgh Sleep Quality Index into Arabic. West J Nurs Res 2010; 32 :250–68. doi:10.1177/0193945909348230 West J. An Arabic validation of a depression inventory. Int J Soc Psychiatry 1985; 31 :282–9. doi:10.1177/002076408503100406 Almojali AI, Almalki SA, Alothman AS, Masuadi EM, Alaqeel MK. The prevalence and association of stress with sleep quality among medical students. J Epidemiol Glob Health. 2017;7(3):169–74. doi: https://doi.org/10.1016/j.jegh.2017.04.005 Jaradat JH, Al-Dwairi R, Riyad J, Al-Rawashdeh I, Elmazar H. Exploring the interplay of sleep quality, stress, and academic performance in Jordanian medical students: A national perspective. JAPAJ. 2024;2(2). Shafiee A, Fili J, Ghafari S, Sattari MA, Borna N, Pourramzani A. The prevalence of sleep disturbance and its possible associated factors among Iranian medical students: A cross-sectional study with a national meta-analysis. Sleep Med X. 2024;7:100107. doi: https://doi.org/10.1016/j.sleepx.2023.100107 Taher A. AL-Kindy College of Medicine. Ali RM, Zolezzi M, Awaisu A, Eltorki Y. Sleep quality and sleep hygiene behaviors among university students in Qatar. Int J Gen Med. 2023;16:2427–39. doi: https://doi.org/10.2147/IJGM.S409107 Jassem M, Abdelwahed RNK, Alyousbashi A, Meer A. Evaluation of daytime sleepiness and sleep quality among resident physicians of Damascus: A cross-sectional study. Sleep Epidemiol. 2022;2:100035. doi: https://doi.org/10.1016/j.sleepe.2022.100035 Meer H, Jeyaseelan L, Sultan MA. Sleep quality and emotional state of medical students in Dubai. Sleep Disord. 2022;2022:8187547. doi: https://doi.org/10.1155/2022/8187547 Saguem BN, Nakhli J, Romdhane I, Nasr SB. Predictors of sleep quality in medical students during COVID-19 confinement. Encephale. 2022;48(1):3–12. doi: https://doi.org/10.1016/j.encep.2021.01.014 El Sahly RA, Ahmed AM, Amer SE, Alsaeiti KD. Assessment of insomnia and sleep quality among medical students at Benghazi University: A cross-sectional study. Apollo Med. 2020;17(2):73–77. doi: https://doi.org/10.4103/am.am_93_19 Bousgheiri F, Allouch A, Sammoud K, Navarro-Martínez R, Ibáñez-Del Valle V, Senhaji M, et al. Factors affecting sleep quality among university medical and nursing students: A study in two countries in the Mediterranean region. Diseases. 2024;12(5):[Article number or pages]. doi: https://doi.org/10.3390/diseases12050133 Elwasify M, Barakat DH, Fawzy M, Elwasify M, Rashed I, Radwan DN. Quality of sleep in a sample of Egyptian medical students. Middle East Curr Psychiatry. 2016;23(4):200–207. doi: https://doi.org/10.1097/01.XME.0000507153.65164.1c Nakie G, Takelle GM, Rtbey G, Andualem F, Tinsae T, Kassa MA, et al. Sleep quality and associated factors among university students in Africa: A systematic review and meta-analysis study. Front Psychiatry. 2024;15:1370757. doi: https://doi.org/10.3389/fpsyt.2023.1370757 Attal BA, Bezdan M, Abdulqader A. Quality of sleep and its correlates among Yemeni medical students: A cross-sectional study. Sleep Disord. 2021;2021:8887870. doi: https://doi.org/10.1155/2021/8887870 Aldabbour B, Jaradat R, Aljbour O, Abdu M, Aljbour J, Dayya AA, et al. Depression, anxiety, stress, sleep quality, and life satisfaction among undergraduate medical students in Gaza Strip: A cross-sectional survey. Res Sq. 2024. Tran D-S, Nguyen D-T, Nguyen T-H, Tran C-T-P, Duong-Quy S, Nguyen T-H. Stress and sleep quality in medical students: A cross-sectional study from Vietnam. Front Psychiatry. 2023;14:1297605. doi: https://doi.org/10.3389/fpsyt.2023.1297605 Mishra J, Panigrahi A, Samanta P, Dash K, Mahapatra P, Behera MR. Sleep quality and associated factors among undergraduate medical students during COVID-19 confinement. Clin Epidemiol Glob Health. 2022;15:101004. doi: https://doi.org/10.1016/j.cegh.2022.101004 Corrêa CC, Oliveira FK, Pizzamiglio DS, Ortolan EVP, Weber SAT. Sleep quality in medical students: A comparison across the various phases of the medical course. J Bras Pneumol. 2017;43(4):285–289. doi: https://doi.org/10.1590/S1806-37562016000000163 Saputri AD, Ritunga I. The effect of sleep quality due to stress on medical students’ academic achievement: A cross-sectional study. Curr J Glob Health. 2023;10(2):52–57. Mancevska S, Pislevski M, Pluncevic Gligoroska J. Assessment of sleep quality during the winter semester in undergraduate medical students enrolled at UKIM, Faculty of Medicine, Skopje, Republic of North Macedonia. JMS. 2024;7(1):17–24. Surani AA, Zahid S, Surani A, Ali S, Mubeen M, Khan RH. Sleep quality among medical students of Karachi, Pakistan. J Pak Med Assoc. 2015;65(4):380–382. Rao W-W, Li W, Qi H, Hong L, Chen C, Li C-Y, et al. Sleep quality in medical students: a comprehensive meta-analysis of observational studies. Sleep Breath. 2020;24(3):1151–65. doi: https://doi.org/10.1007/s11325-020-02033-4 LECOEUR Elisabeth.pdf. Amamou B, Alouani S, Ben Haouala A, Alouani S, Tlili MA, Mhalla A, et al. Depression among medical students in Tunisia: Prevalence and associated factors. World J Psychiatry. 2023;13(10):772–83. doi: https://doi.org/10.5498/wjp.v13.i10.772 Maroon ZA, Borgan SM, Kamel C, Maddison W, Royston M, Donnellan C. Factors associated with depression and anxiety symptoms among medical students in Bahrain. Acad Psychiatry. 2018;42(1):31–40. doi: https://doi.org/10.1007/s40596-017-0733-1 Sherif RF, Saeed NM, Sherif GA, Rabab KS, Sherif FM. Prevalence of depression among Libyan medical students. Zenodo. 2021. Naja WJ, Kansoun AH, Haddad RS. Prevalence of depression in medical students at the Lebanese university and exploring its correlation with Facebook relevance: A questionnaire study. JMIR Res Protoc. 2016;5(2):e96. doi: https://doi.org/10.2196/resprot.4552 Jarwan B. Depression among medical students of Faculty of Medicine, Umm Al-Qura University in Makkah, Saudi Arabia. Int J Med Sci Public Health. 2015;4(2):184. doi: https://doi.org/10.5455/ijmsph.2015.210920144 Rab F, Mamdou R, Nasir S. Rates of depression and anxiety among female medical students in Pakistan. East Mediterr Health J. 2008;14(1):126–33. Wang J, Liu M, Bai J, Chen Y, Xia J, Liang B, et al. Prevalence of common mental disorders among medical students in China: a systematic review and meta-analysis. Front Public Health. 2023;11:1116616. doi: https://doi.org/10.3389/fpubh.2023.1116616 Brenneisen Mayer F, Souza Santos I, Silveira PSP, Itaqui Lopes MH, de Souza ARND, Campos EP, et al. Factors associated to depression and anxiety in medical students: a multicenter study. BMC Med Educ. 2016;16(1):282. doi: https://doi.org/10.1186/s12909-016-0795-5 Georgieva E, Vatansever M, Velkova A, Hristov N, Pesheva P, Simeonova I, et al. Prevalence of depression among three cohorts of medical students. Eur J Public Health. 2020;30(Supplement_5). doi: https://doi.org/10.1093/eurpub/ckaa165.1295 Dutta G, Rajendran N, Kumar T, Varthya SB, Rajendran V. Prevalence of depression among undergraduate medical students in India: A systemic review and meta-analysis. Cureus. 2023;15(1):e33590. doi: https://doi.org/10.7759/cureus.33590 Valladares-Garrido D, Quiroga-Castañeda PP, Berrios-Villegas I, Zila-Velasque JP, Anchay-Zuloeta C, Chumán-Sánchez M, et al. Depression, anxiety, and stress in medical students in Peru: a cross-sectional study. Front Psychiatry. 2023;14:1268872. doi: https://doi.org/10.3389/fpsyt.2023.1268872 Eleftheriou A, Rokou A, Arvaniti A, Nena E, Steiropoulos P. Sleep quality and mental health of medical students in Greece during the COVID-19 pandemic. Front Public Health. 2021;9:775374. doi: https://doi.org/10.3389/fpubh.2021.775374 Alwhaibi M, Al Aloola NA. Associations between stress, anxiety, depression, and sleep quality among healthcare students. J Clin Med. 2023;12(13). doi: https://doi.org/10.3390/jcm12134782 Yasugaki S, Okamura H, Kaneko A, Hayashi Y. Bidirectional relationship between sleep and depression. Neurosci Res. 2025;211:57–64. doi: https://doi.org/10.1016/j.neures.2024.08.015 Gregory AM, Buysse DJ, Willis TA, Rijsdijk FV, Maughan B, Rowe R, et al. Associations between sleep quality and anxiety and depression symptoms in a sample of young adult twins and siblings. J Psychosom Res. 2011;71(4):250–5. doi: https://doi.org/10.1016/j.jpsychores.2011.03.011 Dinis J, Bragança M. Quality of sleep and depression in college students: a systematic review. Sleep Sci. 2018;11(4):290–301. doi: https://doi.org/10.5935/1984-0063.20180045 Quera Salva MA, Hartley S, Barbot F, Alvarez JC, Lofaso F, Guilleminault C. Circadian rhythms, melatonin, and depression. Curr Pharm Des. 2011;17(15):1459–70. doi: https://doi.org/10.2174/138161211796157168 Walker WH, Walton JC, DeVries AC, Nelson RJ. Circadian rhythm disruption and mental health. Transl Psychiatry. 2020;10(1):28. doi: https://doi.org/10.1038/s41398-020-0694-0 Benge E, Pavlova M, Javaheri S. Sleep health challenges among women: insomnia across the lifespan. Front Sleep. 2024;3. doi: https://doi.org/10.3389/fsleep.2024.123456 Rajab AM, Rajab TM, Basha AC, Al-Khani AM, Ali MA, Enabi S, et al. Gender differences in sleep and mental health among Saudi adolescents. Sleep Disord. 2021;2021:5513817. doi: https://doi.org/10.1155/2021/5513817 Zeng W, Chen R, Wang X, Zhang Q, Deng W. Prevalence of mental health problems among medical students in China: A meta-analysis. Med (Baltimore). 2019;98(18):e15337. doi: https://doi.org/10.1097/MD.0000000000015337 Weibel J, Lin Y-S, Landolt H-P, Berthomier C, Brandewinder M, Kistler J, et al. Regular caffeine intake delays REM sleep promotion and attenuates sleep quality in healthy men. J Biol Rhythms. 2021;36(4):384–94. doi: https://doi.org/10.1177/0748730421995678 Drake C, Roehrs T, Shambroom J, Roth T. Caffeine effects on sleep taken 0, 3, or 6 hours before going to bed. J Clin Sleep Med. 2013;9(11):1195–200. doi: https://doi.org/10.5664/jcsm.3170 Chang A-M, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci USA. 2015;112(4):1232–7. doi: https://doi.org/10.1073/pnas.1418490112 Zhong Y, Ma H, Liang Y-F, Liao C-J, Zhang C-C, Jiang W-J. Prevalence of smartphone addiction among Asian medical students: A meta-analysis of multinational observational studies. Int J Soc Psychiatry. 2022;68(6):1171–83. doi: https://doi.org/10.1177/00207640211011492 González G, Vives A. Work status, financial stress, family problems, and gender differences in the prevalence of depression in Chile. Ann Work Expo Health. 2019;63(3):359–70. doi: https://doi.org/10.1093/annweh/wxy109 Cao H, Zhou N, Li X, Serido J, Shim S. Temporal dynamics of the association between financial stress and depressive symptoms throughout emerging adulthood. J Affect Disord. 2021;282:211–8. doi: https://doi.org/10.1016/j.jad.2020.12.134 Szkody E, Hobaica S, Owens S, Boland J, Washburn JJ, Bell D. Financial stress and debt in clinical psychology doctoral students. J Clin Psychol. 2023;79(3):835–53. doi: https://doi.org/10.1002/jclp.23413 Saruhanjan K, Zarski A-C, Bauer T, Baumeister H, Cuijpers P, Spiegelhalder K, et al. Psychological interventions to improve sleep in college students: A meta-analysis of randomized controlled trials. J Sleep Res. 2021;30(1):e13097. doi: https://doi.org/10.1111/jsr.13097 Alzahrani AM, Hakami A, AlHadi A, Al-Maflehi N, Aljawadi MH, Alotaibi RM, et al. The effectiveness of mindfulness training in improving medical students’ stress, depression, and anxiety. PLoS ONE. 2023;18(10):e0293539. doi: https://doi.org/10.1371/journal.pone.0293539 Irish LA, Kline CE, Gunn HE, Buysse DJ, Hall MH. The role of sleep hygiene in promoting public health: A review of empirical evidence. Sleep Med Rev. 2015;22:23–36. doi: https://doi.org/10.1016/j.smrv.2014.10.001 Zhu W, Liu J, Lou H, Mu F, Li B. Influence of smartphone addiction on sleep quality of college students: The regulatory effect of physical exercise behavior. PLoS ONE. 2024;19(7):e0307162. doi: https://doi.org/10.1371/journal.pone.0307162 Behling M. Methods to Stop Caffeine Use and Minimize Caffeine Withdrawal Symptoms in the State of Caffeine Dependence: A Literature Review. [cited 2025 Feb 12]; Available from: http://scholarsarchive.byu.edu/ [email protected] McIntosh W HG. A case study investigating a behavioral intervention to reduce caffeine consumption. J Women’s Health Care. 2014;03(05). Evatt DP, Juliano LM, Griffiths RR. A brief manualized treatment for problematic caffeine use: A randomized control trial. J Consult Clin Psychol. 2016;84(2):113–21. doi: https://doi.org/10.1037/ccp0000138 Guarana CL, Barnes CM, Ong WJ. The effects of blue-light filtration on sleep and work outcomes. J Appl Psychol. 2021;106(5):784–96. doi: https://doi.org/10.1037/apl0000918 Barnes CM, Guarana C, Lee J, Kaur E. Using wearable technology (closed-loop acoustic stimulation) to improve sleep quality and work outcomes. J Appl Psychol. 