Common Mental Disorders among Medical Students: Prevalence, Predictors and Association with Financial and Health System Burden of Pakistan—A Multicenter Study

Common Mental Disorders among Medical Students: Prevalence, Predictors and Association with Financial and Health System Burden of Pakistan—A Multicenter 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 Common Mental Disorders among Medical Students: Prevalence, Predictors and Association with Financial and Health System Burden of Pakistan—A Multicenter Study Farah Rashid, Iffat Noor, Wajeha Najeeb, Hadiya Rashed Siddiqui, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9666691/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 The high prevalence of mental disorders amongst medical students is a growing concern in public health; particularly in Pakistan where the healthcare system is under-resourced and largely depends on out-of-pocket spending. The current research determined prevalence of depression and anxiety, identified major predictors and their association to health deterioration, financial burden, and health system level implications. A cross-sectional study was conducted among 1,630 medical students across nine medical colleges in Islamabad using PHQ-9 and GAD-7 tools. Findings were contextualized within Pakistan’s mental health system and healthcare financing landscape. The prevalence of depression was 57.8% and that of anxiety 46.4%. Association between mental health outcomes and various factors were assessed using multivariable logistic regression. Peer pressure, poor sleep, and screen time were strong predictors. In an environment where mental health services are scarce, workforce is undermanned, and private care is relied upon, these conditions lead to higher out-of-pocket expenses and delayed access to care. This highlights mental health not only as a clinical concern but also an economic and health-system burden. Integrating mental health services into primary care and university settings is essential to reduce long-term financial and health consequences Psychiatry Anxiety Depression Medical Students Mental Health Pakistan Figures Figure 1 Introduction Common mental disorders in university students have become one of the major public health concern globally. These rates are alarmingly high in medical students, (Carrieri et al., 2020). Medical students have distinct challenges in coping with the stresses of their learning environments, they have higher rates of anxiety and depression than other university students (Kaiser, H, et al. 2023). Recent worldwide estimates report that 45% of medical students suffer from anxiety, and 48% from depression, these figures significantly higher than the general population (Rotenstein et al., 2016; Quek et al., 2019). There is evidence that one out of four medical students is depressed, whereas suicidal thoughts have been found in one out of every eleven students (Rotenstein et al., 2016). This degradation has been explained by stressful academic demands, exposure to human suffering, and the pressure to perform well, (Guziak et al., 2025), further aggravated by sleep deprivation, fear of failure, extensive clinical duties and financial stress (Preet et al., 2024; Gökdemir, 2023). These findings highlight the uneven distribution of mental health problems among medical students across. These psychological disorders among medical students are significant not only from a clinical point of view, but also in relation to their academic and professional outcomes, and patient safety (Haykal et al., 2022). Studies indicate that these issues are mainly associated with academic performance, burnout and empathy, which may affect quality of patient outcomes (Sathyanarayanan, 2025; Patel et al., 2018). Additionally untreated mental health problems result in chronic disability and lost productivity, which features the societal and economic importance of mental health (World Health Organization, 2025). In low- and middle-income countries (LMICs), such as Pakistan, the impact of mental health disorders is compounded by scarcity of resources, stigma, and the lack of integration of mental health services in the health system. Statistical data show that about one-third of the population has a psychiatric disorder, and a significant number of people do not receive the necessary mental health care (Rahman et al., 2024). It is an indicator of a significant treatment gap and leading factors responsible are resource limitations, failure to integrate the provision of services into primary care, and sociocultural barriers to seek help. Moreover, in health systems with a high out-of-pocket spending, such as Pakistan, mental health disorders create a significant financial strain on individuals and families and particularly in the context of seeking assistance of a private provider (World Bank, 2023; Saxena and Verguet, 2022). Therefore, the anxiety and depression in students must not be perceived as just psychological disorders but as multidimensional problems with more significant consequences. These conditions are linked to deterioration of physical health, delayed seeking health care, and financial burden on the household. Thus, it is necessary to frame student mental health in the economic as well as in the health system perspective to have a complete picture of its implications in countries like Pakistan. But there is a lack of large, multicenter studies that have investigated both psychosocial and behavioral factors of mental health among medical students. Further, although the economic and health system consequences of mental health issues are increasingly acknowledged, empirical evidence on such consequences as related to student mental health is scant. This research aligned with Sustainable Development Goal 3 (SDG 3), Target 3.4 that entails the promotion of mental health and well-being. By identifying the modifiable risk factors and gaps in the system it seeks to provide evidence to guide institutional and policy responses to improve and contribute to the better access and delivery of mental health services in Pakistan, (World Health Organization, 2023). Therefore, this study aims to (1) assess the prevalence of anxiety and depression among medical students in Pakistan, (2) identify sociodemographic, behavioral and psychosocial factors associated with these disorders and (3) explore the impact of these disorders on individual and health systems conceptually. Conceptual Framework: The theoretical framework of this research is an integrated approach, that considers the biopsychosocial model and stress-coping theory, which emphasizes how social surroundings, psychological processes, systems challenges and individual behaviors interact to determine mental wellbeing. Material and Methods Study Design and Setting This was a multicenter cross-sectional study conducted from January to June 2024 in nine various medical colleges of Islamabad, Pakistan. