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ORIGINAL ARTICLE
Year : 2021  |  Volume : 30  |  Issue : 1  |  Page : 29-35  Table of Contents     

Coping with COVID: Cross-sectional study to assess the psychological impact and coping strategies utilized by Indian internet users during the lockdown of the COVID-19 pandemic


1 Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
2 Department of Psychiatry, INHS Asvini, Mumbai, Maharashtra, India

Date of Submission20-Oct-2020
Date of Acceptance31-Mar-2021
Date of Web Publication17-Jun-2021

Correspondence Address:
Dr. Priyadarshee Patra
INHS Asvini, Mumbai - 400 005, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ipj.ipj_202_20

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   Abstract 

Introduction: The sudden and extended lockdown imposed by the government as an attempt to break the transmission chain of COVID disrupted the lives and plans of many. The impact on mental health of people is variable depending on the appraisal of the situation and the resources and coping strategies. Aim and Objectives: The aim of the study was to know the impact on mental health and coping strategies used by internet users dealing with the COVID-19 pandemic and involved difficulties in India. Materials and Methods: The survey was conducted using Google doc application. Tools included Generalized Anxiety Disorder-7 (GAD-7) questionnaire, Patient Health Questionnaire (PHQ), and brief COPE questionnaire. Statistical Analysis: Descriptive statistics were used to assess the sociodemographic characteristics, GAD-7, PHQ-2, and brief COPE scales. The group differences were analyzed using appropriate parametric or nonparametric tests for the quantitative variable and Chi-square/Mc-Nemar's test for categorical variables. The data were analyzed using SPSS software. Results: Three hundred and twenty six responses were analyzed. Nearly 35.3% screened positive for anxiety disorder and 12% for major depression. Respondents who were screened positive for anxiety disorder used active coping, denial, substance use, behavioral disengagement, planning, and self-blame more often than those screened negative. Those screened positive for major depression used all the coping strategies similar to anxiety disorder except for active coping more often than those who screened negative. While females used adaptive coping more frequently than males, respondents those engaged in essential services employed maladaptive coping less often. Conclusions: Acceptance, positive reframing, and positive coping were the most often employed strategies, while denial, self-blame, and substance use were least often employed.

Keywords: Anxiety, coping, COVID-19, depression, lockdown, psychopathology


How to cite this article:
Singh VV, Patra P, Singal A. Coping with COVID: Cross-sectional study to assess the psychological impact and coping strategies utilized by Indian internet users during the lockdown of the COVID-19 pandemic. Ind Psychiatry J 2021;30:29-35

How to cite this URL:
Singh VV, Patra P, Singal A. Coping with COVID: Cross-sectional study to assess the psychological impact and coping strategies utilized by Indian internet users during the lockdown of the COVID-19 pandemic. Ind Psychiatry J [serial online] 2021 [cited 2021 Aug 1];30:29-35. Available from: https://www.industrialpsychiatry.org/text.asp?2021/30/1/29/318701