2023;108(8):1391–407. doi:https://doi.org/10.1037/apl0001068 Additional Declarations No competing interests reported. Supplementary Files supplementalTable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5453920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":437638888,"identity":"9b7c5e94-fd51-4cc9-a087-d3e6919333ac","order_by":0,"name":"Taleb Alsalloum","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYFAC5gYgYcHAwA6kPgAxGzsBDTwMjCAtEkCtDAyMM0BamEnRwswDtpaAFnv2g42PC2ok7PmbmY9utvm1TZ6PmYHxw8ccPLbwJDYbzzgmkTjjMFva7dy+24ZtzAzMkjO34XNYYps0D5tEAsNhHrPbuT23GYFa2Jh58Wnhf9j+m+efhL08SItlz217wlokEtuYedskGDeAtDD8uJ1IWMuNh83SM/skEjcC/XKzt+F2chszYzNev7D3Jx/8XPDNxl7uePOxGz/+3Lad39588MNHPFpAABERjG1gsgG/ehQtDH8IKh4Fo2AUjIIRCACK/kw6ZlTBTAAAAABJRU5ErkJggg==","orcid":"","institution":"Faculty of Medicine, University of Hama","correspondingAuthor":true,"prefix":"","firstName":"Taleb","middleName":"","lastName":"Alsalloum","suffix":""},{"id":437638891,"identity":"77984927-d42b-4f51-8f12-d47442741678","order_by":1,"name":"Abdallah Alawaisheh","email":"","orcid":"","institution":"Faculty of Medicine, ALBALQA APPLIED UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"Abdallah","middleName":"","lastName":"Alawaisheh","suffix":""},{"id":437638893,"identity":"8bf54176-5575-424b-a791-4cf187f790d8","order_by":2,"name":"Asma Daoud","email":"","orcid":"","institution":"Faculty of Medicine, Ferhat Abbas University","correspondingAuthor":false,"prefix":"","firstName":"Asma","middleName":"","lastName":"Daoud","suffix":""},{"id":437638895,"identity":"ec7e030a-d74c-4bf4-8eb0-d517fd68b9cf","order_by":3,"name":"Asmaa Alnajjar","email":"","orcid":"","institution":"Faculty of Medicine, Al Azhar University","correspondingAuthor":false,"prefix":"","firstName":"Asmaa","middleName":"","lastName":"Alnajjar","suffix":""},{"id":437638896,"identity":"174042d7-4b22-485a-a0fd-ea0ad5b2c69c","order_by":4,"name":"Abdelrahman Meky","email":"","orcid":"","institution":"Faculty of Medicine, Banha University","correspondingAuthor":false,"prefix":"","firstName":"Abdelrahman","middleName":"","lastName":"Meky","suffix":""},{"id":437638897,"identity":"e5355a4d-a929-4d1a-93c3-c5e86b1b5663","order_by":5,"name":"Khaled Funjan","email":"","orcid":"","institution":"Faculty of Medicine, ALBALQA APPLIED UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"Khaled","middleName":"","lastName":"Funjan","suffix":""}],"badges":[],"createdAt":"2024-11-14 12:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5453920/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5453920/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80027333,"identity":"367f92af-1391-405f-898c-fda66079973c","added_by":"auto","created_at":"2025-04-07 06:38:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142696,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Sleep Quality and Depression Levels Across Six Countries\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5453920/v1/682943e1579b79fa0f344a72.png"},{"id":82370923,"identity":"f6fe4c40-14ab-4b6c-a2c7-c2060e153b9f","added_by":"auto","created_at":"2025-05-09 13:38:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2403696,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5453920/v1/00731734-f03d-491c-abe9-35ffd105924a.pdf"},{"id":80026618,"identity":"9e246fd9-3693-4cc1-bb3a-d50635042369","added_by":"auto","created_at":"2025-04-07 06:30:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":46785,"visible":true,"origin":"","legend":"","description":"","filename":"supplementalTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-5453920/v1/009189ed19c1ae04e6e8ab21.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Sleep Quality and Depression among Medical Students: A Cross-Sectional Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAdequate sleep is essential for both mental and physical well-being [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, poor sleep and depression significantly impair the mental health and overall well-being of medical students [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The rigorous demands of medical education, which include long hours of study, strenuous work schedules, and intense competition, contribute to heightened risks of sleep disturbances and depression [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Sleep deprivation impairs cognitive functions such as memory, attention, and overall mental clarity, thereby hindering both academic performance and personal well-being [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As Curcio et al. observed, the quality and quantity of sleep are key factors influencing learning and academic success among students [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe prevalence of poor sleep quality among medical students has been reported in various countries, including India (49.16%), Ethiopia (62%) and Yemen (68%) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Key factors influencing sleep quality include gender, academic level, and socioeconomic status [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While certain studies have found that female medical students report poorer sleep quality compared to their male counterparts, other research emphasizes that these gender differences vary based on context-specific factors such as stress intensity, hormonal fluctuations, and cultural expectations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, sleep quality often declines with advancing academic level, and students from lower socioeconomic backgrounds typically experience more pronounced sleep disturbances [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to sleep disturbances, depression is a prevalent mental health issue among medical students, marked by persistent sadness, loss of interest in activities, and a wide range of emotional and physical symptoms [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A meta-analysis by Long Zhail et al. found that individuals who sleep less than or more than the recommended 7\u0026ndash;9 hours per night are more likely to experience depressive symptoms than those with normal sleep patterns [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Similarly, Perotta et al. demonstrated that medical students with higher depression scores also report greater daytime sleepiness [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite extensive investigations into sleep quality and mental health among medical students globally, studies specifically focusing on the Middle East and North Africa (MENA) region remain scarce [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This gap highlights the need for region-specific studies to understand how cultural, academic, and socio-economic factors influence sleep quality and depression in medical students from MENA countries, such as Jordan, Syria, Algeria, Palestine, Egypt, and Yemen. This study seeks to fill this gap by examining the intersection of sleep disturbances and depression in medical students across these countries, with a focus on how socio-demographic factors impact these outcomes. Therefore, this study aims to answer the following research question: To what extent do sleep disturbances correlate with depressive symptoms among medical students in MENA countries, and how do socio-demographic factors such as gender, academic level, and socioeconomic status moderate this relationship?\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was an online, multicenter, cross-sectional study that targeted medical students from Algeria, Egypt, Syria, Jordan, Palestine, and Yemen and was conducted in April and May 2024. The study initially adopted a convenience sampling technique, obtaining information from medical students who were readily available and willing to participate. This method was chosen for its simplicity and ease of access, allowing rapid data collection. However, convenience sampling may introduce selection bias since participants might not fully represent the broader medical student population. To augment the sample diversity, snowball sampling was subsequently employed, where initial participants referred other medical students likely to be interested in the study. This approach helps broaden the participation but may also lead to network bias, as recruits could share similar characteristics or be confined to the same social circles. By combining these methods, we aimed to maximize data collection; however, the non-probability nature of these techniques limits the generalizability of our findings, which should be considered when interpreting the results. A target of a minimum of 384 participants was set after calculating the required sample size using the following equation: A target minimum of 384 participants was set after calculating the required sample size using the following equation:\u003c/p\u003e \u003cp\u003eN = (z^2 * p * q) / d^2\u003c/p\u003e \u003cp\u003eWhere N is the sample size, z is the reliability coefficient, which is equivalent to 1.96 to get a 95% coefficient of confidence, p\u0026thinsp;=\u0026thinsp;0.5 to get the largest sample size, this is the expected proportion, q\u0026thinsp;=\u0026thinsp;1 \u0026ndash; p\u0026thinsp;=\u0026thinsp;0.5 and d\u0026thinsp;=\u0026thinsp;0.05 the maximum acceptable error margin. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHowever, a much larger sample was obtained, with 773 in number, which increased the statistical strength of this study. We used the STROBE cross-sectional reporting guidelines [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMaterials and data collection\u003c/h3\u003e\n\u003cp\u003eIn this study, data were collected through an online self-completed questionnaire, which was simultaneously in Arabic and could be completed by any participant residing anywhere with an internet connection. Students were urged to complete the survey via different social media channels and platforms of the universities, students\u0026rsquo; groups in Telegram, mailing lists containing students, etc.\u003c/p\u003e \u003cp\u003eThe data were collected without any identification information of the subjects involved in the study. It has to be pointed out that all the respondents were volunteering, and no gifts, discounts, or other types of incentives were to be offered.\u003c/p\u003e \u003cp\u003eThe instruments used in this study were the Pittsburgh Sleep Quality Index (PSQI) and the Beck Depression Inventory (BDI). Recognizing the linguistic diversity and dialectal variations across countries in the Middle East and North Africa (MENA) region, the survey was conducted in Arabic with careful consideration of these differences. Each author was personally engaged in the dissemination of the survey and the adaptation to the local dialects of their respective countries. The questions were meticulously translated and culturally adapted to ensure that the original meanings were preserved across different dialects and cultural contexts. This process aimed to enhance the clarity and relevance of the survey, facilitating better understanding among participants. The adapted questionnaires were then retested for content validity by a panel of experts from the MENA region. This panel assessed the translated items for linguistic clarity, cultural appropriateness, and conceptual equivalence to the original instruments. Before the main study, the instruments were piloted on 25 medical students to evaluate their comprehensibility and reliability. Data collected from this pilot study were not included in the final analysis. The questionnaire comprised a section for demographic data and the following standardized instruments:\u003c/p\u003e\n\u003ch3\u003ePittsburgh Sleep Quality Index (PSQI): \u003c/h3\u003e\n\u003cp\u003eThe PSQI is one of the most frequently utilized self-administered questionnaires that assess sleep quality and its interruptions [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. It comprises 19 individual items, assembled into seven component scores: self-reported sleep quality, sleeping amount of activity, total night\u0026rsquo;s sleep, habitual sleep efficiency, nighttime awakenings, prescription sleep medications, and daytime impairment. Every factor is assessed using the scale of figures ranging from 0 to 3, in which Fig.\u0026nbsp;3 denotes the worst possible scenario. The scores of the seven components are then added up to obtain the global PSQI score, which ranges from 0\u0026ndash;21. The global PSQI score was used, where a higher value of the score indicated poorer sleep quality. Thus, a PSQI global score above 5 was considered as poor sleep quality and a PSQI global score of 5 or below was considered as good sleep quality. It was also gauged that the reliability of the scale was high as noticed from Cronbach\u0026rsquo;s alpha, which was 0. 886.\u003c/p\u003e\n\u003ch3\u003eBeck Depression Inventory (BDI):\u003c/h3\u003e\n\u003cp\u003eBDI is a well-known self-completed 21-item scale that measures the level of depressive symptoms in adolescents and adults [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. They bring four statements each corresponding to one of the symptoms of depression, something like pessimism, guilt, loss of appetite, and so on. These statements are extended to observe the severity level and respondents chose that statement which describes their feelings in recent days. They get indices from 0 to 3, and higher numeration reflects more severe depressive symptoms. The BDI points total all 21 items, ranging from 0 to 63.