2.1 Survey design and instrument
The data used in the study was collected from a randomly selected sample of 1,275 mobile phone users in the six Class 1 metropolises of India— Bengaluru, Chennai, Delhi, Kolkata, Mumbai and Hyderabad. These cities had seen a high number of active cases (22.30% of all cases), and deaths due to COVID-19 (37.99% of all cases), and the shortage of medical facilities (Supplementary Table S1). Respondents were residents of the city, aged between 21 and 60 years—randomly selected from a list of mobile telephone users. The survey was undertaken during the months of August and September 2020, when the lockdown had ended, but COVID cases and deaths were rising rapidly.
Given the restrictions on social interaction, self-reported scales tailored to detect COVID-related mental health issues [like Fear of COVID-19 scale, Corona anxiety scale, COVID stress scale, and Obsession with COVID scale] are used to measure mental health problems.
“(S)elf-report scales might prove useful as they are short, easy to administer [through paper or a digital platform], and feasible to be used when in self-isolation or quarantine. However, these scales may have limited potential to measure outcome parameters of interventions as the findings may not be aligned with objective assessment and be more prone to response bias” [32].
Moreover, the new scales generally focus on one dimension, or at most two, and are unable to discern depression related to COVID-19, or incorporate negative socio-economic consequences of the pandemic has also been noted [33]. Finally, their reliability in different socio-cultural contexts, across different age groups, and exposure groups is not known [32].
Therefore, the survey was administered using the abridged shorter version of the DASS questionnaire, DASS-21 [28]. This is an accepted survey instrument used to measures mental health issues related to anxiety, depression and stress, with good internal consistency [34, 35]. It has been validated in different geographical and socio-cultural contexts, and for different socio-economic and demographic groups [36–38]. It has also been used in research related to SARS [39], and COVID-19 [10, 16, 21, 24, 40]. As anxiety, depression and stress symptoms are commonly reported during COVID-19 in the studies cited earlier, DASS-21 appears an appropriate survey instrument to measure mental health during the current pandemic.
2.3 Compliance with ethical standards
The Institutional Ethics Committee, Presidency University (the institute hosting the study) approved human ethical clearance to conduct the study (PU/IEC(H)/PROV CL/M-01/2020 dated 12/9/2020). The study did not use clinical trials or experiments; nor did it seek any sensitive information. The study and analysis was undertaken adhering to the Indian Council of Medical Research guidelines relevant for ethical research on humans: respect for participants, informed consent, voluntary participation with the right to withdraw, disclosure of funding sources, no harm to participants, avoidance of undue intrusion, no use of deception, preservation of anonymity, participant’s right to check and modify a transcript, confidentiality of personal matters and data protection. The authors have no conflict to declare. The study was not funded.
2.4 Sample profile
The sample profile is given in Table 1. The mean age of the respondents is 37 years, with most of them in the 21 to 50 years’ age group. Females outnumber male respondents marginally. About 40 percent of the respondents belong to the Hindu General category, while Hindus Other Backward Castes comprise 30 percent of the sample. About 81 per cent of the respondents are currently married. Only 15 percent per cent of the respondents are graduates. About 56 percent of the respondents are from households whose main earning member earns a fixed income; about a third of the respondents are from households with self-employed main earners. The average monthly per capita expenditure is about USD 80, and median value is USD 59. About 68 percent respondents have monthly per capita expenditure less than USD 80. While 40 per cent of the respondents reside in bungalow type houses, 17 per cent are slum dwellers. 40 percent of the respondents belong to the households comprises of 4 members, while more than one-fourth of the respondents are from the households consisting of less than 4 members. About 27 per cent of the households have an aged member (viz. aged 60 years or more). Every third respondent has a family member, relative or friend who had COVID, while one out of ten respondents have suffered bereavement due to COVID.
2.5 Statistical analysis
Estimates of Cronbach’s alpha indicate a high level of reliability of responses. The value of alpha is 0.8947 for anxiety, 0.8802 for stress, and 0.8720 for depression. The statistical analysis of the data starts with an exploratory analysis of the mean scales across different socio-demographic groups to identify vulnerable groups. It is followed by a confirmatory analysis using the SEM model. It is a type of confirmatory factor analysis used to measure the value of latent constructs (measurement model); in addition, the model identifies the exogenous causes of the latent variables (structural values). Thus, the observed variables (Y) result from the latent factors (F), while the latent factors themselves are caused by other exogenous variables denoted by X. The model may be described using a path diagram (Figure 1).
The model is described as follows:
Fk´1 = bYm´1 + e [1]
Fk´1 = dXn´1 + v [2]
when b and d are matrices of appropriate dimensions, and e and v are vectors of error terms. Equation 1 describes the relationship between the latent variable and the observed indicators and is called the measurement model. As the ‘indicators’ are ordered categorical variables, the observed indicators have been linked to the latent dimension using an ordered probit model. It is depicted on the right-hand side of Figure 1. The structural part expresses the relationship between the exogenous determinants of the latent variables. It is portrayed on the left-hand side of the path diagram and is described in equation 2.
The vector Y gives the responses to appropriate questions in the DASS-21 schedule. The vector X comprises of the following exogenous variables:
Age of respondents, gender of respondent, whether currently married, socio-religious identity, whether respondent has at least graduate level of education, household size, employment status of main earning member, whether resides in owned house, residence type, and whether faced COVID cases.
Occupation of respondent (or main earning member) and per capita expenditure were not included as they were highly correlated with education, employment status and residential ownership and type. The details of variables are given in Supplementary materials.