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. Participants and Sampling The study population is comprised of undergraduate medical students. We included students who were enrolled in first and second-academic year, aged ≥17 years and provided informed consent. Students with incomplete questionnaires (>20% missing responses) and those currently undergoing psychiatric treatment (self-reported), were excluded to avoid confounding severity estimates. Total 1,630 students participated with 91.5% response rate. Multistage sampling was used. Initially, medical colleges were chosen based on accessibility and permission. Once a college was identified, students were chosen from each college using stratified random sampling. Data Collection Procedure: Data was collected from the selected medical colleges through an on-site survey. We used a structured, self-administered questionnaire, which was administered during scheduled class time. Participants were informed about the purpose of the study, privacy, and anonymity. Data collection was overseen by trained research assistants. Measures: Dependent Variables : There were two main Outcome Variablesi.e. Depression and Anxiety. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), a validated 9-item scale measuring depressive symptoms over the previous two weeks. Scores range from 0–27 and were categorized as: Minimal (0–4), Mild (5–9), Moderate (10–14), Moderately severe (15–19) and Severe (20–27). Anxiety was measured using the Generalized Anxiety Disorder-7 (GAD-7) scale (range: 0–21), categorized as: Minimal (0–4), Mild (5–9), Moderate (10–14) and Severe (15–21). (Anxiety and Depression Association of America, n.d.). For regression analysis, both outcomes were treated as ordinal variables. Predictor Variables: There were several Predictor like, Sociodemographic variables including; Age, Gender, Academic year, Residence (hostel vs family home) and Socioeconomic status (self-reported household income categories) Behavioral variables - Physical activity (low/moderate/high), Sleep pattern (regular vs irregular), Screen time (<2h, 3–4h, ≥5h/day), Social media use (rare, occasional, daily) Psychosocial variables - Peer pressure (yes/no), History of harassment (yes/no), Family support (strong vs weak), Social support (strong vs weak), Coping style (positive vs negative) Emotional Intelligence Measured using the Brief Emotional Intelligence Scale (BEIS-10), analyzed as continuous subscale scores. (NovoPsych, 2025). Results Data was analyzed using IBM SPSS Statistics version 29. Data was summarized using descriptive statistics, with continuous variables expressed as mean and standard deviation (mean ± SD) and categorical variables expressed as frequency and percentage. To test hypothesis, multivariable ordinal logistic regression models were used to calculate adjusted odds ratio (aOR) for anxiety and depression. Prior to the analysis, model assumptions were checked: the Brant test was used to test the proportional odds assumption, and variance inflation factors (VIF) were employed to assess multicollinearity, with VIF less than 5 being acceptable. The significance level of p < .05 was set. Socio-demographic characteristics: A total of 1,630 students participated (response rate: 91%). The mean age was 19.2 ± 1.4 years. Of the participants, 1,100 (67.5%) were female and 530 (32.5%) were male, this represents the national trend of gender ratio in medical colleges of Pakistan. Academic year distribution showed that 800 (49.1%) participants were first-year medical students, while 830(50.9%) were from second year. Socioeconomic backgrounds varied, with 1302 (79.9%) from middle-income, 272(16.7%). In terms of residency, 694 (42.6%) of participants lived in hostels, while 936 (57.4%) were with their families. Majority 1216 (74.6%) came from nuclear families. Prevalence of Mental Health Outcomes The overall prevalence of Depression (PHQ-9 ≥ 10) was 57.8% and Anxiety (GAD-7 ≥ 10): 46.4%. Moderate-to-severe symptoms were observed in a substantial proportion of students, indicating a high burden of psychological distress. Univariate Analysis: Relationship between anxiety scores (GAD-7) and influencing factors The univariate analysis revealed that students without depressive symptoms had low anxiety scores, whereas those with severe depression experienced significantly higher anxiety, with a p-value of < 0.001. When assessing anxiety levels in relation to academic performance, and access to counselling services the findings were not statistically significant (p-value 0.054). However, students using positive coping strategies, strong social and family support, and regular sleep pattern were associated with lower anxiety levels (p-value < 0.001). Further details and univariate analysis between Anxiety and various predictors are available in supplementary file Association of depression severity grades with various factors Analyzing the association of depression grades with various risk factors shows that Gender, residential status, year of study, peer pressure, academic performance, harassment, social media use, screen time are highly significant predictors p < 0.001(details of univariate analysis, available in supplementary file) Multivariable ordinal logistic regression analysis of risk factors for Anxiety and Depression : This analysis showed that among the key predictors of Anxiety Female gender (aOR = 2.13, 95% CI: 1.59–2.86), students facing peer pressure (aOR = 2.04, 95% CI: 1.52–2.70) and harassment (aOR = 2.78, 95% CI: 2.04–3.70) are having double odds of getting anxiety. While Strong family support (aOR = 0.49, 95% CI: 0.32–0.75) and positive coping (aOR = 0.53, 95% CI: 0.40–0.70) were amongst the protective factors. Similarly, amongst the key predictors of depression, peer pressure (aOR = 3.45, 95% CI: 2.50–4.76), Screen time ≥ 5 hours (aOR = 2.33, 95% CI: 1.45–3.70) and Family history of mental illness (aOR = 3.23, 95% CI: 2.33–4.76) contributed significantly. Details in Table 1 . These findings reveal that lifestyle and other psychological factors, such as sleep, peer influence, social and family support were significantly associated with anxiety and depression. The results indicate that modifiable behavioral and social factors play a significant role in mental health. Table 1 Multivariable ordinal logistic regression analysis of risk factors for Anxiety (GAD-7) and Depression (PHQ-9) among undergraduate medical students (n = 1630 ) Variable Comparison Anxiety aOR (95% CI) P-value Depression aOR (95% CI) P-value Gender Female vs Male 2.13 (1.59–2.86) 0.001 1.64 (1.22–2.22) 0.001 Residential Status Family vs Hostel 1.20 (1.04–1.59) 0.167 1.18 (1.10–1.52) 0.257 Academic Year 2nd vs 1st 1.03 (1.08–1.35) 0.01 1.41 (1.10–1.85) 0.013 Co-curricular Act. Yes vs No 0.68 (0.52–0.89) 0.006 0.79 (0.57–0.90) 0.004 Physical Activity Sedentary vs High 1.66 (1.44–1.60) 0.049 1.65 (1.43–1.59) 0.029 High vs Moderate 0.61 (0.42–0.88) 0.009 0.68 (0.47–0.97) 0.033 Sleep Irregular vs Regular 1.96 (1.39–2.78) 0.001 2.27 (1.64–3.23) 0.001 F/H of MH illness Yes vs No 2.38 (1.72–3.33) 0.001 3.23 (2.33–4.76) 0.001 Harassment History Yes vs No 2.04 (1.52–2.70) 0.001 2.56 (1.85–3.45) 0.001 Peer Pressure Yes vs No 2.78 (2.04–3.70) 0.001 3.45 (2.50–4.76) 0.001 Counseling Access Yes vs No 0.83 (0.58–1.12) 0.214 0.68 (0.43–0.91) 0.008 Social Support Strong vs Weak 0.63 (0.48–0.84) 0.001 0.49 (0.37–0.66) 0.001 Family Support Strong vs Weak 0.49 (0.32–0.75) 0.001 0.47 (0.31–0.71) 0.001 Coping Style Positive vs Negative 0.53 (0.40–0.70) 0.001 0.49 (0.37–0.64) 0.001 Social Media Use Daily vs Rarely 1.41 (0.76–2.22) 0.400 3.70 (1.52–9.09) 0.004 Daily vs Occasional 1.25 (0.69–1.69) 0.280 1.64 (1.11–2.38) 0.013 Screen Time ≥ 5h vs <2h 1.79 (1.12–2.78) 0.010 2.33 (1.45–3.70) 0.001 ≥ 5h vs 3–4h 0.93 (0.65–1.30) 0.630 1.02 (0.70–1.47) 0.929 Academic Performance Excellent vs Moderate 0.49 (0.33–0.74) 0.001 0.35 (0.22–0.53) 0.001 Excellent vs Good 0.78 (0.53–1.12) 0.170 0.63 (0.44–0.91) 