case study about covid 19 pandemic

• Research article
• Open access
• Published: 04 June 2021

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews

• Israel Júnior Borges do Nascimento 1 , 2 ,
• Dónal P. O’Mathúna 3 , 4 ,
• Thilo Caspar von Groote 5 ,
• Hebatullah Mohamed Abdulazeem 6 ,
• Ishanka Weerasekara 7 , 8 ,
• Ana Marusic 9 ,
• Livia Puljak   ORCID: orcid.org/0000-0002-8467-6061 10 ,
• Vinicius Tassoni Civile 11 ,
• Irena Zakarija-Grkovic 9 ,
• Tina Poklepovic Pericic 9 ,
• Alvaro Nagib Atallah 11 ,
• Santino Filoso 12 ,
• Nicola Luigi Bragazzi 13 &
• Milena Soriano Marcolino 1

On behalf of the International Network of Coronavirus Disease 2019 (InterNetCOVID-19)

BMC Infectious Diseases volume  21 , Article number:  525 ( 2021 ) Cite this article

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Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO’s Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes.

Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as “critically low”. Identified symptoms of COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%) and gastrointestinal complaints (5–9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%.

Conclusions

In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Peer Review reports

The spread of the “Severe Acute Respiratory Coronavirus 2” (SARS-CoV-2), the causal agent of COVID-19, was characterized as a pandemic by the World Health Organization (WHO) in March 2020 and has triggered an international public health emergency [ 1 ]. The numbers of confirmed cases and deaths due to COVID-19 are rapidly escalating, counting in millions [ 2 ], causing massive economic strain, and escalating healthcare and public health expenses [ 3 , 4 ].

The research community has responded by publishing an impressive number of scientific reports related to COVID-19. The world was alerted to the new disease at the beginning of 2020 [ 1 ], and by mid-March 2020, more than 2000 articles had been published on COVID-19 in scholarly journals, with 25% of them containing original data [ 5 ]. The living map of COVID-19 evidence, curated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), contained more than 40,000 records by February 2021 [ 6 ]. More than 100,000 records on PubMed were labeled as “SARS-CoV-2 literature, sequence, and clinical content” by February 2021 [ 7 ].

Due to publication speed, the research community has voiced concerns regarding the quality and reproducibility of evidence produced during the COVID-19 pandemic, warning of the potential damaging approach of “publish first, retract later” [ 8 ]. It appears that these concerns are not unfounded, as it has been reported that COVID-19 articles were overrepresented in the pool of retracted articles in 2020 [ 9 ]. These concerns about inadequate evidence are of major importance because they can lead to poor clinical practice and inappropriate policies [ 10 ].

Systematic reviews are a cornerstone of today’s evidence-informed decision-making. By synthesizing all relevant evidence regarding a particular topic, systematic reviews reflect the current scientific knowledge. Systematic reviews are considered to be at the highest level in the hierarchy of evidence and should be used to make informed decisions. However, with high numbers of systematic reviews of different scope and methodological quality being published, overviews of multiple systematic reviews that assess their methodological quality are essential [ 11 , 12 , 13 ]. An overview of systematic reviews helps identify and organize the literature and highlights areas of priority in decision-making.

In this overview of systematic reviews, we aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Methodology

Research question.

This overview’s primary objective was to summarize and critically appraise systematic reviews that assessed any type of primary clinical data from patients infected with SARS-CoV-2. Our research question was purposefully broad because we wanted to analyze as many systematic reviews as possible that were available early following the COVID-19 outbreak.

Study design

We conducted an overview of systematic reviews. The idea for this overview originated in a protocol for a systematic review submitted to PROSPERO (CRD42020170623), which indicated a plan to conduct an overview.

Overviews of systematic reviews use explicit and systematic methods for searching and identifying multiple systematic reviews addressing related research questions in the same field to extract and analyze evidence across important outcomes. Overviews of systematic reviews are in principle similar to systematic reviews of interventions, but the unit of analysis is a systematic review [ 14 , 15 , 16 ].

We used the overview methodology instead of other evidence synthesis methods to allow us to collate and appraise multiple systematic reviews on this topic, and to extract and analyze their results across relevant topics [ 17 ]. The overview and meta-analysis of systematic reviews allowed us to investigate the methodological quality of included studies, summarize results, and identify specific areas of available or limited evidence, thereby strengthening the current understanding of this novel disease and guiding future research [ 13 ].

A reporting guideline for overviews of reviews is currently under development, i.e., Preferred Reporting Items for Overviews of Reviews (PRIOR) [ 18 ]. As the PRIOR checklist is still not published, this study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 statement [ 19 ]. The methodology used in this review was adapted from the Cochrane Handbook for Systematic Reviews of Interventions and also followed established methodological considerations for analyzing existing systematic reviews [ 14 ].

Approval of a research ethics committee was not necessary as the study analyzed only publicly available articles.

Eligibility criteria

Systematic reviews were included if they analyzed primary data from patients infected with SARS-CoV-2 as confirmed by RT-PCR or another pre-specified diagnostic technique. Eligible reviews covered all topics related to COVID-19 including, but not limited to, those that reported clinical symptoms, diagnostic methods, therapeutic interventions, laboratory findings, or radiological results. Both full manuscripts and abbreviated versions, such as letters, were eligible.

No restrictions were imposed on the design of the primary studies included within the systematic reviews, the last search date, whether the review included meta-analyses or language. Reviews related to SARS-CoV-2 and other coronaviruses were eligible, but from those reviews, we analyzed only data related to SARS-CoV-2.

No consensus definition exists for a systematic review [ 20 ], and debates continue about the defining characteristics of a systematic review [ 21 ]. Cochrane’s guidance for overviews of reviews recommends setting pre-established criteria for making decisions around inclusion [ 14 ]. That is supported by a recent scoping review about guidance for overviews of systematic reviews [ 22 ].

Thus, for this study, we defined a systematic review as a research report which searched for primary research studies on a specific topic using an explicit search strategy, had a detailed description of the methods with explicit inclusion criteria provided, and provided a summary of the included studies either in narrative or quantitative format (such as a meta-analysis). Cochrane and non-Cochrane systematic reviews were considered eligible for inclusion, with or without meta-analysis, and regardless of the study design, language restriction and methodology of the included primary studies. To be eligible for inclusion, reviews had to be clearly analyzing data related to SARS-CoV-2 (associated or not with other viruses). We excluded narrative reviews without those characteristics as these are less likely to be replicable and are more prone to bias.

Scoping reviews and rapid reviews were eligible for inclusion in this overview if they met our pre-defined inclusion criteria noted above. We included reviews that addressed SARS-CoV-2 and other coronaviruses if they reported separate data regarding SARS-CoV-2.

Information sources

Nine databases were searched for eligible records published between December 1, 2019, and March 24, 2020: Cochrane Database of Systematic Reviews via Cochrane Library, PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Sciences, LILACS (Latin American and Caribbean Health Sciences Literature), PDQ-Evidence, WHO’s Global Research on Coronavirus Disease (COVID-19), and Epistemonikos.

The comprehensive search strategy for each database is provided in Additional file 1 and was designed and conducted in collaboration with an information specialist. All retrieved records were primarily processed in EndNote, where duplicates were removed, and records were then imported into the Covidence platform [ 23 ]. In addition to database searches, we screened reference lists of reviews included after screening records retrieved via databases.

Study selection

All searches, screening of titles and abstracts, and record selection, were performed independently by two investigators using the Covidence platform [ 23 ]. Articles deemed potentially eligible were retrieved for full-text screening carried out independently by two investigators. Discrepancies at all stages were resolved by consensus. During the screening, records published in languages other than English were translated by a native/fluent speaker.

Data collection process

We custom designed a data extraction table for this study, which was piloted by two authors independently. Data extraction was performed independently by two authors. Conflicts were resolved by consensus or by consulting a third researcher.

We extracted the following data: article identification data (authors’ name and journal of publication), search period, number of databases searched, population or settings considered, main results and outcomes observed, and number of participants. From Web of Science (Clarivate Analytics, Philadelphia, PA, USA), we extracted journal rank (quartile) and Journal Impact Factor (JIF).

We categorized the following as primary outcomes: all-cause mortality, need for and length of mechanical ventilation, length of hospitalization (in days), admission to intensive care unit (yes/no), and length of stay in the intensive care unit.

The following outcomes were categorized as exploratory: diagnostic methods used for detection of the virus, male to female ratio, clinical symptoms, pharmacological and non-pharmacological interventions, laboratory findings (full blood count, liver enzymes, C-reactive protein, d-dimer, albumin, lipid profile, serum electrolytes, blood vitamin levels, glucose levels, and any other important biomarkers), and radiological findings (using radiography, computed tomography, magnetic resonance imaging or ultrasound).

We also collected data on reporting guidelines and requirements for the publication of systematic reviews and meta-analyses from journal websites where included reviews were published.

Quality assessment in individual reviews

Two researchers independently assessed the reviews’ quality using the “A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2)”. We acknowledge that the AMSTAR 2 was created as “a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both” [ 24 ]. However, since AMSTAR 2 was designed for systematic reviews of intervention trials, and we included additional types of systematic reviews, we adjusted some AMSTAR 2 ratings and reported these in Additional file 2 .

Adherence to each item was rated as follows: yes, partial yes, no, or not applicable (such as when a meta-analysis was not conducted). The overall confidence in the results of the review is rated as “critically low”, “low”, “moderate” or “high”, according to the AMSTAR 2 guidance based on seven critical domains, which are items 2, 4, 7, 9, 11, 13, 15 as defined by AMSTAR 2 authors [ 24 ]. We reported our adherence ratings for transparency of our decision with accompanying explanations, for each item, in each included review.

One of the included systematic reviews was conducted by some members of this author team [ 25 ]. This review was initially assessed independently by two authors who were not co-authors of that review to prevent the risk of bias in assessing this study.

Synthesis of results

For data synthesis, we prepared a table summarizing each systematic review. Graphs illustrating the mortality rate and clinical symptoms were created. We then prepared a narrative summary of the methods, findings, study strengths, and limitations.

For analysis of the prevalence of clinical outcomes, we extracted data on the number of events and the total number of patients to perform proportional meta-analysis using RStudio© software, with the “meta” package (version 4.9–6), using the “metaprop” function for reviews that did not perform a meta-analysis, excluding case studies because of the absence of variance. For reviews that did not perform a meta-analysis, we presented pooled results of proportions with their respective confidence intervals (95%) by the inverse variance method with a random-effects model, using the DerSimonian-Laird estimator for τ 2 . We adjusted data using Freeman-Tukey double arcosen transformation. Confidence intervals were calculated using the Clopper-Pearson method for individual studies. We created forest plots using the RStudio© software, with the “metafor” package (version 2.1–0) and “forest” function.

Managing overlapping systematic reviews

Some of the included systematic reviews that address the same or similar research questions may include the same primary studies in overviews. Including such overlapping reviews may introduce bias when outcome data from the same primary study are included in the analyses of an overview multiple times. Thus, in summaries of evidence, multiple-counting of the same outcome data will give data from some primary studies too much influence [ 14 ]. In this overview, we did not exclude overlapping systematic reviews because, according to Cochrane’s guidance, it may be appropriate to include all relevant reviews’ results if the purpose of the overview is to present and describe the current body of evidence on a topic [ 14 ]. To avoid any bias in summary estimates associated with overlapping reviews, we generated forest plots showing data from individual systematic reviews, but the results were not pooled because some primary studies were included in multiple reviews.

Our search retrieved 1063 publications, of which 175 were duplicates. Most publications were excluded after the title and abstract analysis ( n = 860). Among the 28 studies selected for full-text screening, 10 were excluded for the reasons described in Additional file 3 , and 18 were included in the final analysis (Fig. 1 ) [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Reference list screening did not retrieve any additional systematic reviews.

PRISMA flow diagram

Characteristics of included reviews

Summary features of 18 systematic reviews are presented in Table 1 . They were published in 14 different journals. Only four of these journals had specific requirements for systematic reviews (with or without meta-analysis): European Journal of Internal Medicine, Journal of Clinical Medicine, Ultrasound in Obstetrics and Gynecology, and Clinical Research in Cardiology . Two journals reported that they published only invited reviews ( Journal of Medical Virology and Clinica Chimica Acta ). Three systematic reviews in our study were published as letters; one was labeled as a scoping review and another as a rapid review (Table 2 ).

All reviews were published in English, in first quartile (Q1) journals, with JIF ranging from 1.692 to 6.062. One review was empty, meaning that its search did not identify any relevant studies; i.e., no primary studies were included [ 36 ]. The remaining 17 reviews included 269 unique studies; the majority ( N = 211; 78%) were included in only a single review included in our study (range: 1 to 12). Primary studies included in the reviews were published between December 2019 and March 18, 2020, and comprised case reports, case series, cohorts, and other observational studies. We found only one review that included randomized clinical trials [ 38 ]. In the included reviews, systematic literature searches were performed from 2019 (entire year) up to March 9, 2020. Ten systematic reviews included meta-analyses. The list of primary studies found in the included systematic reviews is shown in Additional file 4 , as well as the number of reviews in which each primary study was included.

Population and study designs

Most of the reviews analyzed data from patients with COVID-19 who developed pneumonia, acute respiratory distress syndrome (ARDS), or any other correlated complication. One review aimed to evaluate the effectiveness of using surgical masks on preventing transmission of the virus [ 36 ], one review was focused on pediatric patients [ 34 ], and one review investigated COVID-19 in pregnant women [ 37 ]. Most reviews assessed clinical symptoms, laboratory findings, or radiological results.

Systematic review findings

The summary of findings from individual reviews is shown in Table 2 . Overall, all-cause mortality ranged from 0.3 to 13.9% (Fig. 2 ).

A meta-analysis of the prevalence of mortality

Clinical symptoms

Seven reviews described the main clinical manifestations of COVID-19 [ 26 , 28 , 29 , 34 , 35 , 39 , 41 ]. Three of them provided only a narrative discussion of symptoms [ 26 , 34 , 35 ]. In the reviews that performed a statistical analysis of the incidence of different clinical symptoms, symptoms in patients with COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%), gastrointestinal disorders, such as diarrhea, nausea or vomiting (5.0–9.0%), and others (including, in one study only: dizziness 12.1%) (Figs. 3 , 4 , 5 , 6 , 7 , 8 and 9 ). Three reviews assessed cough with and without sputum together; only one review assessed sputum production itself (28.5%).

A meta-analysis of the prevalence of fever

A meta-analysis of the prevalence of cough

A meta-analysis of the prevalence of dyspnea

A meta-analysis of the prevalence of fatigue or myalgia

A meta-analysis of the prevalence of headache

A meta-analysis of the prevalence of gastrointestinal disorders

A meta-analysis of the prevalence of sore throat

Diagnostic aspects

Three reviews described methodologies, protocols, and tools used for establishing the diagnosis of COVID-19 [ 26 , 34 , 38 ]. The use of respiratory swabs (nasal or pharyngeal) or blood specimens to assess the presence of SARS-CoV-2 nucleic acid using RT-PCR assays was the most commonly used diagnostic method mentioned in the included studies. These diagnostic tests have been widely used, but their precise sensitivity and specificity remain unknown. One review included a Chinese study with clinical diagnosis with no confirmation of SARS-CoV-2 infection (patients were diagnosed with COVID-19 if they presented with at least two symptoms suggestive of COVID-19, together with laboratory and chest radiography abnormalities) [ 34 ].

Therapeutic possibilities

Pharmacological and non-pharmacological interventions (supportive therapies) used in treating patients with COVID-19 were reported in five reviews [ 25 , 27 , 34 , 35 , 38 ]. Antivirals used empirically for COVID-19 treatment were reported in seven reviews [ 25 , 27 , 34 , 35 , 37 , 38 , 41 ]; most commonly used were protease inhibitors (lopinavir, ritonavir, darunavir), nucleoside reverse transcriptase inhibitor (tenofovir), nucleotide analogs (remdesivir, galidesivir, ganciclovir), and neuraminidase inhibitors (oseltamivir). Umifenovir, a membrane fusion inhibitor, was investigated in two studies [ 25 , 35 ]. Possible supportive interventions analyzed were different types of oxygen supplementation and breathing support (invasive or non-invasive ventilation) [ 25 ]. The use of antibiotics, both empirically and to treat secondary pneumonia, was reported in six studies [ 25 , 26 , 27 , 34 , 35 , 38 ]. One review specifically assessed evidence on the efficacy and safety of the anti-malaria drug chloroquine [ 27 ]. It identified 23 ongoing trials investigating the potential of chloroquine as a therapeutic option for COVID-19, but no verifiable clinical outcomes data. The use of mesenchymal stem cells, antifungals, and glucocorticoids were described in four reviews [ 25 , 34 , 35 , 38 ].

Laboratory and radiological findings

Of the 18 reviews included in this overview, eight analyzed laboratory parameters in patients with COVID-19 [ 25 , 29 , 30 , 32 , 33 , 34 , 35 , 39 ]; elevated C-reactive protein levels, associated with lymphocytopenia, elevated lactate dehydrogenase, as well as slightly elevated aspartate and alanine aminotransferase (AST, ALT) were commonly described in those eight reviews. Lippi et al. assessed cardiac troponin I (cTnI) [ 25 ], procalcitonin [ 32 ], and platelet count [ 33 ] in COVID-19 patients. Elevated levels of procalcitonin [ 32 ] and cTnI [ 30 ] were more likely to be associated with a severe disease course (requiring intensive care unit admission and intubation). Furthermore, thrombocytopenia was frequently observed in patients with complicated COVID-19 infections [ 33 ].

Chest imaging (chest radiography and/or computed tomography) features were assessed in six reviews, all of which described a frequent pattern of local or bilateral multilobar ground-glass opacity [ 25 , 34 , 35 , 39 , 40 , 41 ]. Those six reviews showed that septal thickening, bronchiectasis, pleural and cardiac effusions, halo signs, and pneumothorax were observed in patients suffering from COVID-19.

Quality of evidence in individual systematic reviews

Table 3 shows the detailed results of the quality assessment of 18 systematic reviews, including the assessment of individual items and summary assessment. A detailed explanation for each decision in each review is available in Additional file 5 .

Using AMSTAR 2 criteria, confidence in the results of all 18 reviews was rated as “critically low” (Table 3 ). Common methodological drawbacks were: omission of prospective protocol submission or publication; use of inappropriate search strategy: lack of independent and dual literature screening and data-extraction (or methodology unclear); absence of an explanation for heterogeneity among the studies included; lack of reasons for study exclusion (or rationale unclear).

Risk of bias assessment, based on a reported methodological tool, and quality of evidence appraisal, in line with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method, were reported only in one review [ 25 ]. Five reviews presented a table summarizing bias, using various risk of bias tools [ 25 , 29 , 39 , 40 , 41 ]. One review analyzed “study quality” [ 37 ]. One review mentioned the risk of bias assessment in the methodology but did not provide any related analysis [ 28 ].

This overview of systematic reviews analyzed the first 18 systematic reviews published after the onset of the COVID-19 pandemic, up to March 24, 2020, with primary studies involving more than 60,000 patients. Using AMSTAR-2, we judged that our confidence in all those reviews was “critically low”. Ten reviews included meta-analyses. The reviews presented data on clinical manifestations, laboratory and radiological findings, and interventions. We found no systematic reviews on the utility of diagnostic tests.

Symptoms were reported in seven reviews; most of the patients had a fever, cough, dyspnea, myalgia or muscle fatigue, and gastrointestinal disorders such as diarrhea, nausea, or vomiting. Olfactory dysfunction (anosmia or dysosmia) has been described in patients infected with COVID-19 [ 43 ]; however, this was not reported in any of the reviews included in this overview. During the SARS outbreak in 2002, there were reports of impairment of the sense of smell associated with the disease [ 44 , 45 ].

The reported mortality rates ranged from 0.3 to 14% in the included reviews. Mortality estimates are influenced by the transmissibility rate (basic reproduction number), availability of diagnostic tools, notification policies, asymptomatic presentations of the disease, resources for disease prevention and control, and treatment facilities; variability in the mortality rate fits the pattern of emerging infectious diseases [ 46 ]. Furthermore, the reported cases did not consider asymptomatic cases, mild cases where individuals have not sought medical treatment, and the fact that many countries had limited access to diagnostic tests or have implemented testing policies later than the others. Considering the lack of reviews assessing diagnostic testing (sensitivity, specificity, and predictive values of RT-PCT or immunoglobulin tests), and the preponderance of studies that assessed only symptomatic individuals, considerable imprecision around the calculated mortality rates existed in the early stage of the COVID-19 pandemic.

Few reviews included treatment data. Those reviews described studies considered to be at a very low level of evidence: usually small, retrospective studies with very heterogeneous populations. Seven reviews analyzed laboratory parameters; those reviews could have been useful for clinicians who attend patients suspected of COVID-19 in emergency services worldwide, such as assessing which patients need to be reassessed more frequently.

All systematic reviews scored poorly on the AMSTAR 2 critical appraisal tool for systematic reviews. Most of the original studies included in the reviews were case series and case reports, impacting the quality of evidence. Such evidence has major implications for clinical practice and the use of these reviews in evidence-based practice and policy. Clinicians, patients, and policymakers can only have the highest confidence in systematic review findings if high-quality systematic review methodologies are employed. The urgent need for information during a pandemic does not justify poor quality reporting.

We acknowledge that there are numerous challenges associated with analyzing COVID-19 data during a pandemic [ 47 ]. High-quality evidence syntheses are needed for decision-making, but each type of evidence syntheses is associated with its inherent challenges.

The creation of classic systematic reviews requires considerable time and effort; with massive research output, they quickly become outdated, and preparing updated versions also requires considerable time. A recent study showed that updates of non-Cochrane systematic reviews are published a median of 5 years after the publication of the previous version [ 48 ].

Authors may register a review and then abandon it [ 49 ], but the existence of a public record that is not updated may lead other authors to believe that the review is still ongoing. A quarter of Cochrane review protocols remains unpublished as completed systematic reviews 8 years after protocol publication [ 50 ].

Rapid reviews can be used to summarize the evidence, but they involve methodological sacrifices and simplifications to produce information promptly, with inconsistent methodological approaches [ 51 ]. However, rapid reviews are justified in times of public health emergencies, and even Cochrane has resorted to publishing rapid reviews in response to the COVID-19 crisis [ 52 ]. Rapid reviews were eligible for inclusion in this overview, but only one of the 18 reviews included in this study was labeled as a rapid review.

Ideally, COVID-19 evidence would be continually summarized in a series of high-quality living systematic reviews, types of evidence synthesis defined as “ a systematic review which is continually updated, incorporating relevant new evidence as it becomes available ” [ 53 ]. However, conducting living systematic reviews requires considerable resources, calling into question the sustainability of such evidence synthesis over long periods [ 54 ].

Research reports about COVID-19 will contribute to research waste if they are poorly designed, poorly reported, or simply not necessary. In principle, systematic reviews should help reduce research waste as they usually provide recommendations for further research that is needed or may advise that sufficient evidence exists on a particular topic [ 55 ]. However, systematic reviews can also contribute to growing research waste when they are not needed, or poorly conducted and reported. Our present study clearly shows that most of the systematic reviews that were published early on in the COVID-19 pandemic could be categorized as research waste, as our confidence in their results is critically low.

Our study has some limitations. One is that for AMSTAR 2 assessment we relied on information available in publications; we did not attempt to contact study authors for clarifications or additional data. In three reviews, the methodological quality appraisal was challenging because they were published as letters, or labeled as rapid communications. As a result, various details about their review process were not included, leading to AMSTAR 2 questions being answered as “not reported”, resulting in low confidence scores. Full manuscripts might have provided additional information that could have led to higher confidence in the results. In other words, low scores could reflect incomplete reporting, not necessarily low-quality review methods. To make their review available more rapidly and more concisely, the authors may have omitted methodological details. A general issue during a crisis is that speed and completeness must be balanced. However, maintaining high standards requires proper resourcing and commitment to ensure that the users of systematic reviews can have high confidence in the results.

Furthermore, we used adjusted AMSTAR 2 scoring, as the tool was designed for critical appraisal of reviews of interventions. Some reviews may have received lower scores than actually warranted in spite of these adjustments.

Another limitation of our study may be the inclusion of multiple overlapping reviews, as some included reviews included the same primary studies. According to the Cochrane Handbook, including overlapping reviews may be appropriate when the review’s aim is “ to present and describe the current body of systematic review evidence on a topic ” [ 12 ], which was our aim. To avoid bias with summarizing evidence from overlapping reviews, we presented the forest plots without summary estimates. The forest plots serve to inform readers about the effect sizes for outcomes that were reported in each review.

Several authors from this study have contributed to one of the reviews identified [ 25 ]. To reduce the risk of any bias, two authors who did not co-author the review in question initially assessed its quality and limitations.

Finally, we note that the systematic reviews included in our overview may have had issues that our analysis did not identify because we did not analyze their primary studies to verify the accuracy of the data and information they presented. We give two examples to substantiate this possibility. Lovato et al. wrote a commentary on the review of Sun et al. [ 41 ], in which they criticized the authors’ conclusion that sore throat is rare in COVID-19 patients [ 56 ]. Lovato et al. highlighted that multiple studies included in Sun et al. did not accurately describe participants’ clinical presentations, warning that only three studies clearly reported data on sore throat [ 56 ].

In another example, Leung [ 57 ] warned about the review of Li, L.Q. et al. [ 29 ]: “ it is possible that this statistic was computed using overlapped samples, therefore some patients were double counted ”. Li et al. responded to Leung that it is uncertain whether the data overlapped, as they used data from published articles and did not have access to the original data; they also reported that they requested original data and that they plan to re-do their analyses once they receive them; they also urged readers to treat the data with caution [ 58 ]. This points to the evolving nature of evidence during a crisis.

Our study’s strength is that this overview adds to the current knowledge by providing a comprehensive summary of all the evidence synthesis about COVID-19 available early after the onset of the pandemic. This overview followed strict methodological criteria, including a comprehensive and sensitive search strategy and a standard tool for methodological appraisal of systematic reviews.

In conclusion, in this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all the reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic could be categorized as research waste. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards to provide patients, clinicians, and decision-makers trustworthy evidence.

Availability of data and materials

All data collected and analyzed within this study are available from the corresponding author on reasonable request.

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Acknowledgments

We thank Catherine Henderson DPhil from Swanscoe Communications for pro bono medical writing and editing support. We acknowledge support from the Covidence Team, specifically Anneliese Arno. We thank the whole International Network of Coronavirus Disease 2019 (InterNetCOVID-19) for their commitment and involvement. Members of the InterNetCOVID-19 are listed in Additional file 6 . We thank Pavel Cerny and Roger Crosthwaite for guiding the team supervisor (IJBN) on human resources management.

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IJBN conceived the research idea and worked as a project coordinator. DPOM, TCVG, HMA, IW, AM, LP, VTC, IZG, TPP, ANA, SF, NLB and MSM were involved in data curation, formal analysis, investigation, methodology, and initial draft writing. All authors revised the manuscript critically for the content. The author(s) read and approved the final manuscript.