\u003c/p\u003e \u003cp\u003eThe interpretation of BDI scores is as follows: score range: 0 to 9 points No depression; 10 to 18 points Mild depression; 19 to 29 points Moderate depression; 30 to 63 points Severe depression. Inner consistency was checked by way of Cronbach\u0026rsquo;s Alpha reliability coefficient of 0.891 .\u003c/p\u003e \u003cp\u003eArabic versions of the PSQI and BDI that have been previously translated and normed were employed in this study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eEthical consideration\u003c/h3\u003e\n\u003cp\u003e Prior to participation, informed consent was obtained from all participants. The procedures of this study complied with the ethical standards outlined in the Declaration of Helsinki. Ethical approval was granted by the Institutional Review Board (IRB) of Al-Balqa Applied University (Approval No. 26/3/2/1279) and the ethical committees of the universities in the six participating countries.\u003c/p\u003e \u003cp\u003eParticipants received detailed information about the study's purpose, procedures, potential risks and benefits, and assurances of confidentiality. Before completing the questionnaire, they provided consent by agreeing to an assent form, affirming that they met the eligibility criteria and were willing to partake in the research. They were informed that their participation was voluntary and that they had the right to withdraw from the study at any time without penalty. All personal data were kept confidential and securely stored, with results reported in aggregate form to protect individual identities. Data were anonymized by assigning codes to each participant, and all electronic data were stored on a secure, password-protected server accessible only to the research team. The collected data will be used solely for research purposes.\u003c/p\u003e \u003cp\u003e Additionally, participants were encouraged to ask any questions they had about the study, and they received comprehensive answers to ensure they fully understood before providing consent. Compliance with national regulations and ethical guidelines in each participating country was maintained throughout the research.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo test the research questions and hypotheses, the data were analyzed by employing Jamovi version 2.3.28.\u003c/p\u003e \u003cp\u003eAssessment of Data Normality:\u003c/p\u003e \u003cp\u003eData normality was evaluated using the Shapiro-Wilk test. Given that the test yielded a p-value below 0.05, we concluded that the continuous variables did not follow a normal distribution. As a result, non-parametric methods were deemed more appropriate for subsequent analyses.\u003c/p\u003e \u003cp\u003eDescriptive Statistics:\u003c/p\u003e \u003cp\u003eFor non-normally distributed continuous variables, descriptive statistics are reported as the median accompanied by the interquartile range (IQR).\u003c/p\u003e \u003cp\u003eGroup Comparisons:\u003c/p\u003e \u003cp\u003eTo compare non-normally distributed continuous variables across more than two groups (e.g., country income level, hours of social media use, caffeine consumption, napping habits, and age), the Kruskal-Wallis test was employed.\u003c/p\u003e \u003cp\u003eFor comparisons involving two groups (e.g., gender, education level, residency area, place of living, and sleep cycle), the Mann-Whitney U test was used.\u003c/p\u003e \u003cp\u003eAddressing Confounding Factors:\u003c/p\u003e \u003cp\u003eTo investigate the relationship between sleep quality and depression, a linear regression analysis was conducted with the PSQI as the dependent variable and the BDI as the independent variable. This model allowed us to control for potential confounding variables by including them as covariates. Each confounder was evaluated to ensure that it met the underlying assumptions of linear regression, such as linearity, independence, and homoscedasticity. The regression coefficient (β) provided insight into the magnitude of the association, while the accompanying p-value determined its statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographics\u003c/h2\u003e \u003cp\u003eOur cross-sectional study aims to explain the prevalence and connection between sleep quality and depression within the target medical students. The sample size of our study was 773 individuals, and most participants were 21\u0026ndash;25 years old (64.8%). The identified proportion of females compared to males was 64.2% and 35.8%, respectively. Most participants were distributed between preclinical and clinical with a difference of 49.9% and 50.1%, respectively. The countries where our participants came from are Palestine 14.1%, Egypt 14.5%, Algeria 20.1%, Jordan 20.4%, Syria 15.1%, and Yemen 15.8%. Most students living in urban areas make up 74.9% of the population and are in the middle of family income, 78.8%. The percentage of students living with families and on-campus housing is 78.4% and 21.6% respectively. Examining lifestyle patterns, an overwhelming majority allocate roughly three or more hours daily to social media engagement (69.9%) and often consume caffeine once or twice daily (46.8%). With occasional nappers representing 52.4% of the group, sleep is most common at night for almost three-quarters of participants (74.6%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and behavioral characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal \u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood sleep\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;375)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor sleep\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;398)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo Depression\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;222)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMild depression\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;251)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModerate depression\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;194)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSevere depression\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlgeria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155\u003c/p\u003e \u003cp\u003e(20.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003cp\u003e(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87\u003c/p\u003e \u003cp\u003e(11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e(6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e(5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEgypt\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e(6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003cp\u003e(7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e(3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18(2.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eJordan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003cp\u003e(20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003cp\u003e(9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003cp\u003e(7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003cp\u003e(6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37\u003c/p\u003e \u003cp\u003e(4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePalestine\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003cp\u003e(14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e(5.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003cp\u003e(3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSyria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117\u003c/p\u003e \u003cp\u003e(15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003cp\u003e(7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e(3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003cp\u003e(4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e(1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYemen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003cp\u003e(15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003cp\u003e(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003cp\u003e(6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e(5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48\u003c/p\u003e \u003cp\u003e(6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003cp\u003e(14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003cp\u003e(9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e(3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMiddle income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e609\u003c/p\u003e \u003cp\u003e(78.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311\u003c/p\u003e \u003cp\u003e(40.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298\u003c/p\u003e \u003cp\u003e(38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e175\u003c/p\u003e \u003cp\u003e(22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e211\u003c/p\u003e \u003cp\u003e(27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e145\u003c/p\u003e \u003cp\u003e(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78\u003c/p\u003e \u003cp\u003e(10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003cp\u003e(2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e(1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003cp\u003e(0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThe number of hours you use social media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLess than an hour a day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e(1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e(1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e(0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOne or two hours a day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202\u003c/p\u003e \u003cp\u003e(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003cp\u003e(13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003cp\u003e(9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63\u003c/p\u003e \u003cp\u003e(8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThree or more hours a day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e540\u003c/p\u003e \u003cp\u003e(69.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003cp\u003e(32.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e286\u003c/p\u003e \u003cp\u003e(37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139\u003c/p\u003e \u003cp\u003e(18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e179\u003c/p\u003e \u003cp\u003e(23.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e133\u003c/p\u003e \u003cp\u003e(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89\u003c/p\u003e \u003cp\u003e(11.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaffeine consumption (coffee, tea, Yerba mate) daily\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLess than a cup daily\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225\u003c/p\u003e \u003cp\u003e(29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003cp\u003e(15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103\u003c/p\u003e \u003cp\u003e(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77\u003c/p\u003e \u003cp\u003e(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e(6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOne or two cups daily\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e362\u003c/p\u003e \u003cp\u003e(46.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179\u003c/p\u003e \u003cp\u003e(23.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108\u003c/p\u003e \u003cp\u003e(14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126\u003c/p\u003e \u003cp\u003e(16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89\u003c/p\u003e \u003cp\u003e(11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39\u003c/p\u003e \u003cp\u003e(5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThree or more cups daily\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186\u003c/p\u003e \u003cp\u003e(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003cp\u003e(9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003cp\u003e(5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNapping\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307\u003c/p\u003e \u003cp\u003e(39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003cp\u003e(16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176\u003c/p\u003e \u003cp\u003e(22.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003cp\u003e(8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e104\u003c/p\u003e \u003cp\u003e(13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83\u003c/p\u003e \u003cp\u003e(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYes, sometimes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e5(52.