Interrelationships between Perceived Stress, Burnout, Depression, and Resilient Coping among Postgraduate Medical Residents: An Analytical Cross-Sectional Study

Interrelationships between Perceived Stress, Burnout, Depression, and Resilient Coping among Postgraduate Medical Residents: An Analytical 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 Interrelationships between Perceived Stress, Burnout, Depression, and Resilient Coping among Postgraduate Medical Residents: An Analytical Cross-Sectional Study Soumya Prakash, Sandeep Alex, Devraj R This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8765697/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: Postgraduate medical residency involves heavy workload and sustained academic pressure, increasing vulnerability to burnout and depression. However, the interrelationships among perceived stress, burnout, depression, and resilient coping remain under explored in the Indian residency context. Objectives: To estimate the prevalence of perceived stress, burnout, depressive symptoms, and resilient coping among postgraduate medical residents, and to identify independent predictors of burnout and depression. Methods: An analytical cross-sectional online survey was conducted among postgraduate medical residents at a Government Medical College in Kerala between November 2024 and June 2025. Validated instruments assessed perceived stress (PSS-10), burnout (abbreviated Copenhagen Burnout Inventory), resilient coping (Brief Resilient Coping Scale), and depressive symptoms (PSQ-4D). Associations were examined using χ² tests and multivariable logistic regression. An exploratory analysis examined whether burnout was associated with the stress–depression pathway. Results: A total of 176 residents participated (64.8% female). Burnout was present in 56.3%, depressive symptoms in 50.0%, and low resilient coping in 51.7%. Although only 22.2% reported high perceived stress, most experienced moderate stress (67.6%). Depression was strongly associated with burnout (OR = 10.17; p < 0.001). High perceived stress independently predicted burnout (aOR = 11.92) and depression (aOR = 37.20), while burnout independently predicted depression (aOR = 6.07). Resilient coping was not independently associated with either outcome. Conclusions: Burnout and depressive symptoms are highly prevalent among postgraduate residents. Burnout appears to be a key correlate linking perceived stress and depression, highlighting the need for organizational and structural interventions beyond individual resilience-focused strategies. Psychology Stress Psychological Burnout Depressive Disorder Psychological Resilience Occupational Stress Postgraduate Medical Residents Introduction Postgraduate medical education combines intensive duties, rigorous academic demands, and high-stakes examinations. This challenging environment often contributes to elevated stress and an increased risk of psychological distress among residents. Stress is highly prevalent among postgraduate medical residents and is frequently accompanied by symptoms of depression and burnout (Abdulrahman et al. 2018 ; Dave et al. 2018 ; Ratnakaran et al. 2016 ). Between 2018 and 2022, 122 medical students in India died by suicide, of whom nearly half were postgraduate residents (Jha 2024 ). Recent reports indicate that nearly 15% of postgraduate medical students experience clinically significant mental health problems, and approximately one-third report suicidal ideation, underscoring the need for attention to trainee well-being (NMC India 2024 ). Resilience is commonly defined as the ability to adapt positively to stressful circumstances or to "bounce back" from difficult experiences.(Windle 2011 ). In an alternate perspective, resilience is a dynamic process involving interdependent individual and contextual systems (Ungar 2024 ). While higher individual resilience has been associated with lower psychological distress and reduced risk of depression, persistent endurance in stressful conditions may paradoxically compromise mental health. Factors that obstruct resilience, such as work–life imbalance and chronic stress exposure, are also major contributors to burnout, suggesting an inverse relationship between burnout and resilient coping. However, evidence regarding its independent association with burnout and depression, as well as its role in modifying stress-related outcomes, remains mixed. Few studies have simultaneously examined perceived stress, burnout, depression, and resilience within a single analytical framework. Therefore, the present study aimed to: (1) estimate the prevalence of perceived stress, burnout, depression, and resilience among postgraduate medical residents; (2) examine the associations between depression and burnout, and their relationships with perceived stress and resilience using bivariate analyses; and (3) identify independent predictors of burnout and depression through multivariable logistic regression. In addition, an exploratory analysis was undertaken to examine whether burnout may lie on the pathway between perceived stress and depression, with findings interpreted cautiously given the cross-sectional design. Methodology Study Design An analytical cross-sectional design was employed, using an online survey. Study Population All currently enrolled postgraduate medical residents at Government Medical College, Kottayam (Kerala, India), were eligible. Inclusion criteria : Postgraduate medical residents studying at Government Medical College Kottayam during the study period. Provided electronic informed consent. Exclusion criteria Submitted incomplete responses on primary scales. Study Duration Data were collected between November 2024 and June 2025. Measures Perceived Stress: Assessed using the Perceived Stress Scale (PSS-10). Higher scores indicate greater perceived stress (Cohen et al. 1983 ). Scores ranging from 0 to 13 were classified as indicating low perceived stress, scores from 14 to 26 as moderate perceived stress, and scores from 27 to 40 as high perceived stress. Burnout: Assessed using the abbreviated Copenhagen Burnout Inventory (aCBI).Higher scores indicate greater burnout (Barton et al. 2022 ). A total score of 16 or higher on Items 1–4 indicates burnout stemming from an internal factor. A total score of 6 or higher on Items 5 and 6 indicates burnout stemming from an external factor. Exceeding the threshold scores for either factor indicates burnout. Resilience: Measured using the Brief Resilient Coping Scale (BRCS). Higher scores indicate better resilient coping (Sinclair and Wallston 2004 ). Scores ranging from 4 to 13 were classified as indicating low resilient coping, scores from 14 to 16 as medium resilient coping, and scores from 17 to 20 as high resilient coping. Depression: Screened using the Primary Care Screening Questionnaire for Depression (PSQ-4D). A score ≥ 2 was considered positive (Indu et al. 2017 ). Specially designed proforma was used to collect basic socio demographic details of participants. Sample Size Using a finite population correction formula and published prevalence estimates [depression: 30.1%(Grover et al. 2018 ); stress: 37.3% (Sahasrabuddhe et al. 2015 ); burnout: 40%(Ratnakaran et al. 2016 ); resilience: 63.9 (Waddimba et al. 2016 )], the sample size calculated was 187 from the total postgraduate resident population of 438. Procedure After obtaining approval from the Institutional Review Board, an