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Supplementary Information

Additional file 1: appendix 1..

Search strategies used in the study.

Additional file 2: Appendix 2.

Adjusted scoring of AMSTAR 2 used in this study for systematic reviews of studies that did not analyze interventions.

Additional file 3: Appendix 3.

List of excluded studies, with reasons.

Additional file 4: Appendix 4.

Table of overlapping studies, containing the list of primary studies included, their visual overlap in individual systematic reviews, and the number in how many reviews each primary study was included.

Additional file 5: Appendix 5.

A detailed explanation of AMSTAR scoring for each item in each review.

Additional file 6: Appendix 6.

List of members and affiliates of International Network of Coronavirus Disease 2019 (InterNetCOVID-19).

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Borges do Nascimento, I.J., O’Mathúna, D.P., von Groote, T.C. et al. Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews. BMC Infect Dis 21 , 525 (2021). https://doi.org/10.1186/s12879-021-06214-4

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Original research article, how teachers conduct online teaching during the covid-19 pandemic: a case study of taiwan.

• Department of Science Communication, National Pingtung University, Pingtung, Taiwan

Although online teaching has been encouraged for many years, the COVID-19 pandemic has promoted it on a large scale. During the COVID-19 pandemic, students at all levels (college, secondary school, and elementary school) were unable to attend school. To maintain student learning, most schools have adopted online teaching. Therefore, the purpose of this study was to explore the design of online teaching activities and online teaching processes adopted by teachers at all levels during the pandemic. Online questionnaires were administered to teachers in Taiwan who had conducted online teaching (including during the formal suspension of classes or simulation exercises) due to the pandemic. According to a quantitative analysis and lag sequential analysis, the instructional behaviors most frequently performed by teachers were roll calls, lectures with a presentation screen, in-class task (assignment) allocation, and whole-class synchronous video-/audio-based discussion. Thus, there were six common significant sequential behaviors among teachers at all levels that were categorized into the four instructional stages of identifying the teaching environment, teaching the class, discussing and evaluating learning effectiveness. College teachers reminded students of some matters first and then called the roll after the students went online. Secondary school teachers were more likely to arrange practical or experimental courses and to use synchronous and asynchronous interactive activities. Finally, elementary school teachers were more likely to use homemade videos and share their screens for teaching and to arrange a large variety of teaching interactions. The differences among colleges, secondary schools, and elementary schools were identified, and suggestions were made accordingly.

Introduction

Since 1990, Internet-based distance teaching has become a global trend, and software, hardware and educational training have been evolving. Nouns related to e-learning, such as online learning, distance teaching, digital learning, mobile learning and recent massive open online courses (MOOCs), have shown a trend of learning via the Internet. However, despite active promotion by governments, there are still many limitations to the online educational environment from teaching and learning perspectives ( Meskhi et al., 2019 ; Sadeghi, 2019 ), such as the support of the administrative system, the establishment of a network bandwidth and teachers’ willingness to record e-Learning materials.

Since the first report of coronavirus disease 2019 (COVID-19) in Wuhan (China) in December 2019, COVID-19 has rapidly spread worldwide ( Zhu et al., 2020 ). The World Health Organization (WHO) declared a public health emergency of international concern on January 30, 2020 and named the disease COVID-19 on February 11, 2020. On March 11, 2020, the WHO declared COVID-19 a global pandemic ( Singhal, 2020 ; World Health Organization, 2020 ).

Due to the respiratory illness caused by COVID-19, many countries have suspended all types of face-to-face activities, including in-person education. The COVID-19 pandemic has forced many changes in most life domains to meet the repercussions of the pandemic control measures, and the education sector was no exception. In many countries, colleges, secondary schools and elementary schools have adopted the strategy of online education during the pandemic. As a result, teachers and students have had to quickly alter their teaching methods, regardless of whether they were experienced in and prepared for online education. Because of this situation, a proper term has appeared in the academic domain: emergency remote education.

Online education-related studies and models have been promoted for years ( Sun and Chen, 2016 ). Before the COVID-19 pandemic, most of these studies were focused on colleges, while teachers and students in elementary and secondary schools remained inexperienced in emergency remote education ( Lestari and Gunawan, 2020 ). For example, Taiwan has promoted digital course certification at the university level for many years, and universities have also supported teachers in recording e-learning materials. Therefore, university teachers are more experienced in online teaching. However, in primary and secondary schools, digital teaching plays only a supplementary role. The pre-epidemic model is for students to go to classrooms. Therefore, teachers in primary and secondary schools have insufficient experience in switching to online teaching.

In response to COVID-19, schools at all levels needed an immediate shift towards online education, which can be both an opportunity and a challenge ( Toquero, 2020 ). Therefore, some studies have been conducted to discuss emergency remote education during the COVID-19 pandemic. For example, Crawford et al. (2020) investigated 20 countries’ responses to the COVID-19 epidemic. They pointed out that the response to higher education is diverse, including nonresponse, campus social isolation strategies, and rapid response to fully online courses. Watermeyer et al. (2020) reported a survey from 1,148 academics working in universities in the United Kingdom. They suggested that online migration is engendering significant dysfunctionality and disturbance to their pedagogical roles and their personal lives. Loima (2020) compared socio educational policies and arguments in Sweden and Finland during the COVID-19 pandemic. The results showed that Swedish and Finnish policy obscured mandates and restricted information. However, remote learning was successful in epidemiologic and curricular senses in Finnish. Basilaia and Kvavadze (2020) conducted a case study in Georgia. The Google Meet platform was implemented for online education with 950 students. The results indicated that the quick transition to the online form of education went successful and that gained experience can be used in the future. Putra et al. (2020) visited 10 websites in Indonesia to explore students’ learning experiences during the COVID-19 pandemic. The results showed that student hardship in learning from home caused a lack of learning resources, such as not accessing the Internet and parents’ ability to support their children’s learning. In Cyprus, Souleles et al. (2020) believed that e-learning is not an add-on to existing teaching and learning practices and that disciplinary differences need to be considered. The provision of hurriedly set up workshops to enhance the skill gaps of teachers, although it is a necessary step, cannot replace the need for sustained training in both the pedagogical and technical areas. In Norway, Langford and Damsa (2020) discovered some phenomena, such as the Zoom revolution, a significant level of interactive online learning, innovations for involuntary teaching reform, collegial competence building and self-help, technological challenges and pedagogical insecurity. In Beijing, when the outbreak prevented people from going to school, the scholars of Peking University proposed the following five specific teaching strategies for online education in pandemic circumstances: 1) a high relevance between online instructional design and student learning; 2) the effective delivery of online instructional information; 3) adequate support provided by faculty and teaching assistants to students; 4) high-quality participation to improve the breadth and depth of students’ learning; and 5) contingency plans to address unexpected incidents on online education platforms ( Bao, 2020 ). In addition, many scholars in medical education have explored the challenges and future of online education in their own field. For example, Goh and Sandars (2020) indicated that major changes have been taking place in global medical education and that it is necessary to strengthen technological innovation to maintain teaching; they proposed that the use of artificial intelligence for adaptive learning and virtual reality might be future trends in medical education.

In addition to the abovementioned studies on overall education, there have been more studies that explore students’ opinions during emergency remote education. Abbasi et al. (2020) reported that when students were unable to go to school because of the epidemic, they did not like online learning as much as face-to-face teaching. Thus, school administrative departments and teachers should take the necessary measures to improve online educational environments. Based on a survey of 77 medical students in their classroom situations, Agarwal and Kaushik (2020) argued that students believed that online courses altered their normal procedures, saved a large amount of time and made it easy for them to obtain teaching materials. The main barriers to learning were the number of participants and technical failures during class conversations. Owusu-Fordjour et al. (2020) investigated online learning among 214 college students and found that the pandemic had a negative effect on their learning because many of them were not used to learning effectively on their own. As most of the students in this region could not access the Internet and lacked the technical knowledge of Internet devices, the learning platforms that were used also posed a challenge for them.

Most of the above studies on students’ opinions focused on college education because college students’ abilities for self-regulated learning in online education are better than those of primary and secondary students because of their age ( Heo and Han, 2018 ). However, when the pandemic began, all schools faced the challenge of switching to emergency remote education. Some studies have explored learning issues in elementary and secondary schools during the outbreak. For example, Sintema (2020) noted that Zambian primary and secondary schools enabled teachers and students to have classes via mobile phones and tablets by implementing e-learning and smart revision portals while increasing the number of mobile devices available for use. The study found that these teaching and learning methods helped teachers deliver teaching materials and students to be capable of self-regulated learning during the pandemic. In addition, Fauzi and Khusuma (2020) surveyed 45 elementary school students and identified problems in implementing online teaching, including 1) the availability of facilities, 2) network and Internet usage, 3) the planning, implementation, and evaluation of learning, and 4) collaboration with parents. The authors expected that online learning would be helpful to teachers during the COVID-19 pandemic, but their results indicated poor outcomes of online learning, with 80% of teachers reporting that they felt dissatisfied with online education.

Study Objectives

According to the abovementioned studies on the COVID-19 pandemic, teachers and students were forced to conduct online education regardless of their level of preparation for it. Most of the recent studies have investigated students’ feelings about online education and learning effectiveness, but there has been little discussion of teachers’ design of teaching activities when they had to switch to online teaching due to the pandemic. Accordingly, this study explored how teachers designed their teaching activities when they switched to online teaching due to the pandemic or how they conducted online teaching in the form of exercises to provide a reference for the future promotion of online education. As a result, the first objective of this study is to discuss teachers’ design of online teaching activity during the COVID-19 pandemic.

Moreover, our knowledge of teachers’ online teaching activities is based on online teaching activities in normal conditions. In addition, teaching activity plans are sequential ( Brown and Green, 2018 ). For example, Gagne’s model of instructional design includes 1) gaining attention, 2) informing the learner of the objective, 3) stimulating the recall of prerequisite learning, 4) presenting the stimulus material, 5) providing learning guidance, 6) eliciting the performance, 7) providing feedback, 8) assessing the performance, and 9) enhancing retention and transfer ( Khadjooi et al. (2011) . The second objective of this study is to explore which activities were carried out first and last and the order of teachers’ teaching activities. Thus, to understand the teaching activities adopted by teachers during the COVID-19 pandemic and the implementation of these teaching activities, this study used a lag sequential analysis to inform the discussion on this topic.

During the COVID-19 pandemic, students at all levels (college, secondary school and elementary school) were unable to attend school. Online teaching can continue to maintain learning activities when everyone is not going out. Therefore, to maintain students’ learning, most schools have adopted online teaching. In addition, for students of different ages, e.g., colleges, secondary schools and elementary schools, the teaching behaviors taken by teachers will be different ( Kennan et al., 2018 ). Understanding how teachers engage in online teaching behaviors at this emergency remote learning time can serve as a reference for the future promotion of e-learning. This study discusses teachers’ design of online teaching activity at all levels during the pandemic. The study explores the following two research questions:

What are the online teaching activities adopted by teachers due to the suspension of classroom teaching due to the COVID-19 pandemic? and

What are the similarities and differences among teachers from colleges, secondary schools and elementary schools in the design of their online teaching activity processes?

Methods and Materials

Data collection and participants.

This study mainly investigates teachers who had conducted online education (including during the formal suspension of classes and simulation exercises) because of the pandemic. Convenience sampling was adopted. Although many courses might have been changed to online teaching at the time that the teachers answered the questions, the study questionnaire asked about the teaching activity design of only one course. Data were collected from May 20 to June 30, 2020, by using a web-based questionnaire with a cross-sectional design. A total of 270 teachers answered the questionnaires, and 223 of the responses were valid. There were 23 college teachers (10.3%), 51 secondary school teachers (22.9%) and 149 elementary school teachers (66.8%).

In this study, a questionnaire on online teaching activities was developed based on the research purpose and some studies (i.e., Nilson and Goodson, 2017 ; Trust and Pektas, 2018 ; Sharoff, 2019 ). The questionnaire consisted of three major parts, namely, basic data (sex male and female), age (below 30 years old, 31–40 years old, 41–50 years old, 51–60 years old and over 61 years old), the served school (college or university, middle or high school, and elementary school), the years of teaching experience, online teaching experience (Were you experienced in online teaching prior to the pandemic (frequently, occasionally and never), Why did you conduct online teaching? (already in use, class suspension due to medical diagnosis and simulation exercises), and in most cases, which of the following methods do you choose for online teaching?) and the teaching process (synchronous teaching, asynchronous teaching and blended teaching). According to the various online teaching platforms and systems used (e.g., Google Classroom, iCAN, iLMS, Microsoft Teams, Moodle, Sunnet LMS, Adobe Connect, Cisco WebEx, CyberLink U Meeting, Google Meet, Jitsi Meet, JoinNet, LINE Chat, Zoom, YouTube Live broadcast, Facebook Live broadcast and Zuvio), the teaching processes were analyzed, summarized and then divided into the 4 categories of teaching (A), learning interaction (B), learning effectiveness (C) and others (D). After the online teaching activity questionnaire was prepared, three experts in online college education, one elementary school teacher, and one online education administrator of the education agency were invited to assist in the review of the questionnaire. The survey questionnaire was refined according to the suggestions received through the experts’ review. The instructional behaviors that comprise the teaching process are listed below.

 A1 Lecturing–presentation screen. A2 Lecturing–blackboard. A3 Sharing a screen with computer software. A4 Playing videos made by teachers. A5 Playing videos made by others. A6 Practical (experimental) demonstration.

B Learning Interaction

 B1 Whole-class synchronous text-based discussion. B2 Whole-class asynchronous text-based discussion. B3 Whole-class synchronous video-/audio-based discussion. B4 Whole-class asynchronous video-/audio-based discussion. B5 Whole-group synchronous text-based discussion. B6 Whole-group asynchronous text-based discussion. B7 Whole-group synchronous video-/audio-based discussion. B8 Whole-group asynchronous video-/audio-based discussion. B9 Whole-class whiteboard interaction. B10 Whole-group whiteboard interaction. B11 Student self-practice. B12 Operation by remote control. B13 Data collection and collation.

C Learning Effectiveness

 C1 In-class study experience. C2 In-class task (assignment) allocation. C3 In-class online test. C4 In-class online questionnaire. C5 In-class peer evaluation. C6 In-class work submission. C7 In-class assignment/work report. C8 After-class study experience. C9 After-class task (assignment) allocation. C10 After-class online test. C11 After-class online questionnaire. C12 After-class peer evaluation/voting. C13 After-class work submission.

 D1 Roll call D2 Inquiry about the status of hardware and software. D3 Reminders of other noncourse matters. D4 Others.

Data Analysis

In this study, descriptive statistics were used to analyze the basic data, the online teaching experience and the first research question. The second research question was analyzed through a lag sequential analysis ( Bakeman and Gottman, 1997 ). Lag sequential analysis ( Bakeman and Gottman, 1997 ) is used not only to explore a continuous sequence of behavioral coding categories (namely, an online teaching process) in which an initial behavioral coding category is followed by a subsequent category but also to visualize behavioral patterns. Researchers have mainly applied this method to the analysis of education issues. For example, Lin et al. (2020) developed a scaffolding-based collaborative problem-solving (CPS) learning environment to improve students’ learning in CPS activities. According to the study results, the learning performance was significantly better for the scaffolding mind tool group than for the study sheet group, and the scaffolding mind tool group showed more diverse cognitive process transitions in their behavioral patterns. Zarzour et al. (2020) investigated the behavioral patterns of students by using eBooks on Facebook for learning. The experimental results indicated significant behavioral learning sequences and revealed that the behaviors of liking, commenting, and sharing posts with peers showed the most significant differences between the students with higher and lower engagement. Wang and Liu (2020) discussed teachers’ current online teaching and students’ interaction and collaborative knowledge construction. According to the results, the design and organization of learning materials and the facilitation of discourse promoted students’ interaction, reduced the number of peripheral students, and supported students’ collaborative knowledge construction.

The following were the five steps in the lag sequential analysis: 1) calculating the number of transitions among the behavioral codes to obtain the transition frequency table; 2) calculating the conditional probability of the transitions among the codes based on the above sequential frequency matrix to produce the sequential transition conditional probability; 3) calculating the expected value of the overall transition process among the codes based on the sequential frequency matrix; 4) verifying whether all sequences were significantly continuous one-by-one based on the Z-score values of the transition frequency calculated from the above three matrices (adjusted residuals table); and 5) drawing the sequence transition association diagram with nodes that represent all coding behaviors connected by arrows for further inferential analysis.

Results and Discussion

Basic data and online teaching experience.

The Google online questionnaire was adopted in this study, and all questions must be answered to be valid. As shown in Table 1 , a total of 223 valid questionnaires were collected in this study. In terms of sex, there were 100 males (44.8%) and 123 females (55.2%), and there was virtually no difference in the numbers of males and females. Therefore, this study is not affected by gender differences. Regarding age, there were 23 people (13.3%) under 30 years old, 24 people (10.8%) between 31 and 40 years, 57 people (25.6%) between 41 and 50 years, 106 people (47.5%) between 51 and 60 years, and 36 people (16.1%) aged 61 years or over. Most of the respondents were between 41 and 60 years old. In the quartile of age, Q1 was 31–40 years, and Q2 (median) and Q3 were 41–50 years. Regarding the years of teaching experience, there were 12 teachers (5.4%) with less than 1 year of service, 26 teachers (11.7%) with 1–5 years of service, 21 teachers (9.4%) with 6–10 years of service, 54 teachers (24.2%) with 11–15 years of service, 57 teachers (25.6%) with 16–20 years of service, and 53 teachers (23.8%) with more than 21 years of service. In the quartile of teaching experience, Q1 is 1–5 years, Q2 (median) is 16–20 years, and Q3 is more than 21 years. Most teachers were found to have many years of experience. At the school level, there were 23 college teachers (10.3%), 51 secondary school teachers (22.9%), and 149 elementary school teachers (66.8%). Thus, most of the respondents were elementary school teachers, followed by secondary school teachers.

TABLE 1 . Participants’ characteristics, including their online teaching experience.

Then, the study examined whether teachers were experienced in online teaching prior to the pandemic. Fourteen teachers (6.3%) had frequently engaged in online teaching, 79 (35.4%) had engaged in it occasionally, and 130 (58.3%) had never engaged in it, which shows that more than half of the teachers had no experience in online teaching. As a result, the reason why online teaching had been adopted was explored. In total, 21 teachers had been teaching online prior to the pandemic (9.4%), seven taught online due to a medical diagnosis (3.1%), and 195 taught online as a part of simulation exercises (87.4%); these findings show that the primary reason for switching to online teaching was simulation exercises, as the COVID-19 pandemic in Taiwan was well controlled. Regarding the modes frequently used in online teaching, 89 teachers (39.9%) used synchronous teaching (teachers and students go online at the same time to carry out teaching and learning activities), 65 teachers (29.1%) used asynchronous teaching (teachers upload teaching materials to the network platform, and students can watch them online within a specified time and carry out learning activities), and 69 teachers (30.9%) used blended teaching (teaching and learning activities that combine both synchronous and asynchronous modes); thus, similar proportions of the teachers used the three teaching modes.

Teaching Activities

The 223 teachers who returned valid questionnaires had a total of 1,310 instructional behaviors, with an average of 5.87 instructional behaviors for each teacher. Table 2 shows the overall instructional behaviors, and the number and percentage of instructional behaviors in elementary schools, secondary schools, and colleges.

TABLE 2 . Number and percentage of various instructional behaviors.

Overall, there were 329 data points (25.11%) for teaching (A), 340 data points (25.95%) for learning interaction (B), 383 data points (29.24%) for learning effectiveness (C), and 258 data points (19.69%) for others (D). The proportion of other instructional behaviors was similar to but slightly lower than the proportions of the remaining three teaching categories. Among the four teaching categories, the top four behaviors were roll call (D1) with 132 data points (10.08%), lecturing with a presentation screen (A1) with 124 data points (9.47%), in-class task (assignment) allocation (C2) with 104 data points (7.94%), and whole-class synchronous video-/audio-based discussion (B3) with 103 data points (7.86%). Thus, the most common behavior in each category was teaching behavior.

Then, the four teaching categories were analyzed from an overall perspective. In teaching (A), lecturing with a presentation screen (A1) was the most frequently used ( N = 124, 9.47%), followed by sharing a screen with computer software (A3) (N = 101, 7.71%); this shows that most teachers frequently lectured with a presentation screen and shared their computer screens in online teaching. In learning interaction (B), whole-class synchronous video-/audio-based discussion (B3) was the most frequently used ( N = 103, 7.86%), followed by student self-practice (B11) ( N = 82, 6.26%); this indicates that the teachers often conducted a whole-class synchronous discussion after teaching and allowed students to become familiar with the teaching content through their own practice. In addition, we also found that the teachers conducted more activities in entire classes than in groups. Although group learning is a common teaching activity in classroom teaching, in the online teaching environment, group interaction is rarely adopted by teachers because of the limitations imposed by the functional design of the learning platform or system. In learning effectiveness (C), the most common and second-most common instructional behaviors both concerned task (assignment) allocation, including class-task (assignment) allocation (C2) with 104 data points (7.94%), and after-class task (assignment) allocation (C9) with 69 data points (5.27%). By comparing all behaviors in class and after class, we found that the frequency of all in-class behaviors ( N = 224, 17.11%) was larger than the frequency of after-class behaviors ( N = 159, 12.14%), which suggests that the teachers mostly evaluated teaching effectiveness in class. Finally, in the other category (D), the most common mode was roll call (D1) with 132 data points (10.08%), followed by inquiry about the status of hardware and software (D2) with 74 data points (5.65%). These two items were important preclass activities in online teaching, although they do not take much time in classroom teaching.

Finally, the study explored the similarities and differences among colleges, secondary schools, and elementary schools in the four categories. In terms of teaching (A), we found that lecturing with a presentation screen (A1) was the most frequently used, followed by sharing a screen with computer software (A3), regardless of the learning stage. In terms of playing videos, we found that most videos played in colleges were made by teachers (A4), while the videos played in secondary and elementary schools were made by others (A5); this shows that college teachers were more likely to make course videos for students to watch. Practical (experimental) demonstration (A6) was the least used. Although physical education courses and experimental courses still existed in the curriculum, the teachers seldom performed practice or experiments in the online teaching environment. In terms of learning interaction (B), we found that whole-class synchronous video-/audio-based discussion (B3) was the most frequently used, regardless of the learning stage. Moreover, unlike student practice (B11), whole-class synchronous text-based discussion (B1) was frequently used in colleges and secondary schools but was less frequently used in elementary schools, while whole-class whiteboard interaction (B9) was frequently used in elementary schools; this indicates that the teachers were more likely to arrange synchronous text-based discussion activities for older students. Finally, we found that data collection and collation (B13), a common activity in online teaching, was used in some secondary and elementary schools but not in colleges. In terms of learning effectiveness (C), we found that task (assignment) allocation (C2 and C9) was the most frequently used, regardless of the learning stage. Second, assignment and work reports (C7 and C13) were commonly used by college teachers for evaluation, online tests (C3 and C10) were commonly used by secondary and elementary teachers for evaluation, and there was almost no difference in their use between online teaching and the current situation in classroom teaching. In terms of the other category (D), based on the proportions of teachers who used the behaviors, we found that the most common behaviors were roll calls (D1), inquiries about the status of hardware and software (D2), and reminders of other noncourse matters (D3), regardless of the learning stage. These behaviors were important for online teaching, but the questionnaire did not dedicate many questions to these behaviors.

Teaching Behavioral Sequence

During the lag sequential analysis, the adjusted residuals table was calculated, where the columns represent initial behaviors, and the rows signify the behaviors that occurred immediately after the behaviors listed in the columns. A Z-score greater than 1.96 indicated that the sequence was significant. In this study, there were 49, 58, and 104 significant behavioral sequences for colleges, secondary schools and elementary schools, respectively (as shown in the Supplementary Appendix ). With the 36 instructional behaviors examined in this study, there were many significant behavioral sequences in each learning stage. To facilitate the discussion, the common significant behavioral sequences of colleges, secondary schools, and elementary schools were first extracted, and six significant behavioral sequences were identified in total. Second, to compare the differences among colleges, secondary schools, and elementary schools in the teaching process, significant behavioral sequences with Z-score values greater than five were discussed. There were 11, 10, and 15 significant behavioral sequences with Z-score values greater than five in colleges, secondary schools and elementary schools, respectively. The values shown in Table 3 are the Z-scores.

TABLE 3 . Significant behavioral sequences (similarities and differences Z-score>5).

There were six common significant behavioral sequences in colleges, secondary schools, and elementary schools ( Figure 1 ). The six significant behavioral sequences were divided into four stages. The first stage included roll calls and the confirmation of an effective online teaching environment (D1→D2). The next stage was teaching the class. The common teaching methods were presentation (A1) and screen sharing (A3). The next stage after teaching included text-based synchronous discussion (A1→B5 and A3→B1). The final stage was the evaluation of learning effectiveness (B5→C7 and C3→C4). Overall, the common significant behavioral sequences in colleges, secondary schools and elementary schools, namely, identifying the teaching environment, teaching the class, discussing and evaluating learning effectiveness, were similar to the usual teaching processes.

FIGURE 1 . Overall behavioral transfer diagram.

Then, the characteristics of the teaching processes in colleges, secondary schools and elementary schools were compared based on the significant behavioral sequences with Z-score values greater than 5. To provide a basis for comparison, the abovementioned phases, i.e., 1) identifying the teaching environment, 2) teaching the class, 3) discussing and 4) evaluating learning effectiveness, were used for discussion. First, colleges ( Figure 2 ) were more likely than secondary and elementary schools to use the following sequence: reminders for students of other noncurriculum matters (D3) → roll call (D1). This may be because, compared with secondary and elementary school teachers, college teachers are more likely to call roll after reminding students of matters during class and waiting for students to go online. This not only presents the actual situation of the physical classroom but also represents the teacher’s differences in class management for students of different ages. In the teaching class stage, there was one common behavioral sequence between college teachers and elementary school teachers, namely, lecturing with a blackboard (A2) → practical (experimental) demonstration (A6). This may be because some experimental course teachers are used to lecture with a blackboard and directly filme experimental courses with cameras. In the discussing stage, college teachers engaged in less interactive learning behaviors than secondary and elementary school teachers, but most of their behaviors were carried out in groups (A5→B6, B5→B10, B10→B3). Finally, in the evaluating learning effectiveness stage, college teachers had more diversified evaluation methods, including practice, tests, and questionnaires. Moreover, college teachers arranged many in-class and after-class evaluations (C1→C12, C3→C12 and C4→C12).

FIGURE 2 . Behavioral transfer diagram for colleges.

Second, in secondary schools ( Figure 3 ), teachers were more likely to arrange practical or experimental courses and then carry out interactive activities such as discussions or questionnaires (A6→B2, A6→B4 and A6→C11). In conducting interactive activities, teachers in secondary schools were more likely to use synchronous and asynchronous methods than teachers in colleges or elementary schools. Finally, in the stage of evaluating learning effectiveness, secondary school teachers had more diversified evaluation methods than college or elementary school teachers, including tests, questionnaires, and practice.

