|Year : 2021 | Volume
| Issue : 3 | Page : 213-218
Rapid survey of psychological status of health-care workers during the early outbreak of COVID-19 pandemic: A single-centre study at a tertiary care hospital in Northern India
Rajesh Kumar1, Anindya Das2, Vanya Singh3, Puneet Kumar Gupta3, Yogesh Arvind Bahurupi4
1 Department of Nursing, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
2 Department of Psychiatry, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
3 Department of Microbiology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
4 Department of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
|Date of Submission||16-Jan-2021|
|Date of Decision||10-Aug-2021|
|Date of Acceptance||11-Aug-2021|
|Date of Web Publication||28-Dec-2021|
Dr. Anindya Das
Department of Psychiatry, All India Institute of Medical Sciences, Rishikesh - 249 203, Uttarakhand
Source of Support: None, Conflict of Interest: None
Background: Considering the impending crisis of COVID-19 and hospitals across India and the world gearing up to manage such cases, an online survey to assess the baseline psychological symptoms in health-care workers (HCWs) of a single tertiary care hospital was designed. The survey was cleared by the institutional ethics committee. Materials and Methods: An online self-reported survey was designed on the Google Survey portal, COVID: A survey of stress (SOS COVID) and posted on various closed WhatsApp group of employees. A snowball sampling method was adopted. We collected self-reported data on socio-demographics and data in relation to COVID-19 patient care, depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder-7), insomnia (Insomnia Severity Index) and perceived stress (Perceived Stress Scale-10). Results: Two hundred and twenty-seven participants responded to the online survey. The mean age was 28.77 years, 64% were female, mostly (74.9%) resided outside the campus and approximately half (46.7%) were frontline worker. On average, participants had low scores on all the scales, but approximately 23% scored above the cut-off for either moderate to severe depression, anxiety or insomnia. Those scoring higher (lower) in one scale also scored similarly on other scales. The chances of scoring above cut-off were significantly higher in females (P = 0.022), postgraduate educated (P = 0.018), physicians (P = 0.006) and residents of the campus (P = 0.011), though being a female and a physician persisted as significant predictors on logistic regression analysis. Conclusions: The COVID-19 pandemic created considerable anxiety and stress among the HCWs. The most vulnerable HCWs are women and physicians who may require special support services to address the extra burden of psychological distress.
Keywords: Anxiety, COVID-19, depression, health-care workers, insomnia, stress
|How to cite this article:|
Kumar R, Das A, Singh V, Gupta PK, Bahurupi YA. Rapid survey of psychological status of health-care workers during the early outbreak of COVID-19 pandemic: A single-centre study at a tertiary care hospital in Northern India. J Med Evid 2021;2:213-8
|How to cite this URL:|
Kumar R, Das A, Singh V, Gupta PK, Bahurupi YA. Rapid survey of psychological status of health-care workers during the early outbreak of COVID-19 pandemic: A single-centre study at a tertiary care hospital in Northern India. J Med Evid [serial online] 2021 [cited 2022 Aug 10];2:213-8. Available from: http://www.journaljme.org/text.asp?2021/2/3/213/333959
| Introduction|| |
The first report of novel coronavirus came from Wuhan, China, at the end of December 2019. The virus was named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The highly contagious virus spread globally and soon was declared a public health emergency of international concern by the World Health Organization on January 30, 2020. The virus is presumed to be transmitted through direct contact or droplet infection, though some other opinions also exist.
In India, the first documented case of COVID-19 was in Thrissur, Kerala, on January 30, 2020, a student returning from Wuhan. By March, people with a travel history to the affected countries, and their contacts, tested positive. Subsequently, significant spreads occurred from religious congregations. India had to face a critical situation to handle such a large and scattered infected population. To add to the worries, social media, electronic handles and news channels were irresponsibly spreading myths and misinformation about coronavirus, creating panic and unrest in the population.
In this grim situation, health-care workers (HCWs) were at the forefront to manage these infected and sick people round the clock. The ever-increasing number of confirmed cases, rising death tolls, crunch of personal protective equipment, lack of drugs, ventilators, sanitisers, circulating fake news and fear of getting infected, contribute to the risk of developing psychosocial distress and mental exhaustion among them.,
Studies have reported that health-care professionals involved in direct patient care have fears to catching an infection, infecting family members, face stigmatisation, more reluctant to quit the job and reported more frequent symptoms of stress, anxiety and depression. Previous studies on HCWs working with SARS and Ebola virus reported symptoms of posttraumatic stress reactions, anxiety and depression with lasting impact on coping abilities.,,
In this context, many mobile-based, telephone, internet and application-based counselling or crisis intervention centres in liaison with local or national mental health institutions had provided psychological assistance to HCWs and the general population free of cost.