Humanity has been flirting with the risk of a pandemic for a long time now. Factors range from myriad causes population explosion, poverty and poor living conditions, large-scaled armed conflicts all around tthe world, leading to migration, the increase in international travel and business, etc. Glimpses of an impending global contagion had been exhibited by the outbreaks of severe acute respiratory syndrome (SARS), middle-east respiratory syndrome, Zika virus, and Ebola. The last recorded pandemic was the Spanish flu pandemic in 1918. The SARS-CoV-2 first identified in Wuhan, China, is now a global pandemic and has caused lakhs of death worldwide.[1] With a population of 1,387,297,452 million people and dismal patient–doctor ratio of 1:1456, Indian health-care professionals are shouldering the burden of this pandemic. Decades of global experience in dealing with outbreaks and epidemics have given rise to an effective intervention technique called social distancing. It refers to the practice of separating the infected individuals or suspected/actual carriers of the illness from the unaffected population and thus halting the chain of spread in the community. Depending on the degree and type of separation, terms such as quarantine, isolation, and shelter-in-place are proven effective strategies against pandemics. Quarantine refers to separation of the healthy but possibly exposed individuals from those who are healthy and have not been exposed. Quarantine may be done at designated locations or at home. It was possibly first used in 1377 during the Black Death in Venice and Dubrovnik.[2] Isolation refers to the separation of the sick who have a communicable/infective disease from those who are healthy. This method is usually implemented in hospitals or health-care facilities and was probably first implemented in 1423 in Venice during outbreak of Black death.[2] Shelter-in-place refers to the method of quarantining people where they are located at the time.[3] As all these measures curtail at an extent the civil liberties of the citizen, the emergence of discontent and clash with the imposing authority is not unusual. On March 24, 2020, as an attempt to limit the spread of SARS–CoV-2 pandemic, the Indian state abruptly imposed a country wide lockdown. The sudden uncertainty about future, loss of employment, uprooting of plans, and the feeling of loss of control tested the resilience of many. New viruses such as SARS-CoV-2 that have never been seen before, if without a recognized cure, are likely to cause widespread fear and panic. This anxiety could also be propagated through social media.[4] Fear thrives on ignorance and misinformation and during pandemics can lead to mass panic and uncontrollable behaviors, leading to destabilization of society.[5] A 2003 study conducted in Canada during the SARS quarantine revealed that increased prevalence of posttraumatic stress disorder symptoms and depressive symptoms were associated with longer duration of quarantine.[6] Several studies have showed a negative impact of isolation on the mental health of the affected in the form of higher scores for depression, anxiety, and anger. The duration of isolation has direct bearing on the severity of the symptoms; longer the period of isolation higher the prevalence and severity of symptoms.[7]

While stress in such situation may be inevitable, the impact on mental health of people is variable depending on the appraisal of the situation and the resources and coping strategies.[8] Authors describe coping styles in various ways, these include positive-negative or adaptive-maladaptive and problem focused-emotion focused. Carver[9] named a list of 14 coping strategies. Looking for alternatives and social support, avoidance, self-perseveration and positive appraisal, humor, and religion have been previously discussed in the context of virus epidemics.[8],[10],[11] While there are studies from some Asian and Western countries, the literature from India is scanty. In the prevailing pandemic situation, we intend to fill this gap with the hope that this addition to the Indian literature would act as a nidus for effective management and future research.

Aim and objectives

This study aims to know the impact on mental health and coping strategies used by internet users dealing with the COVID-19 pandemic and involved difficulties in India. The objectives of the study were (i) to assess the anxiety and depression among Indian internet users during the COVID-19 pandemic and (ii) to assess coping used by Indian internet users during the COVID-19 pandemic.


   Materials and Methods Top


Study population

Study population for the survey was Indian internet users. The survey was conducted using Google doc application.

Tools

The survey had three sections having items for demographic details in section one, items to screen anxiety, and depressive disorder in section two and items to assess coping in section three. Generalized Anxiety Disorder-7 (GAD-7) questionnaire, Patient Health Questionnaire-2 (PHQ-2), and brief COPE questionnaire were used in the survey.

  1. GAD-7 is a screening tool for anxiety disorders developed by Robert L. Spitzer and colleagues.[12] It is available in public domain. Originally developed for generalized anxiety disorder, this tool has good sensitivity and specificity for other types of anxiety disorders also. The scale has been validated and extensively used worldwide. A score of 5 or more on GAD-7 indicates generalized anxiety disorder to be of mild severity or more
  2. PHQ-2 is a two-item screening tool derived from larger PHQ and contains first two items of PHQ-9. The tool is developed by the same team as PHQ and GAD and is available in public domain.[13] A cutoff of 3 screens for major depression
  3. Coping was assessed using brief COPE questionnaire. The questionnaire was developed by Charles Carver and is available in public domain. The 28-item questionnaire assesses coping in 14 coping scales. It has been validated and has been translated in many languages including Hindi. Although Carver[9] did not group his COPE scales into adaptive and maladaptive, Janghel and Shrivastav[14] grouped theses scales into these dimensions.


