|Year : 2021 | Volume
| Issue : 2 | Page : 128-133
A follow-up study to evaluate psychological impact among patients admitted for COVID-19 treatment to a tertiary care hospital
Abdul Salaam Mohammed, Raj Kiran Donthu, Sankar Reddy Tamanampudi Pratap, Ramya Krishna Kurma
Department of Psychiatry, Konaseema Institute of Medical Sciences and Research Foundation, Amalapuram, Andhra Pradesh, India
|Date of Submission||17-Aug-2021|
|Date of Decision||14-Oct-2021|
|Date of Acceptance||16-Oct-2021|
|Date of Web Publication||12-Jan-2022|
Dr. Raj Kiran Donthu
Department of Psychiatry, Konaseema Institute of Medical Sciences and Research Foundation, Amalapuram - 533 201, Andhra Pradesh
Source of Support: None, Conflict of Interest: None
Introduction: Coronavirus disease 19 (COVID-19) is a pandemic caused by a novel virus. It is associated with higher infectivity and mortality, which has led to a rise in psychological problems. This study is an attempt to assess and compare the psychological impact among patients admitted with COVID-19 infection during and after hospital stay.
Materials and Methods: The study was an observational follow-up study involving patients diagnosed and admitted to a tertiary care COVID-19 designated center using reverse transcription-polymerase chain reaction test result. They were assessed once during the hospital stay and again within 15 days of discharge. Along with the socio-demographic details, they were administered a depression, anxiety, and stress (DASS-21) scale. The data were analyzed using the R language.
Results: A total of 154 participants were assessed twice on the DASS-21 scale. Participants expressed significant financial problems and fear of COVID-19 both during admission and after discharge. There was a significant reduction in DASS-21 scores of DASS-21 after discharge. Scores were more reduced among those below 25 years; females; unmarried; higher education; employed; joint family setting and those without children.
Conclusions: In the current study, the psychological impact is reduced after successfully being treated for COVID-19 infection. There is a need to focus on early and continuous psychological interventions to patients along with the COVID-19 specific treatments.
Keywords: COVID-19 treatment, follow-up study, psychological impact
|How to cite this article:|
Mohammed AS, Donthu RK, Pratap SR, Kurma RK. A follow-up study to evaluate psychological impact among patients admitted for COVID-19 treatment to a tertiary care hospital. Telangana J Psychiatry 2021;7:128-33
|How to cite this URL:|
Mohammed AS, Donthu RK, Pratap SR, Kurma RK. A follow-up study to evaluate psychological impact among patients admitted for COVID-19 treatment to a tertiary care hospital. Telangana J Psychiatry [serial online] 2021 [cited 2023 Feb 1];7:128-33. Available from: https://tjpipstsb.org/text.asp?2021/7/2/128/335640
| Introduction|| |
The novel coronavirus disease (COVID-19) is an infectious disease caused by a novel coronavirus. The virus has been named severe acute respiratory syndrome coronavirus 2. It emerged initially in the Wuhan district of China and spread globally. The World Health Organization declared it a pandemic on March 11, 2020.,
The first case in India was confirmed in the Thrissur district of Kerala in a student who had returned home for a vacation from Wuhan University in China. Later, it spread rapidly to several areas of the country, even to most remote places like the tribal areas of Andhra Pradesh. The government of India imposed a strict lockdown from March 22, 2020, to curtail the disease spread. In the initial phases, people went through several phases of shock, lack of knowledge, and panic situation prevailed among the populations in rural areas. Due to the low literacy rate in rural areas people could not comprehend the exact methods of virus spread and used masks in an improper way like covering only the mouth. Day by day, the cases kept on growing exponentially creating havoc among the people who got infected with the virus as well as among the people who lived in the surrounding localities of the infected families.
As the disease was new to mankind, the knowledge regarding pathophysiology and management was limited. Even in the scientific community, there was little understanding of the disease. As the cases started increasing; researchers were studying the disease pathophysiology, treatment strategies, vaccination, etc., and the medical community was managing the cases; our understanding of the disease started increasing. Still, there were a lot of grey areas that need to be understood. Among them is the psychological morbidity associated with the disease.
Currently, studies are being conducted exploring the psychological impact of COVID-19 infection among various groups of individuals. COVID-19-infected patients are the ones facing the major brunt of the psychological impact. A study from New York found a significant number of admitted patients reporting depression and anxiety; while anxiety decreased, depression remained stable even after discharge. These studies play an important role in understanding and applying the same in our clinical practice in the upcoming COVID-19 waves. As per our knowledge, there is limited literature specific to our setting. The current study is an attempt to unveil the psychological morbidity associated with COVID-19 infection among patients during the hospital stay and after discharge.
