Psychological Distress and Its Predictors Among Hospital Admitted COVID-19 Patients

Psychological Distress and Its Predictors Among Hospital Admitted COVID-19 Patients | 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 Psychological Distress and Its Predictors Among Hospital Admitted COVID-19 Patients Renjith R. Pillai, Abhishek Ghosh, Sumit Shrivasthava, Sanuj Muralidharan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1038192/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 Objective Limited evidence is available on the psychological distress among patients hospitalized with COVID -19. We assessed (a) the incidence of psychological distress, posttraumatic symptoms and substance use among patients hospitalized with COVID-19, (b) perceived stress, coping, and social support experienced by distressed and non-distressed patients and the predictors of psychological distress. Method Ours was a hospital-based cross-sectional study, conducted in a Union Territory of India. Patients were assessed (August – September, 2020) at the time of admission (within two days) with standardized instruments (N=250). Results More than 19 percent of respondents had experienced significant psychological distress (probable cases) and nearly 9% reported post traumatic stress symptoms. The cases and non-cases differ in terms of active coping (5.51±0.87 v/s 5.06±1.06; t=3.10, p<0.01), emotional support (5.21±0.87 v/s 4.86±0.79; t=2.57, p<0.01), behavioural disengagement (5.18±0.92 v/s 4.55±1.15; t=3.56, p<0.001), venting (5.42±0.96 v/s 4.80±1.24; t=3.30, p<0.01), acceptance (5.75±1.24 v/s 5.29±1.50; t=2.23, p<0.05), religion (5.43±1.41 v/s 6.06±1.46; t=-2.76, p<0.01) and self-blame (5.65±1.00 v/s 4.82±1.39; t=3.95, p<0.001). Symptoms of post-traumatic stress (OR: 2.058; 95% CI: 1.49-2.84) was the only significant predictor of the psychological distress. Conclusions Nearly one in five hospitalized patients with COVID-19 experience psychological distress. Screening and treatment for trauma and psychological distress should be made an integral component of care for patients with COVID-19 Psychiatry COVID-19 Psychological distress PTSD Substance Use Stress Coping Social Support hospitalized patients 1. Introduction The World Health Organization declared the Coronavirus Disease-19 as pandemic in the March 2020. Starting from China in 2019, World hasn’t yet recovered from this deadly corona virus pandemic with many countries now facing a second wave after a dip in the infections for a while. The first case of COVID-19 in India was reported in the state of Kerala on 30 January 2020. As on 14th April, 2021, 262 million cumulative total samples were tested among which 13.9 million turned out to be positive cases (1). Total patients recovered from COVID-19 so far were 12.4 million and 1.47 active cases are available at present in the country. Total deaths reported due to COVID-19 are 0.17 million (2). World Health Organization (3) reports that most people infected with the COVID-19 virus experience mild to moderate respiratory illness and recover without requiring special treatment. However, confirmed or suspected cases of COVID-19 do suffer from serious health-related problems apart from mental health issues when there is underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer (4,5). Majority of the available studies on the mental health consequences of COVID 19 are done on the general population, with a few focusing on health care workers and vulnerable groups like children and geriatric population. World Health Organization (6) in its report on mental health pronounces that patients with COVID-19 are prone to wide range of mental disorders such as anxiety and depression. Loneliness, boredom, denial, harmful substance use, PTSD, anxiety and depression were reported by suspected and/or confirmed COVID-19 quarantined persons (7, 8, 9, 10). Fever, hypoxia and cough along with adverse effects of prescribed medications (e.g. corticosteroids) are shown increase anxiety and mental distress (7). Two hospital-based studies from China found the incidence of anxiety and depressive symptoms among COVID-19 patients with one study reporting 18.6% and 13.4% and the other as 34% and 28% (11,12) respectively. During the SARS period, in a survey from Hong Kong (13) conducted at a convalescent hospital, around half (50%) of recovered SARS patients reported anxiety, and approximately 20% were fearful, including panic attacks, feelings of depression, or stigmatization. In yet another study (14) from Torondo, Canada, patients with SARS reported fear, loneliness, boredom and anger, and worries about the effects of quarantine and contagion on family members and friends. Post-SARS pandemic or post-Ebola, social and psychological issues were present among physically recovered patients even after a substantial period (15). Attending to the physical, biological and medical needs of the patients should receive attention of the health professionals and policy makers. The psyche of the patients, especially those who are either home quarantined or admitted in the hospitals are seldom looked into. Common mental health problems and at times disorders found among hospital admitted patients in a pandemic situation are often neglected and on the contrary the physical needs of the patients are usually well attended. In other words, the patients are deprived of essential mental health services which are equally important along with routine medical care. To bring mental health needs to the mainstream attention, it’s important to determine the incidence of mental health problems. Such knowledge would be helpful to device evidence-driven strategies to reduce adverse psychosocial impacts and psychiatric symptoms. Thus, the current study was undertaken with the primary objective to determine the incidence and course of psychological distress, posttraumatic symptoms and substance use among subjects recently diagnosed with COVID-19. The secondary objectives were to assess the level of stress, coping and social support experienced by distressed and non-distressed patients and understand the predictors of psychological distress admitted at the hospital with COVID 19. 2. Methods 2.1 Study Setting & Design The data is from a longitudinal study among admitted COVID-19 patients recruited from the Sri Dhanwantry Ayurveda College and Hospital located at Sector 46B, Chandigarh, a National Accreditation Board for Hospitals & Healthcare Providers (NABH) accredited Medical College and Hospital under Indian Systems of Medicine. As per the instruction of Chandigarh Union Territory Administration, this hospital has marked 50 beds for COVID -19 patients in an exclusive ward. Covid diagnosed patients, asymptomatic or with mild to moderate symptoms who do not have home isolation facility were referred from Post Graduate Institute of Medical Education and research (PGIMER), Chandigarh, Government Medical College and Hospital (GMCH), Chandigarh and Government Multi-Speciality Hospital (GMSH) to this hospital for treatment and care. Apart from the in-house BAMS (Bachelor of Ayurvedic Medicine and Surgery) doctors, a MBBS (Bachelor of Medicine, Bachelor of Surgery) Doctor or an MD (Doctor of Medicine) Resident doctor from GMCH, Sector 32, Chandigarh was made available for the basic medication management and care in accordance with Government of India guidelines. Patients stay for a maximum period of 10 days at the hospital; asymptomatic patients with stable vitals are discharged subsequently to stipulated quarantine facilities of the UT Administration. Follow-up of the patient were done physically or telephonically on the completion of four weeks. The study was done in months of August - September, 2020. 2.2 Study Population Assuming that 20% of the subjects in the population have the factor of interest, the study required a sample size of 246 for estimating the expected proportion with 5% absolute precision and 95% confidence. A total of 250 patients were recruited for the final study. 2.3 Measurements The socio-demographic data and the clinical variables were collected with the help of a schedule prepared for the study. The psychological distress was measured using Self Reporting Questionnaire (16) - Cutoff of 5 for males and 6 for females (17) was considered as a case ); post traumatic stress using Trauma Screening questionnaire (2) - cutoff score : 5; severity of substance use using ASSIST - Alcohol, Smoking and Substance Involvement Screening Test (18); degree of stress using Perceived Stress Scale (19); coping strategies using Brief-COPE inventory (20) and perceived social support using Social Support Scale (21). Patients admitted with the confirmed diagnosis of COVID-19, either asymptomatic or have mild to moderate COVID-19, between 18-75 years from either sex, cooperative and well versed in either English, Hindi or Punjabi were included for the study. Those excluded were patients with severe COVID-19, below the age of 18 years or more than 75 years and were unwilling to participate in the study. 2.4 Ethical aspects The Institute Ethics Committee of PGIMER, Chandigarh cleared the study (Reference No: NK/6456/Study/600). Confidentiality was assured and the informed consent was taken before data collection. To minimize the risk of infection, data was collected both in online and offline mode as per the convenience of the patients. Patients with Android mobiles completed data collection of the self-administered instruments through excel sheets. Whatsapp video calls were done by the co-investigators from study hospital to clear the doubts of the respondents as well as to collect the interview administered instruments. In the offline mode, the study instruments (hard copies) were made available to them by PPE attired on-duty staff members in the ward. Scanned copies of the completed instruments were whatsapped back to the investigators and the original questionnaire was kept in the safe custody with lock and keys within the ward accessible only to the investigators or staff members with permission. 2.5 Statistical Analysis The baseline data collected was analysed using IBM SPSS Statistics Version 26. Descriptive statistics were adopted for socio-demographic and clinical variables. Categorical variables were presented in frequency and percentages. Association of psychological distress with independent variables were determined by ‘t’ test or chi square test. To determine the predictors of the psychological distress, binary logistic regression was carried out with the variables significant in the univariate analysis. 