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003cp\u003e(27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190\u003c/p\u003e \u003cp\u003e(24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132\u003c/p\u003e \u003cp\u003e(17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e133\u003c/p\u003e \u003cp\u003e(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e49\u003c/p\u003e \u003cp\u003e(6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYes, always\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003cp\u003e(7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e(3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235\u003c/p\u003e \u003cp\u003e(30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003cp\u003e(12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137\u003c/p\u003e \u003cp\u003e(17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e(6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70\u003c/p\u003e \u003cp\u003e(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e(3.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e21\u0026ndash;25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e501\u003c/p\u003e \u003cp\u003e(64.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e263\u003c/p\u003e \u003cp\u003e(34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e238\u003c/p\u003e \u003cp\u003e(30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164\u003c/p\u003e \u003cp\u003e(21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e149\u003c/p\u003e \u003cp\u003e(19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e113\u003c/p\u003e \u003cp\u003e(14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75\u003c/p\u003e \u003cp\u003e(9.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003cp\u003e(4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e(1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e(0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e496\u003c/p\u003e \u003cp\u003e(64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231\u003c/p\u003e \u003cp\u003e(29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e265\u003c/p\u003e \u003cp\u003e(34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003cp\u003e(16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e162\u003c/p\u003e \u003cp\u003e(21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e125\u003c/p\u003e \u003cp\u003e(16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80\u003c/p\u003e \u003cp\u003e(10.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e277\u003c/p\u003e \u003cp\u003e(35.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003cp\u003e(18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133\u003c/p\u003e \u003cp\u003e(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003cp\u003e(11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92\u003c/p\u003e \u003cp\u003e(11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67\u003c/p\u003e \u003cp\u003e(8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreclinical stage (1-2-3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e386\u003c/p\u003e \u003cp\u003e(49.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003cp\u003e(24.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197\u003c/p\u003e \u003cp\u003e(25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109\u003c/p\u003e \u003cp\u003e(14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e133\u003c/p\u003e \u003cp\u003e(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e101\u003c/p\u003e \u003cp\u003e(13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical stage (4-5-6-7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387\u003c/p\u003e \u003cp\u003e(50.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003cp\u003e(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201\u003c/p\u003e \u003cp\u003e(26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003cp\u003e(14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e121\u003c/p\u003e \u003cp\u003e(15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence area\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e579\u003c/p\u003e \u003cp\u003e(74.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282\u003c/p\u003e \u003cp\u003e(36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e(38.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160\u003c/p\u003e \u003cp\u003e(20.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e201\u003c/p\u003e \u003cp\u003e(26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e145\u003c/p\u003e \u003cp\u003e(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCountryside\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194\u003c/p\u003e \u003cp\u003e(25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003cp\u003e(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003cp\u003e(13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003cp\u003e(7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e(6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e(6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDo you currently live in on-campus or with family\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOn campus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167\u003c/p\u003e \u003cp\u003e(21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003cp\u003e(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89\u003c/p\u003e \u003cp\u003e(11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003cp\u003e(5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003cp\u003e(6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWith family\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e606\u003c/p\u003e \u003cp\u003e(78.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e(38.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309\u003c/p\u003e \u003cp\u003e(40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e178\u003c/p\u003e \u003cp\u003e(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e202\u003c/p\u003e \u003cp\u003e(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e141\u003c/p\u003e \u003cp\u003e(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e85\u003c/p\u003e \u003cp\u003e(11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep Cycle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaytime sleep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196\u003c/p\u003e \u003cp\u003e(25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123\u003c/p\u003e \u003cp\u003e(15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e(6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNight sleep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e577\u003c/p\u003e \u003cp\u003e(74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003cp\u003e(39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e275\u003c/p\u003e \u003cp\u003e(35.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184\u003c/p\u003e \u003cp\u003e(23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e189\u003c/p\u003e \u003cp\u003e(24.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e139\u003c/p\u003e \u003cp\u003e(18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eN\u003c/b\u003e\u0026thinsp;=\u0026thinsp;Number\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between PSQI and BDI\u003c/h2\u003e \u003cp\u003eThis study showed a strong relationship between PSQI as a dependent variable and BDI as an independent variable. Indeed, linear regression analysis generated an estimated value of 0.415 and a p-value of Less than 0.001 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)(Supplemental Table).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003elinear regression taking the PSQI score as the independent variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"20\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c16\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c20\" namest=\"c17\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePredictor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eEstimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eLower\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cb\u003eUpper\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e\u003cb\u003eStand. Estimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e\u003cb\u003eLower\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e\u003cb\u003eUpper\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSleep Quality\u003c/h2\u003e \u003cp\u003eThe median PSQI score in the population was 6.\u003c/p\u003e \u003cp\u003eAlgeria and Syria had average scores of 6, and Egypt had 6.5, while the lowest score was in both Yemen and Jordan at 5 and the highest was in Palestine at 8.\u003c/p\u003e \u003cp\u003eConcerning sleep quality, the data revealed that 48.5% (n\u0026thinsp;=\u0026thinsp;375) reported having good sleep, while 51.5% (n\u0026thinsp;=\u0026thinsp;398) indicated poor sleep quality.\u003c/p\u003e \u003cp\u003eOur study showed that the percentage of poor sleep quality was highest in Palestine at 59.6%. However, the highest prevalence of good sleep quality was in Yemen at 57.4% \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. 62.6% of participants never use sleep medication, however, only 25.4% reported having good sleep, while 67.7% had good sleep efficiency. 43.3% of the students had a good sleep duration, and 90.7% experienced daytime dysfunction. Only 6.0% of students showed that they did not have any sleep disturbance. However, 21.7% of the students needed less than 15 minutes to fall asleep. Participants\u0026rsquo; PSQI scores were significantly affected by several factors: the country of living (p\u0026thinsp;=\u0026thinsp;0.031), income level (p\u0026thinsp;=\u0026thinsp;0.017), usage of social media per day (p\u0026thinsp;=\u0026thinsp;0.016), caffeine consumption (p\u0026thinsp;=\u0026thinsp;0.004), gender (p\u0026thinsp;=\u0026thinsp;0.010), and sleep patterns (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, Participants\u0026rsquo; PSQI scores weren\u0026rsquo;t affected by the frequency of naps (p\u0026thinsp;=\u0026thinsp;0.50), age groups (p\u0026thinsp;=\u0026thinsp;0.076), the level of education (p\u0026thinsp;=\u0026thinsp;0.702), residential area (p\u0026thinsp;=\u0026thinsp;0.538), and changes in living arrangements (p\u0026thinsp;=\u0026thinsp;0.183) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate analysis of factors associated with the BDI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYemen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIncome level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value (Kruskal- Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThe number of hours you use social media\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than an hour a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne or two hours a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree or more hours a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCaffeine consumption (coffee, tea, Yerba mate) daily\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than a cup daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne or two cups daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree or more cups daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNapping\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, sometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, always\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.00776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.00666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreclinical stage (1-2-3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical stage (4-5-6-7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eResidence area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountryside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDo you currently live in on-campus housing or with family?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn campus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWith family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSleep Cycle\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaytime sleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNight sleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDepression\u003c/h2\u003e \u003cp\u003eThe median Beck Depression Inventory (BDI) score was 15.\u003c/p\u003e \u003cp\u003eAlgeria had an average score of 17, Egypt had 14.5, Syria had 15, and Jordan had 13.5. The lowest score was in Yemen at 12, and the highest was in Palestine at 18. Based on our findings, the distribution of BDI levels among participants was no depression in 28.7% (n\u0026thinsp;=\u0026thinsp;222), mild in 32.4% (n\u0026thinsp;=\u0026thinsp;251), moderate in 25.1% (n\u0026thinsp;=\u0026thinsp;194), and severe in 13.8% (n\u0026thinsp;=\u0026thinsp;107). The highest prevalence of no depression was observed in Jordan, at 34.8%. In contrast, Yemen reported the highest prevalence of mild depression at 39.4%. Syria had the highest rate of moderate depression, with 33.3%, while Palestine recorded the highest prevalence of severe depression at 21.1%. The overall prevalence of depression among medical students was highest among Algerian medical students, at 78.7%. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The percentages of students who reported feeling sad, guilty, punished, disappointed, and having an inferiority complex were 36.4%, 31.2%, 57.8%, 40.4%, and 42.3% respectively.\u003c/p\u003e \u003cp\u003eAbout half of the students felt like failures, discouraged about the future, cried more than usual, felt bad, slept more than normal, and worried.\u003c/p\u003e \u003cp\u003eThose who were satisfied with things were 33.2%, and those who could make decisions and work like in the past were 47.7% and 33.9%. Additionally, 38.3% of students thought of killing themselves, while 66.9% felt more tired. 64.0% of students were more irritated, and 72.8% lost interest in others. Only 28.6% noticed the change in their interest in sex. Finally, 43.1 and 38.3% of students experienced a worsening of their appetite and weight. Participants\u0026rsquo; BDI scores were significantly affected by several factors, including differences across countries (p\u0026thinsp;=\u0026thinsp;0.001), income levels (p\u0026thinsp;=\u0026thinsp;0.032), usage of social media per day (p\u0026thinsp;=\u0026thinsp;0.016), caffeine consumption (p\u0026thinsp;=\u0026thinsp;0.026), napping frequency (p\u0026thinsp;=\u0026thinsp;0.008), gender (p\u0026thinsp;=\u0026thinsp;0.008), and sleep patterns (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, Participants\u0026rsquo; BDI scores weren\u0026rsquo;t affected by age (p\u0026thinsp;=\u0026thinsp;0.086), education level (p\u0026thinsp;=\u0026thinsp;0.597), residential area (p\u0026thinsp;=\u0026thinsp;0.584), and changes in living arrangements(p\u0026thinsp;=\u0026thinsp;0.143)(Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate analysis of factors associated with the BDI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYemen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal -Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIncome level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.00893\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThe number of hours you use social media\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than an hour a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne or two hours a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree or more hours a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal -Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCaffeine consumption (coffee, tea, Yerba mate) daily\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than a cup daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne or two cups daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree or more cups daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Kruskal-Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.00945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNapping\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, sometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, always\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal -Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Kruskal -Wallis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.00636\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-value (Mann -Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreclinical stage (1-2-3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical stage (4-5-6-7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eResidence area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountryside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann -Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDo you currently live on-campus or with family?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn campus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWith family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.0739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSleep Cycle\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaytime sleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNight sleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-Value (Mann-Whitney U)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffect size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e\u003cstrong\u003eSleep Quality: Comparisons with MENA and Non-MENA Regions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study found that 51.5% of medical students in the MENA region experienced poor sleep quality, with Palestine reporting the highest prevalence (59.6%) and Yemen the lowest (42.6%). The median Pittsburgh Sleep Quality Index (PSQI) score was 6, indicating moderate student sleep disturbances. Several factors significantly influence sleep quality, including country of residence, income level, social media usage, caffeine consumption, gender, and sleep patterns.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison with MENA Studies\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilar studies across the MENA region have consistently reported high rates of poor sleep quality among medical students. For example, in Saudi Arabia, 64% of medical students exhibited poor sleep quality, while even higher rates were observed in Jordan (74%), Iran (71.1%), Iraq (87%), Qatar (70%), Syria (79.5%), and the UAE (84.3%) [24-30]. Similarly, in North Africa, the prevalence was 72.5% in Tunisia, 76.67% in Libya, and 81.7% in Morocco [31-33]. Variations in the prevalence of sleep disturbance among students across countries may stem from differing social and cultural environments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings regarding PSQI scores align with previous studies in Egypt, where the median PSQI was reported as 6.01. However, higher median PSQI scores have been reported in Iran (7.95), Iraq (8.24), Morocco (7.02), Qatar (7.57), and Jordan (8.16), suggesting more severe sleep disturbances in these countries [25-28,33,34].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe high prevalence of poor sleep quality among medical students in the MENA region can be attributed to multiple factors, including academic pressure, long study hours, high levels of stress, and lifestyle habits. The demanding nature of medical education, irregular sleep schedules, and excessive screen time likely exacerbate these disturbances. A study conducted among medical and nursing students in Morocco and Spain found that intense or weak physical activity and smartphone addiction were correlated with poor sleep quality. The multivariate analysis revealed that factors such as the country of study, involvement in nursing studies, and chronic diseases were significantly associated with poor sleep quality [33]. Furthermore, a systematic review and meta-analysis focusing on African university students identified several factors significantly associated with poor sleep quality, including being stressed during the second academic year, using electronic devices at bedtime, and having a comorbid chronic illness [35]. These findings underscore the multifaceted contributors to sleep disturbances among medical students in the MENA region, highlighting the need for targeted interventions to address these issues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, our study found that Yemen had the lowest PSQI score, indicating better sleep quality compared to other MENA countries. This finding does not align with a study by Ahmed Attal et al., which reported a PSQI score of 6.85 and a poor sleep quality prevalence of 68% among Yemeni medical students [36]. These discrepancies may stem from differences in study populations, sample sizes, or variations in academic workload and social environments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConversely, Palestine had the highest prevalence of poor sleep quality, which is consistent with the findings of Aldabbour et al. (2024), who reported a prevalence of 77.9% among medical students in Gaza [37]. This could be attributed to heightened stress levels associated with political instability, economic hardships, and limited access to mental health and healthcare resources. Chronic exposure to external stressors may contribute to disrupted sleep patterns and poor overall sleep health in Palestinian students [37].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison with non-MENA Studies\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlobally, the prevalence of poor sleep quality among medical students varies. Some countries report prevalence rates consistent with our findings, such as Vietnam (50.27%, PSQI = 5.8) and India (45%, PSQI = 5.8) [38,39]. However, higher prevalence rates have been observed in Brazil (87.1%), Indonesia (\u0026gt;85%), and Macedonia (\u0026gt;60%, PSQI = 8), suggesting more severe sleep disturbances in these regions [40,41]. In contrast, Pakistan reported a lower prevalence (39.5%), indicating comparatively better sleep quality [42,43].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA meta-analysis found a 65% prevalence of poor sleep quality among European medical students, with similar rates in France (65%, PSQI = 7.2) and North America (59.92%) [44,45]. These findings highlight that sleep disturbances are a widespread issue among medical students globally, influenced by academic stress, lifestyle factors, and socioeconomic conditions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepression Among Medical Students: MENA vs. Non-MENA Regions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence in the MENA Region\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Our study found a high prevalence of depression (71.3%) among medical students in the MENA region, with 13.8% experiencing severe depression. Palestine had the highest rate of severe depression (21.1%), while Jordan had the lowest overall prevalence (34.8% of students were not depressed). The median BDI score was 15, ranging from 18 in Palestine to 12 in Yemen. Depression levels were significantly influenced by country of residence, income, social media use, caffeine intake, gender, sleep habits, and napping frequency.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison with MENA Studies\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepression rates vary across MENA countries, likely due to differences in assessment tools, cultural attitudes, and academic stressors. Studies reported prevalence rates of 64% in Tunisia and 69% in Palestine, which consists of our findings, with the lower prevalence found at 40% in Bahrain and 45% in Libya [37,46-48]. In Lebanon, about one-third of medical students had major depression, while in Saudi Arabia, 30.9% reported depressive symptoms, with 2.9% experiencing severe depression [49,50].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison with non-MENA Regions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepression among medical students outside the MENA region varies, with some countries reporting lower prevalence while others show comparably high rates. Lower but still concerning rates are reported in Pakistan (19.5%), China (29%), Africa (38.8%), Brazil (40%), Bulgaria (47.1%), and India (50%) [35,51-55]. These findings indicate that depression is a widespread issue among medical students, although regional variations are affected by academic stress, cultural expectations, and socioeconomic factors. Notably, Peru (71.6%) and Turkey (\u0026gt;70%) report depression rates similar to those in the MENA region, indicating that certain stressors may be shared across different countries [54-56]. The high prevalence in these countries might be attributed to intense academic workloads, financial burdens, and limited access to mental health support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA systematic review and meta-analysis reported a pooled prevalence of depression among medical students in the Middle East at 43.6%, which is higher compared to other regions such as North and South America (30.2%), Europe (23.9%) and Asia (26.6%) [57]. This disparity may be attributed to better mental health infrastructure, greater psychological well-being awareness, and stronger student support systems in these regions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Depression and Poor Sleep Quality\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study identified a significant positive correlation between poor sleep quality and increased depression scores among medical students. This finding aligns with previous research indicating that students experiencing higher levels of depression are more prone to sleep disturbances and vice versa [37,52,57,58]. The bidirectional relationship between sleep and depression is well-documented, suggesting that poor sleep quality can exacerbate depressive symptoms, while depression itself is linked to sleep disorders such as insomnia and frequent nighttime awakenings [59,60]. For instance, a systematic review highlighted that poor sleep quality is significantly associated with depression or depressive symptoms among college students. The review emphasized the importance of sleep quality as a relevant variable in this relationship [61]. Disruptions in circadian rhythms (the body's internal biological clock) have been strongly linked to depression. These disturbances can impair melatonin secretion, a hormone critical for regulating sleep, leading to sleep problems and exacerbating depressive symptoms. Research also suggests that individuals with depression often experience reduced nocturnal melatonin release, which may contribute to the sleep disturbances commonly reported among depressive patients [62,63].