online proforma (Kobo Toolbox) was distributed via WhatsApp groups, including the participant information sheet, consent form, validated scales, and socio-demographic items. Non-responders were reminded monthly, and the survey closed after 7 days following the final reminder. Statistical Analysis Data were screened for completeness before analysis. Missing data were minimal ( 0.70). Descriptive statistics were summarised as frequencies and percentages for categorical variables and as means with standard deviations for continuous variables. Group comparisons were performed using the χ² test or Fisher’s exact test for categorical variables. Multivariable logistic regression analysis was conducted to identify independent predictors of burnout and depression. Variables showing statistical significance in bivariate analyses (p < 0.10), along with clinically relevant covariates, were entered into the regression models. Results were expressed as adjusted odds ratios (aORs) with 95% confidence intervals. An exploratory mediation analysis was performed to examine whether burnout may lie on the pathway between perceived stress and depression. Since this is a cross-sectional study, findings were interpreted as hypothesis-generating. All statistical tests were two-tailed, and a p-value < 0.05 was considered statistically significant. Results Sample Characteristics A total of 176 postgraduate medical residents participated in the study. The mean age of participants was 26.9 years (SD = 2.1). Females constituted 64.8% (n = 114) of the sample, and males accounted for 35.2% (n = 62). With respect to the year of residency, 39.8% were first-year residents, 24.4% second-year residents, and 35.8% third-year residents. Nearly half of the participants belonged to medical specialties (47.7%), followed by surgical (34.7%) and paraclinical specialties (17.6%). The majority of participants were unmarried (58.0%), did not have a confirmed job awaiting them after completion of residency (84.1%), and reported no significant physical health problems (82.4%). Sociodemographic characteristics are presented in Table 1. Prevalence of Psychological Variables The descriptive statistics for the psychological variables are summarised in Table 2. Depressive symptoms were present in 50.0% (n = 88) of participants. Burnout was identified in 56.3% (n = 99) of the sample, with a mean burnout score of 3.15 (SD = 0.84). Internal burnout was present in 44.9% (n = 79) of participants, while external burnout was observed in 30.7% (n = 54). Perceived stress assessed using the PSS-10 revealed a mean score of 21.9 (SD = 7.5). Most participants experienced moderate stress (67.6%, n = 119), followed by high stress (22.2%, n = 39) and low stress (10.2%, n = 18). Resilience assessed using the Brief Resilient Coping Scale (BRCS) showed that 51.7% (n = 91) of participants had low resilience, 36.4% (n = 64) had moderate resilience, and 11.9% (n = 21) demonstrated high resilience. Association Between Depression and Burnout A strong association was observed between depression and burnout. Among participants without depression, 30.7% (n = 27) experienced burnout, whereas 81.8% (n = 72) of those with depression met criteria for burnout. Chi-square analysis demonstrated a highly significant association between depression and burnout (χ² = 46.75, df = 1, p < 0.001). Participants with depression had over ten times higher odds of burnout compared to those without depression (OR = 10.17; 95% CI: 5.02–20.60). Internal burnout was present in 72.7% of participants with depression compared to 17.0% among those without depression. External burnout was observed in 42.0% of participants with depression, in contrast to 19.3% among non-depressed participants. Association of Depression with Perceived Stress and Resilience High perceived stress was more common among participants with depression (40.9%) than among those without depression (3.4%), while low stress was infrequent in the depressed group (1.1%) but more prevalent among non-depressed participants (19.3%). Low resilience was observed in 68.2% of participants with depression compared to 35.2% without depression, whereas high resilience was least common in the depressed group (9.1%). Association Between Burnout, Stress, and Resilience Burnout showed a strong association with perceived stress. Among participants with burnout, 36.4% reported high stress, compared to only 3.9% among those without burnout (χ² = 40.23, df = 2, p < 0.001). Resilience was also significantly associated with burnout (χ² = 10.58, df = 2, p = 0.005). Burnout was present in 65.9% of participants with low resilience, compared to 28.6% among those with high resilience. Sociodemographic Correlates High perceived stress was significantly associated with gender (χ² = 9.50, df = 2, p = 0.009) and specialty (χ² = 16.45, df = 4, p = 0.002), with higher stress observed among females and participants from surgical specialities. Depression was significantly associated with speciality (χ² = 9.21, df = 2, p = 0.010). Resilience levels were significantly associated with job status (χ² = 6.18, df = 2, p = 0.046), with higher resilience observed among participants who were already employed. Multivariable Logistic Regression Analysis Predictors of Burnout After adjustment for perceived stress category, resilience, gender, and speciality, depression remained independently associated with burnout (adjusted OR [aOR] = 6.21; 95% CI: 2.66–14.45; p < 0.001). High perceived stress emerged as the strongest independent predictor of burnout (aOR = 11.92; 95% CI: 3.00–47.30; p < 0.001). Resilience, gender, and speciality were not independently associated with burnout. Model performance indicated good explanatory power (Pseudo R² = 0.32; likelihood ratio test p < 0.001). [Table no. 3] Predictors of Depression In the adjusted model, burnout was independently associated with depression (aOR = 6.07; 95% CI: 2.61–14.11; p < 0.001). High perceived stress demonstrated a strong independent association with depression (aOR = 37.20; 95% CI: 3.05–452.70; p = 0.005). Resilience, gender, and speciality were not independently associated with depression. The model demonstrated good explanatory capacity (Pseudo R² = 0.34; likelihood ratio test p < 0.001). [Table no. 4] Discussion This study examined the interrelationships among perceived stress, burnout, resilient coping, and depressive symptoms in postgraduate medical residents. Approximately half of the residents screened positive for depressive symptoms, and more than half experienced burnout. Depression and burnout were strongly associated even after adjustment for perceived stress, resilient coping, gender, and speciality, while perceived stress demonstrated the strongest association with both outcomes. Exploratory analyses, presented as supplementary material, suggested that burnout may be associated with the relationship between perceived stress and depression; however, these findings should be interpreted cautiously given the cross-sectional design. An important observation in this study was the discrepancy between perceived stress levels and downstream psychological outcomes. Although only 22% of residents met the PSS-10 threshold for high perceived stress, substantially higher proportions screened positive for burnout (59%) and depression (50%). This difference likely reflects variation in construct measurement. The PSS-10 captures current appraisal of stress, whereas