3. Results 3.1 Demographic and clinical profile of the patients The total participants who completed the baseline assessments were 250. Among them, 201 (80.4%) participants were found to be non-cases and 49 (19.6%) participants were probable cases (persons experiencing psychological distress). The mean age of the participants was 47.92 (±13.96) years. The mean years of education of the participants were 14.71 (±1.58) years. Males constituted 52% of the participants and the differences in the proportion of males versus females falling in the non-case and case categories were significant (χ2=9.22, p<0.01). Educational qualification of the majority of the participants (81.2%) ranged between high school and graduation. Married participants were 81.2% and a little more than half of the participants (53.6%) were in some form of remunerative job. Hindu religion (85.2%), middle socio-economic status (81.9%) and nuclear family (77.6%) were the predominant categories among the participants. Majority (82%) of the participants were from urban locality and there were significant differences (χ2=8.86, p<0.01) in the proportion of the urban versus rural participants falling under non-case and case categories. None of the patients required oxygen therapy nor were referred to any higher treatment facilities. The COVID-19 severity was reported as mild by 84.8% participants. Co-morbidities was seen more among non-cases and there was a significant difference (χ2=15.85, p<0.001) in the co-morbid / underlying medical conditions between the participants belonging to non-case and case categories. The prevalence of substance was very low with the mean scores for tobacco, alcohol and cannabis was seen as 1.14 (±5.14), 1.96 (±6.69) and 0.10 (±1.07) respectively on ASSIST. …………………………………………Insert table (1) here……………………………………… 3.2 Trauma, stress, coping and social support The incidence of post traumatic symptoms among the respondents was 8.8%. There was a significant difference (t=-9.88, p<0.001) in the mean PTSD score of the non-case participants (0.79±1.37) from those who are probable cases (4.27±2.37). Similarly, there was also a significant difference (t=-9.34, p<0.001) in the mean perceived stress score among non-cases (4.80±6.49) and probable cases (16.22±7.94). Among the non-cases and probable cases, significant differences were also observed in the subscales of the coping like active coping (5.51±0.87 v/s 5.06±1.06; t=3.10, p<0.01), emotional support (5.21±0.87 v/s 4.86±0.79; t=2.57, p<0.01), behavioural disengagement (5.18±0.92 v/s 4.55±1.15; t=3.56, p<0.001), venting (5.42±0.96 v/s 4.80±1.24; t=3.30, p<0.01), acceptance (5.75±1.24 v/s 5.29±1.50; t=2.23, p<0.05), religion (5.43±1.41 v/s 6.06±1.46; t=-2.76, p<0.01) and self-blame (5.65±1.00 v/s 4.82±1.39; t=3.95, p0.05), friends (t=0.88, p>0.05) and significant others (t=-1.04, p>0.05) were similar in nature in both “non-case” and “case” categories. …………………………………………Insert table (2) here……………………………………… 3.3 Psychological distress and its correlates The socio-demographic and clinical variables significant in the univariate analysis were entered in the logistic regression model to find-out the independent predictors of psychological distress. Only PTSD was found to have more than two times higher odds of causing psychological distress among the participants (p<.0001; OR: 2.058; 95% CI: 1.49-2.84).The variance (Nagelkerke R 2 ) explained by this model was 62.4%. …………………………………………Insert table (3) here……………………………………… 4. Discussion In India, COVID-19 has adversely impacted the economy, jobs, and health infrastructure (22). After a dip in the number of cases, there is again a surge in COIVD-19 cases; mental health of the patients is a concern. Using standardized instruments, this cross-sectional study is perhaps the first study from India done among the hospitalized COVID-19 patients to assess the psychological distress experienced by them. Around 20% of hospitalized patients with COVID-19 reported psychological distress. Psychological distress among hospitalized patients is reported by researchers (23, 24) and apart from PTSD, excessive pre-occupation about pandemic and confinement to a closed space without any opportunity to move out and interact with familiar people could be contributing to the same. Psychosocial interventions are recommended by experts to such distressed patients admitted in the hospitals. Information and accessibility to tele-interventions through dedicated psychosocial and mental health helplines or those run by mental health professional bodies or availability of mental health professionals within the hospital for undertaking tele-video mental health interventions is important. Evidences of some interventions which could be applied with hospital admitted patients include psychological–behavioral intervention (PBI) program comprising psychological support and breathing exercises (25); brief crisis intervention (26); music therapy (27); progressive muscle relaxation training (28); Yoga – meditation and mindfulness (33); mobile phone-based individual counseling (29); internet-based self-help intervention (30) and multimedia psycho educational intervention (24). Males (71.4%) were found to be having more psychological distress than females. This could be due to their bread winner status in the family and their concerns for the other family members as COVID-19 has resulted in more death among males than females across the World, though in India the scenario was opposite (31). Caseness (Psychological distress) was significantly more among urban population (67.3%). Similar finding was reported in a post COVID-19 research from Turkey where they have found urban residents experiencing depression and anxiety more than those from rural areas (32). Strict quarantine within the limited spaces / houses, stress resulting from the difficulty to maintain social distancing due to population density and a general high prevalence of covid cases in the cities (33) are cited as few probable reasons. Contrary to the known findings (34, 35), in the present study patients without any co-morbid conditions were having significantly more distress than those with co-morbid conditions. Hospitalization, attention and care, food and safety measures, regular monitoring of the vitals by the health professionals and psychosocial counseling support made available from the day of admission to such vulnerable patients could be the possible reasons. Mean trauma and perceived stress scores of patients under ‘case’ category was significantly more than those belonging to ‘non- case’ category. Trauma, stress and psychological distress go hand in hand and this had been reported in various studies across the globe (36, 37, 38). The probable reasons for high trauma and perceived stress leading to high psychological distress could be infective nature of illness, reports of deaths and other medical complications arising or triggered due to covid, lack of proven drugs or specific treatment (4), fear of isolation by the community members due to stigma and misinformation, overloading of information at times conflicting and fake ones in social media, impact of negative news report (38), worries about the non affected family members, livelihood issues and financial worries. Looking at the coping strategies, it was seen that in spite of resorting to dysfunctional coping strategies such as behavioural disengagement, venting and self-blame, patients in the non-case category were showing significant “acceptance” to the situation. It’s culturally not uncommon among people to resort to self-blame, venting and behavioural disengagement to cope with difficult situations in India and that perhaps would have reduced the psychological distress. The lesser distress level among patients in ‘non-case’ category also could be due to their better perceived emotional support and active coping strategy. Patients in ‘case’ category were reposing their faith in God (religion) significantly more than those under ‘non-case’ category which is again well within the religious - spiritual cultural background of the country where people resort to god for resolution of their physical and psychological problems. Both the category of patients was receiving fairly equal support from family, friends and significant others. PTSD (trauma) was the only variable found to be a significant predictor of the psychological distress. PTSD is widely reported in literature in the aftermath of various types of disasters such as nuclear accidents, floods, earthquake, tsunami, war and pandemic outbreaks such as SARS (39-44). Earlier studies also have found a similar relationship between PTSD and Psychological Distress (39, 7). Our study had the following limitations: (a) we have included only hospitalized patients and patients with moderate COVID-19; therefore, our study results may not be generalizable to the other groups of patients; (b) this study was from a single center and from an Union Territory of India; the city stands at first position in human development index in the country and has a relatively better health infrastructure (GMSH, GHCH and PGIMER) and per-capita income (4th position in the country) than many other states and union territories of the country (45); therefore, the results of our study may not be extrapolated to other states; (c) we did not use any diagnostic instruments, and therefore could not comment on the incidence of a particular psychiatric diagnosis; (d) this cross-sectional study could not inform us about the course of severe psychological distress. 5. Conclusion The current study showed that around 20% hospitalized patients with COVID-19 had mild to moderate category was experiencing psychological distress. The presence of post-traumatic stress symptoms was a predictor of psychological distress. Though there were variations in the coping strategies adopted by the patients, “acceptance” was associated with less psychological distress. Our study showed that screening and treatment for psychological distress should be made an integral part of care for patients with COVID-19. Use of digital technology appears to be one of the most viable options as it minimizes the chances of infection to the service provider. COVID-19 is going to stay long and hence, it is important for all the in-patient treatment centers to ensure the services of mental health professionals are available within the setting. Declarations Author statements Renjith R. Pillai MSW, M.Phil PSW, PhD: Conceptualization; methodology, data curation, writing – original draft preparation, writing – review & editing. Abhishek Ghosh MD, DM: Conceptualization; methodology, data curation, Formal analysis, Software, writing – original draft preparation, writing – review & editing. Sumit Shrivasthava MD (Ay.), PhD: Investigation; Project administration; Resources; Supervision; Writing - review & editing. Sanuj Muralidharan MD (Ay.): Investigation; Resources; Writing - review & editing. Krishan Kumar MA, M.Phil CP, Ph.D: Conceptualization; Writing – original draft preparation, Writing – review & editing. Saranya S Kumar MD (Ay.): Investigation; Resources; Writing - review & editing Funding Sources None of the authors have received any monetary support from any agencies for the execution of this research work Data Sharing Data will be made available to interested individuals upon formal request to authors Transparency Statement The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported. Declaration of competing interest None of the authors have relevant disclosures. Acknowledgments We thank all the patients and their caregivers for their time and consent to participate in this study. We acknowledge the motivation, dedication and commitment of the on-duty professional staff and healthcare workers as well as trainee students at SDAC and Hospital, Chandigarh for continued service to those affected by COVID-19 pandemic. References Indian Council of Medical Research. COVID-19. https://icmr.gov.in/index.html ; 2021, Accessed date: 14 April 2021 Ministry of Health and Family Welfare. For information on CoVID-19 Vaccine. https://www.mohfw.gov.in/ ; 2021, Accessed date: 14 April 2021 World Health Organization. Corona Virus. https://www.who.int/healthtopics/coronavirus #tab=tab_1 Accessed date: 14 April 2021 Sanyaolu A, Okorie C, Marinkovic A, et al. Comorbidity and its Impact on Patients with COVID-19 [published online ahead of print, 2020 Jun 25]. SN Compr Clin Med. 2020;1–8. doi: 10.1007/s42399-020-00363-4 Ng WH, Tipih T, Makoah NA, et al. Comorbidities in SARS-CoV-2 Patients: a Systematic Review and Meta-Analysis. mBio. 2021;12(1):e03647-20. Published 2021 Feb 9. doi: 10.1128/mBio.03647-20 World Health Organization. The impact of COVID-19 on mental, neurological and substance use services: results of a rapid assessment. Geneva; 2020. Licence: CC BY-NC-SA 3.0 IGO. Wang W, Wu X, Lan X. Rumination mediates the relationships of fear and guilt to posttraumatic stress disorder and posttraumatic growth among adolescents after the Ya'an earthquake. Eur J Psychotraumatol. 2020;11(1):1704993.. doi: 10.1080/20008198.2019 . 1704993 Dong L, Bouey J. Public Mental Health Crisis during COVID-19 Pandemic, China. Emerg Infect Dis. 2020;26(7):1616–1618. doi: 10.3201/eid2607.200407 Li S, Wang Y, Xue J, Zhao N, Zhu T. The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users. Int J Environ Res Public Health. 2020;17(6):2032. Published 2020 Mar 19. doi: 10.3390/ijerph17062032 Hanafi E, Siste K, Limawan AP, et al. Alcohol- and Cigarette-Use Related Behaviors During Quarantine and Physical Distancing Amid COVID-19 in Indonesia. Front Psychiatry. 2021;12:622917. Published 2021 Feb 2. doi: 10.3389/fpsyt.2021.622917 Dai L-L, Wang X, Jiang T-C, Li P-F, Wang Y, Wu S-J, et al. (2020) Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. PLoS ONE 15(8): e0238416. https://doi.org/10.1371/journal.pone. 0238416 Kong X., Zheng K., Tang M. Prevalence and factors associated with depression and anxiety of hospitalized patients with COVID-19. medRxiv. 