0.013 Emotional Intelligence Self-appraisal (per unit ↑) 1.22 (1.09–1.32) 0.001 1.18 (1.09–1.27) 0.001 Appraisal of others (per unit ↑) 1.12 (1.02–1.23) 0.020 1.03 (0.91–1.16) 0.580 Discussions This is a cross-sectional, multi-center study that provides evidence of a high burden of anxiety and depression among medical students of Pakistan with a prevalence of 46.4% and 57.8% respectively. A recent study suggests that nearly 50% of the medical student report clinically significant anxiety or depression symptoms, suggesting the persistence of the problem in different settings (Agyapong-Opoku et al., 2026; Zhai et al., 2025). Studies from Mexico, Nepal, Bangladesh and the Middle East have consistently shown high burden of anxiety and depression among medical students, which is often attributed to academic stress, highly competitive environment and extensive exams (Robles-Rivera et al., 2025 ; Kansakar et al., 2023 ; Rahman et al., 2025; Abdel et al., 20) It is no different in Pakistan, studies conducted in Karachi and Multan have shown a prevalence of 60–70%, and this also adds to the high burden in this population. This could be due to a combination of academic pressures, high competition and psychosocial problems associated with medical course (Iftikhar et al., 2024 ; Ashraf et al., 2020 ). Consistent with the previous studies, it seems that the transition to medical training may be the time of the greatest vulnerability, as students are subjected to increased stress levels associated with the adaption process (Kansakar et al., 2023 ; Sathyanarayanan, 2025). These results support the importance of early identification and specific interventions in the initial years of medical education. Female students in this study displayed a significantly greater odds of anxiety and depression. The same results have been observed in a diverse setting such as Nepal, Saudi Arabia, India, and Egypt (Kansakar et al., 2023 ; Mirza et al., 2021; Raja et al., 2022). There is a well-documented gender difference in mental health outcomes, which is commonly explained by the complexity of their biological, psychological, and sociocultural aspects (Fawzy and Hamed, 2017 ). Other stressors of a gender role, social norms, and academic success can also make female students suffer more in the Pakistani context. Behavior and lifestyle were identified as important determinants of mental health outcomes. Abnormal sleeping habits and lack of physical activity were linked to more odds of both anxiety and depression, which supports the earlier research that has found a protective effect of good sleeping patterns and physical activity on psychological health (Amr and El-Gilany, 2010; Yusefi et al., 2025). Emotional dysregulation and poor cognitive functioning, especially sleep problems, have been closely associated with emotional disturbance and worsening of academic stress, as well as creating a loop of psychological distress. EI can be considered a protective factor due to its ability to improve stress management and adaptive coping (Adel Wahed and Hassan, 2017 ). Psychosocial variables such as peer pressure, social support and coping strategies showed strong relationships with mental health outcomes. Peer pressure was identified as one of the significant predictors of anxiety and depression, which is indicative of the extremely competitive and performance-oriented medical education. The same results were found in recent literature, with academic competition and social comparison playing a significant role in causing student distress (Guziak et al., 2025). In contrast, robust family and social support was also listed as protective factors, as it aligns with the evidence that social connectedness is a vital buffer against stress and psychological morbidity (Taylor, 2018 ; World Health Organization, 2021 ). The role of positive coping was linked to less anxiety and depression. This result is consistent with previous studies that reveal adaptive coping strategies including problem-solving and emotional regulation to alleviate the negative impact of stress (Ibrahim et al., 2013). Such findings underscore the need to incorporate training in coping skills in student support programs. The correlation of more screen time with depressive symptoms in this research aligns with the emerging evidence of excessive digital use with negative mental health effects (Zhai et al., 2025). Importantly, this study focuses on the impact of mental health issues on the health of medical students at a larger scale. The long-term consequences of untreated mental health issues in a country like Pakistan, where the mental health services are scare and under-resourced, can further burden the already choked health system (World Health Organization, 2025). Nevertheless, these results are to be interpreted in the light of some limitations. The cross-sectional design does not allow any causal inference, and the use of the self-reported measures can be a source of reporting bias. Also, even though the study mentions general implications of the economic and health system, they have not been directly measured and should be taken with a grain of salt. Longitudinal designs and economic assessments should be included in future research to get a better insight into the long-term effects of student mental health. Financial Burden and Mental Health Disorder This paper continues to conceptualize mental illnesses as a cause of monetary liability. Even though there was no measurement of direct costs, the ramifications are big. Greater use of health care, such as consultations and drugs, puts financial pressure on students and families, especially in the out-of-pocket health care system prevalent in Pakistan (World Bank, 2023 ). This is further compounded by indirect costs such as worse academic performance, late graduation, and decreased earning potential (Saxena & Verguet, 2022 ). There is also the correlation between mental illness and lower socioeconomic status that supports the interdependence between poverty and mental illness (Mirza & Jenkins, 2004 ). Implications for Health System in Pakistan The implications of the findings of this study to the healthcare system of Pakistan are quite considerable, given that the current healthcare system is already challenged by the lack of resources, workforce, and the lack of integration of mental health services into primary care Anxiety and depression in university students are very high and this is an early burden that can be expected to become a greater demand on mental health services in the long run. As the number of trained professionals is already limited, and services are concentrated in cities, this increasing demand can further expand the treatment gap and increase the disparities in access to mental health care. In addition, reliance on out-of-pocket payments causes economic burdens which have the potential to delay help-seeking behaviour and worsen health outcomes. The broader consequences of this increasing burden are also reduced productivity and co-morbidities with non-communicable diseases that also impact on the health care system. Integrated primary care, task-shifting and scalable mental health programs in universities could be cost-effective strategies that can reduce this burden and improve the mental health of the population (Dayani et al., 2024 ; Patel et al., 2018 ; World Health Organization, 2020). Conclusion In conclusion, this research has indicated a high prevalence of