burnout and depressive symptoms represent cumulative syndromic outcomes that may evolve following prolonged exposure to moderate or persistent stress. Consequently, residents with moderate stress scores may experience burnout and depressive symptoms over time. This aligns with Maslach’s conceptualisation of burnout as a process mediating the impact of chronic stressors on mental health outcomes (Maslach 1998 ). The prevalence of psychological morbidity observed in this population is concerning. Half of the residents screened positive for depressive symptoms, nearly three-fifths experienced burnout, and over half demonstrated low resilient coping. These findings are broadly consistent with prior studies among postgraduate medical trainees reporting high levels of stress-related psychological morbidity during residency training (Alshardi and Farahat 2020; Dave et al. 2018 ; Dyrbye et al. 2014 ; Grover et al. 2018 ; Mitra et al. 2018 ; Priyam et al. 2024; Ratnakaran et al. 2016 ; Shahi et al. 2022). Together, these results underscore the substantial mental health burden faced by residents, particularly in demanding public sector training environments. International research supports a mediating role of resilience in the pathway from stress to depression. Among Spanish nurses during the COVID-19 pandemic, resilience significantly mediated the effects of stress on depression, anxiety, and psychological distress (Lara-Cabrera et al. 2021 ). Similarly, resilience has been shown to critically mediate stress-induced depression and anxiety among nursing students (Devi et al. 2021 ), as well as in psychiatric nurses exposed to occupational stress (Chen et al. 2022 ). In contrast, resilient coping did not retain independent significance in multivariable models in the present study, despite showing protective associations in unadjusted analyses. This divergence may reflect contextual differences in residency training, where workload, duty hours, and responsibility burden may limit the protective influence of individual coping resources. Our findings suggest that perceived stress may be associated with depressive symptoms primarily through burnout, rather than being substantially offset by resilient coping alone. What this study adds While the stress–burnout–depression relationship has been previously documented, analytical evidence from the residency context remains limited (Mitra et al. 2018 ). This study extends existing models by examining perceived stress, burnout, depression, and resilient coping within a single analytical framework among postgraduate medical residents in a Government Medical College. The findings highlight burnout as a key correlate linking perceived stress and depressive symptoms, while resilient coping did not independently explain this association after adjustment. The high prevalence of depression (50%) and burnout (59%) lies at the upper end of both Indian and global estimates, reinforcing the need of addressing resident well-being. Implications These findings have important implications for postgraduate medical training programs. Interventions focusing solely on reducing perceived stress may be insufficient if burnout is not simultaneously addressed. Institutional strategies aimed at optimizing duty hours, improving supervision, ensuring adequate rest, and fostering supportive peer and faculty relationships may help in reducing burnout risk. Given the high prevalence of depressive symptoms, residency programs should also incorporate routine mental health screening and ensure access to confidential counselling services. Structured orientation programs, mentorship and clearly regulated work schedules may further support resident well-being. Strengths and Limitations This study contributes Indian data to a literature largely dominated by international research, thereby enhancing cross-cultural understanding of stress-related mental health outcomes in medical training. The use of validated instruments strengthens measurement reliability, and the inclusion of over 40% of the postgraduate cohort in a large government medical college enhances internal validity within this context. The predominance of female participants reflects the current gender distribution in undergraduate and postgraduate medical training in Kerala, where women constitute an increasing proportion of medical students, and is therefore likely to be representative of the resident population in this setting. Several limitations should be acknowledged. The cross-sectional design precludes causal inference and limits conclusions regarding temporal sequencing. Reliance on self-report measures without diagnostic interviews may introduce reporting bias. The study was conducted at a single institution, which may limit generalizability, although inclusion across specialities and years of training provides breadth. Resilient coping was assessed using a brief scale, which may not fully capture its multidimensional nature. Finally, while resilience did not retain independent significance in adjusted models, this should not be interpreted as evidence against its broader importance, but rather as an indication that structural and organisational stressors may outweigh individual coping resources in the residency context. Conclusion This study demonstrates a high burden of depressive symptoms and burnout among postgraduate medical residents, with strong associations observed between perceived stress, burnout, and depression. Although only a minority of residents met criteria for high perceived stress, the majority reported at least moderate stress levels, which were strongly associated with both burnout and depressive symptoms. Exploratory analyses suggested that burnout may be associated with the relationship between perceived stress and depression; however, these findings should be interpreted cautiously given the cross-sectional design. Taken together, the results indicate that persistent, everyday stressors encountered during residency may be closely linked to adverse mental health outcomes, even in the absence of extreme stress levels. While resilient coping showed protective associations in unadjusted analyses, it did not retain independent significance after adjustment, suggesting that individual coping resources alone may be insufficient in highly demanding training environments. These findings underscore the importance of addressing organisational and structural contributors to stress and burnout to support the mental health and well-being of postgraduate medical trainees. Key Messages for Policy & Practice Burnout is strongly associated with both perceived stress and depressive symptoms among postgraduate medical residents and represents an important correlate linking stress and mental health outcomes. Institutional strategies aimed at reducing workload-related stressors, optimising duty hours, strengthening supervision, and ensuring access to confidential mental health support may be more impactful than approaches focused solely on enhancing individual coping or resilience. Incorporating structured wellness policies within postgraduate medical education is essential to address the substantial mental health burden observed among medical trainees. Declarations Funding - No funding was received. Acknowledgement - The authors acknowledge the use of ChatGPT 5.2(OpenAI) exclusively for language refinement. No generative AI was used for data analysis, content generation, or interpretation of results, and the authors take full responsibility for the manuscript. Conflict of Interest - The authors declare that they have no financial or personal conflicts of interest related to this study. 