2020 doi: 10.1101/2020.03.24.20043075 . (preprint) Tsang HW, Scudds RJ, Chan EY. Psychosocial impact of SARS. Emerg Infect Dis. 2004 Jul;10(7):1326–7. doi: 10.3201/eid1007.040090 . PMID: 15338536; PMCID: PMC3323309. Maunder R, Hunter J, Vincent L, et al. The immediate psychological and occupational impact of the 2003 SARS outbreak in a teaching hospital. CMAJ. 2003;168(10):1245–1251. Kar SK, Yasir Arafat SM, Kabir R, Sharma P, Saxena SK. Coping with Mental Health Challenges During COVID-19. Coronavirus Disease 2019 (COVID-19). 2020;199-213. Published 2020 Apr 30. doi: 10.1007/978-981-15-4814-7_16 World Health Organization. A user’s guide to the Self-Reporting Questionnaire. WHO/MNH/PSSF 94.8. WHO, Geneva. 1994 Netsereab, T.B., Kifle, M.M., Tesfagiorgis, R.B. et al. Validation of the WHO self-reporting questionnaire-20 (SRQ-20) item in primary health care settings in Eritrea. Int J Ment Health Syst, 2018: 12, 61. https://doi.org/10.1186/s13033-018-0242-y Humeniuk, Rachel, Henry-Edwards, S, Ali, Robert, et al. The Alcohol, Smoking and Substance involvement Screening Test (‎‎‎ASSIST)‎‎‎: manual for use in primary care / prepared by R. HumeniukƯ [‎‎‎et al]‎‎‎. World Health Organization. 2010. https://apps.who.int/iris/handle/10665/44320 Cohen, S., Kamarck, T., and Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 386–396. Carver, C. S. You want to measure coping but your protocol’s too long: Consider the brief. Int. J. Behav. Med., 1997; 4(1), 92–100. Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. The Multidimensional Scale of Perceived Social Support. J Pers Assess, 1988; 52(1), 30–41. https://doi.org/10.1207/s15327752jpa5201_2 Mukherjee J. India Faced a Mental Health Crisis in 2020 Due to Covid-19 Pandemic. What Can Change in 2021?. https://www.news18.com/news/buzz/india-faced-a-mental-health-crisis-in-2020-due-to-covid-19-pandemic-what-can-change-in-2021-3228707.html . Accessed date: 14 April 2021 Brooks S. K., Webster R. K., Smith L. E., Woodland L., Wessely S., Greenberg N., et al. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395 (10227), 912 10.2139/ssrn.3532534 Shaygan M, Yazdani Z, Valibeygi A. The effect of online multimedia psychoeducational interventions on the resilience and perceived stress of hospitalized patients with COVID-19: a pilot cluster randomized parallel-controlled trial, BMC psychiatry, 2021, 21(1), 93. https://doi.org/10.1186/s12888-021-03085-6 Kong X, Kong F, Zheng K, Tang M, Chen Y, Zhou J, Li Y, Diao L, Wu S, Jiao P, Su T, Dong Y. Effect of Psychological-Behavioral Intervention on the Depression and Anxiety of COVID-19 Patients. Front Psychiatry. 2020 Nov 20;11:586355. doi: 10.3389/fpsyt.2020.586355 . PMID: 33329130 Gharaati Sotoudeh H, Alavi SS, Akbari Z, Jannatifard F, Artounian V. The Effect of Brief Crisis Intervention Package on Improving Quality of Life and Mental Health in Patients with COVID-19. Iran J Psychiatry. 2020;15(3):205–212. doi: 10.18502/ijps.v15i3.3812 Giordano F, Scarlata E, Baroni M, et al. Receptive music therapy to reduce stress and improve wellbeing in Italian clinical staff involved in COVID-19 pandemic: A preliminary study. Arts Psychother. 2020;70:101688. doi: 10.1016/j.aip.2020.101688 Liu K, Chen Y, Wu D, Lin R, Wang Z, Pan L. Effects of progressive muscle relaxation on anxiety and sleep quality in patients with COVID-19. Complement Ther Clin Pract. 2020 May;39:101132. doi: 10.1016/j.ctcp.2020.101132 . Zhou L, Xie R, Yang X, et al. Feasibility and Preliminary Results of Effectiveness of Social Media-based Intervention on the Psychological Well-being of Suspected COVID-19 Cases during Quarantine. The Canadian Journal of Psychiatry. 2020;65(10):736–738. doi: 10.1177/0706743720932041 Wei, N., Huang, Bc., Lu, Sj. et al. Efficacy of internet-based integrated intervention on depression and anxiety symptoms in patients with COVID-19. J. Zhejiang Univ. Sci. B 21, 400–404 (2020). https://doi.org/10.1631/jzus.B2010013 Dehingia N, Raj A. Sex differences in COVID-19 case fatality: do we know enough? Lancet Glob Health. 2021 Jan;9(1):e14-e15. doi: 10.1016/S2214-109X(20)30464-2. Epub 2020 Nov 5. PMID: 33160453Liu L, Xue P, Li SX, Zhang J, Zhou J, Zhang W. Urban-rural disparities in mental health problems related to COVID-19 in China. Gen Hosp Psychiatry. 2021;69:119-120. doi: 10.1016/j.genhosppsych.2020.07.011 Özdin S, Bayrak Özdin Ş. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: The importance of gender. Int J Soc Psychiatry. 2020;66(5):504–511. doi: 10.1177/0020764020927051 UN Habitat. COVID-19 Response Plans. https://unhabitat.org/sites/default/files/ 2020/04/final_un-habitat_covid-19_response_plan.pdf . Accessed date: 14 April 2021 Varshney M, Parel JT, Raizada N, Sarin SK (2020) Initial psychological impact of COVID-19 and its correlates in Indian Community: An online (FEEL-COVID) survey. PLoS ONE 15(5): e0233874. doi: 10.1371/journal.pone.0233874 Picchianti Diamanti A, Cattaruzza MS, Di Rosa R, Del Porto F, Salemi S, Sorgi ML, Martin Martin LS, Rai A, Iacono D, Sesti G, Alessandri G, Laganà B. Psychological Distress in Patients with Autoimmune Arthritis during the COVID-19 Induced Lockdown in Italy. Microorganisms. 2020 Nov 18;8(11):1818. doi: 10.3390/microorganisms8111818 . Roy, A., Singh, AK., Mishra, S., Chinnadurai, A., Mitra, A., Bakshi, O. Mental health implications of COVID-19 pandemic and its response in India. 2020. Int J Soc Psychiatry. (Online First). https://doi.org/10.1177/0020764020950769 Xiao, S., Luo, D. & Xiao, Y. Survivors of COVID-19 are at high risk of posttraumatic stress disorder. glob health res policy. 2020: 5, 29. https://doi.org/10.1186/s41256-020-00155-2 Chen, Y., Huang, X., Zhang, C. et al. Prevalence and predictors of posttraumatic stress disorder, depression and anxiety among hospitalized patients with coronavirus disease 2019 in China. 2021; BMC Psychiatry 21, 80. https://doi.org/10.1186/s12888-021-03076-7 Shigemura J, Tanigawa T, Saito I, Nomura S. Psychological distress in workers at the Fukushima nuclear power plants. JAMA 2012; 308: 667–669. Dehingia N, Raj A. Sex differences in COVID-19 case fatality: do we know enough? Lancet Glob Health. 2021 Jan;9(1):e14-e15. doi: 10.1016/S2214-109X(20)30464-2. Epub 2020 Nov 5. PMID: 33160453Liu L, Xue P, Li SX, Zhang J, Zhou J, Zhang W. Urban-rural disparities in mental health problems related to COVID-19 in China. Gen Hosp Psychiatry. 2021;69:119-120. doi: 10.1016/j.genhosppsych.2020.07.011 Cenat JM, Derivois D. Assessment of prevalence and determinants of posttraumatic stress disorder and depression symptoms in adults survivors of earthquake in Haiti after 30 months. J Affect Disord. 2014 Apr;159:111–7. doi: 10.1016/j.jad.2014.02.025 . Pillai RR, Sekar, K. Training and Handholding Support for Community Level Workers in Disaster Psychosocial Care Programme, SAJOSPS. 2015; Vol. 15(2). Fontana A, Rosenheck R. Posttraumatic stress disorder among Vietnam Theater Veterans. A causal model of etiology in a community sample. J Nerv Ment Dis. 1994 Dec;182(12) 677–684. Lee AM, Wong JG, McAlonan GM, Cheung V, Cheung C, Sham PC, Chu CM, Wong PC, Tsang KW, Chua SE. Stress and psychological distress among SARS survivors 1 year after the outbreak. Can J Psychiatry. 2007 Apr;52(4):233–40. doi: 10.1177/070674370705200405 . Upadhyay R. At Rs 2.37L, city’s per capita income 4th highest. https://www.tribuneindia.com/news/archive/chandigarh/at-rs-2-37l-city-s-per-capita-income-4th-highest-664944 . Accessed date: 14 April 2021. Tables Table 1: Demographic and clinical profile of patients Variables Total patients (N=250) [Mean (SD)(Range)/ Frequency (%) Non-Case (N=201) [Mean (±SD) (Range)/ Frequency (%) Case (N=49) [Mean (±SD) (Range)/ Frequency (%) t-test/ chi-square test (p value) Age (Years) 47.92 (13.96) [18-41] 38.59±15.54 42.08±16.47 t=-1.39 (0.16) Educational Qualification 14.71 (1.58) [10-17] 14.66±1.5 7 14.92±1.61 t=-1.04 (0.30) Sex Female 130 (52%) 106 (52.7%) 14 (28.6%) χ2=9.22 (0.01) ** Male 120 (48%) 95 (47.3%) 35 (71.4%) Educational Qualification High School to Graduation 203 (81.2%) 166 (82.6%) 37 (75.5.2%) χ2=1.29 (0.25) Above Graduation 47 (18.8%) 35 (17.4%) 12 (24.5%) Marital status Married 203 (81.2%) 161 (80.1%) 42 (85.7%) χ2 =0.81 (0.36) Single 47 (18.8%) 40 (19.9%) 7 (14.3%) Occupation In a remunerative employment 134 (53.6%) 108 (53.7%) 26 (53.1%) χ2=0.007 (0.93) Not in a remunerative employment 116 (46.4%) 93 (46.3%) 23 (46.3%) Religion Hindu 213 (85.2%) 175 (87.1%) 38 (77.6%) χ2 = 2.82 (0.09) Others 37 (14.8%) 26 (12.9%) 11 (22.4%) Socio-economic Status Lower 21 (8.4%) 17 (8.5%) 4 (8.2%) χ2 = 3.89 (0.14) Middle 210 (84.0%) 172 (85.6%) 38 (77.6%) Upper 19 (7.6%) 12 (6.0%) 7 (14.3%) Family Type Nuclear 194 (77.6%) 158 (78.6%) 36 (73.5%) χ2 =0.59 (0.44) Joint 56 (22.4%) 43 (21.4%) 13 (26.5%) Domicile Rural 45 (18%) 29 (14.4%) 16 (32.7%) χ2=8.86 (0.01) ** Urban 205 (82%) 172 (85.6%) 33 (67.3%) Severity of Covid 19 Mild 212 (84.8%) 28 (13.9%) 10 (20.4%) χ2 = 1.28 (0.26) Moderate 38 (15.2%) 17.3 (86.1%) 39 (79.6%) Co-morbid / underlying medical conditions Yes 30 (12%) 16 (8.0%) 14 (28.6%) χ2=15.85 (0.001)*** No 220 (88%) 185 (92.0%) 35 (71.4%) Prevalence of substance use Tobacco 1.14 (±5.14) 0.92 (±4.51) 2.04 (±7.16) t=-1.05 (0.29) Alcohol 1.96 (± 6.69) 1.96 (±6.62) 2.00 (±7.01) t=-0.04 (0.96) Cannabis 0.10 (±1.07) 0.05 (±0.77) 0.27 (±1.85) t=-0.77 (0.44) Table 2 : Comparison of the Trauma, Stress, Coping and Social Support Variables Non-Case (N=201) [Mean (±SD) (Range)/ Frequency(%) Case (N=49) [Mean (±SD) (Range)/ Frequency(%) t-test/ chi-square test (p value) PTSD symptoms 0.79 (± 1.37) 4.27 (± 2.37) t=-9.88 (0.001) *** Perceived Stress 4.80 (±6.49) 16.22 (±7.94) t=-9.34 (0.001) *** Coping Strategies Self-Distraction 4.95 (±0.75) 4.73 (±0.90) t=1.502 (0.13) Active Coping 5.51 (±0.87) 5.06 (±1.06) t=3.10 (0.01) ** Denial 5.07 (±1.08) 4.88 (±1.31) t=0.97 (0.33) Substance Use 2.33 (±0.97) 2.29 (±1.00) t=0.27 (0.79) Emotional Support 5.21 (±0.87) 4.86 (±0.79) t=2.57 (0.01) ** Instrumental Support 5.48 (±1.08) 5.18 (±0.99) t=1.72 (0.08) Behavioural Disengagement 5.18 (± 0.92) 4.55 (±1.15) t=3.56 (0.001) *** Venting 5.42 (±0.96) 4.80 (±1.24) t=3.30 (0.01) ** Positive Reframing 5.12 (±1.01) 4.86 (±1.24) t=1.58 (0.11) Planning 5.35 (±1.13) 5.27 (±1.51) t=0.38 (0.70) Humour 2.45 (±1.06) 2.57 (1.13) t=-0.69 (0.49) Acceptance 5.75 (±1.24) 5.29 (±1.50) t=2.23 (0.02) * Religion 5.43 (±1.41) 6.06 (±1.46) t=-2.76 (0.01) ** Self-Blame 5.65 (±1.00) 4.82 (±1.39) t=3.95 (0.001) *** Social Support Total Score 68.53 (±7.24) 68.80 (±5.58) t=-0.24 (0.81) Family Subscale 20.05 (±2.35) 20.29 (±1.72) t=-0.66 (0.50) Friend Subscale 20.15 (±2.27) 19.69 (±3.50) t=0.88 (0.38) Others Subscale 20.10 (±2.21) 20.46 (±2.05) t=-1.04 (0.30) Table 3 : Predictors of the psychological distress among Covid 19 patients Predictors β S.E.