Aims of the study
To compare the psychological impact among patients admitted for COVID-19 during in-patient stay and after discharge from the hospital.
To assess any relationship between the socio-demographic factors with the psychiatric morbidity during in-patient stay and after discharge.
| Materials and Methods|| |
The study was started after getting approval from the ethics committee. It was conducted in a tertiary care hospital which was approved by the concerned government authorities to specifically treat COVID-19 infected patients from the surrounding areas. During this time, all nonemergency services were stalled to create room for the increasing COVID-19 cases. Hence there were no admissions other than COVID-19-positive cases in the hospital.
It was a follow-up study involving patients diagnosed positive for COVID 19 infection using reverse transcription-polymerase chain reaction (RT-PCR) and referred by the government for further management. They were assessed two times; once at the time of admission (usually within 2 to 3 days of admission) and again within 15 days after discharge from the hospital with a negative RT-PCR test. The duration of the hospital stay was not recorded for the study. Due to strict COVID 19 norms, both the assessments were carried out telephonically by a psychiatry resident doctor who was trained in the administration of the questionnaire. Data collection took place in September and October 2020, almost nearing the end of the first peak of the pandemic in India.
Initially, those participants with a positive diagnosis of COVID-19 were approached while in the hospital for their consent to be included in the study after explaining the study details. Those willing to participate were included. Comorbid diagnosis of diabetes and hypertension, on regular treatment and well-controlled, were also included. Those with COVID 19 complications and comorbid severe medical illness were excluded. To maintain uniformity of the collected data, all the assessments were conducted by the same researcher. Each interview lasted for 20 to 30 min and was timed when the participants were willing to spend time. During the interview, if participants enquired about details not related to the study, they were addressed at the end and adequate care was taken to address all their concerns. Most of these were related to the duration of stay, cost of the treatment, nutrition, etc.
Socio-demographic details relevant to the study were included. Questions relevant to the current pandemic scenario were included such as financial status, emotional feelings of fear, and anger due to the COVID 19 pandemic.
We included questions related to COVID-19 disease perception among the participants. Questions were asked about the effect of disease on their financial status, fear, and anger feelings due to infection. The responses for these questions were recorded as yes/no.
Depression anxiety and stress scale-21 item
It is a self-reported scale designed to measure depression anxiety and stress scale (DASS)., Each of the three scales contains 7 items. Depression scale measures dysphoria, hopelessness, devaluation of life, lack of interest/involvement, anhedonia, and inertia. The anxiety scale measures autonomic arousal, skeletal muscle effects, situational anxiety, and subjective experience of anxious affect. The stress scale includes difficulty in relaxing, nervous arousal, being easily upset/agitated, irritable/over-reactive, and impatient. The scale was available in English, for the study, it was translated into Telugu with the help of a language expert and back-translated using another language expert to check for reliability. Scores for the three scales are calculated by adding the scores for the relevant items. Recommended cut-off scores are provided on the scale for all three scores. The scale was freely available and no permission was required for noncommercial use.
Out of a total of 200 patients approached for participation in the study, 46 were excluded and 154 were included in the study. Among the excluded; 11 refused to give consent, 13 had complications, and 14 were lost during follow-up. Data obtained were populated into Microsoft Excel spreadsheets. The data thus obtained were analyzed using R programming language with R Studio integrated development environment. R language is an open-source platform used for statistical purposes and has robust features to analyze the data. In R program the packages used for analysis were SUMMARYTOOLs, dplyr, and tidyverse. The data were subjected to descriptive analysis to get mean, median, standard deviation, and percentages. The normality of the data was checked by the Shapiro–Wilk test and as the data was not normally distributed; non-parametric tests were used for analysis. Tests used were McNemar, Wilcoxson sign-rank, and Multivariate Analysis of Variance (MANOVA). The data obtained were tabulated and discussed.
| Results|| |
[Table 1] and [Table 2] More than half (55%) of the sample were above 45 years. Males constitute 60% of the sample. The majority were married (83%) and belonged to the Hindu religion (87%). Two-thirds of the patients come from a rural background. Eighteen percent of the patients were illiterate, one-third were employed in unskilled jobs with nearly 30% of the sample earning <5000 per month.
|Table 2: Comparison of variables during and after hospital admission for coronavirus disease-19|
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Depression, anxiety, and stress subscale
[Table 3] and [Table 4] There is a significant reduction in mean scores among the subscales; depression (P < 0.024), anxiety (P < 0.001), and stress (P < 0.001) when compared with in-patient and after discharge assessment. The severity levels of depression and stress became normal, whereas the anxiety levels increased to 92% from the in-patient level of 69%.