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Reviews Clin Gerontol 21(May):152–169. https://doi.org/10.1017/S0959259810000420 Tables Table no. 1 Socio demographic Details Characteristic Number Percentage % Gender Female 114 64.8% Male 62 35.2% Year of Residency First year 70 39.8% Second year 43 24.4% Third year 63 35.8% Specialty Medical 84 47.7% Surgical 61 34.7% Non-clinical / Paraclinical 31 17.6% Marital Status Single 102 58.0% Married 74 42.0% Job Status (Job to resume after residency) Yes 28 15.9% No 148 84.1% Health Issues Yes 31 17.6% No 145 82.4% Table No. 2 Clinical details Variable Mean (SD) Range % (Percentage), Frequency Perceived Stress (PSS-10 total) 21.9 (7.5) 0 – 40 High Stress - 22.2% (N= 39) Moderate Stress - 67.6% (N = 119), Low Stress - 10.2% (N = 18). Burnout (aCBI mean, 1–5) 3.15 (0.84) 1.17 – 5.0 56.3% (N = 99) Internal Burnout - 44.9% (N = 79) External Burnout -30.7% (N = 54). Depression (PSQ-4D total) 1.68 (1.52) 0 – 4 Present-50.0% (N=88) Absent -50.0% (N=88) Resilient Coping (BRCS total) 13.1 (3.4) 4 – 20 High Resilience- 11.9% (N = 21) Moderate Resilience - 36.4% (N = 64) Low Resilience - 51.7% (N = 91) Table no 3. Multivariable Logistic Regression Analysis – Predictors of Burnout Predictor aOR 95% CI p value Depression (Present) 6.21 2.66 – 14.45 <0.001 High stress 11.92 3.00 – 47.30 <0.001 Moderate stress 2.70 0.69 – 10.49 0.15 Low resilience 1.20 0.34 – 4.19 0.77 Medium resilience 0.67 0.20 – 2.18 0.50 Female gender 0.77 0.33 – 1.78 0.53 Surgical specialty 1.82 0.79 – 4.18 0.16 Table no 4. Multivariable Logistic Regression Analysis – Predictors of Depression Predictor aOR 95% CI p value Burnout (Present) 6.07 2.61 – 14.11 <0.001 High stress 37.2 3.05 – 452.7 0.005 Moderate stress 5.57 0.64 – 48.4 0.12 Low resilience 1.20 0.34 – 4.19 0.78 Medium resilience 0.36 0.10 – 1.37 0.14 Female gender 0.72 0.31 – 1.64 0.43 Surgical specialty 1.82 0.78 – 4.24 0.17 Additional Declarations The authors declare no competing interests. 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. 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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-8765697","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584384073,"identity":"cfda7825-af87-4ce7-af4a-e1fa6be4588f","order_by":0,"name":"Soumya Prakash","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYDCCA0hsxgYGhgR+ECuhgBQtkg0gLQakaDEAi+DRwnf7APOHj23bEvtn9z78OKOmLs/4/OrEDw8MGOT5xQ5g1SJ5LoFNcmbb7cQZd44bS244drjY7MbbzRJAhxnOnJ2AVYvBGQY2Zl6gloYbaQySD9gOJG67cXYDSEuCwW2cWpg/g7TMv5HG/PPBv7rEzTPObv5BQAuDNEjLhhtpbJIb25gTN/D3bsNri+QZxjbJGeduG2+8c4zNcmbf4cQZN3i3WSQYSOD0C98Z5sMfPpTdlp13u435Zs+3usT+/rObb/6osJHnl8auBRIZDAyODRIwAQmwSgnsqpGAPUIN/wGCqkfBKBgFo2BkAQB0cG088POWLgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0944-1780","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Soumya","middleName":"","lastName":"Prakash","suffix":""},{"id":584384074,"identity":"9b420ccd-72f8-48e6-8144-aa3e39ce911f","order_by":1,"name":"Sandeep Alex","email":"","orcid":"","institution":"Government Medical College Kottayam","correspondingAuthor":false,"prefix":"","firstName":"Sandeep","middleName":"","lastName":"Alex","suffix":""},{"id":584384075,"identity":"270c5361-6f94-49d0-9b04-71f13894c1f9","order_by":2,"name":"Devraj R","email":"","orcid":"","institution":"Government Medical College Thiruvananthapuram","correspondingAuthor":false,"prefix":"","firstName":"Devraj","middleName":"","lastName":"R","suffix":""}],"badges":[],"createdAt":"2026-02-02 13:42:55","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-8765697/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8765697/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101749646,"identity":"0ba7f795-42f4-4cbb-9d1a-09411d64c5f3","added_by":"auto","created_at":"2026-02-03 09:57:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":978651,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8765697/v1/ef540c80-5a5b-45d4-9b66-5c884c52ef00.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eInterrelationships between Perceived Stress, Burnout, Depression, and Resilient Coping among Postgraduate Medical Residents: An Analytical Cross-Sectional Study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePostgraduate medical education combines intensive duties, rigorous academic demands, and high-stakes examinations. This challenging environment often contributes to elevated stress and an increased risk of psychological distress among residents. Stress is highly prevalent among postgraduate medical residents and is frequently accompanied by symptoms of depression and burnout (Abdulrahman et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dave et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ratnakaran et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Between 2018 and 2022, 122 medical students in India died by suicide, of whom nearly half were postgraduate residents (Jha \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recent reports indicate that nearly 15% of postgraduate medical students experience clinically significant mental health problems, and approximately one-third report suicidal ideation, underscoring the need for attention to trainee well-being (NMC India \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Resilience is commonly defined as the ability to adapt positively to stressful circumstances or to \"bounce back\" from difficult experiences.(Windle \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In an alternate perspective, resilience is a dynamic process involving interdependent individual and contextual systems (Ungar \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). While higher individual resilience has been associated with lower psychological distress and reduced risk of depression, persistent endurance in stressful conditions may paradoxically compromise mental health. Factors that obstruct resilience, such as work\u0026ndash;life imbalance and chronic stress exposure, are also major contributors to burnout, suggesting an inverse relationship between burnout and resilient coping. However, evidence regarding its independent association with burnout and depression, as well as its role in modifying stress-related outcomes, remains mixed. Few studies have simultaneously examined perceived stress, burnout, depression, and resilience within a single analytical framework.\u003c/p\u003e \u003cp\u003eTherefore, the present study aimed to: (1) estimate the prevalence of perceived stress, burnout, depression, and resilience among postgraduate medical residents; (2) examine the associations between depression and burnout, and their relationships with perceived stress and resilience using bivariate analyses; and (3) identify independent predictors of burnout and depression through multivariable logistic regression. In addition, an exploratory analysis was undertaken to examine whether burnout may lie on the pathway between perceived stress and depression, with findings interpreted cautiously given the cross-sectional design.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eAn analytical cross-sectional design was employed, using an online survey.