FIGURE 3 . Behavioral transfer diagram for secondary schools.

In elementary schools ( Figure 4 ), teachers were more likely to use homemade videos and share their screens while teaching and then conduct discussions (A3→B3, A5→B2, A5→B7). The teaching interactions arranged by elementary school teachers were diversified, and discussions containing audio and text were conducted with synchronous and asynchronous methods. Elementary school teachers, similar to college and secondary school teachers, used a variety of evaluation methods. In addition, elementary school teachers arranged many in-class evaluations, and after-class assignments, which is similar to general classroom teaching.

FIGURE 4 . Behavioral transfer diagram for elementary schools.

Discussion and Conclusion

During the COVID-19 pandemic, students at all levels (colleges, secondary schools, and elementary schools) were unable to attend school, and most schools switched to online teaching. To understand the design of online teaching activities among teachers at all levels, online questionnaires were adopted in this study to investigate teachers in Taiwan who had conducted online teaching due to the pandemic. There were 223 valid questionnaires.

The first objective was to explore teachers’ online teaching activities when classroom teaching was suspended due to COVID-19. Based on the results of the frequencies of behaviors in the teaching, learning interaction, learning effectiveness and other categories, the top four instructional behaviors were roll calls, lecturing with a presentation screen, in-class task (assignment) allocation and whole-class synchronous video-/audio-based discussion. Then, the study explored the similarities and differences among colleges, secondary schools, and elementary schools in the four categories. In terms of teaching, lecturing with a presentation screen was the most frequently used, regardless of the learning stage. In terms of playing videos, most videos played in colleges were made by teachers, while most videos played in secondary and elementary schools were made by others. In terms of learning interaction, we found that whole-class synchronous video-/audio-based discussion was the most frequently used, regardless of the learning stage. In addition, teachers’ arrangement of synchronous text-based discussions depended on the learning level. In terms of learning effectiveness, task (assignment) allocation was the most frequent behavior, regardless of the learning stage. Second, assignments and work reports were commonly used by college teachers for evaluation, while teachers in secondary and elementary schools were more likely to use online tests for evaluation. Finally, in terms of the other category, we found that roll calls and inquiries about the learning environment, such as the status of hardware and software, were necessary for online teaching, regardless of the learning stage.

Overall, more time was spent on roll calls and inquiries about the status of hardware and software in online teaching than in classroom teaching. This means that teachers’ technical capabilities for online teaching, students’ familiarity with digital platforms, and the software and hardware assistance provided by the school’s information center will all affect the quality of e-learning. Moreover, in terms of teaching, interaction and evaluation, the arrangement of these activities among teachers at all levels was slightly different from the arrangement of these activities in classroom teaching, and appropriate teaching activities could be designed according to the online teaching environment. Despite the limitations of online teaching platforms, online learning activities can still be carried out.

The second objective of this study was to explore the similarities and differences among college, secondary school and elementary school teachers in the design of the online teaching activity process. According to the sequential behavioral analysis, the common significant behavioral sequences of colleges, secondary school and elementary schools were divided into 1) roll calls and identification of the teaching environment, 2) teaching through presentation and screen demonstration, 3) synchronous text-based discussion, and 4) an effectiveness evaluation. Overall, the common significant behavioral sequences of colleges, secondary schools and elementary schools were similar to the usual teaching processes. In terms of the characteristics, some college teachers reminded students of some matters first and then called the roll after students went online. During class, some teachers in experimental or practical courses were used to lecture with a blackboard, and directly filme experimental courses with cameras. Moreover, college teachers engaged in less interactive learning behaviors, but most of their behaviors were carried out in groups. Second, secondary school teachers were more likely to arrange practical or experimental courses and to use synchronous and asynchronous interactive activities. Finally, elementary school teachers were more likely to use homemade videos and share their screens for teaching and to arrange a large variety of teaching interactions; in addition, discussions containing audio and text were conducted with both synchronous and asynchronous methods.

Overall, colleges, secondary schools, and elementary schools had common significant sequential behaviors, including roll calls and the identification of the teaching environment, teaching through presentation and screen sharing, synchronous text-based discussion and an effectiveness evaluation. Moreover, college, secondary, and elementary school teachers had similar characteristics in the design of their teaching activity processes. In addition to these similar characteristics, college, secondary, and elementary school teachers also have some different characteristics. These different characteristics show that teachers at different stages of learning vary in their teaching strategies. These differences, in addition to showing the current teaching situation, can also provide scholars with information for related follow-up research.

According to the conclusions generated based on the descriptive analysis and lag sequential analysis, the following suggestions can be made.

Despite the small proportion of online practical and experimental courses, as evidenced by the observed online instructional behaviors, such courses are arranged in classroom teaching. It is suggested that when relevant, teachers should consider in advance how to respond to challenges in implementing practical and experimental courses in online teaching.

Discussion is more important in the online teaching environment than in general classroom teaching ( Wu, 2016 ). This study found that whole-class synchronous video-/audio-based discussion was the most frequently used method. Thus, whether activities are conducted as a class or in groups and whether synchronous or asynchronous discussion is used, teachers should improve the online discussion layout and their online leadership skills ( Tseng et al., 2019 ).

In classroom teaching, problem-based learning (PBL) courses are often arranged, which require students to collect and collate data through the Internet ( Dolmans et al., 2016 ). However, in this study, the rate of data collection and collation was low, even in the online education environment, but the activities of data collection and collation in the online learning environment are more suitable for adoption. Therefore, it is suggested that teachers should design activities of data collection and collation for more diversified teaching activities.

Due to the pandemic, people have been restricted in their ability to leave home. Therefore, in addition to the synchronous activities in class during teaching time, it is suggested that teachers arrange after-class asynchronous activities so that students can carry out learning activities when they cannot go out.

In classroom teaching, it does not take much time to call roll or manage hardware and software. However, the two behaviors are important in the online teaching environment. Thus, both teachers and learning platforms or system developers should think about how to reduce the time spent on roll calls and the management of hardware and software.

In terms of the research limitations and suggestions for future studies, this study took Taiwan’s teachers as an example; it is suggested that cross-country comparisons be carried out in future studies. Second, this study mainly discussed the situations, similarities and differences of colleges, secondary schools and elementary schools in the teaching activities and processes affected by the pandemic. However, teaching activities are also influenced by the course that is being taught. Thus, it is suggested that future researchers base their discussions on various types of courses. Finally, teachers’ preparation for online teaching affects the quality of online education ( Hung, 2016 ), which was not analyzed in this study. Therefore, it is suggested that future researchers compare the differences in teachers’ experiences with online teaching.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

The author contributed to the conception of the idea, implementing and analyzing the experimental results, and writing the manuscript.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2021.675434/full#supplementary-material

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Keywords: COVID-19, e-learning, online teaching, lag sequential analysis (LSA), emergency remote education (ERE)

Citation: Wu S-Y (2021) How Teachers Conduct Online Teaching During the COVID-19 Pandemic: A Case Study of Taiwan. Front. Educ. 6:675434. doi: 10.3389/feduc.2021.675434

Received: 03 March 2021; Accepted: 06 May 2021; Published: 28 May 2021.

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*Correspondence: Sheng-Yi Wu, [email protected]

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• Published: 24 March 2022

Health care workers’ experiences during the COVID-19 pandemic: a scoping review

• Souaad Chemali 1 ,
• Almudena Mari-Sáez 1 ,
• Charbel El Bcheraoui 2 &
• Heide Weishaar   ORCID: orcid.org/0000-0003-1150-0265 2  

Human Resources for Health volume  20 , Article number:  27 ( 2022 ) Cite this article

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COVID-19 has challenged health systems worldwide, especially the health workforce, a pillar crucial for health systems resilience. Therefore, strengthening health system resilience can be informed by analyzing health care workers’ (HCWs) experiences and needs during pandemics. This review synthesizes qualitative studies published during the first year of the COVID-19 pandemic to identify factors affecting HCWs’ experiences and their support needs during the pandemic. This review was conducted using the Joanna Briggs Institute methodology for scoping reviews. A systematic search on PubMed was applied using controlled vocabularies. Only original studies presenting primary qualitative data were included.

161 papers that were published from the beginning of COVID-19 pandemic up until 28th March 2021 were included in the review. Findings were presented using the socio-ecological model as an analytical framework. At the individual level, the impact of the pandemic manifested on HCWs’ well-being, daily routine, professional and personal identity. At the interpersonal level, HCWs’ personal and professional relationships were identified as crucial. At the institutional level, decision-making processes, organizational aspects and availability of support emerged as important factors affecting HCWs’ experiences. At community level, community morale, norms, and public knowledge were of importance. Finally, at policy level, governmental support and response measures shaped HCWs’ experiences. The review identified a lack of studies which investigate other HCWs than doctors and nurses, HCWs in non-hospital settings, and HCWs in low- and lower middle income countries.

This review shows that the COVID-19 pandemic has challenged HCWs, with multiple contextual factors impacting their experiences and needs. To better understand HCWs’ experiences, comparative investigations are needed which analyze differences across as well as within countries, including differences at institutional, community, interpersonal and individual levels. Similarly, interventions aimed at supporting HCWs prior to, during and after pandemics need to consider HCWs’ circumstances.

Conclusions

Following a context-sensitive approach to empowering HCWs that accounts for the multitude of aspects which influence their experiences could contribute to building a sustainable health workforce and strengthening health systems for future pandemics.

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Introduction

The COVID-19 pandemic has put health systems worldwide under pressure and tested their resilience. The World Health Organization (WHO) acknowledges health workforce as one of the six building blocks of health systems [ 1 ]. Health care workers (HCWs) are key to a health system’s ability to respond to external shocks such as outbreaks and as first responders are often the hardest hit by these shocks [ 2 ]. Therefore, interventions supporting HCWs are key to strengthening health systems resilience (ibid). To develop effective interventions to support this group, a detailed understanding of how pandemics affect HCWs is needed.

Several recent reviews [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ] focus on HCWs’ experiences during COVID-19 and the impact of the pandemic on HCWs’ well-being, including their mental health [ 3 , 7 , 8 , 11 , 12 , 13 , 14 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Most of these reviews refer to psychological scales measurements to provide quantifiable information on HCWs’ well-being and mental health [ 8 , 13 , 14 , 19 , 21 , 22 , 23 , 24 , 25 , 28 ]. While useful in assessing the scale of the problem, such quantitative measures are insufficient in capturing the breadth of HCWs’ experiences and the factors that impact such experiences. The added value of qualitative studies is in understanding the complex experiences of HCWs during COVID-19 and the contextual factors that influence them [ 29 ].

This paper reviews qualitative studies published during the first year of the pandemic to investigate what is known about HCWs’ experiences during COVID-19 and the factors and support needs associated with those experiences. By presenting HCWs’ perspectives on the pandemic, the scoping review provides the much-needed evidence base for interventions that can help strengthen HCWs and alleviate the pressures they experience during pandemics.

The review follows the Joanna Briggs Institute (JBI) process and guideline on conducting scoping reviews [ 30 ]. JBI updated guidelines identify scoping reviews as the most suitable choice to explore the breadth of literature on a topic, by mapping and summarizing available evidence [ 30 ]. Scoping reviews are also suitable to address knowledge gaps and provide insightful input for decision-making [ 30 ]. The review also applies the PRISMA checklist guidance on reporting literature reviews [ 31 ].

Information sources

A systematic search was conducted on PubMed database between the 9th and 28th of March 2021.

Search strategy

Drawing on Shaw et al. [ 32 ] and WHO [ 33 ], the search strategy used a controlled vocabulary of index terms including Medical Subject Headings (Mesh) of the keywords and synonyms “COVID-19”, “HCWs”, and “qualitative”. Keywords were combined using the Boolean operator “AND” (see Additional file 1 ).

Eligibility criteria

The population of interest included all types of HCWs, independent of geography and settings. Only original studies were included in the review. Papers further had to (1) report primary qualitative data, (2) report on HCWs’ experiences and perceptions during COVID-19, and (3) be available as full texts in English, German, French, Spanish or Arabic, i.e., in a language that could be reviewed by one or several of the authors. Studies focusing solely on HCWs’ assessment of newly introduced modes of telemedicine during COVID-19 were excluded from the review as their clear emphasis on coping with technical challenges deviated from the review’s focus on HCWs’ personal and professional experiences during the pandemic.

Selection process

The initial search yielded 3976 papers. All papers were screened and assessed against the eligibility criteria by one researcher (SC) to identify relevant studies. A random 25% sample of all papers was additionally screened by a second researcher (HW). Any uncertainty or inconsistency regarding inclusion were resolved by discussing the respective articles ( n  = 76) among the authors.

Data collection process

Based on the research question, an initial data extraction form was developed, independently piloted on ten papers by SC and HW and finalised to include information on: (1) author(s), (2) year of publication, (3) type of HCW, (5) study design, (6) sample size, (7) topic of investigation, (8) data collection tool(s), (9) analytical approach, (10) period of data collection, (11) country, (12) income level according to World Bank [ 34 ], (13) context, and (14) main findings related to experiences, factors and support needs. Using the final extraction form, all articles were extracted by SC, with the exception of four German articles (which were extracted by HW), one Spanish and one French article (which were extracted by AMS). As far as applicable, the quality of the included articles was appraised using the JBI critical appraisal tool for qualitative research [ 35 ].

Synthesis methods

The socio-ecological model originally developed by Brofenbrenner was adapted as a framework to analyze and present the findings [ 36 , 37 , 38 ]. The model aims to understand the interconnectedness and dynamics between personal and contextual factors in shaping human development and experiences [ 36 , 38 ]. The model was chosen, because it accounts for the multifaceted interactions between individuals and their environment and is thus suited to capture the different dimensions of HCWs’ experiences, the factors associated with those experiences as well as the sources of support identified. The five socio-ecological levels (individual, interpersonal, institutional, community and policy) of the model served as a framework for analysis and were used to categorise the main themes that were identified in the scoping review as relevant to HCWs’ experiences. The process of identifying the sub-themes was conducted by SC using an excel extraction sheet, in which the main findings were captured and mapped against the socio-ecological framework.

Study selection

The selection process and the number of papers found, screened and included are illustrated in a PRISMA flow diagram (Fig.  1 ). A total of 161 papers were included in the review (see Additional file 2 ). Table 1 lists the included studies based on study characteristics, including type of HCW, healthcare setting, income level of countries studied and data collection tools.

PRISMA flow diagram

Study characteristics

Included papers investigated various types of HCWs. The most investigated type were nurses, followed by doctors/physicians. Medical and nursing students were also studied frequently, while only a small number of studies focused on other professions, e.g., community health workers, therapists and managerial staff. A third of all studies studied multiple HCWs, rather than targeting single professions. The majority of papers investigated so-called “frontline staff”, i.e., HCWs who engaged directly with patients who were suspected or confirmed to be infected with COVID-19. Fewer studies focused on non-frontline staff, and some explored both frontline and non-frontline staff.

Around two-thirds of all papers studied HCWs’ experiences in high-income countries, notably the USA, followed by the UK. Many papers also focused on HCWs in upper-middle income countries, with almost half of them conducted in China. Few papers investigated HCWs in lower-middle income countries, including India, Zimbabwe, Pakistan, Nigeria, and Senegal. Finally, one paper focused on HCWs in Ethiopia, a low-income country. A couple of studies presented data from multiple countries of different income levels, and one study investigating HCWs in Palestine could not be categorised. Overall, the USA was the most studied and China the second most studied geographical location (see Additional file 3 ). Hospitals were by far the most investigated healthcare settings, whereas outpatient settings, including primary care, pharmacies, homes care, nursing homes, healthcare facilities in prisons and schools as well as clinics, were investigated to a considerably lesser extent. Several studies covered more than one setting.

All studies applied a cross-sectional study design, with 54% published in 2020, and the remainder in 2021. A range of qualitative data collection methods were applied, with interviews being by far the most prominent one, followed by open-ended questionnaires. Focus groups and a few other methods including social media, online platforms or recording systems submissions, observations and open reflections were used with rare frequencies. The sample size in studies using interviews ranged between 6 and 450 interviewees. The sample size in studies using Focus Group Discussions (FGDs) ranged between 7 and 40 participants. Further information on the composition and context of the FGDs can be found in additional file 4 . Several studies used multiple data collection tools. The majority of studies applied common analysis methods, including thematic and content analysis, with few using other specific approaches.

Results of syntheses

An overview of the findings based on the socio-ecological framework is summarised in Table 2 , which lists the main sub-themes identified under each socio-ecological level.

Individual level

At the individual level, HCWs’ experiences related to their well-being, professional and personal identity as well as daily work–life routine. In terms of well-being, HCWs reported negative impacts on their physical health (e.g., tiredness, discomfort, skin damage, sleep disorders) [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ] and compromised mental health. The reported negative impact on mental health included increased levels of self-reported stress, depression, anxiety, fear, grief, guilt, anger, isolation, uncertainty and helplessness [ 39 , 41 , 43 , 44 , 45 , 46 , 47 , 49 , 50 , 51 , 52 , 53 , 54 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 ]. The reported reasons for HCWs’ reduced well-being included work-related factors, such as having to adhere to new requirements in the workplace, the lack and/or burden of using Personal Protective Equipment (PPE) [ 41 , 44 , 52 , 63 , 64 , 78 , 93 , 124 , 125 ], increased workload, lack of specialised knowledge and experience, concerns over delivering low quality of care [ 42 , 44 , 49 , 52 , 53 , 63 , 69 , 70 , 73 , 74 , 76 , 78 , 79 , 83 , 84 , 85 , 86 , 89 , 90 , 93 , 94 , 101 , 103 , 109 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 ] and being confronted with ethical dilemmas [ 43 , 72 , 76 , 78 , 136 , 141 , 142 , 143 , 144 , 145 ]. HCWs’ compromised psychological well-being was also triggered by extensive exposure to concerning information via the media and by the pressure that was experienced due to society and the media assigning HCWs hero status [ 53 , 72 , 81 , 92 , 97 , 107 , 139 , 146 ]. Factors that were reported by HCWs as helping them cope with pressure comprised diverse self-care practices and personal activities, including but not limited to psychological techniques and lifestyle adjustments [ 47 , 56 , 64 , 71 , 72 , 78 , 90 , 139 , 147 , 148 ] as well as religious practices [ 81 , 112 , 149 ].

Self-reported well-being differed across occupations, roles in the pandemic response and work settings. One study reported that HCWs working in respiratory, infection and emergency departments expressed more worries compared to HCWs who worked in other hospital wards [ 64 ]. Similarly, frontline HCWs seemed more likely to experience feelings of helplessness and guilt as they witnessed the worsening situation of COVID-19 patients, whereas non-frontline HCWs seemed to experience feelings of guilt due to not supporting their frontline colleagues [ 98 ]. HCWs with managerial responsibility reported heightened concern for their staff’s health [ 75 , 110 , 150 ]. HCWs working in nursing homes and home care reported feelings of being abandoned and not sufficiently recognised [ 75 , 123 , 144 ], while one study investigating HCWs responding to the pandemic in a slums-setting reported fear of violence [ 56 ].

HCWs reported that the pandemic impacted both positively and negatively on their professional and personal identity. While negative emotions were more dominant at the beginning of the pandemic, positive effects were reported to gradually develop after the initial pandemic phase and included an increased sense of motivation, purpose, meaningfulness, pride, resilience, problem-solving attitude, as well as professional and personal growth [ 43 , 44 , 47 , 49 , 50 , 51 , 63 , 67 , 68 , 69 , 71 , 73 , 74 , 75 , 76 , 78 , 79 , 87 , 90 , 91 , 92 , 93 , 98 , 102 , 104 , 112 , 114 , 117 , 118 , 119 , 122 , 124 , 131 , 132 , 143 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 ]. Frontline staff reported particularly strong positive effects related to feelings of making a difference [ 69 , 92 ]. On the other hand, some HCWs reported doubts with regard to their career choices and job dissatisfaction [ 40 , 46 , 59 , 130 ]. Junior staff, assistant doctors and students often reported feelings of exclusion and concerns about the negative effects of the pandemic on their training [ 40 , 162 , 163 ]. Challenges with regard to their professional identity and a sense of failing their colleagues on the frontline were particularly reported by HCWs who had acquired COVID-19 themselves and experienced long COVID-19 [ 121 , 160 , 164 ]. HCWs who reached out to well-being support services expressed concern at being stigmatised [ 97 ].

HCWs reported a work–life imbalance [ 57 , 97 ] as they had to adapt to the disruption of their usual work routine [ 59 , 62 , 131 ]. This disruption manifested in taking on different roles and responsibilities [ 39 , 49 , 67 , 73 , 83 , 89 , 94 , 97 , 110 , 137 , 139 , 144 , 151 ], increased or decreased workload pressure [ 85 , 128 , 130 , 133 ] and sometimes redeployment [ 57 , 155 , 165 ]. HCWs also reported negative financial effects [ 59 , 86 , 166 ].

Interpersonal level

The findings presented in this section relate to HCWs’ perceptions of their relationships in the private and professional environment during the pandemic and to the impact these relationships had on them. With regard to the home environment, HCWs’ concerns over being infected with COVID-19 and transmitting the virus to family members were identified in almost all studies [ 41 , 44 , 48 , 51 , 54 , 56 , 61 , 68 , 75 , 77 , 80 , 85 , 90 , 128 , 139 , 160 , 167 , 168 , 169 , 170 , 171 ]. HCWs living with children or elderly family members were particularly concerned [ 47 , 65 , 95 , 97 , 163 , 172 ]. In some cases, HCWs reported that they had introduced changes to their living situation to protect their loved ones, with some deciding to move out to ensure physical distance and minimise the risk of transmission [ 39 , 43 , 44 , 89 , 105 , 161 ]. Some HCWs reported sharing limited details about their COVID-19-related duties to decrease the anxiety and fear of their significant others [ 81 ]. While in several studies, interpersonal relationships were reported to cause concerns and worries, some study also identified interpersonal relationships and the subsequent emotional connectedness as a helpful resource [ 47 , 173 , 174 ] that could, for example, alleviate anxiety [ 64 ] or provide encouragement for working on the frontline [ 49 , 106 ]. However, interpersonal relationships did not always have a supportive function, with some HCWs reporting being shunned by family and friends [ 66 , 111 , 175 ].

With regard to the work environment, relationships with colleagues were mainly described as supportive and empowering, with various studies reporting the value of teamwork during the pandemic [ 47 , 51 , 52 , 67 , 71 , 77 , 83 , 91 , 97 , 98 , 108 , 134 , 148 , 151 , 161 ]. Challenges with regard to collegial relationships included social distancing (which hindered HCWs’ interaction in the work place) [ 176 ] and working with colleagues one had never worked with before (causing a lack of familiarity with the work environment and difficulties to adapt) [ 79 ]. HCWs who worked in prisons reported interpersonal conflicts due to perceived increased authoritarian behaviour by security personnel that was perceived to manifest in arrogance and non-compliance with hygiene practices [ 88 ].

In terms of HCWs’ relationships with patients, many studies reported challenges in communicating with patients [ 50 , 55 , 126 , 132 , 133 , 172 ]. This was attributed to the use of PPE during medical examinations and care and the reduction of face-to-face visits or a complete switch to telehealth [ 128 , 139 ]. The changes in the relationships with patients varied according to the nature of work. Frontline HCWs, for example, reported challenges in caring for isolated patients [ 41 , 43 , 52 , 148 ], whereas HCWs working in specific settings and occupational roles that required specific interpersonal skills faced other challenges. This was, for example, the case for HCWs working with people with intellectual disabilities, who found it challenging to explain COVID-19 measures to this group and also had to mitigate physical contact that was considered a significant part of their work [ 71 ]. For palliative care staff, the use of PPE and measures of social distancing were challenging to apply with regard to patients and family members [ 177 ]. Building relationships and providing appropriate emotional support was reported to be particularly challenging for mental health and palliative care professionals supporting vulnerable adults or children [ 117 ]. Challenges for health and social care professionals were associated with virtual consultations and more difficult conversations [ 117 ]. Physicians reported particular frustration with remote monitoring of chronic diseases when caring for low-income, rural, and/or elderly patients [ 169 ]. Having to adjust, and compromise on, the relationships with patients caused concerns about the quality of care, which in turn, was reported to impact negatively on HCWs’ professional identity and emotional well-being.

Institutional level

This section presents HCWs’ perceptions of decision-making processes in the work setting, organizational factors and availability of institutional support.

With regard to decision-making, a small number of studies reported HCWs’ trust in the institutions they worked in [ 143 , 172 ], while the majority of studies revealed discontent about institutional leadership and feelings of exclusion from decision-making processes [ 65 , 178 ]. More specifically, HCWs reported a lack of clear communication and coordination [ 41 , 70 , 144 , 148 , 179 ] and a wish to be provided with the rationales behind management decisions and to be included in recovery phase planning [ 48 ]. They perceived centralised decision-making processes as unfamiliar and restrictive [ 150 ]. Instead, HCWs endorsed de-centralised and participatory approaches to communication and decision-making [ 56 ]. Emergency and critical care physicians suggested to include bioethicists as part of the decision-making on triaging scarce critical resources [ 126 ]. Studies of both hospital and primary care settings reported perceived disconnectedness and poor collaboration between managerial, administrative and clinical staff, which was a contributing factor to burnout among HCWs [ 60 , 83 , 149 , 169 , 180 , 181 , 182 ]. Dissatisfaction with communication also related to constantly changing protocols, which were perceived as highly burdening and frustrating, creating ambiguity and negatively affecting HCWs’ work performance [ 44 , 55 , 59 , 78 , 112 , 183 ].

In terms of organizational factors, many HCWs reported a perceived lack of organizational preparedness and poor organization of care [ 60 , 65 , 120 , 179 ]. Changes in the organization of care were perceived as chaotic, especially at the beginning of the pandemic, and changes in roles and responsibilities and role allocation were perceived as unfair and unsatisfying [ 72 , 97 ]. Only in one study, changes in work organisation were perceived positively, with nurses reporting satisfaction with an improved nurse–patient ratio resulting from organisational changes [ 52 ]. Overall, frontline HCWs advocated for more stability in team structure to ensure familiarity and consistency at work [ 47 , 66 , 72 , 114 , 116 ]. HCWs appreciated multidisciplinary teams, despite challenges with regard to achieving rapid and efficient collaboration between members from different departments [ 41 , 143 , 152 ].