depression and anxiety in Pakistani medical students, which is a complex mix of behavioral and psychosocial factors. It also highlights the association between mental health and functional impairment, financial burden, and health system challenges. In addition, reliance on out-of-pocket payments has the potential to delay help-seeking behaviour and worsen health outcomes. The prevention of mental health among students is not only important to personal well-being, but also to the future of the healthcare workforce. The findings suggest there is a dire need for proactive, multifaceted and scalable institutional mental health interventions, including early screening and resilience-building programs. Declarations Compliance with Ethical Standards All procedures performed in studies involving human participants were in accordance with the ethical standards and the study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Ethical approval was obtained from the Institutional Review Board of Health Services Academy (Approval No. IHSA/2022/00009). Participants were assured that Mental health support was available should they experience distress during the survey. Informed consents Written informed consent was obtained from all participants. Data confidentiality and anonymity were strictly maintained. Funding: None to declare Conflicts of Interest : No conflict of interest. Acknowledgment: We sincerely thank all the participants for their meaningful contributions These results are preliminary and form part of a larger, ongoing research project. 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World health statistics 2023 . https://www.who.int/publications/i/item/9789240074323 Additional Declarations The authors declare no competing interests. Supplementary Files GA.png GA 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-9666691","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637516377,"identity":"ffb40b4c-3b60-4e65-ad32-d650a647e361","order_by":0,"name":"Farah Rashid","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0006-5931-6204","institution":"National University of Sciences and Technology, Islamabad. Pakistan","correspondingAuthor":true,"prefix":"","firstName":"Farah","middleName":"","lastName":"Rashid","suffix":""},{"id":637516378,"identity":"e142053a-e9a5-4a97-9df3-fb6cac9b89c7","order_by":1,"name":"Iffat Noor","email":"","orcid":"","institution":", National University of Sciences and Technology, Islamabad, Pakistan.","correspondingAuthor":false,"prefix":"","firstName":"Iffat","middleName":"","lastName":"Noor","suffix":""},{"id":637516379,"identity":"5e5a59f8-1de4-4204-ac30-e5c7c9d5909d","order_by":2,"name":"Wajeha Najeeb","email":"","orcid":"","institution":"CMH Kharian medical college, Kharian. Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Wajeha","middleName":"","lastName":"Najeeb","suffix":""},{"id":637516380,"identity":"70381c80-c0a5-470c-859e-951fdda20e99","order_by":3,"name":"Hadiya Rashed Siddiqui","email":"","orcid":"","institution":"Islamabad Medical \u0026 Dental College, Islamabad. Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Hadiya","middleName":"Rashed","lastName":"Siddiqui","suffix":""},{"id":637516381,"identity":"8c1503d8-46d0-444a-970a-bcc0aadb3c80","order_by":4,"name":"Hafiz Muhammad Ali","email":"","orcid":"","institution":"National University of Sciences and Technology, Islamabad, Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Hafiz","middleName":"Muhammad","lastName":"Ali","suffix":""}],"badges":[],"createdAt":"2026-05-09 23:47:50","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9666691/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9666691/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109197242,"identity":"84c88543-9eff-4816-abb8-806daae5f61b","added_by":"auto","created_at":"2026-05-13 13:13:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":128637,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssessment of anxiety, depression, emotional well-being and academic performance of students:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig 1A. shows 38.4% of students had mild Anxiety and 46.1% had mild depression shown in Fig 1B. The majority had excellent academic performance, with 24.4% reporting moderate level of performance reflected in Fig 1C, while Fig 1D provides details on proportion of percentiles of emotional intelligence grades among students.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9666691/v1/512dc88bc841fe1e41a42c7b.png"},{"id":109219649,"identity":"fe740d13-8133-43bf-abcf-4383d494dc1c","added_by":"auto","created_at":"2026-05-13 19:58:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":346841,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9666691/v1/fade7a66-de10-4c1f-a453-34b7eed8d13c.pdf"},{"id":109197156,"identity":"fd3aa351-aac9-44fb-9f3e-0c0b330d85cf","added_by":"auto","created_at":"2026-05-13 13:13:03","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":354947,"visible":true,"origin":"","legend":"\u003cp\u003eGA\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-9666691/v1/9464959f046ec80e588c32ee.png"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eCommon Mental Disorders among Medical Students: Prevalence, Predictors and Association with Financial and Health System Burden of Pakistan—A Multicenter Study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCommon mental disorders in university students have become one of the major public health concern globally. \u0026nbsp;These rates are alarmingly high in medical students, (Carrieri et al., 2020). Medical students have distinct challenges in coping with the stresses of their learning environments, they have higher rates of anxiety and depression than other university students (Kaiser, H, et al. 2023). Recent worldwide estimates report that 45% of medical students suffer from anxiety, and 48% from depression, these figures significantly higher than the general population (Rotenstein et al., 2016; Quek et al., 2019). There is evidence that one out of four medical students is depressed, whereas suicidal thoughts have been found in one out of every eleven students (Rotenstein et al., 2016). This degradation has been explained by stressful academic demands, exposure to human suffering, and the pressure to perform well, (Guziak et al., 2025), further aggravated by sleep deprivation, fear of failure, extensive clinical duties and financial stress (Preet et al., 2024; G\u0026ouml;kdemir, 2023). These findings highlight the uneven distribution of mental health problems among medical students across.\u003c/p\u003e\n\u003cp\u003eThese psychological disorders among medical students are significant not only from a clinical point of view, but also in relation to their academic and professional outcomes, and patient safety (Haykal et al., 2022). Studies indicate that these issues are mainly associated with academic performance, burnout and empathy, which may affect quality of patient outcomes (Sathyanarayanan, 2025; Patel et al., 2018). Additionally untreated mental health problems result in chronic disability and lost productivity, which features the societal and economic importance of mental health (World Health Organization, 2025).