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Indian Journal of Psychological Medicine logoLink to Indian Journal of Psychological Medicine
. 2020 Jul 6;42(4):353–358. doi: 10.1177/0253717620933992

Prevalence and Predictors of Stress, anxiety, and Depression among Healthcare Workers Managing COVID-19 Pandemic in India: A Nationwide Observational Study

William Wilson 1, Jeffrey Pradeep Raj 2,, Seema Rao 3, Murtuza Ghiya 4, Nisanth Menon Nedungalaparambil 5, Harshit Mundra 6, Roshan Mathew 7
PMCID: PMC7385435  PMID: 33398224

Abstract

Background:

The coronavirus disease 2019 (COVID-19) pandemic has caused great financial and psychological havoc. Healthcare professionals (HCPs) are among the many groups of people who are in the frontline and facing a risk of direct exposure to the virus. This study aimed to assess the prevalence and predictors of stress, depressive, and anxiety symptoms among HCPs of India.

Methods:

It was a cross-sectional, online survey conducted in April 2020 among HCPs who are directly involved in the triage, screening, diagnosing, and treatment of COVID-19 patients and suspects. Stress was estimated using Cohen’s perceived stress scale. Depression and anxiety were assessed using the tools Public Health Questionnaire—9 and Generalized Anxiety Disorder—7. Predictors were analyzed using univariate and multivariate binary logistic regression.

Results:

A total of 433 online responses were obtained, and N = 350 were finally included. The prevalence (95% CI) of HCPs with high-level stress was 3.7% (2.2, 6.2), while the prevalence rates of HCPs with depressive symptoms requiring treatment and anxiety symptoms requiring further evaluation were 11.4% (8.3, 15.2) and 17.7% (13.9, 22.1), respectively. Women had approximately two times the increased odds of developing moderate- or high-level stress, depressive symptoms requiring treatment, and anxiety symptoms requiring further evaluation. Similarly, women staying in a hostel/temporary accommodation had two times the increased odds of developing depression or anxiety symptoms.

Conclusion:

The prevalence of stress, depressive, and anxiety symptoms among HCPs in India during the pandemic is comparable with other countries.

Keywords: Pandemic, COVID-19, stress, anxiety, depression, prevalence, risk factors


Key Messages:

COVID-19 pandemic puts frontline HCPs at great risk of psychological stress. The prevalence values of high-level stress, depressive symptoms requiring treatment, and anxiety symptoms requiring further evaluation were 3.7%, 11.4%, and 17.7%, respectively; these values are comparable to other countries and not high, given the comparatively poor health infrastructure in our country compared to other nations. This could be attributed to the early phase of the pandemic and the resilience of Indian HCPs.

The emergence of the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), causing the coronavirus disease 2019 (COVID-19) over the turn of the year 2020 has wreaked havoc in the medical systems across the world. Over 28 lakh cases have been reported throughout the world, with numbers increasing by the day.1 This has put healthcare professionals (HCP) under tremendous pressures as they deal with many variables some of which are longer working hours, lack of personal protective equipment, lack of specific drugs and protocols, and being away from family. According to previous studies, during the outbreaks of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS), frontline medical staff had reported high levels of stress that resulted in posttraumatic stress disorder (PTSD).2, 3 It was also found that HCPs considered resignation, faced stigmatization,4 and feared contagion and spread to family and friends, resulting in high levels of stress, depression, and anxiety symptoms.5 There have been plenty of reports from China detailing the number of HCPs getting infected and even succumbing to the illness.6 Concerns of the psychological impact of the pandemic like before are arising. This resulted in interventions such as setting up psychological assistance services over the telephone, internet, and application-based sessions.

As on April 11, 2020, India faces the most critical phase of the pandemic, with community transmission not yet in full flow.7 HCPs across the country are facing a fight like never before. Vulnerable to psychological impact, we aim to evaluate the magnitude of stress, anxiety, and depression and to assess possible associated risk factors at this early stage of the pandemic. This would help us plan appropriate interventions at the early stage to prevent a detrimental outcome for the brave HCPs out there.