Regarding institutional support, in some instances, psychological, managerial, material and technical support was positively acknowledged, while the majority of studies reported HCWs’ dissatisfaction with the support provided by the institution they worked in [ 46 , 48 , 73 , 84 , 92 , 97 , 114 , 139 , 144 , 174 , 184 ]. Across studies, a lack of equipment, including the unavailability of suitable PPEs, was one of the most prominent critiques, especially in the initial phase the pandemic [ 41 , 46 , 54 , 55 , 61 , 69 , 70 , 72 , 73 , 81 , 84 , 85 , 96 , 97 , 111 , 118 , 144 , 147 , 168 ]. In one study of a rural nursing home, HCWs reported being illegally required to treat COVID-19 patients without adequate PPE [ 39 ]. Specialised physicians, such as radiologists, for example, reported that PPE were prioritised for COVID-19 ward workers [ 65 ]. In another instance, HCWs reported that they had taken care of their own mask supply [ 113 ]. Insufficient equipment and the subsequent lack of protection induced fear and anxiety regarding one’s personal safety [ 64 , 87 ]. HCWs also reported inadequate human resources, which had consequences on increased workload [ 44 , 46 , 54 , 69 , 75 , 85 ]. Dissatisfaction with limited infrastructure was reported overall and across settings, but specific limitations were particularly relevant in certain contexts [ 116 ]. HCWs in low resource settings, including Pakistan, Zimbabwe and India, reported worsening conditions regarding infrastructure, characterised by a lack of water supply and ventilation, poor conditions of isolation wards and lack of quality rest areas for staff [ 41 , 58 , 84 ]. Despite adaptive interventions aimed at shifting service delivery to outdoors, procedures such as patient registration and laboratory work took place in poorly ventilated rooms [ 56 ]. Technical support such as the accessibility to specialised knowledge and availability of training were identified by HCWs as an important resource that required strengthening. They advocated for better “tailor-made” trainings in emergency preparedness and response, crisis management, PPE use and infection control [ 41 , 52 , 61 , 68 , 73 , 127 , 144 ]. HCWs argued that the availability of such training would improve their sense of control in health emergencies, while a lack of training compromised their confidence in their ability to provide quality healthcare [ 47 , 134 ].

Structural factors such as power hierarchies and inequalities played a role in HCWs’ perceived sense of institutional support amidst the quick changes in their institutions. Such factors were particularly mentioned in studies investigating nurses who reported dissatisfaction over doctors’ dominance and discrimination in obtaining PPE [ 54 ] as well as unfairness in work allocation [ 72 , 184 ]. They also perceived ambiguity in roles and responsibilities between nurses and doctors [ 101 ]. A low sense of institutional support was also reported by other HCWs. Junior medical staff and administrative staff reported feeling exposed to unacceptable risks of infection and a lack of recognition by their institution [ 139 ]. Staff in non‐clinical roles, non-frontline staff, staff working from home, acute physicians and those on short time contracts felt less supported and less recognised compared to colleagues on the frontline [ 48 , 139 ].

Community level

This level entails how morale and norms, as well as public knowledge relate to HCWs’ experiences in the pandemic. On the positive side, societal morale and norms were perceived as enhancing supportive attitudes among the public toward HCWs and triggering community initiatives that supported HCWs in both emotional and material ways [ 47 , 78 , 92 , 108 , 140 , 147 ]. This supportive element was especially experienced by frontline HCWs, who felt valued, appreciated and empowered by their communities. HCWs’ reaction to the hero status that was assigned to them was ambivalent [ 146 , 185 ]. In response to this status attribution, HCWs reported a sense of pressure to be on the frontline and to work beyond their regular work schedule [ 51 ]. With community support being perceived as clearly focusing on hospital frontline staff, HCWs working from home, in nursing homes, home care and non-frontline facilities and wards perceived less public support [ 139 ] and appreciation [ 85 , 144 ]. One study highlighted that HCWs did not benefit from this form of public praise but preferred an appreciation in the form of tangible and financial resources instead [ 160 ].

A clear negative aspect of social norms manifested in the stigmatisation and negative judgment by community members [ 72 , 100 , 106 , 186 , 187 ], who avoided contact with HCWs based on the perceptions that they were virus carriers and spreaders [ 43 , 68 , 92 , 111 ]. Such discrimination had negative consequences with regard to HCWs’ personal lives, including lack of access to public transportation, supermarkets, childcare and other public services [ 65 , 80 , 107 ]. Chinese HCWs working abroad reported bullying due to others perceiving and labeling COVID-19 as the ‘Chinese virus’ [ 77 ]. Negative judgment was mainly reported in studies on nurses . In a study of a COVID-19-designated hospital, frontline nurses reported unusually strict social standards directed solely at them [ 122 ]. In a comparative study of nursing homes in four countries, geriatric nurses reported social stigma toward their profession, which the society perceive not worth of respect [ 75 ].

Beyond social norms, studies identified the level of public awareness, knowledge and compliance as important determinants of HCWs’ experiences and emotional well-being [ 147 ]. For example, a lack of compliance with social distancing and other preventive measures was reported to induce feelings of betrayal, anger and anxiety among HCWs [ 41 , 80 , 81 , 111 , 188 ]. The dissemination of false information and rumors and their negative influence on knowledge and compliance was also reported with anger by HCWs in general [ 58 ], an in particular by those who worked closely with local communities [ 129 ]. Online resources and voluntary groups facilitated information exchange and knowledge transfer, factors which were valued by HCWs as an important source of information and support [ 131 , 189 ].

Policy level

Findings presented here include HCWs’ perceptions of governmental responses, governmental support and the impact of governmental measures on their professional and private situation. In a small number of studies, HCWs expressed confidence in their government’s ability to respond to the pandemic and satisfaction with governmental compensation [ 45 , 47 ]. In most cases, however, HCWs expressed dissatisfactions with the governmental response, particularly with the lack of health system organisation, the lack of a coordinated, unified response and the failure to follow an evidence-based approach to policy making. HCWs also perceived governmental guidelines as chaotic, confusing and even contradicting [ 61 , 85 , 86 , 115 , 117 , 118 , 120 , 123 , 147 , 160 , 182 , 190 ]. In one study, inadequate staffing was directly attributed to inadequate governmental funding decisions [ 191 ]. Many studies reported that HCWs had a sense of being failed by their governments [ 60 , 100 , 191 ], with non-frontline staff, notably HCWs working with the disabled [ 71 , 181 ], the elderly [ 39 , 75 , 123 , 151 ] or in home-based care [ 58 ], being particularly likely to voice feelings of being forgotten, deprioritised, invisible, less recognised and less valued by their governments. Care home staff perceived governmental support to be unequally distributed across health facilities and as being focused solely on public institutions, which prevented them from receiving state benefits [ 149 ].

Measures and regulations imposed at the governmental level had a considerable impact on HCWs’ professional as well as personal experiences. In nursing homes, HCWs perceived governmental regulations such as visiting restrictions as particularly challenging and complained that rules had not been designed or implemented with consideration to individual cases [ 62 ]. The imposed rules burdened them with additional administrative tasks and forced them to compromise on the quality of care, resulting in moral distress [ 62 ]. In abortion clinics, HCWs expressed concerns about their services being classed as non-essential services during the early stages of the pandemic [ 190 ]. Governmental policies also had impacts on HCWs personally. For example, the closure of childcare negatively impacted HCWs’ ability to balance personal and private roles and commitments. National lockdowns which restricted travel made it harder for HCWs to get to work or to see their families, especially in places with low political stability [ 95 ]. The de-escalation of measures, notably the opening of airports, was perceived as betrayal by HCWs who felt they bore the burden of increased COVID-19 incidences resulting from de-escalation strategies [ 111 ].

HCWs identified clear and consistent governmental crisis communication [ 97 , 126 ], better employees’ rights and salaries, and tailored pandemic preparedness and crisis management policies that considered different healthcare settings and HCWs’ needs [ 43 , 64 , 81 , 101 , 124 , 160 , 167 , 169 , 188 , 192 , 193 ] as important areas for improvement. HCWs in primary care advocated for strengthened primary health care, improved public health education [ 45 , 130 ] and a multi-sectoral approach in pandemic management [ 129 ].

Our scoping review of HCWs’ experiences, support needs and factors that influence these experiences during COVID-19 shows that HCWs were affected at individual, interpersonal, institutional, community and policy levels. It also highlights that certain experiences can have disruptive effects on HCWs’ personal and professional lives, and thus identifies problems which need to be addressed and areas that could be strengthened to support HCWs during pandemics.

To the best of our knowledge, our review is the first to provide a comprehensive account of HCWs’ experiences during COVID-19 across contexts. By applying an exploratory angle and focusing on existing qualitative studies, the review does not only provide a rich description of the situation of HCWs but also develops an in-depth analysis of the contextual multilevel factors which impact on HCWs’ experiences.

Our scoping review shows that, while studies on HCWs’ experiences in low resource settings are scarce, the few studies that exist and the comparison with other studies point towards setting-specific experiences and challenges. We thus argue that understanding HCWs’ experiences requires comparative investigations, which not only take countries’ income levels into account but also other contextual differences. For example, in our analysis, we identify particular challenges experienced by HCWs working in urban slums and places with limited infrastructure and low political stability. Similarly, in a recent short communication in Social Science & Medicine, Smith [ 194 ] presents a case study on the particular challenges of midwives in resource-poor rural Indonesia at the start of the pandemic, highlighting increased risks and intra-country health system inequalities. Contextual intra-country differences in HCWs’ experiences also manifest at institutional level. For example, the review suggests that HCWs who work in non-hospital settings, such as primary care services, nursing homes, home based care or disability services, experienced particular challenges and felt less recognized in relation to hospital-based HCWs. In a similar vein, HCWs working in care homes felt that as state support was not equally distributed, those working in public institutions had better chances to benefit from state support.

The review highlights that occupational hierarchies play a crucial role in HCWs’ work-related experiences. Our analysis suggests that existing occupational hierarchies seem to increase or be exposed during pandemics and that occupation is a structural factor in shaping HCWs’ experiences. The review thus highlights the important role that institutions and employers play in pandemics and is in line with the growing body of evidence that associates HCWs’ well-being during COVID-19 with their occupational role [ 195 ] and the availability of institutional support [ 195 , 196 ]. The findings suggest that to address institutional differences and ensure the provision of needs-based support to all groups of HCWs, non-hierarchical and participative processes of decision-making are crucial.

Another contextual factor affecting HCWs’ experiences are their communities. While the majority of HCWs experience emotional and material support from their community, some also feel pressure by the expectations they are confronted with. The most prominent example of such perceived pressure is the ambivalence that was reported with regard to the assignment of a hero status to HCWs. On the one hand, this attribution meant that HCWs felt recognized and appreciated by their communities. On the other hand, it led to HCWs feeling pressured to work without respecting their own limits and taking care of themselves.

This scoping review points towards a number of research gaps, which, if addressed, could help to hone interventions to support HCWs and improve health system performance and resilience.

First, the majority of existing qualitative studies investigate nurses’ and doctors’ experiences during COVID-19. Given that other types of HCWs play an equally important role in pandemic responses, future research on HCWs’ experiences in pandemics should aim for more diversity and help to tease out the specific challenges and needs of different types of HCWs. Investigating different types of HCWs could inform and facilitate the development of tailored solutions and provide need-based support.

Second, the majority of studies on HCWs’ experiences focus on hospital settings. This is not surprising considering that the bulk of societal and political attention during COVID-19 has been on the provision of acute, hospital-based care. The review thus highlights a gap with regard to research on HCWs in settings which might be considered less affected and neglected but which might, in fact, be severely collaterally affected during pandemics, such as primary health centers, care homes and home-based care. It also indicates that research which compares HCWs’ experiences across levels of care can help to tease out differences and identify specific challenges and needs.

Third, the review highlights the predominance of cross-sectional studies. In fact, we were unable to identify any longitudinal studies of HCWs’ experiences during COVID-19. A possible reason for the lack of longitudinal research is the relatively short time that has passed since the start of the pandemic which might have made it difficult to complete longitudinal qualitative studies. Yet, given the dynamics and extended duration of the pandemic, and knowledge about the impact of persistent stress on an individual’s health and well-being [ 197 , 198 , 199 , 200 ], longitudinal studies on HCWs’ experiences during COVID-19 would provide added value and allow an analysis across different stages of the pandemic as well as post-pandemic times. In our review, three differences in HCWs’ experiences across the phases of the pandemic were observed. The first one is on the individual level, reflecting the dominance of the negative emotions at the initial phase of the pandemic, which was gradually followed by increased reporting of the positive impact on HCWs’ personal and professional identity. The two other differences were on the institutional level, referring to the dissatisfaction over the lack of equipment and organization of care, mainly observed at the initial pandemic phase. Further comparative analysis of changes in HCWs’ experiences over the course of a pandemic is an interesting and important topic for future research, which could also map HCWs’ experiences against hospital capacities, availability of vaccines and tests as well as changes in pandemic restrictions. Such comparative analysis can inform the development of suitable policy level interventions accounting for HCWs’ experiences at different pandemic stages, from preparedness to initial response and recovery.

Finally, the majority of studies included in the review were conducted in the Northern hemisphere, revealing a gap in understanding the reality of HCWs in low- and lower middle income countries. Ensuring diversity in geographies and including resource-poor settings in research on HCWs would help gain a better contextual understanding, contribute to strengthening pandemic preparedness in settings, where the need is greatest, and facilitate knowledge transfer between the global North and South. While further research can help to increase our understanding of HCWs’ experiences during pandemics, this scoping review establishes a first basis for the evaluation and improvement of interventions aimed at supporting HCWs prior to, during and after COVID-19. A key finding of our analysis to strengthen HCWs’ resilience are the interdependencies of factors across the five levels of the socio-ecological model. For example, institutional, community or policy level factors (such as dissatisfaction with decision-making processes, public non-compliance or failures in pandemic management) can have a negative impact on HCWs at interpersonal and individual levels by impacting on their professional relationships, mental health or work performance. Similarly, policy, community or institutional level factors (such as adequate policy measures, appreciation within the community and the provision of PPE and other equipment) can act as protective factors for HCWs’ well-being. In line with the social support literature [ 201 ], interpersonal relationships were identified as a key factor in shaping HCWs’ experiences. The identification of the inter-dependencies between factors affecting HCWs during pandemics further highlights that health systems are severely impacted by factors outside the health systems’ control. Previous scholars have recognized the embeddedness of health systems within, and their constant interaction with, their socio-economic and political environment [ 202 ]. Previous literature, however, also shows that interventions tackling distress of HCWs have largely focused on individual level factors, e.g., on interventions aimed at relieving psychological symptoms, rather than on contextual factors [ 16 ]. To strengthen HCWs and empower them to deal with pandemics, the contextual factors that affect their situation during pandemics need to be acknowledged and interventions need to follow a multi-component approach, taking the multitude of aspects and circumstances into account which impact on HCWs’ experiences.

Limitations and strengths

Our scoping review comes with a number of limitations. First, due to resource constraints, the search was conducted using only one database. The authors acknowledge that running the search strategy on other search engines could have resulted in additional interesting studies to be reviewed. To mitigate any weaknesses, extensive efforts were made to build a strong search string by reviewing previous peer-reviewed publications as well as available resources from recognized public health institutions. Considering the high numbers of studies identified, it can be, however, assumed that the search strategy and review led to valid conclusions. Second, the review excluded non-original publications. While other types of publications could have provided additional data and perspectives on HCWs’ experiences, we decided to limit our review to original, peer-reviewed research articles to ensure quality. Third, the review excluded studies on other pandemics, which could have provided further insights into HCWs’ experiences during health crises. Given the limited resources available to the research project, it was decided to focus only on COVID-19 to accommodate a larger target group of all types of HCWs and a variety of geographical locations and healthcare settings. Furthermore, it can be argued that previous pandemics did not reach the magnitude of COVID-19 and did not lead to similar responses. With the review looking at the burden of COVID-19 as a stressor, it can be assumed that the more important the stressor, the more interesting the results. Therefore, the burdens and the way in which HCWs dealt with these burdens would be particularly augmented with regard to COVID-19, making it a suitable focus example to investigate HCWs’ experiences in health crises. The authors acknowledge that during other pandemics HCWs’ experiences might differ and be less pronounced, yet this review has addressed stressors and ways of supporting HCWs that could also inform future health crises. In our view, a major strength of the review is that is does not apply any limitation in terms of the types of HCWs, the geographical locations or the healthcare settings included. This approach did not only allow us to review a wide range of literature on an expanding area of knowledge [ 30 ], but to appropriately investigate HCWs’ experiences during a public health emergency of international concern that affects countries across the globe. Providing detailed information about the contexts in which HCWs were studied, allowed us to shed light on the contextual factors affecting HCWs’ experiences.

Implications for policy and practice

Areas of future interventions that improve HCWs’ resilience at individual level could aim towards alleviating stress and responding to their specific needs during pandemics, in line with encouraging self-care activities that can foster personal psychological resilience. Beyond that, accounting for the context when designing and implementing interventions is crucial. This can be done by addressing the circumstances HCWs live and work in, referred to in German-speaking countries as “Verhältnisprävention”, i.e., prevention through tackling living and working conditions. Respective interventions should tackle all levels outlined in the socio-ecological model, applying a systems approach. At the interpersonal level, creating a positive work environment in times of crises that is supportive of uninterrupted and efficient communication among HCWs and between HCWs and patients is important. In addition, interpersonal support, e.g., by family and friends could be facilitated. At institutional level, organizational change should consider transparent and participatory decision making and responsible planning of resources availability and allocation. At community level, tracing rumors and misinformation during health emergencies is crucial, as well as advocating for accountable journalism and community initiatives that support HCWs in times of crisis. At policy level, pandemic regulations need to account for their consequences on HCWs’ work situations and personal lives. Governmental policies and guidelines should build on scientific evidence and take into account the situations and lived experiences of HCWs across all levels of care.

This scoping review of existing qualitative research on HCWs’ experiences during COVID-19 sheds light on the impact of a major pandemic on the health workforce, a key pillar of health systems. By identifying key drawbacks, strengths that can be built upon, and crucial entry-points for interventions, the review can inform strategies towards strengthening HCWs and improving their experiences. Following a systems approach which takes the five socio-ecological levels into account is crucial for the development of context-sensitive strategies to support HCWs prior to, during and after pandemics. This in turn can contribute to building a sustainable health workforce and to strengthening and better preparing health systems for future pandemics.

Availability of data and materials

All data generated during this study are included in this published article and its supplementary information files, except for a detailed extraction sheet for all studies included, which is available from the corresponding author upon request.

Abbreviations

• Health care workers

Joanna Briggs Institute

Focus Groups Discussions

Personal Protective Equipment

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HW and AMS conceived and designed the scoping review. SC extracted, analyzed and conceptualized the data as well as drafted the initial version of this manuscript. HW and AMS provided quality checks for the methodology and analysis. HW, AMS and CEB substantively revised each version of the manuscript and provided substantial inputs. All authors read and approved the final manuscript.

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Additional file 1.

: Table S1. Search strategy. The document includes the search strings for the review.

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: Table S2. List of included papers. The file lists the 161 included papers, detailing the title, authors, publication year and DOI link.

Additional file 3

: Table S3. List of countries studied. The file includes a table listing the countries in which the included studies were conducted according to frequency.

Additional file 4

: Table S4. Detailed information on FGDs. This document provides information extracted from studies that used FGDs as a qualitative data collection tool. The table lists the overall number of focus group discussion’s participants in each of those studies, the number of FGDs per study, whether FGDs were conducted online or offline, the type of study participants, and any other information on the methods that could be extracted.

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Chemali, S., Mari-Sáez, A., El Bcheraoui, C. et al. Health care workers’ experiences during the COVID-19 pandemic: a scoping review. Hum Resour Health 20 , 27 (2022). https://doi.org/10.1186/s12960-022-00724-1

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DOI : https://doi.org/10.1186/s12960-022-00724-1

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Research Article

Online education and its effect on teachers during COVID-19—A case study from India

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Area of Humanities and Social Sciences, Indian Institute of Management Indore, Indore, Madhya Pradesh, India

• Surbhi Dayal

• Published: March 2, 2023
• https://doi.org/10.1371/journal.pone.0282287
• Reader Comments

COVID pandemic resulted in an initially temporary and then long term closure of educational institutions, creating a need for adapting to online and remote learning. The transition to online education platforms presented unprecedented challenges for the teachers. The aim of this research was to investigate the effects of the transition to online education on teachers’ wellbeing in India.

The research was conducted on 1812 teachers working in schools, colleges, and coaching institutions from six different Indian states. Quantitative and qualitative data was collected via online survey and telephone interviews.

The results show that COVID pandemic exacerbated the existing widespread inequality in access to internet connectivity, smart devices, and teacher training required for an effective transition to an online mode of education. Teachers nonetheless adapted quickly to online teaching with the help of institutional training as well as self-learning tools. However, respondents expressed dissatisfaction with the effectiveness of online teaching and assessment methods, and exhibited a strong desire to return to traditional modes of learning. 82% respondents reported physical issues like neck pain, back pain, headache, and eyestrain. Additionally, 92% respondents faced mental issues like stress, anxiety, and loneliness due to online teaching.

As the effectiveness of online learning perforce taps on the existing infrastructure, not only has it widened the learning gap between the rich and the poor, it has also compromised the quality of education being imparted in general. Teachers faced increased physical and mental health issues due to long working hours and uncertainty associated with COVID lockdowns. There is a need to develop a sound strategy to address the gaps in access to digital learning and teachers’ training to improve both the quality of education and the mental health of teachers.

Citation: Dayal S (2023) Online education and its effect on teachers during COVID-19—A case study from India. PLoS ONE 18(3): e0282287. https://doi.org/10.1371/journal.pone.0282287

Editor: Lütfullah Türkmen, Usak University College of Education, TURKEY

Received: November 13, 2021; Accepted: January 27, 2023; Published: March 2, 2023

Copyright: © 2023 Surbhi Dayal. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data apart from manuscript has been submitted as supporting information .

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

As of November 4, 2021, the spread of novel coronavirus had reached 219 countries and territories of the world, infecting a total of 248 million people and resulting in five million deaths [ 1 ]. In March 2020, several countries including India declared a mandatory lockdown, resulting in the temporary closure of many institutions, not least educational ones. Since then, various restrictions and strategies have been implemented to counter the spread of the virus. These include wearing masks, washing hands frequently, maintaining social and physical distance, and avoiding public gatherings. The pandemic has greatly disrupted all aspects of human life and forced new ways of functioning, notably in work and education, much of which has been restricted to the household environment. The closure for over a year of many schools and colleges across the world has shaken the foundations of the traditional structures of education. Due to widespread restrictions, employees have been forced to carve out working spaces in the family home; likewise, students and teachers have been compelled to bring classes into homes [ 2 ]. Nearly 1.6 billion learners in more than 190 countries have been physically out of school due to the pandemic. In total, 94 percent of the world’s student population has been affected by school closures, and up to 99 percent of this student population come from low-to middle-income countries [ 3 ].

According to the World Economic Forum, the pandemic has changed how people receive and impart education [ 4 ]. Physical interaction between students and teachers in traditional classrooms has been replaced by exchanges on digital learning platforms, such as online teaching and virtual education systems, characterized by an absence of face-to-face connection [ 5 ]. Online education has thus emerged as a viable option for education from preschool to university level, and governments have used tools such as radio, television, and social media to support online teaching and training [ 6 ]. Various stakeholders, including government and private institutions, have collaborated to provide teachers with resources and training to teach effectively on digital platforms. New digital learning platforms like Zoom, Google Classroom, Canvas, and Blackboard have been used extensively to create learning material and deliver online classes; they have also allowed teachers to devise training and skill development programs [ 7 ]. Many teachers and students were initially hesitant to adopt online education. However indefinite closure of institutions required educational facilities to find new methods to impart education and forced teachers to learn new digital skills. Individuals have experienced different levels of difficulty in doing this; for some, “it has resulted in tears, and for some, it is a cup of tea” [ 8 ].

Teachers have reported finding it difficult to use online teaching as a daily mode of communication, and enabling students’ cognitive activation has presented a significant challenge in the use of distance modes of teaching and learning. Teachers have also expressed concerns about administering tests with minimal student interaction [ 9 ]. Lack of availability of smart devices, combined with unreliable internet access, has led to dissatisfaction with teacher-student interaction. Under pressure to select the appropriate tools and media to reach their students, some teachers have relied on pre-recorded videos, which further discouraged interaction. In locations where most teaching is done online, teachers in tier 2 and tier 3 cities (i.e., semi-urban areas) have had to pay extra to secure access to high-speed internet, digital devices, and reliable power sources [ 10 ]. Teachers in India, in particular, have a huge gap in digital literacy caused by a lack of training and access to reliable electricity supply, and internet services. In rural or remote areas, access to smart devices, the internet, and technology is limited and inconsistent [ 6 ]. In cities, including the Indian capital Delhi, even teachers who are familiar with the required technology do not necessarily have the pedagogical skills to meet the demands of online education. The absence of training, along with local factors (for example, stakeholders’ infrastructure and socio-economic standing), contributes to difficulties in imparting digital education successfully [ 10 ]. The gap in digital education across Indian schools is striking. For example, only 32.5% of school children are in a position to pursue online classes. Only 11% of children can take online classes in private and public schools, and more than half can only view videos or other recorded content. Only 8.1% of children in government schools have access to online classes in the event of a pandemic-related restrictions [ 11 ].

The adverse effects of COVID-19 on education must therefore be investigated and understood, particularly the struggles of students and teachers to adapt to new technologies. Significant societal effects of the pandemic include not only serious disruption of education but also isolation caused by social distancing. Various studies [ 7 , 12 , 13 ] have suggested that online education has caused significant stress and health problems for students and teachers alike; health issues have also been exacerbated by the extensive use of digital devices. Several studies [ 6 , 11 , 14 ] have been conducted to understand the effects of the COVID lockdown on digital access to education, students’ physical and emotional well-being, and the effectiveness of online education. However, only a few studies [ 13 , 15 – 17 ] have touched the issues that teachers faced due to COVID lockdown.

In this context, this study is trying to fill existing gaps and focuses on the upheavals that teachers went through to accommodate COVID restrictions and still impart education. It also provides an in-depth analysis of consequences for the quality of education imparted from the teachers’ perspective. It discusses geographical inequalities in access to the infrastructure required for successful implementation of online education. In particular, it addresses the following important questions: (1) how effectively have teachers adapted to the new virtual system? (2) How has online education affected the quality of teaching? (3) How has online education affected teachers’ overall health?

Because of lockdown restrictions, data collection for this study involved a combination of qualitative and quantitative methods in the form of online surveys and telephonic interviews. A questionnaire for teachers was developed consisting of 41 items covering a variety of subjects: teaching styles, life-work balance, and how working online influences the mental and physical well-being of teachers. In the interviews, participants were asked about their experiences of online teaching during the pandemic, particularly in relation to physical and mental health issues. A pilot study was conducted with thirty respondents, and necessary changes to the items were made before the data collection. The survey tool was created using google forms and disseminated via email, Facebook, and WhatsApp. A total of 145 telephonic interviews were also conducted to obtain in-depth information from the respondents.