\u003c/p\u003e\n\u003cp\u003eIn low- and middle-income countries (LMICs), such as Pakistan, the impact of mental health disorders is compounded by scarcity of resources, stigma, and the lack of integration of mental health services in the health system. Statistical data show that about one-third of the population has a psychiatric disorder, and a significant number of people do not receive the necessary mental health care (Rahman et al., 2024). It is an indicator of a significant treatment gap and leading factors responsible are resource limitations, failure to integrate the provision of services into primary care, and sociocultural barriers to seek help. Moreover, in health systems with a high out-of-pocket spending, such as Pakistan, mental health disorders create a significant financial strain on individuals and families and particularly in the context of seeking assistance of a private provider (World Bank, 2023; Saxena and Verguet, 2022).\u003c/p\u003e\n\u003cp\u003eTherefore, the anxiety and depression in students must not be perceived as just psychological disorders but as multidimensional problems with more significant consequences. These conditions are linked to deterioration of physical health, delayed seeking health care, and financial burden on the household. Thus, it is necessary to frame student mental health in the economic as well as in the health system perspective to have a complete picture of its implications in countries like Pakistan. But there is a lack of large, multicenter studies that have investigated both psychosocial and behavioral factors of mental health among medical students. Further, although the economic and health system consequences of mental health issues are increasingly acknowledged, empirical evidence on such consequences as related to student mental health is scant.\u003c/p\u003e\n\u003cp\u003eThis research aligned with Sustainable Development Goal 3 (SDG 3), Target 3.4 that entails the promotion of mental health and well-being. By identifying the modifiable risk factors and gaps in the system it seeks to provide evidence to guide institutional and policy responses to improve and contribute to the better access and delivery of mental health services in Pakistan, (World Health Organization, 2023).\u003c/p\u003e\n\u003cp\u003eTherefore, this study aims to (1) assess the prevalence of anxiety and depression among medical students in Pakistan, (2) identify sociodemographic, behavioral and psychosocial factors associated with these disorders and (3) explore the impact of these disorders on individual and health systems conceptually.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptual Framework:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe theoretical framework of this research is an integrated approach, that considers the biopsychosocial model and stress-coping theory, which emphasizes how social surroundings, psychological processes, systems challenges and individual behaviors interact to determine mental wellbeing.\u003c/p\u003e\n"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a multicenter cross-sectional study conducted from January to June 2024 in nine various medical colleges of Islamabad, Pakistan. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants and Sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population is comprised of undergraduate medical students. We included students who were enrolled in first and second-academic year, aged ≥17 years and provided informed consent. Students with incomplete questionnaires (\u0026gt;20% missing responses) and those currently undergoing psychiatric treatment (self-reported), were excluded to avoid confounding severity estimates. Total 1,630 students participated with 91.5% response rate.\u003c/p\u003e\n\u003cp\u003eMultistage sampling was used. Initially, medical colleges were chosen based on accessibility and permission. Once a college was identified, students were chosen from each college using stratified random sampling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection Procedure:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was collected from the selected medical colleges through an on-site survey. We used a structured, self-administered questionnaire, which was administered during scheduled class time. Participants were informed about the purpose of the study, privacy, and anonymity. Data collection was overseen by trained research assistants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent Variables\u003c/strong\u003e: There were two main Outcome Variablesi.e. Depression and Anxiety.\u0026nbsp;\u003cbr\u003e\u0026nbsp;Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), a validated 9-item scale measuring depressive symptoms over the previous two weeks. Scores range from 0–27 and were categorized as: Minimal (0–4), Mild (5–9), Moderate (10–14), Moderately severe (15–19) and Severe (20–27). \u0026nbsp;Anxiety was measured using the Generalized Anxiety Disorder-7 (GAD-7) scale (range: 0–21), categorized as: Minimal (0–4), Mild (5–9), Moderate (10–14) and Severe (15–21). (Anxiety and Depression Association of America, n.d.). For regression analysis, both outcomes were treated as ordinal variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredictor Variables:\u003c/strong\u003e There were several Predictor like,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSociodemographic\u003c/strong\u003e variables including; Age, Gender, Academic year, Residence (hostel vs family home) and Socioeconomic status (self-reported household income categories)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBehavioral variables\u003c/strong\u003e- Physical activity (low/moderate/high), Sleep pattern (regular vs irregular), Screen time (\u0026lt;2h, 3–4h, ≥5h/day), Social media use (rare, occasional, daily)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePsychosocial variables\u003c/strong\u003e- Peer pressure (yes/no), History of harassment (yes/no), Family support (strong vs weak), Social support (strong vs weak), Coping style (positive vs negative)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional Intelligence\u003c/strong\u003e Measured using the Brief Emotional Intelligence Scale (BEIS-10), analyzed as continuous subscale scores. (NovoPsych, 2025).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eData was analyzed using IBM SPSS Statistics version 29. Data was summarized using descriptive statistics, with continuous variables expressed as mean and standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) and categorical variables expressed as frequency and percentage. To test hypothesis, multivariable ordinal logistic regression models were used to calculate adjusted odds ratio (aOR) for anxiety and depression. Prior to the analysis, model assumptions were checked: the Brant test was used to test the proportional odds assumption, and variance inflation factors (VIF) were employed to assess multicollinearity, with VIF less than 5 being acceptable. The significance level of p \u0026lt; .05 was set.\u003c/p\u003e\n\u003ch3\u003eSocio-demographic characteristics:\u003c/h3\u003e\n\u003cp\u003eA total of 1,630 students participated (response rate: 91%). The mean age was 19.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 years. Of the participants, 1,100 (67.5%) were female and 530 (32.5%) were male, this represents the national trend of gender ratio in medical colleges of Pakistan. Academic year distribution showed that 800 (49.1%) participants were first-year medical students, while 830(50.9%) were from second year. Socioeconomic backgrounds varied, with 1302 (79.9%) from middle-income, 272(16.7%). In terms of residency, 694 (42.6%) of participants lived in hostels, while 936 (57.4%) were with their families. Majority 1216 (74.6%) came from nuclear families.