Materials and Methods

Ethics

The study was approved by the institutional ethics committee. An online written informed consent was obtained from all potential participants.

Study Design and Eligibility Criteria

This was an online-questionnaire-based cross-sectional study conducted in India during the month of April 2020.The online questionnaire was designed on Google Forms and circulated in multiple WhatsApp groups, targeting doctors and nurses involved in triage, screening, diagnosing, and treatment of COVID-19 patients and suspects. Those who were currently doing their internship were excluded.

Study Procedures

The link to the online questionnaire was circulated on April 10, 2020, and the target sample size was achieved on April 25, 2020. A maximum of three reminders were sent in all WhatsApp groups. To limit the number of HCPs who inadvertently answer the questionnaire without being involved in COVD-19 work, a specific yes/no question confirming their work in COVID-19 was asked. Those who marked the answer as “Yes” were allowed to continue answering the questionnaire. The questionnaire had five sections, namely, baseline sociodemographic characteristics, Generalized Anxiety Disorder 7-item (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Scale-10 (PSS-10), and miscellaneous psychosocial questions. Data were collected anonymously, with only one response was permitted per person.

PHQ-9 is a 9-item self-report questionnaire used in clinical practice for screening, diagnosing, monitoring, and measuring the severity of depression. PHQ scores ≥10 have a sensitivity of 88% and a specificity of 88% for major depression and require treatment.8 PSS-10 is an instrument designed to measure the degree to which situations in one’s life are appraised as stressful. PSS items have been found to have good correlations with other stress measures, self-reported health and health service measures, health behavior measures, smoking status, and help-seeking behavior.9 GAD-7 is a 7-item self-report questionnaire used in clinical practice for screening and assessing severity of generalized anxiety disorder. Cut-off points of 5, 10, and 15 may be interpreted as representing mild, moderate, and severe levels of anxiety on the GAD-7. A score of >10 would require further evaluation.10

Sample Size Estimation

Considering an estimated prevalence of depression (p) among HCPs to be 13.5% based on the study by Zhu et al.,11 the sample size estimated using the formula (Zα)2pq/d2 using an alpha error of 5% and an absolute precision (d) of 5% was 179. If estimated considering the prevalence of stress (p = 29.8%), although a different tool being used, and anxiety (p = 24.1%), the sample size, with the other assumptions remaining constant, would be 322 and 281, respectively. Considering the largest value among the three and assuming an approximate 10% of questionnaires to have incomplete responses, we decided to increase the sample size to 350.

Data Management

Data were exported from the Google Forms to Microsoft Excel (Microsoft Corporation, Redmond, Washington, USA, 2016) spreadsheet and coded. Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) Statistics for Windows, Version 20.0 (IBM Corp., USA, 2011).

Statistical Analysis Plan

Demographic characteristics were summarized using descriptive statistics such as frequency and percentages in case of discrete data, or mean and standard deviation (SD) in the case of continuous data. Prevalence rates of high-level stress, anxiety symptoms requiring further evaluation, and depressive symptoms requiring treatment were expressed as proportions with 95% confidence intervals (CI). The hypothesized factors/predictors to each of these conditions, namely stress, anxiety, and depression, such as age, gender, being a doctor, years of experience, hostel/ temporary accommodation, history of mental illness, presence of comorbidities, perceived inability to distress, and employment in the government sector, were subjected to univariate binary logistic regression. Those with a significance of P < 0.2 in the univariate analysis were included in the multivariate binary logistic regression model.

Results

A total of 433 responses were received. Of these, 83 respondents were not involved in any of the COVID-19 related activities and hence were excluded. The remaining 350 from across ten states and one union territory were included in the analysis. A total of 344 participants had disclosed their institutions of affiliation, and the number of participating institutions totaled to 98. Of the 350 participants, 84.3% (n = 295/350) were doctors and the remaining 15.7% (n = 55/350) were nurses. The mean (SD) age of the participants was 30.21 (5.22) years. The demographic characteristics are summarized in Table 1.