β Wald’s χ2 df ‘p' Value Eβ (Odds Ratio) 95% CI for β Constant 2.191 2.436 .809 1 .368 8.941 Sex (1) -.801 .524 2.337 1 .126 .449 .161 - 1.254 Domicile (1) -.160 .691 .054 1 .817 .852 .220 - 3.301 Comorbid Status (1) -.290 .699 .172 1 .678 .748 .190 - 2.945 Trauma .720 .164 19.210 1 .000 2.055 1.489 - 2.836 Perceived Stress .053 .037 2.014 1 .156 1.054 .980 - 1.134 Active Coping .188 .292 .417 1 .519 1.207 .682 - 2.138 Emotional Support -.560 .297 3.544 1 .060 .571 .319 - 1.023 Beh_Dis -.320 .311 1.054 1 .305 .726 .394 - 1.337 Venting -.151 .270 .315 1 .575 .859 .506 - 1.459 Acceptance -.180 .253 .506 1 .477 .835 .509 - 1.371 Religion .307 .201 2.347 1 .125 1.360 .918 - 2.015 Self-blame -.305 .259 1.393 1 .238 .737 .444 - 1.224 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-1038192","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":60401436,"identity":"ee75d797-ece0-4c9f-8d1a-3393cbacc038","order_by":0,"name":"Renjith R. Pillai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYJACgwSGA0CK+QADYwPRWhJAWtgSiNfCwADWwmNAnBbz9t4DBQ9/3MmTn5HzTeLnDhs5BvbDRzfg0yJz5lwC0GHPig1u5G6T7D2TZszAk5Z2A58WCYkcA6CWw4kbpHO3SfC2HU5skOAxw69F/g1Ey/zZOc8k/xKlRYIHoqXhdg6bNHG28IAclna42OD+M2Nr2bY0YzaCfmE/Y2b4w+ZwnnzP4Yc337bZyPGzHz6GVwsQsBkAiQQgZpEAcwkoBwHmB1AtzB+IUD0KRsEoGAUjEAAALylOPlbDlloAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7102-7986","institution":"PGIMER, Chandigarh","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Renjith","middleName":"R.","lastName":"Pillai","suffix":""},{"id":60401437,"identity":"e7c24667-75b6-43f2-8f44-f0e358e2353a","order_by":1,"name":"Abhishek Ghosh","email":"","orcid":"","institution":"PGIMER, Chandigarh","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Ghosh","suffix":""},{"id":60401438,"identity":"1b422a15-932b-4195-885c-d7aaddcde1e2","order_by":2,"name":"Sumit Shrivasthava","email":"","orcid":"","institution":"SDAV College, Chandigarh","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sumit","middleName":"","lastName":"Shrivasthava","suffix":""},{"id":60401439,"identity":"613bf51c-dcaf-4779-91fb-030c2fa164a4","order_by":3,"name":"Sanuj Muralidharan","email":"","orcid":"","institution":"SDAV College, Chandigarh","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sanuj","middleName":"","lastName":"Muralidharan","suffix":""},{"id":60401440,"identity":"0f30308e-19a6-4960-95db-c1679b2ea180","order_by":4,"name":"Krishan Kumar","email":"","orcid":"","institution":"PGIMER, Chandigarh","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Krishan","middleName":"","lastName":"Kumar","suffix":""},{"id":60401441,"identity":"a2e6f5ed-56e7-4946-9119-6b213438204a","order_by":5,"name":"Saranya S Kumar","email":"","orcid":"","institution":"SDAV College, Chandigarh","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Saranya","middleName":"S","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2021-11-01 05:43:17","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-1038192/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1038192/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":15108022,"identity":"0c18c031-1a9e-41ad-9883-a758d446e5f8","added_by":"auto","created_at":"2021-11-01 18:41:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":530862,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1038192/v1/e056c074-3ff1-458b-a32b-b003cb323901.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003ePsychological Distress and Its Predictors Among Hospital Admitted COVID-19 Patients\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe World Health Organization declared the Coronavirus Disease-19 as pandemic in the March 2020. Starting from China in 2019, World hasn\u0026rsquo;t yet recovered from this deadly corona virus pandemic with many countries now facing a second wave after a dip in the infections for a while.\u003c/p\u003e \u003cp\u003eThe first case of COVID-19 in India was reported in the state of Kerala on 30 January 2020. As on 14th April, 2021, 262 million cumulative total samples were tested among which 13.9 million turned out to be positive cases (1). Total patients recovered from COVID-19 so far were 12.4 million and 1.47 active cases are available at present in the country. Total deaths reported due to COVID-19 are 0.17 million (2). World Health Organization (3) reports that most people infected with the COVID-19 virus experience mild to moderate respiratory illness and recover without requiring special treatment. However, confirmed or suspected cases of COVID-19 do suffer from serious health-related problems apart from mental health issues when there is underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer (4,5).\u003c/p\u003e \u003cp\u003eMajority of the available studies on the mental health consequences of COVID 19 are done on the general population, with a few focusing on health care workers and vulnerable groups like children and geriatric population. World Health Organization (6) in its report on mental health pronounces that patients with COVID-19 are prone to wide range of mental disorders such as anxiety and depression. Loneliness, boredom, denial, harmful substance use, PTSD, anxiety and depression were reported by suspected and/or confirmed COVID-19 quarantined persons (7, 8, 9, 10).\u003c/p\u003e \u003cp\u003eFever, hypoxia and cough along with adverse effects of prescribed medications (e.g. corticosteroids) are shown increase anxiety and mental distress (7). Two hospital-based studies from China found the incidence of anxiety and depressive symptoms among COVID-19 patients with one study reporting 18.6% and 13.4% and the other as 34% and 28% (11,12) respectively.\u003c/p\u003e \u003cp\u003eDuring the SARS period, in a survey from Hong Kong (13) conducted at a convalescent hospital, around half (50%) of recovered SARS patients reported anxiety, and approximately 20% were fearful, including panic attacks, feelings of depression, or stigmatization. In yet another study (14) from Torondo, Canada, patients with SARS reported fear, loneliness, boredom and anger, and worries about the effects of quarantine and contagion on family members and friends. Post-SARS pandemic or post-Ebola, social and psychological issues were present among physically recovered patients even after a substantial period (15).\u003c/p\u003e \u003cp\u003eAttending to the physical, biological and medical needs of the patients should receive attention of the health professionals and policy makers. The psyche of the patients, especially those who are either home quarantined or admitted in the hospitals are seldom looked into. Common mental health problems and at times disorders found among hospital admitted patients in a pandemic situation are often neglected and on the contrary the physical needs of the patients are usually well attended. In other words, the patients are deprived of essential mental health services which are equally important along with routine medical care. To bring mental health needs to the mainstream attention, it\u0026rsquo;s important to determine the incidence of mental health problems. Such knowledge would be helpful to device evidence-driven strategies to reduce adverse psychosocial impacts and psychiatric symptoms. Thus, the current study was undertaken with the primary objective to determine the incidence and course of psychological distress, posttraumatic symptoms and substance use among subjects recently diagnosed with COVID-19. The secondary objectives were to assess the level of stress, coping and social support experienced by distressed and non-distressed patients and understand the predictors of psychological distress admitted at the hospital with COVID 19.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Setting \u0026amp; Design\u003c/h2\u003e \u003cp\u003eThe data is from a longitudinal study among admitted COVID-19 patients recruited from the Sri Dhanwantry Ayurveda College and Hospital located at Sector 46B, Chandigarh, a National Accreditation Board for Hospitals \u0026amp; Healthcare Providers (NABH) accredited Medical College and Hospital under Indian Systems of Medicine. As per the instruction of Chandigarh Union Territory Administration, this hospital has marked 50 beds for COVID -19 patients in an exclusive ward. Covid diagnosed patients, asymptomatic or with mild to moderate symptoms who do not have home isolation facility were referred from Post Graduate Institute of Medical Education and research (PGIMER), Chandigarh, Government Medical College and Hospital (GMCH), Chandigarh and Government Multi-Speciality Hospital (GMSH) to this hospital for treatment and care. Apart from the in-house BAMS (Bachelor of Ayurvedic Medicine and Surgery) doctors, a MBBS (Bachelor of Medicine, Bachelor of Surgery) Doctor or an MD (Doctor of Medicine) Resident doctor from GMCH, Sector 32, Chandigarh was made available for the basic medication management and care in accordance with Government of India guidelines. Patients stay for a maximum period of 10 days at the hospital; asymptomatic patients with stable vitals are discharged subsequently to stipulated quarantine facilities of the UT Administration. Follow-up of the patient were done physically or telephonically on the completion of four weeks. The study was done in months of August - September, 2020.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population\u003c/h2\u003e \u003cp\u003eAssuming that 20% of the subjects in the population have the factor of interest, the study required a sample size of 246 for estimating the expected proportion with 5% absolute precision and 95% confidence. A total of 250 patients were recruited for the final study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Measurements\u003c/h2\u003e \u003cp\u003eThe socio-demographic data and the clinical variables were collected with the help of a schedule prepared for the study. The psychological distress was measured using Self Reporting Questionnaire (16) - Cutoff of 5 for males and 6 for females (17) was considered as a case ); post traumatic stress using Trauma Screening questionnaire (2) - cutoff score : 5; severity of substance use using ASSIST - Alcohol, Smoking and Substance Involvement Screening Test (18); degree of stress using Perceived Stress Scale (19); coping strategies using Brief-COPE inventory (20) and perceived social support using Social Support Scale (21). Patients admitted with the confirmed diagnosis of COVID-19, either asymptomatic or have mild to moderate COVID-19, between 18-75 years from either sex, cooperative and well versed in either English, Hindi or Punjabi were included for the study. Those excluded were patients with severe COVID-19, below the age of 18 years or more than 75 years and were unwilling to participate in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Ethical aspects\u003c/h2\u003e \u003cp\u003e The Institute Ethics Committee of PGIMER, Chandigarh cleared the study (Reference No: NK/6456/Study/600). Confidentiality was assured and the informed consent was taken before data collection. To minimize the risk of infection, data was collected both in online and offline mode as per the convenience of the patients. Patients with Android mobiles completed data collection of the self-administered instruments through excel sheets. Whatsapp video calls were done by the co-investigators from study hospital to clear the doubts of the respondents as well as to collect the interview administered instruments. In the offline mode, the study instruments (hard copies) were made available to them by PPE attired on-duty staff members in the ward. Scanned copies of the completed instruments were whatsapped back to the investigators and the original questionnaire was kept in the safe custody with lock and keys within the ward accessible only to the investigators or staff members with permission.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe baseline data collected was analysed using IBM SPSS Statistics Version 26. Descriptive statistics were adopted for socio-demographic and clinical variables. Categorical variables were presented in frequency and percentages. Association of psychological distress with independent variables were determined by \u0026lsquo;t\u0026rsquo; test or chi square test. To determine the predictors of the psychological distress, binary logistic regression was carried out with the variables significant in the univariate analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic and clinical profile of the patients\u003c/h2\u003e \u003cp\u003eThe total participants who completed the baseline assessments were 250. Among them, 201 (80.4%) participants were found to be non-cases and 49 (19.6%) participants were probable cases (persons experiencing psychological distress). The mean age of the participants was 47.92 (\u0026plusmn;13.96) years. The mean years of education of the participants were 14.71 (\u0026plusmn;1.58) years. Males constituted 52% of the participants and the differences in the proportion of males versus females falling in the non-case and case categories were significant (χ2=9.22, p\u0026lt;0.01). Educational qualification of the majority of the participants (81.2%) ranged between high school and graduation. Married participants were 81.2% and a little more than half of the participants (53.6%) were in some form of remunerative job. Hindu religion (85.2%), middle socio-economic status (81.9%) and nuclear family (77.6%) were the predominant categories among the participants. Majority (82%) of the participants were from urban locality and there were significant differences (χ2=8.86, p\u0026lt;0.01) in the proportion of the urban versus rural participants falling under non-case and case categories.