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence of Mental Health Outcomes\u003c/h2\u003e\n \u003cp\u003eThe overall prevalence of Depression (PHQ-9\u0026thinsp;\u0026ge;\u0026thinsp;10) was 57.8% and Anxiety (GAD-7\u0026thinsp;\u0026ge;\u0026thinsp;10): 46.4%. Moderate-to-severe symptoms were observed in a substantial proportion of students, indicating a high burden of psychological distress.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eUnivariate Analysis:\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between anxiety scores (GAD-7) and influencing factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe univariate analysis revealed that students without depressive symptoms had low anxiety scores, whereas those with severe depression experienced significantly higher anxiety, with a p-value of \u0026lt;\u0026thinsp;0.001. When assessing anxiety levels in relation to academic performance, and access to counselling services the findings were not statistically significant (p-value 0.054). However, students using positive coping strategies, strong social and family support, and regular sleep pattern were associated with lower anxiety levels (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Further details and univariate analysis between Anxiety and various predictors are available in supplementary file\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation of depression severity grades with various factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalyzing the association of depression grades with various risk factors shows that Gender, residential status, year of study, peer pressure, academic performance, harassment, social media use, screen time are highly significant predictors p\u0026thinsp;\u0026lt;\u0026thinsp;0.001(details of univariate analysis, available in supplementary file)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariable ordinal logistic regression analysis of risk factors for Anxiety and Depression\u003c/strong\u003e: This analysis showed that among the key predictors of Anxiety Female gender (aOR\u0026thinsp;=\u0026thinsp;2.13, 95% CI: 1.59\u0026ndash;2.86), students facing peer pressure (aOR\u0026thinsp;=\u0026thinsp;2.04, 95% CI: 1.52\u0026ndash;2.70) and harassment (aOR\u0026thinsp;=\u0026thinsp;2.78, 95% CI: 2.04\u0026ndash;3.70) are having double odds of getting anxiety. While Strong family support (aOR\u0026thinsp;=\u0026thinsp;0.49, 95% CI: 0.32\u0026ndash;0.75) and positive coping (aOR\u0026thinsp;=\u0026thinsp;0.53, 95% CI: 0.40\u0026ndash;0.70) were amongst the protective factors.\u003c/p\u003e\n\u003cp\u003eSimilarly, amongst the key predictors of depression, peer pressure (aOR\u0026thinsp;=\u0026thinsp;3.45, 95% CI: 2.50\u0026ndash;4.76), Screen time\u0026thinsp;\u0026ge;\u0026thinsp;5 hours (aOR\u0026thinsp;=\u0026thinsp;2.33, 95% CI: 1.45\u0026ndash;3.70) and Family history of mental illness (aOR\u0026thinsp;=\u0026thinsp;3.23, 95% CI: 2.33\u0026ndash;4.76) contributed significantly. Details in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eThese findings reveal that lifestyle and other psychological factors, such as sleep, peer influence, social and family support were significantly associated with anxiety and depression. The results indicate that modifiable behavioral and social factors play a significant role in mental health.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable ordinal logistic regression analysis of risk factors for Anxiety (GAD-7) and Depression (PHQ-9) among undergraduate medical students (n\u0026thinsp;=\u0026thinsp;1630\u003c/strong\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eComparison\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eAnxiety aOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eDepression aOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFemale vs Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.13 (1.59\u0026ndash;2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.64 (1.22\u0026ndash;2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eResidential Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFamily vs Hostel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.20 (1.04\u0026ndash;1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.18 (1.10\u0026ndash;1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAcademic Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e2nd vs 1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.03 (1.08\u0026ndash;1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.41 (1.10\u0026ndash;1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCo-curricular Act.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.68 (0.52\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.79 (0.57\u0026ndash;0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePhysical Activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSedentary vs High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.66 (1.44\u0026ndash;1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.65 (1.43\u0026ndash;1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHigh vs Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.61 (0.42\u0026ndash;0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.68 (0.47\u0026ndash;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIrregular vs Regular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.96 (1.39\u0026ndash;2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e2.27 (1.64\u0026ndash;3.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eF/H of MH illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.38 (1.72\u0026ndash;3.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e3.23 (2.33\u0026ndash;4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHarassment History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.04 (1.52\u0026ndash;2.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e2.56 (1.85\u0026ndash;3.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePeer Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.78 (2.04\u0026ndash;3.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e3.45 (2.50\u0026ndash;4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCounseling Access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.83 (0.58\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.68 (0.43\u0026ndash;0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eStrong vs Weak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.63 (0.48\u0026ndash;0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.49 (0.37\u0026ndash;0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFamily Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eStrong vs Weak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.49 (0.32\u0026ndash;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.47 (0.31\u0026ndash;0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCoping Style\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePositive vs Negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.53 (0.40\u0026ndash;0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.49 (0.37\u0026ndash;0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Media Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eDaily vs Rarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.41 (0.76\u0026ndash;2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e3.70 (1.52\u0026ndash;9.