Table 1. Demographic Characteristics.

Characteristic Frequency (N = 350) Percentage (%)
Age (years) 18–29 178 50.9
30–44 163 46.6
45–60 9 2.6
Gender Male 187 53.4
Female 163 46.6
Geographical distribution of participants within Indiaa North and Central 42 12.0
South 219 62.6
East and North East 20 5.7
West 69 19.7
Accommodation Home 189 54.0
Hostel 133 38.0
Temporary arrangement 28 8.0
History of mental disorders Yes 15 4.3
No 331 94.6
Did not disclose 4 1.1
Comorbidities Asthma/COPD 15 4.3
Hypertension 9 2.6
Diabetes mellitus 8 2.3
Hypothyroidism 4 1.1
Miscellaneousb 6 1.7

aAs per the six administrative zones of India recognized under Part III of the States Reorganisation Act, 1956.

bPolycystic ovarian disease and allergic rhinitis: two participants each; seronegative arthritis and migraine: One participant each. COPD: chronic obstructive pulmonary disease.

The details regarding the occupation of participants are given in Table 2. Junior residents formed the major proportion (n = 168/350; 48.0%). The mean (SD) years of experience of the participants were 5.52 (4.79).

Table 2. Occupational History.

Variable Category Frequency (N = 350) Percentage (%)
Employment sector Government 165 47.1
Private 185 52.9
Occupation Doctor 295 84.3
Nurses 55 15.7
Designation Junior resident 168 48.0
Senior resident/assistant professor 95 27.1
Associate professor/professor 35 10.0
Staff nurse 52 14.9
Department Emergency medicine 166 47.3
General medicine 68 19.4
Critical care 27 7.7
Paediatrics 16 4.6
Otorhinolaryngology 8 2.3
Infectious diseases 6 1.7
Pulmonology 6 1.7
Other medical specialties 33 9.4
Other surgical specialties 20 5.7
Years of experience Ten years and below 310 88.6
Greater than ten years 40 11.4

The prevalence (95% CI) of HCPs with high-level stress was 3.7% (2.2, 6.2). The prevalence rates (95% CI) of HCPs with depressive symptoms requiring treatment and anxiety symptoms requiring further evaluation were 11.4% (8.3, 15.2) and 17.7% (13.9, 22.1), respectively. The details of various categories of stress, depressive symptoms, and anxiety symptoms, and the details of leisure activities are depicted in Table 3. A large majority (n = 273/350; 78.0% had serious concerns about the spread of infection from them to their friends or family members. Also, most participants (n = 151/350; 43.2% and n = 175/350; 50.0%, respectively) were not satisfied with the administrative support from the institution and the availability of personal protective equipment.

Table 3. Psychological Characteristics.

Variable Category Frequency (N = 350) Percentage (%)
Perceived stress Low 61 17.4
Moderate 276 78.9
High 13 3.7
Depressive symptoms None–Minimal 177 50.6
Mild 133 38.0
Moderate 30 8.6
Moderately severe 7 2.0
Severe 3 0.8
Anxiety symptoms None–Minimal 118 33.7
Mild 170 48.6
Moderate 48 13.7
Severe 14 4.0
Leisure activities Online entertainment 260 74.3
Talking with friends 214 61.1
Physical fitness 118 33.7
Smoking 28 8.0
Alcohol 15 4.3
Unable to do any 25 7.1
Concern about the spread of infection to family High 273 78.0
Moderate 44 12.6
Low 33 9.4
Satisfied with the
institutional support
High 96 27.4
Moderate 103 29.4
Low 151 43.2
Satisfied with the availability of personal protective equipment High 84 24.0
Moderate 91 26.0
Low 175 50.0

