|Year : 2021 | Volume
| Issue : 1 | Page : 23-27
A prospective study of major depressive disorder among COVID 19 survivors at a tertiary care hospital
Kajalpreet Kaur1, Vishal Kanaiyalal Patel2, Parveen Kumar1, Disha Alkeshbhai Vasavada1, Lubna Mohammedrafik Nerli1, Deepak Sachidanand Tiwari3
1 Resident Doctor, M.P. Shah Medical College, Jamnagar, Gujarat, India
2 Associate Professor, Department of Psyciatry, Dr. M.K. Shah Medical College and Research Center, Ahmadabad, Gujarat, India
3 Professor, Department of Psychiatry, M.P. Shah Medical College, Jamnagar, Gujarat, India
|Date of Submission||02-Jan-2021|
|Date of Acceptance||09-Feb-2021|
|Date of Web Publication||29-Mar-2021|
Dr. Parveen Kumar
2nd Floor Trauma Building, Department of Psychiatry, M.P. Shah Medical College, Jamnagar, 361 008, Gujarat
Source of Support: None, Conflict of Interest: None
Background: The COVID-19 pandemic has impacted physical health, wellbeing, and mental health, which has a disastrous effect on the health system. Among disorders emerging in the aftermath of a disaster, depression is the second most common.
Aim: The current study was aimed to estimate the prevalence of major depressive disorder (MDD) at two-time points in individuals who have been hospitalized for the treatment of COVID 19.
Materials and Methods: A prospective study was carried out from May 2020 to October 2020 at a tertiary care center among patients discharged after recovery from novel coronavirus (COVID 19). A diagnostic clinical interview was conducted to diagnose MDD, and its severity in patients who had recovered from COVID 19 using “Patient Health Questionnaire (PHQ-9)” at the time of discharge and 1 month after their discharge from the hospital.
Statistical Analysis: Descriptive statistics and Chi-square test were used for the analysis, P < 0.05 was considered statistically significant.
Results: A total of 440 participants participated in the study. Out of them, 30.90% of participants met the criteria for MDD at the time of discharge and 19.5% at 1 month post-discharge. Participants who stayed for more than 14 days, were admitted to intensive care unit (ICU) and those with co-morbid medical illness had a higher prevalence of MDD.
Conclusion: High prevalence of MDD was observed at the time of discharge among hospitalized participants. Longer duration of hospital stay and admission in ICU is associated with more unpleasant events, subsequently resulting in higher rates of morbidity, such as depression.
Keywords: Depressive disorder, pandemics, SARS-Cov-19, survivors
|How to cite this article:|
Kaur K, Patel VK, Kumar P, Vasavada DA, Nerli LM, Tiwari DS. A prospective study of major depressive disorder among COVID 19 survivors at a tertiary care hospital. Arch Ment Health 2021;22:23-7
|How to cite this URL:|
Kaur K, Patel VK, Kumar P, Vasavada DA, Nerli LM, Tiwari DS. A prospective study of major depressive disorder among COVID 19 survivors at a tertiary care hospital. Arch Ment Health [serial online] 2021 [cited 2021 Sep 17];22:23-7. Available from: https://www.amhonline.org/text.asp?2021/22/1/23/312462
| Introduction|| |
Most disasters are often associated with traumatizing events and have profound effects on the mental health as well as wellbeing of people in general. The novel Coronavirus (COVID-19) pandemic can also be considered one such disaster that humankind is facing. Complex co-morbidities such as posttraumatic stress disorder, depression, substance abuse, and other anxiety disorders are seen to be occurring with disasters. From the available evidence, it is apparent that depression is the second most common disorder to emerge in the aftermath of a disaster.
The prevalence of depressive symptoms was observed around 68% after the flood in Jammu and Kashmir state, and during super-cyclone it continued to be present in survivors even after 1 year of the disaster. The picture was also similar for the global HIV pandemic, in which the prevalence of mental illnesses had been found substantially higher among HIV-infected individuals than in the general population. Moderate-to-severe depressive symptoms were observed in 16.5% of the participants due to COVID 19, along with the observation that COVID-19 may lead to increased risk of suicide.