\u003c/p\u003e \u003cp\u003eNone of the patients required oxygen therapy nor were referred to any higher treatment facilities. The COVID-19 severity was reported as mild by 84.8% participants. Co-morbidities was seen more among non-cases and there was a significant difference (χ2=15.85, p\u0026lt;0.001) in the co-morbid / underlying medical conditions between the participants belonging to non-case and case categories. The prevalence of substance was very low with the mean scores for tobacco, alcohol and cannabis was seen as 1.14 (\u0026plusmn;5.14), 1.96 (\u0026plusmn;6.69) and 0.10 (\u0026plusmn;1.07) respectively on ASSIST.\u003c/p\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;Insert table (1) here\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Trauma, stress, coping and social support\u003c/h2\u003e \u003cp\u003eThe incidence of post traumatic symptoms among the respondents was 8.8%. There was a significant difference (t=-9.88, p\u0026lt;0.001) in the mean PTSD score of the non-case participants (0.79\u0026plusmn;1.37) from those who are probable cases (4.27\u0026plusmn;2.37). Similarly, there was also a significant difference (t=-9.34, p\u0026lt;0.001) in the mean perceived stress score among non-cases (4.80\u0026plusmn;6.49) and probable cases (16.22\u0026plusmn;7.94). Among the non-cases and probable cases, significant differences were also observed in the subscales of the coping like active coping (5.51\u0026plusmn;0.87 v/s 5.06\u0026plusmn;1.06; t=3.10, p\u0026lt;0.01), emotional support (5.21\u0026plusmn;0.87 v/s 4.86\u0026plusmn;0.79; t=2.57, p\u0026lt;0.01), behavioural disengagement (5.18\u0026plusmn;0.92 v/s 4.55\u0026plusmn;1.15; t=3.56, p\u0026lt;0.001), venting (5.42\u0026plusmn;0.96 v/s 4.80\u0026plusmn;1.24; t=3.30, p\u0026lt;0.01), acceptance (5.75\u0026plusmn;1.24 v/s 5.29\u0026plusmn;1.50; t=2.23, p\u0026lt;0.05), religion (5.43\u0026plusmn;1.41 v/s 6.06\u0026plusmn;1.46; t=-2.76, p\u0026lt;0.01) and self-blame (5.65\u0026plusmn;1.00 v/s 4.82\u0026plusmn;1.39; t=3.95, p\u0026lt;0.001). The social support perceived by the patients from family (t=-0.66, p\u0026gt;0.05), friends (t=0.88, p\u0026gt;0.05) and significant others (t=-1.04, p\u0026gt;0.05) were similar in nature in both \u0026ldquo;non-case\u0026rdquo; and \u0026ldquo;case\u0026rdquo; categories.\u003c/p\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;Insert table (2) here\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Psychological distress and its correlates\u003c/h2\u003e \u003cp\u003eThe socio-demographic and clinical variables significant in the univariate analysis were entered in the logistic regression model to find-out the independent predictors of psychological distress. Only PTSD was found to have more than two times higher odds of causing psychological distress among the participants (p\u0026lt;.0001; OR: 2.058; 95% CI: 1.49-2.84).The variance (Nagelkerke R\u003csup\u003e2\u003c/sup\u003e) explained by this model was 62.4%.\u003c/p\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;Insert table (3) here\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn India, COVID-19 has adversely impacted the economy, jobs, and health infrastructure (22). After a dip in the number of cases, there is again a surge in COIVD-19 cases; mental health of the patients is a concern. Using standardized instruments, this cross-sectional study is perhaps the first study from India done among the hospitalized COVID-19 patients to assess the psychological distress experienced by them.\u003c/p\u003e \u003cp\u003eAround 20% of hospitalized patients with COVID-19 reported psychological distress. Psychological distress among hospitalized patients is reported by researchers (23, 24) and apart from PTSD, excessive pre-occupation about pandemic and confinement to a closed space without any opportunity to move out and interact with familiar people could be contributing to the same. Psychosocial interventions are recommended by experts to such distressed patients admitted in the hospitals. Information and accessibility to tele-interventions through dedicated psychosocial and mental health helplines or those run by mental health professional bodies or availability of mental health professionals within the hospital for undertaking tele-video mental health interventions is important. Evidences of some interventions which could be applied with hospital admitted patients include psychological\u0026ndash;behavioral intervention (PBI) program comprising psychological support and breathing exercises (25); brief crisis intervention (26); music therapy (27); progressive muscle relaxation training (28); Yoga \u0026ndash; meditation and mindfulness (33); mobile phone-based individual counseling (29); internet-based self-help intervention (30) and multimedia psycho educational intervention (24).\u003c/p\u003e \u003cp\u003eMales (71.4%) were found to be having more psychological distress than females. This could be due to their bread winner status in the family and their concerns for the other family members as COVID-19 has resulted in more death among males than females across the World, though in India the scenario was opposite (31). Caseness (Psychological distress) was significantly more among urban population (67.3%). Similar finding was reported in a post COVID-19 research from Turkey where they have found urban residents experiencing depression and anxiety more than those from rural areas (32). Strict quarantine within the limited spaces / houses, stress resulting from the difficulty to maintain social distancing due to population density and a general high prevalence of covid cases in the cities (33) are cited as few probable reasons. Contrary to the known findings (34, 35), in the present study patients without any co-morbid conditions were having significantly more distress than those with co-morbid conditions. Hospitalization, attention and care, food and safety measures, regular monitoring of the vitals by the health professionals and psychosocial counseling support made available from the day of admission to such vulnerable patients could be the possible reasons.\u003c/p\u003e \u003cp\u003eMean trauma and perceived stress scores of patients under \u0026lsquo;case\u0026rsquo; category was significantly more than those belonging to \u0026lsquo;non- case\u0026rsquo; category. Trauma, stress and psychological distress go hand in hand and this had been reported in various studies across the globe (36, 37, 38). The probable reasons for high trauma and perceived stress leading to high psychological distress could be infective nature of illness, reports of deaths and other medical complications arising or triggered due to covid, lack of proven drugs or specific treatment (4), fear of isolation by the community members due to stigma and misinformation, overloading of information at times conflicting and fake ones in social media, impact of negative news report (38), worries about the non affected family members, livelihood issues and financial worries.\u003c/p\u003e \u003cp\u003eLooking at the coping strategies, it was seen that in spite of resorting to dysfunctional coping strategies such as behavioural disengagement, venting and self-blame, patients in the non-case category were showing significant \u0026ldquo;acceptance\u0026rdquo; to the situation. It\u0026rsquo;s culturally not uncommon among people to resort to self-blame, venting and behavioural disengagement to cope with difficult situations in India and that perhaps would have reduced the psychological distress. The lesser distress level among patients in \u0026lsquo;non-case\u0026rsquo; category also could be due to their better perceived emotional support and active coping strategy. Patients in \u0026lsquo;case\u0026rsquo; category were reposing their faith in God (religion) significantly more than those under \u0026lsquo;non-case\u0026rsquo; category which is again well within the religious - spiritual cultural background of the country where people resort to god for resolution of their physical and psychological problems. Both the category of patients was receiving fairly equal support from family, friends and significant others.\u003c/p\u003e \u003cp\u003ePTSD (trauma) was the only variable found to be a significant predictor of the psychological distress. PTSD is widely reported in literature in the aftermath of various types of disasters such as nuclear accidents, floods, earthquake, tsunami, war and pandemic outbreaks such as SARS (39-44). Earlier studies also have found a similar relationship between PTSD and Psychological Distress (39, 7).\u003c/p\u003e \u003cp\u003eOur study had the following limitations: (a) we have included only hospitalized patients and patients with moderate COVID-19; therefore, our study results may not be generalizable to the other groups of patients; (b) this study was from a single center and from an Union Territory of India; the city stands at first position in human development index in the country and has a relatively better health infrastructure (GMSH, GHCH and PGIMER) and per-capita income (4th position in the country) than many other states and union territories of the country (45); therefore, the results of our study may not be extrapolated to other states; (c) we did not use any diagnostic instruments, and therefore could not comment on the incidence of a particular psychiatric diagnosis; (d) this cross-sectional study could not inform us about the course of severe psychological distress.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe current study showed that around 20% hospitalized patients with COVID-19 had mild to moderate category was experiencing psychological distress. The presence of post-traumatic stress symptoms was a predictor of psychological distress. Though there were variations in the coping strategies adopted by the patients, \u0026ldquo;acceptance\u0026rdquo; was associated with less psychological distress. Our study showed that screening and treatment for psychological distress should be made an integral part of care for patients with COVID-19. Use of digital technology appears to be one of the most viable options as it minimizes the chances of infection to the service provider. COVID-19 is going to stay long and hence, it is important for all the in-patient treatment centers to ensure the services of mental health professionals are available within the setting.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRenjith R. Pillai MSW, M.Phil PSW, PhD: Conceptualization; methodology, data curation, writing \u0026ndash; original draft preparation, writing \u0026ndash; review \u0026amp; editing. \u0026nbsp;Abhishek Ghosh\u0026nbsp;MD, DM: Conceptualization; methodology, data curation, Formal analysis, Software, writing \u0026ndash; original draft preparation, writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;Sumit\u0026nbsp;Shrivasthava\u0026nbsp;MD (Ay.), PhD: Investigation; Project administration; Resources; Supervision; Writing - review \u0026amp; editing.\u0026nbsp;Sanuj Muralidharan\u0026nbsp;MD (Ay.): Investigation; Resources; Writing - review \u0026amp; editing.\u0026nbsp;Krishan Kumar MA, M.Phil CP, Ph.D: Conceptualization;\u0026nbsp;Writing \u0026ndash; original draft preparation, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;Saranya S Kumar\u0026nbsp;MD (Ay.): Investigation; Resources; Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone of the authors have received any monetary support from any agencies for the execution of this research work\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available to interested individuals upon formal request to authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransparency Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone of the authors have relevant disclosures.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the patients and their caregivers for their time and consent to participate in this study. We acknowledge the motivation, dedication and commitment of the on-duty professional staff and healthcare workers as well as trainee students at SDAC and Hospital, Chandigarh for continued service to those affected by COVID-19 pandemic.