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors Influencing Sleep and Depression: A Global Perspective\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study identified several key factors influencing both sleep quality and depression, including social media usage, caffeine consumption, and gender. These findings align with global research indicating that excessive social media use and high caffeine intake are associated with sleep disturbances and increased psychological stress.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe observed that female medical students generally experienced poorer sleep and higher depression levels, a pattern well-documented in the literature [28,30,32,43,45,46,53,55]. Studies suggest that biological factors such as hormonal fluctuations, as well as psychological and sociocultural influences like increased family responsibilities, contribute to these disparities [64,65]. Contrary to expectations, a study conducted in Yemen found that males were at a higher risk of poor sleep than females [36]. However, several studies have reported no significant correlation between gender and sleep quality or depression [25,31,34,37,66].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study found a negative correlation between caffeine consumption and sleep quality, reinforcing existing evidence that caffeine, as a central nervous system stimulant, disrupts sleep patterns and reduces sleep efficiency [67,68]. However, a study conducted in Jordan found no significant correlation between caffeine intake and sleep quality [25], suggesting that individual tolerance levels and consumption habits may moderate its effects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsistent with our findings, research by Jassem et al. and Bousgheiri et al. highlighted a significant correlation between smartphone use and poor sleep quality [29,33]. Excessive use of electronic devices before bedtime disrupts sleep due to blue light exposure, which suppresses melatonin secretion and alters circadian rhythms\u003ca href=\"https://sciwheel.com/work/citation?ids=433882\u0026amp;pre=\u0026amp;suf=\u0026amp;sa=0\u0026amp;dbf=0\"\u003e\u0026nbsp;\u003c/a\u003e[69]. A meta-analysis of multinational observational studies assessing the prevalence of smartphone addiction among Asian medical students reported that the prevalence was 41.93%. The study also found that smartphone addiction was positively correlated with poor sleep quality, stress, anxiety, depression, neuroticism, and overall health issues among this population [70]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings also support the association between lower socioeconomic status and depression, consistent with the study by Amamou et al. among medical students in Tunisia [46]. Financial stress has been widely recognized as a risk factor for depression in both general and student populations [71-73]. These findings highlight the importance of addressing economic stressors as part of mental health interventions for medical students.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the findings of this study and supporting literature, the following recommendations are proposed to improve sleep quality, mental well-being, and academic performance among medical students:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1. Implement Psychological and Behavioral Interventions for Sleep Improvement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the strong link between poor sleep quality and depression, medical schools should integrate evidence-based psychological interventions such as Cognitive-Behavioral Therapy for Insomnia (CBT-I) and Mindfulness-Based Stress Reduction (MBSR). A meta-analysis by Saruhanjan et al. demonstrated that psychological interventions significantly improve sleep quality and reduce sleep disturbances [74]. Additionally, MBSR has been shown to effectively reduce anxiety and depression among medical students and should be incorporated into wellness programs [75]. Future research should explore the long-term impact of these interventions in high-demand academic settings to ensure their feasibility and effectiveness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Encourage Healthy Lifestyle Habits and Stress Management\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdopting sleep hygiene practices is essential for improving sleep quality, as a review by Irish et al. highlights that consistent sleep timing, stress management, noise reduction, and avoiding caffeine, nicotine, and alcohol contribute to better rest [76]. Medical schools should implement sleep education programs and stress management workshops to promote these practices. Additionally, regular physical activity has been shown to mitigate the negative impact of smartphone addiction on sleep quality and should be encouraged as a protective strategy [77]. Structured mental health programs should also incorporate mindfulness and relaxation techniques, including meditation, breathing exercises, and stress management strategies, to support students' overall well-being.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. Address Caffeine Consumption and Its Impact on Sleep\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eReducing excessive caffeine consumption is crucial, as high caffeine intake among medical students negatively impacts sleep quality. A literature review by Behling identified effective strategies for reducing caffeine use, including gradual dose tapering, caffeine intake journaling, daily exercise, and professional counseling [78]. Additionally, a case study by McIntosh \u0026amp; Heath demonstrated that a structured caffeine reduction plan, combined with behavioral tracking, successfully reduced caffeine intake over two months [79]. To support students in managing their caffeine intake, medical schools should implement structured interventions such as counseling, self-monitoring tools, and awareness campaigns. A randomized controlled trial by Evatt et al. showed that a brief, therapist-guided intervention significantly reduced caffeine consumption with sustained long-term effects [80]. Future research should assess the effectiveness of these interventions on sleep quality, academic performance, and mental health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4. Mitigate the Impact of Screen Time on Sleep Quality\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLimiting blue light exposure before bedtime is essential, as excessive screen use negatively impacts sleep quality. A study by Guarana et al. found that wearing blue-light filtering glasses improved both the quantity and quality of sleep. This led to enhanced work engagement, better task performance, and a reduction in counterproductive behaviors [81].To reduce the impact of blue light, medical students should use blue-light filtering glasses, enable blue-light reduction settings on their devices, and limit their screen time before sleep. Institutions should promote awareness of the impact of blue light on cognitive performance and sleep. Further research is needed to assess the long-term benefits of blue-light filtration on student health and academic performance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5. Explore Technological Aids for Sleep Enhancement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA study by Barnes et al. demonstrated that closed-loop acoustic stimulation, a sound-based wearable technology, significantly improved sleep quality, leading to higher work engagement, task performance, and organizational citizenship behaviors [82]. Future research should investigate the use of sleep-enhancing wearable devices as a practical and cost-effective tool for medical students. Furthermore, sleep hygiene education programs should incorporate technological solutions alongside behavioral strategies to enhance sleep quality and overall well-being.\u003c/p\u003e\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\u003ch3\u003eLimitations and strengths \u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003e1. \u003cstrong\u003eConvenience Sampling:\u003c/strong\u003e The study adopted a convenience sampling technique, which may introduce selection bias as it relies on students willing and able to participate. This method may not fully represent the entire population of medical students in the target countries, potentially affecting the generalizability of the results.\u003c/p\u003e\u003cp\u003e2. \u003cstrong\u003eSnowball Sampling:\u003c/strong\u003e While snowball sampling helped expand the scope and obtain a more diverse sample, it carries a risk of network bias. Participants may tend to recruit peers from similar social circles, which might limit the diversity of the sample and introduce biases related to specific groups or demographics.\u003c/p\u003e\u003cp\u003e3. \u003cstrong\u003eGeographical Limitations:\u003c/strong\u003e The study was conducted in a limited number of MENA countries, which may not fully capture the diversity and variations across the entire region. Future research should aim to include a broader range of countries to validate and extend the findings.\u003c/p\u003e\u003cp\u003e4. \u003cstrong\u003eSelf-Reported Data:\u003c/strong\u003e The reliance on self-reported data from participants may introduce recall bias and social desirability bias. Participants may not accurately recall or report their behaviors and experiences, which could affect the accuracy of the data.\u003c/p\u003e\u003cp\u003e5. \u003cstrong\u003eCross-Sectional Design:\u003c/strong\u003e The study's cross-sectional design does not establish causality between variables. While associations can be identified, it is not possible to determine cause-and-effect relationships.\u003c/p\u003e\u003cp\u003e6. \u003cstrong\u003eResource Constraints:\u003c/strong\u003e Limited resources and logistical challenges restricted the ability to include a larger and more representative sample. This limitation highlights the need for increased funding and support for future research.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eStrengths\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e1.\u003cstrong\u003e\u0026nbsp;Comprehensive Evaluation:\u003c/strong\u003e This study provides one of the first reviews of sleep quality and depression among medical students in multiple countries across the MENA region, offering valuable insights into these critical health issues.\u003c/p\u003e\u003cp\u003e2. \u003cstrong\u003eDiverse Sample:\u003c/strong\u003e The inclusion of students from six different countries enhances the generalizability of the findings and provides a broader perspective on the prevalence and factors associated with poor sleep quality and depression in the region.\u003c/p\u003e\u003cp\u003e3. \u003cstrong\u003eUse of Standardized Instruments:\u003c/strong\u003e The study utilized well-established and validated instruments (PSQI and BDI) to assess sleep quality and depression, ensuring the reliability and comparability of the results with other studies.\u003c/p\u003e\u003cp\u003e4. \u003cstrong\u003eMixed Sampling Methods:\u003c/strong\u003e The combination of convenience and snowball sampling techniques allowed for the inclusion of a diverse group of participants, increasing the representativeness of the sample and helping to capture a wide range of experiences and perspectives.\u003c/p\u003e\u003cp\u003e5. \u003cstrong\u003ePilot Testing:\u003c/strong\u003e The generated questions were retested for content validity before being used in the main study. This step ensured that the questions were culturally and contextually appropriate for the target population.\u003c/p\u003e\u003cp\u003e6. \u003cstrong\u003eFocus on a Neglected Population:\u003c/strong\u003e By focusing on medical students, the study highlights a group that is often overlooked in mental health research,yet is at high risk for poor sleep quality and depression due to the unique stresses of medical education.\u003c/p\u003e\u003cp\u003e7. \u003cstrong\u003ePractical Implications:\u003c/strong\u003e The findings offer practical recommendations for policymakers and educational institutions to address and mitigate the issues of poor sleep quality and depression among medical students, potentially leading to improved mental health outcomes in this population.