The degree to which mental health problems emerge after trauma may vary depending on the mechanism and type of injury. The current literature is lacking in the prevalence of major depression after discharge from the hospital. Therefore, the current study was aimed at the estimation of the prevalence of major depressive disorder (MDD) at two-time points in individuals who had been hospitalized for the treatment of COVID 19, to better understand the health needs of this population.
| Materials and methods|| |
Setting and design
A prospective study was carried out from May 2020 to October 2020 at a tertiary care center among patients discharged after recovery from novel coronavirus (COVID 19), first at the time of discharge and then at 1 month postdischarge from the hospital to examine the prevalence of MDD. The severity of major depression was assessed using the “Patient Health Questionnaire (PHQ-9),” while a diagnostic clinical interview was conducted to diagnose MDD. One month later, a diagnostic clinical interview was carried out again; patients who were not able to reach the hospital were contacted via mobile phone. Patients who gave consent for participation were included in the study. While those with pre-existing psychiatric illness, denied for participation, and uncontrolled medical illnesses at the time of admission and discharge, were excluded from the study. Written informed consent was taken from all the participants. Ethical approval was taken from the institutional ethical committee.
Demographic details such as name, age, gender, income, occupation, history of psychiatric illness, family type, and history of chronic medical illness were included.
Patient health questionnaire-9
The PHQ-9 is a 9-item scale and was used to assess depression. Major depression is diagnosed if 5 or more of the 9 depressive symptom criteria have been present at least “more than half the days” in the past 2 weeks, and 1 of the symptoms is depressed mood or anhedonia. Each item was also scored from “0” (not at all) to “3” (nearly every day) to assess the severity. The total PHQ-9 score can range from 0 to 27. The PHQ-9 score was divided into the following categories of increasing severity: 0–4, 5–9, 10–14, 15–19, and 20 or greater. The internal reliability of the PHQ-9 was excellent, with a Cronbach's α of 0.89.
Sample size calculation
Sample size required for the current study was calculated using Epi-Info software. The sample size for the current study was estimated at 384; Criteria being the prevalence of disorder as 20%, 4% absolute precision, and 95% confidence interval.
Data entry and analysis were done using Microsoft Excel and Epi Info software (Centers for Disease Control and Prevention, Atlanta, Georgia of United States). The sociodemographic profile and prevalence of MDD have been expressed in terms of frequency and percentage. Chi-square test was applied for categorical data such as gender, days of hospital stay, residing with family or alone, different age groups, and history of co-morbid medical illness, to find out the relation with MDD. Pearson correlation test was used to find out the relation of the monthly income of the participants with total PHQ 9 score.
| Results|| |
A total of 440 participants participated in the study. There were 59.10% (n = 260) males and 40.90% (n = 180) females. The age of participants ranged from 21 to 64 years with a mean age of 44.23 ± 12.56 years. Majority of the participants belonged to Hindu religion 96.36% (n = 424) followed by Muslim 3.18% (n = 14) and 0.46% (n = 02) others.
At the time of discharge from the hospital, 30.90% (n = 136) of the participants met the criteria for MDD. Out of the total participants, 14.5% (n = 64) met the criteria for mild, 10.5% (n = 46) for moderate and 5.9% (n = 26) for severe depression.
One month later, 19.5% (n = 86) of the participants met the criteria for MDD. Out of the total participants, 11.8% (n = 52) met the criteria for mild, 5.5% (n = 46) for moderate and 2.3% (n = 26) for severe depression.
[Table 1] shows that participants staying in the hospital for more than 14 days had a statistically higher prevalence of MDD, which was denoted by Chi-square test (χ2 = 19.430, P = 0.001). Participants having any co-morbid medical condition had a statistically higher prevalence of MDD as shown by Chi-square test (χ2 = 21.076, P < 0.001). Participants admitted in ICU of the hospital had a statistically significant higher prevalence of MDD, which was denoted by Chi-square test (χ2 = 21.696, P < 0.001).
|Table 1: Relation of major depressive disorder at discharge with different variables (n =440)|
Click here to view
No statistically significant difference was observed in the prevalence of MDD among different age groups, living condition of participants, and gender, as shown in [Table 1].