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIndian Council of Medical Research. COVID-19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://icmr.gov.in/index.html\u003c/span\u003e\u003c/span\u003e; 2021, Accessed date: 14 April 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health and Family Welfare. For information on CoVID-19 Vaccine. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mohfw.gov.in/\u003c/span\u003e\u003c/span\u003e; 2021, Accessed date: 14 April 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Corona Virus. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/healthtopics/coronavirus\u003c/span\u003e\u003c/span\u003e #tab=tab_1 Accessed date: 14 April 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanyaolu A, Okorie C, Marinkovic A, et al. Comorbidity and its Impact on Patients with COVID-19 [published online ahead of print, 2020 Jun 25]. SN Compr Clin Med. 2020;1\u0026ndash;8. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s42399-020-00363-4\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNg WH, Tipih T, Makoah NA, et al. Comorbidities in SARS-CoV-2 Patients: a Systematic Review and Meta-Analysis. mBio. 2021;12(1):e03647-20. Published 2021 Feb 9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/mBio.03647-20\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. The impact of COVID-19 on mental, neurological and substance use services: results of a rapid assessment. Geneva; 2020. Licence: CC BY-NC-SA 3.0 IGO.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang W, Wu X, Lan X. Rumination mediates the relationships of fear and guilt to posttraumatic stress disorder and posttraumatic growth among adolescents after the Ya'an earthquake. Eur J Psychotraumatol. 2020;11(1):1704993.. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/20008198.2019\u003c/span\u003e\u003c/span\u003e. 1704993\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong L, Bouey J. Public Mental Health Crisis during COVID-19 Pandemic, China. Emerg Infect Dis. 2020;26(7):1616\u0026ndash;1618. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3201/eid2607.200407\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi S, Wang Y, Xue J, Zhao N, Zhu T. The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users. Int J Environ Res Public Health. 2020;17(6):2032. Published 2020 Mar 19. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph17062032\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanafi E, Siste K, Limawan AP, et al. Alcohol- and Cigarette-Use Related Behaviors During Quarantine and Physical Distancing Amid COVID-19 in Indonesia. Front Psychiatry. 2021;12:622917. Published 2021 Feb 2. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2021.622917\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai L-L, Wang X, Jiang T-C, Li P-F, Wang Y, Wu S-J, et al. (2020) Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. PLoS ONE 15(8): e0238416. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone. 0238416\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong X., Zheng K., Tang M. Prevalence and factors associated with depression and anxiety of hospitalized patients with COVID-19. medRxiv. 2020 doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/2020.03.24.20043075\u003c/span\u003e\u003c/span\u003e. (preprint)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsang HW, Scudds RJ, Chan EY. Psychosocial impact of SARS. Emerg Infect Dis. 2004 Jul;10(7):1326\u0026ndash;7. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3201/eid1007.040090\u003c/span\u003e\u003c/span\u003e. PMID: 15338536; PMCID: PMC3323309.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaunder R, Hunter J, Vincent L, et al. The immediate psychological and occupational impact of the 2003 SARS outbreak in a teaching hospital. CMAJ. 2003;168(10):1245\u0026ndash;1251.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKar SK, Yasir Arafat SM, Kabir R, Sharma P, Saxena SK. Coping with Mental Health Challenges During COVID-19. Coronavirus Disease 2019 (COVID-19). 2020;199-213. Published 2020 Apr 30. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-981-15-4814-7_16\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. A user\u0026rsquo;s guide to the Self-Reporting Questionnaire. WHO/MNH/PSSF 94.8. WHO, Geneva. 1994\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNetsereab, T.B., Kifle, M.M., Tesfagiorgis, R.B. et al. Validation of the WHO self-reporting questionnaire-20 (SRQ-20) item in primary health care settings in Eritrea. Int J Ment Health Syst, 2018: 12, 61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13033-018-0242-y\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHumeniuk, Rachel, Henry-Edwards, S, Ali, Robert, et al. The Alcohol, Smoking and Substance involvement Screening Test (\u0026lrm;\u0026lrm;\u0026lrm;ASSIST)\u0026lrm;\u0026lrm;\u0026lrm;: manual for use in primary care / prepared by R. HumeniukƯ [\u0026lrm;\u0026lrm;\u0026lrm;et al]\u0026lrm;\u0026lrm;\u0026lrm;. World Health Organization. 2010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/iris/handle/10665/44320\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen, S., Kamarck, T., and Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 386\u0026ndash;396.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarver, C. S. You want to measure coping but your protocol\u0026rsquo;s too long: Consider the brief. Int. J. Behav. Med., 1997; 4(1), 92\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimet, G. D., Dahlem, N. W., Zimet, S. G., \u0026amp; Farley, G. K. The Multidimensional Scale of Perceived Social Support. J Pers Assess, 1988; 52(1), 30\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1207/s15327752jpa5201_2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMukherjee J. India Faced a Mental Health Crisis in 2020 Due to Covid-19 Pandemic. What Can Change in 2021?. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.news18.com/news/buzz/india-faced-a-mental-health-crisis-in-2020-due-to-covid-19-pandemic-what-can-change-in-2021-3228707.html\u003c/span\u003e\u003c/span\u003e. Accessed date: 14 April 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks S. K., Webster R. K., Smith L. E., Woodland L., Wessely S., Greenberg N., et al. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395 (10227), 912 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2139/ssrn.3532534\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaygan M, Yazdani Z, Valibeygi A. The effect of online multimedia psychoeducational interventions on the resilience and perceived stress of hospitalized patients with COVID-19: a pilot cluster randomized parallel-controlled trial, BMC psychiatry, 2021, 21(1), 93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-021-03085-6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong X, Kong F, Zheng K, Tang M, Chen Y, Zhou J, Li Y, Diao L, Wu S, Jiao P, Su T, Dong Y. Effect of Psychological-Behavioral Intervention on the Depression and Anxiety of COVID-19 Patients. Front Psychiatry. 2020 Nov 20;11:586355. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2020.586355\u003c/span\u003e\u003c/span\u003e. PMID: 33329130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGharaati Sotoudeh H, Alavi SS, Akbari Z, Jannatifard F, Artounian V. The Effect of Brief Crisis Intervention Package on Improving Quality of Life and Mental Health in Patients with COVID-19. Iran J Psychiatry. 2020;15(3):205\u0026ndash;212. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18502/ijps.v15i3.3812\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiordano F, Scarlata E, Baroni M, et al. Receptive music therapy to reduce stress and improve wellbeing in Italian clinical staff involved in COVID-19 pandemic: A preliminary study. Arts Psychother. 2020;70:101688. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.aip.2020.101688\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu K, Chen Y, Wu D, Lin R, Wang Z, Pan L. Effects of progressive muscle relaxation on anxiety and sleep quality in patients with COVID-19. Complement Ther Clin Pract. 2020 May;39:101132. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ctcp.2020.101132\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou L, Xie R, Yang X, et al. Feasibility and Preliminary Results of Effectiveness of Social Media-based Intervention on the Psychological Well-being of Suspected COVID-19 Cases during Quarantine. The Canadian Journal of Psychiatry. 2020;65(10):736\u0026ndash;738. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0706743720932041\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei, N., Huang, Bc., Lu, Sj. et al. Efficacy of internet-based integrated intervention on depression and anxiety symptoms in patients with COVID-19. J. Zhejiang Univ. Sci. B 21, 400\u0026ndash;404 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1631/jzus.B2010013\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehingia N, Raj A. Sex differences in COVID-19 case fatality: do we know enough? Lancet Glob Health. 2021 Jan;9(1):e14-e15. doi: 10.1016/S2214-109X(20)30464-2. Epub 2020 Nov 5. PMID: 33160453Liu L, Xue P, Li SX, Zhang J, Zhou J, Zhang W. Urban-rural disparities in mental health problems related to COVID-19 in China. Gen Hosp Psychiatry. 2021;69:119-120. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.genhosppsych.2020.07.011\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zdin S, Bayrak \u0026Ouml;zdin Ş. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: The importance of gender. Int J Soc Psychiatry. 2020;66(5):504\u0026ndash;511. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0020764020927051\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUN Habitat. COVID-19 Response Plans. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unhabitat.org/sites/default/files/ 2020/04/final_un-habitat_covid-19_response_plan.pdf\u003c/span\u003e\u003c/span\u003e. Accessed date: 14 April 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarshney M, Parel JT, Raizada N, Sarin SK (2020) Initial psychological impact of COVID-19 and its correlates in Indian Community: An online (FEEL-COVID) survey. PLoS ONE 15(5): e0233874. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0233874\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePicchianti Diamanti A, Cattaruzza MS, Di Rosa R, Del Porto F, Salemi S, Sorgi ML, Martin Martin LS, Rai A, Iacono D, Sesti G, Alessandri G, Lagan\u0026agrave; B. Psychological Distress in Patients with Autoimmune Arthritis during the COVID-19 Induced Lockdown in Italy. Microorganisms. 2020 Nov 18;8(11):1818. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/microorganisms8111818\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoy, A., Singh, AK., Mishra, S., Chinnadurai, A., Mitra, A., Bakshi, O. Mental health implications of COVID-19 pandemic and its response in India. 2020. Int J Soc Psychiatry. (Online First). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0020764020950769\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao, S., Luo, D. \u0026amp; Xiao, Y. Survivors of COVID-19 are at high risk of posttraumatic stress disorder. glob health res policy. 2020: 5, 29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s41256-020-00155-2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, Y., Huang, X., Zhang, C. et al. Prevalence and predictors of posttraumatic stress disorder, depression and anxiety among hospitalized patients with coronavirus disease 2019 in China. 2021; BMC Psychiatry 21, 80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-021-03076-7\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShigemura J, Tanigawa T, Saito I, Nomura S. Psychological distress in workers at the Fukushima nuclear power plants. JAMA 2012; 308: 667\u0026ndash;669.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehingia N, Raj A. Sex differences in COVID-19 case fatality: do we know enough? Lancet Glob Health. 2021 Jan;9(1):e14-e15. doi: 10.1016/S2214-109X(20)30464-2. Epub 2020 Nov 5. PMID: 33160453Liu L, Xue P, Li SX, Zhang J, Zhou J, Zhang W. Urban-rural disparities in mental health problems related to COVID-19 in China. Gen Hosp Psychiatry. 