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrates that poor sleep quality and depression are both prevalent and strongly correlated among medical students in the MENA region a finding that directly aligns with our research objectives. These results underscore a serious public health concern, urging policymakers to implement targeted interventions such as enhanced counseling services, integrated mental health education, and robust sleep hygiene programs. Immediate, coordinated action is essential to safeguard students' well-being and academic performance, ultimately fostering a healthier future generation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePSQI: Pittsburgh Sleep Quality Index, BDI: Beck Depression Inventory, MENA: Middle East and North Africa\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCollaborators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbrar Nadhem, Ahmed Reda, Ghadeer Al-Surabi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe want to thank Dr. Omar Alrashid Alhirak for providing support and advice\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributor\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTA, AD, and KF designed the study, TA conducted the analysis, TA, AD, AA, AZA, and AM, collected the data, and wrote the manuscript. All authors contributed substantially to the interpretation of the study findings. All authors reviewed, contributed to, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData are available in a public, open-access repository.\u003c/p\u003e\n\u003cp\u003eAll data related to the analyses and results of this study are freely accessible at the\u003c/p\u003e\n\u003cp\u003eOpen Science Framework and can be reused when given appropriate attribution.\u003c/p\u003e\n\u003cp\u003eThe data are licensed to the first author and can be obtained at\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData.xlsx\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethical committee of Al-Balqa Applied University. The local approval number of IRB was (26/3/2/1279).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWondie T, Molla A, Mulat H, \u003cem\u003eet al.\u003c/em\u003e Magnitude and correlates of sleep quality among undergraduate medical students in Ethiopia: cross-sectional study. \u003cem\u003eSleep Science Practice\u003c/em\u003e 2021;\u003cstrong\u003e5\u003c/strong\u003e:7. doi:10.1186/s41606-021-00058-2\u003c/li\u003e\n\u003cli\u003eNeufeld A, Malin G. How medical students cope with stress: a cross-sectional look at strategies and their sociodemographic antecedents. \u003cem\u003eBMC Med Educ\u003c/em\u003e 2021;\u003cstrong\u003e21\u003c/strong\u003e:299. doi:10.1186/s12909-021-02734-4\u003c/li\u003e\n\u003cli\u003ePerotta B, Arantes-Costa FM, Enns SC, \u003cem\u003eet al.\u003c/em\u003e Sleepiness, sleep deprivation, quality of life, mental symptoms and perception of academic environment in medical students. \u003cem\u003eBMC Med Educ\u003c/em\u003e 2021;\u003cstrong\u003e21\u003c/strong\u003e:111. doi:10.1186/s12909-021-02544-8\u003c/li\u003e\n\u003cli\u003eOmer M. The impact of sleep quality on cognitive function in healthy adults: A cross-sectional study. \u003cem\u003eJ Neurol Sci\u003c/em\u003e 2023;\u003cstrong\u003e455\u003c/strong\u003e:121609. doi:10.1016/j.jns.2023.121609\u003c/li\u003e\n\u003cli\u003eCurcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity and academic performance. \u003cem\u003eSleep Med Rev\u003c/em\u003e 2006;\u003cstrong\u003e10\u003c/strong\u003e:323\u0026ndash;37. doi:10.1016/j.smrv.2005.11.001\u003c/li\u003e\n\u003cli\u003eMassarat Begum, Dimple Siri Chandana Puchakayala. Study to determine the prevalence of poor sleep quality and its correlation with sleep hygiene practices among medical students. \u003cem\u003eAsian J Med Sci\u003c/em\u003e 2022;\u003cstrong\u003e13\u003c/strong\u003e:151\u0026ndash;5. doi:10.3126/ajms.v13i9.46175\u003c/li\u003e\n\u003cli\u003eAttal BA, Bezdan M, Abdulqader A. Quality of Sleep and Its Correlates among Yemeni Medical Students: A Cross-Sectional Study. \u003cem\u003eSleep Disord\u003c/em\u003e 2021;\u003cstrong\u003e2021\u003c/strong\u003e:8887870. doi:10.1155/2021/8887870\u003c/li\u003e\n\u003cli\u003eSchmickler JM, Blaschke S, Robbins R, \u003cem\u003eet al.\u003c/em\u003e Determinants of Sleep Quality: A Cross-Sectional Study in University Students. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e 2023;\u003cstrong\u003e20\u003c/strong\u003e. doi:10.3390/ijerph20032019\u003c/li\u003e\n\u003cli\u003eWong WS, Fielding R. Prevalence of insomnia among Chinese adults in Hong Kong: a population-based study. J Sleep Res. 2011;20:117\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eWang Y, Li Y, Liu X, Liu R, Mao Z, Tu R, Zhang H, Zhang X, Qian X, Jiang J, et al. Gender-specific prevalence of poor sleep quality and related factors in a Chinese rural population: the Henan rural cohort study. Sleep Med. 2019;54:134\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eLi, Y., Bai, W., Zhu, B. et al. Prevalence and correlates of poor sleep quality among college students: a cross-sectional survey. Health Qual Life Outcomes 18, 210 (2020). https://doi.org/10.1186/s12955-020-01465-2\u003c/li\u003e\n\u003cli\u003eSundas N, Ghimire S, Bhusal S, \u003cem\u003eet al.\u003c/em\u003e Sleep Quality among Medical Students of a Tertiary Care Hospital: A Descriptive Cross-sectional Study. \u003cem\u003eJNMA J Nepal Med Assoc\u003c/em\u003e 2020;\u003cstrong\u003e58\u003c/strong\u003e:76\u0026ndash;9. doi:10.31729/jnma.4813 \u003c/li\u003e\n\u003cli\u003eYilmaz D, Tanrikulu F, Dikmen Y. Research on sleep quality and the factors affecting the sleep quality of the nursing students. \u003cem\u003eCurr Health Sci J\u003c/em\u003e 2017;\u003cstrong\u003e43\u003c/strong\u003e:20\u0026ndash;4. doi:10.12865/CHSJ.43.01.03\u003c/li\u003e\n\u003cli\u003eGrandner MA, Patel NP, Gehrman PR, \u003cem\u003eet al.\u003c/em\u003e Who gets the best sleep? Ethnic and socioeconomic factors related to sleep complaints. \u003cem\u003eSleep Med\u003c/em\u003e 2010;\u003cstrong\u003e11\u003c/strong\u003e:470\u0026ndash;8. doi:10.1016/j.sleep.2009.10.006\u003c/li\u003e\n\u003cli\u003eNgasa SN, Sama C-B, Dzekem BS, \u003cem\u003eet al.\u003c/em\u003e Prevalence and factors associated with depression among medical students in Cameroon: a cross-sectional study. \u003cem\u003eBMC Psychiatry\u003c/em\u003e 2017;\u003cstrong\u003e17\u003c/strong\u003e:216. doi:10.1186/s12888-017-1382-3\u003c/li\u003e\n\u003cli\u003eZhai L, Zhang H, Zhang D. Sleep duration and depression among adults: a meta-analysis of prospective studies. \u003cem\u003eDepress Anxiety\u003c/em\u003e 2015;\u003cstrong\u003e32\u003c/strong\u003e:664\u0026ndash;70. doi:10.1002/da.22386\u003c/li\u003e\n\u003cli\u003eFawzy M, Hamed SA. Prevalence of psychological stress, depression and anxiety among medical students in Egypt. \u003cem\u003ePsychiatry Res\u003c/em\u003e 2017;\u003cstrong\u003e255\u003c/strong\u003e:186\u0026ndash;94. doi:10.1016/j.psychres.2017.05.027\u003c/li\u003e\n\u003cli\u003eBarlett JE, Kotrlik J, Higgins C. Organizational Research: Determining Appropriate Sample Size in Survey Research. Information Technology, Learning, and Performance Journal 2001;19.\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008;61:344\u0026ndash;9. doi:10.1016/j.jclinepi.2007.11.008\u003c/li\u003e\n\u003cli\u003eBuysse DJ, Reynolds CF, Monk TH, \u003cem\u003eet al.\u003c/em\u003e The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. \u003cem\u003ePsychiatry Res\u003c/em\u003e 1989;\u003cstrong\u003e28\u003c/strong\u003e:193\u0026ndash;213. doi:10.1016/0165-1781(89)90047-4\u003c/li\u003e\n\u003cli\u003eSalkind MR. Beck depression inventory in general practice. \u003cem\u003eJ R Coll Gen Pract\u003c/em\u003e 1969;\u003cstrong\u003e18\u003c/strong\u003e:267\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eSuleiman KH, Yates BC, Berger AM, \u003cem\u003eet al.\u003c/em\u003e Translating the Pittsburgh Sleep Quality Index into Arabic. \u003cem\u003eWest J Nurs Res\u003c/em\u003e 2010;\u003cstrong\u003e32\u003c/strong\u003e:250\u0026ndash;68. doi:10.1177/0193945909348230\u003c/li\u003e\n\u003cli\u003eWest J. An Arabic validation of a depression inventory. \u003cem\u003eInt J Soc Psychiatry\u003c/em\u003e 1985;\u003cstrong\u003e31\u003c/strong\u003e:282\u0026ndash;9. doi:10.1177/002076408503100406\u003c/li\u003e\n\u003cli\u003eAlmojali AI, Almalki SA, Alothman AS, Masuadi EM, Alaqeel MK. The prevalence and association of stress with sleep quality among medical students. J Epidemiol Glob Health. 2017;7(3):169\u0026ndash;74. doi: https://doi.org/10.1016/j.jegh.2017.04.005\u003c/li\u003e\n\u003cli\u003eJaradat JH, Al-Dwairi R, Riyad J, Al-Rawashdeh I, Elmazar H. Exploring the interplay of sleep quality, stress, and academic performance in Jordanian medical students: A national perspective. JAPAJ. 2024;2(2). \u003c/li\u003e\n\u003cli\u003eShafiee A, Fili J, Ghafari S, Sattari MA, Borna N, Pourramzani A. The prevalence of sleep disturbance and its possible associated factors among Iranian medical students: A cross-sectional study with a national meta-analysis. Sleep Med X. 2024;7:100107. doi: https://doi.org/10.1016/j.sleepx.2023.100107\u003c/li\u003e\n\u003cli\u003eTaher A. AL-Kindy College of Medicine.\u003c/li\u003e\n\u003cli\u003eAli RM, Zolezzi M, Awaisu A, Eltorki Y. Sleep quality and sleep hygiene behaviors among university students in Qatar. Int J Gen Med. 2023;16:2427\u0026ndash;39. doi: https://doi.org/10.2147/IJGM.S409107\u003c/li\u003e\n\u003cli\u003eJassem M, Abdelwahed RNK, Alyousbashi A, Meer A. Evaluation of daytime sleepiness and sleep quality among resident physicians of Damascus: A cross-sectional study. Sleep Epidemiol. 2022;2:100035. doi: https://doi.org/10.1016/j.sleepe.2022.100035\u003c/li\u003e\n\u003cli\u003eMeer H, Jeyaseelan L, Sultan MA. Sleep quality and emotional state of medical students in Dubai. Sleep Disord. 2022;2022:8187547. doi: https://doi.org/10.1155/2022/8187547\u003c/li\u003e\n\u003cli\u003eSaguem BN, Nakhli J, Romdhane I, Nasr SB. Predictors of sleep quality in medical students during COVID-19 confinement. Encephale. 2022;48(1):3\u0026ndash;12. doi: https://doi.org/10.1016/j.encep.2021.01.014\u003c/li\u003e\n\u003cli\u003eEl Sahly RA, Ahmed AM, Amer SE, Alsaeiti KD. Assessment of insomnia and sleep quality among medical students at Benghazi University: A cross-sectional study. Apollo Med. 2020;17(2):73\u0026ndash;77. doi: https://doi.org/10.4103/am.am_93_19\u003c/li\u003e\n\u003cli\u003eBousgheiri F, Allouch A, Sammoud K, Navarro-Mart\u0026iacute;nez R, Ib\u0026aacute;\u0026ntilde;ez-Del Valle V, Senhaji M, et al. Factors affecting sleep quality among university medical and nursing students: A study in two countries in the Mediterranean region. Diseases. 2024;12(5):[Article number or pages]. doi: https://doi.org/10.3390/diseases12050133\u003c/li\u003e\n\u003cli\u003eElwasify M, Barakat DH, Fawzy M, Elwasify M, Rashed I, Radwan DN. Quality of sleep in a sample of Egyptian medical students. Middle East Curr Psychiatry. 2016;23(4):200\u0026ndash;207. doi: https://doi.org/10.1097/01.XME.0000507153.65164.1c\u003c/li\u003e\n\u003cli\u003eNakie G, Takelle GM, Rtbey G, Andualem F, Tinsae T, Kassa MA, et al. Sleep quality and associated factors among university students in Africa: A systematic review and meta-analysis study. Front Psychiatry. 2024;15:1370757. doi: https://doi.org/10.3389/fpsyt.2023.1370757\u003c/li\u003e\n\u003cli\u003eAttal BA, Bezdan M, Abdulqader A. Quality of sleep and its correlates among Yemeni medical students: A cross-sectional study. Sleep Disord. 2021;2021:8887870. doi: https://doi.org/10.1155/2021/8887870\u003c/li\u003e\n\u003cli\u003eAldabbour B, Jaradat R, Aljbour O, Abdu M, Aljbour J, Dayya AA, et al. Depression, anxiety, stress, sleep quality, and life satisfaction among undergraduate medical students in Gaza Strip: A cross-sectional survey. Res Sq. 2024. \u003c/li\u003e\n\u003cli\u003eTran D-S, Nguyen D-T, Nguyen T-H, Tran C-T-P, Duong-Quy S, Nguyen T-H. Stress and sleep quality in medical students: A cross-sectional study from Vietnam. Front Psychiatry. 2023;14:1297605. doi: https://doi.org/10.3389/fpsyt.2023.1297605\u003c/li\u003e\n\u003cli\u003eMishra J, Panigrahi A, Samanta P, Dash K, Mahapatra P, Behera MR. Sleep quality and associated factors among undergraduate medical students during COVID-19 confinement. Clin Epidemiol Glob Health. 2022;15:101004. doi: https://doi.org/10.1016/j.cegh.2022.101004\u003c/li\u003e\n\u003cli\u003eCorr\u0026ecirc;a CC, Oliveira FK, Pizzamiglio DS, Ortolan EVP, Weber SAT. Sleep quality in medical students: A comparison across the various phases of the medical course. J Bras Pneumol. 2017;43(4):285\u0026ndash;289. doi: https://doi.org/10.1590/S1806-37562016000000163\u003c/li\u003e\n\u003cli\u003eSaputri AD, Ritunga I. The effect of sleep quality due to stress on medical students\u0026rsquo; academic achievement: A cross-sectional study. Curr J Glob Health. 