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eAll currently enrolled postgraduate medical residents at Government Medical College, Kottayam (Kerala, India), were eligible.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInclusion criteria\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePostgraduate medical residents studying at Government Medical College Kottayam during the study period.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eProvided electronic informed consent.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSubmitted incomplete responses on primary scales.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eStudy Duration\u003c/h3\u003e\n\u003cp\u003eData were collected between November 2024 and June 2025.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasures\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePerceived Stress: Assessed using the Perceived Stress Scale (PSS-10). Higher scores indicate greater perceived stress (Cohen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). Scores ranging from 0 to 13 were classified as indicating low perceived stress, scores from 14 to 26 as moderate perceived stress, and scores from 27 to 40 as high perceived stress.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBurnout: Assessed using the abbreviated Copenhagen Burnout Inventory (aCBI).Higher scores indicate greater burnout (Barton et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A total score of 16 or higher on Items 1\u0026ndash;4 indicates burnout stemming from an internal factor. A total score of 6 or higher on Items 5 and 6 indicates burnout stemming from an external factor. Exceeding the threshold scores for either factor indicates burnout.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eResilience: Measured using the Brief Resilient Coping Scale (BRCS). Higher scores indicate better resilient coping (Sinclair and Wallston \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Scores ranging from 4 to 13 were classified as indicating low resilient coping, scores from 14 to 16 as medium resilient coping, and scores from 17 to 20 as high resilient coping.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDepression: Screened using the Primary Care Screening Questionnaire for Depression (PSQ-4D). A score\u0026thinsp;\u0026ge;\u0026thinsp;2 was considered positive (Indu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSpecially designed proforma was used to collect basic socio demographic details of participants.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eSample Size\u003c/h3\u003e\n\u003cp\u003eUsing a finite population correction formula and published prevalence estimates [depression: 30.1%(Grover et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); stress: 37.3% (Sahasrabuddhe et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); burnout: 40%(Ratnakaran et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e); resilience: 63.9 (Waddimba et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)], the sample size calculated was 187 from the total postgraduate resident population of 438.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eAfter obtaining approval from the Institutional Review Board, an online proforma (Kobo Toolbox) was distributed via WhatsApp groups, including the participant information sheet, consent form, validated scales, and socio-demographic items. Non-responders were reminded monthly, and the survey closed after 7 days following the final reminder.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were screened for completeness before analysis. Missing data were minimal (\u0026lt;\u0026thinsp;5%) and were handled using the pairwise deletion method. Internal consistency of the study instruments was assessed using Cronbach\u0026rsquo;s α, with all scales demonstrating acceptable reliability (α\u0026thinsp;\u0026gt;\u0026thinsp;0.70). Descriptive statistics were summarised as frequencies and percentages for categorical variables and as means with standard deviations for continuous variables. Group comparisons were performed using the χ\u0026sup2; test or Fisher\u0026rsquo;s exact test for categorical variables.\u003c/p\u003e \u003cp\u003eMultivariable logistic regression analysis was conducted to identify independent predictors of burnout and depression. Variables showing statistical significance in bivariate analyses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10), along with clinically relevant covariates, were entered into the regression models. Results were expressed as adjusted odds ratios (aORs) with 95% confidence intervals.\u003c/p\u003e \u003cp\u003eAn exploratory mediation analysis was performed to examine whether burnout may lie on the pathway between perceived stress and depression. Since this is a cross-sectional study, findings were interpreted as hypothesis-generating. All statistical tests were two-tailed, and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSample Characteristics\u003c/h2\u003e \u003cp\u003eA total of 176 postgraduate medical residents participated in the study. The mean age of participants was 26.9 years (SD\u0026thinsp;=\u0026thinsp;2.1). Females constituted 64.8% (n\u0026thinsp;=\u0026thinsp;114) of the sample, and males accounted for 35.2% (n\u0026thinsp;=\u0026thinsp;62). With respect to the year of residency, 39.8% were first-year residents, 24.4% second-year residents, and 35.8% third-year residents. Nearly half of the participants belonged to medical specialties (47.7%), followed by surgical (34.7%) and paraclinical specialties (17.6%).\u003c/p\u003e \u003cp\u003eThe majority of participants were unmarried (58.0%), did not have a confirmed job awaiting them after completion of residency (84.1%), and reported no significant physical health problems (82.4%). Sociodemographic characteristics are presented in Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Psychological Variables\u003c/h2\u003e \u003cp\u003eThe descriptive statistics for the psychological variables are summarised in Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eDepressive symptoms were present in 50.0% (n\u0026thinsp;=\u0026thinsp;88) of participants. Burnout was identified in 56.3% (n\u0026thinsp;=\u0026thinsp;99) of the sample, with a mean burnout score of 3.15 (SD\u0026thinsp;=\u0026thinsp;0.84). Internal burnout was present in 44.9% (n\u0026thinsp;=\u0026thinsp;79) of participants, while external burnout was observed in 30.7% (n\u0026thinsp;=\u0026thinsp;54).\u003c/p\u003e \u003cp\u003ePerceived stress assessed using the PSS-10 revealed a mean score of 21.9 (SD\u0026thinsp;=\u0026thinsp;7.5). Most participants experienced moderate stress (67.6%, n\u0026thinsp;=\u0026thinsp;119), followed by high stress (22.2%, n\u0026thinsp;=\u0026thinsp;39) and low stress (10.2%, n\u0026thinsp;=\u0026thinsp;18).\u003c/p\u003e \u003cp\u003eResilience assessed using the Brief Resilient Coping Scale (BRCS) showed that 51.7% (n\u0026thinsp;=\u0026thinsp;91) of participants had low resilience, 36.4% (n\u0026thinsp;=\u0026thinsp;64) had moderate resilience, and 11.9% (n\u0026thinsp;=\u0026thinsp;21) demonstrated high resilience.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation Between Depression and Burnout\u003c/h2\u003e \u003cp\u003eA strong association was observed between depression and burnout. Among participants without depression, 30.7% (n\u0026thinsp;=\u0026thinsp;27) experienced burnout, whereas 81.8% (n\u0026thinsp;=\u0026thinsp;72) of those with depression met criteria for burnout. Chi-square analysis demonstrated a highly significant association between depression and burnout (χ\u0026sup2; = 46.75, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Participants with depression had over ten times higher odds of burnout compared to those without depression (OR\u0026thinsp;=\u0026thinsp;10.17; 95% CI: 5.02\u0026ndash;20.60).