[Figure 1] shows that a statistically significant negative correlation between the monthly income of participants and PHQ 9 score (r = −0.145, P = 0.002) as denoted by the Pearson correlation test. This means participants with lower income had more severity of depressive symptoms. Although statistically significant, the r-value shows a weak negative correlation
|Figure 1: Scatter plot between monthly income of participants with total PHQ 9 score|
Click here to view
| Discussion|| |
The current study observed that around 31% of participants had symptoms of major depression at the time of discharge from the hospital, while 19.5% of the participants had symptoms one month after discharge from the hospital. Kong et al.(2020) observed 28.5% prevalence of depression in patients admitted for the management of COVID 19. Wang et al. observed that 16.5% of participants experienced moderate-to-severe depressive symptoms in an online survey conducted at China. Major depression symptoms were also observed in survivors of different disasters. Yadav et al. observed 68% prevalence of depression among adult of the 2014 flood survivors, and symptoms were also present at around years after disaster. Jalloh et al. (2018) reported the prevalence of anxiety and depression symptoms in 6% of participants during the Ebola outbreak in Sierra Leone, symptoms were prevalent even after 1 year. Kar and Bastia observed 26.9% prevalence of MDD among super-cyclone survivors one year after the natural disaster. Secor et al. reported prevalence of depression ranging from 3.6% to 7.1% in his study conducted among Ebola survivors in Liberia, Sierra Leone, and Guinea. de St Maurice et al. in a cross-sectional retrospective study on Ebola survivors reported 13% prevalence of depression in Monrovia, Liberia. There are many factors which could be the possible reasons for higher prevalence, such as stigma, traumatic memories of severe illness, uncertainty of the future, and social isolation
The current study did not find any gender difference in the prevalence of major depression. Kar and Bastia found that female participants had more depression diagnoses than male participants after the disaster. Özdin and Bayrak Özdin observed higher prevalence of depression and anxiety symptoms in female participants during COVID 19. While, Secor et al. observed high prevalence of depression in female participants in survivors of Ebola at Guinea and Sierra Leone, but no such relationship was found among survivors in Liberia. These findings suggest that there are varying contextual and environmental factors and drivers for the mental health conditions among survivors. It is also suggest that risk factors other than gender may be operative in a given individual.
The current study did not find any difference in the prevalence of major depression among different age groups. Similarly study conducted by Özdin and Bayrak Özdin found no statistically significant difference among the 18–49 and above-50 age groups in terms of depression during the COVID 19 pandemic in Turkey. While, Wang et al. (2021) found more anxiety and depression in the elderly and individuals with chronic disease, as they have an increased risk of contracting the disease. The results of the current study may differ due to a different study sample or the presence of various co-morbidities among different age groups. However, the impact of acute, pervasive, and continuing stressors on societal and individual psychologies associated with highly infectious and fatal disease outbreaks are different and poorly understood.
The present study observed high prevalence of major depression among participants with longer duration of hospital stay and those admitted in an intensive care unit (ICU). Aligning with the current study, Kong et al. and Shoar et al. observed higher prevalence of depression in patients with a longer duration of hospital stay. Tedstone and Tarrier and Kangas et al. also observed higher prevalence of psychiatric co-morbidities in participants who had experienced life-threatening situations such as admission in ICU. Cao et al. observed a higher prevalence of psychiatric co-morbidities among residents of villages where most houses were destroyed during the Yun Nan (China) earthquake compared to residents where only minor damage occurred. As people were more likely to remember unpleasant events after the disaster, longer duration of hospital stay was associated with more deleterious effect.
The current study observed high prevalence of major depression among participants with co-morbid medical illness as compared to those without other illnesses. Özdin and Bayrak Özdin also reported higher psychiatric comorbidities in participants with chronic disease. Wang et al. (2020) in a meta-analysis study reported that the elderly and individuals with chronic disease have an increased risk of contracting the disease. These findings emphasize on the COVID 19 mortality and added fear of death, resulting in more depressive symptoms. However, other factors such as social support from family and friends also play a significant role.
The current study observed that participants with higher income had depression with less severity. Zhong et al. observed that participants with high education level have higher levels of information about and better attitudes toward COVID-19. Cao et al. (2020) reported stable family income as a protective factor against anxiety symptoms to some extent during COVID 19. The reason could be that the lower-income group may be concerned about financial problems and worried about the future and loss of employment. However, one's ability to cope with stress, to manage and tolerate emotional distress is the salient characteristic that protects against the mental health symptoms after major stressors.
The current study was conducted using clinical diagnostic interviews which helps in confirming the diagnosis of MDD and adds value to the study. However, the absence of the comparison group is one of the limitations of this study. Since COVID 19 is a new disease, the psychological effect of some possible long-term physical outcomes related to the disease and treatment regimen had not been discovered until recently. To find the true prevalence rate and to explore long-lasting impact related to COVID-19, long-term follow-up studies are needed. Also, there is a need to explore protective factors which will give us more insight into understanding the coping strategies of those survivors. Finally, multicenter studies are needed for a better understanding of the phenomenology.
| Conclusion|| |
High prevalence of MDD was observed at the time of discharge among hospitalized participants. Longer duration of hospital stay and admission in ICU is associated with more unpleasant events, subsequently resulting in higher rates of morbidity, such as depression. Preexisting comorbid conditions further exacerbate the disease outcome. Effective communication strategies and understanding the problem statement could be helpful in dealing with the mental health issues at the time of crisis.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Naushad VA, Bierens JJ, Nishan KP, Firjeeth CP, Mohammad OH, Maliyakkal AM, et al
. A systematic review of the impact of disaster on the mental health of medical responders. Prehosp Disaster Med 2019;34:632-43.