2023;10(2):52\u0026ndash;57. \u003c/li\u003e\n\u003cli\u003eMancevska S, Pislevski M, Pluncevic Gligoroska J. Assessment of sleep quality during the winter semester in undergraduate medical students enrolled at UKIM, Faculty of Medicine, Skopje, Republic of North Macedonia. JMS. 2024;7(1):17\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eSurani AA, Zahid S, Surani A, Ali S, Mubeen M, Khan RH. Sleep quality among medical students of Karachi, Pakistan. J Pak Med Assoc. 2015;65(4):380\u0026ndash;382.\u003c/li\u003e\n\u003cli\u003eRao W-W, Li W, Qi H, Hong L, Chen C, Li C-Y, et al. Sleep quality in medical students: a comprehensive meta-analysis of observational studies. Sleep Breath. 2020;24(3):1151\u0026ndash;65. doi: https://doi.org/10.1007/s11325-020-02033-4\u003c/li\u003e\n\u003cli\u003e\u0026ensp;LECOEUR Elisabeth.pdf. \u003c/li\u003e\n\u003cli\u003eAmamou B, Alouani S, Ben Haouala A, Alouani S, Tlili MA, Mhalla A, et al. Depression among medical students in Tunisia: Prevalence and associated factors. World J Psychiatry. 2023;13(10):772\u0026ndash;83. doi: https://doi.org/10.5498/wjp.v13.i10.772\u003c/li\u003e\n\u003cli\u003eMaroon ZA, Borgan SM, Kamel C, Maddison W, Royston M, Donnellan C. Factors associated with depression and anxiety symptoms among medical students in Bahrain. Acad Psychiatry. 2018;42(1):31\u0026ndash;40. doi: https://doi.org/10.1007/s40596-017-0733-1\u003c/li\u003e\n\u003cli\u003eSherif RF, Saeed NM, Sherif GA, Rabab KS, Sherif FM. Prevalence of depression among Libyan medical students. Zenodo. 2021. \u003c/li\u003e\n\u003cli\u003eNaja WJ, Kansoun AH, Haddad RS. Prevalence of depression in medical students at the Lebanese university and exploring its correlation with Facebook relevance: A questionnaire study. JMIR Res Protoc. 2016;5(2):e96. doi: https://doi.org/10.2196/resprot.4552\u003c/li\u003e\n\u003cli\u003eJarwan B. Depression among medical students of Faculty of Medicine, Umm Al-Qura University in Makkah, Saudi Arabia. Int J Med Sci Public Health. 2015;4(2):184. doi: https://doi.org/10.5455/ijmsph.2015.210920144\u003c/li\u003e\n\u003cli\u003eRab F, Mamdou R, Nasir S. Rates of depression and anxiety among female medical students in Pakistan. East Mediterr Health J. 2008;14(1):126\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eWang J, Liu M, Bai J, Chen Y, Xia J, Liang B, et al. Prevalence of common mental disorders among medical students in China: a systematic review and meta-analysis. Front Public Health. 2023;11:1116616. doi: https://doi.org/10.3389/fpubh.2023.1116616\u003c/li\u003e\n\u003cli\u003eBrenneisen Mayer F, Souza Santos I, Silveira PSP, Itaqui Lopes MH, de Souza ARND, Campos EP, et al. Factors associated to depression and anxiety in medical students: a multicenter study. BMC Med Educ. 2016;16(1):282. doi: https://doi.org/10.1186/s12909-016-0795-5\u003c/li\u003e\n\u003cli\u003eGeorgieva E, Vatansever M, Velkova A, Hristov N, Pesheva P, Simeonova I, et al. Prevalence of depression among three cohorts of medical students. Eur J Public Health. 2020;30(Supplement_5). doi: https://doi.org/10.1093/eurpub/ckaa165.1295\u003c/li\u003e\n\u003cli\u003eDutta G, Rajendran N, Kumar T, Varthya SB, Rajendran V. Prevalence of depression among undergraduate medical students in India: A systemic review and meta-analysis. Cureus. 2023;15(1):e33590. doi: https://doi.org/10.7759/cureus.33590\u003c/li\u003e\n\u003cli\u003eValladares-Garrido D, Quiroga-Casta\u0026ntilde;eda PP, Berrios-Villegas I, Zila-Velasque JP, Anchay-Zuloeta C, Chum\u0026aacute;n-S\u0026aacute;nchez M, et al. Depression, anxiety, and stress in medical students in Peru: a cross-sectional study. Front Psychiatry. 2023;14:1268872. doi: https://doi.org/10.3389/fpsyt.2023.1268872\u003c/li\u003e\n\u003cli\u003eEleftheriou A, Rokou A, Arvaniti A, Nena E, Steiropoulos P. Sleep quality and mental health of medical students in Greece during the COVID-19 pandemic. Front Public Health. 2021;9:775374. doi: https://doi.org/10.3389/fpubh.2021.775374\u003c/li\u003e\n\u003cli\u003eAlwhaibi M, Al Aloola NA. Associations between stress, anxiety, depression, and sleep quality among healthcare students. J Clin Med. 2023;12(13). doi: https://doi.org/10.3390/jcm12134782\u003c/li\u003e\n\u003cli\u003eYasugaki S, Okamura H, Kaneko A, Hayashi Y. Bidirectional relationship between sleep and depression. Neurosci Res. 2025;211:57\u0026ndash;64. doi: https://doi.org/10.1016/j.neures.2024.08.015\u003c/li\u003e\n\u003cli\u003eGregory AM, Buysse DJ, Willis TA, Rijsdijk FV, Maughan B, Rowe R, et al. Associations between sleep quality and anxiety and depression symptoms in a sample of young adult twins and siblings. J Psychosom Res. 2011;71(4):250\u0026ndash;5. doi: https://doi.org/10.1016/j.jpsychores.2011.03.011\u003c/li\u003e\n\u003cli\u003eDinis J, Bragan\u0026ccedil;a M. Quality of sleep and depression in college students: a systematic review. Sleep Sci. 2018;11(4):290\u0026ndash;301. doi: https://doi.org/10.5935/1984-0063.20180045\u003c/li\u003e\n\u003cli\u003eQuera Salva MA, Hartley S, Barbot F, Alvarez JC, Lofaso F, Guilleminault C. Circadian rhythms, melatonin, and depression. Curr Pharm Des. 2011;17(15):1459\u0026ndash;70. doi: https://doi.org/10.2174/138161211796157168\u003c/li\u003e\n\u003cli\u003eWalker WH, Walton JC, DeVries AC, Nelson RJ. Circadian rhythm disruption and mental health. Transl Psychiatry. 2020;10(1):28. doi: https://doi.org/10.1038/s41398-020-0694-0\u003c/li\u003e\n\u003cli\u003eBenge E, Pavlova M, Javaheri S. Sleep health challenges among women: insomnia across the lifespan. Front Sleep. 2024;3. doi: https://doi.org/10.3389/fsleep.2024.123456\u003c/li\u003e\n\u003cli\u003eRajab AM, Rajab TM, Basha AC, Al-Khani AM, Ali MA, Enabi S, et al. Gender differences in sleep and mental health among Saudi adolescents. Sleep Disord. 2021;2021:5513817. doi: https://doi.org/10.1155/2021/5513817\u003c/li\u003e\n\u003cli\u003eZeng W, Chen R, Wang X, Zhang Q, Deng W. Prevalence of mental health problems among medical students in China: A meta-analysis. Med (Baltimore). 2019;98(18):e15337. doi: https://doi.org/10.1097/MD.0000000000015337\u003c/li\u003e\n\u003cli\u003eWeibel J, Lin Y-S, Landolt H-P, Berthomier C, Brandewinder M, Kistler J, et al. Regular caffeine intake delays REM sleep promotion and attenuates sleep quality in healthy men. J Biol Rhythms. 2021;36(4):384\u0026ndash;94. doi: https://doi.org/10.1177/0748730421995678\u003c/li\u003e\n\u003cli\u003eDrake C, Roehrs T, Shambroom J, Roth T. Caffeine effects on sleep taken 0, 3, or 6 hours before going to bed. J Clin Sleep Med. 2013;9(11):1195\u0026ndash;200. doi: https://doi.org/10.5664/jcsm.3170\u003c/li\u003e\n\u003cli\u003eChang A-M, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci USA. 2015;112(4):1232\u0026ndash;7. doi: https://doi.org/10.1073/pnas.1418490112\u003c/li\u003e\n\u003cli\u003eZhong Y, Ma H, Liang Y-F, Liao C-J, Zhang C-C, Jiang W-J. Prevalence of smartphone addiction among Asian medical students: A meta-analysis of multinational observational studies. Int J Soc Psychiatry. 2022;68(6):1171\u0026ndash;83. doi: https://doi.org/10.1177/00207640211011492\u003c/li\u003e\n\u003cli\u003eGonz\u0026aacute;lez G, Vives A. Work status, financial stress, family problems, and gender differences in the prevalence of depression in Chile. Ann Work Expo Health. 2019;63(3):359\u0026ndash;70. doi: https://doi.org/10.1093/annweh/wxy109\u003c/li\u003e\n\u003cli\u003eCao H, Zhou N, Li X, Serido J, Shim S. Temporal dynamics of the association between financial stress and depressive symptoms throughout emerging adulthood. J Affect Disord. 2021;282:211\u0026ndash;8. doi: https://doi.org/10.1016/j.jad.2020.12.134\u003c/li\u003e\n\u003cli\u003eSzkody E, Hobaica S, Owens S, Boland J, Washburn JJ, Bell D. Financial stress and debt in clinical psychology doctoral students. J Clin Psychol. 2023;79(3):835\u0026ndash;53. doi: https://doi.org/10.1002/jclp.23413\u003c/li\u003e\n\u003cli\u003eSaruhanjan K, Zarski A-C, Bauer T, Baumeister H, Cuijpers P, Spiegelhalder K, et al. Psychological interventions to improve sleep in college students: A meta-analysis of randomized controlled trials. J Sleep Res. 2021;30(1):e13097. doi: https://doi.org/10.1111/jsr.13097\u003c/li\u003e\n\u003cli\u003eAlzahrani AM, Hakami A, AlHadi A, Al-Maflehi N, Aljawadi MH, Alotaibi RM, et al. The effectiveness of mindfulness training in improving medical students\u0026rsquo; stress, depression, and anxiety. PLoS ONE. 2023;18(10):e0293539. doi: https://doi.org/10.1371/journal.pone.0293539\u003c/li\u003e\n\u003cli\u003eIrish LA, Kline CE, Gunn HE, Buysse DJ, Hall MH. The role of sleep hygiene in promoting public health: A review of empirical evidence. Sleep Med Rev. 2015;22:23\u0026ndash;36. doi: https://doi.org/10.1016/j.smrv.2014.10.001\u003c/li\u003e\n\u003cli\u003eZhu W, Liu J, Lou H, Mu F, Li B. Influence of smartphone addiction on sleep quality of college students: The regulatory effect of physical exercise behavior. PLoS ONE. 2024;19(7):e0307162. doi: https://doi.org/10.1371/journal.pone.0307162\u003c/li\u003e\n\u003cli\u003eBehling M. Methods to Stop Caffeine Use and Minimize Caffeine Withdrawal Symptoms in the State of Caffeine Dependence: A Literature Review. [cited 2025 Feb 12]; Available from: http://scholarsarchive.byu.edu/[email protected]\u003c/li\u003e\n\u003cli\u003eMcIntosh W HG. A case study investigating a behavioral intervention to reduce caffeine consumption. J Women\u0026rsquo;s Health Care. 2014;03(05). \u003c/li\u003e\n\u003cli\u003eEvatt DP, Juliano LM, Griffiths RR. A brief manualized treatment for problematic caffeine use: A randomized control trial. J Consult Clin Psychol. 2016;84(2):113\u0026ndash;21. doi: https://doi.org/10.1037/ccp0000138\u003c/li\u003e\n\u003cli\u003eGuarana CL, Barnes CM, Ong WJ. The effects of blue-light filtration on sleep and work outcomes. J Appl Psychol. 2021;106(5):784\u0026ndash;96. doi: https://doi.org/10.1037/apl0000918\u003c/li\u003e\n\u003cli\u003eBarnes CM, Guarana C, Lee J, Kaur E. Using wearable technology (closed-loop acoustic stimulation) to improve sleep quality and work outcomes. J Appl Psychol. 2023;108(8):1391\u0026ndash;407. doi:https://doi.org/10.1037/apl0001068\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sleep quality, Medical education, Public health, Depression","lastPublishedDoi":"10.21203/rs.3.rs-5453920/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5453920/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Objective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedical students are especially vulnerable to sleep disturbances and depression due to intense academic pressures and demanding schedules. Yet, the interplay between these issues remains underexplored in the Middle East and North Africa (MENA) region. This study aims to determine the prevalence of poor sleep quality and depression among medical students in the MENA region. It also aims to analyze the relationship between these factors, offering insights that could help improve their overall well-being.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, 773 medical students from Palestine, Algeria, Egypt, Syria, Yemen, and Jordan participated. The questionnaire, also filled out by each student, consisted of demographic and lifestyle data, the Beck Depression Inventory (BDI), and the Pittsburgh Sleep Quality Index (PSQI). BDI assesses the level of depression, while PSQI assesses sleep quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 773 medical students participated in the study. There was a significant correlation between sleep quality and depression level (Spearman’s rho = 0.920, p \u0026lt; 0.001). The average PSQI was 6 and the average BDI score was 15. The results identified that 51.5% of all respondents reported poor sleep quality and around 71.3% had depressive symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study reveals a robust association between poor sleep quality and depression among medical students in the MENA region, highlighting significant repercussions for both academic performance and overall well-being. In response, academic institutions must prioritize the implementation of targeted mental health initiatives, integrate comprehensive sleep hygiene education into their medical curricula, and develop culturally sensitive support systems. Furthermore, collaboration between universities and regional policymakers is crucial to establish sustainable strategies that bolster not only student health but also the resilience of the broader healthcare system.\u003c/p\u003e","manuscriptTitle":"Assessment of Sleep Quality and Depression among Medical Students: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-07 06:30:41","doi":"10.21203/rs.3.rs-5453920/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"37b2381f-683a-4f09-ab8e-6617f3623016","owner":[],"postedDate":"April 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-09T13:38:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-07 06:30:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5453920","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5453920","identity":"rs-5453920","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}