An analysis to identify the predictors of moderate- and high-level stress revealed that female gender (odds ratio [OR] = 2.008, 95% CI = 1.122, 3.594, and P value = 0.019) was the only significant predictor among all the hypothesized factors, thereby negating the need for multivariate analysis. With regards to depressive symptoms requiring treatment, the significant predictors (adjusted OR; 95% CI; P value) were female gender (2.023; 1.021, 4.010; 0.044) and hostel/temporary accommodation (2.355; 1.180, 4.702; 0.015). Similarly, the significant predictors (adjusted OR; 95% CI; P value) of anxiety symptoms requiring further evaluation were female gender (2.180; 1.230, 3.862; 0.008) and hostel/temporary accommodation (1.926; 1.046, 3.548; 0.035). The details of the univariate analysis and multivariate analysis to identify the predictors of stress, depression, and anxiety are summarized in Table 4.

Table 4. Univariate Analysis for Predictors of Stress, Depression, and Anxiety.

Predictors Moderate or High-Level Stress Depression Requiring Treatment Anxiety Requiring Further Evaluation
Odds Ratio P Value Odds Ratio P Value Odds Ratio P Value
Younger agea 1.01 0.85 1.02 0.57 1.03 0.39
Female gender 2.01 0.02 2.08 0.04b 2.24 <0.01c
Being a doctor 1.23 0.58 0.72 0.43 0.73 0.39
Less years of experiencea 1.01 0.79 1.03 0.52 1.06 0.11c
Hostel/temporary accommodation 1.18 0.56 2.41 0.01 2.21 0.01c
History of mental illness 1.39 0.67 1.21 0.81 1.17 0.81
Presence of comorbidities 0.72 0.42 1.39 0.49 0.95 0.91
Perceived inability to distress 1.12 0.85 0.66 0.58 0.88 0.82
Employed in government sector 0.77 0.36 1.27 0.47 1.24 0.44

aConsidered as continuous variables with the hypothesis that lower the value, greater the risk.; bResults of multivariate analysis for predictors of depressive symptoms requiring further treatment (adjusted odds ratio; 95% confidence intervals; P value): female gender (2.023; 1.021, 4.010; 0.044) and hostel/temporary accommodation (2.355; 1.180, 4.702; 0.015).; c Results of multivariate analysis for predictors of anxiety symptoms requiring further evaluation (adjusted odds ratio; 95% confidence intervals; P value): female gender (2.180; 1.230, 3.862; 0.008), less years of experience (1.023; 0.953, 1.099; 0.526) and hostel/temporary accommodation (1.926; 1.046, 3.548; 0.035).

Discussion

The prevalence of high-level stress was low (3.7%) and the rates for depressive symptoms requiring treatment and anxiety symptoms requiring further evaluation (11.4% and 17.7%, respectively) were comparatively more. The prevalence rates of depressive and anxiety symptoms are in line with the findings from similar studies assessing psychological impact during the COVID-19 pandemic in China but the prevalence of high-level stress in our study is comparatively low. However, a huge majority of our participants still have moderately-high stress (78.9%), which is clinically relevant. Zhu et al. from Wuhan, China, the epicenter of the virus outbreak, have reported that among 5,062 HCPs, the prevalence rates of stress, depression, and anxiety were 29.8%, 13.5%, and 24.1%, respectively.11 Another study from China, conducted among 1,257 HCPs, reported that the prevalence rates of severe distress, depressive symptoms requiring treatment, and anxiety symptoms requiring further evaluation were 10.5% (n = 132/1257), 14.8% (n = 186/1257), and 13.3% (n = 154/1257), respectively.12 To the best of the authors’ knowledge, as on April 20, 2020, study results from India or other countries on the psychological impact of COVID-19 among HCPs are yet to be published.