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eDaily vs Occasional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.25 (0.69\u0026ndash;1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.64 (1.11\u0026ndash;2.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eScreen Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;5h vs \u0026lt;2h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.79 (1.12\u0026ndash;2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e2.33 (1.45\u0026ndash;3.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;5h vs 3\u0026ndash;4h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.93 (0.65\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.02 (0.70\u0026ndash;1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAcademic Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eExcellent vs Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.49 (0.33\u0026ndash;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.35 (0.22\u0026ndash;0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eExcellent vs Good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.78 (0.53\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.63 (0.44\u0026ndash;0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEmotional Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSelf-appraisal (per unit \u0026uarr;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.22 (1.09\u0026ndash;1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.18 (1.09\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAppraisal of others (per unit \u0026uarr;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.12 (1.02\u0026ndash;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.03 (0.91\u0026ndash;1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eThis is a cross-sectional, multi-center study that provides evidence of a high burden of anxiety and depression among medical students of Pakistan with a prevalence of 46.4% and 57.8% respectively. A recent study suggests that nearly 50% of the medical student report clinically significant anxiety or depression symptoms, suggesting the persistence of the problem in different settings (Agyapong-Opoku et al., 2026; Zhai et al., 2025). Studies from Mexico, Nepal, Bangladesh and the Middle East have consistently shown high burden of anxiety and depression among medical students, which is often attributed to academic stress, highly competitive environment and extensive exams (Robles-Rivera et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kansakar et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rahman et al., 2025; Abdel et al., 20) It is no different in Pakistan, studies conducted in Karachi and Multan have shown a prevalence of 60\u0026ndash;70%, and this also adds to the high burden in this population. This could be due to a combination of academic pressures, high competition and psychosocial problems associated with medical course (Iftikhar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ashraf et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConsistent with the previous studies, it seems that the transition to medical training may be the time of the greatest vulnerability, as students are subjected to increased stress levels associated with the adaption process (Kansakar et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sathyanarayanan, 2025). These results support the importance of early identification and specific interventions in the initial years of medical education.\u003c/p\u003e \u003cp\u003eFemale students in this study displayed a significantly greater odds of anxiety and depression. The same results have been observed in a diverse setting such as Nepal, Saudi Arabia, India, and Egypt (Kansakar et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mirza et al., 2021; Raja et al., 2022). There is a well-documented gender difference in mental health outcomes, which is commonly explained by the complexity of their biological, psychological, and sociocultural aspects (Fawzy and Hamed, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Other stressors of a gender role, social norms, and academic success can also make female students suffer more in the Pakistani context.\u003c/p\u003e \u003cp\u003eBehavior and lifestyle were identified as important determinants of mental health outcomes. Abnormal sleeping habits and lack of physical activity were linked to more odds of both anxiety and depression, which supports the earlier research that has found a protective effect of good sleeping patterns and physical activity on psychological health (Amr and El-Gilany, 2010; Yusefi et al., 2025). Emotional dysregulation and poor cognitive functioning, especially sleep problems, have been closely associated with emotional disturbance and worsening of academic stress, as well as creating a loop of psychological distress. EI can be considered a protective factor due to its ability to improve stress management and adaptive coping (Adel Wahed and Hassan, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePsychosocial variables such as peer pressure, social support and coping strategies showed strong relationships with mental health outcomes. Peer pressure was identified as one of the significant predictors of anxiety and depression, which is indicative of the extremely competitive and performance-oriented medical education. The same results were found in recent literature, with academic competition and social comparison playing a significant role in causing student distress (Guziak et al., 2025). In contrast, robust family and social support was also listed as protective factors, as it aligns with the evidence that social connectedness is a vital buffer against stress and psychological morbidity (Taylor, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; World Health Organization, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe role of positive coping was linked to less anxiety and depression. This result is consistent with previous studies that reveal adaptive coping strategies including problem-solving and emotional regulation to alleviate the negative impact of stress (Ibrahim et al., 2013). Such findings underscore the need to incorporate training in coping skills in student support programs. The correlation of more screen time with depressive symptoms in this research aligns with the emerging evidence of excessive digital use with negative mental health effects (Zhai et al., 2025).\u003c/p\u003e \u003cp\u003eImportantly, this study focuses on the impact of mental health issues on the health of medical students at a larger scale. The long-term consequences of untreated mental health issues in a country like Pakistan, where the mental health services are scare and under-resourced, can further burden the already choked health system (World Health Organization, 2025).\u003c/p\u003e \u003cp\u003eNevertheless, these results are to be interpreted in the light of some limitations. The cross-sectional design does not allow any causal inference, and the use of the self-reported measures can be a source of reporting bias. Also, even though the study mentions general implications of the economic and health system, they have not been directly measured and should be taken with a grain of salt. Longitudinal designs and economic assessments should be included in future research to get a better insight into the long-term effects of student mental health.