2021;69:119-120. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.genhosppsych.2020.07.011\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenat JM, Derivois D. Assessment of prevalence and determinants of posttraumatic stress disorder and depression symptoms in adults survivors of earthquake in Haiti after 30 months. J Affect Disord. 2014 Apr;159:111\u0026ndash;7. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.02.025\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePillai RR, Sekar, K. Training and Handholding Support for Community Level Workers in Disaster Psychosocial Care Programme, SAJOSPS. 2015; Vol. 15(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFontana A, Rosenheck R. Posttraumatic stress disorder among Vietnam Theater Veterans. A causal model of etiology in a community sample. J Nerv Ment Dis. 1994 Dec;182(12) 677\u0026ndash;684.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee AM, Wong JG, McAlonan GM, Cheung V, Cheung C, Sham PC, Chu CM, Wong PC, Tsang KW, Chua SE. Stress and psychological distress among SARS survivors 1 year after the outbreak. Can J Psychiatry. 2007 Apr;52(4):233\u0026ndash;40. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/070674370705200405\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUpadhyay R. At Rs 2.37L, city\u0026rsquo;s per capita income 4th highest. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.tribuneindia.com/news/archive/chandigarh/at-rs-2-37l-city-s-per-capita-income-4th-highest-664944\u003c/span\u003e\u003c/span\u003e. Accessed date: 14 April 2021.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Demographic and clinical profile of patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"36.925515055467514%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal patients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=250)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Mean (SD)(Range)/\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.580031695721077%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Case\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=201)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Mean (\u0026plusmn;SD) (Range)/\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.00633914421553%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=49)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Mean (\u0026plusmn;SD) (Range)/\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u003cstrong\u003et-test/ chi-square test (p value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"36.925515055467514%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (Years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e47.92 (13.96) [18-41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e38.59\u0026plusmn;15.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e42.08\u0026plusmn;16.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.066561014263076%\"\u003e\n \u003cp\u003et=-1.39 (0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"36.925515055467514%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Qualification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e14.71 (1.58) [10-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e14.66\u0026plusmn;1.5 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e14.92\u0026plusmn;1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.066561014263076%\"\u003e\n \u003cp\u003et=-1.04 (0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e130 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e106 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e14 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2=9.22 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e120 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e95 (47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e35 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Qualification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eHigh School to Graduation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e203 (81.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e166 (82.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e37 (75.5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2=1.29 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eAbove Graduation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e47 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e35 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e12 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e203 (81.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e161 (80.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e42 (85.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2 =0.81 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e47 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e40 (19.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e7 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eIn a remunerative employment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e134 (53.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e108 (53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e26 (53.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2=0.007 (0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.62121212121212%\"\u003e\n \u003cp\u003eNot in a remunerative employment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.234848484848484%\"\u003e\n \u003cp\u003e116 (46.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.424242424242426%\"\u003e\n \u003cp\u003e93 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.12878787878788%\"\u003e\n \u003cp\u003e23 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eHindu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e213 (85.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e175 (87.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e38 (77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2 = 2.82 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e37 (14.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e26 (12.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e11 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-economic Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e21 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e17 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e4 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2\u0026nbsp;= 3.89 (0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e210 (84.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e172 (85.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e38 (77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e19 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e12 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e7 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eNuclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e194 (77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e158 (78.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e36 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2 =0.59 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.62121212121212%\"\u003e\n \u003cp\u003eJoint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.234848484848484%\"\u003e\n \u003cp\u003e56 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.424242424242426%\"\u003e\n \u003cp\u003e43 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.12878787878788%\"\u003e\n \u003cp\u003e13 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDomicile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e45 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e29 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e16 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2=8.86 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.62121212121212%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.234848484848484%\"\u003e\n \u003cp\u003e205 (82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.424242424242426%\"\u003e\n \u003cp\u003e172 (85.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.12878787878788%\"\u003e\n \u003cp\u003e33 (67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeverity of Covid 19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.602218700475436%\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e212 (84.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e28 (13.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e10 (20.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2 = 1.28 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e38 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e17.3 (86.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e39 (79.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-morbid / underlying medical conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.602218700475436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e30 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.580031695721077%\"\u003e\n \u003cp\u003e16 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00633914421553%\"\u003e\n \u003cp\u003e14 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003e\u0026chi;2=15.85 (0.001)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.40096618357488%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.980676328502415%\"\u003e\n \u003cp\u003e220 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e185 (92.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.396135265700483%\"\u003e\n \u003cp\u003e35 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"16.323296354992078%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence of substance use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.602218700475436%\"\u003e\n \u003cp\u003eTobacco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.421553090332806%\"\u003e\n \u003cp\u003e1.14 (\u0026plusmn;5.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.580031695721077%\"\u003e\n \u003cp\u003e0.92 (\u0026plusmn;4.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.00633914421553%\"\u003e\n \u003cp\u003e2.04 (\u0026plusmn;7.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.066561014263076%\"\u003e\n \u003cp\u003et=-1.05 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.62121212121212%\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.234848484848484%\"\u003e\n \u003cp\u003e1.96 (\u0026plusmn; 6.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.424242424242426%\"\u003e\n \u003cp\u003e1.96 (\u0026plusmn;6.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.12878787878788%\"\u003e\n \u003cp\u003e2.00 (\u0026plusmn;7.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.59090909090909%\"\u003e\n \u003cp\u003et=-0.04 (0.96)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.62121212121212%\"\u003e\n \u003cp\u003eCannabis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.234848484848484%\"\u003e\n \u003cp\u003e0.10 (\u0026plusmn;1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.424242424242426%\"\u003e\n \u003cp\u003e0.05 (\u0026plusmn;0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.12878787878788%\"\u003e\n \u003cp\u003e0.27 (\u0026plusmn;1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.59090909090909%\"\u003e\n \u003cp\u003et=-0.77 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 : Comparison of the Trauma, Stress, Coping and Social Support\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"37.65822784810127%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Case\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=201)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Mean (\u0026plusmn;SD) (Range)/\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=49)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Mean (\u0026plusmn;SD) (Range)/\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.265822784810126%\"\u003e\n \u003cp\u003e\u003cstrong\u003et-test/ chi-square test (p value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"37.65822784810127%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTSD symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e0.79 (\u0026plusmn; 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e4.27 (\u0026plusmn; 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.265822784810126%\"\u003e\n \u003cp\u003et=-9.88 (0.001) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"37.65822784810127%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived Stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e4.80 (\u0026plusmn;6.