A closer look into the baseline prevalence of stress, depression, and anxiety among medical staff revealed similar prevalence rates even without the pandemic. A study by Grover et al. among doctors from Chandigarh, conducted in the pre-pandemic period, has reported the prevalence of moderate or severe depression to be 13.2% (n = 59/445) and moderate- or high-level stress to be 80.2% (n = 357/445), using the same tools used by us.13 Swapnil et al. have reported that the prevalence rates of anxiety and depression were 64.60% and 14.18% as assessed using the 28-item general health questionnaire.14 This suggests that the pandemic has not overtly affected the psychological well-being of the HCPs in India. One possible reason could be that the community transmission is in check due to the ongoing nationwide lockdown, thereby reducing the patient load.15 Another factor could be resilience that Indian doctors might have developed during the course of their professional life.16 Medical post-graduate training in India is very competitive,17 usually very vigorous, and with long working hours,18 associated burnout, and routine exposure to a variety of infectious diseases.19 Furthermore, even without a pandemic, the public sector hospitals in India always see a huge number of cases, with very limited staff and infrastructure.20 Exposed to such stressors, the attitude of HCPs to the current crisis could be paradoxically less panic-stricken. Although we discuss that the psychological issues are not much different now when compared to the non-pandemic days, the concern of spreading the infection to family and friends and the concern about lack of administrative support and adequate personal protective equipment is very high as noted in HCPs across the world.21

An analysis of the risk factors for stress, depression, and anxiety symptoms revealed that female gender was a significant predictor. Women were at approximately two times higher odds to develop these conditions. This finding is in line with the findings reported by Lai et al., where women are at increased odds of developing distress (OR: 1.45; P = 0.01), depression (OR: 1.94; P = 0.003), and anxiety (OR: 1.69; P = 0.001).12 Staying at a hostel or other temporary makeshift accommodations was yet another significant predictor, with participants at two-times the increased odds of developing depression or anxiety symptoms. Those living away from home are most likely feeling lonely, which itself is an important risk factor for psychiatric symptoms.22 Female gender is yet another risk factor for the development of psychiatric symptoms during loneliness.22 Although studies from other countries have identified many other predictors of psychological symptoms,12, 21 we believe that the resilience developed during the early days of the professional career, as discussed, have helped Indian HCPs to tide over the psychological crisis the pandemic otherwise would have created.

Our study has a few limitations. By virtue of its design that it is an online questionnaire without face-to-face interviews, it is difficult to pin a clinical diagnosis on participants who exhibited symptoms. The actual prevalence rates of clinically diagnosed psychological issues studied may vary, although validated screening tools have been used in this study. Also, self-selection bias is a possibility. Further, not all cadres of HCPs other than nurses and doctors have participated in the study. Yet another limitation is that India being a large country in area, the burden of patients diagnosed with COVID-19 is varied, with metros facing the brunt of the pandemic rather than the interiors. Thus, the findings may not be truly reflective of the entire nation during the time of this study. Having said that, the main strength of this study is that the psychological impact has been assessed while the trigger event is actually still ongoing and the threat is still looming.

Conclusion

The prevalence rates of high-level stress, depressive symptoms requiring treatment, and anxiety symptoms requiring further evaluation were 3.7%, 11.4%, and 17.7%, respectively. These were comparable to the reports from other countries. Female gender and staying away from family were significant predictors. The government of India has already been taking a lot of initiatives to cater to the psychological needs of the general population and its HCPs, and we recommend that these measures continue to be in place at least till the pandemic completely phases out itself.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