\u003c/p\u003e \u003cp\u003eInternal burnout was present in 72.7% of participants with depression compared to 17.0% among those without depression. External burnout was observed in 42.0% of participants with depression, in contrast to 19.3% among non-depressed participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of Depression with Perceived Stress and Resilience\u003c/h2\u003e \u003cp\u003eHigh perceived stress was more common among participants with depression (40.9%) than among those without depression (3.4%), while low stress was infrequent in the depressed group (1.1%) but more prevalent among non-depressed participants (19.3%). Low resilience was observed in 68.2% of participants with depression compared to 35.2% without depression, whereas high resilience was least common in the depressed group (9.1%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociation Between Burnout, Stress, and Resilience\u003c/h2\u003e \u003cp\u003eBurnout showed a strong association with perceived stress. Among participants with burnout, 36.4% reported high stress, compared to only 3.9% among those without burnout (χ\u0026sup2; = 40.23, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Resilience was also significantly associated with burnout (χ\u0026sup2; = 10.58, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.005). Burnout was present in 65.9% of participants with low resilience, compared to 28.6% among those with high resilience.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Correlates\u003c/h2\u003e \u003cp\u003eHigh perceived stress was significantly associated with gender (χ\u0026sup2; = 9.50, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.009) and specialty (χ\u0026sup2; = 16.45, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;=\u0026thinsp;0.002), with higher stress observed among females and participants from surgical specialities. Depression was significantly associated with speciality (χ\u0026sup2; = 9.21, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.010). Resilience levels were significantly associated with job status (χ\u0026sup2; = 6.18, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.046), with higher resilience observed among participants who were already employed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable Logistic Regression Analysis\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003ePredictors of Burnout\u003c/h2\u003e \u003cp\u003eAfter adjustment for perceived stress category, resilience, gender, and speciality, depression remained independently associated with burnout (adjusted OR [aOR]\u0026thinsp;=\u0026thinsp;6.21; 95% CI: 2.66\u0026ndash;14.45; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). High perceived stress emerged as the strongest independent predictor of burnout (aOR\u0026thinsp;=\u0026thinsp;11.92; 95% CI: 3.00\u0026ndash;47.30; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Resilience, gender, and speciality were not independently associated with burnout. Model performance indicated good explanatory power (Pseudo R\u0026sup2; = 0.32; likelihood ratio test p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). [Table no. 3]\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Depression\u003c/h2\u003e \u003cp\u003eIn the adjusted model, burnout was independently associated with depression (aOR\u0026thinsp;=\u0026thinsp;6.07; 95% CI: 2.61\u0026ndash;14.11; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). High perceived stress demonstrated a strong independent association with depression (aOR\u0026thinsp;=\u0026thinsp;37.20; 95% CI: 3.05\u0026ndash;452.70; p\u0026thinsp;=\u0026thinsp;0.005). Resilience, gender, and speciality were not independently associated with depression. The model demonstrated good explanatory capacity (Pseudo R\u0026sup2; = 0.34; likelihood ratio test p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). [Table no. 4]\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the interrelationships among perceived stress, burnout, resilient coping, and depressive symptoms in postgraduate medical residents. Approximately half of the residents screened positive for depressive symptoms, and more than half experienced burnout. Depression and burnout were strongly associated even after adjustment for perceived stress, resilient coping, gender, and speciality, while perceived stress demonstrated the strongest association with both outcomes. Exploratory analyses, presented as supplementary material, suggested that burnout may be associated with the relationship between perceived stress and depression; however, these findings should be interpreted cautiously given the cross-sectional design.\u003c/p\u003e \u003cp\u003eAn important observation in this study was the discrepancy between perceived stress levels and downstream psychological outcomes. Although only 22% of residents met the PSS-10 threshold for high perceived stress, substantially higher proportions screened positive for burnout (59%) and depression (50%). This difference likely reflects variation in construct measurement. The PSS-10 captures current appraisal of stress, whereas burnout and depressive symptoms represent cumulative syndromic outcomes that may evolve following prolonged exposure to moderate or persistent stress. Consequently, residents with moderate stress scores may experience burnout and depressive symptoms over time. This aligns with Maslach\u0026rsquo;s conceptualisation of burnout as a process mediating the impact of chronic stressors on mental health outcomes (Maslach \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prevalence of psychological morbidity observed in this population is concerning. Half of the residents screened positive for depressive symptoms, nearly three-fifths experienced burnout, and over half demonstrated low resilient coping. These findings are broadly consistent with prior studies among postgraduate medical trainees reporting high levels of stress-related psychological morbidity during residency training (Alshardi and Farahat 2020; Dave et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dyrbye et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Grover et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mitra et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Priyam et al. 2024; Ratnakaran et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shahi et al. 2022). Together, these results underscore the substantial mental health burden faced by residents, particularly in demanding public sector training environments.