The data were collected between December 2020 and June 2021. The Research Advisory Committee on Codes of Ethics for Research of Aggrawal College, Ballabhgarh, Haryana, reviewed and approved this study. A statement included in the google survey form as a means of acquiring written consent from the participants. Information was gathered from 1,812 Indian teachers in six Indian states (Assam, Haryana, Karnataka, Madhya Pradesh, New Delhi, and Rajasthan) working in universities, schools, and coaching institutions. Nearly three-quarters of the total sample population was women. All participants were between the ages of 18 and 60, with an average age of 34 and a clear majority being 35 or younger. Nearly three-quarters of participants work in private institutions (25% in semi-government entities and the remainder in government entities). In terms of education, 52% of participants have a graduate degree, 34% a postgraduate degree, and 14% a doctorate. Table 1 summarizes the demographic characteristics of the participants.

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Results & discussion

Upon analyzing the survey responses, three crucial areas were identified for a better understanding of the effect of COVID-19 on the Indian education system and its teachers: how effectively teachers have adapted, how effective teaching has been, and how teachers’ health has been affected.

1. How effectively have teachers adapted to the new virtual system?

The first research question concerns how willing teachers were to embrace the changes brought about by the online teaching system and how quickly they were able to adapt to online modes of instruction. This information was gathered from December 2020 to June 2021, at which point teachers had been dealing with school lockdowns for months and therefore had some time to become conversant with online teaching.

While 93.82% of respondents were involved in online teaching during the pandemic, only 16% had previously taught online. These results were typically different from the results of a similar study conducted in Jordon where most of the faculty (60%) had previous experience with online teaching and 68% of faculty had also received formal training [ 16 ]. Since the spread of COVID-19 was rapid and the implementation of the lockdown was sudden, government and educational institutions were not prepared for alternative modes of learning, and teachers needed some time for adjustment. Several other factors also affected the effectiveness of the transition to online education, namely access to different types of resources and training [ 18 ].

a. Access to smart devices.

Online teaching requires access to smart devices. A surprising number of teachers stated that they had internet access at home via laptops, smartphones, or tablets. A more pertinent question, however, was whether they had sole access to the smart device, or it was shared with family members. Only 37.25% of those surveyed had a device for their exclusive use while others shared a device with family members, due to lack of access to additional devices and affordability of new devices. During the lockdown, an increase in demand led to a scarcity of smart devices, so that even people who could afford to buy a device could not necessarily find one available for purchase. With children attending online classes, and family members working from home, households found it difficult to manage with only a few devices, and access to a personal digital device became an urgent matter for many. Respondents admitted to relying on their smartphones to teach courses since they lacked access to other devices. Teachers on independent-school rosters were significantly better equipped to access smart devices than those employed at other types of schools. The data also indicates that teachers in higher education and at coaching centers had relatively better access to laptops and desktop computers through their institutions, whereas teachers in elementary and secondary schools had to scramble for securing devices for their own use.

b. Internet access.

Internet access is crucial for effective delivery of online education. However, our survey shows that teachers often struggled to stay connected because of substantial differences between states in the availability of internet. Of the respondents, 52% reported that their internet was stable and reliable, 32% reported it to be satisfactory and the rest reported it to be poor. Internet connectivity was better in the states of Karnataka, New Delhi, and Rajasthan than in Assam, Haryana, and Madhya Pradesh. Internet connectivity in Assam was particularly poor. Consequently, many teachers with access to advanced devices were unable to use them due to inadequate internet connection.

The following comments from a teacher in Assam capture relevant situational challenges: “I do not have an internet modem at home, and teaching over the phone is difficult. My internet connection is exhausted, and I am unable to see or hear the students.” Another teacher from Haryana reported similar difficulties: “During the lockdown, I moved to my hometown, and I do not have internet access here, so I go to a nearby village and send videos to students every three days.” Another teacher from Madhya Pradesh working at a premier institution reported experiencing somewhat different concerns: “I am teaching in one of the institute’s semi-smart classrooms, and while I have access to the internet, my students do not, making it difficult to hear what they are saying.”

These responses indicates clearly that it is not only teachers living in states where connectivity was poor who experienced difficulties in imparting education to students; even those who had good internet connectivity experiences problems caused by the poor internet connections of their students.

c. Tools for remote learning.

Teachers made use of a variety of remote learning tools, but access to these tools varied depending on the educator’s affiliation. Teachers at premier institutions and coaching centers routinely used the Zoom and Google Meet apps to conduct synchronous lessons. Teachers at state colleges used pre-recorded videos that were freely available on YouTube. Teachers in government schools used various platforms, including WhatsApp for prepared material and YouTube for pre-recorded videos. To deliver the content, private school teachers used pre-recorded lectures and Google Meet. In addition to curriculum classes, school teachers offered life skill classes (for example, cooking, gardening, and organizing) to help students become more independent and responsible in these difficult circumstances. In addition to online instruction, 16% of teachers visited their students’ homes to distribute books and other materials. Furthermore, of this 36% visited students’ homes once a week, 29% visited twice a week, 18% once every two weeks, and the rest once a month. Additionally, a survey done on 6435 respondents across six states in India reported that 21% teachers in schools conducted home visits for teaching children [ 19 ].

d. Knowledge and training for the use of information and communication technologies.

With the onset of the pandemic, information and communication technology (ICT) became a pivotal point for the viability of online education. The use of ICT can facilitate curriculum coverage, application of pedagogical practices and assessment, teacher’s professional development, and streamlining school organization [ 20 ]. However, the effective adoption and implementation of ICT necessitated delivery of appropriate training and prolonged practice. Also the manner in which teachers use ICT is crucial to successful implementation of online education [ 21 ]. While countries such as Germany, Japan, Turkey, the United Kingdom, and the United States recognized the importance of ICT by integrating it into their respective teacher training programmes [ 22 ], this has not been case in India. However, there are some training programmes available to teachers once they commence working. In accordance with our survey results, the vast majority of respondents (94%) lacked any ICT training or experience. In the absence of appropriate tools and support, these teachers self-experimented with online platforms, with equal chances of success and failure.

The transition from offline to online or remote learning was abrupt, and teachers had to adapt quickly to the new systems. Our data indicate that teachers in professional colleges and coaching centers received some training to help them adapt to the new online system, whereas teachers in urban areas primarily learned on their own from YouTube videos, and school teachers in rural areas received no support at all. Overall, teachers had insufficient training and support to adjust to this completely new situation. Policy research conducted on online and remote learning systems following COVID-19 has found similar results, namely that teachers implemented distance learning modalities from the start of the pandemic, often without adequate guidance, training, or resources [ 23 ]. Similar trends have been found in the Caribbean, where the unavailability of smart learning devices, lack of or poor internet access, and lack of prior training for teachers and students hampered online learning greatly. Furthermore, in many cases the curriculum was not designed for online teaching, which was a key concern for teachers [ 24 ]. Preparing online lectures as well as monitoring, supervising and providing remote support to students also led to stress and anxiety. Self-imposed perfectionism further exacerbated these issues while delivering online education [ 15 ]. A study conducted on 288 teachers from private and government schools in Delhi and National Capital Region area, also found that transition to online education has further widened the gap between pupils from government and private schools. It was more difficult to reach students from economically weaker sections of the society due to the digital divide in terms of access, usage, and skills gap. The study also found that even when teachers were digitally savvy, it did not mean that they know how to prepare for and take online classes [ 10 ].

2. How has online education affected the quality of teaching?

Once teachers had acquired some familiarity with the online system, new questions arose concerning how online education affected the quality of teaching in terms of learning and assessment, and how satisfied teachers were with this new mode of imparting education. To address these questions, specific questionnaire items about assessment and effectiveness of teaching has been included.

a. Effectiveness of online education.

Respondents agreed unanimously that online education impeded student-teacher bonding. They reported several concerns, including the inattentiveness of the majority of the students in the class, the physical absence of students (who at times logged in but then went elsewhere), the inability to engage students online, and the difficulty of carrying out any productive discussion given that only a few students were participating. Another significant concern was the difficulty in administrating online tests in light of widespread cheating. In the words of one teacher: “I was teaching a new class of students with whom I had never interacted in person. It was not easy because I could not remember the names of the students or relate to them. Students were irritated when I called out their names. It had a significant impact on my feedback. I would like us to return to class so I do not have to manage four screens and can focus on my students and on solving their problems.”

For these reasons, 85.65% of respondents stated that the quality of education had been significantly compromised in the online mode. As a result, only 33% reported being interested in continuing with online teaching after COVID-19. The results show slightly higher dissatisfaction in comparison to another study conducted in India that reported 67% of teachers feeling dissatisfied with online teaching [ 25 ]. Findings of this study were similar to the findings of a survey of lecturers in Ukraine assessing the effectiveness of online education. Lower quality student work was cited as the third most mentioned problem among the problems cited by instructors in their experience with online teaching, right behind unreliable internet connectivity and the issues related with software and hardware. Primary reasons for lower quality student work were drop in the number of assignments and work quality as well as cheating. Almost half (48.7%) of the participants expressed their disapproval of online work and would not like to teach online [ 26 ].

Due to the nature of the online mode, teachers were also unable to use creative methods to teach students. Some were accustomed to using physical objects and role-playing to engage students in the classroom, but they found it extremely difficult to make learning exciting and to engage their students in virtual space. Similar trends have been reported in Australia, where schoolteachers in outback areas did not find online education helpful or practical for children, a majority of whom came from low-income families. The teachers were used to employing innovative methods to keep the students engaged in the classroom. However, in online teaching, they could not connect with their students using those methods, which significantly hampered their students’ progress. Some teachers mentioned difficulties with online teaching caused by not being able to use physical and concrete objects to improve their instructions [ 27 ].

b. Online evaluation.

Of our respondents, 81% said that they had conducted online assessments of their students. Teachers used various online assessment methods, including proctored closed/open book exams and quizzes, assignment submissions, class exercises, and presentations. Teachers who chose not to administer online assessments graded their students’ performance based on participation in class and previous results.

Almost two-thirds of teachers who had administered online assessments were dissatisfied with the effectiveness and transparency of those assessments, given the high rates of cheating and internet connectivity issues. They also reported that family members had been helping students to cheat in exams because they wanted their children to get higher grades by any means necessary. In response, the teachers had tried to devise methods to discourage students and their families from cheating, but they still felt powerless to prevent widespread cheating.

As one respondent stated: “We are taking many precautions to stop cheating, such as asking to install a mirror behind the student and doing online proctoring, but students have their ways out for every matter. They disconnect the internet cable or turn it off and reconnect it later. When we question them, they have a connectivity reason ready”.

Teachers are also concerned about the effects of the digital skills gap on their creation of worksheets, assessments, and other teaching materials. As a result, some private companies have been putting together teacher training programs. The main challenge pertains to be implementation of a type of specialized education that many teachers are unfamiliar with and unwilling to adopt [ 28 ]. Because of the lack of effective and transparent online assessments, school teachers have reported that students were promoted to the next level regardless of their performance. Thus, only time will tell how successful online education has been in terms of its effects on the lives of learners.

3. How has online education affected teacher’s overall health?

The onset of the COVID-19 pandemic brought about a situation that few people had experienced or even imagined living through. Governments and individuals tried their best to adjust to the new circumstances, but sudden lockdown, confinement to the household periphery, and working from home had adverse effects on the mental and physical health of many people, including educators and students. To clarify the effects of online education on teachers’ overall health, a number of questionnaire items were focused on respondents’ feelings during the lockdown, the physical and mental health issues they experienced, and their concerns about the future given the uncertainty of the present situation.

a. Physical health issues.

COVID-19 brought a multitude of changes to the lives of educators. Confinement to the household, working from home, and an increased burden of household and caregiving tasks due to the absence of paid domestic assistants increased physical workload and had corresponding adverse effects on the physical health of educators.

Of the study participants, 82% reported an increase in physical health issues since the lockdown ( Fig 1 ). Notably, 47% of those who were involved in digital mode of learning for less than 3 hours per day reported experiencing some physical discomfort daily, rising to 51% of teachers who worked online for 4–6 hours per day and 55% of teachers who worked more than 6 hours per day. Respondents reported a variety of physical health issues, including headaches, eye strain, back pain, and neck pain.

https://doi.org/10.1371/journal.pone.0282287.g001

The number of hours worked showed a positive correlation with the physical discomfort or health issues experienced. A chi-square test was applied to determine the relationship between the number of online working hours and the frequency of physical issues experienced by the participants and found it to be significant at the 0.05 level ( Table 2 ).

https://doi.org/10.1371/journal.pone.0282287.t002

As Fig 2 shows, 28% respondents’ complaint about experiencing giddiness, headaches; 59% complain of having neck and back pain. The majority of the participants had eye-strain problems most of the time; 32% faced eye problems sometimes, and 18% reported never having any eye issue. In addition, 49% had experienced two issues at the same time and 20% reported experiencing more than 2 physical issues at the same time.

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The data in this study indicates a link between bodily distresses and hours worked. As working hours increased, so did reports of back and neck pain. 47% respondents reported back and neck pain after working for 3 hours or less, 60% after working for 3–6 hours, and nearly 70% after working for 6 hours or more.

The analysis also indicates link between physical issues experienced and the educator’s gender. Women experienced more physical discomfort than men, with 51% reporting frequent discomfort, compared to only 46% of men. Only 14% of female educators reported never experiencing physical discomfort, against 30% of male educators.

In terms of types of discomfort, 76% of female teachers and 51% of male teachers reported eye strain; 62% of female teacher and 43% of male teachers reported back and neck pain; 30% of female teachers and 18% of male teachers said they had experienced dizziness and headaches. The gender differences may be caused by the increase in household and childcare responsibilities falling disproportionately on female educators compared to their male counterparts. Several studies [ 17 , 29 – 31 ] have reported similar results, indicating that the gender gap widened during the pandemic period. The social expectations of women to take care of children increased the gender gap during the pandemic by putting greater responsibilities on women in comparison to men [ 29 ]. Women in academics were affected more in comparison to the men. Working from home burdened female educators with additional household duties and childcare responsibilities. A study done [ 32 ] in France, Germany, Italy, Norway, Sweden, the United States and the United Kingdom discovered that women were immensely affected by lockdown in comparison to men. On top of this, women with children are affected more than women without children.

No effect of age on physical discomfort was observed in this study but increasing use of online tools (such as class websites) for content creation and delivery and extended working periods were major contributors to health problems.

b. Mental health issues.

The psychological effects of the COVID-19 pandemics have also proved difficult to manage. Being at home all day with limited social interaction, not to mention other pandemic-related sources of stress, affected the mental health of many people. The majority of the participants in this study admitted experiencing mental health issues including anxious feelings, low mood, restlessness, hopelessness, and loneliness. According to UNESCO [ 33 ], due to the sudden closure of schools and adaptability to new systems, teachers across the world are suffering from stress. Studies conducted in various parts of the world confirmed similar trends [ 34 , 35 ]. In Israel, teachers reported psychological stress due to online teaching. 30.4% teachers reported being stressed in comparison to 6.1% teachers in traditional classroom settings [ 34 ]. In Spain, teachers experienced various kinds of mental health issues like anxiety, stress, and depression [ 36 ]. An Arabian study found an increased number of cases related to anxiety, depression, and violence during the pandemic [ 37 ]. In New Zealand teachers in Higher education reported being overwhelmed due to the online teaching [ 15 ].

Online teaching appears to have negatively affected the mental health of all the study participants. Women (94%) reported more mental health issues than men (91%), as shown in Fig 3 . Nearly two-thirds of participants said they had been dealing with mental health issues regularly and a third occasionally; only 7% said they never dealt with them. Findings of this study are in line with other studies which found that female teachers had higher levels of stress and anxiety in comparison to men [ 36 ]. Studies conducted in China reported that teachers developed mental health issues due to online classes [ 37 , 38 ].

https://doi.org/10.1371/journal.pone.0282287.g003

Our analysis indicated a positive relationship between the number of working hours and the frequency of mental health issues. Of the respondents who worked online for less than 3 hours, 55% experienced some kind of mental health issue; this rose to 60% of participants who worked online for 3–6 hours, and 66% of those who worked more than 6 hours every day. A chi-square test was applied to determine the relationship between the number of online working hours and the frequency of mental issues experienced by the participants and found it to be significant at the 0.05 level ( Table 3 ).

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In terms of types of mental health issues, respondents reported restlessness, anxious feelings, and a sense of powerlessness, along with feelings of hopelessness, low mood, and loneliness as shown in Fig 4 . The stress of adapting to a new online working environment, the extended hours of work required to prepare content in new formats, the trial-and-error nature of learning and adopting new practices, uncertainty caused by lockdown, and an overall feeling of having no control were some of the contributing factors.

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Mental health issues were more common among those under the age of 35, with 64% reporting a problem most of the time compared to 53% of those over 35. It has been found that job uncertainty is one of the primary causes of a higher prevalence of mental health concerns among younger respondents than among older respondents. These findings are in line with other studies which found higher levels of stress among the young people in comparison to older one [ 36 , 39 ]. Feelings of loneliness and a sense of no control were reported by 30% of respondents under the age of 35, with these feelings occurring constantly or most of the time; only 12% of respondent over the age of 35 reported experiencing these feelings always or most of the time. Of respondents under 35 years of age 61% felt lonely at some point during the COVID-19 pandemic, compared to only 40% of those age 35 or older.

This study also found gender-based differences in the frequency of mental health issues experienced, with 62% of male respondents and 52% of female respondents reporting that they had always experienced mental health issues. The types of issues also differed by gender, with men more likely to report restlessness and loneliness and women more likely to report feeling anxious or helpless. More female respondents reported feelings of hopelessness than male respondents (76% compared to 69%), and they were also more anxious (66%).

The uncertainty of the pandemic seems to have caused helplessness and anxious feelings for female teachers in particular, perhaps because a lack of paid domestic help increased the burden of household and caregiving tasks disproportionately for women at a time when the pressure to adapt to new online platforms was particularly acute. In some cases, respondents left their jobs to accommodate new family dynamics, since private employers offered no assistance or flexibility. Deterioration of mental health also led to the increased number of suicides in Japan during COVID-19 [ 39 ].

However, female teachers fared better than their male counterparts on some measures of mental health. Although half of the respondents (men and women equally) reported low mood during the pandemic, the men reported more restlessness (53%) and loneliness (59%) than the women (50% and 49%, respectively). Restrictions on eating and drinking outside the household may have had a disproportionate effect on male respondents, making them more likely to feel restless or lonely than their female counterparts, who may have handled COVID-related isolation better by being more involved in household work and caregiving.

Number of hours worked online was also a factor contributing to mental health issues. Just as respondents had more physical complaints (including eye strain, back and neck pain, and headaches) the more hours they worked online, respondents who worked longer hours online reported more mental health issues.

One of the major drawbacks of online education is the widespread occurrence of physical and mental health issues, and the results of this study corroborate concerns on this point. This study found that online teaching causes more mental and physical problems for teachers than another study, which only found that 52.7% of respondents had these problems [ 12 ].

A report by the University of Melbourne has also indicated that online teaching and learning have a negative effect on the physical and mental well-being of individuals. Teachers working from home, in particular, have reported isolation, excessive screen time, inability to cope with additional stress, and exhaustion due to increased workload; despite being wary of the risks of exposure to COVID-19, they were eager to return to the campus [ 27 ].

c. Support mechanisms.

In general, teachers experienced good support from family and colleagues during the pandemic, with 45.64% of teachers reported receiving strong support, 29.64 percent moderate support (although the remainder claimed to have received no or only occasional support from family and colleagues). 9.39% of male respondents reported that they have never received any support in comparison to 4.36% females. Female respondents reported receiving more support than male respondents perhaps because they have access to a more extensive network of family members and coworkers. Children, parents, and siblings were cited as the provider of a robust support system by most female respondents. For example, maternal relatives called or texted children to keep them engaged and helped them with homework, and female participants said their peers helped them to prepare lectures and materials. A link was also found between age and support; the older the respondent, the stronger the support system. A possible explanation for this difference is that older people have had time to develop stronger and longer-lasting professional and personal ties than younger people.

This study explored the effects of the COVID-19 pandemic on the Indian education system and teachers working across six Indian states. The effectiveness of online education methods varied significantly by geographical location and demographics based on internet connectivity, access to smart devices, and teachers’ training. While premier higher education institutions and some private institutions had provided teachers with the necessary infrastructure and training to implement effective successful online learning with relatively few challenges, teachers at schools and community colleges have more often been left to adopt a trial-and-error approach to the transition to an online system. Further, it indicates that online education has had a significant effect on the quality of education imparted and the lives and wellbeing of teachers. While online learning has enabled teachers to reach out to students and maintain some normalcy during a time of uncertainty, it has also had negative consequences. Owing to the lack of in-person interaction with and among students in digital classes, the absence of creative learning tools in the online environment, glitches and interruptions in internet services, widespread cheating in exams, and lack of access to digital devices, online learning adversely affected the quality of education. Teachers experienced mounting physical and mental health issues due to stress of adjusting to online platforms without any or minimal ICT training and longer working hours to meet the demands of shifting responsibilities. A positive correlation was found between working hours and mental and physical health problems.

The long-term impact of COVID-19 pandemic on both the education system and the teachers would become clear only with time. Meanwhile, this study sheds light on some of the issues that teachers are facing and needs to be addressed without further ado. These findings will provide direction to the policy makers to develop sound strategies to address existing gaps for the successful implementation of digital learning. However, researchers should continue to investigate the longer-term effects of COVID pandemic on online education.

Supporting information

S1 file. supplementary material..

https://doi.org/10.1371/journal.pone.0282287.s001

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The influence of global crises on reshaping pro-environmental behavior, case study: the COVID-19 pandemic

Affiliations.

• 1 School of Environment, College of Engineering, University of Tehran, Tehran, Iran. Electronic address: [email protected].
• 2 School of Environment, College of Engineering, University of Tehran, Tehran, Iran.
• PMID: 34742989
• PMCID: PMC8596762
• DOI: 10.1016/j.scitotenv.2021.151436

As a profound crisis capable of threatening human well-being as well as existence, the COVID-19 pandemic can be considered as an awakening experience which may lead to the promotion of environmentally responsible behaviors in the society. In the present research, an extended form of the Theory of Planned Behavior has been applied to examine the moderating effect of COVID-19 pandemic on pro-environmental behavior mechanism in Iran. To evaluate this effect, a 5-scale Likert questionnaire was designed comprising of 28 questions in 7 sections of information and concerns about COVID-19, environmental knowledge, subjective norm, attitude, intention, perceived behavioral control and pro-environmental behavior. According to the results, the pandemic has led to an increase in people's knowledge about their environment and has positively affected individuals' subjective norms, or the perceived social pressure to get involved in environmentally friendly actions. Individuals' attitude to perform pro-environmental behaviors has also increased as a result of this incident. Moreover, the role of perceived behavioral control over environmental actions has been influenced by the pandemic situation and the COVID-19 crisis has positively influenced the relationship between intention and pro-environmental behavior.

Keywords: COVID-19; Intention; Pro-environmental behavior; Theory of Planned Behavior.

Copyright © 2021 Elsevier B.V. All rights reserved.

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• Published: 25 May 2022

A comprehensive evaluation of COVID-19 policies and outcomes in 50 countries and territories

• Hsiao-Hui Tsou 1 , 2 ,
• Shu-Chen Kuo 3 ,
• Yu-Hsuan Lin 1 , 4 , 5 , 6 ,
• Chao A. Hsiung 1 ,
• Hung-Yi Chiou 1 , 7 , 8 ,
• Wei J. Chen 9 , 10 ,
• Shiow-Ing Wu 1 ,
• Huey-Kang Sytwu 3 ,
• Pau-Chung Chen 11 , 12 , 13 , 14 ,
• Meng-Hsuan Wu 1 ,
• Ya-Ting Hsu 1 ,
• Hsiao-Yu Wu 1 ,
• Fang-Jing Lee 15 ,
• Shu-Man Shih 1 ,
• Ding-Ping Liu 16 , 17 &
• Shan-Chwen Chang 18  

Scientific Reports volume  12 , Article number:  8802 ( 2022 ) Cite this article

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• Epidemiology
• Health policy
• Infectious diseases

The COVID-19 pandemic struck the world unguarded, some places outperformed others in COVID-19 containment. This longitudinal study considered a comparative evaluation of COVID-19 containment across 50 distinctly governed regions between March 2020 and November 2021. Our analysis distinguishes between a pre-vaccine phase (March–November 2020) and a vaccinating phase (December 2020–November 2021). In the first phase, we develop an indicator, termed lockdown efficiency (LE), to estimate the efficacy of measures against monthly case numbers. Nine other indicators were considered, including vaccine-related indicators in the second phase. Linear mixed models are used to explore the relationship between each government policy & hygiene education (GP&HE) indicator and each vital health & socioeconomic (VH&SE) measure. Our ranking shows that surveyed countries in Oceania and Asian outperformed countries in other regions for pandemic containment prior to vaccine development. Their success appears to be associated with non-pharmaceutical interventions, acting early, and adjusting policies as needed. After vaccines have been distributed, maintaining non-pharmacological intervention is the best way to achieve protection from variant viral strains, breakthrough infections, waning vaccine efficacy, and vaccine hesitancy limiting of herd immunity. The findings of the study provide insights into the effectiveness of emerging infectious disease containment policies worldwide.

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Introduction.

The COVID-19 (coronavirus disease 2019) pandemic unleashed extraordinary challenges on humanity. Governments implemented various policies aimed at containing the spread of infection and stabilizing their economies. Many institutions—including the Economist Intelligence Unit 1 , Oxford COVID-19 Government Response Tracker (OxCGRT) 2 , NLI Research Institute 3 , and Bloomberg 4 —have assessed global responses to the COVID-19 pandemic. However, evaluation criteria differ across these institutions (Supplementary I nformation 1 –3), and their studies have had different focuses and produced varying evaluation results.

Here, we introduce a set of criteria for assessing virus-containment effectiveness, where the aim of containment is to minimize harm to societies and economies. The proposed criteria include several previously examined indicators, namely monthly cases per 100,000 members of a population (per capita), fatality rate, and GDP loss. Additionally, because OxCGRT's stringency index (SI) 2 cannot reflect rigor accurately based on monthly case numbers (Supplementary I nformation 4 ), we propose a lockdown efficiency (LE) parameter, which relates stringency to incidence 5 (Supplementary I nformation 5 ). We include the following five OxCGRT indicators of health-system policies 2 : public information campaigns, testing policy, contact tracing, facial coverings, and (from December 2020 onward) vaccination policy.

To track long-term impacts on health literacy and mental health, we collated data from Google searches for “wash hands”, “face mask”, and “insomnia” as surrogates for national population health literacy and mental health. Surveys on COVID-19–related mental health and health literacy are mostly based on self-reported, cross-sectional studies and rarely multinational 6 . However, population health literacy and mental health trends have been shown to be reflected in search volume trends 7 , 8 . The search engine analysis website Google Trends has been used for population mental-health surveillance as well as for long-term tracking of depression 9 and suicide 10 .