References

  • 1.Coronavirus update (live). https://www.worldometers.info/coronavirus Accessed April 25, 2020.
  • 2.Tam CWC, Pang EPF, Lam LCW. et al. Severe acute respiratory syndrome (SARS) in Hong Kong in, 2003: stress and psychological impact among frontline healthcare workers. Psychol Med; 2004; 34(7): 1197–1204. [DOI] [PubMed] [Google Scholar]
  • 3.Lee SM, Kang WS, Cho A. et al. Psychological impact of the, 2015 MERS outbreak on hospital workers and quarantined hemodialysis patients. Compr Psychiatry; 2018; 87: 123–127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.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. [PMC free article] [PubMed] [Google Scholar]
  • 5.Lee AM, Wong JG, McAlonan GM. et al. Stress and psychological distress among SARS survivors 1 year after the outbreak. Can J Psychiatry; 2007; 52(4): 233–240. [DOI] [PubMed] [Google Scholar]
  • 6.Wu P, Fang Y, Guan Z. et al. The psychological impact of the SARS epidemic on hospital employees in China: exposure, risk perception, and altruistic acceptance of risk. Can J Psychiatry; 2009; 54(5): 302–311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Hindustan Times. “No community transmission of Covid-19 in India,” WHO rectifies error in report, 2020. https://www.hindustantimes.com/india-news/no-community-transmission-of-covid-19-in-india-who-rectifies-error-in-report/story-akxjThGS55OF2u32BYaHYJ.html Accessed April 27, 2020. [Google Scholar]
  • 8.Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med; 2001; 16: 606–613. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav; 1983; 24: 385–396. [PubMed] [Google Scholar]
  • 10.Spitzer RL, Kroenke K, Williams JB. et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med; 2006. May 22; 166(10): 1092–1097. [DOI] [PubMed] [Google Scholar]
  • 11.Zhu Z, Xu S, Wang H. et al. COVID-19 in Wuhan: immediate psychological impact on 5062 health workers. medRxiv, 2020. Jan 1. [Google Scholar]
  • 12.Lai J, Ma S, Wang Y. et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Netw Open; 2020. Mar 2; 3(3): e203976. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Grover S, Sahoo S, Bhalla A. et al. Psychological problems and burnout among medical professionals of a tertiary care hospital of North India: a cross-sectional study. Indian J Psychiatry; 2018; 60: 175–188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Swapnil B, Harshali R, Snehal C. Prevalence of low mental health among nurses in medical intensive care units. Int J Contemp Med Res; 2016; 3(8): 2444–2447. [Google Scholar]
  • 15.News18 India. India has delayed community transmission, lockdown will help us if rules are followed: ICMR scientist. https://www.news18.com/news/india/india-has-delayed-community-transmission-lockdown-will-help-us-if-rules-are-followed-icmr-scientist-2554139.html Accessed April 25, 2020.
  • 16.Zwack J, Schweitzer J. If every fifth physician is affected by burnout, what about the other four? Resilience strategies of experienced physicians. Acad Med; 2013. Mar 1; 88(3): 382–389. [DOI] [PubMed] [Google Scholar]
  • 17.Diwan V, Minj C, Chhari N. et al. Indian medical students in public and private sector medical schools: are motivations and career aspirations different? Studies from Madhya Pradesh, India. BMC Med Educ; 2013. Sep 15; 13: 127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Kaur S, Sharma R, Talwar R. et al. A study of job satisfaction and work environment perception among doctors in a tertiary hospital in Delhi. Indian J Med Sci; 2009. Apr; 63(4): 139–144. [PubMed] [Google Scholar]
  • 19.Wilson W, Raj JP, Narayan G. et al. Quantifying burnout among emergency medicine professionals. J Emerg Trauma Shock; 2017; 10(4): 199–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Bajpai V. The challenges confronting public hospitals in India, their origins, and possible solutions. Adv Public Health; 2014; 2014: 898502. [Google Scholar]
  • 21.Cai H, Tu B, Ma J. et al. Psychological impact and coping strategies of frontline medical staff in Hunan between January and March 2020 during the outbreak of coronavirus disease 2019 (COVID-19) in Hubei, China. Med Sci Monit; 2020. Apr 15; 26: e924171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Mushtaq R, Shoib S, Shah T. et al. Relationship between loneliness, psychiatric disorders and physical health? A review on the psychological aspects of loneliness. J Clin Diagn Res; 2014; 8(9): WE01–WE4. [DOI] [PMC free article] [PubMed] [Google Scholar]

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