Norris FH, Friedman MJ, Watson PJ, Byrne CM, Diaz E, Kaniasty K. 60,000 disaster victims speak: Part I. An empirical review of the empirical literature, 1981-2001. Psychiatry 2002;65:207-39.
Yadav R, Somashekar D, Sodha SV, Laserson KF, Venkatesh S, Chauhan H. Post-flood rapid needs assessment in Srinagar City, Jammu and Kashmir State, India, September, 2014. Disaster Med Public Health Prep 2019;13:133-7.
Kar N, Bastia BK. Post-traumatic stress disorder, depression and generalised anxiety disorder in adolescents after a natural disaster: A study of comorbidity. Clin Pract Epidemiol Ment Health 2006;2:17.
Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al
. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 2020;17:1729.
Xiang YT, Jin Y, Cheung T. Joint international collaboration to combat mental health challenges during the coronavirus disease 2019 pandemic. JAMA Psychiatry 2020;77:989-90.
Guidi J, Fava GA, Bech P, Paykel E. The clinical interview for depression: A comprehensive review of studies and clinimetric properties. Psychother Psychosom 2011;80:10-27.
Arroll B, Goodyear-Smith F, Crengle S, Gunn J, Kerse N, Fishman T, et al
. Validation of PHQ-2 and PHQ-9 to screen for major depression in the primary care population. Ann Fam Med 2010;8:348-53.
Kong X, Zheng K, Tang M, Kong F, Zhou J, Diao L, et al
. Prevalence and factors associated with depression and anxiety of hospitalized patients with Covid-19. MedRxiv [preprint]. 2020. doi: 10.1101/2020.03.24.20043075.
Jalloh MF, Li W, Bunnell RE, Ethier KA, O'Leary A, Hageman KM, et al
. Impact of Ebola experiences and risk perceptions on mental health in Sierra Leone, July 2015. BMJ Glob Health 2018;3:e000471.
Secor A, Macauley R, Stan L, Kagone M, Sidikiba S, Sow S, et al
. Mental health among Ebola survivors in Liberia, Sierra Leone and Guinea: Results from a cross-sectional study. BMJ Open 2020;10:e035217.
de St Maurice A, Ervin E, Orone R, Choi M, Dokubo EK, Rollin PE, et al
. Care of Ebola survivors and factors associated with clinical sequelae-monrovia, Liberia. Open Forum Infect Dis 2018;5:ofy239.
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;66:504-11.
Wang Y, Di Y, Ye J, Wei W. Study on the public psychological states and its related factors during the outbreak of coronavirus disease 2019 (COVID 19) in some regions of China. Psychol Health Med 2021;26:13-22.
Leppin A, Aro AR. Risk perceptions related to SARS and avian influenza: Theoretical foundations of current empirical research. Int J Behav Med 2009;16:7-29.
Shoar S, Naderan M, Aghajani M, Sahimi-Izadian E, Hosseini-Araghi N, Khorgami Z. Prevalence and determinants of depression and anxiety symptoms in surgical patients. Oman Med J 2016;31:176-81.
Tedstone JE, Tarrier N. Posttraumatic stress disorder following medical illness and treatment. Clin Psychol Rev 2003;23:409-48.
Kangas M, Henry JL, Bryant RA. Posttraumatic stress disorder following cancer. A conceptual and empirical review. Clin Psychol Rev 2002;22:499-524.
Cao H, McFarlane AC, Klimidis S. Prevalence of psychiatric disorder following the 1988 Yun Nan (China) earthquake – The first 5-month period. Soc Psychiatry Psychiatr Epidemiol 2003;38:204-12.
Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: Evidence from meta-analysis. Aging (Albany NY) 2020;12:6049-57.
Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, et al
. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: A quick online cross-sectional survey. Int J Biol Sci 2020;16:1745-52.
Cao W, Fang Z, Hou G, Han M, Xu X, Dong J, et al
. The psychological impact of the COVID 19 epidemic on college students in China. Psychiatry Res 2020;287:112934.
Kukihara H, Yamawaki N, Uchiyama K, Arai S, Horikawa E. Trauma, depression, and resilience of earthquake/tsunami/nuclear disaster survivors of Hirono, Fukushima, Japan. Psychiatry Clin Neurosci 2014;68:524-33.