The availability of COVID-19 vaccines cast new hope for curbing the pandemic. Until August 19, 2021, the World Health Organization had issued only emergency-use authorizations for COVID-19 vaccines 11 . By September 12, 2021, 42% of the worldwide population had received at least one dose of a vaccine 12 . Therefore, we incorporate vaccine-related indicators into our research.

We propose a set of ten indices, including four government policy and hygiene education (GP&HE) indicators and six vital health and socioeconomic (VH&SE) measures. Our research is divided into pre- and post-vaccine availability phases. For the first phase (March 2020 to November 2020), we focus on evaluating the appropriateness of the LE indicator, which we developed using linear mixed models to determine how each GP&HE indicator correlates with each VH&SE measure. In the second phase during which there was ongoing vaccine distribution (December 2020 to November 2021), we added vaccine-related indicators to enable more comprehensive containment performance analyses. We compared indicator scores for 50 distinctly governed territories.

Our scoring system, modified from previous studies 2 , 3 , includes GP&HE indicators and VH&SE measures. The GP&HE indicators include: LE; health-system policies; health literacy indicators; and vaccine coverage of the population (December 2020 onward). The VH&SE measures include: one-month cases per capita; infection growth rate; fatality rate; GDP loss due to the pandemic; unemployment rate; and psychological impact (Table 1 ) 2 , 5 , 13 , 14 , 15 .

GP&HE indicators

Government response is associated with COVID-19 incidence 2 . Our newly introduced indicator LE is calculated based on COVID-19 incidence data and the SI 2 , a factor that does not account for COVID-19 incidence. LE has a reasonable correlation with one-month cases per capita (Supplementary I nformation 4 and 5 ).

We developed another indicator called health-system policies, which is a simple average of the four OxCGRT indicators: public information campaigns, testing policy, contact tracing, and facial coverings 2 . Each of these indicators is derived from daily data, and thus could potentially be represented with monthly means or modes. We used monthly modes as the representative score for each month. From December 2020 onward, we added OxCGRT vaccination policy 2 to the calculation of the health-system policies indicator.

Health literacy is beneficial to reducing the spread of infectious diseases 7 . Therefore, Google Trends were used to obtain search trends for “wash hands” and “face mask”, which act as surrogate indicators of health literacy 7 (Supplementary I nformation 6 ).

For the second phase of the research (December 2020–November 2021), we added the aforementioned indicator people covered by vaccines 15 by modifying the calculation of health-system policies to include vaccination policy. This indicator was calculated as the ratio of the number of vaccine doses administered to the number of doses required for full vaccination. For simplicity, we assumed that every individual in each country needs only two doses of vaccine.

VH&SE measures

NLI Research Institute definitions of one-month cases per capita, infection growth rate, and fatality rate were adopted 3 . Unemployment rate and GDP loss were defined relative to the same timeframe in 2020–2021 and 2019–2020 (Table 1 ). We quantified change in searches for “insomnia” to indicate the extent of the pandemic’s impact on a population’s mental health. Searches for insomnia have been used to assess the mental impact of COVID-19 8 , 16 , 17 more commonly than searches for anxiety, panic attack 17 , 18 , depression 8 , or suicide 8 .

Correlation analyses

In phase one, linear mixed models were used to explore the relationship between each GP&HE indicator and VH&SE measure. Because these values vary over time and may affect each other, we conducted two-stage analyses (Supplementary I nformation 4 ). We tested LE and SI legitimacy 2 . In phase two, we calculated Spearman's rank correlation coefficients to determine whether the indicator “people covered by vaccines” correlates with three vital health indicators, namely one-month cases per capita, infection growth rate, and one-month case fatality rate.

Scoring of GP&HE indicators and VH&SE measures

We ranked the performance of 50 countries and territories according to total indicator scores (Supplementary I nformation 7 and 8 ), where a higher score implies better containment performance. We graphed the score distribution (Supplementary Figs. S11 - S31 ) to visualize the relationship between pre-pandemic baseline risk levels and monthly containment scores. We assigned all 50 countries and territories to low, medium, or high baseline risk categories and calculated monthly average containment scores for each risk level (Supplementary I nformation 9 ).

Geographic comparison

We calculated monthly average containment scores for six geographic group and conducted two-sample t-tests and Mann–Whitney U-tests to compare containment performance between Latin American and non-Latin American countries and between Asian and non-Asian countries prior to vaccine introduction (Supplementary I nformation 10 and 11 ). Additionally, we compared mean containment performance scores before versus after inclusion of vaccine indicators (Fig.  2 ).

Statistical analyses were conducted via SAS software (version 9.4); P values were two-tailed with 0.05 significance level.

Sensitivity analysis

We conducted sensitivity analysis to determine the robustness of our study results in relation to uncertainties in the indicator calculation methods and the inclusion/exclusion of Google Trends indicators. Nine scenarios were evaluated (e.g. daily score means vs. modes; see Supplementary Table S35 ). The results obtained with different methods of calculating indices are given in Supplementary Tables S36 –S40. Revised calculations with the inclusion of Google Trends are reported in Supplementary Tables S41 –S44. The results obtained with the main scenarios (as defined in Table 1 ) are shown in Supplementary Tables S45 and S46 , with the former including Google Trends indicators and the latter excluding Google Trends indicators. For the sensitivity analysis, we compared: (1) data in each of Supplementary Tables S36 –S40 to the results in Supplementary Table S46 ; (2) data in each of Supplementary Tables S41 –S44 to the results in Supplementary Table S45 ; and (3) data in each of Supplementary Tables S36 –S39 to data in respective Supplementary Tables S41 –S44 (i.e., Supplementary Table S41 vs. Supplementary Table S36 , Supplementary Table S42 vs. Supplementary Table S37 ; Supplementary Table S43 vs. Supplementary Table S38 ; Supplementary Table S44 vs. Supplementary Table S39 ).

Ethical approval

The institutional review board of the National Health Research Institutes approved this study (EC1091110-E-R1).

Comparison between LE and SI prior to vaccine availability

Two-stage linear mixed models revealed no reasonable relationship between OxCGRT’s SI and one-month cases per capita (Supplementary I nformation 4 ). For each unit increase in the SI in July 2020, the estimated one-month cases per capita in August 2020 increased by 7.83 people ( P  = 0.03; Supplementary Table S2 ). Similar trends are observable for other months, contradicting the expectation that an increase in government policies in month s should reduce case numbers in month s  + 1.

For every unit of increase in LE (defined in Table 1 ) in month s , the estimated one-month cases per capita in month s  + 1 decreases. For each unit of increase in LE in September and October 2020, one-month cases per capita in October and November 2020 decrease by 629.55 and 597.94 people, respectively (both P  < 0.0001; Supplementary Table S3 ). Although the relationships between LE and one-month cases per capita are not statistically significant in other months, we observe a consistent downward trend in cases subsequent to lockdowns.

From our analyses, we deduce that our LE indicator is legitimate, and that the SI does not have a reasonable correlation with one-month cases per capita. Therefore, we use LE as an indicator in our subsequent evaluation.

Two stage-linear mixed models also show that the health-system policy in month s does impact fatality in month s  + 1 within some periods of time. For every unit of increase in health-system policies in April and May 2020, fatality rates in May and June 2020 decrease by 7.84% and 3.86%, respectively ( P  < 0.05; Supplementary Table S4 ).

COVID-19 containment effectiveness

Performance scores for citizens’ health literacy and insomnia (Google Trends data) for six territories over the 21-month study period are shown in Fig.  1 . All monthly COVID-19 containment rankings and scores from March 2020 to November 2021 are shown in Supplementary Tables S6 and S7 and in Supplementary Tables S13 –S33 (Supplementary I nformation 8 and 12 ). The best performing countries and territories in 2020 are located mainly in Asia and Oceania, including Taiwan, the Republic of Korea (Korea), and New Zealand.

Performance scores of six countries analyzed from March 2020 to November 2021. A vaccination indicator was available only from December 2020 to November 2021 (shaded area). The calculation criteria include Google Trends data (i.e., health literacy and psychological impacts indexed by insomnia). Score range, 0–100, with 0 being the worst containment performance.

Baseline risk

Low- and middle-baseline-risk territories are concentrated in Asia, including Vietnam, Korea, and Taiwan, whereas high-baseline-risk nations are located mostly in Europe, including France and the UK. Countries in the Americas span the three risk levels (Fig.  3 a). In the first phase, most low- and middle-baseline-risk countries and territories achieved better containment than their high-risk counterparts. Some countries, such as New Zealand and Finland, were able to restrain COVID-19 transmission despite having high baseline risk levels (Fig.  3 b, Supplementary I nformation 9 and Supplementary Fig. S32 a).

Geographical comparison prior to vaccine allocation

Prior to vaccine distribution, Latin America was severely impacted by the pandemic, while Oceania and Asia had good containment (Fig.  4 a). Non-Latin American nations achieved better overall containment performance than their Latin American counterparts, which were severely affected. From April 2020 to September 2020, performance differed between these two groups, with and without Google Trends data inclusion ( P  < 0.027; Supplementary I nformation 10 ).

Asian governments outperformed their non-Asian counterparts in phase one (Supplementary I nformation 11 ). From March to November 2020, with the exception of July 2020, performance scores of Asian countries were higher than those of non-Asian countries, with and without Google Trends data inclusion ( P  < 0.039).

Asian countries performed dramatically better than non-Asian countries in LE and health-system policies early in the pandemic (April 2020 LE scores P  = 0.007; March/April 2020 health-system policy scores P  < 0.003). These results suggest that Asian governments enacted effective policies early (Supplementary I nformation 11 ).

Scoring system robustness

Sensitivity analyses revealed that (1) changing indicator calculation methods and (2) adding Google Trends indicators altered overall rankings slightly (Supplementary I nformation 13 ).

Performance after vaccine distribution

The best performers in 2020 were mostly in Asia and Oceania, including Taiwan, Korea, Japan, Thailand, and New Zealand. After vaccine indicators are included, the containment performance scores of these countries decrease. Inclusion of vaccine indicators from December 2020 onward results in higher containment performance scores in Singapore, Peru, Chile, Colombia, and Argentina (Figs.  2 , 3 b,c and 4 ). Among the six geographic regions analyzed, North American countries have the highest vaccine coverage. Their containment performance improves rapidly when vaccine indicators are included. Similar improvements are observed in Europe and Latin America (Fig.  4 ). Most high-baseline risk countries benefit from their high vaccination coverage (Supplementary Fig. S32 ).

Average of performance scores in pre-vaccine and vaccine phases of the study. Nine and ten indicators (including Google Trends data) were used to obtain performance scores in pre-vaccine and vaccine phases of the study, respectively. Note that countries/territories with missing data were excluded.

Distribution of baseline risk levels of countries and territories in each geographic region ( a ), and for containment scores (with Google Trends data) in pre-vaccine phase ( b ) and in vaccine phases ( c ). Note that most low- and medium-baseline-risk countries and territories are located in Asia, Latin America, and Africa, while high-baseline-risk areas are located mainly in Europe and North America (excluding Mexico). Note: Hong Kong is excluded due to insufficient data for calculating baseline risk.

Comparison among geographic regions for containment effectiveness ( a ) and people covered by vaccines ( b ) from March 2020 to November 2021. Vaccination indicator available only from December 2020 to November 2021 (shaded area).

Vaccination coverage

In the first 6 months of vaccine distribution, one-month cases per capita in month t correlates positively with vaccine coverage in month t and subsequent months. With the exception of the relationship between one-month cases per capita in May 2021 and people covered by vaccines in August 2021, all remaining months correlated ( P  < 0.0246). In the first 3 months after vaccine distribution ensued (December 2020–February 2021), people covered by vaccines in month t correlated negatively with infection growth rate in the subsequent t + 3, t + 4, or t + 5 months ( P  < 0.0461). Starting in March 2021, people covered by vaccines correlates negatively with infection growth rate in respective subsequent months, though the relationship does not reach statistical significance for all months. A delayed negative correlation of people covered by vaccines with fatality rate can be seen. Starting from June 2021, the number of people vaccinated in month t correlated negatively with fatality rate in month t and subsequent months ( P  < 0.0394) (Supplementary Tables S47 –S49).

To evaluate COVID-19 containment performance impartially, we developed and tested a comprehensive evaluation method that accounts for GP&HE indicators, VH&SE measures, and vaccination. LE captures a nation’s effectiveness in enacting measures according to recent incidence. As variants continue to emerge, a new normal, in which pharmaceutical and non-pharmaceutical interventions are considered should be established. Because it is unreasonable to expect life to normalize completely in the short term, we did not include the global normalcy index 19 in our analyses.

Our sensitivity analysis showed that inclusion of the Google Trends indicator altered the overall rankings of the 50 examined countries and territories slightly. We included it for three reasons: Google Trends data reflect health literacy and impacts on mental health 7 , 8 ; none of the global institutions assessing COVID-19 containment effectiveness have included public responses in their evaluation criteria; and we believe that public response is important for transmission control.

Prior to vaccine allocation, some countries and territories in Asia and Oceania were more successful at suppressing COVID-19 outbreaks than their European and American counterparts. They exhibited a relative weakening of containment performance after inclusion of the vaccine indicator (since December 2020), likely due, at least in part, to their lower vaccination coverage (Supplementary I nformation 12 , Fig.  4 ).

New Zealand and Singapore emerged as the most stable performers. New Zealand has been steadfast in its fight against the vexatious COVID-19, increasing its LE to overcome spikes in infection (March/April 2020) and in fatality (May 2020). Successful containment has contributed to their economic stability during the first phase of pandemic (Supplementary I nformation 12 ). After New Zealand was invaded by the Delta variant in August 2021 20 , the number of confirmed cases and infection rates increased, and New Zealand responded with an accelerated vaccination strategy (Supplementary I nformation 12 ).

Although Singapore did not control rapid viral spread initially, they recovered from outbreaks well. Following a 5-month period of rising cases (April–August 2020), the Singapore government improved its health-system policies and LE, leading to decreased case numbers thereafter. Since January 2021, Singapore has been administering vaccines efficiently, making it a model nation for curbing COVID-19 (Supplementary I nformation 12 ). However, the surge in coronavirus infections and confirmed cases in Singapore since September 2021 may be related to Singapore’s “coexisting with COVID-19” strategy and the Delta variant outbreak 21 , 22 . Whether Singapore can achieve the goal of "live with the virus" has become the focus of global attention.

Changes in containment performance scores of six locations associated with notable performance, activities, or policies are shown in Fig.  1 . Denmark and the UK have high vaccination coverage 23 . Denmark lifted restrictions on September 10, 2021 24 . Starting on July 19, 2021, the UK lifted most of its restrictions and removed social distancing recommendations 25 . In all US regions, restrictions have eased and people have returned to generally normal life 26 . The 2020 Olympic and Paralympic Games took place in Tokyo, Japan from July 23 to August 8 and from August 24 to September 5 of 2021, respectively 27 . Vietnam was Asia's top-performing economy in 2020 28 . Taiwan has been praised for its 253-day streak without local infections 29 .

Denmark's infection growth increased rapidly from September 2020 to January 2021, though their fatality rate remained low. Transmission was mitigated through strict health-system policies, improved LE, and mass vaccinations. Although the number of confirmed cases increased after May 2021, the fatality rate was low. The pandemic within Denmark appeared to be under stable control, but at the end of the study Denmark faced another new wave of outbreaks, the development of which remains to be seen (Fig.  1 , Supplementary I nformation 12 ).

Containment performance in the UK was not satisfactory in phase one. The UK improved LE and health-system policies while administering vaccinations on a massive scale. These efforts enabled a gradual containment of COVID-19 transmission, which was suppressed by March 2021. There was a case/infection growth surge in June 2021 (Fig.  1 , Supplementary I nformation 12 ).

The USA did not control infection well in the first phase, but its containment performance improved in the second phase. They have endured large numbers of confirmed cases with cascading regional surges (Fig.  1 , Supplementary I nformation 12 ).

Japan adopted inclusive health-system policies. Although their confirmed cases increased during the 2021 Olympics, Japan had several prior waves of increased case numbers, including two in 2021 (January and May). Whether the increase in confirmed cases during the Olympics can be attributed to Olympic event gatherings remains to be clarified (Supplementary I nformation 12 ).

Vietnam performed well in early but experienced a short-term containment performance decline in August 2020. Vietnam controlled an outbreak that emerged in February 2021 successfully. Infection growth in Vietnam has been relatively high since May 2021, and was only slightly contained until October, but then increased again in November. Transmission in late summer 2021 may reflect Delta variant invasion under low vaccination coverage (Fig.  1 , Supplementary I nformation 12 ).

Taiwan is an exemplary case. COVID-19 transmission was suppressed early owing to a rapid response by Taiwan's Central Epidemic Command Center with cooperation from local government agencies and the public 30 . Taiwan suffered a case surge under low vaccine coverage in May and June 2021. The Central Epidemic Command Center responded with intensive data gathering, expansive testing, quarantines, and stringent non-pharmaceutical policies 31 . Faced with the highly transmissible Delta variant, Taiwan suppressed case numbers within 2 ~ 3 months (Fig.  1 , Supplementary I nformation 12 ).

While countries seek to increase vaccination coverage, vaccine effectiveness has been tested by the Delta variant and breakthrough infections. In addition to vaccination, non-pharmacological interventions, such as handwashing, masking, and physical distancing, remain important for preventing transmission.

Public health implications

Our research suggests that the top performing nations tend to enact rigorous health system policies and locally-appropriate lockdown measures, especially early in the pandemic (Supplementary I nformation 12 , and Supplementary Table S11 ). Asian countries’ border control policies were implemented earlier than non-Asian countries. In Asian and non-Asian countries, the median times to any border closure from the first reported case in China were 24.50 and 67.50 days, respectively ( P  = 0.0003), and the median times to any border closure from the first domestic case within each country were -10.50 and 8.00 days, respectively ( P  = 0.0027) (Supplementary Table S50 , Supplementary I nformation 15 ). Notwithstanding, stringent lockdown measures should not be enacted without careful consideration, and lockdown policies should be adjusted in response to recent incidence. Flexibility in their implementation can yield containment with minimal harm to societies, economies, and mental health.

Limitations

Several methodological limitations should be noted. First, we include unemployment rate and GDP loss, but not international aid, economic stimulus packages, or other fiscal measures. Second, Google Trends data do not represent a random sampling and may exclude vulnerable groups without internet access or those not actively searching. Third, ideally, only local infection rates should be considered to obtain precise LE measurements. However, because daily local case data are not fully available, we used incidence data inclusive of imported cases to determine LE scores. Therefore, minor inaccuracies in our LE data are expected (Supplementary I nformation 5 ).

Conclusions

This longitudinal study considers government policy indicators, health literacy, health, and socioeconomic criteria between March 2020 and November 2021. For analyses of the data from the period of time preceding vaccine availability, we factor in nine GP&HE indicators and VH&SE measures of the overall COVID-19 containment performance in 50 countries and territories. Following introduction of vaccines, we incorporate relevant vaccine indicators. Our findings provide insights into the effectiveness of emerging infectious disease containment policies worldwide.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files.

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Acknowledgements

The authors thank Dr. Shih-Chung Chen of the Ministry of Health and Welfare, Taipei, Taiwan, Dr. Jih-Haw Chou and Dr. Jen-Hsiang Chuang of the Taiwan Centers for Disease Control, Taipei, Taiwan, and Dr. Kung-Yee Liang of the Institute of Population Health Sciences, the National Health Research Institutes, Taiwan, for their insightful and constructive comments. The authors thank Dr. Shou-Hsia Cheng of the Institute of Health Policy and Management, the College of Public Health, National Taiwan University, Taiwan, for his insight and expertise on two-stage regression model. The authors thank Ms. Ting-Yun Chiu of the Institute of Population Health Sciences, the National Health Research Institutes, Taiwan, for her help with data management. Their expertise greatly assisted in the success of this research.

This study was supported by grants PH-109-PP-02, and PH-110-GP-02 from the National Health Research Institutes, a nonprofit foundation dedicated to medical research and improved healthcare in Taiwan.

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Hsiao-Hui Tsou, Yu-Hsuan Lin, Chao A. Hsiung, Hung-Yi Chiou, Shiow-Ing Wu, Meng-Hsuan Wu, Ya-Ting Hsu, Hsiao-Yu Wu & Shu-Man Shih

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All authors contribute significantly to the design and conduct of this study and have approved submission of this paper for review by your Journal in its present form. The authors’ contribution is listed below: H.H.T., S.C.K., C.A.H., H.Y.C., W.J.C., and S.I.W. contributed significantly to the study’s conception and design. H.H.T., S.C.K., and Y.H.L. contributed to the drafting of the manuscript. H.Y.W., S.M.S., F.J.L., and Y.T.H. contributed to data preparation and validation. M.H.W., Y.T.H., H.Y.W., and F.J.L. provided statistical analysis. C.A.H., H.Y.C., W.J.C., P.C.C., H.K.S., S.I.W., D.P.L., and S.C.C. contributed to interpretation of the data. C.A.H., H.Y.C., W.J.C., P.C.C., H.K.S., and S.I.W. provided administrative, technical, and material support. The research was supervised by H.H.T. H.H.T. is the corresponding author.

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Tsou, HH., Kuo, SC., Lin, YH. et al. A comprehensive evaluation of COVID-19 policies and outcomes in 50 countries and territories. Sci Rep 12 , 8802 (2022). https://doi.org/10.1038/s41598-022-12853-7

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Impact of COVID‐19 on changing consumer behaviour: Lessons from an emerging economy

Debadyuti das.

1 Faculty of Management Studies, Delhi University, Delhi India

Ashutosh Sarkar

2 Indian Institute of Management Kozhikode, Kozhikode India

Arindam Debroy

3 Symbiosis Institute of Business Management Nagpur, Nagpur Maharashtra, India

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The authors declare that the data used in the paper is collected through a questionnaire survey and have not used any proprietary data from any source. The data collected through the primary survey may be made available on demand.

The present study investigates the impact of COVID‐19 on Consumers' changing way of life and buying behaviour based on their socio‐economic backgrounds. A questionnaire survey was carried out to understand the impact of COVID‐19 on consumers' affordability, lifestyle, and health awareness and how these effects influenced their buying behaviour. A total of 425 usable responses were analysed using the structural equation modelling considering Consumers' socio‐economic background as exogenous variables and Consumers' changing way of life and Adaptation in consumers’ buying behaviour as endogenous variables. The study reveals that COVID‐19 has affected the consumers in the unorganised sectors more than others and induced an increase in the demand for affordable substitutes for daily necessities. The demand for wellness and entertainment products is found to depend upon the occupation and family earning status of consumers which is jointly mediated by affordability and lifestyle changes. Further, the findings show that the demand for health and hygiene products depends on the current employment status and family earning status of consumers which is jointly mediated by affordability and awareness towards health and hygiene. The model developed in the present study allows the decision‐makers to identify which segments of the population with certain socio‐economic backgrounds could be targeted for wellness products and which ones could be targeted for health and hygiene products. In addition, the model provides rich insights to the managers as to what kind of product substitution would be viable in the market during the pandemic.

1. INTRODUCTION

COVID‐19 has disrupted humankind in a manner not seen in recent times, infecting 6.5 million people while leaving millions unemployed (Hensher,  2020 ). While the loss of life, occupation, and livelihood are well‐articulated impacts of COVID‐19, the loss of routine social and economic life over a prolonged period is having long‐lasting effects on people (Chriscaden,  2020 ). COVID‐19‐imposed ‘self‐isolation and social lockdown’ has increased mental stress and inflicted psychological and behavioural changes (Witteveen,  2020 ). Under constant fear of infection and restricted mobility, people are becoming more aware of health and changing their lifestyles and eating habits (Sánchez‐Sánchez et al.,  2020 ). Reported preliminary studies also suggest that the nature and extent of the impact of COVID‐19 is not similar across all citizens and depend on their condition of poverty, age, residential status, and other demographic variables (U n ited Nations, n.d.).

As a consequence of the economic, social, and psychological impact of COVID‐19, people have altered how and where they should spend their money (Rogers & Cosgrove,  2020 ). Kirk and Rifkin ( 2020 ) argued that consumers react, cope, and adapt to environmentally‐imposed constraints such as the COVID‐19 pandemic. During the pandemic, consumers have displayed a variety of unusual behaviours (Laato et al.,  2020 ; Pantano et al.,  2020 ) and forced them to spend more on essentials while cutting back discretionary spending. Consumers are also observed to have changed brands and products, substituted spends when stocked out, and become more sensitive towards health and hygiene. Market studies pertaining to the impact of COVID‐19 on consumers have also indicated increased spending on groceries, and health and hygiene products (Rogers & Cosgrove,  2020 ). The above changes have motivated researchers to explore how the consumers behaved during the pandemic and the reasons for such behaviour.

Some of the COVID‐19‐induced behaviours that were studied include consumption shifts (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ), impulsive buying (Naeem,  2020 ), stockpiling, and panic buying (Billore & Anisimova,  2021 ; Keane & Neal,  2021 ; Naeem,  2020 ; Prentice et al.,  2021 ), product and brand substitution (Knowles et al.,  2020 ), and shifts in channel preferences (Mehrolia et al.,  2021 ; Pantano et al.,  2020 ). Researchers have attributed such behaviour to COVID‐19‐induced impacts on consumers' socio‐economic status, changing way of life, and influence on predisposed beliefs (Milaković, 2021 ), changes in the consumers' buying environment such as stockouts, supply and demand disruptions (Prentice et al., 2021 ), and external stimuli such as information and social media exposure. (Laato et al.,  2020 ; Naeem,  2020 ). It was also reported that a significant number of people have lost their jobs (Montenovo et al.,  2020 ) and family income dwindled as a consequence of COVID‐19 (Kansiime et al.,  2021 ). COVID‐19 has affected consumers' disposable income or affordability (Mahmud & Riley,  2021 ), lifestyle (Sánchez‐Sánchez et al.,  2020 ), and awareness (Li et al.,  2021 )—in short, their way of life—making them change their pre‐COVID spending habits. We, however, did not come across research studies that analysed the nature of changes in consumer behaviour due to changes in consumers' affordability, lifestyle changes, and awareness level. This suggests an opportunity to investigate the impact of COVID‐19 on Consumers' changing way of life and consequently on their buying behaviour based on the varying socio‐economic background of the population. Our research primarily focuses on studying consumption shifts and substitution behaviour and connects such changes to the changes in consumers' way of life. Such studies are very important for market researchers and firms in terms of segmentation of the market when a pandemic of this nature affects the entire population. Such studies would help firms in devising targeted marketing strategies during the ongoing pandemic and beyond. With this background, the present study seeks to address the following research questions:

• How has the socio‐economic background influenced Consumers' way of life including affordability, lifestyle changes, and awareness towards health and hygiene arising out of COVID‐19?
• To what extent has the Consumers' changing way of life arising out of COVID‐19 influenced Adaptation in their buying behaviour?
• How has the socio‐economic background led to the Adaptation in consumers' buying behaviour arising out of COVID‐19?