The index hospital during this time also started preparing itself to face the impending crisis. Hospital administration prepared designated COVID areas, set up new intensive care units and prepared standard guidelines on various aspects of patient management (clinical care, the flow of care) and HCWs management (training, posting and quarantining). We planned the current study for a rapid assessment of the magnitude of depression and anxiety symptoms, sleep problems and perceived stress among HCWs at AIIMS Rishikesh, a tertiary care hospital managing COVID-19 cases. We intended to provide essential baseline information on prevailing psychological issues among health-care professionals at AIIMS, Rishikesh, to plan for necessary intervention.
| Materials and Methods|| |
AIIMS Rishikesh faced its first COVID-19 case at the end of April 2020. We conducted an online survey (developed on the Google Survey platform) during May–June 2020 at the beginning of the COVID-19 outbreak. We included all HCWs from the institute working in various capacities (physicians, nurses, paramedical staff and hospital support staff). We excluded all students (but not residents) and did not exclude any HCWs based on a history of mental health problems or degree of exposure to COVID-related work. The survey was bilingual, and all the tools were available in Hindi and English, with a brief description of the survey and a consent form at the beginning. Four sections of the survey consisted of the following tools.
Consisted of information on age, gender, occupation, number of years in the profession, place of residence (in/out of campus) and level of contact with people having COVID-19 (i.e., directly engaged in diagnosing, treating, providing nursing care or working inside COVID-19 designated areas).
Patient Health Questionnaire
It is a self-administered instrument that scores 9 Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria of depression. The participants rated each item on a 4-point Likert scale, 0 (not at all) to 3 (nearly every day) with a total score range, 0–27. A >9 score has been used as a cut-off to diagnose depression as per DSM-IV. It is widely used as a screening tool and well-validated (including the Hindi version) in Indian settings. The scale has sound psychometric properties.
Generalized Anxiety Disorder
It is a 7-items self-administered questionnaire used to screen anxiety disorders in the study. Participants rate each item on a 4-point Likert scale, 0 (not at all) to 3 (nearly every day) with a total score range, 0–21. When screening for anxiety disorders, a recommended cut-off score is >9, where sensitivity and specificity exceed 0.80. The scale is a well-validated and efficient tool for screening anxiety disorders.
Insomnia Severity Index
It consists of 7 items to rate nature, severity and impact of sleep problem on a 5-point Likert scale ranging 0 (no problem) to 4 (very severe problem) (total score range, 0–28). A cut-off of >14 suggests clinically significant sleep problems. It has good psychometric properties, including its validity. We also used the validated Hindi version of the tool side by side with the English version.
Perceived Stress Scale-10
It is a ten-item self-appraised measure to assess how unpredictable, uncontrollable and overloaded respondents find their lives. Participants evaluate their response on a five-point Likert scale; (0: never to 4: very often). It is extensively used for surveys on healthy individuals, including clinical research. It is well-validated on healthy individuals. The Hindi version is validated by a general population sample. The scale proposes no cut-off and recommends it as a dimensional measure.
We took necessary permission for using the tools from the developers/publishers.
We posted the survey link [COVID: Survey of stress (SOS COVID)] on various WhatsApp groups of employees at AIIMS Rishikesh. We identified key personnel from various groups of employees, viz., doctors, nurses, lab technicians, hospital attendants, security guards and clerical staff for posting the link to their closed employee groups. A disclaimer was also added with the link to abstain from responding if the prospective respondent was not currently an employee of AIIMS Rishikesh. The process was repeated after a month to recruit additional participants who had already not responded.
Our intended sample size was 224, assuming a 5% error, 95% confidence interval, a population of about 2500 staff in the hospital and proportion scoring above cut-off scores of scales to be 20%. The latter was assumed based on the usual general population cut-off for each of the scales to be around 10%. However, due to the unique aspect of the pandemic and the specified population, i.e. HCWs, we assumed a higher figure. It also resulted in predicting a larger sample size.
We provided an additional option of receiving feedback if the respondent had agreed to provide an E-mail address, where he/she could receive a summary of their scores on individual scales along with an interpretation if they had scored above the cut-off. In such cases, further information was provided about resources available within the institute and outside (government helplines) for psychological help. We took appropriate ethical approval for the research from the Institute Ethical Committee.
Data from Google Sheets were downloaded as a.xlsx file and imported to SPSS. Data cleaning and coding were done, and missing data were eliminated. Data were analysed using SPPS version 23.0 (IBM Corp., Armonk, NY, USA).The study population characteristics were presented with descriptive statistics, frequency and percentages. The Pearson product–moment correlation coefficient evaluates the relationships between depression, stress, insomnia and anxiety. Independent sample student t-test and Chi-square test were used to compare the demographic characteristics among those scoring above the cut-off on any three scales viz., Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7) and Insomnia Severity Index (ISI). Multivariate logistic regression was used to determine the predictors of scoring above the above cut-off among participants. The level of significance was set at P < 0.05 (two-sided).
| Results|| |
A total of 227 participants responded to the full survey. [Table 1] shows the socio-demographic profile of the respondents. In summary, the participants' mean age was 28.77 (6.08) years, 64% were females, mostly resided outside the campus, with approximately half the respondents (46.7%) were frontline workers (i. e., directly engaged in COVID-19 positive cases or worked within designated COVI-19 areas). Only 22.5% had an experience of being quarantined, and none of the respondents reported to be ever COVID-19 positive at the time of the study.