Collection of data

The survey was circulated in closed groups using a social media chat platforms and e-mails. The responders in turn were further requested to circulate the survey among their social circles. The survey intended to reach out to Indian internet users across the country. The survey was open for responses for 120 hours between 4th and 9th April 2020.

Ethical considerations

The approval of the institutional ethics committee was taken for the study. The informed consent was obtained, and survey had an item for explicitly refusing the consent. The survey was designed to by anonymous, and no identifying details were required. Participants were provided e-mail of one investigator for any queries. The data generated would not be used for any other purpose other than purpose of this study.

Statistical analysis

Descriptive statistics were used to assess the sociodemographic characteristics, GAD-7, PHQ-2, and brief COPE scales. The group differences between screen positive and negatives for GAD-7 and PHQ-2 scales, and coping scales on brief COPE for demographic variables were analyzed using appropriate parametric or nonparametric tests for the quantitative variable and Chi-square/Mc-Nemar's test for categorical variables. The level of statistical significance was kept at P < 0.05 for all tests. Missing value imputation was not done. The data were analyzed using IBM SPSS Statistics v24 (Chicago, IL).


   Results Top


There were 330 responses to survey. Two responses were of minors, and two from users currently staying outside India, they were excluded to maintain homogeneity of responders. Three hundred and twenty-six responses were analyzed. Some responses had missing values, and they were not imputed. Respondents on an average were 37 years of age, stayed with a family of four and were in lockdown due to COVID-19 for 13 days during the study [Table 1]. Respondents were from 23 to 38 states and union territories, mostly Uttar Pradesh and Delhi. A majority lived in cities, had job, were postgraduates, lived in a nuclear family, and had access to their entertainment. Respondents represented various occupations, but health-care workers and uniformed personnel were more common. A little more than half (54.9%) claimed that they were part of government declared essential services. Majority respondents (81.3%) had no chronic illness but almost half (44.6%) had a family member with chronic illness. Clubbed together, 26 (8.0%) respondents were living with a psychiatric illness diagnosed in them or a family member. Thirty-five (10.7%) respondents claimed that the treatment of someone in family got disrupted due to the pandemic and lockdown. A majority (81.3%) claimed that they were not exposed to virus [Table 2].
Table 1: Descriptive statistics for demographic variables

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Table 2: Frequency table for demographic variables

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Assessment of anxiety and depression

Of the total 323 valid responses on GAD-7 scale, more than one-third (35.3%) screened positive for anxiety disorder with score more than 5. Majority of those screened positive, 70.1% had scores in a mild range, 22.8% in moderate, and 7.1% in severe range. Thirty-nine (12%) respondents scored above the cutoff for major depression [Table 3]. Respondents who were female, with history psychiatric illness in family including them, and those claimed treatment disruption were more likely to be screened positive for anxiety disorder. Respondents without work were more likely to be depressed than those had work [Table 4]. Persons screened positive for anxiety disorder were in lockdown for about 2 (1.7) days (P = 0.01) and those screened positive for major depression were about 3 (2.8) days (P = 0.003) longer in lockdown than others.
Table 3: Screening for anxiety disorder and major depression

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Table 4: In between group difference for screen positive anxiety and depressive disorder