The methodology followed in this study involves investigating the influence of exogenous variables including occupation, current employment status, and family earning status on the intervening variables representing Consumers' changing way of life and finally on the dependent variables which reflect the Adaptation in consumers' buying behaviour. The study provides important insights to managers in terms of designing affordable substitute products of daily necessities for the vulnerable section of the society. In addition, it also provides insights to the policy planners in terms of developing appropriate intervention strategies for the affected consumers.

2. BACKGROUND LITERATURE

Adaptations in people's buying behaviour due to COVID‐19 are in line with the existing literature encompassing changes in consumers' needs and preferences induced by events that are environmental, social, biological, cognitive, and behavioural in nature (Mathur et al.,  2006 ). Such disruptions often force consumers to seek stability (Minton & Cabano,  2021 ) and, as a result, they display conservative and planned behaviour (Sarmento et al.,  2019 ). Such stability‐seeking behaviour induces austerity measures among consumers affected by economic recession or slowdown making consumers more price‐sensitive (Hampson & McGoldrick,  2013 ). While, in the past, pandemics such as influenza have affected economic activities significantly (Verikios et al.,  2016 ), some changes in consumers’ behaviour are not entirely due to the economic impacts. For example, during the outbreak of the Asian flu, consumers have displayed risk‐coping strategies that influenced their consumption of chicken meat (Yeung & Yee,  2012 ). Similarly, natural disasters such as Hurricane Katrina contributed to stress‐induced compulsive and impulsive buying behaviour among the affected residents of the US Gulf Coast (Sneath et al.,  2009 ). During natural disasters, consumers have been observed to have spent on luxury brands and premium categories displaying both cross‐category indulgence (Mark et al.,  2016 ) and impulsive buying behaviour (Kennett‐Hensel et al.,  2012 ).

Recently, adaptations in consumers' buying behaviour due to COVID‐19 have been studied under various themes (Kansiime et al.,  2021 ; Laato et al.,  2020 ; Pakravan‐Charvadeh et al.,  2021 ; Pantano et al.,  2020 ; Rayburn et al.,  2021 ). Gordon‐Wilson ( 2021 ) noted that external influences such as COVID‐19 affected ‘consumer's feelings for self‐control’ by changing their shopping behaviour, type of shopping and preference of store format, and consumption of unhealthy snacks and alcohol. Kim et al. ( 2021 ) highlighted the influence of protection motivation in explaining consumers' commitment to hygienic behaviour, prioritization of local restaurants, and conscious consumption. Guthrie et al. ( 2021 ) employed the react‐cope‐adapt framework to understand how consumer behaviour has evolved in terms of their usage of e‐commerce as a result of stressful events such as the COVID‐19. Eroglu et al. ( 2022 ) revealed that the crowding in retail stores significantly affects the shopping satisfaction of consumers during COVID‐19, which is mediated by customer‐employee rapport. They further argued that such relationships significantly differ based on consumers' perceptions about the appropriateness of retailer precautions, the severity of threats, and vulnerability to COVID‐19. Milaković ( 2021 ) demonstrated the moderating effect of consumer adaptability in explaining the influence of consumer vulnerability and consumer resilience on purchase satisfaction and finally on the repurchase intention of consumers. Yap et al. ( 2021 ) introduced a new dimension called technology‐mediated consumption as a coping strategy adopted by consumers in coping with pandemic‐induced stress and anxiety during the pandemic. They further discussed paradoxes explaining the nexus between the consumption of technology and consumer vulnerability. Nayal et al. ( 2021 ) identified various coping strategies for firms to take care of the employee and customer well‐being. Digitalization and innovation emerged as the two focus areas for adoption by firms for their survival post‐COVID‐19. In addition, the study further revealed that consumers have demonstrated a shift in their consumption behaviour during the present pandemic in favour of hygiene, sustainability, and local products.

The present study also deals with the shifts in consumption behaviour and product substitution behaviour among consumers that were observed during COVID‐19. However, our study is quite different from the existing studies in the sense that we attribute such shifts in consumption and product substitution behaviour to how COVID‐19 has impacted the Consumers' way of life. COVID‐19 pandemic has induced changes in consumers' demand—both in magnitude as well as in their preference (del Rio‐Chanona et al.,  2020 ). The pandemic has also resulted in increased consumption of certain products which were either consumed in lesser quantities or not consumed at all before the event (Kirk & Rifkin,  2020 ). Such effects have led to significant upward shifts in the market demand for these products. We refer to such shifts as ‘new demand’. Examples of ‘new demand’ include cleaning and personal hygiene products such as Lysol and hand sanitizers (Chaudhuri,  2020 ), health and wellness products such as vitamins, healthy foods, and other immunity boosters (Hess,  2020 ), packaged goods and beverages, household care products, fresh and organic foods, personal care products (Knowles et al.,  2020 ) and digital platforms (Debroy,  2020 ), which displayed a surge in demand during COVID‐19. Consumers have also displayed substitution behaviour during the pandemic (Knowles et al.,  2020 ) thereby changing significantly the consumption both by volume as well as product preference. Product substitution is also observed during this pandemic due to lifestyle changes while the change of preference is observed due to awareness of health. The literature on product substitution is characterized by several factors prompting substitution behaviour by consumers (Hamilton et al.,  2014 ). However, while studying new demand and product substitution behaviour under disruptive events, we observed that most of these studies are limited to the economic impacts of the events (Martin et al.,  2020 ) and hence, there is still scope for studying such behaviour considering the non‐economic impacts of the pandemic.

Disruption affects people's lives in a variety of ways derailing their normal ways of living. Earlier studies on disruptions dealt with disruption‐induced depression, lifestyle changes, changes in information, awareness, and education (Mathur et al.,  2006 ; Sneath et al.,  2009 ). During the present pandemic also, significant changes in lifestyle and health awareness (Arora & Grey,  2020 ) were observed. The fear of getting infected with COVID‐19 and the government‐imposed lockdowns have reduced mobility and physical activities (Sánchez‐Sánchez et al.,  2020 ); changed dietary and consumption behaviour (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ), and sleep behaviour (Chopra et al.,  2020 ). COVID‐19 has also increased health concerns and awareness impacting consumption of health and wellness products in a significant manner (Baiano et al.,  2020 ; Hess,  2020 ). However, lifestyle changes, awareness towards health, and change in consumption behaviour arising out of COVID‐19 were not found to be uniform across people of diverse socio‐economic groups (Laato et al.,  2020 ). As COVID‐19 has affected the entire population in varying degrees based on their socio‐economic background, there exists a scope for research as to how different consumer groups have adapted their buying behaviour.

3. THEORETICAL MODEL AND DEVELOPMENT OF HYPOTHESES

In order to understand how COVID‐19 has impacted consumers’ way of life and consumer buying behaviour, we mainly draw from preliminary studies, market surveys, and published research articles on the impact of COVID‐19. This study mainly has three dimensions: (1) Consumers' socio‐economic background, (2) Consumers' changing way of life, and (3) Adaptation in consumers' buying behaviour as shown in Figure  1 , which serves as the theoretical model of the present work. Consumers' changing way of life has been captured through ‘Change in affordability’, ‘Lifestyle changes’ and ‘Awareness towards health and hygiene’ arising out of COVID‐19 while Adaptation in consumers' buying behaviour has been represented through ‘Creation of new demand for wellness and entertainment products’, ‘Creation of new demand for health and hygiene products’, ‘Substitution of daily necessities due to affordability’ and ‘Substitution of daily necessities due to awareness towards health’.

Theoretical model of the impact of COVID‐19 on consumer behaviour

3.1. Consumers' socio‐economic background and affordability

COVID‐19 has significantly influenced individual and household incomes and spending habits. However, such economic hardships varied based on their occupation, employment status, and socio‐demographic background (Witteveen,  2020 ). The adverse effects are estimated to be strongest for those occupations that are characterized by lower levels of skill, education, and income, have lesser possibilities of working remotely (Adams‐Prassl et al.,  2020 ), and require more face‐to‐face interpersonal contacts (Avdiu & Nayyar,  2020 ; Montenovo et al.,  2020 ). We have observed that some people have received lower than the regular salary in their current employment while a few others have lost their jobs during lockdowns which has adversely affected their capacity to sustain the household expenditure. Many studies have observed that family income, personal savings, and occupational status affected the ability of a household to continue their pre‐COVID spending (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ; Piyapromdee & Spittal,  2020 ). In addition, the ability to support the household expenditure is found to depend upon the number of earning members, which further reflects the earning potential of a family (Addabbo,  2000 ). Hence, based on the above discussion, we postulate the following hypotheses:

Occupation significantly influences the affordability of consumers.

Current employment status significantly influences the affordability of consumers.

Family earning status significantly influences the affordability of consumers.

3.2. Consumers' socio‐economic background and lifestyle changes

COVID‐19 has brought a dramatic change in the lifestyle of people. However, the change is different for people belonging to different socio‐economic backgrounds. While occupations such as travel, restaurants, Micro, Small, and Medium Enterprises (MSME) have seen reduced business activities, there are people in other occupations, for whom work from home during the pandemic is like a much‐needed break from their monotonous schedule. Thus, the nature of occupation seems to have an impact on the work schedule and lifestyle changes of people. Many studies have noted that occupational social class and status are associated with the lifestyle of people (García‐Mayor et al.,  2021 ). Likewise, receiving a reduced salary or having lost their job during lockdown seems to have had a considerable influence on consumers' lifestyles in terms of daily routine, thought process, and social habits (Khubchandani et al.,  2020 ; PTI,  2020 ). On the other hand, the lifestyle of a family with multiple earning members may be significantly different from a family with a sole earning member (Pew Research,  2008 ). Thus, we advance the following hypotheses:

Occupation significantly influences the lifestyle changes of consumers.

Current employment status significantly influences the lifestyle changes of consumers.

Family earning status significantly influences the lifestyle changes of consumers.

3.3. Consumers' socio‐economic background and awareness towards health and hygiene

COVID‐19 has resulted in people becoming more conscious about their health and personal hygiene (Baiano et al.,  2020 ; Hess,  2020 ). Government advisories and campaigns for maintaining personal hygiene through regular hand washes and wearing masks have resulted in people becoming concerned about their hygiene like never before. However, as occupation varies with the level of education, so does the awareness towards health and hygiene (Teisl et al.,  1999 ). Similarly, awareness towards health and hygiene varies with employment status and family earning status (Prasad et al.,  2008 ). Based on this, we posit the following hypotheses:

Occupation significantly influences the awareness level of consumers towards their health and hygiene.

Current employment status significantly influences the awareness level of consumers towards their health and hygiene.

Family earning status significantly influences the awareness level of consumers towards their health and hygiene.

3.4. Affordability and consumers' buying behaviour

Due to reduced affordability, a large number of people are restricting their expenditure to mostly essentials and healthcare products while cutting down on non‐discretionary products (Martin et al.,  2020 ). This has led to a reduction in sales of many non‐essentials. The pandemic, however, has witnessed a significant rise in the demand for wellness and entertainment products delivered through digital platforms (Bakhtiani,  2021 ; Madnani et al.,  2020 ). Since such subscriptions by consumers are discretionary (Singh,  2020 ), we expect an influence of reduced affordability due to the pandemic on the creation of new demand. Equivalently, it could also be stated that a positive change in affordability would have a positive impact on the usage of such products (Bakhtiani,  2021 ; Madnani et al.,  2020 ). Earlier studies in economics and public health have noted that family income significantly influences demand for hygiene products and associated practices (Aunger et al.,  2016 ; Jacob et al.,  2014 ). In many cases, consumers with lower affordability also explored cheaper alternatives such as private labels and affordable brands (Mishra & Balsara,  2020 ). Therefore, based on the above arguments, we postulate the following hypotheses:

Creation of new demand for wellness and entertainment products is significantly associated with the change in affordability.

Creation of new demand for products relating to health and hygiene is significantly associated with the change in affordability.

The demand for affordable substitute products of daily necessities is significantly associated with the change in affordability.

3.5. Lifestyle changes and demand for wellness and entertainment products

Lifestyle changes due to COVID‐19 have made people more sensitive to fitness that caused a surge in demand for wellness products (Ojha,  2020 ). Many people are now preferring organic and herbal products and are subscribing to fitness classes and channels (Wernau & Gasparro,  2020 ). Furthermore, institutional lockdowns imposed by governments have forced people to stay at home and spend time with their families (Debroy,  2020 ). Additionally, with a regular source of entertainment such as restaurants and movie theatres remaining restricted, people have turned to online platforms for recreation. Even online yoga classes have experienced a spike in their viewership with the spread of this virus (Debroy,  2020 ). Thus, we propose the following hypothesis:

Creation of new demand for wellness and entertainment products is positively associated with Lifestyle changes.

3.6. Awareness towards health and hygiene and demand for health and hygiene products

Marketing experts have always emphasized the importance of increasing awareness among consumers to increase product demand (Baiano et al.,  2020 ; Hess,  2020 ). COVID‐19 has resulted in people becoming more conscious about their health and personal hygiene. As part of maintaining a proper and healthy lifestyle, regular hand washes and wearing masks are considered to be the defence mechanisms of protecting oneself from the virus. Common people have been spending more on buying healthcare products (Rakshit,  2020 ). Moreover, the current times have witnessed an incomparable urge in people to substitute unhealthy food items and daily necessities with healthy ones (Master,  2020 ; Renner et al.,  2020 ). Thus, the following hypotheses are advanced:

Creation of new demand for products relating to health and hygiene is positively associated with consumers' awareness towards health and hygiene.

The demand for healthy substitute products of daily necessities is positively associated with consumers' awareness towards health and hygiene.

3.7. Consumers' socio‐economic background and creation of new demand for wellness and entertainment products

During this pandemic, fitness and wellness products, and digital platforms such as Netflix have become very popular (Debroy,  2020 ). However, the nature of demand for wellness and entertainment products varied across people with different socio‐economic backgrounds. A person's occupation, employment status, and family income influence consumers' preference for wellness products (Suresh & Ravichandran,  2011 ) and also have a considerable impact on the creation of new demand for wellness and entertainment products (Madnani et al.,  2020 ). Therefore, we propose to investigate further the relationship between consumers with diverse socio‐economic backgrounds and the creation of new demand for wellness and entertainment products. Thus, we postulate the following hypotheses:

Occupation significantly influences the creation of new demand for wellness and entertainment products.

Current employment status significantly influences the creation of new demand for wellness and entertainment products.

Family earning status significantly influences the creation of new demand for wellness and entertainment products.

3.8. Consumers' socio‐economic background and creation of new demand for health and hygiene products

This pandemic has also seen an increased demand for health and hygiene products (Dsouza,  2020 ). People have been forced to spend on hand washes, sanitizers, and masks to protect against this rapidly spreading virus. As there are occupations that would put an individual and her/his family into different levels of vulnerabilities (Avdiu & Nayyar,  2020 ), we expect variations in the consumption of health and hygiene products based on their occupation (Riise et al.,  2003 ). Earlier research has established the relationship between family income and consumers' preference for healthy food (Galati et al.,  2019 ; Pakravan‐Charvadeh et al.,  2021 ). The reduced income and job losses would have a significant bearing on both mental stress as well as disposable income (Witteveen,  2020 ) which, in turn, influence the choice of consumers for health and hygiene products (Khubchandani et al.,  2020 ). Therefore, the creation of new demand for health and hygiene products seems to vary depending on the types of occupation, current employment status, and family earning status. Thus, we propose the following hypotheses:

Occupation significantly influences the creation of new demand for products relating to health and hygiene.

Current employment status significantly influences the creation of new demand for products relating to health and hygiene.

Family earning status significantly influences the creation of new demand for products relating to health and hygiene.

4. RESEARCH METHODOLOGY

4.1. design of survey instrument and its reliability.

The findings of Paul and Bhukya ( 2021 ) reveal that the impact of COVID‐19 on consumer behaviour is one of the important contemporary topics of research. However, we could not find any suitable questionnaire in the extant literature with specific reference to the hypothesized research model depicted in Figure  1 which could be directly utilized for data collection purposes. We came across several items in the literature for other kinds of disasters, which were found relevant for our study. In addition, we also observed through newspapers, electronic media, and social media the challenges faced by the consumers in respect of reduced salary, job losses, health issues, the surge in demand for products relating to health and hygiene, etc. arising out of COVID‐19. We took cognizance of all these aspects and framed an open‐ended questionnaire in the initial phase to develop an understanding of different types of challenges faced by the consumers and their impact on changing consumer behaviour. The open‐ended questionnaire was translated into Hindi, Malayalam, and Bengali with the help of three bilingual experts having expertise in Hindi, Malayalam, and Bengali languages respectively along with English. We administered this questionnaire to consumers with different linguistic and socio‐economic backgrounds. We identified five respondents from Government/Public Sector organisations, five from Multinational/Private sector firms, and five from MSMEs. In addition, we identified three independent businessmen and seven daily wage‐earners. All these respondents were requested to participate in the study after thoroughly explaining to them the purpose of undertaking this particular exercise. They agreed to take part in the study. However, the daily wage‐earners had to be given INR100/‐ each to motivate them to take part in the study. Amongst these respondents, some of them could understand Hindi well, some of them could understand Malayalam well while a few others could understand Bengali well. In the case of employees of Public sector and Private sector firms, the questionnaire was sent through email with the request to provide unambiguous responses within a week. In the case of the employees of MSMEs and independent businessmen, we took separate appointments through telephonic calls and requested that one of the authors would seek responses from them in person by maintaining the protocol of social distancing. One author from Delhi and another author from Kozhikode separately conducted this exercise in Delhi and Kozhikode respectively. Finally, in the case of daily wage‐earners, we directly talked to a few rickshaw‐pullers, a few street vendors, and a few masons and managed to secure their responses after incentivizing them. We asked the questions verbally to this category of respondents and they replied to the specific questions based on their experience. Thus, we had to record the conversations which were later transcribed.

Based on the responses received from the preliminary study, we summarized them under different sections and designed another open‐ended questionnaire. The purpose of designing the second‐round open‐ended questionnaire was to cross‐check the same with the experts and to ensure adequate and appropriate coverage of the items under different sections thereby taking care of the content validity of the questionnaire. For example, we identified several items reflecting the financial distress faced by the common people due to COVID‐19 and put them under ‘Affordability’. We requested the experts to exercise their judgment in terms of whether those items represent the essence of ‘Affordability’. Those experts were chosen who had considerable experience in selling essential items either through the offline or online channel. In addition, a few more experts were also selected who conducted research in consumer behaviour for a sufficient period. Accordingly, we selected experts from both academia and industry, which included one Professor of Marketing, two researchers doing research in consumer behaviour, one manager from an offline store selling essential items, and one executive from an online retailer. These experts were known to be thoroughly conversant with the impact of COVID‐19 on the consumers’ way of life and also their changing buying behaviour across consumers of varying socio‐economic backgrounds. The experts recommended the retention of most of the items and the removal of very few ones. Subsequently, we designed the close‐ended questionnaire based on the recommendation of the experts. The close‐ended questionnaire was divided into three sections. The first section contained questions relating to the socio‐demographic profile and earning status of the respondents. The second section carried questions about the factors influencing Consumers' changing way of life arising out of COVID‐19. Finally, the third section contained questions pertaining to the adaptations on consumers' buying behaviour due to COVID‐19. A five‐point Likert scale ranging from 1 = Not at all True to 5 = Absolutely True was used as a response format in the second and third sections. The questionnaire was shown to the same experts once again to elicit their opinion for evaluating its ease of understanding from the perspective of potential respondents. Based on the recommendation of experts, some questions were rephrased. This exercise helped us in ensuring the content validity of the questionnaire. Table  1 presents the first part of the questionnaire while Appendices  1 and 2 show the second and third parts of the questionnaire respectively.

Distribution of the respondents based on socio‐demographic background ( n  = 425)

Subsequently, the reliability of the questionnaire was tested by administering the survey on 30 respondents chosen carefully. Cronbach's alpha of the scale representing Consumers' changing way of life turned out to be 0.795 while the same for the scale showing Adaptation in consumers’ buying behaviour was found to be 0.895. Both the scales showed high corrected item‐to‐total correlations which indicated the presence of high internal consistency. Since the alpha value of both scales was well above the threshold level of 0.7, these scales were considered reliable (Hair et al.,  2009 ).

4.2. Target respondents and collection of data

The survey was administered amongst the respondents with diverse socio‐economic backgrounds in India. The questionnaire was circulated among people working in Government organisations, private sector organisations, MSMEs, and also among the daily wage‐earners. Given the diversity of the languages, we administered the survey in four languages including, English, Hindi, Malayalam, and Bengali. The above languages were chosen as a substantial percentage of the population of India speaks these languages. Efforts were also made to ensure that only one response is received from a single household. Because of the lockdown and the restrictions on mobility, we chose a variety of mediums to reach out to the potential respondents. We approached the potential respondents both through online and offline mode. In the case of online mode, the questionnaire was circulated on social media mainly through LinkedIn, WhatsApp, and Facebook urging people to respond to the questionnaire. These mediums were chosen for their immense popularity in India in terms of the number of users. They were further selected as the authors also have their active networks and groups in these platforms. In the case of offline mode, some respondents were sent questionnaires via email while others were administered through hard copies of the questionnaire in a language of their choice. Field‐workers were hired against remuneration who physically received the responses directly by visiting the respondents' doorsteps or by reaching out to them in public places like, malls, popular restaurants, and shops. Field‐workers were clearly instructed to explain the essence of the questionnaire to the respondents thoroughly before asking them to fill out the questionnaire. They were further advised not to fill out the questionnaire on behalf of the respondents. The questionnaire survey was administered over two months during August and September 2020. During this period, different parts of India were experiencing a variety of restrictions depending on the number and severity of COVID‐19 cases in different places. A total of 494 responses were received out of which 69 responses were found to be incomplete and incoherent. Thus, we were left with 425 usable responses for the final analysis.

4.3. Tests for potential bias in survey data

Non‐response bias was assessed by performing a t ‐test on the scores of early and late respondents based on the assumption that the opinions of late respondents are representative of the opinions of non‐respondents (Krause et al.,  2001 ). A total of 241 responses (56.7%) were received in the first month (i.e., August 2020) while 184 responses (43.3%) were received in the second month (i.e., September 2020). Respondents giving responses in the first month were considered as early respondents while those giving responses in the second month were treated as late respondents. T ‐tests were carried out between early respondents with 241 responses and late respondents with 184 responses on individual items. The results did not reveal any significant difference between the two groups for most of the items. This indicates that the data was relatively free from non‐response bias.

As this study relied on single respondents for doing the final analysis, the potential for common method bias to influence the results was also evaluated. We applied Harman's one‐factor test to evaluate common method bias separately on the scale representing Consumers’ changing way of life and the scale reflecting Adaptation in consumers’ buying behaviour . We carried out the above test separately for both the scales in IBM SPSS (version 25) by doing exploratory factor analysis without rotation. All 13 items representing Consumers’ changing way of life were allowed to be loaded into one single factor and again all 16 items reflecting Adaptation in consumers' buying behaviour were loaded into another single factor. It was found that the common factor representing Consumers' changing way of life explained only 25% of the total variance while the common factor capturing Adaptation in consumers' buying behaviour explained only 30.4% of the total variance. Since the total variance of a single factor was less than 50% in both the scales, the common method bias did not seem to be a concern for the present study (Podsakoff et al.,  2003 ).

5. DATA ANALYSIS AND INTERPRETATION

The 425 usable responses were also checked for missing values and inconsistency. An overview of the respondents' demographic profile, descriptive statistics, Confirmatory Factor Analysis (CFA), and the validation of the conceptual model using the Structured Equation Modelling (SEM) is presented in the following sub‐sections. We utilized IBM SPSS (version 25) for finding out the descriptive statistics of manifest variables and the demographic profile of the respondents. In addition, we also employed IBM SPSS AMOS (version 24) for carrying out CFA and SEM. Regarding descriptive statistics, we determined the minimum score, maximum score, mean and standard deviation of all items of both the scales and presented the same in Appendices  1 and 2 .

5.1. Demographic profile

The socio‐economic profile of 425 respondents revealed that most of them were of working age with a sizeable number of respondents (71.53%) turning out to be male. A majority of the respondents were employed (74.83%). However, a substantial portion of respondents lost their jobs or was receiving reduced salaries after the imposition of lockdown (35.76%). In terms of educational qualification, a major portion of the respondents (69.88%) were graduates with 56% of them having earned their degree in a professional course. The family earning status of the respondents showed that 29.88% were the sole earners in their family. The details of the demographic profile are provided in Table  1 .

5.2. Confirmatory factor analysis

The questionnaire developed through several rounds of an iterative process and validated by the experts allowed us to determine the underlying constructs. We observed that Consumers' changing way of life consists of three constructs while Adaptation in consumers' buying behaviour comprises four constructs. We applied CFA to assess how well the observed variables including 13 items relating to the Consumers' changing way of life and another 16 items representing Adaptation in consumers' buying behaviour arising out of COVID‐19 reflect unobserved or latent constructs in the hypothesized structure. In the CFA model, all seven constructs were allowed to be correlated with each other forming a composite measurement scale representing the Consumers' changing way of life and Adaptation in consumers' buying behaviour due to COVID‐19. The model was assessed by utilizing the maximum likelihood (ML) method. One of the prerequisites of the ML method is the normality of the endogenous variables (Kline,  2016 ). Thus, for ascertaining whether the data of the endogenous variables follow a normal distribution or not, we computed the kurtosis value. We observed that the values of almost all variables remained within the range of −7 to +7, which assuaged the concern regarding the non‐normality of the data (Mueller & Hancock,  2019 ).

All items were evaluated based on several criteria including items standardized regression weights, squared multiple correlations, and standardized residual covariance. In addition, the theoretical importance and practical significance of every item were taken into consideration while refining the model. This resulted in the removal of five variables of the Consumers' changing way of life and another three variables of Consumers' buying behaviour from the model thereby leaving eight items of Consumers' changing way of life and another 13 items of Consumers' buying behaviour in the final measurement model. This, however, did not significantly affect the content validity of the scale. Rather the model became further parsimonious. We found that one construct namely ‘lifestyle changes’ was left with only two items. However, it did not give rise to the problem of under‐identification of the measurement model. The findings of Das ( 2018 ) and Pullman et al. ( 2009 ) revealed several constructs which contain only two items. The presence of such constructs with two items did not create the problem of under‐identification of measurement models in the above research findings. Goodness of fit (GOF) measures of the final measurement model were as follows: χ 2  = 338.939, degrees of freedom ( df ) = 162, p  = .00, χ 2 / df  = 2.092, goodness fit index (GFI) = 0.931, Adjusted Goodness of Fit Index (AGFI) = 0.902, Comparative Fit Index (CFI) = 0.951, Tucker‐Lewis Index (TLI) = 0.937, Root Mean Square Error of Approximation (RMSEA) [90% CI] = 0.051 [0.043, 0.058], Standardized Root Mean Residual (SRMR) = 0.0512. For an adequate model fit, the fit indices of GFI, CFI, and TLI should be at least 0.9 while the same of RMSEA and SRMR should be less than 0.08 (Hair et al.,  2009 ). Thus, based on the fit indices, it could be inferred that the measurement model fits well with the data on all major indices. The details of the measurement results are shown in Table  2 , which includes the descriptive statistics of the constructs pertaining to the Consumers' changing way of life and Adaptation to consumers' buying behaviour . This includes the mean, standard deviation, and reliability value (Cronbach's alpha) of each construct and also the inter‐construct correlations.