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e16.22 (\u0026plusmn;7.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.265822784810126%\"\u003e\n \u003cp\u003et=-9.34 (0.001) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" width=\"13.765822784810126%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoping Strategies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\"\u003e\n \u003cp\u003eSelf-Distraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e4.95 (\u0026plusmn;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e4.73 (\u0026plusmn;0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.265822784810126%\"\u003e\n \u003cp\u003et=1.502 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eActive Coping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.51 (\u0026plusmn;0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.06 (\u0026plusmn;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=3.10 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eDenial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.07 (\u0026plusmn;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.88 (\u0026plusmn;1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=0.97 (0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eSubstance Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e2.33 (\u0026plusmn;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e2.29 (\u0026plusmn;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=0.27 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eEmotional Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.21 (\u0026plusmn;0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.86 (\u0026plusmn;0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=2.57 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eInstrumental Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.48 (\u0026plusmn;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.18 (\u0026plusmn;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=1.72 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eBehavioural Disengagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.18 (\u0026plusmn; 0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.55 (\u0026plusmn;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=3.56 (0.001) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eVenting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.42 (\u0026plusmn;0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.80 (\u0026plusmn;1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=3.30 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003ePositive Reframing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.12 (\u0026plusmn;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.86 (\u0026plusmn;1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=1.58 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003ePlanning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.35 (\u0026plusmn;1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.27 (\u0026plusmn;1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=0.38 (0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eHumour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e2.45 (\u0026plusmn;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e2.57 (1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=-0.69 (0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eAcceptance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.75 (\u0026plusmn;1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.29 (\u0026plusmn;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=2.23 (0.02) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.43 (\u0026plusmn;1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e6.06 (\u0026plusmn;1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=-2.76 (0.01) **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.706422018348626%\"\u003e\n \u003cp\u003eSelf-Blame\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e5.65 (\u0026plusmn;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e4.82 (\u0026plusmn;1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=3.95 (0.001) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" width=\"13.765822784810126%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial Support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.89240506329114%\"\u003e\n \u003cp\u003eTotal Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e68.53 (\u0026plusmn;7.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\"\u003e\n \u003cp\u003e68.80 (\u0026plusmn;5.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.265822784810126%\"\u003e\n \u003cp\u003et=-0.24 (0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.706422018348626%\"\u003e\n \u003cp\u003eFamily Subscale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e20.05 (\u0026plusmn;2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e20.29 (\u0026plusmn;1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=-0.66 (0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.706422018348626%\"\u003e\n \u003cp\u003eFriend Subscale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e20.15 (\u0026plusmn;2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e19.69 (\u0026plusmn;3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=0.88 (0.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.706422018348626%\"\u003e\n \u003cp\u003eOthers Subscale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e20.10 (\u0026plusmn;2.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.91743119266055%\"\u003e\n \u003cp\u003e20.46 (\u0026plusmn;2.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.458715596330276%\"\u003e\n \u003cp\u003et=-1.04 (0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 : Predictors of the psychological distress among Covid 19 patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.E.\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWald\u0026rsquo;s \u0026chi;2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lsquo;p\u0026apos; Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e\u003cstrong\u003eE\u0026beta; (Odds Ratio)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for \u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e2.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e2.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e8.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eSex (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e2.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.161 - 1.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eDomicile (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.220 - 3.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eComorbid Status (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.190 - 2.945\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eTrauma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e19.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e2.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e1.489 - 2.836\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003ePerceived Stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e2.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e1.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.980 - 1.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eActive Coping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e1.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.682 - 2.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eEmotional Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e3.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.319 - 1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eBeh_Dis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e1.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.394 - 1.337\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eVenting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.506 - 1.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eAcceptance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.509 - 1.371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e2.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e1.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.918 - 2.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.70063694267516%\"\u003e\n \u003cp\u003eSelf-blame\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.9171974522293%\"\u003e\n \u003cp\u003e-.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.35031847133758%\"\u003e\n \u003cp\u003e.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e1.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.89171974522293%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.78343949044586%\"\u003e\n \u003cp\u003e.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.92356687898089%\"\u003e\n \u003cp\u003e.444 - 1.224\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"PGIMER, Chandigarh","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":"COVID-19, Psychological distress, PTSD, Substance Use, Stress, Coping, Social Support, hospitalized patients","lastPublishedDoi":"10.21203/rs.3.rs-1038192/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1038192/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eLimited evidence is available on the psychological distress among patients hospitalized with COVID -19. We assessed (a) the incidence of psychological distress, posttraumatic symptoms and substance use among patients hospitalized with COVID-19, (b) perceived stress, coping, and social support experienced by distressed and non-distressed patients and the predictors of psychological distress.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eOurs was a hospital-based cross-sectional study, conducted in a Union Territory of India. Patients were assessed (August \u0026ndash; September, 2020) at the time of admission (within two days) with standardized instruments (N=250).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMore than 19 percent of respondents had experienced significant psychological distress (probable cases) and nearly 9% reported post traumatic stress symptoms. The cases and non-cases differ in terms of active coping (5.51\u0026plusmn;0.87 v/s 5.06\u0026plusmn;1.06; t=3.10, p\u0026lt;0.01), emotional support (5.21\u0026plusmn;0.87 v/s 4.86\u0026plusmn;0.79; t=2.57, p\u0026lt;0.01), behavioural disengagement (5.18\u0026plusmn;0.92 v/s 4.55\u0026plusmn;1.15; t=3.56, p\u0026lt;0.001), venting (5.42\u0026plusmn;0.96 v/s 4.80\u0026plusmn;1.24; t=3.30, p\u0026lt;0.01), acceptance (5.75\u0026plusmn;1.24 v/s 5.29\u0026plusmn;1.50; t=2.23, p\u0026lt;0.05), religion (5.43\u0026plusmn;1.41 v/s 6.06\u0026plusmn;1.46; t=-2.76, p\u0026lt;0.01) and self-blame (5.65\u0026plusmn;1.00 v/s 4.82\u0026plusmn;1.39; t=3.95, p\u0026lt;0.001). Symptoms of post-traumatic stress (OR: 2.058; 95% CI: 1.49-2.84) was the only significant predictor of the psychological distress.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNearly one in five hospitalized patients with COVID-19 experience psychological distress. Screening and treatment for trauma and psychological distress should be made an integral component of care for patients with COVID-19\u003c/p\u003e","manuscriptTitle":"Psychological Distress and Its Predictors Among Hospital Admitted COVID-19 Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-01 18:41:08","doi":"10.21203/rs.3.rs-1038192/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":"53642fc0-c9bd-4ba0-a4bc-3fe0504c7cda","owner":[],"postedDate":"November 1st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":8243595,"name":"Psychiatry"}],"tags":[],"updatedAt":"2021-11-01T18:41:08+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-01 18:41:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1038192","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1038192","identity":"rs-1038192","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}