|Table 3: Comparison of depression, anxiety and stress scale scores during and after hospital admission|
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|Table 4: Distribution of depression, anxiety and stress scale scores (means and percentages)|
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Comparison of socio-demographic variables with the DASS subscales [Table 5]: Using multivariate analysis, a comparison was done between the two assessments, with the socio-demographic factors as the independent variable and DASS subscales as a dependent variable. There was a significant association between the two assessments among age with depression and anxiety; marital status with all the three subscales; number of children, educational and employment status with anxiety; income and type of family with the depression and stress. Based on the median scores, lesser scores were found in ages below 25 years for depression and anxiety; unmarried for all the subscales; intermediate and above level of education for anxiety; working as professionals for anxiety; both the extremes of monthly income (below 5000 and above 30000) for depression and stress; joint family setting for depression and stress; no children for anxiety.
|Table 5: Comparison of sociodemographic variables with the depression, anxiety and stress scale subscales|
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| Discussion|| |
In the current study, the rates of any level of depression and anxiety were 6.9% and 30.4% respectively during the hospital stay. This decreased for both depression and anxiety when assessed after discharge. Hence, the levels of both depression and anxiety were high during the hospital stay, whereas depression levels decreased but anxiety remained higher even after discharge. This when compared to the baseline prevalence that is based on National Mental Health Survey, 2015-2016 the prevalence of depressive disorders and combined anxiety disorders were 2.68% and 3.33%, respectively. The study shows that the hospitalization for COVID-19 is associated with an increase in psychiatric morbidity. There could be various reasons implicated for this increase. The lockdown either directly or indirectly could have or the disease process itself could have contributed. As the study is observational, we could not explore this relationship.
As the infection with COVID-19 is new, there is a paucity of evidence for a direct link for the neurological or psychiatric manifestation to link the infection. Few anecdotal reports have reported changes in the brain leading to neurological manifestations like leakage of blood–brain barrier leading to acute necrotizing encephalopathy in one case and another cytokine storm leading to aphasia and seizures due to demyelination and neuronal cell death. More research is required to establish a direct link between the existence of neurological conditions with the COVID-19 infection. Indirectly, the effects could be related to various reasons such as changes imposed by lockdown, financial problems, fear and chaos due to unprecedented widespread infection, continuous live media coverage regarding the spread of infection, etc. Similar to the current study, a comparative study in India had found that patients had elevated levels of DASS-21 levels during the pandemic.
A meta-analysis by Deng et al. found the pooled prevalence of depression and anxiety in in-patients among various studies to be 48% and 42%, respectively, whereas the same among the outpatients to be 35% and 33%, respectively. The analysis did not yield any significant difference between in and outpatient for both depression and anxiety. However, the study found that the levels of depression and anxiety in both in-patients and out-patients were substantially higher than the prepandemic levels. Another meta-analysis reported pooled prevalence of depression and anxiety among patients as 42% and 37%, respectively. In the current study, even though the levels of depression and anxiety were high during in-patient stay, these decreased to a great extent after discharge. Furthermore, the levels of both depression and anxiety were not high as reported by these studies. We feel that the geographical status of different studies, demographic factors of participants, the timing of the study may have contributed to this finding. Some concerns were highlighted by patients during the interview like shaming of the individuals for the diagnosis during the transportation to a COVID-19 care center, personal protective equipment acting as a barrier in preventing the personal warmth with the healthcare worker, poor confidentiality maintained by media and lay public in reporting the cases could also have played some role. We also feel that inclusion of only mild-to-moderate COVID-19 cases could have contributed to lower levels of psychological impact.
A prospective cohort study in New York by Catherine et al. found depression and anxiety to be 29% and 36% respectively during hospitalization; which decreased to 9% and 20% at 2 weeks of follow-up. A meta-analysis of studies has found younger patients demonstrating optimistic attitudes toward the disease and pessimistic picture by the elderly. It was postulated that younger individuals do not have an underlying comorbid illness, ease to access information; whereas the elderly have underlying comorbid diseases and showed unstable mood. Studies, have found that females were more likely to express emotions and anxiety; whereas males portrayed anger but repressed emotions. Hence, it appears from these studies that each demographic attribute contributes to the psychological impact in a variety of ways. This is in line with the current study findings of different psychological morbidity based on various demographic variables. To tackle this increased psychological impact, it is necessary that psychological counseling and crisis intervention should be focused on elderly patients, females, those who were employed, higher educated, and lesser income groups.