Summary of the measurement results and inter‐construct correlations

The above table shows that Cronbach's alpha coefficients of six constructs out of seven have exceeded 0.7 thereby indicating sound reliability of these constructs (Hair et al.,  2009 ). Alpha coefficient of the remaining one construct reveals acceptable reliability value over 0.6 (Hair et al.,  2009 ). In addition, Table  2 also shows that almost all inter‐construct correlations are significant at 0.1% or 1% level. Only one inter‐construct correlation is significant at 10% level. These inter‐construct correlations help us in ascertaining the discriminant validity of all the constructs, which is discussed in the later part of this section.

This model was systematically evaluated for Construct Reliability (CR), convergent validity, and discriminant validity in order to validate the constructs of the Consumers' changing way of life and Adaptation to consumers' buying behaviour due to COVID‐19. In the present study, we have estimated the CR coefficient of all constructs which is shown in Table  3 . The estimate of CR lying between 0.6 to 0.7 is considered acceptable while the value above 0.7 suggests good reliability of a construct (Hair et al.,  2009 ). Thus, the six constructs may be considered to possess excellent reliability while the remaining one construct is characterized by an acceptable level of reliability.

Results of Reliability, Convergent and Discriminant validity of the consumers' changing way of life and consumers' buying behaviour

Abbreviations: AVE, average variance extracted; CR, construct reliability.

Convergent validity requires that the indicator variables of a given construct share a high proportion of variance in common. It was evaluated by following two different approaches. The first method involves the inspection of estimated factor loadings of items on the constructs in the final CFA model (Anderson & Gerbing,  1988 ). It was found that the standardized loadings of all items are greater than 0.5 and statistically significant ( p  < .001). The second method involves the assessment of convergent validity with the help of Average Variance Extracted (AVE). An AVE of 0.5 or more of a construct indicates a high level of convergent validity (Hair et al.,  2009 ). The seven constructs have AVE ranging from 0.477 to 0.648 as shown in Table  3 . Six constructs have more than the threshold level of AVE (0.5), thus indicating a high convergent validity of the above constructs. Only the lifestyle changes construct is found to have an AVE slightly below the threshold value. However, since this construct meets the criteria of convergent validity in the first method and in the second method, the value of AVE is somewhat close to the threshold value, the lifestyle changes construct may be considered to possess a reasonable level of convergent validity.

Discriminant validity is a measure of how a construct is distinct from other constructs in the same model and whether each construct is measuring different concepts (Hair et al.,  2009 ). Discriminant validity was also assessed by following two different approaches. The first method involves the investigation of the correlation between each pair of constructs in the CFA model. If the correlations between constructs are well below 0.9; then there is very little possibility that a group of items loading significantly on one construct would also load on another construct (Kline,  2016 ). The correlations between the constructs occurred within the range of −0.282 to 0.616, which were well below 0.9. This is reported in Table  2 . The second method involves the comparison of the AVE of each construct with the shared variance of each pair of constructs. If the square root of the AVE of each construct is more than the correlation of each pair of constructs, then this implies that the constructs account for a greater proportion of variance of the items that are assigned to them (Fornell & Larcker,  1981 ). Table  3 shows that the lowest value of AVE of a construct is 0.477. Its square root is 0.690, which exceeds the maximum correlation coefficient of 0.616 between a pair of constructs as reported in Table  2 . Thus, the seven construct CFA model demonstrates a satisfactory level of discriminant validity. This facilitated the SEM on the final measurement model to be carried out for investigating the relationships hypothesized in Section  3 .

5.3. Structural equation modelling

The final measurement model has been taken as the main input for developing the structural model. In the structural model, demographic variables of the respondents including occupation, current employment status, and family earning status were considered as the exogenous variables while Consumers' changing way of life and consumers’ buying behaviour arising out of COVID‐19 were treated as endogenous variables. This was investigated through SEM and the hypotheses formulated earlier were tested. The model was assessed utilizing the ML estimation method. GOF measures of the structural model were as follows: χ 2  = 887.533, df  = 324, p  = .00, χ 2 / df  = 2.739, GFI = 0.878, AGFI = 0.825, TLI = 0.840, CFI = 0.881, RMSEA [90% CI] = 0.064 [0.059, 0.069], SRMR = 0.075. The fit indices indicate that TLI and CFI are below the acceptable level of 0.9 while RMSEA and SRMR are within the acceptable range of 0.08 (Hair et al.,  2009 ). In this context, it is to be mentioned that the model complexity in terms of the number of observed variables, number of parameters estimated, etc. has a significant negative impact on GFI, AGFI, and CFI. Thus, the general rules of thumb with the cut‐off values of GFI or CFI being at least 0.9 may sometimes be misleading for complex models (Baumgartner & Homburg,  1996 ). A similar observation was also made by Srinivasan et al. ( 2002 ) in respect of model complexity. In one of the measurement models developed by them, both CFI and TLI were found below 0.9. However, since both RMSEA and SRMR remained within the acceptable range of 0.08, the model was considered reasonably fitting to the data. Based on the above argument, we can infer that the present findings indicate an acceptable level of fit to the above indices. The final structural model is shown in Figure  2 . We have shown only the significant paths in this model, which include both direct effects and total effects covering both direct and indirect effects. The interpretation of these paths has been provided in appropriate places of the following section.

Final model of the impact of COVID‐19 on consumer behaviour

6. MAJOR FINDINGS

6.1. influence of occupation, employment status and earning status on affordability.

The profile of the socio‐demographic and economic background of the respondents provided in Table  1 reveals that they differ in terms of their occupations, current employment status, and also their earning status. The respondents were categorized into five types of occupations described as Job1 through Job5. In terms of employment status, they were categorized into four types which have been shown as Emp1 through Emp4. Finally, the respondents were classified into three categories in terms of the earning potential of their family, which have been designated as Earn1 through Earn3. All these categorizations in terms of occupation, employment status, and earning status have been indicated in Table  4 . The categorical variables were transformed into binary variables individually before considering them as exogenous variables. In the structural model, Job1, Emp1, and Earn2 were considered as the reference categories for occupation, employment status, and earning status respectively following Cohen et al. ( 2003 ), as each one of them was the most dominant category in the respective socio‐economic classes and least likely to be affected compared to other categories by the pandemic. Out of 21 hypotheses formulated in Section  3 , 15 hypotheses had a direct effect while the remaining six hypotheses involved both direct and indirect (mediating) effects. Tables  4 and ​ and5 5 present the results of hypotheses that only have a direct effect, based on standardized regression weights (β), critical ratios (t‐value), and p values. Table  4 specifically describes the results of the effect of Consumers' socio‐economic background on their changing way of life. The results of Hypothesis  1a showing the relationship between occupation and affordability reveal that the affordability of people with four types of occupations (Job2 through Job5) was negatively affected due to COVID‐19 compared to the affordability of people belonging to the reference category, i.e., Job1. However, the negative effect was found to be significant only for people with occupation categories Job3 and Job5. This suggests that the lockdown affected the affordability of people in the unorganised sector more than the organised sector. The results of Hypothesis  1b explaining the relationship between current employment status and affordability indicate that there was a significant negative effect on the affordability of people of three types of employment (Emp2 through Emp4) due to COVID‐19 compared to the same belonging to the reference category, i.e., Emp1. This directly demonstrates that people having lost their job or receiving reduced salaries due to COVID‐19 were severely affected in terms of their affordability compared to the people who were receiving full salaries. Hypothesis  1c describing the relationship between family earning status and affordability shows that the affordability of people with two categories of earning status (Earn1 and Earn3) was not affected due to COVID‐19 compared to the reference category, i.e., Earn2. This further illustrates the fact that the respondents with a single earning member, multiple earning members, or non‐earning members cannot be differentiated in terms of their affordability due to COVID‐19. The significant impact of occupation with categories Job3 and Job5 on affordability and again the significant effect of employment status including categories Emp2 through Emp4 have been indicated in the final structural model (Figure  2 ).

Results of structural model for socio‐economic factors (direct effects) ( n  = 425)

Job1: Respondents who are working in government or public sector jobs; Job2: Respondents who are working in private sector jobs; Job3: Respondents who are working in MSME sectors/ Contractors/ Daily wage earners;

Job4: Respondents who own their own business or startups; Job5: Respondents with other job profiles.

Emp1: Respondents who are currently employed and getting full salary; Emp2: Respondents who are currently employed but are getting reduced salary; Emp3: Respondents who have lost their jobs during lockdown; Emp4: Respondents with other employment status;

Earn1: Respondents who are the sole earners of the family; Earn2: Respondents who are one of the earning members of the family; Earn3: Respondents who are the non‐earning members of the family.

Results of structural model of consumers' way of life (direct effects) ( n  = 425)

6.2. Influence of occupation, employment status and earning status on lifestyle changes

Following a similar approach, we investigated the influence of occupation, current employment status, and earning status on lifestyle changes of people due to COVID‐19. Hypothesis  2a showing the relationship between occupation and lifestyle changes reveals that the lifestyle changes of people with Job2 through Job5 were significantly affected in opposite direction compared to the lifestyle changes of people with reference category, i.e., Job1. This demonstrates that people other than those engaged in the Government or Public sector did not indulge themselves in lifestyle changes arising out of COVID‐19. Hypothesis  2b explaining the relationship between current employment status reveals that the lifestyle changes of people with Emp2 and Emp3 were positively affected compared to the lifestyle changes of people with reference category, i.e., Emp1. The effect was found to be significant. This signifies that the people receiving a reduced salary or having lost their jobs are becoming more concerned with doing yoga and using herbal products in their day‐to‐day life compared to the people receiving full salary. Hypothesis  2c delineating the relationship between family earning status and lifestyle changes shows that the lifestyle changes of people with Earn1 and Earn3 were not affected compared to the reference category, i.e., Earn2. This indicates that the lifestyle changes of people cannot be differentiated based on their earning status. The significant effect of occupation with categories Job2 through Job5 on lifestyle changes and further the significant effect of employment with categories Emp2 and Emp3 on lifestyle changes have been shown in Figure  2 .

6.3. Influence of occupation, employment status and earning status on awareness towards health

Hypothesis  3a describing the relationship between occupation and awareness towards health reveals that the health awareness of people with occupations Job2 through Job5 was negatively affected compared to the awareness of people with reference category, i.e., Job1. However, the effect was found significant only in the case of Job2. Hypothesis  3b showing the relationship between employment status and awareness towards health indicates that the awareness of people with categories Emp2, Emp3, and Emp4 was not affected compared to the reference category, i.e., Emp1. This implies that the awareness of people towards health cannot be distinguished based on their employment status. Finally, Hypothesis  3c outlining the relationship between earning status and awareness towards health shows that the awareness of people with Earn1 and Earn3 was not affected compared to the reference category, Earn2. This further explains that the awareness of people towards health cannot be discriminated against based on their earning status. The significant effect of occupation with category Job2 on awareness towards health is shown in Figure  2 .

6.4. Association of Affordability, Lifestyle Changes and Health Awareness with Demand for Wellness Products, Health Products, Substitution of Affordable necessities etc

Table  5 presents the results of the impact of different constructs constituting Consumers' changing way of life on the Adaptation in consumers’ buying behaviour . Hypothesis  4a reveals that the increase in demand for wellness and entertainment products was associated with a fall in affordability. However, the effect was not significant. Similarly, the increase in demand for products relating to health and hygiene was associated with a non‐significant decrease in affordability as specified in Hypothesis  4b . Hypothesis  4c shows that the fall in affordability had a significant influence on the demand for affordable substitute products of daily necessities. Hypothesis  5 shows that lifestyle changes had a significant positive influence on the demand for wellness products which explains the reported rise in demand for wellness and entertainment products during the pandemic. Further, increased awareness towards health and hygiene had a significant positive influence on the demand for products relating to health and hygiene as also on the demand for healthy substitute products of daily necessities as described in Hypotheses  6a and 6b respectively. The significant results of Hypotheses  4c , 5 , 6a , and 6b have been delineated in Figure  2 . Thus, our study validates many of the anecdotal explanations that are observed in market surveys and news reports on the effect of COVID‐19 on consumers' changing buying behaviour.

6.5. Influence of occupation on the demand for wellness products

Test results of the remaining six hypotheses involving both direct and indirect effects of socio‐economic background , Consumers’ changing way of life, and consumers' buying behaviour have been shown individually in Tables  6 , ​ ,7, 7 , ​ ,8, 8 , ​ ,9. 9 . These tables show the direct effect, indirect effect, and total effect of the relationships. We utilized the AMOS plugin developed by Gaskin and Lim ( 2018 ) for estimating the specific indirect effect in IBM SPSS AMOS (version 24). Table  6 presents the results of Hypothesis  7 explaining the influence of occupation on the demand for wellness and entertainment products. We considered Job1 as the reference category and tested the scores obtained by categories Job2 through Job5 against the reference category. The results show that the occupation with category Job3 had a significant negative influence on the creation of new demand for wellness and entertainment products compared to the reference category. The association is moderate which is mediated through two mediating constructs: (1) Change in affordability and (2) Lifestyle changes. Further, the mediation is partial. However, it was observed that the creation of new demand for wellness and entertainment products by the remaining categories of occupations including Job2, Job4, and Job5 did not significantly differ from the demand created by the reference category. We present the results of Hypothesis  7 in Table  6 for occupation with category Job3 only. We further show the results of the total significant effect of occupation with category Job3 on the demand for wellness and entertainment products in Figure  2 through a bold arrow.

Hypothesis  7 Influence of occupation on the demand for wellness products (direct, indirect and total effects) ( n  = 425)

Hypothesis  9 Influence of earning status on the demand for wellness products (direct, indirect and total effects) ( n  = 425)

Hypothesis  11 Influence of emp. Status on the creation of new demand for health products (direct, indirect and total effects) ( n  = 425)

Hypothesis  12 Influence of earning status on the creation of new demand for health products (direct, indirect and total effects) ( n  = 425)

6.6. Influence of employment status and earning status on the demand for wellness products

We investigated the results of Hypothesis  8 describing the influence of current employment status on the demand for wellness products considering Emp1 as the reference category and observed that the current employment status of people with categories Emp2 through Emp4 did not have a significant influence on the creation of new demand for wellness and entertainment products compared to the reference category. Since the results of Hypothesis  8 involving all categories of employment status were insignificant, we have not reported the results. We analysed the results of Hypothesis  9 explaining the influence of family earning status on the demand for wellness products considering Earn2 as the reference category. The results are presented in Table  7 . The results reveal that the earning status of people of category Earn1 had a significant negative influence on the creation of new demand for wellness and entertainment products compared to the reference category. The relationship is mediated by two mediating constructs: (1) Change in affordability and (2) Lifestyle changes and the mediation is full. It was further observed that the earning status of people of category Earn3 did not have any significant influence on the demand for wellness and entertainment products compared to the reference category. The significant effect of Hypothesis  9 explaining the influence of earning status with category Earn1 on the demand for wellness and entertainment products is represented in Figure  2 .

6.7. Influence of occupation, employment status and earning status on the demand for health products

We analysed the influence of occupation on the creation of new demand for health and hygiene products considering Job1 as the reference category and found that the occupation with categories Job2 through Job5 did not have a significant influence on the creation of new demand for health and hygiene products compared to the reference category. We, therefore, have not reported the results of Hypothesis  10 . We investigated the results of Hypothesis  11 delineating the influence of current employment status on the creation of new demand for health and hygiene products considering Emp1 as the reference category. The results show that the employment status of category Emp3 had a significant positive influence on the creation of new demand for health and hygiene products compared to the reference category. The association is mediated by two constructs: (1) Change in affordability and (2) Awareness towards health and hygiene and the mediation is partial. We did not observe any significant influence of employment status with categories Emp2 and Emp4 on the creation of new demand for health and hygiene products compared to the reference category. Table  8 presents the results of hypothesis Hypothesis  11 for employment status with category Emp3 only. We have further shown the total significant effect of Hypothesis  11 in respect of employment status of category Emp3 in Figure  2 . Finally, Table  9 outlines the results of Hypothesis  12 explaining the influence of earning status on the creation of new demand for health and hygiene products considering Earn2 as the reference category. The results reveal that the family earning status of category Earn3 had a significant positive influence on the creation of new demand for health and hygiene products compared to the reference category. The association is mediated by two constructs: (1) Change in affordability and (2) Awareness towards health and hygiene and the mediation is partial. The significant total effect of Hypothesis  12 in respect of earning status of category Earn3 is depicted in Figure  2 . The earning status of people of category Earn1 did not have any significant influence on the demand for health and hygiene products compared to the reference category.

7. DISCUSSION

7.1. theoretical contributions.

The main theoretical contribution of the study involves understanding the impact of the socio‐economic background of the respondents in terms of their occupation, employment status, and family earning status on Consumers’ changing way of life and subsequently on consumers’ changing buying behaviour at a granular level in the context of the pandemic. While earlier researchers had studied consumption shifts during the pandemic (Laato et al.,  2020 ; Pakravan‐Charvadeh et al.,  2021 ), we are not aware of any study that investigated the Consumers' changing way of life and their changing buying behaviour arising out of COVID‐19 based on the socio‐economic background of the consumers. Although the survey was carried out in India in the backdrop of COVID‐19 pandemic, the findings of the study could provide important insights to other emerging economies afflicted with COVID‐19. Thus, it may be considered as a significant contribution to the existing body of consumer behaviour literature.

Second , we have gone beyond panic buying and stockpiling behaviour, which are extensively covered in the earlier works (Kirk & Rifkin,  2020 ; Laato et al.,  2020 ), with an attempt to link affordability, lifestyle changes, and health awareness with consumer behaviour. The findings of the study demonstrating the impact of consumers' socio‐economic background on their affordability, lifestyle changes, and awareness towards health and finally on the adaptation in consumers' buying behaviour arising out of COVID‐19 have enabled us to develop a theoretical model which seems to be generalisable for other similar kinds of pandemics in the emerging economies. Third , the extant literature suggests that during the period of the pandemic, consumers focus mostly on essential products and exercise control on discretionary expenditure. However, the present study notes that the demand for some discretionary products (e.g., the demand for wellness and entertainment products) has shown a varying pattern depending on the occupation and earning potential of a family during the pandemic. We have further demonstrated that this change in demand for wellness products among consumers of certain socio‐economic groups is not merely due to the economic impacts but also due to the pandemic‐induced lifestyle changes. By including lifestyle changes, we have added a new dimension to the understanding of consumers’ behaviour during the pandemic and enriched similar studies by earlier researchers such as Naeem ( 2020 ) who attributed consumers’ impulsive buying to information overload. Fourth, the study reveals that the creation of new demand for health and hygiene products was found to depend upon the current employment status and family earning status of consumers which is jointly mediated by affordability and awareness towards health and hygiene. These findings enrich our understanding of consumers' behaviour in terms of their demand for wellness products as also the demand for health and hygiene products during the pandemic (Pakravan‐Charvadeh et al.,  2021 ). Finally , the study further reveals that the consumers demonstrated product substitution behaviour due to the availability of affordable substitutes of daily necessities and also due to the availability of healthy substitutes of daily necessities. Therefore, our study confirms product substitution behaviour during the pandemic as noted by Knowles et al. ( 2020 ). Thus, it may also be considered to be another unique contribution of the present study.

7.2. Managerial implications

The study reveals that the affordability of the most vulnerable section of people including daily wage earners and those working in MSMEs has been affected due to COVID‐19. The study also finds that the affordability of the people receiving a reduced salary or having lost their jobs has also been severely affected. This provides an important insight to the policy planners in terms of developing targeted intervention strategies with a view to providing economic aid to the affected people. In addition, the study provides insights to marketing managers in terms of designing and introducing affordable substitute products of daily necessities for a substantial section of the population. Thus, there lies an opportunity to penetrate the market with inexpensive substitutes in a market already occupied by established brands.

The study shows that people engaged in most of the occupations other than Government or public sector jobs are not much concerned with lifestyle changes arising out of COVID‐19. However, it shows that people receiving a reduced salary or having lost their jobs have become quite active in practicing yoga and utilizing herbal products. This possibly indicates that these consumers have become sensitive in maintaining their health due to the fear of contagion despite the challenging situation faced by them in their professional lives. On further scrutiny, we observed that the demand for wellness products by people working in the unorganised sectors is significantly lower than those working in the organised sectors. It is significantly less in a family with a sole earning member than in a family with multiple earning members. In addition, the demand for wellness products by people receiving a reduced salary or having lost their jobs does not significantly differ from people receiving full salary. Thus, the market planners need to carefully take into consideration the socio‐economic factors of the consumers including occupation, employment status, and family earning status while introducing wellness products in the market. Increased awareness towards health and hygiene motivates marketing managers to introduce innovative products relating to health and hygiene and healthy substitute products of daily necessities. To boost demand, designing appropriate awareness campaigns would be very useful. It is observed that the demand for health and hygiene products by people belonging to different occupations does not significantly differ from the people working in the government or public sector jobs. Further, the people who lost their jobs exhibited significantly more demand for health and hygiene products than those receiving full salary. In addition, the demand for such products by the non‐earning members of a family has significantly increased compared to the multiple earning members of a family. This is quite surprising. This probably indicates that even though the pandemic has negatively affected the economies across the globe, the sale of products relating to health and hygiene has significantly increased. The companies selling products relating to health and hygiene should go all out in their efforts to advertise and increase their sales during such a crisis. Finally, there is an opportunity to introduce healthy substitutes of daily necessities in a market already occupied by established brands.

Given that emerging economies such as India, where this study was carried out, have a large share of the unorganised or informal sector (Murthy,  2019 ), our findings are indicative of the nature of the economic impact that the unorganised sector has experienced during this pandemic. Post‐COVID it would be essential for firms dealing with daily necessities to expand their product assortments to include cheaper alternatives. Emerging economies are further characterized by a smaller market for health and hygiene as well as the wellness and digital entertainment market (Sood,  2020 ). The study observed that it is lifestyle and health awareness that affect the demand for wellness and entertainment products, and hygiene products respectively. Hence, firms dealing with such products in emerging markets should realise that it is important to focus on market creation through lifestyle changes and health awareness in addition to regular promotions. The study also gives enough insights into the customer segments that could be targeted for such efforts.

8. CONCLUSION

In this paper, we have carried out a questionnaire survey to understand the impact of COVID‐19 on consumers' affordability, lifestyle, and health awareness and how these effects influenced their buying behaviour. Analysis of the survey data revealed several interesting facts about the impact of COVID‐19 and how the consumers behaved. Some of the major findings of this study include: (1) COVID‐19 affected the affordability of consumers employed in the unorganised sectors more than those who were employed in the organised sector, (2) Type of occupation, current employment status, and the earning potential of a family had a varying degree of impact on lifestyle changes undergone by consumers, and (3) the health awareness was significantly higher for consumers who lost their jobs or had lower family earning status. It was observed that the demand for wellness and entertainment products was not affected much by affordability but by lifestyle changes while the demand for health and hygiene products was more influenced by consumer awareness towards health. Affordability, on the other hand, influenced the demand for affordable substitutes of daily necessities. Therefore, this study and the findings would be very useful for studying the effects of disruptive events on the nature of the shift in consumption behaviour and substitution behaviour exhibited by consumers. Further, the findings of this study would help organizations formulate appropriate strategies to cope with the shift in consumption and substitution behaviour as a result of the pandemic.

The study is not free from certain limitations. The imposition of lockdown in different parts of India at different points of time made it very difficult for us to carry out the survey. Further given the diversity and the large geographical size of India, we could not reach out to all the diverse groups, communities, and cultures. Increasing reach possibly could have generated more insights into consumer behaviour and market segmentation. Moreover, our study was limited to wellness, entertainment, and health products as also the products of daily necessities. Therefore, extending this research to include more diversity in terms of the nature of products would be useful in further refinement of marketing strategies under disruption.

The observations of Paul and Bhukya ( 2021 ) encourage us to propose extension of the present research primarily along the following directions: (1) cross‐country studies for understanding how the pandemic‐induced disruptions have affected consumer behaviour across various social groups based on culture, region, and age, (2) studies on how organizations cope with such adaptations in consumers' needs during pandemic, and (3) studies focusing on understanding how and to what extent consumers' consumption shifts influence retailers' strategies related to product selection, channel choice, promotions, and discounts. It can also be expected that the choice of the above strategies would differ based on retailers' location, the scale of operations, and the target segments. A major influence on the Consumers' changing way of life during such pandemic‐induced disruptions includes government interventions in the form of schemes, aids, and subsidies. An important extension of the present research would be to understand how such interventions were able to mitigate the adverse impacts of the pandemic on consumers' life and at the same time maintain the sustainability of business organizations.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

ACKNOWLEDGEMENTS

Biographies.

Debadyuti Das is a Professor at the Faculty of Management Studies, Delhi University in the Operations Management Area. He received his Ph.D. from IIT BHU. He has a rich blend of experience in both industry and academics spanning over more than two and half decades. He has extensive experience in executive education and management development programs. His current areas of research include Sustainable Supply Chain Management, Managing Carbon Footprint in Supply Chain, Distribution Network Design in Public Health, Efficient Sourcing and Distribution of water etc.

Ashutosh Sarkar is an Associate Professor at the Indian Institute of Management Kozhikode in the Quantitative Methods & Operations Management Area. He received his Ph.D. from Indian Institute of Technology Kharagpur and was a Fulbright Visiting Scholar at the Naveen Jindal School of Management, University of Texas at Dallas. Earlier, Dr. Sarkar has served as a faculty member at IIT Kharagpur and Institute of Technology‐Banaras Hindu University (now IIT BHU). He has extensive experience in executive education and training. His areas of interests include Inventory and Supply Chain Optimization, Application of Stochastic Dynamic Programming in Operations Management Problems, Purchasing and Supply Chain Risk Management.

Arindam Debroy is an Assistant Professor at the Symbiosis Institute of Business Management Nagpur in the Operations Management Area. He received his Ph.D. from Indian Institute of Technology Kharagpur. He has also received the Institute Fellowship during his doctoral program at IIT Kharagpur. His areas of interests include Inventory and Logistics & Supply Chain Management, Purchase Management, and Project Management.

APPENDIX 1. DESCRIPTIVE STATISTICS OF FACTORS INFLUENCING CONSUMERS' CHANGING WAY OF LIFE

Appendix 2. descriptive statistics of adaptation in consumers' buying behaviour.

Das, D. , Sarkar, A. , & Debroy, A. (2022). Impact of COVID‐19 on changing consumer behaviour: Lessons from an emerging economy . International Journal of Consumer Studies , 46 , 692–715. 10.1111/ijcs.12786 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

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