\u003c/p\u003e \u003cp\u003eInternational research supports a mediating role of resilience in the pathway from stress to depression. Among Spanish nurses during the COVID-19 pandemic, resilience significantly mediated the effects of stress on depression, anxiety, and psychological distress (Lara-Cabrera et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, resilience has been shown to critically mediate stress-induced depression and anxiety among nursing students (Devi et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), as well as in psychiatric nurses exposed to occupational stress (Chen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, resilient coping did not retain independent significance in multivariable models in the present study, despite showing protective associations in unadjusted analyses. This divergence may reflect contextual differences in residency training, where workload, duty hours, and responsibility burden may limit the protective influence of individual coping resources. Our findings suggest that perceived stress may be associated with depressive symptoms primarily through burnout, rather than being substantially offset by resilient coping alone.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eWhat this study adds\u003c/h2\u003e \u003cp\u003eWhile the stress\u0026ndash;burnout\u0026ndash;depression relationship has been previously documented, analytical evidence from the residency context remains limited (Mitra et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This study extends existing models by examining perceived stress, burnout, depression, and resilient coping within a single analytical framework among postgraduate medical residents in a Government Medical College. The findings highlight burnout as a key correlate linking perceived stress and depressive symptoms, while resilient coping did not independently explain this association after adjustment. The high prevalence of depression (50%) and burnout (59%) lies at the upper end of both Indian and global estimates, reinforcing the need of addressing resident well-being.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eImplications\u003c/h2\u003e \u003cp\u003eThese findings have important implications for postgraduate medical training programs. Interventions focusing solely on reducing perceived stress may be insufficient if burnout is not simultaneously addressed. Institutional strategies aimed at optimizing duty hours, improving supervision, ensuring adequate rest, and fostering supportive peer and faculty relationships may help in reducing burnout risk. Given the high prevalence of depressive symptoms, residency programs should also incorporate routine mental health screening and ensure access to confidential counselling services. Structured orientation programs, mentorship and clearly regulated work schedules may further support resident well-being.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study contributes Indian data to a literature largely dominated by international research, thereby enhancing cross-cultural understanding of stress-related mental health outcomes in medical training. The use of validated instruments strengthens measurement reliability, and the inclusion of over 40% of the postgraduate cohort in a large government medical college enhances internal validity within this context. The predominance of female participants reflects the current gender distribution in undergraduate and postgraduate medical training in Kerala, where women constitute an increasing proportion of medical students, and is therefore likely to be representative of the resident population in this setting.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. The cross-sectional design precludes causal inference and limits conclusions regarding temporal sequencing. Reliance on self-report measures without diagnostic interviews may introduce reporting bias. The study was conducted at a single institution, which may limit generalizability, although inclusion across specialities and years of training provides breadth. Resilient coping was assessed using a brief scale, which may not fully capture its multidimensional nature. Finally, while resilience did not retain independent significance in adjusted models, this should not be interpreted as evidence against its broader importance, but rather as an indication that structural and organisational stressors may outweigh individual coping resources in the residency context.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates a high burden of depressive symptoms and burnout among postgraduate medical residents, with strong associations observed between perceived stress, burnout, and depression. Although only a minority of residents met criteria for high perceived stress, the majority reported at least moderate stress levels, which were strongly associated with both burnout and depressive symptoms. Exploratory analyses suggested that burnout may be associated with the relationship between perceived stress and depression; however, these findings should be interpreted cautiously given the cross-sectional design.\u003c/p\u003e \u003cp\u003eTaken together, the results indicate that persistent, everyday stressors encountered during residency may be closely linked to adverse mental health outcomes, even in the absence of extreme stress levels. While resilient coping showed protective associations in unadjusted analyses, it did not retain independent significance after adjustment, suggesting that individual coping resources alone may be insufficient in highly demanding training environments. These findings underscore the importance of addressing organisational and structural contributors to stress and burnout to support the mental health and well-being of postgraduate medical trainees.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eKey Messages for Policy \u0026amp; Practice\u003c/h2\u003e \u003cp\u003eBurnout is strongly associated with both perceived stress and depressive symptoms among postgraduate medical residents and represents an important correlate linking stress and mental health outcomes. Institutional strategies aimed at reducing workload-related stressors, optimising duty hours, strengthening supervision, and ensuring access to confidential mental health support may be more impactful than approaches focused solely on enhancing individual coping or resilience. Incorporating structured wellness policies within postgraduate medical education is essential to address the substantial mental health burden observed among medical trainees.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e- No funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e- The authors acknowledge the use of ChatGPT 5.2(OpenAI) exclusively for language refinement. No generative AI was used for data analysis, content generation, or interpretation of results, and the authors take full responsibility for the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e- The authors declare that they have no financial or personal conflicts of interest related to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdulrahman M, Nair SC, Farooq MM, Kharmiri AA, Marzooqi FA, and Frederick Robert Carrick (2018) Burnout and Depression among Medical Residents in the United Arab Emirates: A Multicenter Study. 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Reviews Clin Gerontol 21(May):152\u0026ndash;169. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0959259810000420\u003c/span\u003e\u003cspan address=\"10.1017/S0959259810000420\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable no. 1 Socio demographic Details\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear of Residency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFirst year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecond year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThird year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecialty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSurgical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-clinical / Paraclinical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob Status (Job to resume after residency)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth Issues\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable No. 2 Clinical details\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (Percentage), Frequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePerceived Stress (PSS-10 total)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.9 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 \u0026ndash; 40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh Stress - 22.2% (N= 39)\u003c/p\u003e\n \u003cp\u003eModerate Stress - 67.6% (N = 119), \u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLow Stress - 10.2% (N = 18).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBurnout (aCBI mean, 1\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.15 (0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.17 \u0026ndash; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;56.3% (N = 99)\u003c/p\u003e\n \u003cp\u003eInternal Burnout - 44.9% (N = 79)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eExternal Burnout -30.7% (N = 54).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDepression (PSQ-4D total)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.68 (1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePresent-50.0% (N=88)\u003c/p\u003e\n \u003cp\u003eAbsent -50.0% (N=88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilient Coping (BRCS total)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.1 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 \u0026ndash; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh Resilience- 11.9% (N = 21)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eModerate Resilience - 36.4% (N = 64)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLow Resilience - 51.7% (N = 91)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable no 3. Multivariable Logistic Regression Analysis \u0026ndash; Predictors of Burnout\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression (Present)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.66 \u0026ndash; 14.45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.92\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.00 \u0026ndash; 47.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eModerate stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.69 \u0026ndash; 10.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eLow resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.34 \u0026ndash; 4.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eMedium resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.20 \u0026ndash; 2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eFemale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.33 \u0026ndash; 1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eSurgical specialty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.79 \u0026ndash; 4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable no 4. Multivariable Logistic Regression Analysis \u0026ndash; Predictors of Depression\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBurnout (Present)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.61 \u0026ndash; 14.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e37.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.05 \u0026ndash; 452.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eModerate stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e5.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.64 \u0026ndash; 48.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eLow resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.34 \u0026ndash; 4.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eMedium resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.10 \u0026ndash; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eFemale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.31 \u0026ndash; 1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eSurgical specialty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.78 \u0026ndash; 4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Government medical college kottayam","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":"Stress, Psychological, Burnout, Depressive Disorder, Psychological Resilience, Occupational Stress, Postgraduate Medical Residents","lastPublishedDoi":"10.21203/rs.3.rs-8765697/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8765697/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003ePostgraduate medical residency involves heavy workload and sustained academic pressure, increasing vulnerability to burnout and depression. However, the interrelationships among perceived stress, burnout, depression, and resilient coping remain under explored in the Indian residency context.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e To estimate the prevalence of perceived stress, burnout, depressive symptoms, and resilient coping among postgraduate medical residents, and to identify independent predictors of burnout and depression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e An analytical cross-sectional online survey was conducted among postgraduate medical residents at a Government Medical College in Kerala between November 2024 and June 2025. Validated instruments assessed perceived stress (PSS-10), burnout (abbreviated Copenhagen Burnout Inventory), resilient coping (Brief Resilient Coping Scale), and depressive symptoms (PSQ-4D). Associations were examined using χ² tests and multivariable logistic regression. An exploratory analysis examined whether burnout was associated with the stress–depression pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 176 residents participated (64.8% female). Burnout was present in 56.3%, depressive symptoms in 50.0%, and low resilient coping in 51.7%. Although only 22.2% reported high perceived stress, most experienced moderate stress (67.6%). Depression was strongly associated with burnout (OR = 10.17; p \u0026lt; 0.001). High perceived stress independently predicted burnout (aOR = 11.92) and depression (aOR = 37.20), while burnout independently predicted depression (aOR = 6.07). Resilient coping was not independently associated with either outcome.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Burnout and depressive symptoms are highly prevalent among postgraduate residents. Burnout appears to be a key correlate linking perceived stress and depression, highlighting the need for organizational and structural interventions beyond individual resilience-focused strategies.\u003c/p\u003e","manuscriptTitle":"Interrelationships between Perceived Stress, Burnout, Depression, and Resilient Coping among Postgraduate Medical Residents: An Analytical Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 09:54:49","doi":"10.21203/rs.3.rs-8765697/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":"78bafa36-9c0e-4645-9f02-f793436097e7","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62166460,"name":"Psychology"}],"tags":[],"updatedAt":"2026-02-03T09:54:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 09:54:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8765697","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8765697","identity":"rs-8765697","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}