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Assessment of coping

The mean scores on the coping scales of Carver[9] are given in [Table 5]. Acceptance, positive reframing, and positive coping were the most often employed strategies, while denial, self-blame, and substance use were least often employed. The score on adaptive coping scale[12] was significantly higher than the maladaptive coping (t = 16.16, P ≤ 0.001). While females used adaptive coping more frequently than males, respondents those engaged in essential services employed maladaptive coping less often. However, respondents scoring beyond cutoff for depressive or anxiety disorder used maladaptive coping more often than those who were screen negative [Table 6]. The scores on the coping scales differed significantly between demographic variables, their perceived status of exposure to virus, having a person with diagnosed illness in the family, and screen positive for anxiety disorder and major depression. Among the individual scales, females used instrumental support, emotional support positive reframing, acceptance, and religion than the males in the study. Respondents not having an employment used humor less often than those had work. Those who were involved in essential services used self-distraction and behavioral disengagement less often than those who were not on essential services. Health-care workers used emotional support and humor more often and denial less often than others. Those staying in nuclear family used religion more often than those staying in joint family, but living with family did not differ from those not living with family. Persons with a family member including themselves having a history of chronic physical or psychiatric illness used planning, humor, acceptance more often, and denial less often than those without such history, but those only with a history of psychiatric illness in family including them used self-distraction, venting, and acceptance more often than those without such history. Respondents who suspected themselves (yes and maybe) of being exposed to virus used planning, humor, acceptance along with instrumental support, and behavior disengagement more frequently than those who considered themselves not exposed. Respondents who were screened positive for anxiety disorder used active coping, denial, substance use, behavioral disengagement, planning, and self-blame more often than those screened negative. Those screened positive for major depression used all the coping strategies similar to those screened for anxiety disorder except for active coping more often than those who were screen negative [Table 7]. Age significantly correlated with planning (P = 0.04) and positive reframing scores (P = 0.03), while days in lockdown correlated with denial (P = 0.03).
Table 5: Mean scores on scales of brief COPE

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Table 6: T-test comparing generalized anxiety disorder-7, patient health questionnaire-2, and coping mean scores between groups

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Table 7: T-test comparing coping scales' mean scores between groups

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   Discussion Top


This study involves respondents from a large part of the country but mostly from more populous states and union territories. Majority of the cases during the study period were also reported for these regions. Sample comprised respondents from multiple walks of life, but the two professions that were in majority (health-care workers and unformed personnel) represents the people most likely to be in contact with disease. The study found that one-third of the respondents screened positive for an anxiety disorder, and 12% screened positive for a depressive disorder. These rates are much higher than those for general population in India.[15] One-third of those screened positive for anxiety scored in moderate-to-severe range. A recent multinational study also found similar rates of moderate-to-severe anxiety disorder and depressive disorder among health-care workers.[16] A review of studies on previous virus epidemics revealed the prevalence of anxiety disorder between 3.2% and 12.6% and depression between 3% and 73% in general population,[14] and more recent meta-analysis of studies on impact of COVID-19 on health-care workers found pooled prevalence of anxiety disorder to be 23·2% and of 22.8% for depression.[17] This study included respondents form different walk of life; however, health-care workers were in majority. Other than sample population methodological and cultural differences can explain the variation in rates of two disorders. Findings that females, with a history of mental illness in family and having lost the job due to the pandemic were more likely to have psychological consequences have been reported from other studies also.[17],[18],[19] The gender difference in response to stress is both biological and environmental including the cultural underpinnings. The loss of job adds onto difficulties and thus may tilt the result of primary and secondary appraisals toward the psychopathology.

Participants coped using adaptive coping more frequently then maladaptive, but those participants screened for anxiety and depressive disorder employed maladaptive coping more than the rest. Since more participants were screened negative, their coping strategy likely helped to effectively negotiate through the stressful period. However, in case of females, they used adaptive coping more than the male respondents. Since females were also more likely to be screened for anxiety disorder, and they used more adaptive coping to deal with anxiety, probably anxiety overwhelmed their coping. Participants in involved essential services were busy in their work, less likely to locked up, and faced the situation upfront and thus used maladaptive coping less often. Thus, it is evident that not using maladaptive coping was more effective than using adaptive coping. Individual coping scales varied with demographic variables, having an illness, and perceived status of exposure to the virus. The coping differences for demographic variables have been found in other studies.[11],[20] Older participants by virtue of their experience are more likely to plan and reframe as found in this study.

Limitations of the study

This study has certain limitations, foremost being the cross-sectional nature of the study, which limited us the understanding the effect of coping on the psychopathology. The Internet-based sample which did not represent all the states is restricted in its spread and thus cannot be greased. Another limitation with the sample is that it might have missed people with severe psychopathology as they might not use internet or like to respond to the survey.


   Conclusion Top


This study on Indian internet users found higher anxiety and depression during COVID-19 pandemic andlockdown. Both adaptive and maladaptive coping coping were used. Lesser use of maladaptive coping was associated with lesser anxiety and depression.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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