[Table 2] shows the mean (standard deviation) scores on the four scales, their inter-correlation and the proportion of participants who scored above the cut-off on these scales. On average, the participants scored low on all the scales. Moreover, there was a significant correlation between all the scales.
|Table 2: Mean scores obtained, proportion scoring more than the cut-off score and inter-correlation of scores on various scales (n=227)|
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We then enumerated all the participants who scored above the cut-off on any three scales viz., PHQ-9, GAD-7 and ISI. We found 52 (22.9%), such respondents. The unadjusted relationship between scoring above cut-off on any of the three scales and independent variables (socio-demographic and experience with COVID-19) is presented in [Table 3]. The chances of scoring above cut-off were significantly higher in females, postgraduate educated, physicians and residents of the campus.
|Table 3: Bivariate relationship of independent variables with scoring above the cut-off on any three scales viz., patient health questionnaire-9, generalized anxiety disorder-7 and insomnia severity index|
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We performed multivariate logistic regression to find the predictors (socio-demographic and experience with COVID-19) of scoring above the cut-off. We performed a forward stepwise method, and the final model (that was significant) included only two variables (Gender and Occupation), though the model suggests a low level of explained variance (Nagelkerke R2 of 0.096). [Table 4] shows the multivariate logistic regression model, a significantly increased odds of scoring above cut-off in females versus males, and physicians versus other staff members were noted.
|Table 4: Multivariate logistic regression model: Predictor of scoring above cut-off on any three scales viz., patient health questionnaire-9, generalized anxiety disorder-7 and insomnia severity index|
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| Discussion|| |
We intended to assess the magnitude of impending psychological issues affecting HCWs at the start of the pandemic. For this, we devised an online self-reported method to assess the proportion of HCWs facing various psychological risks in the impending COVID-19 pandemic. We assessed self-reported depression, anxiety, insomnia and perceived stress in a selected population of HCWs in a single-center, i.e. AIIMS Rishikesh. We found around 23% of HCWs screened positive for any form of moderate psychological problems. Let us consider a general rate of 10% of psychological disorders in the general population. We find a higher preponderance of symptoms, though we consider many who screen positive may not turn out positive for any mental disorder. We also found a significant correlation between the common psychological issues reported (depression, anxiety, insomnia and perceived stress). It may mean that people who are undergoing problems in one area (e.g., perceived stress) may also have co-occurring problems (e.g., anxiety or insomnia).
We used a cut-off score of >9 for GAD-7, as established in Western literature, unlike a score of >6 as used in previous similar research from China. The latter rationalise this based on previous validation studies from China and Korea, yet they do not consider this validation based on people having epilepsy. Nonetheless, we find the proportion of participants who score above the cut-off similar to that of the Chinese study. A study from Singapore reported a similar anxiety rate as our study, but the rates of depression were higher in our study. The probable explanations could be due to the difference in the tool used for screening and other contextual differences. On the other hand, a study from Nepal found a much lower rate of psychological symptoms. Another Indian study on HCWs found a much higher rate of psychological symptoms, but this study was conducted at a later phase of the pandemic.
Moreover, our study suggests the chances of scoring above cut-off were significantly higher in females, postgraduate educated, physicians and residents of the campus, though being a female and a physician persisted as significant predictors. The latter findings are somewhat unique, considering previous studies have differed, showing that psychological symptoms are more prevalent in nonmedical HCWs. While no difference in psychological symptoms between frontline and nonfront line workers has been concurred previously but there are some inconsistencies. Lai et al. have also suggested being female and of the middle-order profession was associated with higher anxiety, depression and distress, somewhat similar to our study.
We interpret our study with the following limitation in mind. Our study was a self-reported survey on an online platform with its inherent limitation; such has a low response rate and self-selective sample. We also used an incremental snowball sampling method, and thus we had little idea of the sampling frame. Nevertheless, we tried to post our survey link through key personnel from among the employees/respondents. Despite our assumption that there will be equivalent representation from all sectors of HCWs, we found nurses to be overrepresented, while staff such as lab assistants, hospital attendants, clerical workers and other lower-level staff were underrepresented. It may be due to the difference in internet use/smartphone possession that we did not predict.
| Conclusions|| |
The COVID-19 pandemic created considerable anxiety and stress among the HCWs. Our study concurs broadly with these findings, yet the scene is not an epidemic. We suggest that the most vulnerable HCWs are women and physicians and may require special support services to address the extra burden of psychological distress amidst the COVID-19 pandemic.
The authors acknowledge Dr. Vijay Krishnan for various technical related issues.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]