A preprint study by Yang et al. had found that patients admitted for COVID-19 treatment while in the isolation ward should receive psychological intervention along with the routine COVID-19 treatment to reduce the psychological impact. There is also evidence to suggest that earlier and continuous professional psychological intervention can reduce mental disturbance. In cases where face-to-face interventions was not possible, online interventions lead to positive attitudes in nearly half of the patients.
| Conclusions|| |
The psychological impact in the current study is low during both the in-patient and after discharge when compared to western studies. There is a need to integrate earlier and continuous professional psychological interventions in all patients along with the routine COVID-19 treatments.
Limitations and strengths
The study was cross-sectional observational, hence the cause and effect relationship could not be established. As the study was conducted in a single tertiary care hospital the results may not generalizable. We could only administer the DASS scale, which is a screening questionnaire due to the operational difficulties imposed by the COVID-19. However, since the study focused on assessing and comparing the psychological impact both during the hospitalization and after discharge, the findings will help us to better understand the psychological impact.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Dhama K, Khan S, Tiwari R, Sircar S, Bhat S, Malik YS, et al.
Coronavirus disease 2019-COVID-19. Clin Microbiol Rev 2020;33:e00028-20.
Parker C, Shalev D, Hsu I, Shenoy A, Cheung S, Nash S, et al.
Depression, anxiety, and acute stress disorder among patients hospitalized with COVID-19: A prospective cohort study. J Acad Consult Liaison Psychiatry 2021;62:211-9.
Levibond SH. The Nature and Measurement of Anxiety, Stress and Depression. Sydney: University of Western Australia; 1983.
Levibond SH, Levibond PF. Manual for the Depression Anxiety Stress Scale (DASS). New South Wales, Australia: Psychology Foundation Monograph; 1993.
R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available from: https://www.R-project.org
. Last assessed on 2021 Aug 10.
RStudio team. RStudio: Integrated Development for R. Boston, MA: PBC: 2020.
Wickham H, Averick M, Bryan J, Chang W, D'Agostino L, Francois R, et al.
Welcome to the tidyverse. J Open Source Softw 2019;4:1686.
NIMHANS. National Mental Health Survey 2015-16 (Summary); 2015.Available from: Indianmhs.nimhans.ac.in/Docs/Summary.df. [Last accessed on 2021 Jun 21].
Poyiadji N, Shahin G, Noujaim D, Stone M, Patel S, Griffith B. COVID-19 associated acute hemorrhagic necrotising encephalopathy: CT and MRI features. Radiology 2020;296:E119-E120.
Filatov A, Sharma P, Hindi F, Patricio S. Neurological complications of coronavirus disease (COVID-19): Encephalopathy. Cureus 2020 Mar 21;12(3):e7352. doi:10.7759/cureus.7352.
Balachandar V, Mahalaxmi I, Subramaniam M, Kaavya J, Senthil Kumar N, Laldinmawii G, et al.
Follow-up studies in COVID-19 recovered patients – Is it mandatory? Sci Total Environ 2020;729:139021.
Salaam MA, Raju GG, Donthu RK, Pasam RS, Acharya A, Tamanampudi S. Psychological impact during the late phase of COVID-19 pandemic among the hospitalised patients and general public in Andhra Pradesh: A cross sectional comparative study. J Evid Based Med Health 2021;8:1614-9.
Deng J, Zhou F, Hou W, Silver Z, Wong CY, Chang O, et al.
The prevelence of depression, anxiety, and sleep disturbance in COVID-19 patients: A meta analysis. Ann N Acad Sci 2021;1486:1-22.
Krishnamoorthy Y, Nagarajan R, Saya GK, Menon V. Prevalence of psychological morbidities among general population, healthcare workers and COVID-19 patients amidst the COVID-19 pandemic: A systematic review and meta-analysis. Psychiatry Res 2020;293:113382.
Luo M, Guo L, Yu M, Jiang W, Wang H. The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public – A systematic review and meta-analysis. Psychiatry Res 2020;291:113190.
Sun N, Wei L, Wang H, Gao M, Hu X, Shi S. Qualitative study of the psychological experience of COVID-19 patients during hospitalisation. J Affect Disord 2020;278:15-22.
Varshney M, Parel JT, Raizada N, Sarin SK. Initial psychological impact of COVID-19 and its correlates in Indian Community: An online (FEEL-COVID) survey. PLoS One 2020;15:e0233874.
Yang L, Wu D, Hou Y, Wang X, Dai N, Wang G, et al.
Analysis of psychological state and clinical psychological intervention model of patients with COVID-19. medRxiv 2020;2020. doi.org/10.1101/2020.03.22.20040899.
Bo HX, Li W, Yang Y, Wang Y, Zhang Q, Cheung T, et al.
Posttraumatic stress symptoms and attitude toward crisis mental health services among clinically stable patients with COVID-19 in China. Psychol Med 2021;51:1052-3.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]