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFinancial Burden and Mental Health Disorder\u003c/h2\u003e \u003cp\u003eThis paper continues to conceptualize mental illnesses as a cause of monetary liability. Even though there was no measurement of direct costs, the ramifications are big. Greater use of health care, such as consultations and drugs, puts financial pressure on students and families, especially in the out-of-pocket health care system prevalent in Pakistan (World Bank, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This is further compounded by indirect costs such as worse academic performance, late graduation, and decreased earning potential (Saxena \u0026amp; Verguet, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). There is also the correlation between mental illness and lower socioeconomic status that supports the interdependence between poverty and mental illness (Mirza \u0026amp; Jenkins, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Health System in Pakistan\u003c/h2\u003e \u003cp\u003eThe implications of the findings of this study to the healthcare system of Pakistan are quite considerable, given that the current healthcare system is already challenged by the lack of resources, workforce, and the lack of integration of mental health services into primary care Anxiety and depression in university students are very high and this is an early burden that can be expected to become a greater demand on mental health services in the long run. As the number of trained professionals is already limited, and services are concentrated in cities, this increasing demand can further expand the treatment gap and increase the disparities in access to mental health care. In addition, reliance on out-of-pocket payments causes economic burdens which have the potential to delay help-seeking behaviour and worsen health outcomes. The broader consequences of this increasing burden are also reduced productivity and co-morbidities with non-communicable diseases that also impact on the health care system. Integrated primary care, task-shifting and scalable mental health programs in universities could be cost-effective strategies that can reduce this burden and improve the mental health of the population (Dayani et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Patel et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; World Health Organization, 2020).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this research has indicated a high prevalence of depression and anxiety in Pakistani medical students, which is a complex mix of behavioral and psychosocial factors. It also highlights the association between mental health and functional impairment, financial burden, and health system challenges. In addition, reliance on out-of-pocket payments has the potential to delay help-seeking behaviour and worsen health outcomes. The prevention of mental health among students is not only important to personal well-being, but also to the future of the healthcare workforce. The findings suggest there is a dire need for proactive, multifaceted and scalable institutional mental health interventions, including early screening and resilience-building programs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e All procedures performed in studies involving human participants were in accordance with the ethical standards and the study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. \u0026nbsp;Ethical approval was obtained from the Institutional Review Board of Health Services Academy (Approval No. IHSA/2022/00009). Participants were assured that Mental health support was available should they experience distress during the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consents\u003c/strong\u003e Written informed consent was obtained from all participants. Data confidentiality and anonymity were strictly maintained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNone to declare\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e: No conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e We sincerely thank all the participants for their meaningful contributions These results are preliminary and form part of a larger, ongoing research project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration:\u0026nbsp;\u003c/strong\u003eAuthors declare that ChatGPT has been used in generating the visual conceptual framework\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdallah, A. R., \u0026amp; Gabr, H. M. (2014). 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(2021). \u003cem\u003eAdolescent mental health\u003c/em\u003e. https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health\u003c/li\u003e\n\u003cli\u003eWorld Bank. (2023). \u003cem\u003eHealth expenditure in Pakistan\u003c/em\u003e.\u003cbr\u003e https://data.worldbank.org/indicator/SH.XPD.CHEX.GD.ZS?locations=PK \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2023). \u003cem\u003eWorld health statistics 2023\u003c/em\u003e. https://www.who.int/publications/i/item/9789240074323\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Anxiety, Depression, Medical Students, Mental Health, Pakistan","lastPublishedDoi":"10.21203/rs.3.rs-9666691/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9666691/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe high prevalence of mental disorders amongst medical students is a growing concern in public health; particularly in Pakistan where the healthcare system is under-resourced and largely depends on out-of-pocket spending. The current research determined prevalence of depression and anxiety, identified major predictors and their association to health deterioration, financial burden, and health system level implications. A cross-sectional study was conducted among 1,630 medical students across nine medical colleges in Islamabad using PHQ-9 and GAD-7 tools. Findings were contextualized within Pakistan’s mental health system and healthcare financing landscape.\u003c/p\u003e\n\u003cp\u003eThe prevalence of depression was 57.8% and that of anxiety 46.4%. Association between mental health outcomes and various factors were assessed using multivariable logistic regression. Peer pressure, poor sleep, and screen time were strong predictors. In an environment where mental health services are scarce, workforce is undermanned, and private care is relied upon, these conditions lead to higher out-of-pocket expenses and delayed access to care. This highlights mental health not only as a clinical concern but also an economic and health-system burden. Integrating mental health services into primary care and university settings is essential to reduce long-term financial and health consequences\u003c/p\u003e","manuscriptTitle":"Common Mental Disorders among Medical Students: Prevalence, Predictors and Association with Financial and Health System Burden of Pakistan—A Multicenter Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 13:10:30","doi":"10.21203/rs.3.rs-9666691/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":"06dd34ac-bb10-41a6-8399-fbd3f3884351","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67856002,"name":"Psychiatry"}],"tags":[],"updatedAt":"2026-05-13T13:10:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 13:10:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9666691","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9666691","identity":"rs-9666691","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}